bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thymoquinone inhibits tumor progression and promotes chemo-sensitivity via modulation of P21/PI3K/Akt axis in colorectal cancer cells
Authors: Zhang Peng , Li Shaowen , Zhang Pei , Sun Yuanfang 
Published: February 2025

Abstract

Natural thymoquinone has been extensively used as a chemopreventive agent and has shown potent anticarcinogenic activity against a broad range of human malignancies. However, the underlying mechanisms and involving signaling pathways are still not well studies. Therefore, this study is aimed to evaluate the effects of thymoquinone on the increasing doxorubicin chemosensitivity via targeting P21 and PI3K/AKT signaling. Caco-2 cells were treated with thymoquinone. MTT assay were applied to assess the impact of different dose of thymoquinone on the doxorubicin cytotoxicity. The mRNA and protein expression levels of PI3K, Akt, P21, P53, Cyc D1, Cdk4, Cdk6, PCNA, Bax, Bcl-2 and caspase-3 were assessed by qRT-PCR and western blotting. A cell death ELISA commercial kits were used to measure apoptosis. We found that thymoquinone treatment significantly decreased proliferation rate in Caco-2 colorectal cancer cells. The survival rate of cells was reduced significantly when doxorubicin was combined with thymoquinone. Thymoquinone upregulated p21, P53 and downregulated Cyc D1, Cdk4, Cdk6, PCNA, as well as suppressed PI3K/Akt signaling pathway. We conclude that thymoquinone induces doxorubicin sensitivity in colorectal cancer cells through targeting p21 and the PI3K/AKT pathway, thus implicating its importance in chemotherapy for colorectal cancer.
Integrative study of various populations of Aporrectodea rosea (Savigny, 1826) based on morphological and molecular analyses (Oligochaeta: Lumbricidae)
Authors: Latif Robabeh , Aminjan Atabak Roohi , Malek Masoumeh , Shekhovtsov Sergei V , Poluboyarova Tatiana V. , Briones Maria J.I. 
Published: February 2025

Abstract

Aporrectodea rosea (Savigny, 1826) is one of the most common earthworm species found in the temperate regions of the Holarctic. In this study, we examined the molecular variation within this species by analyzing both nuclear and mitochondrial sequences. The phylogenetic results were combined with morphological, ecological, and genomic evidence to test species boundaries. Previous studies have divided this species into two lineages: Mediterranean and Eurosiberian. Our analyses revealed that almost all specimens collected from Iran lie within the two established lineages. Some genetic differences observed among the morphotypes in the Iranian populations may relate to their phylogeographic origins (Euro-Siberian/Mediterranean). Additionally, some morphological features might reflect differences in reproductive mode (sexual/parthenogenetic) due to specific ecological conditions.
Severe Bronchiectasis and Chronic Rhinosinusitis Due to Homozygous WFDC2 Variants: The First Three Cases Reported from Japan
Authors: Ito Masashi , Morimoto Kozo , Hijikata Minako , Hasegawa Hirotsugu , Wakabayashi Keiko , Miyabayashi Akiko , Keicho Naoto 
Published: February 2025

Abstract

We report the first three cases of bronchiectasis caused by homozygous WFDC2 variants in Japan. The ages at diagnosis of bronchiectasis were 18, 24, and 16 years, and all patients had a history of chronic sinusitis since childhood. Despite low nasal nitric oxide levels, the radiologic features resembled those of cystic fibrosis, characterized by bronchiectasis predominantly in the upper lobes. All patients experienced frequent exacerbations and respiratory dysfunction, even with long-term macrolide therapy. Consequently, two of the three patients required lung transplantation. Considering the possibility of founder mutations, WFDC2 variants should be included in diagnostic panels for patients with sinopulmonary disease in Asian populations.
Metabolic synergy and complementarity in the Ips typographus holobiont
Authors: Saati-Santamaría Zaki , Kostovčík Martin , Veselská Tereza , Švec Karel , Kolařík Miroslav 
Published: February 2025

Abstract

Microbial symbiosis plays a central role in shaping ecological and evolutionary processes, driving the adaptation of host organisms to challenging environments. However, the mechanisms underlying functional integration and metabolic cooperation within holobionts remain poorly understood. Current research often emphasizes the taxonomic composition of microbiomes, but the metabolic interactions that sustain these associations are less explored, especially in nutrient-poor ecosystems. This study addresses this knowledge gap by investigating the metabolic interdependencies and associations within the gut microbiome of the European spruce bark beetle (Ips typographus, ESBB). Using meta-transcriptomic analyses, we reveal the critical contributions of bacterial and fungal symbionts in facilitating host survival. Our findings show that microbial partners compensate for host metabolic deficiencies, with cross-kingdom cooperation enabling the biosynthesis of essential nutrients such as amino acids and vitamins. Furthermore, a division of labor among microbial taxa is evident, with bacteria primarily degrading plant polymers such as xylan and pectin, and fungi specializing in glucan degradation. Functional redundancy in key pathways suggests an adaptive mechanism to ensure nutrient availability under fluctuating microbial community composition. In addition, we identify a previously unappreciated pathway for nitrogen acquisition via bacterial oxidation of inorganic nitrogen. Our findings highlight the ecological importance of metabolic interdependencies in holobionts and their role in the evolutionary success of symbiotic associations. Our results provide a framework for exploring microbial cooperation in nutrient cycling and resource use.
Exploring Type Iax supernovae observables and progenitors through one-dimensional radiation-hydrodynamics simulations of CO white dwarfs
Authors: Yang Thomas Zhirui , Moon Dae-Sik 
Published: February 2025

Abstract

Early-time radioactive signals from type Ia supernovae (SNeIa) can provide important constraints on the explosion mechanism and the progenitor system. We investigate whether shock ignition models of Chandresehkar-mass carbon oxygen white dwarf stars in the SD WD-He star scenario can account for observed population of the Type Iax supernovae (SN Iax) explosions. We compute 8 1D full-star radiation-hydrodynamic explosion models (using SNEC) from a WD model accreting pure helium from its helium star companion (using MESA), and compare their synthetic light curves as well as other profiles with that of well-observed real SNe Iax. In addition, we explore how the amount of nickel placed from the core of WD would shape these light curves. We find the 56Ni shows a directly proportional relationship to peak luminosity, as peak luminosities of some models match to corresponding SNe Iax with calculated nickel masses. We find that synthetic lightcurves of our models predict early time light curves of observed SNe Iax fairly well, while more discrepancies arise after ~40 days after explosion. Which suggests that real SNe Iax has a more efficient γ-ray deposition in later times than models. This is also shown through color light curves, where model with MNi=0.25M⊙ has a decline rate of Δm15(B)=2.57 mag. Models also predict low-energy SNe better, such as with SN 2023mnc, SN 2019gsc, and SN 2019muj. The photospheric velocity of models reaches a peak kick velocity of ~167000 kms-1 for an Eexp=1.63x1052 erg explosion and then quickly decelerates to stationary at ~15 days. We find that velocity profile of the models shows similar deceleration rate as real SNe Iax and the power law after its been scaled by a factor of 0.1 to match SNe Iax explosion energies.
UK ADHD treatment rates – a regional variation model
Authors: French Blandine , Davies James , Williams Chris , Kirby Amanda 
Published: February 2025

