bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long-Term Greenness Effects of Urban Forests to Reduce PM10 Concentration: Does the Impact Benefit the Population Vulnerable to Asthma?
Authors: Jeong Jinsuk , Kim Chaewan , Choi Sumin , Sou Hong-Duck , Park Chan-Ryul 
Published: December 2024

This study investigates the effect of urban forests in reducing particulate matter (PM) concentrations and its subsequent impact on the number of asthma care visits. Understanding the mechanisms behind the relationship between the greenness of blocking forests and the reduction of PM is crucial for assessing the associated human health benefits. This study analyzed the influencing factors for reducing long-term PM10 concentrations, utilizing the vegetation index and meteorological variables. Results showed that the reduction in PM10 began in 2011, five years after the establishment of the blocking forest. The annual mean PM10 concentrations decreased significantly, driven primarily by summer wind speed and summer Enhanced Vegetation Index (EVI), explaining about 62% of the variation. A decrease in the number of asthma care visits was observed, similar to the trend of PM10 reduction in the residential area and the increase in the greenness of the blocking forest. The influx of PM into the city, primarily driven by prevailing northwesterly winds, may have been mitigated by the growing blocking forest, contributing to a reduction in asthma-related medical visits among urban residents. In particular, since the onset of the COVID-19 pandemic in 2020, the increase in the PM2.5/PM10 ratio in residential area has become more closely linked to the increase in asthma-related medical visits. It suggests another PM2.5 emission source in the residential area. The number of asthma care visits among children (under 11) and the elderly (over 65) exhibited a strong positive correlation with PM10 levels and a negative correlation with the Normalized Difference Vegetation Index (NDVI). This suggests a link between air quality improvement from the greenness of blocking forests with their capacity to capture PM and respiratory health outcomes, especially for the vulnerable groups to asthma. These findings highlight the need to manage pollutant sources such as transportation and the heating system in residential areas beyond industrial emissions as the point pollution source. The management policies have to focus on protecting vulnerable populations, such as children and the elderly, by implementing small-sized urban forests to adsorb the PM2.5 within the city and establishing blocking forests to prevent PM10 near the industrial complex.
The Impact of Selected Components Used in Clinical Nutrition on Inflammation Caused Malnutrition a Literature Review
Authors: Raczyńska* Aleksandra , Koronowicz* Aneta , Skotnicki Piotr , Leszczyńska Teresa 
Published: December 2024

Malnutrition is a disease leading to unfavourable changes. It affects 35-55% of hospitalized patients, and in the case of cancer even 40-90% of patients. Screening nutritional status allows for prevention of malnutrition, which will be an element as important as its treatment. Malnutrition in patients after severe injuries significantly increases catabolic changes. Cytokines and hormones such as epinephrine and cortisol are released, which among other things can increase energy expenditure by 50%. The effect of a properly conducted nutritional treatment is the maintenance or improvement of the nutritional status in patients whose nutrition with a natural diet is insufficient, as well as, in some cases, treatment of the underlying disease. Immunonutrition is characteristic for patients with neurological disorders or cancer. It is a regimen based on the supply of selected ingredients that have the ability to affect immunological and anti-inflammatory pathways. such substances are omega - 3 fatty acids, glutamine, arginine, nucleotides, antioxidants and prebiotic fiber.
Does targeting CPP at CPPopt actually improve cerebrovascular reactivity? A secondary analysis of the COGiTATE randomised controlled trial
Authors: beqiri erta , Tas Jeanette , Czosnyka Marek , Kaam Ruud CR van , Donnelly Joseph , Haeren Roel H , Horst Iwan CC van der , Hutchinson Peter J , Kuijk Sander M.J. van , Liberti Annalisa L , Menon David K , Hoedemaekers Cornelia WE , Depreitere Bart , Meyfroidt Geert , Ercole Ari , Aries Marcel JH , Smielewski Peter 
Published: December 2024

Abstract

Background.
The ‘CPPopt Guided Therapy: Assessment of Target Effectiveness’ (COGiTATE) randomised controlled trial demonstrated the feasibility and safety of targeting an automated cerebral perfusion pressure (CPP) tailored to optimise cerebrovascular autoregulation (CPPopt) in Traumatic Brain Injury (TBI) patients requiring intracranial pressure management. The average values of the autoregulation index PRx were not different between the intervention and control group of the trial. This secondary analysis was performed to investigate whether there were differences in autoregulatory endpoints between the intervention (CPPtarget=CPPopt) and control (CPPtarget=60-70 mmHg) groups in a more granular way. Specifically, was there a difference in autoregulatory status between the two groups and what were the PRx values in 1-hour averaged periods when CPP was close to the CPPopt based target?
Methods.
We analysed data from the 28 and 32 patients randomised to the control and intervention group of the COGiTATE study, respectively. We compared hourly-averaged deltaPRx (PRx minus PRxopt, where PRxopt is PRx at CPPopt) between the two groups focusing on periods of globally preserved/homogeneous autoregulation (negative PRxopt). For each patient in the intervention group, PRx values in periods when deltaCPP (CPP-CPPopt target) was between -5 and +5 mmHg were compared to values in periods when deltaCPP was outside this range.
Results.
Median deltaPRx was significantly lower in the intervention group for nevative PRxopt (Mann-U test, p<0.001). For each patient in this group, median PRx was lower in periods when CPP was close to the CPPopt-based target (Wilcoxon test, p<0.001).
Conclusion.
Despite no difference in grand mean PRx, our results suggest that targeting CPPopt provides an effective way of improving cerebrovascular reactivity in TBI patients, offering a rational intervention for trials that address this issue. We also bring insight into aspects of the PRx/CPP relationship that should be considered for autoregulation-guided management for future clinical protocols and trials design.
Filling the gaps. Computational approaches to incomplete archaeological networks
Authors: Priß Deborah , Wainwright John , Lawrence Dan , Turnbull Laura , Prell Christina , Karritevlis Christodoulos , Ioannides Andreas A. 
Published: December 2024

Abstract

Networks are increasingly used to describe complex archaeological data in terms of nodes (the entities of the system) and edges (representing relationships like distance or similarity between each pair of nodes). Network analysis can then be applied to express local and global properties of the system, including structure (e.g. modularity) or connectivity. However, the usually high amount of missing data in archaeology and the uncertainty they cause make it difficult to obtain meaningful and robust results from the statistical methods utilised in the field of network analysis. Hence, we present in this paper manual and computational methods to 1) fill gaps in the settlement record and 2) reconstruct an ancient route system to retrieve a network that is as complete as possible. Our study focuses on the sites and routes, so-called hollow ways, in the Khabur Valley, Mesopotamia, during the Bronze and Iron Age as one of the most intensively surveyed areas worldwide. We were able to identify additional sites that were missing from the record as well as develop an innovative hybrid approach to complement the partly preserved hollow way system by integrating a manual and computational procedure. The set of methods we used can be adapted to significantly enhance the description of many other cases, and with appropriate extensions successfully tackle almost any archaeological region.
Link between body fat percentage and the future risk of diabetes in Chinese individuals with prediabetes: A 5-year longitudinal cohort study
Authors: Cao Jun , Cai Shichun , Huang Zhenhua , Su Zhaohai , Jiang Rengui , Yang Jiangyong , Zhang Bilong , Zhu Hengqing , Xie Zheng , Lu Weiling 
Published: December 2024

