Context-specific Interactions Research Articles

Capturing the effects of flower strips on natural pest control in agronomic land use models

ContextGiven policy objectives for pesticide reduction, functional biodiversity is increasingly important for agricultural production. However, economic land use optimisation models rarely account for the interplay between agricultural production and functional biodiversity, like natural pest control (NPC). ObjectiveWe present and discuss an approach to consider feedback effects between NPC and agricultural production in a geodata-based farm economic land use model. MethodsThe geodata-based land use model PALUD was extended to incorporate interactions between NPC and crop yields. This included linking a generic NPC model, based on semi-natural habitats, with an econometric approach to estimate yield gaps as a function of NPC potential. As a case study, the model was then applied to the German state Brandenburg, using permanent flower strips as example to promote NPC. Here, we analysed the impacts of enhancing NPC potential on food production and gross margins from arable land use. Results and conclusionsOur analysis revealed that a higher level of NPC through flower strips improved gross margins. by up to 6.4 % and crop production by up to 1.2 % within a pesticide-free environment in Brandenburg. Despite inherent limitations and uncertainties of the approach, our study provides a pivotal advancement in integrating NPC into economic land use models. Future refinements incorporating more detailed knowledge on context-specific interactions between crops, pests and predators will improve model robustness. Our approach and case study results provide valuable insights for policy-making on tailored sustainable landscape development and serve as a foundation for future modelling efforts. SignificanceTo our knowledge the interaction between NPC and crop yields has not yet been integrated into any geospatially based economic land use model before. Incorparating these interactions is vital for guiding policies towards sustainable agricultural systems. In this respect it is important to develop and discuss further methodological approaches.

Unveiling hidden connections in omics data via pyPARAGON: an integrative hybrid approach for disease network construction.

Network inference or reconstruction algorithms play an integral role in successfully analyzing and identifying causal relationships between omics hits for detecting dysregulated and altered signaling components in various contexts, encompassing disease states and drug perturbations. However, accurate representation of signaling networks and identification of context-specific interactions within sparse omics datasets in complex interactomes pose significant challenges in integrative approaches. To address these challenges, we present pyPARAGON (PAgeRAnk-flux on Graphlet-guided network for multi-Omic data integratioN), a novel tool that combines network propagation with graphlets. pyPARAGON enhances accuracy and minimizes the inclusion of nonspecific interactions in signaling networks by utilizing network rather than relying on pairwise connections among proteins. Through comprehensive evaluations on benchmark signaling pathways, we demonstrate that pyPARAGON outperforms state-of-the-art approaches in node propagation and edge inference. Furthermore, pyPARAGON exhibits promising performance in discovering cancer driver networks. Notably, we demonstrate its utility in network-based stratification of patient tumors by integrating phosphoproteomic data from 105 breast cancer tumors with the interactome and demonstrating tumor-specific signaling pathways. Overall, pyPARAGON is a novel tool for analyzing and integrating multi-omic data in the context of signaling networks. pyPARAGON is available at https://github.com/netlab-ku/pyPARAGON.

Prolonged intermittent hypoxia differentially regulates phrenic motor neuron serotonin receptor expression in rats following chronic cervical spinal cord injury

Low-dose (< 2 h/day), acute intermittent hypoxia (AIH) elicits multiple forms of serotonin-dependent phrenic motor plasticity and is emerging as a promising therapeutic strategy to restore respiratory and non-respiratory motor function after spinal cord injury (SCI). In contrast, high-dose (> 8 h/day), chronic intermittent hypoxia (CIH) undermines some forms of serotonin-dependent phrenic motor plasticity and elicits pathology. CIH is a hallmark of sleep disordered breathing, which is highly prevalent in individuals with cervical SCI. Interestingly, AIH and CIH preconditioning differentially impact phrenic motor plasticity. Although mechanisms of AIH-induced plasticity in the phrenic motor system are well-described in naïve rats, we know little concerning how these mechanisms are affected by chronic SCI or intermittent hypoxia preconditioning. Thus, in a rat model of chronic, incomplete cervical SCI (lateral spinal hemisection at C2 (C2Hx), we assessed serotonin type 2A, 2B and 7 receptor expression in and near phrenic motor neurons and compared: 1) intact vs. chronically injured rats; and 2) the impact of preconditioning with varied “doses” of intermittent hypoxia (IH). While there were no effects of chronic injury or intermittent hypoxia alone, CIH affected multiple receptors in rats with chronic C2Hx. Specifically, CIH preconditioning (8 h/day; 28 days) increased serotonin 2A and 7 receptor expression exclusively in rats with chronic C2Hx. Understanding the complex, context-specific interactions between chronic SCI and CIH and how this ultimately impacts phrenic motor plasticity is important as we leverage AIH-induced motor plasticity to restore breathing and other non-respiratory motor functions in people with chronic SCI.

Digital Marketing in the New Era: Exploring the Affordances of Chatbots in Consumer Engagement and Brand Connection

This article explores the evolving landscape of marketing and personalized communication in the digital era, with a particular focus on the affordances of chatbots as pivotal tools for businesses. As consumers increasingly turn to online platforms for information and purchasing decisions, chatbots have emerged as indispensable tools for enhancing customer engagement and delivering personalized experiences. While previous research has outlined the potential benefits and drawbacks of chatbots in marketing, a critical gap exists in understanding their context-specific impact on user perceptions and behaviors. To bridge this gap, this study adopts the affordance theory to investigate how chatbots offer unique affordances to users across various shopping scenarios. Through in-depth interviews with 10 participants spanning different fields and shopping contexts, this research delves into the intricate interplay between chatbots and users. The findings reveal that chatbots indeed provide interactive intelligence, improve user experiences through flexibility in time and place, and contribute to personalized interactions. Yet, specific technological attributes of chatbots, such as their capacity for emotional support and gender portrayals, can be both advantageous and limiting, contingent on the distinct needs of customers. This research underscores the importance of considering the nuanced context-specific interactions between chatbots and users, thus paving the way for a more comprehensive understanding of their multifaceted role in shaping consumer-company identification.

Inferring neuron-neuron communications from single-cell transcriptomics through NeuronChat

Neural communication networks form the fundamental basis for brain function. These communication networks are enabled by emitted ligands such as neurotransmitters, which activate receptor complexes to facilitate communication. Thus, neural communication is fundamentally dependent on the transcriptome. Here we develop NeuronChat, a method and package for the inference, visualization and analysis of neural-specific communication networks among pre-defined cell groups using single-cell expression data. We incorporate a manually curated molecular interaction database of neural signaling for both human and mouse, and benchmark NeuronChat on several published datasets to validate its ability in predicting neural connectivity. Then, we apply NeuronChat to three different neural tissue datasets to illustrate its functionalities in identifying interneural communication networks, revealing conserved or context-specific interactions across different biological contexts, and predicting communication pattern changes in diseased brains with autism spectrum disorder. Finally, we demonstrate NeuronChat can utilize spatial transcriptomics data to infer and visualize neural-specific cell-cell communication.

Caregiver Expectations of Interfacing With Voice Assistants to Support Complex Home Care: Mixed Methods Study.

BackgroundProviding care in home environments is complex, and often the pressure is on caregivers to document information and ensure care continuity. Digital information management and communication technologies may support care coordination among caregivers. However, they have yet to be adopted in this context, partly because of issues with supporting long-term disease progression and caregiver anxiety. Voice assistant (VA) technology is a promising method for interfacing with digital health information that may aid in multiple aspects of being a caregiver, thereby influencing adoption. Understanding the expectations for VAs to support caregivers is fundamental to inform the practical development of this technology.ObjectiveThis study explored caregivers’ perspectives on using VA technology to support caregiving and inform the design of future digital technologies in complex home care.MethodsThis study was part of a larger study of caregivers across North America on the design of digital health technologies to support health communication and information management in complex home care. Caregivers included parents, guardians, and hired caregivers such as personal support workers and home care nurses. Video interviews were conducted with caregivers to capture their mental models on the potential application of VAs in complex home care and were theoretically analyzed using the technology acceptance model. Interviews were followed up with Likert-scale questions exploring perspectives on other VA applications beyond participants’ initial perceptions.ResultsData were collected from 22 caregivers, and 3 themes were identified: caregivers’ perceived usefulness of VAs in supporting documentation, care coordination, and person-centered care; caregivers’ perceived ease of use in navigating information efficiently (they also had usability concerns with this interaction method); and caregivers’ concerns, excitement, expected costs, and previous experience with VAs that influenced their attitudes toward use. From the Likert-scale questions, most participants (21/22, 95%) agreed that VAs should support prompted information recording and retrieval, and all participants (22/22, 100%) agreed that they should provide reminders. They also agreed that VAs should support them in an emergency (18/22, 82%)—but only for calling emergency services—and guide caregivers through tasks (21/22, 95%). However, participants were less agreeable on VAs expressing a personality (14/22, 64%)—concerned they would manipulate caregivers’ perceptions—and listening ambiently to remind caregivers about their documentation (16/22, 73%). They were much less agreeable about VAs providing unprompted assistance on caregiving tasks (9/22, 41%).ConclusionsThe interviews and Likert-scale results point toward the potential for VAs to support family caregivers and hired caregivers by easing their information management and health communication at home. However, beyond information interaction, the potential impact of VA personality traits on caregivers’ perceptions of the care situation and the passive collection of audio data to improve user experience through context-specific interactions are critical design considerations that should be further examined.

Abstract 2130: Uncovering the spatial landscape of tumor-immune interactions using latent spaces from spatial transcriptomics

Abstract Recent advances in spatial transcriptomics (ST) enable us to measure gene expression from cancer tissues while retaining their spatial context. We present a novel bioinformatics pipeline to infer molecular changes from tumor and immune cell interactions in the tumor microenvironment (TME) from ST data. Latent space methods enable inference of biological patterns from ST without the need for spot deconvolution into cell-based spatial features. While linear latent space methods yield interpretable biological patterns, interactions between tumor and immune cells can be nonlinear. To enable comprehensive inference of the pathways in the TME, we developed novel algorithms to characterize biological patterns from ST data using linear latent space methods and further nonlinear effects from their interactions. For any given set of genes, the patternSpotter tool visualizes the spatial variation in the relative contribution of individual patterns to the aggregate expression at each location in the tumor sample. Application of this tool to latent features identified using CoGAPS non-negative matrix factorization on a Visium ST (10x Genomics) data from a lymph node with pancreatic cancer metastasis confirms its known immune cell architecture. Furthermore, we develop a patternMarker algorithm to identify sets of coexpressed genes associated with the patterns, which help us to pinpoint the underlying biological processes and cell types. Further analyzing a breast cancer sample with invasive carcinoma and multiple precursor lesions demonstrates that this approach can uncover tumor and immune regions without prior reliance on pathology annotations from H&amp;E imaging. In this case, an ensemble-based factorization of multiple dimensions enhances our resolution of intra-tumor heterogeneity and identifies distinct hormone receptor pathways in different precursor lesions with the patternMarker algorithm. Additional latent features are associated with immune cells, revealing further heterogeneity in immune infiltration between the invasive carcinoma and distinct precursor lesions. Still, the molecular interactions resulting from this infiltration induce a further non-linear alteration to transcription not captured through the inferred latent spaces. To resolve this, we develop a further interactionMarker statistic to identify regions of inter-pattern interaction and the associated genes. We apply this approach to detect additional intra-tumor heterogeneity in immune signaling from infiltration suggestive of differences in immune attack of invasive lesions. Altogether, our pipeline for latent space analysis of ST can identify the location and context-specific molecular interactions within the TME, broadly applicable to a better understanding of the key drivers of tumorigenesis and resistance to immune attack in cancer. Citation Format: Atul Deshpande, Melanie Loth, Dimitrios Sidiropoulos, QingFeng Zhu, Genevieve Stein-O'Brien, NIkhil Rao, Cedric Uytingco, Stephen Williams, Cesar Santa-Maria, Daniele M. Gilkes, Lei Zhang, Elizabeth Jaffee, Robert Anders, Ludmila Danilova, Luciane T. Kagohara, Elana J. Fertig. Uncovering the spatial landscape of tumor-immune interactions using latent spaces from spatial transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2130.

Divergent transcriptional regulation of astrocyte reactivity across disorders.

