bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lignin phenol quantification from machine learning‐assisted decomposition of liquid chromatography‐absorbance spectroscopy data
Authors: Bruhn Anders Dalhoff , Wünsch Urban , Osburn Christopher L. , Rudolph Jacob C. , Stedmon Colin A. 
Published: June 2023

AbstractAnalysis of lignin in seawater is essential to understanding the fate of terrestrial dissolved organic matter (DOM) in the ocean and its role in the carbon cycle. Lignin is typically quantified by gas or liquid chromatography, coupled with mass spectrometry (GC‐MS or LC‐MS). MS instrumentation can be relatively expensive to purchase and maintain. Here we present an improved approach for quantification of lignin phenols using LC and absorbance detection. The approach applies a modified version of parallel factor analysis (PARAFAC2) to 2nd derivative absorbance chromatograms. It is capable of isolating individual elution profiles of analytes despite co‐elution and overall improves sensitivity and specificity, compared to manual integration methods. For most lignin phenols, detection limits below 5 nmol L−1 were achieved, which is comparable to MS detection. The reproducibility across all laboratory stages for our reference material showed a relative standard deviation between 1.47% and 16.84% for all 11 lignin phenols. Changing the amount of DOM in the reaction vessel for the oxidation (dissolved organic carbon between 22 and 367 mmol L−1), did not significantly affect the final lignin phenol composition. The new method was applied to seawater samples from the Kattegat and Davis Strait. The total concentration of dissolved lignin phenols measured in the two areas was between 4.3–10.1 and 2.1–3.2 nmol L−1, respectively, which is within the range found by other studies. Comparison with a different oxidation approach and detection method (GC‐MS) gave similar results and underline the potential of LC and absorbance detection for analysis of dissolved lignin with our proposed method.
SOCS1‐KIR Peptide in PEGDA Hydrogels Reduces Pro‐Inflammatory Macrophage Activation
Authors: Jha Aakanksha , Larkin Joseph , Moore Erika 
Published: June 2023

AbstractMacrophages modulate the wound healing cascade by adopting different phenotypes such as pro‐inflammatory (M1) or pro‐wound healing (M2). To reduce M1 activation, the JAK/STAT pathway can be targeted by using suppressors of cytokine signaling (SOCS1) proteins. Recently a peptide mimicking the kinase inhibitory region (KIR) of SOCS1 has been utilized to manipulate the adaptive immune response. However, the utilization of SOCS1‐KIR to reduce pro‐inflammatory phenotype in macrophages is yet to be investigated in a biomaterial formulation. This study introduces a PEGDA hydrogel platform to investigate SOCS1‐KIR as a macrophage phenotype manipulating peptide. Immunocytochemistry, cytokine secretion assays, and gene expression analysis for pro‐inflammatory macrophage markers in 2D and 3D experiments demonstrate a reduction in M1 activation due to SOCS1‐KIR treatment. The retention of SOCS1‐KIR in the hydrogel through release assays and diffusion tests is demonstrated. The swelling ratio of the hydrogel also remains unaffected with the entrapment of SOCS1‐KIR. This study elucidates how SOCS1‐KIR peptide in PEGDA hydrogels can be utilized as an effective therapeutic for macrophage manipulation.
Sanggenon C inhibits cell proliferation and induces apoptosis by regulating the MIB1/DAPK1 axis in glioblastoma
Authors: Chang Hongbo , Hou Jianbing , Shao Yaqian , Xu Minghao , Weng Xuelian , Du Yi , Shi Junbo , Zhang Li , Cui Hongjuan 
Published: June 2023

