ER-mitochondria contact sites regulate hepatic lipogenesis via Ip3r-Grp75-Vdac complex recruiting Seipin.

BACKGROUND: Mitochondria and endoplasmic reticulum (ER) contact sites (MERCS) constitute a functional communication platform for ER and mitochondria, and they play a crucial role in the lipid homeostasis of the liver. However, it remains unclear about the exact effects of MERCs on the neutral lipid synthesis of the liver. METHODS: In this study, the role and mechanism of MERCS in palmitic acid (PA)-induced neutral lipid imbalance in the liver was explored by constructing a lipid metabolism animal model based on yellow catfish. Given that the structural integrity of MERCS cannot be disrupted by the si-mitochondrial calcium uniporter (si-mcu), the MERCS-mediated Ca2+ signaling in isolated hepatocytes was intercepted by transfecting them with si-mcu in some in vitro experiments. RESULTS: The key findings were: (1) Hepatocellular MERCs sub-proteome analysis confirmed that, via activating Ip3r-Grp75-voltage-dependent anion channel (Vdac) complexes, excessive dietary PA intake enhanced hepatic MERCs. (2) Dietary PA intake caused hepatic neutral lipid deposition by MERCs recruiting Seipin, which promoted lipid droplet biogenesis. (3) Our findings provide the first proof that MERCs recruited Seipin and controlled hepatic lipid homeostasis, depending on Ip3r-Grp75-Vdac-controlled Ca2+ signaling, apart from MERCs's structural integrity. Noteworthy, our results also confirmed these mechanisms are conservative from fish to mammals. CONCLUSIONS: The findings of this study provide a new insight into the regulatory role of MERCS-recruited SEIPIN in hepatic lipid synthesis via Ip3r-Grp75-Vdac complex-mediated Ca2+ signaling, highlighting the critical contribution of MERCS in hepatic lipid homeostasis.

An integrated machine learning model enhances delayed graft function prediction in pediatric renal transplantation from deceased donors.

BACKGROUND: Kidney transplantation is the optimal renal replacement therapy for children with end-stage renal disease; however, delayed graft function (DGF), a common post-operative complication, may negatively impact the long-term outcomes of both the graft and the pediatric recipient. However, there is limited research on DGF in pediatric kidney transplant recipients. This study aims to develop a predictive model for the risk of DGF occurrence after pediatric kidney transplantation by integrating donor and recipient characteristics and utilizing machine learning algorithms, ultimately providing guidance for clinical decision-making. METHODS: This single-center retrospective cohort study includes all recipients under 18 years of age who underwent single-donor kidney transplantation at our hospital between 2016 and 2023, along with their corresponding donors. Demographic, clinical, and laboratory examination data were collected from both donors and recipients. Univariate logistic regression models and differential analysis were employed to identify features associated with DGF. Subsequently, a risk score for predicting DGF occurrence (DGF-RS) was constructed based on machine learning combinations. Model performance was evaluated using the receiver operating characteristic curves, decision curve analysis (DCA), and other methods. RESULTS: The study included a total of 140 pediatric kidney transplant recipients, among whom 37 (26.4%) developed DGF. Univariate analysis revealed that high-density lipoprotein cholesterol (HDLC), donor after circulatory death (DCD), warm ischemia time (WIT), cold ischemia time (CIT), gender match, and donor creatinine were significantly associated with DGF (P < 0.05). Based on these six features, the random forest model (mtry = 5, 75%p) exhibited the best predictive performance among 97 machine learning models, with the area under the curve values reaching 0.983, 1, and 0.905 for the entire cohort, training set, and validation set, respectively. This model significantly outperformed single indicators. The DCA curve confirmed the clinical utility of this model. CONCLUSIONS: In this study, we developed a machine learning-based predictive model for DGF following pediatric kidney transplantation, termed DGF-RS, which integrates both donor and recipient characteristics. The model demonstrated excellent predictive accuracy and provides essential guidance for clinical decision-making. These findings contribute to our understanding of the pathogenesis of DGF.

Characterization of the components in plasma EVs unveiling the link between EVs-derived complement C3 with the severity and initial treatment response of profound sudden sensorineural hearing loss.

BACKGROUND: Sudden sensorineural hearing loss (SSNHL) is characterized by rapid, unexplained loss of hearing within a 72-hour period and exhibits a high incidence globally. Despite this, the outcomes of therapeutic interventions remain largely unpredictable, especially for those with profound hearing loss. Extracellular vesicles (EVs), nano-sized entities containing biological materials, are implicated in the development of numerous diseases. The specific relationship between EVs and both the severity and treatment effectiveness of SSNHL, however, is not well understood. METHODS: This study involved the analysis of medical records from the Department of Otolaryngology (September 1, 2020 - December 31, 2022) of patients diagnosed with SSNHL according to the 2015 Guidelines for Diagnosis and Treatment of Sudden Deafness in China. Peripheral blood samples from patients with various types of SSNHL before and after treatment were collected, alongside samples from healthy volunteers serving as controls. Plasma EVs were isolated using gel rejection chromatography and analyzed for concentration, marker presence, and morphology using Nanosight, Western blot, and transmission electron microscopy (TEM), respectively. Proteomics and miRNA assessments were conducted to identify differentially expressed proteins and miRNAs in the plasma EVs of SSNHL patients and healthy volunteers. Key proteins were further validated through Western blot analysis. Enzyme-linked immunosorbent assay (ELISA) was utilized to determine the levels of complement C3 in plasma EVs, and correlation analyses were performed with audiological data pre- and post-treatment. RESULTS: Plasma from SSNHL patients of varying types was collected and their EVs were successfully isolated and characterized. Proteomic analysis revealed that complement C3 levels in the plasma EVs of patients with profound SSNHL were significantly higher compared to healthy controls. Differential expression of miRNAs in plasma EVs and their related functions were also identified. The study found that the level of complement C3 in plasma EVs, but not the total plasma complement C3, positively correlated with the severity of SSNHL in patients exhibiting positive therapeutic responses, particularly in those with initially lower levels of EV-associated complement C3. After treatment, complement C3 level was decreased in patients with initially higher levels of EV-associated complement C3. No significant correlation was observed between changes in plasma EV-derived complement C3 levels and the degree of hearing loss in either responders or non-responders among patients with profound SSNHL. CONCLUSION: Differential profiles of proteins and miRNAs were identified in patients with profound SSNHL. Notably, plasma EV-derived complement C3 was linked to both the severity and early treatment effectiveness of patients with profound SSNHL.

[Effect of Plasma Epstein-Barr Virus Nucleic Acid Loads on the Clinical Features and Prognosis in Adult Secondary Hemophagocytic Lymphohistiocytosis].

OBJECTIVE: To investigate the effect of pre-treatment plasma Epstein-Barr virus (EBV) DNA copy number on the clinical features and prognosis of patients with adult secondary hemophagocytic lymphohistiocytosis(sHLH). METHODS: The clinical characteristics, survival rate, and prognostic factors of 171 patients with adult sHLH treated at Jiangsu Province Hospital from June 2017 to January 2022 were retrospectively analyzed in this study. Patients were divided into three groups, including the EBV DNA-negative group(<5.0×102 copies/ml), lower EBV-DNA loads group(5.0×102-8.51×104 copies/ml), and higher EBV-DNA loads group(＞8.51×104 copies/ml), according to pre-treatment plasma EBV-DNA copy number. Cox regression model was established for screening prognostic factors. Adult sHLH survival prediction model was constructed and realized through the nomogram based on EBV-DNA load after adjusted the factors affecting survival of etiology and treatment strategy.Concordance index (C-index) and calibration curves were calculated to verify model predictive and discriminatory capacity. RESULTS: Among 171 adult sHLH patients, 84 patients were not infected with EBV (EBV DNA-negative group), and 87 with EBV (EBV DNA-positive group, 48 lower EBV-DNA loads group and 39 higher EBV-DNA loads group). Consistent elevations in the levels of liver enzymes (ALT and AST), LDH, TG, ß 2-microglobulin and ferritin across the increasing of EBV-DNA load (all P <0.05), while the levels of fibrinogen decrease (P <0.001). The median follow-up time was 52 days (range 20-230 days), and 123 patients died. The overall survival (OS) rate of patients in EBV DNA-positive group was lower than that in EBV DNA-negative group (median OS: 40 days vs 118 days, P <0.001). Higher EBV-DNA loads had worse OS (median OS: 24 days vs 45 days vs 118 days, P <0.0001 for trend) compared to lower EBV-DNA loads and EBV DNA-negative group. Multivariate Cox analysis revealed that higher EBV-DNA loads (P =0.005), fibrinogen≤1.5 g/L (P ＝0.012), ferritin (P ＝0.041), associated lymphoma (P ＝0.002), and anti-tumor based strategy (P ＝0.001) were independent prognostic factors for OS. The C-indexes of 30 day, 90 days, 365 days survival rate were all greater than 0.8 of the nomogram model and calibration curves provided credibility to their predictive capability. Subgroup analysis showed that patients with higher EBV-DNA loads had a significantly worse prognosis in adult sHLH who were women, ferritin＞5 000 µg/L, ß2-microglobulin＞7.4 mmol/L and regardless of age, etiologies, HScore points. CONCLUSION: The EBV-DNA load is a strong and independent predictor for survival in patients with sHLH. The prognostic nomogram based on EBV-DNA loads was dependable and provides a visual tool for evaluating the survival of adult sHLH.

