The spine is the most common site of skeletal metastasis in lung cancer, which frequently leads to severe complications such as pathological fracture and neurological compromise and is associated with poor prognosis. The development and progression of spinal metastasis from lung cancer are linked to the unique local microenvironment and tumor microenvironment (TME) of the vertebral column. During metastatic evolution, the dense vascular network of the spine and a plethora of signaling molecules, together with the complex cellular constituents and their intricate interactions within the TME, all cooperate to facilitate the tumor invasion and colonization of the vertebral compartment. Mechanistic studies delineating the role of the TME in spinal metastasis from lung cancer have markedly expanded, fostering the emergence of innovative therapeutic strategies—including nanomedicines, sono-photodynamic therapy, gene therapy, and combination regimens. These strategies demonstrate remarkably potential for clinical translation and offer new directions for the precision management of spinal metastasis from lung cancer.

Cancer is a serious global health problem and a major cause of human death. Conventional cancer treatments often run the risk of impairing vital organ functions. Anticancer peptides (ACPs) are considered to be one of the most promising therapeutic agents against common human cancers due to their small sizes, high specificity, and low toxicity. Since ACP recognition is highly limited to the laboratory, expensive, and time-consuming, we proposed pLM4ACP, a model for predicting ACPs based on machine learning and protein language models. In this model, the protein language model ProtT5 was used to extract the features of ACPs, and the extracted features were input into the support vector machine (SVM) classification algorithm for optimization and performance evaluation. The model showcased significantly higher accuracy than other methods, with the overall accuracy of 0.763, F1-score of 0.767, Matthews correlation coefficient of 0.527, and area under the curve of 0.827 on the independent test set. This study constructs an efficient anticancer peptide prediction model based on protein language models, further advancing the application of artificial intelligence in the biomedical field and promoting the development of precision medicine and computational biology.
Machine Learning ; Antineoplastic Agents/chemistry* ; Humans ; Peptides/chemistry* ; Support Vector Machine ; Algorithms ; Computational Biology/methods* ; Neoplasms/drug therapy*

Objective:To visually analyze the research hot-spots and development trends of pelvic floor dysfunction nursing, in order to provide a reference for the research of pelvic floor dysfunction nursing in China.Methods:The China National Knowledge Infrastructure (CNKI) and Web of Science core collection were used as the retrieval databases to retrieve the literature in the field of pelvic floor dysfunction nursing from the establishment of the database to January 31, 2025. CiteSpace 6.4.R1 software was used to visually analyze the included literature.Results:A total of 1 947 Chinese articles and 4 931 English articles were included. The number of English literature increased year by year, while Chinese literature showed a downward trend since 2019. There were more and stable core authors and core institutions in foreign research, while there was less cooperation among domestic authors and institutions. The research hotspots abroad mainly focused on improving the quality of nursing care and managing specific health problems. The future development trends were primarily randomized controlled trials, tension-free vaginal tape, postoperative care, and patient experience. The research hotspots in China mainly focused on nursing interventions. The future development trends were primarily patient quality of life and effectiveness evaluation.Conclusions:Due to different development stages, compared with foreign countries, there are still some deficiencies in evidence-based medicine, delicacy of nursing after tension-free vaginal tape, patient experience, innovation of nursing technology, and depth and breadth of nursing research in China. In the future, we should learn from foreign studies to promote the development of nursing research on pelvic floor dysfunction in China.

