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Article: Pharmacokinetics of Cannabis and Its Derivatives in Animals and Humans During Pregnancy and Breastfeeding.

Monfort, Anaëlle / Ferreira, Ema / Leclair, Grégoire / Lodygensky, Gregory Anton

2022 Volume 13, Page(s) 919630

Abstract: Cannabis is one of the most widely used illicit drugs during pregnancy and lactation. With the recent legalization of cannabis in many countries, health professionals are increasingly exposed to pregnant and breastfeeding women who are consuming cannabis ...

Abstract	Cannabis is one of the most widely used illicit drugs during pregnancy and lactation. With the recent legalization of cannabis in many countries, health professionals are increasingly exposed to pregnant and breastfeeding women who are consuming cannabis on a regular basis as a solution for depression, anxiety, nausea, and pain. Cannabis consumption during pregnancy can induce negative birth outcomes such as reduced birth weight and increased risk of prematurity and admission to the neonatal intensive care unit. Yet, limited information is available regarding the pharmacokinetics of cannabis in the fetus and newborn exposed during pregnancy and lactation. Indeed, the official recommendations regarding the use of cannabis during these two critical development periods lack robust pharmacokinetics data and make it difficult for health professionals to guide their patients. Many clinical studies are currently evaluating the effects of cannabis on the brain development and base their groups mostly on questionnaires. These studies should be associated with pharmacokinetics studies to assess correlations between the infant brain development and the exposure to cannabis during pregnancy and breastfeeding. Our project aims to review the available data on the pharmacokinetics of cannabinoids in adults, neonates, and animals. If the available literature is abundant in adult humans and animals, there is still a lack of published data on the exposure of pregnant and lactating women and neonates. However, some of the published information causes concerns on the exposure and the potential effects of cannabis on fetuses and neonates. The safety of cannabis use for non-medical purpose during pregnancy and breastfeeding needs to be further characterized with proper pharmacokinetic studies in humans feasible in regions where cannabis has been legalized. Given the available data, significant transfer occurs to the fetus and the breastfed newborn with a theoretical risk of accumulation of products known to be biologically active.
Language	English
Publishing date	2022-07-12
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2587355-6
ISSN	1663-9812
ISSN	1663-9812
DOI	10.3389/fphar.2022.919630
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Book ; Online: Harmonizing Flows

Beizaee, Farzad / Desrosiers, Christian / Lodygensky, Gregory A. / Dolz, Jose

Unsupervised MR harmonization based on normalizing flows

2023

Abstract: In this paper, we propose an unsupervised framework based on normalizing flows that harmonizes MR images to mimic the distribution of the source domain. The proposed framework consists of three steps. First, a shallow harmonizer network is trained to ... ...

Abstract	In this paper, we propose an unsupervised framework based on normalizing flows that harmonizes MR images to mimic the distribution of the source domain. The proposed framework consists of three steps. First, a shallow harmonizer network is trained to recover images of the source domain from their augmented versions. A normalizing flow network is then trained to learn the distribution of the source domain. Finally, at test time, a harmonizer network is modified so that the output images match the source domain's distribution learned by the normalizing flow model. Our unsupervised, source-free and task-independent approach is evaluated on cross-domain brain MRI segmentation using data from four different sites. Results demonstrate its superior performance compared to existing methods. Comment: 10 pages
Keywords	Computer Science - Computer Vision and Pattern Recognition
Publishing date	2023-01-27
Publishing country	us
Document type	Book ; Online
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Article ; Online: Soft, Conductive, and Anti‐Freezing Conducting Polymer Organohydrogels

Xin Zhou / Pierre Kateb / Floriane Miquet‐Westphal / Gregory A. Lodygensky / Fabio Cicoira

Advanced Sensor Research, Vol 2, Iss 12, Pp n/a-n/a (2023)

2023

Abstract: Abstract Soft and conductive materials are highly desirable for wearable electronics. In particular, anti‐freezing, long‐water retention, and highly conductive gels with Young's modulus matching that of biological tissues, show promise in bioelectronics. ...

