Concept: Correlation and dependence
Empathy is the ability to recognize and respond to the emotional states of other individuals. It is an important psychological process that facilitates navigating social interactions and maintaining relationships, which are important for well-being. Several psychological studies have identified difficulties in both self-report and performance-based measures of empathy in a range of psychiatric conditions. To date, no study has systematically investigated the genetic architecture of empathy using genome-wide association studies (GWAS). Here we report the results of the largest GWAS of empathy to date using a well-validated self-report measure of empathy, the Empathy Quotient (EQ), in 46,861 research participants from 23andMe, Inc. We identify 11 suggestive loci (P < 1 × 10-6), though none were significant at P < 2.5 × 10-8after correcting for multiple testing. The most significant SNP was identified in the non-stratified analysis (rs4882760; P = 4.29 × 10-8), and is an intronic SNP in TMEM132C. The EQ had a modest but significant narrow-sense heritability (0.11 ± 0.014; P = 1.7 × 10-14). As predicted, based on earlier work, we confirmed a significant female advantage on the EQ (P < 2 × 10-16, Cohen's d = 0.65). We identified similar SNP heritability and high genetic correlation between the sexes. Also, as predicted, we identified a significant negative genetic correlation between autism and the EQ (rg= -0.27 ± 0.07, P = 1.63 × 10-4). We also identified a significant positive genetic correlation between the EQ and risk for schizophrenia (rg= 0.19 ± 0.04; P = 1.36 × 10-5), risk for anorexia nervosa (rg= 0.32 ± 0.09; P = 6 × 10-4), and extraversion (rg= 0.45 ± 0.08; 5.7 × 10-8). This is the first GWAS of self-reported empathy. The results suggest that the genetic variations associated with empathy also play a role in psychiatric conditions and psychological traits.
Human umbilical tissue-derived cells (hUTC) represent an attractive cell source and a potential technology for neurorestoration and improvement of functional outcomes following stroke. Male Wistar rats were subjected to a transient middle cerebral artery occlusion (tMCAo) and were intravenously administered hUTC (N = 11) or vehicle (N = 10) 48 hrs after stroke. White matter and vascular reorganization was monitored over a 12-week period using MRI and histopathology. MRI results were correlated with neurological functional and histology outcomes to demonstrate that MRI can be a useful tool to measure structural recovery after stroke. MRI revealed a significant reduction in the ventricular volume expansion and improvement in cerebral blood flow (CBF) in the hUTC treated group compared to vehicle treated group. Treatment with hUTC resulted in histological and functional improvements as evidenced by enhanced expression of vWF and synaptophysin, and improved outcomes on behavioral tests. Significant correlations were detected between MRI ventricular volumes and histological lesion volume as well as number of apoptotic cells. A positive correlation was also observed between MRI CBF or cerebral blood volume (CBV) and histological synaptic density. Neurological functional tests were also significantly correlated with MRI ventricular volume and CBV. Our data demonstrated that MRI measurements can detect the effect of hUTC therapy on the brain reorganization and exhibited positive correlation with histological measurements of brain structural changes and functional behavioral tests after stroke. MRI ventricular volumes provided the most sensitive index in monitoring brain remodeling and treatment effects and highly correlated with histological and functional measurements.
BACKGROUND: Dengue, a mosquito-borne febrile viral disease, is found in tropical and sub-tropical regions and is now extending its range to temperate regions. The spread of the dengue viruses mainly depends on vector population (Aedes aegypti and Aedes albopictus), which is influenced by changing climatic conditions and various land-use/land-cover types. Spatial display of the relationship between dengue vector density and land-cover types is required to describe a near-future viral outbreak scenario. This study is aimed at exploring how land-cover types are linked to the behavior of dengue-transmitting mosquitoes. METHODS: Surveys were conducted in 92 villages of Phitsanulok Province Thailand. The sampling was conducted on three separate occasions in the months of March, May and July. Dengue indices, i.e. container index (C.I.), house index (H.I.) and Breteau index (B.I.) were used to map habitats conducible to dengue vector growth. Spatial epidemiological analysis using Bivariate Pearson’s correlation was conducted to evaluate the level of interdependence between larval density and land-use types. Factor analysis using principal component analysis (PCA) with varimax rotation was performed to ascertain the variance among land-use types. Furthermore, spatial ring method was used as to visualize spatially referenced, multivariate and temporal data in single information graphic. RESULTS: Results of dengue indices showed that the settlements around gasoline stations/workshops, in the vicinity of marsh/swamp and rice paddy appeared to be favorable habitat for dengue vector propagation at highly significant and positive correlation (p = 0.001) in the month of May. Settlements around the institutional areas were highly significant and positively correlated (p = 0.01) with H.I. in the month of March. Moreover, dengue indices in the month of March showed a significant and positive correlation (p <= 0.05) with deciduous forest. The H.I. of people living around horticulture land were significantly and positively correlated (p = 0.05) during the month ofMay, and perennial vegetation showed a highly significant and positive correlation (p = 0.001) in the month of March with C.I. and significant and positive correlation (p <= 0.05) with B.I., respectively. CONCLUSIONS: The study concluded that gasoline stations/workshops, rice paddy, marsh/swamp and deciduous forests played highly significant role in dengue vector growth. Thus, the spatio-temporal relationships of dengue vector larval density and land-use types may help to predict favorable dengue habitat, and thereby enables public healthcare managers to take precautionary measures to prevent impending dengue outbreak.