OBJECTIVES: To analyze the trends of disease burden of lip and oral cancers in East Asia from 1990 to 2021 and its future projections. METHODS: We used the Global Burden of Disease 2021 database to conduct a comprehensive analysis of disease burden data from China (including Taiwan Province of China), Japan, Republic of Korea, Democratic People's Republic of Korea and Mongolia. The data were stratified by age, gender and major risk factors, and a Bayesian age-period-cohort model was employed to predict the future trends. RESULTS: From 1990 to 2021, the burden of lip and oral cancers in East Asian countries exhibited a steady increase. Taiwan Province of China experienced the most significant increases in incidence, prevalence, mortality, and disability-adjusted life years (DALYs), while Mongolia saw a decline in both mortality and DALYs. In 2021, Taiwan Province of China reported the highest rates of lip and oral cancer incidence (27.50 per 100 000), prevalence (137.92 per 100 000), mortality (9.59 per 100 000), and DALYs (292.07 person-years per 100 000), particularly among male and elderly populations. Tobacco use and alcohol consumption significantly exacerbated the disease burden in Taiwan Province of China and Japan. Future projections indicate that the incidence and prevalence of lip and oral cancer in China (excluding Taiwan Province of China) will continue to rise, while their mortality rates are expected to decline in most regions, except for Taiwan Province of China and Democratic People's Republic of Korea. CONCLUSIONS By the year 2035, the disease burden of lip and oral cancers in East Asia is expected to continue to increase, especially in Taiwan Province of China. To address this challenge, it is essential to implement effective measures to control major risk factors, promote early screening, and ensure equitable distribution of healthcare resources.
Humans ; Mouth Neoplasms/epidemiology* ; Incidence ; Lip Neoplasms/epidemiology* ; Asia, Eastern/epidemiology* ; Male ; Disability-Adjusted Life Years ; Prevalence ; Female ; Forecasting ; Risk Factors ; Cost of Illness ; Middle Aged ; Global Burden of Disease ; Aged ; Bayes Theorem

Objective To investigate the effect and mechanism of melatonin in alleviating hypoxia-induced apoptosis in ovarian gra-nulosa cells.Methods Rat ovarian granulosa cells were isolated and divided into normoxic,hypoxic,and melatonin groups.Hypoxia-induced injury models were established in the hypoxic and melatonin groups,and granulosa cells in the melatonin group were treated with melatonin.A total of 24 rats were randomized into the control,model,and intervention groups(n=8 per group).Rat models of declining ovarian function induced by long-term hypoxia were established in the model and intervention groups.The rats in the intervention group were intraperitoneally injected with melatonin.Cell proliferation was measured using a CCK-8 assay,and lactate secretion and HIF-1αprotein with a specific kit,respectively.The levels of estradiol and progesterone in the cell supernatant and rat serum were detected using ELISA.Granulosa cell apoptosis was detected by flow cytometry,ovarian morphology by HE staining,and Bax and caspase-3 expression by Western blotting.Results Compared with the normoxic group,the hypoxic group exhibited decreased granulosa cell proliferation,increased apoptosis,elevated lactate and HIF-1α levels,and reduced estradiol and progesterone levels(P＜0.05).Compared with hypoxic group,these changes were significantly reversed in the molatonin group(P＜0.05).Compared with the control group,the model group showed increased lactate,HIF-1α,Bax,and caspase-3 levels,decreased estradiol and progesterone levels,and reduced follicles.Compared with the model group,all the indicators were ameliorated in the intervention group(P＜0.05).Conclusion Melatonin alleviated hypoxia-induced granulosa cell apoptosis and promoted the recovery of ovarian function.

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

Purpose To investigate the functional connectivity(FC)pattern between the bilateral lower limb sensorimotor cortex(LSM)and the whole brain in type 2 diabetic peripheral neuropathy(DPN).Materials and Methods A total of 44 DPN patients and 43 healthy controls admitted to Shaanxi Provincial People's Hospital from February 2021 to December 2022 were enrolled prospectively and underwent neuropsychological assessment and resting-state fMRI scans.Using bilateral LSM as the regions of interest,the differences of bilateral LSM and whole brain FC between DPN patients and healthy controls were compared.FC in different brain areas were extracted and correlated with clinical/neuropsychological scores.Results Compared with healthy controls,DPN patients had reduced FC of the LSM with the right cerebellar lobule Ⅵ,the right lateral occipitotemporal cortex,the bilateral rostral prefrontal cortex and the bilateral anterior cingulate gyrus.The FC between LSM and right cerebellar Ⅵ in DPN patients were significantly negatively correlated with fasting blood glucose(r=-0.490,P=0.001).The FC between LSM and bilateral anterior cingulate gyrus in DPN patients were significantly positively correlated with Montreal cognitive assessment scores(r=0.479,P=0.001).Conclusion Abnormal FC between LSM and multiple brain regions,suggesting that DPN may have extensive effects on brain regions that maintain motion and motor control function in type 2 diabetes mellitus patients.

