Objective To understand the antibody levels of diphtheria and tetanus among healthy population in Shanghai Pudong New Area, and to provide a scientific basis for improving the vaccine immunization strategy. Methods Random sampling was used to select healthy people of all ages in 16 communities in Shanghai Pudong New Area from 2018 to 2024, and serum samples were collected and tested for serum anti-diphtheria and tetanus toxin IgG antibodies by enzyme-linked immunosorbent assay (ELISA) method to analyze the antibody positivity rate (≥0.1 IU/ml) and the geometric mean concentration (GMC) of antibodies. Results A total of 3 312 serum samples were included, with a male-to-female ratio of 0.76:1, and 53.77% were local residents. The seropositivity rates and geometric mean concentrations (GMC) of both diphtheria and tetanus antibodies generally declined with increasing age, but exhibited a transient rebound in the 7y-. A total of 1 175 individuals (35.48%) were seropositive for diphtheria, with a GMC of 0.054 IU/mL. For tetanus, 988 individuals (29.83%) were seropositive, with a GMC of 0.033 IU/mL. Significant differences in seropositivity rates (χ²_diphtheria=950.005,χ²_tetanus=1 324.393) and GMC (H_diphtheria=1027.160,H_tetanus=1 142.007) were observed among different age groups (P<0.001). Significant differences in seropositivity rates (χ²_diphtheria=950.005,χ²_tetanus=1324.393) and GMC (H_diphtheria=1027.160,H_tetanus=1142.007) were also found across different years (P<0.001). Conclusion The prevalence of diphtheria and tetanus antibodies in the healthy population of Pudong New Area is relatively low, particularly among adults over 20 years of age with inadequate immunization. This underscores the need to reinforce the National Immunization Program (NIP) vaccine specifications for children under 6 years of age and implement an immunization strategy for adolescents or adults against diphtheria and tetanus.

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

Delirium is a common cause and complication of hospitalization in the elderly and is associated with higher risk of future dementia and progression of existing dementia, of which 70% is Alzheimer's disease (AD). AD and delirium, which are known to be aggravated by one another, represent significant societal challenges, especially in light of the absence of effective treatments. The intricate biological mechanisms have led to numerous clinical trial setbacks and likely contribute to the limited efficacy of existing therapeutics. Artificial intelligence (AI) presents a promising avenue for overcoming these hurdles by deploying algorithms to uncover hidden patterns across diverse data types. This review explores the pivotal role of AI in revolutionizing drug discovery for AD and delirium from target identification to the development of small molecule and protein-based therapies. Recent advances in deep learning, particularly in accurate protein structure prediction, are facilitating novel approaches to drug design and expediting the discovery pipeline for biological and small molecule therapeutics. This review concludes with an appraisal of current achievements and limitations, and touches on prospects for the use of AI in advancing drug discovery in AD and delirium, emphasizing its transformative potential in addressing these two and possibly other neurodegenerative conditions.

