Multivariate Correlation Analysis Research Articles

Primary caregiver burden and undiagnosed mental health illness in out-patients with inflammatory bowel disease-A multicentric prospective survey from the IBD Emerging Nations' Consortium.

Mental health is an overlooked aspect of inflammatory bowel disease (IBD) patient care with limited data from the developing world. The primary caregiver burden is expected to be high, but has not been evaluated. We conducted a questionnaire-based survey of consecutive out-patients with no diagnosed mental health illness (n = 289) and their primary caregivers (n = 247) from 10 centers across eight countries (Bangladesh, India, Iran, Malaysia, Myanmar, Nepal, Pakistan, Thailand) of IBD-Emerging Nations' Consortium (ENC). Patients were assessed for anxiety (PHQ-9), depression (GAD-7), quality of life (SIBDQ, IBDCOPE) and medication adherence (MMAS-8). Caregiver burden was assessed by Zarit-Burden Interview (ZBI), Ferrans and Power Quality of Life (QOL) scores and coping strategies (BRIEF-COPE). Multivariate logistic regression and correlation analyses were performed to identify risk factors and theimpact on QOL in patients and caregivers. Moderate to severe depression and anxiety were noted in 33% (severe 3.5%) and 24% (severe 3.8%) patients, respectively. The risk factor for depression was active disease (p < 0.001, OR6.3), while male gender (p = 0.01, OR0.45) and medication adherence (p = 0.003, OR0.75) were protective. Risk factors for anxiety were unmarried status (p = 0.015, OR2.3), female gender (p = 0.004, OR0.41), steroid use (p = 0.016, OR2.1) and active disease (p < 0.001, OR7.97). High GAD-7 and PHQ-9 scores positively correlated with high disease activity (r = 0.55, p < 0.001, Crohn's disease; r = 0.52, p < 0.001 ulcerative colitis) and negatively with SIBDQ (r = - 0.63, p < 0.001; r = - 0.64, p < 0.001 CD; r = 0.36, p = 0.001,UC). Sixty-five percent (159/249) primary caregivers reported high burden (ZBI ≥ 21), which positively correlated with low educational status and low-income and negatively with QOL(r = - 0.33, p < 0.001). The primary adaptive coping strategy among caregivers was religion, while maladaptive strategy was self-distraction. Nearly two-thirds of primary caregivers reported high burden of care. There was also high prevalence of undiagnosed depression and anxiety in IBD out-patients. This highlights the need for patient-caregiver integrated mental-health services in the developing world.

Cerebellum and social abilities: A structural and functional connectivity study in a transdiagnostic sample.

The cerebellum has been involved in social abilities and autism. Given that the cerebellum is connected to the cortex via the cerebello-thalamo-cortical loop, the connectivity between the cerebellum and cortical regions involved in social interactions, that is, the right temporo-parietal junction (rTPJ) has been studied in individuals with autism, who suffer from prototypical deficits in social abilities. However, existing studies with small samples of categorical, case-control comparisons have yielded inconsistent results due to the inherent heterogeneity of autism, suggesting that investigating how clinical dimensions are related to cerebellar-rTPJ functional connectivity might be more relevant. Therefore, our objective was to study the functional connectivity between the cerebellum and rTPJ, focusing on its association with social abilities from a dimensional perspective in a transdiagnostic sample. We analyzed structural magnetic resonance imaging (MRI) and functional MRI (fMRI) scans obtained during naturalistic films watching from a large transdiagnostic dataset, the Healthy Brain Network (HBN), and examined the association between cerebellum-rTPJ functional connectivity and social abilities measured with the social responsiveness scale (SRS). We conducted univariate seed-to-voxel analysis, multivariate canonical correlation analysis (CCA), and predictive support vector regression (SVR). We included 1404 subjects in the structural analysis (age: 10.516 ± 3.034, range: 5.822-21.820, 506 females) and 414 subjects in the functional analysis (age: 11.260 ± 3.318 years, range: 6.020-21.820, 161 females). Our CCA model revealed a significant association between cerebellum-rTPJ functional connectivity, full-scale IQ (FSIQ) and SRS scores. However, this effect was primarily driven by FSIQ as suggested by SVR and univariate seed-to-voxel analysis. We also demonstrated the specificity of the rTPJ and the influence of structural anatomy in this association. Our results suggest that there is a complex relationship between cerebellum-rTPJ connectivity, social performance and IQ. This relationship is specific to the cerebellum-rTPJ connectivity, and is largely related to structural anatomy in these two regions. PRACTITIONER POINTS: We analyzed cerebellum-right temporoparietal junction (rTPJ) connectivity in a pediatric transdiagnostic sample. We found a complex relationship between cerebellum and rTPJ connectivity, social performance and IQ. Cerebellum and rTPJ functional connectivity is related to structural anatomy in these two regions.

