The DOI matches its Crossref record; 204 of the 205 references it cites were found in a registry or an index.
Sweeten PAMPs: role of sugar complexed PAMPs in innate immunity and vaccine biology
Open accessAbstract
Innate sensors play a critical role in the early innate immune responses to invading pathogens through sensing of diverse biochemical signatures also known as pathogen associated molecular patterns (PAMPs). These biochemical signatures primarily consist of a major family of biomolecules such as proteins, lipids, nitrogen bases, and sugar and its complexes, which are distinct from host molecules and exclusively expressed in pathogens and essential to their survival. The family of sensors known as pattern recognition receptors (PRRs) are germ-line encoded, evolutionarily conserved molecules, and consist of Toll-like receptors (TLRs), RIG-I-like receptors (RLRs), NOD-like receptors (NLRs), C-type lectin-like receptors (CLRs), and DNA sensors. Sensing of PAMP by PRR initiates the cascade of signaling leading to the activation of transcription factors, such as NF-κB and interferon regulatory factors (IRFs), resulting in a variety of cellular responses, including the production of interferons (IFNs) and pro-inflammatory cytokines. In this review, we discuss sensing of different types of glycosylated PAMPs such as β-glucan (a polymeric sugar) or lipopolysaccharides, nucleic acid, and so on (sugar complex PAMPs) by different families of sensors, its role in pathogenesis, and its application in development of potential vaccine and vaccine adjuvants.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Yaşlı Kadınlarda Üreme Sağlığı
Kokanalı, D., & Engin Üstün, Y. (n.d.) · DergiPark (Istanbul University) · Cited by 170,090
Two new Later Stone Age sites from the Final Pleistocene in the Falémé Valley, eastern Senegal
Ndiaye, M., Lespez, L., Tribolo, C., Rassé, M., Hadjas, I., Davidoux, S., Huysecom, É., & Douze, K. (2024) · Monash University Research Portal (Monash University) · doi:10.3929/ethz-b-000667478 · Cited by 24,214
The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors
Kawai, T., & Akira, S. (2010) · Nature Immunology · doi:10.1038/ni.1863 · Cited by 9,304
Akira, S., & Takeda, K. (2004) · Nature reviews. Immunology · doi:10.1038/nri1391 · Cited by 8,312
Defective LPS Signaling in C3H/HeJ and C57BL/10ScCr Mice: Mutations in Tlr4 Gene
Poltorak, A., He, X., Smirnova, I., Liu, M.-Y., Huffel, C. V., Du, X., Birdwell, D., Alejos, E., Silva, M., Galanos, C., et al. (1998) · Science · doi:10.1126/science.282.5396.2085 · Cited by 7,631
A Toll-like receptor recognizes bacterial DNA
Hemmi, H., Takeuchi, O., Kawai, T., Kaisho, T., Sato, S., Sanjo, H., Matsumoto, M., Hoshino, K., Wagner, H., Takeda, K., et al. (2000) · Nature · doi:10.1038/35047123 · Cited by 6,491 · cited 1×
“The cellular responses to CpG are mediated through its sensing by the TLR9 receptor (29).”
BackgroundRecognition of double-stranded RNA and activation of NF-κB by Toll-like receptor 3
Alexopoulou, L., Holt, A. C., Medzhitov, R., & Flavell, R. A. (2001) · Nature · doi:10.1038/35099560 · Cited by 6,129
(2023) · doi:10.1126/science · Cited by 6,063
(1996) · Institutional Research Information System University of Turin (University of Turin) · doi:10.1111/j · Cited by 5,486
Cyclic GMP-AMP Synthase Is a Cytosolic DNA Sensor That Activates the Type I Interferon Pathway
Sun, L., Wu, J., Du, F., Chen, X., & Chen, Z. J. (2013) · Science · doi:10.1126/science.1232458 · Cited by 4,996
Flagged first, then by citations
1 of the 205 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Items 201–240 of 240
Wang, D., & Liu, B. (2020) · Research Square · doi:10.21203/rs.3.rs-62336/v1 · Cited by 1
Chen, L., Chen, R., Yao, M., Feng, Z., Yuan, G., Ye, F., Nguyen, K., Karn, J., McComsey, G. A., McIntyre, T. M., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-1950248/v1 · Cited by 1
IFI16 induced hepatocyte inflammation with HBV infection by regulating STING-IRF3 pathwayPreprint
Liu, X., Li, C., Ma, S., Bu, X., Xie, S., & Du, W. (2025) · Research Square · doi:10.21203/rs.3.rs-6883660/v1 · Cited by 1
Szegedi, A., & Dajnoki, Z. (2016) · Bőrgyógyászati és Venerológiai Szemle · doi:10.7188/bvsz.2016.92.4.1
Toll-Like Receptor 11: Role in Post-Transplantation Renal Infections
Mani, I., & Vasdev, K. (2017) · Single Cell Biology · doi:10.4172/2168-9431.1000164
Peckham-Cooper, A. (2017) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)
Statins, Lipids, and Mutations: Consequences for the Heart and Immune System
Ivarsson, E. G. (2019) · Gothenburg University Publications Electronic Archive (Gothenburg University)
Toll Like Receptor 2 Genotypes and Intra-Coronary Stent Restenosis
ABDELAZIZ, M. D. R. H. T., & Gad, M. M. (2019) · The Medical Journal of Cairo University/The Medical Journal of Cairo University · doi:10.21608/mjcu.2019.65618
Luo, G., Niu, J., Fang, J., Tang, J., Lu, Y., Huang, Y., & Jian, J. (2021) · Aquaculture Reports · doi:10.1016/j.aqrep.2021.100782
Al-Qasrawi, D. S. (2021) · Journal of International Crisis and Risk Communication Research · doi:10.13140/rg.2.2.28020.27528
Moran, N. P. (2021) · The Atrium (University of Guelph)
Sánchez-Petidier, M. (2022) · RiuNet (Universitat Politècnica de València) · doi:10.4995/thesis/10251/180753
Maternal immunometabolism adaptation in pregnancy
Rees, A. (2022) · Cronfa (Swansea University) · doi:10.23889/suthesis.59676
Macrophages in gouty inflammation
Malyshev, I. Y., Chernysheva, O. O., Kuznetsova, L. V., & Pikhlak, A. (2022) · Russian Journal of Immunology · doi:10.46235/1028-7221-1096-mig
TLR 1,3 Receptor Gene Polymorphism in Egyptian Patients With Behcets Disease
Abdelmoktader, A. (2022) · Virology & Immunology Journal · doi:10.23880/vij-16000298
Chen, L., Chen, R., Yao, M., Feng, Z., Yuan, G., Ye, F., Nguyen, K., Karn, J., McComsey, G. A., McIntyre, T. M., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-1950248/v2
Epstein-Barr Virus and Malaria Interactions: Immunology Perspective
Budiningsih, I., Middeldorp, J. M., Dachlan, Y. P., & Hadi, U. (2022) · HAYATI Journal of Biosciences · doi:10.4308/hjb.29.6.824-833
Epigenetic regulations in inflammatory diseases
Chakraborty, R., & Patnaik, S. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-823931-5.00014-1
Antibacterial Carbohydrate Vaccines
Compostella, F., Morelli, L., & Lay, L. (2023) · doi:10.1002/9783527831326.ch1
He protec but he also attac – Inflammasomes swinging the sword
Kattner, A. A. (2023) · Biomedical Journal · doi:10.1016/j.bj.2023.100663
Genetic polymorphisms in the pathogenesis and course of Crohn’s disease
Gocel, O., Pendrasik, K., Frąk, W., & Małecka-Wojciesko, E. (2023) · Medical Studies · doi:10.5114/ms.2023.134093
PATHOGENETIC ROLE OF CHANGES SERUM LEVEL INTERLEUKIN-4 DURING THERAPY FOR ULCERATIVE COLITIS
Matveeva, L. V., Mosina, L. M., Алексеевна, К. О., & Trokhina, I. E. (2024) · Molekulyarnaya Meditsina (Molecular medicine) · doi:10.29296/24999490-2024-04-08
Zhong, L., Wu, C., Liao, L., Li, J., & Wu, Y. (2025) · Virulence · doi:10.1080/21505594.2025.2507197
Surveillance and Monitoring of Humoral Immune Responses
Jeyachandran, S., & Maran, B. A. V. (2025) · Springer eBooks · doi:10.1007/978-981-95-1549-3_3
Rajadas, S. E., Sounderrajan, V., Prabhakaran, R. A., Agrawal, R., Jeyadoss, L., Rajan, M., Parthasarathy, K., & Harshavardhan, S. (2024) · Figshare · doi:10.6084/m9.figshare.26735031
Xisto, M. I. D. D. S., dos Santos, S. S., Rossato, L., Yoshikawa, F. S. Y., Haido, R. M. T., de Almeida, S. R., & Barreto‐Bergter, E. (2020) · Figshare · doi:10.6084/m9.figshare.12775128
Rajadas, S. E., Sounderrajan, V., Prabhakaran, R. A., Agrawal, R., Jeyadoss, L., Rajan, M., Parthasarathy, K., & Harshavardhan, S. (2024) · Figshare · doi:10.6084/m9.figshare.26735028
Rajadas, S. E., Sounderrajan, V., Prabhakaran, R. A., Agrawal, R., Jeyadoss, L., Rajan, M., Parthasarathy, K., & Harshavardhan, S. (2024) · Figshare · doi:10.6084/m9.figshare.26735022
Rajadas, S. E., Sounderrajan, V., Prabhakaran, R. A., Agrawal, R., Jeyadoss, L., Rajan, M., Parthasarathy, K., & Harshavardhan, S. (2024) · Figshare · doi:10.6084/m9.figshare.26735025
Ren, P., Zhang, P., Shi, J., Li, H., 金若菲, & Li, H. (2026) · Frontiers in Marine Science · doi:10.3389/fmars.2026.1758043
Molecular and cellular bases of monogenic auto-inflammatory diseases and AA amyloidosis
Jumeau, C. (2019) · theses.fr (ABES) · doi:10.70675/73c2c7f0z679dz44b8z8b68zb2fce75a3d70
Research on nanodelivery systems for nasal vaccine
Le, M. Q. (2018) · theses.fr (ABES) · doi:10.70675/69ebfffaz2030z411fz9091z496d5c90aa07 · Cited by 1
APOBEC3A cytidine deaminase, a potent mutator enzyme leading to nuclear DNA damages
Li, X. (2018) · theses.fr (ABES) · doi:10.70675/c6c54ef9za374z4871zb0e0z9d11e8ea3d84
Leveraging the bacteria for enhanced cancer immunotherapy: from a perspective of synthetic biology
Liu, X., Zhang, H., Du, R., Liu, Z., Ren, Y., & Yang, X. S. (2026) · Cancer Biology & Therapy · doi:10.1080/15384047.2026.2683171
Fatima, S. M., Rahman, M. T., Mostaert, B. J., Razu, I., Hunger, B., Afrin, S., Haque, S. N., Khan, N. A., Zhang, Z., Claussen, A. D., et al. (2026) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2026.1895870
BindingDB (2019) · UC San Diego · doi:10.7270/q21n839s
Metadata
- Authors
- Mahla, R. S.
- Affiliations
- Indian Institute of Science Education and Research, Bhopal (IN)
- Corresponding author
- Mahla, Ranjeet Singh
- ORCID
- Mahla, Ranjeet Singh
- Venue
- Frontiers in Immunology
- Publisher
- Frontiers Media SA
- Published
- 2013
- Volume
- 4
- Pages
- 248-248
- ISSN
- 1664-3224 (ISSN-L)
- PMC
- PMC3759294
- OpenAlex
- W2045475619
- Cited by
- 239
- References
- 205
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 23 · 2023: 20 · 2022: 26 · 2021: 34 · 2020: 34 · 2019: 34 · 2018: 19 · 2017: 19 · 2016: 7 · 2015: 3 · 2014: 4 · 2013: 1
- FWCI
- 0.44
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Immunology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Department of Biotechnology, Ministry of Science and Technology, India (SR/S2/RJN-55/2009, BT/PR6009/GBD/27/382/2012)
- Department of Science and Technology, Ministry of Science and Technology, India
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Immune Response and Inflammation
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Life Sciences › Immunology and Microbiology › Immunology › Immune responses and vaccinations
- Keywords
- pathogen-associated molecular patterns, innate immunity, pattern recognition receptors, Toll-like receptors, RIG-I-like receptors, NOD-like receptors, C-type lectin-like receptors, DNA biosensor, β-glucan, lipopolysaccharide, vaccine adjuvants, vaccine development, interferon signaling, NF-κB, inflammatory cytokines
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
