Tag: nevin manimala

Methods Mol Biol. 2023;2571:33-43. doi: 10.1007/978-1-0716-2699-3_4.

ABSTRACT

Due to the high impact of diet exposure on health, it is crucial the generation of robust data of regular dietary intake, hence improving the accuracy of dietary assessment. The metabolites derived from individual food or group of food have great potential to become biomarkers of food intake (BFIs) and provide more objective food consumption measurements.Herein, it is presented an untargeted metabolomic workflow for the discovery BFIs in blood and urine samples, from the study design to the biomarker identification. Samples are analyzed by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). A wide variety of compounds are covered by separate analyses of medium to nonpolar molecules and polar metabolites based on two LC separations as well as both positive and negative electrospray ionization. The main steps of data treatment of the comprehensive data sets and statistical analysis are described, as well as the principal considerations for the BFI identification.

PMID:36152148 | DOI:10.1007/978-1-0716-2699-3_4

J Gambl Stud. 2022 Sep 24. doi: 10.1007/s10899-022-10159-x. Online ahead of print.

ABSTRACT

As real time soccer gambling is becoming a game of choice for many Nigerian youths, there is need to examine some predictive factors that could account for risky decision making in the population. We combined some cognitive tasks (memory, concentration, executive function and problem solving) and non-cognitive measures (time taken to complete a bet, years of gambling and addiction tendency measures) to derive a more parsimonious model of predicting risky decision making in this population. Twenty-eight undergraduate students that endorsed regular involvement (at least once a week) in soccer betting and were willing to come to the psychology lab for testing were recruited. Four neuropsychological measures (Craft Story 21: Immediate and delayed, Number Span Test: Forward and backward, Trail Making Test: A&B, Tower of Hannoi and a gambling questionnaire (Gamblers Anonymous Questionnaire) were used for the study. Study design was correlational and linear regression (step wise method) was used for data analysis. Step wise regression statistics yielded nine possible model combinations with high predictive strengths. Overall, model 9 (with adjusted R² = 0.57) that has 6 measures including one from non-cognitive and 5 from cognitive measures was adjudged to be most parsimonious putting into consideration its predictive strength and number of tasks required. The tasks in our most parsimonious model were: time taken to complete a bet (non-cognitive), Craft Story 21: immediate (cognitive: memory), Number Span Forward: Total correct and longest correct (cognitive: concentration), Trail Making Test: B (cognitive: executive function) and Tower of Hannoi: Time taken to complete (cognitive: problem solving). Pearson product moment correlation between the predictor variables and the dependent variable (number of odds selected) showed inverse correlation of Craft Story Immediate, Number Span total correct and Number span longest correct suggesting strong divergence of these variables to odd selection. Time taken to complete bet, Trail Making Test: B and time taken to complete Tower of Hannoi respectively had positive correlations with number of odds selected. Our results suggest that multiple domains of cognitive abilities and time taken to complete a bet are important for predicting gamblers at risk for poor decision making. It further suggests that use of single task for a particular cognitive domain could be sufficient in predicting persons at risk for decision making. Overall, our study suggests that risky decision making in real time sports betting could be predicted using fewer neuropsychological tasks measuring wider domains of brain behaviour and a non-cognitive measure.

PMID:36152112 | DOI:10.1007/s10899-022-10159-x

Appl Biochem Biotechnol. 2022 Sep 24. doi: 10.1007/s12010-022-04161-7. Online ahead of print.

