Dietary and serum tyrosine, white matter microstructure and inter-individual variability in executive functions in overweight adults: Relation to sex/gender and age

Tyrosine (tyr), the precursor of the neurotransmitter dopamine, is known to modulate cognitive functions including executive attention. Tyr supplementation is suggested to influence dopamine-modulated cognitive performance. However, results are inconclusive regarding the presence or strength and also the direction of the association between tyr and cognitive function. This pre-registered cross-sectional analysis investigates whether diet-associated serum tyr relates to executive attention performance, and whether this relationship is moderated by differences in white matter microstructure. 59 healthy, overweight, young to middle-aged adults (20 female, 28.3 ± 6.6 years, BMI: 27.3 ± 1.5 kg/m2) drawn from a longitudinal study reported dietary habits, donated blood and completed diffusion-weighted brain magnetic resonance imaging and the attention network test. Main analyses were performed using linear regressions and non-parametric voxel-wise inference testing. Confirmatory analyses did neither support an association between dietary and serum tyr nor a relationship between relative serum tyr/large neutral amino acids (LNAA) levels or white matter microstructure and executive attention performance. However, exploratory analyses revealed higher tyr intake, higher serum tyr and better executive attention performance in the male sex/gender group. In addition, older age was associated with higher dietary tyr intake and lower fractional anisotropy in a widespread cluster across the brain. Finally, a positive association between relative serum tyr/LNAA and executive attention performance was found in the male sex/gender group when accounting for age effects. Our analysis advances the field of dopamine-modulated cognitive functions by revealing sex/gender and age differences which might be diet-related. Longitudinal or intervention studies and larger sample sizes are needed to provide more reliable evidence for links between tyr and executive attention

Longitudinal 7T MRI reveals volumetric changes in subregions of human medial temporal lobe to sex hormone fluctuations

The hippocampus and surrounding medial temporal lobe (MTL) are critical for memory processes, with local atrophy linked to memory deficits. Animal work shows that MTL subregions densely express sex hormone receptors and exhibit rapid structural changes synchronized with hormone fluctuations. Such transient effects in humans have thus far not been shown. By combining a dense-sampling protocol, ultra-high field neuroimaging and individually-derived segmentation analysis, we demonstrate how estradiol and progesterone fluctuations affect MTL subregion volumes across the human menstrual cycle. Twenty-seven healthy women (19-34 years) underwent 7T MRI at six timepoints to acquire T1-weighted and T2-weighted images. Linear mixed-effects modeling showed positive associations between estradiol and parahippocampal cortex volume, progesterone and subiculum and perirhinal Area 35 volumes, and an estradiol*progesterone interaction with CA1 volume. We confirmed volumetric changes were not driven by hormone-related water (cerebral spinal fluid) or blood-flow (pulsed arterial spin labeling) changes. These findings suggest that sex hormones alter structural brain plasticity in subregions that are differentially sensitive to hormones. Mapping how endogenous endocrine factors shape adult brain structure has critical implications for women’s health during the reproductive years as well as later in life, such as increased dementia risk following perimenopause, a period of pronounced sex hormone fluctuations

One‐week escitalopram intake alters the excitation–inhibition balance in the healthy female brain

Neural health relies on cortical excitation-inhibition balance (EIB). Previous research suggests a link between increased cortical excitation and neuroplasticity induced by selective serotonin reuptake inhibitors (SSRIs). Whether there are modulations of EIB following SSRI-administration in the healthy human brain, however, remains unclear. Thus, in a randomized double-blind study, we administered a clinically relevant dose of 20 mg escitalopram for 7 days (time when steady state is achieved) in 59 healthy women (28 escitalopram, 31 placebo) on oral contraceptives. We acquired resting-state electroencephalography data at baseline, after a single dose, and at steady state. We assessed 1/f slope of the power spectrum as a marker of EIB, compared individual trajectories of 1/f slope changes contrasting single dose and 1-week drug intake, and tested the relationship of escitalopram plasma levels and cortical excitatory and inhibitory balance shifts. Escitalopram-intake was associated with decreased 1/f slope, indicating an EIB shift in favor of excitation. Furthermore, 1/f slope at baseline and after a single dose of escitalopram was associated with 1/f slope at steady state. Higher plasma escitalopram levels at a single dose were associated with better maintenance of these EIB changes throughout the drug administration week. These findings demonstrate the potential for 1/f slope to predict individual cortical responsivity to SSRIs and widen the lens through which we map the human brain by testing an interventional psychopharmacological design in a clearly defined endocrinological state

The attention-emotion interaction in healthy female participants on oral contraceptives during 1-week escitalopram intake

Previous findings in healthy humans suggest that selective serotonin reuptake inhibitors (SSRIs) modulate emotional processing via earlier changes in attention. However, many previous studies have provided inconsistent findings. One possible reason for such inconsistencies is that these studies did not control for the influence of either sex or sex hormone fluctuations. To address this inconsistency, we administered 20 mg escitalopram or placebo for seven consecutive days in a randomized, double-blind, placebo-controlled design to sixty healthy female participants with a minimum of 3 months oral contraceptive (OC) intake. Participants performed a modified version of an emotional flanker task before drug administration, after a single dose, after 1 week of SSRI intake, and after a 1-month wash-out period. Supported by Bayesian analyses, our results do not suggest a modulatory effect of escitalopram on behavioral measures of early attentional-emotional interaction in female individuals with regular OC use. While the specific conditions of our task may be a contributing factor, it is also possible that a practice effect in a healthy sample may mask the effects of escitalopram on the attentional-emotional interplay. Consequently, 1 week of escitalopram administration may not modulate attention toward negative emotional distractors outside the focus of attention in healthy female participants taking OCs. While further research in naturally cycling females and patient samples is needed, our results represent a valuable contribution toward the preclinical investigation of antidepressant treatment

Decreased thalamo-cortico connectivity during an implicit sequence motor learning task and 7 days escitalopram intake

Evidence suggests that selective serotonin reuptake inhibitors (SSRIs) reorganize neural networks via a transient window of neuroplasticity. While previous findings support an effect of SSRIs on intrinsic functional connectivity, little is known regarding the influence of SSRI-administration on connectivity during sequence motor learning. To investigate this, we administered 20 mg escitalopram or placebo for 1-week to 60 healthy female participants undergoing concurrent functional magnetic resonance imaging and sequence motor training in a double-blind randomized controlled design. We assessed task-modulated functional connectivity with a psycho-physiological interaction (PPI) analysis in the thalamus, putamen, cerebellum, dorsal premotor, primary motor, supplementary motor, and dorsolateral prefrontal cortices. Comparing an implicit sequence learning condition to a control learning condition, we observed decreased connectivity between the thalamus and bilateral motor regions after 7 days of escitalopram intake. Additionally, we observed a negative correlation between plasma escitalopram levels and PPI connectivity changes, with higher escitalopram levels being associated with greater thalamo-cortico decreases. Our results suggest that escitalopram enhances network-level processing efficiency during sequence motor learning, despite no changes in behaviour. Future studies in more diverse samples, however, with quantitative imaging of neurochemical markers of excitation and inhibition, are necessary to further assess neural responses to escitalopram

Shedding light on the elusive role of endothelial cells in cytomegalovirus dissemination.

Cytomegalovirus (CMV) is frequently transmitted by solid organ transplantation and is associated with graft failure. By forming the boundary between circulation and organ parenchyma, endothelial cells (EC) are suited for bidirectional virus spread from and to the transplant. We applied Cre/loxP-mediated green-fluorescence-tagging of EC-derived murine CMV (MCMV) to quantify the role of infected EC in transplantation-associated CMV dissemination in the mouse model. Both EC- and non-EC-derived virus originating from infected Tie2-cre(+) heart and kidney transplants were readily transmitted to MCMV-naïve recipients by primary viremia. In contrast, when a Tie2-cre(+) transplant was infected by primary viremia in an infected recipient, the recombined EC-derived virus poorly spread to recipient tissues. Similarly, in reverse direction, EC-derived virus from infected Tie2-cre(+) recipient tissues poorly spread to the transplant. These data contradict any privileged role of EC in CMV dissemination and challenge an indiscriminate applicability of the primary and secondary viremia concept of virus dissemination

Association of estradiol and visceral fat with structural brain networks and memory performance in adults

Importance Changes in estradiol during aging are associated with increased dementia risk. It remains unclear how estradiol supports cognitive health and whether risk factors, such as midlife obesity, are exacerbated by estrogen loss. Objectives To assess whether visceral adipose tissue (VAT) moderates the association between age and brain network structure and to investigate whether estradiol moderates the association between VAT and brain network structure. Design, Setting, and Participants Cross-sectional study of data from 974 cognitively healthy adults in Germany who participated in the Health Study of the Leipzig Research Centre for Civilization Diseases, a previously described population-based cohort study. Two moderation analyses were performed, including VAT as the moderator variable between age and brain network structure and estradiol as the moderator variable between VAT and brain network structure. The study was conducted from August 1, 2011, to November 23, 2014. Analyses were conducted from August 2017 to September 201

Acute safety, effectiveness, and real-world clinical usage of ultra-high density mapping for ablation of cardiac arrhythmias: results of the TRUE HD study

AIMS: The objective of this study was to verify acute safety, performance, and usage of a novel ultra-high density mapping system in patients undergoing ablation procedure in a real-world clinical setting. METHODS AND RESULTS: The TRUE HD study enrolled patients undergoing catheter ablation with mapping for all arrhythmias (excluding de novo atrial fibrillation) who were followed for 1 month. Safety was determined by collecting all serious adverse events and adverse events associated with the study devices. Performance was determined as the composite of: ability to map the arrhythmia/substrate, complete the ablation applications, arrhythmia termination (where applicable), and ablation validation. Use of mapping system in the ablation validation workflow was also evaluated. Among the 519 patients who underwent a complete (504) or attempted (15) procedure, 21 (4%) serious ablation-related complications were collected, with 3 (0.57%) potentially related to the mapping catheter. Four hundred and twenty treated patients resulted in a successful procedure confirmed by arrhythmia-specific validation techniques (83.3%; 95% confidence interval: 79.8-86.5%). A total of 1419 electroanatomical maps were created with a median acquisition time of 9:23 min per map. Of these, 372 maps in 222 (44%) patients were collected for ablation validation purposes. Following validation mapping, 162/222 (73%) patients required additional ablation. CONCLUSION: In the TRUE HD study mapping was associated with rates of acute success and complications consistent with previously published reports. Importantly, a low percentage of events (0.57%) was attributed to the mapping catheter. When performed, validation mapping was useful for identifying additional targets for ablation in the majority of patients

MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response

Predicting clinical outcome is remarkably important but challenging. Research efforts have been paid on seeking significant biomarkers associated with the therapy response or/and patient survival. However, these biomarkers are generally costly and invasive, and possibly dissatifactory for novel therapy. On the other hand, multi-modal, heterogeneous, unaligned temporal data is continuously generated in clinical practice. This paper aims at a unified deep learning approach to predict patient prognosis and therapy response, with easily accessible data, e.g., radiographics, laboratory and clinical information. Prior arts focus on modeling single data modality, or ignore the temporal changes. Importantly, the clinical time series is asynchronous in practice, i.e., recorded with irregular intervals. In this study, we formalize the prognosis modeling as a multi-modal asynchronous time series classification task, and propose a MIA-Prognosis framework with Measurement, Intervention and Assessment (MIA) information to predict therapy response, where a Simple Temporal Attention (SimTA) module is developed to process the asynchronous time series. Experiments on synthetic dataset validate the superiory of SimTA over standard RNN-based approaches. Furthermore, we experiment the proposed method on an in-house, retrospective dataset of real-world non-small cell lung cancer patients under anti-PD-1 immunotherapy. The proposed method achieves promising performance on predicting the immunotherapy response. Notably, our predictive model could further stratify low-risk and high-risk patients in terms of long-term survival.Comment: MICCAI 2020 (Early Accepted; Student Travel Award