Objective Investigate the expression level of discs large homolog associated protein 5(DLGAP5)in oral squamous cell carcinoma(OSCC)and analyze its effects on cell proliferation,migration,invasion capacity,and the Warburg effect.Methods Bioinformatics analysis was performed to identify the potential therapeutic targets for OSCC.A total of 72 OSCC tissue samples and 40 adjacent non-cancerous tissue samples collected in the First Affiliated Hospital of Shihezi University from 2013 to 2024 were included,and the clinical pathological and prognostic data were collected from patients.Immunohistochemistry assay was applied to detect the protein expression of DLGAP5,and its association with clinical pathological features was analyzed.Kaplan-Meier survival curve was plotted for survival analysis,and Cox regression model was employed to analyze the prognostic factors.The expression of DLGAP5 at mRNA and protein levels was detected in HOK,SCC-9,SCC-15,SCC-25,and CAL-27 cell lines with RT-qPCR and Western blotting,respectively.Four small interfering RNAs(siRNAs)were designed to target the DLGAP5 sequence,and then based on the transfection efficiency,the sequence with optimal silencing effect was selected for subsequent functional studies.After DLGAP5 was silenced in the CAL-27 and SCC-15 cells,Western blotting was applied to detect the expression of hexokinase 2(HK2)and enolase 1(ENO1),CCK-8,scratch healing and Transwell assays were conducted to assess cell proliferation,migration,and invasion capabilities,and glucose,lactate,and ATP detection kits were utilized to determine the glycolytic metabolic levels in OSCC cells.Results Bioinformatics analysis indicates that DLGAP5 is a potential key therapeutic target for OSCC.Experimental validation demonstrated that DLGAP5 was highly expressed in both OSCC tissues and cells(P<0.05).Analysis of clinical pathology and prognostic data revealed that DLGAP5 expression level was significantly correlated with tumor TNM stage,lymph node metastasis,and differentiation grade in OSCC patients,and high DLGAP5 expression was associated with poor prognosis(P<0.05).DLGAP5 silencing resulted in significantly reduced expression of HK2 and ENO1,markedly decreased levels of glycolytic metabolites(P<0.05),and notably declined cell proliferation,migration,and invasion capabilities(P<0.05).Conclusion DLGAP5 is highly expressed in OSCC.Silencing DLGAP5 may inhibit OSCC cell proliferation,migration,and invasion by indirectly regulating the Warburg effect,and the molecule is associated with poor prognosis in the OSCC patients.

Objective To explore the valve regurgitation status of left heart after the implantation of left ventricular assist device (LVAD) and its effect on prognosis of patients with LVAD implantation. Methods A total of 35 patients with cardiomyopathy who underwent magnetic levitation LVAD implantation at Zhongshan Hospital, Fudan University from February 2021 to July 2024 were retrospectively selected. Clinical data during hospitalization were collected, including preoperative basic data and postoperative valve regurgitation status. Telephone follow-ups were conducted to monitor patients’ survival status and transthoracic echocardiography was used to assess left valve function. Kaplan-Meier survival curves and log-rank test were employed to compare the survival rate of patients with different levels of valve regurgitation. Results The 35 patients had a mean age of (53.9±11.1) years, with 85.7% male, and 3 patients (8.6%) died during hospitalization. Preoperatively, 17 patients (48.6%) had moderate or greater mitral regurgitation, while all 35 patients had less than moderate aortic regurgitation. One month postoperatively, thirty patients were followed up, among which 24 patients (80%) had less than moderate mitral regurgitation, including 11 cases with alleviated regurgitation compared to pre-surgery; 6 patients (20%) had moderate or greater mitral regurgitation, including 4 cases with stable regurgitation and 2 cases with progression of regurgitation compared to pre-surgery; 2 patients (6.7%) had progression of aortic regurgitation to moderate or greater. The follow-up time was 1.2 (1.0, 2.1) years, with 1-year survival rate of 91.4% and 3-year survival rate of 71.1%. Survival analysis showed that the 3-year survival rate of patients with moderate or greater mitral regurgitation one month postoperatively was significantly lower than that of patients with less than moderate regurgitation (66.7% vs 83.3%, P＝0.046). Conclusions After the implantation of magnetic levitation LVAD, most patients showed improvement in mitral regurgitation, while aortic regurgitation remained unchanged. The degree of mitral regurgitation one month postoperatively is associated with prognosis.

Objective: To investigate the distribution characteristics and related factors of weight loss behavior among middle school students in Shanghai, so as to provide a reference for guiding scientific weight loss among middle school students. Methods: From May to June 2021, a stratified cluster random sampling method was used to select 16 758 junior and high school students in 16 districts of Shanghai. Youth Risk Behavior Surveillance System was administered to assess the basic condition and weight loss behaviors of the students. An unordered multinomial Logistic regression model was employed to analyze the factors associated with weight loss behaviors. Results: A total of 5 881 (35.09%) reported engaging in exercise for weight loss, 6 344 (37.86%) reported dieting for weight loss, and 461 (2.75%) engaged in unhealthy weight loss behaviors. The unordered multinomial Logistic regression analysis indicated that compared with the no weight loss behavior group, students from urban areas( OR =1.35,95% CI =1.10-1.66), those with Internet addiction ( OR =1.71,95% CI =1.23-2.38), those with victims of bullying ( OR =2.09, 95% CI =1.68-2.61), those experiencing insomnia ( OR =2.33,95% CI = 1.74-3.11), those feelings of sadness or despair ( OR =3.10, 95% CI =2.42- 3.97 ), and those who perceived their body weight as slightly heavy ( OR =2.77, 95% CI = 2.17-3.55) or very heavy ( OR =3.41, 95% CI =2.44-4.75) were more likely to engage in unhealthy weight loss behaviors ( P <0.05). Conclusions There are significant differences in weight loss behaviors among middle school students with varying characteristics in Shanghai. Negative emotions such as insomnia and feelings of sadness or despair, Internet addiction, cognitive bias in weight and experiences of bullying are identified as related factors for unhealthy weight loss behaviors. Targeted intervention measures should be implemented to guide students towards scientific approaches to weight management.

The present study delves into the cellular mechanisms underlying the antiviral effects of dehydrodiisoeugenol(DEH) by focusing on the transcription factor EB(TFEB)/autophagy-lysosome pathway. The cell counting kit-8(CCK-8) was utilized to assess the impact of DEH on the viability of human non-small cell lung cancer cells(A549). The inhibitory effect of DEH on the replication of influenza A virus(H1N1) was determined by real-time quantitative polymerase chain reaction(RT-qPCR). Western blot was employed to evaluate the influence of DEH on the expression level of the H1N1 virus nucleoprotein(NP). The effect of DEH on the fluorescence intensity of NP was examined by the immunofluorescence assay. A mouse model of H1N1 virus infection was established via nasal inhalation to evaluate the therapeutic efficacy of 30 mg·kg~(-1) DEH on H1N1 virus infection. RNA sequencing(RNA-seq) was performed for the transcriptional profiling of mouse embryonic fibroblasts(MEFs) in response to DEH. The fluorescent protein-tagged microtubule-associated protein 1 light chain 3(LC3) was used to assess the autophagy induced by DEH. Western blot was employed to determine the effect of DEH on the autophagy flux of LC3Ⅱ/LC3Ⅰ under viral infection conditions. Lastly, the role of TFEB expression in the inhibition of DEH against H1N1 infection was evaluated in immortalized bone marrow-derived macrophage(iBMDM), both wild-type and TFEB knockout. The results revealed that the half-maximal inhibitory concentration(IC_(50)) of DEH for A549 cells was(87.17±0.247)μmol·L~(-1), and DEH inhibited H1N1 virus replication in a dose-dependent manner in vitro. Compared with the H1N1 virus-infected mouse model, the treatment with DEH significantly improved the body weights and survival time of mice. DEH induced LC3 aggregation, and the absence of TFEB expression in iBMDM markedly limited the ability of DEH to counteract H1N1 virus replication. In conclusion, DEH exerts its inhibitory activity against H1N1 infection by activating the TFEB/autophagy-lysosome pathway.
Influenza A Virus, H1N1 Subtype/genetics* ; Animals ; Autophagy/drug effects* ; Humans ; Mice ; Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/genetics* ; Influenza, Human/metabolism* ; Lysosomes/metabolism* ; Orthomyxoviridae Infections/genetics* ; Eugenol/pharmacology* ; Antiviral Agents/pharmacology* ; Virus Replication/drug effects* ; A549 Cells ; Male

Anxiety disorder is a major symptom of autism spectrum disorder (ASD) with a comorbidity rate of ~40%. However, the neural mechanisms of the emergence of anxiety in ASD remain unclear. In our study, we found that hyperactivity of basolateral amygdala (BLA) pyramidal neurons (PNs) in Shank3 InsG3680 knock-in (InsG3680^+/+) mice is involved in the development of anxiety. Electrophysiological results also showed increased excitatory input and decreased inhibitory input in BLA PNs. Chemogenetic inhibition of the excitability of PNs in the BLA rescued the anxiety phenotype of InsG3680^+/+ mice. Further study found that the diminished control of the BLA by medial prefrontal cortex (mPFC) and optogenetic activation of the mPFC-BLA pathway also had a rescue effect, which increased the feedforward inhibition of the BLA. Taken together, our results suggest that hyperactivity of the BLA and alteration of the mPFC-BLA circuitry are involved in anxiety in InsG3680^+/+ mice.
Animals ; Prefrontal Cortex/metabolism* ; Basolateral Nuclear Complex/metabolism* ; Mice ; Anxiety/metabolism* ; Nerve Tissue Proteins/genetics* ; Male ; Gene Knock-In Techniques ; Pyramidal Cells/physiology* ; Mice, Transgenic ; Neural Pathways/physiopathology* ; Mice, Inbred C57BL ; Microfilament Proteins

One of the basic questions in the aging field is whether there is a fundamental difference between the aging of lower invertebrates and mammals. A major difference between the lower invertebrates and mammals is the abundancy of noncoding RNAs, most of which are not conserved. We have previously identified a noncoding RNA Terc-53 that is derived from the RNA component of telomerase Terc. To study its physiological functions, we generated two transgenic mouse models overexpressing the RNA in wild-type and early-aging Terc-/- backgrounds. Terc-53 mice showed age-related cognition decline and shortened life span, even though no developmental defects or physiological abnormality at an early age was observed, indicating its involvement in normal aging of mammals. Subsequent mechanistic study identified hyaluronan-mediated motility receptor (Hmmr) as the main effector of Terc-53. Terc-53 mediates the degradation of Hmmr, leading to an increase of inflammation in the affected tissues, accelerating organismal aging. adeno-associated virus delivered supplementation of Hmmr in the hippocampus reversed the cognition decline in Terc-53 transgenic mice. Neither Terc-53 nor Hmmr has homologs in C. elegans. Neither do arthropods express hyaluronan. These findings demonstrate the complexity of aging in mammals and open new paths for exploring noncoding RNA and Hmmr as means of treating age-related physical debilities and improving healthspan.
Animals ; Mice ; RNA, Untranslated/metabolism* ; Aging/genetics* ; Mice, Transgenic ; Telomerase/metabolism* ; RNA/genetics* ; Hippocampus/metabolism* ; Humans ; Mice, Inbred C57BL

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.

Traditional Chinese medicine (TCM) exerts integrative effects on complex diseases owing to the characteristics of multiple components with multiple targets. However, the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians, which has been a major challenge in the global acceptance and application of TCM. Therefore, a standardized TCM prescription system needs to be explored to promote its clinical application. In this study, we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation. We tested its efficacy against intracerebral hemorrhage (ICH). First, the top 100 ICH targets in the GeneCards database were screened according to their relevance scores. Then, SymMap and Traditional Chinese Medicine Systems Pharmacology (TCMSP) databases were applied to find out the target-related ingredients and ingredient-containing herbs, respectively. The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets. The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions. The absorbed components in the serum were detected. In a mouse model of ICH, the new prescription exerted multifaceted effects, including improved neurological function, as well as attenuated neuronal damage, cell apoptosis, vascular leakage, and neuroinflammation. These effects matched well with the core pathological changes in ICH. The multi-targets-directed gradient-weighting strategy presents a promising avenue for tailoring precise, multipronged, unbiased, and standardized TCM prescriptions for complex diseases. This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts.

Image 1.

Structural optimization of lead compounds is a crucial step in drug discovery. One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules, thereby accelerating the molecular optimization process. Deep molecular diffusion generative models simulate a gradual process that creates novel, chemically feasible molecules from noise. However, the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules, leading to challenges in modifying the scaffold-based molecular structures, and creates limitations in the stability and diversity of the generated molecules. To address these challenges, we propose a deep molecular diffusion generative model, the three-dimensional (3D) equivariant diffusion-driven molecular generation (3D-EDiffMG) model. The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder (dual-SWLEE) is introduced to encode both the bonding and non-bonding information based on strong and weak atomic interactions. Additionally, a gate multilayer perceptron (gMLP) block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies. The experimental results show that 3D-EDiffMG effectively generates unique, novel, stable, and diverse drug-like molecules, highlighting its potential for lead optimization and accelerating drug discovery.