Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results. Building on their image-recognition abilities, multimodal LLMs (MLLMs) show promising potential for diagnosis based on radiography, chest computed tomography (CT), electrocardiography (ECG), and common pathological images. These models can also assist in treatment planning by suggesting evidence-based interventions and improving clinical decision support systems through integrated analysis of patient records. Despite these promising developments, significant challenges persist regarding the use of LLMs in medicine, including concerns regarding algorithmic bias, the potential for hallucinations, and the need for rigorous clinical validation. Ethical considerations also underscore the importance of maintaining the function of supervision in clinical practice. This paper highlights the rapid advancements in research on the diagnostic and therapeutic applications of LLMs across different medical disciplines and emphasizes the importance of policymaking, ethical supervision, and multidisciplinary collaboration in promoting more effective and safer clinical applications of LLMs. Future directions include the integration of proprietary clinical knowledge, the investigation of open-source and customized models, and the evaluation of real-time effects in clinical diagnosis and treatment practices.
Humans ; Large Language Models ; Tomography, X-Ray Computed

The success of chimeric antigen receptor T (CAR-T) cells therapy for hematologic malignancies has sparked interest in potential applications for solid tumors. However, unlike the homogeneous, dynamic, and nutrient-rich hematologic environment, CAR-T cells must overcome the complex tumor microenvironment. Ensuring efficient contact with tumor cells remains a primary challenge to enhance the efficacy of CAR-T cell therapy. Abnormal tumor angiogenesis, disordered chemokine production, dense extracellular matrix, and stromal cells all act as biological barriers that hinder contact of CAR-T cells with tumor cells. This review summarizes specific strategies to promote vascular normalization, modulate chemokine production, target physical barriers, combine different therapeutic approaches, and innovative cell delivery methods to enhance infiltration of CAR-T cells into solid tumors. These strategies will help to overcome current limitations and enhance the effectiveness of CAR-T cell therapy for solid tumors.

Radiochemotherapy-induced oral mucositis (OM) is a common oral complication in patients with tumors following head and neck radiotherapy or chemotherapy. Erosion and ulcers are the main features of OM that seriously affect the quality of life of patients and even the progress of tumor treatment. To date, differences in clinical prevention and treatment plans for OM have been noted among doctors of various specialties, which has increased the uncertainty of treatment effects. On the basis of current research evidence, this expert consensus outlines risk factors, clinical manifestations, clinical grading, ancillary examinations, diagnostic basis, prevention and treatment strategies and efficacy indicators for OM. In addition to strategies such as basic oral care, anti-inflammatory and analgesic agents, anti-infective agents, pro-healing agents, and photobiotherapy recommended in previous guidelines, we also emphasize the role of traditional Chinese medicine in OM prevention and treatment. This expert consensus aims to provide references and guidance for dental physicians and oncologists in formulating strategies for OM prevention, diagnosis, and treatment, standardizing clinical practice, reducing OM occurrence, promoting healing, and improving the quality of life of patients.
Humans ; Chemoradiotherapy/adverse effects* ; Consensus ; Risk Factors ; Stomatitis/etiology*

Humans ; Gastrointestinal Microbiome ; Constipation/therapy* ; Probiotics/therapeutic use* ; Patients

The incidence of early-onset gastric cancer (EOGC) is consistently increasing, and its etiology is notably complex. This increase may be attributed to distinctive factors that differ from those associated with late-onset gastric cancer (LOGC), including genetic predispositions, dietary factors, gastric microbiota dysbiosis, and screening of high-risk cases. These factors collectively contribute to the onset of cancer. EOGC significantly differs from LOGC in terms of clinicopathological and molecular characteristics. Moreover, multiple differences in prognosis and clinical management also exist. This study aimed to systematically review the latest research advancements in the epidemiological characteristics, etiological factors, clinicopathological and molecular features, prognosis, and treatment modalities of EOGC.

Objective:To compare the knowledge of endoscopic screening of gastrointestinal cancers between digestive healthcare workers and new chatbots (chatGPT and new Bing).Methods:A test with twenty-three questions of endoscopic screening of gastrointestinal cancers was conducted, focusing on the appropriate age of screening, high-risk factors, the follow-up time, and the advantages and risks of digestive endoscopy. Digestive healthcare workers were invited to complete the test through electronic questionnaires. New Bing and chatGPT were used to answer each question for 10 rounds. The primary endpoint was the correct rate of all answers. The answer accuracy between digestive healthcare workers and new chatbots were compared using variance analysis, and the factors that affected the accuracy of the answers in digestive healthcare workers were explored using univariate and multivariable liner regression analysis.Results:The results of the test completed by 76 digestive healthcare workers (21 residents, 28 digestive nurses, and 27 digestive doctors) were analyzed. The accuracies were 36.4%±10.9%, 34.5%±10.2%, 52.2%± 12.6%, 46.3%±9.8% and 67.1%±9.3% in residents, digestive nurses, digestive doctors, chatGPT, and new Bing, respectively, with significant difference ( F=22.6, P<0.001). The accuracy was highest in new Bing ( P<0.001). The accuracy was comparable between chatGPT and digestive doctors (LSD- t=-1.398, P=0.166), and both higher than that of digestive nurses (LSD- t=2.956, P=0.004; LSD- t=5.955, P<0.001) and residents (LSD- t=2.402, P=0.018; LSD- t=4.951, P<0.001). Furthermore, the accuracy was comparable between digestive nurses and residents (LSD- t=-0.574, P=0.567). Compared with new Bing, digestive doctors had lower accuracy in answering questions related to adverse events of screening, follow-up recommendation of intestinal metaplasia, high risk factors and screening methods for colon cancer ( P<0.05), but higher accuracy in answering questions related to endoscopic adverse events and screening methods for esophageal cancer ( P<0.05). Multivariable liner regression analysis showed that being digestive doctors ( β=11.7, t=3.054, P=0.003) and questionnaire response time (≥7.6 min) ( β=7.8, t=2.894, P=0.005) were independent factors for the answer accuracy of digestive healthcare workers. Conclusion:Compared with digestive healthcare workers, New chatbots—new Bing has higher accuracy in answering gastrointestinal cancer screening-related questions, but performs poorly in answering questions such as adverse events of endoscopy and screening methods for esophageal cancer.

Objective To investigate the effect of knockdown of O-GlcNAc transferase (OGT) on hepatocyte fat synthesis.Methods Liver cell line L02 were used to established the model of hepatic steatosis.The levels of OGT and O-GlcNAc protein were detected by Western blot.The OGT knockdown cell line of L02 cells was established,and its lipid formation ability was detected after induction of oleic acid (OA).Real-time quantitative PCR (qRT-PCR) and Western blot were used to detect mRNA and protein expression of enzymes related to fat synthesis.An independent sample t test was used.Results Western blot showed that the expression of OGT and O-GlcNAc was increased in L02 cells after adipogenesis (P ＜ 0.05).After shOGT lentivirus infects L02 cells,OGT mRNA levels were down-regulated (P ＜ 0.01).Oil red O staining showed that the lipid in L02 shOGT cells decreased,qRT-PCR showed that the mRNA expressions of fat synthase (ACC1),(FASN) and (SCDl) were decreased,the difference was statistically significant (P ＜ 0.05),protein Expression is consistent with mRNA expression.Conclusion Knockdown of OGT can inhibit hepatocyte fat synthesis by reducing O-GlcNAc levels.

In recent years,cancer immunotherapy has attracted considerable attention in the field of biotherapy for the development of chimeric antigen receptor T (CAR-T) cell.CAR-T cells are capable of recognizing tumor cell surface antigens leading to kill tumor cells.Anti-CD19 CAR-T has achieved remarkable success in the treatment of hematopoietic malignancies.Whether it can benefit solid tumor patients to the same extent still faces great challenges,and it has been a focus of attention in immunotherapy for tumors.Compared with hematological malignancies,the microenvironment of solid tumor is more complex,and the screening of tumor specific antigen is more difficult.The infiltration of CAR-T cells from the blood system to the tumor site needs to overcome the tumor stromal barrier.Although part of CAR-T cells can infiltrate into tumor site,its function may be quickly inhibited by multiple factors in microenvironment.In this paper,authors discussed the challenges that CAR-T is facing for solid tumor treatment,including the specificity of the tumor antigen,the heterogeneity of the solid tumor antigen and the inhibitory effect of the tumor microenvironment,and proposed potential strategies to possibly overcome these hurdles.Authors believe that with the development of biotechnology,it will provide more abundant technical means to optimize the structure and function of CAR-T,and CAR-T will make breakthrough progress in the treatment of solid tumor.

Animals ; Gastrointestinal Microbiome ; Gastrointestinal Tract ; microbiology ; Humans ; Obesity ; microbiology ; pathology ; therapy

Objective To establish a stable and reliable mouse model as an alternative to the traditional model of impaired glucose tolerance induced by calorie restriction and its effect on glucose homeostasis.Methods Forty 16-week-old SPF C57BL/6J mice (half male and half female) were randomly divided into four groups by sex and the way of feeding.The mice in the ad libitum (AL) group had free access to basic diet, while the mice in the intermittent fasting (IF) group had normal diet and fasting on alternate days, with free access to water on the fasting days.The changes of body weight and blood glucose concentration in each group were monitored, and intraperitoneal glucose tolerance test and insulin tolerance test in mice were performed before and after the 12-week IF treatment.Results At 12 weeks after IF treatment, the body weight and blood glucose concentration of mice did not show significant difference.After i.p.injection of glucose, the blood glucose concentration of IF mice was less increased than the AL group, and after the insulin injection, the blood glucose concentration was more decreased.Compared to the AL group, the areas under the curve of tolerance test in the IF group were significantly decreased (P < 0.05).Conclusions After IF treatment, the mice show an enhanced sensitivity to insulin and improved glucose tolerance.This establishment method of mouse model of intermittent fasting is easy and simple, therefore, can be used as an effective alternative to traditional calorie restriction model of impaired glucose tolerance.