Pathological Responses in Asian House Shrews (Suncus murinus) to the Naturally Acquired Orientia tsutsugamushi Infection.

Scrub typhus is a re-emerging disease caused by Orientia tsutsugamushi, transmitted by mites belonging to the family Trombiculidae. Humans and rodents acquire the infection by the bite of larval mites/chiggers. Suncus murinus, the Asian house shrew, has been reported to harbor the vector mites and has been naturally infected with O. tsutsugamushi. The present study aimed to localize and record O. tsutsugamushi in the tissues and the host response in shrews naturally infected with O. tsutsugamushi. Sheehan's modified May-Grunwald Giemsa staining was carried out in 365 tissues from 87 animals, and rickettsiae were documented in 87 tissues from 20 animals. Immunohistochemical (IHC) staining, using polyclonal antibodies raised against selected epitopes of the 56-kDa antigen, was carried out, and 81/87 tissue sections were tested positive for O. tsutsugamushi. By IHC, in addition to the endothelium, the pathogen was also demonstrated by IHC in cardiomyocytes, the bronchiolar epithelium, stroma of the lungs, hepatocytes, the bile duct epithelium, the epithelium and goblet cells of intestine, the tubular epithelium of the kidney, and splenic macrophages. Furthermore, the pathogen was confirmed by real-time PCR using blood (n = 20) and tissues (n = 81) of the IHC-positive animals. None of the blood samples and only 22 out of 81 IHC-positive tissues were tested positive by PCR. By nucleotide sequencing of the 56-kDa gene, Gilliam and Karp strains were found circulating among these animals. Although these bacterial strains are highly virulent and cause a wide range of pathological alterations, hence exploring their adaptive mechanisms of survival in shrews will be of significance. Given that the pathogen localizes in various organs following a transient bacteremia, we recommend the inclusion of tissues from the heart, lung, intestine, and kidney of reservoir animals, in addition to blood samples, for future molecular surveillance of scrub typhus.

Investigations of the performance of 3D printed micro wind turbine composed of PLA material.

Wind energy conversion systems (WECS) have gained increasing attention in recent years as promising renewable energy sources. Despite their potential, a clear research gap exists: the majority of WECS underperform in low wind speed conditions, limiting their applicability in many regions. To address this problem, this study proposes a novel approach by developing a 100 W micro wind turbine using Polylactic Acid (PLA) to generate efficient power in low wind speed conditions. The proposed wind turbine design employs Blade Element Momentum Theory (BEMT), which is commonly used for modeling wind turbine performance. Geometric design, mechanical analysis, and aerodynamic analysis are the fundamental considerations for designing any machine. In this work, the CREO 3.0 three-dimensional modeling software is used to create the geometric design of the proposed work. The airfoil SD7080 is selected due to its superior aerodynamic performance, and mechanical properties such as Young's modulus, density, and Poisson's ratio are attained to evaluate the wind blade's performance. Additionally, ANSYS 15.0 is used to conduct a detailed analysis of the proposed wind turbine, evaluating properties such as equivalent stress, deformation, and equivalent strain. Both simulation (ANSYS 15.0) and experimental setups are used to investigate the proposed wind turbine's performance, and the corresponding results are presented and discussed in this manuscript. The results indicate a significant performance improvement of the proposed wind blade when compared to conventional and ABS wind blades, demonstrating its potential as a more efficient solution for WECS. This proposed wind turbine design overcomes the problems like underprformance in low wind speed conditions and the wind turbine efficiency in all regions.

A secure edge computing model using machine learning and IDS to detect and isolate intruders.

The article presents a secure edge computing model that utilizes machine learning for intrusion detection and isolation. It addresses the security challenges arising from the rapid expansion of IoT and edge computing. The proposed Intrusion Detection System (IDS) combines Linear Discriminant Analysis (LDA) and Logistic Regression (LR) to swiftly and accurately identify intrusions without alerting neighboring devices. The model outperforms existing solutions with an accuracy of 96.56%, precision of 95.78%, and quick training time (0.04 s). It is effective against various types of attacks, enhancing the security of edge networks for IoT applications. •The methodology employs a hybrid model that combines LDA and LR for intrusion detection.•Machine learning techniques are used to analyze and identify intrusive activities during data acquisition by edge nodes.•The methodology includes a mechanism to isolate suspected devices and data without notifying neighboring edge nodes to prevent intruders from gaining control over the edge network.

Deep convolutional neural network and IoT technology for healthcare.

Background: Deep Learning is an AI technology that trains computers to analyze data in an approach similar to the human brain. Deep learning algorithms can find complex patterns in images, text, audio, and other data types to provide accurate predictions and conclusions. Neuronal networks are another name for Deep Learning. These layers are the input, the hidden, and the output of a deep learning model. First, data is taken in by the input layer, and then it is processed by the output layer. Deep Learning has many advantages over traditional machine learning algorithms like a KA-nearest neighbor, support vector algorithms, and regression approaches. Deep learning models can read more complex data than traditional machine learning methods. Objectives: This research aims to find the ideal number of best-hidden layers for the neural network and different activation function variations. The article also thoroughly analyzes how various frameworks can be used to create a comparison or fast neural networks. The final goal of the article is to investigate all such innovative techniques that allow us to speed up the training of neural networks without losing accuracy. Methods: A sample data Set from 2001 was collected by www.Kaggle.com. We can reduce the total number of layers in the deep learning model. This will enable us to use our time. To perform the ReLU activation, we will make use of two layers that are completely connected. If the value being supplied is larger than zero, the ReLU activation will return 0, and else it will output the value being input directly. Results: We use multiple parameters to determine the most effective method to test how well our method works. In the next paragraph, we'll discuss how the calculation changes secret-shared Values. By adopting 19 train set features, we train our reliable model to predict healthcare cost's (numerical) target feature. We found that 0.89503 was the best choice because it gave us a good fit (R2) and let us set enough coefficients to 0. To develop our stable model with this Set of parameters, we require 26 iterations. We use an R2 of 0.89503, an MSE of 0.01094, an RMSE of 0.10458, a mean residual deviance of 0.01094, a mean absolute error of 0.07452, and a root mean squared log error of 0.07207. After training the model on the train set, we applied the same parameters to the test set and obtained an R2 of 0.90707, MSE of 0.01045, RMSE of 0.10224, mean residual deviation of 0.01045, MAE of 0.06954, and RMSE of 0.07051, validating our solution approach. The objective value of our secured model is higher than that of the scikit-learn model, although the former performs better on goodness-of-fit criteria. As a result, our protected model performs quite well, marginally outperforming the (very optimized) scikit-learn model. Using a backpropagation algorithm and stochastic gradient descent, deep Learning develops artificial neural systems with several interconnected layers. There may be hidden layers of neurons in the network that have the tanh, rectification, and max-out hyperparameters. Modern features like momentum training, dropout, active learning rate, rate annealed, and L1 or L2 regularization provide exceptional prediction performance. The worldwide model's parameters are multi-threadedly (asynchronously) trained on the data from that node, and the model-based data is then gradually augmented by model averaging over the entire network. The method is executed on a single-node, direct H2O cluster initiated by the operator. The operation is parallel despite there just being a single node involved. The number of threads may be adjusted in the settings menu under Preferences and General. The optimal number of threads for the system is used automatically. Successful predictions in the healthcare data sets are made using the H2O Deep Learning operator. There will be a classification done since its label is binomial. The Splitting Validation operator creates test and training datasets to evaluate the model. By default, the settings of the Deep Learning activator are used. To put it another way, we'll construct two hidden layers, each containing 50 neurons. The Accuracy measure is computed by linking the annotated Sample Set with a Performer (Binominal Classification) operator. Table 3 displays the Deep Learning Model, the labeled data, and the Performance Vector that resulted from the technique. Conclusions: Deep learning algorithms can be used to design systems that report data on patients and deliver warnings to medical applications or electronic health information if there are changes in the patient's health. These systems could be created using deep Learning. This helps verify that patients get the proper effective care at the proper time for each specific patient. A healthcare decision support system was presented using the Internet of Things and deep learning methods. In the proposed system, we examined the capability of integrating deep learning technology into automatic diagnosis and IoT capabilities for faster message exchange over the Internet. We have selected the suitable Neural Network structure (number of best-hidden layers and activation function classes) to construct the e-health system. In addition, the e-health system relied on data from doctors to understand the Neural Network. In the validation method, the total evaluation of the proposed healthcare system for diagnostics provides dependability under various patient conditions. Based on evaluation and simulation findings, a dual hidden layer of feed-forward NN and its neurons store the tanh function more effectively than other NN. To overcome challenges, this study will integrate artificial intelligence with IoT. This study aims to determine the NN's optimal layer counts and activation function variations.

