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Make It Happen with Will Polston - Episode - 87 - Personal Mastery with Dr. Agi Keramidas Episode Notes Make It Happen with Will Polston - Episode - 87 - Personal Mastery with Dr. Agi Keramidas Make It Happen with Will Polston is a weekly podcast that consists of a combination of episodes with Mindset Strategist Will Polston and episodes with Will's guests from around the world providing you with insights on how you can transform your excuses into results to benefit yourself, your family, your friends, your community, society, humanity and the universe, what he calls - The Ripple Effect. Agi Keramidas grew up in Greece, and in 2010 he moved to the UK following a dream he had since a teenager. He's been a dentist for 20+ years, but the identity he embodies now is a knowledge broker and podcaster. He is passionate about personal development, and a lifelong student himself - continuously striving to evolve, realising his potential, and helping others do the same. He is the host of "Personal Development Mastery" podcast, and his mission is to influence and inspire people to stand out and take action towards the next level of their lives. In this episode, Will has Dr. Agi as his guest and they talk about: - How a proper mindset helped him find clarity - The power of compounding and building momentum - The lessons he learned from Unlock Your Potential - Effort vs. Results To find out more about Dr. Agi Keramidas, click here. Check out Dr. Agi's podcast here! Join the free Make It Happen Community Facebook group by clicking here. Take the 5-Minute Quiz that Reveals What's Preventing You from Living a Purposeful, Inspired and Energised Life You Love by clicking here.

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.13.380733v1?rss=1 Authors: Lozupone, C. A., Shaffer, M., Thurimella, K. Abstract: Background: Microbiome studies are often limited by a lack of statistical power due to small sample sizes and a large number of features. This problem is exacerbated in correlative studies of multi-omic datasets. Statistical power can be increased by finding and summarizing modules of correlated observations. Additionally, modules provide biological insight as groups of microbes can have relationships among themselves. Results: To address these challenges we developed SCNIC: Sparse Cooccurrence Network Investigation for Compositional data. SCNIC is open-source software that can generate correlation networks and detect and summarize modules of highly correlated features. We applied SCNIC to a published dataset comparing microbiome composition in men who have sex with men (MSM) who were at a high risk of contracting HIV to non-MSM. By applying SCNIC we achieved increased statistical power and identified microbes that not only differed with MSM-status, but also correlated strongly with each other, suggesting shared environmental drivers or cooperative relationships among them. Conclusions: SCNIC provides an easy way to generate correlation networks, identify modules of correlated features and summarize them for downstream statistical analysis. Although SCNIC was designed considering properties of microbiome data, such as compositionality, it can be applied to a variety of data types including metabolomics data and used to integrate multiple data types. Using SCNIC allows for the identification of functional microbial relationships at scale while increasing statistical power. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.07.373043v1?rss=1 Authors: Qiu, Y., Wang, J., Lei, J., Roeder, K. Abstract: Motivation: Marker genes, defined as genes that are expressed primarily in a single cell type, can be identified from the single cell transcriptome; however, such data are not always available for the many uses of marker genes, such as deconvolution of bulk tissue. Marker genes for a cell type, however, are highly correlated in bulk data, because their expression levels depend primarily on the proportion of that cell type in the samples. Therefore, when many tissue samples are analyzed, it is possible to identify these marker genes from the correlation pattern. Results: To capitalize on this pattern, we develop a new algorithm to detect marker genes by combining published information about likely marker genes with bulk transcriptome data in the form of a semi-supervised algorithm. The algorithm then exploits the correlation structure of the bulk data to refine the published marker genes by adding or removing genes from the list. Availability and implementation: We implement this method as an R package markerpen, hosted on https://github.com/yixuan/markerpen. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.02.365049v1?rss=1 Authors: Verma, S., Dwivedy, A., Kumar, N., Biswal, B. K. Abstract: Background: Over the past two decades, there has been a continued research on the role of small non-coding RNAs including microRNAs (miRNAs) in various diseases. Studies have shown that viruses modulate the host cellular machinery and hijack its metabolic and immune signaling pathways by miRNA mediated gene silencing. Given the immensity of coronavirus disease 19 (COVID-19) pandemic and the strong association of viral encoded miRNAs with their pathogenesis, it is important to study Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) miRNAs. Results: To address this unexplored area, we identified 8 putative novel miRNAs from SARS-CoV-2 genome and explored their possible human gene targets. A significant proportion of these targets populated key immune and metabolic pathways such as MAPK signaling pathway, maturity-onset diabetes of the young, Insulin signaling pathway, endocytosis, RNA transport, TGF-{beta} signaling pathway, to name a few. The data from this work is backed up by recently reported high-throughput transcriptomics datasets obtains from SARS-CoV-2 infected samples. Analysis of these datasets reveal that a significant proportion of the target human genes were down-regulated upon SARS-CoV-2 infection. Conclusions: The current study brings to light probable host metabolic and immune pathways susceptible to viral miRNA mediated silencing in a SARS-CoV-2 infection, and discusses its effects on the host pathophysiology. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.17.343020v1?rss=1 Authors: Abante, J., Goutsias, J. Abstract: Motivation: Identifying regions of the genome that demonstrate significant differences in DNA methylation between groups of samples is an important problem in computational epigenetics. Available methods assume that methylation occurs in a statistically independent manner at individual cytosine-phosphate-guanine (CpG) sites or perform analysis using empirically estimated joint probability distributions of methylation patterns at no more than 4 contiguous CpG sites. These approaches can lead to poor detection performance and loss of reliability and reproducibility due to reduced specificity and sensitivity in the presence of insufficient data. Results: To accommodate data obtained with different bisulfite sequencing technologies, such as RRBS, ERRBS, and WGBS, and improve statistical power, we developed CpelTdm.jl, a Julia package for targeted differential analysis of DNA methylation stochasticity between groups of unmatched or matched samples. This package performs rigorous statistical analysis of methylation patterns within regions of the genome specified by the user that takes into account correlations in methylation and results in robust detection of genomic regions exhibiting statistically significant differences in methylation stochasticity. CpelTdm.jl does not only detect mean methylation differences, as it is commonly done by previous methods, but also differences in methylation entropy and, more generally, between probability distributions of methylation. Availability and Implementation: This Julia package is supported for Windows, macOS, and Linux, and can be freely downloaded from GitHub: https://github.com/jordiabante/CpelTdm.jl . Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.05.326504v1?rss=1 Authors: Robeson, M. S., O'Rourke, D. R., Kaehler, B. D., Ziemski, M., Dillon, M. R., Foster, J. T., Bokulich, N. A. Abstract: Background: Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardizations limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a software package for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. Results: To highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA, and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. Conclusions: RESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.09.27.315937v1?rss=1 Authors: Cao, Y., Shen, Y. Abstract: Motivation: Facing the increasing gap between high-throughput sequence data and limited functional insights, computational protein function annotation provides a high-throughput alternative to experimental approaches. However, current methods can have limited applicability while relying on data besides sequences, or lack generalizability to novel sequences, species and functions. Results: To overcome aforementioned barriers in applicability and generalizability, we propose a novel deep learning model, named Transformer-based protein function Annotation through joint sequence--Label Embedding (TALE). For generalizbility to novel sequences we use self attention-based transformers to capture global patterns in sequences. For generalizability to unseen or rarely seen functions, we also embed protein function labels (hierarchical GO terms on directed graphs) together with inputs/features (sequences) in a joint latent space. Combining TALE and a sequence similarity-based method, TALE+ outperformed competing methods when only sequence input is available. It even outperformed a state-of-the-art method using network information besides sequence, in two of the three gene ontologies. Furthermore, TALE and TALE+ showed superior generalizability to proteins of low homology and never/rarely annotated novel species or functions compared to training data, revealing deep insights into the protein sequence-function relationship. Ablation studies elucidated contributions of algorithmic components toward the accuracy and the generalizability. Copy rights belong to original authors. Visit the link for more info

