Identifying and quantifying heterogeneity in high content analysis: Application of heterogeneity indices to drug discovery

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology. © 2014 Gough et al

A review of UAV Visual Detection and Tracking Methods

This paper presents a review of techniques used for the detection and tracking of UAVs or drones. There are different techniques that depend on collecting measurements of the position, velocity, and image of the UAV and then using them in detection and tracking. Hybrid detection techniques are also presented. The paper is a quick reference for a wide spectrum of methods that are used in the drone detection process.Comment: 10 page

Review of Application of Artificial Neural Networks in Textiles and Clothing Industries over Last Decades

2010-2011 > Academic research: refereed > Chapter in an edited book (author

Adaptive distance-based band hierarchy (ADBH) for effective hyperspectral band selection.

Band selection has become a significant issue for the efficiency of the hyperspectral image (HSI) processing. Although many unsupervised band selection (UBS) approaches have been developed in the last decades, a flexible and robust method is still lacking. The lack of proper understanding of the HSI data structure has resulted in the inconsistency in the outcome of UBS. Besides, most of the UBS methods are either relying on complicated measurements or rather noise sensitive, which hinder the efficiency of the determined band subset. In this article, an adaptive distance-based band hierarchy (ADBH) clustering framework is proposed for UBS in HSI, which can help to avoid the noisy bands while reflecting the hierarchical data structure of HSI. With a tree hierarchy-based framework, we can acquire any number of band subset. By introducing a novel adaptive distance into the hierarchy, the similarity between bands and band groups can be computed straightforward while reducing the effect of noisy bands. Experiments on four datasets acquired from two HSI systems have fully validated the superiority of the proposed framework

Genomic patterns of malignant peripheral nerve sheath tumor (MPNST) evolution correlate with clinical outcome and are detectable in cell-free DNA

UNLABELLED: Malignant peripheral nerve sheath tumor (MPNST), an aggressive soft-tissue sarcoma, occurs in people with neurofibromatosis type 1 (NF1) and sporadically. Whole-genome and multiregional exome sequencing, transcriptomic, and methylation profiling of 95 tumor samples revealed the order of genomic events in tumor evolution. Following biallelic inactivation of NF1, loss of CDKN2A or TP53 with or without inactivation of polycomb repressive complex 2 (PRC2) leads to extensive somatic copy-number aberrations (SCNA). Distinct pathways of tumor evolution are associated with inactivation of PRC2 genes and H3K27 trimethylation (H3K27me3) status. Tumors with H3K27me3 loss evolve through extensive chromosomal losses followed by whole-genome doubling and chromosome 8 amplification, and show lower levels of immune cell infiltration. Retention of H3K27me3 leads to extensive genomic instability, but an immune cell-rich phenotype. Specific SCNAs detected in both tumor samples and cell-free DNA (cfDNA) act as a surrogate for H3K27me3 loss and immune infiltration, and predict prognosis. SIGNIFICANCE: MPNST is the most common cause of death and morbidity for individuals with NF1, a relatively common tumor predisposition syndrome. Our results suggest that somatic copy-number and methylation profiling of tumor or cfDNA could serve as a biomarker for early diagnosis and to stratify patients into prognostic and treatment-related subgroups. This article is highlighted in the In This Issue feature, p. 517

Genomic patterns of malignant peripheral nerve sheath tumor (MPNST) evolution correlate with clinical outcome and are detectable in cell-free DNA

Malignant peripheral nerve sheath tumor (MPNST), an aggressive soft-tissue sarcoma, occurs in people with neurofibromatosis type 1 (NF1) and sporadically. Whole-genome and multiregional exome sequencing, transcriptomic, and methylation profiling of 95 tumor samples revealed the order of genomic events in tumor evolution. Following biallelic inactivation of NF1, loss of CDKN2A or TP53 with or without inactivation of polycomb repressive complex 2 (PRC2) leads to extensive somatic copy-number aberrations (SCNA). Distinct pathways of tumor evolution are associated with inactivation of PRC2 genes and H3K27 trimethylation (H3K27me3) status. Tumors with H3K27me3 loss evolve through extensive chromosomal losses followed by whole-genome doubling and chromosome 8 amplification, and show lower levels of immune cell infiltration. Retention of H3K27me3 leads to extensive genomic instability, but an immune cell-rich phenotype. Specific SCNAs detected in both tumor samples and cell-free DNA (cfDNA) act as a surrogate for H3K27me3 loss and immune infiltration, and predict prognosis

<i>Staphylococcus aureus</i> virulence gene studies : a comparative microarray based approach

The development and application of a partial composite S. aureus virulence-associated gene micro array is described. Epidemic, pandemic and sporadic lineages of healthcare associated(HA-) and community-associated (CA-) S. aureus were compared. The clonal population structure was supported but further evidence for large-scale recombination events was obtained. Phage structural genes linked with the CA phenotype were identified and in silico analysis revealed these to be correlated with phage serogroup. CA strains generally carried a PVL-associated phage either of the A or Fb serogroup, whilst the HA strains predominantly carried sero group B phage. It is proposed that carriage of PVL associated phage rather than the specific pvl genes is correlated with the CA phenotype.These findings further support the role of the accessory genome in shaping the epidemiology of S. aureus.The microarray was used to study gene expression in isogenic strains differing by a deletion in the agr locus. Microarray analysis revealed significant differences between the levels of expression of several genes of the normal and mutant strains. However, RNAIII levels in the non-mutant strain were found to be cell density independent, indicating that the expected quorum sensing mechanism was not functional.Expression profiles of cells grown under biofilm simulating conditions were compared to their planktonic counterparts. Biofilm cells displayed a typical expression profile that was different from both the actively growing planktonic exponential cells and the planktonic stationary cells. The strongest feature of the biofilm state was high level expression of the haemolysin genes. This model therefore is amenable to exploitation in studies designed to improve our understanding of the mechanisms underlining biofilm survival and regulation after long periods of growth

Sarcoma ecosystems : spatial characterization and prognostic significance

Sarcoma is a highly heterogeneous disease with complex biological activities and unique tumor microenvironments (TME) in distinct subtypes. The limited treatment options and inadequate responses to current therapies necessitate a deeper understanding of sarcoma biology and personalized treatment strategies. Our research comprehensively explores the sarcoma TME through advanced spatial analysis and investigates sarcoma's molecular and genetic profiles through transcriptome and genome sequencing. In paper I, we focused on undifferentiated pleomorphic sarcoma (UPS) using multiplex immunofluorescence (mIF) staining for in-depth spatial analysis of B cell populations and lymphocyte aggregates (LAs). LAs in UPS were found to be associated with longer overall survival (OS) and metastasis-free survival (MFS). Moreover, we unveiled distinct maturation profiles among B cell subsets, indicative of different phenotypes that contribute to functional ecosystems in TME. LA-positive tumors displayed a more well-differentiated B cell profile throughout the entire tumor section, not limited in LA regions. We introduced the B-index, an integrated measurement tool combining B cell abundance and maturity, which demonstrated predictive power for both MFS and OS. Using the TissUUmap tool, we identified B cell desert areas characterized by extremely low B cell infiltration. LA-positive tumors displayed smaller and more fragmented B cell desert areas. In paper II, we performed double immunohistochemistry to study CD11c-positive antigen-presenting cells (APCs) and CD8- positive cells in 177 soft tissue sarcoma (STS) patients. We found that CD11c-CD8 interactions in the TME were associated with improved MFS and OS. Transcriptomic analysis in The Cancer Genome Atlas (TCGA) sarcoma cohort supported the prognostic significance of combining CD11c with CD8, irrespective of FOXP3 levels and in the presence of CD274 (PD-L1). In paper III, we conducted transcriptome and targeted DNA sequencing in 91 synovial sarcomas, identifying three distinct Synovial Sarcoma Clusters (SSCs) mirroring histological subtypes. SSC-I was characterized by high cell proliferation and immune evasion with an unfavorable prognosis. SSC-II was dominated by vascularstromal components and correlated with better outcomes. SSC-III displayed biphasic differentiation, genomic complexity, and immune checkpoint-mediated immune suppression, leading to adverse outcomes, even after a good histological response to neoadjuvant treatment. In paper IV, we analyzed Ewing sarcoma (ES) transcriptome signatures in four previously published cohorts and identified 29 prognostic RNA-binding protein (RBP) genes, from which we constructed and validated an RBP-associated prognostic risk model (RPRM). The RPRM demonstrated stable predictive value for prognosis, with NSUN7 emerging as an independent and favorable prognostic marker. In summary, our research integrates spatial analysis of the sarcoma TME to identify unique immune features and prognostic markers. Moreover, we use transcriptomic and genomic analyses to categorize specific sarcoma types for more detailed survival stratification. This work provides a deeper insight into the sarcoma TME and suggests an improved grouping strategy, aiming to shape the development of personalized immunotherapy in the future

Role of \u3ci\u3eMSA\u3c/i\u3e in Immune Evasion, Persistence, and Protease Regulation in the Human Pathogenic Strains of \u3ci\u3eStaphylococcus aureus\u3c/i\u3e

Opportunistic pathogens like Staphylococcus aureus on entering the host can stay colonized at the foci of infection or evade the immune system to disseminate to other sites. In this study we investigated the regulatory influence of the modulator of sarA (msa) on immune evasion and host persistence, employing the hospital-acquired strain S. aureus UAMS-1 and community-acquired strain S. aureus USA300 LAC. In the murine sepsis model, mutation of the msa gene in LAC showed no change in dissemination of infection; however, in UAMS-1 a decrease in microbial load was observed in the lungs. Differential regulation by the msa gene was also observed in the blood survival and neutrophil assays. Several evasion factors were found to be regulated by msa, namely the scn, clfA, spa, aur, and sak genes. Interestingly, the combination of factors and the regulation of these factors differed in the two strains. S. aureus form biofilms on post-surgical wounds, prosthetic devices, and various host tissues that are resilient to immunological clearance and antimicrobial treatments. Biofilm detachment is a stage of biofilm development that aids in metastasis of infection. Proteases are one of the factors that trigger biofilm detachment. In our study, we observed msa to regulate proteases of S. aureus strain LAC when they are not in the form of a biofilm community; however, when they form biofilms the regulatory effect on proteases by the msa gene is absent. Thus, we show the environment-dependent behavior of the msa gene