Spatial-Temporal Pattern Evolution of Public Sentiment Responses to the COVID-19 Pandemic in Small Cities of China: A Case Study Based on Social Media Data Analysis.

The impact of the COVID-19 pandemic on public mental health has become increasingly prominent. Therefore, it is of great value to study the spatial-temporal characteristics of public sentiment responses to COVID-19 exposure to improve urban anti-pandemic decision-making and public health resilience. However, the majority of recent studies have focused on the macro scale or large cities, and there is a relative lack of adequate research on the small-city scale in China.

Ufl1 deficiency causes skin pigmentation by up-regulation of Endothelin-1.

Ufmylation (UFM1 modification) is a newly identified ubiquitin-like modification system involved in numerous cellular processes. However, the regulatory mechanisms and biological functions of this modification remain mostly unknown. We have recently reported that Ufmylation family genes have frequent somatic copy number alterations in human cancer including melanoma, suggesting involvement of Ufmylation in skin function and disease.

Cluster Kernel Reinforcement Learning-based Kalman Filter for Three-Lever Discrimination Task in Brain-Machine Interface.

Brain-Machine Interface (BMI) translates paralyzed people's neural activity into control commands of the prosthesis so that their lost motor functions could be restored. The neural activities represent brain states that change continuously over time which brings the challenge to the online decoder. Reinforcement Learning (RL) has the advantage to construct the dynamic neural-kinematic mapping during the interaction.

Estimating Reward Function from Medial Prefrontal Cortex Cortical Activity using Inverse Reinforcement Learning.

Reinforcement learning (RL)-based brain-machine interfaces (BMIs) learn the mapping from neural signals to subjects' intention using a reward signal. External rewards (water or food) or internal rewards extracted from neural activity are leveraged to update the parameters of decoders in the existing RL-based BMI framework. However, for complex tasks, the design of external reward could be difficult, which may not fully reflect the subject's own evaluation internally.

Modeling Neural Connectivity in a Point-Process Analogue of Kalman Filter.

A neural encoding model describes how single neuron tunes to external stimuli as well as its connectivity with other neurons. The connectivity illustrates the neuronal interaction within populations in response to the shared latent brain states. Understanding these interactions is crucial to computationally predict the neural activity, which elucidates the neural encoding mechanism A computational analysis on the neural connectivity also facilitates developing more point process decoding model to interpret movement state from neural spike observations for brain machine interfaces (BMI).

Clinical value of plasmablasts in predicting disease relapse in patients with IgG4-related disease.

Objectives: To explore the value of plasmablasts in predicting disease relapse in IgG4-related diseases (IgG4-RD).

Methods: Treatment-naïve IgG4-RD patients treated with glucocorticoid (GC) monotherapy or leflunomide (LEF) and GC combination therapy diagnosed at the Chinese PLA General Hospital during February 2017 and January 2018 were included in this study. The absolute plasmablast count was measured by using the absolute count tubes with flow cytometry.

MGA-YOLO: A lightweight one-stage network for apple leaf disease detection.

Apple leaf diseases seriously damage the yield and quality of apples. Current apple leaf disease diagnosis methods primarily rely on human visual inspection, which often results in low efficiency and insufficient accuracy. Many computer vision algorithms have been proposed to diagnose apple leaf diseases, but most of them are designed to run on high-performance GPUs.

Preparation of pyrrolidinyl diglycolamide bonded silica particles and its rare earth separation properties.

The separation of rare earth elements by solid phase containing diglycolamide-type ligands is a hot topic. In this study, 2-[2-oxo-2-(1-pyrrolidinyl)ethoxy]acetic acid (PYRDGA) was synthesized and attached to the silica. The binding strength of SiO@PYRDGA for rare earths showed a single increasing trend with the radius of rare earth atoms.

Metric learning for comparing genomic data with triplet network.

Many biological applications are essentially pairwise comparison problems, such as evolutionary relationships on genomic sequences, contigs binning on metagenomic data, cell type identification on gene expression profiles of single-cells, etc. To make pair-wise comparison, it is necessary to adopt suitable dissimilarity metric. However, not all the metrics can be fully adapted to all possible biological applications.

Higher levels of peripheral blood glucose in the acute stage of stroke increase the risk of post-stroke depression: A systematic review and meta-analysis.

Background: Multiple investigations have shown that diabetes mellitus is a predictor of post-stroke depression (PSD). However, whether elevated levels of fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are associated with an increased risk of PSD remains controversial.

Methods: We comprehensively searched databases for eligible studies.

