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Taking the Yangtze River Economic Belt as the study area, this research comprehensively applies spatial analysis methods and social network analysis methods to investigate the evolutionary characteristics of outdoor sports tourism flow network structure, utilizing online travelogue data collected through Python-based techniques. By integrating spatial analysis and social network analysis, we study the evolution characteristics of the network structure of outdoor sports tourism flow in the Yangtze River Economic Belt from 2012 to 2018. The results show that (1) The Yangtze River Economic Belt has shown steady growth in the number of outdoor sports tourism nodes, with significant spatial disparities in their distribution. These nodes are concentrated primarily in the lower reaches (eastern China) and upper reaches (western China) of the Yangtze River, demonstrating an overall development pattern characterized by “higher density in eastern and western regions compared to the central area.“; (2) the overall network density of outdoor sports tourism flow is not high, but during the study period, the overall network density value of outdoor sports tourism flow continues to rise, the connections between nodes are increasingly close, and the internal structure of the network is becoming clearer with time; and (3) the imbalance of the outdoor sports tourism flow network has gradually increased, which strengthens the role of the urban agglomeration or central city in the outdoor sports tourism flow network, aggravates the unbalanced state of the entire network structure, and the polarization of the network has become increasingly significant. The outdoor sports tourism flow essentially conforms to the “Pareto principle”. This study provides a scientific decision-making basis for rationally planning outdoor sports tourism routes and scientifically developing outdoor sports tourism destinations, while also offering theoretical support for optimizing the spatial layout and spatial structure of the outdoor sports tourism industry in the Yangtze River Economic Belt.

Branching/tillering is an important parameter of plant architecture and is tightly regulated by both internal factors (such as plant hormones) and external factors (such as light conditions). How the various signaling pathways converge to coordinately regulate branching is not well understood. Here, we report that in Arabidopsis , FHY3 and FAR1, two homologous transcription factors essential for phytochrome A-mediated light signaling, and SMXL6/SMXL7/SMXL8, three key repressors of the strigolactone (SL) signaling pathway, directly interact with SPL9 and SPL15 and suppress their transcriptional activation of BRC1 , a key repressor of branching, thus promoting branching. In addition, FHY3 and FAR1 also directly up-regulate the expression of SMXL6 and SMXL7 to promote branching. Simulated shade treatment reduces the accumulation of FHY3 protein, leading to increased expression of BRC1 and reduced branching. Our results establish an integrated model of light and SL coordinately regulating BRC1 expression and branching through converging at the BRC1 promoter. In plants, branching is regulated by both hormones and external cues such as light. Here the authors show that in Arabidopsis , the phytochrome A-signaling components FHY3 and FAR1, and SMXL proteins that repress strigolactone signaling, both interact with SPL proteins to control expression of the branching regulator BRC1 .

Computer vision recognition refers to the use of cameras and computers to replace the human eyes with computer vision, such as target recognition, tracking, measurement, and in-depth graphics processing, to process images to make them more suitable for human vision. Aiming at the problem of combining basketball shooting technology with visual recognition motion capture technology, this article mainly introduces the research of basketball shooting technology based on computer vision recognition fusion motion capture technology. This paper proposes that this technology first performs preprocessing operations such as background removal and filtering denoising on the acquired shooting video images to obtain the action characteristics of the characters in the video sequence and then uses the support vector machine (SVM) and the Gaussian mixture model to obtain the characteristics of the objects. Part of the data samples are extracted from the sample set for the learning and training of the model. After the training is completed, the other parts are classified and recognized. The simulation test results of the action database and the real shot video show that the support vector machine (SVM) can more quickly and effectively identify the actions that appear in the shot video, and the average recognition accuracy rate reaches 95.9%, which verifies the application and feasibility of this technology in the recognition of shooting actions is conducive to follow up and improve shooting techniques.

