	N	Dog Owners(n = 43)	Non dog owners(n = 43)

Match Characteristics

 Gender (N female, %)	43	27 (63%)	27 (63%)

 Age at start of study (years)	43	69.9 (± 4.1)	70.2 (± 4.1)

 Ethnicity (N White British)	43	43 (100%)	43 (100%)

 Cat ownership (N yes)	43	4 (9%)	4 (9%)

Townsend Index	43

 1 (least deprived)		11 (26%)	11 (26%)

 2		15 (35%)	15 (35%)

 3		12 (28%)	12 (28%)

 4		4 (9%)	4 (9%)

 5 (most deprived)		1 (2%)	1 (2%)

Other Characteristics

 Distance between homes (km)	42	12.8 [22.8]

 BMI (kg.m−2)	43	25.4 (± 4.3)	25.8 (± 3.7)

 Participants reporting a chronic health condition at start of study	38/41	14 (37%)	15 (37%)

 Self-reported continuous walking distance (km)	38/37	6.1 ± (2.2)	6.5 ± (2.6)

	N	Dog Owners(n = 43)	Non dog owners(n = 43)

Match Characteristics

Gender (N female, %)	43	27 (63%)	27 (63%)

Age at start of study (years)	43	69.9 (± 4.1)	70.2 (± 4.1)

Ethnicity (N White British)	43	43 (100%)	43 (100%)

Cat ownership (N yes)	43	4 (9%)	4 (9%)

Townsend Index	43

1 (least deprived)		11 (26%)	11 (26%)

2		15 (35%)	15 (35%)

3		12 (28%)	12 (28%)

4		4 (9%)	4 (9%)

5 (most deprived)		1 (2%)	1 (2%)

Other Characteristics

Distance between homes (km)	42	12.8 [22.8]

BMI (kg.m−2)	43	25.4 (± 4.3)	25.8 (± 3.7)

Participants reporting a chronic health condition at start of study	38/41	14 (37%)	15 (37%)

Self-reported continuous wal		6	6.5


FAK location	Parameter	Correlation co-efficient	p-value

Vessels	Patient age	0.096	0.246

 	Tumour size	0.089	0.28

Tumour cells	Patient age	-0.138	0.094

 	Tumour size	0.119	0.148


Parameters	DMFT index	H	Found p	p	Sig./N. sig.

Zn concentration, mmol/l (before stimulation)	<1	2.54	0.28	>0.05	N. sig.

1–6

>6

Zn concentration, mmol/l (after stimulation)	<1	3.56	0.16	>0.05	N. sig.

1–6

>6

Zn quantity, μmol/l (before stimulation)	<1	5.66	0.05	>0.05	N. sig.

1–6

>6

Zn quantity, μmol/l (after stimulation)	<1	7.99	0.01	<0.05	Sig.

Parameters	DMFT index	H	Found p	p	Sig./N. sig.

Zn concentration, mmol/l (after stimulation)	<1	3.56	0.16	>0.05	N. sig.

1–6

>6

Zn quantity, μmol/l (before stimulation)	<1	5.66	0.05	>0.05	N. sig.

1–6

>6

Zn quantity, μmol/l (after stimulation)	<1	7.99	0.01	<0.05	Sig.


Parameter	FS (n = 848)	FGLS (n = 1556)	Total (n = 2404)

Gestational age at birth

< 28 weeks	2 (0.2)	1 (0.1)	3 (0.1)


Experimental groups

Control

CDDP

EP

ECT

IR (3 Gy)

CDDP + IR (3 Gy)

EP + IR (3 Gy)

ECT + IR (3 Gy)

IR (5 Gy)

CDDP + IR (5 Gy)

EP + IR (5 Gy)

ECT + IR (5 Gy)


Risk	Kupelian	D'Amico	Pound

Low	85%	83%	94-82%

Intermediate	65%	50%	72%

High	32%	28%	54%


	Days of pseudopregnancy

Cell Types	1	2	3	4	5	6	7

Luminal epithelium	+	+	+	+/-	+/-	+/-	+/-

Glandular epithelium	+/-	+	+	+/-	+/-	+/-	+/-

Stromal cells	-	-	-	-	-	-	-


Database name	Organization	Remarks	Relevance to investigation interests

National Health and Nutrition Examination Survey (NHANES)	CDC	Section on “Hearing/audiometry (AUQ) for 1 year and over, 1999-2012 with component or lab tests conducted on original sample description. In 2013-2014, there was no component/lab test conducted.	Yes

National Health Interview Survey Occupational Health Supplement (NHIS-OHS)	CDC	Does not contain any audiometric topics.	No

Behavioral Risk Factor Surveillance System (BRFSS)	National Center for Chronic	Option to respond ‘hearing problem’ as the major impairment that limits activities 1998-2002, 2013; Veteran’s Status included, 2003-2008, 2010-2012	Yes

Disease Prevention and Health Promotion (NCCDPHP)

National Health Survey	CDC	Questions by family and individuals on hearing can derive some information about associations with the military, data available from 1997 onward. QOL is a supplemental (optional) component of the survey, available 2010-2012	Yes

Health and Retirement Study (HRS)	University of Michigan	Data from 1992-2014 on hearing status, employment, and QOL measures	Yes

Database name	Organization	Remarks	Relevance to investigation interests

National Health and Nutrition Examination Survey (NHANES)	CDC	Section on “Hearing/audiometry (AUQ) for 1 year and over, 1999-2012 with component or lab tests conducted on original sample description. In 2013-2014, there was no component/lab test conducted.	Yes

National Health Interview Survey Occupational Health Supplement (NHIS-OHS)	CDC	Does not contain any audiometric topics.	No

Behavioral Risk Factor Surveillance 	National Center for Chronic	Option to respond ‘hearing problem’ as the major impairment that lim	Y

Diseas

Database name	Organization	Remarks	Relevance to investigation interests

System (BRFSS)	e Prevention and Health Promotion (NCCDPHP)	its activities 1998-2002, 2013; Veteran’s Status included, 2003-2008, 2010-2012	es

National Health Survey	CDC	Questions by family and individuals on hearing can derive some information about associations with the military, data available from 1997 onward. QOL is a supplemental (optional) component of the survey, available 2010-2012	Yes

Health and Retirement Study (HRS)	University of Michigan	Data from 1992-2014 on hearing status, employment, and QOL measures	Yes


Genes	Forward primer (5′–3′)	Reverse primer (5′–3′)

m-PAX2	AAGCCCGGAGTGATTGGTG	CAGGCGAACATAGTCGGGTT

m-WT1	CAGTTCCCCAACCATTCCTT	AAGCTGGGAGGTCATTTGGT

m-Brachyury (Bry)	ACCCAGACTCGCCCAATTTT	GGAAAGCAGTGGCTGGTGAT

m-CD24	GTTGCACCGTTTCCCGGTAA	CCCCTCTGGTGGTAGCGTTA

m-Osr1	ATTCACCCTAAGCCAGAGATCA	AGGCCAGGTTAGCGAAATCAA

m-Six2	CTCACCACCACGCAAGTCAG	CTCGGAACTGCCTAGCACC

m-Sall1	CTCAACATTTCCAATCCGACCC	GGCATCCTTGCTCTTAGTGGG

m-E-cad	CTCCAGTCATAGGGAGCTGTC	TCTTCTGAGACCTGGGTACAC

m-AQP1	AGGCTTCAATTACCCACTGGA	GTGAGCACCGCTGATGTGA

m-PDGFR	CCACACCCTTGGGGAATAGT	TTTGAAGGGCAAGGAATGTG

m-GAPDH	ACTTCAACAGCAACTCCCACTC	TAGGCCCCTCCTGTTATTATGG

r-IL-10	TAACTGCACCCACTTCCCAGT	TGGCAACCCAAGTAACCCTTA

r-bFGF	CGACCCACACGTCAAACTAC	CCAGGCGTTCAAAGAAGAAA

r-TGF-β1	GCCCTGGATACCAACTACTGCT	GTTGGTTGTAGAGGGCAAGGAC

r-EGF	CGTCTCAGTGGTCATGGATTT	TCAGAAGAACACGGGAATTGT

r-HGF	CTCTCGTTCCTTGGGATTATTG	GATCCCCCACAGATGTGTTTAT

r-PDGF	ATCGAGCCAAGACACCTCAAAC	ATGGGGGCAGTACAGCAAATAC

r-GAPDH	AGTGCCAGCCTCGTCTCATAG	CGTTGAACTTGCCGTGGGTAG


Full sample

Sex

Age

Country [No. studies]

Weight status

Mother’s education


Locus no.	Putative identification	Avg fold difference

Mobile and extrachromosomal element functions: Transposon functions

PG0019	ISPg4 transposase	1.57

PG0050	ISPg4, transposase	1.81

PG0177	ISPg4, transposase	1.87

PG0194	ISPg3, transposase	2.18

PG0225	ISPg4, transposase	1.80

PG0261	ISPg3, transposase	2.20

PG0459	ISPg5, transposase	1.60

PG0487	ISPg4, transposase	1.98

PG0798	ISPg3, transposase	2.11

PG0819	Integrase	1.80

PG0838	Integrase	3.36

PG0841	Mobilizable transposon, excision protein, putative	3.78

PG0842	Mobilizable transposon, hypothetical protein, putative	2.84

PG0872	Mobilizable transposon, xis protein	3.87

PG0873	Mobilizable transposon, tnpC protein	9.34

PG0874	Mobilizable transposon, int protein	2.42

PG0875	Mobilizable transposon, tnpA protein	1.68

PG0970	ISPg4, transposase	1.79

PG1032	ISPg3, transposase	2.23

PG1061	ISPg6, transposase	2.03

PG1261	ISPg4, transposase	2.06

PG1262	ISPg3, transposase	2.11

PG1435	Integrase	2.77

PG1454	Integrase	1.88

PG1658	ISPg4, transposase	1.83

PG1673	ISPg4, transposase	1.77

PG2194	ISPg4, transposase	1.85

PG0461	ISPg7, transposase	−2.77

PG0277	ISPg2, transposase	−1.58

PG0865	ISPg2, transposase	−1.53

PG1746	ISPg2, transposase	−1.63

PG2176	ISPg2, transposase	−1.58

PG1350	ISPg2, transposase	−1.53

Locus no.	Putative identification

Mobile and extrachromosomal element functions: Transposon functions

PG0019	ISPg4 transposase

PG0050	ISPg4, transposase

PG0177	ISPg4, transposase

PG0194	ISPg3, transposase

PG0225	ISPg4, transposase

PG0261	ISPg3, transposase

PG0459	ISPg5, transposase

PG0487	ISPg4, transposase

PG0798	ISPg3, transposase

PG0819	Integrase

PG0838	Integrase

PG0841	Mobilizable transposon, excision protein, putative

PG0842	Mobilizable transposon, hypothetical protein, putative

PG0872	Mobilizable transposon, xis protein

PG0873	Mobilizable transposon, tnpC protein

PG0874	Mobilizable transposon, int protein

PG0875	Mobilizable transposon, tnpA protein

PG0970	ISPg4, transposase

PG1032	ISPg3, transposase

PG1061	ISPg6, transposase

PG1261	ISPg4, transposase

PG1262	ISPg3, transposase

PG1435	Integrase

PG1454	Integrase

PG1658	ISPg4, transposase

PG1673	ISPg4, transposase

PG2194	ISPg4, transposase

PG0461	ISPg7, transposase

PG0277	ISPg2, transposase

PG0865	ISPg2, transposase

PG1746	ISPg2, transposase

PG2176	ISPg2, transposase

PG1350	ISPg2, transposase


TCGA acronym	Cancer type	Paired samples	Unpaired tumor samples	Reference

BRCA	Breast invasive carcinoma	107	929	(3)

COAD	Colon adenocarcinoma	26	236	(1)

HNSC	Head/neck squamous cell carcinoma	38	384	(27)

KICH	Kidney chromophobe	21	41	https://tcga-data.nci.nih.gov/

KIRC	Kidney renal clear cell carcinoma	71	434	(4)

LUAD	Lung adenocarcinoma	57	431	(28)

LUSC	Lung squamous cell carcinoma	50	433	(2)

PRAD	Prostate adenocarcinoma	48	247	https://tcga-data.nci.nih.gov/

THCA	Thyroid carcinoma	58	439	https://tcga-data.nci.nih.gov/


Description	Number of features

Mean, range, interquartile range (x, y, z)	9

Moments: standard deviation, skew, kurtosis (x, y, z)	9

Histogram: bin counts of −2 to 1 z-scores (x, y, z)	12

Derivative of moments: mean, standard deviation, skew, kurtosis (x, y, z)	12

Mean of the squared norm	1

Sum of axial standard deviations	1

Pearson correlation coefficient, r (xy), r (xz), r (yz)	3

Mean cross products (raw and normalized), xy, xz, yz	6

Absolute mean of cross products (raw and normalized)	6

Power spectra: mean, standard deviation, skew, kurtosis (x, y, z)	12

Mean power in 0.5 Hz bins between 0 and 10 Hz (x, y, z)	60


Gene Ontology (GO) Name	Number of Genes Involve	Fold Change	Genes

Highly Expressed in Susceptible Group	Highly Expressed in Resistant Group

Negative regulation of transcription from RNA polymerase II promoter	21	2.0	ELK4, GATAD2A, KANK2, MNT, ARHGAP35, SMAD3, TAL1, CBX6, GFI1, HDAC4, NFATC2, RXRA, RUNX3, ZNF8	N4BP2L2, ANKRD2, BMP4, DUSP26, FOXH1, HSF4, IRF7

Ion transport	17	2.0	ATP7A, KCNA1, SLC39A10, TTYH3, TPCN1	ATP5E, ATP5I, FXYD1, CACNA2D4, CHRNA2, KCNK7, KCNJ15, SLC10A1, SLC22A17, SLC26A8

Protein phosphorylation	15	2.2	PDPK1, ATM, BCR, JAK3, SBK1, ACVR1B, EIF2AK3, HUNK, LMTK2, PRKCI, PDK4, RUNX3	DMPK, NTRK1, TEX14

Immunity	13	1.9	DDX3X, ETS1, JAK3, C3, ERAP1, LST1	CLEC4E, ISG15, S100A12, ZBP1, APOBEC3A, IRF7, PGLYRP1

Innate immunity	9	2.5	DDX3X, JAK3, C3	ISG15, S100A12, ZBP1, APOBEC3A, IRF7, PGLYRP1

Innate immune response	9	1.4	DDX3X, JAK3, APOBEC3A, F12	CLEC4E, S100A12, ZBP1, IRF7, PGLYRP1

RNA polymerase II regulatory region seq-specific DNA binding	9	2.9	GATAD2A, MNT, PRDM15, SMAD3, TAL1, RXRA, RUNX3, ZNF8	-

GTPase activation	9	3.4	AGAP1, ADAP1, BCR, ARHGAP23, ARHGAP35, TBC1D2B, TBC1D9, SIPA1L3	TBCD7

Peptidyl-serine phosphorylation	8	4.4	PDPK1, ATM, BCL2, RICTOR, EIF2AK3, LMTK2, PRKCI	DMPK

Rab GTPase binding	6	3.0	ERC1, RAB11FIP4, RAB29, TBC1D2B, TBC1D9	TBC1D7


Clinicopathological characteristic	Number (%)

Age, years

 Median	70

 Range	47–84

Sex

 Male	30 (85.7)

 Female	5 (14.3)

Smoking status

 Smoker	31 (88.6)

 Never-smoker	4 (11.4)

Histological subtype

 Pure SCLC	2 (5.7)

 Combined SCLC	11 (31.4)

 Pure LCNEC	8 (22.9)

 Combined LCNEC	14 (40.0)

Accompanied component in combined SCLC	Number (% in all combined SCLC)

 LCNEC	9 (81.8)

 Adenocarcinoma	4 (36.4)

 Squamous cell carcinoma	1 (9.1)

 Large cell carcinoma	2 (18.2)

Accompanied component in combined LCNEC	Number (% in all combined LCNEC)

 Adenocarcinoma	10 (71.4)

 Squamous cell carcinoma	6 (42.9)

 Large cell carcinoma	0 (0)


	RNA-Seq datasets comparison	number of DEGs

48 hai	96 hai

up	down	up	down

2Hb8	R NIL Fusarium inoculated – R NIL mock inoculated (R_F/M)	11	21	415	192

M69 Fusarium inoculated – M69 mock inoculated (M69_F/M)	45	167	1283	354

R NIL Fusarium inoculated – M69 Fusarium inoculated (R/M69_F)	350	80	321	426

R NIL mock inoculated – M69 mock inoculated (R/M69_M)	355	70	401	282

6Hb7	R NIL Fusarium inoculated – R NIL mock inoculated (R_F/M)	100	14	304	15

Lacey Fusarium inoculated – Lacey mock inoculated (Lacey_F/M)	12	53	693	227

R NIL Fusarium inoculated – Lacey Fusarium inoculated (R/Lacey_F)	66	36	5	10

R NIL mock inoculated – Lacey mock inoculated (R/Lacey_M)	12	89	4	19

	RNA-Seq datasets comparison	number of DEGs

48 hai

up

2Hb8	R NIL Fusarium inoculated – R NIL mock inoculated (R_F/M)	11

M69 Fusarium inoculated – M69 mock inoculated (M69_F/M)	45

R NIL Fusarium inoculated – M69 Fusarium inoculated (R/M69_F)	350

R NIL mock inoculated – M69 mock inoculated (R/M69_M)	355

6Hb7	R NIL Fusarium inoculated – R NIL mock inoculated (R_F/M)	100

Lacey Fusarium inoculated – Lacey mock inoculated (Lacey_F/M)	12

R NIL Fusarium inoculated – Lacey Fusarium inoculated (R/Lacey_F)	66

R NIL mock inoculated – Lacey mock inoculated (R/Lacey_M)	12


Study name	Treatment arms	Time horizon (weeks)	Relapses	AE-related disc's	Non-AE-related disc's	Completers	Total Nr of patients	Nr of patients experiencing >7% weight gain (total Nr of patients)	Nr of patients experiencing EPS (total Nr of patients)

Kane (42)	Haloperidol depota	52	17	1	18	44	80	NA	NA

	Placebob	52	15	0	2	8	25	NA	NA

Kane (41)	Olanzapine pamoatec	24	68	21	91	419	599	100 (599)	52 (599)

	Olanzapine oral	24	23	8	33	258	322	68 (322)	28 (322)

	Placebob	24	42	6	20	76	144	12 (144)	12 (144)

Hough 2010 (38)	Paliperidone palmitate	31	36	3	28	139	206	12 (206)	21 (206)

	Placebo	42	97	2	27	78	204	6 (204)	12 (204)

Kane (40)	Aripiprazole once-monthly	52	27	9	31	202	269	17 (269)	45 (269)

	Placebo	52	53	5	15	61	134	7 (134)	14 (134)

Fleischhacker (37)	Paliperidone palmitate	53	95	29	100	155	379	50 (346)	67 (379)

	Risperidone LAI	53	56	25	105	184	370	52 (338)	76 (370)

Fleischhacker (39)	Aripiprazole once-monthly	38	22	8	39	196	265	42 (265)	52 (265)

	Aripiprazole oral	38	21	7	60	178	266	43 (266)	46 (266)

	Placebob	38	29	7	34	61	131	8 (131)	18 (131)

Study name	Treatment arms	Time horizon (weeks)	Relapses	AE-related disc's	Non-AE-related disc's	Completers	Total Nr of patients	Nr of patients experiencing >7% weight gain (total Nr of patients)	Nr of patients experiencing EPS (total Nr of patients)

	Placebo	42	97	2	27	78	204	6 (204)	12 (204)

Kane (40)	Aripiprazole once-monthly	52	27	9	31	202	269	17 (269)	45 (269)

	Placebo	52	53	5	15	61	134	7 (134)	14 (134)

Fleischhacker (37)	Paliperidone palmitate	53	95	29	100	155	379	50 (346)	67 (379)

	Risperidone LAI	53	56	25	105	184	370	52 (338)	76 (370)

Fleischhacker (39)	Aripiprazole once-monthly	38	22	8	39	196	265	42 (265)	52 (265)

	Aripiprazole oral	38	21	7	60	178	266	43 (266)	46 (266)

	Placebob	38	29	7	34	61	131	8 (131)	18 (131)


Compound	RRI a	S. boveanum 	C. myrica	H. flagelliformis

Heptadecane	1698	-	-	4.1 ± 0.63

Tetradecanoic acid methyl ester	1718	8.1 ± 0.7	20.3 ± 3.5	8.2 ± 0.9

9-(Z)-Hexadecenoic acid methyl ester	1900	4.0 ± 1.2	54.6 ± 36.3	-

Hexadecanoic acid methyl ester	1922	58.2 ± 4.5	165.7 ± 23.7	95.9 ± 11.5

9,12-(Z,Z)-octadecadienoic acid methyl ester	2094	-	5.8 ± 1.8	-

9-(Z)-octadecenoic acid methyl ester	2101	8.4 ± 2.4	30.1 ± 10.6	8.1 ± 1.2

9-(E)-octadecenoic acid methyl ester	2107	-	16.1 ± 2.0	7.9 ± 1.03

Octadecanoic acid methyl ester	2120	3.6 ± 0.7	11.9 ± 1.5	4.6 ± 0.3

Compound	RRI a	S. boveanum	C. myrica	H. flagelliformis

9-(E)-octadecenoic acid methyl ester	2107	-	16.1 ± 2.0	7.9 ± 1.03

Octadecanoic acid methyl ester	2120	3.6 ± 0.7	11.9 ± 1.5	4.6 ± 0.3


Farm location	Goat breed	Feed type

Farm 1 (F1), Hulu Langat, Selangor	Saanen cross (SC)	Napier grass silageBarley sproutsDatesMulberry leavesCorn grainGoat pellet

Farm 2 (F2), Banting, Selangor	Saanen pure (SP)	Napier grass freshDairy bran

Farm 3 (F3), Hulu Langat, Selangor	Saanen pure (SP)	Napier grass freshGoat pellet 1Goat pellet 2

Farm 4 (F4), Sungai Buloh, Selangor	Saanen–Boer cross (SBC)	Napier grass freshGrower pelletBreeder pelletRice straw

Farm 5 (F5), Nilai, Negeri Sembilan	Jamnapari Koplo (JK)	Napier grass silageWide leavesSoy-bran mixture

Farm 6 (F6), Sungai Buloh, Selangor	Jamnapari Peranakan Etawa cross (JPEC)	Napier grass freshSoy wasteGoat pellet

Farm 7 (F7), Shah Alam, Selangor	Jamnapari–Toggenburg cross (JTC)	Napier grass freshMix grassesDairy bran

Farm 8 (F8), Jeram, Selangor	Jamnapari cross (JC)	Sarang Buaya grass (Ischaemum timorense Kunth)Mix bran

Farm location	Goat breed	Feed type

Farm 8 (F8), Jeram, Selangor	Jamnapari cross (JC)	Sarang Buaya grass (Ischaemum timorense Kunth)Mix bran


Study groups	N	Mean	SD	P-value

Live Demonstration	26	6.69	1.4	.864*

Procedural Video	23	6.78	2.1

Total	49	6.73	1.8

Study groups	N	Mean	SD	P-value

Procedural Video	23	6.78	2.1	.864*

Total	49	6.73	1.8


Resource	Connectivity Comments	Reference

BindingDB	Comprehensive ligand-target database, we now cross-reference selected patent extractions from this source	(43)

ChEMBL and UniChem	Inclusion of our target protein pointers and a ChEMBL look-up for our ligand entries loaded in UniChem	(2,44)

DrugBank	Target cross-references and chemical ontology connection via an API	(45)

ESTER	Alpha/beta hydrolase cross-references	(46)

GeneCards	Gene expression and functional data aggregator	(47)

GPCRDB	Specific pointers to their detailed features, curation of mutations, sequence display toolbox and residue numbering system	(48)

GUDMAP	Links to proteins involved in GenitoUrinary (GU) tract development	(49)

HGNC	Long standing and frequent interactions on target family nomenclature issues	(10)

IMGT/mAb-DB	Pointers to provenanced sequences for clinical antibodies, target interactions, display tools and residue numbering system	(50)

MEROPS	Feature details, classification, ligand mapping, other protease-specific issues	(7)

neXtProt	Data and features additional to Swiss-Prot, semantic mining technology	(51)

NURSA	Detailed NHR information including transcriptome mining functionality	(52)

Orphanet	Unique rare genetic disease curation and disease term connectivity	(53)

PubChem	Covering aspects of chemical curation, drug naming and our submitted structures. Plans for future peptide and BioAssay Links	(4,14)

UniProtKB	Maintenance of our own selectable cross-references to proteins with quantitative interactions	(5)

Wikipedia	Updating, adding new target and ligand links, including filling in ‘chemistry boxes’	(54)

Resource	Connectivity Comments	Reference

IMGT/mAb-DB	Pointers to provenanced sequences for clinical antibodies, target interactions, display tools and residue numbering system	(50)

MEROPS	Feature details, classification, ligand mapping, other protease-specific issues	(7)

neXtProt	Data and features additional to Swiss-Prot, semantic mining technology	(51)

NURSA	Detailed NHR information including transcriptome mining functionality	(52)

Orphanet	Unique rare genetic disease curation and disease term connectivity	(53)

PubChem	Covering aspects of chemical curation, drug naming and our submitted structures. Plans for future peptide and BioAssay Links	(4,14)

UniProtKB	Maintenance of our own selectable cross-references to proteins with quantitative interactions	(5)

Wikipedia	Updating, adding new target and ligand links, including filling in ‘chemistry boxes’	(54)


Multivariate Cox regression

Factor	P	HR	95% CI

			Lower	Upper

INSS Stage (1-3, 4S vs 4)	0.002	7.15	2.08	24.64

NB-hypo	0.007	2.73	1.31	5.69

Age (< 1y vs > 1y)	0.801

MYCN (normal vs amplified)	0.671

Multivariate Cox regression

Factor	P

INSS Stage (1-3, 4S vs 4)	0.002

NB-hypo	0.007

Age (< 1y vs > 1y)	0.801

MYCN (normal vs amplified)	0.671


(n = 593)	One-factor model	Two-factor model	Three-factor model

Sensation	Sensitivity	Pleasant	Unpleasant	Pleasant	Unpleasant	Buzz

Cough	0.27	−0.16	0.52	0.10	0.69	−0.18

Sick	0.15	0.05	0.82	−0.16	0.66	0.29

Nervous	0.17	−0.04	0.50	0.07	0.57	−0.03

Dizzy	−0.46	0.65	0.35	0.06	0.15	0.70

	−0	0	0.21	0.0		0.8

(n = 593)	One-factor model	Two-factor model	Three-factor model

Sensation	Sensitivity	Pleasant	Unpleasant	Pleasant	Unpleasant	Buzz

High	.59	.74		6	−0.03	1

Relaxed	−0.88	0.79	−0.35	0.73	−0.14	0.15

Good	−0.94	0.85	−0.31	0.97	0.00	0.06

RMSEA	0.20	0.05		0.01


Author (year) of published PCR assay	PCR target	PCR technique	Amplicon size (bp)	Zika virus lineage analytical	Zika virus lineage field	No. of human patients tested in studies	Sample types positive in field

Lanciotti et al. (2008)43	Zika virus prM/E,target 1	Hydrolysis probe	76	Asian, African	Asian	 > 200 (combined set)5,10,23,24,34,36,38,40–42,49,50	Serum, urine, amniotic fluid

Lanciotti et al. (2008)43	Zika virus E, target 2	Hydrolysis probe	76	Asian, African	Asian	 > 200 (combined set)5,10,23,24,34,36,38,40–42,49,50	Serum, urine, amniotic fluid

Faye et al. (2013)51	Zika virus NS5	Locked nucleic acid probe	102	Asian, African	African	3 (B Rockx, personal communication, February 2016)	Serum

Tappe et al. (2014)19	Zika virus NS3	Hydrolysis probe	94	Asian	Asian	519–22,25	Serum

Faye et al. (2008)52	Zika virus E	Conventional	364	African	Asian	 > 15 (combined set)53,54	Serum

Pyke et al. (2014)15	Zika virus NS1	Hydrolysis probe	65	Asian	Asian	155	Serum

Pyke et al. (2014)15	Zika virus E	Hydrolysis probe	71	Asian	Asian	155	Serum

Moureau et al. (2007)56	Flavivirus NS5	SYBR®-green-based	269–272	African	Asian	218,57	Serum, urine

Kuno et al. (1998)58	Flavivirus NS5	Conventional	1079	Asian, African	Asian	5159	Serum

Scaramozzino et al. (2001)60	Flavivirus NS5	Conventional (semi-nested)	220	African	Asian	155 (L Barzon, personal communication, February 2016)	Serum, urine

Maher-Sturgess et al. (2008)61	Flavivirus NS5	Conventional	800	African	Asian	115	Serum

Ayers et al. (2006)62	Flavivirus NS5	Conventional	863	–	Asian	117	Serum, urine, nasopharynx


Explanatory variable	OR	95%CI	P value

Presence of C allele in genotype at rs3173798 (Yes=1, No=0)	0.28	0.12–0.67	0.0043

Age (years)	0.97	0.93–1.02	0.27

Gender (female=1, male=0)	0.92	0.39–2.20	0.85

Pre-treatment BCVA (logMAR)	1.49	0.50–4.43	0.47

GLD (μm)	1	1.00–1.00	0.88

Explanatory variable	OR	95%CI	P value

GLD (μm)	1	1.00–1.00	0.88


	The GP and the patient are a well-functioning team (n = 270)

	OR	95% CI	p-value

Age

 16–39	1.30	0.63–2.71	0.471

 40–59a	1.00	–	–

 60+	0.90	0.36–2.24	0.816

Education

 Primary	0.56	0.19–1.69	0.306

 High school	1.69	0.77–3.70	0.192

 University 1–4 yearsa	1.00	–	–

 University 5 years +	0.53	0.25–1.13	0.101

Self-rated degree of CFS/ME

 Mild	0.66	0.32–1.35	0.250

 Moderatea	1.00	–	–

 Severe/very severe	0.38	0.14–0.99	0.047

GP duration

 0–2 yearsa	1.00	–	–

 3 years+	2.32	1.09–4.95	0.030

GP frequencyb

 0 visits	0.75	0.27–2.10	0.590

 1–4 visitsa	1.00	–	–

 5–9 visits	1.13	0.56–2.29	0.730

 10+ visits	2.12	0.75–5.99	0.155


Age group	Patients, no.	%

Infant	9	0

Child	12	0

Adolescent	4	0


Patient	Breed	Age	Sex	Activity	Laminitis Stage	Venography Stage	Prognosis (before Treatment)

CASE 1	QUARTER HORSE	18	F	MARE	BILATERAL ROTATION	4	POOR

CASE 2	QUARTER HORSE	14	F	MARE	BILATERAL CHRONIC ROTATION	4	POOR

CASE 3	THOROUGHBRED	13	G	PLEASURE	MONOLATERAL SINKING AND ROTATION	4	POOR

CASE 4	QUARTER HORSE	10	F	PLEASURE	MONOLATERAL SINKING	3	GUARDED PROGNOSIS

CASE 5	WARMBLOOD	18	G	PLEASURE	BILATERAL SINKING AND ROTATION	3	POOR

CASE 6	WARMBLOOD	15	F	PLEASURE	MONOLATERAL SINKING AND ROTATION	3	POOR

CASE 7	DUTCH WARMBLOOD	21	F	PLEASURE	BILATERAL SINKING AND ROTATION	3-4	POOR

CASE 8	THOROUGHBRED	15	G	PLEASURE	MONOLATERAL ROTATION	3	POOR

CASE 9	PONY	16	G	PLEASURE	BILATERAL SINKING AND ROTATION	4	POOR

Patient	Breed	Age	Sex	Activity	Laminitis Stage	Venography Stage	Prognosis (before Treatment)

CASE 7	DUTCH WARMBLOOD	21	F	PLEASURE	BILATERAL SINKING AND ROTATION	3-4	POOR

CASE 8	THOROUGHBRED	15	G	PLEASURE	MONOLATERAL ROTATION	3	POOR

CASE 9	PONY	16	G	PLEASURE	BILATERAL SINKING AND ROTATION	4	POOR


Scales	N	Mean	SD	Min.	Q1	Median	Q3	Max.	P-value


	Patients’ characteristics

Gender		Age

Females	n	66

Mean (SD)	62.8 (9.28)

95 % CI	60.5, 65.0

Median	63.2

Range	33–87

Males	n	85

Mean (SD)	63.3 (9.84)

