Publications by authors named "Jingzhi Yu"

Article Synopsis
  • The study introduces a new technique for early detection of non-small-cell lung cancer (NSCLC) using metal-peptide complexes that enhance water splitting for better diagnostic signals.
  • It employs a peptide molecular probe that targets the epidermal growth factor receptor (EGFR) and interacts with copper ions to form stable complexes that amplify electrochemical signals.
  • Validated with clinical tissue samples, this method outperforms traditional detection methods in sensitivity and specificity, offering a promising approach for accurate NSCLC diagnosis.
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The clinical use of doxorubicin has been severely limited by doxorubicin-induced cardiotoxicity (DIC). Its mechanism is extremely complex and involves reactive oxygen species overgeneration, DNA damage, and aberrant inflammatory activity, which also involves multi-regulatory cell death mechanisms, including apoptosis, autophagy, and pyroptosis. These mechanisms overlap and crosstalk, resulting in the poor intervention of DIC injury.

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Proteases play a crucial role in industrial enzyme formulations, with activity fluctuations significantly impacting product quality and yield. Therefore, developing a method for precise and rapid detection of protease activity is paramount. This study aimed to develop a rapid and accurate method for quantifying trypsin activity using integrated infrared (IR) and ultraviolet (UV) spectroscopy combined with data fusion techniques.

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γ-aminobutyric acid (GABA) plays an important role in anti-anxiety by inhibiting neurotransmitter in the central nervous system (CNS) of mammals, which is generated in the germinating seeds. The key enzymes activity of GABA metabolism pathway and nutrients content in hemp seeds during germination were studied after treated with ultrasound and CaCl. The mechanism of exogenous stress on key enzymes in GABA metabolism pathway was investigated by molecular dynamics simulation.

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Background: Ferroptosis, a form of regulated cell death (RCD) that relies on excessive reactive oxygen species (ROS) generation, Feaccumulation, abnormal lipid metabolism and is involved in various organ ischemia/reperfusion (I/R) injury, expecially in myocardium. Mitochondria are the powerhouses of eukaryotic cells and essential in regulating multiple RCD. However, the links between mitochondria and ferroptosis are still poorly understood.

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Background: Systemic lupus erythematosus (SLE) is a rare autoimmune disorder characterized by an unpredictable course of flares and remission with diverse manifestations. Lupus nephritis, one of the major disease manifestations of SLE for organ damage and mortality, is a key component of lupus classification criteria. Accurately identifying lupus nephritis in electronic health records (EHRs) would therefore benefit large cohort observational studies and clinical trials where characterization of the patient population is critical for recruitment, study design, and analysis.

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Doxorubicin-induced cardiotoxicity (DIC) adversely impacts patients' long-term health and quality of life. Its underlying mechanism is complex, involving regulatory cell death mechanisms, such as ferroptosis and autophagy. Moreover, it is a challenge faced by patients undergoing cardiac rehabilitation.

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Article Synopsis
  • Longitudinal risk factor levels and patterns may provide better insights into atherosclerotic cardiovascular disease (ASCVD) risk than single, cross-sectional measures used in current clinical assessments.
  • The study compared the traditional Pooled Cohort Equations (PCE) with a deep learning model called Dynamic-DeepHit, analyzing data from over 15,000 participants over 8 years to assess the effectiveness of each model in predicting ASCVD risk.
  • Results showed that the deep learning model outperformed the PCE in terms of both prediction accuracy (AUROC score) and reliability (Brier score), suggesting that incorporating longitudinal data can enhance ASCVD risk prediction.
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Objective: Changes in cardiovascular health (CVH) during the life course are associated with future cardiovascular disease (CVD). Longitudinal clustering analysis using subgraph augmented non-negative matrix factorization (SANMF) could create phenotypic risk profiles of clustered CVH metrics.

Materials And Methods: Life's Essential 8 (LE8) variables, demographics, and CVD events were queried over 15 ears in 5060 CARDIA participants with 18 years of subsequent follow-up.

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Objectives: Advances in artificial intelligence (AI) technology have increased the feasibility of classifying voice disorders using voice recordings as a screening tool. This work develops upon previous models that take in single vowel recordings by analyzing multiple vowel recordings simultaneously to enhance prediction of vocal pathology.

Methods: Voice samples from the Saarbruecken Voice Database, including three sustained vowels (/a/, /i/, /u/) from 687 healthy human participants and 334 dysphonic patients, were used to train 1-dimensional convolutional neural network models for multiclass classification of healthy, hyperfunctional dysphonia, and laryngitis voice recordings.

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Article Synopsis
  • Traditional risk assessment for atherosclerotic cardiovascular disease (ASCVD) typically relies on single, cross-sectional risk factor measurements, but continuous monitoring of these factors over time may provide better insights into a patient's risk.
  • A study involving 15,565 participants found that a deep learning model that uses 8 years of longitudinal risk factor data outperformed the existing Pooled Cohort Equations (PCE) in predicting ASCVD risk, demonstrating improved accuracy and reclassification.
  • The results suggest that integrating longitudinal data into ASCVD risk prediction models enhances their effectiveness, paving the way for better preventive care strategies.
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Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in clinical practice and has a well-established association with coronary artery bypass graft (CABG) surgery. Being able to predict post-operative AF (POAF) may improve surgical outcomes. This study retrospectively assembled a large cohort of 3,807 first-time CABG patients with no prior AF to study factors that contribute to occurrence of POAF, in addition to testing models that may predict its incidence.

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Interventions for blood pressure (BP) control have positive effects on outcomes for patients with hypertension. Research on these effects in small- and medium-sized practices is limited. Our retrospective analysis used data from Healthy Hearts in the Heartland (H3), a research program conducted in 2016-2018 as part of the Agency for Healthcare Research and Quality's EvidenceNOW initiative, to examine the impact of implementing more interventions for BP control in these settings.

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Background: The Pooled Cohort Equations (PCEs) are race- and sex-specific Cox proportional hazards (PH)-based models used for 10-year atherosclerotic cardiovascular disease (ASCVD) risk prediction with acceptable discrimination. In recent years, neural network models have gained increasing popularity with their success in image recognition and text classification. Various survival neural network models have been proposed by combining survival analysis and neural network architecture to take advantage of the strengths from both.

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Chronic kidney disease (CKD) is a common complication of type 2 diabetes mellitus (T2DM). Approximately-one-third of patients with T2DM also have CKD. In clinical trial studies, several anti-diabetic medications (ADM) show evidence of preventing the progression of CKD.

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Sodium-glucose cotransporter-2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP1-RAs) reduce cardiovascular events and mortality in patients with type 2 diabetes mellitus (T2DM). We sought to describe trends in prescribing for SGLT2is and GLP1-RAs in diverse care settings, including (1) the outpatient clinics of a midwestern integrated health system and (2) small- and medium-sized community-based primary care practices and health centers in 3 midwestern states. We included adults with T2DM and ≥1 outpatient clinic visit.

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Despite the important role avoidable emergency department (ED) visits play in healthcare costs and quality of care, there has been little work in development of predictive models to identify patients likely to present with an avoidable ED visit. We use a conservative definition of 'avoidable' ED visits defined as visits that do not require diagnostic or screening services, procedures, or medications, and were discharged home to classify visits as avoidable. Models trained using data from emergency departments across the US yielded a training AUC of 0.

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Introduction: Currently, one of the commonly used methods for disseminating electronic health record (EHR)-based phenotype algorithms is providing a narrative description of the algorithm logic, often accompanied by flowcharts. A challenge with this mode of dissemination is the potential for under-specification in the algorithm definition, which leads to ambiguity and vagueness.

Methods: This study examines incidents of under-specification that occurred during the implementation of 34 narrative phenotyping algorithms in the electronic Medical Record and Genomics (eMERGE) network.

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Background: Small-sized primary care practices, defined as practices with fewer than 10 clinicians, delivered the majority of outpatient visits in the USA. Statin therapy in high-risk individuals reduces atherosclerotic cardiovascular disease (ASCVD) events, but prescribing patterns in small primary care practices are not well known. This study describes statin treatment patterns in small-sized primary care practices and examines patient- and practice-level factors associated with lack of statin treatment.

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Visually guided regulation is a sophisticated and active process, whereby sensory input helps to shape ocular development. Here, we sought to investigate the potential involvement of SorCS1, an important protein in synaptic transmission in neuron, in retinal development. A form-deprivation (FD) rat model was established.

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Purpose: Tetramethylpyrazine (TMP) is the active ingredient extracted from the Chinese herb Chuanxiong. The purpose of our study was to identify the mechanism of therapeutic TMP suppression of pathologic chemokine receptor 4 (CXCR4) transcription.

Methods: C57BL/6J mice with alkali-burned corneas were treated with either TMP eye drops (1.

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Cobalt chloride (CoCl) has long been accepted as a suitable in vitro hypoxia-mimetic agent. The gene CXCR4, which encodes a chemokine receptor, plays a key role in hypoxic retinal disease. Here, we investigated the mRNA and protein expression of CXCR4 in WERI-Rb1 retinoblastoma cells and human umbilical vein endothelial cells (HUVECs) under CoCl-induced hypoxic conditions, by means of real-time PCR and western blot.

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We have studied the electronic structures of icosahedral Ti(N) clusters (N=13, 19, 43, and 55) by using a real-space first-principles cluster method with generalized gradient approximation for exchange-correlation potential. The hexagonal close-packed and fcc close-packed clusters have been studied additionally for comparisons. It is found that the icosahedral structures are the most stable ones except for Ti(43), where fcc close-packed structure is favorable in energy.

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