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Record W4414161440 · doi:10.1371/journal.pone.0332025

Gene expression alterations in testicular biopsies from males with spermatogenesis arrest identified by transcriptome analysis

2025· article· en· W4414161440 on OpenAlexaff
Osamah Batiha, Esra’a Al‐zoubi, Rowida Almomani, Mohammad A. Al Smadi, Sura Al-Rawabdeh, Omar Alshokaibi, Hussam Abu-Farsakh, Abedalrhman Alkhateeb, Masood Abu‐Halima

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsLakehead University
FundersDeanship of Research, Jordan University of Science and Technology
KeywordsTranscriptomeSpermatogenesisDownregulation and upregulationGeneGene expressionMale infertility

Abstract

fetched live from OpenAlex

Spermatogenesis is a complex biological process encompasses several stages of cellular divisions, ultimately resulting in producing mature spermatozoa capable of fertilization. Numerous factors involved in the precise regulation of the spermatogenesis, and any disruptions or alterations in these regulatory mechanisms can lead to spermatogenesis arrest, which may result in male infertility. Among these factors, genetic influences play essential role in regulating the process. This study aimed to identify genes that are differentially expressed in relation to spermatogenesis arrest. Testicular biopsy samples were collected from 22 non-obstructive azoospermic patients diagnosed with spermatogenesis arrest (cases) and nine obstructive azoospermic patients (controls). RNA sequencing (RNA-seq) was performed on five samples from the 22 non-obstructive azoospermic patients and compared to previously published transcriptomic data from obstructive azoospermic patients, which served as the control group. Differential expression analysis of the RNA-seq data identified 1,915 differentially expressed genes, comprising 337 upregulated and 1,578 downregulated genes. Among these, several key candidate genes were identified for further analysis, including the upregulation of FOS, FOSB, RGS1, and CXCL8, as well as the downregulation of TNP2, SPRR2C, LINC02314, and C16orf78. RT-qPCR validation confirmed the RNA-seq findings for these genes in the tested samples. Subsequently, RT-qPCR was performed on the remaining 17 non-obstructive (n = 17) and obstructive azoospermic samples (n = 9) collected in this study. The results from these additional samples were consistent with the RNA-seq data, further supporting the findings. Using gene ontology (GO) analysis and published literature, we linked these genes with spermatogenesis arrest, identifying promising targets that could serve as potential biomarkers for this condition in the future.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.029
GPT teacher head0.235
Teacher spread0.205 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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