bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lake depth, a key parameter regulating evaporation in semi‐arid regions: A case study from Dali Lake, China
Authors: Zhang Zhidong , Tang Qiuhong , Zhao Gang , Gaffney Paul P. J. , Dubois Nathalie 
Published: June 2024

AbstractAs climate change intensifies, understanding the dynamics of lake evaporation is imperative, especially in semi‐arid regions where water resources are already scarce. This study examines the regulatory role of lake depth on evaporation rates, focusing on a terminal lake in a semi‐arid region: Dali Lake in China. Using the Complementary Relationship Lake Evaporation model, we simulated the heat and temperature lag time of Dali Lake, an 8 m deep lake, due to its heat storage capacity. This approach was validated through moderate‐resolution imaging spectroradiometer (MODIS)‐based surface temperatures of Dali Lake and adjacent Ganggenor Lake. Dali Lake, by storing heat during the warmer months, maintains lower surface temperatures compared with the shallower Ganggenor Lake. Under the same climatic conditions, Dali Lake has an annual evaporation of 980 mm, which is 45 mm less than that of Ganggenor Lake, which has an annual evaporation of 1024 mm. To further study the impact of lake depth, we simulated the heat storage and evaporation of Dali Lake during the Holocene, when the lake reached up to 34 m average depth, representative of the maximum depth reached by Dali Lake. During the Holocene, under constant climate conditions, the annual evaporation would be 44 mm/year less than the average evaporation from 1984 to 2016. Average annual evaporation decreased with increasing depth, showing a significant reduction during warmer months, while the release of heat during the ice‐cover period did not result in additional evaporation. Our results highlight the important relationship between lake depth and evaporation under climate change, emphasizing the necessity for depth‐specific water management strategies in semi‐arid regions.
Optimizing live video streaming: Integrating 5G, IoT, and cloud computing with machine learning
Authors: Srinivasan L. , Nishat Humaira , Shargunam S. , Nayak Deepak Kumar , Janani K. 
Published: June 2024

AbstractIn this research, we optimize live video broadcast performance by incorporating advanced technologies such as 5G, the Internet of Things (IoT), and cloud computing. Our approach utilizes the Random Forest classifier to categorize data, achieving a 99% precision rate. A comparative study demonstrates that our proposed technique outperforms RCNN and Mask‐RCNN methods in optimizing video streaming efficacy. We show that our method efficiently enhances video streaming quality by integrating machine learning technologies. The combination of 5G, IoT, and cloud computing creates a robust environment for delivering optimized Live video streaming to users. This research underscores the importance of leveraging cutting‐edge technology to address optimization challenges in modern video streaming systems, focusing on the real‐time optimization of video streams in contemporary technological environments.
Starting high or low in English auctions? The case of frozen saithe in Norway
Authors: Sogn‐Grundvåg Geir , Zhang Dengjun , Asche Frank 
Published: June 2024

AbstractThis study investigates the role of starting prices in sequentially ascending (English) auctions. Applying binary logit and hedonic price models on a unique data set comprising 8217 auctioned lots of frozen saithe, an important species in Norwegian fisheries, we find support for three hypotheses; that low starting prices will lead to a higher share of successful auctions, a higher number of participating bidders, and higher final prices. These results indicate that starting prices in English auctions are important for both seller revenue and auction efficiency and are important with respect to strategic behavior in auction markets for food commodities.
Photobiomodulation minimizes taste changes during hematopoietic cell transplantation: A randomized clinical trial
Authors: Ferreira Mariana Henriques , Bezinelli Letícia Mello , de Paula Eduardo Fernanda , Pereira Andrea Z. , Hamerschlak Nelson , Corrêa Luciana 
Published: June 2024

AbstractPrevention and treatment protocols for taste changes observed during hematopoietic cell transplantation (HCT) are not well‐established. The purpose of this study was to assess the efficacy of photobiomodulation (PBM) in relieving taste changes and preventing lingual papillae atrophy. HCT patients received PBM (n = 42) on the tongue dorsum using an InGaAIP laser (660 nm, 100 mW, 1.1 W/cm2, 8.8 J/cm2). During the HCT conditioning (T0), severe neutropenia (T1), and after neutrophil engraftment (T2), taste acuity for sweet, bitter, sour, and salty solutions, and clinical appearance of lingual papillae were compared with those of a placebo group (n = 43). PBM significantly reduced hypogeusia, ageusia, and parageusia at T1 and T2, and also successfully prevented papillae atrophy during all the analyzed HCT periods. In conclusion, PBM enhanced taste acuity during HCT. The decrease in papillae atrophy indicated a potential regenerative effect of this therapy on tongue mucosa.
Computational modeling of revision total hip arthroplasty involving acetabular defects: A systematic review
Authors: Hopkins Daniel , Callary Stuart A. , Solomon L. B. , Woodford Sarah C. , Lee Peter V. S. , Ackland David C. 
Published: June 2024

