Metabolomics Study Revealed the Effects of CaO-Treated Maize Straw on the Rumen Metabolites.

As an important limiting factor, lignin hinders the utilization rate of maize straw in ruminants. CaO treatment increases the feed digestibility of maize straw by disrupting the ester bonds between hemicellulose, cellulose, and lignin in maize straw. Our previous research found that CaO treatment of corn straw may increase its feed digestibility by altering the rumen microbes' abundance.

The efficacy and safety of addition of pegylated interferon to long-term nucleos(t)ide analogue therapy on functional cure of chronic hepatitis B patient: a systematic review and meta-analysis.

Objective: This meta-analysis aims to assess the efficacy and safety of adding pegylated interferon (Peg-IFN) to long-term nucleos(t)ide analogs (NAs) treatment for achieving functional cure in patients with chronic hepatitis B (CHB).

Methods: This meta-analysis was registered in PROSPERO (CRD42024519116). We searched PubMed, Embase, Cochrane Library and Web of Science for randomized controlled trials that compared adding Peg-IFN to long-term NAs with NAs alone for the treatment of CHB.

In Situ Growth of Columnar PEG on PEDOT and Its Antifouling Properties.

The antifouling properties of conductive polymers have received extensive attention for biosensor and bioelectronic applications. Polyethylene glycol (PEG) is a well-known antifouling material, but the controlled regulation of the surface topography of PEG without a template remains a challenge. Here, we show a columnar structure antifouling conductive polymer brush with enhanced antifouling properties and considerable conductivity.

Comparison of the effect of ultrasounic-harmonic scalpel and electrocautery in the treatment of axillary lymph nodes during radical surgery for breast cancer.

Objective: To compare the efficacy of ultrasounic-harmonic scalpel and electrocautery in the treatment of axillary lymph nodes during radical surgery for breast cancer.

Methods: A prospective study was conducted in the Department of Breast Surgery, Zhongda Hospital Affiliated to Southeast University. A total of 128 patients with pathologically confirmed breast cancer who were treated by the same surgeon from July 2023 to November 2023 were included in the analysis.

Differences of serum glucose and lipid metabolism and immune parameters and blood metabolomics regarding the transition cows in the antepartum and postpartum period.

This study aims to investigate differences in metabolism regarding the transition cows. Eight cows were selected for the test. Serum was collected on antepartum days 14th (ap14) and 7th (ap7) and postpartum days 1st (pp1), 7th (pp7), and 14th (pp14) to detect biochemical parameters.

Additively Manufactured Flexible Liquid Metal-Coated Self-Powered Magnetoelectric Sensors with High Design Freedom.

Although additive manufacturing enables controllable structural design and customized performance for magnetoelectric sensors, their design and fabrication still require careful matching of the size and modulus between the magnetic and conductive components. Achieving magnetoelectric integration remains challenging, and the rigid coils limit the flexibility of the sensors. To overcome these obstacles, this study proposes a composite process combining selective laser sintering (SLS) and 3D transfer printing for fabricating flexible liquid metal-coated magnetoelectric sensors.

Discovering the Active Ingredients of Medicine and Food Homologous Substances for Inhibiting the Cyclooxygenase-2 Metabolic Pathway by Machine Learning Algorithms.

Cyclooxygenase-2 (COX-2) and microsomal prostaglandin E synthase (mPGES-1) are two key targets in anti-inflammatory therapy. Medicine and food homology (MFH) substances have both edible and medicinal properties, providing a valuable resource for the development of novel, safe, and efficient COX-2 and mPGES-1 inhibitors. In this study, we collected active ingredients from 503 MFH substances and constructed the first comprehensive MFH database containing 27,319 molecules.

Machine learning-based classification models for non-covalent Bruton's tyrosine kinase inhibitors: predictive ability and interpretability.

