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.

Plant-derived extracellular vesicles (PDEVs) are nanoscale extracellular vesicles secreted by plant cells, characterized by a lipid bilayer structure. These vesicles carry a variety of bioactive molecules, including proteins, nucleic acids, and lipids, and play essential roles in intercellular communication and physiological regulation in plants. Compared to animal-derived extracellular vesicles, PDEVs offer several advantages, such as a broad range of sources, high biocompatibility, low immunogenicity, and low production costs. Furthermore, PDEVs have demonstrated remarkable potential as natural nanocarriers for drug delivery, due to their ability to efficiently traverse biological barriers, such as the blood-brain barrier, making them promising candidates for drug delivery systems. This review systematically elaborates on the complex composition of PDEVs, which consists of lipids, proteins, and nucleic acids, the typical structural characteristics of their lipid bilayers ranging from 30 to 150 nm, and their versatile loading capabilities as drug carriers, efficiently encapsulating various types of therapeutic agents such as hydrophilic small molecules, hydrophobic drugs, nucleic acids, and proteins. We systematically summarize the recent advancements in strategies for enhancing the loading efficiency of PDEVs, which include methods such as co-incubation, ultrasound-assisted loading, electroporation, freeze-thaw cycles, and microfluidic technology. These techniques are evaluated based on their underlying principles, suitable drug types, and their respective advantages. In addition to loading strategies, we focus on the engineered approaches to achieve targeted delivery using PDEVs, such as genetic engineering modifications, chemical ligand conjugation, membrane fusion technology, and polyethylene glycol (PEG) modification. We discuss the mechanisms of these strategies in enhancing targeting efficiency, prolonging in vivo circulation time, and improving therapeutic efficacy. Further, this review highlights the application of PDEVs in various disease models, including tumor, skin inflammation, metabolic disorders, and neurodegenerative diseases, showcasing their therapeutic potential as multifunctional delivery platforms. The ability of PDEVs to encapsulate diverse therapeutic agents and target specific tissues or cells opens up new avenues for the treatment of complex diseases, offering advantages over conventional drug delivery systems. However, despite the promising applications of PDEVs, several challenges remain in their development and clinical translation. These challenges include variability in source materials, standardization of preparation processes, quality control, scalability of production, and the need for clinical validation. To overcome these obstacles, the integration of advanced technologies such as artificial intelligence-assisted design and multi-omics analysis is proposed as a way to facilitate the precise development of PDEVs. These emerging technologies hold the potential to further enhance the precision and effectiveness of plant-based drug delivery systems, ultimately advancing the field of precision medicine. In conclusion, the use of PDEVs as a platform for drug delivery represents a promising area of research with the potential to revolutionize therapeutic strategies. Their ability to encapsulate and deliver a wide variety of bioactive molecules, along with their inherent advantages in biocompatibility and versatility, makes them a valuable tool in the development of more efficient and targeted therapeutic interventions. Continued research and innovation in this field will pave the way for the clinical implementation of PDEVs in the treatment of various diseases, offering new hope for more effective and sustainable therapeutic options.

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.

ObjectiveTo investigate the contamination status of arsenic (As), cadmium (Cd), lead (Pb), and mercury (Hg) in commercially available aquatic products in Shanghai and their distribution characteristics among different categories of aquatic products, and to assess the dietary exposure levels and non‑carcinogenic health risks of As, Cd, Pb, and Hg through aquatic product consumption among different age groups, so as to provide a scientific basis for food safety surveillance of aquatic products and dietary risk management for residents in Shanghai. MethodsFrom October to November 2021, a total of 90 aquatic product samples, including marine fish, freshwater fish, freshwater shrimp, marine crab, freshwater crab, and mollusks, were randomly collected from 16 districts of Shanghai. Sample pretreatment was performed according to GB 5009.268‒2016 (National Food Safety Standard—Determination of Multi‑elements in Foods). The concentrations of As, Cd, and Pb in aquatic products were determined by inductively coupled plasma mass spectrometry (ICP‑MS), and Hg was determined by direct mercury analyzer. Inorganic arsenic (iAs) was estimated as 3.5% of total As according to the method recommended by the European Food Safety Authority (EFSA). The contamination levels of As, Cd, Pb, and Hg in aquatic products were evaluated according to GB 2762‒2017 (National Food Safety Standard—Maximum Levels of Contaminants in Foods). A combined approach of point assessment and probabilistic assessment was applied to estimate the estimated daily intake (EDI) and non‑carcinogenic risk indicators—hazard quotient (HQ) and hazard index (HI)—for different age groups. ResultsThe detection rates of As and Hg were both 100.00% in all samples, while those of Cd and Pb were 74.44% and 25.56%, respectively. The arithmetic means (wet weight) of the four elements and estimated iAs were: As (1.432 9±3.736 5) mg·kg^-1, iAs (0.050 2±0.130 8) mg·kg^-1, Cd (0.082 5±0.197 8) mg·kg^-1, Pb (0.006 1±0.005 5) mg·kg^-1, and Hg (0.021 9±0.016 7) mg·kg^-1. According to the relevant maximum residue limits, 2 out of 7 mollusk samples (28.57%) and 3 out of 20 marine fish samples (15.00%) exceeded the limit for iAs, and 2 out of 8 marine crab samples (25.00%) exceeded the limit for Cd. The estimated daily intake (EDI, μg·kg^-1·d^-1, by body weight) of iAs, Cd, Pb, and Hg via aquatic product consumption varied among different age groups, with the highest levels observed in children aged 3‒4 years, decreasing gradually with age to the lowest level at 12 ‒ <15 years, with a slight rebound thereafter. The point assessment results showed that the HQs of iAs, Cd, Pb, and Hg ranged from 0 to 0.25, and the cumulative HI ranged from 0.27 to 0.48, all below 1, indicating a relatively low overall risk. The probabilistic assessment results revealed that under the high‑exposure scenario (P_97.5), the HQs of iAs (1.101‒1.281) and Cd (1.175‒1.366) exceeded 1 in children aged 3‒9 years, suggesting potential health risks, while the HQs of Pb and Hg were all below 1, indicating relatively lower risks. ConclusionHg and As are ubiquitously detected in commercially available aquatic products in Shanghai, while the detection rates of Cd and Pb are relatively low. The overall non-carcinogenic risk is at an acceptable level, but children aged 3‒9 years may have potential health risks from iAs and Cd under high-percentile exposure levels. It is recommended to strengthen the monitoring of toxic elements in key aquatic products such as marine fish, mollusks, and marine crabs, and to implement targeted dietary risk management measures for sensitive populations, including children.

To investigate the effects and mechanisms of Yougui Pills(YGP) on oxidative damage induced by hydrogen peroxide(H_2O_2) in human ovarian granulosa cells(KGN). The components in serum with low-and high-doses of YGP were analyzed and compared through ultra-high performance liquid chromatography-quadrupole electrostatic field orbitrap mass spectrometry(UHPLC-QEMS), and selected the serum containing YGP high-dose group to follow-up experiments. To stimulated KGN with 200 μmol·L~(-1) H_2O_2to establish an oxidative damage model, which was divided into normal group, model group, low-, medium-, and high-dose of YGP groups, and the efficacy was further verified on the basis of silencing or overexpressing serine protease inhibitor(Serpina3k), further validating the efficacy based on the silencing or overexpression of Serpina3k. TUNEL staining was used to detect cell apoptosis,enzyme-linked immunosorbent assay(ELISA) was employed to measure the secretion levels of estradiol(E_2) and 17β-E_2 in KGN, and Western blot was utilized to assess the expression of Serpina3k and proteins related to the Keap1/Nrf2 signaling pathway. The results show that compared to the model group, each dose group of YGP not only significantly reduces granulocyte apoptosis and upregulates the secretion levels of E_2 and 17β-E_2, but also significantly upregulates Serpina3k and Nrf2 pathway. Further research has found that overexpression of Serpina3k not only enhances the therapeutic effect of YGP but also increases the expression of Nrf2 and inhibits the expression of Keap1. Conversely, interfering with Serpina3k partially reverses the therapeutic effect of YGP, while also partially. The results indicate that the mechanism by which YGP improves oxidative stress in KGN may be related to its upregulation of Serpina3k expression, which affects the conduction of the Keap1/Nrf2 signaling pathway. This study reveals the mechanism by which YGP protects granular cells, providing a certain theoretical basis for its clinical application.
NF-E2-Related Factor 2/genetics* ; Kelch-Like ECH-Associated Protein 1/genetics* ; Humans ; Female ; Signal Transduction/drug effects* ; Oxidative Stress/drug effects* ; Granulosa Cells/cytology* ; Drugs, Chinese Herbal/pharmacology* ; Apoptosis/drug effects* ; Serpins/genetics*

Background: The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies. Methods: MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function. Results: Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores. Conclusion Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.

Background Attention-deficit hyperactivity disorder (ADHD) is a common neurodevelopmental and behavioral disorder in children, often diagnosed during school age. The etiology of ADHD remains unclear; however, existing studies suggest that environmental factors, such as exposure to triclosan (TCS), may be associated with the occurrence of ADHD-like symptoms in offspring. Nevertheless, relevant research in China remains limited. Objective To investigate the impact of early pregnancy TCS exposure on ADHD-like symptoms in 7-year-old children. Methods This study was based on the Shanghai Birth Cohort (SBC) and included 662 mother-child pairs. TCS concentrations in early pregnancy urine samples were measured using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Demographic information was collected via questionnaires and medical record abstraction. ADHD-like symptoms in 7-year-old children were first assessed using the Strengths and Difficulties Questionnaire (SDQ). Further differentiation of ADHD-like symptom subtypes (inattentive and hyperactive/impulsive) was conducted using the SNAP-IV, a clinically validated ADHD screening tool. Negative binomial regression models were applied to evaluate the associations between prenatal TCS exposure and hyperactive behavior (SDQ assessment) as well as ADHD-like symptom subtypes (SNAP-IV assessment) in 7-year-old children. Results The positive rate of TCS in early pregnancy urine samples was 91.39%, with median concentrations of 0.69 μg·L⁻¹ and 0.63 μg·g⁻¹ before and after the creatinine adjustment, respectively. The modeling results indicated that prenatal TCS exposure was associated with an increased risk of hyperactive symptoms (SDQ assessment) in 7-year-old children (RR=1.04, 95%CI: 1.02, 1.06); the stratified analyses by children sex revealed similar effects for both boys (RR=1.04, 95%CI: 1.02, 1.07) and girls (RR=1.04, 95%CI: 1.01, 1.07). Further analysis of ADHD-like symptom subtypes showed that prenatal TCS exposure increased the risk of inattentive symptoms (RR=1.03, 95%CI: 1.00, 1.05); the sex-stratified analyses indicated associations between TCS exposure and inattentive symptoms (RR=1.03, 95%CI: 1.00, 1.07) as well as hyperactive/impulsive symptoms (RR=1.04, 95%CI: 1.01, 1.08) in girls. Conclusion Prenatal TCS exposure is associated with an increased risk of ADHD-like symptoms in 7-year-old children, primarily contributing to the risk of the inattention subtype. The impact is more pronounced in girls.

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

The renin-angiotensin-aldosterone system (RAAS) is crucial for regulating blood pressure and maintaining fluid balance, while clock genes are essential for sustaining biological rhythms and regulating metabolism. There exists a complex interplay between RAAS and clock genes that may significantly contribute to the development of various cardiovascular and metabolic diseases. Although current literature has identified correlations between these two systems, the specific mechanisms of their interaction remain unclear. Moreover, the interaction patterns under different physiological and pathological conditions need further investigation. This review summarizes the synergistic roles of the RAAS and clock genes in cardiovascular diseases, explores their molecular mechanisms and pathophysiological connections, discusses the application of chronotherapy, and highlights potential future research directions, aiming to provide novel insights for the prevention and treatment of related diseases.
Humans ; Renin-Angiotensin System/genetics* ; Cardiovascular Diseases/genetics* ; CLOCK Proteins/physiology* ; Animals

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*