10 research outputs found

    Cerebellar alterations in a model of Down syndrome: The role of the Dyrk1A gene

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    Down syndrome (DS) is characterized by a marked reduction in the size of the brain and cerebellum. These changes play an important role in the motor alterations and cognitive disabilities observed in this condition. The Ts65Dn (TS) mouse, the most commonly used model of DS, reflects many DS phenotypes, including alterations in cerebellar morphology. One of the genes that is overexpressed in both individuals with DS and TS mice is DYRK1A/Dyrk1A (dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1A), which has been implicated in the altered cerebellar structural and functional phenotypes observed in both populations. The aim of this study was to evaluate the effect of Dyrk1A on different alterations observed in the cerebellum of TS animals. TS mice were crossed with Dyrk1A +/- KO mice to obtain mice with a triplicate segment of Mmu16 that included Dyrk1A (TS +/+/+), mice with triplicate copies of the same genes that carried only two copies of Dyrk1A (TS +/+/-), euploid mice that expressed a normal dose of Dyrk1A (CO +/+) and CO animals with a single copy of Dyrk1A (CO +/-). Male mice were used for all experiments. The normalization of the Dyrk1A gene dosage did not rescue the reduced cerebellar volume. However, it increased the size of the granular and molecular layers, the densities of granular and Purkinje cells, and dendritic arborization. Furthermore, it improved the excitatory/inhibitory balance and walking pattern of TS +/+/- mice. These results support the hypothesis that Dyrk1A is involved in some of the structural and functional cerebellar phenotypes observed in the TS mouse model.This work was supported by grants from the Jerome Lejeune Foundation and Fundación Tatiana Pérez de Guzmán el Bueno and the Spanish Ministry of Economy and Competitiveness (PSI-2016-76194-R, AEI/FEDER, EU) and “Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED, CB06/05/0037)” from Spain

    Early neurological deterioration after subarachnoid haemorrhage: risk factors and impact on outcome

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    Background Early neurological deterioration occurs frequently after subarachnoid haemorrhage (SAH). The impact on hospital course and outcome remains poorly defined. Methods We identified risk factors for worsening on the Hunt–Hess grading scale within the first 24 h after admission in 609 consecutively admitted aneurysmal SAH patients. Admission risk factors and the impact of early worsening on outcome was evaluated using multivariable analysis adjusting for age, gender, admission clinical grade, admission year and procedure type. Outcome was evaluated at 12 months using the modified Rankin Scale (mRS). Results 211 patients worsened within the first 24 h of admission (35%). In a multivariate adjusted model, early worsening was associated with older age (OR 1.02, 95% CI 1.001 to 1.03; p=0.04), the presence of intracerebral haematoma on initial CT scan (OR 2.0, 95% CI 1.2 to 3.5; p=0.01) and higher SAH and intraventricular haemorrhage sum scores (OR 1.05, 95% CI 1.03 to 1.08 and 1.1, 95% CI 1.01 to 1.2; p less than 0.001 and 0.03, respectively). Early worsening was associated with more hospital complications and prolonged length of hospital stay and was an independent predictor of death (OR 12.1, 95% CI 5.7 to 26.1; p less than 0.001) and death or moderate to severe disability (mRS 4–6, OR 8.4, 95% CI 4.9 to 14.5; p=0.01) at 1 year. Conclusions Early worsening after SAH occurs in 35% of patients, is predicted by clot burden and is associated with mortality and poor functional outcome at 1 year

    From Human Days to Machine Seconds: Automatically Answering and Generating Machine Learning Final Exams

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    A final exam in machine learning at a top institution such as MIT, Harvard, or Cornell typically takes faculty days to write, and students hours to solve. We demonstrate that large language models pass machine learning finals at a human level, on finals available online after the models were trained, and automatically generate new human-quality final exam questions in seconds. Previous work has developed program synthesis and few-shot learning methods to solve university-level problem set questions in mathematics and STEM courses. In this work, we develop and compare methods that solve final exams, which differ from problem sets in several ways: the questions are longer, have multiple parts, are more complicated, and span a broader set of topics. We curate a dataset and benchmark of questions from machine learning final exams available online and code for answering these questions and generating new questions. We show how to generate new questions from other questions and course notes. For reproducibility and future research on this final exam benchmark, we use automatic checkers for multiple-choice, numeric, and questions with expression answers. We perform ablation studies comparing zero-shot learning with few-shot learning and chain-of-thought prompting using GPT-3, OPT, Codex, and ChatGPT across machine learning topics and find that few-shot learning methods perform best. We highlight the transformative potential of language models to streamline the writing and solution of large-scale assessments, significantly reducing the workload from human days to mere machine seconds. Our results suggest that rather than banning large language models such as ChatGPT in class, instructors should teach students to harness them by asking students meta-questions about correctness, completeness, and originality of the responses generated, encouraging critical thinking in academic studies.Comment: 9 page

    Síndrome de Behcet: Presentación de un caso

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    Se presentó un paciente joven masculino que acudió a Consulta de Reumatología por presentar aumento de volumen articular asociado a úlceras en el escroto y aftas orales, se interpretó inicialmente como un síndrome de Reiter. En el curso del ingreso se constató la presencia de foliculitis en piel de miembros superiores, tórax y cara e iridoconjuntivitis bilateral, en los rayos X sólo se observó el aumento de partes blandas en la articulación comprometida, el resto de los exámenes complementarios sólo mostraron de interés una aceleración moderada de la velocidad de sedimentación globular. Se rediscutió nuevamente y se observó que presentaba los 4 criterios mayores para el diagnóstico de síndrome de Behcet completo.A young male patient is presented, who went to Rheumatology Medical Service because he had an increased articular volume caused by scrotum ulcers and aphthous ulcers. This case was initially regarded as Reiter´s Syndrome. In the course of the admission, foliculitis in upper limbs, thorax and face skin as well as bilateral iridioconjunctivitis were found; X-ray test showed increased soft parts in the compromised articulation. The rest of the supplementary tests only showed a moderate acceleration of globular sedimentation speed. The case was re-discussed and it was observed that the four main criteria for the diagnosis of a full Behcet´s Syndrome were present

    A Dataset for Learning University STEM Courses at Scale and Generating Questions at a Human Level

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    We present a new dataset for learning to solve, explain, and generate university-level STEM questions from 27 courses across a dozen departments in seven universities. We scale up previous approaches to questions from courses in the departments of Mechanical Engineering, Materials Science and Engineering, Chemistry, Electrical Engineering, Computer Science, Physics, Earth Atmospheric and Planetary Sciences, Economics, Mathematics, Biological Engineering, Data Systems, and Society, and Statistics. We visualize similarities and differences between questions across courses. We demonstrate that a large foundation model is able to generate questions that are as appropriate and at the same difficulty level as human-written questions
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