SPEKcheck — fluorescence microscopy spectral visualisation and optimisation: a web application, javascript library, and data resource

Advanced fluorescence imaging methods require careful matching of excitation sources, dichroics, emission filters, detectors, and dyes to operate at their best. This complex task is often left to guesswork, preventing optimal dye:filter combinations, particularly for multicolour applications. To overcome this challenge we developed SPEKcheck, a web application to visualise the efficiency of the light path in a fluorescence microscope. The software reports values for the excitation efficiency of a dye, the collection efficiency of the emitted fluorescence, and a "brightness" score, allowing easy comparison between different fluorescent labels. It also displays a spectral plot of various elements in the configuration, enabling users to readily spot potential problems such as low efficiency excitation, emission, or high bleedthrough. It serves as an aid to exploring the performance of different dyes and filter sets

Python-Microscope - a new open-source Python library for the control of microscopes

Custom-built microscopes often require control of multiple hardware devices and precise hardware coordination. It is also desirable to have a solution that is scalable to complex systems and that is translatable between components from different manufacturers. Here we report Python-Microscope, a free and open-source Python library for high-performance control of arbitrarily complex and scalable custom microscope systems. Python-Microscope offers simple to use Python-based tools, abstracting differences between physical devices by providing a defined interface for different device types. Concrete implementations are provided for a range of specific hardware, and a framework exists for further expansion. Python-Microscope supports the distribution of devices over multiple computers while maintaining synchronisation via highly precise hardware triggers. We discuss the architectural features of Python-Microscope that overcome the performance problems often raised against Python and demonstrate the different use cases that drove its design: integration with user-facing projects, namely the Microscope-Cockpit project; control of complex microscopes at high speed while using the Python programming language; and use as a microscope simulation tool for software development

Clonal analysis of Salmonella-specific effector T cells reveals serovar-specific and cross-reactive T cell responses

To tackle the complexity of cross-reactive and pathogen-specific T cell responses against related Salmonella serovars, we used mass cytometry, unbiased single-cell cloning, live fluorescence barcoding, and T cell–receptor sequencing to reconstruct the Salmonella-specific repertoire of circulating effector CD4+ T cells, isolated from volunteers challenged with Salmonella enterica serovar Typhi (S. Typhi) or Salmonella Paratyphi A (S. Paratyphi). We describe the expansion of cross-reactive responses against distantly related Salmonella serovars and of clonotypes recognizing immunodominant antigens uniquely expressed by S. Typhi or S. Paratyphi A. In addition, single–amino acid variations in two immunodominant proteins, CdtB and PhoN, lead to the accumulation of T cells that do not cross-react against the different serovars, thus demonstrating how minor sequence variations in a complex microorganism shape the pathogen-specific T cell repertoire. Our results identify immune-dominant, serovar-specific, and cross-reactive T cell antigens, which should aid in the design of T cell–vaccination strategies against Salmonella

Rationale, design, and baseline characteristics in Evaluation of LIXisenatide in Acute Coronary Syndrome, a long-term cardiovascular end point trial of lixisenatide versus placebo

BACKGROUND: Cardiovascular (CV) disease is the leading cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). Furthermore, patients with T2DM and acute coronary syndrome (ACS) have a particularly high risk of CV events. The glucagon-like peptide 1 receptor agonist, lixisenatide, improves glycemia, but its effects on CV events have not been thoroughly evaluated. METHODS: ELIXA (www.clinicaltrials.gov no. NCT01147250) is a randomized, double-blind, placebo-controlled, parallel-group, multicenter study of lixisenatide in patients with T2DM and a recent ACS event. The primary aim is to evaluate the effects of lixisenatide on CV morbidity and mortality in a population at high CV risk. The primary efficacy end point is a composite of time to CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for unstable angina. Data are systematically collected for safety outcomes, including hypoglycemia, pancreatitis, and malignancy. RESULTS: Enrollment began in July 2010 and ended in August 2013; 6,068 patients from 49 countries were randomized. Of these, 69% are men and 75% are white; at baseline, the mean ± SD age was 60.3 ± 9.7 years, body mass index was 30.2 ± 5.7 kg/m(2), and duration of T2DM was 9.3 ± 8.2 years. The qualifying ACS was a myocardial infarction in 83% and unstable angina in 17%. The study will continue until the positive adjudication of the protocol-specified number of primary CV events. CONCLUSION: ELIXA will be the first trial to report the safety and efficacy of a glucagon-like peptide 1 receptor agonist in people with T2DM and high CV event risk