Inhibition of the Integrated Stress Response Prevents Natural Forgetting and Corrects Accelerated Forgetting Associated with Epilepsy.

The neural mechanisms underlying the natural and maladaptive forgetting of established memory remain largely unknown. Brain disease states might hijack the physiological forgetting mechanisms, resulting in maladaptive forgetting such as accelerated forgetting that contributes to cognitive decline in various neurologic conditions including epilepsy. Based on the key role of the integrated stress response (ISR) in memory storage and maintenance, we determined whether the ISR underpins natural and accelerated forgetting.

Frequency and severity of idiopathic epistaxis relative to time of day.

This study investigated the frequency of idiopathic epistaxis onset and its severity relative to the time of day. Idiopathic epistaxis was defined as epistaxis in the emergency department, with no epistaxis diagnosis in any hospital 12 months before incident epistaxis. The timing of epistaxis onset was divided into four categories: morning (6:01-12:00), afternoon (12:01-18:00), evening (18:01-24:00), and overnight (00:01-6:00).

Preparation of heteroatom-doped hyper-crosslinked polymers via waste utilization of sulfur-containing petroleum coke: A promising adsorbent for CO capture.

To overcome the worldwide environmental crisis related to the continuous emission of CO, the use of porous organic polymers, which are excellent absorbents and conversion materials, to reduce CO emission is of great significance. Among them, hyper-crosslinked polymers (HCPs) are porous materials with a high pore density that are synthesized using a simple one-pot method that is economical and can realized at a low temperature, hence they have good application prospects as adsorbents for CO. In this study, a batch of petroleum coke-based HCPs with different sulfur contents was prepared via the one-pot Friedel-Crafts alkylation reaction using inexpensive and abundant petroleum coke as raw material.

A Nomogram for the Prediction of Invasiveness in Invasive Pulmonary Adenocarcinoma on the Basis of Multimodal PET/CT Parameters.

Objective: We investigated the value of PET/CT-based multimodal parameters in predicting the degree of differentiation and epidermal growth factor receptor (EGFR) mutations in invasive lung adenocarcinoma (ILA) and assessed the correlation between PET/CT-based multimodal parameters and Ki67.

Methods: We retrospectively collected 113 patients with ILA who underwent PET/CT examination, and differences in PET/CT multimodal parameters between different differentiation groups were analyzed. Binary logistic regression was used to establish a multiparameter model for predicting EGFR mutation, and ROC curve was used to compare the diagnostic efficiency.

Discovering Photoswitchable Molecules for Drug Delivery with Large Language Models and Chemist Instruction Training.

As large language models continue to expand in size and diversity, their substantial potential and the relevance of their applications are increasingly being acknowledged. The rapid advancement of these models also holds profound implications for the long-term design of stimulus-responsive materials used in drug delivery. The large model used Hugging Face's Transformers package with BigBird, Gemma, and GPT NeoX architectures.

Long-Term Outcomes of Prostate-Specific Membrane Antigen-PET Imaging of Recurrent Prostate Cancer.

Importance: Although prostate-specific membrane antigen positron emission tomography (PSMA-PET) has shown improved sensitivity and specificity compared with conventional imaging for the detection of biochemical recurrent (BCR) prostate cancer, the long-term outcomes of a widespread shift in imaging are unknown.

Objective: To estimate long-term outcomes of integrating PSMA-PET into the staging pathway for recurrent prostate cancer.

Design, Setting, And Participants: This decision analytic modeling study simulated outcomes for patients with BCR following initial definitive local therapy.

Efficacy of magnifying endoscopy combined with narrowband imaging in detection of early gastric cancer: a systematic evaluation and meta-analysis.

Objective: To systematically evaluate the diagnostic accuracy of magnifying endoscopy combined with narrowband imaging (ME-NBI) in detecting early gastric cancer (EGC) and to provide a scientific basis for its clinical utility.

Methods: Literature published before May 2024 that utilized ME-NBI for diagnosing EGC was searched across PubMed, EMBASE, The Cochrane Library, Web of Science, and major Chinese databases. Included studies were cohort studies or randomized controlled trials, and their quality was assessed using the QUADAS-2 framework.

Astrocytic LRRK2 Controls Synaptic Connectivity via Regulation of ERM Phosphorylation.

