The effect of the electric field on lag phase, β-galactosidase production and plasmid stability of a recombinant Saccharomyces cerevisiae strain growing on lactose

Ethanol and β-galactosidase production from cheese whey may significantly contribute to minimise environmental problems while producing value from lowcost raw materials. In this work, the recombinant Saccharomyces cerevisiae NCYC869-A3/pVK1.1 flocculent strain expressing the lacA gene (coding for β-galactosidase) of Aspergillus niger under ADHI promoter and terminator was used. This strain shows high ethanol and β-galactosidase productivities when grown on lactose. Batch cultures were performed using SSlactose medium with 50 gL−1 lactose in a 2-L bioreactor under aerobic and microaerophilic conditions. Temperature was maintained at 30 °C and pH 4.0. In order to determine the effect of an electric field in the fermentation profile, titanium electrodes were placed inside the bioreactor and different electric field values (from 0.5 to 2 Vcm−1) were applied. For all experiments, β-galactosidase activity, biomass, protein, lactose, glucose, galactose and ethanol concentrations were measured. Finally, lag phase duration and specific growth rate were calculated. Significant changes in lag phase duration and biomass yield were found when using 2 Vcm−1. Results show that the electric field enhances the early stages of fermentation kinetics, thus indicating that its application may improve industrial fermentations’ productivity. The increase in electric field intensity led to plasmid instability thus decreasing β-galactosidase production.The authors gratefully acknowledge Fundacao para a Ciencia e a Tecnologia (Portugal) for the scholarships SFRH/BD/11230/2002 and SFRH/BDP/63831/2009 granted to authors I. Castro and C. Oliveira, respectively

Clinical features of De Novo acute myeloid leukemia with concurrent DNMT3A, FLT3 and NPM1 mutations

BACKGROUND: De novo acute myeloid leukemia (AML) with concurrent DNMT3A, FLT3 and NPM1 mutations (AML(DNMT3A/FLT3/NPM1)) has been suggested to represent a unique AML subset on the basis of integrative genomic analysis, but the clinical features of such patients have not been characterized systematically. METHODS: We assessed the features of patients (n = 178) harboring mutations in DNMT3A, FLT3 and/or NPM1, including an index group of AML(DNMT3A/FLT3/NPM1) patients. RESULTS: Patients with AML(DNMT3A/FLT3/NPM1) (n = 35) were significantly younger (median, 56.0 vs. 62.0 years; p = 0.025), mostly women (65.7% vs. 46.9%; p = 0.045), and presented with a higher percentage of bone marrow blasts (p < 0.001) and normal cytogenetics (p = 0.024) in comparison to patients within other mutation groups in this study. Among patients <60 years old, those with AML(DNMT3A/FLT3/NPM1) had a shorter event-free survival (EFS) (p = 0.047). DNMT3A mutations and not FLT3 or NPM1 mutations were independently associated with overall survival (OS) (p = 0.026). Within mutation subgroups, patients with AML(DNMT3A/NPM1) had a significantly shorter OS compared to those with AML(FLT3-ITD/NPM1) (p = 0.047) suggesting that the adverse impact of DNMT3A mutations is more pronounced than that of FLT3-ITD among patients with NPM1 mutation. CONCLUSIONS: DNMT3A has a significant dominant effect on the clinical features and outcomes of de novo AML patients with concurrent DNMT3A, FLT3 and NPM1 mutations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13045-014-0074-4) contains supplementary material, which is available to authorized users

The 5th edition of the World Health Organization classification of haematolymphoid tumours: myeloid and histiocytic/dendritic neoplasms

The upcoming 5th edition of the World Health Organization (WHO) Classification of Haematolymphoid Tumours is part of an effort to hierarchically catalogue human cancers arising in various organ systems within a single relational database. This paper summarizes the new WHO classification scheme for myeloid and histiocytic/dendritic neoplasms and provides an overview of the principles and rationale underpinning changes from the prior edition. The definition and diagnosis of disease types continues to be based on multiple clinicopathologic parameters, but with refinement of diagnostic criteria and emphasis on therapeutically and/or prognostically actionable biomarkers. While a genetic basis for defining diseases is sought where possible, the classification strives to keep practical worldwide applicability in perspective. The result is an enhanced, contemporary, evidence-based classification of myeloid and histiocytic/dendritic neoplasms, rooted in molecular biology and an organizational structure that permits future scalability as new discoveries continue to inexorably inform future editions

Development and Evaluation of a Gas Flamer with The Ability of Targeted-discrete Flaming in Locating and Eradicating Weeds

