Evaluation of the Effect of Hemolysis on Quantitative Chemiluminescent Immunoassay Results for 10 Analytes.

BACKGROUND: The aim is to evaluate the effect of hemolysis on the quantitative chemiluminescent immunoassay results of 10 analytes and to provide a basis for formulating specific sample rejection criteria and reviewing report results. METHODS: Hemolysis based on the clinical hemolysis index, hemolysis 1+, 2+, and 3+ samples and matched normal samples were collected. The quantitative chemiluminescent immunoassay results of 10 analytes from the two samples (hemolysis and normal) were determined and differences between the results obtained from samples with different degrees of hemolysis and those obtained from normal samples were evaluated. RESULTS: A total of 34 pairs of samples were collected, including 10 pairs of 1+ hemolysis samples, 10 pairs of 2+ hemolysis samples, and 14 pairs of 3+ hemolysis samples. The quantitative chemiluminescence immunoassay detection results for the 10 analytes showed that regardless of the degree of hemolysis, the differences in alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), carbohydrate antigen (CA19-9), luteinizing hormone (LH), folli-cle-stimulating hormone (FSH), and ferritin (FER) between the hemolysis and normal samples were all lower than the total allowable error (TEa) based on biological variation; there were no statistically significant differences between the samples. However, the results for insulin (INS) began to decrease significantly at a hemolytic index of 1+, folic acid (FOL) showed an increase at a hemolytic index of 2+, and there was a significant difference at a he-molytic index of 3+. CONCLUSIONS: This research identified the analytes that are susceptible to hemolysis interference in chemiluminescent immunoassays. The influence of hemolysis on hemolytic clinical laboratory tests was closely related to the assay system used; thus, laboratories should evaluate the effect of hemolysis on their own analysis systems and define assay-specific hemolysis warning indices.

A Semi-Supervised Speech Deception Detection Algorithm Combining Acoustic Statistical Features and Time-Frequency Two-Dimensional Features.

Human lying is influenced by cognitive neural mechanisms in the brain, and conducting research on lie detection in speech can help to reveal the cognitive mechanisms of the human brain. Inappropriate deception detection features can easily lead to dimension disaster and make the generalization ability of the widely used semi-supervised speech deception detection model worse. Because of this, this paper proposes a semi-supervised speech deception detection algorithm combining acoustic statistical features and time-frequency two-dimensional features. Firstly, a hybrid semi-supervised neural network based on a semi-supervised autoencoder network (AE) and a mean-teacher network is established. Secondly, the static artificial statistical features are input into the semi-supervised AE to extract more robust advanced features, and the three-dimensional (3D) mel-spectrum features are input into the mean-teacher network to obtain features rich in time-frequency two-dimensional information. Finally, a consistency regularization method is introduced after feature fusion, effectively reducing the occurrence of over-fitting and improving the generalization ability of the model. This paper carries out experiments on the self-built corpus for deception detection. The experimental results show that the highest recognition accuracy of the algorithm proposed in this paper is 68.62% which is 1.2% higher than the baseline system and effectively improves the detection accuracy.

[Particle Size Distribution, Seasonal Variation Characteristics and Human Exposure Assessment of Heavy Metals in Typical Settled Dust from Beijing].

Four types of dust from dormitories, offices, hotels and roads in Beijing were collected and fractionated into 9 fractions, respectively. Totally 36 samples were obtained and analyzed for heavy metals including Cu, Zn, Cr, Pb, Cd and Ni. Particle size distributions of those heavy metals in these four types of dust were investigated and the influencing mechanisms were discussed. Distribution patterns of the same heavy metal in different types of dust showed various characteristics. Also different metals in the same type of dust represented different distribution patterns. Heavy metals in road dust tended to concentrate in finer particles. Two offices from the same building, located in Beijing, China, were selected to study the seasonality of heavy metals in dust. Dust sampling from Office A was conducted at weekly intervals between March 2012 and August 2012, while dust from Office B was sampled fortnightly from March 2012 to December 2012. Generally, levels of all heavy metals remained stable among different seasons, however, Cr and Pb represented more significant fluctuations than other four heavy metals. Based on the geo-accumulation index method, the pollution of Zn, Cu and Pb was more serious in the investigated samples, and dust from offices and hotels were moderately polluted by Zn. According to the risk assessment results, the carcinogenic health risks of the six heavy metals in the four types of dust were negligible.

Change Narratives That Elude Quantification: A Mixed-Methods Analysis of How People with Chronic Pain Perceive Pain Rehabilitation.

Chronic pain negatively impacts health, well-being, and social participation. Effective rehabilitation often hinges on long-term changes in pain-related perceptions and behaviors. However, there are important gaps in understanding how patients perceive these changes. The present pilot study addresses this gap by using qualitative and quantitative methodologies to explore how patients perceive and experience changes in function, participation, and pain-related factors following a chronic pain rehabilitation program. A mixed-method design was used in which the core method was qualitative. Descriptive quantitative data was used to further characterize the sample. Semistructured interviews were conducted 1-6 months following treatment completion. Questionnaires were administered before and after treatment and at follow-up. Interview data was analyzed thematically. Participants' individual descriptive data was compared to established cut-scores and criteria for change. A major theme of personal growth emerged in the qualitative analysis. Participants also discussed the factors that facilitated personal growth and the ongoing challenges to this growth. The quantitative data revealed limited improvement on measures of pain, disability, catastrophizing, and depression. These findings suggest that, despite limited improvement on treatment-related questionnaires, patients can experience an important and enduring sense of personal growth. Clinical and theoretical implications are discussed.