Increased neuroplasticity and neural development during puberty provide a context for which stress and trauma can have dramatic and long-lasting effects on psychological systems; therefore, this ...study was designed to determine whether exposure to potentially traumatic events during puberty uniquely predicts adolescent girls' psychopathology. Because neural substrates associated with different forms of psychopathology seemingly develop at different rates, the possibility that the developmental timing of trauma relative to puberty predicts the nature of psychopathology (posttraumatic stress disorder PTSD, depressive, and anxiety disorders) was examined.
A subset of 2,899 adolescent girls from the National Comorbidity Survey Replication-Adolescent Supplement who completed the study 2+ years postmenarche was selected. Past-year psychiatric disorders and reports of age of trauma exposure were assessed using the Composite International Diagnostic Interview. Developmental stages were defined as the 2 years after the year of menarche ("postpuberty"), 3 years before and year of menarche ("puberty"), 2 to 6 years before the puberty period ("grade school"), and 4 to 5 years after birth ("infancy-preschool").
Compared to other developmental periods, trauma during puberty conferred significantly more risk (50.47% of model R(2)) for girls' past-year anxiety disorder diagnoses (primarily social phobia), whereas trauma during the grade school period conferred significantly more risk (47.24% of model R(2)) for past-year depressive disorder diagnoses. Recency of trauma best predicted past-year PTSD diagnoses.
Supporting rodent models, puberty may be a sensitive period for the impact of trauma on girls' development of an anxiety disorder. Trauma prepuberty or postpuberty distinctly predicts depression or PTSD, suggesting differential etiological processes.
Since its initial recognition, HIV has been responsible for around 35 million deaths globally. The introduction of Antiretroviral Therapy has helped to reduce mortality from HIV. However, the ...resulting increased longevity has influenced the experience of people living with HIV, which now manifests as a chronic condition requiring effective self-management. This review aimed to identify and evaluate the effectiveness of interventions to improve self-management of adults living with HIV on Antiretroviral therapy.
The review included published experimental studies addressing interventions to improve self-management of adults living with HIV on Antiretroviral Therapy. Studies were included if they addressed two or more outcomes of self-management, as defined by the Theory of Individual and Family Self-Management. The search covered four databases and was limited to papers published in the English language from 2001 to March 30, 2019. The reference lists of included studies were further searched for additional studies. Two independent reviewers using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI SUMARI) assessed the methodological quality of the reviewed papers. Data extraction was undertaken using the JBI SUMARI standardized data extraction tool. As the included papers were not homogeneous, it was not possible to conduct a meta-analysis. A narrative synthesis was undertaken to synthesize the findings of the included studies.
The search identified 337 articles from which 10 experimental and 2 quasi-experimental studies were included. The total participant sample in the included studies was 1661 adults living with HIV. The overall evidence quality of the findings was considered moderate. Many of the studies included in this review comprised multi-component interventions to improve self-management. Skills training, in conjunction with other forms of interventions, particularly phone counseling, was commonly employed and generally effective in improving self-management outcomes. Counseling with a symptom management manual was another employed and effective intervention, followed by technology-assisted self-management interventions. The most common outcomes measured were maintaining medication adherence and quality of life, followed by symptom management, self-efficacy, coping, and social support.
Interventions to improve self-management varied across studies. However, promising outcomes achieved in the majority of studies through interventions comprising a combination of skills training, phone counseling, counseling with symptom management manuals, and technology-assisted interventions.
Summary
Computational models of plants have identified gaps in our understanding of biological systems, and have revealed ways to optimize cellular processes or organ‐level architecture to increase ...productivity. Thus, computational models are learning tools that help direct experimentation and measurements. Models are simplifications of complex systems, and often simulate specific processes at single scales (e.g. temporal, spatial, organizational, etc.). Consequently, single‐scale models are unable to capture the critical cross‐scale interactions that result in emergent properties of the system. In this perspective article, we contend that to accurately predict how a plant will respond in an untested environment, it is necessary to integrate mathematical models across biological scales. Computationally mimicking the flow of biological information from the genome to the phenome is an important step in discovering new experimental strategies to improve crops. A key challenge is to connect models across biological, temporal and computational (e.g. CPU versus GPU) scales, and then to visualize and interpret integrated model outputs. We address this challenge by describing the efforts of the international Crops in silico consortium.
