HIV infection is known to be associated with cardiometabolic abnormalities; here we investigated the progression and causes of these abnormalities. Three groups of participants were recruited: HIV-negative subjects and two groups of treatment-naïve HIV-positive subjects, one group initiating antiretroviral treatment, the other remaining untreated. Intima-media thickness (cIMT) increased in HIV-positive untreated group compared to HIV-negative group, but treatment mitigated the difference. We found no increase in diabetes-related metabolic markers or in the level of inflammation in any of the groups. Total cholesterol, low density lipoprotein cholesterol and apoB levels were lower in HIV-positive groups, while triglyceride and Lp(a) levels did not differ between the groups. We found a statistically significant negative association between viral load and plasma levels of total cholesterol, LDL cholesterol, HDL cholesterol, apoA-I and apoB. HIV-positive patients had hypoalphalipoproteinemia at baseline, and we found a redistribution of sub-populations of high density lipoprotein (HDL) particles with increased proportion of smaller HDL in HIV-positive untreated patients, which may result from increased levels of plasma cholesteryl ester transfer protein in this group. HDL functionality declined in the HIV-negative and HIV-positive untreated groups, but not in HIV-positive treated group. We also found differences between HIV-positive and negative groups in plasma abundance of several microRNAs involved in lipid metabolism. Our data support a hypothesis that cardiometabolic abnormalities in HIV infection are caused by HIV and that antiretroviral treatment itself does not influence key cardiometabolic parameters, but mitigates those affected by HIV. Cells were then incubated for 18 h in serum-free RPMI-1640 containing 4 μM LXR agonist TO-901317 . Cholesterol efflux was performed using 1.1% apoB-depleted plasma for 2 h. ApoB-depleted plasma was obtained after precipitation of apoB-containing lipoproteins with Dextran Sulfate  as previously described [Cholesterol efflux assay was performed as previously described . Brieflyescribed .RNA from plasma (400 μl) was extracted using the Qiagen miRNeasy mini kit with the use of TRIzol-LS (ThermoFisher) for organic phase separation and was analysed by an Agilent 2100 Bioanalyzer using Small RNA Chips (Agilent Technologies). Small RNA libraries were constructed from total isolated RNA using the Ion Total RNA-Seq Kit V2  and ligated to adapters containing a unique index barcode according to the manufacturers’ protocol. The yield and size distribution of the small RNA libraries were assessed using the Agilent 2100 Bioanalyzer instrument with the DNA 1000 chip (Agilent Technologies). Equally pooled libraries were prepared for deep sequencing using the Ion Chef system (Life Technologies) and sequenced on the Ion Torrent Ion S5 using Ion 540 chips (Life Technologies). Pre-processing of reads, removal of adapters and barcodes were performed using the Torrent Suite (v.5.8.0). Sequences were analyzed for quality control (FASTQC), aligned to the Human genome (HG19) using the Torrent Suite, and files transferred to Partek Genomic Suite and Flow  for mapping against miRBase V.20 and normalization to reads per million reads (RPM). miRNAs identified with at least 30 RPM were used for further analysis on Partek Genomic suite which included statistical analysis and hierarchical clustering.Descriptive statistics (mean ± SD) were calculated for all the variables of interest at baseline. Longitudinal differences between and within groups for primary and secondary outcomes were assessed using mixed-models for repeated measures (MMRM). The MMRM model included group, time point, group by time point interaction, age, sex, BMI, as well as adjustment for baseline measurements by including baseline as a covariate. The model used an autoregressive variance-covariance structure to model within-individual errors. This model was used to analyse all outcomes. Correlations between outcomes were assessed by Pearson Product Movement correlation. Bonferroni correction was performed to adjust for multiple comparisons. Results were reported as mean ± SEM unless indicated otherwise. Statistical analyses were performed using Stata 13 . Sample size calculations for this study were based on previous evidence for primary outcome measures  .Three groups of participants were recruited and investigated in this study. At the time of recruitment, the first group consisted of 27 HIV-negative subjects (control group). The second group consisted of 19 HIV-positive treatment-naïve participants who remained untreated for the duration of the study (36 months) (untreated group), while the third group consisted of 41 HIV-positive treatment-naïve patients who initiated treatment with an NNRTI-based regimen at the beginning of the study and continued treatment for the duration of the study (treated group). There were losses in follow up in all three groups during the course of the study . The numBaseline characteristics of the participants are shown in At baseline, there was no difference in CD4+ T cell counts or percentages between both HIV-positive groups, however, there was significantly higher viral load in “treated” group ; the latversus baseline), and no further rise was observed after 2 and 3 years (versus baseline), and there was no statistically significant difference versus the control (versus baseline and 1 year).Progression of atherosclerosis was assessed by monitoring changes in cIMT. There was no statistically significant difference in mean cIMT between the groups at baseline. In HIV-negative subjects cIMT rose slightly after 1 year  levels were similar to those of total cholesterol, with no difference between the groups at baseline. A gradual increase in mean plasma LDL-C in the HIV-negative group  was found, a moderate increase in LDL-C levels was observed in the HIV-positive treated group  . There wAt baseline, mean plasma levels of high density lipoprotein cholesterol (HDL-C) and apolipoprotein A-I (apoA-I) in the HIV-positive groups were lower compared to those in HIV-negative subjects ; p<0.05.We used non-denaturing gradient gel electrophoresis to analyse changes in the distribution of apoA-I among HDL particles of different sizes between baseline and after 3 years of follow up. We found no difference between the groups at baseline, but a significant increase in proportion of small HDL3b and HDL3c particles at the expense of large HDL2a particles in HIV-positive untreated patients when compared to the other two groups Figs .versus 2 and 3 years). There was statistically significant difference between the HIV-positive treated and HIV-negative groups after 3 years of follow up . There was no difference in HDL functionality between the groups at baseline . HDL funollow up . We alsoollow up . Similarollow up , p<0.01,ollow up .There was no difference in plasma concentration of lecithin cholesterol acyltransferase (LCAT) between the groups or within the groups during follow up . Plasma We and others have previously suggested that the effects of HIV on lipid metabolism may be mediated in part through differences in microRNAs released into bloodstream , 29. To Raw sequencing reads were aligned to the human genome (HG19) and mapped to miRBase V.20. Reads were then normalised to reads per million (RPM) and miRNA species with greater than 30RPM were used for ANOVA analysis. Significantly expressed miRNA expressing greater than 1.5 fold changes and p-value < 0.05 are shown here. Red indicates high expression and blue indicates low expression.versus CD4+ T cell count and HIV viral load. For this analysis we combined all data for both groups of HIV-positive patients. We found a statistically significant negative association between viral load and plasma levels of total cholesterol , LDL cholesterol , HDL cholesterol , apoA-I  and apoB . We also found a negative association between viral load and cIMT , but this was mainly due to a sharply decreased viral load combined with modest rise in IMT in treated HIV-positive patients. We found a statistically significant positive association between CD4+ T cell count and proportion of HDL3c particles and combined HDL3 (HDL3a+HDL3b+HDL3c) , and a negative association between CD4+ T cell count and proportion of combined HDL2 (HDL2a+HDL2b) particles .To investigate an association between the severity of HIV infection and changes in surrogate markers of atherosclerosis or metabolic parameters, we analysed correlations between all metabolic parameters and IMT In this study, we investigated metabolic dysfunction and atherosclerosis in people newly diagnosed with HIV infection who commenced antiretroviral therapy (ART) or remained untreated for 3 years. This study was performed prior to the recommendation that all HIV-positive patients commence ART immediately after HIV diagnosis regardless of CD4 cell count. A significant rise in cIMT was observed in untreated HIV-infected patients after 2 years. In uninfected group, there was a modest rise in cIMT after 1 year, which did not progress further, and in treated patients a modest rise was seen after 3 years. This finding indicates that progression of atherosclerosis, as assessed by changes in cIMT, seen in HIV-positive patients, was mitigated by ART. This is consistent with a suggestion that HIV infection itself, rather than side-effects of ART, is a major cause of elevated cardiovascular risk in HIV-positive patients , 30. It Analysis of diabetes markers, plasma glucose, insulin and HbA1c levels as well as HOMA indices, showed no significant increase in progression to diabetes related to HIV infection, ART or lifestyle factors. This is in contrast to several reports showing increased risk of diabetes in HIV-positive patients , 33; theWe found a consistent difference in plasma levels of total cholesterol, LDL cholesterol and apoB between HIV-negative and HIV-positive participants. Hypocholesterolemia in untreated HIV-positive patients has been reported previously , 35 whilConsistent with findings from our and other laboratories , 37, 38,Relative to control group, the HIV-infected groups had higher prevalence of smoking, recreational drug use and lower prevalence of alcohol consumption, lifestyle factors that can affect many parameters measured in this study. However, the two HIV-positive groups were similar for these lifestyle factors and most differences seen in HIV-infected untreated group were not seen in HIV-infected treated group over the course of the study suggesting that the differences between the two HIV-infected groups were unlikely to be due to these lifestyle factors.An interesting finding of this study is the effect of HIV infection on plasma microRNA profile. Three most strongly affected microRNAs were found to regulate pathways related to the development of atherosclerosis and metabolic dysfunction. MiR-27 plays a prominent role in lipid metabolism: it is one of the key regulators of the expression of ABCA1 and LDL receptor , 41 and This study has several important limitations. First, the group size was limited, especially that of HIV-positive untreated group. Evolving guidelines demanded initiation of treatment at earlier stages of the disease, depleting this group as the study progressed and introducing a bias by removing patients with more rapid progression of the disease from the untreated group. Thus, negative findings of this study should be treated with caution. Second, we did not differentiate between different treatment regimens. Treatment regimens were determined by the treating physicians and very few patients in HIV-positive treated group received identical regimens; moreover, regimens were frequently changed during the follow up period. Finally, it is important to recognize that cardiometabolic co-morbidities may take more than 3 years to develop and their development may depend on the length of the period between the actual infection, diagnosis and commencement of ART.Overall, this study demonstrates that HIV infection is associated with disturbances of several aspects of cholesterol metabolism and with advancement in the progression of atherosclerosis. Both of these effects are most likely caused by the virus itself. Modern anti-retroviral therapy had mitigated most of the cardiometabolic effects of HIV, at least in short-term, and had no adverse contribution to the cardiometabolic risk. Lifestyle factors also did not have a significant contribution to the cardiometabolic risk.S1 FileSequencing database of miRNA in plasma of study subjects.(XLSX)Click here for additional data file.S2 FileManuscript data.(XLSX)Click here for additional data file.


Based on tail types, Hulun Buir sheep were divided into two lines including small and big fat-tailed, but these two lines have similar genetic background. In this study, we investigated the morphology and transcription level differences of tail fat between these two lines. The RNA-seq analyses indicated several differentially expressed genes when compared between sexes or two tail sizes. Interestingly, we also found an obvious sex difference in the fat metabolism in Hulun Buir sheep. Two different co-expression networks were only shown either in male or in female sheep. Our findings will provide theoretical background in understanding the genetic mechanism of fat deposition in sheep.Hulun Buir sheep of similar genetic background were divided into two lines based on tail types: Small- and big fat-tailed. To explore the molecular mechanism of fat deposition in sheep tails, we firstly evaluated the morphology and transcription level differences of tail fat between these two lines. RNA-Seq technology was used to identify differentially expressed genes (DEGs) in phenotypic extremes of tail sizes. Five comparisons were performed taking into account two factors, sex and tail type. We screened out 373 DEGs between big-tailed and small-tailed Hulun Buir sheep, and 775 and 578 DEGs between two types of tails in male and female sheep, respectively. The results showed an obvious sex difference in the fat metabolism in sheep based on gene ontology (GO), pathway, and network analyses. Intriguingly, there were two different co-expression networks only respectively shown in male and female sheep, which were insulin-related network acting on upstream pathways and PPARG-related network effect in downstream pathways. Furthermore, these two networks were linked by a classic pathway of regulating adipogenesis. This is the first study to investigate the sex differences of fat metabolism in domestic animals, and it demonstrates a new experimental way to study fat metabolism. Our findings will provide theoretical background in understanding the tail-size phenotype in sheep and can be exploited in breeding small-tailed sheep. It is well known that distributions of body fat influence the state of human health. Fat tends to be accumulated on the buttocks in women vs. in the abdomen in men. One perspective from the Tulane University School of Medicine suggest that sex differences in metabolism should be studied in both males and females as physiological systems are not fundamentally the same in two sexes . PreviouIn sheep, fat is deposited in specific positions including tails or rumps. Sheep can be classified into five types based on size of the tail: Short fat-tailed sheep, long fat-tailed sheep, short thin-tailed sheep, long thin-tailed sheep, and fat-rumped sheep . When feThe fat-tailed or fat-rumped sheep have been generated through a long breeding history after both natural and artificial selection. In the past, when food was scarce, fat-tailed sheep had been developed as man preferred foods that were high in calories ,12. HoweHulun Buir sheep, a Chinese indigenous sheep breed, has two types of tails. One is referred to as the “small fat-tailed” line (STH). Another is Hulun Buir big fat-tailed sheep, which is also called the “Barag” line (BTH). Both these types of Hulun Buir sheep belong to the fat-tailed type. However, the tail of the Barag line is significantly larger than that of the STH line . TherefoRNA sequencing is a high-throughput next-generation sequencing technology to survey, characterize, and quantify the transcriptome of a tissue. It provides a genome-wide sequence readout of a transcriptome. The objective of this study was to investigate the differences in gene expression affecting fat metabolism in adipose tissue in Hulun Buir sheep with different tail sizes and sexes using RNA sequencing (RNA-seq) technology. Our findings uncover the genetic mechanism underlying fat deposition in sheep tail, and the information can be exploited in future breeding in sheep.All of the animal experimental procedures were performed in strict accordance with the guidelines proposed by the China Council on Animal Care and the Ministry of Agriculture of the People’s Republic of China. All of the animal experiments were approved by the Chinese Academy of Agricultural Sciences .One hundred and fifty individuals each were selected from small- and big-tailed lines from ~2000 Hulun Buir sheep at approximately 6-month age. All these sheep were maintained under grazing condition in Hulun Buir grassland in Inner Mongolia Autonomous Region, China. Their appearances and shapes completely conformed to breed characteristics of Hulun Buir sheep and had healthy body conditions. Unrelated animals (as far as possible) with birth date records were sampled. Tail fat weights were measured after slaughter and about 8 mL of blood was collected in an EDTA-containing vacutainer and stored in liquid nitrogen (−196°). According to the tail fat weights, six sheep from each of the two lines  were selected with extremes of the phenotypic values. These 12 sheep can be further classified into 4 groups (3 in each) based on tail types and sex: Female big-tailed Hulun Buir sheep (FBT), male big-tailed Hulun Buir sheep (MBT), female small-tailed Hulun Buir sheep (FST), and male small-tailed Hulun Buir sheep (MST). The tail fat tissues were elaborately resected from these 12 sheep. All tissue samples were stored in RNAlater™ stabilization solution  at −80 °C before RNA extraction. Genomic DNA was extracted from the whole blood samples using the DNeasy Blood and Tissue Kit . The extracted DNA was diluted to 50 ng/uL for the Ovine Infinium HD SNP BeadChip genotyping.Ovis aries) genome. Firstly, a quality control on these SNPs was performed using PLINK software [Three hundred sheep, including 12 sheep selected for RNA-seq, were genotyped using the Ovine Infinium HD SNP BeadChip , which contained a total of 606,006 SNPs distributed throughout the domestic sheep . RNA concentrations were measured using a Qubit® 2.0 Fluorometer . RNA degradation, contamination, and integrity were checked in 1% agarose gels with a Bioanalyzer 2100 system .The total RNAs from tail adipose tissues were extracted using the TRIzol reagent . DNA contamination was removed using RNase-free DNase I (New England Biolabs). The sequencing library for mRNA was constructed with an IlluminaTruSeq™ RNA Sample Preparation Kit . The detailed procedures are as follows. The mRNA was purified from total RNA using poly-T oligo-attached magnetic beads and further fragmented. The cleaved RNA fragments were converted into cDNA using reverse transcription and random primers. DNA polymerase I and RNase H subsequently generated second-strand cDNA. Exonuclease/polymerase activities were used to convert remaining overhangs to blunt ends and to remove enzymes. After adenylation of 3′ ends of DNA fragments, Illumina PE adapter oligonucleotides were ligated to prepare for hybridization. To select cDNA fragments approximately 200 bp in length, the library fragments were purified with AMPure XP system . The synthesized cDNA was subjected to end repair; a single ‘A’ nucleotide overhang was attached to the 3′ end; and ligation with adapters and enrichment of cDNA fragments were performed according to the manufacturer’s instructions. RNA purity was checked using a NanoPhotometerOvis aries (Oar_v3.1) was downloaded from the UCSC  and further indexed using the Bowtie algorithm [http://ccb.jhu.edu/software/tophat/index.shtml) with default options. The detailed alignment information included clean reads, Q20 and Q30 values, GC contents, error rates, and the mapping rate of total mapped reads.The qualified cDNA library was sequenced on the Illumina HiSeq 2000 platform , producing 22~35 million clean paired-end reads with a read length of 100 bp on average for each individual. The sheep reference genome of lgorithm . The paiC is the number of reads mapped to gene sequence, N is the total number of mappable reads of a sample, and L is length of the gene sequence. The differentially expressed genes (DEGs) between different groups were identified using both Cufflinks [t-test for defined statistics, to identify significant DEGs [p and q values  are reported in the output files from Cuffdiff. Genes were considered differentially expressed when the p value was less than the false discovery rate after Benjamini–Hochberg correction for multiple testing .The expression of each gene was characterized based on reads per kilo base of transcript per million mapped reads (RPKM) values :RPKM=109ufflinks  and DESeufflinks  methods.ufflinks , and DEGufflinks . A negatant DEGs . The genp value of 0.05 was set as the threshold for significantly differential expression.Under the DESeq method, DEGs were detected using the DESeq R package (1.8.3) . DESeq ap values of less than 0.05 were considered to be significantly enriched for the DEGs. Additionally, the ingenuity pathways analysis (IPA) software v9.0 [https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis) was used to evaluate the DEGs among the four groups of sheep classified based on sex and tail-fat phenotype. Firstly, the accessions of these genes were imported into IPA, and the “Core Analysis” function included in IPA was then used to analyze the genes in the context of networks, biological functions, and canonical pathways.To describe biological functions of the differentially expressed genes, we conducted gene enrichment analysis with gene ontology (GO). The Goseq R package  was emplare v9.0  (QIAGEN UGCG), perilipin 4 (PLIN4), protachykinin-1 precursor (TAC1), MID1 interacting protein 1 (MID1IP1), lipoprotein lipase (LPL), Thy-1 cell surface antigen (THY1), and iroquois homeobox 3 (IRX3). The gene-specific primers were designed based on NCBI reference sequences using Primer5 software  and are listed in GAPDH) gene was chosen as the internal standard to adjust the input of cDNA and to normalize the expression of target genes [® Premix Ex Taq TM  . Each 50 μL qRT-PCR mixture consisted of 2 μL of template cDNA, 0.5 μL of each primer, 10 μL of SYBR® Premix Ex TaqTM (2×), and 7.0 μL of ddH2O (sterilized distilled water). PCR amplification was performed in a 96-well optical plate with the following program: 95 °C for 2 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 15s. The qRT-PCR was performed using the Applied Biosystems 7500 Fast Real-Time PCR System, and the 2−ΔΔCT method was employed to analyze the expression levels of genes [To validate the repeatability and reproducibility of the RNA sequencing data, quantitative real-time PCR (qRT-PCR) was carried out to evaluate the expression levels of seven DEGs related to fat. These genes were randomly selected and included UDP-glucose ceramide glucosyltransferase (et genes . RNA samof genes . The qRThttp://www.ncbi.nlm.nih.gov/bioproject/517348) under accession number PRJNA517348.The raw RNA-seq data used in this study are deposited in NCBI Sequence Read Archive . The details on RNA qualities were showed in p < 0.05, FDR q < 0.05)  . Among tTo investigate the functions of the 373 DEGs, a GO analysis was performed using the GO database according to three factors: Cellular component (CC) terms, molecular function (MF) terms, and biological process (BP) terms. Among these categories, most DEGs were enriched in the BP term; however, there were only a few genes related to fat metabolism and no CC terms were found .KEGG pathway analysis showed that the DEGs were involved in 30 categories. However, only three pathways were related to fat metabolism, namely fatty acid metabolism (oas01212), PI3K-Akt signaling pathway (oas04151), and regulation of lipolysis in adipocytes (oas04923). In total, 6, 14, and 5 genes were involved in these three pathways. The details on the genes and their functional annotations were provided in the Next, the possible functions of the DEGs analyzed using the IPA identified 24 pathways related to lipid metabolism. According to these results, the highest number of genes (40 genes) was associated with the “synthesis of lipid” pathway .Moreover, p < 0.05), including several GO processes related to lipid metabolism. We analyzed the mutual relationships with fat metabolism among the MBT, MST, FBT, and FST groups. There were no genes enriched in the CC term. The largest number of genes was annotated to BP term, and a small number were annotated to MF term. Firstly, when the difference between big-tailed fat and small-tailed fat male sheep were explored, there were no GO terms related to lipids found , fatty acid metabolism (oas01212), and fatty acid elongation (oas00062) . In the Finally, the possible functions of the DEGs were analyzed via IPA. The top diseases and functions associated with the DEGs were collected from four comparisons: MBT vs. MST, FBT vs. FST, MBT vs. FBT, and MST vs. FST. The results regarding lipid metabolism were as follows: 8 pathways were identified in the first comparison, 16 in the second, 19 in the third, and 8 in the fourth.ECHS1, HADHB, PPT1, HADH, and ACSL5 were up-regulated while two, CPT1B and GCDH, were down-regulated. An insulin-related network was detected from the comparison of big-tailed and small-tailed female sheep -related network was annotated from the comparison of big-tailed and small-tailed male sheep . In thisle sheep . In thisgulation . These gn = 6 for each line). The magnitude of fold change obtained by RNA-seq and qRT-PCR was slightly different in some instances. This validated the accuracies of the RNA sequencing data, which was verified by the qRT-PCR data (p < 0.01). These results suggested that the expression profile determined by RNA-seq was reliable.To evaluate the reliability of RNA-seq results, seven DEGs related to fat deposition were randomly selected for qRT-PCR analysis  that could be mapped to the reference genome of sheep was higher than 77.7% reported by Li et al.  and 75.6In this study, RNA-Seq approach identified 373 DEGs between big-tailed sheep and small-tailed sheep regardless of sex. Our next analysis of fat metabolism independent of different tail sizes and types also reflected sex differences, with results revealing 775 and 578 DEGs in the male and female sheep groups, respectively. It can be deduced from these results that there was a greater number of DEGs by sex than by tail type. That is to say, sex-differential genes may be related to various biological systems, from gene expression and regulation to evolution. Fat metabolism was further examined all comparisons between different sexes and tail types. We found that the comparative analysis of different sexes in big-tailed and short-tailed sheep exhibited a total of 47 and 109 DEGs, respectively, which are smaller numbers than all of the above results. Thus, we did not identify many DEGs related to sex control based on examination of the adipose tissue in the sheep tail.ACSL1 is a crucial gene for the lipid metabolism contributing to fatty acid biosynthesis, transport, storage, and degradation in bovine [ACSL1 was differentially regulated in the subcutaneous fat tissues of the Guangling large-tailed sheep and small-tailed Han sheep [PLIN1 is a key regulator of both basal and protein kinase A stimulated lipolysis in mammalian adipose tissue [ELOVL5 and ELOVL6 were involved in the elongation of various polyunsaturated long-chain fatty acids of 18–20 and saturated and monounsaturated fatty acids with 12–16 carbons to 18 carbons, respectively [ACACA has been showed as a potential candidate gene for fat content in sheep milk [PDK4 has been reported as related to meat quality and lipid metabolism of bovine [ACLY is related to the lipid metabolic process and triglyceride biosynthetic process of sheep [ACSL1, PLIN1, ELOVL5, ELOVL6, ACACA, PDK4, and ACLY are plausible functional candidate genes of the metabolism regulation of tail-fat in sheep. Their functional verifications need to be conducted to validate our findings.There are several genes among the DEGs associated with fat deposition, adipogenesis, fatty acid biosynthesis, and lipid metabolism in ruminant animals. n bovine ,41. It wan sheep . PLIN1 ie tissue  and has ectively . ACACA heep milk . PDK4 haf bovine . ACLY isof sheep . These sTo gain insight into the predicted gene networks, GO and pathway enrichment analysis were performed. Comparisons between the BT group and the ST group resulted in assignment to 55 GO terms, with the male sheep groups being allocated to 40 GO terms, while 75 GO terms allocated to female groups. In summary, we obtained three identical GO terms across all sheep groups and the male groups, while 19 of the same GO terms were obtained from all sheep groups and the female groups. In addition, genes in the male and the female sheep groups did not overlap, and there were no identical GO terms between the male and female sheep with the same tail type. The above results indicate that the functional classifications of DEGs in male and female sheep are different. Previous reports in humans also suggest differences between men and women in fat deposition patterns, fat metabolism, and the health consequences of obesity ,47,48,49KEGG pathway analysis was performed to further elucidate the probable functional status of DEGs. The results for the enrichment of the DEGs in the KEGG database showed that the total number of associated pathways was variable; nevertheless, the number of pathways related to fat metabolism was equal or similar between the groups. Total number of pathways assigned to the female sheep group was significantly higher than that assigned to the male sheep group, even though the male sheep group had more DEGs. This finding implied that the fat metabolism of female sheep could be more complex because females exhibit pregnancy, birth, and lactation behaviors. Scientists have also investigated sex differences in humans ,54,55,56ACSL1, ELOVL5, EHHADH, ACACA, ELOVL6, and ACADL; those for the male sheep groups included CPT1B, ECHS1, PPT1, HADH, HADHB, and ACSL5; while those for the female sheep groups induced ACSL1, ELOVL5, FADS1, EHHADH, FADS2, and ACADL. The results indicate that there are differences in genes in the same pathways between male and female sheep, which indicates that the regulatory mechanism of fat metabolism may be different for two sexes in sheep. Previous research has suggested that sex hormones may influence the enzymatic synthesis of long-chain polyunsaturated fatty acids and has shown sex-specific differences in some outcomes [The results presented above revealed only one pathway that was clearly related to fat metabolism: The fatty acid metabolism pathways. However, unexpectedly, different genes were identified in the enrichment analyses of different groups. For example, the results for the BTH vs. STH groups included outcomes . The adioutcomes , which iPPARA , PPARD , and PPARG . The PPARs control the expression of networks of genes involved in adipogenesis, lipid metabolism, inflammation, and maintenance of metabolic homeostasis [Our findings included PPARG-related and insulin-related pathways, which are associated with fat metabolism in male sheep and female sheep, respectively. The peroxisome proliferator-activated receptors (PPARs) are members of the nuclear receptor superfamily of ligand-inducible transcription factors . Three Peostasis . Insulineostasis . Based oeostasis  and Roseeostasis , we simpTo the best of our knowledge, this is the first study to investigate the difference of fat metabolism mechanisms in two lines of Hulun Buir sheep caused by morphological and sex differences. Our study successfully identified the DEGs related to fat metabolism in five comparisons according to tail size and sex of Hulun Buir sheep. Our findings will not only help to determine the functional complexity of fat deposition in sheep, but also will provide valuable information for understanding the phenotypic and functional differences of fat deposition in tails.


Atrial fibrillation (AF) is the most common sustained heart arrhythmia. However, as many cases are asymptomatic, a large proportion of patients remain undiagnosed until serious complications arise. Efficient, cost-effective detection of the undiagnosed may be supported by risk-prediction models relating patient factors to AF risk. However, there exists a need for an implementable risk model that is contemporaneous and informed by routinely collected patient data, reflecting the real-world pathology of AF.This study sought to develop and evaluate novel and conventional statistical and machine learning models for risk-predication of AF. This was a retrospective, cohort study of adults (aged ≥30 years) without a history of AF, listed on the Clinical Practice Research Datalink, from January 2006 to December 2016. Models evaluated included published risk models , machine learning models, which evaluated baseline and time-updated information , and Cox regression.Analysis of 2,994,837 individuals (3.2% AF) identified time-varying neural networks as the optimal model achieving an AUROC of 0.827 vs. 0.725, with number needed to screen of 9 vs. 13 patients at 75% sensitivity, when compared with the best existing model CHARGE-AF. The optimal model confirmed known baseline risk factors  and identified additional time-varying predictors , pulse pressure, and the frequency of blood pressure measurements).The optimal time-varying machine learning model exhibited greater predictive performance than existing AF risk models and reflected known and new patient risk factors for AF. Atrial fibrillation (AF), the most common sustained heart arrhythmia, is assoBoth European and US guidelines recommend diagnosing AF based on a 12-lead electrocardiogram (ECG) or rhythm strip, 8; howeOne approach to improve the precision of patient identification is by applying published risk models that use baseline clinical variables and biomarkers for future AF risk prediction–13 or coa priori. The use of machine learning for predicting disease may enable physicians to speed-up decision making and improve efficiency, reliability, and accuracy. In line with published applications of machine learning in various aspects of healthcare..22].For the baseline model, covariates were taken to be the latest value recorded in the one year (365.25 days) prior to study entry. For the time-varying model, extracted data was structured in 91-day quarters working backwards over a one-year period from AF diagnosis (index) date to reflect evolution of risk factors in the year prior to AF diagnosis . Last-observation-carried-forward was used to impute clinical measurements in quarters with no data.The performance of the final risk model (stage 3) was evaluated on the stage 2 population, to reflect the evolution of the risk factors in the model’s predictions. Inverse-probability weights were applied to ensure the resulting performance metrics were representative of the full study population observed at stage 1, rather than the artificially balanced case-control sample at stage 2. The weights were equal to 1 for patients with AF over follow-up , and calculated as the inverse selection probability for patients without AF, ensuring the original age and sex distributions were recovered.To aid generalizability of the results beyond the sample to which the risk models were fitted, patients were randomly assigned to training and holdout datasets in a 2:1 ratio; these datasets were used to fit and independently assess each risk model, respectively.To aid interpretability of the fitted NN, each covariate’s “relative strength” in predicting AF risk was quantified and exprDiscrimination between AF and non-AF cases was assessed using area under the receiver operating characteristic curve (AUROC): value in the range 0–1, where 1 indicates perfect separation of AF and non-AF cases. Positive predictive value (PPV) and potential number-needed-to-screen (NNS) potenti as candiThe performance of the optimum NN model was evaluated by comparison with the current best-performing of the pre-existing models to predict risk at baseline namely the CHARGE-AF risk equation, which uses classical statistical methods.A total of 2,994,837 patients were included in the baseline model , with 162 and 141.0 mmHg, respectively, compared to 27.6 kg/m2 and 133.3 mmHg for non-AF patients. There was no clinically meaningful difference in mean baseline DBP between AF and non-AF patients , but mean pulse pressure was notably greater for AF patients, at 61.9 mmHg compared to 53.9 mmHg for non-AF patients. Differences in baseline characteristics between AF and non-AF patients were statistically significant for all variables considered, reflecting the large analysed sample. However, only age was observed to have a ‘large’ effect size (Cohen’s d ≥ 0.8) according to Cohen (1988)[Mean age at baseline for patients diagnosed with AF was 70.2 years, compared to 55.5 years for non-AF . AF patien (1988), while oen (1988) as beingA total of 24 and 100 predictors of AF were used in the fitted baseline (stage 1) and time-varying (stage 2) NNs, respectively; key risk factors elicited from these models are summarised in In the time-varying NN, the presence of heart failure in the most recent 91-day quarter contributed most to the prediction of AF diagnoses ; other aTo identify 75% of diagnosed AF cases, the final NN (incorporating predicted probabilities from the baseline and time-varying NN) achieved a PPV of 11.5%, compared to 7.9% for CHARGE-AF and 6.5% for logistic regression , correspThe blue circles represent the 27,135 patients diagnosed with AF, while the grey circles represent patients flagged as being at risk of AF by each of the models. The overlap between the blue and grey circles represents a given level of sensitivity ; the resulting PPV (the percentage of patients flagged by the model that are diagnosed with AF) is represented by the proportion of the grey circle that lies within the overlapping region. The figure therefore demonstrates that, for a given level of sensitivity, our risk model achieves a greater PPV than CHARGE-AF, implying that fewer patients would need to be screened to identify the same number of AF cases. For example, to identify 75% of patients with AF , our risk model would flag 177,726 patients  to be screened (panel A). In comparison, to identify the same proportion of AF cases, CHARGE-AF would flag 257,389 patients  to be screened (panel D).The patient numbers displayed relate to the stage 2 holdout dataset after applying post-stratification weights to reflect the AF, age and sex composition of the full eligible population. A total of 627,768 patients were included in the analysis after weighting; the difference between this total and the sum of the values shown in the figure constitutes true negative cases (patients not flagged and not diagnosed with AF).The NN achieved an AUROC of 0.827, compared to 0.725 for CHARGE-AF and 0.695 for logistic regression . When tiThe developed risk model has a high yield and potential to reduce greatly the number of patients being screened for AF. When compared with the best performing existing model, CHARGE-AF, our risk model reduced the potential NNS by 31% from 13 to 9, equating to 79,663 fewer patients in total. The model had an AUROC of 0.827, a 14.1% relative increase in its ability to discriminate between diagnosed AF and non-AF cases when compared with an AUROC 0.725 for CHARGE-AF. Notably, the relative increase in AUROC achieved by NN over traditional approaches when only baseline covariates were considered was far more modest (2.8% versus CHARGE-AF and 2.6% versus Cox regression), indicative of the potential value of combining machine learning with time-varying covariates. However, even a minor improvement will have tangible implications for patient outcomes in clinical practice, either through unnecessarily screening fewer patients or capturing more cases of AF. The final risk model provided a superior trade-off between sensitivity and precision compared with all the existing AF risk models, and could therefore refine target populations that warrant further investigations to diagnose AF. These results add to the growing body of evidence supporting the use of machine learning techniques across various therapeutic areas.Rather than mining the CPRD for new AF risk factors, possibly without clinical rationale, candidate predictors considered in our machine learning models were derived from three existing risk models Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S1 FigA: baseline covariates; B: time-varying covariates.(PPTX)Click here for additional data file.S2 FigA total of 2,994,837 patients were aged ≥30 years without a five-year history of AF at the start of the study period, and had a complete set of key clinical measurements  recorded over a one-year period. These patients were randomly assigned to training and holdout sets (2:1) to develop and assess the baseline neural network, respectively. The time-varying neural network was trained on all AF cases with at least one year of history at the time of AF and an age- and sex-matched sample of non-AF controls, and was evaluated after applying post-stratification weights to reflect the AF, age and sex composition of the full eligible population.(TIF)Click here for additional data file.S3 Fig(A) presence of heart failure in the latest quarter; (B) number of BMI, DBP and SBP measurements in the latest quarter; (C) maximum change in diastolic blood pressure and systolic blood pressure between the last two quarters; (D) most recent diastolic blood pressure and systolic blood pressure measurements.Predicted probabilities were estimated by the method of partial dependence, whereby each predictor of interest was varied, and all other predictors were fixed at their patient-level observed values. Predicted probabilities were calculated on the unweighted training dataset for the time-varying neural network.(TIF)Click here for additional data file.


