Diseases have remained the major issue for shrimp aquaculture industry for decades by which different shrimp species demonstrated alternative disease resistance or tolerance. However, there had been insufficient studies on the underlying host mechanisms of such phenomenon. Hence, in this study, the main objective involves gaining a deeper understanding into the functional importance of shrimp STAT gene from the aspects of expression, sequence, structure, and associated genes. STAT gene was selected primarily because of its vital signalling roles in stress, endocrine, and immune response. The differential gene expressions of Macrobrachium rosenbergii STAT (MrST) and Penaeus monodon STAT (PmST) under White Spot Syndrome Virus (WSSV) and Vibrio parahaemolyticus/VpAHPND infections were identified through qPCR analysis. Notably, during both pathogenic infections, MrST demonstrated significant gene expression down-regulations (during either early or later post-infection time points) whereas PmST showed only significant gene expression up-regulations. Important sequence conservation or divergence was highlighted through STAT sequence comparison especially amino acid alterations at 614 aa [K (Lysine) to E (Glutamic Acid)] and 629 aa [F (Phenylalanine) to V (Valine)] from PmST (AY327491.1) to PmST (disease tolerant strain). There were significant differences observed between in silico characterized structures of MrST and PmST proteins. Important functional differentially expressed genes (DEGs) in the aspects of stress, endocrine, immune, signalling, and structural were uncovered through comparative transcriptomic analysis. The DEGs associated with STAT functioning were identified including inositol 1,4,5-trisphosphate receptor, hsp90, caspase, ATP binding cassette transmembrane transporter, C-type Lectin, HMGB, ALF1, ALF3, superoxide dismutase, glutathione peroxidase, catalase, and TBK1. The main findings of this study are STAT differential gene expression patterns, sequence divergence, structural differences, and associated functional DEGs. These findings can be further utilized for shrimp health or host response diagnostic studies. STAT gene can also be proposed as a suitable candidate for future studies of shrimp innate immune enhancement.
Intermittent preventive treatment (IPT) is used to reduce malaria morbidity and mortality, especially in vulnerable groups such as children and pregnant women. IPT with the fixed dose combination of piperaquine (PQ) and dihydroartemisinin (DHA) is being evaluated as a potential mass treatment to control and eliminate artemisinin-resistant falciparum malaria. This study explored alternative DHA-PQ adult dosing regimens compared to the monthly adult dosing regimen currently being studied in clinical trials. A time-to-event model describing the concentration-effect relationship of preventive DHA-PQ administration was used to explore the potential clinical efficacy of once-weekly adult dosing regimens. Loading dose strategies were evaluated and the advantage of weekly dosing regimen was tested against different degrees of adherence. Assuming perfect adherence, three tablets weekly dosing regimen scenarios maintained malaria incidence of 0.2 to 0.3% per year compared to 2.1 to 2.6% for all monthly dosing regimen scenarios and 52% for the placebo. The three tablets weekly dosing regimen was also more forgiving (i.e., less sensitive to poor adherence), resulting in a predicted ∼4% malaria incidence per year compared to ∼8% for dosing regimen of two tablets weekly and ∼10% for monthly regimens (assuming 60% adherence and 35% interindividual variability). These results suggest that weekly dosing of DHA-PQ for malaria chemoprevention would improve treatment outcomes compared to monthly administration by lowering the incidence of malaria infections, reducing safety concerns about high PQ peak plasma concentrations and being more forgiving. In addition, weekly dosing is expected to reduce the selection pressure for PQ resistance.
Previous molecular dynamic simulations have reported elongation of the existing beta-sheet in prion proteins. Detailed examination has shown that these elongations do not extend beyond the proline residues flanking these beta-sheets. In addition, proline has also been suggested to possess a possible structural role in preserving protein interaction sites by preventing invasion of neighboring secondary structures. In this work, we have studied the possible structural role of the flanking proline residues by simulating mutant structures with alternate substitution of the proline residues with valine. Simulations showed a directional inhibition of elongation, with the elongation progressing in the direction of valine including evident inhibition of elongation by existing proline residues. This suggests that the flanking proline residues in prion proteins may have a containment role and would confine the beta-sheet within a specific length.
A series of novel 2-amino-4-(3-hydroxy-4-phenoxyphenyl)-6-(4-substituted phenyl) nicotinonitriles were synthesized and evaluated against HepG2, A-549 and Vero cell lines. Compounds 3b (IC50 16.74 ± 0.45 µM) and 3p (IC50 10.57 ± 0.54 µM) were found to be the most active compounds against A-549 cell line among the evaluated compounds. Further 3b- and 3p-induced apoptosis was characterized by AO/EB (acridine orange/ethidium bromide) nuclear staining method and also by DNA fragmentation study. A decrease in cell viability and initiation of apoptosis was clearly evident through the morphological changes in the A-549 cells treated with 3b and 3p when stained with this method. Fragmentation of DNA into nucleosomes was observed which further confirmed the cell apoptosis in cells treated with compound 3b. Flow cytometry studies confirmed the cell cycle arrest at G2/M phase in A549 cells treated with compound 3b. Further in silico studies performed supported the in vitro anticancer activity of these compounds as depicted by dock score and binding energy values.
