Miracle-dz/UniFAR-FTUs huggingface dataset:
Host‐related and environmental factors influence long‐term ectoparasite infestation dynamics of mouse lemurs in northwestern Madagascar

Parasite infestations depend on multiple host‐related and environmental factors. In the case of ectoparasites, which are exposed to the environment beyond the host, an impact of climate, expressed by seasonal or yearly variations, can be expected. However, long‐term dynamics of ectoparasite infestations are rarely studied in nonhuman primates. We investigated the yearly variations in ectoparasite infestations of two small primates, the gray (Microcebus murinus) and the golden‐brown (Microcebus ravelobensis) mouse lemur. For a more comprehensive evaluation, we also analyzed the potential effects of yearly and monthly climatic variation (temperature, rainfall) in addition to habitat, host sex, age, species, and body mass, on ectoparasite infestation. Individuals of both host species were sampled in two study sites within the Ankarafantsika National Park in northwestern Madagascar during several months (March–November) and across 4 years (2010, 2011, 2015, 2016). Our results show significant monthly and yearly variations in the infestation rates of three native ectoparasite taxa (Haemaphysalis spp. ticks, Schoutedenichia microcebi chigger mites, Lemurpediculus spp. sucking lice) and in ectoparasite species richness in both mouse lemur species. In addition, significant impacts of several host‐related (species, sex, body mass) and environmental factors (habitat, temperature, rainfall) were found, but with differences in relevance for the different parasite taxa and partly deviating in their direction. Although some differences could be attributed to either permanent or temporary presence of the parasites on the host or to ecological differences between the host species, the lack of specific knowledge regarding the life cycle and microhabitat requirements of each parasite taxon precludes a complete understanding of the factors that determine their infestation dynamics. This study demonstrates the presence of yearly and monthly dynamics in lemur–parasite interactions in tropical, seasonal, dry deciduous forests in Madagascar, which call out for broad ecological long‐term studies focusing both on primate hosts and their parasites.
Pancreatic Apoplexy

Objectives Patient characteristics with postoperative acute necrotizing pancreatitis and completion pancreatectomy (CP) after pancreaticoduodenectomy (PD) remain unclear. Methods Data from all patients who underwent a PD with need for CP (January 2011–December 2019) at a German University Hospital were analyzed regarding the indications and timing of CP, laboratory and histopathological findings, and overall outcome. Results Six hundred twelve patients underwent PD, 33 (5.4%) of them needed a CP. Indications were grade C pancreatic fistula with or without biliary leak (46% and 12%), biliary leak (6%), and hemorrhage due to pancreatic fistula (36%). Eight patients (24%) underwent CP within 3 days after PD. These fulminant courses (“pancreatic apoplexy”) were accompanied by significantly higher levels of lactate dehydrogenase, C-reactive protein, serum amylase, serum lipase, drain amylase, and drain lipase compared with patients with CP after the third day. Pancreatic apoplexy was histologically associated with higher rates of pancreatic necrosis (P = 0.044) and hemorrhage (P = 0.001). A trend toward higher mortality was observed (75% vs 36%, P = 0.058). Conclusions Pancreatic apoplexy, defined as fulminant necrotizing pancreatitis after PD leading to CP within 3 days, is associated with characteristic laboratory and histopathological findings and a trend to higher mortality.
Addressing Outcome Measure Variability in Myasthenia Gravis Clinical Trials

An increasing number of clinical trials are enrolling patients with myasthenia gravis (MG). A lack of standardization in the performance of outcome measures leads to confusion among site research teams and is a source of variability in clinical trial data. MGNet, the NIH-supported Rare Disease Clinical Research Network for MG, views standardization of MG outcome measures as a critical need. To address this issue, a group of experts summarized key outcome measures used in MG clinical trials and a symposium was convened to address issues contributing to outcome measure variability. Consensus recommendations resulted in changes to outcome measure instructions and, in some cases, modifications to specific instruments. Recommended changes were posted for public commentary before finalization. Changes to the MG-Activities of Daily Living, MG–Quality of Life–15r, and MG–Impairment Index were limited to adding details to the administration instructions. Recommendations for proper positioning of participants and how to score items that could not be performed because of non-MG reasons were provided for the MG Composite. The Quantitative MG (QMG) score required the most attention, and changes were made both to the instructions and the performance of certain items resulting in the QMG-Revised. The Postintervention Status was believed to have a limited role in clinical trials, except for the concept of minimal manifestation status. As a next step, training materials and revised source documents, which will be freely available to study teams, will be created and posted on the MGNet website. Further studies are needed to validate changes made to the QMG-Revised.
Associations between weather conditions and osteoarthritis pain: a systematic review and meta-analysis