A Trust-Based Model for Secure Routing against RPL Attacks in Internet of Things.

In IoT networks, the de facto Routing Protocol for Low Power and Lossy Networks (RPL) is vulnerable to various attacks. Routing attacks in RPL-based IoT are becoming critical with the increase in the number of IoT applications and devices globally. To address routing attacks in RPL-based IoT, several security solutions have been proposed in literature, such as machine learning techniques, intrusion detection systems, and trust-based approaches. Studies show that trust-based security for IoT is feasible due to its simple integration and resource-constrained nature of smart devices. Existing trust-based solutions have insufficient consideration of nodes' mobility and are not evaluated for dynamic scenarios to satisfy the requirements of smart applications. This research work addresses the Rank and Blackhole attacks in RPL considering the static as well as mobile nodes in IoT. The proposed Security, Mobility, and Trust-based model (SMTrust) relies on carefully chosen trust factors and metrics, including mobility-based metrics. The evaluation of the proposed model through simulation experiments shows that SMTrust performs better than the existing trust-based methods for securing RPL. The improvisation in terms of topology stability is 46%, reduction in packet loss rate is 45%, and 35% increase in throughput, with only 2.3% increase in average power consumption.

Trust and Mobility-Based Protocol for Secure Routing in Internet of Things.

In the Internet of Things (IoT), the de facto Routing Protocol for Low Power and Lossy Networks (RPL) is susceptible to several disruptive attacks based on its functionalities and features. Among various RPL security solutions, a trust-based security is easy to adapt for resource-constrained IoT environments. In the existing trust-based security for RPL routing attacks, nodes' mobility is not considered or limited to only the sender nodes. Similarly, these trust-based protocols are not evaluated for mobile IoT environments, particularly regarding RPL attacks. Hence, a trust and mobility-based secure routing protocol is proposed, termed as SMTrust, by critically analysing the trust metrics involving the mobility-based metrics in IoT. SMTrust intends to provide security against RPL Rank and Blackhole attacks. The proposed protocol is evaluated in three different scenarios, including static and mobile nodes in an IoT network. SMTrust is compared with the default RPL objective function, Minimum Rank with Hysteresis Objective Function (MRHOF), SecTrust, DCTM, and MRTS. The evaluation results indicate that the proposed protocol outperforms with respect to packet loss rate, throughput, and topology stability. Moreover, SMTrust is validated using routing protocol requirements analysis to ensure that it fulfils the consistency, optimality, and loop-freeness.

Integrating Oxygen and 3D Cell Culture System: A Simple Tool to Elucidate the Cell Fate Decision of hiPSCs.

Oxygen, as an external environmental factor, plays a role in the early differentiation of human stem cells, such as induced pluripotent stem cells (hiPSCs). However, the effect of oxygen concentration on the early-stage differentiation of hiPSC is not fully understood, especially in 3D aggregate cultures. In this study, we cultivated the 3D aggregation of hiPSCs on oxygen-permeable microwells under different oxygen concentrations ranging from 2.5 to 20% and found that the aggregates became larger, corresponding to the increase in oxygen level. In a low oxygen environment, the glycolytic pathway was more profound, and the differentiation markers of the three germ layers were upregulated, suggesting that the oxygen concentration can function as a regulator of differentiation during the early stage of development. In conclusion, culturing stem cells on oxygen-permeable microwells may serve as a platform to investigate the effect of oxygen concentration on diverse cell fate decisions during development.

Intraosseous mucoepidermoid carcinoma of mandible: a rare case presentation and literature review.

Intraosseous mucoepidermoid carcinoma (IMC) is an atypical salivary gland neoplasm commonly seen in middle-aged adults. Their presentation in young individuals below the age group of 20 years is sporadic. Treatment modality mainly includes radical surgical resection for malignant tumours. There were only 13 reported cases of IMC of mandible below the age of 20 years in the English literature. All the reported cases were only managed with wide resection and radiotherapy. Surgical resection leads to loss of form and function in the young population, decreasing their morale. Hence, reconstruction should be mandated in young individuals for restoring function and aesthetics. We present a case of IMC of the mandible in a young female individual resected and reconstructed with a free fibula bone graft. Satisfactory healing is elicited with no recurrence at the 2-year follow-up period.

Failure to Detect Viral Ribonucleic Acid in Follicular Fluid of a Severe Acute Respiratory Syndrome Coronavirus 2-Infected Female - A Report from the Indian Subcontinent.

Till today, we are still not clear about the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on reproductive tissues and its vertical transmission through the gametes and embryos. There are few case reports that aim to detect the presence or absence of SARS-CoV-2 viral ribonucleic acid (RNA) in the follicular fluid of the infected females. We hereby present the case report of a 33-year-old woman who was undergoing intracytoplasmic sperm injection with testicular sperm aspiration and was found to be positive for SARS-CoV-2 infection. The follicular fluid analysis failed to detect the presence of viral RNA in the sample. Ours is the first case report from India trying to detect the viral RNA from the follicular fluid of a female with SARS-CoV-2 positive status.

Fatty acids-carotenoid complex: An effective anti-TB agent from the chlorella growth factor-extracted spent biomass of Chlorella vulgaris.

ETHNOPHARMACOLOGICAL RELEVANCE: The multidrug-resistant (MDR) pathogen, Mycobacterium tuberculosis, still remains as one of the major threat to mankind, despite the availability of a live attenuated vaccine and effective antibiotics. Marine microalgae, at all times, act as a key resource for valuable therapeutic compounds with limited side effects. AIM OF THE STUDY: The present explorative attempt is to isolate the biomolecules of pharmacological importance from the marine microalgae, Chlorella vulgaris, and to evaluate its effect on the ever dreadful disease, Tuberculosis. The study is also aimed to develop an economically feasible methodology for by-products extraction from microalgae. MATERIALS AND METHODS: Fatty acids-carotenoid complexes (FACC), namely, FACC-1 (red oil) and FACC-2 (brown oil) were isolated, in addition to lipid and lutein from the Chlorella Growth Factor (CGF, a protein fraction enriched with vitamins, minerals and carbohydrates)-extracted spent biomass through column chromatography. RESULTS: FACC-1 is a complex of fatty acids such as oleic and linoleic acids, and carotenoids such as canthaxanthin and neoxanthin. FACC-2 is a complex of oleic, linoleic and linolenic acids and carotenoids (cryptoxanthin and echinenone). Initial screening for evaluation of minimum bactericidal concentration (MBC) of FACC-1 and -2 was performed against Mycobacterium tuberculosis strains such as H37Rv, SHRE sensitive clinical isolate and SHRE resistant clinical isolate. MBC was noted at 10 µg/mL by FACC-1 and at 5 µg/mL by FACC-2, determined using colony forming and Lucipherase Reporter Mycobacteriophages (LRP) assay. Testing in the PAN sensitive isolates indicated that the MBC was noted at 5 µg/mL by FACC-1 and at 2.5 µg/mL by FACC-2. Complete inhibition (100%) was observed at 100 µg/mL by FACC-1 and at 50 µg/mL by FACC-2. Testing of FACC-1 and FACC-2 individually as well as in combination on two different types of MDR strains confirmed the efficacy of the algal oils, wherein in MDR-strain 1, FACC-1 revealed 50% inhibition at 10 µg/mL, while FACC-2 exhibited the same at 5 µg/mL. Conversely, in the case of MDR strain-2, MBC of FACC-1 was at 500 µg/mL and MBCof FACC-2 to be at 250 µg/mL. No significant synergistic effect was observed on combining both the oils. CONCLUSION: The study signifies the development of a potent therapeutic agent comprising of a complex of anti-TB agent (fatty acids) and antioxidants (carotenoids) from the CGF-extracted spent biomass of C. vulgaris.

Long-Lived, Transferred Crystalline Silicon Carbide Nanomembranes for Implantable Flexible Electronics.

Implantable electronics are of great interest owing to their capability for real-time and continuous recording of cellular-electrical activity. Nevertheless, as such systems involve direct interfaces with surrounding biofluidic environments, maintaining their long-term sustainable operation, without leakage currents or corrosion, is a daunting challenge. Herein, we present a thin, flexible semiconducting material system that offers attractive attributes in this context. The material consists of crystalline cubic silicon carbide nanomembranes grown on silicon wafers, released and then physically transferred to a final device substrate (e.g., polyimide). The experimental results demonstrate that SiC nanomembranes with thicknesses of 230 nm do not experience the hydrolysis process (i.e., the etching rate is 0 nm/day at 96 °C in phosphate-buffered saline (PBS)). There is no observable water permeability for at least 60 days in PBS at 96 °C and non-Na+ ion diffusion detected at a thickness of 50 nm after being soaked in 1× PBS for 12 days. These properties enable Faradaic interfaces between active electronics and biological tissues, as well as multimodal sensing of temperature, strain, and other properties without the need for additional encapsulating layers. These findings create important opportunities for use of flexible, wide band gap materials as essential components of long-lived neurological and cardiac electrophysiological device interfaces.

Canine babesiosis among working dogs of organised kennels in India: A comprehensive haematological, biochemical, clinicopathological and molecular epidemiological multiregional study.

Canine babesiosis is a serious disease among tick-borne haemoprotozoan diseases, globally. The present study was envisaged for carrying out thorough investigation of the disease among working dogs of organised kennels situated in different agro-climatic zones of India as comprehensive understanding of the disease from this country was pertinently lacking. During the study period of three years (2012-2014), 330 dogs suspected for babesiosis were examined for clinicopathology by their physical examination, haematological and biochemical parameters estimation, while the detection of apicomplexan parasites was confirmed by using various diagnostic techniques i.e. by conventional microscopy, by two different Babesia specific 18S rRNA based PCR protocols (conventional/simple PCR and nested PCR assays) followed by sequencing of obtained PCR amplicons for Babsesia spp. identification. Out of 330 clinical cases screened 5.15% (17/330), 9.09% (30/330) and 15.45% (51/330) were found to be positive in microscopic examination, simple- and nested- PCR assay, respectively. Comparative statistical analyses of these diagnostic assay results revealed that significant difference exists among the three diagnostic methodologies and thus it is recommended that the nested PCR technique be relied upon as a screening molecular assay and also for epidemiological studies of the disease in this country. Phylogenetic analysis based on 18S rRNA depicted the monophyletic nature and clonal expansion among all the B. gibsoni, under study. Sequencing results of PCR amplicons revealed that B. gibsoni has predominantly established itself over B. vogeli as former was incriminated in 47 cases while latter was confirmed in only four animals. Based on the clinical severity, these 51 affected animals were classified into three main groups' of 17 animals each viz., apparently healthy-, simple or uncomplicated babesiosis- and atypical or complicated babesiosis- group. Haematological and biochemical profiling of these dogs confirmed the characteristics findings of infection by both the Babesia spp. It was observed that the infection by small form of Babesia (B. gibsoni) is posing a significant therapeutic challenge and chemosterilization by commonly prescribed anti-protozoal drugs was not achieved as clinical relapses were often observed. The clinical signs, sequence based confirmation and severity of the infection suggested that there is a positive selection of B. gibsoni (smaller form) over B. vogeli (larger form) in this country and raises serious concerns as prognosis in former is considered to be poor compared to latter. Thus, these findings have opened new paradigms for planning of pragmatic control strategies against this emerging canine health problem.

Transparent crystalline cubic SiC-on-glass electrodes enable simultaneous electrochemistry and optical microscopy.

This work presents crystalline SiC-on-glass as a transparent, robust, and optically stable electrode for simultaneous electrochemical characterization and optical microscope imaging. Experimental results show a large potential window, as well as excellent stability and repeatability over multiple cyclic voltammetric scans in common redox biomarkers such as ruthenium hexaammine and methylene blue. The high optical transmittance and biocompatibility of SiC-on-glass were also observed, enabling cell culture, electrical stimulation, and high resolution fluorescence imaging. This new platform opens exciting opportunities in multi-functional biosensing-probes and observation.

Preventive Effect of Naringin on Metabolic Syndrome and Its Mechanism of Action: A Systematic Review.

BACKGROUND: Metabolic syndrome (MetS), which consists of cluster of conditions, hypertension, hyperlipidemia, hyperglycemia, and visceral obesity, is affecting population worldwide. Studies have shown that plant derived flavonoids have the ability to alleviate MetS. Naringin is a type of glycoside flavonoid found in most plant and it plays a critical role in the treatment of MetS due to its antioxidant activity and ability to regulate cytokines. METHODS: A systematic review was done to study the effects of naringin on the metabolic diseases using electronic databases which include Ovid and Scopus using specific descriptors published from the year 2010 till present to provide updated literature on this field. The articles were assessed and chosen based on the criteria in which the mechanisms and effects of naringin on different metabolic diseases were reported. RESULTS: Thirty-four articles were identified which referred to the studies that correspond to the previously stated criteria. Subsequently after screening for the articles that were published after the year 2010, finally, 19 articles were selected and assessed accordingly. Based on the assessment, naringin could alleviate MetS by reducing visceral obesity, blood glucose, blood pressure, and lipid profile and regulating cytokines. CONCLUSIONS: Naringin is an antioxidant that appears to be efficacious in alleviating MetS by preventing oxidative damage and proinflammatory cytokine release. However, the dosage used in animal studies might not be achieved in human trials. Thus, adequate investigation needs to be conducted to confirm naringin's effects on humans.

Green synthesized silver nanoparticles: Catalytic dye degradation, in vitro anticancer activity and in vivo toxicity in rats.

In this study, silver nanoparticles were synthesized (AgNPs) using aqueous rhizome extract of Acorus calamus (ACRE) and evaluated their in vitro anticancer activity and in vivo toxicity in a Wistar rat model. The synthesized AgNPs showed good catalytic activity against different organic pollutant dyes. In vitro cytotoxic effects of AgNPs were assessed in Hep2, COLO 205 and SH-SY5Y cells using MTT assay. Further, the apoptotic changes induced by AgNPs in more susceptible Hep2 cells were observed through AO/EB, DCFH-DA, Rhodamine 123, PI/DAPI staining, oxidative stress markers and Western blotting. In vivo toxicity study revealed substantial alterations in the levels of serum biochemical markers including AST, ALT, LDH and inflammatory markers such as TNF-α and IL-6 on day 29 when rats treated with AgNPs as compared to control, however, these levels were restored to normal at the end of washout period on day 89. No remarkable changes were observed in liver oxidative stress enzymes. ICP-OES analysis indicated bio-distribution of silver in spleen (5.67 µg/g) and liver (4.98 µg/g) in rats treated with 10 mg/kg b.w of AgNPs on day 29 and elimination of silver from all organs was observed at the end of washout period on day 89. Histopathological analysis revealed no significant changes in kidney, spleen, lungs, heart, testis and brain with 5 and 10 mg/kg b.w of AgNP. However, 10 mg/kg b.w of AgNPs showed moderate degree of cell swelling and vacuolar degeneration in liver and these alterations were reverted back to normal at the end of washout period. Findings from this study signify green synthesized AgNPs at low concentrations might be useful in many ways with ecofriendly nature.

In vivo bio-distribution, clearance and toxicity assessment of biogenic silver and gold nanoparticles synthesized from Abutilon indicum in Wistar rats.

This study reports the bio-distribution and clearance of Abutilon indicum silver and gold nanoparticles (AIAgNPs and AIAuNPs) in Wistar rats. Rats in different groups were orally administered with 5 and 10 mg/Kg BW of AIAgNPs and AIAuNPs (size 1-25 nm) for 28 days and few were maintained until 58 days of washout period. Serum biochemical parameters were not changed significantly at both doses of AIAuNPs and at lower concentration of AIAgNPs. But, with 10 mg/Kg BW of AIAgNPs rats showed elevated levels of AST, ALP and ALT on day 29, however, these levels were restored to normal after washout period. Liver oxidative stress markers were not altered with the treatment of AIAgNPs and AIAuNPs. ICP-OES analysis indicated bio-distribution of Ag and Au more in liver, kidney and spleen on day 29 and was found cleared on day 59. Histological analysis of nine vital organs indicated normal tissue architecture at both doses of AIAuNPs and lower dose of AIAgNPs. While the rats treated with higher dose of AIAgNPs showed mild liver sinusoid cell swelling on day 29, which also was recovered on day 59. Findings of this preclinical study indicate biocompatible nature of biogenic nanoparticles supporting their future biomedical applications.

Neuroprotective effect of Valeriana wallichii rhizome extract against the neurotoxin MPTP in C57BL/6 mice.

Oxidative stress and inflammation are some of the contributing factors for dopaminergic neurodegeneration in Parkinson's disease (PD). Though Valeriana wallichii D.C. is known for its nervine activities its effect against PD is yet to be studied. This is the first report on the antioxidant and anti-inflammatory effect of V. wallichii rhizome extract (VWE) in MPTP induced PD mice. GC-MS analysis of VWE indicated the presence of phytoconstituents like isovaleric acid and acacetin. PD induced mice were treated orally with three different doses (50, 100 and 200mg/kg body weight (BW)) of VWE for 14 days and their behavioural changes were studied on days 0, 8, 13 and 21. The levels of striatal dopamine, mid brain tyrosine hydroxylase positive (TH(+)) cell count, TH protein expression, reactive oxygen species (ROS), lipid peroxidation (LPO), antioxidants and inflammatory cytokines were analysed. Mid brain glial fibrillary acidic protein (GFAP) expression was assessed by immunohistochemistry and western blotting. Also mid brain histopathological analysis was performed. VWE treatment significantly recuperated the altered behavioural test scores, striatal dopamine levels, mid brain TH(+) cell count and TH protein levels, increased GFAP expression and the histopathological changes observed in PD mice. Similarly, diminished levels of antioxidants, elevated levels of ROS, LPO and inflammatory cytokines were also significantly ameliorated following VWE treatment. The effective dose of VWE was found to be 200mg/kg BW. Conclusively, V. wallichii rhizome extract has the potential to mitigate oxidative stress and inflammatory damage in PD.

Development and Validation of a UPLC Method by the QbD-Approach for the Estimation of Rabeprazole and Levosulpiride from Capsules.

Statistical experimental design was used to optimize the chromatographic separations of two pharmaceutical compounds from their respective potential impurities. A fractional factorial design was utilized to study the effects of pH, organic solvent in mobile phases A&B, and flow rate on the resolution of Rabeprazole and Rabeprazole Sulfone, which had closely eluting peaks. A desirability function applied to the optimized conditions predicted the peak resolution between 2.2 and 2.7 for the Rabeprazole & Rabeprazole Sulfone impurity. The chromatographic method employed an Acquity UPLC, BEH C18 column (100 × 2.1 mm i.d., 1.7 µm particle size) with the mobile phase consisting of a phosphate buffer, pH 6.5, and acetonitrile in a gradient program. The flow rate and injection volumes were 0.45 mL/min & 5 µl, respectively, and detection was done at 254 nm. The chromatographic method was validated for linearity, accuracy, precision, specificity, and ruggedness according to ICH guidelines. The results clearly showed that the quality by design concept could be effectively applied to optimize a UPLC chromatographic method with fewer trials and error-free experimentation.

A Single Gradient Stability-Indicating Reversed-Phase LC Method for the Estimation of Impurities in Omeprazole and Domperidone Capsules.

A gradient reversed-phase liquid chromatographic (RP-LC) method was developed for the quantitative estimation of impurities in the pharmaceutical dosage form of Omeprazole and Domperidone capsules. The developed method is a stability-indicating test method for the estimation of impurities generated during the formulation and storage of Omeprazole and Domperidone capsules. The chromatographic separation was achieved on a column packed with octadecyl silane, having a column length of 250 mm and diameter of 4.6 mm with a particle size of 5 µm, and by following a gradient program using a combination of a monobasic potassium phosphate buffer (0.05M) and acetonitrile. Since the spectral properties were similar, both compounds' individual impurities were estimated at 285 nm. Forced degradation studies were performed on Omeprazole pellets (enteric coated) and Domperidone pellets (SR coated) encapsulated in size '1' hard gelatin capsules. Omeprazole and Domperidone were degraded using acid hydrolysis (0.1 N hydrochloric acid), base (0.1 N sodium hydroxide), oxidation (50% hydrogen peroxide), heat (105 °C), and UV light (254 nm). The established method was validated and found to be linear, accurate, precise, specific, robust, and rugged.

Development and Validation of a Precise, Single HPLC Method for the Determination of Tolperisone Impurities in API and Pharmaceutical Dosage Forms.

A novel, sensitive, stability-indicating HPLC method has been developed for the quantitative estimation of Tolperisone-related impurities in both bulk drugs and pharmaceutical dosage forms. Effective chromatographic separation was achieved on a C18 stationary phase with a simple mobile phase combination delivered in a simple gradient programme, and quantitation was by ultraviolet detection at 254 nm. The mobile phase consisted of a buffer and acetonitrile delivered at a flow rate 1.0 ml/min. The buffer consisted of 0.01 M potassium dihydrogen phosphate with the pH adjusted to 8.0 by using diethylamine. In the developed HPLC method, the resolution between Tolperisone and its four potential impurities was found to be greater than 2.0. Regression analysis showed an R value (correlation coefficient) of greater than 0.999 for the Tolperisone impurities. This method was capable of detecting all four impurities of Tolperisone at a level of 0.19 µg/mL with respect to the test concentration of 1000 µg/mL for a 10 µl injection volume. The tablets were subjected to the stress conditions of hydrolysis, oxidation, photolysis, and thermal degradation. Considerable degradation was found to occur in base hydrolysis, water hydrolysis, and oxidation. The stress samples were assayed against a qualified reference standard and the mass balance was found to be close to 100%. The established method was validated and found to be linear, accurate, precise, specific, robust, and rugged.