Miracle-dz/UniFAR-FTUs huggingface dataset:
Accelerometer-measured sleep duration and clinical cardiovascular risk factor scores in older women.

BACKGROUND Evidence suggests that short and long sleep durations are potential lifestyle factors associated with cardiovascular disease (CVD). Research on sleep duration and CVD risk is limited by use of self-report sleep measures, homogeneous populations, and studies on individual CVD risk factors. For women, risk of CVD and inadequate sleep duration increases with age. We hypothesized that accelerometer-measured sleep duration was associated with 10-year predicted probability of future CVD risk in a cohort of aging women. METHODS This cross-sectional analysis included 3367 older women (mean age 78.9 years; 53.3% White), from the Objective Physical Activity and Cardiovascular Health Study, ancillary study to the Women's Health Initiative. Women wore ActiGraph GT3X+ accelerometers on the hip for 24 hours/7 days. A 10-year predicted probability of future CVD risk, the Reynolds Risk Score (RRS), was computed using age, systolic blood pressure, high-sensitivity C-reactive protein (CRP), total and HDL cholesterol, diabetes mellitus status, smoking status, and family history of CVD. Average nightly sleep duration was derived from accelerometer data. Adjusted linear regression models investigated the association between sleep duration and RRS. RESULTS Results suggested a U-shaped relationship between sleep duration and RRS, with both short and long sleep associated with higher RRS (p <0.001). The association remained significant after adjustments for race/ethnicity, education, lifestyle factors and health status indicators. CONCLUSION In older women, actigraphy-ascertained sleep duration was associated with a 10-year predicted probability of future CVD risk. This study supports sleep duration as a modifiable risk factor for CVD in older women.
Current Progress on Equilibrative Nucleoside Transporter Function and Inhibitor Design

Physiological nucleosides are used for the synthesis of DNA, RNA, and ATP in the cell and serve as universal mammalian signaling molecules that regulate physiological processes such as vasodilation and platelet aggregation by engaging with cell surface receptors. The same pathways that allow uptake of physiological nucleosides mediate the cellular import of synthetic nucleoside analogs used against cancer, HIV, and other viral diseases. Physiological nucleosides and nucleoside drugs are imported by two families of nucleoside transporters: the SLC28 concentrative nucleoside transporters (CNTs) and SLC29 equilibrative nucleoside transporters (ENTs). The four human ENT paralogs are expressed in distinct tissues, localize to different subcellular sites, and transport a variety of different molecules. Here we provide an overview of the known structure–function relationships of the ENT family with a focus on ligand binding and transport in the context of a new hENT1 homology model. We provide a generic residue numbering system for the different ENTs to facilitate the interpretation of mutational data produced using different ENT homologs. The discovery of paralog-selective small-molecule modulators is highly relevant for the design of new therapies and for uncovering the functions of poorly characterized ENT family members. Here, we discuss recent developments in the discovery of new paralog-selective small-molecule ENT inhibitors, including new natural product-inspired compounds. Recent progress in the ability to heterologously produce functional ENTs will allow us to gain insight into the structure and functions of different ENT family members as well as the rational discovery of highly selective inhibitors.
Evolution & Development

Correspondence Wim Hordijk, Konrad Lorenz Institute for Evolution and Cognition Research, Martinstrasse 12, 3400 Klosterneuburg, Austria. Email: wim@WorldWideWanderings.net Abstract Developmental mechanisms not only produce an organismal phenotype, but they also structure the way genetic variation maps to phenotypic variation. Here, we revisit a computational model for the evolution of ontogeny based on cellular automata, in which evolution regularly discovered two alternative mechanisms for achieving a selected phenotype, one showing high modularity, the other showing morphological integration. We measure a primary variational property of the systems, their distribution of fitness effects of mutation. We find that the modular ontogeny shows the evolution of mutational robustness and ontogenic simplification, while the integrated ontogeny does not. We discuss the wider use of this methodology on other computational models of development as well as real organisms.
Serum uromodulin is inversely associated with the metabolic syndrome in the KORA F4 study

Objective Metabolic syndrome and obesity are risk factors for chronic kidney disease. However, early kidney alterations may escape diagnosis in these conditions due to glomerular hyperfiltration. Uromodulin, a glycoprotein exclusively synthesized in tubular cells of the thick ascending limb of Henle's loop, is a novel tissue-specific biomarker for kidney function. In contrast to the commonly used markers creatinine and cystatin C, serum uromodulin does not primarily depend on glomerular filtration. We hypothesized that serum uromodulin is a marker for metabolic syndrome and related components. Design The analyses included 1088 participants of the population-based KORA F4 study aged 62–81 years. Metabolic syndrome was present in 554 participants. After a mean follow-up time of 6.5 years, 621 participants were reevaluated, of which 92 had developed incident metabolic syndrome. Methods The association of serum uromodulin with metabolic syndrome and its components were assessed using multivariable logistic regression models. Results Serum uromodulin was inversely associated with metabolic syndrome after adjustment for sex, age, estimated glomerular filtration rate, physical activity, smoking, alcohol consumption and high-sensitivity C-reactive protein (OR 0.65; 95% CI 0.56–0.76 per standard deviation uromodulin; P < 0.001). Serum uromodulin was inversely associated with all single components of metabolic syndrome. However, serum uromodulin was not associated with new-onset metabolic syndrome after the follow-up period of 6.5 ± 0.3 years (OR 1.18; 95% CI 0.86–1.60). Conclusions Serum uromodulin is independently associated with prevalent, but not with incident metabolic syndrome. Low serum uromodulin may indicate a decreased renal reserve in the metabolic syndrome.
Inferring seasonal infection risk at population and regional scales from serology samples.

Accurate estimates of seasonal infection risk can be used by animal health officials to predict future disease risk and better understand the mechanisms driving disease dynamics. It can be difficult to estimate seasonal infection risk in wildlife disease systems because surveillance assays typically target antibodies ('serosurveillance'), which are not necessarily indicative of current infection, and serosurveillance sampling is often opportunistic. Recently developed methods estimate past time of infection from serosurveillance data using quantitative serological assays that indicate the amount of antibodies in a serology sample. However, current methods do not account for common opportunistic and uneven sampling associated with serosurveillance data. We extended the framework of survival analysis to improve estimates of seasonal infection risk from serosurveillance data across population and regional scales. We found that accounting for the right-censored nature of quantitative serology samples greatly improved estimates of seasonal infection risk, even when sampling was uneven in time. Survival analysis can also be used to account for common challenges when estimating infection risk from serology data, such as biases induced by host demography and continually elevated antibodies following infection. The framework developed herein is widely applicable for estimating seasonal infection risk from serosurveillance data in humans, wildlife, and livestock.
Machine learning-based chemical binding similarity using evolutionary relationships of target genes

Abstract Chemical similarity searching is a basic research tool that can be used to find small molecules which are similar in shape to known active molecules. Despite its popularity, the retrieval of local molecular features that are critical to functional activity related to target binding often fails. To overcome this limitation, we developed a novel machine learning-based chemical binding similarity score by using various evolutionary relationships of binding targets. The chemical similarity was defined by the probability of chemical compounds binding to identical targets. Comprehensive and heterogeneous multiple target-binding chemical data were integrated into a paired data format and processed using multiple classification similarity-learning models with various levels of target evolutionary information. Encoding evolutionary information to chemical compounds through their binding targets substantially expanded available chemical-target interaction data and significantly improved model performance. The output probability of our integrated model, referred to as ensemble evolutionary chemical binding similarity (ensECBS), was effective for finding hidden chemical relationships. The developed method can serve as a novel chemical similarity tool that uses evolutionarily conserved target binding information.
A Global View to HBV Chronic Infection: Evolving Strategies for Diagnosis, Treatment and Prevention in Immunocompetent Individuals

Hepatitis B Virus (HBV) is a significant public health challenge. Around 250 million people live with chronic HBV infection. With a global approach to this issue, we focus on new perspective in diagnosis, management and prevention of HBV chronic infection. Precise diagnosis of HBV status is crucial to guide patient management. Although available drugs reduce the risk of liver disease progression, they are not able to definitely eradicate HBV, and new therapeutic options are urgently needed. Thus, prevention of HBV infection is still the most effective strategy to achieve the control of the disease. Key aspects of prevention programs include surveillance of viral hepatitis, screening programs and immunization strategies. In spite of the high success rate of licensed HBV vaccines, a need for improved vaccine persists, especially in order to provide coverage of current non-responders.
Long-term follow-up of patients in the TIght COntrol of inflammation in early Psoriatic Arthritis (TICOPA) trial.

OBJECTIVES The TIght COntrol of inflammation in early Psoriatic Arthritis (TICOPA) study was the first strategy trial in psoriatic arthritis using an early treat-to-target strategy to improve clinical outcomes. The current study aimed to review a cohort of patients who had completed TICOPA to judge if the clinical advantage gained by participants in the tight control (TC) arm was sustained, and to explore subsequent therapy. METHODS A case note review was conducted for a cohort of patients who had participated in TICOPA. Current drug use and clinical status were obtained, with low disease activity judged as no tender or swollen joints, no dactylitis and enthesitis, and no change in treatment required. RESULTS Approximately five years after completion of the TICOPA study, notes were reviewed for 110 patients [TC, n = 54; standard care (StdC), n = 56]. Disease activity was found to be similar in both groups (current low disease activity: TC 69%, StdC 76%). Biologic use at the end of the study was higher in the TC arm (TC 33%, StdC 9%), but at review a similar percentage in both groups were taking biologic drugs (TC 54%, StdC 52%), whereas MTX use diminished. CONCLUSION After several years, clinical outcomes and therapeutic drug use were similarly good for patients in both arms of the TICOPA study, with no obvious clinical advantage after TC ended. Notably, TC did not result in greater biological use long term, and MTX use decreased in both arms of the study.
Macroevolutionary Analyses Suggest That Environmental Factors, Not Venom Apparatus, Play Key Role in Terebridae Marine Snail Diversification

Abstract How species diversification occurs remains an unanswered question in predatory marine invertebrates, such as sea snails of the family Terebridae. However, the anatomical disparity found throughput the Terebridae provides a unique perspective for investigating diversification patterns in venomous predators. In this study, a new dated molecular phylogeny of the Terebridae is used as a framework for investigating diversification of the family through time, and for testing the putative role of intrinsic and extrinsic traits, such as shell size, larval ecology, bathymetric distribution, and anatomical features of the venom apparatus, as drivers of terebrid species diversification. Macroevolutionary analysis revealed that when diversification rates do not vary across Terebridae clades, the whole family has been increasing its global diversification rate since 25 Ma. We recovered evidence for a concurrent increase in diversification of depth ranges, while shell size appeared to have undergone a fast divergence early in terebrid evolutionary history. Our data also confirm that planktotrophy is the ancestral larval ecology in terebrids, and evolutionary modeling highlighted that shell size is linked to larval ecology of the Terebridae, with species with long-living pelagic larvae tending to be larger and have a broader size range than lecithotrophic species. Although we recovered patterns of size and depth trait diversification through time and across clades, the presence or absence of a venom gland (VG) did not appear to have impacted Terebridae diversification. Terebrids have lost their venom apparatus several times and we confirm that the loss of a VG happened in phylogenetically clustered terminal taxa and that reversal is extremely unlikely. Our findings suggest that environmental factors, and not venom, have had more influence on terebrid evolution.
MRSA outbreak in a tertiary neonatal intensive care unit in Iceland

Abstract Introduction: Preventing the spread of methicillin-resistant Staphylococcus aureus (MRSA) and understanding the pathophysiology and transmission is essential. This study describes an MRSA outbreak in a neonatal intensive care unit in Reykjavik, Iceland at a time where no screening procedures were active. Materials and methods: After isolating MRSA in the neonatal intensive care unit in 2015, neonates, staff members and parents of positive patients were screened and environmental samples collected. The study period was from 14 April 2015 until 31 August 2015. Antimicrobial susceptibility testing, spa-typing and whole genome sequencing were done on MRSA isolates. Results: During the study period, 96/143 admitted patients were screened for colonization. Non-screened infants had short admissions not including screening days. MRSA was isolated from nine infants and seven parents. All tested staff members were negative. Eight infants and six parents carried MRSA ST30-IVc with spa-type t253 and one infant and its parent carried MRSA CC9-IVa (spa-type t4845) while most environmental samples were MRSA CC9-IVa (spa-type t4845). Whole genome sequencing revealed close relatedness between all ST30-IVc and CC9-IVa isolates, respectively. All colonized infants received decolonization treatment, but 3/9 were still positive when last sampled. Discussion: The main outbreak source was a single MRSA ST30-IVc (spa-type t253), isolated for the first time in Iceland. A new CC9-IVa (spa-type t4845) was also identified, most abundant on environmental surfaces but only in one patient. The reason for the differences in the epidemiology of the two strains is not clear. The study highlights a need for screening procedures in high-risk settings and guidelines for neonatal decolonization.
Breast Cancer Index and prediction of benefit from extended endocrine therapy in breast cancer patients treated in the Adjuvant Tamoxifen—To Offer More? (aTTom) trial

Abstract Background Extending the duration of adjuvant endocrine therapy reduces the risk of recurrence in a subset of women with early-stage hormone receptor-positive (HR+) breast cancer. Validated predictive biomarkers of endocrine response could significantly improve patient selection for extended therapy. Breast cancer index (BCI) [HOXB13/IL17BR ratio (H/I)] was evaluated for its ability to predict benefit from extended endocrine therapy in patients previously randomized in the Adjuvant Tamoxifen—To Offer More? (aTTom) trial. Patients and methods Trans-aTTom is a multi-institutional, prospective–retrospective study in patients with available formalin-fixed paraffin-embedded primary tumor blocks. BCI testing and central determination of estrogen receptor (ER) and progesterone receptor (PR) status by immunohistochemistry were carried out blinded to clinical outcome. Survival endpoints were evaluated using Kaplan–Meier analysis and Cox regression with recurrence-free interval (RFI) as the primary endpoint. Interaction between extended endocrine therapy and BCI (H/I) was assessed using the likelihood ratio test. Results Of 583 HR+, N+ patients analyzed, 49% classified as BCI (H/I)-High derived a significant benefit from 10 versus 5 years of tamoxifen treatment [hazard ratio (HR): 0.35; 95% confidence interval (CI) 0.15–0.86; 10.2% absolute risk reduction based on RFI, P = 0.027]. BCI (H/I)-low patients showed no significant benefit from extended endocrine therapy (HR: 1.07; 95% CI 0.69–1.65; −0.2% absolute risk reduction; P = 0.768). Continuous BCI (H/I) levels predicted the magnitude of benefit from extended tamoxifen, whereas centralized ER and PR did not. Interaction between extended tamoxifen treatment and BCI (H/I) was statistically significant (P = 0.012), adjusting for clinicopathological factors. Conclusion BCI by high H/I expression was predictive of endocrine response and identified a subset of HR+, N+ patients with significant benefit from 10 versus 5 years of tamoxifen therapy. These data provide further validation, consistent with previous MA.17 data, establishing level 1B evidence for BCI as a predictive biomarker of benefit from extended endocrine therapy. Trial registration ISRCTN17222211; NCT00003678.
Combined Therapy With Hyperbaric Oxygen and Melatonin Effectively Reduce Brain Infarct Volume and Preserve Neurological Function After Acute Ischemic Infarct in Rat.

