Bile acids as a key target: traditional Chinese medicine for precision management of insulin resistance in type 2 diabetes mellitus through the gut microbiota-bile acids axis.

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease caused by insulin resistance (IR) and insufficient insulin secretion. Its characteristic pathophysiological processes involve the interaction of multiple mechanisms. In recent years, globally, the prevalence of T2DM has shown a sharp rise due to profound changes in socio-economic structure, the persistent influence of environmental factors, and the complex role of genetic background.

An integrated microflow cytometry platform with artificial intelligence capabilities for point-of-care cellular phenotype analysis.

The EZ DEVICE is an integrated fluorescence microflow cytometer designed for automated cell phenotyping and enumeration using artificial intelligence (AI). The platform consists of a laser diode, optical filter, objective lens, CMOS image sensor, and microfluidic chip, enabling automated sample pretreatment, labeling, and detection within a single compact unit. AI algorithms segment and identify objects in images captured by the CMOS sensor at 532 and 586 nm emission wavelengths.

Sustainable Pb(II) Removal and Recovery from Wastewater Using a Bioinspired Metal-Phenolic Hybrid Membrane with Efficient Regeneration.

High-performance adsorbents often require efficient selectivity in wastewater, recoverability, and ease of multiple regeneration cycles, but achieving this remains a significant challenge. We report a new strategy for the efficient removal of lead (Pb(II)) from contaminated water streams using an innovative tannic acid (TA)-Fe(III)-based metal-phenolic network (MPN) hybrid membrane (MPN-PAM). This novel membrane exploits the tunable pH-sensitive coordination structure of the MPN to achieve selective removal and recovery of Pb(II) while enabling efficient membrane regeneration by filtration.

Pioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System-Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study.

Background: The rising prevalence and swift spread of multidrug-resistant gram-negative bacteria (MDR-GNB), especially Klebsiella pneumoniae (KP), present a critical global health threat highlighted by the World Health Organization, with mortality rates soaring approximately 50% with inappropriate antimicrobial treatment.

Objective: This study aims to advance a novel strategy to develop an artificial intelligence-clinical decision support system (AI-CDSS) that combines machine learning (ML) with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), aiming to significantly improve the accuracy and speed of diagnosing antibiotic resistance, directly addressing the grave health risks posed by the widespread dissemination of pan drug-resistant gram-negative bacteria across numerous countries.

Methods: A comprehensive dataset comprising 165,299 bacterial specimens and 11,996 KP isolates was meticulously analyzed using MALDI-TOF MS technology.

High-throughput development of tough metallic glass films.

Fast development of metallic glass films with high toughness has been a long-sought goal of humankind in view of their superior properties and great potential for application in the field of soft electronics. However, until now, there has been no effective experimental strategy because of the lack of suitable and precise toughness measurement technology. In the present work, we introduced a feasible route for developing tough metallic glass films using combinatorial material library preparation and high-throughput toughness measurement nanoindentation.

Enhanced Recovery After Craniotomy: Global Practices, Challenges, and Perspectives.

The global demand for hospital care, driven by population growth and medical advances, emphasizes the importance of optimized resource management. Enhanced Recovery After Surgery (ERAS) protocols aim to expedite patient recovery and reduce health care costs without compromising patient safety or satisfaction. Its principles have been adopted in various surgical specialties but have not fully encompassed all areas of neurosurgery, including craniotomy.

STIM1 promotes cervical cancer progression through autophagy activation via TFEB nuclear translocation.

Background: Autophagy plays an important role in maintaining the stability of intracellular environment, abnormal autophagy is associated with the occurrence and progression of cancer, the role of STIM1 in regulating cancer autophagy remains controversial, and its clinical relevance is unclear. Our study aimed to investigate the effect and mechanism of STIM1 on cervical cancer, thus to provide new molecular therapeutic targets for cervical cancer in clinic.

Methods: We collected CIN III, FIGO IB and IIA fresh Specimens without chemotherapy from patients in Renmin Hospital of Hubei University of Medicine (n = 10).

IGFL2 expression and surgical volume: Independent predictors of survival in gastric cancer.

This study aimed to assess the impact of surgeons' annual volume and insulin-like growth factor-like family member 2 (IGFL2) expression on gastric cancer prognosis. Clinicopathological data from 475 patients who underwent D2 lymph node dissection were analyzed. IGFL2 expression was evaluated using immunohistochemistry.

Strong Silkworm Silk Fibers through CNT-Feeding and Forced Reeling.

High-performance silk fibers, with their eco-friendly degradability and renewability, have long captivated researchers as an alternative to synthetic fibers. Spider dragline silk, renowned for its exceptional strength (>1 GPa), has an extremely low yield, hindering its widespread use. While domesticated silkworms (Bombyx mori) can produce silk fibers industrially, their moderate strength (≈0.

Deciphering the multidimensional impact of expression on cancer prognosis, genetic alterations, and cellular functionality: A comprehensive Pan-cancer analysis.

Objectives: IGF-binding protein 1 () is a key regulator of insulin-like growth factors, impacting biological processes, including cancer progression and prognosis.

Materials And Methods: This study investigates genetic alterations affecting IGFBP1 expression in tumors using data from The Cancer Genome Atlas (TCGA) PanCancer Atlas via cBioPortal. We analyzed samples from 32 cancer types for mutation sites, including deep deletions, amplifications, and mutations.

Wet-spinning of carbon nanotube fibers: dispersion, processing and properties.

Owing to the intrinsic excellent mechanical, electrical, and thermal properties of carbon nanotubes (CNTs), carbon nanotube fibers (CNTFs) have been expected to become promising candidates for the next-generation of high-performance fibers. They have received considerable interest for cutting-edge applications, such as ultra-light electric wire, aerospace craft, military equipment, and space elevators. Wet-spinning is a broadly utilized commercial technique for high-performance fiber manufacturing.

Development and Validation of a Two-step Model to Predict Outcomes After Endovascular Treatment for Patients With Acute Ischemic Stroke.

Background: Physicians and patients are eager to know likely functional outcomes at different stages of treatment after acute ischemic stroke (AIS). The aim of this study was to develop and validate a 2-step model to assess prognosis at different time points (pre- and posttreatment) in patients with AIS having endovascular thrombectomy (EVT).

Methods: The prediction model was developed using a prospective nationwide Chinese registry (ANGEL-ACT).

Evaluation of CD4 T Lymphocyte Counts to Predict Survival of ICU Patients with Sepsis Using Sepsis-3 Criteria: A Prospective Cohort Study.

Background: Sepsis remains a major health condition with a high mortality rate that may be related to immunosuppression. T lymphocyte subsets may reflect the immune function of sepsis patients. The purpose of this study was to investigate the predictive value of CD4 T lymphocyte counts of ICU patients for their short-term prognosis.

A Cross Spatio-Temporal Pathology-based Lung Nodule Dataset.

Recently, intelligent analysis of lung nodules with the assistant of computer aided diagnosis (CAD) techniques can improve the accuracy rate of lung cancer diagnosis. However, existing CAD systems and pulmonary datasets mainly focus on Computed Tomography (CT) images from one single period, while ignoring the cross spatio-temporal features associated with the progression of nodules contained in imaging data from various captured periods of lung cancer. If the evolution patterns of nodules across various periods in the patients' CT sequences can be explored, it will play a crucial role in guiding the precise screening identification of lung cancer.

Artificial intelligence-clinical decision support system for enhanced infectious disease management: Accelerating ceftazidime-avibactam resistance detection in Klebsiella pneumoniae.

Background: Effective and rapid diagnostic strategies are required to manage antibiotic resistance in Klebsiella pneumonia (KP). This study aimed to design an artificial intelligence-clinical decision support system (AI-CDSS) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and machine learning for the rapid detection of ceftazidime-avibactam (CZA) resistance in KP to improve clinical decision-making processes.

Methods: Out of 107,721 bacterial samples, 675 specimens of KP with suspected multi-drug resistance were selected.

Migration of naphthalene in a biochar-amended bioretention facility based on HYDRUS-1D analysis.

Biochar has been proved as a promising and efficient filler in bioretention facilities for enhancing the stormwater pollutants removal. However, the migration behaviors of stormwater pollutants in biochar filled bioretention facilities is unclear. In this study, as one of the most typical stormwater pollutants, naphthalene was selected as an example and a HYDRUS-1D model was first used to understand the migration behavior of naphthalene in a bioretention facility.

An Advanced Machine Learning Model for a Web-Based Artificial Intelligence-Based Clinical Decision Support System Application: Model Development and Validation Study.

Background: Breast cancer is a leading global health concern, necessitating advancements in recurrence prediction and management. The development of an artificial intelligence (AI)-based clinical decision support system (AI-CDSS) using ChatGPT addresses this need with the aim of enhancing both prediction accuracy and user accessibility.

Objective: This study aims to develop and validate an advanced machine learning model for a web-based AI-CDSS application, leveraging the question-and-answer guidance capabilities of ChatGPT to enhance data preprocessing and model development, thereby improving the prediction of breast cancer recurrence.

Impact of transforming karst mountainous forests into urban parks on plant diversity patterns.

The conversion of urban montane forest resources into urban parks requires careful assessment to understand its impacts on plant diversity over time. This study aims to enhance urban biodiversity conservation strategies by analyzing how habitat type and park age affect woody plant diversity. We surveyed woody plant species in 60 sample plots across two different habitats (remnant forest vs.

Exploring the characteristics and source-attributed health risks associated with polycyclic aromatic hydrocarbons and metal elements in atmospheric PM during warm and cold periods in the northern metropolitan area of Taiwan.

Polycyclic aromatic hydrocarbons (PAHs) and metal elements are commonly considered hazardous air pollutants due to their toxic, mutagenic, and carcinogenic properties. However, few studies have simultaneously examined their potential sources and health effects. This study aimed to quantify the PAHs and metal elements in atmospheric PM, investigating their characteristics and potential sources to assess associated health risks in the northern metropolitan area of Taiwan.