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Record W4403624991 · doi:10.1021/acsnano.4c05634

Hydrogel Strategies for Female Reproduction Dysfunction

2024· review· en· W4403624991 on OpenAlexaff
Minxuan Jia, Jia‐Min Wang, Chubing Lin, Qingyan Zhang, Yueguang Xue, Xin Huang, Ren Yan, Chunying Chen, Ying Liu, Yanwen Xu

Bibliographic record

VenueACS Nano · 2024
Typereview
Languageen
FieldMedicine
TopicGynecological conditions and treatments
Canadian institutionsNational Institute for Nanotechnology
FundersNational Key Research and Development Program of ChinaGuangzhou Science and Technology Program key projectsChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsInfertilityReproductive systemFemale infertilityFemale reproductive systemAssisted reproductive technologyReproductive medicineReproductive technologyMedicineReproductive physiologyBioinformaticsPhysiologyBiologyInternal medicinePregnancy

Abstract

fetched live from OpenAlex

Infertility is an important issue for human reproductive health, with over half of all cases of infertility associated with female factors. Dysfunction of the complex female reproductive system may cause infertility. In clinical practice, female infertility is often treated with oral medications and/or surgical procedures, and ultimately with assisted reproductive technologies. Owing to their excellent biocompatibility, low immunogenicity, and adjustable mechanical properties, hydrogels are emerging as valuable tools in the reconstruction of organ function, supplemented by tissue engineering techniques to increase their structure and functionality. Hydrogel-based female reproductive reconstruction strategies targeting the pathological mechanisms of female infertility may provide alternatives for the treatment of ovarian, endometrium/uterine, and fallopian tube dysfunction. In this review, we provide a general introduction to the basic physiology and pathology of the female reproductive system, the limitations of current infertility treatments, and the lack of translation from animal models to human reproductive physiology. We further provide an overview of the current and future potential applications of hydrogels in the treatment of female reproductive system dysfunction, highlighting the great prospects of hydrogel-based strategies in the field of translational medicine, along with the significant challenges to be overcome.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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 head0.096
GPT teacher head0.379
Teacher spread0.283 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations15
Published2024
Admission routes1
Has abstractyes

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