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The role of anti-WNT ZNRF3 is central to determining gonadal fate: XY mice lacking functional ZNRF3 exhibit a highly variable gonadal sex reversal phenotype in the fetal period, characterised by appearance of ovarian tissue. To investigate this sex reversal further, we used single-cell RNA-seq to examine the transcriptomes of XY Znrf3-deficient gonads during the mouse sex-determining period. Analyses of cell trajectories in mutant gonads reveal the failure of pre-supporting cells to commit to the Sertoli cell fate, XY granulosa cell development, unstable commitment in those cells that reach the Sertoli path and enhanced contribution to a supportinglike cell fate. By developing a machine learning-based score for transcriptomic similarity to Sertoli and granulosa, we show pervasive disruption to acquisition of testicular cell fate in the mutant supporting cell lineage, with large numbers of cells co-expressing pro-Sertoli and pro-granulosa markers. These data reveal that loss of Znrf3 results in transcriptomic and cellular heterogeneity, with shifts in cellular sex identity that undermine a simple binary model in which mutant supporting cell precursors achieve either Sertoli or granulosa cell differentiation. [ABSTRACT FROM AUTHOR]

The function of the majority of genes in the human and mouse genomes is unknown. Investigating and illuminating this dark genome is a major challenge for the biomedical sciences. The International Mouse Phenotyping Consortium (IMPC) is addressing this through the generation and broad-based phenotyping of a knockout (KO) mouse line for every protein-coding gene, producing a multidimensional data set that underlies a genome-wide annotation map from genes to phenotypes. Here, we develop a multivariate (MV) statistical approach and apply it to IMPC data comprising 148 phenotypes measured across 4,548 KO lines. There are 4,256 (1.4% of 302,997 observed data measurements) hits called by the univariate (UV) model analysing each phenotype separately, compared to 31,843 (10.5%) hits in the observed data results of the MV model, corresponding to an estimated 7.5-fold increase in power of the MV model relative to the UV model. One key property of the data set is its 55.0% rate of missingness, resulting from quality control filters and incomplete measurement of some KO lines. This raises the question of whether it is possible to infer perturbations at phenotype–gene pairs at which data are not available, i.e., to infer some in vivo effects using statistical analysis rather than experimentation. We demonstrate that, even at missing phenotypes, the MV model can detect perturbations with power comparable to the single-phenotype analysis, thereby filling in the complete gene–phenotype map with good sensitivity. A factor analysis of the MV model's fitted covariance structure identifies 20 clusters of phenotypes, with each cluster tending to be perturbed collectively. These factors cumulatively explain 75% of the KO-induced variation in the data and facilitate biological interpretation of perturbations. We also demonstrate that the MV approach strengthens the correspondence between IMPC phenotypes and existing gene annotation databases. Analysis of a subset of KO lines measured in replicate across multiple laboratories confirms that the MV model increases power with high replicability. The function of the majority of genes in the human and mouse genomes is unknown, and illuminating this "dark genome" is a major challenge for the biomedical sciences. This study shows that multi-dimensional phenotypes from single-gene knockout mouse lines can be analysed at a genome-wide scale both to increase power and infer missing phenotypes. [ABSTRACT FROM AUTHOR]

Advanced3Dimagingmodalities, such asmicro-computedtomography (micro-CT), have been incorporated into the high-throughput embryo pipeline of the International Mouse Phenotyping Consortium (IMPC). This project generates large volumes of raw data that cannot be immediately exploited without significant resources of personnel and expertise. Thus, rapid automated annotation is crucial to ensure that 3D imaging data can be integrated with other multi-dimensional phenotyping data. We present an automated computational mouse embryo phenotyping pipeline that harnesses the large amount of wild-type control data available in the IMPC embryo pipeline in order to address issues of low mutant sample number as well as incomplete penetrance and variable expressivity. We also investigate the effect of developmental substage on automated phenotyping results. Designed primarily for developmental biologists, our software performs image pre-processing, registration, statistical analysis and segmentation of embryo images.We also presenta novelanatomicalE14.5 embryo atlas average and, using it with LAMA, show that we can uncover known and novel dysmorphology from two IMPC knockout lines. [ABSTRACT FROM AUTHOR]

