3D-Printed Myocardium-Specific Structure Enhances Maturation and Therapeutic Efficacy of Engineered Heart Tissue in Myocardial Infarction.

Despite advancements in engineered heart tissue (EHT), challenges persist in achieving accurate dimensional accuracy of scaffolds and maturing human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), a primary source of functional cardiac cells. Drawing inspiration from cardiac muscle fiber arrangement, a three-dimensional (3D)-printed multi-layered microporous polycaprolactone (PCL) scaffold is created with interlayer angles set at 45° to replicate the precise structure of native cardiac tissue. Compared with the control group and 90° PCL scaffolds, the 45° PCL scaffolds exhibited superior biocompatibility for cell culture and improved hiPSC-CM maturation in calcium handling.

Carbon sequestration potential of wetlands and regulating strategies response to climate changes.

Wetlands are important carbon sinks for mitigating climate warming. In this paper, greenhouse gas (GHG) fluxes and carbon sequestration capacity of freshwater wetlands, coastal wetlands and constructed wetlands around the world are evaluated, and strategies to improve carbon sequestration by wetlands are proposed based on the main influencing factors. Air temperature and average annual rainfall are significantly positively correlated with CH flux and NO flux in freshwater wetlands and coastal wetlands.

Global glucose metabolism rate as diagnostic marker for disorder of consciousness of patients: quantitative FDG-PET study.

Objective: This study was to employ 18F-flurodeoxyglucose (FDG-PET) to evaluate the resting-state brain glucose metabolism in a sample of 46 patients diagnosed with disorders of consciousness (DoC). The aim was to identify objective quantitative metabolic indicators and predictors that could potentially indicate the level of awareness in these patients.

Methods: A cohort of 46 patients underwent Coma Recovery Scale-Revised (CRS-R) assessments in order to distinguish between the minimally conscious state (MCS) and the unresponsive wakefulness syndrome (UWS).

Characterization of fluoranthene degradation by the novel isolated Pseudomonas xizangensis S4 and its application potential immobilized in potassium humate-modified biochar.

Enhanced microbial remediation represents a promising technique for the removal of polycyclic aromatic hydrocarbons (PAHs). However, high-efficiency remediation agents remain limited, including microbial resources and remediation materials. In this study, a novel strain of Pseudomonas xizangensis S4 was isolated from plateau lake sediment, exhibiting a fluoranthene degradation rate of 41.

Autoencoder-Based System for Detecting Anomalies in Pelletizer Melt Processes.

Effectively identifying and preventing anomalies in the melt process significantly enhances production efficiency and product quality in industrial manufacturing. Consequently, this paper proposes a study on a melt anomaly identification system for pelletizers using autoencoder technology. It discusses the challenges of detecting anomalies in the melt extrusion process of polyester pelletizers, focusing on the limitations of manual monitoring and traditional image detection methods.

Interpretable causal machine learning optimization tool for improving efficiency of internal carbon source-biological denitrification.

Interpretable causal machine learning (ICML) was used to predict the performance of denitrification and clarify the relationships between influencing factors and denitrification. Multiple models were examined, and XG-Boost model provided the best prediction (R = 0.8743).

High-Precision and Lightweight Model for Rapid Safety Helmet Detection.

This paper presents significant improvements in the accuracy and computational efficiency of safety helmet detection within industrial environments through the optimization of the you only look once version 5 small (YOLOv5s) model structure and the enhancement of its loss function. We introduce the convolutional block attention module (CBAM) to bolster the model's sensitivity to key features, thereby enhancing detection accuracy. To address potential performance degradation issues associated with the complete intersection over union (CIoU) loss function in the original model, we implement the modified penalty-decay intersection over union (MPDIoU) loss function to achieve more stable and precise bounding box regression.

Surface engineering-based S, N co-doped biochar for improved anaerobic digestion: Enhancing microbial-pollutant and inter-microbial electron transfer synergistic EPS protection.

Enhancing extracellular electron transfer (EET) efficiency is crucial for improving the anaerobic digestion (AD) system's capability to treat recalcitrant wastewater. In this study, a novel S, N co-doped biochar (S-N-BC) was prepared through surface engineering to optimize EET within AD systems. The addition of S-N-BC significantly enhanced the performance of a mesophilic AD system treating Congo red wastewater, increasing the decolorization rate by 78 %, COD degradation rate by 82 %, and methane yield by 87 % compared to the control.

Glycolytic reprogramming in microglia: A potential therapeutic target for ischemic stroke.

Ischemic stroke is currently the second leading cause of mortality worldwide, with limited treatment options available. As resident immune cells, microglia promptly respond to cerebral ischemic injury, influencing neuroinflammatory damage and neurorepair. Studies suggest that microglia undergo metabolic reprogramming from mitochondrial oxidative phosphorylation to glycolysis in response to ischemia, significantly impacting their function during ischemic stroke.

Predicting photosynthetic bacteria-derived protein synthesis from wastewater using machine learning and causal inference.

Causal inference-assisted machine learning was used to predict photosynthetic bacterial (PSB) protein production capacity and identify key factors. The extreme gradient boosting algorithm effectively predicted protein content, while the gradient boosting decision tree algorithm excelled in predicting protein production, protein productivity, and protein energy yields. Driving factors were identified, with suitable ranges: protein content (pH 6.

