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Abstract Background A large body of data shows that fetal brain development is vulnerable to disruption by air pollution experienced by the mother during pregnancy, adversely affecting cognitive and psychomotor capabilities during childhood (De Asis-Cruz et al., Biol Psychiatry 7:480–90, 2022; Morgan ZEM et al., Environ Health 22:11, 2023). This study has sought to identify gestational windows of susceptibility to prenatal exposure to air pollution. Methods 470 African American and Latina mother/child pairs participated in a prospective cohort study based in the low-income communities of Northern Manhattan and the South Bronx, New York City. Gestational exposure to respirable particulate matter (PM2.5) and nitrogen dioxide (NO2) was assessed through validated models in relation to cognitive and motor development assessed at ages 1, 2, and 3 years using the Bayley-II Scales. Multiple linear regression models and distributed lag models (DLM) were used to identify critical windows of exposure by trimester and week of pregnancy. Results By linear regression, average exposures to NO2 during the first and second trimesters and the entire pregnancy were significantly and negatively associated with the mental developmental index (MDI) at age 1. Average exposures to PM2.5 during the second trimester and the entire pregnancy were also significantly, inversely associated with age 1 MDI. No significant associations were found between these exposures and MDI at age 2. NO2 exposure during the first trimester was significantly negatively associated with MDI at age 3. Using DLM, exposures to NO2 at lags 29–30 weeks (within the first trimester) and PM2.5 at lags 17–18 weeks (second trimester) were significantly and inversely associated with MDI at age 1. Significant, inverse associations were found between exposures to NO2 at lag 29 weeks and PM2.5 at lags 27–29 weeks and children’s MDI at age 3. No significant associations were found between psychomotor index (PDI) and prenatal exposures to NO2 or PM2.5 at ages 1, 2 or 3. Conclusions Our finding that prenatal exposure to air pollution in the first and second trimesters was associated with lower scores for cognitive development at ages 1 and 3 is of concern because of the potential consequences of these outcomes for long-term functioning. They underscore the need for stronger policies to protect pregnant individuals and offspring, particularly during vulnerable, early life-stage of development.

Abstract The poor corrosion resistance of magnesium limits its clinical applications. Accordingly, in the present study, carbon ions were incorporated into a AZ31b magnesium alloy surface via carbon plasma immersion ion-implantation to improve its corrosion resistance and biocompatibility. The surface morphology and properties of the modified alloy were evaluated by field-emission scanning electron microscopy, water contact angle measurement, Raman scattering, X-ray photoelectron spectroscopy, and energy dispersive X-ray spectroscopy. Furthermore, compositional depth profiles were obtained by glow discharge optical emission spectroscopy, revealing a Gaussian-like distribution of carbon concentration. Electrochemical and hydrogen-evolution analysis demonstrated the successfully improved corrosion resistance of the AZ31b Mg alloy, while its biocompatibility was demonstrated by MTT and cell-adherence assays.

Abstract Low-dose computed tomography (LDCT) has emerged as the preferred technology for diagnostic medical imaging due to the potential health risks associated with X-ray radiation and conventional computed tomography (CT) techniques. While LDCT utilizes a lower radiation dose compared to standard CT, it results in increased image noise, which can impair the accuracy of diagnoses. To mitigate this issue, advanced deep learning-based LDCT denoising algorithms have been developed. These primarily utilize Convolutional Neural Networks (CNNs) or Transformer Networks and often employ the Unet architecture, which enhances image detail by integrating feature maps from the encoder and decoder via skip connections. However, existing methods focus excessively on the optimization of the encoder and decoder structures while overlooking potential enhancements to the Unet architecture itself. This oversight can be problematic due to significant differences in feature map characteristics between the encoder and decoder, where simple fusion strategies may hinder effective image reconstruction. In this paper, we introduce WiTUnet, a novel LDCT image denoising method that utilizes nested, dense skip pathway in place of traditional skip connections to improve feature integration. Additionally, to address the high computational demands of conventional Transformers on large images, WiTUnet incorporates a windowed Transformer structure that processes images in smaller, non-overlapping segments, significantly reducing computational load. Moreover, our approach includes a Local Image Perception Enhancement (LiPe) module within both the encoder and decoder to replace the standard multi-layer perceptron (MLP) in Transformers, thereby improving the capture and representation of local image features. Through extensive experimental comparisons, WiTUnet has demonstrated superior performance over existing methods in critical metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM), and Root Mean Square Error (RMSE), significantly enhancing noise removal and image quality. The code is available on github https://github.com/woldier/WiTUNet .

Abstract Obesity is an important risk factor for breast cancer in women before and after menopause. Adipocytes, key mediators in the tumor microenvironment, play a pivotal role in the relationship between obesity with cancer. However, the potential of dietary components in modulating this relationship remains underexplored. Genistein, a soy-derived isoflavone, has shown promise in reducing breast cancer risk, attenuating obesity-associated inflammation, and improving insulin resistance. However, there are no reports examining whether genistein has the ability to reduce the effects of obesity on breast tumor development. In this study, we constructed a mammary tumor model in ovariectomized obese mice and examined the effects of genistein on body condition and tumor growth. Moreover, the effects of genistein on the tumor microenvironment were examined via experimental observation of peritumoral adipocytes and macrophages. In addition, we further investigated the effect of genistein on adipocyte and breast cancer cell crosstalk via coculture experiments. Our findings indicate that dietary genistein significantly alleviates obesity, systemic inflammation, and metabolic disorders induced by a high-fat diet in ovariectomized mice. Notably, it also inhibits tumor growth in vivo. The impact of genistein extends to the tumor microenvironment, where it reduces the production of cancer-associated adipocytes (CAAs) and the recruitment of M2d-subtype macrophages. In vitro, genistein mitigates the transition of adipocytes into CAAs and inhibits the expression of inflammatory factors by activating PPAR-γ pathway and degrading nuclear NF-κB. Furthermore, it impedes the acquisition of invasive properties and epithelial‒mesenchymal transition in breast cancer cells under CAA-induced inflammation, disrupting the Wnt3a/β-catenin pathway. Intriguingly, the PPAR-γ inhibitor T0070907 counteracted the effects of genistein in the coculture system, underscoring the specificity of its action. Our study revealed that genistein can mitigate the adverse effects of obesity on breast cancer by modulating the tumor microenvironment. These findings provide new insights into how genistein intake and a soy-based diet can reduce breast cancer risk.

Abstract Exploring the impact of physical exercise on adolescent insomnia and the chained mediating role of psychological inflexibility and stress between them. In September 2023, a questionnaire survey was conducted among 416 adolescents in Xiangxi Prefecture, collecting data on physical activity, insomnia, psychological inflexibility, stress, and related variables. Statistical analysis was performed, involving 215 boys and 201 girls with an average age of 15.37 ± 0.54 years. (1) Adolescent physical exercise showed significant negative correlations with stress (r =−0.329, P

Abstract Traditional pseudo‐satellite‐based indoor positioning techniques are greatly affected by the presence of multipath effects, leading to a notable reduction in the positioning precision. In order to tackle this challenge, a pseudo‐satellite indoor positioning method based on deep learning is proposed. The method grids the localization region, thus transforming positioning from a regression problem to a classification problem in the gridded areas. 1D‐convolutional neural network is employed to extract the correlation between pseudo‐satellite data and the positioning of indoor areas. Data are collected and the method is validated in three types of areas of the experimental field, namely unobstructed area, semi‐unobstructed area and obstructed area. The experimental results demonstrate that the method exhibits superior positioning accuracy compared to traditional methods, enabling effective localization even in obstructed area.

