Transfer RNA-Derived Fragments and isomiRs Are Novel Components of Chronic TBI-Induced Neuropathology

Neuroinflammation is a secondary injury mechanism that evolves in the brain for months after traumatic brain injury (TBI). We hypothesized that an altered small non-coding RNA (sncRNA) signature plays a key role in modulating post-TBI secondary injury and neuroinflammation. At 3threemonths post-TBI, messenger RNA sequencing (seq) and small RNAseq were performed on samples from the ipsilateral thalamus and perilesional cortex of selected rats with a chronic inflammatory endophenotype, and sham-operated controls. The small RNAseq identified dysregulation of 2 and 19 miRNAs in the thalamus and cortex, respectively. The two candidates from the thalamus and the top ten from the cortex were selected for validation. In the thalamus, miR-146a-5p and miR-155-5p levels were upregulated, and in the cortex, miR-375-3p and miR-211-5p levels were upregulated. Analysis of isomiRs of differentially expressed miRNAs identified 3′nucleotide additions that were increased after TBI. Surprisingly, we found fragments originating from 16 and 13 tRNAs in the thalamus and cortex, respectively. We further analyzed two upregulated fragments, 3′tRF-IleAAT and 3′tRF-LysTTT. Increased expression of the full miR-146a profile, and 3′tRF-IleAAT and 3′tRF-LysTTT was associated with a worse behavioral outcome in animals with chronic neuroinflammation. Our results highlight the importance of understanding the regulatory roles of as-yet unknown sncRNAs for developing better strategies to treat TBI and neuroinflammation.

Gut-Microbiome Composition in Response to Phenylketonuria Depends on Dietary Phenylalanine in BTBR Pahenu2 Mice

Phenylketonuria (PKU) is a metabolic disorder caused by a hepatic enzyme deficiency causing high blood and brain levels of the amino acid Phenylalanine (Phe), leading to severe cognitive and psychological deficits that can be prevented, but not completely, by dietary treatment. The behavioral outcome of PKU could be affected by the gut-microbiome-brain axis, as diet is one of the major drivers of the gut microbiome composition. Gut-microbiome alterations have been reported in treated patients with PKU, although the question remains whether this is due to PKU, the dietary treatment, or their interaction. We, therefore, examined the effects of dietary Phe restriction on gut-microbiome composition and relationships with behavioral outcome in mice. Male and female BTBR Pahenu2 mice received either a control diet (normal protein, “high” Phe), liberalized Phe-restricted (33% natural protein restriction), or severe Phe-restricted (75% natural protein restriction) diet with protein substitutes for 10 weeks (n = 14 per group). Their behavioral performance was examined in an open field test, novel and spatial object location tests, and a balance beam. Fecal samples were collected and sequenced for the bacterial 16S ribosomal RNA (rRNA) region. Results indicated that PKU on a high Phe diet reduced Shannon diversity significantly and altered the microbiome composition compared with wild-type animals. Phe-restriction prevented this loss in Shannon diversity but changed community composition even more than the high-Phe diet, depending on the severity of the restriction. Moreover, on a taxonomic level, we observed the highest number of differentially abundant genera in animals that received 75% Phe-restriction. Based on correlation analyses with differentially abundant taxa, the families Entereococacceae, Erysipelotrichaceae, Porphyromonadaceae, and the genus Alloprevotella showed interesting relationships with either plasma Phe levels and/or object memory. According to our results, these bacterial taxa could be good candidates to start examining the microbial metabolic potential and probiotic properties in the context of PKU. We conclude that PKU leads to an altered gut microbiome composition in mice, which is least severe on a liberalized Phe-restricted diet. This may suggest that the current Phe-restricted diet for PKU patients could be optimized by taking dietary effects on the microbiome into account.

