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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 127 records · Page 7Linked to original sources

Online Self-Report Data for Duchenne Muscular Dystrophy confirms natural history and can be used to assess for therapeutic benefits

To assess the utility of online patient self-report outcomes in a rare disease, we attempted to observe the effects of corticosteroids in delaying age at fulltime wheelchair use in Duchenne muscular dystrophy (DMD) using data from 1,057 males from DuchenneConnect, an online registry. Data collected were compared to prior natural history data in regard to age at diagnosis, mutation spectrum, and age at loss of ambulation. Because registrants reported differences in steroid and other medication usage, as well as age and ambulation status, we could explore these data for correlations with age at loss of ambulation. Using multivariate analysis, current steroid usage was the most significant and largest independent predictor of improved wheelchair-free survival. Thus, these online self-report data were sufficient to retrospectively observe that current steroid use by patients with DMD is associated with a delay in loss of ambulation. Comparing commonly used steroid drugs, deflazacort prolonged ambulation longer than prednisone (median 14 years and 13 years, respectively). Further, use of Vitamin D and Coenzyme Q10, insurance status, and age at diagnosis after 4 years were also significant, but smaller, independent predictors of longer wheelchair-free survival. Nine other common supplements were also individually tested but had lower study power. This study demonstrates the utility of DuchenneConnect data to observe therapeutic differences, and highlights needs for improvement in quality and quantity of patient-report data, which may allow exploration of drug/therapeutic practice combinations impractical to study in clinical trial settings. Further, with the low barrier to participation, we anticipate substantial growth in the dataset in the coming years.

Physiology

NADH as a cancer medicine

We propose that NADH will exert a specific kill action against some cancers. NADH is a natural metabolite. We envisage a low side effect profile and that NADH therapy will, additionally, combat the wastage and weakness of cancer patients, which can be the cause of death in some cases. Significantly, NADH can be administered orally and has already cleared clinical trials, all be it for other pathologies.\n\nBackgroundAerobic respiration consists of glycolysis in the cytoplasm and in the mitochondria: the Krebs cycle and oxidative phosphorylation (OXPHOS) [1, 2]. It requires O2 and net yields 30 ATPs from one glucose molecule. Anaerobic respiration, consisting of glycolysis only, does not require O2 but produces merely 2 ATPs from one glucose molecule. When O2 is available, normal animal cells tend to favour aerobic respiration because of its higher ATP yield.

Cancer Biology

Ex vivo mycobacterial growth inhibition assay (MGIA) for tuberculosis vaccine testing - a protocol for mouse splenocytes

The testing of vaccines for tuberculosis is costly and time-consuming, and dependent on preclinical animal challenge models and clinical trials. We have recently developed a mycobacterial growth inhibition assay (MGIA) to test vaccine efficacy ex vivo. This assay measures the summative effect of the host immune response and may serve as a novel tool to facilitate vaccine testing. It has generated much interest recently, and to facilitate technology transfer and reproducibility between laboratories, we here describe a detailed protocol for an ex vivo MGIA in mouse splenocytes.

Immunology

MDMA impairs response to water intake in healthy volunteers

Hyponatremia is a serious complication of 3,4-methylenedioxymethamphetamine (MDMA) use. We investigated potential mechanisms in two double-blind, placebo-controlled studies. In study 1, healthy drug-experienced volunteers received MDMA or placebo alone and in combination with the alpha-1 adrenergic inverse agonist prazosin, used as a positive control to release antidiuretic hormone (ADH). In study 2, volunteers received MDMA or placebo followed by standardized water intake. MDMA lowered serum sodium, but did not increase ADH or copeptin, although the control prazosin did increase ADH. Water loading reduced serum sodium more after MDMA than after placebo. There was a trend for women to have lower baseline serum sodium than men, but there were no significant interactions with drug condition. Combining studies, MDMA potentiated the ability of water to lower serum sodium. Thus, hyponatremia appears to be a significant risk when hypotonic fluids are consumed during MDMA use. Clinical trials and events where MDMA use is common should anticipate and mitigate this risk.

Pharmacology and Toxicology

Micro-Pharmacodynamics: Bridging In Vitro and In Vivo Experimental Scales in Testing Drug Efficacy and Resistance

Systemic chemotherapy is one of the main anticancer treatments used for most kinds of clinically diagnosed tumors. However, the efficacy of these drugs can be hampered by the physical attributes of the tumor tissue that can impede the transport of therapeutic agents to tumor cells in sufficient quantities. As a result, drugs that work well in vitro often fail at clinical trials when confronted with the complexities of interstitial transport within the tumor microenvironment. The microPD model that we developed is used to investigate the penetration of drug molecules through the tumor tissue and influenced by the physical and metabolic properties of tumor microenvironment, and how it affects drug efficacy and the emergence of drug resistance.

Systems Biology

Unearthing new genomic markers of drug response by improved measurement of discriminative power

BackgroundOncology drugs are only effective in a small proportion of cancer patients. Our current ability to identify these responsive patients before treatment is still poor in most cases. Thus, there is a pressing need to discover response markers for marketed and research oncology drugs in order to improve patient survival, reduce healthcare costs and enhance success rates in clinical trials. Screening these drugs against a large panel of cancer cell lines has been employed to discover new genomic markers of in vitro drug response, which can now be further evaluated on more accurate tumour models. However, while the identification of discriminative markers among thousands of candidate drug-gene associations in the data is error-prone, an appraisal of the effectiveness of such detection task is currently lacking.\n\nResultsHere we present a new non-parametric method to measuring the discriminative power of a drug-gene association. This is enabled by the identification of an auxiliary threshold posing this task as a binary classification problem. Unlike parametric statistical tests, the adopted non-parametric test has the advantage of not making strong assumptions about the data distorting the identification of genomic markers. Furthermore, we introduce a new benchmark to further validate these markers in vitro using more recent data not used to identify the markers. The application of this new methodology has led to the identification of 128 new genomic markers distributed across 61% of the analysed drugs, including 5 drugs without previously known markers, which were missed by the MANOVA test initially applied to analyse data from the Genomics of Drug Sensitivity in Cancer consortium.\n\nAbbreviation

Bioinformatics

Hilbert-Schmidt and Sobol sensitivity indices for static and time series Wnt signaling measurements in colorectal cancer - Part A

Ever since the accidental discovery of Wingless [Sharma R.P., Drosophila information service, 1973, 50, p 134], research in the field of Wnt signaling pathway has taken significant strides in wet lab experiments and various cancer clinical trials augmented by recent developments in advanced computational modeling of the pathway. Information rich gene expression profiles reveal various aspects of the signaling pathway at work and help in studying different issues simultaneously. Hitherto, not many computational studies exist which incorporate the simultaneous study of these issues. This manuscript is an endeavour to * explore the strength of contributing factors in the signaling pathway, * analyze the existing causal relations among the inter/extracellular factors effecting the pathway based on prior biological knowledge and * investigate the deviations in fold changes in the recently found prevalence of psychophysical laws working in the pathway. To achieve this goal, local and global sensitivity analysis is conducted on the (non)linear responses between the factors obtained from static and time series expression profiles using the density (Hilbert-Schmidt Information Criterion) and variance (Sobol) based sensitivity indices. The results show the superiority of the density based indices in comparison to the use of variance based indices mainly due to the former's employment of distance measures using the kernel trick via Reproducing kernel Hilbert space (RKHS) that capture nonlinear relations among various intra/extracellular factors of the pathway in a higher dimensional space. In time series data, using these indices it is now possible to observe where in time, which factors get influenced & contribute to the pathway, as changes in concentration of the other factors are made. This synergy of prior biological knowledge, sensitivity analysis and representations in higher dimensional spaces can facilitate in time based administration of target therapeutic drugs and reveal hidden biological information within colorectal cancer samples. Code has been made available at Google drive on https://drive.google.com/folderview?id=0B7Kkv8wlhPU-Q2NBZGt1ZERrSVE&usp=sharing

Systems Biology

Semi-Supervised Learning of the Electronic Health Record for Phenotype Stratification

Patient interactions with health care providers result in entries to electronic health records (EHRs). EHRs were built for clinical and billing purposes but contain many data points about an individual. Mining these records provides opportunities to extract electronic phenotypes, which can be paired with genetic data to identify genes underlying common human diseases. This task remains challenging: high quality phenotyping is costly and requires physician review; many fields in the records are sparsely filled; and our definitions of diseases are continuing to improve over time. Here we develop and evaluate a semi-supervised learning method for EHR phenotype extraction using denoising autoencoders for phenotype stratification. By combining denoising autoencoders with random forests we find classification improvements across multiple simulation models and improved survival prediction in ALS clinical trial data. This is particularly evident in cases where only a small number of patients have high quality phenotypes, a common scenario in EHR-based research. Denoising autoencoders perform dimensionality reduction enabling visualization and clustering for the discovery of new subtypes of disease. This method represents a promising approach to clarify disease subtypes and improve genotype-phenotype association studies that leverage EHRs.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC=\"FIGDIR/small/039800_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (31K):\norg.highwire.dtl.DTLVardef@567074org.highwire.dtl.DTLVardef@f0e45corg.highwire.dtl.DTLVardef@1207659org.highwire.dtl.DTLVardef@39f8b8_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIDenoising autoencoders (DAs) can model electronic health records.\nC_LIO_LISemi-supervised learning with DAs improves ALS patient survival predictions.\nC_LIO_LIDAs improve patient cluster visualization through dimensionality reduction.\nC_LI

Bioinformatics

Integrating genomics into clinical pediatric oncology using the molecular tumor board at the Memorial Sloan Kettering Cancer Center

BackgroundPediatric oncologists have begun to leverage tumor genetic profiling to match patients with targeted therapies. At the Memorial Sloan Kettering Cancer Center (MSKCC), we developed the Pediatric Molecular Tumor Board (PMTB) to track, integrate, and interpret clinical genomic profiling and potential targeted therapeutic recommendations.\n\nProcedureThis retrospective case series includes all patients reviewed by the MSKCC PMTB from July 2014 to June 2015. Cases were submitted by treating oncologists and potential treatment recommendations were based upon the modified guidelines of the Oxford Centre for Evidence Based Medicine.\n\nResultsThere were 41 presentations of 39 individual patients during the study period. Gliomas, acute myeloid leukemia, and neuroblastoma were the most commonly reviewed cases. Thirty nine (87%) of the 45 molecular sequencing profiles utilized hybrid-capture targeted genome sequencing. In 30 (73%) of the 41 presentations, the PMTB provided therapeutic recommendations, of which 19 (46%) were implemented. Twenty-one (70%) of the recommendations involved targeted therapies. Three (14%) targeted therapy recommendations had published evidence to support the proposed recommendations (evidence levels 1-2), 8 (36%) recommendations had preclinical evidence (level 3), and 11 (50%) recommendations were based upon hypothetical biological rationales (level 4).\n\nConclusionsThe MSKCC PMTB enabled a clinically relevant interpretation of genomic profiling. Effective use of clinical genomics is anticipated to require new and improved tools to ascribe pathogenic significance and therapeutic actionability. Development of specific rule-driven clinical protocols will be needed for the incorporation and evaluation of genomic and molecular profiling in interventional prospective clinical trials.

Genomics

Investigation of the Antimicrobial Activity of Soy Peptides by Developing a High Throughput Drug Screening Assay

BackgroundAntimicrobial resistance is a great concern in the medical community, as well as food industry. Soy peptides were tested against bacterial biofilms for their antimicrobial activity. A high throughput drug screening assay was developed using microfluidic technology, RAMAN spectroscopy, and optical microscopy for rapid screening of antimicrobials and rapid identification of pathogens.\n\nMethodsSynthesized PGTAVFK and IKAFKEATKVDKVVVLWTA soy peptides were tested against Pseudomonas aeruginosa and Listeria monocytogenes using a microdilution assay. Microfluidic technology in combination with Surface Enhanced RAMAN Spectroscopy (SERS) and optical microscopy was used for rapid screening of soy peptides, pathogen identification, and to visualize the impact of selected peptides.\n\nResultsThe PGTAVFK peptide did not significantly affect P. aeruginosa, although it had an inhibitory effect on L. monocytogenes above a concentration of 625 {micro}M. IKAFKEATKVDKVVVLWTA was effective against both P. aeruginosa and L. monocytogenes above a concentration of 37.2 {micro}M. High throughput drug screening assays were able to reduce the screening and bacterial detection time to 4 h. SERS spectra was used to distinguish the two bacterial species.\n\nConclusionsPGTAVFK and IKAFKEATKVDKVVVLWTA soy peptides showed antimicrobial activity against P. aeruginosa and L. monocytogenes. Development of high throughput assays could streamline the drug screening and bacterial detection process. General significance: The results of this study show that the antimicrobial properties, biocompatibility, and biodegradability of soy peptides could possibly make them an alternative to the ineffective antimicrobials and antibiotics currently used in the food and medical fields. High throughput drug screening assays could help hasten pre-clinical trials in the medical field.

Bioengineering

Methods for High-Throughput Drug Combination Screening and Synergy Scoring

Gene products or pathways that are aberrantly activated in cancer but not in normal tissue hold great promises for being effective and safe anticancer therapeutic targets. Many targeted drugs have entered clinical trials but so far showed limited efficacy mostly due to variability in treatment responses and often rapidly emerging resistance. Towards more effective treatment options, we will critically need multi-targeted drugs or drug combinations, which selectively inhibit the cancer cells and block distinct escape mechanisms for the cells to become resistant. Functional profiling of drug combinations requires careful experimental design and robust data analysis approaches. At the Institute for Molecular Medicine Finland (FIMM), we have developed an experimental-computational pipeline for high-throughput screening of drug combination effects in cancer cells. The integration of automated screening techniques with advanced synergy scoring tools allows for efficient and reliable detection of synergistic drug interactions within a specific window of concentrations, hence accelerating the identification of potential drug combinations for further confirmatory studies.

Systems Biology

Modeling and Analysis of Hormone and Mitogenic Signal Integration in Prostate Cancer

Prostate cancer is the most common cancer in men and the second leading cause of cancer related death in the United States. Androgens, such as testosterone, are required for androgen dependent prostate cancer (ADPC) growth. Androgen ablation in combination with radiation or chemotherapy remains the primary non-surgical treatment for ADPC. However, androgen ablation typically fails to permanently arrest cancer progression, often resulting in castration resistant prostate cancer (CRPC). In this study, we analyzed a population of mathematical models that described the integration of androgen and mitogenic signaling in androgen dependent and independent prostate cancer. An ensemble of model parameters was estimated from 43 studies of signaling in androgen dependent and resistant LNCaP cell lines. The model population was then validated by comparing simulations with an additional 33 data sets from LNCaP cell lines and clinical trials. Analysis of the model population suggested that simultaneously targeting the PI3K and MAPK pathways in addition to anti-androgen therapies could be an effective treatment for CRPC. We tested this hypothesis in both ADPC LNCaP cell lines and LNCaP derived CRPC C4-2 cells using three inhibitors: the androgen receptor inhibitor MDV3100 (enzalutamide), the Raf kinase inhibitor sorafenib, and the PI3K inhibitor LY294002. Consistent with model predictions, cell viability decreased at 72 hrs in the dual and triple inhibition cases in both the LNCaP and C4-2 cell lines, compared to treatment with any single inhibitor. Taken together, this study suggested that crosstalk between the androgen and mitogenic signaling axes led to robustness of CRPC to any single inhibitor. Model analysis predicted potentially efficacious target combinations which were confirmed by experimental studies in multiple cell lines, thereby illustrating the potentially important role that mathematical modeling can play in cancer.

Systems Biology

A novel approach to derive human midbrain-specific organoids from neuroepithelial stem cells

Research on human brain development and neurological diseases is limited by the lack of advanced experimental in vitro models that truly recapitulate the complexity of the human brain. Furthermore, animal models of human neurodegenerative diseases have failed dramatically, and the success rate of clinical trials based on these models has been disappointing. Here, we describe a novel and robust human brain organoid system that is highly specific to the midbrain derived from regionally patterned neuroepithelial stem cells. These human midbrain organoids contain spatially organized groups of dopaminergic neurons, which make them an attractive model to study Parkinsons disease. Midbrain organoids are characterized in detail for neuronal, astroglial and oligodendrocyte differentiation. Furthermore, we show the presence of synaptic connections and electrophysiological activity. The complexity of this model is further highlighted by the myelination of neurites. The present midbrain organoid system has the potential to be used for advanced in vitro disease modeling and therapy development.

Cell Biology

Gene expression markers of Tumor Infiltrating Leukocytes

BackgroundAssays of the abundance of immune cell populations in the tumor microenvironment promise to inform immune oncology research and the choice of immunotherapy for individual patients. We propose to measure the intratumoral abundance of various immune cells populations with gene expression. In contrast to IHC and flow cytometry, gene expression assays yield high information content from a clinically practical workflow. Previous studies of gene expression in purified immune cells have reported hundreds of genes showing enrichment in a single cell type, but the utility of these genes in tumor samples is unknown. We describe a novel statistical method for using co-expression patterns in large tumor gene expression datasets to validate previously reported candidate cell type marker genes, and we use this method to winnow previously published gene lists down to a subset of high confidence marker genes.\n\nMethodsWe use co-expression patterns in 9986 samples from The Cancer Genome Atlas (TCGA) to validate previously reported cell type marker genes. We compare immune cell scores derived from these genes to measurements from flow cytometry and immunohistochemistry. We characterize the reproducibility of our cell scores in replicate runs of RNA extracted from FFPE tumor tissue.\n\nResultsWe identify a list of 60 marker genes whose expression levels quantify 14 immune cell populations. Cell type scores calculated from these genes are concordant with flow cytometry and IHC readings, show high reproducibility in replicate RNA samples from FFPE tissue, and reveal an intricate picture of the immune infiltrate in TCGA. Most genes previously reported to be enriched in a single cell type have co-expression patterns inconsistent with cell type specificity.\n\nConclusionsDue to their concise gene set, computational simplicity and utility in tumor samples, these cell type gene signatures may be useful in future discovery research and clinical trials to understand how tumors and therapeutic intervention shape the immune response.

Bioinformatics

Development of a modular automated system for maintenance and differentiation of adherent human pluripotent stem cells.

Patient-specific induced pluripotent stem cells (iPSCs) have tremendous potential for development of regenerative medicine, disease modelling and drug discovery. However, the processes of reprogramming, maintenance and differentiation are labour intensive and subject to inter-technician variability. To address these issues, we established and optimised protocols to allow for the automated maintenance of reprogrammed somatic cells into iPSCs to enable the large-scale culture and passaging of human pluripotent stem cells (PSCs) using a customized TECAN Freedom EVO. Generation of iPSCs was performed offline by nucleofection followed by selection of TRA-1-60 positive cells using a Miltenyi MultiMACS24 Separator. Pluripotency markers were assessed to confirm pluripotency of the generated iPSCs. Passaging was performed using an enzyme-free dissociation method. Proof of concept of differentiation was obtained by differentiating human PSCs into cells of the retinal lineage. Key advantages of this automated approach are the ability to increase sample size, reduce variability during reprogramming or differentiation, and enable medium to high-throughput analysis of human PSCs and derivatives. These techniques will become increasingly important with the emergence of clinical trials using stem cells.

Bioengineering

How polio vaccination affects poliovirus transmission

The oral polio vaccine (OPV) contains live-attenuated polioviruses that induce immunity by causing low virulence infections in vaccine recipients and their close contacts. Widespread immunization with OPV has reduced the annual global burden of paralytic poliomyelitis by a factor of ten thousand or more and has driven wild poliovirus (WPV) to the brink of eradication. However, in instances that have so far been rare, OPV can paralyze vaccine recipients and generate vaccine-derived polio outbreaks. To complete polio eradication, OPV use should eventually cease, but doing so will leave a growing population fully susceptible to infection. If poliovirus is reintroduced after OPV cessation, under what conditions will OPV vaccination be required to interrupt transmission? Can conditions exist where OPV and WPV reintroduction present similar risks of transmission? To answer these questions, we built a multiscale mathematical model of infection and transmission calibrated to data from clinical trials and field epidemiology studies. At the within-host level, the model describes the effects of vaccination and waning immunity on shedding and oral susceptibility to infection. At the between-host level, the model emulates the interaction of shedding and oral susceptibility with sanitation and person-to-person contact patterns to determine the transmission rate in communities. Our results show that inactivated polio vaccine is sufficient to prevent outbreaks in low transmission rate settings, and that OPV can be reintroduced and withdrawn as needed in moderate transmission rate settings. However, in high transmission rate settings, the conditions that support vaccine-derived outbreaks have only been rare because population immunity has been high. Absent population immunity, the Sabin strains from OPV will be nearly as capable of causing outbreaks as WPV. If post-cessation outbreak responses are followed by new vaccine-derived outbreaks, strategies to restore population immunity will be required to ensure the stability of polio eradication.\n\nAuthor SummaryOral polio vaccine (OPV) has played an essential role in the elimination of wild poliovirus (WPV). OPV contains attenuated yet transmissible viruses that can spread from person-to-person. When OPV transmission persists uninterrupted, vaccine-derived outbreaks occur. After OPV is no longer used in routine immunization, as with the cessation of type 2 OPV in 2016, population immunity will decline. A key question is how this affects the potential of OPV viruses to spread within and across communities. To address this, we examined the roles of immunity, sanitation, and social contact in limiting OPV transmission. Our results derive from an extensive review and synthesis of vaccine trial data and community epidemiological studies. Shedding, oral susceptibility to infection, and transmission data are analyzed to systematically explain and model observations of WPV and OPV circulation. We show that in high transmission rate settings, falling population immunity after OPV cessation will lead to conditions where OPV and WPV are similarly capable of causing outbreaks, and that this conclusion is compatible with the known safety of OPV prior to global cessation. Novel strategies will be required to ensure the stability of polio eradication for all time.

epidemiology

A modification-specific peptide-based immunization approach using CRM197 carrier protein: Development of a selective vaccine against pyroglutamate Aβ peptides

Strategies aimed at reducing cerebral accumulation of the amyloid-{beta} (A{beta}) peptides have therapeutic potential in Alzheimers disease (AD). A{beta} immunization has proven to be effective at promoting A{beta} clearance in animal models but adverse effects have hampered its clinical evaluation. The first anti-A{beta} immunization clinical trial, which assessed a full-length A{beta}1-42 vaccine, increased the risk of encephalitis most likely because of autoimmune pro-inflammatory T helper 1 (Th1) response against all forms of A{beta}. Immunization against less abundant but potentially more pathologically relevant A{beta} products, such as N-terminally-truncated pyroglutamate-3 A{beta} (A{beta}pE3), could provide efficacy and improve tolerability in A{beta} immunotherapy. Here, we describe a selective vaccine against A{beta}pE3 using the diphtheria toxin mutant CRM197 as carrier protein for epitope presentation. CRM197 is currently used in licensed vaccines and has demonstrated excellent immunogenicity and safety in humans. In mice, our A{beta}pE3:CRM197 vaccine triggered the production of specific anti-A{beta}pE3 antibodies that did not cross-react with A{beta}1-42, non-cyclized A{beta}E3, or N-terminally-truncated pyroglutamate-11 A{beta} (A{beta}pE11). A{beta}pE3:CRM197 antiserum strongly labeled A{beta}pE3 in insoluble protein extracts and decorated cortical amyloid plaques in human AD brains. Anti-A{beta}pE3 antibodies were almost exclusively of the IgG1 isotype, suggesting an anti-inflammatory Th2 response bias to the A{beta}pE3:CRM197 vaccine. To the best of our knowledge, this study shows for the first time that CRM197 has potential as a safe and suitable vaccine carrier for active and selective immunization against specific protein sequence modifications or conformations, such as A{beta}pE3.

neuroscience

All or Nothing: the False Promise of Anonymity

In early 2016, the International Committee of Medical Journal Editors (ICMJE) proposed that responsible sharing of de-identified individual-level data be required for clinical trials published in their affiliated journals. There would be a delay in implementing this policy to allow for the necessary informed consents to work their way through ethical review. Meanwhile, some researchers and policy makers have conflated the notions of de-identification and anonymity. The former is a process that seeks to mitigate disclosure risk though careful application of rules and statistical analysis, while the latter is an absolute state. The consequence of confusing the process and the state is profound. Extensions to the ICMJE proposal based on the presumed anonymity of data include: sharing unconsented data; sharing data without managing access, as Open Data; and proposals to sell data. This essay aims to show that anonymity (the state) cannot be guaranteed by de-identification (the process), and so these extensions to the ICMJE proposal should be rejected on governance grounds, if no other. This is not as negative a position as it might seem, as other disciplines have been aware of these limitations and concomitant responsibilities for many years. The essay concludes with an example from social science of managed access strategies that could be adopted by the medical field.

scientific communication and education