Abstract: To explore the molecular mechanism by which long non-coding RNA Surfactant Associated 1 Pseudogene(SFTA1P) promotes the proliferation and migration of clear cell renal cell carcinoma(ccRCC) cells by regulating the microRNA-182-5p(miR-182-5p)/fibronectin 1(FN1) pathway. Methods: GEPIA2 software was utilized to analyze the expression ofSFTA1Pin ccRCC tissues from the TCGA database. Quantitative real-time PCR(qPCR) was employed to detect the expression ofSFTA1Pin ccRCC tissues, normal kidney tissues and ccRCC cell lines. A subcellular localization experiment was performed to explore the localization ofSFTA1Pwithin the human renal cell adenocarcinoma cell line(ACHN) derived from ccRCC. ACHN cells were then divided into the following groups: si-Con group, si-SFTA1P #2 group, mimic NC group, miR-182-5p mimic group, anti-miR-Con group, anti-miR-182-5p group, anti-miR-182-5p+si-FN1 group, si-Con+anti-miR-Con group, si-SFTA1P #2+anti-miR-Con group, and si-SFTA1P #2+anti-miR-182-5p group. CCK-8 and Transwell chamber experiments were conducted to assess cell proliferation and migration abilities. qPCR, Western blot, and dual-luciferase reporter assays were employed to elucidate the regulatory interactions amongSFTA1P,miR-182-5p, andFN1. Results: Analysis of The Cancer Genome Atlas(TCGA) database indicated thatSFTA1Pwas overexpressed in ccRCC tissues(P<0.05). When compared to normal kidney tissues,SFTA1Pexpression was markedly elevated in ccRCC tissues(P<0.01). Furthermore, the expression levels ofSFTA1Pin ccRCC cell lines 786-O, SN12-PM6, ACHN, and A498 were significantly higher than those in human renal proximal tubule cells(HK-2)(allP<0.01). Subcellular localization experiments revealed thatSFTA1Ppredominantly localized in the cytoplasm of ACHN cells. Compared to the si-Con group, the si-SFTA1P #2 group exhibited a significant reduction in proliferation and migration abilities of ACHN cells, accompanied by a decrease inFN1mRNA and protein expression(P<0.05). Compared to the mimic NC group, the expression ofFN1mRNA and protein in ACHN cells in the miR-182-5p mimic group reduced(P<0.01). In comparison to the anti-miR-Con group, the expression levels ofFN1mRNA and protein in ACHN cells were significantly elevated in the anti-miR-182-5p group. Additionally, there was a significant enhancement in both cell proliferation and migration capabilities(P<0.05). Conversely, the proliferation and migration abilities of ACHN cells in the anti-miR-182-5p+si-FN1 group were significantly reduced compared to the anti-miR-182-5p group(P<0.05). Furthermore, relative to the si-SFTA1P #2+anti-miR-Con group, the ACHN cells in the si-SFTA1P #2+anti-miR-182-5p group demonstrated increased proliferation and migration abilities, along with elevatedFN1mRNA and protein expression levels(P<0.05). Conclusion SFTA1Pexhibits elevated expression levels in ccRCC and facilitates the proliferation and migration of ccRCC cells through the modulation of themiR-182-5p/FN1signaling pathway.

Methods: This retrospective study analyzed 32 consecutive IDS patients who underwent UEDD surgery. Clinical features, laboratory data (erythrocyte sedimentation rate and C-reactive protein), and treatment outcomes were analyzed. Results: Definite microorganisms were identified in 27 patients (84.3%), with 24 (88.9%) meeting cure criteria. The cure rate was significantly higher in the detected pathogen group compared to the undetected pathogen group (88.9% vs. 80%; χ²=19.36, p<0.0001). Metagenomic next generation sequencing (mNGS) provided faster diagnosis (41.72±6.81 hours) compared to tissue culture (95.74±35.47 hours, p<0.05). The predominant causative pathogen was Mycobacterium tuberculosis, followed by Staphylococcus aureus. Significant improvements were observed in Visual Analog Scale pain scores, from a mean of 7.9 preoperatively to 1.06 at 1 year postoperatively. The Oswestry Disability Index revealed a similar trend, showing significant improvement (p<0.05). Conclusions UEDD is a viable alternative to traditional open surgery for managing IDS in high-risk patients. UEDD offers a dual therapeutic-diagnostic advantage during the initial admission phase, enabling simultaneous debridement, neurological decompression, and targeted biopsy in a single intervention. Compared with traditional tissue culture, mNGS enables rapid microbiological diagnosis and extensive pathogen coverage.

