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Record W3120908621 · doi:10.21203/rs.3.rs-16324/v1

“MicroRNA expression profiling of human milk derived exosomes identifies miR-630 and miR-378g as biomarkers in HIV-1 infected women”

2020· preprint· en· W3120908621 on OpenAlexafffund
Muhammad Atif Zahoor, Xiaodan Yao, Bethany M. Henrick, Chris P. Verschoor, Alashʼle Abimiku, Sophia Osawe, Kenneth L. Rosenthal

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsMcMaster UniversityUniversity Health Network
FundersMcMaster University
KeywordsMicrovesiclesmicroRNAHuman immunodeficiency virus (HIV)Profiling (computer programming)Gene expression profilingBiologyBiomarkerComputational biologyVirologyMedicineGene expressionGeneticsGeneComputer science

Abstract

fetched live from OpenAlex

Abstract Background: Despite the use of antiretroviral therapy (ART) in HIV-1 infected mothers approximately 5% of new HIV-1 infections still occur in breastfed infants annually which warrant for the development of new additional strategies to completely prevent new HIV-1 infections in infants. Human Milk (HM) exosomes are highly enriched in maternal microRNAs (miRNAs) which after ingestion and absorption play an important role in neonatal immunity. Although, HM exosomes from healthy donors are known to inhibit HIV-1 transmission; the effect of HIV-1 on HM exosomal miRNA signatures remains unknown. In the present study, HM derived exosomal miRNA profiles were investigated in HIV-1 infected lactating women. Methods: First week postpartum HM exosomes were purified from uninfected control and HIV-1 infected mothers (n=36), processed for RNA extraction and subjected to miRNA expression profiling by NanoString technology. The data were analyzed, and targets were predicted. Results: We describe that HIV-1 perturbed the differential expression pattern of 19 miRNAs (13 up and 6 downregulated) in HIV-1 infected women compared to healthy controls. DIANA-miR functional Pathway analyses revealed that multiple biological pathways are involved including Cell cycle, Pathways in Cancer, TGF-β signaling, FoxO signaling, Fatty Acid Biosynthesis, p53 signaling and Apoptosis. Further, the receiver operating characteristics (ROC) curve analyses of two of the identified miRNAs, miR-630 and miR-378g for separating HIV-1 infected women from healthy controls yielded areas under the ROC curves of 0.82 (95% CI= 0.67 to 0.82) and 0.83 (95% CI= 0.67 to 0.83), respectively highlighting their potential to serve as biomarkers of HIV-1 infection in women. Conclusions: Our studies provide new information that HIV-1 perturbs the expression levels of HM derived exosomal miRNAs in lactating women. The stability of HM exosomes at room temperature raises the possibility of their utility in HIV-1 screening prior to HIV-1 specific testing in countries like Nigeria. Further, our data may also contribute to the development of new therapeutic strategies in prevention of mother-to-child transmission (MTCT) of HIV-1 in infants.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.271
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2020
Admission routes2
Has abstractyes

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