Effect of antidiabetic drug metformin hydrochloride on micellization behavior of cetylpyridinium bromide in aqueous solution

Herein, the interaction of an antidiabetic drug, metformin hydrochloride (MHCl), and a cationic surfactant, cetylpyridinium bromide (CPB) is investigated in an aqueous medium. The critical micellar concentration (CMC) of CPB is estimated through conductivity experiments and found to be reduced on adding MHCl and further decreased in the presence of NaCl. The reduced CMC is attributed to the solubilization of MHCl by CPB through micellization and the micellization is found to be thermodynamically spontaneous that experiences an augmentation in the presence of NaCl. This is identified from the negative value of standard free energy (Δ G0m). The higher negative value of Δ G0m (-55.41 kJ mol-1) for CPB + MHCl + NaCl than CPB (-37.89 kJ mol-1) and CPB + MHCl (-34.08 kJ mol-1) is suggestive of the above phenomenon. The positive values of Δ S0m in all three cases confirm that the micellization is entropy driven. The binding of MHCl on CPB is quantified by estimating binding constant using the Benesi-Hildebrand (B-H) plot through UV-visible spectral methods. The binding constant values were calculated to be 2.70 M-1 for CPB + MHCl + NaCl compared to 1.258 M-1 for CPB + MHCl predicting a favoring of micellization in the presence of NaCl which is higher than that in the presence of co-solvents. The molecular interaction of MHCl and CPB is justified using FT-IR and NMR techniques. The surface properties of drug surfactant interactions are assessed using SEM techniques. The point of interaction between the drug and surfactant is visualized through the molecular docking approach. The results suggest that CPB would be an effective solubilizer for developing MHCl drug formulations.Communicated by Ramaswamy H. Sarma.

Constructing Z-scheme g-C3N4/TiO2 heterostructure for promoting degradation of the hazardous dye pollutants

The use of dyes and segments has increased widely in recent years, but it poses a serious health risk to ecosystems. In this work, TiO₂ and two-dimensional g-C₃N₄ nanosheets (g-CN) were fabricated through co-precipitation and thermal polymerization technique, respectively. The g-CN-TiO₂ photocatalyst (1: 3, 2: 2, 3: 1) in various weight percentages was prepared using a simple impregnation process. The photocatalytic behaviour of the g-CN, TiO₂ NPs, and different weight percentages of g-CN-TiO₂ photocatalyst was evaluated against methylene blue (MB) dye under UV-visible light illumination. Compared to pristine and other weight percentages of the g-CN-TiO₂ nanocomposite, the optimized g-CN-TiO₂ nanocomposite (3:1) showed promoted performance against MB dye. The enriched catalytic efficiency can be accredited to the low amount of TiO₂ nanoparticles deposited on gCN nanosheets, possibly due to the boosted transport properties of the electron-hole pairs. The enriched photocatalytic behaviour can be attributed to the development of the Z-scheme system between TiO₂ and g-CN. The current study is an outstanding demonstration of the development of maximum catalytic efficiency for destroying hazardous chemical dyes.

Silica nanoparticles derived from Arundo donax L. ash composite with Titanium dioxide nanoparticles as an efficient nanocomposite for photocatalytic degradation dye

