bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence and correlates of depression in early childhood home visitors serving rural Colombian families
Authors: Pérez Catalina , Bernal Raquel , Macias Mariafernanda , Barrueco Sandra 
Published: September 2023

Abstract

Purpose Limited information is available on early childhood provider depression, particularly in lower and middle-income (LMIC) countries, yet evidence from diverse fields indicates that depression negatively affects work functioning. Given extensive investment worldwide in early childhood home visiting programs, understanding home visitor mental health may help improve services for families. The current investigation examined the prevalence and correlates of depression in early childhood home visitors working in rural Colombia.Methods Three hundred and forty-one home visitors (N = 341) completed the Spanish versions of the Center for Epidemiological Studies Depression Scale (CES-D) and the Knowledge of Infant Development Inventory, and self-reported socio-demographic and job-related information. Cross-sectional, clustered statistical analyses were employed in STATA Software.Results Thirteen percent of home visitors met the cut off score for depression. Higher home visitor depression was related to maternal depression among beneficiaries. Additionally, depression was higher among home visitors who were older and those who identified their marital status as separated. Depression was lower among home visitors who completed more home visits and those with higher educational attainment.Conclusions Early childhood providers experienced interconnections in their depression with those whom they served. In addition, social environmental factors related to home visitor depression were identified. The results from this study speak to the importance of considering providers’ mental health as part of the effort of disseminating high quality early childhood home visiting programs. Program and clinical implications are further discussed.
Effects of dietary phytol supplementation on growth performance, immunological parameters, intestinal bacteria, and prevention of oxidative stress following transportation of Nile tilapia, Oreochromis niloticus
Authors: Ahani Saman , Ahani Sara , Yousefi Morteza , Mirghaed Ali Taheri , Rahman Afaf N. Abdel 
Published: September 2023

Abstract
In this study, Nile tilapia, Oreochromis niloticus, fingerlings (2.00 ± 0.02) were fed diets (crude protein 345 g/kg; crude lipid 86.8 g/kg) containing 0 (CTL), 75 (PH-75), 150 (PH-150), and 300 (PH-300) mg/kg phytol for 60 days, at 4% of biomass. The fish were reared in sixteen 70-L tanks (n = 4, each with 40 fish). After 60 days rearing, the fish were subjected to 6-h transportation to monitor the hepatic antioxidant parameters. The results showed that dietary 75 mg/kg phytol significantly improved fish growth (P < 0.001) and feed efficiency (P = 0.015). Plasma lysozyme (P = 0.004) alternative complement (P = 0.006), alkaline phosphatase (P = 0.014) significantly increased in PH-75, 75PH/150PH, and PH-75/PH-300 treatments, respectively. All phytol-treatments led to significant (P = 0.001) increase in the blood neutrophil count. The PH-300 treatment resulted in significantly higher blood WBC (P = 0.008), monocyte (P = 0.010), and eosinophil (P < 0.001) counts, compared to CTL. Phytol also modulated intestinal microbiota by reducing the number of total viable bacteria in PH-75 and PH-150 (P = 0.027) and increasing lactic acid bacteria in PH-75 (P = 0.017). PH-75 and PH-150 had highest survival, antioxidant enzymes, reduced glutathione levels, lowest lipid peroxidation, before and/or after the transportation. PH-300 treatment showed an elevation lipid peroxidation, after the transportation. These findings suggest that dietary phytol may be a good supplement for improving the health and growth performance of Nile tilapia, and the recommended level is 75 mg/kg.
Activation patterns in male and female forebrain circuitries during food consumption under novelty
Authors: Greiner Eliza M. , Witt Mary E. , Moran Stephanie J. , Petrovich Gorica D. 
Published: September 2023

