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Record W1533276971 · doi:10.5772/54142

Alignment of Cells and Extracellular Matrix Within Tissue- Engineered Substitutes

2013· book-chapter· en· W1533276971 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInTech eBooks · 2013
Typebook-chapter
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsMcGill UniversityUniversité LavalCentre hospitalier de l'Université LavalNational Research Council CanadaCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsExtracellular matrixMatrix (chemical analysis)Cell biologyMaterials scienceBiologyComposite material

Abstract

fetched live from OpenAlex

Most of the cells in our body are in direct contact with extracellular matrix (ECM) components which constitute a complex network of nano-scale proteins and glycosaminoglycans. Those cells constantly remodel the ECM by different processes. They build it by secreting different proteins such as collagen, proteoglycans, laminins or degrade it by producing factors such as matrix metalloproteinase (MMP). Cells interact with the ECM via specific receptors, the integrins [1]. They also organize this matrix, guided by different stimuli, to generate patterns, essential for tissue and organ functions. Reciprocally, cells are guided by the ECM, they modify their morphology and phenotype depending on the protein types and organization via bidirectional integrin signaling [2-4]. In the growing field of tissue engineering [5], control of these aspects are of the utmost importance to create constructs that closely mimic native tissues. To do so, we must take into account the composition of the scaffold (synthetic, natural, biodegradable or not), its organization and the dimension of the structure. The particular alignment patterns of ECM and cells observed in tissues and organs such as the corneal stroma, vascular smooth muscle cells (SMCs), tendons, bones and skeletal muscles are crucial for organ function. SMCs express contraction proteins such as alpha-smoothmuscle (SM)-actin, desmin and myosin [6] that are essential for cell contraction [6]. To result in vessel contraction, the cells and ECM need to be organized in such a way that most cells are elongated in the same axis. For tubular vascular constructs, it is suitable that SMCs align in the circumferential direction, as they do in vivo [7, 8]. Another striking example of alignment is skeletal muscle cells that form long polynuclear cells, all elongated in the same axis. Each cell generates a weak and short contraction pulse but collectively, it results in a strong, long and sustained contraction of the muscle and, in term, a displacement of the member. In the corneal stroma, the particular arrangement of the corneal fibroblasts (keratocytes) and ECM is essential to keep the transparency of this tissue [9-13]. Tendons also present a peculiar matrix alignment relative to the muscle axis. It gives a substantial resistance and exceptional mechanical properties to the tissue in that axis [14, 15]. Intervertebral discs [16], cartilage [17], dental enamel [18], and basement membrane of epithelium are other examples of tissues/organs that present peculiar cell and matrix organization. By reproducing and controlling those alignment patterns within tissue-engineered substitutes, a more physiological representation of human tissues could be achieved. Taking into account the importance of cell microenvironment on the functionality of tissue engineered organ substitutes, one can assume the importance of being able to customise the 3D structure of the biomaterial or scaffold supporting cell growth. To do so, some methods have been developed and most of them rely on topographic or contact guidance. This is the phenomenon by which cells elongate and migrate in the same axis as the ECM. Topographic guidance was so termed by Curtis and Clark [19] to include cell shape, orientation and movement in the concept of contact guidance described by Harrison [20] and implemented by Weiss [21, 22]. Therefore, if one can achieve ECM alignment, cells will follow the same pattern. Inversely, if cells are aligned on a patterned culture plate, the end result would be aligned ECM deposition [23]. The specific property of tissues or materials that present a variation in their mechanical and structural properties in different axis is called anisotropy. This property can be evaluated either by birefringence measurements [24, 25], mechanical testing in different axis [26], immunological staining of collagen or actin filaments [23] or direct visualisation of collagen fibrils using their self-fluorescence around 488 nm [27, 28]. Several techniques have been recently developed to mimic the specific alignment of cells within tissues to produce more physiologically relevant constructs. In this chapter, we will describe five different techniques, collagen gel compaction, electromagnetic field, electro‐spinning of nanofibers, mechanical stimulation and microstructured culture plates.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.232
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