Novel Organotin(IV)-Schiff Base Complexes: Synthesis, Characterization, Antimicrobial Activity, and DNA Interaction Studies

Four organotin(IV) complexes with 2-(2-hydroxybenzylideneamino)isoindoline-1,3-dione (L1), and 4-(4-hydroxy-3-methoxybenzylideneamino-N-(pyrimidin-2-yl)benzenesulfonamide (L2) were synthesized and well characterized by analytical and spectral studies. The synthesized compounds were tested for antimicrobial activity by disc diffusion method. The DNA binding of the complexes 1 and 3 with CT-DNA has been performed with absorption spectroscopy, which showed that both the complexes are avid binders of CT-DNA. Also the nuclease activity of complexes 1 and 3 with plasmid DNA (pUC19) was studied using agarose gel electrophoresis. The complex 1 can act as effective DNA cleaving agent when compared to complex 3 resulting in the nicked form of DNA under physiological conditions. The gel was run both in the absence and presence of the oxidizing agent

What Can We Learn Privately?

Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept classes can be learned privately, namely, by an algorithm whose output does not depend too heavily on any one input or specific training example? More precisely, we investigate learning algorithms that satisfy differential privacy, a notion that provides strong confidentiality guarantees in contexts where aggregate information is released about a database containing sensitive information about individuals. We demonstrate that, ignoring computational constraints, it is possible to privately agnostically learn any concept class using a sample size approximately logarithmic in the cardinality of the concept class. Therefore, almost anything learnable is learnable privately: specifically, if a concept class is learnable by a (non-private) algorithm with polynomial sample complexity and output size, then it can be learned privately using a polynomial number of samples. We also present a computationally efficient private PAC learner for the class of parity functions. Local (or randomized response) algorithms are a practical class of private algorithms that have received extensive investigation. We provide a precise characterization of local private learning algorithms. We show that a concept class is learnable by a local algorithm if and only if it is learnable in the statistical query (SQ) model. Finally, we present a separation between the power of interactive and noninteractive local learning algorithms.Comment: 35 pages, 2 figure

Alternative Derivations in (1,1) Rings

Objectives: To show the associativity in one of the subclass of non-associative (γ,δ) rings. Method: Derivation alternator rings are limiting case of associative rings. The ring (1,1) is one of the sub class of (γ,δ) rings. Consider a (1,1) derivation alternator ring R, with characteristic ≠ 2, and it is well known that this ring is neither alternative nor flexible. In this paper it will be proved that right alternative property (R,x,x) holds in R and flexibility follows, finally associativity arrives in R. Findings: If this ring R does not contain nilpotent elements even though it will be associative. Novelty: Further investigators may extend the applications of these rings in science and engineering fields. Mathematics Subject Classification: 2010 MSC 17

OPTIMIZATION OF CULTURE CONDITIONS OF STREPTOMYCES CARPATICUS (MTCC-11062) FOR THE PRODUCTION OF ANTIMICROBIAL COMPOUND

Objective: To improve the antimicrobial compound productivity of Streptomyces carpaticus (MTCC-11062) by optimizing its physical and chemical parameters Methods: Streptomyces carpaticus (MTCC-11062) was isolated from Visakhapatnam sea coast of Bay of Bengal and was screened for its antimicrobial activity by using agar well diffusion method. To improve the production of antimicrobial compound the medium composition and physical parameters were optimized and its productivity was studied against Bacillus cereus (MTCC 430) Escherichia coli (MTCC 443), Candida albicans (MTCC 227) obtained from MTCC, Chandigarh, India. Results: Optimum growth of mycelium and antimicrobial compound production occurred at pH 7.2, agitation 180 rpm and temperature 300C with glucose 10g/L, soyabean meal 2.5g/L, K2HPO4 2g/L, MgSO4 1g/L, NaCl 7.5g/L and trace salts. Conclusion: The optimization of cultural conditions proposed in this paper has effetely improved the antimicrobial compound productivity of Streptomyces carpaticus (MTCC-11062)

Bio prospecting of Lapachol producing endophytic fungi

Background: The association of endophytic fungi with medicinal plants has been one of the evolving areas of research in the past few decades. The secondary metabolites produced owing to such associations have been recognised for a wide range of biological activities. Objectives: The aim of the present review is to highlight the isolation of lapachol from endophytic microorganisms with an emphasis on its biotransformation to improve its efficacy. Methodology: The researchers followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. Published scientific articles on endophytes, host-pathogen interaction and lapachol isolation were collected from reputed journals from 1960 to 2022 using electronic databases using the key words as stated. Following that, the authors chose the required papers based on the criteria they devised. The data was extracted using the common research elements found in the publications. Results and discussion: Lapachol is one such secondary metabolite known for potent antitumor properties. Synthesis of lapachol and its isolation from plant sources have been reported but an expensive process. Therefore, bioprospecting of this metabolite from endophytic fungi have been evaluated by a few researchers. It has been identified that A. niger and Alternaria alternata along with some of the filamentous endophytic fungi have been identified to produce lapachol. Some findings of biotransformation of lapachol to render it more potent have also been reported in the present review. Conclusion: Lapachol is one of the plant secondary metabolites that possess several therapeutic benefits. Owing to its isolation being highly expensive from plant sources, endophytes have been exploited. Furthering to the isolation, the biotrasformation of this bioactive molecule to enhance its efficiency has proven to be useful. In this regard, this review has enlightened some of the biotransformed lapachol and its derivatives with special emphasis on the endophytes that produce them. This review comprehensively highlights the various endophytic sources for lapachol production and its biotransformed derivatives

Information needs assessment in digital environment

The information needs represent gaps in the current knowledge of the user. The professional can assess the information needs of clientele at two levels: first, by analyzing the characteristics of the community served; and second, by analyzing the needs of specific individuals when and where they seek information. Assessment of information need typically occurs through a communication process called interview of information user. The process of assessment of information need through interview can be divided in eight stages. These are determining the purpose, researching the topic, selecting interviewees, structuring the interview, conducting the interview, preparing the report, presenting the report and feedback & further refinement. These have been changed in digital era due to introduction of Internet, e-mail, online groups and blogs. Identifying information needs is a complex process as some of the respondents may think that it is a wastage of time as it is a somewhat time taking process and may attempt to test whether the information provider will provide the information or not. This paper takes up the change brought up due to introduction of digital means in all the eight steps mentioned in assessment of information need through interview

In silico examination of peptides containing selenium and ebselen Backbone To Assess Their Tumoricidal Potential

Introduction: Cancer has been one of the highest causes of morbidity and mortality in the world for decades. Owing to improved therapeutics along with detection, breast cancer mortality has been slowly reducing. The incidence of breast cancer, on the other hand, has increased gradually. More than 100 types of cancer have been identified with a wide range of treatment protocols comprising of chemotherapy, radiation therapy, hormone therapy, etc. In an attempt to curb the serious deleterious effects caused by the chemotherapeutic drugs, numerous peptide molecules are currently popular as alternatives to the standard chemotherapeutic drugs. Methods: In this study, we have carried out in silico investigations to ascertain the anti-proliferative potential of novel peptides based on selenium and ebselen, i.e. Eb-Trp-Asp, 13, Eb-Trp-Glu, 14, and Eb-Trp-Lys, 15. Analysis of protein-ligand interactions, resulting in protein-ligand complex formation, has been carried out using the AutoDockVina in PyRx aided molecular docking technique, which may be an essential indication of druggability of the test peptides. Results: The molecular docking results revealed that the screened ligands had extraordinarily strong binding interactions and affinity for the target. Conclusion: Findings suggested that novel peptide molecule Eb-Trp-Glu, 14 may be a potent anticancer agent

Artificial intelligence and Machine Learning based Techniques in Analyzing the COVID-19 Gene Expression data: A Review

The novel Coronavirus associated with respiratory illness has become a new threat to human health as it is spreading very rapidly among the human population. Scientists and healthcare specialists throughout the world are still looking for a breakthrough technology to help combat the Covid-19 outbreak, despite the recent worldwide urgency. The use of Machine Learning (ML) and Artificial Intelligence (AI) in earlier epidemics has encouraged researchers by providing a fresh approach to combating the latest Coronavirus pandemic. This paper aims to comprehensively review the role of AI and ML for analysis of gene expressed data of COVID-1

Studies on soil fertility status of coffee growing regions in Wayanad district

Top soil in Wayanad region is prone to disturbance and erosion, as the coffee growers’ practice scraping, scuffling and cover digging. It isnecessary to conserve the inherent fertility of top soil by minimum disturbance during farming operations. Otherwise soil deterioration can become one of the major constraints for crop production in the present day exploitative cultivation of plantation crops. It is well known that nutrient availability is influenced by their distribution in the soil as well as other soil characteristics. Soil fertility is the key to meet the nutrient requirement of the crops. Soil test based nutrient management will increase the crop productivity there by helping to save the fertility. The study, carried out to understand the fertility status of the coffee soils, revealed a higher acidity (98%) with deficiencies of calcium (32%), magnesium (96%) and boron (31%) limiting the coffee productivity in the district. The coffee area in the district is strongly acidic (69%) due to lack of liming and continuous use of acid producing fertilizers. Fifty per cent of soil sampleswere high in phosphorus which in turn impair the nutrient balance and affects micronutrient absorption by plants. Deficiency of calcium and magnesium affects uptake of other nutrients which upsets cellular functions. In coffee, boron deficiency will reduce the productivity by affecting flowering and fruit set. Amelioration of soil acidity and optimal use of major, secondary and micronutrients are must to enhance coffee productivity in the district. Application of manures and fertilizers based on soil test values will save the fertilizers and also sustain the soil health. Integrated management of plant nutrients is essential to achieve sustainable coffee crop production

Volatile organic compound emissions in free-range chicken production: Impacts on environment, welfare and sustainability

The increasing demand for free-range poultry products has led to a surge in their availability in the market, prompting a potential decline in premium prices associated with these products. This shift places considerable pressure on upstream costs in chicken production. A comprehensive under-standing of its impact on the environment is essential to ensure the success of commercial and industrial free-range chicken production. However, there exists a significant knowledge gap concerning the emission and concentrations of volatile organic compounds (VOCs) from organic-free range chicken, and their environmental implications have yet to be understood. We aim to address this critical knowledge gap by elucidating the role of VOC emissions in chicken production and assessing their impact on human and animal health, as well as environmental challenges. Understanding the implications of VOC emissions is essential for promoting sustainable and responsible free-range chicken farming practices. By identifying the sources of VOC emissions and their impacts, stakeholders can implement appropriate measures to optimize air quality and enhance the well-being of chickens and workers. Ultimately, this review highlights the role of VOCs in animal production, providing valuable insights for improving the efficiency, environmental sustainability and welfare aspects of free-range chicken farming