Development of spectrophotometric fingerprinting method for Talisadi Churna

Selective and efficient analytical methods are required not only for quality assurance but also for authentication of herbal formulations. A simple, rapid and validated fingerprint method has developed for estimation of piperine in ‘Talisadi churna’, a well known herbal formulation in India. The estimation was carried out in two laboratory batches and three marketed formulation by an ultraviolet spectrophotometric method at 342.8 nm. Keywords: Talisadi churna, PiperinEast and Central African Journal of Pharmaceutical Sciences Vol. 12 (2009) 52-5

The main rhinovirus respiratory tract adhesion site (ICAM-1) is upregulated in smokers and patients with chronic airflow limitation (CAL).

BACKGROUND: ICAM-1 is a major receptor for ~60% of human rhinoviruses, and non-typeable Haemophilus influenzae, two major pathogens in COPD. Increased cell-surface expression of ICAM-1 in response to tobacco smoke exposure has been suggested. We have investigated epithelial ICAM-1 expression in both the large and small airways, and lung parenchyma in smoking-related chronic airflow limitation (CAL) patients. METHODS: We evaluated epithelial ICAM-1 expression in resected lung tissue: 8 smokers with normal spirometry (NLFS); 29 CAL patients (10 small-airway disease; 9 COPD-smokers; 10 COPD ex-smokers); Controls (NC): 15 normal airway/lung tissues. Immunostaining with anti-ICAM-1 monoclonal antibody was quantified with computerized image analysis. The percent and type of cells expressing ICAM-1 in large and small airway epithelium and parenchyma were enumerated, plus percentage of epithelial goblet and submucosal glands positive for ICAM- 1. RESULTS: A major increase in ICAM-1 expression in epithelial cells was found in both large (p < 0.006) and small airways (p < 0.004) of CAL subjects compared to NC, with NLFS being intermediate. In the CAL group, both basal and luminal areas stained heavily for ICAM-1, so did goblet cells and sub-mucosal glands, however in either NC or NLFS subjects, only epithelial cell luminal surfaces stained. ICAM-1 expression on alveolar pneumocytes (mainly type II) was slightly increased in CAL and NLFS (p < 0.01). Pack-years of smoking correlated with ICAM-1 expression (r = 0.49; p < 0.03). CONCLUSION: Airway ICAM-1 expression is markedly upregulated in CAL group, which could be crucial in rhinoviral and NTHi infections. The parenchymal ICAM-1 is affected by smoking, with no further enhancement in CAL subjects

β-catenin, Twist and Snail: Transcriptional regulation of EMT in smokers and COPD, and relation to airflow obstruction.

COPD is characterised by poorly reversible airflow obstruction usually due to cigarette smoking. The transcription factor clusters of β-catenin/Snail1/Twist has been implicated in the process of epithelial mesenchymal transition (EMT), an intermediate between smoking and airway fibrosis, and indeed lung cancer. We have investigated expression of these transcription factors and their "cellular localization" in bronchoscopic airway biopsies from patients with COPD, and in smoking and non-smoking controls. An immune-histochemical study compared cellular protein expression of β-catenin, Snail1 and Twist, in these subject groups in 3 large airways compartment: epithelium (basal region), reticular basement membrane (Rbm) and underlying lamina propria (LP). β-catenin and Snail1 expression was generally high in all subjects throughout the airway wall with marked cytoplasmic to nuclear shift in COPD (P < 0.01). Twist expression was generalised in the epithelium in normal but become more basal and nuclear with smoking (P < 0.05). In addition, β-catenin and Snail1 expression, and to lesser extent of Twist, was related to airflow obstruction and to expression of a canonical EMT biomarker (S100A4). The β-catenin-Snail1-Twist transcription factor cluster is up-regulated and nuclear translocated in smokers and COPD, and their expression is closely related to both EMT activity and airway obstruction

The role of environmental exposure to non-cigarette smoke in lung disease

Chronic exposure to household indoor smoke and outdoor air pollution is a major contributor to global morbidity and mortality. The majority of these deaths occur in low and middle-income countries. Children, women, the elderly and people with underlying chronic conditions are most affected. In addition to reduced lung function, children exposed to biomass smoke have an increased risk of developing lower respiratory tract infections and asthma-related symptoms. In adults, chronic exposure to biomass smoke, ambient air pollution, and opportunistic exposure to fumes and dust are associated with an increased risk of developing chronic bronchitis, chronic obstructive pulmonary disease (COPD), lung cancer and respiratory infections, including tuberculosis. Here, we review the evidence of prevalence of COPD in people exposed to non-cigarette smoke. We highlight mechanisms that are likely involved in biomass-smoke exposure-related COPD and other lung diseases. Finally, we summarize the potential preventive and therapeutic strategies for management of COPD induced by non-cigarette smoke exposure

Design, fabrication and performance evaluation of a 22-channel direct reading atomic emission spectrometer using inductively coupled plasma as a source of excitation

The indigenous design, fabrication and performance evaluation of a polychromator, using inductively coupled plasma (ICP) as a source of excitation, are described. A concave holographic grating is used as the dispersing element and a Paschen-Runge mount is chosen to focus the spectra over a wide range along the Rowland circle. Twenty-two exit slits, mounted along the circle, precisely correspond to the wavelengths used for determination of up to twenty elements present in the plasma. Radiations emerging from the exit slits are detected by photomultiplier tubes placed behind them. The photomultiplier signal is recorded by an electronic system consisting of an integrator and a PC-based data acquisition system. The performance of the spectrometer has been evaluated with an ICP excitation source. Synthetic standards in deionized water containing a mixture of twenty impurities have been analysed. Typical determination limits observed for elements range from sub-ppm to ppm levels. All the elements present as impurities can be detected simultaneously. It is also observed that each element has a different emitting region in the ICP flame for which the maximum signal to the background is obtained. The determination limits obtained corresponding to these zones are the lowest. A study of the sensitive emitting zones for several elements has been carried out and the results are demonstrated by photographs of the ICP flame. The study will help in achieving the minimum value of determination limit for an impurity element

Internet of Medical Things (IoMT) and Reflective Belief Design-Based Big Data Analytics with Convolution Neural Network-Metaheuristic Optimization Procedure (CNN-MOP)

In recent times, the Internet of Medical Things (IoMT) is a new loomed technology, which has been deliberated as a promising technology designed for various and broadly connected networks. In an intelligent healthcare system, the framework of IoMT observes the health circumstances of the patients dynamically and responds to backings their needs, which helps detect the symptoms of critical rare body conditions based on the data collected. Metaheuristic algorithms have proven effective, robust, and efficient in deciphering real-world optimization, clustering, forecasting, classification, and other engineering problems. The emergence of extraordinary, very large-scale data being generated from various sources such as the web, sensors, and social media has led the world to the era of big data. Big data poses a new contest to metaheuristic algorithms. So, this research work presents the metaheuristic optimization algorithm for big data analysis in the IoMT using gravitational search optimization algorithm (GSOA) and reflective belief network with convolutional neural networks (DBN-CNNs). Here the data optimization has been carried out using GSOA for the collected input data. The input data were collected for the diabetes prediction with cardiac risk prediction based on the damage in blood vessels and cardiac nerves. Collected data have been classified to predict abnormal and normal diabetes range, and based on this range, the risk for a cardiac attack has been predicted using SVM. The performance analysis is made to reveal that GSOA-DBN_CNN performs well in predicting diseases. The simulation results illustrate that the GSOA-DBN_CNN model used for prediction improves accuracy, precision, recall, F1-score, and PSNR

Rational Mutational Analysis of a Multidrug MFS Transporter CaMdr1p of Candida albicans by Employing a Membrane Environment Based Computational Approach

