bluuebunny/crossref_metadata_2025 huggingface dataset:
Relationships between Neonatal Nutrition and Growth to 36 Weeks’ Corrected Age in ELBW Babies–Secondary Cohort Analysis from the Provide Trial
Authors: Cormack Barbara E. , Jiang Yannan , Harding Jane E. , Crowther Caroline A. , Bloomfield Frank H.
Published: March 2020

A key modifiable factor for improving neurodevelopment in extremely low birthweight (ELBW) babies may be improving growth, especially head growth, by optimising nutrition in the early neonatal period. We aimed to investigate relationships between nutrient intakes in the 4 weeks after birth, and growth from birth to 36 weeks’ corrected age (CA) in ELBW babies. We undertook a prospective cohort study of 434 participants enrolled in a randomised controlled trial (ProVIDe) in eight New Zealand and Australian neonatal intensive care units. Macronutrient intakes from birth to 4 weeks and weight, length and head circumference measurements from birth to 36 weeks’ CA were collected. From birth to 36 weeks’ CA, the median (IQR) z-score changes were: weight −0.48 (−1.09, 0.05); length −1.16 (−1.86, −0.43), and head circumference −0.82 (−1.51, −0.19). Changes in z-score to 4 weeks and 36 weeks’ CA were correlated with protein intake. Each 1 g·Kg−1·d−1 total protein intake in week 2 was associated with 0.26 z-score increase in head circumference at 36 weeks’ CA. Both nutritional intake and change in z-scores to 36 weeks’ CA differed widely amongst sites. Correlations between nutrition and growth, and differences in these amongst sites, indicate there may be potential to improve growth with enhanced nutrition practices.
Biological Control of Tomato Gray Mold Caused by Botrytis Cinerea with the Entomopathogenic Fungus Metarhizium Anisopliae
Authors: Sarven Most.Sinthia , Hao Qiuyan , Deng Junbo , Yang Fang , Wang Gaofeng , Xiao Yannong , Xiao Xueqiong
Published: March 2020

Gray mold disease caused by Botrytis cinerea is a devastating disease that leads to serious financial loss. In this study, the entomopathogenic fungus Metarhizium anisopliae that acts against the gray mold pathogen B. cinerea was evaluated. M. anisopliae produced a significant inhibition zone in front of the B. cinerea colony in the dual culture test. In addition, volatile organic compounds generated by M. anisopliae were shown to have an inhibitory effect on B. cinerea mycelia growth and reduced 41% of gray mold severity of postharvest tomatoes. The 10% concentration of the culture filtrate of M. anisopliae inhibited 88.62% of colony radial growth as well as 63.85% of sclerotia germination and all conidia germination of B. cinerea. Furthermore, the culture filtrate of M. anisopliae retained its inhibitory effect against the radial growth of B. cinerea even after heating for 15 min at 100 °C. Feasible mechanisms of M. anisopliae involved in the control of B. cinerea were explored, and it was demonstrated that the plasma membrane of B. cinerea conidia was damaged by the product of metabolism of M. anisopliae. In addition, after treating with culture filtrate of M. anisopliae, the B. cinerea phenotype was shown to be abnormal, and cell organelles of B. cinerea mycelia were damaged significantly. A significant control efficacy of M. anisopliae against tomato gray mold was detected on both the detached leaf assay (84.24%) as well as the whole plant (72.38%). In addition, a 78% reduction in tomato fruit mold was detected at a 10% treated concentration of M. anisopliae. These findings suggest that M. anisopliae possesses potential as a biocontrol agent against tomato gray mold in the greenhouse and during the postharvest stage.
Pharmacotechnical Development of a Nasal Drug Delivery Composite Nanosystem Intended for Alzheimer’s Disease Treatment
Authors: Adnet Thomas , Groo Anne-Claire , Picard Céline , Davis Audrey , Corvaisier Sophie , Since Marc , Bounoure Frédéric , Rochais Christophe , Le Pluart Loïc , Dallemagne Patrick , Malzert-Fréon Aurélie
Published: March 2020

Direct nose-to-brain delivery has been raised as a non-invasive powerful strategy to deliver drugs to the brain bypassing the blood-brain barrier (BBB). This study aimed at preparing and characterizing an innovative composite formulation, associating the liposome and hydrogel approaches, suitable for intranasal administration. Thermosensitive gel formulations were obtained based on a mixture of two hydrophilic polymers (Poloxamer 407, P407 and Poloxamer 188, P188) for a controlled delivery through nasal route via liposomes of an active pharmaceutical ingredient (API) of potential interest for Alzheimer’s disease. The osmolarity and the gelation temperature (T° sol-gel) of formulations, defined in a ternary diagram, were investigated by rheometry and visual determination. Regarding the issue of assays, a mixture composed of P407/P188 (15/1%, w/w) was selected for intranasal administration in terms of T° sol-gel and for the compatibility with the olfactory mucosal (280 ± 20 mOsmol, pH 6). Liposomes of API were prepared by the thin film hydration method. Mucoadhesion studies were performed by using mucin disc, and they showed the good natural mucoadhesive characteristics of in situ gel formulations, which increased when liposomes were added. The study demonstrated successful pharmacotechnical development of a promising API-loaded liposomes in a thermosensitive hydrogel intended for nasal Alzheimer’s disease treatment.
Topical Pioglitazone Nanoformulation for the Treatment of Atopic Dermatitis: Design, Characterization and Efficacy in Hairless Mouse Model
Authors: Espinoza Lupe Carolina , Vera-García Rodrigo , Silva-Abreu Marcelle , Domènech Òscar , Badia Josefa , Rodríguez-Lagunas María J. , Clares Beatriz , Calpena Ana Cristina
Published: March 2020

Pioglitazone (PGZ) is a drug used to treat type 2 diabetes mellitus that has been reported to show additional therapeutic activities on diverse inflammatory parameters. The aim of this study was to optimize a topical PGZ-loaded nanoemulsion (PGZ-NE) in order to evaluate its effectiveness for treating atopic dermatitis (AD). The composition of the nanoformulation was established by pseudo-ternary diagram. Parameters such as physical properties, stability, in vitro release profile, and ex vivo permeation were determined. The efficacy study was carried out using oxazolone-induced AD model in hairless mice. PGZ-NE released the drug following a hyperbolic kinetic. Additionally, its properties provided high retention potential of drug inside the skin. Therapeutic benefits of PGZ-NE were confirmed on diverse events of the inflammatory process, such as reduction of lesions, enhancement of skin barrier function, diminished infiltration of inflammatory cells, and expression of pro-inflammatory cytokines. These results were reinforced by atomic force microscope (AFM), which demonstrated the ability of the formulation to revert the rigidification caused by oxazolone and consequently improve the elasticity of the skin. These results suggest that PGZ-NE may be a promising treatment for inflammatory dermatological conditions such as AD.
Investigating the Suitability of High Content Image Analysis as a Tool to Assess the Reversibility of Foamy Alveolar Macrophage Phenotypes In Vitro
Authors: Hoffman Ewelina , Murnane Darragh , Hutter Victoria
Published: March 2020

Many potential inhaled medicines fail during development due to the induction of a highly vacuolated or “foamy” alveolar macrophage phenotype response in pre-clinical studies. There is limited understanding if this response to an inhaled stimulus is adverse or adaptive, and additionally if it is a transient or irreversible process. The aim of this study was to evaluate whether high content image analysis could distinguish between different drug-induced foamy macrophage phenotypes and to determine the extent of the reversibility of the foamy phenotypes by assessing morphological changes over time. Alveolar-like macrophages derived from the human monocyte cell line U937 were exposed for 24 h to compounds known to induce a foamy macrophage phenotype (amiodarone, staurosporine) and control compounds that are not known to cause a foamy macrophage phenotype in vitro (fluticasone and salbutamol). Following drug stimulation, the cells were rested in drug-free media for the subsequent 24 or 48 h. Cell morphometric parameters (cellular and nuclear area, vacuoles numbers and size) and phospholipid content were determined using high content image analysis. The foamy macrophage recovery was dependent on the mechanism of action of the inducer compound. Amiodarone toxicity was associated with phospholipid accumulation and morphometric changes were reversed when the stimulus was removed from culture environment. Conversely cells were unable to recover from exposure to staurosporine which initiates the apoptosis pathway. This study shows that high content analysis can discriminate between different phenotypes of foamy macrophages and may contribute to better decision making in the process of new drug development.
miRNA–mRNA Integrated Analysis Reveals Roles for miRNAs in a Typical Halophyte, Reaumuria soongorica, during Seed Germination under Salt Stress
Authors: Zhang Huilong , Liu Xiaowei , Yang Xiuyan , Wu Haiwen , Zhu Jianfeng , Zhang Huaxin
Published: March 2020

MicroRNAs (miRNAs) are endogenous small RNAs that play a crucial role in plant growth, development, and environmental stress responses. Reaumuria soongorica is a typical halophyte that is widely distributed in saline–alkali desert regions. Under salt stress, R. soongorica can complete germination, a critical biological process in the life cycle of seed plants. To identify miRNAs and predict target mRNAs involved in seed germination during salt stress, nine small-RNA libraries were constructed and analyzed from R. soongorica seeds treated with various concentrations of NaCl. We also obtained transcriptome data under the same treatment conditions. Further analysis identified 88 conserved miRNAs representing 25 defined families and discovered 13 novel miRNAs from nine libraries. A co-expression analysis was performed on the same samples to identify putative miRNA–mRNA interactions that were responsive to salt stress. A comparative analysis of expression during germination under 273 (threshold) and 43 mM (optimal) NaCl treatments identified 13 differentially expressed miRNAs and 23 corresponding target mRNAs, while a comparison between 43 mM NaCl and non-salt-stress conditions uncovered one differentially expressed miRNA and one corresponding target mRNA. These results provide basic data for further study of molecular mechanisms involved in the germination of salt-stressed R. soongorica seeds, and also provide a reference for the improvement of salt tolerance during plant germination.
Neuroprotective Effects of Dried Tubers of Aconitum napellus
Authors: Shoaib Ambreen , Siddiqui Hefazat Hussain , Dixit Rakesh Kumar , Siddiqui Sahabjada , Deen Badrud , Khan Andleeb , Alrokayan Salman H. , Khan Haseeb A. , Ahmad Parvaiz
Published: March 2020

The present study was designed to explore the neuroprotective properties of Aconitum napellus (Ranunculaceae). The plant detoxification was done using either water, or cow or goat milk as per the Ayurvedic shodhana method. The evaluation of the neuroprotective role of A. napellus was performed on diabetic neuropathy induced by streptozotocin in Sprague Dawley (SD) rats. Body mass, blood sugar level, oral glucose tolerance test, hyperalgesia, cold allodynia, motor co-ordination test, and locomotor activity, oxidative biomarkers (TBARS, reduced glutathione, catalase and superoxide dismutase) and sciatic nerve histomorphology were assessed. The in vitro studies were done on human neuroblastoma cell line SHSY-5Y and used an MTT assay to assess the antiproliferative activity of different extracts. Results suggest that the goat milk treated chloroform extract has less percentage of aconitine. After administration of the detoxified chloroform extract to the diabetic animals, there was a significant improvement in the myelination and degenerative changes of the nerve fibers along with behavioral changes (p < 0.05 as compared with diabetic control group). The findings of the in vitro research show an effective neuroprotective role of A. napellus. This suggests that A. napellus should be further investigated for its effect in diabetic pathology.
Plasticization Effect of Bio-Based Plasticizers from Soybean Oil for Tire Tread Rubber
Authors: Xu Haoshu , Fan Tao , Ye Neng , Wu Weidong , Huang Daye , Wang Danling , Wang Zhao , Zhang Liqun
Published: March 2020

Modified soybean oil (MSO) is synthesized from soybean oil (SO) and sulfur, aiming to reduce the double bond quantity of SO and avoid harmful effects on the crosslink density and mechanical properties of rubber. MSO modified with different weight percentages of sulfur is then used to plasticize tire tread rubber (TR). It is found that the crosslink density and modulus of MSO- plasticized rubber are significantly improved compared with that of SO-plasticized TR. MSO modified with 6 wt % sulfur (MSO-6%) exhibits the best plasticization effect on TR, thus, the plasticization effect of MSO-6% on TR was further studied by adjusting its additive content. Thereafter, the Mooney viscosity, Payne effect, mechanical property of different amount of MSO-6% plasticized TR are studied to investigate their plasticization effect. At the same additive content of plasticizer, the plasticization effect of MSO-6% and a commonly used aromatic hydrocarbon plasticizer (AO) is compared to determine the potential application of MSO on tire tread rubber. It is found MSO shows similar plasticization effect on TR compared with AO. More important, the aging resistance property and wear resistance property of MSO-6% plasticized rubber are better than those of AO-plasticized rubber. Therefore, MSO-6% is a promising bio-based plasticizer for tire tread rubber.
Self-Consistent Mean Field Calculations of Polyelectrolyte-Surfactant Mixtures in Solution and upon Adsorption onto Negatively Charged Surfaces
Authors: Guzmán Eduardo , Fernández-Peña Laura , S. Luengo Gustavo , Rubio Ana , Rey Antonio , Léonforte Fabien
Published: March 2020

Self-Consistent Mean-Field Calculations (SCF) have provided a semi-quantitative description of the physico-chemical behavior of six different polyelectrolyte-surfactant mixtures. The SCF calculations performed showed that both the formation of polymer-surfactant in bulk and the adsorption of the formed complexes onto negatively-charged surfaces are strongly affected by the specific nature of the considered systems, with the polymer-surfactant interactions playing a central role in the self-assembly of the complexes that, in turn, affects their adsorption onto interfaces and surfaces. This work evidences that SCF calculations are a valuable tool for deepening on the understanding of the complex physico-chemical behavior of polyelectrolyte-surfactant mixtures. However, it is worth noting that the framework obtained on the basis of an SCF approach considered an equilibrium situation which may, in some cases, be far from the real situation appearing in polyelectrolyte-surfactant systems.
Switchable Lipid Provides pH-Sensitive Properties to Lipid and Hybrid Polymer/Lipid Membranes
Authors: Passos Gibson Victor , Fauquignon Martin , Ibarboure Emmanuel , Leblond Chain Jeanne , Le Meins Jean-François
Published: March 2020

Blending amphiphilic copolymers and lipids constitutes a novel approach to combine the advantages of polymersomes and liposomes into a new single hybrid membrane. Efforts have been made to design stimuli-responsive vesicles, in which the membrane’s dynamic is modulated by specific triggers. In this investigation, we proposed the design of pH-responsive hybrid vesicles formulated with poly(dimethylsiloxane)-block-poly(ethylene oxide) backbone (PDMS36-b-PEO23) and cationic switchable lipid (CSL). The latter undergoes a pH-triggered conformational change and induces membrane destabilization. Using confocal imaging and DLS measurements, we interrogated the structural changes in CSL-doped lipid and hybrid polymer/lipid unilamellar vesicles at the micro- and nanometric scale, respectively. Both switchable giant unilamellar lipid vesicles (GUV) and hybrid polymer/lipid unilamellar vesicles (GHUV) presented dynamic morphological changes, including protrusions and fission upon acidification. At the submicron scale, scattered intensity decreased for both switchable large unilamellar vesicles (LUV) and hybrid vesicles (LHUV) under acidic pH. Finally, monitoring the fluorescence leakage of encapsulated calcein, we attested that CSL increased the permeability of GUV and GHUV in a pH-specific fashion. Altogether, these results show that switchable lipids provide a pH-sensitive behavior to hybrid polymer/lipid vesicles that could be exploited for the triggered release of drugs, cell biomimicry studies, or as bioinspired micro/nanoreactors.
Formation of Asymmetric and Symmetric Hybrid Membranes of Lipids and Triblock Copolymers
Authors: Tsai Hsiang-Chi , Yang Yan-Ling , Sheng Yu-Jane , Tsao Heng-Kwong
Published: March 2020

Hybrid membranes formed by co-assembly of AxByAx (hydrophilic-hydrophobic-hydrophilic) triblock copolymers into lipid bilayers are investigated by dissipative particle dynamics. Homogeneous hybrid membranes are developed as lipids and polymers are fully compatible. The polymer conformations can be simply classified into bridge- and loop-structures in the membranes. It is interesting to find that the long-time fraction of loop-conformation ( f L ) of copolymers in the membrane depends significantly on the hydrophilic block length (x). As x is small, an equilibrium f L * always results irrespective of the initial conformation distribution and its value depends on the hydrophobic block length (y). For large x, f L tends to be time-invariant because polymers are kinetically trapped in their initial structures. Our findings reveal that only symmetric hybrid membranes are formed for small x, while membranes with stable asymmetric leaflets can be constructed with large x. The effects of block lengths on the polymer conformations, such as transverse and lateral spans ( d ⊥ and d ‖ ) of bridge- and loop-conformations, are discussed as well.
Modeling of Novel Thermodynamic Cycles to Produce Power and Cooling Simultaneously
Authors: Rivera Wilfrido , Sánchez-Sánchez Karen , Hernández-Magallanes J. Alejandro , Jiménez-García J. Camilo , Pacheco Alejandro
Published: March 2020

Thermodynamic cycles to produce power and cooling simultaneously have been proposed for many years. The Goswami cycle is probably the most known cycle for this purpose; however, its use is still very limited. In the present study, two novel thermodynamic cycles based on the Goswami cycle are presented. The proposed cycles use an additional component to condense a fraction of the working fluid produced in the generator. Three cycles are modeled based on the first and second laws of thermodynamics: Two new cycles and the original Goswami cycle. The results showed that in comparison with the original Goswami cycle, the two proposed models are capable of increasing the cooling effect, but the cycle with flow extraction after the rectifier presented higher irreversibilities decreasing its exergy efficiency. However, the proposed cycle with flow extraction into the turbine was the most efficient, achieving the highest values of the energy utilization factor and the exergy efficiency. It was found that for an intermediate split ratio value of 0.5, the power produced in the turbine with the flow extraction decreased 23% but the cooling power was 6 times higher than that obtained with the Goswami Cycle.
Single-Use Printed Biosensor for L-Lactate and Its Application in Bioprocess Monitoring
Authors: Theuer Lorenz , Randek Judit , Junne Stefan , Neubauer Peter , Mandenius Carl-Fredrik , Beni Valerio
Published: March 2020

There is a profound need in bioprocess manufacturing for low-cost single-use sensors that allow timely monitoring of critical product and production attributes. One such opportunity is screen-printed enzyme-based electrochemical sensors, which have the potential to enable low-cost online and/or off-line monitoring of specific parameters in bioprocesses. In this study, such a single-use electrochemical biosensor for lactate monitoring is designed and evaluated. Several aspects of its fabrication and use are addressed, including enzyme immobilization, stability, shelf-life and reproducibility. Applicability of the biosensor to off-line monitoring of bioprocesses was shown by testing in two common industrial bioprocesses in which lactate is a critical quality attribute (Corynebacterium fermentation and mammalian Chinese hamster ovary (CHO) cell cultivation). The specific response to lactate of the screen-printed biosensor was characterized by amperometric measurements. The usability of the sensor at typical industrial culture conditions was favorably evaluated and benchmarked with commonly used standard methods (HPLC and enzymatic kits). The single-use biosensor allowed fast and accurate detection of lactate in prediluted culture media used in industrial practice. The design and fabrication of the biosensor could most likely be adapted to several other critical bioprocess analytes using other specific enzymes. This makes this single-use screen-printed biosensor concept a potentially interesting and versatile tool for further applications in bioprocess monitoring.
Industrial Production of Poly-β-hydroxybutyrate from CO2: Can Cyanobacteria Meet this Challenge?
Authors: Carpine Roberta , Olivieri Giuseppe , Hellingwerf Klaas J. , Pollio Antonino , Marzocchella Antonio
Published: March 2020

The increasing impact of plastic materials on the environment is a growing global concern. In regards to this circumstance, it is a major challenge to find new sources for the production of bioplastics. Poly-β-hydroxybutyrate (PHB) is characterized by interesting features that draw attention for research and commercial ventures. Indeed, PHB is eco-friendly, biodegradable, and biocompatible. Bacterial fermentation processes are a known route to produce PHB. However, the production of PHB through the chemoheterotrophic bacterial system is very expensive due to the high costs of the carbon source for the growth of the organism. On the contrary, the production of PHB through the photoautotrophic cyanobacterium system is considered an attractive alternative for a low-cost PHB production because of the inexpensive feedstock (CO2 and light). This paper regards the evaluation of four independent strategies to improve the PHB production by cyanobacteria: (i) the design of the medium; (ii) the genetic engineering to improve the PHB accumulation; (iii) the development of robust models as a tool to identify the bottleneck(s) of the PHB production to maximize the production; and (iv) the continuous operation mode in a photobioreactor for PHB production. The synergic effect of these strategies could address the design of the optimal PHB production process by cyanobacteria. A further limitation for the commercial production of PHB via the biotechnological route are the high costs related to the recovery of PHB granules. Therefore, a further challenge is to select a low-cost and environmentally friendly process to recover PHB from cyanobacteria.
Model-Based Real Time Operation of the Freeze-Drying Process
Authors: Vilas Carlos , A. Alonso Antonio , Balsa-Canto Eva , López-Quiroga Estefanía , Trelea Ioan Cristian
Published: March 2020

