Background: Artificial intelligence (AI) and telemedicine have significant potential to transform dermatology care delivery, but patient perspectives on these technologies have not been systematically compared. Objective: This study aimed to examine patient perspectives on AI and telemedicine in dermatology to inform implementation strategies as these technologies increasingly converge in clinical practice. Methods: A comprehensive literature search was conducted using PubMed, Scopus, and Embase databases between August 2024 and October 2024. We identified 48 papers addressing patient perspectives on AI and telemedicine in dermatology, with none directly comparing patients’ views of both technologies. Results: Several distinct themes emerged regarding patient perspectives on these technologies: willingness to use, perceived benefits and risks, barriers to implementation, and conditions necessary for successful integration. Findings revealed that patients express hesitancy toward AI-based diagnoses that lack dermatologist involvement, while preferences for teledermatology varied by reason for appointment, age, and previous technology exposure. Patients’ motivations for implementing AI are connected to its potential for quicker diagnoses and improved triage efficiency. At the same time, telemedicine addresses logistical challenges such as reduced travel time and improved appointment availability. Both technologies were perceived to improve accessibility and diagnostic efficiency, though patients expressed concerns about AI’s limited communication abilities and teledermatology’s inability to perform physical examinations. Primary adoption barriers for these modalities included technological limitations and trust concerns, with patients emphasizing the need for dermatologist oversight, transparency, and adequate educational resources for successful integration. Conclusions: The complementary strengths of AI and teledermatology suggest they could mitigate each other’s limitations when integrated—AI potentially enhancing teledermatology’s diagnostic accuracy, while teledermatology addresses AI’s lack of human connection. By thoroughly examining these perspectives, this review may serve as a guide for the patient-centered integration of technology in the future landscape of accessible dermatologic care.

Background: Artificial intelligence (AI) and telemedicine are rapidly changing the way dermatological care is delivered. As these tools are increasingly used in tandem, understanding how patients perceive the integration of AI across different care settings is important for responsible implementation. Objectives: To assess patient perceptions of AI in dermatology across five care modalities and examine how demographic factors influence acceptance. Methods: A cross-sectional survey was conducted among 130 adults at a US academic dermatology clinic between December 2024 and April 2025. Participants rated trust, comfort, perceived quality, privacy and confidence in equitable performance across three AI-involved modalities: standalone AI apps, AI-assisted in-person visits and AI-assisted telemedicine visits. Differences in perception outcomes across the three care modalities were analysed using repeated measures Anova. Logistic and linear regressions analysed predictors of acceptance, including age, race, skin tone, socioeconomic status, rurality and technology experience. Results: Patients strongly preferred dermatologist-involved care over standalone AI, with 73.8% trusting dermatologist-guided AI and only 1.5% trusting AI apps alone. Comfort and perceptions of equal performance across skin tones were significantly higher for telemedicine and AI-assisted visits compared with AI apps (P < 0.001). Darker skin tone and Black race predicted lower acceptance of AI-assisted care (P = 0.01 and P = 0.003, respectively), while greater technology familiarity predicted higher acceptance (P = 0.05). Comfort varied by clinical scenario, with in-person visits showing dramatically higher odds of patient comfort compared with AI apps alone [odds ratio (OR) 232.8 for new concerns, OR 137.3 for serious concerns, OR 18.4 for sensitive concerns]. AI-assisted in-person visits also showed significantly higher odds of comfort over AI apps (OR 18.4 for serious concerns, OR 3.6 for ongoing concerns). Conclusions: Patients strongly prefer AI as clinical support systems rather than autonomous decision-makers, especially for high-stakes and sensitive concerns. Differences in acceptance by race and skin tone point to the need for better representation in datasets and clearer communication about how these tools perform. Moving forward, development and implementation should emphasize clinician and patient involvement, fairness and patient choice to ensure AI is integrated into dermatology in a way that earns patient trust.

