Miracle-dz/UniFAR-FTUs huggingface dataset:
Orthogonal analysis of variants in APOE gene using in-silico approaches reveals novel disrupting variants

Introduction: Alzheimer’s disease (AD) is one of the most prominent medical conditions in the world. Understanding the genetic component of the disease can greatly advance our knowledge regarding its progression, treatment and prognosis. Single amino-acid variants (SAVs) in the APOE gene have been widely investigated as a risk factor for AD Studies, including genome-wide association studies, meta-analysis based studies, and in-vivo animal studies, were carried out to investigate the functional importance and pathogenesis potential of APOE SAVs. However, given the high cost of such large-scale or experimental studies, there are only a handful of variants being reported that have definite explanations. The recent development of in-silico analytical approaches, especially large-scale deep learning models, has opened new opportunities for us to probe the structural and functional importance of APOE variants extensively. Method: In this study, we are taking an ensemble approach that simultaneously uses large-scale protein sequence-based models, including Evolutionary Scale Model and AlphaFold, together with a few in-silico functional prediction web services to investigate the known and possibly disease-causing SAVs in APOE and evaluate their likelihood of being functional and structurally disruptive. Results: As a result, using an ensemble approach with little to no prior field-specific knowledge, we reported 5 SAVs in APOE gene to be potentially disruptive, one of which (C112R) was classificed by previous studies as a key risk factor for AD. Discussion: Our study provided a novel framework to analyze and prioritize the functional and structural importance of SAVs for future experimental and functional validation.
Internet gaming disorder and aggression: A meta-analysis of teenagers and young adults

Background and aims Internet gaming disorder (IGD) and aggression (AG) are widespread phenomena around the world. Numerous studies have explored the relationship between the two but findings from such studies are inconsistent. The meta-analysis aimed to evaluate the relationship between IGD and AG as well as identify the variables moderating the relationship. Method Studies investigating the relationship between IGD and AG were searched using selected terms to identify studies published from 1999 to 2022 on CNKI, Wanfang Data, Chongqing VIP Information Co., Ltd. (VIP), Baidu scholar, ProQuest dissertations, Taylor & Francis, Springer, Web of Science, Google Scholar, Elsevier Science (Science Direct), EBSCO, and PsycINFO. The identified studies were pooled and analyzed. Results A total of 30 samples comprising 20,790 subjects were identified. Results showed that there was a moderate relationship between IGD and AG (r = 0.300, 95%CI [0.246, 0.353]). Moderator analysis revealed that the relationship between IGD and AG was moderated by the region, age, and survey year. Conclusion This meta-analysis indicated that people with a higher level of IGD might show more aggression, and people with more aggression might have a higher level of IGD. The correlation coefficient between IGD and AG was significantly higher in Asia than in Europe, higher in primary school than in middle school and university, and higher by increasing year. Overall, our findings provide a basis for developing prevention and intervention strategies against IGD and AG. Systematic review registration: https://www.crd. york.ac. uk/prospero/display_record. php? ID=CRD42022375267, 42022375267.
Clinical frailty scale as a predictor of outcome in elderly patients affected by moderate or severe traumatic brain injury

Background Older age is a well-known risk factor for unfavorable outcome in traumatic brain injury (TBI). However, many older people with TBI respond well to aggressive treatments, suggesting that chronological age and TBI severity alone may be inadequate prognostic markers. Frailty is an age-related homeostatic imbalance of loss of physiologic and cognitive reserve resulting in both limitation in autonomy of activities of daily living and vulnerability to adverse events. We hypothesized that frailty would be associated with 6-month adverse functional outcome in older people affected by moderate or severe TBI. Methods This was a single-center prospective observational study. We enrolled consecutive patients aged ≥65 years after TBI with Glasgow Coma Scale ≤13 and admitted to our Neurosurgical Intensive Care Unit. Frailty was evaluated by Clinical Frailty Scale (CFS). Relationships between TBI severity, frailty and extended Glasgow Outcome Scale (GOSE) at 6-month were evaluated. Results Sixty patients were studied, 65% were males, their age was 76 years (IQR 70–80) and their admission GCS was 8 (IQR 6–11) with a GCS motor score of 5 (IQR 4–5). Twenty eight were vulnerable-frail (defined as CFS ≥ 4). Vulnerable-frail patients showed greater 6-month mortality and unfavorable outcome compared to non-frail [87% vs. 30% OR and 95% CI: 15.7 (3.9–55.2), p < 0.0001 and 92% vs. 51% OR and 95% CI: 9.9 (2.1–46.3), p = 0.002]. In univariate analysis patients with unfavorable outcome were more frequently male and vulnerable-frail, had a higher prevalence of pre-existing neurodegenerative disease, abnormal pupil, lower GCS and had worst CT scan characteristics. At multivariate analysis, only CFS ≥ 4 and traumatic subarachnoid hemorrhage remained associated to 6-month outcome. Conclusion Frailty was associated with 6 month-outcome, suggesting that the pre-injury functional status could represent an additional indicator to stratify patient’s severity and to predict outcome.
OncoRTT: Predicting novel oncology-related therapeutic targets using BERT embeddings and omics features

Late-stage drug development failures are usually a consequence of ineffective targets. Thus, proper target identification is needed, which may be possible using computational approaches. The reason being, effective targets have disease-relevant biological functions, and omics data unveil the proteins involved in these functions. Also, properties that favor the existence of binding between drug and target are deducible from the protein’s amino acid sequence. In this work, we developed OncoRTT, a deep learning (DL)-based method for predicting novel therapeutic targets. OncoRTT is designed to reduce suboptimal target selection by identifying novel targets based on features of known effective targets using DL approaches. First, we created the “OncologyTT” datasets, which include genes/proteins associated with ten prevalent cancer types. Then, we generated three sets of features for all genes: omics features, the proteins’ amino-acid sequence BERT embeddings, and the integrated features to train and test the DL classifiers separately. The models achieved high prediction performances in terms of area under the curve (AUC), i.e., AUC greater than 0.88 for all cancer types, with a maximum of 0.95 for leukemia. Also, OncoRTT outperformed the state-of-the-art method using their data in five out of seven cancer types commonly assessed by both methods. Furthermore, OncoRTT predicts novel therapeutic targets using new test data related to the seven cancer types. We further corroborated these results with other validation evidence using the Open Targets Platform and a case study focused on the top-10 predicted therapeutic targets for lung cancer.
βγ G-proteins, but not regulators of G-protein signaling 4, modulate opioid-induced respiratory rate depression

Opioid medications are the mainstay of pain management but present substantial side-effects such as respiratory depression which can be lethal with overdose. Most opioid drugs, such as fentanyl, act on opioid receptors such as the G-protein-coupled µ-opioid receptors (MOR). G-protein-coupled receptors activate pertussis toxin-sensitive G-proteins to inhibit neuronal activity. Binding of opioid ligands to MOR and subsequent activation G proteins βγ is modulated by regulator of G-protein signaling (RGS). The roles of G-proteins βγ and RGS in MOR-mediated inhibition of the respiratory network are not known. Using rodent models to pharmacologically modulate G-protein signaling, we aim to determine the roles of βγ G-proteins and RGS4. We showed that inhibition of βγ G-proteins using gallein perfused in the brainstem circuits regulating respiratory depression by opioid drugs results in complete reversal of respiratory depression. Blocking of RGS4 using CCG55014 did not change the respiratory depression induced by MOR activation despite co-expression of RGS4 and MORs in the brainstem. Our results suggest that neuronal inhibition by opioid drugs is mediated by G-proteins, but not by RGS4, which supports the concept that βγ G-proteins could be molecular targets to develop opioid overdose antidotes without the risks of re-narcotization often found with highly potent opioid drugs. On the other hand, RGS4 mediates opioid analgesia, but not respiratory depression, and RGS4 may be molecular targets to develop pain therapies without respiratory liability.
Influence of training status on cardiac and vascular functioning in young recreational and competitive male rowers

Introduction The aim of the study was to investigate the influence of training status on cardiovascular function in young male recreational and competitive rowers. Methods Ejection duration in percentage to the heart rate period (ED%), subendocardial viability ratio (SEVR), augmentation index at 75 bpm (AIx75) and carotid to femoral pulse wave velocity (cf-PWV) of competitive rowers (CR) (age 17.6 ± 4.1 years), recreational rowers (RR) (age 16.7 ± 2.70 years) and athletes practicing other recreational sports (ORS) (age 15.3 ± 1.4 years) were assessed. Results ED% was lower in CR compared to ORS (31.9 ± 3.9% vs. 38.4 ± 4.8%; p = 0.026) and cf-PWV was higher in CR compared to ORS (5.5 ± 1.0 m/s vs. 4.7 ± 0.5 m/s; p = 0.032). SEVR was higher in CR compared to RR and ORS (165.8 ± 33.7% vs. 127.4 ± 30.4% and 128.3 ± 27.8%; p = 0.022) and AIx75 was lower in CR compared to RR and ORS (−15.7 ± 8.6% vs. 1.2 ± 9.9% and 1.5 ± 9.1; p = 0.001). Discussion Healthy, young competitive male rowers reported higher myocardial performance and better cardiovascular health than recreational athletes. Interpretations of cf-PWV in competitive rowers should be performed alongside other cardiovascular indicators.
Attenuation of stretch-induced arrhythmias following chemical ablation of Purkinje fibres, in isolated rabbit hearts

Purkinje fibres (PFs) play an important role in some ventricular arrhythmias and acute ventricular stretch can evoke mechanically-induced arrhythmias. We tested whether Purkinje fibres, play a role in these arrhythmias. Pseudo-ECGs were recorded in isolated, Langendorff-perfused, rabbit hearts in which the left ventricular endocardial surface was also irrigated with Tyrode, via an indwelling catheter placed in the left ventricular lumen. The number and period of ectopic activations was measured during left ventricular lumen inflation via an indwelling fluid-filled balloon (500 μL added over 2 s and maintained for 15 s in total). Mechanically-induced arrhythmias occurred in 70% of balloon inflations: they were maximal in the first 5 s and ceased within 15 s. Brief, (10 s) irrigation of the left ventricular lumen with Lugol solution (IK/I2), via the indwelling catheter, reduced inflation-induced ectopics by 98% (p < 0.05). Ablation of endocardial PFs by Lugol was confirmed by Triphenyltetrazolium Chloride staining. Optical mapping revealed the left ventricular epicardial activation patterns of ectopics could have PF-mediated and focal sources. In silico modelling predicted ectopic sources originating in the endocardial region propagate to and through the Purkinje fibres network. Acute distention-induced ectopics are multi-focal, their attenuation by Lugol, their activation patterns and in silico modelling indicate a participation of Purkinje fibres in these arrhythmias.
Estimation of tomato water status with photochemical reflectance index and machine learning: Assessment from proximal sensors and UAV imagery

Tracking plant water status is a critical step towards the adaptive precision irrigation management of processing tomatoes, one of the most important specialty crops in California. The photochemical reflectance index (PRI) from proximal sensors and the high-resolution unmanned aerial vehicle (UAV) imagery provide an opportunity to monitor the crop water status efficiently. Based on data from an experimental tomato field with intensive aerial and plant-based measurements, we developed random forest machine learning regression models to estimate tomato stem water potential (ψ stem), (using observations from proximal sensors and 12-band UAV imagery, respectively, along with weather data. The proximal sensor-based model estimation agreed well with the plant ψ stem with R 2 of 0.74 and mean absolute error (MAE) of 0.63 bars. The model included PRI, normalized difference vegetation index, vapor pressure deficit, and air temperature and tracked well with the seasonal dynamics of ψ stem across different plots. A separate model, built with multiple vegetation indices (VIs) from UAV imagery and weather variables, had an R 2 of 0.81 and MAE of 0.67 bars. The plant-level ψ stem maps generated from UAV imagery closely represented the water status differences of plots under different irrigation treatments and also tracked well the temporal change among flights. PRI was found to be the most important VI in both the proximal sensor- and the UAV-based models, providing critical information on tomato plant water status. This study demonstrated that machine learning models can accurately estimate the water status by integrating PRI, other VIs, and weather data, and thus facilitate data-driven irrigation management for processing tomatoes.
Understanding bacterial biofilms: From definition to treatment strategies

