Mass Spectrometry-Based Proteomics for Translational Research: A Technical Overview

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease

Gender and sociocultural factors in animal source foods (ASFs) access and consumption in lower-income households in urban informal settings of Nairobi, Kenya

BACKGROUND: Gender shapes household decision-making and access for nutritious diets, including animal source foods (ASFs) that impact on child health and nutrition status. However, research shows that the poorest households in the urban informal settlements of Nairobi have low ASFs consumption. This study was conducted to explore further from a qualitative perspective the gender, sociocultural factors affecting household ASF consumption this study. METHODS: To explore further on the topic of study, an exploratory qualitative study was carried out to establish the factors that influence access, allocation and consumption of animal source foods (ASFs) by households in urban informal settings of Nairobi. Nineteen focus group discussions with men and women were conducted to enable in-depth exploration of ASFs consumption. RESULTS: Gender influences decision-making of household ASFs dietary intake. Gendered power dynamics prevail with men as breadwinners and household heads often determining the food access and consumption of ASFs. Women are increasingly accessing short-term waged-based incomes in urban informal settings and now play a role in food and nutrition security for their households. This enforces the idea that women's decision-making autonomy is an important aspect of women empowerment, as it relates to women's dietary diversity and subsequently, better household nutritional status. As evidenced in this study, if a woman has bargaining power based on accessing incomes to support their household food needs, she will not jeopardize food security. The mobile digital money platform was key in enabling access to resources to access food. Use of trust to access food on credit and purchasing smaller packaged quantities of food were also enablers to access of food/ASFs

Plasmonic nanoparticles assemblies templated by helical bacteria and resulting optical activity

Plasmonic nanoparticles (NPs) adsorbing onto helical bacteria can lead to formation of NP helicoids with micron scale pitch. Associated chiroptical effects can be utilized as bioanalytical tool for bacterial detection and better understanding of the spectral behavior of helical self‐assembled structures with different scales. Here, we report that enantiomerically pure helices with micron scale of chirality can be assembled on Campylobacter jejuni, a helical bacterium known for severe stomach infections. These organisms have right‐handed helical shapes with a pitch of 1–2 microns and can serve as versatile templates for a variety of NPs. The bacteria itself shows no observable rotatory activity in the visible, red, and near‐IR ranges of electromagnetic spectrum. The bacterial dispersion acquires chiroptical activity at 500–750 nm upon plasmonic functionalization with Au NPs. Finite‐difference time‐domain simulations confirmed the attribution of the chiroptical activity to the helical assembly of gold nanoparticles. The position of the circular dichroism peaks observed for these chiral structures overlaps with those obtained before for Au NPs and their constructs with molecular and nanoscale chirality. This work provides an experimental and computational pathway to utilize chiroplasmonic particles assembled on bacteria for bioanalytical purposes.Gold nanoparticles assemble onto the surface of helical bacterium, Campylobacter jejuni, producing right‐handed helices with a pitch of 1–2 microns. The bacterial dispersion acquires chiroptical activity at 500–750 nm that matches the calculated chiroplasmonic spectra. This study provides a pathway to utilize chiroplasmonic particles for monitoring shape dynamics of bacteria and identification of helical bacteria in complex microbiomes.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155927/1/Supporting_information_Chirality_Manuscript_2020.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155927/2/chir23225_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155927/3/chir23225.pd

A Process for Co-Designing Educational Technology Systems for Refugee Children

There is a growing interest in the potential for technology to facilitate emergency education of refugee children. However, designing in this space requires knowledge of the displaced population and the contextual dynamics surrounding it. Design should therefore be informed by both existing research across relevant disciplines, and from the practical experience of those who are on the ground facing the problem in real life. This paper describes a process for designing appropriate technology for these settings. The process draws on literature from emergency education, student engagement and motivation, educational technology, and participatory design. We emphasise a thorough understanding of the problem definition, the nature of the emergency, and of socio-cultural aspects that can inform the design process. We describe how this process was implemented leading to the design of a digital learning space for children living in a refugee camp in Greece. This drew on involving different groups of participants such as social-workers, parents, and children

How to design a complex behaviour change intervention: experiences from a nutrition-sensitive agriculture trial in rural India

Many public health interventions aim to promote healthful behaviours, with varying degrees of success. With a lack of existing empirical evidence on the optimal number or combination of behaviours to promote to achieve a given health outcome, a key challenge in intervention design lies in deciding what behaviours to prioritise, and how best to promote them. We describe how key behaviours were selected and promoted within a multisectoral nutrition-sensitive agriculture intervention that aimed to address maternal and child undernutrition in rural India. First, we formulated a Theory of Change, which outlined our hypothesised impact pathways. To do this, we used the following inputs: existing conceptual frameworks, published empirical evidence, a feasibility study, formative research and the intervention team’s local knowledge. Then, we selected specific behaviours to address within each impact pathway, based on our formative research, behaviour change models, local knowledge and community feedback. As the intervention progressed, we mapped each of the behaviours against our impact pathways and the transtheoretical model of behaviour change, to monitor the balance of behaviours across pathways and along stages of behaviour change. By collectively agreeing on definitions of complex concepts and hypothesised impact pathways, implementing partners were able to communicate clearly between each other and with intervention participants. Our intervention was iteratively informed by continuous review, by monitoring implementation against targets and by integrating community feedback. Impact and process evaluations will reveal whether these approaches are effective for improving maternal and child nutrition, and what the effects are on each hypothesised impact pathway

Dynamic modeling of mean-reverting spreads for statistical arbitrage

Statistical arbitrage strategies, such as pairs trading and its generalizations, rely on the construction of mean-reverting spreads enjoying a certain degree of predictability. Gaussian linear state-space processes have recently been proposed as a model for such spreads under the assumption that the observed process is a noisy realization of some hidden states. Real-time estimation of the unobserved spread process can reveal temporary market inefficiencies which can then be exploited to generate excess returns. Building on previous work, we embrace the state-space framework for modeling spread processes and extend this methodology along three different directions. First, we introduce time-dependency in the model parameters, which allows for quick adaptation to changes in the data generating process. Second, we provide an on-line estimation algorithm that can be constantly run in real-time. Being computationally fast, the algorithm is particularly suitable for building aggressive trading strategies based on high-frequency data and may be used as a monitoring device for mean-reversion. Finally, our framework naturally provides informative uncertainty measures of all the estimated parameters. Experimental results based on Monte Carlo simulations and historical equity data are discussed, including a co-integration relationship involving two exchange-traded funds.Comment: 34 pages, 6 figures. Submitte

Assessment of climate change and vulnerability in Indian state of Telangana for better agricultural planning

Climate variability and change pose ever-growing challenges in the semiarid tropics, where majority of the population depend on climate-dependent activities such as agriculture. This has rendered these countries more vulnerable to climate change–induced variability. In spite of the uncertainties about anticipated magnitude of climate change on regional scale, an assessment of the possible changes in key climatic elements to identify most vulnerable locations becomes important for formulating adaptation strategies. This study compiles the existing knowledge about observed climate and projections of future change in Telangana state of India. The agriculture in this semiarid state has to adapt to changes in mean climate variables to increased variability with greater risk of extreme weather events, such as prolonged dry spells. Based on climatic vulnerability assessment, we found that the number of vulnerable mandals (currently 28%) will be increased to 45% during early century and to 59% by mid-century. As per the climate exposure index scores, Jogulamba-Gadwal district was found to be most sensitive. Overall, vulnerability index scores indicated that Adilabad, Nagarkurnool, Nalgonda, Peddapalli, Suryapet, Wanaparthy, and Yadadri are extremely vulnerable districts in the state. The ranking of vulnerable mandals in each district envisages the need for a holistic approach for each mandal or a group of mandals to reduce their sensitivity though implementation of site-specific adaptation strategies to minimize climate-related shocks not only in agriculture but also in other sectors