Background: The widespread and evolution of RNA viruses, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlights the importance of fast identification of virus subtypes, particularly in non-laboratory settings. Rapid and inexpensive at-home testing of viral nucleic acids with single-base resolution remains a challenge.
Methods: Topologically constrained DNA ring is engineered as substrates for the trans-cleavage of Cas13a to yield an accelerated post isothermal amplification. The capacity of CRISPR/Cas13a for discriminating single nucleotide variant (SNV) in viral genome is leveraged by designing synthetic mismatches and hairpin structure in CRISPR RNA (crRNA), enabling robust discrimination of different SARS-CoV-2 variants. Via optimisation of CasTDR3pot to be one-pot assay, CasTDR1pot can detect Omicron and its subvariants, with only a few copies in clinical samples in less than 30 min without pre-amplification.
Findings: The detection system boasts high sensitivity (0.1 aM), single-base specificity, and the advantage of a rapid "sample-to-answer" process, which takes only 30 min. In the detection of SARS-CoV-2 clinical samples and their variant strains, CasTDR1pot has achieved 100% accuracy. Furthermore, the design of a portable signal-reading device facilitates user-friendly result interpretation. For the detection needs of different RNA viruses, the system can be adapted simply by designing the corresponding crRNA.
Interpretation: Our study provides a rapid and accurate molecular diagnostic tool for point-of-care testing, epidemiological screening, and the detection of diseases associated with other RNA biomarkers with excellent single nucleotide differentiation, high sensitivity, and simplicity.
Funding: National Key Research and Development Program of China (No. 2023YFB3208302), National Natural Science Foundation of China (No. 22377110, 22034004, 82402749, 82073787, 22122409), National Key Research and Development Program of China (No. 2021YFA1200104), Henan Province Fund for Cultivating Advantageous Disciplines (No. 222301420019).
Background: Transthoracic echocardiography (TTE) is the primary modality for diagnosing aortic stenosis (AS), yet it requires skilled operators and can be resource-intensive. We developed and validated an artificial intelligence (AI)-based system for evaluating AS that is effective in both resource-limited and advanced settings.
Methods: We created a dual-pathway AI system for AS evaluation using a nationwide echocardiographic dataset (developmental dataset, n = 8427): 1) a deep learning (DL)-based AS continuum assessment algorithm using limited 2D TTE videos, and 2) automating conventional AS evaluation. We performed internal (internal test dataset [ITDS], n = 841) and external validation (distinct hospital dataset [DHDS], n = 1696; temporally distinct dataset [TDDS], n = 772) for diagnostic value across various stages of AS and prognostic value for composite endpoints (cardiovascular death, heart failure, and aortic valve replacement).
Findings: The DL index for the AS continuum (DLi-ASc, range 0-100) increased with worsening AS severity and demonstrated excellent discrimination for any AS (AUC 0.91-0.99), significant AS (0.95-0.98), and severe AS (0.97-0.99). DLi-ASc was independent predictor for composite endpoint (adjusted hazard ratios 2.19, 1.64, and 1.61 per 10-point increase in ITDS, DHDS, and TDDS, respectively). Automatic measurement of conventional AS parameters demonstrated excellent correlation with manual measurement, resulting in high accuracy for AS staging (98.2% for ITDS, 82.1% for DHDS, and 96.8% for TDDS) and comparable prognostic value to manually-derived parameters.
Interpretation: The AI-based system provides accurate and prognostically valuable AS assessment, suitable for various clinical settings. Further validation studies are planned to confirm its effectiveness across diverse environments.
Funding: This work was supported by a grant from the Institute of Information & Communications Technology Planning & Evaluation (IITP) funded by the Korea government (Ministry of Science and ICT; MSIT, Republic of Korea) (No. 2022000972, Development of a Flexible Mobile Healthcare Software Platform Using 5G MEC); and the Medical AI Clinic Program through the National IT Industry Promotion Agency (NIPA) funded by the MSIT, Republic of Korea (Grant No.: H0904-24-1002).
Background: Lipid species are emerging as biomarkers for cardiometabolic risk in both adults and children. The genetic regulation of lipid species and their impact on cardiometabolic risk during early life remain unexplored.
Methods: Using mass spectrometry-based lipidomics, we measured 227 plasma lipid species in 1149 children and adolescents (44.8% boys) with a median age of 11.2 years. We performed genome-wide association analyses to identify genetic variants influencing lipid species. Colocalisation and Mendelian randomisation (MR) analyses were performed to infer causality between lipid species and cardiometabolic outcomes.
Findings: We identified 37 genome-wide significant loci for 52 lipid species, nine of which are previously unreported. Colocalisation analyses revealed that seven lipid loci shared genetic variants associated with adult cardiometabolic outcomes. One-sample MR analysis identified positive causal associations between ceramides and liver enzymes, sphingomyelins and hemoglobin A1c (HbA1c), and phosphatidylethanolamines and high-sensitivity C-reactive protein in children and adolescents. Two-sample MR using adult-based summary statistics showed consistent direction of associations and indicated additional causal links, specifically between ceramides and elevated HbA1c levels, and phosphatidylinositols with elevated liver enzymes.
Interpretation: These findings highlight the potential long-term implications of plasma lipid genetic determinants on cardiometabolic risk.
Funding: Novo Nordisk Foundation, The Innovation Fund Denmark, The Danish Heart Foundation, EU Horizon, and LundbeckFonden.
Background: Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging tick-borne phlebovirus that causes viral hemorrhagic fever. Pandemic concerns have arisen due to the increased human-to-human transmission and high mortality rate, highlighting the urgent need for specific therapeutics.
Methods: Our observational study characterized the memory B cell response to natural SFTSV infection in four survivors. Monoclonal antibodies (mAbs) targeting the SFTSV glycoprotein N (Gn) were isolated and tested for in vitro neutralizing activities and effects on virus binding. Structural analysis was performed to identify neutralizing epitopes recognized by the mAbs. Prophylactical and therapeutical protections were evaluated using a lethal SFTSV infection model.
Findings: The selected mAbs exhibiting neutralizing activity primarily originate from the IGHV5-51 and IGHV3-30 germlines and target four distinct antigenic sites on SFTSV Gn. These elite mAbs effectively blocked the interaction between Gn and the cell receptor, preventing infections from five phylogenetically distinct SFTSV clades. Structural analysis revealed a novel neutralizing epitope located within SFTSV Gn domain I recognized by the elite mAbs. In mice of lethal infections with different SFTSV strains, administering a low dose of elite mAbs significantly improved survival rates in both prophylactic and therapeutic settings.
Interpretation: This study identifies potent broadly neutralizing antibodies that holds promise for use in humans against SFTSV infection and highlights inhibition of receptor binding as a crucial mechanism for effective antibody-mediated neutralization against phleboviruses.
Funding: The National Key Research and Development Plan of China (2018YFE0200401, 2022YFC2303300), National Natural Science Foundation of China (81825019), China Postdoctoral Science Foundation (2023M741824).
The role of genomics in public health surveillance has been accentuated by its crucial contributions during the COVID-19 pandemic, demonstrating its potential in addressing global disease outbreaks. While Africa has made strides in expanding multi-pathogen genomic surveillance, the integration into foodborne disease (FBD) surveillance remains nascent. Here we highlight the critical components to strengthen and scale-up the integration of whole genome sequencing (WGS) in foodborne disease surveillance across the continent. We discuss priority use-cases for FBD, and strategies for the implementation. We also highlight the major challenges such as data management, policy and regulatory frameworks, stakeholder engagement, the need for multidisciplinary collaborations and the importance of robust monitoring and evaluation, aiming to bolster Africa's preparedness and response to future health threats.
Background: Ideally, vaccination should induce protective long-lived humoral and cellular immunity. Current licensed COVID-19 mRNA vaccines focused on the spike (S) region induce neutralizing antibodies that rapidly wane.
Methods: Herein, we show that a subunit vaccine (CD40.CoV2) targeting spike and nucleocapsid antigens to CD40-expressing cells elicits broad specific human (hu)Th1 CD4+ and CD8+ T cells in humanized mice.
Findings: CD40.CoV2 vaccination selectively enriched long-lived spike- and nucleocapsid-specific CD8+ progenitors with stem-cell-like memory (Tscm) properties, whereas mRNA BNT162b2 induced effector memory CD8+ T cells. CD8+ Tscm cells produced IFNγ and TNF upon antigenic restimulation and showed a high proliferation rate. We demonstrate that CD40 activation is specifically required for the generation of huCD8+ Tscm cells.
Interpretation: These results support the development of a CD40-vaccine platform capable of eliciting long-lasting T-cell immunity.
Funding: This work was supported by Inserm, Université Paris-Est Créteil, and the Investissements d'Avenir program, Vaccine Research Institute (VRI), managed by the ANR.
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