Managing the Spatial Externalities of Renewable Energy Deployment: Uniform vs. Differentiated Regulation

With the expansion of renewable energy sources (RES) in countries all over the world, policy design to address the negative impacts of RES plants on their local and regional environment gains in importance. We analyse whether policy design should be spatially-differentiated or uniform when negative RES environmental externalities are spatially heterogeneous and display interregional cumulative effects. In a theoretical model of the RES electricity generation sector, we compare the welfare differential between both regulatory designs and analyse how it is affected by cumulative environmental effects. While we confirm that the welfare costs of attaining a RES deployment target are lower under a spatially-differentiated than a spatiallyuniform regulation, we find that the welfare costs are contingent on the presence of cumulative environmental effects. This depends on the heterogeneity of region-specific generation cost parameters and social cost parameters of RES electricity generation. If heterogeneity is more (less) pronounced in regional generation cost parameters than in regional social cost parameters, positive (negative) cumulative effects decrease the welfare costs of a uniform instrument

The Types, Roles, and Practices of Documentation in Data Analytics Open Source Software Libraries: A Collaborative Ethnography of Documentation Work

Computational research and data analytics increasingly relies on complex ecosystems of open source software (OSS) "libraries" -- curated collections of reusable code that programmers import to perform a specific task. Software documentation for these libraries is crucial in helping programmers/analysts know what libraries are available and how to use them. Yet documentation for open source software libraries is widely considered low-quality. This article is a collaboration between CSCW researchers and contributors to data analytics OSS libraries, based on ethnographic fieldwork and qualitative interviews. We examine several issues around the formats, practices, and challenges around documentation in these largely volunteer-based projects. There are many different kinds and formats of documentation that exist around such libraries, which play a variety of educational, promotional, and organizational roles. The work behind documentation is similarly multifaceted, including writing, reviewing, maintaining, and organizing documentation. Different aspects of documentation work require contributors to have different sets of skills and overcome various social and technical barriers. Finally, most of our interviewees do not report high levels of intrinsic enjoyment for doing documentation work (compared to writing code). Their motivation is affected by personal and project-specific factors, such as the perceived level of credit for doing documentation work versus more "technical" tasks like adding new features or fixing bugs. In studying documentation work for data analytics OSS libraries, we gain a new window into the changing practices of data-intensive research, as well as help practitioners better understand how to support this often invisible and infrastructural work in their projects

A prognostic baseline blood biomarker and tumor growth kinetics integrated model in paclitaxel/platinum treated advanced non-small cell lung cancer patients

Paclitaxel/platinum chemotherapy, the backbone of standard first-line treatment of advanced non-small cell lung cancer (NSCLC), exhibits high interpatient variability in treatment response and high toxicity burden. Baseline blood biomarker concentrations and tumor size (sum of diameters) at week 8 relative to baseline (RS8) are widely investigated prognostic factors. However, joint analysis of data on demographic/clinical characteristics, blood biomarker levels, and chemotherapy exposure-driven early tumor response for improved prediction of overall survival (OS) is clinically not established. We developed a Weibull time-to-event model to predict OS, leveraging data from 365 patients receiving paclitaxel/platinum combination chemotherapy once every three weeks for ≤six cycles. A developed tumor growth inhibition model, combining linear tumor growth and first-order paclitaxel area under the concentration-time curve-induced tumor decay, was used to derive individual RS8. The median model-derived RS8 in all patients was a 20.0% tumor size reduction (range from −78% to +15%). Whereas baseline carcinoembryonic antigen, cytokeratin fragments, and thyroid stimulating hormone levels were not significantly associated with OS in a subset of 221 patients, and lactate dehydrogenase, interleukin-6 and neutrophil-to-lymphocyte ratio levels were significant only in univariate analyses (p value < 0.05); C-reactive protein (CRP) in combination with RS8 most significantly affected OS (p value < 0.01). Compared to the median population OS of 11.3 months, OS was 128% longer at the 5th percentile levels of both covariates and 60% shorter at their 95th percentiles levels. The combined paclitaxel exposure-driven RS8 and baseline blood CRP concentrations enables early individual prognostic predictions for different paclitaxel dosing regimens, forming the basis for treatment decision and optimizing paclitaxel/platinum-based advanced NSCLC chemotherapy

C-Reactive Protein as an Early Predictor of Efficacy in Advanced Non-Small-Cell Lung Cancer Patients: A Tumor Dynamics-Biomarker Modeling Framework

In oncology, longitudinal biomarkers reflecting the patient’s status and disease evolution can offer reliable predictions of the patient’s response to treatment and prognosis. By leveraging clinical data in patients with advanced non-small-cell lung cancer receiving first-line chemotherapy, we aimed to develop a framework combining anticancer drug exposure, tumor dynamics (RECIST criteria), and C-reactive protein (CRP) concentrations, using nonlinear mixed-effects models, to evaluate and quantify by means of parametric time-to-event models the significance of early longitudinal predictors of progression-free survival (PFS) and overall survival (OS). Tumor dynamics was characterized by a tumor size (TS) model accounting for anticancer drug exposure and development of drug resistance. CRP concentrations over time were characterized by a turnover model. An x-fold change in TS from baseline linearly affected CRP production. CRP concentration at treatment cycle 3 (day 42) and the difference between CRP concentration at treatment cycles 3 and 2 were the strongest predictors of PFS and OS. Measuring longitudinal CRP allows for the monitoring of inflammatory levels and, along with its reduction across treatment cycles, presents a promising prognostic marker. This framework could be applied to other treatment modalities such as immunotherapies or targeted therapies allowing the timely identification of patients at risk of early progression and/or short survival to spare them unnecessary toxicities and provide alternative treatment decisions

