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Ciliopathies are characterized by the absence or dysfunction of primary cilia. Despite the fact that cognitive impairments are a common feature of ciliopathies, how cilia dysfunction affects neuronal development has not been characterized in detail. Here, we show that primary cilium-mediated signaling is required cell-autonomously by neurons during neural circuit formation. In particular, a functional primary cilium is crucial during axonal pathfinding for the switch in responsiveness of axons at a choice point, or intermediate target. Utilizing different animal models and in vivo, ex vivo, as well as in vitro experiments, we provide evidence for a critical role of primary cilium-mediated signaling in long-range axon guidance. The primary cilium on the cell body of commissural neurons transduces long-range guidance signals sensed by growth cones navigating an intermediate target. In extension of our finding that Shh is required for the rostral turn of post-crossing commissural axons, we suggest a model implicating the primary cilium in Shh signaling upstream of a transcriptional change of axon guidance receptors, which in turn mediate the repulsive response to floorplate-derived Shh shown by post-crossing commissural axons.
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BACKGROUND: In Australian remote communities, First Nations children with otitis media (OM)-related hearing loss are disproportionately at risk of developmental delay and poor school performance, compared to those with normal hearing. Our objective was to compare OM-related hearing loss in children randomised to one of 2 pneumococcal conjugate vaccine (PCV) formulations. METHODS AND FINDINGS: In 2 sequential parallel, open-label, randomised controlled trials (the PREVIX trials), eligible infants were first allocated 1:1:1 at age 28 to 38 days to standard or mixed PCV schedules, then at age 12 months to PCV13 (13-valent pneumococcal conjugate vaccine, +P) or PHiD-CV10 (10-valent pneumococcal Haemophilus influenzae protein D conjugate vaccine, +S) (1:1). Here, we report prevalence and level of hearing loss outcomes in the +P and +S groups at 6-monthly scheduled assessments from age 12 to 36 months. From March 2013 to September 2018, 261 infants were enrolled and 461 hearing assessments were performed. Prevalence of hearing loss was 78% (25/32) in the +P group and 71% (20/28) in the +S group at baseline, declining to 52% (28/54) in the +P groups and 56% (33/59) in the +S group at age 36 months. At primary endpoint age 18 months, prevalence of moderate (disabling) hearing loss was 21% (9/42) in the +P group and 41% (20/49) in the +S group (difference -19%; (95% confidence interval (CI) [-38, -1], p = 0.07) and prevalence of no hearing loss was 36% (15/42) in the +P group and 16% (8/49) in the +S group (difference 19%; (95% CI [2, 37], p = 0.05). At subsequent time points, prevalence of moderate hearing loss remained lower in the +P group: differences -3%; (95% CI [-23, 18], p = 1.00 at age 24 months), -12%; (95% CI [-30, 6], p = 0.29 at age 30 months), and -9%; (95% CI [-23, 5], p = 0.25 at age 36 months). A major limitation was the small sample size, hence low power to reach statistical significance, thereby reducing confidence in the effect size. CONCLUSIONS: In this study, we observed a high prevalence and persistence of moderate (disabling) hearing loss throughout early childhood. We found a lower prevalence of moderate hearing loss and correspondingly higher prevalence of no hearing loss in the +P group, which may have substantial benefits for high-risk children, their families, and society, but warrant further investigation. TRIAL REGISTRATION: ClinicalTrials.gov NCT01735084 and NCT01174849.
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Perda Auditiva , Otite Média , Vacinas Pneumocócicas , Humanos , Lactente , Vacinas Pneumocócicas/administração & dosagem , Vacinas Pneumocócicas/uso terapêutico , Perda Auditiva/epidemiologia , Austrália/epidemiologia , Pré-Escolar , Feminino , Masculino , Otite Média/epidemiologia , Otite Média/prevenção & controle , Prevalência , Vacinas Conjugadas/administração & dosagem , Infecções Pneumocócicas/prevenção & controle , Infecções Pneumocócicas/epidemiologia , Esquemas de ImunizaçãoRESUMO
INTRODUCTION: Large language models like Chat Generative Pre-Trained Transformer (ChatGPT) are increasingly used in academic writing. Faculty may consider use of artificial intelligence (AI)-generated responses a form of cheating. We sought to determine whether general surgery residency faculty could detect AI versus human-written responses to a text prompt; hypothesizing that faculty would not be able to reliably differentiate AI versus human-written responses. METHODS: Ten essays were generated using a text prompt, "Tell us in 1-2 paragraphs why you are considering the University of Rochester for General Surgery residency" (Current trainees: n = 5, ChatGPT: n = 5). Ten blinded faculty reviewers rated essays (ten-point Likert scale) on the following criteria: desire to interview, relevance to the general surgery residency, overall impression, and AI- or human-generated; with scores and identification error rates compared between the groups. RESULTS: There were no differences between groups for %total points (ChatGPT 66.0 ± 13.5%, human 70.0 ± 23.0%, P = 0.508) or identification error rates (ChatGPT 40.0 ± 35.0%, human 20.0 ± 30.0%, P = 0.175). Except for one, all essays were identified incorrectly by at least two reviewers. Essays identified as human-generated received higher overall impression scores (area under the curve: 0.82 ± 0.04, P < 0.01). CONCLUSIONS: Whether use of AI tools for academic purposes should constitute academic dishonesty is controversial. We demonstrate that human and AI-generated essays are similar in quality, but there is bias against presumed AI-generated essays. Faculty are not able to reliably differentiate human from AI-generated essays, thus bias may be misdirected. AI-tools are becoming ubiquitous and their use is not easily detected. Faculty must expect these tools to play increasing roles in medical education.