Astrocytes, a major glial cell type of the brain, regulate synapse numbers and function. However, whether astrocyte dysfunction can cause synaptic pathologies in neurological disorders such as Parkinson's Disease (PD) is unknown. Here, we investigated the impact of the most common PD-linked mutation in the leucine-rich repeat kinase 2 () gene (G2019S) on the synaptic functions of astrocytes.

Treatment Access among Younger Medicaid Beneficiaries with Multiple Myeloma.

Purpose: Continuous Medicaid coverage prior to a cancer diagnosis has been associated with earlier detection and better outcomes, for patients with solid tumors. In this study, we aimed to determine if this was observed among patients with multiple myeloma, a hematologic cancer where there are no routine screening tests and most are diagnosed through acute medical events.

Materials And Methods: This is an analysis of the Merative MarketScan Multistate Medicaid Database, a claims-based dataset.

A Human Feedback Strategy for Photoresponsive Molecules in Drug Delivery: Utilizing GPT-2 and Time-Dependent Density Functional Theory Calculations.

Photoresponsive drug delivery stands as a pivotal frontier in smart drug administration, leveraging the non-invasive, stable, and finely tunable nature of light-triggered methodologies. The generative pre-trained transformer (GPT) has been employed to generate molecular structures. In our study, we harnessed GPT-2 on the QM7b dataset to refine a UV-GPT model with adapters, enabling the generation of molecules responsive to UV light excitation.

Biological Roles of Lipids in Rice.

Lipids are organic nonpolar molecules with essential biological and economic importance. While the genetic pathways and regulatory networks of lipid biosynthesis and metabolism have been extensively studied and thoroughly reviewed in oil crops such as soybeans, less attention has been paid to the biological roles of lipids in rice, a staple food for the global population and a model species for plant molecular biology research, leaving a considerable knowledge gap in the biological roles of lipids. In this review, we endeavor to furnish a current overview of the advancements in understanding the genetic foundations and physiological functions of lipids, including triacylglycerol, fatty acids, and very-long-chain fatty acids.

[Land Use Change Driving and Optimization of Carbon Budget in Hangzhou Metropolitan Area].

As climate change, such as global warming, has become a global environmental issue, clarifying the mechanism driving the carbon budget based on land use change has become an inevitable path to realize the "double carbon" goal. Based on the land use change characteristics in the Hangzhou Metropolitan Area from 1995 to 2020, this study employed the inventory accounting method, concentration index, and panel regression models to investigate the driving mechanisms of carbon budget dynamics influenced by land use changes. Moreover, the study utilized a "scenario-actor" policy analysis framework to propose low-carbon strategies through the integration of land use management within territorial spatial planning.

Gut microbiota modulates neurotransmitter and gut-brain signaling.

Neurotransmitters, including 5-hydroxytryptamine (5-HT), dopamine (DA), gamma-aminobutyric acid (GABA), and glutamate, are essential transductors in the Gut-Brain Axis (GBA), playing critical roles both peripherally and centrally. Accumulating evidence suggests that the gut microbiota modulates intestinal neurotransmitter metabolism and gut-to-brain signaling, shedding light on the crucial role of the gut microbiota in brain function and the pathogenesis of various neuropsychiatric diseases, such as major depression disorder (MDD), anxiety, addiction and Parkinson's disease (PD). Despite the exciting findings, the mechanisms underlying the modulation of neurotransmitter metabolism and function by the gut microbiota are still being elucidated.

Asymptomatic Incidence of Monoclonal Gammopathy of Undetermined Significance and Preclinical Duration to Myeloma Diagnosis: A Modeling Study.

Background: Monoclonal gammopathy of undetermined significance (MGUS) is the premalignant condition of multiple myeloma. Given a lack of population-based screening for MGUS and its asymptomatic nature, the epidemiology of MGUS remains unknown. This study estimated age- and race/ethnicity-specific MGUS incidence and preclinical duration from MGUS to multiple myeloma in the United States.

Transdermal characteristic study of bovine sialoglycoproteins with anti-skin aging and accelerating skin wound healing.

