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Tuberculosis incidence in solid organ transplant recipients in Europe: A multicenter TBnet cohort study.
No full textBACKGROUND: Solid organ transplant (SOT) recipients face elevated tuberculosis risk, yet optimal prevention strategies in low- to medium-incidence regions remain unclear. METHODS: We conducted a multicenter retrospective cohort study of adult SOT recipients transplanted between 2007 and 2012 at 15 European centers, with follow-up through 2018. The primary outcome was microbiologically confirmed post-transplant tuberculosis. Incidence rates were calculated per 100,000 person-years; standardized incidence ratios (SIRs) used World Health Organization country-specific background rates. Cox models assessed risk factors. RESULTS: Among 5805 patients (median age 51; 62.7% male; 73.9% renal transplants), 33.8% were tested for tuberculosis infection and 10.3% received tuberculosis preventive therapy (TPT). Over 33,785 person-years, 23 patients (0.4%) developed tuberculosis (68.0/100,000 person-years). Highest incidence occurred in patients with positive screening but no TPT (233.8/100,000). Incidence was higher in Southern vs. Central Europe (251.9 vs. 28.7/100,000), with pooled SIRs of 12.8 and 3.1, respectively. Tuberculosis risk was elevated among Southern European recipients (HR 22.9) and those with migration history (HR 2.7). CONCLUSION: Tuberculosis risk is increased in European SOT recipients. Regionally adapted prevention strategies, including targeted screening in low-incidence areas and universal screening in higher-incidence regions, are warranted
Formation of multi-planetary systems via pebble accretion in externally photoevaporating discs in stellar clusters
No full textSplitting schizophrenia: divergent cognitive and educational outcomes revealed by genomic structural equation modelling.
No full textThe genetic relationship between schizophrenia, IQ, and educational attainment (EA) is complex. Schizophrenia polygenic scores (PGS) are linked to lower IQ, whilst higher IQ-PGS correlates with reduced schizophrenia risk. Paradoxically, genetic predisposition to higher EA has been associated with increased schizophrenia risk, a relationship potentially confounded by genetic overlap between schizophrenia and bipolar disorder. Using a latent-variable Genomic Structural Equation Modelling approach to GWAS summary statistics for schizophrenia and bipolar disorder, we dissected the genetic contribution to schizophrenia, identifying 63 SNPs specifically associated with schizophrenia (SZspecific) and 78 shared with bipolar disorder (PSYshared). Both schizophrenia (rg = -0.22) and SZspecific (rg = -0.24) were genetically negatively correlated with IQ; correlations between bipolar disorder and PSYshared with IQ were less pronounced (both rg = -0.07). Schizophrenia exhibited no correlation with EA, yet the latent variables demonstrated divergent relationships; PSYshared was positively correlated (rg = 0.11), whereas SZspecific was negatively correlated (rg = -0.06). PGS analyses in the UK Biobank (n = 381,688), corroborated these divergent relationships, SZspecific-PGS was negatively associated with EA (β = -0.13, p < 2e-16), whereas the PSYshared-PGS was positively associated (β = 0.14, p < 2e-16). Mendelian randomisation provided additional support but also confirmed the presence of genetic pleiotropy. These findings underscore the utility of genetic methods in dissecting the heterogeneity of neuropsychiatric disorders, supporting the existence of two possible pathways to schizophrenia: one shared with bipolar disorder and another with greater neurocognitive impact
DESAFIOS DO ESTADO BRASILEIRO FRENTE À PANDEMIA PELA COVID-19: O CASO DA PARADIPLOMACIA MARANHENSE
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Timing the Environment in International Law: Reflections on Temporality in the Three Advisory Opinions on Climate Change
No full textWhy aren't they used? Systematic review of barriers to implementation of Clinical Decision Support Systems for early cancer detection in primary care.
Get PDFBACKGROUND: Early cancer detection is crucial for patient outcomes. Clinical Decision Support Systems (CDSS) have been developed to assist with decision-making about screening or symptomatic assessment in primary care, but implementation remains challenging. AIM: The aim of this study was to compare barriers to implementation of cancer-specific CDSS for screening and symptomatic presentation in primary care. DESIGN AND SETTING: Systematic mixed-methods literature review. METHODS: We conducted a sub-analysis within a systematic review. Qualitative and quantitative data on barriers were coded into themes guided by the Theoretical Domains Framework. Frequencies of studies mentioning barriers were compared between CDSS for cancer detection and other conditions, and between cancer-CDSS for screening and symptomatic presentation. RESULTS: 29 cancer-specific CDSS were identified, addressing screening (n=15) and symptomatic presentation (n=14), with a further 70 addressing other conditions. There were minimal differences in barriers for cancer-specific CDSS and other CDSS. There were differences between cancer-specific CDSS for screening and symptomatic presentation. Barriers more frequently reported for CDSS for symptomatic presentation involved workflow integration (n=9, 64% vs n=4, 27%), medicolegal uncertainty (n=4, 29% vs n=0, 0%), requirements of skills (n=7, 50% vs n=2, 13%), interference with decision-making processes (n=6, 43% vs n=2, 13%), and negative emotions (n=8, 57% vs n=4, 27%). CONCLUSION: The function and healthcare context of CDSS in the diagnostic process (symptomatic assessment or screening decision-making) appears to be more relevant to implementation than the targeted condition. Involving stakeholders to clarify medicolegal issues and workflow integration is essential for the implementation of CDSS for symptomatic presentation
QAISim: a toolkit for modeling and simulation of AI in quantum cloud computing environments
No full textQuantum computing offers new ways to explore the theory of computation via the laws of quantum mechanics. Due to the rising demand for quantum computing resources, there is growing interest in developing cloud-based quantum resource sharing platforms that enable researchers to test and execute their algorithms on real quantum hardware. These cloud-based systems face a fundamental challenge in efficiently allocating quantum hardware resources to fulfill the growing computational demand of modern Internet of Things (IoT) applications. So far, attempts have been made in order to make efficient resource allocation, ranging from heuristic-based solutions to machine learning. In this work, we employ quantum reinforcement learning based on parameterized quantum circuits to address the resource allocation problem to support large IoT networks. We propose a python-based toolkit called QAISim for the simulation and modeling of Quantum Artificial Intelligence (QAI) models for designing resource management policies in quantum cloud environments. We have simulated policy gradient and Deep Q-Learning algorithms for reinforcement learning. QAISim exhibits a substantial reduction in model complexity compared to its classical counterparts with fewer trainable variables
Combined components: simplifying forward resuscitation - a flow, time and resource analysis of prehospital transfusion.
Get PDFINTRODUCTION: Delivering balanced blood resuscitation at the point of injury remains a significant logistical challenge in prehospital trauma care. To inform optimal transfusion strategies in austere environments, we conducted a simulation-based study comparing the operational demands of three prehospital transfusion approaches. METHODS: Three doctor-paramedic teams (six clinicians) undertook a crossover simulation of traumatic haemorrhage, completing all three arms in random order: two units red-cells-in-plasma (RCP), two units red blood cells plus two units thawed fresh frozen plasma (RBC+FFP), and two units red cells plus two units lyophilised plasma (RBC+LyoP). Outcomes were flow time (defined as time from decision-to-transfuse to completion of transfusion of all units), touch time (hands-on time) and process burden (steps, equipment, checks, personnel), timed in real-time and verified on video. A postscenario questionnaire captured user perceptions. RESULTS: All scenarios were completed without missing data. RCP consistently required the least time and operational effort. Median flow times (min:s) were 06:31 (RCP), 12:20 (RBC+FFP) and 16:29 (RBC+LyoP) (p=0.019). Median touch times (min:s) were 02:31 (RCP), 05:21 (RBC+FFP) and 13:03 (RBC+LyoP) (p=0.017). Touch/flow ratios were lowest for RCP (0.39), indicating reduced cognitive and physical load. Standardised process mapping identified 26 steps for RCP versus 46 for RBC+FFP and 52 for RBC+LyoP, reflecting a single set-up and one repetition for RCP compared with multiple repetitions and added reconstitution steps for LyoP. Equipment (4, 10, 12), checks (8, 16, 16) and personnel required (2, 2, 3) followed the same efficiency gradient. Five of six participants rated RCP as optimal for the patient, and all six for the crew; LyoP was unanimously judged as the most demanding. CONCLUSIONS: In a simulated trauma scenario, a combined RCP component was delivered more quickly and with substantially less process burden than separate components. These operational gains support combined-component strategies for prehospital haemorrhage resuscitation in both military and civilian settings