New Insight into the Effects of Different Types of Midfoot and Hindfoot Deformities on the Functional Outcomes of Rheumatoid Arthritis Patients

In advanced stages of rheumatoid arthritis (RA), the pattern of joint involvement leads to varied types of foot deformities such as forefoot, midfoot, and hindfoot deformities. We aim to evaluate midfoot and hindfoot deformities and their effect on functional outcomes in RA patients. In this prospective cross-sectional study clinical and radiological evaluations of 100 adult RA patients were studied for midfoot and hindfoot deformities. The RA disease activity, functional disability level, specific foot and ankle assessments, gait speed, and balance tests were assessed. Radiological examinations of the weight-bearing feet in a standing position were done. We found that the most frequent deformity type was the planovalgus foot (24%). There were statistically significant differences between the types of foot deformities and disease duration, disease activity, falls, Tinetti and Berg balance Test, and health assessment questionnaire-disability index. The multivariate regression analysis of independent correlates of falling detected that patients with equinovarus deformity were 2.5 times more liable for falling with 63.5% predictive power. According to the predictive criteria of deformity type for falling, the equinocavovarus type had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 91%, 84.5%, 98.5%, 99%, and 84%, respectively. We found in RA patients, midfoot and hindfoot deformities cause a significant reduction of functional ability and quality of life. The early detection of foot deformities requires a good awareness of the clinical and radiographic diagnosis of different types of deformities thus reducing the possible functional disabilities via early management by combined orthotic, physiotherapy, and surgical treatments. Level of Clinical Evidence4

Dementia Subtypes Defined Through Neuropsychiatric Symptom-Associated Brain Connectivity Patterns.

Understanding the heterogeneity of neuropsychiatric symptoms (NPSs) and associated brain abnormalities is essential for effective management and treatment of dementia. To identify dementia subtypes with distinct functional connectivity associated with neuropsychiatric subsyndromes. Using data from the Open Access Series of Imaging Studies-3 (OASIS-3; recruitment began in 2005) and Alzheimer Disease Neuroimaging Initiative (ADNI; recruitment began in 2004) databases, this cross-sectional study analyzed resting-state functional magnetic resonance imaging (fMRI) scans, clinical assessments, and neuropsychological measures of participants aged 42 to 95 years. The fMRI data were processed from July 2022 to February 2024, with secondary analysis conducted from August 2022 to March 2024. Participants without medical conditions or medical contraindications for MRI were recruited. A multivariate sparse canonical correlation analysis was conducted to identify functional connectivity-informed NPS subsyndromes, including behavioral and anxiety subsyndromes. Subsequently, a clustering analysis was performed on obtained latent connectivity profiles to reveal neurophysiological subtypes, and differences in abnormal connectivity and phenotypic profiles between subtypes were examined. Among 1098 participants in OASIS-3, 177 individuals who had fMRI and at least 1 NPS at baseline were included (78 female [44.1%]; median [IQR] age, 72 [67-78] years) as a discovery dataset. There were 2 neuropsychiatric subsyndromes identified: behavioral (r = 0.22; P = .002; P for permutation = .007) and anxiety (r = 0.19; P = .01; P for permutation = .006) subsyndromes from connectivity NPS-associated latent features. The behavioral subsyndrome was characterized by connections predominantly involving the default mode (within-network contribution by summed correlation coefficients = 54) and somatomotor (within-network contribution = 58) networks and NPSs involving nighttime behavior disturbance (R = -0.29; P < .001), agitation (R = -0.28; P = .001), and apathy (R = -0.23; P = .007). The anxiety subsyndrome mainly consisted of connections involving the visual network (within-network contribution = 53) and anxiety-related NPSs (R = 0.36; P < .001). By clustering individuals along these 2 subsyndrome-associated connectivity latent features, 3 subtypes were found (subtype 1: 45 participants; subtype 2: 43 participants; subtype 3: 66 participants). Patients with dementia of subtype 3 exhibited similar brain connectivity and cognitive behavior patterns to those of healthy individuals. However, patients with dementia of subtypes 1 and 2 had different dysfunctional connectivity profiles involving the frontoparietal control network (FPC) and somatomotor network (the difference by summed z values was 230 within the SMN and 173 between the SMN and FPC for subtype 1 and 473 between the SMN and visual network for subtype 2) compared with those of healthy individuals. These dysfunctional connectivity patterns were associated with differences in baseline dementia severity (eg, the median [IQR] of the total score of NPSs was 2 [2-7] for subtype 3 vs 6 [3-8] for subtype 1; P = .04 and 5.5 [3-11] for subtype 2; P = .03) and longitudinal progression of cognitive impairment and behavioral dysfunction (eg, the overall interaction association between time and subtypes to orientation was F = 4.88; P = .008; using the time × subtype 3 interaction item as the reference level: β = 0.05; t = 2.6 for time × subtype 2; P = .01). These findings were further validated using a replication dataset of 193 participants (127 female [65.8%]; median [IQR] age, 74 [69-77] years) consisting of 154 newly released participants from OASIS-3 and 39 participants from ADNI. These findings may provide a novel framework to disentangle the neuropsychiatric and brain functional heterogeneity of dementia, offering a promising avenue to improve clinical management and facilitate the timely development of targeted interventions for patients with dementia.

