FTO SNP rs55872725 , and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP , located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes.The Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the  Large, well-phenotyped cohort studies have constituted the backbone of epidemiology for several decades. Prospectively collected longitudinal information on exposures and outcomes enables a broad spectrum of analyses and has led to novel insights into disease etiology, such as the link between smoking and lung cancer ,2 as welWithin the Nurses’ Health Study (NHS) , Nurses’Here, we describe our pipeline for merging and imputing the individual GWAS datasets within NHS, NHSII, HPFS and PHS. Datasets were merged based on genotype platform family and all data were subsequently imputed to a common reference panel . We preIn 1976, the Nurses’ Health Study (NHS) was launched with the goal of studying women’s health . Since tEach GWAS study was approved by the Brigham and Women’s Hospital Institutional Review Board. Return of the mailed self-administered questionnaires was voluntary. Thus, receipt of a completed questionnaire was considered as evidence of a desire to participate in the study and was taken as a formal indication of consent.Table 1). The primary traits are breast cancer [Table 1) at four different genotyping centers . Standard quality control filters for call rate, Hardy-Weinberg equilibrium, and other measures were applied to the genotyped SNPs and/or samples. In total, these GWAS data sets comprise 20,769 participants including 11,522 from NHS, 934 subjects from NHSII, 7,018 subjects from HPFS and 1,305 subjects from PHS.Since 2007, twelve separate GWAS have been conducted within these four cohorts . To achieve the largest GWAS datasets as possible without losing SNP information, we created three datasets–HumanHap comprising six GWAS datasets, OmniExpress comprising four GWAS datasets and Affymetrix 6.0 comprising two GWAS datasets. In the merging process, we removed any SNPs that were not in all studies for a specific platform or had a missing call rate>5%. We flipped strands where appropriate and removed A/T and C/G SNPs to create the final compiled datasets.Successfully merging genotype data for different individuals requires complete overlap in SNPs. SNPs that are missing by design (due to different genotyping platforms) from some studies will be correlated with the primary phenotype for that dataset. This might cause spurious results in any secondary analysis on related traits. Although a missing SNP can be imputed, it will have a higher degree of inaccuracy in imputed compared with genotyped SNPs, potentially creating differential measurement error that could also lead to bias ,46,47. T0, Z1 and Z2 . If 0≤Z0≤0.1 and 0≤Z1≤0.1 and 0.9≤Z2≤1.1 then a pair was flagged as being identical twins or duplicates. Pairs were considered full siblings if 0.17≤Z0≤0.33 and 0.4≤Z1≤0.6 and 0.17≤Z2≤0.33. Half siblings or avunculars were defined as having 0.4≤Z1≤0.6 and 0≤Z2≤0.1. Some of the duplicates flagged were expected, having been genotyped in multiple datasets and hence having the same cohort identifiers. In this case, one of each pair was randomly chosen for removal from the dataset. In instances where pairs showed pairwise genotype concordance rate>0.999 but were not expected duplicates, both individuals were removed. Related individuals  were not removed from the final datasets. In the HumanHap dataset, 107 individuals were removed because they were duplicates or flagged for removal in the genotyping step, leaving 6,787 subjects. In addition, 8 pairs of individuals were flagged as related. In the OmniExpress dataset, we removed 39 subjects leaving 5,917 IDs and 5 pairs of related subjects. In the Affymetrix dataset, 167 individuals were removed because they were duplicates or were flagged for removal from secondary genotype data cleaning, leaving a total of 8,065 individuals. Across all three datasets, we identified 444 duplicate pairs (406 expected) and thus removed additional 482 individuals from analysis across all three platform families.We ran a pairwise identity by descent (IBD) analysis within and across the combined dataset to detect duplicate and related individuals based on resulting IBD probabilities ZAfter removing duplicate and related pairs of IDs, we used EIGENSTRAT  to run p−8) and examined QQ plots. In the Affymetrix dataset, 100 SNPs were flagged and removed. In the HumanHap dataset, 8 SNPs had p<10−8 in at least one of the QC regressions and were removed. No SNPs in the OmniExpress dataset had p<10−8 and hence, no SNP was removed.To identify any SNPs that created spurious associations, we ran several logistic regression analyses among subjects that were selected as controls in the initial GWAS . For each regression, we used cohort-specific controls from one original GWAS as cases and the rest of the controls in that dataset as controls. For example, in the OmniExpress dataset, we considered NHS controls from the gout GWAS as “cases” while treating controls from the gout (HPFS), endometrial cancer (NHS), colon cancer , and mammographic density (NHS) as “controls”. We repeated this, treating each cohort-specific “controls set” as “cases” and all other controls as “controls”. For each GWAS, we extracted genome-wide significant SNPs  as the reference panel. SNP and indel genotypes were imputed in three steps. First, genotypes on each chromosome were split into chunks to facilitate windowed imputation in parallel using ChunkChromosome (v.2011-08-05). Then each chunk of chromosome was phased using MACH ,51 (v.1.2 (cm) and obtained it by extracting information on weight from the accompanying questionnaire collected at time of blood draw. If weight information was missing, we extracted it from the questionnaire closest in time to time of blood draw. Height was extracted from the baseline questionnaire. We obtained data on BMI for 20,283 participants. VTE is a spectrum of disease that includes pulmonary embolism (PE) and deep vein thromboembolism (DVT). Physician-diagnosed PE has been asked on every biennial NHS questionnaire since 1982, and every NHSII and HPFS questionnaire since cohort inception. In the NHS, DVT without PE is captured when a nurse answers that she has had phlebitis or thrombophlebitis (ICD-9 = 453.x). In NHS, NHSII and HPFS cohorts through 2010 (we did not have VTE data for PHS), we identified 6,041 individuals who reported VTE. Self-reported PE was verified through medical records review by a trained physician (CK). DVT cases are based on self-report, though a validation study of 100 DVT cases found self-reports to be highly consistent (>96%) with medical record review. In total, we identified 1,364 VTE cases with GWAS data. We treated all non-VTE cases with GWAS data as controls . Since we did not have data on VTE in PHS, we excluded PHS from this analysis.To validate our merged GWAS datasets, we conducted two proof-of principle GWAS of one quantitative trait (BMI) and one binary trait (VTE). We defined BMI as weight (kg)/heightSNPs and indels with an imputation quality score <0.3  or a minor allele frequency (MAF) <0.01 were excluded. Primary association analysis was performed separately within each platform family . For imputed SNPs, the estimated number of effect alleles (ranging from 0 to 2) was used as a covariate. For BMI, we conducted linear regression adjusting for study (indicator variables including cohort as well as primary GWAS outcome), age at blood draw and the top four principal components. For VTE, we conducted logistic regression adjusting for study as above and the top four principal components. For both BMI and VTE, we combined platform family-specific results with fixed-effects meta-analysis using the METAL  softwareFig 2 and the distribution of imputation quality score for rare (MAF≤0.01) variants is shown in ) with 49–51% of markers having an imputation quality score ≥0.3. When restricting to markers with MAF>0.01 (~10 million), 92–94% of the markers had a quality score ≥0.3, compared to 29–32% of markers with MAF≤0.01. After filtering markers based on MAF (>0.01) and imputation r-sq (≥0.3), approximately 9.8 million markers were available for analysis.We imputed a total of 31,326,389 markers  and the majority (69%) of these had a MAF≤0.01. The average imputation quality score by minor frequency for each platform family is shown in S4A–S4C Fig) showed no indication of systematic bias (genomic inflation factor λ = 1.00–1.02). The results from the meta-analysis are shown in Figs 4. We observed a tail of strongly associated SNPs with the top SNPs located in the known BMI FTO locus . Given that the FTO locus has also been associated with Type 2 Diabetes, we reran the analysis excluding all Type 2 Diabetes cases , The association for the FTO SNP rs55872725 remained strongly significant . We also observed genome-wide significant associations for the previously identified TMEM18  and FANCL loci . None of the SNPs that were originally reported were the top SNP in our data. However, for these three regions . Using a significance level of p = 0.05, 59% (19/32) known BMI SNPs [.We had BMI and GWAS data for 20,283 individuals  within NHS, NHSII, HPFS and PHS. Platform-specific QQ-plots  showed no indication of systematic bias (genomic inflation factor λ = 1.00–1.01). The results from the meta-analysis are shown in Figs 7 (genomic inflation factor λ = 1.00). We observed a strong association located downstream of the F5 gene . We also observed genome-wide significant associations for the ABO locus  and a nominal association (P = 0.007) with the previously VTE-associated F11 locus. For both the F5 and ABO regions , our top SNPs showed moderate correlation with previously reported top SNP . Using a significance level of p = 