bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dispersed surface Ru ensembles on MgO(111) for catalytic ammonia decomposition
Authors: Fang Huihuang , Wu Simson , Ayvali Tugce , Zheng Jianwei , Fellowes Joshua , Ho Ping-Luen , Leung Kwan Chee , Large Alexander , Held Georg , Kato Ryuichi , Suenaga Kazu , Reyes Yves Ira A. , Thang Ho Viet , Chen Hsin-Yi Tiffany , Tsang Shik Chi Edman 
Published: February 2023

AbstractAmmonia is regarded as an energy vector for hydrogen storage, transport and utilization, which links to usage of renewable energies. However, efficient catalysts for ammonia decomposition and their underlying mechanism yet remain obscure. Here we report that atomically-dispersed Ru atoms on MgO support on its polar (111) facets {denoted as MgO(111)} show the highest rate of ammonia decomposition, as far as we are aware, than all catalysts reported in literature due to the strong metal-support interaction and efficient surface coupling reaction. We have carefully investigated the loading effect of Ru from atomic form to cluster/nanoparticle on MgO(111). Progressive increase of surface Ru concentration, correlated with increase in specific activity per metal site, clearly indicates synergistic metal sites in close proximity, akin to those bimetallic N2 complexes in solution are required for the stepwise dehydrogenation of ammonia to N2/H2, as also supported by DFT modelling. Whereas, beyond surface doping, the specific activity drops substantially upon the formation of Ru cluster/nanoparticle, which challenges the classical view of allegorically higher activity of coordinated Ru atoms in cluster form (B5 sites) than isolated sites.
Suppression of kernel vibrations by layer-by-layer ligand engineering boosts photoluminescence efficiency of gold nanoclusters
Authors: Zhong Yuan , Zhang Jiangwei , Li Tingting , Xu Wenwu , Yao Qiaofeng , Lu Min , Bai Xue , Wu Zhennan , Xie Jianping , Zhang Yu 
Published: February 2023

AbstractThe restriction of structural vibration has assumed great importance in attaining bright emission of luminescent metal nanoclusters (NCs), where tremendous efforts are devoted to manipulating the surface landscape yet remain challenges for modulation of the structural vibration of the metal kernel. Here, we report efficient suppression of kernel vibration achieving enhancement in emission intensity, by rigidifying the surface of metal NCs and propagating as-developed strains into the metal core. Specifically, a layer-by-layer triple-ligands surface engineering is deployed to allow the solution-phase Au NCs with strong metal core-dictated fluorescence, up to the high absolute quantum yields of 90.3 ± 3.5%. The as-rigidified surface imposed by synergistic supramolecular interactions greatly influences the low-frequency acoustic vibration of the metal kernel, resulting in a subtle change in vibration frequency but a reduction in amplitude of oscillation. This scenario therewith impedes the non-radiative relaxation of electron dynamics, rendering the Au NCs with strong emission. The presented study exemplifies the linkage between surface chemistry and core-state emission of metal NCs, and proposes a strategy for brighter emitting metal NCs by regulating their interior metal core-involved motion.
JNK signaling in pioneer neurons organizes ventral nerve cord architecture in Drosophila embryos
Authors: Karkali Katerina , Saunders Timothy E. , Panayotou George , Martín-Blanco Enrique 
Published: February 2023

AbstractMorphogenesis of the Central Nervous System (CNS) is a complex process that obeys precise architectural rules. Yet, the mechanisms dictating these rules remain unknown. Analyzing morphogenesis of theDrosophilaembryo Ventral Nerve Cord (VNC), we observe that a tight control of JNK signaling is essential for attaining the final VNC architecture. JNK signaling in a specific subset of pioneer neurons autonomously regulates the expression of Fasciclin 2 (Fas 2) and Neurexin IV (Nrx IV) adhesion molecules, probably via the transcription factorzfh1. Interfering at any step in this cascade affects fasciculation along pioneer axons, leading to secondary cumulative scaffolding defects during the structural organization of the axonal network. The global disorder of architectural landmarks ultimately influences nervous system condensation. In summary, our data point to JNK signaling in a subset of pioneer neurons as a key element underpinning VNC architecture, revealing critical milestones on the mechanism of control of its structural organization.
Antitumour activity of neratinib in patients with HER2-mutant advanced biliary tract cancers
Authors: Harding James J. , Piha-Paul Sarina A. , Shah Ronak H. , Murphy Jessica J. , Cleary James M. , Shapiro Geoffrey I. , Quinn David I. , Braña Irene , Moreno Victor , Borad Mitesh , Loi Sherene , Spanggaard Iben , Park Haeseong , Ford James M. , Arnedos Mónica , Stemmer Salomon M. , de la Fouchardiere Christelle , Fountzilas Christos , Zhang Jie , DiPrimeo Daniel , Savin Casey , Duygu Selcuklu S. , Berger Michael F. , Eli Lisa D. , Meric-Bernstam Funda , Jhaveri Komal , Solit David B. , Abou-Alfa Ghassan K. 
Published: February 2023

AbstractHER2 mutations are infrequent genomic events in biliary tract cancers (BTCs). Neratinib, an irreversible, pan-HER, oral tyrosine kinase inhibitor, interferes with constitutive receptor kinase activation and has activity in HER2-mutant tumours. SUMMIT is an open-label, single-arm, multi-cohort, phase 2, ‘basket’ trial of neratinib in patients with solid tumours harbouring oncogenic HER2 somatic mutations (ClinicalTrials.gov: NCT01953926). The primary objective of the BTC cohort, which is now complete, is first objective response rate (ORR) to neratinib 240 mg orally daily. Secondary objectives include confirmed ORR, clinical benefit rate, progression-free survival, duration of response, overall survival, safety and tolerability. Genomic analyses were exploratory. Among 25 treatment-refractory patients (11 cholangiocarcinoma, 10 gallbladder, 4 ampullary cancers), the ORR is 16% (95% CI 4.5–36.1%). The most common HER2 mutations are S310F (n = 11; 48%) and V777L (n = 4; 17%). Outcomes appear worse for ampullary tumours or those with co-occurring oncogenic TP53 and CDKN2A alterations. Loss of amplified HER2 S310F and acquisition of multiple previously undetected oncogenic co-mutations are identified at progression in one responder. Diarrhoea is the most common adverse event, with any-grade diarrhoea in 14 patients (56%). Although neratinib demonstrates antitumour activity in patients with refractory BTC harbouring HER2 mutations, the primary endpoint was not met and combinations may be explored.
The feasibility and impact of implementing a computer-guided consultation to target health inequality in Asthma
Authors: Chakrabarti B. , Kane B. , Barrow C. , Stonebanks J. , Reed L. , Pearson M. G. , Davies L. , Osborne M. , England P. , Litchfield D. , McKnight E. , Angus R. M. 
Published: February 2023

AbstractGreater Manchester has a greater prevalence and worse asthma outcomes than the national average. This study aims to evaluate a digital approach to primary care asthma management and in particular the initial impact of implementing Clinical Decision Support System software in the form of a computer-guided consultation (CGC) in the setting of primary care asthma reviews in deprived areas of Greater Manchester. The CGC (LungHealth Ltd) is an intelligent decision support system ensuring accurate guideline-based staging of asthma and assessment of asthma control with the software subsequently prompting guideline-standard management. Patients on asthma registers in Greater Manchester Primary Care Networks were identified and underwent remote review by nursing staff using the CGC linked directly to the GP clinical system. Three-hundred thirty-eight patients (mean age 59 (SD 17) years; 60% Female) were reviewed. The CGC reported the patient’s asthma control to be “Good” in 22%, “Partial” in 6% and “Poor” in 72%. ACT scores were significantly higher in those patients exhibiting “Good” and “Partial” control when compared to those with “Poor” control. The number of steroid courses and hospital admissions in the previous 12 months was significantly lower in those patients exhibiting “Good” and “Partial” control when compared to those with “Poor” control. Nineteen percent were found not to have a personalised asthma management plan during CGC review, which was alerted by the CGC and subsequently, all but 3 patients had this created on review completion (McNemar’s test; p < 0.001). 5% were found not to have been prescribed regular inhaled steroid therapy resulting in the operator being alerted by the CGC in all cases. Overall, 44% underwent alteration in asthma therapy following the CGC review with 82% of these representing treatment escalation. An end-to-end digital service solution is feasible for Asthma within primary care and the utilisation of a CGC when conducting primary care asthma reviews increases implementation of guideline-level management thus addressing healthcare inequality while enabling identification of “high risk” asthma patients and guiding appropriate therapy escalation and de-escalation.
Exploring individual differences in musical rhythm and grammar skills in school-aged children with typically developing language
Authors: Nitin Rachana , Gustavson Daniel E. , Aaron Allison S. , Boorom Olivia A. , Bush Catherine T. , Wiens Natalie , Vaughan Chloe , Persici Valentina , Blain Scott D. , Soman Uma , Hambrick David Z. , Camarata Stephen M. , McAuley J. Devin , Gordon Reyna L. 
Published: February 2023