Background: Freeze-drying or lyophilization is a dehydration process employed in high added-value food and biochemical goods. It helps to maintain product organoleptic and nutritional properties. The proper handling of the product temperature during the operation is critical to preserve quality and to reduce the process duration. Methods: Mathematical models are useful tools that can be used to design optimal policies that minimize production costs while keeping product quality. In this work, we derive an operational mathematical model to describe product quality and stability during the freeze-drying process. Model identification techniques are used to provide the model with predictive capabilities. Then, the model is used to design optimal control policies that minimize process time. Results and conclusion: Experimental measurements suggest splitting the process into two subsystems, product and chamber, to facilitate the calibration task. Both models are successfully validated using experimental data. Optimally designed control profiles are able to reduce the process duration by around 30% as compared with standard policies. The optimization task is introduced into a real time scheme to take into account unexpected process disturbances and model/plant mismatch. The implementation of the real time optimization scheme shows that this approach is able to compensate for such disturbances.
Phytochemical Compounds of Branches from P. halepensis Oily Liquid Extract and S. terebinthifolius Essential Oil and Their Potential Antifungal Activity
Authors: Mohamed Abeer A. , Behiry Said I. , Ali Hayssam M. , EL-Hefny Mervat , Salem Mohamed Z.M. , Ashmawy Nader A.
Published: March 2020

In the present study, the antifungal activity of wood treated with Pinus halepensis branch n-hexane oily liquid extract (OLE) and Schinus terebinthifolius branch essential oil (EO) was evaluated against the growth of four phytopathogenic fungi—Bipolaris oryzae, Fusarium oxysporum, Fusarium solani, and Rhizoctonia solani. Air-dried wood samples of Pinus roxburghii were autoclaved, and each wood received 100 µL of the concentrated oils from P. halepensis and S. terebinthifolius. The main compounds identified in S. terebinthifolius branch EO were terpinen-4-ol (18.25%), cis-β-terpineol (15.60%), γ-terpinene (12.46%), sabinene (9.83%), α-terpinene (8.56%), and 4-thujanol (6.71%), while the main compounds in P. halepensis branch HeO were 2-undecenal (22.25%), 4-hydroxy-10-methyl-3,4,7,8,9,10-hexahydro-2H-oxecin-2-one (8.43%), (Z)-2-decenal (6.88%), nonanal (5.85%), (2E)-2-decenal (4.65%), (E,E)-2,4-decadienal (4.41%), arachidonic acid methyl ester (4.36%), and 2-(7-heptadecynyloxy)tetrahydro-2H-pyran (4.22%). P. halepensis OLE at a concentration of 3% showed the highest inhibition percentage of fungal growth (IPFG) of B. oryzae, followed by S. terebinthifolius EO at 3% and 2%, with IPFG values of 80%, 74.44%, and 71.66%, respectively. At a concentration of 3%, branch oils from S. terebinthifolius and P. halepensis were found to have the highest IPFG values with 45.55% and 40.55%, respectively, against F. oxysporum growth. Moderate to weak activity was found against F. solani when S. terebinthifolius EO and P. halepensis OLE were applied to wood. EO and OLE-treated wood samples at 3% produced inhibitions of 54.44% and 41.11%, respectively, against R. solani.
Integration of Time-Series Transcriptomic Data with Genome-Scale CHO Metabolic Models for mAb Engineering
Authors: Huang Zhuangrong , Yoon Seongkyu
Published: March 2020

Chinese hamster ovary (CHO) cells are the most commonly used cell lines in biopharmaceutical manufacturing. Genome-scale metabolic models have become a valuable tool to study cellular metabolism. Despite the presence of reference global genome-scale CHO model, context-specific metabolic models may still be required for specific cell lines (for example, CHO-K1, CHO-S, and CHO-DG44), and for specific process conditions. Many integration algorithms have been available to reconstruct specific genome-scale models. These methods are mainly based on integrating omics data (i.e., transcriptomics, proteomics, and metabolomics) into reference genome-scale models. In the present study, we aimed to investigate the impact of time points of transcriptomics integration on the genome-scale CHO model by assessing the prediction of growth rates with each reconstructed model. We also evaluated the feasibility of applying extracted models to different cell lines (generated from the same parental cell line). Our findings illustrate that gene expression at various stages of culture slightly impacts the reconstructed models. However, the prediction capability is robust enough on cell growth prediction not only across different growth phases but also in expansion to other cell lines.
Secondary Metabolites Profiling, Biological Activities and Computational Studies of Abutilon figarianum Webb (Malvaceae)
Authors: Saleem Hammad , Sarfraz Muhammad , Ahsan Hafiz Muhammad , Khurshid Umair , Kazmi Syed Asif Jahanzeb , Zengin Gokhan , Locatelli Marcello , Ahmad Irshad , Abdallah Hassan H. , Mahomoodally Mohamad Fawzi , Rengasamy Kannan RR , Ahemad Nafees
Published: March 2020

This research endeavors to inspect the chemical and biological profiling of methanol and dichloromethane (DCM) extracts prepared from Abutilon figarianum Webb. Total bioactive constituents and secondary metabolites were assessed via ultra-high performance liquid chromatography (UHPLC-MS). Biological effects were evaluated via antioxidant and enzymes inhibitory assays. The methanol extract was able to give the highest phenolic (51.92 mg GAE/g extract) and flavonoid (72.59 mg QE/g extract) contents and was found to contain 11 bioactive metabolites, including flavonoid, alkaloid, phenolic and fatty acid derivatives, as accessed by UHPLC-MS analysis. Similarly, the phytochemical profiling of the DCM extract tentatively identified the 12 different secondary metabolites, most of these were fatty acid derivatives. The methanol extract was most active in the radical scavenging, reducing power and total antioxidant power assays, while dichloromethane extract showed the highest metal chelating activity. For enzyme inhibition, the DCM extract showed the highest activity against cholinesterases, glucosidase and amylase, whereas methanol extract was most active against tyrosinase. Docking studies have supported the observed biological activity, where isobergapten showed higher activity against tyrosinase (−7.63 kcal/mol) with inhibition constant (2.55 µM), as opposed to other enzymes. The observed antioxidant and inhibitory potentials of A. figarianum against the studied enzymes tend to endorse this plant as a prospective source of bioactive phytochemicals.
Mapping Three Decades of Changes in the Brazilian Savanna Native Vegetation Using Landsat Data Processed in the Google Earth Engine Platform
Authors: Alencar Ane , Z. Shimbo Julia , Lenti Felipe , Balzani Marques Camila , Zimbres Bárbara , Rosa Marcos , Arruda Vera , Castro Isabel , Fernandes Márcico Ribeiro João , Varela Victória , Alencar Isa , Piontekowski Valderli , Ribeiro Vivian , M. C. Bustamante Mercedes , Eyji Sano Edson , Barroso Mario
Published: March 2020

Widespread in the subtropics and tropics of the Southern Hemisphere, savannas are highly heterogeneous and seasonal natural vegetation types, which makes change detection (natural vs. anthropogenic) a challenging task. The Brazilian Cerrado represents the largest savanna in South America, and the most threatened biome in Brazil owing to agricultural expansion. To assess the native Cerrado vegetation (NV) areas most susceptible to natural and anthropogenic change over time, we classified 33 years (1985–2017) of Landsat imagery available in the Google Earth Engine (GEE) platform. The classification strategy used combined empirical and statistical decision trees to generate reference maps for machine learning classification and a novel annual dataset of the predominant Cerrado NV types (forest, savanna, and grassland). We obtained annual NV maps with an average overall accuracy ranging from 87% (at level 1 NV classification) to 71% over the time series, distinguishing the three main NV types. This time series was then used to generate probability maps for each NV class. The native vegetation in the Cerrado biome declined at an average rate of 0.5% per year (748,687 ha yr−1), mostly affecting forests and savannas. From 1985 to 2017, 24.7 million hectares of NV were lost, and now only 55% of the NV original distribution remains. Of the remnant NV in 2017 (112.6 million hectares), 65% has been stable over the years, while 12% changed among NV types, and 23% was converted to other land uses but is now in some level of secondary NV. Our results were fundamental in indicating areas with higher rates of change in a long time series in the Brazilian Cerrado and to highlight the challenges of mapping distinct NV types in a highly seasonal and heterogeneous savanna biome.
Monitoring of Canopy Stress Symptoms in New Zealand Kauri Trees Analysed with AISA Hyperspectral Data
Authors: Meiforth Jane J. , Buddenbaum Henning , Hill Joachim , Shepherd James
Published: March 2020

The endemic New Zealand kauri trees (Agathis australis) are under threat by the deadly kauri dieback disease (Phytophthora agathidicida (PA)). This study aimed to identify spectral index combinations for characterising visible stress symptoms in the kauri canopy. The analysis is based on an aerial AISA hyperspectral image mosaic and 1258 reference crowns in three study sites in the Waitakere Ranges west of Auckland. A field-based assessment scheme for canopy stress symptoms (classes 1–5) was further optimised for use with RGB aerial images. A combination of four indices with six bands in the spectral range 450–1205 nm resulted in a correlation of 0.93 (mean absolute error 0.27, RMSE 0.48) for all crown sizes. Comparable results were achieved with five indices in the 450–970 nm region. A Random Forest (RF) regression gave the most accurate predictions while a M5P regression tree performed nearly as well and a linear regression resulted in slightly lower correlations. Normalised Difference Vegetation Indices (NDVI) in the near-infrared / red spectral range were the most important index combinations, followed by indices with bands in the near-infrared spectral range from 800 to 1205 nm. A test on different crown sizes revealed that stress symptoms in smaller crowns with denser foliage are best described in combination with pigment-sensitive indices that include bands in the green and blue spectral range. A stratified approach with individual models for pre-segmented low and high forest stands improved the overall performance. The regression models were also tested in a pixel-based analysis. A manual interpretation of the resulting raster map with stress symptom patterns observed in aerial imagery indicated a good match. With bandwidths of 10 nm and a maximum number of six bands, the selected index combinations can be used for large-area monitoring on an airborne multispectral sensor. This study establishes the base for a cost-efficient, objective monitoring method for stress symptoms in kauri canopies, suitable to cover large forest areas with an airborne multispectral sensor.
Estimation of Shortwave Solar Radiation on Clear-Sky Days for a Valley Glacier with Sentinel-2 Time Series
Authors: Zhang Yanli , Qin Xiang , Li Xin , Zhao Jun , Liu Yushuo
Published: March 2020

