bluuebunny/crossref_metadata_2025_split huggingface dataset:
Has Muscle Power Better Discriminative Capacity Compared to Muscle Strength in Predicting Worsening Disability in Older Adults?
Authors: Travaglini Silvia , Bonvicini Maria , Bandinelli Stefania , Ferrucci Luigi , Antonelli Incalzi Raffaele , Pedone Claudio 
Published: January 2025

Abstract

Background
Poor muscle strength is a risk factor for disability; nonetheless, its discriminative capacity in identifying people who will become disabled is poor. We evaluated whether muscle power, which also is a risk factor for disability, has better discriminative capacity compared to muscle strength.

Methods
We used data from the population-based InCHIANTI study. Our outcome measure was the loss of at least 1 basic or instrumental activity of daily living between baseline and 3-year follow-up visit. Body weight standardized knee isometric strength and leg power (power rig) were used as exposure variables. Discriminative capacity was estimated using the area under the receiver-operating curves. Both strength and power were dichotomized as below versus equal of above sex-specific first quartile. Sensitivity, specificity, and positive/negative predictive values (PPV, NPV) were calculated.

Results
We included 763 participants (415 women), with a mean age of 73.5 years (standard deviation: 6.4). In men, using muscle strength we obtained an area under the curve (AUC) of 0.70, with sensitivity = 0.45, specificity = 0.80, PPV = 0.27, and NPV = 0.90; using muscle power we obtained an AUC of 0.82, sensitivity = 0.73, specificity = 0.86, PPV = 0.46, and NPV = 0.95. In women, using muscle strength we obtained an AUC of 0.62, with sensitivity = 0.39, specificity = 0.81, PPV = 0.39, and NPV = 0.81; using muscle power we obtained an AUC = 0.69, sensitivity = 0.40, specificity = 0.83, PPV = 0.42, and NPV = 0.82.

Conclusions
We found that in men muscle power had better discriminative capacity, especially higher sensitivity, compared to muscle strength for prediction of worsening disability. No meaningful difference in overall discriminative capacity was found in women.
Functional redundancy of transcription factors SlNOR and SlNOR-like1 is required for pollen development in tomato
Authors: Li Hong-Li , Xiang Lan-Ting , Zhao Xiao-Dan , Zhu Ben-Zhong , Zhu Hong-Liang , Qu Gui-Qin , Luo Yun-Bo , Gao Ying , Jiang Cai-Zhong , Fu Da-Qi 
Published: January 2025

Abstract
In tomato, SlNOR and SlNOR-like1, members of the NAC family of transcription factors (TFs), are known to play critical roles in regulating fruit rpening and are highly expressed in floral organs. However, their role in flower development remains unclear. In this study, we generated and functionally characterized a double knockout mutant, nor/nor-like1. Our findings reveal that the pollen abortion of the nor/nor-like1 impedes ovarian enlargement, resulting in fruit formation failure. Histological analyses demonstrate that the pollen wall collapse occurs during the mature pollen stage and leads to the abnormal pollen wall component deposition at the microspore stage, resulting in the male sterility in the double knockout mutant lines. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analyses further suggest that the loss of SlNOR and SlNOR-like1 function affects several metabolic pathways related to pollen development, including ‘ABC transporters’, ‘lipid metabolism’, ‘phenylpropanoid biosynthesis’, ‘hormone signal transduction’, ‘starch and sucrose metabolism’ and ‘cutin, suberine and wax biosynthesis’. Furthermore, our results demonstrate that SlNOR and SlNOR-like1 could directly bind to the promoters of key genes associated with pollen wall formation and activate their expression, including ATP-binding cassette (ABC) transporters of the G family (SlABCG8/9/23), ECERIFERUM (SlCER1) and glycine-rich protein (SlGRP92). These findings suggest that SlNOR and SlNOR-like1 may play a redundant role in the biosynthesis and transport of sporopollenin precursors, cuticular wax biosynthesis, and exine formation. In summary, our study highlights a previously uncharacterized role of SlNOR and SlNOR-like1 in tomato pollen wall formation and male fertility.
Situated polycrises: Somali responses to COVID-19
Authors: Kleist N , Albrecht P , Ali A E , Bradbury M , Hassan M A , Kanyinga K , Mohamed F D , Musa A M , Norman J 
Published: January 2025

