Machine learning in the prediction of immunotherapy response and prognosis of melanoma: a systematic review and meta-analysis.

Background: The emergence of immunotherapy has changed the treatment modality for melanoma and prolonged the survival of many patients. However, a handful of patients remain unresponsive to immunotherapy and effective tools for early identification of this patient population are still lacking. Researchers have developed machine learning algorithms for predicting immunotherapy response in melanoma, but their predictive accuracy has been inconsistent.

Deep skin diseases diagnostic system with Dual-channel Image and Extracted Text.

Background: Due to the lower reliability of laboratory tests, skin diseases are more suitable for diagnosis with AI models. There are limited AI dermatology diagnostic models combining images and text; few of these are for Asian populations, and few cover the most common types of diseases.

Methods: Leveraging a dataset sourced from Asia comprising over 200,000 images and 220,000 medical records, we explored a deep learning-based system for Dual-channel images and extracted text for the diagnosis of skin diseases model DIET-AI to diagnose 31 skin diseases, which covers the majority of common skin diseases.

The abscopal effect of anti-CD95 and radiotherapy in melanoma.

Background: Radiotherapy (RT) is frequently adopted to control cancer cell proliferation, which is achieved by altering the tumor microenvironment (TME) and immunogenicity. Apoptosis of cancer cells is the major effect of radiation on tumor tissues. Fas/APO-1(CD95) receptors on the cell membrane are death receptors that can be activated by diverse factors, including radiation and integration with CD95L on CD8 T cells.

Altered Gut Microbiota in H1-Antihistamine-Resistant Chronic Spontaneous Urticaria Associates With Systemic Inflammation.

Background And Objective: Chronic spontaneous urticaria (CSU) is a histamine-mediated inflammatory skin disease, and second-generation non-sedating H1-antihistamines (nsAH) at licensed doses have long been the first-line therapy in CSU. However, about 50% of patients are resistant to nsAH, and the precise pathogenesis remains largely unknown but seems to be associated with low-level systemic or intestinal inflammation. We aim to determine the fecal microbial composition and clarify its correlation with the clinical profiles og CSU with nsAH resistance.

Curcumin assists anti-EV71 activity of IFN-α by inhibiting IFNAR1 reduction in SH-SY5Y cells.

Background And Aim: Enterovirus 71(EV71) can cause severe hand, foot, and mouth disease (HFMD) with brain tissue involvement. Few effective anti-EV71 drugs are presently available in clinical practice. Interferon-α (IFN-α) was ineffective while Curcumin was effective in restricting EV71 replication in non-neuronal cells.

Translocating lipopolysaccharide correlates with the severity of enterovirus A71-induced HFMD by promoting pro-inflammation and viral IRES activity.

Background: The increase of inflammation-inducing enterobacteria was recently observed in severe hand, foot, and mouth disease (HFMD) caused by Enterovirus A71 (EV-A71). This study aimed to verify the occurrence of bacterial translocation (BT) and further explore the contributory role of BT to severity of EV-A71-mediated HFMD cases.

Methods: Serum specimens from 65 mild and 65 severe EV-A71-associated HFMD cases and 65 healthy children were collected.