Objective To explore the clinical factors influencing complete response in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (nCRT). Methods Clinical data of LARC patients treated in the Department of Radiation Oncology at Beijing Shijitan Hospital between January 2013 and December 2024 were retrospectively collected. All patients received nCRT, after which surgery or a watch-and-wait approach was adopted based on treatment response. Univariable and multivariable logistic regression analyses were performed to identify prognostic factors influencing complete response. A clinical prediction model was constructed based on the multivariable analysis results, and its predictive performance was evaluated using the receiver operating characteristic curve. Results A total of 113 eligible patients were included. After nCRT, 19 patients (16.8%) achieved complete response, including 3 with clinical complete response and 16 with pathological complete response. Univariable analysis indicated that pretreatment clinical N stage, extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen were associated with complete response after nCRT (P<0.05). Multivariable logistic regression analysis identified pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen as independent influencing factors for complete response (P<0.05). A prediction model incorporating these independent factors yielded an area under the receiver operating characteristic curve of 0.813 (95% confidence interval: 0.713-0.913), with a sensitivity of 89.5% and a specificity of 60.6%, demonstrating good predictive performance. Conclusion Pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen are independent factors influencing complete response after nCRT in LARC patients. The prediction model combining these factors may assist in evaluating treatment efficacy following nCRT in LARC patients.

Peripheral artery disease(PAD),commonly encountered in vascular surgery,predominantly affects the lower limbs and presents with ischemic symptoms resulting from atherosclerosis.It carries risks of adverse limb events and cardiovascular events.Antithrombotic therapy remains a cornerstone in the management of PAD.This article reviews the evidence and research progress regarding dual-pathway antithrombotic therapy for PAD.Multiple clinical trials have demonstrated that,compared to single antiplatelet therapy,dual-pathway antithrombotic therapy significantly reduces the risks of major adverse limb events and major adverse cardiovascular events without a significant increase in bleeding risk.For high-risk patients,such as those with advanced age,multivessel disease,comorbid coronary artery disease,or those undergoing endovascular revascularization,the benefits of dual-pathway antithrombotic therapy are particularly pronounced.Current clinical guidelines have incorporated dual-pathway antithrombotic therapy into their recommendations,standardized criteria for identifying the most appropriate patient populations remain lacking.Despite its advantages in reducing adverse events,its long-term safety profile and optimal target populations warrant further investigation.

Tumor metastasis is the leading cause of high mortality in most cancers, and numerous studies have demonstrated that the malignant crosstalk of multiple components in the tumor microenvironment (TME) together promotes tumor metastasis. Cancer-associated fibroblasts (CAFs) are the major stromal cells and crosstalk centers in the TME of various kinds of tumors, such as breast cancer, pancreatic cancer, and prostate cancer. Recently, the CAF-induced pro-tumor metastatic TME has gained wide attention, being considered as one of the effective targets for tumor therapy. With in-depth research, CAFs have been found to promote tumor metastasis through multiple mechanisms, such as inducing epithelial-mesenchymal transition in tumor cells, remodeling the extracellular matrix, protecting circulating tumor cells, and facilitating the formation of a pre-metastatic niche. To enhance the anti-tumor metastasis effect, therapeutic strategies designed by combining nano-drug delivery systems with CAF modulation are undoubtedly a desirable choice, as evidenced by the research over the past decades. Herein, we introduce the physiological properties of CAFs, detail the possible mechanisms whereby CAFs promote tumor metastasis, categorize CAFs-based nano-drug delivery strategies according to their anti-metastasis functions and discuss the current challenges, possible solutions, as well as the future directions in order to provide a theoretical basis and reference for the utilization of CAFs-based nano-drug delivery strategies to promote tumor metastasis therapy.

Perineural invasion (PNI) by tumor cells is a key phenotype of highly-invasive oral squamous cell carcinoma (OSCC). Since Schwann cells (SCs) and fibroblasts maintain the physiological homeostasis of the peripheral nervous system, and we have focused on cancer-associated fibroblasts (CAFs) for decades, it's imperative to elucidate the impact of CAFs on SCs in PNI⁺ OSCCs. We describe a disease progression-driven shift of PNI^- towards PNI⁺ during the progression of early-stage OSCC (31%, n = 125) to late-stage OSCC (53%, n = 97), characterized by abundant CAFs and nerve demyelination. CAFs inhibited SC proliferation/migration and reduced neurotrophic factors and myelin in vitro, and this involved up-regulated ER stress and decreased MAPK signals. Moreover, CAFs also aggravated the paralysis of the hind limb and PNI in vivo. Unexpectedly, leukemia inhibitory factor (LIF) was exclusively expressed on CAFs and up-regulated in metastatic OSCC. The LIF inhibitor EC330 restored CAF-induced SC inactivation. Thus, OSCC-derived CAFs inactivate SCs to aggravate nerve injury and PNI development.
Schwann Cells/metabolism* ; Mouth Neoplasms/metabolism* ; Humans ; Cancer-Associated Fibroblasts/metabolism* ; Animals ; Carcinoma, Squamous Cell/metabolism* ; Neoplasm Invasiveness/pathology* ; Male ; Female ; Mice ; Cell Movement/physiology* ; Cell Proliferation/physiology* ; Cell Line, Tumor ; Leukemia Inhibitory Factor/metabolism* ; Middle Aged

Stem-leaf saponins from Panax notoginseng (SLSP) comprise numerous PPD-type saponins with diverse pharmacological properties; however, their role in Parkinson's disease (PD), characterized by microglia-mediated neuroinflammation, remains unclear. This study evaluated the effects of SLSP on suppressing microglia-driven neuroinflammation in experimental PD models, including the 1-methyl-4-phenylpyridinium (MPTP)-induced mouse model and lipopolysaccharide (LPS)-stimulated BV-2 microglia. Our findings revealed that SLSP mitigated behavioral impairments and excessive microglial activation in models of PD, including MPTP-treated mice. Additionally, SLSP inhibited the upregulation of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX2) and attenuated the phosphorylation of PI3K, protein kinase B (AKT), nuclear factor-κB (NFκB), and inhibitor of NFκB protein α (IκBα) both in vivo and in vitro. Moreover, SLSP suppressed the production of inflammatory markers such as interleukin (IL)-1β, IL-6, and tumor necrosis factor alpha (TNF-α) in LPS-stimulated BV-2 cells. Notably, the P2Y2R agonist partially reversed the inhibitory effects of SLSP in LPS-treated BV-2 cells. These results suggest that SLSP inhibit microglia-mediated neuroinflammation in experimental PD models, likely through the P2Y2R/PI3K/AKT/NFκB signaling pathway. These novel findings indicate that SLSP may offer therapeutic potential for PD by attenuating microglia-mediated neuroinflammation.
Animals ; Panax notoginseng/chemistry* ; Saponins/pharmacology* ; Microglia/immunology* ; Mice ; NF-kappa B/immunology* ; Signal Transduction/drug effects* ; Proto-Oncogene Proteins c-akt/immunology* ; Phosphatidylinositol 3-Kinases/genetics* ; Male ; Parkinson Disease/immunology* ; Mice, Inbred C57BL ; Disease Models, Animal ; Plant Leaves/chemistry* ; Neuroinflammatory Diseases/drug therapy* ; Humans

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To identify high-risk factors for healthcare-associated infection(HAI)in patients in inten-sive care units(ICUs),and develop a quick response(QR)code-based APP prediction tool.Methods Information of inpatients in general ICUs of three hospitals in Guizhou Province from January to December 2024 were collected.Risk factors were analyzed with a logistic regression model.QR code-based APP was constructed and validated.Results A total of 1 782 patients in general ICUs of three hospitals in Guizhou Province in 2024 were included in the analysis,out of which 410 were HAI cases,and the incidence of HAI was 23.01％.Multivariate logistic regre-ssion analysis results of HAI in ICU inpatients showed that regional gross domestic product(GDP)≥58 685 Yuan,performing pathogen culture during this hospitalization,history of diabetes mellitus,history of cancer,length of hospital stay ≥7 days before infection,and duration of persistent fever＞5 days before infection were independent risk factors for HAI in ICU patients(all P＜0.05).The discrimination of the model(area under the receiver operating characteristic curve[AUC]of 0.841),calibration(Brier score of 0.129),and clinical effectiveness(net benefit of 11.4％when the risk threshold was 5％-74％)all performed well.Conclusion The QR code-based APP prediction tool is of great significance for scientific research transformation and precise HAI control.