Managing spatial sustainability trade-offs: The case of wind power

The deployment of onshore wind power involves spatial sustainability trade-offs, e.g., between the minimization of energy system costs, the mitigation of impacts on humans and biodiversity, and equity concerns. We analyze challenges arising for decision-making if wind power generation capacity has to be allocated spatially in the presence of such trade-offs. The analysis is based on a game developed for and played by stakeholders in Germany. The results of the game illustrate that there is no unanimously agreed ranking of sustainability criteria among the participating stakeholders. They disagreed not only on the weights of different criteria but also their definition and measurement. Group discussions further revealed that equity concerns mattered for spatial allocation. Yet, stakeholders used quite different concepts of equity. The results support the importance of transparent, multi-level and participatory approaches to take decisions on the spatial allocation of wind power generation capacity

AMPK negatively regulates tensin-dependent integrin activity

Tight regulation of integrin activity is paramount for dynamic cellular functions such as cell matrix adhesion and mechanotransduction. Integrin activation is achieved through intracellular interactions at the integrin cytoplasmic tails and through integrin-ligand binding. In this study, we identify the metabolic sensor AMP-activated protein kinase (AMPK) as a beta 1-integrin inhibitor in fibroblasts. Loss of AMPK promotes beta 1-integrin activity, the formation of centrally located active beta 1-integrin- and tensin-rich mature fibrillar adhesions, and cell spreading. Moreover, in the absence of AMPK, cells generate more mechanical stress and increase fibronectin fibrillogenesis. Mechanistically, we show that AMPK negatively regulates the expression of the integrin-binding proteins tensin1 and tensin3. Transient expression of tensins increases beta 1-integrin activity, whereas tensin silencing reduces integrin activity in fibroblasts lacking AMPK. Accordingly, tensin silencing in AMPK-depleted fibroblasts impedes enhanced cell spreading, traction stress, and fibronectin fiber formation. Collectively, we show that the loss of AMPK up-regulates tensins, which bind beta 1-integrins, supporting their activity and promoting fibrillar adhesion formation and integrin-dependent processes.Peer reviewe

Absence seizures in C3H/HeJ and knockout mice caused by mutation of the AMPA receptor subunit Gria4

Absence epilepsy, characterized by spike–wave discharges (SWD) in the electroencephalogram, arises from aberrations within the circuitry of the cerebral cortex and thalamus that regulates awareness. The inbred mouse strain C3H/HeJ is prone to absence seizures, with a major susceptibility locus, spkw1, accounting for most of the phenotype. Here we find that spkw1 is associated with a hypomorphic retroviral-like insertion mutation in the Gria4 gene, encoding one of the four amino-3-hydroxy-5-methyl-4isoxazolepropionic acid (AMPA) receptor subunits in the brain. Consistent with this, Gria4 knockout mice also have frequent SWD and do not complement spkw1. In contrast, null mutants for the related gene Gria3 do not have SWD, and Gria3 loss actually lowers SWD of spkw1 homozygotes. Gria3 and Gria4 encode the predominant AMPA receptor subunits in the reticular thalamus, which is thought to play a central role in seizure genesis by inhibiting thalamic relay cells and promoting rebound burst firing responses. In Gria4 mutants, synaptic excitation of inhibitory reticular thalamic neurons is enhanced, with increased duration of synaptic responses—consistent with what might be expected from reduction of the kinetically faster subunit of AMPA receptors encoded by Gria4. These results demonstrate for the first time an essential role for Gria4 in the brain, and suggest that abnormal AMPA receptor-dependent synaptic activity can be involved in the network hypersynchrony that underlies absence seizures

A computationally designed antigen eliciting broad humoral responses against SARS-CoV-2 and related sarbecoviruses

The threat of spillovers of coronaviruses associated with the severe acute respiratory syndrome (SARS) from animals to humans necessitates vaccines that offer broader protection from sarbecoviruses. By leveraging a viral-genome-informed computational method for selecting immune-optimized and structurally engineered antigens, here we show that a single antigen based on the receptor binding domain of the spike protein of sarbecoviruses elicits broad humoral responses against SARS-CoV-1, SARS-CoV-2, WIV16 and RaTG13 in mice, rabbits and guinea pigs. When administered as a DNA immunogen or by a vector based on a modified vaccinia virus Ankara, the optimized antigen induced vaccine protection from the Delta variant of SARS-CoV-2 in mice genetically engineered to express angiotensin-converting enzyme 2 and primed by a viral-vector vaccine (AZD1222) against SARS-CoV-2. A vaccine formulation incorporating mRNA coding for the optimized antigen further validated its broad immunogenicity. Vaccines that elicit broad immune responses across subgroups of coronaviruses may counteract the threat of zoonotic spillovers of betacoronaviruses