Downward surface shortwave radiation (DSSR) is the main energy source for most glacial melting, and Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper (TM) data have been used extensively in the inversion of input parameters for estimating DSSR. However, for valley glaciers under complex climatic conditions, the values of MODIS atmospheric products, especially aerosol products, are often invalid, and TM images are always saturated with snow. Furthermore, an estimation model based on optical satellite images must simultaneously consider terrain and atmospheric effects and the transient nature of ice/snow albedo. Based on a high-resolution (12 m) digital elevation model (DEM), the newly launched Sentinel-2 satellites, rather than MODIS and TM, were used to provide input data for our published mountain radiation scheme in a valley glacier. Considering Laohugou Glacier No. 12 as the study area, 62 typical Sentinel-2 scenes were selected and spatiotemporal DSSR variations on the glacier surface were obtained with a 10 m spatial resolution during a mass-balance year from September 2017 to August 2018. Ground-based measurements on 52 clear-sky days were used for validation and the mean bias error (MBE = −16.0 W/m2) and root-mean-square difference (RMSD = 73.6 W/m2) were relatively low. The results confirm that DSSR is affected mainly by the solar zenith angle and atmospheric attenuation in flat areas of valley glaciers, while in areas with complex terrain, the DSSR received by the glacier surface is affected primarily by the terrain and ice/snow albedo, which exhibits very high spatial heterogeneity.
Machine Learning Algorithms to Predict Forage Nutritive Value of In Situ Perennial Ryegrass Plants Using Hyperspectral Canopy Reflectance Data
Authors: Smith Chaya , Karunaratne Senani , Badenhorst Pieter , Cogan Noel , Spangenberg German , Smith Kevin
Published: March 2020

Nutritive value (NV) of forage is too time consuming and expensive to measure routinely in targeted breeding programs. Non-destructive spectroscopy has the potential to quickly and cheaply measure NV but requires an intermediate modelling step to interpret the spectral data. A novel machine learning technique for forage analysis, Cubist, was used to analyse canopy spectra to predict seven NV parameters, including dry matter (DM), acid detergent fibre (ADF), ash, neutral detergent fibre (NDF), in vivo dry matter digestibility (IVDMD), water soluble carbohydrates (WSC), and crude protein (CP). Perennial ryegrass (Lolium perenne) was used as the test crop. Independent validation of the developed models revealed prediction capabilities with R2 values and Lin’s concordance values reported between 0.49 and 0.82, and 0.68 and 0.89, respectively. Informative wavelengths for the creation of predictive models were identified for the seven NV parameters. These wavelengths included regions of the electromagnetic spectrum that are usually excluded due to high background variation, however, they contain important information and utilising them to obtain meaningful signals within the background variation is an advantage for accurate models. Non-destructive field spectroscopy along with the predictive models was deployed infield to measure NV of individual ryegrass plants. A significant reduction in labour was observed. The associated increase in speed and reduction of cost makes targeting NV in commercial breeding programs now feasible.
Metabolic Profiling of Varronia curassavica Jacq. Terpenoids by Flow Modulated Two-Dimensional Gas Chromatography Coupled to Mass Spectrometry
Authors: Facanali Roselaine , Marques Marcia Ortiz Mayo , Hantao Leandro Wang
Published: March 2020

In this study, a metabolomic approach was used to investigate the effect of seasonality on the chemical composition and yield of anti-inflammatory active principle, α-humulene, in the essential oil of three genotypes of Varronia curassavica Jacq. (Syn. Cordia verbenaceae). The essential oils were extracted by hydrodistillation and analyzed by comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS). The GC×GC approach a three-fold improvement in qualitative analysis (48 compounds were identified by GC-MS versus 135 by GC×GC-MS). The improved resolving power of GC×GC resolved important coelutions and enabled the detection of unusual substances in V. curassavica essential oil. The chromatographic data was analyzed by using peak table-based chemometrics, namely, principal component analysis (PCA) and hierarchical cluster analysis (HCA). The metabolic study showed that seasonality has a significant effect on the chemical composition. The α-humulene content was affected by genotype and season. Spring and summer were the best harvest seasons for the yield of the active ingredient, found in higher concentrations in the VC2 genotype. The proposed metabolomic workflow was successfully applied to terpene analysis found in V. curassavica essential oil, and such results have broadened our understanding of the influence of seasonal factors on the specialized metabolism of the species.
Mixed Matrix Membrane Tip Extraction Coupled with UPLC–MS/MS for the Monitoring of Nonsteroidal Anti-Inflammatory Drugs in Water Samples
Authors: Ganesan Thipashini , Mukhtar Nurul Hazirah , Lim Hong Ngee , See Hong Heng
Published: March 2020

An ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) method, in combination with a mixed matrix membrane microextraction method for the quantification of nonsteroidal anti-inflammatory drugs (NSAIDs) in environmental water samples, is reported. The extraction device was prepared by casting well-dispersed polymeric bonded octadecyl (C18) particles in a cellulose triacetate matrix solution onto commercially available 200 μL micropipette tips. The membrane formed contains 25% of the adsorbent loading amount and was firmly attached to the inner wall of the membrane tip. The dynamic extraction was performed by withdrawing and dispensing the sample solution through the tip device for effective analyte adsorption, followed by the analyte desorption process into 40 μL of methanol and acetonitrile (1:1) prior to UPLC–MS/MS analysis. NSAIDs—namely diclofenac, ibuprofen, indoprofen, naproxen and sulindac—were chosen as targeted analytes. Several extraction parameters were comprehensively optimized, including sample pH value, ionic strength, dynamic extraction cycle, desorption solvent and desorption time. The optimized conditions demonstrated a linear range from 0.25 to 500 ng L−1, with correlation coefficients (r2) from 0.9988 to 0.9992 and detection limits ranging from 0.08 to 0.40 ng L−1. The recoveries of the spiked water samples were between 92% and 99% and exhibited excellent precision relative to standard deviations (RSDs ≤ 4.9%), and enrichment factors (EFs) were at 201–249 for the developed approach.
Thermal Properties of Semolina Doughs with Different Relative Amount of Ingredients
Authors: Fanari Fabio , Carboni Gianluca , Grosso Massimiliano , Desogus Francesco
Published: March 2020

The impact of the relative amount of ingredients, wheat variety, and kneading time on the thermal properties of semolina doughs were investigated by means of thermogravimetric analysis (TGA). The doughs were prepared by mixing water, semolina, yeast, and salt in different proportions. The gelatinized flour fraction plays an important role in the thermal properties’ definition, while the water amount influences the development of the dough network and, consequently, the starch gelatinization phenomena. Furthermore, the amount of yeast and salt influences the dough network force and, consequently, the thermal properties. The TGA technique was applied in order to evidence the mass loss as a function of the increasing temperature, considering that this behavior depends on the dough network force and extension. In such a way, it was possible to find some information on the relationship between the dough characteristics and the thermogravimetric analysis outputs. The study is devoted to acquiring deeper knowledge about the thermophysical characteristics of doughs in the breadmaking industrial processes, where the controllability and the energy performances need to be improved. A deeper knowledge of the dough properties, in terms of measurable parameters, could help to decrease the amounts of off-specification products, resulting in a much more energy-efficient and sustainable processing.
Economic Growth, Public and Private Investment: A Comparative Study of China and the United States
Authors: Ari Ibrahim , Koc Muammer
Published: March 2020

Public and private investments play a central role in production functions by providing the required capital for development. There are many studies in the literature investigating the linear macroeconomic relations based on public and private investment in cross-country and country-specific analyses by focusing on various perspectives and methodologies. However, there is a gap in the literature in exploring nonlinear causal relations among public-private investment and economic growth, particularly in the U.S. and China, in order to comparatively discuss policy implementations and potential implications. To narrow the gap, this study investigates nonlinear causal relationships between public-private investment and gross domestic product in the U.S. and China, which are the largest economies comprising about 40 percent of the global gross domestic product (GDP) in 2018. These countries show a similar pattern in economic growth and implementing sustainable development goals, although they follow considerably different socio-economic regimes and fall into different development levels (i.e., developed and developing countries). Therefore, there should be a common underlying mechanism in macroeconomic factors that fosters economic development. In this regard, the motivation behind the study is to reveal a common, but hidden, behavior of the nonlinear causal relations of given macroeconomic factors in these countries to make recommendations about sustainable economic growth for policymakers. To this end, there are three main contributions of the paper. First, the research finds nonlinear dependencies in the related time series between 1960–2015, thereby nonlinear causality tests are performed to reach more reliable information than the linear causality. Second, the study formulates a feedback loop between public and private investment through economic growth, which indicates that public and private investment should stimulate each other directly or indirectly (i.e., through the GDP). Third, the direction of the causality does not affect sustainable economic growth as long as it exists directly or indirectly.
Consumers’ Perceptions and Attitudes toward Products Preventing Microfiber Pollution in Aquatic Environments as a Result of the Domestic Washing of Synthetic Clothes
Authors: Herweyers Laure , Catarci Carteny Camilla , Scheelen Linda , Watts Regan , Du Bois Els
Published: March 2020

Microfibers released by synthetic clothes have a significant negative effect on the environment. Several solutions have been proposed and evaluated for their effectiveness, but studies have failed to address the human-centered aspects of these products. In this research, the possibilities and needs from a consumer perspective for a new filtering system for domestic washing machines were examined. First, a quantitative (questionnaire) and a qualitative (interviews and observations) exploration were done to understand the desired requirements from a user perspective. Next, the acceptance of various existing solutions for microfiber catching was investigated. To verify these requirements, a new concept was designed and evaluated with a questionnaire. The results were analyzed using descriptive statistics. It can be concluded that the problem of microfibers is not well known, and the impact of people’s washing behavior is underestimated. Since microfibers are almost invisible, the effectiveness needed to be proven. Effectiveness is seen as the most important characteristic of a product that captures microfibers, followed by durability. Both factors ensure long-term usage. However, changing washing habits is not evident, and usage should be straightforward and user-friendly to save time, especially considering the new cleaning actions, which should be clear and unambiguous.