Miracle-dz/UniFAR-FTUs huggingface dataset:
Epidemiology of Injuries in National Collegiate Athletic Association Men's Track and Field: 2014-2015 Through 2018-2019.

CONTEXT College athletes have been competing in championship track and field events since 1921; the numbers of competing teams and participating athletes have expanded considerably. BACKGROUND Monitoring injuries of men's track and field athletes using surveillance systems is critical in identifying emerging injury-related patterns. METHODS Exposure and injury data collected in the National Collegiate Athletic Association Injury Surveillance Program during the 2014-2015 through 2018-2019 academic years were analyzed. Injury counts, rates, and proportions were used to describe injury characteristics; injury rate ratios were used to examine differential injury rates. RESULTS Overall, men's track and field athletes were injured at a rate of 2.37 per 1000 athlete-exposures; injuries occurred at a higher rate during competition compared with practice. Most injuries were to the thigh (26.2%), lower leg (17.3%), or knee (10.7%) and were caused by noncontact (37.2%) or overuse (31.5%) mechanisms. The most reported injury was hamstring tear (14.9%). SUMMARY The etiologies of thigh and lower-leg injuries warrant further attention in this population. Future researchers should also separately examine injury incidence during indoor and outdoor track and field seasons.
Latent Tuberculosis Infection among Health Workers in Germany—A Retrospective Study on Progression Risk and Use of Preventive Therapy

Despite the decline in tuberculosis incidence (TB) in Germany, health workers (HW) are at greater risk of becoming infected with Mycobacterium tuberculosis. To date, little is known about the risk of progression of latent tuberculosis infections (LTBI) and the use of Tuberculosis Preventive Therapy (TPT) among HW. Routine data from the German Statutory Institution for Accident Insurance and Prevention for Health and Welfare Services (BGW) were analysed and a retrospective survey was conducted. A self-administered questionnaire was sent to 1711 HW who had received recognition of an LTBI as an occupational disease between the years 2009 and 2018. The response rate was 42.3% after correcting for those with no actual address (20.4%). We included 575 HW in the data analysis of the retrospective survey. The cumulative incidence of progression, the incidence density and the associated 95% confidence interval (95% CI) were calculated. Three progressive cases were identified in the analysis of the routine data. In the survey cohort, three HW developed TB during the observation period of 5.4 years on average (standard deviation: 2.8 years; interquartile range: 5.0 years). The cumulative TB incidence was 0.52% in the survey group (95% CI: 0.14% to 1.65%). The incidence density was 0.97 cases per 1000 person years (95% CI: 0.25 to 3.10). One-third of the respondents underwent TPT. Significant differences were observed between age and activity groups in the use of TPT, but not between the genders, year of diagnosis or the reason for performing the screening. The data indicate that the risk of progression of an LTBI is low for HW. However, one-third of the HW had undergone TPT. Information about the expected progression risk is important so that it can be weighed against the risk of side effects of TPT.
Design of a Spark Big Data Framework for PM2.5 Air Pollution Forecasting

In recent years, with rapid economic development, air pollution has become extremely serious, causing many negative effects on health, environment and medical costs. PM2.5 is one of the main components of air pollution. Therefore, it is necessary to know the PM2.5 air quality in advance for health. Many studies on air quality are based on the government’s official air quality monitoring stations, which cannot be widely deployed due to high cost constraints. Furthermore, the update frequency of government monitoring stations is once an hour, and it is hard to capture short-term PM2.5 concentration peaks with little warning. Nevertheless, dealing with short-term data with many stations, the volume of data is huge and is calculated, analyzed and predicted in a complex way. This alleviates the high computational requirements of the original predictor, thus making Spark suitable for the considered problem. This study proposes a PM2.5 instant prediction architecture based on the Spark big data framework to handle the huge data from the LASS community. The Spark big data framework proposed in this study is divided into three modules. It collects real time PM2.5 data and performs ensemble learning through three machine learning algorithms (Linear Regression, Random Forest, Gradient Boosting Decision Tree) to predict the PM2.5 concentration value in the next 30 to 180 min with accompanying visualization graph. The experimental results show that our proposed Spark big data ensemble prediction model in next 30-min prediction has the best performance (R2 up to 0.96), and the ensemble model has better performance than any single machine learning model. Taiwan has been suffering from a situation of relatively poor air pollution quality for a long time. Air pollutant monitoring data from LASS community can provide a wide broader monitoring, however the data is large and difficult to integrate or analyze. The proposed Spark big data framework system can provide short-term PM2.5 forecasts and help the decision-maker to take proper action immediately.
Gait Flexibility among Older Persons Significantly More Impaired in Fallers Than Non-Fallers—A Longitudinal Study

