Background Sunshine duration is closely associated with population mental health and emotional states, although its relationship with mental and behavioral disorders (MBD) remains insufficiently studied. Objective To analyze the effect of sunshine duration on hospital admissions for MBD in Zigong City, Sichuan Province. Methods Hospital admission records for MBD from 10 medical institutions, meteorological data, and ambient air pollutant concentrations were collected in Zigong City from January 1, 2019 to December 31, 2024. A distributed lag non-linear model (DLNM) was employed to calculate single-day and cumulative lag effects of different sunshine duration exposures—0 h (P₀, P₅, P₂₅), 6 h (P₇₅), and 10.4 h (P₉₅)—on hospitalization risks for MBD, stratified by diagnostic category, sex, and age groups. Results This study analyzed 36597 hospital admissions for MBD in Zigong City. The exposure-response curve for sunshine duration at lag 0 d exhibited an inverted N-shaped pattern, with minimum relative risk (RR) of hospitalizations observed at 14 h sunshine duration. The immediate effects of different levels of sunshine duration on the hospitalization risk for MBD, schizophrenia, schizotypal and delusional disorders (SSDD), and neurotic, stress-related and somatoform disorders (NSSD) were significant, with the cumulative effect peaking at lags 12–13 days. For extremely short sunshine duration 0 h, the maximum relative risk (RR) values (with 95% confidence intervals, 95%CI) of hospitalization risk were 1.209 (1.001, 1.459) at lag 1 d for SSDD patients and 1.398 (1.133, 1.724) at lag 0 d for NSSD patients, respectively. The cumulative effect on hospitalization risk induced by short sunshine duration 6 h was higher than that induced by extremely short sunshine duration 0 h and long sunshine duration 10.4 h. Among populations stratified by gender and age, male patients and those aged over 70 years had higher hospitalization risks. For short sunshine duration 6 h, the cumulative RR (CRR) value (95%CI) of hospitalization risk for male MBD patients was 3.373 (1.362, 8.358) at cumulative lag 0–12 d, which was higher than that for female patients [2.943 (1.471, 5.889) at cumulative lag 0–13 d]. The population aged over 70 years was more sensitive to single-day and cumulative lag effects on hospitalization risk than other age groups. For short sunshine duration 6 h, the RR and CRR values (95%CI) of single-day and cumulative lag effects on hospitalization risk were 1.336 (1.002, 1.783) at lag 0 day and 5.085 (1.680, 15.392) at cumulative lag 0–12 d, respectively. At lag 13 d, long sunshine duration 10.4 h exposure was associated with depression hospitalizations in patients <20 years with RR=1.127 (95%CI: 1.002, 1.270). Conclusion When the daily sunshine duration is less than 14 h, it will increase the hospitalization risk of MBD in the population to varying degrees, with both single-day and cumulative lag effects. It is recommended that the public, especially vulnerable groups such as people with MBD aged 70 years and above and those with depression under 20 years, strengthen health protection to reduce the health risks caused by changes in sunshine.

ObjectiveTo investigate the effect of Danggui Shaoyaosan on the expression of Toll-like receptor 4/nuclear factor-kappa B p65/NOD-like receptor protein 3 （TLR4/NF-κB p65/NLRP3） signaling pathway in the renal tissues of db/db mice with spontaneous diabetes， and to explore the potential mechanism by which Danggui Shaoyaosan alleviates inflammation in diabetic kidney disease （DKD）. MethodsThirty db/db mice were divided into five groups： A model group， Danggui Shaoyaosan low- （16.77 g·kg^-1·d^-1）， medium- （33.54 g·kg^-1·d^-1）， and high-dose （67.08 g·kg^-1·d^-1） intervention groups， as well as an irbesartan group （0.025 g·kg^-1·d^-1） by the random number table method， with 6 mice in each group. Additionally， 6 db/m mice were assigned to the normal group. After 8 weeks of intervention， the following parameters were determined by corresponding methods： body weight， fasting blood glucose （FBG）， 24-hour urinary protein （24 h-UTP）， and serum creatinine （SCr） levels， renal histopathological analysis by hematoxylin-eosin （HE） staining， Masson staining， and periodic acid-Schiff （PAS） staining， the protein and mRNA expression levels of TLR4， NF-κB p65， NLRP3， tumor necrosis factor-alpha （TNF-α）， interleukin-1β （IL-1β）， interleukin-6 （IL-6）， interleukin-10 （IL-10）， and interleukin-18 （IL-18） by Western blot and Real-time quantitative polymerase chain reaction （Real-time PCR）， as well as TLR4， NF-κB p65， and NLRP3 protein expression in renal tissues by immunohistochemistry （IHC）. ResultsCompared with the normal group， the model group exhibited increased body weight， FBG， 24 h-UTP， and SCr levels （P<0.05）； disordered renal structure， thickened basement membrane， and interstitial inflammatory cell infiltration， elevated TLR4， NF-κB p65， NLRP3， TNF-α， IL-1β， IL-6， and IL-18 expression； as well as decreased IL-10 expression （P<0.05）. Compared with the model group， these pathological changes and biochemical abnormalities were reversed in the medicine intervention groups to varying degrees （P<0.05）. ConclusionDanggui Shaoyaosan may delay DKD progression by alleviating renal inflammatory response and reducing urinary protein excretion via modulating the TLR4/NF-κB p65/NLRP3 signaling pathway.

