Innovation policy involves trading off monopoly output and pricing in the short run in exchange for incentives for firms to develop new products in the future. While existing research demonstrates that expected profits fuel R&D investments, little is known about the novelty of the projects funded by these investments. Relying on data that describe the scientific approaches used by a large sample of experimental drug projects, we expand on this literature by examining the scientific novelty of pharmaceutical R&D investments following the creation of the Medicare Part D program. We find little evidence that the positive demand shock implied by this program prompted firms to undertake scientifically novel R&D activity, as measured by whether the specific scientific approach had been used before. However, we find some evidence that firms invested in products involving novel combinations of scientific approaches. These estimates can inform economists and policymakers assessing the tradeoffs associated with marginal changes in commercial returns from newly developed pharmaceutical products.

We show a causal impact of immigration on innovation and dynamism in US counties. To identify the causal impact of immigration, we use 130 years of detailed data on migrations from foreign countries to US counties to isolate quasi-random variation in the ancestry composition of US counties that results purely from the interaction of two historical forces: (i) changes over time in the relative attractiveness of different destinations within the US to the average migrant arriving at the time and (ii) the staggered timing of the arrival of migrants from different origin countries. We then use this plausibly exogenous variation in ancestry composition to predict the total number of migrants flowing into each US county in recent decades. We show four main results. First, immigration has a positive impact on innovation, measured by the patenting of local firms. Second, immigration has a positive impact on measures of local economic dynamism. Third, the positive impact of immigration on innovation percolates over space, but spatial spillovers quickly die out with distance. Fourth, the impact of immigration on innovation is stronger for more educated migrants.

A wrap that also keeps mosquitoes away and a sheet that slips between you and the airplane seat are a couple of products that help keep you safe.

Dixie State University recently announced both a new educational certificate and a new director for its Atwood Innovation Plaza.

strataconf: Innovative ways journalists are using data to tell stories http://t.co/y8RVUwHO4G Global open data, scholarships, mapping a civil war & more

Level up with Tableau to build eye-catching, easy-to-interpret data visualizations. In this follow-up guide to Practical Tableau, author Ryan Sleeper takes you through a collection of unique tips and tutorials for using this popular software. Beginning to advanced Tableau users will learn how to go beyond Show Me to make better charts and learn dozens of tricks to improve both the author and user experience.

Rita J. King, co-director and EVP for business development at Science House, recently conducted a series of interviews with business leaders, exploring the challenges and hurdles companies face in evolving business landscapes. In this interview, King chats with James Jorasch, founding CEO of Science House, about the importance of innovation and how to inspire and […]

(University of Massachusetts Lowell) UMass Medical School and UMass Lowell will perform a key role in a new National Institutes of Health initiative aimed at speeding innovation, development and commercialization of COVID-19 testing technologies via their Center for Advancing Point of Care Technologies collaboration.

Entrepreneur Ricky Chan’s information technology company has been hard at work developing a virtual reality application that enables designers and their clients to walk through different versions of their home or office without having to physically move a single piece of furniture.

From the colour of the walls to the style of fixtures and fittings, Mr Chan’s app caters to all personal tastes and design ideas.

“We have customers who are interior designers or furniture retailers. Our virtual reality application brings their sketches to life. Designers in the past needed weeks to produce sketches. Now they can make designs instantly,” he explained.

Up to 40% of the application was developed at Smart-Space 8 in Tsuen Wan, Cyberport’s first co-working space outside its main Pok Fu Lam campus.

“Cyberport provides funding that helps to lower our expenses and we can hold seminars here with a rental fee that is much lower than the market price,” Mr Chan added.
 

The 20,000 sq ft space launched last year was specifically designed with young entrepreneurs in mind and provides workshops and seminars for startups. For companies that wish to join the Smart-Space 8 community, one of its founders must be aged between 18 and 35 and the company itself should not have been in operation for longer than seven years.

Smart-Space 8 users are entitled to comprehensive entrepreneurial support and value-added services to accelerate their businesses such as the Cyberport Creative Micro Fund and Cyberport Incubation Programme.

Mr Chan, who lives in the New Territories, said the added bonus of setting up shop in Smart-Space 8 is the commute, as Cyberport in Pok Fu Lam is farther away for him and his clients.

Cyberport may be expanding beyond Pok Fu Lam, but some entrepreneurs like agriculture technology company CEO and founder Gordon Tam have opted to stay at the home campus because of the incentives available.

“The business network here is unique. There are so many startups and we encourage and learn from each other.”

Mr Tam’s company sells vegetables from an indoor farm to local supermarkets and is now exploring the overseas market. He credits the vibrant community and ecosystem at Cyberport for building up his business.

“Traditional agriculture comes with a host of problems and the efficiency of Hong Kong’s agriculture industry is relatively low. This is why we are looking into indoor agriculture. We want to grow plants in industrial buildings.”

When Mr Tam joined the Cyberport Incubation Programme, his firm was offered two years of rent reduction. But more importantly, he said, the space is a one-of-a-kind ecosystem where his team can brainstorm ideas and continue to innovate.

Other startup owners share the same sentiment. Information technology company CEO and founder Stark Chan noted that with Cyberport as a public body, it offers a lot of support and rents are more stable.

“We have been here since we first started up. My colleagues are familiar with this environment and the atmosphere is good for innovation,” Mr Chan said.

(St. Jude Children's Research Hospital) Funding will help expand collaboration across engineering and physical sciences to expand tools for studying pediatric diseases.

Anne-Claude Gingras
Apr 1, 2020; 19:572-573
Editorial

This programme of work addresses the conundrum of nuclear weapons as a wicked problem in a complex adaptive system.

Research Event

Event participants

Helen Alderson, Head of Regional Delegation to UK and Ireland, International Committee of the Red Cross
Paul van Zyl, Co-Founder and Chief Creative Officer, The Conduit
Maya Marissa Malek, Chief Executive Officer, Amanie Advisors Global Office
Chair: Maram Ahmed, Senior Teaching Fellow, SOAS, University of London

In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.

We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.

Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

Top-down proteomics studies intact proteoform mixtures and offers important advantages over more common bottom-up proteomics technologies, as it avoids the protein inference problem. However, achieving complete molecular characterization of investigated proteoforms using existing technologies remains a fundamental challenge for top-down proteomics. Here, we benchmark the performance of ultraviolet photodissociation (UVPD) using 213 nm photons generated by a solid-state laser applied to the study of intact proteoforms from three organisms. Notably, the described UVPD setup applies multiple laser pulses to induce ion dissociation, and this feature can be used to optimize the fragmentation outcome based on the molecular weight of the analyzed biomolecule. When applied to complex proteoform mixtures in high-throughput top-down proteomics, 213 nm UVPD demonstrated a high degree of complementarity with the most employed fragmentation method in proteomics studies, higher-energy collisional dissociation (HCD). UVPD at 213 nm offered higher average proteoform sequence coverage and degree of proteoform characterization (including localization of post-translational modifications) than HCD. However, previous studies have shown limitations in applying database search strategies developed for HCD fragmentation to UVPD spectra which contains up to nine fragment ion types. We therefore performed an analysis of the different UVPD product ion type frequencies. From these data, we developed an ad hoc fragment matching strategy and determined the influence of each possible ion type on search outcomes. By paring down the number of ion types considered in high-throughput UVPD searches from all types down to the four most abundant, we were ultimately able to achieve deeper proteome characterization with UVPD. Lastly, our detailed product ion analysis also revealed UVPD cleavage propensities and determined the presence of a product ion produced specifically by 213 nm photons. All together, these observations could be used to better elucidate UVPD dissociation mechanisms and improve the utility of the technique for proteomic applications.

The presentation of peptides on class I human leukocyte antigen (HLA-I) molecules plays a central role in immune recognition of infected or malignant cells. In cancer, non-self HLA-I ligands can arise from many different alterations, including non-synonymous mutations, gene fusion, cancer-specific alternative mRNA splicing or aberrant post-translational modifications. Identifying HLA-I ligands remains a challenging task that requires either heavy experimental work for in vivo identification or optimized bioinformatics tools for accurate predictions. To date, no HLA-I ligand predictor includes post-translational modifications. To fill this gap, we curated phosphorylated HLA-I ligands from several immunopeptidomics studies (including six newly measured samples) covering 72 HLA-I alleles and retrieved a total of 2,066 unique phosphorylated peptides. We then expanded our motif deconvolution tool to identify precise binding motifs of phosphorylated HLA-I ligands. Our results reveal a clear enrichment of phosphorylated peptides among HLA-C ligands and demonstrate a prevalent role of both HLA-I motifs and kinase motifs on the presentation of phosphorylated peptides. These data further enabled us to develop and validate the first predictor of interactions between HLA-I molecules and phosphorylated peptides.

Protein-protein interactions play a vital role in nearly all cellular functions. Hence, understanding their interaction patterns and three-dimensional structural conformations can provide crucial insights about various biological processes and underlying molecular mechanisms for many disease phenotypes. Cross-linking mass spectrometry (XL-MS) has the unique capability to detect protein-protein interactions at a large scale along with spatial constraints between interaction partners. The inception of MS-cleavable cross-linkers enabled the MS2-MS3 XL-MS acquisition strategy that provides cross-link information from both MS2 and MS3 level. However, the current cross-link search algorithm available for MS2-MS3 strategy follows a "MS2-centric" approach and suffers from a high rate of mis-identified cross-links. We demonstrate the problem using two new quality assessment metrics ["fraction of mis-identifications" (FMI) and "fraction of interprotein cross-links from known interactions" (FKI)]. We then address this problem, by designing a novel "MS3-centric" approach for cross-link identification and implementing it as a search engine named MaXLinker. MaXLinker outperforms the currently popular search engine with a lower mis-identification rate, and higher sensitivity and specificity. Moreover, we performed human proteome-wide cross-linking mass spectrometry using K562 cells. Employing MaXLinker, we identified a comprehensive set of 9319 unique cross-links at 1% false discovery rate, comprising 8051 intraprotein and 1268 interprotein cross-links. Finally, we experimentally validated the quality of a large number of novel interactions identified in our study, providing a conclusive evidence for MaXLinker's robust performance.

The use of protein biomarkers as surrogates for clinical endpoints requires extensive multilevel validation including development of robust and sensitive assays for precise measurement of protein concentration. Multiple reaction monitoring (MRM) is a well-established mass-spectrometric method that can be used for reproducible protein-concentration measurements in biological specimens collected via microsampling. The dried blood spot (DBS) microsampling technique can be performed non-invasively without the expertise of a phlebotomist, and can enhance analyte stability which facilitate the application of this technique in retrospective studies while providing lower storage and shipping costs, because cold-chain logistics can be eliminated. Thus, precise, sensitive, and multiplexed methods for measuring protein concentrations in DBSs can be used for de novo biomarker discovery and for biomarker quantification or verification experiments. To achieve this goal, MRM assays were developed for multiplexed concentration measurement of proteins in DBSs.

The lower limit of quantification (LLOQ) was found to have a median total coefficient of variation (CV) of 18% for 245 proteins, whereas the median LLOQ was 5 fmol of peptide injected on column, and the median inter-day CV over 4 days for measuring endogenous protein concentration was 8%. The majority (88%) of the assays displayed parallelism, whereas the peptide standards remained stable throughout the assay workflow and after exposure to multiple freeze-thaw cycles. For 190 proteins, the measured protein concentrations remained stable in DBS stored at ambient laboratory temperature for up to 2 months. Finally, the developed assays were used to measure the concentration ranges for 200 proteins in twenty same sex, same race and age matched individuals.

Dynamic tyrosine phosphorylation is fundamental to a myriad of cellular processes. However, the inherently low abundance of tyrosine phosphorylation in the proteome and the inefficient enrichment of phosphotyrosine(pTyr)-containing peptides has led to poor pTyr peptide identification and quantitation, critically hindering researchers' ability to elucidate signaling pathways regulated by tyrosine phosphorylation in systems where cellular material is limited. The most popular approaches to wide-scale characterization of the tyrosine phosphoproteome use pTyr enrichment with pan-specific, anti-pTyr antibodies from a large amount of starting material. Methods that decrease the amount of starting material and increase the characterization depth of the tyrosine phosphoproteome while maintaining quantitative accuracy and precision would enable the discovery of tyrosine phosphorylation networks in rarer cell populations. To achieve these goals, the BOOST (Broad-spectrum Optimization Of Selective Triggering) method leveraging the multiplexing capability of tandem mass tags (TMT) and the use of pervanadate (PV) boost channels (cells treated with the broad-spectrum tyrosine phosphatase inhibitor PV) selectively increased the relative abundance of pTyr-containing peptides. After PV boost channels facilitated selective fragmentation of pTyr-containing peptides, TMT reporter ions delivered accurate quantitation of each peptide for the experimental samples while the quantitation from PV boost channels was ignored. This method yielded up to 6.3-fold boost in pTyr quantification depth of statistically significant data derived from contrived ratios, compared with TMT without PV boost channels or intensity-based label-free (LF) quantitation while maintaining quantitative accuracy and precision, allowing quantitation of over 2300 unique pTyr peptides from only 1 mg of T cell receptor-stimulated Jurkat T cells. The BOOST strategy can potentially be applied in analyses of other post-translational modifications where treatments that broadly elevate the levels of those modifications across the proteome are available.

State-of-the-art proteomics-grade mass spectrometers can measure peptide precursors and their fragments with ppm mass accuracy at sequencing speeds of tens of peptides per second with attomolar sensitivity. Here we describe a compact and robust quadrupole-orbitrap mass spectrometer equipped with a front-end High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Interface. The performance of the Orbitrap Exploris 480 mass spectrometer is evaluated in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes in combination with FAIMS. We demonstrate that different compensation voltages (CVs) for FAIMS are optimal for DDA and DIA, respectively. Combining DIA with FAIMS using single CVs, the instrument surpasses 2500 peptides identified per minute. This enables quantification of >5000 proteins with short online LC gradients delivered by the Evosep One LC system allowing acquisition of 60 samples per day. The raw sensitivity of the instrument is evaluated by analyzing 5 ng of a HeLa digest from which >1000 proteins were reproducibly identified with 5 min LC gradients using DIA-FAIMS. To demonstrate the versatility of the instrument, we recorded an organ-wide map of proteome expression across 12 rat tissues quantified by tandem mass tags and label-free quantification using DIA with FAIMS to a depth of >10,000 proteins.

We present a technological advancement for the estimation of the affinities of Protein-Protein Interactions (PPIs) in living cells. A novel set of vectors is introduced that enables a quantitative yeast two-hybrid system based on fluorescent fusion proteins. The vectors allow simultaneous quantification of the reaction partners (Bait and Prey) and the reporter at the single-cell level by flow cytometry. We validate the applicability of this system on a small but diverse set of PPIs (eleven protein families from six organisms) with different affinities; the dissociation constants range from 117 pm to 17 μm. After only two hours of reaction, expression of the reporter can be detected even for the weakest PPI. Through a simple gating analysis, it is possible to select only cells with identical expression levels of the reaction partners. As a result of this standardization of expression levels, the mean reporter levels directly reflect the affinities of the studied PPIs. With a set of PPIs with known affinities, it is straightforward to construct an affinity ladder that permits rapid classification of PPIs with thus far unknown affinities. Conventional software can be used for this analysis. To permit automated analysis, we provide a graphical user interface for the Python-based FlowCytometryTools package.

Ion mobility can add a dimension to LC-MS based shotgun proteomics which has the potential to boost proteome coverage, quantification accuracy and dynamic range.  Required for this is suitable software that extracts the information contained in the four-dimensional (4D) data space spanned by m/z, retention time, ion mobility and signal intensity. Here we describe the ion mobility enhanced MaxQuant software, which utilizes the added data dimension. It offers an end to end computational workflow for the identification and quantification of peptides and proteins in LC-IMS-MS/MS shotgun proteomics data. We apply it to trapped ion mobility spectrometry (TIMS) coupled to a quadrupole time-of-flight (QTOF) analyzer. A highly parallelizable 4D feature detection algorithm extracts peaks which are assembled to isotope patterns. Masses are recalibrated with a non-linear m/z, retention time, ion mobility and signal intensity dependent model, based on peptides from the sample. A new matching between runs (MBR) algorithm that utilizes collisional cross section (CCS) values of MS1 features in the matching process significantly gains specificity from the extra dimension. Prerequisite for using CCS values in MBR is a relative alignment of the ion mobility values between the runs. The missing value problem in protein quantification over many samples is greatly reduced by CCS aware MBR.MS1 level label-free quantification is also implemented which proves to be highly precise and accurate on a benchmark dataset with known ground truth. MaxQuant for LC-IMS-MS/MS is part of the basic MaxQuant release and can be downloaded from http://maxquant.org.

Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t-test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all datasets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several datasets including E.coli proteome spike-in data, using both label-free and TMT-labelled quantification. In comparison to previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared to other statistical methods in both label-free and labelled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.

The presentation of post-translationally modified (PTM) peptides by cell surface HLA molecules has the potential to increase the diversity of targets for surveilling T cells. Whilst immunopeptidomics studies routinely identify thousands of HLA-bound peptides from cell lines and tissue samples, in-depth analyses of the proportion and nature of peptides bearing one or more PTMs remains challenging. Here we have analyzed HLA-bound peptides from a variety of allotypes and assessed the distribution of mass spectrometry-detected PTMs, finding deamidation of asparagine or glutamine to be highly prevalent. Given that asparagine deamidation may arise either spontaneously or through enzymatic reaction, we assessed allele-specific and global motifs flanking the modified residues. Notably, we found that the N-linked glycosylation motif NX(S/T) was highly abundant across asparagine-deamidated HLA-bound peptides. This finding, demonstrated previously for a handful of deamidated T cell epitopes, implicates a more global role for the retrograde transport of nascently N-glycosylated polypeptides from the ER and their subsequent degradation within the cytosol to form HLA-ligand precursors. Chemical inhibition of Peptide:N-Glycanase (PNGase), the endoglycosidase responsible for the removal of glycans from misfolded and retrotranslocated glycoproteins, greatly reduced presentation of this subset of deamidated HLA-bound peptides. Importantly, there was no impact of PNGase inhibition on peptides not containing a consensus NX(S/T) motif. This indicates that a large proportion of HLA-I bound asparagine deamidated peptides are generated from formerly glycosylated proteins that have undergone deglycosylation via the ER-associated protein degradation (ERAD) pathway. The information herein will help train deamidation prediction models for HLA-peptide repertoires and aid in the design of novel T cell therapeutic targets derived from glycoprotein antigens.

Invitation Only Research Event

Reverse innovation may sound like some attempt to return to the dark ages - but it has a specific meaning, especially when it comes to med-tech. It’s about where we look for innovation - and overturning our preconceived ideas of where new ideas come from. Mark Skopec, and Matthew Harris - both from Imperial College London are two of the authors...

This MPI Europe webinar examines innovative ways to better design and implement predeparture orientation programs for resetttling refugees. The discussion features observations from a refugee who went through an orientation program before being resettled in the Netherlands, and a resettlement agency official in Norway.

The third Social Innovation for Refugee Inclusion conference in Brussels, co-organized by MPI Europe with the U.S. and Canadian Missions to the European Union and the European Economic and Social Committee, explored how innovations in living situations for refugees can promote community-driven inclusion, overcome divisions, facilitate economic opportunities, and foster a sense of "home."

A discussion, including the former United Nations Deputy High Commissioner for Refugees, examining the huge strains on the global protection system and how it can better respond to protracted refugee situations and other long-term displacement, focusing on the conclusions of the Transatlantic Council on Migration's recent meeting, Beyond Asylum: Rethinking Protection Policies to Meet Sharply Escalating Needs.

The Center for Research & Education in Technology is encouraging dental schools to find out how to participate in its program and learn about the benefits to the school and its students.

In the three years since the European migration and refugee crisis vividly captured public attention, a wave of innovative initiatives has emerged to help newcomers settle into receiving societies. Now, as the sense of crisis abates, this report explores what these initiatives will need to do to outlast the hype and produce lasting change on key integration issues such as housing, economic inclusion, and community building.

Fostering the social and economic inclusion of refugees has long been the domain of governments and NGOs. In the wake of the 2015–16 European migration and refugee crisis, however, new actors have emerged and taken on important roles in integrating newcomers. This report describes key discussions and takeaways from an MPI Europe conference on these developments.

Brussels and Gütersloh, 05.03.2020 — Anticipated reform of the Common European Asylum System (CEAS), which was high on the agenda as nearly 2 million asylum seekers arrived at Europe’s door in 2015-16, quickly fell victim to EU Member State competing views on what constitutes equal burden-sharing, domestic politics around migration and the urgency of first addressing overtaxed national asylum systems.

Over the last decade, a number of governments have launched start-up visa programs in the hopes of attracting talented immigrant entrepreneurs with innovative business ideas. With the track record for these programs a mixed one, this report explains how embedding start-up visas within a broader innovation strategy could lead to greater success.

Massachusetts is the fifth state to join the Innovative Assessment Demonstration Authority created through the Every Student Succeeds Act, which allows states to experiment with new forms of testing.

The Every Student Succeeds Act allows up to seven states to try out new kinds of tests in a handful of districts before taking them statewide.