ABSTRACT

In this pandemic situation, radiological images are the biggest source of information in healthcare and, at the same time, one of the foremost troublesome sources to analyze. Clinicians now-a-days must depend to a great extent on therapeutic image investigation performed by exhausted radiologists and some of the time analyzed and filtered themselves. Due to an overflow of patients, transmission of these medical data becomes frequent and maintaining confidentiality turns out to be one of the most important aspects of security along with integrity and availability. Chaos-based cryptography has proven a useful technique in the process of medical image encryption. The specialty of using chaotic maps in image security is its capability to increase the unpredictability and this causes the encryption robust. There are large number of literature available with chaotic map; however, most of these are not useful in low-precision devices due to their time-consuming nature. Taking into consideration of all these facts, a modified encryption technique is proposed for 2D COVID-19 images without compromising security. The novelty of the encryption procedure lies in the proposed design which is split into mainly three parts. In the first part, a variable length gray level code is used to generate the secret key to confuse the intruder and subsequently it is used as the initial parameter of both the chaotic maps. In the second part, one-stage image pixels are shuffled using the address code obtained from the sorting transformation of the first logistic map. In the final stage, a complete diffusion is applied for the whole image using the second chaotic map to counter differential and statistical attack. Algorithm validation is done by experimentation with visual image and COVID-19 X-ray images. In addition, a quantitative analysis is carried out to ensure a negligible data loss between the original and the decrypted image. The strength of the proposed method is tested by calculating the various security parameters like correlation coefficient, NPCR, UACI, and key sensitivity. Comparison analysis shows the effectiveness for the proposed method. Implementation statistics shows time efficiency and proves more security with better unpredictability.

PMID:36152105 | DOI:10.1007/s12010-022-04161-7

Arch Immunol Ther Exp (Warsz). 2022 Sep 24;70(1):23. doi: 10.1007/s00005-022-00660-x.

ABSTRACT

Angiotensin II type 1 receptor (AT1R) antibodies are considered non-HLA (human leukocyte antigen) antibodies connected with humoral rejection after kidney transplantation. The role of AT1R antibodies in the pathogenesis of glomerular diseases and systemic vasculitis is unknown. We assessed the level of AT1R antibodies in 136 patients with different types of glomerulonephritis and systemic vasculitis and we observed kidney function and proteinuria, serum albumin and total protein levels for 2 years. The mean levels of AT1R antibodies were the following: 6.00 ± 1.31 U/ml in patients with membranous nephropathy (n = 18), 5.67 ± 1.31 U/ml with focal and segmental glomerulosclerosis (n = 25), 6.26 ± 2.25 U/ml with lupus nephropathy (n = 17), 10.60 ± 6.72 U/ml with IgA nephropathy (n = 14), 6.69 ± 2.52 U/ml with mesangial proliferative (non IgA) glomerulonephritis (n = 6), 6.63 ± 1.38 U/ml with systemic vasculitis (n = 56), including c-ANCA (anti-neutrophil cytoplasmic antibodies) vasculitis: 11.22 ± 10.78 U/ml (n = 40) and p-ANCA vasculitis: 12.65 ± 14.59 U/ml (n = 16). The mean AT1R antibodies level was higher in patients with lupus nephropathy and systemic vasculitis compared to glomerulonephritis groups. An inverse statistically significant correlation between AT1R antibodies and serum albumin (r = – 0.51) in membranous nephropathy group was also found. Prospective analysis of creatinine levels indicated an increase of creatinine levels during time among patients with higher AT1R antibodies levels in p-ANCA vasculitis. Lupus nephropathy and systemic vasculitis patients may have high levels of AT1R antibodies. AT1R antibodies may be associated with the severity of membranous nephropathy and the course of p-ANCA vasculitis, although influence of concomitant factors is difficult to exclude.

PMID:36152104 | DOI:10.1007/s00005-022-00660-x

Environ Sci Pollut Res Int. 2022 Sep 24. doi: 10.1007/s11356-022-23154-x. Online ahead of print.

ABSTRACT

Americas have a mix of developing and developed economies. Thus, the pollution haven hypothesis (PHH) is expected in the developing countries of Latin America. Using the spatial Durbin model, the present study investigates the effects of foreign direct investment (FDI), exports, and imports on emissions in 18 Latin American countries from 1970 to 2019, including economic growth and the financial market development (FMD) in the model. The environmental Kuznets curve (EKC) is validated, and the region is found in the first stage of the EKC. Hence, Latin American economic growth has environmental consequences. Exports have a positive impact on home and neighboring countries’ CO₂ emissions and pollute the whole region, which validates the PHH. Imports could not affect the home economies but have positive environmental effects on neighboring economies and the entire Latin American region. The negative coefficient of imports is larger than the positive coefficient of exports. Therefore, the net effect of trade is environmentally pleasant in Latin America. Moreover, FDI has a statistically insignificant effect and the impact of FMD is positive on CO₂ emissions. The study recommends caring the exporting, financial, and economic activities for a sustainable environment in Latin America.

PMID:36152100 | DOI:10.1007/s11356-022-23154-x

Environ Sci Pollut Res Int. 2022 Sep 24. doi: 10.1007/s11356-022-23184-5. Online ahead of print.

ABSTRACT

The objective of this study is to examine the impact of green energy consumption (GEC), foreign direct investment (FDI), green innovation technology (GIT), and environmental pollution (EP) on economic growth (EG) of selected South Asian countries under the sustainable development goal (SDGs) number seven (7). This study uses panel annual data set from world development indicators (WDI) and OECD statistics for twenty-one (21) years starting from 2000 to 2020. This study applies dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) for data analysis and long-run relationship among variables. The findings of our study states that FDI, green energy consumption, and green innovation technology have positive effect among selected sample countries. However, it is noted that environmental degradation has adverse effect on economic growth.

PMID:36152099 | DOI:10.1007/s11356-022-23184-5

Environ Sci Pollut Res Int. 2022 Sep 24. doi: 10.1007/s11356-022-23112-7. Online ahead of print.

ABSTRACT

Dams are studied not only for potential advantages but also for possible environmental repercussions. The objective of this case study is to see the effects caused by Gomal Zam Dam on temperature, humidity and precipitation in their surroundings, both spatially and temporally. The meteorology parameters’ characteristics have been detected using two different approaches, Mann-Kendall statistical test and Sen’s slope estimator. Data stations chosen were those that have been close to the dam and sufficiently far away from the dam. As a consequence, although temporal changes in mean heat were established, periodic and regional disparities in humidity readings were found.

PMID:36152095 | DOI:10.1007/s11356-022-23112-7

Pediatr Surg Int. 2022 Sep 24. doi: 10.1007/s00383-022-05251-7. Online ahead of print.

ABSTRACT

PURPOSE: Congenital tracheo-oesophageal fistula (TOF) occurs in 1 in 3000 births. Perioperative management for TOF repair requires co-ordination with a multi-disciplinary team, support from critical care units, and expertise in neonatal and cardiothoracic anaesthesia. Charlotte Maxeke Johannesburg academic hospital (CMJAH) is a quaternary referral centre that serves the regional community of Johannesburg, in Gauteng, South Africa. The aim of this research was to describe the perioperative outcomes of neonates undergoing surgical TOF repair at CMJAH. Factors in the preoperative, intra-operative, and postoperative management were considered to find relationships with the perioperative outcomes.

METHOD: A retrospective single institution study was conducted with a population of 38 neonates who underwent congenital TOF repair from 1 January 2015 to 31 March 2020 at CMJAH. Descriptive statistics were used to describe the biodata using percentages, median, and inter-quartile ranges. An in-depth description of neonates that died was performed.

RESULTS: A total of 38 neonates diagnosed with TOF/OA were operated on during the study period. The mortality rate was 15.8%. No deaths occurred intraoperatively. In addition, 52.6% of the neonates had a prolonged stay in ICU, 44% had a delay in the initiation of feeds, 65% developed sepsis, and 36.8% had surgical related complications. CPR was required in 1 neonate, hypoxia leading to bradycardia in 10, and hyperlactataemia in 9 neonates. Inotropic support was required in 6 neonates, and vasopressor support in 4. Blood product transfusion were necessary for 9 neonates.

CONCLUSION: The in-hospital mortality of TOF repair was better than that reported in other African countries and worse than international findings. In-hospital morbidity was burdened by respiratory illness and sepsis. Areas where management could be improved include widespread foetal anomaly scanning, incorporation of bronchoscopy, and preoperative respiratory optimisation.

PMID:36152075 | DOI:10.1007/s00383-022-05251-7

J Neurol. 2022 Sep 24. doi: 10.1007/s00415-022-11387-2. Online ahead of print.

ABSTRACT

BACKGROUND: In multiple sclerosis (MS), determination of regional brain atrophy is clinically relevant. However, analysis of large datasets is rare because of the increased variability in multicenter data.

PURPOSE: To compare different methods to correct for center effects. To investigate regional gray matter (GM) volume in relapsing-remitting MS in a large multicenter dataset.

METHODS: MRI scans of 466 MS patients and 279 healthy controls (HC) were retrieved from the Italian Neuroimaging Network Initiative repository. Voxel-based morphometry was performed. The center effect was accounted for with different methods: (a) no correction, (b) factor in the statistical model, (c) ComBat method and (d) subsampling procedure to match single-center distributions. By applying the best correction method, GM atrophy was assessed in MS patients vs HC and according to clinical disability, disease duration and T₂ lesion volume. Results were assessed voxel-wise using general linear model.

RESULTS: The average residuals for the harmonization methods were 5.03 (a), 4.42 (b), 4.26 (c) and 2.98 (d). The comparison between MS patients and HC identified thalami and other deep GM nuclei, the cerebellum and several cortical regions. At single-center analysis, the thalami were always involved, whereas different other regions were found in each center. Cerebellar atrophy correlated with clinical disability, while deep GM nuclei atrophy correlated with T₂-lesion volume.

CONCLUSION: Harmonization based on subsampling more effectively decreased the residuals of the statistical model applied. In comparison with findings from single-center analysis, the multicenter results were more robust, highlighting the importance of data repositories from multiple centers.

PMID:36152049 | DOI:10.1007/s00415-022-11387-2

Eur Radiol. 2022 Sep 24. doi: 10.1007/s00330-022-09143-1. Online ahead of print.

ABSTRACT

OBJECTIVES: To evaluate commercial deep learning-based software for fully automated coronary artery calcium (CAC) scoring on non-electrocardiogram (ECG)-gated low-dose CT (LDCT) with different slice thicknesses compared with manual ECG-gated calcium-scoring CT (CSCT).

METHODS: This retrospective study included 567 patients who underwent both LDCT and CSCT. All LDCT images were reconstructed with a 2.5-mm slice thickness (LDCT_2.5-mm), and 453 LDCT scans were reconstructed with a 1.0-mm slice thickness (LDCT_1.0-mm). Automated CAC scoring was performed on CSCT (CSCT_auto), LDCT_1.0-mm, and LDCT_2.5-mm images. The reliability of CSCT_auto, LDCT_1.0-mm, and LDCT_2.5-mm was compared with manual CSCT scoring (CSCT_manual) using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. Agreement, in CAC severity category, was analyzed using weighted kappa statistics. Diagnostic performance at various Agatston score cutoffs was also calculated.

RESULTS: CSCT_auto, LDCT_1.0-mm, and LDCT_2.5-mm demonstrated excellent agreement with CSCT_manual (ICC [95% confidence interval, CI]: 1.000 [1.000, 1.000], 0.937 [0.917, 0.952], and 0.955 [0.946, 0.963], respectively). The mean difference with 95% limits of agreement was lower with LDCT_1.0-mm than with LDCT_2.5-mm (19.94 [95% CI, -244.0, 283.9] vs. 45.26 [-248.2, 338.7]). Regarding CAC severity, LDCT_1.0-mm achieved almost perfect agreement, and LDCT_2.5-mm achieved substantial agreement (kappa [95% CI]: 0.809 [0.776, 0.838], 0.776 [0.740, 0.809], respectively). Diagnostic performance for detecting Agatston score ≥ 400 was also higher with LDCT_1.0-mm than with LDCT_2.5-mm (F1 score, 0.929 vs. 0.855).

CONCLUSIONS: Fully automated CAC-scoring software with both CSCT and LDCT yielded excellent reliability and agreement with CSCT_manual. LDCT_1.0-mm yielded more accurate Agatston scoring than LDCT_2.5-mm using fully automated commercial software.

KEY POINTS: • Total Agatston scores and all vessels of CSCT_auto, LDCT_1.0-mm, and LDCT_2.5-mm demonstrated excellent agreement with CSCT_manual (all ICC > 0.85). • The diagnostic performance for detecting all Agatston score cutoffs was better with LDCT_1.0-mm than with LDCT_2.5-mm. • This automated software yielded a lower degree of underestimation compared with methods described in previous studies, and the degree of underestimation was lower with LDCT_1.0-mm than with LDCT_2.5-mm.

PMID:36152039 | DOI:10.1007/s00330-022-09143-1