Epigenetic memory of coronavirus infection in innate immune cells and their progenitors.

Inflammation can trigger lasting phenotypes in immune and non-immune cells. Whether and how human infections and associated inflammation can form innate immune memory in hematopoietic stem and progenitor cells (HSPC) has remained unclear. We found that circulating HSPC, enriched from peripheral blood, captured the diversity of bone marrow HSPC, enabling investigation of their epigenomic reprogramming following coronavirus disease 2019 (COVID-19). Alterations in innate immune phenotypes and epigenetic programs of HSPC persisted for months to 1 year following severe COVID-19 and were associated with distinct transcription factor (TF) activities, altered regulation of inflammatory programs, and durable increases in myelopoiesis. HSPC epigenomic alterations were conveyed, through differentiation, to progeny innate immune cells. Early activity of IL-6 contributed to these persistent phenotypes in human COVID-19 and a mouse coronavirus infection model. Epigenetic reprogramming of HSPC may underlie altered immune function following infection and be broadly relevant, especially for millions of COVID-19 survivors.

Glycine decarboxylase activity drives non-small cell lung cancer tumor-initiating cells and tumorigenesis.

Identification of the factors critical to the tumor-initiating cell (TIC) state may open new avenues in cancer therapy. Here we show that the metabolic enzyme glycine decarboxylase (GLDC) is critical for TICs in non-small cell lung cancer (NSCLC). TICs from primary NSCLC tumors express high levels of the oncogenic stem cell factor LIN28B and GLDC, which are both required for TIC growth and tumorigenesis. Overexpression of GLDC and other glycine/serine enzymes, but not catalytically inactive GLDC, promotes cellular transformation and tumorigenesis. We found that GLDC induces dramatic changes in glycolysis and glycine/serine metabolism, leading to changes in pyrimidine metabolism to regulate cancer cell proliferation. In the clinic, aberrant activation of GLDC correlates with poorer survival in lung cancer patients, and aberrant GLDC expression is observed in multiple cancer types. This link between glycine metabolism and tumorigenesis may provide novel targets for advancing anticancer therapy.

Enantioselective Transformations in the Synthesis of Therapeutic Agents.

The proportion of approved chiral drugs and drug candidates under medical studies has surged dramatically over the past two decades. As a consequence, the efficient synthesis of enantiopure pharmaceuticals or their synthetic intermediates poses a profound challenge to medicinal and process chemists. The significant advancement in asymmetric catalysis has provided an effective and reliable solution to this challenge. The successful application of transition metal catalysis, organocatalysis, and biocatalysis to the medicinal and pharmaceutical industries has promoted drug discovery by efficient and precise preparation of enantio-enriched therapeutic agents, and facilitated the industrial production of active pharmaceutical ingredient in an economic and environmentally friendly fashion. The present review summarizes the most recent applications (2008-2022) of asymmetric catalysis in the pharmaceutical industry ranging from process scales to pilot and industrial levels. It also showcases the latest achievements and trends in the asymmetric synthesis of therapeutic agents with state of the art technologies of asymmetric catalysis.

Dynamic genomic changes in methotrexate-resistant human cancer cell lines beyond DHFR amplification suggest potential new targets for preventing drug resistance.

BACKGROUND: Although DHFR gene amplification has long been known as a major mechanism for methotrexate (MTX) resistance in cancer, the early changes and detailed development of the resistance are not yet fully understood. METHODS: We performed genomic, transcriptional and proteomic analyses of human colon cancer cells with sequentially increasing levels of MTX-resistance. RESULTS: The genomic amplification evolved in three phases (pre-amplification, homogenously staining region (HSR) and extrachromosomal DNA (ecDNA)). We confirm that genomic amplification and increased expression of DHFR, with formation of HSRs and especially ecDNAs, is the major driver of resistance. However, DHFR did not play a detectable role in the early phase. In the late phase (ecDNA), increase in FAM151B protein level may also have an important role by decreasing sensitivity to MTX. In addition, although MSH3 and ZFYVE16 may be subject to different posttranscriptional regulations and therefore protein expressions are decreased in ecDNA stages compared to HSR stages, they still play important roles in MTX resistance. CONCLUSION: The study provides a detailed evolutionary trajectory of MTX-resistance and identifies new targets, especially ecDNAs, which could help to prevent drug resistance. It also presents a proof-of-principal approach which could be applied to other cancer drug resistance studies.

