bluuebunny/crossref_metadata_2025_split huggingface dataset:
Amino‐Modified Polymer Immobilized Ionic Liquid Stabilized Ruthenium Nanoparticles: Efficient and Selective Catalysts for the Partial and Complete Reduction of Quinolines
Authors: Alharbi Adhwa A. , Wills Corinne , Chamberlain Thomas W. , Bourne Richard A. , Griffiths Anthony , Collins Sean M. , Wu Kejun , Mueller Pia , Knight Julian G. , Doherty Simon 
Published: April 2023

AbstractRuNPs stabilised by amino‐decorated imidazolium‐based polymer immobilized ionic liquids catalyse the dimethylamine borane mediated reduction of quinolines to 1,2‐dihydroquinoline (DHQ) and 1,2,3,4‐tetrahydroquinoline (THQ). Partial reduction of 3‐substituted quinolines to the corresponding 1,2‐dihydroquinoline was achieved with 100 % selectivity in toluene under mild conditions. This is the first report of the selective partial reduction of 3‐substituted quinolines to the corresponding 1,2‐dihydroquinolines with a heterogeneous nanoparticle‐based catalyst. A wide range of substituted quinolines have also been reduced to the corresponding 1,2,3,4‐tetrahydroquinoline with high selectivity and good yields by adjusting the reaction time. The 1,2‐dihydroquinolines readily release dihydrogen in toluene at 60 °C in the absence of catalyst with no evidence for disproportionation and as such are potential organo‐hydride reagents. The initial TOF of 610 mol quinoline converted mol Ru−1 h−1 for the reduction of quinoline is among the highest to be reported for a metal nanoparticle‐based catalyst and the conversion of 96 % obtained after 4 h at 65 °C is significantly higher than its platinum nanoparticle counterpart PtNP@NH2‐PEGPIILS as well as 5 wt/% Ru/C, which only reached 9 % and 11 % conversion, respectively, at the same time. Hot filtration experiments showed that the active species was heterogeneous.
Iodine(III)‐Mediated Oxidation of Anilines to Construct Dibenzazepines**
Authors: White Carmen Margaret , Zorigt Naranchimeg , Deng Tianning , Driver Tom G. 
Published: April 2023

AbstractThe development of an efficient process that produces bioactive medium‐sized N‐heterocyclic scaffolds from 2‐substituted anilines using either iodosobenzene or (bis(trifluoroacetoxy)iodo)‐benzene is reported. The tether between the sulfonamide and the aryl group can be varied to access dihydroacridine‐, dibenzazepine‐, or dibenzazocine scaffolds. While substitution on the aniline portion is limited to electron‐neutral‐ or electron‐poor groups, a broader range of functional groups are tolerated on the ortho‐aryl substituent and site selective C−NAr bond formation can be achieved. Preliminary mechanistic investigations suggest that medium‐ring formation occurs via radical reactive intermediates.
Label distribution learning with high‐order label correlations
Authors: Li Yulin , Lin Yaojin , Yu Xiehua , Guo Lei , Li Shaozi 
Published: April 2023

SummaryLabel distribution learning (LDL) is an emerging learning paradigm, which can be used to solve the label ambiguity problem. In spite of the recent great progress in LDL algorithms considering label correlations, the majority of existing methods only measure pairwise label correlations through the commonly used similarity metric, which is incapable of accurately reflecting the complex relationship between labels. To solve this problem, a novel label distribution learning method—based on high‐order label correlations (LDL‐HLC) is proposed. By virtue of the ‐regularization sparse reconstruction of the label space, the high‐order label correlations matrix is firstly obtained. Then, a new regular term can be constructed to fit the final prediction label distribution via the correction matrix. Furthermore, efficient classification performance and complete feature selection are guaranteed by common features learning via ‐regularization. Finally, the performance and effectiveness of the proposed algorithm are well illustrated through extensive experiments on 14 label distribution datasets and comparisons with some existing algorithms.
Ovarian cancer detection in computed tomography images using ensembled deep optimized learning classifier
Authors: Boyanapalli Arathi , Shanthini A. 
Published: April 2023

SummaryOvarian cancer (OC) is one of the most common deadly diseases threatening women worldwide. In day to day life, a challenging task still exists for identifying OC in the early stages. There are different existing deep learning (DL) classification methods applied for OC detection but has some limitations: difficult to locate the exact position of the tumor and more complex. In order to overcome these problems, the proposed ensemble deep optimized classifier‐improved aquila optimization (EDOC‐IAO) classifier is introduced to detect different types of OC in computed tomography images. The image is resized and filtered in pre‐processing using the modified wiener filter (MWF). The pre‐processed image is given to the optimized ensemble classifier (ResNet, VGG‐16, and LeNet). The IAO is utilized for improving accuracy and overfitting. The fusion is done by average weighted fusion (AWF), and the image features are extracted. Finally, the softmax layer performs the OC classification and detects different ovarian tumor classes. Python is the simulation tool used. The open source TCGA‐OV dataset is used for OC classification. The proposed OC classification using the EDOC‐IAO model obtained higher accuracy (96.532%) for detecting OC than other methods.
Introducing an adaptive model forauto‐scalingcloud computing based on workload classification
Authors: Alidoost Alanagh Yoosef , Firouzi Mojtaba , Rasouli Kenari Abdolreza , Shamsi Mahboubeh 
Published: April 2023

SummaryWith the increasing expansion of cloud computing services, one of the main goals of researchers is to solve its major challenges. Cloud service providers must satisfy the service level agreement for customers and prevent resource wastage as much as possible. Without a precise, optimal, and dynamic policy, this is unattainable. The key idea is the ability to acquire resources as you need them and release resources when you no longer need them, named “Cloud Elasticity.” Elasticity is a trade‐off between resource acquisition and release, and if this optimization is done best, the service level agreement will be fully achieved and the cloud provider will have the least waste of resources. The researchers used machine learning techniques to predict user workload and decide to scale up/out the resources. A challenging issue is the different characteristics of the users' workloads. The results show that each prediction algorithm works well on a class of users' workloads not all. Hence, in this study, a new architecture has been suggested to automatically classify the workloads based on their sequential statistical characteristics. First, the sequential statistical characteristics of the users' workload are extracted and then a trained neural network classifies the user's workload. The developed adaptive model chooses the best suitable algorithm among LR, SVM, and ARIMA to predict the workload. The results indicate a 10% improvement in forecast error.
Design, synthesis, anticancer, and antibacterial evaluation of some quinazolinone‐based derivatives as DHFR inhibitors
Authors: Osman Eman O. , Emam Soha H. , Sonousi Amr , Kandil Mai M. , Abdou Amr M. , Hassan Rasha A. 
Published: April 2023

AbstractTwo series of quinazolinone derivatives were designed and synthesized as dihydrofolate reductase (DHFR) inhibitors. All compounds were evaluated for their antibacterial and antitumor activities. Antibacterial activity was evaluated against three strains of Gram‐positive and Gram‐negative bacteria. Compound 3d exhibited the highest inhibitory activity against Staphylococcus aureus DHFR (SaDHFR) with IC50 of 0.769 ± 0.04 μM compared to 0.255 ± 0.014 μM for trimethoprim. Compound 3e was also more potent than trimethoprim against Escherichia coli DHFR (EcDHFR) with IC50 of 0.158 ± 0.01 μM and 0.226 ± 0.014 μM, respectively. Compound 3e exhibited a promising antiproliferative effect against most of the tested cancer cells. It also showed potent activity against leukemia (CCRF‐CEM, and RPMI‐8226); lung NCI‐H522, and CNS U251 with GI% of 65.2, 63.22, 73.28, and 97.22, respectively. The cytotoxic activity of compound 3e was almost half the activity of doxorubicin against CCRF‐CEM cell line with IC50 of 1.569 ± 0.06 μM and 0.822 ± 0.03 µM, respectively. In addition, compound 3e inhibited human DHFR with IC50 value of 0.527 ± 0.028 µM in comparison to methotrexate (IC50 = 0.118 ± 0.006 µM). Compound 3e caused an arrest of the cell cycle mainly at the S phase and caused a rise in the overall apoptotic percentage from 2.03% to 48.51%. (23.89‐fold). Treatment of CCRF‐CEM cells with compound 3e produced a significant increase in the active caspase‐3 level by 6.25‐fold compared to untreated cells. Molecular modeling studies were performed to evaluate the binding pattern of the most active compounds in the bacterial and human DHFR.
The opposing roles of lethal and nonlethal effects of parasites on host resource consumption
Authors: Resetarits Emlyn J. , Ellis William T. , Byers James E. 
Published: April 2023

AbstractAlthough parasites can kill their hosts, they also commonly cause nonlethal effects on their hosts, such as altered behaviors or feeding rates. Both the lethal and nonlethal effects of parasites can influence host resource consumption. However, few studies have explicitly examined the joint lethal and nonlethal effects of parasites to understand the net impacts of parasitism on host resource consumption. To do this, we adapted equations used in the indirect effects literature to quantify how parasites jointly influence basal resource consumption through nonlethal effects (altered host feeding rate) and lethal effects (increased host mortality). To parametrize these equations and to examine the potential temperature sensitivity of parasite influences, we conducted a fully factorial lab experiment (crossing trematode infection status and a range of temperatures) to quantify feeding rates and survivorship curves of snail hosts. We found that infected snails had significantly higher mortality and ate nearly twice as much as uninfected snails and had significantly higher mortality, resulting in negative lethal effects and positive nonlethal effects of trematodes on host resource consumption. The net effects of parasites on resource consumption were overall positive in this system, but did vary with temperature and experimental duration, highlighting the context dependency of outcomes for the host and ecosystem. Our work demonstrates the importance of jointly investigating lethal and nonlethal effects of parasites and provides a novel framework for doing so.
Patterns of understory invasion in invasive timber stands of a tropical sky island
Authors: Jobin Varughese , Das Arundhati , Harikrishnan C. P. , Chanda Ritobroto , Lawrence Swapna , Robin V. V. 
Published: April 2023

AbstractCurrent climate and land cover change threaten global mountaintops with increased spread of invasive species. Long‐established plantations of invasive trees on these mountaintops can alter their surroundings, further increasing invader‐facilitated invasion. Identifying the ecological conditions promoting such associations can help develop better management interventions. The Western Ghats's Shola Sky Islands (>1400 m MSL) host vast stretches of invasive tree plantations that sustain the colonization of other invasive woody, herbaceous, and fern species in their understories. Here, we analyzed vegetation and landscape variables from 232 systematically placed plots in randomly selected grids using non‐metric multidimensional scaling and Phi coefficient approaches to examine patterns of association (positive interactions) between understory invasive species with specific invasive overstory species. We also conducted GLMM with zero inflation to determine the influence of environmental variables where such associations occur. We find that understory invasion of multiple species under the canopy of other invasives is widespread across the Shola Sky Islands. Stands ofEucalyptushost the colonization of 70% of non‐native invasive species surveyed across the Shola Sky Islands. In particular, theLantana camarainvasion is strongly associated withEucalyptusstands. We also found that climatic variables affect the colonization of understory woody invasive species, while invasion by exotic herbaceous species is associated with the density of road networks. Canopy cover impacts all invasives negatively, while fire incidence was negatively associated with invasion byLantanaspp. and thePteridiumspp. While the restoration of natural habitats primarily targets the highly invasiveAcacia, less invasiveEucalyptusandPinusare often not included. Our study suggests that retaining such invasive species in natural habitats, particularly protected areas, can hinder ongoing grassland restoration efforts by facilitating further invasions by multiple woody and herbaceous species.
Restoration and resilience to sea level rise of a salt marsh affected by dieback events
Authors: Rolando J. L. , Hodges M. , Garcia K. D. , Krueger G. , Williams N. , Carr J. , Robinson J. , George A. , Morris J. , Kostka J. E. 
Published: April 2023

AbstractThe frequency of salt marsh dieback events has increased over the last 25 years with unknown consequences to the resilience of the ecosystem to accelerated sea level rise (SLR). Salt marsh ecosystems impacted by sudden vegetation dieback events were previously thought to recover naturally within a few months to years. In this study, we used a 13‐year collection of remotely sensed imagery to provide evidence that approximately 14% of total marsh area has not revegetated 10 years after a dieback event in Charleston, SC. Dieback onset coincided with a severe drought in 2012, as indicated by the Palmer drought stress index. A second dieback event occurred in 2016 after a historic flood influenced by Hurricane Joaquin in 2015. Unvegetated zones reached nearly 30% of the total marsh area in 2017. We used a light detection and ranging‐derived digital elevation model to determine that most affected areas were associated with lower elevation zones in the interior of the marsh. Further, restoration by grass planting was effective, with pilot‐scale restored plots having greater aboveground biomass than reference sites after two years of transplanting. A positive outcome indicated that the stressors that caused the dieback are no longer present. Despite that, many affected areas have not recovered naturally, even though they are located within the typical elevation range of healthy marshes. A mechanistic modeling approach was used to assess the effects of vegetation dieback on salt marsh resilience to SLR. Predictions indicate that a highly productive restored marsh (2000 g m−2 year−1) would persist at a moderate SLR rate of 60 cm in 100 years, whereas a nonrestored mudflat would lose all its elevation capital after 100 years. Thus, rapid restoration of marsh dieback is critical to avoid further degradation. Also, failure to incorporate the increasing frequency and intensity of extreme climatic events that trigger irreversible marsh diebacks underestimates salt marsh vulnerability to climate change. Finally, at an elevated SLR rate of 122 cm in 100 years, which is most likely an extreme climate change scenario, even highly productive ecosystems augmented by sediment placement would not keep pace with SLR. Thus, climate change mitigation actions are also urgently needed to preserve present‐day marsh ecosystems.
Heart failure with preserved ejection fraction phenogroup classification using machine learning
Authors: Kyodo Atsushi , Kanaoka Koshiro , Keshi Ayaka , Nogi Maki , Nogi Kazutaka , Ishihara Satomi , Kamon Daisuke , Hashimoto Yukihiro , Nakada Yasuki , Ueda Tomoya , Seno Ayako , Nishida Taku , Onoue Kenji , Soeda Tsuneari , Kawakami Rika , Watanabe Makoto , Nagai Toshiyuki , Anzai Toshihisa , Saito Yoshihiko 
Published: April 2023

