Covariance Structure Research Articles

Comparative evaluation of interpretation methods in surface-based age prediction for neonates

Significant changes in brain morphology occur during the third trimester of gestation. The capability of deep learning in leveraging these morphological features has enhanced the accuracy of brain age predictions for this critical period. Yet, the opaque nature of deep learning techniques, often described as "black box" approaches, limits their interpretability, posing challenges in clinical applications. Traditional interpretable methods developed for computer vision and natural language processing may not directly translate to the distinct demands of neuroimaging. In response, our research evaluates the effectiveness and adaptability of two interpretative methods—regional age prediction and the perturbation-based saliency map approach—for predicting the brain age of neonates. Analyzing 664 T1 MRI scans with the NEOCIVET pipeline to extract brain surface and cortical features, we assess how these methods illuminate key brain regions for age prediction, focusing on technical analysis with clinical insight. Through a comparative analysis of the saliency index (SI) with relative brain age (RBA) and the examination of structural covariance networks, we uncover the saliency index's enhanced ability to pinpoint regions vital for accurate indication of clinical factors. Our results highlight the advantages of perturbation techniques in addressing the complexities of medical data, steering clinical interventions for premature neonates towards more personalized and interpretable approaches. This study not only reveals the promise of these methods in complex medical scenarios but also offers a blueprint for implementing more interpretable and clinically relevant deep learning models in healthcare settings.

An empirical investigation of health dynamics of elders in China

Using data from the China Health and Nutrition Survey (CHNS), an index of health frailty is developed for individuals ages fifty-five and older. The evolution of the Frailty Index with age is first contrasted with self-reports of health. Then the temporal moments of the data are examined by considering the covariance structure of shocks that arrive at different ages with frailty in subsequent years. Then a formal model is estimated that incorporates both age-dependent auto-regressive and transitory components. The covariance structure of frailty is found to be convex in age. Larger shocks arrive as the sample ages but they decline rapidly. The evolutions of shocks beyond a specific age are modestly persistent (auto-regressive). The initial age-dependent transitory shocks become a larger portion of the total health risk as age increases.

227 Moderate body weight loss reduces total antioxidant capacity in pregnant beef heifers and one-carbon metabolite supplementation does not mitigate this response

Abstract In beef heifers, body weight (BW) gain and physiological stress are important considerations for reproductive outcomes and whole herd production efficiencies. The objective of this study was to determine if dietary one-carbon metabolite (OCM) supplementation in moderate BW loss pregnant heifers alters circulating total antioxidant capacity, superoxide dismutase, and glutathione peroxidase activity. In a replicated 2 × 2 factorial, Angus-cross heifers (n = 81) were stratified by BW to gain 0.45 kg/d (CON) or lose 0.23 kg/d (RES) and receive corn carrier with OCM supplements (+OCM) or without (−OCM). The OCM supplements consisted of vitamin B12 (20 mg) and folate (320 mg) injections weekly and dietary rumen-protected methionine (7.4 g/d) and choline (44.4 g/d) from breeding (d 0) to d 63 of gestation. The four treatment groups were: CON−OCM (n = 20), CON+OCM (n = 21), RES−OCM (n = 21), and RES+OCM (n = 19). Heifers underwent estrus synchronization and were bred via artificial insemination using female sexed semen to a single sire. Pregnancy was diagnosed and fetal sex was verified on d 35 of gestation. Blood was collected and assayed for total antioxidant capacity, superoxide dismutase, and glutathione peroxidase activity on d −2 (baseline), 35, and 63 of gestation for all three replicates. Data were analyzed using the MIXED procedure of SAS with repeated measures to determine the effect of gain, supplement, day, and their two-way and three-way interactions. The gain × supplement interaction remained in all models, but other interactions were removed if P > 0.10. Replicate and heifer BW were included in the model as covariates and covariance structure was determined by lowest AIC and BIC. Statistical significance was considered at P ≤ 0.05 and tendencies at 0.05 < P ≤ 0.10. There was no BW gain × supplement interaction, or main effect of OCM supplements in total antioxidants. There was a gain × day effect (P ≤ 0.01), in which total antioxidants were increased on d 35 and further increased on d 63 in CON compared with RES treatments. There was no gain × supplement interaction, or main effect of gain or OCM supplements in superoxide dismutase and glutathione peroxidase. However, both superoxide dismutase and glutathione peroxidase were decreased (P ≤ 0.01) on d 63 compared with d 0 and 35. These data suggest that moderate BW loss reduces total antioxidant capacity in pregnant beef heifers, which could affect redox homeostasis. However, OCM supplements did not affect total antioxidant capacity, superoxide dismutase, or glutathione peroxidase. These findings are somewhat surprising considering oxidative stress has been well characterized in nutrient-restricted pregnancies, and given the interconnection between energy metabolism and one-carbon metabolism. Future research is warranted to fully elucidate the therapeutic effects of one-carbon metabolites.