Astrocytes respond toinjury and disease in the central nervous system with reactive changes that influence the outcome of the disorder1-4. These changes include differentially expressed genes (DEGs) whose contextual diversity and regulation are poorly understood. Here we combined biological and informatic analyses, including RNA sequencing, protein detection, assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and conditional gene deletion, to predict transcriptional regulators that differentially control more than 12,000 DEGs that arepotentiallyassociated with astrocyte reactivity across diverse central nervous system disorders in mice and humans. DEGs associated with astrocyte reactivity exhibited pronounced heterogeneity across disorders. Transcriptional regulators also exhibited disorder-specific differences, but a core group of 61 transcriptional regulators was identified as common across multiple disorders in both species. We show experimentally that DEG diversity is determined by combinatorial, context-specific interactions between transcriptional regulators. Notably, the same reactivity transcriptional regulators can regulate markedly different DEG cohorts in different disorders; changes in the access of transcriptional regulators to DNA-binding motifs differ markedly across disorders; and DEG changes can crucially require multiple reactivity transcriptional regulators. We show that, by modulating reactivity, transcriptional regulators can substantially alter disorder outcome, implicating them as therapeutic targets. We provide searchable resources of disorder-related reactive astrocyte DEGs and their predicted transcriptional regulators. Our findings show that transcriptional changes associated with astrocyte reactivity are highly heterogeneous and are customized from vast numbers of potential DEGs through context-specific combinatorial transcriptional-regulator interactions.

Social-Ecological Interactions Influencing Primate Harvest: Insights From Madagascar

Globally, non-human primates face mounting threats due to unsustainable harvest by humans. There is a need to better understand the diverse drivers of primate harvest and the complex social-ecological interactions influencing harvest in shared human-primate systems. Here, we take an interdisciplinary, systems approach to assess how complex interactions among primate biological and ecological characteristics and human social factors affect primate harvest. We apply our approach through a review and synthesis of the literature on lemur harvest in Madagascar, a country with one of the highest primate species richness in the world coupled with high rates of threatened primate species and populations in decline. We identify social and ecological factors affecting primate harvest, including the characteristics of lemurs that may make them vulnerable to harvest by humans; factors describing human motivations for (or deterrents to) harvest; and political and governance factors related to power and accessibility. We then discuss social-ecological interactions that emerge from: (1) the prevalence of informal institutions (e.g., cultural taboos), (2) adoption of human predatory strategies, (3) synergies with habitat use and habitat loss, and (4) interactions among regional- and local-scale factors (multi-level interactions). Our results illustrate that social-ecological interactions influencing lemur harvest in Madagascar are complex and context-specific, while influenced by a combination of interactions between species-specific characteristics and human social factors. These context-specific interactions may be also influenced by local-level cultural practices, land use change, and effects from regional-level social complexities such as political upheaval and food insecurity. We conclude by discussing the importance of identifying and explicitly accounting for nuances in underlying social-ecological systems and putting forth ideas for future research on primate harvest in shared human-primate systems, including research on social-ecological feedbacks and the application of Routine Activities Theory.

Effect of progestin therapy on steroid receptor status and cellular proliferation in low-grade endometrial adenocarcinoma

<h3>Objectives:</h3> Low grade endometrioid endometrial cancer is a hormone sensitive disease however little is known about the role of steroid receptors in the development or treatment of disease. Our objective was to determine if steroid receptor status, or change in receptor status, predicts response to progesterone therapy in women with early stage, low grade endometrial cancer. <h3>Methods:</h3> A retrospective cohort of women was identified who underwent primary progesterone therapy for treatment of grade 1 endometrial adenocarcinoma. Steroid receptor (SR) status as well as Ki-67 expression was assessed with immunohistochemistry on pre- and post-treatment formalin fixed paraffin embedded biopsy specimens. Automated image analysis on digitized immunostained slides was performed. Estrogen Receptor (ER), Progesterone Receptor (PR), Androgen Receptor (AR) and Glucocorticoid Receptor (GR) were scored with an H-score and Ki-67 was reported as percent positive. Clinical and pathologic variables, including response to progesterone therapy were collected. SR levels and clinical characteristics were compared using paired t- and Fischer exact tests. <h3>Results:</h3> Fourteen women were included in this analysis, the majority of whom (13/14) had a progestin IUD for treatment of their carcinoma and the majority (9/14) were non-surgical candidates due to medical co-morbidities. Eight women had resolution of adenocarcinoma and six women did not have a response to therapy. Median treatment duration was 4.8 months (range 3.3 – 9.3). Responders were more likely to be younger and pre-menopausal. Two patients had mismatch repair deficient tumors, neither responded to progestin therapy. Both ER and PR declined significantly after progestin treatment (median H-score pre vs post for ER 183 vs 104, p=0.013; PR 110 vs 40, p<.001). GR levels increased (23 vs 47, p=0.003). AR demonstrated variable response. Neither pre-treatment, post-treatment, nor change in SR levels were associated with response to progestin therapy. Women with a response to therapy had lower Ki-67 levels prior to treatment compared to women who did not respond to therapy (26% vs 39%, p=0.033). <h3>Conclusions:</h3> Both ER and PR levels declined during progestin treatment in primary low grade endometrial adenocarcinoma suggesting a negative feedback loop from PR to ER signaling at the level of protein expression. Neither pre-treatment SR levels, nor change in SR receptor status predicted a response to progestin therapy which suggests more complex context-specific interactions of SRs and their ligands. Pre-treatment cellular proliferation as a biomarker for response to hormonal therapy warrants further study.

Modulators of MicroRNA Function in the Immune System.

MicroRNAs (miRNAs) play a key role in fine-tuning host immune homeostasis and responses through the negative regulation of mRNA stability and translation. The pathways regulated by miRNAs are well characterized, but the precise mechanisms that control the miRNA-mediated regulation of gene expression during immune cell-development and immune responses to invading pathogens are incompletely understood. Context-specific interactions of miRNAs with other RNA species or proteins may modulate the function of a given miRNA. Dysregulation of miRNA function is associated with various human diseases, such as cardiovascular diseases and cancers. Here, we review the potential modulators of miRNA function in the immune system, including the transcription regulators of miRNA genes, miRNA-processing enzymes, factors affecting miRNA targeting, and intercellular communication.

Locally Adapted Mimulus Ecotypes Differentially Impact Rhizosphere Bacterial and Archaeal Communities in an Environment-Dependent Manner

Plant root−microbe interactions influence plant productivity, health, and resistance to stress. Although there is evidence that plant species and even genotypes can alter soil microbial community structure, environmental conditions can potentially outweigh plant genetic effects. Here, we used a reciprocal transplant experiment to understand the contributions of the environment and the host plant to rhizosphere microbiome composition in locally adapted ecotypes of Mimulus guttatus (syn. Erythranthe guttata). Two genotypes of a coastal ecotype and two genotypes of an inland ecotype were planted at coastal and inland sites. After 3 months, we collected rhizosphere and bulk soil and assessed microbial communities by 16S rRNA gene sequencing. We found that local environment (coastal versus inland site) strongly influenced rhizosphere communities, at least in part due to distinct local microbial species pools. Host identity played a smaller role: at each site, the ecotypes exhibited remarkably similar composition of microbial communities at the class level, indicating that divergent M. guttatus ecotypes recruit phylogenetically similar rhizosphere communities, even in environments to which they are maladapted. Nevertheless, the two ecotypes significantly differed in community composition at both sites due, in part, to an exclusive set of taxa associated with each ecotype. They also differed in alpha diversity at the inland site. Although this indicates that locally adapted M. guttatus ecotypes are genetically diverged in factors shaping rhizosphere communities, our findings highlight the context-specific interactions between host identity and local environment that shape those communities. [Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Structural biology of telomeres and telomerase.

Telomeres are protein-DNA complexes that protect chromosome ends from illicit ligation and resection. Telomerase is a ribonucleoprotein enzyme that synthesizes telomeric DNA to counter telomere shortening. Human telomeres are composed of complexes between telomeric DNA and a six-protein complex known as shelterin. The shelterin proteins TRF1 and TRF2 provide the binding affinity and specificity for double-stranded telomeric DNA, while the POT1-TPP1 shelterin subcomplex coats the single-stranded telomeric G-rich overhang that is characteristic of all our chromosome ends. By capping chromosome ends, shelterin protects telomeric DNA from unwanted degradation and end-to-end fusion events. Structures of the human shelterin proteins reveal a network of constitutive and context-specific interactions. The shelterin protein-DNA structures reveal the basis for both the high affinity and DNA sequence specificity of these interactions, and explain how shelterin efficiently protects chromosome ends from genome instability. Several protein-protein interactions, many provided by the shelterin component TIN2, are critical for upholding the end-protection function of shelterin. A survey of these protein-protein interfaces within shelterin reveals a series of "domain-peptide" interactions that allow for efficient binding and adaptability towards new functions. While the modular nature of shelterin has facilitated its part-by-part structural characterization, the interdependence of subunits within telomerase has made its structural solution more challenging. However, the exploitation of several homologs in combination with recent advancements in cryo-EM capabilities has led to an exponential increase in our knowledge of the structural biology underlying telomerase function. Telomerase homologs from a wide range of eukaryotes show a typical retroviral reverse transcriptase-like protein core reinforced with elements that deliver telomerase-specific functions including recruitment to telomeres and high telomere-repeat addition processivity. In addition to providing the template for reverse transcription, the RNA component of telomerase provides a scaffold for the catalytic and accessory protein subunits, defines the limits of the telomeric repeat sequence, and plays a critical role in RNP assembly, stability, and trafficking. While a high-resolution definition of the human telomerase structure is only beginning to emerge, the quick pace of technical progress forecasts imminent breakthroughs in this area. Here, we review the structural biology surrounding telomeres and telomerase to provide a molecular description of mammalian chromosome end protection and end replication.

Eavesdropping on the conversation between immune cells and the skin epithelium.

The skin epithelium covers our body and serves as a vital interface with the external environment. Here, we review the context-specific interactions between immune cells and the epithelium that underlie barrier fitness and function. We highlight the mechanisms by which these two systems engage each other and how immune-epithelial interactions are tuned by microbial and inflammatory stimuli. Epithelial homeostasis relies on a delicate balance of immune surveillance and tolerance, breakdown of which results in disease. In addition to their canonical immune functions, resident and recruited immune cells also supply the epithelium with instructive signals to promote repair. Decoding the dialogue between immunity and the epithelium therefore has great potential for boosting barrier function or mitigating inflammatory epithelial diseases.

Context-specific interactions in literature-curated protein interaction databases

BackgroundDatabases of literature-curated protein-protein interactions (PPIs) are often used to interpret high-throughput interactome mapping studies and estimate error rates. These databases combine interactions across thousands of published studies and experimental techniques. Because the tendency for two proteins to interact depends on the local conditions, this heterogeneity of conditions means that only a subset of database PPIs are interacting during any given experiment. A typical use of these databases as gold standards in interactome mapping projects, however, assumes that PPIs included in the database are indeed interacting under the experimental conditions of the study.ResultsUsing raw data from 20 co-fractionation experiments and six published interactomes, we demonstrate that this assumption is often false, with up to 55% of purported gold standard interactions showing no evidence of interaction, on average. We identify a subset of CORUM database complexes that do show consistent evidence of interaction in co-fractionation studies, and we use this subset as gold standards to dramatically improve interactome mapping as judged by the number of predicted interactions at a given error rate.ConclusionsWe recommend using this CORUM subset as the gold standard set in future co-fractionation studies. More generally, we recommend using the subset of literature-curated PPIs that are specific to the experimental context whenever possible.

Bcl11a Marks Mammary Progenitor Cells and Promotes Early Cellular Changes Associated with TNBC by Recruiting Chd8

The transcription factor Bcl11a is an oncogene in triple negative breast cancer (TNBC), the subtype with the poorest prognostic outcome. Here we perform lineage-tracing combined with single-cell RNA-sequencing (scRNAseq) to show that Bcl11a is expressed in long lived luminal progenitor cells that expand in response to MPA/DMBA mediated oncogenesis. Moreover, we find that the deletion of Bcl11a protects mice from developing tumours in the Brca1/p53 mouse model of TNBC. scRNAseq of pre-cancerous mammary epithelial cells revealed that the deletion fully reverses an aberrant differentiation behaviour of the luminal progenitor compartment associated with Brca1 loss-of-function. Finally, we show that BCL11A interacts with and recruits the chromatin remodeller CHD8, which, we demonstrate is essential for mediating the oncogenic effects of BCL11A. In summary, BCL11A promotes early stages of TNBC via its formation of context specific protein interactions making them ideal candidate for drug development.

Poor Children in Rich Households and Vice Versa: A Blurred Picture or Hidden Realities?

An expanding evidence base suggests that children experiencing monetary and multidimensional poverty are not the same. This article breaks new ground by providing a unique mixed methods investigation of drivers of child poverty mismatch in Ethiopia and Vietnam, considering the role of measurement error and individualistic and structural factors. The analysis capitalises on large-scale secondary quantitative panel data and combines this with purposively collected primary qualitative data in both countries. It finds that factors at the household and structural level can mediate the effects of monetary poverty in terms of multidimensional poverty and vice versa, but that the size and sign of these effects are specific to place and time. The policy mix aiming to reduce all forms of child poverty need to be targeted on the basis of a multidimensional assessment of poverty and reflect the complex and context-specific interactions between determinants of child poverty.

Bioturbating invertebrates enhance decomposition and nitrogen cycling in urban stormwater ponds

Stormwater retention ponds manage runoff in developed areas, reducing flooding and erosion, and improving downstream water quality. Urban ponds also serve as habitat for aquatic organisms in an otherwise terrestrial habitat. However, the relationship between common pond species and biogeochemical function of ponds is poorly understood. Using a microcosm experiment, we evaluated the influence of two bioturbating invertebrates, Chironomus sp. and Lumbriculus variegatus, on sediment–water column nutrient exchange and benthic metabolism in stormwater ponds with divergent management histories and sediment organic matter (OM) content. Both organisms facilitated net release of reactive inorganic nitrogen to the water column, flipping the net reactive nitrogen balance of sediments relative to controls. Release of ammonium to the water column and sediment oxygen consumption were enhanced by both species, especially during colonization, but sediment uptake of nitrate was strongly enhanced by Chironomus and inhibited by L. variegatus. Comparison with direct animal respiration and excretion rates allows attribution of direct relative to indirect effects of bioturbation and bioirrigation. The influence of L. variegatus is predominantly direct, whereas Chironomus has strong direct and indirect biogeochemical effects. After 30 days, microalgal photosynthetic efficiency was reduced in all L. variegatus treatments, and context specific interactions appeared, with a reduction in OM in sediment with initially higher values, and reduced nitrate uptake in sediments with lower OM. Animal impacts on key processes ultimately influence downstream water quality and this study illustrates the important role of tolerant benthic invertebrates in mediating ecosystem functions in even the most disturbed aquatic ecosystems.

A Quantitative Systems Pharmacology Approach to Infer Pathways Involved in Complex Disease Phenotypes.

Designing effective therapeutic strategies for complex diseases such as cancer and neurodegeneration that involve tissue context-specific interactions among multiple gene products presents a major challenge for precision medicine. Safe and selective pharmacological modulation of individual molecular entities associated with a disease often fails to provide efficacy in the clinic. Thus, development of optimized therapeutic strategies for individual patients with complex diseases requires a more comprehensive, systems-level understanding of disease progression. Quantitative systems pharmacology (QSP) is an approach to drug discovery that integrates computational and experimental methods to understand the molecular pathogenesis of a disease at the systems level more completely. Described here is the chemogenomic component of QSP for the inference of biological pathways involved in the modulation of the disease phenotype. The approach involves testing sets of compounds of diverse mechanisms of action in a disease-relevant phenotypic assay, and using the mechanistic information known for the active compounds, to infer pathways and networks associated with the phenotype. The example used here is for monogenic Huntington's disease (HD), which due to the pleiotropic nature of the mutant phenotype has a complex pathogenesis. The overall approach, however, is applicable to any complex disease.

Early career development in the public sector: Lessons from a social constructionist perspective

This article explores the contribution a social constructionist paradigm can make to the study of career, through a small-scale empirical study of recent graduates employed in New Zealand’s state sector. A social constructionist lens denies the possibility of an individualised, generalised understanding of ‘career’, highlighting instead its local, contingent character as the product of social interaction. Our respondents’ collective construction of career was heavily shaped by a range of context-specific interactions and influences, such as the perception of a distinctive national identity, as well as by their young age and state sector location. It was also shaped by the research process, with us as researchers implicated in these meaning-making processes. Social constructionism shines a light on aspects of the field that are underplayed by mainstream, scientific approaches to the study of career, and therefore has valuable implications for practitioners, as well as scholars.