TAMs in Brain Metastasis: Molecular Signatures in Mouse and Man

Macrophages not only represent an integral part of innate immunity but also critically contribute to tissue and organ homeostasis. Moreover, disease progression is accompanied by macrophage accumulation in many cancer types and is often associated with poor prognosis and therapy resistance. Given their critical role in modulating tumor immunity in primary and metastatic brain cancers, macrophages are emerging as promising therapeutic targets. Different types of macrophages infiltrate brain cancers, including (i) CNS resident macrophages that comprise microglia (TAM-MG) as well as border-associated macrophages and (ii) monocyte-derived macrophages (TAM-MDM) that are recruited from the periphery. Controversy remained about their disease-associated functions since classical approaches did not reliably distinguish between macrophage subpopulations. Recent conceptual and technological advances, such as large-scale omic approaches, provided new insight into molecular profiles of TAMs based on their cellular origin. In this review, we summarize insight from recent studies highlighting similarities and differences of TAM-MG and TAM-MDM at the molecular level. We will focus on data obtained from RNA sequencing and mass cytometry approaches. Together, this knowledge significantly contributes to our understanding of transcriptional and translational programs that define disease-associated TAM functions. Cross-species meta-analyses will further help to evaluate the translational significance of preclinical findings as part of the effort to identify candidates for macrophage-targeted therapy against brain metastasis.

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Large scale meta-analysis of preclinical toxicity data for target characterisation and hypotheses generation

PLoS ONE ◽

10.1371/journal.pone.0252533 ◽

2021 ◽

Vol 16 (6) ◽

pp. e0252533

Author(s):

Jordi Munoz-Muriedas

Keyword(s):

Animal Studies ◽

Large Scale ◽

Meta Analysis ◽

Preclinical Studies ◽

Technological Advances ◽

Consistent Manner ◽

Critical Components ◽

Meta Analyses ◽

And Control

Recent technological advances in the field of big data have increased our capabilities to query large databases and combine information from different domains and disciplines. In the area of preclinical studies, initiatives like SEND (Standard for Exchange of Nonclinical Data) will also contribute to collect and present nonclinical data in a consistent manner and increase analytical possibilities. With facilitated access to preclinical data and improvements in analytical algorithms there will surely be an expectation for organisations to ensure all the historical data available to them is leveraged to build new hypotheses. These kinds of analyses may soon become as important as the animal studies themselves, in addition to being critical components to achieve objectives aligned with 3Rs. This article proposes the application of meta-analyses at large scale in corporate databases as a tool to exploit data from both preclinical studies and in vitro pharmacological activity assays to identify associations between targets and tissues that can be used as seeds for the development of causal hypotheses to characterise of targets. A total of 833 in-house preclinical toxicity studies relating to 416 compounds reported to be active (pXC50 ≥ 5.5) against a panel of 96 selected targets of interest for potential off-target non desired effects were meta-analysed, aggregating the data in tissue–target pairs. The primary outcome was the odds ratio (OR) of the number of animals with observed events (any morphology, any severity) in treated and control groups in the tissue analysed. This led to a total of 2139 meta-analyses producing a total of 364 statistically significant associations (random effects model), 121 after adjusting by multiple comparison bias. The results show the utility of the proposed approach to leverage historical corporate data and may offer a vehicle for researchers to share, aggregate and analyse their preclinical toxicological data in precompetitive environments.

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Xie, Liu, & Jaeger (2020). Cross-talker generalization during foreign-accented speech perception

10.31234/osf.io/e2z5m ◽

2021 ◽

Author(s):

Xin Xie ◽

Linda Liu ◽

T. Florian Jaeger

Keyword(s):

Speech Perception ◽

Large Scale ◽

Critical Role ◽

Talker Variability ◽

Total N ◽

Accented Speech ◽

Bayesian Data Analysis ◽

Meta Analyses ◽

Open Question

Speech perception depends on the ability to generalize previously experienced input effectively across talkers. How such cross-talker generalization is achieved has remained an open question. In a seminal study, Bradlow & Bent (2008, henceforth BB08) found that exposure to just five minutes of accented speech can elicit improved recognition that generalizes to an unfamiliar talker of the same accent (N=70 participants). Cross-talker generalization was, however, only observed after exposure to multiple talkers of the accent, not after exposure to a single accented talker. This contrast between single- and multi-talker exposure has been highly influential beyond research on speech perception, suggesting a critical role of exposure variability in learning and generalization. We assess the replicability of BB08’s findings in two large-scale perception experiments (total N=640) including 20 unique combinations of exposure and test talkers. Like BB08, we find robust evidence for cross-talker generalization after multi-talker exposure. Unlike BB08, we also find evidence for generalization after single-talker exposure. The degree of cross-talker generalization depends on the specific combination of exposure and test talker. This and other recent findings suggest that exposure to cross-talker variability is not necessary for cross-talker generalization. Variability during exposure might affect generalization only indirectly, mediated through the informativeness of exposure about subsequent speech during test: similarity-based inferences can explain both the original BB08 and the present findings. We present Bayesian data analysis, including Bayesian meta-analyses and replication tests for generalized linear mixed models. All data, stimuli, and reproducible literate (R markdown) code are shared via OSF.

