A case of angiolymphoid hyperplasia with eosinophilia (ALH) is reported in a 42-year-old woman who developed multiple nodules behind the ear. Angiolymphoid hyperplasia with eosinophilia usually occurs on the head and neck of young adults and is more common in women than in men. Characteristic histologic features of ALH present in this case included proliferation of thick-walled blood vessels lined by prominent endothelial cells, infiltration of the interstitium by chronic inflammatory cells (mainly eosinophils), and presence of lymphoid follicles with germinal centers. The patient referred for surgeon for complete excision. in this context , cases previously described in the literature, and the differential diagnosis of ALH are discussed

Metals are vital cellular components chosen by nature to perform various critical metabolic activities in living beings. Metal complexes are keys in catalysis, material production, photochemistry, and biological systems. Many studies were conducted to determine their role in biological processes. Transition metal complexes are becoming more important as therapeutic compounds due to their role in inorganic chemistry. Recent advances in inorganic chemistry have created transition metal complexes with target organic ligands that may be therapeutic. Researchers interested in medical applications may find this study useful since it highlights the importance of metals and current developments in medicinal chemistry, such as new approaches to crea

The present systematic review aimed to combine the evidence on rodent models on molecular regulators of root dentinogenesis across the temporal phases and spatial zones, and evaluate the translation of this map for human dental development and regenerative therapies. A PRISMA 2020‑guided systematic review of experimental studies through the major electronic databases was performed. Data on models, molecules, techniques, spatiotemporal expression and the functional outcomes were extracted. The ARRIVE guidelines and SYRCLE's risk of bias tool were used to assess the risk of bias in animal studies. The evidence form rodent studies supports an organized network that begins with initiation at the cervical loop that requires the downregulation

In recent years, the evolution of the community structure in social networks has gained significant attention. Due to the rapid and continuous evolution of real-world networks over time. This makes the process of identifying communities and tracking their topology changes challenging. To tackle these challenges, it is necessary to find efficient methodologies for analyzing the behavior patterns of dynamic communities. Several previous reviews have introduced algorithms and models for community detection. However, these methods have not been very accurate in identifying communities. Moreover, none of the reviewed papers made an apparent effort to link algorithms that can accurately detect dynamic communities. This review aims to present a ta

Background/Objectives: Cancer pain affects 55–95% of patients with advanced malignancy, representing a complex syndrome involving nociceptive, neuropathic and nociplastic mechanisms. Despite therapeutic advances, two-thirds of patients with metastatic cancer experience inadequate pain control. This scoping review synthesizes recent advances in cancer pain pathophysiology and management, focusing on molecular and cellular mechanisms, emerging pharmacological, interventional and technological therapies and key evidence gaps to inform future precision-based pain management strategies. Methods: Following PRISMA-ScR methodology, we searched PubMed, Embase, Scopus, and Web of Science for studies published between January 2022 and Septem

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect