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Flavonoid glycosides are widespread in plants, and are of great interest owing to their diverse biological activities and effectiveness in preventing chronic diseases. Periploca forrestii, a renowned medicinal plant of the Apocynaceae family, contains diverse flavonoid glycosides and is clinically used to treat rheumatoid arthritis and traumatic injuries. However, the mechanisms underlying the biosynthesis of these flavonoid glycosides have not yet been elucidated. In this study, we used widely targeted metabolomics and full-length transcriptome sequencing to identify flavonoid diversity and biosynthetic genes in P. forrestii. A total of 120 flavonoid glycosides, including 21 C-, 96 O-, and 3 C/O-glycosides, were identified and annotated. Based on 24,123 full-length coding sequences, 99 uridine diphosphate sugar-utilizing glycosyltransferases (UGTs) were identified and classified into 14 groups. Biochemical assays revealed that four UGTs exhibited O-glycosyltransferase activity toward apigenin and luteolin. Among them, PfUGT74B4 and PfUGT92A8 were highly promiscuous and exhibited multisite O-glycosylation or consecutive glycosylation activities toward various flavonoid aglycones. These four glycosyltransferases may significantly contribute to the diversity of flavonoid glycosides in P. forrestii. Our findings provide a valuable genetic resource for further studies on P. forrestii and insights into the metabolic engineering of bioactive flavonoid glycosides.

Abstract Background In an aging society, depression has become a public health challenge that can lead to many adverse health outcomes; evidence addressing the link between depression and motor cognitive risk syndrome (MCR, a novel syndrome that effectively predicts dementia) is still lacking. Methods A PRISMA checklist was used to systematically review the relevant peer-reviewed literature for the primary data analysis. A computer search of CNKI, Wan Fang Data, CBM, VIP, PubMed, Web of Science, Embase, Cochrane Library, Scopus, and Ovid databases, all from creation to March 15, 2023. A meta-analysis was conducted using Stata 17.0, the Newcastle-Ottawa Scale instrument (NOS), and the Agency for Healthcare Research and Quality (AHRQ) for quality appraisal. We used Q and I2 statistics to assess heterogeneity and random effects models to pool estimates. Egger’s regression tests and adjustments were made using the trim and fill test. Result Thirteen studies were included, including seven cross-sectional studies and six cohort studies, and data on the association between depression and MCR in the elderly were extracted. Moreover, the results of the meta-analysis showed that there was a significant correlation between depression and MCR in the cross-sectional study [OR = 2.43, 95% CI(1.31 ~ 3.54), P

Introduction: The interplay between influential factors and the incidence of subthreshold depression (SD) in young adults remains poorly understood. Objectives: This study sought to understand the dietary habits, gut microbiota composition, etc. among individuals with SD in young adults and to investigate their association with SD occurrence. Methods: Employing a cross-sectional approach, 178 individuals with SD, aged 18–32 years, were matched with 114 healthy counterparts. SD status was evaluated using the Zung Self-rating Depression Scale (SDS), Zung Self-rating Anxiety Scale (SAS), Beck Depression Inventory 2nd version (BDI-II), the 17-item Hamilton Rating Scales of Depression (HAMD-17), and Pittsburgh Sleep Quality Index (PSQI). Metagenomic sequencing was utilized to identify fecal microbial profiles. Dietary patterns were discerned via factor analysis of a 25-item food frequency questionnaire (FFQ). Logistic regression analysis and mediation analysis were performed to explore the potential links between gut microbiota, dietary patterns, and incident SD. Results: Data on dietary habits were available for 292 participants (mean [SD] age, 22.1 [2.9] years; 216 [73.9 %] female). Logistic regression analysis revealed that dietary patterns Ⅰ (odds ratio [OR], 0.34; 95 % CI, 0.15–0.75) and IV (OR, 0.39; 95 % CI, 0.17–0.86 and OR, 0.39; 95 % CI, 0.18–0.84) were associated with reduced risk of SD. Distinct microbial profiles were observed in young adults with SD, marked by increased microbial diversity and taxonomic alterations. Moreover, mediation analysis suggested Veillonella atypica as a potential mediator linking SDS or BDI-II scores with a healthy dietary pattern rich in bean products, coarse grains, nuts, fruits, mushrooms, and potatoes (β = 0.25, 95 % CI: 0.02–0.78 and β = 0.18, 95 % CI: 0.01–0.54). Conclusions: Our findings highlight the complex interplay between dietary patterns, gut microbiota, and the risk of developing SD in young adults, underscoring the potential for dietary interventions and microbiome modulation in mental health promotion.

Abstract Objectives This study aims to reveal the current knowledge map, research hotspots of functional magnetic resonance imaging (fMRI) studies on depression, as well as identify the brain regions associated with depression. Methods CiteSpace was conducted to analyze the publication outputs, country, institution, cited journals, author and cited author, references, keyword cocurrence and burst keywords of fMRI studies in depression from 2010 to 2024. And a meta-analysis of fMRI was used to identify brain regions associated with depression using Neurosynth. Results A total of 4,049 publications were included, and Gong Qiyong was the most prolific authors. Neuroimage, Biological Psychiatry, and Human Brain Mapping were prominent journals. Default mode network (DMN), prefrontal cortex, amygdala, and anterior cingulate cortex were the popular keywords. The fMRI studies on depression have mainly focused on major depression, especially the DMN. Functional connectivity and regional homogeneity of brain regions were research hotspots. The meta-analysis revealed significant differences in brain regions between patients with depression and healthy controls, including the Amygdala_L, Insula_R, Frontal_Inf_Oper_R, Cingulum_Post_L, Putamen_L, Thalamus_R, Angular_L, Precuneus_R, Frontal_Sup_R, Occipital_Inf_L. Conclusions This study sheds light on key issues and future directions in fMRI research on depression, elucidating the brain regions related to depression. Graphical Abstract

Abstract Background and aims Human papillomavirus (HPV) infection is widespread. The regional differences in infection rates and dominant HPV types are a significant aspect of the virus’s epidemiological characteristics. In China, these differences are further influenced by the country’s diverse ethnic composition, as well as varying economic and cultural conditions across regions. Additionally, factors such as population migration contribute to the exacerbation of these regional disparities in HPV infection rates. Methods We conducted an analysis of the current prevalence of HPV among 108,863 patients in Chongqing from 2017 to 2022, along with an investigation into the interaction between HPV and vaginal microbiota. Additionally, we explored the relationship between HPV clearance time and disease outcomes. Results Our findings revealed an overall HPV positive rate of 30.14% (32,813/108,863) in Chongqing, China. The top five HPV positive rates were as follows: HPV52 (7.78%), HPV16 (5.85%), HPV58 (4.41%), HPV53 (3.17%), and HPV39 (2.47%). The age-related trend of HPV infection exhibited a bimodal curve. Importantly, the positive rate of high-risk HPV (BV: 24.74%, AV: 24.38%, VVC: 18.19%, TV: 22.81%) was significantly higher than those in the control group (all P

Abstract SASH1 (SAM and SH3 domain containing 1) has been increasingly reported as a tumor suppressor gene. However, there is limited research on the role of SASH1 in breast cancer. This manuscript aims to investigate the mechanism of SASH1 in the occurrence, development, and prognosis of breast cancer. Firstly, we obtained RNA-sequencing data of the tumors from the Genomic Data Commons data portal website, along with the corresponding clinical information of patients. Pan-cancer analysis was performed to analyze the expression of SASH1 across all tumors. Univariate Cox regression analysis was used to assess the correlation between SASH1 expression and the prognosis of breast cancer patients. Then, immunohistochemistry was utilized to evaluate the expression levels of SASH1, p-Akt, p-PI3K, and p-mTOR in breast cancer tissue. Finally, a cell assay was employed to analyze the impact of SASH1 on the proliferation and invasion of breast cancer cells (MDA-MB-231). The results revealed that SASH1 expression is decreased in BRCA, LUSC, LUAD, CESC, ESCA, and COAD. Meta-analysis also found that SASH1 is downregulated in most tumor tissues, and the expression level of SASH1 in breast cancer was significantly lower than that in the control group (OR = 0.14, 95% CI = 0.08–0.25; P

Evaluation of the suitability of university ladder classroom environment on humans is an effective approach to improve the quality of the indoor environment and protect human health. However, there are unresolved issues regarding the suitability of university ladder classroom environment for humans. For example, the design of enclosure structure and heating ventilation and air conditioning (HVAC) system is unreasonable, and the indoor air quality does not meet the required standard. In this study, the suitability of university ladder classroom environment on humans was considered the research object. The evaluation indices of indoor environment were selected from indoor air quality, indoor thermal and humid environments, light environment, and sound environment. And the health and comfort of users were taken as the evaluation indices of users. According to the results of expert investigations and case measurements, the index weight was determined by the expert-entropy weight method, and a complete evaluation system of indices was built. There were two first-level, six second-level, and fourteen third-level indices in the evaluation system. The evaluation indices of each level with the largest weight were indoor environment (0.5940), user health (0.2530), and indoor temperature (0.1175) respectively. By comparing the actual learning effect to the evaluation results, the applicability of the evaluation system was determined. The evaluation system of the suitability of university ladder classroom environment on humans is convenient for operators to identify the weak points between humans and the environment. The evaluation system is endowed with important theoretical and practical significance to realize the green development of colleges and universities and build an environment-friendly campus.

