The effect of gender norms on the association between violence and hope among girls in the Democratic Republic of the Congo

Background.Girls at early stages of adolescence are vulnerable to violence victimization in humanitarian contexts, but few studies examine factors that affect girls’ hope in these settings. We assessed attitudes toward traditional gender norms as an effect modifier of the relationship between violence exposure and future orientation in displaced girls.Methods.Secondary analysis, using multivariable regression of cross-sectional data from girls ages 10–14 in South Kivu, Democratic Republic of the Congo. Key variables of interest were attitudes toward intimate partner violence (IPV), Children's Hope Scale (CHS) score, and exposure to physical, emotional, and sexual violence within the last 12 months. Additional covariates included age, educational status, and territory.Results.The interaction of exposure to violence and attitudes toward IPV magnified the association between violence exposure and lower CHS score for physical violence (β = −0.09, p = 0.040) and unwanted sexual touching (β = −0.20, p = 0.003) among girls age 10–14, when adjusting for other covariates. The interaction of exposure to violence and attitudes toward IPV magnified the association between violence exposure and lower CHS score for forced sex (β = −0.22, p = 0.016) among girls age 13–14, when adjusting for covariates. Findings for emotional violence, any form of sexual violence, and coerced sex trended toward lower CHS scores for girls who reported higher acceptance of IPV, but did not reach significance.Conclusions.Findings support the utility of gender norms-transformative programming in increasing resilience of girls who have experienced sexual violence in humanitarian contexts

How gender- and violence-related norms affect self-esteem among adolescent refugee girls living in Ethiopia.

BACKGROUND: Evidence suggests adolescent self-esteem is influenced by beliefs of how individuals in their reference group perceive them. However, few studies examine how gender- and violence-related social norms affect self-esteem among refugee populations. This paper explores relationships between gender inequitable and victim-blaming social norms, personal attitudes, and self-esteem among adolescent girls participating in a life skills program in three Ethiopian refugee camps. METHODS: Ordinary least squares multivariable regression analysis was used to assess the associations between attitudes and social norms, and self-esteem. Key independent variables of interest included a scale measuring personal attitudes toward gender inequitable norms, a measure of perceived injunctive norms capturing how a girl believed her family and community would react if she was raped, and a peer-group measure of collective descriptive norms surrounding gender inequity. The key outcome variable, self-esteem, was measured using the Rosenberg self-esteem scale. RESULTS: Girl's personal attitudes toward gender inequitable norms were not significantly predictive of self-esteem at endline, when adjusting for other covariates. Collective peer norms surrounding the same gender inequitable statements were significantly predictive of self-esteem at endline (ß = -0.130; p  =  0.024). Additionally, perceived injunctive norms surrounding family and community-based sanctions for victims of forced sex were associated with a decline in self-esteem at endline (ß = -0.103; p  =  0.014). Significant findings for collective descriptive norms and injunctive norms remained when controlling for all three constructs simultaneously. CONCLUSIONS: Findings suggest shifting collective norms around gender inequity, particularly at the community and peer levels, may sustainably support the safety and well-being of adolescent girls in refugee settings

Disclosure bias for group versus individual reporting of violence amongst conflict-affected adolescent girls in DRC and Ethiopia

Methodologies to measure gender-based violence (GBV) have received inadequate attention, especially in humanitarian contexts where vulnerabilities to violence are exacerbated. This paper compares the results from individual audio computer-assisted self-administered (ACASI) survey interviews with results from participatory social mapping activities, employed with the same sample in two different post-conflict contexts. Eighty-seven internally displaced adolescent girls from the Democratic Republic of the Congo and 78 Sudanese girls living in Ethiopian refugee camps were interviewed using the two methodologies. Results revealed that the group-based qualitative method elicited narratives of violence focusing on events perpetrated by strangers or members of the community more distantly connected to girls. In contrast, ACASI interviews revealed violence predominantly perpetrated by family members and intimate partners. These findings suggest that group-based methods of information gathering frequently used in the field may be more susceptible to socially accepted narratives. Specifically, our findings suggest group-based methods may produce results showing that sexual violence perpetrated by strangers (e.g., from armed groups in the conflict) is more prevalent than violence perpetrated by family and intimate partners. To the extent this finding is true, it may lead to a skewed perception that adolescent GBV involving strangers is a more pressing issue than intimate partner and family-based sexual violence, when in fact, both are of great concern

