The origin of carbonate mud and implications for global climate.

Carbonate mud represents one of the most important geochemical archives for reconstructing ancient climatic, environmental, and evolutionary change from the rock record. Mud also represents a major sink in the global carbon cycle. Yet, there remains no consensus about how and where carbonate mud is formed. Here, we present stable isotope and trace-element data from carbonate constituents in the Bahamas, including ooids, corals, foraminifera, and algae. We use geochemical fingerprinting to demonstrate that carbonate mud cannot be sourced from the abrasion and mixture of any combination of these macroscopic grains. Instead, an inverse Bayesian mixing model requires the presence of an additional aragonite source. We posit that this source represents a direct seawater precipitate. We use geological and geochemical data to show that "whitings" are unlikely to be the dominant source of this precipitate and, instead, present a model for mud precipitation on the bank margins that can explain the geographical distribution, clumped-isotope thermometry, and stable isotope signature of carbonate mud. Next, we address the enigma of why mud and ooids are so abundant in the Bahamas, yet so rare in the rest of the world: Mediterranean outflow feeds the Bahamas with the most alkaline waters in the modern ocean (>99.7th-percentile). Such high alkalinity appears to be a prerequisite for the nonskeletal carbonate factory because, when Mediterranean outflow was reduced in the Miocene, Bahamian carbonate export ceased for 3-million-years. Finally, we show how shutting off and turning on the shallow carbonate factory can send ripples through the global climate system.

Development and clinical validation of a dual ddPCR assay for detecting carbapenem-resistant Acinetobacter baumannii in bloodstream infections.

Objective: Acinetobacter baumannii (A. baumannii, AB) represents a major species of Gram-negative bacteria involved in bloodstream infections (BSIs) and shows a high capability of developing antibiotic resistance. Especially, carbapenem-resistant Acinetobacter baumannii (CRAB) becomes more and more prevalent in BSIs. Hence, a rapid and sensitive CRAB detection method is of urgent need to reduce the morbidity and mortality due to CRAB-associated BSIs. Methods: A dual droplet digital PCR (ddPCR) reaction system was designed for detecting the antibiotic resistance gene OXA-23 and AB-specific gene gltA. Then, the specificity of the primers and probes, limit of detection (LOD), linear range, and accuracy of the assay were evaluated. Furthermore, the established assay approach was validated on 37 clinical isolates and compared with blood culture and drug sensitivity tests. Results: The dual ddPCR method established in this study demonstrated strong primer and probe specificity, distinguishing CRAB among 21 common clinical pathogens. The method showed excellent precision (3 × 10-4 ng/µL, CV < 25%) and linearity (OXA-23: y = 1.4558x + 4.0981, R2 = 0.9976; gltA: y = 1.2716x + 3.6092, R2 = 0.9949). While the dual qPCR LOD is 3 × 10-3 ng/µL, the dual ddPCR's LOD stands at 3 × 10-4 ng/µL, indicating a higher sensitivity in the latter. When applied to detect 35 patients with BSIs of AB, the results were consistent with clinical blood culture identification and drug sensitivity tests. Conclusion: The dual ddPCR detection method for OXA-23 and gltA developed in this study exhibits good specificity, excellent linearity, and a higher LOD than qPCR. It demonstrates reproducibility even for minute samples, making it suitable for rapid diagnosis and precision treatment of CRAB in BSIs.

Type I Interferon Pathway-Related Hub Genes as a Potential Therapeutic Target for SARS-CoV-2 Omicron Variant-Induced Symptoms.

BACKGROUND: The global pandemic of COVID-19 is caused by the rapidly evolving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The clinical presentation of SARS-CoV-2 Omicron variant infection varies from asymptomatic to severe disease with diverse symptoms. However, the underlying mechanisms responsible for these symptoms remain incompletely understood. METHODS: Transcriptome datasets from peripheral blood mononuclear cells (PBMCs) of COVID-19 patients infected with the Omicron variant and healthy volunteers were obtained from public databases. A comprehensive bioinformatics analysis was performed to identify hub genes associated with the Omicron variant. Hub genes were validated using quantitative RT-qPCR and clinical data. DSigDB database predicted potential therapeutic agents. RESULTS: Seven hub genes (IFI44, IFI44L, MX1, OAS3, USP18, IFI27, and ISG15) were potential biomarkers for Omicron infection's symptomatic diagnosis and treatment. Type I interferon-related hub genes regulated Omicron-induced symptoms, which is supported by independent datasets and RT-qPCR validation. Immune cell analysis showed elevated monocytes and reduced lymphocytes in COVID-19 patients, which is consistent with retrospective clinical data. Additionally, ten potential therapeutic agents were screened for COVID-19 treatment, targeting the hub genes. CONCLUSIONS: This study provides insights into the mechanisms underlying type I interferon-related pathways in the development and recovery of COVID-19 symptoms during Omicron infection. Seven hub genes were identified as promising biological biomarkers for diagnosing and treating Omicron infection. The identified biomarkers and potential therapeutic agent offer valuable implications for Omicron's clinical manifestations and treatment strategies.