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Purpose: 7-ketocholesterol (7kCh), a natural byproduct of oxidation in lipoprotein deposits is implicated in the pathogenesis of diabetic retinopathy and age-related macular degeneration (AMD). This study was performed to investigate whether several clinical drugs can inhibit 7kCh-induced caspase activation and mitigate its apoptotic effects on retinal cells in vitro. Method: Two populations of retinal cells, human retinal pigment epithelial cells (ARPE-19) and rat neuroretinal cells (R28) were exposed to 7kCh in the presence of the following inhibitors: Z-VAD-FMK (pan-caspase inhibitor), simvastatin, memantine, epicatechin, and Z-IETD-FMK (caspase-8 inhibitor) or Z-ATAD-FMK (caspase-12 inhibitor). Caspase-3/7, -8, and -12 activity levels were measured by fluorochrome caspase assays to quantify cell death. IncuCyte live-cell microscopic images were obtained to quantify cell counts. Results: Exposure to 7kCh for 24 hours significantly increased caspase activities for both ARPE-19 and R28 cells (P < 0.05). In ARPE cells, pretreatment with various drugs had significantly lower caspase-3/7, -8, and -12 activities, reported in % change in mean signal intensity (msi): Z-VAD-FMK (48% decrease, P < 0.01), memantine (decreased 47.8% at 1 µM, P = 0.0039 and 81.9% at 1 mM, P < 0.001), simvastatin (decreased 85.3% at 0.01 µM, P < 0.001 and 84.8% at 0.05 µM, P < 0.001) or epicatechin (83.6% decrease, P < 0.05), Z-IETD-FMK (68.1% decrease, P < 0.01), and Z-ATAD-FMK (47.7% decrease, P = 0.0017). In contrast, R28 cells exposed to 7kCh continued to have elevated caspase-3/7, -8, and -12 activities (between 25.7% decrease and 17.5% increase in msi, P > 0.05) regardless of the pretreatment. Conclusion: Several current drugs protect ARPE-19 cells but not R28 cells from 7kCh-induced apoptosis, suggesting that a multiple-drug approach is needed to protect both cells types in various retinal diseases.

Matrix targeting sequences (MTSs) direct proteins from the cytosol into mitochondria. Efficient targeting often relies on internal matrix targeting-like sequences (iMTS-Ls) which share structural features with MTSs. Predicting iMTS-Ls was tedious and required multiple tools and webservices. We present iMLP, a deep learning approach for the prediction of iMTS-Ls in protein sequences. A recurrent neural network has been trained to predict iMTS-L propensity profiles for protein sequences of interest. The iMLP predictor considerably exceeds the speed of existing approaches. Expanding on our previous work on iMTS-L prediction, we now serve an intuitive iMLP webservice available at http://iMLP.bio.uni-kl.de and a stand-alone command line tool for power user in addition.

Differences in technical efficiency across farms are one of the major factors explaining differences in farm survival and growth and changes in farm industry structure. This study employs Data Envelopment Analysis (DEA) to compute technical inefficiency scores for output, energy, materials, pesticides and fertiliser of a sample of Dutch indoor vegetable farms within the period 2006–2016. A bootstrap truncated regression model is used to determine statistical associations between producer-specific characteristics and technical inefficiency scores for the specified inputs. For the sample of indoor growers, the average technical inefficiency was about 14% for energy, 23% for materials, 24% for pesticides and 22% for fertilisers. The bootstrap truncated regression suggested that the degree of specialisation exerts adverse effects on the technical inefficiency of variable inputs. While age, short-term, long-term debt and subsidy were statistically significant, the coefficients were not economically significant. Building the capacity of farmers to reduce input inefficiency will enable farmers to be competitive and reduce the adverse effects of input overuse on the environment.

The introduction of Xylella fastidiosa in Apulia has resulted in the desiccation of millions of olive trees. Here, we employ a multi-country partial equilibrium model to analyze the possible distribution of economic impacts among olive oil processors and consumers. The results suggest that the majority of the impacts would fall on consumers as a consequence of higher prices. If the disease disperses beyond the current extent in Italy the decline in consumer welfare ranges from 4.1 billion to 10.3 billion Euro over the course of 50 years depending on the rate of disease spread. In other words, each of the 195 million households in Europe would incur additional costs ranging 63 cents to 1.6 Euro every year over the course of 50 years. Introductions of the pathogen into Greece or Spain could cost European consumers between 0.4 billion to 3.3 billion Euro and 1.8 billion to 53 billion Euro, respectively. This would correspond to additional annual household costs ranging 6 to 51 cents and 27 cents to 8.2 Euro, respectively. As significant economic consequences from further dispersal of the disease are borne by consumers, the economic threat is not limited to producers but should be contextualized as a societal problem.

