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Record W4385978994 · doi:10.3390/curroncol30080560

Anemia, Iron Deficiency, and Iron Regulators in Pancreatic Ductal Adenocarcinoma Patients: A Comprehensive Analysis

2023· article· en· W4385978994 on OpenAlexvenueno aff
Małgorzata Osmola, Beata Gierej, Katarzyna Mleczko‐Sanecka, Aneta Jończy, Olga Ciepiela, Leszek Kraj, Bogna Ziarkiewicz‐Wróblewska, Grzegorz Basak

Bibliographic record

VenueCurrent Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnemiaHepcidinGastroenterologyFerroportinInternal medicineFerritinImmunohistochemistryIron deficiencyPathology

Abstract

fetched live from OpenAlex

Anemia and iron deficiency (ID) are common complications in patients with pancreatic ductal adenocarcinoma (PDAC), but their underlying causes remain unclear. This study investigated the incidence and characteristics of anemia and micronutrient deficiencies in PDAC patients before initiating chemotherapy. A total of 103 PDAC patients were included, comprising 67 in the palliative and 36 in the adjuvant groups. The overall incidence of anemia was 42.7% (n = 44), with comparable rates in both groups. Normocytic and normochromic anemia were predominant, with mild and moderate cases observed in 32% and 10.7% of the cohort, respectively. ID was evident in 51.4% of patients, with absolute ID more frequent in the adjuvant than in the palliative group (19.4% vs. 13.4%). Functional ID occurred more often in the palliative than in the adjuvant group (41.8% vs. 25%). Vitamin B12 and folate deficiency occurred in <5% (n = 5) of patients. Furthermore, 8.7% (n = 9) of patients had chronic kidney disease and anemia. To elucidate mechanisms of iron deficiency, the study explored the expression of iron regulators (hepcidin (HEP), ferroportin (FPN), and ZIP14 protein) and mitochondrial mass in PDAC tissue with immunohistochemical (IHC) staining and Perl’s Prussian blue to detect iron deposits on available tumor samples (n = 56). ZIP14 expression was significantly higher in less advanced tumors (p = 0.01) and correlated with mitochondrial mass (p < 0.001), potentially indicating its role in local iron homeostasis. However, no significant impact of tissue iron regulators on patient survival was observed. Perl’s Prussian blue staining revealed iron deposits within macrophages, but not in pancreatic duct cells. Furthermore, the GEPIA database was used to compare mRNA expression of iron regulators (HEP, FPN, and ZIP14) and other genes encoding iron transport and storage, including Transferrin Receptor Protein 1 (TfR1) and both ferritin chain subunits (FTH and FTL), in PDAC and normal pancreatic samples. FPN, TfR1, FTH, and FTL showed higher expression in tumor tissues, indicating increased iron usage by cancer. ZIP14 expression was higher in the pancreas than in PDAC and was correlated with FPN expression. The study highlights the importance of baseline iron status assessment in managing PDAC patients due to the high incidence of anemia and iron deficiency. Furthermore, ZIP14, in addition to HEP and FPN, may play a crucial role in local iron homeostasis in PDAC patients, providing valuable insights into the underlying mechanisms of iron dysregulation.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.075
GPT teacher head0.393
Teacher spread0.319 · 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

Citations17
Published2023
Admission routes1
Has abstractyes

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