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Summary: Transparent and accurate reporting in early phase dose-finding (EPDF) clinical trials is crucial for informing subsequent larger trials. The SPIRIT statement, designed for trial protocol content, does not adequately cover the distinctive features of EPDF trials. Recent findings indicate that the protocol contents in past EPDF trials frequently lacked completeness and clarity. To address this gap, the international consensus-driven SPIRIT-DEFINE checklist was developed through a robust methodological framework for guideline development, with the aim to improve completeness and clarity in EPDF trial protocols. The checklist builds on the SPIRIT statement, adding 17 new items and modifying 15 existing ones.The SPIRIT-DEFINE explanation and elaboration (E&E) document provides comprehensive information to enhance understanding and usability of the SPIRIT-DEFINE checklist when writing an EPDF trial protocol. Each new or modified checklist item is accompanied by a detailed description, its rationale with supportive evidence, and examples of good reporting curated from EPDF trial protocols covering a range of therapeutic areas and interventions. We recommend utilising this paper alongside the SPIRIT statement, and any relevant extensions, to enhance the development and review of EPDF trial protocols.By facilitating adoption of the SPIRIT-DEFINE statement for EPDF trials, this E&E document can promote enhancement of methodological rigour, patient safety, transparency, and facilitate the generation of high-quality, reproducible evidence that will strengthen the foundation of early phase research and ultimately improve patient outcomes. Funding: This work is a further extension of the SPIRIT-DEFINE study, which obtained no external funding. The principal investigator (CY) used internal staff resources, together with additional resources from external partners, to conduct this study. The SPIRIT-DEFINE study is a component of the DEFINE project, which also developed the MRC/NIHR funded CONSORT-DEFINE guidance. ICR-CTSU receives programmatic infrastructure funding from Cancer Research UK (C1491/A25351; CTUQQR-Dec22/100004), which has contributed to accelerating the advancement and successful completion of this work.

Summary: Early phase dose-finding (EPDF) trials are key in the development of novel therapies, with their findings directly informing subsequent clinical development phases and providing valuable insights for reverse translation. Comprehensive and transparent reporting of these studies is critical for their accurate and critical interpretation, which may improve and expedite therapeutic development. However, quality of reporting of design characteristics and results from EPDF trials is often variable and incomplete. The international consensus-based CONSORT-DEFINE (Consolidated Standards for Reporting Trials Dose-finding Extension) statement, an extension of the CONSORT statement for randomised trials, was developed to improve the reporting of EPDF trials. The CONSORT-DEFINE statement introduced 21 new items and modified 19 existing CONSORT items.This CONSORT-DEFINE Explanation and Elaboration (E&E) document provides important information to enhance understanding and facilitate the implementation of the CONSORT-DEFINE checklist. For each new or modified checklist item, we provide a detailed description and its rationale with supporting evidence, and present examples from EPDF trial reports published in peer-reviewed scientific journals. When reporting the results of EPDF trials, authors are encouraged to consult the CONSORT-DEFINE E&E document, together with the CONSORT and CONSORT-DEFINE statement papers, and adhere to their recommendations. Widespread adoption of the CONSORT-DEFINE statement is likely to enhance the reporting quality of EPDF trials, thus facilitating the peer review of such studies and their appraisal by researchers, regulators, ethics committee members, and funders. Funding: This work is a further extension of the CONSORT-DEFINE study, which was funded by the UK Medical Research Council (MRC)-National Institute for Health and Care Research (NIHR) Methodology Research Programme (MR/T044934/1). The Clinical Trials and Statistics Unit at The Institute of Cancer Research (ICR-CTSU) receives programmatic infrastructure funding from Cancer Research UK (C1491/A25351; CTUQQR-Dec 22/100 004), which has contributed to accelerating the advancement and successful completion of this work.

Introduction Early phase dose-finding (EPDF) studies are critical for the development of new treatments, directly influencing whether compounds or interventions can be investigated in further trials to confirm their safety and efficacy. There exists guidance for clinical trial protocols and reporting of completed trials in the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 and CONsolidated Standards Of Reporting Randomised Trials (CONSORT) 2010 statements. However, neither the original statements nor their extensions adequately cover the specific features of EPDF trials. The DEFINE (DosE-FIndiNg Extensions) study aims to enhance transparency, completeness, reproducibility and interpretation of EPDF trial protocols (SPIRIT-DEFINE) and their reports once completed (CONSORT-DEFINE), across all disease areas, building on the original SPIRIT 2013 and CONSORT 2010 statements.Methods and analysis A methodological review of published EPDF trials will be conducted to identify features and deficiencies in reporting and inform the initial generation of the candidate items. The early draft checklists will be enriched through a review of published and grey literature, real-world examples analysis, citation and reference searches and consultation with international experts, including regulators and journal editors. Development of CONSORT-DEFINE commenced in March 2021, followed by SPIRIT-DEFINE from January 2022. A modified Delphi process, involving worldwide, multidisciplinary and cross-sector key stakeholders, will be run to refine the checklists. An international consensus meeting in autumn 2022 will finalise the list of items to be included in both guidance extensions.Ethics and dissemination This project was approved by ICR’s Committee for Clinical Research. The Health Research Authority confirmed Research Ethics Approval is not required. The dissemination strategy aims to maximise guideline awareness and uptake, including but not limited to dissemination in stakeholder meetings, conferences, peer-reviewed publications and on the EQUATOR Network and DEFINE study websites.Registration details SPIRIT-DEFINE and CONSORT-DEFINE are registered with the EQUATOR Network.

High-throughput sequencing of 16S ribosomal RNA gene amplicons has facilitated understanding of complex microbial communities, but the inherent noise in PCR and DNA sequencing limits differentiation of closely related bacteria. Although many scientific questions can be addressed with broad taxonomic profiles, clinical, food safety, and some ecological applications require higher specificity. Here we introduce a novel sub-operational-taxonomic-unit (sOTU) approach, Deblur, that uses error profiles to obtain putative error-free sequences from Illumina MiSeq and HiSeq sequencing platforms. Deblur substantially reduces computational demands relative to similar sOTU methods and does so with similar or better sensitivity and specificity. Using simulations, mock mixtures, and real data sets, we detected closely related bacterial sequences with single nucleotide differences while removing false positives and maintaining stability in detection, suggesting that Deblur is limited only by read length and diversity within the amplicon sequences. Because Deblur operates on a per-sample level, it scales to modern data sets and meta-analyses. To highlight Deblur's ability to integrate data sets, we include an interactive exploration of its application to multiple distinct sequencing rounds of the American Gut Project. Deblur is open source under the Berkeley Software Distribution (BSD) license, easily installable, and downloadable from https://github.com/biocore/deblur. IMPORTANCE Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time.

IntroductionCognitive impairments are a common and significant issue for young people with a severe mental illness. Young people with schizophrenia, bipolar disorder and major depression all experience significant cognitive problems that impede their ability to return to work or study. These neurocognitive problems are frequently exacerbated by social cognitive deficits that interfere with their ability to integrate into the community and understand the social and emotional nuances about them. This study aimed to assess if the addition of a social cognitive remediation treatment to a neurocognitive remediation therapy improved functional outcome.MethodsFive youth mental health services were trained in both the Neuropsychological Educational Approach to Remediation (NEAR) and the Social Cognition and Interaction Training (SCIT) treatments. Participants were randomised between receiving either NEAR + SCIT or NEAR + treatment as usual (TAU) over a 20-week period, with all participants receiving the NEAR treatment first. Symptoms, neurocognition, social cognition and functioning were examined at baseline, end of treatment and at 3 months follow-up and compared between the two arms of the study. The primary outcome was function.ResultsThirty-nine participants were randomised to treatment (Schizophrenia spectrum = 28, Bipolar disorder = 7, Major Depression = 2). The trial was curtailed by Covid-related service restrictions. There was an overall significant improvement in function over time with a trend towards a greater improvement in the NEAR + SCIT arm. No changes in symptoms, neurocognitive or social cognitive measures were seen. While 74% completed treatment only 49% agreed to follow up at 3 months affecting our ability to interpret the findings. Attrition did not differ by arm.ConclusionsIn a pragmatic, service-based research project, treatment aimed at improving cognition enhanced functional outcome in young people with a range of severe mental illnesses. There was a trend towards improved function in young people who had a combined NEAR + SCIT approach.Clinical Trial RegistrationIdentifier: ACTRN12622000192785.

ABSTRACT High-throughput sequencing of 16S ribosomal RNA gene amplicons has facilitated understanding of complex microbial communities, but the inherent noise in PCR and DNA sequencing limits differentiation of closely related bacteria. Although many scientific questions can be addressed with broad taxonomic profiles, clinical, food safety, and some ecological applications require higher specificity. Here we introduce a novel sub-operational-taxonomic-unit (sOTU) approach, Deblur, that uses error profiles to obtain putative error-free sequences from Illumina MiSeq and HiSeq sequencing platforms. Deblur substantially reduces computational demands relative to similar sOTU methods and does so with similar or better sensitivity and specificity. Using simulations, mock mixtures, and real data sets, we detected closely related bacterial sequences with single nucleotide differences while removing false positives and maintaining stability in detection, suggesting that Deblur is limited only by read length and diversity within the amplicon sequences. Because Deblur operates on a per-sample level, it scales to modern data sets and meta-analyses. To highlight Deblur’s ability to integrate data sets, we include an interactive exploration of its application to multiple distinct sequencing rounds of the American Gut Project. Deblur is open source under the Berkeley Software Distribution (BSD) license, easily installable, and downloadable from https://github.com/biocore/deblur . IMPORTANCE Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time.

Schooling and the knowledge acquired at school have been considered both a cause of loss of indigenous knowledge (because it opens pathways to the non-indigenous world and worldviews) and a potential remedy to its demise (if educational curricula is aligned with indigenous realities by giving instruction in local languages and incorporating local knowledge in school content). We test the association between academic and local environmental knowledge using data from a society of forager-horticulturalists in the Bolivian Amazon who were exposed to a partially contextualized school curriculum. We found that although schooling and academic knowledge bear a negative association with local knowledge the magnitude is low, probably because schooling was partially contextualized. Contextualized learning might help avoid that the provision of universal education comes at the cost of humanity's cultural diversity. (Contains 5 tables.)