A Contemporary Review of Trachea, Nose, and Ear Cartilage Bioengineering and Additive Manufacturing.

The complex structure, chemical composition, and biomechanical properties of craniofacial cartilaginous structures make them challenging to reconstruct. Autologous grafts have limited tissue availability and can cause significant donor-site morbidity, homologous grafts often require immunosuppression, and alloplastic grafts may have high rates of infection or displacement. Furthermore, all these grafting techniques require a high level of surgical skill to ensure that the reconstruction matches the original structure. Current research indicates that additive manufacturing shows promise in overcoming these limitations. Autologous stem cells have been developed into cartilage when exposed to the appropriate growth factors and culture conditions, such as mechanical stress and oxygen deprivation. Additive manufacturing allows for increased precision when engineering scaffolds for stem cell cultures. Fine control over the porosity and structure of a material ensures adequate cell adhesion and fit between the graft and the defect. Several recent tissue engineering studies have focused on the trachea, nose, and ear, as these structures are often damaged by congenital conditions, trauma, and malignancy. This article reviews the limitations of current reconstructive techniques and the new developments in additive manufacturing for tracheal, nasal, and auricular cartilages.

Categorical versus dimensional approaches to autism-associated intermediate phenotypes in 22q11.2 microdeletion syndrome.

BACKGROUND: 22q11.2 Microdeletion syndrome (22q11DS) is associated with elevated rates of autism spectrum disorders (ASDs), although the diagnosis is controversial. In order to determine whether there is a biological substrate of ASD in 22q11DS, we examined neurocognitive and structural neuroanatomic differences between those with 22q11DS and an ASD diagnosis (22q11DS-ASD+) and those with 22q11DS without ASD (22q11DS-ASD-); we then determined whether these differences were better characterized within a categorical or dimensional framework. METHODS: We collected multiple neurocognitive measures and high-resolution T1-weighted scans on 116 individuals (29 22q11DS-ASD+, 32 22q11DS-ASD-, 55 typically developing controls) between 6 and 26 years of age. Measures of subcortical volume, cortical thickness (CT), and surface area were extracted using the FreeSurfer image analysis suite. Group differences in neurocognitive and neuroanatomic measures were assessed; regression analyses were then performed to determine whether a categorical or dimensional measure of ASD was a better predictor of neurocognitive impairment and/or neuroanatomic abnormalities observed in 22q11DS-ASD+. RESULTS: In comparison to 22q11DS-ASD-, 22q11DS-ASD+ participants exhibited decreased bilateral hippocampal CT and decreased right amygdala volumes. Those with 22q11DS-ASD+ also showed slowed processing speed and impairments in visuospatial and facial memory. Neurocognitive impairments fit a dimensional model of ASD, whereas reductions in parahippocampal CT were best explained by a categorical measure of ASD. CONCLUSIONS: A combination of categorical and dimensional measures of ASD may provide the most comprehensive understanding of ASDs in 22q11DS.