The detailed seepage process and rainfall infiltration temporal variation cannot be observed visually due to the complexity and non-visibility of the internal structure of landslide body, thus making it difficult to identify the specific process of rainfall in the whole process of landslide catastrophic evolution, which leads to the incomplete understanding of the formation mechanism of rainfall-induced landslide. Therefore, the new technological methods for directly observing and monitoring the infiltration and seepage process of rainfall-induced landslide is of great significance for deep understanding the formation mechanism of landslide induced by raining. Transparent soil test technology enables non-invasive, continuous, non-destructive and visual measurement or monitoring inside soil or rock mass bodies. In this paper, the current status of the development of transparent soil testing technology and its application in different fields especially in the application of slope engineering and practice in the visual simulation of seepage processes are summarized from the aspects of transparent soil material properties, geotechnical engineering properties, experimental equipment and image processing analysis technology, and the feasibility of applying it to the visual observation of seepage in landslide is discussed. On this basis, the transparent soil material is screened and the preparation method is optimized. The transparent soil is used to replace the traditional geotechnical model material to establish a landslide transparent soil physical model suitable for seepage process observation. The physical simulation test of landslide seepage under rainfall conditions is carried out to obtain information on the whole process of rainfall infiltration-induced landslide disaster, and to determine the process and characteristics of the seepage process of the groundwater. The model test is an effective application of transparent soil test technology in the field of landslide seepage visual observation, expanding a new way of landslide disaster visual simulation, and further determining the complex impact of groundwater seepage on landslide. It is conducive to reveal the evolution law of rainfall-induced landslide, explore the sliding mechanism of landslide, and provide a scientific and technological support for rainfall landslide disaster prevention and disaster planning.

Abstract Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by hyperglycemia resulting from defects in insulin secretion and/or insulin action. Increasing evidence suggests that inflammation played an important role in the pathogenesis of T2DM. Prospective studies on the link between immunoglobulins concentrations and the risk of T2DM in adults are limited. We developed a cohort study including 7,093 adults without T2DM history. The incidence of T2DM was 16.45 per 1,000 person-years. Compared with the lowest quartiles, the hazard ratios (95% confidence intervals) of T2DM for the highest quartiles of IgG, IgE, IgM and IgA were 0.64 (0.48–0.85), 0.94 (0.72–1.23), 0.68 (0.50–0.92) and 1.62 (1.24–2.11) (P for trend was

Abstract Background Tooth segmentation on intraoral scanned (IOS) data is a prerequisite for clinical applications in digital workflows. Current state-of-the-art methods lack the robustness to handle variability in dental conditions. This study aims to propose and evaluate the performance of a convolutional neural network (CNN) model for automatic tooth segmentation on IOS images. Methods A dataset of 761 IOS images (380 upper jaws, 381 lower jaws) was acquired using an intraoral scanner. The inclusion criteria included a full set of permanent teeth, teeth with orthodontic brackets, and partially edentulous dentition. A multi-step 3D U-Net pipeline was designed for automated tooth segmentation on IOS images. The model’s performance was assessed in terms of time and accuracy. Additionally, the model was deployed on an online cloud-based platform, where a separate subsample of 18 IOS images was used to test the clinical applicability of the model by comparing three modes of segmentation: automated artificial intelligence-driven (A-AI), refined (R-AI), and semi-automatic (SA) segmentation. Results The average time for automated segmentation was 31.7 ± 8.1 s per jaw. The CNN model achieved an Intersection over Union (IoU) score of 91%, with the full set of teeth achieving the highest performance and the partially edentulous group scoring the lowest. In terms of clinical applicability, SA took an average of 860.4 s per case, whereas R-AI showed a 2.6-fold decrease in time (328.5 s). Furthermore, R-AI offered higher performance and reliability compared to SA, regardless of the dentition group. Conclusions The 3D U-Net pipeline was accurate, efficient, and consistent for automatic tooth segmentation on IOS images. The online cloud-based platform could serve as a viable alternative for IOS segmentation.

BackgroundAs individuals age, they commonly experience reduced physical activity and cognitive decline. While evidence, there is limited trajectory research on their concurrent progression and interrelation in individuals over 55 years old.MethodsThe data was collected from 5,765 individuals aged over 55 years who participated in the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2020. Physical activity was measured by IPAQ, cognitive function by episodic memory, and mental intactness score. Separate sets of group-based trajectory models were fitted to identify physical activity trajectories and cognitive function trajectories. Multivariate logistic regression was used to estimate the association between baseline characteristics and each set of trajectories. Group-based dual trajectory modeling (GBDTM) was applied to quantify these associations.ResultsGBDTM identified three distinct trajectory groups for physical activity and cognitive outcomes. The physical activity trajectories were classified as “Persistently low physical activity” (74.2%), “Decreasing physical activity” (13.7%), and “Rising physical activity” (12.1%). Similarly, cognitive function trajectories were categorized as “Persistently low cognitive function” (22.2%), “Persistently moderate cognitive function” (37.9%), and “Persistently high cognitive function” (39.9%). Notably, 15.6% of participants followed the trajectories of “Persistently low physical activity” and “Persistently low cognitive function.” The presence of a severe decline in physical activity was associated with an increased likelihood of poor cognitive function and vice versa. Age, sex, education, residential status, BMI, and visual impairment were identified as significant predictors for physical activity and cognitive decline.ConclusionThis study found that the GBDTM can determine the consistent trajectories of physical activity and cognitive function trajectories that persistently decline in individuals over 55 years. Analyses of predictive factors can be instrumental in promoting physical activity and delaying cognitive decline.

A series of para-quinone methide derivatives were evaluated their anti-inflammatory activity. Through the screening of the lipopolysaccharide (LPS)-induced inflammatory cell model in Raw264.7 cells, it was found that the inhibitory activity of meta-substituted derivatives on NO production was superior to that of ortho- and para-substituted derivatives. Among them, in the inflammatory cell model, the meta-trifluoromethyl substituted para-quinone methide derivative 1i had the best activity in inhibiting LPS-induced excess generation of NO. And 1i could effectively inhibit the increase of ROS in inflammatory cells, the expression of iNOS related to the production of NO, and the expressions of inflammation related initiating protein TLR4, pro-inflammatory cytokines IL-6 and TNF-α, inflammasome NLRP3 and Caspase1. In the dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) mouse model, the active derivative 1i could inhibit DSS-induced colon shortening, and reverse DSS-induced pathological changes in colon tissue, such as inflammatory infiltration, structural destruction and crypt disappearance. 1i could effectively inhibit oxidative stress, inflammation and apoptosis in UC mice. Moreover, through the determination of serum biochemical indicators, tissue pathologies and tissue organ indexes, 1i could effectively reverse the damage to mouse liver and kidney caused by DSS, playing a protective role in liver and kidney of mice. In summary, 1i was an effective anti-inflammatory reagent and could be developed as a potential drug for anti-UC.

