{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36029522", "kind": "science-record", "revision": 4, "content_hash": "sha256:aefee70dfd9add311108c2bf9eabba6c8586e4d64dbcd6d1a1338bd800a3bc52", "created_at": "2026-11-01T18:15:11Z", "updated_at": "2026-11-01T22:07:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "microRNA-based signatures obtained from endometrial fluid identify implantative endometrium.", "doi": "10.1093/humrep/deac184", "pmid": "36029522", "authors": ["Jone Ibañez-Perez", "María Díaz-Nuñez", "Marc Clos-García", "Lucía Lainz", "María Iglesias", "Miren Díez-Zapirain", "Aintzane Rabanal", "Laura Bárcena", "Monika González", "Juan J Lozano", "Urko M Marigorta", "Esperanza González", "Félix Royo", "Ana M Aransay", "Nerea Subiran", "Roberto Matorras", "Juan Manuel Falcón-Pérez"], "journal": "Human reproduction (Oxford, England)", "year": 2022, "abstract": "STUDY QUESTION: Is it possible to use free and extracellular vesicle-associated microRNAs (miRNAs) from human endometrial fluid (EF) samples as non-invasive biomarkers for implantative endometrium?\nSUMMARY ANSWER: The free and extracellular vesicle-associated miRNAs can be used to detect implantative endometrium in a non-invasive manner.\nWHAT IS KNOWN ALREADY: miRNAs and extracellular vesicles (EVs) from EF have been described as mediators of the embryo-endometrium crosstalk. Therefore, the analysis of miRNA from this fluid could become a non-invasive technique for recognizing implantative endometrium. This analysis could potentially help improve the implantation rates in ART.\nSTUDY DESIGN, SIZE, DURATION: In this prospective study, we first optimized different protocols for EVs and miRNA analyses using the EF of a setup cohort (n = 72). Then, we examined differentially expressed miRNAs in the EF of women with successful embryo implantation (discovery cohort n = 15/validation cohort n = 30) in comparison with those for whom the implantation had failed (discovery cohort n = 15/validation cohort n = 30). Successful embryo implantation was considered when pregnancy was confirmed by vaginal ultrasound showing a gestational sac 4 weeks after embryo transfer (ET).\nPARTICIPANTS/MATERIALS, SETTING, METHODS: The EF of the setup cohort was obtained before starting fertility treatment during the natural cycle, 16-21 days after the beginning of menstruation. For the discovery and validation cohorts, the EF was collected from women undergoing frozen ET on Day 5, and the samples were collected immediately before ET. In this study, we compared five different methods; two of them based on direct extraction of RNA and the other three with an EV enrichment step before the RNA extraction. Small RNA sequencing was performed to determine the most efficient method and find a predictive model differentiating between implantative and non-implantative endometrium. The models were confirmed using quantitative PCR in two sets of samples (discovery and validation cohorts) with different implantation outcomes.\nMAIN RESULTS AND THE ROLE OF CHANCE: The protocols using EV enrichment detected more miRNAs than the methods based on direct RNA extraction. The two most efficient protocols (using polymer-based precipitation (PBP): PBP-M and PBP-N) were used to obtain two predictive models (based on three miRNAs) allowing us to distinguish between an implantative and non-implantative endometrium. The first Model 1 (PBP-M) (discovery: AUC = 0.93; P-value = 0.003; validation: AUC = 0.69; P-value = 0.019) used hsa-miR-200b-3p, hsa-miR-24-3p and hsa-miR-148b-3p. Model 2 (PBP-N) (discovery: AUC = 0.92; P-value = 0.0002; validation: AUC = 0.78; P-value = 0.0002) used hsa-miR-200b-3p, hsa-miR-24-3p and hsa-miR-99b-5p. Functional analysis of these miRNAs showed strong association with key implantation processes such as in utero embryonic development or transforming growth factor-beta signaling.\nLARGE SCALE DATA: The FASTQ data are available in the GEO database (access number GSE178917).\nLIMITATIONS, REASONS FOR CAUTION: One important factor to consider is the inherent variability among the women involved in the trial and among the transferred embryos. The embryos were pre-selected based on morphology, but neither genetic nor molecular studies were conducted, which would have improved the accuracy of our tests. In addition, a limitation in miRNA library construction is the low amount of input RNA.\nWIDER IMPLICATIONS OF THE FINDINGS: We describe new non-invasive protocols to analyze miRNAs from small volumes of EF. These protocols could be implemented in clinical practice to assess the status of the endometrium before attempting ET. Such evaluation could help to avoid the loss of embryos transferred to a non-implantative endometrium.\nSTUDY FUNDING/COMPETING INTEREST(S): J.I.-P. was supported by a predoctoral grant from the Basque Government (PRE_2017_0204). This study was partially funded by the Grant for Fertility Innovation (GFI, 2011) from Merck (Darmstadt, Germany). It was also supported by the Spanish Ministry of Economy and Competitiveness MINECO within the National Plan RTI2018-094969-B-I00, the European Union's Horizon 2020 research and innovation program (860303), the Severo Ochoa Centre of Excellence Innovative Research Grant (SEV-2016-0644) and the Instituto de Salud Carlos III (PI20/01131). The funding entities did not play any role in the study design, collection, analysis and interpretation of data, writing of the report or the decision to submit the article for publication. The authors declare no competing interests.", "claims": [{"id": "claim-method", "statement": "A subset of miRNAs was used to generate two linear regression models with k-fold cross-validations, one for each miRNA extraction protocol assessed.