Fuchsia standishii J. Harrison, 1840, a perennial shrub, is renowned for its vividly colored and uniquely shaped blooms, which have an extended flowering season. Commonly cultivated as an ornamental potted plant, it is utilized in traditional Chinese medicine. In this study, we successfully sequenced and assembled the complete chloroplast genome of F. standishii using high-throughput Illumina sequencing technology. The assembled chloroplast genome displays a typical quadripartite structure, with a total length of 156,391 bp. It consists of a pair of inverted repeat regions (IRs), each measuring 25,069 bp, separated by a large single-copy region (LSC) of 87,754 bp and a small single-copy region (SSC) of 18,499 bp. The overall GC content of the genome is 37.60%. The genome includes a total of 129 genes, comprising 84 protein-coding genes, 37 tRNA genes, and eight rRNA genes. Phylogenetic analysis of 17 complete chloroplast genomes revealed that F. standishii forms a monophyletic group with the entire Circaea. This study provides a molecular foundation for future phylogenetic research on Fuchsia.

Garcinia esculenta Y. H. Li. 1981 (Clusiaceae) is an endemic tree species in China, primarily found in western and northwestern Yunnan Province. In this research, the complete chloroplast genome of G. esculenta was sequenced using the Illumina NovaSeq6000 platform. The result showed that the length of the complete chloroplast genome was 155,853 bp, which was composed of a large single-copy region (LSC) of 84,534 bp, a small single-copy region (SSC) of 17,175 bp, and a pair of inverted repeat (IR) regions of 27,072 bp. The overall GC content was 36.1%. The complete chloroplast genome encompassed 128 genes, comprising 83 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Phylogenetic analysis of the complete chloroplast genome sequences of 22 species revealed that G. esculenta is most closely related to G. oblongifolia.

We investigate the resonance problem and prove the existence of multiple periodic solutions to a second order parameter-dependent equation $ x''+f(t, x) = sp(t) $. We weaken the usual requirement on the sublinearity of perturbations when $ |x| $ becomes large; and develop a more general method to investigate the rotational characterizations of the Landesman-Lazer conditions. Furthermore, $ f $ does not satisfy the common sign condition, and even the global existence of the solution is not guaranteed.

Abstract Visual working memory depends on both material-specific brain areas in the ventral visual stream (VVS) that support the maintenance of stimulus representations and on regions in the prefrontal cortex (PFC) that control these representations. How executive control prioritizes working memory contents and whether this affects their representational formats remains an open question, however. Here, we analyzed intracranial EEG (iEEG) recordings in epilepsy patients with electrodes in VVS and PFC who performed a multi-item working memory task involving a retro-cue. We employed Representational Similarity Analysis (RSA) with various Deep Neural Network (DNN) architectures to investigate the representational format of prioritized VWM content. While recurrent DNN representations matched PFC representations in the beta band (15–29 Hz) following the retro-cue, they corresponded to VVS representations in a lower frequency range (3–14 Hz) towards the end of the maintenance period. Our findings highlight the distinct coding schemes and representational formats of prioritized content in VVS and PFC.

Abstract In the process of penicillin fermentation, there is a strong nonlinear relationship between the input eigenvector and multiple output vectors, which makes the prediction accuracy of the existing model difficult to meet the requirements of chemical production. Therefore, a local selective ensemble learning multi-objective soft sensing modeling strategy is proposed in this study. Firstly, a localization method based on transfer entropy and k-means is proposed to reconstruct the sample set. Then, based on the reconstructed local samples, the local soft sensing model is established by the multi-objective support vector regression method, and the selective ensemble of sub-models and the adaptive calculation of prediction weights are realized. At the same time, to reduce the adverse effects caused by improper selection of model parameters, the sparrow search algorithm is used to realize the tuning of the mentioned model parameters. Finally, the proposed modeling strategy is simulated. The results show that, compared with other methods, the proposed local selective ensemble learning multi-objective soft sensing modeling strategy has better prediction performance.

Abstract Smart highways endorse green and low-carbon handling construction infrastructures for promoting pollution-free environments and driving spaces. With the incorporation of artificial intelligence and smart computing features, sophisticated decision systems improve the aim of such smart highway constructions. For promoting green and low-carbon highway construction infrastructure, this research article introduces a pollution control-facilitated recommendation system (PCFRS). The system aims to satisfy eco-friendly driving demands and low-carbon emission requirements. In this system, eco-friendly driving demands and low-carbon emissions are the prime requirements for designing such highways. The research employs fuzzy control algorithms to analyze the relationship between green demands and demand satisfaction factors across different infrastructures based on policies from environmental departments and governing agencies. The green demands as formulated by the environmental department/ governing agencies are used for verifying the demand and relationship factors across various infrastructures. The fuzzy algorithm provides recommendations for optimal highway infrastructure design by identifying the maximum possible combinations of satisfaction factors, enabling cost-effective construction while meeting green environment and low-carbon emission goals. This process is aided by a fuzzy control algorithm with the relationship and demand factor as crisp inputs. The decisions on the maximum possible combinations of the satisfaction factor are used for infrastructure recommendations. The need for optimal design and promoting green environments are optimal across various highway lanes.

Abstract Male sex, early life chemical exposure and the brain aromatase enzyme have been implicated in autism spectrum disorder (ASD). In the Barwon Infant Study birth cohort (n = 1074), higher prenatal maternal bisphenol A (BPA) levels are associated with higher ASD symptoms at age 2 and diagnosis at age 9 only in males with low aromatase genetic pathway activity scores. Higher prenatal BPA levels are predictive of higher cord blood methylation across the CYP19A1 brain promoter I.f region (P = 0.009) and aromatase gene methylation mediates (P = 0.01) the link between higher prenatal BPA and brain-derived neurotrophic factor methylation, with independent cohort replication. BPA suppressed aromatase expression in vitro and in vivo. Male mice exposed to mid-gestation BPA or with aromatase knockout have ASD-like behaviors with structural and functional brain changes. 10-hydroxy-2-decenoic acid (10HDA), an estrogenic fatty acid alleviated these features and reversed detrimental neurodevelopmental gene expression. Here we demonstrate that prenatal BPA exposure is associated with impaired brain aromatase function and ASD-related behaviors and brain abnormalities in males that may be reversible through postnatal 10HDA intervention.

Abstract Objective To provide evidence for choosing surgical or nonsurgical treatment for epilepsy in patients with unilateral multilobar and hemispheric polymicrogyria (PMG). Methods We searched published studies until September 2022 related to unilateral multilobar and hemispheric PMG and included patients who were followed up at the Pediatric Epilepsy Centre of Peking University First Hospital in the past 10 years. We summarized the clinical characteristics and compared the long‐term outcomes after surgical or nonsurgical (anti‐seizure medications, ASMs) treatment. Results A total of 70 patients (49 surgical, 21 non‐surgical) with unilateral multilobar and hemispheric PMG were included. The median age at epilepsy onset was 2.5 years (1.0–4.1). The most common seizure types were focal and atypical absence seizures. In the whole cohort, 87.3% had hemiparesis and 67.1% had electrical status epilepticus during slow sleep (ESES). There were significant differences in age at epilepsy onset, extent of lesion, and EEG interictal discharges between the two groups. At the last follow‐up (median 14.1 years), the rates of seizure‐freedom (81.6% vs. 57.1%, p = 0.032) and ASM discontinuation (44.4% vs. 6.3%, p = 0.006) were higher in the surgical group than in the nonsurgical group. Patients in the surgical group had a higher rate of seizure‐freedom with complete resection/disconnection than with subtotal resection (87.5% vs. 55.6%, p = 0.078), but with no statistically significant difference. In the nonsurgical group, more extensive lesions were associated with worse seizure outcomes. Cognition improved postoperatively in 90% of surgical patients. Significance In patients with unilateral multilobar and hemispheric PMG, the age of seizure onset, the extent of the lesion and EEG features can help determine whether surgery should be performed early. Additionally, surgery could be more favorable for achieving seizure freedom and cognitive improvement sooner. Plain Language Summary We aim to summarize clinical characteristics and compare the long‐term outcomes after surgical and nonsurgical (ASM) treatment to provide a basis for treatment decisions for patients with unilateral multilobar and hemispheric polymicrogyria (PMG)‐related epilepsy. We found that patients with unilateral hemispheric and multilobar PMG had significantly higher rates of seizure freedom and ASM discontinuation with surgical treatment than with nonsurgical treatment. In the surgical group, seizure outcomes were better in patients treated with complete resection/disconnection than in those treated with subtotal resection, but the difference was not statistically significant.