Xenobiotic responses of Drosophila melanogaster to insecticides with different modes of action and entry.

Depending on their chemical structure, insecticides enter the insect body either through the cuticle or by ingestion (mode of entry [MoE]), and, naturally, harm or even kill insects through different mechanisms (modes of action). In parallel, they trigger a systemic detoxification response, especially by activation of detoxification gene expression. We monitored the acute genetic alterations of known xenobiotic response target genes against five different insecticides with two most common MoEs (contact toxicity and stomach toxicity), found that: 1.

Extracting synchronized neuronal activity from local field potentials based on a marked point process framework.

Brain-machine interfaces (BMIs) translate neural activity into motor commands to restore motor functions for people with paralysis. Local field potentials (LFPs) are promising for long-term BMIs, since the quality of the recording lasts longer than single neuronal spikes. Inferring neuronal spike activity from population activities such as LFPs is challenging, because LFPs stem from synaptic currents flowing in the neural tissue produced by various neuronal ensembles and reflect neural synchronization.

Novel LncRNA ZFHX4-AS1 as a Potential Prognostic Biomarker That Affects the Immune Microenvironment in Ovarian Cancer.

Background: Ovarian cancer (OvCa) is a malignant disease of the female reproductive system with a high mortality rate. LncRNA has been confirmed to play a crucial role in the development and progression of various cancer types. Novel lncRNA ZFHX4-AS1 has been reported in several cancers, albeit its functional mechanisms in OvCa remain unclear.

TAS2R supports odontoblastic differentiation of human dental pulp stem cells in the inflammatory microenvironment.

Background: Inflammatory microenvironment promotes odontoblastic differentiation in human dental pulp stem cells (hDPSCs), but the regulatory mechanisms remain unclear. In this study, we aimed to explore the role of TAS2R in odontoblastic differentiation of hDPSCs in the inflammatory microenvironment.

Methods: Microarray analysis was performed to explore the differential mRNA profiles in inflammatory and healthy pulp tissues from the patients.

Spike prediction on primary motor cortex from medial prefrontal cortex during task learning.

. Brain-machine interfaces (BMIs) aim to help people with motor disabilities by interpreting brain signals into motor intentions using advanced signal processing methods. Currently, BMI users require intensive training to perform a pre-defined task, not to mention learning a new task.

Personalized tooth-supported digital guide plate used in the treatment of trigeminal neuralgia with balloon compression.

Background: Balloon compression (BC) is a simple and effective operation to treat trigeminal neuralgia (TN). The most difficult procedure in BC is related to fast and accurate foramen ovale (FO) insertion. In this study, we introduced a new method incorporating a personalized tooth-supported digital guide plate to reduce patient trauma, improve the accuracy and the success rate of insertion, and reduce surgeons' radiation exposure.

Atypical Climacteric and Functional Ethylene Metabolism and Signaling During Fruit Ripening in Blueberry ( sp.).

Climacteric fruits display an increase in respiration and ethylene production during the onset of ripening, while such changes are minimal in non-climacteric fruits. Ethylene is a primary regulator of ripening in climacteric fruits. The ripening behavior and role of ethylene in blueberry ( sp.

Neutrophil-to-Lymphocyte Ratio, Platelet-to-Lymphocyte Ratio, and Monocyte-to-Lymphocyte Ratio in Depression: An Updated Systematic Review and Meta-Analysis.

Background: Research on neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) in depression is still emerging and has increased 3-fold since the first meta-analysis. An updated meta-analysis with sufficient studies can provide more evidence for a potential relationship between NLR, PLR, MLR, and depression.

Methods: We identified 18 studies from the PubMed, EMBASE, Cochrane library, and Web of Science databases.

N6-methyladenosine-related lncRNAs identified as potential biomarkers for predicting the overall survival of Asian gastric cancer patients.

Objective: Gastric cancer (GC) is one of the most prevalent malignant tumors in Asian countries. Studies have proposed that lncRNAs can be used as diagnostic and prognostic indicators of GC due to the high specificity of lncRNAs expression involvement in GC. Recently, N6-methyladenosine (m6A) has also emerged as an important modulator of the expression of lncRNAs in GC.

Selection and identification of a specific peptide binding to ovarian cancer cells from a phage-displayed peptide library.

Objectives: Ovarian cancer is one of the most fatal gynecological malignancies. It is emergently needed to select a novel molecular fragment as a targeting element for the future development of molecular imaging diagnosis and targeting chemotherapy to ovarian cancer.

Results: After five rounds of biopanning, a total of 44 positive phage clones were selected from final phage displayed peptide library.