Dementia Subtypes Defined Through Neuropsychiatric Symptom–Associated Brain Connectivity Patterns

Understanding the heterogeneity of neuropsychiatric symptoms (NPSs) and associated brain abnormalities is essential for effective management and treatment of dementia. To identify dementia subtypes with distinct functional connectivity associated with neuropsychiatric subsyndromes. Using data from the Open Access Series of Imaging Studies-3 (OASIS-3; recruitment began in 2005) and Alzheimer Disease Neuroimaging Initiative (ADNI; recruitment began in 2004) databases, this cross-sectional study analyzed resting-state functional magnetic resonance imaging (fMRI) scans, clinical assessments, and neuropsychological measures of participants aged 42 to 95 years. The fMRI data were processed from July 2022 to February 2024, with secondary analysis conducted from August 2022 to March 2024. Participants without medical conditions or medical contraindications for MRI were recruited. A multivariate sparse canonical correlation analysis was conducted to identify functional connectivity-informed NPS subsyndromes, including behavioral and anxiety subsyndromes. Subsequently, a clustering analysis was performed on obtained latent connectivity profiles to reveal neurophysiological subtypes, and differences in abnormal connectivity and phenotypic profiles between subtypes were examined. Among 1098 participants in OASIS-3, 177 individuals who had fMRI and at least 1 NPS at baseline were included (78 female [44.1%]; median [IQR] age, 72 [67-78] years) as a discovery dataset. There were 2 neuropsychiatric subsyndromes identified: behavioral (r = 0.22; P = .002; P for permutation = .007) and anxiety (r = 0.19; P = .01; P for permutation = .006) subsyndromes from connectivity NPS-associated latent features. The behavioral subsyndrome was characterized by connections predominantly involving the default mode (within-network contribution by summed correlation coefficients = 54) and somatomotor (within-network contribution = 58) networks and NPSs involving nighttime behavior disturbance (R = -0.29; P < .001), agitation (R = -0.28; P = .001), and apathy (R = -0.23; P = .007). The anxiety subsyndrome mainly consisted of connections involving the visual network (within-network contribution = 53) and anxiety-related NPSs (R = 0.36; P < .001). By clustering individuals along these 2 subsyndrome-associated connectivity latent features, 3 subtypes were found (subtype 1: 45 participants; subtype 2: 43 participants; subtype 3: 66 participants). Patients with dementia of subtype 3 exhibited similar brain connectivity and cognitive behavior patterns to those of healthy individuals. However, patients with dementia of subtypes 1 and 2 had different dysfunctional connectivity profiles involving the frontoparietal control network (FPC) and somatomotor network (the difference by summed z values was 230 within the SMN and 173 between the SMN and FPC for subtype 1 and 473 between the SMN and visual network for subtype 2) compared with those of healthy individuals. These dysfunctional connectivity patterns were associated with differences in baseline dementia severity (eg, the median [IQR] of the total score of NPSs was 2 [2-7] for subtype 3 vs 6 [3-8] for subtype 1; P = .04 and 5.5 [3-11] for subtype 2; P = .03) and longitudinal progression of cognitive impairment and behavioral dysfunction (eg, the overall interaction association between time and subtypes to orientation was F = 4.88; P = .008; using the time × subtype 3 interaction item as the reference level: β = 0.05; t = 2.6 for time × subtype 2; P = .01). These findings were further validated using a replication dataset of 193 participants (127 female [65.8%]; median [IQR] age, 74 [69-77] years) consisting of 154 newly released participants from OASIS-3 and 39 participants from ADNI. These findings may provide a novel framework to disentangle the neuropsychiatric and brain functional heterogeneity of dementia, offering a promising avenue to improve clinical management and facilitate the timely development of targeted interventions for patients with dementia.

