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World Journal of Psychiatry Dec 2012Several parallels exist between platelets and the brain, which make them interesting for studying the neurobiology of psychiatric disorders, such as Alzheimer's disease,...
Several parallels exist between platelets and the brain, which make them interesting for studying the neurobiology of psychiatric disorders, such as Alzheimer's disease, depression, schizophrenia and anxiety disorders. Platelets store, secrete and process the amyloid precursor protein which is cleaved into the β-amyloid (Aβ) peptides. The accumulation of Aβ in brain (plaques) and vessels (Aβ-angiopathy) is a major hallmark in AD. Platelets contain high amounts of serotonin and a dysfunction of the serotoninergic system is involved in the development of several behavior disorders, such as depression, anxiety disorders and self aggressive disturbances. Furthermore, platelets are able to take up dopamine and express various dopamine receptors, which make them to an interesting tool to study the underlying mechanisms of schizophrenia. In summary, platelets are an interesting and easily accessible cell type to study changes related to different psychiatric disorders and platelets proteins may be useful as diagnostic biomarkers for some psychiatric disorders.
PubMed: 24175174
DOI: 10.5498/wjp.v2.i6.91 -
Molecular and Cellular Endocrinology Jul 2013Rodents are clearly valuable models for assessing disruption of fertility. The effects of different steroid treatments at different stages of reproductive life through... (Review)
Review
Rodents are clearly valuable models for assessing disruption of fertility. The effects of different steroid treatments at different stages of reproductive life through from fetal to adult have been assessed for effects on fertility, ovarian morphology, hypothalamic-pituitary function or metabolic consequences. The results show that steroid treatments do disrupt fertility in many cases, but the underlying mechanisms are complicated by the effects of the different treatments at multiple sites. As models for PCOS at the ovarian level however, there are a number of problems particularly related to the fact that rodents are multi-ovular species. Apart from an absence of ovulation and corpora lutea, many of the different steroid regimes result in an increase in large atretic, or cystic follicles that do not parallel PCOS in women. Indeed a number of treatments are given at times when they will cause disruption of the positive feedback effects of estradiol, thus blocking ovulation in adult life. The resulting ovarian morphology thus appears to be like that of PCOS but is in fact not a clear mimic. This review of the various studies highlights parallels and problems with the use of rodents to study the mechanisms underlying the development of PCOS in women.
Topics: Animals; Disease Models, Animal; Female; Gonadal Steroid Hormones; Humans; Ovary; Pituitary Gland; Polycystic Ovary Syndrome; Rodentia
PubMed: 23098676
DOI: 10.1016/j.mce.2012.10.007 -
Genes Nov 2019Genomic biomarkers such as DNA methylation (DNAm) are employed for age prediction. In recent years, several studies have suggested the association between changes in...
Genomic biomarkers such as DNA methylation (DNAm) are employed for age prediction. In recent years, several studies have suggested the association between changes in DNAm and its effect on human age. The high dimensional nature of this type of data significantly increases the execution time of modeling algorithms. To mitigate this problem, we propose a two-stage parallel algorithm for selection of age related CpG-sites. The algorithm first attempts to cluster the data into similar age ranges. In the next stage, a parallel genetic algorithm (PGA), based on the MapReduce paradigm (MR-based PGA), is used for selecting age-related features of each individual age range. In the proposed method, the execution of the algorithm for each age range (data parallel), the evaluation of chromosomes (task parallel) and the calculation of the fitness function (data parallel) are performed using a novel parallel framework. In this paper, we consider 16 different healthy DNAm datasets that are related to the human blood tissue and that contain the relevant age information. These datasets are combined into a single unioned set, which is in turn randomly divided into two sets of train and test data with a ratio of 7:3, respectively. We build a Gradient Boosting Regressor (GBR) model on the selected CpG-sites from the train set. To evaluate the model accuracy, we compared our results with state-of-the-art approaches that used these datasets, and observed that our method performs better on the unseen test dataset with a Mean Absolute Deviation (MAD) of 3.62 years, and a correlation (R) of 95.96% between age and DNAm. In the train data, the MAD and R are 1.27 years and 99.27%, respectively. Finally, we evaluate our method in terms of the effect of parallelization in computation time. The algorithm without parallelization requires 4123 min to complete, whereas the parallelized execution on 3 computing machines having 32 processing cores each, only takes a total of 58 min. This shows that our proposed algorithm is both efficient and scalable.
Topics: Aging; Algorithms; Computational Biology; CpG Islands; DNA Methylation; Epigenesis, Genetic; Genetic Fitness; Humans; Models, Genetic
PubMed: 31775313
DOI: 10.3390/genes10120969 -
Computational Intelligence and... 2021In high-paced and efficient life and work, fatigue is one of the important factors that cause accidents such as traffic and medical accidents. This study designs a...
In high-paced and efficient life and work, fatigue is one of the important factors that cause accidents such as traffic and medical accidents. This study designs a feature map-based pruning strategy (PFM), which effectively reduces redundant parameters and reduces the time and space complexity of parallelized deep convolutional neural network (DCNN) training; a correction is proposed in the Map stage. The secant conjugate gradient method (CGMSE) realizes the fast convergence of the conjugate gradient method and improves the convergence speed of the network; in the Reduce stage, a load balancing strategy to control the load rate (LBRLA) is proposed to achieve fast and uniform data grouping to ensure the parallelization performance of the parallel system. Finally, the related fatigue algorithm's research and simulation based on the human eye are carried out on the PC. The human face and eye area are detected from the video image collected using the USB camera, and the frame difference method and the position information of the human eye on the face are used. To track the human eye area, extract the relevant human eye fatigue characteristics, combine the blink frequency, closed eye duration, PERCLOS, and other human eye fatigue determination mechanisms to determine the fatigue state, and test and verify the designed platform and algorithm through experiments. This system is designed to enable people who doze off, such as drivers, to discover their state in time through the system and reduce the possibility of accidents due to fatigue.
Topics: Algorithms; Big Data; Blinking; Computer Simulation; Humans; Neural Networks, Computer
PubMed: 34335710
DOI: 10.1155/2021/2747940 -
European Journal of Cell Biology Jun 2023The neuronal ceroid lipofuscinoses (NCLs), collectively referred to as Batten disease, are a group of fatal neurodegenerative disorders that primarily affect children.... (Review)
Review
The neuronal ceroid lipofuscinoses (NCLs), collectively referred to as Batten disease, are a group of fatal neurodegenerative disorders that primarily affect children. The etiology of Batten disease is linked to mutations in 13 genes that encode distinct CLN proteins, whose functions have yet to be fully elucidated. The social amoeba Dictyostelium discoideum has been adopted as an efficient and powerful model system for studying the diverse cellular roles of CLN proteins. The genome of D. discoideum encodes several homologs of human CLN proteins, and a growing body of literature supports the conserved roles and networking of CLN proteins in D. discoideum and humans. In humans, CLN proteins have diverse cellular roles related to autophagy, signal transduction, lipid homeostasis, lysosomal ion homeostasis, and intracellular trafficking. Recent work also indicates that CLN proteins play an important role in protein secretion. Remarkably, many of these findings have found parallels in studies with D. discoideum. Accordingly, this review will highlight the translatable value of novel work with D. discoideum in the field of NCL research and propose further avenues of research using this biomedical model organism for studying the NCLs.
Topics: Child; Humans; Dictyostelium; Neuronal Ceroid-Lipofuscinoses; Proteins; Lysosomes; Mutation
PubMed: 36917916
DOI: 10.1016/j.ejcb.2023.151305 -
Cell Reports Methods Jan 2024New technologies and large-cohort studies have enabled novel variant discovery and association at unprecedented scale, yet functional characterization of these variants...
New technologies and large-cohort studies have enabled novel variant discovery and association at unprecedented scale, yet functional characterization of these variants remains paramount to deciphering disease mechanisms. Approaches that facilitate parallelized genome editing of cells of interest or induced pluripotent stem cells (iPSCs) have become critical tools toward this goal. Here, we developed an approach that incorporates libraries of CRISPR-Cas9 guide RNAs (gRNAs) together with inducible Cas9 into a piggyBac (PB) transposon system to engineer dozens to hundreds of genomic variants in parallel against isogenic cellular backgrounds. This method empowers loss-of-function (LoF) studies through the introduction of insertions or deletions (indels) and copy-number variants (CNVs), though generating specific nucleotide changes is possible with prime editing. The ability to rapidly establish high-quality mutational models at scale will facilitate the development of isogenic cellular collections and catalyze comparative functional genomic studies investigating the roles of hundreds of genes and mutations in development and disease.
Topics: Humans; CRISPR-Cas Systems; Gene Editing; Mutation; Induced Pluripotent Stem Cells; Genomics
PubMed: 38091988
DOI: 10.1016/j.crmeth.2023.100672 -
Acoustic Constraints and Musical Consequences: Exploring Composers' Use of Cues for Musical Emotion.Frontiers in Psychology 2017Emotional communication in music is based in part on the use of pitch and timing, two cues effective in emotional speech. Corpus analyses of natural speech illustrate... (Review)
Review
Emotional communication in music is based in part on the use of pitch and timing, two cues effective in emotional speech. Corpus analyses of natural speech illustrate that happy utterances tend to be higher and faster than sad. Although manipulations altering melodies show that passages changed to be higher and faster sound happier, corpus analyses of unaltered music paralleling those of natural speech have proven challenging. This partly reflects the importance of modality (i.e., major/minor), a powerful musical cue whose use is decidedly imbalanced in Western music. This imbalance poses challenges for creating musical corpora analogous to existing speech corpora for purposes of analyzing emotion. However, a novel examination of music by Bach and Chopin balanced in modality illustrates that, consistent with predictions from speech, their major key (nominally "happy") pieces are approximately a major second higher and 29% faster than their minor key pieces (Poon and Schutz, 2015). Although this provides useful evidence for parallels in use of emotional cues between these domains, it raises questions about how composers "trade off" cue differentiation in music, suggesting interesting new potential research directions. This places those results in a broader context, highlighting their connections with previous work on the natural use of cues for musical emotion. Together, these observational findings based on unaltered music-widely recognized for its artistic significance-complement previous experimental work systematically manipulating specific parameters. In doing so, they also provide a useful musical counterpart to fruitful studies of the acoustic cues for emotion found in natural speech.
PubMed: 29249997
DOI: 10.3389/fpsyg.2017.01402 -
Frontiers in Oncology 2020The immune escape mechanisms at the base of tumor progression in endometrial cancer mimic immune tolerance mechanisms occurring at the maternal-fetal interface. The... (Review)
Review
The immune escape mechanisms at the base of tumor progression in endometrial cancer mimic immune tolerance mechanisms occurring at the maternal-fetal interface. The biological and immunological processes behind the maternal-fetal interface are finely tuned in time and space during embryo implantation and subsequent pregnancy stages; conversely, those behind cancer progression are often aberrant. The environment composition at the maternal-fetal interface parallels the pro-tumor microenvironment identified in many cancers, pointing to the possibility for the use of the maternal-fetal interface as a model to depict immune therapeutic targets in cancer. The framework of cancer environment signatures involved in immune adaptations, precisely timed in cancer progression, could reveal a specific "immune clock" in endometrial cancer, which might guide clinicians in patient risk class assessment, diagnostic workup, management, surgical and therapeutic approach, and surveillance strategies. Here, we review studies approaching this hypothesis, focusing on what is known so far about oncofetal similarities in immunity with the idea to individualize personalized immunotherapy targets, through the downregulation of the immune escape stage or the reactivation of the pro-inflammatory processes suppressed by the tumor.
PubMed: 32226771
DOI: 10.3389/fonc.2020.00156 -
Analytical Chemistry Sep 2022Proteomic analysis on the scale that captures population and biological heterogeneity over hundreds to thousands of samples requires rapid mass spectrometry methods,...
Proteomic analysis on the scale that captures population and biological heterogeneity over hundreds to thousands of samples requires rapid mass spectrometry methods, which maximize instrument utilization (IU) and proteome coverage while maintaining precise and reproducible quantification. To achieve this, a short liquid chromatography gradient paired to rapid mass spectrometry data acquisition can be used to reproducibly quantify a moderate set of analytes. High-throughput profiling at a limited depth is becoming an increasingly utilized strategy for tackling large sample sets but the time spent on loading the sample, flushing the column(s), and re-equilibrating the system reduces the ratio of meaningful data acquired to total operation time and IU. The dual-trap single-column configuration (DTSC) presented here maximizes IU in rapid analysis (15 min per sample) of blood and cell lysates by parallelizing trap column cleaning and sample loading and desalting with the analysis of the previous sample. We achieved 90% IU in low microflow (9.5 μL/min) analysis of blood while reproducibly quantifying 300-400 proteins and over 6000 precursor ions. The same IU was achieved for cell lysates and over 4000 proteins (3000 at CV below 20%) and 40,000 precursor ions were quantified at a rate of 15 min/sample. Thus, DTSC enables high-throughput epidemiological blood-based biomarker cohort studies and cell-based perturbation screening.
Topics: Biomarkers; Chromatography, Liquid; Humans; Mass Spectrometry; Proteome; Proteomics
PubMed: 36044770
DOI: 10.1021/acs.analchem.2c02609 -
Journal of Digital Imaging Aug 2018The aim of this study was to develop an open-source, modular, locally run or server-based system for 3D radiomics feature computation that can be used on any computer... (Review)
Review
The aim of this study was to develop an open-source, modular, locally run or server-based system for 3D radiomics feature computation that can be used on any computer system and included in existing workflows for understanding associations and building predictive models between image features and clinical data, such as survival. The QIFE exploits various levels of parallelization for use on multiprocessor systems. It consists of a managing framework and four stages: input, pre-processing, feature computation, and output. Each stage contains one or more swappable components, allowing run-time customization. We benchmarked the engine using various levels of parallelization on a cohort of CT scans presenting 108 lung tumors. Two versions of the QIFE have been released: (1) the open-source MATLAB code posted to Github, (2) a compiled version loaded in a Docker container, posted to DockerHub, which can be easily deployed on any computer. The QIFE processed 108 objects (tumors) in 2:12 (h/mm) using 1 core, and 1:04 (h/mm) hours using four cores with object-level parallelization. We developed the Quantitative Image Feature Engine (QIFE), an open-source feature-extraction framework that focuses on modularity, standards, parallelism, provenance, and integration. Researchers can easily integrate it with their existing segmentation and imaging workflows by creating input and output components that implement their existing interfaces. Computational efficiency can be improved by parallelizing execution at the cost of memory usage. Different parallelization levels provide different trade-offs, and the optimal setting will depend on the size and composition of the dataset to be processed.
Topics: Diffusion of Innovation; Evaluation Studies as Topic; Humans; Image Processing, Computer-Assisted; Imaging, Three-Dimensional; Positron-Emission Tomography; Quality Control; Radiology, Interventional; Tomography, X-Ray Computed
PubMed: 28993897
DOI: 10.1007/s10278-017-0019-x