CaMdr1p is a multidrug MFS transporter of pathogenic Candida albicans. An over-expression of the gene encoding this protein is linked to clinically encountered azole resistance. In-depth knowledge of the structure and function of CaMdr1p is necessary for an effective design of modulators or inhibitors of this efflux transporter. Towards this goal, in this study, we have employed a membrane environment based computational approach to predict the functionally critical residues of CaMdr1p. For this, information theoretic scores which are variants of Relative Entropy (Modified Relative Entropy REM) were calculated from Multiple Sequence Alignment (MSA) by separately considering distinct physico-chemical properties of transmembrane (TM) and inter-TM regions. The residues of CaMdr1p with high REM which were predicted to be significantly important were subjected to site-directed mutational analysis. Interestingly, heterologous host Saccharomyces cerevisiae, over-expressing these mutant variants of CaMdr1p wherein these high REM residues were replaced by either alanine or leucine, demonstrated increased susceptibility to tested drugs. The hypersensitivity to drugs was supported by abrogated substrate efflux mediated by mutant variant proteins and was not attributed to their poor expression or surface localization. Additionally, by employing a distance plot from a 3D deduced model of CaMdr1p, we could also predict the role of these functionally critical residues in maintaining apparent inter-helical interactions to provide the desired fold for the proper functioning of CaMdr1p. Residues predicted to be critical for function across the family were also found to be vital from other previously published studies, implying its wider application to other membrane protein families

Accurate thermal conductivities from optimally short molecular dynamics simulations

The evaluation of transport coefficients in extended systems, such as thermal conductivity or shear viscosity, is known to require impractically long simulations, thus calling for a paradigm shift that would allow to deploy state-of-the-art quantum simulation methods. We introduce a new method to compute these coefficients from optimally short molecular dynamics simulations, based on the Green-Kubo theory of linear response and the cepstral analysis of time series. Information from the full sample power spectrum of the relevant current for a single and relatively short trajectory is leveraged to evaluate and optimally reduce the noise affecting its zero-frequency value, whose expectation is proportional to the corresponding conductivity. Our method is unbiased and consistent, in that both the resulting bias and statistical error can be made arbitrarily small in the long-time limit. A simple data-analysis protocol is proposed and validated with the calculation of thermal conductivities in the paradigmatic cases of elemental and molecular fluids (liquid Ar and H2O) and of crystalline and glassy solids (MgO and a-SiO2). We find that simulation times of one to a few hundred picoseconds are sufficient in these systems to achieve an accuracy of the order of 10% on the estimated thermal conductivities

The influence of glucose-lowering therapies on cancer risk in type 2 diabetes

AIMS/HYPOTHESIS: The risk of developing a range of solid tumours is increased in type 2 diabetes, and may be influenced by glucose-lowering therapies. We examined the risk of development of solid tumours in relation to treatment with oral agents, human insulin and insulin analogues. METHODS: This was a retrospective cohort study of people treated in UK general practices. Those included in the analysis developed diabetes >40 years of age, and started treatment with oral agents or insulin after 2000. A total of 62,809 patients were divided into four groups according to whether they received monotherapy with metformin or sulfonylurea, combined therapy (metformin plus sulfonylurea), or insulin. Insulin users were grouped according to treatment with insulin glargine, long-acting human insulin, biphasic analogue and human biphasic insulin. The outcome measures were progression to any solid tumour, or cancer of the breast, colon, pancreas or prostate. Confounding factors were accounted for using Cox proportional hazards models. RESULTS: Metformin monotherapy carried the lowest risk of cancer. In comparison, the adjusted HR was 1.08 (95% CI 0.96-1.21) for metformin plus sulfonylurea, 1.36 (95% CI 1.19-1.54) for sulfonylurea monotherapy, and 1.42 (95% CI 1.27-1.60) for insulin-based regimens. Adding metformin to insulin reduced progression to cancer (HR 0.54, 95% CI 0.43-0.66). The risk for those on basal human insulin alone vs insulin glargine alone was 1.24 (95% CI 0.90-1.70). Compared with metformin, insulin therapy increased the risk of colorectal (HR 1.69, 95% CI 1.23-2.33) or pancreatic cancer (HR 4.63, 95% CI 2.64-8.10), but did not influence the risk of breast or prostate cancer. Sulfonylureas were associated with a similar pattern of risk as insulin. CONCLUSIONS/INTERPRETATION: Those on insulin or insulin secretagogues were more likely to develop solid cancers than those on metformin, and combination with metformin abolished most of this excess risk. Metformin use was associated with lower risk of cancer of the colon or pancreas, but did not affect the risk of breast or prostate cancer. Use of insulin analogues was not associated with increased cancer risk as compared with human insulin