Gait disorders are a relevant factor for falls and possible to measure with wearable devices. If a wearable sensor can detect differences in gait parameters between fallers and non-fallers has not yet been studied. The aim of this study was to measure and compare gait parameters, vestibular function, and balance performance between fallers and non-fallers among a group of older persons. Participants were senior members (n = 101) of a Swedish non-profit gymnastic association. Gait parameters were obtained using an inertial measurement unit (IMU) that the participants wore on the leg while walking an obstacle course and on an even surface. Vestibular function was assessed by the Head-shake test, the Head impulse test, and the Dix–Hallpike maneuver. Balance was assessed by the Timed Up and Go, the Timed Up and Go manual, and the Timed Up and Go cognitive tests. Falls during the 12-month follow-up period were monitored using fall diaries. Forty-two persons (41%) had fallen during the 12-month follow-up. Fallers had more limited ability to vary their gait (gait flexibility) than non-fallers (p < 0.001). No other differences between fallers and non-fallers were found. The use of gait flexibility, captured by an IMU, seems better for identifying future fallers among healthy older persons than Timed Up and Go or Timed Up and Go combined with a cognitive or manual task.
Study Crafting and Self-Undermining in Higher Education Students: A Weekly Diary Study on the Antecedents

The aim of the current study is to validate the adaptation of the job demands–resources theory to the study context. In addition, we introduce the concepts study crafting and self-undermining to the study demands–resources framework by examining the mediating role of engagement and exhaustion in the relationship between study characteristics and study crafting and self-undermining. Over four consecutive weeks, 205 higher education students answered a questionnaire about their weekly study demands and resources, their well-being (i.e., engagement, exhaustion), and their study crafting and self-undermining behaviors. Multilevel structural equation modeling (controlling for autoregressors of mediators and dependent variables from the previous week) demonstrated a positive relationship between study resources and study crafting mediated by engagement, as well as a positive relationship between study demands and self-undermining mediated by exhaustion. Our findings show that even short-term fluctuations in study characteristics affect students’ well-being and, in turn, their proactive and dysfunctional behaviors. Accordingly, universities should provide a resource-rich study environment and limit study demands as much as possible. Furthermore, our results demonstrate that students can also actively influence their study environment themselves.
Evolutionary Turnover in Wnt Gene Expression but Conservation of Wnt Signaling during Ovary Determination in a TSD Reptile

Temperature-dependent sex determination (TSD) is a well-known characteristic of many reptilian species. However, the molecular processes linking ambient temperature to determination of gonad fate remain hazy. Here, we test the hypothesis that Wnt expression and signaling differ between female- and male-producing temperatures in the snapping turtle Chelydra serpentina. Canonical Wnt signaling involves secretion of glycoproteins called WNTs, which bind to and activate membrane bound receptors that trigger β-catenin stabilization and translocation to the nucleus where β-catenin interacts with TCF/LEF transcription factors to regulate expression of Wnt targets. Non-canonical Wnt signaling occurs via 2 pathways that are independent of β-catenin: one involves intracellular calcium release (the Wnt/Ca2+ pathway), while the other involves activation of RAC1, JNK, and RHOA (the Wnt/planar cell polarity pathway). We screened 20 Wnt genes for differential expression between female- and male-producing temperatures during sex determination in the snapping turtle. Exposure of embryos to the female-producing temperature decreased expression of 7 Wnt genes but increased expression of 2 Wnt genes and Rspo1 relative to embryos at the male-producing temperature. Temperature also regulated expression of putative Wnt target genes in vivo and a canonical Wnt reporter (6x TCF/LEF sites drive H2B-GFP expression) in embryonic gonadal cells in vitro. Results indicate that Wnt signaling was higher at the female- than at the male-producing temperature. Evolutionary analyses of all 20 Wnt genes revealed that thermosensitive Wnts, as opposed to insensitive Wnts, were less likely to show evidence of positive selection and experienced stronger purifying selection within TSD species.
Drug–Drug Interactions in Italian Patients with Chronic Hepatitis C Treated with Pangenotypic Direct Acting Agents: Insights from a Real-World Study

