bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cancer-related pain in head and neck cancer survivors: longitudinal findings from the Head and Neck 5000 clinical cohort
Authors: Bolnykh Iakov , Patterson Joanne M , Harding Sam , Watson Laura-Jayne , Lu Liya , Hurley Katrina , Thomas Steve J , Sharp Linda 
Published: February 2024

Abstract
Purpose
Reports suggest pain is common in head and neck cancer (HNC). However, past studies are limited by small sample sizes and design and measurement heterogeneity. Using data from the Head and Neck 5000 longitudinal cohort, we investigated pain over a year post-diagnosis. We assessed: temporal trends; compared pain across HNC treatments, stages, sites and by HPV status; and identified subgroups of patients at increased risk of pain.

Methods
Sociodemographic and clinical data and patient-reported pain (measured by EORTC QLQ-C30 and QLQ-H&N35) were collected at baseline (pre-treatment), 4- and 12- months. Using mixed effects multivariable regression, we investigated time trends and identified associations between (i) clinically-important general pain and (ii) HN-specific pain and clinical, socio-economic, and demographic variables.

Results
2,870 patients were included. At baseline, 40.9% had clinically-important general pain, rising to 47.6% at 4-months and declining to 35.5% at 12-months. HN-specific pain followed a similar pattern (mean score (sd): baseline 26.4 (25.10); 4-months. 28.9 (26.55); 12-months, 17.2 (19.83)). Across time, general and HN-specific pain levels were increased in: younger patients, smokers, and those with depression and comorbidities at baseline, and more advanced, oral cavity and HPV negative cancers.

Conclusions
There is high prevalence of general pain in people living with HNC. We identified subgroups more often reporting general and HN-specific pain towards whom interventions could be targeted.

Implications for cancer survivors
Greater emphasis should be placed on identifying and treating pain in HNC. Systematic pain screening could help identify those who could benefit from an early pain management plan.
The Microphytobenthos are Abundant and Mediate Key Carbon Fluxes in Tropical Mangroves
Authors: Loo Yan Ping , Ouyang Xiaoguang , Lai Derrick Y. F. , Lee Shing Yip 
Published: February 2024

AbstractThe microphytobenthos (MPB) are known to play important ecological roles in estuarine ecosystems. While tidal flat MPB are widely studied, mangrove MPB are often overlooked due to the common belief that the light-limited environment under the mangrove canopy is not conducive to MPB growth. We assessed the biomass and community characteristics of the MPB in two contrasting mangrove forests (silty substrate and brackish influence versus sandy substrate and oceanic influence), their seasonal photosynthetic performance, as well as their role in mediating porewater carbon flux. Biomass measured as chlorophyll a concentration indicated that MPB abundance was equal, if not higher, in mangroves than on tidal flats. While mangrove sediments fostered an equally rich assemblage of MPB (estimated 23 to 45 genera) as the adjacent tidal flat, the MPB genus composition was different across all habitats, sites, and seasons, indicating the strong environmental influence on MPB assemblages. This study identified porewater salinity, temperature, and pH, as well as irradiance level and surface soil temperature to be accountable for 23.5% of this variation. MPB in all sampling locations were dominated by pennate diatoms, while cyanobacteria were common in the estuarine (as opposed to oceanic) site. Compared to tidal flat MPB, mangrove MPB exhibited photosynthetic performance characteristic of lower light acclimation. A mesocosm experiment using enriched stable isotopes of carbon and nitrogen indicated that a tight coupling exists between mangrove-derived carbon and MPB. Mangrove MPB are abundant and different from tidal flat MPB, and are functional photosynthetic entities with a regulatory role in nutrient cycling in mangrove ecosystems.
Gezondheidsapps voor patiënten met diabetes mellitus type 2: bruikbaar in de eerste lijn?
Authors: Smeijers Judith Johanna , Bults Marloes , den Ouden Marjolein Elisabeth Maria , Bekhuis Robin Enya Marije 
Published: February 2024

samenvattingInleidingEr zijn verschillende mobiele gezondheidsapps beschikbaar voor patiënten met diabetes mellitus type 2 (DMT2). In de huidige diabeteszorg worden deze apps beperkt ingezet door eerstelijnsprofessionals. In dit onderzoek zijn de attitude, barrières en technologiekwalificaties van eerstelijnsprofessionals ten aanzien van mobiele gezondheidsapps in kaart gebracht.MethodeIn een kwalitatief onderzoek zijn semigestructureerde interviews afgenomen bij twaalf eerstelijnsprofessionals. De gebruikte topiclijst was gebaseerd op het Enhanced Technology Acceptance Model en V-model. De data zijn met ATLAS.ti9 geanalyseerd via een thematische analyse (deductieve codering).ResultatenEerstelijnsprofessionals zien potentie in het gebruik van mHealth voor patiënten met DMT2. De meest door eerstelijnsprofessionals genoemde patiëntgerelateerde barrières zijn: hogere leeftijd van patiënten (> 65 jaar), het ontbreken van digitale vaardigheden en gebrek aan motivatie en kennis bij patiënten. Professionalgerelateerde barrières waren: gebrekkige/ontbrekende koppeling met het huisartsinformatiesysteem en beperkte tijd voor de professional om zich te verdiepen in mHealth. Eerstelijnsprofessionals vinden dat ze voldoende technologiekwalificaties bezitten om patiënten te vertellen en instrueren over mHealth. Hierbij is scholing van belang. Eerstelijnsprofessionals missen informatie om betrouwbare apps te vinden, en om veilig en vaardig met apps te werken.ConclusieEerstelijnsprofessionals hebben een positieve attitude ten aanzien van mHealth. Om mHealth in de huidige diabeteszorg te integreren, is het van belang dat professionals technologiekwalificaties ontwikkelen, er voldoende tijd beschikbaar is en er een koppeling is tussen mHealth en bestaande informatiesystemen.
Network pharmacology and molecular docking study of Ermiaosan (二妙散) in the treatment of ulcerative colitis with dampness-heat syndrome
Authors: Qu Ying , Li Shiying , Wu Weiming , Zhou Lu , Nie Guikuan , Zhang Tao , Zhang Shuxin 
Published: February 2024

Abstract
Objective
To study Ermiaosan in the treatment of UC by using network pharmacology and molecular docking, and to provide references for experiments and clinical application for treating UC with dampness-heat syndrome.

Methods
The main active chemical components of Ermiaosan were screened out through TCMSP, the targets of components were obtained from TCMSP, the SwissTargetPrediction, TTD and the DrugBank database, and these targets genes were retrieved by UniProt database, the disease genes were obtained from TTD and Genecard database. String tool was used to constructed the PPI network, to built these components and their corresponding targets, Cytoscape software was applied to merge the networks and screen out the core network. And Bioinformatic analysis was performed using the OECloud tools to explore the enrichment analyses of GO and KEGG. Molecular docking was applied to check the affinity between the components and selected targets.

Results
Forty-six main active components were predicted from Ermiaosan, and 408 intersection genes were screened from drug-disease genes. The enrichment included PI3K–Akt, TNF and HIF-1 signaling pathway, and the networks analysis showed that Ermiaosan acted on seven key targets AKT1, TNF, IL6,TP53, VEGFA, IL1B and CTNNB1 to play roles in treating UC. Molecular docking showed that top 3 chemical components could bind stably with these targets.

Conclusion
Ermiaosan can relieve dampness-heat syndrome of UC, the possible potential mechanism might be related to the targets AKT1, TNF, IL6,TP53, VEGFA, IL1B and CTNNB1 linked with TNF, PI3K-Akt, and HIF-1 signaling pathway, it will provide meaningful references for further study in experiments and clinical investigations.
Investigation of corrosion behavior of Al–TiO2 nanocomposite produced using air plasma spray and accumulative roll bonding method
Authors: Aminian Hamed , Borhani Ehsan , Mahmoudi Mohammad , Amouaghaei Omid , Shafyei Ali 
Published: February 2024

AbstractThis work is an attempt to study the Al–TiO2 nanocomposite properties applying accumulative roll bonding process. For this purpose, nano Titania powder was first coated on aluminum foil by air plasma spraying process. The nanocomposite was then fabricated in one, two, three, five, and seven cycles by ARB. To investigate the effect of ARB process cycles on an Al-5% wt. TiO2 nanocomposite, characterization tests including XRD, quantitative XRD analysis by MAUD software, FESEM, EDS, electrochemical impedance, and TAFEL polarization tests were performed on the samples. The results indicate that the crystallite size reduced from 156 to 31 nm and the dislocation density quadrupled in the composite. The results of XRD analysis showed an increase in the dislocation density in the composite when the number of cycles increases. The reduction of crystallite size and increase of the grain boundaries have caused a sudden increase in the dislocation density. As the ARB cycle increases, the local porosity decreases and the local cracks due to the separation of the titanium sprayed droplets disappear in the matrix phase, and the reinforcing phase has more diffusion in the matrix. With the increase of ARB cycles, the percentage of titanium and oxygen elements on the surface was decreasing, but they remained until the last cycle. Among the non-rolled and rolled samples in different cycles, ARBed samples after 1 cycle and 5 cycles had not only the lowest and highest corrosion current densities but also the highest and lowest total resistance (Rt), respectively. This indicates max corrosion resistance due to the decrease in defect and porosity resulting from plasma spray and min corrosion resistance as a result of formation of galvanic cell between Al-matrix and Ti-reinforcing particles, respectively.
Signalling overhead diminution in M-MIMO using NOMA transmission
Authors: Imran M. , Hayat O. , Ngah R. 
Published: February 2024

Abstract
With the increase in demand for mobile and Internet of Things devices, Orthogonal Multiple Access (OMA) cannot manage the maximum number of users. In this technique, the number of radio frequencies must be equivalent to the number of users. It causes to increase in signalling overhead. Therefore, it requires special attention to reduce the signalling overhead to escalate the spectral and energy efficiency. This paper investigates different Non Orthogonal Multiple Access (NOMA) techniques, and the results are compared with OMA techniques. A novel NOMA technique Multi User Shared Access (MUSA) is applied. It adjusts maximum users and has good spectral and energy efficiency compared to OMA techniques. In this proposed technique, maximum complex spreading codes are generated for the users and each user picks that code and transmits its data at the same radio frequency chain. The proposed scheme MUSA-NOMA has 12.8% more energy efficiency and 6.51% spectral efficiency compared to SCMA-NOMA and 32% more energy efficiency and 18.5% spectral efficiency compared to OMA.

Article highlights

Imagine you're using your phone in a crowded area where many people are also trying to connect, signalling congestion will occur. In traditional setups, it is difficult to manage everyone's signals.

Instead of dealing with each person's signal separately, NOMA allows the communication system to treat similar groups together, streamlining the process.

It's like having group discussions instead of one-on-one talks, making the whole communication setup more efficient and less complicated. This way, your phone and the network can handle many connections more smoothly, providing a better experience for everyone.
A fundamental concept for linking methods, system models, and specific models
Authors: Kranabitl Philipp , Faustmann Clemens , Bajzek Matthias , Kollegger Stefan , Hick Hannes 
Published: February 2024

AbstractIn the field of model-based development, and especially model-based systems engineering, the efficient and effective use of system models and specific models is of great interest. However, models strongly depend on the method they are linked to. Methods require models as input and associated models that are part of the method itself. Subsequent, methods are applied to adapt, enhance or generate output models. If a model is analyzed regarding its fidelity, level of detail, or maturity, only a combined consideration of methods and models in the development approach leads to a valid assessment. Therefore, the principle link of methods, system models, and specific models is defined and a concept for the application in product development is presented. It is stated, that a combined view on methods and models leads to improved accuracy of information interpretation and therefore optimizes efficiency and effectiveness during the product development.
Comparison between methacrylate copolymers and their magnetite nanocomposite as pour point depressant for lubricating base oil
Authors: El-Bahnasawi Alshaimaa H. , Albohy Salwa A. H. , El-Azabawy Olfat E. , El-Segaey Abeer A. , El-Koly Nagda G. , Al-Shafey Hussin I. 
Published: February 2024

AbstractA novel pour point depressant was synthesized by developing a polymeric nanocomposite using polymethacrylate and magnetite nanoparticles. The primary objective was to assess and compare the efficacy of PMA and PMA/Fe3O4 nanocomposite in reducing the gelation point, yield stress, apparent viscosity, and pour point of waxy crude oil. Extensive assessments were conducted to evaluate the performance of these additives. Rheometry tests were employed to measure the pour point of the lubricating oil pour point following the addition of PMA and PMA/Fe3O4 nanocomposite. The findings demonstrated a significant reduction in pour point, reaching values of − 18 °C, − 27 °C, − 24 °C, and − 36 °C for CP1, CP2, NP1, and NP2, respectively, at an optimal concentration of 10,000 ppm. Various characterization techniques such as Fourier Transform Infrared Spectrometer, Proton Nuclear Magnetic Resonance, X-ray Diffraction, Scanning Electron Microscope, Differential Scanning Calorimetry, Dynamic Light Scattering, Polarized Optical Microscope, and Gel Permeation Chromatography were utilized to analyze the polymers. Furthermore, the effectiveness of each polymer as a viscosity index improver (VII) and pour point depressant for mineral-based oil was evaluated. The mechanism of action of the polymers as pour point depressants was investigated through photomicrographic analysis. Additionally, the rheological properties of the formulated lubricant were assessed and reported. Thermogravimetric analysis was used to determine the thermal stability of the polymers, revealing that the copolymer nanocomposites exhibited higher thermal stability, viscosity index (VI), and molecular weights compared to the copolymers alone. These enhancements in thermal stability and molecular properties contributed to the improved pour point depressant (PPD) properties. Overall, the study successfully synthesized a novel pour point depressant and evaluated its performance using various tests and characterization techniques. The results demonstrated the effectiveness of the additives in reducing the pour point and improving the thermal stability of the lubricating oil.
Comprehensive modelling of prostate cancer progression: integrating continuous and binary biomarkers with event time data and missing covariates
Authors: Liaqat Madiha , Khan Rehan Ahmad , Kamal Shahid 
Published: February 2024

AbstractLongitudinal studies involve recording observations at scheduled visits or time points for individuals until a predetermined event, like reaching satisfactory tumor shrinkage in cancer studies. Furthermore, dropout in longitudinal studies leads to incomplete data, which significantly increases the risk of bias. An amended joint shared-random effects model (SREM) is proposed for mixed continuous and binary longitudinal measurements and a time-to-event (TTE) outcome, incorporating missing covariates. In the proposed model, a conditional model is applied for the mixed continuous and binary longitudinal outcomes; a mixed effect model is considered for the continuous longitudinal outcome. For the binary longitudinal outcome, given the continuous longitudinal outcome, a logistic mixed effect model is considered. These models share common random effects with the model for the event time outcome. The model formulation is based on Bayesian statistical thinking via Markov Chain Monte Carlo (MCMC). The proposed joint modelling is applied to contribute to the understanding of the progression of prostate cancer (PCa) by considering a generalized linear mixed effects model for time-varying covariates that incorporate ignorable missingness. The association between prostate-specific antigen (PSA) with alkaline phosphatase (ALP) and tumor status has been studied with mixed conclusions.
Political nomadism and the Jihadist ‘Safe Haven’ in northern Mali: an entry point through Tuareg relational political dynamics
Authors: Bencherif Adib 
Published: February 2024

ABSTRACTJihadist groups have found a ‘safe haven’ in northern Mali. They have managed this by operating strategically to establish themselves and to develop relationships with local communities, but characteristics of the environment have also facilitated their development and survival. In northern Mali, the political landscape is fragmented, and replete with competition between the central authority and various groups of local elites, who are themselves divided. I conceptualise this fluid environment as a context that incentivises ‘political nomadism’. Using the Tuareg communities as an entry point, I explore the complex dynamics between local and national political actors and jihadist groups in northern Mali. I argue that the jihadist ‘safe haven’ in northern Mali is highly relational and has been facilitated by the form of political nomadism practiced in the region since the 1990s. The article is based on eight months of fieldwork conducted between 2016 and 2017 in Mali and Niger.
A city-level dataset of heavy metal emissions into the atmosphere across China from 2015–2020
Authors: Dong Qi , Li Yue , Wei Xinhua , Jiao Le , Wu Lina , Dong Zexin , An Yi 
Published: February 2024

AbstractThe absence of nationwide distribution data regarding heavy metal emissions into the atmosphere poses a significant constraint in environmental research and public health assessment. In response to the critical data deficiency, we have established a dataset covering Cr, Cd, As, and Pb emissions into the atmosphere (HMEAs, unit: ton) across 367 municipalities in China. Initially, we collected HMEAs data and covariates such as industrial emissions, vehicle emissions, meteorological variables, among other ten indicators. Following this, nine machine learning models, including Linear Regression (LR), Ridge, Bayesian Ridge (Bayesian), K-Neighbors Regressor (KNN), MLP Regressor (MLP), Random Forest Regressor (RF), LGBM Regressor (LGBM), Lasso, and ElasticNet, were assessed using coefficient of determination (R2), root-mean-square error (RMSE) and Mean Absolute Error (MAE) on the testing dataset. RF and LGBM models were chosen, due to their favorable predictive performance (R2: 0.58–0.84, lower RMSE/MAE), confirming their robustness in modelling. This dataset serves as a valuable resource for informing environmental policies, monitoring air quality, conducting environmental assessments, and facilitating academic research.
Fermian guesstimation can boost the wisdom-of-the-inner-crowd
Authors: Gomilsek Tamara , Hoffrage Ulrich , Marewski Julian N. 
Published: February 2024

AbstractHow can people’s ability to make accurate estimations be boosted? Psychological research on the wisdom-of-the-inner-crowd suggests that people’s judgments improve when they use a simple consider-the-opposite-strategy, dubbed—inspired by Enlightenment philosopher Hegel—dialectical-bootstrapping: A person generates a first estimate (thesis), then rejects it and generates another one (anti-thesis), and finally integrates both (synthesis). Yet, the wisdom-of-the-inner-crowd-phenomenon comes with controversy concerning its measurement, robustness, and moderators. We (1) introduce a novel class of strategies to elicit the wisdom-of-the-inner-crowd. These strategies root in physics, where Nobel-laureate Enrico Fermi used back-of-the-envelope guesstimation, for instance, when assessing the explosive yield of the first tested nuclear bomb. Fermian strategies prescribe decomposing an estimation problem into subtasks, solving the subtasks separately, and ultimately integrating those solutions into a final estimate. In an experiment using a new task-environment, we find (2) that a similarity-based Fermian-strategy boosts the wisdom-of-the-inner-crowd even more than consider-the-opposite does, (3) that the provision of a memory aid differentially affects those two strategies’ performance, and (4) that data trimming matters. Moreover, and for the first time, we document (5) overprecision in wisdom-of-the-inner-crowd estimations. Finally, we (6) replicate previous results, including that the collective intelligence of two persons still outperforms asking oneself twice.
RNA as a component of scrapie fibrils
Authors: Bridges Leslie R. 
Published: February 2024

AbstractRecently, electron cryo-microscopy (cryo-EM) maps of fibrils from the brains of mice and hamsters with five infectious scrapie strains have been published and deposited in the electron microscopy data bank (EMDB). As noted by the primary authors, the fibrils contain a second component other than protein. The aim of the present study was to identify the nature of this second component in the published maps using an in silico approach. Extra densities (EDs) containing this component were continuous, straight, axial, at right angles to protein rungs and within hydrogen-bonding distance of protein, consistent with a structural role. EDs co-located with strips of basic residues, notably lysines, and formed a conspicuous cladding over parts of the N-terminal lobe of the protein. A Y-shaped polymer consistent with RNA was found, in places forming a single chain and at one location forming a duplex, comprising two antiparallel chains, and raising the intriguing possibility of replicative behaviour. To reflect the monotonous nature of the protein interface, it is suggested that the RNA may be a short tandem repeat. Fibrils from brains of patients with Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis and other neurodegenerations also contain EDs and may be of a similar aetiology.
Knocking out the LRRK2 gene increases sensitivity to wavelength information in rats
Authors: Østergaard Freja Gam 
Published: February 2024

AbstractLeucine-rich repeat kinase 2 (LRRK2) is a gene related to familial Parkinson’s disease (PD). It has been associated with nonmotor symptoms such as disturbances in the visual system affecting colour discrimination and contrast sensitivity. This study examined how deficiency of LRRK2 impacts visual processing in adult rats. Additionally, we investigated whether these changes can be modelled in wild-type rats by administering the LRRK2 inhibitor PFE360. Visual evoked potentials (VEPs) and steady-state visual evoked potentials (SSVEPs) were recorded in the visual cortex and superior colliculus of female LRRK2-knockout and wild-type rats to study how the innate absence of LRRK2 changes visual processing. Exposing the animals to stimulation at five different wavelengths revealed an interaction between genotype and the response to stimulation at different wavelengths. Differences in VEP amplitudes and latencies were robust and barely impacted by the presence of the LRRK2 inhibitor PFE360, suggesting a developmental effect. Taken together, these results indicate that alterations in visual processing were related to developmental deficiency of LRRK2 and not acute deficiency of LRRK2, indicating a role of LRRK2 in the functional development of the visual system and synaptic transmission.