In this study, we built classification models using machine learning techniques to predict the bioactivity of non-covalent inhibitors of Bruton's tyrosine kinase (BTK) and to provide interpretable and transparent explanations for these predictions. To achieve this, we gathered data on BTK inhibitors from the Reaxys and ChEMBL databases, removing compounds with covalent bonds and duplicates to obtain a dataset of 3895 inhibitors of non-covalent. These inhibitors were characterized using MACCS fingerprints and Morgan fingerprints, and four traditional machine learning algorithms (decision trees (DT), random forests (RF), support vector machines (SVM), and extreme gradient boosting (XGBoost)) were used to build 16 classification models.

Prediction and Structure-Activity Relationship Analysis on Ready Biodegradability of Chemical Using Machine Learning Method.

Persistent contaminants from different industries have already caused significant risks to the environment and public health. In this study, a data set containing 1306 not readily biodegradable (NRB) and 622 readily biodegradable (RB) chemicals was collected and characterized by CORINA descriptors, MACCS fingerprints, and ECFP_4 fingerprints. We utilized decision tree (DT), support vector machine (SVM), random forest (RF), and deep neural network (DNN) to construct 34 classification models that could predict the biodegradability of compounds.

Prediction of bioactivities of microsomal prostaglandin E synthase-1 inhibitors by machine learning algorithms.

There is a strong interest in the development of microsomal prostaglandin E2 synthase-1 (mPGES-1) inhibitors of their potential to safely and effectively treat inflammation. Herein, 70 QSAR models were built on the dataset (735 mPGES-1 inhibitors) characterized with RDKit descriptors by multiple linear regression (MLR), support vector machine (SVM), random forest (RF), deep neural networks (DNN), and eXtreme Gradient Boosting (XGBoost). The other three regression models on the dataset are represented by SMILES using self-attention recurrent neural networks (RNN) and Graph Convolutional Networks (GCN).

Spontaneous Fe/Fe redox cycling in single-atom catalysts: Conjugation effect and electron delocalization.

The mechanism of spontaneous Fe/Fe redox cycling in iron-centered single-atom catalysts (I-SACs) is often overlooked. Consequently, pathways for continuous SO /HO⋅ generation during peroxymonosulfate (PMS) activation by I-SACs remain unclear. Herein, the evolution of the iron center and ligand in I-SACs was comprehensively investigated.

A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.

Background: The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis.

Profiling COVID-19 Vaccine Adverse Events by Statistical and Ontological Analysis of VAERS Case Reports.

Since the beginning of the COVID-19 pandemic, vaccines have been developed to mitigate the spread of SARS-CoV-2, the virus that causes COVID-19. These vaccines have been effective in reducing the rate and severity of COVID-19 infection but also have been associated with various adverse events (AEs). In this study, data from the Vaccine Adverse Event Reporting System (VAERS) was queried and analyzed via the Cov19VaxKB vaccine safety statistical analysis tool to identify statistically significant (i.

Classification models and SAR analysis on HDAC1 inhibitors using machine learning methods.

Histone deacetylase (HDAC) 1, a member of the histone deacetylases family, plays a pivotal role in various tumors. In this study, we collected 7313 human HDAC1 inhibitors with bioactivities to form a dataset. Then, the dataset was divided into a training set and a test set using two splitting methods: (1) Kohonen's self-organizing map and (2) random splitting.

Recent Advances on High-Performance Polyaryletherketone Materials for Additive Manufacturing.

Polyaryletherketone (PAEK) is emerging as an important high-performance polymer material in additive manufacturing (AM) benefiting from its excellent mechanical properties, good biocompatibility, and high-temperature stability. The distinct advantages of AM facilitate the rapid development of PAEK products with complex customized structures and functionalities, thereby enhancing their applications in various fields. Herein, the recent advances on AM of high-performance PAEKs are comprehensively reviewed, concerning the materials properties, AM processes, mechanical properties, and potential applications of additively manufactured PAEKs.

3D-Printed Anisotropic Polymer Materials for Functional Applications.