Abstract

Objective:Given the scarce research on the link between body fat percentage(BF%) and diabetes risk among Chinese adults with prediabetes, our study aimed to investigate the relationship between BF% and the likelihood of developing diabetes in this group.
Methods: This historical cohort study included 26,014 Chinese individuals diagnosed with prediabetes, who underwent health evaluations between 2010 and 2016.We utilized Cox proportional hazards regression models to investigate the relationship between baseline BF% and the risk of diabetes in adults diagnosed with prediabetes. Furthermore, we utilized Cox proportional hazards models in combination with cubic spline functions and smooth curve fitting to assess the nonlinear relationship between initial BF% and the onset of diabetes. To ensure the dependability of our findings, we conducted various sensitivity and subgroup analyses.
Results: After controlling for various covariates, the research indicated a positive correlation between BF% and diabetes risk (HR=1.43, 95% CI: 1.31-1.55, p<0.0001).The likelihood of developing diabetes progressively rose across the BF% quartiles (Q1 to Q4), with Q4 showing a significantly elevated risk relative to Q1 (adjusted HR=1.96, 95% CI=1.63-2.36).Furthermore, a nonlinear association emerged between BF% and diabetes risk in adults with prediabetes, marked by an inflection point at 25.2%.On the left side of this turning point, the HR stood at 3.14 (95% CI 2.08-4.75), whereas on the right side, it was 1.28 (95% CI 1.16-1.42).
Conclusion: Our study indicates a positive, nonlinear relationship between BF% and diabetes risk among Chinese individuals with prediabetes. For this population, reducing BF% can lower the risk of developing diabetes, particularly when BF% is decreased to below 25.2%.
Structural MRI Study of Pareidolia and Visual Hallucinations in Drug-Naïve Parkinson’s Disease
Authors: Ozawa Masakazu , Shiraishi Tomotaka , Murakami Hidetomo , Yoshimaru Daisuke , Onda Asako , Matsuno Hiromasa , Komatsu Teppei , Sakuta Kenichi , Sakai Kenichiro , Umehara Tadashi , Mitsumura Hidetaka , Okano Hirotaka James , Iguchi Yasuyuki 
Published: December 2024

Abstract

Visual hallucinations (VH) and pareidolia, a type of minor hallucination, share common underlying mechanisms. However, the similarities and differences in their brain regions remain poorly understood in Parkinson’s disease (PD). A total of 104 drug-naïve PD patients underwent structural MRI and were assessed for pareidolia using the Noise Pareidolia Test (NPT) were enrolled. Subcortical gray matter volume and cortical surface volume were analyzed using the FreeSurfer software. Structural analyses revealed associations between NPT scores and atrophy in the right thalamus, right hippocampus, right temporal cortex, and right orbitofrontal cortex in all PD participants. These results were almost the same after adjusting for right-handed 97 patients with PD. It is considered that hallucinations in patients with PD are related to altered integration of sensory input (bottom-up) and prior knowledge (top-down) within the visual system. Our findings indicate that pareidolia in PD involves both bottom-up (thalamus and temporal cortex) and top-down (orbitofrontal cortex) processing disturbances; in contrast, VH predominantly involves bottom-up but not top-down regions. Understanding these distinctions could aid in the development of targeted interventions for hallucinations in patients with PD.
Comprehensive characterization of solar wind interaction with lunar crustal magnetic fields: Kaguya low-altitude observations
Authors: Ogino Kohei , Harada Yuki , Nishino Masaki N , Saito Yoshifumi , Yokota Shoichiro , Kasahara Yoshiya , Kumamoto Atsushi , Takahashi Futoshi , Shimizu Hisayoshi 
Published: December 2024

Abstract

Although the Moon does not have a global intrinsic magnetic field, lunar crustal magnetic anomalies (LMAs) are nonuniformly distributed over the lunar surface. The interaction between the solar wind and LMAs leads to the formation of mini-magnetospheres. Since the spatial scales of LMAs are very small, below several tens of kilometers, solar wind ions are demagnetized while electrons are still magnetized, forming Hall electric fields typically at low altitudes (~30 km). Since direct observations of these interaction regions are challenging from typical nominal altitudes of lunar orbiters (~100 km), the solar wind-LMA interaction has not been fully understood. In this study, we analyze low-altitude data obtained by Kaguya over various LMAs to comprehensively characterize the plasma environment and electromagnetic fields in the solar wind-LMA interaction region. We observe strong solar wind ion reflection and whistler mode waves at 1–10 Hz under high solar wind dynamic pressure and strong interplanetary magnetic field conditions, respectively. These trends are particularly clear over spatially extended LMAs. Over both spatially isolated and extended LMAs, strong Broadband Electrostatic Noise at 1–10 kHz tends to be observed when the spacecraft is magnetically connected to the lunar surface. In addition, our results suggest that anti-moonward electrostatic fields at low altitudes contribute to the acceleration, deceleration, and reflection of incident solar wind particles, and the resulting modification of particle velocity distribution functions can strongly influence the nature of the solar wind-LMA interaction including plasma wave excitation. Based on Kaguya data, we also develop a predictable indicator of the central interaction region where solar wind ions and electrons are decoupled. We propose that this indicator can be utilized to define regions of interest for future low-altitude or lander missions to LMA.
Latent profile analysis of anticipatory grief in family caregivers of patients with chronic heart failure and its influencing factors
Authors: Chen Ting , Su Li , Yu Jiajie , Zhao Huiming , Xiao Haoran , Wang Yali 
Published: December 2024

Abstract

Background
Anticipatory grief has been shown to be highly prevalent among family caregivers of patients with advanced illness. However, there is less research on the anticipatory grief of family caregivers with chronic heart failure. Therefore, the purpose of this study was to explore the profile of anticipatory grief among family caregivers of patients with chronic heart failure and to analyze the influencing factors of different profiles.
Methods
A convenience sampling method was adopted to select 205 family caregivers of chronic heart failure patients hospitalized in a tertiary general hospital in Sichuan Province as the research subjects. A general information questionnaire, Anticipatory Grief Scale (AGS), and Fear of Progression Questionnaire-Short Form (FoP-Q-SF) were used for the survey. Latent profile analysis was conducted on the anticipatory grief of family caregivers of chronic heart failure patients, and univariate analysis and multinomial logistic regression analysis were used to explore the influencing factors of anticipatory grief in each subgroup.
Results
The anticipatory grief of family caregivers of chronic heart failure patients could be divided into three latent categories: low anticipatory grief class (16.4%), moderate anticipatory grief class (58.7%), and high anticipatory grief and loss class (24.8%). Gender, education, relationship with the patient, course of disease, and fear of progression were the influencing factors of the latent profile of anticipatory grief among family caregivers of chronic heart failure patients (all P < 0.05).
Conclusion
There are differences in the level of anticipatory grief among different subgroups of family caregivers of chronic heart failure patients. Medical staff can develop personalized intervention measures on the basis of the influencing factors of different categories to alleviate anticipatory grief of family caregivers and promote physical and mental health of caregivers in chronic heart failure patients.
Concordance and Test-Retest Consistency of Sleep Biomarker-Based Neurodegenerative Disorder Profiling
Authors: Levendowski Daniel J , Tsuang Debby , Chahine Lana M. , Walsh Christine M. , Berka Chris , Lee-Iannotti Joyce K. , Salat David , Fischer Corrine , Mazeika Gandis , Boeve Bradley F. , Strambi Luigi Ferini , Lewis Simon J.G. , Neylan Thomas C. , Louis Erik K. St 
Published: December 2024

Abstract

Biomarkers that aid in early detection of neurodegeneration are needed to enable early symptomatic treatment and enable identification of people who may benefit from neuroprotective interventions. Increasing evidence suggests that sleep biomarkers may be useful, given the bi-directional relationship between sleep and neurodegeneration and the prominence of sleep disturbances and altered sleep architectural characteristics in several neurodegenerative disorders. This study aimed to demonstrate that sleep can accurately characterize specific neurodegenerative disorders (NDD). A four-class machine-learning algorithm was trained using age and nine sleep biomarkers from patients with clinically-diagnosed manifest and prodromal NDDs, including Alzheimer’s disease dementia (AD = 27), Lewy body dementia (LBD = 18), and isolated REM sleep behavior disorder (iRBD = 15), as well as a control group (CG = 58). The algorithm was validated in a total of 381 recordings, which included the training data set plus an additional AD = 10, iRBD = 18, Parkinson disease without dementia (PD = 29), mild cognitive impairment (MCI = 78) and CG = 128. Test-retest consistency was then assessed in LBD = 10, AD = 9, and CG = 46. The agreement between the NDD profiles and their respective clinical diagnoses exceeded 75% for the AD, LBD, and CG, and improved when NDD participants classified Likely Normal with NDD indications consistent with their clinical diagnosis were considered. Profiles for iRBD, PD and MCI participants were consistent with the heterogeneity of disease severities, with the majority of overt disagreements explained by normal sleep characterization in 27% of iRBD, 21% of PD, and 26% of MCI participants. For test-retest assignments, the same or similar NDD profiles were obtained for 88% of LBD, 86% in AD, and 98% of CG participants. The potential utility for NDD subtyping based on sleep biomarkers demonstrates promise and requires further prospective development and validation in larger NDD cohorts.
Trends and epidemiology of children treated in specialized burn centers in the Netherlands between 2009 and 2022
Authors: Kemme Frederique M , Berg Eline L van den , Vries Annebeth Meij-de , Gigengack Rolf K , Cuijpers Maxime D , Baar Margriet E van , Nieuwenhuis Marianne K , Zuijlen Paul PM van , Vlies Cees H van der , Bosma Eelke , Pijpe Anouk , N/A Dutch Burn Repository Group 
Published: December 2024

Abstract

Purpose
Knowledge about trends and epidemiology of pediatric burns is useful to identify patterns, to advance medical research, to design prevention programs and resource allocation. The aim of this study is to describe the epidemiology and trends of pediatric burns between 2009–2022 in the three Dutch burn centers. A secondary objective of this study is to evaluate the influence of the COVID-19 pandemic on the pattern of pediatric burns.
Methods
A register-based cohort study was conducted based on data from the Dutch Burn Repository R3. Patients between 0–17 years at the time of the burn injury admitted between 2009 and 2022 to one of the three burn centers, were included. Descriptive statistics were used to investigate the incidence and patient, burn and treatment characteristics. The COVID-19 pandemic years (2020–2021) were compared with the pooled results from pre-COVID years (2017–2019).
Results
A total of 4017 patients were included in this study, of which 3085 (77%) were overnight admissions. The incidence and absolute number of pediatric burn admissions gradually increased over the years, with a small temporary decrease in 2020–2021. Patient- and burn characteristics remained relatively consistent over the years. Three quarters of all patients were between 0 and 3 years old and the majority were boys (59%). A decreasing ratio of length of stay per % total burned surface area and an increase in day admissions was observed since 2016 onwards, which intensified during the COVID-19 pandemic.
Conclusions
There was a slight increase in the number of pediatric admissions to the burn centers between 2009 and 2022. Young children (0–3 years) remain the most frequently affected group. A shorter relative length of stay was observed, as well as an increase in day admissions, which was reinforced by the COVID-19 pandemic.
Evaluating CMIP6 model performance of wet and dry spells by using novel climate rainfall indices over the Southeast Asia Region
Authors: Soe Thet Mar , Okrah Abraham , Oo Kyaw Than , Kamukama Ebaju Gerverse , Zhang Fangmin 
Published: December 2024

Abstract

Understanding and accurately predicting precipitation events is crucial due to their significant impacts on human lives and economies, especially in the Southeast Asia (SEA) region. This study evaluates the performance of CMIP6 models in simulating precipitation indices, focusing on both spatial patterns and temporal variations from 1981 to 2010. Models were classified into two groups: the 'Good_group,' which demonstrated robust performance, and the 'Bad_group,' which exhibited notable biases. The Good_group comprising ACCESS-CM2, ACCESS-ESM1-5, BCC-CSM2-MR, MIROC6, NorESM2-LM, and NorESM2-MM consistently performed better in simulating total precipitation (PRCPTOT), consecutive dry days (CDD), and daily intensity (SDII). These models showed smaller biases and more accurate representations of spatial patterns and temporal variability in the SEA region. Conversely, the Bad_group including EC-Earth3, EC-Earth3-Veg, GFDL-ESM4, and MPI-ESM1-2-LR exhibited significant biases and poorer performance. Specifically, Good_group models provided a more realistic simulation of PRCPTOT and SDII with reduced biases, whereas Bad_group models showed larger errors, especially in northeastern India and Myanmar. For CDD, Good_group models estimated fewer consecutive dry days than observed, while Bad_group models overestimated them. Despite advancements in CMIP6 models, including higher resolutions and improved parameterizations, challenges persist in accurately simulating wet spells dynamics in the complex SEA region. This study identifies the most skilful models and areas for improvement, offering valuable insights for model selection and enhancing climate projections and adaptation strategies in the SEA region.