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Record W4319160856 · doi:10.3389/fmolb.2023.1104577

Specialized pro-resolving lipid mediators regulate inflammatory macrophages: A paradigm shift from antibiotics to immunotherapy for mitigating COVID-19 pandemic

2023· review· en· W4319160856 on OpenAlexaff
Vikram Kumar, Nusrath Yasmeen, Anis Ahmad Chaudhary, Abdullah S. Alawam, Mohammed Al‐Zharani, Nosiba S. Basher, S Harikrishnan, Muddapuram Deeksha Goud, Aishwarya Pandey, Sudarshan Singh Lakhawat, Pushpender Kumar Sharma

Bibliographic record

VenueFrontiers in Molecular Biosciences · 2023
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsInstitut National de la Recherche Scientifique
FundersAmity Institute of Biotechnology, Amity UniversityAl-Imam Muhammad Ibn Saud Islamic UniversityAmity University
KeywordsCytokine stormARDSImmunologyMedicineCytokineInflammationProinflammatory cytokinePopulationMacrophage activation syndromeDiseaseLungInternal medicineInfectious disease (medical specialty)ArthritisCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

The most severe clinical manifestations of the horrifying COVID-19 disease, that claimed millions of lives during the pandemic time, were Acute respiratory distress syndrome (ARDS), Coagulopathies, septic shock leading eventually to death. ARDS was a consequence of Cytokine storm. The viral SARS-COV2infection lead to avalanche of cytokines and eicosanoids causing "cytokine storm" and "eicosanoid storm." Cytokine storm is one of the macrophage-derived inflammatory responses triggered by binding of virus particles to ACE2 receptors of alveolar macrophages, arise mainly due to over production of various pro-inflammatory mediators like cytokines, e.g., interleukin (IL)-1, IL-2, and tumor necrosis factor (TNF)- α, causing pulmonary edema, acute respiratory distress, and multi-organ failure. Cytokine storm was regarded as the predictor of severity of the disease and was deemed one of the causes of the high mortality rates due to the COVID-19. The basis of cytokine storm is imbalanced switching between an inflammation increasing - pro-inflammatory (M1) and an inflammation regulating-anti-inflammatory (M2) forms of alveolar macrophages which further deteriorates if opportunistic secondary bacterial infections prevail in the lungs. Lack of sufficient knowledge regarding the virus and its influence on co-morbidities, clinical treatment of the diseases included exorbitant use of antibiotics to mitigate secondary bacterial infections, which led to the unwarranted development of multidrug resistance (MDR) among the population across the globe. Antimicrobial resistance (AMR) needs to be addressed from various perspectives as it may deprive future generations of the basic health immunity. Specialized pro-resolving mediators (SPMs) are generated from the stereoselective enzymatic conversions of essential fatty acids that serve as immune resolvents in controlling acute inflammatory responses. SPMs facilitate the clearance of injured tissue and cell debris, the removal of pathogens, and augment the concentration of anti-inflammatory lipid mediators. The SPMs, e.g., lipoxins, protectins, and resolvins have been implicated in exerting inhibitory influence on with cytokine storm. Experimental evidence suggests that SPMS lower antibiotic requirement. Therefore, in this review potential roles of SPMs in enhancing macrophage polarization, triggering immunological functions, hastening inflammation resolution, subsiding cytokine storm and decreasing antibiotic requirement that can reduce AMR load are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.042
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.080
GPT teacher head0.439
Teacher spread0.359 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2023
Admission routes1
Has abstractyes

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