Biology subjects

Moussa, H.

Publications and source records attributed to Moussa, H..

3 recordsLinked to original sources

bioRxiv2025

Chitosan-Polyphosphate Scaffold Loaded with Copper for Endodontic Regeneration: A Laboratory Study

ObjectiveRegenerative endodontics procedures show promise in treating immature teeth with necrotic pulp and apical periodontitis. This procedure involves the replacement of damaged and infected pulp tissue with viable tissue that restores the normal tooth structure and function. Antimicrobials are currently used to control the infection; however, they are cytotoxic to stem cells of the apical papilla (SCAP) and can lead to root canal calcification. Management of these teeth requires a scaffold that can control root canal infection, wick the blood into the canal, and support the viability and differentiation of SCAP while inhibiting intracanal calcification. This study aims to develop a composite scaffold made of polyphosphate, a calcium binding inorganic polymer shown to promote cell proliferation and tissue regeneration, chitosan, a natural antimicrobial polymer that supports stem cell viability and activity, and copper, a metal ion with bactericidal properties. MethodologyThe scaffold was prepared by adding copper (Cu) to chitosan solution, followed by polyphosphate. The resulting scaffold was then freeze-dried and analyzed for elemental composition, chemical structure, release of Cu, antibacterial properties, cytotoxicity, as well as differentiation and mineralization assays. Data were analysed by a two-way analysis of variance (ANOVA) followed by the Tukey post hoc test. ResultThis study demonstrates that, by combining polyphosphate and chitosan, we could fabricate a scaffold that inhibits bacterial growth by 40 % and supports the viability of fibroblast and SCAP. Adding copper to this scaffold further increased bacterial growth inhibition by up to 68% while preserving cell viability. The immunocytochemistry and Alizarin Red staining revealed that this scaffold also supports the odontogenic differentiation of these stem cells while inhibiting their mineralization potential. Furthermore, this scaffold can be fabricated as a 3D cone-shaped scaffold with a strong vertical wicking ability at a rate of 0.5 mm/s and excellent degradability, with 53 % of the scaffold degraded after 28 days. ConclusionsThis study shows that a copper-loaded chitosan-polyphosphate scaffold combines biocompatibility, antibacterial activity, wicking ability, and biodegradability and has great potential as an endodontic regenerative scaffold.

bioengineering↗

bioRxiv2024

Predicting Primary Graft Dysfunction in Lung Transplantation: Machine Learning-Guided Biomarker Discovery

BACKGROUNDThere is an urgent need to better understand the pathophysiology of primary graft dysfunction (PGD) so that point-of-care methods can be developed to predict those at risk. Here we utilize a multiplex multivariable approach to define cytokine, chemokines, and growth factors in patient-matched biospecimens from multiple biological sites to identify factors predictive of PGD. METHODSBiospecimens were collected from patients undergoing bilateral LTx from three distinct sites: donor lung perfusate, post-transplant bronchoalveolar lavage (BAL) fluid (2h), and plasma (2h and 24h). A 71-multiplex panel was performed on each biospecimen. Cross-validated logistic regression (LR) and random forest (RF) machine learning models were used to determine whether analytes in each site or from combination of sites, with or without clinical data, could discriminate between PGD grade 0 (n = 9) and 3 (n = 8). RESULTSUsing optimal AUROC, BAL fluid at 2h was the most predictive of PGD (LR, 0.825; RF, 0.919), followed by multi-timepoint plasma (LR, 0.841; RF, 0.653), then perfusate (LR, 0.565; RF, 0.448). Combined clinical, BAL, and plasma data yielded strongest performance (LR, 1.000; RF, 1.000). Using a LASSO of the predictors obtained using LR, we selected IL-1RA, BCA-1, and Fractalkine, as most predictive of severe PGD. CONCLUSIONSBAL samples collected 2h post-transplant were the strongest predictors of severe PGD. Our machine learning approach not only identified novel cytokines not previously associated with PGD, but identified analytes that could be used as a point-of-care cytokine panel aimed at identifying those at risk for developing severe PGD.

immunology↗

bioRxiv2023

Maintenance of pig brain function under extracorporeal pulsatile circulatory control (EPCC)

Selective vascular access to the brain is desirable in metabolic tracer, pharmacological and other studies aimed to characterize neural properties in isolation from somatic influences from chest, abdomen or limbs. However, current methods for artificial control of cerebral circulation can abolish pulsatility-dependent vascular signaling or neural network phenomena such as the electrocorticogram even when preserving individual neuronal activity. Thus, we set out to mechanically render cerebral hemodynamics fully regulable to replicate or modify native pig brain perfusion. To this end, blood flow to the head was surgically separated from the systemic circulation and full extracorporeal pulsatile circulatory control (EPCC) delivered via a modified aorta or brachiocephalic artery. This control relied on a computerized algorithm that maintained, for several hours, blood pressure, flow and pulsatility at near-native values individually measured before EPCC. Continuous electrocorticography and brain depth electrode recordings were used to evaluate brain activity relative to the standard offered by awake human electrocorticography. Under EPCC, this activity remained unaltered or minimally perturbed compared to the native circulation state, as did cerebral oxygenation, pressure, temperature and microscopic structure. Thus, our approach enables the study of neural activity and its circulatory manipulation in independence of most of the rest of the organism.

neuroscience↗