Tag: nevin manimala

PLoS One. 2022 Oct 31;17(10):e0277017. doi: 10.1371/journal.pone.0277017. eCollection 2022.

ABSTRACT

Household screening is common when information about characteristics of household members is needed for selection of survey respondents. When key characteristics have a low prevalence, or are oversampled, this can result in a large number of sampled households screened, many of which have no persons selected. For in-person surveys this can be inefficient and costly, especially in an environment of declining response. A multimode design using a mail, push-to-web approach is an attractive alternative due to lower cost and high internet penetration. However, little is known about the comparable data quality properties between in-person and web modes. While in-person screening is considered a gold standard approach, respondents may fail to report household members and interviewers may unintentionally screen out reluctant respondents. Similarly, those self-responding sometimes fail to report unrelated household members or young children. In this study we compared in-person and web screening in the National Health and Nutrition Examination Survey. Households were randomly selected to complete a self-administered web screener and subsequently be screened by an interviewer during an in-person visit. We report on the comparability of household characteristics between modes to determine if web screening provides data equivalent to in-person screening. We examine time between the web and in-person screening to see if true change can account for differences. In the presence of conflicting data, we examine selection criteria based on the screening responses to see how inaccuracies affect selection status, or if inaccuracies or person omissions are systematically related to a specific mode. Approximately 93% (80/86) of households agreed on selection status between the web and in-person modes. Household composition matched fully for 84% (72/86) of households. These results indicate that web screening is a viable option enumerating households in population surveys.

PMID:36315571 | DOI:10.1371/journal.pone.0277017

PLoS One. 2022 Oct 31;17(10):e0276841. doi: 10.1371/journal.pone.0276841. eCollection 2022.

ABSTRACT

BACKGROUND: The prevalence of coronavirus disease 2019 (COVID-19) has endangered the psychological health of individuals. This study aimed to assess the quality of life and its related psychological problems during COVID-19 pandemic.

METHODS: In this cross-sectional study, 559 citizens above the age of 16 years, in Isfahan and Bandar Abbas cities in Iran were selected with a convenient sampling method. An online questionnaire was used to collect the data, which consisted of five sections: demographic information, short health anxiety inventory (SHAI), perceived stress scale (PSS), world health organization quality of life questionnaire (WHOQOL-BREF) and Padua inventory. Data were analyzed using statistical tests including t-test, path analysis and structural equation modeling (SEM) using SPSS 24 and Amos 21 statistical software.

RESULTS: A total of 559 subjects with the mean age of 37.34 ± 11.19 years participated in this study. Most of the participants were female (78.5%), married (71.6%) and employed (40.9%). The majority of them also had a bachelor’s degree (42.9%). There were significant negative correlations between perceived helplessness (r = -.597, p = .000), perceived stress (r = -.715, p = .000), risk of disease (r = -.302, p = .000), negative effect of disease (r = -.424, p = .000), health anxiety (r = -.366, p = .000), contamination obsessions (r = -.187, p = .000) and washing compulsions (r = -.193, p = .000) with quality of life. On other hand, significant positive correlation was found between perceived self-efficacy (r = .665, p = .000) and quality of life.

CONCLUSIONS: According to our findings, health anxiety, perceived stress and obsessive-compulsive disorder were negatively affected psychological health during COVID-19 which in turn decreased quality of life. Therefore, we suggest considering prevention and treatment of theses psychological problems to diminish the risk of reduced quality of life during COVID-19 global pandemic crisis.

PMID:36315557 | DOI:10.1371/journal.pone.0276841

IEEE J Biomed Health Inform. 2022 Oct 31;PP. doi: 10.1109/JBHI.2022.3218453. Online ahead of print.

ABSTRACT

The use of transfer learning in brain-computer interfaces (BCIs) has potential applications. As electroencephalogram (EEG) signals vary among different paradigms and subjects, existing EEG transfer learning algorithms mainly focus on the alignment of the original space. They may not discover hidden details owing to the low-dimensional structure of EEG. To effectively transfer data from a source to target domain, a multi-manifold embedding domain adaptive algorithm is proposed for BCI. First, we aligned the EEG covariance matrix in the Riemannian manifold and extracted the characteristics of each source domain in the tangent space to reflect the differences between different source domains. Subsequently, we mapped the extracted characteristics to the Grassmann manifold to obtain a common feature representation. In domain adaptation, the geometric and statistical attributes of EEG data were considered simultaneously, and the target domain divergence matrix was updated with pseudo-labels to maximize the inter-class distance and minimize the intra-class distance. Datasets generated via BCIs were used to verify the effectiveness of the algorithm. Under two experimental paradigms, namely single-source to single-target and multi-source to single-target, the average accuracy of the algorithm on three datasets was 73.31% and 81.02%, respectively, which is more than that of several state-of-the-art EEG cross-domain classification approaches. Our multi-manifold embedded domain adaptive method achieved satisfactory results on EEG transfer learning. The method can achieve effective EEG classification without a same subject’s training set.

PMID:36315544 | DOI:10.1109/JBHI.2022.3218453

PLoS One. 2022 Oct 31;17(10):e0276933. doi: 10.1371/journal.pone.0276933. eCollection 2022.

ABSTRACT

Senile plaques, which are mostly composed of beta-amyloid peptide, are the main signature of Alzheimer’s disease (AD). Two main forms of beta-amyloid in humans are 40 and 42-amino acid, long; the latter is considered more relevant to AD etiology. The concentration of soluble beta-amyloid-42 (Aβ42) in cerebrospinal fluid (CSF-Aβ42) and the density of amyloid depositions have a strong negative correlation. However, AD patients have lower CSF-Aβ42 levels compared to individuals with normal cognition (NC), even after accounting for this correlation. The goal of this study was to infer deviations of Aβ42 metabolism parameters that underlie this difference using data from the Alzheimer’s Disease Neuroimaging Initiative cohort. Aβ42 is released to the interstitial fluid (ISF) by cells and is removed by several processes. First, growth of insoluble fibrils by aggregation decreases the concentration of soluble beta-amyloid in the ISF. Second, Aβ42 is physically transferred from the brain to the CSF and removed with the CSF flow. Finally, there is an intratissue removal of Aβ42 ending in proteolysis, which can occur either in the ISF or inside the cells after the peptide is endocytosed. Unlike aggregation, which preserves the peptide in the brain, transfer to the CSF and intratissue proteolysis together represent amyloid removal. Using a kinetic model of Aβ42 turnover, we found that compared to NC subjects, AD patients had dramatically increased rates of amyloid removal. A group with late-onset mild cognitive impairment (LMCI) also exhibited a higher rate of amyloid removal; however, this was less pronounced than in the AD group. Estimated parameters in the early-onset MCI group did not differ significantly from those in the NC group. We hypothesize that increased amyloid removal is mediated by Aβ42 cellular uptake; this is because CSF flow is not increased in AD patients, while most proteases are intracellular. Aβ cytotoxicity depends on both the amount of beta-amyloid internalized by cells and its intracellular conversion into toxic products. We speculate that AD and LMCI are associated with increased cellular amyloid uptake, which leads to faster disease progression. The early-onset MCI (EMCI) patients do not differ from the NC participants in terms of cellular amyloid uptake. Therefore, EMCI may be mediated by the increased production of toxic amyloid metabolites.

PMID:36315527 | DOI:10.1371/journal.pone.0276933

JMIR Res Protoc. 2022 Oct 31;11(10):e39225. doi: 10.2196/39225.

ABSTRACT

BACKGROUND: Digital technologies are widely recognized for their equalizing effect, improving access to affordable health care regardless of gender, ethnicity, socioeconomic status, or geographic region. The Thrive by Five app is designed to promote positive interactions between children and their parents, extended family, and trusted members of the community to support socioemotional and cognitive development in the first 5 years of life and to strengthen connections to culture and community.

OBJECTIVE: This paper aims to describe the iterative co-design process that underpins the development and refinement of Thrive by Five’s features, functions, and content. Minderoo Foundation commissioned this work as a quality improvement activity to support an engaging user experience and inform the development of culturally appropriate and relevant content for parents and caregivers in each country where the app is implemented.

METHODS: The app content, referred to as Collective Actions, comprises “The Why,” that presents scientific principles that underpin socioemotional and cognitive development in early childhood. The scientific information is coupled with childrearing activities for parents, extended family, and members of the community to engage in with the children to support their healthy development and to promote positive connections between parents, families, and communities and these young children. Importantly, the initial content is designed and iteratively refined in collaboration with a subject matter expert group from each country (ie, alpha testing). This content is then configured into the app (either a beta version or localized version) for testing (ie, beta testing) by local parents and caregivers as well as experts who are invited to provide their feedback and suggestions for improvements in app content, features, and functions via a brief web-based survey and a series of co-design workshops. The quantitative survey data will be analyzed using descriptive statistics, whereas the analysis of qualitative data from the workshops will follow established thematic techniques.

RESULTS: To date, the co-design protocol has been completed with subject matter experts, parents, and caregivers from 9 countries, with the first results expected to be published by early 2023. The protocol will be implemented serially in the remaining 21 countries.

CONCLUSIONS: Mobile technologies are the primary means of internet connection in many countries worldwide, which underscores the potential for mobile health programs to improve access to valuable, evidence-based, and previously unavailable parenting information. However, for maximum impact, it is critically important to ensure that mobile health programs are designed in collaboration with the target audience to support the alignment of content with parents’ cultural values and traditions and its relevance to their needs and circumstances.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39225.

PMID:36315237 | DOI:10.2196/39225

Appl Immunohistochem Mol Morphol. 2022 Nov 1. doi: 10.1097/PAI.0000000000001084. Online ahead of print.

ABSTRACT

BMP-2 and Noggin are expressed in several tissues and participate in cell differentiation and proliferation during odontogenesis and tumor development. We evaluated the immunohistochemical expression of these proteins in ameloblastomas (AMs), odontogenic keratocysts (OKCs), and dentigerous cysts (DCs). The expression in AM (n.20), OKC (n.20), and DC (n.20) was evaluated by the percentage of positive cells and expression intensity, resulting in a total immunostaining score. Analysis of BMP-2 and Noggin revealed positivity in all cases. The Mann-Whitney test showed a statistically significant difference for Noggin between AM and DC and between OKC/DC. The mean DC scores were always higher than those of the other groups, regardless of the assessment method. Individual analysis of each lesion showed a positive and significant correlation between the percentage of cells positive for BMP-2 and Noggin in DC. We demonstrated the presence of BMP-2 and Noggin in AMs/OKCs/DCs. Marked expression of BMP-2 was observed in OKCs and AMs. There was also a positive correlation between BMP-2 and Noggin in DCs, suggesting a greater role of these markers in the bone formation and remodeling process since DCs are characterized by phases of bone quiescence and healing.

PMID:36315234 | DOI:10.1097/PAI.0000000000001084

J Magn Reson Imaging. 2022 Oct 31. doi: 10.1002/jmri.28509. Online ahead of print.

ABSTRACT

BACKGROUND: The measurement of the concentration of theranostic agents in vivo is essential for the assessment of their therapeutic efficacy and their safety regarding healthy tissue. To this end, there is a need for quantitative T₁ measurements that can be obtained as part of a standard clinical imaging protocol applied to tumor patients.

PURPOSE: To generate T₁ maps from MR images obtained with the magnetization-prepared rapid gradient echo (MPRAGE) sequence. To evaluate the feasibility of the proposed approach on phantoms, animal and patients with brain metastases.

STUDY TYPE: Pilot.

PHANTOM/ANIMAL MODEL/POPULATION: Solutions containing contrast agents (chelated Gd³⁺ and iron nanoparticles), male rat of Wistar strain, three patients with brain metastases.

FIELD STRENGTH/SEQUENCE: A 3-T and 7-T, saturation recovery (SR), and MPRAGE sequences.

ASSESSMENT: The MPRAGE T₁ measurement was compared to the reference SR method on phantoms and rat brain at 7-T. The robustness of the in vivo method was evaluated by studying the impact of misestimates of tissue proton density. Concentrations of Gd-based theranostic agents were measured at 3-T in gray matter and metastases in patients recruited in NanoRad clinical trial.

STATISTICAL TESTS: A linear model was used to characterize the relation between T₁ measurements from the MPRAGE and the SR acquisitions obtained in vitro at 7-T.

RESULTS: The slope of the linear model was 0.966 (R² = 0.9934). MPRAGE-based T₁ values measured in the rat brain were 1723 msec in the thalamus. MPRAGE-based T₁ values measured in patients in white matter and gray matter amounted to 747 msec and 1690 msec. Mean concentration values of Gd³⁺ in metastases were 61.47 μmol.

DATA CONCLUSION: The T₁ values obtained in vitro and in vivo support the validity of the proposed approach. The concentrations of Gd-based theranostic agents may be assessed in patients with metastases within a standard clinical imaging protocol using the MPRAGE sequence.

EVIDENCE LEVEL: 2.

TECHNICAL EFFICACY: Stage 1.

PMID:36315197 | DOI:10.1002/jmri.28509

Klin Lab Diagn. 2022 Oct 14;67(10):600-606. doi: 10.51620/0869-2084-2022-67-10-600-606.

ABSTRACT

The relationship between multiple sclerosis and the state of the human microbiome was studied, namely, the change in the representation of microbiota phylotypes, the proportion of coccal flora, the proportion of anaerobic, gram-negative, proteolytically active microflora, as well as the concentration of markers of bacterial plasmalogen and endotoxin in the blood. Microbiome studies were carried out by gas chromatography – mass spectrometry of microbial markers in the blood. A statistically significant increase in blood concentrations of the total level of microbial markers of bacterial plasmalogen and endotoxin was determined in multiple sclerosis, which may be associated with an increase in the permeability of the intestinal wall. In multiple sclerosis, the proportion of coccal, gram-negative, anaerobic microflora with a proteolytic type of metabolic activity increases. The correlations of the representation of microbiota phylotypes change due to the switching of the direct relationship Proteobacteria-Bacteroides to Proteobacteria-Firmicutes. In multiple sclerosis, Actinobacteria and Proteobacteria increase and Firmicutes decrease. Conclusion. The multiple sclerosis disease may be associated with pathological changes in the structure of the microbiome and the growth of endotoxemia, which may be one of the factors in the pathogenesis of the disease. New laboratory markers for diagnosing and predicting the course of MS have been proposed.

PMID:36315176 | DOI:10.51620/0869-2084-2022-67-10-600-606

Klin Lab Diagn. 2022 Oct 14;67(10):570-574. doi: 10.51620/0869-2084-2022-67-10-570-574.

ABSTRACT

Multiple myeloma (MM) is a malignant tumor occurring from plasma cells that produce an abnormal monoclonal immunoglobulin – a paraprotein. A distinctive feature of Bence-Jones myeloma is the excretion of monoclonal free light chains of immunoglobulins with 24h urine, and the absence of monoclonal intact immunoglobulins secretion. Comprehensive analysis of biochemical parameters in blood serum and 24h urine in patients with Bence-Jones multiple myeloma using electrophoretic and immunoturbidimetric methods to assess their sensitivity as biomarkers. 50 patients with a morphologically confirmed diagnosis of MM of the Bence-Jones immunochemical type were examined. 28 people without oncological diseases were examinedas a control. Detection of monoclonal secretion in blood serum and daily urine was performed by immunofixation electrophoresis on the Hydrasys 2 electrophoretic system (Sebia). The determination of free light chains of immunoglobulins (FLC) was performed by the immunoturbidimetric method (Binding Site) on an Advia 1800 analyzer (Siemens). Analysis of IgG, IgA, IgM, β2-microglobulin and C-reactive protein was performed on Cobas 6000 analyzer (Roche). The median excretion of Bence-Jones protein in 24h urine of MM patients was 0.49 g/24h (0.06-2.45 g/24h). In the blood serum, in 86% of cases, the presence of paraproteinemia, represented by κ and λ type light chains of immunogloublins was detected. At the same time, the frequency of detection of monoclonal secretion in blood serum in Bence-Jones type λ myeloma was 95.7%, which was statistically significantly higher than the frequency of detection of monoclonal secretion of type κ – 77.8%. In patients with identified paraproteinemia, Bence-Jones protein excretion in daily urine (median 0.82 g/day) was statistically significantly higher than in patients without a monoclonal component detected in blood serum (median 0.04 g/24h). The levels of FLC in blood serum obtained by immunoturbidimetry in Bence-Jones myeloma of the corresponding type were higher than the reference levels in 100% of cases. The median level of κ-FLC reached 4358 mg/l, λ-FLC – 2225 mg/l, which was statistically significantly higher than the control levels. The median concentrations of IgG, IgA and IgM in patients with Bence-Jones myeloma were statistically significantly lower than in the control group, while the medians of β2-microglobulin and C-reactive protein were significantly higher than in the control. Our investigation showed high diagnostic efficiency of electrophoretic and immunoturbidimetric analysis of monoclonal secretion in patients with Bence-Jones MM, while FLC analysis demonstrated maximum sensitivity. Bence-Jones MM revealed biochemical signs of secondary immunodeficiency and general inflammatory syndrome.

PMID:36315171 | DOI:10.51620/0869-2084-2022-67-10-570-574

Big Data. 2022 Oct 28. doi: 10.1089/big.2021.0064. Online ahead of print.

ABSTRACT

Artificial neural networks (ANNs) have been frequently used in forecasting problems in recent years. One of the most popular types of ANNs in these days is Pi-Sigma artificial neural networks (PS-ANNs). PS-ANNs have a high order ANN structure and they use both multiplicative and additive neuron models in their architecture. PS-ANNs produce superior forecasting performance because of their high order structure. PS-ANNs are affected negatively by an outlier or outliers in a data set because of having a multiplicative neuron model in their architecture. In this study, a new robust learning algorithm based on particle swarm optimization and Huber’s loss function for PS-ANNs is proposed. To evaluate the performance of the proposed method, Dow Jones stock exchange and Australian beer consumption data sets are analyzed and the obtained results are compared with many ANNs types proposed in the literature. Besides, the performance of the proposed method in outlier cases is also investigated by injecting outliers into these data sets. It is seen that the proposed learning algorithm has a satisfying performance both the data have an outlier or outliers’ case and original case.

PMID:36315168 | DOI:10.1089/big.2021.0064