ObjectiveTo assess the cost-effectiveness of human immunodeficiency virus (HIV) prevention and control strategies across different high-risk populations, investment levels, and allocation proportions in an area, thereby providing a reference for optimizing resource allocation in acquired immunodeficiency syndrome (AIDS) prevention and control. MethodsDemographic, epidemiological, and clinical progression data of the target population in an area from 2018 to 2024 were collected, along with the input costs and intervention coverage of HIV-related projects. The Optima HIV model was utilized to perform fitting and prediction, whereby the allocation of resources to optimized target populations and program interventions was modeled under varying future investment scenarios to predict the impacts on the reduction of new HIV infections and HIV-related deaths. ResultsUnder the scenario of maintaining the current level of intervention input for HIV key populations, new HIV infections and related deaths in the region were predicted to be controlled at a low level by 2030. In terms of intervention input for HIV key populations, it is suggested that appropriately increasing the intervention input for key HIV populations will further reduce new HIV infections and HIV-related deaths in the region. However, when the total input increases to 1.75 times the baseline level, the marginal effect of input will be saturated. Regarding structural adjustments in investment and considering both the current total investment scenario and 1.75 times the total investment scenario, it is predicted that further reductions in regional HIV new infections and HIV-related deaths can be achieved, provided that the intervention input for key populations (including men who have sex with men, MSM) is increased, while concurrently intensifying the proportion of intervention measures such as condom promotion to form optimized intervention portfolios. ConclusionIn the field of HIV/ AIDS prevention and control, sustained commitment to intervention investment, with a strategic focus on interventions for key populations and intensified implementation of critical intervention measures, will effectively improve the epidemiological impacts of HIV/AIDS prevention and control efforts.

OBJECTIVE To investigate the mechanism of isochlorogenic acid A against hepatocellular carcinoma based on the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin （PI3K/Akt/mTOR） signaling pathway and multi-omics technology. METHODS The invasion rate and migration rate of human hepatocellular carcinoma HepG2 cells after 48 h of intervention with 0 （control group）， 0.25 and 0.5 mg/mL isochlorogenic acid A were examined； mRNA expression of DEP domain-containing mTOR-interacting protein （DEPTOR）， the protein expressions of mTOR， PI3K and phosphatase and tensin homologue deleted on chromosome ten （PTEN）， as well as the phosphorylation level of Akt protein were determined in the cells. Metabolomics analysis was performed using liquid chromatography-tandem mass spectrometry， and differential metabolites were screened and subjected to Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis； transcriptomics monitoring was conducted by RNA sequencing， and differentially expressed genes were screened and subjected to gene ontology （GO） and KEGG pathway enrichment analyses. RESULTS Compared with the control group， intervention with 0.25 and 0.5 mg/mL isochlorogenic acid A for 48 h significantly inhibited the invasion rate and migration rate of HepG2 cells， significantly up-regulated the mRNA expression of DEPTOR and the protein expression of PTEN， and significantly down-regulated the protein expression of PI3K and the phosphorylation level of Akt protein （except for 0.25 mg/mL isochlorogenic acid A） （ P ＜0.05）. A total of 304 differential metabolites and 212 differentially expressed genes were screened by multi-omics analysis. KEGG pathway enrichment analysis suggested that isochlorogenic acid A regulated key signaling of HepG2 cell growth mainly by inhibiting the PI3K/Akt signaling pathway， synergizing with metabolic reprogramming such as mTOR signaling pathway， ferroptosis， pentose phosphate pathway and purine/pyrimidine metabo lism. CONCLUSIONS The anti-hepatocellular carcinoma effect of isochlorogenic acid A is associated with the blockade of abnormal activation of the PI3K/Akt/mTOR signaling pathway. In addition， it may also be related to the inhibition of the pentose phosphate pathway and purine/pyrimidine metabolism， as well as the induction of ferroptosis，etc.

Intelligent prescription recommendation has become an important research direction in traditional Chinese medicine (TCM), offering new opportunities to support clinical decision-making and promote the modernization of TCM practice. With the rapid development of artificial intelligence (AI), a variety of computational approaches have been proposed to learn prescription patterns from clinical data and generate personalized treatment recommendations. However, despite increasing research activity, systematic and comprehensive reviews of AI-driven methods for TCM prescription recommendation remain limited. In this study, we present a comprehensive review of computational approaches for herbal prescription recommendation (HPR) in TCM. Existing methods are systematically categorized into several major paradigms, including traditional machine learning methods, topic model methods, sequential generative methods, deep learning and graph-based methods, and large language model–based frameworks. In addition to summarizing methodological developments, we also review commonly used public datasets and evaluation metrics in this field. Furthermore, representative models with publicly available implementations are experimentally evaluated on multiple benchmark datasets to provide a comparative analysis of their performance on the HPR task. Finally, we discuss the key challenges that hinder the practical deployment of intelligent prescription recommendation systems, including data heterogeneity, limited interpretability, and insufficient integration of TCM domain knowledge. Future research directions are outlined to facilitate the development of more reliable, interpretable, and clinically applicable AI-assisted HPR systems for TCM.

Cholangiocarcinoma (CCA) is a malignancy characterized by tumor cells originating in the liver or bile ducts, exhibiting features of cholangiocyte differentiation. It poses a significant clinical challenge due to the limited diagnostic and therapeutic options available. Robust animal models are essential for advancing our understanding of CCA pathogenesis and developing effective treatments. This review provides a comprehensive overview of CCA mouse models, highlighting various approaches, including chemical induction, genetically engineered models, and tumor xenografts. Each model is discussed in terms of its establishment techniques, pathological characteristics, and research significance, with a focus on intrahepatic CCA. Chemical induction models, such as diethylnitrosamine- and azoxymethane-induced models, offer insights into tumorigenesis processes, whereas genetically modified models involving alterations in key genes such as Kirsten rat sarcoma viral oncogene homolog, tumor protein 53, and isocitrate dehydrogenase serve as important tools for studying the molecular mechanisms underlying CCA. Xenograft models, including patient-derived xenografts, bridge the gap between experimental research and clinical applications, allowing for precise therapeutic evaluations. By comparing these models, this review underscores their respective advantages and limitations, paving the way for future studies aiming to optimize and innovate CCA modeling strategies.

Panretinal photocoagulation(PRP)is the first-line treatment for severe non-proliferative diabetic retinopathy and proliferative diabetic retinopathy(PDR).Its therapeutic efficacy varies due to multiple patient-specific systemic and ocular factors. Despite standardized PRP, some patients fail to show adequate regression of neovascularization and subsequently develop vitreous hemorrhage(VH). In such cases, pars plana vitrectomy(PPV)effectively clears the hemorrhage, restores transparency of the ocular media, supplement PRP, and delays the progression of PDR, thus becoming a critical intervention. With recent advances in surgical techniques, concepts, and equipment, early PPV intervention for VH following PRP has emerged as a growing research focus. Nevertheless, consensus remains lacking regarding its indications, optimal timing, and surgical protocols. This article systematically reviews relevant domestic and international studies, summarizing the surgical timing, approaches, and prognoses of PPV for VH in PDR patients after PRP, aiming to provide evidence-based reference for clinical decision-making and reduce the risk of PDR-related blindness.

ObjectiveTo optimize the flow cytometric sorting workflow for myeloid-derived suppressor cells （MDSCs） from murine Lewis lung carcinoma （LLC） subcutaneous tumor tissues， improving single-cell suspension preparation efficiency and sorting purity， thereby providing high-quality cells for subsequent functional studies. MethodsSubcutaneous LLC tumor tissues were harvested from C57BL/6 mice， and two enzymatic digestion protocols were first compared to evaluate their effects on single-cell suspension preparation. After staining with a viability dye （Live/Dead） and fluorochrome-conjugated anti-mouse antibodies against CD45， CD11b， and Gr-1， cells were loaded onto a Beckman CytoFLEX cell sorter. Next， conventional and optimized gating strategies were applied. In the optimized strategy， the CD45⁺ population was used as the initial gate to directly define an MDSC-enriched region， followed by selection of CD11b⁺Gr-1⁺ cells. Finally， purity was assessed by flow cytometry， viability was determined by trypan blue staining， and RT-qPCR was performed to measure the expression of MDSC signature genes， including Arg1， Nos2， IL-10， and S100A8/A9. ResultsThe optimized enzymatic digestion protocol significantly increased the yield and viability of single cells. After optimization of the gating strategy， the post-sort positivity rate （purity） was markedly improved. Arg1， Nos2， IL-10 and S100A8/A9 were highly expressed in the sorted cells， indicating that the isolated cells retained characteristic MDSC features and functional signatures. ConclusionBy optimizing both the tissue digestion protocol and the flow cytometric gating strategy， we establish an efficient workflow for isolating MDSCs from tumor tissues. This method improves the yield and purity of single-cell preparations while preserving antigen integrity， providing a reliable methodological foundation for subsequent studies on MDSC function and metabolism.

Background: Visual impairment is increasingly prevalent, underscoring the need for effective prevention strategies. This study investigated the association between cardiovascular health and visual impairment using three progressively developed metrics: Life’s Simple 7 (LS7), a cardiovascular health score developed by the American Heart Association based on 7 components, including physical activity, smoking status, body mass index (BMI), diet, blood glucose, blood pressure, and total cholesterol; Life’s Essential 8(LE8), which adds sleep health as an additional component; and Life’s Crucial 9 (LC9), which further incorporates mental health. We aimed to evaluate whether these expanded metrics provide additional explanatory value and to inform future public health strategies. Objective: To investigate the associations among LS7, LE8, and LC9 cardiovascular health scores and visual impairment in National Health and Nutrition Examination Survey 2013 to 2018, assess the added value of sleep and mental health components, and identify key contributing subcomponents using regression and machine learning methods. Methods: We analyzed data from 9891 participants in the 2013 to 2018 National Health and Nutrition Examination Survey. Multivariable logistic regression, restricted cubic spline modeling, and subgroup analyses were conducted to evaluate the association between cardiovascular health and visual impairment. Machine learning methods, including Random Forest and SHapley Additive exPlanations, a model interpretation approach used to assess feature importance, were applied. The Boruta algorithm, a feature selection method, was used to identify key subcomponents of cardiovascular health. Results: Participants with visual impairment were older, had lower poverty-to-income ratios, and exhibited lower cardiovascular health scores (LS7, LE8, and LC9). Higher cardiovascular health scores were negatively associated with visual impairment. Each one standard deviation increase in LS7, LE8, and LC9 was associated with approximately 8%, 2%, and 3% lower odds of visual impairment, respectively. LS7 showed the strongest negative association, whereas LE8 and LC9 emerged as the most important predictors in the machine learning models. Key subcomponents such as blood glucose, blood pressure, and BMI, as well as mental health status, were strongly associated with visual impairment. Conclusion: Higher cardiovascular health scores were negatively associated with visual impairment. LS7 demonstrated the strongest statistical association, whereas LE8 and LC9 were the most influential features in the machine learning models. Blood glucose, blood pressure, BMI, and mental health status were important correlates of visual impairment. From the perspective of the “prevention and treatment of diseases” in traditional Chinese medicine and the holistic concept, the aforementioned research findings confirm that severe visual impairment is indeed an external manifestation of overall health imbalance (such as organ dysfunction and Qi deficiency and blood stasis). The prevention strategy lies in comprehensively adjusting lifestyle, emotional factors, and metabolic indicators (corresponding to the key factors in the study) to restore the body’s internal balance and achieve prevention before disease arises.

Systemic chronic inflammation associated with advancing age is closely linked to the onset and progression of multiple age-related diseases. This persistent inflammatory state, commonly termed inflammaging, reflects complex interactions between accumulated cellular damage and dysregulated immune responses. Inflammasomes are multiprotein complexes of the innate immune system that respond to cellular stress and damage and amplify inflammatory signaling. Their sustained or recurrent activation may contribute to the establishment and maintenance of inflammaging. This review focuses on the NLRP3 inflammasome and summarizes its activation mechanisms, regulatory pathways, and pathological significance within the aging microenvironment. Particular attention is given to neurodegenerative diseases, osteoarthritis, atherosclerosis, and type 2 diabetes, emphasizing shared activation mechanisms and tissue-specific effects. Although initiating stimuli differ among these conditions, several molecular events can contribute to NLRP3 inflammasome activation. Priming mediated by nuclear factor‑κB (NF‑κB) promotes the expression of NLRP3 and pro-interleukin-1β, whereas lysosomal damage, mitochondrial dysfunction, reactive oxygen species accumulation, mitochondrial DNA release, and potassium efflux can participate in activation pathways. These events are interconnected rather than obligatory sequential steps in every setting. Inflammasome assembly promotes caspase-1 activation, which facilitates interleukin-1β and interleukin-18 maturation and gasdermin D cleavage, potentially leading to pyroptosis. The relative contributions of these processes depend on cell type, tissue context, and disease stage. Within aging tissues, persistent damage signals and impaired cellular homeostasis may favor repeated inflammasome activation, establishing a cycle of inflammatory amplification and further tissue injury. However, the pathological consequences vary across organs. In neurodegenerative diseases, inflammasome signaling is associated with neuroinflammation and neuronal vulnerability; in osteoarthritis, it may contribute to joint inflammation and cartilage degeneration. In atherosclerosis, it is implicated in vascular inflammation and plaque progression, whereas in type 2 diabetes, it is linked to metabolic inflammation and impaired glucose homeostasis. These distinctions underscore the importance of interpreting shared molecular mechanisms within specific tissue environments. The review further discusses the therapeutic potential of targeting inflammasomes to mitigate inflammaging and associated disease processes. Strategies include inhibiting NLRP3 activation, modulating upstream stress and priming pathways, and limiting downstream inflammatory signaling or pyroptotic cell death. By interrupting shared mechanisms of inflammatory amplification, these approaches may offer opportunities for coordinated intervention across multiple age-related disorders. Nevertheless, mechanistic overlap does not imply uniform therapeutic responses, and benefits observed in experimental models should not be equated with established clinical efficacy or evidence of delayed human aging.Successful clinical translation will require careful consideration of disease stage, tissue specificity, treatment timing, and the consequences of prolonged interference with innate immune defenses. Long-term safety is particularly important for older populations and preventive applications. The limited availability of validated biomarkers of inflammasome activity also complicates patient stratification, assessment of target engagement, and monitoring of therapeutic responses. Future research should clarify causal relationships, identify contexts in which inflammasome inhibition is most beneficial, and establish reliable translational endpoints. Overall, inflammasomes represent an important link between aging-associated damage and chronic inflammatory amplification, supporting their investigation as shared targets for early intervention in multiple age-related diseases, while highlighting the need for disease-specific evaluation and rigorous assessment of benefits and risks.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective To explore the pathogenesis of Alzheimer's disease by examining the effects of dihydroartemisinin(DHA)on cognitive behavior,hippocampal,cerebral cortex and retinal cell morphology,β-amyloid(Aβ)and autophagy-related proteins in 5×FAD mice.Methods Twenty 5×FAD mice and 5 wild type(WT)mice were selected,all of which were female.The 5×FAD mice were randomly divided into model(M)group,donepezil(D)group,low-dose DHA(DHA-L)group,and high-dose DHA(DHA-H)group.The WT and M groups were not treated,and the D group was given donepezil 0.1 mg/kg per day.DHA-L group and DHA-H group were given 10 mg/kg and 20 mg/kg DHA per day,respectively.Group D,group DHA-L and group DHA-H were given intragastric administration once a day for 3 months.The changes of in cognitive behavior were measured by Morris experiment.HE staining was used to observe the arrangement and morphology of nerve cells in cerebral cortex,hippocampus and retina.The expressions of Aβ protein in cerebral cortex,hippocampus and retina were detected by immunohistochemistry.Western blotting detected the expression of autophagy related proteins(LC3-Ⅰ,LC3-Ⅱ,Beclin-1,P62,β-actin).Results The DHA-H group and the D group exhibited more frequent adoption of both linear and trending exploration routes.Compared to the model group,significant differences in the contents of Aβ in the hippocampal CA1,cerebral cortex S1,and retinal were observed(P＜0.0001)in the other four groups.The analysis also showed significant differences in autophagy-associated proteins between the DHA-L,DHA-H,and model groups(P＜0.01).Conclusion DHA improves cognitive function and increases the number of nerve cells in mice.It also reduces Aβ content in the cerebral cortex,hippocampus,and retina,along with improving autophagy-associated protein deposition in mice.