Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

Oral solid dosage forms require processes such as disintegration and dissolution to release the drug before it can be absorbed and utilized by the body. In this manuscript, imaging technology was used to continuously visualize and characterize the in vitro static drug release process of gliclazide modified release tablets from 15 manufacturers, combined with the traditional method of in vitro dissolution testing, to determine the release profile of gliclazide modified release tablets, to evaluate the similarity of the release profiles by using the similarity factor (f₂) method and based on the analysis of the release profiles fitted with a variety of mathematical models. The results indicate that the gliclazide modified release tablets produced by 14 companies are hydrophilic gel matrix tablets. Compared to the reference listed drug, the release profiles of formulations from 11 companies show high similarity (f₂ > 50) to the reference. Among these, formulations with visual characteristics similar to the reference exhibit similar release curves. This study provides an alternative method for the in vitro consistency evaluation of gliclazide modified release tablets, aiming to assess the in vitro release behaviour of generic formulations more accurately and comprehensively.

ObjectiveNeuroinflammation plays a crucial role in both the onset and progression of ischemic stroke, exerting a significant impact on the recovery of the central nervous system. Excessive neuroinflammation can lead to secondary neuronal damage, further exacerbating brain injury and impairing functional recovery. As a result, effectively modulating and reducing neuroinflammation in the brain has become a key therapeutic strategy for improving outcomes in ischemic stroke patients. Among various approaches, targeting immune regulation to control inflammation has gained increasing attention. This study aims to investigate the role of in vitro induced regulatory T cells (Treg cells) in suppressing neuroinflammation after ischemic stroke, as well as their potential therapeutic effects. By exploring the mechanisms through which Tregs exert their immunomodulatory functions, this research is expected to provide new insights into stroke treatment strategies. MethodsNaive CD4⁺ T cells were isolated from mouse spleens using a negative selection method to ensure high purity, and then they were induced in vitro to differentiate into Treg cells by adding specific cytokines. The anti-inflammatory effects and therapeutic potential of Treg cells transplantation in a mouse model of ischemic stroke was evaluated. In the middle cerebral artery occlusion (MCAO) model, after Treg cells transplantation, their ability to successfully migrate to the infarcted brain region and their impact on neuroinflammation levels were examined. To further investigate the role of Treg cells in stroke recovery, the changes in cytokine expression and their effects on immune cell interactions was analyzed. Additionally, infarct size and behavioral scores were measured to assess the neuroprotective effects of Treg cells. By integrating multiple indicators, the comprehensive evaluation of potential benefits of Treg cells in the treatment of ischemic stroke was performed. ResultsTreg cells significantly regulated the expression levels of both pro-inflammatory and anti-inflammatory cytokines in vitro and in vivo, effectively balancing the immune response and suppressing excessive inflammation. Additionally, Treg cells inhibited the activation and activity of inflammatory cells, thereby reducing neuroinflammation. In the MCAO mouse model, Treg cells were observed to accumulate in the infarcted brain region, where they significantly reduced the infarct size, demonstrating their neuroprotective effects. Furthermore, Treg cell therapy notably improved behavioral scores, suggesting its role in promoting functional recovery, and increased the survival rate of ischemic stroke mice, highlighting its potential as a promising therapeutic strategy for stroke treatment. ConclusionIn vitro induced Treg cells can effectively suppress neuroinflammation caused by ischemic stroke, demonstrating promising clinical application potential. By regulating the balance between pro-inflammatory and anti-inflammatory cytokines, Treg cells can inhibit immune responses in the nervous system, thereby reducing neuronal damage. Additionally, they can modulate the immune microenvironment, suppress the activation of inflammatory cells, and promote tissue repair. The therapeutic effects of Treg cells also include enhancing post-stroke recovery, improving behavioral outcomes, and increasing the survival rate of ischemic stroke mice. With their ability to suppress neuroinflammation, Treg cell therapy provides a novel and effective strategy for the treatment of ischemic stroke, offering broad application prospects in clinical immunotherapy and regenerative medicine.

Objective To explore the feasibility of automatic segmentation of clinical target volume(CTV)and organs at risk(OARs)for cervical cancer using AccuLearning(AL)based on geometric and dosimetric indices.Methods Seventy-five CT localization images with manual contouring data of postoperative cervical cancer were enrolled in this study.Sixty cases were randomly selected to trained to generate automatic segmentation model by AL,and the CTV and OARs of the remaining 15 cases were automatically contoured.Radiotherapy plans on the automatic segmentation contours were imported on the CT images of manual contours.The efficiency,Dice similarity coefficient(DSC),Hausdorff distance(HD)and dosimetric parameters were compared between the two methods.Results The time of automatic segmentation was significantly shorter than that of the manual contour(P<0.05).The DSC of all structures were≥0.87.The HD of bowel bag and rectum were about 10 mm,and that of the rest of OARs were less than 5 mm.CTV(D98,V90% ,V95% ,Dmean,HI),bowel bag(V50)and bladder(V50)had significant differences in dosimetric comparison(P<0.05).Conclusion The automatic segmentation model based on AL can improve the efficiency of radiotherapy.Automatic segmentation of OARs has the potential of clinical application,while that of CTV still needs to be further modified.

Objective To explore the correlation between intestinal dose and acute radiation enteritis(ARE)in patients with cervical cancer received concurrent chemoradiotherapy,and optimize the dose limit of intestinal tissue.Methods 158 cervical cancer patients received concurrent chemoradiotherapy from 2014 to 2019 were selected in this study.According to CTCAE 5.0,patients with ARE≥grade 2 were classified as ARE≥grade 2 group,otherwise classified as ARE0.7,P<0.05).Conclusions For patients with cervical cancer received concurrent chemoradiotherapy,the dose of bowelbag V5 and V40 should be considered to rationally optimize the dose of bowelbag in the radiotherapy plan,so as to reduce the incidence of ARE≥grade 2.

