A Simplified Crossing Fiber Model in Diffusion Weighted Imaging

Diffusion MRI (dMRI) is a vital source of imaging data for identifying anatomical connections in the living human brain that form the substrate for information transfer between brain regions. dMRI can thus play a central role toward our understanding of brain function. The quantitative modeling and analysis of dMRI data deduces the features of neural fibers at the voxel level, such as direction and density. The modeling methods that have been developed range from deterministic to probabilistic approaches. Currently, the Ball-and-Stick model serves as a widely implemented probabilistic approach in the tractography toolbox of the popular FSL software package and FreeSurfer/TRACULA software package. However, estimation of the features of neural fibers is complex under the scenario of two crossing neural fibers, which occurs in a sizeable proportion of voxels within the brain. A Bayesian non-linear regression is adopted, comprised of a mixture of multiple non-linear components. Such models can pose a difficult statistical estimation problem computationally. To make the approach of Ball-and-Stick model more feasible and accurate, we propose a simplified version of Ball-and-Stick model that reduces parameter space dimensionality. This simplified model is vastly more efficient in the terms of computation time required in estimating parameters pertaining to two crossing neural fibers through Bayesian simulation approaches. Moreover, the performance of this new model is comparable or better in terms of bias and estimation variance as compared to existing models

A Simplified Crossing Fiber Model in Diffusion Weighted Imaging

Diffusion MRI (dMRI) is a vital source of imaging data for identifying anatomical connections in the living human brain that form the substrate for information transfer between brain regions. dMRI can thus play a central role toward our understanding of brain function. The quantitative modeling and analysis of dMRI data deduces the features of neural fibers at the voxel level, such as direction and density. The modeling methods that have been developed range from deterministic to probabilistic approaches. Currently, the Ball-and-Stick model serves as a widely implemented probabilistic approach in the tractography toolbox of the popular FSL software package and FreeSurfer/TRACULA software package. However, estimation of the features of neural fibers is complex under the scenario of two crossing neural fibers, which occurs in a sizeable proportion of voxels within the brain. A Bayesian non-linear regression is adopted, comprised of a mixture of multiple non-linear components. Such models can pose a difficult statistical estimation problem computationally. To make the approach of Ball-and-Stick model more feasible and accurate, we propose a simplified version of Ball-and-Stick model that reduces parameter space dimensionality. This simplified model is vastly more efficient in the terms of computation time required in estimating parameters pertaining to two crossing neural fibers through Bayesian simulation approaches. Moreover, the performance of this new model is comparable or better in terms of bias and estimation variance as compared to existing models

Aceros al molibdeno sinterizados con gradiente funcional

Las propiedades que se solicitan a las piezas y productos exigen, la mayoría de las veces, una combinación de materiales que respondan a requerimientos específicos en función de su posición. La fabricación de materiales compuestos y materiales con gradiente funcional proporciona grandes posibilidades de respuesta a las necesidades demandas, tanto de satisfacción de requerimientos como de reducción de materias primas necesarias. En este sentido, satisfacer las propiedades demandadas, de manera localizada geométricamente, puede suponer un ahorro de materias primas y de los residuos relacionados en su fabricación. En el presente estudio de la sinterización a 1120 ºC de un compacto de dos aceros de diferentes composiciones (un acero con un 0,3 % C y un 2 % de cobre y un acero al molibdeno con un 0,7 % carbono y un 2 % de cobre) ofrece unas posibilidades muy atractivas de eficiencia, al reducir en el interior la composición que se requiere en la superficie de las piezas. Se han caracterizado las propiedades mecánicas de este acero sinterizado con gradiente funcional: densidad, variación dimensional, durezas y resistencia mecánica; ilustradas con el análisis de imagen mediante microscopía óptica y electrónica de barrido

Age-specific periictal electroclinical features of generalized tonic-clonic seizures and potential risk of sudden unexpected death in epilepsy (SUDEP)

Generalized tonic–clonic seizure (GTCS) is the commonest seizure type associated with sudden unexpected death in epilepsy (SUDEP). This study examined the semiological and electroencephalographic differences (EEG) in the GTCSs of adults as compared with those of children. The rationale lies on epidemiological observations that have noted a tenfold higher incidence of SUDEP in adults.Weanalyzed the video-EEG data of 105 GTCS events in 61 consecutive patients (12 children, 23 seizure events and 49 adults, 82 seizure events) recruited from the Epilepsy Monitoring Unit. Semiological, EEG, and 3-channel EKG features were studied. Periictal seizure phase durations were analyzed including tonic, clonic, total seizure, postictal EEG suppression (PGES), and recovery phases. Heart rate variability (HRV)measures includingRMSSD (root mean square successive difference of RR intervals), SDNN (standard deviation of NN intervals), and SDSD (standard deviation of differences) were analyzed (including low frequency/high frequency power ratios) during preictal baseline and ictal and postictal phases. Generalized estimating equations (GEEs)were used to find associations between electroclinical features. Separate subgroup analyses were carried out on adult and pediatric age groups as well as medication groups (no antiepileptic medication cessation versus unchanged or reduced medication) during admission.Major differences were seen in adult and pediatric seizures with total seizure duration, tonic phase, PGES, and recovery phases being significantly shorter in children (p b 0.01). Generalized estimating equation analysis, using tonic phase duration as the dependent variable, found age to correlate significantly (p b 0.001), and this remained significant during subgroup analysis (adults and children) such that each 0.12-second increase in tonic phase duration correlated with a 1-second increase in PGES duration. Postictal EEG suppression durations were on average 28 s shorter in children. With cessation of medication, total seizure duration was significantly increased by a mean value of 8 s in children and 11 s in adults (p b 0.05). Tonic phase duration also significantly increased with medication cessation, and although PGES durations increased, this was not significant. Root mean square successive difference was negatively correlated with PGES duration (longer PGES durations were associated with decreased vagally mediated heart rate variability; p b 0.05) but not with tonic phase duration. This study clearly points out identifiable electroclinical differences between adult and pediatric GTCSs that may be relevant in explaining lower SUDEP risk in children. The findings suggest that some prolonged seizure phases and prolonged PGES duration may be electroclinical markers of SUDEP risk and merit further study

Modeling the heterogeneity in risk of progression to Alzheimer's disease across cognitive profiles in mild cognitive impairment

Heterogeneity in risk of conversion to Alzheimer's disease (AD) among individuals with mild cognitive impairment (MCI) is well known. Novel statistical methods that are based on partially ordered set (poset) models can be used to create models that provide detailed and accurate information about performance with specific cognitive functions. This approach allows for the study of direct links between specific cognitive functions and risk of conversion to AD from MCI. It also allows for further delineation of multi-domain amnestic MCI, in relation to specific non-amnestic cognitive deficits, and the modeling of a range of episodic memory functioning levels. From the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, conversion at 24 months of 268 MCI subjects was analyzed. It was found that 101 of those subjects (37.7%) converted to AD within that time frame. Poset models were then used to classify cognitive performance for MCI subjects. Respective observed conversion rates to AD were calculated for various cognitive subgroups, and by APOE e4 allele status. These rates were then compared across subgroups. The observed conversion rate for MCI subjects with a relatively lower functioning with a high level of episodic memory at baseline was 61.2%. In MCI subjects who additionally also had relatively lower perceptual motor speed functioning and at least one APOE e4 allele, the conversion rate was 84.2%. In contrast, the observed conversion rate was 9.8% for MCI subjects with a relatively higher episodic memory functioning level and no APOE e4 allele. Relatively lower functioning with cognitive flexibility and perceptual motor speed by itself also appears to be associated with higher conversion rates. Among MCI subjects, specific baseline cognitive profiles that were derived through poset modeling methods, are clearly associated with differential rates of conversion to AD. More precise delineation of MCI by such cognitive functioning profiles, including notions such as multidomain amnestic MCI, can help in gaining further insight into how heterogeneity arises in outcomes. Poset-based modeling methods may be useful for providing more precise classification of cognitive subgroups among MCI for imaging and genetics studies, and for developing more efficient and focused cognitive test batteries

