Objective:The aim of this study is to re-evaluate the systematic reviews and meta-analyses on statins for the treat-ment of erectile dysfunction(ED)and construct an umbrella review,thereby providing robust evidence-based for the clinical applica-tion of statins in ED treatment.Methods:A comprehensive computerized search was conducted across CNKI,Wanfang Database,VIP,WOS,Embase,PubMed,and Cochrane Library databases from their inception to September 12,2024,for all systematic reviews and meta-analyses addressing statin interventions in ED.The methodological quality,reporting quality,and evidence quality of the in-cluded studies were assessed and summarized using PRISMA 2020,AMSTAR 2,and GRADE systems.Results:Four systematic re-views and meta-analyses were included.According to the AMSTAR 2 evaluation,one paper was rated as low quality,while the remai-ning three were classified as very low quality.PRISMA 2020 evaluation results indicated that the average score of the four included studies was 29,with all being of medium quality but exhibiting partial deficiencies.The proportion of fully consistent items across the four studies ranged from 52.38％to 80.95％.GRADE system tool evaluation revealed 11 outcome indicators,of which only one was rated as intermediate evidence.The remainders were categorized as low or very low evidence,with no high-quality evidence identified.Conclusion:Statins demonstrate efficacy in treating ED.However,the current quality of relevant systematic reviews is suboptimal,with notable deficiencies in methodological,reporting,and evidential quality.Further high-quality studies are warranted to provide more reliable evidence-based medical guidance for clinical practice.

Objective:To explore and analyze the correlation between the expression of mismatch repair(MMR)protein and programmed death ligand 1(PD-L1)in colorectal cancer(CRC)tissue and clinical pathological characteristics.Methods:The study period were from July 2021 to December 2024,200 cases of colorectal cancer patients treated in our hospital were selected as the research subjects.Collected all patient lesion tissue samples(lesion group)and adjacent tissue samples(located ≥5 cm from the tumor edge,adjacent group),and used the immunohistochemistry(IHC)method to detect the expression of Mismatch repair(MMR)(MLH1,MSH2,MSH6,and PMS2)protein and PD-L1 protein.Investigated the clinical and pathological characteristics of patients and conducted correlation analysis.Results:The positive rates of dMMR and pMMR protein expression in the lesion group were 39.00％and 70.00％,respectively,while those in the adjacent cancer group were 11.00％and 89.00％,respectively.There were significant difference compared between the lesion group and the adjacent cancer group(P＜0.05).The positive rate of PD-L1 protein expression in the lesion group were 25.00％,while that in the adjacent cancer group were 80.00％.The expression of PD-L1 protein in the lesion group were significantly lower than that in the adjacent cancer group(P＜0.05).There were significant differences in the positive rates of MMR and PD-L1 protein expression among patients with different histological differentiation,clinical stages,and lymph node metastasis(P＜0.05),while there were no significant differences in the positive rates of MMR and PD-L1 protein expression among patients of different genders,ages,and disease sites(P＞0.05).Spearman analysis showed there were correlation between the expression of MMR and PD-L1 proteins in colorectal cancer tissues and clinical pathological features such as histological differentiation,clinical staging,and lymph node metastasis(P＜0.05).Conclusion:Low expression of MMR and PD-L1 proteins are commonly observed in colorectal cancer tissues.The expression of MMR and PD-L1 proteins in colorectal cancer tissues are correlated with clinical pathological features such as histological differentiation,clinical staging,and lymph node metastasis.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

With the continuous advancement of educational technology and the expanding scope of medical education,the limitations of traditional teaching models in clinical hematology laboratory instruction have become increasingly evident.To address the demands of cultivating laboratory medicine professionals in the new era,an innovative teaching approach has been explored using the"Clinical Hematology Laboratory"course at Xi'an Medical College as a practical platform,aiming to enhance the professional competence of laboratory medicine students.Guided by the Outcome-Based Education(OBE)concept,this study integrates diverse teaching methodologies,including Problem-Based Learning(PBL),Case-Based Learning(CBL),flipped classroom,and virtual simulation,to construct a student-centered,competency-oriented teaching system.Through the optimization of teaching objectives and the strategic combination of instructional methods,this research provides novel insights and practical paradigms for clinical hematology laboratory education,thereby contributing to the sustainable development of laboratory medicine training.

