Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

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.

Alzheimer's disease (AD) is characterized by cognitive and functional deterioration, with pathological features such as amyloid-beta (Aβ) aggregates in the extracellular spaces of parenchymal neurons and intracellular neurofibrillary tangles formed by the hyperphosphorylation of tau protein. Despite a thorough investigation, current treatments targeting the reduction of Aβ production, promotion of its clearance, and inhibition of tau protein phosphorylation and aggregation have not met clinical expectations, posing a substantial obstacle in the development of drugs for AD. Recently, artificial intelligence (AI), computational biology (CB), and systems biology (SB) have emerged as promising methodologies in AD research. Their capacity to analyze extensive and varied datasets facilitates the identification of intricate patterns, thereby enriching our comprehension of AD pathology. This paper provides a comprehensive examination of the utilization of AI, CB, and SB in the diagnosis of AD, including the use of imaging omics for early detection, drug discovery methods such as lecanemab, and complementary therapies like phototherapy. This review offers novel perspectives and potential avenues for further research in the realm of translational AD studies.

Stem cells play a crucial role in maintaining tissue regenerative capacity and homeostasis. However, mechanisms associated with stem cell senescence require further investigation. In this study, we conducted a proteomic analysis of human dental pulp stem cells (HDPSCs) obtained from individuals of various ages. Our findings showed that the expression of NUP62 was decreased in aged HDPSCs. We discovered that NUP62 alleviated senescence-associated phenotypes and enhanced differentiation potential both in vitro and in vivo. Conversely, the knocking down of NUP62 expression aggravated the senescence-associated phenotypes and impaired the proliferation and migration capacity of HDPSCs. Through RNA-sequence and decoding the epigenomic landscapes remodeled induced by NUP62 overexpression, we found that NUP62 helps alleviate senescence in HDPSCs by enhancing the nuclear transport of the transcription factor E2F1. This, in turn, stimulates the transcription of the epigenetic enzyme NSD2. Finally, the overexpression of NUP62 influences the H3K36me2 and H3K36me3 modifications of anti-aging genes (HMGA1, HMGA2, and SIRT6). Our results demonstrated that NUP62 regulates the fate of HDPSCs via NSD2-dependent epigenetic reprogramming.
Humans ; Dental Pulp/cytology* ; Nuclear Pore Complex Proteins/genetics* ; Cellular Senescence/genetics* ; Stem Cells/metabolism* ; Epigenesis, Genetic ; Cell Proliferation ; Cell Differentiation ; Histone-Lysine N-Methyltransferase/metabolism* ; Cells, Cultured ; Cellular Reprogramming ; Cell Movement ; Proteomics

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

Objective: This study aimed to explore the correlation between balance function and core muscle activation in patients with adolescent idiopathic scoliosis (AIS), compared to healthy individuals. Methods: A total of 24 AIS patients and 25 healthy controls were recruited. The limits of stability (LOS) test were conducted to assess balance function, while surface electromyography was used to measure the activity of core muscles, including the internal oblique, external oblique, and multifidus. Diaphragm thickness was measured using ultrasound during different postural tasks. Center of pressure (COP) displacement and trunk inclination distance were also recorded during the LOS test. Results: AIS patients showed significantly greater activation of superficial core muscles, such as the internal and external oblique muscles, compared to the control group (p < 0.05). Diaphragm activation was lower in AIS patients during balance tasks (p < 0.01). Although no significant difference was observed in COP displacement between the groups, trunk inclination was significantly greater in the AIS group during certain tasks (p < 0.05). Conclusion These findings suggest distinct postural control patterns in AIS patients, highlighting the importance of targeted interventions to improve balance and core muscle function in this population.

Objective:To evaluate the safety and efficacy of the probiotic Bifidobacterium longum subsp. longum BL21 (BL21) in preventing radiation-induced diarrhea (RID) in cervical cancer patients during radiotherapy (RT) and to investigate the intestinal microbiota in the patients. Methods:This study was a prospective, single-arm, phase Ⅱ clinical trial, involving cervical cancer patients treated with radical and adjuvant RT. From the first day of RT, participants took one pack of BL21 powder (containing 20 billion colony-forming unit(CFU) of Bifidobacterium longum subsp. longum BL21) orally every day until the end of RT. The occurrence of adverse events and RID during RT were assessed as per Common Terminology Criteria for Adverse Events ( CTCAE) v5.0. In this way, the safety and efficacy of BL21 in preventing RID were evaluated. Additionally, the intestinal microbiota in fecal samples collected from the patients before and after RT were analyzed using 16S rRNA sequencing. Results:A total of 35 cervical cancer patients were enrolled in this study, with 29 cases incorporated for the final analysis. No serious adverse event related to the administration of BL21 was observed. The patients exhibited slight RID, with the majority (22/29) developing no or grade 1 RID during RT. The microbiota in the fecal samples showed decreased alpha diversity after RT, as indicated by the Chao1 ( P = 0.002) and Shannon ( P = 0.005) indices. Furthermore, these samples exhibited a notably higher abundance of genus Clostridium (LDA score = 3.98). The fecal samples from patients with grade 1 RID or no RID post-RT exhibited higher alpha diversity than those from patients with grade 2 RID or above post-RT (Chao1: P = 0.07, Shannon: P = 0.28), as well as a high abundance of genera Gemmiger (LDA score = 4.48) and Dorea (LDA score = 3.83). Conclusions:The administration of BL21 to cervical cancer patients during RT is simple, convenient, safe, and effective in preventing RID, thus warranting further investigation.

Objective To identify subtypes of lower-grade gliomas based on multi-omics data integration with consensus clustering ensemble(MICCE)method,and further assess prognosis risk across different subtypes and explore differentially expressed biomarkers and pathways.Methods We applied the consensus clustering ensemble method to integrate the subtype results of seven multi-omics data integration methods(SNF,joint SNF,CIMLR,ConsensusClusterPlus,MoCluster,NEMO,iClusterBayes)for mRNA,miRNA,and DNA methylation data from LGG patients,identifying a robust molecular subtyping.Then we performed survival analysis based on the subtype results,and Cox proportional risk models were fitted to assess the prognosis of patients with different subtypes.Differentially expressed genes(DEmiRNAs,DEmRNAs and DMGs)between different subtypes were screened,and GO(gene ontology)analysis and KEGG enrichment analysis were performed for overlapping genes among DEmiRNAs target genes,DEmRNAs,and DMGs.Ultimately,immune infiltration analysis and pathway activity analysis were conducted to quantify the biological differences among different subtypes.Results Patients were classified into three subtypes:a high-risk cluster,a moderate-risk cluster,and a low-risk cluster.The results showed that the high-risk cluster were 7.70 times more likely to die than patients in low-risk cluster.A total of 2512 DEmRNAs,14 DEmiRNAs and 255 DMGs were screened,the combined analysis genes yielded 665 genes which are regulated by mRNA,miRNA and DNA methylation and enriched 62 GO items and 52 KECG pathways with statistical differences.The analysis of immune infiltration and pathway activity indicates that there are two immune cells and four signaling pathways with statistically significant differences.Conclusion MICCE can effectively identify high-risk patients of LGG.Subsequent analysis reveals differential genes and pathways related to the progression of LGG with different subtypes,providing important clues for the personalized treatment of LGG.

Objective To investigate the clinical efficacy and safety of facilitated percutaneous coronary intervention(PCI)with half-dose recombinant staphylokinase(r-SAK)in patients with ST-segment elevation myocardial infarction(STEMI)who are expected to undergo PCI within 120 minutes.Methods From October 2021 to August 2022,a total of 200 STEMI patients in eight centers were included and randomly assigned in a 1﹕1 ratio to either r-SAK group or control group.Patients received loading doses of aspirin and ticagrelor and intravenous heparin and were randomized to receive an intravenous bolus of either 5 mg r-SAK or normal saline prior to PCI.The outcomes were set as ST-segment resolution(STR)at 60-90 minutes after PCI,the proportion and transition of pathological Q waves on the 5th day after PCI,and the proportion of high-sensitivity cardiac troponin T(hs-cTnT)peaking within 12 hours of onset.The safety outcome was major bleeding events defined as Bleeding Academic Research Consortium(BARC)≥type 3 bleeding during hospitalization.Results Compared with the control group,the r-SAK group had a higher proportion of STR≥70%within 60-90 minutes after PCI(58.3%vs.40.3%,P=0.009);a lower proportion of pathological Q waves(59.1%vs.74.1%,P=0.040);a lower rate of Q wave progression(14.8%vs.43.2%,P＜0.001);a higher rate of Q wave disappearance(12.5%vs.3.7%,P=0.027);and a higher proportion of hs-cTnT peaking within 12 hours of symptom onset[31/40(77.5%)vs.17/33(51.5%),P=0.027].Regarding the safety outcome,no significant difference in BARC≥type 3 bleeding was found between the two groups during hospitalization(P＞0.05).Conclusions For STEMI patients who were expected to undergo primary PCI within 120 minutes of symptom onset,the facilitated PCI with half-dose r-SAK significantly increased the proportion of STR≥70%at 60-90 minutes after PCI,reduced the formation of pathological Q waves,and shortened the time to peak hs-cTnT,without increasing the risk of bleeding,which should be an alternative reperfusion strategy worthy of further study.