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Cognitive impairment due to multiple sclerosis (MS) is common and often limits occupational functioning, contributes to disability, and reduces quality of life. Early detection of cognitive involvement in MS is critical for treatment planning and intervention, and frequent, regular cognitive monitoring may provide insight into subtle changes in disease progression.

To compare the sensitivity and specificity of clinical, computer-based and experimental measures to early cognitive involvement in MS.

Cognitive functioning was compared in MS participants early in the disease course to matched healthy controls using conventional, computer-based and functional assessments the Brief International Cognitive Assessment in MS (BICAMS); the computer-based Cogstate Brief Battery (CBB); the Attention Network Test-Interaction (ANT-I), including intra-individual variability; and the Test of Everyday Cognitive Ability (TECA), a functional measure of instrumental activities of daily living.

MS participants (n=25, mean disease duration= 5.82±3.65years) and demographically matched healthy controls (n=29) completed the cognitive assessments. The Cogstate measure of choice reaction time (AUC=0.73, p=.004), intra-individual variability on the ANT-I (AUC=0.79, p=.001), and TECA (AUC=0.78, p=.001) scores were the most sensitive and specific markers of cognitive involvement in MS.

Brief, repeatable, computer-based measures of reaction time and variability detect early MS associated cognitive involvement.

Brief, repeatable, computer-based measures of reaction time and variability detect early MS associated cognitive involvement.Mesial temporal lobe epilepsy (mTLE) has been considered a network disorder disease in which brain regions extending beyond the epileptogenic zones are always affected. However, abnormalities in white matter (WM) functional networks and their associations with widespread network dysfunction are still being identified in mTLE. Accordingly, we investigated the altered functional activities in WM networks in mTLE using fMRI, which has recently been used to probe WM function. We collected resting-state fMRI data from 39 unilateral mTLE patients with hippocampal sclerosis and 29 healthy controls. Eleven WM networks were clustered according to temporal correlation profile. The functional connectivity (FC) of the WM networks were evaluated and compared between the two groups. Furthermore, we assessed the capacity of WM FC for seizure lateralization. According to our analysis, mTLE led to decreased FC within deep WM networks. In addition, the cortical regions involved in seizure propagation and several brain regions displaying interhemispheric disruption showed enhanced functional coupling with deep WM networks. FCs between the ipsilateral deep WM networks and the insula, temporal lobe, and supramarginal gyrus demonstrated positive correlation with seizure frequency. Moreover, the seizure onset zones of 33 patients out of 39 patients could be correctly lateralized. Our findings reveal functional disruptions in WM networks extending to extratemporal regions, supporting the network disorder hypothesis and suggesting that deep WM networks are key network nodes associated with massive dysfunction in mTLE. Moreover, the FC of the WM represents a potentially useful functional imaging measure for the diagnosis of mTLE.Cells continually degrade and replace damaged proteins. However, the high energetic demand of protein turnover generates reactive oxygen species that compromise the long-term health of the proteome. Thus, the relationship between aging, protein turnover, and energetic demand remains unclear. Here, we used a proteomic approach to measure rates of protein turnover within primary fibroblasts isolated from a number of species with diverse life spans including the longest-lived mammal, the bowhead whale. We show that organismal life span is negatively correlated with turnover rates of highly abundant proteins. In comparison with mice, cells from long-lived naked mole rats have slower rates of protein turnover, lower levels of ATP production, and reduced reactive oxygen species levels. Despite having slower rates of protein turnover, naked mole rat cells tolerate protein misfolding stress more effectively than mouse cells. We suggest that in lieu of a rapid constitutive turnover, long-lived species may have evolved more energetically efficient mechanisms for selective detection and clearance of damaged proteins.Dermestidae generally appears on dry corpses and carcasses, especially if mummified or skeletonized. They are forensically important insect species for estimating longer postmortem intervals (PMI). As they develop, Dermestidae larvae undergo multiple larval ecdyses; however, a lack of guidelines for determining the larval instar limits their forensic application. Herein, we explored how temperature impacts the development of Dermestes tessellatocollis Motschulsky, 1860 (Coleoptera Dermestidae). HS94 At seven constant temperatures (16, 19, 22, 25, 28, 31, and 34 °C), the developmental time from egg to adult was 163.87 ± 9.19, 103.56 ± 3.02, 63.59 ± 2.88, 51.49 ± 2.74, 47.86 ± 3.01, 44.62 ± 4.65, and 41.80 ± 4.87 days respectively. Four morphological indexes, including head capsule width, pronotum width, mesonotum width, and body length, were taken in vivo at regular intervals to identify methods for larval instar determination in D. tessellatocollis. The acquired morphological data were used to simulate fitted curves and equations depicting the relationship between the four morphological indexes and instars. From the validation experiment, we could hardly determine a specific instar based on the morphological indexes. The combination of morphometric data (head capsule, pronotum, and mesonotum width) generated the classification accuracy at 100%, 87.5%, 85%, and 93% for the 1st, 2nd/3rd, 4th/5th, and 6th/7th instars, respectively. Nevertheless, the accuracy was unsatisfactory for application in forensic casework. This study provides fundamental development data for adopting D. tessellatocollis in minimum postmortem interval (PMImin) estimations; however, further studies are needed to improve the classification accuracy for the larval instar determination.