Faculty Bibliography

OBJECTIVES/OBJECTIVE:To assess differences in career longevity, as a potential marker of athlete well-being, before and after the 1995 implementation of the Women's Tennis Association (WTA) Age Eligibility Rule (AER) and Player Development Programmes (PDP), which focused on organisational, physical and psychosocial education, skill building and support for adolescent athletes (≤17 years). METHODS:Career longevity data were collected through 2019 on adolescent players who began professional tournament play between 1970 and 2014 and reached a WTA singles ranking of 1-150 for a minimum of 1 week during their careers. Players were separated into pre-AER/PDP and post-AER/PDP groups, consisting of those who played their first professional events (FPE) before or after 1 January 1995. Measures of career longevity included career duration and premature retirement. RESULTS:Eight-hundred and eleven players were included in this study (51% pre-AER/PDP). The median career duration was 14.2 years for the post-AER/PDP group compared with 12.1 years for the pre-AER/PDP group (p<0.001). Moreover, post-AER/PDP players had higher probabilities of 10-year and 15-year careers compared with pre-AER/PDP players. After adjusting for age at FPE, athletes in the pre-AER/PDP group had an increased risk of shorter career duration (HR 1.55; 95% CI 1.31 to 1.83) and increased odds of premature retirement (OR 5.39; 95% CI 2.28 to 12.75) than athletes in the post-AER/PDP group. CONCLUSIONS:Adolescent athletes participating on the WTA after the combined AER/PDP initiative had longer career durations, higher probabilities of 10-year and 15-year careers, and decreased risk of premature retirement compared with those participating prior to AER/PDP. Organisational practices that encompass both education and competition regulation can positively affect career longevity related to improving athlete well-being.

Switching between enzyme replacement therapies (ERT) and substrate reduction therapies (SRT) in patients with type 1 Gaucher disease (GD1) is not uncommon; however, the reasons for switchng treatments have not been explored in detail. Data from the Gaucher Outcome Survey (GOS), an international registry for patients with confirmed GD, were used to evaluate the reasons for, and consequences of, switching between these treatment types. Of the 1843 patients enrolled in GOS on 25 February 2020, 245 had undergone a treatment switch: 222 from initial ERT to SRT (of whom 88 later switched back to ERT) and 23 from initial SRT to ERT. The most common reasons for ERT-SRT switching were duration of infusion (25.4%), drug shortage (22.0%), and adverse events (AEs; 11.9%), and for SRT-ERT switching, AEs (63.6%), lack of beneficial effect (16.4%), and participation in a clinical trial (9.1%). Bodyweight and hematologic parameters largely remained stable before and after switching between ERT and SRT, although with substantial variation between patients. These findings contribute to understanding why treatment switching occurs in patients with GD, and may help physicians recognize the real-world impact of treatment switching between ERT and SRT for patients with GD.

Non-motor symptoms of Parkinson's disease (PD) such as dysautonomia and REM sleep behavior disorder (RBD) are recognized to be important prodromal symptoms that may also indicate clinical subtypes of PD with different pathogenesis. Unbiased clustering analyses showed that subjects with dysautonomia and RBD symptoms, as well as early cognitive dysfunction, have faster progression of the disease. Through analysis of the Parkinson's Progression Markers Initiative (PPMI) de novo PD cohort, we tested the hypothesis that symptoms of dysautonomia and RBD, which are readily assessed by standard questionnaires in an ambulatory care setting, may help to independently prognosticate disease progression. Although these two symptoms associate closely, dysautonomia symptoms predict severe progression of motor and non-motor symptoms better than RBD symptoms across the 3-year follow-up period. Autonomic system involvement has not received as much attention and may be important to consider for stratification of subjects for clinical trials and for counseling patients.

Smart health applications have received significant attention in recent years. Novel applications hold significant promise to overcome many of the inconveniences faced by persons with disabilities throughout daily living. For people with blindness and low vision (BLV), environmental perception is compromised, creating myriad difficulties. Precise localization is still a gap in the field and is critical to safe navigation. Conventional GNSS positioning cannot provide satisfactory performance in urban canyons. 3D mapping-aided (3DMA) GNSS may serve as an urban GNSS solution, since the availability of 3D city models has widely increased. As a result, this study developed a real-time 3DMA GNSS-positioning system based on state-of-the-art 3DMA GNSS algorithms. Shadow matching was integrated with likelihood-based ranging 3DMA GNSS, generating positioning hypothesis candidates. To increase robustness, the 3DMA GNSS solution was then optimized with Doppler measurements using factor graph optimization (FGO) in a loosely-coupled fashion. This study also evaluated positioning performance using an advanced wearable system's recorded data in New York City. The real-time forward-processed FGO can provide a root-mean-square error (RMSE) of about 21 m. The RMSE drops to 16 m when the data is post-processed with FGO in a combined direction. Overall results show that the proposed loosely-coupled 3DMA FGO algorithm can provide a better and more robust positioning performance for the multi-sensor integration approach used by this wearable for persons with BLV.

Post-zygotically acquired genetic variants, or somatic variants, that arise during cortical development have emerged as important causes of focal epilepsies, particularly those due to malformations of cortical development. Pathogenic somatic variants have been identified in many genes within the PI3K-AKT-mTOR-signalling pathway in individuals with hemimegalencephaly and focal cortical dysplasia (type II), and more recently in SLC35A2 in individuals with focal cortical dysplasia (type I) or non-dysplastic epileptic cortex. Given the expanding role of somatic variants across different brain malformations, we sought to delineate the landscape of somatic variants in a large cohort of patients who underwent epilepsy surgery with hemimegalencephaly or focal cortical dysplasia. We evaluated samples from 123 children with hemimegalencephaly (n = 16), focal cortical dysplasia type I and related phenotypes (n = 48), focal cortical dysplasia type II (n = 44), or focal cortical dysplasia type III (n = 15). We performed high-depth exome sequencing in brain tissue-derived DNA from each case and identified somatic single nucleotide, indel and large copy number variants. In 75% of individuals with hemimegalencephaly and 29% with focal cortical dysplasia type II, we identified pathogenic variants in PI3K-AKT-mTOR pathway genes. Four of 48 cases with focal cortical dysplasia type I (8%) had a likely pathogenic variant in SLC35A2. While no other gene had multiple disease-causing somatic variants across the focal cortical dysplasia type I cohort, four individuals in this group had a single pathogenic or likely pathogenic somatic variant in CASK, KRAS, NF1 and NIPBL, genes previously associated with neurodevelopmental disorders. No rare pathogenic or likely pathogenic somatic variants in any neurological disease genes like those identified in the focal cortical dysplasia type I cohort were found in 63 neurologically normal controls (P = 0.017), suggesting a role for these novel variants. We also identified a somatic loss-of-function variant in the known epilepsy gene, PCDH19, present in a small number of alleles in the dysplastic tissue from a female patient with focal cortical dysplasia IIIa with hippocampal sclerosis. In contrast to focal cortical dysplasia type II, neither focal cortical dysplasia type I nor III had somatic variants in genes that converge on a unifying biological pathway, suggesting greater genetic heterogeneity compared to type II. Importantly, we demonstrate that focal cortical dysplasia types I, II and III are associated with somatic gene variants across a broad range of genes, many associated with epilepsy in clinical syndromes caused by germline variants, as well as including some not previously associated with radiographically evident cortical brain malformations.

Multiple system atrophy (MSA) is a rare neurodegenerative disease that is characterized by neuronal loss and gliosis in multiple areas of the central nervous system including striatonigral, olivopontocerebellar and central autonomic structures. Oligodendroglial cytoplasmic inclusions containing misfolded and aggregated α-synuclein are the histopathological hallmark of MSA. A firm clinical diagnosis requires the presence of autonomic dysfunction in combination with parkinsonism that responds poorly to levodopa and/or cerebellar ataxia. Clinical diagnostic accuracy is suboptimal in early disease because of phenotypic overlaps with Parkinson disease or other types of degenerative parkinsonism as well as with other cerebellar disorders. The symptomatic management of MSA requires a complex multimodal approach to compensate for autonomic failure, alleviate parkinsonism and cerebellar ataxia and associated disabilities. None of the available treatments significantly slows the aggressive course of MSA. Despite several failed trials in the past, a robust pipeline of putative disease-modifying agents, along with progress towards early diagnosis and the development of sensitive diagnostic and progression biomarkers for MSA, offer new hope for patients.

Neural responses to visual stimuli exhibit complex temporal dynamics, including sub-additive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. These phenomena are often studied independently. Here, we demonstrate these phenomena within the same experiment and model the underlying neural computations with a single computational model. We extracted time-varying responses from electrocorticographic (ECoG) recordings from patients presented with stimuli that varied in contrast, duration, and inter-stimulus interval (ISI). Aggregating data across patients from both sexes yielded 98 electrodes with robust visual responses, covering both earlier (V1-V3) and higher-order (V3a/b, LO, TO, IPS) retinotopic maps. In all regions, the temporal dynamics of neural responses exhibit several non-linear features: peak response amplitude saturates with high contrast and longer stimulus durations; the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs; response latency decreases with increasing contrast. These features are accurately captured by a computational model comprised of a small set of canonical neuronal operations: linear filtering, rectification, exponentiation, and a delayed divisive normalization. We find that an increased normalization term captures both contrast- and adaptation-related response reductions, suggesting potentially shared underlying mechanisms. We additionally demonstrate both changes and invariance in temporal response dynamics between earlier and higher-order visual areas. Together, our results reveal the presence of a wide range of temporal and contrast-dependent neuronal dynamics in the human visual cortex, and demonstrate that a simple model captures these dynamics at millisecond resolution.SIGNIFICANCE STATEMENTSensory inputs and neural responses change continuously over time. It is especially challenging to understand a system that has both dynamic inputs and outputs. Here we use a computational modeling approach that specifies computations to convert a time-varying input stimulus to a neural response time course, and use this to predict neural activity measured in the human visual cortex. We show that this computational model predicts a wide variety of complex neural response shapes that we induced experimentally by manipulating the duration, repetition and contrast of visual stimuli. By comparing data and model predictions, we uncover systematic properties of temporal dynamics of neural signals, allowing us to better understand how the brain processes dynamic sensory information.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Identification of an epileptogenic lesion on structural neuroimaging in individuals with focal epilepsy is important for management and treatment planning. The objective of this study was to determine the frequency of MRI-identified potentially epileptogenic structural abnormalities in a large multicenter study of adolescent and adult patients with newly diagnosed focal epilepsy. METHODS:Patients with a new diagnosis of focal epilepsy enrolled in the Human Epilepsy Project observational cohort study underwent 3-Tesla (3T) brain MRI using a standardized protocol. Imaging findings were classified as normal, abnormal, or incidental. Abnormal findings were classified as focal or diffuse, and as likely epilepsy-related or of unknown relationship to epilepsy. Fisher exact tests were performed to determine whether abnormal imaging or abnormality type was associated with clinical characteristics. RESULTS:418 participants were enrolled. 218 participants (59.3%) had no abnormalities detected, 149 (35.6%) had abnormal imaging, and 21 (5.0%) had incidental findings. 78 participants (18.7%) had abnormalities that were considered epilepsy-related and 71 (17.0%) had abnormalities of unknown relationship to epilepsy. Older participants were more likely to have imaging abnormalities, while participants with focal and epilepsy-related imaging abnormalities were younger than those without these abnormalities. 131 participants (31.3%) had a family history of epilepsy. Epilepsy-related abnormalities were not associated with participant sex, family history of epilepsy, or seizure type. DISCUSSION/CONCLUSIONS:We found that one in five patients with newly diagnosed focal epilepsy has an MRI finding that is likely causative and may alter treatment options. An additional one in five patients has abnormalities of unknown significance. This information is important for patient counseling, prognostication, and management.