OBJECTIVE: Cigarette smoking exacerbates the progression of pulmonary tuberculosis (TB). The role of tertiary lymphoid structures (TLS) in chronic lung diseases has gained attention; however, it remains unclear whether smoking-exacerbated lung damage in TB is associated with TLS. This study aimed to analyze the characteristics of pulmonary TLS in smokers with TB and to explore the possible role of TLS in smoking-related lung injury in TB. METHODS: Lung tissues from 36 male patients (18 smokers and 18 non-smokers) who underwent surgical resection for pulmonary TB were included in this study. Pathological and immunohistological analyses were conducted to evaluate the quantity of TLS, and chest computed tomography (CT) was used to assess the severity of lung lesions. The correlation between the TLS quantity and TB lesion severity scores was analyzed. The immune cells and chemokines involved in TLS formation were also evaluated and compared between smokers and non-smokers. RESULTS: Smoker patients with TB had significantly higher TLS than non-smokers ( P < 0.001). The TLS quantity in both the lung parenchyma and peribronchial regions correlated with TB lesion severity on chest CT (parenchyma: r = 0.5767; peribronchial: r = 0.7373; both P < 0.001). Immunohistochemical analysis showed increased B cells, T cells, and C-X-C motif chemokine ligand 13 (CXCL13) expression in smoker patients with TB ( P < 0.001). CONCLUSION Smoker TB patients exhibited increased pulmonary TLS, which was associated with exacerbated lung lesions on chest CT, suggesting that cigarette smoking may exacerbate lung damage by promoting TLS formation.
Humans ; Male ; Tuberculosis, Pulmonary/immunology* ; Middle Aged ; Tertiary Lymphoid Structures/pathology* ; Adult ; Lung/pathology* ; Smoking/adverse effects* ; Smokers ; Aged ; Tomography, X-Ray Computed

Ulcerative colitis(UC) is a recurrent, chronic, nonspecific inflammatory bowel disease. The longer the course of the disease, the higher the risk of cancerization. In recent years, the incidence and mortality rates of colon cancer in China have been increasing year by year, seriously threatening the life and health of patients. Therefore, studying the mechanism of "inflammation cancer transformation" in UC and conducting early intervention is crucial. The "Kenang" theory is an important component of traditional Chinese medicine(TCM) theory of phlegm and blood stasis. It is based on the coexistence of phlegm and blood stasis in the body and deeply explores the pathogenic syndromes and characteristics of phlegm and blood stasis. Kenang is a pathological product formed when long-term Qi stagnation leads to the internal formation of phlegm and blood stasis, which is hidden deep within the body. It is characterized by being hidden, progressive, and difficult to treat. The etiology and pathogenesis of "inflammation cancer transformation" in UC are consistent with the connotation of the "Kenang" theory. The internal condition for the development of UC "inflammation cancer transformation" is the deficiency of healthy Qi, with Qi stagnation being the key pathological mechanism. Phlegm and blood stasis are the main pathogenic factors. Phlegm and blood stasis accumulate in the body over time and can produce cancer toxins. Due to the depletion of healthy Qi and a weakened constitution, the body is unable to limit the proliferation and invasion of cancer toxins, eventually leading to cancer transformation in UC. In clinical treatment, the focus should be on removing phlegm and blood stasis, with syndrome differentiation and treatment based on three basic principles: supporting healthy Qi to strengthen the body's foundation, resolving phlegm and blood stasis to break up the Kenang, and regulating Qi and blood to smooth the flow of energy and resolve stagnation. This approach helps to dismantle the Kenang, delay, block, or even reverse the cancerization process of UC, reduce the risk of "inflammation cancer transformation", improve the patient's quality of life, and provide new perspectives and strategies for early intervention in the development of colon cancer.
Humans ; Colitis, Ulcerative/immunology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/therapeutic use* ; Cell Transformation, Neoplastic

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*

Neoadjuvant therapy has become the standard treatment for locally advanced resectable esophageal cancer, significantly improving long-term survival compared to surgery alone. Neoadjuvant therapy has evolved to include various strategies, such as concurrent chemoradiotherapy, chemotherapy, immunotherapy, or targeted combination therapy. This enriches clinical treatment options and provides a more personalized and scientific treatment approach for patients. This article aims to comprehensively summarize current academic research hot topics, review the rationale and evaluation measures of neoadjuvant therapy, discuss challenges in restaging methods after neoadjuvant therapy, and identify the advantages and disadvantages of various neoadjuvant therapeutic strategies.

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

Objective To investigate the epidemiological characteristics of knee osteoarthritis(KOA)among military personnel in plateau regions and to explore its risk factors.Methods From July 2023 to July 2024,a multi-stage stratified cluster random sampling method was employed to survey the prevalence of KOA and related risk factors among military personnel in the northwest plateau regions of China,covering different altitudes(1500-4500 m)and geographical areas(Gansu,Qinghai,Tibet,and Xinjiang).All study subjects were divided into KOA and non-KOA groups based on the presence or absence of KOA.Variables including age,gender,body mass index(BMI),education level,smoking status,military rank,military branch,service duration,regional altitude,annual average temperature,training duration,perceived training intensity,and history of knee injury were selected for univariate analyses between groups.Variables with P<0.05 in the univariate analyses were included in the binary multifactor logistic regression to identify risk factors for KOA.Results A total of 3000 questionnaires were distributed,and 2854 valid questionnaires were collected,with a response rate of 95.13%.The sample included 2584 males and 270 females,with 510 cases of KOA,resulting in a prevalence rate of 17.9%.Univariate analysis showed that there were statistically significant differences between KOA and non-KOA groups in terms of age,BMI,smoking status,military rank,military branch,service duration,regional altitude,annual average temperature,training duration,perceived training intensity,and history of knee injury(P<0.05).However,no significant differences were found in gender and education level(P>0.05).Binary multivariate logistic regression analysis revealed that older age(OR=1.382,P=0.017),higher BMI(P<0.01),smoking(OR=1.929,P<0.01),higher military rank(OR=1.485,P=0.007),being a member of the Armed Police(P<0.01),longer service duration(P<0.01),higher regional altitude(OR=1.459,P<0.01),lower annual average temperature(OR=1.188,P=0.001),longer training duration(P<0.01),higher perceived training intensity(OR=2.450,P<0.01),and history of knee injury(OR=2.768,P=0.002)were independent risk factors for KOA.Conclusions Older age,overweight/obesity,smoking,higher military rank,being a member of the Armed Police,longer service duration,higher altitude,cold climate,longer training duration,higher training intensity,and history of knee injury are independent risk factors for KOA among military personnel in the northwest plateau regions of China.