Hyperconnectivity is a fundamental response to neurological disruption

In the cognitive and clinical neurosciences, the past decade has been marked by dramatic growth in a literature examining brain "connectivity" using noninvasive methods. We offer a critical review of the blood oxygen level dependent functional MRI (BOLD fMRI) literature examining neural connectivity changes in neurological disorders with focus on brain injury and dementia. The goal is to demonstrate that there are identifiable shifts in local and large-scale network connectivity that can be predicted by the degree of pathology. We anticipate that the most common network response to neurological insult is hyperconnectivity but that this response depends upon demand and resource availability

Prevalence of Cardiovascular Conditions After Traumatic Brain Injury: A Comparison Between the Traumatic Brain Injury Model Systems and the National Health and Nutrition Examination Survey

BACKGROUND: The purpose of this study is to compare the prevalence of self-reported cardiovascular conditions among individuals with moderate to severe traumatic brain injury (TBI) to a propensity-matched control cohort. METHODS AND RESULTS: A cross-sectional study described self-reported cardiovascular conditions (hypertension, congestive heart failure [CHF], myocardial infarction [MI], and stroke) from participants who completed interviews between January 2015 and March 2020 in 2 harmonized large cohort studies, the TBI Model Systems and the National Health and Nutrition Examination Survey. Mixed-effect logistic regression models were used to compare the prevalence of cardiovascular conditions after 1:1 propensity-score matching based on age, sex, race, ethnicity, body mass index, education level, and smoking status. The final sample was 4690 matched pairs. Individuals with TBI were more likely to report hypertension (odds ratio [OR], 1.18 [95% CI, 1.08-1.28]) and stroke (OR, 1.70 [95% CI, 1.56-1.98]) but less likely to report CHF (OR, 0.81 [95% CI, 0.67-0.99]) or MI (OR, 0.66 [95% CI, 0.55-0.79]). There was no difference in rate of CHF or MI for those ≤50 years old; however, rates of CHF and MI were lower in the TBI group for individuals \u3e50 years old. Over 65% of individuals who died before the first follow-up interview at 1 year post-TBI were \u3e50 years old, and those \u3e50 years old were more likely to die of heart disease than those ≤50 years old (17.6% versus 8.6%). CONCLUSIONS: Individuals with moderate to severe TBI had an increased rate of self-reported hypertension and stroke but lower rate of MI and CHF than uninjured adults, which may be due to survival bias

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Not AvailableThe freezing of bull semen significantly hamper the motility of sperm which reduces the conception rate in dairy cattle. The prediction of postthaw motility (PTM) before freezing will be useful to take the decision on discarding or freezing of the germplasm. The artificial neural network (ANN) methodology found to be useful in prediction and classification problems related to animal science, and hence, the present study was undertaken to compare the efficiency of ANN in prediction of PTM on the basis of the number of ejaculates, volume, and concentration of sperms. The combined effect of Y-specific microsatellite alleles on the actual and predicted PTM was also studied. The results revealed that the prediction accuracy of PTM based on the semen quality parameters was comparatively lower because of higher variability in the data set. The ANN gave better prediction accuracy (34.88%) than the multiple regression analysis models (32.04%). The root mean square error was lower for ANN (8.4353) than that in the multiple regression analysis (8.6168). The haplotype or combined effect of microsatellite alleles on actual and predicted PTM was found to be highly significant (P < 0.01). On the basis of results, it was concluded that the ANN methodology can be used for prediction of PTM in crossbred bulls.Not Availabl

Molecular effects of encapsulation of glucose oxidase dimer by graphene

Knowing the nature of the enzyme-graphene interface is critical for a design of graphene-based biosensors. Extensive contacts between graphene and enzyme could be obtained by employing a suitable encapsulation which does not impede its enzymatic reaction. We have performed molecular dynamics simulations to obtain an insight on many forms of contact between glucose oxidase dimer and the single-layer graphene nano-sheets. The unconnected graphene sheets tended to form a flat stack regardless of their initial positions around the enzyme, whereas the same graphene sheets linked together formed a flower-like shape engendering different forms of wrapping of the enzyme. During the encapsulation no core hydrophobic residues of the enzyme were exposed. Since the polar and charged amino acids populated the enzyme's surface we also estimated, using DFT calculations, the interaction energies of individual polar and charged amino acid residues with graphene. It was found that the negatively charged residues can bind to graphene unexpectedly strongly; however, the main effect of encapsulation comes from the overlap of adjacent edges of graphene sheets