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Abstract The presence of cancer stem cells (CSCs) contributes significantly to treatment resistance in various cancers, including head and neck squamous cell carcinoma (HNSCC). Despite this, the relationship between cancer stemness and immunity remains poorly understood. In this study, we aimed to identify potential immunotherapeutic targets and sensitive drugs for CSCs in HNSCC. Using data from public databases, we analyzed expression patterns and prognostic values in HNSCC. The stemness index was calculated using the single-sample gene set enrichment analysis (ssgsea) algorithm, and weighted gene co-expression network analysis (WGCNA) was employed to screen for key stemness-related modules. Consensus clustering was then used to group samples for further analysis, and prognosis-related key genes were identified through regression analysis. Our results showed that tumor samples from HNSCC exhibited higher stemness indices compared to normal samples. WGCNA identified a module highly correlated with stemness, comprising 187 genes, which were significantly enriched in protein digestion and absorption pathways. Furthermore, we identified sensitive drugs targeting prognostic genes associated with tumor stemness. Notably, two genes, HLF and CCL11, were found to be highly associated with both stemness and immunity. In conclusion, our study identifies a stemness-related gene signature and promising drug candidates for CSCs of HNSCC. Additionally, HLF and CCL11, which are associated with both stemness and immunity, represent potential targets for immunotherapy in HNSCC.

Abstract Background The inter-reviewer reliability of the risk of bias (RoB) assessment lacked agreement in previous studies. It is important to analyse these disagreements to improve the repeatability of RoB assessment. The objective of the study was to evaluate the frequency and reasons for disagreements in RoB assessments for randomised controlled trials (RCTs) that were included in multiple Cochrane reviews in the field of hypertension. Methods A cross-sectional study was employed. We retrieved any RCTs that had been included in multiple Cochrane reviews in the field of hypertension from ARCHIE. The results of the RoB assessments were extracted, and the distributions of agreements and possible reasons for disagreement were analyzed. Results Twenty-six Cochrane reviews were included in this study. A total of 78 RCTs appeared in more than one Cochrane review. The level of agreement ranged from domain to domain. “Blinding of outcome assessment” showed a reasonably high level of agreement (94.9%), while “incomplete outcome data”, “selective outcome reporting” and “other sources of bias” showed moderate levels of agreement (74.6%, 79.2% and 75.6%, respectively). However, the domains of “allocation concealment”, “random sequence generation” and “blinding of participants and personnel” showed low levels of agreement (24.4%, 23.5%, and 47.4%, respectively). In the domains of “allocation concealment” and “blinding of participants and personnel”, the agreement group had higher proportion of publication year ≤ 1996 than the disagreement group (P = 0.008 and P

Abstract Artificial intelligence (AI) telephone is reliable for the follow‐up and management of hypertensives. It takes less time and is equivalent to manual follow‐up to a high degree. We conducted a reliability study to evaluate the efficiency of AI telephone follow‐up in the management of hypertension. During May 18 and June 30, 2020, 350 hypertensives managed by the Pengpu Community Health Service Center in Shanghai were recruited for follow‐up, once by AI and once by a human. The second follow‐up was conducted within 3–7 days (mean 5.5 days). The mean length time of two calls were compared by paired t‐test, and Cohen's Kappa coefficient was used to evaluate the reliability of the results between the two follow‐up visits. The mean length time of AI calls was shorter (4.15 min) than that of manual calls (5.24 min, P

Abstract Objective Although blood urea nitrogen (BUN) has a crucial impact on many diseases, its effect on outcomes in patients with hyperlipidemia remains unknown. The study aimed to investigate the relationships between BUN levels and all-cause and cardiovascular disease (CVD) mortality in individuals with hyperlipidemia. Methods This analysis comprised 28,122 subjects with hyperlipidemia from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018. The risk of BUN on mortality was evaluated using weighted Cox regression models. Additionally, to illustrate the dose-response association, the restricted cubic spline (RCS) was used. Results During the observation period, 4276 participant deaths were recorded, of which 1206 were due to CVD. Compared to patients with hyperlipidemia in the third BUN quintile, the hazard ratios (HRs) for all-cause mortality were 1.26 (95% CIs: 1.09, 1.45) and 1.22 (95% CIs: 1.09, 1.37) for patients in the first and fifth quintiles of BUN, respectively. The HRs for CVD mortality among patients in the fifth quintile of BUN were 1.48 (95% CIs: 1.14, 1.93). BUN levels were found to have a U-shaped association with all-cause mortality and a linear association with CVD mortality using restricted triple spline analysis. Conclusions This study revealed that both low and high BUN levels in patients with hyperlipidemia are associated with heightened all-cause mortality. Furthermore, elevated BUN levels are also associated with increased CVD mortality. The findings indicate that patients with hyperlipidemia may face an elevated risk of death if they have abnormal BUN levels.

Purpose: This scoping review aimed to offer researchers and practitioners an understanding of artificial intelligence (AI) applications in physical activity (PA) interventions; introduce them to prevalent machine learning (ML), deep learning (DL), and reinforcement learning (RL) algorithms; and encourage the adoption of AI methodologies. Methods: A scoping review was performed in PubMed, Web of Science, Cochrane Library, and EBSCO focusing on AI applications for promoting PA or predicting related behavioral or health outcomes. AI methodologies were summarized and categorized to identify synergies, patterns, and trends informing future research. Additionally, a concise primer on predominant AI methodologies within the realm of PA was provided to bolster understanding and broader application. Results: The review included 24 studies that met the predetermined eligibility criteria. AI models were found effective in detecting significant patterns of PA behavior and associations between specific factors and intervention outcomes. Most studies comparing AI models to traditional statistical approaches reported higher prediction accuracy for AI models on test data. Comparisons of different AI models yielded mixed results, likely due to model performance being highly dependent on the dataset and task. An increasing trend of adopting state-of-the-art DL and RL models over standard ML was observed, addressing complex human–machine communication, behavior modification, and decision-making tasks. Six key areas for future AI adoption in PA interventions emerged: personalized PA interventions, real-time monitoring and adaptation, integration of multimodal data sources, evaluation of intervention effectiveness, expanding access to PA interventions, and predicting and preventing injuries. Conclusion: The scoping review highlights the potential of AI methodologies for advancing PA interventions. As the field progresses, staying informed and exploring emerging AI-driven strategies is essential for achieving significant improvements in PA interventions and fostering overall well-being.

Abstract Background Cervicovaginal microbiome plays an important role in the persistence of HPV infection and subsequent disease development. However, cervicovaginal microbiota varied cross populations with different habits and regions. Identification of population-specific biomarkers from cervicovaginal microbiota and host metabolome axis may support early detection or surveillance of HPV-induced cervical disease at all sites. Therefore, in the present study, to identify HPV-specific biomarkers, cervicovaginal secretion and serum samples from HPV-infected patients (HPV group, n = 25) and normal controls (normal group, n = 17) in Xichang, China were collected for microbiome (16S rRNA gene sequencing) and metabolome (UHPLC-MS/MS) analysis, respectively. Results The results showed that key altered metabolites of 9,10-DiHOME, α-linolenic acid, ethylparaben, glycocholic acid, pipecolic acid, and 9,12,13-trihydroxy-10(E),15(Z)-octadecadienoic acid, correlating with Sneathia (Sneathia_amnii), Lactobacillus (Lactobacillus_iners), Atopobium, Mycoplasma, and Gardnerella, may be potential biomarkers of HPV infection. Conclusion The results of current study would help to reveal the association of changes in cervicovaginal microbiota and serum metabolome with HPV infections.

