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

OBJECTIVE: To investigate the molecular mechanism and explore blood transfusion strategies for a proband exhibiting the JK (a-b-) phenotype and anti-JK³ high frequency antigen antibody and her eight family members. METHODS: The Kidd blood phenotype and irregular antibodies in a family were identified by serologic tests. Exon 4-11 and intron region of SLC14A1 gene were sequenced by Sanger method. RESULTS: The combination of the gene JK*B (c.499A>G,c.512G>A,c.588A>G) and gene JK*B (c.342-1G>A,588A>G) in this family were considered to result in the JK (a-b-) phenotype in two members. The members carrying gene JK*A(c.130G>A,588A>G) all present serological JK^a+W. Members carrying gene JK*B (c.499A>G,c.588A>G) all present serological JK^b+W, which has not been previously reported to cause antigenic weakening. The proband with JK (a-b-) phenotype produced anti-JK³ antibodies, the hospital formulated a number of blood preparation strategies for the patient and she was discharged after recovery. CONCLUSION In this study, the molecular mechanism of JK (a-b-) in this family was identified, the transfusion strategy of rare blood group was established in our institution preliminary, and the necessity of establishing a rare blood group bank was revealed in this region. It is suggested that JK*B (c.499A>G,c.588A>G) may be a new genetic pattern leading to the weakening of Kidd antigenicity, which lays a foundation for the study of population genetics.
Humans ; Blood Transfusion ; Female ; Kidd Blood-Group System/genetics* ; Phenotype ; Pedigree

OBJECTIVES: To explore the underlying pharmacological mechanisms and its potential effects of Chinese medicine herbal formula Sini Powder (SNP) on hepatocellular carcinoma (HCC). METHODS: The active components of SNP and their in vivo distribution were identified using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Construction of component-target-disease networks, protein-protein interaction network, Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and molecular docking were employed to analyze the active components and anti-HCC mechanisms of SNP. Cell viability assay and wound healing assay were utilized to confirm the effect of SNP-containing serum (2.5%, 5.0%, 10%, 20%, and 40%), isoprenaline or propranolol (both 10, 100, and 1,000 µ mol/L) on proliferation and migration of HepG 2 or Huh7 cells. Meanwhile, the effect of isoprenaline or propranolol on the β 2 adrenergic receptor (ADRB2) mRNA expression on HepG2 cells were measured by real-time quantitative reverse transcription (RT-qPCR). Mice with subcutaneous tumors were either subjected to chronic restraint stress (CRS) followed by SNP administration (364 mg/mL) or directly treated with SNP (364 mg/mL). These two parallel experiments were performed to validate the effects of SNP on stress responses. Stress-related proteins and hormones were quantified using RT-qPCR, enzyme-linked immunosorbent assay, and immunohistochemistry. Metagenomic sequencing was performed to confirm the influence of SNP on the gut microbiota in the tumor-bearing CRS mice. RESULTS: The distribution of the 12 active components of SNP was confirmed in various tissues and feces. Network pharmacology analysis confirmed the anti-HCC effects of the 5 active components. The potential anti-HCC mechanisms of SNP may involve the epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase Src (SRC) and signal transducer and activator of transcription 3 (STAT3) pathways. SNP-containing serum inhibited the proliferation of HepG2 and Huh7 cells at concentrations of 2.5% and 5.0%, respectively, after 24 h of treatment. Furthermore, SNP suppressed tumor progression in tumor-bearing mice exposed to CRS. SNP treatment also downregulated the expressions of stress-related proteins and pro-inflammatory cytokines, primarily by modulating the gut microbiota. Specifically, the abundance of Alistipes and Prevotella, which belong to the phylum Bacteroidetes, increased in the SNP-treated group, whereas Lachnospira, in the phylum Firmicutes, decreased. CONCLUSION SNP can combat HCC by alleviating stress responses through the regulation of gut microbiota.
Animals ; Gastrointestinal Microbiome/drug effects* ; Liver Neoplasms/microbiology* ; Carcinoma, Hepatocellular/microbiology* ; Humans ; Drugs, Chinese Herbal/therapeutic use* ; Powders ; Cell Proliferation/drug effects* ; Mice ; Molecular Docking Simulation ; Cell Line, Tumor ; Hep G2 Cells ; Receptors, Adrenergic, beta-2/genetics* ; Stress, Physiological/drug effects* ; Cell Movement/drug effects* ; Male ; Protein Interaction Maps/drug effects* ; Cell Survival/drug effects* ; Proto-Oncogene Mas

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.