This study tested the hypothesis that combined hyperbaric oxygen (HBO) and melatonin (Mel) was superior to either one for protecting the brain functional and parenchymal integrity from acute ischemic stroke (IS) injury. Adult-male Sprague-Dawley rats were divided into groups 1 (sham-operated control), 2 (IS), 3 (IS + HBO), 4 (IS + Mel), and 5 (IS + HBO-Mel). By day 28 after IS, the brain infarct area (BIA) was lowest in group 1, highest in group 2, significantly higher in groups 3 and 4 than in group 5, but not different between groups 3 and 4. The neurological function at day 7, 14, and 28 exhibited an opposite pattern to BIA among the 5 groups. The protein expressions of inflammatory (IL-1β/IL-6/iNOS/TNF-α/p-NF-κB), apoptotic (cleaved-caspase3/cleaved-PARP/mitochondrial Bax), mitochondrial/DNA-damaged (cytochrome-C/γ-H2AX), oxidative stress (NOX-1/NOX-2), and autophagy (i.e. ratio of CL3B-II/CL3B-I) biomarkers displayed an identical pattern of BIA among 5 groups. Cellular expressions of inflammation (F4/80+/GFAP+) and DNA-damaged biomarker (γ-H2AX+) exhibited an identical pattern, whereas the integrities of myelin sheath/neuron (MPB+/NeuN+), endothelial cell (CD31+/vWF+), and number of small vessels exhibited an opposite pattern of BIA among the 5 groups. Combined HBO-Mel therapy offered an additional benefit in protecting the brain against IS injury.
Region specific parasympathetic nerve remodeling in the left atrium contributes to creation of a vulnerable substrate for atrial fibrillation.

Atrial fibrillation (AF) is the most common heart rhythm disorder and a major cause of stroke. Unfortunately, current therapies for AF are suboptimal, largely because the molecular mechanisms underlying AF are poorly understood. Since the autonomic nervous system is thought to increase vulnerability to AF, we investigated in a rapid atrial pacing (RAP) canine model the anatomic and electrophysiological characteristics of autonomic remodeling in different regions of the left atrium. RAP led to marked hypertrophy of parent nerve bundles in the posterior left atrium (PLA), resulting in a global increase in parasympathetic and sympathetic innervation throughout the left atrium. Parasympathetic fibers were more heterogeneously distributed in the PLA when compared to other left atrial regions; this led to greater fractionation and disorganization of AF electrograms in the PLA. Computational modeling revealed that heterogeneously distributed parasympathetic activity exacerbates sympathetic substrate for wave break and reentry. We further discovered that levels of Nerve Growth Factor (NGF) were greatest in the left atrial appendage (LAA), where AF was most organized. Preferential NGF release by the LAA - likely a direct function of frequency and regularity of atrial stimulation - may have important implications for creation of a vulnerable AF substrate.
Sensory dysregulation in tic disorders is associated with executive dysfunction and comorbidities

Tics are conceptualized as a sensorimotor phenomenon with a premonitory urge typically described by patients. As observed in other neurodevelopmental disorders, we have observed sensory dysregulation symptoms, such as tactile hypersensitivity to clothing, in children with tic disorders; however, formal clinical research in this area is limited.
miRDB: an online database for prediction of functional microRNA targets

Abstract MicroRNAs (miRNAs) are small noncoding RNAs that act as master regulators in many biological processes. miRNAs function mainly by downregulating the expression of their gene targets. Thus, accurate prediction of miRNA targets is critical for characterization of miRNA functions. To this end, we have developed an online database, miRDB, for miRNA target prediction and functional annotations. Recently, we have performed major updates for miRDB. Specifically, by employing an improved algorithm for miRNA target prediction, we now present updated transcriptome-wide target prediction data in miRDB, including 3.5 million predicted targets regulated by 7000 miRNAs in five species. Further, we have implemented the new prediction algorithm into a web server, allowing custom target prediction with user-provided sequences. Another new database feature is the prediction of cell-specific miRNA targets. miRDB now hosts the expression profiles of over 1000 cell lines and presents target prediction data that are tailored for specific cell models. At last, a new web query interface has been added to miRDB for prediction of miRNA functions by integrative analysis of target prediction and Gene Ontology data. All data in miRDB are freely accessible at http://mirdb.org.