Effects of microwave heating on the thermal states of biological tissues

A mathematical analysis of microwave heating equations in one-dimensional multi-layer model has been discussed. Maxwell's equations and transient bioheat transfer equation were numerically calculated by using finite difference method to predict the effects of thermal physical properties on the transient temperature of biological tissues. This prediction of the temperature evolution in biological bodies can be used as an effective tool for thermal diagnostics in medical practices. Key words: Microwave heating, Maxwell's equations, bioheat, multi layer. African Journal of Biotechnology Vol.2(11) 2003: 453-45

Determination of Gossypol in Hamid and Bt (Seeni 1) Cottonseed Oil using Fourier Transform Infrared Spectroscopy

This study was conducted to determine the gossypol content in Bt cottonseed (Seeni-1) oil by using Fourier Transform Infrared (FTIR) spectroscopy with an Attenuated Total Reflectance (ATR) element. The wavelengths used were selected by spiking refined, bleached deodorized palm oil (RBDPO) to gossypol concentrations of 0-5% and noting the regions of maximal absorbance. Absorbance values of the wavelength regions 3700-2400 & 1900-750 cm−1 and a partial least squares (PLS) method were used to derive calibration models for Hamid cottonseed oil, Seeni-1 cottonseed oil, and gossypol-spiked RBDPO. The coefficients of determination (R2) for the calibration models were computed for the FTIR spectroscopy results against those found by using the wet chemical method AOCS method Ba 8–78. The R2 was 0.8916, 0.9581, and 0.9374 for Hamid cottonseed oil, Seeni-1 cottonseed oil, and gossypol-spiked RBDPO, respectively. The standard error (SE) of the calibration was 0.053, 0.078, and 0.062, respectively. The calibration models were validated using the cross-validation technique within the same set of oil samples. The results of FTIR spectroscopy as a useful technique determining gossypol content in crude cottonseed oil showed that there is a significant difference (p <0.05) in the amount of gossypol content in Hamid and Bt Seeni-1 cottonseed oils

Interaction of hope and optimism with anxiety and depression in a specific group of cancer survivors: a preliminary study

<p>Abstract</p> <p>Background</p> <p>Anxiety and depression have been identified as a common psychological distress faced by the majority of cancer patients. With the increasing number of cancer cases, increasing demands will be placed on health systems to address effective psychosocial care and therapy. The objective of this study was to assess the possible role of hope and optimism on anxiety and depression. We also wanted to investigate if there is a specific component of hope that could play a role in buffering anxiety and depression amongst cancer patients.</p> <p>Methods</p> <p>A retrospective cross sectional study was conducted in the outpatient station of the Oral and Maxillofacial Surgery at the University of Hong Kong, Hong Kong SAR, PR-China. Fifty patients successfully treated for OC cancer were recruited after their informed consents had been obtained during the review clinic. During their regular follow-up controls in the outpatient clinic the patients compiled the hospital anxiety and depression scale (HADS), hope scale (HS) and the life orientation scale-revised (LOT-R).</p> <p>Results</p> <p>Hope was negatively correlated with depression (<it>r </it>= -.55, <it>p </it>< .001) and anxiety (r = -.38, <it>p </it>< .05). Similar pattern was found between optimism and the latter adjustment outcomes (depression: <it>r </it>= -.55, <it>p </it>< .001; anxiety: <it>r </it>= -.35, <it>p </it>< .05). Regression analyses indentified that both hope and optimism were significant predictors of depression. Hope and optimism had equal association with depression (hope: <it>β </it>= .40 versus optimism: <it>β </it>= .38). Hope and optimism together were significantly predictive of anxiety, whereas neither hope nor optimism alone was significant individual predictors of anxiety.</p> <p>Conclusions</p> <p>Hope and optimism both negatively correlated with patients' level of anxiety and depression. Besides theoretical implications, this study brings forward relevant findings related to developing specific clinical psychological care in the field of oncology that to date has not been researched specifically in the field of oncology. The results of this study will help guide the direction of future prospective studies in the field of oncology. This will contribute significantly to increasing patients quality of life as well enabling health care facilities to provide all cancer patients a more holistic cancer care.</p

Inferring the role of transcription factors in regulatory networks

<p>Abstract</p> <p>Background</p> <p>Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple organisms up to higher eukaryotes. Admittedly, a key ingredient in developing a reconstruction method is its ability to integrate heterogeneous sources of information, as well as to comply with practical observability issues: measurements can be scarce or noisy. In this work, we show how to combine a network of genetic regulations with a set of expression profiles, in order to infer the functional effect of the regulations, as inducer or repressor. Our approach is based on a consistency rule between a network and the signs of variation given by expression arrays.</p> <p>Results</p> <p>We evaluate our approach in several settings of increasing complexity. First, we generate artificial expression data on a transcriptional network of <it>E. coli </it>extracted from the literature (1529 nodes and 3802 edges), and we estimate that 30% of the regulations can be annotated with about 30 profiles. We additionally prove that at most 40.8% of the network can be inferred using our approach. Second, we use this network in order to validate the predictions obtained with a compendium of real expression profiles. We describe a filtering algorithm that generates particularly reliable predictions. Finally, we apply our inference approach to <it>S. cerevisiae </it>transcriptional network (2419 nodes and 4344 interactions), by combining ChIP-chip data and 15 expression profiles. We are able to detect and isolate inconsistencies between the expression profiles and a significant portion of the model (15% of all the interactions). In addition, we report predictions for 14.5% of all interactions.</p> <p>Conclusion</p> <p>Our approach does not require accurate expression levels nor times series. Nevertheless, we show on both data, real and artificial, that a relatively small number of perturbation experiments are enough to determine a significant portion of regulatory effects. This is a key practical asset compared to statistical methods for network reconstruction. We demonstrate that our approach is able to provide accurate predictions, even when the network is incomplete and the data is noisy.</p

New insights into the genetic diversity of Schistosoma mansoni and S. haematobiumin Yemen

The file attached is the Published/publisher’s pdf version of the article.© 2015 Sady et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated

Depth-related effects on a meiofaunal community dwelling in the periphyton of a mesotrophic lake

Kreuzinger B, Schroeder F, Majdi N, Traunspurger W. Depth-related effects on a meiofaunal community dwelling in the periphyton of a mesotrophic lake. PLoS One. 2015;10(9): e0137793.Periphyton is a complex assemblage of micro- and meiofauna embedded in the organic matrix that coats most submerged substrate in the littoral of lakes. The aim of this study was to better understand the consequences of depth-level fluctuation on a periphytic community. The effects of light and wave disturbance on the development of littoral periphyton were evaluated in Lake Erken (Sweden) using an experimental design that combined in situ shading with periphyton depth transfers. Free-living nematodes were a major contributor to the meiofaunal community. Their species composition was therefore used as a proxy to distinguish the contributions of light- and wave-related effects. The periphyton layer was much thicker at a depth of 30 cm than at 200 cm, as indicated by differences in the amounts of organic and phototrophic biomass and meiofaunal and nematode densities. A reduction of the depth-level of periphyton via a transfer from a deep to a shallow location induced rapid positive responses by its algal, meiofaunal, and nematode communities. The slower and weaker negative responses to the reverse transfer were attributed to the potentially higher resilience of periphytic communities to increases in the water level. In the shallow littoral of the lake, shading magnified the effects of phototrophic biomass erosion by waves, as the increased exposure to wave shear stress was not compensated for by an increase in photosynthesis. This finding suggests that benthic primary production will be strongly impeded in the shallow littoral zones of lakes artificially shaded by construction or embankments. However, regardless of the light constraints, an increased exposure to wave action had a generally positive short-term effect on meiofaunal density, by favoring the predominance of species able to anchor themselves to the substrate, especially the Chromadorid nematode Punctodora ratzeburgensis

A year of genomic surveillance reveals how the SARS-CoV-2 pandemic unfolded in Africa.

The progression of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in Africa has so far been heterogeneous, and the full impact is not yet well understood. In this study, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations predominantly from Europe, which diminished after the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1, and C.1.1. Although distorted by low sampling numbers and blind spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a source for new variants

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century