0.05, three of nine known VTE SNPs [.We had information on VTE status and GWAS data for 1,364 cases and 17,628 controls within NHS, NHSII and HPFS. The median number of case subjects by dataset was 87.5 and ranged from 16 in the NHSII breast cancer GWAS dataset  to 417 in the type 2 diabetes GWAS dataset . The small number of cases in many individual GWAS data sets led to unstable study-specific association statistics. Restricting to studies with an expected case minor allele count >10 for SNPs with a MAF of 0.05 (i.e. studies with at least 200 cases) reduced the sample size to 417 cases and 5,356 controls. However, within each compiled imputed GWAS dataset, VTE case numbers ranged from 406 (OmniExpress) to 532 (Affymetrix). Thus, combining the individual GWAS datasets into three main datasets enabled association analysis of hundreds of cases rather than tens, leading to more stable estimates in the regression analysis. Platform-specific QQ-plots  since the SNP overlap across platforms was low on a genome-wide scale . An attempt to impute a genome-wide dataset comprising only 75,000 SNPs as starting point would have resulted in decreased imputation accuracy in regions of the genome with sparse genotype data. Moreover, it has been shown that different platforms might call SNPs differently and that SNP-specific allele frequencies can differ between platforms (see  for furtFTO and TMEM18 that both reached genome-wide significance (P<5x10-8). In addition, out of 32 known BMI SNPs we observed nominal significance (P<0.05) for 19 of them, all in the same direction as expected from previous reports. Of note, our sample size  is less than 10% of the original GWAS that had a total sample size of 249,766 individuals. Therefore, we would not expect to observe significant associations for all BMI SNPs due to limited power. For VTE, we observed genome-wide significant associations for the F5 and ABO loci that are both known to be associated with VTE. In addition, we also observed a nominal association (P = 0.007) with the F11 region. Our BMI and VTE results confirm that GWAS analysis of secondary traits in this data is valid and provides a platform for future studies of secondary traits. We ran the BMI and VTE analyses twice, the first time without removing duplicates between the datasets , and the second time with the duplicates removed. Although the 444 pairs constitute less than 5% of our total sample size, including them had an impact on the genomic inflation factor . These results are especially interesting as it is often difficult to identify duplicates across studies when raw data from all participating studies are not available. Care should be taken to remove overlapping subjects across GWAS contributing to a meta-analysis, but any remaining cryptic overlap may inflate association statistics. In that case, statistical adjustment procedures like LD score regression [To assess the validity of our data, we conducted two proof-of-principle GWAS. The first trait we studied was BMI, and in line with what expected, we observed strong evidence of associations with known BMI loci including gression  can be uOne of the main benefits with collecting comprehensive genetic information on cohort subjects is the opportunity to assess interactions between genetic factors and prospectively collected environmental data. To date, few gene-environment interactions have been identified and although their extent and clinical impact remain an open empirical question, the current lack of homogenous large datasets with both genetic and environmental data has precluded comprehensive investigation. Capitalizing on this GWAS resource, we will be able to explore gene-environment interactions for a plethora of outcomes including complex traits such as height and BMI, but also disease outcomes. It will also allow us to study the impact of environmental factors within genetic strata to identify individuals for whom a particular intervention might be especially important –59.Accumulation of these GWAS data is ongoing and we expect to generate new GWAS data for an additional 15,000 participants within the next two years, almost doubling our total GWAS sample size. This growing resource will be a core component of future studies aiming to elucidate how genes and the environment impact public health.S1 FigDifferent colors correspond to different imputation quality score r-sq thresholds. Data is categorized by minor allele frequency.(PDF)Click here for additional data file.S2 FigDifferent colors correspond to different imputation quality score r-sq thresholds. Data is categorized by minor allele frequency.(PDF)Click here for additional data file.S3 FigDifferent colors correspond to different imputation quality score r-sq thresholds. Data is categorized by minor allele frequency.(PDF)Click here for additional data file.S4 FigA: QQ-plot for GWAS analysis of body mass index on the Illumina Omniexpress platform . B: QQ-plot for GWAS analysis of body mass index on the Affymetrix platform . C: QQ-plot for GWAS analysis of body mass index on the Illumina HumanHap platform .(PDF)Click here for additional data file.S5 FigFTO locus. B: LocusZoom plot for the BMI TMEM18 locus. C: LocusZoom plot for the BMI FANCL locus.A: LocusZoom plot for the BMI (PDF)Click here for additional data file.S6 FigA: QQ-plot for GWAS analysis of venous on the Illumina Omniexpress platform . B: QQ-plot for GWAS analysis of venous on the Illumina Omniexpress platform . C: QQ-plot for GWAS analysis of venous on the Affymetrix platform .(PDF)Click here for additional data file.S7 FigF5 locus. B: LocusZoom plot for the VTE ABO locus.A: LocusZoom plot for the VTE (PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.


However, the relationship between HRC and liver fibrogenesis is still unknown. Our data demonstrates that HRC was upregulated in fibrotic liver and activated hepatic stellate cells (HSCs). TGF-β treatment increased α-SMA and HRC expression dose-dependently in HSCs. Repression of HRC reduced α-SMA, CTGF and collagen expression, and inhibited HSC proliferation and migration. In addition, we found that the anti-fibrosis effect of HRC knockdown was associated with endoplasmic reticulum (ER) stress. Silencing of HRC decreased the expression of ER stress and autophagy markers. Moreover, ER stress agonist thapsigargin (TG) enhanced, whereas ER stress antagonist 4-phenylbutyric acid (4-PBA) alleviated HSCs activation and autophagy. In conclusion, these data indicate that depletion of HRC inhibited HSC activation through the ER stress pathway, and HRC may be a potential regulator of liver fibrosis.The histidine-rich calcium-binding protein (HRC) is a regulator of Ca Summary: We provide the first evidence to confirm that HRC is a factor in liver fibrosis, and we clarify the molecular mechanism of HRC in hepatic stellate cell activation and liver fibrosis. Liver fibrosis is a wound-healing response to chronic liver injury, and it also considered as a pre-cancerous condition which may result in hepatocellular carcinoma (HCC). Activated hepatic stellate cells (HSCs) are responsible for the excessive deposition of extracellular matrix (ECM) proteins during hepatic fibrogenesis . Prevent2+ homeostasis  is a regulator in Caeostasis . Calciumeostasis . Activatesponses . Recentlesponses , 2013. HRecent data indicate that ER stress plays a pivotal role in the progression of liver diseases, including liver fibrosis . InhibitFor the first time, we discovered that HRC was upregulated in fibrotic liver and activated HSCs. Moreover, we demonstrated that HRC knockdown inhibited the activation, proliferation and migration of HSCs, which was partly attributed to ER stress and autophagy.To explore the role of HRC in liver fibrosis, immunohistochemistry was performed to determine the expression of HRC in human samples. The results showed that the expression of HRC was gradually increased along with the severity of liver fibrosis, and HRC was significantly overexpressed in cirrhosis A. In addFreshly isolated (1 day) or 7-day cultured primary rat HSCs were used as quiescent and activated cells, respectively, as described in our previous study .The exprNext, we wondered whether HSCs activation could be inhibited by HRC knockdown. RNA interference was used to downregulate HRC expression in LX-2 cells A. ReductAs endoplasmic reticulum (ER) stress is emerging as a well-described determinant of HSCs activation , we hypoRecent data has indicated that ER stress induces HSC activation through autophagy . Therefo2+ homeostasis. Increasing evidence has revealed that Ca2+ signaling plays a crucial role in HSC activation, proliferation and contraction  participates in the regulation of Catraction . Furthertraction . Chen eting HSCs , and Atoc effect . Howeverin vitro. Mechanistic studies revealed that ER stress and autophagy were responsible for the observed effects of HRC on HSC activation. Collectively, these results suggest that HRC may be a promising target for anti-fibrotic therapy.Previous literature has demonstrated that HRC plays an important role in cardiac fibrosis, and our data support this notion in liver fibrosis as well. Here, for the first time, we found that HRC was significantly upregulated in fibrotic liver, and during the activation of HSCs, the expression of HRC could be obviously induced. Furthermore, we demonstrated that HRC knockdown inhibited HSCs activation, proliferation and migration The central step in liver fibrosis is the activation of HSCs, inhibition of HSC activation is considered a key target for the treatment of hepatic fibrosis . To asse. demonstrated that liver fibrosis was greatly attenuated in CHOP-deficient mice following bile duct ligation  were divided into five groups according to the severity of liver fibrosis, including S0 (n=5), S1 (n=10), S2 (n=10), S3 (n=2) and S4 (n=18), which were diagnosed by the pathologists at Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology. All procedures involving human participants were performed after obtained their informed consent, which was also in accordance with the Medical Ethics Committee of Tongji Hospital.Human samples (n=6/group). Rats were treated with thioacetamide (TAA) or saline (200 mg kg−1) by intraperitoneal (i.p.) injection twice a week for 8 weeks. All procedures performed in studies involving animals were approved by the Institutional Laboratory Animal Care and Use Committee by the Institutional Laboratory Animal Care and Use Committee of Tongji hospital.Male Sprague–Dawley (SD) rats weighting about 200 g were randomly divided into three groups , Masson and Sirius Red staining. An HRC polyclonal antibody  was used to detect the expression of HRC in fibrotic liver.Table S1.Total RNA was extracted using TRIzol reagent . Reverse-transcribed complementary DNA was synthesized using the PrimeScript RT reagent kit . Real-time polymerase chain reaction was performed using SYBR Premix ExTaq (TaKaRa) on an ABI StepOne Real-Time PCR System . The sequences of the primers used for PCR are listed in Table S2.Western blot was performed as previously described . BrieflyFor RNA interference, HRC siRNA was synthesised by RiboBio , and then transfected into LX-2 cells using lipofectamine 2000 (Invitrogen) according to the manufacturer's instructions. The sequence of siHRC was designed as follows: CCACAGAGACGAGGAAGAA.Cell proliferation was analyzed by Cell Counting Kit-8 (CCK-8) assay  according to the manufacturer's instructions.4 cells in 0.2 ml media were plated in the upper chambers, 600 μl DMEM medium containing 10% fetal calf serum  was added to the lower chamber. After 24 h, cells that migrated through the membrane to the lower surface were fixed with 4% paraformaldehyde, stained with crystal violet and counted by microscopy .Cell migration assay was performed using transwell chambers . Briefly, a total of 5×10t-test was performed to assess the significance of differences between two groups. A P-value <0.05 was considered statistically significant.Data are presented as means±s.d. Student's


Similarly, babies of women with low carbohydrate intake were 312 g lighter compared with those of women with a moderate carbohydrate intake . Our results suggest that second trimester maternal carbohydrate intake has significant impacts on total gestational weight gain and neonatal birth weight.Poor maternal nutrition is a major contributor to the high incidence of low birth weight deliveries in developing countries. This study aimed to assess the impact of second trimester maternal dietary intake on gestational weight gain and neonatal birth weight. A longitudinal study was conducted in a tertiary care hospital in Sri Lanka. Participants were 141 pregnant women at 18–24 weeks gestation who were followed up until delivery. Maternal dietary intake was assessed using a validated Food Frequency Questionnaire at 21.1 ± 1.8 gestational weeks. Gestational weight gain was examined at the end of 28 weeks gestation and at the end of pregnancy. Energy and nutrient intakes were calculated using NutriSurvey 2007  nutrient analysis software, modified for Sri Lankan foods. The mean total gestational weight gain of women with low carbohydrate intake (229–429 g/day) was 2.2 kg less than that of women with moderate carbohydrate intake (430–629 g/day)  0.428–4.083 kg;  Despite a consistent decline in maternal and infant mortality, Sri Lanka continues to experience crucial health problems among pregnant women, infants, and children. A significant problem is the high percentage of low birth weight (LBW) deliveries. LBW is defined as weight at birth less than 2500 g regardless of gestational age. According to 2012 national health statistics, there were 55,557 LBW deliveries in Sri Lanka, accounting for 16.3% of total live births [Perinatal complications associated with LBW are mostly attributed to fetal prematurity, but may also result from intrauterine growth restriction . LBW incMaternal malnutrition is the main contributing factor underlying high LBW percentages in many developing countries , and plastring hoppers, hoppers, pittu or bread with one or two curries. To date, no studies on the relationships among maternal dietary intake, gestational weight gain, and neonatal birth weight have been conducted in Sri Lanka. This study aimed to assess the influence of second trimester maternal dietary intake on GWG and neonatal birth weight, and to explore the relationships among these three factors.Sri Lankans have a unique dietary pattern. The staple meal is large serving of rice accompanied by different vegetable, egg, meat or fish side dishes cooked with spices and (most often) coconut milk. This rice and curry meal is commonly consumed as lunch, although it may also form breakfast and dinner, depending on personal preferences and factors such as economic status. Traditional morning and evening meals usually comprise a starchy staple such as This study used a longitudinal design, and was conducted in antenatal clinics at the General Hospital Kurunegala, Sri Lanka from October 2015 to June 2016. A convenience sample of pregnant women at 18–24 weeks gestation was included and they were followed up until delivery. Initial recruitment consisted of 150 pregnant women.Women were invited to participate in the study through a recruitment poster displayed in the hospital’s outpatient department. Pregnant women who were interested in participating were requested to inform the researcher directly, in person or via telephone. Written information sheets were provided to all interested women, including an explanation of the study purpose, data collection methods, time taken for data collection and confidentiality of personal information.n = 2, multiple fetuses identified at the 20-week ultra sound scan n = 2, and maternal desire to deliver at another hospital n = 3) and two personal withdrawals, resulting in nine exclusions between the recruitment process and the end of pregnancy.Exclusion criteria were risk factors according to obstetric history  and medical history . Impending neonates with a 5-minute Apgar score less than 5, and women who expected to deliver their baby at another hospital were also excluded. Based on these criteria, there were seven exclusions by the researcher  international BMI cut-off points were used for BMI group categorization [Socioeconomic and demographic data were collected by the researcher through interviews using a pre-designed and pre-tested questionnaire. Maternal body weight and height were measured using standard scales. Pre-pregnancy BMI was calculated by pre-pregnancy weight in kg  divided by height in mrization  were useThriposha, a supplement of pulses provided to pregnant women, was included in the FFQ under the pulses group. This is a nutrient supplement pack that is given to all pregnant women through community maternity clinics to combat protein, energy, and micronutrient deficiencies. It is a pre-cooked and ready-to-eat cereal legume-based food. In total, 100 g of Thriposha contains 401.8 kcal of energy, 61.9 g of carbohydrate, 20.0 g of protein, 7.8 g of fat, 1700 IU of vitamin A, and 18 mg of iron. It is recommended to consume 50 g of Thriposha each day during pregnancy. Participants were asked to complete the FFQ once in the second trimester . The FFQ was self-administered, with support from the researcher provided where necessary. Questions focused on the women’s usual dietary intake in the second trimester. Food photographs were included in the questionnaire to facilitate understanding of portion sizes. Dietary assessment aids were day-to-day standard household measurements . Energy and nutrient intakes were calculated using NutriSurvey 2007  nutrient analysis software, after modification for individual Sri Lankan food items and recipes.Participants’ dietary intake was assessed using a Food Frequency Questionnaire (FFQ) that was developed and validated for Sri Lankan adults, including women ,9. ThripFor curry/mixed dishes, ingredients were weighed to the nearest 1 g of edible portion using a standard kitchen weighing scale .Dishes were cooked according to the validated recipes.The final products were measured using standard household measurement utensils.Modification of the nutrient analysis software involved adding single food items to the original software using information from the food composition tables of Sri Lanka , and theRecipes (curry/mixed dishes) were entered in to the modified software by entering single food items according to the validated recipes. For each recipe, a cooking method was applied from the available options in the software to approximate weight loss due to water evaporation from different food preparation methods. The software then automatically calculated and standardized the nutrient composition for 100 g of final product. One cup was considered 150 mL and one glass 200 mL. The portion size of each food item in the FFQ was also measured and the software was modified as necessary. After the final software modification, the FFQ was entered in the software with the option of changing frequency of consumption to daily, weekly or monthly. Finally, participants’ FFQ data were entered into the software and estimated energy, carbohydrate, and protein intakes per day were calculated.The EER for the second trimester of pregnancy for each woman was calculated based on IOM guidelines :EER  for women aged 19 years and older  was usedThe RDA of protein during the second trimester for each woman was calculated as 1.1 g/kg/day, using the women’s pre-pregnancy weight .p < 0.05 was considered statistically significant.All data were