Abstract Background Exposure to famine in the prenatal period is associated with an increased risk of metabolic disease, including obesity and type 2 diabetes. We employed nuclear magnetic resonance (NMR) metabolomic profiling to identify the metabolic changes that are associated with survival of prenatal famine exposure during the Dutch Famine at the end of World War II and subsequently assess their link to disease. Methods NMR metabolomics data were generated from serum in 480 individuals prenatally exposed to famine (mean 58.8 years, 0.5 SD) and 464 controls (mean 57.9 years, 5.4 SD). We tested associations of prenatal famine exposure with levels of 168 individual metabolic biomarkers and compared the metabolic biomarker signature of famine exposure with those of 154 common diseases. Results Prenatal famine exposure was associated with higher concentrations of branched-chain amino acids ((iso)-leucine), aromatic amino acid (tyrosine), and glucose in later life (0.2–0.3 SD, p

Highlights Fundamental principles for designing synergistic composite catalysts are reviewed. The synergistic effect between various active sites, promoting electrocatalytic performance in different reactions are highlighted. The challenges and perspectives for multiple active sites catalysts are discussed.

AIM: To investigate the clinical features of the ocular surface in patients with different degrees of myopia. METHODS: A cross-sectional study was conducted involving 122 participants with myopia in Beijing Tongren Hospital from February to June, 2023. After completing the Ocular Surface Disease Index (OSDI) score scale, measurements were taken for refraction, biometric parameters and ocular surface parameters. The prevalence, severity and related parameters of the dry eye among different groups based on axial length (AL) were compared. Correlation analysis was performed between ocular surface parameters and refraction/biometric measurement parameters. RESULTS: Statistically significant differences were observed in refractive error, corneal thickness, anterior chamber depth, and subfoveal choroidal thickness among the groups (all P

A prominent strengthened Y2O3 stabilized t-ZrO2 (YSTZ)/MgO nanocomposite coating is achieved by the plasma electrolytic oxidation (PEO) process and in-situ synthesized YSTZ reinforced phase with a quantitative control approach. The idea of activating double slip systemic semi-coherent interface dislocations in YSTZ/MgO nanocomposite coating to realize crack self-healing is proposed. High dislocation densities are associated with {101} YSTZ slip and {111} MgO slip system to coordinate interfacial deformation to stop crack initiation and propagation. This crack propagation path can absorb more fracture energy, providing more opportunities for crack deflection and bridge, which closes crack and realizes crack self-healing.

Aiming at the complex working conditions environmental factors such as high noise, low illumination, motion blur and mass gangue mixing in coal mines, which lead to the problems of misdetection, omission and low detection accuracy in gangue recognition, a gangue recognition model based on CFS-YOLO algorithm is proposed. The ConvNeXt V2（Convolutional Neural Network with NeXt Units Version 2）feature extraction module is adopted to replace the two C3（Cross stage partial bottle neck mudule）modules at the end of the backbone network, which effectively mitigates the feature collapse problem as well as maintains the diversity of the features in the network delivery process by adding Masked Autoencoder and Global Response Normalization layers to the ConvNeXt architecture. The Focal-EIOU (Focal and Efficient Intersection Over Union) loss function is adopted to replace the original CIOU (Computer Intersection Over Union) loss function to optimize the sample imbalance problem in the bounding box regression task by means of its Focal-Loss mechanism and adjusting the sample weights, which improves the convergence speed and localization accuracy of the model. The parameter-free attention mechanism （Simple Attention Mechanism, SimAM） is added to the back-end of each C3 module of the backbone network to enhance the model's ability of extracting key features of coal gangue targets with large scale variation or low resolution by virtue of its attention weight adaptive adjustment strategy. The effectiveness and superiority of the proposed CFS-YOLO model is verified by ablation and comparison experiments. The experimental results show that the CFS-YOLO model can effectively improve the detection effect of coal gangue under the complex environment of high noise, low illumination, motion blur and large amount of mixed coal gangue in coal mines. The mean Average Presicion (mAP) of the model reaches 90.2%, which is 3.7% higher than the mean Average Presicion (mAP) of the original YOLOv5s model, and the average detection speed reaches 90.09 FPS (Frames Per Second), which can fully satisfy the demand of real-time detection of coal gangue. Meanwhile, compared with six YOLO algorithms such as YOLOv5s, YOLOv7-tiny and YOLOv8n, the CFS-YOLO model has the strongest adaptability to the complex environment of coal mines and the best comprehensive detection performance, which can provide technical support for intelligent and efficient sorting of coal gangue.

Abstract The home-rearing environment (HRE) is significantly related to preschoolers’ academic and behavioral development. Children’s screen time has become an increasingly important aspect of the family environment in today’s digital age. However, few studies explored screen time’s indirect role in the relationships between HRE and children’s development. This study was conducted in three provinces of China, and 825 child-parent dyads participated. The results indicated that a high-quality HRE is directly associated with better language and cognitive skills, self-regulation, self-efficacy, and fewer problem behaviors in children. Screen time has an indirect role in this relationship, suggesting that a better HRE associated with lower screen time improves children’s outcomes. However, the HRE did not show a significant indirect role through screen time related to children’s problem behavior, indicating other factors may play a role. The study highlights the importance of fostering enriching home environments and managing screen time to support children’s development.

Abstract Objectives To construct a combined model based on bi-regional quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), as well as clinical-radiological (CR) features for predicting microvascular invasion (MVI) in solitary Barcelona Clinic Liver Cancer (BCLC) stage A hepatocellular carcinoma (HCC), and to assess its ability for stratifying the risk of recurrence after hepatectomy. Methods Patients with solitary BCLC stage A HCC were prospective collected and randomly divided into training and validation sets. DCE perfusion parameters were obtained both in intra-tumoral region (ITR) and peritumoral region (PTR). Combined DCE perfusion parameters (C DCE) were constructed to predict MVI. The combined model incorporating C DCE and CR features was developed and evaluated. Kaplan–Meier method was used to investigate the prognostic significance of the model and the survival benefits of different hepatectomy approaches. Results A total of 133 patients were included. Total blood flow in ITR and arterial fraction in PTR exhibited the best predictive performance for MVI with areas under the curve (AUCs) of 0.790 and 0.792, respectively. C DCE achieved AUCs of 0.868 (training set) and 0.857 (validation set). A combined model integrated with the α-fetoprotein, corona enhancement, two-trait predictor of venous invasion, and C DCE could improve the discrimination ability to AUCs of 0.966 (training set) and 0.937 (validation set). The combined model could stratify the prognosis of HCC patients. Anatomical resection was associated with a better prognosis in the high-risk group (p

Abstract Radio-immunotherapy exploits the immunostimulatory features of ionizing radiation (IR) to enhance antitumor effects and offers emerging opportunities for treating invasive tumor indications such as melanoma. However, insufficient dose deposition and immunosuppressive microenvironment (TME) of solid tumors limit its efficacy. Here we report a programmable sequential therapeutic strategy based on multifunctional fusogenic liposomes (Lip@AUR-ACP-aptPD-L1) to overcome the intrinsic radio-immunotherapeutic resistance of solid tumors. Specifically, fusogenic liposomes are loaded with gold-containing Auranofin (AUR) and inserted with multivariate-gated aptamer assemblies (ACP) and PD-L1 aptamers in the lipid membrane, potentiating melanoma-targeted AUR delivery while transferring ACP onto cell surface through selective membrane fusion. AUR amplifies IR-induced immunogenic death of melanoma cells to release antigens and damage-associated molecular patterns such as adenosine triphosphate (ATP) for triggering adaptive antitumor immunity. AUR-sensitized radiotherapy also upregulates matrix metalloproteinase-2 (MMP-2) expression that combined with released ATP to activate ACP through an “and” logic operation-like process (AND-gate), thus triggering the in-situ release of engineered cytosine-phosphate-guanine aptamer-based immunoadjuvants (eCpG) for stimulating dendritic cell-mediated T cell priming. Furthermore, AUR inhibits tumor-intrinsic vascular endothelial growth factor signaling to suppress infiltration of immunosuppressive cells for fostering an anti-tumorigenic TME. This study offers an approach for solid tumor treatment in the clinics.

Abstract Factor-dependent termination uses molecular motors to remodel transcription machineries, but the associated mechanisms, especially in eukaryotes, are poorly understood. Here we use single-molecule fluorescence assays to characterize in real time the composition and the catalytic states of Saccharomyces cerevisiae transcription termination complexes remodeled by Sen1 helicase. We confirm that Sen1 takes the RNA transcript as its substrate and translocates along it by hydrolyzing multiple ATPs to form an intermediate with a stalled RNA polymerase II (Pol II) transcription elongation complex (TEC). We show that this intermediate dissociates upon hydrolysis of a single ATP leading to dissociation of Sen1 and RNA, after which Sen1 remains bound to the RNA. We find that Pol II ends up in a variety of states: dissociating from the DNA substrate, which is facilitated by transcription bubble rewinding, being retained to the DNA substrate, or diffusing along the DNA substrate. Our results provide a complete quantitative framework for understanding the mechanism of Sen1-dependent transcription termination in eukaryotes.

Lonicera japonica Thunb. is widely used in Asian countries as a food ingredient to make healthy drinks, with lonicerin, a flavone O-glycoside, as a predominant bioactive compound. This study investigated lonicerin’s effects on high-fat diet-induced hepatic steatosis in mice, compared to its aglycone luteolin. Results showed that lonicerin significantly reduced diet-induced body weight gain and hepatic lipid accumulation in mice, demonstrating greater efficacy than luteolin. This lipid-lowering effect was due to inhibited hepatic fatty acid (FA) biosynthesis and promoted fecal lipid excretion. Moreover, lonicerin favorably modulated gut microbiota by increasing Dubosiella, Eubacterium_brachy_group, and Bilophila, while reducing the pathogenic Desulfovibrionaceae. These changes led to elevated short-chain fatty acid production and altered fecal bile acid (BA) profiles, likely activating the intestinal FXR-FGF15 pathway to inhibit hepatic FA synthesis. In conclusion, lonicerin alleviated diet-induced hepatic steatosis by promoting fecal lipid excretion and inhibiting hepatic FA biosynthesis through modulating the gut microbiota-BA-intestinal FXR axis.

Abstract Background Glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs), a class of injectable antidiabetic drugs, have shown significant efficacies in improving glycemic and weight control in patients with type 2 diabetes (T2D). However, the long‐term safety of GLP‐1 RAs remains insufficiently studied. This study aimed to provide real‐world evidence on potential adverse outcomes associated with GLP‐1 RAs use in T2D patients without major chronic diseases including impaired cardiac or renal function. Methods We conducted a retrospective cohort study involving 7746 T2D patients on GLP‐1 RAs in Shenzhen, China. They were compared with 124 371 metformin‐only users and 36 146 insulin‐only users, forming two therapy control groups. GLP‐1 RAs users were also further 1:2 paired with the control groups. Competing risk survival analyses were conducted to assess the incidence risks, presenting subdistributional hazard ratios (sHRs) with 95% confidence intervals (CIs) for various adverse outcomes associated with GLP‐1 RAs use. Results Compared with metformin‐only users, GLP‐1 RAs use was associated with increased risks of various adverse outcomes (sHRs with 95% CIs), including pancreatitis (2.01, 1.24–3.24), acute nephritis (3.20, 2.17–4.70), kidney failure (3.73, 2.74–5.08), thyroid cancer (2.25, 1.23–4.10), and thyroid dysfunction (1.27, 1.00–1.63), respectively; Similar results were also found when compared with insulin‐only users. Importantly, long‐term (≥12 months) GLP‐1 RAs use may further elevate the incidence risks of pancreatitis, acute nephritis, thyroid cancer, and thyroid dysfunction. Conclusion Compared with traditional T2D treatments, GLP‐1 RAs use may be associated with increased risks of various adverse outcomes in a Chinese population. Cautions were strongly warranted in the use of GLP‐1 RAs. Further validation is crucial across diverse populations.

Abstract The typical metal chloride‐graphite intercalation compounds (MC‐GICs) inherit intercalation capacity, high charge conductivity, and high tap density from graphite, and these are considered as one of the promising alternatives of graphite anode in rechargeable metal‐ion batteries (MIBs). Notably, the special interlayer decoupling effects and the introduction of extra conversion capacity by metal chloride could greatly break the capacity limitation of graphite anodes and achieve higher energy density in MIBs. The optimization of both graphite host and metal chloride species with specific structures endows MC‐GICs with design feasibility for different application requirements of different MIBs, such as several times the actual capacity compared to graphite anodes, rapid migration of large carriers, and other properties. Herein, a brief review has been provided with the latest understanding of conductivity characteristics and energy storage mechanisms of MC‐GICs and their interesting performance features of full potential application in rechargeable MIBs. Based on the existing research of MC‐GICs, necessary improvements and prospects in the near future have been put forward.

Abstract BackgroundIncremental advancements in artificial intelligence (AI) technology have facilitated its integration into various disciplines. In particular, the infusion of AI into medical education has emerged as a significant trend, with noteworthy research findings. Consequently, a comprehensive review and analysis of the current research landscape of AI in medical education is warranted. ObjectiveThis study aims to conduct a bibliometric analysis of pertinent papers, spanning the years 2013‐2022, using CiteSpace and VOSviewer. The study visually represents the existing research status and trends of AI in medical education. MethodsArticles related to AI and medical education, published between 2013 and 2022, were systematically searched in the Web of Science core database. Two reviewers scrutinized the initially retrieved papers, based on their titles and abstracts, to eliminate papers unrelated to the topic. The selected papers were then analyzed and visualized for country, institution, author, reference, and keywords using CiteSpace and VOSviewer. ResultsA total of 195 papers pertaining to AI in medical education were identified from 2013 to 2022. The annual publications demonstrated an increasing trend over time. The United States emerged as the most active country in this research arena, and Harvard Medical School and the University of Toronto were the most active institutions. Prolific authors in this field included Vincent Bissonnette, Charlotte Blacketer, Rolando F Del Maestro, Nicole Ledows, Nykan Mirchi, Alexander Winkler-Schwartz, and Recai Yilamaz. The paper with the highest citation was “Medical Students’ Attitude Towards Artificial Intelligence: A Multicentre Survey.” Keyword analysis revealed that “radiology,” “medical physics,” “ehealth,” “surgery,” and “specialty” were the primary focus, whereas “big data” and “management” emerged as research frontiers. ConclusionsThe study underscores the promising potential of AI in medical education research. Current research directions encompass radiology, medical information management, and other aspects. Technological progress is expected to broaden these directions further. There is an urgent need to bolster interregional collaboration and enhance research quality. These findings offer valuable insights for researchers to identify perspectives and guide future research directions.

Streptococcus species are important pathogens implicated in bovine mastitis, causing considerable economic losses within the global dairy industry. With the development of multidrug-resistant bacteria, it is crucial to develop novel antibiotic alternatives. Here, we constructed a novel chimeric endolysin, Cly2v, which comprises the Ply2741 CHAP domain (1-155aa) and the PlyV12 CBD domain (146-314aa). Biochemical characterization analysis indicated that Cly2v exhibits a melting temperature of 50.7°C and retains stable bactericidal activity at pH = 3–10. In vitro experiments demonstrated that Cly2v exhibited more efficient bactericidal activity against Streptococcus compared to the parental endolysin Ply2741. Cly2v (25 μg/mL) can effectively inhibit and reduce biofilms formed by Streptococcus, resulting in a 68 and 44% reduction in OD590nm for S. agalactiae X2 and S. uberis 002–1 biofilms. Notably, in a mouse mastitis model, treatment with Cly2v (50 μg/gland) led to a reduction in bacterial load by 2.16 log10CFU/ml and decreased inflammatory cytokine levels in mammary tissue. To our knowledge, this represents the first application of a chimeric endolysin in the treatment of early-stage mouse mastitis induced by streptococci. Additionally, in a systemic infection model, treatment with Cly2v (400 μg/mouse) provided protection rates of up to 100 and 78% against S. agalactiae ATCC13813 infections when challenged for 1 h and 3 h, respectively. Furthermore, a significant reduction in bacterial loads was observed in the blood and organs compared to the PBS group. In summary, Cly2v possesses significant potential as an alternative antibiotic for the treatment of streptococci-induced bovine mastitis and systemic infections.

IntroductionAir pollution poses serious health risks to humans, with particular harm to children.ObjectivesTo address the gap in understanding the efficacy of policies to reduce exposure to air pollution, we sought to assess the temporal relationship between the enactment of major air pollution and climate policies in NYC and trends in air quality during the period 1998–2021. We used previously available data from citywide monitoring and new data from the Columbia Center for Children’s Environmental Health (CCCEH) longitudinal cohort studies of mothers and children living in communities in Northern Manhattan and the South Bronx.MethodsWe utilized publicly available citywide air monitoring data for particulate matter (PM2.5) and nitrogen dioxide (NO2) from 2009 to 2021 from the New York City Community Air Survey (NYCCAS) database and CCCEH cohort data on residential exposure to PM2.5 and NO2 and personal exposure to polycyclic aromatic hydrocarbons (PAH) during pregnancies occurring from 1998–2016 and 1998–2021, respectively. We compared annual and overall reductions in PM2.5 and NO2 citywide and reductions in PAH concentrations in the cohort studies.ResultsAs previously reported, annual average concentrations of pollutants in NYC dropped significantly over time. Between 1998 and 2021, PM2.5 and NO2 concentrations were reduced citywide by 37 and 31%, respectively. In our CCCEH cohorts, between 1998 and 2016, the annual average PM2.5 and NO2 concentrations also decreased significantly by 51 and 48%, respectively. Between 1998 and 2020, PAH concentrations decreased significantly by 66%.Discussion/conclusionWhile it is not possible to link improved air quality to a single policy, our analysis provides evidence of a cumulative beneficial effect of clean air and climate policies enacted between 1998 and 2021 both city-wide and in our cohorts residing in communities that have been disproportionately affected by air pollution. There are important implications for health benefits, particularly for children, who are known to be especially vulnerable to these exposures. The results support further environmental and social policy changes to prevent the serious health impacts of air pollution from fossil fuel emissions.

IntroductionMaize stalk rot (MSR), caused by Fusarium graminearum, is the most serious soil borne disease in maize production, seriously affecting maize yield and quality worldwide. Microbial biocontrol agents are the best means of controlling MSR and reducing the use of chemical fungicides, such as Bacillus spp.Methods and resultsIn the study, a soil-isolated strain B105-8 was identified as B. velezensis (accession No. PP325775.1 and No. PP869695.1), demonstrated a broad spectrum against various pathogens causing maize diseases, which effectively controlled MSR, exhibited a high control efficacy of more than 60% and growth-promoting effect in the pot plant. B105-8 could effectively improve soil urease (S-UE), invertase (S-SC), and catalase (S-CAT) activities. S-NP activity showed an initial increase with a peak of 20,337 nmol/h/g, followed by a decrease, but activity remained significantly better than control treatment with chemical fungicides. The application of B105-8 repaired the damage caused by F. graminearum on soil activity. The antifungal compound B-1, extracted from B105-8, was purified using a protein purifier, revealing inhibitory effects against F. graminearum. Mass spectrometry analysis indicated the potential presence of C14 Bacillomycin, C15 Iturin, C15 Mycosubtilin, C17, and C15 fengycin in B-1. In pot experiments, a 5 μL/mL concentration of B-1 exhibited 69% control on MSR, enhancing maize root elongation, elevation, and fresh weight. At 10 μL/mL, B-1 showed 89.0 and 82.1% inhibition on spore production and mycelial growth, causing hyphal deformities.DiscussionThis study presents the innovative use of B. velezensis, isolated from maize rhizosphere in cold conditions to effectively control MSR caused by F. graminearum. The findings highlight the remarkable regional and adaptive characteristics of this strain, making it an excellent candidate to fight MSR in diverse environments. In conclusion, B. velezensis B105-8 demonstrated potential as a biocontrol agent for MSR.

The treatment of oral squamous cell carcinoma (OSCC) remains a significant difficulty, as there has been no improvement in survival rates over the past fifty years. Hence, exploration and confirmation of new dependable treatment targets and biomarkers is imperative for OSCC therapy. TEAD transcription factors are crucial for integrating and coordinating multiple signaling pathways that are essential for embryonic development, organ formation, and tissue homeostasis. In addition, by attaching to coactivators, TEAD modifies the expression of genes such as Cyr61, Myc, and connective tissue growth factor, hence facilitating tumor progression. Therefore, TEAD is regarded as an effective predictive biomarker due to its significant connection with clinical parameters in several malignant tumors, including OSCC. The efficacy of existing drugs that specifically target TEAD has demonstrated encouraging outcomes, indicating its potential as an optimal target for OSCC treatment. This review provides an overview of current targeted therapy strategies for OSCC by highlighting the transcription mechanism and involvement of TEAD in oncogenic signaling pathways. Finally, the feasibility of utilizing TEAD as an innovative approach to address OSCC and its potential clinical applications were analyzed and discussed.

Lung squamous cell carcinoma (LUSC) is the second most common pathological type of non-small cell lung cancer (NSCLC). However, compared with lung adenocarcinoma (LUAD), the incidence of driver gene mutations in LUSC is relatively lower and treatment options for LUSC patients are very limited. We described a LUSC patient with a novel FGFR3-IER5L fusion revealed by next generation sequencing in this report. The patient refused surgery, radiotherapy or chemotherapy and received anlotinib treatment. Anlotinib is a small molecular multi-target tyrosine kinase inhibitor, which can inhibit the activity of kinases including vascular endothelial growth factor receptor 2/3 (VEGFR2/3), fibroblast growth factor receptor 1-4 (FGFR1-4), platelet-derived growth factor receptor α/β (PDGFRα/β), and c-Kit. The patient achieved partial response and the progression-free survival was 3.8 months.

Generalized fear is a maladaptive behavior in which non-threatening stimuli elicit a fearful response. The ventral tegmental area (VTA) has been demonstrated to play important roles in fear response and fear memory generalization, but the precious neural circuit mechanism is still unclear. Here, we demonstrated that VTA-zona incerta (ZI) glutamatergic projection is involved in regulating high-intensity threatening training induced generalization and anxiety. Combining calcium signal recording and chemogentics, our work reveals that VTA glutamatergic neurons respond to closed arm entering in the model of PTSD. Inhibition of VTA glutamatergic neurons or the glutamatergic projection to ZI could both relieve fear generalization and anxiety. Together, our study proves the VTA - ZI glutamatergic circuit is involved in mediating fear generalization and anxiety, and provides a potential target for treating post-traumatic stress disorder.

BackgroundAs the global population ages, we witness a broad scientific and technological revolution tailored to meet the health challenges of older adults. Over the past 25 years, technological innovations, ranging from advanced medical devices to user-friendly mobile apps, are transforming the way we address these challenges, offering new avenues to enhance the quality of life and well-being of the aging demographic. ObjectiveThis study aimed to systematically review the development trends in technology for managing and caring for the health of older adults over the past 25 years and to project future development prospects. MethodsWe conducted a comprehensive bibliometric analysis of literatures related to technology-based solutions for health challenges in aging, published up to March 18, 2024. The search was performed using the Web of Science Core Collection, covering a span from 1999 to 2024. Our search strategy was designed to capture a broad spectrum of terms associated with aging, health challenges specific to older adults, and technological interventions. ResultsA total of 1133 publications were found in the Web of Science Core Collection. The publication trend over these 25 years showed a gradual but fluctuating increase. The United States was the most productive country and participated in international collaboration most frequently. The predominant keywords identified through this analysis included “dementia,” “telemedicine,” “older-adults,” “telehealth,” and “care.” The keywords with citation bursts included “telemedicine” and “digital health.” ConclusionsThe scientific and technological revolution has significantly improved older adult health management, particularly in chronic disease monitoring, mobility, and social connectivity. The momentum for innovation continues to build, with future research likely to focus on predictive analytics and personalized health care solutions, further enhancing older adults’ independence and quality of life.

In-58, a peptide derived from indolicidin, shows extraordinary antibacterial activity and lower toxicity than indolicidin toward mammalian cells. Here, we investigated the antifungal activity of In-58 against the human pathogen Sporothrix globosa in vitro and in vivo. In-58 markedly inhibited the growth of Sporothrix globosa isolates in microdilution assays and showed no antagonism with any tested antifungal agent (itraconazole, terbinafine or amphotericin B). Scanning electron microscopy and propidium iodide staining indicated that In-58 alters the cell wall integrity and interacts with DNA, leading to disruption of S. globosa in a dose-dependent manner. In S. globosa, the mitochondrial membrane potential decreased and reactive oxygen species increased after treatment with In-58. In vivo experiments in the Galleria mellonella (greater wax moth) larval infection model revealed the effectiveness of In-58 against S. globosa infection with low toxicity. Our results indicate that In-58 possesses remarkable antifungal activity against S. globosa in vitro and in vivo. It has potential as a novel drug for the treatment of sporotrichosis.

BackgroundSystemic immune-inflammatory markers combine various individual inflammatory cell parameters to comprehensively explore their relationship with the development and long-term outcomes of cardiovascular, cerebrovascular, and oncological disorders. The systemic immune-inflammatory marker index has not been extensively studied in terms of its impact on the long-term prognosis following cerebral revascularization in MMD patients. Our research aims to address this gap and improve the prediction of long-term outcomes for these patients.MethodsWe included 851 patients with Moyamoya disease who underwent cerebral revascularization at our medical center from 2009 to 2021. Systemic immune-inflammatory markers were calculated based on routine blood test results at admission, and follow-up was conducted for over 6 months after surgery. During monitoring and upon release, we evaluated patient neurological condition by utilizing the modified Rankin Scale (mRS). We examined the correlation between alterations in mRS ratings and systemic immune-inflammatory markers.ResultsComparing the unfavorable long-term prognosis group to the favorable long-term prognosis group, it was found that the NLR level was markedly higher (p = 0.037), while the LMR was lower in the unfavorable long-term prognosis group (p = 0.004). Results from logistic regression analysis revealed that the high-level LMR group had a lower risk of unfavorable long-term prognosis compared to the low-level group (T3: OR = 0.433, 95% CI [0.204–0.859], p = 0.026). The AUC of the model was 0.750 (95% CI [0.693–0.806]).ConclusionLymphocyte-to-monocyte ratio levels are independently linked to an increased risk of unfavorable long-term prognosis, highlighting LMR as a new and effective predictor for postoperative Moyamoya patients.

Background: The elevated long-term cardiovascular disease (CVD) risks associated with pneumonia have been observed among inpatients, yet the risks associated with outpatients are less understood. Methods: We used register-based data and a matched cohort design, including 98,354 pneumonia inpatients and 44,486 outpatients, as well as a 5-fold number of matched healthy controls. Associations between pneumonia presentation (in inpatient and outpatient settings) and long-term CVD risks were measured by rate difference and hazard ratio (HR) using Poisson and Cox regressions in a time-dependent manner. Results: During a maximum follow-up period of 5.7 years of ischemic heart disease (IHD), heart failure (HF), and stroke were documented among pneumonia inpatients.Relative to healthy controls, pneumonia patients showed increased risks of IHD, HF, and stroke. Women and young inpatients demonstrated stronger associations of CVD with pneumonia; inpatients aged 60 years or older showed the highest excessive CVD risks. Conclusions: Pneumonia demanding outpatient and inpatient cares are intermediate-term and long-term risk factors of incident CVDs respectively, underscoring the need to plan setting-specific and time-dependent CVD-preventive cares following pneumonia presentation.

ABSTRACT: High-laying ducks are often fed high-energy, nutritious feeds to maintain high productivity, which predisposes them to lipid metabolism disorders and the development of fatty liver syndrome (FLS), which seriously affects production performance and has a substantial economic impact on the poultry industry. Therefore, it is necessary to elucidate the mechanisms underlying the development of fatty liver syndrome. In this study, seven Shan Partridge ducks, each with fatty liver syndrome and normal laying ducks, were selected, and Hematoxylin Eosin staining (HE staining), Masson staining, and transcriptome sequencing were performed on liver tissue. In addition to exploring key genes and pathways using conventional analysis methods, we constructed the first Kyoto Encyclopedia of Genes and Genomes (KEGG) database-based predefined gene set containing 12,764 pathways and 16,836 genes and further performed gene set enrichment analysis (GSEA) on the liver transcriptome data. Finally, key nodes and biological processes were identified via the protein-protein interaction (PPI) network. The results showed that the liver in the FL group exhibited steatosis and fibrosis, and a total of 3,663 genes with upregulated expression versus 2,296 downregulated genes were screened by conventional analysis. GSEA analysis and PPI network analysis revealed that the liver in the FL group exhibited disruption of the mitochondrial electron transport chain, leading to decreased oxidative phosphorylation and the secretion of excessive proinflammatory factors amid the continuous accumulation of lipids. Under continuous chronic inflammation, cell cycle arrest triggers apoptosis, while fibrosis becomes more severe, and procarcinogenic genes are activated, leading to the continuous development and deterioration of the liver. In conclusion, the predefined gene set constructed in this study can be used for GSEA, and the identified hub genes provide useful reference data and a solid foundation for the study of the genetic regulatory mechanism of fatty liver syndrome in ducks.

Mangrove wetlands, characterized by high biodiversity and crucial ecological functions, have witnessed extensive restoration efforts in China in recent decades. Despite the successful recovery of standing vegetation, the alterations in below-ground microbial communities, vital engines for completing biogeochemical cycles in wetlands, remain poorly understood. Here, the prokaryotic and microeukaryotic communities in restored mangrove forests (RMF) and natural mangrove forests (NMF) in Shenzhen, the world’s first International Mangrove Center in China were investigated and compared. This work aimed to explore an appropriate sampling strategy for sedimentary microbial community biodiversity study and evaluate their heterogeneity and network stability in RMF and NMF. The results revealed that a “broad-coverage and sparse-spot” sampling strategy was conducive to ensuring a sufficient representation of microbial diversity in mangrove wetlands. Significant differences were found in microbial community structures of RMF and NMF, with the relative abundances of Myxococcales and Cerozoa as potential biomarkers, respectively. RMF displayed higher prokaryotic richness, microbial community dissimilarity, and spatial turnover rate compared to those of NMF, indicating greater microbial diversity and spatial heterogeneity in RMF. Meanwhile, the RMF microbial network was characterized by lower complexity but higher modularity, robustness, and the ratio of negative to positive cohesion. These demonstrated that microbiomes were shaped by stability constraints and the RMF microbial network was more stable and resistant to environmental variations than that of NMF. Interestingly, the stability of these microbial networks appeared to depend on the topological roles of key species rather than on their abundance. Overall, this study disclosed a kind of relationship between the aboveground elements of restored and natural mangrove forests and their belowground microbial communities. These findings provide references for comprehensive assessments of biodiversity, stability, and ecological restoration in mangrove ecosystems.

The dual energy X-ray transmission identification of coal gangue still faces challenges in thickness, hardening, afterglow, and fan-shaped effects, among which the parameters for 5-150 mm wide thickness coal gangue separation fluctuate significantly and the recognition rate is to be improved. Therefore, this paper proposes a multi-dimensional identification method of dual-energy X-ray transmission of coal gangue based on geometric feature constraints. This method distinguishes the thickness of coal gangue by two geometric features of the minimum circumscribed circle diameter and area of the target image, restricts the spatial distribution of X-ray transmission response characteristics, and then weakens the influence of defects from multiple dimensions. With a small amount of low-density coal and high-density gangue, the paper obtains X-ray transmission response characteristics, position characteristics, and geometric characteristics, and combine them with Relief-F feature selection to establish a strong feature combination. To test the recognition performance of multiple classifiers, medium Gaussian SVM is selected as the classification model for multi-dimensional methods. Taking strong feature combinations as input, the final decision model and classification of unknown coal gangue pixels are automatically created, and the separation parameter p-value is obtained through pixel transformation image processing method. The results show that there is a strong linear correlation between p-value and coal gangue density, and density can be used to select p-value to regulate sorting. The p-value shows a weak linear correlation with the thickness of coal gangue. Within a wide thickness range, the p-value has a small degree of dispersion and good separability, giving separation parameters a large adjustment space. The mass experimental verification results show that the p-value of the multi-dimensional method for pre discharge gangue separation parameter is 33.01%. Using this separation parameter to identify coal gangue with different densities and coal types, the overall recognition rate reaches 99.57%. The overall recognition rate of raw coal pre discharge gangue in the thickness range of 5-150 mm is 99.37%. Compared with H-L method and R-L method, the multi-dimensional method has higher recognition rate, and the p-value calculated for coal gangue with different thickness has higher accuracy and better consistency. It demonstrates the effectiveness of multi-dimensional recognition methods under geometric feature constraints and the advantages of separation parameter regulation, which is of design reference meaning for current dual energy X-ray coal gangue separation device recognition algorithms.

Abstract Multicomponent oxides are intriguing materials in heterogeneous catalysis, and the interface between various components often plays an essential role in oxidations. However, the underlying principles of how the hetero-interface affects the catalytic process remain largely unexplored. Here we report a unique structure design of MnCoO x catalysts by chemical reduction, specifically for ethane oxidation. Part of the Mn ions incorporates with Co oxides to form spinel Mn x Co3-x O4, while the rests stay as MnO2 domains to create the MnO2-Mn x Co3-x O4 interface. MnCoO x with Mn/Co ratio of 0.5 exhibits an excellent activity and stability up to 1000 h under humid conditions. The synergistic effects between MnO2 and Mn x Co3-x O4 are elucidated, in which the C2H6 tends to be adsorbed on the interfacial Co sites and subsequently break the C-H bonds on the reactive lattice O of MnO2 layer. Findings from this study provide valuable insights for the rational design of efficient catalysts for alkane combustion.

Abstract Objective Bayesian network (BN) models were developed to explore the specific relationships between influencing factors and type 2 diabetes mellitus (T2DM), coronary heart disease (CAD), and their comorbidities. The aim was to predict disease occurrence and diagnose etiology using these models, thereby informing the development of effective prevention and control strategies for T2DM, CAD, and their comorbidities. Method Employing a case-control design, the study compared individuals with T2DM, CAD, and their comorbidities (case group) with healthy counterparts (control group). Univariate and multivariate Logistic regression analyses were conducted to identify disease-influencing factors. The BN structure was learned using the Tabu search algorithm, with parameter estimation achieved through maximum likelihood estimation. The predictive performance of the BN model was assessed using the confusion matrix, and Netica software was utilized for visual prediction and diagnosis. Result The study involved 3,824 participants, including 1,175 controls, 1,163 T2DM cases, 982 CAD cases, and 504 comorbidity cases. The BN model unveiled factors directly and indirectly impacting T2DM, such as age, region, education level, and family history (FH). Variables like exercise, LDL-C, TC, fruit, and sweet food intake exhibited direct effects, while smoking, alcohol consumption, occupation, heart rate, HDL-C, meat, and staple food intake had indirect effects. Similarly, for CAD, factors with direct and indirect effects included age, smoking, SBP, exercise, meat, and fruit intake, while sleeping time and heart rate showed direct effects. Regarding T2DM and CAD comorbidities, age, FBG, SBP, fruit, and sweet intake demonstrated both direct and indirect effects, whereas exercise and HDL-C exhibited direct effects, and region, education level, DBP, and TC showed indirect effects. Conclusion The BN model constructed using the Tabu search algorithm showcased robust predictive performance, reliability, and applicability in forecasting disease probabilities for T2DM, CAD, and their comorbidities. These findings offer valuable insights for enhancing prevention and control strategies and exploring the application of BN in predicting and diagnosing chronic diseases.

Introduction: Rice flowering is a major agronomic trait, determining yield and ecological adaptability in particular regions. ABA plays an essential role in rice flowering, but the underlying molecular mechanism remains largely elusive. Objectives: In this study, we demonstrated a “SAPK8-ABF1-Ehd1/Ehd2” pathway, through which exogenous ABA represses rice flowering in a photoperiod-independent manner. Methods: We generated abf1 and sapk8 mutants using the CRISPR-Cas9 method. Using yeast two-hybrid, Pull down, BiFC and kinase assays, SAPK8 interacted and phosphorylated ABF1. ABF1 directly bound to the promoters of Ehd1 and Ehd2 using ChIP-qPCR, EMSA, and LUC transient transcriptional activity assay, and suppressed the transcription of these genes. Results: Under both long day and short day conditions, simultaneous knock-out of ABF1 and its homolog bZIP40 accelerated flowering, while SAPK8 and ABF1 over-expression lines exhibited delayed flowering and hypersensitivity to ABA-mediated flowering repression. After perceiving the ABA signal, SAPK8 physically binds to and phosphorylates ABF1 to enhance its binding to the promoters of master positive flowering regulators Ehd1 and Ehd2. Upon interacting with FIE2, ABF1 recruited PRC2 complex to deposit H3K27me3 suppressive histone modification on Ehd1 and Ehd2 to suppress these genes transcription, thereby leading to later flowering. Conclusion: Our work highlighted the biological functions of SAPK8 and ABF1 in ABA signaling, flowering control and the involvement of a PRC2-mediated epigenetic repression mechanism in the transcription regulation governed by ABF1 on ABA-mediated rice flowering repression.

Abstract Background Transforming growth factor-β (TGF-β) is a cytokine with multiple functions, including cell growth regulation, extracellular matrix production, angiogenesis homeostasis adjustment and et al. TGF-β pathway activation promotes tumor metastasis/progression and mediates epithelial-mesenchymal transmission suppressing immunosurveillance in advanced tumors. GFH018, a small molecule inhibitor blocking TGF-β signal transduction, inhibits the progression and/or metastasis of advanced cancers. This first-in-human study evaluated the safety, tolerability, pharmacokinetics (PK), and efficacy of GFH018 monotherapy in patients with advanced solid tumors. Methods This phase I, open-label, multicenter study used a modified 3+3 dose escalation and expansion design. Adult patients with advanced solid tumors failing the standard of care were enrolled. Starting at 5 mg, eight dose levels up to 85 mg were evaluated. Patients received GFH018 BID (14d-on/14d-off) starting on the 4th day after a single dose on cycle 1, day 1. Subsequent cycles were defined as 28 days. The study also explored the safety of 85 mg BID 7d-on/7d-off. Adverse events were graded using NCI criteria for adverse events (NCI-CTCAE v5.0). PK was analyzed using a noncompartmental method. Efficacy was evaluated using RECIST 1.1. Blood samples were collected for biomarker analysis. Results Fifty patients were enrolled and received at least one dose of GFH018. No dose-limiting toxicity occurred, and the maximum tolerated dose was not reached. Forty-three patients (86.0%) had at least one treatment-related adverse event (TRAE), and three patients (6.0%) had ≥ G3 TRAEs. The most common TRAEs (any grade/grade ≥3) were AST increased (18%/0%), proteinuria (14%/2%), anemia (14%/2%), and ALT increased (12%/0%). No significant cardiotoxicity or bleeding was observed. GFH018 PK was linear and dose-independent, with a mean half-life of 2.25–8.60 h from 5 – 85 mg. Nine patients (18.0%) achieved stable disease, and one patient with thymic carcinoma achieved tumor shrinkage, with the maximum target lesion decreased by 18.4%. Serum TGF-β1 levels were not associated with clinical responses. The comprehensive recommended dose for Phase II was defined as 85 mg BID 14d-on/14d-off. Conclusions GFH018 monotherapy presented a favorable safety profile without cardiac toxicity or bleeding. Modest efficacy warrants further studies, including combination strategies. Trial registration ClinicalTrial. gov ( https://www.clinicaltrials.gov/ ), NCT05051241. Registered on 2021-09-02.