Abstract Bipolar disorder (BD) showed the highest suicide rate of all psychiatric disorders, and its underlying causative genes and effective treatments remain unclear. During diagnosis, BD is often confused with schizophrenia (SC) and major depressive disorder (MDD), due to which patients may receive inadequate or inappropriate treatment, which is detrimental to their prognosis. This study aims to establish a diagnostic model to distinguish BD from SC and MDD in multiple public datasets through bioinformatics and machine learning and to provide new ideas for diagnosing BD in the future. Three brain tissue datasets containing BD, SC, and MDD were chosen from the Gene Expression Omnibus database (GEO), and two peripheral blood datasets were selected for validation. Linear Models for Microarray Data (Limma) analysis was carried out to identify differentially expressed genes (DEGs). Functional enrichment analysis and machine learning were utilized to identify. Least absolute shrinkage and selection operator (LASSO) regression was employed for identifying candidate immune-associated central genes, constructing protein-protein interaction networks (PPI), building artificial neural networks (ANN) for validation, and plotting receiver operating characteristic curve (ROC curve) for differentiating BD from SC and MDD and creating immune cell infiltration to study immune cell dysregulation in the three diseases. RBM10 was obtained as a candidate gene to distinguish BD from SC. Five candidate genes (LYPD1, HMBS, HEBP2, SETD3, and ECM2) were obtained to distinguish BD from MDD. The validation was performed by ANN, and ROC curves were plotted for diagnostic value assessment. The outcomes exhibited the prediction model to have a promising diagnostic value. In the immune infiltration analysis, Naive B, Resting NK, and Activated Mast Cells were found to be substantially different between BD and SC. Naive B and Memory B cells were prominently variant between BD and MDD. In this study, RBM10 was found as a candidate gene to distinguish BD from SC; LYPD1, HMBS, HEBP2, SETD3, and ECM2 serve as five candidate genes to distinguish BD from MDD. The results obtained from the ANN network showed that these candidate genes could perfectly distinguish BD from SC and MDD (76.923% and 81.538%, respectively).

Abstract Background The swift transition to online teaching in medical education has presented the challenge of replicating in-class engagement and interaction essential for active learning. Despite online team-based learning (TBL) offering potential solutions through structured cooperative activities, its efficacy in virtual simulation experiment courses remains scantily researched. This study investigates the effectiveness of online TBL for teaching virtual patient experiments in a basic medical laboratory course and contrasts it with traditional offline teaching in terms of student performance and perceptions. Methods A comparative analysis involved 179 Year 3 medical students using online TBL, face-to-face TBL (FTF-TBL), and the flipped classroom (FC) approach. The learning outcomes were assessed based on experiment reports, IRAT scores, TRAT scores, and final exam performance. Students’ perceptions of both online and in-class TBL methodologies were also surveyed. Results Both online and in-class TBL groups demonstrated comparable academic outcomes and surpassed the FC group in academic performance. Students displayed a marked preference for the TBL format (whether online or in-class), valuing its enhancement of learning interest and practical knowledge application. Nevertheless, refinements in discussion efficiency, platform convenience, and student-instructor interaction were indicated as potential areas of improvement in the online setting. Conclusions Online TBL, along with its in-class counterpart, showed superior academic performance and a more positive learning experience compared to the FC group. These findings underscore the potential of online TBL in adapting to modern pedagogical challenges and enriching medical education through virtual simulation experiments.

Abstract Background Multispecies biofilms located in the anatomical intricacies of the root canal system remain the greatest challenge in root canal disinfection. The efficacy of Er:YAG laser-activated irrigation techniques for treating multispecies biofilms in these hard-to-reach areas has not been proved. The objective of this laboratory study was to evaluate the effectiveness of two Er:YAG laser-activated irrigation techniques, namely, photon-induced photoacoustic streaming (PIPS) and shock wave-enhanced emission photoacoustic streaming (SWEEPS), in treating multispecies biofilms within apical artificial grooves and dentinal tubules, in comparison with conventional needle irrigation (CNI), passive ultrasonic irrigation (PUI), and sonic-powered irrigation (EDDY). Two types of multispecies root canal biofilm models were established in combination with two assessment methods using scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) with the aim to obtain more meaningful results. Methods Ninety extracted human single-rooted premolars were chosen for two multispecies biofilm models. Each tooth was longitudinally split into two halves. In the first model, a deep narrow groove was created in the apical segment of the canal wall. After cultivating a mixed bacterial biofilm for 4 weeks, the split halves were reassembled and subjected to five irrigation techniques: CNI, PUI, EDD, PIPS, and SWEEPS. The residual biofilms inside and outside the groove in Model 1 were analyzed using SEM. For Model 2, the specimens were split longitudinally once more to evaluate the percentage of killed bacteria in the dentinal tubules across different canal sections (apical, middle, and coronal thirds) using CLSM. One-way analysis of variance and post hoc multiple comparisons were used to assess the antibiofilm efficacy of the 5 irrigation techniques. Results Robust biofilm growth was observed in all negative controls after 4 weeks. In Model 1, within each group, significantly fewer bacteria remained outside the groove than inside the groove (P 0.05). In Model 2, SWEEPS and EDDY exhibited superior bacterial killing efficacy within the dentinal tubules, followed by PIPS, PUI, and CNI (P

Abstract Recently, weak supervision has received growing attention in the field of salient object detection due to the convenience of labelling. However, there is a large performance gap between weakly supervised and fully supervised salient object detectors because the scribble annotation can only provide very limited foreground/background information. Therefore, an intuitive idea is to infer annotations that cover more complete object and background regions for training. To this end, a label inference strategy is proposed based on the assumption that pixels with similar colours and close positions should have consistent labels. Specifically, k‐means clustering algorithm was first performed on both colours and coordinates of original annotations, and then assigned the same labels to points having similar colours with colour cluster centres and near coordinate cluster centres. Next, the same annotations for pixels with similar colours within each kernel neighbourhood was set further. Extensive experiments on six benchmarks demonstrate that our method can significantly improve the performance and achieve the state‐of‐the‐art results.

Oncolytic viruses (OVs) have emerged as a potential strategy for tumor treatment due to their ability to selectively replicate in tumor cells, induce apoptosis, and stimulate immune responses. However, the therapeutic efficacy of single OVs is limited by the complexity and immunosuppressive nature of the tumor microenvironment (TME). To overcome these challenges, engineering OVs has become an important research direction. This review focuses on engineering methods and multi-modal combination therapies for OVs aimed at addressing delivery barriers, viral phagocytosis, and antiviral immunity in tumor therapy. The engineering approaches discussed include enhancing in vivo immune response, improving replication efficiency within the tumor cells, enhancing safety profiles, and improving targeting capabilities. In addition, this review describes the potential mechanisms of OVs combined with radiotherapy, chemotherapy, cell therapy and immune checkpoint inhibitors (ICIs), and summarizes the data of ongoing clinical trials. By continuously optimizing engineering strategies and combination therapy programs, we can achieve improved treatment outcomes and quality of life for cancer patients.

IntroductionLiuweizhiji Gegen-Sangshen beverage (LGS) is popular in China, which has been used for alleviating alcohol-mediated discomfort and preventing alcoholic liver disease (ALD). This beverage is consisted of six herbal components that are known as functional foods and fruits. LGS is rich in polysaccharides, however, the activity and quality evaluation of LGS-derived polysaccharides remain unexplored. The purpose of this study is thus to establish a comprehensive quality control methodology for the assessment of LGS polysaccharides (LGSP) and to further explore the anti-oxidant, anti-inflammatory as well as prebiotic effect of LGSP.MethodsLGSP was extracted, followed by analysis of molecular weight distribution, monosaccharide content and structural characterization via integrating the application of high-performance size exclusion chromatography (HPSEC), 1-phenyl-3-methyl-5-pyrazolone-HPLC (PMP-HPLC), fourier transform infrared spectroscopy (FT-IR) as well as nuclear magnetic resonance spectroscopy (NMR) techniques. The anti-oxidation activity of LGSP was determined by DPPH, ABTS, hydroxyl radical scavenging capacity and total antioxidant capacity. The anti-inflammation of LGSP were assessed on the RAW 264.7 cells. The effect of LGSP on growth of Lactobacillus, Bifidobacterium bifidum and Bifidobacterium adolescentis was evaluated.ResultsThe results demonstrated that LGSP had two molecular weight distribution peaks, with the average molecular weights of (6.569 ± 0.12) × 104 Da and (4.641 ± 0.30) × 104 Da. LGSP was composed of 8 monosaccharides, with galacturonic acid, glucose rhamnose and galactose representing the highest molar ratios. Homogalacturonic acid (HG) type and rhamnosegalacturonic acid glycans I (RG-I) type and α-1,4-glucan were present in LGSP. LGSP concentration in LGS was 17.94 ± 0.28 mg/mL. Furthermore, fingerprint analysis combined with composition quantification of 10 batches of LGSP demonstrated that there was a high similarity among batches. Notably, LGSP exhibited anti-oxidant effect and inhibited expressions of pro-inflammatory factors (TNF-α and IL-6) in LPS-stimulated RAW 264.7 cells. In addition, LGSP remarkably promoted the proliferation of probiotics Lactobacillus, Bifidobacterium bifidum and Bifidobacterium adolescentis, showing good prebiotic activity.DiscussionThe results of present study would be of help to gain the understanding of structure–activity relationship of LGSP, provide a reference for quality evaluation of bioactive LGSP, and facilitate development of unique health and functional products in the future.