Reproducibility in the statistical analyses of data from high-throughput phenotyping screens requires a robust and reliable analysis foundation that allows modelling of different possible statistical scenarios. Regular challenges are scalability and extensibility of the analysis software. In this manuscript, we describe OpenStats, a freely available software package that addresses these challenges. We show the performance of the software in a high-throughput phenomic pipeline in the International Mouse Phenotyping Consortium (IMPC) and compare the agreement of the results with the most similar implementation in the literature. OpenStats has significant improvements in speed and scalability compared to existing software packages including a 13-fold improvement in computational time to the current production analysis pipeline in the IMPC. Reduced complexity also promotes FAIR data analysis by providing transparency and benefiting other groups in reproducing and re-usability of the statistical methods and results. OpenStats is freely available under a Creative Commons license at www.bioconductor.org/packages/OpenStats. [ABSTRACT FROM AUTHOR]

Background: Around 50 million people have dementia worldwide, with nearly 10 million new cases every year. Diagnosis is complex and often relies on expensive and invasive measures, with most patients accessing medical support when they already experience symptoms. Method: The Early Detection of Neurodegenerative diseases (EDoN) initiative, spearheaded by Alzheimer's Research UK, brings together over 60 experts from 49 universities, research projects, patient cohorts and technology providers to create machine learning models to detect the earliest stages of dementia‐causing diseases. EDoN has reviewed behavioural and physiological modalities with the strongest association with pre‐clinical disease. Result: Over 140 modalities were identified from the review and were shortlisted to create the version 1 digital toolkit. This first version includes Mezurio and Longevity smartphone apps, a Fitbit charge 4 activity tracker and Dreem 3 sleep headband. This Toolkit was further refined through patient and public involvement studies and collects 26 measures related to 7 aspects of behaviour and physiology (cognition, neural activity, physical activity, heart rate, fine motor movement, sleep, language and speech). The Toolkit is now being used to collect digital data in four international cohorts (Boston University Alzheimer's Disease Research Center ‐ BU ADRC; The predictors of COgnitive DECline in attenders of memory clinic using digital devices ‐ CODEC‐2; Western Australia Memory Study ‐ WAMS; Healthy Brain Aging ‐ HBA), alongside prospective and retrospective clinical data, to inform the development of machine learning models. Conclusion: EDoN will build models with digital markers, validating them against other biomarkers to predict dementia subtypes and individualised disease trajectories. Based on the outputs of the initial models, EDoN will go through a series of iterations of cohort engagement, modality and tool refinement, and data collection. Workstreams are underway to inform data security, privacy, ethics and open policy research, as well as considering the integration of the final EDoN Toolkit into healthcare systems globally. EDoN aims to deliver a cost‐effective, low burden and population‐wide method for early detection of dementia‐causing diseases that will benefit the public, patients, carers, researchers and clinicians, as well as the broader healthcare system and the delivery of new therapies. [ABSTRACT FROM AUTHOR]

