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Photodynamic therapy (PDT) is a highly effective and widely adopted treatment strategy for many skin diseases, particularly for multiple actinic keratoses (AKs). However, PDT is ineffective in some cases, especially if AKs occur in the acral part of the body. Several methods to improve the efficacy of PDT without significantly increasing the risks of side effects have been proposed. In this study, we reviewed the combination-based PDT treatments described in the literature for treating AKs; both post-treatment and pretreatment were considered including topical (i.e., diclofenac, imiquimod, adapalene, 5-fluorouracil, and calcitriol), systemic (i.e., acitretin, methotrexate, and polypodium leucotomos), and mechanical-physical (i.e., radiofrequency, thermomechanical fractional injury, microneedling, microdermabrasion, and laser) treatment strategies. Topical pretreatments with imiquimod, adapalene, 5-fluorouracil, and calcipotriol were more successful than PDT alone in treating AKs, while the effect of diclofenac gel was less clear. Both mechanical laser treatment with CO 2 and Er:YAG (Erbium:Yttrium-Aluminum-Garnet) as well as systemic treatment with Polypodium leucotomos were also effective. Different approaches were relatively more effective in particular situations such as in immunosuppressed patients, AKs in the extremities, or thicker AKs. Conclusions: Several studies showed that a combination-based approach enhanced the effectiveness of PDT. However, more studies are needed to further understand the effectiveness of combination therapy in clinical practice and to investigate the role of acitretin, methotrexate, vitamin D, thermomechanical fractional injury, and microdermabrasion in humans.

Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis., (© 2022. The Author(s).)

Recently, the zebrafish has been established as one of the most important model organisms for medical research. Several studies have proved that there is a high level of similarity between human and zebrafish genomes, which encourages the use of zebrafish as a model for understanding human genetic disorders, including cancer. Interestingly, zebrafish skin shows several similarities to human skin, suggesting that this model organism is particularly suitable for the study of neoplastic and inflammatory skin disorders. This paper appraises the specific characteristics of zebrafish skin and describes the major applications of the zebrafish model in dermatological research., (© 2022. The Author(s).)

Background: Patients with liver disease may be at increased risk of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection due to immune dysfunction. However, the risk of nosocomial SARS-CoV-2 infection in these patients remains unknown. This study aimed to determine whether patients with liver disease are at an increased risk of nosocomial transmission of SARS-CoV-2 infection upon admission to the hospital for diagnostic or therapeutic procedures., Methods: The study prospectively enrolled 143 patients who were admitted at least once to the hepatology unit at our hospital; 95 patients (66%) were admitted at least twice during the study period. History of past symptomatic SARS-CoV-2 exposure was assessed on the day before hospital admission via an interview. Patients were evaluated for active SARS-CoV-2 infection via real-time reverse transcription-polymerase chain reaction (RT-PCR) performed on nasopharyngeal swabs and tests for serum anti-SARS-CoV-2 immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies., Results: None of the patients enrolled tested positive for SARS-CoV-2 infection by RT-PCR at the first or the second clinical evaluation. One patient who had previously received a liver transplant and who had a history of symptomatic SARS-CoV-2 infection that occurred 4 months before hospital admission tested positive for anti-SARS-CoV-2 IgG but not IgM antibodies at each of the two hospital admissions., Conclusions: The results of our study suggest that patients with liver disease are at no increased risk of nosocomial SARS-CoV-2 infection. These data support the policy of maintaining clinical hospital checks that will be necessary until or possibly even after the completion of the current SARS-CoV-2 vaccination campaign., (© 2022. The Author(s).)

Introduction: Near-Infrared Photoimmunotherapy (NIR-PIT) is a novel molecularly targeted phototherapy. This technique is based on a conjugate of a near-infrared photo-inducible molecule (antibody-photon absorber conjugate, APC) and a monoclonal antibody that targets a tumor-specific antigen. To date, this novel approach has been successfully applied to several types of cancer., Areas Covered: The authors discuss the possible use of NIR-PIT for the management of skin diseases, with special attention given to squamous cell carcinomas, advanced melanomas, and primary cutaneous lymphomas., Expert Opinion: NIR-PIT may be an attractive strategy for the treatment of skin disorders. The main advantage of NIR-PIT therapy is its low toxicity to healthy tissues. Cutaneous lymphocyte antigen is a potential molecular target for NIR-PIT for both cutaneous T-cell lymphomas and inflammatory skin disorders.

Viral diseases are the cause of many global epidemics, leading to deaths, affecting the quality of life of populations, and impairing public health. The limitations in the treatment of viral diseases and the constant resistance to conventional antiviral treatments encourage researchers to discover new compounds. In this perspective, this literature review presents isolated molecules and extracts of natural products capable of inhibiting the activity of the nonstructural protein that acts as the RNA-dependent RNA polymerase. The literature review presented natural compounds with the potential to be tested as alternative medicines or used in the development of synthetic drugs to prevent the replication of RNA viruses, such as COVID-19, hepatitis C, and dengue viruses, among others. Natural products are known to exhibit remarkable activities in mitigation of different viral diseases, in addition, they help to decrease the aggravation of infections. Consequently, reducing hospitalization time and deaths., Competing Interests: Conflict of interestThe authors declare no competing interests., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Alzheimer's disease is the primary cause of dementia worldwide, with an increasing morbidity burden that may outstrip diagnosis and management capacity as the population ages. Current methods integrate patient history, neuropsychological testing and MRI to identify likely cases, yet effective practices remain variably applied and lacking in sensitivity and specificity. Here we report an interpretable deep learning strategy that delineates unique Alzheimer's disease signatures from multimodal inputs of MRI, age, gender, and Mini-Mental State Examination score. Our framework linked a fully convolutional network, which constructs high resolution maps of disease probability from local brain structure to a multilayer perceptron and generates precise, intuitive visualization of individual Alzheimer's disease risk en route to accurate diagnosis. The model was trained using clinically diagnosed Alzheimer's disease and cognitively normal subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (n = 417) and validated on three independent cohorts: the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) (n = 382), the Framingham Heart Study (n = 102), and the National Alzheimer's Coordinating Center (NACC) (n = 582). Performance of the model that used the multimodal inputs was consistent across datasets, with mean area under curve values of 0.996, 0.974, 0.876 and 0.954 for the ADNI study, AIBL, Framingham Heart Study and NACC datasets, respectively. Moreover, our approach exceeded the diagnostic performance of a multi-institutional team of practicing neurologists (n = 11), and high-risk cerebral regions predicted by the model closely tracked post-mortem histopathological findings. This framework provides a clinically adaptable strategy for using routinely available imaging techniques such as MRI to generate nuanced neuroimaging signatures for Alzheimer's disease diagnosis, as well as a generalizable approach for linking deep learning to pathophysiological processes in human disease., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: Elevation of factor VIII is associated with higher risk of large vessel arterial occlusions including stroke., Methods: Factor VIII levels were examined in consecutive patients with acute ischemic stroke (AIS) presenting to a single center between July 2008 and May 2012. Factor VIII levels exceeding the laboratory reference range were considered elevated (>150%)., Results: Factor VIII level was elevated in 72.4% (84 of 116) of the patients. Elevated factor VIII level was more frequent in blacks, diabetics, and patients who were anemic. Patients with elevated factor VIII had higher median baseline National Institute of Health Stroke Scale (NIHSS; 5 vs 2, P = .0295) and twice the frequency of neuroworsening (21.4% vs 9.4%), but discharge NIHSS and modified Rankin Scale were similar in the groups., Conclusions: High factor VIII level was found in the majority of tested patients with AIS. Several baseline differences were found between patients with normal and high factor VIII levels, but no differences were identified in outcome.

Background: Neuroprotective agents have the potential to reduce ischemia to penumbra of the cortex, but are time-sensitive. To quickly determine whether a cortical stroke is present without imaging, we created a scoring system based on the NIH stroke scale (NIHSS) that can accurately predict cortical damage in an acute ischemic stroke (AIS)., Methods: Patients treated with tPA for AIS were retrospectively assessed through prospectively acquired databases at two stroke centers. Stroke was classified as cortical vs. non-cortical stroke. The total NIHSS score, cortical components (gaze, visual fields, language, and neglect) and cortical score (sum of cortical components) were analyzed for site 1 and then validated for site 2 for sensitivity and positive predictive value (PPV) for a cortical stroke., Results: An acute infarct was detected in 194/239 (81%) patients at site 1 and 122/174 (70%) at site 2 on diffusion-weighted MRI. Cortical involvement was found in 71% (site 1) and 75% (site 2). The median cortical score was 25% of the total NIHSS score at both sites. NIHSS ≥ 4 had the highest sensitivity; PPV was 90% for any cortical sign with ≥ 2 points. The best combination of sensitivity and PPV was cortical score/NIHSS score ≥10%., Discussion: If a trial targeting cortical stroke required that the cortical score represent at least 10% of the total NIHSS score with no imaging, less than 10% of patients with cortical stroke would be missed and less than 18% of patients would be misclassified as having a cortical stroke.