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Record W4205629395 · doi:10.15252/embj.2020106825

Hypophosphorylated pRb knock‐in mice exhibit hallmarks of aging and vitamin C‐preventable diabetes

2022· article· en· W4205629395 on OpenAlexafffund
Zhe Jiang, Huiqin Li, Stephanie A. Schroer, Véronique Voisin, YoungJun Ju, Marek Pacal, Natalie Erdmann, Wei Shi, Philip E.D. Chung, Tao Deng, Nien‐Jung Chen, Giovanni Ciavarra, Alessandro Datti, Tak W. Mak, Lea Harrington, Frederick A. Dick, Gary D. Bader, Rod Bremner, Minna Woo, Eldad Zacksenhaus

Bibliographic record

VenueThe EMBO Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsWestern UniversityUniversité de MontréalInstitute for Research in Immunology and CancerPrincess Margaret Cancer CentreSinai Health SystemLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of TorontoUniversity Health Network
FundersNational Center for Research ResourcesNational Institute of General Medical SciencesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsBiologyEndocrinologyInternal medicinePhosphorylationRetinoblastoma proteinCell cycleKnockout mouseCell biologyApoptosisMedicineGenetics

Abstract

fetched live from OpenAlex

In this manuscript Jiang et al present findings pointing towards a role of pRb N-terminal phosphorylation in b-cell proliferation.They develop de RbDK7 mice, which show increased fasting glucose from age 3 months, and abnormal glucose homeostasis and decreased pancreatic islet size with aging (more than 6 months).The authors state that this phenotype is due to increased DNA-damage response and senescence in pancreatic beta cells, and identify Vitamin C enriched diet, as a means to revert their phenotype.This is indeed novel, as the role of the phosphorylation of pRb directly, has never been described in vivo, and this to my knowledge the 1st mouse model allowing it.Despite being rather well written, I find the data presented rather confusing, since the authors show a lot of results not related to their phenotype, and lack in my opinion key experiments to support their main claims.In addition, the results (in the figures) are shown in a disorganized manner, and lack key details.Out of all the images (IHC, IF, telomeres, SA-Beta-Gal), only figure 2E and 7E show scale bars, and more than half of the images have no quantification at all, despite n>3 indicated in figure legends for most experiments.Finally, the authors describe their main findings in beta-cells, but use a plethora of models, ranging from thymocytes, splenocytes, MEFs, retina, myotubes and even a breast cancer model (PyMT).I believe the findings done in those models to be of certain relevance, but they could be moved to supplementary images to free space for the findings needed to support the author's main finding.Major concerns:1.The author's main finding is that the homozygous presence of RbDK7 causes diabetes, and prevents pancreatic beta cells from proliferating, however, the "gold-standard" assay of streptozotocin [STZ]-induced diabetes was not performed.In addition, there is no figure showing an actual defect in either circulating insulin levels, or glucose/feeding induced insulin secretion.Similarly, no insulin IHC or IF is shown comparing RbDK7 and WT mice ( corresponding to Figure 5D), with the except from the single image from 14.5 pregnant female mice in Figure 5G.Importantly, insulin is not part of the differentially regulated genes identified by microarray when comparing RbDK7 and WT mice pancreatic islets.2. Glucose induced Insulin secretion from isolated mice was not measured either.3. The authors claim that the diabetic phenotype RbDK7 mice is aging dependent, but if I understood correctly, most molecular and histological analysis were performed well before the phenotype appears, suggesting that other tissues than pancreatic islets are touched.By observing the single radiograph shown in figure 4D and the single skin H-E staining shown in figure 5F, I would imagine that RbDK7 mice also have enlarged liver and lipodystrophy, with total loss of skin adipose tissue.Unfortunately, the age of the animals used for those figures is not specified in the manuscript.4. Similarly, the authors claim that the diabetic phenotype observed in RbDK7 mice is due to an increased senescence in beta cells, however, the senescence in pancreatic islets cells is not actually measured (SA-Bgal, secretion or protein of SASP proteins), see PMID 3079928. 5.Many figures lack scale bars, quantifications (and thus statistics), and clear indications of whether independent experiments were performed, making it difficult to estimate data quality/reliability. 6.Similarly, for the main findings, concerning glucose homeostasis, insulin levels, and pancreatic beta cells, the age and sex of the mice is not clearly specified in the legends or the methods (it is only specified that GSIS, ITT and GTT were performed using male mice, does it mean females were used for histology and microarray?).In addition, whereas clear differences in glucose levels are not shown before 3 months old, the analysis of pancreatic sections is performed in 10day old mice or "young mice" in others, when even specified.This is especially important since the size of pancreatic islet is known to change with age ( PMID 32005707 and PMID 27284112, and the islets of RbDK7 do not actually decrease in size (Fig 5D), they rather do not show the published age dependent expansion, and even more since the authors use islet size as a readout for islet fitness.7. Some key experiments are not at all described in the methods section, like the islet isolation and the microarray analysis.Other experiments are never detailed.Numerous key experimental details are not written, making it unlikely that the data can be reproduced in other labs.8. Some panels show no clear staining, yet the authors draw negative conclusions: KIR6.2 in fig S5 and pS15-p53 in fig S6.Minor concerns: • The panels in Figure 3H appear inverted.• The authors state that no difference in myogenesis is observed, despite only showing single images that actually point to 1: a defective myogenesis protocol in vitro, 2: a decrease of myotube differentiation in vitro, 3: a decreased in myotube thickness in vivo.The authors should either measure myogenesis properly, or remove this data from the paper, since it does not really relate to the main finding.( see PMID 23868259 and PMID 19001499) • The experiment in figure 7A should be repeated several times, to be of sufficient quality for publication.• What is stained red and green in figure 6G middle panels?• The authors should at least discuss why, despite observing, according to their own words decreased proliferation, no cell cycle/proliferation gene seems to be differentially expressed in their microarray.• The authors mention abnormal islet morphology in their discussion but show no data about that in the results section.• The authors mention loss of beta cell organization in their discussion but show no data about that in the results section.• The authors should show a survival curve of RbDK7 and WT male and female mice, to further support their premature aging clam.Referee #2: This manuscript presents an interesting mouse genetic model to study the effects of retinoblastoma protein (Rb) phosphorylation in vivo.The Rb tumor suppressor protein has been well studied for its role in various cellular processes and cancer, and its inactivation through Cdk phosphorylation is a critical mechanism driving normal and cancer cell proliferation.The authors rightly point out that to date all studies of the implications of Rb phosphorylation have been performed in vitro, and this study is the first to probe deficiencies that occur in vivo specifically from a lack of Rb phosphorylation at several sites.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.009
GPT teacher head0.228
Teacher spread0.219 · 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 designBench or experimental
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".

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Citations21
Published2022
Admission routes2
Has abstractno

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