entered and rechecked in Microsoft Excel 2007. Data for energy and macronutrient intakes were transferred from NutriSurvey 2007 to Minitab version 17 for statistical analysis. Descriptive statistics were expressed as mean ± standard deviation (SD). Correlations between neonatal birth weight, gestational weight gain, dietary intake and other continuous variables were evaluated with Pearson’s correlation analysis. To test the effects of different levels of energy and macronutrient intakes on gestational weight gain and neonatal birth weight, participating women were divided into two groups by energy intake  and two protein intake groups  based on estimated dietary intakes. As all women were above the RDA for carbohydrate, they were grouped in three categories with same class interval: 1 = 229–429 g/day; 2 = 430–629 g/day; and 3 = 630–829 g/day. One-way analysis of variance (ANOVA) was used to examine the differences in means of gestational weight gain, energy and nutrient intakes and neonatal birth weight. Two general linear models were constructed to define independent factors associated with total gestational weight gain and neonatal birth weight, controlling for confounders. Total energy intake was not included in the general linear models to avoid multicollinearity, as the total energy intake represents energy from carbohydrate, protein, and fat. For each analysis, 95% confidence intervals were calculated, and Informed written consent was obtained from all the subjects before they participated in the study. The study was conducted in compliance with the principles of the Declaration of Helsinki, and the protocol was approved by the Ethical Review Committee, Graduate School of Health Sciences, Niigata University, Japan (No: 125); the Ethical Review Committee, Faculty of Allied Health Sciences, University of Peradeniya, Sri Lanka; and the Institutional Ethical Review Committee, Teaching Hospital Kurunegala, Sri Lanka (No: ERC/2015/06).The final sample included 126 healthy newborns. Of these, 22 (17.4%) were LBW babies. In total, 20.6% women were underweight when they became pregnant and 56.7% had normal BMI. Participants’ characteristics are summarized in Of the 141 pregnant women, 138 returned a completed FFQ. Two incomplete questionnaires were excluded from the final analysis. The mean EER was 2224.4 ± 138.6 kcal/day; 26 (19.1%) participants were below the EER, whereas almost all women (100%) had a carbohydrate intake above the RDA . The mean RDA of protein was 57.3 ± 11.3 g/day, and 81.6% women had a protein intake above the RDA . Of the total energy intake, 72.8% was from carbohydrate and 9.8% was from protein. The protein intake mainly comprised plant protein , with only 12.8% of the total protein intake being animal protein. The mean animal protein intake was 9.1 g/day and the mean plant protein was intake 53.9 g/day. Women with the lowest level of monthly household income showed the lowest total energy, carbohydrate, and protein intakes, but this did not reach statistical significance. Women living in rural areas showed the highest carbohydrate intake, but this did not significantly differ from women in urban and sub-urban areas .p = 0.046). When the analysis was repeated with pre-pregnancy BMI and gestational age fixed, there was a moderate positive correlation between total GWG and neonatal birth weight . Maternal height (r = 0.283), pre-pregnancy weight (r = −0.247), and pre-pregnancy BMI (r = −0.340) were significantly correlated with total GWG (p < 0.05). Gestational age (r = 0.315), pre-pregnancy weight (r = 0.234), and pre-pregnancy BMI (r = 0.187) were significantly correlated with neonatal birth weight (p < 0.05). A strong positive correlation was observed between GWG up to 28 weeks gestation and total GWG . None of the studied dietary factors  showed a significant correlation with total GWG or neonatal birth weight.The correlation between total GWG and neonatal birth weight was 0.194 (p < 0.001), whereas both the pre-pregnancy BMI category (p < 0.001) and dietary protein intake category (p < 0.05) were significantly associated with total GWG , pre-pregnancy BMI category (p < 0.001), and daily carbohydrate intake category (p < 0.05) on total GWG. The respective effects of fat intake, parity, and dietary protein intake category were not significant (p > 0.05). Women with an underweight pre-pregnancy BMI showed a higher mean total GWG (3.8 kg) compared with women with normal pre-pregnancy BMI (p < 0.001). Similarly, women with underweight pre-pregnancy BMI showed a 4.8 kg higher mean total GWG compared with women who were overweight (p < 0.001) and a 5.4 kg higher gain than those who were obese (p < 0.001). The mean total GWG for women with a carbohydrate intake of 229–429 kcal/day was 2.2 kg below that of women with a carbohydrate intake of 430–629 kcal/day (p = 0.016).The fitted general linear model  showed sp < 0.05)  were significantly associated with neonatal birth weight ( < 0.05) .2R (adjusted) = 13.3%) showed that pre-pregnancy BMI (p = 0.025), gestational age (p < 0.001), parity (p < 0.05), and carbohydrate intake category (p < 0.05) had significant effects on neonatal birth weight. The babies of urban mothers were 258 g lighter than those of rural mothers; However, the difference was not significant (p = 0.062). The mean birth weight of babies of primiparous mothers was 187.4 g below that of babies of multiparous mothers (p = 0.046). For the carbohydrate intake category, the mean neonatal birth weight for category 1  was 312 g below the mean birth weight of those in category 2  (p = 0.006). Income level had no significant effect on neonatal birth weight (p > 0.05)  .Thriposha intake was 34.8 ± 29.3 g/day (range 0–200 g/day); 11.8% (16/136) of women reported they were not consuming the supplement at all. There was no significant difference in total GWG between women who consumed 0–49 g/day of Thriposha (9.0 ± 3.7 kg) and those who consumed ≥50 g/day (9.8 ± 3.9 kg) (p = 0.271). The mean neonatal birth weight was 2859.1 ± 488.4 g in mothers who consumed 0–49 g/day of Thriposha, and 2906.3 ± 523.1 g in those who consumed ≥50 g/day. There was no significant difference in mean neonatal birth weight between the two Thriposha groups .The mean The present study showed that 17.4% of deliveries were LBW babies, which was slightly above the national LBW rates for 2014 . This miIn the present study, all participating women had a carbohydrate intake during pregnancy above the RDA. The mean energy intake was significantly higher than previous studies ,19. HoweOur study revealed a significant relationship between second trimester carbohydrate intake and neonatal birth weight. Godfrey et al. found that birth weight was inversely related to carbohydrate intake in early pregnancy , which iThriposha supplement for pregnant women aims to maintain satisfactory GWG and reduce the LBW percentage. Although this supplement is distributed free of charge, the present study indicated that the mean Thriposha intake was below the recommended intake of 50 g/day. In addition, 11.8% of women reported that they were not consuming the Thriposha supplement even though they received it from the community clinics. This may be because the supplement was consumed by the entire family rather than the pregnant woman. However, in the present study, supplement consumption showed no significant effect on either GWG or neonatal birth weight. Further large scale, nationwide studies are recommended to evaluate the effects of supplements distributed free of charge by community clinics.Provision of the There was a notable data loss between recruitment and the end of data collection, resulting in a smaller sample size than expected. In addition, using a FFQ to collect dietary intake data might have resulted in over/under estimation of actual intake. Despite these limitations, the present study provides the first local estimates of energy and macronutrient consumption among pregnant women in Sri Lanka.The Sri Lanka Ministry of Health recommends that the total GWG should be based on the IOM 2009 revised guidelines. Over 15% of women with inadequate GWG delivered LBW infants, indicating that although the IOM guidelines were developed for Americans with larger body frames, they were useful in our setting for identifying women at risk of delivering LBW infants. Culturally and economically competent health care is required to allow Sri Lankan women to achieve a desirable GWG; the emphasis should be on a healthy diet and regular weight monitoring. Nutritional education should be integrated into first-trimester antenatal education sessions, with a focus on meals meeting the dietary requirements of pregnancy and featuring a variety of foods from all food groups. Individual nutritional counseling should be provided to women at risk, especially those with an underweight pre-pregnancy BMI, those exhibiting low GWG, and those on poor diets. We also found that almost all women consumed more than the RDA of carbohydrates during pregnancy. Thus, culturally appropriate dietary recommendations relevant in the Sri Lankan context should be essential components of strategies seeking to prevent low birth weight.Second trimester maternal carbohydrate intake shows significant relationships with total GWG and neonatal birth weight. Maintaining a moderate level of carbohydrate intake (430–629 g/day) during the second trimester of pregnancy may promote favorable total GWG and neonatal birth weight in the Sri Lankan context. Our results highlight the need for primary healthcare providers to be vigilant in assessing maternal dietary intake during the second trimester. Individualized education should be provided about good sources of carbohydrates in meals for pregnant women who show weight gain below the recommended levels.


P < 0.001). In the multiple linear regression analysis, lower serum SHBG level was strongly correlated with a higher incidence of NAFLD, but not MS components. In logistic regression analyses, after adjusted for age, sex, duration of diabetes, smoking status, and alcohol use, the ORs and 95%CI for presence of MS was 2.26 (95%CI 1.91–2.68) and for presence of NAFLD was 6.36 (95%CI 4.87–8.31) with per one SD decrease in serum SHBG (both P < 0.001). In conclusion, lower serum SHBG is associated with a higher prevalence of NAFLD, compared with MS and other metabolic disorders, in T2D patients. NAFLD might be an important influencing factor for the association of circulating SHBG with MS in T2D patients.Metabolic syndrome (MS) and non-alcoholic fatty liver disease (NAFLD) have been identified as risk factors affecting serum sex hormone binding globulin (SHBG) levels. We conducted this cross-sectional study to delineate whether MS or NAFLD has more impact on circulating SHBG levels in type 2 diabetes (T2D) patients. Anthropometric and biochemical parameters including serums SHBG, testosterone (TT), liver enzymes, lipids, insulin, C-peptide and plasma glucose were measured. Regardless of the MS status, SHBG level was significantly lower in NAFLD patients than in non-NAFLD patients ( Epidemiological studies have found that serum SHBG level is altered in metabolic disorders, such as abdominal obesity, dyslipidemia, and insulin resistance4. Low serum SHBG has been considered as an independent predictive factor for metabolic syndrome (MS)6. However, several studies have highlighted the relationship between low SHBG with fatty liver. Our previous study has found that low serum SHBG, but not androgen, is independently associated with non-alcoholic fatty liver disease (NAFLD) in T2D patients7. A 9-month lifestyle interventional study has reported a significant correlation between magnetic resonance (MR) measured liver fat content and serum SHBG levels, but the relationship is independent of the changes in total body fat or abdominal fat mass8. Furthermore, a cross-sectional study has observed a significant association between the hepatic fat accumulation and circulating SHBG levels in men and premenopausal women, but no association between circulating SHBG and MS was observed9. However, whether MS or NAFLD has more impact on circulating SHBG levels has not been addressed.Sex hormone binding globulin (SHBG) is a glycoprotein made primarily in the liver10. Subjects with MS are usually with a high presence of NAFLD than those without MS11. Meanwhile, many common metabolic disorders of MS and NAFLD have been identified as factors tightly related to SHBG4. Therefore, the association between serum SHBG, MS and NAFLD is complex.MS and NAFLD share many metabolic abnormalities in glucose and lipid metabolism13 and its overexpression in NAFLD mouse models has been recently found to modulate hepatic lipogenesis14, we have reasoned that the apparent relationship between serum SHBG and MS may be mainly driven by the association of SHBG with NAFLD. Towards that end, we conducted this study aiming to delineate the relationship of serum SHBG with MS and NAFLD in T2D patients.A better elucidation for the association between serum SHBG with MS and NAFLD would help to understand their pathogenesis. Since SHBG is predominantly produced and regulated in the hepatocytes15. We excluded the subjects with acute or severe chronic diabetes complications, acute or chronic infections, hypo/hyperthyroidism, renal dysfunction, excessive alcohol consumption , autoimmune hepatitis or chronic viral liver disease, cholestasis or other metabolic/genetic liver disease, and the histories of taking corticosteroids, hormone, antiretroviral or anticancer drugs. A total of 1001 patients  were enrolled into the study. Of them, 198 were newly diagnosed as T2D according to the WHO criteria, 425 received oral hypoglycemic medicines, 181 received insulin therapy and 197 received both medications.This study was approved by the ethical committee of Nanjing Drum Tower hospital. Written informed consents were provided by all subjects prior to this study. All methods were performed in accordance with the ethical standards of the responsible committees for human experimentation and with the WMA Declaration of Helsinki. T2D patients who visited the Nanjing Drum Tower Hospital between September 2009 and December 2015 were sequentially enrolled into this retrospective study. T2D was defined based by World Health Organization (WHO) 1999 diagnostic criteria as fasting plasma glucose ≥7.0 mmol/l or 2-h plasma glucose ≥11.1 mmol/l 16.Diagnose of NAFLD was based on abdominal ultrasound performed by experienced ultra-sonographer after excluding other causes of chronic liver disease and excessive alcohol consumption as detailed above. Hepatic steatosis was diagnosed according to the following ultra-sonographic criteria: abnormal intensity and high-level echoes from the hepatic parenchyma, depths of echo penetration into of the liver, liver-kidney differences in echo amplitude and blurred liver vessel structure and abnormal visualization of diaphragm17: (1) abdominal obesity (waist circumference ≥90 cm for Asian men or ≥80 cm for Asian women); (2) at least two of the following four components: 1) triglycerides ≥150 mg/dl (1.7 mmol/L), or specific treatment for this lipid abnormality; 2) HDL cholesterol <40 mg/dl (1.03 mmol/L) for men or <50 mg/dl (1.29 mmol/L) for women, or specific treatment for this lipid abnormality; 3) systolic/diastolic blood pressure ≥130/85 mmHg or receiving drug treatment; and 4) fasting plasma glucose ≥100 mg/dl (5.6 mmol/L), or previously diagnosed T2D or receiving treatment.MS was diagnosed according to the 2005 IDF criteriaIn order to determine the relationship of SHBG with the complexity of MS, we divided patients into five subgroups, MS1, MS2, MS3, MS4, and MS5, according to the number of MS components (MS score).18.Anthropometric parameters of height, weight and waist circumference (WC) were measured using standard equipment and techniques. Blood was drawn in the morning after a 12-h overnight fast and was analyzed for alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), fasting plasma glucose , glycosylated haemoglobin , fasting serum insulin (F-INS), fasting C-peptide (F-CP), total testosterone (TT), and serum SHBG  at the central clinical laboratory of the hospital. Body mass index (BMI) was calculated as weight (in kilograms) divided by the square of height (in meters). The insulin resistance was calculated using the homeostasis model assessment method (HOMA-IR = fasting insulin*fasting glucose/22.5)2-test. One-way analysis of variance (ANOVA) followed by Bonferroni post hoc test was used to compare the difference of SHBG between NAFLD and non-NAFLD groups and MS score subgroups. Relationships between SHBG and metabolic parameters were performed using partial correlation analysis adjusted for age and sex. Multiple linear regression models were conducted for the independent variables which significantly related to SHBG in univariate analysis before. The binary logistic regression analyses were used to determine the effects of decreasing serum SHBG levels on prevalence of MS and NAFLD. Potential confounding factors such as age, sex, duration of diabetes, smoking status, alcohol use, BMI, WC, GGT, TG, HDL-C, HOMA–IR and TT, which have been reported in researches to influence MS and NAFLD incidence were taken into consideration in different adjustment models. The results were expressed as odds ratios (OR) and 95% confidence intervals (CI). All statistical analyses were performed using SPSS 20.0 software . P-value of <0.05 was considered statistically significant.Continuous data were expressed as means ± SD or standard error of the mean (SEM). Categorical data were expressed as percentages. Variables not normally distributed were log-transformed before analyses. Continuous data were tested with independent samples t-test or Mann–Whitney U test, as appropriate. Categorical variables were tested with Pearson χThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.P < 0.001). On the contrary, HDL-C in the NAFLD group was significantly lower than that in the non-NAFLD group (P < 0.001) (Table ).According to ultrasonic diagnosis, all T2D patients were divided into NAFLD group  and non-NAFLD group . 71.9% (n = 326) patients were diagnosed with MS in NAFLD group, and 40.1% (n = 220) patients were diagnosed with MS in non-NAFLD group. Variables of BMI, WC, ALT, AST, GGT, TG, FPG, F-INS, fasting C-peptide, and HOMA-IR in the NAFLD group were significantly higher, compared with the non-NAFLD group  nmol/L; MS group: 39.79 ± 0.98 vs. 23.91 ± 0.83 nmol/L; both P < 0.001]. However, the difference of serum SHBG levels between MS and non-MS subgroups was only statically significant in non-NAFLD group (P = 0.002), but not in NAFLD group (P > 0.05) . This analysis shows that the NAFLD condition contributed more to the SHBG reduction (~43% decrease) in both non-MS and MS patients, whereas the MS status contributed to a less degree of SHBG reduction (~10.3%) in non-NAFLD patients .To determine the association of SHBG with MS status, we divided all study subjects into groups with or without MS and divided them into five subgroups from M1 to M5 according to the number of metabolic components. As shown in Fig. 05) Fig. . This ants Fig. .Figure P for linear trend <0.001, one-way ANOVA), but not in NAFLD group . Mean levels of SHBG in each MS score subgroups of non-NAFLD were significantly higher than those in NAFLD (P < 0.001) .With the number of MS components increasing, serum SHBG levels decreased, with the linear trend statically significant in non-NAFLD group (01) Fig. .P < 0.05), whereas serum SHBG levels were not related to AST, TC, LDL-C or HbA1c (P > 0.05) (Supplementary Table ).Correlation analyses showed that, after adjusted for age and sex, serum SHBG levels were negatively associated with BMI, WC, ALT, GGT, TG, FPG, F-INS, fasting C-peptide, HOMA-IR, and positively associated with HDL-C (P = 0.007). When NAFLD being added into this regression model as an independent variable, a strong correlation was found between lower serum SHBG levels and higher NAFLD incidence with β and 95%CI was −0.295  (P < 0.001). Nevertheless, in this model, no independent relationship was found between the serum SHBG level and MS scores with β and 95%CI was −0.081  (P = 0.057)  and 95% confidence interval (CI) was −0.165  (P < 0.001). In model b, with further adjustment for BMI, WC, GGT (log-transformed), TG, HDL–C, and HOMA–IR, the SHBG related ORs for presence of both MS and NAFLD decreased slightly . Moreover, the additional adjustment for total testosterone (log-transformed) in model c did not obviously influent the related ORs of Model b. The