Partial Correlation Research Articles

Influential Signs of Dry Eye-Related Ocular Symptoms in Participants With Unstable Tear Film.

The aim of this study was to investigate the factors influencing dry eye disease (DED)-related ocular symptoms in participants with short fluorescein tear break-up time (FTBUT). This cross-sectional study included 82 participants with short FTBUT (<10 seconds). Examinations included Ocular Surface Disease Index (OSDI), FTBUT, average noninvasive tear break-up time (NIBUTave), lid wiper epitheliopathy, lipid layer thickness, blink rate, partial blink, tear meniscus height, and meibomian gland (MG) evaluation which included ratio of residual MG area (RMGA) and MG grade in tarsal plates. One-way analysis of variance was used to detect differences between symptomatic tear film instability group (FTBUT <5 s, OSDI ≥13), asymptomatic tear film instability group (FTBUT <5 s, OSDI <13), and control group (FTBUT ≥5 s, OSDI <13). A bivariate correlation, partial correlation, and multiple linear regression analyses were used to identify major factors. Only the right eye was included. Among the participants with FTBUT <5 seconds, symptomatic group showed less upper RMGA ( P < 0.001) and NIBUTave ( P = 0.010). OSDI was negatively associated with upper RMGA ( r = -0.450, P < 0.001) and NIBUTave ( r = -0.414, P = 0.001), and positively associated with upper MG grade ( r = 0.277, P = 0.027). Linear regression analysis showed that the upper RMGA significantly affected OSDI (B = -41.895, P = 0.001), while not significantly correlated with age, upper MG grade, and NIBUTave. The upper RMGA might be the main factor affecting DED-related discomfort in participants with unstable tear film, indicating an early ocular change in DED.

The role of asymptomatic carriers on the dynamics of a lymphatic filariasis model incorporating control strategies

This study presents a mathematical model to investigate the patterns of transmission in lymphatic filariasis. The model considers chronic, acute, and asymptomatic individuals and integrates key control strategies. Random synthetic data is generated robustly through numerical solutions to closely replicate real-world scenarios and encompass uncertainties. The synthetic data adheres to a Gaussian distribution to ensure validity and reliability. Following the derivation of the basic and effective reproduction number using the next generation matrix approach, Latin Hypercube Sampling (LHS) and the Partial Rank Correlation Coefficient (PRCC) algorithm is utilized to assess the parameters that significantly influence the model outputs. The study examine the trajectories of different population compartments through numerical simulations over time, with particular emphasis on the role played by asymptomatic individuals in the transmission of the disease. To assess the potential for disease elimination, the study introduces a range of strategies involving protective measures, treatment interventions, and mosquito control. These strategies are determined through sensitivity analysis. The findings demonstrate that the simultaneous implementation of all control measures has a noteworthy effect in managing lymphatic filariasis. In conclusion, the proposed model enhances understanding of lymphatic filariasis dynamics and informs effective control strategies.

Quantifying the water use efficiency of karst ecosystems and response to environmental factors

Study regionThe study area is located in Guizhou province, the centre of the karst region in southwest China. Study focusAs a typical karst region, Guizhou has long faced challenges with water scarcity. Quantifying water use efficiency (WUE) is crucial for the efficient use of water resources and sustainable management. This study examined the spatio-temporal evolution patterns and its driving factors on WUE in Guizhou using Theil-Sen's slope, partial correlation methods, and the geographic detector model. New hydrological insights for the region(1) The multi-annual mean WUE of non-karst region (NKR, 2.75 gC kg-1 H2O yr-1) is higher than that of karst region (KR, 2.10 gC kg-1 H2O yr-1) during 2001–2020. (2) The rate of increase of WUE was three times higher in KR than in NKR. (3) Precipitation and temperature were identified as the key factors influencing WUE. Interactions between each environmental factors were observed to have both bi-variate and non-linear enhancement effects. Notably, in the NKR, soil moisture, vegetation type and leaf area index were the dominant factors influencing WUE, with interactions between environmental factors had both enhanced and weakened effect on WUE. (4) The synergistic effects of these interactions exceeded the individual or cumulative effects of the two environmental factors. These findings contribute to our understanding of the environmental factors driving changes in WUE in the KR.

