bluuebunny/crossref_metadata_2025_split huggingface dataset:
Treatment of bone‐cartilage defects with dual‐layer tissue‐engineered scaffolds loaded with icariin and quercetin
Authors: Dai Guoda , Xu Chen , Han Baoguo , Wang Zhichen , Cai Jianpin , You Wulin , Zhang Yafeng 
Published: July 2024

AbstractOver the past few decades, significant research has been conducted on tissue‐engineered constructs for cartilage repair. However, there is a growing interest in addressing subchondral bone repair along with cartilage regeneration. This study focuses on a bilayer tissue engineering scaffold loaded with icariin (ICA) and quercetin (QU) for simultaneous treatment of knee joint cartilage and subchondral bone defects. The cytotoxicity of dual‐layer scaffolds loaded with ICA and QU was assessed through live/dead cell staining. Subsequently, these dual‐layer scaffolds loaded with ICA and QU were implanted into cartilage and subchondral bone defects in Sprague–Dawley (SD) rats. The repair effects were evaluated through macroscopic observation, computed tomography, and immunohistochemistry. After 12 weeks of implantation of dual‐layer scaffolds loaded with ICA and QU into the cartilage and bone defects of SD rats, better repair effects were observed in both cartilage and bone defects compared to the blank control group. We found that the dual‐layer tissue‐engineered scaffold loaded with ICA and QU had excellent biocompatibility and could effectively repair articular cartilage and subchondral bone injuries, showing promising prospects for clinical applications.
Amino acid metabolic reprogramming in the tumor microenvironment and its implication for cancer therapy
Authors: Zhang Jiarong , Chen Mingjian , Yang Yuxin , Liu Ziqi , Guo Wanni , Xiang Pingjuan , Zeng Zhaoyang , Wang Dan , Xiong Wei 
Published: July 2024

AbstractAmino acids are essential building blocks for proteins, crucial energy sources for cell survival, and key signaling molecules supporting the resistant growth of tumor cells. In tumor cells, amino acid metabolic reprogramming is characterized by the enhanced uptake of amino acids as well as their aberrant synthesis, breakdown, and transport, leading to immune evasion and malignant progression of tumor cells. This article reviews the altered amino acid metabolism in tumor cells and its impact on tumor microenvironment, and also provides an overview of the current clinical applications of amino acid metabolism. Innovative drugs targeting amino acid metabolism hold great promise for precision and personalized cancer therapy.
Gene expression differences associated with intrinsic hindfoot muscle loss in the jerboa, Jaculus jaculus
Authors: Tran Mai P. , Ochoa Reyes Daniel , Weitzel Alexander J. , Saxena Aditya , Hiller Michael , Cooper Kimberly L. 
Published: July 2024

AbstractVertebrate animals that run or jump across sparsely vegetated habitats, such as horses and jerboas, have reduced the number of distal limb bones, and many have lost most or all distal limb muscle. We previously showed that nascent muscles are present in the jerboa hindfoot at birth and that these myofibers are rapidly and completely lost soon after by a process that shares features with pathological skeletal muscle atrophy. Here, we apply an intra‐ and interspecies differential RNA‐Seq approach, comparing jerboa and mouse muscles, to identify gene expression differences associated with the initiation and progression of jerboa hindfoot muscle loss. We show evidence for reduced hepatocyte growth factor and fibroblast growth factor signaling and an imbalance in nitric oxide signaling; all are pathways that are necessary for skeletal muscle development and regeneration. We also find evidence for phagosome formation, which hints at how myofibers may be removed by autophagy or by nonprofessional phagocytes without evidence for cell death or immune cell activation. Last, we show significant overlap between genes associated with jerboa hindfoot muscle loss and genes that are differentially expressed in a variety of human muscle pathologies and rodent models of muscle loss disorders. All together, these data provide molecular insight into the process of evolutionary and developmental muscle loss in jerboa hindfeet.
Advanced Myocardial MRI Tissue Characterization Combining Contrast Agent‐Free T1‐Rho Mapping With Fully Automated Analysis
Authors: de Villedon de Naide Victor , Narceau Kalvin , Ozenne Valery , Villegas‐Martinez Manuel , Nogues Victor , Brillet Nina , Huiyue Zhang Jana , Benlala Ilyes , Stuber Matthias , Cochet Hubert , Bustin Aurélien 
Published: July 2024

BackgroundMyocardial T1‐rho (T1ρ) mapping is a promising method for identifying and quantifying myocardial injuries without contrast agents, but its clinical use is hindered by the lack of dedicated analysis tools.PurposeTo explore the feasibility of clinically integrated artificial intelligence‐driven analysis for efficient and automated myocardial T1ρ mapping.Study TypeRetrospective.PopulationFive hundred seventy‐three patients divided into a training (N = 500) and a test set (N = 73) including ischemic and nonischemic cases.Field Strength/SequenceSingle‐shot bSSFP T1ρ mapping sequence at 1.5 T.AssessmentThe automated process included: left ventricular (LV) wall segmentation, right ventricular insertion point detection and creation of a 16‐segment model for segmental T1ρ value analysis. Two radiologists (20 and 7 years of MRI experience) provided ground truth annotations. Interobserver variability and segmentation quality were assessed using the Dice coefficient with manual segmentation as reference standard. Global and segmental T1ρ values were compared. Processing times were measured.Statistical TestsIntraclass correlation coefficients (ICCs) and Bland–Altman analysis (bias ±2SD); Paired Student's t‐tests and one‐way ANOVA. A P value <0.05 was considered significant.ResultsThe automated approach significantly reduced processing time (3 seconds vs. 1 minute 51 seconds ± 22 seconds). In the test set, automated LV wall segmentation closely matched manual results (Dice 81.9% ± 9.0) and closely aligned with interobserver segmentation (Dice 82.2% ± 6.5). Excellent ICCs were achieved on a patient basis (0.94 [95% CI: 0.91 to 0.96]) with bias of −0.93 cm2 ± 6.60. There was no significant difference in global T1ρ values between manual (54.9 msec ± 4.6; 95% CI: 53.8 to 56.0 msec, range: 46.6–70.9 msec) and automated processing (55.4 msec ± 5.1; 95% CI: 54.2 to 56.6 msec; range: 46.4–75.1 msec; P = 0.099). The pipeline demonstrated a high level of agreement with manual‐derived T1ρ values at the patient level (ICC = 0.85; bias +0.52 msec ± 5.18). No significant differences in myocardial T1ρ values were found between methods across the 16 segments (P = 0.75).Data ConclusionAutomated myocardial T1ρ mapping shows promise for the rapid and noninvasive assessment of heart disease.Evidence Level3Technical EfficacyStage 1
Integrated serum proteomic and N‐glycoproteomic characterization of dengue patients
Authors: Hu Xiao , Song Jiamin , Ye Guoguo , Zhu Miao , Lan Jianfeng , Zeng Lijiao , Ke Zhiyi , Yuan Jing 
Published: July 2024

AbstractDengue fever is a mosquito‐borne viral disease caused by the dengue virus (DENV). It poses a public health threat globally and, while most people with dengue have mild symptoms or are asymptomatic, approximately 5% of affected individuals develop severe disease and need hospital care. However, knowledge of the molecular mechanisms underlying dengue infection and the interaction between the virus and its host remains limited. In the present study, we performed a quantitative proteomic and N‐glycoproteomic analysis of serum from 19 patients with dengue and 11 healthy people. The results revealed distinct proteomic and N‐glycoproteomic landscapes between the two groups. Notably, we report for the first time the changes in the serum N glycosylation pattern following dengue infection and provide abundant information on glycoproteins, glycosylation sites, and intact N‐glycopeptides using recently developed site‐specific glycoproteomic approaches. Furthermore, a series of key functional pathways in proteomic and N‐glycoproteomic were identified. Collectively, our findings significantly improve understanding of host and DENV interactions and the general pathogenesis and pathology of DENV, laying a foundation for functional studies of glycosylation and glycan structures in dengue infection.
Evaluation of soluble co‐inhibitors and co‐stimulators levels of the immune response in gastric cancer
Authors: da Silva Luciana Mata , Martins Mário Rino , dos Santos Rogerio Luiz , Da Silva Jeronimo Paulo Assis , Lima Cecilia Araujo Carneiro , Forones Nora Manoukian , Torres Leuridan Cavalcante 
Published: July 2024