Objective To investigate the post-discharge exercise behavior and factors influencing moderate to vigorous intensity physical activity (MVPA) in patients undergoing lung surgery. Methods A total of 2874 patients from the large prospective, observational perioperative lung symptom study cohort (CN-PRO-Lung 3) in the Department of Thoracic Surgery at Sichuan Cancer Hospital between April 7, 2021, and January 31, 2024, were selected as the survey subjects. A survey was conducted using the Investigation of Exercise Behavior after Lung Surgery questionnaire and the International Physical Activity Questionnaire-Short Form (IPAQ-SF) among patients who underwent lung surgery. Binary logistic regression was used to analyze the factors influencing patients’ engagement in MVPA. Results A total of 702 patients were surveyed, including 252 males and 450 females, with an average age of (52.4±10.2) years. Patients with lung cancer accounted for 85.9%. Only 36.0% of the patients had regular exercise habits, while 42.3% did not engage in any physical activity. The three main barriers for postoperative exercise were physical discomfort (pain, coughing, shortness of breath, etc, 54.7%), lack of professional guidance (41.7%), and concerns about the surgical wound (28.9%). The proportions of patients engaging in vigorous, moderate, and low-intensity physical activity were 5.7%, 28.2%, and 66.1%, respectively. Multivariate analysis showed that patients with a personal annual income ≥50000 yuan (OR=1.52, 95%CI 1.01-2.29, P=0.044), high school education or above (OR=1.92, 95%CI 1.33-2.76, P<0.001), and lobectomy (OR=1.44, 95%CI 1.02-2.03, P=0.037) engaged in more MVPA. Conclusion Patients undergoing lung surgery have inadequate physical activity after discharge, particularly lacking in MVPA. Patients with higher income, higher educational levels, and lobectomy are more frequently engaged in MVPA. Measures such as symptom control, providing exercise guidance, and enhancing education on wound care may potentially improve the inadequate physical activity in lung surgery patients after discharge.

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 exosome-like nanovesicles (PELNs), characterized by a natural lipid bilayer membrane, have rapidly emerged as a prominent research frontier in medicine owing to their unique biological properties and robust therapeutic potential. This review comprehensively examines the biological profiles, mechanistic functions, and recent engineering advancements of PELNs. In terms of composition, PELNs are uniquely enriched in plant-specific glycolipids, phosphatidylserine, secondary metabolites, and highly stable 2'-O-methylated miRNAs. This distinct molecular makeup endows them with exceptional biocompatibility, negligible immunogenicity, and the capacity for cross-species molecular communication. Mechanistically, PELNs demonstrate profound anti-inflammatory efficacy by suppressing the NF-κB and NLRP3 inflammasome pathways. They also serve as potent immune modulators, driving macrophage M1/M2 polarization and regulating T cell activity. Additionally, PELNs exhibit promising antitumor capabilities, targeting malignancies via reactive oxygen species (ROS) induction, TRAIL pathway activation, and tumor microenvironment remodeling. Crucially, the plant miRNAs encapsulated within PELNs remain highly stable in the gastrointestinal tract, allowing them to selectively alter gene expression in specific gut microbiota communities. This interaction deeply influences host immunity and metabolism, highlighting the vital role in cross-species regulation. Advancements in bioengineering have further expanded the clinical utility of PELNs. Targeted delivery efficiency can be significantly amplified via surface functionalization (e.g., folate and RGD sequences) and state-of-the-art drug loading technologies such as sonication and electroporation. Consequently, engineered PELNs surpass traditional synthetic nanocarriers in penetrating natural physiological barriers, particularly for oral and transdermal drug administration. Despite these advantages, clinical translation is currently hindered by the lack of standardized isolation protocols, challenges in scalable manufacturing, and the need for robust quality control frameworks. Looking forward, the integration of multi-omics approaches and AI-driven “molecular fingerprinting”—coupled with the design of synthetic biomimetic vesicles—will be instrumental in overcoming these bottlenecks, ultimately establishing PELNs as a next-generation platform for precision medicine and targeted nanotherapeutic delivery.

OBJECTIVE To provide standardized guidance for the homogenization construction and management of pharmaceutical care in urban medical groups. METHODS This consensus was jointly initiated by the Therapeutic Drug Monitoring Professional Committee of the Chinese Pharmacological Society and the Expert Committee on Precision Clinical Medication of the Guangdong Pharmaceutical Association. Led by Guangzhou Red Cross Hospital， a drafting group of 7 members and an expert group of 36 members were organized. The outline of the Expert Consensus on Homogeneous Construction and Management of Pharmaceutical Care in Urban Medical Groups （hereinafter referred to as the “Consensus”） was discussed and finalized using the nominal group technique， and a preliminary draft was formed. The Delphi method was used for online c orrespondence review， and 12 external experts were invited for evaluation. After analyzing and revising expert opinions， the final Consensus was formed. RESULTS &CONCLUSIONS This Consensus defines the position setting and appointment procedures for the chief pharmacist， and establishes a three-tier professional guidance network of “chief pharmacist-regional/specialist pharmacist-pharmaceutical liaison of member institutions”. It formulates unified management standards for the drug supply catalog， establishes a full-process homogenization mechanism for prescription review， prescription commentation and comprehensive pharmaceutical care， and specifies the core functions and performance requirements of the prescription review system. It also supports by long-term mechanisms including cost allocation and performance assessment. This consensus can serve as a systematic reference for the homogeneous construction and management of pharmaceutical care systems in urban medical groups.

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.

This study explores the antiviral effects of Lopinavir on porcine hemagglutinating en-cephalomyelitis virus(PHEV)in vitro and in vivo.Using PHEV-infected N2a cells as an in vitro experimental model,the impact of varying concentrations of Lopinavir on PHEV replication was analyzed through Western blot and qRT-PCR techniques.The results demonstrated that Lopinavir was beneficial to PHEV replication at low-concentration,but as the concentration increased,Lopi-navir began to exert an inhibitory effect,with the most pronounced effect observed at a concentra-tion of 8 μmol/L.PHEV-infected 3-week-old male BALB/c mice were utilized in vivo experi-ments,with Lopinavir(10 mg/kg)administered intragastrically three days post-infection.Follow-ing the onset of illness in the control group,all mice were euthanized,and brain tissues were col-lected for histopathological examination.The findings indicated that Lopinavir significantly reduced the distribution of PHEV and ameliorated the pathological damage in brain tissue,and prolonged the survival time of the mice.In conclusion,Lopinavir exhibits an antiviral effect against PHEV both in vitro and in vivo,offering a theoretical basis for the prevention and treatment of PHEV in-fections in clinical practice.

OBJECTIVE: To investigate the clinical characteristics, curative effect and prognostic factors of patients with multiple myeloma (MM) complicated with light chain myocardial amyloidosis (AL-CA). METHODS: The data of 38 patients diagnosed with MM complicated with AL-CA in our hospital from January 2018 to December 2023 were retrospectively analyzed, and the data were comprehensively screened by multiple methods such as positive two-dimensional spot tracking echocardiography (2D-STE). Survival analysis was performed using the Kaplan-Meier method. Cox regression models were used to screen for independent prognostic factors. RESULTS: Among the 38 MM patients with AL-CA, 23 were male and 15 were female, with a median age of 60(50,75) years. The 1-year survival rate was 71.05%. Patients who underwent transplantation had significantly better survival outcomes than those who did not (P < 0.01). Additionally, the median survival time of patients with all-negative FISH results at the first visit was statistically different compared to patients with other mutations (P < 0.05). Multivariate Cox regression analysis showed that all negative FISH results at the first visit and the absence of autologous hematopoietic stem cell transplantation (ASCT) were not independent risk factor for the prognosis of patients with MM and AL-CA (P >0.05). CONCLUSION ASCT may improve the prognosis of MM patients with AL-CA, and negative FISH results may indicate poor prognosis, but the results still need to be verified by larger samples.
Humans ; Multiple Myeloma/complications* ; Retrospective Studies ; Aged ; Female ; Male ; Middle Aged ; Prognosis ; Hematopoietic Stem Cell Transplantation ; Amyloidosis/complications* ; Survival Rate ; Proportional Hazards Models

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged