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This study examined the influence of lifestyle habits on health self-assessments among elderly rural men and the effect of age on the strength of the impact to provide a basis for targeted health improvement in this population. Data from the 2018 Chinese longitudinal healthy longevity survey were analyzed using one-way analysis of variance, regression analysis, and Shapley value decomposition tests. The model analysis results showed that elderly rural men who did not drink alcohol or were moderate drinkers, maintained regular sleep patterns, exercised regularly, and had active social interactions had better health self-assessment results (p < 0.01). Notably, the impact of lifestyle habits on health perceptions varied with age. Specifically, the influence of alcohol consumption and sleep duration decreased with age, while the benefits of physical activity and social engagement became more pronounced. These results suggest that lifestyle habits significantly impact the health self-assessments of elderly rural men, with notable variations observed in the strength of these effects across different ages. To improve the overall health of elderly rural men, alcohol cessation interventions should be implemented as early as possible, attention should be paid to the sleep habits of young male seniors, and low-intensity group exercise and social activities should be actively organized for older male seniors.

Soil salinization/alkalization is a complex environmental factor that includes not only neutral salt NaCl but also other components like Na2CO3. miRNAs, as small molecules that regulate gene expression post-transcriptionally, are involved in plant responses to abiotic stress. In this study, maize seedling roots were treated for 5 h with 100 mM NaCl, 50 mM Na2CO3, and H2O, respectively. Sequencing analysis of differentially expressed miRNAs under these conditions revealed that the Na2CO3 treatment group had the most differentially expressed miRNAs. Cluster analysis indicated their main involvement in the regulation of ion transport, binding, metabolism, and phenylpropanoid and flavonoid biosynthesis pathways. The unique differentially expressed miRNAs in the NaCl treatment group were related to the sulfur metabolism pathway. This indicates a significant difference in the response patterns of maize to different treatment groups. This study provides theoretical evidence and genetic resources for further analysis of the molecular mechanisms behind maize’s salt–alkali tolerance.

Abstract Background B-cell CLL/lymphoma 6 member B (BCL6B) operates as a sequence-specific transcriptional repressor within the nucleus, playing crucial roles in various biological functions, including tumor suppression, immune response, stem cell self-renew, and vascular angiogenesis. However, whether BCL6B is involved in endothelial cell (EC) development has remained largely unknown. ETS variant transcription factor 2 (ETV2) is well known to facilitate EC differentiation. This study aims to determine the important role of BCL6B in EC differentiation and its potential mechanisms. Methods Doxycycline-inducible human induced pluripotent stem cell (hiPSC) lines with BCL6B overexpression or BCL6B knockdown were established and subjected to differentiate into ECs and vessel organoids (VOs). RNA sequencing analysis was performed to identify potential signal pathways regulated by BCL6B during EC differentiation from hiPSCs. Quantitative real-time PCR (qRT-PCR) was used to detect the expression of pluripotency and vascular-specific marker genes expression. EC differentiation efficiency was determined by Flow cytometry analysis. The performance of EC was evaluated by in vitro Tube formation assay. The protein expression and the vessel-like structures were assessed using immunofluorescence analysis or western blot. Luciferase reporter gene assay and chromatin immunoprecipitation (ChIP)-PCR analysis were used to determine the regulatory relationship between BCL6B and ETV2. Results Functional ECs and VOs were successfully generated from hiPSCs. Notably, overexpression of BCL6B suppressed while knockdown of BCL6B improved EC differentiation from hiPSCs. Additionally, the overexpression of BCL6B attenuated the capacity of derived hiPSC-ECs to form a tubular structure. Furthermore, compared to the control VOs, BCL6B overexpression repressed the growth of VOs, whereas BCL6B knockdown had little effect on the size of VOs. RNA sequencing analysis confirmed that our differentiation protocol induced landscape changes for cell/tissue/system developmental process, particularly vascular development and tube morphogenesis, which were significantly modulated by BCL6B. Subsequent experiments confirmed the inhibitory effect of BCL6B is facilitated by the binding of BCL6B to the promoter region of ETV2, led to the suppression of ETV2's transcriptional activity. Importantly, the inhibitory effect of BCL6B overexpression on EC differentiation from hiPSCs could be rescued by ETV2 overexpression. Conclusions BCL6B inhibits EC differentiation and hinders VO development by repressing the transcriptional activity of ETV2.

Abstract Background Early-life cardiovascular risk factors (CVRFs) are known to be associated with target organ damage during adolescence and premature cardiovascular morbidity and mortality during adulthood. However, contemporary data describing whether the prevalence of CVRFs and treatment and control rates have changed are limited. This study aimed to examine the temporal trends in the prevalence, treatment, and control of CVRFs among US adolescents over the past 2 decades. Methods This is a serial cross-sectional study using data from nine National Health and Nutrition Examination Survey cycles (January 2001—March 2020). US adolescents (aged 12 to 19 years) with information regarding CVRFs (including hypertension, elevated blood pressure [BP], diabetes, prediabetes, hyperlipidemia, obesity, overweight, cigarette use, inactive physical activity, and poor diet quality) were included. Age-adjusted trends in CVRF prevalence, treatment, and control were examined. Joinpoint regression analysis was performed to estimate changes in the prevalence, treatment, and control over time. The variation by sociodemographic characteristics were also described. Results A total of 15,155 US adolescents aged 12 to 19 years (representing ≈ 32.4 million people) were included. From 2001 to March 2020, there was an increase in the prevalence of prediabetes (from 12.5% [95% confidence interval (CI), 10.2%-14.9%] to 37.6% [95% CI, 29.1%-46.2%]) and overweight/obesity (from 21.1% [95% CI, 19.3%-22.8%] to 24.8% [95% CI, 21.4%-28.2%]; from 16.0% [95% CI, 14.1%-17.9%] to 20.3% [95% CI, 17.9%-22.7%]; respectively), no improvement in the prevalence of elevated BP (from 10.4% [95% CI, 8.9%-11.8%] to 11.0% [95% CI, 8.7%-13.4%]), diabetes (from 0.7% [95% CI, 0.2%-1.2%] to 1.2% [95% CI, 0.3%-2.2%]), and poor diet quality (from 76.1% [95% CI, 74.0%-78.2%] to 71.7% [95% CI, 68.5%-74.9%]), and a decrease in the prevalence of hypertension (from 8.1% [95% CI, 6.9%-9.4%] to 5.5% [95% CI, 3.7%-7.3%]), hyperlipidemia (from 34.2% [95% CI, 30.9%-37.5%] to 22.8% [95% CI, 18.7%-26.8%]), cigarette use (from 18.0% [95% CI, 15.7%-20.3%] to 3.5% [95% CI, 2.0%-5.0%]), and inactive physical activity (from 83.0% [95% CI, 80.7%-85.3%] to 9.5% [95% CI, 4.2%-14.8%]). Sex and race/ethnicity affected the evolution of CVRF prevalence differently. Whilst treatment rates for hypertension and diabetes did not improve significantly (from 9.6% [95% CI, 3.5%-15.8%] to 6.0% [95% CI, 1.4%-10.6%]; from 51.0% [95% CI, 23.3%-78.7%] to 26.5% [95% CI, 0.0%-54.7%]; respectively), BP control was relatively stable (from 75.7% [95% CI, 56.8%-94.7%] to 73.5% [95% CI, 40.3%-100.0%]), while glycemic control improved to a certain extent, although it remained suboptimal (from 11.8% [95% CI, 0.0%-31.5%] to 62.7% [95% CI, 62.7%-62.7%]). Conclusions From 2001 to March 2020, although prediabetes and overweight/obesity increased, hypertension, hyperlipidemia, cigarette use, and inactive physical activity decreased among US adolescents aged 12 to 19 years, whereas elevated BP, diabetes, and poor diet quality remained unchanged. There were disparities in CVRF prevalence and trends across sociodemographic subpopulations. While treatment and control rates for hypertension and diabetes plateaued, BP control were stable, and improved glycemic control was observed.

Oxidative stress is vital in gastrointestinal diseases, but how lactic acid bacteria protect human gastric adenocarcinoma cells (AGS) is unclear. Here, we aimed to investigate Lactiplantibacillus plantarum ZJ316 (L. plantarum ZJ316) for its potential to alleviate oxidative stress in AGS cells and elucidate mechanisms involved. Treatment with L. plantarum ZJ316 and fermentation supernatant (ZJ316 FS) bolstered cell viability under hydrogen peroxide (H2O2)-induced oxidative stress, boosting antioxidant enzymes like superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) while reducing reactive oxygen species (ROS) and malondialdehyde (MDA). Oral probiotics also alleviated oxidative damage from D-galactose in mice. Additionally, L. plantarum ZJ316 and ZJ316 FS alleviated H2O2-induced inflammation and apoptosis by modulating the expression of inflammatory and apoptotic factors. However, the protective effect was hindered when pretreated with the Nrf2 inhibitor ML385. These findings suggest that L. plantarum ZJ316 and fermentation supernatant alleviate oxidative damage by activating the Nrf2/HO-1 pathway, showing promise in development of antioxidant functional foods.

Waterbirds are often used as indicators of wetland biodiversity and ecosystem health due to their sensitivity to environmental changes. However, most studies have focused on long-term variations of waterbird communities, while the intra-annual changes have rarely been investigated. Here, we analyzed the seasonal dynamics of compositions and the intra-annual variations of species richness and abundance of waterbird communities among the nine major river basins of China, and focused on the effects of different residential types and taxonomic groups on the diversity variations. In most of the nine basins, the waterbird communities in spring and autumn showed high similarity, while those in summer and winter were quite different. Such a seasonal cycle of species composition was caused by the seasonal migration of waterbirds. The season with higher species richness shifted from summer to winter as the latitude of the basin decreased within China, but almost all basins had the lowest community abundance in summer. This was because the variation of richness was directly influenced by the variation in species composition, but the variation of abundance was more influenced by the population size of different waterbird assemblages. Our results emphasized the importance of seasonal dynamics of waterbird communities to the understanding of their migration patterns, and highlighted the impact of different waterbird assemblages on intra-annual community variations. Additionally, we also noted the potential effects of population size and behaviors at different parts of the waterbird life circle on the observations of them. The information gathered in this study will provide guidance for the conservation of waterbird species and their habitats.

ABSTRACT Backgroud According to the 2020 statistics from the World Health Organization’s International Agency for Research on Cancer (IARC), it is projected that there will be over 1 million new cases of gastric cancer (GC) patients worldwide in 2020, resulting in approximately 770 000 deaths. Gastric cancer ranks fifth in terms of incidence rate and forth in death rate among malignant tumors. Despite advancements in early diagnostic techniques, the incidence of GC has exhibited a marginal decline; nevertheless, the mortality rate remains elevated for advanced inoperable patients with no currently available efficacious treatment options. Recent Finding Chinese medicine (CM) has emerged as an efficacious treatment for GC, gradually gaining acceptance and widespread usage in China. It exhibits distinctive advantages in the prevention and treatment of metastasis. CM and natural medicine possess the ability to elicit antitumor effects by augmenting immune cell population, enhancing immune cell activity, and improving the tumor immune microenvironment. CMs and natural remedies encompass a diverse range of types, characterized by multiple targets, pathways, and extensive pharmacological effects. Consequently, they have become a prominent research area among oncologists worldwide. Numerous studies have demonstrated that CM and natural medicine can directly or indirectly enhance innate immune system components (including macrophages, natural killer cells, and myeloid suppressor cells), adaptive immune system elements (such as T lymphocytes and regulatory T cells), relevant cytokines (e.g., IL‐2, IL‐4, IL‐10, TNF‐α), and PD‐1/PD‐L1 axis regulation, thereby bolstering the cytotoxicity of immune cells against tumor cells. Conclusions This ultimately leads to an improved tumor immune microenvironment facilitating superior antitumor efficacy. This paper critically examines the role of CM and natural medicine in regulating immunotherapy for GC, aiming to establish a new theoretical framework for the clinical treatment and prevention of gastric cancer within the realm of CM.

Abstract Objectives The purpose of our study is to further understanding of the depression symptoms of HIV/AIDS patients in Guilin, Guangxi via exploring whether there is a mediating effect of sleep quality on medical-social support and depression symptoms and therefore provide a theoretical basis for application of medical-social support to alleviate depression symptoms of HIV/AIDS patients. Methods A convenience sampling method was used to select 200 HIV/AIDS patients for the study. Depression symptoms, sleep quality, and medical-social support of the study participants were investigated using The Center for Epidemiological Studies Depression Scale (CES-D), The Pittsburg Sleep Quality Index (PSQI), and The Medical Outcomes Study Social Support Survey (MOS-SSS), respectively. Predictors of depression symptoms were explored by multiple linear regression, and Pearson correlation was used to analyze the relationship between sleep quality, medical-social support, and depression symptoms. Mediating effect analysis was performed by nonparametric Bootstrap test. Results In this study, the incidence of depression symptoms was 54.4%. Multiple linear regression analysis showed that leanness (β = 0.161, P = 0.008), obesity (β = 0.186, P = 0.002), sleep quality score > 7 (β = 0.331, P 56 (β = -0.247, P

Abstract Chemotherapy is a commonly effective treatment for most types of cancer. However, many patients experience a relapse due to minimal residual disease (MRD) after chemotherapy. Previous studies have analyzed the changes induced by chemotherapy for specific types of cancer, but our study is the first to comprehensively analyze MRD across various types of cancer. We included both bulk and single-cell RNA sequencing datasets. We compared the expression of the entire genome and calculated scores for canonical pathway signatures and immune infiltrates before and after chemotherapy across different types of cancer. Our findings revealed that DUSP1 was the most significantly and widely enriched gene in pan-cancer MRD. DUSP1 was found to be essential for MRD formation and played a role in T cell-fibroblast communications and the cytotoxic function of CD4 + T cells. Overall, our analysis provides a comprehensive understanding of the changes caused by chemotherapy and identifies potential targets for preventing and eliminating MRD, which could lead to long-term survival benefits for patients.

In the cockpit, minimising the pilots' thermal discomfort due to solar exposure while ensuring clear visibility is essential. This study numerically examined the solar radiation effect on thermal fields of an Airbus A320 cockpit and assessed global and local thermal comfort of three aircrews using the Fanger model and the Equivalent Homogeneous Temperature (EHT) model. The productivity of aircrews based on thermal comfort was further estimated. A total of 27 cases, encompassing a combination of environmental and HVAC parameters were performed. This dataset was used for data analysis, employing an explainable machine, XGBoost, to highlight the significance of each variable on the pilot's thermal satisfaction. Outcomes proved that solar radiation penetrating the cockpit domain facilitated a non-homogeneous temperature distribution and thermal stratification. With strong solar exposure, it was recommended to set cockpit's maximum supply temperature smaller than 19[Formula: see text]C, maintaining RH between 10–20% for appropriate global thermal environment. Aircrew productivity loss was estimated to decline by 2.7% to 5.6% due to solar intensity variation, with pilot being the most affected. Without solar radiation, the local comfort of lower body segments was compromised. Rising solar radiation resulted in significant EHT gradient changes in the upper torso compared to the lower body, highlighting the predominance of radiative heat transfer at the upper level. Analysis via XGBoost revealed that mean radiant temperature had the most substantial impact on thermal satisfaction in the cockpit, underscoring the efficiency of optimising cockpit materials for better absorption and reflection of radiative heat for enhanced thermal environment control.

ObjectiveTo evaluate the effect of comfort nursing on postoperative nausea and vomiting in patients with idiopathic scoliosis undergoing posterior correction surgery.Methods92 patients with idiopathic scoliosis were taken as the subjects and segmented into a control group and an experimental group (n = 46/each group). The former received routine care, while the latter one performed comfortable care. The observation period is 48 h after surgery. Record and compare the incidence, grade, frequency, and pain level of nausea and vomiting in both groups, as well as postoperative physical signs and symptoms, drug use, and postoperative recovery. Investigating the patient's satisfaction with nursing care. The research data is analyzed using SPSS26.0 software. P

IntroductionMany probiotics have the ability to produce extracellular polysaccharides (EPS). EPS derived from these probiotics has been confirmed to regulate the host intestinal microecological balance and alleviate the symptoms of diseases caused by gastrointestinal microecological imbalance.ResultsLactic acid bacteria (LAB) strain with good exopolysaccharide (EPS) producing ability, namely, Lacticaseibacillus paracasei ZFM54 (L. paracasei ZFM54) was screened. The fermentation conditions of L. paracasei ZFM54 for EPS production were optimized. The EPS54 was characterized by chemical component and monosaccharide composition determination, UV, FT-IR and NMR spectra analysis. Cango red, SEM, AFM and XRD analysis were conducted to characterize the structure of EPS54. The EPS54 effectively reduced the colonization of Helicobacter pylori to AGS cells and recovered the cell morphology. EPS54 could also effectively alleviate the gastritis in the H. pylori-infected mice by down-regulating the mRNA expression levels of pro-inflammatory cytokines IL-6, IL-8, IL-1β and TNF-α and up-regulating the mRNA expression of inflammatory cytokine IL-10 in gastric cells. EPS54 was also found to be able to positively regulate the structure of gastric microbiota.ConclusionThe EPS 54 from L. paracasei ZFM54 can alleviate gastritis in H. pylori-infected mice by modulating the gastric microbiota.

As an important index reflecting the degree of soil salinization and alkalization, the proportion of saline-alkali patches (PSP) is beneficial for identifying the degree of saline-alkali land on a large scale with high spatial heterogeneity. However, determining the optimal scale for observing PSP remains inconclusive. In this article, we considered a typical area of saline-alkali land, which is located in Da'an City in Northeast China, as an example and selected nine sample areas from the sentinel-2A remote sensing images to calculate the salt index. According to the semivariogram function, we obtained the spatial autocorrelation range of the average radius of saline-alkali land. By combining the Nyquist-Shannon sampling theory, we determined the optimal scale for the remote sensing monitoring of saline-alkali land in Da'an City. The PSP index is calculated using this scale. The results were as follows: First, the optimal scale for the remote sensing monitoring of saline-alkali land in Da'an City is 41.2 m, and the calculated PSP index at this scale has the best correlation with the measured pH value data (R2 = 0.828). Second, Using the PSP index calculated at this scale, we divided the degree of saline-alkali land in Da'an City into three grades. Among them, the slightly, moderately, and severely saline-alkali lands cover areas of 90.52, 111.78, and 959.77 km2, respectively. In this article, we propose a new method for grading the degree of soil salinization and alkalization on land with high spatial heterogeneity, providing technical support for the utilization of saline-alkali land.

Colorectal cancer remains a leading cause of cancer-related deaths worldwide, with early detection and removal of polyps being critical in preventing disease progression. Automated polyp segmentation, particularly in colonoscopy images, is a challenging task due to the variability in polyp appearance and the low contrast between polyps and surrounding tissues. In this work, we propose an edge-enhanced network (EENet) designed to address these challenges by integrating two novel modules: the covariance edge-enhanced attention (CEEA) and cross-scale edge enhancement (CSEE) modules. The CEEA module leverages covariance-based attention to enhance boundary detection, while the CSEE module bridges multi-scale features to preserve fine-grained edge details. To further improve the accuracy of polyp segmentation, we introduce a hybrid loss function that combines cross-entropy loss with edge-aware loss. Extensive experiments show that the EENet achieves a Dice score of 0.9208 and an IoU of 0.8664 on the Kvasir-SEG dataset, surpassing state-of-the-art models such as Polyp-PVT and PraNet. Furthermore, it records a Dice score of 0.9316 and an IoU of 0.8817 on the CVC-ClinicDB dataset, demonstrating its strong potential for clinical application in polyp segmentation. Ablation studies further validate the contribution of the CEEA and CSEE modules.

The maize Snf2 gene family plays a crucial role in chromatin remodeling and response to environmental stresses. In this study, we identified and analyzed 35 members of the maize Snf2 gene family (ZmCHR1 to ZmCHR35) using the Ensembl Plants database. Each protein contained conserved SNF2-N and Helicase-C domains. Phylogenetic analysis revealed six groups among the Snf2 proteins, with an uneven distribution across subfamilies. Physicochemical analysis indicated that the Snf2 proteins are hydrophilic, with varied amino acid lengths, isoelectric points, and molecular weights, and are predominantly localized in the nucleus. Chromosomal mapping showed that these genes are distributed across all ten maize chromosomes. Gene structure analysis revealed diverse exon–intron arrangements, while motif analysis identified 20 conserved motifs. Collinearity analysis highlighted gene duplication events, suggesting purifying selection. Cis-regulatory element analysis suggested involvement in abiotic and biotic stress responses. Expression analysis indicated tissue-specific expression patterns and differential expression under various stress conditions. Specifically, qRT-PCR validation under drought stress showed that certain Snf2 genes were upregulated at 12 h and downregulated at 24 h, revealing potential roles in drought tolerance. These findings provide a foundation for further exploration of the functional roles of the maize Snf2 gene family in development and stress responses.

ABSTRACT: The pathogenesis of inflammatory bowel disease may be related to local inflammatory damage and disturbances in intestinal microecology. Probiotic therapy is a safe and effective therapeutic approach. Considering that fermented milk is accepted and enjoyed by many people as a daily dietary intervention strategy, its potential to alleviate dextran sulfate sodium (DSS)–induced chronic colitis in mice needs to be explored. In this study, we evaluated the therapeutic effects of Lactiplantibacillus plantarum ZJ316–fermented milk by establishing a mouse model of DSS-induced chronic colitis. The results showed that the disease severity and colonic lesions of inflammatory bowel disease were effectively alleviated by ingestion of fermented milk. At the same time, the expression of proinflammatory cytokines (TNF-α, IL-1β, and IL-6) effectively decreased, and the expression of antiinflammatory cytokines (IL-10) increased. Results based on 16S rRNA gene sequencing indicated that the structure and diversity of intestinal microorganisms changed markedly by intake of L. plantarum ZJ316–fermented milk, and fermented milk reduced the abundance of harmful bacteria (Helicobacter) while promoting the growth of beneficial bacteria (Faecalibacterium, Lactiplantibacillus, and Bifidobacterium). Additionally, the levels of short-chain fatty acids (acetic acid, propionic acid, butyric acid, pentanoic acid, and isobutyric acid) were also increased. In conclusion, the intake of L. plantarum ZJ316–fermented milk can alleviate chronic colitis by suppressing the inflammatory response and regulating intestinal microbiota.

Abstract Background This study aims to investigate the relationship between different dietary patterns and non-alcoholic fatty liver disease (NAFLD). Methods Residents over 30 years old in the ecological longevity cohort in Gongcheng Yao Autonomous County, Guangxi Province were the research objects selected from 2018 to 2019. Physical examination, baseline population survey, and food frequency questionnaire (FFQ) survey were conducted. Dietary patterns were analyzed by factor analysis. Influencing factors of NAFLD were analyzed by multiple logistic regression. Results NAFLD was diagnosed in 241 of 2664 participants based on ultrasonography, and the detection rate was 9.0%. Factor analysis yielded a total of three dietary patterns, namely, traditional Chinese, Western, and cereal-potato dietary patterns. Results of multivariate logistic regression analysis showed that after adjusting for confounding factors, participants in the highest quartile of the Western dietary pattern exhibited a higher prevalence of NAFLD (OR = 2.799; 95% CI: 1.620–4.837; p

Maize, a vital cereal in global agriculture, faces significant yield challenges due to drought exacerbated by climate change. This study explores the genetic and molecular bases of drought resilience in maize, focusing on the EPF/EPFL gene family known for its role in stomatal regulation. Through a genome-wide analysis across seven grass species, we identified and characterized 16 ZmEPF/EPFL genes in maize. Focusing on their gene structure, expression patterns, and evolutionary relationships. The study integrated genome-wide searches, phylogenetic analysis, gene expression profiling under drought and other abiotic stresses, and qRT-PCR validation to elucidate the functional roles of these genes in drought response. Our results demonstrate that specific ZmEPF/EPFL genes are differentially expressed under varying drought conditions, suggesting their involvement in the plant’s adaptive response to water scarcity. Furthermore, interaction analyses reveal that these genes are linked to key processes such as stomatal development and oxidative stress management. This study provides a comprehensive overview of the ZmEPF/EPFL gene family’s contribution to stomatal development and drought tolerance, offering insights that could guide future breeding strategies for drought-resistant maize varieties.

Abstract Interest in macrocycles as potential therapeutic agents has increased rapidly. Macrocyclization of bioactive acyclic molecules provides a potential avenue to yield novel chemical scaffolds, which can contribute to the improvement of the biological activity and physicochemical properties of these molecules. In this study, we propose a computational macrocyclization method based on Transformer architecture (which we name Macformer). Leveraging deep learning, Macformer explores the vast chemical space of macrocyclic analogues of a given acyclic molecule by adding diverse linkers compatible with the acyclic molecule. Macformer can efficiently learn the implicit relationships between acyclic and macrocyclic structures represented as SMILES strings and generate plenty of macrocycles with chemical diversity and structural novelty. In data augmentation scenarios using both internal ChEMBL and external ZINC test datasets, Macformer display excellent performance and generalisability. We showcase the utility of Macformer when combined with molecular docking simulations and wet lab based experimental validation, by applying it to the prospective design of macrocyclic JAK2 inhibitors.

Extracellular vesicles (EVs) derived from mesenchymal stem cells (MSCs) have emerged as a new mode of intercellular crosstalk and are responsible for many of the therapeutic effects of MSCs. To promote the application of MSC-EVs, recent studies have focused on the manipulation of MSCs to improve the production of EVs and EV-mediated activities. The current paper details an optimization method using non-invasive low-intensity pulsed ultrasound (LIPUS) as the stimulation for improving oral MSC-EV production and effectiveness. Stem cells from apical papilla (SCAP), a type of oral mesenchymal stem cell, displayed intensity-dependent pro-osteogenic and anti-inflammatory responses to LIPUS without significant cytotoxicity or apoptosis. The stimuli increased the secretion of EVs by promoting the expression of neutral sphingomyelinases in SCAP. In addition, EVs from LIPUS-induced SCAP exhibited stronger efficacy in promoting the osteogenic differentiation and anti-inflammation of periodontal ligament cells in vitro and alleviating oral inflammatory bone loss in vivo. In addition, LIPUS stimulation affected the physical characteristics and miRNA cargo of SCAP-EVs. Further investigations indicated that miR-935 is an important mediator of the pro-osteogenic and anti-inflammatory capabilities of LIPUS-induced SCAP-EVs. Taken together, these findings demonstrate that LIPUS is a simple and effective physical method to optimize SCAP-EV production and efficacy.

Abstract Background Computational drug repurposing is crucial for identifying candidate therapeutic medications to address the urgent need for developing treatments for newly emerging infectious diseases. The recent COVID-19 pandemic has taught us the importance of rapidly discovering candidate drugs and providing them to medical and pharmaceutical experts for further investigation. Network-based approaches can provide repurposable drugs quickly by leveraging comprehensive relationships among biological components. However, in a case of newly emerging disease, applying a repurposing methods with only pre-existing knowledge networks may prove inadequate due to the insufficiency of information flow caused by the novel nature of the disease. Methods We proposed a network-based complementary linkage method for drug repurposing to solve the lack of incoming new disease-specific information in knowledge networks. We simulate our method under the controlled repurposing scenario that we faced in the early stage of the COVID-19 pandemic. First, the disease-gene-drug multi-layered network was constructed as the backbone network by fusing comprehensive knowledge database. Then, complementary information for COVID-19, containing data on 18 comorbid diseases and 17 relevant proteins, was collected from publications or preprint servers as of May 2020. We estimated connections between the novel COVID-19 node and the backbone network to construct a complemented network. Network-based drug scoring for COVID-19 was performed by applying graph-based semi-supervised learning, and the resulting scores were used to validate prioritized drugs for population-scale electronic health records-based medication analyses. Results The backbone networks consisted of 591 diseases, 26,681 proteins, and 2,173 drug nodes based on pre-pandemic knowledge. After incorporating the 35 entities comprised of complemented information into the backbone network, drug scoring screened top 30 potential repurposable drugs for COVID-19. The prioritized drugs were subsequently analyzed in electronic health records obtained from patients in the Penn Medicine COVID-19 Registry as of October 2021 and 8 of these were found to be statistically associated with a COVID-19 phenotype. Conclusion We found that 8 of the 30 drugs identified by graph-based scoring on complemented networks as potential candidates for COVID-19 repurposing were additionally supported by real-world patient data in follow-up analyses. These results show that our network-based complementary linkage method and drug scoring algorithm are promising strategies for identifying candidate repurposable drugs when new emerging disease outbreaks.

To ensure that grid-connected currents are of high quality, it is crucial to optimize the dynamic performance of grid-connected inverters and their control. This study suggests using a combination of reduced-order linear active disturbance rejection control (LADRC) and a Proportional-Integral (PI) controller. By applying this control strategy to a single-phase photovoltaic grid-connected system, the system's ability to suppress grid harmonics is significantly improved. The validity and effectiveness of this control approach have been confirmed through simulations and experiments. The results show that the LADRC-based control system is robust and capable of rejecting disturbances, resulting in a significant reduction in the Total Harmonic Distortion (THD) of grid-connected currents. Comparative analysis with traditional control methods demonstrates the superior performance of the proposed approach.

Allergic rhinitis (AR) is a common inflammation that affects many people globally. Quercetin has anti-allergic biological activity in AR. Here, we aimed to explore the effects of quercetin on type 1 helper T (Th1)/Th2 and regulatory T cells (Treg)/Th17 balance. We established an ovalbumin (OVA)-induced mouse model and orally administered 20, 35, and 50 mg/kg/day quercetin. The nasal symptoms of mice were observed. The immunoglobulin levels, Treg/Th17-related factors, and pro-inflammatory factors were examined by ELISA. The differentiated inflammation cells were visualized using the diff-quick staining assay. The nasal histopathology was evaluated using H&E, periodic acid Schiff (PAS), and Giemsa staining assay. The results showed that quercetin attenuated OVA-induced rubbing and sneezing. Quercetin reduced IgE, IgG1, histamine, and increased IgG2 in serum. The number of differentiated inflammation cells and goblet cells in tissues that elevated by OVA was reduced by quercetin. Moreover, OVA increased the Treg cell percentage, the levels of IL-17, TGF-β, IL-6, TNF-α, and decreased Th17 cell percentage, IL-10 and FOXP3 levels, while quercetin abrogated their levels induced by OVA. Additionally, quercetin inactivated the NF-κB pathway. Taken together, quercetin attenuated AR symptoms by balancing the Th1/Th2, Treg/Th17 ratios, and inactivating the NF-κB pathway. The results suggested that quercetin may use for AR treatment.

Abstract Retrosynthesis is a procedure where a target molecule is transformed into potential reactants and thus the synthesis routes can be identified. Recently, computational approaches have been developed to accelerate the design of synthesis routes. In this paper,we develop a generative framework G 2 Retro for one-step retrosynthesis prediction. G 2 Retro imitates the reversed logic of synthetic reactions. It first predicts the reaction centers in the target molecules (products), identifies the synthons needed to assemble the products, and transforms these synthons into reactants. G 2 Retro defines a comprehensive set of reaction center types, and learns from the molecular graphs of the products to predict potential reaction centers. To complete synthons into reactants, G 2 Retro considers all the involved synthon structures and the product structures to identify the optimal completion paths, and accordingly attaches small substructures sequentially to the synthons. Here we show that G 2 Retro is able to better predict the reactants for given products in the benchmark dataset than the state-of-the-art methods.

It is crucial to discover novel antimicrobial drugs to combat resistance. This study investigated the antibacterial properties of halicin (SU3327), an AI-identified anti-diabetic drug, against 13 kinds of common clinical pathogens of animal origin, including multidrug-resistant strains. Employing minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assessments, halicin demonstrated a broad-spectrum antibacterial effect. Time-killing assays revealed its concentration-dependent bactericidal activity against Escherichia coli ATCC 25922 (E. coli ATCC 25922), Staphylococcus aureus ATCC 29213 (S. aureus ATCC 29213), and Actinobacillus pleuropneumoniae S6 (APP S6) after 4 h of treatment at concentrations above the MIC. Halicin exhibited longer post-antibiotic effects (PAEs) and sub-MIC effects (PA-SMEs) for E. coli 25922, S. aureus 29213, and APP S6 compared to ceftiofur and ciprofloxacin, the commonly used veterinary antimicrobial agents, indicating sustained antibacterial action. Additionally, the results of consecutive passaging experiments over 40 d at sub-inhibitory concentrations showed that bacteria exhibited difficulty in developing resistance to halicin. Toxicology studies confirmed that halicin exhibited low acute toxicity, being non-mutagenic, non-reproductive-toxic, and non-genotoxic. Blood biochemical results suggested that halicin has no significant impact on hematological parameters, liver function, and kidney function. Furthermore, halicin effectively treated respiratory A. pleuropneumoniae infections in murine models. These results underscore the potential of halicin as a new antibacterial agent with applications against clinically relevant pathogens in veterinary medicine.

Extreme drought weather has occurred frequently in recent years, resulting in serious yield loss in tea plantations. The study of drought in tea plantations is becoming more and more intensive, but there are fewer studies on drought-resistant measures applied in actual production. Therefore, in this study, we investigated the effect of exogenous tea polyphenols on the drought resistance of tea plant by pouring 100 mg·L−1 of exogenous tea polyphenols into the root under drought. The exogenous tea polyphenols were able to promote the closure of stomata and reduce water loss from leaves under drought stress. Drought-induced malondialdehyde (MDA) accumulation in tea leaves and roots was also significantly reduced by exogenous tea polyphenols. Combined transcriptomic and metabolomic analyses showed that exogenous tea polyphenols regulated the abnormal responses of photosynthetic and energy metabolism in leaves under drought conditions and alleviated sphingolipid metabolism, arginine metabolism, and glutathione metabolism in the root system, which enhanced the drought resistance of tea seedlings. Exogenous tea polyphenols induced jasmonic acid–isoleucine (JA-ILE) accumulation in the root system, and the jasmonic acid–isoleucine synthetase gene (TEA028623), jasmonic acid ZIM structural domain proteins (JAMs) synthesis genes (novel.22237, TEA001821), and the transcription factor MYC2 (TEA014288, TEA005840) were significantly up-regulated. Meanwhile, the flavonoid metabolic flow was significantly altered in the root; for example, the content of EGCG, ECG, and EGC was significantly increased. Thus, exogenous tea polyphenols enhance the drought resistance of tea plants through multiple pathways.

Armadillo (ARM) was a gene family important to plants, with crucial roles in regulating plant growth, development, and stress responses. However, the properties and functions of ARM family members in maize had received limited attention. Therefore, this study employed bioinformatics methods to analyze the structure and evolution of ARM-repeat protein family members in maize. The maize (Zea mays L.) genome contains 56 ARM genes distributed over 10 chromosomes, and collinearity analysis indicated 12 pairs of linkage between them. Analysis of the physicochemical properties of ARM proteins showed that most of these proteins were acidic and hydrophilic. According to the number and evolutionary analysis of the ARM genes, the ARM genes in maize can be divided into eight subgroups, and the gene structure and conserved motifs showed similar compositions in each group. The findings shed light on the significant roles of 56 ZmARM domain genes in development and abiotic stress, particularly drought stress. RNA-Seq and qRT-PCR analysis revealed that drought stress exerts an influence on specific members of the ZmARM family, such as ZmARM4, ZmARM12, ZmARM34 and ZmARM36. The comprehensive profiling of these genes in the whole genome, combined with expression analysis, establishes a foundation for further exploration of plant gene function in the context of abiotic stress and reproductive development.

Background: Di(2-ethylhexyl) phthalate (DEHP) a parent compound that is metabolized into 4 phthalate metabolites, which correlate to adverse cardio-metabolic risk factors. This study aimed to explore the links between urinary DEHP metabolites and serum lipids in the U.S. general adult population. Methods: In this cross-sectional study, data on 11 urinary phthalate metabolites from the 2005–2018 National Health and Nutrition Examination Surveys (NHANES) were analyzed. Multivariate linear regression and restricted cubic spline (RCS) were used to examine the relationship between phthalate metabolites [specific DEHPs: mono-(2-ethyl-5-carboxy-pentyl) phthalate (MECPP), mono-(2-ethyl-5-hydroxy-hexyl) phthalate (MEHHP), mono-(2-ethylhexyl) phthalate (MEHP), mono-(2-ethyl-5-oxo-hexyl) phthalate (MEOHP)] and serum lipids (triglycerides [TG], total cholesterol [TC], low-density lipoprotein cholesterol [LDL-C], and high-density lipoprotein cholesterol [HDL-C]). To identify mixed exposure effects of phthalate metabolites, quantile g-computation (QG-C) and weighted quantile sum (WQS) regression were employed for the lipid profiles. Results: A total of 9141 adults were included in the analysis. MECPP, MEHHP, MEHP, and MEOHP in the highest quartile had a negative relationship with HDL-C compared to the lowest quartile (All P for trend 0.05). The WQS index of DEHP metabolites showed independent correlations with HDL-C [β = −0.26, 95%CI (−0.43, −0.09), P = 0.002], TC [β = 0.55, 95%CI (0.13, 0.98), P = 0.011], and TG [β = 2.40, 95%CI (0.85, 3.96), P = 0.003]. Conclusion: Our study suggests that environmental DEHP exposure may affect serum HDL-C and TG levels in the general adult population. Further research is warranted to confirm these findings and illuminate the underlying mechanisms of DEHP exposure on lipids.

Summary: The majority of activated ovarian follicles undergo atresia during reproductive life in mammals, and only a small number of follicles are ovulated. Though hormone treatment has been widely used to promote folliculogenesis, the molecular mechanism behind follicle selection and atresia remains under debate due to inconsistency among investigation models. Using a high-throughput molecular pathology strategy, we depicted a transcriptional atlas of mouse follicular granulosa cells (GCs) under physiological condition and obtained molecular signatures in healthy and atresia GCs during development. Functional results revealed hypoxia-inducible factor 1 (HIF1) as a major effector downstream of follicle-stimulating hormone (FSH), and HIF1 activation is essential for follicle growth. Energy shortage leads to prevalent AMP-activated protein kinase (AMPK) activation and drives follicular atresia. FSHR-mTOR-HIF1 signaling helps follicles escape from the atresia fate, while energy stress persists. Our work provides a comprehensive understanding of the molecular network behind follicle selection and atresia under physiological condition.

Electromagnetic tomography (EMT), also known as magnetic inductance tomography (MIT) is a tomographic modality widely employed in process industry and biomedical applications. In particular, this technique plays an important role in imaging metallic objects since it can produce conductivity and permeability distributions in the region of interest. An EMT system consists of a coil array, a data acquisition system, and an imaging reconstruction computer. Coils are used to generate electromagnetic field which interacts with the objects under investigation and measure the induced voltages. Conventionally, coils with sufficient inductance coupling (considerable number of turns or dimensions) are used to achieve high sensitivity and good SNR performance. However, this poses limitations for some applications, such as high-temperature applications and small-scale facilities. In high-temperature applications such as in steel or copper production processes, coils of the large number of turns are more likely to be damaged due to the breakdown of insulating materials between the turns, resulting in measuring errors. Besides, EMT applied in small-scale facility requires sensors with reduced dimensions, which results in weak magnetic coupling and lower SNR. In order to address these issues, this article proposes a method to transform the impedance and hence increase the sensor signal level through designing boosting transformers. Simulation and experimental results suggest that this increases the system SNR and image stability.

Water stress is a major factor limiting corn production in the semi-arid and semi-humid regions of the world. Well-scheduled irrigation is necessary to increase seed yield and ensure yield stability in these regions. A reasonable and intelligent irrigation system is generally based on the measurement of soil water content or the monitoring of corn water demand. Therefore, it is vital to be able to quickly and accurately determine the optimal threshold of the physiological parameters of corn.In this paper, in order to find the optimal threshold of the physiological parameters of corn, experiments in the open fields were conducted from February to June by measuring the corn growth under different degrees of water stress using remote sensing instruments. In this experiment, sweet corn 18# was chosen as the experimental subject, and several parameters of remote sensing spectral index such as leaf water potentia, Normalized difference vegetation index (NDVI), photochemical vegetation index (PRI), and PSII light quantum yield (QY) were measured at the same time every day-along with the varying moisture status—for the duration of the experiment. For this experiment, it was very important to set the varying moisture statuses as the moisture controlling standard. Leaf water potential and QY were selected as indexes to check the different moisture statuses. The QY proved to be sensitive to the water stress of corn and was chosen as the indicator. Furthermore, the effects on the corn under differing levels of water stress were explored by analyzing the variation trend of different remote sensing spectral indices. The main results and conclusions are as follows:(1) Differing degrees of water stress at the jointing stage of corn growth will cause the inhibition (in varying degrees) of leaf water potential, QY, NDVI, and PRI; and will also inhibit the processes of transpiration and photosynthesis. (2) After halting the water stress, with the different levels of water replenishment, the leaf water potential, QY, NDVI, and PRI will display the characteristics of the compensation phenomena. The compensation levels will depend on the degree of water stress. When the water stress is mild, all of the leaf water potential indexes, QY, NDVI, PRI will recover to normal levels or even succeed normal levels in a very short period of time-known as the super compensation effect. Meanwhile, for moderate levels of water stress, the compensation phenomena is also present; however, the replenishment of water cannot reach normal levels. Further, the water replenishment effect does not appear under conditions of severe water stress. This indicates that it is beneficial in maize growth for the corn to be under conditions of mild water stress.(3) Lastly, from the significance of the QY, water potential, PRI, and NDVI to water stress, it is apparent that the QY is the most reliable. Therefore, QY is the most reasonable choice to guide the water-saving irrigation in irrigated farming areas.

Abstract Background Exposure to heavy metals in the environment is widespread, while the relationship between combined exposure to heavy metals and dyslipidemia is unclear. Methods A cross-sectional study was performed, and 3544 participants aged 30 years or older were included in the analyses. Heavy metal concentrations in plasma were based on inductively coupled plasma‒mass spectrometry. The relationship between heavy metals and dyslipidemia was estimated by logistic regression. BKMR was used to evaluate metal mixtures and their potential interactions. Results In logistic regression analysis, participants in the fourth quartile of Fe and Zn (Fe > 1352.38 µg/L; Zn > 4401.42 µg/L) had a relatively higher risk of dyslipidemia (Fe, OR = 1.13, 95% CI: 0.92,1.38; Zn, OR = 1.30, 95% CI: 1.03,1.64). After sex stratification, females in the third quartile of plasma Zn (1062.05-4401.42 µg/L) had a higher relative risk of dyslipidemia (OR = 1.75, 95% CI: 1.28, 2.38). In BKMR analysis, metal mixtures were negatively associated with dyslipidemia in females when all metal concentrations were above the 50th percentile. In the total population (estimated from 0.030 to 0.031), As was positively associated with dyslipidemia when other metals were controlled at the 25th, 50th, or 75th percentile, respectively, and As was below the 75th percentile. In females (estimated from − 0.037 to -0.031), Zn was negatively associated with dyslipidemia when it was above the 50th percentile. Conclusion This study indicated that As was positively associated with dyslipidemia and that Zn may be negatively associated with dyslipidemia in females. Combined metal exposure was negatively associated with dyslipidemia in females. Females with low plasma Zn levels are more likely to develop dyslipidemia and should receive more clinical attention in this population.

Abstract Background Kidney stones have become a worldwide public health problem. The purpose of this research is to study the relationship between plasma cadmium level and the prevalence of kidney stones in an adult population. Methods The data of this study were based on a current survey conducted from December 2018 to November 2019 in Gongcheng Yao Autonomous County, Guangxi, China. A total of 940 study subjects of the same sex and age (within 2 years of each other) according to 1:1 matching were selected for a case–control study. The diagnosis of kidney stones was based on the presence of strong light spots, patches, clusters, or bands within the renal sinus region, followed by an echo-free bundle of acoustic images. Plasma metal elements were determined by the metal plasma method. The relationship between plasma cadmium concentration and the prevalence of kidney stones was assessed using logistic regression and restricted cubic spline regression. Results The crude ratio for kidney stones in the highest quartile of plasma cadmium was 1.164 (95% CI, 1.121 to 2.324) compared with the lowest quartile. A positive correlation was found between the two (P for trend = 0.039). After adjusting for potential confounders, the ratio of plasma cadmium to kidney stones in the highest quartile was 1.606 (95% CI, 1.100 to 2.344) compared with the lowest quartile, and the findings remained unchanged. Conclusion The odds of kidney stones in adults increased with increasing plasma cadmium exposure, and high plasma cadmium may be a risk factor for kidney stones.

This longitudinal study used diet-wide association studies (DWAS) to investigate the association between diverse dietary food and nutrient intakes and the onset of type 2 diabetes mellitus (T2DM). Out of 502,505 participants from the UK Biobank, 119,040 with dietary data free of T2DM at the baseline were included, and 3241 developed T2DM during a median follow-up of 11.7 years. The DWAS analysis, which is based on Cox regression models, was used to analyse the associations between dietary food or nutrient intake factors and T2DM risk. The study found that 10 out of 225 dietary factors were significantly associated with the T2DM risk. Total alcohol (HR = 0.86, 0.85–0.92, p = 1.26 × 10−32), red wine (HR = 0.89, 0.88–0.94, p = 7.95 × 10−19), and fresh tomatoes (HR = 0.92, 0.89–0.94, p = 2.3 × 10−11) showed a negative association with T2DM risk, whereas sliced buttered bread exhibited a positive association. Additionally, 5 out of 21 nutrient intake variables revealed significant associations with the T2DM risk, with iron having the highest protective effect and starch as a risk factor. In conclusion, DWAS is an effective method for discovering novel associations when exploring numerous dietary variables simultaneously and could provide valuable insight into future dietary guidance for T2DM.

Semantic segmentation plays a pivotal role in the intelligent interpretation of remote sensing images (RSIs). However, conventional methods predominantly focus on learning representations within the spatial domain, often resulting in suboptimal discriminative capabilities. Given the intrinsic spectral characteristics of RSIs, it becomes imperative to enhance the discriminative potential of these representations by integrating spectral context alongside spatial information. In this paper, we introduce the spectrum-space collaborative network (SSCNet), which is designed to capture both spectral and spatial dependencies, thereby elevating the quality of semantic segmentation in RSIs. Our innovative approach features a joint spectral–spatial attention module (JSSA) that concurrently employs spectral attention (SpeA) and spatial attention (SpaA). Instead of feature-level aggregation, we propose the fusion of attention maps to gather spectral and spatial contexts from their respective branches. Within SpeA, we calculate the position-wise spectral similarity using the complex spectral Euclidean distance (CSED) of the real and imaginary components of projected feature maps in the frequency domain. To comprehensively calculate both spectral and spatial losses, we introduce edge loss, Dice loss, and cross-entropy loss, subsequently merging them with appropriate weighting. Extensive experiments on the ISPRS Potsdam and LoveDA datasets underscore SSCNet’s superior performance compared with several state-of-the-art methods. Furthermore, an ablation study confirms the efficacy of SpeA.

Abstract The insecticidal crystalline proteins (Crys) are a family of insect endotoxin functioning in crop protection. As insects keep evolving into tolerance to the existing Crys, it is necessary to discover new Cry proteins to overcome potential threatens. Crys possess three functional domains at their N-termini, and the most active region throughout evolution was found at the domain-III. We swapped domain-IIIs from various Cry proteins and generated seven chimeric proteins. All recombinants were expressed in Escherichia coli and their toxicity was assessed by dietary exposure assays. Three of the seven Crys exhibited a high toxicity to Asian corn borer over the controls. One of them, Cry1Ab-Gc, a chimeric Cry1Ab being replaced with the domain-III of Cry1Gc, showed the highest toxicity to rice stem borer when it was over-expressed in Oryza sativa. Furthermore, it was also transformed into maize, backcrossed into commercial maize inbred lines and then produced hybrid to evaluate their commercial value. Transgenic maize performed significant resistance to the Asian corn borer without affecting the yield. We further showed that this new protein did not have adverse effects on the environment. Our results indicated that domain III swapped of Crys could be used as an efficient method for developing new engineered insecticidal protein.

Abstract Background Influenza A virus infection due to drug resistance and side effects of the conventional antiviral drugs yet remains a serious public health threat for humans and animals. Forsythiaside A is an effective ingredient isolated from the Chinese herbal medicine forsythia. It has various pharmacological effects and has a good therapeutic effect against a variety of infectious diseases. This study aimed to further explore the immunological mechanism of Forsythiaside A in the treatment of influenza virus-infected mice and its effect on the Toll-like receptor 7 (TLR7) signaling pathway in the lungs of these mice. Methods C57/BL6J mice and TLR7−/− mice were infected with the FM1 strains (H1N1 and A/FM/1/4) of the Influenza A virus. Each group of experimental mice were divided into the mock, virus, oseltamivir, and Forsythiaside A groups. Weight change, lung index change, and the mRNA and protein expression levels of key factors in the TLR7 signaling pathway were detected. Flow cytometry was used to detect the changes in the Th1/Th2 and Th17/Treg ratios. Results After infection with the Influenza A virus, the weight loss of C57/BL6J mice treated with forsythoside A and oseltamivir decreased, and the pathological tissue sections showed that the inflammatory damage was reduced. The expression levels of the key factors, TLR7, myeloid differentiation factor 88(Myd88), and nuclear factor-kappa B (NF-κB) in the TLR7 signaling pathway were significantly reduced. Flow cytometry showed that Th1/Th2 and Th17/Treg ratios decreased after Forsythiaside A treatment. In the TLR7−/− mice, there was no significant change after Forsythiaside A treatment in the virus group. Conclusions Forsythiaside A affects the TLR7 signaling pathway in mouse lung immune cells and reduces the inflammatory response caused by the Influenza A virus FM1 strain in mouse lungs.

Changes in slope aspect have important effects on the C, N and P nutrient contents and stoichiometric characteristics of plants and soils. As an important forest type in the subtropical region, Pinus massoniana forests play an important role in the restoration and development of forest ecosystems. In this study, the effect of slope aspect on the C, N and P contents and stoichiometry of leaves and soils of four P. massoniana forest types (i.e., pure P. massoniana forest (PF), P. massoniana-Liquidambar formosana mixed forest (PLM), P. massoniana -Platycarya strobilacea mixed forest (PPM), and P. massoniana-Quercus acutissima mixed forest (PQM)) in north subtropical region of China were studied. The results showed that slope aspect had significant effects on soil C, N and P contents, leaf N content (LNC), soil C:P and N:P ratios, and leaf C:N and N:P ratios in four P. massoniana forests. SOC, STN and STP contents differed significantly on the two slopes, with the three mixed forests having higher contents on the sunny slope than on the shady slope. Among the four forest types, the SOC, STN and STP contents of PQM were the highest on both slopes, and their soil C:P and N:P ratios were all the highest on the sunny slope. The LNC and leaf N:P ratios were higher on shady slope than on sunny slope, while the leaf C:N ratio was higher on sunny slope than on shady slope. At the species level, leaf N content and N:P ratio in the three deciduous species were higher than in the evergreen species of P. massoniana, while leaf C content and C:N ratio were lower than in P. massoniana. The interaction between slope aspect and forest type caused a certain range of fluctuations in stoichiometry of the four forest types, but the overall ecological stoichiometry remained stable, and plant growth of the four forest types in the study area was limited by N. Slope-induced changes in soil nutrient content of the four P. massoniana forest types directly affect leaf C:N:P stoichiometry, and soil N and P contents are key factors affecting leaf stoichiometry, especially soil P content.

Summary: The coordination of chloroplast and nuclear genome status is critical for plant cell function. Here, we report that Arabidopsis CHLOROPLAST AND NUCLEUS DUAL-LOCALIZED PROTEIN 1 (CND1) maintains genome stability in the chloroplast and the nucleus. CND1 localizes to both compartments, and complete loss of CND1 results in embryo lethality. Partial loss of CND1 disturbs nuclear cell-cycle progression and photosynthetic activity. CND1 binds to nuclear pre-replication complexes and DNA replication origins and regulates nuclear genome stability. In chloroplasts, CND1 interacts with and facilitates binding of the regulator of chloroplast genome stability WHY1 to chloroplast DNA. The defects in nuclear cell-cycle progression and photosynthesis of cnd1 mutants are respectively rescued by compartment-restricted CND1 localization. Light promotes the association of CND1 with HSP90 and its import into chloroplasts. This study provides a paradigm of the convergence of genome status across organelles to coordinately regulate cell cycle to control plant growth and development.

Abstract Effective and successful clinical trials are essential in developing new drugs and advancing new treatments. However, clinical trials are very expensive and easy to fail. The high cost and low success rate of clinical trials motivate research on inferring knowledge from existing clinical trials in innovative ways for designing future clinical trials. In this manuscript, we present our efforts on constructing the first publicly available Clinical Trials Knowledge Graph, denoted as $$\mathop {\mathtt {CTKG}}\limits$$ CTKG . $$\mathop {\mathtt {CTKG}}\limits$$ CTKG includes nodes representing medical entities in clinical trials (e.g., studies, drugs and conditions), and edges representing the relations among these entities (e.g., drugs used in studies). Our embedding analysis demonstrates the potential utilities of $$\mathop {\mathtt {CTKG}}\limits$$ CTKG in various applications such as drug repurposing and similarity search, among others.

Plant factory is an important field of practice in smart agriculture which uses highly sophisticated equipment for precision regulation of the environment to ensure crop growth and development efficiently. Environmental factors, such as temperature and humidity, significantly impact crop production in a plant factory. Given the inherent complexities of dynamic models associated with plant factory environments, including strong coupling, strong nonlinearity and multi-disturbances, a nonlinear adaptive decoupling control approach utilizing a high-order neural network is proposed which consists of a linear decoupling controller, a nonlinear decoupling controller and a switching function. In this paper, the parameters of the controller depend on the generalized minimum variance control rate, and an adaptive algorithm is presented to deal with uncertainties in the system. In addition, a high-order neural network is utilized to estimate the unmolded nonlinear terms, consequently mitigating the impact of nonlinearity on the system. The simulation results show that the mean error and standard error of the traditional controller for temperature control are 0.3615 and 0.8425, respectively. In contrast, the proposed control strategy has made significant improvements in both indicators, with results of 0.1655 and 0.6665, respectively. For humidity control, the mean error and standard error of the traditional controller are 0.1475 and 0.441, respectively. In comparison, the proposed control strategy has greatly improved on both indicators, with results of 0.0221 and 0.1541, respectively. The above results indicate that even under complex conditions, the proposed control strategy is capable of enabling the system to quickly track set values and enhance control performance. Overall, precise temperature and humidity control in plant factories and smart agriculture can enhance production efficiency, product quality and resource utilization.

This paper investigates gauge invariance in a bulk massless q-form field on a p-brane with codimension two, utilizing a general Kaluza–Klein (KK) decomposition. The KK decomposition analysis reveals four distinct KK modes: the conventional q-form, two (q−1)-forms and one (q−2)-form. These diverse modes are essential for maintaining gauge invariance. We also find eight Schrödinger-like equations for the four modes due to the two extra dimensions, and their mass spectra are closely related. The KK decomposition process gives rise to four dualities on the p-brane, originating from the inherent Hodge duality present in the bulk. Notably, these dual symmetries play a significant role in maintaining the equivalence of bulk dual fields during dimensional reduction.

The central government of China encourages enthusiasm for biodiversity conservation by implementing a transfer payment policy targeted at Biodiversity National Key Ecological Functional Areas at the county scale. Biodiversity National Key Ecological Functional Areas are types of PAs that were designated by the State Council of China for the implementation of biodiversity conservation. However, regional comparative assessment results of biodiversity conservation effectiveness in different county-level administrative units are still lacking. In this study, we developed a reference condition index to represent the ecological background, and we then constructed a conservation effectiveness index to compare the conservation efforts among 131 counties in seven Biodiversity National Key Ecological Functional Areas. The results showed the following: (1) The biological background could be well reflected by the reference condition index. The Tropical Rainforest Ecological Function Area in Mountain Areas in the Middle of Hainan Island had the best biological background, while the Desert Ecological Function Area on the Northwest Qiangtang Plateau had the worst. (2) The biodiversity conservation effectiveness of the Desert Ecological Function Area on the Northwest Qiangtang Plateau was the best, and that of the Wetland Ecological Function Area of the Three River Plain was worst. (3) Among the 131 counties, Taibai County in the Biodiversity Ecological Function Area of Qinba Mountain performed best, while Fujin City in the Wetland Ecological Function Area of the Three River Plain performed worst. Our study could provide valuable insights for the transfer payment. Meanwhile, it can also supply a scientific reference for the management of Biodiversity National Key Ecological Functional Areas to enhance biodiversity.

With the fast urbanization, urban heat island (UHI) effect is becoming more and more pronounced. Identify and evaluate the temporal-spatial variations and the driving factors that are in urgent need to alleviate a series of problems caused by heat island. Changchun of Jilin province is located in northeast China, using multiperiod satellites images and other ancillary data to invert the surface temperature and acquire the surface land cover classification, then it analyzed the temporal-spatial variation of UHI effect and relation between urban developments. The temporal variations of UHI effects based on air temperature (AT) showed: the UHI was strong at night and weak in daytime; the UHI was strong in autumn and winter and weak in spring and summer; the UHI effect increased rapidly before 2015 and decreased after 2015. The spatial variations of UHI based on land surface temperature (LST) effected: The area of higher temperature zone increased, while the area of other areas declined. The strength order of the UHI effect for different land surface covering types was: building land> grassland> woodland>water area. This meant how to layout urban land use types were important, reasonable urban land planning was necessary for urban sustainable development. This study provided an important basis for counteracting the UHI effect and promoting the construction of an eco-city.

Autoimmune encephalitis associated with antibody against contactin-associated protein-like 2 (CASPR2) varies in its clinical presentation. The disease is difficult to distinguish from some other conditions without testing for anti-CASPR2 antibody in blood serum or cerebrospinal fluid. Cerebral lesions are typically detected by magnetic resonance imaging (MRI) in the medial temporal lobe or hippocampus. Here, we describe a patient with anti-CASPR2 antibody autoimmune encephalitis whose imaging manifestations mimicked infarction in the left frontal lobe. The 48-year-old man reported memory loss, convulsions, and disturbed consciousness one day after drinking wine. The right upper arm showed reduced autonomous movement after painful stimuli, and MRI showed abnormal hyperintensities in the left frontal lobe on T2 and fluid-attenuated inversion recovery sequences, restricted diffusion, and decreased cerebral blood flow, mimicking acute cerebral infarction. Contrast-enhanced T1-weighted MRI showed gyral enhancement involving the cortex and subcortical white matter. Computed tomography angiography did not identify culprit blood vessels. Symptoms did not improve with anti-platelet or lipid-lowering therapy. Screening for serum antibodies associated with autoimmune encephalitis detected antibody against CASPR2, and intravenous immunoglobulin therapy substantially improved symptoms. This case provides the first indication that anti-CASPR2 antibody-associated autoimmune encephalitis can manifest as involvement of the cortex and subcortical white matter in the frontal lobe based on MRI. It emphasizes the need for thorough investigation, including analysis of potential autoimmunity, of patients whose imaging findings mimic ischemic infarction.

IntroductionThyroid hormone receptor β (THR-β) plays a critical role in metabolism regulation and has become an attractive target for treating lipid metabolism disorders in recent years. Thus, in this study, we discovered CS271011, a novel THR-β agonist, and assessed the safety and efficiency of CS271011 compared to MGL-3196 in vitro and in vivo. MethodsWe conducted luciferase reporter gene assays to assess the activation of THR-β and α in vitro. C57BL/6J mice were fed a high-fat diet for 12 weeks, CS271011 was administered by gavage at the dose of 1 mg/kg and 3 mg/kg, and MGL-3196 was administered at the dose of 3 mg/kg for 10 weeks. Body weight, food intake, serum and hepatic parameters, histological analysis, pharmacokinetic studies, RNA sequencing of the liver and heart, and expression of hepatic lipid-metabolic genes were determined to evaluate the safety and efficiency of CS271011. ResultsCompared with MGL-3196, CS271011 showed higher THR-β activation in vitro. In the diet-induced obesity mice model, CS271011 demonstrated favourable pharmacokinetic properties in mice and was enriched in the liver. Finally, CS271011 improved dyslipidaemia and reduced liver steatosis in the diet-induced obesity murine model. Mechanistically, CS271011 and MGL-3196 showed potent regulation of lipid metabolism-related genes. ConclusionsCS271011 is a potent and liver-targeted THR-β agonist for treating lipid metabolism disorders.

The aboveground biomass (AGB) of withered grass is an important early-warning indicator for grassland fire risk. Most grassland fires occur during the dry-grass season. In order to improve the fire-warning efficiency of withered AGB, it is essential to rapidly acquire the amount of withered-grass biomass. Remote-sensing data has been widely used in monitoring and estimating grassland yields during the growing season. However, applying remote sensing to the estimation of withered grass is still in need of exploration. The aim of this work was to try to establish a remote-sensing estimation model for withered AGB in the dry-grass season. The estimation of aboveground biomass can effectively prevent the occurrence of fire, protect the environment, facilitate local management and reduce economic losses. Our approach was to, first, calculate a dry-grass index based on Sentinel-2 image data and using ENVI, SNAP, and ArcGIS software. Second, a model to estimate the fuel quantity during the dry-grass season was established by regression analysis combined with field-measured data. Finally, the estimation model was used to predict the amount of fuel in different months of the dry-grass season, followed by the fire-defense elements, which were quantified and mapped in the Longzhao Marsh wetlands. It was found that: 1) the two indices were significantly correlated (0.678) with the amount of fuel; 2) the established model could accurately estimate the amount of fuel in the study area during the dry season, and accurate test results demonstrated that the correlation between the estimated results of the best model and the measured values was 0.863, indicating high accuracy; 3) the spatiotemporal variation of withered grass in the study area was obviously different, and the quantities of fuel predicted for the other months were more accurate, which may reflect monthly dynamic changes in actual fuel quantities; and 4) the establishment of a remote-sensing estimation model for fuel quantity in the Longzhao Marsh during the dry-grass season could provide important parameters for fire-risk warning in the western grassland of Jilin Province and Northeast China.

In response to the difficulties of flood plain quality assessment, red-edge spectral remote sensing data acquired from the Jilin-01 satellite were used. The Grassland Quality Index (GQI) was formed by the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) related to the determination of grassland quality and the first principal component of the red-edge Chlorophyll Index obtained by principal component analysis. The GQI was applied to evaluate grassland quality in the flooded plain, which is an important grassland ecological-barrier area in the western area of Jilin Province, and was then verified using field measurement data. Results show that 1) 80% of grasslands in Xianghai Nature Reserve are of a medium quality, and the grasslands with good growth status account for approximately 15% and are mainly concentrated in the wetland and swamp areas in the central south part of the reserve and that 2) the correlation of the evaluation results was verified using the survey field biomass, and the coefficient of the empirical correlation model is 0.96, which indicates good consistency. This study is of practical significance for the timely and accurate monitoring of grassland growth, which is beneficial for the development of livestock husbandry and the protection of the ecological environment in northern China.

Solar activity has significant impacts on human activities and health. One most commonly used measure of solar activity is the sunspot number. This paper compares three important non-deep learning models, four popular deep learning models, and their five ensemble models in forecasting sunspot numbers. In particular, we propose an ensemble model called XGBoost-DL, which uses XGBoost as a two-level nonlinear ensemble method to combine the deep learning models. Our XGBoost-DL achieves the best forecasting performance (RMSE $$ = 25.70$$ and MAE $$ = 19.82$$) in the comparison, outperforming the best non-deep learning model SARIMA (RMSE $$ = 54.11$$ and MAE $$ = 45.51$$), the best deep learning model Informer (RMSE $$ = 29.90$$ and MAE $$ = 22.35$$) and the NASA’s forecast (RMSE $$ = 48.38$$ and MAE $$ = 38.45$$). Our XGBoost-DL forecasts a peak sunspot number of 133.47 in May 2025 for Solar Cycle 25 and 164.62 in November 2035 for Solar Cycle 26, similar to but later than the NASA’s at 137.7 in October 2024 and 161.2 in December 2034. An open-source Python package of our XGBoost-DL for the sunspot number prediction is available at https://github.com/yd1008/ts_ensemble_sunspot.