Quantifying and addressing the impact of measurement error in network models

Network psychometric models are often estimated using a single indicator for each node in the network, thus failing to consider potential measurement error. In this study, we investigate the impact of measurement error on cross-sectional network models. First, we conduct a simulation study to evaluate the performance of models based on single indicators as well as models that utilize information from multiple indicators per node, including average scores, factor scores, and latent variables. Our results demonstrate that measurement error impairs the reliability and performance of network models, especially when using single indicators. The reliability and performance of network models improves substantially with increasing sample size and when using methods that combine information from multiple indicators per node. Second, we use empirical data from the STAR*D trial (n = 3,731) to further evaluate the impact of measurement error. In the STAR*D trial, depression symptoms were assessed via three questionnaires, providing multiple indicators per symptom. Consistent with our simulation results, we find that when using sub-samples of this dataset, the discrepancy between the three single-indicator networks (one network per questionnaire) diminishes with increasing sample size. Together, our simulated and empirical findings provide evidence that measurement error can hinder network estimation when working with smaller samples and offers guidance on methods to mitigate measurement error.Stress and Psychopatholog

Insights From Liver-Humanized Mice on Cholesterol Lipoprotein Metabolism and LXR-Agonist Pharmacodynamics in Humans

Background and Aims Genetically modified mice have been used extensively to study human disease. However, the data gained are not always translatable to humans because of major species differences. Liver-humanized mice (LHM) are considered a promising model to study human hepatic and systemic metabolism. Therefore, we aimed to further explore their lipoprotein metabolism and to characterize key hepatic species-related, physiological differences. Approach and Results Fah(-/-), Rag2(-/-), and Il2rg(-/-) knockout mice on the nonobese diabetic (FRGN) background were repopulated with primary human hepatocytes from different donors. Cholesterol lipoprotein profiles of LHM showed a human-like pattern, characterized by a high ratio of low-density lipoprotein to high-density lipoprotein, and dependency on the human donor. This pattern was determined by a higher level of apolipoprotein B100 in circulation, as a result of lower hepatic mRNA editing and low-density lipoprotein receptor expression, and higher levels of circulating proprotein convertase subtilisin/kexin type 9. As a consequence, LHM lipoproteins bind to human aortic proteoglycans in a pattern similar to human lipoproteins. Unexpectedly, cholesteryl ester transfer protein was not required to determine the human-like cholesterol lipoprotein profile. Moreover, LHM treated with GW3965 mimicked the negative lipid outcomes of the first human trial of liver X receptor stimulation (i.e., a dramatic increase of cholesterol and triglycerides in circulation). Innovatively, LHM allowed the characterization of these effects at a molecular level. Conclusions LHM represent an interesting translatable model of human hepatic and lipoprotein metabolism. Because several metabolic parameters displayed donor dependency, LHM may also be used in studies for personalized medicine.Peer reviewe

The Beck Cognitive Insight Scale (BCIS): translation and validation of the Taiwanese version

<p>Abstract</p> <p>Background</p> <p>Over the last few decades, research concerning the insight of patients with schizophrenia and its relationships with other clinical variables has been given much attention in the clinical setting. Since that time, a series of instruments assessing insight have been developed. The purpose of this study was to examine the reliability and validity of the Taiwanese version of the Beck Cognitive Insight Scale (BCIS). The BCIS is a self-administered instrument designed to evaluate cognitive processes that involves reevaluating patients' anomalous experiences and specific misinterpretations.</p> <p>Methods</p> <p>The English language version of the BCIS was translated into Taiwanese for use in this study. A total of 180 subjects with and without psychosis completed the Taiwanese version of the BCIS and additional evaluations to assess researcher-rated insight scales and psychopathology. Psychometric properties (factor structures and various types of reliability and validity) were assessed for this translated questionnaire.</p> <p>Results</p> <p>Overall, the Taiwanese version of the BCIS showed good reliability and stability over time. This translated scale comprised a two-factor solution corresponding to reflective attitude and certain attitude subscales. Following the validation of the internal structure of the scale, we obtained an R-C (reflective attitude minus certain attitude) index of the translated BCIS, representing the measurement of cognitive insight by subtracting the score of the certain attitude subscale from that of the reflective attitude subscale. As predicted, the differences in mean reflective attitude, certain attitude and R-C index between subjects with and without psychosis were significant. Our data also demonstrated that psychotic patients were significantly less reflective, more confident in their beliefs, and had less cognitive insight compared with nonpsychotic control groups.</p> <p>Conclusions</p> <p>In light of these findings, we believe that the Taiwanese version of BCIS is a valid and reliable instrument for the assessment of cognitive insight in psychotic patients.</p

Association between plasma metabolites and gene expression profiles in five porcine endocrine tissues

Background: Endocrine tissues play a fundamental role in maintaining homeostasis of plasma metabolites such as non-esterified fatty acids and glucose, the levels of which reflect the energy balance or the health status of animals. However, the relationship between the transcriptome of endocrine tissues and plasma metabolites has been poorly studied. Methods: We determined the blood levels of 12 plasma metabolites in 27 pigs belonging to five breeds, each breed consisting of both females and males. The transcriptome of five endocrine tissues i.e. hypothalamus, adenohypophysis, thyroid gland, gonads and backfat tissues from 16 out of the 27 pigs was also determined. Sex and breed effects on the 12 plasma metabolites were investigated and associations between genes expressed in the five endocrine tissues and the 12 plasma metabolites measured were analyzed. A probeset was defined as a quantitative trait transcript (QTT) when its association with a particular metabolic trait achieved a nominal P value < 0.01. Results: A larger than expected number of QTT was found for non-esterified fatty acids and alanine aminotransferase in at least two tissues. The associations were highly tissue-specific. The QTT within the tissues were divided into co-expression network modules enriched for genes in Kyoto Encyclopedia of Genes and Genomes or gene ontology categories that are related to the physiological functions of the corresponding tissues. We also explored a multi-tissue co-expression network using QTT for non-esterified fatty acids from the five tissues and found that a module, enriched in hypothalamus QTT, was positioned at the centre of the entire multi-tissue network. Conclusions: These results emphasize the relationships between endocrine tissues and plasma metabolites in terms of gene expression. Highly tissue-specific association patterns suggest that candidate genes or gene pathways should be investigated in the context of specific tissues

Can cognitive insight predict symptom remission in a first episode psychosis cohort?

BACKGROUND: The outcome of first episode psychosis (FEP) is highly variable and difficult to predict. Cognitive insight measured at illness onset has previously been found to predict psychopathology 12-months later. The aims of this study were to examine whether the prospective relationship between cognitive insight and symptom severity is evident at four-years following FEP and to examine some psychological correlates of cognitive insight. METHODS: FEP participants (n = 90) completed the Beck Cognitive Insight Scale (BCIS) at illness onset, and associations between BCIS scores with symptom severity outcomes (4-years after FEP) were assessed. The BCIS scales (self-reflectiveness and self-certainty) were examined as a composite score, and individually compared to other cognitive measures (IQ and jumping to conclusions (JTC) bias). RESULTS: Regression analyses revealed that the cognitive insight composite did not predict 4-year symptom remission in this study while the self-reflection subscale of the BCIS predicted severity of symptoms at 4-years. Self-certainty items of the BCIS were not associated with symptom severity. Significant correlations between the JTC bias, self-certainty and IQ were found, but self-reflection did not correlate with these other cognitive measures. CONCLUSIONS: Self-reflective capacity is a more relevant and independent cognitive construct than self-certainty for predicting prospective symptom severity in psychosis. Improving self-reflection may be a useful target for early intervention research

Assessing cognitive insight in nonpsychiatric individuals and outpatients with schizophrenia in Taiwan: an investigation using the Beck Cognitive Insight Scale

<p>Abstract</p> <p>Background</p> <p>The Beck Cognitive Insight Scale (BCIS) was designed for the assessment of the cognitive processes involved in self-reflection and the ability to modify erroneous beliefs and misinterpretations. Studies investigating the factor structure of the BCIS have indicated a two-factor model in the psychotic population. The factor structure of the BCIS, however, has not received much consideration in the nonpsychiatric population. The present study examined the factor structure and validity of the BCIS and compared its scores between nonpsychiatric individuals and outpatients with psychosis.</p> <p>Method</p> <p>The Taiwanese version of the BCIS was administered to 507 nonpsychiatric individuals and 118 outpatients with schizophrenia. The psychometric properties of the BCIS were examined through the following analyses: exploratory and confirmatory factor analyses, reliability, correlation analyses, and discriminative validity.</p> <p>Results</p> <p>The BCIS showed adequate internal consistency and stability over time. Exploratory and confirmatory factor analyses on the 15-item measure indicated a two-factor solution that supported the two dimensions of the Taiwanese BCIS, which was also observed with the original BCIS. Following the construct validation, we obtained a composite index (self-reflectiveness minus self-certainty) of the Taiwanese BCIS that reflected cognitive insight. Consistent with previous studies, our results indicated that psychosis is associated with low self-reflectiveness and high self-certainty, which possibly reflect lower cognitive insight. Our results also showed that better cognitive insight is related to worse depression in patients with schizophrenia spectrum disorders, but not in nonpsychiatric individuals. The receiver operating characteristic (ROC) analyses revealed that the area under the curve (AUC) was 0.731. A composite index of 3 was a good limit, with a sensitivity of 87% and a specificity of 51%.</p> <p>Conclusion</p> <p>The BCIS proved to be useful for measuring cognitive insight in Taiwanese nonpsychiatric and psychotic populations.</p

Characteristics of horse meat production in Northern Italy

Horse meat consumption is widespread in Italy since ancient times, Among European countries, Italy is the major consumer of horse meat and related meat products. However, national production has never been able to satisfy market demand; the refore more than half of the consumed meat is imported. A survey on productive assets has been carried out in a horse and bovine slaughterhouse located on Emilia-Romagna region to investigate the characteristics of horse meat production in Northern Italy. The two-years period 2004-2005 was chosen for this investigation. The abattoir under examination provided to slaughter 4,375 horses in 2004 and 4,770 in 2005. Around 16% of the slaughtered horses were foals, being less than two years old. The results of the present survey confirmed that half of the slaughtered horses came from Hungary and, to a much lesser extent, from Poland. The horses of Italian origin were mainly from Lombardia, Emilia-Romagna, Veneto, and Toscana regions