Miracle-dz/UniFAR-FTUs huggingface dataset:
The Gain-of-Function R222S Variant in Scn11a Contributes to Visceral Hyperalgesia and Intestinal Dysmotility in Scn11aR222S/R222S Mice

Background The SCN11A gene encodes the α-subunit of the Nav1. 9 channel, which is a regulator of primary sensory neuron excitability. Nav1.9 channels play a key role in somatalgia. Humans with the gain-of-function mutation R222S in SCN11A exhibit familial episodic pain. As already known, R222S knock-in mice carrying a mutation orthologous to the human R222S variant demonstrate somatic hyperalgesia. This study investigated whether Scn11aR222S/R222S mice developed visceral hyperalgesia and intestinal dysmotility. Methods We generated Scn11aR222S/R222S mice using the CRISPR/Cas9 system. The somatic pain threshold in Scn11aR222S/R222S mice was assessed by Hargreaves' test and formalin test. The excitability of dorsal root ganglia (DRG) neurons was assessed by whole-cell patch-clamp recording. Visceralgia was tested using the abdominal withdrawal reflex (AWR), acetic acid-induced writhing, and formalin-induced visceral nociception tests. Intestinal motility was detected by a mechanical recording of the intestinal segment and a carbon powder propelling test. The excitability of the enteric nervous system (ENS) could influence gut neurotransmitters. Gut neurotransmitters participate in regulating intestinal motility and secretory function. Therefore, vasoactive intestinal peptide (VIP) and substance P (SP) were measured in intestinal tissues. Results The R222S mutation induced hyperexcitability of dorsal root ganglion neurons in Scn11aR222S/R222S mice. Scn11aR222S/R222S mice exhibited somatic hyperalgesia. In addition, Scn11aR222S/R222S mice showed lower visceralgia thresholds and slowed intestinal movements when compared with wild-type controls. Moreover, Scn11aR222S/R222S mice had lower SP and VIP concentrations in intestinal tissues. Conclusions These results indicated that Scn11aR222S/R222S mice showed visceral hyperalgesia and intestinal dysmotility.
Abnormal Insular Dynamic Functional Connectivity and Its Relation to Social Dysfunctioning in Children With Attention Deficit/Hyperactivity Disorder

Anomalies in large-scale cognitive control networks impacting social attention abilities are hypothesized to be the cause of attention deficit hyperactivity disorder (ADHD). The precise nature of abnormal brain functional connectivity (FC) dynamics including other regions, on the other hand, is unknown. The concept that insular dynamic FC (dFC) among distinct brain regions is dysregulated in children with ADHD was evaluated using Insular subregions, and we studied how these dysregulations lead to social dysfunctioning. Data from 30 children with ADHD and 28 healthy controls (HCs) were evaluated using dynamic resting state functional magnetic resonance imaging (rs-fMRI). We evaluated the dFC within six subdivisions, namely both left and right dorsal anterior insula (dAI), ventral anterior insula (vAI), and posterior insula (PI). Using the insular sub-regions as seeds, we performed group comparison between the two groups. To do so, two sample t-tests were used, followed by post-hoc t-tests. Compared to the HCs, patients with ADHD exhibited decreased dFC values between right dAI and the left middle frontal gyrus, left postcentral gyrus and right of cerebellum crus, respectively. Results also showed a decreased dFC between left dAI and thalamus, left vAI and left precuneus and left PI with temporal pole. From the standpoint of the dynamic functional connectivity of insular subregions, our findings add to the growing body of evidence on brain dysfunction in ADHD. This research adds to our understanding of the neurocognitive mechanisms behind social functioning deficits in ADHD. Future ADHD research could benefit from merging the dFC approach with task-related fMRI and non-invasive brain stimulation, which could aid in the diagnosis and treatment of the disorder.
Pre-Exposure With Extracellular Vesicles From Aspergillus fumigatus Attenuates Inflammatory Response and Enhances Fungal Clearance in a Murine Model Pulmonary Aspergillosis

Aspergillus fumigatus is a ubiquitous and saprophytic filamentous fungus and the main etiologic agent of aspergillosis. Infections caused by A. fumigatus culminate in a strong inflammatory response that can evolve into respiratory failure and may be lethal in immunocompromised individuals. In the last decades, it has been demonstrated that extracellular vesicles (EVs) elicit a notable biological response in immune cells. EVs carry a variety of biomolecules, therefore are considered potential antigen delivery vehicles. The role of EVs as a strategy for modulating an effective response against infections caused by A. fumigatus remains unexplored. Here we investigate the use of EVs derived from A. fumigatus as an immunization tool to induce a more robust immune response to A. fumigatus pulmonary infection. In order to investigate that, male C57BL/6 mice were immunized with two doses of EVs and infected with A. fumigatus. Pre-exposure of mice to EVs was able to induce the production of specific IgG serum for fungal antigens. Besides that, the immunization with EVs reduced the neutrophilic infiltrate into the alveoli, as well as the extravasation of total proteins and the production of proinflammatory mediators IL-1β, IL-6, and CXCL-1. In addition, immunization prevented extensive lung tissue damage and also improved phagocytosis and fungus clearance. Noteworthy, immunization with EVs, associated with subclinical doses of Amphotericin B (AmB) treatment, rescued 50% of mice infected with A. fumigatus from lethal fungal pneumonia. Therefore, the present study shows a new role for A. fumigatus EVs as host inflammatory response modulators, suggesting their use as immunizing agents.
A Theoretical Review on EFL/ESL Teachers' Professional Development: Approaches, Applications, and Impacts

Teachers as the most important elements of education constantly need professional development (PD) courses in order to improve their pedagogy and practice. Given this, many educational systems worldwide have paid special attention to designing courses by which the quality of teaching and learning raises considerably. This surge of interest has ended in different studies on PD programs in L2 education. However, the pertinent literature lacks a comprehensive review of the models, applications, and impacts of EFL/ESL teachers' PD and various aspects influenced by this construct. To fill this gap and add fresh insights into this strand of research, the present study aimed to review the definitions, characteristics, models, goals, and uses of teacher professional development (TPD) in L2 education. Moreover, several empirical studies were touched on to support the claims of TPD impact on teachers. Finally, the study presented different implications for L2 teachers, teacher trainers, researchers, and policy-makers who can realize the significance and impact of effective TPD courses on the whole process of teaching and learning.
Exosomal Composition, Biogenesis and Profiling Using Point-of-Care Diagnostics—Implications for Cardiovascular Disease

Arteriosclerosis is an important age-dependent disease that encompasses atherosclerosis, in-stent restenosis (ISR), pulmonary hypertension, autologous bypass grafting and transplant arteriosclerosis. Endothelial dysfunction and the proliferation of vascular smooth muscle cell (vSMC)-like cells is a critical event in the pathology of arteriosclerotic disease leading to intimal-medial thickening (IMT), lipid retention and vessel remodelling. An important aspect in guiding clinical decision-making is the detection of biomarkers of subclinical arteriosclerosis and early cardiovascular risk. Crucially, relevant biomarkers need to be good indicators of injury which change in their circulating concentrations or structure, signalling functional disturbances. Extracellular vesicles (EVs) are nanosized membraneous vesicles secreted by cells that contain numerous bioactive molecules and act as a means of intercellular communication between different cell populations to maintain tissue homeostasis, gene regulation in recipient cells and the adaptive response to stress. This review will focus on the emerging field of EV research in cardiovascular disease (CVD) and discuss how key EV signatures in liquid biopsies may act as early pathological indicators of adaptive lesion formation and arteriosclerotic disease progression. EV profiling has the potential to provide important clinical information to complement current cardiovascular diagnostic platforms that indicate or predict myocardial injury. Finally, the development of fitting devices to enable rapid and/or high-throughput exosomal analysis that require adapted processing procedures will be evaluated.
Evaluating Challenges and Adoption Factors for Active Assisted Living Smart Environments

While there have been rapid advancements in individual technologies such as Internet of Things (IoT) and Active Assisted Living (AAL) to address challenges related to an aging population, there remain large gaps in how these technologies can be integrated into the broader ecosystem to support older adults in aging in place. This research provides an overview of 15 solutions available to date around the globe and compares key factors for adoption in each solution, including user acceptance, privacy and security, accessibility, and interoperability. To scale these solutions sustainably and universally, the development and implementation of standards for key factors for adoption in AAL environments is critical. There is also a need for increased and sustainable funding to complement research priorities, to continue advancing AAL technologies.
p53/NF-kB Balance in SARS-CoV-2 Infection: From OMICs, Genomics and Pharmacogenomics Insights to Tailored Therapeutic Perspectives (COVIDomics)

SARS-CoV-2 infection affects different organs and tissues, including the upper and lower airways, the lung, the gut, the olfactory system and the eye, which may represent one of the gates to the central nervous system. Key transcriptional factors, such as p53 and NF-kB and their reciprocal balance, are altered upon SARS-CoV-2 infection, as well as other key molecules such as the virus host cell entry mediator ACE2, member of the RAS-pathway. These changes are thought to play a central role in the impaired immune response, as well as in the massive cytokine release, the so-called cytokine storm that represents a hallmark of the most severe form of SARS-CoV-2 infection. Host genetics susceptibility is an additional key side to consider in a complex disease as COVID-19 characterized by such a wide range of clinical phenotypes. In this review, we underline some molecular mechanisms by which SARS-CoV-2 modulates p53 and NF-kB expression and activity in order to maximize viral replication into the host cells. We also face the RAS-pathway unbalance triggered by virus-ACE2 interaction to discuss potential pharmacological and pharmacogenomics approaches aimed at restoring p53/NF-kB and ACE1/ACE2 balance to counteract the most severe forms of SARS-CoV-2 infection.
Editorial: Advancement in Gene Set Analysis: Gaining Insight From High-Throughput Data

Augmented Intelligence & Precision Health Laboratory, Department of Radiology and Research Institute of the McGill University Health Centre, Montreal, QC, Canada, Department of Computer Science, Wayne State University, Detroit, MI, United States, Biostatistics Centre and Department of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, Netherlands, Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada
Integration of Protein-Protein Interaction Networks and Gene Expression Profiles Helps Detect Pancreatic Adenocarcinoma Candidate Genes

More and more cancer-associated genes (CAGs) are being identified with the development of biological mechanism research. Integrative analysis of protein-protein interaction (PPI) networks and co-expression patterns of these genes can help identify new disease-associated genes and clarify their importance in specific diseases. This study proposed a PPI network and co-expression integration analysis model (PRNet) to integrate PPI networks and gene co-expression patterns to identify potential risk causative genes for pancreatic adenocarcinoma (PAAD). We scored the importance of the candidate genes by constructing a high-confidence co-expression-based edge-weighted PPI network, extracting protein regulatory sub-networks by random walk algorithm, constructing disease-specific networks based on known CAGs, and scoring the genes of the sub-networks with the PageRank algorithm. The results showed that our screened top-ranked genes were more critical in tumours relative to the known CAGs list and significantly differentiated the overall survival of PAAD patients. These results suggest that the PRNet method of ranking cancer-associated genes can identify new disease-associated genes and is more informative than the original CAGs list, which can help investigators to screen potential biomarkers for validation and molecular mechanism exploration.
Whole-Genome Sequencing of KMR3 and Oryza rufipogon-Derived Introgression Line IL50-13 (Chinsurah Nona 2/Gosaba 6) Identifies Candidate Genes for High Yield and Salinity Tolerance in Rice

The genomes of an elite rice restorer line KMR3 (salinity-sensitive) and its salinity-tolerant introgression line IL50-13, a popular variety of coastal West Bengal, India, were sequenced. High-quality paired-end reads were obtained for KMR3 (147.6 million) and IL50-13 (131.4 million) with a sequencing coverage of 30X-39X. Scaffolds generated from the pre-assembled contigs of each sequenced genome were mapped separately onto the reference genome of Oryza sativa ssp. japonica cultivar Nipponbare to identify genomic variants in terms of SNPs and InDels. The SNPs and InDels identified for KMR3 and IL50-13 were then compared with each other to identify polymorphic SNPs and InDels unique and common to both the genomes. Functional enrichment analysis of the protein-coding genes with unique InDels identified GO terms involved in protein modification, ubiquitination, deubiquitination, peroxidase activity, and antioxidant activity in IL50-13. Linoleic acid metabolism, circadian rhythm, and alpha-linolenic acid metabolism pathways were enriched in IL50-13. These GO terms and pathways are involved in reducing oxidative damage, thus suggesting their role in stress responses. Sequence analysis of QTL markers or genes known to be associated with grain yield and salinity tolerance showed polymorphism in 20 genes, out of which nine were not previously reported. These candidate genes encoded Nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4 (NB-ARC) domain-containing protein, cyclase, receptor-like kinase, topoisomerase II-associated protein PAT1 domain-containing protein, ion channel regulatory protein, UNC-93 domain-containing protein, subunit A of the heteromeric ATP-citrate lyase, and three conserved hypothetical genes. Polymorphism was observed in the coding, intron, and untranslated regions of the genes on chromosomes 1, 2, 4, 7, 11, and 12. Genes showing polymorphism between the two genomes were considered as sequence-based new candidates derived from Oryza rufipogon for conferring high yield and salinity tolerance in IL50-13 for further functional studies.
Core Components of Abscisic Acid Signaling and Their Post-translational Modification

Abscisic acid (ABA) is a major phytohormone that regulates plant growth, development, and abiotic/biotic stress responses. Under stress, ABA is synthesized in various plant organs, and it plays roles in diverse adaptive processes, including seed dormancy, growth inhibition, and leaf senescence, by modulating stomatal closure and gene expression. ABA receptor, clade A protein phosphatase 2C (PP2C), and SNF1-related protein kinase 2 (SnRK2) proteins have been identified as core components of ABA signaling, which is initiated via perception of ABA with receptor and subsequent activation or inactivation by phosphorylation/dephosphorylation. The findings of several recent studies have established that the post-translational modification of these components, including phosphorylation and ubiquitination/deubiquitination, play important roles in regulating their activity and stability. In this review, we discuss the functions of the core components of ABA signaling and the regulation of their activities via post-translational modification under normal and stress conditions.
Machine Learning Advances in Microbiology: A Review of Methods and Applications

Microorganisms play an important role in natural material and elemental cycles. Many common and general biology research techniques rely on microorganisms. Machine learning has been gradually integrated with multiple fields of study. Machine learning, including deep learning, aims to use mathematical insights to optimize variational functions to aid microbiology using various types of available data to help humans organize and apply collective knowledge of various research objects in a systematic and scaled manner. Classification and prediction have become the main achievements in the development of microbial community research in the direction of computational biology. This review summarizes the application and development of machine learning and deep learning in the field of microbiology and shows and compares the advantages and disadvantages of different algorithm tools in four fields: microbiome and taxonomy, microbial ecology, pathogen and epidemiology, and drug discovery.
Effectiveness and Nephrotoxicity of Intravenous Polymyxin B in Carbapenem-Resistant Gram-Negative Bacterial Infections Among Chinese Children

Background: No clinical study on the use of polymyxin B in Chinese children has been reported, thus making it difficult for pediatric clinicians to rationally select these drugs. Methods: A retrospective analysis of children treated with polymyxin B during hospitalization in a hospital from June 2019 to June 2021 was conducted to analyze its effectiveness and the incidence of acute kidney injury (AKI) during treatment with polymyxin B. Results: A total of 55 children were included in this study, and the results showed that the intravenous polymyxin B-based regimen had an effective rate of 52.7% in the treatment of Carbapenem-resistant Gram-negative bacterial (CR-GNB) infection in children. The results of the subgroup analysis showed that the course of treatment was longer in the favorable clinical response group than in the unfavorable outcome group (p = 0.027) and that electrolyte disturbances in children during the course of treatment could lead to unfavorable clinical outcomes (p = 0.042). The risk of incidence of AKI during treatment was 27.3%, and the all-cause mortality rate in the children on their discharge from the hospital was 7.3%. Conclusion: Polymyxin B can be used as a salvage therapy for CR-GNB infection in children when no other susceptible antibiotics are available, and the monitoring of kidney function should be strengthened.
DACPGTN: Drug ATC Code Prediction Method Based on Graph Transformer Network for Drug Discovery

