Health behavior change models for HIV prevention and AIDS care: practical recommendations for a multi-level approach

Despite increasing recent emphasis on the social and structural determinants of HIV-related behavior, empirical research and interventions lag behind, partly because of the complexity of social-structural approaches. This article provides a comprehensive and practical review of the diverse literature on multi-level approaches to HIV-related behavior change in the interest of contributing to the ongoing shift to more holistic theory, research, and practice. It has the following specific aims: (1) to provide a comprehensive list of relevant variables/factors related to behavior change at all points on the individual-structural spectrum, (2) to map out and compare the characteristics of important recent multi-level models, (3) to reflect on the challenges of operating with such complex theoretical tools, and (4) to identify next steps and make actionable recommendations. Using a multi-level approach implies incorporating increasing numbers of variables and increasingly context-specific mechanisms, overall producing greater intricacies. We conclude with recommendations on how best to respond to this complexity, which include: using formative research and interdisciplinary collaboration to select the most appropriate levels and variables in a given context; measuring social and institutional variables at the appropriate level to ensure meaningful assessments of multiple levels are made; and conceptualizing intervention and research with reference to theoretical models and mechanisms to facilitate transferability, sustainability, and scalability

Land Conservation in the Northeastern United States: An Assessment of Historic Trends and Current Conditions

This article discusses the evolution of land conservation efforts and outcomes in the Northeast, examine major drivers of landscape change, and review key conservation tools that have been used to protect public values at the local and landscape levels. We then assess the current status of land conservation, and draw lessons for other regions facing conservation challenges across mixed ownership landscapes under varying development and land-use pressures. Finally, we explore new and emerging trends in the factors driving land development and conservation activities in an effort to assess the challenges that lie ahead

AnchorWave: Sensitive alignment of genomes with high sequence diversity, extensive structural polymorphism, and whole-genome duplication

Millions of species are currently being sequenced, and their genomes are being compared. Many of them have more complex genomes than model systems and raise novel challenges for genome alignment. Widely used local alignment strategies often produce limited or incongruous results when applied to genomes with dispersed repeats, long indels, and highly diverse sequences. Moreover, alignment using many-to-many or reciprocal best hit approaches conflicts with well-studied patterns between species with different rounds of whole-genome duplication. Here, we introduce Anchored Wavefront alignment (AnchorWave), which performs whole-genome duplication–informed collinear anchor identification between genomes and performs base pair–resolved global alignment for collinear blocks using a two-piece affine gap cost strategy. This strategy enables AnchorWave to precisely identify multikilobase indels generated by transposable element (TE) presence/absence variants (PAVs). When aligning two maize genomes, AnchorWave successfully recalled 87% of previously reported TE PAVs. By contrast, other genome alignment tools showed low power for TE PAV recall. AnchorWave precisely aligns up to three times more of the genome as position matches or indels than the closest competitive approach when comparing diverse genomes. Moreover, AnchorWave recalls transcription factor–binding sites at a rate of 1.05- to 74.85-fold higher than other tools with significantly lower false-positive alignments. AnchorWave complements available genome alignment tools by showing obvious improvement when applied to genomes with dispersed repeats, active TEs, high sequence diversity, and whole-genome duplication variation.This project is supported by the United States Department of Agriculture Agricultural Research Service, NSF No. 1822330, NSF No. 1854828, the European Union's Horizon 2020 Framework Programme under the DeepHealth project [825111], the European Union Regional Development Fund within the framework of The European Regional Development Fund Operational Program of Catalonia 2014 to 2020 with a grant of 50% of total cost eligible under the DRAC project [001-P-001723], and National Natural Science Foundation of China No. 31900486. M.C.S. was supported by NSF Postdoctoral Research Fellowship in Biology No. 1907343. M.M. was partially supported by the Spanish Ministry of Economy, Industry, and Competitiveness under Ramón y Cajal (RYC) fellowship number RYC-2016-21104.Peer ReviewedPostprint (published version

Using research feedback loops to implement a disability case study with Aboriginal and Torres Strait Islander communities and service providers in regional and remote Australia

