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Cancer drug sensitivity prediction from routine histology images
Get PDFDrug sensitivity prediction models can aid in personalising cancer therapy, biomarker discovery, and drug design. Such models require survival data from randomised controlled trials which can be time consuming and expensive. In this proof-of-concept study, we demonstrate for the first time that deep learning can link histological patterns in whole slide images (WSIs) of Haematoxylin & Eosin (H&E) stained breast cancer sections with drug sensitivities inferred from cell lines. We employ patient-wise drug sensitivities imputed from gene expression-based mapping of drug effects on cancer cell lines to train a deep learning model that predicts patients’ sensitivity to multiple drugs from WSIs. We show that it is possible to use routine WSIs to predict the drug sensitivity profile of a cancer patient for a number of approved and experimental drugs. We also show that the proposed approach can identify cellular and histological patterns associated with drug sensitivity profiles of cancer patients
Bernoulli factories and duality in Wright-Fisher and Allen-Cahn models of population genetics
No full textMathematical models of genetic evolution often come in pairs, connected by a so-called duality relation. The most seminal example are the Wright-Fisher diffusion and the Kingman coalescent, where the former describes the stochastic evolution of neutral allele frequencies in a large population forwards in time, and the latter describes the genetic ancestry of randomly sampled individuals from the population backwards in time. As well as providing a richer description than either model in isolation, duality often yields equations satisfied by quantities of interest. We employ the so-called Bernoulli factory - a celebrated tool in simulation-based computing - to derive duality relations for broad classes of genetics models. As concrete examples, we present Wright-Fisher diffusions with general drift functions, and Allen-Cahn equations with general, nonlinear forcing terms. The drift and forcing functions can be interpreted as the action of frequency-dependent selection. To our knowledge, this work is the first time a connection has been drawn between Bernoulli factories and duality in models of population genetics
Adoption of core outcome sets in osteoarthritis clinical trials – still a long way to go
No full textA core outcome set is an agreed set of outcome measures that researchers should collect and report in all clinical trials for a specific condition. 1 Determining what should be included in a core outcome set is a robust process. It often involves gaining agreement on what areas (known as domains) are of importance for all stakeholders in a clinical area. This is followed by gaining agreement on what the most robust tools (known as instruments) are to measure each domain
Digital pathology for reporting histopathology samples, including cancer screening samples – definitive evidence from a multisite study
Get PDFAims
To conduct a definitive multicentre comparison of digital pathology (DP) with light microscopy (LM) for reporting histopathology slides including breast and bowel cancer screening samples.
Methods
A total of 2024 cases (608 breast, 607 GI, 609 skin, 200 renal) were studied, including 207 breast and 250 bowel cancer screening samples. Cases were examined by four pathologists (16 study pathologists across the four speciality groups), using both LM and DP, with the order randomly assigned and 6 weeks between viewings. Reports were compared for clinical management concordance (CMC), meaning identical diagnoses plus differences which do not affect patient management. Percentage CMCs were computed using logistic regression models with crossed random-effects terms for case and pathologist. The obtained percentage CMCs were referenced to 98.3% calculated from previous studies.
Results
For all cases LM versus DP comparisons showed the CMC rates were 99.95% [95% confidence interval (CI) = 99.90–99.97] and 98.96 (95% CI = 98.42–99.32) for cancer screening samples. In speciality groups CMC for LM versus DP showed: breast 99.40% (99.06–99.62) overall and 96.27% (94.63–97.43) for cancer screening samples; [gastrointestinal (GI) = 99.96% (99.89–99.99)] overall and 99.93% (99.68–99.98) for bowel cancer screening samples; skin 99.99% (99.92–100.0); renal 99.99% (99.57–100.0). Analysis of clinically significant differences revealed discrepancies in areas where interobserver variability is known to be high, in reads performed with both modalities and without apparent trends to either.
Conclusions
Comparing LM and DP CMC, overall rates exceed the reference 98.3%, providing compelling evidence that pathologists provide equivalent results for both routine and cancer screening samples irrespective of the modality used
The effect of transitory health shocks on schooling outcomes : the case of dengue fever in Brazil
Get PDFIn this paper, we estimate the causal effect of transitory individual-level health shocks on schooling outcomes in Brazil. We focus on dengue fever, which, despite putting half of the world’s population at risk, has received relatively little attention, possibly due to its low mortality. We link individual register data on dengue infections with detailed individual records from the Brazilian school census and use a fixed effects estimation strategy to estimate the effect of dengue infections on grade retention and dropout. We find that dengue infections during the school year have a substantial negative effect on measures of student success, with an increase in grade retention of 3.5 percent and an increase in dropout of 4.6 percent. Using information on monthly attendance from the monitoring system of conditionalities of the Brazilian cash transfer Bolsa Famılia, we provide evidence that infections reduce school attendance
A compatibility study of protective coatings for temperature sensor integration into sodium-ion battery cells
Get PDFInstrumented battery cells (i.e. those containing sensors) and smart cells (with integrated control and communication circuitry) are essential for the development of the next-generation battery technologies, such as Sodium-ion Batteries (SIBs). The mapping and monitoring of parameters, for example the quantification of temperature gradients, helps improve cell designs and optimise management systems. Integrated sensors must be protected against the harsh cell electrolytic environment. State-of-the-art coatings include the use of Parylene polymer (our reference case). We applied three new types of coatings (acrylic, polyurethane and epoxy based) to thermistor arrays mounted on flexible printed circuit board (PCBs). We systematically analyse the coatings: (i) PCB submersion within electrolyte vials (8 weeks); (ii) analysis of sample inserted into coin cell; (iii) analysis of sensor and cell performance data for 1Ah pouch SIBs. Sodium-based liquid electrolyte was selected, consisting of a 1 M solution of sodium hexafluorophosphate (NaPF6) dissolved in a mixture of ethylene carbonate and diethylene carbonate in a ratio of 3:7 (v/v%). Our novel experiments revealed that the epoxy based coated sensors offered reliable temperature measurements; superior performance observed compared to the Parylene sensors (erroneous results from one sample were reported, under 5 d submersed in electrolyte). Nuclear magnetic resonance (NMR) spectroscopy revealed in the case of most coatings tested, formation of additional species occurred during exposure to the different coatings applied to the PCBs. The epoxy-based coating demonstrated resilience to the electrolytic-environment, as well as minimal effect on cell performance (capacity degradation compared to unmodified-reference, within 2% for the coin cell, and within 3.4% for pouch cell). The unique methodology detailed in this work allows sensor coatings to be trialled in a realistic and repeatable cell environment. This study demonstrated for the first time that this epoxy-based coating enables scalable, affordable, and resilient sensors to be integrated towards next-generation Smart SIBs
Developing performance portable plasma edge simulations : a survey
No full textHeterogeneous architectures are increasingly common in modern High-Performance Computing (HPC) systems. Achieving high-performance on such heterogeneous systems requires new approaches to application development that are able to achieve the three Ps: Performance, Portability, and Productivity.
In this paper, we provide an overview of the state-of-the-art for developing high-performance, portable and productive multi-physics applications with particular focus on the simulation of a plasma fusion reactor. Simulating such a complex system relies on both fluid- and particle-based simulations, and coupling interfaces between these two domains. We also review the current state-of-the-art in reasoning about the performance, portability and productivity of HPC applications
Quantum critical behavior of the hyperkagome magnet Mn3CoSi
Get PDFβ-Mn-type family alloys Mn3TX (T = Co, Rh, and Ir; X = Si and Ge) have a three-dimensional antiferromagnetic (AF) corner-shared triangular network, i.e., the hyperkagome lattice. The antiferromagnet Mn3RhSi shows magnetic short-range order over a wide temperature range of approximately 500 K above the Néel temperature TN of 190 K. In this family of compounds, as the lattice parameter decreases, the long-range magnetic ordering temperature decreases. Mn3CoSi has the smallest lattice parameter and the lowest TN in the family. The quantum critical point (QCP) from AF to the quantum paramagnetic state is expected near a cubic lattice parameter of 6.15 Å. Although the Néel temperature of Mn3CoSi is only 140 K, the emergence of the quantum critical behavior in Mn3CoSi is discussed. We study how the magnetic short-range order appears in Mn3CoSi by using neutron scattering, μSR, and bulk characterization such as specific heat capacity. According to the results, the neutron scattering intensity of the magnetic short-range order in Mn3CoSi does not change much at low temperatures from that of Mn3RhSi, although the μSR short-range order temperature of Mn3CoSi is largely suppressed to 240 K from that of Mn3RhSi. Correspondingly, the volume fraction of the magnetic short-range order regions, as shown by the initial asymmetry drop ratio of μSR above TN, also becomes small. Instead, the electronic-specific heat coefficient γ of Mn3CoSi is the largest in this Mn3T Si system, possibly due to the low-energy spin fluctuation near the quantum critical point
La biopolítica racial del humanitarismo en África : examinando la construcción de la resiliencia europea en el Sahel y en la cuenca del lago Chad
No full textThis paper examines humanitarianism in the “Global South” through engaging with resilience projects in the Sahel and Lake Chad Basin (LCB) in Africa. It addresses how recent humanitarianism has moved away from top-down interventions which sought to either intervene to save those that have been rendered as “bare life” (Agamben, 1998: 4) by their own governments or improve the state’s —especially “fragile” and “failing” ones— capacity to govern, towards society-based projects which seek to produce resilient subjects. While previous accounts of security and development emphasized why fragile states and authoritarian regimes could constitute a threat to their people and the international system, society, or community, where justifications for interventions were based on their flouting of specific international norms and conventions. In contrast, recent humanitarianism has become less targeted at regime change as was evident with the reluctance that followed the unproductive cases in Afghanistan, Iraq, and Libya where assumptions that regime change, or democracy promotion could achieve or promote the ends of liberal governance. Moving away from these statist focus, post-intervention has moved towards strengthening the capacities of communities to withstand shocks, adapt and self-transform their own the broader social milieu
The cell edit : looking at and beyond non-structural proteins to understand membrane rearrangement in coronaviruses
Get PDFSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-stranded RNA virus that sits at the centre of the recent global pandemic. As a member of the coronaviridae family of viruses, it shares features such as a very large genome (>30 kb) that is replicated in a purpose-built replication organelle. Biogenesis of the replication organelle requires significant and concerted rearrangement of the endoplasmic reticulum membrane, a job that is carried out by a group of integral membrane non-structural proteins (NSP3, 4 and 6) expressed by the virus along with a host of viral replication enzymes and other factors that support transcription and replication. The primary sites for RNA replication within the replication organelle are double membrane vesicles (DMVs). The small size of DMVs requires generation of high membrane curvature, as well as stabilization of a double-membrane arrangement, but the mechanisms that underlie DMV formation remain elusive. In this review, we discuss recent breakthroughs in our understanding of the molecular basis for membrane rearrangements by coronaviruses. We incorporate established models of NSP3-4 protein-protein interactions to drive double membrane formation, and recent data highlighting the roles of lipid composition and host factor proteins (e.g. reticulons) that influence membrane curvature, to propose a revised model for DMV formation in SARS-CoV-2. [Abstract copyright: Copyright © 2023. Published by Elsevier Inc.