Structural Antagonism-Aided Conformational Regulation Enables an Aptamer-Loop G-Quadruplex Modular Sensor of ß-Lactoglobulin.

A simple, reliable method for identifying ß-lactoglobulin (ß-LG) in dairy products is needed to protect those with ß-LG allergies. A common, practical strategy for target detection is designing simplified nucleic acid nanodevices by integrating functional components. This work presents a label-free modular ß-LG aptasensor consisting of an aptamer-loop G-quadruplex (G4), the working conformation of which is regulated by conformational antagonism to ensure respective module functionality and the related signal transduction. The polymorphic conformations of the module-fused sequence are systematically characterized, and the cause is revealed as shifting antagonistic equilibrium. Combined with conformational folding dynamics, this helped regulate functional conformations by fine-tuning the sequences. Furthermore, the principle of specific ß-LG detection by parallel G4 topology is examined as binding on the G4 aptamer loop by ß-LG to reinforce the G4 topology and fluorescence. Finally, a label-free, assembly-free, succinct, and turn-on fluorescent aptasensor is established, achieving excellent sensitivity across five orders of magnitude, rapidly detecting ß-LG within 22-min. This study provides a generalizable approach for the conformational regulation of module-fused G4 sequences and a reference model for creating simplified sensing devices for a variety of targets.

Perovskite photodetector-based laser absorption spectroscopy for gas detection.

A gas detection method based on CH3NH3PbI3 (MAPbI3) and poly (3,4-ethylenedioxythiophene): poly (4-styrene sulfonate) (PEDOT:PSS) composite photodetectors (PDs) is proposed. The operation of the PD primarily relies on the photoelectric effect within the visible light band. Our study involves constructing a gas detection system based on tunable diode laser spectroscopy (TDLAS) and MAPbI3/PEDOT:PSS PD, and O2 was selected as the target analyte. The system has achieved a minimum detection limit (MDL) of 0.12% and a normalized noise equivalent absorption coefficient (NNEA) of 8.83 × 10-11 cm-1⋅W⋅Hz-1/2. Furthermore, the Allan deviation analysis results indicate that the system can obtain sensitivity levels as low as 0.058% over an averaging time of 328 seconds. This marks the first use of MAPbI3/PEDOT:PSS PD in gas detection based on TDLAS. Despite the detector's performance leaves much to be desired, this innovation offers a new approach to developing spectral based gas detection system.

Induced Decomposition and Slip Interface Transformation of Oleic Acid Enables Ultralow Wear in Boundary Lubrication.

The tribological behavior of carboxylic acids, especially oleic acid, in boundary lubrication conditions is a subject of interest. This study presents the results of four-ball tribological tests conducted under varying contact pressures and sliding speeds. The findings reveal a critical turning speed within a confined zone, which causes a significant change in the frictional performances of oleic acid, leading to the formation of an ultralow wear tribofilm. This tribofilm, predominantly composed of oxyhydrogen compounds and hydrocarbons with more than five carbon atoms, is generated by the molecular action of oleic acid. Reactive nonequilibrium molecular dynamics simulations demonstrate that the shear speed-dependent decomposition modes of oleic acid and the transformation of the lubrication slip interface are the fundamental processes underlying the formation of this ultralow-wear boundary tribofilm.

ACOX1 deficiency-induced lipid metabolic disorder facilitates chronic interstitial fibrosis development in renal allografts.