Abstract	Abstract Soft and conductive materials are highly desirable for wearable electronics. In particular, anti‐freezing, long‐water retention, and highly conductive gels with Young's modulus matching that of biological tissues, show promise in bioelectronics. Herein, soft organohydrogels obtained by mixing poly (3,4‐ethylenedioxythiophene) doped with polystyrene sulfonate (PEDOT:PSS), ethylene glycol (EG), and tannic acid (TA) are reported. The PEDOT/EG/TA organohydrogels exhibit a low compressive Young's modulus of ≈20 kPa, a conductivity of ≈6 S cm−1, as well as anti‐freezing and water retention properties. Epidermal patch electrodes prepared using the PEDOT/EG/TA gel exhibit low skin–electrode impedance at low frequency (1–100 Hz) and high‐quality electrocardiography (ECG) and electromyography signal recordings. Moreover, these gels demonstrate long‐term stability with high ECG recording quality after being placed under ambient conditions for seven days.
Keywords	anti‐freezing ; high conductivity ; long‐water retention ; organohydrogels ; PEDOT:PSS ; Technology (General) ; T1-995 ; Science ; Q
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Wiley-VCH
Document type	Article ; Online
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Article ; Online: Non-invasive in vivo MRI detects long-term microstructural brain alterations related to learning and memory impairments in a model of inflammation-induced white matter injury.

Pierre, Wyston C / Zhang, Erjun / Londono, Irène / De Leener, Benjamin / Lesage, Frédéric / Lodygensky, Gregory A

Behavioural brain research

2022 Volume 428, Page(s) 113884

Abstract: Magnetic resonance imaging (MRI) is currently under investigation as a non-invasive tool to monitor neurodevelopmental trajectories and predict risk of cognitive deficits following white matter injury (WMI) in very preterm infants. In the present study, ... ...

Abstract	Magnetic resonance imaging (MRI) is currently under investigation as a non-invasive tool to monitor neurodevelopmental trajectories and predict risk of cognitive deficits following white matter injury (WMI) in very preterm infants. In the present study, we evaluated the capacity of multimodal MRI (high-resolution T2-weighted imaging and diffusion tensor imaging)to assess changes following WMI and their relationship to learning and memory performance in Wistar rats as it has been demonstrated for preterm infants. Multimodal MRI performed at P31-P32 shown that animals exposed to neonatal LPS could be classified into two groups: minimal and overt injury. Animals with overt injury had significantly enlarged ventricles, hippocampal atrophy, diffusivity changes in hippocampal white and gray matter, in the striatum and the cortex. Following neonatal LPS exposure, animals presented learning and memory impairments as shown at the fear conditioning test at P36-P38. The severity of learning and memory deficits was related to increased mean diffusivity in the hippocampal region. In conclusion, non-invasive multimodal MRI (volumetric and DTI) assessed and classified the extent of injury at long-term following neonatal LPS exposure. Microstructural changes in the hippocampus at DTI were associated to learning and memory impairments. This further highlights the utility of multimodal MRI as a non-invasive quantitative biomarker following perinatal inflammation.
MeSH term(s)	Animals ; Brain/diagnostic imaging ; Brain Injuries/pathology ; Diffusion Tensor Imaging/methods ; Female ; Humans ; Infant, Newborn ; Infant, Premature ; Inflammation/chemically induced ; Inflammation/diagnostic imaging ; Inflammation/pathology ; Lipopolysaccharides ; Magnetic Resonance Imaging/methods ; Memory Disorders/diagnostic imaging ; Memory Disorders/etiology ; Memory Disorders/pathology ; Pregnancy ; Rats ; Rats, Wistar ; White Matter/diagnostic imaging ; White Matter/pathology
Chemical Substances	Lipopolysaccharides
Language	English
Publishing date	2022-04-06
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	449927-x
ISSN	1872-7549 ; 0166-4328
ISSN (online)	1872-7549
ISSN	0166-4328
DOI	10.1016/j.bbr.2022.113884
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Article ; Online: Toward quantitative MRI analysis: A smart approach to characterize neonatal white matter injury.

Lodygensky, Gregory A / Thompson, Deanne K

Neurology

2017 Volume 88, Issue 7, Page(s) 610–611

MeSH term(s)	Female ; Humans ; Image Processing, Computer-Assisted/methods ; Infant ; Infant, Newborn ; Leukoencephalopathies/diagnostic imaging ; Magnetic Resonance Imaging/methods ; Male
Language	English
Publishing date	2017-01-18
Publishing country	United States
Document type	Editorial
ZDB-ID	207147-2
ISSN	1526-632X ; 0028-3878
ISSN (online)	1526-632X
ISSN	0028-3878
DOI	10.1212/WNL.0000000000003621
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Article ; Online: Modulatory effect of IL-1 inhibition following lipopolysaccharide-induced neuroinflammation in neonatal microglia and astrocytes.

Pierre, Wyston C / Londono, Irène / Quiniou, Christiane / Chemtob, Sylvain / Lodygensky, Gregory A

International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience

2022 Volume 82, Issue 3, Page(s) 243–260

Abstract: Introduction: Inflammation-induced white matter injury (WMI) in preterm infants is characterized by microglia activation, astrogliosis, oxidative stress and neurodevelopmental impairments. Microglia and astrocytes activation can be described under a ... ...

Abstract	Introduction: Inflammation-induced white matter injury (WMI) in preterm infants is characterized by microglia activation, astrogliosis, oxidative stress and neurodevelopmental impairments. Microglia and astrocytes activation can be described under a broad spectrum of activation profile with extremes described as pro-inflammatory/neurotoxic (M1 microglia or A1 astrocyte) or anti-inflammatory/neuroprotective (M2 microglia or A2 astrocyte) in response to stimuli including lipopolysaccharide (LPS) and interleukin 1 (IL-1). As IL-1 signalling pathway has been posited as a major driver of inflammation-induced perinatal WMI, our aim was to evaluate the contribution of IL-1 modulation in LPS-induced microglia and astrocyte activation. Methods: Primary neonatal cell co-cultures of astrocytes and microglia were treated with LPS (100 ng/ml) for 8 h or 24 h. Two distinct IL-1 receptor antagonists, Rytvela or Kineret (1 μg/ml), were added simultaneously with LPS to respectively modulate or block IL-1 receptor. Medium was collected to measure levels of IL-1β. Expression of markers related to pro- and anti-inflammatory microglia and astrocyte activation profiles and antioxidant genes were assessed. Results: At 8 h, LPS exposure induced pro- (M1/A1) and anti-inflammatory (M2/A2) marker expression and inhibited antioxidant gene expression in microglia and astrocytes. By 24 h, continuous LPS exposure increased pro-inflammatory and neurotoxic microglial and astrocytic markers (M1/A1), as well as antioxidant genes. Administration of IL-1 antagonists Rytvela and Kineret with continuous LPS exposure had no significant effect on modulation of specific microglia and astrocyte activation pathways. Discussion/conclusion: We show that LPS effects on in vitro neonatal microglia and astrocytes co-cultures are time dependent eliciting a number of pro- and anti-inflammatory responses during the acute phase of inflammation (8 h), which shift towards pro-inflammatory and neurotoxic factors by 24 h. Although LPS-induced inflammation led to abundant IL-1 expression, IL-1 inhibition had no significant impact on in vitro modulation of microglia and astrocyte activation pathways towards M2 and A2 activation profile.
MeSH term(s)	Anti-Inflammatory Agents/metabolism ; Anti-Inflammatory Agents/pharmacology ; Anti-Inflammatory Agents/therapeutic use ; Antioxidants/metabolism ; Astrocytes/metabolism ; Cells, Cultured ; Female ; Humans ; Infant, Newborn ; Infant, Premature ; Inflammation/metabolism ; Interleukin 1 Receptor Antagonist Protein/metabolism ; Interleukin 1 Receptor Antagonist Protein/pharmacology ; Interleukin 1 Receptor Antagonist Protein/therapeutic use ; Lipopolysaccharides/toxicity ; Microglia/metabolism ; Neuroinflammatory Diseases ; Neurotoxicity Syndromes ; Pregnancy ; Receptors, Interleukin-1/metabolism ; Receptors, Interleukin-1/therapeutic use
Chemical Substances	Anti-Inflammatory Agents ; Antioxidants ; Interleukin 1 Receptor Antagonist Protein ; Lipopolysaccharides ; Receptors, Interleukin-1
Language	English
Publishing date	2022-03-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	605533-3
ISSN	1873-474X ; 0736-5748
ISSN (online)	1873-474X
ISSN	0736-5748
DOI	10.1002/jdn.10179
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Article ; Online: Determining regional brain growth in premature and mature infants in relation to age at MRI using deep neural networks.

Beizaee, Farzad / Bona, Michele / Desrosiers, Christian / Dolz, Jose / Lodygensky, Gregory

Scientific reports

2023 Volume 13, Issue 1, Page(s) 13259

Abstract: Neonatal MRIs are used increasingly in preterm infants. However, it is not always feasible to analyze this data. Having a tool that assesses brain maturation during this period of extraordinary changes would be immensely helpful. Approaches based on deep ...

Abstract	Neonatal MRIs are used increasingly in preterm infants. However, it is not always feasible to analyze this data. Having a tool that assesses brain maturation during this period of extraordinary changes would be immensely helpful. Approaches based on deep learning approaches could solve this task since, once properly trained and validated, they can be used in practically any system and provide holistic quantitative information in a matter of minutes. However, one major deterrent for radiologists is that these tools are not easily interpretable. Indeed, it is important that structures driving the results be detailed and survive comparison to the available literature. To solve these challenges, we propose an interpretable pipeline based on deep learning to predict postmenstrual age at scan, a key measure for assessing neonatal brain development. For this purpose, we train a state-of-the-art deep neural network to segment the brain into 87 different regions using normal preterm and term infants from the dHCP study. We then extract informative features for brain age estimation using the segmented MRIs and predict the brain age at scan with a regression model. The proposed framework achieves a mean absolute error of 0.46 weeks to predict postmenstrual age at scan. While our model is based solely on structural T2-weighted images, the results are superior to recent, arguably more complex approaches. Furthermore, based on the extracted knowledge from the trained models, we found that frontal and parietal lobes are among the most important structures for neonatal brain age estimation.
MeSH term(s)	Female ; Humans ; Infant, Newborn ; Infant ; Infant, Premature ; Brain/diagnostic imaging ; Magnetic Resonance Imaging/methods ; Premature Birth ; Neural Networks, Computer
Language	English
Publishing date	2023-08-15
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/s41598-023-40244-z
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Article ; Online: Erratum to 'Self-healing, stretchable and highly adhesive hydrogels for epidermal patch electrodes' [Acta Biomaterialia 139 (2022) 296-306].

Zhou, Xin / Rajeev, Ashna / Subramanian, Arunprabaharan / Li, Yang / Rossetti, Nicolò / Natale, Giovanniantonio / Lodygensky, Gregory A / Cicoira, Fabio

Acta biomaterialia

2022 Volume 145, Page(s) 436

Language	English
Publishing date	2022-04-26
Publishing country	England
Document type	Published Erratum
ZDB-ID	2173841-5
ISSN	1878-7568 ; 1742-7061
ISSN (online)	1878-7568
ISSN	1742-7061
DOI	10.1016/j.actbio.2022.04.018
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Article ; Online: Recent advances in preclinical and clinical multimodal MR in the newborn brain.

Enguix, Vicente / Ding, Yang / Lodygensky, Gregory A

Journal of magnetic resonance (San Diego, Calif. : 1997)

2018 Volume 292, Page(s) 149–154

Abstract: Aside from injury identification, MRI of the newborn brain has given us insight into cortical and white matter development, identified windows of vulnerabilities, enabled the introduction of therapeutic hypothermia which has become the standard of care ... ...

Abstract	Aside from injury identification, MRI of the newborn brain has given us insight into cortical and white matter development, identified windows of vulnerabilities, enabled the introduction of therapeutic hypothermia which has become the standard of care in neonatal asphyxia, and is fostering leapfrogging discoveries in the field of neuro-genetics. This article reviews the main advances in recent years in newborn brain imaging both in preclinical and clinical research.
MeSH term(s)	Adult ; Animals ; Animals, Newborn ; Brain/diagnostic imaging ; Female ; Humans ; Infant, Newborn ; Infant, Newborn, Diseases/diagnostic imaging ; Magnetic Resonance Imaging/methods ; Pregnancy
Language	English
Publishing date	2018-04-30
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1469665-4
ISSN	1096-0856 ; 1557-8968 ; 1090-7807 ; 0022-2364
ISSN (online)	1096-0856 ; 1557-8968
ISSN	1090-7807 ; 0022-2364
DOI	10.1016/j.jmr.2018.04.017
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Article ; Online: Mild Neonatal Encephalopathy-How, When, and How Much to Treat?

Lodygensky, Gregory A / Battin, Malcolm R / Gunn, Alistair J

JAMA pediatrics

2017 Volume 172, Issue 1, Page(s) 3–4

MeSH term(s)	Disease Progression ; Humans ; Hypoxia-Ischemia, Brain/diagnosis ; Hypoxia-Ischemia, Brain/therapy ; Infant, Newborn ; Prognosis ; Severity of Illness Index
Language	English
Publishing date	2017-11-04
Publishing country	United States
Document type	Journal Article
ZDB-ID	2701223-2
ISSN	2168-6211 ; 2168-6203
ISSN (online)	2168-6211
ISSN	2168-6203
DOI	10.1001/jamapediatrics.2017.3044
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