Abstract
The influence of novelty on feeding behavior is significant and can override both homeostatic and hedonic drives due to the uncertainty of potential danger. Previous work found that novel food hypophagia is enhanced in a novel environment and that males habituate faster than females. The current study’s aim was to identify the neural substrates of separate effects of food and context novelty. Adult male and female rats were tested for consumption of a novel or family food in either a familiar or in a novel context. Test-induced Fos expression was measured in the amygdalar, thalamic, striatal, and prefrontal cortex regions that are important for appetitive responding, contextual processing, and reward motivation. Food and context novelty induced strikingly different activation patterns. Novel context induced Fos robustly in almost every region analyzed, including the central (CEA) and basolateral complex nuclei of the amygdala, the thalamic paraventricular (PVT) and reuniens nuclei, the nucleus accumbens (ACB), the medial prefrontal cortex prelimbic and infralimbic areas, and the dorsal agranular insular cortex (AI). Novel food induced Fos in a few select regions: the CEA, anterior basomedial nucleus of the amygdala, anterior PVT, and posterior AI. There were also sex differences in activation patterns. The capsular and lateral CEA had greater activation for male groups and the anterior PVT, ACB ventral core and shell had greater activation for female groups. These activation patterns and correlations between regions, suggest that distinct functional circuitries control feeding behavior when food is novel and when eating occurs in a novel environment.
Characterizing industry payments to ophthalmologists before and after onset of the COVID-19 pandemic
Authors: Choudhry Hassaam S , Choudhry Hannaan S , Burton Carter , Patel Aman M , Patel Riya , Li Ximin , Berkowitz Sean , Kaleem Mona A 
Published: September 2023

Abstract
Purpose
The COVID-19 pandemic had profound effects on many different aspects of our healthcare system and the relationship between industry and physicians was no exception. The present database study evaluates industry payments to ophthalmologists in order to identify whether there are significant differences in industry payments to ophthalmologists before and after onset of the pandemic.
Methods
The Centers for Medicare & Medicaid Services Open Payments Database was queried for all ophthalmologists who received industry payments between 2018 and 2021. Pre-Covid was defined as 2018–2019 while post-Covid was defined as 2020–2021. Payment date, value, type, company making payment, and state of recipient were recorded. The top ten companies and states in terms of payment value were included in analysis. Generalized Estimating Equations (GEE) modeling was used to assess significance.
Results
There were 729,263 industry payments to 20,832 ophthalmologists totaling $817,892,867.54 included for analysis in this study. We found that there was a significant increase in the mean value of research payments and a significant decrease in the mean value of general payments after the onset of the pandemic (both p < 0.001). We also report significant changes in industry payments to ophthalmologists based on the company making the payment and the state in which the ophthalmologist practices.
Conclusions
Our results suggest that significant differences exist in industry payment patterns to ophthalmologists following onset of the COVID-19 pandemic. Understanding underlying reasons for the observed differences may improve our understanding of the relationship between industry and clinical ophthalmology.
Portability profiled power analysis based on deep domain adaptation
Authors: Li Xiang , Yang Ning , Liu Weifeng , Zeng Lu , Chen Aidong 
Published: September 2023

Abstract
The security of password information is essential to protect personal privacy and sensitive data. In recent years, deep learning-based side-channel profiled analysis has been more in-depth research. However, the differences between devices caused by circuit design, process parameters and other hardware characteristics have not been well solved, and the generalization ability of pre-trained models on new devices is poor, and the prediction performance is low. Therefore, this paper proposes a new method, Portability Profiled Power Analysis (PPPA) strategy, which combines domain adaptive and deep learning technology to model and calibrate the domain difference between the profiling device and the target device. Improve model adaptability in different device environments. Experiments show that the proposed method can recover the key information of different devices and effectively reduce the influence of domain differences caused by different devices.
Cholecystokinin B Receptor Agonists Alleviates Anterograde Amnesia in CCK-deficient and Aged Alzheimer's Disease Mice
Authors: Zhang Nan , Sui Yixuan , Jendrichovsky Peter , Feng Hemin , Shi Heng , Zhang Xu , Xu Shenghui , Sun Wenjian , Zhang Huatang , Chen Xi , Tortorella Micky D , He Jufang 
Published: September 2023

Abstract
Background As one major symptom of Alzheimer’s disease (AD), anterograde amnesia describes patients with an inability in new memory formation. The crucial role of the entorhinal cortex in forming new memories has been well established, and the neuropeptide cholecystokinin (CCK) is reported to be released from the entorhinal cortex to enable neocortical associated memory and long-term potentiation. Though several studies reveal that the entorhinal cortex and CCK are related to AD, it is less well studied. It is unclear whether CCK is a good biomarker or further a great drug candidate for AD.Methods mRNA expressions of CCK and CCK-B receptor (CCKBR) were examined in two mouse models, 3xTg AD and CCK knock-out (CCK−/−) mice. Animals’ cognition was investigated with Morris water maze, novel object recognition test and neuroplasticity with in-vitro electrophysiological recording. Drugs were given intraperitoneally to animals to investigate the rescue effects on cognitive deficits, or applied to brain slices directly to explore the influence in inducement of long-term potentiation.Results Aged 3xTg AD mice exhibited reduced CCK mRNA expression in the entorhinal cortex but reduced CCKBR expression in the neocortex and hippocampus, and impaired cognition and neuroplasticity comparable with CCK−/− mice. Importantly, the animals displayed improved performance and enhanced long-term potentiation after the treatment of CCKBR agonists.Conclusions Here we provide more evidence to support the role of CCK in learning and memory and its potential to treat AD. We elaborated on the rescue effect of a promising novel drug, HT-267, on aged 3xTg AD mice. Although the physiological etiology of CCK in AD still needs to be further investigated, this study sheds light on a potential pharmaceutical candidate for AD and dementia.
Reliability analysis of three-dimensional reinforced slope considering the spatial variability in soil parameters
Authors: Wang Yuke , Shao Linlan , Wan Yukuai , Chen Hao 
Published: September 2023

Abstract
In this paper, a procedure is proposed for calculating the reliability of three-dimensional reinforced slopes, taking into consideration the spatial variability of soil strength parameters. An ellipsoidal sliding surface is utilized as an approximate substitute for the actual sliding surface. The Karhunen–Loève (KL) expansion method is employed to generate random fields. The safety factor of the reinforced slope is determined using the Bishop method, and the reliability is evaluated through the Monte Carlo method. Based on the procedure, the effects of different reinforcement parameters and random parameters on the mean safety factor and failure probability of three-dimensional slopes are studied and compared with the results of two-dimensional slopes. It is observed that slope reliability is significantly improved by the implementation of the upper sparse and lower dense reinforcement scheme, leading to a notable 38.4% reduction in failure probability and a 2.4% increase in the safety factor. Additionally, an effective means of enhancing slope reliability is found to be the increase in the length and number of reinforcement layers. The reliability of 3D reinforced slopes is notably influenced by the spatial variability of soil strength parameters. The degree of influence of autocorrelation distance on the failure probability is ranked as lz > lx > ly. When lz increases from 1m to 5m, the failure probability is increased by 221.85%, from 5.4–17.38%. As the correlation coefficient r(c, φ) increases from − 0.7 to -0.3, the failure probability is increased by 26.7%. The comparison with 2D reinforced slopes reveals that 3D reinforced slopes demonstrate a higher safety factor and a lower failure probability. As a result, slope reliability is tended to be underestimated by the 2D slope analysis.
Comparison of estimated GFR using cystatin C versus creatinine in pediatric kidney transplant recipients
Authors: Pizzo Helen , Nguyen John , Schwartz George J , Wesseling-Perry Katherine , Ettenger Robert , Chambers Eileen Tsai , Weng Patricia 
Published: September 2023

Abstract
Background
An accurate, rapid estimate of glomerular filtration rate (GFR) in kidney transplant patients affords early detection of transplant deterioration and timely intervention. This study compared the performance of serum creatinine (Cr) and cystatin C (CysC)-based GFR equations to iohexol GFR (iGFR) among pediatric kidney transplant recipients.
Methods
CysC, Cr, and iGFR were obtained from 45 kidney transplant patients, 1–18 years old. Cr- and CysC-estimated GFR (eGFR) was compared against iGFR using the Cr-based (Bedside Schwartz, U25-Cr), CysC-based (Gentian CysC, CAPA, U25-CysC), and Cr-CysC combination (CKiD Cr-CysC, U25 Cr-CysC) equations in terms of bias, precision, and accuracy. Bland-Altman plots assessed the agreement between eGFR and iGFR. Secondary analyses evaluated the formulas in patients with biopsy-proven histological changes, and K/DOQI CKD staging.
Results
U25-CysC and Gentian CysC equations had the smallest bias. 88.9% of U25-CysC and 82.2% of Gentian CysC estimations were within 30% iGFR; 37.8% of both and 40% of CKiD Cr-CysC were within 10% iGFR. In subjects with histological changes on biopsy, U25-CysC and Gentian CysC had the smallest bias and were most accurate - both with 83.3% of and 41.7% of estimates within 30% and 10% iGFR, respectively. U25-CysC, CKiD Cr-CysC, and U25 Cr-CysC, were the most precise. Bland-Altman plots show the Bedside Schwartz, Gentian CysC, CAPA, and U25-CysC tend to overestimate GFR when > 100 ml/min/1.72m2. CAPA misclassified CKD stage the least (whole cohort 24.4%, histological changes on biopsy 33.3%).
Conclusion
In this small cohort, CysC-based equations appear to have better bias, precision, and accuracy in predicting GFR.
Calibrated Explanations for Regression
Authors: Löfström Tuwe , Löfström Helena , Johansson Ulf , Sönströd Cecilia , Matela Rudy 
Published: September 2023

Abstract

Artificial Intelligence (AI) is often an integral part of modern decision support systems (DSS). The best-performing predictive models used in AI-based DSS lack transparency. Explainable Artificial Intelligence (XAI) aims to create AI systems that can explain their rationale to human users. Local explanations in XAI can provide information about the causes of individual predictions in terms of feature importance. However, a critical drawback of existing local explanation methods is their inability to quantify the uncertainty associated with a feature's importance. This paper introduces an extension of a feature importance explanation method, Calibrated Explanations (CE), previously only supporting classification, with support for standard regression and probabilistic regression, i.e., the probability that the target is above an arbitrary threshold. The extension for regression keeps all the benefits of CE, such as calibration of the prediction from the underlying model with confidence intervals, uncertainty quantification of feature importance, and allows both factual and counterfactual explanations. CE for standard regression provides fast, reliable, stable, and robust explanations. CE for probabilistic regression provides an entirely new way of creating probabilistic explanations from any ordinary regression model, allowing dynamic selection of thresholds. The performance of CE for probabilistic regression regarding stability and speed is comparable to LIME. The method is model agnostic with easily understood conditional rules. An implementation in Python is freely available on GitHub and for installation using both pip and conda, making the results in this paper easily replicable.
Characterizations of a New Generalized Family of Distributions
Authors: Maswadah M. 
Published: September 2023

Abstract

This paper introduces a new family that extends some lifetime distributions, such as the Weibull, inverse Weibull, Lomax, logistic, and log-logistic distributions, which could be applied in several fields, especially to fit lifetime data. This family has a monotonically increasing and decreasing hazard rate. Some characteristics of one of these distributions, such as the Weibull-Logistic distribution, have been studied, including the hazard rate function, quantile function, moments, and distribution of the order statistics. Three real data sets have been studied that show this distribution can be used quite effectively in fitting and analyzing real lifetime data and provides a better fit than other well-known lifetime models such as Weibull, inverse Weibull, and log-logistic distributions. Finally, Monte Carlo simulations have been carried out to calculate the asymptotic confidence bounds for the distribution parameters.
Mercury Speciation in Highly Contaminated Soils from Chlor‐Alkali Plants Using Chemical Extractions
Authors: Neculita Carmen‐Mihaela , Zagury Gérald J. , Deschênes Louise 
Published: September 2023

ABSTRACTA four‐step novel sequential extraction procedure (SEP) was developed to assess Hg fractionation and mobility in three highly contaminated soils from chlor‐alkali plants (CAPs). The SEP was validated using a certified reference material (CRM) and pure Hg compounds. Total, volatile, and methyl Hg concentrations were also determined using single extractions. Mercury was separated into four fractions defined as water‐soluble (F1), exchangeable (F2) (0.5 M NH4Ac–EDTA and 1 M CaCl2 were tested), organic (F3) (successive extractions with 0.2 M NaOH and CH3COOH 4% [v/v]), and residual (F4) (HNO3 + H2SO4 + HClO4). The soil characterization revealed extremely contaminated (295 ± 18 to 11 500 ± 500 mg Hg kg−1) coarse‐grained sandy soils having an alkaline pH (7.9–9.1), high chloride concentrations (5–35 mg kg−1), and very low organic carbon content (0.00–18.2 g kg−1). Methyl Hg concentrations were low (0.2–19.3 μg kg−1) in all soils. Sequential extractions indicated that the majority of the Hg was associated with the residual fraction (F4). In Soils 1 and 3, however, high percentages (88–98%) of the total Hg were present as volatile Hg. Therefore, in these two soils, a high proportion of volatile Hg was present in the residual fraction. The nonresidual fraction (F1 + F2 + F3) was most abundant in Soil 1 (14–42%), suggesting a higher availability of Hg in this soil. The developed and validated SEP was reproducible and efficient for highly contaminated samples. Recovery ranged between 93 and 98% for the CRM and 70 and 130% for the CAP‐contaminated soils.
Health risk assessment of nitrate pollution of drinking groundwater in rural areas of Suihua, China
Authors: Sun Qifa , Yang Ke , Liu Tao , Yu Junbo , Li Chunhai , Yang Dexian , Hu Chen , Guo Lin 
Published: September 2023

Abstract
In order to investigate the health risks of NO3− in rural drinking groundwater in Suihua, China and provide a basis for healthy drinking water, 40 sets of groundwater samples were collected in the Suihua area, and the average concentration of nitrate in the study area was 71.66 mg/L, statistical analysis software (SPSS19), Hydrogeochemical Analysis Software (AqQA) and groundwater pollution analysis software were used. Through water sample collection, chemical analysis and construction of human health risk model (HHRA), a qualitative and quantitative assessment of NO3− health risk was carried out for people of different ages and sexes, and it was concluded that there was NO3− pollution health risk in rural drinking groundwater in Suihua. Health risk level: infants &gt; children &gt; adult females &gt; adult males. The evaluation provides a scientific basis for the prevention and control of NO3− pollution in groundwater and new ideas for preventing human health risks.
Correlation between wastewater and COVID-19 case incidence rates in major California sewersheds across three variant periods
Authors: Rabe Angela , Ravuri Sindhu , Burnor Elisabeth , Steele Joshua A. , Kantor Rose S. , Choi Samuel , Forman Stanislav , Batjiaka Ryan , Jain Seema , León Tomás M. , Vugia Duc J. , Yu Alexander T. 
Published: September 2023

Abstract

Monitoring for COVID-19 through wastewater has been used for adjunctive public health surveillance, with SARS-CoV-2 viral concentrations in wastewater correlating with incident cases in the same sewershed. However, the generalizability of these findings across sewersheds, laboratory methods, and time periods with changing variants and underlying population immunity has not been well described. The California Department of Public Health partnered with six wastewater treatment plants starting in January 2021 to monitor wastewater for SARS-CoV-2, with analyses performed at four laboratories. Using reported PCR-confirmed COVID-19 cases within each sewershed, the relationship between case incidence rates and wastewater concentrations collected over 14 months was evaluated using Spearman's correlation and linear regression. Strong correlations were observed when wastewater concentrations and incidence rates were averaged (10- and 7-day moving window for wastewater and cases, respectively, ρ = 0.73–0.98 for N1 gene target). Correlations remained strong across three time periods with distinct circulating variants and vaccination rates (winter 2020–2021/Alpha, summer 2021/Delta, and winter 2021–2022/Omicron). Linear regression revealed that slopes of associations varied by the dominant variant of concern, sewershed, and laboratory (β = 0.45–1.94). These findings support wastewater surveillance as an adjunctive public health tool to monitor SARS-CoV-2 community trends.