Abstract Background Mild cognitive impairment has received widespread attention as a high-risk population for Alzheimer’s disease, and many studies have developed or validated predictive models to assess it. However, the performance of the model development remains unknown. Objective The objective of this review was to provide an overview of prediction models for the risk of Alzheimer’s disease dementia in older adults with mild cognitive impairment. Method PubMed, EMBASE, Web of Science, and MEDLINE were systematically searched up to October 19, 2023. We included cohort studies in which risk prediction models for Alzheimer’s disease dementia in older adults with mild cognitive impairment were developed or validated. The Predictive Model Risk of Bias Assessment Tool (PROBAST) was employed to assess model bias and applicability. Random-effects models combined model AUCs and calculated (approximate) 95% prediction intervals for estimations. Heterogeneity across studies was evaluated using the I 2 statistic, and subgroup analyses were conducted to investigate sources of heterogeneity. Additionally, funnel plot analysis was utilized to identify publication bias. Results The analysis included 16 studies involving 9290 participants. Frequency analysis of predictors showed that 14 appeared at least twice and more, with age, functional activities questionnaire, and Mini-mental State Examination scores of cognitive functioning being the most common predictors. From the studies, only two models were externally validated. Eleven studies ultimately used machine learning, and four used traditional modelling methods. However, we found that in many of the studies, there were problems with insufficient sample sizes, missing important methodological information, lack of model presentation, and all of the models were rated as having a high or unclear risk of bias. The average AUC of the 15 best-developed predictive models was 0.87 (95% CI: 0.83, 0.90). Discussion Most published predictive modelling studies are deficient in rigour, resulting in a high risk of bias. Upcoming research should concentrate on enhancing methodological rigour and conducting external validation of models predicting Alzheimer’s disease dementia. We also emphasize the importance of following the scientific method and transparent reporting to improve the accuracy, generalizability and reproducibility of study results. Registration This systematic review was registered in PROSPERO (Registration ID: CRD42023468780).

Crocus sativus (saffron) is a globally autumn-flowering plant, and its stigmas are the most expensive spice and valuable herb medicine. Crocus specialized metabolites, crocins, are biosynthesized in distant species, Gardenia (eudicot) and Crocus (monocot), and the evolution of crocin biosynthesis remains poorly understood. With the chromosome-level Crocus genome assembly, we revealed that two rounds of lineage-specific whole genome triplication occurred, contributing important roles in the production of carotenoids and apocarotenoids. According to the kingdom-wide identification, phylogenetic analysis, and functional assays of carotenoid cleavage dioxygenases (CCDs), we deduced that the duplication, site positive selection, and neofunctionalization of Crocus-specific CCD2 from CCD1 members are responsible for the crocin biosynthesis. In addition, site mutation of CsCCD2 revealed the key amino acids, including I143, L146, R161, E181, T259, and S292 related to the catalytic activity of zeaxanthin cleavage. Our study provides important insights into the origin and evolution of plant specialized metabolites, which are derived by duplication events of biosynthetic genes.

Gastric cancer (GC) is a prevalent global malignancy, often diagnosed at advanced stage due to a lack of early symptoms and reliable markers. Previous research has identified gliomedin (GLDN) as a potential predictive marker for poor prognosis in cancer patients. However, the specific relationship between GLDN expression and GC prognosis has been unclear. Using the Tumor-Immune System Interaction Database (TISIDB), we examined GLDN expression in GC tissues and found a positive correlation with advanced clinical stages. Kaplan-Meier Plotter analysis further demonstrated that elevated GLDN levels were closely associated with poor prognosis in GC patients. To explore the functional significance of GLDN in GC, we conducted experiments involving GLDN overexpression and knockdown in GC cell lines, as well as subcutaneous tumor formation in nude mice. Our findings provided compelling evidence that GLDN promotes GC cell proliferation, viability, and migration, significantly enhancing tumor growth in vivo. Mechanistically, RNA-sequencing (RNA-seq) combined with bioinformatics analysis revealed that GLDN influences genes enriched in the p53 signaling pathway. Our data suggest that GLDN likely regulates cell proliferation through the p53-p21-CyclinD/CDK4 signaling axis. In conclusion, our study underscores GLDN's critical role in regulating GC cell proliferation and migration, and proposes its potential as a prognostic marker for GC patients.

Abstract Surface‐enhanced Raman scattering (SERS) imaging technology faces significant technical bottlenecks in ensuring balanced spatial resolution, preventing image bias induced by substrate heterogeneity, accurate quantitative analysis, and substrate preparation that enhances Raman signal strength on a global scale. To systematically solve these problems, artificial intelligence techniques are applied to analyze the signals of pesticides based on 3D and dynamic SERS imaging. Utilizing perovskite/silver nanoparticles composites (CaTiO3/Ag@BONPs) as enhanced substrates, enabling it not only to cleanse pesticide residues from the surface to pulp of fruits and vegetables, but also to investigate the penetration dynamics of an array of pesticides (chlorpyrifos, thiabendazole, thiram, and acetamiprid). The findings challenge existing paradigms, unveiling a previously unnoticed weakening process during pesticide invasion and revealing the surprising permeability of non‐systemic pesticides. Of particular note is easy to overlook that the combined application of pesticides can inadvertently intensify their invasive capacity due to pesticide interactions. The innovative study delves into the realm of pesticide penetration, propelling a paradigm shift in the understanding of food safety. Meanwhile, this strategy provides strong support for the cutting‐edge application of SERS imaging technology and also brings valuable reference and enlightenment for researchers in related fields.

As economically significant species, bivalves maintain intimate contact with external microorganisms during respiration and filter feeding, rendering them prime candidates for investigating microbial communities. Although numerous studies have been conducted on the microbial communities inhabiting the mantles, the composition and functions of the microbial community residing within the coloured mantles remain unclear. The pigments in the coloured areas may attract some microorganisms related to pigments. Thus, in vitro culture can be utilized to rapidly assess the fundamental characteristics of the microbial community present in the coloured mantles. Our results indicated that the microbial community in the coloured mantles of three bivalves (Crassostrea gigas, Mytilus edulis, and Chlamys farreri) responded differently to various media, resulting in pigmentation occurring on tyrosine medium. Further analyses by Metabarcoding revealed a relatively low abundance of melanin-producing strains on the surface of coloured mantles, which may be related to the requirement of melanin-producing strains for a specific nutritional environment. Then, we observed that there were significant differences in the composition of the microbial communities in coloured mantles of the three bivalves, with different bivalves possessing distinct biomarkers. These microorganisms affect the host by regulating the immune system and aiding digestion, nutrient absorption, and nitrification. Correlation analysis showed that multiple metabolites of the three bivalves were strongly correlated with bacterial biomarkers and may play an important role in maintaining the dynamic balance of surface microbial communities. In conclusion, this study discussed the multifaceted effects of microorganisms on the dynamic equilibrium of bivalves microbial communities, exploring the intricate connection between the host and the microbe, as well as the composition of microbial communities. This lays the foundation for comprehending the intricate symbiotic relationship between bivalves and their microbial counterparts and offers a theoretical foundation for the future development of microbial preparations intended for bivalves body surfaces.

MicroRNAs (miRNAs) represent a class of non-coding small RNAs that are prevalent in eukaryotes, typically comprising approximately 22 nucleotides, and have the ability to post-transcriptionally regulate gene expression. miRNAs exhibit diverse types and functions, with mechanisms of action that include cell differentiation, proliferation, apoptosis, and regulation of signaling pathways. Both viruses and their hosts can encode miRNAs, which serve as crucial effector molecules in the complex interaction between viruses and host cells. Host miRNAs can either directly interact with the virus genome to inhibit virus replication or facilitate virus replication by providing necessary substances. Viral miRNAs can directly bind to host mRNAs, thereby influencing translation efficiency, suppressing the immune response, and ultimately enhancing virus replication. This article comprehensively reviews the roles of miRNAs in virus-host interactions, aiming to provide valuable insights into viral pathogenic mechanisms and potential therapeutic approaches.

Abstract Background Small extracellular vesicles (EVs), exemplified by exosomes, mediate intercellular communication by transporting proteins, mRNAs, and miRNAs. Post-translational modifications are involved in controlling small EV secretion process. However, whether palmitoylation regulates small EV secretion, remains largely unexplored. Methods Vacuole Membrane Protein 1 (VMP1) was testified to be S-palmitoylated by Palmitoylation assays. VMP1 mutant plasmids were constructed to screen out the exact palmitoylation sites. Small EVs were isolated, identified and compared between wild-type VMP1 or mutant VMP1 transfected cells. Electron microscope and immunofluorescence were used to detect multivesicular body (MVB) number and morphology change when VMP1 was mutated. Immunoprecipitation and Mass spectrum were adopted to identify the protein that interacted with palmitoylated VMP1, while knock down experiment was used to explore the function of targeted protein ALIX. Taking human Sertoli cells (SCs) and human spermatogonial stem cell like cells (SSCLCs) as a model of intercellular communication, SSCLC maintenance was detected by flow cytometry and qPCR at 12 days of differentiation. In vivo, mouse model was established by intraperitoneal injection with palmitoylation inhibitor, 2-bromopalmitate (2BP) for 3 months. Results VMP1 was identified to be palmitoylated at cysteine 263,278 by ZDHHC3. Specifically, palmitoylation of VMP1 regulated its subcellular location and enhanced the amount of small EV secretion. Mutation of VMP1 palmitoylation sites interfered with the morphology and biogenesis of MVBs through suppressing intraluminal vesicle formation. Furthermore, inhibition of VMP1 palmitoylation impeded small EV secretion by affecting the interaction of VMP1 with ALIX, an accessory protein of the ESCRT machinery. Taking SCs and SSCLCs as a model of intercellular communication, we discovered VMP1 palmitoylation in SCs was vital to the growth status of SSCLCs in a co-culture system. Inhibition of VMP1 palmitoylation caused low self-maintenance, increased apoptosis, and decreased proliferation rate of SSCLCs. In vivo, intraperitoneal injection of 2BP inhibited VMP1 palmitoylation and exosomal marker expression in mouse testes, which were closely associated with the level of spermatogenic cell apoptosis and proliferation. Conclusions Our study revealed a novel mechanism for small EV secretion regulated by VMP1 palmitoylation in Sertoli cells, and demonstrated its pivotal role in intercellular communication and SSC niche.

Abstract The application of risk management strategies is a common approach in emergency response scenarios. However, scant knowledge exists regarding its utilization in the specific context of an outbreak, both theoretically and practically. This study delves into the realm of risk management during the COVID-19 pandemic, focusing on four key measurements: risk avoidance (RA), risk reduction (RD), risk transfer (RT), and risk retention (RR). Using 800 valid responses collected from 31 provinces across China between August 1 and September 30, 2020, this study investigates spatial disparities in individuals’ intentions towards risk management. To achieve this, an extended version of the Theory of Planned Behavior (E-TPB) is applied. The Structural Equation Model’s path analyses revealed several findings: (1) discernible spatial disparities in RR, RA, and RD intentions between large and small cities; (2) RD and RR intentions were significantly associated with attitude, subjective norm, perceived behavioral control, and risk perception; (3) RA and RT intentions were significantly associated with attitude and risk perception; (4) risk perception exihibiting both direct and indirect effects on RA and RR intentions. This study contributs to the urban studies literature by extending the theoretical framework of risk management in the context of COVID-19. It enhances the measurement tools employed in the TPB model and scrutinizes spatial disparities in the adoption of preventative measures against COVID-19. The findings underscore the importance for local policymakers to consider geographical differences when formulating effective strategies for COVID-19 prevention.

Persistent inflammation can trigger the development of colorectal cancer, especially in patients with inflammatory bowel disease (IBD). The precise molecular mechanisms underlying this process are not fully understood. This study investigated the molecular modifications that occur in the cellular microenvironment during inflammation-induced and colitis-associated cancers. Studies showed that genetic mutations and post-translational modifications of oncogene proteins can alter the biological functions of macrophage inflammatory proteins, complicating the intricate interactions between inflammation and cancer. The researchers also observed abnormal glycosylation patterns in cases of inflammation and colitis-associated cancers. This observation suggests that glycoproteins present in bodily fluids could potentially serve as valuable disease markers. Additionally, the researchers investigated general signaling alterations that manifest in cases of colitis-associated cancer. They proposed a provisional molecular model that suggests the involvement of endoplasmic reticulum (ER) stress during the transition from inflammation to cancer. This potential pathway is mediated through the FKBP/c-Myc/p53 signaling axis. In the context of protein glycosylation, we summarize the potential molecular mechanisms of IBD-induced carcinogenesis. This knowledge could potentially lead to the development of novel targets for the clinical treatment of colorectal cancer.

Abstract Background Predicting the prognosis of primary percutaneous coronary intervention(PPCI) in ST-segment elevation myocardial infarction (STEMI) patients in the perioperative period is of great clinical significance. The inflammatory response during the perioperative period is also an important factor. This study aimed to investigate the dynamic changes in the systemic immune inflammatory index (SII) during the perioperative period of PPCI and evaluate its predictive value for in-hospital and out-of-hospital outcomes in patients with STEMI. Methods This retrospective study included 324 consecutive patients with STEMI who were admitted to the cardiac care unit. Blood samples were collected before PPCI, 12 h (T1), 24 h, 48 h after PPCI, the last time before hospital discharge (T2), and 1 month after hospital discharge. The SII was calculated as (neutrophils×platelets)/lymphocytes. Based on whether the primary endpoint occurred, we divided the patients into event and non-event groups. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors that might influence the occurrence of the primary endpoint. Dynamic curves of SII were plotted, and receiver operating characteristic (ROC) curves were drawn for each node to calculate the optimal critical value, sensitivity, and specificity to assess their predictive ability for in-hospital and out-of-hospital courses. Kaplan-Meier curves were used to analyze the differences in survival rates at different SII inflammation levels. Results High levels of SII were individually related to the occurrence of the in-hospital period and long-term outcomes during the post-operative follow-up of STEMI patients (in-hospital SII: T1:OR 1.001,95%CI 1.001–1.001, P

Abstract Background B-box (BBX) family is a class of zinc finger transcription factors (TFs) that play essential roles in regulating plant growth, development, as well as abiotic stress. However, no systematic analysis of BBX genes has yet been conducted in alfalfa (Medica go sativa L.), and their functions have not been elucidated up to now. Results In this study, 28 MsBBX genes were identified from the alfalfa genome, which were clustered into 4 subfamilies according to an evolutionary tree of BBX proteins. Exon-intron structure and conserved motif analysis reflected the evolutionary conservation of MsBBXs in alfalfa. Collinearity analysis showed that segmental duplication promoted the expansion of the MsBBX family. Analysis of cis-regulatory elements suggested that the MsBBX genes possessed many growth/development-, light-, phytohormone-, and abiotic stress-related elements. MsBBX genes were differentially expressed in leaves, flowers, pre-elongated stems, elongated stems, roots and nodules, and most MsBBXs were remarkably induced by drought, salt and various plant growth regulators (ABA, JA, and SA). Further functional verification demonstrated that overexpressing of the MsBBX11 gene clearly promoted salt tolerance in transgenic Arabidopsis by regulating growth and physiological processes of seedlings. Conclusions This research provides insights into further functional research and regulatory mechanisms of MsBBX family genes under abiotic stress of alfalfa.

Parkinson’s disease (PD) is a prevalent neurodegenerative disease for which no effective treatment currently exists. In this study, we identified formononetin (FMN), a neuroprotective component found in herbal medicines such as Astragalus membranaceus and Glycyrrhiza uralensis, as a potential agent targeting multiple pathways involved in PD. To investigate the anti-PD effects of FMN, we employed Caenorhabditis elegans (C. elegans) PD models, specifically the transgenic strain NL5901 and the MPP(+)-induced strain BZ555, to investigate the effects of FMN on the key pathological features of PD, including dyskinesia, dopamine neuron damage, and reactive oxygen species (ROS) accumulation. The MPP(+)-induced SH-SY5Y cell PD model was utilized to evaluate the effects of FMN on cell viability, ROS accumulation, and mitochondrial dysfunction. The signaling pathway induced by FMN was analyzed using transcriptomic techniques and subsequently validated in vitro. Our results indicate that FMN significantly reduced ROS accumulation and improved both dopaminergic neuron vitality and dyskinesia in the C. elegans PD models. In the cell PD model, FMN significantly reduced ROS accumulation and enhanced mitochondrial membrane potential (MMP) and cell viability. A transcriptomic analysis suggested that the effects of FMN are associated with Nrf2 activation. Furthermore, ML385, a specific Nrf2 inhibitor, blocked the beneficial effects of FMN in vitro, indicating that FMN ameliorates dyskinesia and protects dopaminergic neurons through Nrf2 signaling pathway activation. In addition, the effects of FMN on ameliorating dyskinesia and protecting dopamine neurons were comparable to those of the Nrf2 agonist of sulforaphane (SFN) in vivo. The results of this study confirm that FMN exerts significant anti-PD effects primarily through the Nrf2 signaling pathway. These findings provide crucial insights for the development of anti-PD therapies.

This paper considers the problem of tracking a three-dimensional target under the condition that only a single two-dimensional radar is available. Since a two-dimensional radar can only measure the slant range and azimuth information relative to the target, an unobservability issue arises in this tracking application. Therefore, we first investigate the observability issue of tracking a three-dimensional target with a single two-dimensional radar from two perspectives, including intuitive illustration and quantitative analysis. From the perspective of intuitive illustration, we demonstrate “What is the unobservability issue” and “How does the relative target-radar geometry influence the observability of the tracking system”. From the perspective of quantitative analysis, we construct a novel observability metric for this special tracking problem. Second, aiming at improving tracking performance under the unobservability of target height, we propose an observability-based Gaussian sum cubature Kalman filter. Built within the Gaussian sum framework and based on the height-parameterized strategy, this novel algorithm uses a set of independent fifth-degree cubature Kalman filters, each of which can detect the system observability variation and enhance the tracking accuracy by using a Gaussian splitting scheme under low-degree observability. Finally, the effectiveness of the presented filtering algorithm is validated through lots of simulation experiments.

The sugar transporter (STP) gene family is a key regulator of plant development, which is crucial for the efficient transport and utilization of sugars during plant growth and development. In this study, we identified the MeSTP7 gene, which is highly expressed in cassava fibrous roots, early storage roots, and under hormonal treatment, including IAA, MeJA, ABA, and GA3, and abiotic stressors, such as mannitol and NaCl. A strong response was observed with exoqenous IAA. Transfecting MeSTP7 into Arabidopsis promoted early seedling growth, particularly in lateral root development. The content of endogenous hormones (IAA and MeJA) as well as soluble sugars (sucrose, fructose, and glucose) was elevated in transgenic Arabidopsis. Hormone treatments with IAA, MeJA, GA3, and ABA on transgenic Arabidopsis revealed that transgenic Arabidopsis responded positively to added 20 μM IAA. They also exhibited co-induced regulation of lateral root formation by GA3, MeJA, and ABA. qRT-PCR analysis showed that overexpression of MeSTP7 upregulated the expression of IAA14, ARF7, and ARF19 in Arabidopsis. Under IAA treatment, the expression of these genes was similarly upregulated but downregulated under MeJA treatment. These results suggest that MeSTP7 may promote Arabidopsis seedling development by increasing the content of sucrose, glucose, and fructose in roots, which in turn influences IAA-based hormonal signaling.

The potential role of peroxisome proliferator-activated receptor (PPAR) in regulating the biosynthesis of long-chain polyunsaturated fatty acids (LCPUFA) has not been explored in marine gastropod. In this study, we identified and characterized a PPAR gene from the abalone species Haliotis discus hannai Ino. This gene encodes a peptide consisting of 469 amino acids and comprises typical four domains: A/B domain, DNA-binding domain, D domain, and ligand-binding domain. Highest homology with that of the Patella depressa (51.08 %) from multiple alignments and phylogenetic tree analyses revealed it is a direct orthologue of the vertebrate PPAR. Tissue distribution analysis demonstrated that PPAR was highly expressed in muscle and gill, with lower expression observed in the kidney, female gonad, and hepatopancreas. Dual-luciferase reporter assays indicated that abalone PPAR significantly up-regulated the promoter activity of Δ5 fatty acyl desaturase (Δ5fad), a crucial enzyme in LCPUFA biosynthesis. Furthermore, C18PUFA significantly increased the expressions of Δ5fad and PPAR in the hepatopancreas of abalone compared to the control group fed with an LCPUFA-rich diet. These findings suggest that PPAR acts as a positive transcription factor for the fad gene, contributing to the transcriptional regulation of LCPUFA biosynthesis in abalone.

Summary: The suppressive effect of insulin on food intake has been documented for decades. However, whether insulin signals can encode a certain type of nutrients to regulate nutrient-specific feeding behavior remains elusive. Here, we show that in female Drosophila, a pair of dopaminergic neurons, tritocerebrum 1-dopaminergic neurons (T1-DANs), are directly activated by a protein-intake-induced insulin signal from insulin-producing cells (IPCs). Intriguingly, opto-activating IPCs elicits feeding inhibition for both protein and sugar, while silencing T1-DANs blocks this inhibition only for protein food. Elevating insulin signaling in T1-DANs or opto-activating these neurons is sufficient to mimic protein satiety. Furthermore, this signal is conveyed to local neurons of the protocerebral bridge (PB-LNs) and specifically suppresses protein intake. Therefore, our findings reveal that a brain-derived insulin signal encodes protein satiety and suppresses feeding behavior in a nutrient-specific manner, shedding light on the functional specificity of brain insulin signals in regulating behaviors.

The epipelagic macroalgae of Ulva prolifera and Sargassum are the primary contributors to widespread seaweed tides globally. Both ocean plants release large amounts of chromophoric dissolved organic matter (CDOM) into the surrounding seawater. The photochemical reactivity of this CDOM, however, has not been adequately addressed. In this study, we extracted CDOM from Ulva prolifera and Sargassum, examined their ultraviolet (UV)-visible absorption characteristics, and quantified their broadband apparent quantum yields (AQY) of absorbance photobleaching and photomineralization (in terms of CO2, CO, and CH4 photoproduction). On a per-unit-weight basis, Sargassum leached 3.5 times more CDOM than did Ulva prolifera in terms of the absorption coefficient averaged over 254–500 nm. Both Ulva prolifera and Sargassum CDOM were characterized by quasi-exponential decay absorption spectra, with Sargassum CDOM exhibiting a distinct shoulder over 310–350 nm suggestive of mycosporine amino acids. The Sargassum CDOM had a higher photobleaching AQY but lower photomineralization AQYs compared to Ulva prolifera CDOM. The photobleaching and photomineralization AQYs of both macroalgal CDOM are, however, orders of magnitude higher than those of CDOM in various natural waters. Potential photoproduction rates of CO2 and CO from the Ulva prolifera CDOM and Sargassum CDOM during the bloom periods are several times to orders of magnitude higher than the air-sea fluxes of these gases in the absence of the macroalgae. This study demonstrates that CDOM released by Ulva prolifera and Sargassum is extremely prone to photobleaching and photomineralization, rendering floating mats of these plants in oceans as potential “hotspots” of greenhouse gas emissions to the atmosphere. This photochemical feedback should be considered when assessing ocean afforestation as a CO2 removal approach to mitigate climate warming.

Abstract Green power‐driven CO2 electroreduction using earth‐abundant Ni‐based catalysts is a highly promising approach to fulfill renewable energy storage and a negative carbon cycle. However, metallic Ni nanoparticles and clusters always show severe hydrogen evolution during CO2 electroreduction. Single atomic Ni catalysts demonstrate promising performance for CO2 electroreduction, whereas the very weak binding to intermediates and the very low metal loadings severely limit their activity, efficiency, and practical application. In this concept, we discuss how to regulate the electronic structures of Ni‐based catalysts to enhance the activity and selectivity of CO2 electroreduction. This work will offer instructive guidance in elaborating transition metal catalysts for highly efficient CO2 electroreduction, which may become suitable for future industrial applications.

Ambient ultraviolet radiation (UVB) from solar and artificial light presents serious environmental risks to aquatic ecosystems. The Pacific oyster, Crassostrea gigas, perceives changes in the external environment primarily through its mantle tissue, which contains many nerve fibers and tentacles. Changes within the mantles can typically illustrate the injury of ambient UVB. In this study, a comprehensive analysis of phenotypic, behavioral, and physiological changes demonstrated that extreme UVB radiation (10 W/m²) directly suppressed the behavioral activities of C. gigas. Conversely, under ambient UVB radiation (5 W/m²), various physiological processes exhibited significant alterations in C. gigas, despite the behavior remaining relatively unaffected. Using mathematical model analysis, the integrated analysis of the full-length transcriptome, proteome, and metabolome showed that ambient UVB significantly affected the metabolic processes (saccharide, lipid, and protein metabolism) and cellular biology processes (autophagy, apoptosis, oxidative stress) of the C. gigas mantle. Subsequently, using Procrustes analysis and Pearson correlation analysis, the association between multi-omics data and physiological changes, as well as their biomarkers, revealed the effect of UVB on three crucial biological processes: activation of autophagy signaling (key factors: Ca2+, LC3B, BECN1, caspase-7), response to oxidative stress (reactive oxygen species, heat shock 70, cytochrome c oxidase), and recalibration of energy metabolism (saccharide, succinic acid, translation initiation factor IF-2). These findings offer a fresh perspective on the integration of multi-data from non-model animals in ambient UVB risk assessment.

Copper plays a crucial role in the heterogenous dissociation of chlorothiophenols (CTPs) to form chlorothiophenoxy radicals (CTPRs), which is the initial and critical step in the formation of polychlorinated thianthrenes/dibenzothiophenes (PCTA/DTs). Here, first-principles calculations were performed to investigate the activity of Cu(111) surface towards the formation of adsorbed 2-CTPR from 2-CTP. The interaction between 2-CTP and Cu(111) surface was explored to find stable adsorption configurations. Besides, the decomposition routes of 2-CTP on the Cu(111) surface were further explored. Moreover, the effects of water on the formation of absorbed 2-CTPR on the Cu(111) surface were examined. Our results demonstrate that the flat adsorption of 2-CTP on the surface with adsorption energy in the range of −33.21 kcal/mol to −28.37 kcal/mol is more stable than the vertical adsorption with adsorption energy ranging from −23.53 kcal/mol to −13.38 kcal/mol. The Cu(111) surface catalyzes the conversion of 2-CTP into the adsorbed 2-CTPR with a modest energy barrier of 9.46 kcal/mol. Furthermore, water molecules exhibit stronger catalytic activity in this process with a decreased energy barrier of 5.87 kcal/mol through “water bridge” and hydrogen bonding. Specifically, the water accepts the hydrogen atom from 2-CTP and donates another hydrogen to the surface via “water bridge”. This research provides a molecular-level understanding of the heterogeneous formation of PCTA/DTs by fly ash, suggesting novel approaches for control strategy and legislation of dioxin analogues.

Abstract Horse chestnut (Aesculus chinensis) is an important medicinal tree that contains various bioactive compounds, such as aescin, barrigenol-type triterpenoid saponins (BAT), and aesculin, a glycosylated coumarin. Herein, we report a 470.02 Mb genome assembly and characterize an Aesculus-specific whole-genome duplication event, which leads to the formation and duplication of two triterpenoid biosynthesis-related gene clusters (BGCs). We also show that AcOCS6, AcCYP716A278, AcCYP716A275, and AcCSL1 genes within these two BGCs along with a seed-specific expressed AcBAHD6 are responsible for the formation of aescin. Furthermore, we identify seven Aesculus-originated coumarin glycoside biosynthetic genes and achieve the de novo synthesis of aesculin in E. coli. Collinearity analysis shows that the collinear BGC segments can be traced back to early-diverging angiosperms, and the essential gene-encoding enzymes necessary for BAT biosynthesis are recruited before the splitting of Aesculus, Acer, and Xanthoceras. These findings provide insight on the evolution of gene clusters associated with medicinal tree metabolites.

Accurate habitat prediction of Bigeye Tuna, the main fishing target of tuna pelagic fishery, is of great significance to the fishing operation. In response to the fact that most of the current studies use single-source data for habitat prediction, and the association between spatiotemporal features and habitat distribution is not fully explored and that this has limited the further improvement of prediction accuracy, this paper analyzes the spatiotemporal distribution of the characteristics of Bigeye Tuna’s highly migratory nature. Additionally, it puts forward a method of habitat prediction that utilizes heterosource remote-sensing data for the four-dimensional time–space–environment–spectrum (TSES) for deep-level feature extraction. First, a multi-source heterogeneous dataset was constructed by combining the spatiotemporal distribution characteristics of the product-level environmental remote-sensing data and the L1B-level original spectral remote-sensing data, and then a multi-branch, dynamic spatiotemporal feature extraction, Long Short-Term Memory Network (LSTM) time-series model was constructed to extract the characteristics of the heterogeneous data. This model was constructed to fully explore and utilize the multidimensional deep-level TSES distribution features affecting the habitat prediction. Finally, the two types of heterogeneous data were subjected to the weighted average-based decision-level fusion to obtain the final prediction results. The experimental results show that compared with other methods, the proposed method in this paper outperforms traditional machine-learning models and other single-source, data-based time-series models, with R2 reaching 0.96278 and RMSE decreasing to 0.031361 in the validation experiments of these models. In contrast, the method in this paper demonstrates good generalization ability and achieves accurate prediction of future fishery distribution.

Objective: Osteoarthritis (OA), widely seen in the elderly, is featured by cartilage degradation, subchondral bone remolding, and synovium inflammation. Currently, there is no cure for OA development. Phillygenin (PHI), an active ingredient from the Forsythiae Fructus, possesses many biological properties, such as anti-inflammation and anti-oxidative stress in several diseases. However, the potential effects and underlying mechanisms of PHI on OA remain unclear. Methods: Western blotting, RT-PCR, ELISA and tissue staining were employed to explore the mechanisms by which PHI exerted a protective effect on IL-1β-induced production of pro-inflammation cytokines and extracellular matrix (ECM) degradation in primary murine chondrocytes and destabilization of the medial meniscus (DMM) mouse models. Results: In this study, we found that PHI inhibited the production of pro-inflammation cytokines and ECM degradation induced by IL-1β in primary murine chondrocytes. Mechanically, PHI inhibited the NF-κB pathway via activating nuclear factor (erythrluteolind-derived 2)-like 2 (Nrf2). In vivo experiments also confirmed the chondroprotection of PHI in DMM mouse models. Conclusion: PHI alleviated IL-1β-induced inflammation cytokines and ECM degradation via activating Nrf2 and inhibiting NF-κB pathway. The translational potential of this article: This study provides a biological rationale for the use of PHI as a potential candidate for OA treatment.

Graph de-anonymization is a technique used to reveal connections between entities in anonymized graphs, which is crucial in detecting malicious activities, network analysis, social network analysis, and more. Despite its paramount importance, conventional methods often grapple with inefficiencies and challenges tied to obtaining accurate query graph data. This paper introduces a neural-based inexact graph de-anonymization, which comprises an embedding phase, a comparison phase, and a matching procedure. The embedding phase uses a graph convolutional network to generate embedding vectors for both the query and anonymized graphs. The comparison phase uses a neural tensor network to ascertain node resemblances. The matching procedure employs a refined greedy algorithm to discern optimal node pairings. Additionally, we comprehensively evaluate its performance via well-conducted experiments on various real datasets. The results demonstrate the effectiveness of our proposed approach in enhancing the efficiency and performance of graph de-anonymization through the use of graph embedding vectors.

Synapse is the fundamental structure for neurons to transmit information between cells. The proper synapse formation is crucial for developing neural circuits and cognitive functions of the brain. The aberrant synapse formation has been proved to cause many neurological disorders, including autism spectrum disorders and intellectual disability. Synaptic cell adhesion molecules (CAMs) are thought to play a major role in achieving mechanistic cell-cell recognition and initiating synapse formation via trans-synaptic interactions. Due to the diversity of synapses in different brain areas, circuits and neurons, although many synaptic CAMs, such as Neurexins (NRXNs), Neuroligins (NLGNs), Synaptic cell adhesion molecules (SynCAMs), Leucine-rich-repeat transmembrane neuronal proteins (LRRTMs), and SLIT and NTRK-like protein (SLITRKs) have been identified as synaptogenic molecules, how these molecules determine specific synapse formation and whether other molecules driving synapse formation remain undiscovered are unclear. Here, to provide a tool for synapse labeling and synaptic CAMs screening by artificial synapse formation (ASF) assay, we generated synaptotagmin-1-tdTomato (Syt1-tdTomato) transgenic mice by inserting the tdTomato-fused synaptotagmin-1 coding sequence into the genome of C57BL/6J mice. In the brain of Syt1-tdTomato transgenic mice, the tdTomato-fused synaptotagmin-1 (SYT1-tdTomato) signals were widely observed in different areas and overlapped with synapsin-1, a widely-used synaptic marker. In the olfactory bulb, the SYT1-tdTomato signals are highly enriched in the glomerulus. In the cultured hippocampal neurons, the SYT1-tdTomato signals showed colocalization with several synaptic markers. Compared to the wild-type (WT) mouse neurons, cultured hippocampal neurons from Syt1-tdTomato transgenic mice presented normal synaptic neurotransmission. In ASF assays, neurons from Syt1-tdTomato transgenic mice could form synaptic connections with HEK293T cells expressing NLGN2, LRRTM2, and SLITRK2 without immunostaining. Therefore, our work suggested that the Syt1-tdTomato transgenic mice with the ability to label synapses by tdTomato, and it will be a convenient tool for screening synaptogenic molecules.