An important problem in systems biology is to reconstruct gene regulatory networks (GRNs) from experimental data and other a priori information. The DREAM project offers some types of experimental data, such as knockout data, knockdown data, time series data, etc. Among them, multifactorial perturbation data are easier and less expensive to obtain than other types of experimental data and are thus more common in practice. In this article, a new algorithm is presented for the inference of GRNs using the DREAM4 multifactorial perturbation data. The GRN inference problem among [Formula: see text] genes is decomposed into [Formula: see text] different regression problems. In each of the regression problems, the expression level of a target gene is predicted solely from the expression level of a potential regulation gene. For different potential regulation genes, different weights for a specific target gene are constructed by using the sum of squared residuals and the Pearson correlation coefficient. Then these weights are normalized to reflect effort differences of regulating distinct genes. By appropriately choosing the parameters of the power law, we constructe a 0-1 integer programming problem. By solving this problem, direct regulation genes for an arbitrary gene can be estimated. And, the normalized weight of a gene is modified, on the basis of the estimation results about the existence of direct regulations to it. These normalized and modified weights are used in queuing the possibility of the existence of a corresponding direct regulation. Computation results with the DREAM4 In Silico Size 100 Multifactorial subchallenge show that estimation performances of the suggested algorithm can even outperform the best team. Using the real data provided by the DREAM5 Network Inference Challenge, estimation performances can be ranked third. Furthermore, the high precision of the obtained most reliable predictions shows the suggested algorithm may be helpful in guiding biological experiment designs.
- Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
- Published over 5 years ago
The aim of this study was to quantify anteroposterior facial soft tissue changes with respect to underlying skeletal movements after Le Fort I maxillary advancement and mandibular setback surgery with sagittal split osteotomy in Class III skeletal deformity by using lateral cephalograms taken before and after the operation. The material consisted of 31 patient (15 female, 16 male cases, mean age was 26.7 ± 2.5 years) with Class III skeletal deformity. All patients were treated by Le Fort I maxillary advancement and mandibular setback surgery with sagittal split osteotomy. Lateral cephalograms were taken before and 1.4 ± 0.3 years after surgery. Wilcoxon test was used to compare the pre- and post-surgical measurements. Pearson correlation test was used to compare the relationships between the skeletal, dental and facial soft tissue changes. In the maxilla, the APOINTAP (the anteroposterior position of A point) and ITIPAP (the anteroposterior position of upper incisor) showed significant protractions (-3.19 ± 3.63, and -3.19 ± 4.52, p < 0.01). In the mandible, the L1TIPAP (the anteroposterior position of lower incisor, -3.20 ± 5.83, p < 0.01), L1TIPSI (the superoinferior position of lower incisor, -2.43 ± 10.31, p < 0.05), BPOINTSP (the superoinferior position of B point, -2.28 ± 12.51, p < 0.05) and BPOINTAP (the anteroposterior position of B point, -3.19 ± 9.31, p < 0.01) showed significant retractions and upper positions after bimaxillary surgery. The insignificant decrease in soft tissue Pog-Vert distance was correlated the significant upper position of B point and lower incisor (r: 0.851, p < 0.001 and r: 0.842, p < 0.001).
PURPOSE: Existing patient self-reported shoulder scoring systems fail to express physicians' points of view, and understanding the wording can sometimes lead to confusion in Easterners. We sought to develop a valid, reliable, and responsive shoulder scoring system that combines the points of view of physicians and patients and is easily understood for worldwide applicability. METHODS: Six steps were followed to develop the scale: (1) investigation, identification of a specific population, and patient and physician interviews; (2) item generation, according to existing shoulder scales, a literature review, and patient and physician interviews; (3) item reduction, by combining and adjusting items; (4) formatting of the questionnaire, designed using both subjective and objective scales, with a 100-point score range; (5) pretesting, to eliminate confusion and misunderstanding of items, and (6) preliminary evaluation. Pearson correlation coefficients were calculated to assess validity (compared with American Shoulder and Elbow Surgeons, Constant-Murley, and University of California, Los Angeles scores), intraclass correlation coefficients were calculated to assess reliability (with a 2-week test-retest interval), and the standardized response mean was calculated to assess responsiveness (comparing preoperative and postoperative scores in patients). RESULTS: The final scoring system was designed to have a 100-point score range, with higher scores indicating better function. It consisted of self-report assessment by patients (61 points in total) and objective assessment by physicians (39 points in total). Updated scales, including a night pain subscale, patient-physician satisfaction, and 2-dimensional visual analog scale tool, were incorporated in our system. Compared with the other 3 scoring systems (American Shoulder and Elbow Surgeons, Constant-Murley, and University of California, Los Angeles scores), the new scoring system has shown favorable validity, with a Pearson correlation coefficient greater than 0.7. In addition, the intraclass correlation coefficient was greater than 0.9 during a 2-week test-retest interval, indicating high reliability, and the standardized response mean of the new system was greater than that of the other 3 scoring systems, indicating sensitive responsiveness. CONCLUSIONS: A new shoulder scoring system has been developed based on patients' and physicians' points of view and worldwide applicability and was verified to be valid, reliable, and responsive. The new scoring system includes a 2-dimensional visual analog scale, night pain subscale, and patient-physician satisfaction scale, which are not included in the existing scoring systems. LEVEL OF EVIDENCE: Level III, development of diagnostic criteria.