Only a few cases of papillary glioneuronal tumour (PGNT) with predominantly focal symptomatology are described in the literature. We report on the clinical, radiological, and histopathological features of PGNT. The intraoperative pathology revealed no tumour in the walls of the cyst, thus surgical resection of the nodule was performed leaving the cyst wall intact. There was no recurrence of tumour at the three-year follow-up, although a long-term follow-up is necessary. Papillary glioneuronal tumour (PGNT) is an uncommon central nervous system tumour type. The first time this name was used by Komori et al. in 1998  and gangA 38-year-old, otherwise healthy, right-handed man presented with a two-year progressive history of motor dysphasia and a three-month history of progressive right-hand weakness. The patient also had one short episode of right leg numbness and weakness. A neurological examination showed reflex asymmetry (right > left), hemihypesthesia, hemiparesis (4/5), and positive Babinski sign on the right. Magnetic resonance imaging (MRI) of the brain revealed a 54 x 54 x 52 mm cystic lesion of the left frontal lobe in front of the precentral gyrus with a septum attached to the posterior wall of the cyst. The cyst was hypointense on T1-weighted images (T1WI)  and 5-μm sections were stained immunohistochemically for glial fibrillary acidic protein (GFAP), synaptophysin, and Ki-67 protein. Histologically, the tumour consisted of morphologically and immunohistochemically distinct components. Small pseudopapillary structures were seen consisting of hyalinized small vessels Figure .The interpapillary space contained cells varying in size from small neurocyte cells to large ganglioid cells  that stained positive for synaptophysin Figure .The Ki-67 labeling index was low Figure .There were scattered hemosiderin deposits observed but no vascular proliferation or necrosis.PGNT predominantly affects the younger population as the patients’ age varied from 11 to 41 years in the series reported by Li et al. . The preNeuroimaging usually shows a cyst lesion with the most frequent pattern being a cystic and solid tumour or cystic tumour with mural nodule , 9, 13. Except for a few reported cases of aggressive behavior , 5, 7, hThe patients diagnosed with PGNT usually undergo gross-total or partial resections, although radiotherapy and chemotherapy for more aggressive tumours were also reported , 9-11. TThe case presented here is rare, as only a few patients with predominantly focal neurological deficits were reported in the literature so far -10. Our Patients with supratentorial, paraventricular cystic lesions, and intracystic septal enhancements should be suspected of having PGNT. The tumour is benign and gross-total resection provides the cure for patients. In the selected cases, a favorable outcome could be achieved by removing only the nodular component, however, a long-term follow-up is important to confirm the true biological behavior of PGNT.


Background: Task sharing of TTE may improve capacity for heart failure diagnosis and management in patients in remote, low-resource settings but the impact on diagnostic accuracy and patient outcomes has not been studied.Objectives: Determine feasibility and impact of non-expert training in transthoracic echocardiography (TTE) to improve the diagnosis and outcomes of patients with suspected heart failure in Uganda.Methods: This two-part study examined an innovative training program to develop TTE competency among non-experts and used a pre-post design to determine the impact of decentralized TTE. Four of 8 non-experts (50%) passed a three-part training course. The training comprised of distance learning through a web-based curriculum, a 2-day hands-on workshop with cardiologists, and independent practice with remote mentorship. Continuous measures were compared (pre- vs. post-TTE) using t-tests or Wilcoxon rank-sum tests as distributionally appropriate and categorical variables assessed through chi-square testing. Sensitivity and specificity were calculated according to standard methodology comparing diagnosis pre- and post-TTE during phase 2.Results: Performance in the post-training phase showed good agreement with expert categorization (κ = 0.80) with diagnostic concordance in 421 of 454 studies (92.7%). TTE changed the preliminary diagnosis in 81% of patients, showing low specificity of clinical decision-making alone . Dilated cardiomyopathy, hypertensive heart disease with preserved systolic function, and right heart failure were the most underdiagnosed conditions prior to TTE while hypertensive heart disease with decreased systolic function was the most over-diagnosed condition.Conclusions: In conclusion, non-expert providers can achieve a high level of proficiency for the categorization of heart failure using handheld TTE in low-resource settings and use of telemedicine and remote mentorship may improve performance and feasibility. The addition of TTE resulted in substantial improvement in etiological specificity. Further study is needed to understand implications of this strategy on healthcare utilization, long-term patient outcomes, and cost. Heart failure has been described as a global pandemic  affectinThe mission of the Uganda Heart Institute includes strengthening of regional centers for decentralized cardiovascular care. The strategy of this program has included regular visits to district and regional referral hospitals for patient consultation and ongoing provider education. However, these outreach clinics are limited by both financial constraints and the large patient volumes at the main tertiary center limiting on-site staff to provide ongoing care and timely diagnosis between clinics.A literature review and discussion with local providers identified heart failure as the most common cardiovascular diagnosis in the region, as well as the condition that posed the greatest diagnostic challenge –9. In 20The study consisted of two parts: part 1 focused on developing TTE competency among non-experts  through Patients with suspicion of heart failure were recruited from clinical referrals from the outpatient/acute care and inpatient wards. An attempt was made to broadly capture all patients ≥ 1 year of age presenting with signs or symptoms of possible heart failure. Inclusion criteria focused on signs/symptoms suspicious of heart failure developed by consensus between the LRRH team and investigators. The intent was to improve diagnostic accuracy; thus, criteria thought to be highly sensitive, with a trade-off of lower specificity were included and any one of the following was acceptable: (1) Dyspnea or exercise intolerance > 1 month in duration, (2) Lower extremity edema, (3) Abdominal distention believed to be ascites, (4) Cough > 1 month or wheezing < 1 month & Chest X-ray not consistent with focal lung infection or TB, (5) Tachycardia not attributed to infection/fever. Defined as >100 bpm in adults, >120 bpm for children ≥ 5 years, >140 bpm for children <5 years, (6) Cyanosis or clubbing, (7) Syncope, (8) Chest pain or palpitations, with two or more of the following , (9) Acute stroke , and (10) High provider suspicion of cardiovascular pathology based on diagnostic workup .All frontline healthcare providers were educated about the inclusion criteria and research staff rounded to help with patient identification.http://www.wiredhealthresources.net/EchoProject/), 2) completion of a 2-day echocardiography course led by four expert cardiologists, 3) independent practice with remote mentorship, targeting acquisition and interpretation of least 30 echocardiographic studies, 4) Competency assessment.Eight non-expert health professionals working at LRRH and without previous experience in TTE – including three nurses, two clinical officers, one sonographer, and two physicians  – were recruited to participate based on expressed interest in the program, availability, input from hospital leadership, and plans to continue working at LRRH for the duration of the study. These health professionals gave written informed consent for participation. Training consisted of four stages , clinical presentation and data , diagnostic classification , and outcome data  were collected on patients meeting inclusion criteria utilizing standard data capture forms.A 4-month pre-intervention survey was undertaken prior to TTE introduction to understand the baseline diagnostic profile, referral practices, and outcomes of patients with suspected heart failure.After local consultation and records review for the most prevalent causes of patient heart failure, we identified the major diagnostic categories at presentation as normal, pericardial disease, hypertensive heart disease with preserved systolic function (thickened IVS without systolic dysfunction), hypertensive heart disease with systolic dysfunction (thickened IVS with systolic dysfunction), dilated cardiomyopathy , valvular heart disease (rheumatic or other), right-sided heart failure and other . A simplified diagnostic TTE protocol as outlined above , and a 12-lead ECG was added to the existing practice of history, physical exam, and occasional ancillary testing (such as chest radiography). ECG interpretation was supported through a 1 day in-person training on ECG basics but was mainly limited to the automatic read and rhythm diagnosis.A 4-month post-intervention survey was undertaken with TTE integrated into the diagnostic workup for those with suspected heart failure, utilizing parallel recruitment, inclusion criteria, and case report forms. In addition, additional pre- and post-TTE data were collected from providers .Focused TTE and ECG by trained non-experts (Part 1) were performed as part of the clinical assessment and used to aid in final diagnostic classification. Consultation with other clinicians in this study was neither encouraged nor discouraged as this phase was a pragmatic application of TTE into clinical care. Data were not captured on rates of consultation within the group. Real-time expert interpretation was not utilized during this stage, but all TTEs were retrospectively reviewed by cardiologists blinded to on-ground diagnosis after study completion and categorized for determination of non-expert accuracy.Study data were collected and managed using REDCap (Research Electronic Data Capture) tool, a secure, web-based application designed to support data capture for research studies, hosted at Children’s National Medical Center, Washington DC . All datThe number of TTEs performed by each participant was captured. Results of competency testing were reported as pass (≥80%) or fail (<80%). Non-expert performance post-training were compared with remote expert interpretations. TTE studies were uploaded onto google drive and were downloaded off the server by the remote experts. Remote experts entered interpretation into RedCap and the treating clinicians downloaded the reports off the RedCap server. Discordance between on-site and remote readings was considered with differences in final category of heart failure, including no heart failure. Kappa coefficient (κ) was calculated as the degree of agreement between the two. Sensitivity, specificity, and predictive values were determined from the percentage of patients with true-positive and true-negative results with 95% CIs by heart failure category. Additionally, data were also analysed for agreement on the echocardiographic components of diagnosis. Continuous data are reported as mean ± SD or as median and IQRs if not normally distributed, and categorical data are reported as numbers and percentages.Demographic, clinical, diagnostic, and outcomes data were collected on standardized paper reporting forms and transcribed into REDCap. Data are presented by study phase as mean and standard deviation, median and interquartile range, and number and percentage as appropriate. Continuous measures were compared (pre- vs. post-TTE) using t-tests or Wilcoxon rank-sum tests as distributionally appropriate and categorical variables assessed through chi-square testing. Sensitivity and specificity were calculated according to standard methodology comparing diagnosis pre- and post-TTE during phase 2.The study was approved by the institutional review boards of Makerere University School of Medicine, the Uganda National Council of Science and Technology, University Hospitals Cleveland Medical Center  and Children’s National Medical Center .Eight non-expert participants began the TTE-training course. Of these, all eight passed the competency assessment at the end of Stage 1 with an overall mean score of 86.7%, and all eight were present for the duration of Stage 2 training. Only six of the eight participants completed the minimum of 30 practice TTE studies during Stage 3 and were eligible for final competency testing. Of the six participants who took the Stage 4 final competency assessment, four received passing scores of ≥80% and moved into the post-training phase as sonographers for Part 2, including one nurse, one medical officer, one sonographer and one internal medicine specialist.A total of 455 TTEs were performed during the post-training phase, with one being excluded from this analysis secondary to image loss. The average time to review a study was 5 min. Image quality was considered good  in 82%, acceptable  in 12%, poor (missing frames from imaging protocol and/or >2 parameters not able to be fully assessed) in 6% with no studies categorized as unable to interpret.Overall agreement during the post-training phase between non-expert and expert heart failure categorization was good , coinciding in 421 (92.7%) of 454 studies ). Non-exConcordance among component diagnoses was worse than the concordance among heart failure diagnoses . Of these, the most common diagnoses included hypertensive heart failure (52.6%), no heart failure (19.8%) and heart failure not otherwise specified (NOS) (16.0%). Almost one-third of the patients  were admitted to the inpatient wards at presentation with a median length of stay of 4 days (IQR), and 27  died during that admission.There were 454 patients captured during the post-intervention, phase 2. Of these the most common final diagnoses included hypertensive heart disease with reduced systolic function (26.4%), dilated cardiomyopathy (17.6%), and no heart failure (15.4%). One hundred and seventy-three patients (38.1%) were admitted to the inpatient wards with a median length of stay of 5 days (IQR), and 21 (4.6%) died during that admission.In Phase 2, TTE evaluation resulted in a change between preliminary  and final  major diagnostic category in 367 (80.8%) patients. Incorporating TTE into diagnostic decision-making during phase 2, clinical impression had a reasonable sensitivity of 89.9% (95% CI 85.0–93.6%) but a very low specificity of 14.2% (95% CI 10.1–19.2%).In the study population, this led to a clinical positive predictive value for heart failure without use of TTE as 47.0% (95% CI 45.3–48.7), and a clinical negative predictive value for heart failure of 62.5% (95% CI 50.1–73.5). Dilated cardiomyopathy, hypertensive heart disease with preserved systolic function, and right heart failure were the most underdiagnosed conditions prior to TTE while hypertensive heart disease with decreased systolic function was the most over-diagnosed condition .10.1080/In addition, access to TTE allowed for elimination of the diagnostic category heart failure NOS, the preliminary diagnosis of 68 patients (16%) of patients in Phase 1 and 109 patients (24%) in Phase 2. In Phase 2, TTE revealed that 25% of these patients were ultimately found to have no evidence of heart failure allowing for continued work-up of differential diagnosis. Of the 75% with heart disease, the majority had dilated cardiomyopathy, valvular heart disease, and other heart diseases  . ECG proIn phase 2, there were more patients who were discharged to home without follow-up (p < 0.01) and less patients scheduled for follow-up at the outpatient cardiac clinic (p < 0.01). Phase 2 also saw fewer patients self-discharging from the inpatient wards against medical advice. There was no difference in death during hospitalization between phases, though total numbers were small and lacked sufficient power (p = 0.24) .10.1080/Heart failure is a major cause of cardiovascular morbidity and mortality in sub-Saharan Africa ,12. ThisThese findings have broad implications for supporting decentralized cardiac care in resource-limited settings. Despite the current Ugandan guidelines recommending chest x-ray, ECG, and TTE as standard investigations for suspected heart failure , only 3%The training used in this study represents an innovation that could potentially facilitate the broader and more consistent training and competency testing needed to ensure high-quality care. Graduates of our training program showed very high agreement  between non-expert and expert categorization of heart failure, and 82% of the TTE studies were classified as good quality. These results represent substantial improvement from a previous study, which utilized only a 4-day training (similar to our Stage 2) of family physicians in remote Spanish primary care clinics, resulting in only 58% agreement of heart failure categorization and 35.4% of the studies classified as good quality . The praThe practicum period also served as an informal measure of non-expert investment, availability, and skill level. Of the eight non-experts who were originally recruited for the project, only six completed the minimum number of practicum studies needed to advance and only four passed the final competency test to advance as a program sonographer. The lack of trainee advancement in the program was primarily due to the high ratio of patients to staff at LRRH and a lack of time to take on additional responsibilities. Specific issues included trainees that worked at other medical sites in combination with LRRH had less time to complete the training due to other work commitments, some trainees had staffing shortages in their departments and had difficulty finding time to scan, and physicians were also more likely to travel for meetings or regional conferences, therefore, unable to complete the required about of scans. Our experience suggests that task shifting of TTE might be best accomplished when including some degree of both self-selection and rigorous skill assessment.The largest impact of adding TTE was, unsurprisingly, the improvement in specificity of the etiology of heart failure. While pericardial disease and congenital heart disease were diagnosed with high accuracy without the addition of TTE, dilated cardiomyopathy and right heart failure were significantly under-diagnosed and hypertensive heart disease with reduced systolic function was over-diagnosed. TTE was able to differentiate between those with intraventricular septal hypertrophy and preserved systolic function (i.e. hypertensive heart disease with preserved systolic function) and those with intraventricular septal hypertrophy with diminished LV function (i.e. hypertensive heart disease with reduced systolic function). Even though our study was not designed to assess appropriateness of therapeutics, knowing the correct etiology of heart failure symptoms likely leads to more targeted therapeutics, which may improve long-term costs, patient symptoms, and outcomes.While our study confirms that a decentralized strategy of heart failure diagnosis unequivocally improved the quality of patient diagnosis, we failed to demonstrate differences in mortality with the addition of TTE. This could have resulted from low numbers of death, the limited ability to assess longer-term mortality (only inpatient outcome), and the fact that many who succumb to inpatient mortality at the time of diagnosis present with advanced, decompensated heart failure. A broader study is needed to understand if more specific diagnoses in milder cases lead to less hospitalizations and improved survival as well as contribute to more appropriate healthcare utilization.Our study has several limitations. First, we did not mandate that in the post-training period final non-expert diagnosis be made in isolation. While we did not capture data on collaboration, it was common for two or more of the sonographers to review images together, necessarily increasing accuracy. However, collaboration between imagers is common in the clinical setting and, intentionally, we did not limit it in this pragmatic study. Second, our study focused only on the diagnosis of definite heart failure, and we did not train or evaluate the ability of our non-experts to diagnose more subtle forms of heart disease, which are likely common in this low-resource community. Third, in an effort to simplify training and broadly classify heart failure patients into wide diagnostic categories, we utilized only qualitative and semi-quantitative diagnostics. In this structure, more complete evaluation by a cardiologist with fully functional TTE equipment would be needed in cases where surgical or catheter interventions were being considered.In conclusion, this study demonstrates that non-expert providers can achieve a high level of proficiency for the categorization of heart failure using handheld TTE in low-resource settings. In addition, we have shown that a model incorporating low-bandwidth telemedicine and web-based reporting can facilitate a longer mentorship period, resulting in high performance. The largest advantage seen after the initiation of TTE was substantial improvement in etiological specificity. Further study is needed to understand implications of this strategy on healthcare utilization, long-term patient outcomes, and cost. The application of this strategy has the potential to significantly improve task shifting of TTE in resource limited settings, improving the diagnosis and care for heart failure patients around the globe.