related ORs and 95%CI for MS was 1.91  (P = 0.001) and for NAFLD was 5.23  (P < 0.001) . Thus, the decrease of SHBG exerts a larger impact on the presence of NAFLD than MS.Binary logistic regression analyses were used to determine the effects of decreased serum SHBG levels on the incidence states of either MS or NAFLD. To illustrate the independent relationship between serum SHBG and MS/NAFLD, we conducted the following adjustment models to eliminate the potential confounders. In model a, after adjusted for age, sex, duration of diabetes (quartiles), smoking status, and alcohol use, the ORs and 95%CI for presence of MS was 2.26  and for presence of NAFLD was 6.36  with per one SD decrease in serum SHBG (SD = 17.27 nmol/L) (both In the present study, we provide evidence that NAFLD is an influencing factor for the association of serum SHBG with MS in T2D patients. Firstly, low circulating SHBG is prevalent in NAFLD than in non-NAFLD patients, regardless of the MS status. Secondly, although circulating SHBG levels are associated with scores of MS in T2D patients, the association is no longer significant when NAFLD is included in the study. Thirdly, the decrease of circulating SHBG has a larger impact on the presence of NAFLD than MS.et al.9. In their study, ultrasound diagnosed fatty liver was shown to exert a significant influence on serum SHBG concentrations in men and in premenopausal women, while no association between serum SHBG and metabolic syndrome was found. Besides, our data support that fatty liver is perhaps an influencing factor for the association of serum SHBG level with MS in that when the parameter of NAFLD was added into our linear regression model, the association turned to be no longer statistically significant. This clinical finding is also supported by the animal study by Selva et al.19 that SHBG production is down-regulated in fatty liver due to the reduced expression of HNF-4a.Our finding is in agreement with a population-based cohort study by Flechtner-Mors per SD decrease of serum SHBG, the ORs for presence of NAFLD increased 5.1–6.3 folds, compared to 1.8–2.2 folds for MS. Association of SHBG with MS has been observed in many studies where NAFLD is not separated from MS6. Our study provides an explanation for the association in that large percentage of MS patients coexist with NAFLD and that NAFLD and MS share with impaired insulin sensitivity and lipid dyslipidemia20. Since the association is independent of many known confounding factors such as obesity, insulin resistance, and lipid disorders, it indicates that the association of SHBG with those metabolic traits is probably a consequence of NAFLD on SHBG levels (Fig. We also provide evidence that SHBG is more closely associated with NAFLD than MS. Although the result showed a correlation between SHBG and MS status, we found that the NAFLD condition contributed more to the lower SHBG, for that even in patients with all the five MS components, serum SHBG level was still higher in non-NAFLD group than that in NAFLD group Fig. . Further22, but these studies have not assessed the effect of SHBG on this association. Our studies indicated that serum SHBG, but not testosterone, is associated with fatty liver or other metabolic disorders. The mechanism for the link between NAFLD and SHBG level remains to be further illustrated23. Saez-Lopez et al.14 recently showed that SHBG plays a suppressive role in hepatic lipogenesis in that SHBG overexpression in NAFLD mouse model ameliorates liver fat accumulation. Hence, there appears a vicious feedback between NAFLD and SHBG in the liver: fat accumulation suppresses SHBG production and the resulting lower SHBG results in fat accumulation. More studies in this respect may lead to new therapeutic approach for NAFLD.Several studies have highlighted the significance of testosterone deficiency in pathogenesis of hepatic steatosisThe current study shows that serum SHBG is significantly associated with metabolic disorders of abdominal obesity, liver enzyme, blood lipids, and insulin resistance. However, SHBG levels are significantly lower in NAFLD patients than in non-NAFLD patients regardless of the MS status. Lower serum SHBG is more associated with a higher prevalence of NAFLD, compared with MS and other metabolic disorders. Hence, the reduction of SHBG level in MS and T2D subjects is probably driven by fatty liver.Supplementary Table S1


Capra pyrenaica). Despite several studies on the effects of mange on ibex, the pathological and clinical picture derived from sarcoptic mange infestation is still poorly understood. To further knowledge of sarcoptic mange pathology, samples from ibex were evaluated from histological, microbiological and serological perspectives.Sarcoptic mange has been identified as the most significant infectious disease affecting the Iberian ibex . Skin biopsies were examined at different stages of the disease for quantitative cellular, structural and vascular changes. Sixteen different non-dermal tissues of each ibex were taken for histological study. Acetylcholinesterase and serum amyloid A protein levels were evaluated from blood samples from ibex with different lesional grade. Samples of mangy skin, suppurative lesions and internal organs were characterized microbiologically by culture. Bacterial colonies were identified by a desorption/ionization time-of-flight mass spectrometry system (MALDI TOF/TOF).The histological study of the skin lesions revealed serious acanthosis, hyperkeratosis, rete ridges, spongiotic oedema, serocellular and eosinophilic crusts, exocytosis foci, apoptotic cells and sebaceous gland hyperplasia. The cellular response in the dermis was consistent with type I and type IV hypersensitivity responses. The most prominent histological findings in non-dermal tissues were lymphoid hyperplasia, leukocytosis, congestion and the presence of amyloid deposits. The increase in serum concentrations of acetylcholinesterase and amyloid A protein correlated positively with the establishment of the inflammatory response in mangy skin and the presence of systemic amyloidosis. A wide variety of bacterial agents were isolated and the simultaneous presence of these in mangy skin, lymph nodes and internal organs such as lungs, liver, spleen and kidney was compatible with a septicaemic pattern of infection.The alteration of biomarkers of inflammation and its implication in the pathogenesis of the disease and development of lesions in non-dermal tissues and septicaemic processes are serious conditioners for the survival of the mangy ibex. This severe clinical picture could be an important factor when considering the decision to eliminate animals that exceed a certain disease threshold from a population. Sarcoptes scabiei that affects both humans and animals worldwide [Capra pyrenaica), some of which have led to high mortality rates [Sarcoptic mange is a highly contagious infection of the skin caused by the burrowing mite orldwide . It is rorldwide –4. Severty rates , 6. AlthClinical signs of sarcoptic mange generally include a combination of alopecia, scaling and crusting . HoweverS. scabiei.Despite the availability of wide-ranging information on the pathology of sarcoptic mange in the Iberian ibex –17, therC. p. hispanica)  were captured, 33 in the Sierra Nevada Natural Space (SNNS) , and 6 in the Sierras de Cazorla, Segura y Las Villas Natural Park (SCSVNP) . Initial IgG levels against S. scabiei were measured by an enzyme-linked immunosorbent assay (ELISA) developed for alpine chamois (Rupicapra rupicapra) in order to exclude ibex that had previously been in contact with the disease [ad libitum access to food and water [Thirty nine Iberian ibex  were selectively harvested as part of a management program devoted to controlling both ibex density and the spread of sarcoptic mange in the SNNS.All ibex were captured using a rifle and anaesthetic darts with a combination of ketamine (3 mg/kg) and xylazine (3 mg/kg) .S. scabiei, and the remaining 14 ibex being left to act as controls. A 2cm2 skin fragment from a naturally S. scabiei-parasitized wild ibex from the SNNS was attached with elastic bandages to the previously shaved inter-scapular region to induce contact between the mites and the host skin. In order to determine the density and therefore the number of mites infesting each ibex, the density of mites was calculated in skin pieces adjacent to those used for the infestation. In these adjacent skin samples, mites were counted with a stereomicroscope after overnight digestion in 5% KOH solutions at 40 °C [After an adaptation period, 25 of the 39 ibex (22 from SNNS and three from SCSVNP) were experimentally infested with at 40 °C .The resuThe experimental period lasted for 150 days after infestation. Experimentally and naturally infected ibex were visually assigned to one of the following three categories defined according to the percentage of skin surface affected: healthy (mange-free ibex), mild , and severe (consolidation and chronic stages with lesions on more than 50% of the host skin surface) .Blood samples and skin biopsies were collected at 26, 46, 103 and 150 days post-infestation (dpi). Blood samples (20 ml) were taken from each ibex  by jugular venipuncture, and kept at 4 °C in a cooling box until reaching the laboratory. Adjacent skin biopsies were taken after shaving the inter-scapular region using an 8 mm diameter punch biopsy tool . In the control group, skin samples were only collected at 103 dpi. To do so, each ibex was separated into a handling crush for subsequent physical restraint (blindfolding and limb immobilization) and a local anaesthetic was administered . After collecting the skin samples, each animal was treated with an antiseptic spray. Each biopsy was placed into 10% neutral buffered formalin for 48–72 h, and then transferred to 60% ethanol and stored at 4 °C until histological analysis.Nineteen of the 25 ibex experimentally infected were euthanized at 150 dpi due to their severe mange infections. Naturally infected animals  were euthanized at the time of capture. Before euthanasia, blood samples were collected from each ibex. Animals were anaesthetized by intramuscular injection with a mixture of xylazine (3 mg/kg) and ketamine (3 mg/kg), and euthanized with T-61® .Scabietic ibex were necropsied under strict hygienic conditions immediately after death. Gross pathologic examination was performed on all animals and organs following a standard protocol. The following samples were collected from each ibex for histological study: superficial lymph nodes (SLN) draining the mangy skin lesions , intracavitary lymph nodes (ILN) , central nervous system, tongue, thyroid gland, skeletal muscle, heart (papillary muscle), lungs , liver, kidney, adrenal gland, spleen, pancreas, small intestine (ileum), large intestine (colon), ovary