OBJECTIVE To investigate the clinical characteristics and risk factors for batroxobin-related severe hypofibrinogenemia （HFIB） and construct a risk prediction model. METHODS A retrospective analysis was conducted on inpatients treated with batroxobin in the First Medical Center of a tertiary hospital from January 1， 2020， to December 31， 2024. Patients were categorized into non-severe HFIB group and severe HFIB group based on the severity of HFIB. Univariate and multivariate Logistic regression analyses were performed to identify the independent influencing factors for batroxobin-related severe HFIB. A nomogram was developed using the “rms” package in R 4.5 software. The predictive performance of the model was evaluated using the receiver operating characteristic curve. Calibration was assessed via the Bootstrap resampling method， and goodness-of-fit was evaluated with the Hosmer-Lemeshow test. RESULTS A total of 1 472 patients were included in this study. Of these， 1 445 developed HFIB， yi elding an incidence of 98.17%. Furthermore， 895 were classified as severe HFIB， accounting for 60.80% of the cohort. Multivariate Logistic regression analysis showed that increased age， high initial dose per 10 kg body weight， use of maintenance dose， and concomitant glucocorticoid use were independent risk factors for batroxobin-related severe HFIB， while high baseline fibrinogen （FIB） level was identified as a protective factor. The model demonstrated an area under the curve of 0.760 （95% CI： 0.735-0.785）. The mean absolute error of the calibration curve was 0.006. The P value of the Hosmer-Lemeshow test was 0.609. CONCLUSIONS Batroxobin can rapidly and significantly reduce FIB levels and carries a risk of inducing severe HFIB. Patients with advanced age， high initial dose per 10 kg body weight， use of maintenance dose and concomitant glucocorticoid use had a higher risk of batroxobin-related severe HFIB， while high baseline FIB level had a lower risk of batroxobin-related severe HFIB. The risk prediction model developed based on these factors can be used to predict the likelihood of batroxobin-related severe HFIB.

This paper primarily reviews the current research status of passive and active monitoring methods for interventional radiology personnel, encompassing the types and wearing positions of personal dosimeters, simulation results versus measured outcomes, and discrepancies between different simulation results. By reviewing domestic and international literature, it lists effective dose estimation formulas for single- and dual-dosimeter systems developed by various researchers worldwide. Recommendations are proposed based on the current dosimeter wearing practices among interventional radiology staff, providing reference for the formulation of relevant standards.

ObjectiveTo investigate the potential mechanism of Danggui Shaoyaosan （DSS） in ameliorating renal injury in db/db mice. MethodsThirty 8-week-old specific pathogen-free （SPF）-grade male db/db mice and six db/m mice were acclimated for one week. Urinary microalbumin and blood glucose levels were measured weekly in both db/db and db/m mice. Successful modeling was determined by significantly higher microalbuminuria in db/db mice compared to db/m mice and a fasting blood glucose ≥16.7 mmol·L^-1. The 30 db/db mice were randomly divided into five groups： the model group， the irbesartan （IBN） group， and three DSS dose groups （low-， medium-， and high-dose DSS groups， administered at 16.77， 33.54， 67.08 g·kg^-1·d^-1， respectively）. Additionally， the six db/m mice served as the normal control group. The IBN group received irbesartan at 0.025 g·kg^-1·d^-1 by gavage， while the three DSS groups received DSS at 16.77， 33.54， and 67.08 g·kg^-1·d^-1 by gavage， respectively. The normal and model groups were administered with an equivalent volume of normal saline by gavage. All interventions lasted for 8 consecutive weeks. After intervention， serum creatinine （SCr）， blood urea nitrogen （BUN）， urinary total protein （UTP）， triglyceride （TG）， and low-density lipoprotein cholesterol （LDL-C） were measured to evaluate the therapeutic efficacy of the treatments. Renal histopathological changes were observed with hematoxylin-eosin （HE） staining. Western blot was used to detect the protein expression of silencing information regulator 1 （SIRT1）， hypoxia-inducible factor-1α （HIF-1α）， very low-density lipoprotein receptor （VLDLr）， and cluster of differentiation 31 （CD31）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA levels of HIF-1α and VLDLr. Immunohistochemistry was used to observe the expression and distribution of HIF-1α and Caspase-3. ResultsCompared to the normal group， the model group showed significantly increased SCr， BUN， UTP， TG， and LDL-C. HE staining revealed glomerulosclerosis， mesangial matrix hyperplasia， capillary loop distortion and thickening， with extensive inflammatory cell infiltration. Protein expression of SIRT1 and CD31 significantly decreased （P<0.05）， while HIF-1α and VLDLr protein and mRNA levels increased （P<0.05）. Immunohistochemistry showed increased expression of HIF-1α and Caspase-3 （P<0.05）， indicating hypoxia and apoptosis in renal cells. In all treatment groups， SCr， BUN， TG， and LDL-C were significantly reduced compared to the model group （P<0.05）， and UTP was significantly improved in the medium-dose DSS group （P<0.05）. Renal tissue structure and morphology were improved， inflammatory cells were reduced， and no vascular hyaline degeneration was observed. SIRT1 and CD31 protein expression was elevated to varying degrees compared to the model group （P<0.05）， while HIF-1α and VLDLr protein and mRNA levels decreased （P<0.05）. Immunohistochemistry showed reduced expression of HIF-1α and Caspase-3 in all treatment groups （P<0.05）， with the most significant improvement observed in the IBN group and medium-dose DSS group （P<0.05）. ConclusionDSS can effectively ameliorate glomerulosclerosis and lipid deposition in db/db mice， and its mechanism may involve the SIRT1/HIF-1α/VLDLr signaling pathway.

