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Article ; Online: Wearable and Non-Invasive Sensors for Rock Climbing Applications: Science-Based Training and Performance Optimization.

Breen, Miyuki / Reed, Taylor / Nishitani, Yoshiko / Jones, Matthew / Breen, Hannah M / Breen, Michael S

2023 Volume 23, Issue 11

Abstract: Rock climbing has evolved from a method for alpine mountaineering into a popular recreational activity and competitive sport. Advances in safety equipment and the rapid growth of indoor climbing facilities has enabled climbers to focus on the physical ... ...

Abstract	Rock climbing has evolved from a method for alpine mountaineering into a popular recreational activity and competitive sport. Advances in safety equipment and the rapid growth of indoor climbing facilities has enabled climbers to focus on the physical and technical movements needed to elevate performance. Through improved training methods, climbers can now achieve ascents of extreme difficulty. A critical aspect to further improve performance is the ability to continuously measure body movement and physiologic responses while ascending the climbing wall. However, traditional measurement devices (e.g., dynamometer) limit data collection during climbing. Advances in wearable and non-invasive sensor technologies have enabled new applications for climbing. This paper presents an overview and critical analysis of the scientific literature on sensors used during climbing. We focus on the several highlighted sensors with the ability to provide continuous measurements during climbing. These selected sensors consist of five main types (body movement, respiration, heart activity, eye gazing, skeletal muscle characterization) that demonstrate their capabilities and potential climbing applications. This review will facilitate the selection of these types of sensors in support of climbing training and strategies.
MeSH term(s)	Sports ; Mountaineering/physiology ; Muscle, Skeletal/physiology ; Data Collection ; Wearable Electronic Devices
Language	English
Publishing date	2023-05-25
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23115080
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Article ; Online: Integrating Wearable Sensors and Video to Determine Microlocation-Specific Physiologic and Motion Biometrics-Method Development for Competitive Climbing.

Breen, Miyuki / Reed, Taylor / Breen, Hannah M / Osborne, Charles T / Breen, Michael S

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 16

Abstract: Competitive indoor climbing has increased in popularity at the youth, collegiate, and Olympic levels. A critical aspect for improving performance is characterizing the physiologic response to different climbing strategies (e.g., work/rest patterns, ... ...

Abstract	Competitive indoor climbing has increased in popularity at the youth, collegiate, and Olympic levels. A critical aspect for improving performance is characterizing the physiologic response to different climbing strategies (e.g., work/rest patterns, pacing) and techniques (e.g., body position and movement) relative to location on climbing wall with spatially varying characteristics (e.g., wall inclinations, position of foot/hand holds). However, this response is not well understood due to the limited capabilities of climbing-specific measurement and assessment tools. In this study, we developed a novel method to examine time-resolved sensor-based measurements of multiple personal biometrics at different microlocations (finely spaced positions; MLs) along a climbing route. For the ML-specific biometric system (MLBS), we integrated continuous data from wearable biometric sensors and smartphone-based video during climbing, with a customized visualization and analysis system to determine three physiologic parameters (heart rate, breathing rate, ventilation rate) and one body movement parameter (hip acceleration), which are automatically time-matched to the corresponding video frame to determine ML-specific biometrics. Key features include: (1) biometric sensors that are seamlessly embedded in the fabric of an athletic compression shirt, and do not interfere with climbing performance, (2) climbing video, and (3) an interactive graphical user interface to rapidly visualize and analyze the time-matched biometrics and climbing video, determine timing sequence between the biometrics at key events, and calculate summary statistics. To demonstrate the capabilities of MLBS, we examined the relationship between changes in ML-specific climbing characteristics and changes in the physiologic parameters. Our study demonstrates the ability of MLBS to determine multiple time-resolved biometrics at different MLs, in support of developing and assessing different climbing strategies and training methods to help improve performance.
MeSH term(s)	Adolescent ; Biometry ; Humans ; Movement/physiology ; Posture ; Sports/physiology ; Wearable Electronic Devices
Language	English
Publishing date	2022-08-20
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22166271
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Article ; Online: Microenvironment Tracker (MicroTrac) model to estimate time-location of individuals for air pollution exposure assessments: model evaluation using smartphone data.

Breen, Michael S / Xu, Yadong / Christopher Frey, H / Breen, Miyuki / Isakov, Vlad

Journal of exposure science & environmental epidemiology

2022 Volume 33, Issue 3, Page(s) 407–415

Abstract: Background: A critical aspect of air pollution exposure assessments is determining the time spent in various microenvironments (ME), which can have substantially different pollutant concentrations. We previously developed and evaluated a ME ... ...

Abstract	Background: A critical aspect of air pollution exposure assessments is determining the time spent in various microenvironments (ME), which can have substantially different pollutant concentrations. We previously developed and evaluated a ME classification model, called Microenvironment Tracker (MicroTrac), to estimate time of day and duration spent in eight MEs (indoors and outdoors at home, work, school; inside vehicles; other locations) based on input data from global positioning system (GPS) loggers. Objective: In this study, we extended MicroTrac and evaluated the ability of using geolocation data from smartphones to determine the time spent in the MEs. Method: We performed a panel study, and the MicroTrac estimates based on data from smartphones and GPS loggers were compared to 37 days of diary data across five participants. Results: The MEs were correctly classified for 98.1% and 98.3% of the time spent by the participants using smartphones and GPS loggers, respectively. Significance: Our study demonstrates the extended capability of using ubiquitous smartphone data with MicroTrac to help reduce time-location uncertainty in air pollution exposure models for epidemiologic and exposure field studies.
MeSH term(s)	Humans ; Smartphone ; Air Pollution/analysis ; Air Pollutants/analysis ; Time ; Environmental Pollutants ; Environmental Exposure/analysis ; Environmental Monitoring/methods
Chemical Substances	Air Pollutants ; Environmental Pollutants
Language	English
Publishing date	2022-12-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	2218551-3
ISSN	1559-064X ; 1559-0631
ISSN (online)	1559-064X
ISSN	1559-0631
DOI	10.1038/s41370-022-00514-w
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Article: Transient peripheral blood transcriptomic response to ketamine treatment in children with ADNP syndrome.

Grice, Ariela S Buxbaum / Sloofman, Laura / Levy, Tess / Walker, Hannah / Ganesh, Gauri / de Los Santos, Miguel Rodriguez / Armini, Pardis / Buxbaum, Joseph D / Kolevzon, Alexander / Kostic, Ana / Breen, Michael S

medRxiv : the preprint server for health sciences

2024

Abstract: Activity-dependent neuroprotective protein (ADNP) syndrome is a rare neurodevelopmental disorder resulting in intellectual disability, developmental delay and autism spectrum disorder (ASD) and is due to mutations in ... ...

Abstract	Activity-dependent neuroprotective protein (ADNP) syndrome is a rare neurodevelopmental disorder resulting in intellectual disability, developmental delay and autism spectrum disorder (ASD) and is due to mutations in the
Language	English
Publishing date	2024-01-31
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.01.29.24301949
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Article ; Online: Cellular and genetic drivers of RNA editing variation in the human brain.

Cuddleston, Winston H / Li, Junhao / Fan, Xuanjia / Kozenkov, Alexey / Lalli, Matthew / Khalique, Shahrukh / Dracheva, Stella / Mukamel, Eran A / Breen, Michael S

Nature communications

2022 Volume 13, Issue 1, Page(s) 2997

Abstract: Posttranscriptional adenosine-to-inosine modifications amplify the functionality of RNA molecules in the brain, yet the cellular and genetic regulation of RNA editing is poorly described. We quantify base-specific RNA editing across three major cell ... ...

Abstract	Posttranscriptional adenosine-to-inosine modifications amplify the functionality of RNA molecules in the brain, yet the cellular and genetic regulation of RNA editing is poorly described. We quantify base-specific RNA editing across three major cell populations from the human prefrontal cortex: glutamatergic neurons, medial ganglionic eminence-derived GABAergic neurons, and oligodendrocytes. We identify more selective editing and hyper-editing in neurons relative to oligodendrocytes. RNA editing patterns are highly cell type-specific, with 189,229 cell type-associated sites. The cellular specificity for thousands of sites is confirmed by single nucleus RNA-sequencing. Importantly, cell type-associated sites are enriched in GTEx RNA-sequencing data, edited ~twentyfold higher than all other sites, and variation in RNA editing is largely explained by neuronal proportions in bulk brain tissue. Finally, we uncover 661,791 cis-editing quantitative trait loci across thirteen brain regions, including hundreds with cell type-associated features. These data reveal an expansive repertoire of highly regulated RNA editing sites across human brain cell types and provide a resolved atlas linking cell types to editing variation and genetic regulatory effects.
MeSH term(s)	Brain/metabolism ; Humans ; Inosine/genetics ; Inosine/metabolism ; Quantitative Trait Loci/genetics ; RNA/metabolism ; RNA Editing/genetics
Chemical Substances	Inosine (5A614L51CT) ; RNA (63231-63-0)
Language	English
Publishing date	2022-05-30
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-30531-0
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Article ; Online: Modelling PTSD diagnosis using sleep, memory, and adrenergic metabolites: An exploratory machine-learning study.

Breen, Michael S / Thomas, Kevin G F / Baldwin, David S / Lipinska, Gosia

Human psychopharmacology

2019 Volume 34, Issue 2, Page(s) e2691

Abstract: Objective: Features of posttraumatic stress disorder (PTSD) typically include sleep disturbances, impaired declarative memory, and hyperarousal. This study evaluated whether these combined features may accurately delineate pathophysiological changes ... ...

Abstract	Objective: Features of posttraumatic stress disorder (PTSD) typically include sleep disturbances, impaired declarative memory, and hyperarousal. This study evaluated whether these combined features may accurately delineate pathophysiological changes associated with PTSD. Method: We recruited a cohort of PTSD-diagnosed individuals (N = 20), trauma survivors without PTSD (TE; N = 20), and healthy controls (HC; N = 20). Analyses of between-group differences and support vector machine (SVM)-learning were applied to participant features. Results: Analyses of between-group differences replicated previous findings, indicating that PTSD-diagnosed individuals self-reported poorer sleep quality, objectively demonstrated less sleep depth, and evidenced declarative memory deficits in comparison to HC. Integrative SVM-learning distinguished HC from trauma participants with 80% accuracy using a combination of five features, including subjective and objective sleep, neutral declarative memory, and metabolite variables. PTSD and TE participants could be distinguished with 70% accuracy using a combination of subjective and objective sleep variables but not by metabolite or declarative memory variables. Conclusion: From among a broad range of sleep, cognitive, and biochemical variables, sleep characteristics were the primary features that could differentiate those with PTSD from those without. Our exploratory SVM-learning analysis establishes a framework for future sleep- and memory-based PTSD investigations that could drive improvements in diagnostic accuracy and treatment.
MeSH term(s)	Adult ; Cohort Studies ; Cross-Sectional Studies ; Epinephrine/metabolism ; Female ; Humans ; Machine Learning ; Memory/physiology ; Memory Disorders/diagnosis ; Memory Disorders/metabolism ; Memory Disorders/psychology ; Norepinephrine/metabolism ; Sleep/physiology ; Sleep Wake Disorders/diagnosis ; Sleep Wake Disorders/metabolism ; Sleep Wake Disorders/psychology ; Stress Disorders, Post-Traumatic/diagnosis ; Stress Disorders, Post-Traumatic/metabolism ; Stress Disorders, Post-Traumatic/psychology ; Young Adult
Chemical Substances	Norepinephrine (X4W3ENH1CV) ; Epinephrine (YKH834O4BH)
Language	English
Publishing date	2019-02-22
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	632931-7
ISSN	1099-1077 ; 0885-6222
ISSN (online)	1099-1077
ISSN	0885-6222
DOI	10.1002/hup.2691
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Article ; Online: Systematic review of blood transcriptome profiling in neuropsychiatric disorders: guidelines for biomarker discovery.

Breen, Michael S / Stein, Dan J / Baldwin, David S

Human psychopharmacology

2016 Volume 31, Issue 5, Page(s) 373–381

Abstract: Introduction: The utility of blood for genome-wide gene expression profiling and biomarker discovery has received much attention in patients diagnosed with major neuropsychiatric disorders. While numerous studies have been conducted, statistical rigor ... ...

Abstract	Introduction: The utility of blood for genome-wide gene expression profiling and biomarker discovery has received much attention in patients diagnosed with major neuropsychiatric disorders. While numerous studies have been conducted, statistical rigor and clarity in terms of blood-based biomarker discovery, validation, and testing are needed. Methods: We conducted a systematic review of the literature to investigate methodological approaches and to assess the value of blood transcriptome profiling in research on mental disorders. We were particularly interested in statistical considerations related to machine learning, gene network analyses, and convergence across different disorders. Results: A total of 108 peripheral blood transcriptome studies across 15 disorders were surveyed: 25 studies used a variety of machine learning techniques to assess putative clinical viability of the candidate biomarkers; 11 leveraged a higher-order systems-level perspective to identify gene module-based biomarkers; and nine performed analyses across two or more neuropsychiatric phenotypes. Notably, ~50% of the surveyed studies included fewer than 50 samples (cases and controls), while ~75% included less than 100. Conclusions: Detailed consideration of statistical analysis in the early stages of experimental planning is critical to ensure blood-based biomarker discovery and validation. Statistical guidelines are presented to enhance implementation and reproducibility of machine learning and gene network analyses across independent studies. Future studies capitalizing on larger sample sizes and emerging next-generation technologies set the stage for moving the field forwards. Copyright © 2016 John Wiley & Sons, Ltd.
Language	English
Publishing date	2016-09
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	632931-7
ISSN	1099-1077 ; 0885-6222
ISSN (online)	1099-1077
ISSN	0885-6222
DOI	10.1002/hup.2546
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Article ; Online: Transcriptional signatures of participant-derived neural progenitor cells and neurons implicate altered Wnt signaling in Phelan-McDermid syndrome and autism.

Breen, Michael S / Browne, Andrew / Hoffman, Gabriel E / Stathopoulos, Sofia / Brennand, Kristen / Buxbaum, Joseph D / Drapeau, Elodie

Molecular autism

2020 Volume 11, Issue 1, Page(s) 53

Abstract: Background: Phelan-McDermid syndrome (PMS) is a rare genetic disorder with high risk of autism spectrum disorder (ASD), intellectual disability, and language delay, and is caused by 22q13.3 deletions or mutations in the SHANK3 gene. To date, the ... ...

Abstract	Background: Phelan-McDermid syndrome (PMS) is a rare genetic disorder with high risk of autism spectrum disorder (ASD), intellectual disability, and language delay, and is caused by 22q13.3 deletions or mutations in the SHANK3 gene. To date, the molecular and pathway changes resulting from SHANK3 haploinsufficiency in PMS remain poorly understood. Uncovering these mechanisms is critical for understanding pathobiology of PMS and, ultimately, for the development of new therapeutic interventions. Methods: We developed human-induced pluripotent stem cell (hiPSC)-based models of PMS by reprogramming peripheral blood samples from individuals with PMS (n = 7) and their unaffected siblings (n = 6). For each participant, up to three hiPSC clones were generated and differentiated into induced neural progenitor cells (hiPSC-NPCs; n = 39) and induced forebrain neurons (hiPSC-neurons; n = 41). Genome-wide RNA-sequencing was applied to explore transcriptional differences between PMS probands and unaffected siblings. Results: Transcriptome analyses identified 391 differentially expressed genes (DEGs) in hiPSC-NPCs and 82 DEGs in hiPSC-neurons, when comparing cells from PMS probands and unaffected siblings (FDR < 5%). Genes under-expressed in PMS were implicated in Wnt signaling, embryonic development, and protein translation, while over-expressed genes were enriched for pre- and postsynaptic density genes, regulation of synaptic plasticity, and G-protein-gated potassium channel activity. Gene co-expression network analysis identified two modules in hiPSC-neurons that were over-expressed in PMS, implicating postsynaptic signaling and GDP binding, and both modules harbored a significant enrichment of genetic risk loci for developmental delay and intellectual disability. Finally, PMS-associated genes were integrated with other ASD hiPSC transcriptome findings and several points of convergence were identified, indicating altered Wnt signaling and extracellular matrix. Limitations: Given the rarity of the condition, we could not carry out experimental validation in independent biological samples. In addition, functional and morphological phenotypes caused by loss of SHANK3 were not characterized here. Conclusions: This is the largest human neural sample analyzed in PMS. Genome-wide RNA-sequencing in hiPSC-derived neural cells from individuals with PMS revealed both shared and distinct transcriptional signatures across hiPSC-NPCs and hiPSC-neurons, including many genes implicated in risk for ASD, as well as specific neurobiological pathways, including the Wnt pathway.
MeSH term(s)	Adolescent ; Adult ; Autistic Disorder/genetics ; Child ; Child, Preschool ; Chromosome Deletion ; Chromosome Disorders/genetics ; Chromosome Disorders/pathology ; Chromosomes, Human, Pair 22/genetics ; Female ; Gene Expression Profiling ; Gene Expression Regulation ; Humans ; Induced Pluripotent Stem Cells/pathology ; Male ; Neural Stem Cells/metabolism ; Neural Stem Cells/pathology ; Neurons/metabolism ; Neurons/pathology ; Reproducibility of Results ; Wnt Signaling Pathway/genetics
Language	English
Publishing date	2020-06-19
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2540930-X
ISSN	2040-2392 ; 2040-2392
ISSN (online)	2040-2392
ISSN	2040-2392
DOI	10.1186/s13229-020-00355-0
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Article ; Online: The impact of air exchange rate on ambient air pollution exposure and inequalities across all residential parcels in Massachusetts.

Rosofsky, Anna / Levy, Jonathan I / Breen, Michael S / Zanobetti, Antonella / Fabian, M Patricia

Journal of exposure science & environmental epidemiology

2018 Volume 29, Issue 4, Page(s) 520–530

Abstract: Individual housing characteristics can modify outdoor ambient air pollution infiltration through air exchange rate (AER). Time and labor-intensive methods needed to measure AER has hindered characterization of AER distributions across large geographic ... ...

Abstract	Individual housing characteristics can modify outdoor ambient air pollution infiltration through air exchange rate (AER). Time and labor-intensive methods needed to measure AER has hindered characterization of AER distributions across large geographic areas. Using publicly-available data and regression models associating AER with housing characteristics, we estimated AER for all Massachusetts residential parcels. We conducted an exposure disparities analysis, considering ambient PM
MeSH term(s)	Air Pollutants/analysis ; Environmental Exposure ; Environmental Monitoring/methods ; Housing ; Humans ; Massachusetts ; Particulate Matter/analysis ; Seasons ; Socioeconomic Factors
Chemical Substances	Air Pollutants ; Particulate Matter
Language	English
Publishing date	2018-09-21
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2218551-3
ISSN	1559-064X ; 1559-0631
ISSN (online)	1559-064X
ISSN	1559-0631
DOI	10.1038/s41370-018-0068-3
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Article ; Online: Mitochondrial pathogenic mutations are population-specific.

Breen, Michael S / Kondrashov, Fyodor A

Biology direct

2010 Volume 5, Page(s) 68

Abstract: Background: Surveying deleterious variation in human populations is crucial for our understanding, diagnosis and potential treatment of human genetic pathologies. A number of recent genome-wide analyses focused on the prevalence of segregating ... ...

Abstract	Background: Surveying deleterious variation in human populations is crucial for our understanding, diagnosis and potential treatment of human genetic pathologies. A number of recent genome-wide analyses focused on the prevalence of segregating deleterious alleles in the nuclear genome. However, such studies have not been conducted for the mitochondrial genome. Results: We present a systematic survey of polymorphisms in the human mitochondrial genome, including those predicted to be deleterious and those that correspond to known pathogenic mutations. Analyzing 4458 completely sequenced mitochondrial genomes we characterize the genetic diversity of different types of single nucleotide polymorphisms (SNPs) in African (L haplotypes) and non-African (M and N haplotypes) populations. We find that the overall level of polymorphism is higher in the mitochondrial compared to the nuclear genome, although the mitochondrial genome appears to be under stronger selection as indicated by proportionally fewer nonsynonymous than synonymous substitutions. The African mitochondrial genomes show higher heterozygosity, a greater number of polymorphic sites and higher frequencies of polymorphisms for synonymous, benign and damaging polymorphism than non-African genomes. However, African genomes carry significantly fewer SNPs that have been previously characterized as pathogenic compared to non-African genomes. Conclusions: Finding SNPs classified as pathogenic to be the only category of polymorphisms that are more abundant in non-African genomes is best explained by a systematic ascertainment bias that favours the discovery of pathogenic polymorphisms segregating in non-African populations. This further suggests that, contrary to the common disease-common variant hypothesis, pathogenic mutations are largely population-specific and different SNPs may be associated with the same disease in different populations. Therefore, to obtain a comprehensive picture of the deleterious variability in the human population, as well as to improve the diagnostics of individuals carrying African mitochondrial haplotypes, it is necessary to survey different populations independently. Reviewers: This article was reviewed by Dr Mikhail Gelfand, Dr Vasily Ramensky (nominated by Dr Eugene Koonin) and Dr David Rand (nominated by Dr Laurence Hurst).
MeSH term(s)	African Continental Ancestry Group/genetics ; Base Sequence ; Continental Population Groups/genetics ; DNA, Mitochondrial/genetics ; Genetic Variation ; Genome, Human ; Haplotypes ; Heterozygote ; Humans ; Mutation ; Polymorphism, Single Nucleotide ; Sequence Deletion
Chemical Substances	DNA, Mitochondrial
Language	English
Publishing date	2010-12-31
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1745-6150
ISSN (online)	1745-6150
DOI	10.1186/1745-6150-5-68
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