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Family Support in Early Hearing Detection and Intervention (EHDI) Systems

Perspectives on Hearing and Hearing Disorders in Childhood ◽

10.1044/hhdc22.1.11 ◽

2012 ◽

Vol 22 (1) ◽

pp. 11-21

Author(s):

Patti Martin ◽

Nannette Nicholson ◽

Charia Hall

Keyword(s):

Family Support ◽

Hard Of Hearing ◽

Critical Role ◽

Annual Conference ◽

Federal Law ◽

Think Tank ◽

Learning Collaborative ◽

Technological Advances ◽

Improved Outcomes ◽

Program Components

Family support has evolved from a buzzword of the 1990s to a concept founded in theory, mandated by federal law, valued across disciplines, and espoused by both parents and professionals. This emphasis on family-centered practices for families of young children with disabilities, coupled with federal policy initiatives and technological advances, served as the impetus for the development of Early Hearing Detection and Intervention (EHDI) programs (Nicholson & Martin, in press). White, Forsman, Eichwald, and Muñoz (2010) provide an excellent review of the evolution of EHDI systems, which include family support as one of their 9 components. The National Center for Hearing Assessment and Management (NCHAM), the Maternal and Child Health Bureau, and the Center for Disease Control Centers cosponsored the first National EHDI Conference. This conference brought stakeholders including parents, practitioners, and researchers from diverse backgrounds together to form a learning collaborative (Forsman, 2002). Attendees represented a variety of state, national, and/or federal agencies and organizations. This forum focused effort on the development of EHDI programs infused with translating research into practices and policy. When NCHAM, recognizing the critical role of family support in the improvement of outcomes for both children and families, created a think tank to investigate the concept of a conference centered on support for families of children who are deaf or hard of hearing in 2005, the “Investing in Family Support” (IFSC) conference was born. This conference was specifically designed to facilitate and enhance EHDI efforts within the family support arena. From this venue, a model of family support was conceptualized and has served as the cornerstone of the IFSC annual conference since 2006. Designed to be a functional framework, the IFSC model delineates where and how families find support. In this article, we will promote and encourage continued efforts towards defining operational measures and program components to ultimately quantify success as it relates to improved outcomes for these children and their families. The authors view this opportunity to revisit the theoretical underpinnings of family support, the emerging research in this area, and the basics of the IFSC Model of Family Support as a call to action. We challenge professionals who work with children identified as deaf or hard of hearing to move family support from conceptualization to practices that are grounded in evidence and ever mindful of the unique and dynamic nature of individual families.

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Nursing professionals’ attitudes toward use of physical restraints in Styrian nursing homes Austria

Pflege ◽

10.1024/1012-5302/a000649 ◽

2019 ◽

Vol 32 (1) ◽

pp. 57-63

Author(s):

Hannes Mayerl ◽

Tanja Trummer ◽

Erwin Stolz ◽

Éva Rásky ◽

Wolfgang Freidl

Keyword(s):

Nursing Homes ◽

Large Scale ◽

Critical Role ◽

Physical Restraint ◽

Care Practice ◽

Physical Restraints ◽

Convenience Sample ◽

Restraint Use ◽

Positive Attitudes ◽

Nursing Professionals

Abstract. Background: Given that nursing staff play a critical role in the decision regarding use of physical restraints, research has examined nursing professionals’ attitudes toward this practice. Aim: Since nursing professionals’ views on physical restraint use have not yet been examined in Austria to date, we aimed to explore nursing professionals’ attitudes concerning use of physical restraints in nursing homes of Styria (Austria). Method: Data were collected from a convenience sample of nursing professionals (N = 355) within 19 Styrian nursing homes, based on a cross-sectional study design. Attitudes toward the practice of restraint use were assessed by means of the Maastricht Attitude Questionnaire in the German version. Results: The overall results showed rather positive attitudes toward the use of physical restraints, yet the findings regarding the sub-dimensions of the questionnaire were mixed. Although nursing professionals tended to deny “good reasons” for using physical restraints, they evaluated the consequences of physical restraint use rather positive and considered restraint use as an appropriate health care practice. Nursing professionals’ views regarding the consequences of using specific physical restraints further showed that belts were considered as the most restricting and discomforting devices. Conclusions: Overall, Austrian nursing professionals seemed to hold more positive attitudes toward the use of physical restraints than counterparts in other Western European countries. Future nationwide large-scale surveys will be needed to confirm our findings.

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Identification of and Correction for Publication Bias: Comment

10.31222/osf.io/dh87m ◽

2019 ◽

Author(s):

Amanda Kvarven ◽

Eirik Strømland ◽

Magnus Johannesson

Keyword(s):

Publication Bias ◽

False Positive ◽

Large Scale ◽

Meta Analysis ◽

False Positive Rate ◽

Effect Sizes ◽

Replication Studies ◽

Moderate Reduction ◽

Positive Rate ◽

Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

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STEM-20. A CANCER STEM CELL-SELECTIVE APOPTOSIS-INDUCING SMALL MOLECULE FOR THE TREATMENT OF GBM

Neuro-Oncology ◽

10.1093/neuonc/noaa215.837 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii200-ii200

Author(s):

Stephen Skirboll ◽

Natasha Lucki ◽

Genaro Villa ◽

Naja Vergani ◽

Michael Bollong ◽

...

Keyword(s):

Stem Cells ◽

Cancer Stem Cells ◽

Small Molecules ◽

Small Molecule ◽

Large Scale ◽

Critical Role ◽

Tumor Formation ◽

Cell Type ◽

Caspase 1 ◽

Activation Assay

Abstract INTRODUCTION Glioblastoma multiforme (GBM) is the most aggressive form of primary brain cancer. A subpopulation of multipotent cells termed GBM cancer stem cells (CSCs) play a critical role in tumor initiation and maintenance, drug resistance, and recurrence following surgery. New therapeutic strategies for the treatment of GBM have recently focused on targeting CSCs. Here we have used an unbiased large-scale screening approach to identify drug-like small molecules that induce apoptosis in GBM CSCs in a cell type-selective manner. METHODS A luciferase-based survival assay of patient-derived GBM CSC lines was established to perform a large-scale screen of ∼one million drug-like small molecules with the goal of identifying novel compounds that are selectively toxic to chemoresistant GBM CSCs. Compounds found to kill GBM CSC lines as compared to control cell types were further characterized. A caspase activation assay was used to evaluate the mechanism of induced cell death. A xenograft animal model using patient-derived GBM CSCs was employed to test the leading candidate for suppression of in vivo tumor formation. RESULTS We identified a small molecule, termed RIPGBM, from the cell-based chemical screen that induces apoptosis in primary patient-derived GBM CSC cultures. The cell type-dependent selectivity of RIPGBM appears to arise at least in part from redox-dependent formation of a proapoptotic derivative, termed cRIPGBM, in GBM CSCs. cRIPGBM induces caspase 1-dependent apoptosis by binding to receptor-interacting protein kinase 2 (RIPK2) and acting as a molecular switch, which reduces the formation of a prosurvival RIPK2/TAK1 complex and increases the formation of a proapoptotic RIPK2/caspase 1 complex. In an intracranial GBM xenograft mouse model, RIPGBM was found to significantly suppress tumor formation. CONCLUSIONS Our chemical genetics-based approach has identified a small molecule drug candidate and a potential drug target that selectively targets cancer stem cells and provides an approach for the treatment of GBMs.

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Dual Roles of the Activin Signaling Pathway in Pancreatic Cancer

Biomedicines ◽

10.3390/biomedicines9070821 ◽

2021 ◽

Vol 9 (7) ◽

pp. 821

Author(s):

Wanglong Qiu ◽

Chia-Yu Kuo ◽

Yu Tian ◽

Gloria H. Su

Keyword(s):

Pancreatic Cancer ◽

Signaling Pathway ◽

Critical Role ◽

Genetic Mutations ◽

Cancer Genetic ◽

Dual Roles ◽

Activin Signaling ◽

Physiological Processes ◽

Cancer Types ◽

Related Proteins

Activin, a member of the TGF-β superfamily, is involved in many physiological processes, such as embryonic development and follicle development, as well as in multiple human diseases including cancer. Genetic mutations in the activin signaling pathway have been reported in many cancer types, indicating that activin signaling plays a critical role in tumorigenesis. Recent evidence reveals that activin signaling may function as a tumor-suppressor in tumor initiation, and a promoter in the later progression and metastasis of tumors. This article reviews many aspects of activin, including the signaling cascade of activin, activin-related proteins, and its role in tumorigenesis, particularly in pancreatic cancer development. The mechanisms regulating its dual roles in tumorigenesis remain to be elucidated. Further understanding of the activin signaling pathway may identify potential therapeutic targets for human cancers and other diseases.