Defining Translational Significance in Gerontology

Innovation in Aging requires a statement from authors on translational significance. This requirement forces authors to consider the implications of their research for changing some component of aging. How does the research address a challenge posed by aging bodies, minds, relationships, or societies? The editorial board has developed criteria for assessing translational significance. Translational research must meet at least one of three criteria. It (i) must predict or explain a health or behavioral outcome, (ii) be advanced enough in deployment or development to assess these effects, and (iii) have a clear pathway to large-scale program delivery or change in clinical practice. The criteria rule out some kinds of submissions, such as scale development, single-case studies, or reviews of literature. We use these criteria to structure each article’s required translational significance statement. Rethinking translation may help focus research across the full set of GSA journals.

An Infant Sleep Electroencephalographic Marker of Thalamocortical Connectivity Predicts Behavioral Outcome in Late Infancy

Infancy represents a critical period during which thalamocortical brain connections develop and mature. Deviations in the maturation of thalamocortical connectivity are linked to neurodevelopmental disorders. There is a lack of early biomarkers to detect and localize neuromaturational deviations, which can be overcome with mapping through high-density electroencephalography (hdEEG) assessed in sleep. Specifically, slow waves and spindles in non-rapid eye movement (NREM) sleep are generated by the thalamocortical system, and their characteristics, slow wave slope and spindle density, are closely related to neuroplasticity and learning. Recent studies further suggest that information processing during sleep underlying sleep-dependent learning is promoted by the temporal coupling of slow waves and spindles, yet slow wave-spindle coupling remains unexplored in infancy. Thus, we evaluated three potential biomarkers: 1) slow wave slope, 2) spindle density, and 3) the temporal coupling of slow waves with spindles. We use hdEEG to first examine the occurrence and spatial distribution of these three EEG features in healthy infants and second to evaluate a predictive relationship with later behavioral outcomes. We report four key findings: First, infants' EEG features appear locally: slow wave slope is maximal in occipital and frontal areas, whereas spindle density is most pronounced frontocentrally. Second, slow waves and spindles are temporally coupled in infancy, with maximal coupling strength in the occipital areas of the brain. Third, slow wave slope, spindle density, and slow wave-spindle coupling are not associated with concurrent behavioral status (6 months). Fourth, spindle density in central and frontocentral regions at age 6 months predicts later behavioral outcomes at 12 and 24 months. Neither slow wave slope nor slow wave-spindle coupling predict behavioral development. Our results propose spindle density as an early EEG biomarker for identifying thalamocortical maturation, which can potentially be used for early diagnosis of neurodevelopmental disorders in infants. These findings are complemented by our companion paper that demonstrates the linkage of spindle density to infant nighttime movement, framing the possible role of spindles in sensorimotor microcircuitry development. Together, our studies suggest that early sleep habits, thalamocortical maturation, and behavioral outcome are closely interwoven. A crucial next step will be to evaluate whether early therapeutic interventions may be effective to reverse deviations in identified individuals at risk.

Baseline Depression-Like Behaviors in Wild-Type Adolescent Mice Are Strain and Age but Not Sex Dependent

Depression is a major neuropsychiatric disorder, decreasing the ability of hundreds of millions of individuals worldwide to function in social, academic, and employment settings. Beyond the alarming public health problem, depression leads to morbidity across the entire age including adolescence and adulthood. Modeling depression in rodents has been used to understand the pathophysiological mechanisms behind this disorder and create new therapeutics. Although women are two times more likely to be diagnosed with depression compared to men, behavioral experiments on rodent models of depression are mainly performed in males based on the assumption that the estrous cycles in females may affect the behavioral outcome and cause an increase in the intrinsic variability compared to males. Still, the inclusion of female rodents in the behavioral analysis is mandatory to establish the origin of sex bias in depression. Here, we investigated the baseline depression-like behaviors in male and female mice of three adolescent wild-type inbred strains, C57BL/6N, DBA/2, and FVB/N, that are typically used as background strains for mouse models of neuropsychiatric disorders. Our experiments, performed at two different developmental stages during adolescence (P22–P26 and P32–P36), revealed strain but no sex differences in a set of depression-related tests, including tail suspension, sucrose preference and forced swim tests. Additionally, the 10-day interval during this sensitive period uncovered a strong impact on the behavioral outcome of C57BL/6N and FVB/N mice, highlighting a significant effect of maturation on behavioral patterns. Since anxiety-related behavioral tests are often performed together with depression tests in mouse models of neuropsychiatric disorders, we extended our study and included hyponeophagia as an anxiety test. Consistent with a previous study revealing sex differences in other anxiety tests in adolescent mice, male and females mice behaved differently in the hyponeophagia test at P27. Our study gives insight into the behavioral experiments assessing depression and stresses the importance of considering strain, age and sex when evaluating neuropsychiatric-like traits in rodent models.

A META-ANALYSIS OF SMARTPHONE ADDICTION AND BEHAVIORAL OUTCOMES

Though smartphones have become the icon of the 21st century, they are possibly the biggest source of non-drug addiction. The purpose of this meta-analysis was to identify behavioral outcomes associated with smartphone addiction, and to evaluate their overall and individual relationships with smartphone addiction. This metaanalysis conducted a preliminary review of 6115 studies which investigated the relationships between smartphone addiction and behavioral outcomes. Fifty-three studies fulfilled the inclusion criteria developed for this study and their review identified thirteen behavioral outcomes of smartphone addiction. Meta-analytical tests confirmed a positive and significant relationship between smartphone addition and overall behavioral outcome. However, the combined effects were significantly heterogeneous and this could be attributed to the diverse nature of behavioral outcomes, dispersion of studies across the globe, and varying demographics of samples. The results showed the prevalence of the following eight behavioral outcomes: anxiety, depression, loneliness, mental health, self-control, self-regulation, stress; and withdrawal that had a significant and positive relationship with smartphone addiction, while only self-esteem had a significant and negative relationship with smartphone addiction. Finally, depression was identified as the behavioral outcome that has a significant and positive relationship with smartphone addiction irrespective of global geographic and demographic variations. This article has elaborated on smartphone addiction criteria similar to that established for researches in substance abuse and addiction. Furthermore, the article has been able to show that smartphone addiction and its problematic use has become an emerging problem with grave consequences.

When and Why Contexts Predict Unethical Behavior: Evidence From a Laboratory Bribery Game

In economic unethical decision-making experiments, one important methodological investigation is what types of contexts should be used to frame the instructions. Within the experimental economics community, using neutral-context instructions instead of loaded-context instructions is the mainstream practice. Because the loaded contexts may impact behavior in an unpredictable manner and therefore, put experimental control at risk. Nevertheless, using the loaded-context instructions could be advantageous in several ways. A properly framed context can help to facilitate learning and gain ecological validity. The challenge is whether we can identify when and why the loaded context may alter behavior. In this paper, we aim to test if being familiar with a loaded context can systematically influence unethical decisions in a bribery game. We conduct a laboratory bribery game experiment with three different treatments: the neutral-context treatment, the familiar-context treatment, and the unfamiliar-context treatment. Using the neutral-context treatment as a benchmark, we find that participants in the familiar-context treatment express stronger negative attitudes toward corruption. Attitudes toward unethical behavior are the same in the neutral-context treatment and the unfamiliar-context treatment. Behaviorally, the participants in the familiar-context treatment are much less likely to engage in corrupt activities. The neutral-context treatment and the unfamiliar-context treatment produce the same behavioral outcome.

Time in Associative Learning: A Review on Temporal Maps

Ability to recall the timing of events is a crucial aspect of associative learning. Yet, traditional theories of associative learning have often overlooked the role of time in learning association and shaping the behavioral outcome. They address temporal learning as an independent and parallel process. Temporal Coding Hypothesis is an attempt to bringing together the associative and non-associative aspects of learning. This account proposes temporal maps, a representation that encodes several aspects of a learned association, but attach considerable importance to the temporal aspect. A temporal map helps an agent to make inferences about missing information by applying an integration mechanism over a common element present in independently acquired temporal maps. We review the empirical evidence demonstrating the construct of temporal maps and discuss the importance of this concept in clinical and behavioral interventions.