Effect of developmental and adult diet composition on reproductive aging in Drosophila melanogaster.

Diet significantly affects reproductive outcomes across species, yet the precise effects of macronutrient compositions beyond caloric intake on reproductive aging are understudied. Existing literature presents conflicting views on the fertility impacts of nutrient-rich versus nutrient-poor developmental diets, underscoring a notable research gap. This study addresses these gaps by examining effects of isocaloric diets with varied protein-to-carbohydrate ratios during both developmental and adult stages on reproductive aging of a large, outbred Drosophila melanogaster population (n = âˆ¼2100). Our results clearly demonstrate an age-dependent dietary impact on reproductive output, initially dominated by the developmental diet, then by a combination of developmental and adult diets in early to mid-life, and ultimately by the adult diet in later life. Importantly, we found that the effects of developmental and adult diets on reproductive output are independent, with no significant interaction. Further investigations into the mechanisms revealed that the effect of developmental diet on fecundity is regulated via ovarioles formation and vitellogenesis; while, the effect of adult diet on fecundity is mostly regulated only via vitellogenesis. These insights resolve disputes in the literature about dietary impacts on fertility and offer valuable perspectives for optimizing fertility strategies in improving public health and conservation efforts in this changing world.

Non-protein A purification platform for continuous processing of monoclonal antibody therapeutics.

Protein A capture chromatography, the core of a mAb purification platform, is known to account for more than 50% of downstream processing costs along with other limitations including lack of complete stability to alkaline cleaning solutions, relatively lower binding capacity, and ligand leaching. Researchers have explored alternatives to protein A chromatography, both chromatographic and non-chromatographic, but with limited success. In this paper, we propose a non-protein A purification platform for continuous processing of monoclonal antibodies (mAbs). The proposed platform consists of precipitation in coiled flow inverter reactor, cation exchange chromatography for capture, multimodal chromatography and a salt tolerant anion exchange membrane as polishing steps. The versatility of the proposed platform has been successfully demonstrated for three different mAbs. In all cases, acceptable process yield was obtained (70-80 %) and the product quality attributes of the final unformulated drug substance were consistent and well within accepted limits (HCP < 100 ppm, DNA < 10 ppb, % aggregate content < 1%) along with desired charge variant composition.

Author Correction: US Power Production at Risk from Water Stress in a Changing Climate.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Recent developments in chromatographic purification of biopharmaceuticals.

Over the last several decades, researchers have time and again proposed use of non-chromatographic methods for processing of biotherapeutic products. However, chromatography continues to be the backbone of downstream processing, particularly at process scale. There are many reasons for this, critical ones being the unparalleled scalability, robustness, and selectivity that process chromatography offers over its peers. It is no surprise then that process chromatography has been a topic of major developments in resin matrix, ligand chemistry, modalities, high throughput process development, process modelling, and approaches for control. In this review, we attempt to summarize major developments in the above-mentioned areas. Greater significance has been given to advancements in the last 5 years (2013-2017).

US Power Production at Risk from Water Stress in a Changing Climate.

Thermoelectric power production in the United States primarily relies on wet-cooled plants, which in turn require water below prescribed design temperatures, both for cooling and operational efficiency. Thus, power production in US remains particularly vulnerable to water scarcity and rising stream temperatures under climate change and variability. Previous studies on the climate-water-energy nexus have primarily focused on mid- to end-century horizons and have not considered the full range of uncertainty in climate projections. Technology managers and energy policy makers are increasingly interested in the decadal time scales to understand adaptation challenges and investment strategies. Here we develop a new approach that relies on a novel multivariate water stress index, which considers the joint probability of warmer and scarcer water, and computes uncertainties arising from climate model imperfections and intrinsic variability. Our assessments over contiguous US suggest consistent increase in water stress for power production with about 27% of the production severely impacted by 2030s.

Integrated Chromatographic Platform for Simultaneous Separation of Charge Variants and Aggregates from Monoclonal Antibody Therapeutic Products.

Achieving consistent product quality of a biotherapeutic is a major target for any biopharmaceutical manufacturer, even more for a biosimilar producer as comparability with the innovator product is a regulatory expectation. The complexity of biotherapeutic products and their tedious manufacturing processes, however, make this a non-trivial exercise. The primary motivation of this work is to develop an integrated chromatographic platform for purification of monoclonal antibody (mAb) therapeutics that can deliver the desired separation of both charge variants and aggregates, in addition to the process related impurities like host cell proteins (HCP) and host cell DNA. To achieve the same, an integrated two-stage chromatographic process platform consisting of cation exchange chromatography and multimodal chromatography is being proposed. The versatility of the proposed platform has been successfully demonstrated for three different mAbs. It have been shown that in each case charge variant separation is achieved with the required clearance of aggregates (<1%), HCP (<10 ppm), and DNA (<5 ppb). Moreover, the proposed platform is conducive to use for development of a continuous process and offers smaller process time, lower buffer utilization, and decreased operational costs when compared to the conventional purification platforms.

Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network.

The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general.