Induction of antiviral innate immune responses depends on a family of innate immune receptors, the Toll-like receptors (TLR). TLR mediate the antiviral immune responses by recognizing virus infection, activating signaling pathways and inducing the production of antiviral cytokines and chemokines. ssRNA and dsRNA viruses can be recognized by TLR7/8 and TLR3, respectively. TLR receptors are also involved in the recognition of viruses containing genomes rich in CpG DNA motifs as well as envelope glycoproteins. Cytoplasmic recognition of dsRNA by RNA helicases such as RIG-I and MDA5 provides another means of recognizing viral nucleic acid. In order to counteract the innate host immune system viruses evolved mechanisms that block recognition and signaling through pattern recognition receptors, such as TLRs and RNA helicases. Recently, TLR agonists represent a promising approach for the treatment of infectious diseases. This review will focus on the current knowledge of TLR-mediated immune responses to several viral infections.
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http://dx.doi.org/10.2174/1874285800802010049 | DOI Listing |
J Virol
January 2025
Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.
The common cold coronaviruses are a source of ongoing morbidity and mortality particularly among elderly and immunocompromised individuals. While cross-reactive immune responses against multiple coronaviruses have been described following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination, it remains unclear if these confer any degree of cross-protection against the common cold coronaviruses. A recombinant fowl adenovirus vaccine expressing the SARS-CoV-2 spike protein (FAdV-9-S19) was generated, and protection from SARS-CoV-2 challenge was shown in K18-hACE2 mice.
View Article and Find Full Text PDFJ Virol
January 2025
Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.
Unlabelled: Respiratory and encephalitic virus infections represent a significant risk to public health globally. Detailed investigations of immunological responses and disease outcomes during sequential virus infections are rare. Here, we define the impact of influenza virus infection on a subsequent virus encephalitis.
View Article and Find Full Text PDFJ Virol
January 2025
SA MRC Antibody Immunity Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Parktown, Johannesburg, South Africa.
The Antibody Mediated Prevention (AMP) trials showed that passively infused VRC01, a broadly neutralizing antibody (bNAb) targeting the CD4 binding site (CD4bs) on the HIV-1 envelope protein (Env), protected against neutralization-sensitive viruses. We identified six individuals from the VRC01 treatment arm with multi-lineage breakthrough HIV-1 infections from HVTN703, where one variant was sensitive to VRC01 (IC < 25 ug/mL) but another was resistant. By comparing Env sequences of resistant and sensitive clones from each participant, we identified sites predicted to affect VRC01 neutralization and assessed the effect of their reversion in the VRC01-resistant clone on neutralization sensitivity.
View Article and Find Full Text PDFmBio
January 2025
Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China.
Unlabelled: The KREMEN1 (KRM1) protein is a cellular receptor for multiple enteroviruses that cause hand, foot, and mouth disease (HFMD), including coxsackievirus CVA2, CVA3, CVA4, CVA5, CVA6, CVA10, and CVA12. The molecular basis for the broad recognition of these viruses by the KRM1 receptor remains unclear. Here, we report the indispensable role of the completely conserved VP2 capsid protein residue K140 (designated K2140) in mediating receptor recognition and infection by CVA10 and other KRM1-dependent enteroviruses.
View Article and Find Full Text PDFDiagn Interv Radiol
January 2025
Huadong Hospital, Fudan University, Department of Thoracic Surgery, Shanghai, China.
Purpose: Patients with advanced non-small cell lung cancer (NSCLC) have varying responses to immunotherapy, but there are no reliable, accepted biomarkers to accurately predict its therapeutic efficacy. The present study aimed to construct individualized models through automatic machine learning (autoML) to predict the efficacy of immunotherapy in patients with inoperable advanced NSCLC.
Methods: A total of 63 eligible participants were included and randomized into training and validation groups.
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