Sexuality is a part of life and continues throughout life. Despite this, many children and young people around the world learn confusing or misleading information about sex and relationships, especially during adolescence, because they lack comprehensive sexuality education within their families or in schools. For this reason, it is necessary to provide comprehensive sexuality education (CSE) from an early age.
Nanofiber drug delivery systems offer promising potential for controlled and targeted drug release due to their high surface area/volume ratios, tunable porosity and ability to encapsulate a variety of therapeutic agents including small molecules, proteins and nucleic acids. These systems, usually produced by electrospinning, provide precise control over drug release kinetics, increasing bioavailability and minimising systemic side effects. Their applications extend to various fields such as transdermal, oral and ocular routes.
Sudden Hearing Loss (SHL) is characterized by hearing loss of at least 30 dB, seen in three consecutive frequencies and developing within 72 hours. The cause of SHL cannot be determined in 90% of cases, but causes such as viral infections, vascular problems, and autoimmune diseases should be investigated. Epidemiologically, the annual incidence is 5-20 cases per 100,000 people. Early initiation of treatment is critical, and corticosteroids are the first choice. Advanced treatment options include intratympanic corticosteroid injections and post-auricular steroid injections, hyperbaric oxygen therapy, and combinations of these. Rapid initiation of treatment is important for reversibility of hearing loss. In addition, personalized approaches are recommended in the treatment of SHL. Studies are ongoing to understand the genetic and molecular biological basis of SHL.
Artificial intelligence (AI) is set to bring significant innovations to both otology and otorhinolaryngology (ORL), significantly improving examination, diagnosis, treatment, and surgical planning. AI-enabled audiometry performs objective hearing tests, reducing the need for human interpretation and improving the accuracy of results. AI algorithms can analyze drug regimens and predict the risk of hearing damage in patients with pre-existing hearing loss or patients undergoing cochlear implants. AI-assisted image analysis can help diagnose conditions such as otosclerosis, ossicular chain defects, detection of endolymphatic hydrops, localization of tinnitus in the brain, and cholesteatoma from CT or MRI scans with high accuracy rates.
Various emotional and social stimuli influence individuals' eating behaviors. Eating attitudes, beyond being merely physiological needs, are intertwined with the social relationships formed throughout one's life. When university students transition to a new lifestyle, they may encounter feelings of loneliness impacting their eating attitudes. In this study, 557 students enrolled in a foundation university participated. Data were collected online using the Social and Emotional Loneliness Scale and the Eating Attitudes Test. The findings revealed a weakly positive and significant correlation between students' social and emotional loneliness and their eating attitudes, indicating that feelings of loneliness can indeed influence eating behaviors. It is recommended that further exploration of the factors contributing to emotional and social loneliness among university students is conducted and appropriate interventions to promote healthy eating attitudes are devised.
Aim: The rapid increase in the use of food additives has paralleled the widespread consumption of ready-made and packaged foods. Additives such as sweeteners, colorants, preservatives, and thickeners have become unavoidable in daily life. In particular, sodium benzoate and potassium sorbate are widely used as powerful antimicrobial agents in the food and pharmaceutical industries. However, there needs to be more scientific data regarding the effects of their extensive use on human health. These uncertainties have highlighted the need for further investigation into the potentially harmful effects of sodium benzoate and potassium sorbate. This study aims to assess the cytotoxic effects of sodium benzoate and potassium sorbate on L929 mouse fibroblast and HOB human osteoblast cells based on their concentrations.
Derginizin 2024 yılı ilk sayısında yayımlanan ve Özkan tarafından hazırlanan “Milenyum Öncesi Travma Yönetiminde Yaşananlar-Houston Çalışması” isimli ilginç mektubu büyük bir ilgi ile okudum. Yazarı travma yönetiminde milat niteliğinde olan Houston Çalışmasını artıları ve eksileri ile özetleyen ve travma yönetiminde yaşanan bu majör değişim sürecini anlatan yazılarından dolayı tebrik ediyorum (1). Literatürde özellikle Prenses Diana olgusu özelinde de tartışılmış olan ve yazarında bahsettiği altın saatler kavramından bahsederek tartışmaya katkı sunmak istiyorum.
Altın saatler özellikle hastane öncesi için kullanılan ve hastalarını travmadan sonraki 60 dakika içinde ileri tıbbi destek tedavisine ulaşması gerekliliğini ifade etmektedir. Terminoloji ilk kez Adams Cowley tarafından kullanılmıştır.
Köprülü ve arkadaşlarının derginizin beşinci cilt ikinci sayısında yayınladığı “Sağlık Etki Değerlendirmesi (SED) Kavramı ve Türkiye Deneyimi” başlıklı çalışmayı ilgiyle okudum (Köprülü ve ark, 2024). SED, ülkemizde uygulanmaya başlayan önemli bir kavramdır. Yazarlara ülkemizde de uygulanmaya başlanmış olan sağlık etki değerlendirilmesi (SED)” kavramı ve ülkemizdeki durumunu tartışan ilginç yazılarından dolayı teşekkür ediyorum. Bununla birlikte çalışmanın tartışmasına katkı sunmak ve dergi okurlarina farkli bir perspektif kazandirmak adina infodemiyoloji kavramından bahsetmek istiyorum.
İnfodemioloji, internet ve diğer dijital platformlardaki veri akışını inceleyen ve bu verilerden sağlıkla ilgili davranışları ve eğilimleri anlamaya çalışan bir bilim dalıdır. Bu disiplin, hastalık salgınları gibi olaylarda, insanların internet arama alışkanlıkları, sosyal medya etkileşimleri ve diğer dijital izlerini analiz ederek hastalıkların yayılma hızı ve kapsamı hakkında önemli ipuçları sağlar.
Artificial intelligence (AI) is increasingly recognized for its transformative potential in healthcare, particularly in emergency medicine. The fast-paced, highstakes nature of emergency departments (EDs) demands rapid decision-making, often under significant time and resource constraints. AI-driven solutions have already demonstrated their ability to enhance diagnostic accuracy, improve triage processes, and optimize resource allocation in emergency settings. However, AI’s potential extends beyond clinical practice into the realm of medical education, where large language models (LLMs) may offer novel opportunities for training future emergency medicine professionals.
Recent advancements in AI have enabled the development of sophisticated diagnostic tools that can assist clinicians in managing critical patients more effectively.
