Association between aerobic fitness and the functional connectome in patients with schizophrenia

Schizophrenia is accompanied by widespread alterations in static functional connectivity associated with symptom severity and cognitive deficits. Improvements in aerobic fitness have been demonstrated to ameliorate symptomatology and cognition in people with schizophrenia, but the intermediary role of macroscale connectivity patterns remains unknown. Therefore, we aim to explore the relation between aerobic fitness and the functional connectome in individuals with schizophrenia. Further, we investigate clinical and cognitive relevance of the identified fitness-connectivity links. 58 patients with schizophrenia were included in the resting-state fMRI analysis. Multilevel Bayesian partial correlations between aerobic fitness and functional connections across the whole brain as well as between static functional connectivity patterns and clinical and cognitive outcome were performed. Preliminary causal inferences were enabled based on a mediation analysis. Static functional connectivity between the subcortical nuclei and the cerebellum as well as between temporal seeds mediated the attenuating impact of aerobic fitness on total symptom severity. Functional connections between cerebellar seeds affected the positive link between aerobic fitness and global cognition, while the functional interplay between central and limbic seeds drove the beneficial relation between aerobic fitness and emotion recognition. The current study provides first insights into the interactions between aerobic fitness, the functional connectome and clinical and cognitive outcome in people with schizophrenia, but results have to be interpreted carefully. Further interventional aerobic exercise studies are needed in order to replicate the current findings and to enable conclusive causal inferences.

Frequency and burden of potentially treatable symptoms in glioma patients with stable disease: a classical and a network approach

Background: Glioma patients experience a multitude of symptoms, impacting health-related quality of life. We aimed to assess frequency and burden of patient-reported symptoms in glioma patients with stable disease and whether patients would consider treatment. We also explored how symptoms co-occur and interact within a network.Methods: Patients rated frequency and burden and whether they would consider treatment of seventeen symptoms. Correlations between frequency, burden, and considering treatment were evaluated with Kendall’s Tau correlation coefficients. Partial correlations between symptom frequency scores were visualized as a symptom network.Results: Fifty-two glioma patients with stable disease were included (31 grade II/III, 21 grade IV tumors). The top five symptoms were fatigue, memory problems, reduced physical fitness, concentration problems, and drowsiness. Fatigue had the highest median frequency, 4.5 with an interquartile range of 2.5, on a seven-point Likert scale. More than 50% of patients experienced three or more symptoms simultaneously. In a network, symptoms seem to cluster together in a Fatigue, Cognition and Anxiety cluster. Overall, about one-third of patients would consider treatment for at least one symptom. Considering treatment correlated only moderately with frequency and burden (range of correlations 0.24-0.57 and 0.28-0.61, respectively).Conclusion: Glioma patients with stable disease often experience multiple co-occurring symptoms with a high symptom burden. Despite the high prevalence of symptoms, the inclination to undergo treatment was relatively low. The most frequent and burdensome symptoms and the way they are interrelated and cluster together could serve as a roadmap for future research on symptom management and treatment.

Emergent fractal phase in energy stratified random models

We study the effects of partial correlations in kinetic hopping terms of long-range disordered random matrix models on their localization properties. We consider a set of models interpolating between fully-localized Richardson’s model and the celebrated Rosenzweig-Porter model (with implemented translation-invariant symmetry). In order to do this, we propose the energy-stratified spectral structure of the hopping term allowing one to decrease the range of correlations gradually. We show both analytically and numerically that any deviation from the completely correlated case leads to the emergent non-ergodic delocalization in the system unlike the predictions of localization of cooperative shielding. In order to describe the models with correlated kinetic terms, we develop the generalization of the Dyson Brownian motion and cavity approaches basing on stochastic matrix process with independent rank-one matrix increments and examine its applicability to the above set of models.

Choroidal thickness and choriocapillaris vascular density in myopic anisometropia

