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Blast-induced neurotrauma (BINT) is a pressing concern for veterans and civilians exposed to explosive devices. Affected personnel may have increased risk for long-term cognitive decline and developing tauopathies including Alzheimer's disease-related disorders (ADRD) or frontal-temporal dementia (FTD). The goal of this study was to identify the effect of BINT on molecular networks and their modulation by mutant tau in transgenic (Tg) mice overexpressing the human tau P301L mutation (rTg4510) linked to FTD or non-carriers. The primary focus was on the phosphoproteome because of the prominent role of hyperphosphorylation in neurological disorders. Discrimination learning was assessed following injury in the subsequent 6 weeks, using the automated home-cage monitoring CognitionWall platform. At 40 days post injury, label-free phosphoproteomics was used to evaluate molecular networks in the frontal cortex of mice. Utilizing a weighted peptide co-expression network analysis (WpCNA) approach, we identified phosphopeptide networks tied to associative learning and mossy-fiber pathways and those which predicted learning outcomes. Phosphorylation levels in these networks were inversely related to learning and linked to synaptic dysfunction, cognitive decline, and dementia including Atp6v1a and Itsn1. Low-intensity blast (LIB) selectively increased pSer262tau in rTg4510, a site implicated in initiating tauopathy. Additionally, individual and group level analyses identified the Arhgap33 phosphopeptide as an indicator of BINT-induced cognitive impairment predominantly in rTg4510 mice. This study unveils novel interactions between ADRD genetic susceptibility, BINT, and cognitive decline, thus identifying dysregulated pathways as targets in potential precision-medicine focused therapeutics to alleviate the disease burden among those affected by BINT.

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Animal models of Alzheimer's Disease (AD) are attractive tools for preclinical, prodromal drug testing. The TgF344-AD (Tg) rat exhibits cognitive deficits and 5 major hallmarks of AD. Here we show that spatial water maze (WMZ) memory deficits and proteomic differences in dorsal CA1 were present in young Tg rats. Aged learning-unimpaired (AU) and aged learning-impaired (AI) proteome associated changes were identified and differed by sex. Levels of phosphorylated tau, reactive astrocytes and microglia were significantly increased in aged Tg rats and correlated with the WMZ learning index (LI); in contrast, no significant correlation was present between amyloid plaques or insoluble Aß levels and LI. Neuroinflammatory markers were also significantly correlated with LI and increased in female Tg rats. The anti-inflammatory marker, triggering receptor expressed on myeloid cells-2 (TREM2), was significantly reduced in aged impaired Tg rats and correlated with LI. Identifying and understanding mechanisms that allow for healthy aging by overcoming genetic drivers for AD, and/or promoting drivers for successful aging, are important for developing successful therapeutics against AD.

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Difficulty index and its derivative performance index (PFI) have been commonly used to measure student learning outcomes. However, these indexes have a high volatility and low sensitivity. This work has established the simplex learning index (SLI), which has a low volatility and high sensitivity. To construct SLI, students were divided into two groups based on their scores on the whole quiz. The item SLI and lecture SLI were derived from the results of students in the high-scoring group. Exam results from nine cohorts of medical students in two phases of learning were analyzed. The volatility, measured by the ratio between the standard deviation and the mean, was >65% lower in SLI than in PFI. Using the lecture SLI as a metric, one lecture B22 (Metabolism of Amino Acids), was identified that had an average SLI of 0.66 in earlier four student cohorts in phase 1 learning. Two major changes were made on the lecture, lecture organization and the delivery method, in phase 2. Students from recent five cohorts in phase 2 had an average SLI of 0.84, which was 26.6% higher than that in phase 1 (P < 0.02). In contrast, when PFI was used, the change was only 13.46% and insignificant (P = 0.29). In the same period, implementation of the same delivery method did not yield significant changes in learning outcomes in lecture B24 (Metabolism of Nucleotides). Taken together, this work shows that SLI is a better indicator for learning outcomes and suggests that lecture reorganization is the key to improved student learning.

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In this paper we performed the evaluation of ankle motor performance and motor learning during a goal-directed task, executed using the pediAnklebot robot. The protocol consisted of 3 phases (Familiarization, Adaptation, and Wash Out) repeated one time for each movement direction (plantarflexion, dorsiflexion, inversion, and eversion). During Familiarization and Wash out subjects performed goal-directed movements in unperturbed environment, whereas during Adaptation phase, a curl viscous force field was applied and it was randomly removed 10 times out of 200. Ankle motor performance was evaluated by means of a set of indices grouped into: accuracy, smoothness, temporal, and stopping indices. Learning Index was calculated to study the motor learning during the adaptation phase, which was subdivided into 5 temporal intervals (target sets). The outcomes related to the ankle motor performance highlighted that the best performance in terms of accuracy and smoothness of the trajectories was obtained in dorsiflexion movements in the sagittal plane, and in inversion rotations in the frontal plane. Differences between movement directions revealed an anisotropic behavior of the ankle joint. Results of the Learning index showed a capability of the subjects to rapidly adapt to a perturbed force field depending on the magnitude of the perceived field.

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OBJECTIVES: To verify the value of deep learning in diagnosing nonalcoholic fatty liver disease (NAFLD) by comparing 3 image-processing techniques. METHODS: A total of 240 participants were recruited and divided into 4 groups (normal, mild, moderate, and severe NAFLD groups), according to the definition and the ultrasound scoring system for NAFLD. Two-dimensional hepatic imaging was analyzed by the envelope signal, grayscale signal, and deep-learning index obtained by 3 image-processing techniques. The values of the 3 methods ranged from 0 to 65,535, 0 to 255, and 0 to 4, respectively. We compared the values among the 4 groups, draw receiver operating characteristic curves, and compared the area under the curve (AUC) values to identify the best image-processing technique. RESULTS: The envelope signal value, grayscale value, and deep-learning index had a significant difference between groups and increased with the severity of NAFLD (P < .05). The 3 methods showed good ability (AUC > 0.7) to identify NAFLD. Meanwhile, the deep-learning index showed the superior diagnostic ability in distinguishing moderate and severe NAFLD (AUC = 0.958). CONCLUSIONS: The envelope signal and grayscale values were vital parameters in the diagnosis of NAFLD. Furthermore, deep learning had the best sensitivity and specificity in assessing the severity of NAFLD.

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The neural cell adhesion molecule (NCAM) and its functionally linked polysialyltransferases, ST8SIA2 and ST8SIA4, are crucial for synaptic plasticity. Variations in encoding genes have been associated with mental illness. Since cannabinoids can alter NCAM polysialylation, we hypothesized that delta-9-tetrahydrocannabinol (Δ9-THC) might act as environmental 'second hit' regarding cognition of St8sia2(-/-) mice. These mice show per se minor behavioral abnormalities, consisting of reduced anxiety and mild cognitive deficits. Chronic Δ9-THC treatment of juvenile male wildtype mice (St8sia2(+/+)) (7mg/kg every other day over 3 weeks) did not appreciably affect cognition. St8sia2(-/-) mice, however, displayed a synergistic negative consequence of Δ9-THC on learning/memory, accompanied by polysialic acid-free NCAM-180 reduction in hippocampus and polysialic acid increase in dentate outer molecular layer. These synergistic effects became obvious only months after the last Δ9-THC. We conclude that juvenile cannabis exposure may cause delayed but lasting damage on cognition in subjects genetically predisposed to altered NCAM polysialylation.

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