Abstract Obesity is a metabolic disorder closely associated with profound alterations in gut microbial composition. However, the dynamics of species composition and functional changes in the gut microbiome in obesity remain to be comprehensively investigated. In this study, we conducted a meta-analysis of metagenomic sequencing data from both obese and non-obese individuals across multiple cohorts, totaling 1351 fecal metagenomes. Our results demonstrate a significant decrease in both the richness and diversity of the gut bacteriome and virome in obese patients. We identified 38 bacterial species including Eubacterium sp. CAG:274, Ruminococcus gnavus, Eubacterium eligens and Akkermansia muciniphila, and 1 archaeal species, Methanobrevibacter smithii, that were significantly altered in obesity. Additionally, we observed altered abundance of five viral families: Mesyanzhinovviridae, Chaseviridae, Salasmaviridae, Drexlerviridae, and Casjensviridae. Functional analysis of the gut microbiome indicated distinct signatures associated to obesity and identified Ruminococcus gnavus as the primary driver for function enrichment in obesity, and Methanobrevibacter smithii, Akkermansia muciniphila, Ruminococcus bicirculans, and Eubacterium siraeum as functional drivers in the healthy control group. Additionally, our results suggest that antibiotic resistance genes and bacterial virulence factors may influence the development of obesity. Finally, we demonstrated that gut vOTUs achieved a diagnostic accuracy with an optimal area under the curve of 0.766 for distinguishing obesity from healthy controls. Our findings offer comprehensive and generalizable insights into the gut bacteriome and virome features associated with obesity, with the potential to guide the development of microbiome-based diagnostics.

Abstract The dietary inflammatory index (DII) is a measure of the inflammatory potential of the diet and is closely associated with insulin resistance (IR) and stroke. And IR may play an important role in the development of stroke. Therefore, this study aimed to evaluate the relationship between DII and stroke risk while delving into the potential role of IR in this association. We analyzed data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, performing weighted univariate analyses, logistic regression, and mediation analyses. At baseline, 3.89% of participants developed stroke, and we observed stroke patients exhibited higher DII scores. After adjusting for covariates, compared to participants in the first quartile of DII scores, those in the third quartile and fourth quartile had increased odds of experiencing a stroke (OR: 1.78, 95% CI: 1.18–2.68) and (OR: 1.70, 95% CI: 1.16–2.50), respectively. Moreover, a significant dose–response relationship was observed (P-trend

Abstract Enterotoxigenic E. coli is one of the bacterial pathogens contributing to the global resistance crisis in public health and animal husbandry. The problem of antibiotic resistance is becoming more and more serious, and phage is considered one of the potential alternatives to antibiotics that could be utilized to treat bacterial infections. Our study isolated and identified a lytic phage PGX1 against multidrug-resistant enterotoxigenic E. coli EC6 strain from sewage. The phage lysis profile revealed that PGX1 exhibited a lytic effect on multidrug-resistant enterotoxigenic E. coli strains of serotype O60. Through phage whole genome sequencing and bioinformatics analysis, PGX1 was found to be the class Caudoviricetes, family Autographiviridae, genus Teseptimavirus. The length of the PGX1 genome is about 37,009 bp, containing 54 open reading frames (ORFs). Notably, phage PGX1 lacks any lysogenic-related genes or virulence genes. Furthermore, phage PGX1 demonstrates strong adaptability, tolerance, and stability in various pH (pH4-10) and temperatures (4–40°C). The in vivo and in vitro tests demonstrated that phage PGX1 significantly removes and inhibits the formation of multidrug-resistant EC6 biofilm and effectively controls the Galleria mellonella larvae and enterotoxigenic E. coli EC6 during mice infection. In conclusion, the above findings demonstrated that phage PGX1 may be a novel antimicrobial agent to control multidrug-resistant E. coli infections.

Abstract TMEFF1 is a new protein involved in the physiological functions of the central nervous system, and we previously reported TMEFF1 can promote ovarian cancer. ST14 was determined to be involved in the processes of epidermal differentiation, epithelial cell integrity, and vascular endothelial cell migration, etc. The relationship between ST14 and TMEFF1 in the ovary remains unknown. In this study, we detected the expression of ST14 and TMEFF1 in 130 different ovarian cancer tissues through immunohistochemistry. We determined ST14 and TMEFF1 were highly expressed in ovarian cancer, indicating a higher degree of tumor malignancy and a worse prognosis. Tissues significantly expressing ST14 also highly expressed TMEFF1, and the expression of the two proteins was positively correlated. Consistently, immunofluorescence double staining demonstrated the co-localization of ST14 and TMEFF1 in the same region, and immunoprecipitation confirmed the interaction between ST14 and TMEFF1. TMEFF1 expression was also reduced after knocking down ST14 through Western blot. MTT, wound healing and Transwell assays results determined that knockdown of ST14 inhibited proliferation, migration and invasion of ovarian cancer cells in vitro, but the inhibitory effect was restored after adding TMEFF1 exogenous protein. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways analysis showed that ST14 and its related genes were enriched in the processes of epithelial formation, intercellular adhesion, protein localization, and mitosis regulation. We also clarified the kinase, microRNA, and transcription factor target networks and the impact of genetic mutations on prognosis. Overall, high expression of ST14 and TMEFF1 in ovarian cancer predicts higher tumor malignancy and a worse prognosis. ST14 and TMEFF1 co-localize and interact with each other in ovarian cancer. ST14 can regulate TMEFF1 expression to promote proliferation, migration and invasion of ovarian cancer cells. We speculate that the relationship between ST14 and TMEFF1 in ovarian cancer could become a potential target for anti-cancer therapy.

Abstract Combined straw and straw-derived biochar input is commonly applied by farmland management in low-fertility soils. Although straw return increases soil organic matter (SOM) contents, it also primes SOM mineralization. The mechanisms by which active microorganisms mineralize SOM and the underlying factors remain unclear for such soils. To address these issues, paddy soil was amended with 13C-labeled straw, with and without biochar (BC) or ferrihydrite (Fh), and incubated for 70 days under flooded conditions. Compound-specific 13C analysis of phospholipid fatty acids (13C-PLFAs) allowed us to identify active microbial communities utilizing the 13C-labeled straw and specific groups involved in SOM mineralization. Cumulative SOM mineralization increased by 61% and 27% in soils amended with Straw + BC and Straw + Fh + BC, respectively, compared to that with straw only. The total PLFA content was independent of the straw and biochar input. However, 13C-PLFAs contents increased by 35–82% after biochar addition, reflecting accelerated microbial turnover. Compared to that in soils without biochar addition, those with biochar had an altered microbial community composition-increased amounts of 13C-labeled gram-positive bacteria (13C-Gram +) and fungi, which were the main active microorganisms mineralizing SOM. Microbial reproduction and growth were susceptible to nutrient availability. 13C-Gram + and 13C-fungi increased with Olsen P but decreased with dissolved organic carbon and $${\text{NO}}_{3}^{ - }$$ NO 3 - contents. In conclusion, biochar acts as an electron shuttle, stimulates iron reduction, and releases organic carbon from soil minerals, which in turn increases SOM mineralization. Gram + and fungi were involved in straw decomposition in response to biochar application and responsible for SOM mineralization. Graphical Abstract