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BMJ Open Science 2021Preclinical research is a vital step in the drug discovery pipeline and more generally in helping to better understand human disease aetiology and its management....
Preclinical research is a vital step in the drug discovery pipeline and more generally in helping to better understand human disease aetiology and its management. Systematic reviews (SRs) can be powerful in summarising and appraising this evidence concerning a specific research question, to highlight areas of improvements, areas for further research and areas where evidence may be sufficient to take forward to other research domains, for instance clinical trial. Guidance and tools for preclinical research synthesis remain limited despite their clear utility. We aimed to create an online end-to-end platform primarily for conducting SRs of preclinical studies, that was flexible enough to support a wide variety of experimental designs, was adaptable to different research questions, would allow users to adopt emerging automated tools and support them during their review process using best practice. In this article, we introduce the Systematic Review Facility (https://syrf.org.uk), which was launched in 2016 and designed to support primarily preclinical SRs from small independent projects to large, crowdsourced projects. We discuss the architecture of the app and its features, including the opportunity to collaborate easily, to efficiently manage projects, to screen and annotate studies for important features (metadata), to extract outcome data into a secure database, and tailor these steps to each project. We introduce how we are working to leverage the use of automation tools and allow the integration of these services to accelerate and automate steps in the systematic review workflow.
PubMed: 35047698
DOI: 10.1136/bmjos-2020-100103 -
Journal of Medical Internet Research Jan 2022Metadata are created to describe the corresponding data in a detailed and unambiguous way and is used for various applications in different research areas, for example,... (Review)
Review
BACKGROUND
Metadata are created to describe the corresponding data in a detailed and unambiguous way and is used for various applications in different research areas, for example, data identification and classification. However, a clear definition of metadata is crucial for further use. Unfortunately, extensive experience with the processing and management of metadata has shown that the term "metadata" and its use is not always unambiguous.
OBJECTIVE
This study aimed to understand the definition of metadata and the challenges resulting from metadata reuse.
METHODS
A systematic literature search was performed in this study following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for reporting on systematic reviews. Five research questions were identified to streamline the review process, addressing metadata characteristics, metadata standards, use cases, and problems encountered. This review was preceded by a harmonization process to achieve a general understanding of the terms used.
RESULTS
The harmonization process resulted in a clear set of definitions for metadata processing focusing on data integration. The following literature review was conducted by 10 reviewers with different backgrounds and using the harmonized definitions. This study included 81 peer-reviewed papers from the last decade after applying various filtering steps to identify the most relevant papers. The 5 research questions could be answered, resulting in a broad overview of the standards, use cases, problems, and corresponding solutions for the application of metadata in different research areas.
CONCLUSIONS
Metadata can be a powerful tool for identifying, describing, and processing information, but its meaningful creation is costly and challenging. This review process uncovered many standards, use cases, problems, and solutions for dealing with metadata. The presented harmonized definitions and the new schema have the potential to improve the classification and generation of metadata by creating a shared understanding of metadata and its context.
Topics: Humans; Metadata; Publications; Reference Standards
PubMed: 35014967
DOI: 10.2196/25440 -
MBio Dec 2021High-throughput 16S rRNA sequencing has allowed the characterization of helminth-uninfected (HU) and helminth-infected (HI) gut microbiomes, revealing distinct profiles.... (Meta-Analysis)
Meta-Analysis
High-throughput 16S rRNA sequencing has allowed the characterization of helminth-uninfected (HU) and helminth-infected (HI) gut microbiomes, revealing distinct profiles. However, there have been no qualitative or quantitative syntheses of these studies, which show marked variation in participant age, diet, pathogen of interest, and study location. A predefined minimally biased search strategy identified 23 studies in humans. For each of these studies, we qualitatively addressed the effects of helminth infection on within-individual (alpha) and between-individual (beta) fecal microbiome diversity, infection-associated microbial taxa, the effect of helminth clearance on microbiome composition, microbiome composition as a predictor of infection status or treatment outcome, and treatment-specific effects on the fecal microbiome. Concomitantly, we performed a meta-analysis on a subset of 7 of these studies containing raw, paired-end 16S reads and individual-level metadata, comprising 424 pretreatment or untreated HI individuals and 497 HU controls. After reducing the batch effect and adjusting for age, our data demonstrated that intestinal helminth parasites can alter the host gut microbiome by increasing alpha diversity and promoting taxonomic reassortment and gradient collapse. Most strongly influencing the microbiome composition were the helminths found in the large intestine, Enterobius vermicularis and Trichuris trichiura, suggesting that this influence appears to be specific to soil-transmitted helminths (STH) species and host anatomical niche. In summary, using a large and diverse sample set captured in the meta-analysis, we were able to evaluate the influence of individual helminth species as well as species-species interactions, each of which explained a significant portion of the variation in the microbiome. The gut microbiome has established importance in regulating many aspects of human health, including nutrition and immunity. While many internal and environmental factors are known to influence the microbiome, less is known about the effects of intestinal helminth parasites (worms), which together affect one-sixth of the world's population. Through a comprehensive qualitative systematic review and quantitative meta-analysis of existing literature, we provide strong evidence that helminth infection dynamically shifts the intestinal microbiome structure. Moreover, we demonstrated that such influence seems to be specific to helminth species and host anatomical niche. Our findings suggest that the gut microbiome may underlie some of the pathology associated with intestinal worm infection and support future work to understand the precise nature of the helminth-microbiome relationship.
