Characteristics of Cerebral Autoregulation After Mechanical Thrombectomy and Its Relationship With Prognosis.

Aims: To investigate the characteristics of dynamic cerebral autoregulation (dCA) in patients after mechanical thrombectomy (MT) and the relationship between dCA and prognosis.

Methods: In this prospective study, 89 and 158 patients were enrolled in the MT and non-MT groups, respectively. Both groups underwent dCA measurements within 3 days after stroke.

Proton Exchange Membrane Water Splitting: Advances in Electrode Structure and Mass-Charge Transport Optimization.

Proton exchange membrane water electrolysis (PEMWE) represents a promising technology for renewable hydrogen production. However, the large-scale commercialization of PEMWE faces challenges due to the need for acid oxygen evolution reaction (OER) catalysts with long-term stability and corrosion-resistant membrane electrode assemblies (MEA). This review thoroughly examines the deactivation mechanisms of acidic OER and crucial factors affecting assembly instability in complex reaction environments, including catalyst degradation, dynamic behavior at the MEA triple-phase boundary, and equipment failures.

TriSwinUNETR lobe segmentation model for computing DIR-free CT-ventilation.

Purpose: Functional radiotherapy avoids the delivery of high-radiation dosages to high-ventilated lung areas. Methods to determine CT-ventilation imaging (CTVI) typically rely on deformable image registration (DIR) to calculate volume changes within inhale/exhale CT image pairs. Since DIR is a non-trivial task that can bias CTVI, we hypothesize that lung volume changes needed to calculate CTVI can be computed from AI-driven lobe segmentations in inhale/exhale phases, without DIR.

Nomogram for predicting nutritional risk of cognitive impairment.

Background: Cognitive impairment patients are prone to malnutrition, which further promotes cognitive decline. Cognitive impairment patients are unable to accurately answer subjective questions in the nutrition screening scale. Therefore, it is crucial to establish a nutritional risk prediction model using objective evaluation indicators to evaluate the nutritional status of cognitive impairment patients during hospitalization.

Identifying shared diagnostic genes and mechanisms in vascular dementia and Alzheimer's disease via bioinformatics and machine learning.

Background: Alzheimer's disease (AD) and vascular dementia (VaD) share overlapping pathophysiological characteristics, yet comparative genetic studies are rare. Understanding these overlaps may aid in identifying common diagnostic markers and therapeutic targets.

Objective: This study identifies shared diagnostic genes and mechanisms linking AD and VaD.

Exploring the interconnections of loneliness, anxiety, and depression among nursing students: a network analysis approach.

Objective: Nursing students experience higher rates of anxiety and depression than students in other disciplines due to the demanding academic requirements and clinical training challenges. Loneliness and symptoms of anxiety and depression occur simultaneously; however, the specific interrelationships between these states remain inadequately investigated. This study aimed to utilize network analysis to examine the item-level reciprocal action between loneliness, anxiety, and depression among nursing students.

Facile synthesis of novel Ni-BDC-NH/Au NPs SERS substrates with synergistic enhancement effects for high-performance detection.

Substrate materials with high sensitivity and good reproducibility are highly desirable for the practical applications of surface-enhanced Raman scattering (SERS) techniques. In this study, a novel gold nanoparticle-loaded Ni-based metal-organic framework (Ni-BDC-NH/Au NPs) SERS substrate was successfully synthesized an electrostatic self-assembly method. The enhancement of the SERS signal is achieved owing to the synergy between the chemical enhancement (CM) effect of Ni-BDC-NH and the electromagnetic enhancement (EM) of Au NPs, and the enriching of the analyte near the SERS "hot spots" through the strong adsorption capacity of Ni-BDC-NH.

Effects of glucocorticoid administration routes on patients with acute exacerbations of chronic obstructive pulmonary disease in China: A propensity score-matched longitudinal analysis.

Background: Glucocorticoids are widely used for managing acute exacerbations of chronic obstructive pulmonary disease (AECOPD); however, limited studies have described the comparative effectiveness of inhaled corticosteroids (ICS), systemic corticosteroids administered orally or intravenously (oral/intra), and a combination of ICS and oral/intra for AECOPD treatment in China. Thus, we aimed to explore the effects of different glucocorticoid administration routes during hospitalization on both short- and long-term patient prognosis in AECOPD.

