HRR as a predictor of lung health: insights from the NHANES database.

Background: Chronic respiratory diseases (CRPD) are a global health threat characterized by oxidative stress, systemic inflammation, hypoxemia, and respiratory distress. Inflammatory indicators such as hemoglobin-to-red blood cell distribution width ratio (HRR) have been explored in relation to diseases of the respiratory system, but the correlation between HRR and pulmonary function has not been established. As part of this study, a representative sample of the National Health and Nutrition Examination Survey (NHANES) respondents aged 40 or over was used to examine the correlation between HRR and pulmonary function indices.

Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm - a 10-year multicenter retrospective study.

Background: Gastroparesis following complete mesocolic excision (CME) can precipitate a cascade of severe complications, which may significantly hinder postoperative recovery and diminish the patient's quality of life. In the present study, four advanced machine learning algorithms-Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), and -nearest neighbor (KNN)-were employed to develop predictive models. The clinical data of critically ill patients transferred to the intensive care unit (ICU) post-CME were meticulously analyzed to identify key risk factors associated with the development of gastroparesis.

The association between neutrophil to high-density lipoprotein cholesterol ratio and gallstones: a cross-sectional study.

Objective: Several studies have discussed the relationship between cholesterol and gallstones, and high-density lipoprotein cholesterol (HDL-C) as a representative of this has been addressed in various diseases. The metric neutrophil to high-density lipoprotein cholesterol ratio (NHR) derived from HDL-C has attracted much attention. The purpose of this article is to examine the relationship between NHR and gallstones in a population of American adults.

Identification of intraoperative hypoxemia and hypoproteinemia as prognostic indicators in anastomotic leakage post-radical gastrectomy: an 8-year multicenter study utilizing machine learning techniques.

Background: Complications and mortality rates following gastrectomy for gastric cancer have improved over recent years; however, complications such as anastomotic leakage (AL) continue to significantly impact both immediate and long-term prognoses. This study aimed to develop a machine learning model to identify preoperative and intraoperative high-risk factors and predict mortality in patients with AL after radical gastrectomy.

Methods: For this investigation, 906 patients diagnosed with gastric cancer were enrolled and evaluated, with a comprehensive set of 36 feature variables collected.

Using Generalized Linear Mixed Models in the Analysis of Count and Rate Data in Single-case Eperimental Designs: A Step-by-step Tutorial.

Generalized linear mixed models (GLMMs) have great potential to deal with count and rate data in single-case experimental designs (SCEDs). However, applied researchers face challenges to apply such an advanced approach in their own studies. Hence, our study aimed to provide a tutorial and demonstrate a step-by-step procedure of using GLMMs to handle SCED count and rate outcomes.

Helicobacter Pylori Infection as the Predominant High-Risk Factor for Gastric Cancer Recurrence Post-Gastrectomy: An 8-Year Multicenter Retrospective Study.

Purpose: The reappearance of gastric cancer, a frequent postoperative complication following radical gastric cancer surgery, substantially impacts the near-term and far-reaching medical outlook of patients. The objective of this research was to create a machine learning algorithm that could recognize high-risk factors for gastric cancer recurrence and anticipate the correlation between gastric cancer recurrence and Helicobacter pylori (H. pylori) infection.

Association between dietary copper intake and constipation in US adults.

Dietary micronutrients are integral to the development and progression of constipation; however, the specific relationship between dietary copper intake and constipation has not been thoroughly investigated. This study aims to examine the correlation between dietary copper intake and constipation among U.S.

The correlation between urinary iodine levels and gallstone risk: elevated iodine intake linked to gallstone occurrence.

Background: Essential trace elements are vital for human growth and development. Nevertheless, excessive intake can pose risks. As of yet, no research has looked at the possibility of a relationship between the prevalence of gallstones and urinary concentrations of nickel, molybdenum, and iodine.

The association between dietary vitamin B1 intake and constipation: a population-based study.

Background: Numerous researches have indicated a correlation between the intake of dietary micronutrients and the occurrence of constipation. Nevertheless, the correlation between constipation and vitamin B1 remains uninvestigated. The main aim of this research was to examine the association between chronic constipation and the consumption of vitamin B1 in the diet among adult participants of the National Health and Nutrition Examination Survey (NHANES).

Association between dietary magnesium intake and gallstones: the mediating role of atherogenic index of plasma.

Background: Dyslipidemia and abnormalities in cholesterol metabolism are commonly observed in individuals with gallstone disease. Previous research has demonstrated that dietary magnesium can influence lipid metabolism. The atherogenic index of plasma (AIP) has emerged as a novel lipid marker.

Diabetes Mellitus Mediates the Relationship Between Atherogenic Index of Plasma and Gallstones: A Population-Based Cross-Sectional Study.

Purpose: Previous studies have shown a correlation between diabetes mellitus and gallstone formation. The atherogenic index of plasma (AIP) is associated with many metabolic diseases. However, insufficient evidence still exists to elucidate the association between AIP and gallstones.

Identification of high-risk factors for recurrence of colon cancer following complete mesocolic excision: An 8-year retrospective study.

Background: Colon cancer recurrence is a common adverse outcome for patients after complete mesocolic excision (CME) and greatly affects the near-term and long-term prognosis of patients. This study aimed to develop a machine learning model that can identify high-risk factors before, during, and after surgery, and predict the occurrence of postoperative colon cancer recurrence.

Methods: The study included 1187 patients with colon cancer, including 110 patients who had recurrent colon cancer.

Identification of high-risk factors associated with mortality at 1-, 3-, and 5-year intervals in gastric cancer patients undergoing radical surgery and immunotherapy: an 8-year multicenter retrospective analysis.

Background: Combining immunotherapy with surgical intervention is a prevailing and radical therapeutic strategy for individuals afflicted with gastric carcinoma; nonetheless, certain patients exhibit unfavorable prognoses even subsequent to this treatment regimen. This research endeavors to devise a machine learning algorithm to recognize risk factors with a high probability of inducing mortality among patients diagnosed with gastric cancer, both prior to and during their course of treatment.

Methods: Within the purview of this investigation, a cohort of 1015 individuals with gastric cancer were incorporated, and 39 variables encompassing diverse features were recorded.

Applying interpretable machine learning algorithms to predict risk factors for permanent stoma in patients after TME.

Objective: The purpose of this study was to develop a machine learning model to identify preoperative and intraoperative high-risk factors and to predict the occurrence of permanent stoma in patients after total mesorectal excision (TME).

Methods: A total of 1,163 patients with rectal cancer were included in the study, including 142 patients with permanent stoma. We collected 24 characteristic variables, including patient demographic characteristics, basic medical history, preoperative examination characteristics, type of surgery, and intraoperative information.

Uncertain Dynamic Characteristic Analysis for Structures with Spatially Dependent Random System Parameters.

This work presents a robust non-deterministic free vibration analysis for engineering structures with random field parameters in the frame of stochastic finite element method. For this, considering the randomness and spatial correlation of structural physical parameters, a parameter setting model based on random field theory is proposed to represent the random uncertainty of parameters, and the stochastic dynamic characteristics of different structural systems are then analyzed by incorporating the presented parameter setting model with finite element method. First, Gauss random field theory is used to describe the uncertainty of structural material parameters, the random parameters are then characterized as the standard deviation and correlation length of the random field, and the random field parameters are then discretized with the Karhunen-Loeve expansion method.

Operation decision of competitive mining supply chain based on social responsibility.

The development of the green economy has significantly impact the traditional mining industry. Mining enterprises must invest in green technology to reduce the environmental pollution caused by flying dust and soil erosion and are subject to increased scrutiny to be socially responsible when conducting their business. To address this issue, we consider a competitive mining supply chain system consisting of two excavators and two exclusive retailers.

Myosin head as the main off-odors binding region: Key binding residues and conformational changes in the binding process.

This study aims to elucidate the dynamic binding characteristics between off-odors (hexanal, 1-octen-3-ol, nonanal) and myosin at cold storage (277 K) and oral temperatures (310 K) through spatial-temporal molecular dynamics (MD) simulation. Conformational analysis indicated that binding with off-odors could not significantly change the myosin secondary structure, and the myosin/(off-odors) structure became a stable and compact state in the later binding stages. Myosin head was the primary binding region with hydrophobic interactions as the dominant force rather than hydrogen bonds (average bond number 202.

Improvement of methanol tolerance and catalytic activity of Rhizomucor miehei lipase for one-step synthesis of biodiesel by semi-rational design.

Exploiting highly active and methanol-resistant lipase is of great significance for biodiesel production. A semi-rational directed evolution method combined with N-glycosylation is reported, and all mutants exhibiting higher catalytic activity and methanol tolerance than the wild type (WT). Mutant N267 retained 64% activity after incubation in 50% methanol for 8 h, which was 48% greater than that of WT.

A New Approach for Fatigue Reliability Analysis of Thin-Walled Structures with DC-ILSSVR.

Fatigue analysis is of great significance for thin-walled structures in the spacecraft industry to ensure their service reliability during operation. Due to the complex loadings of thin-walled structures under thermal-structural-acoustic coupling conditions, the calculation cost of finite element (FE) simulations is relatively expensive. To improve the computational efficiency of dynamic reliability analysis on thin-walled structures to within acceptable accuracy, a novel probabilistic approach named DC-ILSSVR was developed, in which the rotation matrix optimization (RMO) method was used to initially search for the model parameters of least squares support vector regression (LS-SVR).

Arginine methylation of METTL14 promotes RNA N-methyladenosine modification and endoderm differentiation of mouse embryonic stem cells.

RNA N-methyladenosine (mA), the most abundant internal modification of mRNAs, plays key roles in human development and health. Post-translational methylation of proteins is often critical for the dynamic regulation of enzymatic activity. However, the role of methylation of the core methyltransferase METTL3/METTL14 in mA regulation remains elusive.

Structural insights into acyl-ACP selective recognition by the Aeromonas hydrophila AHL synthase AhyI.

Background: Aeromonas hydrophila is a gram-negative bacterium and the major causative agent of the fish disease motile aeromonad septicemia (MAS). It uses N-acyl-homoserine lactone (AHL) quorum sensing signals to coordinate biofilm formation, motility, and virulence gene expression. The AHL signaling pathway is therefore considered to be a therapeutic target against pathogenic A.

Green Supply Chain Decisions Under Different Power Structures: Wholesale Price vs. Revenue Sharing Contract.

In the market, once consumers have a low-carbon preference, they will choose green low-carbon products. The market demand for green products is not only related to product price, but also consumers' low-carbon preference. In this way, enterprise has to consider the cost of carbon emissions in the process of production and operation.

Identification of a Novel Acyl Homoserine Lactone Synthase, AhyI, in and Structural Basis for Its Substrate Specificity.

In the Gram-negative bacterium , -acyl homoserine lactone (AHL)-mediated quorum sensing (QS) influences pathogenicity, protein secretion, and motility. However, the catalytic mechanism of AHL biosynthesis and the structural basis and substrate specificity for AhyI members remain unclear. In this study, we cloned the gene from the isolate HX-3, and the overexpressed AhyI protein was confirmed to produce six types of AHLs by ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis, contrasting with previous reports that AhyI only produces -butanoyl-l-homoserine lactone (C-HSL) and -hexanoyl-l-homoserine lactone (C-HSL).

An effective HIV-1 integrase inhibitor screening platform: Rationality validation of drug screening, conformational mobility and molecular recognition analysis for PFV integrase complex with viral DNA.

As an important target for the development of novel anti-AIDS drugs, HIV-1 integrase (IN) has been widely concerned. However, the lack of a complete accurate crystal structure of HIV-1 IN greatly blocks the discovery of novel inhibitors. In this work, an effective HIV-1 IN inhibitor screening platform, namely PFV IN, was filtered from all species of INs.