Benign prostatic hyperplasia (BPH) is a common urological condition affecting elderly men worldwide. In 2021, there were 112,502 (95% UI: 88,131.8–142,634.2) thousand prevalent cases globally, compared to 50,705.8 (95% UI: 38,735.5–65,693.4) thousand cases in 1990, representing a 122% increase. Over the past 30 years, the burden of BPH in low and low-middle socio-demographic index (SDI) regions have shown an upward trend and is projected to continue increasing over the next 15 years. Middle-SDI regions are facing the heaviest absolute burden of BPH. Despite declining prevalence, incidence, and disability-adjusted life years rates in high-middle SDI regions, the absolute BPH burden remains high, ranking second among the five SDI regions. In contrast, high-SDI regions exhibit a relatively low and stable BPH burden, though significant variations exist even among countries within the high-SDI category. Additionally, the global 65–69 age group bears the highest burden, with the 40–44 and 80+ age groups showing increasing trends. The burden of BPH varies significantly across regions, socioeconomic statuses, and countries, yet the absolute burden is generally increasing. The substantial regional differences in BPH burden underscore its widespread impact and potential controllability, indicating the need for more targeted healthcare efforts to address the growing BPH burden.

Prostate cancer (PCa) is a common malignant tumor with increasing incidence and high heterogeneity among males worldwide. In the era of big data and artificial intelligence, the paradigm of biomarker discovery is shifting from traditional experimental and small data-based identification toward big data-driven and systems-level screening. Complex interactions between genetic factors and environmental effects provide opportunities for systems modeling of PCa genesis and evolution. We hereby review the current research frontiers in informatics for PCa clinical translation. First, the heterogeneity and complexity in PCa development and clinical theranostics are introduced to raise the concern for PCa systems biology studies. Then biomarkers and risk factors ranging from molecular alternations to clinical phenotype and lifestyle changes are explicated for PCa personalized management. Methodologies and applications for multi-dimensional data integration and computational modeling are discussed. The future perspectives and challenges for PCa systems medicine and holistic healthcare are finally provided.

Pyroptosis is a specific type of programmed cell death (PCD) characterized by distinct morphological changes, including cell swelling, membrane blebbing, DNA fragmentation, and eventual cell lysis. Pyroptosis is closely associated with human-related diseases, such as inflammation and malignancies. Since the initial observation of pyroptosis in Shigella flexneri-infected macrophages more than 20 years ago, various pyroptosis-inducing agents, including ions, small molecules, and biological nanomaterials, have been developed for tumor treatment. Given that pyroptosis can activate the body's robust immune response against tumor and promote the formation of the body's long-term immune memory in tumor treatment, its status as a type of immunogenic cell death is self-evident. Therefore, pyroptosis should be used as a powerful anti-tumor strategy. However, there still is a lack of a comprehensive summary of the most recent advances in pyroptosis-based cancer therapy. Therefore, it is vital to fill this gap and inspire future drug design to better induce tumor cells to undergo pyroptosis to achieve advanced anti-tumor effects. In this review, we summarize in detail the most recent advances in triggering tumor cell immunogenic pyroptosis for adequate tumor clearance based on various treatment modalities, and highlight material design and therapeutic advantages. Besides, we also provide an outlook on the prospects of this emerging field in the next development.

With the development of aggregation‐induced emission (AIE) materials, the drawbacks of conventional fluorescence materials subjected to aggregation‐caused quenching (ACQ) have been resolved. This has allowed for the improvement of novel AIE fluorescent materials that exhibit enhanced photostability, a higher signal‐to‐noise ratio, and better imaging quality. Meanwhile, the enhanced phototherapeutic effect of AIE materials has garnered widespread attention in the realm of tumor treatment. The distinct physiological and anatomical characteristics of the urinary system make it suitable for the use of AIE materials. Additionally, AIE‐based phototherapy provides a superior solution to deal with the weaknesses of conventional treatments for urologic neoplasms. In this review, the scientific advancement on the use of AIE materials in urinary system diseases since the emergence of the AIE concept is reviewed in detail. The review highlights the promise of AIE materials for biomarkers detection, fluorescence imaging (FLI) in vivo and in vitro, AIE‐based phototherapy, and synergistic therapy from both diagnostic and therapeutic viewpoints. It is firmly believed that AIE materials hold immense untapped potential for the diagnosis and treatment of urologic disease, as well as all diseases of the human body.

HLA donor-specific antibodies (DSAs) binding to vascular endothelial cells of the allograft trigger inflammation, vessel injury, and antibody-mediated rejection (AMR). Accumulation of intragraft-recipient macrophages is a histological characteristic of AMR, which portends worse outcome. HLA class I (HLA I) DSAs enhance monocyte recruitment by activating endothelial cells and engaging FcγRs, but the DSA-activated donor endothelial influence on macrophage differentiation is unknown. In this study, we explored the consequence of DSA-activated endothelium on infiltrating monocyte differentiation. Here we show that cardiac allografts from murine recipients treated with MHC I DSA upregulated genes related to monocyte transmigration and Fc receptor stimulation. Human monocytes co-cultured with HLA I IgG-stimulated primary human endothelium promoted monocyte differentiation into CD68⁺ CD206⁺ CD163⁺ macrophages (M(HLA I IgG)), whereas HLA I F(ab')₂ stimulated endothelium solely induced higher CD206 (M(HLA I F(ab')₂ )). Both macrophage subtypes exhibited significant changes in discrete cytokines/chemokines and unique gene expression profiles. Cross-comparison of gene transcripts between murine DSA-treated cardiac allografts and human co-cultured macrophages identified overlapping genes. These findings uncover the role of HLA I DSA-activated endothelium in monocyte differentiation, and point to a novel, remodeling phenotype of infiltrating macrophages that may contribute to vascular injury.

Background: The early detection of high-grade prostate cancer (HGPCa) is of great importance. However, the current detection strategies result in a high rate of negative biopsies and high medical costs. In this study, the authors aimed to establish an Asian Prostate Cancer Artificial intelligence (APCA) score with no extra cost other than routine health check-ups to predict the risk of HGPCa. Patients and methods: A total of 7476 patients with routine health check-up data who underwent prostate biopsies from January 2008 to December 2021 in eight referral centres in Asia were screened. After data pre-processing and cleaning, 5037 patients and 117 features were analyzed. Seven AI-based algorithms were tested for feature selection and seven AI-based algorithms were tested for classification, with the best combination applied for model construction. The APAC score was established in the CH cohort and validated in a multi-centre cohort and in each validation cohort to evaluate its generalizability in different Asian regions. The performance of the models was evaluated using area under the receiver operating characteristic curve (ROC), calibration plot, and decision curve analyses. Results: Eighteen features were involved in the APCA score predicting HGPCa, with some of these markers not previously used in prostate cancer diagnosis. The area under the curve (AUC) was 0.76 (95% CI:0.74–0.78) in the multi-centre validation cohort and the increment of AUC (APCA vs. PSA) was 0.16 (95% CI:0.13–0.20). The calibration plots yielded a high degree of coherence and the decision curve analysis yielded a higher net clinical benefit. Applying the APCA score could reduce unnecessary biopsies by 20.2% and 38.4%, at the risk of missing 5.0% and 10.0% of HGPCa cases in the multi-centre validation cohort, respectively. Conclusions: The APCA score based on routine health check-ups could reduce unnecessary prostate biopsies without additional examinations in Asian populations. Further prospective population-based studies are warranted to confirm these results.