Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-coding RNA in endothelial-to-mesenchymal transition

Abstract Endothelial-to-mesenchymal transition (EndMT) is the process wherein endothelial cells lose their typical endothelial cell markers and functions and adopt a mesenchymal-like phenotype. EndMT is required for development of the cardiac valves, the pulmonary and dorsal aorta, and arterial maturation, but activation of the EndMT programme during adulthood is believed to contribute to several pathologies including organ fibrosis, cardiovascular disease, and cancer. Non-coding RNAs, including microRNAs, long non-coding RNAs, and circular RNAs, modulate EndMT during development and disease. Here, we review the mechanisms by which non-coding RNAs facilitate or inhibit EndMT during development and disease and provide a perspective on the therapeutic application of non-coding RNAs to treat fibroproliferative cardiovascular disease.
“I Despise Myself for Thinking about Them.” A Thematic Analysis of the Mental Health Implications and Employed Coping Mechanisms of Self-Reported Non-Offending Minor Attracted Persons

ABSTRACT ‘Non-offending pedophiles’ or ‘minor attracted persons’ are individuals who suppress an attraction to children. Previous analyses of this population’s mental illness employed overt self-report methods, limited by social desirability. Additionally, studies assessing the coping mechanisms employed to remain offense-free are underpowered; understanding of these would facilitate the rehabilitation of prior offenders. A thematic analysis of coping mechanisms and mental illness was conducted on 5,210 posts on the ‘Virtuous Pedophiles’ forum. Four themes emerged for coping mechanisms: Managing risk and attraction to children, Managing mood, Managing preferences prosocially and Friends, family and relationships, with 13 subthemes. Five themes emerged for mental ill-health, including: Addiction, Anxiety, Depression, Self-hatred/Self-harm/Suicide and Other. Self-hatred/Self-harm/Suicide accounted for almost a third of discussed mental ill-health. These results highlight the severity of mental ill-health amongst this population and the coping mechanisms employed to remain offense-free.
Using the Personalized Advantage Index for individual treatment allocation to cognitive behavioral therapy (CBT) or a CBT with integrated exposure and emotion-focused elements (CBT-EE)

Abstract Even though different psychotherapeutic interventions for depression have shown to be effective, patients suffering from depression vary substantially in their treatment response. The goal of this study was to answer the following research questions: (1) What are the most important predictors determining optimal treatment allocation to cognitive behavioral therapy (CBT) or CBT with integrated exposure and emotion-focused elements (CBT-EE)? , and (2) Would model-determined treatment allocation using this predictive information result in better treatment outcomes? Bayesian Model Averaging (BMA) was applied to the data of a randomized controlled trial comparing the efficacy of CBT and CBT-EE in depressive outpatients. Predictions were made for every patient for both treatment conditions and an optimal versus a suboptimal treatment was identified in each case. An index comparing the two estimates, the Personalized Advantage Index (PAI), was calculated. Different predictors were found for both conditions. A PAI of 1.35 BDI-II points for the two conditions was found and 46% of the sample was predicted to have a clinically meaningful advantage in one of the therapies. Although the utility of the PAI approach must be further confirmed in prospective research, the present study study promotes the identification of specific interventions favorable for specific patients.
Findings From a Trial of the Smartphone and OnLine Usage-based eValuation for Depression (SOLVD) Application: What Do Apps Really Tell Us About Patients with Depression? Concordance Between App-Generated Data and Standard Psychiatric Questionnaires for Depression and Anxiety

Objective: Depression imposes a notable societal burden, with limited treatment success despite multiple available psychotherapy and medications choices. Potential reasons may include the heterogeneity of depression diagnoses and the presence of comorbid anxiety symptoms. Despite technological advances and the introduction of many mobile phone applications (apps) claiming to relieve depression, major gaps in knowledge still exist regarding what apps truly measure and how they correlate with psychometric questionnaires. The goal of this study was to evaluate whether mobile daily mood self-ratings may be useful in monitoring and classifying depression symptoms in a clinically depressed population compared with standard psychometric instruments including the Patient Health Questionaire-9 (PHQ-9), the Hamilton Rating Scale for Depression (HAM-D), and the Hamilton Anxiety Rating Scale (HAM-A). Method: For this study, 22 patients with major depressive disorder with or without comorbid anxiety disorder were recruited. The diagnosis of depression was confirmed through the Mini International Neuropsychiatric Interview (MINI). Over an 8-week period, daily moods were self-reported through the Smartphone and OnLine Usage-based eValuation for Depression (SOLVD) application, a custom-designed application that was downloaded onto patients’ mobile devices. Depression and anxiety symptoms were also measured biweekly using the HAM-D, HAM-A, and PHQ-9. Results: Significant correlations were observed among self-evaluated mood, daily steps taken, SMS (text) frequency, average call duration, and biweekly psychometric scores (|r|>0.5, P<0.05). The correlation coefficients were higher in individuals with more severe depressive symptoms. Conclusions: Although this study, given its limited sample size, was exploratory in nature, it helps fill a significant gap in our knowledge of the concordance between ratings obtained on the Ham-D, Ham-A, and the PHQ-9 psychometric instruments and data obtained via a smartphone app. These questionnaires represent gold-standard, commonly used psychiatric research/clinical instruments, and, thus, this information can serve as a foundation for digital phenotyping for depression and pave the way for interventional studies using smartphone applications.
A latent unknown clustering integrating multi-omics data (LUCID) with phenotypic traits

MOTIVATION Epidemiologic, clinical, and translational studies are increasingly generating multiplatform omics data. Methods that can integrate across multiple high-dimensional data types while accounting for differential patterns are critical for uncovering novel associations and underlying relevant subgroups. RESULTS We propose an integrative model to estimate latent unknown clusters (LUCID) aiming to both distinguish unique genomic, exposure and informative biomarkers/omic effects while jointly estimating subgroups relevant to the outcome of interest. Simulation studies indicate that we can obtain consistent estimates reflective of the true simulated values, accurately estimate subgroups, and recapitulate subgroup-specific effects. We also demonstrate the use of the integrated model for future prediction of risk subgroups and phenotypes. We apply this approach to two real data applications to highlight the integration of genomic, exposure, and metabolomic data. AVAILABILITY AND IMPLEMENTATION The LUCID method is implemented through the LUCIDus R package available on CRAN (https://CRAN.R-project.org/package=LUCIDus). SUPPLEMENTARY INFORMATION Supplementary materials are available at Bioinformatics online.
Young children, adolescent girls and women with type 1 diabetes are more overweight and obese than reference populations, and this is associated with increased cardiovascular risk factors

Overweight and obesity are frequently reported in young persons with type 1 diabetes, however its relative magnitude in comparison to the general population is not well understood. This study compared the prevalence of overweight and obesity in young persons with type 1 diabetes to a reference population and explored possible associated factors, including gender, age, HbA1c, insulin regimen, age at diagnosis, diabetes duration, socio‐economic status and cardiovascular disease risk factors.
A patient and family reporting system for perceived ambulatory note mistakes: experience at 3 U.S. healthcare centers

OBJECTIVE The study sought to test a patient and family online reporting system for perceived ambulatory visit note inaccuracies. MATERIALS AND METHODS We implemented a patient and family electronic reporting system at 3 U.S. healthcare centers: a northeast urban academic adult medical center (AD), a northeast urban academic pediatric medical center (PED), and a southeast nonprofit hospital network (NET). Patients and families reported potential documentation inaccuracies after reading primary care and subspecialty visit notes. Results were characterized using descriptive statistics and coded for clinical relevance. RESULTS We received 1440 patient and family reports (780 AD, 402 PED, and 258 NET), and 27% of the reports identified a potential inaccuracy (25% AD, 35% PED, 28% NET). Among these, patients and families indicated that the potential inaccuracy was important or very important in 58% of reports (55% AD, 55% PED, 71% NET). The most common types of potential inaccuracies included description of symptoms (21%), past medical problems (21%), medications (18%), and important information that was missing (15%). Most patient- and family-reported inaccuracies resulted in a change to care or to the medical record (55% AD, 67% PED, data not available at NET). DISCUSSION About one-quarter of patients and families using an online reporting system identified potential documentation inaccuracies in visit notes and more than half were considered important by patients and clinicians, underscoring the potential role of patients and families as ambulatory safety partners. CONCLUSIONS Partnering with patients and families to obtain reports on inaccuracies in visit notes may contribute to safer care. Mechanisms to encourage greater use of patient and family reporting systems are needed.
Effects of dietary threonine supplementation on productivity and expression of genes related to protein deposition and amino acid transportation in breeder hens of yellow-feathered chicken and their offspring

ABSTRACT This study investigated the effects of the dietary threonine (Thr) levels on the performance, offspring traits, embryo amino acid transportation, and protein deposition in breeder hens of yellow-feathered chickens. In total, 720 breeder hens of Lingnan yellow-feathered chickens were randomly assigned to 1 of 6 dietary treatments, with 6 replicates per treatment (20 birds per replicate). The breeder hens were fed either basal diet (Thr = 0.38%) or basal diet supplemented with 0.12, 0.24, 0.36, 0.48, or 0.60% Thr from 197 to 266 D. There was a positive response in terms of the laying rate after adding different levels of Thr to the diet, but no significant effects on the average daily gain, average daily egg weight, feed conversion ratio, average broken eggs, and unqualified egg rate (P > 0.05). However, the eggshell strength and eggshell percentage decreased in a linear manner as the dietary Thr concentration increased (P = 0.05). Dietary supplementation with Thr had significant effects on the expression of mucin 2 (MUC2) in the uterus and zonula occludens protein 1 (ZO-1) in the duodenum of breeders (P < 0.05). In chick embryos at embryonic age 18 D, significant upregulation of poultry target of rapamycin (pTOR) occurred in the liver and breast muscle, as well as threonine dehydrogenase (TDH) in the thigh, and aminopeptidase (ANPEP) (P < 0.05) in the duodenum and ileum due to dietary Thr supplementation, but there were no effects on MUC2 expression in the duodenum and ileum (P > 0.05). The livability of the progeny broilers tended to increase with the dietary Thr concentration (quadratic, P = 0.08). Thus, dietary supplementation with Thr had positive effects on the laying production by breeder hens and offspring performance, and it also regulated the expression levels of genes related to amino acid transportation and protein deposition. The optimal dietary Thr concentration that maximized the laying rate in yellow-feathered chicken breeders aged 197 to 266 D was 0.68% according to quadratic regression analysis.
Allosteric gate modulation confers K+ coupling in glutamate transporters

Excitatory amino acid transporters (EAATs) mediate glial and neuronal glutamate uptake to terminate synaptic transmission and to ensure low resting glutamate concentrations. Effective glutamate uptake is achieved by cotransport with 3 Na+ and 1 H+, in exchange with 1 K+. The underlying principles of this complex transport stoichiometry remain poorly understood. We use molecular dynamics simulations and electrophysiological experiments to elucidate how mammalian EAATs harness K+ gradients, unlike their K+‐independent prokaryotic homologues. Glutamate transport is achieved via elevator‐like translocation of the transport domain. In EAATs, glutamate‐free re‐translocation is prevented by an external gate remaining open until K+ binding closes and locks the gate. Prokaryotic GltPh contains the same K+‐binding site, but the gate can close without K+. Our study provides a comprehensive description of K+‐dependent glutamate transport and reveals a hitherto unknown allosteric coupling mechanism that permits adaptions of the transport stoichiometry without affecting ion or substrate binding.
How parasite interaction strategies alter virulence evolution in multi‐parasite communities

The majority of organisms host multiple parasite species, each of which can interact with hosts and competitors through a diverse range of direct and indirect mechanisms. These within‐host interactions can directly alter the mortality rate of coinfected hosts and alter the evolution of virulence (parasite‐induced host mortality). Yet we still know little about how within‐host interactions affect the evolution of parasite virulence in multi‐parasite communities. Here, we modeled the virulence evolution of two coinfecting parasites in a host population in which parasites interacted through cross immunity, immune suppression, immunopathology, or spite. We show (1) that these within‐host interactions have different effects on virulence evolution when all parasites interact with each other in the same way versus when coinfecting parasites have unique interaction strategies, (2) that these interactions cause the evolution of lower virulence in some hosts, and higher virulence in other hosts, depending on the hosts infection status, and (3) that for cross immunity and spite, whether parasites increase or decrease the evolutionarily stable virulence in coinfected hosts depended on interaction strength. These results improve our understanding of virulence evolution in complex parasite communities, and show that virulence evolution must be understood at the community scale.
Docking flexible cyclic peptides with AutoDock CrankPep.

While a new therapeutic cyclic peptide is approved nearly every year, docking large macrocycles has remained challenging. Here, we present a new version of our peptide docking software AutoDock CrankPep (ADCP), extended to dock peptides cyclized through their backbone and/or sidechain disulfide bonds. We show that within the top 10 solutions, ADCP identifies the proper interactions for 71% of a dataset of 38 complexes, thus making it a useful tool for rational peptide-based drug design.
Evolutionary Ecology of Wolbachia Releases for Disease Control.

Wolbachia is an endosymbiotic Alphaproteobacteria that can suppress insect-borne diseases through decreasing host virus transmission (population replacement) or through decreasing host population density (population suppression). We contrast natural Wolbachia infections in insect populations with Wolbachia transinfections in mosquitoes to gain insights into factors potentially affecting the long-term success of Wolbachia releases. Natural Wolbachia infections can spread rapidly, whereas the slow spread of transinfections is governed by deleterious effects on host fitness and demographic factors. Cytoplasmic incompatibility (CI) generated by Wolbachia is central to both population replacement and suppression programs, but CI in nature can be variable and evolve, as can Wolbachia fitness effects and virus blocking. Wolbachia spread is also influenced by environmental factors that decrease Wolbachia titer and reduce maternal Wolbachia transmission frequency. More information is needed on the interactions between Wolbachia and host nuclear/mitochondrial genomes, the interaction between invasion success and local ecological factors, and the long-term stability of Wolbachia-mediated virus blocking. Expected final online publication date for the Annual Review of Genetics, Volume 53 is November 23, 2019. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Deregulation of long noncoding RNA SNHG17 and TTC28-AS1 is associated with type 2 diabetes mellitus

Abstract Long noncoding RNAs (lncRNAs) have emerged as key players in several biological processes and complex diseases including type 2 diabetes mellitus (T2DM). The purpose of this study was to investigate the expression levels of SNHG17 and TTC28-AS1 in T2DM patients. Quantitative real‐time RT‐PCR analysis was performed using peripheral blood mononuclear cells (PBMCs) samples from patients diagnosed with T2DM and healthy controls. Binary logistic regression analysis was carried out to determine the odds of development of T2DM based on expression levels of lncRNAs and clinical characteristic of the subjects. Spearman’s correlation analysis was used to clarify the correlation between SNHG17 and TTC28-AS1 expressions to metabolic features. We found that SNHG17 and TTC28-AS1were down-regulated in the T2DM group compared to the healthy control group. The logistic regression revealed that body mass index (BMI), systolic blood pressure (SBP), fasting blood glucose (FBG) and TTC28-AS1 expression substantially affect T2DM susceptibility. Furthermore, expression of SNHG17 was negatively correlated with high‐density lipoprotein cholesterol (HDL‐C) and expression of TTC28-AS1 was positively correlated with low‐density lipoprotein cholesterol (LDL‐C). Decreased expressions of lncRNAs TTC28-AS1 and SNHG17 in T2DM are possibly associated with the development of T2DM.
Prostate‐specific membrane antigen‐positron emission tomography/computed tomography (PSMA‐PET/CT)‐guided stereotactic ablative body radiotherapy for oligometastatic prostate cancer: a single‐institution experience and review of the published literature

To report the outcomes of stereotactic ablative body radiotherapy (SABR) in men with oligometastatic prostate cancer (PCa) diagnosed on prostate‐specific membrane antigen (PSMA)‐positron emission tomography/computed tomography (PET/CT), based on a single‐institution experience and the published literature.
BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches

Abstract As the first web server to analyze various biological sequences at sequence level based on machine learning approaches, many powerful predictors in the field of computational biology have been developed with the assistance of the BioSeq-Analysis. However, the BioSeq-Analysis can be only applied to the sequence-level analysis tasks, preventing its applications to the residue-level analysis tasks, and an intelligent tool that is able to automatically generate various predictors for biological sequence analysis at both residue level and sequence level is highly desired. In this regard, we decided to publish an important updated server covering a total of 26 features at the residue level and 90 features at the sequence level called BioSeq-Analysis2.0 (http://bliulab.net/BioSeq-Analysis2.0/), by which the users only need to upload the benchmark dataset, and the BioSeq-Analysis2.0 can generate the predictors for both residue-level analysis and sequence-level analysis tasks. Furthermore, the corresponding stand-alone tool was also provided, which can be downloaded from http://bliulab.net/BioSeq-Analysis2.0/download/. To the best of our knowledge, the BioSeq-Analysis2.0 is the first tool for generating predictors for biological sequence analysis tasks at residue level. Specifically, the experimental results indicated that the predictors developed by BioSeq-Analysis2.0 can achieve comparable or even better performance than the existing state-of-the-art predictors.
Dietary intakes of flavan-3-ols and cardiometabolic health: systematic review and meta-analysis of randomized trials and prospective cohort studies

ABSTRACT Background Although available data suggest that some dietary flavan-3-ol sources reduce cardiometabolic risk, to our knowledge no review has systematically synthesized their specific contribution. Objective We aimed to examine, for the first time, if there is consistent evidence that higher flavan-3-ol intake, irrespective of dietary source, reduces cardiometabolic risk. Methods MEDLINE, Cochrane Central, and Commonwealth Agricultural Bureau abstracts were searched for prospective cohorts and randomized controlled trials (RCTs) published from 1946 to March 2019 on flavan-3-ol intake and cardiovascular disease (CVD) risk. Random-effects models meta-analysis was used. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach assessed the strength of evidence. Results Of 15 prospective cohorts (23 publications), 4 found highest compared with lowest habitual intakes of flavan-3-ols were associated with a 13% reduction in risk of CVD mortality and 2 found a 19% reduction in risk of chronic heart disease (CHD) incidence. Highest compared with lowest habitual intakes of monomers were associated with a reduction in risk of type 2 diabetes mellitus (T2DM) (n = 5) and stroke (n = 4) (10% and 18%, respectively). No association was found for hypertension. Of 156 RCTs, flavan-3-ol intervention resulted in significant improvements in acute/chronic flow-mediated dilation (FMD), systolic (SBP) and diastolic blood pressure (DBP), total cholesterol (TC), LDL and HDL cholesterol, triglycerides (TGs), hemoglobin A1c (HbA1c), and homeostasis model assessment of insulin resistance (HOMA-IR). All analyses, except HbA1c, were associated with moderate/high heterogeneity. When analyses were limited to good methodological quality studies, improvements in TC, HDL cholesterol, SBP, DBP, HOMA-IR, and acute/chronic FMD remained significant. In GRADE evaluations, there was moderate evidence in cohort studies that flavan-3-ol and monomer intakes were associated with reduced risk of CVD mortality, CHD, stroke, and T2DM, whereas RCTs reported improved TC, HDL cholesterol, SBP, and HOMA-IR. Conclusions Available evidence supports a beneficial effect of flavan-3-ol intake on cardiometabolic outcomes, but there was considerable heterogeneity in the meta-analysis. Future research should focus on an integrated intake/biomarker approach in cohorts and high-quality dose–response RCTs. This review was registered at www.crd. york.ac. uk/PROSPERO/ as CRD42018035782.