260 Industrial hemp (Cannabis sativa) supplementation improved plasma antioxidant enzymes and stress hormones in beef cattle

Abstract Industrial hemp is a rich source of antioxidants due to its high CBD but there is little information known about its impact on plasma antioxidant enzyme activity and stress hormone in beef cattle. The objective of this study was to determine the effect of industrial hemp supplementation on plasma antioxidant enzymes and stress hormone of Angus cattle. Black Angus heifers (n = 20) were completely randomized into either control (CON: n = 10, receiving 0 g of hemp) or hemp (HEMP: n = 10, receiving 30 g of hemp in 200 g of commercial concentrate) in a trial that lasted for 6 wk. Each group was replicated twice. Hay and water were offered ad libitum, experimental diets were offered o700 h daily. Blood samples were collected on d 0, 7, 14, 21, 28, 35 of the experiment for enzyme-linked immunosorbent assay to determine enzyme activity using standard kits. Data were analyzed using GLIMMIX procedure for repeated measure in SAS 9.4 with Compound symmetry as covariance structure while means were separated with Tukey at 5% alpha. There was significant (P < 0.05) difference in cortisol with HEMP group having 97.54 ng/mL and 122.23 ng/mL for CON. There was treatment x time interaction in total antioxidant capacity (TAOC) and malondialdehyde, TAOC range was 7.26 to 13.95 U/mL in HEMP group and 7.56 to 11.80 U/mL in CON. In conclusion, industrial hemp improved plasma antioxidant status, reduced lipid peroxidation and decreased stress level thereby improving the performance and welfare of beef cattle

501 The effect of dietary camelina, flaxseed, and canola oil supplementation on skin fatty acid profile, inflammation and immune responses in healthy adult horses

Abstract As n-6 and n-3 fatty acids (FA) have pro- and anti-inflammatory effects, respectively, supplemental oils have the potential to impact inflammation, the immune response, and skin and coat health. This study aimed to evaluate the effects of camelina (CAM), in comparison to canola (OLA) and flaxseed (FLX) oil on the skin FA profile, inflammation, and the immune response in horses. Horses [n = 24; 14.2 ± 4.8 yr; 518 ± 63 kg body weight (BW)] were acclimated to sunflower oil over 4 wk. Groups were balanced by location, age, weight, sex, and breed and randomly assigned one of the three treatments (CAM, OLA, FLX). Horses were fed their assigned oil at a dose of 0.37 g/kg BW for 16 wk. Skin samples were collected on wk 16, and the skin FA composition was analyzed by gas chromatography. On wk 10 and 12, keyhole limpet hemocyanin (KLH) was administered intramuscularly to each horse to stimulate a systemic immune response. Blood was collected on wk 14 and 16 for the evaluation of plasma KLH immunoglobulin G (IgG) concentrations using a modified ELISA protocol and results were presented as optical density units. On wk 12, after the first KLH injection, a delayed-type hypersensitivity (DTH) test was performed by intradermally injecting KLH and the area of swelling was measured using the software ImageJ at 0.5-, 1-, 8-, 24-, 48-, 72-, and 96-h post-injection. Data were analyzed using the GLIMMIX procedure of SAS considering the effects of treatment, time, and their interaction as fixed, and the effects of horse and location as random. Repeated measures on horses were modelled using a spatial power covariance structure. Significance was declared at P ≤ 0.05 and when fixed effects were significant, means were separated using Tukey-Kramer adjustments. Immune and inflammatory responses were produced by the KLH injections; however, there were no differences among treatment groups regarding KLH antibody and DTH response (P > 0.44). The percentages of palmitic (P = 0.02) and stearic acid (P = 0.03) in the skin at wk 16 were greater in FLX as compared with CAM but neither differed from the OLA. The percentage of linoleic acid (P = 0.01) was greater in CAM than OLA but neither differed from FLX at wk 16. The percentage of all other FA was similar among treatment groups (P > 0.06). These results suggest that CAM is comparable to FLX and OLA regarding support of an immune and inflammatory response, and the oil FA composition was not reflected in the skin FA profile after feeding for 16 wk as hypothesized. In conclusion, at the dose provided, CAM supports a similar immune and inflammatory response to KLH as FLX and OLA; however, the lack of incorporation of FA from the diet into the skin should be further explored.

502 Cat and mouse: The effect of consuming four different diet formants (intact mice, raw, canned wet and kibble) on energy expended to consume a meal and immediately post-prandial in domestic cats

Abstract Cats are obligate carnivores; however, we feed them a variety of different diet formats without a clear understanding of feeding behavior and metabolism among diet formats. Whole-prey or raw diets may mimic a more natural diet and require more energy to consume. However, there is currently a dearth of literature examining feline energy expenditure (EE) during the consumption of and immediate post-prandial period when fed different diet formats. The present study aimed to investigate differences in the energetics of adult cats consuming four different diet formats in isocaloric offerings: raw intact mice, commercial raw, canned wet, and kibble diets. Adult neutered male cats [n = 12; body weight (BW) = 4.82 ± 0.164 kg) were used in a 4 x 4 replicated Latin square design and adapted to consuming each diet format before the initiation of the study. Following a 2-d adaptation period, cats were fed 25% of their daily caloric requirement (50.77 ± 1.549 kcal) in indirect calorimetry chambers in which VO2 and VCO2 exchange were measured. Energy expenditure (kcal/BW0.67 kg) was calculated for the consumption period, 15 min immediately post-prandial and 2 h post-prandial. Respiratory gases were measured for one fasted reading, followed by the first feeding. During each feeding, measurements were taken during the consumption period and 15 min post-prandial. For the following 2 h, respiratory gases were measured every 25 min for an additional 4 measures of respiratory gases. All data were analyzed using a generalized linear mixed model considering the effects of treatment, time and their interaction as fixed, and the effects of cat and period as random. A spatial power covariance structure was used to model repeated measures. Significance was considered at P < 0.05 and Tukey’s post-hoc test was performed to separate means. Energy expenditure during consumption and 15 min post-prandial was similar among treatments, and EE for 15 min post-prandial was greater than EE during consumption (P < 0.001). During the 2 h post-prandial, EE for the mice diet was greater than the kibble and canned wet diets (P < 0.001), while EE for the raw diet was only greater than the kibble diet (P < 0.001). Energy expenditure was similar between the kibble and canned wet diets (P = 0.919) and between the mice and raw diets (P = 0.598). Among all treatments and time periods, the mouse diet had the greatest mean EE. An increase in EE during the feeding period and post-prandial could benefit sedentary indoor cats who may be in positive energy balance. Feeding cats a naturalistic diet, such as intact mice or a raw diet, may increase activity levels and EE, but the longer-term effects of these feeding formats on energy balance need to be explored.

308 Isoenergetic reduction of dietary macronutrients reveals distinct fecal metabolomic signatures in lean and obese cats fed at maintenance

Abstract Obesity has become a concerning problem in cats. Increasing evidence demonstrates the utility of metabolomics in identifying disease biomarkers and assessing the effects of nutritional interventions, although limited information exists regarding alterations in fecal metabolites in lean and obese domestic cats in response to different macronutrient content. In the current study, three extruded diets were formulated based on adult maintenance using an isoenergentic approach. These diets were created by adjusting the levels of identical ingredients to achieve a low-protein [LP; protein 28% metabolizable energy (ME), fat 40%ME, NFE 32% ME), a low-fat (LF; protein 42% ME, fat 30% ME, NFE 30% ME), and a low-carbohydrate (LC; protein 36% ME, fat 41% ME, NFE 23% ME] diet. Healthy neutered male adult cats [n = 18; body condition scores (BCS) 4 or 5 (lean, n = 9) and 8 or 9 (obese, n = 9)] were fed each diet for a period of 4 wk in a 3 x 3 Latin square design. Fecal samples from each cat were collected between d 22 and 28 of each treatment period. A total of 67 fecal metabolites in six groups (35 amino acids, 11 fatty acids, 10 sugars and sugar metabolites, 5 alcohols, 3 nitrogenous bases, and 3 others) were analyzed using 1H NMR spectroscopy. To evaluate the impact of body condition, diet and their interaction on each metabolite, proc GLIMMIX covariance structure was selected by the smallest Akaike information criterion value in SAS. The Shapiro-Wilk test was used to check normality and lognormal or beta distribution were applied when appropriate. Bonferroni correction post-hoc test was followed to correct Type I error. Statistical significance was considered at P < 0.05. In lean cats, significantly greater concentrations of fecal proteinogenic and branched-chain amino acids, such as methionine, valine, and L-lysine, as well as pyruvic acid and sugars (P < 0.05) were observed. This suggests that these metabolites may either be more actively fermented by bacteria or not utilized as extensively as in obese cats, potentially contributing to a reduction in obesity status. Regardless of body condition, there is a possibility of an enhanced activity in the tryptophan degradation pathway, leading to the greatest concentrations of fecal tryptophan (P = 0.04) in the LF diet, while the greatest fecal D-galactose (P = 0.04) in the LP diet was likely due to the greater dietary carbohydrate content. These observed results suggested that fecal metabolites were influenced by both body condition and diet; however, body condition had a more substantial impact on metabolite changes in cats, whereas no body condition and diet interaction were noted. Overall, the study indicated distinct fecal metabolic signatures in lean and obese cats subjected to different macronutrient diets and further research is warranted to validate the observed findings. Funding was provided by Champion Petfoods, Natural Sciences and Engineering Council of Canada and Mitacs Accelerate.

Data-driven optimal shrinkage of singular values under high-dimensional noise with separable covariance structure with application

We develop a data-driven optimal shrinkage algorithm, named extended OptShrink (eOptShrink), for matrix denoising with high-dimensional noise and a separable covariance structure. This noise is colored and dependent across samples. The algorithm leverages the asymptotic behavior of singular values and vectors of the noisy data's random matrix. Our theory includes the sticking property of non-outlier singular values, delocalization of weak signal singular vectors, and the spectral behavior of outlier singular values and vectors. We introduce three estimators: a novel rank estimator, an estimator for the spectral distribution of the pure noise matrix, and the optimal shrinker eOptShrink. Notably, eOptShrink does not require estimating the noise's separable covariance structure. We provide a theoretical guarantee for these estimators with a convergence rate. Through numerical simulations and comparisons with state-of-the-art optimal shrinkage algorithms, we demonstrate eOptShrink's application in extracting maternal and fetal electrocardiograms from single-channel trans-abdominal maternal electrocardiograms.

Structural brain characteristics of epilepsy patients with comorbid migraine without aura

Migraine is a common bi-directional comorbidity of epilepsy, indicating potential complex interactions between the two conditions. However, no previous studies have used brain morphology analysis to assess possible interactions between epilepsy and migraine. Voxel-based morphometry (VBM), surface-based morphometry (SBM), and structural covariance networks (SCNs) can be used to detect morphological changes with high accuracy. We recruited 30 individuals with epilepsy and comorbid migraine without aura (EM), along with 20 healthy controls (HC) and 30 epilepsy controls (EC) without migraine. We used VBM, SBM, and SCN analysis to compare differences in gray matter volume, cortical thickness, and global level and local level graph theory indexes between the EM, EC, and HC groups to investigate structural brain changes in the EM patients. VBM analysis showed that the EM group had gray matter atrophy in the right temporal pole compared with the HC group (p < 0.001, false discovery rate correction [FDR]). Furthermore, the headache duration in the EM group was negatively correlated with the gray matter volume of the right temporal pole (p < 0.05). SBM analysis showed cortical atrophy in the left insula, left posterior cingulate gyrus, left postcentral gyrus, left middle temporal gyrus, and left fusiform gyrus in the EM compared with the HC group (p < 0.001, family wise error correction). We found a positive correlation between headache frequency and the cortical thickness of the left middle temporal gyrus (p < 0.05). SCN analysis revealed no differences in global parameters between the three groups. The area under the curve (AUC) of the nodal betweenness centrality in the right postcentral gyrus was lower in the EM group compared with the HC group (p < 0.001, FDR correction), and the AUC of the nodal degree in the right fusiform gyrus was lower in the EM group compared with the EC group (p < 0.001, FDR correction). We found clear differences in brain structure in the EM patients compared with the HC group. Accordingly, migraine episodes may influence brain structure in epilepsy patients. Conversely, abnormal brain structure may be an important factor in the development of epilepsy with comorbid migraine without aura. Further studies are needed to investigate the role of brain structure in individuals with epilepsy and comorbid migraine without aura.

The Chronic Progressive Repeated Measures (CPRM) Model for Clinical Trials Comparing Change Over Time in Quantitative Trait Outcomes

Repeated measures analysis is a common analysis plan for clinical trials comparing change over time in quantitative trait outcomes in treatment versus control. Mixed model for repeated measures (MMRM) assuming an unstructured covariance of repeated measures is the default statistical analysis plan, with alternative covariance structures specified in the event that the MMRM model with unstructured covariance does not converge. We here describe a parsimonious covariance structure for repeated measures analysis that is specifically appropriate for longitudinal repeated measures of chronic progressive conditions. This model has the parsimonious features of the mixed effects model with random slopes and intercepts, but without restricting the repeated measure means to be linear with time. We demonstrate with data from completed trials that this pattern of longitudinal trajectories spreading apart over time is typical of Alzheimer’s disease. We further demonstrate that alternative covariance structures typically specified in statistical analysis plans using MMRM perform poorly for chronic progressive conditions, with the compound symmetry model being anticonservative, and the autoregressive model being poorly powered. Finally, we derive power calculation formulas for the chronic progressive repeated measures model that have the advantage of being independent of the design of the pilot studies informing the power calculations. When data follow the pattern of a chronic progressive condition. These power formulas are also appropriate for sizing clinical trials using MMRM analysis with unstructured covariance of repeated measures.

Effect of Dialysis on Structural Brain Connectivity in Patients with End-Stage Renal Disease

Introduction: Patients with end-stage renal disease (ESRD) are known to have reduced structural and functional brain connectivity in the brain regions associated with cognitive function. However, the effect of dialysis on brain connectivity remains unclear. This study aimed to evaluate the effects of dialysis on structural brain connectivity in patients with ESRD. Methods: This prospective study included 20 patients with ESRD in the pre-dialysis stage and 35 healthy controls. The patients underwent T2-weighted and three-dimensional T1-weighted magnetic resonance imaging before and 3 months after dialysis initiation. Moreover, the cortical thickness was calculated. We applied graph theoretical analysis to calculate the structural covariance network based on cortical thickness. We compared the cortical thickness and structural covariance network of patients with ESRD in the pre-dialysis stage with those of healthy controls and with those of patients with ESRD in the post-dialysis stage. Results: The mean cortical thickness in both hemispheres was lower in patients with ESRD in the pre-dialysis stage than in healthy controls (2.296 vs. 2.354, p = 0.030; 2.282 vs. 2.362, p = 0.004, respectively) and was higher in patients with ESRD in the post-dialysis stage than in those in the pre-dialysis stage (2.333 vs. 2.296, p = 0.001; 2.322 vs. 2.282, p = 0.002, respectively). Analysis of the structural covariance network revealed that the assortative coefficient was lower in patients with ESRD in the pre-dialysis stage than in healthy controls (−0.062 vs. −0.031, p = 0.029) and was higher in patients with ESRD in the post-dialysis stage than in those in the pre-dialysis stage (−0.002 vs. −0.062, p = 0.042). Conclusion: We observed differences in the cortical thickness and structural covariance networks before and after dialysis in patients with ESRD. This indicates that dialysis affects structural brain connectivity, contributing to the understanding of the pathophysiological mechanism of cognitive function alterations resulting from dialysis in patients with ESRD.

Concurrent Functional Linear Regression Via Plug-in Empirical Likelihood

AbstractFunctional data with non-smooth features (e.g., discontinuities in the functional mean and/or covariance) and monotonicity arise frequently in practice. This paper develops simultaneous inference for concurrent functional linear regression in this setting. We construct a simultaneous confidence band for a functional covariate effect of interest. Along with a Wald-type formulation, our approach is based on a powerful nonparametric likelihood ratio method. Our procedures are flexible enough to allow discontinuities in the coefficient functions and the covariance structure, while accounting for discretization of the observed trajectories under a fixed dense design. A simulation study shows that the proposed likelihood ratio-based procedure outperforms the Wald-type procedure in moderate sample sizes. We apply the proposed methods to studying the effect of age on the occupation time curve derived from wearable device data obtained in an NHANES study.

Progressive gray matter atrophy in parkinsonian variant of multiple system atrophy assessed by using causal structural covariance network.

Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown. In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T1-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P. With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL. MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.

Structural covariance network activity in the medial prefrontal cortex is modulated by childhood abuse in adolescents with depression

Aberrant structural covariance (SC) in the medial prefrontal cortex (mPFC) is believed to play a crucial role in adolescent-onset major depressive disorder (AO-MDD). However, the effect of childhood abuse (CA) on SC in AO-MDD patients is still unknown. Here, we measured anomalous SC in the mPFC of AO-MDD patients and assessed the potential modulation of this feature by CA. We acquired T1-weighted structural images of AO-MDD patients (n = 93) and healthy controls (HCs, n = 81). Using voxel-based morphometry analysis, we calculated gray matter volumes for each subject. Subsequently, we classified abnormal SC in the mPFC into three subtypes according to overall CA. Compared with HCs, AO-MDD patients showed alterations in the structural covariance network of the mPFC, which is a central region in the default mode network (DMN). We also found an anterior-posterior dissociation in the structural covariance connectivity of the DMN. A history of CA modulated bilateral mPFC SC. These changes were primarily focused on the SC between the mPFC and the limbic system, indicating a gap in the rate of neural maturation between these regions. In summary, the DMN and frontal-limbic system, which are involved in emotional processing, appear to play a significant role in the development of AO-MDD. These findings highlight the crucial effects of CA on neurophysiological alterations in individuals with AO-MDD.

Structural covariation between cerebellum and neocortex intrinsic structural covariation links cerebellum subregions to the cerebral cortex.

The human cerebellum is increasingly recognized to be involved in nonmotor and higher-order cognitive functions. Yet, its ties with the entire cerebral cortex have not been holistically studied in a whole brain exploration with a unified analytical framework. Here, we characterized dissociable cortical-cerebellar structural covariation patterns based on regional gray matter volume (GMV) across the brain in n = 38,527 UK Biobank participants. Our results invigorate previous observations in that important shares of cortical-cerebellar structural covariation are described as 1) a dissociation between the higher-level cognitive system and lower-level sensorimotor system and 2) an anticorrelation between the visual-attention system and advanced associative networks within the cerebellum. We also discovered a novel pattern of ipsilateral, rather than contralateral, cerebral-cerebellar associations. Furthermore, phenome-wide association assays revealed key phenotypes, including cognitive phenotypes, lifestyle, physical properties, and blood assays, associated with each decomposed covariation pattern, helping to understand their real-world implications. This systems neuroscience view paves the way for future studies to explore the implications of these structural covariations, potentially illuminating new pathways in our understanding of neurological and cognitive disorders.NEW & NOTEWORTHY Cerebellum's association with the entire cerebral cortex has not been holistically studied in a unified way. Here, we conjointly characterize the population-level cortical-cerebellar structural covariation patterns leveraging ∼40,000 UK Biobank participants whole brain structural scans and ∼1,000 phenotypes. We revitalize the previous hypothesis of an anticorrelation between the visual-attention system and advanced associative networks within the cerebellum. We also discovered a novel ipsilateral cerebral-cerebellar associations. Phenome-wide association (PheWAS) revealed real-world implications of the structural covariation patterns.

Spatial Patterns of Productivity and Human Development Potentials for Pinus pinea L.

Pinus pinea (stone pine), a Mediterranean species, is valued for its highly nutritious pine nuts and its ability to adapt to different environmental conditions. The species has been increasingly planted in Chile, where its main ecological requirements are met across a vast area. However, new plantations are established without considering social dimensions. Policymakers can regulate private decisions on tree planting through the appropriate design of economic incentives to foster social well-being. The objective of this work was to describe spatial patterns of potential areas for the cultivation of the exotic nut-bearing conifer P. pinea in central Chile and the possible correlation of those patterns with human development indices. Spatial data layers of the municipality development index (MDI), elevation, edaphoclimatic variables, and stone pine nut’s productive potential were overlapped at the municipality scale along 1225 km in central Chile. A spatial principal component analysis (sPCA) was used to integrate multiple dimensions, summarizing covariation structures, and identifying spatial patterns in the study area. Key results showed that spatial patterns of the potential productive index (PPI) were strongly regulated by the spatial pattern of climate and soil variables, whereas the spatial pattern of MDI showed a cryptic pattern and that the three dimensions of MDI—welfare, economy, and education—showed a different spatial movement, especially education and welfare. The results allow us to recommend that public policies boost municipality development through the promotion of P. pinea plantations and should target areas with a high productive potential and low MDI to generate socio-economic improvements. These findings are useful for the strategic spatial planning of the species cropping in Chile.

