Partial Correlation Research Articles

Altered individual gray matter structural covariance networks in early abstinence patients with alcohol dependence.

While alterations in cortical thickness have been widely observed in individuals with alcohol dependence, knowledge about cortical thickness-based structural covariance networks is limited. This study aimed to explore the topological disorganization of structural covariance networks based on cortical thickness at the single-subject level among patients with alcohol dependence. Structural imaging data were obtained from 61 patients with alcohol dependence during early abstinence and 59 healthy controls. The single-subject structural covariance networks were constructed based on cortical thickness data from 68 brain regions and were analyzed using graph theory. The relationships between network architecture and clinical characteristics were further investigated using partial correlation analysis. In the structural covariance networks, both patients with alcohol dependence and healthy controls displayed small-world topology. However, compared to controls, alcohol-dependent individuals exhibited significantly altered global network properties characterized by greater normalized shortest path length, greater shortest path length, and lower global efficiency. Patients exhibited lower degree centrality and nodal efficiency, primarily in the right precuneus. Additionally, scores on the Alcohol Use Disorder Identification Test were negatively correlated with the degree centrality and nodal efficiency of the left middle temporal gyrus. The results of this correlation analysis did not survive after multiple comparisons in the exploratory analysis. Our findings may reveal alterations in the topological organization of gray matter networks in alcoholism patients, which may contribute to understanding the mechanisms of alcohol addiction from a network perspective.

Glymphatic abnormality in systemic lupus erythematosus detected by diffusion tensor image analysis along the perivascular space.

This study aimed to evaluate the activity of the glymphatic system in systemic lupus erythematosus (SLE) by a diffusion-based method termed "Diffusion Tensor Image Analysis aLong the Perivascular Space (DTI-ALPS)", and examined its correlations with morphological changes in the brain. In this cross-sectional study, forty-five female patients with SLE and thirty healthy controls (HCs) were included. Voxel-based and surface-based morphometric analyses were performed to examine T1 weighted images, and diffusion tensor images were acquired to determine diffusivity along the x-, y-, and z-axes in the plane of the lateral ventricle body. The ALPS-index was calculated. The differences in values between SLE patients and HC group were compared using the independent samples t test or Mann-Whitney U test. For the correlations between the ALPS-index and brain morphological parameters, partial correlation analysis and Pearson's correlation analysis were conducted. SLE patients showed lower values for the ALPS-index in left (1.543 ± 0.141 vs 1.713 ± 0.175, p < 0.001), right (1.428 ± 0.142 vs 1.556 ± 0.139, p < 0.001) and whole (1.486 ± 0.121 vs 1.635 ± 0.139, p < 0.001) brain compared with the HC group. The reduced ALPS-index showed significant positive correlations with gray matter loss. The non-invasive ALPS-index could serve as a sensitive and effective neuroimaging biomarker for individually quantifying glymphatic activity in patients with SLE. Glymphatic system abnormality may be involved in the pathophysiologic mechanism underlying central nervous system damage in SLE patients.

Decreased brain iron deposition based on quantitative susceptibility mapping correlates with reduced neurodevelopmental status in children with autism spectrum disorder.

To investigate potential correlations between the susceptibility values of certain brain regions and the severity of disease or neurodevelopmental status in children with autism spectrum disorder (ASD), 18 ASD children and 15 healthy controls (HCs) were recruited. The neurodevelopmental status was assessed by the Gesell Developmental Schedules (GDS) and the severity of the disease was evaluated by the Autism Behavior Checklist (ABC). Eleven brain regions were selected as regions of interest and the susceptibility values were measured by quantitative susceptibility mapping. To evaluate the diagnostic capacity of susceptibility values in distinguishing ASD and HC, the receiver operating characteristic (ROC) curve was computed. Pearson and Spearman partial correlation analysis were used to depict the correlations between the susceptibility values, the ABC scores, and the GDS scores in the ASD group. ROC curves showed that the susceptibility values of the left and right frontal white matter had a larger area under the curve in the ASD group. The susceptibility value of the right globus pallidus was positively correlated with the GDS-fine motor scale score. These findings indicated that the susceptibility value of the right globus pallidus might be a viable imaging biomarker for evaluating the neurodevelopmental status of ASD children.

