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Article ; Online: Efficient gene-environment interaction testing through bootstrap aggregating.

Lau, Michael / Kress, Sara / Schikowski, Tamara / Schwender, Holger

2023 Volume 13, Issue 1, Page(s) 937

Abstract: Gene-environment (GxE) interactions are an important and sophisticated component in the manifestation of complex phenotypes. Simple univariate tests lack statistical power due to the need for multiple testing adjustment and not incorporating potential ... ...

Abstract	Gene-environment (GxE) interactions are an important and sophisticated component in the manifestation of complex phenotypes. Simple univariate tests lack statistical power due to the need for multiple testing adjustment and not incorporating potential interplay between several genetic loci. Approaches based on internally constructed genetic risk scores (GRS) require the partitioning of the available sample into training and testing data sets, thus, lowering the effective sample size for testing the GxE interaction itself. To overcome these issues, we propose a statistical test that employs bagging (bootstrap aggregating) in the GRS construction step and utilizes its out-of-bag prediction mechanism. This approach has the key advantage that the full available data set can be used for both constructing the GRS and testing the GxE interaction. To also incorporate interactions between genetic loci, we, furthermore, investigate if using random forests as the GRS construction method in GxE interaction testing further increases the statistical power. In a simulation study, we show that both novel procedures lead to a higher statistical power for detecting GxE interactions, while still controlling the type I error. The random-forests-based test outperforms a bagging-based test that uses the elastic net as its base learner in most scenarios. An application of the testing procedures to a real data set from a German cohort study suggests that there might be a GxE interaction involving exposure to air pollution regarding rheumatoid arthritis.
MeSH term(s)	Gene-Environment Interaction ; Cohort Studies ; Computer Simulation ; Phenotype ; Risk Factors ; Models, Genetic
Language	English
Publishing date	2023-01-17
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/s41598-023-28172-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Pulmonary Glomus Tumor.

Acharya, Sudeep / Anwar, Shamsuddin / Thapa, Kumar / Thapa, Sakura / Lau, Michael

Cureus

2023 Volume 15, Issue 5, Page(s) e38684

Abstract: Glomus tumors, which account for less than 2% of soft tissue tumors, are a rare benign soft tissue neoplasm. They originated from neuro-myo-arterial glomus tissue whose primary function is regulation of the body temperature. This tissue is commonly ... ...

Abstract	Glomus tumors, which account for less than 2% of soft tissue tumors, are a rare benign soft tissue neoplasm. They originated from neuro-myo-arterial glomus tissue whose primary function is regulation of the body temperature. This tissue is commonly located in the dermis or subcutis in the subungual region; however, it can be extracutaneous such as in bones, the genitourinary tract, the gastrointestinal tract, and the respiratory tract. Histologically, a glomus tumor is made of proliferating rounded or cuboidal epithelioid cells in a meshwork of blood vessels. Although a benign growth, they can rarely show malignant features with infiltration of surrounding tissue with the rapid multiplication of cells in which case it is labeled as a malignant glomus tumor. Pulmonary glomus tumors are extremely rare and most commonly occur in middle-aged men. They are mostly asymptomatic, but a small percentage of patients may present with hemoptysis and cough if there is large airway involvement. We present an interesting case of a middle-aged man presenting with cough and occasional hemoptysis, found to have an endobronchial nodular lesion, and subsequently diagnosed with a pulmonary glomus tumor.
Language	English
Publishing date	2023-05-07
Publishing country	United States
Document type	Case Reports
ZDB-ID	2747273-5
ISSN	2168-8184
ISSN	2168-8184
DOI	10.7759/cureus.38684
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Book ; Thesis: Psychosoziale Auswirkungen des Schwangerschaftsabbruches

Lau, Michael

1989

Keywords	Pregnancy, Unwanted ; Abortion, Induced / psychology
Size	35, 3 S.
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Kiel, Univ., Diss., 1989
HBZ-ID	HT003497036
Database	Catalogue ZB MED Medicine, Health

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Article ; Online: Evaluation of tree-based statistical learning methods for constructing genetic risk scores.

Lau, Michael / Wigmann, Claudia / Kress, Sara / Schikowski, Tamara / Schwender, Holger

BMC bioinformatics

2022 Volume 23, Issue 1, Page(s) 97

Abstract: Background: Genetic risk scores (GRS) summarize genetic features such as single nucleotide polymorphisms (SNPs) in a single statistic with respect to a given trait. So far, GRS are typically built using generalized linear models or regularized ... ...

Abstract	Background: Genetic risk scores (GRS) summarize genetic features such as single nucleotide polymorphisms (SNPs) in a single statistic with respect to a given trait. So far, GRS are typically built using generalized linear models or regularized extensions. However, these linear methods are usually not able to incorporate gene-gene interactions or non-linear SNP-response relationships. Tree-based statistical learning methods such as random forests and logic regression may be an alternative to such regularized-regression-based methods and are investigated in this article. Moreover, we consider modifications of random forests and logic regression for the construction of GRS. Results: In an extensive simulation study and an application to a real data set from a German cohort study, we show that both tree-based approaches can outperform elastic net when constructing GRS for binary traits. Especially a modification of logic regression called logic bagging could induce comparatively high predictive power as measured by the area under the curve and the statistical power. Even when considering no epistatic interaction effects but only marginal genetic effects, the regularized regression method lead in most cases to inferior results. Conclusions: When constructing GRS, we recommend taking random forests and logic bagging into account, in particular, if it can be assumed that possibly unknown epistasis between SNPs is present. To develop the best possible prediction models, extensive joint hyperparameter optimizations should be conducted.
MeSH term(s)	Algorithms ; Cohort Studies ; Humans ; Polymorphism, Single Nucleotide ; Regression Analysis ; Risk Factors
Language	English
Publishing date	2022-03-21
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-022-04634-w
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Predictive analytics for step-up therapy: Supervised or semi-supervised learning?

Morid, Mohammad Amin / Lau, Michael / Del Fiol, Guilherme

Journal of biomedical informatics

2021 Volume 119, Page(s) 103842

Abstract: Background: Step-up therapy is a patient management approach that aims to balance the efficacy, costs and risks posed by different lines of medications. While the initiation of first line medications is a straightforward decision, stepping-up a patient ... ...

Abstract	Background: Step-up therapy is a patient management approach that aims to balance the efficacy, costs and risks posed by different lines of medications. While the initiation of first line medications is a straightforward decision, stepping-up a patient to the next treatment line is often more challenging and difficult to predict. By identifying patients who are likely to move to the next line of therapy, prediction models could be used to help healthcare organizations with resource planning and chronic disease management. Objective: To compared supervised learning versus semi-supervised learning to predict which rheumatoid arthritis patients will move from the first line of therapy (i.e., conventional synthetic disease-modifying antirheumatic drugs) to the next line of therapy (i.e., disease-modifying antirheumatic drugs or targeted synthetic disease-modifying antirheumatic drugs) within one year. Materials and methods: Five groups of features were extracted from an administrative claims database: demographics, medications, diagnoses, provider characteristics, and procedures. Then, a variety of supervised and semi-supervised learning methods were implemented to identify the most optimal method of each approach and assess the contribution of each feature group. Finally, error analysis was conducted to understand the behavior of misclassified patients. Results: XGBoost yielded the highest F-measure (42%) among the supervised approaches and one-class support vector machine achieved the highest F-measure (65%) among the semi-supervised approaches. The semi-supervised approach had significantly higher F-measure (65% vs. 42%; p < 0.01), precision (51% vs. 33%; p < 0.01), and recall (89% vs. 59%; p < 0.01) than the supervised approach. Excluding demographic, drug, diagnosis, provider, and procedure features reduced theF-measure from 65% to 61%, 57%, 54%, 51% and 49% respectively (p < 0.01). The error analysis showed that a substantial portion of false positive patients will change their line of therapy shortly after the prediction period. Conclusion: This study showed that supervised learning approaches are not an optimal option for a difficult clinical decision regarding step-up therapy. More specifically, negative class labels in step-up therapy data are not a robust ground truth, because the costs and risks associated with higher line of therapy impact objective decision making of patients and providers. The proposed semi-supervised learning approach can be applied to other step-up therapy applications.
MeSH term(s)	Arthritis, Rheumatoid/diagnosis ; Arthritis, Rheumatoid/drug therapy ; Humans ; Supervised Machine Learning ; Support Vector Machine
Language	English
Publishing date	2021-06-17
Publishing country	United States
Document type	Journal Article
ZDB-ID	2057141-0
ISSN	1532-0480 ; 1532-0464
ISSN (online)	1532-0480
ISSN	1532-0464
DOI	10.1016/j.jbi.2021.103842
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Article ; Online: A new species of Calamaria (Squamata: Colubridae) from Guangdong Province, southern China

Yeung, Ho Yuen / Lau, Michael W. N. / Yang, Jian-Huan

Vertebrate Zoology 2022 June 27, v. 72, p. 433-444

2022 , Page(s) 433–444

Abstract: A new species of the genus Calamaria Boie, 1827, Calamaria arcana sp. nov., is described based on a single male specimen collected from Mt. Dadongshan, Guangdong, southern China. The new species can be distinguished from all known congeners by the ... ...

Abstract	A new species of the genus Calamaria Boie, 1827, Calamaria arcana sp. nov., is described based on a single male specimen collected from Mt. Dadongshan, Guangdong, southern China. The new species can be distinguished from all known congeners by the significant genetic divergence in the mitochondrial cytochrome-b gene fragment (p-distance ≥ 13.9%), and morphologically by the combination of the following characters: (1) ten modified maxillary teeth; (2) four supralabials, second and third supralabials entering orbit; (3) preocular present; (4) mental not touching anterior chin shields; (5) six scales and shields surrounding the paraparietal; (6) 170 ventral scales; (7) 22 paired subcaudals; (8) tail not gradually tapering, abruptly tapering at the tip; (9) dorsal scales reduced to five rows above last subcaudal at tail; (10) dorsum of body and tail brownish; (11) dark collar on nuchal region absent; (12) two outermost dorsal scale rows light yellow with upper margins partly dark pigmented; (13) ventral scales immaculate, without dark outermost corners and pigmentation anteriorly; and (14) absence of distinct dark longitudinal line or scattered spots on the underside of tail. Calamaria arcana sp. nov., represents the fifth species of the genus recorded in China. Following the IUCN Red List Categories and Criteria, we propose the new species to be listed as Data Deficient.
Keywords	Colubridae ; cytochrome b ; genes ; genetic variation ; males ; mitochondria ; new species ; pigmentation ; tail ; vertebrates ; zoology ; China ; Calamariaarcana sp. nov. ; Calamariinae ; integrative taxonomy ; morphology ; phylogeny ; snake ; Southeast Asia
Language	English
Dates of publication	2022-0627
Size	p. 433-444
Publishing place	Senckenberg Gesellschaft für Naturforschung
Document type	Article ; Online
Note	Resource is Open Access ; Other License Information
ZDB-ID	2392087-7
ISSN	2625-8498 ; 1864-5755
ISSN (online)	2625-8498
ISSN	1864-5755
DOI	10.3897/vz.72.e84516
Database	NAL-Catalogue (AGRICOLA)

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Article: Formative Study on the Wearability and Usability of a Large-Volume Patch Injector.

Lange, Jakob / Schneider, Andreas / Jordi, Christoph / Lau, Michael / Disher, Timothy

Medical devices (Auckland, N.Z.)

2021 Volume 14, Page(s) 363–377

Abstract: Background: The subcutaneous self-administration of biologics using a single large-volume bolus dose requires novel large-volume patch injectors. However, the usability and wearability of such on-body devices has rarely been investigated thus far. ... ...

Abstract	Background: The subcutaneous self-administration of biologics using a single large-volume bolus dose requires novel large-volume patch injectors. However, the usability and wearability of such on-body devices has rarely been investigated thus far. Therefore, this formative simulated use experiment studies the overall handling and acceptability in terms of the size and weight of a novel 10 mL large-volume patch injector device platform. Methods: Twenty-three participants, including patients and healthcare professionals, simulated two injections with the large-volume patch injector, each lasting 17 min. During the injections, the patient participants performed predefined movements and activities with the on-body devices. Perceived usability and wearability were assessed through observation by the moderator and participant-reported feedback using five-point Likert scales and open-ended interviews. Results: All participants successfully completed the simulated injections. Only non-serious usability issues were identified. Users rated the device acceptability in terms of wearability and usability with high ratings. Conclusion: The results suggest the safe and effective usage of a novel prefilled large-volume patch injector that enables the subcutaneous delivery of a single bolus dose of up to 10 mL with an injection duration of 15 min. The participants of the simulated use study successfully used the device regardless of the disease state, age, or body size and habitus.
Language	English
Publishing date	2021-11-16
Publishing country	New Zealand
Document type	Journal Article
ZDB-ID	2520731-3
ISSN	1179-1470
ISSN	1179-1470
DOI	10.2147/MDER.S337670
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Article: Lullaby: A Novel Algorithm to Extract Fetal QRS in Real Time Using Periodic Trend Feature.

Jilani, Daniel / Le, Tai / Etchells, Tim / Lau, Michael P H / Cao, Hung

IEEE sensors letters

2022 Volume 6, Issue 9

Abstract: Fetal heart rate (fHR) is an important indicator for monitoring of fetal cardiac health and development. The widely-used method based on ultrasound, however, is not continuous and often requires an expert to perform; thus, it is mostly used in clinics ... ...

Abstract	Fetal heart rate (fHR) is an important indicator for monitoring of fetal cardiac health and development. The widely-used method based on ultrasound, however, is not continuous and often requires an expert to perform; thus, it is mostly used in clinics during checkups. The advances in wearable technology have paved the way for home assessment of fHR via the extraction of the mother's abdominal electrocardiogram (ECG) acquired by novel patches. Several methods have been developed for such; however, the computation is either too slow for real-time monitoring or too heavy to be performed in a wearable. In this work, we develop and validate the Lullaby algorithm - a novel method for fetal QRS extraction from aECG. The results showed that Lullaby is almost 7 times faster than existing methods with a better F1-score of 0.815, holding promise to transform perinatal monitoring.
Language	English
Publishing date	2022-08-19
Publishing country	United States
Document type	Journal Article
ISSN	2475-1472
ISSN	2475-1472
DOI	10.1109/lsens.2022.3200072
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Article ; Online: Fetal Electrocardiogram Extraction from the Mother's Abdominal Signal Using the Ensemble Kalman Filter.

Sarafan, Sadaf / Le, Tai / Lau, Michael P H / Hameed, Afshan / Ghirmai, Tadesse / Cao, Hung

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 7

Abstract: Fetal electrocardiogram (fECG) assessment is essential throughout pregnancy to monitor the wellbeing and development of the fetus, and to possibly diagnose potential congenital heart defects. Due to the high noise incorporated in the abdominal ECG (aECG) ...

Abstract	Fetal electrocardiogram (fECG) assessment is essential throughout pregnancy to monitor the wellbeing and development of the fetus, and to possibly diagnose potential congenital heart defects. Due to the high noise incorporated in the abdominal ECG (aECG) signals, the extraction of fECG has been challenging. And it is even a lot more difficult for fECG extraction if only one channel of aECG is provided, i.e., in a compact patch device. In this paper, we propose a novel algorithm based on the Ensemble Kalman filter (EnKF) for non-invasive fECG extraction from a single-channel aECG signal. To assess the performance of the proposed algorithm, we used our own clinical data, obtained from a pilot study with 10 subjects each of 20 min recording, and data from the PhysioNet 2013 Challenge bank with labeled QRS complex annotations. The proposed methodology shows the average positive predictive value (PPV) of 97.59%, sensitivity (SE) of 96.91%, and F1-score of 97.25% from the PhysioNet 2013 Challenge bank. Our results also indicate that the proposed algorithm is reliable and effective, and it outperforms the recently proposed extended Kalman filter (EKF) based algorithm.
MeSH term(s)	Algorithms ; Arrhythmias, Cardiac ; Electrocardiography/methods ; Female ; Fetal Monitoring/methods ; Fetus ; Humans ; Mothers ; Pilot Projects ; Pregnancy ; Signal Processing, Computer-Assisted
Language	English
Publishing date	2022-04-05
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/s22072788
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Article: Enhanced Antioxidant Effects of the Anti-Inflammatory Compound Probucol When Released from Mesoporous Silica Particles.

Lau, Michael / Sealy, Benjamin / Combes, Valery / Morsch, Marco / Garcia-Bennett, Alfonso E

Pharmaceutics

2022 Volume 14, Issue 3

Abstract: Brain endothelial cells mediate the function and integrity of the blood brain barrier (BBB) by restricting its permeability and exposure to potential toxins. However, these cells are highly susceptible to cellular damage caused by oxidative stress and ... ...

Abstract	Brain endothelial cells mediate the function and integrity of the blood brain barrier (BBB) by restricting its permeability and exposure to potential toxins. However, these cells are highly susceptible to cellular damage caused by oxidative stress and inflammation. Consequent disruption to the integrity of the BBB can lead to the pathogenesis of neurodegenerative diseases. Drug compounds with antioxidant and/or anti-inflammatory properties therefore have the potential to preserve the structure and function of the BBB. In this work, we demonstrate the enhanced antioxidative effects of the compound probucol when loaded within mesoporous silica particles (MSP) in vitro and in vivo zebrafish models. The dissolution kinetics were significantly enhanced when released from MSPs. An increased reduction in lipopolysaccharide (LPS)-induced reactive oxygen species (ROS), cyclooxygenase (COX) enzyme activity and prostaglandin E
Language	English
Publishing date	2022-02-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527217-2
ISSN	1999-4923
ISSN	1999-4923
DOI	10.3390/pharmaceutics14030502
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