ObjectiveTo provide evidence for strengthening tuberculosis control in Inner Mongolia by analyzing changes and influencing factors in public awareness of tuberculosis prevention and control information among residents between the early stage and 17 years after the implementation of the directly observed treatment， short-course （DOTS） strategy. MethodsBased on the "National Public Knowledge， Belief and Behavior Questionnaire on Tuberculosis Prevention and Control" designed by the Chinese Center for Disease Control and Prevention， a questionnaire survey was conducted among residents in Inner Mongolia using a multi-stage stratified random sampling method. Chi-square test was used for univariate analysis， and binary Logistic regression was employed to explore the influencing factors of public awareness of tuberculosis prevention and control information. ResultsThe overall awareness rate of core information on tuberculosis prevention and control among the public was 67.7% in 2006， and it decreased to 49.2% in 2023 （P<0.05）. Multivariate Logistic regression analysis showed， compared with the groups aged 15-29， illiterate and semi-illiterate， those with public medical care， and those with three or fewer family members， the awareness rate of the groups aged 60 and above （OR=0.689）， those with primary and junior high school education （OR=0.856）， and those with self-paid medical care （OR=0.468） was significantly lower in 2006. The awareness rate was relatively high in groups with more than 3 family members （OR=1.236） （P<0.05）. Compared with the groups aged 15-29， illiterate and semi-illiterate， married， Han ethnicity， employed， and those receiving public medical care， the awareness rate was higher among the groups aged 30-59 （OR=1.976）， 60 and above （OR=2.224）， those with high school education and above （OR=2.801）， and single （OR=2.244） in 2023. However， the awareness rates of ethnic minorities （OR=0.737）， the unemployed （OR=0.557）， and self-funded medical care （OR=0.497） groups were significantly lower （P<0.05）. ConclusionPublic awareness of TB prevention knowledge in Inner Mongolia remains suboptimal. Strengthening diversified health education campaigns， addressing social stigma， and improving healthcare access are critical to enhance regional TB control outcomes.

Autism spectrum disorder （ASD）， also known as autism， is a series of neurodevelopmental disorders characterized by social disorders and repetitive stereotyped behaviors/narrow interests. Its pathogenesis is complex， and there is a lack of effective treatment drugs， with some cases having adverse outcomes. Recent studies have consistently revealed that individuals with autism spectrum disorder （ASD） commonly exhibit characteristics such as gut microbiota dysbiosis （abnormal Bacteroidetes/Firmicutes ratio）， impaired intestinal barrier function （elevated serum levels of zonulin and LPS）， and intestinal immune dysregulation （increased pro-inflammatory cytokines including IL-6 and TNF-α）， suggesting that gastrointestinal abnormalities may influence central nervous system development through neuroendocrine， immunoregulatory， and metabolic pathways. Consequently， growing scholarly attention has focused on dietary interventions as potential approaches to alleviate clinical symptoms in children with ASD. This review systematically summarizes the role of gut microbiota and their metabolite alterations in ASD pathogenesis， along with recent advancements in understanding the microbiota-gut-brain axis mechanisms. Additionally， it elaborates on the therapeutic effects and underlying biological basis of restrictive diet therapy， modified diet therapy， and nutritional supplementation therapy in promoting the health of children with ASD. This systematic review reveals that children with ASD exhibit significant gut microbiota dysbiosis （e.g.， increased Clostridium， decreased Faecalibacterium） and abnormal metabolite profiles （e.g.， altered short-chain fatty acid spectra， elevated 4EPS levels）. These alterations exacerbate neuroinflammation and immune dysregulation through the microbiota-gut-brain axis， thereby impacting nervous system development and function. Furthermore， interventions such as ketogenic diets， camel milk， and specific nutritional supplements can alleviate certain ASD symptoms by modulating gut microbiota， restoring intestinal barrier function， and improving metabolic pathways. Future investigations should aim to create multi-omics evaluation systems for pinpointing potential beneficiaries， devise individualized intervention strategies rooted in microbiome characteristics， and verify their therapeutic value and safety in large-scale randomized controlled trials. These efforts are crucial to transitioning ASD treatment from symptomatic control to address disease etiology， thereby paving the way for improving prognoses.