Background: The purpose of this prospective study was to perform a head-to-head comparison of the two methods most frequently used for evaluation of carotid plaque characteristics: Multi-detector Computed Tomography Angiography (MDCTA) and black-blood 3 T-cardiovascular magnetic resonance (bb-CMR) with respect to their ability to identify symptomatic carotid plaques. Methods: 22 stroke unit patients with unilateral symptomatic carotid disease and > 50% stenosis by duplex ultrasound underwent MDCTA and bb-CMR (TOF, pre- and post-contrast fsT1w-, and fsT2w-sequences) within 15 days of symptom onset. Both symptomatic and contralateral asymptomatic sides were evaluated. By bb-CMR, plaque morphology, composition and prevalence of complicated AHA type VI lesions (AHA-LT6) were evaluated. By MDCTA, plaque type (non-calcified, mixed, calcified), plaque density in HU and presence of ulceration and/or thrombus were evaluated. Sensitivity (SE), specificity (SP), positive and negative predictive value (PPV, NPV) were calculated using a 2-by-2-table. Results: To distinguish between symptomatic and asymptomatic plaques AHA-LT6 was the best CMR variable and presence/absence of plaque ulceration was the best CT variable, resulting in a SE, SP, PPV and NPV of 80%, 80%, 80% and 80% for AHA-LT6 as assessed by bb-CMR and 40%, 95%, 89% and 61% for plaque ulceration as assessed by MDCTA. The combined SE, SP, PPV and NPV of bb-CMR and MDCTA was 85%, 75%, 77% and 83%, respectively. Conclusions: Bb-CMR is superior to MDCTA at identifying symptomatic carotid plaques, while MDCTA offers high specificity at the cost of low sensitivity. Results were only slightly improved over bb-CMR alone when combining both techniques.

Background: Murine gammaherpesvirus 68 (MHV-68) is used as a model to study the function of gammaherpesvirus glycoproteins. gp150 of MHV-68, encoded by open reading frame M7, is a positional homolog of gp350/220 of EBV and of gp35/37 of KSHV. Since it had been proposed that gp350/220 of EBV might be a suitable vaccine antigen to protect from EBV-associated diseases, gp150 has been applied as a model vaccine in the MHV-68 system. When analyzing the function of gp150, previous studies yielded conflicting results on the role of gp150 in latency amplification, and disparities between the mutant viruses which had been analyzed were blamed for the observed differences. Results: To further develop MHV-68 as model to study the function of gammaherpesvirus glycoproteins in vivo, it is important to know whether gp150 contributes to latency amplification or not. Thus, we re-evaluated this question by testing a number of gp150 mutants side by side. Our results suggest that gp150 is dispensable for latency amplification. Furthermore, we investigated the effect of vaccination with gp150 using gp150-containing exosomes. Vaccination with gp150 induced a strong humoral and cellular immune response, yet it did not affect a subsequent MHV-68 challenge infection. Conclusions: In this study, we found no evidence for a role of gp150 in latency amplification. The previously observed contradictory results on the role of gp150 in latency amplification were not related to differences between the mutant viruses which had been used.

Background: Sequencing of mRNA (RNA-seq) by next generation sequencing technologies is widely used for analyzing the transcriptomic state of a cell. Here, one of the main challenges is the mapping of a sequenced read to its transcriptomic origin. As a simple alignment to the genome will fail to identify reads crossing splice junctions and a transcriptome alignment will miss novel splice sites, several approaches have been developed for this purpose. Most of these approaches have two drawbacks. First, each read is assigned to a location independent on whether the corresponding gene is expressed or not, i.e. information from other reads is not taken into account. Second, in case of multiple possible mappings, the mapping with the fewest mismatches is usually chosen which may lead to wrong assignments due to sequencing errors. Results: To address these problems, we developed ContextMap which efficiently uses information on the context of a read, i.e. reads mapping to the same expressed region. The context information is used to resolve possible ambiguities and, thus, a much larger degree of ambiguities can be allowed in the initial stage in order to detect all possible candidate positions. Although ContextMap can be used as a stand-alone version using either a genome or transcriptome as input, the version presented in this article is focused on refining initial mappings provided by other mapping algorithms. Evaluation results on simulated sequencing reads showed that the application of ContextMap to either TopHat or MapSplice mappings improved the mapping accuracy of both initial mappings considerably. Conclusions: In this article, we show that the context of reads mapping to nearby locations provides valuable information for identifying the best unique mapping for a read. Using our method, mappings provided by other state-of-the-art methods can be refined and alignment accuracy can be further improved.

Background: Immunization against amyloid-beta (A beta), the peptide that accumulates in the form of senile plaques and in the cerebrovasculature in Alzheimer's disease (AD), causes a dramatic immune response that prevents plaque formation and clears accumulated A beta in transgenic mice. In a clinical trial of A beta immunization, some patients developed meningoencephalitis and hemorrhages. Neuropathological investigations of patients who died after the trial showed clearance of amyloid pathology, but also a powerful immune response involving activated T cells probably underlying the negative effects of the immunization. Results: To define the impact of T cells on this inflammatory response we used passive immunization and adoptive transfer to separate the effect of IgG and T cell mediated effects on microhemorrhage in APPPS1 transgenic mice. Neither anti A beta IgG nor adoptively transferred T cells, alone, led to increased cerebrovascular damage. However, the combination of adoptively transferred T cells and passive immunization led to massive cerebrovascular bleeding that ranged from multiple microhemorrhages in the parenchyma to large hematomas. Conclusions: Our results indicate that vaccination can lead to A beta and T cell induced cerebral micro-hemorrhages and acute hematomas, which are greatly exacerbated by T cell mediated activity.

Background: Given the considerable toxicity and modest benefit of adjuvant chemotherapy for non-small cell lung cancer (NSCLC), there is clearly a need for new treatment modalities in the adjuvant setting. Active specific immunotherapy may represent such an option. However, clinical responses have been rare so far. Manipulating the host by inducing lymphopenia before vaccination resulted in a magnification of the immune response in the preclinical setting. To evaluate feasibility and safety of an irradiated, autologous tumor cell vaccine given following induction of lymphopenia by chemotherapy and reinfusion of autologous peripheral blood mononuclear cells (PBMC), we are currently conducting a pilot-phase I clinical trial in patients with NSCLC following surgical resection. This paper reports on the first clinical experience and evidence of an immune response in patients suffering from NSCLC. Methods: NSCLC patients stages I-IIIA are recruited. Vaccines are generated from their resected lung specimens. Patients undergo leukapheresis to harvest their PBMC prior to or following the surgical procedure. Furthermore, patients receive preparative chemotherapy ( cyclophosphamide 350 mg/m(2) and fludarabine 20 mg/m(2) on 3 consecutive days) for induction of lymphopenia followed by reconstitution with their autologous PBMC. Vaccines are administered intradermally on day 1 following reconstitution and every two weeks for a total of up to five vaccinations. Granulocytemacrophagecolony- stimulating-factor (GM-CSF) is given continuously ( at a rate of 50 mu g/24 h) at the site of vaccination via minipump for six consecutive days after each vaccination. Results: To date, vaccines were successfully manufactured for 4 of 4 patients. The most common toxicities were local injection-site reactions and mild constitutional symptoms. Immune responses to chemotherapy, reconstitution and vaccination are measured by vaccine site and delayed type hypersensitivity (DTH) skin reactions. One patient developed positive DTH skin tests so far. Immunohistochemical assessment of punch biopsies taken at the local vaccine site reaction revealed a dense lymphocyte infiltrate. Further immunohistochemical differentiation showed that CD1a+ cells had been attracted to the vaccine site as well as predominantly CD4+ lymphocytes. The 3-day combination chemotherapy consisting of cyclophosphamide and fludarabine induced a profound lymphopenia in all patients. Sequential FACS analysis revealed that different T cell subsets (CD4, CD8, CD4CD25) as well as granulocytes, B cells and NK cells were significantly reduced. Here, we report on clinical safety and feasibility of this vaccination approach during lymphoid recovery and demonstrate a patient example. Conclusion: Thus far, all vaccines were well tolerated. The overall trial design seems safe and feasible. Vaccine site reactions associated with infusion of GM-CSF via mini-pump are consistent with the postulated mechanism of action. More detailed immune-monitoring is required to evaluate a potential systemic immune response. Further studies to exploit homeostasis-driven T cell proliferation for the induction of a specific anti-tumor immune response in this clinical setting are warranted.