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Record W4361002707 · doi:10.7759/cureus.36736

Comparison of Histological Changes in Tissue Specimens Kept in Tap Water, River Water and Seawater for Different Intervals of Time

2023· article· en· W4361002707 on OpenAlexaff
Mimansha Patel, Asha Saroja Peyyeti, Subhasini Singh, Manu Gupta, Mrigakshi Yadav, B Renuka, Ramanpal Singh

Bibliographic record

VenueCureus · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsTap waterMedicineH&E stainStainingConnective tissueSeawaterTime of deathPathologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Forensic pathologists find it difficult to ascertain the actual reason for death and the actual mode of death in drowning cases. It is commonly acknowledged that not all people whose dead bodies are found in water perished from drowning. The medico-legal inquiry includes an important component that examines dead bodies collected from the water. The corpse's time in the water continues to be the main concern. This aids in determining the time of death, which is crucial to any medico-legal investigation. The traditional histological analysis of hematoxylin and eosin (H&E)-stained oral soft tissue can be crucial in the assessment of this feature. Hence, this study was done to compare histological changes in the tissue specimens kept in tap water, river water, and seawater for different intervals of time. MATERIALS AND METHODS: One hundred eighty specimens were obtained from 180 dead bodies and divided randomly into three categories. Category A consisted of 60 specimens submerged in tap water, Category B of 60 specimens submersed in river water, and Category C consisted of 60 specimens submerged in seawater. The specimens underwent routine histological processing and H&E staining. The microscopic evaluation of specimens was carried out at two hours and on the first, second, third, fourth, and fifth days of submersion. Details were recorded regarding the structural changes, cellular changes, connective tissue changes, changes in the basement membrane, and intensity of H&E staining. Once the process of routine histological processing and H&E staining was completed for each study specimen, an evaluation of microscopic changes in the tissue was made. RESULTS: The present study revealed that seawater preserved tissue best and for a longer period than river water and tap water. River water preserved tissue better than tap water. In pathologic tissue, details were preserved for much longer. It was noted that in squamous cell carcinoma, connective tissue was destroyed earlier than epithelium, in contrast to normal tissue where epithelium was destroyed before connective tissue. CONCLUSION: This study indicates that the medium of submersion in drowning victims affects the histopathological features. The time of death is an important aspect of forensic investigation. Considering this, all cases of drowning should be very carefully evaluated, and the medium taken into consideration while determining the time of death, as tissue degrades faster in freshwater than in seawater.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.077
GPT teacher head0.326
Teacher spread0.249 · 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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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