Background: Sialoglycoproteins play important roles in various biological processes, including cell adhesion, immune response, and cell signaling. Our previous studies indicated that the bovine sialoglycoproteins could be developed as a reagent against skin aging and as a new candidate for accelerating skin wound healing as well as inhibiting scar formation. However, transdermal characteristic of the bovine sialoglycoproteins is still unknown.

Probing perfection: The relentless art of meddling for pulmonary airway segmentation from HRCT via a human-AI collaboration based active learning method.

In the realm of pulmonary tracheal segmentation, the scarcity of annotated data stands as a prevalent pain point in most medical segmentation endeavors. Concurrently, most Deep Learning (DL) methodologies employed in this domain invariably grapple with other dual challenges: the inherent opacity of 'black box' models and the ongoing pursuit of performance enhancement. In response to these intertwined challenges, the core concept of our Human-Computer Interaction (HCI) based learning models (RS_UNet, LC_UNet, UUNet and WD_UNet) hinge on the versatile combination of diverse query strategies and an array of deep learning models.

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.

Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway structures remains prohibitively time-consuming. While significant efforts have been made towards enhancing automatic airway modelling, current public-available datasets predominantly concentrate on lung diseases with moderate morphological variations.

Engineering Bacillus licheniformis as industrial chassis for efficient bioproduction from starch.

Starch is an attractive feedstock in biorefinery processes, while the low natural conversion rate of most microorganisms limits its applications. Herein, starch metabolic pathway was systematically investigated using Bacillus licheniformis DW2 as the host organism. Initially, the effects of overexpressing amylolytic enzymes on starch hydrolysis were evaluated.

A deep learning model integrating a wind direction-based dynamic graph network for ozone prediction.

Ozone pollution is an important environmental issue in many countries. Accurate forecasting of ozone concentration enables relevant authorities to enact timely policies to mitigate adverse impacts. This study develops a novel hybrid deep learning model, named wind direction-based dynamic spatio-temporal graph network (WDDSTG-Net), for hourly ozone concentration prediction.

[Impacts of Urban Form on Carbon Emissions Under the Goal of Carbon Emission Peak and Carbon Neutrality: A Case Study of the Yangtze River Economic Belt].

Clarifying the mechanism of influence of urban form on carbon emissions is an important prerequisite for achieving urban carbon emission reduction. Taking the Yangtze River Economic Belt as an example, this study elaborated on the general mechanism of urban form on carbon emissions, used multi-source data to quantitatively evaluate the urban form, and explored the impacts of urban form indicators on carbon emissions from 2005 to 2020 at global and sub-regional scales with the help of spatial econometric models and geodetector, respectively. The results showed that:① The carbon emissions of the Yangtze River Economic Belt increased from 2 365.

ScRNA-seq reveals novel immune-suppressive T cells and investigates CMV-TCR-T cells cytotoxicity against GBM.

Background: Glioblastoma (GBM) is a fatal primary brain malignancy in adults. Previous studies have shown that cytomegalovirus (CMV) is a risk factor for tumorigenesis and aggressiveness for glioblastoma. However, little is known about how CMV infection affects immune cells in the tumor microenvironment of GBM.

18Beta-Glycyrrhetinic Acid Attenuates HO-Induced Oxidative Damage and Apoptosis in Intestinal Epithelial Cells via Activating the PI3K/Akt Signaling Pathway.

Oxidative stress causes gut dysfunction and is a contributing factor in several intestinal disorders. Intestinal epithelial cell survival is essential for maintaining human and animal health under oxidative stress. 18beta-Glycyrrhetinic acid (GA) is known to have multiple beneficial effects, including antioxidant activity; however, the underlying molecular mechanisms have not been well established.

Anaplasma bovis and Bartonella spp. in Libyan Jirds (Meriones libycus) from China.

Anaplasma bovis (1), Bartonella krasnovii (3), and Bartonella sp. (17) were detected in 80 Libyan jirds (Meriones libycus) from China. These findings extend the known host and geographic ranges of these pathogens, with neither A.

Immunotherapy utilization patterns in patients with advanced cancer and autoimmune disease.

Purpose: Immunotherapy has been shown to improve cancer survival, but there are no consensus guidelines to inform use in patients with both cancer and autoimmune disease (AD). We sought to examine immunotherapy utilization patterns between cancer patients with and without AD.

Patients And Methods: This retrospective cohort study utilized data from a de-identified nationwide oncology database.