Simple Summary The alarming rise in early-onset cancers among adolescents and young adults parallels the global surge in ultra-processed food (UPF) consumption. Beyond poor nutrition, UPFs act as “Trojan horses,” introducing biologically active compounds, particularly endocrine-disrupting chemicals (EDCs), that interfere with hormonal regulation, immune responses, and microbial balance. These exposures, often occurring during vulnerable developmental stages, disrupt endocrine signalling; promote chronic, low-grade inflammation; alter the gut microbiota; and induce epigenetic changes, thereby creating a permissive environment for carcinogenesis. Key EDCs migrate from packaging into foods, while additives and high-temperature processing further compound the risk. This review integrates emerging evidence across disciplines to highlight UPFs as silent but systemic disruptors of metabolic and genetic homeostasis. The “Trojan horse” model reframes UPFs as long-term, multifactorial risk factors, underscoring the need for multi-omics research and personalised dietary strategies to assess and mitigate cancer risks in younger populations.

Psoriatic arthritis (PsA) is a chronic inflammatory disease that extends beyond musculoskeletal and dermatologic involvement to elevate cardiometabolic risk. Emerging evidence highlights the critical role of systemic inflammation in metabolic dysregulation, accelerating insulin resistance, dyslipidemia, and oxidative stress, all of which contribute to the increased burden of cardiovascular disease in PsA. This review explores the intricate interplay between inflammatory mediators—such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-17 (IL-17),—adipokine imbalances, and lipid metabolism abnormalities, all of which foster endothelial dysfunction and atherosclerosis. The dysregulation of adipokines, including leptin, adiponectin, and resistin, further perpetuates inflammatory cascades, exacerbating cardiovascular risk. Additionally, the metabolic alterations seen in PsA, particularly insulin resistance and lipid dysfunction, not only contribute to cardiovascular comorbidities but also impact disease severity and therapeutic response. Understanding these mechanistic links is imperative for refining risk stratification strategies and tailoring interventions. By integrating targeted immunomodulatory therapies with metabolic and cardiovascular risk management, a more comprehensive approach to PsA treatment can be achieved. Future research must focus on elucidating shared inflammatory and metabolic pathways, enabling the development of innovative therapeutic strategies to mitigate both systemic inflammation and cardiometabolic complications in PsA.

Importance Rapid digitalization of health care and a dearth of digital health education for medical students and junior physicians worldwide means there is an imperative for more training in this dynamic and evolving field. Objective To develop an evidence-informed, consensus-guided, adaptable digital health competencies framework for the design and development of digital health curricula in medical institutions globally. Evidence Review A core group was assembled to oversee the development of the Digital Health Competencies in Medical Education (DECODE) framework. First, an initial list was created based on findings from a scoping review and expert consultations. A multidisciplinary and geographically diverse panel of 211 experts from 79 countries and territories was convened for a 2-round, modified Delphi survey conducted between December 2022 and July 2023, with an a priori consensus level of 70%. The framework structure, wordings, and learning outcomes with marginal percentage of agreement were discussed and determined in a consensus meeting organized on September 8, 2023, and subsequent postmeeting qualitative feedback. In total, 211 experts participated in round 1, 149 participated in round 2, 12 participated in the consensus meeting, and 58 participated in postmeeting feedback. Findings The DECODE framework uses 3 main terminologies: domain, competency, and learning outcome. Competencies were grouped into 4 domains: professionalism in digital health, patient and population digital health, health information systems, and health data science. Each competency is accompanied by a set of learning outcomes that are either mandatory or discretionary. The final framework comprises 4 domains, 19 competencies, and 33 mandatory and 145 discretionary learning outcomes, with descriptions for each domain and competency. Six highlighted areas of considerations for medical educators are the variations in nomenclature, the distinctiveness of digital health, the concept of digital health literacy, curriculum space and implementation, the inclusion of discretionary learning outcomes, and socioeconomic inequities in digital health education. Conclusions and Relevance This evidence-informed and consensus-guided framework will play an important role in enabling medical institutions to better prepare future physicians for the ongoing digital transformation in health care. Medical schools are encouraged to adopt and adapt this framework to align with their needs, resources, and circumstances.

Background In addition to age, body mass index (BMI), abdominal circumference, and parity, measuring the mother's pelvic diameters is a non-invasive, cost-effective method that can assist gynecologists in determining the optimal management of labor. Our study aimed to examine the associations between maternal age, pelvic diameters, BMI, abdominal circumference, and parity with delivery outcomes and investigate differences in pelvic diameters in relation to maternal age, BMI, delivery outcomes, parity, and episiotomy. Materials and methods The observational, cross-sectional study included 108 pregnant women in the active phase of labor who were admitted to the Gynecological Clinic at the Clinical Center University of Sarajevo. During admission, maternal data were registered: age, body height, body weight, abdominal circumference, and BMI. Using a pelvinometer, pelvic diameters were recorded: interspinous diameter (DS), intertrochanteric diameter (DT), intercristal diameter (DC), and external conjugate (CE). The Anterior Pelvic Index (API) was calculated by dividing the DS by the participants' height and multiplying the result by 100. Data were analyzed using SPSS Statistics for Windows, Version 17 (Released 2008; SPSS Inc., Chicago, United States). Results Women who underwent cesarean section were significantly older compared to those with spontaneous vaginal delivery. A significant correlation was observed between maternal age, BMI, and delivery outcomes. Obese women had significantly higher DT compared to women with normal or overweight BMI. Primiparous and multiparous women differed significantly in CE, while other pelvic diameters did not differ. Women with episiotomy had significantly lower DS and CE diameters compared to those without episiotomy during vaginal delivery. Conclusion Maternal age, BMI, and pelvic diameters are significant delivery outcome determinants; our findings suggest that these parameters deserve to be included in delivery outcome assessment as they provide substantial information in the journey of achieving personalized delivery care and decision-making.

ABSTRACT Background: The triglyceride/high-density lipoprotein (TG/HDL) ratio emerges as a promising marker for cardiovascular risk. However, the relationship between overall serum lipid levels and hemorrhagic stroke (HS) remains uncertain. Therefore, our study aims to explore the association between this novel index and mortality in HS patients. Methods: Utilizing a retrospective-prospective framework from January 2020 to August 2023, we scrutinized data from 104 hospitalized patients diagnosed with HS, with particular attention to their medical backgrounds and lipid profiles. Results: Age (odds ratio [OR], 1.078; 95% confidence interval [CI], 1.032–1.125; P = 0.001), atrial fibrillation (OR, 0.237; 95% CI, 0.074–0.760; P = 0.015), glucose level (OR, 1.121; 95% CI, 1.007–1.247; P = 0.037), and TG/HDL index (OR, 0.368; 95% CI, 0.173–0.863; P = 0.020) emerged as independent predictors for in-hospital mortality, as determined by both univariable and multivariable logistic regression analyses. Conclusion: Our results add weight to the growing evidence backing the utility of the TG/HDL index in assessing cardiovascular risk among HS patients. They emphasize the necessity of adopting a comprehensive risk assessment and management strategy that incorporates both traditional markers and novel indicators.