A Commitment to Open Source in Neuroscience

Modern neuroscience increasingly relies on custom-developed software, but much of this is not being made available to the wider community. A group of researchers are pledging to make code they produce for data analysis and modeling open source, and are actively encouraging their colleagues to follow suit

Re-Os dating of pyrite confirms an early diagenetic onset and extended duration of mineralization in the Irish Zn-Pb ore field

0000-0002-7706-6003The Irish Midlands region contains one of the world’s largest hydrothermal Zn-Pb ore districts, but uncertainty exists in the timing of mineralization relative to host rock ages. Consequently, genetic models for ore formation are poorly constrained and remain controversial. Here we use Re-Os geochronology to show that ore-stage pyrite from the Lisheen deposit formed at 346.6 ± 3.0 Ma, shortly after host rock deposition. Pyrite from the Silvermines deposit returns an age of 334.0 ± 6.1 Ma, indicating that at least some mineralization occurred during later burial. These age determinations show that the much younger paleomagnetic ages reported for the Irish Zn-Pb deposits reflect remagnetization during the Variscan orogeny, a process that we suggest affects paleomagnetic dating more widely. The Re-Os ages overlap with the ages of lower Carboniferous volcanic rocks in the Midlands, which are the product of magmatism that has been invoked as the driving force for hydrothermal activity. The relatively low initial Os ratios for both Lisheen (0.253 ± 0.045) and Silvermines (0.453 ± 0.006) are compatible with derivation of Os from these magmas, or from the Caledonian basement that underlies the ore deposits.This journal is published under the terms of Green Open Access. Authors may post a copy of the accepted (i.e., post-peer review) version of their paper (https://doi.org/10.1130/G36296.1) in a repository of their choice or to their personal website after the relevant embargo period has passed. The embargo period will be 12 months from formal online publication

LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2.

Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties

NetPyNE, a tool for data-driven multiscale modeling of brain circuits.

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis - connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena

libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.

NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment

Parenchymal involvement on CT pulmonary angiography in SARS-CoV-2 Alpha variant infection and correlation of COVID-19 CT severity score with clinical disease severity and short-term prognosis in a UK cohort

AIM: To determine if there is a difference in radiological, biochemical, or clinical severity between patients infected with Alpha-variant SARS-CoV-2 compared with those infected with pre-existing strains, and to determine if the computed tomography (CT) severity score (CTSS) for COVID-19 pneumonitis correlates with clinical severity and can prognosticate outcomes. MATERIALS AND METHODS: Blinded CTSS scoring was applied to 137 hospital patients who had undergone both CT pulmonary angiography (CTPA) and whole-genome sequencing of SARS-CoV-2 within 14 days of CTPA between 1/12/20–5/1/21. RESULTS: There was no evidence of a difference in imaging severity on CTPA, viral load, clinical parameters of severity, or outcomes between Alpha and preceding variants. CTSS on CTPA strongly correlates with clinical and biochemical severity at the time of CTPA, and with patient outcomes. Classifying CTSS into a binary value of “high” and “low”, with a cut-off score of 14, patients with a high score have a significantly increased risk of deterioration, as defined by subsequent admission to critical care or death (multivariate hazard ratio [HR] 2.76, p<0.001), and hospital length of stay (17.4 versus 7.9 days, p<0.0001). CONCLUSION: There was no evidence of a difference in radiological severity of Alpha variant infection compared with pre-existing strains. High CTSS applied to CTPA is associated with increased risk of COVID-19 severity and poorer clinical outcomes and may be of use particularly in settings where CT is not performed for diagnosis of COVID-19 but rather is used following clinical deterioration

Retinoic acid reduces human neuroblastoma cell migration and invasiveness: effects on DCX, LIS1, neurofilaments-68 and vimentin expression

<p>Abstract</p> <p>Background</p> <p>Neuroblastoma is a severe pediatric tumor, histologically characterised by a variety of cellular phenotypes. One of the pharmacological approaches to neuroblastoma is the treatment with retinoic acid. The mechanism of action of retinoic acid is still unclear, and the development of resistance to this differentiating agent is a great therapy problem.</p> <p>Doublecortin, a microtubule-associated protein involved in neuronal migration, has recently been proposed as a molecular marker for the detection of minimal residual disease in human neuroblastoma. Nevertheless, no information is available on the expression of doublecortin in the different cell-types composing human neuroblastoma, its correlation with neuroblastoma cell motility and invasiveness, and the possible modulations exerted by retinoic acid treatment.</p> <p>Methods</p> <p>We analysed by immunofluorescence and by Western blot analysis the presence of doublecortin, lissencephaly-1 (another protein involved in neuronal migration) and of two intermediate filaments proteins, vimentin and neurofilament-68, in SK-N-SH human neuroblastoma cell line both in control conditions and under retinoic acid treatment. Migration and cell invasiveness studies were performed by wound scratch test and a modified microchemotaxis assay, respectively.</p> <p>Results</p> <p>Doublecortin is expressed in two cell subtypes considered to be the more aggressive and that show high migration capability and invasiveness.</p> <p>Vimentin expression is excluded by these cells, while lissencephaly-1 and neurofilaments-68 are immunodetected in all the cell subtypes of the SK-N-SH cell line. Treatment with retinoic acid reduces cell migration and invasiveness, down regulates doublecortin and lissencephaly-1 expression and up regulates neurofilament-68 expression. However, some cells that escape from retinoic acid action maintain migration capability and invasiveness and express doublecortin.</p> <p>Conclusion</p> <p>a) Doublecortin is expressed in human neuroblastoma cells that show high motility and invasiveness;</p> <p>b) Retinoic acid treatment reduces migration and invasiveness of the more aggressive cell components of SK-N-SH cells;</p> <p>c) The cells that after retinoic acid exposure show migration and invasive capability may be identified on the basis of doublecortin expression.</p

Long-term radiological and histological outcomes following selective internal radiation therapy to liver metastases from breast cancer.

Liver metastasis from breast cancer is associated with poor prognosis and is a major cause of early morbidity and mortality. When liver resection is not feasible, minimally invasive directed therapies are considered to attempt to prolong survival. Selective internal radiation therapy (SIRT) with yttrium-90 microspheres is a liver-directed therapy that can improve local control of liver metastases from colorectal cancer. We present a case of a patient with a ductal breast adenocarcinoma, who developed liver and bone metastasis despite extensive treatment with systemic chemotherapies. Following SIRT to the liver, after an initial response, the patient ultimately progressed in the liver after 7 months. Liver tumor histology obtained 20 months after the SIRT intervention demonstrated the presence of the resin microspheres in situ. This case report demonstrates the long-term control that may be achieved with SIRT to treat liver metastases from breast cancer that is refractory to previous chemotherapies, and the presence of microspheres in situ long-term

Racial differences in treatment and survival in older patients with diffuse large B-cell lymphoma (DLBCL)

<p>Abstract</p> <p>Background</p> <p>Diffuse large B-cell lymphoma (DLBCL) comprises 31% of lymphomas in the United States. Although it is an aggressive type of lymphoma, 40% to 50% of patients are cured with treatment. The study objectives were to identify patient factors associated with treatment and survival in DLBCL.</p> <p>Methods</p> <p>Using Surveillance, Epidemiology, and End Results (SEER) registry data linked to Medicare claims, we identified 7,048 patients diagnosed with DLBCL between January 1, 2001 and December 31, 2005. Patients were followed from diagnosis until the end of their claims history (maximum December 31, 2007) or death. Medicare claims were used to characterize the first infused chemo-immunotherapy (C-I therapy) regimen and to identify radiation. Multivariate analyses were performed to identify patient demographic, socioeconomic, and clinical factors associated with treatment and with survival. Outcomes variables in the survival analysis were all-cause mortality, non-Hodgkin's lymphoma (NHL) mortality, and other/unknown cause mortality.</p> <p>Results</p> <p>Overall, 84% (n = 5,887) received C-I therapy or radiation treatment during the observation period: both, 26%; C-I therapy alone, 53%; and radiation alone, 5%. Median age at diagnosis was 77 years, 54% were female, 88% were white, and 43% had Stage III or IV disease at diagnosis. The median time to first treatment was 42 days, and 92% of these patients had received their first treatment by day 180 following diagnosis. In multivariate analysis, the treatment rate was significantly lower among patients ≥ 80 years old, blacks versus whites, those living in a census tract with ≥ 12% poverty, and extra-nodal disease. Blacks had a lower treatment rate overall (Hazard Ratio [HR] 0.77; P < 0.001), and were less likely to receive treatment within 180 days of diagnosis (Odds Ratio [OR] 0.63; P = 0.002) than whites. In multivariate survival analysis, black race was associated with higher all-cause mortality (HR 1.24; P = 0.01) and other/unknown cause mortality (HR 1.35; P = 0.01), but not mortality due to NHL (HR 1.16; P = 0.19).</p> <p>Conclusions</p> <p>In elderly patients diagnosed with DLBCL, there are large differences in treatment access and survival between blacks and whites.</p