Parkinson's disease (PD), a major neurodegenerative disease faced by an aging society worldwide, has not yet been fully elucidated in terms of its pathogenesis. Currently, clinical treatment mainly relies on symptom management and can only be relieved by medication. In recent years, many studies have shown that polysaccharides have potential in treatment of neurodegenerative diseases. Polysaccharides play a role in PD in ways such as anti-oxidative stress response, improvement of mitochondrial dysfunction, inhibition of neuroinflammation, anti-neurotoxicity, and activation of autophagy. This study discusses the mechanism of polysaccharides in PD, aiming to provide new ideas for PD prevention and treatment and new drug development in the future.

Objective To investigate the value of gadolinium-ethoxybenzyl-diethylenetriaminepentaacetic acid(Gd-EOB-DTPA)enhanced MRI and T1 mapping for evaluating vessels encapsulating tumor clusters(VETC)caused by hepatocellular carcinoma(HCC).Methods Totally 112 cases of HCC confirmed by surgical pathology were retrospectively enrolled and categorized into positive group(n=46)and negative group(n=66)based on the presence or absence of VETC.Gd-EOB-DTPA enhanced MRI features and T1 mapping parameters were compared between groups.Multivariate logistic regression analysis was used to identify independent risk factors for HCC VETC,and a combined nomogram model was developed.Receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate the efficacy of the identified independent risk factors and nomogram model for predicting HCC VETC.Results The maximum diameter of HCC,incidence of non-smooth tumor margin,prevalence of peritumoral hypo-intensity on hepatobiliary phase(HBP),as well as T1 value of HBP(T1post)in positive group were all higher,while the change rate of T1 value(ΔT1％)in positive group was lower than those in negative group(all P＜0.05).The increased maximum diameter,non-smooth margin,peritumoral hypo-intensity on HBP and low ΔT1％were all independent risk factors for HCC VETC(all P＜0.05),with AUC for predicting HCC VETC of 0.680,0.675,0.686 and 0.752,respectively.The nomogram model developed based on the combination of the above factors showed sensitivity of 78.79％,specificity of 71.74％and AUC of 0.839 for predicting HCC VETC.Conclusion Gd-EOB-DTPA enhanced MRI combined with T1 mapping could be used to effectively predict HCC VETC.

Objective:This study identifies independent predictive indicators to distinguish autoimmune gastritis from Helicobacter pylori ( H. pylori)-induced atrophic gastritis and validates their diagnostic performance to compare laboratory indicators of autoimmune gastritis and H. pylori-induced atrophic gastritis. Methods:A retrospective comparison of laboratory examination indicators was conducted for chronic atrophic gastritis patients with involvement of the gastric fundus and corpus, who were followed up at the Department of Gastroenterology, Xijing Hospital, from January 2014 to September 2024. Receiver operating characteristic (ROC) curves were utilized to determine the optimal cutoff points and corresponding diagnostic thresholds. In addition, multivariate logistic regression analysis was conducted to identify independent predictive indicators for autoimmune gastritis, with further assessment in a validation cohort.Results:A total of 139 patients with autoimmune gastritis and 209 patients with H. pylori-induced atrophic gastritis were included. Pepsinogen (PG) Ⅰ levels and the PG Ⅰ/PG Ⅱ ratio in patients with autoimmune gastritis were significantly lower than in those with H. pylori-induced atrophic gastritis [11.0 (4.8, 22.5) vs. 41.8 (32.2, 59.9) μg/L, U=722.00, P<0.001; 1.24 (0.75, 3.54) vs. 5.76 (4.31, 7.12), U=817.00, P<0.001], while gastrin levels were significantly higher [375 (84, 738) vs. 49 (35, 81) ng/L, U=378.00, P<0.001]. PG Ⅰ was identified as an independent predictive variable, with an area under the ROC curve of 0.847 (95% CI 0.791-0.904), sensitivity of 77.6%, specificity of 91.8%, positive predictive value of 80.5%, and negative predictive value of 90.5%. Conclusions:Significant differences in laboratory indicators were observed between autoimmune gastritis and H. pylori-induced atrophic gastritis in chronic atrophic gastritis involving gastric fundus and corpus. Besides, PG Ⅰ demonstrated good diagnostic performance in identifying autoimmune gastritis and can effectively differentiate between different types of atrophic gastritis.