The Elusive Third Subunit IIa of the Bacterial B-Type Oxidases: The Enzyme from the Hyperthermophile Aquifex aeolicus

The reduction of molecular oxygen to water is catalyzed by complicated membrane-bound metallo-enzymes containing variable numbers of subunits, called cytochrome c oxidases or quinol oxidases. We previously described the cytochrome c oxidase II from the hyperthermophilic bacterium Aquifex aeolicus as a ba3-type two-subunit (subunits I and II) enzyme and showed that it is included in a supercomplex involved in the sulfide-oxygen respiration pathway. It belongs to the B-family of the heme-copper oxidases, enzymes that are far less studied than the ones from family A. Here, we describe the presence in this enzyme of an additional transmembrane helix “subunit IIa”, which is composed of 41 amino acid residues with a measured molecular mass of 5105 Da. Moreover, we show that subunit II, as expected, is in fact longer than the originally annotated protein (from the genome) and contains a transmembrane domain. Using Aquifex aeolicus genomic sequence analyses, N-terminal sequencing, peptide mass fingerprinting and mass spectrometry analysis on entire subunits, we conclude that the B-type enzyme from this bacterium is a three-subunit complex. It is composed of subunit I (encoded by coxA2) of 59000 Da, subunit II (encoded by coxB2) of 16700 Da and subunit IIa which contain 12, 1 and 1 transmembrane helices respectively. A structural model indicates that the structural organization of the complex strongly resembles that of the ba3 cytochrome c oxidase from the bacterium Thermus thermophilus, the IIa helical subunit being structurally the lacking N-terminal transmembrane helix of subunit II present in the A-type oxidases. Analysis of the genomic context of genes encoding oxidases indicates that this third subunit is present in many of the bacterial oxidases from B-family, enzymes that have been described as two-subunit complexes

Novel Insights into the Diversity of Catabolic Metabolism from Ten Haloarchaeal Genomes

BACKGROUND: The extremely halophilic archaea are present worldwide in saline environments and have important biotechnological applications. Ten complete genomes of haloarchaea are now available, providing an opportunity for comparative analysis. METHODOLOGY/PRINCIPAL FINDINGS: We report here the comparative analysis of five newly sequenced haloarchaeal genomes with five previously published ones. Whole genome trees based on protein sequences provide strong support for deep relationships between the ten organisms. Using a soft clustering approach, we identified 887 protein clusters present in all halophiles. Of these core clusters, 112 are not found in any other archaea and therefore constitute the haloarchaeal signature. Four of the halophiles were isolated from water, and four were isolated from soil or sediment. Although there are few habitat-specific clusters, the soil/sediment halophiles tend to have greater capacity for polysaccharide degradation, siderophore synthesis, and cell wall modification. Halorhabdus utahensis and Haloterrigena turkmenica encode over forty glycosyl hydrolases each, and may be capable of breaking down naturally occurring complex carbohydrates. H. utahensis is specialized for growth on carbohydrates and has few amino acid degradation pathways. It uses the non-oxidative pentose phosphate pathway instead of the oxidative pathway, giving it more flexibility in the metabolism of pentoses. CONCLUSIONS: These new genomes expand our understanding of haloarchaeal catabolic pathways, providing a basis for further experimental analysis, especially with regard to carbohydrate metabolism. Halophilic glycosyl hydrolases for use in biofuel production are more likely to be found in halophiles isolated from soil or sediment

Metabolism of halophilic archaea

In spite of their common hypersaline environment, halophilic archaea are surprisingly different in their nutritional demands and metabolic pathways. The metabolic diversity of halophilic archaea was investigated at the genomic level through systematic metabolic reconstruction and comparative analysis of four completely sequenced species: Halobacterium salinarum, Haloarcula marismortui, Haloquadratum walsbyi, and the haloalkaliphile Natronomonas pharaonis. The comparative study reveals different sets of enzyme genes amongst halophilic archaea, e.g. in glycerol degradation, pentose metabolism, and folate synthesis. The carefully assessed metabolic data represent a reliable resource for future system biology approaches as it also links to current experimental data on (halo)archaea from the literature

