Pioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System-Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study.

Background: The rising prevalence and swift spread of multidrug-resistant gram-negative bacteria (MDR-GNB), especially Klebsiella pneumoniae (KP), present a critical global health threat highlighted by the World Health Organization, with mortality rates soaring approximately 50% with inappropriate antimicrobial treatment.

Objective: This study aims to advance a novel strategy to develop an artificial intelligence-clinical decision support system (AI-CDSS) that combines machine learning (ML) with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), aiming to significantly improve the accuracy and speed of diagnosing antibiotic resistance, directly addressing the grave health risks posed by the widespread dissemination of pan drug-resistant gram-negative bacteria across numerous countries.

Methods: A comprehensive dataset comprising 165,299 bacterial specimens and 11,996 KP isolates was meticulously analyzed using MALDI-TOF MS technology.

Artificial intelligence-clinical decision support system for enhanced infectious disease management: Accelerating ceftazidime-avibactam resistance detection in Klebsiella pneumoniae.

Background: Effective and rapid diagnostic strategies are required to manage antibiotic resistance in Klebsiella pneumonia (KP). This study aimed to design an artificial intelligence-clinical decision support system (AI-CDSS) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and machine learning for the rapid detection of ceftazidime-avibactam (CZA) resistance in KP to improve clinical decision-making processes.

Methods: Out of 107,721 bacterial samples, 675 specimens of KP with suspected multi-drug resistance were selected.

An Advanced Machine Learning Model for a Web-Based Artificial Intelligence-Based Clinical Decision Support System Application: Model Development and Validation Study.

Background: Breast cancer is a leading global health concern, necessitating advancements in recurrence prediction and management. The development of an artificial intelligence (AI)-based clinical decision support system (AI-CDSS) using ChatGPT addresses this need with the aim of enhancing both prediction accuracy and user accessibility.

Objective: This study aims to develop and validate an advanced machine learning model for a web-based AI-CDSS application, leveraging the question-and-answer guidance capabilities of ChatGPT to enhance data preprocessing and model development, thereby improving the prediction of breast cancer recurrence.

Recurrent Occupational Hantavirus Infections Linked to Feeder Rodent Breeding Farm, Taiwan, 2022.

We investigated 2 acute cases and 1 previous case of Seoul hantavirus infection in workers in a feeder rodent breeding farm in Taiwan. Prevalence of hantavirus IgG among the tested feeder rats was 37.5%.

Artificial Intelligence-Clinical Decision Support System in Infectious Disease Control: Combatting Multidrug-Resistant with Machine Learning.

Purpose: The World Health Organization has identified (KP) as a significant threat to global public health. The rising threat of carbapenem-resistant (CRKP) leads to prolonged hospital stays and higher medical costs, necessitating faster diagnostic methods. Traditional antibiotic susceptibility testing (AST) methods demand at least 4 days, requiring 3 days on average for culturing and isolating the bacteria and identifying the species using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), plus an extra day for interpreting AST results.

Innovative strategies against superbugs: Developing an AI-CDSS for precise Stenotrophomonas maltophilia treatment.

Objectives: The World Health Organization named Stenotrophomonas maltophilia (SM) a critical multi-drug resistant threat, necessitating rapid diagnostic strategies. Traditional culturing methods require up to 96 h, including 72 h for bacterial growth, identification with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) through protein profile analysis, and 24 h for antibiotic susceptibility testing. In this study, we aimed at developing an artificial intelligence-clinical decision support system (AI-CDSS) by integrating MALDI-TOF MS and machine learning to quickly identify levofloxacin and trimethoprim/sulfamethoxazole resistance in SM, optimizing treatment decisions.

Monitoring coronavirus disease progression and clinical impact through quantitative viral load testing.

Background: The viral load (VL) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals is critical for improving clinical treatment strategies, care, and decisions. Several studies have reported that the initial SARS-CoV-2 VL is associated with disease severity and mortality. Cycle threshold (Ct) values and/or copies/mL are often used to quantify VL.

Host-Pathogen Interactions in Urinary Tract Infections: Investigating Genetic Risk Factors in the Taiwanese Population.

Background: () urinary tract infections pose a significant challenge in Taiwan. The significance of this issue arises because of the growing concerns about the antibiotic resistance of . Therefore, this study aimed to uncover potential genomic risk factors in Taiwanese patients with urinary tract infections through genome-wide association studies (GWAS).

Clinical Evaluation of Direct Reverse Transcription PCR for Detection of SARS-CoV-2 Compared to Conventional RT-PCR in Patients with Positive Rapid Antigen Test Results during Circulation of Emerging Viral Variants.

The emergence of the Omicron (B.1.1.

Spatiotemporal signaling underlies progressive vascular rarefaction in myocardial infarction.

Therapeutic angiogenesis represents a promising avenue to revascularize the ischemic heart. Its limited success is partly due to our poor understanding of the cardiac stroma, specifically mural cells, and their response to ischemic injury. Here, we combine single-cell and positional transcriptomics to assess the behavior of mural cells within the healing heart.

DPPIV fibro-adipogenic progenitors form the niche of adult skeletal muscle self-renewing resident macrophages.

Adult tissue-resident macrophages (RMs) are either maintained by blood monocytes or through self-renewal. While the presence of a nurturing niche is likely crucial to support the survival and function of self-renewing RMs, evidence regarding its nature is limited. Here, we identify fibro-adipogenic progenitors (FAPs) as the main source of colony-stimulating factor 1 (CSF1) in resting skeletal muscle.

Computed Tomography-Defined Sarcopenia in Outcomes of Patients with Unresectable Hepatocellular Carcinoma Undergoing Radioembolization: Assessment with Total Abdominal, Psoas, and Paraspinal Muscles.

Introduction: Sarcopenia is an adverse prognostic factor in patients with liver cirrhosis and hepatocellular carcinoma (HCC). Image-based sarcopenia assessment allows a standardized method to assess abdominal skeletal muscle. However, which is an index muscle for sarcopenia remains unclear.

Accelerating pandemic response with the emergency Omicron RT-PCR test: A comprehensive solution for COVID-19 diagnosis and tracking.

The Omicron variant of concern (VOC) has surged in many countries and replaced the previously reported VOC. To identify different Omicron strains/sublineages on a rapid, convenient, and precise platform, we report a novel multiplex real-time reverse transcriptase polymerase chain reaction (RT-PCR) method in one tube based on the Omicron lineage sequence variants' information. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) subvariants were used in a PCR-based assay for rapid identification of Omicron sublineage genotyping in 1000 clinical samples.

Comparison of thermal alkaline pretreatment and zinc acetate-catalyzed methanolysis (MtOH-ZnOAc) for anaerobic digestion of bioplastic waste.

The aim of this work was to study the effect of thermal alkaline pretreatment and zinc acetate-catalyzed methanolysis (MtOH-ZnOAc) in biogas production from bioplastic in anaerobic digestion. The pretreated bioplastic with MtOH-ZnOAc performs efficient solubilization and produced 205.7 ± 6.

Activation of β-catenin in mesenchymal progenitors leads to muscle mass loss.

Loss of muscle mass is a common manifestation of chronic disease. We find the canonical Wnt pathway to be activated in mesenchymal progenitors (MPs) from cancer-induced cachectic mouse muscle. Next, we induce β-catenin transcriptional activity in murine MPs.

Spatial compartmentalization of signaling imparts source-specific functions on secreted factors.

Efficient regeneration requires multiple cell types acting in coordination. To better understand the intercellular networks involved and how they change when regeneration fails, we profile the transcriptome of hematopoietic, stromal, myogenic, and endothelial cells over 14 days following acute muscle damage. We generate a time-resolved computational model of interactions and identify VEGFA-driven endothelial engagement as a key differentiating feature in models of successful and failed regeneration.

Monitoring algorithm of hospitalized patients in a medical center with SARS-CoV-2 (Omicron variant) infection: clinical epidemiological surveillance and immunological assessment.

Purpose: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major healthcare threat worldwide. Since it was first identified in November 2021, the Omicron (B.1.

The application of a novel 5-in-1 multiplex reverse transcriptase-polymerase chain reaction assay for rapid detection of SARS-CoV-2 and differentiation between variants of concern.

Objectives: We have established a novel 5-in-1 VOC assay to rapidly detect SARS-CoV-2 and immediately distinguish whether positive samples represent variants of concern (VOCs).

Methods: This assay could distinguish among five VOCs: Alpha, Beta, Gamma, Delta, and Omicron, in a single reaction tube. The five variants exhibit different single nucleotide polymorphisms (SNPs) in their viral genome, which can be used to distinguish them.

TNFα and IFNγ cooperate for efficient pro- to anti-inflammatory transition of macrophages during muscle regeneration.

IFNγ is traditionally known as a proinflammatory cytokine with diverse roles in antimicrobial and antitumor immunity. Yet, findings regarding its sources and functions during the regeneration process following a sterile injury are conflicting. Here, we show that natural killer (NK) cells are the main source of IFNγ in regenerating muscle.

Critical pediatric neurological illness associated with COVID-19 (Omicron BA.2.3.7 variant) infection in Taiwan: immunological assessment and viral genome analysis in tertiary medical center.

Objectives: Since April 2022, another wave of the Omicron epidemic has struck Taiwanese society, and children with severe neurological complications have been reported frequently. A few cases even developed acute fulminant encephalitis. To investigate the possible causes of the increased incidence of such complications in Taiwan, we reviewed several cases of pediatric patients with severe neurological symptoms.

Metabolic reprogramming of skeletal muscle by resident macrophages points to CSF1R inhibitors as muscular dystrophy therapeutics.

The role of tissue-resident macrophages during tissue regeneration or fibrosis is not well understood, mainly due to the lack of a specific marker for their identification. Here, we identified three populations of skeletal muscle-resident myelomonocytic cells: a population of macrophages positive for lymphatic vessel endothelial receptor 1 (LYVE1) and T cell membrane protein 4 (TIM4 or TIMD4), a population of LYVE1TIM4 macrophages, and a population of cells likely representing dendritic cells that were positive for CD11C and major histocompatibility complex class II (MHCII). Using a combination of parabiosis and lineage-tracing experiments, we found that, at steady state, TIM4 macrophages were replenished from the blood, whereas TIM4 macrophages locally self-renewed [self-renewing resident macrophages (SRRMs)].

Emergency SARS-CoV-2 variants of concern: rapidly direct RT-qPCR detection without RNA extraction, clinical comparison, cost-effective, and high-throughput.

Since the late 2020, the evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern has been characterized by the emergence of spike protein mutations, and these variants have become dominant worldwide. The gold standard SARS-CoV-2 diagnosis protocol requires two complex processes, namely, RNA extraction and real-time reverse transcriptase polymerase chain reaction (RT-PCR). There is a need for a faster, simpler, and more cost-effective detection strategy that can be utilized worldwide, especially in developing countries.

Clinical Comparative Evaluation of the LabTurbo AIO Reverse Transcription-Polymerase Chain Reaction and World Health Organization-Recommended Assays for the Detection of Emerging SARS-CoV-2 Variants of Concern.

Purpose: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent behind coronavirus disease-2019 (COVID-19). Single-plex reverse transcription-polymerase chain reaction (RT-PCR)-based assays are widely used for COVID-19 detection but exhibit decreased sensitivity and specificity in detecting the rapidly spreading SARS-CoV-2 variants; in contrast, multiplex RT-PCR reportedly yields better results. Here, we aimed at comparatively analyzing the clinical performance of the LabTurbo AIO COVID-19 RNA testing kit, a multiplex quantitative RT-PCR kit, including a three-target (, and ), single-reaction, triplex assay used for SARS-CoV-2 detection, with that of the WHO-recommended RT-PCR assay.

Emergency SARS-CoV-2 Variants of Concern: Novel Multiplex Real-Time RT-PCR Assay for Rapid Detection and Surveillance.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread worldwide. Many variants of SARS-CoV-2 have been reported, some of which have increased transmissibility and/or reduced susceptibility to vaccines. There is an urgent need for variant phenotyping for epidemiological surveillance of circulating lineages.