Publications by authors named "Xing He"

Background: Previous epidemiologic studies of autoimmune diseases in the United States (US) have included a limited number of diseases or used meta-analyses that rely on different data collection methods and analyses for each disease.

Methods: To estimate the prevalence of autoimmune diseases in the US, we used electronic health record data from six large medical systems in the US. We developed a software program using common methodology to compute the estimated prevalence of autoimmune diseases alone and in aggregate that can be readily used by other investigators to replicate or modify the analysis over time.

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Reticulophagy selectively degrades fragments of the endoplasmic reticulum (ER) through macroautophagy/autophagy to maintain ER homeostasis. The deficiency of reticulophagy results in the unfolded protein response (UPR), which is a crucial clue to the pathogenesis of inflammatory diseases. However, the detailed mechanism underlying the cross-regulation between reticulophagy and inflammatory diseases remains largely unclear.

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Alarmin cytokines including IL-25, IL-33, and thymic stromal lymphopoietin (TSLP) function as danger signals to trigger host immunity in response to tissue injury caused by pathogenic factors such as parasitic infections. Parasitic diseases also provide an excellent context to study their functions and mechanisms. Numerous studies have indicated that alarmin cytokine released by non-immune cells such as epithelial and stromal cells induce the hosts to initiate a type 2 immunity that drives parasite expulsion but also host pathology such as tissue injury and fibrosis.

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Immunoreceptors have crucial roles in sensing environmental signals and initiating immune responses to protect the host. Dysregulation of immunoreceptor signalling can therefore lead to a range of diseases, making immunoreceptor-based therapies a promising frontier in biomedicine. A common feature of various immunoreceptors is the basic-residue-rich sequence (BRS), which is a largely unexplored aspect of immunoreceptor signalling.

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Scanning ion conductance microscopy (SICM) is a powerful surface imaging tool used in the electrolytic environment. Tip-enhanced Raman spectroscopy (TERS) can give more information in addition to the morphology provided by the SICM by utilizing label-free Raman spectroscopy aided by the localized plasmonic enhancement from the metal-coated probes. In this study, the integration of SICM with TERS is demonstrated through employing a silver-coated plasmonic nanopipette.

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Background: Integrating advanced machine-learning (ML) algorithms into clinical practice is challenging and requires interdisciplinary collaboration to develop transparent, interpretable, and ethically sound clinical decision support (CDS) tools. We aimed to design a ML-driven CDS tool to predict opioid overdose risk and gather feedback for its integration into the University of Florida Health (UFHealth) electronic health record (EHR) system.

Methods: We used user-centered design methods to integrate the ML algorithm into the EHR system.

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Trifluoromethyl (CF) and other fluoroalkyl groups are of great significance in the fields of pharmaceutical chemistry and agricultural chemicals. Fluoroalkyl acids, especially trifluoroacetic acid (TFA) is considered the most ideal fluoroalkylation reagent due to its low cost and easy availability. However, the extremely high oxidation potential requirement of TFA limits its wide application.

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ER-phagy, a selective form of autophagic degradation of endoplasmic reticulum (ER) fragments, plays an essential role in governing ER homeostasis. Dysregulation of ER-phagy is associated with the unfolded protein response (UPR), which is a major clue for evoking inflammatory diseases. However, the molecular mechanism underpinning the connection between ER-phagy and disease remains poorly defined.

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This article presents two innovative matrix neurodynamic approaches (MNAs) designed to tackle the rank minimization problem. First, by introducing the matrix norm-normalized sign function, two variants of MNA are developed: finite-time converging MNA (FIN -MNA) and fixed-time converging MNA (FIX -MNA). Then, the proposed approaches are shown to guarantee the existence and uniqueness of solutions, and based on Lyapunov analysis, it is demonstrated that the proposed approaches converge to the optimal solution within FIN and FIX .

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Presented herein is an atom- and step-economical method enabling the precise assembly of a heptacyclic scaffold containing both azocine and indoline units through the cascade reactions of indolin-1-yl(aryl)methanimines with diazo indanediones. The formation of products involves C-H bond activation and double carbene insertion followed by intramolecular condensation, retro-[2 + 2] cycloaddition, and recyclization. This cascade reaction not only provided a concise and straightforward strategy for the synthesis of the otherwise difficult to obtain heptacyclic compounds from readily available substrates but also disclosed an unprecedented reaction mode for indoline derivatives and diazo compounds.

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Chirality-controlled synthesis of carbon nanotubes (CNTs) is one of the ultimate goals in the field of nanotube synthesis. At present, direct synthesis achieving a purity of over 90%, which can be called single-chirality synthesis, has been achieved for only two types of chiralities: (14,4) and (12,6) CNTs. Here, we realized an ultrahigh-purity (∼95.

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This article presents a novel proximal gradient neurodynamic network (PGNN) for solving composite optimization problems (COPs). The proposed PGNN with time-varying coefficients can be flexibly chosen to accelerate the network convergence. Based on PGNN and sliding mode control technique, the proposed time-varying fixed-time proximal gradient neurodynamic network (TVFxPGNN) has fixed-time stability and a settling time independent of the initial value.

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Article Synopsis
  • * Researchers used a dataset of 3,080 patients and manually annotated 394 reports to establish a gold standard for training various transformer models, such as BERT and RoBERTa, for better accuracy in identifying and linking nodule characteristics.
  • * The results showed that the RoBERTa-mimic model excelled in nodule concept extraction with a score of 0.9279, while ALBERT-base and GatorTron were effective in linking characteristics, achieving a score of 0.9737;
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The rapid advancement of artificial intelligence (AI) in the 21st century is driving profound societal changes and playing a crucial role in optimizing energy systems to achieve carbon neutrality. Most G20 nations have developed national AI strategies and are advancing AI applications in energy, manufacturing, and agriculture sectors to meet this goal. However, disparities exist among these nations, creating an "AI divide" that needs to be addressed for regulatory consistency and fair distribution of AI benefits.

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Introduction: Alzheimer's disease (AD) is often misclassified in electronic health records (EHRs) when relying solely on diagnosis codes. This study aimed to develop a more accurate, computable phenotype (CP) for identifying AD patients using structured and unstructured EHR data.

Methods: We used EHRs from the University of Florida Health (UFHealth) system and created rule-based CPs iteratively through manual chart reviews.

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The air fryer utilizes heated air rather than hot oil to achieve frying, eliminating the need for cooking oil, rendering it a healthier cooking method than traditional frying and baking. However, there is limited evidence supporting that the air fryer could effectively reduce the level of food-derived carcinogen. In this study, we compared the concentration of Benzo[a]pyrene (BaP), a typical carcinogen, in beef patties cooked using an air fryer and an oven, under different cooking conditions, including temperatures (140 °C, 160 °C, 180 °C, and 200 °C), times (9, 14, and 19 min), and oil added or not.

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κ-Carrageenan (CG) was employed to mask the bitterness induced by 50% KCl in surimi gels to achieve salt reduction and gel performance improvement. The combination of KCl and CG (KCl + CG) yielded the increased textural characteristics and water-holding capacity (WHC) of surimi gels and facilitated the transition of free water to immobilized water. In addition, the KCl + CG supplement increased the turbidity and particle size of myofibrillar protein (MP) sols but decreased the surface hydrophobicity in a dose-dependent manner.

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Metals exhibit nonequilibrium electron and lattice subsystems at transient times following femtosecond laser excitation. In the past four decades, various optical spectroscopy and time-resolved diffraction methods have been used to study electron-phonon coupling and the effects of underlying dynamical processes. Here, we take advantage of the surface specificity of reflection ultrafast electron diffraction (UED) to examine the structural dynamics of photoexcited metal surfaces, which are apparently slower in recovery than predicted by thermal diffusion from the profile of absorbed energy.

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Background: Mutations in metabolic enzymes and co-administration of drugs may affect the blood concentration of pirfenidone effective in pulmonary fibrosis. To provide a basis for the precise clinical use of pirfenidone, the authors analyzed the correlation between steady-state pirfenidone trough concentration and adverse drug reactions (ADRs) and examined the impact of CYP1A2*1C (rs2069514) and *1F (rs762551) variants and co-administration on pirfenidone blood concentrations and ADRs.

Methods: Forty-four patients were enrolled.

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Objectives: Racial disparities in kidney transplant access and posttransplant outcomes exist between non-Hispanic Black (NHB) and non-Hispanic White (NHW) patients in the United States, with the site of care being a key contributor. Using multi-site data to examine the effect of site of care on racial disparities, the key challenge is the dilemma in sharing patient-level data due to regulations for protecting patients' privacy.

Materials And Methods: We developed a federated learning framework, named dGEM-disparity (decentralized algorithm for Generalized linear mixed Effect Model for disparity quantification).

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This study investigates the impact of clinical trial eligibility criteria on patient survival and serious adverse events (SAEs) in colorectal cancer (CRC) drug trials using real-world data. We utilized the OneFlorida+ network's data repository, conducting a retrospective analysis of CRC patients receiving FDA-approved first-line metastatic treatments. Propensity score matching created balanced case-control groups, which were evaluated using survival analysis and machine learning algorithms to assess the effects of eligibility criteria.

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Background: Anxiety and depression are common comorbidities in idiopathic pulmonary fibrosis (IPF) that impair health-related quality of life. However, there is a lack of studies focusing on the mental disorder of IPF after antifibrotic treatment and their related predictive factors.

Methods: Patients with an initial diagnosis of IPF were enrolled.

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Background: Electronic health records (EHRs) are digital records of individual health information. However, their adoption and utilization remain low. This study explores the factors influencing the implementation of EHRs through a questionnaire survey to enhance individual awareness and adoption of EHRs.

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Previous studies have revealed tight metabolic complementarity between bivalves and their endosymbiotic chemosynthetic bacteria, but little is known about their interactions with ectosymbionts. Our analysis of the ectosymbiosis between a deep-sea scallop (Catillopecten margaritatus) and a gammaproteobacterium showed that bivalves could be highly interdependent with their ectosymbionts as well. Our microscopic observation revealed abundant sulfur-oxidizing bacteria (SOB) on the surfaces of the gill epithelial cells.

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Revived attention in black phosphorus (bP) has been tremendous in the past decade. While many photoinitiated experiments have been conducted, a cross-examination of bP's photocarrier and structural dynamics is still lacking. In this article, we provide such analysis by examining time-resolved data acquired using optical transient reflectivity and reflection ultrafast electron diffraction, two complementary methods under the same experimental conditions.

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