Methods: Data were collected from the Acute Exacerbations of Chronic Obstructive Pulmonary Disease Inpatient Registry study, a nationwide multicenter, prospective, observational study conducted in China from September 2017 to November 2021.

Mesothelin-targeted CAR-T cells secreting NKG2D-BiTEs exhibit potent efficacy against triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype with poor prognosis and limited treatment options. Chimeric antigen receptor (CAR)-T cell therapy holds promise, but its efficacy is hindered by tumor antigen escape and heterogeneity. To address these challenges, we developed a novel bispecific T cell engagers CAR-T (BiTEs CAR-T) targeting Mesothelin (MSLN) and secreting NKG2D-Bispecific T cell Engagers (BiTEs) to engage NKG2D ligands (NKG2DL).

Characterization and optimization of mnn11Δ-mediated enhancement in heterologous protein production in Kluyveromyces marxianus.

Background: N-glycosylation is a prevalent post-translational modification in eukaryotes, essential for regulating protein secretion. In Saccharomyces cerevisiae, glycosylation mutants have been shown to enhance the secretion of heterologous glycosylated proteins. However, whether these mutants can also increase the secretion of non-glycosylated proteins and whether the growth defects associated with glycosylation mutations can be mitigated remains unclear.

Unveiling the oncogenic role of SLC25A13: a multi-omics pan-cancer analysis reveals its impact on glioma progression.

SLC25A13, a pivotal component of the mitochondrial aspartate-glutamate carrier, is integral to cellular metabolism and has been linked to various diseases. However, its role in cancer biology remains largely unexplored. In this study, we employed multi-omics data to elucidate the genetic landscape, expression profile, and prognostic value of SLC25A13 in a pan-cancer context.

A short-term predictive model for disease progression in acute-on-chronic liver failure: integrating spectral CT extracellular liver volume and clinical characteristics.

Background: Acute-on-chronic liver failure (ACLF) is a life-threatening hepatic syndrome. Therefore, this study aimed to develop a comprehensive model combining extracellular liver volume derived from spectral CT (ECV) and sarcopenia, for the early prediction of short-term (90-day) disease progression in ACLF.

Materials And Methods: A retrospective cohort of 126 ACLF patients who underwent hepatic spectral CT scans was included.

Single-cell transcriptomic atlas of the human testis across the reproductive lifespan.

Testicular aging is associated with declining reproductive health, but the molecular mechanisms are unclear. Here we generate a dataset of 214,369 single-cell transcriptomes from testicular cells of 35 individuals aged 21-69, offering a resource for studying testicular aging and physiology. Machine learning analysis reveals a stronger aging response in somatic cells compared to germ cells.

Prediction of open-pit mine truck travel time based on LSTM-TabTransformer.

Truck travel time prediction is the basis for real-time optimal scheduling decision of open-pit trucks. Most prediction models for open-pit truck travel time mainly rely on a single machine learning algorithm or model to optimize the hyperparameters, which is difficult to accurately capture the composite characteristics of truck travel time data, affectting the accuracy of the prediction results. This paper proposed a travel time prediction method for open-pit trucks based on LSTM-TabTransformer.

An intercity investment network dataset of China based on the enterprise registration records (2000-2020).

Intercity investment activities among enterprises reflect the flow of capital between cities, thereby directly illustrating the economic connections between them. However, there is currently no publicly available dataset that captures this important feature. In this study, we introduce an intercity investment network (IIN) dataset for China, covering the period from 2000 to 2020, based on 17,273,411 large-scale enterprise registration records.

Sleep traits causally affect epigenetic age acceleration: a Mendelian randomization study.

Sleep disorders (SDs) are a common issue in the elderly. Epigenetic clocks based on DNA methylation (DNAm) are now considered highly accurate predictors of the aging process and are associated with age-related diseases. This study aimed to investigate the causal relationship between sleep traits and the epigenetic clock using Mendelian randomization (MR) analysis.

Preclinical Safety Assessment of the Oral Administration of Lactobacillus plantarum GUANKE in Animal Models.

Probiotics have a long history as fermented food or food supplements. The health benefits and safety profiles of probiotics are strain-specific and should be evaluated individually. The aim of this study was to assess the safety of the Lactobacillus plantarum GUANKE (GUANKE) strain by conducting pharmacological studies, oral toxicity assessments, and investigating the colonization and translocation of GUANKE in experimental animal models.