95 % CI	61.2, 65.4

Median	62.9

Range	37–81

Total	n	151

Mean (SD)	63.1 (9.58)

95 % CI	61.5, 64.6

Median	62.9

Range	33–87


Clinical and epidemiological characteristic	Another malignancy	P

PostiodineN = 7 (46.66%)	PreiodineN = 8 (53.33%)

Males N (%)	4 (57.14)	3 (37.5)	0.6193

Age at thyroidectomy (years)*	61 ± 17	51 ± 13.7	0.2295

Follow-up period (months)**	75 (48; 336)	56.5 (20; 60)	0.1505

Age at diagnosis of a second neoplasia* (years)	69.4 ± 11.4	46.1 ± 20.2	0.0187

Classic nonpapilliferous histological type N (%)	3 (42.85)	2 (25)	0.6084


CONSENSUS CRITERIA FOR DEMENTIA CASE ASCERTAINMENT

PROBABLE DEMENTIA	POSSIBLE DEMENTIA

ANY of the following (without opposing evidence from same/other source):- dementia diagnosis on death certificate (any part)- dementia diagnosed on clinical review (ICD-10/DSM-IV)- dementia diagnosis in electronic general medical records (Trak)- dementia diagnosis in electronic psychiatric records (PIMS)- ICD-10 criteria for dementia diagnosis met by data within any existing records	ANY of the following (without opposing evidence from same/other source):- recorded cognitive impairment on death certificate- cognitive impairment/decline recorded in notes, but incomplete evidence to meet ICD-10 diagnostic criteria- possibility of dementia recorded in notes but no formal diagnosis/incomplete evidence to meet ICD-10 diagnostic criteria


(1) Memory	(2) Language	(3) Perceptual	(4) Visuospatial	(5) Calculation

Rey immediate recall	Semantic fluency 	VOSP X-detection	Barrage	Additions

Rey delayed recall	Phonological fluency	Benton	Spatial span	Subtractions

Recognition accuracy	Reading	Famous faces	H cancellation

 	Naming

(1) Memory	(2) Language	(3) Perceptual	(4) Visuospatial

Rey immediate recall	Semantic fluency	VOSP X-detection	Barrage

Rey delayed recall	Phonological fluency	Benton	Spatial span

Recognition accuracy	Reading	Famous faces	H cancellation

	Naming

(5) Calculation

Additions

Subtractions


Change in response variables	Explanatory variables

Dose of tofacitiniba	Lymphocyte sub-populations

T (CD3+)	TH(CD3+/CD4+)

CMV viral load, copies/500 ng total DNA	df	3	1	1

F value	1.26	0.14	0.04

p value	0.2926	0.7047	0.8411

EBV viral load, copies/500 ng total DNA	df	3	1	1

F value	0.50	0.54	1.69

p value	0.6807	0.4627	0.1955

CRP level, mg/L	df	3	1	1

F value	3.18	1.45	1.84

p value	0.0262	0.2315	0.1775


#	Nugget Topic	Nugget Content (3rd ed.)

6.	Pharmacological management of neuropathic pain	Use a step-wise evidence-based protocol for the management of neuropathic pain in SCI, and review pain management annually.

10.	Diet & fluid management in neurogenic bowel	Refer spinal cord injured patients with persistent constipation to a specialist with experience with SCI or neurogenic bowel.

11.	Screening of colorectal cancer	Initiate colorectal cancer screening for patients with SCI using the same principles as those for the general population.

13.	Recognizing Urinary Tract Infections in SCI Patients	Diagnosis of UTI in SCI patients requires 3 criteria: (1) significant bacteriuria; (2) pyuria; and (3) signs & symptoms.

14. 	Pharmacological management of UTI in SCI	There is no superior agent or class of antibiotics for UTIs in spinal cord injury. Recurrent UTIs should be treated as complicated infections, and treatment must be customized to the patient and the infecting organism.

15.	Screening for Bladder Cancer	Routine screening for bladder cancer is recommended only for high-risk patients; that is those with indwelling or suprapubic catheters, complete lesions, >10 years since injury, bladder stones, or recurrent urinary tract infections.

17.	Treatment of Skin Breakdown	Treat Stage I or II wounds with standard wound care. Treat Stage III or IV wounds with specialist/surgical intervention.

20.	Wheel chair accessibility of your practice	Conduct an accessibility audit of your office or clinic space and procedures using the Primary Care Accessibility Checklist.


CNTs	Hydroxyl Content % (w/w)	Carboxyl Content % (w/w)	Diameter (nm)	Length (μm)	SSA (m2/g)	PC Sets	PC Names

F1	_	_	10–20	30–100	>165	M	M1


Sample	Number of lethality (%)

Tribolium castaneum	Rhyzopertha dominica	Callosbruchus analis

Crude extract	0.33 ± 0.57	3.3 ± 5.7	0	0	0	0

Chloroform 	1.33 ± 0.57	13.3 ± 5.7	4.66 ± 0.57	46.6 ± 5.7	0	0

Ethyl acetate 	0.66 ± 0.57	6.6 ± 5.7	6.66 ± 1.15	66.6 ± 11.5	6.6 ± 5.7	66.6 ± 0

n-butanol 	0	0	0	0	0.66 ± 0.57	6.6 ± 5.7

Aqueous 	0	0	1.33 ± 0.57	13.3 ± 5.7	0	0

Permethrin (standard)	10 ± 0	100	10 ± 0	100	10 ± 0.01	100

Saline	0	0	0	0	0	0


Costa	Argentina	Brazil	Chile	Colombia	Ecuador	Mexico	Peru

< 1	Rivaroxavan	Rivaroxavan	Rivaroxavan	Rivaroxavan	–	Rivaroxavan	Rivaroxavan

1–4	Apixaban, Indacaterol, Linagliptin, Ticagrelor	Apixaban, Roflumilast, Ticagrelor	Apixaban, Indacaterol	Apixaban, Indacaterol	Indacaterol	–	–

5–9	–	Belatacept	–	–	–	Azilsartan, Linagliptin	–

10–19	–	–	Belimumab	–	–	Apixaban, Ticagrelor	–

20–39	Aflibercept, Regorafenib	Aflibercept	Aflibercept	Aflibercept	–	–	–

40–59	Belatacept, Tofacitinib	Belimumab	–	Tofacitinib	–	–	–

60–99	Telaprevir	–	–	–	–	–	–

100–149	–	Telaprevir	–	–	–	–	–

150–200	Pasireotide	Pertuzumab	–	–	–	Tofacitinib	–

201–896	Ipilimumab, Vandetanib	Ipilimumab, Vandetanib	Ipilimumab, Taliglucerase alfa	–	–	Pasireotide, Pertuzumab	–

Costa	Argentina	Brazil	Chile

< 1	Rivaroxavan	Rivaroxavan	Rivaroxavan

1–4	Apixaban, Indacaterol, Linagliptin, Ticagrelor	Apixaban, Roflumilast, Ticagrelor	Apixaban, Indacaterol

5–9	–	Belatacept	–

10–19	–	–	Belimumab

20–39	Aflibercept, Regorafenib	Aflibercept	Aflibercept

40–59	Belatacept, Tofacitinib	Belimumab	–

60–99	Telaprevir	–	–

100–149	–	Telaprevir	–

150–200	Pasireotide	Pertuzumab	–

201–896	Ipilimumab, Vandetanib	Ipilimumab, Vandetanib	Ipilimumab, Taliglucerase alfa

Colombia	Ecuador	Mexico	Peru

Rivaroxavan	–	Rivaroxavan	Rivaroxavan

Apixaban, Indacaterol	Indacaterol	–	–

–	–	Azilsartan, Linagliptin	–

–	–	Apixaban, Ticagrelor	–

Aflibercept	–	–	–

Tofacitinib	–	–	–

–	–	–	–

–	–	–	–

–	–	Tofacitinib	–

–	–	Pasireotide, Pertuzumab	–


Origin	Methods	Dysregulated miRNAs	Study Details

Aortic stenosis

Aortic valve leaflets [24]	Microarray qPCR	Downregulated: 26a, 30b, 195	9 patients with BAV (AS vs. aortic insufficiency requiring AVR)

Aortic valve leaflets [26]	qPCR	Downregulated: 30b	10 AS patients requiring AVR (calcific vs. adjacent tissue)

Aortic valve leaflets [27]	qPCR	Downregulated: 148a-3p 	4 BAVs vs. healthy aortic valves

Aortic valve leaflets [28]	Microarray qPCR	Upregulated: 125b Downregulated: 374b*, 602, 939	20 calcific AS valves vs. 6 control valves

Aortic valve leaflets [25]	Microarray qPCR	Upregulated: 151-3p, 152, 030e, 032, 145, 768-5p, 190, 373* Downregulated: 141, 370, 022, 1972, 330-5p, 566-pre, 1469, 1908, 648-pre, 637, 1282, 622, 486-3p, 187, 1909*, 564, 027a, 194*, 125b-1-pre, 551a-pre, 575, 585-pre, 211-pre, 449b*, 124-3-pre, 185-pre, 1202	19 BAVs vs. 17 TAVs from AS patients requiring AVR

LV intraoperative biopsies [29]	qPCR	Upregulated: 133a	46 AS patients requiring AVR

LV intraoperative biopsies [31]	qPCR	Upregulated: 21	75 AS patients requiring AVR vs. 32 surgical controls

LV intraoperative biopsies [32]	qPCR	Downregulated: 1	5 AS patients before TAVI vs. healthy controls

Endomyocardial biopsies [33]	Microarray qPCR	Downregulated: 18b, 122	28 AS patients with severe myocardial fibrosis vs. non-severe fibrosis

LV intraoperative biopsies [30]	qPCR	Upregulated: 133a	74 AS patients requiring AVR

Mitral valve disease

Tissues from the right and the left atrial appendages [37]	Microarray qPCR	Upregulated: 4484 Downregulated: 1, 23b-3p, 26a-5p, 30c-5p, 125b-5p, 133b, 143-3p, 145-5p, 4454	18 rheumatic mitral valve disease patients (10 AF vs. 8 SR) requiring mitral valve surgery

Tissues from the left atrial appendage [36]	Microarray qPCR	Upregulated: 466, 574-3p, 3613-3p Downregulated: 1, 26a-5p 	12 patients with mitral stenosis (6 SR, 6 AF) requiring mitral valve surgery

Mitral valve leaflets [38]	RNA-seq	Upregulated: 656, 379-3p, 664a-3p, 34c-3p 	10 patients with myxomatous mitral valve vs. 10 controls

Mitral valve leaflets [39]	whole genome miRNA qPCR	Upregulated: 500, 3174 Downregulated: 17, 203, 505, 646, 939, 1193, 1273e, 4298	10 myxomatous mitral valve prolapse vs. fibroelastic deficiency

Origin	Methods	Dysregulated miRNAs

Aortic stenosis

Aortic valve leaflets [24]	Microarray qPCR	Downregulated: 26a, 30b, 195

Aortic valve leaflets [26]	qPCR	Downregulated: 30b

Aortic valve leaflets [27]	qPCR	Downregulated: 148a-3p

Aortic valve leaflets [28]	Microarray qPCR	Upregulated: 125b Downregulated: 374b*, 602, 939

Aortic valve leaflets [25]	Microarray qPCR	Upregulated: 151-3p, 152, 030e, 032, 145, 768-5p, 190, 373* Downregulated: 141, 370, 022, 1972, 330-5p, 566-pre, 1469, 1908, 648-pre, 637, 1282, 622, 486-3p, 187, 1909*, 564, 027a, 194*, 125b-1-pre, 551a-pre, 575, 585-pre, 211-pre, 449b*, 124-3-pre, 185-pre, 1202

LV intraoperative biopsies [29]	qPCR	Upregulated: 133a

LV intraoperative biopsies [31]	qPCR	Upregulated: 21

LV intraoperative biopsies [32]	qPCR	Downregulated: 1

Endomyocardial biopsies [33]	Microarray qPCR	Downregulated: 18b, 122

LV intraoperative biopsies [30]	qPCR	Upregulated: 133a

Mitral valve disease

Tissues from the right and the left atrial appendages [37]	Microarray qPCR	Upregulated: 4484 Downregulated: 1, 23b-3p, 26a-5p, 30c-5p, 125b-5p, 133b, 143-3p, 145-5p, 4454

Tissues from the left atrial appendage [36]	Microarray qPCR	Upregulated: 466, 574-3p, 3613-3p Downregulated: 1, 26a-5p

Mitral valve leaflets [38]	RNA-seq	Upregulated: 656, 379-3p, 664a-3p, 34c-3p

Mitral valve leaflets [39]	whole genome miRNA qPCR	Upregulated: 500, 3174 Downregulated: 17, 203, 505, 646, 939, 1193, 1273e, 4298

Study Details

Aortic stenosis

9 patients with BAV (AS vs. aortic insufficiency requiring AVR)

10 AS patients requiring AVR (calcific vs. adjacent tissue)

4 BAVs vs. healthy aortic valves

20 calcific AS valves vs. 6 control valves

19 BAVs vs. 17 TAVs from AS patients requiring AVR

46 AS patients requiring AVR

75 AS patients requiring AVR vs. 32 surgical controls

5 AS patients before TAVI vs. healthy controls

28 AS patients with severe myocardial fibrosis vs. non-severe fibrosis

74 AS patients requiring AVR

Mitral valve disease

18 rheumatic mitral valve disease patients (10 AF vs. 8 SR) requiring mitral valve surgery

12 patients with mitral stenosis (6 SR, 6 AF) requiring mitral valve surgery

10 patients with myxomatous mitral valve vs. 10 controls

10 myxomatous mitral valve prolapse vs. fibroelastic deficiency


Variable	Base case value	Distribution	Parameters	Source/Notes

Probability of sustained virological response (SVR) in control group	0.02%	Beta	Alpha = 1 Beta = 559	Koretz et al.[23]

Log risk ratio (SVR: interferon versus no-intervention control)	2.9209 	Normal	Mean = 2.9209 Standard deviation = 1.0255	Koretz et al.[23] Note this yields a base case probability of SVR in the interferon group of 3.31%

5-year probability of death in no-intervention control group	6.72%	Beta	Alpha = 57 Beta = 791 	Koretz et al.[23] Annual probability therefore = 1.40% (= SRc in Table 2)

Log risk ratio (death: interferon versus no-intervention control)	0.3424 (0.1649)	Normal	Mean = 0.3424 Standard deviation = 0.1649	Koretz et al.[23] Note this yields a base case 5 year probability of death with interferon = 9.47%, annual probability = 2.01% = SRi in Table 2

Annual all-cause mortality by age	0.34% for 50 year male; 0.23% for 50 year female; 0.09% for 30 year male; 0.04% for 30 year female; 2.17% for 70 year old male; 1.41% for 70 year old female	Constant	Not applicable	Interim life tables (based on all reported deaths in the UK)[25], the sample size is assumed large enough for the standard error to be zero

Discount rate	3.50%	Constant	Not applicable	HM Treasury Green Book[26]

Variable	Base case value

Probability of sustained virological response (SVR) in control group	0.02%

Log risk ratio (SVR: interferon versus no-intervention control)	2.9209

5-year probability of death in no-intervention control group	6.72%

Log risk ratio (death: interferon versus no-intervention control)	0.3424 (0.1649)

Annual all-cause mortality by age	0.34% for 50 year male; 0.23% for 50 year female; 0.09% for 30 year male; 0.04% for 30 year female; 2.17% for 70 year old male; 1.41% for 70 year old female

Discount rate	3.50%

Distribution	Parameters	Source/Notes

Beta	Alpha = 1 Beta = 559	Koretz et al.[23]

Normal	Mean = 2.9209 Standard deviation = 1.0255	Koretz et al.[23] Note this yields a base case probability of SVR in the interferon group of 3.31%

Beta	Alpha = 57 Beta = 791	Koretz et al.[23] Annual probability therefore = 1.40% (= SRc in Table 2)

Normal	Mean = 0.3424 Standard deviation = 0.1649	Koretz et al.[23] Note this yields a base case 5 year probability of death with interferon = 9.47%, annual probability = 2.01% = SRi in Table 2

Constant	Not applicable	Interim life tables (based on all reported deaths in the UK)[25], the sample size is assumed large enough for the standard error to be zero

Constant	Not applicable	HM Treasury Green Book[26]


Tx-type; Cause of Death	< 12 months	> 12 months	p-value

Total: 278

SLTx (n = 97)

 Total number of deaths	17	51	0.158

 Death from Organ Rejection	2 (12%)	10 (20%)

 Death from Infection	4 (23%)	16 (31%)

 Death from Malignancy	1 (6%)	10 (20%)

 Death from Other Causes	10 (59%)	15 (29%)

DLTx (n = 172)

 Total number of deaths	16	47	0.388

 Death from Organ Rejection	4 (25%)	20 (42%)

 Death from Infection	4 (25%)	6 (13%)

 Death from Malignancy	1 (6%)	6 (13%)

 Death from Other Causes	7 (44%)	15 (32%)

HLTx (n = 9)

 Total number of deaths	1	4	0.576

 Death from Organ Rejection	0 (0%)	1 (25%)

 Death from Infection	0 (0%)	0 (0%)

 Death from Malignancy	0 (0%)	0 (0%)

 Death from Other Causes	1 (100%)	3 (75%)


Variable	Bivariate linear regression	Multivariate linear regression

Coefficient (95 % CI)	P-value	Coefficient (95 % CI)	P-value

Male gender	5.707 (2.887, 8.526)	<0.001	5.429 (2.517, 8.341)	<0.001

Age (in years)	0.988 (0.297, 1.679)	0.005	0.460 (−0.241, 1.160)	0.198

University educational program	0.716 (−2.252, 3.684)	0.636	-

Number of births managed during training	0.183 (0.074, 0.291)	0.001	0.164 (0.055, 0.273)	0.003

Felt classroom resources were available and helpful	−0.131 (−2.888, 2.626)	0.926	-

Felt number of instructors was adequate	2.191 (−0.565, 4.947)	0.119	2.428 (−0.529, 5.385)	0.107

Felt instructors were effective in facilitating learning	−2.469 (−5.217, 0.278)	0.078	−3.543 (−6.360, −0.726)	0.014

Felt instructors were fair and unbiased in assessing	−2.742 (−5.648, 0.164)	0.064	−2.794 (−5.710, 0.122)	0.060

Felt skills lab resources were available and helpful	3.593 (0.574, 6.612)	0.020	2.749 (−0.528, 6.025)	0.100

Felt number of skills lab assistants was adequate	2.835 (−0.171, 5.840)	0.064	2.239 (−1.043, 5.520)	0.181

Felt skills lab assistants supported students effectively	0.073 (−2.678, 2.824)	0.959	-

Felt number of preceptors was adequate	2.070 (−1.254, 5.395)	0.222	0.204 (−3.92, 4.321)	0.922

Felt clinical teachers and preceptors supported students	1.892 (−1.575, 5.359)	0.284	0.636 (−3.651, 4.923)	0.771

Felt clinical experience was sufficient	4.619 (1.915, 7.323)	0.001	4.650 (1.863, 7.437)	0.001

Variable	Bivariate linear regression	Multivariate linear regression

Coefficient (95 % CI)	P-value	Coefficient (95 % CI)	P-value

Felt number of skills lab assistants was adequate	2.835 (−0.171, 5.840)	0.064	2.239 (−1.043, 5.520)	0.181

Felt skills lab assistants supported students effectively	0.073 (−2.678, 2.824)	0.959	-

Felt number of preceptors was adequate	2.070 (−1.254, 5.395)	0.222	0.204 (−3.92, 4.321)	0.922

Felt clinical teachers and preceptors supported students	1.892 (−1.575, 5.359)	0.284	0.636 (−3.651, 4.923)	0.771

Felt clinical experience was sufficient	4.619 (1.915, 7.323)	0.001	4.650 (1.863, 7.437)	0.001


Growth year	Thickness/μm	Sheet name	Brix degree/%	Acid value/%	Peel color/a value

2004	30	unmulched	9.0 ± 0.3	0.68 ± 0.05	21.7 ± 1.0

MS-3,7,0	10.3 ± 0.2	0.74 ± 0.09	25.3 ± 1.4


Post Hoc Test (1 mL)	Age group (i)	Age Group (j)	Mean Difference (μi − μj)	95% Confidence Interval

Lower	Upper

Scheffé’s *	51–60	21–30	0.152	−0.077	0.381

51–60	31–50	0.334	0.118	0.551

21–30	31–50	0.183	−0.020	0.385

Post Hoc Test (1 mL)	Age group (i)	Age Group (j)	Mean Difference (μi − μj)	95% Confidence Interval

Lower	Upper

Scheffé’s *	21–30	31–50	0.183	−0.020	0.385


Variable	ALSPAC n (%)(N=6768)	Pelotas n (%)(N=3508)	χ2

Exposures


	Histopathological score

	Day 7	Day 21	Day 35


Systemic organ class and preferred terma	Total (N = 209)

Number of Subjects (%)	Number of Adverse Events

Resistance mechanism disorders

 Infection susceptibility increased	1 (0.48)	1

 Polyomavirus infection	1 (0.48)	1

Gastro-intestinal system disorders

 Diarrhoea	5 (2.39)	5

 Stomatitis	3 (1.44)	3

 Stomatitis ulcerative	1 (0.48)	1

 Abdominal pain	2 (0.96)	2

 Nausea	1 (0.48)	1

Urinary system disorders

 Azotaemia	6 (2.87)	6

 Albuminuria	1 (0.48)	1

 Oliguria	1 (0.48)	1

Skin and appendages disorders

 Acne	1 (0.48)	1

 Rash	1 (0.48)	1

 Rash erythematous	2 (0.96)	2

 Dermatitis	1 (0.48)	1

Metabolic and nutritional disorders

 Diabetes mellitus	1 (0.48)	1

 Diabetes mellitus aggravated	1 (0.48)	1

 Plasma osmolality increased	1 (0.48)	1

Body as a whole– general disorders

 Edema peripheral	1 (0.48)	1

 Face edema	2 (0.96)	2

 Anaphylactic reaction	1 (0.48)	1

Liver and biliary system disorders

 Hepatic function abnormal	1 (0.48)	1

 Cholangitis	1 (0.48)	1

Musculo-skeletal system disorders

 Avascular necrosis bone	1 (0.48)	1

Secondary terms – events

 Transplant rejection	2 (0.96)	2

Respiratory system disorders

 Coughing (≥ 4 weeks)	1 (0.48)	1

White cell and RES disorders

 Leucopenia	1 (0.48)	1

Systemic organ class and preferred terma	Total (N = 209)

Number of Subjects (%)

Resistance mechanism disorders

Infection susceptibility increased	1 (0.48)

Polyomavirus infection	1 (0.48)

Gastro-intestinal system disorders

Diarrhoea	5 (2.39)

Stomatitis	3 (1.44)

Stomatitis ulcerative	1 (0.48)

Abdominal pain	2 (0.96)

Nausea	1 (0.48)

Urinary system disorders

Azotaemia	6 (2.87)

Albuminuria	1 (0.48)

Oliguria	1 (0.48)

Skin and appendages disorders

Acne	1 (0.48)

Rash	1 (0.48)

Rash erythematous	2 (0.96)

Dermatitis	1 (0.48)

Metabolic and nutritional disorders

Diabetes mellitus	1 (0.48)

Diabetes mellitus aggravated	1 (0.48)

Plasma osmolality increased	1 (0.48)

Body as a whole– general disorders

Edema peripheral	1 (0.48)

Face edema	2 (0.96)

Anaphylactic reaction	1 (0.48)

Liver and biliary system disorders

Hepatic function abnormal	1 (0.48)

Cholangitis	1 (0.48)

Musculo-skeletal system disorders

Avascular necrosis bone	1 (0.48)

Secondary terms – events

Transplant rejection	2 (0.96)

Respiratory system disorders

Coughing (≥ 4 weeks)	1 (0.48)

White cell and RES disorders

Leucopenia	1 (0.48)

Total (N = 209)

Number of Adverse Events

Resistance mechanism disorders

1

1

Gastro-intestinal system disorders

5

3

1

2

1

Urinary system disorders

6

1

1

Skin and appendages disorders

1

1

2

1

Metabolic and nutritional disorders

1

1

1

Body as a whole– general disorders

1

2

1

Liver and biliary system disorders

1

1

Musculo-skeletal system disorders

1

Secondary terms – events

2

Respiratory system disorders

1

White cell and RES disorders

1


Variable	Category	IIR	Non- IIR	Total

n (%)	n (%)	n (%)

Age	≥ 35 years	31 (38.3)	31 (38.3)	62 (38.3)

Marital status	Married	74 (91.4)	72 (88.9)	146 (90.1)

Family type	Nuclear	38 (46.9)	47 (58)	85 (52.5)

Extended nuclear	13 (16)	10 (12.3)	23 (14.2)

Joint	30 (37)	24 (29.6)	54 (33.3)

Education	≥ Primary education	65 (80.2)	48 (59.2)	113 (69.7)

Literacy	Read and write	59 (72.8)	41 (50.6)	100 (61.7)

Household visit /week	Mean (±SD)	52 (±42)	42 (±68)	47 (±57)

Serving population	Mean (±SD)	255 (±134)	206 (±147)	231 (±142)

Focus group discussion held prior to join Mitanin program	Yes	54 (66.7)	60 (74.1)	114 (70.4)

Village meeting held prior to join Mitanin program	Yes	38 (33.3)	43 (53.1)	81 (50)

Prior work experience	Yes	14 (17.3)	09 (11.1)	23 (14.2)

Primary reason of join Mitanin program	Financial incentives	04 (4.9)	04 (4.9)	08 (4.9)

Opportunity to learn	07 (8.6)	06 (7.4)	13 (8)

Support village health facilities	23 (28.4)	13 (16)	36 (22.2)

Social prestige	01 (1.2)	01 (1.2)	02 (1.2)

Pressure from family and relatives	37 (45.7)	47 (58)	84 (51.9)

Other	9 (11.1)	10 (12.3)	19 (11.7)

Variable	Category	IIR	Non- IIR	Total

n (%)	n (%)	n (%)

Prior work experience	Yes	14 (17.3)	09 (11.1)	23 (14.2)

Primary reason of join Mitanin program	Financial incentives	04 (4.9)	04 (4.9)	08 (4.9)

Opportunity to learn	07 (8.6)	06 (7.4)	13 (8)

Support village health facilities	23 (28.4)	13 (16)	36 (22.2)

Social prestige	01 (1.2)	01 (1.2)	02 (1.2)

Pressure from family and relatives	37 (45.7)	47 (58)	84 (51.9)

Other	9 (11.1)	10 (12.3)	19 (11.7)


	Parent, N = 100/217	Child, N = 63/130

Missing values (1st–3rd quartiles)	No missing values	No missing values

Response pattern	PF and HRQoL positively skewed	PF and HRQoL positively skewed

Floor effect, median

 PF	92.0%	90.5%

 HRQoL PhH	60.0%	71.4%

 HRQoL PsH	66.0%	69.8%

 Pain VAS	47.0%	36.5%

 Disease activity VAS	39.0%	36.5%

 Well-being VAS	48.0%	50.8%

Ceiling effect, median

 PF	0.0%	0.0%

 HRQoL PhH	4.0%	1.6%

 HRQoL PsH	0.0%	0.0%

 Pain VAS	1.0%	0.0%

 Disease activity VAS	3.0%	1.6%

 Well-being VAS	0.0%	0.0%

Items with equivalent item-scale correlation	87% for PF, 90% for HRQoL	73% for PF, 90% for HRQoL

Items with items-scale correlation ≥ 0.4	87% for PF, 100% for HRQoL	67% for PF, 100% for HRQoL

Cronbach’s alpha

 PF-LL	0.82	0.84

 PF-HW	0.74	0.89

 PF-US	0.64	0.47

 HRQoL-PhH	0.86	0.86

 HRQoL-PsH	0.85	0.76

Items with item-scale correlation lower than the Cronbach alpha	93% for PF, 100% for HRQoL	100% for PF, 100% for HRQoL

Test–retest intraclass correlation

 PF total score	0.60	–

 HRQoL-PhH	0.62	–

 HRQoL-PsH	0.97	–

Spearman’s correlation with JIA core-set variables, median

 PF	0.4	0.4

 HRQoL PhH	0.4	0.4

 HRQoL PsH	0.3	0.2

 Pain VAS	0.2	0.3

 Disease activity VAS	0.3	0.4

 Well-being VAS	0.3	0.4

	Parent, N = 100/217	Child, N = 63/130

Missing values (1st–3rd quartiles)	No missing values	No missing values

Response pattern	PF and HRQoL positively skewed	PF and HRQoL positively skewed

Floor effect, median

PF	92.0%	90.5%

HRQoL PhH	60.0%	71.4%

HRQoL PsH	66.0%	69.8%

Pain VAS	47.0%	36.5%

Disease activity VAS	39.0%	36.5%

Well-being VAS	48.0%	50.8%

Ceiling effect, median

PF	0.0%	0.0%

HRQoL PhH	4.0%	1.6%

HRQoL PsH	0.0%	0.0%

Pain VAS	1.0%	0.0%

Disease activity VAS	3.0%	1.6%

Well-b	0	0.0%

	Parent, N = 100/217	Child, N = 63/130

eing VAS	.0%

Items with equivalent item-scale correlation	87% for PF, 90% for HRQoL	73% for PF, 90% for HRQoL

Items with items-scale correlation ≥ 0.4	87% for PF, 100% for HRQoL	67% for PF, 100% for HRQoL

Cronbach’s alpha

PF-LL	0.82	0.84

PF-HW	0.74	0.89

PF-US	0.64	0.47

HRQoL-PhH	0.86	0.86

HRQoL-PsH	0.85	0.76

Items with item-scale correlation lower than the Cronbach alpha	93% for PF, 100% for HRQoL	100% for PF, 100% for HRQoL

Test–retest intraclass correlation

PF total score	0.60	–

HRQoL-PhH	0.62	–

HRQoL-PsH	0.97	–

Spearman’s correlation with JIA core-set variables, median

PF	0.4	0.4

HRQoL PhH	0.4	0.4

HRQoL PsH	0.3	0.2

Pain VAS	0.2	0.3

Disease activity VAS	0.3	0.4

Well-being VAS	0.3	0.4


	n (%) of sites

	Dacron (N = 38b)	PTFE (N = 19b)	Any material (N = 57b)

Bleedinga at 0 min

“No bleeding”	34 (89)	19 (100)	53 (93)

“Oozing”	4 (11)	0 (0)	4 (7)

“No bleeding” or “oozing”	38 (100)	19 (100)	57 (100)

Bleedinga at 10 min

“No bleeding”	37 (97)	19 (100)	56 (98)

“Oozing”	1 (3)	0 (0)	1 (2)

“No bleeding” or “oozing”	38 (100)	19 (100)	57 (100)


5	.74184	.14837	.10979

C. Time 5 values calculated directly from time 0 populations and z values (Eq. (2))

5	.77844	.13275	.08881


Variable	N	%

Child’s gender

Male	232	48.54

Female	246	52.46

Child’s age (months)

12–35	186	38.91

36–59	292	61.09

Child’s skin color

White	379	79.29

Non-White	99	20.71

Household income

>1 BMW*	338	74.78

≤1 BMW*	114	25.22

Mother’s level of education

≥8 years	268	56.78

<8 years	204	43.22

Father’s level of education

≥8 years	247	55.38

<8 years	199	44.62

Does the child brush his/her teeth?

Yes	434	90.99

No	43	9.01

Children’s dental caries

dmft = 0	317	66.32

dmft ≥ 1	161	33.68

Children’s previous visit to the dentist

Yes	112	23.68

No	361	76.32

Reason for dental visit

Preventive	82	67.77

Others than preventive	39	32.23

Type of healthcare system

Private	45	36.89

Public	77	63.11

Variable	N	%

Father’s level of education

≥8 years	247	55.38

<8 years	199	44.62

Does the child brush his/her teeth?

Yes	434	90.99

No	43	9.01

Children’s dental caries

dmft = 0	317	66.32

dmft ≥ 1	161	33.68

Children’s previous visit to the dentist

Yes	112	23.68

No	361	76.32

Reason for dental visit

Preventive	82	67.77

Others than preventive	39	32.23

Type of healthcare system

Private	45	36.89

Public	77	63.11


Box D. Content validity (including face validity)

General requirements	yes	no	?

1	Was assessed if all items refer to relevant aspects of the construct to be measured?	□	□	□

2	Was assessed if all items are relevant for the study population? Considering e.g. age, gender, disease characteristics, country, setting	□	□	□

3	Was assessed if all items are relevant for the purpose of the application of the measurement instrument? i.e. (1) discriminative (distinguish between groups at one point in time), (2) evaluative (assess change over time), and/or (3) predictive (predict future values)	□	□	□

4	Was assessed if all items together comprehensively reflect the construct to be measured in terms of (1) content coverage and description of domains, and (2) the theoretical foundation?	□	□	□

5	Were there any important flaws in the design or methods of the study?	□	□

Box D. Content validity (including face validity)

General requirements	yes	no	?

1	Was assessed if all items refer to relevant aspects of the construct to be measured?	□	□	□

2	Was assessed if all items are relevant for the study population? Considering e.g. age, gender, disease characteristics, country, setting	□	□	□

	Was assessed if all items are relevant for the purpose of the application of the measurement instrument? i.e. (1) discriminative (distinguish between groups at one point in time), (2) evaluative (assess change over time), a	□	□	□

3	nd/or (3) predictive (predict future values)

4	Was assessed if all items together comprehensively reflect the construct to be measured in terms of (1) content coverage and description of domains, and (2) the theoretical foundation?	□	□	□

5	Were there any important flaws in the design or methods of the study?	□	□


	Single cellular RNA sample	Pooled RNA sample	Pooled DNA sample

TNF-α	95	95	100

β2-MG	90	90	100

MIF	88	88	100

UBC	81	80	100


	cn/cn	cn/+

Growth plates studied	# Histologic sections	Range of # of sections per growth plate	Growth plates studied	# Histologic sections	Range of # of sections per growth plate

Humerus	12	46	(1–9)	8	23	(2–5)

Femur	7	31	(1–7)	7	31	(2–11)

Tibia	7	40	(2–12)	9	30	(2–6)

	26	117		24	87

	cn/cn	cn/+

Growth plates studied	# Histologic sections	Range of # of sections per growth plate	Growth plates studied

Humerus	12	46	(1–9)	8

Femur	7	31	(1–7)	7

Tibia	7	40	(2–12)	9

	26	117		24

cn/+

# Histologic sections	Range of # of sections per growth plate

23	(2–5)

31	(2–11)

30	(2–6)

87


	Homicides (per 100,000)	DALY (thousands)

World	7.9	21,701,428

High income countries	2.7	886,297

Low–middle income countries	Africa	20.1	6,333,294

The Americas	24.1	6,024,751

Eastern Mediterranean	3.9	1,346,008

Europe	9.8	1,826,177

South-East Asia	5.8	3,444,677

Western Pacific	2.8	1,775,947

Guatemala (1)	61.3	175

El Salvador (2)	54.9	113

Côte d'Ivoire (3)	52.5	324

Brazil (13)	29.6	2488

South Africa (17)	27.3	1006

Russian Federation (39)	18.4	1276

Mexico (43)	17.9	415

Indonesia (76)	8.3	611

United States of America (93)	6.2	599


Gene	Fraction of est2∆ rad51∆ xxx∆ that are able to form survivors	Reference

in BY4741 backgrounda	in W303 background

YLR358C	1/5 (20%)	4/9 (44%)


	Parity

Measurements	0	1	2	3	4	5	6 or later

Number of serviced records	93,604	78,243	70,596	62,258	53,371	43,634	52,352

Number of first return records	11,458	8734	5625	4730	3772	2694	2614

First return occurrences, %	12.2	11.2	8.0	7.6	7.1	6.2	5.0

Number of second return records	2325	1324	834	695	490	297	290

Number of culled records after the second returna	246	142	87	105	68	55	49

Number of removed records after the second returnb	394	232	168	136	90	68	64

Number of SRB femalesc	532	235	145	104	70	34	38

SRB risk for first-served females, %	0.57	0.30	0.21	0.17	0.13	0.08	0.07


Kidney cancer dataset	CANOVA	Kendall	Pearson	Spearman	Hoeffding	Distance	MIC

Significant gene number	5901	11569	8239	11629	4953	10946	8081

Computing time (seconds)	24	65	32	32	44	~106	114


Article	Number (M/F)1	C/R/R-S2	Age Mean ± SD3/Median (range)	ST4	Cut-off	Rate(+)5	Follow up Mean ± SD/Median (range)	OM6	Surgery	MA7

	9(NR)	R	an: 64 (22–92)	aseline	3/7.5 ml	209	 NR(0.2-39.1)		NR	S

	3-5 W:115(NR) 6-12 W:134(NR)	NR	NR	During-treatment: 3-5 W,6-12 W11	≥3/7.5 ml	3-5 W: 17/115; 6-12 W: 10/134	NR	OS	NR	YES

Kuboki 2013 [14]	63(34/29)	41/22/0	Median: 61(33–81)	Baseline	≥3/7.5 ml	19/63	Median:8.7(NR)	OS; PFS	NR	YES

Deneve 2013 [13]	69(43/26)	66/8/1	Median: 75(38–95)	Baseline	≥1/7.5 ml	20/69	Mean:31 ± NR Median:36 (0–52)	NR	YES	NO

Sastre 2012 [28]	Baseline:180(118/62)	40/121/19	Median: 65(40–82)	Baseline	≥3/7.5 ml	85/180	NR	OS; PFS	123YES	YES

	Cycle3:147(NR)	NR	NR	Cycle3	≥3/7.5 ml	23/147	NR	OS; PFS	123YES	NO

Sato 2012 [29]	25(NR)	NR	NR	Baseline	≥3/7.5 ml	14/25	NR	OS	M1:NO12	NO

	25(NR)	NR	NR	Baseline	≥1/7.5 ml	18/25	NR	OS	M1:NO	NO

Papavasiliou 2010 [30]	20(13/7)	NR	Median: 54 (41–81)	Baseline During-treatment	≥3/7.5 ml	Pre:2/20 intra: 10/20; post: 1/18	Median:11.5 (5–25)	OS; PFS	YES	NO

Tol 2010 [31]	467 (284/183)	225/122/ 120	Median: 63(27–83)	Baseline	≥3/7.5 ml	Baseline: 129/451	Median: 16.8(NR)	OS; PFS	NR	YES

	1-2 W: 368(NR) 3-5 W:320(NR) 6-12 W:336(NR) 13-20 W: 254(NR)	NR	Median: 63(27–83)	During-treatment: 1-2/3-5/6-12/13-20 W	≥3/7.5 ml	1-2 W: 21/368; 3-5 W: 17/320; 6-12 W: 18/336; 13-20 W: 16/254	NR	OS; PFS	NR	YES

Hiraiwa 2008 [15]	40(NR)	NR	NR	Baseline + During-treatment	≥2/7.5 ml	14/40	NR	OS	YES	YES


Biomolecule	Molecular weight (kDa)	Isoelectric point	Charge	Hydrodynamic radius (Å)	Amount (μg)

AcSDKP peptide	0.4	5.5	Negative	7a	1000

Insulin	5.73	5.3	Negative	13	111

PEG-QK	11.27	9.4	Positive	36.9a,b,c	27

Lysozyme	14.3	11.35	Positive	19.1	1200 (transwell) 350 (release)

VEGF	45.5	9.22	Positive	30.2	7.5

BSA	66.4	4.7	Negative	36.3	1200


Delivery system	Diameter (mm)	Headspace (ml)	Milk-to-air interface (cm2)

Gerber (G)	52	176	21.23

Ventaire (V)	54	183	22.89

Dr. Brown's (DB)	50	66*	19.63

Elan (EL)	67	180	35.24*

BornFree (BF)	65	127*	33.17*

Playtex Drop-Ins (PD)	56	158	24.62*

Avent Natural (AN)	66	205	34.19*

Control	52	74*	20.42

Delivery system

Gerber (G)

Ventaire (V)

Dr. Brown's (DB)

Elan (EL)

BornFree (BF)

Playtex Drop-Ins (PD)

Avent Natural (AN)

Control


Dataset	Nematode hits 	Trematode hits 	Cestode hits

C. elegans proteins (Wormpep)	8457	345	280

S. mansoni proteins	3440	598	419

Human proteins	4539	408	326

NR protein database	10116	652	497

S. japonicum proteins	3456	612	416

Dataset	Nematode hits	Trematode hits	Cestode hits

C. elegans proteins (Wormpep)	8457	345	280

S. mansoni proteins	3440	598	419

Human proteins	4539	408	326

NR protein d	1011	652	497

atabase	6

S. japonicum proteins	3456	612	416


Variables		Frequency	Percent

Abdomen palpated to rule out the presence of second baby	Yes	331	62.7

No	197	37.3

Uterotonic drugs given	Oxytocin	432	81.8

Ergometrine	61	11.6

Misoprostol	30	5.7

Not given	5	0.9

Dose of uterotonic drugs given	0.5 mg	24	4.5

10 IU	486	96.6

0.5 mg	12	2.3

Others	6	1.1

Route of uterotonic drugs given	IM	519	97.2

IV	9	1.7

Oral	6	1.1

Wait uterine contraction 2–3 min to apply CCT	Yes	243	46

No	285	54

Wait gush of blood	Yes	283	53.6

No	245	46.4

Counter cord traction applied	Yes	472	89.4

No	56	10.6

Placenta supported by two hands during placenta delivery	Yes	421	79.7

No	107	20.3

Membrane extracted gently with lateral movement	Yes	293	55.5

No	235	44.5

Uterine massage immediately after delivery of placenta	Yes	227	43

No	301	57

Uterine relaxation ensured	Yes	161	30.5

No	367	69.5

Inform and demonstrate the mother massage uterus	Yes	196	37.1

No	332	62.9

Skill	Skilled	173	32.8

	Not skilled	355	67.2

Dose of uterotonic drugs given	Others	6	1.1

Route of uterotonic drugs given	IM	519	97.2

IV	9	1.7

Oral	6	1.1

Wait uterine contraction 2–3 min to apply CCT	Yes	243	46

No	285	54

Wait gush of blood	Yes	283	53.6

No	245	46.4

Counter cord traction applied	Yes	472	89.4

No	56	10.6

Placenta supported by two hands during placenta delivery	Yes	421	79.7

No	107	20.3

Membrane extracted gently with lateral movement	Yes	293	55.5

No	235	44.5

Uterine massage immediately after delivery of placenta	Yes	227	43

No	301	57

Uterine relaxation ensured	Yes	161	30.5

No	367	69.5

Inform and demonstrate the mother massage uterus	Yes	196	37.1

No	332	62.9

Skill	Skilled	173	32.8

	Not skilled	355	67.2


Cutoff	Results	African populationN (%)	Caucasian populationN (%)	p

AR ≥ 1%	Negative	22 (33.8)	22 (16.9)

Positive	43 (66.2)	108 (83.1)	0.008

AR ≥ 10%	Negative	25 (38.5)	27 (20.8)

Positive	40 (61.5)	103 (79.2)	0.009


Species	Title of publication	cDNAs used for reprogramming	Origin of cDNAs

Rhesus macaque (Macaca mulatta)	Generation of induced pluripotent stem cells from adult rhesus monkey fibroblasts [24]	POU5F1, SOX2 KLF4 and MYC 	Rhesus

Common marmoset (Callithrix jacchus)	Generation of induced pluripotent stem cells from newborn marmoset skin fibroblasts [25]	POU5F1, SOX2 KLF4 and MYC 	Human

Common marmoset (Callithrix jacchus)	Generating induced pluripotent stem cells from common marmoset (Callithrix jacchus) fetal liver cells using defined factors, including Lin28 [26]	POU5F1, SOX2, KLF4, MYC, NANOG and LIN28 	Human

Rhesus macaque (Macaca mulatta)	Reprogramming Huntington monkey skin cells into pluripotent stem cells [27]	POU5F1, SOX2 and KLF4 	Rhesus

Pigtailed macaque (Macaca nemestrina)	Efficient generation of nonhuman primate induced pluripotent stem cells [28]	POU5F1, SOX2 KLF4 and MYC 	Human

Cynomolgus monkey (Macaca fascicularis)	Development of histocompatible primate induced pluripotent stem cells for neural transplantation [29]	POU5F1, SOX2 KLF4 and MYC 	Human

Rhesus macaque (Macaca mulatta)	Generation of pancreatic insulin-producing cells from rhesus monkey induced pluripotent stem cells [30]	POU5F1, SOX2 KLF4 and MYC 	Rhesus

Pigtailed macaque (Macaca nemestrina)	Safeguarding nonhuman primate iPS cells with suicide genes [31]	POU5F1, SOX2 KLF4 and MYC 	Human

Drill (Mandrillus leucophaeus)	Induced pluripotent stem cells from highly endangered species [32]	POU5F1, SOX2 KLF4 and MYC 	Human

Cynomolgus monkey (Macaca fascicularis)	Induction of retinal pigment epithelial cells from monkey iPS cells [33]	POU5F1, SOX2 KLF4 and MYC 	Human


Age	Sex	Cause of death

60	F	Hemorrhagic stroke

56	F	Hemorrhagic stroke

25	M	Traumatic brain injury

40	F	Hemorrhagic stroke

50	F	Hemorrhagic stroke

28	M	Traumatic brain injury

43	F	Traumatic brain injury

20	M	Traumatic brain injury

58	F	Hemorrhagic stroke

20	M	Hypoxic brain injury

19	M	Traumatic brain injury

19	M	Traumatic brain injury

35	M	Hemorrhagic stroke

49	M	Hemorrhagic stroke

55	F	Hemorrhagic stroke

33	M	Traumatic brain injury

27	M	Traumatic brain injury

18	M	Traumatic brain injury

23	M	Traumatic brain injury

52	M	Hemorrhagic stroke

56	M	Hemorrhagic stroke

45	F	Hemorrhagic stroke

55	F	Hemorrhagic stroke


Predictor	B	SE	t

MEDIATOR—PERCEPTIONS OF INJUSTICE

Control: Negative affectivity	0.13	0.02	8.27***

Predictor: Observed incivility toward women	0.61	0.04	17.51***

Moderator: Observer gender	0.02	0.02	1.04

Interaction: Observed Incivility × Observer Gender	0.09	0.04	2.50*

OUTCOME—PERCEPTIONS OF SAFETY

Control: Negative affectivity	−0.19	0.03	−6.25***

Mediator: Perceptions of injustice	−0.14	0.05	−2.68**

Predictor: Observed incivility toward women	−0.07	0.07	0.85

Moderator: Observer gender	0.54	0.03	16.58***

Interaction: Observed incivility × Observer gender	0.13	0.07	1.94†

Direct and indirect effects	B	SE	95% CI

CONDITIONAL DIRECT EFFECTS ON PERCEPTIONS OF SAFETY

Men	−0.07	0.11	−0.15, 0.28

Women	−0.19*	0.08	−0.36, −0.02

CONDITIONAL INDIRECT EFFECTS ON PERCEPTIONS OF SAFETY

(THROUGH PERCEPTIONS OF INJUSTICE)

Men	−0.10	0.04	−0.14, −0.00

Women	−0.07	0.03	−0.18, −0.00

Index of moderated mediation	−0.02	0.02	−0.07, −0.00


Source	Patients	Inclusion criteria	Antioxidant agent	Dose	Route	Endpoints	Followup	Events

CHAOS [106]	2002	Angiographically demonstrated CAD	Vit E	400/800 IU	PO	CV death + MI; nonfatal MI	510 d	CV death: 27 vit E, 23 pl; nonfatal MI: 14 vit E, 41 pl

WHS [107]	39876	Healthy women	Vit E	600 IU q48 h	PO	Composite endpoint (CV death, MI, and stroke)	10.1 y	CV events: Vit E 482, pl 517; CV death: Vit E 106, pl 140; MI: Vit E 196, pl 195

SPACE [108]	196	Hemodialysis CV disease pts	Vit E	800 IU	PO	Composite endpoint (MI, ACS, PAD, and stroke)	519 d	Composite endpoint: Vit E 15, pl 33;CV death: vit E 9, pl 15; nonfatal MI: vit E 8, pl 18

Tepel et al. [109]	134	Hemodialysis CV disease pts	Acetylcysteine	1200 mg 	PO	Composite endpoint (CV death, MI, PTCA/CABG, PAD, and stroke)	14.5 m	Composite endpoint: acetylcysteine 18, pl 33

Milman et al. [110]	1434	Diabetes mellitus Hp 2-2 genotype	Vit E	400 IU	PO	Composite endpoint (CV death, MI, and stroke)	18 m	Composite endpoint: Vit E 16, pl 33

Source	Patients	Inclusion criteria	Antioxidant agent	Dose	Route	Endpoints	Followup	Events

CHAOS [106]	2002	Angiographically demonstrated CAD	Vit E	400/800 IU	PO	CV death + MI; nonfatal MI	510 d	CV death: 27 vit E, 23 pl; nonfatal MI: 14 vit E, 41 pl

WHS [107]	39876	Healthy women	Vit E	600 IU q48 h	PO	Composite endpoint (CV death, MI, and stroke)	10.1 y	CV events: Vit E 482, pl 517; CV death: Vit E 106, pl 140; MI: Vit E 196, pl 195

SPACE 	196	Hemod	Vit E	800 I		Composite endpoint 	519 d	Composite endpoint: Vit E 15, pl 33;CV death: vit E 9, pl 15; nonfatal MI: vit E 8, pl 18

Source	Patients	Inclusion criteria	Antioxidant agent	Dose	Route	Endpoints	Followup	Events

[108]		ialysis CV disease pts		U	PO	(MI, ACS, PAD, and stroke)

Tepel et al. [109]	134	Hemodialysis CV disease pts	Acetylcysteine	1200 mg	PO	Composite endpoint (CV death, MI, PTCA/CABG, PAD, and stroke)	14.5 m	Composite endpoint: acetylcysteine 18, pl 33

Milman et al. [110]	1434	Diabetes mellitus Hp 2-2 genotype	Vit E	400 IU	PO	Composite endpoint (CV death, MI, and stroke)	18 m	Composite endpoint: Vit E 16, pl 33


Language version ofsurvey	Responses

English	17785

Spanish	1052

French	955

Russian	330

Chinese	265

Japanese	258

Arabic	18

Total	20663


 	Correlation coefficient (r)	P value

Tissue estriol-tissue OxLDL	0.36	 0.004

Tissue estriol-GW	0.25	 >0.05

Tissue OxLDL-GW	0.04	 >0.05

Tissue estriol-infant's birth weight 	0.39	 0.002

Tissue estriol-systolic BP 	−0.44	0.001

Tissue estriol-diastolic BP 	−0.48	0.001


Variable	N	Median	Mean	SD

Programs offering residential treatment*

 Average daily client census	49	26.0	43.4	59.0

 Client occupancy ratio (%)†	49	87.7	86.2	0.1

 Average length of stay (days)	47	96.0	118.8	92.8

 Daily residential reimbursement ($)	38	183.00	200.92	99.72

 Quality Score#	78	15.0	14.6	1.6

Programs offering outpatient treatment*

 Average daily client census	59	20.0	39.7	57.1

 Client occupancy ratio (%)†	47	50.0	55.9	0.3

 Average treatment duration (days)	47	120.0	131.7	92.8

 Daily outpatient reimbursement ($)	26	50.50	55.73	26.47

 Quality Score#	93	15.0	14.3	1.9


Subject No.a	Sex (age)c	CD4 Count (cells/μl)	CD8 Count (cells/μl)	Plasma Viral Load (copies/ml)	HCVb	HBVb	HIV Subtype

1	M(4		1326	18	P


COX4 Expression	Hsp60 Expression	Total, N

-	+	++	+++

	1	15	5		3


MMCO Metrics	Metrics Detail	MMCO V2.0 (Existing Work) [6]	MMCO V3.0 (Extended Work)

Metrics	Axioms	793	1092

Logical Axioms	624	859

Class count	45	225

Object Property count	3	25

Individual count	114	157

DL Expressivity	ALCO	ALCHOF(D)

Asserted Triples	0	3312

Inferred Triples	0	6041

Class Axioms	SubClassOf	32	222

Equivalent Classes	9	17

Disjoint Classes	5	14

Individual Axioms	Class Assertion	360	58

Object Property Assertion	212	27

Data Property Assertion	0	1

Metrics	Asserted Triples	0	3312

Inferred Triples	0	6041

Class Axioms	SubClassOf	32	222

Equivalent Classes	9	17

Disjoint Classes	5	14

Individual Axioms	Class Assertion	360	58

Object Property Assertion	212	27

Data Property Assertion	0	1


Canagliflozin (300 mg q.d.) and cyclosporine A (400 mg q.d.)

Parameter	Arithmetic mean (SD)	Geometric meana

Canagliflozin alone (n = 18)	Canagliflozin + cyclosporine A (n = 17)	Canagliflozin alone (reference) (n = 17)	Canagliflozin + cyclosporine A (test) (n = 17)	Estimated ratio (test/reference), % (90% CI)

Cmax.ss (ng/mL)	2,887 (735)	2,923 (467)	2,864.03	2,887.13	100.81 (91.31; 111.30)

AUCτ.ss (ng×h/mL)	22,158 (4203)	27,819 (5267)	22,243.50	27,355.78	122.98 (118.66; 127.46)

tmax.ss (h)b	2.00 (1.00 – 3.00)	4.00 (1.50 – 6.00)	–	–	–


Factor	HR	95 % confidence interval	P value

Acute kidney injury 3	7.35	2.15–25.07	0.001

Peripheral vascular disease	1.95	1.12–3.39	0.019

Chronic renal failure	1.59	0.96–2.62	0.07

Diabetes mellitus	0.83	0.49–1.40	0.48

Female gender	0.47	0.28–0.80	0.005

Factor	HR	95 % confidence interval	P value

Peripheral vascular disease	1.95	1.12–3.39	0.019

Chronic renal failure	1.59	0.96–2.62	0.07

Diabetes mellitus	0.83	0.49–1.40	0.48

Female gender	0.47	0.28–0.80	0.005


	MIC (μg/mL)

Formulation	MS-Lac	Estimated Gentamicin in Microspheres *

MS-Lac1	2.16	0.31

MS-Lac2	2.92	0.31

MS-Lac3	4.00	0.31

MIC (μg/mL)

MS-Lac	Estimated Gentamicin in Microspheres *

2.16	0.31

2.92	0.31

4.00	0.31


Variable	Adjusted PR (95%CI)	p-valuea

Housing area

Urban	1

Rural	1.15 (1.0-1.3)	0.030

School type

Municipal	3.30 (1.1-9.4)	0.026

State	3.40 (1.1-9.6)	0.022

Particular	1

School education of mother

Illiterate or up to the 4th grade	1.67 (1.1-2.4)	0.005

High school	1.54 (1.0-2.2)	0.023

Completed college	1

Flossing

Yes/daily	0.97 (0.8-1.1)	0.703

Sometimes	0.80 (0.7-0.9)	0.003

Never	1


Variable	Patients (%)

Gender

 Male	74 (71.8)

 Female	29 (28.2)

Age (y)

 Mean	58.3

 Range	26–75

Tumor location

 EGJ	41 (39.8)

 Body	27 (26.2)

 Antrum	35 (34.0)

Treatment

 FOLFOX	19 (18.5)

 SOX	46 (44.7)

 XELOX	24 (23.3)

 XP	6 (5.8)

 Other	8 (7.7)

Clinical tumor stage

 II	33 (32.0)

 III	70 (68.0)

Tumor regression grade (TRG)

 1a	8 (7.8)

 1b	9 (8.7)

 2	23 (22.3)

 3	63 (61.2)

Variable	Patients (%)

Gender

Male	74 (71.8)

F	29


Patients	n = 3191

Age, years	70 ± 10

≤65 years, %	30

66-79 years, %	54

≥80 years, %	16

Gender, male vs. female, %	43 vs. 57

BMI, kg/m2	23 ± 3

SBP at entry, mmHg	147 ± 17

Uncontrolled SBP (≥140 mmHg) at entry, %	66

DBP at entry, mmHg	83 ± 11

Uncontrolled DBP (≥90 mmHg) at entry, %	37

Uncontrolled SBP and/or uncontrolled DBP at entry, %	68

Diabetes, %	32

Smoking, %	12

Drinking, %	14

Patients

Age, years

≤65 years, %

66-79 years, %

≥80 years, %

Gender, male vs. female, %

BMI, kg/m2

SBP at entry, mmHg

Uncontrolled SBP (≥140 mmHg) at entry, %

DBP at entry, mmHg

Uncontrolled DBP (≥90 mmHg) at entry, %

Uncontrolled SBP and/or uncontrolled DBP at entry, %

Diabetes, %

Smoking, %

Drinking, %


 	Progression-free survival	Overall survival

AUC (95% CIs)	0.71 (0.57–0.83)	0.65 (0.50–0.78)

Criterion (cut-off)	≥19%	≥13%

Sensitivity	73%	58%

Specificity	77%	70%

p value	0.0054	0.057

	Progression-free survival

AUC (95% CIs)	0.71 (0.57–0.83)

Criterion (cut-off)	≥19%

Sensitivity	73%

Specificity	77%

p value	0.0054


Patient characteristics	Value

Age (years), median (IQR)	38.0 (29.0–43.0)

Sex, n (%)

 Female	13 (68.4)

 Male	6 (31.6)

Race, n (%)

 White	19 (100)

Main comorbidities, n (%)a

 Hypertension	3 (15.8)

 Asthma	2 (10.5)

 Hypercholesterolaemia	2 (10.5)

Major features for TSC diagnosis, n (%)a

 Renal AML	19 (100)

 Facial angiofibromas/forehead plaque	15 (79.0)

 Cortical tuber	10 (52.6)

 Hypomelanotic macules (≥3)	7 (36.8)

 Subependymal nodule	7 (36.8)

 Non-traumatic ungual/periungual fibroma	4 (21.1)

 Single/multiple cardiac rhabdomyoma	4 (21.1)

 Lymphangiomyomatosis	3 (15.8)

 Connective tissue nevus	2 (10.5)

Minor features for TSC diagnosis, n (%)a

 Multiple renal cysts	11 (57.9)

 Multiple randomly distributed pits in dental enamel	3 (15.8)

 Bone cysts	3 (15.8)

 Non-renal hamartoma	2 (10.5)

 “Confetti” skin lesions	1 (5.26)

Sum of volumes of target renal AML lesions (cm3), median (IQR)	260.0 (127.8–322.2)

Volume of right kidney (cm3), median (IQR)	329.4 (193.0–979.7)b

Volume of left kidney (cm3), median (IQR)	299.0 (184.2–404.7)c


	Inpatient hospital contact (1987–2012)

	No bereavement	Bereavement

	N	Crude IR (100,000 PYs)	N

Any STI	5903	17.00	1188

Condyloma a	2833	8.14	700

Gonorrhea	123	0.35	33

Chlamydia	952	2.74	136

Syphilis	65	0.19	20

GHS	1946	5.59	302

Acute salpingitis	11361	32.60	3540

HIV	120	0.34	96

HBV	435	1.25	161


No.	IUPAC Name

BDE-209	Deca-bromodiphenyl ether

BDE-208	2,2',3,3',4,5,5',6, 6'- nona-bromodiphenyl ether

BDE-207	2,2',3,3',4,4',5,6,6'-nona-bromodiphenyl ether

BDE-206	2,2',3,3',4,4',5,5',6-nona-bromodiphenyl ether

BDE-203	2,2',3,4,4',5,5',6-octa-bromodiphenyl ether

BDE-196	2,2',3,3',4,4',5,6'-octa-bromodiphenyl ether

BDE-190	2,3,3',4,4',5,6-hepta-bromodiphenyl ether

BDE-183	2,2',3,4,4',5',6-hepta-bromodiphenyl ether

BDE-181	2,2',3,4,4',5,6-hepta-bromodiphenyl ether

BDE-155	2,2',4,4',6,6'-hexa-bromodiphenyl ether

BDE-154	2,2',4,4',5,6'-hexa-bromodiphenyl ether

BDE-153	2,2',4,4',5,5'-hexa-bromodiphenyl ether

BDE-139	2,2',3,4,4',6-hexa-bromodiphenyl ether

BDE-138	2,2',3,4,4',5'-hexa-bromodiphenyl ether

BDE-100	2,2',4,4',6-penta-bromodiphenyl ether

BDE-99	2,2',4,4',5-penta-bromodiphenyl ether

BDE-85	2,2',3,4,4'-penta-bromodiphenyl ether

BDE-77	3,3',4,4'-tetra-bromodiphenyl ether

BDE-47	2,2',4,4'-tetra-bromodiphenyl ether

BDE-28	2,4,4'-Tri-bromodiphenyl ether

IUPAC Name

Deca-bromodiphenyl ether

2,2',3,3',4,5,5',6, 6'- nona-bromodiphenyl ether

2,2',3,3',4,4',5,6,6'-nona-bromodiphenyl ether

2,2',3,3',4,4',5,5',6-nona-bromodiphenyl ether

2,2',3,4,4',5,5',6-octa-bromodiphenyl ether

2,2',3,3',4,4',5,6'-octa-bromodiphenyl ether

2,3,3',4,4',5,6-hepta-bromodiphenyl ether

2,2',3,4,4',5',6-hepta-bromodiphenyl ether

2,2',3,4,4',5,6-hepta-bromodiphenyl ether

2,2',4,4',6,6'-hexa-bromodiphenyl ether

2,2',4,4',5,6'-hexa-bromodiphenyl ether

2,2',4,4',5,5'-hexa-bromodiphenyl ether

2,2',3,4,4',6-hexa-bromodiphenyl ether

2,2',3,4,4',5'-hexa-bromodiphenyl ether

2,2',4,4',6-penta-bromodiphenyl ether

2,2',4,4',5-penta-bromodiphenyl ether

2,2',3,4,4'-penta-bromodiphenyl ether

3,3',4,4'-tetra-bromodiphenyl ether

2,2',4,4'-tetra-bromodiphenyl ether

2,4,4'-Tri-bromodiphenyl ether


	Appearance

Rich looking/smart/elegant	Liked the colors

Different	Simple/neat

Looks cold/refreshing/clean	Eye-catching/bold

Bright	Attractive

Happy	Modern and up-to-date

Ordinary	Plain

Similar to others	Cheap looking

Dull/drab	Unattractive

Messy/chopped up/gaudy/cluttered

	Functionality

Was easier to open	Did a better job keeping tobacco out of your pocket or purse

Was easier to close	Did a better job of keeping cigarettes from spilling out

Protected the cigarettes better	Did a better job of keeping cigarettes fresh

Was more pleasing to look at	Did a better job of keeping cigarettes from being crushed

Felt more comfortable in your hand	Was more different from other cigarette packages

Fit better in your pocket or purse

	Appearance

	/neat

Looks cold/refreshing/clean	Eye-catching/bold

Bright	Attractive

Happy	Modern and up-to-date

Ordinary	Plain

Similar to others	Cheap looking

Dull/drab	Unattractive

Messy/chopped up/gaudy/cluttered

	Functionality

Was easier to open	Did a better job keeping tobacco out of your pocket or purse

Was easier to close	Did a better job of keeping cigarettes from spilling out

Protected the cigarettes better	Did a better job of keeping cigarettes fresh

Was more pleasing to look at	Did a better job of keeping cigarettes from being crushed

Felt more comfortable in your hand	Was more different from other cigarette packages

Fit better in your pocket or purse


	Prior to 1:1 matching	After 1:1 matching*

Variables	Vulvar cancer patients	Controls	P-value*	Vulvar cancer patients	Controls	P-value*

N	505	569,648		505	505


	Arm A IRI+LV+5FU	Arm B LV+5FU	P (log-rank)

Disease-free survival (DFS)			0.436

 Progressions, n (%)	110 (24.9)	112 (25.9)

 Median (months)	Not reached yet	Not reached yet

 three-year DFS (%)	78	76

 five-year DFS (%)	70	68

 seven-year DFS (%)	66	63

Overall survival (OS)			0.334

 Deaths, n (%)	118 (26.8)	128 (29.6)

 Median (months)	Not reached yet	Not reached yet

 three-year OS (%)	88	86

 five-year OS (%)	78	76

 seven-year OS (%)	72	69

	Arm A IRI+LV+5FU	Arm B LV+5FU

Disease-free survival (DFS)

Progressions, n (%)	110 (24.9)	112 (25.9)

Median (months)	Not reached yet	Not reached yet

three-year DFS (%)	78	76

five-year DFS (%)	70	68

seven-year DFS (%)	66	63

Overall survival (OS)

Deaths, n (%)	118 (26.8)	128 (29.6)

Median (months)	Not reached yet	Not reached yet

three-year OS (%)	88	86

five-year OS (%)	78	76

seven-year OS (%)	72	69


Deliveries in six months	Total number %	Without malformation number %	With malformation number %

Ayder referral hospital	503**	33	484	32	19	3.8

Mekelle hospital	1013**	67	1000	66	13	1.3

Males	684	45	662*	44	22*	3.2

Females	832	55	822	54	10	1.2

LBW	822	54	800	97	22	2.7

LBW Male	374	25	362	97	12	3.2

LBW Female	448	30	438	98	10	2.2

VLBW	530	35	515	97	15	2.8

VLBW Male	243	16	238	98	5	2.1

VLBW Female	287	19	277	97	10	3.5

Total deliveries	1516	100	1484	98	32	2.1

Deliveries in six months	Total number %	Without malformation number %	With malformation number %

LBW Female	448	30	438	98	10	2.2

VLBW	530	35	515	97	15	2.8

VLBW Male	243	16	238	98	5	2.1

VLBW Female	287	19	277	97	10	3.5

Total deliveries	1516	100	1484	98	32	2.1


Chemotherapy cycles

>4 cycles

EBRT dose

Dose to point A

No UV brachytherapy

Total dose to point A


Characteristics	Unstandardized Coefficients	Standardized Coefficients	t	Sig.