Topics: Adolescent; Adult; Aged; Animals; Bacteria; Child; Child, Preschool; Dysbiosis; Feces; Female; Gastrointestinal Microbiome; Helminthiasis; Helminths; Humans; Infant; Male; Middle Aged; Phylogeny; Young Adult
PubMed: 34933444
DOI: 10.1128/mBio.02890-21 -
Cardiology 2022Transparent and robust real-world evidence sources are increasingly important for global health, including cardiovascular (CV) diseases. We aimed to identify global...
BACKGROUND
Transparent and robust real-world evidence sources are increasingly important for global health, including cardiovascular (CV) diseases. We aimed to identify global real-world data (RWD) sources for heart failure (HF), acute coronary syndrome (ACS), and atrial fibrillation (AF).
METHODS
We conducted a systematic review of publications with RWD pertaining to HF, ACS, and AF (2010-2018), generating a list of unique data sources. Metadata were extracted based on the source type (e.g., electronic health records, genomics, and clinical data), study design, population size, clinical characteristics, follow-up duration, outcomes, and assessment of data availability for future studies and linkage.
RESULTS
Overall, 11,889 publications were retrieved for HF, 10,729 for ACS, and 6,262 for AF. From these, 322 (HF), 287 (ACS), and 220 (AF) data sources were selected for detailed review. The majority of data sources had near complete data on demographic variables (HF: 94%, ACS: 99%, and AF: 100%) and considerable data on comorbidities (HF: 77%, ACS: 93%, and AF: 97%). The least reported data categories were drug codes (HF, ACS, and AF: 10%) and caregiver involvement (HF: 6%, ACS: 1%, and AF: 1%). Only a minority of data sources provided information on access to data for other researchers (11%) or whether data could be linked to other data sources to maximize clinical impact (20%). The list and metadata for the RWD sources are publicly available at www.escardio.org/bigdata.
CONCLUSIONS
This review has created a comprehensive resource of CV data sources, providing new avenues to improve future real-world research and to achieve better patient outcomes.
Topics: Acute Coronary Syndrome; Atrial Fibrillation; Comorbidity; Heart Failure; Humans; Information Storage and Retrieval
PubMed: 34781301
DOI: 10.1159/000520674 -
The Lancet. Digital Health Jan 2022Publicly available skin image datasets are increasingly used to develop machine learning algorithms for skin cancer diagnosis. However, the total number of datasets and...
Publicly available skin image datasets are increasingly used to develop machine learning algorithms for skin cancer diagnosis. However, the total number of datasets and their respective content is currently unclear. This systematic review aimed to identify and evaluate all publicly available skin image datasets used for skin cancer diagnosis by exploring their characteristics, data access requirements, and associated image metadata. A combined MEDLINE, Google, and Google Dataset search identified 21 open access datasets containing 106 950 skin lesion images, 17 open access atlases, eight regulated access datasets, and three regulated access atlases. Images and accompanying data from open access datasets were evaluated by two independent reviewers. Among the 14 datasets that reported country of origin, most (11 [79%]) originated from Europe, North America, and Oceania exclusively. Most datasets (19 [91%]) contained dermoscopic images or macroscopic photographs only. Clinical information was available regarding age for 81 662 images (76·4%), sex for 82 848 (77·5%), and body site for 79 561 (74·4%). Subject ethnicity data were available for 1415 images (1·3%), and Fitzpatrick skin type data for 2236 (2·1%). There was limited and variable reporting of characteristics and metadata among datasets, with substantial under-representation of darker skin types. This is the first systematic review to characterise publicly available skin image datasets, highlighting limited applicability to real-life clinical settings and restricted population representation, precluding generalisability. Quality standards for characteristics and metadata reporting for skin image datasets are needed.
