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To evaluate the performance of three rapid influenza diagnostic tests (RIDTs) for detecting influenza A and B viruses compared to RT-PCR. A total of 291 subjects with acute respiratory infections were enrolled. Respiratory specimens were collected and tested for influenza A and B viruses using three RIDTs.

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Tight sandstone gas reservoirs are characterized by high water saturation, significant seepage resistance, low single-well productivity, rapid decline, and low gas recovery. Enhancing the recovery rate of tight sandstone gas reservoirs is a complex engineering challenge that necessitates thorough, refined, and systematic research into its fundamental theories. This study employs a comprehensive approach integrating mercury injection, nuclear magnetic resonance, micro-model visualization, and simulation experiments of displacement and inter-layer seepage flow, alongside foundational seepage theories, to systematically explore the characteristics of tight sandstone gas reservoirs, seepage patterns, and methods for improving gas recovery.

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Backgroud: Fluid volume abnormalities are a major cause of exacerbations in heart failure patients. However, there is few efficient, rapid, or cost-effective clinical approach for determining volume status, resulting in inadequate or unsatisfactory treatment. The aim was to develop an early fluid volume detection model for heart failure patients utilizing a machine learning stratification.

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Background: Surgical site infections (SSIs) have been shown to increase patient morbidity and mortality, impact on quality of life and place a significant economic burden on healthcare systems worldwide. Irrigation using wound cleansing and antiseptic effective solutions during surgical procedures is a key part of SSI prevention. The optimal solution would have minimal cytotoxicity to the patient while maintaining a minimum concentration required for antimicrobial activity necessary to prevent opportunistic pathogens and biofilm formation.

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Amplification-free detection of using CRISPR-Cas12a and graphene field-effect transistors.

Nanoscale

January 2025

State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China.

Current molecular tests for tuberculosis (TB), such as whole genome sequencing and Xpert /rifampicin resistance assay, exhibit limited sensitivity and necessitate the pre-amplification step of target DNA. This limitation greatly increases detection time and poses an increased risk of infection. Here, we present a graphene field-effect transistor (GFET) based on the CRISPR/Cas system for detecting .

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