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What Do We Know About Ligaments?

Ligaments have been extensively studied in anatomy and are traditionally defined as structures that connect bones and contribute to joint stability. However, a universally accepted definition of "ligament" remains elusive. Many structures classified as ligaments do not connect bones, such as the ligamentum arteriosum, raising questions about the criteria used for their designation. Moreover, distinguishing ligaments from tendons presents a significant challenge because of their shared histological characteristics and the lack of a clear, standardized definition of "ligament". Historically, ligaments have been named primarily on the basis of their gross anatomical appearance rather than well-defined structural or functional criteria. Ambiguities in nomenclature such as the interchangeable use of "patellar ligament" and "patellar tendon" further complicate classification. Additionally, dissection bias can lead to the artificial identification of ligaments because traditional dissection techniques can isolate tissue layers in a manner that creates the illusion of distinct ligament structures. Given these limitations, gross anatomical dissection alone is insufficient to confirm the presence of a ligament, necessitating histological validation based on a fundamental definition. Establishing a precise classification system that differentiates traditional bone-to-bone ligaments from other connective structures is imperative. Close collaboration between anatomists and surgeons is essential for refining anatomical definitions because inaccurate classifications can have direct implications for clinical practice, particularly in ligament reconstruction. A research-driven, standardized definition of ligaments can enhance anatomical education and improve surgical precision.

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Kaposi Sarcoma-Associated Herpesvirus Risk and Disease in Kidney Donors and Transplant Recipients with HIV in the United States.

Due to high prevalence of Kaposi Sarcoma (KS)-Associated Herpesvirus (KSHV) among people with HIV, KSHV-associated disease (KAD) may be increased after kidney transplantation from donors with HIV (HIV D+) to recipients with HIV (HIV R+). Anti-KSHV antibodies were measured in HIV R+ and donors with and without HIV (HIV D-) using a 30-antigen multiplex assay within three multicenter kidney transplantation studies. KSHV seropositivity was defined as reactivity to conventional KSHV antigens (≥1 ORF73 or K8.1); reactivity to expanded 5-antigen and 30-antigen panels were also reported. Risk factors were identified using modified Poisson regression. Recipients were monitored for post-transplant anti-KSHV antibody changes and KAD. KSHV seroprevalence was 40.6% (143/352) among HIV R+, 25.2% (33/131) among HIV D+, and 7.5% (4/53) among HIV D-. In the multivariable model, only men who have sex with men (MSM) was associated with KSHV seropositivity: relative risk 1.51 (95% confidence interval [CI] 1.07-2.14) in recipients and 2.39 (95%CI 1.03-5.53) in donors. Among 418 HIV R+ (215 HIV D+/R+, 203 HIV D-/R+), there were 5 KAD cases (incidence 0.63 cases/100 person-years, 95%CI 0.26-1.52): 3 skin-only KS, 1 multicentric Castleman disease, 1 allograft KS. The allograft KS occurred in a female HIV D+/R+ and was likely donor-derived. Remaining KAD cases occurred in male HIV D-/R+ and were likely recipient KSHV reactivation or acquisition. In the United States, KSHV seroprevalence in donors and recipients with HIV was high, particularly among MSM. Reassuringly, KSHV-associated disease was rare, and primarily attributed to recipient rather than donor-derived KSHV.

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Superior Cerebrovascular Outcomes with Tirzepatide versus Semaglutide in Diabetic CABG patients: A Global Network Study of Propensity-Matched Patients

Abstract Purpose To compare the effectiveness of tirzepatide (dual GLP-1/GIP receptor agonist) versus semaglutide (GLP-1 receptor agonist) in managing post-operative outcomes for diabetic patients undergoing coronary artery bypass grafting (CABG). Methods Using the TriNetX global network (2022–2024), we analyzed 2,294 propensity-matched pairs of diabetic adults who underwent CABG and received either tirzepatide or semaglutide. Post-operative complications, cardiovascular events, cerebrovascular outcomes, healthcare utilization, and mortality at 6 months and 3 years were evaluated. Results At 3 years, tirzepatide showed superior cerebrovascular protection with reduced incidence of transient ischemic attacks (2.5% vs 3.6%, HR = 0.692, 95%CI = 0.494–0.970, p = 0.026) and cerebral infarction (5.6% vs 7.6%, HR = 0.739, 95%CI = 0.588–0.927, p = 0.006) compared to semaglutide. These benefits, however, were not present or significant in tirzepatide in the short term (6 months) and had similar risk rates to that of semaglutide. Despite tirzepatide’s long term cerebrovascular benefits, overall cardiovascular event rates were comparable between both cohorts. All-cause mortality between tirzepatide and semaglutide at 6 months and 3 years were also similar in risk. Post-operative complications and healthcare utilization were comparable between groups. Conclusion In diabetic patients undergoing CABG, tirzepatide demonstrated superior long term (3 year) cerebrovascular protection compared to semaglutide while maintaining a similar safety profile. These findings suggest tirzepatide may be particularly beneficial for preventing cerebrovascular events in this high-risk population.

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The Roles of Artificial Intelligence in Teaching Anatomy: A Systematic Review.

Anatomy education is a cornerstone of medical training and relies on cadaveric dissection and 2D illustrations. Technological advancements and integrated curricula have reduced the focus on detailed anatomy and challenged educators to engage Generation Z learners with interactive, tech-driven methods. Advanced imaging and artificial intelligence (AI) offer a solution, providing virtual dissection simulations and personalized learning tools that mimic 3D anatomy and adapt to individual student needs. Machine learning, a subset of AI, enhances this process by enabling predictive analytics, adaptive feedback, and tailored learning pathways based on performance data, significantly improving anatomical comprehension. Despite its benefits, AI integration raises concerns about over-reliance on technology, biases, and diminished human interaction in training. This review examines AI's transformative potential in anatomy education while emphasizing the need for balanced implementation and ethical oversight. A systematic review following PRISMA guidelines was conducted, utilizing PubMed and backward citation searches. The search yielded 56studies, with 47 additional articles from citations, resulting in 61 included studies. These explored AI applications such as virtual dissection simulations, machine learning algorithms for adaptive feedback, and gamified learning experiences, which were shown to enhance engagement, personalize learning, and improve anatomical understanding. Concerns about over-reliance on AI and the loss of human interaction were also raised. AI has the potential to enhance anatomy education, but careful consideration of ethical and practical implications is essential. A balanced approach combining traditional methods with AI and robust oversight is crucial for effective integration.

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