Pan-cancer and single-cell analysis reveal dual roles of lymphocyte activation gene-3 (LAG3) in cancer immunity and prognosis.

Lymphocyte activating gene-3 (LAG3) is a distinctive T cell co-receptor that is expressed on the surface of lymphocytes. It plays a special inhibitory immune checkpoint role due to its unique domain and signaling pattern. Our aim is to explore the correlation between LAG3 in cancers and physiological processes related to a range of cancers, as well as build LAG3-related immunity and prognostic models.

Application of machine learning in ultrasonic pretreatment of sewage sludge: Prediction and optimization.

In this research, typical industrial scenarios were analyzed optimized by machine learning algorithms, which fills the gap of massive data and industrial requirements in ultrasonic sludge treatment. Principal component analysis showed that the ultrasonic density and ultrasonic time were positively correlated with soluble chemical oxygen demand (SCOD), total nitrogen (TN), and total phosphorus (TP). Within five machine learning models, the best model for SCOD prediction was XG-boost (R = 0.

Feasibility and mechanism of adsorption and bioreduction of hexavalent chromium using Rhodopseudomonas palustris immobilized on multiple materials.

Rhodopseudomonas palustris immobilized on multiple materials was used to invistigate Cr(VI) adsorption and bioreduction. The highest Cr(VI) removal (97.5%) was achieved at 276h under the opitimed conditions of 2.

Haematococcus pluvialis meets gellan gum: Rheological and thermal exploration of a new resource food and biomedical gel matrix.

The increasing interest in hydrogel matrices and their diverse applications has fueled extensive research. However, single-component gels have a limited adjustable performance range, and multi-component gels raise concerns about biological safety, hindering their widespread use. This study focuses on harnessing high-speed shearing and ultrasound-assisted methods to incorporate active natural Haematococcus pluvialis (HP), creating novel composite hydrogels in conjunction with biological macromolecule gellan gum, and eliminating the need for structural modifications or chemical crosslinking.

Yeast culture enhances long-term fermentation of corn straw by ruminal microbes for volatile fatty acid production: Performance and mechanism.

Ruminal microbes can efficiently ferment biomass waste to produce volatile fatty acids (VFAs). However, keeping long-term efficient VFA production efficiency has become a bottleneck. In this study, yeast culture (YC) was used to enhance the VFA production in long-term fermentation.

Bowel preparation experiences and needs before follow-up colonoscopy in older adult postoperative colorectal cancer patients: A qualitative study.

Background: The bowel preparation process prior to colonoscopy determines the quality of the bowel preparation, which in turn affects the quality of the colonoscopy. Colonoscopy is an essential procedure for postoperative follow-up monitoring of colorectal cancer (CRC) patients. Previous studies have shown that advanced age and a history of colorectal resection are both risk factors for inadequate bowel preparation.

Recent advances in methane and hydrogen production from lignocellulosic degradation with anaerobic fungi.

Anaerobic fungi (AF) efficiently degrade lignocellulosic biomass with unique pseudoroot system and enzymatic properties that can remove polysaccharides and some lignified components from plant cell walls, further releasing acetate, lactate, ethanol, hydrogen (H), etc. As research on AF for bioengineering has become a hot topic, a review of lignocellulosic conversion with AF for methane (CH) and H production is needed. Efficient degradation of lignocellulose with AF mainly relies on multiple free carbohydrate-active enzymes and cellulosomes in the free and bound state.

Inhibition of KIF5b-mediated Nav1.8 transport by ropivacaine contributes to axonal regeneration following sciatic nerve injury in rats.

Peripheral nerve injury (PNI), typically caused by traumatic accidents or medical events, is currently one of the most common diseases that leads to limb disability. After PNI, tetrodotoxin-resistant voltage-gated sodium channel Nav1.8 is upregulated at the lesion site.

Performance, mechanism regulation and resource recycling of bacteria-algae symbiosis system for wastewater treatment: A review.

The bacteria-algae synergistic wastewater treatment process not only efficiently eliminates nutrients and absorbs heavy metals, but also utilizes photosynthesis to convert light energy into chemical energy, generating valuable bioresource. The study systematically explores the formation, algal species, and regulatory strategies of the bacterial-algal symbiosis system. It provides a detailed analysis of various interaction mechanisms, with a particular focus on nutrient exchange, signal transduction, and gene transfer.

Genome-centric metagenomic analysis reveals mechanisms of quorum sensing promoting anaerobic digestion under sulfide stress: Syntrophic metabolism and microbial self-adaptation.

Sulfide stress is a common inhibition factor in anaerobic digestion systems with sulfur-rich feedstocks. Quorum sensing (QS) signaling molecule N-acyl-homoserine lactones (AHLs) possess positive effect on promoting anaerobic digestion. However, the micro-biological mechanisms of AHLs affecting syntrophic metabolism and microbial self-adaptation have not yet been deciphered in anaerobic digestion under sulfide stress.

MHIPM: Accurate Prediction of Microbe-Host Interactions Using Multiview Features from a Heterogeneous Microbial Network.

Current studies have demonstrated that microbe-host interactions (MHIs) play important roles in human public health. Therefore, identifying the interactions between microbes and hosts is beneficial to understanding the role of the microbiome and their underlying mechanisms. However, traditional wet-lab experimental approaches are insufficient for large-scale exploration of candidate microbes, as they are costly, laborious, and time-consuming.