Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
2,635
result(s) for
"Macdonald, Robert"
Sort by:
The human epilepsy mutation GABRG2(Q390X) causes chronic subunit accumulation and neurodegeneration
The Q390X mutation in the GABA
A
receptor GABRG2 has been associated with Dravet syndrome in humans. In this study, the authors generated a new genetic epileptic encephalopathy animal model, the
Gabrg2
+/Q390X
knock-in mouse, and show that expression of this mutant protein leads to seizures, chronic accumulation and aggregation of mutant subunit protein and age-dependent neurodegeneration.
Genetic epilepsy and neurodegenerative diseases are two common neurological disorders that are conventionally viewed as being unrelated. A subset of patients with severe genetic epilepsies who have impaired development and often go on to die of their disease respond poorly to anticonvulsant drug therapy, suggesting a need for new therapeutic targets. Previously, we reported that multiple GABA
A
receptor epilepsy mutations result in protein misfolding and abnormal receptor trafficking. We have now developed a model of a severe human genetic epileptic encephalopathy, the
Gabrg2
+/Q390X
knock-in mouse. We found that, in addition to impairing inhibitory neurotransmission, mutant GABA
A
receptor γ2(Q390X) subunits accumulated and aggregated intracellularly, activated caspase 3 and caused widespread, age-dependent neurodegeneration. These findings suggest that the fundamental protein metabolism and cellular consequences of the epilepsy-associated mutant γ2(Q390X) ion channel subunit are not fundamentally different from those associated with neurodegeneration. Our results have far-reaching relevance for the identification of conserved pathological cascades and mechanism-based therapies that are shared between genetic epilepsies and neurodegenerative diseases.
Journal Article
Using large language models to accelerate communication for eye gaze typing users with ALS
Accelerating text input in augmentative and alternative communication (AAC) is a long-standing area of research with bearings on the quality of life in individuals with profound motor impairments. Recent advances in large language models (LLMs) pose opportunities for re-thinking strategies for enhanced text entry in AAC. In this paper, we present SpeakFaster, consisting of an LLM-powered user interface for text entry in a highly-abbreviated form, saving 57% more motor actions than traditional predictive keyboards in offline simulation. A pilot study on a mobile device with 19 non-AAC participants demonstrated motor savings in line with simulation and relatively small changes in typing speed. Lab and field testing on two eye-gaze AAC users with amyotrophic lateral sclerosis demonstrated text-entry rates 29–60% above baselines, due to significant saving of expensive keystrokes based on LLM predictions. These findings form a foundation for further exploration of LLM-assisted text entry in AAC and other user interfaces.
Individuals with severe motor impairments use gaze to type and communicate. This paper presents a large language model-based user interface that enables gaze typing in highly abbreviated forms, achieving significant motor saving and speed gain.
Journal Article
Changing places : the science and art of new urban planning
\"Urban policy innovations designed to confront the many challenges that cities face abound. In most cases, there is little evidence that a given intervention has achieved the desired outcome. In Changing Places, MacDonald, Branas and Stokes argue that there is a widespread disconnect between those who implement place-based changes-such as planners and building or land developers-and the community of scientists who are now starting to rigorously evaluate these changes. They emphasize that planners and developers need to recognize the value of scientific testing and that scientists need to embrace the indispensable and action-oriented work of planners and land developers. Though there have been other calls for place-based research, the authors focus specifically on structural interventions that are scalable and sustainable. They draw on research from multiple fields-city planning, criminology, economics, epidemiology, public health, and more-to demonstrate that well-designed changes to place can significantly improve the health and safety of large groups of people. The manuscript covers a broad range of interventions, including those focused on building and housing, land and open space, transportation and street environments, and entertainment and recreation centers. The book ends with a discussion of unintended consequences and suggestions for future research\"-- Provided by publisher.
Book
Deleterious Rare Variants Reveal Risk for Loss of GABAA Receptor Function in Patients with Genetic Epilepsy and in the General Population
Genetic epilepsies (GEs) account for approximately 50% of all seizure disorders, and familial forms include mutations in single GABAA receptor subunit genes (GABRs). In 144 sporadic GE cases (GECs), exome sequencing of 237 ion channel genes identified 520 GABR variants. Among these variants, 33 rare variants in 11 GABR genes were present in 24 GECs. To assess functional risk of variants in GECs, we selected 8 variants found in GABRA, 3 in GABRB, and 3 in GABRG and compared them to 18 variants found in the general population for GABRA1 (n = 9), GABRB3 (n = 7), and GABRG2 (n = 2). To identify deleterious variants and gain insight into structure-function relationships, we studied the gating properties, surface expression and structural perturbations of the 32 variants. Significant reduction of GABAA receptor function was strongly associated with variants scored as deleterious and mapped within the N-terminal and transmembrane domains. In addition, 12 out of 17 variants mapped along the β+/α- GABA binding interface, were associated with reduction in channel gating and were predicted to cause structural rearrangements of the receptor by in silico simulations. Missense or nonsense mutations of GABRA1, GABRB3 and GABRG2 primarily impair subunit biogenesis. In contrast, GABR variants affected receptor function by impairing gating, suggesting that different mechanisms are operating in GABR epilepsy susceptibility variants and disease-causing mutations. The functional impact of single GABR variants found in individuals with sporadic GEs warrants the use of molecular diagnosis and will ultimately improve the treatment of genetic epilepsies by using a personalized approach.
Journal Article
Assessing student performance using the national standards & grade-level outcomes for K-12 physical education
\"Provides assessments that measure student achievement of SHAPE America's Grade-Level Outcomes and thus serves as a companion book for the Standards book and the three SHAPE America Lesson Planning books. Scope--covers most of the elementary grade-level outcomes and samples for middle school and high school plus info on how to create more assessments. Written for K-12 physical education teachers, K-12 physical education administrators and curriculum writers, and PETE students\"-- Provided by publisher.
Book
6-Formylindolo(3,2-b)Carbazole (FICZ) Modulates the Signalsome Responsible for RA-Induced Differentiation of HL-60 Myeloblastic Leukemia Cells
6-Formylindolo(3,2-b)carbazole (FICZ) is a photoproduct of tryptophan and an endogenous high affinity ligand for aryl hydrocarbon receptor (AhR). It was previously reported that, in patient-derived HL-60 myeloblastic leukemia cells, retinoic acid (RA)-induced differentiation is driven by a signalsome containing c-Cbl and AhR. FICZ enhances RA-induced differentiation, assessed by expression of the membrane differentiation markers CD38 and CD11b, cell cycle arrest and the functional differentiation marker, inducible oxidative metabolism. Moreover, FICZ augments the expression of a number of the members of the RA-induced signalsome, such as c-Cbl, Vav1, Slp76, PI3K, and the Src family kinases Fgr and Lyn. Pursuing the molecular signaling responsible for RA-induced differentiation, we characterized, using FRET and clustering analysis, associations of key molecules thought to drive differentiation. Here we report that, assayed by FRET, AhR interacts with c-Cbl upon FICZ plus RA-induced differentiation, whereas AhR constitutively interacts with Cbl-b. Moreover, correlation analysis based on the flow cytometric assessment of differentiation markers and western blot detection of signaling factors reveal that Cbl-b, p-p38α and pT390-GSK3β, are not correlated with other known RA-induced signaling components or with a phenotypic outcome. We note that FICZ plus RA elicited signaling responses that were not typical of RA alone, but may represent alternative differentiation-driving pathways. In clusters of signaling molecules seminal to cell differentiation, FICZ co-administered with RA augments type and intensity of the dynamic changes induced by RA. Our data suggest relevance for FICZ in differentiation-induction therapy. The mechanism of action includes modulation of a SFK and MAPK centered signalsome and c-Cbl-AhR association.
Journal Article
Interpretable survival prediction for colorectal cancer using deep learning
Deriving interpretable prognostic features from deep-learning-based prognostic histopathology models remains a challenge. In this study, we developed a deep learning system (DLS) for predicting disease-specific survival for stage II and III colorectal cancer using 3652 cases (27,300 slides). When evaluated on two validation datasets containing 1239 cases (9340 slides) and 738 cases (7140 slides), respectively, the DLS achieved a 5-year disease-specific survival AUC of 0.70 (95% CI: 0.66–0.73) and 0.69 (95% CI: 0.64–0.72), and added significant predictive value to a set of nine clinicopathologic features. To interpret the DLS, we explored the ability of different human-interpretable features to explain the variance in DLS scores. We observed that clinicopathologic features such as T-category, N-category, and grade explained a small fraction of the variance in DLS scores (
R
2
= 18% in both validation sets). Next, we generated human-interpretable histologic features by clustering embeddings from a deep-learning-based image-similarity model and showed that they explained the majority of the variance (
R
2
of 73–80%). Furthermore, the clustering-derived feature most strongly associated with high DLS scores was also highly prognostic in isolation. With a distinct visual appearance (poorly differentiated tumor cell clusters adjacent to adipose tissue), this feature was identified by annotators with 87.0–95.5% accuracy. Our approach can be used to explain predictions from a prognostic deep learning model and uncover potentially-novel prognostic features that can be reliably identified by people for future validation studies.
Journal Article