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Record W7135231873 · doi:10.36253/ijae-3753

A morphometric study of human submandibular gland in type 2 diabetic status

2014· article· W7135231873 on OpenAlexaboutno aff

Bibliographic record

VenueItalian Journal of Anatomy and Embryology · 2014
Typearticle
Language
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsnot available
Fundersnot available
KeywordsSerous fluidDiabetes mellitusSubmandibular glandSalivary glandParenchymaSecretionConnective tissue

Abstract

fetched live from OpenAlex

Diabetes Mellitus Type 2 represents one of the principal diseases that afflict the world population. It is well documented that diabetes affects both morphology and function of several organs. In diabetic rats significant structural changes have been demonstrated in salivary glands, such as accumulation of secretory material and lipid droplets within secretory cells, parenchymal degeneration and its replacement with fibrous connective tissue (1). With regard to human salivary glands, the data are scanty and conflicting. Our work, carried out by light and electron microscopy, is based on the evaluation of the morphological changes which occur in human submandibular glands of diabetic with respect to non diabetic patients. Surgical fragments of glandular tissue were fixed, dehydrated, and processed for light and electron microscopy. Randomly chosen images were analyzed with Image Pro Plus software to record the dimension of acini, serous cells, secretory granules and other variables. Data were analyzed by Student’s t-test and Mann Whitney test. In diabetic glands statistically significant morphological changes were observed, such as enlargement of serous acini and increase of secretory granules area. These results suggest that the secretory activity of human submandibular gland is severely affected by the diabetic status. Obviously these data need to be confirmed with further measurements in order to explain better how diabetes affects human salivary glands. Maria Alberta Lilliu gratefully acknowledges Sardinia Regional Government for the financial support of her PhD scholarship (P.O.R. Sardegna F.S.E. Operational Programme of the Autonomous Region of Sardinia, European Social Fund 2007-2013 - Axis IV Human Resources, Objective l.3, Line of Activity l.3.1.). Michela Isola gratefully acknowledges Sardinia Regional Government for the financial support (P.O.R. Sardegna F.S.E. Operational Programme of the Autonomous Region of Sardinia, European Social Fund 2007-2013 - Axis IV Human Resources, Objective l.3, Line of Activity l.3.1 “Avviso di chiamata per il finanziamento di Assegni di Ricerca”).

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.284
Teacher spread0.269 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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