The Impossibility of a Perfectly Competitive Labor Market

Using the institutional theory of transaction cost, I demonstrate that the assumptions of the competitive labor market model are internally contradictory and lead to the conclusion that on purely theoretical grounds a perfectly competitive labor market is a logical impossibility. By extension, the familiar diagram of wage determination by supply and demand is also a logical impossibility and the neoclassical labor demand curve is not a well-defined construct. The reason is that the perfectly competitive market model presumes zero transaction cost and with zero transaction cost all labor is hired as independent contractors, implying multi-person firms, the employment relationship, and labor market disappear. With positive transaction cost, on the other hand, employment contracts are incomplete and the labor supply curve to the firm is upward sloping, again causing the labor demand curve to be ill-defined. As a result, theory suggests that wage rates are always and everywhere an amalgam of an administered and bargained price. Working Paper 06-0

Allopurinol versus usual care in UK patients with ischaemic heart disease (ALL-HEART) : a multicentre, prospective, randomised, open-label, blinded-endpoint trial

Funding Information: ISM reports research grants from Menarini, EMA, Sanofi, Health Data Research UK, the British Heart Foundation, and Innovative Medicines Initiative; institutional consultancy income from AstraZeneca outside the submitted work; and personal income from AstraZeneca and Amgen outside the submitted work. TMM reports grants from Menarini/Ipsen/Teijin and Merck Sharp & Dohme outside the submitted work, and personal income for consultancy from Novartis and AstraZeneca outside the submitted work, and is a trustee of the Scottish Heart Arterial Risk Prevention Society. AGB reports personal income from Novartis, Mylan, AstraZeneca, Bayer, Daiichi-Sankyo, Boehringer, Pfizer, Galderma, Zambon, and Novo-Nordisk outside the submitted work. ADS and the University of Dundee hold a European patent for the use of xanthine oxidase inhibitors in treating chest pain in angina pectoris. AW declares personal income for consultancy from AbbVie, Akcea, Albireo, Alexion, Allergan, Amarin, Apsara, Arena, Astellas, AstraZeneca, Autolus, Bayer, Biocryst, Biogen, Biomarin, Bristol Myers Squibb, Boehringer Ingelheim, Calico, Celgene, Chiesi, Daiichi Sankyo, Diurnal, Elsai, Eli Lilly, Ferring, Galapagos, Gedeon Richter, Gilead, GlaxoSmithKline, GW Pharma, Idorsia, Incyte, Intercept, Ionis, Ipsen, Janssen, Jazz, Jcyte, Kite Gilead, LEK, Leo Pharma, Les Laboratoires Servier, Lundbeck, Merck (Merck Sharp & Dohme), Merck-Serono, Mitenyi, Mundibiopharma, Mustang Bio, Mylan, Myovant, Norgine, Novartis, Novo Nordisk, Orchard, Paion, Pfizer, Pierre Fabre, PTC, RegenXBio, Rhythm, Sanofi, Santen, Sarepta, SeaGen, Shionogi, Sigmatec, SOBI, Takeda, Tanaya, UCB, and Vertex outside the submitted work. JST declares research funding from the UK National Institute for Health and Care Research (NIHR) and NHS England outside the submitted work and membership of a UK National Institute for Health and Care Excellence guideline committee on management of atrial fibrillation. All other authors declare no competing interests. Funding Information: This study was funded by the NIHR Health Technology Assessment programme (HTA 11/36/41 to ISM, IF, CJH, LW, ADS, AGB, AJA, AW, JST, and TMM). The views expressed are those of the authors and not necessarily those of the NIHR or the UK Department of Health and Social Care. The study was supported by the Scottish Primary Care Research Network, Support for Science Scotland (Grampian, Highlands, Tayside, Fife, Forth Valley, Greater Glasgow and Clyde, Lothian, Ayrshire and Arran, Dumfries and Galloway, and Lanarkshire), and the NIHR Local Clinical Research Networks (East Midlands, West Midlands, Eastern, North Thames, Yorkshire and Humber, North East and North Cumbria, North West Coast, Kent, Surrey and Sussex, and South West Peninsula), which assisted with recruitment and other study activities. We thank Public Health Scotland and NHS Digital for providing data linkage. We thank all the participants, physicians, nurses, and other staff who participated in the ALL-HEART study. Funding Information: This study was funded by the NIHR Health Technology Assessment programme (HTA 11/36/41 to ISM, IF, CJH, LW, ADS, AGB, AJA, AW, JST, and TMM). The views expressed are those of the authors and not necessarily those of the NIHR or the UK Department of Health and Social Care. The study was supported by the Scottish Primary Care Research Network, Support for Science Scotland (Grampian, Highlands, Tayside, Fife, Forth Valley, Greater Glasgow and Clyde, Lothian, Ayrshire and Arran, Dumfries and Galloway, and Lanarkshire), and the NIHR Local Clinical Research Networks (East Midlands, West Midlands, Eastern, North Thames, Yorkshire and Humber, North East and North Cumbria, North West Coast, Kent, Surrey and Sussex, and South West Peninsula), which assisted with recruitment and other study activities. We thank Public Health Scotland and NHS Digital for providing data linkage. We thank all the participants, physicians, nurses, and other staff who participated in the ALL-HEART study. Publisher Copyright: © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licensePeer reviewedPublisher PD

Novelty detection and learning drives

This document presents Deliverable 5.1 of the IM-CLeVeR (Intrinsically Motivated Cumulative Learning Versatile Robots) EU FP7 project. It represents one of two deliverables from Workpackage 5 (Novelty Detection and Drives for Autonomous Learning)

Allopurinol versus usual care in UK patients with ischaemic heart disease (ALL-HEART): a multicentre, prospective, randomised, open-label, blinded-endpoint trial

BACKGROUND: Allopurinol is a urate-lowering therapy used to treat patients with gout. Previous studies have shown that allopurinol has positive effects on several cardiovascular parameters. The ALL-HEART study aimed to determine whether allopurinol therapy improves major cardiovascular outcomes in patients with ischaemic heart disease. METHODS: ALL-HEART was a multicentre, prospective, randomised, open-label, blinded-endpoint trial done in 18 regional centres in England and Scotland, with patients recruited from 424 primary care practices. Eligible patients were aged 60 years or older, with ischaemic heart disease but no history of gout. Participants were randomly assigned (1:1), using a central web-based randomisation system accessed via a web-based application or an interactive voice response system, to receive oral allopurinol up-titrated to a dose of 600 mg daily (300 mg daily in participants with moderate renal impairment at baseline) or to continue usual care. The primary outcome was the composite cardiovascular endpoint of non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death. The hazard ratio (allopurinol vs usual care) in a Cox proportional hazards model was assessed for superiority in a modified intention-to-treat analysis (excluding randomly assigned patients later found to have met one of the exclusion criteria). The safety analysis population included all patients in the modified intention-to-treat usual care group and those who took at least one dose of randomised medication in the allopurinol group. This study is registered with the EU Clinical Trials Register, EudraCT 2013-003559-39, and ISRCTN, ISRCTN32017426. FINDINGS: Between Feb 7, 2014, and Oct 2, 2017, 5937 participants were enrolled and then randomly assigned to receive allopurinol or usual care. After exclusion of 216 patients after randomisation, 5721 participants (mean age 72·0 years [SD 6·8], 4321 [75·5%] males, and 5676 [99·2%] white) were included in the modified intention-to-treat population, with 2853 in the allopurinol group and 2868 in the usual care group. Mean follow-up time in the study was 4·8 years (1·5). There was no evidence of a difference between the randomised treatment groups in the rates of the primary endpoint. 314 (11·0%) participants in the allopurinol group (2·47 events per 100 patient-years) and 325 (11·3%) in the usual care group (2·37 events per 100 patient-years) had a primary endpoint (hazard ratio [HR] 1·04 [95% CI 0·89–1·21], p=0·65). 288 (10·1%) participants in the allopurinol group and 303 (10·6%) participants in the usual care group died from any cause (HR 1·02 [95% CI 0·87–1·20], p=0·77). INTERPRETATION: In this large, randomised clinical trial in patients aged 60 years or older with ischaemic heart disease but no history of gout, there was no difference in the primary outcome of non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death between participants randomised to allopurinol therapy and those randomised to usual care. FUNDING: UK National Institute for Health and Care Research

A local human Vδ1 T cell population is associated with survival in nonsmall-cell lung cancer

Funding Information: D.B. has consulted for NanoString, reports honoraria from AstraZeneca and has a patent (PCT/GB2020/050221) issued on methods for cancer prognostication. J.R. and M.A.B. have consulted for Achilles Therapeutics. N.M. has stock options in and has consulted for Achilles Therapeutics. N.M. holds European patents relating to targeting neoantigens (PCT/EP2016/059401), identifying patient response to immune checkpoint blockade (PCT/EP2016/071471), determining HLA loss of heterozygosity (PCT/GB2018/052004) and predicting survival rates of patients with cancer (PCT/GB2020/050221). A.H. attended one advisory board for Abbvie, Roche and GRAIL, and reports personal fees from Abbvie, Boehringer Ingelheim, Takeda, AstraZeneca, Daiichi Sankyo, Merck Serono, Merck/MSD, UCB and Roche for delivering general education/training in clinical trials. A.H. owned shares in Illumina and Thermo Fisher Scientific (sold in 2020) and receives fees for membership of Independent Data Monitoring Committees for Roche-sponsored clinical trials. S.A.Q. is co-founder and Chief Scientific Officer of Achilles Therapeutics. A.C.H. is a board member and equity holder in ImmunoQure, AG and Gamma Delta Therapeutics, and is an equity holder in Adaptate Biotherapeutics and chair of the scientific advisory board. C.S. acknowledges grant support from Pfizer, AstraZeneca, Bristol Myers Squibb, Roche-Ventana, Boehringer Ingelheim, Archer Dx Inc (collaboration in minimal residual disease-sequencing technologies) and Ono Pharmaceuticals, is an AstraZeneca Advisory Board member and Chief Investigator for the MeRmaiD1 clinical trial. C.S has consulted for Amgen, AstraZeneca, Bicycle Therapeutics, Bristol Myers Squibb, Celgene, Genentech, GlaxoSmithKline, GRAIL, Illumina, Medixci, Metabomed, MSD, Novartis, Pfizer, Roche-Ventana and Sarah Cannon Research Institute. C.S. has stock options in Apogen Biotechnologies, Epic Biosciences and GRAIL, and has stock options and is co-founder of Achilles Therapeutics. C.S. holds patents relating: to assay technology to detect tumor recurrence (PCT/GB2017/053289); to targeting neoantigens (PCT/EP2016/059401), identifying patent response to immune checkpoint blockade (PCT/EP2016/071471), determining HLA loss of heterozygosity (PCT/GB2018/052004), predicting survival rates of patients with cancer (PCT/GB2020/050221); to treating cancer by targeting Insertion/deletion (indel) mutations (PCT/GB2018/051893); to identifying indel mutation targets (PCT/GB2018/051892); to methods for lung cancer detection (PCT/US2017/028013); and to identifying responders to cancer treatment (PCT/GB2018/051912). The remaining authors declare no competing interests. Funding Information: We thank the Oxford Genomics Centre at the Wellcome Centre for Human Genetics (funded by Wellcome Trust grant no. 203141/Z/16/Z) for the generation and initial processing of the RNA-seq data from sorted TILs. We thank S. Bola for technical support and S. Vanloo for administrative support. The GTEx project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by the NCI, NHGRI, NHLBI, NIDA, NIMH and NINDS. Y.W. was supported by a Wellcome Trust Clinical Research Career Development Fellowship (no. 220589/Z/20/Z), an Academy of Medical Sciences Starter Grant for Clinical Lecturers, a National Institute for Health Research (NIHR) Academic Clinical Lectureship and the NIHR University College London Hospitals Biomedical Research Centre. D.B. was supported by funding from the NIHR University College London Hospitals Biomedical Research Centre, the ideas 2 innovation translation scheme at the Francis Crick Institute, the Breast Cancer Research Foundation (BCRF) and a Cancer Research UK (CRUK) Early Detection and Diagnosis Project award. M.J.H. is a CRUK Fellow and has received funding from CRUK, NIHR, Rosetrees Trust, UKI NETs and the NIHR University College London Hospitals Biomedical Research Centre. C.S. is Royal Society Napier Research Professor. This work was supported by the Francis Crick Institute which receives its core funding from CRUK (no. FC001169), the UK Medical Research Council (no. FC001169) and the Wellcome Trust (no. FC001169). This research was funded in whole, or in part, by the Wellcome Trust (no. FC001169). For the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. C.S. is funded by CRUK (TRACERx, PEACE and CRUK Cancer Immunotherapy Catalyst Network), CRUK Lung Cancer Centre of Excellence (no. C11496/A30025), the Rosetrees Trust, Butterfield and Stoneygate Trusts, NovoNordisk Foundation (ID16584), Royal Society Professorship Enhancement Award (no. RP/EA/180007), the NIHR Biomedical Research Centre at University College London Hospitals, the CRUK–University College London Centre, Experimental Cancer Medicine Centre and the BCRF. This work was supported by a Stand Up To Cancer‐LUNGevity-American Lung Association Lung Cancer Interception Dream Team Translational Research Grant (grant no. SU2C-AACR-DT23-17 to S. M. Dubinett and A. E. Spira). Stand Up To Cancer is a division of the Entertainment Industry Foundation. Research grants are administered by the American Association for Cancer Research, the Scientific Partner of SU2C. C.S. receives funding from the European Research Council (ERC) under the European Union’s Seventh Framework Programme (no. FP7/2007-2013) Consolidator Grant (no. FP7-THESEUS-617844), European Commission ITN (no. FP7-PloidyNet 607722), an ERC Advanced Grant (PROTEUS) from the ERC under the European Union’s Horizon 2020 research and innovation program (grant no. 835297), and Chromavision from the European Union’s Horizon 2020 research and innovation program (grant no. 665233). Publisher Copyright: © 2022, The Author(s).Peer reviewedPublisher PD

Mitochondrial Cox1 Sequence Data Reliably Uncover Patterns of Insect Diversity But Suffer from High Lineage-Idiosyncratic Error Rates

The demand for scientific biodiversity data is increasing, but taxonomic expertise is often limited or not available. DNA sequencing is a potential remedy to overcome this taxonomic impediment. Mitochondrial DNA is most commonly used, e.g., for species identification ("DNA barcoding"). Here, we present the first study in arthropods based on a near-complete species sampling of a family-level taxon from the entire Australian region. We aimed to assess how reliably mtDNA data can capture species diversity when many sister species pairs are included. Then, we contrasted phylogenetic subsampling with the hitherto more commonly applied geographical subsampling, where sister species are not necessarily captured. We sequenced 800 bp cox1 for 1,439 individuals including 260 Australian species (78% species coverage). We used clustering with thresholds of 1 to 10% and general mixed Yule Coalescent (GMYC) analysis for the estimation of species richness. The performance metrics used were taxonomic accuracy and agreement between the morphological and molecular species richness estimation. Clustering (at the 3% level) and GMYC reliably estimated species diversity for single or multiple geographic regions, with an error for larger clades of lower than 10%, thus outperforming parataxonomy. However, the rates of error were higher for some individual genera, with values of up to 45% when very recent species formed nonmonophyletic clusters. Taxonomic accuracy was always lower, with error rates above 20% and a larger variation at the genus level (0 to 70%). Sørensen similarity indices calculated for morphospecies, 3% clusters and GMYC entities for different pairs of localities was consistent among methods and showed expected decrease over distance. Cox1 sequence data are a powerful tool for large-scale species richness estimation, with a great potential for use in ecology and β-diversity studies and for setting conservation priorities. However, error rates can be high in individual lineages

Distribution and Habitat Associations of Billfish and Swordfish Larvae across Mesoscale Features in the Gulf of Mexico

Ichthyoplankton surveys were conducted in surface waters of the northern Gulf of Mexico (NGoM) over a three-year period (2006–2008) to determine the relative value of this region as early life habitat of sailfish (Istiophorus platypterus), blue marlin (Makaira nigricans), white marlin (Kajikia albida), and swordfish (Xiphias gladius). Sailfish were the dominant billfish collected in summer surveys, and larvae were present at 37.5% of the stations sampled. Blue marlin and white marlin larvae were present at 25.0% and 4.6% of the stations sampled, respectively, while swordfish occurred at 17.2% of the stations. Areas of peak production were detected and maximum density estimates for sailfish (22.09 larvae 1000 m−2) were significantly higher than the three other species: blue marlin (9.62 larvae 1000 m−2), white marlin (5.44 larvae 1000 m−2), and swordfish (4.67 larvae 1000 m−2). The distribution and abundance of billfish and swordfish larvae varied spatially and temporally, and several environmental variables (sea surface temperature, salinity, sea surface height, distance to the Loop Current, current velocity, water depth, and Sargassum biomass) were deemed to be influential variables in generalized additive models (GAMs). Mesoscale features in the NGoM affected the distribution and abundance of billfish and swordfish larvae, with densities typically higher in frontal zones or areas proximal to the Loop Current. Habitat suitability of all four species was strongly linked to physicochemical attributes of the water masses they inhabited, and observed abundance was higher in slope waters with lower sea surface temperature and higher salinity. Our results highlight the value of the NGoM as early life habitat of billfishes and swordfish, and represent valuable baseline data for evaluating anthropogenic effects (i.e., Deepwater Horizon oil spill) on the Atlantic billfish and swordfish populations

Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.

The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies

Allele-Specific HLA Loss and Immune Escape in Lung Cancer Evolution

Immune evasion is a hallmark of cancer. Losing the ability to present neoantigens through human leukocyte antigen (HLA) loss may facilitate immune evasion. However, the polymorphic nature of the locus has precluded accurate HLA copy-number analysis. Here, we present loss of heterozygosity in human leukocyte antigen (LOHHLA), a computational tool to determine HLA allele-specific copy number from sequencing data. Using LOHHLA, we find that HLA LOH occurs in 40% of non-small-cell lung cancers (NSCLCs) and is associated with a high subclonal neoantigen burden, APOBEC-mediated mutagenesis, upregulation of cytolytic activity, and PD-L1 positivity. The focal nature of HLA LOH alterations, their subclonal frequencies, enrichment in metastatic sites, and occurrence as parallel events suggests that HLA LOH is an immune escape mechanism that is subject to strong microenvironmental selection pressures later in tumor evolution. Characterizing HLA LOH with LOHHLA refines neoantigen prediction and may have implications for our understanding of resistance mechanisms and immunotherapeutic approaches targeting neoantigens. Video Abstract [Figure presented] Development of the bioinformatics tool LOHHLA allows precise measurement of allele-specific HLA copy number, improves the accuracy in neoantigen prediction, and uncovers insights into how immune escape contributes to tumor evolution in non-small-cell lung cancer