Antifungal activity of probiotic strain Lactiplantibacillus plantarum MYSN7 against Trichophyton tonsurans

The primary objective of this study was to assess the probiotic attributes and antifungal activity of lactic acid bacteria (LAB) against the fungus, Trichophyton tonsurans. Among the 20 isolates screened for their antifungal attributes, isolate MYSN7 showed strong antifungal activity and was selected for further analysis. The isolate MYSN7 exhibited potential probiotic characteristics, having 75 and 70% survival percentages in pH3 and pH2, respectively, 68.73% tolerance to bile, a moderate cell surface hydrophobicity of 48.87%, and an auto-aggregation percentage of 80.62%. The cell-free supernatant (CFS) of MYSN7 also showed effective antibacterial activity against common pathogens. Furthermore, the isolate MYSN7 was identified as Lactiplantibacillus plantarum by 16S rRNA sequencing. Both L. plantarum MYSN7 and its CFS exhibited significant anti-Trichophyton activity in which the biomass of the fungal pathogen was negligible after 14 days of incubation with the active cells of probiotic culture (10⁶ CFU/ml) and at 6% concentration of the CFS. In addition, the CFS inhibited the germination of conidia even after 72 h of incubation. The minimum inhibitory concentration of the lyophilized crude extract of the CFS was observed to be 8 mg/ml. Preliminary characterization of the CFS showed that the active component would be organic acids in nature responsible for antifungal activity. Organic acid profiling of the CFS using LC-MS revealed that it was a mixture of 11 different acids, and among these, succinic acid (9,793.60 μg/ml) and lactic acid (2,077.86 μg/ml) were predominant. Additionally, a scanning electron microscopic study revealed that CFS disrupted fungal hyphal structure significantly, which showed scanty branching and bulged terminus. The study indicates the potential of L. plantarum MYSN7 and its CFS to control the growth of T. tonsurans. Furthermore, in vivo studies need to be conducted to explore its possible applications on skin infections.

Chloroplasts alter their morphology and accumulate at the pathogen interface during infection by Phytophthora infestans

Upon immune activation, chloroplasts switch off photosynthesis, produce antimicrobial compounds and associate with the nucleus through tubular extensions called stromules. Although it is well established that chloroplasts alter their position in response to light, little is known about the dynamics of chloroplast movement in response to pathogen attack. Here, we report that during infection with the Irish potato famine pathogen Phytophthora infestans, chloroplasts accumulate at the pathogen interface, associating with the specialized membrane that engulfs the pathogen haustorium. The chemical inhibition of actin polymerization reduces the accumulation of chloroplasts at pathogen haustoria, suggesting that this process is partially dependent on the actin cytoskeleton. However, chloroplast accumulation at haustoria does not necessarily rely on movement of the nucleus to this interface and is not affected by light conditions. Stromules are typically induced during infection, embracing haustoria and facilitating chloroplast interactions, to form dynamic organelle clusters. We found that infection-triggered stromule formation relies on BRASSINOSTEROID INSENSITIVE 1-ASSOCIATED KINASE 1 (BAK1)-mediated surface immune signaling, whereas chloroplast repositioning towards haustoria does not. Consistent with the defense-related induction of stromules, effector-mediated suppression of BAK1-mediated immune signaling reduced stromule formation during infection. On the other hand, immune recognition of the same effector stimulated stromules, presumably via a different pathway. These findings implicate chloroplasts in a polarized response upon pathogen attack and point to more complex functions of these organelles in plant-pathogen interactions.

Artificial neural network based modelling approach for municipal solid waste gasification in a fluidized bed reactor

In this paper, multi-layer feed forward neural networks are used to predict the lower heating value of gas (LHV), lower heating value of gasification products including tars and entrained char (LHV_p) and syngas yield during gasification of municipal solid waste (MSW) during gasification in a fluidized bed reactor. These artificial neural networks (ANNs) with different architectures are trained using the Levenberg-Marquardt (LM) back-propagation algorithm and a cross validation is also performed to ensure that the results generalise to other unseen datasets. A rigorous study is carried out on optimally choosing the number of hidden layers, number of neurons in the hidden layer and activation function in a network using multiple Monte Carlo runs. Nine input and three output parameters are used to train and test various neural network architectures in both multiple output and single output prediction paradigms using the available experimental datasets. The model selection procedure is carried out to ascertain the best network architecture in terms of predictive accuracy. The simulation results show that the ANN based methodology is a viable alternative which can be used to predict the performance of a fluidized bed gasifier.

Fractional order fuzzy control of hybrid power system with renewable generation using chaotic PSO

This paper investigates the operation of a hybrid power system through a novel fuzzy control scheme. The hybrid power system employs various autonomous generation systems like wind turbine, solar photovoltaic, diesel engine, fuel-cell, aqua electrolyzer etc. Other energy storage devices like the battery, flywheel and ultra-capacitor are also present in the network. A novel fractional order (FO) fuzzy control scheme is employed and its parameters are tuned with a particle swarm optimization (PSO) algorithm augmented with two chaotic maps for achieving an improved performance. This FO fuzzy controller shows better performance over the classical PID, and the integer order fuzzy PID controller in both linear and nonlinear operating regimes. The FO fuzzy controller also shows stronger robustness properties against system parameter variation and rate constraint nonlinearity, than that with the other controller structures. The robustness is a highly desirable property in such a scenario since many components of the hybrid power system may be switched on/off or may run at lower/higher power output, at different time instants.

Multi-objective LQR with optimum weight selection to design FOPID controllers for delayed fractional order processes

An optimal trade-off design for fractional order (FO)-PID controller is proposed with a Linear Quadratic Regulator (LQR) based technique using two conflicting time domain objectives. A class of delayed FO systems with single non-integer order element, exhibiting both sluggish and oscillatory open loop responses, have been controlled here. The FO time delay processes are handled within a multi-objective optimization (MOO) formalism of LQR based FOPID design. A comparison is made between two contemporary approaches of stabilizing time-delay systems withinLQR. The MOO control design methodology yields the Pareto optimal trade-off solutions between the tracking performance and total variation (TV) of the control signal. Tuning rules are formed for the optimal LQR-FOPID controller parameters, using median of the non-dominated Pareto solutions to handle delayed FO processes.

Symbolic representation for analog realization of a family of fractional order controller structures via continued fraction expansion

This paper uses the Continued Fraction Expansion (CFE) method for analog realization of fractional order differ-integrator and few special classes of fractional order (FO) controllers viz. Fractional Order Proportional-Integral-Derivative (FOPID) controller, FO[PD] controller and FO lead-lag compensator. Contemporary researchers have given several formulations for rational approximation of fractional order elements. However, approximation of the controllers studied in this paper, due to having fractional power of a rational transfer function, is not available in analog domain; although its digital realization already exists. This motivates us for applying CFE based analog realization technique for complicated FO controller structures to get equivalent rational transfer functions in terms of the controller tuning parameters. The symbolic expressions for rationalized transfer function in terms of the controller tuning parameters are especially important as ready references, without the need of running CFE algorithm every time and also helps in the synthesis of analog circuits for such FO controllers.

Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier

A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well.

Performance comparison of optimal fractional order hybrid fuzzy PID controllers for handling oscillatory fractional order processes with dead time

Fuzzy logic based PID controllers have been studied in this paper, considering several combinations of hybrid controllers by grouping the proportional, integral and derivative actions with fuzzy inferencing in different forms. Fractional order (FO) rate of error signal and FO integral of control signal have been used in the design of a family of decomposed hybrid FO fuzzy PID controllers. The input and output scaling factors (SF) along with the integro-differential operators are tuned with real coded genetic algorithm (GA) to produce optimum closed loop performance by simultaneous consideration of the control loop error index and the control signal. Three different classes of fractional order oscillatory processes with various levels of relative dominance between time constant and time delay have been used to test the comparative merits of the proposed family of hybrid fractional order fuzzy PID controllers. Performance comparison of the different FO fuzzy PID controller structures has been done in terms of optimal set-point tracking, load disturbance rejection and minimal variation of manipulated variable or smaller actuator requirement etc. In addition, multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used to study the Pareto optimal trade-offs between the set point tracking and control signal, and the set point tracking and load disturbance performance for each of the controller structure to handle the three different types of processes.

Multi-objective optimization framework for networked predictive controller design

Networked Control Systems (NCSs) often suffer from random packet dropouts which deteriorate overall system's stability and performance. To handle the ill effects of random packet losses in feedback control systems, closed over communication network, a state feedback controller with predictive gains has been designed. To achieve improved performance, an optimization based controller design framework has been proposed in this paper with Linear Matrix Inequality (LMI) constraints, to ensure guaranteed stability. Different conflicting objective functions have been optimized with Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The methodology proposed in this paper not only gives guaranteed closed loop stability in the sense of Lyapunov, even in the presence of random packet losses, but also gives an optimization trade-off between two conflicting time domain control objectives.

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples.

Handling packet dropouts and random delays for unstable delayed processes in NCS by optimal tuning of PIλDμ controllers with evolutionary algorithms

The issues of stochastically varying network delays and packet dropouts in Networked Control System (NCS) applications have been simultaneously addressed by time domain optimal tuning of fractional order (FO) PID controllers. Different variants of evolutionary algorithms are used for the tuning process and their performances are compared. Also the effectiveness of the fractional order PI(λ)D(μ) controllers over their integer order counterparts is looked into. Two standard test bench plants with time delay and unstable poles which are encountered in process control applications are tuned with the proposed method to establish the validity of the tuning methodology. The proposed tuning methodology is independent of the specific choice of plant and is also applicable for less complicated systems. Thus it is useful in a wide variety of scenarios. The paper also shows the superiority of FOPID controllers over their conventional PID counterparts for NCS applications.

Migraine and depression: common pathogenetic and therapeutic ground?

Migraine and depression are recognized as comorbid disorders on the basis of several epidemiological data and on the possibility of shared mechanisms. On the other hand, there is a lack of studies concerning therapeutic strategies in patients with this comorbidity. The aim of this paper is to briefly review the literature about the migraine and depression comorbidity and on the putative common neurobiological mechanisms, as well to discuss the possible therapeutic options in treating patients with both disorders.

Tuning of an optimal fuzzy PID controller with stochastic algorithms for networked control systems with random time delay

An optimal PID and an optimal fuzzy PID have been tuned by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output for a networked control system (NCS). The tuning is attempted for a higher order and a time delay system using two stochastic algorithms viz. the Genetic Algorithm (GA) and two variants of Particle Swarm Optimization (PSO) and the closed loop performances are compared. The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers.

Enhancement of manumycin A-induced apoptosis by methoxyamine in myeloid leukemia cells

Farnesyltransferase inhibitors (FTIs) are currently under investigation for leukemia treatment. We evaluated the FTI manumycin A (manumycin) in two myeloid leukemia cell lines (U937 and HL-60). Manumycin induced nitric oxide production and apoptosis of the leukemia cells. Nitric oxide or other reactive oxygen species may induce oxidative DNA damage, and the number of apurinic sites increased after manumycin treatment, which was reversed by concurrent treatment with N-acetyl-L-cysteine. Since repair of DNA damage is important to cell survival, we hypothesized that methoxyamine, an inhibitor of base-excision repair, would enhance the antineoplastic effect of manumycin. The combination of manumycin and methoxyamine resulted in enhanced apoptosis by six criteria increased annexin V binding, release of mitochondrial cytochrome c into the cytosol, activation of caspase-9, activation of caspase-3, specific cleavage of poly-adenosyl ribose polymerase, and increase in the sub-G1 cell cycle fraction. The drug combination enhanced inhibition on the soft agar clonogenic assay and on the formazan dye cell viability assay. The effects of manumycin or manumycin plus methoxyamine on apoptosis were blocked by N-acetyl-L-cysteine, and partially by nitric oxide synthase inhibitors or scavenger of peroxide. We conclude that methoxyamine enhances manumycin-induced apoptosis in myeloid leukemia cells.

Histopathological influence of alkaline ionized water on myocardial muscle of mother rats

We have reported that a marked necrosis and subsequent fibrosis of myocardium occurred among male rats 15 weeks old given alkaline ionized water (AKW) during gestation and suckling periods, and after weaning. In this study, it was examined whether similar lesions would occur in mother rats which were given AKW from day zero of gestation to day 20 of lactation. The myocardial lesion in the mother rats given AKW showed cell infiltration, vacuolation and fibrosis in the papillary muscle of the left ventricle, as were observed in male rats of 15 weeks old. Myocardial degeneration may cause a leakage of potassium into the blood that results in a higher concentration of potassium in the blood in the test group than in that of the control group given tap water.

Influences of alkaline ionized water on milk yield, body weight of offspring and perinatal dam in rats

The authors previously reported that male offspring of mothers rats given alkaline ionized water (AKW) showed a significantly higher body weight by day 14 after birth than did offspring of mother rats given tap water (TPW); furthermore, marked myocardial necrosis and fibrosis were observed particularly in the former male offspring at the age of 15 weeks. In the present experiment we looked for differences in bioparameters, namely the milk yield of mothers and suckled milk volume of the offspring, between the AKW- and the TPW-treated groups in order to reveal the factors which cause the unusual body weight gain in the offspring. Even though we were able to repeat our previous observation (the body weight of the male offspring of the AKW group increased significantly more by day 14 and 20 after birth and of the female by day 20 after birth than did that of the TPW group (p < 0.05), no significant difference was noted in any of the bioparameters, including those related to milk production and consumption. It is thus suspected that the water-hydrated cation, which was transferred either to the fetus through the placenta or to the offspring through the milk, might be the cause of the unusual body weight increase. Since calcium plays an important role in skeletal formation, it is tentatively concluded that the higher calcium concentration of AKW enriched the mother, serum calcium which was transferred to the fetus through the placenta and to the offspring through the milk.