Abstract PO1-07-02: Sensitive tumor detection, accurate quantification, and ER subtyping using low-pass methylome of liquid biopsy samples from patients (pts) with metastatic breast cancer (mBC)

Abstract Background The presence and amount of blood circulating tumor DNA (Tumor Content, TC) is emerging as a clinically relevant factor in many cancers, including BC. In the metastatic setting, a commonly used tumor tissue agnostic approach involves analyzing Copy Number Alterations (CNA) from low-pass whole-genome sequencing (lpWGS) by ichorCNA. However, with a lower limit of detection of 3%, it is unsuitable for low TC applications, such as monitoring disease in response to treatment. Here we report on the use of low-pass whole genome bisulfite sequencing (lpWGBS) coupled with a novel tool, METER (METhylation analyzER), to overcome current limitations of lpWGS, enabling sensitive TC detection, accurate quantification, and ER subtyping from mBC liquid biopsies. Methods METER is a computational tool to analyse TC exploiting BC-specific Differentially Methylated Sites (DMS) and Regions (DMR) in lpWGBS data. To define BC DMSs and DMRs, Rocker-meth was applied to the WGBS profiles of 30 BC tissue (BASIS dataset) and 23 healthy donor cell free DNA (cfDNA) (Fox-Fisher 2021). METER consists of three modules: 1) METER-quant, a DMS-based quantifier of TC; 2) METER-detect, a DMR-based z-score method to classify samples as TC+ (METER+) or TC- (METER-); 3) METER-subtype, to infer ER status via Robust Partial Correlation applied to ER+ vs. ER- BC DMR. We generated lpWGBS data (coverage 0.5-1X) of 135 cfDNA samples from 58 pts (45 ER+, 13 ER-, 55 (95%) up to 3 previous lines of treatment; before starting treatment (T0, n=58), after the first cycle (T1, n=25), and at progression (T2, n=22)) and 30 from healthy individuals as controls. ichorCNA using sensitive parameters (allowing normal fraction up to 0.99) was used to estimate reference TC. A leave-one-out strategy applied to the control samples was used to estimate the false discovery rate (FDR) of METER-detect classification. METER+/- pts were tested for association with OS and PFS using the log-rank test and compared with ichorCNA detection (TC by ichorCNA above or below 3%, ichorCNA+/-). Results TC of 105 cfDNA BC samples by METER-quant was concordant with estimates from the state-of-the-art tool ichorCNA (R &amp;gt;0.90, p&amp;lt; 1e-10). In 22 pts with complete longitudinal data, METER-quant median TC of 0.05 at T0 (IQR 0.02-0.12), 0.02 at T1 (0.01-0.07), and 0.06 at T2 (0.03-0.11) were obtained, with significant difference observed for T0 vs T1 and T2 vs T1 (paired Wilcoxon p&amp;lt; 0.05). Across all time points, METER-detect classified 43% of the n=42 ichorCNA- samples as METER+. The reliability and prognostic performance of METER and ichorCNA detection classification were then compared using clinical outcome data. Based on T0 data, METER+ pts had significantly worse OS than METER- (HR=4.2 CI=2.0-8.9, p&amp;lt; 0.001). This effect was stronger than using ichorCNA (HR=2.3 CI=1.3-4.0, p=0.006). Worse PFS at T0 was observed for METER+ compared with METER- pts (HR=3.7 CI=1.8-7.9, p&amp;lt; 0.001), while no significant association was observed for ichorCNA+ pts (HR=1.4 CI=0.8-2.5, p=0.2). Of note, ichorCNA-/METER+ pts (N=11) at T0 had worse PFS compared with ichorCNA-/METER- (N=11) (HR=3.7 CI 1.4-9.7, p=0.005). Considering the 73 METER+ and 53 samples with METER-quant &amp;gt;5%, METER-subtype showed an accuracy of 0.84 (CI=0.73-0.92) and 0.94 (CI=0.83-0.99) respectively in classifying ER status based on IHC. Discussion lpWGBS enables tumor tissue agnostic analysis and concurrent investigation of complementary molecular features, including CNA and DNA methylation patterns. In a small and heterogeneous cohort, METER showed comparable performance to state-of-the-art tools in terms of TC quantification (ichorCNA) and ER subtyping (IHC), while offering enhanced sensitivity and ensuring a low FDR. METER showed promising prognostic stratification capabilities, particularly for patients with low TC. Validation in an extended prospective cohort is currently ongoing. Citation Format: Marta Paoli, Agostina Nardone, Francesca Galardi, Chiara Biagioni, Dario Romagnoli, Francesca De Luca, Gian Marco Franceschini, Ilenia Migliaccio, Marta Pestrin, Giuseppina Sanna, Emanuela Risi, Luca Livraghi, Erica Moretti, Laura Biganzoli, Luca Malorni, Francesca Demichelis, Matteo Benelli. Sensitive tumor detection, accurate quantification, and ER subtyping using low-pass methylome of liquid biopsy samples from patients (pts) with metastatic breast cancer (mBC) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-02.

Association of anhedonia with brain-derived neurotrophic factor and interleukin-10 in major depressive disorder

BackgroundAnhedonia, a core symptom of major depressive disorder (MDD), manifests in two forms: anticipatory and consummatory, reflecting a diminished capacity to anticipate or enjoy pleasurable activities. Prior studies suggest that brain-derived neurotrophic factor (BDNF) and interleukin-10 (IL-10) may play key roles in the emergence of anhedonia in MDD. The specific relationships between these biomarkers and the two forms of anhedonia remain unclear. This study investigated the potential links between BDNF, IL-10, and both forms of anhedonia in MDD patients. MethodsThis study included 43 participants diagnosed with MDD and 58 healthy controls. It involved detailed assessments of depression and anxiety levels, anticipatory and consummatory pleasure, cognitive functions, and a broad spectrum of plasma biomarkers, such as C-reactive protein, various interleukins, and BDNF. Using partial correlation, variables related to pleasant experiences were identified. Stepwise multiple linear regression analysis was applied to pinpoint the independent predictors of anhedonia in the MDD group. ResultsDemographically, both groups were comparable in terms of age, sex, body mass index, educational year, and marital status. Individuals with MDD displayed markedly reduced levels of anticipatory and consummatory pleasure, higher anxiety, and depression scores compared to healthy controls. Additionally, cognitive performance was notably poorer in the MDD group. These patients also had lower plasma diamine oxidase levels. Analysis linked anhedonia to impaired delayed memory. Regression results identified IL-10 and BDNF as independent predictors of anticipatory and consummatory anhedonia, respectively. ConclusionThese findings demonstrate that anticipatory and consummatory anhedonia are influenced by independent factors, thereby providing critical insights into the distinct neuroimmunological mechanisms that underlie various forms of anhedonia.Clinicl Trial Registration Number: NCT03790085

Study on pulp metabolism of patients with pulpitis using ultra-performance liquid chromatography coupled with Orbitrap mass spectrometry

Background and aimsPulpitis, a pulp disease caused by caries, trauma, and other factors, has a high clinical incidence. This study focused on identifying possible metabolic biomarkers of pulpitis cases and analyzing the related metabolic pathways for providing a theoretical foundation to diagnose and prevent pulpitis. Materials and methodsPulp samples from 20 pulpitis cases together with 20 normal participants were analyzed with a serum metabolomics approach using ultra-high-performance liquid chromatography (UPLC)/Orbitrap mass spectrometry. Moreover, this work carried out multivariate statistical analysis for screening potential biomarkers of pulpitis. ResultsThrough biomarker analysis and identification, such as partial least squares discrimination analysis, orthogonal partial least squares discriminant analysis model establishment, correlation analysis, and biomarker pathway analysis, 40 biomarkers associated with 20 metabolic pathways were identified, including 20 upregulated and 20 downregulated metabolites. Those major biomarkers included oxoglutaric acid, inosine, citric acid, and PA(14:1(9Z)/PGD1). Among them, oxoglutaric acid and inosine were most significantly downregulated and had the highest correlation with pulpitis. Among these metabolic pathways, GABAergic synapse and alanine, aspartate, and glutamate metabolism were positively correlated with pulpitis. 4. ConclusionsThese biomarkers as well as metabolic pathways may offer the theoretical foundation to understand pulpitis pathogenesis and develop preventive drugs.