OBJECTIVE: To investigate the relationship between the trajectories of serum potassium changes after intensive care unit (ICU) admission and 30-day death risk in patients with sepsis. METHODS: A retrospective cohort study was conducted, including adult patients with sepsis admitted to the comprehensive ICU, medical intensive care unit (MICU) and emergency intensive care unit (EICU) of Guizhou Medical University Affiliated Hospital from January 2020 to January 2024. The patients who had a minimum of 5 days' hospitalisation in the ICU and who had at least 7 consecutive days of the serum potassium measurements were classified into five trajectories groups according to group-based trajectory modelling (GBTM) using SAS software. This was based on tendency changes in serum potassium levels in patients after admission to the ICU, which was categorized as follows: slowly increased from a low level group, slowly increased from a medium level of normal range group, slowly decreased from a medium level of normal range group, slowly decreased from a high level group, and slowly increased from a high level of normal range group. The patient's gender, age, medical history, and white blood cell count (WBC), platelet count (PLT), procalcitonin (PCT), activated partial thromboplastin time (APTT), prothrombin time (PT), blood sodium, and serum creatinine (SCr) at the time of admission to the ICU were collected. At the same time, the patient's worst sequential organ failure assessment (SOFA) score within 24 hours of admission to the ICU, length of ICU stay, and 30-day outcome were record. The differences in clinical data among different groups of patients were compared. The 30-day cumulative survival rates of the various serum potassium trajectories were plotted using Kaplan-Meier survival curves, the groups were then compared using the Log-Rank test. A multivariate Cox proportional risk regression analysis was developed to evaluate the independent effect of serum potassium trajectory on 30-day death risk. RESULTS: Finally, 342 ICU sepsis patients were enrolled, of which 42 patients in the slowly increased from a low level group (12.28%), 127 patients in the slowly increased from a medium level of normal range group (37.14%), 118 patients in the slowly decreased from a medium level of normal range group (34.50%), 28 patients in the slowly decreased from a high level group (8.19%), and 27 patients in the slowly increased from a high level of normal range group (7.89%). Except for age and APTT differences, there were no statistically significant differences in other clinical characteristics among the patients in the different serum potassium trajectories groups. Kaplan-Meier survival curves showed that there was statistically significant difference in the 30-day cumulative survival rate among the patients in the different serum potassium trajectories groups (Log-Rank test: χ² = 14.696, P = 0.005), with the lowest in the slowly increased from a high level of normal range group (39.3%). Multivariate Cox proportional risk regression analysis showed that the patients with the serum potassium trajectory of slowly increased from a high level of normal range had the highest 30-day death risk [hazard ratio (HR) = 2.341, 95% confidence interval (95%CI) was 1.049-5.226, P = 0.038]. This association persisted after adjustment for variables such as gender, age, medical history, SOFA score, WBC, PLT, PCT, APTT, PT, blood sodium, and SCr (HR = 3.058, 95%CI was 1.249-7.488, P = 0.014). CONCLUSION Compared with the patients whose serum potassium fluctuated within the normal range, the sepsis patients in the ICU with a serum potassium trajectory that slowly increased from a high level of normal range had a significantly higher 30-day death risk.
Humans ; Retrospective Studies ; Intensive Care Units ; Sepsis/blood* ; Potassium/blood* ; Male ; Female ; Middle Aged ; Aged ; Risk Factors ; Hospital Mortality ; Prognosis

BACKGROUND: A growing body of research is exploring the role of antioxidant and anti-inflammatory dietary supplements in the treatment of osteoarthritis, highlighting an increasing emphasis on non-pharmacological interventions. Although more patients are turning to supplements to manage osteoarthritis, their actual effectiveness remains uncertain. OBJECTIVE: This study aims to provide a comprehensive evaluation of the available evidence concerning the efficacy of various dietary supplements in osteoarthritis treatment. SEARCH STRATEGY: We searched PubMed, Embase, Cochrane Library and Web of Science for studies on the use of various dietary supplements in the treatment of osteoarthritis from the creation of each database until Jan 20, 2025. INCLUSION CRITERIA: (1) Research object: osteoarthritis. (2) Intervention measures: patients in the treatment group received dietary supplements, while the control group received placebos. (3) Research type: randomized controlled trials (RCTs). DATA EXTRACTION AND ANALYSIS: Two researchers independently examined the literature and retrieved data based on predefined criteria. The information gathered included the first author, year of publication, sample size, participant demographics, length of the follow-up period, intervention and control measures, and inclusion indications. RCTs comparing dietary supplements to placebo with the pain and function subscales of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) among patients with osteoarthritis were included. The optimal dietary supplement was identified based on the total ranking by summing the surface under the cumulative ranking curve (SUCRA) of these two scores. Furthermore, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was used to confirm the quality of the evidence. RESULTS: Overall, 23 studies covering 21 dietary supplements and involving 2455 participants met the inclusion criteria. In the WOMAC pain score, the SUCRA of passion fruit peel extract was 91% (mean difference [MD]: -9.2; 95% confidence interval [CI]: [-16.0, -2.3]), followed by methylsulfonylmethane (89%), undenatured type II collagen (87%), collagen (84%), and Lanconone (82%). The SUCRA (99%) of passion fruit peel extract (MD: -41.0; 95% CI: [-66.0, -16.0]) ranked first in terms of the WOMAC function score, followed by Lanconone (95%), collagen (86%), ParActin (84%), and Lactobacillus casei strain Shirota (83%). The top three total rankings are passion fruit peel extract (95.0%), Lanconone (88.5%), and collagen (85.0%). However, the GRADE revealed low evidence quality. CONCLUSION Passion fruit peel extract was the best supplement for improving WOMAC pain and function scores in patients with osteoarthritis, followed by Lanconone and collagen. However, further large-scale, well designed RCTs are required to substantiate these promising findings. Please cite this article as: Chen CS, Wen L, Yang F, Deng YC, Ji JH, Chen RJ, Chen Z, Chen G, Gu JY. Effects of dietary supplements on patients with osteoarthritis: A systematic review and network meta-analysis. J Integr Med. 2025; 23(4): 357-369.
Humans ; Dietary Supplements ; Osteoarthritis/drug therapy* ; Randomized Controlled Trials as Topic