AbstractA growing number of studies have shown a connection between rhythmic processing and language skill. It has been proposed that domain-general rhythm abilities might help children to tap into the rhythm of speech (prosody), cueing them to prosodic markers of grammatical (syntactic) information during language acquisition, thus underlying the observed correlations between rhythm and language. Working memory processes common to task demands for musical rhythm discrimination and spoken language paradigms are another possible source of individual variance observed in musical rhythm and language abilities. To investigate the nature of the relationship between musical rhythm and expressive grammar skills, we adopted an individual differences approach in N = 132 elementary school-aged children ages 5–7, with typical language development, and investigated prosodic perception and working memory skills as possible mediators. Aligning with the literature, musical rhythm was correlated with expressive grammar performance (r = 0.41, p < 0.001). Moreover, musical rhythm predicted mastery of complex syntax items (r = 0.26, p = 0.003), suggesting a privileged role of hierarchical processing shared between musical rhythm processing and children’s acquisition of complex syntactic structures. These relationships between rhythm and grammatical skills were not mediated by prosodic perception, working memory, or non-verbal IQ; instead, we uncovered a robust direct effect of musical rhythm perception on grammatical task performance. Future work should focus on possible biological endophenotypes and genetic influences underlying this relationship.
Transportation of nanomaterial Maxwell fluid flow with thermal slip under the effect of Soret–Dufour and second-order slips: nonlinear stretching
Authors: Abbas Nadeem , Shatanawi Wasfi , Shatnawi Taqi A. M. 
Published: February 2023

AbstractIn this study, impact of second order slip for Maxwell fluid at vertical exponential stretching sheet is deliberated. Dufour and Soret impact for vertical exponential stretching sheet under nonlinear radiation are deliberated. Thermal and concentration slips with viscous dissipation are taken into account under the Buongiorno’s model. Under the above assumptions, the differential model constructed using the boundary layer approximations using the governing equations. The similarities transformations are introduced which applied the differential model (partial differential equations) and developed the dimensionless differential equations (ordinary differential equations). The dimensionless differential equations are cracked by numerical scheme. The impact of physical parameters are presented by tables and graphs. The curves of fluid velocity enhanced due to increasing the values of velocity slip. Velocity slip is a fluid-boundary interaction in physics. If the velocity slip increased, the fluid velocity profile would eventually become increasing. Temperature curves declined by improving values of $${K}_{1}$$

K
1

. The thermal thickness reduced when improved the values of $${K}_{1}$$

K
1

.
Using machine learning to predict venous thromboembolism and major bleeding events following total joint arthroplasty
Authors: Shohat Noam , Ludwick Leanne , Sherman Matthew B. , Fillingham Yale , Parvizi Javad 
Published: February 2023

AbstractVenous thromboembolism (VTE) and major bleeding (MBE) are feared complications that are influenced by numerous host and surgical related factors. Using machine learning on contemporary data, our aim was to develop and validate a practical, easy-to-use algorithm to predict risk for VTE and MBE following total joint arthroplasty (TJA). This was a single institutional study of 35,963 primary and revision total hip (THA) and knee arthroplasty (TKA) patients operated between 2009 and 2020. Fifty-six variables related to demographics, comorbidities, operative factors as well as chemoprophylaxis were included in the analysis. The cohort was divided to training (70%) and test (30%) sets. Four machine learning models were developed for each of the outcomes assessed (VTE and MBE). Models were created for all VTE grouped together as well as for pulmonary emboli (PE) and deep vein thrombosis (DVT) individually to examine the need for distinct algorithms. For each outcome, the model that best performed using repeated cross validation was chosen for algorithm development, and predicted versus observed incidences were evaluated. Of the 35,963 patients included, 308 (0.86%) developed VTE (170 PE’s, 176 DVT’s) and 293 (0.81%) developed MBE. Separate models were created for PE and DVT as they were found to outperform the prediction of VTE. Gradient boosting trees had the highest performance for both PE (AUC-ROC 0.774 [SD 0.055]) and DVT (AUC-ROC 0.759 [SD 0.039]). For MBE, least absolute shrinkage and selection operator (Lasso) analysis had the highest AUC (AUC-ROC 0.803 [SD 0.035]). An algorithm that provides the probability for PE, DVT and MBE for each specific patient was created. All 3 algorithms had good discriminatory capability and cross-validation showed similar probabilities comparing predicted and observed failures indicating high accuracy of the model. We successfully developed and validated an easy-to-use algorithm that accurately predicts VTE and MBE following TJA. This tool can be used in every-day clinical decision making and patient counseling.
Identifying congenital generalized lipodystrophy using deep learning-DEEPLIPO
Authors: da Cunha Olegario Natália Bitar , da Cunha Neto Joel Sotero , Barbosa Paulo Cirillo Souza , Pinheiro Plácido Rogério , Landim Pedro Lino Azevêdo , Montenegro Ana Paula Dias Rangel , Fernandes Virginia Oliveira , de Albuquerque Victor Hugo Costa , Duarte João Batista Furlan , da Cruz Paiva Lima Grayce Ellen , Junior Renan Magalhães Montenegro 
Published: February 2023

AbstractCongenital Generalized Lipodystrophy (CGL) is a rare autosomal recessive disease characterized by near complete absence of functional adipose tissue from birth. CGL diagnosis can be based on clinical data including acromegaloid features, acanthosis nigricans, reduction of total body fat, muscular hypertrophy, and protrusion of the umbilical scar. The identification and knowledge of CGL by the health care professionals is crucial once it is associated with severe and precocious cardiometabolic complications and poor outcome. Image processing by deep learning algorithms have been implemented in medicine and the application into routine clinical practice is feasible. Therefore, the aim of this study was to identify congenital generalized lipodystrophy phenotype using deep learning. A deep learning approach model using convolutional neural network was presented as a detailed experiment with evaluation steps undertaken to test the effectiveness. These experiments were based on CGL patient’s photography database. The dataset consists of two main categories (training and testing) and three subcategories containing photos of patients with CGL, individuals with malnutrition and eutrophic individuals with athletic build. A total of 337 images of individuals of different ages, children and adults were carefully chosen from internet open access database and photographic records of stored images of medical records of a reference center for inherited lipodystrophies. For validation, the dataset was partitioned into four parts, keeping the same proportion of the three subcategories in each part. The fourfold cross-validation technique was applied, using 75% (3 parts) of the data as training and 25% (1 part) as a test. Following the technique, four tests were performed, changing the parts that were used as training and testing until each part was used exactly once as validation data. As a result, a mean accuracy, sensitivity, and specificity were obtained with values of [90.85 ± 2.20%], [90.63 ± 3.53%] and [91.41 ± 1.10%], respectively. In conclusion, this study presented for the first time a deep learning model able to identify congenital generalized lipodystrophy phenotype with excellent accuracy, sensitivity and specificity, possibly being a strategic tool for detecting this disease.
The importance of the Andes in the evolutionary radiation of Sigmodontinae (Rodentia, Cricetidae), the most diverse group of mammals in the Neotropics
Authors: Vallejos-Garrido Paulo , Pino Kateryn , Espinoza-Aravena Nicolás , Pari Alexander , Inostroza-Michael Oscar , Toledo-Muñoz Macarena , Castillo-Ravanal Boris , Romero-Alarcón Viviana , Hernández Cristián E. , Palma R. Eduardo , Rodríguez-Serrano Enrique 
Published: February 2023

