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Record W4394166643 · doi:10.6084/m9.figshare.21275966

Additional file 5 of Changes in concentrations of cervicovaginal immune mediators across the menstrual cycle: a systematic review and meta-analysis of individual patient data

2022· review· en· W4394166643 on OpenAlexaff
Sean M. Hughes, Claire Levy, Ronit Katz, Erica M. Lokken, Melis N. Anahtar, Melissa Barousse Hall, Frideborg Bradley, Philip E. Castle, Valerie Cortez, Gustavo F. Doncel, Raina N. Fichorova, Paul L. Fidel, Keith R. Fowke, Suzanna C. Francis, Mimi Ghosh, Loris Y. Hwang, Mariel Jais, Vicky Jespers, Vineet Joag, Rupert Kaul, Jordan K. Kyongo, Timothy Lahey, Huiying Li, Julia Makinde, Lyle R. McKinnon, Anna‐Barbara Moscicki, Richard M. Novak, Mickey V. Patel, Intira Sriprasert, Andrea R. Thurman, Sergey Yegorov, Nelly Mugo, Alison C. Roxby, Elizabeth Micks, Florian Hladik

Bibliographic record

VenueOpen MIND · 2022
Typereview
Languageen
FieldImmunology and Microbiology
TopicReproductive System and Pregnancy
Canadian institutionsToronto General HospitalMcMaster UniversityUniversity of TorontoUniversity of Manitoba
Fundersnot available
KeywordsMenstrual cycleImmune systemMeta-analysisMedicinePsychologyImmunologyInternal medicineHormone

Abstract

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Additional file 5: Figure S1. Assessment of publication bias. A Funnel plots. Symbols show the effect of the menstrual cycle (x-axis) and the standard error of that effect (y-axis, reversed). Each symbol shows an individual study. Vertical solid line shows no effect. Vertical dashed line shows the meta-estimate of effect. Diagonal dashed lines enclose the region expected to include 95% of studies based on the estimated meta-effect and the standard errors. B Results of Egger’s tests for publication bias. Figure S2. Periovulatory meta-analyses. A The log2 difference between periovulatory and follicular phases (log2-pg/mL of the follicular phase minus log2-pg/mL of the periovulatory phase). For TGF-β1, the error bars for one study and the meta-estimate extend off-scale. B The log2 difference between periovulatory and luteal phases (log2-pg/mL of the luteal phase minus log2-pg/mL of the periovulatory phase). For IL-10, the error bars for one study extend off-scale. Each row represents a different immune mediator, with the symbols showing the mean and the lines showing the 95% confidence intervals. Gray symbols indicate individual studies and black the meta-estimates as determined by inverse-variance pooling random effects models. Black filled symbols indicate p < 0.05 while white filled symbols indicate p > 0.05. Positive numbers indicate higher during the follicular or luteal phase, while negative numbers indicate higher during the periovulatory phase. Fig S3. Subgroup analysis: Does the effect of menstrual cycle differ by assay method, geographical region, or method of determining menstrual phase? A Meta-analyses, comparing all studies (black circles) to studies grouped by assay method (ELISA: blue squares; MSD: yellow triangles; Luminex: green diamonds). B Meta-analyses, comparing all studies (black circles) to studies grouped by geographical region of sample origin (Africa: blue diamonds; Europe: red squares; North America: green triangles). C Meta-analyses, comparing all studies (black circles) to studies grouped by method of menstrual cycle phasing (Days since LMP: orange squares; Progesterone: pale purple diamonds; Progesterone plus LH: dark purple triangles). Figure S4. Secondary outcomes: Method of determining menstrual cycle phase and normalization to total protein. A The standard errors of the effect sizes for the difference between menstrual cycle phases, with phases determined by days since last menstrual period (“LMP”) or serum progesterone (“Prog”). Each symbol represents an immune factor, with lines connecting the same immune factor. B The standard errors of the effect sizes for the difference between menstrual cycle phases as determined using raw concentration measurements (pg/mL) and concentrations normalized to total protein (pg/pg total protein). Each symbol represents an immune factor, with lines connecting the same immune factor. Table S1. Summary of immune mediators measured in single studies. Table S2. Summary of follicular vs. periovulatory meta-analyses. Table S3. Summary of luteal vs. periovulatory meta-analyses. Table S4. Covariates adjusted for in multivariate analysis of each study.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.618
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.6180.000

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 head0.143
GPT teacher head0.368
Teacher spread0.225 · 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 designMeta-analysis
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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