Ratiometric array of conjugated polymers–fluorescent protein provides a robust mammalian cell sensor

© 2016 American Chemical Society.Supramolecular complexes of a family of positively charged conjugated polymers (CPs) and green fluorescent protein (GFP) create a fluorescence resonance energy transfer (FRET)-based ratiometric biosensor array. Selective multivalent interactions of the CPs with mammalian cell surfaces caused differential change in FRET signals, providing a fingerprint signature for each cell type. The resulting fluorescence signatures allowed the identification of 16 different cell types and discrimination between healthy, cancerous, and metastatic cells, with the same genetic background. While the CP-GFP sensor array completely differentiated between the cell types, only partial classification was achieved for the CPs alone, validating the effectiveness of the ratiometric sensor. The utility of the biosensor was further demonstrated in the detection of blinded unknown samples, where 121 of 128 samples were correctly identified. Notably, this selectivity-based sensor stratified diverse cell types in minutes, using only 2000 cells, without requiring specific biomarkers or cell labeling

Effect of Indoor Environment on Occupant Air Comfort and Productivity in Office Buildings: A Response Surface Analysis Approach

Indoor air quality is a significant factor influencing occupant comfort, health and productivity. Indoor air comfort and its relationship to occupant comfort and productivity are widely documented. Statistical correlation between the two has been highlighted in scientific literature. This paper investigates any unique correlations between non-air quality parameters (such as lux level, temperature, and noise level) and indoor air comfort and presents a study investigating the effect of indoor environmental quality on occupant air comfort and productivity. This study was conducted by collecting data on indoor environmental parameters using remote sensors and an online survey for occupant responses for twelve months. Data analysis was performed using Response Surface Analysis to present mathematical relationships between indoor environmental quality parameters and occupant air comfort. Results show that carbon dioxide up to 600 ppm, VOC up to 25% (by volume) and humidity up to 60% have a positive impact on occupant air comfort and productivity. Our research highlighted that some non-air quality parameters, such as outdoor temperature and lux levels, affect occupant air comfort. These results would enable built environment professionals to design and operate offices (subtropical desert climate) conducive to occupant comfort and productivity

Women-focused development intervention reduces delays in accessing emergency obstetric care in urban slums in Bangladesh: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Recognizing the burden of maternal mortality in urban slums, in 2007 BRAC (formally known as Bangladesh Rural Advancement Committee) has established a woman-focused development intervention, Manoshi (the Bangla abbreviation of mother, neonate and child), in urban slums of Bangladesh. The intervention emphasizes strengthening the continuum of maternal, newborn and child care through community, delivery centre (DC) and timely referral of the obstetric complications to the emergency obstetric care (EmOC) facilities. This study aimed to assess whether Manoshi DCs reduces delays in accessing EmOC.</p> <p>Methods</p> <p>This cross-sectional study was conducted during October 2008 to January 2009 in the slums of Dhaka city among 450 obstetric complicated cases referred either from DCs of Manoshi or from their home to the EmOC facilities. Trained female interviewers interviewed at their homestead with structured questionnaire. <it>Pearson's </it>chi-square test, <it>t</it>-test and Mann-Whitney test were performed.</p> <p>Results</p> <p>The median time for making the decision to seek care was significantly longer among women who were referred from home than referred from DCs (9.7 hours vs. 5.0 hours, p < 0.001). The median time to reach a facility and to receive treatment was found to be similar in both groups. Time taken to decide to seek care was significantly shorter in the case of life-threatening complications among those who were referred from DC than home (0.9 hours vs.2.3 hours, p = 0.002). Financial assistance from Manoshi significantly reduced the first delay in accessing EmOC services for life-threatening complications referred from DC (p = 0.006). Reasons for first delay include fear of medical intervention, inability to judge maternal condition, traditional beliefs and financial constraints. Role of gender was found to be an important issue in decision making. First delay was significantly higher among elderly women, multiparity, non life-threatening complications and who were not involved in income-generating activities.</p> <p>Conclusions</p> <p>Manoshi program reduces the first delay for life-threatening conditions but not non-life-threatening complications even though providing financial assistance. Programme should give more emphasis on raising awareness through couple/family-based education about maternal complications and dispel fear of clinical care to accelerate seeking EmOC.</p

Impact of land-use changes on soil properties and carbon pools in India: A meta-analysis

Not AvailableLand-use changes (LUC), primarily due to deforestation and soil disturbance, are one of the major causes of soil quality degradation and greenhouse gas emissions. Effects of LUC on soil physicochemical properties and changes in soil quality and land use management strategies that can effectively restore soil carbon and microbial biomass levels have been reported from all over the world, but the impact analysis of such practices in the Indian context is limited. In this study, over 1,786 paired datasets (for meta-analysis) on land uses (LUs) were collected from Indian literature (1990–2019) to determine the magnitude of the influence of LUC on soil carbon, microbial biomass, and other physical and chemical properties at three soil depths. Meta-analysis results showed that grasslands (36.1%) lost the most soil organic carbon (SOC) compared to native forest lands, followed by plantation lands (35.5%), cultivated lands (31.1%), barren lands (27.3%), and horticulture lands (11.5%). Our findings also revealed that, when compared to forest land, the microbial quotient was lower in other LUs. Due to the depletion of SOC stock, carbon dioxide equivalent (CO2 eq) emissions were significantly higher in all LUs than in forest land. Results also showed that due to the conversion of forest land to cultivated land, total carbon, labile carbon, non-labile carbon, microbial biomass carbon, and SOC stocks were lost by 21%, 25%, 32%, 26%, and 41.2%, respectively. Changes in soil carbon pools and properties were more pronounced in surface (0–15 cm) soils than in subsurface soils (15–30 cm and 30–45 cm). Restoration of the SOC stocks from different LUs ranged from a minimum of 2% (grasslands) to a maximum of 48% (plantation lands). Overall, this study showed that soil carbon pools decreased as LUC transitioned from native forestland to other LUs, and it is suggested that adopting crop-production systems that can reduce CO2 emissions from the intensive LUs such as the ones evaluated here could contribute to improvements in soil quality and mitigation of climate change impacts, particularly under Indian agro-climatic conditions.Not Availabl

Multi-step time series prediction intervals using neuroevolution

Multi-step time series forecasting (TSF) is a crucial element to support tactical decisions (e.g., designing production or marketing plans several months in advance). While most TSF research addresses only single-point prediction, prediction intervals (PIs) are useful to reduce uncertainty related to important decision making variables. In this paper, we explore a large set of neural network methods for multi-step TSF and that directly optimize PIs. This includes multi-step adaptations of recently proposed PI methods, such as lower--upper bound estimation (LUBET), its ensemble extension (LUBEXT), a multi-objective evolutionary algorithm LUBE (MLUBET) and a two-phase learning multi-objective evolutionary algorithm (M2LUBET). We also explore two new ensemble variants for the evolutionary approaches based on two PI coverage--width split methods (radial slices and clustering), leading to the MLUBEXT, M2LUBEXT, MLUBEXT2 and M2LUBEXT2 methods. A robust comparison was held by considering the rolling window procedure, nine time series from several real-world domains and with different characteristics, two PI quality measures (coverage error and width) and the Wilcoxon statistic. Overall, the best results were achieved by the M2LUBET neuroevolution method, which requires a reasonable computational effort for time series with a few hundreds of observations.This article is a result of the project NORTE-01- 0247-FEDER-017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). We would also like to thank the anonymous reviewers for their helpful suggestionsinfo:eu-repo/semantics/publishedVersio

Modern computing: Vision and challenges

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress

THPP target assignment reveals EchA6 as an essential fatty acid shuttle in mycobacteria

Phenotypic screens for bactericidal compounds against drug-resistant tuberculosis are beginning to yield novel inhibitors. However, reliable target identification remains challenging. Here, we show that tetrahydropyrazo[1,5-a]pyrimidine-3-carboxamide (THPP) selectively pulls down EchA6 in a stereospecific manner, instead of the previously assigned target Mycobacterium tuberculosis MmpL3. While homologous to mammalian enoyl-coenzyme A (CoA) hydratases, EchA6 is non-catalytic yet essential and binds long-chain acyl-CoAs. THPP inhibitors compete with CoA-binding, suppress mycolic acid synthesis, and are bactericidal in a mouse model of chronic tuberculosis infection. A point mutation, W133A, abrogated THPP-binding and increased both the in vitro minimum inhibitory concentration and the in vivo effective dose 99 in mice. Surprisingly, EchA6 interacts with selected enzymes of fatty acid synthase II (FAS-II) in bacterial two-hybrid assays, suggesting essentiality may be linked to feeding long-chain fatty acids to FAS-II. Finally, our data show that spontaneous resistance-conferring mutations can potentially obscure the actual target or alternative targets of small molecule inhibitors

Addressing Recruitment Challenges in the Engage-HU Trial in Young Children with Sickle Cell Disease

Background: Sickle cell disease (SCD) is a genetic disorder that causes significant medical and neurologic morbidity in children. Hydroxyurea (HU) is the primary medication used to prevent these complications. National Heart, Lung, and Blood Institute (NHLBI) guidelines recommend offering HU to children as young as 9 months of age with SCD (HbSS or HbSB0 thalassemia) using a shared decision-making approach. Although HU has proven efficacious it remains underutilized and caregivers report that they are not always actively involved in the decision to initiate this therapy. Reasons for limited HU uptake likely include lack of clinician knowledge and training and negative caregiver perceptions. Thus, we developed the Engage-HU trial as a novel approach to address HU utilization barriers. A critical consideration for this trial was that SCD primarily affects individuals of African and Hispanic/Latino descent. In these minority populations, intervention trials are sometimes terminated early because of recruitment difficulties related to mistrust of research, caregiver burden, and transportation issues. As such, the Engage-HU trial design included best-practice strategies for recruiting people of color in research. This study describes these strategies, the initial recruitment plan, preliminary recruitment outcomes and strategies, and our procedural adaptations. Study Design and Methods: Engage-HU is a randomized control trial (NCT03442114) to assess how clinicians can engage caregivers in a shared discussion that considers their values and preferences and includes evidence that supports HU. Engage-HU compares two dissemination methods for clinicians to facilitate shared decision-making with caregivers of young children with SCD: 1) the American Society of Hematology Pocket Guide, and 2) the HU Shared-Decision Making (H-SDM) Toolkit. The study aims to recruit 174 caregivers and evaluate the effectiveness of the dissemination methods on patient-centered outcomes (caregiver confidence in decision-making and perceptions of experiencing shared decision-making) as well as HU uptake and child health outcomes. Eligible children are aged 0 to 5 years, candidates for HU, and their caregiver has not made a decision about HU in the past 3 months. The trial is being conducted at 9 sites in the United States and uses a stepped-wedge design. Data will be analyzed based on the intent-to-treat principle. All participants will remain in the arm of the study to which they were randomized, regardless of whether or not they receive the assigned dissemination method. The primary endpoints are caregiver decisional uncertainty and caregiver perception of shared decision-making measured using validated tools. Data will be analyzed using a linear mixed effects regression model with a robust variance estimator and maximum likelihood estimation with observations clustered within site. The Engage-HU trial includes adaptations to increase recruitment such as tailored messaging, a relational recruitment approach, streamlined data collection, and a Stakeholder Advisory Committee. However, even with these adaptations, the first 6-months of the trial yielded lower than anticipated recruitment. Rather than terminate the trial or accept low enrollment, the research team implemented a series of recruitment strategies to address barriers including helping to improve research coordinator knowledge of the study purpose and adjusting no-show and follow-up procedures (e.g., calls to families after missed appointments and reminder calls before appointments). Site clinicians and clinic staff were provided with additional training so they could give more context about Engage-HU to caregivers and the study principal investigator led monthly "all coordinator" calls to provide support by sharing updates and experiences about successful recruitment. Implementation of these strategies resulted in triple the number of enrollments over the next 7-months compared to the previous 6-months (Table 1). Our goal in sharing this information is to provide lessons learned that can be implemented in future trials with the systematically underserved SCD population. It is also anticipated that methods described here may also inform clinical approaches to better engage caregivers of young children around critical clinical conversations, such as initiating medications like HU. Disclosures King: Magenta Therapeutics: Membership on an entity's Board of Directors or advisory committees; Bioline: Consultancy; RiverVest: Consultancy; Novimmune: Research Funding; Celgene: Consultancy; Tioma Therapuetics: Consultancy; Amphivena Therapeutics: Research Funding; WUGEN: Current equity holder in private company; Cell Works: Consultancy; Incyte: Consultancy. Smith-Whitley:Prime: Other: Education material; Celgene: Membership on an entity's Board of Directors or advisory committees; Global Blood Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Neumayr:Emmaus: Consultancy; Bayer: Consultancy; CTD Holdings: Consultancy; Pfizer: Consultancy; ApoPharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Micelle: Other: Site principal investigator; GBT: Other: Site principal investigator; PCORI: Other: site principal investigator; Novartis: Other: co-investigator; Bluebird Bio: Other: co-investigator; Sangamo Therapeutics: Other; Silarus: Other; Celgene: Other; La Jolla Pharmaceuticals: Other; Forma: Other; Imara: Other; National Heart, Lung, and Blood Institute: Other; Health Resources and Services Administration: Other; Centers for Disease Control and Prevention: Other; Seattle Children's Research: Other. Yates:Novartis: Research Funding. Thompson:Novartis: Consultancy, Honoraria, Research Funding; CRISPR/Vertex: Research Funding; BMS: Consultancy, Research Funding; Baxalta: Research Funding; Biomarin: Research Funding; bluebird bio, Inc.: Consultancy, Research Funding. </jats:sec