Zinc Oxide-Loaded Recycled PET Nanofibers for Applications in Healthcare and Biomedical Devices.

Polyethylene terephthalate (PET) is a widely utilized synthetic polymer, favored in various applications for its desirable physicochemical characteristics and widespread accessibility. However, its extensive utilization, coupled with improper waste disposal, has led to the alarming pollution of the environment. Thus, recycling PET products is essential for diminishing global pollution and turning waste into meaningful materials.

Is anti-müllerian hormone useful for monorchidism diagnosis in the tomcat?

Monorchidism is an uncommon condition in tomcats, defined by the congenital absence of one of the testicles. Due to the lack of information regarding possible biomarkers, most monorchidism cases require laparotomy in order to differentiate it from cryptorchidism. Human data suggest that monorchid patients have lower serum anti-Müllerian hormone (AMH) levels when compared to cryptorchids, premises that has been also scrutinized in veterinary medicine.

Interferon signaling is enhanced by ATR inhibition in glioblastoma cells irradiated with X-rays, protons or carbon ions.

Background And Purpose: Interferon (IFN) signaling plays an important role in antitumor immune responses. Inhibitors of the DNA damage response, such as ATR inhibitors, can increase IFN signaling upon conventional radiotherapy with X-rays. However, it is not known whether such inhibitors also enhance IFN signaling after irradiation with high linear energy transfer (LET) particles.

Generative 3D Cardiac Shape Modelling for in-silico Trials.

We propose a deep learning method to model and generate synthetic aortic shapes based on representing shapes as the zero-level set of a neural signed distance field, conditioned by a family of trainable embedding vectors with encode the geometric features of each shape. The network is trained on a dataset of aortic root meshes reconstructed from CT images by making the neural field vanish on sampled surface points and enforcing its spatial gradient to have unit norm. Empirical results show that our model can represent aortic shapes with high fidelity.