AbstractThe Andean mountains stand out for their striking species richness and endemicity that characterize many emblematic Neotropical clades distributed in or around these mountains. The radiation of the Sigmodontinae subfamily, the most diversified mammalian group in the Neotropics, has been historically related to Andean orogenesis. We aim to evaluate this interplay between geological processes and biological responses through the diversification dynamics, the biogeographical history, and the range evolution of the subfamily. For these, we built the most comprehensive phylogeny and gathered 14,836 occurrences for the subfamily. We identified one shift in the speciation rate in the genusAkodon, which suffered their Andean radiation after the arrival of non-Andean ancestors. Our biogeographic analyses show multiple dispersal paths throughout the evolution that allowed this subfamily to colonize all Neotropics. The Northern Andes and Central-Southern Andes were the most important sources of diversity. In addition, the Central-Southern Andes were the most relevant sink, receiving the highest number of lineages. The Andean region exhibited higher speciation and turnover rates than non-Andean regions. Thus, our results support the crucial role of the Andean Mountains in the Sigmodontinae radiation, acting as a "macroevolutionary cradle" and "species attractor" for several sigmodontine lineages at different times, and as a "species pump" becoming the biogeographic source of multiple widely distributed neotropical lineages. Then, complex macroevolutionary dynamics would explain these rodents' high extant Andean diversity and their wide distribution in the Neotropics.
Restoration of insect communities after land use change is shaped by plant diversity: a case study on carabid beetles (Carabidae)
Authors: Lange Markus , Ebeling Anne , Voigt Winfried , Weisser Wolfgang 
Published: February 2023

AbstractThere is no doubt about the insect decline currently taking place in ecosystems with large anthropogenic impacts. Thus, there is a need for practices that avoid insect decline and or help to recover insect communities that have already suffered. Plant diversity has been shown to be positively related to insect abundance and diversity and to ecosystem functions provided by insects. However, it remains open if increased plant diversity can help to recover decreased populations. Here, we tested over one decade the effects of plant diversity on the carabid community in a large grassland biodiversity experiment and how plant diversity fostered the establishment of a natural grassland community after conversion of an arable field. There was a dramatic decline in carabid abundance from 2003, the first year after establishing the diversity experiment, to 2005. However, subsequently, the abundance increased constantly. One year after the land use change most individuals and species were those commonly found in agricultural fields. In subsequent years the community was dominated by grassland species. While plant diversity did not affect the abundance and richness of the carabid community, the turnover to a more native grassland community was accelerated by plant diversity in the first years after the land use change. In contrast, in later years plant diversity stabilized the community assemblage. Our study shows that high plant diversity can contribute to a faster transition of insect populations towards naturally occurring community assemblages and at later stages to more stabilized assemblages.
Evaluation and remediation protocol of selected organochlorine pesticides and heavy metals in industrial wastewater using nanoparticles (NPs) in Nigeria
Authors: Nnaji Jude Chidozie , Amaku James Friday , Amadi Okoche Kelvin , Nwadinobi Solomon Ireji 
Published: February 2023

AbstractLimited knowledge of the level of contaminants in industrial wastewater within the Nigerian states together with the global challenge of water supply have compelled our investigation into the analyses and removal of organochlorine pesticides (OCPs) and heavy metal contents in industrial wastewater. Wastewater samples were collected from 13 industries across five states in Nigeria. The OCPs content of the samples was extracted, cleaned up and analysed using gas chromatography-mass spectrometry. The results indicate that the mean concentrations of the OCPs in the effluent samples ranged from 1.76 ng L−1 (Dieldrin) to 0.89 ng L−1 (endrin). Cadmium (Cd), chromium (Cr) and lead (Pb) were evaluated in all the effluent water samples. The results show that the average concentrations of the heavy metal ions in the effluent samples ranged from 0.008 ± 0.003 mg L−1 (Cd) to 2.215 ± 0.841 mg L−1 (Pb). For the removal of the identified contaminants, biomagnetite nanoparticles (BioMag), magnetite nanoparticles (MagNPs), biomagnetite-CMC nanocomposite (BioMag-CMC) and magnetite-CMC nanocomposite (MagNPs-CMC) were synthesised and characterised using Braunauer–Emmett–Teller (BET), Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD) and high resolution-transmission electron microscopy (HR-TEM). This study demonstrates the successful application of nanoparticles (NPs) and nanocomposites in the removal of OCPs and heavy metal ions in industrial effluents. The routine assessment and continuous removal become important to attain a state of clean and healthy aquatic ecosystem due to rapid industrial and technological advances.