BACKGROUND:Currently,miR-196b-5p has been found to play a role in cell proliferation,migration and inhibition of scar hyperplasia,but there is a lack of relevant studies on whether it plays a role in the process of wound healing.OBJECTIVE:To investigate the effect of miR-196b-5p in adipose stem cell-derived exosomes on burn wound healing.METHODS:The models of deep second degree skin burn in SD rats were established and randomly divided into four groups:blank control group,exosome group,agomiR-196b-5p group,and exosome+antagomiR-196b-5p group,with 10 rats in each group.PBS,adipose-derived stem cell-derived exosomes,miR-196b-5p agonist,and miR-196b-5p inhibitor were injected around the wound according to different groups.Wound healing was observed immediately after injury and on days 7,14,and 21 after injury.On day 7 after surgery,hematoxylin-eosin staining was used to observe the expression of inflammation in the wound surface.On day 14 after suregery,Masson staining was used to observe the expression of collagen and immunohistochemical staining was used to observe the expression of CD31 in the wound surface.On day 7 after surgery,western blot assay was performed to detect the expression of α-smooth muscle actin and type Ⅰ collagen in the wound surface.RESULTS AND CONCLUSION:(1)The wound healing was faster in the agomiR-196b-5p group,while it was slower in the blank control group and the exosome+antagomiR-196b-5p group.(2)Compared with the blank control group and the exosome+antagomiR-196b-5p group,the wound infiltration of inflammatory cells was less in the exosome group and the agomiR-196b-5p group,and the expression of CD31 was significantly increased(P＜0.01).(3)Compared with the blank control group and the exosome+antagomiR-196b-5p group,the expression levels of α-smooth muscle actin and type Ⅰ collagen were increased in the exosome group and the agomiR-196b-5p group(P＜0.05).These findings indicate that miR-196b-5p in adipose stem cell-derived exosomes can promote burn wound healing in rats.

BACKGROUND:Currently,miR-196b-5p has been found to play a role in cell proliferation,migration and inhibition of scar hyperplasia,but there is a lack of relevant studies on whether it plays a role in the process of wound healing.OBJECTIVE:To investigate the effect of miR-196b-5p in adipose stem cell-derived exosomes on burn wound healing.METHODS:The models of deep second degree skin burn in SD rats were established and randomly divided into four groups:blank control group,exosome group,agomiR-196b-5p group,and exosome+antagomiR-196b-5p group,with 10 rats in each group.PBS,adipose-derived stem cell-derived exosomes,miR-196b-5p agonist,and miR-196b-5p inhibitor were injected around the wound according to different groups.Wound healing was observed immediately after injury and on days 7,14,and 21 after injury.On day 7 after surgery,hematoxylin-eosin staining was used to observe the expression of inflammation in the wound surface.On day 14 after suregery,Masson staining was used to observe the expression of collagen and immunohistochemical staining was used to observe the expression of CD31 in the wound surface.On day 7 after surgery,western blot assay was performed to detect the expression of α-smooth muscle actin and type Ⅰ collagen in the wound surface.RESULTS AND CONCLUSION:(1)The wound healing was faster in the agomiR-196b-5p group,while it was slower in the blank control group and the exosome+antagomiR-196b-5p group.(2)Compared with the blank control group and the exosome+antagomiR-196b-5p group,the wound infiltration of inflammatory cells was less in the exosome group and the agomiR-196b-5p group,and the expression of CD31 was significantly increased(P＜0.01).(3)Compared with the blank control group and the exosome+antagomiR-196b-5p group,the expression levels of α-smooth muscle actin and type Ⅰ collagen were increased in the exosome group and the agomiR-196b-5p group(P＜0.05).These findings indicate that miR-196b-5p in adipose stem cell-derived exosomes can promote burn wound healing in rats.

Gastric cancer(GC) ranks among the most prevalent cancers and is a leading cause of cancer-related mortality globally. Recently, artificial intelligence(AI) has enhanced the dia-gnosis and treatment of GC, as well as the accuracy and sensitivity of personalized treatment strategies due to its efficient computational and learning capabilities. The authors review the clinical applications of AI-based medical imaging and digital pathology in GC diagnosis and treatment, inclu-ding early screening and diagnosis, differential diagnosis, lymph node and peritoneal metastasis, molecular typing, monitoring of treatment efficacy, and prognostic assessment. In addition, future directions and challenges in the field are discussed, emphasizing the importance of integrating AI technology into clinical practice.

Gastric cancer(GC) ranks among the most prevalent cancers and is a leading cause of cancer-related mortality globally. Recently, artificial intelligence(AI) has enhanced the dia-gnosis and treatment of GC, as well as the accuracy and sensitivity of personalized treatment strategies due to its efficient computational and learning capabilities. The authors review the clinical applications of AI-based medical imaging and digital pathology in GC diagnosis and treatment, inclu-ding early screening and diagnosis, differential diagnosis, lymph node and peritoneal metastasis, molecular typing, monitoring of treatment efficacy, and prognostic assessment. In addition, future directions and challenges in the field are discussed, emphasizing the importance of integrating AI technology into clinical practice.

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.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Objective To investigate the effect of adipose-derived stem cell exosome(ADSC-Exo)on the proliferation and migration of fibroblasts as well as on wound healing of deep second degree burns in rats.Methods Fibroblasts were cultured with ADSC-Exo or in phosphate-buffered saline(PBS).The effect of ADSC-Exo on the proliferation and migration of fibroblasts was observed using the CCK-8 assay and scratch test.Forty Sprague-Dawley(SD)rats were selected to construct a deep second-degree burn model and divided into the exosome and control groups.The exosome group was injected with the ADSC-Exo solution around the wound,and the control group was injected with an equal amount of PBS solution.Wound healing was observed in both groups.Inflammatory infiltration was observed using hematoxylin and eosin(HE)staining,and wound angiogenesis was observed using CD31 immunohistochemical staining.Results The CCK-8 assay revealed that ADSC-Exo promoted fibroblast proliferation in a concentration-dependent manner.The results of the scratch test showed that ADSC-Exo significantly enhanced the migratory ability of fibroblasts(P＜0.000 1).The wound healing results showed that ADSC-Exo injection promoted burn wound healing in rats(P＜0.000 1).Pathological analysis indicated that inflammatory cell infil-tration was less and CD31 expression was higher in the ADSC-Exo group than in the control group(P＜0.01).Conclusion ADSC-Exo promoted the proliferation and migration of fibroblasts,reduced wound inflammation,promoted neovascularization,and enhanced wound healing.

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

OBJECTIVE: Pneumoconiosis, a lung disease caused by irreversible fibrosis, represents a significant public health burden. This study investigates the causal relationships between gut microbiota, gene methylation, gene expression, protein levels, and pneumoconiosis using a multi-omics approach and Mendelian randomization (MR). METHODS: We analyzed gut microbiota data from MiBioGen and Esteban et al. to assess their potential causal effects on pneumoconiosis subtypes (asbestosis, silicosis, and inorganic pneumoconiosis) using conventional and summary-data-based MR (SMR). Gene methylation and expression data from Genotype-Tissue Expression and eQTLGen, along with protein level data from deCODE and UK Biobank Pharma Proteomics Project, were examined in relation to pneumoconiosis data from FinnGen. To validate our findings, we assessed self-measured gut flora from a pneumoconiosis cohort and performed fine mapping, drug prediction, molecular docking, and Phenome-Wide Association Studies to explore relevant phenotypes of key genes. RESULTS: Three core gut microorganisms were identified: Romboutsia ( OR = 0.249) as a protective factor against silicosis, Pasteurellaceae ( OR = 3.207) and Haemophilus parainfluenzae ( OR = 2.343) as risk factors for inorganic pneumoconiosis. Additionally, mapping and quantitative trait loci analyses revealed that the genes VIM, STX8, and MIF were significantly associated with pneumoconiosis risk. CONCLUSIONS This multi-omics study highlights the associations between gut microbiota and key genes ( VIM, STX8, MIF) with pneumoconiosis, offering insights into potential therapeutic targets and personalized treatment strategies.
Humans ; Male ; East Asian People/genetics* ; Europe ; Gastrointestinal Microbiome ; Lung ; Macrophage Migration-Inhibitory Factors/metabolism* ; Mendelian Randomization Analysis ; Multiomics ; Pneumoconiosis/microbiology* ; Intramolecular Oxidoreductases