Does Warming Enhance the Effects of Eutrophication in the Seagrass Posidonia oceanica?

Seagrass meadows are disappearing at rates comparable to those reported for mangroves, coral reefs, and tropical rainforests. One of the main causes of their decline is the so-called cultural eutrophication, i.e., the input of abnormal amounts of nutrients derived from human activities. Besides the impact of eutrophication at a local scale, the occurrence of additional stress factors such as global sea warming may create synergisms in detriment of seagrass meadows’ health. In the present study, we aimed to evaluate if plants undergoing chronic cultural eutrophication and plants growing in relatively pristine waters are more (or less) sensitive to heat stress, nutrient load and the combination of both stressors. To address this question, a mesocosm experiment was conducted using Posidonia oceanica collected from two environments with different nutrients load history. Plants were exposed in controlled conditions to high nutrient concentrations, increased temperature and their combination for 5 weeks, to assess the effect of the single stressors and their interaction. Our results revealed that plants experiencing chronic cultural eutrophication (EU) are more sensitive to further exposure to multiple stressors than plants growing in oligotrophic habitats (OL). OL and EU plants showed different morphological traits and physiological performances, which corroborates the role of local pressures in activating different strategies in response to global environmental changes. EU-plants appeared to be weaker during the treatments, showing the greatest percentage of mortality, particularly under increased temperature. Temperature and nutrient treatments showed opposite effects when tested individually and an offset response when combined. The activation of physiological strategies with high energetic expenses to cope with excess of nutrients and other stressors, could affect plants present and future persistence, particularly under eutrophic conditions. Our results represent a step forward in understanding the complex interactions that occur in natural environments. Moreover, unraveling intraspecific strategies and the role of local acclimation/adaptation in response to multiple stressors could be crucial for seagrass conservation strategies under a climate change scenario

Mixed integer programming in production planning with backlogging and setup carryover : modeling and algorithms

This paper proposes a mixed integer programming formulation for modeling the capacitated multi-level lot sizing problem with both backlogging and setup carryover. Based on the model formulation, a progressive time-oriented decomposition heuristic framework is then proposed, where improvement and construction heuristics are effectively combined, therefore efficiently avoiding the weaknesses associated with the one-time decisions made by other classical time-oriented decomposition algorithms. Computational results show that the proposed optimization framework provides competitive solutions within a reasonable time

A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning

We present an empirical evaluation of machine learning algorithms in cross-domain few-shot learning based on a fixed pre-trained feature extractor. Experiments were performed in five target domains (CropDisease, EuroSAT, Food101, ISIC and ChestX) and using two feature extractors: a ResNet10 model trained on a subset of ImageNet known as miniImageNet and a ResNet152 model trained on the ILSVRC 2012 subset of ImageNet. Commonly used machine learning algorithms including logistic regression, support vector machines, random forests, nearest neighbour classification, naïve Bayes, and linear and quadratic discriminant analysis were evaluated on the extracted feature vectors. We also evaluated classification accuracy when subjecting the feature vectors to normalisation using p-norms. Algorithms originally developed for the classification of gene expression data—the nearest shrunken centroid algorithm and LDA ensembles obtained with random projections—were also included in the experiments, in addition to a cosine similarity classifier that has recently proved popular in few-shot learning. The results enable us to identify algorithms, normalisation methods and pre-trained feature extractors that perform well in cross-domain few-shot learning. We show that the cosine similarity classifier and ℓ² -regularised 1-vs-rest logistic regression are generally the best-performing algorithms. We also show that algorithms such as LDA yield consistently higher accuracy when applied to ℓ² -normalised feature vectors. In addition, all classifiers generally perform better when extracting feature vectors using the ResNet152 model instead of the ResNet10 model

Comparação da Radiação Solar Global Incidente Obtida por Diferentes Fontes de Dados para o Norte de SP

O objetivo deste trabalho foi comparar os dados de radiaçãosolar global incidente de três torres micrometeorológicas localizados naregião norte do estado de São Paulo, com os dados disponíveis de outrasfontes: estações meteorológicas de superfície mais próximas e estimativasa partir de satélites (modelo GL1.2). A regressão linear entre as estimativasde radiação do modelo GL1.2 com as observações na área decerrado indicou um ajuste melhor do que o obtido com a estaçãometeorológica mais próxima. Esses resultados sugerem que as estimativasde radiação do modelo GL1.2 podem ser usadas para o preenchimentode falhas de Ki medida nas torres micrometeorológicas e potencialmentecomo forçante em esquemas de superfície e modelos hidrológicosaplicados a bacias hidrográficas da região

Piecewise linear approximations for the static-dynamic uncertainty strategy in stochastic lot-sizing

In this paper, we develop mixed integer linear programming models to compute near-optimal policy parameters for the non-stationary stochastic lot sizing problem under Bookbinder and Tan's static-dynamic uncertainty strategy. Our models build on piecewise linear upper and lower bounds of the first order loss function. We discuss different formulations of the stochastic lot sizing problem, in which the quality of service is captured by means of backorder penalty costs, non-stockout probability, or fill rate constraints. These models can be easily adapted to operate in settings in which unmet demand is backordered or lost. The proposed approach has a number of advantages with respect to existing methods in the literature: it enables seamless modelling of different variants of the above problem, which have been previously tackled via ad-hoc solution methods; and it produces an accurate estimation of the expected total cost, expressed in terms of upper and lower bounds. Our computational study demonstrates the effectiveness and flexibility of our models.Comment: 38 pages, working draf

Identification of glucose transporters in Aspergillus nidulans

o characterize the mechanisms involved in glucose transport, in the filamentous fungus Aspergillus nidulans, we have identified four glucose transporter encoding genes hxtB-E. We evaluated the ability of hxtB-E to functionally complement the Saccharomyces cerevisiae EBY.VW4000 strain that is unable to grow on glucose, fructose, mannose or galactose as single carbon source. In S. cerevisiae HxtB-E were targeted to the plasma membrane. The expression of HxtB, HxtC and HxtE was able to restore growth on glucose, fructose, mannose or galactose, indicating that these transporters accept multiple sugars as a substrate through an energy dependent process. A tenfold excess of unlabeled maltose, galactose, fructose, and mannose were able to inhibit glucose uptake to different levels (50 to 80 %) in these s. cerevisiae complemented strains. Moreover, experiments with cyanide-m-chlorophenylhydrazone (CCCP), strongly suggest that hxtB, -C, and –E mediate glucose transport via active proton symport. The A. nidulans ΔhxtB, ΔhxtC or ΔhxtE null mutants showed ~2.5-fold reduction in the affinity for glucose, while ΔhxtB and -C also showed a 2-fold reduction in the capacity for glucose uptake. The ΔhxtD mutant had a 7.8-fold reduction in affinity, but a 3-fold increase in the capacity for glucose uptake. However, only the ΔhxtB mutant strain showed a detectable decreased rate of glucose consumption at low concentrations and an increased resistance to 2-deoxyglucose.The authors would like to thank the Fundacao de Amparo a Pesquisa do Estado de Sao Paulo and Conselho Nacional de Desenvolvimento Cientifico e Tecnologico, Brazil for financial support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Global gene expression analysis in time series following N-acetyl L-cysteine induced epithelial differentiation of human normal and cancer cells in vitro

BACKGROUND: Cancer prevention trials using different types of antioxidant supplements have been carried out at several occasions and one of the investigated compounds has been the antioxidant N-acetyl-L-cysteine (NAC). Studies at the cellular level have previously demonstrated that a single supplementation of NAC induces a ten-fold more rapid differentiation in normal primary human keratinocytes as well as a reversion of a colon carcinoma cell line from neoplastic proliferation to apical-basolateral differentiation [1]. The investigated cells showed an early change in the organization of the cytoskeleton, several newly established adherens junctions with E-cadherin/β-catenin complexes and increased focal adhesions, all features characterizing the differentiation process. METHODS: In order to investigate the molecular mechanisms underlying the proliferation arrest and accelerated differentiation induced by NAC treatment of NHEK and Caco-2 cells in vitro, we performed global gene expression analysis of NAC treated cells in a time series (1, 12 and 24 hours post NAC treatment) using the Affymetrix GeneChip™ Human Genome U95Av2 chip, which contains approximately 12,000 previously characterized sequences. The treated samples were compared to the corresponding untreated culture at the same time point. RESULTS: Microarray data analysis revealed an increasing number of differentially expressed transcripts over time upon NAC treatment. The early response (1 hour) was transient, while a constitutive trend was commonly found among genes differentially regulated at later time points (12 and 24 hours). Connections to the induction of differentiation and inhibition of growth were identified for a majority of up- and down-regulated genes. All of the observed transcriptional changes, except for seven genes, were unique to either cell line. Only one gene, ID-1, was mutually regulated at 1 hour post treatment and might represent a common mediator of early NAC action. The detection of several genes that previously have been identified as stimulated or repressed during the differentiation of NHEK and Caco-2 provided validation of results. In addition, real-time kinetic PCR analysis of selected genes also verified the differential regulation as identified by the microarray platform. CONCLUSION: NAC induces a limited and transient early response followed by a more consistent and extensively different expression at later time points in both the normal and cancer cell lines investigated. The responses are largely related to inhibition of proliferation and stimulation of differentiation in both cell types but are almost completely lineage specific. ID-1 is indicated as an early mediator of NAC action

Secondary Metabolites of Marine Microbes: From Natural Products Chemistry to Chemical Ecology

Marine natural products (MNPs) exhibit a wide range of pharmaceutically relevant bioactivities, including antibiotic, antiviral, anticancer, or anti-inflammatory properties. Besides marine macroorganisms such as sponges, algae, or corals, specifically marine bacteria and fungi have shown to produce novel secondary metabolites (SMs) with unique and diverse chemical structures that may hold the key for the development of novel drugs or drug leads. Apart from highlighting their potential benefit to humankind, this review is focusing on the manifold functions of SMs in the marine ecosystem. For example, potent MNPs have the ability to exile predators and competing organisms, act as attractants for mating purposes, or serve as dye for the expulsion or attraction of other organisms. A large compilation of literature on the role of MNPs in marine ecology is available, and several reviews evaluated the function of MNPs for the aforementioned topics. Therefore, we focused the second part of this review on the importance of bioactive compounds from crustose coralline algae (CCA) and their role during coral settlement, a topic that has received less attention. It has been shown that certain SMs derived from CCA and their associated bacteria are able to induce attachment and/or metamorphosis of many benthic invertebrate larvae, including globally threatened reef-building scleractinian corals. This review provides an overview on bioactivities of MNPs from marine microbes and their potential use in medicine as well as on the latest findings of the chemical ecology and settlement process of scleractinian corals and other invertebrate larvae