AbstractRevision total hip arthroplasty (rTHA) involving acetabular defects is a complex procedure associated with lower rates of success than primary THA. Computational modeling has played a key role in surgical planning and prediction of postoperative outcomes following primary THA, but modeling applications in rTHA for acetabular defects remain poorly understood. This study aimed to systematically review the use of computational modeling in acetabular defect classification, implant selection and placement, implant design, and postoperative joint functional performance evaluation following rTHA involving acetabular defects. The databases of Web of Science, Scopus, Medline, Embase, Global Health and Central were searched. Fifty‐three relevant articles met the inclusion criteria, and their quality were evaluated using a modified Downs and Black evaluation criteria framework. Manual image segmentation from computed tomography scans, which is time consuming, remains the primary method used to generate 3D models of hip bone; however, statistical shape models, once developed, can be used to estimate pre‐defect anatomy rapidly. Finite element modeling, which has been used to estimate bone stresses and strains, and implant micromotion postoperatively, has played a key role in custom and off‐the‐shelf implant design, mitigation of stress shielding, and prediction of bone remodeling and implant stability. However, model validation is challenging and requires rigorous evaluation and comparison with respect to mid‐ to long‐term clinical outcomes. Development of fast, accurate methods to model acetabular defects, including statistical shape models and artificial neural networks, may ultimately improve uptake of and expand applications in modeling and simulation of rTHA for the research setting and clinic.
GLIM criteria validation and reliability in critically ill patients with cancer: A prospective study
Authors: Gersely Gabriela Delvaux , Klein Rafaela Camila Martins , da Rocha Gabriela Del Gallo Vieira , Bruzaca Wannia Ferreira de Sousa , Ribeiro Lia Mara Kauchi , Santos Bárbara Chaves , de Almeida Maria Manuela Ferreira Alves , Junior João Manoel Silva , Correia Maria Isabel Toulson Davisson , Waitzberg Dan Linetzky , Ozorio Gislaine Aparecida 
Published: June 2024

AbstractBackgroundThe present study aims to assess the interrater reliability of the Global Leadership Initiative on Malnutrition (GLIM) criteria, a framework to provide a consensus diagnosis of malnutrition. We also aimed to investigate its concurrent and predictive validity in the context of patients with cancer admitted to the intensive care unit (ICU).MethodsIndividuals aged ≥19 years with cancer who were admitted to the ICU within 48 h of their initial hospital admission were included. Nutrition status was assessed with the Nutritional Risk Screening 2002, the Subjective Global Assessment (SGA), and the GLIM criteria. Interrater reliability was assessed by the kappa test (>0.80). The SGA served as the established benchmark for assessing concurrent validity. To evaluate predictive validity, the occurrence of mortality within 30 days was the outcome, and Cox regression models were applied.ResultsA total of 212 patients were included: 66.9% were at nutrition risk, and 45.8% were malnourished according to the SGA. According to the GLIM criteria, 68.4% and 66% were identified as malnourished by evaluators 1 and 2, respectively (κ = 0.947; P < 0.001). The GLIM combination incorporating weight loss and the presence of inflammation exhibited sensitivity (82.4%) and specificity (92%). In the multivariate Cox regression models, most GLIM combinations emerged as independent predictors of complications.ConclusionThe GLIM criteria demonstrated satisfactory interrater reliability, and the combination involving weight loss and the presence of inflammation exhibited noteworthy sensitivity and specificity. Most GLIM combinations emerged as independent predictors of 30‐day mortality.
Structural Characteristics of Fibrillar Crystals in Uniaxially Stretched Isotactic Polypropylene Dominated by Temperature and Strain
Authors: Lin Hao , Guo Jiang , Huang Xiang , Jiang Shengbao , Xu Mengyi 
Published: June 2024

AbstractThe spherulitic morphology of isotactic polypropylene can be transformed into the oriented fibrillar morphology through hot stretching processes with varying temperature (Ts) or altering strain (εt). The effects of Ts and εt on the structural characteristics of fibrillar crystals are comprehensively investigated with respect to crystal orientation, long periodic spacing, lamellar thickness (Lc), crystallinity (Xc), melting point, and chain relaxation behavior. Small‐angle X‐ray scattering patterns illustrate that the fibrillar crystals consist of alternated stacks of crystalline lamellae and amorphous layers. High Ts leads to a low orientation degree of lamellae, whereas large εt facilitates a high orientation level. The Xc and mean Lc are improved continuously with the increasing of Ts or εt, indicating a stretching‐enhanced crystallization behavior driven by the two factors. The endothermic profiles reveal that new chain‐folded lamellae with relatively thinner thickness form during the hot stretching process. The formation of thinner lamellae is dominated by the melting–recrystallization mechanism. This work would provide guidance for optimizing process conditions to manipulate the microstructure of hot‐stretched semicrystalline polymers.
Soft Actuators and Actuation: Design, Synthesis, and Applications
Authors: Kalulu Mulenga , Chilikwazi Bright , Hu Jun , Fu Guodong 
Published: June 2024

AbstractSoft actuators are one of the most promising technological advancements with potential solutions to diverse fields’ day‐to‐day challenges. Soft actuators derived from hydrogel materials possess unique features such as flexibility, responsiveness to stimuli, and intricate deformations, making them ideal for soft robotics, artificial muscles, and biomedical applications. This review provides an overview of material composition and design techniques for hydrogel actuators, exploring 3D printing, photopolymerization, cross‐linking, and microfabrication methods for improved actuation. It examines applications of hydrogel actuators in biomedical, soft robotics, bioinspired systems, microfluidics, lab‐on‐a‐chip devices, and environmental, and energy systems. Finally, it discusses challenges, opportunities, advancements, and regulatory aspects related to hydrogel actuators.
Enhanced Microstructural Uniformity in Sulfuric‐Acid‐Treated Poly(3,4‐Ethylenedioxythiophene):Poly(Styrene Sulfonate) Films Using Raman Map Analysis
Authors: Kim Hyewon , Park Jiyeong , Jang Jaehee , Sasongko Nurwarrohman Andre , Heo Jaeseong , Lee Songyi , Kwak Kyungwon , Kee Seyoung , Park Myeongkee 
Published: June 2024

AbstractPoly(3,4‐ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) films have emerged as potential alternatives to indium–tin oxide as transparent electrodes in optoelectronic devices because of their superior transparency, flexibility, and chemical doping stability. However, pristine PEDOT:PSS films show low conductivities because the insulating PSS‐rich domains isolate the conductive PEDOT‐rich domains. In this study, the conductivities and corresponding spatially resolved Raman properties of PEDOT:PSS thin films treated with various concentrations of H2SO4 are presented. After the PEDOT:PSS films are treated with the H2SO4 solutions, their electrical conductivities are significantly improved from 0.5 (nontreated) to 4358 S cm−1 (100% v/v). Raman heat maps of the peak shifts and widths of the Cα═Cβ stretching mode are constructed. A blueshift and width decrease of the Cα═Cβ Raman mode in PEDOT are uniformly observed in the entire measurement area (20 × 20 µm2), indicating that microstructural transitions are successfully accomplished across the area from the coiled to linear conformation and high crystallinity upon H2SO4 treatment. Thus, it is proved that comprehensive Raman map analysis can be easily utilized to clarify microstructural properties distributed in large areas induced by various dopants. These results also offer valuable insights for evaluating and optimizing the performance of other conductive thin films.
Oxycodone or Higher Dose of Levodopa for the Treatment of Parkinsonian Central Pain: OXYDOPA Trial
Authors: Brefel‐Courbon Christine , Harroch Estelle , Marques Ana , Devos David , Thalamas Claire , Rousseau Vanessa , Ory‐Magne Fabienne , Fabbri Margherita , Maltête David , Rouaud Tiphaine , Drapier Sophie , Tir Melissa , Thobois Stephane , Salhi Hayet , Corvol Jean Christophe , Castelnovo Giovanni , Lagha‐Boukbiza Ouhaid , Fluchère Fréderique , Frismand Solene , Ansquer Solene , Sommet Agnes , Rascol Olivier 
Published: June 2024

AbstractBackgroundAmong the different types of pain related to Parkinson's disease (PD), parkinsonian central pain (PCP) is the most disabling.ObjectivesWe investigated the analgesic efficacy of two therapeutic strategies (opioid with oxycodone‐ prolonged‐release (PR) and higher dose of levodopa/benserazide) compared with placebo in patients with PCP.MethodsOXYDOPA was a randomized, double‐blind, double‐dummy, placebo‐controlled, multicenter parallel‐group trial run at 15 centers within the French NS‐Park network. PD patients with PCP (≥30 on the Visual Analogue Scale [VAS]) were randomly assigned to receive oxycodone‐PR (up to 40 mg/day), levodopa/benserazide (up to 200 mg/day) or matching placebo three times a day (tid) for 8 weeks at a stable dose, in add‐on to their current dopaminergic therapy. The primary endpoint was the change in average pain intensity over the previous week rated on VAS from baseline to week‐10 based on modified intention‐to‐treat analyses.ResultsBetween May 2016 and August 2020, 66 patients were randomized to oxycodone‐PR (n = 23), levodopa/benserazide (n = 20) or placebo (n = 23). The mean change in pain intensity was −17 ± 18.5 on oxycodone‐PR, −8.3 ± 11.1 on levodopa/benserazide, and −14.3 ± 18.9 in the placebo groups. The absolute difference versus placebo was −1.54 (97.5% confidence interval [CI], −17.0 to 13.90; P = 0.8) on oxycodone‐PR and +7.79 (97.5% CI, −4.99 to 20.58; P = 0.2) on levodopa/benserazide. Similar proportions of patients in each group experienced all‐cause adverse events. Those leading to study discontinuation were most frequently observed with oxycodone‐PR (39%) than levodopa/benserazide (5%) or placebo (15%).ConclusionsThe present trial failed to demonstrate the superiority of oxycodone‐PR or a higher dose of levodopa in patients with PCP, while oxycodone‐PR was poorly tolerated. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
FetoML: Interpretable predictions of the fetotoxicity of drugs based on machine learning approaches
Authors: Jeong Myeonghyeon , Yoo Sunyong 
Published: June 2024

AbstractPregnant females may use medications to manage health problems that develop during pregnancy or that they had prior to pregnancy. However, using medications during pregnancy has a potential risk to the fetus. Assessing the fetotoxicity of drugs is essential to ensure safe treatments, but the current process is challenged by ethical issues, time, and cost. Therefore, the need forin silicomodels to efficiently assess the fetotoxicity of drugs has recently emerged. Previous studies have proposed successful machine learning models for fetotoxicity prediction and even suggest molecular substructures that are possibly associated with fetotoxicity risks or protective effects. However, the interpretation of the decisions of the models on fetotoxicity prediction for each drug is still insufficient. This study constructed machine learning‐based models that can predict the fetotoxicity of drugs while providing explanations for the decisions. For this, permutation feature importance was used to identify the general features that the model made significant in predicting the fetotoxicity of drugs. In addition, features associated with fetotoxicity for each drug were analyzed using the attention mechanism. The predictive performance of all the constructed models was significantly high (AUROC: 0.854‐0.974, AUPR: 0.890‐0.975). Furthermore, we conducted literature reviews on the predicted important features and found that they were highly associated with fetotoxicity. We expect that our model will benefit fetotoxicity research by providing an evaluation of fetotoxicity risks for drugs or drug candidates, along with an interpretation of that prediction.
Prediction of adverse drug reactions due to genetic predisposition using deep neural networks
Authors: Dafniet Bryan , Taboureau Olivier 
Published: June 2024

AbstractDrug development is a long and costly process, often limited by the toxicity and adverse drug reactions (ADRs) caused by drug candidates. Even on the market, some drugs can cause strong ADRs that can vary depending on an individual polymorphism. The development of Genome‐wide association studies (GWAS) allowed the discovery of genetic variants of interest that may cause these effects. In this study, the objective was to investigate a deep learning approach to predict genetic variations potentially related to ADRs. We used single nucleotide polymorphisms (SNPs) information from dbSNP to create a network based on ADR‐drug‐target‐mutations and extracted matrixes of interaction to build deep Neural Networks (DNN) models. Considering only information about mutations known to impact drug efficacy and drug safety from PharmGKB and drug adverse reactions based on the MedDRA System Organ Classes (SOCs), these DNN models reached a balanced accuracy of 0.61 in average. Including molecular fingerprints representing structural features of the drugs did not improve the performance of the models. To our knowledge, this is the first model that exploits DNN to predict ADR‐drug‐target‐mutations. Although some improvements are suggested, these models can be of interest to analyze multiple compounds over all of the genes and polymorphisms information accessible and thus pave the way in precision medicine.
Nobiletin Protects Against Alcoholic Liver Disease in Mice via the BMAL1‐AKT‐Lipogenesis Pathway
Authors: Li Xudong , Zhuang Runxuan , Zhang Ke , Zhang Yuchun , Lu Zhitian , Wu Fan , Wu Xiaoli , Li Wenxue , Zhang Zheqing , Zhang Huijie , Zhu Wei , Zhang Bo 
Published: June 2024

ScopeAlcoholic liver disease (ALD) is a global public health concern. Nobiletin, a polymethoxyflavone abundant in citrus fruits, enhances circadian rhythms and ameliorates diet‐induced hepatic steatosis, but its influences on ALD are unknown. This study investigates the role of brain and muscle Arnt‐like protein‐1 (Bmal1), a key regulator of the circadian clock, in nobiletin‐alleviated ALD.Methods and resultsThis study uses chronic ethanol feeding plus an ethanol binge to establish ALD models in Bmal1flox/flox and Bmal1 liver‐specific knockout (Bmal1LKO) mice. Nobiletin mitigates ethanol‐induced liver injury (alanine aminotransferase [ALT]), glucose intolerance, hepatic apoptosis, and lipid deposition (triglyceride [TG], total cholesterol [TC]) in Bmal1flox/flox mice. Nobiletin fails to modulated liver injury (ALT, aspartate aminotransferase [AST]), apoptosis, and TG accumulation in Bmal1LKO mice. The expression of lipogenic genes (acetyl‐CoA carboxylase alpha [Acaca], fatty acid synthase [Fasn]) and fatty acid oxidative genes (carnitine pamitoyltransferase [Cpt1a], cytochrome P450, family 4, subfamily a, polypeptide 10 [Cyp4a10], and cytochrome P450, family4, subfamily a, polypeptide 14 [Cyp4a14]) is inhibited, and the expression of proapoptotic genes (Bcl2 inteacting mediator of cell death [Bim]) is enhanced by ethanol in Bmal1flox/flox mice. Nobiletin antagonizes the expression of these genes in Bmal1flox/flox mice and not in Bmal1LKO mice. Nobiletin activates protein kinase B (PKB, also known as AKT) phosphorylation, increases the levels of the carbohydrate response element binding protein (ChREBP), ACC1, and FASN, and reduces the level of sterol‐regulatory element binding protein 1 (SREBP1) and phosphorylation of ACC1 in a Bmal1‐dependent manner.ConclusionNobiletin alleviates ALD by increasing the expression of genes involved in fatty acid oxidation by increasing AKT phosphorylation and lipogenesis in a Bmal1‐dependent manner.
In situ alkali‐free growth of octahedral Ag2O nanoparticles by bacterial cellulose for efficient antibacterial application
Authors: Zhou Man , Cui Youfeng , Feng Qin , Wu Wangcheng , Zhou Yanli , Xu Song , Ma Hao , Lin Liwei , Li Zhongyu 
Published: June 2024

AbstractUniform octahedral Ag2O nanoparticles were in situ synthesized within natural bacterial cellulose (BC) films without any inorganic alkali. The morphological transformation of Ag2O from nanoparticles and small nanoplates to an octahedral structure was well controlled by varying the UV exposure time. To reduce and anchor Ag2O nanoparticles, abundant hydroxyl groups on the surface of natural BC fibers ensured an ideal environment for the mild redox reaction between Ag+ and –OH groups. The structural features and structure–activity relationship of Ag2O/BC films were confirmed through TEM, energy dispersive spectroscopy assisted SEM analysis, Fourier transform IR, X‐ray photoelectron spectroscopy, TGA and XRD. The structure–antibacterial activity relationship of the Ag2O/BC films was proved against both Gram‐positive (Staphylococcus aureus) and Gram‐negative (Escherichia coli) bacteria. They also showed excellent performance in the photocatalytic degradation of organic dyes. Ag2O/BC films have potential bactericidal applications in the field of pharmacy, specifically for wound dressing and flexible wearable materials. © 2024 Society of Chemical Industry.