ObjectiveTo investigate the therapeutic efficacy of Danggui Shaoyaosan （DSS） on renal injury in db/db mice and its impact on endoplasmic reticulum stress （ERS） in renal tissues. MethodsThirty 8-week-old male db/db mice and six db/m mice were acclimated for one week， after which urinary microalbumin and blood glucose levels were monitored to establish a diabetic kidney disease （DKD） model. The model mice were randomly divided into a model group， an irbesartan group， and three DSS treatment groups with different doses （16.77， 33.54， and 67.08 g·kg^-1·d^-1）. A normal group was set as control. Each group was intragastrically administered with the corresponding drugs or saline for 8 weeks. After the intervention， general conditions were observed. Serum cystatin C （Cys-C）， 24-hour urinary total protein （24 h-UTP）， 24-hour urinary microalbumin （24 h-UMA）， urinary creatinine （Ucr）， and urea nitrogen （UUN） were measured. Transmission electron microscopy （TEM） was used to observe glomerular basement membrane （GBM） and ultrastructural changes of the endoplasmic reticulum （ER） in glomerular endothelial cells. Western blot， real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， and immunohistochemistry were used to analyze renal tissue structure and the expression of GRP78， CHOP， and related markers. ResultsCompared with the normal group， the mice in the model group showed curled posture， sluggish response， poor fur condition， increased levels of Cys-C， 24 h-UTP， 24 h-UMA， and UUN （P<0.05）， while Ucr decreased （P<0.05）. The GBM was significantly thickened， with podocyte and foot process fusion. The protein expressions of GRP78， CHOP， and ATF6 were significantly upregulated （P<0.05）， the mRNA levels of GRP78 and CHOP increased （P<0.05）， and immunohistochemistry showed an enhanced GRP78 signal （P<0.05）. After treatment， the mice exhibited improved behavior， normalized GBM and podocyte structure， improved ER morphology and markedly better biochemical indicators. Western blot， Real-time PCR， and immunohistochemistry indicated that the ERS-related markers were downregulated in the DSS treatment groups （P<0.05）， suggesting alleviated ERS and improved renal function. ConclusionDSS can effectively ameliorate renal pathological damage in db/db mice， possibly by regulating ERS in glomerular endothelial cells， although the underlying signaling mechanisms require further investigation.

ObjectiveTo establish a new noninvasive， simple， and convenient clinical predictive model by identifying independent predictive factors for rebleeding after endoscopic therapy in cirrhotic patients with esophagogastric variceal bleeding （EGVB）， and to provide a basis for individualized risk assessment and development of clinical intervention strategies. MethodsCirrhotic patients with EGVB who were diagnosed and treated in The First Affiliated Hospital of Xi’an Medical University from September 2018 to October 2023 were enrolled as subjects， and according to whether the patient experienced rebleeding within 1 year after endoscopic therapy， they were divided into rebleeding group with 93 patients and non-rebleeding group with 84 patients. Clinical data were collected and analyzed. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. A Logistic model was established based on the results of the univariate and multivariate analyses， and the receiver operating characteristic （ROC） curve and the area under the ROC curve （AUC） were used to assess the accuracy of the model. R software was used to visualize the model by plotting a nomogram， and the Bootstrap method was used for internal validation of the model. ResultsThe multivariate analysis showed that red blood cell count （RBC）， cholinesterase （ChE）， alkaline phosphatase （ALP）， albumin （Alb）， thrombin time （TT）， portal vein trunk diameter， sequential therapy， and primary prevention were independent predictive factors for rebleeding. Based on the results of the multivariate analysis， a logistic model was established as logit（P）=-0.805-1.978×（RBC）+0.001×（ChE）-0.020×（ALP）-0.314×（Alb）+0.567×（TT）+0.428×（portal vein trunk diameter）-2.303×［sequential therapy （yes=1， no=0）］-2.368×［primary prevention （yes=1， no=0）］. The logistic model （AUC=0.928， 95% confidence interval ［CI］： 0.893—0.964， P<0.001） had a better performance in predicting rebleeding than MELD score （AUC=0.603， 95%CI： 0.520—0.687， P=0.003）， Child-Pugh class （AUC=0.650， 95%CI： 0.578—0.722， P=0.001）， and FIB-4 index （AUC=0.587， 95%CI： 0.503—0.671， P=0.045）. The model had an optimal cut-off value of 0.607， a sensitivity of 0.817， and a specificity of 0.817. Internal validation confirmed that the model had good predictive performance and accuracy. ConclusionSequential therapy， implementation of primary prevention， an increase in RBC， and an increase in Alb are protective factors against rebleeding， while prolonged TT and widened main portal vein diameter are risk factors. The logistic model based on these independent predictive factors can predict rebleeding and thus holds promise for clinical application.

Disease computable phenotype is a data model designed to identify specific clinical conditions or characteristics, which automatically extracts information from clinical databases such as electronic health records through algorithms. Phenotypic data for rare diseases often reside in unstructured text. Due to the scarcity of rare disease cases, atypical symptoms, and insufficient physician experience, misdiagnosis and underdiagnosis rates remain high. In this context, the application of computable phenotype technology holds promise for improving the accuracy and efficiency of rare disease diagnosis. This article reviews the current research status, challenges, and opportunities of computable phenotype technology in biomedicine, particularly in the field of rare diseases, and proposes a development and validation framework for rare disease computable phenotypes, aiming to provide research and development insights for computable phenotypes to empower the diagnosis and treatment of rare diseases.

p21 (encoded by the CDKN1A gene) is a critical cell cycle regulatory protein endowed with versatile biological functions. In various sex hormone-related cancers, p21 exhibits a paradoxical dual role, capable of both inhibiting tumorigenesis and promoting cancer progression, exerting dual, often opposing, effects on cellular fate that are dictated by the specific context. The clinical targeting of p21 remains elusive, largely due to its functionally pleiotropic and context-dependent nature within intricate regulatory networks. During the initial, hormone-dependent phase of cancers like breast and prostate cancer, p21 expression and activity are largely governed by the transcriptional programs of estrogen or androgen receptor signaling. This hormonal regulation contributes to the control of tumor cell proliferation and underpins the initial efficacy of endocrine therapies. In contrast, as these diseases advance to late stages or evolve into non-hormone-dependent subtypes—exemplified by castration-resistant prostate cancer (CRPC) and specific forms of triple-negative breast cancer (TNBC)—these conventional hormonal control mechanisms often become dysfunctional or are entirely bypassed. This fundamental transition creates a critical therapeutic void, highlighting the urgent need to identify and exploit alternative molecular pathways to effectively target p21’s function. Promising strategies may include the precise modulation of its upstream transcriptional regulators, downstream effector proteins, or the intersecting parallel signaling networks that critically influence its activity. This review provides a systematic synthesis of the intricate and interconnected mechanisms that underpin the dual effects of p21 in sex hormone-related tumors. These mechanisms are categorized into three core, interrelated functional domains. (1) cell cycle regulation: p21 executes its canonical tumor-suppressive role by binding to and inhibiting cyclin-dependent kinases (CDKs) and by directly interacting with proliferating cell nuclear antigen (PCNA), thereby inducing cell cycle arrest, predominantly at the G1/S checkpoint; (2) apoptosis modulation: p21 exerts a highly context-dependent influence on programmed cell death, functioning either as a pro-apoptotic agent under severe genotoxic stress or as a pro-survival factor by inhibiting apoptosis through interactions with proteins like Bcl-2; (3) hormonal and signaling crosstalk: p21 is an integral node within broader cellular networks, engaging in direct physical interactions with hormone receptors(e.g., AR, ER) and participating in complex feedback loops with key oncogenic pathways, including PI3K/AKT, MAPK/ERK, and p53. Critically, the role of p21 is not static but highly dynamic. It can undergo a functional switch from tumor-suppressive to tumor-promoting in response to therapeutic pressures, metabolic alterations, or evolving tumor microenvironment cues. These adaptive shifts are frequently implicated in the development of therapy resistance and disease recurrence, particularly in advanced, hormone-resistant cancers. By synthesizing these insights, this review aims to establish a coherent theoretical framework to guide the future development of novel therapeutic strategies that target the p21 pathway. It underscores the necessity of moving beyond a simplistic, binary view of p21 and emphasizes the forthcoming challenges, such as the discovery of reliable biomarkers to predict its functional state and the rational design of context-specific pharmacological modulators to selectively harness its therapeutic potential.