We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on (18)F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 (18)F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75±1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUV(max) (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUV(max). We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16).
Resistive random access memory based on the resistive switching phenomenon is emerging as a strong candidate for next generation non-volatile memory. So far, the resistive switching effect has been observed in many transition metal oxides, including strongly correlated ones, such as, cuprate superconductors, colossal magnetoresistant manganites and Mott insulators. However, up to now, no clear evidence of the possible relevance of strong correlation effects in the mechanism of resistive switching has been reported. Here, we study Pr0.7Ca0.3MnO3, which shows bipolar resistive switching. Performing micro-spectroscopic studies on its bare surface we are able to track the systematic electronic structure changes in both, the low and high resistance state. We find that a large change in the electronic conductance is due to field-induced oxygen vacancies, which drives a Mott metal-insulator transition at the surface. Our study demonstrates that strong correlation effects may be incorporated to the realm of the emerging oxide electronics.
Dimensional ultrasonographic relationship of the right lobe of pancreas with associated anatomic landmarks in clinically normal dogs
- The Journal of veterinary medical science / the Japanese Society of Veterinary Science
- Published almost 3 years ago
The purpose of this prospective study was to establish the ultrasonographic characteristics of the dimension of the right pancreatic lobe with that of the associated anatomic landmarks in healthy dogs. Ultrasonographic examinations were performed on 25 dogs. The thickness of the right pancreatic lobe was compared with that of mural thickness of duodenum, diameters of duodenum, pancreatic duct, abdominal aorta, portal vein, caudal vena cava, and length and width of the right kidney and right adrenal gland. The correlation between each pancreatic parameter and the dimensions of the anatomical landmarks were assessed using linear regression analysis and Pearson’s correlation coefficient ® test. Significant, but weak linear correlations were observed between thickness of right pancreatic lobe with that of duodenum mural thickness (r=0.605, R(2)=0.339, P=0.001); duodenum diameter (r=0.573, R(2)=0.299, P=0.003); and right adrenal gland length (r=0.508, R(2)=0.052, P=0.01). There was no significant dimensional relationship with other selected anatomic landmarks. The ratio between the thickness of right pancreatic lobe and the mural thickness of duodenum, diameter of duodenum and length of right adrenal gland were 2.88 ± 0.53, 1.27 ± 0.27, and 0.81 ± 0.15, respectively. Calculating the ratio of thickness of the right pancreatic lobe with the dimension of significantly correlated anatomic landmarks is a useful and simple method for evaluating the size of the right pancreatic lobe in dogs in clinical practice.
Recent research shows bidirectional communication between the normal brain and the peripheral immune system. Glioma is a primary brain tumor characterized by systemic immunosuppression. To better understand gliomagenesis, we evaluated associations between 277 prediagnostic serum cytokines and glioma. We used glioma (n = 487) and matched control (n = 487) specimens from the Janus Serum Bank Cohort in Oslo, Norway. Conditional logistic regression allowed us to identify those cytokines that were individually associated with glioma. Next, we used heat maps to compare case to control Pearson correlation matrices of 12 cytokines modeled in an in silico study of the interaction between the microenvironment and the tumor. We did the same for case-control correlation matrices of lasso-selected cytokines and all 277 cytokines in the data set. Cytokines related to glioma risk (P ≤ .05) more than 10 years before diagnosis are sIL10RB, VEGF, beta-Catenin and CCL22. LIF was associated with decreased glioma risk within five years before glioma diagnosis (odds ratio (OR) = 0.47, 95% confidence interval (CI) = 0.23, 0.94). After adjustment for cytokines above, the previously observed interaction between IL4 and sIL4RA persisted (> 20 years before diagnosis, OR = 1.72, 95% CI = 1.20, 2.47). In addition, during this period, case correlations among 12 cytokines were weaker than were those among controls. This pattern was also observed among 30 lasso- selected cytokines and all 277 cytokines. We identified four cytokines and one interaction term that were independently related to glioma risk. We have documented prediagnostic changes in serum cytokine levels that may reflect the presence of a preclinical tumor.