DTI-MHAPR: optimized drug-target interaction prediction via PCA-enhanced features and heterogeneous graph attention networks.

Drug-target interactions (DTIs) are pivotal in drug discovery and development, and their accurate identification can significantly expedite the process. Numerous DTI prediction methods have emerged, yet many fail to fully harness the feature information of drugs and targets or address the issue of feature redundancy. We aim to refine DTI prediction accuracy by eliminating redundant features and capitalizing on the node topological structure to enhance feature extraction.

Central corticotropin releasing hormone receptor 2 may participate in sex differential regulation of cold-evoked eating behavior.

Corticotropin-releasing factor (CRF) is an important stress hormone, and because of the different distributions and functions of its receptors, CRF has various effects on the stress response of animals. CRF receptor 2 (CRFR2) is a functional receptor of CRF that may be related to appetite regulation and sex differences. In this study, male and female C57BL/6 mice were exposed to an ambient temperature of 4 °C, and feed intake were determined.

ChatEMG: Synthetic Data Generation to Control a Robotic Hand Orthosis for Stroke.

Intent inferral on a hand orthosis for stroke patients is challenging due to the difficulty of data collection. Additionally, EMG signals exhibit significant variations across different conditions, sessions, and subjects, making it hard for classifiers to generalize. Traditional approaches require a large labeled dataset from the new condition, session, or subject to train intent classifiers; however, this data collection process is burdensome and time-consuming.

Risk factors and prediction model for postpartum psychiatric disorders: a retrospective cohort study of 1418 Chinese women from 2020 to 2022.

Background: Postpartum psychiatric disorders (PPDs) have been deemed as a significant public health concern, affecting both maternal health and family dynamics. This study aimed to examine the current status of PPDs, identify the potential risk factors of PPDs, and further develop a clinical nomogram model for predicting PPDs in Chinese women.

Method: In this retrospective cohort study, 1418 postpartum women attending the routine postpartum examination at the 42nd day after delivery in Jiangsu Women and Children Health Hospital were recruited as participants from December 2020 to December 2022.

Corrigendum: Initial experience with radiomics of carotid perivascular adipose tissue in identifying symptomatic plaque.

[This corrects the article DOI: 10.3389/fneur.2024.

Wild rice GL12 synergistically improves grain length and salt tolerance in cultivated rice.

The abounding variations in wild rice provided potential reservoirs of beneficial genes for rice breeding. Maintaining stable and high yields under environmental stresses is a long-standing goal of rice breeding but is challenging due to internal trade-off mechanisms. Here, we report wild rice GL12 improves grain length and salt tolerance in both indica and japonica genetic backgrounds.

Prediction of Vascular Access Stenosis by Lightweight Convolutional Neural Network Using Blood Flow Sound Signals.

This research examines the application of non-invasive acoustic analysis for detecting obstructions in vascular access (fistulas) used by kidney dialysis patients. Obstructions in these fistulas can interrupt essential dialysis treatment. In this study, we utilized a condenser microphone to capture the blood flow sounds before and after angioplasty surgery, analyzing 3819 sound samples from 119 dialysis patients.

Parallelization of Three Dimensional Cardiac Simulation on GPU.

Background: The simulation of electrophysiological cardiac models plays an important role in facilitating the investigation of cardiac behavior under various conditions. However, these simulations often require a lot of computational resources.

Methods: To address this challenge, this study introduced a method for speeding up three-dimensional cardiac simulations using GPU parallelization.

Computer simulation of low-power and long-duration bipolar radiofrequency ablation under various baseline impedances.

Compared to traditional unipolar radiofrequency ablation (RFA), bipolar RFA offers advantages such as more precise heat transfer and higher ablation efficiency. Clinically, myocardial baseline impedance (BI) is one of the important factors affecting the effectiveness of ablation. We aim at finding suitable ablation protocols and coping strategies by analyzing the ablation effects and myocardial impedance changes of bipolar RFA under different BIs.

A method for miRNA diffusion association prediction using machine learning decoding of multi-level heterogeneous graph Transformer encoded representations.

MicroRNAs (miRNAs) are a key class of endogenous non-coding RNAs that play a pivotal role in regulating diseases. Accurately predicting the intricate relationships between miRNAs and diseases carries profound implications for disease diagnosis, treatment, and prevention. However, these prediction tasks are highly challenging due to the complexity of the underlying relationships.

The Plaque Analysis Classifies the Coronary Artery Disease-Reporting and Data System (CAD-RADS) Stenosis and Plaque Burden Categories: Association of the Plaque Features, Fat Attenuation Index, Coronary Computed Tomography Fractional Flow Reserve, and the Combination of Stenosis and Calcification.

Background: The coronary artery disease-reporting and data system (CAD-RADS) 2.0 is used to standardize the reporting of coronary computed tomography angiography (CCTA) results. Artificial intelligence software can quantify the plaque composition, fat attenuation index, and fractional flow reserve.

Q negatively regulates wheat salt tolerance through directly repressing the expression of TaSOS1 and reactive oxygen species scavenging genes.

The Q transcription factor plays important roles in improving multiple wheat domestication traits such as spike architecture, threshability and rachis fragility. However, whether and how it regulates abiotic stress adaptation remain unclear. We found that the transcriptional expression of Q can be induced by NaCl and abscisic acid treatments.

Initial experience with radiomics of carotid perivascular adipose tissue in identifying symptomatic plaque.

Background: Carotid atherosclerotic ischemic stroke threatens human health and life. The aim of this study is to establish a radiomics model of perivascular adipose tissue (PVAT) around carotid plaque for evaluation of the association between Peri-carotid Adipose Tissue structural changes with stroke and transient ischemic attack.

Methods: A total of 203 patients underwent head and neck computed tomography angiography examination in our hospital.

Relationship Analysis Between Pericoronary Fat Attenuation Index and Parameters of Single Plaque.

Objective: The aim of the study is to investigate the relationship between plaque parameters and pericoronary fat attenuation index (FAI).

Methods: A retrospective collection was performed on 227 patients with coronary heart disease who underwent coronary computed tomography angiography examinations in our hospital from May 2021 to April 2023, with a total of 254 right coronary or left anterior descending coronary arteries exhibiting solitary plaques within the FAI measurement area. Based on whether the proximal coronary FAI value was ≥ -70.

The coupling of anammox with microalgae-bacteria symbiosis: Nitrogen removal performance and microbial community.

The partial nitrification-anammox process for ammonia nitrogen wastewater treatment requires mechanical aeration to provide oxygen, which is not conducive to energy saving. The microalgae-bacteria symbiotic system (MaBS) has the advantages of low carbon and energy saving in wastewater biological nitrogen removal. Therefore, this study combined the MaBS with an anammox process to provide oxygen, through the photosynthesis of microalgae instead of mechanical aeration.

Diurnal switches in diazotrophic lifestyle increase nitrogen contribution to cereals.

Uncoupling of biological nitrogen fixation from ammonia assimilation is a prerequisite step for engineering ammonia excretion and improvement of plant-associative nitrogen fixation. In this study, we have identified an amino acid substitution in glutamine synthetase, which provides temperature sensitive biosynthesis of glutamine, the intracellular metabolic signal of the nitrogen status. As a consequence, negative feedback regulation of genes and enzymes subject to nitrogen regulation, including nitrogenase is thermally controlled, enabling ammonia excretion in engineered Escherichia coli and the plant-associated diazotroph Klebsiella oxytoca at 23 °C, but not at 30 °C.

Beat-wise segmentation of electrocardiogram using adaptive windowing and deep neural network.

Timely detection of anomalies and automatic interpretation of an electrocardiogram (ECG) play a crucial role in many healthcare applications, such as patient monitoring and post treatments. Beat-wise segmentation is one of the essential steps in ensuring the confidence and fidelity of many automatic ECG classification methods. In this sense, we present a reliable ECG beat segmentation technique using a CNN model with an adaptive windowing algorithm.

Development and validation of an inflammatory response-related gene and clinical factor-based signature for predicting prognosis in gastric cancer.

Background: Gastric cancer (GC) is an aggressive disease that requires prognostic tools to aid in clinical management. The prognostic power of clinical features is unsatisfactory, which might be improved by combining mRNA-based signatures. Inflammatory response is widely associated with cancer development and treatment response.

Senescence-related genes define prognosis, immune contexture, and pharmacological response in gastric cancer.

As one of the prevalent tumors worldwide, gastric cancer (GC) has obtained sufficient attention in its clinical management and prognostic stratification. Senescence-related genes are involved in the tumorigenesis and progression of GC. A machine learning algorithm-based prognostic signature was developed from six senescence-related genes including , , , , , and .

Gut-derived bacterial LPS attenuates incubation of methamphetamine craving via modulating microglia.

Background: The microbiota-gut-brain axis plays a critical role in the pathophysiology of neuropsychiatric disorders, and the compositions of gut microbiota are altered by addictive drugs. However, the role of gut microbiota in the incubation of methamphetamine (METH) craving remains poorly understood.

Methods: 16S rRNA gene sequencing was performed to assess the richness and diversity of gut microbiota in METH self-administration model.