Background This study aims to examine interocular differences in the choroidal thickness and vascular density of the choriocapillaris in anisometropic myopes and to further explore the relationship between choroidal blood flow and myopia. Methods The sample comprised 44 participants with anisometropic myopia, aged 9 to 18 years, with normal best-corrected visual acuity. All participants underwent a series of examinations, including spherical equivalent refraction (SER) and axial length (AL), measured by a Lenstar optical biometer and optical coherence tomography angiography (OCTA) scanner. OCT measured the choroidal thickness, vascular density, and flow voids of the choriocapillaris, and a customized algorithm was implemented in MATLAB R2017a with the post-correction of AL. The choroidal thickness was measured at the fovea and 0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 mm nasally, temporally, inferiorly, and superiorly to the fovea. The vascular density and the flow voids of the choriocapillaris were measured at a 0.6-mm-diameter central circle, and the 0.6–2.5 mm diameter circle in the nasal, temporal, inferior, and superior regions. Repeated-measured ANOVAs were used to analyze the interocular differences. Partial correlations with the K value and age adjustments were used to study the relationships between the choroidal thickness, the choriocapillaris vascular density and flow voids, the SER and AL. Results The choroidal thickness of the more myopic eyes was significantly thinner than less myopic eyes (P ≤ 0.001), and the flow voids in the more myopic eyes were more than less myopic eyes (P = 0.002). There was no significant difference in the vascular density of the choriocapillaris between the more and less myopic eyes (P = 0.525). However, when anisometropia was more than 1.50 D, the vascular density of choriocapillaris in the more myopic eyes was significantly less than the less myopic eyes (P = 0.026). The interocular difference of the choroidal thickness was significantly correlated with the interocular difference in SER and AL in the center, superior, and inferior regions but not in the nasal or temporal regions. The interocular differences of the vascular density and the flow voids of the choriocapillaris were not correlated with the interocular difference of SER and AL. Conclusions The choroidal thickness is thinner in the more myopic eyes. The flow void is increased, and the vascular density of the choriocapillaris is reduced in the more myopic eyes of children with anisometropia exceeding 1.50 D.

Isolated Effects of Indian Ocean Basin-Wide and El Niño–Southern Oscillation on Austral Winter Rainfall over South America

Contrasting effects of the tropical Indian and Pacific Oceans on the atmospheric circulation and rainfall interannual variations over South America during southern winter are assessed considering the effects of the warm Indian Ocean basin-wide (IOBW) and El Niño (EN) events, and of the cold IOBW and La Niña events, which are represented by sea surface temperature-based indices. Analyses are undertaken using total and partial correlations. When the effects of the two warm events are isolated from each other, the contrasts between the associated rainfall anomalies in most of South America become accentuated. In particular, EN relates to anomalous wet conditions, and the warm IOBW event to opposite conditions in extensive areas of the 5° S–25° S band. These effects in the 5° S–15° S sector are due to the anomalous regional Hadley cells, with rising motions in this band for the EN and sinking motions for the warm IOBW event. Meanwhile, in subtropical South America, the opposite effects of the EN and warm IOBW seem to be due to the presence of anomalous anticyclone and cyclone and associated moisture transport, respectively. These opposite effects of the warm IOBW and EN events on the rainfall in part of central South America might explain the weak rainfall relation in this region to the El Niño–Southern Oscillation (ENSO). Our results emphasize the important role of the tropical Indian Ocean in the South American climate and environment during southern winter.

FARCI: Fast and Robust Connectome Inference

The inference of neuronal connectome from large-scale neuronal activity recordings, such as two-photon Calcium imaging, represents an active area of research in computational neuroscience. In this work, we developed FARCI (Fast and Robust Connectome Inference), a MATLAB package for neuronal connectome inference from high-dimensional two-photon Calcium fluorescence data. We employed partial correlations as a measure of the functional association strength between pairs of neurons to reconstruct a neuronal connectome. We demonstrated using in silico datasets from the Neural Connectomics Challenge (NCC) and those generated using the state-of-the-art simulator of Neural Anatomy and Optimal Microscopy (NAOMi) that FARCI provides an accurate connectome and its performance is robust to network sizes, missing neurons, and noise levels. Moreover, FARCI is computationally efficient and highly scalable to large networks. In comparison with the best performing connectome inference algorithm in the NCC, Generalized Transfer Entropy (GTE), and Fluorescence Single Neuron and Network Analysis Package (FluoroSNNAP), FARCI produces more accurate networks over different network sizes, while providing significantly better computational speed and scaling.

Revisiting the Relationships between Fat-to-Protein Ratio in Milk and Energy Balance in Dairy Cows of Different Parities, and at Different Stages of Lactation

A statistical re-assessment of aggregated individual cow data was conducted to examine trends in fat-to-protein ratio in milk (FPR), and relationships between FPR and energy balance (EB, MJ of ME/day) in Holstein-Friesian dairy cows of different parities, and at different stages of lactation. The data were collected from 27 long-term production trials conducted between 1996 and 2016 at the Agri-Food and Biosciences Institute (AFBI) in Hillsborough, Northern Ireland. In total, 1321 lactations (1 to 20 weeks in milk; WIM), derived from 840 individual cows fed mainly grass silage-based diets, were included in the analysis. The energy balance was calculated daily and then averaged weekly for statistical analyses. Data were further split in 4 wk. intervals, namely, 1–4, 5–8, 9–12, 13–16, and 17–20 WIM, and both partial correlations and linear regressions (mixed models) established between the mean FPR and EB during these periods. Three FPR score categories (‘Low’ FPR, <1.0; ‘Normal’ FPR, 1.0–1.5; ‘High’ FPR, >1.5) were adopted and the performance and EB indicators within each category were compared. As expected, multiparous cows experienced a greater negative EB compared to primiparous cows, due to their higher milk production relative to DMI. Relatively minor differences in milk fat and protein content resulted in large differences in FPR curves. Second lactation cows displayed the lowest weekly FPR, and this trend was aligned with smaller BW losses and lower concentrations of non-esterified fatty acids (NEFA) until at least 8 WIM. Partial correlations between FPR and EB were negative, and ‘greatest’ in early lactation (1–4 WIM; r = −0.38 on average), and gradually decreased as lactation progressed across all parities (17–20 WIM; r = −0.14 on average). With increasing parity, daily EB values tended to become more negative per unit of FPR. In primiparous cows, regression slopes between FPR and EB differed between 1–4 and 5–8 WIM (−54.6 vs. −47.5 MJ of ME/day), while differences in second lactation cows tended towards significance (−57.2 vs. −64.4 MJ of ME/day). Irrespective of the lactation number, after 9–12 WIM, there was a consistent trend for the slope of the linear relationships between FPR and EB to decrease as lactation progressed, with this likely reflecting the decreasing milk nutrient demands of the growing calf. The incidence of ‘High’ FPR scores was greatest during 1–4 WIM, and decreased as lactation progressed. ‘High’ FPR scores were associated with increased energy-corrected milk (ECM) yields across all parities and stages of lactation, and with smaller BW gains and increasing concentrations (log transformed) of blood metabolites (non-esterified fatty acid, NEFA; beta-hydroxybutyrate, BHB) until 8 WIM. Results from the present study highlight the strong relationships between FPR in milk, physiological changes, and EB profiles during early lactation. However, while FPR can provide an indication of EB at a herd level, the large cow-to-cow variation indicates that FPR cannot be used as a robust indicator of EB at an individual cow level.

Symptom Correlates Using Network Analysis in Pediatric Patients Undergoing Blood and Marrow Transplant

Introduction: Youth undergoing blood and marrow transplantation (BMT) experience significant distress. The widespread and mainstream use of mHealth technologies such as smartphone applications offer a unique opportunity to collect patient-generated health data that can enhance patients' and clinicians' understanding of symptom onset, trajectories, and inter-relationships. Network analysis (NA) is a useful tool that can illuminate inter-relationships between symptoms, leading to better collective understanding of the symptom experiences of these youths. This knowledge can lead to enhanced patient-caregiver interactions/collaborations, treatment management, and potentially support improved inference around adverse clinical outcomes. Objective: To determine the feasibility of using network analysis to evaluate mHealth symptom data in patients undergoing BMT. Aim 1. Estimate the network by creating a graphic model that depicts symptom inter-relationships. Aim 2. Identify influential symptoms in the network by evaluating centrality indices and assessing the stability of edges and centrality results. Methods : Study participants undergoing BMT recorded daily symptoms via a smartphone app from preconditioning through 120 days. Patients report their symptom experience (intensity and distress on a scale of 0-10). NA was conducted on the initial patients (n=3) to evaluate inter-relationships between reported symptoms. Each symptom is represented by a circle (node), while associations (regularized partial correlations coefficients) between symptoms are depicted as lines (edges). Stronger associations among symptoms present as thicker lines in the network and a higher value in the weighted matrix table. Centrality indices identify and quantify symptoms that exert more influence in the network. These symptoms are influential in the network due to their strength (sum of absolute values of its connections with other nodes), betweenness (number of times a node lies on the shortest path between two other nodes), or closeness (the summed average distance of a node to all other nodes). Other centrality measures also exist. Centrality tests aimed to evaluate symptoms for their reported importance to the youth and association of those symptoms with other reported symptoms. The more "central" a symptom, the higher the potential to transmit effects to and from other symptoms in the network. This can make them important foci for intervention. Stability testing was used to assess the network's accuracy. Results/Discussion: Descriptive statistics are summarized in Table 1. The estimated network (Fig. 1) provided details on the eight most often reported symptoms; nausea, tired (intensity and distress), vomiting, pain, mouth pain, and sore throat (intensity). The network shows strong mutual associations (regularized partial correlations) between the intensity and distress of nausea (.596) and being tired (.722). There was also a strong relationship between mouth pain and sore throat (.791). A less strong relationship was noted between nausea intensity and tired intensity (.145), and tired intensity and pain intensity (.187). A slight negative relationship was noted between vomiting intensity and pain intensity (-.086). The centrality indices (Fig. 2) revealed vomiting intensity (-1.917) as the strongest symptom with the highest closeness (-1.715). The symptom with the highest betweenness centrality was equal for both nausea intensity and tired intensity at 1.286. To assess confidence in the network estimation we replicated this test 1000 times (non-parametric bootstrapping, n=1000) on the edge stability and centrality results (Fig. 3). Results indicate areas with wide confidence intervals (instability) especially in the edge between vomiting intensity and mouth pain. Conclusion: It is feasible to use mHealth data from youth who experience symptom distress during BMT. However, efforts to obtain more data is necessary if we hope to make accurate inferences from the data. Future work will focus on enriching data collection, examining clinically important sign and symptom patterns and interrelationships, and to explore feasibility of using mHealth data for individualized/precision care and possible predictive uses. Figure 1 Figure 1. Disclosures Shah: Novartis: Research Funding, Speakers Bureau; GBT: Consultancy, Research Funding, Speakers Bureau; CSL Behring: Consultancy; Guidepoint Global: Consultancy; Alexion: Speakers Bureau; Bluebird Bio: Consultancy; Emmaus: Consultancy; GLG: Consultancy.

Validation of an Acoustic-Based Framework of Speech Motor Control: Assessing Criterion and Construct Validity Using Kinematic and Perceptual Measures

Purpose This study investigated the criterion (analytical and clinical) and construct (divergent) validity of a novel, acoustic-based framework composed of five key components of motor control: Coordination, Consistency, Speed, Precision, and Rate. Method Acoustic and kinematic analyses were performed on audio recordings from 22 subjects with amyotrophic lateral sclerosis during a sequential motion rate task. Perceptual analyses were completed by two licensed speech-language pathologists, who rated each subject's speech on the five framework components and their overall severity. Analytical and clinical validity were assessed by comparing performance on the acoustic features to their kinematic correlates and to clinician ratings of the five components, respectively. Divergent validity of the acoustic-based framework was then assessed by comparing performance on each pair of acoustic features to determine whether the features represent distinct articulatory constructs. Bivariate correlations and partial correlations with severity as a covariate were conducted for each comparison. Results Results revealed moderate-to-strong analytical validity for every acoustic feature, both with and without controlling for severity, and moderate-to-strong clinical validity for all acoustic features except Coordination, without controlling for severity. When severity was included as a covariate, the strong associations for Speed and Precision became weak. Divergent validity was supported by weak-to-moderate pairwise associations between all acoustic features except Speed (second-formant [F2] slope of consonant transition) and Precision (between-consonant variability in F2 slope). Conclusions This study demonstrated that the acoustic-based framework has potential as an objective, valid, and clinically useful tool for profiling articulatory deficits in individuals with speech motor disorders. The findings also suggest that compared to clinician ratings, instrumental measures are more sensitive to subtle differences in articulatory function. With further research, this framework could provide more accurate and reliable characterizations of articulatory impairment, which may eventually increase clinical confidence in the diagnosis and treatment of patients with different articulatory phenotypes.

Do Hospital Workers Feel They Are Ready to Manage a Sanitary Crisis in a Pre-Crisis Context?

Objective: The aim of this study was to measure the perception of readiness to manage a sanitary crisis for hospital workers and to study the factors related to this perception. Methods: This study was a cross-sectional study; 408 French hospital workers responded to an online questionnaire. The variables studied concerned the perceived personal preparedness, the perception of colleagues’ and hospital’s preparedness, perception of the situation, and preparatory behavioral acts. Correlations, partial correlations, and multiple linear regressions were applied. Results: Based on Pearson’s correlations, the higher the participants’ sense of personal efficacy and control over their behavior, the more ready they feel (r p = 0.77*** and r p = 0.55***). The more participants perceive their colleagues as ready and their hospital as prepared, the more ready they feel (r p = 0.52*** and r p = 0.46***). Based on Pearson’s partial correlations, upon controlling the effect of preparedness perception, declared preparedness is not significantly correlated with personal readiness perception (r p = 0.01). Conclusion: The perception of personal readiness does not depend only on actual preparedness but also on individual and collective variables. Technically, these results confirm the value of relying on psychosocial variables during training. It would be interesting to propose empowerment in training courses. It also seems necessary to demonstrate crisis management efficacy at different levels: institutional, collective, and individual.