Methods: This retrospective study analyzed 32 consecutive IDS patients who underwent UEDD surgery. Clinical features, laboratory data (erythrocyte sedimentation rate and C-reactive protein), and treatment outcomes were analyzed. Results: Definite microorganisms were identified in 27 patients (84.3%), with 24 (88.9%) meeting cure criteria. The cure rate was significantly higher in the detected pathogen group compared to the undetected pathogen group (88.9% vs. 80%; χ²=19.36, p<0.0001). Metagenomic next generation sequencing (mNGS) provided faster diagnosis (41.72±6.81 hours) compared to tissue culture (95.74±35.47 hours, p<0.05). The predominant causative pathogen was Mycobacterium tuberculosis, followed by Staphylococcus aureus. Significant improvements were observed in Visual Analog Scale pain scores, from a mean of 7.9 preoperatively to 1.06 at 1 year postoperatively. The Oswestry Disability Index revealed a similar trend, showing significant improvement (p<0.05). Conclusions UEDD is a viable alternative to traditional open surgery for managing IDS in high-risk patients. UEDD offers a dual therapeutic-diagnostic advantage during the initial admission phase, enabling simultaneous debridement, neurological decompression, and targeted biopsy in a single intervention. Compared with traditional tissue culture, mNGS enables rapid microbiological diagnosis and extensive pathogen coverage.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

Methods: This retrospective study analyzed 32 consecutive IDS patients who underwent UEDD surgery. Clinical features, laboratory data (erythrocyte sedimentation rate and C-reactive protein), and treatment outcomes were analyzed. Results: Definite microorganisms were identified in 27 patients (84.3%), with 24 (88.9%) meeting cure criteria. The cure rate was significantly higher in the detected pathogen group compared to the undetected pathogen group (88.9% vs. 80%; χ²=19.36, p<0.0001). Metagenomic next generation sequencing (mNGS) provided faster diagnosis (41.72±6.81 hours) compared to tissue culture (95.74±35.47 hours, p<0.05). The predominant causative pathogen was Mycobacterium tuberculosis, followed by Staphylococcus aureus. Significant improvements were observed in Visual Analog Scale pain scores, from a mean of 7.9 preoperatively to 1.06 at 1 year postoperatively. The Oswestry Disability Index revealed a similar trend, showing significant improvement (p<0.05). Conclusions UEDD is a viable alternative to traditional open surgery for managing IDS in high-risk patients. UEDD offers a dual therapeutic-diagnostic advantage during the initial admission phase, enabling simultaneous debridement, neurological decompression, and targeted biopsy in a single intervention. Compared with traditional tissue culture, mNGS enables rapid microbiological diagnosis and extensive pathogen coverage.

Objective To investigate the safety and efficacy of super-selective arterial embolization in the treatment of abdominal wall hematoma.Methods The clinical data of 11 patients with abdominal wall hematoma,who were admitted to the Northern Jiangsu People's Hospital of China from January 2018 to December 2023,were retrospectively analyzed.All patients received angiography together with super-selective arterial embolization.The effectiveness of embolization treatment was evaluated by the technical success rate and therapeutic effect,and the safety was evaluated by the incidence of complication.Results The median age of the 11 patients was 70 years,91％were female,with a body mass index(BMI)of 25.1 kg/m2,subcutaneous fat thickness of 2.8 cm,and international normalized ratio(INR)of 1.12.DSA showed that 8 patients(72％)had active bleeding signs,3 patients(28％)had no active bleeding signs.Under DSA,a total of 18 responsible vessels,including 6 lumbar arteries(33.3％),5 deep circumflex iliac arteries(27.7％),5 inferior epigastric arteries(27.7％)and 2 iliolumbar arteries(11.3％),were identified and were treated with embolization.The median time spent for operation was 80 minutes.The technical success rate was 100％and the clinical effective rate was 91％.No operation-related major complications occurred,and the median hospital stay was 6 days.Conclusion For the abdominal wall hematoma in aged,obesity patients with underlying diseases,super-selective arterial embolization is a therapeutic method with high technical success rate,high clinical effective rate and satisfactory clinical safety.

Objective To discuss the clinical efficacy of microwave ablation(MWA)combined with percutaneous vertebroplasty(PVP),radiofrequency ablation(RFA)combined with PVP,and simple PVP in the treatment of vertebral metastatic tumors.Methods A total of 65 patients with vertebral metastatic tumors,who were admitted to the Northern Jiangsu People's Hospital of China to receive treatment from January 2019 to June 2023,were enrolled in this study.The patients were divided into MWA plus PVP group(M+P group,n=25,27 diseased vertebral bodies in total),RFA plus PVP group(R+P group,n=20,23 diseased vertebral bodies in total),and simple PVP group(P group,n=20,24 diseased vertebral bodies in total).Visual analog scale(VAS)score was used to assess the preoperative pain degree and the postoperative relief degree.Bone cement distribution and leakage at one week after surgery were evaluated.Results Successful operation was accomplished in all of the patients.No serious procedure-related complications occurred in all the patients of three groups.In R+P group,P group and M+P group,the preoperative mean VAS scores were(8.48±0.80)points,(8.57±0.98)points and(8.20±1.00)points respectively;the differences among the three groups were not statistically significant(P＞0.05).One week after operation,the pain was significantly relieved in all the patients of three groups;the mean VAS scores in R+P group,P group and M+P group were(4.10±0.85)points,(3.17±0.93)points and(2.44±1.23)points respectively,and the reduction in VAS score was most pronounced in M+P group(P＜0.05).Six months after operation;the mean VAS scores in R+P group,P group and M+P group were(1.87±0.84)points,(4.60±1.09)points and(1.48±0.71)points respectively;and the reduction in VAS score was most pronounced in the M+P group(P＜0.05).The used amount of bone cement in M+P group,R+P group and P group was(7.54±1.44)mL,(5.48±1.12)mL and(4.59±1.56)mL respectively,the difference among the three groups was statistically significant(P＜0.05).The vascular leakage rate(34.8％)and non-vascular leakage rate(52.2％)in P group were remarkably higher than those in R+P group and in M+P group(P＜0.05).No statistically significant difference in the rate of cement leakage existed between R+P group and M+P group(P＞0.05).Conclusion For the treatment of vertebral metastases,MW A plus PVP is superior to RFA plus PVP in pain relief rate.

Objective To develop and validate a machine learning-based predictive model to assess the in-hospital mortality risk of patients with myocardial infarction(MI)complicated by heart failure(HF)undergoing percutaneous coronary intervention(PCI).Methods This retrospective study analyzed MI patients with HF who underwent PCI at The First Affiliated Hospital of Xinjiang Medical University from January 2019 to January 2023.Patient data,including demographic characteristics,vital signs,laboratory test results,imaging parameters and medication use,were collected and randomly divided into a training set(70％)and a validation set(30％).The extreme gradient boosting(XGBoost)model was used to identify variables significantly associated with in-hospital mortality,and the Shapley additive explanations(SHAP)model was applied to assess feature importance.A predictive model was then constructed using univariate and multivariate Logistic regression analyses.Model performance was evaluated using receiver operating characteristic(ROC)curves,area under the curve(AUC)values,calibration curves,and decision curve analysis.Finally,a nomogram was developed for intuitive risk assessment.Results A total of 1 214 MI patients with HF were included in the study,with a median age of 64 years.The in-hospital mortality rate was 7.41％(90 deaths).XGBoost feature selection identified ten key predictive variables:age,myoglobin,albumin,fasting blood glucose,N-terminal pro-B-type natriuretic peptide(NT-proBNP),diabetes mellitus,creatinine,cystatin C,procalcitonin,and left ventricular ejection fraction.Based on these variables,a Logistic regression model was developed,with seven final predictors:age,diabetes mellitus,creatinine,fasting blood glucose,cystatin C,NT-proBNP,and albumin.The model demonstrated high predictive accuracy,with AUC value of 0.869(95％CI:0.84-0.89)in the training set and 0.827(95％CI:0.79-0.85)in the validation set.The calibration curve indicated that the predicted probabilities were consistent with the actual observed outcomes,and decision curve analysis showed that the model had a high net benefit across various decision thresholds.Conclusion This study developed a machine learning-based predictive model incorporating Logistic regression to assess the in-hospital mortality risk of MI patients with HF undergoing PCI.The model demonstrated high predictive performance and clinical utility.The nomogram derived from this model provides an intuitive tool for individualized risk assessment,aiding clinicians in the early identification of high-risk patients,optimizing intervention strategies,and improving patient outcomes.

Objective To construct and validate machine learning-based models to predict the risk of acute kidney injury(AKI)following percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 2 315 STEMI patients who underwent PCI between January 2020 and June 2023 were included;306(13.2％)of them developed AKI.Baseline variables were screened using LASSO regression,with the optimal λ value selected via 10-fold cross-validation to identify AKI-associated features.Subsequently,eight distinct machine learning models were constructed and evaluated for their predictive performance.SHAP value analysis was employed to assess the impact of key variables on model predictions.Results LASSO regression identified seven variables significantly associated with AKI,including age,multivessel disease,preoperative creatinine,heart failure,white blood cell count,hemoglobin,and albumin levels.Among all the models,the light gradient boosting machine(LGBM)and extreme gradient boosting(XGB)demonstrated the best predictive performance,with training set AUCs being 0.899(95％CI:0.877-0.921)and 0.893(95％CI:0.868-0.918),and validation set AUCs being 0.809(95％CI:0.763-0.856)and 0.871(95％CI:0.833-0.909),respectively.SHAP analysis revealed that albumin,age,preoperative creatinine,and white blood cell count were the primary contributors to AKI risk.Conclusion This study successfully developed and validated machine learning-based predictive models capable of effectively identifying the risk of AKI following PCI in STEMI patients,thus providing valuable support for clinical decision-making.