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Re: Moving towards <i>in situ</i> tracheal regeneration: the bionic tissue engineered transplantation approach <i>J. Cell. Mol. Med.</i> Vol. 14, No. 7, 2010, pp. 1877–1889

2010· letter· en· W4235584950 on OpenAlexaff
Siba Haykal, Thomas K. Waddell, Stefan O.P. Hofer

Bibliographic record

VenueJournal of Cellular and Molecular Medicine · 2010
Typeletter
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDecellularizationTissue engineeringRegenerative medicineRegeneration (biology)TransplantationExtracellular matrixCartilageMesenchymal stem cellBiomedical engineeringPathologyStem cellAnatomyCell biologyMedicineBiologySurgery

Abstract

fetched live from OpenAlex

Malignancy, subglottic stenosis and traumatic injury to the trachea require surgical resection. When short segments are involved, primary re-anastomosis affords excellent results. Longer lesions, involving more than half of the tracheal length in adults or one third of the tracheal length in children, require novel solutions for surgical repair. In this paper, Bader and Macchiarini review the history of tracheal reconstruction, the failed attempts at tracheal replacements using prosthetic materials, autografts and allografts and the problems faced with reepithelialization, revascularization, maintenance of cartilage integrity and immunogenicity. More specifically, they describe their regenerative approach to tracheal replacement involving the use of an ‘immunotolerant’ decellularized donor trachea repopulated with recipient mesenchymal stem cell derived chondrocytes and bronchial epithelial cells using a manufactured bioreactor and more recently, the bionic airway tissue-engineered replacement. This tissue-engineered tracheal approach shows great promise; however, a few concepts surrounding methodology should be questioned. Decellularized tissues/ organs have been widely used to yield natural scaffolds for tissue engineering and regenerative medicine purposes. Decellularization literature implies that an ideal decellularization technique is tissue/organ specific, includes a combination of physical, chemical and enzymatic approach allowing lysis of cell membrane, separation and solubilization of cellular components and removal of cellular debris [1]. This needs to be accomplished without significant disruption to the extracellular matrix (ECM) components in order to maintain biochemical composition, morphology and behaviour of the tissue/ organ. Sodium deoxycholate, an ionic detergent, was initially used to isolate pure kidney glomerular, tubular, retinal and brain blood vessel basement membranes. Autolysis of the tissue with distilled water and a treatment with DNAse were necessary to prevent agglutination of the tissue upon contact with this detergent [2]. Despite the authors’ claim of the efficiency of this detergent in both porcine jejunal segment [3] and tracheal decellularization in comparison with other protocols, quantification of ECM components such as glycosaminoglycans, collagen, elastin and laminin before and after decellularization would be helpful in establishing its true efficacy at maintaining tracheal structure. The preservation of function of decellularized organs is a key concept in this area of research. Repetitive cycles of their detergent-enzymatic method, ranging from 17 cycles for porcine tracheas to 25 cycles for human tracheas, allowed for preservation of biomechanical strength and induced loss of antigenicity. Structural integrity of these tracheal grafts was measured only by using a tensile-test device and exposing tracheas to increasing uniaxial force where, the tracheal rupture point was measured [4]. Clinically important characteristics of tracheal function are more dependent on tracheal collapsibility and studies should probably focus on measuring tracheal compliance instead. In addition, immunogenicity of tracheal grafts in this porcine model was assessed by using immunohistochemical methods to determine the number of cycles required, in combination with the expression of an inflammatory marker and the development of anti-pig leucocyte antigen antibodies in mice implanted with porcine bioengineered tracheas [4]. Immunogenicity in their clinical transplantation was assessed by immunostaining for Major Histocompatibility Complex Class I (MHCI) and Major Histocompatibility Complex Class II (MHCII) markers on tracheal sections following decellularization [5]. The authors also do not comment on immune response directed to recellularized tracheal allografts despite the growing evidence of the immunomodulatory role of mesenchymal stem cells [6]. Theoretically, ECM components are considered to be conserved between species and individuals; however, inflammatory reactions and hyperacute rejection to these natural scaffolds have been reported [7] and traditional histological methods are far too simplistic to predict long term remodelling outcome. Finally, the authors propose bionic airway tissue-engineered replacement, to avoid in vitro cell seeding and culture of these cells within a bioreactor before surgical implantation. Despite having been quoted by the authors to have important advantages for regulatory, financial and clinical sustainability of tissue engineering technologies, it should be noted that this method has not been attempted in their animal model and the fate of the mesenchymal stromal cells and epithelial cells seeded on these grafts has yet to be determined. Importantly, this paper nicely reviews the concept of producing immunotolerant tissues/organs for transplantation and extends the promise for applications of regenerative and tissue-engineered therapies. The authors have no conflicts of interest.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.004

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 head0.222
Teacher spread0.213 · 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 designNot applicable
Domainnot available
GenreCommentary

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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Citations2
Published2010
Admission routes1
Has abstractyes

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