The impact of nodule size on malignancy risk in indeterminate thyroid nodules.

Background: The association between malignancy risk and nodule size in indeterminate thyroid nodules (ITNs) remains controversial. Thus, we aimed to explore the impact of nodule size as a predictor of cancer in patients with ITNs. Methods: This cross-sectional study assessed 113 patients who underwent surgical intervention for ITNs, comparing two groups based on nodule size (≥4 or <4 cm). The correlation between nodule size and malignancy risk was examined. Other variables of interest included demographics, thyroid-stimulating hormone (TSH) levels, type of surgery, and ultrasound features. Results: Of the 113 patients, 88.5% were aged <55 years, 76.1% were women, and 65.5% had nodules <4 cm. Mean nodule size was 3.4±2.3 cm. There was no significant correlation between malignancy risk and nodule size (P=0.55). An association was observed between <4 cm nodules and elevated TSH levels (P=0.03) and between ≥4 cm nodules and the presence of hypervascularity (P=0.04). Nodules <4 cm were more likely to have extrathyroidal extension, lymphovascular invasion, and positive margins than those ≥4 cm; however, this was not significant. Conclusions: Our findings showed no association between nodule size and malignancy risk, suggesting that size alone is not a predictor of cancer development. Further prospective studies are required to confirm these results.

A Parkinson's disease model composed of 3D bioprinted dopaminergic neurons within a biomimetic peptide scaffold.

Parkinson's disease (PD) is a progressive neurological disorder that affects movement. It is associated with lost dopaminergic (DA) neurons in thesubstantia nigra, a process that is not yet fully understood. To understand this deleterious disorder, there is an immense need to develop efficientin vitrothree-dimensional (3D) models that can recapitulate complex organs such as the brain. However, due to the complexity of neurons, selecting suitable biomaterials to accommodate them is challenging. Here, we report on the fabrication of functional DA neuronal 3D models using ultrashort self-assembling tetrapeptide scaffolds. Our peptide-based models demonstrate biocompatibility both for primary mouse embryonic DA neurons and for human DA neurons derived from human embryonic stem cells. DA neurons encapsulated in these scaffolds responded to 6-hydroxydopamine, a neurotoxin that selectively induces loss of DA neurons. Using multi-electrode arrays, we recorded spontaneous activity in DA neurons encapsulated within these 3D peptide scaffolds for more than 1 month without decrease of signal intensity. Additionally, vascularization of our 3D models in a co-culture with endothelial cells greatly promoted neurite outgrowth, leading to denser network formation. This increase of neuronal networks through vascularization was observed for both primary mouse DA and cortical neurons. Furthermore, we present a 3D bioprinted model of DA neurons inspired by the mouse brain and created with an extrusion-based 3D robotic bioprinting system that was developed during previous studies and is optimized with time-dependent pulsing by microfluidic pumps. We employed a hybrid fabrication strategy that relies on an external mold of the mouse brain construct that complements the shape and size of the desired bioprinted model to offer better support during printing. We hope that our 3D model provides a platform for studies of the pathogenesis of PD and other neurodegenerative disorders that may lead to better understanding and more efficient treatment strategies.

Fabrication of a Lateral Flow Assay for Rapid In-Field Detection of COVID-19 Antibodies Using Additive Manufacturing Printing Technologies.

The development of lateral flow immunoassay (LFIA) using three-dimensional (3D) printing and bioprinting technologies can enhance and accelerate the optimization process of the fabrication. Therefore, the main goal of this study is to investigate methods to speed up the developing process of a LFIA as a tool for community screening. To achieve this goal, an in-house developed robotic arm and microfluidic pumps were used to print the proteins during the development of the test. 3D printing technologies were used to design and print the housing unit for the testing strip. The proposed design was made by taking into consideration the environmental impact of this disposable medical device.