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Article ; Online: P59 Marked Differences in Cerebral Haemodynamics Obtained with Transcranial Doppler vs. 2-D Angle-corrected Ultrasound

Christopher Brown / Mahfoudha Al Shezawi / Laura Watkeys / Maggie Munnery / Christopher Pugh / Eric Stöhr / Barry McDonnell

Artery Research, Vol 25, Iss

2020 Volume 1

Abstract: ... may not capture the correct flow velocities because of sub-optimal angles of insonation. Conversely, 2-D ...

Abstract	Introduction: The assessment of middle cerebral artery (MCA) haemodynamics is essential for the diagnosis and monitoring of cerebrovascular disease. However, conventional transcranial Doppler (TCD) may not capture the correct flow velocities because of sub-optimal angles of insonation. Conversely, 2-D ultrasound (2D-US) allows for the visualisation and angle-correction of MCA haemodynamics. Therefore, this study aimed to determine potential differences in MCA haemodynamics obtained with TCD and 2D-US. Methods: MCA haemodynamics were obtained in a blinded, randomised order with TCD and 2D-US (non-angle-corrected = 2D-US-NON and angle-corrected = 2D-US-ANGLE) from the temporal left posterior window in twenty-seven healthy participants. Recordings were analysed for peak-systolic velocity (PSV), end-diastolic velocity (ED), pulsatility index (PI) and resistance index (RI). Statistical agreements between TCD and 2D-US were determined using linear regression, independent samples t-test and Bland-Altman analysis. Results: MCA haemodynamics obtained with TCD explained less than 50% of the values obtained with 2D-US-NON & 2D-US-ANGLE, respectively (PSV r2 = 0.34 & 0.37; ED: r2 = 0.37 & 0.44; PI: r2 = 0.20 & 0.22; RI: r2 = 0.30 & 0.32). Compared with 2D-US-NON, TCD produced similar PSV (p = 0.65) but significantly higher ED (p < 0.0001), lower PI (p < 0.0001) and lower RI (p < 0.0001). 2D-US angle-correction resulted in a significantly higher PSV compared with TCD (p = 0.005) while all other differences remained. Bland-Altman analysis revealed a bias between the two methods ranging from 11–40%, with large individual variability. Conclusion: TCD and 2D ultrasound produce significantly different values for MCA haemodynamics, even when 2D-US is non-angle-corrected. This may have important implications when using indices of MCA haemodynamics in the evaluation of cerebrovascular disease.
Keywords	Specialties of internal medicine ; RC581-951 ; Diseases of the circulatory (Cardiovascular) system ; RC666-701
Subject code	610
Language	English
Publishing date	2020-02-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Breast cancer risk markedly lower with serum 25-hydroxyvitamin D concentrations ≥60 vs <20 ng/ml (150 vs 50 nmol/L): Pooled analysis of two randomized trials and a prospective cohort.

McDonnell, Sharon L / Baggerly, Carole A / French, Christine B / Baggerly, Leo L / Garland, Cedric F / Gorham, Edward D / Hollis, Bruce W / Trump, Donald L / Lappe, Joan M

PloS one

2018 Volume 13, Issue 6, Page(s) e0199265

Abstract: ... hydroxyvitamin D [25(OH)D] concentrations and lower breast cancer risk, few have assessed this association ... for concentrations >40 ng/ml.: Objective: To investigate the relationship between 25(OH)D concentration and breast ... cancer risk across a broad range of 25(OH)D concentrations among women aged 55 years and older.: Methods ...

Abstract	Background: While numerous epidemiologic studies have found an association between higher serum 25-hydroxyvitamin D [25(OH)D] concentrations and lower breast cancer risk, few have assessed this association for concentrations >40 ng/ml. Objective: To investigate the relationship between 25(OH)D concentration and breast cancer risk across a broad range of 25(OH)D concentrations among women aged 55 years and older. Methods: Analyses used pooled data from two randomized clinical trials (N = 1129, N = 2196) and a prospective cohort (N = 1713) to examine a broad range of 25(OH)D concentrations. The outcome was diagnosis of breast cancer during the observation periods (median: 4.0 years). Three analyses were conducted: 1) Incidence rates were compared according to 25(OH)D concentration from <20 to ≥60 ng/ml (<50 to ≥150 nmol/L), 2) Kaplan-Meier plots were developed and 3) multivariate Cox regression was used to examine the association between 25(OH)D and breast cancer risk using multiple 25(OH)D measurements. Results: Within the pooled cohort (N = 5038), 77 women were diagnosed with breast cancer (age-adjusted incidence: 512 cases per 100,000 person-years). Results were similar for the three analyses. First, comparing incidence rates, there was an 82% lower incidence rate of breast cancer for women with 25(OH)D concentrations ≥60 vs <20 ng/ml (Rate Ratio = 0.18, P = 0.006). Second, Kaplan-Meier curves for concentrations of <20, 20-39, 40-59 and ≥60 ng/ml were significantly different (P = 0.02), with the highest proportion breast cancer-free in the ≥60 ng/ml group (99.3%) and the lowest proportion breast cancer-free in the <20 ng/ml group (96.8%). The proportion with breast cancer was 78% lower for ≥60 vs <20 ng/ml (P = 0.02). Third, multivariate Cox regression revealed that women with 25(OH)D concentrations ≥60 ng/ml had an 80% lower risk of breast cancer than women with concentrations <20 ng/ml (HR = 0.20, P = 0.03), adjusting for age, BMI, smoking status, calcium supplement intake, and study of origin. Conclusions: Higher 25(OH)D concentrations were associated with a dose-response decrease in breast cancer risk with concentrations ≥60 ng/ml being most protective.
MeSH term(s)	Aged ; Aged, 80 and over ; Breast Neoplasms/blood ; Breast Neoplasms/epidemiology ; Breast Neoplasms/pathology ; Female ; Humans ; Middle Aged ; Proportional Hazards Models ; Prospective Studies ; Randomized Controlled Trials as Topic ; Risk Factors ; Vitamin D/analogs & derivatives ; Vitamin D/blood
Chemical Substances	Vitamin D (1406-16-2) ; 25-hydroxyvitamin D (A288AR3C9H)
Language	English
Publishing date	2018-06-15
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0199265
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Breast cancer risk markedly lower with serum 25-hydroxyvitamin D concentrations ≥60 vs <20 ng/ml (150 vs 50 nmol/L)

Sharon L McDonnell / Carole A Baggerly / Christine B French / Leo L Baggerly / Cedric F Garland / Edward D Gorham / Bruce W Hollis / Donald L Trump / Joan M Lappe

PLoS ONE, Vol 13, Iss 6, p e

Pooled analysis of two randomized trials and a prospective cohort.

2018 Volume 0199265

Abstract: ... hydroxyvitamin D [25(OH)D] concentrations and lower breast cancer risk, few have assessed this association ... for concentrations >40 ng/ml. OBJECTIVE:To investigate the relationship between 25(OH)D concentration and breast ... cancer risk across a broad range of 25(OH)D concentrations among women aged 55 years and older. METHODS ...

Abstract	BACKGROUND:While numerous epidemiologic studies have found an association between higher serum 25-hydroxyvitamin D [25(OH)D] concentrations and lower breast cancer risk, few have assessed this association for concentrations >40 ng/ml. OBJECTIVE:To investigate the relationship between 25(OH)D concentration and breast cancer risk across a broad range of 25(OH)D concentrations among women aged 55 years and older. METHODS:Analyses used pooled data from two randomized clinical trials (N = 1129, N = 2196) and a prospective cohort (N = 1713) to examine a broad range of 25(OH)D concentrations. The outcome was diagnosis of breast cancer during the observation periods (median: 4.0 years). Three analyses were conducted: 1) Incidence rates were compared according to 25(OH)D concentration from <20 to ≥60 ng/ml (<50 to ≥150 nmol/L), 2) Kaplan-Meier plots were developed and 3) multivariate Cox regression was used to examine the association between 25(OH)D and breast cancer risk using multiple 25(OH)D measurements. RESULTS:Within the pooled cohort (N = 5038), 77 women were diagnosed with breast cancer (age-adjusted incidence: 512 cases per 100,000 person-years). Results were similar for the three analyses. First, comparing incidence rates, there was an 82% lower incidence rate of breast cancer for women with 25(OH)D concentrations ≥60 vs <20 ng/ml (Rate Ratio = 0.18, P = 0.006). Second, Kaplan-Meier curves for concentrations of <20, 20-39, 40-59 and ≥60 ng/ml were significantly different (P = 0.02), with the highest proportion breast cancer-free in the ≥60 ng/ml group (99.3%) and the lowest proportion breast cancer-free in the <20 ng/ml group (96.8%). The proportion with breast cancer was 78% lower for ≥60 vs <20 ng/ml (P = 0.02). Third, multivariate Cox regression revealed that women with 25(OH)D concentrations ≥60 ng/ml had an 80% lower risk of breast cancer than women with concentrations <20 ng/ml (HR = 0.20, P = 0.03), adjusting for age, BMI, smoking status, calcium supplement intake, and study of ...
Keywords	Medicine ; R ; Science ; Q
Subject code	610 ; 616
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity

Lindner, Benjamin / Goldwyn, Joshua H. / McDonnell, Mark D.

2016

Abstract: Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For example, ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, and neural networks are ... ...

Abstract	Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For example, ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, and neural networks are embedded in spontaneous background activity. The mathematical and computational tool sets contributing to our understanding of stochastic neural dynamics have expanded rapidly in recent years. New theories have emerged detailing the dynamics and computational power of the balanced state in recurrent networks. At the cellular level, novel stochastic extensions to the classical Hodgkin-Huxley model have enlarged our understanding of neuronal dynamics and action potential initiation. Analytical methods have been developed that allow for the calculation of the firing statistics of simplified phenomenological integrate-and-fire models, taking into account adaptation currents or temporal correlations of the noise. This Research Topic is focused on identified physiological/internal noise sources and mechanisms. By internal, we mean variability that is generated by intrinsic biophysical processes. This includes noise at a range of scales, from ion channels to synapses to neurons to networks. The contributions in this Research Topic introduce innovative mathematical analysis and/or computational methods that relate to empirical measures of neural activity and illuminate the functional role of intrinsic noise in the brain
Keywords	Science (General) ; Neurosciences. Biological psychiatry. Neuropsychiatry
Size	1 electronic resource (156 p.)
Publisher	Frontiers Media SA
Document type	Book ; Online
Note	English ; Open Access
HBZ-ID	HT020090604
ISBN	9782889198849 ; 2889198847
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Direct Probe of Vibrational Fingerprint and Combination Band Coupling.

McDonnell, Ryan P / Oram, Kelson / Boyer, Mark A / Kohler, Daniel D / Meyer, Kent A / Sibert Iii, Edwin L / Wright, John C

The journal of physical chemistry letters

2024 Volume 15, Issue 14, Page(s) 3975–3981

Abstract: Vibrational fingerprints and combination bands are a direct measure of couplings that control molecular properties. However, most combination bands possess small transition dipoles. Here we use multiple, ultrafast coherent infrared pulses to resolve ... ...

Abstract	Vibrational fingerprints and combination bands are a direct measure of couplings that control molecular properties. However, most combination bands possess small transition dipoles. Here we use multiple, ultrafast coherent infrared pulses to resolve vibrational coupling between CH
Language	English
Publishing date	2024-04-03
Publishing country	United States
Document type	Journal Article
ISSN	1948-7185
ISSN (online)	1948-7185
DOI	10.1021/acs.jpclett.4c00297
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study.

Madakkatel, Iqbal / Zhou, Ang / McDonnell, Mark D / Hyppönen, Elina

Scientific reports

2021 Volume 11, Issue 1, Page(s) 22997

Abstract: We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models were ...

Abstract	We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models were built using gradient boosting decision trees (GBDT) and important predictors were identified using a Shapley values-based feature attribution method, SHAP values. Cox models controlled for false discovery rate were used for confounder adjustment, interpretability, and further validation. The pipeline was tested using information from 502,506 UK Biobank participants, aged 37-73 years at recruitment and followed over seven years for mortality registrations. From the 11,639 predictors included in GBDT, 193 potential risk factors had SHAP values ≥ 0.05, passed the correlation test, and were selected for further modelling. Of the total variable importance summed up, 60% was directly health related, and baseline characteristics, sociodemographics, and lifestyle factors each contributed about 10%. Cox models adjusted for baseline characteristics, showed evidence for an association with mortality for 166 out of the 193 predictors. These included mostly well-known risk factors (e.g., age, sex, ethnicity, education, material deprivation, smoking, physical activity, self-rated health, BMI, and many disease outcomes). For 19 predictors we saw evidence for an association in the unadjusted but not adjusted analyses, suggesting bias by confounding. Our GBDT-SHAP pipeline was able to identify relevant predictors 'hidden' within thousands of variables, providing an efficient and pragmatic solution for the first stage of hypothesis free risk factor identification.
MeSH term(s)	Aged ; Cognition Disorders/epidemiology ; Cognition Disorders/mortality ; Cohort Studies ; Databases, Factual ; Female ; Humans ; Life Style ; Machine Learning ; Male ; Middle Aged ; Mortality/trends ; Risk Factors ; Smoking/epidemiology ; Smoking/mortality ; United Kingdom/epidemiology
Language	English
Publishing date	2021-11-26
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-02476-9
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The quest for better clinical word vectors: Ontology based and lexical vector augmentation versus clinical contextual embeddings.

Nath, Namrata / Lee, Sang-Heon / McDonnell, Mark D / Lee, Ivan

Computers in biology and medicine

2021 Volume 134, Page(s) 104433

Abstract: Background: Word vectors or word embeddings are n-dimensional representations of words and form the backbone of Natural Language Processing of textual data. This research experiments with algorithms that augment word vectors with lexical constraints ... ...

Abstract	Background: Word vectors or word embeddings are n-dimensional representations of words and form the backbone of Natural Language Processing of textual data. This research experiments with algorithms that augment word vectors with lexical constraints that are popular in NLP research and clinical domain constraints derived from the Unified Medical Language System (UMLS). It also compares the performance of the augmented vectors with Bio + Clinical BERT vectors which have been trained and fine-tuned on clinical datasets. Methods: Word2vec vectors are generated for words in a publicly available de-identified Electronic Health Records (EHR) dataset and augmented by ontologies using three algorithms that have fundamentally different approaches to vector augmentation. The augmented vectors are then evaluated alongside publicly available Bio + Clinical BERT on their correlation with human-annotated lists using Spearman's correlation coefficient. They are also evaluated on the downstream task of Named Entity Recognition (NER). Quantitative and empirical evaluations are used to highlight the strengths and weaknesses of the different approaches. Results: The counter-fitted word2vec vectors augmented with information from the UMLS ontology produced the best correlation overall with human-annotated evaluation lists (Spearman's correlation of 0.733 with mini mayo-doctors' annotation) while Bio + Clinical BERT produces the best results in the NER task (F1 of 0.87 and 0.811 on the i2b2 2010 and i2b2 2012 datasets respectively) in our experiments. Conclusion: Clinically adapted word2vec vectors successfully encapsulate concepts of lexical and clinical synonymy and antonymy and to a smaller extent, hyponymy and hypernymy. Bio + Clinical BERT vectors perform better at NER and avoid out-of-vocabulary words.
MeSH term(s)	Algorithms ; Electronic Health Records ; Humans ; Natural Language Processing ; Unified Medical Language System
Language	English
Publishing date	2021-04-28
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	127557-4
ISSN	1879-0534 ; 0010-4825
ISSN (online)	1879-0534
ISSN	0010-4825
DOI	10.1016/j.compbiomed.2021.104433
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Book ; Online: RanPAC

McDonnell, Mark D. / Gong, Dong / Parveneh, Amin / Abbasnejad, Ehsan / Hengel, Anton van den

Random Projections and Pre-trained Models for Continual Learning

2023

Abstract: Continual learning (CL) aims to incrementally learn different tasks (such as classification) in a non-stationary data stream without forgetting old ones. Most CL works focus on tackling catastrophic forgetting under a learning-from-scratch paradigm. ... ...

Abstract	Continual learning (CL) aims to incrementally learn different tasks (such as classification) in a non-stationary data stream without forgetting old ones. Most CL works focus on tackling catastrophic forgetting under a learning-from-scratch paradigm. However, with the increasing prominence of foundation models, pre-trained models equipped with informative representations have become available for various downstream requirements. Several CL methods based on pre-trained models have been explored, either utilizing pre-extracted features directly (which makes bridging distribution gaps challenging) or incorporating adaptors (which may be subject to forgetting). In this paper, we propose a concise and effective approach for CL with pre-trained models. Given that forgetting occurs during parameter updating, we contemplate an alternative approach that exploits training-free random projectors and class-prototype accumulation, which thus bypasses the issue. Specifically, we inject a frozen Random Projection layer with nonlinear activation between the pre-trained model's feature representations and output head, which captures interactions between features with expanded dimensionality, providing enhanced linear separability for class-prototype-based CL. We also demonstrate the importance of decorrelating the class-prototypes to reduce the distribution disparity when using pre-trained representations. These techniques prove to be effective and circumvent the problem of forgetting for both class- and domain-incremental continual learning. Compared to previous methods applied to pre-trained ViT-B/16 models, we reduce final error rates by between 20% and 62% on seven class-incremental benchmarks, despite not using any rehearsal memory. We conclude that the full potential of pre-trained models for simple, effective, and fast CL has not hitherto been fully tapped. Code is at github.com/RanPAC/RanPAC. Comment: 32 pages, 11 figures
Keywords	Computer Science - Machine Learning ; Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2023-07-05
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study

Iqbal Madakkatel / Ang Zhou / Mark D. McDonnell / Elina Hyppönen

Scientific Reports, Vol 11, Iss 1, Pp 1-

2021 Volume 11

Abstract: Abstract We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality ... ...

Abstract	Abstract We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models were built using gradient boosting decision trees (GBDT) and important predictors were identified using a Shapley values-based feature attribution method, SHAP values. Cox models controlled for false discovery rate were used for confounder adjustment, interpretability, and further validation. The pipeline was tested using information from 502,506 UK Biobank participants, aged 37–73 years at recruitment and followed over seven years for mortality registrations. From the 11,639 predictors included in GBDT, 193 potential risk factors had SHAP values ≥ 0.05, passed the correlation test, and were selected for further modelling. Of the total variable importance summed up, 60% was directly health related, and baseline characteristics, sociodemographics, and lifestyle factors each contributed about 10%. Cox models adjusted for baseline characteristics, showed evidence for an association with mortality for 166 out of the 193 predictors. These included mostly well-known risk factors (e.g., age, sex, ethnicity, education, material deprivation, smoking, physical activity, self-rated health, BMI, and many disease outcomes). For 19 predictors we saw evidence for an association in the unadjusted but not adjusted analyses, suggesting bias by confounding. Our GBDT-SHAP pipeline was able to identify relevant predictors ‘hidden’ within thousands of variables, providing an efficient and pragmatic solution for the first stage of hypothesis free risk factor identification.
Keywords	Medicine ; R ; Science ; Q
Subject code	310
Language	English
Publishing date	2021-11-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications.

Boyd, Chris / Brown, Greg / Kleinig, Timothy / Dawson, Joseph / McDonnell, Mark D / Jenkinson, Mark / Bezak, Eva

Diagnostics (Basel, Switzerland)

2021 Volume 11, Issue 3

Abstract: Research into machine learning (ML) for clinical vascular analysis, such as those useful for stroke and coronary artery disease, varies greatly between imaging modalities and vascular regions. Limited accessibility to large diverse patient imaging ... ...

Abstract	Research into machine learning (ML) for clinical vascular analysis, such as those useful for stroke and coronary artery disease, varies greatly between imaging modalities and vascular regions. Limited accessibility to large diverse patient imaging datasets, as well as a lack of transparency in specific methods, are obstacles to further development. This paper reviews the current status of quantitative vascular ML, identifying advantages and disadvantages common to all imaging modalities. Literature from the past 8 years was systematically collected from MEDLINE
Language	English
Publishing date	2021-03-19
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics11030551
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