This Italian observational real-world study aims to assess in chronic hepatitis C virus (HCV) patients treated with pangenotypic direct acting agents (pDAAs) glecaprevir/pibrentasvir (GLE/PIB) or sofosbuvir/velpatasvir (SOF/VEL) the potential drug–drug interactions (DDIs) with concomitant medications prescribed, with a focus on cardiovascular and system nervous (CNS) co-medications. Data were collected from administrative databases covering 6.9 million health-assisted individuals. All patients prescribed SOF/VEL or GLE/PIB between 11/2017 and 12/2018 were included. Patients were analyzed while on DAA. DDIs were identified according to the Liverpool University tool. Overall, 3181 HCV patients were included: 1619 in the GLE/PIB cohort and 1562 in the SOF/VEL cohort. SOF/VEL patients were generally older than GLE/PIB ones (mean age 58.4 vs. 53.1, p < 0.001) and had more cardiovascular and CNS comorbidities (58% vs. 42%, p < 0.001 and 33% vs. 28%, p = 0.002, respectively). Contraindications due to DDIs in the GLE/PIB cohort affected 9.3% and 3.2% of patients before and on DAA, respectively, while the percentages in the SOF/VEL cohort were 3.2% before and 0.4% after pDAAs initiation. Among GLE/PIB patients, 2.7% had cardiovascular drugs (all statins) contraindicated while on DAA. The potential DDIs between cardiovascular drugs and SOF/VEL were mainly with statins (5%). SOF/VEL was prescribed in patients with older age and with more cardiovascular and CNS comorbidities. Despite this, a proportion of contraindicated drugs lower than that of GLE/PIB was registered.
Hepato-protective effects of thymoquinone and beta-aminoisobutyric acid in streptozocin induced diabetic rats

ABSTRACT We investigated the hepato-protective effects of thymoquinone (TQ) and beta-aminoisobutyric acid (BAIBA). We used five groups of 8-week-old male rats: untreated control group, streptozotocin (STZ) diabetic group, STZ + TQ group, STZ + BAIBA group, and STZ + TQ + BAIBA group. After experimental diabetes mellitus (DM) was established using STZ, TQ was given to the STZ + TQ group, BAIBA to the STZ + BAIBA group, and TQ and BAIBA to the STZ + TQ + BAIBA group. In the STZ group, body weight, relative liver weight, and glutathione, blood albumin and insulin levels were decreased compared to the control. Also, water and food consumption, tumor necrosis factor-α expression, malondialdehyde, blood glucose, alanine aminotransferase, aspartate aminotransferase and gamma glutamyl transferase levels were increased the STZ group compared to the control group. In the STZ group, sinusoid congestion and dilation, monocyte and lymphocyte infiltration and microvesicular steatosis were observed in the liver tissue. Pathological changes caused by DM were reduced significantly in the STZ + TQ, STZ + BAIBA and STZ + TQ + BAIBA groups. The protective effect of BAIBA was greater than for TQ; the greatest protective effect was observed following combined use of TQ + BAIBA. We suggest that our findings for the STZ + TQ, STZ + BAIBA and STZ + TQ + BAIBA groups were due to the antioxidant effects of TQ and BAIBA. TQ and BAIBA appear to be potential therapeutic agents for ameliorating hepatic damage due to DM.
The Social Effects of Emotions.