Frailty has been associated with an increased risk of adverse postoperative outcomes in elderly patients. We examined the impact of preoperative frailty on loss of functional independence following emergency abdominal surgery in the elderly.This prospective cohort study was performed at a tertiary hospital, enrolling patients 65 years of age and above who underwent emergency abdominal surgery from June 2016 to February 2018. Premorbid variables, perioperative characteristics and outcomes were collected. Two frailty measures were compared in this study—the Modified Fried’s Frailty Criteria (mFFC) and Modified Frailty Index-11 (mFI-11). Patients were followed-up for 1 year.p < 0.01) were significantly associated with loss of functional independence at 1 year. However, frailty, as assessed by mFI-11, showed a weaker correlation than mFFC . On multivariable analysis, only premorbid frailty (by mFFC) remained statistically significant .A total of 109 patients were prospectively recruited. At baseline, 101 (92.7%) were functionally independent, of whom seven (6.9%) had loss of independence at 1 year; 28 (25.7%) and 81 (74.3%) patients were frail and non-frail (by mFFC) respectively. On univariate analysis, age, Charlson Comorbidity Index and frailty (mFFC) (univariate OR 13.00, 95% CI 2.21–76.63, The mFFC is useful for frailty screening amongst elderly patients undergoing emergency abdominal surgery and is a predictor for loss of functional independence at 1 year. Including the risk of loss of functional independence in perioperative discussions with patients and caregivers is important for patient-centric emergency surgical care. Early recognition of this at-risk group could help with discharge planning and priority for post-discharge support should be considered. The number of surgical procedures in the elderly population has increased in the past few decades –4. In thFrailty, a decrease in physiological reserve, is associated with multisystem impairments , 9, and Frailty has been associated with increased risk of postoperative complications, longer length of stay, discharge to step-down care, loss of functional independence and higher readmission rates in post-surgical patients , 11, 18.This prospective cohort study was performed at the Singapore General Hospital, the largest tertiary hospital in Singapore. We prospectively enrolled patients 65 years of age and above who underwent emergency abdominal surgery  from June 2016 to February 2018. Written informed consent was obtained prior to enrolment in the study. Vascular, gynaecological and transplant surgeries and emergency operations for complications of elective surgery were excluded. For patients who were cognitively impaired, their next-of-kin were recruited into the caregiver arm of the study and a surrogate questionnaire was used. Patients who were not expected to survive the index admission were excluded. Patients whose cognitive state precluded informed consent, and who had no next-of-kin to consent to the caregiver arm of the study, were excluded. The SingHealth Centralised Institutional Review Board approved the study (2016/2338).All patients were approached postoperatively in the general ward. Upon recruitment, premorbid characteristics including demographic information, medical comorbidities (scored using the Charlson Comorbidity Index [CCI]), nutritional status , cognitive function , functional independence (by Modified Barthel’s Index) and frailty measures (Modified Fried’s Frailty Criteria and Modified Frailty Index-11) were assessed. Perioperative characteristics  and outcomes , length of hospitalisation, reoperation and 30-day unplanned readmission) were collected. Patients were followed-up for 1 year, with reassessment of functional independence and unplanned readmission at follow-up . The primary outcome was loss of functional independence at 1 year and its predictors.The primary measure of frailty in the study was mFFC, shown in a preliminary analysis of this cohort to have a stronger association with poor outcomes . The mFFThe alternative frailty measure used was the mFI-11, which is an 11-point scoring system comprising 11 possible comorbidities and/or deficits as follows: diabetes mellitus; congestive cardiac failure; hypertension requiring medication; history of either transient ischemic attack or cerebrovascular accident; functional status that is non-independent; history of myocardial infarction; history of peripheral vascular disease or rest pain; history of cerebrovascular accident with neurological deficit; history of either chronic obstructive pulmonary disease or pneumonia; history of either prior percutaneous coronary intervention, previous coronary surgery or history of angina; history of impaired sensorium . Each mFU test and chi-square test or Fischer’s exact test respectively, with a statistical significance level of 0.05 used. In the sub-group of patients who were functionally independent at baseline (Modified Barthel’s Index ≥80), univariate and multivariable logistic regression  were performed to identify factors associated with loss of functional independence at 1 year (Modified Barthel’s Index < 80).Statistical analysis was performed using SPSS Statistics Version 19.0 (Armonk NY: IBM Corp). Continuous variables were summarised by median  and categorical variables by frequency (%). Continuous and categorical variables were analysed using the Mann-Whitney A total of 109 patients fulfilling the inclusion criteria were prospectively recruited. The baseline demographic and perioperative characteristics are summarised in Table p = 0.001), longer median length of stay  and higher rates of unplanned readmissions at 1 year  (Table Frailty (by mFFC) was significantly associated with higher rates of postoperative morbidity  were functionally independent (mBI ≥ 80/100), of whom 69 (68.3%) completed planned follow-up at 1 year. Of these patients, seven (6.9%) had loss of independence at 1 year (Modified Barthel’s Index < 80/100) (Table p < 0.01) were significantly associated with loss of functional independence at 1 year. However, frailty, as assessed by mFI-11, showed a weaker correlation than mFFC    group had a consistently lower proportion of patients who were functionally independent Fig. . Most ofLoss of functional independence has gained increasing recognition as a high-priority patient-centred outcome with long-term implications on quality of life and healthcare costs , 28. ApaMany studies have shown strong associations between frailty and poorer healthcare-related outcomes in both surgical and non-surgical patients , 17, 18.Looking beyond the immediate postoperative period, this study found preoperative frailty to be predictive of poorer long-term functional outcomes, even for patients who were functionally independent at baseline. Amongst the patients who were functionally independent at baseline, we found higher odds of losing functional independence at 1 year amongst those with preoperative frailty. Donald et al. recently reported a similar association following elective vascular surgery alongside higher rates of discharge to a non-home location and 30-day mortality . This hiThis study has several limitations, including the relatively small sample size, lack of standardisation of postoperative care protocols across managing surgeons, and a lost-to-follow-up rate of 33.1%. It would be difficult to extrapolate our study findings to cognitively impaired patients who do not have caregivers and potentially high-risk patients, as we could not recruit them into the study. On the other hand, the study’s prospective cohort design facilitated standardised and complete data collection which is of particular value in the use of rigorous measures of various pre- and postoperative variables such as frailty and functional independence, and featured a 1-year follow-up period to examine the temporal trends of longer-term functional independence, a dimension not widely available in existing literature. To the best of our knowledge, this represents the first study to examine the relationship between frailty and functional independence outcomes in the elderly after emergency abdominal surgery. This study informs potential future research examining patient-centred decision-making in emergency surgery situations, as well as the potential benefit of holistic rehabilitative intervention programmes amongst frail elderly patients undergoing emergency abdominal surgery.The mFFC is a useful tool for frailty screening amongst elderly patients undergoing emergency abdominal surgery as a predictor for loss of functional independence at 1 year. Including the risk of loss of functional independence in perioperative discussions with patients and caregivers is important for patient-centric emergency surgical care. Early recognition of this at-risk patient subgroup with dedicated and detailed postoperative rehabilitation and discharge planning should be considered to help mitigate enduring functional impairments in the long-term.


HIV testing rates are suboptimal among at-risk men. Crowdsourcing may be a useful tool for designing innovative, community-based HIV testing strategies to increase HIV testing. The purpose of this study was to use a stepped wedge cluster randomized controlled trial (RCT) to evaluate the effect of a crowdsourced HIV intervention on HIV testing uptake among men who have sex with men (MSM) in eight Chinese cities.An HIV testing intervention was developed through a national image contest, a regional strategy designathon, and local message contests. The final intervention included a multimedia HIV testing campaign, an online HIV testing service, and local testing promotion campaigns tailored for MSM. This intervention was evaluated using a closed cohort stepped wedge cluster RCT in eight Chinese cities  from August 2016 to August 2017. MSM were recruited through Blued, a social networking mobile application for MSM, from July 29 to August 21 of 2016. The primary outcome was self-reported HIV testing in the past 3 months. Secondary outcomes included HIV self-testing, facility-based HIV testing, condom use, and syphilis testing. Generalized linear mixed models (GLMMs) were used to analyze primary and secondary outcomes. We enrolled a total of 1,381 MSM. Most were ≤30 years old (82%), unmarried (86%), and had a college degree or higher (65%). The proportion of individuals receiving an HIV test during the intervention periods within a city was 8.9%  greater than during the control periods. In addition, the intention-to-treat analysis showed a higher probability of receiving an HIV test during the intervention periods as compared to the control periods . The intervention also increased HIV self-testing . There was no effect on facility-based HIV testing , condom use , or syphilis testing . A total of 48.6%  of participants reported that they received HIV self-testing. Among men who received two HIV tests, 32 individuals seroconverted during the 1-year study period. Study limitations include the use of self-reported HIV testing data among a subset of men and non-completion of the final survey by 23% of participants. Our study population was a young online group in urban China and the relevance of our findings to other populations will require further investigation.In this setting, crowdsourcing was effective for developing and strengthening community-based HIV testing services for MSM. Crowdsourced interventions may be an important tool for the scale-up of HIV testing services among MSM in low- and middle-income countries (LMIC).NCT02796963ClinicalTrials.gov  In a randomized controlled trial, Joseph Tucker and colleagues study the effect of a crowdsourced intervention on HIV testing among men who have sex with men in China. HIV testing remains low among key populations, including MSM, especially in low- and middle-income countries.Although crowdsourcing has been recommended as a tool for developing public health interventions, few studies have formally evaluated crowdsourcing as a way to promote health in a real-world setting.Previous studies on crowdsourcing have suggested that it may be a promising approach to increase HIV testing among MSM in China.We investigated the effectiveness of a crowdsourced intervention in promoting HIV testing among Chinese MSM in eight cities distributed in two provinces.We found that the crowdsourced intervention was effective in promoting HIV testing. Compared to the control period, the intervention period showed an 8.9% absolute increase (and a 43% relative increase) in HIV testing.The intervention was particularly effective in promoting HIV self-testing.In this setting, we found crowdsourcing was a way to develop innovative and effective HIV testing services. Further research is needed to examine this approach in other settings.A crowdsourcing approach can help build and sustain community engagement related to HIV testing.Programs aiming to expand HIV testing should consider crowdsourcing as a tool to design tailored services. Approximately 14 million people living with HIV have yet to be tested, compromising the effectiveness of HIV treatment and prevention programs . EntrencIn China, HIV infection rates are still increasing among MSM, highlighting the need for innovative HIV testing interventions ,7. RecenCrowdsourcing can be a useful tool to develop community-driven HIV testing services in LMIC . It alloHowever, the potential for crowdsourcing as a tool to develop community health services, such as HIV testing, is uncertain; crowdsourcing for health improvement has focused on developing single components of health campaigns , rather The purpose of this stepped wedge cluster randomized controlled trial (RCT) was to evaluate a comprehensive crowdsourced intervention to increase HIV testing uptake among MSM in China.The study protocol provides a more detailed description of the trial design and analysis plan  19]. Br. Br19]. The steps for intervention development are shown in The nationwide open contest solicited concepts and images promoting HIV testing for 6 weeks, which was conducted from March to April of 2016. We promoted the contest through social media and in-person community events with CBO partners. Three social media platforms promoted the contest: WeChat, an instant messaging system similar to Facebook and Twitter; Weibo, a Chinese microblogging platform; and QQ, an instant messaging software. The four largest cities in Guangdong and Shandong Provinces  were selected to implement additional in-person community events to promote the open contest. In-person events included classroom presentations led by contest organizers, feedback sessions for potential contest entries, and announcements during events. Entries were evaluated by local MSM and experts using a 10-point scale . The top 40 entries (out of 431) were used as brainstorming materials for the regional designathon. Five images from this contest judged as exceptional were ultimately used in the final intervention as promotional materials.The regional designathon was conducted in May of 2016. It was a 3-day, hackathon-like event, during which teams of five each developed an HIV testing service strategy [The final intervention integrated exceptional images from the national contest  and the We selected four cities each from Guangdong province  and Shandong province . Each city had existing infrastructure for MSM HIV surveillance led by the local CDC and capacity to deliver new HIV testing services. Participants were eligible if they were born biologically male, age 16 or older, currently living and planning to live in one of the eight cities for 12 months post-enrollment, HIV-negative or unknown HIV status, had not had HIV testing within the past 3 months, had anal sex with a man at least once during their lifetime, and were willing to provide their cell phone numbers for follow-up. We recruited participants through China’s largest MSM social networking mobile phone application (app), Blued, by sending a survey invitation to registered users in the eight selected cities.We randomly assigned the order of intervention for each of the four cities in Guangdong province and Shandong province, then paired the cities by order of intervention . Prior tAfter electronically signing an informed consent form, all participants were asked to fill out a survey at baseline, and at every 3 months thereafter. Any participant who returned a photo of a positive test result was counseled to seek out confirmatory testing from their local CDC or CBO and was no longer eligible for subsequent follow-up surveys. Conditions of the control state, intervention, and post-intervention period are shown in To determine the necessary sample size for recruitment, we assumed that a crowdsourced intervention would be more effective than a conventional method for promoting HIV testing . We assuThe primary outcome of this study was the proportion of participants who tested for HIV over the previous 3 months. This was assessed based on self-reported data from each follow-up survey. We also measured the following secondary outcomes: facility-based HIV testing; HIV self-testing; syphilis testing; condomless sex; using WeChat, Weibo, QQ, or mobile phone applications to give/receive information about HIV testing; anticipated HIV stigma; HIV testing social norms; HIV testing self-efficacy; and community engagement in sexual health. We adapted validated scales to measure anticipated HIV stigma , HIV tesp-value. We encountered non-convergence problems when a log-binomial GLMM was used to estimate relative risk. Thus, we employed a log Poisson GLMM model [Descriptive analysis was used to summarize the demographic characteristics and HIV testing proportions. To investigate the effect of the intervention, we evaluated the difference in probability of HIV testing in the control period and in the intervention period (including the post-intervention period). We applied intention-to-treat analysis utilizing generalized linear mixed models (GLMMs) to evaluate the primary and secondary study outcomes. Intervention status and time indicators allowing for piecewise secular trends were considered fixed effects, while sites and individual participants with multiple measurements across the four follow-ups were considered random effects . We treaMM model .Sensitivity analyses were conducted to evaluate a per-protocol effect and a city/cluster-level effect of the intervention on HIV testing proportion in the past 3 months. The per-protocol analysis only included participants who reported viewing the intervention materials. For the city-level intervention effect, we used the HIV-testing proportion of each city across the four follow-ups as the outcome, and fit a normal linear mixed model that accounted for the random effect of sites to estimate the difference in HIV testing proportions. An intention-to-treat sensitivity analysis was conducted to evaluate the effectiveness of the intervention while adjusting for the province in the model. According to our prespecified analysis plan, we tested interactions with age (>30 years old versus ≤30 years old) and for cities with in-person community activities during the intervention development phase . We also used multiple imputations to examine the intervention effect. Using multiple imputations by chained equations and 30 imputed datasets, missing HIV testing data were imputed at each follow-up period using a logit model that included baseline variables  and intervention status during the respective follow-up period. A log Poisson GLMM was fit to estimate relative risk. Rubin’s rules were employed to pool the parameter estimates using the MIANALYZE Procedure in SAS . All datEthical approval was obtained from the institutional review committees at the Guangdong Provincial Center for Skin Diseases and STI Control , Shandong University , University of North Carolina at Chapel Hill , and the University of California, San Francisco . The trial is registered with ClinicalTrials.gov (NCT02796963).Participants were recruited from July 29, 2016, and followed until August 21, 2017. Overall, the study link was clicked 39,764 times. Of these, 16,193 withdrew from the survey prior to reading the consent form and 21,187 people did not meet eligibility requirements. Among the remaining, 1,003 did not sign the informed consent form. A total of 1,381 participants were enrolled. Of these, 203, 139, 134, and 203 were recruited from Guangzhou, Jiangmen, Zhuhai, and Shenzhen, respectively, in Guangdong province, while 180, 189, 182, and 151 were recruited from Yantai, Jinan, Qingdao, and Jining, respectively, in Shandong province .Based on the predetermined randomization schedule, 383 participants from Guangzhou and Yantai were assigned to the first intervention group (Group 1), 328 participants from Jiangmen and Jinan were assigned to the second group (Group 2), 316 participants from Zhuhai and Qingdao were assigned to the third group (Group 3), and 354 participants from Shenzhen and Jining were assigned to the fourth group (Group 4) .Among the 1,313 HIV-negative or status unknown participants after the third follow-up, 306 did not finish our last survey, with a loss-to-follow-up rate of 23%  greater during the intervention periods . In addip = 0.52). In addition, the intervention had a similar effect in cities with in-person community activities  compared to cities that did not have in-person activities   compared to MSM over 30 years old  .Out of 1,219 participants who completed at least one follow-up survey, 755 (62%) unique participants self-reported that they tested for HIV at any point during the study period. Of these, 642 (85%) tested during the intervention and post-intervention periods . Of the A total of 593 participants  received HIV self-testing. Of these, 442 (75%) used our self-testing platform, and 132 (30%) returned their self-test results via WeChat. Among these individuals, seven (5%) confirmed results were positive. We found that 93.9% of self-reported results were consistent with the returned photo of results .By the end of the study period, 99 participants  reported a positive HIV test result. The cumulative HIV prevalence among those who tested for HIV was 13.1%. Of these, 32 individuals seroconverted during the 1-year study period. Seroconversion was defined has having an initial negative HIV test and then a subsequent positive HIV test.HIV testing is an essential first step in the HIV care continuum. Although HIV testing is a major global health priority, in key populations large numbers of people remain untested . We recrWithin our study cohort, 62% of participants self-reported that they received HIV testing at least once during the study period, and 56% of previously untested MSM received HIV testing. This is consistent with the literature on global community-based HIV testing promotion ,28,29 buThe World Health Organization now recommends HIV self-testing . While tOur data indicated that the intervention was effective among both young and older MSM. Young MSM were heavily invested in all of the participatory activities that shaped the design and implementation of the intervention. Given the high rates of WeChat/Weibo use among youth, we speculate that crowdsourcing may be particularly effective among young MSM who use social media. Considering that our intervention engaged substantial youth in each city to provide feedback about HIV services ,20, crowOur study has several research and policy implications. It suggests that crowdsourcing could be used to design tailored HIV services, providing direction for subsequent crowdsourcing research. Also, crowdsourcing provides an inclusive, effective way to solicit community input; hence, it might be used to inform health policy ,39. FinaOur study has several limitations. First, most HIV testing data were based on self-report. Nevertheless, previous studies have demonstrated that HIV test self-report reliably correlates with operational HIV testing data ,41. WithIn summary, crowdsourcing can help spur the development of new HIV testing services. Our data demonstrate that a crowdsourcing approach effectively increased HIV testing in Chinese cities, especially HIV self-testing among MSM. While the crowdsourcing approach was implemented across cities, each city’s local contests helped shape and contextualize testing messages for local communities. Crowdsourcing approaches may be an important tool for localizing and differentiating HIV services.S1 Text(DOCX)Click here for additional data file.S2 Text(DOCX)Click here for additional data file.S3 Text(DOCX)Click here for additional data file.S4 Text(DOCX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S1 CONSORT Checklist(DOCX)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.S1 TableMSM, men who have sex with men.(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 TableMSM, men who have sex with men.(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 TableMSM, men who have sex with men.(DOCX)Click here for additional data file.