‘Multi-Epitope-Targeted’ Immune-Specific Therapy for a Multiple Sclerosis-Like Disease via Engineered Multi-Epitope Protein Is Superior to Peptides

Antigen-induced peripheral tolerance is potentially one of the most efficient and specific therapeutic approaches for autoimmune diseases. Although highly effective in animal models, antigen-based strategies have not yet been translated into practicable human therapy, and several clinical trials using a single antigen or peptidic-epitope in multiple sclerosis (MS) yielded disappointing results. In these clinical trials, however, the apparent complexity and dynamics of the pathogenic autoimmunity associated with MS, which result from the multiplicity of potential target antigens and “epitope spread”, have not been sufficiently considered. Thus, targeting pathogenic T-cells reactive against a single antigen/epitope is unlikely to be sufficient; to be effective, immunospecific therapy to MS should logically neutralize concomitantly T-cells reactive against as many major target antigens/epitopes as possible. We investigated such “multi-epitope-targeting” approach in murine experimental autoimmune encephalomyelitis (EAE) associated with a single (“classical”) or multiple (“complex”) anti-myelin autoreactivities, using cocktail of different encephalitogenic peptides vis-a-vis artificial multi-epitope-protein (designated Y-MSPc) encompassing rationally selected MS-relevant epitopes of five major myelin antigens, as “multi-epitope-targeting” agents. Y-MSPc was superior to peptide(s) in concomitantly downregulating pathogenic T-cells reactive against multiple myelin antigens/epitopes, via inducing more effective, longer lasting peripheral regulatory mechanisms (cytokine shift, anergy, and Foxp3+ CTLA4+ regulatory T-cells). Y-MSPc was also consistently more effective than the disease-inducing single peptide or peptide cocktail, not only in suppressing the development of “classical” or “complex EAE” or ameliorating ongoing disease, but most importantly, in reversing chronic EAE. Overall, our data emphasize that a “multi-epitope-targeting” strategy is required for effective immune-specific therapy of organ-specific autoimmune diseases associated with complex and dynamic pathogenic autoimmunity, such as MS; our data further demonstrate that the “multi-epitope-targeting” approach to therapy is optimized through specifically designed multi-epitope-proteins, rather than myelin peptide cocktails, as “multi-epitope-targeting” agents. Such artificial multi-epitope proteins can be tailored to other organ-specific autoimmune diseases

Archaic chaos: intrinsically disordered proteins in Archaea

Background: Many proteins or their regions known as intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) lack unique 3D structure in their native states under physiological conditions yet fulfill key biological functions. Earlier bioinformatics studies showed that IDPs and IDRs are highly abundant in different proteomes and carry out mostly regulatory functions related to molecular recognition and signal transduction. Archaea belong to an intriguing domain of life whose members, being microbes, are characterized by a unique mosaic-like combination of bacterial and eukaryotic properties and include inhabitants of some of the most extreme environments on the planet. With the expansion of the archaea genome data (more than fifty archaea species from five different phyla are known now), and with recent improvements in the accuracy of intrinsic disorder prediction, it is time to re-examine the abundance of IDPs and IDRs in the archaea domain.Results: The abundance of IDPs and IDRs in 53 archaea species is analyzed. The amino acid composition profiles of these species are generally quite different from each other. The disordered content is highly species-dependent. Thermoproteales proteomes have 14% of disordered residues, while in Halobacteria, this value increases to 34%. In proteomes of these two phyla, proteins containing long disordered regions account for 12% and 46%, whereas 4% and 26% their proteins are wholly disordered. These three measures of disorder content are linearly correlated with each other at the genome level. There is a weak correlation between the environmental factors (such as salinity, pH and temperature of the habitats) and the abundance of intrinsic disorder in Archaea, with various environmental factors possessing different disorder-promoting strengths. Harsh environmental conditions, especially those combining several hostile factors, clearly favor increased disorder content. Intrinsic disorder is highly abundant in functional Pfam domains of the archaea origin. The analysis based on the disordered content and phylogenetic tree indicated diverse evolution of intrinsic disorder among various classes and species of Archaea.Conclusions: Archaea proteins are rich in intrinsic disorder. Some of these IDPs and IDRs likely evolve to help archaea to accommodate to their hostile habitats. Other archaean IDPs and IDRs possess crucial biological functions similar to those of the bacterial and eukaryotic IDPs/IDRs

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks