Publications by authors named "Joyce Tay"

Biocatalysis using whole cell biotransformation presents an alternative approach to producing complex molecules when compared to traditional synthetic chemical processes. This method offers several advantages, including scalability, self-contained co-factor recycling systems, the use of cost-effective raw materials, and reduced purification costs. Notably, biotransformation using microbial consortia provides benefits over monocultures by enhancing biosynthesis efficiency and productivity through division of labor and a reduction in metabolic burden.

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Background: New-onset atrial fibrillation (AF) is associated with an increased risk of stroke in hospitalized patients with severe sepsis. Post-cardiac arrest patients experience conditions similar to sepsis. This study investigated whether pre-arrest AF is associated with poor neurological recovery following in-hospital cardiac arrest (IHCA).

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Article Synopsis
  • The study aimed to validate and compare statistical and machine learning models for predicting outcomes after out-of-hospital cardiac arrest, while also assessing the impact of COVID-19 on these predictions.
  • The analysis included 2,161 adult patients from 3 hospitals between 2015 and 2023, focusing on neurological outcomes at hospital discharge and comparing performance before and after 2020.
  • The Utstein-Based Return of Spontaneous Circulation score showed the best predictive performance (AUC 0.85), significantly outperforming other models, particularly after the onset of the COVID-19 pandemic.
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Background: During cardiopulmonary resuscitation (CPR), end-tidal carbon dioxide (EtCO) is primarily determined by pulmonary blood flow, thereby reflecting the blood flow generated by CPR. We aimed to develop an EtCO trajectory-based prediction model for prognostication at specific time points during CPR in patients with out-of-hospital cardiac arrest (OHCA).

Methods: We screened patients receiving CPR between 2015-2021 from a prospectively collected database of a tertiary-care medical center.

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Malposition of a nasogastric tube (NGT) can lead to severe complications. We aimed to develop a computer-aided detection (CAD) system to localize NGTs and detect NGT malposition on portable chest X-rays (CXRs). A total of 7378 portable CXRs were retrospectively retrieved from two hospitals between 2015 and 2020.

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Background: This study aimed to investigate the association between the temporal transitions in heart rhythms during cardiopulmonary resuscitation (CPR) and outcomes after out-of-hospital cardiac arrest.

Methods: This was an analysis of the prospectively collected databases in 3 academic hospitals in northern and central Taiwan. Adult patients with out-of-hospital cardiac arrest transported by emergency medical service between 2015 and 2022 were included.

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Background: The 2022 AHA/ACC/HFSA guidelines for the management of heart failure (HF) makes therapeutic recommendations based on HF status. We investigated whether the prognosis of in-hospital cardiac arrest (IHCA) could be stratified by HF stage and left ventricular ejection fraction (LVEF).

Methods: This single-center retrospective study analyzed the data of patients who experienced IHCA between 2005 and 2020.

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Article Synopsis
  • A deep learning algorithm was developed to detect pulmonary tuberculosis (PTB) from chest X-rays (CXRs) in emergency settings, using a large dataset of 3,498 images, including training and testing from various sources.
  • The algorithm, based on EfficientNetV2, showed high performance with an area under the ROC curve (AUC) of 0.878 for detecting PTB, especially excelling in posterior-anterior CXRs (AUC 0.940).
  • This algorithm's accurate detection capabilities could significantly reduce the time needed to identify and isolate PTB patients, potentially helping to prevent the spread of the disease.
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We aimed to develop machine learning (ML)-based algorithms to assist physicians in ultrasound-guided localization of cricoid cartilage (CC) and thyroid cartilage (TC) in cricothyroidotomy. Adult female volunteers were prospectively recruited from two hospitals between September and December, 2020. Ultrasonographic images were collected via a modified longitudinal technique.

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Article Synopsis
  • - The study focuses on using machine learning algorithms to better predict COVID-19 infections based on patient data from emergency departments (EDs), emphasizing the importance of timely diagnoses to control the disease spread
  • - Researchers developed and validated a predictive model using data from suspected COVID-19 patients at two different EDs: the first cohort from the US during the early pandemic and the second from a different country later on
  • - Three machine learning methods (random forest, gradient boosting, and extra trees classifiers) were tested for their effectiveness, with random forest showing the best performance in accurately identifying COVID-19 cases among patients in the testing cohort
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Objectives: We aimed to develop a computer-aided detection (CAD) system to localize and detect the malposition of endotracheal tubes (ETTs) on portable supine chest radiographs (CXRs).

Design: This was a retrospective diagnostic study. DeepLabv3+ with ResNeSt50 backbone and DenseNet121 served as the model architecture for segmentation and classification tasks, respectively.

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Article Synopsis
  • - The study aims to create two deep learning systems to diagnose and locate pneumothorax using portable chest X-rays taken while patients are lying down.
  • - Researchers used a large dataset of images from emergency and intensive care settings, splitting them into training and testing groups, and employed advanced AI models for both detection and segmentation tasks.
  • - Both systems demonstrated high performance in diagnosing pneumothorax, outperforming human experts in many instances, despite a drop in accuracy with smaller pneumothorax sizes, suggesting strong potential for broader clinical use.
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, the world's most common chronic infection-causing pathogen, is responsible for causing gastric ulcers, the fourth-leading cause of cancer-related death globally in 2020. In recent years, the effectiveness of the current treatment regimen (two antibiotics and one proton pump inhibitor) has often been plagued with problems such as resistance and the undesired elimination of commensal bacteria. Herein, we report the synthesis of block and random copolycarbonates, functionalized with cationic guanidinium and anionic acetate functional groups, aimed at selectively killing in the acidic environment of the stomach, while remaining nontoxic to the commensal bacteria in the gut.

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Article Synopsis
  • The RACA score is a model used to predict the likelihood of "return of spontaneous circulation" (ROSC) in patients who experience out-of-hospital cardiac arrest (OHCA), incorporating factors such as age, gender, arrest cause, and more.
  • The study aimed to enhance the RACA score by including end-tidal carbon dioxide (EtCO) measurements during CPR, creating the EtCO + RACA score to better estimate ROSC for patients taken to the emergency department.
  • Data from 530 patients were analyzed, finding that the EtCO + RACA score showed strong predictive ability for ROSC, demonstrating better performance compared to the traditional RACA score.
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Background: Mass casualties caused by natural disasters and man-made events may overwhelm local emergency medical services and healthcare systems. Logistics is essential to a successful emergency medical response. Drills have been used in disaster preparedness to validate plans, policies, procedures, and agreements, and identify resource gaps.

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Anticancer drug resistance is a large contributing factor to the global mortality rate of cancer patients. Anticancer macromolecules such as polymers have been recently reported to overcome this issue. Anticancer macromolecules have unselective toxicity because they are highly positively charged.

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Background: We aimed to identify distinct trajectories of end-tidal carbon dioxide (EtCO) during cardiopulmonary resuscitation in patients with out-of-hospital cardiac arrest (OHCA) and to investigate the association between EtCO trajectories and OHCA outcomes.

Methods: This was a secondary analysis of a prospectively collected database on adult patients with OHCA who had been resuscitated in the emergency department of a tertiary medical center between 2015 and 2020. The primary outcome was the return of spontaneous circulation (ROSC).

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Cationic synthetic anticancer polymers and peptides have attracted increasing attention for advancing cancer treatment without causing drug resistance development. To circumvent in vivo instability and toxicity caused by cationic charges of the anticancer polymers/peptides, we report, for the first time, a nanoparticulate delivery system self-assembled from a negatively charged pH-sensitive polypeptide poly(ethylene glycol)-b-poly(ʟ-lysine)-graft-cyclohexene-1,2-dicarboxylic anhydride and a cationic anticancer polypeptide guanidinium-functionalized poly(ʟ-lysine) (PLL-Gua) via electrostatic interaction. The formation of nanoparticles (Gua-NPs) neutralized the positive charges of PLL-Gua.

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Background: Little is known about pain trajectories in the emergency department (ED), which could inform the heterogeneous response to pain treatment. We aimed to identify clinically relevant subphenotypes of pain resolution in the ED and their relationships with clinical outcomes.

Methods: This retrospective cohort study used electronic clinical warehouse data from a tertiary medical center.

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As the human cost of the pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still being witnessed worldwide, the development of broad-spectrum antiviral agents against emerging and re-emerging viruses is seen as a necessity to hamper the spread of infections. Various targets during the viral life-cycle can be considered to inhibit viral infection, from viral attachment to viral fusion or replication. Macromolecules represent a particularly attractive class of therapeutics due to their multivalency and versatility.

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Use of traditional anticancer chemotherapeutics has been hindered by the multifactorial nature of multi-drug resistance (MDR) development and metastasis. Recently, cationic polycarbonates were reported as novel unconventional anticancer agents that mitigated MDR and inhibited metastasis. The aim of this study is to explore structure-anticancer activity relationship.

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This study aimed to investigate whether early surgical decompression was associated with favorable neurological recovery in patients with traumatic spinal cord injury (tSCI). We searched PubMed and Embase from the database inception through December 2020 and selected studies comparing the impact of early versus late surgical decompression on neurological recovery as assessed by American Spinal Injury Association Impairment Scale (AIS) for adult patients sustaining tSCI. We pooled the effect estimates in random-effects models and quantified the heterogeneity by the statistics.

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Background: Frontline health care workers, including physicians, are at high risk of contracting coronavirus disease (COVID-19) owing to their exposure to patients suspected of having COVID-19.

Objective: The aim of this study was to evaluate the benefits and feasibility of a double triage and telemedicine protocol in improving infection control in the emergency department (ED).

Methods: In this retrospective study, we recruited patients aged ≥20 years referred to the ED of the National Taiwan University Hospital between March 1 and April 30, 2020.

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Synthetic macromolecular antimicrobials have shown efficacy in the treatment of multidrug resistant (MDR) pathogens. These synthetic macromolecules, inspired by Nature's antimicrobial peptides (AMPs), mitigate resistance by disrupting microbial cell membrane or targeting multiple intracellular proteins or genes. Unlike AMPs, these polymers are less prone to degradation by proteases and are easier to synthesize on a large scale.

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The Notch receptor and its ligands are key components in a core metazoan signaling pathway that regulates the spatial patterning, timing and outcome of many cell-fate decisions. Ligands contain a disulfide-rich Delta/Serrate/LAG-2 (DSL) domain required for Notch trans-activation or cis-inhibition. Here we report the X-ray structure of a receptor binding region of a Notch ligand, the DSL-EGF3 domains of human Jagged-1 (J-1(DSL-EGF3)).

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