Chronic interstitial fibrosis presents a significant challenge to the long-term survival of transplanted kidneys. Our research has shown that reduced expression of acyl-coenzyme A oxidase 1 (ACOX1), which is the rate-limiting enzyme in the peroxisomal fatty acid ß-oxidation pathway, contributes to the development of fibrosis in renal allografts. ACOX1 deficiency leads to lipid accumulation and excessive oxidation of polyunsaturated fatty acids (PUFAs), which mediate epithelial-mesenchymal transition (EMT) and extracellular matrix (ECM) reorganization respectively, thus causing fibrosis in renal allografts. Furthermore, activation of Toll-like receptor 4 (TLR4)-nuclear factor kappa-B (NF-κB) signaling induced ACOX1 downregulation in a DNA methyltransferase 1 (DNMT1)-dependent manner. Overconsumption of PUFA resulted in endoplasmic reticulum (ER) stress, which played a vital role in facilitating ECM reorganization. Supplementation with PUFAs contributed to delayed fibrosis in a rat model of renal transplantation. The study provides a novel therapeutic approach that can delay chronic interstitial fibrosis in renal allografts by targeting the disorder of lipid metabolism.

High-fidelity source mask optimization for suppressing line-end shortening.

Source mask optimization (SMO) is a widely used computational lithography technique for compensating lithographic distortion. However, line-end shortening is still a key factor that cannot be easily corrected and affects the image fidelity of lithography at advanced nodes. This paper proposes a source mask optimization method that suppresses line-end shortening and improves lithography fidelity. An adaptive hybrid weight method is employed to increase the weights of the line end during the optimization, which adaptively updates the weights in each iteration according to the edge placement error (EPE). A cost function containing a penalty term based on the normalized image log slope (NILS) is established to ensure the fidelity of the overall feature when paying more attention to the line-end region. The scope of this penalty term is regulated by widening and extending the split contour to further reduce the line-end shortening. Simulation results show that the proposed method can effectively suppress the line-end shortening and improve the lithography fidelity compared with the traditional SMO method.

Kaempferol Alleviates Hepatic Injury in Nonalcoholic Steatohepatitis (NASH) by Suppressing Neutrophil-Mediated NLRP3-ASC/TMS1-Caspase 3 Signaling.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a significant hepatic condition that has gained worldwide attention. Kaempferol (Kae), renowned for its diverse biological activities, including anti-inflammatory, antioxidant, anti-aging, and cardio-protective properties, has emerged as a potential therapeutic candidate for non-alcoholic steatohepatitis (NASH). Despite its promising therapeutic potential, the precise underlying mechanism of Kae's beneficial effects in NASH remains unclear. Therefore, this study aims to clarify the mechanism by conducting comprehensive in vivo and in vitro experiments. RESULTS: In this study, a murine model of non-alcoholic steatohepatitis (NASH) was established by feeding C57BL/6 female mice a high-fat diet for 12 weeks. Kaempferol (Kae) was investigated for its ability to modulate systemic inflammatory responses and lipid metabolism in this model (20 mg/kg per day). Notably, Kae significantly reduced the expression of NLRP3-ASC/TMS1-Caspase 3, a crucial mediator of liver tissue inflammation. Additionally, in a HepG2 cell model induced with palmitic acid/oleic acid (PA/OA) to mimic NASH conditions, Kae demonstrated the capacity to decrease lipid droplet accumulation and downregulate the expression of NLRP3-ASC/TMS1-Caspase 3 (20 µM and the final concentration to 20 nM). These findings suggest that Kae may hold therapeutic potential in the treatment of NASH by targeting inflammatory and metabolic pathways. CONCLUSIONS: These findings suggest that kaempferol holds potential as a promising therapeutic intervention for ameliorating non-alcoholic fatty liver disease (NAFLD).

Click-Chemistry-Mediated Cell Membrane Glycopolymer Engineering to Potentiate Dendritic Cell Vaccines.

Dendritic cell vaccine (DCV) holds great potential in tumor immunotherapy owing to its potent ability in eliciting tumor-specific immune responses. Aiming at engineering enhanced DCV, we report the first effort to construct a glycopolymer-engineered DC vaccine (G-DCV) via metabolicglycoengineering and copper-free click-chemistry. Model G-DCV was prepared by firstly delivering tumor antigens, ovalbumin (OVA) into dendritic cells (DC) with fluoroalkane-grafted polyethyleneimines, followed by conjugating glycopolymers with a terminal group of dibenzocyclooctyne (DBCO) onto dendritic cells. Compared to unmodified DCV, our G-DCV could induce stronger T cell activation due to the enhanced adhesion between DCs and T cells. Notably, such G-DCV could more effectively inhibit the growth of the mouse B16-OVA (expressing OVA antigen) tumor model after adoptive transfer. Moreover, by combination with an immune checkpoint inhibitor, G-DCV showed further increased anti-tumor effects in treating different tumor models. Thus, our work provides a novel strategy to enhance the therapeutic effectiveness of DC vaccines.

Metal-Free Atom Transfer Radical Polymerization to Prepare Recylable Micro-Adjuvants for Dendritic Cell Vaccine.

In the development of dendritic cell (DC) vaccines, the maturation of DCs is a critical stage. Adjuvants play a pivotal role in the maturation of DCs, with a major concern being to ensure both efficacy and safety. This study introduces an innovative approach that combines high efficacy with safety through the synthesis of micro-adjuvants grafted with copolymers of 2-(methacrylamido) glucopyranose (MAG) and methacryloxyethyl trimethyl ammonium chloride (DMC). The utilization of metal-free surface-initiated atom transfer radical polymerization enables the production of safe and recyclable adjuvants. These micrometer-sized adjuvants surpass the optimal size range for cellular endocytosis, enabling the retrieval and reuse of them during the ex vivo maturation process, mitigating potential toxicity concerns associated with the endocytosis of non-metabolized nanoparticles. Additionally, the adjuvants exhibit a "micro-ligand-mediated maturation enhancement" effect for DC maturation. This effect is influenced by the shape of the particle, as evidenced by the distinct promotion effects of rod-like and spherical micro-adjuvants with comparable sizes. Furthermore, the porous structure of the adjuvants enables them to function as cargo-carrying "micro-shuttles", releasing antigens upon binding to DCs to facilitate efficient antigen delivery.

AI Chatbots in Clinical Laboratory Medicine: Foundations and Trends.

BACKGROUND: Artificial intelligence (AI) conversational agents, or chatbots, are computer programs designed to simulate human conversations using natural language processing. They offer diverse functions and applications across an expanding range of healthcare domains. However, their roles in laboratory medicine remain unclear, as their accuracy, repeatability, and ability to interpret complex laboratory data have yet to be rigorously evaluated. CONTENT: This review provides an overview of the history of chatbots, two major chatbot development approaches, and their respective advantages and limitations. We discuss the capabilities and potential applications of chatbots in healthcare, focusing on the laboratory medicine field. Recent evaluations of chatbot performance are presented, with a special emphasis on large language models such as the Chat Generative Pre-trained Transformer in response to laboratory medicine questions across different categories, such as medical knowledge, laboratory operations, regulations, and interpretation of laboratory results as related to clinical context. We analyze the causes of chatbots' limitations and suggest research directions for developing more accurate, reliable, and manageable chatbots for applications in laboratory medicine. SUMMARY: Chatbots, which are rapidly evolving AI applications, hold tremendous potential to improve medical education, provide timely responses to clinical inquiries concerning laboratory tests, assist in interpreting laboratory results, and facilitate communication among patients, physicians, and laboratorians. Nevertheless, users should be vigilant of existing chatbots' limitations, such as misinformation, inconsistencies, and lack of human-like reasoning abilities. To be effectively used in laboratory medicine, chatbots must undergo extensive training on rigorously validated medical knowledge and be thoroughly evaluated against standard clinical practice.

