BACKGROUND: BNP is a sensitive and widely used biomarker for an early diagnosis of heart failure. Currently, most commercial BNP detection products use EDTA plasma samples. The aim of this study was to evaluate the clinical performance of the BNP test by using whole blood samples compared to plasma samples, and to evaluate the effect of the anticoagulant type on the BNP test result.
METHODS: In total, 106 patients with different BNP levels from the Dahua Hospital volunteered for this study. Clinically homogenous samples, including EDTA anticoagulant plasma, EDTA whole blood, and heparin anticoagulant plasma, were collected and analyzed by using i-Reader S automatic immuno-analyzer and its supporting reagent kits. Pearson\'s correlation and weighted least squares linear regression analysis, Bland-Altman plotting, and Kappa test were used for statistical analysis.
RESULTS: Correlation analysis showed that BNP concentrations, measured from EDTA anticoagulated plasma samples, had a good linear regression relationship with BNP from whole blood samples, with a slope of 0.9477, r = 0.9978, p < 0.05. A similar correlation was observed between EDTA anticoagulated plasma samples and heparin anticoagulant plasma, with a slope of 0.8413, r = 0.9793, p < 0.05. The BNP concentration measured from the heparin plasma samples were lower than of the EDTA plasma samples. Bland-Altman analysis for assessing BNP concentration agreement showed there was no outlier ratio between EDTA whole blood and EDTA plasma within the range of the detection system, as well as no outlier between EDTA anticoagulated and heparin anticoagulant plasma. Kappa coefficient of BNP concentration between homologous EDTA anticoagulated and heparin anticoagulant plasma was 0.8553 (p < 0.001), and for EDTA anticoagulated plasma and homologous whole blood it was 0.8941 (p < 0.001).
CONCLUSIONS: The diagnostic performance of EDTA anticoagulated whole blood samples did not differ significantly from EDTA anticoagulated plasma samples for the BNP test. This study showed no big significant difference between EDTA anticoagulated and heparin anticoagulated plasma measurements within 2 hours. The type of anticoagulant should be carefully chosen when performing the BNP test if BNP samples were in vitro for a long time.

BACKGROUND: There are many studies of medical costs in late life in general, but nursing home residents\' needs and the costs of external medical services and interventions outside of nursing home services are less well described.
METHODS: We examined the direct medical costs of nursing home residents in their last year of life, as well as limited to the period of stay in the nursing home, adjusted for age, sex, Hospital Frailty Risk Score (HFRS), and diagnosis of dementia or advanced cancer. This was an observational retrospective study of registry data from all diseased nursing home residents during the years 2015-2021 using healthcare consumption data from the Stockholm Regional Council, Sweden. T tests, Wilcoxon rank sum tests and chi-square tests were used for comparisons of groups, and generalized linear models (GLMs) were constructed for univariable and multivariable linear regressions of health cost expenditures to calculate risk ratios (RRs) with 95% confidence intervals (95% CIs).
RESULTS: According to the adjusted (multivariable) models for the 38,805 studied nursing home decedents, when studying the actual period of stay in nursing homes, we found significantly greater medical costs associated with male sex (RR 1.29 (1.25-1.33), p < 0.0001) and younger age (65-79 years vs. ≥90 years: RR 1.92 (1.85-2.01), p < 0.0001). Costs were also greater for those at risk of frailty according to the Hospital Frailty Risk Score (HFRS) (intermediate risk: RR 3.63 (3.52-3.75), p < 0.0001; high risk: RR 7.84 (7.53-8.16), p < 0.0001); or with advanced cancer (RR 2.41 (2.26-2.57), p < 0.0001), while dementia was associated with lower medical costs (RR 0.54 (0.52-0.55), p < 0.0001). The figures were similar when calculating the costs for the entire last year of life (regardless of whether they were nursing home residents throughout the year).
CONCLUSIONS: Despite any obvious explanatory factors, male and younger residents had higher medical costs at the end of life than women. Having a risk of frailty or a diagnosis of advanced cancer was strongly associated with higher costs, whereas a dementia diagnosis was associated with lower external, medical costs. These findings could lead us to consider reimbursement models that could be differentiated based on the observed differences.

CONCLUSIONS: Transcriptomics and proteomics information collected on a platform can predict additive and non-additive effects for platform traits and additive effects for field traits. The effects of climate change in the form of drought, heat stress, and irregular seasonal changes threaten global crop production. The ability of multi-omics data, such as transcripts and proteins, to reflect a plant\'s response to such climatic factors can be capitalized in prediction models to maximize crop improvement. Implementing multi-omics characterization in field evaluations is challenging due to high costs. It is, however, possible to do it on reference genotypes in controlled conditions. Using omics measured on a platform, we tested different multi-omics-based prediction approaches, using a high dimensional linear mixed model (MegaLMM) to predict genotypes for platform traits and agronomic field traits in a panel of 244 maize hybrids. We considered two prediction scenarios: in the first one, new hybrids are predicted (CV-NH), and in the second one, partially observed hybrids are predicted (CV-POH). For both scenarios, all hybrids were characterized for omics on the platform. We observed that omics can predict both additive and non-additive genetic effects for the platform traits, resulting in much higher predictive abilities than GBLUP. It highlights their efficiency in capturing regulatory processes in relation to growth conditions. For the field traits, we observed that the additive components of omics only slightly improved predictive abilities for predicting new hybrids (CV-NH, model MegaGAO) and for predicting partially observed hybrids (CV-POH, model GAOxW-BLUP) in comparison to GBLUP. We conclude that measuring the omics in the fields would be of considerable interest in predicting productivity if the costs of omics drop significantly.

Obesity poses significant challenges, necessitating comprehensive strategies for effective intervention. Bariatric Surgery (BS) has emerged as a crucial therapeutic approach, demonstrating success in weight loss and comorbidity improvement. This study aimed to evaluate the outcomes of BS in a cohort of 48 Uruguayan patients and investigate the interplay between BS and clinical and metabolic features, with a specific focus on FSTL1, an emerging biomarker associated with obesity and inflammation. We quantitatively analyzed BS outcomes and constructed linear models to identify variables impacting BS success. The study revealed the effectiveness of BS in improving metabolic and clinical parameters. Importantly, variables correlating with BS success were identified, with higher pre-surgical FSTL1 levels associated with an increased effect of BS on BMI reduction. FSTL1 levels were measured from patient plasma using an ELISA kit pre-surgery and six months after. This research, despite limitations of a small sample size and limited follow-up time, contributes valuable insights into understanding and predicting the success of BS, highlighting the potential role of FSTL1 as a useful biomarker in obesity.

UNASSIGNED: To investigate association between optic disc parameters analyzed by optical coherence tomography (OCT) and occurrence of peripheral retinal tears in patients with symptomatic posterior vitreous detachment (PVD).
UNASSIGNED: This cross-sectional study enrolled 75 patients with symptoms of acute PVD, who were allocated into two groups based on whether a peripheral retinal tear occurred or not.
UNASSIGNED: When comparing the average retinal nerve fiber layer (RNFL) thickness (μm) between retinal tear and control groups, it was shown that patients with a retinal tear have a significantly higher (87.18 [95% confidence interval (CI), 84.47 to 89.9] vs 81.14 [95% CI, 77.81 to 84.46], P = 0.005) average RNFL thickness. Furthermore, we observed a significant difference (0.13, 0.06 to 0.22 vs 0.07, 0.04 to 0.1, P = 0.036, Mann-Whitney U-test) in the size of cup volume (mm3) between the tear and control groups, respectively. Linear regression showed a significant decrease (P = 0.029) in average RNFL thickness with increasing age, but without a significant difference between the two groups. There was no statistically significant difference between the tear and control groups in terms of rim area, disc area, and average cup-to-disc ratio.
UNASSIGNED: Patients with a higher average RNFL thickness and larger cup volume measured by OCT were more prone to develop a peripheral retinal tear. Increased peripapillary average RNFL thickness due to trauma and subsequent inflammation, possibly related to the more adherent posterior hyaloid membrane to the retina, may also indicate strengthened adhesions in the areas of the peripheral retina where retinal tears occur. OCT analysis of the optic nerve head may be used in everyday clinical practice as a predictor of the development of peripheral retinal tears in patients with symptomatic PVD.

Group defense in prey and hunting cooperation in predators are two important ecological phenomena and can occur concurrently. In this article, we consider cooperative hunting in generalist predators and group defense in prey under a mathematical framework to comprehend the enormous diversity the model could capture. To do so, we consider a modified Holling-Tanner model where we implement Holling type IV functional response to characterize grazing pattern of predators where prey species exhibit group defense. Additionally, we allow a modification in the attack rate of predators to quantify the hunting cooperation among them. The model admits three boundary equilibria and up to three coexistence equilibrium points. The geometry of the nontrivial prey and predator nullclines and thus the number of coexistence equilibria primarily depends on a specific threshold of the availability of alternative food for predators. We use linear stability analysis to determine the types of hyperbolic equilibrium points and characterize the non-hyperbolic equilibrium points through normal form and center manifold theory. Change in the model parameters leading to the occurrences of a series of local bifurcations from non-hyperbolic equilibrium points, namely, transcritical, saddle-node, Hopf, cusp and Bogdanov-Takens bifurcation; there are also occurrences of global bifurcations such as homoclinic bifurcation and saddle-node bifurcation of limit cycles. We observe two interesting closed \'bubble\' form induced by global bifurcations due to change in the strength of hunting cooperation and the availability of alternative food for predators. A three dimensional bifurcation diagram, concerning the original system parameters, captures how the alternation in model formulation induces gradual changes in the bifurcation scenarios. Our model highlights the stabilizing effects of group or gregarious behaviour in both prey and predator, hence supporting the predator-herbivore regulation hypothesis. Additionally, our model highlights the occurrence of \"saltatory equilibria\" in ecological systems and capture the dynamics observed for lion-herbivore interactions.

The response envelope model proposed by Cook et al. (2010) is an efficient method to estimate the regression coefficient under the context of the multivariate linear regression model. It improves estimation efficiency by identifying material and immaterial parts of responses and removing the immaterial variation. The response envelope model has been investigated only for continuous response variables. In this paper, we propose the multivariate probit model with latent envelope, in short, the probit envelope model, as a response envelope model for multivariate binary response variables. The probit envelope model takes into account relations between Gaussian latent variables of the multivariate probit model by using the idea of the response envelope model. We address the identifiability of the probit envelope model by employing the essential identifiability concept and suggest a Bayesian method for the parameter estimation. We illustrate the probit envelope model via simulation studies and real-data analysis. The simulation studies show that the probit envelope model has the potential to gain efficiency in estimation compared to the multivariate probit model. The real data analysis shows that the probit envelope model is useful for multi-label classification.

UNASSIGNED: To determine the association of urinary phthalate metabolites with chronic obstructive pulmonary disease (COPD), airflow obstruction, lung function and respiratory symptoms.
UNASSIGNED: Our study included a total of 2023 individuals aged ≥ 40 years old in the National Health and Nutrition Examination Survey (NHANES). Multivariate logistic regression was conducted to explore the correlation of eleven urinary phthalate metabolites (MCNP, MCOP, MECPP, MnBP, MCPP, MEP, MEHHP, MEHP, MiBP, MEOHP, and MBzP) with COPD, airflow obstruction and respiratory symptoms. Linear regression analyses were used to evaluate the relationship between urinary phthalate metabolites and lung function.
UNASSIGNED: When compared to the first tertile, the third tertile of MEHHP was associated with the risk of COPD [OR: 2.779; 95% confidence interval (CI): 1.129-6.840; P = 0.026]. Stratified analysis showed that MEHHP increased the risk of COPD by 7.080 times in male participants. Both MCPP and MBzP were positively correlated with the risk of airflow obstruction. The third tertile of MBzP increased the risk of cough by 1.545 (95% CI: 1.030-2.317; P = 0.035) times. Both FEV1 and FVC were negatively associated with MEHHP, MECPP, MnBP, MEP, MiBP and MEOHP.
UNASSIGNED: Higher levels of MEHHP are associated with increased risk of COPD, and lower measures of FEV1 and FVC. MBzP is positively related to airflow obstruction and cough.

BACKGROUND: This study investigated the current status of the quality of life (QOL) of drug-resistant tuberculosis (DR-TB) patients in Nanjing, China, and analyzed the influencing factors.
METHODS: The survey was conducted among patients with DR-TB who were hospitalized in the tuberculosis department of the Second Hospital of Nanjing (Nanjing Public Health Medical Center) from July 2022 to May 2023. The Chinese version of the World Health Organization Quality of Life (WHOQOL-BREF) questionnaire was used to investigate the QOL levels of patients with DR-TB, and a multiple linear regression model was used to analyze the QOL influencing factors.
RESULTS: A total of 135 patients participated in the study; 69.6% were male, the average age was 46.30 ± 17.98 years, 13.33% had an education level of elementary school or below, and 75.56% were married. The QOL scores were 51.35 ± 17.24, 47.04 ± 20.28, 43.89 ± 17.96, and 35.00 ± 11.57 in the physiological, psychological, social, and environmental domains, respectively. The differences between the four domain scores and the Chinese normative results were statistically significant (P < 0.05). The results of multiple linear regression analysis showed that the factors related to the physiological domain included residence, family per-capita monthly income, payment method, adverse drug reactions (ADRs), and comorbidities; psychological domain correlates included educational level, family per-capita monthly income, course of the disease, and caregivers; social domain correlates included age and comorbidities; and factors related to the environmental domain included age, education level, and comorbidities.
CONCLUSIONS: In Nanjing, China, patients with younger age, higher education level, living in urban areas, high family per-capita monthly income, no adverse drug reactions, no comorbidities, and having caregivers have better quality of life. Future interventions to improve the quality of life of patients with drug-resistant tuberculosis could be tailored to a specific factor.

Modeling and accurately forecasting trend and seasonal patterns of a time series is a crucial activity in economics. The main propose of this study is to evaluate and compare the performance of three traditional forecasting methods, namely the ARIMA models and their extensions, the classical decomposition time series associated with multiple linear regression models with correlated errors, and the Holt-Winters method. These methodologies are applied to retail time series from seven different European countries that present strong trend and seasonal fluctuations. In general, the results indicate that all the forecasting models somehow follow the seasonal pattern exhibited in the data. Based on mean squared error (MSE), root mean squared error (RMSE), mean absolute percentage error (MAPE), mean absolute scaled error (MASE) and U-Theil statistic, the results demonstrate the superiority of the ARIMA model over the other two forecasting approaches. Holt-Winters method also produces accurate forecasts, so it is considered a viable alternative to ARIMA. The performance of the forecasting methods in terms of coverage rates matches the results for accuracy measures.