This study aims to investigate the pathogenesis of precancerous lesions of gastric cancer(PLGC) and explore the potential molecular mechanism of Weifuchun Capsules(WFC) in treating PLGC via the nuclear factor-κB(NF-κB)/NOD-like receptor protein 3(NLRP3) inflammasome signaling pathway. Ninety male SPF-grade Wistar rats were randomized into a normal feeding group and a modeling group. The normal feeding group received a regular diet, while the modeling group was subjected to the disease-syndrome combined modeling of PLGC. Specifically, the rats had free access to the water containing 120 μg·mL~(-1) N-methyl-N'-nitro-N-nitrosoguanidine(MNNG) and received a diet containing 0.05% ranitidine in an irregular feeding pattern(alternations between fasting and overfeeding). After 15 weeks, the rats in the normal feeding group were randomized into control, control-NF-κB activator betulinic acid(C-BA), and control-NF-κB inhibitor pyrrolidine dithiocarbamaten(C-PDTC) groups. Meanwhile, the rats in the modeling group continuously underwent the modeling procedure and were randomized into model, WFC, model-NF-κB activator(M-BA), and model-NF-κB inhibitor(M-PDTC) groups. The model group and control group were given aseptic water by intragastric administration, once a day. WFC was given at a dose(432 mg·kg~(-1)) 6 times the equivalent dose for adults(body weight: 60 kg) by gavage, once a day. The rats in the C-BA and M-BA groups were administrated with BA by intraperitoneal injection at a dose of 10 mg·kg~(-1), twice a week. The rats in the C-PDTC and M-PDTC groups were administrated with PDTC by intraperitoneal injection at a dose of 50 mg·kg~(-1), twice a week. The interventions were carried out for 4 weeks. Histopathological changes of the gastric mucosa were observed and scored by hematoxylin-eosin(HE) and alcian blue-periodic acid Sthiff(AB-PAS) staining. The levels of inflammatory cytokines including interleukin(IL)-1β, IL-6, IL-18, tumor necrosis factor-alpha(TNF-α), and IL-10 in the gastric tissue were determined by enzyme-linked immunosorbent assay(ELISA). The expression levels of proteins associated with the NF-κB/NLRP3 inflammasome in the gastric mucosa were determined by Western blot. The positive expression areas of proteins related to NF-κB/NLRP3 inflammasome in the gastric mucosa were measured by immunohistochemistry. The results showed that compared with the control group, the model, C-BA, and M-BA groups showed significantly risen scores of mucosal inflammation, degree of inflammatory activity, gland atrophy, and intestinal metaplasia, and the model and M-BA groups showed significanly risen scores of dysplasia. Compared with the model group, the WFC group demonstrated significantly declined scores of mucosal inflammation and degree of inflammatory activity, as well as declined scores of intestinal metaplasia and dysplasia. Compared with the control group, the model and C-BA groups showed significantly elevated levels of IL-1β, IL-6, IL-18, and TNF-α in the gastric tissue, and the model group showed significantly elevated level of IL-10. In addition, the model and C-BA groups showed significantly up-regulated expression of NF-κB p65, NLRP3, cysteine-aspartic acid protease 1(caspase-1), and apoptosis-associated speck-like protein containing a CARD(ASC) in the gastric mucosa and increased positive expression areas of NF-κB p65, NLRP3, and ASC. Compared with the model group, the WFC group showed significantly decreased levels of IL-1β, IL-6, IL-18, TNF-α, and IL-10 in the gastric tissue, and the M-PDTC group showed significantly lowered levels of IL-1β, IL-18, and TNF-α in the gastric mucosa. Both WFC and M-PDTC groups demonstrated significantly down-regulated expression levels of NF-κB p65, phosphorylated NF-κB p65(p-NF-κB p65), NLRP3, and caspase-1 in the gastric mucosa, along with significant decreases in the positive expression areas of NF-κB p65, NLRP3, and ASC. In conclusion, the pathogenesis of PLGC is closely related to the activation of the NF-κB/NLRP3 inflammasome signaling pathway. WFC can alleviate mucosal inflammation, inhibit glandular atrophy, partially reverse intestinal metaplasia, and reduce dysplasia to delay the process of inflammation-cancer transformation, and meanwhile it can effectively lower the levels of inflammatory cytokines and down-regulate the expression of pathway-related proteins in the stomach. Therefore, WFC may treat PLGC by inhibiting the NF-κB/NLRP3 inflammasome signaling pathway.
Animals ; Male ; NF-kappa B/genetics* ; Rats ; Rats, Wistar ; Drugs, Chinese Herbal/administration & dosage* ; Signal Transduction/drug effects* ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Stomach Neoplasms/pathology* ; Inflammasomes/genetics* ; Humans ; Precancerous Conditions/metabolism* ; Capsules

Based on serum metabolomics and gut microbiota technology, this study explores the effects and mechanisms of the water extract of Ziziphi Spinosae Semen(SZRW) and the petroleum ether extract of Ziziphi Spinosae Semen(SZRO) in improving depressive-like behaviors induced by sleep deprivation. A modified multi-platform water environment method was employed to establish a rat model of sleep deprivation. Depressive-like behaviors in rats were assessed through the sucrose preference test and forced swim test. The expression of barrier proteins, such as Occludin, in the colon was determined by immunofluorescence. UPLC-Q-Orbitrap MS was utilized to analyze the serum metabolic profiles of sleep-deprived rats, screen for differential metabolites, and analyze metabolic pathways. The diversity of the gut microbiota was detected using 16S rRNA gene sequencing. Spearman correlation coefficient analysis was conducted to assess the correlation between differential metabolites and gut microbiota. The results indicated that SZRO significantly increased the sucrose preference index and decreased the immobility time in the forced swim test in rats. A total of 34 differential metabolites were identified through serum metabolomics. SZRW and SZRO shared five metabolic pathways, including phenylalanine metabolism. SZRW uniquely featured taurine and hypotaurine metabolism, while SZRO uniquely featured linoleic acid metabolism and tyrosine metabolism. Correlation analysis revealed that SZRW could upregulate the abundance of Bilophila, promoting the production of indole-3-propionic acid and subsequently upregulating the expression levels of intestinal tight junction proteins such as ZO-1, Occludin, and Claudin-1. SZRO could indirectly influence metabolic pathways such as arginine metabolism and linoleic acid metabolism by upregulating the abundance of gut microbiota such as Coprococcus and Eubacterium species. Both SZRW and SZRO can regulate endogenous metabolism, including amino acids, energy, and lipids, alter the gut microbiota microecology, and improve depressive-like behaviors. SZRO demonstrated superior effects in regulating metabolic pathways and gut microbiota structure compared to SZRW. The findings of this study provide a scientific basis for elucidating the pharmacodynamic material basis of Ziziphi Spinosae Semen.
Animals ; Rats ; Gastrointestinal Microbiome/drug effects* ; Male ; Metabolomics ; Drugs, Chinese Herbal/administration & dosage* ; Depression/blood* ; Rats, Sprague-Dawley ; Sleep Deprivation/complications* ; Ziziphus/chemistry* ; Antidepressive Agents/administration & dosage* ; Behavior, Animal/drug effects* ; Humans

Immune checkpoints include a series of receptor-ligand pairs that play a key role in the proliferation, activation, and immune regulatory responses of immune cells. Although immune checkpoint inhibitors (ICIs), such as programmed death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) have achieved good therapeutic effects in clinical practice, some patients still experience ineffective treatment and immune resistance. A large amount of evidence has shown that immune checkpoint proteins are related to cell metabolism during immune regulation. On the one hand, immune checkpoints connect to alter the metabolic reprogramming of tumor cells to compete for nutrients required by immune cells. On the other hand, immune checkpoints regulate the metabolic pathways of immune cells, such as phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) to affect the activation of immune cells. Based on a review of the literature, this article reviews the mechanisms by which PD-1, CTLA-4, T cell immunoreceptor with Ig and ITIM domains (TIGIT), T cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), cluster of differentiation 47 (CD47), and indoleamine 2,3-dioxygenase 1 (IDO1) regulate cell metabolic reprogramming, and looks forward to whether targeting the ligand-receptor pairs of immune checkpoints in a "dual regulation" manner and inhibiting metabolic pathways can effectively solve the problem of tumor immune resistance.
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Humans ; Neoplasms/genetics* ; Metabolic Networks and Pathways/immunology* ; Animals ; Immune Checkpoint Inhibitors/pharmacology*