Abstract
This article interrogates the concept of polycrisis through a case-study of Somali perceptions of and responses to the COVID-19 pandemic, introducing the notion of situated polycrises. Inspired by Heidegger's thinking on thrownness and Haraway's on situated knowledges, the term ‘situated polycrises’ underscores the importance of localized perspectives in understanding global crises, challenging universal narratives about their nature and effect. Based on a collective multi-sited methodology with insights from 14 locations in east African and western countries, we examine how Somalis navigated the pandemic amid ongoing emergencies, highlighting the interplay of social, political and cultural factors that influence crisis perceptions and responses. We show that for Somalis drought constitutes a crisis baseline, and that family-related support intensified while collective crisis response occurred at a low level except in the UK, putting claims that COVID-19 was an unprecedented crisis into perspective. We further argue against understanding polycrisis as a novel phenomenon, suggesting that in regions like Somali-inhabited east Africa, where multiple emergencies have intertwined and reinforced one another for decades, the pandemic occurred in an overall context of a long-term polycrisis. We thereby contribute to the nascent literature on polycrisis, both as perceived and confronted from below and in a transnational social field perspective.
Soft balancing in the regions: causes, characteristics and consequences
Authors: Paul T V , He Kai , Wivel Anders 
Published: January 2025

Abstract
US decline and retrenchment is increasing the importance of regional dynamics across the international system. Over the past decade, International Relations scholars have described and conceptualized this development variously as ‘de-centred globalism’, a ‘multi-order world’, a ‘multiplex world’ or a multicultural ‘no one's world’, but the links between the regional and global levels and the roles and functions of regional institutions in power politics continue to be poorly understood. This special section uses the analytical lens of soft balancing—that is, attempts at restraining a threatening power through diplomatic and institutional delegitimation—to explore these links. Soft balancing has been used extensively to understand developments at the great power level, but its focus on diplomatic and institutional strategies holds considerable potential for explaining how rising powers, middle powers and smaller states seek to navigate the emerging international order. Contributors to the section discuss developments in the Indo-Pacific, central Asia, Europe and BRICS to answer questions such as: what are the characteristics of soft balancing in the regions? How do regional actors apply different soft balancing strategies? When and under what conditions will soft balancing strategies be effective? What is their impact on regional and global orders? This introduction offers an overview of soft balancing in theory and practice and their relevance to the world's regions.
Clonal Hematopoiesis of Indeterminate Potential in Crohn’s Disease and Ulcerative Colitis
Authors: Esai Selvan Myvizhi , Nathan Daniel I , Guisado Daniela , Collatuzzo Giulia , Iruvanti Sushruta , Boffetta Paolo , Mascarenhas John , Hoffman Ronald , Cohen Louis J , Marcellino Bridget K , Gümüş Zeynep H 
Published: January 2025

Abstract

Background
Clonal hematopoiesis of indeterminate potential (CHIP) is the presence of somatic mutations in myeloid and lymphoid malignancy genes in the blood cells of individuals without a hematologic malignancy. Inflammation is hypothesized to be a key mediator in the progression of CHIP to hematologic malignancy and patients with CHIP have a high prevalence of inflammatory diseases. This study aimed to identify the prevalence and characteristics of CHIP in patients with inflammatory bowel disease (IBD).

Methods
We analyzed whole-exome sequencing data from 587 Crohn’s disease (CD), 441 ulcerative colitis (UC), and 293 non-IBD controls to assess CHIP prevalence and used logistic regression to study associations with clinical outcomes.

Results
Older UC patients (age &gt; 45) harbored increased myeloid-CHIP mutations compared to younger patients (age ≤ 45) (P = .01). Lymphoid-CHIP was more prevalent in older IBD patients (P = .007). Young CD patients were found to have myeloid-CHIP with high-risk features. Inflammatory bowel disease patients with CHIP exhibited unique mutational profiles compared to controls. Steroid use was associated with increased CHIP (P = .05), while anti-TNF therapy was associated with decreased myeloid-CHIP (P = .03). Pathway enrichment analyses indicated an overlap between CHIP genes, IBD phenotypes, and inflammatory pathways.

Conclusions
Our findings underscore a connection between IBD and CHIP pathophysiology. Patients with IBD and CHIP had unique risk profiles, especially among older UC patients and younger CD patients. These findings suggest distinct evolutionary pathways for CHIP in IBD and necessitate awareness among IBD providers and hematologists to identify patients potentially at risk for CHIP-related complications including malignancy, cardiovascular disease, and acceleration of their inflammatory disease.
Assessing mercury exposure to water and fish of the Mackenzie watershed using a Bayesian network analysis
Authors: Jermilova Una , Kirk Jane L , Moe S Jannicke , Landis Wayne G , Sharpe Emma , McGovern Maeve , Braaten Hans Fredrik Veiteberg , Gundersen Cathrine Brecke , Dastoor Ashu P , Schaefer Kevin , Hintelmann Holger H 
Published: January 2025

Abstract
Bayesian Network Relative Risk Models (BN-RRM) were developed to assess recent (2005–2020) risk of mercury (Hg) exposure to the freshwater ecosystems of Great Slave Lake (GSL) and the Mackenzie River Basin (MRB) in the Canadian Northwest Territories. Risk is defined as the probability of a specified adverse outcome; here the adverse outcome was the probability of environmental Hg concentrations exceeding the Hg regulatory guidelines (thresholds values) established to protect the health of humans and aquatic biota. Environmental models and Hg monitoring studies were organized into a probabilistic (Bayesian network) model which considered six Hg input pathways, including atmospheric Hg deposition, Hg release from permafrost thaw, terrestrial to aquatic Hg transfer via soil erosion, and the proximity to mining, fossil fuel developments, and retrogressive permafrost thaw slumps (RPTS). Sensitivity analysis was used to assess spatial trends in influence of the sources to Hg concentrations in freshwater and in the tissue of five keystone fish species (lake whitefish, lake trout, northern pike, walleye, and burbot) which are essential for the health and food security of the people in the MRB. The risk to the health of keystone fish species, defined by toxicological dose-response curves, was generally low but greatest in GSL where fish size, mine proximity, and soil erosion were identified to be important explanatory variables. These BN-RRMs provide a probabilistic framework to integrate advances in Hg cycling modeling, identify gaps in Hg monitoring efforts, and calculate risk to environmental endpoints under alternative scenarios of mitigation measures. For example, the models predicted that the successful implementation of the Minamata Treaty, corresponding to 35%–60% reduction in atmospheric Hg deposition, would translate to a ∼1.2-fold reduction in fish Hg concentrations. In this way, these models can form the basis for a decision-support tool for comparing and ranking risk-reduction initiatives.
Monitoring wetland cover changes and land surface temperatures using remote sensing and GIS in Göksu Delta
Authors: Gültürk Doğruyol Pınar 
Published: January 2025

Abstract
Wetlands provide necessary ecosystem services, such as climate regulation and contribution to biodiversity at global and local scales, and they face spatial changes due to natural and anthropogenic factors. The degradation of the characteristic structure signals potential severe threats to biodiversity. This study aimed to monitor the long-term spatial changes of the Göksu Delta, a critical Ramsar site, using remote sensing techniques. It seeks to analyze the relationship between these changes and land surface temperature (LST) and predict future land use patterns through machine learning (ML) methods. In this context, the normalized difference vegetation index, modified normalized difference water index, normalized difference bareness index, and normalized difference moisture index remote sensing spectral index analyses and LST maps were generated using Landsat 8 Operational Land Imager (OLI) satellite imagery for 1985, 2000, 2015, and 2023. Kappa accuracy assessments demonstrated a high level of agreement between the generated maps and ground truth data. Pearson correlation analysis was used to assess the consistency of the relationship between spectral index analyses and LST, revealing a statistically significant correlation at the 0.01 level. The study revealed that Lake Akgöl lost 58.85% of its water body over the 38 years of monitoring the delta. This loss was primarily attributed to increased LST and human activities. The land use land cover model for the year 2031, developed using artificial neural networks and cellular automata from ML methods, projected a 7.50% decrease in total water bodies, a 46.94% reduction in vegetated areas, and a 36.85% increase in nonvegetated areas. In conclusion, it was emphasized that the adverse land use trends within the Göksu Delta are expected to persist, degrading its ecosystem services and values. In this context, the study's findings can be utilized to identify strong strategies for protecting the delta.
Valuation of regulating ecosystem services in Africa: a review of policy impact reporting
Authors: Akello Gertrude , Opinde Godwin , Letema Sammy 
Published: January 2025

Abstract
Regulating ecosystem services (RES) play a very critical role in the sustenance of environmental health and human well-being, yet their valuation remains a complex and dynamic field. The variety of valuation methods, each with its strengths and limitations, as well as the limited methodological guidance for the selection of appropriate methods, poses a challenge in the valuation of RES. This review examined RES valuation studies in Africa, focusing on growth trends, methodological preferences, and policy reporting approaches. Drawing on the existing literature, we also explored the use of decision trees to support the choice of appropriate methods. A synthesis of peer-reviewed literature identified 31 studies, and their analysis revealed the dominant use of single-valuation methods in the assessment of RES and a varied growth rate in the number of valuation studies over the period under review. Furthermore, a notable heterogeneity exists in the methods used to report policy impact across various value assessments. This review contributes valuable insights into the current state of RES valuation research, necessary to advance methodologies, guide future research, and inform policy discussions on the sustainable management of ecosystems.
Application of artificial intelligence for nutrient estimation in surface water bodies of basins with intensive agriculture
Authors: Medina-Jiménez José Luis , Amabilis-Sosa Leonel Ernesto , Mendivil-García Kimberly , Morales-Rosales Luis Alberto , Gonzalez-Huitrón Víctor Alejandro , Rodríguez-Rangel Héctor 
Published: January 2025

Abstract
Eutrophication is one of the most relevant concerns due to the risk to water supply and food security. Nitrogen and phosphorus chemical species concentrations determined the risk and magnitude of eutrophication. These analyses are even more relevant in basins with intensive agriculture due to agrochemical discharges. However, analyzing these nutrients is labor intensive, as sampling to intercalibration in the laboratory requires considerable financial and human resources. Currently, artificial intelligence allows the modeling of phenomena and variables in various fields. This research focuses on the exploration of other machine learning methods, including multilayer perceptron (MLP), k-nearest neighbor (KNN), convolutional neural network (CNN), and random forest (RF) for the estimation of nutrients in surface waters of Sinaloa, Mexico (11 model basins), the states with the highest exports of agricultural products. Nutrients were considered in all possible chemical forms, such as total nitrogen, Kjeldahl nitrogen, ammonia nitrogen, total phosphorus, and orthophosphate. For estimation, the selected input parameters are characterized by pH, dissolved oxygen, conductivity, water temperature, and total suspended solids, which do not require chemical reagents and can be measured in real time. The parameter information was obtained from the National Network for Water Quality Monitoring database (6,200 data recorded since 2012). Finally, hyperparameter normalization and optimization (HPO) methods were implemented to maximize the best-performing model. Each model obtained different coefficient of determination values (R2): MLP between 0.64 and 0.77, CNN from 0.65 to 0.76, KNN from 0.64 to 0.79, and RF from 0.79 to 0.85. The latter is considered the best performer, with values of 0.95 in training and 0.94 in validation after applying HPO. Notably, the models are valid for any surface water body and in any climatic season in the state of Sinaloa, México. Therefore decision-makers can use them for science-based environmental regulation of land use and pesticide application.
Identification and treatment of false methane values produced by the tunable diode laser absorption spectroscopy technology equipped on unmanned aerial vehicles
Authors: De Molfetta Maurizio , Fosco Donatello , Renzulli Pietro Alexander , Notarnicola Bruno 
Published: January 2025

Abstract
Fugitive or diffuse methane emissions constitute an important source of damage to the environment, much greater even than CO2 both over a time span of 20 years and over a longer time span of 100. It is therefore of preeminent importance to undertake all the efforts necessary to implement new tools, protocols, and methods that contribute to the identification and measurement of these emissions to implement site-specific actions of mitigation, repair, and conscious management of the emitting plants. Among the remote sensing and leak detection technologies currently used, the tunable diode laser absorption spectroscopy (TDLAS) method plays a relevant role. Thanks to the study and implementation of increasingly high-performance sensors to be equipped on drones, this method is strongly promoted in the unmanned aerial vehicle sector. However, as often happens, the operational performance of a measurement method must be associated with measurement errors, which must be foreseen (where possible), and certainly detailed and corrected. The purpose of this article is to describe the procedure for identifying and processing “false-positive” values recorded by the payload during a survey flight for the measurement of methane concentrations in airborne matrix, with a TDLAS sensor. The methodology contained in this article is based on the study of scientific evidence referable to previous in-depth experiences on false positives and largely on the direct experience gained by the project team of the TALSEF laboratory (University of Bari, Italy) during numerous measurement campaigns in landfills, oil and gas sites, and cattle stables.
A proposal on bird focal species selection for higher tier risk assessments of plant protection products in the EU
Authors: Gießing Benedikt , Kragten Steven , Hotopp Ines , Russ Anja , Fan Marie , Sprenger Dennis , Weyers Arnd , Wolf Christian 
Published: January 2025

Abstract
The revised EFSA 2023 Guidance on the risk assessment of plant protection products for birds and mammals emphasises vulnerability as a relevant criterion for focal species (FS) selection rather than prevalence. The EFSA 2023 Guidance suggests to rank FS candidates for each dietary group according to their expected exposure by estimating a species-specific daily dietary dose (DDD). Species experiencing higher exposure would be ranked as potentially more vulnerable and can be identified as FS candidates. The DDD is calculated using an estimated “proportion of diet an individual obtains from the (treated) crop” (PT). A PT is derived from a radio-tracking field study in the crop of interest, but such data are not available for all species. We introduce the frequency of occurrence in surveys (FOsurvey) in each study field from FS field studies as a proxy for PT in theoretical DDD calculations. The presence of a species during a high proportion of surveys, resulting in a high FOsurvey, could indicate a high proportion of foraging time spent in this crop. To evaluate whether FOsurvey is an appropriate proxy for PT, empirical PT values from radio-tracking studies for different bird species were correlated to respective FOsurvey values from FS studies in the same crop and growth stage. Based on 10 case examples covering different species and crops, a positive correlation was shown between PT and FOsurvey, supporting the suitability of the proposed approach. Based on a positive correlation between the species’ prevalence and the new theoretical DDD, the list of the most relevant FS resulting from the new ranking approach is not expected to differ significantly from the FS selection, according to the methodology proposed in EFSA 2009. However, in a few cases, additional species were identified as potential FS, therefore requiring further consideration in the risk assessment.
A unified approach to SimpleTreat input and settings for wastewater treatment removal predictions
Authors: Burns Thomas D , Beking Michael , Shen Jesse , De Knecht Joop , Bakker Joost , van Vlaardingen Peter , Tolls Johannes , Gouin Todd 
Published: January 2025

Abstract
SimpleTreat has become a common tool used in ecological risk assessments to estimate the removal efficiency of a chemical from a secondary wastewater treatment plant and hence inform on release to the environment. Organization A, Organization B, and Organization C performed a comparative study of SimpleTreat predictions and parameter selection methodologies across the three organizations. SimpleTreat versions 3.1 and 4.1 were run for a set of 10 chemicals using different settings and different approaches to obtain the inputs needed to run the tool. The impacts of these differences on removal predictions for the set of chemicals were explored, and a unified framework was proposed to guide users in the effective use of SimpleTreat.