The impact of supply chain-related factors on the environmental performance of manufacturing firms in Turkey

This paper investigates the impact of supply chain-related factors on the adoption of proactive environmental strategies, and the impact of such strategies on environmental investments and environmental performance. Data were collected from 96 Turkish manufacturers using an online questionnaire. The model was tested with PLS, a structural equation modelling method. The results show that a proactive environmental strategy leads to higher environmental investments which in turn lead to higher environmental performance. The results also show that two supply chain-related factors, organizational commitment and collaboration with suppliers, positively impact proactivity, whereas customer pressure does not have any significant direct impact on proactivity but it does positively impact environmental investments

Submission of structural biology data for review purposes.

The editors discuss the submission of structural biology data

Spain's Budget Neglects Research

Letter.-- Carlos Fenollosa et al.Peer Reviewe

The Role of Compensatory Beliefs in Rationalizing Environmentally Detrimental Behaviors

Compensatory green beliefs (CGBs) reflect the idea that a pro-environmental behavior (e.g., recycling) can off-set the negative effects of an environmentally detrimental behavior (e.g., driving). It is thought that CGBs might help explain why people act in ways that appear to contradict their pro-environmental intentions, and inconsistently engage in pro-environmental behaviors. The present study sought to investigate the nature and use of CGBs. A series of interviews suggested that participants endorsed CGBs to: (a) reduce feelings of guilt with respect to (the assumed or actual) negative environmental impact of their actions, and (b) to defend their green credentials in social situations. Participants also justified detrimental behaviors on the basis of higher loyalties (e.g., family’s needs), or the perceived difficulty of performing more pro-environmental actions. In addition to shedding light on how, when, and why people might hold and use CGBs, the research also provides new insight into how CGBs should be assessed

Site-specific perturbations of alpha-synuclein fibril structure by the Parkinson's disease associated mutations A53T and E46K.

PMCID: PMC3591419This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Parkinson's disease (PD) is pathologically characterized by the presence of Lewy bodies (LBs) in dopaminergic neurons of the substantia nigra. These intracellular inclusions are largely composed of misfolded α-synuclein (AS), a neuronal protein that is abundant in the vertebrate brain. Point mutations in AS are associated with rare, early-onset forms of PD, although aggregation of the wild-type (WT) protein is observed in the more common sporadic forms of the disease. Here, we employed multidimensional solid-state NMR experiments to assess A53T and E46K mutant fibrils, in comparison to our recent description of WT AS fibrils. We made de novo chemical shift assignments for the mutants, and used these chemical shifts to empirically determine secondary structures. We observe significant perturbations in secondary structure throughout the fibril core for the E46K fibril, while the A53T fibril exhibits more localized perturbations near the mutation site. Overall, these results demonstrate that the secondary structure of A53T has some small differences from the WT and the secondary structure of E46K has significant differences, which may alter the overall structural arrangement of the fibrils

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting

BACKGROUND: The COVID-19 pandemic has a large impact worldwide and is known to particularly affect the older population. This paper outlines the protocol for external validation of prognostic models predicting mortality risk after presentation with COVID-19 in the older population. These prognostic models were originally developed in an adult population and will be validated in an older population (≥ 70 years of age) in three healthcare settings: the hospital setting, the primary care setting, and the nursing home setting.METHODS: Based on a living systematic review of COVID-19 prediction models, we identified eight prognostic models predicting the risk of mortality in adults with a COVID-19 infection (five COVID-19 specific models: GAL-COVID-19 mortality, 4C Mortality Score, NEWS2 + model, Xie model, and Wang clinical model and three pre-existing prognostic scores: APACHE-II, CURB65, SOFA). These eight models will be validated in six different cohorts of the Dutch older population (three hospital cohorts, two primary care cohorts, and a nursing home cohort). All prognostic models will be validated in a hospital setting while the GAL-COVID-19 mortality model will be validated in hospital, primary care, and nursing home settings. The study will include individuals ≥ 70 years of age with a highly suspected or PCR-confirmed COVID-19 infection from March 2020 to December 2020 (and up to December 2021 in a sensitivity analysis). The predictive performance will be evaluated in terms of discrimination, calibration, and decision curves for each of the prognostic models in each cohort individually. For prognostic models with indications of miscalibration, an intercept update will be performed after which predictive performance will be re-evaluated.DISCUSSION: Insight into the performance of existing prognostic models in one of the most vulnerable populations clarifies the extent to which tailoring of COVID-19 prognostic models is needed when models are applied to the older population. Such insight will be important for possible future waves of the COVID-19 pandemic or future pandemics.</p