Significance Statement
Computational plant models increase our comprehension of biological processes and reveal gaps in knowledge. Integrated, multiscale models have the potential to increase our predictive capability for crop response to future environments. This perspective article highlights the need for multiscale modeling for the development of crop ideotypes, and contends that advanced visualization of multiscale model simulations will guide future efforts for experimental measurement and engineering.
Research with military veterans has established that distress may arise in response to perpetrating violent behaviors that violate individuals' moral beliefs. To date, no studies have similarly ...examined morally‐related cognitive and emotional responses specifically among intimate partner violence (IPV) perpetrators. However, research on moral cognitions and emotions in response to IPV perpetration may inform understanding of the behavior and potential mechanisms for intervention. In the current series of four studies, we used classical test theory to develop a measure of moral distress following IPV perpetration that focuses on thoughts about the actions (assimilated cognitions), thoughts about the self due to one's actions (accommodated cognitions), and emotions experienced due to one's actions (moral emotions). Items were developed and tested among two samples of undergraduate students, and psychometric properties of the final measure were confirmed among two community samples. The final measure consists of three subscales consisting of five items each. Results demonstrate support for internal consistency and test–retest reliability, convergent, discriminant, and incremental validity, and factor structure. This measure can be used in future research designed to examine how individuals respond to their IPV perpetration, and to study the implications this may have for long‐term outcomes and behavioral change.
The dynamic nature of gene regulatory networks allows cells to rapidly respond to environmental change. However, the underlying temporal connections are missed, even in kinetic studies, as ...transcription factor (TF) binding within at least one time point is required to identify primary targets. The TF-regulated but unbound genes are dismissed as secondary targets. Instead, we report that these genes comprise transient TF-target interactions most relevant to rapid signal transduction. We temporally perturbed a master TF (Basic Leucine Zipper 1, bZIP1) and the nitrogen (N) signal it transduces and integrated TF regulation and binding data from the same cell samples. Our enabling approach could identify primary TF targets based solely on gene regulation, in the absence of TF binding. We uncovered three classes of primary TF targets: (i) poised (TF-bound but not TF-regulated), (ii) stable (TF-bound and TF-regulated), and (iii) transient (TF-regulated but not TF-bound), the largest class. Unexpectedly, the transient bZIP1 targets are uniquely relevant to rapid N signaling in planta, enriched in dynamic N-responsive genes, and regulated by TF and N signal interactions. These transient targets include early N responders nitrate transporter 2.1 and NIN-like protein 3, bound by bZIP1 at 1—5 min, but not at later time points following TF perturbation. Moreover, promoters of these transient targets are uniquely enriched with cis-regulatory motifs coinherited with bZIP1 binding sites, suggesting a recruitment role for bZIP1. This transient mode of TF action supports a classic, but forgotten, "hit-and-run" transcription model, which enables a "catalyst TF" to activate a large set of targets within minutes of signal perturbation.
Methylation of N.sup.6 adenosine (m.sup.6A) is known to be important for diverse biological processes including gene expression control, translation of protein, and messenger RNA (mRNA) splicing. ...However, its role in the development of human cancers is poorly understood. By analyzing datasets from the Cancer Genome Atlas Research Network (TCGA) acute myeloid leukemia (AML) study, we discover that mutations and/or copy number variations of m.sup.6A regulatory genes are strongly associated with the presence of TP53 mutations in AML patients. Further, our analyses reveal that alterations in m.sup.6A regulatory genes confer a worse survival in AML. Our work indicates that genetic alterations of m.sup.6A regulatory genes may cooperate with TP53 and/or its regulator/downstream targets in the pathogenesis and/or maintenance of AML. Keywords: RNA modification, m.sup.6A, Leukemia, Acute myeloid leukemia, TP53 mutation
This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in ...plants. Our “just-in-time” analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to “prune” the network to 155 TFs and 608 targets. This network precision was reconfirmed using genome-wide TF-target regulation data for four additional TFs (TGA1, HHO5/6, and PHL1) not used in network pruning. These higher-confidence edges in the GRN were further filtered by independent TF-target binding data, used to calculate a TF “N-specificity” index. This refined GRN identifies the temporal relationship of known/validated regulators of N signaling (NLP7/8, TGA1/4, NAC4, HRS1, and LBD37/38/39) and 146 additional regulators. Six TFs—CRF4, SNZ, CDF1, HHO5/6, and PHL1—validated herein regulate a significant number of genes in the dynamic N response, targeting 54% of N-uptake/assimilation pathway genes. Phenotypically, inducible overexpression of CRF4 in planta regulates genes resulting in altered biomass, root development, and 15NO₃⁻ uptake, specifically under low-N conditions. This dynamic N-signaling GRN now provides the temporal “transcriptional logic” for 155 candidate TFs to improve nitrogen use efficiency with potential agricultural applications. Broadly, these time-based approaches can uncover the temporal transcriptional logic for any biological response system in biology, agriculture, or medicine.
