Mineral oil contaminants composed of saturated hydrocarbons(MOSH)and aromatic hydrocarbons(MOAH)are commonly found in edible oils and related processed foods.Currently,the analysis of mineral oils primarily employs the liquid chromatography-gas chromatography-flame ionization detector(LC-GC-FID)method.Liquid chromatography is used to purify and separate MOSH and MOAH from interfering substances,and the interface technology transfers MOSH or MOAH into different GC channels for quantitative analysis.The MOSH and MOAH chromatograms typically exhibit an irregular hump shape,with sharp peaks above the hump representing natural hydrocarbon interferences,which usually do not affect the identification of the hump profile.However,when the purification of interferences is incomplete,they can form one or more gaps above the hump,interfering with the accurate judgment and delineation of the hump profile,and leading to poor reproducibility of analysis results of mineral oil.In this study,an algorithm that mimicked the manual drawing of the hump shape or contour was proposed for automatically determining the mineral oil hump contour(i.e.,the lower envelope line).The algorithm used a multiple second-order difference quotient filtering method to identify and remove the gaps above the hump.The method involved first searching and determining the lowest value of the mineral oil hump,which was the valley point sequence,and then applying second-order difference quotient filtering to the valley point sequence.Compared to the hump,the second-order difference quotient of sharp peaks was a significantly larger negative value.By filtering out the points in the valley point sequence with larger negative second-order difference quotients(or multiple second-order difference quotients),the sharp peaks above the hump were removed.To verify the accuracy of the algorithm,42 different types of samples,including edible oils and milk powders were analyzed,using both the automatic algorithm and manual methods.The results showed that there were no significant differences in the detected mineral oil contents between these two methods.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Aim To investigate the effect of long-chain non-coding RNA(lncRNA)GS1-124K5.4 targeting regulation of PRDX6 on proliferation,migration and in-vasion of lung squamous carcinoma(LUSC)cells and the underlying mechanism.Methods The expression level of lncRNA GS1-124K5.4 in lung cancer tissues and adjacent tissues of 60 patients with LUSC were de-termined by fluorescence in situ hybridization.The ex-pression level of lncRNA GS1-124K5.4 in human nor-mal lung cells and LUSC cells were determined by qRT-PCR.Two kinds of LUSC cells(NCI-H 1703,SK-MES-1)with highest expression level of lncRNA GS1-124K5.4 were selected for subsequent experi-ments.The distribution of lncRNA GS1-124K5.4 in cells was studied by fluorescence in situ hybridization and prokaryotic separation.The effect of knockdown of lncRNA GS1-124K5.4 on proliferation of NCI-H1703 and SK-MES-1 cells was studied by CCK-8 experiment and cell clone formation experiment;the effect of knockdown of lncRNA GS1-124K5.4 on migration of NCI-H1703 and SK-MES-1 cells was studied by cell scratch experiment and Transwell cell migration experi-ment;and the effect of knockdown of lncRNA GS1-124K5.4 on invasion of NCI-H1703 and SK-MES-1 cells was studied by Transwell invasion experiment.The protein to be bound by lncRNA GS1-124K5.4 was detected by RNA pull-down combined with mass spec-trometry and immune-precipitation.The effect of knockdown of lncRNA GS1-124K5.4 targeting PRDX6 on proliferation,migration and invasion of NCI-H1703 and SK-MES-1 cells was studied.Results(1)The fluorescence intensity of lncRNA GS1-124K5.4 in lung squamous cell carcinoma increased compared with that in adjacent tissues(P＜0.05),and the expression of lncRNA GS1-124K5.4 was related with lymph node metastasis and clinical stage(P＜0.05).(2)The ex-pression level of lncRNA GS1-124K5.4 in NCI-H1703,NCI-H520 and SK-MES-1 cells significantly increased(P＜0.05).(3)The result of fluorescence in situ hybridization experiment and nucleoplasm sepa-ration experiment showed that lncRNA GS1-124K5.4 was mainly distributed in cell nucleus.(4)The prolif-eration,migration and invasion ability of NCI-H1703 and SK-MES-1 cells with knockdown of lncRNA GS1-124K5.4 significantly decreased(P＜0.05).(5)PRDX6 protein to be bound to LncRNA GS1-124K5.4 was determined by RNA pull-down combined with mass spectrometry and immunoprecipitation.(6)The prolif-eration,migration and invasion ability of NCI-H1703 and SK-MES-1 cells with overexpression of lncRNA GS1-124K5.4 significantly increased(P＜0.05);the proliferation,migration and invasion ability of NCI-H1703 and SK-MES-1 cells with knockdown of PRDX6 significantly decreased(P＜0.05);the proliferation,migration and invasion ability of NCI-H1703 and SK-MES-1 cells with overexpression of lncRNAGS1-124K5.4 and knockdown of PRDX6 showed no signifi-cant change(P＞0.05).Conclusions LncRNA GS1-124K5.4 is highly expressed in lung squamous cell carcinoma,and it may promote the proliferation,migration and invasion of lung squamous carcinoma cells by targeting the expression of PRDX6 protein.

