Membraneless organelles involved in RNA processing are biomolecular condensates assembled by phase separation. Despite the important role of intrinsically disordered protein regions (IDRs), the ...specific interactions underlying IDR phase separation and its functional consequences remain elusive. To address these questions, we used minimal condensates formed from the C-terminal disordered regions of two interacting translational regulators, FMRP and CAPRIN1. Nuclear magnetic resonance spectroscopy of FMRP-CAPRIN1 condensates revealed interactions involving arginine-rich and aromatic-rich regions. We found that different FMRP serine/threonine and CAPRIN1 tyrosine phosphorylation patterns control phase separation propensity with RNA, including subcompartmentalization, and tune deadenylation and translation rates in vitro. The resulting evidence for residue-specific interactions underlying co-phase separation, phosphorylation-modulated condensate architecture, and enzymatic activity within condensates has implications for how the integration of signaling pathways controls RNA processing and translation.
Activity-dependent translation requires the transport of mRNAs within membraneless protein assemblies known as neuronal granules from the cell body toward synaptic regions. Translation of mRNA is ...inhibited in these granules during transport but quickly activated in response to neuronal stimuli at the synapse. This raises an important question: how does synaptic activity trigger translation of once-silenced mRNAs? Here,we demonstrate a strong connection between phase separation, the process underlying the formation of many different types of cellular granules, and in vitro inhibition of translation. By using the Fragile X Mental Retardation Protein (FMRP), an abundant neuronal granule component and translational repressor, we show that FMRP phase separates in vitro with RNA into liquid droplets mediated by its C-terminal low-complexity disordered region (i.e., FMRPLCR). FMRPLCR posttranslational modifications by phosphorylation and methylation have opposing effects on in vitro translational regulation, which corroborates well with their critical concentrations for phase separation. Our results, combined with bioinformatics evidence, are supportive of phase separation as a general mechanism controlling activity-dependent translation.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
It is unclear how disease mutations impact intrinsically disordered protein regions (IDRs), which lack a stable folded structure. These mutations, while prevalent in disease, are frequently neglected ...or annotated as variants of unknown significance. Biomolecular phase separation, a physical process often mediated by IDRs, has increasingly appreciated roles in cellular organization and regulation. We find that autism spectrum disorder (ASD)- and cancer-associated proteins are enriched for predicted phase separation propensities, suggesting that IDR mutations disrupt phase separation in key cellular processes. More generally, we hypothesize that combinations of small-effect IDR mutations perturb phase separation, potentially contributing to “missing heritability” in complex disease susceptibility.
Could mutations that alter protein phase separation properties, but not structure, potentially explain some of the “missing heritability” in complex disease susceptibility?
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Protein phase separation is implicated in formation of membraneless organelles, signaling puncta and the nuclear pore. Multivalent interactions of modular binding domains and their target motifs can ...drive phase separation. However, forces promoting the more common phase separation of intrinsically disordered regions are less understood, with suggested roles for multivalent cation-pi, pi-pi, and charge interactions and the hydrophobic effect. Known phase-separating proteins are enriched in pi-orbital containing residues and thus we analyzed pi-interactions in folded proteins. We found that pi-pi interactions involving non-aromatic groups are widespread, underestimated by force-fields used in structure calculations and correlated with solvation and lack of regular secondary structure, properties associated with disordered regions. We present a phase separation predictive algorithm based on pi interaction frequency, highlighting proteins involved in biomaterials and RNA processing.
To identify pelvic floor muscle therapy mobile health applications (apps) targeting women with urinary incontinence (UI), and evaluate them in a standardized fashion.
A systematic search of English ...language apps on the Canadian App Store (iOS) and Google Play (Android) Store was performed. Eligible apps were evaluated independently by 5 reviewers using the validated Mobile App Rating Scale (MARS) tool. Descriptive characteristics were summarized and MARS subscale and overall quality scores werereported.