B	Std. Error	Beta


Author	Year	Population	Sample size	Method	Cut-off	miRNA	Survival analysis	Source of HR	Follow-up (month)

Luo	2015	China	88	qRT-PCR	Median	miR-26b	OS, RFS	Reported	mean 74 (5.12-98.5)

Safari	2015	Iran	40	qRT-PCR	Median	miR-20a	OS	DE	100

						miR-10a	OS	DE

Wang C	2015	China	138	qRT-PCR	Median	miR-335	OS, RFS	Reported, DE	Mean 71(23-117)

Wang Q	2015	China	114	qRT-PCR	Median	miR-145	OS	Reported	median 47(11-69)

He	2014	China	73	qRT-PCR	ROC curve	miR-107	OS, DFS	DE	median 68.4

						miR-130a	OS, DFS	DE

Liang	2014	China	335	qRT-PCR	X-tile algorithm	miR-215	DFS	Reported	60

Ma	2014	China	60	qRT-PCR	ROC curve	miR-205	OS	Reported	60

Park	2014	Korea	45	qRT-PCR	2.5-fold	miR-363-3p	OS	Reported	60

Wang	2014	China	54	qRT-PCR	Median	miR-31	OS	Reported	60

Yang	2014	China	133	qRT-PCR	Median	miR-126	OS	Reported	60

Luo	2013	China	60	qRT-PCR	Mean	miR-497	OS, DFS	Reported, DE	60

Shen	2013	China	126	qRT-PCR	Median	miR-224	OS	DE	median 51.9

Huang	2012	China	44	qRT-PCR	Mean	miR-125b	OS	Reported	mean 23.6 (2-70)

						miR-100	OS	Reported

						miR-143	OS	DE

						miR-145	OS	DE

						miR-199a-5p	OS	DE

Author	Year	Population	Sample size	Method	Cut-off	miRNA	Survival analysis	Source of HR

Luo	2015	China	88	qRT-PCR	Median	miR-26b	OS, RFS	Reported

Safari	2015	Iran	40	qRT-PCR	Median	miR-20a	OS	DE

						miR-10a	OS	DE

Wang C	2015	China	138	qRT-PCR	Median	miR-335	OS, RFS	Reported, DE

Wang Q	2015	China	114	qRT-PCR	Median	miR-145	OS	Reported

He	2014	China	73	qRT-PCR	ROC curve	miR-107	OS, DFS	DE

						miR-130a	OS, DFS	DE

Liang	2014	China	335	qRT-PCR	X-tile algorithm	miR-215	DFS	Reported

Ma	2014	China	60	qRT-PCR	ROC curve	miR-205	OS	Reported

Park	2014	Korea	45	qRT-PCR	2.5-fold	miR-363-3p	OS	Reported

Wang	2014	China	54	qRT-PCR	Median	miR-31	OS	Reported

Yang	2014	China	133	qRT-PCR	Median	miR-126	OS	Reported

Luo	2013	China	60	qRT-PCR	Mean	miR-497	OS, DFS	Reported, DE

Shen	2013	China	126	qRT-PCR	Median	miR-224	OS	DE

Huang	2012	China	44	qRT-PCR	Mean	miR-125b	OS	Reported

						miR-100	OS	Reported

						miR-143	OS	DE

						miR-145	OS	DE

						miR-199a-5p	OS	DE


 	Mean (±SD) nuclear gray level

Normal urothelium (NU), global	106±15

NU, superficial epithelial layer	104±15

NU, intermediate cell layers	106±15

NU, basal cell layer	108±14

Urothelial carcinoma (UC), global	100±15

UC, nuclei not adjacent to the stroma	101±15

UC, nuclei adjacent to the stroma	99±16


Study Authors	Best Model/Main Finding	Subsequent Criticisms

Hubbell (2001)	ZSM	Goodness of fit only determined by graphical observation.

McGill (2003)	ZSM does not fit the data better than the lognormal	Used simulations to fit the ZSM

Volkov et al. (2003)	Derived an analytical solution for the ZSM and found the ZSM provided the best fit	Analytical equations did not represent the full solution as they applied solely to the mean number of species in a given class (Etienne and Olff 2004)

Vallade and Houchmandzadeh (2003)	Published a full analytical solution for the ZSM	Equations were later determined to be flawed (i.e., they applied the mean number of species in a given class) and were corrected by Etienne and Alonso (2005)

Alonso and McKane (2004)	Developed a different analytic solution	Rigorous fitting of the ZSM required likelihood methods

Etienne and Olff (2004)	Found slightly better support for the lognormal using a Bayesian approach

Etienne (2005)	Published the correct analytical solution and sampling formula. Two forms of the likelihood equations exist: (a) Ewens’ (1972) sampling formula of neutral alleles is used in the case of no dispersal limitation and (b) Etienne's (2005) formula in cases of dispersal limitation

Etienne and Alonso (2005)	Unified two different approaches to arrive at the full analytical solution: the genealogical approach (Etienne 2005) and master equation-based approach (e.g., Alonso and McKane 2004)

McGill et al. (2006)	Compared nine goodness-of-fit measures with the BCI data and found that for eight out of the nine measures the lognormal outperformed the ZSM

Jabot and Chave (2011)	Built on Etienne's (2005) maximum likelihood framework to develop a more robust test of neutrality incorporating the SAD of Hubbell's SINM and Shannon's index. The SAD of the BCI 50-ha plot did not significantly differ from neutrality; however, the SADs of smaller scale subplots from within the BCI plot were significantly non-neutral

Rosindell and Cornell (2013)	(a) The gamma and negative binomial distributions provided a better fit than the ZSM (b) The SENM predicts SADs which are more realistic than those from the SINM

Study Authors	Best Model/Main Finding	Subsequent Criticisms

Hubbell (2001)	ZSM	Goodness of fit only determined by graphical observation.

McGil	ZS	Used simulations to fit the

Study Authors	Best Model/Main Finding	Subsequent Criticisms

l (2003)	M does not fit the data better than the lognormal	ZSM

Volkov et al. (2003)	Derived an analytical solution for the ZSM and found the ZSM provided the best fit	Analytical equations did not represent the full solution as they applied solely to the mean number of species in a given class (Etienne and Olff 2004)

Vallade and Houchmandzadeh (2003)	Published a full analytical solution for the ZSM	Equations were later determined to be flawed (i.e., they applied the mean number of species in a given class) and were corrected by Etienne and Alonso (2005)

Alonso and McKane (2004)	Developed a different analytic solution	Rigorous fitting of the ZSM required likelihood methods

Etienne and Olff (2004)	Found slightly better support for the lognormal using a Bayesian approach

Etienne (2005)	Published the correct analytical solution and sampling formula. Two forms of the likelihood equations exist: (a) Ewens’ (1972) sampling formula of neutral alleles is used in the case of no dispersal limitation and (b) Etienne's (2005) formula in cases of dispersal limitation

Etienne and Alonso (2005)	Unified two different approaches to arrive at the full analytical solution: the genealogical approach (Etienne 2005) and master equation-based approach (e.g., Alonso and McKane 2004)

McGill et al. (2006)	Compared nine goodness-of-fit measures with the BCI data and found that for eight out of the nine measures the lognormal outperformed the ZSM

Jabot and Chave (2011)	Built on Etienne's (2005) maximum likelihood framework to develop a more robust test of neutrality incorporating the SAD of Hubbell's SINM and Shannon's index. The SAD of the BCI 50-ha plot did not significantly differ from neutrality; however, the SADs of smaller scale subplots from within the BCI plot were significantly non-neutral

Rosindell and Cornell (2013)	(a) The gamma and negative binomial distributions provided a better fit than the ZSM (b) The SENM predicts SADs which are more realistic than those from the SINM


Function units	Known or possible role	References

ULK1 complex

ULK1	Binds with ATG13, ATG101, and FIP200	[19, 20, 163]

ATG13	Bridges the interaction of ULK1 and FIP200; is required for the localization and stability of ULK1 and stimulates the kinase activity of ULK1	[164]

ATG101	Interacts with ULK1 in an ATG13-dependent manner; regulates the stability and basal phosphorylation of ATG13 and ULK1	[24, 25, 164]

FIP200	Scaffold protein, binds with ULK1 and ATG13; is required for proper localization, stability and kinase activity of ULK1	[19, 20, 29, 164, 165]

PI3K complex III

Beclin 1	BH3-only protein; interacts with Bcl-2	[28, 29, 39]

ATG14L	Enhances Vps34 lipid kinase activity, upregulates autophagy	[28, 30]

hVps15	Ser/Thr protein kinase, is required for Vps34 membrane association	[166]

Vps34	PI3K, forms Phosphatidylinositol 3-phosphate (PI3P) for autophagy	[167, 168]

ATG12 conjugation system

ATG5	Forms isopeptide bond with ATG12	[31, 169]

ATG12	Ubiquitin-like protein; forms isopeptide bond with Atg5 conjugation	[31, 169]

ATG7	E1-like activating enzyme, catalyzes ATG12–ATG5 and LC3-II-PE conjugation	[31]

ATG10	E2-like activating enzyme; catalyzes ATG12–ATG5	[31]

ATG16L1	Conjugates to ATG12-ATG5 complex	[170]

LC3 conjugation system

LC3	Ubiquitin-like protein, conjugates to PE, an important marker of autophagy	[34, 171]

ATG4	Cysteine protease, regulates the level of free LC3-I	[31, 34]

ATG7	E1-like activating enzyme, catalyzes ATG12–ATG5 and LC3-II-PE conjugation	[31, 34]

ATG3	E2-like conjugating enzyme analog, catalyzes LC3-II-PE conjugation	[31, 34]

Other essential proteins

WIPI-2	Mammalian homolog of yeast Atg18, a PI3P-binding protein, facilitates LC3 lipidation	[35, 172]

ATG2	Probably plays an essential role at late step of autophagosome formation	[29, 36]

ATG9	The only known transmembrane protein, may contribute to membrane recruitment	[37]


Factors of associationa	All (n = 3458)	Uganda (n = 491)

Adjusted OR	95 % CI	P value	Adjusted OR	95 % CI	P value

UC allocation by sleeping place (vs by people)	1.63	1.07–2.48	0.025	1.60	1.02–2.52	0.042

Wealth quintile

 Lowest	1.00		<0.001	1.00		0.172

 Second	1.09	0.78–1.53	1.21	0.59–2.46

 Middle	1.39	1.01–1.91	1.40	0.72–2.71

 Fourth	1.66	1.19–2.31	1.48	0.76–2.91

 Highest	1.91	1.37–2.64	2.79	1.20–6.53

Household of four people or more (vs three or less)	0.25	0.18–0.35	<0.001	0.42	0.24–0.76	0.005

Household with any child under five (vs no child under five)	0.37	0.30–0.47	<0.001	0.20	0.10–0.38	<0.001

Factors of associationa	All (n = 3458)	Uganda (n = 491)

Adjusted OR	95 % CI	P value	Adjusted OR	95 % CI

UC allocation by sleeping place (vs by people)	1.63	1.07–2.48	0.025	1.60	1.02–2.52

Wealth quintile

Lowest	1.00		<0.001	1.00

Second	1.09	0.78–1.53	1.21	0.59–2.46

Middle	1.39	1.01–1.91	1.40	0.72–2.71

Fourth	1.66	1.19–2.31	1.48	0.76–2.91

Highest	1.91	1.37–2.64	2.79	1.20–6.53

Household of four people or more (vs three or less)	0.25	0.18–0.35	<0.001	0.42	0.24–0.76

Household with any child under five (vs no child under five)	0.37	0.30–0.47	<0.001	0.20	0.10–0.38

Uganda (n = 491)

P value

0.042

Wealth quintile

0.172

0.005

<0.001


Set	Description	Min	Max	Mean	Median	St.dev.

1	Training Set (32 articles)	4	147	19	14	24

2	Test Set (50 articles – gold standard)	0	375	33	19	63

3	Test Set (507 articles – silver standard)	0	375	18	12	27

Set	Description	Min	Max	Mean	Median	St.dev.

1	Training Set (32 articles)	4	147	19	14	24

2	Test Set (50 articles – gold standard)	0	375	33	19	63

	Test Set (507 articles – silver st	0	375	18	1	2


 	Intervention armn/N(%, 95% CI)	Standard invitation armn/N(%, 95% CI)

Possible unintended consequences

Parents made an informed decision	28/54 (51.9, 26.7–76.1)	9/33 (27.3, 7.6–63.2)

Acceptability

Incentives are a good idea	42/59 (71.2, 47.7–87.0)	25/35 (71.4, 45.0–88.4)

Possible mechanisms of action

Very/quite motivated to return the form	105/200 (52.5, 35.0–69.4)	101/191 (52.9, 45.7–59.9)

Very easy/easy to remember to return the form	154/201 (76.6, 43.5–93.3)	133/193 (68.9, 63.6–73.8)

Returning the form is very/quite important	125/203 (61.6, 39.7–79.6)	131/194 (67.5, 59.1–74.9)

Gave consent form to parents the same day they received it from school	141/202 (69.8, 47.6–85.5)	111/193 (57.5, 52.3–62.5)


Cluster	n	%	Cluster group1	Pulsotype	n	%	Pulsotype group1

C1	6	3.2	Less common	C1a	3	1.6	Less common

 	 	 	 	C1b	1	0.5	Rare

 	 	 	 	C1c	2	1.0	Rare

C2	1	0.5	Rare	C2a	1	0.5	Rare

C3	18	9.7	Less common	C3a	17	9.2	Less common

 	 	 	 	C3b	1	0.5	Rare

C4	1	0.5	Rare	C4a	1	0.5	Rare

C5	1	0.5	Rare	C5a	1	0.5	Rare

C6	1	0.5	Rare	C6a	1	0.5	Rare

C7	1	0.5	Rare	C7a	1	0.5	Rare

C8	2	1.0	Rare	C8a	2	1.0	Rare

C9	1	0.5	Rare	C9a	1	0.5	Rare

C10	5	2.7	Less common	C10a	3	1.6	Less common

 	 	 	 	C10b	1	0.5	Rare

 	 	 	 	C10c	1	0.5	Rare

C11	82	44.3	Common	C11a	79	42.7	Common

 	 	 	 	C11b	1	0.5	Rare

 	 	 	 	C11c	2	1.0	Rare

C12	1	0.5	Rare	C12a	1	0.5	Rare

C13	1	0.5	Rare	C13a	1	0.5	Rare

C14	1	0.5	Rare	C14a	1	0.5	Rare

C15	54	29.2	Common	C15a	8	4.3	Less common

 	 	 	 	C15b	40	21.6	Common

 	 	 	 	C15c	6	3.2	Less common

C16	1	0.5	Rare	C16a	1	0.5	Rare

C17	7	3.8	Less common	C17a	3	1.6	Less common

 	 	 	 	C17b	3	1.6	Less common

 	 	 	 	C17c	1	0.5	Rare

C18	1	0.5	Rare	C18a	1	0.5	Rare

Cluster	n	%	Cluster group1	Pulsotype	n	%	Pulsotype group1

C1	6	3.2	Less common	C1a	3	1.6	Less common

				C1b	1	0.5	Rare

				C1c	2	1.0	Rare

C2	1	0.5	Rare	C2a	1	0.5	Rare

	1	9.	Less common	C3a	17	9.2	Les

C3	8	7					s common

				C3b	1	0.5	Rare

C4	1	0.5	Rare	C4a	1	0.5	Rare

C5	1	0.5	Rare	C5a	1	0.5	Rare

C6	1	0.5	Rare	C6a	1	0.5	Rare

C7	1	0.5	Rare	C7a	1	0.5	Rare

C8	2	1.0	Rare	C8a	2	1.0	Rare

C9	1	0.5	Rare	C9a	1	0.5	Rare

C10	5	2.7	Less common	C10a	3	1.6	Less common

				C10b	1	0.5	Rare

				C10c	1	0.5	Rare

C11	82	44.3	Common	C11a	79	42.7	Common

				C11b	1	0.5	Rare

				C11c	2	1.0	Rare

C12	1	0.5	Rare	C12a	1	0.5	Rare

C13	1	0.5	Rare	C13a	1	0.5	Rare

C14	1	0.5	Rare	C14a	1	0.5	Rare

C15	54	29.2	Common	C15a	8	4.3	Less common

				C15b	40	21.6	Common

				C15c	6	3.2	Less common

C16	1	0.5	Rare	C16a	1	0.5	Rare

C17	7	3.8	Less common	C17a	3	1.6	Less common

				C17b	3	1.6	Less common

				C17c	1	0.5	Rare

C18	1	0.5	Rare	C18a	1	0.5	Rare


Elements	GP (genome proportion, %)

Retrotransposon	11.05

 Copia	5.81

 Gypsy	4.88

 LINE/SINE	0.33

 Unclassified LTR	0.03

Transposon	1.41

 hAT	0.93

 Mutator	0.27

 DNA/CMC-EnSpm	0.10

 Tc1-Mariner	0.11

rDNA	4.32

Satellite	12.93

Unclassified	1.02

Total	30.73

Elements	GP (genome proportion, %)

Retrotransposon	11.05

Copia	5.81

Gypsy	4.88

LINE/SINE	0.33

Unclassified LTR	0.03

Transposon	1.41

hAT	0.93

Mutator	0.27

DNA/CMC-En	0.10

Elements	GP (genome proportion, %)

Spm

Tc1-Mariner	0.11

rDNA	4.32

Satellite	12.93

Unclassified	1.02

Total	30.73


Characteristic	Non-recurrent	Metachronous metastasis	p-value1

absolute	%	absolute	%

Total number	33	 	12

Age [years]	n.s.

Mean	65	 	68

Median	67	 	67

Disease-free survival time [months]	0.000

Mean	78	 	17

Median	77	 	13

Gender	 	 	 	 	n.s.

Female	14	42,4	8	66,7

Male	19	57,6	4	33,3

UICC stage	n.s.

I	6	18,2	2	16,7

II	18	54,5	8	66,7

III	9	27,3	2	16,7

Location	n.s.

Colon	14	42,4	5	41,7

Sigma	16	48,5	4	33,3

Rectum	3	9,1	3	25

Characteristic	Non-recurrent	Metachronous metastasis

absolute	%	absolute	%

Colon	14	42,4	5	41,7

Sigma	16	48,5	4	33,3

Rectum	3	9,1	3	25


	Cortical region

1	Banks of the superior temporal sulcus

2	Caudal anterior cingulate

3	Caudal middle frontal

4	Cuneus

5	Entorhinal

6	Frontal pole

7	Fusiform

8	Inferior parietal

9	Inferior temporal

10	Insula

11	Isthmus of the cingulate

12	Lateral occipital

13	Lateral orbitofrontal

14	Lingual

15	Medial orbitofrontal

16	Middle temporal

17	Parahippocampal

18	Paracentral

19	Pars opercularis

20	Pars orbitalis

21	Pars triangularis

22	Peri-calcarine

23	Postcentral

24	Posterior cingulate

25	Precentral

26	Precuneus

27	Rostral anterior cingulate

28	Rostral middle frontal

29	Superior frontal

30	Superior parietal

31	Superior temporal

32	Supra-marginal

33	Temporal pole

34	Transverse temporal

Cortical region

Banks of the superior temporal sulcus

Caudal anterior cingulate

Caudal middle frontal

Cuneus

Entorhinal

Frontal pole

Fusiform

Inferior parietal

Inferior temporal

Insula

Isthmus of the cingulate

Lateral occipital

Lateral orbitofrontal

Lingual

Medial orbitofrontal

Middle temporal

Parahippocampal

Paracentral

Pars opercularis

Pars orbitalis

Pars triangularis

Peri-calcarine

Postcentral

Posterior cingulate

Precentral

Precuneus

Rostral anterior cingulate

Rostral middle frontal

Superior frontal

Superior parietal

Superior temporal

Supra-marginal

Temporal pole

Transverse temporal


	Healthy weight	Increased weight

Persistent oligoarthritis	95 (90.5)	10 (9.5)

ERA	55 (68)	26 (32)

Poliarthritis RF (+)	46 (78)	13 (22)

Systemic	28 (90.5)	1 (9.5)

Undifferentiated	17 (81)	4 (19)

Psoriatic	16 (100)	0 (0)

Extended oligoarthritis	8 (89)	1 (11)

Poliarthritis RF (-)	4 (80)	1 (20)


Function	Genes		Fold change

Intestinal peptides	GIP	Glucose inhibitory peptide	−1.72

GKN1	Gastrokine 1	−1.54

GKN2	Gastrokine 2	−1.51

VIP	Vasoactive intestinal polypeptide	1.30

Inflammation and oxidative stress	PTGS2	Prostaglandin-endoperoxide synthase – COX-2	1.20

DUSD1	Dual specificity phosphatase 1	1.37

S100A8	S100 calcium binding protein A8	1.59

S100A9	S100 calcium binding protein A9	1.51

IL1B	Interleukin 1 beta	1.21

GPX8	Glutathione peroxidase 8	1.21

FOS	Cellular oncogene c-Fos	1.55

JUN	Jun proto-oncogene	1.32

Transporters	SLC28A2	Sodium-coupled nucleoside transporter	−1.68

SLC2A3	Facilitated glucose transporter 3	1.25

Extracellular matrix	MUC5AC	Mucin 5 AC	−1.58

MUC2	Mucin 2	−1.32

MUC6	Mucin 6	1.21

MMP7	Metalloproteinase 7	1.27

VIL1	Villin 1	−1.22

Digestive functions	PGA5	Pepsinogen A	−1.97

LCT	Lactase	1.76

GLB1	β-galactosidase	−1.21

PNLIPRP2	Pancreatic lipase	1.30

PRSS1	Trypsin 1	1.24

ELA3A	Elastase	1.25

Immunity	GP2	Glycoprotein 2	1.38

HLA-A	Major histocompatibility complex class I A	2.63

HLA-C	Major histocompatibility complex class I C	−1.20

HLA-F	Major histocompatibility complex class I F	−1.28

HLA-DQA1	Major histocompatibility complex class II DQ alpha 1	1.38

HLA-DQB1	Major histocompatibility complex class II DQ beta 1	1.22

HLA-DRB1	Major histocompatibility complex class II DR beta 1	−1.35

HLA-DRB4	Major histocompatibility complex class II DR beta 4	1.39

Cholesterol homeostasis	LDLR	Low density lipoprotein receptor	1.30

APOD	Apolipoprotein D-III	1.20

APOA1	Apolipoprotein A-I	−1.37

Function	Genes

Intestinal peptides	GIP	Glucose inhibitory peptide

GKN1	Gastrokine 1

GKN2	Gastrokine 2

VIP	Vasoactive intestinal polypeptide

Inflammation and oxidative stress	PTGS2	Prostaglandin-endoperoxide synthase – COX-2

DUSD1	Dual specificity phosphatase 1

S100A8	S100 calcium binding protein A8

S100A9	S100 calcium binding protein A9

IL1B	Interleukin 1 beta

GPX8	Glutathione peroxidase 8

FOS	Cellular oncogene c-Fos

JUN	Jun proto-oncogene

Transporters	SLC28A2	Sodium-coupled nucleoside transporter

SLC2A3	Facilitated glucose transporter 3

Extracellular matrix	MUC5AC	Mucin 5 AC

MUC2	Mucin 2

MUC6	Mucin 6

MMP7	Metalloproteinase 7

VIL1	Villin 1

Digestive functions	PGA5	Pepsinogen A

LCT	Lactase

GLB1	β-galactosidase

PNLIPRP2	Pancreatic lipase

PRSS1	Trypsin 1

ELA3A	Elastase

Immunity	GP2	Glycoprotein 2

HLA-A	Major histocompatibility complex class I A

HLA-C	Major histocompatibility complex class I C

HLA-F	Major histocompatibility complex class I F

HLA-DQA1	Major histocompatibility complex class II DQ alpha 1

HLA-DQB1	Major histocompatibility complex class II DQ beta 1

HLA-DRB1	Major histocompatibility complex class II DR beta 1

HLA-DRB4	Major histocompatibility complex class II DR beta 4

Cholesterol homeostasis	LDLR	Low density lipoprotein receptor

APOD	Apolipoprotein D-III

APOA1	Apolipoprotein A-I


 	Hospital plan for follow-up

General practitioner (n = 23)	Specialist health service (n = 66)

Hospital guidelines for follow-up	General practitioner (n = 11)	3	8

Specialist health service (n = 78)	20	58


Viral Systems	Copolymers	Genes	Targets	Administration	Observations	References

rAAV	Pluronic® F127	GM-CSF	solid tumors	in vivo intratumoral infusion (mouse)	higher efficiency by combining DC, local tumor irradiation and controlled supply of recombinant mGM-CSF with Pluronic®	[77]

	Pluronic® F68	lacZ	adipose tissue	in vivo inguinal (mouse)	increased transgene expression after 4 weeks	[78]

	Pluronic® F127	lacZ	cartilage	in vitro hMSCs	controlled release of rAAV for high efficiencies over time and gene expression levels similar to those achieved by direct vector application	[80]

	Pluronic® F68, Tetronic® 908	RFP, lacZ, and SOX9	cartilage	in vitro hMSCs	encapsulation of rAAV in polymeric micelles for effective, durable, and safe modification of hMSCs; restoration of hMSC transduction in conditions of gene transfer inhibition; effective chondrogenesis	[79]

	Pluronic® F68, Tetronic® 908	lacZ	cartilage	in vitro hOACs in situ human osteochondral model	micellar encapsulation for increased stability and bioactivity of rAAV; high levels of safe transgene expression in vitro and in experimental osteochondral defects in situ	[81]

	Pluronic® F68, Tetronic® 908	TGF-β	cartilage	in vitro hOACs in situ human osteochondral model	increased levels of transgene expression compared with free vector treatment; high proteoglycan deposition and increased cell numbers in hOACs in vitro; high deposition of type-II collagen and reduced hypertrophy in osteochondral defects models in situ	[82]

	Pluronic® F68, Tetronic® 908	lacZ	cartilage	in vitro hMSCs	high concentrations of rAAV; sustained levels of transgene expression over time	[92]

Viral Systems	Copolymers	Genes	Targets	Administration	Observations

rAAV	Pluronic® F127	GM-CSF	solid tumors	in vivo intratumoral infusion (mouse)	higher efficiency by combining DC, local tumor irradiation and controlled supply of recombinant mGM-CSF with Pluronic®

	Pluronic® F68	lacZ	adipose tissue	in vivo inguinal (mouse)	increased transgene expression after 4 weeks

	Pluronic® F127	lacZ	cartilage	in vitro hMSCs	controlled release of rAAV for high efficiencies over time and gene expression levels similar to those achieved by direct vector application

	Pluronic® F68, Tetronic® 908	RFP, lacZ, and SOX9	cartilage	in vitro hMSCs	encapsulation of rAAV in polymeric micelles for effective, durable, and safe modification of hMSCs; restoration of hMSC transduction in conditions of gene transfer inhibition; effective chondrogenesis

	Pluronic® F68, Tetronic® 908	lacZ	cartilage	in vitro hOACs in situ human osteochondral model	micellar encapsulation for increased stability and bioactivity of rAAV; high levels of safe transgene expression in vitro and in experimental osteochondral defects in situ

	Pluronic® F68, Tetronic® 908	TGF-β	cartilage	in vitro hOACs in situ human osteochondral model	increased levels of transgene expression compared with free vector treatment; high proteoglycan deposition and increased cell numbers in hOACs in vitro; high deposition of type-II collagen and reduced hypertrophy in osteochondral defects models in situ

	Pluronic® F68, Tetronic® 908	lacZ	cartilage	in vitro hMSCs	high concentrations of rAAV; sustained levels of transgene expression over time


	Dispensation rate of generics	P

Pre-adoption[% (drugs/total drugs)]	Post-adoption[% (drugs/total drugs)]

All drugs subjected to analysis	48.3 (447/926)	57.7 (604/1046)	< 0.001*

Drugs that have the same ingredients or different ingredients as the newly adopted generic drugs

 Drugs with same ingredients	44.7 (135/302)	64.0 (217/339)	< 0.001*

 Drugs with different ingredients	50.0 (312/624)	54.7 (387/707)	0.094

Priscribing facility

 Gifu Municipal Hospital	47.5 (197/415)	66.5 (254/382)	< 0.001*

 Other hospitals/clinics	48.9 (250/511)	52.7 (350/664)	0.219

	Dispensation rate of generics	P

Pre-adoption[% (drugs/total drugs)]	Post-adoption[% (drugs/total drugs)]

All drugs subjected to analysis	48.3 (447/926)	57.7 (604/1046)	< 0.001*

Drugs that have the same ingredients or different ingredients as the newly adopted generic drugs

Drugs with same ingredients	44.7 (135/302)	64.0 (217/339)	< 0.001*

Drugs with different ingredients	50.0 (312/624)	54.7 (387/707)	0.094

Priscribing facility

G	47.5 	66.5 (254	<

	Dispensation rate of generics	P

Pre-adoption[% (drugs/total drugs)]	Post-adoption[% (drugs/total drugs)]

ifu Municipal Hospital	(197/415)	/382)	0.001*

Other hospitals/clinics	48.9 (250/511)	52.7 (350/664)	0.219


Descriptor	P-values

	Not ranked	30 Top-ranked	20 Top-ranked

C	1.2 e-1	5.8 e-1	5.6 e-1

D	5.1 e-3	2.6 e-1	2.4 e-1

Variance	9.0 e-2	3.4 e-1	5.7 e-1

Descriptor	P-values

	Not ranked	30 Top-ranked

C	1.2 e-1	5.8 e-1

D	5.1 e-3	2.6 e-1

Variance	9.0 e-2	3.4 e-1

P-values

20 Top-ranked

5.6 e-1

2.4 e-1

5.7 e-1


Migraine Triggers	N	%

Identified any Triggers	3416	82.9

Stress	2669	55.8

Environment (weather, etc...)	2870	60.0

Lack of Sleep	2484	51.9

Hormones/menstrual cycle	1792	37.4

Certain food drink	2138	44.7

Missing meals	1884	39.4

Certain smell	2046	42.7

Alcohol/drugs	1235	25.8

Physical Activity	1241	25.9

Sexual Activity	325	6.8

Other	739	15.4

Steps taken to avoid triggers	3033	63.4

Migraine Triggers	N	%

Certain smell	2046	42.7

Alcohol/drugs	1235	25.8

Physical Activity	1241	25.9

Sexual Activity	325	6.8

Other	739	15.4

Steps taken to avoid triggers	3033	63.4


Group	Cohesive fracture in tooth	Cohesive fracture in laminate	Adhesive	Mixed cohesive and adhesive

Control	5	1	0	5

SC	4	0	3	4

LC	1	0	5	4

Total	10	1	8	13

Cohesive fra	Cohesive fracture in lamin	Adhesiv	Mixed cohesive and adhesi

Group	cture in tooth	ate	e	ve

Control	5	1	0	5

SC	4	0	3	4

LC	1	0	5	4

Total	10	1	8	13


PAMAM dendrimer generation (G)	Terminal amines (#)	Naked dendrimer molecular weight (kDa)	Gd-G5-doxorubicin dendrimer molecular weight (kDa)	Gd-DTPA conjugation (%)	Doxorubicin conjugation (%)	Molar relaxivity (mM-1s-1)

G5	128	29#	85‡	48.1	7.8	10.1&

PAMAM dendrimer generation (G)	Terminal amines (#)	Naked dendrimer molecular weight (kDa)	Gd-G5-doxorubicin dendrimer molecular weight (kDa)	Gd-DTPA conjugation (%)	Doxorubicin conjugation (%)	Molar relaxivity (mM-1s-1)

G	12	2		48.		10.1&