Conservation implications of climatically heterogeneous areas for species diversity in a biodiversity hotspot.

Climate heterogeneity is commonly associated with exceptionally high species richness, thus bolstering ecological resilience and maximizing long-term biodiversity benefits. However, few studies have been conducted to examine the implications of climatically heterogeneous areas (CHAs) for effective biodiversity conservation. In this study, we collected occurrence records of birds and vascular plants in a biodiversity hotspot in Yunnan, China, and delineated corresponding CHAs.

Screening biomarkers for autism spectrum disorder using plasma proteomics combined with machine learning methods.

Background And Aims: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder in children. Early intervention is effective. Investigation of novel blood biomarkers of ASD facilitates early detection and intervention.

Proteomic analysis of plasma total exosomes and placenta-derived exosomes in patients with gestational diabetes mellitus in the first and second trimesters.

Gestational diabetes mellitus (GDM) is the first spontaneous hyperglycemia during pregnancy. Early diagnosis and intervention are important for the management of the disease. This study compared and analyzed the proteins of total plasma exosomes (T-EXO) and placental-derived exosomes (PLAP-EXO) in pregnant women who subsequently developed GDM (12-16 weeks), GDM patients (24-28 weeks) and their corresponding controls to investigate the pathogenesis and biomarkers of GDM associated with exosomes.

Integration of proteomics and metabolomics analysis investigate mechanism of As-induced immune injury in rat spleen.

Arsenic (As) is a widespread metalloid and human carcinogen found in the natural environment, and multiple toxic effects have been shown to be associated with As exposure. As can be accumulated in the spleen, the largest peripheral lymphatic organ, and long-term exposure to As can lead to splenic injury. In this study, a Sprague-Dawley (SD) rat model of As-poisoned was established, aiming to explore the molecular mechanism of As-induced immune injury through the combined analysis of proteomics and metabolomics of rats' spleen.

High-Selective Separation Recovery of Ni, Co, and Mn from the Spent LIBs Via Acid Dissolution and Multistage Oxidation Precipitation.

For recovering Ni, Co, and Mn from lithium-ion batteries, traditional chemical precipitation methods demonstrate low selectivity and significantly contribute to environmental pollution. This study proposes a separation recovery technique for transition metals, specifically Ni, Co, and Mn, from spent LIBs, involving "acid dissolution" and "multistage oxidation precipitation". More than 98 % of transition metals can be extracted from spent LIBs using a low acid concentration (0.

Application of Proteomics and Machine Learning Methods to Study the Pathogenesis of Diabetic Nephropathy and Screen Urinary Biomarkers.

Diabetic nephropathy (DN) has become the main cause of end-stage renal disease worldwide, causing significant health problems. Early diagnosis of the disease is quite inadequate. To screen urine biomarkers of DN and explore its potential mechanism, this study collected urine from 87 patients with type 2 diabetes mellitus (which will be classified into normal albuminuria, microalbuminuria, and macroalbuminuria groups) and 38 healthy subjects.

Effects of arsenic exposure on blood trace element levels in rats and sex differences.

Arsenic (As) is a widespread environmental metalloid and human carcinogen, and its exposure is associated with a wide range of toxic effects, leading to serious health hazards. As poisoning is a complex systemic multi-organ and multi-system damage disease. In this study, a rat model of As poisoning was established to investigate the levels of trace elements in the blood of rats and sex differences in the effect of As on every trace elements in rat blood.

Coaxial Electrospun Porous Core-Shell Nanofibrous Membranes for Photodegradation of Organic Dyes.

In this study, a series of AgCl/ZnO-loaded nanofibrous membranes were prepared using coaxial electrospinning. Their physical and chemical characteristics were evaluated by SEM, TEM, XRD, XPS, IR, PL, and UV-visible spectrometer, and the photocatalytic experiments using methylene blue (MB) as a model pollutant. The formation of AgCl/ZnO heterojunction and the structure of core-shell nanofibers with porous shell layer were confirmed.

Selective Recovery of Battery-Grade LiCO from Spent NCM Cathode Materials Using a One-Step Method of CO Carbonation Recovery Without Acids or Bases.

The recovery of spent lithium-ion batteries by traditional acid leaching is limited by serious pollution, complicated technology, and the low purity of LiCO. To address the problems of the traditional acid leaching process and increasing demand for decarbonization, a technique for the selective carbonation leaching of Li and the recovery of battery-grade LiCO by a simple concentration precipitation process without acids or bases was developed. The coupling of CO and reducing agents could effectively promote the precipitation of MCO (M=Ni/Co/Mn) and the selective leaching of Li by decreasing the reducing capability needed for transition metals and decreasing the pH of the solution.

Autism spectrum disorder: pathogenesis, biomarker, and intervention therapy.

Autism spectrum disorder (ASD) has become a common neurodevelopmental disorder. The heterogeneity of ASD poses great challenges for its research and clinical translation. On the basis of reviewing the heterogeneity of ASD, this review systematically summarized the current status and progress of pathogenesis, diagnostic markers, and interventions for ASD.

Research Advances in Superabsorbent Polymers.

