Diagnosis of epilepsy by machine learning of high-performance plasma metabolic fingerprinting.

Epilepsy is a chronic neurological disorder that causes a major threat to public health and the burden of disease worldwide. High-performance diagnostic tools for epilepsy need to be developed to improve diagnostic accuracy and efficiency while still missing. Herein, we utilized nanoparticle-enhanced laser desorption/ionization mass spectrometry (NELDI MS) to acquire plasma metabolic fingerprints (PMFs) from epileptic and healthy individuals for timely and accurate screening of epilepsy.

Identification of Breast Cancer Immune-related Prognostic Characteristics in Tumor Microenvironment.

Background: Accumulated evidence suggest that tumor microenvironment (TME) plays a crucial role in breast cancer (BRCA) progression and therapeutic effects.

Objective: This study aimed to characterize immune-related BRCA subtypes in TME, and identify genes with prognostic value.

Methods: RNA sequencing profiles with corresponding clinical data from The Cancer Genome Atlas (TCGA) database of BRCA patients were downloaded to evaluate immune infiltration using the single-sample gene set enrichment (ssGAEA) algorithm.

Designing Peptide-Based Nanoinhibitors of Programmed Cell Death Ligand 1 (PD-L1) for Enhanced Chemo-immunotherapy.

The combination of immune checkpoint blockade (ICB) and chemotherapy has shown significant potential in the clinical treatment of various cancers. However, circulating regeneration of PD-L1 within tumor cells greatly limits the efficiency of chemo-immunotherapy and consequent patient response rates. Herein, we report the synthesis of a nanoparticle-based PD-L1 inhibitor (FRS) with a rational design for effective endogenous PD-L1 suppression.

Association of molecular subtypes and treatment with survival in invasive micropapillary breast cancer: an analysis of the Surveillance, Epidemiology, and End Results database.

Background: This study aims to examine the features, treatments, and survival of invasive micropapillary carcinoma (IMPC) according to different molecular subtypes.

Methods: In this cohort study, data between 2010 and 2018 were retrospectively reviewed from the Surveillance, Epidemiology, and End Results database. Molecular subtypes were categorized into four varieties: hormone receptor (HR)+/HER2- (Luminal A), HR+/HER2+ (Luminal B), HR-/HER2- [triple-negative (TN)], and HR-/HER2+ (HER2 enriched).

Identification of Bamboo Species Based on Extreme Gradient Boosting (XGBoost) Using Zhuhai-1 Orbita Hyperspectral Remote Sensing Imagery.

Mapping the distribution of bamboo species is vital for the sustainable management of bamboo and for assessing its ecological and socioeconomic value. However, the spectral similarity between bamboo species makes this work extremely challenging through remote sensing technology. Existing related studies rarely integrate multiple feature variables and consider how to quantify the main factors affecting classification.

Spatial-Temporal Evolution and Driving Forces of Drying Trends on the Qinghai-Tibet Plateau Based on Geomorphological Division.

The Qinghai-Tibet Plateau (QTP) is a sensor of global climate change and regional human activities, and drought monitoring will help to achieve its ecological protection and sustainable development. In order to effectively control the geospatial scale effect, we divided the study area into eight geomorphological sub-regions, and calculated the Temperature-Vegetation Drought Index (TVDI) of each geomorphological sub-region based on MODIS Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) data, and synthesized the TVDI of the whole region. We employed partial and multiple correlation analyses to identify the relationship between TVDI and temperature and precipitation.

Spatial-Temporal Evolution and Driving Forces of NDVI in China's Giant Panda National Park.

Identifying the ecological evolution trends and vegetation driving mechanisms of giant panda national parks can help to improve the protection of giant panda habitats. Based on the research background of different geomorphological zoning, we selected the MODIS NDVI data from 2000 to 2020 to analyze the NDVI trends using a univariate linear model. A partial correlation analysis and multiple correlation analysis were used to reveal the influence of temperature and precipitation on NDVI trends.

Susceptibility Analysis of Geohazards in the Longmen Mountain Region after the Wenchuan Earthquake.

Multitemporal geohazard susceptibility analysis can not only provide reliable results but can also help identify the differences in the mechanisms of different elements under different temporal and spatial backgrounds, so as to better accurately prevent and control geohazards. Here, we studied the 12 counties (cities) that were severely affected by the Wenchuan earthquake of 12 May 2008. Our study was divided into four time periods: 2008, 2009-2012, 2013, and 2014-2017.