C5aR1-positive adipocytes mediate non-shivering thermogenesis in neonatal mice.

Brown adipose tissue (BAT) plays an important role in maintaining body temperature in newborn mammals; however, its mechanisms remain poorly understood. Here, we report the identification of a special population of brown adipose tissue-derived stromal cells (ASCs) in neonatal mice that highly express CD45 and can be differentiated into adipocytes with lower thermogenic ability. These CD45 adipocytes also characteristically contained complement C5a receptor 1(C5aR1) on the cell membrane.

Unraveling pathogenesis and potential biomarkers for autism spectrum disorder associated with HIF1A pathway based on machine learning and experiment validation.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a high social burden and limited treatments. Hypoxic condition of the brain is considered an important pathological mechanism of ASD. HIF1A is a key participant in brain hypoxia, but its contribution to the pathophysiological landscape of ASD remains unclear.

A multi-view learning approach with diffusion model to synthesize FDG PET from MRI T1WI for diagnosis of Alzheimer's disease.

Introduction: This study presents a novel multi-view learning approach for machine learning (ML)-based Alzheimer's disease (AD) diagnosis.

Methods: A diffusion model is proposed to synthesize the fluorodeoxyglucose positron emission tomography (FDG PET) view from the magnetic resonance imaging T1 weighted imaging (MRI T1WI) view and incorporate two synthesis strategies: one-way synthesis and two-way synthesis. To assess the utility of the synthesized views, we use multilayer perceptron (MLP)-based classifiers with various combinations of the views.

Spraying KHPO Alleviates the Damage of Spring Low-Temperature Stress by Improving the Physiological Characteristics of Wheat Flag Leaves.

The low-temperature stress (LTS) in spring results in tremendous yield loss in wheat production, and the application of potassium dihydrogen phosphate (KHPO) can alleviate stress-induced damage. However, the underlying effect of spraying KHPO on the physiological characteristics of wheat flag leaves under spring LTS remains unclear. In this study, we investigated the effect of spraying KHPO on flag leaf physiological traits and yield under spring LTS, including treatments at 15 °C and spraying HO (CK), treatment at -4 °C and spraying HO (LT1), and treatment at -4 °C and spraying KHPO (LT2).

Increased serum carboxylesterase-1 levels are associated with metabolic dysfunction associated steatotic liver disease and metabolic syndrome in children with obesity.

Background: Carboxylesterase 1(CES1) is expressed mainly in the liver and adipose tissue and is highly hypothesized to play an essential role in metabolism. Our study aimed to investigate the association between CES1 and metabolic syndrome (MetS) and metabolic dysfunction associated steatotic liver disease (MASLD) in children with obesity in China.

Methods: This study included 72 children with obesity aged 6-13years (including 25(35%) diagnosed as MetS and 36(50%) diagnosed as MASLD).

Fractional Tensor Recurrent Unit (fTRU): A Stable Forecasting Model With Long Memory.

The tensor recurrent model is a family of nonlinear dynamical systems, of which the recurrence relation consists of a -fold (called degree- ) tensor product. Despite such models frequently appearing in advanced recurrent neural networks (RNNs), to this date, there are limited studies on their long memory properties and stability in sequence tasks. In this article, we propose a fractional tensor recurrent model, where the tensor degree is extended from the discrete domain to the continuous domain, so it is effectively learnable from various datasets.

A comparative study of GNN and MLP based machine learning for the diagnosis of Alzheimer's Disease involving data synthesis.

Alzheimer's Disease (AD) is a neurodegenerative disease that commonly occurs in older people. It is characterized by both cognitive and functional impairment. However, as AD has an unclear pathological cause, it can be hard to diagnose with confidence.

A Systematic Review of Application Progress on Machine Learning-Based Natural Language Processing in Breast Cancer over the Past 5 Years.

Artificial intelligence (AI) has been steadily developing in the medical field in the past few years, and AI-based applications have advanced cancer diagnosis. Breast cancer has a massive amount of data in oncology. There has been a high level of research enthusiasm to apply AI techniques to assist in breast cancer diagnosis and improve doctors' efficiency.

Integrated analyses of brain and platelet omics reveal their common altered and driven molecules in Alzheimer's disease.

Platelets may serve as a perfect peripheral source for exploring diagnostic biomarkers for Alzheimer's disease (AD); however, the molecular linkage between platelet and the brain is missing. To find the common altered and driving molecules in both brain and the platelet, we performed an integrated analysis of our platelet omics and brain omics reported in the literature, and analyzed their correlations with AD-specific pathology and cognitive impairment. By integrating the gene and protein expression profiles from 269 AD patients, we deduced 239 differentially expressed proteins (DEPs) appeared in both brain and the platelet, and 70.

Alzheimer-like tau accumulation in dentate gyrus mossy cells induces spatial cognitive deficits by disrupting multiple memory-related signaling and inhibiting local neural circuit.

Abnormal tau accumulation and spatial memory loss constitute characteristic pathology and symptoms of Alzheimer disease (AD). Yet, the intrinsic connections and the mechanism between them are not fully understood. In the current study, we observed a prominent accumulation of the AD-like hyperphosphorylated and truncated tau (hTau N368) proteins in hippocampal dentate gyrus (DG) mossy cells of 3xTg-AD mice.

An intelligent early warning system of analyzing Twitter data using machine learning on COVID-19 surveillance in the US.

The World Health Organization (WHO) declared on 11th March 2020 the spread of the coronavirus disease 2019 (COVID-19) a pandemic. The traditional infectious disease surveillance had failed to alert public health authorities to intervene in time and mitigate and control the COVID-19 before it became a pandemic. Compared with traditional public health surveillance, harnessing the rich data from social media, including Twitter, has been considered a useful tool and can overcome the limitations of the traditional surveillance system.

