Detection of rare mutations, copy number alterations, and methylation in the same template DNA molecules.

The analysis of cell-free DNA (cfDNA) from plasma offers great promise for the earlier detection of cancer. At present, changes in DNA sequence, methylation, or copy number are the most sensitive ways to detect the presence of cancer. To further increase the sensitivity of such assays with limited amounts of sample, it would be useful to be able to evaluate the same template molecules for all these changes. Here, we report an approach, called MethylSaferSeqS, that achieves this goal, and can be applied to any standard library preparation method suitable for massively parallel sequencing. The innovative step was to copy both strands of each DNA-barcoded molecule with a primer that allows the subsequent separation of the original strands (retaining their 5-methylcytosine residues) from the copied strands (in which the 5-methylcytosine residues are replaced with unmodified cytosine residues). The epigenetic and genetic alterations present in the DNA molecules can then be obtained from the original and copied strands, respectively. We applied this approach to plasma from 265 individuals, including 198 with cancers of the pancreas, ovary, lung, and colon, and found the expected patterns of mutations, copy number alterations, and methylation. Furthermore, we could determine which original template DNA molecules were methylated and/or mutated. MethylSaferSeqS should be useful for addressing a variety of questions relating genetics and epigenetics.

Associations Between Brain Metabolites Measured With MR Spectroscopy and Head Impacts in High School American Football Athletes.

BACKGROUND: While changes in brain metabolites after injury have been reported, relationships between metabolite changes and head impacts are less characterized. PURPOSE: To investigate alterations in neurochemistry in high school athletes as a function of head impacts, concussion, and the use of a jugular vein compression (JVC) collar. STUDY TYPE: Prospective controlled trial. SUBJECTS: A total of 284 male American football players, divided into JVC collar and noncollar groups; 215 included in final analysis (age = 15.9 ± 1.0 years; 114 in collar group). FIELD STRENGTH/SEQUENCE: 3 Tesla/T1-weighted gradient echo, 1H point resolved spectroscopy, acquired between August and November 2018. ASSESSMENT: Head impacts were quantified using accelerometers. Concussion was diagnosed by medical professionals for each team. Pre- to postseason differences in total N-acetylaspartate (tNAA), total choline (tCho), myo-inositol (myoI), and glutamate + glutamine (Glx), in primary motor cortex (M1) and anterior cingulate cortex (ACC), relative to total creatine (tCr), were determined. STATISTICAL TESTS: Group-wise comparisons were performed using Wilcoxon signed-rank, Friedman's, and Mann-Whitney U tests. Relationships between ∆metabolite/tCr and mean g-force were analyzed using linear regressions accounting for concussion and JVC collar. Significance was set at P ≤ 0.05. RESULTS: In participants without concussion, a significant decrease in tCho/tCr (0.233 ± 1.40 × 10-3 to 0.227 ± 1.47 × 10-7) and increase in Glx/tCr (1.60 ± 8.75 × 10-3 to 1.63 ± 1.08 × 10-2) in ACC were observed pre- to postseason. The relationship between ∆tCho/tCr in M1 and ACC and mean g-force from >80 g to >140 g differed significantly between participants with and without concussion (M1 ß ranged from 3.9 × 10-3 to 2.1 × 10-3; ACC ß ranged from 2.7 × 10-3 to 2.1 × 10-3). Posthoc analyses revealed increased tCho/tCr in M1 was positively associated with mean g-force >100 g (ß = 3.6 × 10-3) and >110 g (ß = 2.9 × 10-3) in participants with concussion. Significant associations between ∆ myoI / tCr $$ \Delta \mathrm{myoI}/\mathrm{tCr} $$ in ACC and mean g-force >110 g (ß = -1.1 × 10-3) and >120 g (ß = -1.1 × 10-3) were observed in the collar group only. DATA CONCLUSION: Diagnosed concussion and the use of a JVC collar result in distinct neurochemical trends after repeated head impacts. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Deep Learning Models for Abdominal CT Organ Segmentation in Children: Development and Validation in Internal and Heterogeneous Public Datasets.