Topics: Datasets as Topic; Dermoscopy; Humans; Machine Learning; Skin Neoplasms
PubMed: 34772649
DOI: 10.1016/S2589-7500(21)00252-1 -
Microbial Cell Factories Oct 2021Recombinant enzyme expression in Escherichia coli is one of the most popular methods to produce bulk concentrations of protein product. However, this method is often...
Recombinant enzyme expression in Escherichia coli is one of the most popular methods to produce bulk concentrations of protein product. However, this method is often limited by the inadvertent formation of inclusion bodies. Our analysis systematically reviews literature from 2010 to 2021 and details the methods and strategies researchers have utilized for expression of difficult to express (DtE), industrially relevant recombinant enzymes in E. coli expression strains. Our review identifies an absence of a coherent strategy with disparate practices being used to promote solubility. We discuss the potential to approach recombinant expression systematically, with the aid of modern bioinformatics, modelling, and 'omics' based systems-level analysis techniques to provide a structured, holistic approach. Our analysis also identifies potential gaps in the methods used to report metadata in publications and the impact on the reproducibility and growth of the research in this field.
Topics: Biotechnology; Escherichia coli; Gene Expression; Inclusion Bodies; Industrial Microbiology; Recombinant Proteins; Research Design; Solubility
PubMed: 34717620
DOI: 10.1186/s12934-021-01698-w -
Virulence Dec 2021is an emerging zoonotic pathogen. Over 100 putative virulence factors have been described, but it is unclear to what extent these virulence factors could contribute to... (Meta-Analysis)
Meta-Analysis
is an emerging zoonotic pathogen. Over 100 putative virulence factors have been described, but it is unclear to what extent these virulence factors could contribute to zoonotic potential of . We identified all virulence factors studied in experimental models of human origin in a systematic review and assessed their contribution to zoonotic potential in a subsequent genomic meta-analysis. PubMed and Scopus were searched for English-language articles that studied virulence published until 31 March 2021. Articles that analyzed a virulence factor by knockout mutation, purified protein, and/or recombinant protein in a model of human origin, were included. Data on virulence factor, strain characteristics, used human models and experimental outcomes were extracted. All publicly available genomes with available metadata on host, disease status and country of origin, were included in a genomic meta-analysis. We calculated the ratio of the prevalence of each virulence factor in human and pig isolates. We included 130 articles and 1703 genomes in the analysis. We identified 53 putative virulence factors that were encoded by genes which are part of the core genome and 26 factors that were at least twice as prevalent in human isolates as in pig isolates. Hhly3 and NisK/R were particularly enriched in human isolates, after stratification by genetic lineage and country of isolation. This systematic review and genomic meta-analysis have identified virulence factors that are likely to contribute to the zoonotic potential of .
Topics: Animals; Genomics; Streptococcal Infections; Streptococcus suis; Swine; Swine Diseases; Virulence; Virulence Factors
PubMed: 34666617
DOI: 10.1080/21505594.2021.1985760 -
Scandinavian Journal of Surgery : SJS :... 2022Patients presenting with synchronous colorectal liver metastases are increasingly being considered for a curative treatment, and the liver-first approach is gaining... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Patients presenting with synchronous colorectal liver metastases are increasingly being considered for a curative treatment, and the liver-first approach is gaining popularity in this context. However, little is known about the completion rates of the liver-first approach and its effects on survival.
METHODS
A systematic review and meta-analysis of liver-first strategy for colorectal liver metastasis. The primary outcome was an assessment of the completion rates of the liver-first approach. Secondary outcomes included overall survival, causes of non-completion, and clinicopathologic data.
RESULTS
Seventeen articles were amenable for inclusion and the total study population was 1041. The median completion rate for the total population was 80% (range 20-100). The median overall survival for the completion and non-completion groups was 45 (range 12-69) months and 13 (range 10.5-25) months, respectively. Metadata showed a significant survival benefit for the completion group, with a univariate hazard ratio of 12.0 (95% confidence interval, range 5.7-24.4). The major cause of non-completion (76%) was liver disease progression before resection of the primary tumor. Pearson tests showed significant negative correlation between median number of lesions and median size of the largest metastasis and completion rate.
CONCLUSIONS
The liver-first approach offers a complete resection to most patients enrolled, with an overall survival benefit when completion can be assured. One-fifth fails to return to intended oncologic therapy and the major cause is interim metastatic progression, most often in the liver. Risk of non-completion is related to a higher number of lesions and large metastases. The majority of studies stem from primary rectal cancers, which may influence on the return to intended oncologic therapy as well. 170459.
Topics: Abdomen; Colorectal Neoplasms; Hepatectomy; Humans; Liver Neoplasms; Retrospective Studies; Treatment Outcome
PubMed: 34605325
DOI: 10.1177/14574969211030131 -
Archives of Orthopaedic and Trauma... Nov 2022In this review paper, graft failure rates of different graft types (hamstring tendon autografts, bone-patellar tendon-bone autografts, quadriceps tendon autografts and... (Review)
Review
INTRODUCTION
In this review paper, graft failure rates of different graft types (hamstring tendon autografts, bone-patellar tendon-bone autografts, quadriceps tendon autografts and diverse allografts) that are used for surgical reconstruction of the anterior cruciate ligament are compared and statistically analysed.
METHODS
Literature search was conducted in PubMed according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) criteria. A total of 194 studies, which reported graft failure rates of at least one of the anterior cruciate ligament reconstruction methods mentioned above, were included in this systematic review. To be able to compare studies with different follow-up periods, a yearly graft failure rate for each reconstruction group was calculated and then investigated for significant differences by using the Kruskal-Wallis test.
RESULTS
Overall, a total of 152,548 patients treated with an anterior cruciate ligament reconstruction were included in the calculations. Comparison of graft types showed that hamstring tendon autografts had a yearly graft failure rate of 1.70%, whereas the bone-patellar tendon-bone autograft group had 1.16%, the quadriceps tendon autograft group 0.72%, and the allografts 1.76%.
CONCLUSION
The findings of this meta-data study indicate that reconstructing the anterior cruciate ligament using quadriceps tendon autografts, hamstring tendon autografts, patellar tendon autografts or allografts does not show significant differences in terms of graft failure rates.
Topics: Anterior Cruciate Ligament; Anterior Cruciate Ligament Injuries; Anterior Cruciate Ligament Reconstruction; Autografts; Bone-Patellar Tendon-Bone Grafting; Hamstring Tendons; Humans; Transplantation, Autologous
PubMed: 34536121
DOI: 10.1007/s00402-021-04147-w -
European Journal of Cancer (Oxford,... Oct 2021Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the...
BACKGROUND
Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinicopathological practice.
OBJECTIVE
The objective of the study was to systematically analyse the current state of research on reader studies involving melanoma and to assess their potential clinical relevance by evaluating three main aspects: test set characteristics (holdout/out-of-distribution data set, composition), test setting (experimental/clinical, inclusion of metadata) and representativeness of participating clinicians.
METHODS
PubMed, Medline and ScienceDirect were screened for peer-reviewed studies published between 2017 and 2021 and dealing with AI-based skin cancer classification involving melanoma. The search terms skin cancer classification, deep learning, convolutional neural network (CNN), melanoma (detection), digital biomarkers, histopathology and whole slide imaging were combined. Based on the search results, only studies that considered direct comparison of AI results with clinicians and had a diagnostic classification as their main objective were included.
RESULTS
A total of 19 reader studies fulfilled the inclusion criteria. Of these, 11 CNN-based approaches addressed the classification of dermoscopic images; 6 concentrated on the classification of clinical images, whereas 2 dermatopathological studies utilised digitised histopathological whole slide images.
CONCLUSIONS
All 19 included studies demonstrated superior or at least equivalent performance of CNN-based classifiers compared with clinicians. However, almost all studies were conducted in highly artificial settings based exclusively on single images of the suspicious lesions. Moreover, test sets mainly consisted of holdout images and did not represent the full range of patient populations and melanoma subtypes encountered in clinical practice.
Topics: Automation; Biopsy; Clinical Competence; Deep Learning; Dermatologists; Dermoscopy; Diagnosis, Computer-Assisted; Humans; Image Interpretation, Computer-Assisted; Melanoma; Microscopy; Neural Networks, Computer; Pathologists; Predictive Value of Tests; Reproducibility of Results; Skin Neoplasms
PubMed: 34509059
DOI: 10.1016/j.ejca.2021.06.049