Applications of Explainable Artificial Intelligence in Diagnosis and Surgery.

In recent years, artificial intelligence (AI) has shown great promise in medicine. However, explainability issues make AI applications in clinical usages difficult. Some research has been conducted into explainable artificial intelligence (XAI) to overcome the limitation of the black-box nature of AI methods.

TiO Hollow Spheres With Flower-Like SnO Shell as Anodes for Lithium-Ion Batteries.

SnO is a promising anode material for lithium-ion batteries due to its high theoretical specific capacity and low operation voltage. However, its poor cycling performance hinders its commercial application. In order to improve the cycling stability of SnO electrodes, novel flower-like SnO/TiO hollow spheres were prepared by facile hydrothermal method using carbon spheres as templates.

Identification of novel ACAN mutations in two Chinese families and genotype-phenotype correlation in patients with 74 pathogenic ACAN variations.

Background: ACAN (OMIM 155760) is located on chromosome 15q26 and encodes the production of aggrecan. Aggrecan is a large chondroitin sulfate proteoglycan with a molecular weight of 254 kDa and contains 2530 amino acids. It is a critical structural component of the extracellular matrix of cartilage, including growth plate, articular, and intervertebral disk cartilage.

The Role and Impact of Deep Learning Methods in Computer-Aided Diagnosis Using Gastrointestinal Endoscopy.

At present, the application of artificial intelligence (AI) based on deep learning in the medical field has become more extensive and suitable for clinical practice compared with traditional machine learning. The application of traditional machine learning approaches to clinical practice is very challenging because medical data are usually uncharacteristic. However, deep learning methods with self-learning abilities can effectively make use of excellent computing abilities to learn intricate and abstract features.

Linking reservoir ecosystems research to the sustainable development goals.

Reservoirs account for about 10% of the freshwater stored in lakes worldwide. These reservoirs are home to 'reservoir ecosystems', that is, the aquatic and non-aquatic interactive ecosystems associated with artificial lakes where water is stored, typically behind a dam, for human purposes. While reservoir ecosystems provide various ecosystem services for sustainable development, their significance in research and policy has not been well understood and not well defined in the 2030 United Nation's (UN) Agenda for Sustainable Development.

Molecular dynamics and in silico mutagenesis on the reversible inhibitor-bound SARS-CoV-2 main protease complexes reveal the role of lateral pocket in enhancing the ligand affinity.

The 2019 novel coronavirus pandemic caused by SARS-CoV-2 remains a serious health threat to humans and there is an urgent need to develop therapeutics against this deadly virus. Recent scientific evidences have suggested that the main protease (M) enzyme in SARS-CoV-2 can be an ideal drug target due to its crucial role in the viral replication and transcription processes. Therefore, there are ongoing research efforts to identify drug candidates against SARS-CoV-2 M that resulted in hundreds of X-ray crystal structures of ligand-bound M complexes in the Protein Data Bank (PDB) describing the interactions of different fragment chemotypes within different sites of the M.

A High Proportion of Novel ACAN Mutations and Their Prevalence in a Large Cohort of Chinese Short Stature Children.

Context: Aggrecan, encoded by the ACAN gene, is the main proteoglycan component in the extracellular cartilage matrix. Heterozygous mutations in ACAN have been reported to cause idiopathic short stature. However, the prevalence of ACAN pathogenic variants in Chinese short stature patients and clinical phenotypes remain to be evaluated.

Binder-Free Charantia-Like Metal-Oxide Core/Shell Nanotube Arrays for High-Performance Lithium-Ion Anodes.

The performance of anodes of lithium-ion batteries relies largely on the architecture and composition of the hybrid active materials. We present a two-step, seed-free, solution-based method for the direct growth of hierarchical charantia-like TiO/FeO core/shell nanotube arrays on carbon cloth substrates. An ultrahigh loading of the nanomaterial on carbon fibers was achieved with this method without the use of a binder.

Three-Dimensional PrGO-Based Sandwich Composites With MoS Flowers as Stuffings for Superior Lithium Storage.

Graphene-based MoS nanocomposites are expected to be promising anode materials for lithium ion batteries because of their large specific capacity and high conductivity. However, the aggregation of graphene and the weak interaction between the two components hinder their practical application. Inspired by the sandwich structure, novel three-dimensional flower-like MoS-PrGO sandwich composites were proposed as an advanced anode material for lithium-ion batteries.

Deletion at 12q12 increases the risk of developmental delay and intellectual disability.

Single-nucleotide polymorphism (SNP) arrays have been widely used to identify novel genomic imbalances. Many of these genomic imbalances have been confirmed to interact with developmental delays, intellectual disabilities (IDs), and congenital defects. Here, we identify a Chinese girl with a 3.

High-Frequency Stimulation of the Subthalamic Nucleus Activates Motor Cortex Pyramidal Tract Neurons by a Process Involving Local Glutamate, GABA and Dopamine Receptors in Hemi-Parkinsonian Rats.

Deep brain stimulation (DBS) is widely used to treat advanced Parkinson’s disease (PD). Here, we investigated how DBS applied on the subthalamic nucleus (STN) influenced the neural activity in the motor cortex. Rats, which had the midbrain dopaminergic neurons partially depleted unilaterally, called the hemi-Parkinsonian rats, were used as a study model.

Tracking-by-detection of surgical instruments in minimally invasive surgery via the convolutional neural network deep learning-based method.

Background: Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging problem. Tracking of surgical instruments by vision-based methods is quite lucrative, due to its flexible implementation via software-based control with no need to modify instruments or surgical workflow.

Methods: A MIS instrument is conventionally split into a shaft and end-effector portions, while a 2D/3D tracking-by-detection framework is proposed, which performs the shaft tracking followed by the end-effector one.