Mainly based on the "constitution-syndrome-disease location correlation" approach， this study constructs a traditional Chinese medicine （TCM） framework for understanding hypertension comorbidities. From the perspective of shared constitutional predispositions and similar pathomechanistic characteristics， hypertension comorbidity should not be regarded as a simple aggregation of multiple diseases. Rather， it is generally rooted in biased constitutions such as yin-deficiency， qi-deficiency， yang-deficiency， phlegm-dampness， dampness-heat， and blood-stasis constitutions， accompanied by the long-term interplay of pathogenic mechanisms involving wind， fire， phlegm， stasis， and deficiency， and gradually manifests as comorbidities affecting different systems through the evolution of disease locations related to the liver， heart， spleen， and kidney. On this basis， cardiac-， cerebral-， renal-， and metabolic-related comorbidities are taken as the major categories， and their characteristics related to constitution， syndrome， and disease location are systematically summarized to clarify the correspondence between shared pathomechanisms and predominant disease locations， and to propose corresponding prevention and treatment strategies. This framework further incorporates constitution-based stratification into risk stratification for prospective intervention， and takes syndrome as the central link in developing multi-disease treatment strategies such as boosting qi and activating blood， as well as resolving phlegm and unblocking collaterals. A clinical pathway is thereby proposed， encompassing constitution assessment， syndrome differentiation， comorbidity risk stratification， integrated traditional Chinese and western medicine intervention， and follow-up feedback. This study aims to provide a reference for the theoretical development and collaborative management of hypertension comorbidities in TCM.

Objective To explore the relationship between intestinal flora imbalance and pulmonary function in patients with chronic obstructive pulmonary disease (COPD), and to analyze the related influencing factors. Methods A total of 310 patients with COPD who were admitted to Air Force Military Medical University Tangdu Hospital from June 2022 to December 2024 were retrospectively analyzed. Based on intestinal flora status, the enrolled patients were classified into imbalance group (n=83) and non-imbalance group (n=227). Logistic regression analysis was conducted to analyze the independent related factors of intestinal flora imbalance in COPD patients. Based on the above factors, a prediction model was constructed, and ROC curve analysis model was applied to analyze the predictive value of the model on intestinal flora imbalance. Results Logistic regression analysis revealed that age, IL-6, albumin, pulmonary function, long-term bed rest and long-term use of antibiotics were related to intestinal flora imbalance in COPD patients (all P<0.05). ROC results of the Logistic prediction model showed that the area under the curve, sensitivity, specificity and 95%CI were 0.961, 0.880, 0.996 and 0.932-0.989 respectively. Conclusion The intestinal flora imbalance in patients with COPD is closely related to lung function, age, inflammatory status, nutritional indicators, activity ability and antibiotic use.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

AIM:To measure preoperative corneal curvature in elderly cataract patients using five different systems, including Keratograph 5M, Pentacam, KR.800 autorefractor, IOL Master, and KR-1W wavefront aberrometer, analyze its discrepancy and consistency, and provide a reference for accurate intraocular lens(IOL)power calculation in elderly patients before cataract surgery.METHODS:This prospective study included 53 elderly cataract in-patients(90 eyes)who were admitted to our ophthalmology department between October 2022 and November 2024. The corneal curvature values(K1, K2)of postoperative eyes were measured using Keratograph 5M, Pentacam, KR.800, IOL Master, and KR-1W, and the mean keratometry(Km)was calculated.RESULTS:Statistically significant differences were observed in K1, K2, and Km values between Keratograph 5M and Pentacam, as well as between Keratograph 5M and IOL Master(all P<0.05), whereas no significant differences were found in K1, K2 and Km between Keratograph 5M and KR.800 or KR-1W(all P>0.05). Pearson correlation analysis showed a certain correlation of K1, K2 and Km obtained from Keratograph 5M with those from KR.800, Pentacam, IOL Master, and KR-1W(r=0.913-0.987, all P<0.001). Bland-Altman scatter plots demonstrated good consistency between Keratograph 5M and KR.800 or KR-1W, while its consistency with Pentacam and IOL Master was relatively poor.CONCLUSION:As an ocular surface analyzer, Keratograph 5M offers advantages such as simplicity, rapid measurement, strong repeatability, and low patient cooperation requirements. In elderly patients, corneal curvature measurements obtained by Keratograph 5M demonstrated good consistency with those from KR.800 and KR-1W, making them interchangeable based on individual conditions and cooperation levels of patients. However, its consistency with Pentacam and IOL Master was relatively poor; therefore, clinical practical situation should be considered when selecting such measurement devices.

Objective To observe the differences in gut microbiota in chronic unpredictable mild stress(CUMS)-induced depression model rats of both sexes,and to provide experimental evidence for exploring sex differences in depression onset.Methods Thirty-two healthy SD rats were divided randomly into four groups based on sex:Male control group(Control-M),Female control group(Control-F),Male model group(Model-M),and Female model group(Model-F)(n=8 rats per group).Rats in the control groups were fed without stimulation,while rats in the model groups were stimulated using the 28 d CUMS-induced depression method.After successful modeling,fresh feces were collected from all rats for high-throughput 16S rRNA sequencing.Behavioral observations were also conducted before and after preparing the model.Results The result of sucrose-preference,open-field,and forced-swimming tests differed significantly between the control and model groups.The result of the sucrose-preference test also differed between the sexes,while there was no difference in the open-field or forced-swimming test between the sexes.The α and β diversity of the gut microbiota genera showed an upward trend in the CUMS group compared with the control group.The ratio of Firmicutes/Bacteroidetes and the richness of the Roseburia and Lachnospiraceae_NK4A136_group were decreased in male rats but showed an increasing trend in female rats.Conclusions The ratio of Firmicutes/Bacteroidetes in the gut microbiota may be a key factor affecting the difference in the onset of depression between males and females,while the Roseburia and Lachnospiraceae_NK4A136_group be potential factors in correcting the gut microbiota and improving the symptoms of depression.

Periodontitis is a common chronic infectious disease resulting from the interaction between oral microorganisms and the host's immune system.The immune system plays a dual role in regulating inflammation.Macrophages,as a component of innate immu-nity,play a crucial role in both the onset and resolution of periodontitis.This article reviews the role of macrophages in periodontitis and the recent advances in targeting macrophages for the treatment of periodontitis.

Objective To explore the relationship between serum Niemann-pick type C1 like protein1(NPC1L1)and propro-tein convertase subtilisin/kexin type 9(PCSK9)levels and the risk of type 2 diabetes mellitus(T2DM)in Mongolian residents.Methods A total of 72 Mongolian patients with T2DM treated in Peking University Cancer Hospital,Inner Mongolia Hospital and the Affiliated Hospital of Inner Mongolia Medical University from June 2022 to June 2024 were selected as the T2DM group,and 81 healthy people in the same period were selected as the control group.LASSO model and multivariate Logistic regression model were used to screen the risk factors of disease onset.Multiple linear regression was used to analyze the correlation between NPC1L1 and PCSK9 levels and insulin function.Restricted cubic spline(RCS)model was used to analyze the dose-response relationship between NPC1L1 and PCSK9 levels and the incidence of T2DM,and explored the interaction between NPC1L1 and PCSK9 levels on the incidence of T2DM.Results NPC1L1(3.11±0.80 ng/L)and PCSK9(10.63±0.79 ng/L)in T2DM group were significantly higher than those in the control group(0.52±0.22 ng/L,3.21±0.17 ng/L),and the differences were statisti-cally significant(t=27.982,82.443,all P<0.05).NPC1L1(OR=2.458,95%CI=2.364～2.594,P<0.05)and PCSK9(OR=2.905,95%CI=2.541～3.528)were risk factors for T2DM(all P<0.001).The results of multiple linear regression analysis showed that as NPC1L1 and PCSK9 levels increased,FINS,HbA1c,C-P and OGTT levels also increased accordingly.With the increase of NPC1L1 and PCSK9 levels,insulin function also decreased(all P<0.05).The results of RCS model showed that with the increase of NPC1L1 and PCSK9 levels,the probability of T2DM incidence also increased(χ2=22.334,25.537,all P<0.001).No significant interaction was found between NPC1L1,PCSK9 levels and islet function indexes(P>0.05).Conclusion The levels of NPC1L1 and PCSK9 are closely related to the risk of T2DM in Mongolian residents.With the increase of NPC1L1 and PCSK9 levels,the incidence probability of T2DM increases.