Peer-to-peer tele-consultative services for critical care, Afghanistan, Kenya, Pakistan, United Republic of Tanzania.

Objective: To develop a tele-intensive care service providing peer-to-peer teleconsultation for physicians in remote and resource-constrained health-care settings for treatment of critically ill patients, and to evaluate the outcomes of the service.

Methods: The Aga Khan University started the coronavirus disease 2019 (COVID-19) tele-intensive care unit in 2020. A central command centre used two-way audiovisual technology to connect experienced intensive care specialists to clinical teams in remote hospital settings.

Evaluating the efficacy of nano-cyclosporine A in mice model of ulcerative colitis: a meta-analysis.

Cyclosporine A is an immunosuppressive drug used in clinics to treat steroid-refractory ulcerative colitis (UC). However, due to its side effects, researchers are evaluating novel drug delivery-based treatment options. Nanoparticles-based cyclosporine (Nano-CSA) offers a promising option for the treatment of UC, and various in vivo studies on animals have been conducted.

Preclinical Evaluation of [ F]P4B-2412 as Phosphodiesterase 4B Radioligand for Positron Emission Tomography Imaging.

Phosphodiesterase 4B (PDE4B) plays a critical role in cAMP hydrolysis and is highly expressed in brain regions associated with neuroinflammation and central nervous system (CNS) disorders. Selective PDE4B radioligands hold significant potential for elucidating disease mechanisms, such as those in Parkinson's disease and schizophrenia, and enabling target occupancy measurements. In this study, we developed [ F]P4B-2412, a novel PDE4B-selective radioligand, and evaluated its utility for positron emission tomography imaging (PET).

Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders.

Although the Transformer architecture has established itself as the industry standard for jobs involving natural language processing, it still has few uses in computer vision. In vision, attention is used in conjunction with convolutional networks or to replace individual convolutional network elements while preserving the overall network design. Differences between the two domains, such as significant variations in the scale of visual things and the higher granularity of pixels in images compared to words in the text, make it difficult to transfer Transformer from language to vision.