Nonparametric testing of the covariate significance for spatial point patterns under the presence of nuisance covariates

Determining the relevant spatial covariates is one of the most important problems in the analysis of point patterns. Parametric methods may lead to incorrect conclusions, especially when the model of interactions between points is wrong. Therefore, we propose a fully nonparametric approach to testing significance of a covariate, taking into account the possible effects of nuisance covariates. Our tests match the nominal significance level, and their powers are comparable with the powers of parametric tests in cases where both the model for intensity function and the model for interactions are correct. When the parametric model for the intensity function is wrong, our tests achieve higher powers. The proposed methods rely on Monte Carlo testing and take advantage of the newly introduced concepts: the covariate-weighted residual measure and nonparametric residuals. We also define a correlation coefficient between a point process and a covariate and a partial correlation coefficient quantifying the dependence between a point process and a covariate of interest while removing the influence of nuisance covariates.

Distinctive subgingival microbial signatures in older adults with different levels of cognitive function.

To examine association between subgingival microbial signatures and levels of cognitive impairment in older adults. We analysed subgingival plaque samples and 16S ribosomal RNA sequences for microbiota among 165 participants (normal controls [NCs]: 40, subjective cognitive decline [SCD]: 40, mild cognitive impairment [MCI]: 49 and dementia: 36). The bacterial richness was lower among individuals with worse cognitive function, and subgingival microbial communities differed significantly among the four groups. Declining cognitive function was associated with decreasing relative abundance of genera Capnocytophaga, Saccharibacteria_genera_incertae_sedis, Lautropia and Granulicatella, and increasing abundance of genus Porphyromonas. Moreover, there were differentially abundant genera among the groups. Random forest model based on subgingival microbiota could distinguish between cognitive impairment and NC (AUC = 0.933, 95% confidence interval 0.873-0.992). Significant correlations were observed between oral microbiota and sex, Montreal Cognitive Assessment (MoCA) score and Mini-Mental State Examination score. Partial correlation analysis showed that Leptotrichia and Burkholderia were closely negatively associated with the MoCA score after adjusting for multiple covariates. Gene function was not significantly different between SCD and NC groups, whereas three homozygous genes were altered in MCI patients and two in dementia patients. This is the first study to demonstrate an association between the composition, function and metabolic pathways of subgingival microbiota and different levels of cognitive function among older individuals. Future cohort studies should assess its diagnostic usefulness for cognitive impairment.

Amygdala volumes and associations with socio-emotional competencies in preterm youth: cross-sectional and longitudinal data.

Socio-emotional difficulties often result from very preterm (VPT) birth. The amygdala's developmental trajectory, including its nuclei, has been recognized as a significant factor in observed difficulties. This study aims to assess the relationship between amygdala volume and socio-emotional competencies in VPT children and adolescents. Socio-emotional competencies were assessed, and amygdala volumes, including subnuclei, were extracted automatically from structural scans in a cross-sectional cohort of VPT (n = 75) and full-term (FT, n = 41) aged 6-14 years. Group differences in amygdala volumes were assessed using ANCOVA, and associations with socio-emotional competencies were studied using partial least squares correlation (PLSC). In a VPT subgroup, additional longitudinal data with amygdala volumes at term-equivalent age (TEA) were manually extracted, growth rates calculated, and associations with school-age socio-emotional competencies investigated using PLSC. Using cross-sectional data at school-age, amygdala volumes displayed comparable developmental patterns between the VPT and the FT groups. Greater volumes were associated with more emotional regulation difficulties in VPT and lower affect recognition competencies in FT. In the longitudinal VPT subgroup, no significant associations were found between amygdala volume trajectory and socio-emotional competencies. Although our findings suggest typical amygdala development after VPT birth, further research is necessary to elucidate the developmental trajectory of amygdala and the role of resilience factors. In our cohort, amygdala volumes, including subnuclei, displayed comparable developmental trajectories between the very preterm and the full-term groups. Higher amygdala volumes at school-age were associated with higher emotional regulation difficulties in the very-preterm born group, and with lower affect recognition abilities in full-term born children and adolescents. In a subgroup of very-preterm children and adolescents followed from birth to school-age, no significant associations were found between amygdala volumes at term-equivalent age and socio-emotional competencies at school-age.