Anisotropy is the characteristic of a material to exhibit variations in its mechanical, electrical, thermal, optical properties, etc. along different directions. Anisotropic materials have attracted great research interest because of their wide applications in aerospace, sensing, soft robotics, and tissue engineering.

3D Printing and Chemical Dealloying of a Hierarchically Micro- and Nanoporous Catalyst for Wastewater Purification.

Hierarchically porous-structured materials show tremendous potential for catalytic applications. In this work, a facile method through the combination of three-dimensional (3D) printing and chemical dealloying was employed to synthesize a nanoporous-copper-encapsulating microporous-diamond-cellular-structure (NPC@DCS) catalyst. The developed NPC@DCS catalyst was utilized as a heterogeneous photo-Fenton-like catalyst where its catalytic applications in the remediation of organic wastewater were exemplified.

Building 2D classification models and 3D CoMSIA models on small-molecule inhibitors of both wild-type and T790M/L858R double-mutant EGFR.

Epidermal growth factor receptor (EGFR) has received widespread attention because it is an important target for anticancer drug design. Mutations in the EGFR, especially the T790M/L858R double mutation, have made cancer treatment more difficult. We herein built the structure-activity relationship models of small-molecule inhibitors on wild-type and T790M/L858R double-mutant EGFR with a whole dataset of 379 compounds.

Effects of maize straw treated with various levels of CaO and moisture on composition, structure, and digestion by in vitro gas production.

Objective: The objective of this study was to explore the effects of maize straw treated with calcium oxide (CaO) and various moisture, on the composition and molecular structure of the fiber, and gas production by fermentation in an in vitro rumen environment.

Methods: The experiment used 4×3 Factorial treatment. Maize straws were treated with 4 concentrations of CaO (0%, 3%, 5%, and 7% of dry straw weight) and 3 moisture contents (40%, 50%, and 60%).

Capillary-Force-Driven Self-Assembly of 4D-Printed Microstructures.

Capillary-force-driven self-assembly is emerging as a significant approach for the massive manufacture of advanced materials with novel wetting, adhesion, optical, mechanical, or electrical properties. However, academic value and practical applications of the self-assembly are greatly restricted because traditional micropillar self-assembly is always unidirectional. In this work, two-photon-lithography-based 4D microprinting is introduced to realize the reversible and bidirectional self-assembly of microstructures.

Expression and Function of WNT6: From Development to Disease.

WNT family member 6 (WNT6) is a member of the highly conserved WNT protein family. It plays an essential role in the normal development process, not only in embryonic morphogenesis, but also in post-natal homeostasis. WNT6 functions in mice and humans.

Selective Laser Sintering-Based 4D Printing of Magnetism-Responsive Grippers.

Components fabricated by four-dimensional (4D) printing hold the potential for applications in soft robotics because of their characteristics of responding to external stimuli. Grippers, being the common structures used in robotics, were fabricated by the selective laser sintering (SLS)-based 4D printing of magnetism-responsive materials and tested for remote-controllable deformation in an external magnetic field. A composite material consisting of magnetic Nd2Fe14B powder and thermoplastic polyurethane powder was selected as the raw material for the SLS; the magnetic particle acquired permanent magnetism by magnetization after the SLS process.

Quantifying urban wastewater treatment sector's greenhouse gas emissions using a hybrid life cycle analysis method - An application on Shenzhen city in China.

Substantial amounts of greenhouse gas (GHG) emissions generated at urban wastewater treatment plants (WWTP) are gaining increasing appreciation. Improving upon the commonly used Process-Based Life-Cycle Analysis (PLCA) and Environmentally-Extended Life-Cycle Analysis (EIO-LCA) models, we construct a Hybrid Life Cycle Analysis (HLCA) model and quantify both direct and indirect GHG emissions at the operational stage of WWTPs in Shenzhen, one of the fastest urbanizing cities in the world. Data are collected from 26 wastewater treatment plants in Shenzhen, out of all 32, covering 5 commonly used wastewater treatment technologies in China, i.