While there is a well-developed body of literature in the health field that describes processes to implement research, there is a dearth of similar literature in the disability field of research involving complex conditions. Moreover, the development of meaningful and sustainable knowledge translation is now a standard component of the research process. Knowledge users, including community members, service providers, and policy makers now call for evidence-led meaningful activities to occur rapidly. In response, this article presents a case study that explores the needs and priorities of Aboriginal and Torres Strait Islander women in Australia who have experienced a traumatic brain injury due to family violence. Drawing on the work of Indigenous disability scholars such as Gilroy, Avery and others, this article describes the practical and conceptual methods used to transform research to respond to the realities of community concerns and priorities, cultural considerations and complex safety factors. This article offers a unique perspective on how to increase research relevance to knowledge users and enhance the quality of data collection while also overcoming prolonged delays of knowledge translation that can result from the research-production process

Computational modelling of cell chain migration reveals mechanisms that sustain follow-the-leader behaviour

Follow-the-leader chain migration is a striking cell migratory behaviour observed during vertebrate development, adult neurogenesis and cancer metastasis. Although cell–cell contact and extracellular matrix (ECM) cues have been proposed to promote this phenomenon, mechanisms that underlie chain migration persistence remain unclear. Here, we developed a quantitative agent-based modelling framework to test mechanistic hypotheses of chain migration persistence. We defined chain migration and its persistence based on evidence from the highly migratory neural crest model system, where cells within a chain extend and retract filopodia in short-lived cell contacts and move together as a collective. In our agent-based simulations, we began with a set of agents arranged as a chain and systematically probed the influence of model parameters to identify factors critical to the maintenance of the chain migration pattern. We discovered that chain migration persistence requires a high degree of directional bias in both lead and follower cells towards the target. Chain migration persistence was also promoted when lead cells maintained cell contact with followers, but not vice-versa. Finally, providing a path of least resistance in the ECM was not sufficient alone to drive chain persistence. Our results indicate that chain migration persistence depends on the interplay of directional cell movement and biased cell–cell contact

A bacterial quorum-sensing precursor induces mortality in the marine coccolithophore, Emiliania huxleyi

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Frontiers in Microbiology 7 (2016): 59, doi:10.3389/fmicb.2016.00059.Interactions between phytoplankton and bacteria play a central role in mediating biogeochemical cycling and food web structure in the ocean. However, deciphering the chemical drivers of these interspecies interactions remains challenging. Here, we report the isolation of 2-heptyl-4-quinolone (HHQ), released by Pseudoalteromonas piscicida, a marine gamma-proteobacteria previously reported to induce phytoplankton mortality through a hitherto unknown algicidal mechanism. HHQ functions as both an antibiotic and a bacterial signaling molecule in cell–cell communication in clinical infection models. Co-culture of the bloom-forming coccolithophore, Emiliania huxleyi with both live P. piscicida and cell-free filtrates caused a significant decrease in algal growth. Investigations of the P. piscicida exometabolome revealed HHQ, at nanomolar concentrations, induced mortality in three strains of E. huxleyi. Mortality of E. huxleyi in response to HHQ occurred slowly, implying static growth rather than a singular loss event (e.g., rapid cell lysis). In contrast, the marine chlorophyte, Dunaliella tertiolecta and diatom, Phaeodactylum tricornutum were unaffected by HHQ exposures. These results suggest that HHQ mediates the type of inter-domain interactions that cause shifts in phytoplankton population dynamics. These chemically mediated interactions, and other like it, ultimately influence large-scale oceanographic processes.This research was support through funding from the Gordon and Betty Moore Foundation through Grant GBMF3301 to MJ and TM; NIH grant from the National Institute of Allergy and Infectious Disease (NIAID – 1R21Al119311-01) to TM and KW; the National Science Foundation (OCE – 1313747) and US National Institute of Environmental Health Science (P01-ES021921) through the Oceans and Human Health Program to BM. Additional financial support was provided to TM from the Flatley Discovery Lab

Systems-level analysis of age-related macular degeneration reveals global biomarkers and phenotype-specific functional networks

Abstract Background Age-related macular degeneration (AMD) is a leading cause of blindness that affects the central region of the retinal pigmented epithelium (RPE), choroid, and neural retina. Initially characterized by an accumulation of sub-RPE deposits, AMD leads to progressive retinal degeneration, and in advanced cases, irreversible vision loss. Although genetic analysis, animal models, and cell culture systems have yielded important insights into AMD, the molecular pathways underlying AMD's onset and progression remain poorly delineated. We sought to better understand the molecular underpinnings of this devastating disease by performing the first comparative transcriptome analysis of AMD and normal human donor eyes. Methods RPE-choroid and retina tissue samples were obtained from a common cohort of 31 normal, 26 AMD, and 11 potential pre-AMD human donor eyes. Transcriptome profiles were generated for macular and extramacular regions, and statistical and bioinformatic methods were employed to identify disease-associated gene signatures and functionally enriched protein association networks. Selected genes of high significance were validated using an independent donor cohort. Results We identified over 50 annotated genes enriched in cell-mediated immune responses that are globally over-expressed in RPE-choroid AMD phenotypes. Using a machine learning model and a second donor cohort, we show that the top 20 global genes are predictive of AMD clinical diagnosis. We also discovered functionally enriched gene sets in the RPE-choroid that delineate the advanced AMD phenotypes, neovascular AMD and geographic atrophy. Moreover, we identified a graded increase of transcript levels in the retina related to wound response, complement cascade, and neurogenesis that strongly correlates with decreased levels of phototransduction transcripts and increased AMD severity. Based on our findings, we assembled protein-protein interactomes that highlight functional networks likely to be involved in AMD pathogenesis. Conclusions We discovered new global biomarkers and gene expression signatures of AMD. These results are consistent with a model whereby cell-based inflammatory responses represent a central feature of AMD etiology, and depending on genetics, environment, or stochastic factors, may give rise to the advanced AMD phenotypes characterized by angiogenesis and/or cell death. Genes regulating these immunological activities, along with numerous other genes identified here, represent promising new targets for AMD-directed therapeutics and diagnostics. Please see related commentary: http://www.biomedcentral.com/1741-7015/10/21/abstrac

Technology-assisted stroke rehabilitation in Mexico: a pilot randomized trial comparing traditional therapy to circuit training in a Robot/technology-assisted therapy gym

Background Stroke rehabilitation in low- and middle-income countries, such as Mexico, is often hampered by lack of clinical resources and funding. To provide a cost-effective solution for comprehensive post-stroke rehabilitation that can alleviate the need for one-on-one physical or occupational therapy, in lower and upper extremities, we proposed and implemented a technology-assisted rehabilitation gymnasium in Chihuahua, Mexico. The Gymnasium for Robotic Rehabilitation (Robot Gym) consisted of low- and high-tech systems for upper and lower limb rehabilitation. Our hypothesis is that the Robot Gym can provide a cost- and labor-efficient alternative for post-stroke rehabilitation, while being more or as effective as traditional physical and occupational therapy approaches. Methods A typical group of stroke patients was randomly allocated to an intervention (n = 10) or a control group (n = 10). The intervention group received rehabilitation using the devices in the Robot Gym, whereas the control group (n = 10) received time-matched standard care. All of the study subjects were subjected to 24 two-hour therapy sessions over a period of 6 to 8 weeks. Several clinical assessments tests for upper and lower extremities were used to evaluate motor function pre- and post-intervention. A cost analysis was done to compare the cost effectiveness for both therapies. Results No significant differences were observed when comparing the results of the pre-intervention Mini-mental, Brunnstrom Test, and Geriatric Depression Scale Test, showing that both groups were functionally similar prior to the intervention. Although, both training groups were functionally equivalent, they had a significant age difference. The results of all of the upper extremity tests showed an improvement in function in both groups with no statistically significant differences between the groups. The Fugl-Meyer and the 10 Meters Walk lower extremity tests showed greater improvement in the intervention group compared to the control group. On the Time Up and Go Test, no statistically significant differences were observed pre- and post-intervention when comparing the control and the intervention groups. For the 6 Minute Walk Test, both groups presented a statistically significant difference pre- and post-intervention, showing progress in their performance. The robot gym therapy was more cost-effective than the traditional one-to-one therapy used during this study in that it enabled therapist to train up to 1.5 to 6 times more patients for the approximately same cost in the long term. Conclusions The results of this study showed that the patients that received therapy using the Robot Gym had enhanced functionality in the upper extremity tests similar to patients in the control group. In the lower extremity tests, the intervention patients showed more improvement than those subjected to traditional therapy. These results support that the Robot Gym can be as effective as traditional therapy for stroke patients, presenting a more cost- and labor-efficient option for countries with scarce clinical resources and funding. Trial registration ISRCTN98578807