Background For patients with stage III epithelial ovarian cancer, there are limited studies on the effects of postoperative adjuvant radiotherapy (RT). Here we assessed the therapeutic efficacy and toxicity of postoperative radiotherapy to the abdominal and pelvic lymphatic drainage area for stage III epithelial ovarian cancer patients, who had all received surgery and chemotherapy (CT). Methods We retrospectively collected patients with stage III epithelial ovarian cancer after cytoreductive surgery (CRS) and full-course adjuvant CT. The chemoradiotherapy (CRT) group patients were treated with intensity modulated radiotherapy (IMRT) to the abdominal and pelvic lymphatic drainage area in our hospital between 2010 and 2020. A propensity score matching analysis was conducted to compare the results between the CRT and CT groups. Kaplan-Meier analysis estimated overall survival (OS), disease-free survival (DFS), and local control (LC) rates. The log-rank test determined the significance of prognostic factors. Results A total of 132 patients with median follow-up of 73.9 months (9.1-137.7 months) were included (44 and 88 for the CRT and RT groups, retrospectively). The baseline characteristics of age, histology, level of CA12-5, surgical staging, residual tumour, courses of adjuvant CT, and courses to reduce CA12-5 to normal were all balanced. The median DFS time, 5-year OS, and local recurrence free survival (LRFS) were 100.0 months vs 25.9 months ( P = .020), 69.2% vs 49.9% ( P = .002), and 85.9% vs 50.5% ( P = .020), respectively. The CRT group mainly presented with acute haematological toxicities, with no statistically significant difference compared with grade III intestinal adverse effects (3/44 vs 6/88, P = .480). Conclusion This report demonstrates that long-term DFS could be achieved in stage III epithelial ovarian cancer patients treated with IMRT preventive radiation to the abdominal and pelvic lymphatic area. Compared with the CT group, DFS and OS were significantly prolonged and adverse effects were acceptable.

Rationale and objectives: This study aimed to investigate the effect of intestinal dysbiosis on the hippocampal volume using proton magnetic resonance spectroscopy (1H-MRS) in a type 2 diabetes mellitus (T2DM) rat model. Materials and methods: We established a T2DM animal model with high-fat diet and streptozotocin (HFD/STZ) administration to Sprague-Dawley rats. Short-term ceftriaxone sodium administration was used to establish a T2DM intestinal dysbiosis (T2DM-ID) model. After establishing the model, fecal microbiota were detected using 16S rRNA sequencing. The models were then subjected to magnetic resonance imaging (MRI). Associations between MRI findings and fecal microbiota were evaluated. Results: Magnetic resonance imaging (MRI) showed that the bilateral hippocampal voxel value and N-acetylaspartate (NAA) level were lower in the experimental group than in the normal control (NC) group (p

A systematic understanding of shifts in the temporal and spatial distributions of ecosystem services (ESs) in the Yellow River Basin and the trade-offs and synergies between these services and their driving variables is essential for effective management of the environment and for enhancing human well-being. This study quantitatively assessed the carbon storage (CS), water yield (WY), habitat quality (HQ), and soil retention (SR) from 2000 to 2020, combinded Bayesian Belief Network (BBN) and ESs, determined the crucial elements influencing the supply of ESs via sensitivity analysis, identified synergies and trade-offs between ESs via probabilistic reasoning, and explored the driving processes via scenario analysis. The following are the key findings of this research. (1) Geographically, the Yellow River Basin, SR, CS, and WY exhibited higher levels in southern regions and lower levels in northern regions, whereas HQ showed higher levels in the northwestern region and lower levels in the southeastern region. Both WY and CS showed annual increases in the time series. (2) With respect to trade-offs and synergistic interactions, HQ, WY, and CS had a synergistic connection, whereas SR and HQ, CS, WY had a trade-off connection. (3) According to the BBN sensitivity analysis, the normalized difference vegetation index (NDVI), temperature, precipitation, and land use (LU) were the main variable nodes affecting ESs. (4) The results of the scenario analysis revealed that LU was the primary driver of the four ESs In addition, precipitation and NDVI primarily drove the synergistic and trade-off relationships between HQ, CS, and WY. This study combined BBN and ESs to develop a new method for investigating ES functions and established a solid scientific foundation for ES management and macroeconomic growth planning.

BackgroundChronic kidney disease (CKD) is a common complication among individuals with hypertension. We aimed to identify the prevalence of CKD and the sex and race disparities within the hypertensive population in the United States from 2001–2016.MethodsA total of 16,148 participants with hypertension were included, representing 561,909,480 individuals from the U.S. population between 2001 and 2016, as documented in the National Health and Nutrition Examination Survey. The prevalence of albuminuria and CKD stage were assessed using survey-weighted general linear regression analysis. Heterogeneity in the CKD stage among the hypertensive population, stratified by sex and race, was identified through survey-weighted logistic regression analysis.ResultsOverall, the prevalence of albuminuria remained stable (p for trend = 0.3196), and changes in the CKD stage were minimal (p for trend > 0.05) from 2001–2016. In the analysis of CKD stage heterogeneity by sex and race, the prevalence of CKD was higher among women than men and higher among individuals of other races combined than non-Hispanic Whites, but the differences were not statistically significant.ConclusionThe overall CKD stage within the hypertensive population plateaued between 2001 and 2016. Our findings highlight the importance of continuous monitoring and potential refinement of renoprotection strategies in individuals with hypertension to mitigate the persistent burden of CKD and address health disparities among different demographic groups.

BackgroundThe severity, symptoms, and outcome of COVID-19 is thought to be closely linked to how the virus enters host cells. This process involves the key roles of angiotensin-converting enzyme 2 (ACE2) and the Tyrosine protein kinase receptor UFO (AXL) receptors. However, there is limited research on the circulating levels of ACE2 and AXL and their implications in COVID-19.MethodsA control group of 71 uninfected individuals was also included in the study. According to the Guidance for Corona Virus Disease 2019 (10th edition), a cohort of 358 COVID-19 patients were categorized into non-severe and severe cases. Serum ACE2/AXL levels in COVID-19 patients were detected by enzyme-linked immunosorbent assay (ELISA) at different time points post-COVID-19 infection, including days 0-7, 8-15, 31-179 and >180 days. Serum SARS-CoV-2 IgG/IgM antibodies in COVID-19 patients at the same intervals were assessed by using an iFlash 3000 Chemiluminescence Immunoassay Analyzer. The receiver operating characteristic (ROC) curves were used to assess the diagnostic value of the biological markers, and the association between laboratory parameters and illness progression were explored.ResultsCompared with the uninfected group, the levels of ACE2 and AXL in the COVID-19 group were decreased, and the SARS-COV-2 IgG level was increased. AXL (AUC = 0.774) demonstrated a stronger predictive ability for COVID-19 than ACE2. In the first week after infection, only the level of AXL was statistically different between severe group and non-severe group. After first week, the levels of ACE2 and AXL were different in two groups. Moreover, in severe COVID-19 cases, the serum ACE2, AXL, and SARS-COV-2 IgM levels reached a peak during days 8–15 before declining, whereas serum SARS-COV-2 IgG levels continued to rise, reaching a peak at day 31-180 days before decreasing. In addition, the AXL level continued to decrease and the SARS-COV-2 IgG level continued to increase in the infected group after 180 days compared to the uninfected group.ConclusionsThe levels of serum ACE2 and AXL correlate with COVID-19 severity. However, AXL can also provide early warning of clinical deterioration in the first week after infection. AXL appears to be a superior potential molecular marker for predicting COVID-19 progression.

The aim of this study is to clarify the role of physical activity level and physical function on cognitive function of the elderly. A nested case–control investigation from a middle-aged and elderly cognitive health cohort was conducted. 103 mild cognitive impairment (MCI) patients were selected for the purpose of the study and matched 1:1 according to age and sex. Handgrip strength, gait speed and 5-time chair stand test were used to evaluate physical function. The physical activity scale for the elderly (PASE) was used to assess physical activity level. The Montreal cognitive assessment (MoCA) was used to quickly screen the mild cognitive impairment of the subjects. Body composition was estimated by bioelectrical impedance analysis. The total score of MoCA and the scores of different cognitive domains in two groups were different, handgrip strength was lower in the MCI group. Multivariate logistic regression model results showed that handgrip strength decreased could increase the risk of MCI(OR = 3.008, 95%CI: 1.421,6.369), higher PASE score was correlated with lower risk of MCI (OR = 0.402, 95%CI: 0.168,0.966). After combining body composition indices, handgrip strength and PASE score remained significantly associated with the occurrence of MCI, and there is an interaction. Logistic regression models were used for receiver operating characteristic curve analysis, all models demonstrate a good level of predictive performance for MCI. Physical activity level and physical function are associated with mild cognitive impairment. Higher physical activity level, normal handgrip strength are correlated with lower risk of MCI.

Abstract Acacetin, one of the flavonoid compounds, is a natural product found in various plants, including Silver birch, and Damiana. Previous studies showed that acacetin has anti-cancer effects on many kinds of cancer cells, however, the role of and the mechanisms of actions of acacetin on non-small cell lung cancer (NSCLC) cells is still not fully understood. Herein, we found that, in vitro, acacetin inhibited the proliferation, invasion, and migration of NSCLC cells, A549 and H460, in a dose-dependent manner. Meanwhile, flow cytometry assay results showed that acacetin induced G2/M phase cell cycle arrest, and apoptosis of NSCLC cells. In vivo, acacetin suppressed tumor formation of A549-xenografted nude mice model with no obvious toxicities. Western blotting results showed that the protein levels of cell cycle-related proteins cyclin B1, cyclin D, and anti-apoptotic protein Bcl-2 had decreased, while the apoptosis-related protein Bak had increased both in NSCLC cells and in A549-xenografted tumor tissues. For investigating the molecular mechanism behind the biological effects of acacetin on NSCLC, we found that acacetin induced the expression levels of tumor suppressor p53 both in vitro and in vivo. MicroRNA, miR-34a, the direct target of p53, has been shown anti-NSCLC proliferation effects by suppressing the expression of its target gene programmed death ligand 1 (PD-L1). We found that acacetin upregulated the expression levels of miR-34a, and downregulated the expression levels of PD-L1 of NSCLC cells in vitro and of tumors in vivo. In vitro, knockdown p53 expression by siRNAs reversed the induction effects of acacetin on miR34a expression and abolished the inhibitory activity of acacetin on NSCLC cell proliferation. Furthermore, using agomir and antagomir to overexpress and suppress the expression miR-34a in NSCLC cells was also examined. We found that miR-34a agomir showed similar effects as acacetin on A549 cells, while miR-34a antagomir could partially or completely reverse acacetin’s effects on A549 cells. In vivo, intratumor injection of miR-34a antagomir could drastically suppress the anti-tumor formation effects of acacetin in A549-xenografted nude mice. Overall, our results showed that acacetin inhibits cell proliferation and induces cell apoptosis of NSCLC cells by regulating miR-34a.

Abstract Background Latent tuberculosis infection (LTBI) often progresses to active tuberculosis, necessitating the development of novel vaccine to prevent LTBI. In this study, we aimed to design a Mycobacterium tuberculosis (M. tuberculosis) vaccine that could elicit a potent immune response to prevent LTBI. Methods We used bioinformatics and immunoinformatics techniques to develop a multi‐epitope vaccine (MEV) called C624P. The vaccine contained six cytotoxic T lymphocytes (CTL), two helper T lymphocytes (HTL), and four B‐cell epitopes derived from six antigens associated with LTBI and the Mycobacterium tuberculosis region of difference. We added Toll‐like receptor (TLR) agonists and PADRE peptide to the MEV to enhance its immunogenicity. We then analyzed the C624P vaccine's physical and chemical properties, spatial structure, molecular docking with TLRs, and immunological features. Results The C624P vaccine displayed good antigenicity and immunogenicity scores of 0.901398 and 3.65609, respectively. The vaccine structure was stable, with 42.82% α‐helix content, a Z‐value of −7.84, and a favored Ramachandran plot area of 85.84% after majorization. Molecular docking analysis showed that the C624P vaccine could bind tightly to TLR2 (−1011.0 kcal/mol) and TLR4 (−941.4 kcal/mol). Furthermore, the C624P vaccine effectively stimulated T and B lymphocytes, resulting in high levels of Th1 cytokines such as IFN‐γ and IL‐2. Conclusions The C624P vaccine represents a promising MEV for preventing LTBI. The vaccine's good antigenicity, immunogenicity, stability, and ability to activate immune responses suggest its effectiveness in preventing LTBI. Our study demonstrated the utility of bioinformatics and immunoinformatics techniques in designing safe and effective tuberculosis vaccines.

Abstract Imaging-guided photothermal therapy (PTT) for cancers recently gathered increasing focus thanks to its precise diagnosis and potent therapeutic effectiveness. Croconaine (CR) dyes demonstrate potential in expanding utility for near infrared (NIR) dyes in bio-imaging/theranostics. However, reports on CR dyes for PTT are scarce most likely due to the short of the efficacious delivery strategies to achieve specific accumulation in diseased tissues to induce PTT. Extracellular vesicles (EVs) are multifunctional nanoparticle systems that function as safe platform for disease theragnostics, which provide potential benefits in extensive biomedical applications. Here, we developed a novel delivery system for photothermal molecules based on a CR dye that exerts photothermal activity through CDH17 nanobody-engineered EVs. The formed CR@E8-EVs showed strong NIR absorption, excellent photothermal performance, good biological compatibility and superb active tumor-targeting capability. The CR@E8-EVs can not only visualize and feature the tumors through CR intrinsic property as a photoacoustic imaging (PAI) agent, but also effectively retard the tumor growth under laser irradiation to perform PTT. It is expected that the engineered EVs will become a novel delivery vehicle of small organic photothermal agents (SOPTAs) in future clinical PTT applications.

Terminology plays a crucial role in shaping our understanding of a field. In this editorial, we focus on the widely used terms "wet end" and "wet end chemistry" within the realm of papermaking. By delving into historical records, our aim is to provide a deeper understanding and a clearer perspective on these terms. It is worth noting that exploring terminology can enhance comprehension and foster a more comprehensive understanding of the subject matter.

ObjectivesIn this study, we compared the dynamic changes in body composition during XELOX/SOX chemotherapy in patients with gastric cancer. Furthermore, we investigated the potential impact of these changes on the occurrence of toxic side effects.MethodsPatients with gastric cancer who received adjuvant or first-line XELOX/SOX chemotherapy between January 2020 and June 2023 were enrolled. The Brief Conghua Scale was used to assess energy intake, and nutritional management was carried out with reference to the Chinese Guidelines for Nutritional Therapy of Cancer 2020. The NRS 2002 Nutritional Risk Screening Scale, PG-SGA scale, bioelectrical impedance analysis, and dynamic changes in lumbar 3 vertebral skeletal muscle index were compared between baseline and post-chemotherapy in the study. The neutropenia was evaluated using the Common Terminology Criteria for Adverse Events V.5.0, developed by the National Institutes of Health.ResultsDynamic follow-up was completed in 39 cases, with a mean follow-up time of 117.62 ± 43.38 days. The incidence of sarcopenia increased significantly after chemotherapy, escalating from 46.2% to 51.3%. After chemotherapy, the mean L3SMI decreased from 36.00 cm2/m2 to 34.99 cm2/m2. Furthermore, when compared to pre-chemotherapy values, the body composition indexes body mass index (BMI), SL3, fat mass free index (FFMI), lean body mass (LBM), and body surface area (BSA) were significantly reduced after chemotherapy. Regardless of baseline or post-chemotherapy status, the incidence of grade ≥ 3 neutropenia was significantly higher in the sarcopenia group than in the non-sarcopenia group. Furthermore, when the skeletal muscle index decreased during chemotherapy, the incidence of grade ≥ 3 neutropenia was significantly higher in both the sarcopenia and non-sarcopenia groups compared to baseline. When the incidence of grade ≥ 3 neutropenia in the post-chemotherapy sarcopenia group was compared to baseline status, the increase was significantly higher in the sarcopenia group than in the maintenance/increase group.ConclusionsSkeletal muscle mass decreased progressively during XELOX/SOX chemotherapy in gastric cancer patients, followed by a higher incidence of grade ≥ 3 neutropenia.

Objective: Protein disulfide isomerase A3 (PDIA3) promotes the correct folding of newly synthesized glycoproteins in the endoplasmic reticulum. PDIA3 is overexpressed in most tumors, and it may become a biomarker of cancer prognosis and immunotherapy. Our study aims to detect the expression level of PDIA3 in gastric cancer (GC) and its association with GC development as wells as the underlying mechanisms. Methods: GC cell lines with PDIA3 knockdown by siRNA, CRISPR-cas9 sgRNAs or a pharmacological inhibitor of LOC14 were prepared and used. PDIA3 knockout GC cells were established by CRISPR-cas9-PDIA3 system. The proliferation, migration, invasion and cell cycle of GC cells were analyzed by cell counting kit-8 assay, wound healing assay, transwell assay and flow cytometry, respectively. Immunodeficient nude mice was used to evaluate the role of PDIA3 in tumor formation. Quantitative PCR and western blot were used for examining gene and protein expressions. RNA sequencing was performed to see the altered gene expression. Results: The expressions of PDIA3 in GC tissues and cells were increased significantly, and its expression was negatively correlated with the three-year survival rate of GC patients. Down-regulation of PDIA3 by siRNA, LOC14 or CRISPR-cas9 significantly inhibited proliferation, invasion and migration of GC cells TMK1 and AGS, with cell cycle arrested at G2/M phase. Meanwhile, decreased PDIA3 significantly inhibited growth of tumor xenograft in vivo. It was found that cyclin G1 (encoded by CCNG1 gene) expression was decreased by downregulation of PDIA3 in GC cells both in vitro and in vivo. In addition, protein levels of other cell cycle related factors including cyclin D1, CDK2, and CDK6 were also significantly decreased. Further study showed that STAT3 was associated with PDIA3-mediated cyclin G1 regulation. Conclusion: PDIA3 plays an oncogenic role in GC. Our findings unfolded the functional role of PDIA3 in GC development and highlighted a novel target for cancer therapeutic strategy.

IntroductionAmyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease with poorly understood pathophysiology. Recent studies have highlighted systemic inflammation, especially the role of circulating inflammatory proteins, in ALS.MethodsThis study investigates the potential causal link between these proteins and ALS. We employed a two-sample Mendelian Randomization(MR) approach, analyzing data from large-scale genome-wide association studies to explore the relationship between 91 circulating inflammatory proteins and ALS. This included various MR methods like MR Egger, weighted median, and inverse-variance weighted, complemented by sensitivity analyses for robust results.ResultsSignificant associations were observed between levels of inflammatory proteins, including Adenosine Deaminase, Interleukin-17C, Oncostatin-M, Leukemia Inhibitory Factor Receptor, and Osteoprotegerin, and ALS risk. Consistencies were noted across different P-value thresholds. Bidirectional MR suggested that ALS risk might influence levels of certain inflammatory proteins.DiscussionOur findings, via MR analysis, indicate a potential causal relationship between circulating inflammatory proteins and ALS. This sheds new light on ALS pathophysiology and suggests possible therapeutic targets. Further research is required to confirm these results and understand the specific roles of these proteins in ALS.

BackgroundStreet greenery may have a profound effect on residents’ active travel (AT), a mode of transportation involving walking and cycling. This study systematically reviewed the scientific evidence on the effects of street greenery on active travel.MethodsA comprehensive search was performed using keywords and references in PubMed, Web of Science, Scopus, and Cochrane Library. The review included studies that met the following criteria: (1) Study design: experimental studies, cross sectional studies, (2) Participants: individuals of all ages, (3) Exposure variables: street greenery, including street vegetation (e.g., trees, shrubs, and lawns), (4) Outcomes: active travel behaviors (walking, cycling), (5) Article type: peer-reviewed articles, (6) Search time window: from the inception of relevant electronic literature database until 21 June 2023, (7) Geographic scope: worldwide; (8) Language: articles in English.ResultsTwenty-six cross-sectional studies met the inclusion criteria and were analyzed. These studies employed objective metrics for assessing street greenery and varied methodologies to measure AT, including 14 using subjective measurements (like self-reported surveys), 10 using objective data (such as mobile app analytics), and two studies combined both approaches. This review identifies a generally positive impact of street greenery on active travel in various aspects. However, the extent of this influence varies with factors such as temporal factors (weekdays vs. weekends), demographic segments (age and gender), proximity parameters (buffer distances), and green space quantification techniques. Street greenness promotes active travel by enhancing environmental esthetics, safety, and comfort, while also improving air quality, reducing noise, and fostering social interactions. In addition, the study suggests that variables like weather, seasonality, and cultural context may also correlate with the effectiveness of street greenery in encouraging active travel.ConclusionStreet greenery positively influences active travel, contributing to public health and environmental sustainability. However, the findings also indicate the need for more granular, experimental, and longitudinal studies to better understand this relationship and the underlying mechanisms. These insights are pivotal for urban planners and policymakers in optimizing green infrastructure to promote active transportation, taking into account local demographics, socio-economic factors, and urban design.

The incidence of hepatocellular carcinoma (HCC) ranks first among primary liver cancers, and its mortality rate exhibits a consistent annual increase. The treatment of HCC has witnessed a significant surge in recent years, with the emergence of targeted immune therapy as an adjunct to early surgical resection. Adoptive cell therapy (ACT) using tumor-infiltrating lymphocytes (TIL) has shown promising results in other types of solid tumors. This article aims to provide a comprehensive overview of the intricate interactions between different types of TILs and their impact on HCC, elucidate strategies for targeting neoantigens through TILs, and address the challenges encountered in TIL therapies along with potential solutions. Furthermore, this article specifically examines the impact of oncogenic signaling pathways activation within the HCC tumor microenvironment on the infiltration dynamics of TILs. Additionally, a concise overview is provided regarding TIL preparation techniques and an update on clinical trials investigating TIL-based immunotherapy in solid tumors.

IntroductionUnderstanding speech in background noise is an effortful endeavor. When acoustic challenges arise, linguistic context may help us fill in perceptual gaps. However, more knowledge is needed regarding how different types of background noise affect our ability to construct meaning from perceptually complex speech input. Additionally, there is limited evidence regarding whether perceptual complexity (e.g., informational masking) and linguistic complexity (e.g., occurrence of contextually incongruous words) interact during processing of speech material that is longer and more complex than a single sentence. Our first research objective was to determine whether comprehension of spoken sentence pairs is impacted by the informational masking from a speech masker. Our second objective was to identify whether there is an interaction between perceptual and linguistic complexity during speech processing.MethodsWe used multiple measures including comprehension accuracy, reaction time, and processing effort (as indicated by task-evoked pupil response), making comparisons across three different levels of linguistic complexity in two different noise conditions. Context conditions varied by final word, with each sentence pair ending with an expected exemplar (EE), within-category violation (WV), or between-category violation (BV). Forty young adults with typical hearing performed a speech comprehension in noise task over three visits. Each participant heard sentence pairs presented in either multi-talker babble or spectrally shaped steady-state noise (SSN), with the same noise condition across all three visits.ResultsWe observed an effect of context but not noise on accuracy. Further, we observed an interaction of noise and context in peak pupil dilation data. Specifically, the context effect was modulated by noise type: context facilitated processing only in the more perceptually complex babble noise condition.DiscussionThese findings suggest that when perceptual complexity arises, listeners make use of the linguistic context to facilitate comprehension of speech obscured by background noise. Our results extend existing accounts of speech processing in noise by demonstrating how perceptual and linguistic complexity affect our ability to engage in higher-level processes, such as construction of meaning from speech segments that are longer than a single sentence.

Abstract Aberrant activation of epidermal growth factor receptor (EGFR) signaling is closely related to the development of non-small cell lung cancer (NSCLC). However, targeted EGFR therapeutics such as tyrosine kinase inhibitors (TKIs) face the challenge of EGFR mutation-mediated resistance. Here, we showed that the reduced JmjC domain-containing 5 (JMJD5) expression is negatively associated with EGFR stability and NSCLC progression. Mechanically, JMJD5 cooperated with E3 ligase HUWE1 to destabilize EGFR and EGFR TKI-resistant mutants for proteasomal degradation, thereby inhibiting NSCLC growth and promoting TKI sensitivity. Furthermore, we identified that JMJD5 can be transported into recipient cells via extracellular vesicles, thereby inhibiting the growth of NSCLC. Together, our findings demonstrate the tumor-suppressive role of JMJD5 in NSCLC and suggest a putative therapeutic strategy for EGFR-related NSCLC by targeting JMJD5 to destabilize EGFR.

