Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Based on the traditional Chinese medicine(TCM) theory of "kidney-brain interaction", a two-sample Mendelian randomization(MR) analysis was conducted to investigate the causal effects of chronic kidney disease(CKD) on Alzheimer's disease(AD) and analyze the potential mechanisms of kidney-tonifying and essence-replenishing TCM to improve AD. From the perspective that CKD is closely related to the core pathogenesis of AD, namely "kidney deficiency, essence loss, and marrow reduction", genome-wide association study(GWAS) data was used, with the inverse variance weighting(IVW) method as the main approach to reveal the causal association between CKD and AD. Sensitivity analysis was conducted to evaluate the robustness of the results. To further investigate the causal effects of CKD on AD, two different AD datasets were used as outcomes, and the urinary albumin-to-creatinine ratio(UACR) data was used as the exposure for a supplementary analysis. On this basis, the modern scientific mechanism of the kidney-tonifying and essence-replenishing method for improving AD was further explored. The IVW analysis show that CKD(ieu-b-2: OR=1.084, 95%CI[1.011, 1.163], P=0.024; ieu-b-5067: OR=1.001, 95%CI[1.000, 1.001], P=0.002) and UACR(ieu-b-2: OR=1.247, 95%CI[1.021, 1.522], P=0.031; ieu-b-5067: OR=1.001, 95%CI[1.000, 1.003], P=0.015) both have significant causal effects on AD in different datasets, with CKD increasing the risk of AD. The sensitivity analysis further confirmed the reliability of the results. Genetic studies have shown that CKD has a significant causal effect on AD, suggesting that controlling CKD is an important intervention measure for preventing and treating AD. Therefore, further research on CKD's role in AD is crucial in clinical practice. The research enriches the theoretical implication of "kidney-brain interaction", deepens the understanding of AD' etiology, and provides further insights and directions for the prevention and treatment of AD with TCM, specifically from a kidney-based perspective.
Humans ; Alzheimer Disease/genetics* ; Renal Insufficiency, Chronic/genetics* ; Kidney/metabolism* ; Brain/physiopathology* ; Genome-Wide Association Study ; Medicine, Chinese Traditional ; Mendelian Randomization Analysis

BACKGROUND: Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN). METHODS: This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models. RESULTS: The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability. CONCLUSIONS The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
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Humans ; Male ; Female ; Lung Neoplasms/pathology* ; Middle Aged ; Retrospective Studies ; Artificial Intelligence ; Aged ; Tomography, X-Ray Computed ; Adult ; Solitary Pulmonary Nodule/diagnostic imaging* ; ROC Curve

OBJECTIVE: To systematically evaluate the effect and safety of the combination of Compound Xuanju Capsules (CXC) and Western medicine (WM) in the treatment of type Ш prostatitis complicated by ED. METHODS: We searched for randomized controlled trials (RCT) on the treatment of type Ш prostatitis complicated by ED with CXC+WM or WM in the Chinese and English databases CNKI, VIP, Wanfang Digital, Duxiu Academic Search and Chaoxing Electronic Book Information Retrieval, Fangzheng Apabi Electronic Book, Google Scholar Search, Web of Science, Scopus, PubMed, and others from their establishment to April 2024. According to the Cochrane Handbook requirement, we subjected the identified RCTs to meta-analysis using the RevMan 5.3 software. RESULTS: A total of 16 eligible studies were identified, involving 742 cases treated by combination therapy of CXC+WM and another 742 with WM alone. The results of meta-analysis showed that the rate of clinical effectiveness was dramatically higher in the CXC+WM than in the WM group (P<0.01, MD = 6.19, 95% CI: 4.63－8.28), and so were the IIEF-5 scores (P < 0.004, MD = 2.90, 95% CI: 0.90－4.89), while the quality of life (QOL) scores were significantly lower in the former group than in the latter (P<0.01, MD = －1.94, 95% CI: －2.47－－1.40), and so were the NIH-CPSI scores (P<0.01, MD = －3.92, 95% CI: －4.94－－2.91). No statistically significant difference was reported in the adverse reactions between the two groups (P = 0.12, MD = 0.03, 95% CI: －0.01－0.08). Publication bias analysis on the effectiveness rate of the results revealed an incomplete symmetry between the two sides of the funnel plot, indicating the possibility of publication biases. CONCLUSION The combination therapy of CXC+WM is superior to WM alone in the treatment of type Ш prostatitis complicated by ED for its high safety and effect of improving the patients' erectile function, but inferior to the latter in improving the QOL and NIH-CPSI scores of the patients.
Male ; Humans ; Prostatitis/complications* ; Erectile Dysfunction/complications* ; Drugs, Chinese Herbal/therapeutic use* ; Capsules ; Randomized Controlled Trials as Topic ; Drug Therapy, Combination ; Treatment Outcome ; Quality of Life ; Phytotherapy