Of 139 mobile health apps identified, 20 unique apps were included for full review, of which there were 7 iOS only apps, 6 Android only apps, and 7 apps available in both stores. At the time of analysis, most apps had been updated within the last year (60%). Only 1 app had been trialed and verified by evidence in scientific literature. The majority of apps were free to download (80%). The median (interquartile range) MARS overall quality score was 3.7 (0.8) on a 0-5 scale, ranging from 2.7 to 4.1. The highest-rated subscale was “functionality” with a median score of 4.1 (0.6); the lowest-rated was “information” with a median score of 3.4 (0.6). The median MARS subjective quality score was 2.9 (1.0).
There are both free and paid apps available on-line that deliver pelvic floor muscle therapy programs. Evaluation using the MARS tool identified that many apps are not of high quality, and only 1 was evidence-based and has been trialed clinically. This knowledge is relevant to the choice of apps by both patients and caregivers.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Microexons represent the most highly conserved class of alternative splicing, yet their functions are poorly understood. Here, we focus on closely related neuronal microexons overlapping prion-like ...domains in the translation initiation factors, eIF4G1 and eIF4G3, the splicing of which is activity dependent and frequently disrupted in autism. CRISPR-Cas9 deletion of these microexons selectively upregulates synaptic proteins that control neuronal activity and plasticity and further triggers a gene expression program mirroring that of activated neurons. Mice lacking the Eif4g1 microexon display social behavior, learning, and memory deficits, accompanied by altered hippocampal synaptic plasticity. We provide evidence that the eIF4G microexons function as a translational brake by causing ribosome stalling, through their propensity to promote the coalescence of cytoplasmic granule components associated with translation repression, including the fragile X mental retardation protein FMRP. The results thus reveal an autism-disrupted mechanism by which alternative splicing specializes neuronal translation to control higher order cognitive functioning.
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•Autism-disrupted eIF4G microexons mediate activity-dependent responses•eIF4G microexons suppress the expression of critical synaptic proteins•eIF4G microexon-deficient mice display social behavior and memory deficits•eIF4G microexons coalesce with neuronal granule components and stall ribosomes
Gonatopoulos-Pournatzis et al. demonstrate that conserved, autism-disrupted microexons in eIF4G translation initiation factors regulate the neuronal proteome and control higher order cognitive functions. The microexons function as a translational brake and elicit ribosome stalling on transcripts encoding synaptic proteins through their propensity to coalesce with FMRP and other neuronal granule components.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
A common maneuver drivers perform and experience on the road is changing lanes. Autonomous vehicles are required to engage a lane change safely and to react to the other road users’ lane changes. To ...develop autonomous vehicles that change lanes or respond to the lead vehicle’s lane changes in a safe and human-like way, one should investigate the factors that affect human driver responses. By reviewing the literature to identify potential factors, this study extracted these factors from a naturalistic driving data set and associated them with driver deceleration and acceleration responses to the lead vehicle’s cut-in and cut-out to develop predictive models for the impact of the events on traffic flow. After the events were verified as accurate, the variables associated with the events, including range, range rate, speed, lateral position in the lane, and average acceleration were analyzed using logistic regression, support vector machines (SVM), and two forms of decision trees. In total, 799 cut-in events and 684 cut-out events with the necessary variables were applied for analysis. The significant variables influencing driver behavior were found, and using these variables, the predictive models achieved around 80% accuracy for cut-ins, and 73% accuracy for cut-outs on test data. These results will assist in the future design of autonomous vehicle control to minimize detrimental effects on traffic when changing lanes and safe longitudinal control when responding to a lead vehicle’s lane changes, allowing for safe integration with human drivers, and better design of driver assistance systems.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
Purposes
To review the uses of AI for magnetic resonance (MR) imaging assessment of primary pediatric cancer and identify common literature topics and knowledge gaps. To assess the adherence of the ...existing literature to the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) guidelines.
Materials and methods
A scoping literature search using MEDLINE, EMBASE and Cochrane databases was performed, including studies of > 10 subjects with a mean age of < 21 years. Relevant data were summarized into three categories based on AI application: detection, characterization, treatment and monitoring. Readers independently scored each study using CLAIM guidelines, and inter-rater reproducibility was assessed using intraclass correlation coefficients.
Results
Twenty-one studies were included. The most common AI application for pediatric cancer MR imaging was pediatric tumor diagnosis and detection (13/21 62% studies). The most commonly studied tumor was posterior fossa tumors (14 67% studies). Knowledge gaps included a lack of research in AI-driven tumor staging (0/21 0% studies), imaging genomics (1/21 5% studies), and tumor segmentation (2/21 10% studies). Adherence to CLAIM guidelines was moderate in primary studies, with an average (range) of 55% (34%–73%) CLAIM items reported. Adherence has improved over time based on publication year.
Conclusion
The literature surrounding AI applications of MR imaging in pediatric cancers is limited. The existing literature shows moderate adherence to CLAIM guidelines, suggesting that better adherence is required for future studies.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract Background We examined attention-deficit hyperactivity disorder in adolescents with epilepsy and the association with seizure-related and sociodemographic variables. Methods Strengths and ...Weakness of Attention-Deficit Hyperactivity Disorder Symptoms and Normal Behaviors rating scale was administered to 122 children with epilepsy and 50 children with asthma, aged 10 to 18 years attending mainstream schools. Results Twenty-nine (23.7%) adolescents with epilepsy compared with five (10%) with asthma had attention deficit hyperactivity disorder ( P = 0.037). Adolescents with epilepsy had a significantly higher score in the inattention subscale when compared with those with asthma (−0.25 ± 1.2 vs −0.64 ± 1.07, P = 0.049). Combined subtype was most frequent in the epilepsy group. Oppositional defiant disorders were more prevalent in those having attention deficit hyperactivity disorder. Psychiatric assistance had only been provided to one third of our patients with epilepsy and attention deficit hyperactivity disorder at the time of study. There was a negative correlation between attention deficit hyperactivity disorder scores and age of seizure onset. A positive correlation was observed between the number of antiepileptic drugs and the inattentive subscale score. The impact of various correlates on individual subtypes was not identical. Independent risk factors associated with attention deficit hyperactivity disorder were medical comorbidities (odds ratio = 12.82, 95% confidence interval 4.44, 37.03, P < 0.0001) and age at seizure onset (odds ratio = 0.73, 95% confidence interval 0.56, 0.94, P = 0.016). Conclusions Attention deficit hyperactivity disorder is overrepresented in adolescents with epilepsy; screening for its symptoms should be an integral part of management in adolescents with epilepsy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
► The driving model may predict the effects of time-gaps and in-vehicle tasks on driving performance. ► Predictions from the model were validated by the experiment with a bus-driving simulator. ► For ...auto manufacturers, this modeling approach is helpful for the ACC prototype evaluation.
Researchers have devoted a great deal of attention to the effects of driver assist systems on driver performance. This article describes a modeling approach to simulate the effects of time-gaps for adaptive cruise control (ACC) and manual in-vehicle tasks on bus-driver performance. A concept model was built with the knowledge of modularization, parameterization, and parallel processing. By running the model, the predictions for the effects of five levels of time-gaps and two types of in-vehicle tasks were collected in three measures: (1) mean gap, (2) minimum gap, and (3) collision rate. The model performed well in prediction, especially when driving with in-vehicle tasks. Predictions from the model were validated by the experiment with a verified fixed-base bus-driving simulator, used in the authors’ previous studies. Throughout the modeling approach, this research provides a theoretical and accurate way to assess effects of time-gaps and vehicle-equipped interfaces. In follow-up research, the authors will apply this approach to evaluate other driving assist systems (e.g. collision warning systems and navigation systems) to create a customized software kit.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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