Hartvigburks5329

Artificial intelligence (AI) has been studied in ophthalmology since availability of digital information in ophthalmic care. The significant turning point was availability of commercial digital color fundus photography in the late 1990s, which caused digital screening for diabetic retinopathy (DR) to take off. Automated Retinal Disease Assessment software was then developed using machine learning to detect abnormal lesions in fundus to screen DR. The use of this version of AI had not been generalized because the specificity at 45% was not high enough, although the sensitivity reached 90%. The recent breakthrough in machine learning is the invent of deep learning, which accelerates its performance to be on par with experts. The first 2 breakthrough studies on deep learning for screening DR were conducted in Asia. The first represented collaboration of datasets between Asia and the United States for algorithms development, whereas the second represented algorithms developed in Asia but validated in different populations across the world. Both found accuracy for detecting referable DR of >95%. Diversity and variety are unique strengths of Asia for AI studies. There are many more studies of AI ongoing in Asia not only as prospective deployments in DR but in glaucoma, age-related macular degeneration, cataract, and systemic disease, such as Alzheimer's disease. Some Asian countries have laid out plans for digital health care system using AI as one of the puzzle pieces for solving blindness. More studies on AI and digital health are expected to come from Asia in this new decade.The Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory coronavirus-2, was first reported in December 2019. The World Health Organization declared COVID-19 a pandemic on March 11, 2020 and as of April 17, 2020, 210 countries are affected with >2,000,000 infected and 140,000 deaths. The estimated case fatality rate is around 6.7%. We need to step up our infection control measures immediately or else it may be too late to contain or control the spread of COVID-19. In case of local outbreaks, the risk of infection to healthcare workers and patients is high. Ophthalmic practice carries some unique risks and therefore high vigilance and special precautions are needed. We share our protocols and experiences in the prevention of infection in the current COVID-19 outbreak and the previous severe acute respiratory syndrome epidemic in Hong Kong. We also endeavor to answer the key frequently asked questions in areas of the coronaviruses, COVID-19, disease transmission, personal protection, mask selection, and special measures in ophthalmic practices. COVID-19 is highly infectious and could be life-threatening. Using our protocol and measures, we have achieved zero infection in our ophthalmic practices in Hong Kong and China. Preventing spread of COVID-19 is possible and achievable.PURPOSE OF REVIEW Is to highlight the recent advances in the diagnosis and management of non-IgE-mediated food allergy which is a common consideration in primary care and in allergy and gastroenterology subspecialty practices evaluating infants. RECENT FINDINGS The review focuses on food protein-induced enterocolitis syndrome (FPIES) and includes other non-IgE-mediated food allergy in nursing infants, food protein-induced allergic proctocolitis, and food protein-induced enteropathy. For FPIES, we review the 2017 International Consensus Guidelines that provided the first comprehensive framework for its diagnosis and management and that were supplemented by a 2019 position paper by the European Academy of Allergy and Clinical Immunology. We review recent reports that support FPIES as a diagnosis of primarily infants, highlight the problem of delayed diagnosis, reveal the need for improved biomarkers, emphasize new and common food protein triggers, and identify new approaches for evaluation of tolerance. SUMMARY As formal diagnostic criteria for non-IgE-mediated food allergies are defined and prevalence data is increasingly reported, there will likely be improved recognition and evaluation of these conditions. Currently, large-scale prospective studies evaluating their incidence and prevalence, associated risk factors, and natural history are needed. Although avoidance of the suspected trigger food protein remains the cornerstone of management, additional studies of underlying pathophysiology and biomarkers of disease will likely reveal new avenues for therapeutics.PURPOSE OF REVIEW Cancer is one of the leading causes of death and the incidence rates are constantly rising. The heterogeneity of tumors poses a big challenge for the treatment of the disease and natural antibodies additionally affect disease progression. The introduction of engineered mAbs for anticancer immunotherapies has substantially improved progression-free and overall survival of cancer patients, but little efforts have been made to exploit other antibody isotypes than IgG. RECENT FINDINGS In order to improve these therapies, 'next-generation antibodies' were engineered to enhance a specific feature of classical antibodies and form a group of highly effective and precise therapy compounds. Advanced antibody approaches include among others antibody-drug conjugates, glyco-engineered and Fc-engineered antibodies, antibody fragments, radioimmunotherapy compounds, bispecific antibodies and alternative (non-IgG) immunoglobulin classes, especially IgE. SUMMARY The current review describes solutions for the needs of next-generation antibody therapies through different approaches. Careful selection of the best-suited engineering methodology is a key factor in developing personalized, more specific and more efficient mAbs against cancer to improve the outcomes of cancer patients. learn more We highlight here the large evidence of IgE exploiting a highly cytotoxic effector arm as potential next-generation anticancer immunotherapy.PURPOSE OF REVIEW Neuropsychiatric lupus (NPSLE) comprises a disparate collection of syndromes affecting the central and peripheral nervous systems. Progress in the attribution of neuropsychiatric syndromes to SLE-related mechanisms and development of targeted treatment strategies has been impeded by a lack of objective imaging biomarkers that reflect specific neuropsychiatric syndromes and/or pathologic mechanisms. The present review addresses recent publications of neuroimaging techniques in NPSLE. RECENT FINDINGS Imaging studies grouping all NPSLE syndromes together are unable to differentiate between NPSLE and non-NPSLE. In contrast, diffusion tensor imaging, FDG-PET, resting, and functional MRI techniques in patients with stable non-NPSLE demonstrate abnormal network structural and functional connectivity and regional brain activity in multiple cortical areas involving the limbic system, hippocampus, frontal, parietal, and temporal lobes. Some of these changes associate with impaired cognitive performance or mood disturbance, autoantibodies or inflammatory proteins.