Pediatric Organ and Tissue Donation—A 10-Year Retrospective Study in Portugal

Organ and tissue donation can transform lives. One donor can ensure the survival of up to 8 people through their organs and improve the quality of life for dozens more through tissue donation. Portugal has an excellent transplantation rate, but deaths still occur while waiting for an organ. The study aimed to analyze pediatric organ and tissue donors nationally and evaluate brain deaths in a pediatric intensive care unit (PICU) over the past 10 years to identify any potential lost donors. We conducted a retrospective descriptive study of pediatric organ and tissue donors and diagnosed brain deaths from January 2011 to December 2021. Demographic and clinical data were analyzed, including those provided by the National Transplant Coordination. Over the past 10 years in Portugal, 121 pediatric donors (11.7 per million population) were collected, and 569 organs and tissues were collected. During the same period in the PICU, there were 125 deaths, including 20 brain deaths. Of this group, 4 were organ and tissue donors. In the non-donor group (n = 16), a potential lost donor case stands out. Pediatric specialists need to be more familiar with the donation process, which would enable the identification and optimization of all potential donors, thus minimizing the number of potentially lost organs.info:eu-repo/semantics/publishedVersio

Entanglement renormalization and boundary critical phenomena

The multiscale entanglement renormalization ansatz is applied to the study of boundary critical phenomena. We compute averages of local operators as a function of the distance from the boundary and the surface contribution to the ground state energy. Furthermore, assuming a uniform tensor structure, we show that the multiscale entanglement renormalization ansatz implies an exact relation between bulk and boundary critical exponents known to exist for boundary critical systems.Comment: 6 pages, 4 figures; for a related work see arXiv:0912.164

African genomes illuminate the early history and transition to selfing in Arabidopsis thaliana

Over the past 20 y, many studies have examined the history of the plant ecological and molecular model, Arabidopsis thaliana, in Europe and North America. Although these studies informed us about the recent history of the species, the early history has remained elusive. In a large-scale genomic analysis of African A. thaliana, we sequenced the genomes of 78 modern and herbarium samples from Africa and analyzed these together with over 1,000 previously sequenced Eurasian samples. In striking contrast to expectations, we find that all African individuals sampled are native to this continent, including those from sub-Saharan Africa. Moreover, we show that Africa harbors the greatest variation and represents the deepest history in the A. thaliana lineage. Our results also reveal evidence that selfing, a major defining characteristic of the species, evolved in a single geographic region, best represented today within Africa. Demographic inference supports a model in which the ancestral A. thaliana population began to split by 120-90 kya, during the last interglacial and Abbassia pluvial, and Eurasian populations subsequently separated from one another at around 40 kya. This bears striking similarities to the patterns observed for diverse species, including humans, implying a key role for climatic events during interglacial and pluvial periods in shaping the histories and current distributions of a wide range of species

Long-Term Safety of Growth Hormone in Adults With Growth Hormone Deficiency:Overview of 15 809 GH-Treated Patients

Context Data on long-term safety of growth hormone (GH) replacement in adults with GH deficiency (GHD) are needed. Objective We aimed to evaluate the safety of GH in the full KIMS (Pfizer International Metabolic Database) cohort. Methods The worldwide, observational KIMS study included adults and adolescents with confirmed GHD. Patients were treated with GH (Genotropin [somatropin]; Pfizer, NY) and followed through routine clinical practice. Adverse events (AEs) and clinical characteristics (eg, lipid profile, glucose) were collected. Results A cohort of 15 809 GH-treated patients were analyzed (mean follow-up of 5.3 years). AEs were reported in 51.2% of patients (treatment-related in 18.8%). Crude AE rate was higher in patients who were older, had GHD due to pituitary/hypothalamic tumors, or adult-onset GHD. AE rate analysis adjusted for age, gender, etiology, and follow-up time showed no correlation with GH dose. A total of 606 deaths (3.8%) were reported (146 by neoplasms, 71 by cardiac/vascular disorders, 48 by cerebrovascular disorders). Overall, de novo cancer incidence was comparable to that in the general population (standard incidence ratio 0.92; 95% CI, 0.83-1.01). De novo cancer risk was significantly lower in patients with idiopathic/congenital GHD (0.64; 0.43-0.91), but similar in those with pituitary/hypothalamic tumors or other etiologies versus the general population. Neither adult-onset nor childhood-onset GHD was associated with increased de novo cancer risks. Neutral effects were observed in lipids/fasting blood glucose levels. Conclusion These final KIMS cohort data support the safety of long-term GH replacement in adults with GHD as prescribed in routine clinical practice

Targeted next-generation sequencing provides novel clues for associated epilepsy and cardiac conduction disorder/SUDEP

Sudden unexpected death in epilepsy is an unpredicted condition in patients with a diagnosis of epilepsy, and autopsy does not conclusively identify cause of death. Although the pathophysiological mechanisms that underlie this entity remain unknown, the fact that epilepsy can affect cardiac function is not surprising. The genetic factors involving ion channels co-expressed in the heart and brain and other candidate genes have been previously described. In the present study, 20 epilepsy patients with personal or family history of heart rhythm disturbance/cardiac arrhythmias/sudden death were sequenced using a custom resequencing panel. Twenty-six relatives were genetically analysed to ascertain the family segregation in ten individuals. Four subjects revealed variants with positive genotype-phenotype segregation: four missense variants in the CDKL5, CNTNAP2, GRIN2A and ADGRV1 genes and one copy number variant in KCNQ1. The potential pathogenic role of variants in new candidate genes will need further studies in larger cohorts, and the evaluation of the potential pathogenic role in the cardio-cerebral mechanisms requires in vivo/in vitro studies. In addition to family segregation, evaluation of the potential pathogenic roles of these variants in cardio-cerebral mechanisms by in vivo/in vitro studies should also be performed. The potential pathogenic role of variants in new candidate genes will need further studies in larger cohorts

The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services

BACKGROUND: Many complementary solutions are available for the identifier mapping problem. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. RESULTS: Here we present BridgeDb, a software framework for gene, protein and metabolite identifier mapping. This framework provides a standardized interface layer through which bioinformatics tools can be connected to different identifier mapping services. This approach makes it easier for tool developers to support identifier mapping. Mapping services can be combined or merged to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb provides its own ready-to-go mapping services, both in webservice and local database forms. However, the framework is intended for customization and adaptation to any identifier mapping service. BridgeDb has already been integrated into several bioinformatics applications. CONCLUSION: By uncoupling bioinformatics tools from mapping services, BridgeDb improves capability and flexibility of those tools. All described software is open source and available at http://www.bridgedb.org

Predicting Function Delay with a Machine Learning Model: Improve the Long-term Survival of Pancreatic Grafts

The impact of delayed graft function on outcomes following various solid organ transplants is well documented and addressed in the literature. Delayed graft function following various solid organ transplants is associated with both short- and long-term graft survival issues. In a retrospective cohort study including 106 patients we evaluated whether pancreas graft survival differs according to moment of insulin therapy following simultaneous pancreaskidney transplant. As a result, we aimed to identify possible risk factors and build a machine-learning-based model that predicts the likelihood of dysfunction following SPK transplant patients based on day zero data after transplant, allowing to enhance pancreatic graft survival. Feature selection by Relief algorithm yielded donor features, age, cause of death, hemoglobin, gender, ventilation days, days in ICU, length of cardiac respiratory arrest and recipient features, gender, long-term insulin, dialysis type, time of diabetes mellitus, vPRA pre-Tx, number of HLA-A mismatches and PRDI, all contributed to the models' strength.info:eu-repo/semantics/publishedVersio

Identifying multimorbidity profiles associated with COVID-19 severity in chronic patients using network analysis in the PRECOVID Study; 35181720

A major risk factor of COVID-19 severity is the patient''s health status at the time of the infection. Numerous studies focused on specific chronic diseases and identified conditions, mainly cardiovascular ones, associated with poor prognosis. However, chronic diseases tend to cluster into patterns, each with its particular repercussions on the clinical outcome of infected patients. Network analysis in our population revealed that not all cardiovascular patterns have the same risk of COVID-19 hospitalization or mortality and that this risk depends on the pattern of multimorbidity, besides age and sex. We evidenced that negative outcomes were strongly related to patterns in which diabetes and obesity stood out in older women and men, respectively. In younger adults, anxiety was another disease that increased the risk of severity, most notably when combined with menstrual disorders in women or atopic dermatitis in men. These results have relevant implications for organizational, preventive, and clinical actions to help meet the needs of COVID-19 patients. © 2022, The Author(s)