The Anatomical Therapeutic Chemical (ATC) classification system is a drug classification scheme proposed by the World Health Organization, which is widely used for drug screening, repositioning, and similarity research. The ATC system assigns different ATC codes to drugs based on their anatomy, pharmacological, therapeutics and chemical properties. Predicting the ATC code of a given drug helps to understand the indication and potential toxicity of the drug, thus promoting its use in the therapeutic phase and accelerating its development. In this article, we propose an end-to-end model DACPGTN to predict the ATC code for the given drug. DACPGTN constructs composite features of drugs, diseases and targets by applying diverse biomedical information. Inspired by the application of Graph Transformer Network, we learn potential novel interactions among drugs diseases and targets from the known interactions to construct drug-target-disease heterogeneous networks containing comprehensive interaction information. Based on the constructed composite features and learned heterogeneous networks, we employ graph convolution network to generate the embedding of drug nodes, which are further used for the multi-label learning tasks in drug discovery. Experiments on the benchmark datasets demonstrate that the proposed DACPGTN model can achieve better prediction performance than the existing methods. The source codes of our method are available at https://github.com/Szhgege/DACPGTN.
Dynamic Characteristics and Effect on Thrust of Jet Tail Vortex Ring for Pump Jet Propulsion

When a pump is propelled by a propeller, the nozzle flooding of the jet wake area will produce a turbulent quasi-sequence structure and have a certain impact on the outflow field structure and thrust characteristics of the water jet propulsion pump. In this paper, a method that combined numerical simulation with vortex dynamics is adopted, which analyzes the dynamic characteristics and influence on the thrust characteristics of the water jet propulsion pump. A large eddy simulation turbulence model and a dimensionless water jet propulsion pump velocity coefficient were used to reveal flow structure and relation, with the pump operation parameters of the wake vortex ring. The thrust with a trailing vortex ring is 7.0% higher than that without a trailing vortex ring. Vortex dynamics and mathematical statistics are combined to quantitatively analyze the dynamic characteristics of the jet tail vortex ring. Finally, the formation time of the vortex ring is obtained in exponential relation with dimensionless transmission velocity and vorticity coefficient, which has nonlinear relation with vortex intensity coefficient and helicity coefficient. BP Neural Network combined with the LM algorithm is used to establish the mathematical relationship between the thrust and the physical characteristic parameters of the vortex ring.
Didattica in ambito matematico, scientifico e tecnologico nella scuola Teaching methods in mathematics, science and technology in schools

La societa odierna e attraversata da dinamiche non immaginabili fino a pochi decenni or sono: crescente pervasivita delle tecnologie digitali, sviluppo scientifico e tecnologico, flussi migratori, economie emergenti, crisi dei sistemi economico finanziari, trasformazioni delle strutture familiari e dei comportamenti sociali. Queste trasformazioni determinano l’esigenza di nuovi modelli per lo sviluppo e configurano il sapere come una risorsa sempre piu strategica per il progresso economico, sociale e per la qualita della vita (Hanushek & Woessmann, 2007). La scuola deve, quindi, affrontare sfide e problemi che derivano sia dalle mutate esigenze della societa attuale sia da insufficienze e bisogni a cui e sempre stato difficile offrire soluzioni efficaci (OECD, 2008). Per fare fronte al difficile compito di preparare gli individui a vivere ed operare in una societa attraversata stabilmente dal cambiamento si rende necessario andare oltre la concezione tradizionale dell’apprendimento basata in modo prevalente sulla trasmissione di conoscenze per entrare in una logica di apprendimento come un processo continuo che accompagni l’individuo lungo tutto il suo percorso di vita.