Objectives To explore the causal relationship between asthma-related pneumonia and heart failure(HF)by using two-sample Mendelian randomization(MR)analysis.Methods The causal relationship between asthma-related pneumonia and HF were systematically evaluated through two-sample MR analysis based on publicly available Genome-Wide Association Study data.Inverse variance weighted(IVW),MR-Egger,weighted median,weighted mode,and simple mode methods were used.Different models were used to analyze sensitivity.Testing approaches were conducted to assess the robustness of the results.Results IVW analysis results showed that there was a causal relationship between asthma-related pneumonia and HF risk(OR=1.113,95％CI:1.027-1.206,P=0.009).HF was not found to have a causal effect on asthma-related pneumonia risk based on IVW analysis(OR=1.018,95％CI:0.780-1.328,P=0.893).The variance used in all MR analyses showed no heterogeneity or horizontal pleiotropy.The leave-one-out analysis revealed that no single nucleotide polymorphism disproportionately influenced the results,further confirming the credibility of the bidirectional MR findings.Conclusion This study established a causal relationship between asthma-related pneumonia and HF risk.No clear causal relationship between HF and asthma-related pneumonia risk was found.

Objective:To develop and validate CT radiomics models based on machine learning for predicting recurrence of chronic subdural hematoma (cSDH) after endoscopic treatment.Methods:A retrospective study was performed; 252 patients with cSDH who underwent endoscopic treatment in Department of Neurosurgery, the Second Affiliated Hospital of Soochow University from October 2016 to October 2024 were selected. The clinical and imaging data of these patients were collected, and these patients were divided into a training set ( n=176) and a validation set ( n=76) at a ratio of 7:3. Patients in both sets were further sub-divided into a recurrence group and a non-recurrence group based on whether they had recurrence within 3 months of discharge. (1) Radiomics features of cSDH on initial non-enhanced CT images were extracted using 3D-Slicer software. Optimal features were selected through univariate analysis and least absolute shrinkage and selection operator (LASSO) regression analysis; based on these optimal features, 3 machine learning algorithms (Logistic, support vector machine [SVM], and K-nearest neighbor [KNN]) were used to construct CT radiomics models. Differences in predictive performance of different radiomics models were compared by analyzing indicators such as sensitivity, specificity, and area under receiver operating characteristic (ROC) curve (AUC), and the best model was selected. (2) Based on the initial non-enhanced CT images, cSDH was classified into homogeneous type, laminar type, septated type, and trabecular type according to Nakaguchi classification system; combined these cSDH typing with clinical features (clinical Markwalder's grade and bilateral hematoma), univariate analysis and multivariate Logistic regression analysis were used to screen the independent risk factors for cSDH recurrence. Based on these factors, the 3 machine learning algorithms (Logistic, SVM, KNN) were used to construct hematoma typing-clinical feature models; differences in predictive performance of different hematoma typing-clinical feature models were compared by analyzing indicators such as sensitivity, specificity, and AUC, and the best model was selected. (3) DeLong's test was used to compare the ROC curve differences between the CT radiomics model and hematoma typing-clinical feature model. Decision curve analysis was used to compare the effective scope of the CT radiomics model and hematoma typing-clinical feature model. Results:(1) Seven optimal CT radiomics features based on wavelet transform were obtained after univariate analysis and LASSO regression: one gray-level dependence matrix feature, one first-order energy feature, two gray-level co-occurrence matrix features, two gray level size zone matrix features, and one gray-level run-length matrix feature. The KNN model constructed based on these 7 optimal features had the best performance in predicting cSDH recurrence, with an AUC of 0.845, a sensitivity of 0.833, a specificity of 0.857, a recall rate of 0.833, and an F1 score of 0.476 in patients from the validation set. (2) Three independent risk factors for cSDH recurrence were screened out through univariate analysis and multivariate Logistic regression analysis: hematoma Nakaguchi classification, Markwalder's grade, and bilateral hematoma. Logistic model constructed based on these 3 factors had the best performance in predicting cSDH recurrence, with an AUC of 0.675, a sensitivity of 0.609, a specificity of 0.654, a recall rate of 0.609, and an F1 score of 0.311 in patients from the validation set. (3) DeLong's test showed that the AUC of the CT radiomics model was significantly greater than that of the hematoma typing-clinical feature model in patients from the training set and validation set ( P=0.027 and P=0.035). Decision curve analysis showed that in the CT radiomics model, the net benefit of the model was >0 when the risk threshold was 0.05-0.95; in the hematoma typing-clinical feature model, the net benefit of the model was >0 when the risk threshold was 0.05-0.55. Conclusion:The KNN model based on 7 CT radiomics features in this study can effectively predict the cSDH recurrence in patients after endoscopic treatment, and its performance is obviously better than that of hematoma typing-clinical feature model constructed in this study.

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Recent data suggest that vascular endothelial growth factor receptor inhibitor (VEGFRi) can enhance the anti-tumor activity of the anti-programmed cell death-1 (anti-PD-1) antibody in colorectal cancer (CRC) with microsatellite stability (MSS). However, the comparison between this combination and standard third-line VEGFRi treatment is not performed, and reliable biomarkers are still lacking. We retrospectively enrolled MSS CRC patients receiving anti-PD-1 antibody plus VEGFRi (combination group, n=54) or VEGFRi alone (VEGFRi group, n=32), and their efficacy and safety were evaluated. We additionally examined the immune characteristics of the MSS CRC tumor microenvironment (TME) through single-cell and spatial transcriptomic data, and an MSS CRC immune cell-related signature (MCICRS) that can be used to predict the clinical outcomes of MSS CRC patients receiving immunotherapy was developed and validated in our in-house cohort. Compared with VEGFRi alone, the combination of anti-PD-1 antibody and VEGFRi exhibited a prolonged survival benefit (median progression-free survival: 4.4 vs. 2.0 months, P=0.0024; median overall survival: 10.2 vs. 5.2 months, P=0.0038) and a similar adverse event incidence. Through single-cell and spatial transcriptomic analysis, we determined ten MSS CRC-enriched immune cell types and their spatial distribution, including naive CD4⁺ T, regulatory CD4⁺ T, CD4⁺ Th17, exhausted CD8⁺ T, cytotoxic CD8⁺ T, proliferated CD8⁺ T, natural killer (NK) cells, plasma, and classical and intermediate monocytes. Based on a systemic meta-analysis and ten machine learning algorithms, we obtained MCICRS, an independent risk factor for the prognosis of MSS CRC patients. Further analyses demonstrated that the low-MCICRS group presented a higher immune cell infiltration and immune-related pathway activation, and hence a significant relation with the superior efficacy of pan-cancer immunotherapy. More importantly, the predictive value of MCICRS in MSS CRC patients receiving immunotherapy was also validated with an in-house cohort. Anti-PD-1 antibody combined with VEGFRi presented an improved clinical benefit in MSS CRC with manageable toxicity. MCICRS could serve as a robust and promising tool to predict clinical outcomes for individual MSS CRC patients receiving immunotherapy.
Humans ; Colorectal Neoplasms/drug therapy* ; Male ; Female ; Immunotherapy ; Middle Aged ; Aged ; Tumor Microenvironment/immunology* ; Retrospective Studies ; Microsatellite Instability ; Transcriptome ; Single-Cell Analysis ; Programmed Cell Death 1 Receptor/immunology* ; Gene Expression Profiling ; Immune Checkpoint Inhibitors/therapeutic use* ; Adult ; Receptors, Vascular Endothelial Growth Factor/antagonists & inhibitors*

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome