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Introduction: Golden pompano (Trachinotus ovatus) is economically significant important for offshore cage aquaculture in China and Southeast Asian countries. Lack of high-quality genomic data and accurate gene annotations greatly restricts its genetic breeding progress. Objectives: To decode the mechanisms of sex determination and rapid growth in golden pompano and facilitate the sex- and growth-aimed genetic breeding. Methods: Genome assemblies of male and female golden pompano were generated using Illumina, PacBio, BioNano, genetic maps and Hi-C sequencing data. Genomic comparisons, whole genome re-sequencing of 202 F1 individuals, QTL mapping and gonadal transcriptomes were used to analyze the sex determining region, sex chromosome evolution, SNP loci, and growth candidate genes. Zebrafish model was used to investigate the functions of growth candidate gene. Results: Female (644.45 Mb) and male (652.12 Mb) genomes of golden pompano were assembled and annotated at the chromosome level. Both genomes are highly conserved and no new or highly differentiated sex chromosomes occur. A 3.5 Mb sex determining region on LG15 was identified, where Hsd17b1, Micall2 and Lmx1a were putative candidates for sex determination. Three SNP loci significantly linked to growth were pinpointed, and a growth-linked gene gpsstr1 was identified by locus BSNP1369 (G → C, 17489695, Chr23). Loss of sstr1a (homologue of gpsstr1) in zebrafish caused growth retardation. Conclusion: This study provides insights into sex chromosome evolution, sex determination and rapid growth of golden pompano.

Abstract To overcome the limitation of a single classification model’s inability to simultaneously identify multiple lesion targets within periapical radiographs, This study proposes YoCNET (Yolov5 + ConvNeXt), a novel deep learning integrated model. YoCNET leverages the target detection capability of Yolov5 and the image classification capability of ConvNeXt to achieve automatic segmentation of individual teeth and concurrent detection of periapical lesions across multiple teeth. A dataset of 1,305 periapical radiographs was used to train and validate the ConvNeXt and ResNet34 models, with an 8:2 split for training and validation. Deciduous teeth were excluded from the dataset. Furthermore, 717 individual teeth images were extracted from 200 previously unused periapical radiographs for integrated model validation. Evaluation metrics included accuracy, precision, sensitivity, F1 score, AUC (Area Under Curve), and a confusion matrix.The YoCNET integrated model demonstrated values of 90.93%, 98.88%, 85.30%, 0.9159, and 0.9757 for accuracy, precision, sensitivity, F1 score, and AUC, respectively. These metrics were superior to those achieved by the YoRNET (Yolov5 + ResNet34) integrated model, which recorded 80.47%, 83.78%, 82.16%, 0.8296, and 0.8822. The integrated model achieved high accuracy and efficiency in automatic teeh segmentation by Yolov5 and in automatically detecting multiple periapical lesions by ConvNeXt. YoCNET exhibited superior overall data performance, making it a more suitable deep learning integrated model for clinical applications.

Abstract Aiming at the Terrestrial Water Storage(TWS) changes in the Amazon River basin, this article uses the coordinate time series data of the Global Navigation Satellite System (GNSS), adopts the Variational Mode Decomposition and Bidirectional Long and Short Term Memory(VMD-BiLSTM) method to extract the vertical crustal deformation series, and then adopts the Principal Component Analysis(PCA) method to invert the changes of terrestrial water storage in the Amazon Basin from July 15, 2012 to July 25, 2018. Then, the GNSS inversion results were compared with the equivalent water height retrieved from Gravity Recovery and Climate Experiment (GRACE) data. The results show that (1) the extraction method proposed in this article has better denoising effect than the traditional method; (2) the surface hydrological load deformation can be well calculated using GNSS coordinate vertical time series, and then the regional TWS changes can be inverted, which has a good consistency with the result of GRACE inversion of water storage, and has almost the same seasonal variation characteristics; (3) There is a strong correlation between TWS changes retrieved by GNSS based on surface deformation characteristics and water mass changes calculated by GRACE based on gravitational field changes, but GNSS satellite’s all-weather measurement results in a finer time scale compared with GRACE inversion results. In summary, GNSS can be used as a supplementary technology for monitoring terrestrial water storage changes, and can complement the advantages of GRACE technology.

Objective This study aimed to identify and characterize a novel endo-β-glucanase, IDSGLUC9-4, from the rumen metatranscriptome of Hu sheep. Methods A novel endo-β-glucanase, IDSGLUC9-4, was heterologously expressed in Escherichia coli and biochemically characterized. The optimal temperature and pH of recombinant IDSGLUC9-4 were determined. Subsequently, substrate specificity of the enzyme was assessed using mixed-linked glucans including barley β-glucan and Icelandic moss lichenan. Thin-layer chromatography (TLC), high-performance liquid chromatography (HPLC), matrix assisted laser desorption ionization time of flight mass spectrometry analyses were conducted to determine the products released from polysaccharides and cello-oligosaccharides substrates. Results The recombinant IDSGLUC9-4 exhibited temperature and pH optima of 40°C and pH 6.0, respectively. It exclusively hydrolyzed mixed-linked glucans, with significant activity observed for barley β-glucan (109.59±3.61 μmol/mg min) and Icelandic moss lichenan (35.35±1.55 μmol/mg min). TLC and HPLC analyses revealed that IDSGLUC9-4 primarily released cellobiose, cellotriose, and cellotetraose from polysaccharide substrates. Furthermore, after 48 h of reaction, IDSGLUC9-4 removed most of the glucose, indicating transglycosylation activity alongside its endo-glucanase activity. Conclusion The recombinant IDSGLUC9-4 was a relatively acid-resistant, mesophilic endo-glucanase (EC 3.2.1.4) that hydrolyzed glucan-like substrates, generating predominantly G3 and G4 oligosaccharides, and which appeared to have glycosylation activity. These findings provided insights into the substrate specificity and product profiles of rumen-derived GH9 glucanases and contributed to the expanding knowledge of cellulolytic enzymes and novel herbivore rumen enzymes in general.

Identifying novel compound–protein interactions (CPIs) plays a pivotal role in target identification and drug discovery. Although the recent multimodal methods have achieved outstanding advances in CPI prediction, they fail to effectively learn both intra-modality and inter-modality dynamics, which limits their prediction performance. To address the limitation, we propose a novel multimodal tensor fusion CPI prediction framework, named MMTF-CPI, which contains three unimodal learning modules for structure, heterogeneous network and transcriptional profiling modalities, a tensor fusion module and a prediction module. MMTF-CPI is capable of focusing on both intra-modality and inter-modality dynamics with the tensor fusion module. We demonstrated that MMTF-CPI is superior to multiple state-of-the-art multimodal methods across seven datasets. The prediction performance of MMTF-CPI is significantly improved with the tensor fusion module compared to other fusion methods. Moreover, our case studies confirmed the practical value of MMTF-CPI in target identification. Via MMTF-CPI, we also discovered several candidate compounds for the therapy of breast cancer and non-small cell lung cancer.

Abstract Background Health lifestyles exert a substantial influence on the quality of everyday life, primarily affecting health maintenance and enhancement. While health-related practices during the COVID-19 pandemic may have positively altered the health lifestyles of Canadians to a certain degree, government reports indicate that issues related to health behaviors, such as cigarette smoking, physical inactivity, and alcohol consumption, continue to pose challenges to the health of Canadians. Social determinants of these health behaviors thus hold significant academic value in the formulation of policy guidelines. Objective The aim of this study is to scrutinize the social determinants of health with respect to social factors that have may have impacts on the health-related behaviors of Canadians. We tested health behaviors including cigarette use, alcohol consumption, and participation in physical exercise, which are integral to the promotion and improvement of individual health. Methods To examine the social determinants of Canadians’ health lifestyles, we utilized nationally representative data from the 2017–2018 Canadian Community Health Survey annual component. Our data analysis involved the bootstrapping method with two-level mixed-effect logistic regressions, ordered logistic regressions, and negative binomial regressions. Additionally, we conducted several robustness checks to confirm the validity of our findings. Results The findings show that demographic background, socioeconomic status, social connections, and physical and mental health conditions all play a role in Canadians’ smoking, physical activity, and drinking behaviors. Noticeably, the association patterns linking to these social determinants vary across specific health lifestyles, shedding light on the complex nature of the social determinants that may influence young and middle-aged Canadians’ health lifestyles. Moreover, in the context of Canada, the health-region level demographic, socioeconomic, and working conditions are significantly linked to residents’ health lifestyles. Conclusions Investigating the social determinants of health lifestyles is pivotal for policymakers, providing them with the necessary insights to create effective interventions that promote healthy behaviors among specific demographic groups. It is recommended that health education and interventions at the community level targeting smoking, physical inactivity, and alcohol consumption be introduced. These interventions should be tailored to specific subgroups, considering their demographic and socioeconomic characteristics, social networks, and health status. For instance, it is imperative to focus our attention on individuals with lower educational attainment and socioeconomic status, particularly in relation to their smoking habits and physical inactivity. Conversely, interventions aimed at addressing alcohol consumption should be targeted towards individuals of a higher socioeconomic status. This nuanced approach allows for a more effective and tailored intervention strategy.

In this study, aiming at fulfilling the requirement of polarization acquisition and utilization, a method for active deception jamming recognition based on the time-varying polarization-conversion metasurface is investigated. First, an anisotropic phase-modulated metasurface supporting 3-bit phase quantization in the 9.6～10.1 GHz frequency band is designed. By optimizing the periodical phase coding, the polarization state can be converted on demand. And then, loading the polarization-conversion metasurface on a single polarization radar antenna so that the polarization states of the antenna can change along a specific trajectory. By extracting the difference in the polarization domain between target and active deception jamming, the active deception jamming could be distinguished from the radar echo. The simulation results show that under the constraints of three different polarization trajectories, the active deception jamming and targets exhibit a significant clustering effect, and the identification effect is stable. Compared with jamming identification methods that rely on dual-polarization or full-polarization radar systems, the proposed method has both low cost and high efficiency, which has great application potential in radar anti-jamming.

Abstract Background In plants, the leaf functions as a solar panel, where photosynthesis converts carbon dioxide and water into carbohydrates and oxygen. In soybean, leaf type traits, including leaf shape, leaf area, leaf width, and leaf width so on, are considered to be associated with yield. In this study, we performed morphological characterization, transcriptome analysis, and endogenous hormone analysis of a rolled and narrow leaf mutant line (rl) in soybean. Results Compared with wild type HX3, mutant line rl showed rolled and narrower leaflet, and smaller leaf, meanwhile rl also performed narrower pod and narrower seed. Anatomical analysis of leaflet demonstrated that cell area of upper epidermis was bigger than the cell area of lower epidermis in rl, which may lead rolled and narrow leaf. Transcriptome analysis revealed that several cytokinin oxidase/dehydrogenase (CKX) genes (Glyma.06G028900, Glyma.09G225400, Glyma.13G104700, Glyma.14G099000, and Glyma.17G054500) were up-regulation dramatically, which may cause lower cytokinin level in rl. Endogenous hormone analysis verified that cytokinin content of rl was lower. Hormone treatment results indicated that 6-BA rescued rolled leaf enough, rescued partly narrow leaf. And after 6-BA treatment, the cell area was similar between upper epidermis and lower epidermis in rl. Although IAA content and ABA content were reduced in rl, but exogenous IAA and ABA didn’t affect leaf type of HX3 and rl. Conclusions Our results suggest abnormal cytokinin metabolism caused rolled and narrow leaf in rl, and provide valuable clues for further understanding the mechanisms underlying leaf development in soybean.

