Extracranial arteriovenous malformations: a 10-year experience at a German vascular anomaly center and evaluation of diagnostic imaging for endovascular therapy assessment.

Background: Arteriovenous malformations (AVMs) account for <3% of vascular anomalies. This study aims to present the 10-year experience of a German vascular anomaly center (VAC) with AVMs and evaluate diagnostic imaging for treatment-relevant information for minimally invasive therapy planning.

Material And Methods: A retrospective study including patients from the VAC database with AVMs was conducted.

Haematogenous seeding in mycosis fungoides and Sézary syndrome: Current evidence and clinical implications.

Cutaneous T-cell lymphomas (CTCLs) are a heterogeneous group of diseases characterised by abnormal neoplastic T-cell growth in the skin. Mycosis fungoides (MF), the most common CTCL, manifests as erythematous skin patches and/or plaques, tumours or erythroderma. The disease may involve blood, lymph nodes and rarely viscera.

Comparing Patient's Confidence in Clinical Capabilities in Urology: Large Language Models Versus Urologists.

Background And Objective: Data on interaction of patients with artificial intelligence (AI) are limited, primarily derived from small-scale studies, cross-sectional surveys, and qualitative reviews. Most patients have not yet encountered AI in their clinical experience. This study explored patients' confidence in AI, specifically large language models, after a direct interaction with a chatbot in a clinical setting.

Expected benefits and concerns regarding virtual reality in caring for terminally ill cancer patients - a qualitative interview study.

Background: Many palliative cancer patients require inpatient hospital treatment for medical reasons, which contrasts their frequent desire to be at home. Virtual reality (VR) could be a way of bringing the home environment closer to them. First observations have shown benefits from VR for inpatients in palliative care.

My virtual escape from patient life: a feasibility study on the experiences and benefits of individualized virtual reality for inpatients in palliative cancer care.

Background: Cancer patients benefit from Virtual Reality (VR) in burdensome situations, but evidence is scarce for palliative situations. Based on earlier work in palliative care, individualized VR interventions like seeing the patient's home may address a patient's wish to be at home and thus have a greater effect compared to standard VR content. Yet, some patients and relatives may be concerned about their privacy.

Effectiveness of the Medical Chatbot PROSCA to Inform Patients About Prostate Cancer: Results of a Randomized Controlled Trial.

Background And Objective: Artificial intelligence (AI)-powered conversational agents are increasingly finding application in health care, as these can provide patient education at any time. However, their effectiveness in medical settings remains largely unexplored. This study aimed to assess the impact of the chatbot "PROState cancer Conversational Agent" (PROSCA), which was trained to provide validated support from diagnostic tests to treatment options for men facing prostate cancer (PC) diagnosis.

Retinal nerve fiber layer defects and chronic kidney disease: the Kailuan Eye Study.

Aim: To investigate whether retinal nerve fiber layer defects (RNFLDs) is a potential risk factor for chronic kidney disease (CKD) in Chinese adults.

Methods: The Kailuan Eye Study was a population-based study that included 14 440 participants. All participants underwent detailed assessments, RNFLDs were diagnosed using color fundus photographs.

Small Ring Molecules Comprising 3-6 Boron Atoms: An Account on Synthesis, Structure, and Orbital Engineering.

ConspectusUnlike carbon, boron does not usually form ring compounds due to its electron-deficiency-driven affinity toward polyhedral geometries. The polyhedral boranes having -, -, -, or -shapes can be structurally and electronically correlated using various electron counting rules developed by Wade, Mingos, and one of us. However, in the last few decades, boron chemistry progressed significantly toward ring systems.

Evaluation of Sézary cell marker expression and cell death behaviour upon in vitro treatment by flow cytometry in Sézary syndrome patients.

The diagnosis of Sézary syndrome (SS) relies on the identification of blood Sézary cells (SC) by different markers via flow cytometry. Treatment of SS is challenging since its pathogenesis is characterized by cell death resistance rather than hyperproliferation. In this study, we establish an integrated approach that considers both the expression of SC markers and sensitivity to cell death both spontaneously and upon in vitro treatment.

Introducing MCC-PS: a novel prognostic score for Merkel cell carcinoma.

Introduction: Merkel cell carcinoma (MCC) is an aggressive skin cancer with a poor prognosis, which only improved with the introduction of immunotherapies. An MCC prediction model with high diagnostic accuracy is lacking. The aim was to develop an MCC prognostic score (MCC-PS) based on combinations of previously proposed risk factors.

High Glucose Increases Lactate and Induces the Transforming Growth Factor Beta-Smad 1/5 Atherogenic Pathway in Primary Human Macrophages.

Hundreds of millions of people worldwide are expected to suffer from diabetes mellitus. Diabetes is characterized as a dynamic and heterogeneous disease that requires deeper understanding of the pathophysiology, genetics, and metabolic shaping of this disease and its macro/microvascular complications. Macrophages play an essential role in regulating local immune responses, tissue homeostasis, and disease pathogenesis.

Influence of Tyrosine Kinase Inhibitors and Everolimus on TGFβ1 and TGF-β Receptor 2 in Squamous Cell Carcinoma Cells.

Background/aim: Transforming growth factor-β (TGF-β) plays a significant role in the formation of different cancer subtypes. There is evidence that TGF-β pathways promote cancerogenic cell characteristics but also have tumor-suppressor capabilities. The tyrosine kinase inhibitors nilotinib, dasatinib, erlotinib, gefitinib, and everolimus are approved as targeted therapies for several tumor entities, including head and neck squamous cell carcinoma (HNSCC).

Sphinganine recruits TLR4 adaptors in macrophages and promotes inflammation in murine models of sepsis and melanoma.

After recognizing its ligand lipopolysaccharide, Toll-like receptor 4 (TLR4) recruits adaptor proteins to the cell membrane, thereby initiating downstream signaling and triggering inflammation. Whether this recruitment of adaptor proteins is dependent solely on protein-protein interactions is unknown. Here, we report that the sphingolipid sphinganine physically interacts with the adaptor proteins MyD88 and TIRAP and promotes MyD88 recruitment in macrophages.

DEAD box RNA helicases are pervasive protein kinase interactors and activators.

DEAD box (DDX) RNA helicases are a large family of ATPases, many of which have unknown functions. There is emerging evidence that besides their role in RNA biology, DDX proteins may stimulate protein kinases. To investigate if protein kinase-DDX interaction is a more widespread phenomenon, we conducted three orthogonal large-scale screens, including proteomics analysis with 32 RNA helicases, protein array profiling, and kinome-wide in vitro kinase assays.

Toward a systematic grading for the selection of patients to undergo awake surgery: identifying suitable predictor variables.

Background: Awake craniotomy is the standard of care for treating language eloquent gliomas. However, depending on preoperative functionality, it is not feasible in each patient and selection criteria are highly heterogeneous. Thus, this study aimed to identify broadly applicable predictor variables allowing for a more systematic and objective patient selection.

Essential phospholipids impact cytokine secretion and alter lipid-metabolizing enzymes in human hepatocyte cell lines.

Background: Essential phospholipids (EPL) are hepatoprotective.

Methods: The effects on interleukin (IL)-6 and -8 secretion and on certain lipid-metabolizing enzymes of non-cytotoxic concentrations of EPL (0.1 and 0.

Concurrent inhibition of ALK and SRC kinases disrupts the ALK lung tumor cell proteome.

Precision oncology has revolutionized the treatment of ALK-positive lung cancer with targeted therapies. However, an unmet clinical need still to address is the treatment of refractory tumors that contain drug-induced resistant mutations in the driver oncogene or exhibit resistance through the activation of diverse mechanisms. In this study, we established mouse tumor-derived cell models representing the two most prevalent EML4-ALK variants in human lung adenocarcinomas and characterized their proteomic profiles to gain insights into the underlying resistance mechanisms.

Valuing Negative Affect Weakens Affect-Health Linkages: Similarities and Differences Across Affect Valuation Measures.

Negative affect (NA) has been robustly linked to poorer psychological health, including greater depressive symptoms, personal burnout, and perceived stress. These associations, known as , have been postulated by our research team to vary with different levels of (NAV), such that people who NA states as more pleasant, helpful, appropriate, and/or meaningful may show weaker affect-health links. Another affect valuation construct is , which is the degree to which people ideally want to experience NA states (i.

Federated Learning for Decentralized Artificial Intelligence in Melanoma Diagnostics.

Importance: The development of artificial intelligence (AI)-based melanoma classifiers typically calls for large, centralized datasets, requiring hospitals to give away their patient data, which raises serious privacy concerns. To address this concern, decentralized federated learning has been proposed, where classifier development is distributed across hospitals.

Objective: To investigate whether a more privacy-preserving federated learning approach can achieve comparable diagnostic performance to a classical centralized (ie, single-model) and ensemble learning approach for AI-based melanoma diagnostics.