In the past decade, anti-vascular endothelial growth factor (VEGF) therapy has become more popular and the standard of care for several retinal diseases including exudative age-related macular degeneration (AMD) (Brown et al., 2006; Martin et al., 2012; Rosenfeld et al., 2006; Tufail et al., 2010), diabetic macular edema (DME) (Brown et al., 2013; Do et al., 2012; Do et al., 2013; TDRCR, 2015), and macular edema (ME) due to retinal vein occlusion (RVO) (Brown et al., 2010; Brown et al., 2013; Campochiaro et al., 2010; Wu et al., 2008). Ranibizumab (Lucentis®, Genentech, San Francisco, CA) is a humanized, recombinant, monoclonal antibody fragment. Intended for intraocular use, a 0.5mg/0.05ml dose is approved by the Food and Drug Administration for exudative AMD and ME due to RVO; a 0.3mg/0.05ml dose is approved by the FDA for DME, and diabetic retinopathy (DR). Bevacizumab (Avastin®, Genentech, San Francisco, CA) is a humanized monoclonal human immunoglobulin gamma 1 (IgG1) antibody that selectively binds to circulating VEGF and inhibit its binding to cell surface receptors. A 1.25mg/0.05ml is used off-label in the United States and is commonly used worldwide for exudative AMD, DME and RVO. Aflibercept (Eylea®, Regeneron Pharmaceuticals, Tarrytown, NY) is a recombinant protein receptor decoy composed of two VEGF receptors 1 and 2 fused with the Fc region of human IgG1. Compared to the former two anti-VEGF drugs, it has a higher binding affinity for VEGF and it also binds to VEGF-B and Placental growth factor (PGF). A concentration of 2.0mg/0.05ml is approved by the FDA for wet AMD, DME, ME due to RVO, and DR in patients with DME. Ziv-aflibercept (Zaltrap®, Sanofi Aventis, Bridgewater, NJ and Regeneron Pharmaceuticals, Tarrytown, NY), also known as VEGF Trap-oncologic, contains 25 mg/ml ziv-aflibercept, however contains higher sucrose concentrations than aflibercept (Eylea), which results in higher osmolality (Bayer, 2014; Group, 2012). Ziv-aflibercept is approved by the FDA for treatment of resistant or progressing metastatic colorectal cancer. However, Mansour et al. (Mansour et al., 2015; Mansour et al., 2017a; Mansour et al., 2017b); de Oliveira Dias et al. (de Oliveira Dias et al., 2015; de Oliveira Dias et al., 2017; de Oliveira Dias et al., 2016); and Chhablani et al., (Chhablani, 2015; Chhablani et al., 2017), among other authors, have published several reports finding good outcomes and no apparent safety issues in a series of patients treated with intravitreal ziv-aflibercept. Previous studies have shown that anti-VEGF drugs in clinically significant doses do not affect cell viability in vitro in a human retinal pigment epithelium (RPE) cell line (ARPE-19) (Luthra et al., 2006; Malik et al., 2014b). Nonetheless, subtle cytotoxic changes in RPE cells, such as decrease in mitochondrial membrane potential, could be observed even at clinical doses for some anti-VEGF drugs (Malik et al., 2014b). Numerous publications have described in vitro differential responses to the different anti-VEGF drugs in various retinal cells (Deissler et al., 2012; Klettner et al., 2010; Schnichels et al., 2013). Muller cells are predominant glial cells in the retina and provide structural and metabolic support to retinal neurons. Several studies have described numerous functions of Muller cells, including regulation of cellular homeostasis and pH, modulation of neurotransmitter recycling, contribution to the blood-retinal barrier by surrounding retinal capillaries with glial processes (Limb et al., 2002; Reichenbach and Bringmann, 2013), acting as light collectors by directing light to photoreceptors (Franze et al., 2007; Reichenbach and Bringmann, 2013), and secretion and regulation of VEGF and pigment epithelium derived factor (PEDF) (Garcia and Vecino, 2003; Limb et al., 2002; Reichenbach and Bringmann, 2013). Muller cells have also been associated with retinal neuroprotection, wound healing and regeneration (Garcia and Vecino, 2003). The purpose of this study was to evaluate the in vitro response and differences in gene expression of human retinal Muller cells treated with different concentrations of ranibizumab, bevacizumab, aflibercept or ziv-aflibercept. Assays for cell viability, metabolic activity, mitochondrial membrane potential (ΔΨm), reactive oxygen species (ROS) and apoptosis were used to evaluate responses to the anti-VEGF drugs. In addition, differences in the expression levels for angiogenesis-related, pro-apoptotic, inflammation and oxidative stress genes were assessed.

Bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix have been two economically important aquaculture species in China for centuries. In the past decades, bighead and silver carp have been introduced from the Yangtze River to many river systems in China, including the Pearl River, in annual, large-scale, stocking activities to enhance wild fisheries. Nonetheless, few studies have assessed the ecological or genetic impacts of such introductions on native conspecific fish populations. An mtDNA D-loop segment of 978 bp from 213 bighead carp samples from 9 populations and a 975 bp segment from 204 silver carp samples from 10 populations were obtained to evaluate genetic diversity and population integrity. Results from a haplotype network analysis revealed that most haplotypes of the Pearl River clustered with those of Yangtze River origin and only a small proportion were distinct, suggesting that both the native Pearl River bighead and silver carp populations are currently dominated by genetic material from the Yangtze River. The genetic diversity of Pearl River populations is high in both species because of this inter-population gene flow, but the diversity of native Pearl River populations is low. To preserve the native genetic diversity, stocking of non-native fingerlings should cease immediately and native Pearl River bighead and silver carp fish farms should be established. This research demonstrates the danger to native biodiversity across China because of the substantial, ongoing stock-enhancement activities without prior genetic assessment.

Targeted mass spectrometry has become the method of choice to gain absolute quantification information of high quality, which is essential for a quantitative understanding of biological systems. However, the design of absolute protein quantification assays remains challenging due to variations in peptide observability and incomplete knowledge about factors influencing peptide detectability. Here, we present a deep learning algorithm for peptide detectability prediction, d::pPop, which allows the informed selection of synthetic proteotypic peptides for the successful design of targeted proteomics quantification assays. The deep neural network is able to learn a regression model that relates the physicochemical properties of a peptide to its ion intensity detected by mass spectrometry. The approach makes use of experimentally detected deviations from the assumed equimolar abundance of all peptides derived from a given protein. Trained on extensive proteomics datasets, d::pPop's plant and non-plant specific models can predict the quality of proteotypic peptides for not yet experimentally identified proteins. Interrogating the deep neural network after learning from ~76,000 peptides per model organism allows to investigate the impact of different physicochemical properties on the observability of a peptide, thus providing insights into peptide observability as a multifaceted process. Empirical evaluation with rank accuracy metrics showed that our prediction approach outperforms existing algorithms. We circumvent the delicate step of selecting positive and negative training sets and at the same time also more closely reflect the need for selecting the top most promising peptides for targeting a protein of interest. Further, we used an artificial QconCAT protein to experimentally validate the observability prediction. Our proteotypic peptide prediction approach not only facilitates the design of absolute protein quantification assays via a user-friendly web interface but also enables the selection of proteotypic peptides for not yet observed proteins, hence rendering the tool especially useful for plant research.

Visualizations are mainly used for providing an easy access to complex information and data. Collaborative visualization as the shared use of computer supported, visual representations of data by more than one person aims to joint information processing activities. Within this paper we apply the concept of collaborative information visualization to the field of analysis of mobile device data. By linking the concept of Quantified Self to our approach, we derive an application for integrating end users into the analysis of mobile device data provided by them. Based on its evaluation we were able to make informed statements about the main enablers for data analysis from an end-user’s perspective such as the interest in the own behavior, the comparison with other study participants as well as the importance of an appropriate baseline.

A stationary catadioptric concentrating photovoltaic module with aperture area over 100 cm2, geometric concentration of 180×, and collection within 60° of polar incidence was designed, prototyped, and characterized. The module performance followed modeling closely with a peak power conversion efficiency of 26% for direct irradiance. Tracking of the sun is accomplished via translational micro-tracking completely internal to the module, avoiding the cost and complexity of mechanical two-axis trackers that point towards the sun. This demonstrates the potential for concentrating photovoltaic modules with significantly higher efficiency than industry standard silicon photovoltaic modules that could be installed in stationary configurations on rooftops.

In this paper, we argue that the roaming functionalities implemented at the data link layer (Layer 2) have certain drawbacks causing delay in the handoff process for mobile hosts in a wireless local area network. Through real experiments, we show how the triggering of the roam process is delayed which affects data transmission. Even though the network interface cards and drivers were from different manufactures, the decision process related to the hand-offs had significant similarities ? the use of a crude timer and an un-sophisticated approach for detecting error conditions. Identifying the mechanisms that cause a mobile host to roam, we suggest a pro-active algorithm that eases the effects of waiting too long to roam. By monitoring the current received signal strength, we were able to initiate the probing process early enough which in turn helped the roaming process.

When we consider models in model-based design (MBD) approaches in the HCI field, we can say that the first generation of tool for user interface construction was based on database models. The second generation of MBD approaches includes models such as the user model, task model, cognitive model, system model etc. However, the third generation of models is the one facing current and future challenges. In this summary report, we present our discussion on the future challenges of MBD.