Loss of protein homeostasis is a hallmark of cellular senescence, and ribosome pausing plays a crucial role in the collapse of proteostasis. However, our understanding of ribosome pausing in senescent cells remains limited. In this study, we utilized ribosome profiling and G-quadruplex RNA immunoprecipitation sequencing techniques to explore the impact of RNA G-quadruplex (rG4) on the translation efficiency in senescent cells. Our results revealed a reduction in the translation efficiency of rG4-rich genes in senescent cells and demonstrated that rG4 structures within coding sequence can impede translation both in vivo and in vitro. Moreover, we observed a significant increase in the abundance of rG4 structures in senescent cells, and the stabilization of the rG4 structures further exacerbated cellular senescence. Mechanistically, the RNA helicase DHX9 functions as a key regulator of rG4 abundance, and its reduced expression in senescent cells contributing to increased ribosome pausing. Additionally, we also observed an increased abundance of rG4, an imbalance in protein homeostasis, and reduced DHX9 expression in aged mice. In summary, our findings reveal a novel biological role for rG4 and DHX9 in the regulation of translation and proteostasis, which may have implications for delaying cellular senescence and the aging process.
G-Quadruplexes ; Cellular Senescence ; Ribosomes/genetics* ; Humans ; Animals ; Mice ; DEAD-box RNA Helicases/genetics* ; Protein Biosynthesis ; RNA/chemistry* ; Neoplasm Proteins

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Aim To study the neuroprotective effects of Herba siegesbeckiae extract on cerebral ischemia/ reperfusion rats and its mechanism. Methods Sixty SD rats were randomly divided into model group, low, middle and high dose groups of Herba siegesbeckiae, and Sham operation group, and the drug was given continuously for seven days. The degree of neurologic impairment was evaluated by mNSS, and the infarct volume was measured by MRI. The number of Nissl-posi- tive cells was detected by Nissl staining, and the apop- tosis was accessed by Tunel staining. Furthermore, the expression of Bax, Bcl-2 and NeuN was observed by Western blot, and the expression of NeuN was detected by immunofluorescence staining. The expression of IL- 1β, TNF-α and IL-6 mRNA was performed by RT- qPCR. Results The mNSS score and the volume of ischemic cerebral infarction in the model group were significantly increased, and Herba siegesbeckiae extract treatment significantly decreased the mNSS score and infarct volume (P<0.05, P<0.01). Herba siegesbeckiae extract could increase the number of Nissl-pos- itive cells and the expression of NeuN (P<0.01), and reduce the number of Tunel-positive cells (P<0.01). Western blot showed that Herba siegesbeckiae extract inhibited the expression of Bax, increased Bcl-2 and NeuN in ischemic brain tissue (P<0.01). RT-qPCR showed that Herba siegesbeckiae extract inhibited the expression of IL-1 β, TNF-α and IL-6 mRNA in the is-chemic brain tissue (P<0.01). Conclusions Herba siegesbeckiae extract can reduce the cerebral infarction volume, improve the neurological function damage, inhibit the apoptosis of nerve cells and the expression of inflammatory factors and promote the expression of NeuN, there by exerting protective effects on MCAO rats.