and testicle. All samples were fixed in a similar way to the skin biopsies. For the microbiological studies, the following samples were taken and stored separately in sterile tubes: skin , suppurative lesions, lungs, liver, spleen and kidney.Skin biopsies and the rest of the fixed non-dermal tissues were briefly washed with 10% phosphate buffered saline (PBS) solution and embedded in paraffin wax . Serial 5 μm sections from all specimens were mounted on glass slides , stained with haematoxylin and eosin (HE) and analyzed by light microscopy.Skin sections were examined for quantitative cellular, structural and vascular changes Table . Epidermg for 10 min and stored separately at -82 °C. Serum SAA concentrations (μg/ml) were quantified as the mean value of two measurements using a commercially available ELISA kit . AChE activity (μmol/ml*min) was measured using acetylthiocholine as a substrate [Within 24 h of collection, serum was obtained by centrifugation at 4750× ubstrate .In the laboratory, samples were processed in biological safety cabinets within 12 h after collection. Twenty grams of each tissue and/or pathological material was placed in a sterile airtight bag with 3 ml of sterile 10% PBS and homogenized for 5 min . An aliquot of 800 μl of the resulting homogenate was added to a sterile cryotube together with 200 μl of glycerol. The cryo tubes were stored at -20 °C until microbiological analysis.Samples were cultured on TSA and Columbia agar plates supplemented with 5% sheep blood  and incubated aerobically at 37 °C for 24–48 h. Cells from representative bacterial pure and freshly-cultivated colonies were re-suspended in 300 μl of HPLC-grade water and mixed vigorously prior to the addition of 900 μl of HPLC-grade ethanol. Subsequently, an acetonitrile/formic acid extraction protocol was performed following the manufacturer’s instructions . After protein extraction, 1 μl of each isolate extract was spotted onto a 384-spot polished steel target plate, left to dry at room temperature and then overlaid with 1 μl of α-cyano-4-hydroxy-cinnamic acid (HCCA) matrix. All isolates were analyzed in a Bruker Daltonik UltrafleXtreme MALDI TOF/TOF (desorption/ionization time-of-flight mass spectrometry) system, which obtained one spectrum per sample used to assess the suitability of this spectrometric approach for identification at species level. Each spectrum was acquired using FlexControl software (Version 3.4) in automatic mode in a random sampling pattern. The identification of all the clinical isolates in this study was performed by MALDI Biotyper Real Time Classification software. The reliability of the identification was evaluated from the log (score) values, calculated with the MALDI Biotyper software mentioned above.post-hoc comparison test with Bonferroni correction was used to determine the differences between the groups analyzed. A Spearman’s rank correlation coefficient test was applied to establish the coefficients between the different variables analyzed. To compare the frequency of lesions observed in non-dermal tissues between experimentally exposed and naturally infected animals, the Fisher’s exact test was used. P-values < 0.05 were considered to be statistically significant.The results of the histopathological changes and serum SAA and AChE concentrations were reported as median and standard deviations, calculated using routine descriptive statistical procedures. The Kolmogorov-Smirnov test was used to assess data normality. Non-parametric statistical methods were used to compare groups. A Mann-Whitney U-test was employed to compare the control group with the clinical stage of the exposed groups. To evaluate the response of the different parameters in term of the time of exposure and mange status of the different infested groups, Friedman tests with repeated measures were performed. In a second step, a Wilcoxon signed rank All statistical analyses were performed with the R software version 3. 3. 1  .The clinical outcome and evolution of the infested ibex changed during the infestation period. Sixteen infested ibex progressed to severe stages of the disease. However, seven ibex, all of which from SNNS, only developed a self-limiting clinic process, with mange lesions on less than 50% of their skin surface, and showed evident signs of recovery. All infested ibex from SCSVNP evolved to severe stages of the disease. Until 46 dpi, all ibex developed localized lesions in the inoculation zone (inter-scapular area) and facial area (mildly affected). From 103 dpi onwards, in all ibex except those with a self-limiting clinic process, mange lesions were generalized, extending over the lumbar region and the ventral part of the abdomen and limbs (severely affected). Animals showed pruritus throughout the disease and intermittently scratched themselves. In the most severe clinical stages, both naturally and experimentally infested ibex showed scales, marked lichenification, alopecia, crusts, dermal fissures in limbs and moderate inflammation of eyelids and lips  higher than those of the control group , increasing significantly (post-hoc test: P = 0.012) between 46 and 103 dpi. In the final stage the values decreased and returned to the levels of the early stages of the disease. The number of eosinophilic and serocellular crust foci were correlated (r(353) = 0.546, P < 0.0001 and r(384) = 0.402, P = 0.0012, respectively) with the presence of mites/burrows, but values were significantly  lower by 150 dpi. Acanthosis  and rete ridges  showed variation along the different dpi. These reached their maximum number  by 26 dpi and then decreased significantly  by 46 dpi, remaining unchanged during the rest of the disease. Likewise, acanthosis was correlated (r(394) = 0.329, P = 0.031) with the presence of mites/burrows. Signs of cytotoxicity such as spongitic oedema, apoptotic keratinocytes and exocytosis foci increased significantly (post-hoc test: P < 0.0001) up to 46 dpi  during the more severe stages (from 103 dpi onward)  lower than those that progressed to severe stages (103and 150 dpi), and were even lower than those observed during the first days of the disease (26 dpi).Histopathological changes in mangy skin between dpi were compared and shown in Table oup Fig. . For thedpi Fig. , and therd) Fig. . In ibexFr test: χ2 = 90.14, df = 2, P = 0.036), remaining unchanged until 150 dpi, at which point their number fell significantly (post-hoc test: P = 0.044). The number of lymphocytes (r(343) = 0.586, r(346) = 0.584, r(286) = 0.640), eosinophils (r(431) = 0.284, r(398) = 0.324, r(452) = 0.205), mast cells (r(277) = 0.763, r(281) = 0.699, r(149) = 0.811) and neutrophils (r(293) = 0.699, r(354) = 0.566, r(366) = 0.515) was significantly correlated (P < 0.0001) with the presence of spongiotic oedema, exocytosis foci and apoptotic cells respectively. With the exception of plasma cells , the number of lymphocytes, mast cells, eosinophils and neutrophils was significantly  higher during the first 46 dpi, but then decreased significantly (P < 0.001). The number of plasma cells was low in all the stages analyzed. In animals with self-limiting lesions, the number of inflammatory cells decreased significantly (post-hoc test: P < 0.0001) in relation to the first 46 dpi. However, except for neutrophils (post-hoc test: P = 0.019), these values showed no significant differences (post-hoc test: P = 0.394) with the ibex that reached the most severe stages of the disease.In the dermis, the number of sebaceous glands also varied according to dpi  were found between the lesions observed in the two groups.The histopathological findings in the non-dermal tissues are detailed in Table W = 78, P = 0.0037) in the ibex with localized lesions  and, by contrast, decreased in severely infected animals  (Table r(374) = 0.531, P = 0.032), eosinophils (r(388) = 0.343, P = 0.042), mast cells (r(363) = 0.398, P = 0.0076) and neutrophils (r(452) = 0.252, P = 0.011) found in mangy skin lesions. SAA concentrations only increased significantly  in the most severe stages of the disease (Table r(496) = −0.184, P = 0.0087) with AChE concentrations. At the time of euthanasia, serum SAA levels were positively correlated (r(282) = 0.719, P < 0.0001) with the number of organs that showed reactive amyloidosis  [Nyctereutes procyonoides) [Vombatus ursinus) [Lynx lynx) [The macroscopic and histological skin lesions observed in mangy ibex closely match the classical descriptions of sarcoptic mange in wild and domestic animals , 3. The  vulpes) , raccoononoides) , wombatsursinus)  and Euranx lynx) . Howevernx lynx) , which mnx lynx) . We thusnx lynx) . The hypS. scabiei infection alters the cholinergic system and thereby contributing to the establishment of the local inflammatory response and the pathogenesis of the disease.Cholinesterases have been reported as having the capacity to increase local and systemic inflammatory events in various pathological states . In our The most prominent histological findings in non-dermal tissues were lymphoid hyperplasia, leukocytosis, congestion, and the presence of amyloid deposits Table . SystemiStaphylococcus was the dominant genus and infrequent species such as S. nepalensis were isolated. Infections by these bacteria are often secondary to a primary skin disease that provides the conditions for these commensal bacteria to proliferate [Psoroptes ovis with S. aureus causes a specific response of IgG antibodies against S. aureus antigens, suggesting that these bacteria may play some role in the immune-pathogenesis of mange [Staphylococcus have been isolated in mite burrows and in their faecal pellets [A wide variety of bacterial agents were isolated in mangy ibex Table . The simliferate , 42, 43.liferate , 45. Furof mange . The mit pellets . However pellets , 48.In humans, especially in children, scabies-associated skin bacterial infection is a common risk factor for systemic complications such as acute post-streptococcal glomerulonephritis and sometimes rheumatic heart disease , 50. HowIn this study we provide a complete description of sarcoptic mange in the Iberian ibex through a description of its effects in naturally and experimentally infested animals, combining a serological, microbiological and histological approach. The alteration of biomarkers of inflammation and its implication in the pathogenesis of the disease and development of lesions in non-dermal tissues and septicaemic processes are serious conditioners for the survival of mangy ibex. These findings could be relevant in the management of affected ibex populations, since this could contribute to decisions on the elimination of animals that exceed a certain disease threshold from a population. In turn, our work provides a solid basis for further investigation of other factors that influence the pathogenesis of this disease.


In vitro activity of DI was determined by phagocytosis activation using flow cytometric analysis of fluorescence-labeled latex bead uptake, expression of immune-modulating 84 genes using PCRarray, and tumor killing using coculturing with immune cells. Anti-PCa activity of DI in vivo was examined in male TRAMP mice. In vitro DI stimulated phagocytosis and expression of a panel of inflammatory mediators  in cultured macrophages and increased tumor killing of both macrophages and TRAMP mouse splenocytes. Daily intake of this herbal product significantly suppressed the tumor size (P = 0.0368) with lower histopathologic scores (P = 0.0364) in TRAMP mice, which were associated with an increase in both splenocyte cytotoxicity against tumor cells and numbers of CD8 T cells, macrophages, and dendritic cells in the spleens in vivo. In conclusion, daily intake of DI prevents PCa progression in TRAMP mice, suggesting the possible effectiveness of the immunostimulant herbal products on prevention of PCa progression after diagnosis of low-risk PCa.Low-risk prostate cancer (PCa) does not require immediate treatment, but PCa progression after years of active surveillance will need the treatment. This study was to test the efficacy of immunostimulant Deep Immune (DI) in controlling PCa progression. DI is an extract of eight different medicinal herbs. In developed countries such as the United States of America and Canada, prostate cancer (PCa) is the most common cancer in men and is one of the leading causes of cancer death , 2. Once in vitro and/or in vivo . The mice in extract group received the herbal DI extract-containing drinking water for 3 months as the mice in control group. All the mice in these three groups were kept in a conventional room of the animal care facility before euthanasia .Three experimental groups were included in this study: onset  for histological grading of PCa. The disease grading of each sample was performed according to the pathological characters of prostatic intraepithelial neoplasia (PIN) and adenocarcinoma as previously described  in a bli4Cl, 1.0 mM KHCO3, 0.1 mM EDTA, pH 6.8). The phenotypes +, CD11b+, and Mac3+ cells) of the splenocyte population were determined by fluorescence-activated cell sorting (FACS) analysis using fluorescent-labeled rat monoclonal antibodies  antibodies following the manufacturer's protocol . Briefly, cells were probed with each fluorescence dye-conjugated antibody in the dark for 30 min at 4°C. After washing with PBS, the positively stained cells were detected by using flow cytometry and further quantified using FlowJo software (Tree Star Inc.).A single cell suspension of splenocytes was prepared by gently crushing the spleens of mice in phosphate-buffered saline (PBS) in a cell strainer , followed by removal of erythrocytes by a brief incubation (~4 min) with lysis buffer (0.15 M NHt-test (nonparametric) was performed as appropriate for comparing the data between groups. A P value of ≤0.05 was considered significant.Data were presented as either mean ± standard derivation (SD) or mean ± standard error of the mean (SEM). Analysis of variance (ANOVA) or two-tailed Data (average of 3 separate measurements) from the chemical composition analysis of DI using spectrophotometric methods showed that the DI extract contained 15.95% (w/w) of total sugar including polysaccharides, 29.85% (w/w) of triterpenoids saponins, 0.15% (w/w) of flavonoids, and 1.15% (w/w) of protein, suggesting that the major components of this product were triterpenoids and polysaccharides/sugar.− ionization modes (data not shown) did not show as many peaks as on ESI+, and, by ESI+, a total of 14 ion peaks were clearly identified . The experiment on ESIentified , and thehinensis .μg/mL) was able to activate the phagocytosis of macrophages. As shown in P = 0.0288, one-way ANOVA, n = 6), and 25 μg/mL resulted in the highest level of phagocytosis (12.32 ± 0.75) as compared to 9.64 ± 0.3 in untreated controls .The activation of anti-tumor-cytotoxic activity of macrophages has been considered an effective immunotherapy against tumor progression , and actμg/mL herbal extract-stimulated RAW264.7 cells compared to untreated control  were significantly co-upregulated and only one (il23a) was downregulated   .μg/mL of the extract . The activation of antitumor immune response by the DI product was further confirmed in TRAMP splenocytes. As shown in μg/mL of extract and an increase to 40.65 ± 10.9 with 50 μg/mL and 31.27 ± 7.99 with 100 μg/mL . Taken together, this data demonstrates a stimulation of anti-PCa cytotoxity of immune cells, including macrophages, by the DI product in cocultures.To evaluate the antitumor activity of the DI product-activated immune cells, a cytotoxicity assay using cocultures was performed. As shown in  in vivo immune stimulation by the DI product against PCa development was tested in male TRAMP mice. After 12 weeks of treatment, as shown in n = 6) in mice before or at the beginning of treatment (Onset) to 1.671 ± 0.5124 g (n = 12) without any treatment (Control) , but tumors did not grow in mice receiving the herbal extract in their drinking water, which is indicated by the fact that the tumor weight  in extract-treated mice was not significantly different from that in the “onset” group , or the tumor growth was significantly suppressed as compared to those in control or untreated group .The efficacy ofn = 18) was significantly lower than 3.887 ± 0.3836 (n = 12) observed in the control group . We did not have histological data of the tumors from the “onset” group. Taken together, oral administration of the herbal extract significantly suppressed PCa development in TRAMP mice.Tumor differentiation of PCa in these mice was graded by histology at the end of treatment. +), NK cells (NK1.1+), macrophages (Mac-3+), and dendritic cells  decreased in mice after 3 months of tumor growth in control group as compared with that in “onset” group, and these decreases were not seen in mice receiving the DI product as no difference in the percentage of these effector cells was seen between onset and extract-treated groups. These data suggested that daily intake of DI product specifically maintained these effector immune cells systemically.To verify if the tumor suppression by DI product treatment was associated with an increase in anti-tumor immunity in mice, the proportion of effector immune cells in the spleens and their tumor-killing activity were examined. As indicated in P = 0.0005, two-way ANOVA, n = 6), and herbal extract treatment significantly stimulated splenocyte cytoxicity against tumor cells , indicating that the antitumor immune activity of these mice could be ranked in the order of high to low as follows: extract-treated > onset > untreated control.The tumor-killing activity of these splenocytes was further examined in cocultures with TRAMP-C2 cells at different ratios. As shown in  G. lucidum [ A. membranaceus [Cancer immunotherapy is a therapeutic approach by which natural antitumor immunity is activated or restored and has been approved for the treatment of many types of cancer, including melanoma, squamous cell lung cancer, and metastatic renal cell carcinoma , and it  lucidum , 42, andranaceus , 44. TheA. membranaceus, C. pilosula, G. lucidum, E. senticosus, L. lucidum, S. chinensis, A. macrocephala, and Glycyrrhiza spp.) with ethanol and water   . In vivo of mice , implyinDo we have a target of an immunotherapy or immunostimulatory strategy for controlling the progression of low-risk PCa in patients? By immunohistochemical methods, DCs (or Langerhans cells) and HLA class II-positive macrophages are mostly identified only in prostate carcinoma of a low grade (grades 1-2) . ShimuraIn conclusion, data from this experimental study indicate that herbal products (like the DI product) containing different immunostimulant components and activating different immune cells, particularly macrophages or DCs offer promise as agents for secondary prevention of PCa from progression after PCa diagnosis, particularly for those patients with low-risk PCa and on AS. Each herb is added to this particular polyherbal formulation on the basis of its traditional uses. There are, however, limited data in the literature showing the immunoactive ingredients, their mechanisms of action, and their safety and efficacy in human subjects. Further studies of the efficacy of this herbal product or similar, modified products against PCa progression are required using a human preclinical model and in human subjects.