Divergence in seasonal hydrology across northern Eurasia: Emerging trends and water cycle linkages

Discharge from large Eurasia rivers increased during the 20th century, yet much remains unknown regarding details of this increasing freshwater flux. Here, for the three largest Eurasian basins (the Ob, Yenisei, and Lena) we examine the nature of annual and seasonal discharge trends by investigating the flow changes along with those for precipitation, snow depth, and snow water equivalent. On the basis of a multiperiod trend analysis and examination of station data, we propose two characteristic regimes to explain the long‐term discharge increase from these large Eurasian rivers. Over the early decades from approximately 1936 to 1965, annual precipitation correlates well with annual discharge, and positive discharge trends are concurrent with summer/fall discharge increases. The latter decades were marked by a divergence between winter/spring flows, which increased, amid summer/fall discharge declines. A comparison of cold season precipitation (CSP) and spring discharge trends across subbasins of the Ob, Yenisei, and Lena shows limited agreement with one precipitation data set but good agreement (R2 \u3e 0.90) when a second is used. While natural variability in the Arctic system tends to mask these emerging trends, spatial and temporal changes can generally be characterized by increased solid precipitation, primarily to the north, along with a drier hydrography during the warm season

New Directions in Diagnostics for Aortic Aneurysms: Biomarkers and Machine Learning

This review article presents an appraisal of pioneering technologies poised to revolutionize the diagnosis and management of aortic aneurysm disease, with a primary focus on the thoracic aorta while encompassing insights into abdominal manifestations. Our comprehensive analysis is rooted in an exhaustive survey of contemporary and historical research, delving into the realms of machine learning (ML) and computer-assisted diagnostics. This overview draws heavily upon relevant studies, including Siemens’ published field report and many peer-reviewed publications. At the core of our survey lies an in-depth examination of ML-driven diagnostic advancements, dissecting an array of algorithmic suites to unveil the foundational concepts anchoring computer-assisted diagnostics and medical image processing. Our review extends to a discussion of circulating biomarkers, synthesizing insights gleaned from our prior research endeavors alongside contemporary studies gathered from the PubMed Central database. We elucidate the prevalent challenges and envisage the potential fusion of AI-guided aortic measurements and sophisticated ML frameworks with the computational analyses of pertinent biomarkers. By framing current scientific insights, we contemplate the transformative prospect of translating fundamental research into practical diagnostic tools. This narrative not only illuminates present strides, but also forecasts promising trajectories in the clinical evaluation and therapeutic management of aortic aneurysm disease

Psychedelics Promote Structural and Functional Neural Plasticity.

Atrophy of neurons in the prefrontal cortex (PFC) plays a key role in the pathophysiology of depression and related disorders. The ability to promote both structural and functional plasticity in the PFC has been hypothesized to underlie the fast-acting antidepressant properties of the dissociative anesthetic ketamine. Here, we report that, like ketamine, serotonergic psychedelics are capable of robustly increasing neuritogenesis and/or spinogenesis both in vitro and in vivo. These changes in neuronal structure are accompanied by increased synapse number and function, as measured by fluorescence microscopy and electrophysiology. The structural changes induced by psychedelics appear to result from stimulation of the TrkB, mTOR, and 5-HT2A signaling pathways and could possibly explain the clinical effectiveness of these compounds. Our results underscore the therapeutic potential of psychedelics and, importantly, identify several lead scaffolds for medicinal chemistry efforts focused on developing plasticity-promoting compounds as safe, effective, and fast-acting treatments for depression and related disorders

Intrathecal enzyme replacement for Hurler syndrome: biomarker association with neurocognitive outcomes.

PurposeAbnormalities in cerebrospinal fluid (CSF) have been reported in Hurler syndrome, a fatal neurodegenerative lysosomal disorder. While no biomarker has predicted neurocognitive response to treatment, one of these abnormalities, glycosaminoglycan nonreducing ends (NREs), holds promise to monitor therapeutic efficacy. A trial of intrathecal enzyme replacement therapy (ERT) added to standard treatment enabled tracking of CSF abnormalities, including NREs. We evaluated safety, biomarker response, and neurocognitive correlates of change.MethodsIn addition to intravenous ERT and hematopoietic cell transplantation, patients (N = 24) received intrathecal ERT at four peritransplant time points; CSF was evaluated at each point. Neurocognitive functioning was quantified at baseline, 1 year, and 2 years posttransplant. Changes in CSF biomarkers and neurocognitive function were evaluated for an association.ResultsOver treatment, there were significant decreases in CSF opening pressure, biomarkers of disease activity, and markers of inflammation. Percent decrease in NRE from pretreatment to final intrathecal dose posttransplant was positively associated with percent change in neurocognitive score from pretreatment to 2 years posttransplant.ConclusionIntrathecal ERT was safe and, in combination with standard treatment, was associated with reductions in CSF abnormalities. Critically, we report evidence of a link between a biomarker treatment response and neurocognitive outcome in Hurler syndrome

Cyberbullying and Sleep Disturbance Among Early Adolescents in the U.S.

ObjectiveTo determine the association between cyberbullying (victimization and perpetration) and sleep disturbance among a demographically diverse sample of 10-14-year-old early adolescents.MethodsWe analyzed cross-sectional data from the Adolescent Brain Cognitive Development (ABCD) Study (Year 2, 2018-2020) of early adolescents (10-14 years) in the US. Modified Poisson regression analyses examined the association between cyberbullying and self-reported and caregiver-reported sleep disturbance measures.ResultsIn a sample of 9,443 adolescents (mean age 12.0 years, 47.9% female, 47.8% white), 5.1% reported cyberbullying victimization, and 0.5% reported cyberbullying perpetration in the past 12 months. Cyberbullying victimization in the past 12 months was associated with adolescent-reported trouble falling/staying asleep (risk ratio [RR] 1.87, 95% confidence interval [CI] 1.57, 2.21) and caregiver-reported overall sleep disturbance of the adolescent (RR: 1.16 95% CI 1.00, 1.33), in models adjusting for sociodemographic factors and screen time. Cyberbullying perpetration in the past 12 months was associated with trouble falling/staying asleep (RR 1.95, 95% CI 1.21, 3.15) and caregiver-reported overall sleep disturbance of the adolescent (RR: 1.49, 95% CI 1.00, 2.22).ConclusionsCyberbullying victimization and perpetration are associated with sleep disturbance in early adolescence. Digital media education and counseling for adolescents, parents, teachers, and clinicians could focus on guidance to prevent cyberbullying and support healthy sleep behavior for early adolescents

Bedtime screen use behaviors and sleep outcomes: Findings from the Adolescent Brain Cognitive Development (ABCD) Study

ObjectivesTo determine associations between bedtime screen time behaviors and sleep outcomes in a national study of early adolescents.MethodsWe analyzed cross-sectional data from 10,280 early adolescents aged 10-14 (48.8% female) in the Adolescent Brain Cognitive Development Study (Year 2, 2018-2020). Regression analyses examined the association between self-reported bedtime screen use and self- and caregiver-reported sleep measures, including sleep disturbance symptoms, controlling for sex, race/ethnicity, household income, parent education, depression, data collection period (pre- vs. during COVID-19 pandemic), and study site.ResultsOverall, 16% of adolescents had at least some trouble falling or staying asleep in the past 2 weeks and 28% had overall sleep disturbance, based on caregiver reports. Adolescents who had a television or an Internet-connected electronic device in the bedroom had a greater risk of having trouble falling or staying asleep (adjusted risk ratio 1.27, 95% CI 1.12-1.44) and overall sleep disturbance (adjusted risk ratio 1.15, 95% CI 1.06-1.25). Adolescents who left their phone ringer activated overnight had more trouble falling/staying asleep and greater overall sleep disturbance compared to those who turned off their cell phones at bedtime. Streaming movies, playing video games, listening to music, talking/texting on the phone, and using social media or chat rooms were all associated with trouble falling/staying asleep and sleep disturbance.ConclusionsSeveral bedtime screen use behaviors are associated with sleep disturbances in early adolescents. The study's findings can inform guidance for specific bedtime screen behaviors among early adolescents

Genetically engineered minipigs model the major clinical features of human neurofibromatosis type 1.

Neurofibromatosis Type 1 (NF1) is a genetic disease caused by mutations in Neurofibromin 1 (NF1). NF1 patients present with a variety of clinical manifestations and are predisposed to cancer development. Many NF1 animal models have been developed, yet none display the spectrum of disease seen in patients and the translational impact of these models has been limited. We describe a minipig model that exhibits clinical hallmarks of NF1, including café au lait macules, neurofibromas, and optic pathway glioma. Spontaneous loss of heterozygosity is observed in this model, a phenomenon also described in NF1 patients. Oral administration of a mitogen-activated protein kinase/extracellular signal-regulated kinase inhibitor suppresses Ras signaling. To our knowledge, this model provides an unprecedented opportunity to study the complex biology and natural history of NF1 and could prove indispensable for development of imaging methods, biomarkers, and evaluation of safety and efficacy of NF1-targeted therapies