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Rejection following liver transplantation continues to impact transplant recipients although rates have decreased over time with advances in immunosuppression management. The diagnosis of rejection remains challenging with liver biopsy remaining the reference standard for diagnosis. Proper classification of rejection type and severity is imperative as this guides management and ultimately graft preservation. Future areas of promise include non-invasive testing for detection of rejection to reduce the morbidity associated with invasive testing and further advances in immunosuppression management to reduce toxicities associated with immunosuppression while minimizing rejection related morbidity.
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BACKGROUND: Assigning trauma team activation (TTA) levels for trauma patients is a classification task that machine learning models can help optimize. However, performance is dependent on the "ground-truth" labels used for training. Our purpose was to investigate 2 ground truths, the Cribari matrix and the Need for Trauma Intervention (NFTI), for labeling training data. STUDY DESIGN: Data were retrospectively collected from the institutional trauma registry and electronic medical record, including all pediatric patients (age <18 years) who triggered a TTA (January 2014 to December 2021). Three ground truths were used to label training data: (1) Cribari (Injury Severity Score >15 = full activation), (2) NFTI (positive for any of 6 criteria = full activation), and (3) the union of Cribari+NFTI (either positive = full activation). RESULTS: Of 1,366 patients triaged by trained staff, 143 (10.47%) were considered undertriaged using Cribari, 210 (15.37%) using NFTI, and 273 (19.99%) using Cribari+NFTI. NFTI and Cribari+NFTI were more sensitive to undertriage in patients with penetrating mechanisms of injury (p = 0.006), specifically stab wounds (p = 0.014), compared with Cribari, but Cribari indicated overtriage in more patients who required prehospital airway management (p < 0.001), CPR (p = 0.017), and who had mean lower Glasgow Coma Scale scores on presentation (p < 0.001). The mortality rate was higher in the Cribari overtriage group (7.14%, n = 9) compared with NFTI and Cribari+NFTI (0.00%, n = 0, p = 0.005). CONCLUSIONS: To prioritize patient safety, Cribari+NFTI appears best for training a machine learning algorithm to predict the TTA level.
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Escala de Gravidade do Ferimento , Triagem , Ferimentos e Lesões , Humanos , Criança , Estudos Retrospectivos , Ferimentos e Lesões/terapia , Ferimentos e Lesões/diagnóstico , Ferimentos e Lesões/mortalidade , Feminino , Masculino , Pré-Escolar , Adolescente , Triagem/normas , Triagem/métodos , Aprendizado de Máquina , Centros de Traumatologia , Equipe de Assistência ao Paciente/organização & administração , Lactente , Sistema de RegistrosRESUMO
CONTEXT: Neighborhood and built environment encompass one key area of the Social Determinants of Health (SDOH) and is frequently assessed using area-level indices. OBJECTIVE: We sought to systematically review the pediatric surgery literature for use of commonly applied area-level indices and to compare their utility for prediction of outcomes. DATA SOURCES: A literature search was conducted using PubMed, Ovid MEDLINE, Ovid MEDLINE Epub Ahead of Print, PsycInfo, and an artificial intelligence search tool (1/2013-2/2023). STUDY SELECTION: Inclusion required pediatric surgical patients in the US, surgical intervention performed, and use of an area-level metric. DATA EXTRACTION: Extraction domains included study, patient, and procedure characteristics. RESULTS: Area Deprivation Index is the most consistent and commonly accepted index. It is also the most granular, as it uses Census Block Groups. Child Opportunity Index is less granular (Census Tract), but incorporates pediatric-specific predictors of risk. Results with Social Vulnerability Index, Neighborhood Deprivation Index, and Neighborhood Socioeconomic Status were less consistent. LIMITATIONS: All studies were retrospective and quality varied from good to fair. CONCLUSIONS: While each index has strengths and limitations, standardization on ideal metric(s) for the pediatric surgical population will help build the inferential power needed to move from understanding the role of SDOH to building meaningful interventions towards equity in care. TYPE OF STUDY: Systematic Review. LEVEL OF EVIDENCE: Level III.