Hypothyroidism is a risk factor for metabolic dysfunction-associated steatotic liver disease (MASLD) but it is not clear whether subclinical hypothyroidism (SCH) increases the risk of MASLD and whether SCH patients with MASLD require treatment. In this study, we reviewed articles published in PubMed from 2013 to 2024 with SCH/hypothyroidism and MASLD as keywords. According to the studies retrieved, SCH increases the likelihood of developing MASLD. Thyroid hormones influence energy metabolism and storage in adipose tissues, as well as fatty acid and cholesterol metabolism and transport in the liver. L-T 4 replacement therapy reduces the prevalence of MASLD, especially in patients with severe SCH or mild SCH with dyslipidemia. Recent studies showed that thyroid hormone analogues and thyroid hormone β receptor agonists obtained positive results in the treatment of MASLD in animal models and clinical trials, and Resmetirom has been approved by the US. Food and Drug Administration (FDA) under the name Rezdiffra for use in conjunction with dietary and exercise regimens for managing non-cirrhotic NASH in adults with moderate to advanced fibrosis.

The development of immunoprophylactic products against respiratory syncytial virus (RSV) has resulted in notable advancements, leading to an increased demand for preclinical experiments and placing greater demands on animal models. Nevertheless, the field of RSV research continues to face the challenge of a lack of ideal animal models. Despite the demonstration of efficacy in animal studies, numerous RSV vaccine candidates have been unsuccessful in clinical trials, primarily due to the lack of suitable animal models. The most commonly utilized animal models for RSV research are cotton rats, mice, lambs, and non-human primates. These animals have been extensively employed in mechanistic studies and in the development and evaluation of vaccines and therapeutics. However, each model only exemplifies some, but not all, aspects of human RSV disease. The aim of this study was to provide a comprehensive summary of the disease symptoms, viral replication, pathological damage, and enhanced RSV disease (ERD) conditions across different RSV animal models. Furthermore, the advantages and disadvantages of each model are discussed, with the intention of providing a valuable reference for related RSV research.

Evidence is mounting that the gut-brain axis plays an important role in mental diseases fueling mechanistic investigations to provide a basis for future targeted interventions. However, shotgun metagenomic data from treatment-naïve patients are scarce hampering comprehensive analyses of the complex interaction between the gut microbiota and the brain. Here we explore the fecal microbiome based on 90 medication-free schizophrenia patients and 81 controls and identify a microbial species classifier distinguishing patients from controls with an area under the receiver operating characteristic curve (AUC) of 0.896, and replicate the microbiome-based disease classifier in 45 patients and 45 controls (AUC = 0.765). Functional potentials associated with schizophrenia include differences in short-chain fatty acids synthesis, tryptophan metabolism, and synthesis/degradation of neurotransmitters. Transplantation of a schizophrenia-enriched bacterium, Streptococcus vestibularis, appear to induces deficits in social behaviors, and alters neurotransmitter levels in peripheral tissues in recipient mice. Our findings provide new leads for further investigations in cohort studies and animal models.

Psychiatric disorders are the leading cause of disability worldwide while the pathogenesis remains unclear. Genome-wide association studies (GWASs) have made great achievements in detecting disease-related genetic variants. However, functional information on the underlying biological processes is often lacking. Current reports propose the use of metabolic traits as functional intermediate phenotypes (the so-called genetically determined metabotypes or GDMs) to reveal the biological mechanisms of genetics in human diseases. Here we conducted a two-sample Mendelian randomization analysis that uses GDMs to assess the causal effects of 486 human serum metabolites on 5 major psychiatric disorders, which respectively were schizophrenia (SCZ), major depression (MDD), bipolar disorder (BIP), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD). Using genetic variants as proxies, our study has identified 137 metabolites linked to the risk of psychiatric disorders, including 2-methoxyacetaminophen sulfate, which affects SCZ (P = 1.7 × 10–5) and 1-docosahexaenoylglycerophosphocholine, which affects ADHD (P = 5.6 × 10–5). Fourteen significant metabolic pathways involved in the 5 psychiatric disorders assessed were also detected, such as glycine, serine, and threonine metabolism for SCZ (P = .0238), Aminoacyl-tRNA biosynthesis for both MDD (P = .0144) and ADHD (P = .0029). Our study provided novel insights into integrating metabolomics with genomics in order to understand the mechanisms underlying the pathogenesis of human diseases.