AbstractBackgroundCo‐inhibitor and co‐stimulator mediators trigger actions that result in immunological homeostasis and are being evaluated as potential therapeutic targets in gastric cancer (GC).ObjectiveTo evaluate the soluble levels of sPD‐1, sPD‐L1, sPD‐L2, sTIM‐3, sGal9, sGITR, and sGITRL in GC patients.MethodsThe cross‐sectional study was carried out at the Hospital de Cancer de Pernambuco, Brazil between 2017 and 2018. A total of 74 GC patients and 30 healthy controls were included.ResultsLow levels of sPD1 (p = 0.0179), sPDL2 (p = 0.0003), and sGal9 (p < 0.0001), and higher levels of sPDL1 (p = 0.004), sTIM‐3 (p = 0.0072), sGITR (p = 0.0179), and sGITRL (p = 0.0055) compared to the control group. High sPD‐1, sTIM‐3, and sGal9 levels in stage IV compared I/II and III (p < 0.05). High sPDL1, sGal9, and sGITRL levels in esophagogastric junction compared to body and Pylorus/Antrum groups (p < 0.05). No significant differences were observed in sPD1, sPDL1, sPDL2, sTIM3, sGal9, sGITR, and sGITRL levels between the intestinal, diffuse, and mixed GC groups. Low sGITR levels in GC patients who died within the first 24 months compared to the who survived (p = 0.0332).ConclusionsThere is an association of sPD1, sTIM‐3, and sGal9 with disease progression and sGITR with death, these mediators may be potential prognostic biomarkers in GC.
Simulation and experimental benchmarking of a proton pencil beam scanning nozzle model for development of MR‐integrated proton therapy
Authors: Oborn Bradley M. , Semioshkina Ekaterina , van der Kraaij Erik , Hoffmann Aswin L. 
Published: July 2024

AbstractBackgroundMR‐integrated proton therapy is under development. It consists of the unique challenge of integrating a proton pencil beam scanning (PBS) beam line nozzle with an magnetic resonance imaging (MRI) scanner. The magnetic interaction between these two components is deemed high risk as the MR images can be degraded if there is cross‐talk during beam delivery and image acquisition.PurposeTo create and benchmark a self‐consistent proton PBS nozzle model for empowering the next stages of MR‐integrated proton therapy development, namely exploring and de‐risking complete integrated prototype system designs including magnetic shielding of the PBS nozzle.Materials and MethodsMagnetic field (COMSOL ) and radiation transport (Geant4) models of a proton PBS nozzle located at OncoRay (Dresden, Germany) were developed according to the manufacturers specifications. Geant4 simulations of the PBS process were performed by using magnetic field data generated by the COMSOL simulations. In total 315 spots were simulated which consisted of a scan pattern with 5 cm spot spacings and for proton energies of 70, 100, 150, 200, and 220 MeV. Analysis of the simulated deflection at the beam isocenter plane was performed to determine the self‐consistency of the model. The magnetic fringe field from a sub selection of 24 of the 315 spot simulations were directly compared with high precision magnetometer measurements. These focused on the maximum scanning setting of 20 cm beam deflection as generated from the second scanning magnet in the PBS for a proton beam energy of 220 MeV. Locations along the beam line central axis (CAX) were measured at beam isocenter and downstream of 22, 47, 72, 97, and 122 cm. Horizontal off‐axis positions were measured at 22 cm downstream of isocenter ( 50, 100, and 150 cm from CAX).ResultsThe proton PBS simulations had good spatial agreement to the theoretical values in all 315 spots examined at the beam line isocenter plane (0–2.9 mm differences or within 1.5 % of the local spot deflection amount). Careful analysis of the experimental measurements were able to isolate the changes in magnetic fields due solely to the scanning magnet contribution, and showed 1.9 1.2 –9.4 1.2 changes over the range of measurement locations. Direct comparison with the equivalent simulations matched within the measurement apparatus and setup uncertainty in all but one measurement point.ConclusionsFor the first time a robust, accurate and self‐consistent model of a proton PBS nozzle assembly has been created and successfully benchmarked for the purposes of advancing MR‐integrated proton therapy research. The model will enable confidence in further simulation based work on fully integrated designs including MRI scanners and PBS nozzle magnetic shielding in order to de‐risk and realize the full potential of MR‐integrated proton therapy.
A multiscale 3D network for lung nodule detection using flexible nodule modeling
Authors: Song Wenjia , Tang Fangfang , Marshall Henry , Fong Kwun M. , Liu Feng 
Published: July 2024