IVF laboratory management through workflow-based RFID tag witnessing and real-time information entry.

BACKGROUND: Dual-person inspection in IVF laboratories cannot fully avoid mix-ups or embryo transfer errors, and data transcription or entry is time-consuming and redundant, often leading to delays in completing medical records. METHODS: This study introduced a workflow-based RFID tag witnessing and real-time information entry platform for addressing these challenges. To assess its potential in reducing mix-ups, we conducted a simulation experiment in semen preparation to analyze its error correction rate. Additionally, we evaluated its impact on work efficiency, specifically in operation and data entry. Furthermore, we compared the cycle costs between paper labels and RFID tags. Finally, we retrospectively analyzed clinical outcomes of 20,424 oocyte retrieval cycles and 15,785 frozen embryo transfer cycles, which were divided into paper label and RFID tag groups. RESULTS: The study revealed that comparing to paper labels, RFID tag witnessing corrected 100% of tag errors, didn't affect gamete/embryo operations, and notably shorten the time of entering data, but the cycle cost of RFID tags was significantly higher. However, no significant differences were observed in fertilization, embryo quality, blastocyst rates, clinical pregnancy, and live birth rates between two groups. CONCLUSIONS: RFID tag witnessing doesn't negatively impact gamete/embryo operation, embryo quality and pregnancy outcomes, but it potentially reduces the risk of mix-ups or errors. Despite highly increased cost, integrating RFID tag witnessing with real-time information entry can remarkably decrease the data entry time, substantially improving the work efficiency. This workflow-based management platform also enhances operational safety, ensures medical informational integrity, and boosts embryologist's confidence.

Machine learning is an effective method to predict the 3-month prognosis of patients with acute ischemic stroke.

Background and objectives: Upwards of 50% of acute ischemic stroke (AIS) survivors endure varying degrees of disability, with a recurrence rate of 17.7%. Thus, the prediction of outcomes in AIS may be useful for treatment decisions. This study aimed to determine the applicability of a machine learning approach for forecasting early outcomes in AIS patients. Methods: A total of 659 patients with new-onset AIS admitted to the Department of Neurology of both the First and Second Affiliated Hospitals of Bengbu Medical University from January 2020 to October 2022 included in the study. The patient' demographic information, medical history, Trial of Org 10,172 in Acute Stroke Treatment (TOAST), National Institute of Health Stroke Scale (NIHSS) and laboratory indicators at 24 h of admission data were collected. The Modified Rankine Scale (mRS) was used to assess the 3-mouth outcome of participants' prognosis. We constructed nine machine learning models based on 18 parameters and compared their accuracies for outcome variables. Results: Feature selection through the Least Absolute Shrinkage and Selection Operator cross-validation (Lasso CV) method identified the most critical predictors for early prognosis in AIS patients as white blood cell (WBC), homocysteine (HCY), D-Dimer, baseline NIHSS, fibrinogen degradation product (FDP), and glucose (GLU). Among the nine machine learning models evaluated, the Random Forest model exhibited superior performance in the test set, achieving an Area Under the Curve (AUC) of 0.852, an accuracy rate of 0.818, a sensitivity of 0.654, a specificity of 0.945, and a recall rate of 0.900. Conclusion: These findings indicate that RF models utilizing general clinical and laboratory data from the initial 24 h of admission can effectively predict the early prognosis of AIS patients.

[Simultaneous detection of lower aliphatic amines and conventional cations in atmospheric PM2.5 particulates by ion chromatography].

