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Record W4414192454 · doi:10.1101/2025.09.09.675181

Isolation of functional lysosomes from skeletal muscle

2025· preprint· en· W4414192454 on OpenAlexafffund
Thulasi Mahendran, Anastasiya Kuznyetsova, Neushaw Moradi, David A. Hood

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsSkeletal muscleLysosomeOrganelleMitochondrionAutophagyFunction (biology)MyocyteEnzyme

Abstract

fetched live from OpenAlex

Abstract Lysosomes are membrane-bound organelles responsible for the degradation of damaged or dysfunctional cellular components, including mitochondria. Their acidic internal environment and the presence of an array of hydrolytic enzymes facilitate the efficient breakdown of macromolecules such as proteins, lipids, and nucleic acids. Mitochondria play a critical role in maintaining skeletal muscle homeostasis to meet the energy demands under physiological and pathological conditions. Mitochondrial quality control within skeletal muscle during processes such as exercise, disuse, and injury is regulated by mitophagy, where dysfunctional mitochondria are targeted for lysosomal degradation. The limited understanding of quality control mechanisms in skeletal muscle necessitates the need for isolating intact lysosomes to assess organelle integrity and the degradative functions of hydrolytic enzymes. Although several methods exist for lysosome isolation, the complex structure of skeletal muscle makes it challenging to obtain relatively pure and functional lysosomes due to the high abundance of contractile proteins. Here we describe a method to isolate functional lysosomes from small amounts of mouse skeletal muscle tissue, preserving membrane integrity. We also describe functional assays that allow direct evaluation of lysosomal enzymatic activity and we provide data indicating reduced lysosomal degradative activity in lysosomes from aging muscle. We hope that this protocol provides a valuable tool to advance our understanding of lysosomal biology in skeletal muscle, supporting investigations into lysosome-related dysfunction in aging, disease, and exercise adaptations. New and Noteworthy Lysosomes within skeletal muscle function to degrade dysfunctional debris and initiate retrograde signaling pathways. We developed a method to isolate purified lysosomal fractions using a small portion of skeletal muscle, eliminating the need for density gradients or lysosome-modifying agents, ensuring high lysosomal purity without compromising structure or function. By enabling functional analysis via acid phosphatase, cathepsin-B activity, and calcium release, this approach offers a powerful tool to study lysosomal roles in muscle physiology, disease, and exercise. Graphical Abstract

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

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