Abstract Colorectal cancer (CRC) is one of the malignant tumors with the highest morbidity and mortality and poor prognosis. The mammalian gene family of Cab45/reticulocalbin/ERC-45/calumenin (CREC) consists of RCN1, RCN2, RCN3, SDF4 and CALU. Although CREC family members have been associated with CRC, the expression pattern, prognostic value, and the role of CREC family in CRC remain unclear. In this study, the expression, survival and biological functions of CREC family in CRC were determined via bioinformatic datasets analysis and experimental verification on clinical CRC specimen. Bioinformatic analysis showed that the expression levels of most CREC family genes were higher in CRC tissues than in normal colorectal tissues. The qPCR and western blot results also revealed that the transcriptional and protein levels of CREC family were elevated in CRC tissues compared with adjacent tissues. Besides, CREC family was significantly correlated with advanced tumor stage and poor prognosis of CRC patients. The expression levels of CREC family had correlations with genomic mutation and methylation, and with the infiltration levels of CD4 + T cells, macrophages, neutrophils, and dendritic cells in the microenvironment of CRC. Functional networks enrichment analysis indicated that the genes of CREC family were essential factors for CRC metastasis. Collectively, these findings suggest that CREC family might be potential targets for the treatment of CRC and candidate prognostic markers for CRC patients.

The objective of this study was to reveal the effect of rumen degradable starch (RDS) on bile acid metabolism and liver transcription in dairy goats using metabolomics and transcriptomics. Eighteen Guanzhong dairy goats of a similar weight and production level (body weight = 45.8 ± 1.54 kg, milk yield = 1.75 ± 0.08 kg, and second parity) were randomly assigned to 3 treatment groups where they were fed a low RDS (LRDS, RDS = 20.52% DM) diet, medium RDS (MRDS, RDS = 22.15% DM) diet, or high RDS (HRDS, RDS = 24.88% DM) diet, respectively. The goats were fed with the experimental diets for 5 weeks. On the last day of the experiment, all goats were anesthetized, and peripheral blood and liver tissue samples were collected. The peripheral blood samples were used in metabolomic analysis and white blood cell (WBC) count, whereas the liver tissue samples were used in transcriptomic analysis. Based on the metabolomics results, the relative abundances of primary bile acids in the peripheral blood were significantly reduced in the group that was fed the HRDS diet (P

This research investigates environmental inequalities within Guangzhou’s Huangpu District against the backdrop of rapid urbanisation and industrial expansion in Asia. This study identifies environmental hotspots, particularly in socially vulnerable areas characterised by high industrial density, using a vulnerability framework and analysing census and pollution data. Utilising satellite imagery, urban planning documents, and field research, we delve into the internal environmental conflicts arising from industrial land use. Our findings reveal how diverse stakeholders, guided by their rationales and interests, collectively contribute to spatial inequalities within a market-driven context. Importantly, we emphasise that environmental inequality transcends mere conflicts of interest among stakeholders and is fundamentally shaped by the prevailing market-oriented spatial development model in peri-urban areas. This model results in urban segmentation, socio-economic stratification, and an uneven distribution of environmental risks and resources. Our study advocates for a paradigmatic shift in China’s peri-urban spatial development and the integration of environmental protection and social equity alongside economic growth. We recommend moving away from short-term speculative practices and promoting long-term, community-engaged urban renewal strategies that harmonise economic progress with improved living standards and environmental sustainability.

IntroductionTubulin epsilon and delta complex 2 (TEDC2) is widely expressed in various human tissues and primarily governs centriole stability. However, the biological significance of TEDC2 in pan-cancer is unclear.MethodsIn this study, we employed R software and various online bioinformatics analysis tools to investigate the functional attributes of TEDC2 in human tumours and its potential involvement in immune response. The status of TEDC2 expression was evaluated in samples from the TCGA and GEO datasets, as well as in tumour and corresponding normal samples from the TCGA database. Subsequently, Kaplan-Meier estimates, clinical correlations, and univariate Cox regressions were used to analyze the 33 types of tumors from TCGA and determine the prognostic significance of TEDC2. Moreover, nomogram models were formulated using three distinct tumours, namely kidney renal clear cell carcinoma (KIRC), lung adenocarcinoma (LUAD), and liver hepatocellular carcinoma (LIHC), to evaluate the prognostic significance of TEDC2 in tumours. Furthermore, TEDC2 was investigated for its correlation with the levels of immune cell infiltration, and a functional enrichment analysis was conducted to identify potential signalling pathways involving TEDC2. ResultsDifferential analysis revealed that 16 tumour types expressed TEDC2 to a greater extent than normal tissues. The abnormal expression of TEDC2 can predict survival outcomes in patients with adrenocortical carcinoma (ACC), KIRC, kidney renal papillary cell carcinoma (KIRP), LUAD, LIHC, lower grade glioma (LGG), and thymoma (THYM). Subsequent results indicated that TEDC2 has the ability to influence ECM regulators, cell cycle, and Immune checkpoint-associated signalling pathways, which could potentially lead to a poor prognosis and tumour progression.DiscussionTEDC2 has been identified as a potential therapeutic target that could predict the prognosis of multiple tumour types, making it a promising target for reversing tumour development.

As a ligand-dependent transcription factor, retinoid-associated orphan receptor γt (RORγt) that controls T helper (Th) 17 cell differentiation and interleukin (IL)-17 expression plays a critical role in the progression of several inflammatory and autoimmune conditions. An emerging novel approach to the therapy of these diseases thus involves controlling the transcriptional capacity of RORγt to decrease Th17 cell development and IL-17 production. Several RORγt inhibitors including both antagonists and inverse agonists have been discovered to regulate the transcriptional activity of RORγt by binding to orthosteric- or allosteric-binding sites in the ligand-binding domain. Some of small-molecule inhibitors have entered clinical evaluations. Therefore, in current review, the role of RORγt in Th17 regulation and Th17-related inflammatory and autoimmune diseases was highlighted. Notably, the recently developed RORγt inhibitors were summarized, with an emphasis on their optimization from lead compounds, efficacy, toxicity, mechanisms of action, and clinical trials. The limitations of current development in this area were also discussed to facilitate future research.

Abstract Background There are differences in vitamin D levels between periodontitis and healthy individuals, but the effect of vitamin D on periodontitis is controversial. The purpose of this Meta-analysis is twofold: (1) compare vitamin D levels in individuals with or without periodontitis; (2) assess the effects of vitamin D supplementation during scaling and root planing (SRP) on periodontal clinical parameters in individuals with periodontitis. Methods A systematic search was conducted in five databases (PubMed, Web of Science, MEDLINE, EMBASE, and Cochrane library), published from the database inception to 12 September 2022. The Cochrane Collaboration Risk of bias (ROB) assessment tool, the risk of bias in non-randomized studies of intervention (ROBINS-I) tool, the Newcastle–Ottawa Quality Assessment Scale (NOS), and Agency for Healthcare Quality and Research (AHRQ) were used to evaluate randomized controlled trial (RCT), non-RCT, case–control study, and cross-sectional study, respectively. Statistical analysis was performed using RevMan 5.3 and Stata 14.0 software, with weighted mean difference (WMD), standardized mean difference (SMD) and 95% confidence intervals (CI) as the effect measures, and heterogeneity was tested by subgroup analysis, sensitivity analysis, Meta-regression. Results A total of 16 articles were included. The results of Meta-analysis showed that periodontitis was associated with lower serum vitamin D levels compared to normal population (SMD = -0.88, 95%CI -1.75 ~ -0.01, P = 0.048), while there was no significant difference in serum or saliva 25(OH)D levels between periodontitis and normal population. Additionally, the Meta-analysis showed that SRP + vitamin D and SRP alone had a statistically significant effect on serum vitamin D levels in individuals with periodontitis (SMD = 23.67, 95%CI 8.05 ~ 32.29, P = 0.003; SMD = 1.57, 95%CI 1.08 ~ 2.06, P

Abstract Background Antenatal depression (AD) is a major depressive disorder during pregnancy, which may lead to devastating sequelae for the expectant mothers and infants. This study aimed to investigate the prevalence, to analyze trajectory model based on EPDS score, and to explore the influence factors of AD among pregnant women in Chengdu, China. Methods Participants from four maternity hospitals in Chengdu, China were recruited when they had their first pregnancy medical check-up during March 2019 to May 2020. All participants were required to fill in Edinburgh Postnatal Depression Scale Chinese version (EPDS) once during three trimesters and provided information about their health status, social-demographic etc. The trajectory model, chi-square test and multivariate binary logistic regression were used to analyze all collected data. Results A total of 4560 pregnant women were recruited, while 1051 women completed the study. The prevalence of depression symptoms during the first, second and third trimesters were 32.92% (346/1051), 19.79% (208/1051) and 20.46% (215/1051) respectively. According to the results of the latent growth mixture modeling, the trajectory model of three categories based on EPDS score were identified in this study: low-risk group (38.2%, 401/1051), medium-risk group (54.8%, 576/1051) and high-risk group (7%, 74/1051). Good marital relationship (P = 0.007, OR = 0.33, 95% CI 0.147 ~ 0.74), good relationship with parents-in-law (P = 0.011, OR = 0.561, 95% CI 0.36 ~ 0.874), planned pregnancy (P = 0.018, OR = 0.681, 95% CI 0.496 ~ 0.936) were the protective factors while lower education level (P = 0.036, OR = 1.355, 95% CI 1.02 ~ 1.799), fear about dystocia (P = 0.0, OR = 1.729, 95% CI 1.31 ~ 2.283), recent major negative life events (P = 0.033, OR = 2.147, 95% CI 1.065 ~ 4.329) were the risk factors of medium-risk group. Good marital relationship (P = 0.005, OR = 0.2, 95% CI 0.065 ~ 0.615), good relationship with parents-in-law (P = 0.003, OR = 0.319, 95% CI 0.15 ~ 0.679) were also protective factors of high-risk group, but the risk factors for high-risk group were medical history (P = 0.046, OR = 1.836, 95% CI 1.011 ~ 3.334), pregnancy complications (P = 0.022, OR = 2.015, 95% CI 1.109 ~ 3.662), worry about dystocia (P = 0.003, OR = 2.365, 95% CI 1.347 ~ 4.153), recent major negative life events (P = 0.011, OR = 3.661, 95% CI 1.341 ~ 9.993). No protective or risk factors were identified for low-risk group. Conclusion Even the incidence and levels of depression in the first trimester of pregnancy were the highest, the probability of pregnancy women get depression during gestation period were higher than other population. Therefore, it’s important to monitor the psychological status of pregnant women during the whole pregnancy, especially in the first trimester. The study suggested a good partner relationship and good relations with parents-in-law both protected pregnant women from depression and promoted the well-being of mothers and children.

The objective of task allocation in unmanned systems is to complete tasks at minimal costs. However, the current algorithms employed for coordinating multiple unmanned systems in task allocation tasks frequently converge to local optima, thus impeding the identification of the best solutions. To address these challenges, this study builds upon the sheep flock optimization algorithm (SFOA) by preserving individuals eliminated during the iterative process within a prior knowledge set, which is continuously updated. During the reproduction phase of the algorithm, this prior knowledge is utilized to guide the generation of new individuals, preventing their rapid reconvergence to local optima. This approach aids in reducing the frequency at which the algorithm converges to local optima, continually steering the algorithm towards the global optimum and thereby enhancing the efficiency of task allocation. Finally, various task scenarios are presented to evaluate the performances of various algorithms. The results show that the algorithm proposed in this paper is more likely than other algorithms to escape from local optima and find the global optimum.

Image quality assessment (IQA) has a very important role and wide applications in image acquisition, storage, transmission and processing. In designing IQA models, human visual system (HVS) characteristics introduced play an important role in improving their performances. In this paper, combining image distortion characteristics with HVS characteristics, based on the structure similarity index (SSIM) model, a novel IQA model based on the perceived structure similarity index (PSIM) of image is proposed. In the method, first, a perception model for HVS perceiving real images is proposed, combining the contrast sensitivity, frequency sensitivity, luminance nonlinearity and masking characteristics of HVS; then, in order to simulate HVS perceiving real image, the real images are processed with the proposed perception model, to eliminate their visual redundancy, thus, the perceived images are obtained; finally, based on the idea and modeling method of SSIM, combining with the features of perceived image, a novel IQA model, namely PSIM, is proposed. Further, in order to illustrate the performance of PSIM, 5335 distorted images with 41 distortion types in four image databases (TID2013, CSIQ, LIVE and CID) are used to simulate from three aspects: overall IQA of each database, IQA for each distortion type of images, and IQA for special distortion types of images. Further, according to the comprehensive benefit of precision, generalization performance and complexity, their IQA results are compared with those of 12 existing IQA models. The experimental results show that the accuracy (PLCC) of PSIM is 9.91% higher than that of SSIM in four databases, on average; and its performance is better than that of 12 existing IQA models. Synthesizing experimental results and theoretical analysis, it is showed that the proposed PSIM model is an effective and excellent IQA model.

Abstract Controversy exists as toward the association of excessive fruits intake and certain disease risks. Longan is an edible fruit rich in high levels of fructose, glucose and sucrose. Herein, the effect of longan fruit on the development of nonalcoholic fatty liver disease (NAFLD) was investigated. Longan extracts at the doses of 4.0 g/kg, 8.0, and 16.0 g/kg were orally administered for 4 weeks to healthy C57BL/6J mice or to C57BL/6J mice fed with a HFD diet. In mice fed with a normal diet, repeated longan intake for 4 weeks at excess doses (8 or 16 g/kg), but not the normal dose (4 g/kg), promoted inflammation and gut dysbiosis‐like status and reduced short‐chain fatty acids (SCFAs) production. In high‐fat diet (HFD)‐fed mice, longan intake at 4 g/kg hardly influenced the NAFLD development. In contrast, excess longan intake (8 or 16 g/kg) promoted NAFLD pathogenesis, including increased abnormality in hepatic indices, elevated inflammation, and gut permeability associated with more severe liver steatosis and fibrosis. Moreover, the exacerbated pathogenic markers were positively correlated with increased blood sugar, aggravated HFD‐associated microbial dysbiosis. Effects mediated by excess longan intake resembled that of equivalent free sugars supplementation, suggesting that high level of free sugars in fruits contributed to the promotion of NAFLD development as demonstrated in case of excessive longan intake.

Abstract B7 family members act as co-stimulatory or co-inhibitory molecules in the adaptive immune system. Thisstudy aimed to investigate the dysregulation, prognostic value and regulatory network of B7 family members in non-small cell lung cancer (NSCLC). Data for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients were extracted from public databases. Patient prognosis was determined by Kaplan–Meier analysis. The downstream signaling pathways of B7 family were identified via GO and KEGG analysis. The key B7 related genes were selected by network, correlation and functional annotation analysis. Most B7 family members were dysregulated in LUAD and LUSC. The expression of B7-1/2/H3 and B7-H5 were significantly associated with overall survival in LUAD and LUSC, respectively. The major pathway affected by B7 family was the EGFR tyrosine kinase inhibitor resistance and ErbB signaling pathway. MAPK1, MAPK3 and MAP2K1 were pivotal B7 related genes in both LUAD and LUSC. This study reveals an overall dysregulation of B7 family members in NSCLC and highlights the potential of combination use of tyrosine kinase inhibitors or MEK/ERK inhibitors with B7 member blockade for NSCLC treatment.

Objectives Prosthesis awareness is the perception of foreign bodies, which has a critical effect on the function of the prosthetic joint. In total hip arthroplasty (THA), the direct anterior approach (DAA) has more advantages than the posterior approach (PA), including superior rehabilitation outcomes. This study was to evaluate the recovery of “prosthesis awareness” through these two approaches. Methods Three hundred and seventy‐six patients who received THA with either DAA (n = 41) or PA (n = 335) from January 2016 to December 2017 were retrospectively analyzed. The Forgotten Joint Score‐12 (FJS‐12), Harris hip score (HHS), and visual analog scale (VAS) analyses were used to evaluate the recovery of “prosthesis awareness” in these patients 2 weeks, 1, 3, 6, and 12 months after surgery. The student t‐test, Wilcoxon rank sum test, chi‐square test, and MANOVA were used to compare the differences among groups. Results We found that DAA patients had higher FJS‐12 scores than PA patients at 2 weeks (42.15 ± 3.36 vs. 38.09 ± 3.28, p = 0.042), 1 month (49.06 ± 5.14 vs. 41.11 ± 5.21, p = 0.038), and 3 months (53.23 ± 4.07 vs. 48.09 ± 3.71, t = 3.152, p = 0.045). And the recovery rates of FJS‐12 scores in DAA and PA groups at 2 weeks, 1 month, and 3 months after surgery were 75.46% ± 6.04%, 84.05% ± 6.57%, 91.37% ± 7.13%, and 74.14% ± 5.54%, 78.16% ± 6.01%, 88.23% ± 6.42%, respectively. To compare the recovery effects of the two procedures in more detail, we classified the 12 items in FJS‐12 that evaluate different types of gravity center motions into three categories: low‐movement group (LG), middle‐movement group (MG), and high‐movement group (HG). Interestingly, DAA patients had significantly higher HG than PA patients at 2 weeks, 1 month, and 3 months after operation (t = 3.225, p = 0.022 at 2 weeks, t = 3.081, p = 0.041 at 1 month and t = 2.783, p = 0.046 at 3 months), whereas no significant differences were observed in LG‐ and MG‐related items. In addition, there were no significant differences in HHS and VAS scores between DAA and PA patients at 2 weeks (p = 0.102, p = 0.093), or from 1 month to 12 months (each p > 0.05). Conclusions DAA‐mediated THA is superior to PA in terms of prosthesis adaptability and recovery of hip joint motion in the first 3 months after surgery, especially concerning high‐movement gravity center motions.