In flowering plants, the pollen coat protects the released male germ cells from desiccation and damage during pollination. However, we know little about the mechanism by which the chemical composition of the pollen coat prevents dehydration of pollen grains. Here we report that deficiency of a grass conserved triterpene synthase, OsOSC12/OsPTS1, in rice leads to failure of pollen coat formation. The mutant plants are male sterile at low relative humidity (RH < 60%), but fully male fertile at high relative humidity (>80%). The lack of three major fatty acids in the pollen coat results in rapid dehydration of pollen grains. We show that applying mixtures of linolenic acid and palmitic acid or stearic acid are able to prevent over-dehydration of mutant pollen grains. We propose that humidity-sensitive genic male sterility (HGMS) could be a desirable trait for hybrid breeding in rice, wheat, maize, and other crops. In flowering plants, the pollen coat surrounds the male germ cells and protects against dehydration, damage and pathogen attack. Here, the authors show that a deficiency in terpenoid synthesis results in rice pollen over-dehydration and leads to a humidity-sensitive conditional male sterile phenotype.

Cepharanthine is a secondary metabolite isolated from Stephania . It has been reported that it has anti-conronaviruses activities including severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Here, we assemble three Stephania genomes ( S. japonica , S. yunnanensis , and S. cepharantha ), propose the cepharanthine biosynthetic pathway, and assess the antiviral potential of compounds involved in the pathway. Among the three genomes, S. japonica has a near telomere-to-telomere assembly with one remaining gap, and S. cepharantha and S. yunnanensis have chromosome-level assemblies. Following by biosynthetic gene mining and metabolomics analysis, we identify seven cepharanthine analogs that have broad-spectrum anti-coronavirus activities, including SARS-CoV-2, Guangxi pangolin-CoV (GX_P2V), swine acute diarrhoea syndrome coronavirus (SADS-CoV), and porcine epidemic diarrhea virus (PEDV). We also show that two other genera, Nelumbo and Thalictrum , can produce cepharanthine analogs, and thus have the potential for antiviral compound discovery. Results generated from this study could accelerate broad-spectrum anti-coronavirus drug discovery. Cepharanthine is a secondary metabolite isolated from Stephania with a variety of medicinal properties. Here, the authors assembled three Stephania genomes, propose cepharanthine biosynthetic pathway, and assess the antiviral potential of cepharanthine-related metabolites.

Ultrahigh-voltage electricity systems are a vital part of energy networks, often across wide regions passing through mountainous terrains. The instability of slopes forming tower foundations along transmission lines poses a large risk to the entire energy network. Moreover, the tower foundations along extra-high-voltage electricity transmission lines are a very special type of element that are also highly vulnerable to landslides. In this study, an integrative risk assessment framework, including a hazard assessment, vulnerability analysis for the specified element at risk, and consequence estimation, is proposed to quantify the direct and indirect risks of landslides to power transmission lines. The Yanzi landslide, where a tower of the major ultrahigh-voltage transmission line from Sichuan (western China) to Shanghai (eastern China) has just been constructed, is taken as a case study. The correlation between landslide displacement and tower structure tilting is studied. In terms of the precipitation return period, factors of safety, failure probability, and deformation are simulated. A physical vulnerability curve is fitted by assuming a Weibull relationship between the horizontal deformation (hazard intensity) of the landslide and the tower inclination ratio. The total risk is calculated as the sum of the direct and indirect losses, among which the potential indirect risk due to tower damage is much greater than the direct risk. This work demonstrates the importance of landslide treatment strategies along electricity transmission lines by considering the potential indirect risks. The risk assessment model of landslides affecting ultrahigh-voltage electricity transmission lines proposed in this study could be useful for other types of indirect landslide risk evaluations.