As one of the most competitive specialties in medicine, dermatology presents unique challenges for residency applicants, especially following the shift in Unite

Background/Objectives: Glioblastomas (GBMs) are dreadful brain tumors with abysmal survival outcomes. GBM extracellular vesicles (EVs) dramatically affect normal brain cells (largely astrocytes) constituting the tumor microenvironment (TME). We asked if EVs from different GBM patient-derived spheroid lines would differentially alter recipient brain cell phenotypes. This turned out to be the case, with the net outcome of treatment with GBM EVs nonetheless converging on increased tumorigenicity. Methods: GBM spheroids and brain slices were derived from neurosurgical patient tissues following informed consent. Astrocytes were commercially obtained. EVs were isolated from conditioned culture media by ultrafiltration, concentration, and ultracentrifugation. EVs were characterized by nanoparticle tracking analysis, electron microscopy, biochemical markers, and proteomics. Astrocytes/brain tissues were treated with GBM EVs before downstream analyses. Results: EVs from different GBMs induced brain cells to alter secretomes with pro-inflammatory or TME-modifying (proteolytic) effects. Astrocyte responses ranged from anti-viral gene/protein expression and cytokine release to altered extracellular signal-regulated protein kinase (ERK1/2) signaling pathways, and conditioned media from EV-treated cells increased GBM cell proliferation. Conclusions: Astrocytes/brain slices treated with different GBM EVs underwent non-identical changes in various omics readouts and other assays, indicating “personalized” tumor-specific GBM EV effects on the TME. This raises concern regarding reliance on “model” systems as a sole basis for translational direction. Nonetheless, net downstream impacts from differential cellular and TME effects still led to increased tumorigenic capacities for the different GBMs.

Present a case of Mirvetuximab soravtansine (MIRV)-induced intraepithelial corneal deposits, review a proposed mechanism to explain the blurred vision our patient experienced, and explain clinical exams that may be used to support the diagnosis. A 63-year-old female with metastatic ovarian cancer diagnosed with intraepithelial corneal deposits two weeks after her first MIRV infusion. Treatment with topical prednisolone acetate 1 % ophthalmic suspension and lubricating eye drops without interruption of her MIRV infusions resulted in complete resolution of blurry vision and corneal deposits. The natural reversibility of MIRV-induced keratopathies underscores the need for prompt and regular ophthalmic assessments throughout drug administration. Understanding the mechanism behind these corneal changes, how to recognize them in a clinical setting, and expedite their reversal are essential to improve quality-of-life metrics in patients receiving MIRV transfusions.

Ultraviolet B (UVB) radiation triggers DNA damage and immune suppression, establishing conditions favorable for skin carcinogenesis. Previous studies have shown that a downstream adaptor for Toll-like receptors (TLRs), myeloid differentiation primary response 88 (MyD88), plays a role in UVB-induced DNA damage and immunosuppression. However, specific mechanisms for the effects on dendritic cells and T cells remain poorly understood. The objective of this study is to determine the role of MyD88 and TIR-domain-containing adaptor inducing interferon-β (TRIF), another key TLR downstream adaptor, in UVB-induced suppression of dendritic cell activity and T cell function. MyD88−/−, Trif−/−, and wild-type (WT) mice were evaluated for UVB-induced effects on dendritic cell, T cells, and contact hypersensitivity responses in skin. MyD88−/− mice exhibited significant resistance to UVB-induced immune suppression, compared to Trif−/− mice and wild-type controls. The MyD88 deficiency significantly reduced UVB-induced Treg cells that were CD4⁺CD25⁺Foxp3⁺ and produced interleukin (IL)-10. Moreover, it significantly inhibited the UVB-induced suppression of IL-12/IL-23 producing CD11c⁺ dendritic cells. Further experiments confirmed that MyD88 conditional knockout (MyD88fl/flXCD11c.Cre) mice were protected against UVB-induced immune suppression. Dendritic cells from MyD88 genomic or conditional knockout mice were resistant to UVB-induced reduction of major histocompatibility complex (MHC) class II antigens. These findings show that MyD88 plays a key role in UVB-induced immune suppression. The deficiency in the MyD88 gene inhibits UVB-induced suppression of CD11c+ dendritic cell (DC) activity and reduces UVB-induced development of Treg cells. Our studies demonstrate a new mechanism for MyD88-mediated regulation of UVB-induced immune suppression.