Cancer is a leading cause of mortality in children and results in a significant disease burden. Lipid metabolic reprogramming emerges as a pivotal cancer hallmark, bearing profound implications for understanding tumorigenesis, developing treatment strategies, and improving prognoses. However, research on lipid metabolism and lipid nutritional interventions related to childhood cancers is notably limited compared to adult cancers. This review focused on the current understanding of fatty acid, cholesterol, and phospholipid metabolism in childhood cancers and discussed the correlation between major lipid dietary patterns (such as high-fat, ketogenic, and Mediterranean diets) and the development and progression of childhood cancers. This review also highlighted existing research gaps on the mechanisms of lipid metabolism and the effects of major lipid dietary patterns, and warranted improved research depth, experimental design, and sample size. Therefore, we advocate for future epidemiological, basic science, and multidisciplinary research in the field of childhood cancers to understand more comprehensively and profoundly the role of lipid nutrition in the prevention and treatment of pediatric cancers.

In recent years, with the development of organ preservation, surgical techniques, perioperative management and immunosuppression regimens, the success rate of liver transplantation and survival rate of the recipients have been significantly enhanced. Liver transplantation has become the optimal treatment for patients with end-stage liver disease. However, biliary complications still commonly occur after liver transplantation, especially biliary anastomotic stricture. Severe biliary anastomotic stricture will not only increase the cost of treatment, but also lead to graft loss and even affect the survival rate of recipients. Therefore, timely diagnosis and treatment of biliary anastomotic stricture play a significant role in improving the survival rate of liver transplant recipients. In this article, the risk factors, clinical symptoms, diagnosis and treatment of biliary anastomotic stricture after liver transplantation were reviewed, aiming to provide novel ideas for the research, diagnosis and treatment of biliary anastomotic stricture after liver transplantation, and further enhance clinical efficacy of liver transplantation and the quality of life of recipients.

Objective:To investigate the predictive value of preoperative D-dimer level for futile recanalization (FR) after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS).Methods:It was a nested case-control study. A total of 116 patients with large vessel occlusion (LVO) stroke, who underwent successful recanalization (modified Thrombolysis in Cerebral Infarction, mTICI≥2b) after MT at the Stroke Unit of Beijing Hospital from August 2018 to January 2022,were consecutively enrolled, including 72 males (62.1%) with the age of (72.8±13.1) years. According to the 3-month modified Rankin Scale (mRS) score after MT, patients were divided into the meaningful recanalization group (mRS 0-2, n=41) and the futile recanalization group (mRS 3-6, n=75). The baseline clinical data of enrolled patients was collected. Logistic regression analysis was used to identify the independent risk factors for FR after MT in patients with AIS. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of D-dimer for FR. Results:Multivariate logistic regression analysis showed that high baseline systolic blood pressure (SBP) ( OR=1.038, 95% CI: 1.012-1.065, P=0.004), baseline National Institutes of Health Stroke Scale (NIHSS) score≥12 ( OR=10.157, 95% CI: 3.624-28.470, P<0.001) and high preoperative D-dimer level ( OR=4.536, 95% CI: 1.379-14.922, P=0.013) were independent predictors of FR after MT in AIS patients with LVO. ROC curve analysis indicated a good predictive value of preoperative D-dimer for the occurrence of FR ( AUC=0.733, 95% CI: 0.638-0.829, P<0.05), the optimal cut-off value of D-dimer was 2.65 μg/L(Lg), with the Youden index, sensitivity, specificity and accuracy of 0.435, 53.3%, 90.2% and 66.4%, respectively. Conclusion:High preoperative D-dimer level is an independent predictor of futile recanalization after MT in AIS patients with LVO, which shows good predictive ability for futile recanalization.

Objective Using literature metrology,scientific literature in the field of depression models in animals was analyzed to better understand the development trends and hot topics in this field.Methods We obtained publications on depression and animal models from 2013 to 2022 from the Web of Science core set database.CiteSpace 6.1 R1(64-bit)Basic was used to analyze annual publications,countries,institutions,authors,and keywords related to this field.Results A total of 1000 articles were included in this study.From 2013 to 2022,the number of articles published increased gradually and then stabilized.In terms of the number of articles,the United States had the most published articles(256).Wegener Gregers was the most influential author in the field with 23 published articles.Conclusions The field focuses on signaling pathways and therapeutic approaches to determine the pathogenesis of depression and better treatments.This study provides a visual analysis of trends in depression research to help researchers keep up with the latest developments.

The human oral microbiome harbors one of the most diverse microbial communities in the human body, playing critical roles in oral and systemic health. Recent technological innovations are propelling the characterization and manipulation of oral microbiota. High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes. New long-read platforms improve genome assembly from complex samples. Single-cell genomics provides insights into uncultured taxa. Advanced imaging modalities including fluorescence, mass spectrometry, and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution. Fluorescence techniques link phylogenetic identity with localization. Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification. Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches. Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly, gene expression, metabolites, microenvironments, virulence mechanisms, and microbe-host interfaces in the context of health and disease. However, significant knowledge gaps persist regarding community origins, developmental trajectories, homeostasis versus dysbiosis triggers, functional biomarkers, and strategies to deliberately reshape the oral microbiome for therapeutic benefit. The convergence of sequencing, imaging, cultureomics, synthetic systems, and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict, prevent, diagnose, and treat associated oral diseases.
Humans ; Phylogeny ; Biomimetics ; Dysbiosis ; Homeostasis ; Mass Spectrometry