Time-of-flight secondary ion mass spectrometer(TOF-SIMS)is a highly sensitive surface analysis instrument with high spatial resolution.Traditional TOF-SIMS instruments for sample targets use high field extraction methods.Although the ion collection efficiency is high,it is prone to issues such as low-energy ion beam defocusing,sample morphology sensitivity,and organic molecule ion dissociation.This study aimed to develope an efficient low-field ion extraction system suitable for TOF-SIMS with a continuous beam source.The SIMION simulation software was used to construct a model of the secondary ion optical extraction system.The key factors affecting the extraction efficiency were studied,and the structural parameters of the extraction cone were optimized.Using an indium target as the sample,an experimental test of the performance of the ion extraction system was carried out on the TOF-SIMS instrument.The influences of the voltages of the ion extraction cone and the single lens on the ion extraction efficiency were consistent with the simulation results.By adopting the technology of deflection and coaxial dynamic compensation,the imaging field of view of the ion extraction system was increased to 500 μm×500 μm.The energy window of the ion extraction system reached 10 eV,and the large imaging depth of field of 400 μm was achieved.In the test of a 5 mg/L cholesterol thin film sample,the signal-to-noise ratio of the characteristic peak[M-OH]+reached 4453.The results showed that this low-field secondary ion extraction system effectively improved the performance of the continuous beam TOF-SIMS instrument.

OBJECTIVE: To identify the risk factors for acute respiratory distress syndrome (ARDS) in geriatric patients following gastrointestinal perforation surgery, and constructed a model to validate its predictive value. METHODS: A retrospective analysis was conducted. The clinical data of geriatric patients (aged ≥ 60 years) after gastrointestinal perforation surgery admitted to the intensive care unit (ICU) of Hebei General Hospital from October 2017 to October 2024 were enrolled. Two groups were divided according to whether ARDS occurred postoperatively, and the differences in each index between the groups were compared. Lasso regression and multifactorial Logistic regression analyses were used to identify independent risk factors for the development of ARDS, and a prediction model was constructed based on these, which was presented using a nomogram. The receiver operator characteristic curve (ROC curve), calibration curve, and decision curve analysis (DCA) were plotted to evaluate the discrimination, accuracy, and clinical practicability of the model. RESULTS: A total of 155 geriatric patients following gastrointestinal perforation surgery were ultimately included in the analysis, among whom 43 developed ARDS, with an incidence rate of 27.7%. There were significantly differences in age, body mass index (BMI), acute kidney injury comorbidity, heart rate, onset time, the duration of surgery, the site of perforation, seroperitoneum, amount of bleeding, shock comorbidity, central venous pressure (CVP), C-reactive protein, and albumin between ARDS and non-ARDS groups. Lasso regression identified nine significant predictors: age, BMI, acute kidney injury comorbidity, onset time, seroperitoneum, shock comorbidity, CVP, hemoglobin, and albumin. Multivariate Logistic regression analysis identified BMI [odds ratio (OR) = 1.310, P < 0.001], hemoglobin (OR = 1.019, P = 0.045), seroperitoneum (OR = 1.001, P = 0.017), and albumin (OR = 0.871, P < 0.001) as independent risk factors for the occurrence of ARDS. A prediction model was constructed based on the above four independent risk factors, and the ROC curve showed that the area under the curve (AUC) of the model for predicting the occurrence of ARDS was 0.885 [95% confidence interval (95%CI) was 0.824-0.946], and internal validation was performed using bootstrap resampling (Bootstrap 500 times), which showed that the AUC value of the model was 0.886 (95%CI was 0.883-0.889). Calibration curves revealed excellent concordance between observed outcomes and model predictions. DCA indicated a high net benefit value for the model, which has good clinical utility. CONCLUSIONS BMI, hemoglobin, seroperitoneum, and albumin were identified as independent risk factors for ARDS in geriatric patients following gastrointestinal perforation surgery. The prediction model constructed using these four indicators facilitates early identification of high-risk individuals by clinicians.
Humans ; Respiratory Distress Syndrome/etiology* ; Retrospective Studies ; Aged ; Risk Factors ; Logistic Models ; Postoperative Complications ; Intestinal Perforation/surgery* ; Male ; ROC Curve ; Female ; Middle Aged ; Intensive Care Units ; Nomograms

Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology* ; Humans ; Wastewater/analysis* ; COVID-19/epidemiology* ; Public Health ; Wastewater-Based Epidemiological Monitoring ; SARS-CoV-2

Human Respiratory Stem Cells (RSCs) play a crucial role in the maintenance, repair and regeneration of the respiratory system. As a novel therapeutic method, stem cell therapy is a popular research direction in the medical field. And with the in-depth research on the mechanism of pneumonia caused by respiratory infections in recent years, the use of RSCs to explore pneumonia caused by respiratory infections and its therapeutic strategies has become a hot topic. In this paper, we firstly outlined the types of RSCs, summarized the mechanism of pneumonia caused by respiratory tract infections, discussed the advantages of RSCs application and the progress of culture differentiation, and elaborated the therapeutic exploration of RSCs in pneumonia caused by respiratory tract infections.

Objective:Analysis of the composition of pathogen spectrum and prevalence characteristics in throat swabs of patients with acute respiratory infections (ARI) in Yucheng city, Henan province, from March to June 2023.Methods:After 1 153 throat swabs were collected from ARI patients in Yucheng, 18 respiratory pathogens were tested using a real-time fluorescence quantitative polymerase chain reaction (qPCR) method. The characterization of pathogens spectrum was analyzed.Results:A total of 1 153 throat swabs from ARI patients were collected from March to June 2023 in Yucheng, including 171 outpatients and 982 hospitalized patients. A total of 244 positive samples for common respiratory pathogens were detected (at least one pathogen per sample was detected). The total detection rate of respiratory pathogens was 21.16%, and the top three detection rates were, in descending order, human bocavirus (HBoV), enterovirus (EV), and human parainfluenza virus (HPIV). The main detection month for pathogens was May, with a detection rate of 42.3% (60/142). The main respiratory pathogens detected are HBoV, EV, and HPIV. The detection rate of the age group under 1 year old was the highest, at 25.1% (49/195), mainly consisting of HBoV, respiratory syncytial virus (RSV), and HPIV. The main clinical manifestations of respiratory pathogen-positive patients were fever and cough, and the clinical diagnosis was mainly lower respiratory tract infection, all of which were hospitalized patients.Conclusions:The respiratory pathogens in ARI patients were mainly HBoV, EV, and HPIV from March to June, 2023 in Yucheng. The peak of the epidemic was in May, mainly infecting children under 5 years of age.

The patient is a 63-year-old man with a history of chronic illness, presenting with intermittent low-grade fever, recurrent dry cough, and shortness of breath upon exertion. Lung CT showed a nodule in the left lung and a large mass in the right lung with liquefactive necrosis and an air-fluid level accompanied by pleural effusion. Laboratory findings showed significantly increasedf immunoglobulin G (IgG), IgG4, and total immunoglobulin E, along with a mild increase in eosinophils, and moderate elevations in erythrocyte sedimentation rate and high-sensitivity C-reactive protein. Malignant tumors, immunological, and hematological diseases were ruled out. Various antibiotic treatments were ineffective and the condition was recurrent. Conventional methods failed to identify the pathogen. Metagenomic next-generation sequencing (mNGS) technology was used to detect Mycobacterium monacense from lung tissue. Targeted antibiotic treatment was effective with no further episodes of low-grade fever and alleviation of dry cough symptoms. This case underscores the clinical significance of mNGS technology for the diagnosis and treatment of unexplained pulmonary infections, providing a useful reference for clinical diagnostic and treatment.

With the rapid development of computer vision technology, deep learning models have demonstrated new research area and potential value in intelligent microbiological detection. By utilizing multilayer neural networks and large amounts of training data, these models are capable of automated extraction and analysis for complex features, thereby improving the efficiency and accuracy of detection. This paper introduces the research background of deep learning in microbiological image detection, and elaborates on the methods for constructing microbiological image datasets, including data collection, preprocessing, annotation, and partitioning, and introduces typical deep learning models as well as their application examples in various microbiological detection. Deep learning in microbiological image analysis faces numerous challenges which needs further development.