AbstractBackgroundLung cancer is the most common type of cancer. Detection of lung cancer at an early stage can reduce mortality rates. Pulmonary nodules may represent early cancer and can be identified through computed tomography (CT) scans. Malignant risk can be estimated based on attributes like size, shape, location, and density.PurposeDeep learning algorithms have achieved remarkable advancements in this domain compared to traditional machine learning methods. Nevertheless, many existing anchor‐based deep learning algorithms exhibit sensitivity to predefined anchor‐box configurations, necessitating manual adjustments to obtain optimal outcomes. Conversely, current anchor‐free deep learning‐based nodule detection methods normally adopt fixed‐size nodule models like cubes or spheres.MethodsTo address these technical challenges, we propose a multiscale 3D anchor‐free deep learning network (M3N) for pulmonary nodule detection, leveraging adjustable nodule modeling (ANM). Within this framework, ANM empowers the representation of target objects in an anisotropic manner, with a novel point selection strategy (PSS) devised to accelerate the learning process of anisotropic representation. We further incorporate a composite loss function that combines the conventional L2 loss and cosine similarity loss, facilitating M3N to learn nodules’ intensity distribution in three dimensions.ResultsExperiment results show that the M3N achieves 90.6% competitive performance metrics (CPM) with seven predefined false positives per scan on the LUNA 16 dataset. This performance appears to exceed that of other state‐of‐the‐art deep learning‐based networks reported in their respective publications. Individual test results also demonstrate that M3N excels in providing more accurate, adaptive bounding boxes surrounding the contours of target nodules.ConclusionsThe newly developed nodule detection system reduces reliance on prior knowledge, such as the general size of objects in the dataset, thus it should enhance overall robustness and versatility. Distinct from traditional nodule modeling techniques, the ANM approach aligns more closely with the morphological characteristics of nodules. Time consumption and detection results demonstrate promising efficiency and accuracy which should be validated in clinical settings.
1933 bis 1945: Verfolgung, Emigration, Widerstand
Authors: Maier Helmut 
Published: July 2024

AbstractNeue Ergebnisse der Biografieforschung liefern Zahlen zu verfolgten Chemikern, Laboranten und Studierenden und offenbaren deren Schicksale. Diese Menschen fehlten als Korrektiv bei der Gründung der GDCh.
Prozessindustrie: Petrochemie unter Strom
Authors: Neubauer Uta 
Published: July 2024

AbstractBASF testet in Ludwigshafen neuartige Öfen für Steamcracker. Sie arbeiten elektrisch statt mit Gas. Das senkt die Kohlendioxid‐Emissionen erheblich. Für eine nachhaltige Chemieindustrie sind aber weitere Umstellungen nötig.
Frühjahrsschule „The Chemistry of f‐Elements“
Authors: Kersting Berthold 
Published: July 2024

AbstractBei der Spring School „The Chemistry of f‐Elements“ diskutierten 48 nationale und internationale Teilnehmer:innen grundlegende Aspekte zur Chemie der f‐Block‐Elemente sowie neue Ergebnisse und Entwicklungen dieser Elemente in abiotischen und biologischen Systemen. Die Frühjahrsschule fand vom 27. Februar bis zum 1. März in Leipzig im Rahmen des vom BMBF geförderten Verbundprojekts Fenabium II statt.
Nachruf: Peter Jutzi (1938 – 2024)
Authors: Braun Thomas , Mitzel Norbert , Müller Christian , Siemeling Ulrich 
Published: July 2024

AbstractPeter Jutzi forschte zur metallorganischen Chemie der Hauptgruppenelemente. Spektakulär war seine Entdeckung des Silicocens, der ersten molekularen Silicium(II)‐Verbindung.
Brandbekämpfung: Für flüssig befüllte Feuerlöscher
Authors: Steinbach Cynthia , Zeiff Andreas 
Published: July 2024

AbstractSchaumlöscher lassen sich nach Produktion und Wartung mit Fasspumpen füllen. Damit ist die Produktion schnell auf Feuerlöscher ohne per‐ und polyfluorierte Alkylsubstanzen umzurüsten.
Steinhofer‐Vorlesung 2024 in Freiburg
Authors: Breit Bernhard 
Published: July 2024

AbstractBei einer festlichen Vorlesungsveranstaltung an der Universität Freiburg hielt Christof Sparr die diesjährige Steinhofer‐Vorlesung. Diese bedeutende Auszeichnung würdigt Wissenschaftler aus allen Bereichen der Chemie, die bereits in jungen Jahren herausragende internationale Sichtbarkeit erlangt haben.
Enhancing sustainability and biodegradability of poly(butylene succinate) (PBS) composite filaments reinforced with cocoa bean shell residues
Authors: Araújo Robson Pinto , Beatrice Cesar Augusto Gonçalves , Backes Eduardo Henrique , Costa Lidiane Cristina 
Published: July 2024

AbstractIn this research, we have successfully produced biodegradable composite filaments using Poly(butylene succinate) (PBS) and cocoa bean shell residues (CBS). These composite filaments, fabricated by incorporating up to 20 wt% of the natural filler into the PBS matrix through extrusion processing, have undergone rigorous rheological, mechanical, thermal, morphological, and soil disintegration characterizations. The results have unveiled the potential of printing biodegradable biocomposite filaments, with the materials demonstrating thermal stability in the printing process temperature range. However, a reduction in thermal stability was observed with the incorporation of the natural filler. Differential scanning calorimetry (DSC) analyses indicated a small crystallinity variation for the composites concerning the pure PBS matrix. Furthermore, incorporating the natural filler improved the disintegration rate in the composites' soil, suggesting that CBS can increase and modulate the biodegradation rate of the PBS matrix, thereby expanding its applications in sustainable packaging, 3D printed parts for consumer goods, and agriculture.Highlights
Sustainable innovation by using PBS‐CBS filaments for eco‐conscious production.
CBS boosts biodegradation and soil disintegration.
Shaping a greener future with eco‐friendly 3D printing of PBS‐CBS biocomposites.
Facile synthesis of carboxymethyl cellulose from Indonesia's coconut fiber cellulose for bioplastics applications
Authors: Ndruru Sun Theo Constan Lotebulo , Amri Naufal , Kusuma Samuel Budhi Wardhana , Prasetyo Ridho , Hayati Atika Trisna , Mawarni Rista Siti , Meliana Yenny , Restu Witta Kartika , Triwulandari Evi , Sampora Yulianti , Ghozali Muhammad , Marlina Anita , Sakti Aditya Wibawa , Wahyuningrum Deana , Arcana I Made 
Published: July 2024

AbstractCoconut fibers contain many lignocellulosic components; therefore, they have the potential to be used as cellulose‐based materials. This study aims to synthesize carboxymethyl cellulose (CMC) for bioplastic applications from coconut fiber cellulose obtained from South Tangerang, Indonesia. The isolation of cellulose was conducted in two key stages: alkaline treatment using a delignification reactor and bleaching with hydrogen peroxide (H2O2). The facile synthesis of CMC involved two important steps: alkaline treatment and carboxymethylation of isolated cellulose. The yield of cellulose isolated from coconut fiber was 16.39% for biomass and 64.84% for delignification products. The cellulose produced exhibited a crystallinity index (C.I.) of 89%. The yield of CMC was 14.67%, with a C.I. was 56.66%. The CMC obtained was categorized as having a medium molecular weight of 249,048 Da with a polymerization degree of 1046. Cellulose starts to decompose at a temperature interval of 292.05–381.45°C, whereas CMC decomposes at a lower temperature interval of 245.42–299.73°C. Thermochemical calculations were conducted by using the density functional theory (DFT), confirming a spontaneous reaction with a Gibbs free energy of −5.25 kJ mol−1. Bioplastics were fabricated in two stages: blending with carboxymethyl chitosan (CMChi) and plasticizing with glycerol. The addition of CMCh increased the C.I. and tensile strength, while the addition of glycerol to CMC/CMChi (80/20) blend‐based bioplastic reduced the C.I. and tensile strength, but enhanced the relative contact angle.Highlights
Cellulose was isolated from coconut fibers through a two‐stage process involving delignification and bleaching;
Carboxymethyl cellulose was synthesized by reacting the cellulose of coconut fibers with monochloroacetic acid in isopropanol with NaOH as the catayst;
The optimum condition for achieving the highest elongation at break among the blending compositions was found in the CMC/CMChi (80/20) blend bioplastic;
Adding up to 30 wt% glycerol decreased the tensile strength and increased the elongation at break;
The addition of glycerol enhanced the hydrophobic properties of CMC/CMCh blend‐based bioplastics.
Sustainable nitrogen fixation by novel gliding arc plasma reactor for the production of nitrogen fertilizers
Authors: Angineni Jyothsna , Reddy PathpiReddy Manoj Kumar , Anga Srinivas , Somaiah Puppala Veera 
Published: July 2024

AbstractA novel plasma reactor is being investigated for green NOx production, crucial for nitrate‐based fertilizer manufacturing. Various parameters, including air flow rates, gas ratios, ozone, and catalyst effects are explored for NO → NO2 conversion. NOx concentrations reach ~0.6 vol%, with a total production of ~9.7 gr/h and energy cost of ~3.0 mJ/mol, notably favorable for atmospheric gliding arc plasma. Selectivity (~75%) towards NO2 is achieved with ozone addition or catalytic treatment, pivotal for nitrate fertilizer and HNO3 production.