Wetting or greening? Probing the global trends in Vegetation Condition Index (VCI)

Vegetation Condition Index (VCI), as a widely used drought index for monitoring vegetation drought stress and estimating drought trends, is constructed by normalizing the long-term satellite-based Normalized Difference Vegetation Index (NDVI) data. However, under global greening, vegetation across different regions has shown an increasing trend in greenness, which may cause VCI to inherit the greening trend in NDVI and further hamper its ability in drought trend analysis. Therefore, this study quantitatively explored the underlying relationship among VCI, global greening, and drought from 2001 to 2021 to examine the utility of VCI in a changing environment. Multi-source indicators were employed as surrogates for vegetation greenness and drought, respectively. Particularly, the Leaf Area Index (LAI) and Net Primary Production (NPP) were used as proxies for vegetation greenness while the Root-Zone Soil Moisture (RZSM), Palmer Drought Severity Index (PDSI), and Standardized Precipitation-Evapotranspiration Index (SPEI) were used for drought indices. Based on Sen’s slope estimator, Mann-Kendall (MK) test, and partial correlation analysis, our results show that the proportion of pixels with an increasing trend in VCI is approximately 38.5%, which is similar to the greenness-related indices (i.e., NPP [26.47%] and LAI [59.14%]), and is significantly higher than the other drought indices (i.e., RZSM [19.83%], PDSI [10.38%], and SPEI [9.32%]). Furthermore, our results demonstrate that the VCI, as a drought index, exhibits a closer correlation with greenness-related indicators (LAI and NPP) than other drought indices (RZSM, PDSI, and SPEI). These results reveal the potential limitations in the practical applications of VCI and could enhance our understanding of vegetation dynamics and drought trends, especially in the current greening globe. Additionally, this study serves as a cautionary note for the scientific community involved in drought monitoring, emphasizing that the VCI may not be a suitable tool for evaluating long-term trends in drought impacts on vegetation.

Impact of Preseason Climate Factors on Vegetation Photosynthetic Phenology in Mid–high Latitudes of the Northern Hemisphere

During the period preceding the vegetation growing season (GS), temperature emerges as the pivotal factor determining phenology in northern terrestrial ecosystems. Despite extensive research on the impact of daily mean temperature (Tmean) during the preseason period, the influence of diurnal temperature range (DTR) on vegetation photosynthetic phenology (i.e., the impact of the plant photosynthetic cycle on seasonal time scale) has largely been neglected. Using a long-term vegetation photosynthetic phenology dataset and historical climate data, we examine vegetation photosynthetic phenology dynamics and responses to climate change across the mid–high latitudes of the Northern Hemisphere from 2001 to 2020. Our data reveal an advancing trend in the start of the GS (SOS) by −0.15 days per year (days yr−1), affecting 72.1% of the studied area. This is particularly pronounced in western Canada, Alaska, eastern Asia, and latitudes north of 60°N. Conversely, the end of the GS (EOS) displays a delaying trend of 0.17 days yr−1, impacting 62.4% of the studied area, especially northern North America and northern Eurasia. The collective influence of an earlier SOS and a delayed EOS has resulted in the notably prolonged length of the GS (LOS) by 0.32 days yr−1 in the last two decades, affecting 70.9% of the studied area, with Eurasia and western North America being particularly noteworthy. Partial correlation coefficients of the SOS with preseason Tmean, DTR, and accumulated precipitation exhibited negative values in 98.4%, 93.0%, and 39.2% of the study area, respectively. However, there were distinct regional variations in the influence of climate factors on the EOS. The partial correlation coefficients of the EOS with preseason Tmean, DTR, and precipitation were positive in 58.6%, 50.1%, and 36.3% of the region, respectively. Our findings unveil the intricate mechanisms influencing vegetation photosynthetic phenology, holding crucial significance in understanding the dynamics of carbon sequestration within terrestrial ecosystems amidst climate change.

Assessing complex PTSD and PTSD: validation of the German version of the International Trauma Interview (ITI)

ABSTRACT Background: With the introduction of the ICD-11 into clinical practice, the reliable distinction between Posttraumatic Stress Disorder (PTSD) and Complex Posttraumatic Stress Disorder (CPTSD) becomes paramount. The semi-structured clinician-administered International Trauma Interview (ITI) aims to close this gap in clinical and research settings. Objective: This study investigated the psychometric properties of the German version of the ITI among trauma-exposed clinical samples from Switzerland and Germany. Method: Participants were 143 civilian and 100 military participants, aged M = 40.3 years, of whom 53.5% were male. Indicators of reliability and validity (latent structure, internal reliability, inter-rater agreement, convergent and discriminant validity) were evaluated. Confirmatory factor analysis (CFA) and partial correlation analysis were conducted separately for civilian and military participants. Results: Prevalence of PTSD was 30% (civilian) and 33% (military) and prevalence of CPTSD was 53% (civilians) and 21% (military). Satisfactory internal consistency and inter-rater agreement were found. In the military sample, a parsimonious first-order six-factor model was preferred over a second-order two-factor CFA model of ITI PTSD and Disturbances in Self-Organization (DSO). Model fit was excellent among military participants but no solution was supported among civilian participants. Overall, convergent validity was supported by positive correlations of ITI PTSD and DSO with DSM-5 PTSD. Discriminant validity for PTSD symptoms was confirmed among civilians but low in the military sample. Conclusions: The German ITI has shown potential as a clinician-administered diagnostic tool for assessing ICD-11 PTSD and CPTSD in primary care. However, further exploration of its latent structure and discriminant validity are indicated.

Evaluation of IFNAR2 and TYK2 transcripts’ prognostic role in COVID-19 patients: a retrospective study

Background and objectivesThis study aimed to investigate the possible prognostic significance of interferon alpha–beta receptor subunit 2 (IFNAR2) and tyrosine kinase 2 (TYK2) expressions.MethodsWe conducted a retrospective study including COVID-19 adult patients. All blood samples were collected before any interventions. The expressions of IFNAR2 and TYK2 were assessed using real-time PCR in venous blood samples of 54 cases and 56 controls. The transcript quantities of IFNAR2 and TYK2 genes were assessed using a Delta-Ct method.ResultsOur findings show no significant differences in gene expression levels for IFNAR2 and TYK2 between patients who required oxygen (O2) therapy and those who did not (p-value = 0.732 and p-value = 0.629, respectively). Likewise, there were no significant differences in IFNAR2 and TYK2 expressions between patients hospitalized for less than 7 days and those hospitalized for 7 days or more (p-value = 0.455 and p-value = 0.626, respectively). We also observed a weak correlation between IFNAR2 expression and CRP (p-value = 0.045, r = 0.192). There was a negative correlation between the expression levels of IFNAR2 and TYK2 transcripts in COVID-19 patients (p-value = 0.044; partial correlation coefficient = -0.283). Additionally, IFNAR2 and TYK2 were significantly downregulated in the COVID-19 group compared to healthy subjects (p-value = 0.002 and p-value = 0.028, respectively). However, neither IFNAR2 nor TYK2 expression was significantly different between the case subgroups based on COVID-19 severity. The IFNAR2 ΔΔCt (B = -0.184, 95% CI: -0.524–0.157, p-value = 0.275) and the TYK2 ΔΔCt (B = 0.114, 95% CI: -0.268–0.496, p-value = 0.543) were not found to be significant predictors of hospitalization duration. The area under the curve (AUC) for IFNAR2 expression is 0.655 (p-value = 0.005, 95% CI: 0.554–0.757), suggesting its poor discriminative value.ConclusionWe were unable to comment definitively on the prognostic power of IFNAR2 and TYK2 expressions in COVID-19 patients, and larger-scale studies are needed. The principal limitations of this study included the lack of longitudinal analysis and limited sample size.

Parameter estimation and global sensitivity analysis of a bacterial-plasmid model with impulsive drug treatment

In this paper, a mathematical model is developed to study bacterial resistance caused by plasmids and mutations in the presence of the impulsive drug treatment. Firstly, the stability of the bacterial-plasmid extinction periodic solution is proved by Floquet theory and the permanence of system is presented while some conditions are satisfied. Secondly, the nontrivial periodic solution bifurcated from the bacterial-plasmid extinction periodic solution is obtained in view of the four-dimensional impulsive control of bifurcation method. Good fitting results are given by the Mean Absolute Percentage Error method for four different cases of bacterial media. Further, the global sensitivity of R0 is analyzed by the Partial Rank Correlation Coefficient method, and the parameters that have important influence on the system are determined. Finally, numerical simulations are performed to validate the accuracy of the theoretical findings.