AbstractSanggenon C (SC), a herbal flavonoid extracted from Cortex Mori, has been mentioned to possess more than one treasured organic properties. However, the molecular mechanism of its anti‐tumor impact in glioblastoma (GBM) remains unclear. In this study, we reported that SC displayed a GBM‐suppressing impact in vitro and in vivo with no apparent organ toxicity. SC dramatically suppressed cell proliferation‐induced cell apoptosis in GBM cells. Mechanistically, we unveiled that SC modulated the protein expression of death associated protain kinase 1 (DAPK1) by controlling the ubiquitination and degradation of DAPK1. Quantitative proteomic and Western blot analyses showed that SC improved DAPK1 protein degradation via decreasing the expression of E3 ubiquitin ligase Mindbomb 1 (MIB1). More importantly, the effects of SC on cell proliferation and apoptosis of GBM cells have been in part reversed through DAPK1 downregulation or MIB1 overexpression, respectively. These results indicated that SC might suppress cell proliferation and induce cell apoptosis by decreasing MIB1‐mediated DAPK1 degradation. Furthermore, we found that SC acted synergistically with temozolomide (TMZ), an anti‐cancer drug used in GBM, resulting in elevated chemotherapeutic sensitivity of GBM to TMZ. Collectively, our data suggest that SC might be a promising anti‐cancer agent for GBM therapy.
Application of various genetic analysis techniques for detecting two rare cases of 9p duplication mosaicism during prenatal diagnosis
Authors: Zhang Sufen , Zhou Yuqiu , Xiao Gefei , Qiu Xianrong 
Published: June 2023

AbstractBackgroundThe identification of genetic mosaicism and the genetic counseling needed following its discovery have been challenging problems in the field of prenatal diagnosis. Herein, we describe the clinical phenotypes and various prenatal diagnostic processes used for two rare cases of 9p duplication mosaicism and review the prior literature in the field to evaluate the merits of different methods for diagnosing mosaic 9p duplication.MethodsWe recorded ultrasound examinations, reported the screening and diagnosis pathways, and analyzed the mosaic levels of the two cases of 9p duplication using karyotype analysis, chromosomal microarray analysis (CMA), and fluorescence in situ hybridization analysis (FISH).ResultsCase 1 had a normal clinical phenotype for tetrasomy 9p mosaicism, and Case 2 showed multiple malformations caused by both trisomy 9 and trisomy 9p mosaicism. Both cases were initially suspected after non‐invasive prenatal screening (NIPT) based on cell‐free DNA. The mosaic ratio of 9p duplication found via karyotyping was lower than what was discovered by CMA and FISH, in both cases. Contrary to previous findings, the mosaic level of trisomy 9 found by karyotype analysis was greater than what was found by CMA, in terms of complex mosaicism involving trisomy 9 and trisomy 9p, in Case 2.ConclusionNIPT can indicate 9p duplication mosaicism during prenatal screening. Different strengths and limitations existed in terms of diagnosing mosaic 9p duplication by karyotype analysis, CMA, and FISH. The combined use of various methods may be capable of more accurately determining break‐points and mosaic levels of 9p duplication during prenatal diagnosis.
Liquid–liquid phase separation in synaptopathies
Authors: Jiang Huihui , Wu Haitao 
Published: June 2023

AbstractLiquid–liquid phase separation has emerged as an important mechanism for regulating cell activity by promoting the formation of membrane‐less condensates. In the nervous system, the formation of distinct molecular condensates via phase separation is involved in synaptic assembly and function. Disruption of phase separation is associated with several disease states, such as cancer, neurodegenerative disorders, and neurodevelopmental disorders. This review summarizes the function of phase separation in the assembly and plasticity of the synapse, discusses the role of abnormal phase separation in neurological diseases, and proposes potential treatment options for these neurological diseases based on phase separation.
An optimization based multi‐block‐structured grid generation method
Authors: Sauer Marcel , Morsbach Christian 
Published: June 2023

SummaryA new optimization based meshing technique for block‐structured meshes is presented. Given a topological block partition, block sizes, and distance constraints, meshes are generated automatically. The optimization effort is limited by using a BSpline based intermediate layer with reduced degrees of freedom, making it suitable for high resolution meshes. The optimization itself minimizes approximated grid criteria defined in the intermediate layer domain. Sampling the intermediate layer results in a mesh, which is projected in order to preserve geometric constraints. The capability of the new method is shown for 2D and 3D geometries.
Ultrasonic radiation‐induced synthesis, characterization, and biological activity of a new Fe3O4 supported‐sulfonated graphene oxide/polyaniline nano‐composite
Authors: Jakhar Prakash , Sharma Shaily , Sharma Himanshu 
Published: June 2023

AbstractIn this investigation, a unique Fe3O4‐supported‐sulfonated graphene oxide/polyaniline (FSGO/PANI) nano‐composite was designed and further, it was evaluated for antimicrobial activity. In situ polymerization in an aqueous acidic medium using ultrasonic irradiation technique was used to create this innovative nano‐composite (FSGO/PANI). FTIR, XRD, SEM, EDX, and NMR, approaches were used to characterize the surface morphologies as well as structures of the developed FSGO/PANI nano‐composite. Both FTIR and NMR spectroscopy supported the existence of polyaniline (PANI). XRD data depicted that the produced nano‐composite was an amorphous material. TGA data were used to confirm the thermal stability of FSGO/PANI. At 100°C, the nano‐composite lost weight relatively slowly (11%) and roughly (34.35%) at 400°C. The FSGO/PANI nano‐composite showed excellent results in form of MIC (minimum inhibitory concentration) and ZOI (zone of inhibition) against bacterial strains and fungal strains in tests for antimicrobial activity.
Family perspectives on the transition from active treatment to survivorship for children with cancer
Authors: Parker Kellee , Christensen Vivian , Lindemulder Susan , Chan Lai Hin Kimi , Saxton Lauren , Cottrell Erika 
Published: June 2023

AbstractBackgroundCompleting therapy for childhood cancer is an exciting milestone. However, this adjustment can be extremely stressful for patients and their families as they transition from cancer patient to survivor. A better understanding of the patient and family experience and their needs during this transition is crucial for developing guidelines and leveraging support for future patients and families.ProcedureParticipants were recruited from across the United States using a maximum variation sampling strategy. Families were eligible if they had a child diagnosed with cancer before age 15 and had completed treatment at least 1 year prior to their interview. Participants completed a 90–180‐minute semi‐structured interview either in person or virtually. Interviews focused on the experiences of getting a diagnosis, experiences with treatment, information seeking, impact of cancer on the family, social support, and transitions to survivorship. Inductive thematic analysis revealed a wide variety of themes. This paper examines the transition from active cancer therapy into survivorship.ResultsIdentified primary themes included (i) feelings about transitioning off therapy; (ii) coping with lingering effects; and (iii) experiences of transitioning off therapy and survivorship care. Subthemes highlighted the need for more support for both patients and families during this transition.ConclusionPatients and families desire more support during the transition off therapy. Suggestions included access to additional resources, earlier transition to receiving survivorship care, and more holistic survivorship care. Further research is needed to determine best models and feasibility of delivering this desired support to all patients and families.
The relationship between sarcopenia, multidimensional frailty, and malnutrition cluster and long‐term mortality in hospitalized patients with cirrhosis
Authors: Guo Gaoyue , Wang Han , Yang Wanting , Li Chaoqun , Zhao Xingliang , Fan Xiaofei , Hui Yangyang , Cui Binxin , Wang Xiaoyu , Zhang Xuqian , Jiang Kui , Sun Chao 
Published: June 2023

AbstractAimSarcopenia, multidimensional frailty, and malnutrition represent common debilitating conditions in the context of cirrhosis, linked to a variety of dismal outcomes. We aimed to clarify their overlap and cumulative impact on long‐term mortality in hospitalized patients with cirrhosis.MethodsConsecutive patients with cirrhosis were prospectively recruited from January 2018 to December 2020. The diagnosis of sarcopenia, multidimensional frailty, and malnutrition was standardized according to the consensus definition and our well‐documented criteria. The prevalence of the respective debilitating condition and the concurrence of this comorbidity were calculated.ResultsIn total, 253 patients with cirrhosis aged 64 years with a female predominance (52.4%) were recruited. Sarcopenia was present in 20.9% (53/253), multidimensional frailty in 12.6% (32/253), and malnutrition in 44.7% (113/253) of the entire cohort. Approximately half of the patients had at least one debilitating condition (127/253). Sarcopenia and malnutrition co‐existed in 33 nonfrail patients (13.0%) and multidimensional frailty and malnutrition in eight nonsarcopenic patients (3.2%). Fifteen (5.9%) subjects had all three debilitating conditions, namely malnutrition, sarcopenia, and frailty (MSF) group. The proportions of males, infections, and ascites were significantly higher in the MSF group. Patients in the MSF group had the highest levels of neutrophil‐to‐lymphocyte ratio and creatinine. The 2‐year mortality rates in patients with three debilitating conditions, two conditions, one condition, and no conditions were 60.0%, 23.8%, 21.4%, and 13.5%, respectively. Multivariate Cox regression indicated the long‐term mortality risk was approximately four‐fold higher among patients in the MSF group compared to those with no conditions.ConclusionsA fraction of patients with cirrhosis exhibited comorbidities of sarcopenia, multidimensional frailty, and malnutrition, linked to a higher risk of long‐term mortality.
Modifying explosive behavior with additives
Authors: Busby Taylor , Smith James , Sheehan Pam , Oxley Jimmie 
Published: June 2023

AbstractThe influence of additives on the detonation velocity of a polyethylene wax/RDX formulation was examined. Additives included species of various shock impedance: glass microballoons; glass microspheres; polymethyl methacrylate (PMMA) microspheres; thermally expandable microspheres (TEMs); and PMMA microencapsulated pentaerythritol tetranitrate (PETN). Performance of the insensitive explosive 2,4‐dinitroanisole (DNAN) was enhanced by addition of PETN‐either neat or encapsulated, but encapsulation did not increase the sensitivity of the formulation. The energy contribution of the encapsulated PETN to the detonation front of the insensitive explosive 2,4‐dinitroanisole (DNAN) was also demonstrated. Present in 5 wt%, the encapsulated PETN allowed DNAN to sustain a reaction (5.36 km/s) at 13 mm, well below its critical diameter.
Perturbative Solution of the Einstein Constraints with Spin and Momentum Far Away From a Binary Source in the Bowen‐York Formalism
Authors: Altas Emel , Ertugrul Emine , Tekin Bayram 
Published: June 2023

AbstractThe momentum and Hamiltonian constraints of vacuum Einstein equations, within the Bowen‐York formalism, for two interacting black holes in close separation, with anti‐parallel spins and anti‐parallel linear momenta is studied. An analytical solution using perturbation theory is given. The location and the shape of the apparent horizon which generically depend on all the parameters, angles, and the separation between the black holes are also computed. The solution only works for distances far away from the black holes. To gain more insight close into the black holes, one has to go to the higher orders in perturbation theory, which is a rather cumbersome process. But the solution presented here can be of some use for numerical computations as the latter should match our result for the described problem.
Country context, race and wages: A comparative analysis of Ethiopian immigrant labour market integration in the United States and Israel
Authors: Tesfai Rebbeca , Saabneh Ameed 
Published: June 2023

AbstractAmerican immigration policy debates focus on immigrants' (lack of) labour market success. While research shows that Black African immigrants experience the largest wage disadvantage, studies rarely discuss whether country‐context—formed by immigration policy and migration history—matters for their wages and whether race matters differently across place. We use Israeli and US data to determine whether Ethiopian immigrants are most disadvantaged across country contexts. Our results indicate that Ethiopian immigrants' credentials are higher in the United States, but that does not lead to higher relative wages than in Israel. Because we find that Ethiopian immigrants who are most similar to the native‐born earn nearly identical wages to the most marginalized groups in both countries, it is clear that country context plays only a small role in wage disparities. Instead, discrimination and unobserved differences between groups are most important.
Treeline remote sensing: from tracking treeline shifts to multi‐dimensional monitoring of ecotonal change
Authors: Garbarino Matteo , Morresi Donato , Anselmetto Nicolò , Weisberg Peter J. 
Published: June 2023

AbstractRemote sensing applications have a long history in treeline research. Recent reviews have examined the topic mainly from a methodological point of view. Here, we propose a question‐oriented review of remote sensing in treeline ecology to relate remote sensing methodologies to key ecological metrics and identify knowledge gaps and promising areas for future research. We performed a meta‐analysis to assess the role of remote sensing as a tool for measuring spatial patterns and dynamics of alpine and Arctic treeline ecotone globally. We assessed the geographic distribution, scale of analysis, and relationships between remote sensing techniques and treeline ecological metrics through co‐occurrence mapping and multivariate statistics. Our analysis revealed that only 10% of treeline ecology studies applied remote sensing tools, often associated with the keyword ‘climate change’. Monitoring studies adopted coarser spatial resolutions over longer temporal extents in comparison with other treeline studies. A multiscale and multi‐sensor spatial approach was implemented in just 19% of papers. Long‐term research commonly relied on aerial and oblique photography to measure treeline shifts through photointerpretation within a multidisciplinary framework. More recent treeline dynamics were often quantified using greenness trends derived from the pixel‐based classification of satellite images. Many recent short‐term studies focused on delineating tree scale metrics derived from the object‐based classification of uncrewed aerial vehicle (UAV) images or LiDAR data. Over the past decade, high‐resolution and low‐cost UAV remote sensing has emerged as an interesting opportunity to fill the gap between local‐scale ecological patterns and coarse‐resolution satellite sensors. Additionally, treeline remote sensing applications would strongly benefit from multidisciplinary frameworks that integrate field studies in ecology and environmental science. The multi‐dimensional structural complexity of treelines typically responds to environmental drivers over multiple scales and thus is best described with multiscale and multi‐sensor approaches.
Data‐driven approach for investigating and predicting of compressive strength of fly ash–slag geopolymer concrete
Authors: Tran Van Quan 
Published: June 2023