Bacterial biofilms are complex microbial communities encased in extracellular polymeric substances. Their formation is a multi-step process. Biofilms are a significant problem in treating bacterial infections and are one of the main reasons for the persistence of infections. They can exhibit increased resistance to classical antibiotics and cause disease through device-related and non-device (tissue) -associated infections, posing a severe threat to global health issues. Therefore, early detection and search for new and alternative treatments are essential for treating and suppressing biofilm-associated infections. In this paper, we systematically reviewed the formation of bacterial biofilms, associated infections, detection methods, and potential treatment strategies, aiming to provide researchers with the latest progress in the detection and treatment of bacterial biofilms.
Two simple assays for assessing the seeding activity of proteopathic tau

The regional distribution of neurofibrillary tangles of hyperphosphorylated tau aggregates is associated with the progression of Alzheimer’s disease (AD). Misfolded proteopathic tau recruits naïve tau and templates its misfolding and aggregation in a prion-like fashion, which is believed to be the molecular basis of propagation of tau pathology. A practical way to assess tau seeding activity is to measure its ability to recruit/bind other tau molecules and to induce tau aggregation. Based on the properties of proteopathic tau, here we report the development of two simple assays to assess tau seeding activity ----- capture assay in vitro and seeded-tau aggregation assay in cultured cells. In the capture assay, proteopathic tau was applied onto a nitrocellulose membrane and the membrane was incubated with cell lysate containing HA-tagged tau151-391 (HA-tau151-391). The captured tau on the membrane was determined by immuno-blots developed with anti-HA. For the seeded-tau aggregation assay, HEK-293FT cells transiently expressing HA-tau151-391 were treated with proteopathic tau in the presence of Lipofectamine 2000 and then lysed with RIPA buffer. RIPA-insoluble fraction containing aggregated tau was obtained by ultracentrifugation and analyzed by immuno-blot developed with anti-HA. To validate these two assays, we assessed the seeding activity of tau in the middle frontal gyrus, middle temporal gyrus and basal forebrain of AD and control brains and found that AD, but not control, brain extracts effectively captured and seeded tau151-391 aggregation. Basal forebrain contained less phospho-tau and tau seeding activity. The levels of captured tau or seeded-tau aggregates were positively correlated to the levels of phospho-tau, Braak stages and tangle sores. These two assays are specific and sensitive and can be carried out in a regular biomedical laboratory setting by using routine biochemical techniques.
Relational bullying and disordered eating: Testing a moderated mediation model of the role of shame and self-compassion

Objective Experiences of relational bullying (RB) in adolescence are associated with the development of disordered eating. This association may be related to heightened shame resulting from perceived social inferiority, low social rank, and/or negative evaluation by others. Self-compassion may act as a protective factor against the influence of RB on shame and disordered eating. In the current study, we investigated whether shame mediated the relationship between recalled RB and current disordered eating in a sample of young adults. Then, using conditional process analysis, we examined whether the observed mediation was moderated by self-compassion. Method Participants were 359 young adults (aged 17–25) who completed online self-report measures of recalled RB experiences and current disordered eating, shame, and self-compassion. Results Experiences of RB were positively related to current shame and disordered eating, and negatively related to current self-compassion, with small-to-medium effect sizes. The association between RB and disordered eating was partially mediated by shame, and this mediation was moderated by self-compassion. Discussion Our results suggest that young adults with lower self-compassion are more likely to demonstrate a relationship between recalled RB and disordered eating through the mechanism of shame. These findings have important implications for both anti-bullying awareness and eating disorder prevention programs.
Neurophysiological mechanisms of transcranial alternating current stimulation

Neuronal oscillations are the primary basis for precise temporal coordination of neuronal processing and are linked to different brain functions. Transcranial alternating current stimulation (tACS) has demonstrated promising potential in improving cognition by entraining neural oscillations. Despite positive findings in recent decades, the results obtained are sometimes rife with variance and replicability problems, and the findings translation to humans is quite challenging. A thorough understanding of the mechanisms underlying tACS is necessitated for accurate interpretation of experimental results. Animal models are useful for understanding tACS mechanisms, optimizing parameter administration, and improving rational design for broad horizons of tACS. Here, we review recent electrophysiological advances in tACS from animal models, as well as discuss some critical issues for results coordination and translation. We hope to provide an overview of neurophysiological mechanisms and recommendations for future consideration to improve its validity, specificity, and reproducibility.
GutAlive® enables DNA-based microbiome analysis without disrupting the original composition and diversity

Introduction A precise fecal microbiome analysis requires normalized methods for microbiome sampling, transport and manipulation in order to obtain a representative snapshot of the microbial community. GutAlive® is the unique stool collection kit that generates an anaerobic atmosphere enabling oxygen sensitive bacteria to survive, maintaining the original microbiome composition and diversity. Methods Five stool samples from different donors were collected using two different sampling devices, GutAlive® and Zymo DNA/RNA Shield®, and processed at four different time points. Shotgun metagenomics was used to evaluate the influence of the device and the processing timing on the microbial populations to unravel the potential fluctuations on the composition and diversity of the fecal microbiome and the metabolic pathways profiling. Additionally, RT-qPCR was used to quantify bacterial cell viability for downstream applications of microbiota samples beyond metagenomics. Results Our results show that GutAlive® enables bacterial cell viability overtime preserving DNA integrity, obtaining high-quantity and high-quality DNA to perform microbiome analysis using shotgun metagenomics. Based on the taxonomic profiling, metabolic pathways analysis, phylogeny and metagenome-assembled genomes, GutAlive® displayed greater performance without significant variability over time, showcasing the stabilization of the microbiome preserving the original composition and diversity. Indeed, this DNA stabilization is enabled with the preservation of bacterial viability on an anaerobic environment inside of the sampling device, without the addition of any reagents that interact directly with sample. Conclusion All the above makes GutAlive® an user-friendly kit for self-collection of biological samples, suitable for microbiome analysis, diagnostics, fecal microbiota transplant and bacterial isolation, maintaining the stability and bacterial viability over time, preserving the original composition and diversity of the microbiome.
Pan-cancer analysis of super enhancer-induced PRR7-AS1 as a potential prognostic and immunological biomarker

Introduction: Systematic pan-cancer analysis of the roles and regulatory mechanisms for PRR7-AS1 is currently not available. Methods: In the present study, a comprehensive bioinformatic approach was used to mine the underlying oncogenic effects of PRR7-AS1, including expression status, prognostic value and immune characteristics. Results: We discovered that PRR7-AS1 expression was remarkably upregulated in most cancer types and exhibited a negative correlation with the prognosis. Furthermore, PRR7-AS1 expression was inversely connected with the majority of tumor-infiltrating immune cells, immune scores and immune checkpoint gene expression in pancancer. There was also a significant correlation between PRR7-AS1 expression status and tumor mutational burden, microsatellite instability, and neoantigens in certain tumors. PRR7-AS1 had the best predictive power for immune checkpoint blockade efficacy compared to other well-recognized biomarkers. PRR7-AS1 overexpression could affect cytotoxic T cells-mediated antitumor responses. Functional enrichment analysis revealed that PRR7-AS1 might be involved in the metabolic pathways. Super enhancer activity might have participated in the regulation of PRR7-AS1 expression. And we constructed the competitive endogenous RNA networks for PRR7-AS1. Discussion: In general, PRR7-AS1 had the potential to be a diagnostic, prognostic and immune biomarker for pan cancer. PRR7-AS1 was correlated with an immunosuppressive microenvironment and was a new potential target for immunotherapy. Epigenetic factors were the driving forces for PRR7-AS1 overexpression in tumors.