We review the burgeoning literature on the social effects of emotions, documenting the impact of emotional expressions on observers' affect, cognition, and behavior. We find convergent evidence that emotional expressions influence observers' affective reactions, inferential processes, and behaviors across various domains, including close relationships, group decision making, customer service, negotiation, and leadership. Affective reactions and inferential processes mediate the effects of emotional expressions on observers' behaviors, and the relative potency of these mediators depends on the observers' information processing and the perceived appropriateness of the emotional expressions. The social effects of emotions are similar across expressive modalities (face, voice, body, text, symbols). We discuss the findings in relation to emotional contagion, emotional intelligence, emotion regulation, emotions as social information (EASI) theory, and the functionality of emotions in engendering social influence. Finally, we identify gaps in our current understanding of the topic and call for interdisciplinary collaboration and methodological diversification. Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Few-Shot Learning in Spiking Neural Networks by Multi-Timescale Optimization

Abstract Learning new concepts rapidly from a few examples is an open issue in spike-based machine learning. This few-shot learning imposes substantial challenges to the current learning methodologies of spiking neuron networks (SNNs) due to the lack of task-related priori knowledge. The recent learning-to-learn (L2L) approach allows SNNs to acquire priori knowledge through example-level learning and task-level optimization. However, existing L2L-based frameworks do not target the neural dynamics (i.e., neuronal and synaptic parameter changes) on different timescales. This diversity of temporal dynamics is an important attribute in spike-based learning, which facilitates the networks to rapidly acquire knowledge from very few examples and gradually integrate this knowledge. In this work, we consider the neural dynamics on various timescales and provide a multi-timescale optimization (MTSO) framework for SNNs. This framework introduces an adaptive-gated LSTM to accommodate two different timescales of neural dynamics: short-term learning and long-term evolution. Short-term learning is a fast knowledge acquisition process achieved by a novel surrogate gradient online learning (SGOL) algorithm, where the LSTM guides gradient updating of SNN on a short timescale through an adaptive learning rate and weight decay gating. The long-term evolution aims to slowly integrate acquired knowledge and form a priori, which can be achieved by optimizing the LSTM guidance process to tune SNN parameters on a long timescale. Experimental results demonstrate that the collaborative optimization of multi-timescale neural dynamics can make SNNs achieve promising performance for the few-shot learning tasks.
Kinetic modeling and statistical optimization of submerged production of anti-Parkinson’s prodrug L-DOPA by Pseudomonas fluorescens

Abstract L-DOPA, a precursor of dopamine, is the drug of choice for Parkinson’s disease, which persists due to decreased levels of dopamine in the brain. Present study emphasis the microbial production of L-DOPA rather than the biotransformation of L-DOPA by L-tyrosine. The production of L-DOPA by bacterial isolates had gained more acceptance due to its more straightforward extraction and downstream processes. Pseudomonas fluorescens was used to produce the L-DOPA in a bioreactor system under submerged condition. The design of experiment-based Taguchi orthogonal array method was adopted for the optimization of production. L-9 orthogonal array using the analysis of mean approach was used to study the effect of different factors viz NaCl, lactose, tryptone, and inducer on the microbial production of L-DOPA. The method mentioned above is less time consuming and does not require any harsh chemicals, proving it to be an eco-friendly process. After optimizing selected factors, i.e., NaCl (1.2 g/l), lactose (1.5 g/l), tryptone (4 g/l), and inducer (0.1 g/l), 16.9 % of enhancement in L-DOPA production with 66.6% of process cost saving was observed. The production of L-DOPA was increased from 3.426 ± 0.08 g/l to 4.123 ± 0.05 g/l after optimization. Subsequently, unstructured kinetic models were adopted to simulate the fermentation kinetics and understand the metabolic process. Fisher’ F test and determination coefficients (R 2) confirmed that the Velhurst–Pearl logistic equation, Luedeking–Piret equation, and modified Luedeking–Piret equation was best fitted with the biomass production, product formation, and substrate utilization, respectively.
Characterization of Proteobacterial Plasmid Integron-Encoded qac Efflux Pump Sequence Diversity and Quaternary Ammonium Compound Antiseptic Selection in Escherichia coli Grown Planktonically and as Biofilms

Qac efflux pumps from proteobacterial multidrug-resistant plasmids are integron encoded and confer resistance to quaternary ammonium compound (QAC) antiseptics; however, many are uncharacterized and misannotated. A survey of >2,000 plasmid-carried qac genes identified 37 unique qac sequences that correspond to one of five representative motifs: QacE, QacEΔ1, QacF/L, QacH/I, and QacG. ABSTRACT Qac efflux pumps from proteobacterial multidrug-resistant plasmids are integron encoded and confer resistance to quaternary ammonium compound (QAC) antiseptics; however, many are uncharacterized and misannotated. A survey of >2,000 plasmid-carried qac genes identified 37 unique qac sequences that correspond to one of five representative motifs: QacE, QacEΔ1, QacF/L, QacH/I, and QacG. Antimicrobial susceptibility testing of each cloned qac member in Escherichia coli highlighted distinctive antiseptic susceptibility patterns that were most prominent when cells grew as biofilms.
(E)-3-furan-2-yl-N-phenylacrylamide (PAM-4) decreases nociception and emotional manifestations of neuropathic pain in mice by α7 nicotinic acetylcholine receptor potentiation

ABSTRACT Clinical intervention of pain is often accompanied by changes in affective behaviors, so both assays of affective and sensorial aspects of nociception play an important role in the development of novel analgesics. Although positive allosteric modulation (PAM) of α7 nicotinic acetylcholine receptors (nAChRs) has been recognized as a novel approach for the relief of sensorial aspects of pain, their effects on affective components of pain remain unclear. Therefore, we investigated whether PAM-4, a highly selective α7-nAChR PAM, attenuates inflammatory and neuropathic pain, as well as the concomitant depressive/anxiety comorbidities. The anti-nociceptive activity of PAM-4 was assessed in mice using the formalin test and chronic constriction injury (CCI)-induced neuropathic pain model. The anxiolytic- and antidepressant-like activity of PAM-4 was evaluated using the marble burying test and forced swimming test. Acute systemic administration of PAM-4 dose-dependently reversed formalin-induced paw licking behavior and CCI-induced mechanical allodynia without development of any motor impairment. PAM-4 reversed the decreased swimming time and number of buried marbles in CCI-treated mice, suggesting that this ligand attenuates chronic pain-induced depression-like behavior and anxiogenic-like effects. The effects of PAM-4 were inhibited by the α7-selective antagonist methyllycaconitine, indicating molecular mechanism mediated by α7-nAChRs. Indeed, electrophysiological recordings showed the PAM-4 enhances human α7 nAChRs with higher potency and efficacy compared to rat α7 nAChRs. These findings suggest that PAM-4 reduces both sensorial and affective behaviors induced by chronic pain in mice by α7-nAChR potentiation. PAM-4 deserves further investigations for the management of chronic painful conditions with comorbidities.
Pediatric Unintentional Fall-Related Injuries in a Statewide Trauma Registry

Objectives The purpose of the study was to evaluate patterns of fall-related injury through childhood and identify risk factors for more severe fall-related injuries with the goal of informing targeted prevention strategies for different ages. Methods The study population consisted of pediatric patients in the Iowa Trauma Registry from January 1, 2010, to December 31, 2014, who sustained an unintentional fall-related injury (N = 3856 patients). Multinomial logistic regression analysis was used to predict injury severity. Adjusted odds ratios were calculated characterizing the relationship between fall severity and age, sex, race, and fall type. Results More males (62%) sustained a fall-related injury during the study period when compared with females (38%; P < 0.0001). Head injuries were the most common type of injury in the younger than 1 year age group (77%), whereas fractures were the predominant injury type in all other age groups, followed by head injuries. Those younger than 1 year (adjusted odds ratio, 4.0; 95% confidence interval, 2.36–6.90) and aged 15 to 18 years (adjusted odds ratio, 1.9; 95% confidence interval, 1.17–3.03) were more likely to have an Injury Severity Score of ≥16 than those aged 10 to 14 years. Conclusions Recommendations and prevention strategies need to focus on specific risk factors to reduce the harm of multilevel falls. As we have shown, patterns of fall injuries presenting to trauma hospitals differ by age, thus suggesting that prevention strategies focus on specific age groups.