ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

To summarize the clinical experience of Professor WANG Jie in treating palpitation using the method of tonifying the kidneys and invigorating blood. It is believed that kidney yang deficiency and heart vessel stasis are the key pathogenesis of palpitation， and it is advocated to treat palpitation by tonifying the kidney and invigorating the blood. Meanwhile，the methods of draining water， dissolving phlegm， and fortifying the spleen to supplement the blood should be applied. For palpitation with kidney yang deficiency and heart vessel stasis with upward water， the treatment could use self-prescribed Bushen Huoxue Lishui Formula （补肾活血利水方）； for palpitation with phlegm obstruction in blood vessel， the treatment could use self-prescribed Bushen Huoxue Huatan Formula （补肾活血化痰方）； for palpitation with spleen yang deficiency， the treatment could use self-prescribed Bushen Huoxue Jianpi Formula （补肾活血健脾方）.

Purpose: This study aimed to explore the trends in research keywords and topics in the field of urology based on text mining over the recent decades. The investigation looked into changes in frequent subject keywords and the trends in prevailing research topics, as reflected in representative urology journals over recent decades. Materials and Methods: A total of 27,129 bibliographic documents were collected from four urology journals, including European Urology, Journal of Urology, BJU International, and World Journal of Urology. The study then examined the changes in the most frequent author keywords over the decades. Moreover, structured topic modeling was employed to identify twenty prevailing research topics in urology and to examine their trends across different periods. Results: The study observed consistently increasing patterns in author keywords and topics related to the prostate and oncology.Conversely, research fields such as pediatrics, male infertility, voiding dysfunction, and cancer biology exhibited a downward trend in urology. Potential factors or reasons underlying these trends were further discussed in this study. Conclusions This exploratory study uncovered major research topics in the discipline of urology. The findings of this study depict the domain of urology research in recent decades, providing insights for both researchers and clinicians seeking to better understand the research trends in the discipline.

Objective To analyze the trend of influenza epidemic intensity in Urumqi City, Xinjiang, in early 2023, and to provide a reference basis for influenza surveillance, prevention and control. Methods Based on the daily number of influenza cases in Urumqi from January 1, 2023 to March 26, 2023, a generalized linear model was established to correlate the cumulative number of cases with the number of days of illness, and the corresponding doubling time was calculated. Results A total of 9 243 influenza cases were included in this study, including 7733 confirmed cases and 1510 suspected cases. The peak incidence of influenza occurred in March, and 6039 positive cases were detected, with a positivity rate of 78.09%. The age group of 3-6 years old had the highest proportion of influenza positive cases, accounting for 32.20%. The longest doubling time among confirmed cases was 13.49 (95% CI:11.95-15.47) in stage 2 (January 22 to February 13), and the shortest was in stage 3 (February 14 to March 26), which was 9.41 (95% CI:8.24-10.91). Conclusion The shorter the doubling time, the faster the speed of influenza transmission, and it is necessary to strengthen the prevention and control of influenza in winter and spring.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, with few effective treatments currently available. The multifactorial nature of AD, shaped by genetic, environmental, and biological factors, complicates both research and clinical management. Recent advances in artificial intelligence (AI) and multi-omics technologies provide new opportunities to elucidate the molecular mechanisms of AD and identify early biomarkers for diagnosis and prognosis. AI-driven approaches such as machine learning, deep learning, and network-based models have enabled the integration of large-scale genomic, transcriptomic, proteomic, metabolomic, and microbiomic datasets. These efforts have facilitated the discovery of novel molecular signatures and therapeutic targets. Methods including deep belief networks and joint deep semi-non-negative matrix factorization have contributed to improvements in disease classification and patient stratification. However, ongoing challenges remain. These include data heterogeneity, limited interpretability of complex models, a lack of large and diverse datasets, and insufficient clinical validation. The absence of standardized multi-omics data processing methods further restricts progress. This review systematically summarizes recent advances in AI-driven multi-omics research in AD, highlighting achievements in early diagnosis and biomarker discovery while discussing limitations and future directions needed to advance these approaches toward clinical application.

Poly(ADP-ribose) polymerase 1 (PARP1) is a multifunctional protein involved in diverse cellular functions, notably DNA damage repair. Pharmacological inhibition of PARP1 has therapeutic benefits for various pathologies. Despite the increased use of PARP inhibitors, challenges persist in achieving PARP1 selectivity and effective blood-brain barrier (BBB) penetration. The development of a PARP1-specific positron emission tomography (PET) radioligand is crucial for understanding disease biology and performing target occupancy studies, which may aid in the development of PARP1-specific inhibitors. In this study, we leverage the recently identified PARP1 inhibitor, AZD9574, to introduce the design and development of its ¹⁸F-isotopologue ([¹⁸F]AZD9574). Our comprehensive approach, encompassing pharmacological, cellular, autoradiographic, and in vivo PET imaging evaluations in non-human primates, demonstrates the capacity of [¹⁸F]AZD9574 to specifically bind to PARP1 and to successfully penetrate the BBB. These findings position [¹⁸F]AZD9574 as a viable molecular imaging tool, poised to facilitate the exploration of pathophysiological changes in PARP1 tissue abundance across various diseases.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

OBJECTIVE: Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity. METHODS: To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes. RESULTS: We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1. CONCLUSION We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Circadian Rhythm/genetics* ; Prognosis ; Male ; Female ; Biomarkers, Tumor/genetics* ; Middle Aged ; Machine Learning ; Computational Biology

ObjectiveTo investigate the role of sphingosine-1-phosphate （S1P） in abnormal ossification in ankylosing spondylitis （AS）， clarify the relationship between S1P and “angiogenesis-osteogenesis” coupling， and provide new strategies for AS treatment. MethodsFemoral heads from AS patients and patients undergoing routine hip replacement were collected for immunohistochemical （IHC） staining to evaluate osteogenesis and H-type vessel formation. In vitro， ELISA was used to quantify the synthesis of S1P and analyze the expression changes of S1P signaling pathway-related molecules during the osteogenic differentiation of mesenchymal stem cells derived from patients with ankylosing spondylitis （ASMSCs） and those from healthy donors （HDMSCs）， to evaluate the activation status of S1P pathway during osteogenesis. Sphingosine kinase 1 （SK1） expression was knocked down in MSCs， and the S1P receptor inhibitor FTY720 was applied to block S1P signaling. Alkaline phosphatase （ALP） activity and Alizarin Red S （ARS） quantification were used to assess the effect of S1P on ASMSCs osteogenesis. Conditioned medium from osteogenically induced MSCs was used to treat human umbilical vein endothelial cells （HUVECs） to evaluate the effect of S1P on angiogenesis. An AS mouse model （SKG mice） was treated with FTY720 or the SK1 inhibitor PF-543 citrate. IHC staining and micro-CT scanning were used to assess abnormal ossification and spinal fusion， and immunofluorescence was used to evaluate H-type vessel formation. ResultsCompared with Osteonecrosis of the Femoral Head（ONFH） patients， AS patients exhibited excessive osteogenesis and H-type vessel formation （OCN P＜0.001， CD31 P＜0.001， EMCN P＜0.001）. During osteogenic differentiation， S1P expression and secretion were significantly higher in ASMSCs than in HDMSCs （P=0.0179）. Inhibition of S1P signaling with FTY720 or SK1 knockdown significantly suppressed osteogenic differentiation （compared with ASMSC， ARS： HDMSC P=0.001 8， FTY720 P＜0.001， si-SK1 P＜0.001； ALP： HDMSC P=0.032 8， FTY720 P=0.001 6， si-SK1 P＜0.001） of ASMSCs and the angiogenesis of HUVEC（compared with ASMSC， cell-covered area， total loops， total tube length and total branch points P＜0.001）. Treatment with FTY720 or PF-543 markedly inhibited abnormal ossification and spinal fusion（compared with Curdlan， arthritis index score， P＜0.001； OCN：control P=0.002， PF-543 P=0.010 7， FTY720 P=0.015 9 ） in AS mice and reduced H-type vessel formation （CD31⁺EMCN⁺： compared with curdlan， control P＜0.001， PF-543 P=0.001 7， FTY720 P=0.002 1）. ConclusionIncreased S1P synthesis in ASMSCs promotes osteogenic differentiation via autocrine mechanisms and further enhances ossification by facilitating H-type angiogenesis. Inhibiting S1P secretion in ASMSCs significantly suppresses abnormal ossification in AS.

Objective:To explore the correlation between peripheral blood B cell count and clinical features and prognosis of patients with newly diagnosed diffuse large B-cell lymphoma(DLBCL).Methods:The relationship of peripheral blood B cell count with clinical features,laboratory indexes and prognosis in 67 patients with newly diagnosed DLBCL was retrospectively analyzed.Results:Patients were divided into low B-cell count group(B cell＜0.1 × 109/L,n=34)and high B-cell count group(B cell≥0.1 × 109/L,n=33)according to the median B cell count values.Compared with the high B cell count group,the low B cell count group had a higher proportion of patients with Lugano stage Ⅲ-Ⅳ,elevated LDH,elevated β2-MG and IPI score 3-5 and increased CRP(P=0.033,0.000,0.023,0.001,0.033).The peripheral CD3+and CD4+cell counts of patients in the low B cell count group were significantly lower than those in the high B cell count group(P=0.010,0.017).After initial treatment,overall response rate(ORR)and complete remission(CR)rate in high B cell count group were significantly higher than those in low B cell count group(P=0.032,0.013).The median follow-up time of patients was 23(2-77)months,progression-free survival(PFS)and overall survival(OS)of patients in the high B cell count group were significantly better than those in the low B cell count group(P=0.001,0.002).Univariate analysis showed that pretreatment low B cell count in the peripheral blood was associated with shortened PFS and OS(HR=4.108,P=0.002;HR=8.218,P=0.006).Multivariate analysis showed that low B cell count was an independent prognostic factor for shortened PFS(HR=3.116,P=0.037).Conclusion:Decreased peripheral blood B cell count in newly diagnosed DLBCL patients is associated with high-risk clinical features and may affect the efficacy of immunochemotherapy,which is associated with poor clinical prognosis.