Influence of climate variability and land cover dynamics on the spatio-temporal NDVI patterns in western hydrological regions of Bangladesh

Analyzing vegetation greenness considering climate and land cover changes is crucial for Bangladesh given the historically drier North-West and South-West regions of Bangladesh have shown prominent climatic and hydrological variations. Therefore, this study assessed the spatial and temporal variation of NDVI and its relationship with climate and land cover changes from 2000 to 2022 for these regions. In this study, Moran's I and Getis Ord Gi* were employed for spatial autocorrelation and Mann-Kendall, Sen's slope test along with Innovative Trend Analysis were deployed to identify temporal trends of NDVI. RMSE, MAE and R-squared values were assessed between computed and observed PET. Correlation of NDVI with climate variables were assessed through multivariate correlation analysis and correlation mapping. Additionally, Pearson product moment correlation was applied between different types of land cover and NDVI. Spatial autocorrelation outcomes showed that NDVI values have been clustered in distinct hotspots and cold-spots over the years. Temporal trend detection results indicate that NDVI values are rising significantly all over the regions. Multivariate correlation analysis identified no climate variable to be the limiting factor for NDVI changes. Similarly, the precipitation-NDVI correlation map displayed no significant correlation. Nonetheless, temperature-NDVI correlation map illustrated varying degrees of mostly moderate and strong positive correlations with distinct negative correlation results in the Sundarbans of South-West region. Land cover pattern analysis with NDVI showed a positive correlation to forest, cropland and vegetation area increasing and negative correlation to grassland and barren area decreasing. In this regard, Rangpur division exhibited stronger correlations than Rajshahi division in North-West. The findings indicate that NDVI changes in the regions are largely dependent on land cover changes in comparison to climate trends. This can instigate further research in other hydrological regions to explore the natural and man-made factors that can affect the greenery and vegetation density in specific regions.

Seasonal dynamics of antibiotic resistance genes and mobile genetic elements in a subtropical coastal ecosystem: Implications for environmental health risks

Antibiotic resistance poses a considerable global public health concern, leading to heightened rates of illness and mortality. However, the impact of seasonal variations and environmental factors on the health risks associated with antibiotic resistance genes (ARGs) and their assembly mechanisms is not fully understood. Based on metagenomic sequencing, this study investigated the antibiotic resistome, mobile genetic elements (MGEs), and microbiomes in a subtropical coastal ecosystem of the Beibu Gulf, China, over autumn and winter, and explored the factors influencing seasonal changes in ARG and MGE abundance and diversity. Results indicated that ARG abundance and diversity were higher in winter than in autumn, with beta-lactam and multidrug resistance genes being the most diverse and abundant, respectively. Similarly, MGE abundance and diversity increased in winter and were strongly correlated with ARGs. In contrast, more pronounced associations between microbial communities, especially archaea, and the antibiotic resistome were observed in autumn than in winter. The co-occurrence network identified multiple interactions between MGEs and various multidrug efflux pumps in winter, suggesting a potential for ARG dissemination. Multivariate correlation analyses and path modeling indicated that environmental factors driving microbial community changes predominantly influenced antibiotic resistome assembly in autumn, while the relative importance of MGEs increased significantly in winter. These findings suggest an elevated health risk associated with antimicrobial resistance in the Beibu Gulf during winter, attributed to the dissemination of ARGs by horizontal gene transfer. The observed seasonal variations highlight the dynamic nature of antibiotic resistance dissemination in coastal ecosystems, emphasizing the need for comprehensive surveillance and management measures to address the growing threat of antimicrobial resistance in vulnerable environments.

#770 Urinary PTM3 Fetuin-A in CKD patients with and without diabetic kidney disease

Abstract Background and Aims Fetuin-A is a member of the cystatins superfamily, primarily synthesized in the liver, which is involved in multiple physiological processes including calcium homeostasis, cell signaling, calcification inhibition and the regulation of insulin sensitivity. Diabetes mellitus may impact upon Fetuin-A regulation and kidney tubular cells produce Fetuin-A as part of stress and inflammatory response and release it in urine in case of kidney damage. A novel post-translational modification (PTM) fragment derived from the cleavage of Fetuin-A (PTM3) has recently emerged as a very sensitive biomarker for early kidney damage, but its usefulness in the context of CKD has not been assessed yet. In this study, we aimed at evaluating the clinical significance of urinary PTM3 fetuin A in a pilot cohort of CKD patients with or without diabetic kidney disease (DKD). Method We enrolled 47 adult patients with CKD (mean CKD-Epi 40.10 ± 16.5 mL/min/1.73 m2) due to DKD (n = 34) or other causes (n = 13). PTM3 levels were measured in the urine (uPTM3) using a commercially available ELISA kit. 15 healthy individuals served as controls. Clinical, anthropometric and laboratory parameters were also recorded. Results Collectively, all CKD patients displayed higher levels of uPTM3 than the ones of control group (0.84 [0.10-1.15] vs 29.68 [2.50-55.16] ng/mL p = 0.0005). Moreover, uPTM3 values were higher in DKD patients than in non-DKD CKD patients (39.4 [4.20-28.2] vs. 4.15 [0.29-1.38] p &amp;lt; 0.01). uPTM3 had a remarkable diagnostic capacity at ROC analysis to discriminate CKD patients from controls (AUC 0.776; p &amp;lt; 0.001; Fig. 1) and, within CKD patients, to discriminate between DKD and non-DKD patients (AUC 0.673; p = 0.02; Fig. 2). At multivariate correlation analyses, only proteinuria (β = 0.442; p = 0.02) and BMI (β = 0.334; p = 0.04) values remained significantly associated with uPTM3 Fetuin-A in the whole cohort, thus indicating that renal damage following metabolic syndrome may play a significant impact on the overall balance of this protein. Conclusion uPTM3 could be a novel sensitive biomarker reflecting renal damage in CKD patients and could also represent an additional tool for assessing the renal involvement in diabetic patients. Further studies are needed to evaluate whether uPTM3 measurement may predict different disease evolution in these patients.

In-depth analysis of volatolomic and odorous profiles of novel craft beer by permutation test features selection and multivariate correlation analysis

This research explored the impact of binary cereal blends [barley with durum wheat (DW) and soft wheat (CW)], four autochthonous yeast strains (9502, 9518, 14061 and 17290) and two refermentation sugar concentrations (6–9 g/L), on volatolomics (VOCs) and odour profiles of craft beers using unsupervised statistics. For the first time, we applied permutation test to select volatiles with higher significance in explaining variance among samples. The unsupervised approach on the 19 selected VOCs revealed cereal-yeast interaction to be the main source of variability and DW-9502-6/9, DW-17290-6, CW-17290-6 and CW-9518-6 being the best technological strategies. In particular, in samples DW-9502-6/9, concentrations of some of the selected volatiles were observed to be approximately three to more than seven times higher than the average. PLS-correlation between VOCs and odour profiles proved to be very useful in assessing the weight of each of the selected VOCs on the perception of odour notes.

Examining the role of motivation in shaping future primary school teachers' professional competence in Kazakhstan

The issue of developing the professional competence of teachers is one of the priorities in the Kazakhstani education system. One of the most significant challenges in the context of improving abilities is increasing students' motivation. This study aims to examine the role of motivation in shaping future primary school teachers' professional competence. The methods of multivariate correlation analysis, a method for finding structure diagrams of motives and their integral subsystems with their subsequent analysis were used to conduct the study. The research was conducted at the Korkyt Ata Kyzylorda University (Kyzylorda, Kazakhstan). A sample of 57 participants was used for the study. The majority of respondents were female (92.36%) and male (7.64%). According to the study, it has been found that the main reason for studying among students is to receive vocational training in order to find a good and well-paid job which provides the opportunity to use personal abilities and receive higher education in their specialty. Following the findings of this study, practical recommendations are offered to increase student motivation as a factor in developing professional competence. The developed assessment-criteria diagnostic tools can be used in pedagogical monitoring in universities and in advanced training courses for teachers.

PermDroid a framework developed using proposed feature selection approach and machine learning techniques for Android malware detection

The challenge of developing an Android malware detection framework that can identify malware in real-world apps is difficult for academicians and researchers. The vulnerability lies in the permission model of Android. Therefore, it has attracted the attention of various researchers to develop an Android malware detection model using permission or a set of permissions. Academicians and researchers have used all extracted features in previous studies, resulting in overburdening while creating malware detection models. But, the effectiveness of the machine learning model depends on the relevant features, which help in reducing the value of misclassification errors and have excellent discriminative power. A feature selection framework is proposed in this research paper that helps in selecting the relevant features. In the first stage of the proposed framework, t-test, and univariate logistic regression are implemented on our collected feature data set to classify their capacity for detecting malware. Multivariate linear regression stepwise forward selection and correlation analysis are implemented in the second stage to evaluate the correctness of the features selected in the first stage. Furthermore, the resulting features are used as input in the development of malware detection models using three ensemble methods and a neural network with six different machine-learning algorithms. The developed models’ performance is compared using two performance parameters: F-measure and Accuracy. The experiment is performed by using half a million different Android apps. The empirical findings reveal that malware detection model developed using features selected by implementing proposed feature selection framework achieved higher detection rate as compared to the model developed using all extracted features data set. Further, when compared to previously developed frameworks or methodologies, the experimental results indicates that model developed in this study achieved an accuracy of 98.8%.

Variation in thoracic inlet measurements and its correlation with pulmonary dysfunction in kyphoscoliotic deformities: a prospective case-control study.

Pulmonary dysfunction in thoracic kyphoscoliosis has been correlated with chest wall distortion, uneven trunk growth and restrictive pattern. The study aims to analyse the variation in thoracic inlet measurements on pulmonary dysfunction with varying curve magnitude and thoracic cage parameters. In a non-randomised, prospective case-control study, 80 consecutive patients with thoracic kyphoscoliosis were divided into 3 groups based on Cobb angle: Group 1 (31-50), Group 2 (51-80) and Group 3 (> 80). Thoracic inlet measurement was calculated by thoracic inlet index (TI) on MRI at the sternal level. Pulmonary function and thoracic cage parameters [hemi thorax height, rib-apex distance, AP chest diameter at sternal level and transverse thoracic diameter] were documented. TI values were compared with 20 age-matched asymptomatic controls. Multivariate correlation and regression analysis were performed to investigate the correlations. The mean age of the study cohort was 14.1 ± 4.4years, including Group 1 (6 patients), Group 2 (55 patients) and Group 3 (19 patients) versus 12.9 ± 2.2years in controls. The mean TI was 2.8 ± 0.56 in Group 1, 3.7 ± 0.9 in Group 2 and 4.0 ± 1.12 in Group 3 versus 2.6 ± 0.43 in controls. Pulmonary dysfunction was severe with TI > 7.1 (p < 0.001) in Group 3 patients with thoracic hypokyphosis. Multivariate regression for thoracic parameters and TI > 5.6 showed significant correlation of pulmonary dysfunction in Group 2 and 3 curves with apex between T1 and T4, whereas transverse thoracic diameter, rib-apex distance and hemi thorax height were weakly associated. Thoracic inlet index (TI), a neglected pre-operative variable associated with pulmonary dysfunction in thoracic kyphoscoliosis, can be evaluated on MRI without an additional cost and radiation.

Predictive factors of bone strength variation in adolescent girls according to body composition.

This study examined correlations among anthropometric parameters, body composition, bone parameters and predictive factors of bone mass in adolescent girls with different body fat percentages (%fat). A total of 129 females aged 15-18 years were categorized into 3 groups using %fat-for-age at the 50th and 95th percentiles as cutoff points (normal, over, and excess %fat groups). We recorded anthropometric data and measured the speed of sound at the tibia and radius using quantitative ultrasound. Dual-energy x-ray absorptiometry (DXA) was used to measure body composition and bone parameters, including bone mineral density (BMD), bone mineral content (BMC), and the BMD-z-score (z-score) in the lumbar spine (LS) and whole body (WB). These parameters were compared among the 3 groups using bivariate and multivariate correlation analyses. There were strong correlations among all anthropometric parameters, body composition, and DXA in the over %fat group. Lean parameters strongly correlated with LS and WB in the normal %fat group, whereas both lean mass (LM) and fat mass (FM) were positively correlated with BMC in the excess %fat group. The predictive factors of bone mass differed among the groups, as follows: lean body mass was predictive of BMD and BMC at both sites in the normal and over %fat groups; LM and body weight were predictive of LS-BMC and WB-bones, respectively, in the over %fat group; and FM was predictive of WB-bones in the excess %fat group. Body fat and waist circumference were negative predictors of bone mass. Predictive factors of bone strength appear to depend on the amount of body fat in adolescent girls.

Cough symptoms in children following COVID-19: a single-center retrospective study.

Cough is the most common respiratory symptom in children with mild coronavirus disease 2019 (COVID-19); however, evidence regarding the duration and severity of COVID-19-related cough is sparse. Herein, we investigated the correlation between cough severity/duration and disease duration in children with allergic diseases following COVID-19. This single-center, retrospective case-control study was conducted at the Department of Pediatrics, Peking University Third Hospital, from February 6-13, 2023. Children aged 0-16 completed a questionnaire survey collecting basic information and weekly cough scores for 8 consecutive weeks after COVID-19 in December 2022. The Kaplan-Meier method was used to draw event curves, and the log-rank method was used to compare inter-group differences. Stepwise regression was applied for multivariate analysis of correlations between age, sex, allergic diseases, and the degree and duration of cough following COVID-19. Overall, 686 children were included, of whom 183 (26.7%) had allergic diseases and 503 (73.3%) did not. Kaplan-Meier analysis identified significant differences between patients with and without allergic disease (log-rank test, P = 0.002) and between patients with no allergic disease and those with one and more than one allergic disease (log-rank test, P = 0.003). Multivariate regression identified a link between the presence of more than one allergic disease and coughing for >4 weeks after infection (P < 0.001). Allergic disease was the primary factor linked to cough symptoms lasting 8 weeks and cough severity (P < 0.001). Allergic disease contributes to the prolonged duration and severity of coughing in children with mild COVID-19.

Intraocular lens power calculation: angle κ and ocular biomechanics

Purpose: To study the effect of ocular biomechanics on the prediction error of intraocular lens (IOL) power calculation. Setting: Centro Hospitalar Universitário do Porto, Porto, Portugal. Design: Prospective longitudinal study. Methods: This study included 67 subjects. Before cataract surgery subjects underwent biometry with IOLMaster 700 and biomechanical analysis with Corvis Scheimpflug technology. The targeted spherical equivalent was calculated with SRK-T and Barrett Universal II. Associations between prediction error (PE), absolute prediction error (AE), and biometric and biomechanical parameters were performed with stepwise multivariate linear correlation analysis. Results: Using the SRKT formula, there was association between PE and Corvis Biomechanical Index (CBI, B = −0.531, P = .011) and between AE and the horizontal offset between the center of the pupil and the visual axis (angle κ, B = −0.274, P = .007). Considering the Barret Universal II formula, PE was independently associated with anterior chamber depth (B = −0.279, P = .021) and CBI (B = −0.520, P = .013) and AE was associated with angle κ (B = −0.370, P = .007). Conclusions: A large angle κ may reduce the predictability of IOL power calculation. Ocular biomechanics likely influence the refractive outcomes after IOL implantation. This study showed that eyes with softer corneal biomechanics had more myopic PE. This may relate to anteriorization of the effective lens position. Dynamic measurements may be the way to progress into future formulas.

Orange fruit peels from PDO varieties of Ribera (Sicily, Italy): An insight into the chemistry and bioactivity of volatile and non-volatile secondary metabolites extracted using a microwave-assisted method

Peels of Washington Navel (WAS), Navelina (NAV), and Vaniglia Apireno (VAN) orange fruits from Ribera (Sicily, Italy) represent abundant by-products of the Italian agro-food sector. In this work, volatile (VE) and non-volatile (NVE) extracts were obtained from fresh peels using a microwave-assisted protocol, and were characterized for their content in secondary metabolites and bioactivity. VEs exerted antibacterial activity against different pathogens, and were toxic on Caco2 cells. Their main component was limonene (>85 %). NVEs inhibited tyrosinase, amylase, and glucosidase in vitro, and exerted significant antioxidant effects on THP-1 XBlue cells. They showed also anti-inflammatory properties, by decreasing NF-κB activity in LPS-stimulated cells. Putative molecular effectors were highlighted by multivariate correlation analysis. Overall, NVEs may represent novel sustainable nutraceutical ingredients with anti-inflammatory and metabolic properties, and can be obtained by using eco-sustainable approaches. Our results will encourage the reuse of by-products of the orange processing chain and will contribute to increase its circularity in the future.

Multivariate canonical correlation analysis identifies additional genetic variants for chronic kidney disease

Chronic kidney diseases (CKD) have genetic associations with kidney function. Univariate genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), two complementary kidney function markers. However, it is unknown whether additional SNPs for kidney function can be identified by multivariate statistical analysis. To address this, we applied canonical correlation analysis (CCA), a multivariate method, to two individual-level CKD genotype datasets, and metaCCA to two published GWAS summary statistics datasets. We identified SNPs previously associated with kidney function by published univariate GWASs with high replication rates, validating the metaCCA method. We then extended discovery and identified previously unreported lead SNPs for both kidney function markers, jointly. These showed expression quantitative trait loci (eQTL) colocalisation with genes having significant differential expression between CKD and healthy individuals. Several of these identified lead missense SNPs were predicted to have a functional impact, including in SLC14A2. We also identified previously unreported lead SNPs that showed significant correlation with both kidney function markers, jointly, in the European ancestry CKDGen, National Unified Renal Translational Research Enterprise (NURTuRE)-CKD and Salford Kidney Study (SKS) datasets. Of these, rs3094060 colocalised with FLOT1 gene expression and was significantly more common in CKD cases in both NURTURE-CKD and SKS, than in the general population. Overall, by using multivariate analysis by CCA, we identified additional SNPs and genes for both kidney function and CKD, that can be prioritised for further CKD analyses.

A mixture of mobility and meteorological data provides a high correlation with COVID-19 growth in an infection-naive population: a study for Spanish provinces.

We use Spanish data from August 2020 to March 2021 as a natural experiment to analyze how a standardized measure of COVID-19 growth correlates with asymmetric meteorological and mobility situations in 48 Spanish provinces. The period of time is selected prior to vaccination so that the level of susceptibility was high, and during geographically asymmetric implementation of non-pharmacological interventions. We develop reliable aggregated mobility data from different public sources and also compute the average meteorological time series of temperature, dew point, and UV radiance in each Spanish province from satellite data. We perform a dimensionality reduction of the data using principal component analysis and investigate univariate and multivariate correlations of mobility and meteorological data with COVID-19 growth. We find significant, but generally weak, univariate correlations for weekday aggregated mobility in some, but not all, provinces. On the other hand, principal component analysis shows that the different mobility time series can be properly reduced to three time series. A multivariate time-lagged canonical correlation analysis of the COVID-19 growth rate with these three time series reveals a highly significant correlation, with a median R-squared of 0.65. The univariate correlation between meteorological data and COVID-19 growth is generally not significant, but adding its two main principal components to the mobility multivariate analysis increases correlations significantly, reaching correlation coefficients between 0.6 and 0.98 in all provinces with a median R-squared of 0.85. This result is robust to different approaches in the reduction of dimensionality of the data series. Our results suggest an important effect of mobility on COVID-19 cases growth rate. This effect is generally not observed for meteorological variables, although in some Spanish provinces it can become relevant. The correlation between mobility and growth rate is maximal at a time delay of 2-3 weeks, which agrees well with the expected 5?10 day delays between infection, development of symptoms, and the detection/report of the case.

Decoding the dynamic perception of risk and speed using naturalistic stimuli: A multivariate, whole-brain analysis.

Time-resolved decoding of speed and risk perception in car driving is important for understanding the perceptual processes related to driving safety. In this study, we used an fMRI-compatible trackball with naturalistic stimuli to record dynamic ratings of perceived risk and speed and investigated the degree to which different brain regions were able to decode these. We presented participants with first-person perspective videos of cars racing on the same course. These videos varied in terms of subjectively perceived speed and risk profiles, as determined during a behavioral pilot. During the fMRI experiment, participants used the trackball to dynamically rate subjective risk in a first and speed in a second session and assessed overall risk and speed after watching each video. A standard multivariate correlation analysis based on these ratings revealed sparse decodability in visual areas only for the risk ratings. In contrast, the dynamic rating-based correlation analysis uncovered frontal, visual, and temporal region activation for subjective risk and dorsal visual stream and temporal region activation for subjectively perceived speed. Interestingly, further analyses showed that the brain regions for decoding risk changed over time, whereas those for decoding speed remained constant. Overall, our results demonstrate the advantages of time-resolved decoding to help our understanding of the dynamic networks associated with decoding risk and speed perception in realistic driving scenarios.

Urinary Post-Translationally Modified Fetuin-A (uPTM-FetA) in Chronic Kidney Disease Patients with and without Diabetic Kidney Disease.

Background and Objectives: A novel post-translational modification (PTM) fragment derived from the cleavage of Fetuin-A (PTM-FetA) has recently emerged as a sensitive biomarker for kidney damage in diabetic patients, but evidence in other chronic renal diseases is lacking. In this pilot study, we aimed at evaluating the clinical significance of urinary PTM-FetA (uPTM-FetA) in a mixed cohort of patients with non-advanced chronic kidney disease (CKD) secondary to diabetic kidney disease (DKD) or other causes. Materials and Methods: We enrolled 47 adult patients with CKD (mean CKD-Epi 40.10 ± 16.5 mL/min/1.73 m2) due to DKD (n = 34) or other etiology (n = 13). uPTM-FetA was measured in the urine using a commercially available ELISA kit. Fifteen healthy individuals served as controls. Results: Collectively, all CKD patients displayed remarkably higher levels of uPTM-FetA than controls (0.84 [0.10-1.15] vs. 29.68 [2.50-55.16] ng/mL p = 0.0005), but values were lower in non-DKD than in DKD patients (1.66 [0.09-4.19] vs. 13.9 [0.01-45.02] ng/mL; p = 0.01). uPTM-FetA showed a great diagnostic capacity at ROC analyses to identify the presence of CKD (AUC 0.776; p < 0.001) and, within CKD patients, to discriminate the diabetic and non-diabetic etiology (AUC 0.673; p = 0.02). At multivariate correlation analyses, proteinuria (β = 0.442; p = 0.02) and BMI (β = -0.334; p = 0.04) were the sole independent predictors of uPTM-FetA in this study population. Conclusions: uPTM-FetA could be a novel sensitive biomarker at the crossroad of chronic renal damage and metabolic dysfunction. Additionally, this biomarker could also represent a non-invasive, complementary tool for discriminating among different CKD etiologies (DKD vs. non-DKD) in difficult cases or when renal biopsy is not available.