Superabsorbent polymers are new functional polymeric materials that can absorb and retain liquids thousands of times their masses. This paper reviews the synthesis and modification methods of different superabsorbent polymers, summarizes the processing methods for different forms of superabsorbent polymers, and organizes the applications and research progress of superabsorbent polymers in industrial, agricultural, and biomedical industries. Synthetic polymers like polyacrylic acid, polyacrylamide, polyacrylonitrile, and polyvinyl alcohol exhibit superior water absorption properties compared to natural polymers such as cellulose, chitosan, and starch, but they also do not degrade easily.

Investigating metabolic dysregulation in serum of triple transgenic Alzheimer's disease male mice: implications for pathogenesis and potential biomarkers.

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease that lacks convenient and accessible peripheral blood diagnostic markers and effective drugs. Metabolic dysfunction is one of AD risk factors, which leaded to alterations of various metabolites in the body. Pathological changes of the brain can be reflected in blood metabolites that are expected to explain the disease mechanisms or be candidate biomarkers.

Subcellular proteomics insights into Alzheimer's disease development.

Alzheimer's disease (AD), one of the most common dementias, is a neurodegenerative disease characterized by cognitive impairment and decreased judgment function. The expected number of AD patient is increasing in the context of the world's advancing medical care and increasing human life expectancy. Since current molecular mechanism studies on AD pathogenesis are incomplete, there is no specific and effective therapeutic agent.

Multi-Granularity Context Network for Efficient Video Semantic Segmentation.

Current video semantic segmentation tasks involve two main challenges: how to take full advantage of multi-frame context information, and how to improve computational efficiency. To tackle the two challenges simultaneously, we present a novel Multi-Granularity Context Network (MGCNet) by aggregating context information at multiple granularities in a more effective and efficient way. Our method first converts image features into semantic prototypes, and then conducts a non-local operation to aggregate the per-frame and short-term contexts jointly.

Toosendanin Induces Hepatocyte Damage by Inhibiting Autophagic Flux via TFEB-Mediated Lysosomal Dysfunction.

Toosendanin (TSN) is a triterpenoid from the fruit or bark of Sieb et Zucc, which has clear antitumor and insecticidal activities, but it possesses limiting hepatotoxicity in clinical application. Autophagy is a degradation and recycling mechanism to maintain cellular homeostasis, and it also plays an essential role in TSN-induced hepatotoxicity. Nevertheless, the specific mechanism of TSN on autophagy-related hepatotoxicity is still unknown.

Person Foreground Segmentation by Learning Multi-Domain Networks.

Separating the dominant person from the complex background is significant to the human-related research and photo-editing based applications. Existing segmentation algorithms are either too general to separate the person region accurately, or not capable of achieving real-time speed. In this paper, we introduce the multi-domain learning framework into a novel baseline model to construct the Multi-domain TriSeNet Networks for the real-time single person image segmentation.

Exploring the origins of the indentation size effect at submicron scales.

The origin of the indentation size effect has been extensively researched over the last three decades, following the establishment of nanoindentation as a broadly used small-scale mechanical testing technique that enables hardness measurements at submicrometer scales. However, a mechanistic understanding of the indentation size effect based on direct experimental observations at the dislocation level remains limited due to difficulties in observing and quantifying the dislocation structures that form underneath indents using conventional microscopy techniques. Here, we employ precession electron beam diffraction microscopy to "look beneath the surface," revealing the dislocation characteristics (e.

Local Semantic Siamese Networks for Fast Tracking.

Learning a powerful feature representation is critical for constructing a robust Siamese tracker. However, most existing Siamese trackers learn the global appearance features of the entire object, which usually suffers from drift problems caused by partial occlusion or non-rigid appearance deformation. In this paper, we propose a new Local Semantic Siamese (LSSiam) network to extract more robust features for solving these drift problems, since the local semantic features contain more fine-grained and partial information.

Steam Oxidation of Austenitic Heat-Resistant Steels TP347H and TP347HFG at 650⁻800 °C.

Steam oxidation of austenitic heat-resistant steels TP347H and TP347HFG at 650⁻800 °C was investigated. Comprehensive micro-characterization technologies containing Scanning Electron Microscope (SEM), Energy Dispersive X-ray Spectroscopy (EDS), X-ray Diffraction (XRD), and X-ray Photoelectron Spectroscopy (XPS) were employed to observe and analyze the oxidation products. Results show that breakaway oxidation behaviors were observed on TP347H at 700 °C and 800 °C.

Microstructure of FeCrAl Thin Film Composed of Nanocrystals Deposited on Zr Alloy and Their Corrosion Behavior Under Water Steam Atmosphere.

Zr alloy cladding materials is the core component of the nuclear reactor, the safety of cladding materials is very important. Zr alloy cladding materials is inclined to react with water under high temperature. The products are ZrO₂ and H₂.

Multiobject Tracking by Submodular Optimization.

In this paper, we propose a new multiobject visual tracking algorithm by submodular optimization. The proposed algorithm is composed of two main stages. At the first stage, a new selecting strategy of tracklets is proposed to cope with occlusion problem.