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36029522", "locator": "sections[28] \"Regression study\" paragraph 2", "quote": "A subset of miRNAs was used to generate two linear regression models with k-fold cross-validations, one for each miRNA extraction protocol assessed."}], "state": "complete"}, {"id": "claim-data-access", "statement": "FASTQ data are available in GEO with the access number GSE178917 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178917).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36029522", "locator": "sections[39] \"Data Availability\" paragraph 2", "quote": "FASTQ data are available in GEO with the access number GSE178917 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178917)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Two three-miRNA models derived from extracellular-vesicle-enriched endometrial fluid distinguished implantative from non-implantative endometrium, with the PBP-N model showing stronger validation performance (AUC = 0.78).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36029522", "locator": "sections[0] \"Abstract\" paragraph 6", "quote": "The two most efficient protocols (using polymer-based precipitation (PBP): PBP-M and PBP-N) were used to obtain two predictive models (based on three miRNAs) allowing us to distinguish between an implantative and non-implantative endometrium."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Two three-miRNA models derived from extracellular-vesicle-enriched endometrial fluid distinguished implantative from non-implantative endometrium, with the PBP-N model showing stronger validation performance (AUC = 0.78).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36029522"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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Small RNA sequencing was performed to determine the most efficien", "As than the PBP-N procedure (Fig. 3A). Small RNA-Seq analysis of the RNA obtained using PBP-N and", "e two methods (Fig. 3B). Moreover, the small RNA-Seq analysis of fractions F3 and F4 detected 204", "number of unique miRNAs detected using small RNA-Seq for each method and the number of miRNAs com"], "order_basis": "paper_text_order:1855", "id": "assay:1"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["13 miRNAs suitable for further validation by qPCR in the same samples. In the case of PBP-N, f", "= 30), obtained using the small RNA-Seq and qPCR. The miRNAs selected as internal normalizers", "hree miRNA-based predictive models tested by qPCR in the discovery cohort. 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At the evidence floor the work type comes from title framing and a fixed prior, not from anything in the paper, so the published work-type split should be read as a rough triage signal rather than a measured distribution. The impact is bounded but not removed: since 2026-10-23 the engine excludes floor-confidence records from the shortlist entirely and publishes them separately as held out, so the recommendation is unaffected even though the census is.","status":"unverified","severity":"high"},{"code":"runtime_is_modelled","basis":["Runtime is summed from published per-assay hour figures. 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Records without an assay match currently receive a zero-hour model value.","status":"unverified","severity":"high"},{"code":"signal_score_without_citations","basis":["5,529 of 5,529 records (100.0%) have no citation count from the source metadata."],"claim":"Signal score","gloss":"The signal score uses publication-type weight because the mirror supplied zero citation counts.","detail":"The source supplied no citation counts for any record in this run, so the signal score is publication-type weight only. The citation term of the ranking is inert here, and the shortlist is ordered by publication type alone.","status":"unverified","severity":"high"},{"code":"abstract_absent","basis":["1,667 of 5,529 records (30.2%) carry no abstract at all."],"claim":"Evidence base for classification","gloss":"Some records contain a title and publication type only, defining the available classification evidence.","detail":"Where the mirror contains a title and publication types only, those fields define the classifier evidence. 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The three-way work type remains a diagnostic and is reported separately.","status":"measured","severity":"high"},{"code":"llm_comparison_not_measured","basis":["rule_based_v1+lex99e1195c7d6f produced 5,529 of 5,529 classifications.","Measured on 438 labelled records; these are RULE-BASED figures, not model results."],"claim":"Rule-based versus LLM agreement","gloss":"Every number here is the rule engine’s own. Model comparison begins when a working API credential is connected and measured.","detail":"The published two-way decision agreed with a human reading on 310 of 399 decidable records (77.7%). The diagnostic three-way label agreed on 288 of 390 decidable records (73.9%). Every percentage in this run belongs to the rule engine. Model comparison begins when a working API credential is connected and measured.","status":"not_measured","severity":"high"},{"code":"confidence_is_a_band","basis":["low band: 135 of 210 hand-judged records were correct, 64.3% [57.6, 70.5] (95% CI).","medium band: 80 of 104 hand-judged records were correct, 76.9% [68.0, 84.0] (95% CI).","high band: 73 of 76 hand-judged records were correct, 96.0% [89.0, 98.7] (95% CI).","A fitted calibrated probability was built, measured and withdrawn: it overstated held-out accuracy and reorders nothing."],"claim":"Confidence band and evidence score","gloss":"The confidence band carries a measured accuracy interval; 0.85 represents relative rank strength.","detail":"Confidence on this run is a BAND plus its measured accuracy interval. The number stored alongside each record is a monotone evidence score that orders records; 0.85 represents relative rank strength. A fitted probability was withdrawn after it overstated held-out accuracy. Threshold on the band.","status":"measured","severity":"medium"},{"code":"three_way_split_is_diagnostic","basis":["The corpus is published at the two-way decision: automatable or not-automatable. The three-way split (data_only / physical / mixed) is published as a diagnostic with its measured reliability attached, not as a claim, because the rule engine's `mixed` call cannot be defended.","The engine called 22 record(s) mixed; 10 matched the human judgement (45.5%, 95% CI 26.9-65.3).","The engine's `mixed` call is right on 10/22 hand-judged records (45.5%, 95% CI 26.9%-65.3%); a constant `physical` guess scores 36.4%.","The engine's `mixed` call does not reliably beat a constant `physical` guess on the hand-judged records it labels mixed.","The sign of that difference flips between two independent samples, so the three-way refinement is not demonstrably informative.","The mixed stratum contributes a disproportionate share of errors relative to its size.","At title-only depth the physical/mixed split collapses: a title says that work was done, not whether it was also analysed."],"claim":"The published decision is two-way","gloss":"The three-way split is shown for diagnosis only. The published split is two ways.","detail":"Count and filter the corpus on automatable versus not-automatable. The data_only / physical / mixed split remains an internal engine diagnostic because the mixed call has lower measured reliability.","status":"measured","severity":"medium"},{"code":"automatable_flag_unproven","basis":["6 of 29 assay families are marked automatable now: meta_analysis, machine_learning, survival_analysis, pca, molecular_docking, differential_expression.","The flag is a rule over assay family and work type; validation begins with the first executed replication.","It inherits the 75.2% data_only agreement rate, because the flag requires the record to be analysis-only."],"claim":"Automatable now","gloss":"This flag marks assay families the rules classify as data-only. The first executed replication will validate it.","detail":"This flag marks families the rules consider replicable from data alone. Its validity depends on the analysis-only classification and will be measured through an executed replication.","status":"unverified","severity":"medium"}],"confidence_policy":"band_with_measured_interval","confidence_contract":{"policy":"band_with_measured_interval","summary":"Confidence is reported as a BAND with a measured accuracy interval. The raw evidence score supplies monotone ordering. A fitted point estimate was withdrawn after it overstated held-out accuracy.","evidence_score":"A monotone evidence score in [0,1] built from cue mass, axis separation and text coverage. Use it to order records. Interpret 0.85 as relative rank strength.","confidence_band":"low | medium | high. Consumers threshold on this value.","band_accuracy":"Wilson 95% interval on the measured agreement of the hand-judged records in this band.","calibrated_confidence":"WITHDRAWN. Reintroduction requires held-out evidence demonstrating reliable estimates across every bin."},"band_accuracy":{"low":{"n":210,"low":0.576,"band":"low","high":0.7046,"agree":135,"accuracy":0.6429},"high":{"n":76,"low":0.8903,"band":"high","high":0.9865,"agree":73,"accuracy":0.9605},"medium":{"n":104,"low":0.6795,"band":"medium","high":0.8397,"agree":80,"accuracy":0.7692}},"provider":"rule_based_v1+lex99e1195c7d6f","lexicon_id":"99e1195c7d6f","contract_published_at":"2026-10-23T12:25:29.022232+00:00","confidence_is_band":true,"confidence_is_probability":false,"decision_taxonomy":"two_way","decidable_fraction_two_way":0.8854,"decidable_fraction_two_way_low":0.8565,"decidable_fraction_two_way_high":0.9143,"decidable_fraction_three_way":0.8586,"decidable_fraction_three_way_low":0.8287,"decidable_fraction_three_way_high":0.8884,"decidable_population":5529,"validation_sample_size":438,"three_way_cost_fraction":0.0268,"three_way_cost_records":148,"decision_counts":{"automatable":230,"not_automatable":5299},"decision_split":{"automatable":{"count":230,"share":0.04159884246699222},"not_automatable":{"count":5299,"share":0.9584011575330078}},"diagnostic_work_type_counts":{"mixed":24,"physical":5275,"data_only":230}}}