AbstractFly ash–slag geopolymer concrete is an intangible material that does not use conventional Portland cement, thereby reducing CO2 emissions into the environment, and helping to increase sustainable development. However, compared with conventional concrete, the compressive strength of fly ash–slag geopolymer concrete is complexly dependent on many factors. Using the data‐driven approach for investigating and predicting fly ash–slag geopolymer concrete compressive strength is a suitable choice. This study introduces 11 easily accessible machine learning models in open‐source libraries of the Python programming language such as support vector machine, random forest (RF), gradient boosting (GB), AdaBoost, decision trees, light GB machine, extreme GB (XGB), K‐nearest neighbors, multivariable regression, Gaussian process regression, and CatBoost (CatB). Based on a dataset of 158 samples, 14 inputs, and 1 output variable compressive strength, the performance of 11 machine learning models was evaluated through 4 criteria including coefficient of determination, root mean square error, mean absolute error, and mean absolute percentage error combined with 10 repeats of 10‐fold cross‐validation. Four models have the best performance based on the above four criteria value in determining compressive strength for testing dataset sorted descending is CatB > XGB > RF > GB. Global Shapley (SHAP) value‐based CatB and XGB indicates three groups of factors with decreasing influence on compressive strength of geopolymer concrete: group I (slag, molarity, coarse aggregate, curing temperature, and alkaline activator/binder) > group II (Na2SiO3 content, NaOH content, fine aggregate, fly ash content), curing period > group III (extra water added, NaOH/Na2SiO3, superplasticizer content, rest period). Extra water added, NaOH/Na2SiO3, superplasticizer content, rest period have insignificant influence on the compressive strength value of geopolymer concrete. The greater the slag content in the slag–fly ash mixture, the greater the compressive strength of geopolymer concrete. The optimum molarity of NaOH concentration is about 14–16 M for designing the compressive strength of geopolymer concrete. SHAP values partial dependence plots (PDP) and PDP indicate that alkaline activator/binder optimal values exist to achieve high compressive strength. The compressive strength increases with curing temperature between 20 and 100°C. PDP values show that the tendency to increase compressive strength with increasing coarse aggregate content from about 750 to 1250 kg/m3.
Additives enhancing supported amines performance in CO2 capture from air
Authors: Wang Yaozu , Miao Yihe , Ge Bingyao , He Zhijun , Zhu Xuancan , Liu Shanke , Li Jia , Yu Lijun 
Published: June 2023

AbstractThe utilization of supported amines as adsorbents in direct air capture (DAC) has been demonstrated to be a promising strategy for the reduction of CO2 emissions. To improve the performance of amine‐based adsorbents, the incorporation of additives has been widely adopted. In the present study, we conduct a comprehensive comparison of seven additives on tetraethylenepentamine‐impregnated mesoporous silica as a representative amine‐based adsorbent. The results indicate that minor molecular weight additives with hydroxyl groups show improved adsorption–desorption performance and increase oxidative stability. A proposed mechanism for these improvements is the combined physical and chemical promotion effects of hydroxyl groups. Through a comprehensive review of existing literature, it is found that the effects of additives on amine‐based adsorbents are dependent on factors, such as additive type, pristine adsorbent properties, incorporation method, and testing conditions. Based on these findings, it is recommended that future DAC systems prioritize the use of hydroxyl‐containing additives, whereas higher CO2 concentration and temperature capture may benefit from the incorporation of additives without hydroxyl groups. These conclusions are expected to contribute to the design of efficient adsorbents for CO2 capture.