Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of an Ultra-Endurance Event on Cardiovascular Function and Cognitive Performance in Marathon Runners

Background Ultra-marathon running participation has become increasingly more popular in recent years; however, there is inconclusive evidence concerning the effects of participation on cognition and cardiovascular function. The purpose of this study was to examine alterations in cardiovascular function and cognitive performance and their association in ultra-marathon runners prior to and following an ultra-endurance event. Methods In total, 24 runners (19 males and 5 females) participated in an ultra-marathon race (FatDog120) held in British Columbia, Canada. Participants competed in varying races distances [48 km (n = 2), 80 km (n = 7), 113 km (n = 3), and 193 km (n = 12)]. Cognition was assessed prior to and upon race completion using simple reaction time, choice reaction time, discrimination reaction time, and recognition memory (% correct). Cardiovascular function was assessed prior to and upon race completion using radial applanation tonometry for diastolic pulse contour examination. Results Cognitive performance displayed significantly (p < 0.001) slower reaction times post-race for simple (30.2%), discrimination (22.7%), and choice reaction time (30.5%), as well as a significant (p < 0.05) reduction in memory test performance (−8.2%). A significant association between systemic vascular resistance and choice reaction time was observed post-race (r = 0.41, p < 0.05). Significant changes in post-race cardiovascular function were observed in resting heart rate (31.5%), cardiac output (27.5%), mean arterial blood pressure (−5.6%), total systemic resistance (−17.6%), systolic blood pressure (−7.0%), pulse pressure (−11.2%), and rate pressure product (22.4%). There was evidence of enhanced cardiovascular function being associated with improved cognitive performance before and after the ultra-endurance event. Conclusion Ultra endurance running is associated with marked impairments in cognitive performance that are associated (at least in part) with changes in cardiovascular function in healthy adults.
Multilocus Genotyping of Giardia duodenalis in Alpine Musk Deer (Moschus chrysogaster) in China

Giardia duodenalis is the underlying cause of a significant number of outbreaks of gastrointestinal illness in humans and animals worldwide. The purpose of this study was to elucidate the prevalence and genetic diversity of G. duodenalis in captive alpine musk deer (Moschus chrysogaster) in China. A total of 202 fecal samples were collected from three farms in Gansu Province, China. Identification of G. duodenalis was conducted by nested PCR targeting the genes coding for SSU rRNA, β-giardin (bg), glutamate dehydrogenase (gdh) and triosephosphate isomerase (tpi). The overall prevalence of G. duodenalis in captive alpine musk deer in surveyed area was 19.3% (39/202). Two G. duodenalis genetic assemblages were identified, namely assemblage A and E. Mixed genotype infections (A+E) were found in 15.4% (6/39) of positive samples. Multilocus genotyping (MLG) analysis of G. duodenalis isolates revealed six novel assemblage A MLGs formed by two newly-described MLG-subtypes which belonged to sub-assemblage AI. To the best of our knowledge, this is the first report on MLG of G. duodenalis isolates in captive alpine musk deer in China. The presence of zoonotic assemblages and sub-assemblages of G. duodenalis in deer species suggests that these animals may potentially act as a reservoir of this protozoan for humans.
Resumption of Elective Orthopaedic Surgery in the US Epicenter of COVID-19: Overcoming the Continuous Challenges

On 1 March 2020, New York State confirmed its first case of COVID-19. An explosive progression of hospitalizations ensued, and all elective surgeries were cancelled between 23 March and 13 May 2020 per federal and state mandate. Upon return to elective surgery in May, 2020, the hospital found itself navigating uncharted territory. The unpredictability of the post-pandemic environment has required the healthcare team to constantly reassess and revise processes to ensure optimal patient outcomes, as well as safe practices for staff providing perioperative care. Health care professionals must continue to remain adaptable and amenable to constant change.
Insulin-Like ILP2 Regulates Trehalose Metabolism to Tolerate Hypoxia/Hypercapnia in Tribolium castaneum

RNAi was used to downregulate the expression of insulin-like peptides (ILP2), with air-modulation, and high-concentration CO2 stress, in the larvae of Tribolium castaneum. We assessed the changes in carbohydrate-related content, trehalase activity, and the expression levels of trehalose pathway genes. And pupation, adult emergence, pupation rate, and mortality were assessed. There was a significant change in the expression of ILPs in T. castaneum, at a certain concentration of CO2. ILP2 RNAi did not alter the trehalose content significantly, however, the glycogen and glucose content increased significantly. High-concentration CO2 stress altered the trehalose content and reduced the glycogen and glucose content. The expression levels of TPS and TRE2 were up-regulated by hypoxia/hypercapnia and dsILP2 combination, with the increase of CO2 concentration, other trehalase genes begin to respond successively. ILP2 knockout raised the mortality and reduced the pupation rate and eclosion rate in CO2. Understanding the insulin pathway responses to hypoxic stress induced by a high concentration of CO2 would further elucidate the mechanisms underlying trehalose metabolism in insects.
Orphan Nuclear Receptor NR4A2 Is Constitutively Expressed in Cartilage and Upregulated in Inflamed Synovium From hTNF-Alpha Transgenic Mice

Orphan nuclear receptor 4A2 (NR4A2/Nurr1) is a constitutively active transcription factor with potential roles in the onset and progression of inflammatory arthropathies. NR4A2 is overexpressed in synovium and cartilage from individuals with rheumatoid arthritis (RA), psoriatic arthritis, and osteoarthritis. This study documents the expression and tissue localization of NR4A2 and upstream regulator nuclear factor kappa B (NF-κB) in the human tumor necrosis factor-alpha (hTNF-α) transgenic mouse model of RA. Since TNF-α is a potent inducer of NR4A2 in vitro, we hypothesized that NR4A2 would also be upregulated and active during disease progression in this model. Expression levels of NR4A2, related receptors NR4A1 (Nur77) and 3 (NOR1), and NF-κB1 transcripts were quantified by RT-qPCR in hTNF-α and wild-type joints at three stages of disease. The protein distribution of NR4A2 and NF-κB subunit RelA (p65) was analyzed by quantitative immunohistochemistry. Global gene expression of 88 RA-related genes was also screened and compared between groups. Consistent with previous reports on the hTNF-α model, transgenic mice exhibited significant weight loss and severely swollen paws by 19 weeks of age compared to age-matched wild-type controls. NR4A1-3 and NF-κB1 were constitutively expressed at disease onset and in healthy joints. NF-κB1 transcript levels increased 2-fold in hTNF-α paws with established disease (12 weeks), followed by a 2-fold increase in NR4A2 at the late disease stage (19 weeks). NR4A2 and RelA proteins were overexpressed in inflamed synovium prior to symptoms of arthritis, suggesting that gene expression changes documented in whole paws were largely driven by elevated expression in diseased synovium. Broader screening of RA-related genes by RT-qPCR identified several differentially expressed genes in hTNF-α joints including those encoding inflammatory cytokines and chemokines, matrix-degrading enzymes and inhibitors, cell surface receptors, intracellular signaling proteins and transcription factors. Consensus binding sites for NR4A receptors and NF-κB1 were enriched in the promoters of differentially expressed genes suggesting central roles for these transcription factors in this model. This study is the first comprehensive analysis of NR4A2 in an animal model of RA and validates the hTNF-α model for testing of small molecules and genetic strategies targeting this transcription factor.
Tetrandrine Prevents Neomycin-Induced Ototoxicity by Promoting Steroid Biosynthesis

Aminoglycoside antibiotics are widely used for the treatment of serious acute infections, life-threatening sepsis, and tuberculosis, but all aminoglycosides cause side effects, especially irreversible ototoxicity. The mechanisms underlying the ototoxicity of aminoglycosides need further investigation, and there are no effective drugs in the clinic. Here we showed that tetrandrine (TET), a bioactive bisbenzylisoquinoline alkaloid derived from Stephania tetrandra, ameliorated neomycin-induced cochlear hair cell injury. In both in vitro and in vivo experiments we found that TET administration significantly improved auditory function and reduced hair cell damage after neomycin exposure. In addition, we observed that TET could significantly decrease oxidative stress and apoptosis in hair cells after neomycin exposure. Finally, RNA-seq analysis suggested that TET protected against neomycin-induced ototoxicity mainly by promoting steroid biosynthesis. Collectively, our results provide pharmacological evidence showing that TET may be a promising agent in preventing aminoglycosides-induced ototoxicity.
Preserved Electroencephalogram Power and Global Synchronization Predict Better Neurological Outcome in Sudden Cardiac Arrest Survivors