Objective To investigate the effect of dexmedetomidine(Dex)on bone loss in tail-suspended rats and primarily explore its regulatory mechanism on bone metabolism.Methods A total of 30 male rats were randomly divided into a control group,a model group,and a Dex group,with 10 animals in each group.Rat model of osteoporosis was established by hind limb suspension for 4 weeks.Dex at a dose of 10 μg/kg was given intraperitoneally,once every other day from the day of tail suspension.And equal amount of normal saline was given to the control and model group.Bone histological staining was used to observe the trabecular bone area fraction.Biomechanical three-point bending test was employed to measure the maximum load,stiffness,and fracture energy.Dual calcein/alizarin red fluorescence labeling and tartrate resistant acid phosphatase(TRAP)staining were applied respectively to detect the mineral apposition rate and bone formation rate as well as the number of osteoclasts on bone surfaces.Secondly,after primary osteoblasts were isolated from the tibiae of tail-suspended rats and then treated with 1 nmol/L Dex,the proportion of alkaline phosphatase(ALP)-positive osteoblasts and the activity of the enzyme were detected by ALP staining and activity test.qRT-PCR was applied to measure the expression of osteogenic activity-related factors,including osteocalcin(Ocn),Runt related transcription factor 2(Runx2),Osterix protein(Osx),and type 1 collagen(Col1).Results The animal experiments revealed that Dex treatment significantly increased the tibial trabecular bone area fraction,inhibited the decrease in bone mechanical strength,and enhanced the mineralization deposition rate and new bone formation rate of trabecular bone in the tail-suspended rats(all P＜0.001).The in vitro experiments showed that Dex treatment obviously improved ALP activity and the number of ALP-positive osteoblasts in primary osteoblasts isolated from tail-suspended rats(P＜0.01),and up-regulated the expression levels of osteogenic differentiation-related genes,such as Ocn,Runx2,Osx and Col1(P＜0.01).Conclusion Dex exerts anti-bone loss effect in tail-suspended rats,which may be associated with its stimulation on osteoblast-mediated bone formation.

″Boundarics in biomedicine″(or″Biomedical boundarics″)is an emerging frontier interdisciplinary subject that focuses on addressing key scientific issues related to the formation,identification,and evolution of biological boundaries within living organisms.In this field,the study of tumor boundaries is of particular importance.Imaging tumor boundaries not only helps to reveal the molecular mechanisms of tumor boundary evolution and interaction with the microenvironment,tumor invasion and metastasis,but is also crucial for clinical tumor diagnosis,treatment decision-making,efficacy monitoring and prognosis evaluation.Molecular probes,as functional substances that enhance imaging signals,play a crucial role in tumor boundary recognition.In this article,the basic concepts and research significance of boundarics in biomedicine and tumor boundarics in biomedicine were summarized firstly.Then a comprehensive review of the research progress in tumor boundary imaging molecular probes was provided,covering areas such as magnetic imaging,optical imaging,acoustic imaging,nuclear imaging,and multimodal imaging.The strategies to regulate the sensitivity,specificity,and safety of molecular probes through chemical structure modifications,conjugation with targeting ligands,and tumor microenvironment-responsive designs were emphasized.Finally,the research trends of molecular probes for tumor boundary imaging were analyzed,and the challenges faced in this field and the future research directions were discussed.

Single-cell metabolite analysis at the small molecule level reveals intercellular heterogeneity and molecular diversity,especially living cell metabolite analysis which can provide more accurate biochemical information.In this study,a comprehensive single-cell metabolomics mass spectrometry analysis platform was constructed based on continuous ultrasonic sample introduction,aiming to improve the utilization rate of single cells and the efficiency of mass spectrometry detection.This platform utilized mechanical motion generated by a miniaturized ultrasound module,which minimally affected cell integrity and viability,enabling cell suspension and dispersion for up to 60 min,with cell viability exceeding 70%.By comparing cell suspension densities and the cell number of mass spectrometry detections between static and ultrasound groups,the results showed that the ultrasound treatment significantly reduced cell sedimentation rate and increased single-cell mass spectrometry detection efficiency.Applying this platform to single-cell analysis of cell line of mouse cerebellar astrocytes(C8D1A)and mouse glioma(GL261)cells achieved clustering and differential analysis of different cell types,demonstrating the method's potential in analyzing cellular heterogeneity and identifying cells.This approach promised to provide new insights and solutions for single-cell analysis.