Objective: To investigate the health-related quality of life and its influencing factors in elderly patients with metabolic syndrome (MS), so as to provide the evidence for improving health-related quality of life in older adults with chronic diseases. Methods: In 2021, elderly MS patients aged ≥60 years from four districts in Nanjing City were selected as the study subjects using a multi-stage random sampling method. Data on social demographic information, lifestyle, disease history and blood biochemical indicators were collected through questionnaire surveys, physical examination and laboratory tests. Health utility value and EuroQol Visual Analog Scale (EQ-VAS) score were assessed using the EuroQol 5-dimension 3-level questionnaire. Factors affecting health-related quality of life were identified with the Tobit regression model and multiple linear regression model. Results: A total of 3 378 elderly MS patients were included, with a median age of 67.00 (interquartile range, 7.00) years. There were 1 558 males (46.12%) and 1 820 females (53.88%). The median (interquartile range) of health utility value and EQ-VAS score were 1.00 (0.03) and 80.00 (15.00). Tobit regression and multiple linear regression analysis showed that gender (female, β=-0.034), education level (middle school, β=0.024; junior college and above, β=0.046), marital status (married, β=0.014), physical activity (sufficient, β=0.013), vegetable intake (meet standard, β=-0.009) and fruit intake (meet standard, β=0.016) were the influencing factors of health utility value. Residence (urban area, β=1.933) and alcohol consumption (yes, β=1.761) were influencing factors of EQ-VAS score. Age, cardiovascular and cerebrovascular diseases, malignant tumors and chronic respiratory diseases were the influencing factors of health utility value and EQ-VAS score. Conclusion Age, sex, marital status, residence, lifestyle and disease are mainly associatied with the health-related quality of life in elderly MS patients.

The paper explores the etiology and pathogenesis of chronic fatigue syndrome (CFS), and its diagnosis and treatment with acupuncture and moxibustion based on "body-qi-mind trinity life view". It is believed that CFS refers to the comorbidity of body, qi and mind. In the disease, spleen deficiency in transportation and transformation is the root, resulting in malnutrition of muscles; liver qi stagnation is the pivot, causing dysfunction of three jiao; and disharmony between heart and kidney is crucial, leading to dysfunction of mind. The strategy of treatment with acupuncture and moxibustion is proposed, "relieving general pain of the body as the top priority, regulating qi is the pivot, and housing the mind is the foundation". For relieving general pain of the body, acupuncture is applied to Sanyinjiao (SP6) and Zusanli (ST36) that is the essential prescription to relieve muscular pain. For regulating qi, Waiguan (TE5) and Gongsun (SP4) are selected to promote the pivot of shaoyang and regulate qi movement of three jiao. For housing the mind, acupuncture is delivered at Shenmen (HT7) and moxibustion is applied to Yongquan (KI1), Gaohuang (BL43) and Baihui (GV20) to harmonize the heart and kidney and tranquilize the mind. This intervention mode, i.e. harmonizing among body, qi and mind, and promoting the circulation of qi and blood, is conductive to restoring the body, qi and mind. It provides a new idea to clinical diagnosis and treatment of CFS with acupuncture and moxibustion.
Humans ; Moxibustion ; Fatigue Syndrome, Chronic/physiopathology* ; Acupuncture Therapy ; Qi ; Acupuncture Points ; Male ; Female

With the increasing utilization of cancer therapy, the incidence of lung injury associated with these treatments continues to rise. The recognition of pulmonary toxicity related to cancer therapy has become increasingly critical, for which interstitial lung disease (ILD) is a common cause of mortality. Cancer therapy-related ILD (CT-ILD) can result from a variety of treatments including chemotherapy, targeted therapy, immune checkpoint inhibitors, antibody-drug conjugates, and radiotherapy. CT-ILD may progress rapidly and even be life-threatening; therefore, prompt diagnosis and timely treatment are crucial for effective management. This review aims to provide valuable information on the risk factors associated with CT-ILD; elucidate its underlying mechanisms; discuss its clinical features, imaging, and histological manifestations; and emphasize the clinical-related views of its diagnosis. In addition, this review provides an overview of grading, typing, and staging treatment strategies used for the management of CT-ILD.
Humans ; Lung Diseases, Interstitial/diagnosis* ; Neoplasms/therapy* ; Risk Factors ; Immune Checkpoint Inhibitors/adverse effects* ; Antineoplastic Agents/therapeutic use*

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures