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

The chemical components of Carthami Flos were investigated by using macroporous resin, silica gel column chromatography, reversed-phase octadecylsilane(ODS) column chromatography, Sephadex LH-20, and semi-preparative high-performance liquid chromatography(HPLC). The planar structures of the compounds were established based on their physicochemical properties and ultraviolet-visible(UV-Vis), infrared(IR), high-resolution electrospray ionization mass spectrometry(HR-ESI-MS), and nuclear magnetic resonance(NMR) spectroscopic technology. The absolute configurations were determined by comparing the calculated and experimental electronic circular dichroism(ECD). Six flavonoid C-glycosides were isolated from the 30% ethanol elution fraction of macroporous resin obtained from the 95% ethanol extract of Carthami Flos, and identified as saffloquinoside F(1), 5-hydroxysaffloneoside(2), iso-5-hydroxysaffloneoside(3), isosafflomin C(4), safflomin C(5), and vicenin 2(6). Among these, the compounds 1 to 3 were new chalcone C-glycosides. The compounds 1, 2, 4, and 5 could significantly increase the viability of H9c2 cardiomyocytes damaged by oxygen-glucose deprivation/reoxygenation(OGD/R) at a concentration of 50 μmol·L~(-1), showing their good cardioprotective activity.
Glycosides/pharmacology* ; Flowers/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Carthamus tinctorius/chemistry* ; Chalcones/pharmacology* ; Animals

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

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.

Patients suffering from nerve injury often experience exacerbated pain responses and complain of memory deficits. The dorsal hippocampus (dHPC), a well-defined region responsible for learning and memory, displays maladaptive plasticity upon injury, which is assumed to underlie pain hypersensitivity and cognitive deficits. However, much attention has thus far been paid to intracellular mechanisms of plasticity rather than extracellular alterations that might trigger and facilitate intracellular changes. Emerging evidence has shown that nerve injury alters the microarchitecture of the extracellular matrix (ECM) and decreases ECM rigidity in the dHPC. Despite this, it remains elusive which element of the ECM in the dHPC is affected and how it contributes to neuropathic pain and comorbid cognitive deficits. Laminin, a key element of the ECM, consists of α-, β-, and γ-chains and has been implicated in several pathophysiological processes. Here, we showed that peripheral nerve injury downregulates laminin β1 (LAMB1) in the dHPC. Silencing of hippocampal LAMB1 exacerbates pain sensitivity and induces cognitive dysfunction. Further mechanistic analysis revealed that loss of hippocampal LAMB1 causes dysregulated Src/NR2A signaling cascades via interaction with integrin β1, leading to decreased Ca²⁺ levels in pyramidal neurons, which in turn orchestrates structural and functional plasticity and eventually results in exaggerated pain responses and cognitive deficits. In this study, we shed new light on the functional capability of hippocampal ECM LAMB1 in the modulation of neuropathic pain and comorbid cognitive deficits, and reveal a mechanism that conveys extracellular alterations to intracellular plasticity. Moreover, we identified hippocampal LAMB1/integrin β1 signaling as a potential therapeutic target for the treatment of neuropathic pain and related memory loss.
Animals ; Laminin/genetics* ; Hippocampus/metabolism* ; Neuralgia/metabolism* ; Cognitive Dysfunction/etiology* ; Male ; Peripheral Nerve Injuries/metabolism* ; Extracellular Matrix/metabolism* ; Integrin beta1/metabolism* ; Pyramidal Cells/metabolism* ; Signal Transduction

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

OBJECTIVE: We aimed to investigate the patterns of fasting blood glucose (FBG) trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers. METHODS: The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort (TGOC) between 2017 and 2022. A group-based trajectory model was used to identify the FBG trajectories. Environmental risk scores (ERS) were constructed using regression coefficients from the occupational hazard model as weights. Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories. RESULTS: FBG trajectories were categorized into three groups. An association was observed between high temperature, noise exposure, and FBG trajectory ( P < 0.05). Using the first quartile group of ERS1 as a reference, the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90 and 2.21 times, respectively (odds ratio [ OR] = 1.90, 95% confidence interval [ CI]: 1.17-3.10; OR = 2.21, 95% CI: 1.09-4.45). CONCLUSION An association was observed between occupational hazards based on ERS and FBG trajectories. The risk of FBG trajectory levels increase with an increase in ERS.
Humans ; Male ; Adult ; Blood Glucose/analysis* ; China ; Prospective Studies ; Occupational Exposure/adverse effects* ; Risk Factors ; Middle Aged ; Steel ; Fasting/blood* ; Metal Workers ; East Asian People

OBJECTIVE: To investigate the association between ABO blood types and gestational diabetes mellitus (GDM) risk. METHODS: A prospective birth cohort study was conducted. ABO blood types were determined using the slide method. GDM diagnosis was based on a 75-g, 2-h oral glucose tolerance test (OGTT) according to the criteria of the International Association of Diabetes and Pregnancy Study Groups. Logistic regression was applied to calculate the odds ratios ( ORs) and 95% confidence intervals ( CIs) between ABO blood types and GDM risk. RESULTS: A total of 30,740 pregnant women with a mean age of 31.81 years were enrolled in this study. The ABO blood types distribution was: type O (30.99%), type A (26.58%), type B (32.20%), and type AB (10.23%). GDM was identified in 14.44% of participants. Using blood type O as a reference, GDM risk was not significantly higher for types A ( OR = 1.05) or B ( OR = 1.04). However, women with type AB had a 19% increased risk of GDM ( OR = 1.19, 95% CI = 1.05-1.34; P < 0.05), even after adjusting for various factors. This increased risk for type AB was consistent across subgroup and sensitivity analyses. CONCLUSION The ABO blood types may influence GDM risk, with type AB associated with a higher risk. Incorporating it-either as a single risk factor or in combination with other known factors-could help identify individuals at risk for GDM before or during early pregnancy.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/etiology* ; ABO Blood-Group System ; Adult ; Prospective Studies ; Risk Factors ; Young Adult