Subtle Radiographic Progression at Six Months Can Be Detected Using Automated Quantitative Software in Rheumatoid Arthritis While Receiving Tocilizumab.

We investigated whether our in-house software equipped with partial image phase-only correlation (PIPOC) can detect subtle radiographic joint space narrowing (JSN) progression at six months and predict JSN progression in rheumatoid arthritis (RA) patients receiving Tocilizumab. The study included 39 RA patients who were treated with Tocilizumab. Radiological progression of the metacarpophalangeal and the proximal interphalangeal joints was evaluated according to the Genant-modified Sharp score (GSS) at 0, 6, and 12 months. Automatic measurements were performed with the software. We validated the software in terms of accuracy in detecting the JSN progression. The success rate of the software for joint space width (JSW) measurement was 96.8% (449/464). The 0-12-month JSW change by the software was significantly greater in joints with the 0-6-month PIPOC (+) group than the 0-6-month PIPOC (-) group (p < 0.001). The 0-12-month JSW change by the software was 0-12-month GSS (+) than with 0-12-month GSS (-) (p = 0.02). Here, "(+)" indicates the JSN progression during the follow-up period. Meanwhile, "(-)" indicates no JSN progression during the follow-up period. Linear regression tests showed significant correlations between the 0-6-month and the 0-12-month PIPOC in the left 2nd and 3rd MCP joints (R2 = 0.554 and 0.420, respectively). Our in-house software equipped with PIPOC could predict subsequent JSN progression with only short-term observations.

Supportive care needs and anxious-depressive symptoms in cancer patients: An interaction effect between emotional competence and the COVID-19 pandemic?

The main objective was to assess the link between emotional competence (EC) and adjustment outcomes such as supportive care needs (SCN) and anxious-depressive symptoms in cancer patients starting chemotherapy. The second objective was to assess the interaction effect between EC and the COVID-19 pandemic (i.e. patients included before or during the pandemic) on these outcomes. At the beginning of care, 255 patients with digestive or hematological cancer, recruited before the pandemic began (n = 156, 61.2%) or during the pandemic (n = 99, 38.8%), completed the Short Profile of Emotional Competence, the Hospital Anxiety and Depression Scale, and the Supportive Care Needs Survey Short Form. Partial correlations and multiple regressions were used. Intrapersonal EC showed negative significant correlations with psychological unmet SCN (r = -.32, p < .001), anxiety (r = -.37, p < .001), and depression (r = -.46, p < .001). Interpersonal EC showed only significant interaction effects (p < .05): it was only associated with fewer unmet physical and daily SCN (p < .002) and fewer depressive symptoms (p < .004) during pandemic. Results show significant associations between intrapersonal EC and better adjustment of cancer patients from the early stage of care. Interpersonal EC seems to be a significant resource to deal with illness only in difficult contexts such as the COVID-19 pandemic.

The role of Allee effect in cannibalistic species: An action plan to sustain the declining cod population

The role of Allee effect in cannibalistic species: An action plan to sustain the declining cod population

Exploring the relationship between dietary patterns and obesity among Nigerian adults: a cross-sectional study

Background/ObjectiveNo previous study has investigated the association between dietary pattern and both general and abdominal obesity risk among adults in Nigeria. This study aimed to evaluate the associations between dietary patterns and the risk of obesity among adult age 18 and above in Ekiti State, Southwestern Nigeria.Methods and study designsA total of 1003 adults were included in this cross-sectional study (males = 558; females = 445). Body mass index (BMI) and waist-to-hip (WHR) were used to assess general and abdominal obesity respectively and they were categorized using WHO recommendation. Partial correlation analyses were performed to assess the associations of dietary patterns with BMI and WHR. Prevalence ratio between dietary pattern and both general and abdominal obesity were calculated using Robust Poisson Regression.ResultsThe prevalence of general obesity among adults was 15.9%, (11.6% among men and 20.2% among women); abdominal obesity was 32.3% (28.9% among males and 44.5% among females). Four dietary patterns were identified; diversified traditional pattern; typical traditional pattern; milk and bread pattern and egg and fish pattern. Diversified traditional pattern was negatively associated with BMI (PR = 0.571, 95%CI: 0.360 ~ 0.905, p = 0.017), and typical traditional pattern was positively associated with BMI (PR = 1.561, 95% CI: 1.043 ~ 2.339, p = 0.031) and WHR in females (PR = 1.849, 95% CI: 1.256 ~ 2.721, p = 0.005). In comparison to those in the lowest quartile, adults with the highest quartile of the typical traditional pattern had a higher risk for abdominal obesity (PR = 1.849, 95%CI = 1.256 ~ 2.721, p = 0.020).ConclusionThis study reports an alarming increase in Obesity prevalence among Nigeria adults which is greatly influence by their lifestyle and eating pattern. We found out that a typical traditional food pattern was associated with a higher risk of both general and abdominal obesity, but a diverse traditional food pattern was associated to a reduced risk of general obesity.

Financial deepening on income inequality: A quantitative meta-analysis study

AbstractThere exists a vast empirical literature on Financial Sector Development (FSD) and the income inequality nexus; however, it lacks consensus. To study this, 24 studies with 87 regression estimates on financial institution depth and income inequality were collected. This paper used the most common method of economic meta-analysis, the Partial Correlation Coefficient (PCC), to answer the question: What is the magnitude and impact, if any, of financial institution depth on income inequality? In addition, a multivariate meta-regression model was used to find moderator variables that produced mixed results in the literature. The results show that the global average comovement of financial institution depth (domestic credit) on income inequality is very small but positive; suggesting that growth in domestic credit may widen income inequality. The positive correlation between domestic credit and income inequality highlights how financial institutions use household income and collateral as a signal when deciding on credit applications. Finally, the multivariate regression results suggest that the present heterogeneity within the literature stems from different methodologies and control variables included in the econometric models, and panel studies that mix countries with heterogeneous characteristics. These suggest that different components of FSD may impact income inequality differently.

Assessment of OCT-Based Macular Curvature and Its Relationship with Macular Microvasculature in Children with Anisomyopia.

To evaluate the intraocular differences in optical coherence tomography (OCT)-based macular curvature index (MCI) among children with anisomyopia and to investigate the relationship between MCI and the macular microvasculature. Fifty-two schoolchildren with anisometropia > 2.00 D were enrolled and underwent comprehensive examinations including cycloplegic refraction, axial length (AL), and swept source OCT/OCT angiography. OCT-based MCIs were determined from horizontal and vertical B-scans by a customized curve fitting model in MATLAB R2022 at 1-mm-, 3-mm-, and 6-mm-diameter circles at fovea. Characteristics and topographic variation of MCI was analyzed, and the relationships with microvascularity and its associated factors were investigated. MCI achieved high reliability and repeatability. There were overall larger MCIs in the more myopic eyes than the less myopic eyes in 1-mm-, 3-mm-, and 6-mm-diameter circles at fovea (all p < 0.001). For the topographic variation, horizontal MCI was significantly greater than vertical MCI (all p < 0.001), and was the largest in 6-mm circle, followed by 3-mm and 1-mm circles. Stronger correlation of horizontal MCI with myopic severity than vertical MCI was found. Partial Pearson's correlation found MCI was negatively associated with deep capillary plexus (DCP) vessel density (p = 0.016). Eyes with a higher MCI in a 6-mm circle were more likely to have longer AL (p < 0.001), lower DCP vessel density (p = 0.037), and thinner choroidal thickness (ChT) (p = 0.045). Larger MCI was found in the more myopic eyes of children with anisomyopia and was significantly associated with smaller DCP density, suggesting that MCI was an important indicator of myopia-related retinal microvascularity change, and it could be a valuable metric for myopia assessment in children.

Negative family and interpersonal relationship are associated with centromedial amygdala functional connectivity alterations in adolescent depression.

The amygdala, known for its functional heterogeneity, plays a critical role in the neural mechanism of adolescent major depressive disorder (aMDD). However, changes in its subregional functional networks in relation to stressful factors remain unclear. We recruited 78 comorbidity-free, medication-naive aMDD patients and 40 matched healthy controls (HC) to explore changes in resting-state functional connectivity (FC) across four amygdala subregions: the centromedial nucleus (CM), the basolateral nucleus (LB), the superficial nucleus (SF), and the amygdalostriatal transition area (Astr). Then, we performed partial correlation analysis to investigate the relationship between amygdala subregional FC and stressful factors as measured by the Chinese Version of Family Environment Scale (FES-CV) and the Adolescent Self-Rated Life Events Scale (ASLEC). Compared to HC, aMDD patients demonstrated significantly decreased functional connectivity between the left CM and left precentral gyrus, as well as between left SF and left precentral gyrus, and between left LB and posterior cingulate gyrus (PCC)/precuneus. In aMDD group, left CM-precentral gyrus FC exhibited negative correlation with interpersonal relationship and punishment, and positive correlation with family cohesion and expressiveness. This study reveals distinct patterns of abnormal functional connectivity among amygdala subregions in aMDD. Our findings suggest that the CM network, in particular, may be involved in stress-related factors in aMDD, which provide a potential target for the prevention and treatment of adolescent depression.

Targeted metabolomics-based understanding of the sleep disturbances in drug-naïve patients with schizophrenia

BackgroundSleep disturbances are a common occurrence in patients with schizophrenia, yet the underlying pathogenesis remain poorly understood. Here, we performed a targeted metabolomics-based approach to explore the potential biological mechanisms contributing to sleep disturbances in schizophrenia.MethodsPlasma samples from 59 drug-naïve patients with schizophrenia and 36 healthy controls were subjected to liquid chromatography-mass spectrometry (LC-MS) targeted metabolomics analysis, allowing for the quantification and profiling of 271 metabolites. Sleep quality and clinical symptoms were assessed using the Pittsburgh Sleep Quality Index (PSQI) and the Positive and Negative Symptom Scale (PANSS), respectively. Partial correlation analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) model were used to identify metabolites specifically associated with sleep disturbances in drug-naïve schizophrenia.Results16 characteristic metabolites were observed significantly associated with sleep disturbances in drug-naïve patients with schizophrenia. Furthermore, the glycerophospholipid metabolism (Impact: 0.138, p<0.001), the butanoate metabolism (Impact: 0.032, p=0.008), and the sphingolipid metabolism (Impact: 0.270, p=0.104) were identified as metabolic pathways associated with sleep disturbances in drug-naïve patients with schizophrenia.ConclusionsOur study identified 16 characteristic metabolites (mainly lipids) and 3 metabolic pathways related to sleep disturbances in drug-naïve schizophrenia. The detection of these distinct metabolites provide valuable insights into the underlying biological mechanisms associated with sleep disturbances in schizophrenia.

Multiple paths to rumination within a network analytical framework

Theories of rumination have proposed different psychological factors to place one at risk for repetitive negative thinking. A comprehensive empirical test that captures the most relevant contributors to rumination is lacking. Building on influential self-regulatory and metacognitive frameworks, we modeled how key constructs in this context relate to ruminative thinking. 498 participants completed online questionnaires including indicators of rumination, metacognition, promotion goal orientation, effortful control, and depression. We estimated regularized partial correlation networks to investigate unique associations between the different constructs and followed these analyses up with directed acyclic graphs to identify potential pathways towards rumination. Results demonstrated that: (1) both self-regulatory and metacognitive factors were directly linked to rumination, amongst these were (2) positive beliefs, negative beliefs about uncontrollability and harm, cognitive self-consciousness, depression, effortful control, perfectionism, and (lack of) cognitive confidence, and (3) we identified multiple directed pathways, suggesting three direct contributors to rumination while controlling for the influence of all other variables: diminished effortful control, positive beliefs, and cognitive self-consciousness. This study is the first to comprehensively assess metacognitive and self-regulatory frameworks of rumination in a data-driven manner. Our findings suggest that there are multiple pathways towards rumination, which should be incorporated in clinical case conceptualization of rumination and related disorders.

Remote Sensing-Based Monitoring of Cotton Growth and Its Response to Meteorological Factors

Cotton is an important economic crop and strategic resource. Monitoring its growth and analysing its response to meteorological factors are crucial for field management and yield estimation. This study selects the primary cotton-producing regions in northern Xinjiang as the study area. Firstly, using the Google Earth Engine cloud platform, the Cotton Mapping Index (CMI) was utilised to extract cotton planting areas from 2019 to 2023. Secondly, Sentinel-2A data were used to calculate the NDVI of cotton during the growing season and analyse its variation characteristics. Finally, correlation, lag, and partial correlation analyses were conducted between cotton NDVI and meteorological factors, including effective accumulated temperature, wind speed, precipitation, and solar shortwave radiation, to explore the response relationship. The results indicate the following: (1) The optimal classification threshold of CMI in the study area was determined to be 0.74, which was applied to extract cotton planting areas over the years. The overall classification accuracy achieved was 84.85%. The R2 value for the cotton area extracted by CMI compared to the cotton planting area in the statistical yearbook data is 0.98, with an average relative error of 16.84%. CMI’s classification use effectively distinguishes cotton from other major crops, such as wheat and corn, in the study area. Compared with different classification methods, CMI is more convenient and efficient for extracting cotton planting areas, contributing significantly to yield estimation and management. (2) We found that from 2019 to 2023, some fields were planted with cotton yearly. In order to prevent land degradation, a crop rotation system should be implemented, in which cotton rotates with other crops to reduce the rate of soil nutrient loss and achieve sustainable agricultural development. (3) NDVI can effectively monitor the spatiotemporal changes and regional variations in cotton growth. Sentinel-2 multi-spectral imagery possesses high spatial and temporal resolution, enabling effective monitoring of cotton growth, provision of cotton growth data for field managers, and application in cotton production management. Additionally, cotton yield estimation can be achieved by comparing the overall growth of cotton across different years. (4) Cotton NDVI exhibits a strong correlation with effective accumulated temperature and solar radiation, with the majority passing the significance test, suggesting a significant promotion effect on cotton growth by accumulated temperature and solar radiation. In cotton cultivation management, attention should be directed toward monitoring changes in accumulated temperature and solar radiation. Moreover, NDVI changes in response to solar radiation exhibit a certain lag. The correlation between NDVI and precipitation is low, likely attributed to local cotton cultivation primarily relying on drip irrigation. Cotton NDVI is negatively correlated with wind speed. Cotton planting should consider weather changes and take corresponding preventive management measures. The research results have significant reference value for monitoring cotton growth, disaster prevention, and sustainable agricultural development.

Exploring cultural contributions to the neuropsychology of social cognition: the advanced clinical solutions

ABSTRACT Introduction Culture and social cognition are deeply intertwined, yet how this rich intersectionality is expressed neuropsychologically remains an important question. Method In a convenience sample of 128 young adults (mean age = 24.9 years) recruited from a majority-minority urban university, we examined performance-based neuropsychological measures of social cognition, the Advanced Clinical Solutions-Social Perception (ACS-SP), in relation to both cultural orientation, as assessed by the Individualism-Collectivism Scale (ICS) and spoken English language, as assessed by the oral word pronunciation measure of the Wide Range Achievement Test-4 (WRAT4). Results Results indicated higher WRAT4 scores correlated with better performance across all ACS-SP measures of social cognition. Controlling for these associations in spoken English, partial correlations linked lower scores across both prosody interpretation and affect naming ACS-SP tasks with a propensity to view social relationships vertically, irrespective of individualistic or collectivistic orientations. Hierarchical regression results showed that cultural orientation and English-language familiarity each specifically and uniquely contributed to ACS-SP performance for matching prosody with facial expressions. Conclusions These findings underscore the importance of incorporating and prioritizing both language and cultural factors in neuropsychological studies of social cognition. They may be viewed as offering strong support for expanding the boundaries of the construct of social cognition beyond its current theoretical framework of one that privileges Western, educated, industralized, rich and democratic (WEIRD) values, customs, and epistemologies.

Neuroimaging and epigenetic analysis reveal novel epigenetic loci in major depressive disorder.

Epigenetic modifications, such as DNA methylation, contribute to the pathophysiology of major depressive disorder (MDD). This study aimed to identify novel MDD-associated epigenetic loci using DNA methylation profiles and explore the correlations between epigenetic loci and cortical thickness changes in patients with MDD. A total of 350 patients with MDD and 161 healthy controls (HCs) were included in the epigenome-wide association studies (EWAS). We analyzed methylation, copy number alteration (CNA), and gene network profiles in the MDD group. A total of 234 patients with MDD and 135 HCs were included in neuroimaging methylation analysis. Pearson's partial correlation analysis was used to estimate the correlation between cortical thickness of brain regions and DNA methylation levels of the loci. In total, 2018 differentially methylated probes (DMPs) and 351 differentially methylated regions (DMRs) were identified. DMP-related genes were enriched in two networks involved in the central nervous system. In neuroimaging analysis, patients with MDD showed cortical thinning in the prefrontal regions and cortical thickening in several occipital regions. Cortical thickness of the left ventrolateral prefrontal cortex (VLPFC, i.e. pars triangularis) was negatively correlated with eight DMPs associated with six genes (EML6, ZFP64, CLSTN3, KCNMA1, TAOK2, and NT5E). Through combining DNA methylation and neuroimaging analyses, negative correlations were identified between the cortical thickness of the left VLPFC and DNA methylation levels of eight DMPs. Our findings could improve our understanding of the pathophysiology of MDD.

Bridging personality dimensions and eating symptoms: A transdiagnostic network approach

AbstractObjectiveEating disorders (ED) have recently been studied from a network approach, conceptualising them as a complex system of interconnected variables, while highlighting the role of non‐ED symptoms and personality dimensions. This study aims to explore the connections between personality and ED symptoms, identify central nodes, and compare the EDs network to a healthy control network.MethodsWe employed network analysis to examine the personality‐ED symptom connections in 329 individuals with an ED diagnosis and 192 healthy controls. We estimated a regularised partial correlation network and the indices of centrality and bridge centrality to identify the most influential nodes for each group. Network differences between groups were also examined.ResultsLow Self‐Directedness and high Harm avoidance emerged as central bridge nodes, displaying the strongest relationship with ED symptoms. Both networks differed in their global connectivity and structure, although no differences were found in bridge centrality and centrality indices.ConclusionsThese findings shed light on the role of personality dimensions, such as Self‐Directedness and Harm Avoidance in the maintenance of ED psychopathology, supporting the transdiagnostic conceptualisation of ED. This study advances a deeper understanding of the complex interplay between personality dimensions and ED symptoms, offering potential directions for clinical interventions.

High-dimensional partial correlation coefficients: A survey study of estimation Methods

. The partial correlation coefficient (Pcor) measures the degree of association between two random variables after removing the effect of another set of variables, called the controlling variables. When the dimension of these controlling variables is high, estimating Pcor becomes exceedingly challenging, as conventional computational methods fail to provide efficient estimators. Although several methods have been proposed for estimating Pcor in high-dimensional data, they primarily focus on testing whether its value is zero rather than enhancing estimation efficiency. This article concentrates on improving estimation efficiency and surveys existing methods. Through extensive simulation studies on high-dimensional data, we observe that all current methods consistently underestimate the absolute values of Pcor, with the bias being more pronounced when Pcor is positive. By considering a combination of regression equations, X = Z α + ε and Y = Z β + ζ , the method proposed in this article demonstrates a significant improvement over existing approaches. Stocks data in Hong Kong is employed to demonstrate the effectiveness of these methods.