Abstract Background Although there is an assertion that weather conditions affect osteoarthritis (OA) pain, the results from clinical studies remain inconsistent. This meta-analysis was performed to evaluate the association between weather conditions and OA pain. Methods Cochrane Library, Embase, PubMed, and Web of Science were searched from inception to September 30, 2022. Observational studies that explored all weather conditions associated with pain intensity were included. In the systematic review, the methodological quality of the selected studies was assessed and a best-evidence synthesis was used to make qualitative conclusions. Based on homogeneous results, Fisher’s Z scores derived from the effect size of temperature (T), barometric pressure (BP) or relative humidity (RH) related to OA pain were synthesized and further transformed to the correlation coefficients (summary r) in meta-analysis. Results A total of 14 studies were included in the best-evidence synthesis of a qualitative systematic review. There was strong evidence with 13 of 14 studies reporting consistent findings that weather factors in general, including any kind of meteorological condition, were associated with OA pain. Subsequently, 3 studies regarding BP or T, and 5 studies regarding RH with the pain of OA were included in quantitative meta-analyses. Both BP (pooled Fisher’s Z = 0.37, 95% CI 0.15 to 0.59; summary r = 0.35, 95% CI 0.15 to 0.53) and RH (pooled Fisher’s Z = 0.10, 95% CI 0.01 to 0.18; summary r = 0.086, 95% CI −0.05 to 0.22) were positively related to OA pain, while T was negatively related to OA pain (pooled Fisher’s Z = −0.38, 95% CI −0.60 to −0.16; summary r = −0.36, 95% CI −0.54 to −0.16). Conclusions In this study, weather factors in general were significantly associated with OA pain. It may provide useful references for the daily health management of OA. More studies designed with the consistent meteorological condition are warranted to validate the findings. KEY MESSAGE Many people with osteoarthritis think their joint pain is affected by the weather, while the association between OA pain and weather conditions is still unclear. This is a systematic review and meta-analysis of 14 observational studies for the association between weather conditions and OA pain. Weather conditions appear to be associated with OA pain. Barometric pressure and relative humidity were positively correlated to OA pain intensity, while temperature was negatively correlated to OA pain.
KaryoNet: Chromosome Recognition With End-to-End Combinatorial Optimization Network

Chromosome recognition is a critical way to diagnose various hematological malignancies and genetic diseases, which is however a repetitive and time-consuming process in karyotyping. To explore the relative relation between chromosomes, in this work, we start from a global perspective and learn the contextual interactions and class distribution features between chromosomes within a karyotype. We propose an end-to-end differentiable combinatorial optimization method, KaryoNet, which captures long-range interactions between chromosomes with the proposed Masked Feature Interaction Module (MFIM) and conducts label assignment in a flexible and differentiable way with Deep Assignment Module (DAM). Specially, a Feature Matching Sub-Network is built to predict the mask array for attention computation in MFIM. Lastly, Type and Polarity Prediction Head can predict chromosome type and polarity simultaneously. Extensive experiments on R-band and G-band two clinical datasets demonstrate the merits of the proposed method. For normal karyotypes, the proposed KaryoNet achieves the accuracy of 98.41% on R-band chromosome and 99.58% on G-band chromosome. Owing to the extracted internal relation and class distribution features, KaryoNet can also achieve state-of-the-art performances on karyotypes of patients with different types of numerical abnormalities. The proposed method has been applied to assist clinical karyotype diagnosis. Our code is available at: https://github.com/xiabc612/KaryoNet.
Regulating emotions with experience – the effectiveness of reappraisal inventiveness depends on situational familiarity

ABSTRACT Background and Objectives Previous research identified cognitive reappraisal as an adaptive emotion regulation strategy. However, theories on emotion regulation flexibility suggest that reappraisal effectiveness (RE) may depend on an individual’s familiarity with stressors. In this study, we expect high reappraisal inventiveness (RI), i.e., the generation of many and categorically different reappraisals, to increase RE for individuals with low situational familiarity. Individuals with high situational familiarity, however, would be more effective with low RI. Design A total of 148 participants completed the Script-based Reappraisal Task, in which they were presented with fear- and anger-eliciting scripts. Depending on trial type, participants were instructed to reappraise (reappraisal-trial) or react naturally (control-trial) to the scripts. After each trial, participants indicated affective states and reappraisals. We assessed RI and calculated RE-scores as difference between affect ratings in reappraisal- and control-trials for valence and arousal. Finally, participants rated the familiarity with each situation. Results The results indicated a significant moderating effect of situational familiarity on the relationship between RI and RE-valence (not RE-arousal). The moderation was mainly driven by a detrimental effect of RI for individuals with high situational familiarity. Conclusions Our results hint at the importance of individual experience with emotional content in the research of cognitive reappraisal.
Adoption of sodium-glucose cotransporter-2 inhibitors among prescribers caring for nursing home residents.

BACKGROUND Sodium-glucose cotransporter-2 inhibitor (SGLT2I) use has increased among community-dwelling populations, but little is known about how clinicians have prescribed them for US nursing home (NH) residents. We described the adoption of SGLT2Is by prescribers caring for long-stay NH residents by clinician specialty and over time, compared with sulfonylureas, an older diabetes medication class. METHODS We conducted a retrospective cohort study of prescribers of SGLT2Is and sulfonylureas for all long-stay US NH residents aged 65 years or older (2017-2019). Using 100% of Medicare Part D claims linked to prescriber characteristics data, we identified all dispensings of SGLT2Is and sulfonylureas for long-stay NH residents and their associated prescribers. We described the distribution of prescriber specialties for each drug class over time as well as the number of NH residents prescribed SGLT2s versus sulfonylureas. We estimated the proportions of prescribers who prescribed both drug classes versus only sulfonylureas or only SGLT2Is. RESULTS We identified 36,427 unique prescribers (SGLT2I: N = 5811; sulfonylureas: N = 35,443) for 117,667 NH residents between 2017 and 2019. For both classes, family medicine and internal medicine physicians accounted for most prescriptions (75%-81%). Most clinicians (87%) prescribed only sulfonylureas, 2% prescribed SGLT2Is only, and 11% prescribed both. Geriatricians were least likely to prescribe only SGLT2Is. We observed an increase in the number of residents with SGLT2I use from n = 2344 in 2017 to n = 5748 in 2019. CONCLUSIONS Among NH residents, most clinicians have not incorporated SGLT2Is into their prescribing for diabetes, but the extent of use is increasing. Family medicine and internal medicine physicians prescribed the majority of diabetes medications for NH residents, and geriatricians were the least likely to prescribe only SGLT2Is. Future research should explore provider concerns regarding SGLT2I prescribing, particularly adverse events.
Use of Both Alcohol and Cannabis Protective Behavioral Strategies is Associated with Fewer Negative Consequences: A Moderation Analysis

Abstract Background: Concurrent alcohol and cannabis (i.e. marijuana) use (CAM; use of both substances within the same specified time frame) is prevalent among college students and associated with increased risk of negative substance-related consequences. Extant research supports the use of protective behavioral strategies (PBS) for reducing negative consequences associated with both alcohol and cannabis use. However, limited research exists regarding the efficacy of PBS among CAM users, and it is unknown whether using PBS for both alcohol and cannabis augments protective effects. The present study tested four moderation models to evaluate the interactive effects of alcohol and cannabis PBS on alcohol and cannabis negative consequences and use frequency. Methods: A multisite sample of college students (N = 1705) reporting past-month CAM use completed questionnaires regarding substance use behaviors, PBS use, and substance-related negative consequences. Results: Alcohol and cannabis PBS were negatively associated with alcohol and cannabis use, respectively. However, two-way interactions between PBS on substance use were not supported, such that negative associations between PBS and same-substance use were not augmented as other-substance PBS use increased. Interactive effects of alcohol and cannabis PBS on negative alcohol and cannabis consequences were supported, such that negative associations between alcohol PBS and consequences were augmented as cannabis PBS increased and vice versa. Conclusions: Findings suggest that using both types of PBS may increase protective effects against negative consequences among CAM users. Accordingly, promoting both types of PBS may enhance extant harm reduction interventions.
Optimization of medium with perfusion microbioreactors for high density CHO cell cultures at very low renewal rate aided by design of experiments

A novel approach of design of experiment (DoE) is developed for the optimization of key substrates of the culture medium, amino acids, and sugars, by utilizing perfusion microbioreactors with 2 mL working volume, operated in high cell density continuous mode, to explore the design space. A mixture DoE based on a simplex‐centroid is proposed to test multiple medium blends in parallel perfusion runs, where the amino acids concentrations are selected based on the culture behavior in presence of different amino acid mixtures, and using targeted specific consumption rates. An optimized medium is identified with models predicting the culture parameters and product quality attributes (G0 and G1 level N‐glycans) as a function of the medium composition. It is then validated in runs performed in perfusion microbioreactor in comparison with stirred‐tank bioreactors equipped with alternating tangential flow filtration (ATF) or with tangential flow filtration (TFF) for cell separation, showing overall a similar process performance and N‐glycosylation profile of the produced antibody. These results demonstrate that the present development strategy generates a perfusion medium with optimized performance for stable Chinese hamster ovary (CHO) cell cultures operated with very high cell densities of 60 × 106 and 120 × 106 cells/mL and a low cell‐specific perfusion rate of 17 pL/cell/day, which is among the lowest reported and is in line with the framework recently published by the industry.
DeepAlloDriver: a deep learning-based strategy to predict cancer driver mutations

Abstract Driver mutations can contribute to the initial processes of cancer, and their identification is crucial for understanding tumorigenesis as well as for molecular drug discovery and development. Allostery regulates protein function away from the functional regions at an allosteric site. In addition to the known effects of mutations around functional sites, mutations at allosteric sites have been associated with protein structure, dynamics, and energy communication. As a result, identifying driver mutations at allosteric sites will be beneficial for deciphering the mechanisms of cancer and developing allosteric drugs. In this study, we provided a platform called DeepAlloDriver to predict driver mutations using a deep learning method that exhibited >93% accuracy and precision. Using this server, we found that a missense mutation in RRAS2 (Gln72 to Leu) might serve as an allosteric driver of tumorigenesis, revealing the mechanism of the mutation in knock-in mice and cancer patients. Overall, DeepAlloDriver would facilitate the elucidation of the mechanisms underlying cancer progression and help prioritize cancer therapeutic targets. The web server is freely available at: https://mdl.shsmu. edu.cn/DeepAlloDriver.
Deletion of quinolinate phosphoribosyltransferase gene accelerates frailty phenotypes and neuromuscular decline with aging in a sex‐specific pattern

Decline in neuromuscular function with aging is known to be a major determinant of disability and all‐cause mortality in late life. Despite the importance of the problem, the neurobiology of age‐associated muscle weakness is poorly understood. In a previous report, we performed untargeted metabolomics on frail older adults and discovered prominent alteration in the kynurenine pathway, the major route of dietary tryptophan degradation that produces neurotoxic intermediate metabolites. We also showed that neurotoxic kynurenine pathway metabolites are correlated with increased frailty score. For the present study, we sought to further examine the neurobiology of these neurotoxic intermediates by utilizing a mouse model that has a deletion of the quinolinate phosphoribosyltransferase (QPRT) gene, a rate‐limiting step of the kynurenine pathway. QPRT−/− mice have elevated neurotoxic quinolinic acid level in the nervous system throughout their lifespan. We found that QPRT−/− mice have accelerated declines in neuromuscular function in an age‐ and sex‐specific manner compared to control strains. In addition, the QPRT−/− mice show premature signs of frailty and body composition changes that are typical for metabolic syndrome. Our findings suggest that the kynurenine pathway may play an important role in frailty and age‐associated muscle weakness.
Evaluating translocation success of wild eastern hellbenders (Cryptobranchus alleganiensis alleganiensis) in Blue Ridge Ecoregion streams using pre- and post-translocation home range sizes and movement metrics

Translocations of freshwater species have become a widespread conservation strategy to mitigate the impacts of habitat fragmentation, yet they are not often rigorously monitored using animal movement data to determine their success. We demonstrate the value of monitoring pre- and post-translocation movements and home-range sizes of a fully-aquatic, benthic stream salamander, the eastern hellbender (Cryptobranchus a. alleganiensis) to determine translocation success. We studied the home range sizes, movements, and habitat use of individuals (n = 27) in two self-sustaining populations (S1 & S2) for one year, and then subsequently collected similar data from a subset of these individuals (n = 17) that were translocated into two nearby streams (T1 & T2) with dam-isolated, declining populations in the Blue Ridge Ecoregion of Tennessee. We collected 1,571 location data points (869 pre-translocation and 715 post-translocation) from four study sites, and evaluated effects of mass, sex, and pre-translocation home range size/sedentariness, as well as habitat covariates on home range size and movements. Hellbender home range sizes increased from pre-translocation estimates at both sites, but response depended primarily on physical characteristics of release sites. Home range and fine-scale movement metrics indicated that hellbenders translocated from S1 to T1 settled in more quickly, had greater site fidelity, and smaller home ranges than hellbenders translocated from S2 to T2. Hellbender movements were influenced by cover rock size and density rather than individual characteristics. Study-long survival rates of translocated hellbenders increased from S1 to T1 (80% to 100%) and decreased from S2 to T2 (76% to 33%). Monitoring pre- and post-translocation movements was a valuable method for evaluating short-term translocation success in a freshwater environment. For future hellbender translocations, managers should prioritize selecting suitable release sites with contiguous boulder-dense areas (1–2 per m2), adequate prey (crayfish) densities (>1/m2), and habitats with low risk of predation.
Satellite autonomous orbit determination using magnetometers

Considering the characteristic of the geomagnetic field near-earth orbit, an EKF-based magnetometer satellite orbit determination algorithm is proposed to reduce the expense of the autonomous navigation. To form a navigation model for the magnetometer-based satellite navigation system, the algorithm establishes the observation equation by IGRF model and establishes the status equation by adopting the stellite orbit motion equation with the earth-fixed coordinate which associates with the IGRF model by the position function. Simulation results show that the model has simple structure, strong capability of description and the algorithm is more reliable and astringency.