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Abstract With the development of science and technology, industrial production requires more and more precise parts processing, precision processing has become a trend. In this trend. The traditional processing methods have been difficult to meet the market demand for micro-hole parts. Therefore, combining the characteristics of EDM and Ultrasound-assisted Machining, a new horizontal Ultrasound-assisted EDM system for deep and small holes is designed and applied in physical machining. The experimental results show that the horizontal ultrasonic vibration of workpiece can promote the efficiency and depth of EDM, and improve the electrode wear and the inner surface roughness of small holes. By comparing the processing effects of different materials, it is found that the processing efficiency and depth of pig iron are better than those of stainless steel. In conclusion, the horizontal ultrasonic vibration system established in this paper not only improves the processing effect of conventional EDM to a certain extent, but also does not affect the spindle feed and working fluid circulation of EDM machine tools. It enriches the research direction of ultrasonic assisted EDM and has broad market prospects.

Abstract Background Acute kidney injury (AKI) is a major complication following cardiac surgery with a high incidence in those with existing kidney dysfunction. Platelet distribution width (PDW) reflects variability in platelet size and serves as an indicator of platelet activation. Recent investigations linked PDW changes to kidney pathology, suggesting its utility in identifying individuals at risk for AKI, thus necessitating exploration of its predictive value. Methods Patients with preoperative renal dysfunction [15 ≤ estimated glomerular filtration rate (eGFR) 0.05). Conclusions This study underscored perioperative PDW changes as a significant predictor of postoperative AKI in patients with renal insufficiency, highlighting its potential in refining risk stratification and management strategies. Clinical trial number Not applicable for this observational retrospective study.

Abstract Background Acute kidney injury (AKI) represents a significant post-cardiac surgery complication, particularly prevalent among individuals with pre-existing renal dysfunction. Chronic kidney disease (CKD) is frequently accompanied by persistent, low-grade inflammation, which is known to exacerbate systemic stress responses during surgical procedures. This study hypothesizes that these inflammatory responses might influence the incidence and severity of postoperative acute kidney injury (AKI), potentially serving as a protective mechanism by preconditioning the kidney to stress. Methods This retrospective study enrolled patients with preoperative renal dysfunction (eGFR between 15 and 60 ml/min/1.73 m²) who underwent cardiac surgery between January 2020 and December 2022. Preoperative inflammatory biomarkers were evaluated. The primary outcome was the incidence of postoperative AKI, as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Multivariate regression models and sensitivity analyses were conducted to ascertain the relationship between inflammatory biomarkers and AKI. Restricted cubic spines (RCS) was conducted to explore nonlinear associations between inflammatory biomarkers and AKI. Results AKI occurred in 53.4% (392/734) of patients, accompanied by significant mortality and length of hospital stay increases in cases of AKI (P

Abstract Background Modified furosemide responsiveness index (mFRI) is a novel biomarker for assessing diuretic response and AKI progression in patients with early AKI. However, the comparative predictive performance of mFRI and novel renal biomarkers for adverse renal outcomes remains unclear. In a single-center prospective study, we aimed to evaluate the discriminatory abilities of mFRI and other novel renal biomarkers in predicting AKI progression and prognosis in patients with initial mild and moderate AKI (KDIGO stage 1 to 2). Results Patients with initial mild and moderate AKI within 48 h following cardiac surgery were included in this study. The mFRI, renal biomarkers (including serum or urinary neutrophil gelatinase-associated lipocalin [sNGAL or uNGAL], serum cystatin C, urinary N-acetyl-beta-D-glycosaminidase [uNAG], urinary albumin-to-creatinine ratio) and cytokines (TNF, IL-1β, IL-2R, IL-6, IL-8, and IL-10) were measured at AKI diagnosis. The mFRI was calculated for each patient, which was defined as 2-hour urine output divided by furosemide dose and body weight. Of 1013 included patients, 154 (15.2%) experienced AKI progression, with 59 (5.8%) progressing to stage 3 and 33 (3.3%) meeting the composite outcome of hospital mortality or receipt of renal replacement therapy (RRT). The mFRI showed non-inferiority or potential superiority to renal biomarkers and cytokines in predicting AKI progression (area under the curve [AUC] 0.80, 95% confidence interval [CI] 0.77–0.82), progression to stage 3 (AUC 0.87, 95% CI 0.85–0.89), and composite outcome of death and receipt of RRT (AUC 0.85, 95% CI 0.82–0.87). Furthermore, the combination of a functional biomarker (mFRI) and a urinary injury biomarker (uNAG or uNGAL) resulted in a significant improvement in the prediction of adverse renal outcomes than either individual biomarker (all P

Abstract Background The optimal sedative regime for noninvasive ventilation (NIV) intolerance remains uncertain. The present study aimed to assess the efficacy and safety of remifentanil (REM) compared to dexmedetomidine (DEX) in cardiac surgery patients with moderate-to-severe intolerance to NIV. Methods In this multicenter, prospective, single-blind, randomized controlled study, adult cardiac surgery patients with moderate-to-severe intolerance to NIV were enrolled and randomly assigned to be treated with either REM or DEX for sedation. The status of NIV intolerance was evaluated using a four-point NIV intolerance score at different timepoints within a 72-h period. The primary outcome was the mitigation rate of NIV intolerance following sedation. Results A total of 179 patients were enrolled, with 89 assigned to the REM group and 90 to the DEX group. Baseline characteristics were comparable between the two groups, including NIV intolerance score [3, interquartile range (IQR) 3–3 vs. 3, IQR 3–4, p = 0.180]. The chi-squared test showed that mitigation rate, defined as the proportion of patients who were relieved from their initial intolerance status, was not significant at most timepoints, except for the 15-min timepoint (42% vs. 20%, p = 0.002). However, after considering the time factor, generalized estimating equations showed that the difference was statistically significant, and REM outperformed DEX (odds ratio = 3.31, 95% confidence interval: 1.35–8.12, p = 0.009). Adverse effects, which were not reported in the REM group, were encountered by nine patients in the DEX group, with three instances of bradycardia and six cases of severe hypotension. Secondary outcomes, including NIV failure (5.6% vs. 7.8%, p = 0.564), tracheostomy (1.12% vs. 0%, p = 0.313), ICU LOS (7.7 days, IQR 5.8–12 days vs. 7.0 days, IQR 5–10.6 days, p = 0.219), and in-hospital mortality (1.12% vs. 2.22%, p = 0.567), demonstrated comparability between the two groups. Conclusions In summary, our study demonstrated no significant difference between REM and DEX in the percentage of patients who achieved mitigation among cardiac surgery patients with moderate-to-severe NIV intolerance. However, after considering the time factor, REM was significantly superior to DEX. Trial registration ClinicalTrials.gov (NCT04734418), registered on January 22, 2021. URL of the trial registry record: https://register.clinicaltrials.gov/prs/app/action/SelectProtocol?sid=S000AM4S&selectaction=Edit&uid=U00038YX&ts=3&cx=eqn1z0 .

Abstract Background The development of acute kidney injury (AKI) post-cardiac surgery significantly increases patient morbidity and healthcare costs. Prior researches have established Syndecan-1 (SDC-1) as a potential biomarker for endothelial injury and subsequent acute kidney injury development. This study assessed whether postoperative SDC-1 levels could further predict AKI requiring kidney replacement therapy (AKI-KRT) and AKI progression. Methods In this prospective study, 122 adult cardiac surgery patients, who underwent valve or coronary artery bypass grafting (CABG) or a combination thereof and developed AKI within 48 h post-operation from May to September 2021, were monitored for the progression to stage 2–3 AKI or the need for KRT. We analyzed the predictive value of postoperative serum SDC-1 levels in relation to multiple endpoints. Results In the study population, 110 patients (90.2%) underwent cardiopulmonary bypass, of which thirty received CABG or combined surgery. Fifteen patients (12.3%) required KRT, and thirty-eight (31.1%) developed progressive AKI, underscoring the severe AKI incidence. Multivariate logistic regression indicated that elevated SDC-1 levels were independent risk factors for progressive AKI (OR = 1.006) and AKI-KRT (OR = 1.011). The AUROC for SDC-1 levels in predicting AKI-KRT and AKI progression was 0.892 and 0.73, respectively, outperforming the inflammatory cytokines. Linear regression revealed a positive correlation between SDC-1 levels and both hospital (β = 0.014, p = 0.022) and ICU stays (β = 0.013, p

Abstract 3D point cloud data, as an immersive detailed data source, has been increasingly used in numerous applications. To deal with the computational and storage challenges of this data, it needs to be compressed before transmission, storage, and processing, especially in real-time systems. Instead of decoding the compressed data stream and subsequently conducting downstream tasks on the decompressed data, analyzing point clouds directly in their compressed domain has attracted great interest. In this paper, we dive into the realm of compressed point cloud classification (CPCC), aiming to achieve high point cloud classification accuracy in a bitrate-saving way by ensuring the bit stream contains a high degree of representative information of the point cloud. Edge information is one of the most important and representative attributes of the point cloud because it can display the outlines or main shapes. However, extracting edge points or information from point cloud models is challenging due to their irregularity and sparsity. To address this challenge, we adopt an advanced edge-sampling method that enhances existing state-of-the-art (SOTA) point cloud edge-sampling techniques based on attention mechanisms and consequently develop a novel CPCC method “CPCC-PES” that focuses on point cloud’s edge information. The result obtained on the benchmark ModelNet40 dataset shows that our model has superior rate-accuracy trade-off performance than SOTA works. Specifically, our method achieves over 90% Top-1 Accuracy with a mere 0.08 bits-per-point (bpp), marking a remarkable over 96% reduction in BD-bitrate compared with specialized codecs. This means that our method only consumes 20% of the bitrate of other SOTA works while maintaining comparable accuracy. Furthermore, we propose a new evaluation metric named BD-Top-1 Accuracy to evaluate the trade-off performance between bitrate and Top-1 Accuracy for future CPCC research.

Abstract Background Acute kidney injury (AKI) significantly increases morbidity and mortality following cardiac surgery, especially in patients with pre-existing renal impairments. N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a marker of cardiac stress and dysfunction, conditions often exacerbated during cardiac surgery and prevalent in chronic kidney disease (CKD) patients. Elevated NT-proBNP levels can indicate underlying cardiac strain, hemodynamic instability and volume overload. This study evaluated the association between perioperative changes in NT-proBNP levels and the incidence of AKI in this particular patient group. Methods This retrospective study involved patients with impaired renal function (eGFR 15–60 ml/min/1.73 m²) who underwent cardiac surgery from July to December 2022. It analyzed the association between the ratio of preoperative and ICU admittance post-surgery NT-proBNP levels and the development of AKI and AKI stage 2–3, based on KDIGO criteria, using multivariate logistic regression models. Restricted cubic spline analysis assessed non-linear associations between NT-proBNP and endpoints. Subgroup analysis was performed to assess the heterogeneity of the association between NT-proBNP and endpoints in subgroups. Results Among the 199 participants, 116 developed postoperative AKI and 16 required renal replacement therapy. Patients with AKI showed significantly higher postoperative NT-proBNP levels compared to those without AKI. Decreased baseline eGFR and increased post/preoperative NT-proBNP ratios were associated with higher AKI risk. Specifically, the highest quantile post/preoperative NT-proBNP ratio indicated an approximately seven-fold increase in AKI risk and a ninefold increase in AKI stage 2–3 risk compared to the lowest quantile. The area under the receiver operating characteristic curve for predicting AKI and AKI stage 2–3 using NT-proBNP were 0.63 and 0.71, respectively, demonstrating moderate accuracy. Subgroup analysis demonstrated that the positive association between endpoints and logarithmic transformed post/preoperative NT-proBNP levels was consistently robust in subgroup analyses stratified by age, sex, surgery, CPB application, hypertension, diabetes status and fluid balance. Conclusion Perioperative NT-proBNP level changes are predictive of postoperative AKI in patients with pre-existing renal deficiencies undergoing cardiac surgery, aiding in risk assessment and patient management.

Abstract Endothelins and their receptors, ETA and ETB, play vital roles in maintaining vascular homeostasis. Therapeutically targeting endothelin receptors, particularly through ETA antagonists, has shown efficacy in treating pulmonary arterial hypertension (PAH) and other cardiovascular- and renal-related diseases. Here we present cryo-electron microscopy structures of ETA in complex with two PAH drugs, macitentan and ambrisentan, along with zibotentan, a selective ETA antagonist, respectively. Notably, a specialized anti-ETA antibody facilitated the structural elucidation. These structures, together with the active-state structures of ET-1-bound ETA and ETB, and the agonist BQ3020-bound ETB, in complex with Gq, unveil the molecular basis of agonist/antagonist binding modes in endothelin receptors. Key residues that confer antagonist selectivity to endothelin receptors were identified along with the activation mechanism of ETA. Furthermore, our results suggest that ECL2 in ETA can serve as an epitope for antibody-mediated receptor antagonism. Collectively, these insights establish a robust theoretical framework for the rational design of small-molecule drugs and antibodies with selective activity against endothelin receptors.

Abstract Background No reliable clinical tools exist to predict acute kidney injury (AKI) progression. We aim to explore a scoring system for predicting the composite outcome of progression to severe AKI or death within seven days among early AKI patients after cardiac surgery. Methods In this study, we used two independent cohorts, and patients who experienced mild/moderate AKI within 48 h after cardiac surgery were enrolled. Eventually, 3188 patients from the MIMIC-IV database were used as the derivation cohort, while 499 patients from the Zhongshan cohort were used as external validation. The primary outcome was defined by the composite outcome of progression to severe AKI or death within seven days after enrollment. The variables identified by LASSO regression analysis were entered into logistic regression models and were used to construct the risk score. Results The composite outcome accounted for 3.7% (n = 119) and 7.6% (n = 38) of the derivation and validation cohorts, respectively. Six predictors were assembled into a risk score (AKI-Pro score), including female, baseline eGFR, aortic surgery, modified furosemide responsiveness index (mFRI), SOFA, and AKI stage. And we stratified the risk score into four groups: low, moderate, high, and very high risk. The risk score displayed satisfied predictive discrimination and calibration in the derivation and validation cohort. The AKI-Pro score discriminated the composite outcome better than CRATE score, Cleveland score, AKICS score, Simplified renal index, and SRI risk score (all P

Abstract Background Skin mottling is a common manifestation of peripheral tissue hypoperfusion, and its severity can be described using the skin mottling score (SMS). This study aims to evaluate the value of the SMS in detecting peripheral tissue hypoperfusion in critically ill patients following cardiac surgery. Methods Critically ill patients following cardiac surgery with risk factors for tissue hypoperfusion were enrolled (n = 373). Among these overall patients, we further defined a hypotension population (n = 178) and a shock population (n = 51). Hemodynamic and perfusion parameters were recorded. The primary outcome was peripheral hypoperfusion, defined as significant prolonged capillary refill time (CRT, > 3.0 s). The characteristics and hospital mortality of patients with and without skin mottling were compared. The area under receiver operating characteristic curves (AUROC) were used to assess the accuracy of SMS in detecting peripheral hypoperfusion. Besides, the relationships between SMS and conventional hemodynamic and perfusion parameters were investigated, and the factors most associated with the presence of skin mottling were identified. Results Of the 373-case overall population, 13 (3.5%) patients exhibited skin mottling, with SMS ranging from 1 to 5 (5, 1, 2, 2, and 3 cases, respectively). Patients with mottling had lower mean arterial pressure, higher vasopressor dose, less urine output (UO), higher CRT, lactate levels and hospital mortality (84.6% vs. 12.2%, p

IntroductionOsteoporosis, characterized by low bone mineral density (BMD), is an increasingly serious public health issue. So far, several traditional regression models and machine learning (ML) algorithms have been proposed for predicting osteoporosis risk. However, these models have shown relatively low accuracy in clinical implementation. Recently proposed deep learning (DL) approaches, such as deep neural network (DNN), which can discover knowledge from complex hidden interactions, offer a new opportunity to improve predictive performance. In this study, we aimed to assess whether DNN can achieve a better performance in osteoporosis risk prediction.MethodsBy utilizing hip BMD and extensive demographic and routine clinical data of 8,134 subjects with age more than 40 from the Louisiana Osteoporosis Study (LOS), we developed and constructed a novel DNN framework for predicting osteoporosis risk and compared its performance in osteoporosis risk prediction with four conventional ML models, namely random forest (RF), artificial neural network (ANN), k-nearest neighbor (KNN), and support vector machine (SVM), as well as a traditional regression model termed osteoporosis self-assessment tool (OST). Model performance was assessed by area under ‘receiver operating curve’ (AUC) and accuracy.ResultsBy using 16 discriminative variables, we observed that the DNN approach achieved the best predictive performance (AUC = 0.848) in classifying osteoporosis (hip BMD T-score ≤ −1.0) and non-osteoporosis risk (hip BMD T-score > −1.0) subjects, compared to the other approaches. Feature importance analysis showed that the top 10 most important variables identified by the DNN model were weight, age, gender, grip strength, height, beer drinking, diastolic pressure, alcohol drinking, smoke years, and economic level. Furthermore, we performed subsampling analysis to assess the effects of varying number of sample size and variables on the predictive performance of these tested models. Notably, we observed that the DNN model performed equally well (AUC = 0.846) even by utilizing only the top 10 most important variables for osteoporosis risk prediction. Meanwhile, the DNN model can still achieve a high predictive performance (AUC = 0.826) when sample size was reduced to 50% of the original dataset.ConclusionIn conclusion, we developed a novel DNN model which was considered to be an effective algorithm for early diagnosis and intervention of osteoporosis in the aging population.

Abstract Background The effects of surgical day (workdays or weekends) on occurrence and outcome of cardiac surgery associated -acute kidney injury (CSA-AKI) remains unclear. This study aimed to compare the incidence and short-term outcomes of CSA-AKI in patients undergoing surgery on workdays and weekends. Materials and methods Patients who underwent cardiac surgery from July 2020 to December 2020 were retrospectively enrolled in this study. These patients were divided into a weekend group and workday group. The primary endpoint was the incidence of CSA-AKI. The secondary endpoints included renal function recovery and in-hospital mortality. The logistic regression model was used to explore the risk factors for CSA-AKI. Stratification analysis was performed to estimate the association between CSA-AKI and weekend surgery stratified by emergency surgery. Results A total of 1974 patients undergoing cardiac surgery were enrolled. The incidence of CSA-AKI in the weekend group was significantly higher than that in the workday group (42.8% vs. 34.7%, P = 0.038). Further analysis of patients with CSA-AKI showed that there was no difference in renal function recovery between the workday AKI group and weekend AKI group. There was no difference in in-hospital mortality between the weekend group and workday group (3.6% vs. 2.4%, P = 0.327); however, the in-hospital mortality of the weekend AKI group was significantly higher than that of the workday AKI group (8.5% vs. 2.9%, P = 0.014). Weekend surgery and emergency surgery were independent risk factors for CSA-AKI. The multiplicative model showed an interaction between weekend surgery and emergency surgery; weekend surgery was related to an increased risk of AKI among patients undergoing emergency surgery [adjusted OR (95% CI): 1.96 (1.012-8.128)]. Conclusions The incidence of CSA-AKI in patients undergoing cardiac surgery on weekends was significantly higher compared to that in patients undergoing cardiac surgery on workdays. Weekend surgery did not affect the in-hospital mortality of all patients but significantly increased the mortality of AKI patients. Weekend surgery and emergency surgery were independent risk factors for CSA-AKI. Weekend emergency surgery significantly increased the risk of CSA-AKI.

Abstract Although the gut microbiota has been reported to influence osteoporosis risk, the individual species involved, and underlying mechanisms, remain largely unknown. We performed integrative analyses in a Chinese cohort of peri-/post-menopausal women with metagenomics/targeted metabolomics/whole-genome sequencing to identify novel microbiome-related biomarkers for bone health. Bacteroides vulgatus was found to be negatively associated with bone mineral density (BMD), which was validated in US white people. Serum valeric acid (VA), a microbiota derived metabolite, was positively associated with BMD and causally downregulated by B. vulgatus. Ovariectomized mice fed B. vulgatus demonstrated increased bone resorption and poorer bone micro-structure, while those fed VA demonstrated reduced bone resorption and better bone micro-structure. VA suppressed RELA protein production (pro-inflammatory), and enhanced IL10 mRNA expression (anti-inflammatory), leading to suppressed maturation of osteoclast-like cells and enhanced maturation of osteoblasts in vitro. The findings suggest that B. vulgatus and VA may represent promising targets for osteoporosis prevention/treatment.

For the multi-objective flow shop scheduling problem in the supply chain environment, this paper proposes the Fuzzy Relevance Entropy method (FREM) to solve the adaptive value assignment problem in the multi-objective optimization process of the supply chain environment by combining Fuzzy Information Entropy Theory (FIET) and Degree of Membership Function (DMF). Firstly, the uncertainty of each sub-objective of the ideal solution and Pareto solution of the objective is extracted using the Degree of Membership Function. Secondly, each solution is mapped into an affiliation degree fuzzy set and the information contained in the fuzzy set is reprocessed using Fuzzy Information Entropy Theory. Finally, the amount of information contained in the ideal solution solved by the Pareto method is used to guide the evolution of the Particle Swarm Optimization (PSO) algorithm, thus avoiding the traditional multi-objective optimization process of assigning weights to solve the fitness link. This paper combines both the Fuzzy Relevance Entropy method and the Stochastic Weight method with Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms to address the five-objective flow shop scheduling problem in the supply chain environment. Experimental results demonstrate that the proposed Fuzzy Relevance Entropy method effectively solves the multi-objective flow shop scheduling problem in the supply chain environment and achieves better optimization results compared to the Stochastic Weight method.

Abstract Background Patients receiving surgical treatment of acute type A Aortic Dissection (aTAAD) are common to suffer organ dysfunction in the intensive care unit due to overwhelming inflammation. Previous studies have revealed that glucocorticoids may reduce complications in certain patient groups, but evidence between postoperative glucocorticoids administration and improvement in organ dysfunction after aTAAD surgery are lacking. Methods This study will be an investigator-initiated, prospective, single-blind, randomized, single-center study. Subjects with confirmed diagnosis of aTAAD undergoing surgical treatment will be enrolled and 1:1 randomly assigned to receive either glucocorticoids or normal treatment. All patients in the glucocorticoids group will be given methylprednisolone intravenously for 3 days after enrollment. The primary endpoint will be the amplitude of variation of Sequential Organ Failure Assessment score on post-operative day 4 compared to baseline. Discussion The trial will explore the rationale for postoperative application of glucocorticoids in patients after aTAAD surgery. Trial registration This study has been registered on ClinicalTrials.gov (NCT04734418).

Abstract Background Cardiac surgery-associated acute kidney injury (AKI) is one of the common complications of cardiac surgery. Preoperative angiography helps assess heart disease but may increase the risk of AKI. Although more and more patients with preoperative renal dysfunction can undergo cardiac surgery with the advances in surgical techniques, there is little research on the effect of angiography on postoperative AKI in these patients. This study investigates whether angiography increases the risk of AKI after cardiac surgery in patients with preoperative renal dysfunction (15 ≤ eGFR

Abstract Background Sepsis is an abnormal immune response after infection, wherein the lung is the most susceptible organ to fail, leading to acute lung injury. To overcome the limitations of current therapeutic strategies and develop more specific treatment, the inflammatory process, in which T cell-derived extracellular vesicles (EVs) play a central role, should be explored deeply. Methods Liquid chromatography–tandem mass spectrometry was performed for serum EV protein profiling. The serum diacylglycerol kinase kappa (DGKK) and endotoxin contents of patients with sepsis-induced lung injury were measured. Apoptosis, oxidative stress, and inflammation in A549 cells, bronchoalveolar lavage fluid, and lung tissues of mice were measured by flow cytometry, biochemical analysis, enzyme-linked immunosorbent assay, quantitative real-time polymerase chain reaction, and western blot. Results DGKK, the key regulator of the diacylglycerol (DAG)/protein kinase C (PKC) pathway, exhibited elevated expression in serum EVs of patients with sepsis-induced lung injury and showed strong correlation with sepsis severity and disease progression. DGKK was expressed in CD4+ T cells under regulation of the NF-κB pathway and delivered by EVs to target cells, including alveolar epithelial cells. EVs produced by CD4+ T lymphocytes exerted toxic effects on A549 cells to induce apoptotic cell death, oxidative cell damage, and inflammation. In mice with sepsis induced by cecal ligation and puncture, EVs derived from CD4+ T cells also promoted tissue damage, oxidative stress, and inflammation in the lungs. These toxic effects of T cell-derived EVs were attenuated by the inhibition of PKC and NOX4, the downstream effectors of DGKK and DAG. Conclusions This approach established the mechanism that T-cell-derived EVs carrying DGKK triggered alveolar epithelial cell apoptosis, oxidative stress, inflammation, and tissue damage in sepsis-induced lung injury through the DAG/PKC/NOX4 pathway. Thus, T-cell-derived EVs and the elevated distribution of DGKK should be further investigated to develop therapeutic strategies for sepsis-induced lung injury.

Abstract Background Acute kidney injury (AKI) is a common complication after cardiac surgery, and preoperative renal dysfunction is an important risk factor. Proteinuria indicates renal structural damage, but there are few studies on proteinuria and the risk of AKI after cardiac surgery in patients with renal dysfunction. This study aimed to elucidate whether proteinuria can predict AKI after cardiac surgery in patients with renal dysfunction. Methods Patients with stages 3–4 chronic kidney disease (CKD) who underwent cardiac surgery were included in this retrospective study. AKI was defined according to the KDIGO criteria. The association between proteinuria and AKI in patients with CKD stages 3–4 was investigated. Results The incidence of AKI in the entire cohort (n = 1546) was 53.55%. The in-hospital mortality of patients with was higher than patients without AKI (AKI vs. no AKI, 4.7 vs. 0.8%, P

Abstract Background While transcription factor (TF) regulation is known to play an important role in osteoblast development, differentiation, and bone metabolism, the molecular features of TFs in human osteoblasts at the single-cell resolution level have not yet been characterized. Here, we identified modules (regulons) of co-regulated genes by applying single-cell regulatory network inference and clustering to the single-cell RNA sequencing profiles of human osteoblasts. We also performed cell-specific network (CSN) analysis, reconstructed regulon activity-based osteoblast development trajectories, and validated the functions of important regulons both in vivo and in vitro. Results We identified four cell clusters: preosteoblast-S1, preosteoblast-S2, intermediate osteoblasts, and mature osteoblasts. CSN analysis results and regulon activity-based osteoblast development trajectories revealed cell development and functional state changes of osteoblasts. CREM and FOSL2 regulons were mainly active in preosteoblast-S1, FOXC2 regulons were mainly active in intermediate osteoblast, and RUNX2 and CREB3L1 regulons were most active in mature osteoblasts. Conclusions This is the first study to describe the unique features of human osteoblasts in vivo based on cellular regulon active landscapes. Functional state changes of CREM, FOSL2, FOXC2, RUNX2, and CREB3L1 regulons regarding immunity, cell proliferation, and differentiation identified the important cell stages or subtypes that may be predominantly affected by bone metabolism disorders. These findings may lead to a deeper understanding of the mechanisms underlying bone metabolism and associated diseases.

BackgroundHip fracture occurs when an applied force exceeds the force that the proximal femur can support (the fracture load or “strength”) and can have devastating consequences with poor functional outcomes. Proximal femoral strengths for specific loading conditions can be computed by subject-specific finite element analysis (FEA) using quantitative computerized tomography (QCT) images. However, the radiation and availability of QCT limit its clinical usability. Alternative low-dose and widely available measurements, such as dual energy X-ray absorptiometry (DXA) and genetic factors, would be preferable for bone strength assessment. The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion.ResultsWe developed new models using multi-view variational autoencoder (MVAE) for feature representation learning and a product of expert (PoE) model for multi-view information fusion. We applied the proposed models to an in-house Louisiana Osteoporosis Study (LOS) cohort with 931 male subjects, including 345 African Americans and 586 Caucasians. We performed genome-wide association studies (GWAS) to select 256 genetic variants with the lowest p-values for each proximal femoral strength and integrated whole genome sequence (WGS) features and DXA-derived imaging features to predict proximal femoral strength. The best prediction model for fall fracture load was acquired by integrating WGS features and DXA-derived imaging features. The designed models achieved the mean absolute percentage error of 18.04%, 6.84% and 7.95% for predicting proximal femoral fracture loads using linear models of fall loading, nonlinear models of fall loading, and nonlinear models of stance loading, respectively.ConclusionThe proposed models are capable of predicting proximal femoral strength using WGS features and DXA-derived imaging features. Though this tool is not a substitute for predicting FEA using QCT images, it would make improved assessment of hip fracture risk more widely available while avoiding the increased radiation exposure from QCT.

Abstract Purpose This national study aimed to investigate the lung ultrasound (LUS) training and practice of respiratory therapists (RTs) in mainland China. Methods A cross-sectional multicenter survey was conducted from May 22, 2021 to August 12, 2021, through online platforms. This survey included RTs in mainland China. The survey was divided into four sections: (1) demographic characteristics and basic information; (2) basic information about LUS training and practice; (3) LUS practice details; and (4) Other ultrasound training and practice. Results A total of 514 responses were received, and 494 valid responses were included in the analysis. 81.2% (401/494) participants’ highest degree of education was a bachelor’s degree, and 43.1% (213/494) participants were at level II in terms of job ranking. 99.2%(490/494) participants agreed that the RTs needed to learn lung ultrasound, but only 12.3% (61/494) participants had received a LUS training course. Further, 66.2% (327/494) experienced participants responded to Sect. 3. Most of RTs used LUS when the patient had hypoxia (265/327, 81%) or dyspnea (260/317, 79.5%); they also used it during spontaneous breathing trial(SBT) (191/327, 58.4%) or in prone position (177/327, 54.1%). The A-line (302/327, 92.4%), B-line (299/327, 91.4%), lung slide (263/327, 80.4%), and bat sign (259/327, 79.2%) were well known as LUS signs. Also, 30.6% (100/327) participants did not use the LUS protocol in their clinical practice, and only 25.4%(83/327) participants said they had used LUS scores. Moreover, 55.7% (182/327) participants frequently changed the respiratory therapy strategy according to LUS results. Conclusions We should improve the number and workplace of RTs in mainland China in the future. We should also standardize the application of LUS practice and training for RTs in mainland China and establish corresponding certification pathways.

Abstract Aims Recombinant human brain natriuretic peptide (rh‐BNP) is commonly used as a decongestive therapy. This study aimed to investigate the instant effects of rh‐BNP on cardiac output and venous return function in post‐cardiotomy patients with congestive heart failure (CHF). Methods and results Twenty‐four post‐cardiotomy heart failure patients were enrolled and received a standard loading dose of rh‐BNP. Haemodynamic monitoring was performed via a pulmonary artery catheter before and after the administration of rh‐BNP. The cardiac output and venous return functions were estimated by depicting Frank‐Starling and Guyton curves. After rh‐BNP infusion, variables reflecting cardiac congestion and venous return function, such as pulmonary artery wedge pressure, mean systemic filling pressure (Pmsf) and venous return resistance index (VRRI), reduced from 15 ± 3 to 13 ± 3 mmHg, from 32 ± 7 to 28 ± 7 mmHg and from 6.7 ± 2.6 to 5.7 ± 1.8 mmHg min m2/L, respectively. Meanwhile, cardiac index, stroke volume index, and the cardiac output function curve remained unchanged per se. The decline in Pmsf [−13% (−22% to −8%)] and VRRI [−12% (−25% to −5%)] was much greater than that in the systemic vascular resistance index [−7% (−14% to 0%)]. In the subgroup analysis of reduced ejection fraction (

Abstract Background Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accurate machine-learning model to identify patients at risks of NIV failure after extubation in intensive care units (ICUs). Methods Patients who underwent NIV after extubation in the eICU Collaborative Research Database (eICU-CRD) were included. NIV failure was defined as need for invasive ventilatory support (reintubation or tracheotomy) or death after NIV initiation. A total of 93 clinical and laboratory variables were assessed, and the recursive feature elimination algorithm was used to select key features. Hyperparameter optimization was conducted with an automated machine-learning toolkit called Neural Network Intelligence. A machine-learning model called Categorical Boosting (CatBoost) was developed and compared with nine other models. The model was then prospectively validated among patients enrolled in the Cardiac Surgical ICU of Zhongshan Hospital, Fudan University. Results Of 929 patients included in the eICU-CRD cohort, 248 (26.7%) had NIV failure. The time from extubation to NIV, age, Glasgow Coma Scale (GCS) score, heart rate, respiratory rate, mean blood pressure (MBP), saturation of pulse oxygen (SpO2), temperature, glucose, pH, pressure of oxygen in blood (PaO2), urine output, input volume, ventilation duration, and mean airway pressure were selected. After hyperparameter optimization, our model showed the greatest accuracy in predicting NIV failure (AUROC: 0.872 [95% CI 0.82–0.92]) among all predictive methods in an internal validation. In the prospective validation cohort, our model was also superior (AUROC: 0.846 [95% CI 0.80–0.89]). The sensitivity and specificity in the prediction group is 89% and 75%, while in the validation group they are 90% and 70%. MV duration and respiratory rate were the most important features. Additionally, we developed a web-based tool to help clinicians use our model. Conclusions This study developed and prospectively validated the CatBoost model, which can be used to identify patients who are at risk of NIV failure. Thus, those patients might benefit from early triage and more intensive monitoring. Trial registration: NCT03704324. Registered 1 September 2018, https://register.clinicaltrials.gov .

Abstract Background This study examined the associations between physical activity, obesity, and sarcopenia in middle-aged and older adults. Methods We analyzed the data of 8, 919 study participants aged between 45 to 97 (mean age = 57.2 ± 8.8) from a Southern state in the United States. Self-reported physical activity was classified to regular exercise ≥ 3 times/week, 0.05). Positive associations of exercising

Abstract Background Quantitative computed tomography (QCT) analysis may serve as a tool for assessing the severity of coronavirus disease 2019 (COVID-19) and for monitoring its progress. The present study aimed to assess the association between steroid therapy and quantitative CT parameters in a longitudinal cohort with COVID-19. Methods Between February 7 and February 17, 2020, 72 patients with severe COVID-19 were retrospectively enrolled. All 300 chest CT scans from these patients were collected and classified into five stages according to the interval between hospital admission and follow-up CT scans: Stage 1 (at admission); Stage 2 (3–7 days); Stage 3 (8–14 days); Stage 4 (15–21 days); and Stage 5 (22–31 days). QCT was performed using a threshold-based quantitative analysis to segment the lung according to different Hounsfield unit (HU) intervals. The primary outcomes were changes in percentage of compromised lung volume (%CL, − 500 to 100 HU) at different stages. Multivariate Generalized Estimating Equations were performed after adjusting for potential confounders. Results Of 72 patients, 31 patients (43.1%) received steroid therapy. Steroid therapy was associated with a decrease in %CL (− 3.27% [95% CI, − 5.86 to − 0.68, P = 0.01]) after adjusting for duration and baseline %CL. Associations between steroid therapy and changes in %CL varied between different stages or baseline %CL (all interactions, P

Low left ventricular ejection fraction (LVEF) was always considered a high-risk factor for surgery. A growing number of patients with preoperative low LVEF have undergone cardiac surgery in recent years. The transition of postoperative LVEF and its correlation with short-term outcomes is not yet clear. We retrospectively collected the clinical data of cardiac surgery patients with low preoperative LVEF (≤40%). LVEF measurements were collected preoperatively and at least twice postoperatively. The primary endpoint was the composite endpoint of hospital mortality or length of intensive care unit (ICU) stay ≥7 days. Univariate logistic regression was used to evaluate the association of each indicator with the outcomes, including calculation of the area under the receiver operating characteristic (ROC) curve. A two-piecewise linear regression model was applied to examine the threshold effect of the LVEF on the composite endpoint using a smoothing function. From 1 January to 31 December 2018, a total of 123 patients had low LVEF preoperatively, of whom 35 (28.5%) met the composite endpoint. LVEF was 35% [interquartile range (IQR) 30%–42%] at first measurement and increased to 40% (IQR 35%–45%) at final measurement during their hospitalization. There was a linear relationship between composite endpoint and lowest level of postoperative LVEF. The base e logarithm of odds ratio [Ln(OR)] of composite endpoint decreased with increasing LVEF (OR = 0.83, 95% confidence interval 0.76–0.91, p < 0.01). Most patients with low preoperative LVEF will benefit from cardiac surgery. The lowest measurement of postoperative LVEF can be used to evaluate the short-term outcome of patients after cardiac surgery.

Kidney transplantation (KT) is an ultimate treatment of end-stage chronic kidney disease, which can meet a lot of complications induced by immune system. With under-controlled immunosuppression, the patient will obtain a good prognosis. Otherwise, allograft disfunction will cause severe organ failure and even immune collapse. Acute or chronic allograft dysfunction after KT is related to Th17, Treg, and Th17/Treg to a certain extent. Elevated Th17 levels may lead to acute rejection or chronic allograft dysfunction. Treg mainly plays a protective role on allografts by regulating immune response. The imbalance of the two may further aggravate the balance of immune response and damage the allograft. Controlling Th17 level, improving Treg function and level, and adjusting Th17/Treg ratio may have positive effects on longer allograft survival and better prognosis of receptors.

BackgroundPhysical activity (PA) is associated with various health benefits, especially in improving chronic health conditions. However, the metabolic changes in host metabolism in response to PA remain unclear, especially in racially/ethnically diverse populations.ObjectiveThis study is to assess the metabolic profiles associated with the frequency of PA in White and African American (AA) men.MethodsUsing the untargeted metabolomics data collected from 698 White and AA participants (mean age: 38.0±8.0, age range: 20-50) from the Louisiana Osteoporosis Study (LOS), we conducted linear regression models to examine metabolites that are associated with PA levels (assessed by self-reported regular exercise frequency levels: 0, 1-2, and ≥3 times per week) in White and AA men, respectively, as well as in the pooled sample. Covariates considered for statistical adjustments included race (only for the pooled sample), age, BMI, waist circumstance, smoking status, and alcohol drinking.ResultsOf the 1133 untargeted compounds, we identified 7 metabolites associated with PA levels in the pooled sample after covariate adjustment with a false discovery rate of 0.15. Specifically, compared to participants who did not exercise, those who exercised at a frequency ≥3 times/week showed higher abundances in uracil, orotate, 1-(1-enyl-palmitoyl)-2-oleoyl-GPE (P-16:0/18:1) (GPE), threonate, and glycerate, but lower abundances in salicyluric glucuronide and adenine in the pooled sample. However, in Whites, salicyluric glucuronide and orotate were not significant. Adenine, GPE, and threonate were not significant in AAs. In addition, the seven metabolites were not significantly different between participants who exercised ≥3 times/week and 1-2 times/week, nor significantly different between participants with 1-2 times/week and 0/week in the pooled sample and respective White and AA groups.ConclusionsMetabolite responses to PA are dose sensitive and may differ between White and AA populations. The identified metabolites may help advance our knowledge of guiding precision PA interventions. Studies with rigorous study designs are warranted to elucidate the relationship between PA and metabolites.

Genotype imputation has a wide range of applications in genome-wide association study (GWAS), including increasing the statistical power of association tests, discovering trait-associated loci in meta-analyses, and prioritizing causal variants with fine-mapping. In recent years, deep learning (DL) based methods, such as sparse convolutional denoising autoencoder (SCDA), have been developed for genotype imputation. However, it remains a challenging task to optimize the learning process in DL-based methods to achieve high imputation accuracy. To address this challenge, we have developed a convolutional autoencoder (AE) model for genotype imputation and implemented a customized training loop by modifying the training process with a single batch loss rather than the average loss over batches. This modified AE imputation model was evaluated using a yeast dataset, the human leukocyte antigen (HLA) data from the 1,000 Genomes Project (1KGP), and our in-house genotype data from the Louisiana Osteoporosis Study (LOS). Our modified AE imputation model has achieved comparable or better performance than the existing SCDA model in terms of evaluation metrics such as the concordance rate (CR), the Hellinger score, the scaled Euclidean norm (SEN) score, and the imputation quality score (IQS) in all three datasets. Taking the imputation results from the HLA data as an example, the AE model achieved an average CR of 0.9468 and 0.9459, Hellinger score of 0.9765 and 0.9518, SEN score of 0.9977 and 0.9953, and IQS of 0.9515 and 0.9044 at missing ratios of 10% and 20%, respectively. As for the results of LOS data, it achieved an average CR of 0.9005, Hellinger score of 0.9384, SEN score of 0.9940, and IQS of 0.8681 at the missing ratio of 20%. In summary, our proposed method for genotype imputation has a great potential to increase the statistical power of GWAS and improve downstream post-GWAS analyses.

The cardiac function reserve is crucial for the successful weaning of V-A ECMO. During the V-A ECMO weaning phase, the gradual reduction in pump flow converts the blood flow originally driven by the pump to native cardiac output and also transforms afterload (caused by retrograde flow) into ventricular preload, thus introducing a “flow challenge” to the native heart. In this perspective, we propose to use this flow challenge as a test to simulate the preload-to-afterload conversion to assess cardiac functional reserve quantitatively. With this short article we offer the hemodynamic and clinical aspects regarding the flow challenge test.

As a photoelectric material, the luminescent efficiency improvement of organic–inorganic perovskite material is a hot topic. This work fabricated a nanoporous distributed Bragg reflector based on GaN with a periodic structure using electrochemical etching methods. Considering the fact that hybrid perovskite materials are difficult to prepare on an inorganic GaN-based substrate, ultraviolet ozone treatment was implemented to enhance the surface activity of the prepared distributed Bragg reflector substrate. Cubic CH3NH3PbBr3 crystals with smooth surfaces and precise edges were successfully prepared on the ozone-treated distributed Bragg reflector substrate by a two-step immersion method in the air environment. The structural property of the prepared CH3NH3PbBr3 crystals was investigated using X-ray diffraction, scanning electron microscopy and Fourier-transform infrared spectroscopy. The structural analysis results showed that CH3NH3PbBr3 crystals grown on the prepared distributed Bragg reflector and reference substrates have the same structure, with a good crystal quality. The photoluminescence intensity of CH3NH3PbBr3 crystals grown on the distributed Bragg reflector was significantly enhanced. The enhancement is approximately 3.11-fold compared with CH3NH3PbBr3 crystals grown on the unetched reference GaN substrate. Moreover, there is a 7.2 nm spectral blue shift. The enhancement of the photoluminescence intensity could be attributed to the out-coupling of emission light in the prepared crystals, and the blue shift could be attributed to the stress relaxation caused by the nanoporous GaN structure of the distributed Bragg reflector substrate.

Cow milk consumption (CMC) and alterations of gut bacterial composition are proposed to be closely related to human health and disease. Our research aims to investigate the changes in human gut microbial composition in Chinese peri-/postmenopausal women with different CMC habits. A total of 517 subjects were recruited and questionnaires about their CMC status were collected; 394 subjects were included in the final analyses. Fecal samples were used for studying gut bacterial composition. All the subjects were divided into a control group (n = 248) and a CMC group (n = 146) according to their CMC status. Non-parametric tests and LEfSe at different taxonomic levels were used to reveal differentially abundant taxa and functional categories across different CMC groups. Relative abundance (RA) of one phylum (p_Actinobacteria), three genera (g_Bifidobacterium, g_Anaerostipes, and g_Bacteroides), and 28 species diversified significantly across groups. Specifically, taxa g_Anaerostipes (p < 0.01), g_Bacteroides (p < 0.05), s_Anaerostipes_hadrus (p < 0.01), and s_Bifidobacterium_pseudocatenulatum (p < 0.01) were positively correlated with CMC levels, but p_Actinobacteria (p < 0.01) and g_Bifidobacterium (p < 0.01) were negatively associated with CMC levels. KEGG module analysis revealed 48 gut microbiome functional modules significantly (p < 0.05) associated with CMC, including Vibrio cholerae pathogenicity signature, cholera toxins (p = 9.52e-04), and cephamycin C biosynthesis module (p = 0.0057), among others. In conclusion, CMC was associated with changes in gut microbiome patterns including beta diversity and richness of some gut microbiota. The alterations of certain bacteria including g_Anaerostipes and s_Bifidobacterium_pseudocatenulatum in the CMC group should be important for human health. This study further supports the biological value of habitual cow milk consumption.

Purpose: The increasing prevalence of sarcopenia remains an ongoing challenge to health care systems worldwide. The lack of treatments encouraged the discovery of human proteomes to find potential therapeutic targets. As one of the major components of the human proteome, plasma proteins are functionally connected with various organs of the body to regulate biological processes and mediate overall homeostasis, which makes it crucial in various complex processes such as aging and chronic diseases. By performing a systematic causal analysis of the plasma proteome, we attempt to reveal the etiological mechanism and discover drug targets for sarcopenia.Methods: By using data from four genome-wide association studies for blood proteins and the UK Biobank data for sarcopenia-related traits, we applied two-sample Mendelian randomization (MR) analysis to evaluate 310 plasma proteins as possible causal mediators of sarcopenia-related traits: appendicular lean mass (ALM) and handgrip strength (right and left). Then we performed a two-sample bidirectional Mendelian randomization analysis for the identified putatively causal proteins to assess potential reverse causality that the trait values may influence protein levels. Finally, we performed phenome-wide MR analysis of the identified putatively causal proteins for 784 diseases to test the possible side effects of these proteins on other diseases.Results: Five plasma proteins were identified as putatively causal mediators of sarcopenia-related traits. Specifically, leukocyte immunoglobulin-like receptor subfamily B member 2 (LILRB2), asporin (ASPN), and contactin-2 (CNTN2) had potential causal effects on appendicular lean mass, and ecto-ADP-ribosyltransferase 4 (ART4) and superoxide dismutase 2 (SOD2) had putative causal effects on the handgrip strength, respectively. None of the five putatively causal proteins had a reverse causality relationship with sarcopenia-related traits, and no side effects on other diseases were identified.Conclusion: We identified five plasma proteins that may serve as putatively potential novel drug targets for sarcopenia. Our study attested to the value of two-sample MR analysis in identifying and prioritizing putatively potential therapeutic targets for complex diseases.

BackgroundWe use longitudinal chest CT images to explore the effect of steroids therapy in COVID-19 pneumonia which caused pulmonary lesion progression.Materials and MethodsWe retrospectively enrolled 78 patients with severe to critical COVID-19 pneumonia, among which 25 patients (32.1%) who received steroid therapy. Patients were further divided into two groups with severe and significant-severe illness based on clinical symptoms. Serial longitudinal chest CT scans were performed for each patient. Lung tissue was segmented into the five lung lobes and mapped into the five pulmonary tissue type categories based on Hounsfield unit value. The volume changes of normal tissue and pneumonia fibrotic tissue in the entire lung and each five lung lobes were the primary outcomes. In addition, this study calculated the changing percentage of tissue volume relative to baseline value to directly demonstrate the disease progress.ResultsSteroid therapy was associated with the decrease of pneumonia fibrotic tissue (PFT) volume proportion. For example, after four CT cycles of treatment, the volume reduction percentage of PFT in the entire lung was −59.79[±12.4]% for the steroid-treated patients with severe illness, and its p-value was 0.000 compared to that (−27.54[±85.81]%) in non-steroid-treated ones. However, for the patient with a significant-severe illness, PFT reduction in steroid-treated patients was −41.92[±52.26]%, showing a 0.275 p-value compared to −37.18[±76.49]% in non-steroid-treated ones. The PFT evolution analysis in different lung lobes indicated consistent findings as well.ConclusionSteroid therapy showed a positive effect on the COVID-19 recovery, and its effect was related to the disease severity.

Abstract Background Evaluation of fluid responsiveness during veno-arterial extracorporeal membrane oxygenation (VA-ECMO) support is crucial. The aim of this study was to investigate whether changes in left ventricular outflow tract velocity–time integral (ΔVTI), induced by a Trendelenburg maneuver, could predict fluid responsiveness during VA-ECMO. Methods This prospective study was conducted in patients with VA-ECMO support. The protocol included four sequential steps: (1) baseline-1, a supine position with a 15° upward bed angulation; (2) Trendelenburg maneuver, 15° downward bed angulation; (3) baseline-2, the same position as baseline-1, and (4) fluid challenge, administration of 500 mL gelatin over 15 min without postural change. Hemodynamic parameters were recorded at each step. Fluid responsiveness was defined as ΔVTI of 15% or more, after volume expansion. Results From June 2018 to December 2019, 22 patients with VA-ECMO were included, and a total of 39 measurements were performed. Of these, 22 measurements (56%) met fluid responsiveness. The R 2 of the linear regression was 0.76, between ΔVTIs induced by Trendelenburg maneuver and the fluid challenge. The area under the receiver operating characteristic curve of ΔVTI induced by Trendelenburg maneuver to predict fluid responsiveness was 0.93 [95% confidence interval (CI) 0.81–0.98], with a sensitivity of 82% (95% CI 60–95%), and specificity of 88% (95% CI 64–99%), at a best threshold of 10% (95% CI 6–12%). Conclusions Changes in VTI induced by the Trendelenburg maneuver could effectively predict fluid responsiveness in VA-ECMO patients. Trial registration ClinicalTrials.gov, NCT 03553459 (the TEMPLE study). Registered on May 30, 2018

Early retention or initial threshold voltage shift (IVS) is one of the key reliability challenges in charge trapping memory (CTM) based 3D NAND flash. Re-program scheme was introduced in quad-level-cell (QLC) NAND (Shibata et al., 2007, Lee et al., 2018, Shibata et al., 2019, and Khakifirooz et al., 2021), and the IVS improvement by re-program scheme was reported. In this work, it is found that re-program can suppress ~81% of IVS in 3D NAND, which is much more significant than that of 2D NAND ~50% (Chen et al., 2010). The mechanisms of IVS improvement by re-program scheme in 3D NAND are investigated. Both vertical de-trapping in the BE-tunneling oxide and charge lateral migration (LM) in the charge-trap layer are suppressed in re-program. Re-program is effective in vertical de-trapping suppression both in checker-board pattern (C/P) and solid-board pattern (S/P) cases, and is effective in LM suppression only in C/P case. Furthermore, the LM improvement by re-program scheme is more pronounced with gate length (Lg) and inter-gate space (Ls) scaling down, showing potential in the reliability improvement of advanced 3D NAND technologies.

Background In this study, we applied a composite index of neutrophil-lymphocyte * platelet ratio (NLPR), and explore the significance of the dynamics of perioperative NLPR in predicting cardiac surgery-associated acute kidney injury (CSA-AKI). Methods During July 1st and December 31th 2019, participants were prospectively derived from the ‘Zhongshan Cardiovascular Surgery Cohort’. NLPR was determined using neutrophil counts, lymphocyte and platelet count at the two-time points. Dose-response relationship analyses were applied to delineate the non-linear odds ratio (OR) of CSA-AKI in different NLPR levels. Then NLPRs were integrated into the generalized estimating equation (GEE) to predict the risk of AKI. Results Of 2449 patients receiving cardiovascular surgery, 838 (34.2%) cases developed CSA-AKI with stage 1 (n = 658, 26.9%), stage 2–3 (n = 180, 7.3%). Compared with non-AKI patients, both preoperative and postoperative NLPR were higher in AKI patients (1.1[0.8, 1.8] vs. 0.9[0.7,1.4], p 11.0 were more likely to develop AKI with an OR of 1.02. Integrating the dynamic NLPRs into the GEE model, we found that the AUC was 0.806(95% CI 0.793–0.819), which was significantly higher than the AUC without NLPR (0.799, p

Abstract Background The present study aimed at comparing the success rate and safety of proximal versus distal approach for ultrasound (US)-guided axillary vein catheterization (AVC) in cardiac surgery patients susceptible to bleeding. Methods In this single-center randomized controlled trial, cardiac surgery patients susceptible to bleeding and requiring AVC were randomized to either the proximal or distal approach group for US-guided AVC. Patients susceptible to bleeding were defined as those who received oral antiplatelet drugs or anticoagulants for at least 3 days. Success rate, catheterization time, number of attempts, and mechanical complications within 24 h were recorded for each procedure. Results A total of 198 patients underwent randomization: 99 patients each to the proximal and distal groups. The proximal group had the higher first puncture success rate (75.8% vs. 51.5%, p

Abstract Background Over 5,488,000 cases of coronavirus disease-19 (COVID-19) have been reported since December 2019. We aim to explore risk factors associated with mortality in COVID-19 patients and assess the use of D-dimer as a biomarker for disease severity and clinical outcome. Methods We retrospectively analyzed the clinical, laboratory, and radiological characteristics of 248 consecutive cases of COVID-19 in Renmin Hospital of Wuhan University, Wuhan, China from January 28 to March 08, 2020. Univariable and multivariable logistic regression methods were used to explore risk factors associated with in-hospital mortality. Correlations of D-dimer upon admission with disease severity and in-hospital mortality were analyzed. Receiver operating characteristic curve was used to determine the optimal cutoff level for D-dimer that discriminated those survivors versus non-survivors during hospitalization. Results Multivariable regression that showed D-dimer > 2.0 mg/L at admission was the only variable associated with increased odds of mortality [OR 10.17 (95% CI 1.10–94.38), P = 0.041]. D-dimer elevation (≥ 0.50 mg/L) was seen in 74.6% (185/248) of the patients. Pulmonary embolism and deep vein thrombosis were ruled out in patients with high probability of thrombosis. D-dimer levels significantly increased with increasing severity of COVID-19 as determined by clinical staging (Kendall’s tau-b = 0.374, P = 0.000) and chest CT staging (Kendall’s tau-b = 0.378, P = 0.000). In-hospital mortality rate was 6.9%. Median D-dimer level in non-survivors (n = 17) was significantly higher than in survivors (n = 231) [6.21 (3.79–16.01) mg/L versus 1.02 (0.47–2.66) mg/L, P = 0.000]. D-dimer level of > 2.14 mg/L predicted in-hospital mortality with a sensitivity of 88.2% and specificity of 71.3% (AUC 0.85; 95% CI = 0.77–0.92). Conclusions D-dimer is commonly elevated in patients with COVID-19. D-dimer levels correlate with disease severity and are a reliable prognostic marker for in-hospital mortality in patients admitted for COVID-19.

In this study, the effects of soil spatial variability in braced excavations are investigated by focusing on three structural responses: wall bending moments, wall shear forces, and strut forces. The soil spatial variability is modeled using random field theory, and the generated soil parameters are mapped onto a finite element model. A procedure for automating the Monte Carlo simulation, which is used for probabilistic analysis, is described. A case study demonstrates that the soil spatial variability has a considerable effect on the excavation-induced structural responses. Furthermore, a reliability analysis is performed to estimate the failure probability for three structural failure modes. The results demonstrate the importance of considering soil spatial variability in the structural assessment of braced excavations. Keywords: Braced excavations, Soil spatial variability, Random field modeling, Finite element method

ObjectiveEvaluate the effect of the combination of clindamycin with low-dose trimethoprim-sulfamethoxazole (TMP/SMX) regimen on sever Pneumocystis pneumonia (PCP) after renal transplantation.Method20 severe PCP patients after renal transplantation were included in this historical-control, retrospective study. A 10 patients were treated with the standard dose of TMP/SMX (T group), the other 10 patients were treated with the combination of clindamycin and low dose TMP/SMX (CT group).ResultsAlthough there was no significant difference in the hospital survival between the two groups, the CT protocol improved the PaO2/FiO2 ratio more significantly and rapidly after the 6th ICU day (1.51 vs. 0.38, P = 0.014). CT protocol also ameliorated the pulmonary infiltration and the lactate dehydrogenase level more effectively. Moreover, the CT protocol reduced the incidence of pneumomediastinum (0 vs. 50%, P = 0.008), the length of hospital staying (26.5 vs. 39.0 days, P = 0.011) and ICU staying (12.5 vs. 22.5 days, P = 0.008). Furthermore, more thrombocytopenia (9/10 vs. 3/10, P = 0.020) was emerged in the T group than in the CT group. The total adverse reaction rate was much lower in the CT group than in the T group (8/80 vs. 27/80, P < 0.001). Consequently, the dosage of TMP/SMX was reduced in 8 patients, while only 2 patients in the CT group received TMP/SMX decrement (P = 0.023).ConclusionThe current study proposed that clindamycin combined with low-dose TMP/SMX was more effective and safer the than single use of TMP/SMX for severe PCP patients after renal transplantation (NCT 04328688).

BackgroundSeptic myocardial depression has been associated with increased morbidity and mortality. miR-885-5p has been shown to regulate cell growth, senescence, and/or apoptosis. Published studies demonstrated that Homeobox-containing protein 1 (HMBOX1) inhibits inflammatory response, regulates cell autophagy, and apoptosis. However, the role of miR-885-5p/HMBOX1 in sepsis and septic myocardial depression and the underlying mechanism is not fully understood.Materials and MethodsExosomes (exos) derived from sepsis patients (sepsis-exos) were isolated using ultracentrifugation. Rats were subjected to cecal ligation and puncture surgery and treated with sepsis-exos. HMBOX1 was knocked down or overexpressed in AC16 cells using lentiviral plasmids carrying short interfering RNAs targeting human HMBOX1 or carrying HMBOX1 cDNA. Cell pyroptosis was measured by flow cytometry. The secretion of IL-1β and IL-18 was examined by ELISA kits. Quantitative polymerase chain reaction (PCR) or western blot was used for gene expression.ResultsSepsis-exos increased the level of miR-885-5p, decreased HMBOX1, elevated IL-1β and IL-18, and promoted pyroptosis in AC16 cells. Septic rats treated with sepsis-exos increased the serum inflammatory cytokines is associated with increased pyroptosis-related proteins of hearts. MiR-885-5p bound to the three prime untranslated regions of HMBOX1 to negatively regulate its expression. Overexpressing HMBOX1 reversed miR-885-5p-induced elevation of inflammatory cytokines and upregulation of NLRP3, caspase-1, and GSDMD-N in AC16 cells. The mechanistic study indicated that the effect of HMBOX1 was NF-κB dependent.ConclusionSepsis-exos promoted the pyroptosis of AC16 cells through miR-885-5p via HMBOX1. The results show the significance of the miR-885-5p/HMBOX1 axis in myocardial cell pyroptosis and provide new directions for the treatment of septic myocardial depression.

Objective: Primary graft dysfunction (PGD) is the leading cause of early death after heart transplantation. Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) can provide temporary mechanical circulatory support and time for functional recovery of the transplanted heart. The purpose of this study was to analyze the timing and prognoses of VA-ECMO in patients with severe PGD after heart transplantation.Methods: A total of 130 patients underwent heart transplantation at the Zhongshan Hospital Affiliated with Fudan University between January 2014 and December 2020. All patients received basiliximab immunoinduction and a classic double vena cava anastomosis orthotopic heart transplantation. Among them, 29 patients (22.3%) developed severe PGD in the early postoperative period. VA-ECMO was performed in patients with difficulty weaning from cardiopulmonary bypass (CPB) or postoperative refractory cardiogenic shock. Patients were divided into two groups according to whether or not they were successfully weaned from VA-ECMO (patients who survived for 48 h after weaning and did not need VA-ECMO assistance again). The perioperative clinical data were recorded, and all patients were followed up until discharge. Early outcomes were compared between groups.Results: A total of 29 patients with VA-ECMO support after heart transplantation were included in this study. The proportion of patients receiving VA-ECMO was 22.3% (29/130). Nineteen patients (65.5%) needed VA-ECMO due to difficulty with weaning from CPB, and 10 patients required VA-ECMO for postoperative cardiogenic shock. Nineteen patients (65.5%) were successfully weaned from VA-ECMO. Overall, in-hospital mortality of VA-ECMO support patients was 55.2%. The main causes of death were ventricular fibrillation (four cases), major bleeding (three cases), infection (four cases), and graft failure (five cases).Conclusion: Despite advances in heart transplantation, severe PGD remains a lethal complication after heart transplantation. At present, the treatment for severe PGD after heart transplantation is a challenge. VA-ECMO provides an effective treatment for severe PGD after heart transplantation, which can promote graft function recovery.

Background: Enteral nutrition (EN) is recommended within the first 24–48 h for patients with hemodynamic stability, following admission to an intensive care unit (ICU). However, for patients with approximate stable hemodynamics requiring mechanical circulatory support and vasoactive drugs, the application of early EN remains controversial. We sought to evaluate the tolerance of early EN in patients with cardiogenic shock who required vasoactive drugs and mechanical circulatory support after cardiac surgery.Methods: This single-center, prospective observational study included patients with cardiogenic shock, requiring vasoactive drugs and mechanical circulatory support after cardiac surgery, undergoing EN. The primary endpoint was EN tolerance and secondary endpoints were mortality, length of mechanical ventilation, and length of ICU stay.Results: From February 2019 to December 2020, 59 patients were enrolled, of which 25 (42.37%) developed intolerance within 3 days of starting EN. Patients in the EN intolerant group had a longer median length of mechanical ventilation (380 vs. 128 h, p = 0.006), a longer median ICU stay (20 vs. 11.5 days, p = 0.03), and a higher proportion of bloodstream infections (44 vs. 14.71%, p = 0.018). The median EN calorie levels for all patients in the first 3 days of EN were 4.00, 4.13, and 4.28 kcal/kg/day, respectively. Median protein intake levels of EN in the first 3 days were 0.18, 0.17, and 0.17 g/kg/day, respectively. No significant difference was observed in the median dose of vasoactive drugs between the groups (0.035 vs. 0.05 μg/kg/min, p = 0.306).Conclusions: Patients with cardiogenic shock after cardiac surgery had a high proportion of early EN intolerance, and patients with EN intolerance had a worse prognosis, but no significant correlation was identified between EN tolerance and the dose of vasoactive drugs.

Background: Hypoperfusion, a common manifestation of many critical illnesses, could lead to abnormalities in body surface thermal distribution. However, the interpretation of thermal images is difficult. Our aim was to assess the mortality risk of critically ill patients at risk of hypoperfusion in a prospective cohort by infrared thermography combined with deep learning methods. Methods: This post-hoc study was based on a cohort at high-risk of hypoperfusion. Patients’ legs were selected as the region of interest. Thermal images and conventional hypoperfusion parameters were collected. Six deep learning models were attempted to derive the risk of mortality (range: 0 to 100%) for each patient. The area under the receiver operating characteristic curve (AUROC) was used to evaluate predictive accuracy. Results: Fifty-five hospital deaths occurred in a cohort consisting of 373 patients. The conventional hypoperfusion (capillary refill time and diastolic blood pressure) and thermal (low temperature area rate and standard deviation) parameters demonstrated similar predictive accuracies for hospital mortality (AUROC 0.73 and 0.77). The deep learning methods, especially the ResNet (18), could further improve the accuracy. The AUROC of ResNet (18) was 0.94 with a sensitivity of 84% and a specificity of 91% when using a cutoff of 36%. ResNet (18) presented a significantly increasing trend in the risk of mortality in patients with normotension (13 [7 to 26]), hypotension (18 [8 to 32]) and shock (28 [14 to 62]). Conclusions: Interpreting infrared thermography with deep learning enables accurate and non-invasive assessment of the severity of patients at risk of hypoperfusion.