Self‐management for adults with epilepsy: Aggregate Managing Epilepsy Well Network findings on depressive symptoms

ObjectiveTo assess depressive symptom outcomes in a pooled sample of epilepsy self‐management randomized controlled trials (RCTs) from the Managing Epilepsy Well (MEW) Network integrated research database (MEW DB).MethodsFive prospective RCTs involving 453 adults with epilepsy compared self‐management intervention (n = 232) versus treatment as usual or wait‐list control outcomes (n = 221). Depression was assessed with the nine‐item Patient Health Questionnaire. Other variables included age, gender, race, ethnicity, education, income, marital status, seizure frequency, and quality of life. Follow‐up assessments were collapsed into a visit 2 and a visit 3; these were conducted postbaseline.ResultsMean age was 43.5 years (SD = 12.6), nearly two‐thirds were women, and nearly one‐third were African American. Baseline sample characteristics were mostly similar in the self‐management intervention group versus controls. At follow‐up, the self‐management group had a significantly greater reduction in depression compared to controls at visit 2 (P < .0001) and visit 3 (P = .0002). Quality of life also significantly improved in the self‐management group at visit 2 (P = .001) and visit 3 (P = .005).SignificanceAggregate MEW DB analysis of five RCTs found depressive symptom severity and quality of life significantly improved in individuals randomized to self‐management intervention versus controls. Evidence‐based epilepsy self‐management programs should be made more broadly available in neurology practices.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151320/1/epi16322_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151320/2/epi16322.pd

Increased Glucose Availability Sensitizes Pancreatic Cancer to Chemotherapy

Pancreatic Ductal Adenocarcinoma (PDAC) is highly resistant to chemotherapy. Effective alternative therapies have yet to emerge, as chemotherapy remains the best available systemic treatment. However, the discovery of safe and available adjuncts to enhance chemotherapeutic efficacy can still improve survival outcomes. We show that a hyperglycemic state substantially enhances the efficacy of conventional single- and multi-agent chemotherapy regimens against PDAC. Molecular analyses of tumors exposed to high glucose levels reveal that the expression of GCLC (glutamate-cysteine ligase catalytic subunit), a key component of glutathione biosynthesis, is diminished, which in turn augments oxidative anti-tumor damage by chemotherapy. Inhibition of GCLC phenocopies the suppressive effect of forced hyperglycemia in mouse models of PDAC, while rescuing this pathway mitigates anti-tumor effects observed with chemotherapy and high glucose

Incidence, Recurrence, and Risk Factors for Peri-ictal Central Apnea and Sudden Unexpected Death in Epilepsy

Introduction: Peri-ictal breathing dysfunction was proposed as a potential mechanism for SUDEP. We examined the incidence and risk factors for both ictal (ICA) and post-convulsive central apnea (PCCA) and their relationship with potential seizure severity biomarkers (i. e., post-ictal generalized EEG suppression (PGES) and recurrence. Methods: Prospective, multi-center seizure monitoring study of autonomic, and breathing biomarkers of SUDEP in adults with intractable epilepsy and monitored seizures. Video EEG, thoraco-abdominal excursions, capillary oxygen saturation, and electrocardiography were analyzed. A subgroup analysis determined the incidences of recurrent ICA and PCCA in patients with ≥2 recorded seizures. We excluded status epilepticus and obscured/unavailable video. Central apnea (absence of thoracic-abdominal breathing movements) was defined as ≥1 missed breath, and ≥5 s. ICA referred to apnea preceding or occurring along with non-convulsive seizures (NCS) or apnea before generalized convulsive seizures (GCS). Results: We analyzed 558 seizures in 218 patients (130 female); 321 seizures were NCS and 237 were GCS. ICA occurred in 180/487 (36.9%) seizures in 83/192 (43.2%) patients, all with focal epilepsy. Sleep state was related to presence of ICA [RR 1.33, CI 95% (1.08–1.64), p = 0.008] whereas extratemporal epilepsy was related to lower incidence of ICA [RR 0.58, CI 95% (0.37–0.90), p = 0.015]. ICA recurred in 45/60 (75%) patients. PCCA occurred in 41/228 (18%) of GCS in 30/134 (22.4%) patients, regardless of epilepsy type. Female sex [RR 11.30, CI 95% (4.50–28.34), p < 0.001] and ICA duration [RR 1.14 CI 95% (1.05–1.25), p = 0.001] were related to PCCA presence, whereas absence of PGES was related to absence of PCCA [0.27, CI 95%(0.16–0.47), p < 0.001]. PCCA duration was longer in males [HR 1.84, CI 95% (1.06–3.19), p = 0.003]. In 9/17 (52.9%) patients, PCCA was recurrent. Conclusion: ICA incidence is almost twice the incidence of PCCA and is only seen in focal epilepsies, as opposed to PCCA, suggesting different pathophysiologies. ICA is likely to be a recurrent semiological phenomenon of cortical seizure discharge, whereas PCCA may be a reflection of brainstem dysfunction after GCS. Prolonged ICA or PCCA may, respectively, contribute to SUDEP, as evidenced by two cases we report. Further prospective cohort studies are needed to validate these hypotheses

Incidence, Recurrence, and Risk Factors for Peri-ictal Central Apnea and Sudden Unexpected Death in Epilepsy

Introduction: Peri-ictal breathing dysfunction was proposed as a potential mechanism for SUDEP. We examined the incidence and risk factors for both ictal (ICA) and post-convulsive central apnea (PCCA) and their relationship with potential seizure severity biomarkers (i. e., post-ictal generalized EEG suppression (PGES) and recurrence.Methods: Prospective, multi-center seizure monitoring study of autonomic, and breathing biomarkers of SUDEP in adults with intractable epilepsy and monitored seizures. Video EEG, thoraco-abdominal excursions, capillary oxygen saturation, and electrocardiography were analyzed. A subgroup analysis determined the incidences of recurrent ICA and PCCA in patients with ≥2 recorded seizures. We excluded status epilepticus and obscured/unavailable video. Central apnea (absence of thoracic-abdominal breathing movements) was defined as ≥1 missed breath, and ≥5 s. ICA referred to apnea preceding or occurring along with non-convulsive seizures (NCS) or apnea before generalized convulsive seizures (GCS).Results: We analyzed 558 seizures in 218 patients (130 female); 321 seizures were NCS and 237 were GCS. ICA occurred in 180/487 (36.9%) seizures in 83/192 (43.2%) patients, all with focal epilepsy. Sleep state was related to presence of ICA [RR 1.33, CI 95% (1.08–1.64), p = 0.008] whereas extratemporal epilepsy was related to lower incidence of ICA [RR 0.58, CI 95% (0.37–0.90), p = 0.015]. ICA recurred in 45/60 (75%) patients. PCCA occurred in 41/228 (18%) of GCS in 30/134 (22.4%) patients, regardless of epilepsy type. Female sex [RR 11.30, CI 95% (4.50–28.34), p &lt; 0.001] and ICA duration [RR 1.14 CI 95% (1.05–1.25), p = 0.001] were related to PCCA presence, whereas absence of PGES was related to absence of PCCA [0.27, CI 95% (0.16–0.47), p &lt; 0.001]. PCCA duration was longer in males [HR 1.84, CI 95% (1.06–3.19), p = 0.003]. In 9/17 (52.9%) patients, PCCA was recurrent.Conclusion: ICA incidence is almost twice the incidence of PCCA and is only seen in focal epilepsies, as opposed to PCCA, suggesting different pathophysiologies. ICA is likely to be a recurrent semiological phenomenon of cortical seizure discharge, whereas PCCA may be a reflection of brainstem dysfunction after GCS. Prolonged ICA or PCCA may, respectively, contribute to SUDEP, as evidenced by two cases we report. Further prospective cohort studies are needed to validate these hypotheses

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder