329 research outputs found

    Gender-Specific Effects on the Cardiorespiratory System and Neurotoxicity of Intermittent and Permanent Low-Level Lead Exposures

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    \ua9 2024 by the authors. Lead exposure is a significant health concern, ranking among the top 10 most harmful substances for humans. There are no safe levels of lead exposure, and it affects multiple body systems, especially the cardiovascular and neurological systems, leading to problems such as hypertension, heart disease, cognitive deficits, and developmental delays, particularly in children. Gender differences are a crucial factor, with women’s reproductive systems being especially vulnerable, resulting in fertility issues, pregnancy complications, miscarriages, and premature births. The globalization of lead exposure presents new challenges in managing this issue. Therefore, understanding the gender-specific implications is essential for developing effective treatments and public health strategies to mitigate the impact of lead-related health problems. This study examined the effects of intermittent and permanent lead exposure on both male and female animals, assessing behaviours like anxiety, locomotor activity, and long-term memory, as well as molecular changes related to astrogliosis. Additionally, physiological and autonomic evaluations were performed, focusing on baro- and chemoreceptor reflexes. The study’s findings revealed that permanent lead exposure has more severe health consequences, including hypertension, anxiety, and reactive astrogliosis, affecting both genders. However, males exhibit greater cognitive, behavioural, and respiratory changes, while females are more susceptible to chemoreflex hypersensitivity. In contrast, intermittent lead exposure leads to hypertension and reactive astrogliosis in both genders. Still, females are more vulnerable to cognitive impairment, increased respiratory frequency, and chemoreflex hypersensitivity, while males show more reactive astrocytes in the hippocampus. Overall, this research emphasizes the importance of not only investigating different types of lead exposure but also considering gender differences in toxicity when addressing this public health concern

    What traits are carried on mobile genetic elements, and why?

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    Although similar to any other organism, prokaryotes can transfer genes vertically from mother cell to daughter cell, they can also exchange certain genes horizontally. Genes can move within and between genomes at fast rates because of mobile genetic elements (MGEs). Although mobile elements are fundamentally self-interested entities, and thus replicate for their own gain, they frequently carry genes beneficial for their hosts and/or the neighbours of their hosts. Many genes that are carried by mobile elements code for traits that are expressed outside of the cell. Such traits are involved in bacterial sociality, such as the production of public goods, which benefit a cell's neighbours, or the production of bacteriocins, which harm a cell's neighbours. In this study we review the patterns that are emerging in the types of genes carried by mobile elements, and discuss the evolutionary and ecological conditions under which mobile elements evolve to carry their peculiar mix of parasitic, beneficial and cooperative genes

    An HR-MAS MR Metabolomics Study on Breast Tissues Obtained with Core Needle Biopsy

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    BACKGROUND: Much research has been devoted to the development of new breast cancer diagnostic measures, including those involving high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopic techniques. Previous HR-MAS MR results have been obtained from post-surgery samples, which limits their direct clinical applicability. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we performed HR-MAS MR spectroscopic studies on 31 breast tissue samples (13 cancer and 18 non-cancer) obtained by percutaneous core needle biopsy. We showed that cancer and non-cancer samples can be discriminated very well with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA) multivariate model on the MR spectra. A subsequent blind test showed 69% sensitivity and 94% specificity in the prediction of the cancer status. A spectral analysis showed that in cancer cells, taurine- and choline-containing compounds are elevated. Our approach, additionally, could predict the progesterone receptor statuses of the cancer patients. CONCLUSIONS/SIGNIFICANCE: HR-MAS MR metabolomics on intact breast tissues obtained by core needle biopsy may have a potential to be used as a complement to the current diagnostic and prognostic measures for breast cancers

    CRISPR Recognition Tool (CRT): a tool for automatic detection of clustered regularly interspaced palindromic repeats

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    <p>Abstract</p> <p>Background</p> <p>Clustered Regularly Interspaced Palindromic Repeats (CRISPRs) are a novel type of direct repeat found in a wide range of bacteria and archaea. CRISPRs are beginning to attract attention because of their proposed mechanism; that is, defending their hosts against invading extrachromosomal elements such as viruses. Existing repeat detection tools do a poor job of identifying CRISPRs due to the presence of unique spacer sequences separating the repeats. In this study, a new tool, CRT, is introduced that rapidly and accurately identifies CRISPRs in large DNA strings, such as genomes and metagenomes.</p> <p>Results</p> <p>CRT was compared to CRISPR detection tools, Patscan and Pilercr. In terms of correctness, CRT was shown to be very reliable, demonstrating significant improvements over Patscan for measures precision, recall and quality. When compared to Pilercr, CRT showed improved performance for recall and quality. In terms of speed, CRT proved to be a huge improvement over Patscan. Both CRT and Pilercr were comparable in speed, however CRT was faster for genomes containing large numbers of repeats.</p> <p>Conclusion</p> <p>In this paper a new tool was introduced for the automatic detection of CRISPR elements. This tool, CRT, showed some important improvements over current techniques for CRISPR identification. CRT's approach to detecting repetitive sequences is straightforward. It uses a simple sequential scan of a DNA sequence and detects repeats directly without any major conversion or preprocessing of the input. This leads to a program that is easy to describe and understand; yet it is very accurate, fast and memory efficient, being O(<it>n</it>) in space and O(<it>nm</it>/<it>l</it>) in time.</p

    Pairwise statistical significance of local sequence alignment using multiple parameter sets and empirical justification of parameter set change penalty

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    Background: Accurate estimation of statistical significance of a pairwise alignment is an important problem in sequence comparison. Recently, a comparative study of pairwise statistical significance with database statistical significance was conducted. In this paper, we extend the earlier work on pairwise statistical significance by incorporating with it the use of multiple parameter sets. Results: Results for a knowledge discovery application of homology detection reveal that using multiple parameter sets for pairwise statistical significance estimates gives better coverage than using a single parameter set, at least at some error levels. Further, the results of pairwise statistical significance using multiple parameter sets are shown to be significantly better than database statistical significance estimates reported by BLAST and PSI-BLAST, and comparable and at times significantly better than SSEARCH. Using non-zero parameter set change penalty values give better performance than zero penalty. Conclusion: The fact that the homology detection performance does not degrade when using multiple parameter sets is a strong evidence for the validity of the assumption that the alignment score distribution follows an extreme value distribution even when using multiple parameter sets. Parameter set change penalty is a useful parameter for alignment using multiple parameter sets. Pairwise statistical significance using multiple parameter sets can be effectively used to determine the relatedness of a (or a few) pair(s) of sequences without performing a time-consuming database search
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