Neural correlates of anhedonia in young adults with subthreshold depression: A graph theory approach for cortical-subcortical structural covariance

BackgroundAnhedonia is an enduring symptom of subthreshold depression (StD) and predict later onset of major depressive disorder (MDD). Brain structural covariance describes the inter-regional distribution of morphological changes compared to healthy controls (HC) and reflects brain maturation and disease progression. We investigated neural correlates of anhedonia from the structural covariance. MethodsT1-weighted brain magnetic resonance images were acquired from 79 young adults (26 StD, 30 MDD, and 23 HC). Intra-individual structural covariance networks of 68 cortical surface area (CSAs), 68 cortical thicknesses (CTs), and 14 subcortical volumes were constructed. Group-level hubs and principal edges were defined using the global and regional graph metrics, compared between groups, and examined for the association with anhedonia severity. ResultsGlobal network metrics were comparable among the StD, MDD, and HC. StD exhibited lower centralities of left pallidal volume than HC. StD showed higher centralities than HC in the CSAs of right rostral anterior cingulate cortex (ACC) and pars triangularis, and in the CT of left pars orbitalis. Less anhedonia was associated with higher centralities of left pallidum and right amygdala, higher edge betweenness centralities in the structural covariance (EBSC) of left postcentral gyrus-parahippocampal gyrus and LIPL-right amygdala. More anhedonia was associated with higher centralities of left inferior parietal lobule (LIPL), left postcentral gyrus, left caudal ACC, and higher EBSC of LIPL-left postcentral gyrus, LIPL-right lateral occipital gyrus, and left caudal ACC-parahippocampal gyrus. LimitationsThis study has a cross-sectional design. ConclusionsStructural covariance of brain morphologies within the salience and limbic networks, and among the salience-limbic-default mode-somatomotor-visual networks, are possible neural correlates of anhedonia in depression.

Changed ventral striatum structural covariance and grey matter volume in depression during a one-year follow-up

Empirical findings suggest reduced cortico-striatal structural connectivity in patients with major depressive disorder (MDD). However, the relationship between the abnormal structural covariance and one-year outcome of first-episode drug-naive patients has not been evaluated. This longitudinal study aimed to identify specific changes of ventral striatum-related brain structural covariance and grey matter volume in forty-two first-episode patients with major depression disorder compared with thirty-seven healthy controls at the baseline and the one-year follow-up conditions. At the baseline, patients showed decreased structural covariance between the left ventral striatum and the bilateral superior frontal gyrus (SFG), bilateral middle frontal gyrus (MFG), right supplementary motor area (SMA) and left precentral gyrus and increased grey matter volume at the left fusiform and left parahippocampus. At the one-year follow-up, patients showed decreased structural covariance between the left ventral striatum and the right SFG, right MFG, left precentral gyrus and left postcentral gyrus, and increased structural covariance between the right ventral striatum and the right amygdala, right hippocampus, right parahippocampus, right superior temporal pole, right insula and right olfactory bulb and decreased volume at the left SMA compared with controls. These findings suggest that specific ventral striatum connectivity changes contribute to the early brain development of the MDD.

Decision tree learning with random forest models using agricultural and ecological field data incorporating multi-factor studies and covariate structure

Decision tree learning with random forest models using agricultural and ecological field data incorporating multi-factor studies and covariate structure

The Bergen-Yale Sexual Addiction Scale (BYSAS): Longitudinal Measurement Invariance Across a Two-Year Interval.

The Bergen-Yale Sexual Addiction Scale (BYSAS; [1]) is arguably the most popular questionnaire at present for assessing sex addiction. Employing Confirmatory Factor Analysis (CFA) and treating item scores as ordered categorical, we applied Weighted Least Square Mean and Variance Adjusted Chi-Square (WLSMV) extraction to investigate the longitudinal measurement and structural invariance of ratings on the BYSAS among 276 adults (mean = 31.86 years; SD = 9.94 years; 71% male) over a two-year period, with ratings at three yearly intervals. Overall, there was support for configural invariance, full loading, full threshold, the full unique factor invariance; and all structural (latent variances and covariances) components. Additionally, there was no difference in latent mean scores across the three-time points. The psychometric and practical implications of the findings are discussed.