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Complex Network Modelling of Origin–Destination Commuting Flows for the COVID-19 Epidemic Spread Analysis in Italian Lombardy Region

Applied Sciences ◽

10.3390/app11104381 ◽

2021 ◽

Vol 11 (10) ◽

pp. 4381

Author(s):

Angela Lombardi ◽

Nicola Amoroso ◽

Alfonso Monaco ◽

Sabina Tangaro ◽

Roberto Bellotti

Keyword(s):

Urban Areas ◽

Large Scale ◽

Critical Role ◽

Potential Contribution ◽

Epidemic Spread ◽

Network Modelling ◽

Lombardy Region ◽

Commuting Flows ◽

Dynamic Growth ◽

Spread Analysis

Currently the whole world is affected by the COVID-19 disease. Italy was the first country to be seriously affected in Europe, where the first COVID-19 outbreak was localized in the Lombardy region. The further spreading of the cases led to the lockdown of the most affected regions in northern Italy and then the entire country. In this work we investigated an epidemic spread scenario in the Lombardy region by using the origin–destination matrix with information about the commuting flows among 1450 urban areas within the region. We performed a large-scale simulation-based modeling of the epidemic spread over the networks related to three main motivations, i.e., work, study and occasional transfers to quantify the potential contribution of each category of travellers to the spread of the epidemic process. Our findings outline that the three networks are characterised by different weight dynamic growth rates and that the network “work” has a critical role in the diffusion phenomenon showing the greatest contribution to the epidemic spread.

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EARRINGS: an efficient and accurate adapter trimmer entails no a priori adapter sequences

Bioinformatics ◽

10.1093/bioinformatics/btab025 ◽

2021 ◽

Author(s):

Ting-Hsuan Wang ◽

Cheng-Ching Huang ◽

Jui-Hung Hung

Keyword(s):

Open Source Software ◽

Large Scale ◽

A Priori ◽

Supplementary Information ◽

Supplementary Data ◽

Comparable Accuracy ◽

Meta Analyses ◽

Next Generation Sequencing Ngs ◽

Adapter Trimming ◽

Generation Sequencing

Abstract Motivation Cross-sample comparisons or large-scale meta-analyses based on the next generation sequencing (NGS) involve replicable and universal data preprocessing, including removing adapter fragments in contaminated reads (i.e. adapter trimming). While modern adapter trimmers require users to provide candidate adapter sequences for each sample, which are sometimes unavailable or falsely documented in the repositories (such as GEO or SRA), large-scale meta-analyses are therefore jeopardized by suboptimal adapter trimming. Results Here we introduce a set of fast and accurate adapter detection and trimming algorithms that entail no a priori adapter sequences. These algorithms were implemented in modern C++ with SIMD and multithreading to accelerate its speed. Our experiments and benchmarks show that the implementation (i.e. EARRINGS), without being given any hint of adapter sequences, can reach comparable accuracy and higher throughput than that of existing adapter trimmers. EARRINGS is particularly useful in meta-analyses of a large batch of datasets and can be incorporated in any sequence analysis pipelines in all scales. Availability and implementation EARRINGS is open-source software and is available at https://github.com/jhhung/EARRINGS. Supplementary information Supplementary data are available at Bioinformatics online.

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A Novel Real-Time Thermal Analysis and Layer Time Control Framework for Large Scale Additive Manufacturing

Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability ◽

10.1115/msec2020-8321 ◽

2020 ◽

Author(s):

Sepehr Fathizadan ◽

Feng Ju ◽

Kyle Rowe ◽

Alex Fiechter ◽

Nils Hofmann

Keyword(s):

Additive Manufacturing ◽

Surface Temperature ◽

Real Time ◽

Large Scale ◽

Production Efficiency ◽

Control Method ◽

Data Extraction ◽

Critical Role ◽

Imaging Data ◽

Time Data

Abstract Production efficiency and product quality need to be addressed simultaneously to ensure the reliability of large scale additive manufacturing. Specifically, print surface temperature plays a critical role in determining the quality characteristics of the product. Moreover, heat transfer via conduction as a result of spatial correlation between locations on the surface of large and complex geometries necessitates the employment of more robust methodologies to extract and monitor the data. In this paper, we propose a framework for real-time data extraction from thermal images as well as a novel method for controlling layer time during the printing process. A FLIR™ thermal camera captures and stores the stream of images from the print surface temperature while the Thermwood Large Scale Additive Manufacturing (LSAM™) machine is printing components. A set of digital image processing tasks were performed to extract the thermal data. Separate regression models based on real-time thermal imaging data are built on each location on the surface to predict the associated temperatures. Subsequently, a control method is proposed to find the best time for printing the next layer given the predictions. Finally, several scenarios based on the cooling dynamics of surface structure were defined and analyzed, and the results were compared to the current fixed layer time policy. It was concluded that the proposed method can significantly increase the efficiency by reducing the overall printing time while preserving the quality.

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