Contributors:Sabrina Feliciano Oliveira, José Maria Rodrigues da Luz, Maria Catarina Megumi Kasuya, Luiz Orlando Ladeira, Ary Correa Junior
The majority of the textile dyes are harmful to the environment and potentially carcinogenic. Among strategies for their exclusion, the treatment of dye contaminated wastewater with fungal extract, containing lignin peroxidase (LiP), may be useful. Two fungi isolates, Pleurotus ostreatus (PLO9) and Ganoderma lucidum (GRM117), produced the enzymatic extract by fermentation in the lignocellulosic residue, Jatropha curcas seed cake. The extracts from PLO9 and GRM117 were immobilized on carbon nanotubes and showed an increase of 18 and 27-fold of LiP specific activity compared to the free enzyme. Also, LiP from both fungi extracts showed higher Vmax and lower Km values. Only the immobilized extracts could be efficiently reused in the dye decolourization, contrary, the carbon nanotubes became saturated and they should be discarded over time. This device may offer a final biocatalyst with higher catalytic efficiency and capability to be reused in the dye decolourization process.
Contributors:Dezhi Zhang, Qingwen Zhan, Yuche Chen, Shuangyan Li
This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit–cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank–Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed model is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. Carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.
In dealing with the multiplicity problem of large dataset, clusters or families of hypotheses are often the units of interest. A scoring method is motivated in adopting a rejection space for p-values that are classified into spatial or labeled groups. A score that measures the benefits/costs of making a true/false discovery is computed and rejection space that maximizes the number of rejections with positive score is adopted. Renewal and boundary-crossing theories are used to compute the exceedance probability of the score. Level of strong group type I error control is validated using Monte Carlo and importance sampling methods. It is shown that the scoring method maintains detection power and achieves robustness against model deviation. The scoring method is applied on a copy number variation tumor dataset and short intervals of the chromosome with biological relevance are identified.
Contributors:Severina Pacifico, Silvia Galasso, Simona Piccolella, Nadine Kretschmer, San-Po Pan, Paola Nocera, Annamaria Lettieri, Rudolf Bauer, Pietro Monaco
In the course of a screening program on the seasonal phenol composition of wild Mediterranean medicinal and aromatic plants, broadly used for culinary purposes, Foeniculum vulgare Mill. was the focus of the present study. Hydroalcoholic extracts from fennel freeze-dried leaves, collected in different seasons along 2012 and 2013years, were quali-quantitatively analyzed through LC/MS/MS techniques. Winter extract contained, beyond several hydroxycinnamoyl quinic acids and flavonol glycosides, two chromone derivatives. Flavonol hexuronides were the main spring sample constituents. Phenol profile differences among the extracts influenced massively their bioactivity. When the antioxidant screening was performed, winter extract effectively scavenged DPPH and ABTS+ and reduced Fe3+. Although all the extracts did not show cytotoxicity, they were differently able to exert cytoprotection in H2O2-oxidized cell systems and to affect COX-2 gene expression in THP-1 cells. The most active one was winter extract, which inhibited COX-2 expression by 40%, whereas spring sample showed a weak pro-inflammatory capability.
Contributors:P. Tellechea, N. Pujol, P. Esteve-Belloch, B. Echeveste, M.R. García-Eulate, J. Arbizu, M. Riverol
La enfermedad de Alzheimer de inicio precoz (EAIP), definida como la que se manifiesta antes de los 65 años de edad, muestra ciertas características diferentes de la enfermedad de Alzheimer de inicio tardío (EAIT). Nuestro objetivo fue analizar los trabajos más actuales que comparan la clínica, la neuropsicología, la patología, la genética y la neuroimagen de la EAIP y la EAIT, para determinar si nos enfrentamos a dos enfermedades distintas o a variantes de una misma entidad. Como resultado, hallamos consistencia en algunas características diferenciales entre los 2 cuadros clínicos. Fundamentalmente, la EAIP comienza con mayor frecuencia con una clínica atípica; la valoración cognitiva muestra mayor afectación de las funciones ejecutiva y visuoespacial y de las praxias, y menor afectación de la memoria; la neuropatología evidencia mayor densidad y una distribución más difusa de la patología tipo Alzheimer; los estudios de neuroimagen estructural y funcional muestran una afectación cortical mayor y más difusa, afectando al neocórtex (especialmente el precuneus). En conclusión, las evidencias actuales hacen pensar que la EAIP y la EAIT son variantes clínicas de una misma entidad, que en el caso de la EAIT se ve influida probablemente por factores asociados al envejecimiento.
Contributors:Nadia Spano, Valentina Guccini, Marco Ciulu, Ignazio Floris, Valeria M. Nurchi, Angelo Panzanelli, Maria I. Pilo, Gavino Sanna
Surprisingly, a reliable method for measuring the concentration of free fluoride ions in honey is still missing from the literature, notwithstanding the generally recognized importance of the analyte and the matrix. To fill this gap, this study proposes and validates a straightforward ion-specific electrode potentiometric method for this task. The method offers very low detection and quantification limits (6.7μgkg−1 and 25μgkg−1, respectively), good linearity (R2>0.994), good sensitivity (typically 55±3mV for an order of magnitude of concentration) in an unusually low concentration interval (between 0.020 and 1mgL−1), and acceptable precision and bias. The method was applied to 30 unifloral (thistle, eucalyptus and strawberry tree) honey samples from Sardinia, Italy. The amount of free fluoride ions found in these honeys appears to be lower than the range usually found in the literature; indeed, early results suggest a possible dependence of the analyte concentration on the honey’s botanical origin.
Contributors:Ian Jeffreys, Genevieve Graves, Michael Roth
This study evaluates effectiveness of driver education teaching greater fuel efficiency (Eco-Driving) in a real world setting in Australia. The driving behaviour, measured in fuel use (litres per 100km of travel) of a sample of 1056 private drivers was monitored over seven months. 853 drivers received education in eco-driving techniques and 203 were monitored as a control group. A simple experimental design was applied comparing the pre and post training fuel use of the treated sample compared to a control sample. This study found the driver education led to a statistically significant reduction in fuel use of 4.6% or 0.51 litres per 100km compared to the control group.
Contributors:M. Sikirou, A. Shittu, K.A. Konaté, A.T. Maji, A.S. Ngaujah, K.A. Sanni, S.A. Ogunbayo, I. Akintayo, K. Saito, K.N. Dramé, A. Ahanchédé, R. Venuprasad
Iron (Fe) toxicity is recognized as one of the most widely spread soil constraints for rice production especially in West Africa. Oryza glaberrima the cultivated rice species that originated from West Africa is well-adapted to its growing ecologies. The aim of this study was to identify the promising O. glaberrima accessions tolerant to Fe toxicity from the 2106 accessions held at the AfricaRice gene bank. The screenings were conducted over a four-year period and involved evaluating the entries under Fe-toxic field conditions in West Africa, selecting good yielding accessions and repeating the testing with newly selected lines. Three accessions (TOG 7206, TOG 6218-B and TOG 7250-A) were higher yielding than O. sativa checks under stress but with similar yields under control conditions. These accessions yielded over 300g/m2 under both Fe toxicity and control conditions. In conclusion, these materials could be used as donors in breeding programs for developing high yielding rice varieties suited to Fe toxicity affected areas in West Africa.
This study aimed to produce inexpensive 5-aminolevulinic acid (ALA) in a non-sterile latex rubber sheet wastewater (RSW) by Rhodopseudomonas palustris TN114 and PP803 for the possibility to use in agricultural purposes by investigating the optimum conditions, and applying of wood vinegar (WV) as an economical source of levulinic acid to enhance ALA content. The Box–Behnken Design experiment was conducted under microaerobic-light conditions for 96h with TN114, PP803 and their mixed culture (1:1) by varying initial pH, inoculum size (% v/v) and initial chemical oxygen demand (COD, mg/L). Results showed that the optimal condition (pH, % inoculum size, COD) of each set to produce extracellular ALA was found at 7.50, 6.00, 2000 for TN114; 7.50, 7.00, 3000 for PP803; and 7.50, 6.00, 4000 for a mixed culture; and each set achieved COD reduction as high as 63%, 71% and 75%, respectively. Addition of the optimal concentration of WV at mid log phase at 0.63% for TN114, and 1.25% for PP803 and the mixed culture significantly increased the ALA content by 3.7–4.2times (128, 90 and 131μM, respectively) compared to their controls. ALA production cost could be reduced approximately 31times with WV on the basis of the amount of levulinic acid used. Effluent containing ALA for using in agriculture could be achieved by treating the RSW with the selected ALA producer R. palustris strains under the optimized condition with a little WV additive.
Finite mixture modeling is one of the most rapidly developing areas of statistics due to its modeling flexibility and appealing interpretability. Gaussian mixture models have been popular among researchers for decades proving their usefulness in various applications. However, when Gaussian mixture components do not provide an adequate fit for the data, more general models must be considered. Traditional remedies for deviation from normality include employing a more appropriate distribution as well as transforming data to near-normality. Merging both approaches by introducing a mixture model with components derived from the multivariate Manly transformation is proposed. Such mixture models show good performance in modeling skewness and have excellent interpretability. Forward and backward model selection algorithms are proposed to choose an appropriate multivariate transformation. At each step of these algorithms, a model with the specific combination of skewness parameters is estimated by means of the expectation–maximization algorithm. The developed technique is carefully illustrated on synthetic data and applied to several well-known datasets, with promising results.