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.

ObjectiveTo establish a risk recognition model for coronary artery stenosis by using a machine learning method and to identify the key causative factors. MethodsPatients aged ≥18 years，diagnosed with coronary heart disease through coronary angiography from January 2013 to May 2020 in two prominent hospitals in Shanxi Province， were continuously enrolled. Logistic regression，back propagation neural network （BPNN）， and random forest（RF）algorithms were used to construct models for detecting the causative factors of coronary artery stenosis. Sensitivity （TPR）， specificity （TNR）， accuracy （ACC）， positive predictive value （PV+）， negative predictive value （PV-）， area under subject operating characteristic curve （AUC）， and calibration curve were used to compare the discrimination and calibration performance of the models. The best model was then employed to predict the main risk variables associated with coronary stenosis. ResultsThe RF model exhibited superior comprehensive performance compared to logistic regression and BPNN models. The TPR values for logistic regression，BPNN，and RF models were 75.76%， 74.30%， and 93.70%， while ACC values were 74.05%， 72.30%， and 79.49%， respectively. The AUC values were：logistic regression 0.739 9； BPNN 0.723 1； RF 0.752 2. Manifestations such as chest pains，abnormal ST segments on ECG，ventricular premature beats with hypertension， atrial fibrillation， regional wall motion abnormalities（RWMA） by color echocardiography， aortic regurgitation（AR）， pulmonary insufficiency （PI）， family history of cardiovascular diseases，and body mass index（BMI）were identified as top ten important variables affecting coronary stenosis according to the RF model. ConclusionsRandom forest model shows the best comprehensive performance in identification and accurate assessment of coronary artery stenosis. The prediction of risk factors affecting coronary artery stenosis can provide a scientific basis for clinical intervention and help to formulate further diagnosis and treatment strategies so as to delay the disease progression.

Objective To screen a verification method for influenza virus inactivation in MDCK cells, and apply it to the sample detection before and after influenza virus inactivation, so as to provide a reliable method for the quality detection of influenza vaccines. Methods Four types of influenza viruses adapted to MDCK cells, B/Yamagata(BY), B/Victoria(BV),H1N1 and H3N2, were diluted to 10, 1, 0. 1, 0. 01, 0. 001, and 0. 000 1 lgCCID_(50)/mL separately, which were then inoculated into MDCK cells and cultured by changing the medium(discarding after adsorption for 1. 5 h and adding virus culture medium, passaging every 3 d for a total of 3 generations), rehydration method(adding virus culture medium directly after adsorption for 1. 5 h, passaging every 3 d for a total of 3 generations), and method in European Pharmacopoeia(passaging every 4 d for a total of 3 generations). The cytopathic effect(CPE) was observed every day, the virus solutions of different passages were harvested, and the hemagglutinin(HA) titers were detected to determine the optimum inactivation verification method. Finally, the optimum inactivation verification method was used to detect samples before and after inactivation of influenza virus. Results Influenza virus could be detected at the titer of 0. 1-1 lgCCID_(50)/mL by both changing medium method and rehydration method, while influenza virus could be detected in the titer range of 1-10 lgCCID_(50)/mL by test protocol in European Pharmacopoeia, and the titer of HA detected by rehydration method was higher than those by the other two methods. Therefore, rehydration method was determined as the optimum inactivation verification method. The samples detected by rehydration method were all positive before influenza virus inactivation and negative after virus inactivation.Conclusion Rehydration method is the optimum method to verify the influenza virus inactivation in MDCK cells, which can be used to detect the quality of influenza vaccines.

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.

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.

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.

Objective To establish a simultaneous detection approach for 34 emerging contaminants(ECs)in tap water by liquid chromatography-tandem mass spectrometry(HPLC-MS/MS).Human health risk assessment was performed according to the detection results from 43 tap water samples.Methods Tap water samples were concentrated and extracted by solid phase extraction,and then blown to near dry by nitrogen at 40℃.The sample extracts were dissolved in methanol-water solution(95:5,VN)to 0.5 mL for analyzing.Agilent Jet Stream Electrospray Ionization(AJS ESI)and the multiple reaction monitoring(MRM)mode were performed for MS to acquire the data of 34 ECs.A database including precursor ion,product ion and retention times was established accordingly.Results The average linear correlation coefficients(r)of 34 kinds of ECs was 0.995 9.The limits of detection were 0.01～0.60 ng/L and the recoveries were between 60.7％and 119.8％.The intra-group precisions were between 0.05％～9.89％and the intra-day precisions were between 0.20％～14.40％for the spiked samples.The method was applied to analyze 43 tap water samples and a total of 15 ECs were detected.According to the results,the detection rate of caffeine was the highest(84％),and the concentration range was ND～74.42 ng/L.Among all the ECs detected,1,2,3-benzotriazole had the highest concentration(ND～361.15 ng/L),where detection rate was 44％.Humans may be exposed to these ECs by drinking the tap water.The human health risk assessments of 12 kinds of ECs were carried out,however,the estimated risk was negligible(risk quotient＜0.01).Conclusion The method is simple,highly sensitive and selective,and could meet the detection needs of ECs at trace level in tap water.There was no human health risk posed for ECs identified in 43 tap water samples analyzed by this method.