Fritillaria ussuriensis Maxim. (F.M.) has been widely used in both food and medication for more than 2000 years. In order to achieve its comprehensive utilization and investigate the structural characterization and biology activity, response surface methodology (RSM) was used to optimize the ultrasound-assisted extraction conditions of F.M. polysaccharides. The optimal extraction conditions were ultrasonic power of 174.2 W, ratio of liquid to material of 40.7 mL/g and ultrasonic time of 82.0 min. In addition, a neutral polysaccharide F-1 was obtained, and its structure characterization, antioxidant and immunological activity were evaluated. The structural properties of the polysaccharide were characterized by UV, IR, GC-MS, NMR and AFM. Monosaccharide composition of F-1 (MW 18.11 kDa) was rhamnose, arabinose, glucosamine hydrochloride, galactose, and glucose which under the ratio of 0.9: 3.8: 0.2: 2.9: 92.2. The fractions of F-1 were mainly linked by → 6)-α-D-Glcp-(1 → with branch chain α-D-Glcp-(1 → 4)-α-D-Glcp-(1 → and 4,6)-α-D-Glcp-(1 → residues. Moreover, F-1 has a significant scavenging activity, which can clear hydroxyl radicals, superoxide anion, DPPH and ABTS. In addition, the immunological activity showed that F-1 had an effect on macrophage phagocytic activity. And it can increase the release of inflammatory factors including TNF-α, IL-1β and IL-6. F-1 is a novel polysaccharide with significant activity in antioxidant and immunological activity, which has great potential for antioxidant and immunizer in food, pharmaceutical and cosmetic industries. The study can provide a methodological basis for polysaccharide research and theoretical basis for the industrialized production and practical application.

The aging population has become an issue that cannot be ignored, and research on aging is receiving increasing attention. PL 1-3 possesses diverse pharmacological properties including anti-oxidative stress, inhibits inflammatory responses and anti-apoptosis. This study showed that PL 1-3 could protect mice, especially the brain, against the aging caused by D-galactose (D-gal). D-gal could cause oxidative stress, inflammation, apoptosis and tissue pathological injury and so on in aging mice. The treatment of PL 1-3 could increase the anti-oxidative stress ability in the serum, liver, kidney and brain of aging mice, via increasing the total antioxidant capacity and the levels of anti-oxidative defense enzymes (superoxide dismutase, glutathione peroxidase, and catalase), and reducing the end product of lipid peroxidation (malondialdehyde). In the brain, in addition to the enhanced anti-oxidative stress via upregulating the level of the nuclear factor erythroid 2-related factor 2 and heme oxygenase 1, PL 1-3 could improve the dysfunction of the cholinergic system via reducing the active of acetylcholinesterase so as to increase the level of acetylcholine, increase the anti-inflammatory and anti-apoptosis activities via downregulating the expressions of pro-inflammatory cytokines (interleukin-6 and tumor necrosis factor-α) and pro-apoptosis proteins (Bcl-2 associated X protein and Caspase-3) in the D-gal-induced aging mice, to enhance the anti-aging ability via upregulating the expression of sirtuin 1 and downregulating the expressions of p53, p21, and p16. Besides, PL 1-3 could reverse the liver, kidney and spleen damages induced by D-gal in aging mice. These results suggested that PL 1-3 may be developed as an anti-aging drug for the prevention and intervention of age-related diseases.

Objectives: To evaluate the diagnostic value of targeted next generation sequencing (tNGS) in childhood tuberculosis (TB) and compare the accuracy with Xpert MTB/RIF method. Methods: Children aged ≤18 years with symptoms suggestive of TB during July 2021 to December 2022 at Beijing Children's Hospital were included, and the performances of tNGS and Xpert were evaluated. Results: A total of 103 children with suspected TB were recruited, including 72 discharge diagnosis of TB and 31 non-TB cases. The mean age was 7.37 ± 4.77 years, and 62.1 % were male. The most common type of specimens was gastric aspirate (GA) (59, 57.3 %). Among all the 72 TB patients, tNGS showed higher sensitivity than Xpert, but the difference was not significant (34.7 %, 25/72 vs 20.8 %, 15/72; P = 0.063). The specificities of tNGS and Xpert were 87.1 % (27/31) and 96.8 % (30/31), respectively (P = 0.162). Among different types of specimen, the highest sensitivity of tNGS on sputum and pus was observed (80.0 %, 4/5), followed by pleural effusion (50.0 %, 2/4). One rifampin resistance and one protionamide resistance were detected in bacteriologically confirmed TB by tNGS. Conclusion: tNGS had a higher sensitivity but lower specificity compared to Xpert in diagnosis of children TB. tNGS yielded higher sensitivity than Xpert on gastric aspirate and sputum and pus.

Abstract Background Endometriosis (EMs), the ectopic planting of functional endometrium outside of the uterus, is a leading cause of infertility and pelvic pain. As a fundamental mRNA modification, N6-methyladenosine (m6A) participates in various pathological processes. However, the role of m6A RNA modification in endometriosis remains unclear. The present study explores METTL3-mediated m6A modification and the mechanisms involved in endometriosis. Methods The dominant m6A regulators in EMs were analysed using RT‒PCR. Candidate targets and possible mechanisms of METTL3 were assessed by m6A-mRNA epitranscriptomic microarray and RNA sequencing. A primary ESCs model was employed to verify the effect of METTL3 on m6A modification of SIRT1 mRNA, and the mechanism was elucidated by RT‒PCR, Western blotting, MeRIP, and RIP assays. CCK-8 viability assays, Transwell invasion assays, EdU proliferation assays, wound healing migration assays, and senescence-associated β-galactosidase staining were performed to illuminate the potential biological mechanism of METTL3 and SIRT1 in ESCs in vitro. An in vivo PgrCre/ + METTL3 −/− female homozygous mouse model and a nude mouse xenograft model were employed to further investigate the physiologic consequences of METTL3-mediated m6A alteration on EMs. Results Our data show that decreased METTL3 expression significantly downregulates m6A RNA methylation levels in ESCs. Silencing m6A modifications mediated by METTL3 accelerates ESCs viability, proliferation, migration, and invasion in vitro. The m6A reader protein YTHDF2 binds to m6A modifications to induce the degradation of SIRT1 mRNA. SIRT1/FOXO3a signalling pathway activation is subsequently inhibited, promoting the cellular senescence of ESCs and inhibiting the ectopic implantation of ESCs in vitro and in vivo. Conclusions Our findings demonstrate that METTL3-mediated m6A methylation epigenetically regulates the ectopic implantation of ESCs, resulting in the progression of endometriosis. Our study establishes METTL3-YTHDF2-SIRT1/FOXO3a as a critical axis and potential mechanism in endometriosis.

Abstract Background Three-dimensional (3D) printing is a novel innovation in the field of craniomaxillofacial surgery, however, a lack of evidence exists related to the comparison of the trueness of skull models fabricated using different technology-based printers belonging to different cost segments. Methods A study was performed to investigate the trueness of cone-beam computed tomography-derived skull models fabricated using different technology based on low-, medium-, and high-cost 3D printers. Following the segmentation of a patient’s skull, the model was printed by: (i) a low-cost fused filament fabrication printer; (ii) a medium-cost stereolithography printer; and (iii) a high-cost material jetting printer. The fabricated models were later scanned by industrial computed tomography and superimposed onto the original reference virtual model by applying surface-based registration. A part comparison color-coded analysis was conducted for assessing the difference between the reference and scanned models. A one-way analysis of variance (ANOVA) with Bonferroni correction was applied for statistical analysis. Results The model printed with the low-cost fused filament fabrication printer showed the highest mean absolute error ( $$1.33\pm 0.24 \text{mm}$$ 1.33 ± 0.24 mm ), whereas both medium-cost stereolithography-based and the high-cost material jetting models had an overall similar dimensional error of $$0.07\pm 0.03 \text{mm}$$ 0.07 ± 0.03 mm and $$0.07\pm 0.01 \text{mm}$$ 0.07 ± 0.01 mm , respectively. Overall, the models printed with medium- and high-cost printers showed a significantly ( $$p

In order to obtain lactic acid bacteria (LAB) with a strong acid production capacity, good tolerance, and high function from persimmon vinegar broth, which is suitable for plant substrate fermentation. Using the persimmon vinegar broth naturally fermented as a source of lactic acid bacteria, five strains were isolated using MRS liquid culture medium and calcium-dissolving circle methods. The abilities of producing acid, tolerance, antioxidant and β-glucosidase production of the 5 LABs were measured, the morphology and 16S rDNA identification of the screened two LABs with stronger comprehensive performance were analyzed. Based on the results of the screening, Lactobacillus acidophilus and Lactobacillus plantarum were identified as two excellent strains of lactic acid bacteria. Both lactic acid bacteria produced acid at a rate of 2.00 and 2.24 g/100 mL, respectively. Among the pH tolerances, the lowest was 1.5, the highest was 10% for ethanol, 1% for bile salts, and 7% for NaCl. The scavenging abilities of screened two LABs on ABTS+, DPPH, O2- free radicals were 65.12% and 62.26%, 77.42% and 68.89%, 93.76% and 87.89%, respectively. The production of β-glucosidase were 26.37 and 30.27 IU/L. In this paper, the two LABs strains with strong biological properties were obtained from persimmon vinegar broth for plant substrate fermentation, which could provide strain resources for the development of probiotics.