Many amine pollutants exist in the atmosphere. Lower aliphatic amines promote the formation and growth of particles into PM2.5, which damages the heart, lungs, and kidneys of the human body. PM2.5, a common atmospheric particulate pollutant with complex compositions, is the main cause of haze weather. Therefore, measuring the contents of lower aliphatic amines and cations in PM2.5 is of great significance for monitoring environmental air quality and protecting human health. This study established a suppressed ion-chromatographic method with conductivity for the simultaneous detection of four lower aliphatic amines (methylamine, dimethylamine, trimethylamine, and ethylamine) and five cations (Na+, N[Formula: see text], and Ca2+ showed high concentrations. The contents of the four lower aliphatic amines were low; however, the ethylamine content in some samples was high. The results indicate that the proposed method meets the quantification requirements for cations and lower aliphatic amines in PM2.5, with simple processing, high sensitivity, and good accuracy. It can quickly and accurately detect a large number of samples and be used to assess the pollution of small particles in the air as well as trace pollution sources to protect human health.

Deciphering the reduction of antibiotic resistance genes (ARGs) during medium-chain fatty acids production from waste activated sludge: Driven by inhibition of ARGs transmission and shift of microbial community.

Medium-chain fatty acids (MCFAs) production from waste activated sludge (WAS) by chain extension (CE) is a promising technology. However, the effects and mechanisms of CE process on the fate of antibiotic resistance genes (ARGs) remain unclear. In this study, the results showed that the removal efficiency of ARGs was 81.15 % in CE process, suggesting its efficacy in reducing environmental risks. Further, the observed decrease in mobile genetic elements (MGEs) indicated that CE process restricted the horizontal gene transfer (HGT). Complementing this, the increase in soluble organic matters and extracellular 16 S rDNA confirmed that MCFAs production caused bacterial damage. Decreased intracellular ARGs and increased extracellular ARGs further revealed that MCFAs production impaired ARGs hosts, thereby limiting the vertical gene transfer (VGT) of ARGs. Shift of microbial community combined with co-occurrence network analysis demonstrated that functional bacteria without host potential for ARGs were enriched, but potential ARGs and MGEs hosts decreased, showing the role of functional bacterial phylogeny and selection pressure of MCFAs in reducing ARGs. Finally, partial least squares path model was used to systematic verify the mechanism of ARGs removal in CE process, which was attributed to the inhibition of ARGs transmission (HGT and VGT) and shift of microbial community.

The Relationship between Quantitative Parameters of Dual-energy CT and HIF-1α Expression in Non-Small Cell Lung Cancer.

OBJECTIVE: This study aimed to investigate whether there is a correlation between quantitative parameters of dual-energy computed tomography (DECT) and the relative expression of HIF-1α in patients with non-small cell lung cancer (NSCLC) to preliminarily explore the value of DECT in evaluating the hypoxia of tumor microenvironment and tumor biological behavior and provide more information for the treatment of NSCLC. METHODS: This retrospective research included 36 patients with pathologically confirmed NSCLC who underwent dual-energy enhanced CT scans. The quantitative parameters of DECT were analyzed, including iodine concentration, water concentration, the CT values corresponding to 40keV, 70keV, 100keV, and 130keV in arterial and venous phases, and the normalized iodine concentration and the slope of the energy spectrum curve were calculated. Postoperative specimens underwent HIF immunohistochemical staining by two pathologists. Spearman correlation analysis was adopted as the statistical methodology. The data were analyzed by SPSS26.0 statistical software. RESULTS: Water concentration (r=0.659, P<0.001 and r= 0.632, P<0.001, the CT values corresponding to 100keV (r=0.645, P<0.001 and r= 0.566, P<0.001) and 130keV (r=0.687, P<0.001 and r= 0.682, P<0.001) in arterial and venous phases, and CT value of 70keV in arterial phase (r=0.457, P=0.005) were positively correlated with HIF-1α expression level. There was no correlation among iodine concentration, standardized iodine concentration, CT value of 40keV, λHU, and HIF-1α expression in arterial and venous levels (P >0.05). CONCLUSION: The quantitative parameters of DECT have a certain correlation with HIF-1α expression in NSCLC. Moreover, it has been demonstrated that DECT can be used to predict hypoxia in tumor tissues and the prognosis of lung cancer patients.