π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing.

Peptide sequencing via tandem mass spectrometry (MS/MS) is essential in proteomics. Unlike traditional database searches, deep learning excels at de novo peptide sequencing, even for peptides missing from existing databases. Current deep learning models often rely on autoregressive generation, which suffers from error accumulation and slow inference speeds.

Identification of iron metabolism-related genes in coronary heart disease and construction of a diagnostic model.

Background: Coronary heart disease is a common cardiovascular disease, yferroptosiset its relationship with iron metabolism remains unclear.

Methods: Gene expression data from peripheral blood samples of patients with coronary heart disease and a healthy control group were utilized for a comprehensive analysis that included differential expression analysis, weighted gene co-expression network analysis, gene enrichment analysis, and the development of a logistic regression model to investigate the associations and differences between the groups. Additionally, the CIBERSORT algorithm was employed to examine the composition of immune cell types within the samples.

Exploring molecular mechanisms of postoperative delirium through multi-omics strategies in plasma exosomes.

Currently, the diagnosis of delirium is solely based on clinical observation, lacking objective diagnostic tools, and the regulatory networks and pathological mechanisms behind it are not yet fully understood. Exosomes have garnered considerable interest as potential biomarkers for a variety of illnesses. This research aimed to delineate both the proteomic and metabolomic landscapes inherent to exosomes, assessing their diagnostic utility in postoperative delirium (POD) and understanding the underlying pathophysiological frameworks.

Study on the correlation between the level of insulin resistance and changes in the degree of cerebral atherosclerosis in non-diabetic patients.

Background: Cerebral infarction is a health problem of global concern and brings a particular burden to medical treatment.

Objective: To analyze the correlation between insulin resistance (IR) levels and changes in cerebral atherosclerosis (AS) degree in non-diabetic patients with cerebral infarction.

Methods: A total of 134 non-diabetic patients with cerebral infarction who visited the Department of Neurology of our hospital from May 2019 to October 2020 were selected and underwent MRA/CTA (Magnetic resonance angiography/Computed tomography angiography) of cerebral arteries to refine the cerebrovascular imaging data, and according to the results of cerebral AS load, the patients were divided into mild AS group and severe AS group, and the insulin resistance index was calculated with HOMA-IR (homeostasis model assessment of insulin resistance) to evaluate the IR level and HOMA-IR was compared between the two groups.

Horizontal transmission of a rice bacterial pathogen among plants by rice planthoppers.

Pantoea ananatis is a bacterium commonly found in various agronomic crops and agricultural pests. In this study, we present findings on a genome-reduced strain of P. ananatis, known as Lstr, which was initially isolated from Laodelphax striatellus (small brown rice planthopper, SBPH).

Exploring the causal relationship between the immune cell-inflammatory factor axis and lung cancer: a Mendelian randomization study.

Background: Lung cancer is a major health burden globally and smoking is a well-known risk factor. It has been observed that chronic inflammation contributes to lung cancer progression, with immune cells and inflammatory cytokines implicated in tumor development. Clarifying the causal links between these immune components and lung cancer could enhance prevention and therapy.

α-Lactalbumin based scaffolds for infected wound healing and tissue regeneration.

Interruption of wound healing by multi-drug resistant-bacterial infection is a harmful issue for the worldwide health care system, and conventional treatment approaches may not resolve this issue due to antimicrobial resistance. So, there is an unmet need to develop scaffolds with intrinsic wound healing properties to combat bacterial-infected wounds. Inspired by the α-lactalbumin's (Lalb's) ability to promote collagen synthesis, we herein electrospun Lalb with cephalexin (CPL) and epigallocatechin (EP) to produce nanofibers (CE-Lalb NFs) to solve this issue.

Response Characteristics of the Community Structure and Metabolic Genes of Oil-Recovery Bacteria after Targeted Activation of Petroleum Hydrocarbon-Degrading Bacteria in Low-Permeability Oil Reservoirs.

The microbial enhanced oil recovery (MEOR) process has been identified as a promising alternative to conventional enhanced oil recovery methods because it is eco-friendly and economically advantageous. However, the knowledge about the composition and diversity of microbial communities in artificially regulated reservoirs, especially after activating petroleum hydrocarbon-degrading bacteria (PHDB) by injecting exogenous nutrients, is still insufficient. This study utilized a combination of high-throughput sequencing and metagenomics technology to reveal the structural evolution characteristics of the indigenous microbial community in the reservoir during the PHDB activated for enhanced oil recovery, as well as the response relationship between the expression of its oil production functional genes and crude oil biodegradation.

Obstructed vein delivery of ceftriaxone via poly(vinyl-pyrrolidone)-iodine-chitosan nanofibers for the management of diabetic foot infections and burn wounds.

Superficial skin injuries especially burn injuries and unhealed diabetic foot open wounds remain troubling for public health. The healing process is often interrupted by the invasion of resistant pathogens that results in the failure of conventional procedures outside the clinical settings. Herein, we designed nanofibers dressing with intrinsic antibacterial potential of poly(vinyl-pyrrolidone)-iodine/ poly (vinyl)-alcohol by electrospinning with chitosan encapsulating ceftriaxone (CPC/NFs).

MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction.

This study aims to tackle the intricate challenge of predicting RNA-small molecule binding sites to explore the potential value in the field of RNA drug targets. To address this challenge, we propose the MultiModRLBP method, which integrates multi-modal features using deep learning algorithms. These features include 3D structural properties at the nucleotide base level of the RNA molecule, relational graphs based on overall RNA structure, and rich RNA semantic information.

Degradation selectivity for bamboo fiber and parenchyma lignin-carbohydrates complexes (LCC) esters.

The degradation of lignin-carbohydrate complex (LCC) esters has been proven to be crucial for the selective separation of lignocellulosic components. This study utilized Raman microspectroscopy to image the preferential degradation of lignin and LCC esters from the bamboo wall during successive NaOH (0.2 to 5.

Contrast-enhanced ultrasound to predict malignant upgrading of atypical ductal hyperplasia.

Background: A malignancy might be found at surgery in cases of atypical ductal hyperplasia (ADH) diagnosed via US-guided core needle biopsy (CNB). The objective of this study was to investigate the diagnostic performance of contrast-enhanced ultrasound (CEUS) in predicting ADH diagnosed by US-guided CNB that was upgraded to malignancy after surgery.

Methods: In this retrospective study, 110 CNB-diagnosed ADH lesions in 109 consecutive women who underwent US, CEUS, and surgery between June 2018 and June 2023 were included.

Bio-evaluations of sericin coated hesperidin nanoparticles for gastric ulcer management.

Gastric ulcers are worrying, and their worsening conditions may result in bleeding in the internal lining of the stomach. The problem is annoying, and both patients and professionals are still not satisfied with the available treatment options. Hesperidin, a flavonoid molecule with potent anti-inflammatory and antioxidant effects, can work like witchcraft to repair gastric ulcers and preserve the stomach lining.

Association between Weight-Adjusted Waist Index and depressive symptoms: A nationally representative cross-sectional study from NHANES 2005 to 2018.

Background: Depressive symptoms are strongly associated with the development of various diseases and are one of the leading causes of disability in the world. However, the relationship between weight-adjusted waist index (WWI) and depressive symptoms has not been studied. This study aimed to assess the relationship between depressive symptoms and WWI.

Hydrophobic Porphyrin Titanium-Based MOFs for Visible-Light-Driven CO Reduction to Formate.

Three hydrophobic porphyrin titanium-based metal-organic frameworks (MOFs) (HPA/DGIST-1, DPA/DGIST-1, and OPA/DGIST-1) were synthesized through a postsynthetic coordination reaction by using alkylphosphonic acid of different lengths (HPA, hexylphosphonic acid; DPA, dodecylphosphonic acid; OPA, octadecylphosphonic acid). Compared with the hydrophilic DGIST-1, modified DGIST-1 exhibits excellent hydrophobicity and presents good stability in humid atmospheres. Due to the introduction of porphyrin ligands, HPA/DGIST-1, DPA/DGIST-1, and OPA/DGIST-1 showed good visible-light absorption (380-700 nm) and sensitive photogenerated charge responses.

RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding.

Motivation: Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC-peptide binding is vital for the development of cancer therapeutic vaccines. While recent deep learning-based methods have achieved significant performance in predicting MHC-peptide binding affinity, most of them separately encode MHC molecules and peptides as inputs, potentially overlooking critical interaction information between the two.

Association Between Copper Intake and Migraine: a National Cross-sectional Study.

Migraine is a common clinical neurological disorder that adversely affects humans and society. The relationship between copper intake and migraine has been less studied and controversial. The purpose of this study was to determine the relationship between copper intake and migraine and to guide dietary interventions.

Facial Landmark based BMI Analysis for Pervasive Health Informatics.

Body Mass Index (BMI), calculated based on the ratio between a person's height and weight, is a widely used metric for body weight or fatness. In this paper, we investigate the potential of face image-based BMI estimation using an RGB camera. We proposed a simple yet highly reproducible image processing framework that converts an input face image into a BMI value or obesity class (underweight, normal and overweight).

Thermomechanical Properties of Zeta (AgIn) Phase.

The thermomechanical properties of materials within die-attach joints play an essential role in assessing the reliability of high-power modules. Ag-In transient liquid phase (TLP) bonding serves as an alternative method for die attachment. However, relevant material data for the ζ (AgIn) phase, one of the Ag-In intermetallic compound (IMC) products of TLP bonding, are limited.

The Design of a 1-6 GHz Broadband Double-Balanced Mixer.

This brief proposes a 1-6 GHz broadband double-balanced mixer. On the basis of the standard Marchand balun mixer, two techniques to enhance the performance of the mixer are proposed. Firstly, by loading capacitors, the amplitude and phase imbalance of the balun at high frequencies are improved, thereby expanding the relative bandwidth of the mixer by 0.

Association of serum oleic acid level with depression in American adults: a cross-sectional study.

Background: As the most abundant fatty acid in plasma, oleic acid has been found to be associated with multiple neurological diseases; however, results from studies of the relationship between oleic acid and depression are inconsistent.

Methods: This cross-sectional study analyzed 4,459 adults from the National Health and Nutrition Examination Survey 2011-2014. The following covariates were adjusted in multivariable logistic regression models: age, sex, race/ethnicity, education level, marital status, body mass index, physical activity, smoking status, alcohol status, metabolic syndrome, omega-3 polyunsaturated fatty acids, and total cholesterol.

DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features.

Phosphorylation, as one of the most important post-translational modifications, plays a key role in various cellular physiological processes and disease occurrences. In recent years, computer technology has been gradually applied to the prediction of protein phosphorylation sites. However, most existing methods rely on simple protein sequence features that provide limited contextual information.