Abstract

Background – Attention deficit hyperactivity disorder (ADHD) is a common condition impacting approximately 5% of children and 3-4% of adults in the United Kingdom (UK). While it cannot be cured, treatment has shown to positively impact the difficulties associated with ADHD. However, ADHD is widely under-diagnosed and under-treated in the UK. This paper reports the results of a model developed to estimate pharmacological treatment rates by area across National Health Service (NHS) integrated care systems (ICSs) in England, health boards in Scotland and Wales, and health & social care trusts (HSCTs) in Northern Ireland.
Methods - The model used UK general population and ADHD prevalence data to estimate the number of patients with ADHD in each area. Prescription data for medicines licensed for the treatment of ADHD were then used to estimate the number of patients that are untreated and treated, and percentage treatment rates by area.
Results - Nationally, the estimated proportions of the children and young people (CYP; 5–17 years) and adult populations (18–65 years) treated were 26.6% and 15.6%, respectively, of the expected ADHD populations. Treatment rates by ICS or health board in England, Scotland and Wales ranged from 11.7% to 60.6% for the CYP population, and 8.6% to 24.8% in the adult population (data for Northern Ireland were not available by age group). Overall treatment rates (ages 5–65 years) in Northern Ireland ranged from 6.7% in the lowest ranking HSCT to 31.1% in the highest-ranking HSCT.
Conclusions - In the UK, there is currently a high degree of geographic variation across all NHS systems and a generally low level of treatment of ADHD, especially in adults. Up to a 4.6-fold difference in pharmacological treatment rates was observed between NHS service provider areas.
Engaging Leadership Reduces Quiet Quitting and Improves Work Engagement: Evidence from Nurses in Greece
Authors: Moisoglou Ioannis , Katsiroumpa Aglaia , Papathanasiou Ioanna V. , Konstantakopoulou Olympia , Katharaki Maria , Galanis Petros 
Published: February 2025

Abstract

Aim: To examine the impact of engaging leadership on quiet quitting and work engagement among nurses.
Design: A cross-sectional study was conducted with a convenience sample.
Methods: Data collection occurred in October 2024 via an online survey. We used valid tools to measure our study variables; the “Engaging Leadership Scale-12” for engaging leadership, the “Quiet Quitting Scale” for quiet quitting, and the “Utrecht Work Engagement Scale-3” for work engagement. We applied univariate and multivariable linear regression analysis to identify the association between engaging leadership, quiet quitting and work engagement.
Results: Our multivariable models showed a negative association between engaging leadership and quiet quitting connecting. Moreover, we found a positive association between engaging leadership and work engagement after elimination of confounders.
Conclusion: Our findings suggest that higher levels of engaging leadership reduce quiet quitting and improve work engagement. Nurses managers should adopt engaging leadership to improve nurses’ motivation and thus, clinical outcomes.
Implications for the Profession and/or Patient Care: Nurses that tend to quiet quitting and exhibit disengagement markedly diminish their performance, opt to deliver reduced nursing care, and their job lacks vitality. They frequently contemplate resigning from their employment. Nonetheless, such work behavior can compromise the quality and safety of care, result in missing care, and lead to patient dissatisfaction.
Impact: Our study emphasizes the significant impact of engaging leadership, which enhances nurses' motivation and engagement to work by strengthening, empowering, fostering teamwork, and inspiring them. The adoption and implementation of engaging leadership by nursing administrations serves as a crucial supportive mechanism within the demanding work environment of nurses.
A hybrid data assimilation and machine learning approach for enhancing operational forecasting in 2D hydrodynamic models
Authors: Cremer Clemens Johannes Matthias , Mariegaard Jesper Sandvig , Andersson Henrik Johan 
Published: February 2025

ABSTRACT

Data assimilation (DA) integrates observations to enhance model predictions, but its benefits can rapidly decay during forecast for models heavily influenced by boundary conditions. To extend forecast accuracy, we combine machine learning (ML) with DA in a hybrid approach. We utilize ML to create synthetic point observations, which are assimilated into the model and thus propagated to other positions and model variables. In a case study, we apply the approach to a tidal estuary hydrodynamic model using a long short-term memory (LSTM) network for ML forecasts and the Ensemble Kalman Filter (EnKF) for assimilation. Hereby, physical consistency and spatial representation of water levels in the estuary are maintained. Our results from 100 forecast runs show significant improvements: over 40% accuracy increase in forecasts up to 4 h ahead, and a &gt;5% error reduction at 9 h compared with a traditional numerical model without assimilation.
Source identification and characterization of water-insoluble single particulate matter in rainfall sequences
Authors: Kilic Murat , Kilic Serpil , Pamukoğlu Muhammet Yunus 
Published: February 2025

ABSTRACT
Analysis of atmospheric pollutants in rainwater provides valuable information on the environmental impacts of both natural and anthropogenic pollution sources. Air pollution studies often show that particulate matter (PM) collection on filters is used for subsequent analysis. However, this approach can result in significant particle accumulation on filters and complicate their characterization by semi-quantitative analytical techniques. In this study, insoluble PM in sequentially collected rainwater samples was analyzed for particle size, morphology, and chemical composition. Scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectrometry (EDS) and a particle size analyzer were used for these analyses. By combining SEM–EDS data with particle size distribution analyses, chemical composition findings, and upper atmosphere back-orbit modeling, specific sources of insoluble particles in rainwater were identified. In addition, rainwater samples were analyzed for pH, electrical conductivity, and major anions and cations. The pH values varied from 6.19 to 7.04, while the electrical conductivity values varied from 5.35 to 83.53 μS/cm. Among the major ions, relatively high concentrations of Ca2+, SO42−, and NO3− were detected, while F−, Mg2+, Na+, and Cl− were observed in lower concentrations. The contributions of sea salt were evidenced by the presence of Cl− and Na+ ions.
United States floods within the context of atmospheric moisture sources and pathways
Authors: Aljoda Ali , Jain Shaleen 
Published: February 2025

ABSTRACT
Floods are devastating and costly, making accurate flood frequency and magnitude estimates essential for engineering and planning. This study examines flood characterization within a hydroclimate context. At-site analysis links flood events to atmospheric moisture pathways and source origins to understand the floods regionality and develop new modalities for flood frequency estimation in a changing climate. A novel principal curves approach is developed and applied to 623 stream gauges across the conterminous United States (US) over the 1956–2015 period, analyzing 37,380 annual floods, with Atmospheric Rivers (ARs) contributing ∼73%. The Northwest, West, Northeast, and Southeast experienced 70–100% AR-driven floods, while the East North Central, Central, South, and Southwest saw &lt;70%, and the West North Central had &lt;15%. Attributing floods to their moisture source significantly improves flood frequency curves, enhancing upper-tail fit and reducing uncertainties. Pacific Ocean ARs increase the 100-year flood magnitude by up to 345% in the West, Atlantic Ocean ARs amplify it by 400% in the East North Central, Caribbean Sea and Gulf of Mexico ARs raise it by 350% in the South, and Local Moisture increases it by 600% in the Southeast. These findings enhance flood risk management and climate adaptation strategies.
Core Outcome Set Development for Tension-Type Headache Treatment Using Traditional Chinese Medicine: Protocol for a Delphi Consensus Study
Authors: Fu Guojing , Chen Yunmeng , Liang Xiao , Guo Chunli , Fan Xueming , Gong Xiao , Chen Wenjie , Teng Jing , Tang Jun , Liao Xing , Wei Jingjing , Zhang Yunling 
Published: February 2025

Background
Tension-type headache (TTH) is the most common type of headache and the second most common health-related complaint among children and adults. Traditional Chinese medicine (TCM) offers unique therapeutic benefits in treating TTH. However, the lack of standardized evidence—such as inconsistencies in outcome selection and reporting in clinical studies, a lack of consensus on outcomes and measures, high risks of selective reporting bias, and missing data—has limited the development of robust evidence supporting the efficacy of TCM in treating TTH. Therefore, establishing a core outcome set (COS) is crucial for standardizing TCM clinical studies for TTH, thereby enhancing the quality and comparability of research findings.

Objective
This study aims to develop a COS for future clinical studies on the treatment of TTH with TCM.

Methods
The COS will be developed through the following 3 stages. First, systematic reviews and semistructured interviews will be conducted to identify potential essential outcomes, which will be evaluated by the steering committee to finalize a preliminary list of outcomes. Data will be processed using thematic analysis to ensure comprehensive coverage of relevant outcomes. Second, a 2-round Delphi survey will be conducted, inviting stakeholders, including health care experts and patients with tension-type headaches, to determine the importance of each outcome. Statistical analysis will be used to assess the level of consensus and prioritize outcomes based on predefined criteria. Third, a face-to-face consensus meeting will be held to finalize the COS and recommend measurement times for each outcome. Key outcomes will be interpreted based on their clinical relevance and feasibility of measurement, ensuring the COS is comprehensive and applicable in clinical settings.

Results
The protocol has been registered in PROSPERO, with the review commencing on October 1, 2024, and anticipated results by November 15, 2024. The systematic reviews will be finalized, followed by the Delphi survey and consensus conference in late 2024 and early 2025. The COS findings will be reported per COS-STAR (Core Outcome Set–STAndards for Reporting) guidelines, published in an international journal, presented at conferences, and disseminated to participants for clinical application.

Conclusions
This study is necessary as developing a COS for future TCM clinical studies in the treatment of TTH can maximize the value of data from individual trials and provide high-quality research evidence.

Trial Registration
Core Outcome Measures in Effectiveness Trials Initiative 1473; https://tinyurl.com/3ts62s2p

International Registered Report Identifier (IRRID)
PRR1-10.2196/63481
Bridging the Gap
Authors: Vissing Andrew , Verghese Priya S. , Dixon Angelina , Ghossein Cybele 
Published: February 2025

Key Points

Despite recommendations, many nephrology programs lack a structured transition clinic or transition protocol for young adults.There is a lack of coordination between partnered adult and pediatric programs to establish formal transition practices.Adult nephrology programs generally perceive a lower need for health care transition practices compared to pediatric nephrology programs.

Background
The transition from pediatric to adult care can be challenging for young adults living with kidney disease. The International Society of Nephrology recommends establishing a transition process for this vulnerable population. The prevalence of nephrology transition clinics and protocols in academic medical centers, however, is currently unknown.

Methods
General nephrology and transplant nephrology programs were surveyed at both pediatric and adult medical centers to explore the current state of nephrology transition practices. Programs without transition clinics were asked to identify obstacles preventing the establishment of a transition clinic.

Results
Overall, there were 488 programs targeted for survey distribution. There were 188 survey responses with an overall response rate of 39%. Only 20% of programs had a transition clinic, and 32% of programs reported neither having an established transition clinic nor a transition protocol. Adult programs were more likely to lack an established transition clinic or protocol compared with pediatric programs (42% versus 20%, P = 0.001). Of partnered pediatric and adult programs that both responded to the survey, 51% were discordant in their transition practices. For the 150 programs without a transition clinic, there were 119 comments regarding obstacles to the establishment of such a clinic. Resource and financial obstacles were mentioned most frequently (50% of comments). Adult programs were more likely to mention no perceived need or obstacles compared with pediatric programs (17% versus 4%, P = 0.04).

Conclusions
Despite guidelines recommending pediatric to adult transition programs for young adults with kidney disease, transition clinics remain uncommon. Although there are many cited barriers to the establishment of a nephrology transition clinic, our study highlights the lack of coordination and cooperation between adult and pediatric centers, which may stem from a lack of perceived need or interest from adult nephrology programs.
Application of Convolutional Neural Networks and Rolling Guidance Filter in Image Fusion for Detecting Brain Tumors
Authors: S. Karthikeyan  , P. Velmurugadass  
Published: February 2025

Medical image fusion is the technique of integrating images from several medical imaging modalities without causing any distortion or information loss. By preserving every feature in the fused image, it increases the value of medical imaging for the diagnosis and treatment of medical conditions. A novel fusion mechanism for multimodal image data sets is proposed in this paper. Each of the source image is smoothened using cross guided filter in the initial step. Guided filter output is further smoothened to remove fine structures using rolling guidance filter. Then details (high frequency) of each source image are extracted by subtracting the rolling guidance filter output from corresponding source image. These details are fed to convolutional neural networks to obtain decision maps. Finally the source images are fused based on decision map using maximum rule of combination. We assessed the performance of our suggested methodology using several pairs of medical imaging datasets that are accessible to the general public. According to the quantitative evaluation, the recommended fusion strategy for multimodal image fusion improves the average IE by 12.4%, MI by 41.8%, SF by 21.4%, SD by 22.81%, MSSIM by 31.1%, and by 39% when compared to existing methods, which makes it appropriate for use in the medical field for accurate diagnosis.