Quantitative EEG (qEEG) delineates complex brain activities. Global field synchronization (GFS) is one multichannel EEG analysis that measures global functional connectivity through quantification of synchronization between signals. We hypothesized that preservation of global functional connectivity of brain activity might be a surrogate marker for good outcome in sudden cardiac arrest (SCA) survivors. In addition, we examined the relation of phase coherence and GFS in a mathematical approach. We retrospectively collected EEG data of SCA survivors in one academic medical center. We included 75 comatose patients who were resuscitated following in-hospital or out-of-hospital nontraumatic cardiac arrest between 2013 and 2017 in the intensive care unit (ICU) of National Taiwan University Hospital (NTUH). Twelve patients (16%) were defined as good outcome (GO) (CPC 1–2). The mean age in the GO group was low (51.6 ± 15.7 vs. 68.1 ± 12.9, p < 0.001). We analyzed standard EEG power, computed EEG GFS, and assessed the cerebral performance category (CPC) score 3 months after discharge. The alpha band showed the highest discrimination ability (area under curve [AUC] = 0.78) to predict GO using power. The alpha band of GFS showed the highest AUC value (0.8) to predict GO in GFS. Furthermore, by combining EEG power + GFS, the alpha band showed the best prediction value (AUC 0.86) in predicting GO. The sensitivity of EEG power + GFS was 73%, specificity was 93%, PPV was 0.67%, and NPV was 0.94%. In conclusion, by combining GFS and EEG power analysis, the neurological outcome of the nontraumatic cardiac arrest survivor can be well-predicted. Furthermore, we proved from a mathematical point of view that although both amplitude and phase contribute to obtaining GFS, the interference in phase variation drastically changes the possibility of generating a good GFS score.
Activation of the PPARγ Prevents Ferroptosis-Induced Neuronal Loss in Response to Intracerebral Hemorrhage Through Synergistic Actions With the Nrf2

Intracerebral hemorrhage (ICH) is a subtype of stroke characterized by high mortality and disability rates. The long-term effects of ICH-induced intracranial hematoma on patients’ neurological function are unclear. Currently, an effective treatment that significantly reduces the rates of death and disability in patients with ICH is not available. Based on accumulating evidence, ferroptosis may be the leading factor contributing to the neurological impairment caused by ICH injury. Peroxisome proliferator-activated receptor γ (PPARγ) is a ligand-activated receptor in the nuclear hormone receptor family that synergistically interacts with the nuclear factor erythrocyte 2-related factor 2 (Nrf2) pathway to promote the expression of related genes and inhibit ferroptosis. Primary rat hippocampal neurons were treated with heme (50 μM) and erastin (50 μM) to induce ferroptosis, followed by the PPARγ agonist pioglitazone (PDZ, 10 μM) to verify the inhibitory effect of PPARγ activation on ferroptosis. ML385 (2 μM), a novel and specific NRF2 inhibitor, was administered to the inhibitor group, followed by an analysis of cellular activity and immunofluorescence staining. In vivo Assays, ICH rats injected with autologous striatum were treated with 30 mg/kg/d pioglitazone, and the inhibitor group was injected with ML385 (30 mg/kg). The results showed that PDZ inhibited ferroptosis in neurons by increasing the expression of PPARγ, Nrf2 and Gpx4 in vitro, while PDZ reduced ferroptosis in neurons after ICH and promoted the recovery of neural function in vivo. Our results suggest that PDZ, a PPARγ agonist, promotes Gpx4 expression through the interaction between PPARγ and the Nrf2 pathway, inhibits ferroptosis of neurons after ICH, and promotes the recovery of neural function.
Network Pharmacology and Comparative Transcriptome Reveals Biotargets and Mechanisms of Curcumol Treating Lung Adenocarcinoma Patients With COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has led to 4,255,892 deaths worldwide. Although COVID-19 vaccines are available, mutant forms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have reduced the effectiveness of vaccines. Patients with cancer are more vulnerable to COVID-19 than patients without cancer. Identification of new drugs to treat COVID-19 could reduce mortality rate, and traditional Chinese Medicine(TCM) has shown potential in COVID-19 treatment. In this study, we focused on lung adenocarcinoma (LUAD) patients with COVID-19. We aimed to investigate the use of curcumol, a TCM, to treat LUAD patients with COVID-19, using network pharmacology and systematic bioinformatics analysis. The results showed that LUAD and patients with COVID-19 share a cluster of common deregulated targets. The network pharmacology analysis identified seven core targets (namely, AURKA, CDK1, CCNB1, CCNB2, CCNE1, CCNE2, and TTK) of curcumol in patients with COVID-19 and LUAD. Clinicopathological analysis of these targets demonstrated that the expression of these targets is associated with poor patient survival rates. The bioinformatics analysis further highlighted the involvement of this target cluster in DNA damage response, chromosome stability, and pathogenesis of LUAD. More importantly, these targets influence cell-signaling associated with the Warburg effect, which supports SARS-CoV-2 replication and inflammatory response. Comparative transcriptomic analysis on in vitro LUAD cell further validated the effect of curcumol for treating LUAD through the control of cell cycle and DNA damage response. This study supports the earlier findings that curcumol is a potential treatment for patients with LUAD and COVID-19.
Whole-Genome Sequence Approach and Phylogenomic Stratification Improve the Association Analysis of Mutations With Patient Data in Influenza Surveillance

Each year, seasonal influenza results in high mortality and morbidity. The current classification of circulating influenza viruses is mainly focused on the hemagglutinin gene. Whole-genome sequencing (WGS) enables tracking mutations across all influenza segments allowing a better understanding of the epidemiological effects of intra- and inter-seasonal evolutionary dynamics, and exploring potential associations between mutations across the viral genome and patient’s clinical data. In this study, mutations were identified in 253 Influenza A (H3N2) clinical isolates from the 2016-2017 influenza season in Belgium. As a proof of concept, available patient data were integrated with this genomic data, resulting in statistically significant associations that could be relevant to improve the vaccine and clinical management of infected patients. Several mutations were significantly associated with the sampling period. A new approach was proposed for exploring mutational effects in highly diverse Influenza A (H3N2) strains through considering the viral genetic background by using phylogenetic classification to stratify the samples. This resulted in several mutations that were significantly associated with patients suffering from renal insufficiency. This study demonstrates the usefulness of using WGS data for tracking mutations across the complete genome and linking these to patient data, and illustrates the importance of accounting for the viral genetic background in association studies. A limitation of this association study, especially when analyzing stratified groups, relates to the number of samples, especially in the context of national surveillance of small countries. Therefore, we investigated if international databases like GISAID may help to verify whether observed associations in the Belgium A (H3N2) samples, could be extrapolated to a global level. This work highlights the need to construct international databases with both information of viral genome sequences and patient data.
Measuring Perceived Research Competence of Junior Researchers

Graduates of doctoral (Ph.D.) programs are expected to be competent at designing and conducting research independently. Given the level of research competence needed to successfully conduct research, it is important that assessors of doctoral programs (e.g., faculty and staff) have a reliable and validated tool for measuring and tracking perceived research competence among their students and graduates. A high level of research competence is expected for all Ph.D. graduates worldwide, in addition to in all disciplines/fields. Moreover, graduates of Ph.D. programs may complete their studies in one country but then obtain a research position in another country, emphasizing the need to ensure that all doctoral programs are fostering similar levels of research competence. Thus, the purpose of this study was to gather additional evidence for validity and reliability of the Research Competence (R-Comp) scale. Specifically, we sought to extend the findings of by adapting the scale, translating it to other languages, and applying the tool with a sample of early stage researchers. Our findings provide initial evidence that the adapted PR-Comp is appropriate for use in three languages and across a variety of disciplines/programs of study.
Recent Photovoltaic Cell Parameter Identification Approaches: A Critical Note