Renal calcification (RCALC) resulting in nephrolithiasis and nephrocalcinosis, which affects ∼10% of adults by 70 years of age, involves environmental and genetic etiologies. Thus, nephrolithiasis and nephrocalcinosis occurs as an inherited disorder in ∼65% of patients, and may be associated with endocrine and metabolic disorders including: primary hyperparathyroidism, hypercalciuria, renal tubular acidosis, cystinuria, and hyperoxaluria. Investigations of families with nephrolithiasis and nephrocalcinosis have identified some causative genes, but further progress is limited as large families are unavailable for genetic studies. We therefore embarked on establishing mouse models for hereditary nephrolithiasis and nephrocalcinosis by performing abdominal X‐rays to identify renal opacities in N‐ethyl‐N‐nitrosourea (ENU)‐mutagenized mice. This identified a mouse with RCALC inherited as an autosomal dominant trait, designated RCALC type 2 (RCALC2). Genomewide mapping located the Rcalc2 locus to a ∼16‐Mbp region on chromosome 11D‐E2 and whole‐exome sequence analysis identified a heterozygous mutation in the DNA polymerase gamma‐2, accessory subunit (Polg2) resulting in a nonsense mutation, Tyr265Stop (Y265X), which co‐segregated with RCALC2. Kidneys of mutant mice (Polg2+/Y265X) had lower POLG2 mRNA and protein expression, compared to wild‐type littermates (Polg2+/+). The Polg2+/Y265X and Polg2+/+ mice had similar plasma concentrations of sodium, potassium, calcium, phosphate, chloride, urea, creatinine, glucose, and alkaline phosphatase activity; and similar urinary fractional excretion of calcium, phosphate, oxalate, and protein. Polg2 encodes the minor subunit of the mitochondrial DNA (mtDNA) polymerase and the mtDNA content in Polg2+/Y265X kidneys was reduced compared to Polg2+/+ mice, and cDNA expression profiling revealed differential expression of 26 genes involved in several biological processes including mitochondrial DNA function, apoptosis, and ubiquitination, the complement pathway, and inflammatory pathways. In addition, plasma of Polg2+/Y265X mice, compared to Polg2+/+ littermates had higher levels of reactive oxygen species. Thus, our studies have identified a mutant mouse model for inherited renal calcification associated with a Polg2 nonsense mutation. © 2018 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome. [ABSTRACT FROM AUTHOR]

Otitis media (OM), inflammation of the middle ear (ME), is a common cause of conductive hearing impairment. Despite the importance of the disease, the aetiology of chronic and recurrent forms of middle ear inflammatory disease remains poorly understood. Studies of the human population suggest that there is a significant genetic component predisposing to the development of chronic OM, although the underlying genes are largely unknown. Using N-ethyl-N-nitrosourea mutagenesis we identified a recessive mouse mutant, edison, that spontaneously develops a conductive hearing loss due to chronic OM. The causal mutation was identified as a missense change, L972P, in the Nischarin (NISCH) gene. edison mice develop a serous or granulocytic effusion, increasingly macrophage and neutrophil rich with age, along with a thickened, inflamed mucoperiosteum. We also identified a second hypomorphic allele, V33A, with only modest increases in auditory thresholds and reduced incidence of OM. NISCH interacts with several proteins, including ITGA5 that is thought to have a role in modulating VEGF-induced angiogenesis and vascularization. We identified a significant genetic interaction between Nisch and Itga5; mice heterozygous for Itga5-null and homozygous for edison mutations display a significantly increased penetrance and severity of chronic OM. In order to understand the pathological mechanisms underlying the OM phenotype, we studied interacting partners to NISCH along with downstream signalling molecules in the middle ear epithelia of edison mouse. Our analysis implicates PAK1 and RAC1, and downstream signalling in LIMK1 and NF-κB pathways in the development of chronic OM. [ABSTRACT FROM AUTHOR]

Phenotypes have gained increased notoriety in the clinical and biological domain owing to their application in numerous areas such as the discovery of disease genes and drug targets, phylogenetics and pharmacogenomics. Phenotypes, defined as observable characteristics of organisms, can be seen as one of the bridges that lead to a translation of experimental findings into clinical applications and thereby support 'bench to bedside' efforts. However, to build this translational bridge, a common and universal understanding of phenotypes is required that goes beyond domain-specific definitions. To achieve this ambitious goal, a digital revolution is ongoing that enables the encoding of data in computer-readable formats and the data storage in specialized repositories, ready for integration, enabling translational research. While phenome research is an ongoing endeavor, the true potential hidden in the currently available data still needs to be unlocked, offering exciting opportunities for the forthcoming years. Here, we provide insights into the state-of-the-art in digital phenotyping, by means of representing, acquiring and analyzing phenotype data. In addition, we provide visions of this field for future research work that could enable better applications of phenotype data. [ABSTRACT FROM AUTHOR]

