Stratifying triple-negative breast cancer: which definition(s) to use?

Triple-negative breast cancers (TNBC) have increased rates of pathologic complete response following neoadjuvant chemotherapy, yet have poorer prognosis compared with non-TNBC. Known as the triple-negative paradox, this highlights the need to dissect the biologic and clinical heterogeneity within TNBC. In the present issue, Keam and colleagues suggest two subgroups of TNBC exist based on the proliferation-related marker Ki-67, each with differential response and prognosis following neoadjuvant chemotherapy. To place results into context, we review several definitions available under the TNBC umbrella that may stratify TNBC into clinically relevant subgroups

Differential expression analysis for sequence count data

*Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.

*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. 

*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from "http://www-huber.embl.de/users/anders/DESeq":http://www-huber.embl.de/users/anders/DESeq

Tissue Microenvironments Define and Get Reinforced by Macrophage Phenotypes in Homeostasis or during Inflammation, Repair and Fibrosis

Current macrophage phenotype classifications are based on distinct in vitro culture conditions that do not adequately mirror complex tissue environments. In vivo monocyte progenitors populate all tissues for immune surveillance which supports the maintenance of homeostasis as well as regaining homeostasis after injury. Here we propose to classify macrophage phenotypes according to prototypical tissue environments, e.g. as they occur during homeostasis as well as during the different phases of (dermal) wound healing. In tissue necrosis and/or infection, damage- and/or pathogen-associated molecular patterns induce proinflammatory macrophages by Toll-like receptors or inflammasomes. Such classically activated macrophages contribute to further tissue inflammation and damage. Apoptotic cells and antiinflammatory cytokines dominate in postinflammatory tissues which induce macrophages to produce more antiinflammatory mediators. Similarly, tumor-associated macrophages also confer immunosuppression in tumor stroma. Insufficient parenchymal healing despite abundant growth factors pushes macrophages to gain a profibrotic phenotype and promote fibrocyte recruitment which both enforce tissue scarring. Ischemic scars are largely devoid of cytokines and growth factors so that fibrolytic macrophages that predominantly secrete proteases digest the excess extracellular matrix. Together, macrophages stabilize their surrounding tissue microenvironments by adapting different phenotypes as feed-forward mechanisms to maintain tissue homeostasis or regain it following injury. Furthermore, macrophage heterogeneity in healthy or injured tissues mirrors spatial and temporal differences in microenvironments during the various stages of tissue injury and repair. Copyright (C) 2012 S. Karger AG, Base

Intensifying the manufacture of hiPSC therapy products through metabolic and process understanding

In vitro differentiation of human induced pluripotent stem cells into specific lineages such as cardiomyocytes (hPSC-CM) and hepatocytes (hPCS-Hep) is a crucial process to enable their application in cell therapy and drug discovery. Nevertheless, despite the remarkable efforts over the last decade towards the implementation of protocols for hPSC expansion and differentiation, there are some technological challenges remaining include the low scalability and differentiation yields. Additionally, generated cells are still immature, closely reminiscent of fetal/embryonic cells in what regards phenotype and function. In this study, we aim to overcome this hurdle by devising bioinspired and integrated strategies to improve the generation and functionality of these hiPSC-derivatives. We also applied robust multi-parametric techniques including proteomics, transcriptomics, metabolomics and fluxomics as complementary analytical tools to support bioprocess optimization and product characterization. We cultured hiPSC as 3D aggregates in stirred-tank bioreactors (STB) operated in perfusion and used a capacitance probe for in situ monitoring of cell growth/differentiation. After cell expansion, the hepatic differentiation step was integrated by addition of key soluble factors and controlling the dissolved oxygen concentration at various stages of the process to generate populations enriched for definitive endoderm, hepatocyte progenitors and mature hepatocytes. The analyses of hepatic markers expression throughout the stages of the differentiation confirmed that hepatocyte differentiation was improved in 3D spheroids when compared to 2D culture. Noteworthy, these hiPSC-HLC exhibited functional characteristics typical of hepatocytes (albumin production, glycogen storage and CYP450 activity). We also demonstrate the potential of dielectric spectroscopy to monitor cell expansion and hepatic differentiation in STB. For CM differentiation, we relied on the aggregation of hPSC-derived cardiac progenitors to establish a scalable differentiation protocol capable of generating highly pure CM aggregate cultures. We assessed if alteration of culture medium composition to mimic in vivo substrate usage during cardiac development improved further hPSC-CM maturation in vitro. Our results showed that shifting hPSC-CMs from glucose-containing to galactose- and fatty acid-containing medium promotes their fast maturation into adult-like CMs with higher oxidative metabolism, transcriptional signatures closer to those of adult ventricular tissue, higher myofibril density and alignment, improved calcium handling, enhanced contractility, and more physiological action potential kinetics. “-Omics” analyses showed that addition of galactose to culture medium and culturing the cells under perfusion improves total oxidative capacity of the cells and ameliorates fatty acid oxidation. This study demonstrated that metabolic shifts during differentiation/maturation of hPSC-CM are a cause, rather than a consequence, of the phenotypic and functional alterations observed. The metabolic-based strategy established herein holds technical and economic advantages over the existing protocols due to its scalability, simplicity and ease of application. Funding: This work was supported by FCT-funded projects NETDIAMOND (SAICTPAC/0047/2015), MetaCardio (Ref.032566) and FCT/ERA-Net (ERAdicatPH; Ref. E-Rare3/0002/2015). iNOVA4Health Research Unit (LISBOA-01-0145-FEDER-007344) is also acknowledged

Controlling passively-quenched single photon detectors by bright light

Single photon detectors based on passively-quenched avalanche photodiodes can be temporarily blinded by relatively bright light, of intensity less than a nanowatt. I describe a bright-light regime suitable for attacking a quantum key distribution system containing such detectors. In this regime, all single photon detectors in the receiver Bob are uniformly blinded by continuous illumination coming from the eavesdropper Eve. When Eve needs a certain detector in Bob to produce a click, she modifies polarization (or other parameter used to encode quantum states) of the light she sends to Bob such that the target detector stops receiving light while the other detector(s) continue to be illuminated. The target detector regains single photon sensitivity and, when Eve modifies the polarization again, produces a single click. Thus, Eve has full control of Bob and can do a successful intercept-resend attack. To check the feasibility of the attack, 3 different models of passively-quenched detectors have been tested. In the experiment, I have simulated the intensity diagrams the detectors would receive in a real quantum key distribution system under attack. Control parameters and side effects are considered. It appears that the attack could be practically possible.Comment: Experimental results from a third detector model added. Minor corrections and edits made. 11 pages, 10 figure

Disease activity level, remission and response in established rheumatoid arthritis: Performance of various criteria sets in an observational cohort, treated with anti-TNF agents

<p>Abstract</p> <p>Background</p> <p>Most composite indices of disease activity and response criteria in RA have been validated and compared in clinical trials rather than routine care. We therefore wanted to compare the performance of the DAS28, SDAI and CDAI activity indices, their activity states, their response criteria, and also compare with the ACR response criteria in an observational clinical setting.</p> <p>Methods</p> <p>Agreement between the criteria sets was investigated using κ statistics in a non-randomized cohort of 1789 RA patients from southern Sweden, starting their first course of anti-TNF-treatment. Mean disease duration was 12 years. Completer analysis was used.</p> <p>Results</p> <p>Agreement between high, moderate and low activity states was moderate or substantial, with κ = 0.5 or better for all criteria. Agreement between SDAI and CDAI disease states was > 90% in these categories with κ > 0.8. DAS28 original and modified cut point remission had good agreement (κ = 0.91). Agreement between responses was substantial at the overall/ACR20 level (about 95%, κ = 0.7 or better) for all criteria. By contrast, agreement was poor between moderate and high level responses.</p> <p>Conclusion</p> <p>Disease activity states according to the various indices perform similarly and show substantial agreement at all levels except remission. Agreement between SDAI and CDAI states is excellent. Response criteria, applied at the individual patient level, are hard to interpret and show poor agreement, except at the lowest level of response. Thus, they should not be applied uncritically in clinical practice.</p

Data quality problems in discrete event simulation of manufacturing operations

High-quality input data are a necessity for successful discrete event simulation (DES) applications, and there are available methodologies for data collection in DES projects. However, in contrast to standalone projects, using DES as a daily manufacturing engineering tool requires high-quality production data to be constantly available. In fact, there has been a major shift in the application of DES in manufacturing from production system design to daily operations, accompanied by a stream of research on automation of input data management and interoperability between data sources and simulation models. Unfortunately, this research stream rests on the assumption that the collected data are already of high quality,and there is a lack of in-depth understanding of simulation data quality problems from a practitioners’ perspective.Therefore, a multiple-case study within the automotive industry was used to provide empirical descriptions of simulation data quality problems, data production processes, and relations between these processes and simulation data quality problems. These empirical descriptions are necessary to extend the present knowledge on data quality in DES in a practical real-world manufacturing context, which is a prerequisite for developing practical solutions for solving data quality problems such as limited accessibility, lack of data on minor stoppages, and data sources not being designed for simulation. Further, the empirical and theoretical knowledge gained throughout the study was used to propose a set of practical guidelines that can support manufacturing companies in improving data quality in DES

Disentangling astroglial physiology with a realistic cell model in silico

Electrically non-excitable astroglia take up neurotransmitters, buffer extracellular K+ and generate Ca2+ signals that release molecular regulators of neural circuitry. The underlying machinery remains enigmatic, mainly because the sponge-like astrocyte morphology has been difficult to access experimentally or explore theoretically. Here, we systematically incorporate multi-scale, tri-dimensional astroglial architecture into a realistic multi-compartmental cell model, which we constrain by empirical tests and integrate into the NEURON computational biophysical environment. This approach is implemented as a flexible astrocyte-model builder ASTRO. As a proof-of-concept, we explore an in silico astrocyte to evaluate basic cell physiology features inaccessible experimentally. Our simulations suggest that currents generated by glutamate transporters or K+ channels have negligible distant effects on membrane voltage and that individual astrocytes can successfully handle extracellular K+ hotspots. We show how intracellular Ca2+ buffers affect Ca2+ waves and why the classical Ca2+ sparks-and-puffs mechanism is theoretically compatible with common readouts of astroglial Ca2+ imaging