Since the 21st century, the global economy has developed rapidly, global energy resources have been decreasing and environmental problems have become increasingly prominent (Wang et al., 2020). Solar energy has become the most promising renewable energy source due to its abundant resources and wide distribution (Xi et al., 2016). Therefore, the development and utilization of solar photovoltaic technology is one of the important measures to achieve carbon peaking and carbon neutrality (Yang et al., 2020a). In particular, photovoltaic (PV) system has the characteristics of no danger of depletion, no need to consume fuel, high energy quality and short construction period, which has attracted widespread attention around the world (Yang et al., 2020b). However, PV system has highly nonlinear properties. Therefore, in order to achieve accurate modeling of PV systems, it is crucial to improve the accuracy of PV system parameter identification. So far, meta-heuristic-based parameter identification strategies for PV systems have been widely used. However, there are still many challenges to improve the accuracy of PV system parameter identification (Sun and Yang, 2020). In the current published literature, strategies to improve the identification accuracy of PV system parameters have not been fully considered, and the potential risks it brings are worth considering. This paper clarifies the above problems and puts forward some views on the problems existing in the identification of PV system parameters.
GhSOC1s Evolve to Respond Differently to the Environmental Cues and Promote Flowering in Partially Independent Ways

Gossypium hirsutum is most broadly cultivated in the world due to its broader adaptation to the environment and successful breeding of early maturity varieties. However, how cotton responds to environmental cues to adjust flowering time to achieve reproductive success is largely unknown. SOC1 functions as an essential integrator for the endogenous and exogenous signals to maximize reproduction. Thus we identified six SOC1-like genes in Gossypium that clustered into two groups. GhSOC1-1 contained a large intron and clustered with monocot SOC1s, while GhSOC1-2/3 were close to dicot SOC1s. GhSOC1s expression gradually increased during seedling development suggesting their conserved function in promoting flowering, which was supported by the early flowering phenotype of 35S:GhSOC1-1 Arabidopsis lines and the delayed flowering of cotton silencing lines. Furthermore, GhSOC1-1 responded to short-day and high temperature conditions, while GhSOC1-2 responded to long-day conditions. GhSOC1-3 might function to promote flowering in response to low temperature and cold. Taken together, our results demonstrate that GhSOC1s respond differently to light and temperature and act cooperatively to activate GhLFY expression to promote floral transition and enlighten us in cotton adaptation to environment that is helpful in improvement of cotton maturity.
Topological Alterations of the Brain Functional Network in Type 2 Diabetes Mellitus Patients With and Without Mild Cognitive Impairment

The aim of this study was to explore the topological alterations of the brain functional network in type 2 diabetes mellitus (T2DM) patients with and without mild cognitive impairment (MCI) using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory approaches. In total, 27 T2DM patients with MCI, 27 T2DM patients without MCI, and 27 healthy controls (HCs) underwent rs-fMRI scanning. The whole-brain functional network was constructed by thresholding the Pearson’s correlation matrices of 90 brain regions. The topological organization of the constructed networks was analyzed by using graph theory approaches. The global and nodal properties of the participants in the three groups were compared by using one-way ANOVA as well as post hoc Tukey’s t-tests. The relationships between the altered topological properties and clinical features or scores of neuropsychological tests were analyzed in T2DM patients with MCI. At the global level, the global and local efficiency of the patients in the T2DM with MCI group were significantly higher than that of participants in the HCs group, and the length of the characteristic path was significantly lower than that of the participants in the HCs group (p < 0.05). No significant difference was found among the other groups. At the nodal level, when compared with T2DM patients without MCI, T2DM patients with MCI showed significantly increased nodal centrality in four brain regions, which were mainly located in the orbitofrontal lobe and anterior cingulate gyrus (ACG) (p < 0.05). No significant difference was found between the T2DM patients without MCI and HCs. Moreover, nodal degree related coefficient (r = −0381, p = 0.050) and nodal efficiency (r = −0.405, P = 0.036) of the ACG showed a significant closed correlation with the scores of the digit span backward test in the T2DM patients with MCI. Our results suggested that the increased nodal properties in brain regions of the orbitofrontal lobe and ACG were biomarkers of cognitive impairment in T2DM patients and could be used for its early diagnosis. The global topological alterations may be related to the combination of MCI and T2DM, rather than any of them.