Aggressive behavior is a major public health issue for which there are few efficacious treatments. Although much of information processing is automatic, there are few studies of early-stage decoding ...biases (e.g., attention bias to threat) and aggressive behavior, potentially resulting in missed opportunities for identifying targets of intervention. Previous studies are limited by indirect measures of attention bias and little consideration of proximal factors like state fear, which organizes perception and motivates defensive behaviors. We used laboratory methods (i.e., eye-tracking, idiographic mood induction, and the Point Subtraction Aggression Paradigm), to examine the association between attention bias to physical and negative evaluation threat and in vivo defensive responding (i.e., aggression and escape) and the potential moderating role of state fear among 74 undergraduate students. As predicted, attention bias to threat was positively associated with in vivo aggression. Fear did not potentiate aggression or modify the relationship between attentional bias to threat and aggression; however, in the fear condition, greater attentional bias to threat was associated with less escape behavior. Findings add to the sparse literature identifying early-stage decoding processes as possible risk factors of aggression and suggest a need for additional research on freeze behavior in response to threat and provocation.
•Laboratory methods were used to examine attention biases, state fear, and aggression.•Aggression was associated with biases to physical and negative evaluation threats.•During fear, threat bias was linked to less escape (freezing), not more aggression.•Attention bias to threat may be a viable target of intervention for aggression.
SUMMARY
Out of the three aromatic amino acids, the highest flux in plants is directed towards phenylalanine, which is utilized to synthesize proteins and thousands of phenolic metabolites ...contributing to plant fitness. Phenylalanine is produced predominantly in plastids via the shikimate pathway and subsequent arogenate pathway, both of which are subject to complex transcriptional and post‐transcriptional regulation. Previously, it was shown that allosteric feedback inhibition of arogenate dehydratase (ADT), which catalyzes the final step of the arogenate pathway, restricts flux through phenylalanine biosynthesis. Here, we show that in petunia (Petunia hybrida) flowers, which typically produce high phenylalanine levels, ADT regulation is relaxed, but not eliminated. Moderate expression of a feedback‐insensitive ADT increased flux towards phenylalanine, while high overexpression paradoxically reduced phenylalanine formation. This reduction could be partially, but not fully, recovered by bypassing other known metabolic flux control points in the aromatic amino acid network. Using comparative transcriptomics, reverse genetics, and metabolic flux analysis, we discovered that transcriptional regulation of the d‐ribulose‐5‐phosphate 3‐epimerase gene in the pentose phosphate pathway controls flux into the shikimate pathway. Taken together, our findings reveal that regulation within and upstream of the shikimate pathway shares control over phenylalanine biosynthesis in the plant cell.
Significance Statement
An increase in phenylalanine levels is a frequent target of metabolic engineering strategies for efficient production of phenylalanine‐derived metabolites. Phenylalanine is produced predominantly in plastids via the shikimate pathway and is subject to complex transcriptional and post‐transcriptional regulation, which occurs not only within the pathway but also upstream in the pentose phosphate pathway.
Increase in demand for our primary foodstuffs is outstripping increase in yields, an expanding gap that indicates large potential food shortages by mid-century. This comes at a time when yield ...improvements are slowing or stagnating as the approaches of the Green Revolution reach their biological limits. Photosynthesis, which has been improved little in crops and falls far short of its biological limit, emerges as the key remaining route to increase the genetic yield potential of our major crops. Thus, there is a timely need to accelerate our understanding of the photosynthetic process in crops to allow informed and guided improvements via in-silico-assisted genetic engineering. Potential and emerging approaches to improving crop photosynthetic efficiency are discussed, and the new tools needed to realize these changes are presented.
Human health and well-being depend on adequate nutrition. Although the current food production is suitable for the needs of the global population, there is a significant potential for future food shortages. This Review discusses the biological limits of crop production and how engineering cellular processes such as photosynthesis can be used to improve the yield of our major crops.
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