BACKGROUND. Deep learning abdominal organ segmentation algorithms have shown excellent results in adults; validation in children is sparse. OBJECTIVE. The purpose of this article is to develop and validate deep learning models for liver, spleen, and pancreas segmentation on pediatric CT examinations. METHODS. This retrospective study developed and validated deep learning models for liver, spleen, and pancreas segmentation using 1731 CT examinations (1504 training, 221 testing), derived from three internal institutional pediatric (age ≤ 18 years) datasets (n = 483) and three public datasets comprising pediatric and adult examinations with various pathologies (n = 1248). Three deep learning model architectures (SegResNet, DynUNet, and SwinUNETR) from the Medical Open Network for Artificial Intelligence (MONAI) framework underwent training using native training (NT), relying solely on institutional datasets, and transfer learning (TL), incorporating pretraining on public datasets. For comparison, TotalSegmentator, a publicly available segmentation model, was applied to test data without further training. Segmentation performance was evaluated using mean Dice similarity coefficient (DSC), with manual segmentations as reference. RESULTS. For internal pediatric data, the DSC for TotalSegmentator, NT models, and TL models for normal liver was 0.953, 0.964-0.965, and 0.965-0.966, respectively; for normal spleen, 0.914, 0.942-0.945, and 0.937-0.945; for normal pancreas, 0.733, 0.774-0.785, and 0.775-0.786; and for pancreas with pancreatitis, 0.703, 0.590-0.640, and 0.667-0.711. For public pediatric data, the DSC for TotalSegmentator, NT models, and TL models for liver was 0.952, 0.871-0.908, and 0.941-0.946, respectively; for spleen, 0.905, 0.771-0.827, and 0.897-0.926; and for pancreas, 0.700, 0.577-0.648, and 0.693-0.736. For public primarily adult data, the DSC for TotalSegmentator, NT models, and TL models for liver was 0.991, 0.633-0.750, and 0.926-0.952, respectively; for spleen, 0.983, 0.569-0.604, and 0.923-0.947; and for pancreas, 0.909, 0.148-0.241, and 0.699-0.775. The DynUNet TL model was selected as the best-performing NT or TL model considering DSC values across organs and test datasets and was made available as an open-source MONAI bundle (https://github.com/cchmc-dll/pediatric_abdominal_segmentation_bundle.git). CONCLUSION. TL models trained on heterogeneous public datasets and fine-tuned using institutional pediatric data outperformed internal NT models and Total-Segmentator across internal and external pediatric test data. Segmentation performance was better in liver and spleen than in pancreas. CLINICAL IMPACT. The selected model may be used for various volumetry applications in pediatric imaging.

A greater modulation of the visual and fronto-parietal networks for children in a post-media versus pre-media exposure group.

AIM: Media use in children has exploded in the past several decades, most recently fuelled by portable electronic devices. This study aims to explore differences in functional brain connectivity in children during a story-listening functional MRI (fMRI) task using data collected before (1998) and after (2013) the widespread adoption of media. METHODS: Cross-sectional data were collected from English-speaking 5- to 7-year-old children at Cincinnati Children's Hospital Medical Center, USA, of a functional MRI narrative comprehension task completed in 1998 (n = 22) or 2013 (n = 25). Imaging data were processed using a graph theory approach, focusing on executive functions, language and visual processing networks supporting reading. RESULTS: Group differences suggest more efficient processing in the fronto-parietal network in the pre-media group while listening to stories. A modulation of the visual and fronto-parietal networks for the post-media exposure group was found. CONCLUSION: Further studies are needed to assess effects over time in the more exposed group to discern a causal effect of portable devices on cognitive networks.

Examining reaction time variability on the stop-signal task in the ABCD study.

OBJECTIVE: Reaction time variability (RTV) has been estimated using Gaussian, ex-Gaussian, and diffusion model (DM) indices. Rarely have studies examined interrelationships among these performance indices in childhood, and the use of reaction time (RT) computational models has been slow to take hold in the developmental psychopathology literature. Here, we extend prior work in adults by examining the interrelationships among different model parameters in the ABCD sample and demonstrate how computational models of RT can clarify mechanisms of time-on-task effects and sex differences in RTs. METHOD: This study utilized trial-level data from the stop signal task from 8916 children (9-10 years old) to examine Gaussian, ex-Gaussian, and DM indicators of RTV. In addition to describing RTV patterns, we examined interrelations among these indicators, temporal patterns, and sex differences. RESULTS: There was no one-to-one correspondence between DM and ex-Gaussian parameters. Nonetheless, drift rate was most strongly associated with standard deviation of RT and tau, while nondecisional processes were most strongly associated with RT, mu, and sigma. Performance worsened across time with changes driven primarily by decreasing drift rate. Boys were faster and less variable than girls, likely attributable to girls' wide boundary separation. CONCLUSIONS: Intercorrelations among model parameters are similar in children as has been observed in adults. Computational approaches play a crucial role in understanding performance changes over time and can also clarify mechanisms of group differences. For example, standard RT models may incorrectly suggest slowed processing speed in girls that is actually attributable to other factors.

Liver T1 Relaxation Quantification Using a 3-Dimensional Interleaved Look-Locker Acquisition With T2 Preparation Pulse Sequence (3D-QALAS): Comparison With Conventional 2-Dimensional MOLLI.

BACKGROUND: Changes in liver magnetic resonance imaging T1 relaxation times are associated with histologic inflammation and fibrosis. OBJECTIVE: To compare liver T1 measurements obtained using a novel single-breath-hold 3-dimensional (3D) whole-liver T1 estimation method (3D-QALAS) to standard-of-care 2-dimensional (2D) modified Look-Locker (2D-MOLLI) measurements. METHODS: With institutional review board approval, research magnetic resonance imaging examinations were performed in 19 participants at 1.5 T. T1 relaxometry of the liver was performed using a novel 3D whole-liver T1 estimation method (3D-QALAS) as well as a 2D modified Look-Locker (2D-MOLLI) method. The 3D method covered the entire liver in a single breath hold, whereas 2D imaging was performed at 4 anatomic levels in 4 consecutive breath holds. T1 measurements from parametric maps were obtained by a single operator, and region-of-interest area-weighted mean T1 values were calculated. Pearson correlation ( r ) was used to assess correlation between T1 estimation methods, and the paired t test and Bland-Altman analysis were used to compare agreement in T1 measurements. RESULTS: In 18 participants (1 participant was excluded from analysis because of respiratory motion artifacts on 3D-QALAS images), 2D-MOLLI and 3D-QALAS mean T1 measurements were strongly correlated ( r = 0.95, [95% CI: 0.87-0.98]; P < 0.0001). 2D-MOLLI T1 values were significantly longer than 3D-QALAS values (647.2 ± 87.3 milliseconds vs. 554.7 ± 75.8 milliseconds; P < 0.0001) with mean bias = 92.5 milliseconds (95% limits of agreement, 36.8, 148.2 milliseconds). CONCLUSION: Whole-liver T1 measurements obtained using a novel single-breath-hold 3D T1 estimation method correlate with a standard-of-care multiple consecutive-breath-hold 2D single-slice method but demonstrate systematic bias that should be considered or corrected when used in a clinical or research setting.

Maternal education as an environmental factor related to reading in children with reading difficulties: A functional magnetic resonance imaging study.

The expanded simple view of reading (SVR) model suggests that word decoding, language comprehension and executive functions are necessary for reading comprehension. Children with reading difficulties (RDs) often have deficits in critical components of reading established in the expanded SVR model and alterations in brain function of reading-related regions. Maternal education could provide children with advantageous educational opportunities or resources that support reading acquisition. The primary goal of this study was to examine the contributions of maternal education to the behavioural and neurobiological correlates of the expanded SVR model. Seventy-two 8- to 12-year-old children with RDs and typical readers (TRs) completed reading, behavioural and an functional magnetic resonance imaging stories-listening task to determine the functional connectivity of the receptive language network to the whole brain in association with maternal education. Higher maternal education was associated with better vocabulary in children with RDs and positive functional connectivity between the receptive language network and regions related to visual processing in children with RDs versus TRs. These data suggest that maternal education supports the ability to comprehend oral language and engagement of neural networks that support imagination/visualization in children with RDs.

Velocity-Encoded Phase-Contrast MRI for Measuring Mesenteric Blood Flow in Patients With Newly Diagnosed Small-Bowel Crohn Disease.

BACKGROUND. Intestinal inflammation is associated with radiologic and histologic hyperemia. A paucity of studies have used MRI to measure mesenteric blood flow in patients with Crohn disease. OBJECTIVE. The purpose of this study was to evaluate the application of velocity-encoded phase-contrast MRI for measuring mesenteric blood flow in patients with newly diagnosed small-bowel Crohn disease. METHODS. This prospective study included 20 patients with ileal Crohn disease newly diagnosed between December 2018 and October 2021 (eight female participants, 12 male participants; median age, 14.0 years), and 15 healthy control participants (eight female participants, seven male participants; median age, 17.0 years). Patients with Crohn disease underwent investigational MRI and laboratory assessments at diagnosis and at 6 weeks and 6 months after initiating anti-tumor necrosis factor-α medical therapy; control participants underwent a single investigational MRI examination. All MRI examinations included a velocity-encoded phase-contrast acquisition, which was used to measure blood flow in the abdominal aorta, superior mesenteric artery (SMA), and superior mesenteric vein (SMV). Mann-Whitney U test was used to compare blood flow measurements (ratios of SMA and SMV blood flow to aorta blood flow [hereafter, SMA-to-aorta and SMV-to-aorta blood flow, respectively]) between groups; Friedman test was used to evaluate temporal changes in blood flow. Spearman correlation was used to assess relationships between blood flow measurements and laboratory markers of intestinal inflammation. Diagnostic performance was assessed by ROC analysis. RESULTS. At baseline, SMA-to-aorta blood flow in patients versus control participants was 0.44 versus 0.30 (p = .003), and SMV-to-aorta blood flow was 0.36 versus 0.21 (p = .002). At 6 weeks and 6 months, SMA-to-aorta blood flow in patients decreased to 0.30 and 0.27 (p < .001), and SMV-to-aorta blood flow decreased to 0.27 and 0.21 (p = .02), respectively. SMA-to-aorta and SMV-to-aorta blood flow were positively correlated with C-reactive protein (rho, 0.34 [p = .01] and 0.35 [p = .008], respectively) and fecal calprotectin (rho, 0.34 [p = .01] vs 0.47 [p < .001]). AUCs for differentiating patients from controls were 0.79 for SMA-to-aorta (sensitivity, 60%; specificity, 100%) and 0.82 for SMV-to-aorta (sensitivity, 75%; specificity, 87%) blood flow. CONCLUSION. Mesenteric blood flow is quantifiable using velocity-encoded phase-contrast MRI. The measurements differ between patients with ileal Crohn disease and healthy control participants and change in response to medical therapy. CLINICAL IMPACT. MRI-based mesenteric blood flow measurements provide a potential novel marker of intestinal inflammation.

Multiregion whole-exome sequencing of intraductal papillary mucinous neoplasms reveals frequent somatic KLF4 mutations predominantly in low-grade regions.

OBJECTIVE: Intraductal papillary mucinous neoplasms (IPMNs) are non-invasive precursor lesions that can progress to invasive pancreatic cancer and are classified as low-grade or high-grade based on the morphology of the neoplastic epithelium. We aimed to compare genetic alterations in low-grade and high-grade regions of the same IPMN in order to identify molecular alterations underlying neoplastic progression. DESIGN: We performed multiregion whole exome sequencing on tissue samples from 17 IPMNs with both low-grade and high-grade dysplasia (76 IPMN regions, including 49 from low-grade dysplasia and 27 from high-grade dysplasia). We reconstructed the phylogeny for each case, and we assessed mutations in a novel driver gene in an independent cohort of 63 IPMN cyst fluid samples. RESULTS: Our multiregion whole exome sequencing identified KLF4, a previously unreported genetic driver of IPMN tumorigenesis, with hotspot mutations in one of two codons identified in >50% of the analyzed IPMNs. Mutations in KLF4 were significantly more prevalent in low-grade regions in our sequenced cases. Phylogenetic analyses of whole exome sequencing data demonstrated diverse patterns of IPMN initiation and progression. Hotspot mutations in KLF4 were also identified in an independent cohort of IPMN cyst fluid samples, again with a significantly higher prevalence in low-grade IPMNs. CONCLUSION: Hotspot mutations in KLF4 occur at high prevalence in IPMNs. Unique among pancreatic driver genes, KLF4 mutations are enriched in low-grade IPMNs. These data highlight distinct molecular features of low-grade and high-grade dysplasia and suggest diverse pathways to high-grade dysplasia via the IPMN pathway.

The effects of internal jugular vein compression for modulating and preserving white matter following a season of American tackle football: A prospective longitudinal evaluation of differential head impact exposure.

The purpose of this clinical trial was to examine whether internal jugular vein compression (JVC)-using an externally worn neck collar-modulated the relationships between differential head impact exposure levels and pre- to postseason changes in diffusion tensor imaging (DTI)-derived diffusivity and anisotropy metrics of white matter following a season of American tackle football. Male high-school athletes (n = 284) were prospectively assigned to a non-collar group or a collar group. Magnetic resonance imaging data were collected from participants pre- and postseason and head impact exposure was monitored by accelerometers during every practice and game throughout the competitive season. Athletes' accumulated head impact exposure was systematically thresholded based on the frequency of impacts of progressively higher magnitudes (10 g intervals between 20 to 150 g) and modeled with pre- to postseason changes in DTI measures of white matter as a function of JVC neck collar wear. The findings revealed that the JVC neck collar modulated the relationships between greater high-magnitude head impact exposure (110 to 140 g) and longitudinal changes to white matter, with each group showing associations that varied in directionality. Results also revealed that the JVC neck collar group partially preserved longitudinal changes in DTI metrics. Collectively, these data indicate that a JVC neck collar can provide a mechanistic response to the diffusion and anisotropic properties of brain white matter following the highly diverse exposure to repetitive head impacts in American tackle football. Clinicaltrials.gov: NCT# 04068883.

Maternal depression is associated with decreased functional connectivity within semantics and phonology networks in preschool children.

INTRODUCTION: Maternal depression is characterized by a lack of emotional responsiveness and engagement with their child, which may lead to the child's decreased cognitive, and language outcomes all related to the child's future reading outcomes. The relations between maternal depression and functional connectivity in neural circuits supporting language in the child was explored. METHODS: Eleven 4-year-old girls completed language abilities assessment and resting-state functional magnetic resonance imaging scan. Their mothers completed the Beck's Depression Inventory (BDI) to examine maternal depression when the child was 12 months old and at the age of 4. Functional connections within the child's resting-state phonology, semantics, language networks were correlated with maternal BDI scores at the age of 4 years. RESULTS: Higher maternal depression was associated with the child's decreased within the semantic and phonological networks connectivity during rest. Higher maternal depression at 4 years moderated the relationship between early depression scores and functional connectivity within the phonological network. CONCLUSIONS: Maternal depression in the first year of life is related to functional connections of phonological processing and enhanced by current maternal depression levels. We conclude that after a mother gives birth, resources should be provided to minimize depressive symptoms and interventions should be applied to support their child's language development for future reading acquisition.

DeepLiverNet: a deep transfer learning model for classifying liver stiffness using clinical and T2-weighted magnetic resonance imaging data in children and young adults.

BACKGROUND: Although MR elastography allows for quantitative evaluation of liver stiffness to assess chronic liver diseases, it has associated drawbacks related to additional scanning time, patient discomfort, and added costs. OBJECTIVE: To develop a machine learning model that can categorically classify the severity of liver stiffness using both anatomical T2-weighted MRI and clinical data for children and young adults with known or suspected pediatric chronic liver diseases. MATERIALS AND METHODS: We included 273 subjects with known or suspected chronic liver disease. We extracted data including axial T2-weighted fast spin-echo fat-suppressed images, clinical data (e.g., demographic/anthropomorphic data, particular medical diagnoses, laboratory values) and MR elastography liver stiffness measurements. We propose DeepLiverNet (a deep transfer learning model) to classify patients into one of two groups: no/mild liver stiffening (<3 kPa) or moderate/severe liver stiffening (≥3 kPa). We conducted internal cross-validation using 178 subjects, and external validation using an independent cohort of 95 subjects. We assessed diagnostic performance using accuracy, sensitivity, specificity and area under the receiver operating characteristic curve (AuROC). RESULTS: In the internal cross-validation experiment, the combination of clinical and imaging data produced the best performance (AuROC=0.86) compared to clinical (AuROC=0.83) or imaging (AuROC=0.80) data alone. Using both clinical and imaging data, the DeepLiverNet correctly classified patients with accuracy of 88.0%, sensitivity of 74.3% and specificity of 94.6%. In our external validation experiment, this same deep learning model achieved an accuracy of 80.0%, sensitivity of 61.1%, specificity of 91.5% and AuROC of 0.79. CONCLUSION: A deep learning model that incorporates clinical data and anatomical T2-weighted MR images might provide a means of risk-stratifying liver stiffness and directing the use of MR elastography.

Associations between home literacy environment, brain white matter integrity and cognitive abilities in preschool-age children.

AIM: Caregiver-child reading is advocated by health organisations, citing cognitive and neurobiological benefits. The influence of home literacy environment (HLE) on brain structure prior to kindergarten has not previously been studied. METHODS: Preschool-age children completed assessments of language (EVT-2, CTOPP-2 Rapid Object Naming) and emergent literacy skills (Get Ready to Read!, The Reading House) followed by diffusion tensor imaging (DTI). Parents completed a survey of HLE (StimQ-P2 READ), which has four subscales. DTI measures included axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD) and fractional anisotropy (FA). RESULTS: Forty-seven children completed DTI (54 ± 7 months, range 36-63; 27 girls). StimQ-P2 READ scores correlated with higher EVT-2, GRTR and TRH scores, controlling for age and gender (P < .01), and also with lower AD, RD and MD in tracts supporting language and literacy skills, controlling for age, gender and income (P < .05, family-wise error corrected). Correlations were strongest for the Bookreading Quantity subscale, including with higher scores on all cognitive measures including CTOPP-2, and also with higher FA in left-lateralised literacy-supporting tracts, controlling for age, gender and income. CONCLUSION: More nurturing home reading environment prior to kindergarten may stimulate brain development supporting language and literacy skills, reinforcing the need for further study.

Machine Learning Prediction of Liver Stiffness Using Clinical and T2-Weighted MRI Radiomic Data.

OBJECTIVE. The purpose of this study is to develop a machine learning model to categorically classify MR elastography (MRE)-derived liver stiffness using clinical and nonelastographic MRI radiomic features in pediatric and young adult patients with known or suspected liver disease. MATERIALS AND METHODS. Clinical data (27 demographic, anthropomorphic, medical history, and laboratory features), MRI presence of liver fat and chemical shift-encoded fat fraction, and MRE mean liver stiffness measurements were retrieved from electronic medical records. MRI radiomic data (105 features) were extracted from T2-weighted fast spin-echo images. Patients were categorized by mean liver stiffness (< 3 vs ≥ 3 kPa). Support vector machine (SVM) models were used to perform two-class classification using clinical features, radiomic features, and both clinical and radiomic features. Our proposed model was internally evaluated in 225 patients (mean age, 14.1 years) and externally evaluated in an independent cohort of 84 patients (mean age, 13.7 years). Diagnostic performance was assessed using ROC AUC values. RESULTS. In our internal cross-validation model, the combination of clinical and radiomic features produced the best performance (AUC = 0.84), compared with clinical (AUC = 0.77) or radiomic (AUC = 0.70) features alone. Using both clinical and radiomic features, the SVM model was able to correctly classify patients with accuracy of 81.8%, sensitivity of 72.2%, and specificity of 87.0%. In our external validation experiment, this SVM model achieved an accuracy of 75.0%, sensitivity of 63.6%, specificity of 82.4%, and AUC of 0.80. CONCLUSION. An SVM learning model incorporating clinical and T2-weighted radiomic features has fair-to-good diagnostic performance for categorically classifying liver stiffness.

Electrical stimulation mapping of language with stereo-EEG.

OBJECTIVE: We prospectively validated stereo-electroencephalography (EEG) electrical stimulation mapping (ESM) of language against a reference standard of meta-analytic functional magnetic resonance imaging (fMRI) framework (Neurosynth). METHODS: Language ESM was performed using 50 Hz, biphasic, bipolar, stimulation at 1-8 mA, with a picture naming task. Electrode contacts (ECs) were scored as ESM+ if ESM interfered with speech/language function. For each patient, presurgical MRI was transformed to a standard space and coregistered with computed tomographic (CT) scan to obtain EC locations. After whole-brain parcellation, this fused image data were intersected with three-dimensional language fMRI (Neurosynth), and each EC was classified as lying within/outside the fMRI language parcel. Diagnostic odds ratio (DOR) and other indices were estimated. Current thresholds for language inhibition and after-discharges (ADs) were analyzed using multivariable linear mixed models. RESULTS: In 10 patients (5 females), aged 5.4-21.2 years, speech/language inhibition was noted with ESM on 87/304 (29%) ECs. Stereo-EEG language ESM was a valid classifier of fMRI (Neurosynth) language sites (DOR: 9.02, p < 0.0001), with high specificity (0.87) but poor sensitivity (0.57). Similar diagnostic indices were seen for ECs in frontal or posterior regions, and gray or white matter. Language threshold (3.1 ±â€¯1.5 mA) was lower than AD threshold (4.0 ±â€¯2.0 mA, p = 0.0001). Language and AD thresholds decreased with age and intelligence quotient. Electrical stimulation mapping triggered seizures/auras represented patients' habitual semiology with 1 Hz stimulation. CONCLUSIONS: Stereo-EEG ESM can reliably identify cerebral parcels with/without language function but may under detect all language sites. We suggest a 50-Hz stimulation protocol for language ESM with stereo-EEG.

Altered brain microstructure in association with repetitive subconcussive head impacts and the potential protective effect of jugular vein compression: a longitudinal study of female soccer athletes.

PURPOSE: To (1) quantify white matter (WM) alterations in female high school athletes during a soccer season and characterise the potential for normalisation during the off-season rest period, (2) determine the association between WM alterations and exposure to repetitive subconcussive head impacts, and (3) evaluate the efficacy of a jugular vein compression collar to prevent WM alterations associated with head impact exposure. METHODS: Diffusion tensor imaging (DTI) data were prospectively collected from high school female soccer participants (14-18 years) at up to three time points over 9 months. Head impacts were monitored using accelerometers during all practices and games. Participants were assigned to a collar (n=24) or non-collar group (n=22). The Tract-Based Spatial Statistics approach was used in the analysis of within-group longitudinal change and between-group comparisons. RESULTS: DTI analyses revealed significant pre-season to post-season WM changes in the non-collar group in mean diffusivity (2.83%±2.46%), axial diffusivity (2.58%±2.34%) and radial diffusivity (3.52%±2.60%), but there was no significant change in the collar group despite similar head impact exposure. Significant correlation was found between head impact exposure and pre-season to post-season DTI changes in the non-collar group. WM changes in the non-collar group partially resolved at 3 months off-season follow-up. DISCUSSION: Microstructural changes in WM occurred during a season of female high school soccer among athletes who did not wear the collar device. In comparison, there were no changes in players who wore the collar, suggesting a potential prophylactic effect of the collar device in preventing changes associated with repetitive head impacts. In those without collar use, the microstructural changes showed a reversal towards normal over time in the off-season follow-up period.

White matter alterations over the course of two consecutive high-school football seasons and the effect of a jugular compression collar: A preliminary longitudinal diffusion tensor imaging study.

The cumulative effects of repetitive subclinical head impacts during sports may result in chronic white matter (WM) changes and possibly, neurodegenerative sequelae. In this pilot study, we investigated the longitudinal WM changes over the course of two consecutive high-school football seasons and explored the long-term effects of a jugular vein compression collar on these WM alterations. Diffusion tensor imaging data were prospectively collected both pre- and postseason in the two consecutive seasons. Participants were assigned into either collar or noncollar groups. Tract-based spatial statistics (TBSS) approach and region of interest-based approach were used to quantify changes in WM diffusion properties. Despite comparable exposure to repetitive head impacts, significant reductions in mean, axial, and/or radial diffusivity were identified in Season 1 in multiple WM regions in the noncollar group but not in the collar group. After an 8- to 9-month long off-season, these changes observed in the noncollar group partially and significantly reversed but also remained significantly different from the baseline. In Season 2, trend level WM alterations in the noncollar group were found but located in spatially different regions than Season 1. Last, the WM integrity in the collar group remained unchanged throughout the four time points. In conclusion, we quantitatively assessed the WM structural changes and partial reversal over the course of two consecutive high-school football seasons. In addition, the mitigated WM alterations in athletes in the collar group might indicate potential effect of the collar in ameliorating the changes against repetitive head impacts. Hum Brain Mapp 39:491-508, 2018. © 2017 Wiley Periodicals, Inc.

Deactivated CRISPR Associated Protein 9 for Minor-Allele Enrichment in Cell-Free DNA.

BACKGROUND: Cell-free DNA (cfDNA) diagnostics are emerging as a new paradigm of disease monitoring and therapy management. The clinical utility of these diagnostics is relatively limited by a low signal-to-noise ratio, such as with low allele frequency (AF) mutations in cancer. While enriching for rare alleles to increase their AF before sample analysis is one strategy that can greatly improve detection capability, current methods are limited in their generalizability, ease of use, and applicability to point mutations. METHODS: Leveraging the robust single-base-pair specificity and generalizability of the CRISPR associated protein 9 (Cas9) system, we developed a deactivated Cas9 (dCas9)-based method of minor-allele enrichment capable of efficient single-target and multiplexed enrichment. The dCas9 protein was complexed with single guide RNAs targeted to mutations of interest and incubated with cfDNA samples containing mutant strands at low abundance. Mutation-bound dCas9 complexes were isolated, dissociated, and the captured DNA purified for downstream use. RESULTS: Targeting the 3 most common epidermal growth factor receptor mutations (exon 19 deletion, T790M, L858R) found in non-small cell lung cancer (NSCLC), we achieved >20-fold increases in AF and detected mutations by use of qPCR at an AF of 0.1%. In a cohort of 18 NSCLC patient-derived cfDNA samples, our method enabled detection of 8 out of 13 mutations that were otherwise undetected by qPCR. CONCLUSIONS: The dCas9 method provides an important application of the CRISPR/Cas9 system outside the realm of genome editing and can provide a step forward for the detection capability of cfDNA diagnostics.