Check Claims Before You Publish

Key evidence supporting scientific strengths

• Breadth and topic focus: Author publishes repeatedly on cancer signaling (PI3K/AKT, Wnt/Notch), cancer stem cells, noncoding RNAs and chemotherapy resistance — reflected by multiple review and original articles across 2011–2024 (representative works cited below).
• Impactful reviews: Several reviews (open‑access in respectable journals) have accrued moderate-to-high citations, e.g., PI3K/AKT & EMT review (157 cites) and ovarian cancer stem cell review (138 cites), indicating influence in niche cancer biology subfields.
• Consistent productivity: Publication counts increase markedly in 2019–2023 (visualized above), suggesting an active and sustained research program.

Representative high-quality works (direct evidence)

1. PI3K/AKT signaling pathway as a critical regulator of epithelial-mesenchymal transition in colorectal tumor cells (2023) — last author M. Moghbeli; open access review synthesizing PI3K/AKT roles in EMT and metastasis; extensive reference list (n=181) and 157 citations to date, useful for assessing the author's domain expertise in signaling and EMT.

   PI3K/AKT EMT review

2. Ovarian cancer stem cells and targeted therapy (2019) — Moghbeli as a middle author; broad, clinically oriented review with 138 citations supporting the author’s involvement in stem-cell and therapy-resistance literature.

   Ovarian cancer stem cells review

3. Role of SALL4 in the progression and metastasis of colorectal cancer (2013) — middle author on original research; 83 citations indicate contribution to molecular oncology literature.

   SALL4 colorectal cancer article

4. Cancer stem cell detection and isolation (2014) — first author; review focused on CSC detection methodologies; contributes to methodological understanding in the field.

   CSC detection review

5. Long non-coding RNAs as regulators of doxorubicin resistance (2021) — last author; review on lncRNA-mediated chemoresistance mechanisms with 75 citations, showing involvement in noncoding RNA and therapy resistance networks.

   lncRNAs and doxorubicin resistance review

Critical appraisal — strengths, limitations, and blind spots

• Strengths: Consistent thematic focus (cancer signaling, stem cells, ncRNAs, therapy resistance), frequent review synthesis (useful for the field), several well-cited papers indicating influence in specialized subfields.
• Limitations: Heavy reliance on narrative reviews (limits reproducibility and increases selection bias), fewer large-scale original clinical/translational datasets in lead-author position visible in top-cited works, and many findings summarized are dependent on heterogeneous in vitro models and require in vivo/clinical validation (explicitly noted in those reviews) — these limitations reduce direct translational strength.
• Potential biases/blindspots: Narrative review format invites citation/selection bias and positive-result bias; the published work focuses on mechanistic/marker studies often reliant on cell lines and small cohorts — common pitfalls include overgeneralization from cell-line models to human disease and lack of pre-registered protocols or meta-analytic synthesis.

What would change the assessment?

• Stronger evidence that would raise scientific score: prospective clinical validation of proposed markers/pathways, robust in vivo models demonstrating therapeutic benefit, or leading multi‑center trials of interventions based on the reviewed mechanisms.
• Evidence that would lower confidence: retractions, reproducibility failures in key mechanistic papers, or demonstration that major conclusions rest on irreproducible in vitro artifacts.

Quick methodological recommendations for the author (to increase rigor & translational impact)

1. Adopt systematic-review or meta‑analytic methods where feasible to reduce selection bias in literature syntheses.
2. Lead or co‑lead multi‑center studies or consortia to collect larger clinical cohorts for biomarker validation.
3. Prioritize mechanistic papers that combine robust in vivo models with orthogonal validation (protein, functional assays, patient-derived xenografts, and clinical correlative data).