As urbanization in China progresses, urban spatial development is transitioning from rapid expansion to more intensive and compact growth. This study examined the role of physical geography and environmental factors in shaping the urban spatial development in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Based on the current natural conditions, we selected evaluation indices from topography, hydrogeology, climatic conditions, and natural disasters. These indices were used to create a carrying capacity and suitability evaluation system for development land under natural constraints. Finally, the spatial development potential of the city was finalized by taking into account the current state of the built-up area of the city. Meanwhile, we employed the Optimal Parameters-based Geographical Detector and assessed the impact of 14 natural factors on the spatial development of urban built-up areas. In 2020, the GBA had 52,168.77 km2 of land suitable for construction, of which 34,241.13 km2 was highly suitable (61.29%) and 17,927.64 km2 was moderately suitable (32.09%). At the Bay Area level, 90.15% of the development potential remains untapped; at the city level, Zhaoqing City has the highest potential at 99.56%, while Macao has the lowest at 26.83%. Key factors influencing urban development include silty sand content, annual average relative humidity, and cumulative temperature above 0 °C, with varying impacts across different urban scales. At the Bay Area level, the silty sand content, annual average relative humidity, and cumulative temperature above 0 °C are the main influencing factors on the spatial development of urban built-up areas; at the city level, the main factors are annual average relative humidity and cumulative active temperature above 0 °C. This study reveals the important influence of natural environmental factors on urban spatial development, which is conducive to promoting sustainable development of land resources in GBA.

Untreated or inadequately treated silver−containing wastewater may pose adverse effects on hu−man health and the ecological environment. Currently, significant progress has been made in the treatment of Ag(I) in wastewater using adsorption methods, with adsorbents playing a pivotal role in this process. This paper provides a systematic review of various adsorbents for the recovery and treatment of Ag(I) in wastewater, including MOFs, COFs, transition metal sulfides, metal oxides, biomass materials, and other polymeric materials. The adsorption mechanisms of these materials for Ag(I) are elaborated upon, along with the challenges currently faced. Furthermore, insights into optimizing adsorbents and developing novel adsorbents are proposed in this study.

IntroductionSince its outbreak in December 2019, SARS-CoV-2 has spread rapidly across the world, posing significant threats and challenges to global public health. SARS-CoV-2, together with SARS-CoV and MERS-CoV, is a highly pathogenic coronavirus that contributes to fatal pneumonia. Understanding the similarities and differences at the transcriptome level between SARS-CoV-2, SARS-CoV, as well as MERS-CoV is critical for developing effective strategies against these viruses.MethodsIn this article, we comparatively analyzed publicly available transcriptome data of human cell lines infected with highly pathogenic SARS-CoV-2, SARS-CoV, MERS-CoV, and lowly pathogenic HCoV-229E. The host gene expression profiles during human coronavirus (HCoV) infections were generated, and the pathways and biological functions involved in immune responses, antiviral efficacy, and organ damage were intensively elucidated.ResultsOur results indicated that SARS-CoV-2 induced a stronger immune response versus the other two highly pathogenic HCoVs. Specifically, SARS-CoV-2 induced robust type I and type III IFN responses, marked by higher upregulation of type I and type III IFNs, as well as numerous interferon-stimulated genes (ISGs). Further Ingenuity Pathway Analysis (IPA) revealed the important role of ISGs for impeding SARS-CoV-2 infection, and the interferon/ISGs could be potential targets for therapeutic interventions. Moreover, our results uncovered that SARS-CoV-2 infection was linked to an enhanced risk of multi-organ toxicity in contrast to the other two highly pathogenic HCoVs.DiscussionThese findings provided valuable insights into the pathogenic mechanism of SARS-CoV-2, which showed a similar pathological feature but a lower fatality rate compared to SARS-CoV and MERS-CoV.

ABSTRACTOur previous work revealed that unbalanced dietary intake was an important independent factor associated with constipation and gastrointestinal (GI) symptoms in children with autism spectrum disorder (ASD). Growing evidence has shown the alterations in the gut microbiota and gut microbiota-derived metabolites in ASD. However, how the altered microbiota might affect the associations between unbalanced diets and GI symptoms in ASD remains unknown. We analyzed microbiome and metabolomics data in 90 ASD and 90 typically developing (TD) children based on 16S rRNA and untargeted metabolomics, together with dietary intake and GI symptoms assessment. We found that there existed 11 altered gut microbiota (FDR-corrected P-value

Alfalfa is an excellent leguminous forage crop that is widely cultivated worldwide, but its yield and quality are often affected by drought and soil salinization. Hyperosmolality-gated calcium-permeable channel (OSCA) proteins are hyperosmotic calcium ion (Ca2+) receptors that play an essential role in regulating plant growth, development, and abiotic stress responses. However, no systematic analysis of the OSCA gene family has been conducted in alfalfa. In this study, a total of 14 OSCA genes were identified from the alfalfa genome and classified into three groups based on their sequence composition and phylogenetic relationships. Gene structure, conserved motifs and functional domain prediction showed that all MsOSCA genes had the same functional domain DUF221. Cis-acting element analysis showed that MsOSCA genes had many cis-regulatory elements in response to abiotic or biotic stresses and hormones. Tissue expression pattern analysis demonstrated that the MsOSCA genes had tissue-specific expression; for example, MsOSCA12 was only expressed in roots and leaves but not in stem and petiole tissues. Furthermore, RT–qPCR results indicated that the expression of MsOSCA genes was induced by abiotic stress (drought and salt) and hormones (JA, SA, and ABA). In particular, the expression levels of MsOSCA3, MsOSCA5, MsOSCA12 and MsOSCA13 were significantly increased under drought and salt stress, and MsOSCA7, MsOSCA10, MsOSCA12 and MsOSCA13 genes exhibited significant upregulation under plant hormone treatments, indicating that these genes play a positive role in drought, salt and hormone responses. Subcellular localization results showed that the MsOSCA3 protein was localized on the plasma membrane. This study provides a basis for understanding the biological information and further functional analysis of the MsOSCA gene family and provides candidate genes for stress resistance breeding in alfalfa.

In the past, the primary emphasis of livestock and poultry breeding was mainly on improving the growth rate, meat production efficiency and disease resistance. However, the improvement of meat quality has become a major industrial focus due to the ongoing advancements in livestock and poultry breeding. Skeletal muscles consist of multinucleated myofibers formed through the processes of myoblast proliferation, differentiation and fusion. Muscle fibers can be broadly classified into two main types: slow-twitch (Type I) and fast-twitch (Type II). Fast-twitch fibers can be further categorized into Type IIa, Type IIx, and Type IIb. The proportion of Type I and Type IIa muscle fibers is positively associated with meat quality, while the presence of Type IIb muscle fibers in skeletal muscle tissue is inversely related to meat quality. Consequently, muscle fiber composition directly influences meat quality. The distribution of these fiber types within skeletal muscle is governed by a complex network, which encompasses numerous pivotal regulators and intricate signaling pathways. This article aims to succinctly outline the parameters utilized for assessing meat quality, elucidate the relationship between muscle fiber composition and meat quality as well as elaborate on the relevant genetic factors and their molecular mechanisms that regulate muscle fiber types in livestock and poultry. This summary will enrich our comprehension of how to improve meat quality in livestock and poultry, providing valuable insights for future improvements.