Infrastructure and economic networks can be used to describe different dimensions of urban systems, and a close relationship exists between them. Therefore, it is important to study the dynamic coupling relationship between them to promote the formation and development of urban networks. Relevant studies have compared and analyzed the evolution characteristics of urban network structures from different dimensions; however, relatively few studies have focused on the dynamic coupling relationship between high-speed rail and remote investment networks. The formation and development of high-speed rail networks has become a key factor affecting remote investment networks, and the layout of a remote investment network also affects the development of a high-speed rail network. To this end, we used high-speed railway operation service data and related transaction data of listed companies from 2008 to 2023 to construct high-speed railway and remote investment networks reflecting intercity high-speed railway and enterprise remote investment connections, respectively. QAP correlation analysis was used to explore the overall correlation between the two networks. Using the quadrantal diagram method and the coupling coordination degree model, we discuss the spatiotemporal coupling coordination of the two networks, identify the types of cities and urban connections, and propose operational planning suggestions for cities and high-speed railways. The results indicate the following: 1) Both the scale and density of the high-speed rail network and the off-site investment network show a rapid growth trend, and the expansion of the high-speed rail network is significantly faster than that of the off-site investment network. There is a significant positive correlation between high-speed rail and the remote investment network as a whole, and the degree of correlation first increases and then decreases. 2) In terms of space, cities with the simultaneous development of high-speed rail and remote investment networks are primarily concentrated in the administrative and economic centers of the eastern region. However, cities with lagging high-speed rail networks are mainly located in non-transportation hub cities in the economically developed areas of the Pearl River Delta, Dalian, and Urumqi. Moreover, cities with advanced high-speed rail networks are mainly centered in the central and eastern regions around the main high-speed rail lines. 3) Cities with synchronous development of high-speed rail and remote investment networks are mainly located in developed cities within the five major urban agglomerations. The pairs of cities with lagging high-speed rail networks are mainly located between the core cities of different urban agglomerations. Pairs of cities with advanced high-speed rail networks are typically positioned between cities that are closer together and contain at least one city with a less developed economy. The relevant research results can provide policy support for China's high-speed rail operation planning and urban system construction.

Abstract The cold tolerance of Litopenaeus vannamei is important for breeding in specific areas. To explore the cold tolerance mechanism of L. vannamei, this study analyzed biochemical indicators, cell apoptosis, and metabolomic responses in cold-tolerant (Lv-T) and common (Lv-C) L. vannamei under low-temperature stress (18 °C and 10 °C). TUNEL analysis showed a significant increase in apoptosis of hepatopancreatic duct cells in L. vannamei under low-temperature stress. Biochemical analysis showed that Lv-T had significantly increased levels of superoxide dismutase (SOD) and triglycerides (TG), while alanine aminotransferase (ALT), alkaline phosphatase (ALP), lactate dehydrogenase (LDH-L), and uric acid (UA) levels were significantly decreased compared to Lv-C (p

Abstract Purpose To investigate the associations between the most popular social media platform WeChat usage and cognitive performance among the middle-aged and older Chinese population using data from a nationally representative survey. Methods In total, 17,472 participants (≥ 45 years old) from the China Health and Retirement Longitudinal Study (CHARLS, Wave 4, 2018) were analyzed. Cognitive performance including episodic memory and executive function was assessed using Mini-Mental Status Examination (MMSE). Other confounding variables included socio-economic characteristics, medical status, and lifestyle-related information. Multiple linear regression models were used to test the association between cognitive performance and WeChat usage by introducing covariates hierarchically. Subgroup analyses of age and gender were conducted to estimate the robustness of the primary findings. Results After adjusting for multiple confounders across all linear models, WeChat usage is significantly associated with executive function, episodic memory, and global cognitive performance (all p values

Multifunctional therapeutics have emerged as a solution to the constraints imposed by drugs with singular or insufficient therapeutic effects. The primary challenge is to integrate diverse pharmacophores within a single-molecule framework. To address this, we introduced DeepSA, a novel edit-based generative framework that utilizes deep simulated annealing for the modification of articaine, a well-known local anesthetic. DeepSA integrates deep neural networks into metaheuristics, effectively constraining molecular space during compound generation. This framework employs a sophisticated objective function that accounts for scaffold preservation, anti-inflammatory properties, and covalent constraints. Through a sequence of local editing to navigate the molecular space, DeepSA successfully identified AT-17, a derivative exhibiting potent analgesic properties and significant anti-inflammatory activity in various animal models. Mechanistic insights into AT-17 revealed its dual mode of action: selective inhibition of NaV1.7 and 1.8 channels, contributing to its prolonged local anesthetic effects, and suppression of inflammatory mediators via modulation of the NLRP3 inflammasome pathway. These findings not only highlight the efficacy of AT-17 as a multifunctional drug candidate but also highlight the potential of DeepSA in facilitating AI-enhanced drug discovery, particularly within stringent chemical constraints.

Abstract Members of the multiple antibiotic resistance regulator (MarR) protein family are ubiquitous in bacteria and play critical roles in regulating cellular metabolism and antibiotic resistance. MarR family proteins function as repressors, and their interactions with modulators induce the expression of controlled genes. The previously characterized modulators are insufficient to explain the activities of certain MarR family proteins. However, recently, several MarR family proteins have been reported to sense sulfane sulfur, including zero‐valent sulfur, persulfide (R‐SSH), and polysulfide (R‐SnH, n ≥ 2). Sulfane sulfur is a common cellular component in bacteria whose levels vary during bacterial growth. The changing levels of sulfane sulfur affect the expression of many MarR‐controlled genes. Sulfane sulfur reacts with the cysteine thiols of MarR family proteins, causing the formation of protein thiol persulfide, disulfide bonds, and other modifications. Several MarR family proteins that respond to reactive oxygen species (ROS) also sense sulfane sulfur, as both sulfane sulfur and ROS induce the formation of disulfide bonds. This review focused on MarR family proteins that sense sulfane sulfur. However, the sensing mechanisms reviewed here may also apply to other proteins that detect sulfane sulfur, which is emerging as a modulator of gene regulation.

Abstract Background The crossbreeding of specialized beef cattle breeds with Chinese indigenous cattle is a common method of genetic improvement. Xia’nan cattle, a crossbreed of Charolais and Nanyang cattle, is China’s first specialized beef cattle breed with independent intellectual property rights. After more than two decades of selective breeding, Xia’nan cattle exhibit a robust physique, good environmental adaptability, good tolerance to coarse feed, and high meat production rates. This study analyzed the population genetic structure, genetic diversity, and genomic variations of Xia’nan cattle using whole-genome sequencing data from 30 Xia’nan cattle and 178 published cattle genomic data. Result The ancestry estimating composition analysis showed that the ancestry proportions for Xia’nan cattle were mainly Charolais with a small amount of Nanyang cattle. Through the genetic diversity studies (nucleotide diversity and linkage disequilibrium decay), we found that the genomic diversity of Xia’nan cattle is higher than that of specialized beef cattle breeds in Europe but lower than that of Chinese native cattle. Then, we used four methods to detect genome candidate regions influencing the excellent traits of Xia’nan cattle. Among the detected results, 42 genes (θπ and CLR) and 131 genes (F ST and XP-EHH) were detected by two different detection strategies. In addition, we found a region in BTA8 with strong selection signals. Finally, we conducted functional annotation on the detected genes and found that these genes may influence body development (NR6A1), meat quality traits (MCCC1), growth traits (WSCD1, TMEM68, MFN1, NCKAP5), and immunity (IL11RA, CNTFR, CCL27, SLAMF1, SLAMF7, NAA35, and GOLM1). Conclusion We elucidated the genomic features and population structure of Xia’nan cattle and detected some selection signals in genomic regions potentially associated with crucial economic traits in Xia’nan cattle. This research provided a basis for further breeding improvements in Xia’nan cattle and served as a reference for genetic enhancements in other crossbreed cattle.

Abstract Background Immune checkpoint inhibitors are a relatively new advancement in the world of cancer therapy. As such, their adverse effects have yet to be fully understood, with only recent literature documenting autoimmune phenomena secondary to their utilization. Specific immune checkpoint inhibitors have recently been linked with the development of myasthenia gravis, which is classically known to manifest spontaneously in patients. Given the relative rarity of this presentation, the risk of misdiagnosis and subsequent mortality and morbidity is concerning. Case presentation We discuss the case of a 73-year-old male who presented with clinical symptoms of myasthenia gravis and myositis shortly after beginning treatment with Pembrolizumab. The diagnosis of myasthenia gravis was initially missed at an outside hospital, which delayed initiation of proper treatment. Conclusion While the incidence of “de-novo” diseases secondary to immune checkpoint inhibitors might be increasing, guidelines regarding best treatment options do not yet exist, leaving many providers at a loss when faced with making clinical decisions surrounding patients with De novo myasthenia gravis. Thus, our goal is to underscore the importance of early recognition of this disease, and emphasize the need for a standard of care as immune checkpoint inhibitors usage becomes more prevalent.