Stereoselective synthesis of cis- and trans-bicyclo [6.3.0] undec-4-en-10-ones. Efficient precursors of 4-oxo-1,2-cyclopentane dipropanoic acids

Short syntheses of title compounds from cheap, readily available cis, cis-1,5-cyclooctadiene are described

Downregulation of calcineurin activity in cervical carcinoma

BACKGROUND: Calcineurin (CaN) is an important serine-threonine phosphatase (PP2B), which plays a crucial role in calcium-calmodulin mediated signal transduction events. Calcineurin has been implicated in pathogenesis of various diseases cardiac hypertrophy, diabetic neuropathy and Alzheimer's, however its role in neoplasia remains unclear. RESULTS: In view of this we evaluated the calcineurin activity in serum and biopsy samples collected from women diagnosed with invasive squamous cell carcinoma of cervix. A significant reduction was observed in the calcineurin activity in cancer cervix patients compared to the control group. However the calcineurin activity remained unaltered in the cervical scrapes obtained from patients diagnosed with low-grade squamous intra epithelial lesions (LSIL). Interestingly the downregulation of calcineurin activity in squamous cell carcinomas was not accompanied by any significant change in DNA-binding affinity of the transcriptional factor NFAT (Nuclear Factor of Activated T-cells). All the squamous cell carcinoma samples used in the present study were positive for high-risk human papillomavirus (HPV) types. CONCLUSION: The present study demonstrates the downregulation of calcineurin activity in squamous cell carcinoma of cervix with high risk HPV infection. We conclude that perturbations in calcineurin-mediated pathway may be involved in development of cervical neoplasia

Time Domain Signal Detection for MIMO OFDM

The MIMO techniques with OFDM is regarded as a promising solution for increasing data rates, for wireless access qualities of future wireless local area networks, fourth generation wireless communication systems, and for high capacity, as well as better performance. Hence as part of continued research, in this paper an attempt is made to carry out modelling, analysis, channel matrix estimation, synchronization and simulation of MIMO-OFDM system. A time domain signal detection algorithm can be based on Second Order Statistics (SOS) proposed for MIMO-OFDM system over frequency selective fading channels. In this algorithm, an equalizer is first inserted to reduce the MIMO channels to ones with channel length shorter than or equal to the Cyclic Prefix (CP) length. A system model in which the ith received OFDM block left shifted by j samples introduced. MIMO OFDM system model which uses the equalizer can be designed using SOS of the received signal vector to cancel the most of the Inter Symbol Interference (ISI). The transmitted signals are then detected from the equalizer output. In the proposed algorithm, only 2P (P transmitted antennas / users in the MIMO-OFDM system) columns of the channel matrix need to be estimated and channel length estimation is unnecessary, which is an advantage over an existing algorithms. In addition, the proposed algorithm is applicable for irrespective of whether the channel length is shorter than, equal to or longer than the CP length. Simulation results verify the effectiveness of the proposed algorithm and shows that it out performs the existing one in all cases

HYPERPHOSPHATEMIA IN END STAGE RENAL DISEASE: PREVALENCE AND PATIENTS CHARACTERISTICS OF MULTIETHNIC POPULATION OF UNITED ARAB EMIRATES

Objective: Hyperphosphatemia is significantly associated with increased mortality among end stage renal disease (ESRD) patients on hemodialysis. There is paucity of data on hyperphosphatemia in ESRD patients of the multiethnic population of United Arab Emirates (UAE). The study aimed to investigate the prevalence and characteristics of hyperphosphatemia in ESRD patients of the multiethnic population of UAE undergoing maintenance hemodialysis.Methods: Adults ESRD patients undergoing maintenance hemodialysis for more than six months at the study site were included. Demographic, clinical and biological data of the patients were collected. Patient characteristics were compared as per the serum phosphate level, between patients with or without hyperphosphatemia. Univariate and multivariate logistic regression analyses were carried out to identify the predictors of hyperphosphatemia.Results: Hyperphosphatemia was present in 73.8% of the study population, while 31.3% presented with high calcium-phosphate product. Univariate logistic analysis revealed that hyperphosphatemia was inversely correlated with age, hemoglobin, serum calcium, and hypertensive nephropathy as cause of renal disease, and positively correlated with female gender, expatriate status, body mass index (BMI), higher number of comorbidities, calcium-phosphate product and parathyroid hormone (PTH). Multivariate logistic regression model revealed that only age, BMI, hemoglobin and PTH independently correlated with hyperphosphatemia.Conclusion: We report a high prevalence of hyperphosphatemia in multiethnic study population undergoing maintenance hemodialysis at a secondary care hospital in UAE. In this study population, only age, BMI, hemoglobin and PTH were identified as independent predictors of hyperphosphatemia

Studies on phytochemicals: Part XV-Investigation on the alkaloidal constituents of Indian Mappia foetida

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The burden of disease attributable to ambient PM2.5-bound PAHs exposure in Nagpur, India

Polycyclic aromatic hydrocarbons (PAHs) bound to PM2.5 are genotoxic carcinogens that can also elicit non-cancer effects. Previous studies report substantial burdens of PAHs-related lung cancer, but no estimate for other cancer types or non-carcinogenic burden. Here, we assessed the burden of disease, in DALYs/person/year, attributable to thirteen priority PAHs in PM2.5 in Nagpur district, for several endpoints linked to benzo[a]pyrene, to inform policy decision-making for mitigation. We conducted detailed assessment of concentrations of PAHs in nine areas, covering urban, peri-urban and rural environments, from February 2013 to June 2014. PAHs concentrations were converted to benzo[a]pyrene equivalent concentration for cancer and non-cancer effects using relative potency factors and relative toxicity factors derived from quantitative structure-activity relationships, respectively. We derived severity for each endpoint using GBD 2016 dataset. The annual average concentration of total PAHs in Nagpur district was 458±246 ng/m3, and results in 0.011 DALYs/person/year (49,000 DALYs/year), much higher than the WHO reference limit of 1×10-6 DALYs/person/year. PAHs-related burden follow this order: developmental (mostly cardiovascular) impairment (55.1%) > cancer (26.5%) or lung cancer (23.1%) > immunological impairment (18.0%) > reproductive abnormally (0.4%). The estimated DALYs/person/year is high. Mitigation intervention should target combustion sources having the highest level of exposure

Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).The modern-day urban energy sector possesses the integrated operation of various microgrids located in a vicinity, named cluster microgrids, which helps to reduce the utility grid burden. However, these cluster microgrids require a precise electric load projection to manage the operations, as the integrated operation of multiple microgrids leads to dynamic load demand. Thus, load forecasting is a complicated operation that requires more than statistical methods. There are different machine learning methods available in the literature that are applied to single microgrid cases. In this line, the cluster microgrids concept is a new application, which is very limitedly discussed in the literature. Thus, to identify the best load forecasting method in cluster microgrids, this article implements a variety of machine learning algorithms, including linear regression (quadratic), support vector machines, long short-term memory, and artificial neural networks (ANN) to forecast the load demand in the short term. The effectiveness of these methods is analyzed by computing various factors such as root mean square error, R-square, mean square error, mean absolute error, mean absolute percentage error, and time of computation. From this, it is observed that the ANN provides effective forecasting results. In addition, three distinct optimization techniques are used to find the optimum ANN training algorithm: Levenberg−Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. The effectiveness of these optimization algorithms is verified in terms of training, test, validation, and error analysis. The proposed system simulation is carried out using the MATLAB/Simulink-2021a® software. From the results, it is found that the Levenberg−Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.Peer reviewe

The health burden and economic costs averted by ambient PM 2.5 pollution reductions in Nagpur, India

National estimates of the health and economic burdens of exposure to ambient fine particulate matter (PM2.5) in India reveal substantial impacts. This information, often lacking at the local level, can justify and drive mitigation interventions. Here, we assess the health and economic gains resulting from attainment of WHO guidelines for PM2.5 concentrations – including interim target 2 (IT-2), interim target 3 (IT-3), and theWHO air quality guideline (AQG) – in Nagpur district to inform policy decision making for mitigation. We conducted a detailed assessment of concentrations of PM2.5 in 9 areas, covering urban, peri-urban and rural environments, from February 2013 to June 2014. We used a combination of hazard and survival analyses based on the life table method to calculate attributed annual number of premature deaths and disability-adjusted life years (DALYs) for five health outcomes linked to PM2.5 exposure: acute lower respiratory infection for children b5 years, ischemic heart disease, chronic obstructive pulmonary disease, stroke and lung cancer in adults !25 years. We used GBD 2013 data on deaths and DALYs for these diseases. We calculated averted deaths, DALYs and economic loss resulting from planned reductions in average PM2.5 concentration from current level to IT-2, IT-3 and AQG by the years 2023, 2033 and 2043, respectively. The economic cost for premature mortality was estimated as the product of attributed deaths and value of statistical life for India, while morbidity was assumed to be 10% of the mortality cost. The annual average PM2.5 concentration in Nagpur district is 34± 17 μg m−3 and results in 3.3 (95% confidence interval [CI]: 2.6, 4.2) thousand premature deaths and 91 (95% CI: 68, 116) thousand DALYs in 2013 with economic loss of USD 2.2 (95% CI: 1.7, 2.8) billion in that year. It is estimated that interventions that achieve IT-2, IT-3 and AQG by 2023, 2033 and 2043,would avert, respectively, 15, 30 and 36%, of the attributed health and economic loss in those years, translating into an impressively large health and economic gain. To achieve this, we recommend an exposure-integrated source reduction approach

Regional research priorities in brain and nervous system disorders

The characteristics of neurological, psychiatric, developmental and substance-use disorders in low-and middle-income countries are unique and the burden that they have will be different from country to country. Many of the differences are explained by the wide variation in population demographics and size, poverty, conflict, culture, land area and quality, and genetics. Neurological, psychiatric, developmental and substance-use disorders that result from, or are worsened by, a lack of adequate nutrition and infectious disease still afflict much of sub-Saharan Africa, although disorders related to increasing longevity, such as stroke, are on the rise. In the Middle East and North Africa, major depressive disorders and post-traumatic stress disorder are a primary concern because of the conflict-ridden environment. Consanguinity is a serious concern that leads to the high prevalence of recessive disorders in the Middle East and North Africa and possibly other regions. The burden of these disorders in Latin American and Asian countries largely surrounds stroke and vascular disease, dementia and lifestyle factors that are influenced by genetics. Although much knowledge has been gained over the past 10 years, the epidemiology of the conditions in low-and middle-income countries still needs more research. Prevention and treatments could be better informed with more longitudinal studies of risk factors. Challenges and opportunities for ameliorating nervous-system disorders can benefit from both local and regional research collaborations. The lack of resources and infrastructure for health-care and related research, both in terms of personnel and equipment, along with the stigma associated with the physical or behavioural manifestations of some disorders have hampered progress in understanding the disease burden and improving brain health. Individual countries, and regions within countries, have specific needs in terms of research priorities.Fil: Ravindranath, Vijayalakshmi. Indian Institute of Science; IndiaFil: Dang, Hoang Minh. Vietnam National University; VietnamFil: Goya, Rodolfo Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Mansour, Hader. University of Pittsburgh; Estados Unidos. Mansoura University; EgiptoFil: Nimgaonkar, Vishwajit L.. University of Pittsburgh; Estados UnidosFil: Russell, Vivienne Ann. University of Cape Town; SudáfricaFil: Xin, Yu. Peking University; Chin