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

The telomere structure in the cell nucleus is crucial for maintaining the stability and functions of chromosomes.Telomerase is a ribonucleoprotein reverse transcriptase,which catalyzes the elongation of telomeres using its own RNA as a template,thereby counteracting the shortening of telomeres caused by chromosome replication and cell division.Due to its overexpression in over 85％of malignant tumor cells,telomerase has emerged as a highly promising biomarker and a novel target for cancer therapy.In recent years,given the importance of precise quantification of telomerase activity in guiding medical diagnosis and treatment strategies,researchers have developed various high-performance telomerase detection techniques.Among these,electrochemical biosensing technique has cause much attention due to its high sensitivity,operational convenience,rapid response,and ease of miniaturization.This paper focused on the latest advances in electrochemical sensing technique for detection of telomerase activity,aiming to provide inspiration for designing novel telomerase activity detection strategies by elucidating three unique properties of telomerase primer extension products.

A method for determination and targeted screening of diflorasone components in health products using ultra performance liquid chromatography-quadrupole time of flight mass spectrometry(UPLC-Q-TOF/MS)was established.Four representative diflorasone and esters(diflorasone,diflorasone diacetate,diflorasone-17-propionate,and diflorasone-21-propionate)were selected to optimize the pretreatment conditions,and 10 mL of extraction solvent dosage,15 min of extraction time and 5 g of salting-out agent as the optimal conditions were selected by response surface methodology.The results showed that the four analytes exhibited good linearity within the concentration range of 2.0?100 μg/L with the chromatographic peak area,and the correlation coefficients(R2)were all greater than 0.9990,while the results of recovery and relative standard deviation could satisfy the requirements of determination.The common characteristic ions of diflorasone and esters werem/z121 andm/z335,and their specific structures were obtained by analyzing the cleavage pathway based on the optimized determination conditions.A targeted screening method for other esters of diflorasone based on characteristic ions guidance strategy was established.This method had many advantages such as high efficiency,high sensitivity and good reproducibility,and could be used for targeted screening of diflorasone and esters in health products.The developed characteristic ion guided strategy could be employed to construct mass spectral databases for various glucocorticoids,enabling comprehensive targeted screening across a broad range of compounds.

Objective To explore the relationship between platelet-to-leukocyte ratio(PLR)and neutro-phil-to-lymphocyte ratio(NLR)and fibrinogen(Fib)levels in the peripheral blood of stroke patients and deep vein thrombosis(DVT)of the lower limbs,as well as their predictive value for wether DVT occurred in stroke patients.Methods A total of 106 stroke patients admitted to the hospital from January 1,2022 to January 30,2024 were retrospectively selected as the research subjects.According to the occurrence of DVT in the pa-tients,they were divided into the DVT group(n=38)and the non-DVT group(n=68),and the levels of PLR,NLR and Fib in the two groups were compared.Multivariate Logistic regression was used to analyze the influencing factors of DVT in stroke patients,and the receiver operating characteristic(ROC)curve was used to analyze the predictive value of PLR,NLR and Fib for DVT in stroke patients.Results The proportions of patients in the DVT group with NIHSS score＞14 points,GCS score＞8 points,and dehydrating drug use time＞5 days were higher than those in the non-DVT group(P＜0.05),and the levels of PLR,NLR and Fib were higher than those in the non-DVT group(P＜0.05).The results of Logistic regression analysis showed that the upregulation of PLR,NLR and Fib levels were all risk factors for DVT in stroke patients(P＜0.05).ROC curve analysis showed that the area under the curve(AUC)of the combined prediction of DVT in stroke patients by PLR,NLR and Fib was 0.890,with a sensitivity of 81.62％and a specificity of 88.78％.The com-bined detection AUC was higher than that predicted separately by PLR,NLR and Fib(Z=2.768,3.424,3.657,all P＜0.05).Conclusion Peripheral blood PLR,NLR and Fib levels are closely related to the occur-rence of DVT in stroke patients.]The combined application of PLR,NLR and Fib has a high predictive value in the occurrence of DVT in stroke patients and can be used as an effective biomarker to predict DVT occur-rence.

Fibroblast growth factor,as a critical protein regulating cell growth and differentiation,exhibits aberrant signaling closely associated with various pathological pathologies,including cancer.Among the members of the fibroblast growth factor family,fibroblast growth factor 9(FGF9)has been identified as a critical player in cancer initiation and progression.While numerous studies have investigated the molecular mechanisms of FGF9 individually,comprehensive reviews addressing its impact in cancer remain scarce.This article systematically reviews the functional mechanisms and regulatory networks of FGF9 in cancer,with a focus on its roles in common malignancies such as lung cancer,liver cancer,gastric cancer,colorectal cancer,breast cancer,and ovarian cancer.The aim is to facilitate translational research on FGF9 for targeted cancer diagnosis and therapy.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.