The Relationship between Different Assays for Detection and Quantification of Amyloid Beta 42 in Human Cerebrospinal Fluid

Alzheimer's disease (AD), which is characterized by a degeneration of neurons and their synapses, is one of the most common forms of dementia. CSF levels of amyloid β42 (Aβ42) have been recognized as a strong candidate to serve as an AD biomarker. There are a number of commercial assays that are routinely employed for measuring Aβ42; however, these assays give diverse ranges for the absolute levels of CSF Aβ42. In order to employ CSF Aβ42 as a biomarker across multiple laboratories, studies need to be performed to understand the relationship between the different platforms. We have analyzed CSF samples from both diseased and nondiseased subjects with two different widely used assay platforms. The results showed that different values for the levels of CSF Aβ42 were reported, depending on the assay used. Nonetheless, both assays clearly demonstrated statistically significant differences in the levels of Aβ42 in CSF from AD relative to age-matched controls (AMC). This paper provides essential data for establishing the relationship between these assays and provides an important step towards the validation of Aβ42 as a biomarker for AD

The unique skeleton of siliceous sponges (Porifera; Hexactinellida and Demospongiae) that evolved first from the Urmetazoa during the Proterozoic: a review

Sponges (phylum Porifera) had been considered as an enigmatic phylum, prior to the analysis of their genetic repertoire/tool kit. Already with the isolation of the first adhesion molecule, galectin, it became clear that the sequences of sponge cell surface receptors and of molecules forming the intracellular signal transduction pathways triggered by them, share high similarity with those identified in other metazoan phyla. These studies demonstrated that all metazoan phyla, including Porifera, originate from one common ancestor, the Urmetazoa. The sponges evolved prior to the Ediacaran-Cambrian boundary (542 million years ago [myr]) during two major &quot;snowball earth events&quot;, the Sturtian glaciation (710 to 680 myr) and the Varanger-Marinoan ice ages (605 to 585 myr). During this period the ocean was richer in silica due to the silicate weathering. The oldest sponge fossils (Hexactinellida) have been described from Australia, China and Mongolia and are thought to have existed coeval with the diverse Ediacara fauna. Only little younger are the fossils discovered in the Sansha section in Hunan (Early Cambrian; China). It has been proposed that only the sponges possessed the genetic repertoire to cope with the adverse conditions, e.g. temperature-protection molecules or proteins protecting them against ultraviolet radiation. <br><br> The skeletal elements of the Hexactinellida (model organisms <i>Monorhaphis chuni</i> and <i>Monorhaphis intermedia</i> or <i>Hyalonema sieboldi</i>) and Demospongiae (models <i>Suberites domuncula</i> and <i>Geodia cydonium</i>), the spicules, are formed enzymatically by the anabolic enzyme silicatein and the catabolic enzyme silicase. Both, the spicules of Hexactinellida and of Demospongiae, comprise a central axial canal and an axial filament which harbors the silicatein. After intracellular formation of the first lamella around the channel and the subsequent extracellular apposition of further lamellae the spicules are completed in a net formed of collagen fibers. <br><br> The data summarized here substantiate that with the finding of silicatein a new aera in the field of bio/inorganic chemistry started. For the first time strategies could be formulated and experimentally proven that allow the formation/synthesis of inorganic structures by organic molecules. These findings are not only of importance for the further understanding of basic pathways in the body plan formation of sponges but also of eminent importance for applied/commercial processes in a sustainable use of biomolecules for novel bio/inorganic materials

Factors associated with suicidal attempts in female patients with mood disorder

AimThis study aims to establish a nomogram model to predict the relevance of SA in Chinese female patients with mood disorder (MD).MethodThe study included 396 female participants who were diagnosed with MD Diagnostic Group (F30–F39) according to the 10th Edition of Disease and Related Health Problems (ICD-10). Assessing the differences of demographic information and clinical characteristics between the two groups. LASSO Logistic Regression Analyses was used to identify the risk factors of SA. A nomogram was further used to construct a prediction model. Bootstrap re-sampling was used to internally validate the final model. The Receiver Operating Characteristic (ROC) curve and C-index was also used to evaluate the accuracy of the prediction model.ResultLASSO regression analysis showed that five factors led to the occurrence of suicidality, including BMI (β = −0.02, SE = 0.02), social dysfunction (β = 1.72, SE = 0.24), time interval between first onset and first dose (β = 0.03, SE = 0.01), polarity at onset (β = −1.13, SE = 0.25), and times of hospitalization (β = −0.11, SE = 0.06). We assessed the ability of the nomogram model to recognize suicidality, with good results (AUC = 0.76, 95% CI: 0.71–0.80). Indicating that the nomogram had a good consistency (C-index: 0.756, 95% CI: 0.750–0.758). The C-index of bootstrap resampling with 100 replicates for internal validation was 0.740, which further demonstrated the excellent calibration of predicted and observed risks.ConclusionFive factors, namely BMI, social dysfunction, time interval between first onset and first dose, polarity at onset, and times of hospitalization, were found to be significantly associated with the development of suicidality in patients with MD. By incorporating these factors into a nomogram model, we can accurately predict the risk of suicide in MD patients. It is crucial to closely monitor clinical factors from the beginning and throughout the course of MD in order to prevent suicide attempts

Development and validation of a prediction nomogram for non-suicidal self-injury in female patients with mood disorder

BackgroundNon-suicidal self-injury (NSSI) is a highly prevalent behavioral problem among people with mental disorders that can result in numerous adverse outcomes. The present study aimed to systematically analyze the risk factors associated with NSSI to investigate a predictive model for female patients with mood disorders.MethodsA cross-sectional survey among 396 female patients was analyzed. All participants met the mood disorder diagnostic groups (F30–F39) based on the Diseases and Related Health Problems 10th Revision (ICD-10). The Chi-Squared Test, t-test, and the Wilcoxon Rank-Sum Test were used to assess the differences of demographic information and clinical characteristics between the two groups. Logistic LASSO Regression Analyses was then used to identify the risk factors of NSSI. A nomogram was further used to construct a prediction model.ResultsAfter LASSO regression selection, 6 variables remained significant predictors of NSSI. Psychotic symptom at first-episode (β = 0.59) and social dysfunction (β = 1.06) increased the risk of NSSI. Meanwhile, stable marital status (β = −0.48), later age of onset (β = −0.01), no depression at onset (β = −1.13), and timely hospitalizations (β = −0.10) can decrease the risk of NSSI. The C-index of the nomogram was 0.73 in the internal bootstrap validation sets, indicated that the nomogram had a good consistency.ConclusionOur findings suggest that the demographic information and clinical characteristics of NSSI can be used in a nomogram to predict the risk of NSSI in Chinese female patients with mood disorders

Kinematic calibration of a 3-DOF spindle head using a double ball bar

This paper presents a simple and effective approach for kinematic calibration of a 3-DOF spindle head developed for high-speed machining. This approach is implemented in three steps, (i) error modeling that allows the geometric errors affecting the compensatable and uncompensatable pose accuracy to be classified; (ii) identification of the geometric errors using a set of distance measurements acquired by a double ball bar (DBB) with a single installation; (iii) design of a linearized error compensator for real-time error implementation. Experimental results on a prototype machine show that the compensatable pose accuracy can significantly be improved by the proposed approach

The integrated impacts of climate change, water availability and socio-economic development on China’s food production

Food production in China is a fundamental component of the national economy and driver of agricultural policy. Sustaining and increasing output to meet growing demand faces significant challenges including, climate change, increasing population, agricultural land loss, and competing demands for water. The integrated impacts of climate change, water availability, and other socioeconomic pressures on China’s food production are poorly understood. By linking crop and water simulation models and two scenarios of climate and socioeconomic change (downscaled from IPCC SRES A2 and B2) we demonstrate that under these scenarios out to 2050 the absolute effects of climate change alone are modest and the interactive effects of other drivers are negative, leading to overall changes in total production. Outcomes are highly dependent on socioeconomic development pathways and the effects of CO2 fertilization on crop yields which may almost wholly offset the decreases in production. We find that water availability plays a significant limiting role on potential cereal production. Per capita cereal production falls in all cases, by up to 40% of the current baseline. These results are likely to be optimistic because the CO2 crop yield response function is highly uncertain and the effects of extreme events on crop growth and water availability are likely to be underestimated

Correlation and predictive ability of sensory characteristics and social interaction in children with autism spectrum disorder

BackgroundIndividuals with autism spectrum disorder (ASD) often have different social characteristics and particular sensory processing patterns, and these sensory behaviors may affect their social functioning. The objective of our study is to investigate the sensory profiles of children with ASD and their association with social behavior. Specifically, we aim to identify the predictive role of sensory processing in social functioning.MethodsThe Short Sensory Profile (SSP) was utilized to analyze sensory differences between ASD children and their peers. The Social Responsiveness Scale (SRS) and other clinical scales were employed to assess the social functioning of children with ASD. Additionally, the predictive ability of sensory perception on social performance was discussed using random forest and support vector machine (SVM) models.ResultsThe SSP scores of ASD children were lower than those of the control group, and there was a significant negative correlation between SSP scores and clinical scale scores (P &lt; 0.05). The random forest and SVM models, using all the features, showed higher sensitivity, while the random forest model with 7-feature factors had the highest specificity. The area under the receiver operating characteristic (ROC) curve (AUC) for all the models was higher than 0.8.ConclusionAutistic children in our study have different patterns of sensory processing than their peers, which are significantly related to their patterns of social functioning. Sensory features can serve as a good predictor of social functioning in individuals with ASD

An integrated multi-study analysis of intra-subject variability in cerebrospinal fluid amyloid-β concentrations collected by lumbar puncture and indwelling lumbar catheter

INTRODUCTION: Amyloid-β (Aβ) has been investigated as a diagnostic biomarker and therapeutic drug target. Recent studies found that cerebrospinal fluid (CSF) Aβ fluctuates over time, including as a diurnal pattern, and increases in absolute concentration with serial collection. It is currently unknown what effect differences in CSF collection methodology have on Aβ variability. In this study, we sought to determine the effect of different collection methodologies on the stability of CSF Aβ concentrations over time. METHODS: Grouped analysis of CSF Aβ levels from multiple industry and academic groups collected by either lumbar puncture (n=83) or indwelling lumbar catheter (n=178). Participants were either placebo or untreated subjects from clinical drug trials or observational studies. Participants had CSF collected by lumbar puncture or lumbar catheter for quantitation of Aβ concentration by enzyme linked immunosorbent assay. Data from all sponsors was converted to percent of the mean for Aβ40 and Aβ42 for comparison. Repeated measures analysis of variance was performed to assess for factors affecting the linear rise of Aβ concentrations over time. RESULTS: Analysis of studies collecting CSF via lumbar catheter revealed tremendous inter-subject variability of Aβ40 and Aβ42 as well as an Aβ diurnal pattern in all of the sponsors' studies. In contrast, Aβ concentrations from CSF samples collected at two time points by lumbar puncture showed no significant differences. Repeated measures analysis of variance found that only time and draw frequency were significantly associated with the slope of linear rise in Aβ40 and Aβ42 concentrations during the first 6 hours of collection. CONCLUSIONS: Based on our findings, we recommend minimizing the frequency of CSF draws in studies measuring Aβ levels and keeping the frequency standardized between experimental groups. The Aβ diurnal pattern was noted in all sponsors' studies and was not an artifact of study design. Averaging Aβ concentrations at each time point is recommended to minimize the effect of individual variability. Indwelling lumbar catheters are an invaluable research tool for following changes in CSF Aβ over 24-48 hours, but factors affecting Aβ concentration such as linear rise and diurnal variation need to be accounted for in planning study designs