Comparing the stability and reproducibility of brain-behavior relationships found using canonical correlation analysis and partial least squares within the ABCD sample

Abstract Canonical correlation analysis (CCA) and partial least squares correlation (PLS) detect linear associations between two data matrices by computing latent variables (LVs) having maximal correlation (CCA) or covariance (PLS). This study compared the similarity and generalizability of CCA- and PLS-derived brain-behavior relationships. Data were accessed from the baseline Adolescent Brain Cognitive Development (ABCD) dataset (N &amp;gt; 9,000, 9–11 years). The brain matrix consisted of cortical thickness estimates from the Desikan-Killiany atlas. Two phenotypic scales were examined separately as the behavioral matrix; the Child Behavioral Checklist (CBCL) subscale scores and NIH Toolbox performance scores. Resampling methods were used to assess significance and generalizability of LVs. LV1 for the CBCL brain relationships was found to be significant, yet not consistently stable or reproducible, across CCA and PLS models (singular value: CCA = .13, PLS = .39, p &amp;lt; .001). LV1 for the NIH brain relationships showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, p &amp;lt; .001). The current study suggests that stability and reproducibility of brain-behavior relationships identified by CCA and PLS are influenced by the statistical characteristics of the phenotypic measure used when applied to a large population-based pediatric sample.

Unveiling the dynamics of "scenes changing as steps move" in a Chinese classical garden: a case study of Jingxinzhai Garden

Chinese classical gardens are a significant cultural heritage in the history of world gardening, with their central architectural principle of "scenes changing as steps move" (步移景异) embodying traditional Chinese aesthetic ideals. This study employed the variation of visual complexity during a tour as a representation of this principle, using Jingxinzhai (静心斋) Garden as a case study. The visual environmental characteristics were quantified using the Fraclab box-counting, Canny edge detection, and DeepLab V3 + model, and the spatial distribution of fractal dimension and visual index of landscape elements were analyzed. Through partial correlation analysis, hierarchical regression analysis, and one-way ANOVA, the relevant factors (BVI, RVI, GVI, WVI) and influencing factors (BVI, RVI, GVI) and the differences among landscape element combinations of visual complexity were identified. Furthermore, the distribution patterns and causes of visual complexity in Chinese classical gardens were then discussed. This study proposes an effective method for quantifying the visual environmental characteristics of Chinese classical gardens and provides an explanation of the concept of "scenes changing as steps move" from the perspective of visual environment. It offers important references for a deeper understanding of Chinese classical garden design and planning.

The associations between daily reports of loneliness and psychotic experiences in the early risk stages for psychosis.

Bi-directional associations between loneliness and psychotic experiences (PEs) have been reported, but the mechanisms underlying these associations are unknown. This study aims to explore associations between daily reports of loneliness and PEs, and test differences in this association across young adult individuals at different levels of risk for psychosis. We analysed 90-day diary data on loneliness and PEs from N = 96 participants (mean age 24.7, range 18-35, 77% female) divided into 4 subgroups, each indexing increased levels of risk for psychosis according to the clinical staging model: 'psychometric' (n = 25), 'low' (n = 27), 'mild' (n = 24), and 'ultra-high'(n = 20) risk. Multilevel vector autoregressive models examined within-day (contemporaneous) and between-day (temporal) associations between loneliness and PEs for the total sample. Next, these associations were compared across subgroups. Loneliness and PEs were significantly associated contemporaneously (partial correlation B = 0.14) but not temporally. Subgroup membership moderated both contemporaneous and temporal associations. The contemporaneous association between loneliness and PEs was stronger in the low-risk subgroup compared to the mild-risk (B = -0.35, p < .01) and ultra-high-risk (B = -0.36, p < .01) subgroups. The temporal association between loneliness on the previous day and PEs on the current day was stronger in mild-risk subgroup compared to the ultra-high-risk subgroup (B = -0.03, p = .03). After adjusting for multiple testing, only the contemporaneous-but not the temporal-associations remained statistically significant. Loneliness is associated with PEs in individuals at risk for psychosis, particularly in those with low to mild symptoms. Our findings tentatively suggest that especially individuals with low expressions of PEs may be more sensitive to social context, but future studies are needed to replicate and further unravel the potentially stage-specific interplay between social context and PEs.

Adoption of ICT4D and its determinants: A systematic review and meta-analysis

Various Digital Agricultural Technologies (DAT) have been developed and implemented around the world. This study aims to estimate the overall adoption rate and identify the determinant factors for a better adoption perspective after decades of innovation and dissemination. A systematic review was conducted on published studies that reported adoption rates and determinant factors using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. We used meta-regression and the partial correlation coefficient to estimate the effect size and establish the correlation between socioeconomic characteristics and the adoption of various technologies reported. Fifty-two studies with 32400 participants met the selection criteria and were included in the study. The results revealed an overall pooled adoption rate of 39 %, with the highest adoption rates in developing countries in Africa and South America. Socioeconomic factors such as age, education, gender, and income were found to be the main determinants and should be considered when designing technology for sustainable adoption. The study also found that young farmers were more susceptible to adoption. Moreover, farmers with higher income levels and educational attainment are more likely to use technology linked to agricultural production, market access, and digital advising, implying that high-income farmers with more education are more tech-savvy. However, this does not exclude low-income and low-educated farmers from adopting the technologies, as many models and strategies with socioeconomic considerations were developed. It is one of the reasons behind the underlying enthusiasm for digital agricultural adoption in low and middle-income countries.

Association between homotopic connectivity and clinical symptoms in first-episode schizophrenia

BackgroundAbnormal functional connectivity (FC) in the brain has been observed in schizophrenia patients. However, studies on FC between homotopic brain regions are limited, and the results of these studies are inconsistent. The aim of this study was to compare homotopic connectivity between first-episode schizophrenia (FES) patients and healthy subjects and assess its correlation with clinical symptoms. MethodsThirty-one FES patients and thirty-three healthy controls (HC) were included in the study. The voxel-mirrored homotopic connectivity (VMHC) method of resting-state functional magnetic resonance imaging (rs-fMRI) was used to analyse the changes in homotopic connectivity between the two groups. The 5-factor PANSS model was used to quantitatively evaluate the severity of symptoms in FES patients. Partial correlation analysis was used to assess the correlation between homotopic connectivity changes and clinical symptoms. ResultsCompared to those in the HC group, VMHC values were decreased in the paracentral lobule (PL), thalamus, and superior temporal gyrus (STG) in the FES group (P < 0.05, FDR correction). No significant differences in white matter volume (WMV) within the subregion of the corpus callosum or in brain regions associated with reduced VMHC were observed between the two groups. Partial correlation analyses revealed that VMHC in the bilateral STG of FES patients was positively correlated with negative symptoms (rleft = 0.46, p < 0.05; rright = 0.47, p < 0.05), and VMHC in the right thalamus was negatively correlated with disorganized/concrete symptoms (rright = 0.45, p < 0.05). ConclusionOur study revealed that homotopic connectivity is altered in the resting-state brain of FES patients and correlates with the severity of negative symptoms; this change may be independent of structural changes in white matter. These findings may contribute to the development of the abnormal connectivity hypothesis in schizophrenia patients.

Biodiversity patterns of the coral reef cryptobiota around the Arabian Peninsula

The Arabian Peninsula accounts for approximately 6% of the world’s coral reefs. Some thrive in extreme environments of temperature and salinity. Using 51 Autonomous Reef Monitoring Structure (ARMS), a standardized non-destructive monitoring device, we investigated the spatial patterns of coral reef cryptobenthic diversity in four ecoregions around the Arabian Peninsula and analyzed how geographical and/or environmental drivers shape those patterns. The mitochondrial cytochrome c oxidase subunit I (COI) gene was used to identify Amplicon Sequence Variants and assign taxonomy of the cryptobenthic organisms collected from the sessile and mobile fractions of each ARMS. Cryptobenthic communities sampled from the two ecoregions in the Red Sea showed to be more diverse than those inhabiting the Arabian (Persian) Gulf and the Gulf of Oman. Geographic distance revealed a stronger relationship with beta diversity in the Mantel partial correlation than environmental distance. However, the two mobile fractions (106–500 µm and 500–2000 µm) also had a significant correlation between environmental distance and beta diversity. In our study, dispersal limitations explained the beta diversity patterns in the selected reefs, supporting the neutral theory of ecology. Still, increasing differences in environmental variables (environmental filtering) also had an effect on the distribution patterns of assemblages inhabiting reefs within short geographic distances. The influence of geographical distance in the cryptofauna assemblages makes these relevant, yet usually ignored, communities in reef functioning vulnerable to large scale coastal development and should be considered in ecosystem management of such projects.

Dynamic Change and Attribution Regarding Fractional Vegetation Coverage in Mengdong River Basin

The situation of rocky desertification in the southwestern part of China is very serious and has been included as one of three major ecological problems. In this study, using Landsat images as the data sources, we estimated the fractional vegetation coverage (FVC) in the Mengdong River Basin in the Hunan Province over the past 40 years, analyzed its spatio-temporal variation characteristics, and explored the driving mechanism (climate and anthropogenic) using the Mann–Kendall, Hurst index, and partial correlation methods. Specifically, the impact of ecological engineering on the recovery of vegetation cover in rocky desertification areas was analyzed and discussed in this study. The results demonstrate the following: (1) The changes in FVC in the study area before and after the rocky desertification management ecological project differed significantly, with a very small change in the rate of change in the mean value of FVC between 1987 and 1999 (&lt;0.1%), while the FVC had a significant linear growth trend between 2000 and 2022 (&gt;0.9%). (2) The Hurst index of FVC ranged from −0.233 to 2.476, with an average value of 0.864. The area with an H value greater than 0.75 accounted for 80.12%, indicating that the future trend in the vast majority of regions will develop in accordance with the current change trend. (3) The average partial correlation coefficients between FVC and precipitation and between FVC and temperature were −0.02 and 0.27, respectively, showing that FVC is more sensitive to temperature than precipitation. The combination of climate change and human activities is the main cause of FVC change. The contributions of climate change (precipitation and temperature) and human activities to FVC variation are about 30% and 70%, respectively. Ecological restoration projects have a significant positive effect on the recovery of vegetation in rocky desertification areas. The results of this study are intended to provide a scientific basis for analyzing the characteristics of vegetation restoration in existing rocky desertification areas and ecological management in future rocky desertification areas.

Interrelationships among accumulations of intra- and peri-organ fat, visceral fat, and subcutaneous fat.

We aimed to clarify the relationship between intra- and peri-organ fat, visceral fat, and subcutaneous fat. We used abdominal CT to evaluate intra- and peri-organ fat accumulations in the pancreas, liver, spleen, renal parenchyma, renal sinus, and skeletal muscle. The relationships between these fats, visceral fat, and subcutaneous fat were examined by using the partial correlation and covariance analysis, adjusting for BMI. We found that visceral fat and each intraand peri-organ fat accumulation were positively correlated, whereas subcutaneous fat and the accumulation of each intra- and peri-organ fat and visceral fat were negatively correlated. Pancreas fat, liver fat, renal sinus fat, and skeletal muscle fat accumulated significantly more in people with excessive visceral fat accumulation than in those without excessive visceral fat accumulation (p = 0.01, 0.006, 0.008, 0.02, respectively). In conclusion, intra- and peri-organ fat accumulation in each organ shows a positive correlation with visceral fat and a negative correlation with subcutaneous fat, independent of BMI.

Microstructural brain abnormalities and associated neurocognitive dysfunction in obstructive sleep apnea: a pilot study with diffusion kurtosis imaging.

To assess the possible brain abnormalities in adult patients with moderate and severe obstructive sleep apnea (OSA) using the mean kurtosis (MK) from diffusion kurtosis imaging (DKI) and analyze the correlation between MK and cognitive function. A total of 30 patients with moderate and severe OSA and 30 healthy controls (HCs) evaluated by the Montreal Cognitive Assessment (MoCA) scale were enrolled. All subjects underwent DKI and 3D T1-weighted imaging (T1WI) on a 3.0T MR scanner. The MK values of gray and white matter brain regions were compared. Partial correlation analysis was used to analyze the correlation between respiratory sleep parameters/cognitive score and MK values in different brain regions. Compared with the HCs, the MK of 20 brain regions (13 after false discovery rate (FDR) correction) and cognitive scores in the OSA group were significantly lower. In the OSA group, the apnea-hypopnea index (AHI) was negatively correlated with the MK in the white matter of the right occipital lobe; the LSpO2 was positively correlated with the MK in the bilateral parietal, precentral, and right postcentral cortex; the total score of MoCA scale was positively correlated with MK in the left hippocampus; the language function was positively correlated with MK in the white matter of left parietal lobe, and the delayed recall was positively correlated with the MK in right insula cortex and bilateral cingulate. After FDR correction, only the correlations of LSpO2 with right precentral gyrus cortex, and bilateral parietal cortex were significant. MK values of DKI imaging may provide valuable information in assessing the neurological impacts of obstructive sleep apnea.