Objective:To investigate the prognosis of patients with initially resectable gastric cancer liver metastasis (GCLM) who were treated by different modalities, and analyze the influencing factors for prognosis of patients.Methods:The retrospective cohort study was conducted. The clinicopathological data of 327 patients with initially resectable GCLM who were included in the database of a nationwide multicenter retrospective cohort study on GCLM based on real-world data from January 2010 to December 2019 were collected. There were 267 males and 60 females, aged 61(54,68)years. According to the specific situations of patients, treatment modalities included radical surgery combined with systemic treatment, palliative surgery combined with systemic treatment, and systemic treatment alone. Observation indicators: (1) clinical characteristics of patients who were treated by different modalities; (2) prognostic outcomes of patients who were treated by different modalities; (3) analysis of influencing factors for prognosis of patients with initially resectable GCLM; (4) screening of potential beneficiaries in patients who were treated by radical surgery plus systemic treatment and patients who were treated by palliative surgery plus systemic treatment. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the independent sample t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was conducted using the rank sum test. Count data were described as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test. The Kaplan-Meier method was used to calculate survival rate and draw survival curve, and Log-Rank test was used for survival analysis. Univariate and multivariate analyses were conducted using the COX proportional hazard regression model. The propensity score matching was employed by the 1:1 nearest neighbor matching method with a caliper value of 0.1. The forest plots were utilized to evaluate potential benefits of diverse surgical combined with systemic treatments within the population. Results:(1) Clinical characteristics of patients who were treated by different modalities. Of 327 patients, there were 118 cases undergoing radical surgery plus systemic treatment, 164 cases undergoing palliative surgery plus systemic treatment, and 45 cases undergoing systemic treatment alone. There were significant differences in smoking, drinking, site of primary gastric tumor, diameter of primary gastric tumor, site of liver metastasis, and metastatic interval among the three groups of patients ( P<0.05). (2) Prognostic outcomes of patients who were treated by different modalities. The median overall survival time of the 327 pati-ents was 19.9 months (95% confidence interval as 14.9-24.9 months), with 1-, 3-year overall survival rate of 61.3%, 32.7%, respectively. The 1-year overall survival rates of patients undergoing radical surgery plus systemic treatment, palliative surgery plus systemic treatment and systemic treatment alone were 68.3%, 63.1%, 30.6%, and the 3-year overall survival rates were 41.1%, 29.9%, 11.9%, showing a significant difference in overall survival rate among the three groups of patients ( χ2=19.46, P<0.05). Results of further analysis showed that there was a significant difference in overall survival rate between patients undergoing radical surgery plus systemic treatment and patients undergoing systemic treatment alone ( hazard ratio=0.40, 95% confidence interval as 0.26-0.61, P<0.05), between patients undergoing palliative surgery plus systemic treatment and patients under-going systemic treatment alone ( hazard ratio=0.47, 95% confidence interval as 0.32-0.71, P<0.05). (3) Analysis of influencing factors for prognosis of patients with initially resectable GCLM. Results of multivariate analysis showed that the larger primary gastric tumor, poorly differentiated tumor, larger liver metastasis, multiple hepatic metastases were independent risk factors for prognosis of patients with initially resectable GCLM ( hazard ratio=1.20, 1.70, 1.20, 2.06, 95% confidence interval as 1.14-1.27, 1.25-2.31, 1.04-1.42, 1.45-2.92, P<0.05) and immunotherapy or targeted therapy, the treatment modality of radical or palliative surgery plus systemic therapy were independent protective factors for prognosis of patients with initially resectable GCLM ( hazard ratio=0.60, 0.39, 0.46, 95% confidence interval as 0.42-0.87, 0.25-0.60, 0.30-0.70, P<0.05). (4) Screening of potentinal beneficiaries in patients who were treated by radical surgery plus systemic treatment and patients who were treated by palliative surgery plus systemic treatment. Results of forest plots analysis showed that for patients with high-moderate differentiated GCLM and patients with liver metastasis located in the left liver, the overall survival rate of patients undergoing radical surgery plus systemic treatment was better than patients undergoing palliative surgery plus systemic treatment ( hazard ratio=0.21, 0.42, 95% confidence interval as 0.09-0.48, 0.23-0.78, P<0.05). Conclusions:Compared to systemic therapy alone, both radical and palliative surgery plus systemic therapy can improve the pro-gnosis of patients with initially resectable GCLM. The larger primary gastric tumor, poorly differen-tiated tumor, larger liver metastasis, multiple hepatic metastases are independent risk factors for prognosis of patients with initial resectable GCLM and immunotherapy or targeted therapy, the treatment modality of radical or palliative surgery plus systemic therapy are independent protective factors for prognosis of patients with initially resectable GCLM.