Abstract Sepsis is a difficult‐to‐treat systemic condition in which liver dysfunction acts as both regulator and target. However, the dynamic response of diverse intrahepatic cells to sepsis remains poorly characterized. Capsaicin (CAP), a multifunctional chemical derived from chilli peppers, has recently been shown to potentially possess anti‐inflammatory effects, which is also one of the main approaches for drug discovery against sepsis. We performed single‐cell RNA transcriptome sequencing on 86,830 intrahepatic cells isolated from normal mice, cecal ligation and puncture‐induced sepsis model mice and CAP‐treated mice. The transcriptional atlas of these cells revealed dynamic changes in hepatocytes, macrophages, neutrophils, and endothelial cells in response to sepsis. Among the extensive crosstalk across these major subtypes, KC_Cxcl10 shared strong potential interaction with other cells when responding to sepsis. CAP mitigated the severity of inflammation by partly reversing these pathophysiologic processes. Specific cell subpopulations in the liver act collectively to escalate inflammation, ultimately causing liver dysfunction. CAP displays its health‐promoting function by ameliorating liver dysfunction induced by sepsis. Our study provides valuable insights into the pathophysiology of sepsis and suggestions for future therapeutic gain.

BackgroundBipolar disorder and metabolic syndrome are both associated with the expression of immune disorders. The current study aims to find the effective diagnostic candidate genes for bipolar affective disorder with metabolic syndrome.MethodsA validation data set of bipolar disorder and metabolic syndrome was provided by the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were found utilizing the Limma package, followed by weighted gene co-expression network analysis (WGCNA). Further analyses were performed to identify the key immune-related center genes through function enrichment analysis, followed by machine learning-based techniques for the construction of protein–protein interaction (PPI) network and identification of the Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF). The receiver operating characteristic (ROC) curve was plotted to diagnose bipolar affective disorder with metabolic syndrome. To investigate the immune cell imbalance in bipolar disorder, the infiltration of the immune cells was developed.ResultsThere were 2,289 DEGs in bipolar disorder, and 691 module genes in metabolic syndrome were identified. The DEGs of bipolar disorder and metabolic syndrome module genes crossed into 129 genes, so a total of 5 candidate genes were finally selected through machine learning. The ROC curve results-based assessment of the diagnostic value was done. These results suggest that these candidate genes have high diagnostic value.ConclusionPotential candidate genes for bipolar disorder with metabolic syndrome were found in 5 candidate genes (AP1G2, C1orf54, DMAC2L, RABEPK and ZFAND5), all of which have diagnostic significance.

Polygonum perfoliatum L. is an herbal medicine that has been extensively used in traditional Chinese medicine to treat various health conditions ranging from ancient internal to surgical and gynecological diseases. Numerous studies suggest that P. perfoliatum extract elicits significant anti-tumor, anti-inflammatory, anti-bacterial, and anti-viral effects. Nevertheless, the underlying mechanisms of its anti-liver cancer effects remain poorly understood. Our study suggests that P. perfoliatum stem extract (PPLA) has a favorable safety profile and exhibits a significant anti-liver cancer effect both in vitro and in vivo. We identified that PPLA activates the cGMP-PKG signaling pathway, and key regulatory genes including ADRA1B, PLCB2, PRKG2, CALML4, and GLO1 involved in this activation. Moreover, PPLA modulates the expression of genes responsible for the cell cycle. Additionally, we identified four constituents of PPLA, namely taxifolin, myricetin, eriodictyol, and pinocembrin, that plausibly act via the cGMP-PKG signaling pathway. Both in vitro and in vivo experiments confirmed that PPLA, along with its constituting compounds taxifolin, myricetin, and eriodictyol, exhibit potent anti-cancer activities and hold the promise of being developed into therapeutic agents.

BackgroundAs a primary source of added sugars in the US diet, sugar-sweetened beverage (SSB) consumption is presumed to contribute to obesity prevalence and poor oral health. We systematically synthesized and quantified evidence from US-based natural experiments concerning the impact of SSB taxes on beverage prices, sales, purchases, and consumption.MethodsA keyword and reference search was performed in PubMed, Web of Science, Cochrane Library, Scopus, and EconLit from the inception of an electronic bibliographic database to Oct 31, 2022. Meta-analysis was conducted to estimate the pooled effect of soda taxes on SSB consumption, prices, passthrough rate, and purchases.ResultsTwenty-six natural experiments, all adopting a difference-in-differences approach, were included. Studies assessed soda taxes in Berkeley, Oakland, and San Francisco in California, Philadelphia in Pennsylvania, Boulder in Colorado, Seattle in Washington, and Cook County in Illinois. Tax rates ranged from 1 to 2 ¢/oz. The imposition of the soda tax was associated with a 1.06 ¢/oz. (95% confidence interval [CI] = 0.90, 1.22) increase in SSB prices and a 27.3% (95% CI = 19.3, 35.4%) decrease in SSB purchases. The soda tax passthrough rate was 79.7% (95% CI = 65.8, 93.6%). A 1 ¢/oz. increase in soda tax rate was associated with increased prices of SSBs by 0.84 ¢/oz (95% CI = 0.33, 1.35).ConclusionSoda taxes could be effective policy leverage to nudge people toward purchasing and consuming fewer SSBs. Future research should examine evidence-based classifications of SSBs, targeted use of revenues generated by taxes to reduce health and income disparities, and the feasibility of redesigning the soda tax to improve efficiency.

METTL7A is a protein-coding gene expected to be associated with methylation, and its expression disorder is associated with a range of diseases. However, few research have been carried out to explore the relationship between METTL7A and tumor malignant phenotype as well as the involvement potential mechanism. We conducted our research via a combination of silico analysis and molecular biology techniques to investigate the biological function of METTL7A in the progression of cancer. Gene expression and clinical information were extracted from the TCGA database to explore expression variation and prognostic value of METTL7A. In vitro, CCK8, transwell, wound healing and colony formation assays were conducted to explore the biological functions of METT7A in cancer cell. GSEA was performed to explore the signaling pathway involved in METTL7A and validated via western blotting. In conclusion, METTL7A was downregulated in most cancer tissues and its low expression was associated with shorter overall survival. In melanoma, METTL7A downregulation was associated with poorer clinical staging, lower levels of TIL infiltration, higher IC50 levels of chemotherapeutic agents, and poorer immunotherapy outcomes. QPCR results confirm that METTL7A is down-regulated in melanoma cells. Cell function assays showed that METTL7A knockdown promoted proliferation, invasion, migration and clone formation of melanoma cells. Mechanistic studies showed that METTL7A inhibits tumorigenicity through the p53 signaling pathway. Meanwhile, METTL7A is also a potential immune regulatory factor.

Over a third of the global chemical production and sales occurred in China, which make effective assessment and management for chemicals produced by China’s chemical industry essential not just for China but for the world. Here, we systematical assessed the persistence (P), bioaccumulation (B), mobility (M) and toxicity (T) potency properties for the chemicals listed in Inventory of Existing Chemical Substances of China (IECSC) via experimental data retrieved from large scale databases and in silico data generated with well-established models. Potential PBT, PMT and PB&MT substances were identified. High risk potentials were highlighted for groups of synthetic intermediates, raw materials, as well as a series of biocides. The potential PBT and PMT synthetic intermediates and/or raw materials unique to the IECSC were dominated with organofluorines, for example, the intermediates used as electronic light-emitting materials. Meanwhile, the biocides unique to the IECSC were mainly organochlorines. Some conventional classes of insecticides, such as organochlorines and pyrethroids, were classified as being of high concern. We further identified a group of PB&MT substances that were considered to be both “bioaccumulative” and “mobile”. Their properties and common substructures for several major clusters were characterized. The present results prioritized groups of substances with high potentials to cause adverse effects to the environment and humans, many of which have not yet been fully recognized.