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The exponential rise in advanced software computing and low-cost hardware has broadened the horizon for the Internet of Medical Things (IoMT), interoperable e-Healthcare systems serving varied purposes including electronic healthcare records (EHRs) and telemedicine. However, being heterogeneous and dynamic in nature, their database security remains a challenge forever. Numerous intrusion attacks including bot-attack and malware have confined major classical databases towards e-Healthcare. Despite the robustness of NoSQL over the structured query language databases, the dynamic data nature over a heterogeneous environment makes it vulnerable to intrusion attacks, especially over interoperable e-Healthcare systems. Considering these challenges, this work proposed a first of its kind semantic feature-driven NoSQL intrusion attack (NoSQL-IA) detection model for interoperable e-Healthcare systems. This work assessed the efficacy of the different semantic feature-extraction methods like Word2Vec, Continuous Bag of Words, N-Skip Gram (SKG), Count Vectorizer, TF-IDF, and GLOVE towards NoSQL-IA prediction. Subsequently, to minimize computational exhaustion, different feature selection methods including Wilcoxon Rank Sum Test (WRST), significant predictor test, principal component analysis, Select K-Best, and variance threshold feature selection algorithms were employed. To alleviate the data imbalance problem, it applied different resampling methods including upsampling, downsampling, and synthetic minority oversampling technique (SMOTE) over the selected features. Later, Min–Max normalization was performed over the input feature vectors to alleviate any possibility of overfitting. Towards NoSQL-IA prediction, different machine learning methods like Multinomial Naïve Bayes, decision tree, logistic regression, support vector machine, k-NN, AdaBoost, Extra Tree Classifier, random forest ensemble, and XG-Boost were applied, which classified each input query as the regular query or the NoSQL-IA attack query. The depth performance assessment revealed that the use of Word2Vec features SKG in sync with VTFS feature selection and SMOTE resampling processed with the bootstrapped random forest classifier can provide the best performance in terms of high accuracy (98.86%), F-Measure (0.974), and area under the curve (AUC) (0.981), thus enabling it suitable for interoperable e-Healthcare database security.

In the present work, Aspergillus niger was employed to produce commercially valuable malic acid from crude glycerol derived from waste cooking oil. Crude glycerol dosage, yeast extract dosage and initial pH were the influencing factors playing a significant role in the malic acid synthesis. The optimal condition for malic acid biosynthesis was studied by using response surface methodology. Further the feasibility analysis for biosynthesis of malic acid from crude glycerol was studied using the laboratory scale optimized data, with this experimentally optimized data, plant was simulated using SuperPro Designer (v10). The cost involved for malic acid synthesis per unit volume was likely expected to be $0.43/kg of malic acid using reactive extraction method. Thus, process optimization combined with techno-economical analysis of malic acid production could be beneficial.

Herbal infusions like ayurvedic aristas are widely consumed by Indian population for good health. With increasing awareness about radiological assessment, an effort was made to assess the radioactivity concentration of naturally occurring radionuclides in herbal medicines. (210)Po is an important alpha particle emitter contributing to internal dose to man from ingestion. Though (210)Po can be spontaneously deposited on silver disk for alpha spectrometric measurements with less radiochemical step, great care has to be taken during the sample pretreatment step owing to the high volatility of polonium even at low temperatures. Aim of the study was to evaluate an appropriate sample pretreatment method for estimation of polonium in herbal medicines. (209)Po was used for radiochemical yield calculation. Conventional open vessel wet ashing, physical evaporation, freeze-drying and microwave digestion in a Teflon vessel were examined. The recovery ranged between 9 and 79%. The lowest recovery was obtained for the samples that were processed by open vessel digestion without any volume reduction. The recoveries were comparable for those samples that were freeze dried and subjected to HNO3 + HClO4 + H2O2 + HF acid digestion and microwave digested samples. (210)Po concentration in the samples ranged from 11.3 to 39.6 mBq/L.

Successful infection with chikungunya virus (CHIKV) depends largely on the ability of this virus to manipulate cellular processes in its favour through specific interactions with several host factors. The knowledge of virus-host interactions is of particular value for understanding the interface through which therapeutic strategies could be applied. In the current study, the authors have employed a computational method to study the protein interactions between CHIKV and both its human host and its mosquito vector. In this structure-based study, 2028 human and 86 mosquito proteins were predicted to interact with those of CHIKV through 3918 and 112 unique interactions, respectively. This approach could predict 40 % of the experimentally confirmed CHIKV-host interactions along with several novel interactions, suggesting the involvement of CHIKV in intracellular cell signaling, programmed cell death, and transcriptional and translational regulation. The data corresponded to those obtained in earlier studies for HIV and dengue viruses using the same methodology. This study provides a conservative set of potential interactions that can be employed for future experimental studies with a view to understanding CHIKV biology.

Chandipura virus (CHPV) is an emerging rhabdovirus responsible for several outbreaks of fatal encephalitis among children in India. The characteristic structure of the virus is a result of extensive and specific interplay among its five encoded proteins. The revelation of interactions among CHPV proteins can help in gaining insight into viral architecture and pathogenesis. In the current study, we carried out comprehensive yeast two-hybrid (Y2H) analysis to elucidate intraviral protein-protein interactions. All of the interactions identified by Y2H were assessed for reliability by GST pull-down and ELISA. A total of eight interactions were identified among four viral proteins. Five of these interactions are being reported for the first time for CHPV. Among these, the glycoprotein (G)-nucleocapsid (N) interaction could be considered novel, as this has not been reported for any members of the family Rhabdoviridae. This study provides a framework within which the roles of the identified protein interactions can be explored further for understanding the biology of this virus at the molecular level.

Rhabdoviridae, characterized by bullet-shaped viruses, is known for its diverse host range, which includes plants, arthropods, fishes and humans. Understanding the viral-host interactions of this family can prove beneficial in developing effective therapeutic strategies. The host proteins interacting with animal rhabdoviruses have been reviewed in this report. Several important host proteins commonly interacting with animal rhabdoviruses are being reported, some of which, interestingly, have molecular features, which can serve as potential antiviral targets. This review not only provides the generalized importance of the functions of animal rhabdovirus-associated host proteins for the first time but also compares them among the two most studied viruses, i.e. Rabies virus (RV) and Vesicular Stomatitis virus (VSV). The comparative data can be used for studying emerging viruses such as Chandipura virus (CHPV) and the lesser studied viruses such as Piry virus (PIRYV) and Isfahan virus (ISFV) of the Rhabdoviridae family.

Purpose: Mukta Shukti (Pearl oyster shell); a sudha varga dravya, attains better therapeutic properties with proper sodhana and marana processes. It is indicated in Amlapitta, Parinamashoola and Annadravashoola. Acharya Susruta mentioned; Amla is the property of Vidagdha Pitta. The term Amlapitta may be correlated with Acid reflux syndrome which comprises of various types of Gastro esophageal reflux diseases like Gastritis, Peptic ulcer etc. A peptic ulcer is a sore on the lining of the stomach or duodenum, the beginning of the small intestine. A bacterium called Helicobacter pylori is a major cause of peptic ulcers. An attempt was made in this regard to establish standards to assure quality and to assess antiulcer activity of Mukta Sukti Bhasma. Method: Mukta sukti Bhasma prepared as per Rasatarangini and subjected to Atomic absorption spectroscopy (AAS) and X ray diffraction (XRD). Anti ulcer activity of Mukta sukti Bhasma in Albino rats by Aspirin induced gastric ulcer. Sucralfate as standard group and normal food water as control group used for the comparison. Result: Mukta sukti Bhasma showed highly significant Anti ulcer activity than control group. The alkaline pH and chemical components might have contributed by inhibiting secretions, neutralizing the acidity and reducing size of the ulcerative lesions. Presence of Calcium (Ca), Magnesium (Mg), Manganese (Mn), Iron (Fe), Potassium (K), Aluminum (Al), Copper (Cu), Sodium (Na) and Zinc (Zn) were detected in raw Mukta sukti and Mukta sukti Bhasma. X ray diffraction shown face centered Cubic, hexagonal, tetragonal and monoclinic crystal structures. Conclusion: In aspirin induced model, the Mukta sukti Bhasma and standard group (Sucralfate) showed highly significant Anti ulcer activity than control group (food water). The Mukta sukti Bhasma showed highly significant Anti ulcer activity than standard group (Sucralfate) when compared. This experimental study has given scientific evidence for the claim in the ancient text regarding the Anti ulcer property of Mukta sukti Bhasma which gives scope for conducting clinical study.