Generalizability of a Machine Learning Model for Improving Utilization of Parathyroid Hormone-Related Peptide Testing across Multiple Clinical Centers.

BACKGROUND: Measuring parathyroid hormone-related peptide (PTHrP) helps diagnose the humoral hypercalcemia of malignancy, but is often ordered for patients with low pretest probability, resulting in poor test utilization. Manual review of results to identify inappropriate PTHrP orders is a cumbersome process. METHODS: Using a dataset of 1330 patients from a single institute, we developed a machine learning (ML) model to predict abnormal PTHrP results. We then evaluated the performance of the model on two external datasets. Different strategies (model transporting, retraining, rebuilding, and fine-tuning) were investigated to improve model generalizability. Maximum mean discrepancy (MMD) was adopted to quantify the shift of data distributions across different datasets. RESULTS: The model achieved an area under the receiver operating characteristic curve (AUROC) of 0.936, and a specificity of 0.842 at 0.900 sensitivity in the development cohort. Directly transporting this model to two external datasets resulted in a deterioration of AUROC to 0.838 and 0.737, with the latter having a larger MMD corresponding to a greater data shift compared to the original dataset. Model rebuilding using site-specific data improved AUROC to 0.891 and 0.837 on the two sites, respectively. When external data is insufficient for retraining, a fine-tuning strategy also improved model utility. CONCLUSIONS: ML offers promise to improve PTHrP test utilization while relieving the burden of manual review. Transporting a ready-made model to external datasets may lead to performance deterioration due to data distribution shift. Model retraining or rebuilding could improve generalizability when there are enough data, and model fine-tuning may be favorable when site-specific data is limited.

Effective multi-objective inverse lithography technology at full-field and full-chip levels with a hybrid dynamic priority algorithm.

Inverse lithography technology (ILT), such as source mask optimization (SMO), is used to improve lithography performance. Usually, a single objective cost function is selected in ILT, and an optimal structure for one field point is achieved. The optimal structure is not the case for other images at full field points where the aberrations of the lithography system are different, even in high-quality lithography tools. The optimal structure that must match the high-performance images at the full field is urgently required for extreme ultraviolet lithography (EUVL). In contrast, multi-objective optimization algorithms (MOAs) limit the application of multi-objective ILT. Assigning target priority is incomplete in current MOAs, which results in the over-optimization of some targets and under-optimization of others. In this study, multi-objective ILT and a hybrid dynamic priority (HDP) algorithm were investigated and developed. High-performance images with high fidelity and high uniformity were obtained at multi-field and multi-clip areas across the die. A hybrid criterion was developed for the completion and reasonable prioritization of each target to ensure sufficient improvement. Compared to the current MOAs, the uniformity of images at full-field points was improved by up to 31.1% by the HDP algorithm in the case of multi-field wavefront error-aware SMO. The multi-clip source optimization (SO) problem showed the universality of the HDP algorithm to deal with different ILT problems. It acquired higher imaging uniformity than existing MOAs, which indicated that the HDP is more qualified for multi-objective ILT optimization than existing MOAs.

Buildup of multiple spatiotemporal nonlinear dynamics in an all-fiber multimode laser.

Ultrafast lasers based on multimode fibers have attracted extensive attention owing to the large mode-field area and nonlinear tolerance. The high spatial degree of freedom of multimode fibers is significant for spatiotemporal pulses locked both in transverse and longitudinal modes, where the energy of output pulses can be remarkably improved. Herein, the 1.5-µm all-fiber spatiotemporal mode-locked laser was realized based on carbon nanotubes as a saturable absorber. Moreover, by tuning the polarization controller and the pump power carefully, the output wavelengths can be ranged from 1529 to 1565 nm based on the multimode interference filter. In addition, Q-switched mode-locking and spatiotemporal mode-locked dual combs were also observed by further adjusting the polarization controller. Such a kind of an all-fiber multimode laser offers a crucial insight into the spatiotemporal nonlinear dynamics, which is of great significance in scientific research and practical applications.

Inhibition of hyaluronic acid degradation pathway suppresses glioma progression by inducing apoptosis and cell cycle arrest.

BACKGROUND: Abnormal hyaluronic acid (HA) metabolism is a major factor in tumor progression, and the metabolic regulation of HA mainly includes HA biosynthesis and catabolism. In glioma, abnormal HA biosynthesis is intimately involved in glioma malignant biological properties and the formation of immunosuppressive microenvironment; however, the role of abnormal HA catabolism in glioma remains unclear. METHODS: HA catabolism is dependent on hyaluronidase. In TCGA and GEPIA databases, we found that among the 6 human hyaluronidases (HYAL1, HYAL2, HYAL3, HYAL4, HYALP1, SPAM1), only HYAL2 expression was highest in glioma. Next, TCGA and CGGA database were further used to explore the correlation of HYAL2 expression with glioma prognosis. Then, the mRNA expression and protein level of HYAL2 was determined by qRT-PCR, Western blot and Immunohistochemical staining in glioma cells and glioma tissues, respectively. The MTT, EdU and Colony formation assay were used to measure the effect of HYAL2 knockdown on glioma. The GSEA enrichment analysis was performed to explore the potential pathway regulated by HYAL2 in glioma, in addition, the HYAL2-regulated signaling pathways were detected by flow cytometry and Western blot. Finally, small molecule compounds targeting HYAL2 in glioma were screened by Cmap analysis. RESULTS: In the present study, we confirmed that Hyaluronidase 2 (HYAL2) is abnormally overexpressed in glioma. Moreover, we found that HYAL2 overexpression is associated with multiple glioma clinical traits and acts as a key indicator for glioma prognosis. Targeting HYAL2 could inhibit glioma progression by inducing glioma cell apoptosis and cell cycle arrest. CONCLUSION: Collectively, these observations suggest that HYAL2 overexpression could promote glioma progression. Thus, treatments that disrupt HA catabolism by altering HYAL2 expression may serve as effective strategies for glioma treatment.

Targeting copper death genotyping associated gene RARRES2 suppresses glioblastoma progression and macrophages infiltration.

BACKGROUND: Copper homeostasis is associated with malignant biological behavior in various tumors. The excessive accumulation of copper can induce tumor death, which is named cuproptosis, and it is also closely related to tumor progression and the formation of the immune microenvironment. However, the associations of cuproptosis with glioblastoma (GBM) prognosis and microenvironment construction are poorly understood. METHOD: First, TCGA and GEO (GSE83300, GSE74187) merged datasets were used to analyze the association of cuproptosis-related genes (CRGs) with GBM. Then, we performed cluster analysis of CRGs in GBM from the GEO (GSE83300, GSE74187) and TCGA merged datasets. Subsequently, the prognostic risk model was constructed by least absolute shrinkage and selection operator (LASSO) according to gene expression features in CRG clusters. Next, we performed a series of in-depth analyses, including tumor mutational burden (TMB) analysis, cluster analysis, and GBM IDH status prediction. Finally, RARRES2 was identified as a target gene for GBM treatment, especially IDH wild-type GBM. In addition, we further analyzed the correlation of CRG clusters and RARRES2 expression with the GBM immune microenvironment by ESTIMATE and CIBERSORT analyses. In vitro experiments were conducted to demonstrate that targeting RARRES2 inhibits glioblastoma progression and macrophage infiltration, particularly IDH wild-type GBM. RESULTS: In the present study, we demonstrated that the CRG cluster was closely related to GBM prognosis and immune cell infiltration. Moreover, the prognostic risk model constructed with the three genes (MMP19, G0S2, RARRES2) associated with the CRG clusters could well evaluate the prognosis and immune cell infiltration in GBM. Subsequently, after further analyzing the tumor mutational burden (TMB) in GBM, we confirmed that RARRES2 in the prognostic risk model could be used as a crucial gene signature to predict the prognosis, immune cell infiltration and IDH status of GBM patients. CONCLUSION: This study fully revealed the potential clinical impact of CRGs on GBM prognosis and the microenvironment, and determined the effect of the crucial gene (RARRES2) on the prognosis and tumor microenvironment construction of GBM, meanwhile, our study also revealed over-expressed RARRES2 is related to the IDH satus of GBM, which provides a novel strategy for the treatment of GBM, particularly IDH wild-type GBM.

Extension characteristics of TdT and its application in biosensors.

The advantages of rapid amplification of nucleic acid without a template based on terminal deoxyribonucleotidyl transferase (TdT) have been widely used in the field of biosensors. However, the catalytic efficiency of TdT is affected by extension conditions. The sensitivity of TdT- mediated biosensors can be improved only under appropriate conditions. Therefore, in this review, we provide a comprehensive overview of TdT extension characteristics and its applications in biosensors. We focus on the relationship between TdT extension conditions and extension efficiency. Furthermore, the construction strategy of TdT-mediated biosensors according to five different recognition types and their applications in targets are discussed and, finally, several current challenges and prospects in the field are taken into consideration.

Brief introduction to terminal deoxyribonucleotidyl transferase (TdT) characteristics.Provided a systematic and comprehensive summary of TdT extension conditions.Summarized the four effect factors of catalytic efficiency based on extension conditions and enzyme conformation.Sensing strategies of TdT-mediated biosensors for five different recognitions were summarized in detail.The applications of TdT-mediated biosensors in six targets were introduced in detail.

Improved Utilization of Serial Testing Without Increased Admissions after Implementation of High-Sensitivity Troponin I: a Controlled Retrospective Cohort Study.

BACKGROUND: Guidelines recommend high-sensitivity cardiac troponin (hs-cTn) for diagnosis of myocardial infarction. Use of hs-cTn is increasing across the U.S., but questions remain regarding clinical and operational impact. Prior studies have had methodologic limitations and yielded conflicting results. OBJECTIVE: To evaluate the impact of transitioning from conventional cardiac troponin (cTn) to hs-cTn on test and resource utilization, operational efficiency, and patient safety. DESIGN: Retrospective cohort study in two New York City hospitals during the months before and after transition from conventional cTn to hs-cTn at Hospital 1. Hospital 2 served as a control. PARTICIPANTS: Consecutive emergency department (ED) patients with at least one cTn test resulted. INTERVENTION: Multifaceted hs-cTn intervention bundle, including a 0/2-h diagnostic algorithm for non-ST-elevation myocardial infarction, an educational bundle, enhancements to the electronic medical record, and nursing interventions to facilitate timed sample collection. MAIN MEASURES: Primary outcomes included serial cTn test utilization, probability of hospital admission, ED length of stay (LOS), and among discharged patients, probability of ED revisit within 72 h resulting in hospital admission. Multivariable regression models adjusted for age, sex, temporal trends, and interhospital differences. KEY RESULTS: The intervention was associated with increased use of serial cTn testing (adjusted risk difference: 48 percentage points, 95% CI: 45-50, P < 0.001) and ED LOS (adjusted geometric mean difference: 50 min, 95% CI: 50-51, P < 0.001). There was no significant association between the intervention and probability of admission (adjusted relative risk [aRR]: 0.99, 95% CI: 0.89-1.1, P = 0.81) or probability of ED revisit within 72 h resulting in admission (aRR: 1.1, 95% CI: 0.44-2.9, P = 0.81). CONCLUSIONS: Implementation of a hs-cTn intervention bundle was associated with an improvement in serial cTn testing, a neutral effect on probability of hospital admission, and a modest increase in ED LOS.