Introduction: Prostate cancer is one of the most common cancers threatening public health worldwide. Although chemotherapy plays an important role in treating prostate cancer, it leads to many adverse effects and is prone to drug resistance. Quercetin, a natural product, is used in traditional Chinese medicine because of its strong antitumor activity and few side effects. Methods: In this study, we combined quercetin and paclitaxel to kill prostate cancer cells in vivo and in vitro, and we investigated the relevant mechanism of this combination treatment. After the cancer cells were treated with quercetin or/and paclitaxel, cell growth inhibition, apoptosis, the cell cycle, reactive oxygen species (ROS) generation, and several endoplasmic reticulum (ER) stress signaling pathway related gene expressions were evaluated. Results: The combined treatment with quercetin and paclitaxel significantly inhibited cell proliferation, increased apoptosis, arrested the cell cycle at the G2/M phase, inhibited cell migration, dramatically induced ER stress to occur, and increased ROS generation. In a PC-3 cancer-bearing murine model, this combination treatment exerted the most beneficial therapeutic effects, and quercetin increased the cancer cell-killing effects of paclitaxel, with nearly no side effects compared with the single paclitaxel treatment group. Conclusion: Combination treatment possessed enhanced anti-cancer effects, and these results will provide a basis for treating prostate cancer using a combination of quercetin and paclitaxel.

Chaetothyriales is an ascomycetous order within Eurotiomycetes. The order is particularly known through the black yeasts and filamentous relatives that cause opportunistic infections in humans. All species in the order are consistently melanized. Ecology and habitats of species are highly diverse, and often rather extreme in terms of exposition and toxicity. Families are defined on the basis of evolutionary history, which is reconstructed by time of divergence and concepts of comparative biology using stochastical character mapping and a multi-rate Brownian motion model to reconstruct ecological ancestral character states. Ancestry is hypothesized to be with a rock-inhabiting life style. Ecological disparity increased significantly in late Jurassic, probably due to expansion of cytochromes followed by colonization of vacant ecospaces. Dramatic diversification took place subsequently, but at a low level of innovation resulting in strong niche conservatism for extant taxa. Families are ecologically different in degrees of specialization. One of the clades has adapted ant domatia, which are rich in hydrocarbons. In derived families, similar processes have enabled survival in domesticated environments rich in creosote and toxic hydrocarbons, and this ability might also explain the pronounced infectious ability of vertebrate hosts observed in these families. Conventional systems of morphological classification poorly correspond with recent phylogenetic data. Species are hypothesized to have low competitive ability against neighboring microbes, which interferes with their laboratory isolation on routine media. The dataset is unbalanced in that a large part of the extant biodiversity has not been analyzed by molecular methods, novel taxonomic entities being introduced at a regular pace. Our study comprises all available species sequenced to date for LSU and ITS, and a nomenclatural overview is provided. A limited number of species could not be assigned to any extant family.

As chronic inflammatory conditions driven by immune dysregulation are influenced by genetics and environment factors, psoriasis and atopic dermatitis (AD) have traditionally been considered to be distinct diseases characterized by different T cell responses. Psoriasis, associated with type 17 helper T (Th17)-mediated inflammation, presents as well-defined scaly plaques with minimal pruritus. AD, primarily linked to Th2-mediated inflammation, presents with poorly defined erythema, dry skin, and intense itching. However, psoriasis and AD may overlap or transition into one another spontaneously, independent of biological agent usage. Emerging evidence suggests that defects in skin barrier-related molecules interact with the polarization of T cells, which forms a skin barrier-inflammatory loop with them. This loop contributes to the chronicity of the primary disease or the transition between psoriasis and AD. This review aimed to elucidate the mechanisms underlying skin barrier defects in driving the overlap between psoriasis and AD. In this review, the importance of repairing the skin barrier was underscored, and the significance of tailoring biologic treatments based on individual immune status instead of solely adhering to the treatment guidelines for AD or psoriasis was emphasized.

The application of artificial intelligence (AI) in cancer pathology has shown significant potential to enhance diagnostic accuracy, streamline workflows, and support precision oncology. This review examines the current applications of AI across various cancer types, including breast, lung, prostate, and colorectal cancer, where AI aids in tissue classification, mutation detection, and prognostic predictions. The key technologies driving these advancements include machine learning, deep learning, and computer vision, which enable automated analysis of histopathological images and multi-modal data integration. Despite these promising developments, challenges persist, including ensuring data privacy, improving model interpretability, and meeting regulatory standards. Furthermore, this review explores future directions in AI-driven cancer pathology, including real-time diagnostics, explainable AI, and global accessibility, emphasizing the importance of collaboration between AI and pathologists. Addressing these challenges and leveraging AI’s full potential could lead to a more efficient, equitable, and personalized approach to cancer care.