Transjugular Intrahepatic Portosystemic Shunt for Preventing Rebleeding of Esophageal Varices in Patients with Portal Cavernous Transformation.

Purpose: Recurrent esophageal variceal bleeding and/or refractory ascites in patients with cavernous transformation of the portal vein (CTPV) is associated with a high fatality rate. Transjugular intrahepatic portosystemic shunt (TIPS) provides a treatment option for preventing esophageal variceal rebleeding and/or refractory ascites. This retrospective study evaluated the safety and efficacy of TIPS for the patients involved.

Uncovering the Prevalence and Genetic Characterization of Rabbit-Derived Paslahepevirus Balayani (Hepatitis E Virus) in Hebei Province, China.

Paslahepevirus balayani (hepatitis E virus) is a zoonotic pathogen, with rabbit Paslahepevirus balayani (HEV-3ra) being widely distributed among global rabbit populations. Notably, in China, rabbits constitute a significant HEV host, second only to swine. Emerging evidence suggests that HEV-3ra possesses the capability to cross species barriers and infect humans.

Temperature-Responsive Microemulsion for Efficient Recyclable Degreasing of Fatty Pickled Sheepskin.

In the leather production process, emulsification degreasing can effectively remove grease. However, the direct discharge of emulsifiers often leads to substantial pollution. With the aim of addressing this issue and realizing the recycling of degreasing agents, temperature-responsive microemulsions were proposed for the leather degreasing process in this research.

Rapid and real time detection of black tea rolling quality by using an inexpensive machine vison system.

Rolling is a crucial step in black tea manufacturing. Rolling is achieved through a rolling machine, which achieves the processes of crushing, tearing, and curling. At present, the lack of intelligent detection for black tea rolling quality has limited the development of automation in the black tea industry.

Arsenene-Vanadene nanodots co-activate Apoptosis/Ferroptosis for enhanced chemo-immunotherapy.

Triple-Negative Breast Cancer (TNBC) represents a highly aggressive subtype of breast cancer with an unfavorable prognosis, characterized by minimal immune infiltration and pronounced immune suppression, resulting in a limited response to immunotherapy. In this study, a multifunctional Arsenene-Vanadene nanodot (AsV) drug delivery system is introduced, which responds to the tumor microenvironment by releasing arsenic and vanadium. Arsenic undergoes oxidation to generate highly toxic trivalent arsenic, which induces apoptosis in tumor cells while utilizing apoptotic cell debris to transiently activate the immune system.

Pancreas-targeted lipid nanoparticles for relatively non-invasive interleukin-12 mRNA therapy in orthotopic pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) represents 90 % of pancreatic cancers and shows limited response to immune therapy owing to the highly immunosuppressive tumor microenvironment (TME). Cytokine-encoded mRNA therapy demonstrates a great promise in converting "cold" tumors into "hot" ones, while it is typically administered through intratumoral injection and applicable only to superficial tumors, which limites their application in PDAC. In this study, we design and develop a lipid nanoparticle (LNP) delivery system capable of targeting pancreatic tissue via intraperitoneal (I.

[An efficient and lightweight skin pathology detection method based on multi-scale feature fusion using an improved RT-DETR model].

Objectives: The presence of multi-scale skin lesion regions and image noise interference and limited resources of auxiliary diagnostic equipment affect the accuracy of skin disease detection in skin disease detection tasks. To solve these problems, we propose a highly efficient and lightweight skin disease detection model using an improved RT-DETR model.

Methods: A lightweight FasterNet was introduced as the backbone network and the FasterNetBlock module was parametrically refined.

MiLNet: Multiplex Interactive Learning Network for RGB-T Semantic Segmentation.

Semantic segmentation methods enhance robust and reliable understanding under adverse illumination conditions by integrating complementary information from visible and thermal infrared (RGB-T) images. Existing methods primarily focus on designing various feature fusion modules between different modalities, overlooking that feature learning is the critical aspect of scene understanding. In this paper, we propose a novel module-free Multiplex Interactive Learning Network (MiLNet) for RGB-T semantic segmentation, which adeptly integrates multi-model, multi-modal, and multi-level feature learning, fully exploiting the potential of multiplex feature interaction.