Water pollution is a serious problem that threatens both developed and developing countries. Several methods have been used to purify contaminated water, among which the photocatalytic decomposition approach is widely used to purify contaminated water from organic pollutants. In this work, biomass derived SiO₂ nanoparticles composite with TiO₂ semiconductors used as an efficient photocatalyst for degradation of RhB dye molecules under UV-visible light irradiation is proclaimed. The different weight percentages of Arundo donax L. ash-derived SiO₂ nanoparticles combined with TiO₂ nanoparticles were prepared through the wet impregnation method. The photocatalytic degradation ability of the as-prepared samples has been scrutinized against the degradation of Rh B dye in which the pronounced photocatalytic degradation efficiency 93.7% is successfully achieved on 50 wt % SiO₂-50 wt % TiO₂ nanocomposite photocatalyst. The catalytic performance of the nanocomposite decreases with an increase of 50%-75% in SiO₂ nanoparticles. There could have been a decrease in degradation efficiency due to an excess amount of SiO₂ covering TiO₂ nanoparticles, which prevented photons from reaching the nanoparticles. The efficiency of cyclic decomposition of the 50 wt% SiO₂-50 wt% TiO₂ composite showed only a slight change in photocatalytic capacity compared to the first cycle, which ensures the durability of the sample. However, the hydroxyl radical species play the main role in the degradation process, which has been confirmed by the scavenger test. The probable reaction mechanism is also deliberated in detail. The high photocatalytic performance of novel eco-friendly SiO₂-TiO₂ photocatalyst make it ideal for water purification applications.

An enhanced Hidden Semi-Markov model for outlier detection in multivariate datasets

Outlier detection in multivariate data is one of the critical challenges in preprocessing phase. Many outlier detection methods have been emerged for the past few years to perform outlier detection efficiently in multivariate datasets. The prediction accuracy cannot be improved without proper outlier analysis and the prediction model might not confirm the expected behavior. The generation of huge data in real time applications makes the outlier detection process more crucial and challenging. Most of the currently available detection methods are based on mean and covariance that are not suitable for handling large volume of datasets, they are suitable for handlind static data and simple data to detect outliers. They cannot cope up with large scale data. So, there is a need for an efficient outlier detection model to detect the outliers in multivariate datasets. The primary objective of this research work is to develop a robust model for outlier detection in multivariate data. To achieve this, the work proposed an enhanced Hidden Semi-Markov Model (HSMM) which allows arbitrary time distribution in its states to detect outliers. The proposed work utilized six benchmark datasets and the performance is compared with several outlier detection algorithms such as HMM, iForest, FastABOD, and Expose. The work achieves 98.2 % of accuracy which is significantly better for detecting outliers in multivariate dataset. The proposed work improvised the percentage of acheivements between 2% to 25% than the currently available models.. The experimental analysis shows that the proposed model performs well than the currently available models in terms of accuracy, and receiver operation curve (ROC).

Characteristics of microplastics in the beach sediments of Marina tourist beach, Chennai, India

Marina beach in Chennai metropolitan city attracts numerous tourists from all around the world, and it is an important ecological habitat for many life forms. Rapid urbanisation and industrial developments have led to excessive use of plastics and increased the amount of plastic waste generated in the natural environment. This first baseline study evaluates the microplastic (MP) accumulation in beach surface sediments of Marina and Pattinapakkam beaches through FTIR, AFM and SEM analyses. Sediment samples were collected from 40 stations and different types of MP polymers were identified. On average, 459 (60.8%) and 297 (39.2%) MP particles were found in the samples from Marina and Pattinapakkam beaches, respectively. We found that polyethylene types and additives are the dominant MPs in both areas. This study provided us with new insights into the human activities and natural processes in these marine environments. To solve the problem of plastic accumulation in the marine environment, the government should first play an active role in addressing the problem of plastic waste by introducing laws to control the sources of plastic waste and the use of plastic additives.

A highly virulent variant of HIV-1 circulating in the Netherlands

We discovered a highly virulent variant of subtype-B HIV-1 in the Netherlands. One hundred nine individuals with this variant had a 0.54 to 0.74 log₁₀ increase (i.e., a ~3.5-fold to 5.5-fold increase) in viral load compared with, and exhibited CD4 cell decline twice as fast as, 6604 individuals with other subtype-B strains. Without treatment, advanced HIV-CD4 cell counts below 350 cells per cubic millimeter, with long-term clinical consequences-is expected to be reached, on average, 9 months after diagnosis for individuals in their thirties with this variant. Age, sex, suspected mode of transmission, and place of birth for the aforementioned 109 individuals were typical for HIV-positive people in the Netherlands, which suggests that the increased virulence is attributable to the viral strain. Genetic sequence analysis suggests that this variant arose in the 1990s from de novo mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence.

Design and Development of Modified Ensemble Learning with Weighted RBM Features for Enhanced Multi-disease Prediction Model

In this computer world, huge data are generated in several fields. Statistics in the healthcare engineering provides data about many diseases and corresponding patient's information. These data help to evaluate a huge amount of data for identifying the unknown patterns in the diseases and are also utilized for predicting the disease. Hence, this work is to plan and implement a new computer-aided technique named modified Ensemble Learning with Weighted RBM Features (EL-WRBM). Data collection is an initial process, in which the data of various diseases are gathered from UCI repository and Kaggle. Then, the gathered data are pre-processed by missing data filling technique. Then, the pre-processed data are performed by deep belief network (DBN), in which the weighted features are extracted from the RBM regions. Then, the prediction is made by ensemble learning with classifiers, namely, support vector machine (SVM), recurrent neural network (RNN), and deep neural network (DNN), in which hyper-parameters are optimized by the adaptive spreading rate-based coronavirus herd immunity optimizer (ASR-CHIO). At the end, the simulation analysis reveals that the suggested model has implications to support doctor diagnoses.

Monitoring and predicting regional land use and land cover changes in an estuarine landscape of India

Deciphering land use and land cover (LULC) change patterns, identifying the variables that act as the major driving forces of change, and predicting possible changes are necessary tools of decision support for policymakers. Estuarine landscapes world over are under extreme pressure of developmental activities because of their resources. The developmental activities lead to unforeseen changes in the traditional land use practices, making it necessary for investigation of the possible outcomes. The present study aims to study the changing pattern of LULC in the East Godavari River Estuarine Ecosystem (EGREE) landscape during 1977-2015 using temporal satellite data and to predict the possible LULC changes by 2029. Cellular Automata-Markov model (CAMM) with and without the multi-criteria evaluator (MCE) and the multi-layer perceptron (MLP) models were used for future LULC prediction. Between 1977 and 2015, mangroves were converted to aquaculture (5.81 km²) on the landward side and were also lost to submergence at the seaward side (15 km²). All of the coastal scrub (69 km²) was lost to beach clearing. Over this period, the aquaculture area rose to 177 km². The CAMM with MCE was found to yield better predictions. A further rise was predicted in aquaculture (16%), built-up (30%), and Casuarina plantations (28%) by 2029. The study highlighted the LULC change patterns in EGREE, an important estuarine landscape of India. The information generated in this study can act as baseline information for the stakeholders and policy makers in decision-making of developmental projects, land acquisition, and diversion of agricultural land to non-agricultural purposes.

Synthesis and discovery of pyrazolo-pyridine analogs as inflammation medications through pro- and anti-inflammatory cytokine and COX-2 inhibition assessments

This article briefs about the efforts taken to synthesis, characterize and develop (E)-5-methyl-2-phenyl-3-(thiophen-2-yl)-7-(thiophen-2-ylmethylene)-3,3a,4,5,6,7-hexahydro-2H-pyrazolo[4,3-c]pyridine and their analogs. In the two-step reaction, the first step is the synthesis of (3Z,5E)-1-methyl-3,5-bis(thiophen-2-ylmethylene)piperidin-4-one derivatives (3a-l) by stirring the mixture of 1-methylpiperidin-4-one and substituted thiophene-carbaldehydes in presence of methanol. In the second and final step, compounds 3a-l were refluxed with phenyl-hydrazine to achieve the target compounds (E)-5-methyl-2-phenyl-3-(thiophen-2-yl)-7-(thiophen-2-ylmethylene)-3,3a,4,5,6,7-hexahydro-2H-pyrazolo[4,3-c]pyridine and their analogs (5a-l) in good yield. These compounds were used to assess their inflammation regulation properties in macrophages by executing quantitative pro-inflammatory and anti-inflammatory proteins such as TNF-α, IL-1β, IL6, and IL-10 respectively. In silico and in vitro COX-2 inhibition studies helped to understand the molecular interaction or plausible mechanism during the inflammation regulation that showed by the compounds. In the results, among the 12-member family of pyrazolo-pyridines (5a-l), 5a, 5b, 5g, and 5j were showed excellent in silico binding affinity (1-10 nM), least binding energy (-12.45 to -14.27 kcal/mol) and in vitro COX-2 inhibition (relative percentage activity maximum 96.42%). Thus, these compounds perhaps to be future anti-inflammatory drugs.

Preparation, characterization and molecular modeling studies of the beta-cyclodextrin inclusion complex with benzoguanamine and its analytical application as chemosensor for the selective sensing of Ce4

The inclusion complex of β-cyclodextrin (β-CD) with benzoguanamine (BGA) has been investigated in three states. UV-Visible and fluorescence spectral techniques are used in liquid state. FTIR, NMR and MASS techniques are used in solid state and virtual state studies are done by molecular simulation work. The binding constants for the formation of 1:1 BGA:β-CD inclusion complex is estimated by UV-Visible and fluorescence spectral techniques. The chemosensory ability of BGA:β-CD complex was investigated thoroughly for various metal cations and we found the emission of complex showed a linear increase in the intensity for Ce⁴⁺ with the linearity range of 1000 μM-2000 μM. Sensitivity analysis shows good sensing for Ce⁴⁺ with the LOD of 671 μM and LOQ of 2034 μM. Our result suggests that the BGA:β-CD inclusion complex would be promising material for developing solid state sensory device for sensing Ce⁴⁺.

A Rare Survival in Celphos Poisoning

Aluminium phosphide poisoning releases phosphine gas which causes inhibition of cytochrome oxidase, inhibition of electron transport chain and thereby myocardial suppression. It is known to cause various electric abnormalities in the heart from ST-T depression to fatal tachyarrhythmias. Here we present a case of celphos poisoning presenting with both supraventricular tachycardia and ventricular tachycardia.

Service failures after online flash sales: role of deal proneness, attribution, and emotion

Purpose

The purpose of this paper is to focus on failures in online flash sales (OFS) and to explore why consumers participate in an OFS even after experiencing service failure. It also examines the role of deal proneness, attribution, and emotions.

Design/methodology/approach

Using a mixed method approach to gain insights into this relatively unexplored phenomenon of OFS, this research uses netnography followed by a survey study.

Findings

The findings show that deal-prone customers tend to ignore service failures during OFS and re-participate in the future. In the context of OFS, failures attributed to internal locus of attribution (LOA) also have a negative effect on re-participation compared with failures attributed to external LOA. Furthermore, there is a three-way interaction among deal proneness, LOA, and past emotions. The results show that negative past emotions further exacerbate the impact of attribution on the link between deal proneness and re-participation.

Originality/value

In contrast with prior research, the paper shows that consumers participate even after service failure. The proposed difference is between customers who experience different LOA and past emotions offers insights into their behavior after service failure in a new context of an online/electronic commerce event – flash sales. This paper specifically explores the role of internal LOA and finds that it has a more negative impact than external LOA on re-participation.

Actinobacterial community structure in the Polar Frontal waters of the Southern Ocean of the Antarctica using Geographic Information System (GIS): A novel approach to study Ocean Microbiome

Integration of microbiological data and geographical locations is necessary to understand the spatiotemporalpatterns of themicrobial diversity of an ecosystem. The Geographic Information System (GIS) to map and cataloguethe data ontheactinobacterial diversity of the Southern Ocean waterswas completed through sampling and analysis. Water samples collectedat two sampling stations viz.Polar Front 1(Station 1) andPolar Front 2(Station2)during7^thIndian Scientific Expedition to the Indian Ocean Sector of the Southern Ocean (SOE-2012-13)were used for analysis. At the outset, two different genera of Actinobacteria were recorded at both sampling stations.Streptomyces was the dominantedwiththehigh score (> 60%), followed by Nocardiopsis (< 30%)at both the sampling stations-Polar Front 1 and Polar Front 2-along withother invasive genera such as Agrococcus, Arthrobacter, Cryobacterium, Curtobacterium,Microbacterium, Marisediminicola, Rhodococcus and Kocuria. This data will help to discriminate the diversity and distribution pattern of the Actinobacteria in the Polar Frontal Region of the Southern Ocean waters.Itis a novel approachusefulfor geospatial cataloguing of microbial diversityfromextreme nichesand in various environmental gradations.Furthermore,this research work will act as the milestone for bioprospecting of microbial communities and their products having potential applications in healthcare, agriculture and beneficial to mankind. Hence, this research work would have significance in creating a database on microbial communities of the Antarctic ecosystem.

Service innovations: a neuropsychiatry outreach clinic

Aims and Method

We describe the neuropsychiatry outreach clinic in west Kent and review referrals to the clinic over a 4-year period. By comparing the referral pattern of west Kent with adjacent health authorities we show how an outreach clinic can influence the number of neuropsychiatric referrals.

Results

Referrals from west Kent increased from 87 in the 4-year period prior to the outreach clinic to 255 in the 4-year period that the clinic has been in existence. Forty-nine of these patients were first assessed in the outreach clinic. The number of referrals from east Surrey and east Sussex remained low in the same period.

Clinical Implications

An outreach clinic provides access to specialist expertise and increases local awareness of specialist services. Similar outreach clinics in other areas may enhance the clinical care of patients who are currently not being referred to neuropsychiatry.

<b>New distribution records of Elegant Water Shrew <I>Nectogale elegans</I> Milne-Edwards, 1870 (Mammalia: Eulipotyphla: Soricidae) from the western Himalaya, Uttarakhand, India</b>

Of the 13 known species of water shrews in the world, two water shrews are known from India, the Elegant Water Shrew Nectogale elegans and Himalayan Water Shrew Chimmarogale himalayica.  Of these, the Elegant Water Shrew was earlier reported only from streams of north Sikkim, and Arunachal Pradesh, India.  During the period 2014–2016, the Elegant Water Shrews were sighted at three different locations in Uttarakhand State in the western Himalayan region.  The present records are evidence for the broader range of distribution of Nectogale elegans in India indicating that the species is more widely distributed than previously thought.  We present the details of sightings, habitats and behavior of shrews that were recorded during our study on impact of climate change on the aquatic ecosystem of the Himalaya.

Long circulating PEGylated-chitosan nanoparticles of rosuvastatin calcium: Development and in vitro and in vivo evaluations

The aim of this study was to improve the pharmacokinetics and pharmacodynamics profile of rosuvastatin calcium by formulating long-circulating PEGylated chitosan nanoparticles (NPs). Chitosan was PEGylated by a carbodiimide mediated reaction, using a carboxylic acid derivative of PEG (polyethylene glycol). The NPs were optimised for particle size, polydispersity index, zeta potential and drug entrapment efficiency. In vitro drug release, pharmacokinetic and pharmacodynamics studies of the optimized nanoparticles were performed. PEGylation of chitosan was confirmed by FTIR analysis. Drug-excipient compatibility was studied by differential scanning calorimetry and FTIR analyses. Two batches of nanoparticles were optimized with particle size of <200nm and entrapment efficiency of ≈14%. In vitro drug release studies revealed cumulative release of 14.07±0.57% and 22.02±0.81% of rosuvastatin over the period of 120h, indicating appreciable sustained release of drug. TEM analysis showed the spherical structure of nanoparticles. Pharmacokinetic studies indicated that optimized NPs showed prolonged drug release over a period of 72h. Pharmacodynamics studies in hyperlipidemic rat model demonstrated greater lipid-lowering capability of rosuvastatin nanoparticles in comparison with plain rosuvastatin. The nanoparticles demonstrated substantial prolonged delivery of the drug in vivo along with better therapeutic action, which could be potential drug delivery modality for 'statins'.