Farmers are now more interested in application of weed control methods and tools with less environmental side effects. Flame weeding using propane gas is an approach with almost no any chemical residue on the soil and plant surfaces or underground water. In this research, a flame weeding machine with the ability of uniform and also discrete flaming was developed and evaluated in laboratory and field scales. In this apparatus, machine vision technology successfully discriminates between soil and weeds (plants grown in between the corn rows are considered as weeds) under natural illumination. In the laboratory tests, the effect of three forward speeds (0.5, 0.7 and 0.9 m s-1) on flam leading or lagging was investigated. The feasibility of using this technology for site-specific weed control of a corn field in comparison with conventional continuous flaming was investigated. The field trials were conducted with both continuous and discrete flaming approaches. The system performance and weed response to flaming treatments were evaluated by measuring the fuel consumption, counting the number of and weighting the survived and dead weeds one and three days after each flaming treatment. The results of laboratory tests showed that the effect of forward speed on system accuracy was significant and the system performance was more accurate at forward speeds of 0.5 and 0.7 m s-1 than 0.9 m s-1. According to the field experiments, continuous and discrete flaming methods exhibited similar results in eradication of weeds (both number and weight-based), while the fuel consumption of the discrete flaming was lower than the continuous one. The results also showed that discrete flaming by employing machine vision technology could be an efficient substitute for continuous flaming due to its lower fuel consumption and potential reduction of air pollution as well as other benefits of flame weeding

Mapping Alfalfa Yield Using an Energy Monitoring System on a Rectangular Hay Baler

The most advanced part of precision agriculture technology is yield monitoring of grain and non-grain crops. In this study, the horizontal pressing force of baling plunger and the angular position of the plunger connecting rod were simultaneously measured by installing a load cell and a shaft encoder on the connecting rod and plunger flywheel of a small rectangular baler, respectively. The signals of these sensors were processed in an electronic board and the output data were recorded on a portable computer for monitoring and further analysis. Before baling the harvested alfalfa from the test field, random samples were collected and weighted to obtain a referenced measure of the yield variation along the entire field. Comparing the yield data with the pressing energy and angular position data indicated a good correlation between the throughput rate of the baler and the horizontal force imparted on the baler plunger. The estimated crop yield variations were geo-referenced by using a GPS receiver. By combining the output data of the installed sensors and the positioning data, the yield map of the test field was prepared

Design, Development and Evaluation of a Mass Flow Sensor for Grain Combine Harvesters

In grain yield monitoring system, the amount of clean grain mass flow rate to the storage bin is the most important yield property. In this research, an impact-plate type grain mass flow sensor was designed, developed and evaluated. After construction of the impact sensor, it was calibrated by loading the impact plate with static weights ranging from 0.5 to 4.5 kg every 0.5 kg and its linear response to the applied loads was proved with a correlation coefficient of 0.99. Then, grain mass flow measurement tests and data collection were conducted according to the ASABE standard S587, developed for grain mass flow sensors. The tests were conducted in three phases: 1- constant and steady state flow, 2- linear variation of flow, 3- oscillating flow. The results showed that the output of impact plate sensor varies proportionally and linearly with increasing wheat grain (Rowshan cultivar) mass flow rate. The error in prediction of actual flow rate was decreased by increasing the mass flow rate such that the calculated errors at 25%, 50%, 75% and 100% of flow capacity (4.25 kg s-1) were 8.3%, 6.3%, 5.2% and 4.9%, respectively. The high coefficient of determination (R2 = 0.9975) between accumulated mass flow data of impact plate sensor and the reference scale data indicated high accuracy and sensitivity of impact plate sensor in prediction of mass flow variations. The average percent error of impact sensor in variable flow rate in “ramp-up-ramp-down”, “ramp-down-ramp-up” and oscillating flows were 7.4%, 8.6% and 8.3%, respectively

On the neurocomputing based intelligent simulation of tractor fuel efficiency parameters

Tractor fuel efficiency parameters (TFEPs) (fuel consumption per working hour (FCWH), fuel consumption per tilled area (FCTA) and specific volumetric fuel consumption (SVFC)) were intelligently simulated. A neurocomputing based simulation strategy (adaptive neuro-fuzzy inference system (ANFIS)) was used to simulate the TFEPs. A comparison was also made between results of the best ANFIS environment and those of another neurocomputing based simulation strategy, artificial neural network (ANN). Field experiments were conducted at plowing depths of 10, 20 and 30 (cm) and forward speeds of 2, 4 and 6 (km/h) using a disk plow implement. Statistical descriptor parameters applied to evaluate simulation environments indicated that the best simulation environment of both ANFIS and ANN were able to perfectly predict the TFEPs. However, the best comprehensive ANN simulation environment with a simple architecture of 2-6-3 was easier to use than three individual ANFIS simulation environments. The ANN results revealed that simultaneous increase of forward speed from 2 to 6 (km/h) and plowing depth from 10 to 30 (cm) led to nonlinear increment of the FCWH from 5.29 to 14.89 (L/h) and nonlinear decrement of the SVFC from 2.95 to 0.67 (L/h kW). Meanwhile, forward speed increment along with plowing depth decrement resulted in nonlinear decrement of the FCTA from 28.13 to 12.24 (L/ha). Interaction of forward speed and plowing depth on the FCWH and SVFC was congruent, while it was incongruent for the FCTA. It is suggested to employ the ANN environment in developing future fuel planning schemes of tractor during tillage operations. Keywords: Adaptive neuro-fuzzy inference system, Artificial neural network, Fuel consumption per working hour, Fuel consumption per tilled area, Specific volumetric fuel consumptio