bluuebunny/crossref_metadata_2025_split huggingface dataset:
Caffeine content in filter coffee brews as a function of degree of roast and extraction yield
Authors: Lindsey Zachary R. , Williams Joshua R. , Burgess James S. , Moore Nathan T. , Splichal Pierce M. 
Published: November 2024

AbstractThe effect of degree of roast on resulting caffeine content in brewed coffee has been extensively researched, but conflicting methodologies and results have muddled development of a general conclusion. In this study, 30 unique combinations of green coffee variety, degree of roast, and brew time were investigated regarding extraction yield and caffeine content. An AeroPress brewer was used to prepare brew samples using a 15:1 mass ratio of brew water to ground coffee. Refractometry and HPLC were respectively used to measure extraction yield and caffeine content of brewed samples. Scanning electron microscopy was used to measure porosity of roasted seeds and showed increasing porosity with the degree of roast. Extraction yields generally decreased for roast batches with roasting mass losses greater than $$\sim$$
∼
12–14%, and caffeine concentrations in 10-min brews decreased for roast batches with drop temperatures greater than $$\sim$$
∼
400–420 $$^{\circ }$$

∘

F. Under identical brewing conditions, caffeine concentrations in brewed samples were generally lower for dark roasts than light and medium roasts. However, at identical extraction yields, dark roasts generally exhibited higher caffeine concentrations than lighter roasted coffees. It is likely that the volatilization or decomposition of soluble compounds and increased porosity due to roasting act as competing mechanisms that determine compound concentrations in resulting brews.
Preparation and kinetic studies of a new antibacterial sodium alginate gelatin hydrogel composite
Authors: ElTatawy Reem A. , Ismail Amel M. , Ayoup Mohammed Salah , Ismail Magda M. F. , Fetouh Howida Abouel 
Published: November 2024

Abstract
This study involved synthesis of a novel antibacterial heterocyclic compound, sodium 2-(2-(3-phenyl-1, 2, 4-oxadiazol-5-yl) phenoxy) acetate abbreviated as Na-POPA. Further development of a biocompatible, pH-responsive hydrogel drug carrier prepared utilizing the natural polymers gelatin and sodium alginate. The compound loaded on the hydrogel represented new drug delivery system. Comprehensive characterization of Na-POPA was performed using Fourier-transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance (¹H NMR), carbon-13 nuclear magnetic resonance (¹³C NMR), and high-resolution mass spectrometry (HRMS). The compound was loaded onto the sodium alginate/gelatin hydrogel carrier under feasible experimental conditions. The successful incorporation of Na-POPA into the hydrogel matrix was confirmed via scanning electron microscopy (SEM), powder X-ray diffraction (pXRD) analysis and FT-IR spectroscopy. Cytotoxicity assays revealed that the all the loaded and unloaded compound induced cell toxicity at large concentration much lower than many reported results. The hydrogel reduced the inherent cytotoxicity of Na-POPA and enhanced its biocompatibility. The release kinetics of Na-POPA from the hydrogel were evaluated spectrophotometrically at different pH conditions simulating biological fluids. The release rate at pH 1.2 was greater than the release at pH 6.8, with a higher cumulative release observed at pH 6.8. The release kinetics obeyed the pseudo-second-order kinetic model, indicating a controlled release mechanism influenced by the hydrogel’s physicochemical properties. Electrochemical impedance spectroscopy and cyclic voltammetry further confirmed that the compound release was pH-dependent. The high swelling and solubility at pH 6.8 enhance the release. The larger amount released at 6.8 (target intestine) because of more solubility, leaching and swelling rather than shrinking.
Controlled layer-by-layer assembly and structured coloration of Ti3C2Tz MXene/polyelectrolyte heterostructures
Authors: Neal Natalie N. , Arole Kailash , Cao Huaixuan , Kotasthane Vrushali , Xiang Sisi , Ross Diego , Stevenson Peter R. , Radovic Miladin , Green Micah J. , Lutkenhaus Jodie L. 
Published: November 2024

AbstractStructural color arises from light scattering rather than organic pigments and can be found in Nature, such as in bird feathers and butterfly wings. Synthetic materials can mimic Nature by leveraging materials with contrasting optical characteristics by controlling each materials’ spatial arrangement in a heterostructure. Two-dimensional MXene nanosheets are particularly interesting due to their unique optical properties, but MXenes have not been used directly as a structural colorant because it is challenging to control the spatial placement of MXenes at the nanometer level. Here, we report the emergence of structural color in layer-by-layer (LbL) assemblies of Ti3C2Tz MXene nanosheets and polyelectrolyte heterostructures with controlled block thicknesses. The block thickness and spatial placement of MXene are controlled by the assembly’s salt concentration and number of layer pairs. This work demonstrates that optical characteristics of MXene/polyelectrolyte heterostructures depend on MXene content and placement, while deepening the understanding of MXenes within structural color films.
Spatial resolution enhancement using deep learning improves chest disease diagnosis based on thick slice CT
Authors: Yu Pengxin , Zhang Haoyue , Wang Dawei , Zhang Rongguo , Deng Mei , Yang Haoyu , Wu Lijun , Liu Xiaoxu , Oh Andrea S. , Abtin Fereidoun G. , Prosper Ashley E. , Ruchalski Kathleen , Wang Nana , Zhang Huairong , Li Ye , Lv Xinna , Liu Min , Zhao Shaohong , Li Dasheng , Hoffman John M. , Aberle Denise R. , Liang Chaoyang , Qi Shouliang , Arnold Corey 
Published: November 2024

AbstractCT is crucial for diagnosing chest diseases, with image quality affected by spatial resolution. Thick-slice CT remains prevalent in practice due to cost considerations, yet its coarse spatial resolution may hinder accurate diagnoses. Our multicenter study develops a deep learning synthetic model with Convolutional-Transformer hybrid encoder-decoder architecture for generating thin-slice CT from thick-slice CT on a single center (1576 participants) and access the synthetic CT on three cross-regional centers (1228 participants). The qualitative image quality of synthetic and real thin-slice CT is comparable (p = 0.16). Four radiologists’ accuracy in diagnosing community-acquired pneumonia using synthetic thin-slice CT surpasses thick-slice CT (p < 0.05), and matches real thin-slice CT (p > 0.99). For lung nodule detection, sensitivity with thin-slice CT outperforms thick-slice CT (p < 0.001) and comparable to real thin-slice CT (p > 0.05). These findings indicate the potential of our model to generate high-quality synthetic thin-slice CT as a practical alternative when real thin-slice CT is preferred but unavailable.
Allosteric substrate release by a sialic acid TRAP transporter substrate binding protein
Authors: Schneberger Niels , Hendricks Philipp , Peter Martin F. , Gehrke Erik , Binder Sophie C. , Koenig Paul-Albert , Menzel Stephan , Thomas Gavin H. , Hagelueken Gregor 
Published: November 2024

AbstractThe tripartite ATP-independent periplasmic (TRAP) transporters enable Vibrio cholerae and Haemophilus influenzae to acquire sialic acid, aiding their colonization of human hosts. This process depends on SiaP, a substrate-binding protein (SBP) that captures and delivers sialic acid to the transporter. We identified 11 nanobodies that bind specifically to the SiaP proteins from H. influenzae (HiSiaP) and V. cholerae (VcSiaP). Two nanobodies inhibited sialic acid binding. Detailed structural and biophysical studies of one nanobody-SBP complex revealed an allosteric inhibition mechanism, preventing ligand binding and releasing pre-bound sialic acid. A hydrophobic surface pocket of the SBP is crucial for the allosteric mechanism and for the conformational rearrangement that occurs upon binding of sialic acid to the SBP. Our findings provide new clues regarding the mechanism of TRAP transporters, as well as potential starting points for novel drug design approaches to starve these human pathogens of important host-derived molecules.
Conserved glucokinase regulation in zebrafish confirms therapeutic utility for pharmacologic modulation in diabetes
Authors: Schmitner Nicole , Thumer Sophie , Regele Dominik , Mayer Elena , Bergerweiss Ines , Helker Christian , Stainier Didier Y. R. , Meyer Dirk , Kimmel Robin A. 
Published: November 2024

AbstractGlucokinase (GCK) is an essential enzyme for blood glucose homeostasis. Because of its importance in glucose metabolism, GCK is considered an attractive target for the development of antidiabetic drugs. However, a viable therapeutic agent has still to emerge, prompting efforts to improve understanding of the complex regulation and biological effects of GCK. Using the vertebrate organism zebrafish, an attractive model to study metabolic diseases and pharmacological responses, we dissected the complexities of gck regulation and unraveled effects of Gck modulation. We found that while gck expression in zebrafish islet cells is constitutive, gck expression in the liver is regulated by nutritional status, confirming similarity to the mammalian system. A combination of transgenic gck reporter lines and our diabetes model, the pdx1 mutant, allowed monitoring of gck expression under pathological conditions, revealing reduced gck expression and activity in the liver, which was unresponsive to nutrient stimulation, and decreased expression in the islet due to the reduced number of β-cells. Gck activation substantially ameliorated hyperglycemia in pdx1 mutants, without inducing oxidative stress responses in liver or islet. In-depth characterization of Gck activity and regulation at the cellular level in a whole-organism diabetes model clarifies its applicability as a drug target for therapies.
Ultra-lightweight rechargeable battery with enhanced gravimetric energy densities >750 Wh kg−1 in lithium–sulfur pouch cell
Authors: Kakiage Kenji , Yano Toru , Uehara Hiroki , Kakiage Masaki 
Published: November 2024

AbstractLithium–sulfur (Li–S) rechargeable batteries have been expected to be lightweight energy storage devices with the highest gravimetric energy density at the single-cell level reaching up to 695 Wh kg(cell)−1, having also an ultralow rate of 0.005 C only in the first discharge. Sulfurized polyacrylonitrile (SPAN) is one of the sulfur-based active materials, which allows more freedom in the Li–S cell design because it shows no undesirable reactions with electrolyte solutions. Here we present an original Li–S pouch cell construction, ADEKA’s Lithium–Sulfur/Pouch Cell (ALIS-PC). It is an ultra-lightweight rechargeable battery cell, which is designed by combining the SPAN cathode and effective ten technologies involving chemical engineering. As a result, the highest gravimetric energy densities of 713 and 761 Wh kg(cell)−1 after some charge-and-discharge cycles, which were based on the total mass of all cell components, were achieved with successful operating at 0.1 and 0.05C-rates, respectively, significantly exceeding those of commercial lithium-ion and next-generation rechargeable batteries in development.
Insights into durability against resistance from the antibiotic nitrofurantoin
Authors: Kettlewell Riannah , Jones Charlotte , Felton Timothy W. , Lagator Mato , Gifford Danna R. 
Published: November 2024

AbstractNitrofurantoin has shown exceptional durability against resistance over 70 years of use. This longevity stems from factors such as rapid achievement of therapeutic concentrations, multiple physiological targets against bacteria, low risk of horizontal gene transfer, and the need to acquire multiple mutations to achieve resistance. These combined features limit resistance emergence and spread of nitrofurantoin resistance. We propose nitrofurantoin as an exemplar for developing other durable treatments.
Policy options for sustainable access to off-patent antibiotics in Europe
Authors: Panteli Dimitra , Anderson Michael , Fieldman Thomas , Baraldi Enrico , Tängdén Thomas , Vogler Sabine , Årdal Christine , Mossialos Elias 
Published: November 2024

AbstractSecuring sustainable access to existing antibiotics optimises agent choice for individual treatments and is crucial to curb antibiotic resistance. Access to antibiotics is often restricted in many countries, due to general market unavailability or episodic shortages. This article outlines key policy options to maintain availability of existing antibiotics and enhance antibiotic supply chain resilience focusing on the perspectives of European Union (EU) and European Economic Area (EEA) institutions and member states.
Domain‐adaptation‐based named entity recognition with information enrichment for equipment fault knowledge graph
Authors: Xiong Dengrui , Li Xinyu , Gao Liang , Gao Yiping 
Published: November 2024

AbstractNumerous files, such as records and logs, are generated in the process of equipment diagnosis and maintenance (D&M). These files contain lots of unstructured plain text. Knowledge in these files could be reused for similar equipment faults. In practice, knowledge presented in plain text is hard to acquire. Thus, automated named entity recognition (NER) and relation extraction (RE) methods based on pretrained encoders could be used to extract entities and relations and develop a structured knowledge graph (KG), thus facilitating intelligent manufacturing. However, equipment fault NER exhibits suboptimal performance with existing encoders pretrained on general‐domain corpus. In this paper, domain‐adaptation‐based NER with information enrichment is proposed for developing an equipment fault KG. A domain‐adapted encoder is tailored for equipment fault NER through domain‐adaptive pretraining (DAPT). Update of word segmentation dictionary and adjustment of masking approach are implemented during DAPT for information enrichment, which helps make the most of the limited domain‐specific pretraining corpus. Experimental results show that the F1 score of NER is improved by 1.22% using the domain‐adapted encoder compared to its counterpart using the encoder pretrained on general‐domain corpus. Furthermore, a reliable and robust question answering (QA) application of the developed equipment fault KG is also shown.
Efficient class‐agnostic obstacle detection for UAV‐assisted waterway inspection systems
Authors: Alonso Pablo , Íñiguez de Gordoa Jon Ander , Ortega Juan Diego , Nieto Marcos 
Published: November 2024

AbstractEnsuring the safety of water airport runways is essential for the correct operation of seaplane flights. Among other tasks, airport operators must identify and remove various objects that may have drifted into the runway area. In this paper, the authors propose a complete and embedded‐friendly waterway obstacle detection pipeline that runs on a camera‐equipped drone. This system uses a class‐agnostic version of the YOLOv7 detector, which is capable of detecting objects regardless of its class. Additionally, through the usage of the GPS data of the drone and camera parameters, the location of the objects are pinpointed with 0.58 m Distance Root Mean Square. In our own annotated dataset, the system is capable of generating alerts for detected objects with a recall of 0.833 and a precision of 1.
An efficient hybrid algorithm based on particle swarm optimisation and teaching‐learning‐based optimisation for parameter estimation of photovoltaic models
Authors: Wang Dianlang , Qiu Zhongrui , Yin Qi , Wang Haifeng , Chen Jing , Zeng Chengbi 
Published: November 2024

AbstractIn recent years, many meta‐heuristic algorithms have been investigated to estimate the parameters of photovoltaic (PV) models. However, the accuracy of the estimated parameters still needs to be concerned, especially for some complex PV models with many unknown parameters. In order to estimate the unknown parameters of the PV models more precisely and reliably, an efficient hybrid algorithm based on particle swarm optimisation and teaching‐learning‐based optimisation (PSOTLBO) is proposed in this paper. In PSOTLBO, inspired by the learner phase of teaching‐learning‐based optimisation (TLBO), an improved learner phase is designed and introduced into the basic PSO to enhance the global search ability and the ability to get rid of local optimum. The improved learner phase divides the population into four groups according to three values, which are the average fitness values of the overall population, the population in the first half of the fitness ranking and the population in the second half of the fitness ranking. Typically, each group has its particular movement pattern concentrating on exploration or exploitation respectively to improve the search efficiency of the algorithm. Furthermore, to deal with individuals beyond the boundary, a new designed probabilistic rebound strategy is introduced, which increases the diversity of population and avoids population aggregation at the search boundary. Then, the proposed PSOTLBO is applied to estimate the parameters of the single diode model, double diode model and PV module model. The comparative results between PSOTLBO and other 14 advanced algorithms show that the average root mean square error values of different PV models obtained by PSOTLBO are 9.86021878E−04, 9.82630511E−04, 2.42507487E−03, 1.72981371E−03, and 1.66006031E−02, respectively, which indicate that PSOTLBO can provide more accurate and stable parameter estimation results than other compared algorithms. Furthermore, the convergence experimental results demonstrate that PSOTLBO has outstanding performance in convergence speed and stability.
Prediction of the Survival Status, Immunotherapy Response, and
Medication of Lung Adenocarcinoma Patients Based on Hypoxia- and
Apoptosis-Related Genes
Authors: Shi Ziliang , Sang Zi , Xiao Junmeng , Hou Jianbin , Geng Mingfei 
Published: November 2024

AbstractTo predict patient survival prognosis, we aimed to establish a novel set of gene
features associated with hypoxia and apoptosis. RNA-seq and clinical data of
LUAD were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression
Omnibus (GEO) databases, while hypoxia and apoptosis-related genes were obtained
from the Molecular Signatures Database (MsigDB). A 13-gene-prognostic model
incorporating hypoxia and apoptosis genes was developed using
univariate/multivariate Cox regression, Nonnegative Matrix Factorization (NMF)
clustering, and LASSO regression. Patients were divided into high-risk (HR) and
low-risk (LR) groups according to the median risk score. Gene Ontology (GO) and
Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed
distinct biological processes between HR and LR groups, including hormone
regulation and lipid metabolism pathways. Single sample gene set enrichment
analysis (ssGSEA) indicated elevated cell infiltration levels of Neutrophils and
T_helper_cells in the LR group, while NK cells and Th1cells were higher in the
HR group. Immunophenoscore (IPS) and tumor immune dysfunction and exclusion
(TIDE) analyses suggested potential benefits of immunotherapy for LR group
patients. In conclusion, this prognostic feature integrating hypoxia- and
apoptosis-related genes offers insights into predicting survival, immune status,
and treatment response in LUAD patients, paving the way for personalized
treatment strategies.
The rare reason for massive lactic aciduria and mitochondrial
disorders: combined oxidative phosphorylation deficiency type 23
(COXPD23)
Authors: Akar Halil Tuna , Akduman Hasan , Kolkıran Abdülkerim , Taşadelen Elifcan , Aycan Nur 
Published: November 2024

AbstractMitochondrial respiratory chain dysfunction and impaired oxidative
phosphorylation are rare but significant causes of mitochondrial diseases in
children, presenting with diverse clinical features. Combined oxidative
phosphorylation deficiency type 23 (COXPD23), an autosomal recessive disorder
due to GTPBP3 gene mutations, typically manifests as lactic acidosis,
hypertrophic cardiomyopathy, and encephalopathy. This case report describes a
male infant born at 35 weeks gestation, who exhibited severe lactic aciduria and
hypotonia but no cardiomyopathy, which is atypical for COXPD23. Genetic analysis
revealed a novel homozygous missense variant in the GTPBP3 gene. Despite
intensive metabolic and supportive treatments, the patientʼs condition worsened,
leading to death on the 23rd day. This case emphasizes the need to consider
mitochondrial cytopathies in neonates with persistent metabolic acidosis and
hyperlactatemia and highlights the importance of early genetic screening for
accurate diagnosis and management.
Contilistat, a New Multitarget Small Polyfunctionalized Indole Derivative
Authors: Hansen Finn K. , Marco-Contelles José , Toledano-Pinedo Mireia , Diez-Iriepa Daniel , Porro-Pérez Alicia , Schäker-Hübner Linda , Hanl Maria , Samadi Abdelouahid , Almendros Pedro , Iriepa Isabel , Rodríguez-Fernández M. Mercedes , Griñán-Ferré Christian , Siwek Agata , Wolak Małgorzata , Satała Grzegorz , Bojarski Andrzej J. , Doroż-Płonka Agata , Handzlik Jadwiga , Godyń Justyna , Knez Damijan , Gobec Stanislav , Więckowska Anna 
Published: November 2024

AbstractWe describe the design, synthesis, and in vitro biological evaluation of contilistat, a novel polyfunctionalized indole derivative designed as a hybrid of contilisant and vorinostat containing key pharmacophoric groups of both parent ligands.
Analysis of circularity metrology of small cylindrical workpiece with a segmenting scan method
Authors: Li Qiaolin , Zeng Chuang , Zhao Jiali , Wu Dan , Zhang Liang 
Published: November 2024

Owing to eccentricity and inclination, circularity of a cylindrical workpiece cannot be measured precisely by a circularity measuring machine when the workpiece has a small dimension (diameter ≤ 3 mm). In this paper, with the aim of solving this problem, circularity metrology of a small cylindrical workpiece using a segmenting scanning method is analyzed. The cross-sectional circle of the cylinder is segmented into several equivalent arcs for measurement by a two-dimensional coordinate measuring machine (profilometer). The circularity contour is obtained by stitching together arc contours obtained by data processing of the coordinates. Different segmenting patterns for coordinate scanning are considered. Measurement results are presented for three segmentation patterns, with 8, 10, and 12 equal segments, respectively. These results are evaluated in terms of the matching coefficient between neighboring arc contours on circumferential stitching, the Euclidean distance between neighboring arc contours on radial stitching, and the curvature of the arcs. From these evaluations, it is found that as the number of segments is increased, the matching coefficient increases from 0.14 to 0.50, the Euclidean distance decreases from 32 nm to 26 nm, and the curvature becomes close to the standard value.