ABSTRACT
Dipeptidyl-peptidase-like protein 6 (DPPX) antibody-mediated encephalitis is a rare type of autoimmune encephalitis (AE), which mainly manifests as diarrhea accompanied by weight loss, cognitive decline, epileptic seizures, and even psychiatric symptoms. Remarkably, it is also reported to be associated with tumors, predominantly B-cell lymphoma. Overall, the AE remains uncharacterized clinically and its long-term prognosis remains elusive. Herein, we report the first case of DPPX antibody-mediated AE secondary to breast cancer. Importantly, it substantially improves after aggressive immunotherapy. Our case highlights DPPX antibody-mediated AE as a paraneoplastic syndrome and discusses the pearls in its diagnosis and management.
ABSTRACT
Ultralong organic phosphorescence (UOP) materials have attracted considerable attention in recent years. Herein, a new type of flexible films is fabricated by doping amphipathic pyrene tetrasulfonic acid sodium salts into amorphous poly(vinyl alcohol) matrix, which enables the realization of color-tunable UOP spanning from orange-red to green after excitation light is switched off. Interestingly, precise control of the proportion of isolated-molecular and aggregated-state phosphorescence is demonstrated for colorful afterglow using photo-activation. An increase in the dynamic phosphorescence lifetime of isolated molecules is observed from 894.75 to 1735.71 ms following an 8 min irradiation under ambient conditions. The photo-activation, however, showed little influence on aggreated-state phosphorescence. This flexible and processable film exhibits versatile applications in multicolor afterglow displays, ultraviolet detection, multilevel information encryption, etc. This study not only provides a strategy for the rational regulation of UOP colors but also expands the application potential of color-tunable UOP materials.
ABSTRACT
Glioma is one of the most fatal primary brain tumors, and it is well-known for its difficulty in diagnosis and management. Medical imaging techniques such as magnetic resonance imaging (MRI), positron emission tomography (PET), and spectral imaging can efficiently aid physicians in diagnosing, treating, and evaluating patients with gliomas. With the increasing clinical records and digital images, the application of artificial intelligence (AI) based on medical imaging has reduced the burden on physicians treating gliomas even further. This review will classify AI technologies and procedures used in medical imaging analysis. Additionally, we will discuss the applications of AI in glioma, including tumor segmentation and classification, prediction of genetic markers, and prediction of treatment response and prognosis, using MRI, PET, and spectral imaging. Despite the benefits of AI in clinical applications, several issues such as data management, incomprehension, safety, clinical efficacy evaluation, and ethical or legal considerations, remain to be solved. In the future, doctors and researchers should collaborate to solve these issues, with a particular emphasis on interdisciplinary teamwork.