Cryopreservation is the most promising way for long-term storage of biological samples e.g., single cells and cellular structures. Among various cryopreservation methods, vitrification is advantageous by employing high cooling rate to avoid the formation of harmful ice crystals in cells. Most existing vitrification methods adopt direct contact of cells with liquid nitrogen to obtain high cooling rates, which however causes the potential contamination and difficult cell collection. To address these limitations, we developed a non-contact vitrification device based on an ultra-thin freezing film to achieve high cooling/warming rate and avoid direct contact between cells and liquid nitrogen. A high-throughput cell printer was employed to rapidly generate uniform cell-laden microdroplets into the device, where the microdroplets were hung on one side of the film and then vitrified by pouring the liquid nitrogen onto the other side via boiling heat transfer. Through theoretical and experimental studies on vitrification processes, we demonstrated that our device offers a high cooling/warming rate for vitrification of the NIH 3T3 cells and human adipose-derived stem cells (hASCs) with maintained cell viability and differentiation potential. This non-contact vitrification device provides a novel and effective way to cryopreserve cells at high throughput and avoid the contamination and collection problems.
Brain segmentation in magnetic resonance images (MRI) is an important stage in clinical studies for different issues such as diagnosis, analysis, 3-D visualizations for treatment and surgical planning. MR Image segmentation remains a challenging problem in spite of different existing artifacts such as noise, bias field, partial volume effects and complexity of the images. Some of the automatic brain segmentation techniques are complex and some of them are not sufficiently accurate for certain applications. The goal of this paper is proposing an algorithm that is more accurate and less complex).
Dairy farmers often keep almost all their newborn heifer calves despite the high cost of rearing. By rearing all heifer calves, farmers have more security and retain flexibility to cope with the uncertainty in the availability of replacement heifers in time. This uncertainty is due to mortality or infertility during the rearing period and the variation in culling rate of lactating cows. The objective of this study is to provide insight in the economically optimal number of heifer calves to be reared as replacements. A herd-level stochastic simulation model was developed specific for this purpose with a herd of 100 dairy cows; the biological part of the model consisted of a dairy herd unit and rearing unit for replacement heifers. The dairy herd unit included variation in the number of culled dairy cows. The rearing unit incorporated variation in the number of heifers present in the herd by including uncertainty in mortality and variation in fertility. The dairy herd unit and rearing unit were linked by the number of replacement heifers and culled dairy cows. When not enough replacement heifers were available to replace culled dairy cows, the herd size was temporarily reduced, resulting in an additional cost for the empty slots. When the herd size reached 100 dairy cows, the available replacement heifers that were not needed were sold. It was assumed that no purchase of cows and calves occurred. The optimal percentage of 2-wk-old heifer calves to be retained was defined as the percentage of heifer calves that minimized the average net costs of rearing replacement heifers. In the default scenario, the optimal retention was 73% and the total net cost of rearing was estimated at €40,939 per herd per year. This total net cost was 6.5% lower than when all heifer calves were kept. An earlier first-calving age resulted in an optimal retention of 75%, and the net costs of rearing were €581 per herd per year lower than in the default scenario. For herds with a lower or higher culling rate of dairy cows (10 or 40% instead of 25% in the default scenario), it was optimal to retain 35 or 100% of the heifer calves per year. Herds that had a lower or higher cost of empty slots (€50 or €120 per month instead of €82 in the default scenario) had an optimal retention of 49 or 83% per year; the optimal retention percentage was dependent on farm and herd characteristics. For Dutch dairy farming conditions, it was not optimal to keep all heifer calves.
Oil palm trunk (OPT) sap was utilized for growth and bioethanol production by Saccharomycescerevisiae with addition of palm oil mill effluent (POME) as nutrients supplier. Maximum yield (YP/S) was attained at 0.464g bioethanol/g glucose presence in the OPT sap-POME-based media. However, OPT sap and POME are heterogeneous in properties and fermentation performance might change if it is repeated. Contribution of parametric uncertainty analysis on bioethanol fermentation performance was then assessed using Monte Carlo simulation (stochastic variable) to determine probability distributions due to fluctuation and variation of kinetic model parameters. Results showed that based on 100,000 samples tested, the yield (YP/S) ranged 0.423-0.501g/g. Sensitivity analysis was also done to evaluate the impact of each kinetic parameter on the fermentation performance. It is found that bioethanol fermentation highly depend on growth of the tested yeast.
Traditional robotic work cell design and programming are considered inefficient and outdated in current industrial and market demands. In this research, virtual reality (VR) technology is used to improve human-robot interface, whereby complicated commands or programming knowledge is not required. The proposed solution, known as VR-based Programming of a Robotic Work Cell (VR-Rocell), consists of two sub-programmes, which are VR-Robotic Work Cell Layout (VR-RoWL) and VR-based Robot Teaching System (VR-RoT). VR-RoWL is developed to assign the layout design for an industrial robotic work cell, whereby VR-RoT is developed to overcome safety issues and lack of trained personnel in robot programming. Simple and user-friendly interfaces are designed for inexperienced users to generate robot commands without damaging the robot or interrupting the production line. The user is able to attempt numerous times to attain an optimum solution. A case study is conducted in the Robotics Laboratory to assemble an electronics casing and it is found that the output models are compatible with commercial software without loss of information. Furthermore, the generated KUKA commands are workable when loaded into a commercial simulator. The operation of the actual robotic work cell shows that the errors may be due to the dynamics of the KUKA robot rather than the accuracy of the generated programme. Therefore, it is concluded that the virtual reality based solution approach can be implemented in an industrial robotic work cell.
Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.
A series of hexahydro-1,6-naphthyridines were synthesized in good yields by the reaction of 3,5-bis[(E)-arylmethylidene]tetrahydro-4(1H)-pyridinones with cyanoacetamide in the presence of sodium ethoxide under simple mixing at ambient temperature for 6-10 minutes and were assayed for their acetylcholinesterase (AChE) inhibitory activity using colorimetric Ellman's method. Compound 4e with methoxy substituent at ortho-position of the phenyl rings displayed the maximum inhibitory activity with IC50 value of 2.12 μM. Molecular modeling simulation of 4e was performed using three-dimensional structure of Torpedo californica AChE (TcAChE) enzyme to disclose binding interaction and orientation of this molecule into the active site gorge of the receptor.
This research examines the precision of an adaptive neuro-fuzzy computing technique in estimating the anti-obesity property of a potent medicinal plant in a clinical dietary intervention. Even though a number of mathematical functions such as SPSS analysis have been proposed for modeling the anti-obesity properties estimation in terms of reduction in body mass index (BMI), body fat percentage, and body weight loss, there are still disadvantages of the models like very demanding in terms of calculation time. Since it is a very crucial problem, in this paper a process was constructed which simulates the anti-obesity activities of caraway (Carum carvi) a traditional medicine on obese women with adaptive neuro-fuzzy inference (ANFIS) method. The ANFIS results are compared with the support vector regression (SVR) results using root-mean-square error (RMSE) and coefficient of determination (R(2)). The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the ANFIS approach. The following statistical characteristics are obtained for BMI loss estimation: RMSE=0.032118 and R(2)=0.9964 in ANFIS testing and RMSE=0.47287 and R(2)=0.361 in SVR testing. For fat loss estimation: RMSE=0.23787 and R(2)=0.8599 in ANFIS testing and RMSE=0.32822 and R(2)=0.7814 in SVR testing. For weight loss estimation: RMSE=0.00000035601 and R(2)=1 in ANFIS testing and RMSE=0.17192 and R(2)=0.6607 in SVR testing. Because of that, it can be applied for practical purposes.
Simulation of fluidized bed reactor (FBR) was accomplished for treating wastewater using Fenton reaction, which is an advanced oxidation process (AOP). The simulation was performed to determine characteristics of FBR performance, concentration profile of the contaminants, and various prominent hydrodynamic properties (e.g., Reynolds number, velocity, and pressure) in the reactor. Simulation was implemented for 2.8 L working volume using hydrodynamic correlations, continuous equation, and simplified kinetic information for phenols degradation as a model. The simulation shows that, by using Fe(3+) and Fe(2+) mixtures as catalyst, TOC degradation up to 45% was achieved for contaminant range of 40-90 mg/L within 60 min. The concentration profiles and hydrodynamic characteristics were also generated. A subsequent scale-up study was also conducted using similitude method. The analysis shows that up to 10 L working volume, the models developed are applicable. The study proves that, using appropriate modeling and simulation, data can be predicted for designing and operating FBR for wastewater treatment.
Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.
Microbial strains optimization for the overproduction of desired phenotype has been a popular topic in recent years. The strains can be optimized through several techniques in the field of genetic engineering. Gene knockout is a genetic engineering technique that can engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, the complexities of the metabolic networks have made the process to identify the effects of genetic modification on the desirable phenotypes challenging. Furthermore, a vast number of reactions in cellular metabolism often lead to the combinatorial problem in obtaining optimal gene deletion strategy. Basically, the size of a genome-scale metabolic model is usually large. As the size of the problem increases, the computation time increases exponentially. In this paper, we propose Differential Bees Flux Balance Analysis (DBFBA) with OptKnock to identify optimal gene knockout strategies for maximizing the production yield of desired phenotypes while sustaining the growth rate. This proposed method functions by improving the performance of a hybrid of Bees Algorithm and Flux Balance Analysis (BAFBA) by hybridizing Differential Evolution (DE) algorithm into neighborhood searching strategy of BAFBA. In addition, DBFBA is integrated with OptKnock to validate the results for improving the reliability the work. Through several experiments conducted on Escherichia coli, Bacillus subtilis, and Clostridium thermocellum as the model organisms, DBFBA has shown a better performance in terms of computational time, stability, growth rate, and production yield of desired phenotypes compared to the methods used in previous works.
Thermal characteristics of turbulent nanofluid flow in a rectangular pipe have been investigated numerically. The continuity, momentum, and energy equations were solved by means of a finite volume method (FVM). The symmetrical rectangular channel is heated at the top and bottom at a constant heat flux while the sides walls are insulated. Four different types of nanoparticles Al2O3, ZnO, CuO, and SiO2 at different volume fractions of nanofluids in the range of 1% to 5% are considered in the present investigation. In this paper, effect of different Reynolds numbers in the range of 5000 < Re < 25000 on heat transfer characteristics of nanofluids flowing through the channel is investigated. The numerical results indicate that SiO2-water has the highest Nusselt number compared to other nanofluids while it has the lowest heat transfer coefficient due to low thermal conductivity. The Nusselt number increases with the increase of the Reynolds number and the volume fraction of nanoparticles. The results of simulation show a good agreement with the existing experimental correlations.
Level crossings are amongst the most complex of road safety issues, due to the addition of rail infrastructure, trains and train operations. The differences in the operational characteristics of different warning devices together with varying crossing, traffic or/and train characteristics, cause different driver behaviour at crossings. This paper compares driver behaviour towards two novel warning devices (rumble strips and in-vehicle audio warning) with two conventional warning devices (flashing light and stop sign) at railway level crossings using microsimulation modelling. Two safety performance indicators directly related to collision risks, violation and time-to-collision, were adopted. Results indicated the active systems were more effective at reducing likely collisions compared to passive devices. With the combined application of driving simulation and traffic microsimulation modelling, traffic safety performance indicators for a level crossing can be estimated. From these, relative safety comparisons for the different traffic devices are derived, or even for absolute safety evaluation with proper calibration from field investigations.
The present study deals with the functional severity of a coronary artery stenosis assessed by the fractional flow reserve (FFR). The effects of different geometrical shapes of lesion on the diagnostic parameters are unknown. In this study, 3D computational simulation of blood flow in three different geometrical shapes of stenosis (triangular, elliptical, and trapezium) is considered in steady and transient conditions for 70% (moderate), 80% (intermediate), and 90% (severe) area stenosis (AS). For a given percentage AS, the variation of diagnostic parameters which are derived from pressure drop across the stenosis was found in three different geometrical shapes of stenosis and it was observed that FFR is higher in triangular shape and lower in trapezium shape. The pressure drop coefficient (CDP) was higher in trapezium shape and lower in triangular model whereas the LFC shows opposite trend. From the clinical perspective, the relationship between percentage AS and FFR is linear and inversely related in all the three models. A cut-off value of 0.75 for FFR was observed at 76.5% AS in trapezium model, 79.5% in elliptical model, and 82.7% AS for the triangular shaped model. The misinterpretation of the functional severity of the stenosis is in the region of 76.5%-82.7 % AS from different shapes of stenosis models.
The seismic performance of RC columns could be significantly improved by continuous spiral reinforcement as a result of its adequate ductility and energy dissipation capacity. Due to post-earthquake brittle failure observations in beam-column connections, the seismic behaviour of such connections could greatly be improved by simultaneous application of this method in both beams and columns. In this study, a new proposed detail for beam to column connection introduced as "twisted opposing rectangular spiral" was experimentally and numerically investigated and its seismic performance was compared against normal rectangular spiral and conventional shear reinforcement systems. In this study, three full scale beam to column connections were first designed in conformance with Eurocode (EC2-04) for low ductility class connections and then tested by quasistatic cyclic loading recommended by ACI Building Code (ACI 318-02). Next, the experimental results were validated by numerical methods. Finally, the results revealed that the new proposed connection could improve the ultimate lateral resistance, ductility, and energy dissipation capacity.