Structure-switching aptamers have become ubiquitous in several applications, notably in analytical devices such as biosensors, due to their ease of supporting strong signaling. Aside from their ability to bind specifically with their respective target, this class of aptamers also undergoes a conformational rearrangement upon target recognition. While several well-studied and early-developed aptamers (e.g., cocaine, ATP, and thrombin) have been found to have this structure-switching property, the vast majority do not. As a result, it is common to try to engineer aptamers into switches. This proves challenging in part because of the difficulty in obtaining structural and functional information about aptamers. In response, we review various readily available biophysical characterization tools that are capable of assessing structure switching of aptamers. In doing so, we delve into the fundamentals of these different techniques and detail how they have been utilized in characterizing structure-switching aptamers. While each of these biophysical techniques alone has utility, their real power to demonstrate the occurrence of structural change with ligand binding is when multiple techniques are used. We hope that through a deeper understanding of these techniques, researchers will be better able to acquire biophysical information about their aptamer–ligand systems and accelerate the translation of aptamers into biosensors.

This study investigates the relationship between occupational skills and wages in Thailand using the Labour Force Survey from 1985 to 2020. We quantify the contribution of changes in the skill requirement and highlight the increase in the return on the ‘brain’ and the decrease in the penalty on ‘brawn’, which helps explain the wage distribution changes across periods. We further explore the polarisation in the labour market and analyse the changes in the wage distribution by applying the decomposition method proposed by Firpo et al (2009). Our results suggest that wage dispersion increases in the top end over the first two time periods but decreases in the third time period, while it continues to decrease in the lower end of the distribution.

India’s phenomenal service-led growth in recent decades has generated debate on the role of services vis-à-vis manufacturing as the engine of growth. With the rapidly increasing importance of Information and Communication Technology (ICT) in global production systems since the 1990s, there have been claims of services having developed a growth dynamism similar to manufacturing. This article examines the role of services in India’s growth process using the concept of inter-sectoral linkages to make comparison with the role of manufacturing. Input-Output linkages and time series analysis reveal that services have been much less integrated in India’s production structure than manufacturing. They were also less important in generating indirect employment spillovers through sectoral linkages, compared with manufacturing. Service sector growth is found to be autonomously driven by final demand and therefore less dependent on its interconnections with the rest of the economy from the production side. The findings also indicate that service sector growth has stimulated manufacturing growth but not vice versa. However, the impact of services on manufacturing from the demand-side is neither sustainable nor desirable going forward. India is in urgent need of strategically developing its manufacturing sector through integrating dynamic services like ICT and internalising productivity gains. At the same time measures to address India’s inequality are critical to broaden the country’s demand base and make the growth process more sustainable and inclusive. In this sense, inequality reduction is a prerequisite for growth and should not be seen as an alternative to it.

Participants in the leadership breakout session at the Clinical Translational Science Awards (CTSA) virtual 2020 conference discussed and ranked six recommendations in terms of feasibility, impact, and priority for advancing Diversity, Equity, and Inclusion (DEI) efforts to elevate underrepresented populations to leadership positions in CTSAs and their broader institutions. A thematic analysis of chat and polling data identified challenges and opportunities to achieve DEI goals, with the three most promising recommendations as: cross-institutional Principal Investigator (P.I.) action-learning workgroups, transparent policies for recruiting and promoting underrepresented minorities (URM) leadership, and a clear succession plan to nurture and elevate URM leaders. Suggestions are made to improve DEI in CTSA leadership and allow for greater representation in the translational science field.

This analysis examines aggregate structural changes in the United States dairy industry, 1987–2017. We estimate the likelihood of operation changes in herd size, entry, or exits for each of the lower 48 states using a semiparametric Markov process model. Small- and medium-sized dairy longevity correlates with higher dairy margins and productivity improvements. An increase in consumer expenditures on dairy products is associated with smaller operation exits. Industry dynamics exhibit a persistent trend toward consolidation in most states. The exit probability for each state and all size classes has increased significantly for most states since 2002.

Este artículo analiza las trayectorias de modernización estructural para la industria de ocho países latinoamericanos (Bolivia, Brasil, Colombia, Costa Rica, Ecuador, México, Perú, Uruguay) desde 1970 hasta la fecha. Desde una perspectiva teórica estructuralista que explora las interacciones dinámicas entre el cambio estructural y el escalamiento tecnológico, se construye un índice de modernización. Los hallazgos muestran que el establecimiento de modelos económicos neoliberales en Latinoamérica a partir de los años ochenta, significó un punto de ruptura en estas trayectorias. Mientras la racionalización de procesos productivos por parte de las empresas implicó un desplazamiento del empleo en dirección de usos de baja productividad relativa, el desarrollo de industrias intensivas en capital e insertas en dinámicas globales, no impulsó la modernización estructural debido a la naturaleza de las tareas efectuadas. Los ejercicios permiten esbozar una primera tipología en términos de las carencias más apremiantes de cada caso.

Although coffee is still an important agricultural commodity in Colombia, the coffee share of GDP has significantly declined over the past 40 years. Controlling for changes in relative prices, factor endowments, and technological change, we analyze the coffee share decline in conjunction with other agricultural output by applying a Vector Error Correction model. The results indicate that while market liberalization policies contributed to the declining coffee share of GDP, the decline was partly offset by the end of coffee export quotas. Our results support policies in favor of assistance for farmers to compete in international markets.

Advanced economies undergo three transitions during their development: (1) transition from a rural to an urban economy, (2) transition from low-income growth to high-income growth, (3) transition from high fertility and mortality rates to low modern levels. The timings of these transitions are correlated in the historical development of most advanced economies. I consider a nonlinear model of endogenous long-run economic and demographic change, in which child quantity-quality substitution is driven by declining child mortality. Because the model captures the interactions between all three transitions, it is able to explain three additional empirical patterns: a declining urban-rural wage gap, a declining rural-urban family size ratio, and most surprisingly, that early urbanization slows development. This third prediction distinguishes the model from other theories of long-run growth, and I document evidence for it in cross-country data.

In this paper, I introduce a Bayesian model for detecting changepoints in a time series of overdispersed counts, such as contributions to candidates over the course of a campaign or counts of terrorist violence. To avoid having to specify the number of changepoint ex ante, this model incorporates a hierarchical Dirichlet process prior to estimate the number of changepoints as well as their location. This allows researchers to discover salient structural breaks and perform inference on the number of such breaks in a given time series. I demonstrate the usefulness of the model with applications to campaign contributions in the 2012 U.S. Republican presidential primary and incidences of global terrorism from 1970 to 2015.