Background: Nuclease-based technologies have been developed that enable targeting of specific DNA sequences directly in the zygote. These approaches provide an opportunity to modify the genomes of inbred mice, and allow the removal of strain-specific mutations that confound phenotypic assessment. One such mutation is the Cdh23ahl allele, present in several commonly used inbred mouse strains, which predisposes to age-related progressive hearing loss. Results: We have used targeted CRISPR/Cas9-mediated homology directed repair (HDR) to correct the Cdh23ahl allele directly in C57BL/6NTac zygotes. Employing offset-nicking Cas9 (D10A) nickase with paired RNA guides and a single-stranded oligonucleotide donor template we show that allele repair was successfully achieved. To investigate potential Cas9-mediated 'off-target' mutations in our corrected mouse, we undertook whole-genome sequencing and assessed the 'off-target' sites predicted for the guide RNAs (≤4 nucleotide mis-matches). No induced sequence changes were identified at any of these sites. Correction of the progressive hearing loss phenotype was demonstrated using auditory-evoked brainstem response testing of mice at 24 and 36 weeks of age, and rescue of the progressive loss of sensory hair cell stereocilia bundles was confirmed using scanning electron microscopy of dissected cochleae from 36-week-old mice. Conclusions: CRISPR/Cas9-mediated HDR has been successfully utilised to efficiently correct the Cdh23ahl allele in C57BL/6NTac mice, and rescue the associated auditory phenotype. The corrected mice described in this report will allow age-related auditory phenotyping studies to be undertaken using C57BL/6NTac-derived models, such as those generated by the International Mouse Phenotyping Consortium (IMPC) programme. [ABSTRACT FROM AUTHOR]

Mutagenesis-based screens in mice are a powerful discovery platform to identify novel genes or gene functions associated with disease phenotypes. An N-ethyl- N-nitrosourea (ENU) mutagenesis screen induces single nucleotide variants randomly in the mouse genome. Subsequent phenotyping of mutant and wildtype mice enables the identification of mutated pathways resulting in phenotypes associated with a particular ENU lesion. This unbiased approach to gene discovery conducts the phenotyping with no prior knowledge of the functional mutations. Before the advent of affordable next generation sequencing (NGS), ENU variant identification was a limiting step in gene characterization, akin to 'finding a needle in a haystack'. The emergence of a reliable reference genome alongside advances in NGS has propelled ENU mutation discovery from an arduous, time-consuming exercise to an effective and rapid form of mutation discovery. This has permitted large mouse facilities worldwide to use ENU for novel mutation discovery in a high-throughput manner, helping to accelerate basic science at the mechanistic level. Here, we describe three different strategies used to identify ENU variants from NGS data and some of the subsequent steps for mutation characterisation. [ABSTRACT FROM AUTHOR]

Streptococcus pneumoniae is an important human pathogen responsible for high mortality and morbidity worldwide. The susceptibility to pneumococcal infections is controlled by as yet unknown genetic factors. To elucidate these factors could help to develop new medical treatments and tools to identify those most at risk. In recent years genome wide association studies (GWAS) in mice and humans have proved successful in identification of causal genes involved in many complex diseases for example diabetes, systemic lupus or cholesterol metabolism. In this study a GWAS approach was used to map genetic loci associated with susceptibility to pneumococcal infection in 26 inbred mouse strains. As a result four candidate QTLs were identified on chromosomes 7, 13, 18 and 19. Interestingly, the QTL on chromosome 7 was located within S. pneumoniae resistance QTL (Spir1) identified previously in a linkage study of BALB/cOlaHsd and CBA/CaOlaHsd F2 intercrosses. We showed that only a limited number of genes encoded within the QTLs carried phenotype-associated polymorphisms (22 genes out of several hundred located within the QTLs). These candidate genes are known to regulate TGFβ signalling, smooth muscle and immune cells functions. Interestingly, our pulmonary histopathology and gene expression data demonstrated, lung vasculature plays an important role in resistance to pneumococcal infection. Therefore we concluded that the cumulative effect of these candidate genes on vasculature and immune cells functions as contributory factors in the observed differences in susceptibility to pneumococcal infection. We also propose that TGFβ-mediated regulation of fibroblast differentiation plays an important role in development of invasive pneumococcal disease. Gene expression data submitted to the NCBI Gene Expression Omnibus Accession No: GSE49533 SNP data submitted to NCBI dbSNP Short Genetic Variation http://www.ncbi.nlm.nih.gov/projects/SNP/snp_viewTable.cgi?handle=MUSPNEUMONIA. [ABSTRACT FROM AUTHOR]

Forward genetics screens with N-ethyl-N-nitrosourea (ENU) provide a powerful way to illuminate gene function and generate mouse models of human disease; however, the identification of causative mutations remains a limiting step. Current strategies depend on conventional mapping, so the propagation of affected mice requires non-lethal screens; accurate tracking of phenotypes through pedigrees is complex and uncertain; out-crossing can introduce unexpected modifiers; and Sanger sequencing of candidate genes is inefficient. Here we show how these problems can be efficiently overcome using whole-genome sequencing (WGS) to detect the ENU mutations and then identify regions that are identical by descent (IBD) in multiple affected mice. In this strategy, we use a modification of the Lander-Green algorithm to isolate causative recessive and dominant mutations, even at low coverage, on a pure strain background. Analysis of the IBD regions also allows us to calculate the ENU mutation rate (1.54 mutations per Mb) and to model future strategies for genetic screens in mice. The introduction of this approach will accelerate the discovery of causal variants, permit broader and more informative lethal screens to be used, reduce animal costs, and herald a new era for ENU mutagenesis. [ABSTRACT FROM AUTHOR]

Phenotype-driven approaches in mice are powerful strategies for the discovery of genes and gene functions and for unravelling complex biological mechanisms. Traditional methods for mutation discovery are reliable and robust, but they can also be laborious and time consuming. Recently, high-throughput sequencing (HTS) technologies have revolutionised the process of forward genetics in mice by paving the way to rapid mutation discovery. However, successful application of HTS for mutation discovery relies heavily on the sequencing approach employed and strategies for data analysis. Here we review current HTS applications and resources for mutation discovery and provide an overview of the practical considerations for HTS implementation and data analysis. [ABSTRACT FROM AUTHOR]

The International Mouse Phenotyping Consortium (IMPC) () will reveal the pleiotropic functions of every gene in the mouse genome and uncover the wider role of genetic loci within diverse biological systems. Comprehensive informatics solutions are vital to ensuring that this vast array of data is captured in a standardised manner and made accessible to the scientific community for interrogation and analysis. Here we review the existing EuroPhenome and WTSI phenotype informatics systems and the IKMC portal, and present plans for extending these systems and lessons learned to the development of a robust IMPC informatics infrastructure. [ABSTRACT FROM AUTHOR]

Two large-scale phenotyping efforts, the European Mouse Disease Clinic (EUMODIC) and the Wellcome Trust Sanger Institute Mouse Genetics Project (SANGER-MGP), started during the late 2000s with the aim to deliver a comprehensive assessment of phenotypes or to screen for robust indicators of diseases in mouse mutants. They both took advantage of available mouse mutant lines but predominantly of the embryonic stem (ES) cells resources derived from the European Conditional Mouse Mutagenesis programme (EUCOMM) and the Knockout Mouse Project (KOMP) to produce and study 799 mouse models that were systematically analysed with a comprehensive set of physiological and behavioural paradigms. They captured more than 400 variables and an additional panel of metadata describing the conditions of the tests. All the data are now available through EuroPhenome database () and the WTSI mouse portal (), and the corresponding mouse lines are available through the European Mouse Mutant Archive (EMMA), the International Knockout Mouse Consortium (IKMC), or the Knockout Mouse Project (KOMP) Repository. Overall conclusions from both studies converged, with at least one phenotype scored in at least 80 % of the mutant lines. In addition, 57 % of the lines were viable, 13 % subviable, 30 % embryonic lethal, and 7 % displayed fertility impairments. These efforts provide an important underpinning for a future global programme that will undertake the complete functional annotation of the mammalian genome in the mouse model. [ABSTRACT FROM AUTHOR]

Motivation: To evaluate how well current anatomical ontologies fit the way real-world users apply anatomy terms in their data annotations. Methods: Annotations from three diverse multi-species public-domain datasets provided a set of use cases for matching anatomical terms in two major anatomical ontologies (the Foundational Model of Anatomy and Uberon), using two lexical-matching applications (Zooma and Ontology Mapper). Results: Approximately 1500 terms were identified; Uberon/Zooma mappings provided 286 matches, compared to the control and Ontology Mapper returned 319 matches. For the Foundational Model of Anatomy, Zooma returned 312 matches, and Ontology Mapper returned 397. Conclusions: Our results indicate that for our datasets the anatomical entities or concepts are embedded in user-generated complex terms, and while lexical mapping works, anatomy ontologies do not provide the majority of terms users supply when annotating data. Provision of searchable cross-products for compositional terms is a key requirement for using ontologies. [ABSTRACT FROM AUTHOR]

Background: Large-scale international projects are underway to generate collections of knockout mouse mutants and subsequently to perform high throughput phenotype assessments, raising new challenges for computational researchers due to the complexity and scale of the phenotype data. Phenotypes can be described using ontologies in two differing methodologies. Traditionally an individual phenotypic character has either been defined using a single compound term, originating from a species-specific dedicated phenotype ontology, or alternatively by a combinatorial annotation, using concepts from a range of disparate ontologies, to define a phenotypic character as an entity with an associated quality (EQ). Both methods have their merits, which include the dedicated approach allowing use of community standard terminology, and the combinatorial approach facilitating cross-species phenotypic statement comparisons. Previously databases have favoured one approach over another. The EUMODIC project will generate large amounts of mouse phenotype data, generated as a result of the execution of a set of Standard Operating Procedures (SOPs) and will implement both ontological approaches to capture the phenotype data generated. Results: For all SOPs a four-tier annotation is made: a high-level description of the SOP, to broadly define the type of data generated by the SOP; individual parameter annotation using the EQ model; annotation of the qualitative data generated for each mouse; and the annotation of mutant lines after statistical analysis. The qualitative assessments of phenodeviance are made at the point of data entry, using child PATO qualities to the parameter quality. To facilitate data querying by scientists more familiar with single compound terms to describe phenotypes, the mappings between the Mammalian Phenotype (MP) ontology and the EQ PATO model are exploited to allow querying via MP terms. Conclusion: Well-annotated and comparable phenotype databases can be achieved through the use of ontologically derived comparable phenotypic statements and have been implemented here by means of OBO compatible EQ annotations. The implementation we describe also sees scientists working seamlessly with ontologies through the assessment of qualitative phenotypes in terms of PATO qualities and the ability to query the database using community-accepted compound MP terms. This work represents the first time the combinatorial and single-dedicated approaches have both been implemented to annotate a phenotypic dataset. [ABSTRACT FROM AUTHOR]

An essential aspect to understanding the functional significance of individual genes in the mouse genome is an understanding of the phenotypic consequences of gene mutations. A wide variety of online sites exist that provide different types of phenotypic information on the laboratory mouse. In this review, we describe the major resources that are currently available and discuss some of the bioinformatics requirements that will be necessary to make more seamless searching, comparison and analysis of these various data types possible. [ABSTRACT FROM AUTHOR]

Del(13)Svea36H (Del36H) is a deletion of ∼20% of mouse chromosome 13 showing conserved synteny with human chromosome 6p22.1-6p22.3/6p25. The human region is lost in some deletion syndromes and is the site of several disease loci. Heterozygous De136H mice show numerous phenotypes and may model aspects of human genetic disease. We describe 12.7 Mb of finished, annotated sequence from Del36H. Del36H has a higher gene density than the draft mouse genome, reflecting high local densities of three gene families (vomeronasal receptors, serpins, and prolactins) which are greatly expanded relative to human. Transposable elements are concentrated near these gene families. We therefore suggest that their neighborhoods are gene factories, regions of frequent recombination in which gene duplication is more frequent. The gene families show different proportions of pseudogenes, likely reflecting different strengths of purifying selection and/or gene conversion. They are also associated with relatively low simple sequence concentrations, which vary across the region with a periodicity of ∼5 Mb. Del36H contains numerous evolutionarily conserved regions (ECRs). Many lie in noncoding regions, are detectable in species as distant as Ciona intestinalis, and therefore are candidate regulatory sequences. This analysis will facilitate functional genomic analysis of De136H and provides insights into mouse genome evolution. [ABSTRACT FROM AUTHOR]