AbstractAimsHeart failure (HF) with preserved ejection fraction (HFpEF) is a complex syndrome with a poor prognosis. Phenotyping is required to identify subtype‐dependent treatment strategies. Phenotypes of Japanese HFpEF patients are not fully elucidated, whose obesity is much less than Western patients. This study aimed to reveal model‐based phenomapping using unsupervised machine learning (ML) for HFpEF in Japanese patients.Methods and resultsWe studied 365 patients with HFpEF (left ventricular ejection fraction >50%) as a derivation cohort from the Nara Registry and Analyses for Heart Failure (NARA‐HF), which registered patients with hospitalization by acute decompensated HF. We used unsupervised ML with a variational Bayesian–Gaussian mixture model (VBGMM) with common clinical variables. We also performed hierarchical clustering on the derivation cohort. We adopted 230 patients in the Japanese Heart Failure Syndrome with Preserved Ejection Fraction Registry as the validation cohort for VBGMM. The primary endpoint was defined as all‐cause death and HF readmission within 5 years. Supervised ML was performed on the composite cohort of derivation and validation. The optimal number of clusters was three because of the probable distribution of VBGMM and the minimum Bayesian information criterion, and we stratified HFpEF into three phenogroups. Phenogroup 1 (n = 125) was older (mean age 78.9 ± 9.1 years) and predominantly male (57.6%), with the worst kidney function (mean estimated glomerular filtration rate 28.5 ± 9.7 mL/min/1.73 m2) and a high incidence of atherosclerotic factor. Phenogroup 2 (n = 200) had older individuals (mean age 78.8 ± 9.7 years), the lowest body mass index (BMI; 22.78 ± 3.94), and the highest incidence of women (57.5%) and atrial fibrillation (56.5%). Phenogroup 3 (n = 40) was the youngest (mean age 63.5 ± 11.2) and predominantly male (63.5 ± 11.2), with the highest BMI (27.46 ± 5.85) and a high incidence of left ventricular hypertrophy. We characterized these three phenogroups as atherosclerosis and chronic kidney disease, atrial fibrillation, and younger and left ventricular hypertrophy groups, respectively. At the primary endpoint, Phenogroup 1 demonstrated the worst prognosis (Phenogroups 1–3: 72.0% vs. 58.5% vs. 45%, P = 0.0036). We also successfully classified a derivation cohort into three similar phenogroups using VBGMM. Hierarchical and supervised clustering successfully showed the reproducibility of the three phenogroups.ConclusionsML could successfully stratify Japanese HFpEF patients into three phenogroups (atherosclerosis and chronic kidney disease, atrial fibrillation, and younger and left ventricular hypertrophy groups).
Yb(OTf)3 Anchored on Crosslinked Chitosan Microsphere: A Green Heterogenized Catalyst for the Synthesis of Bispiro‐Fused Heterocycles
Authors: Chen Lin , Jiao Wen‐Ya 
Published: April 2023

AbstractUsing renewable biomass chitosan as a raw material, crosslinked chitosan microsphere (CCM) was prepared by inverse suspension, which was then immersed in the ethanol solution of Yb(OTf)3 to fabricate CCM‐supported Yb(OTf)3 (Yb(OTf)3@CCM). The three‐component [3+2] cycloaddition of isatins, tetrahydroisoquinolines and 5‐alkenyl rhodanines was developed with Yb(OTf)3@CCM as a green heterogeneous catalyst, which gave access to a suite of architecturally complex bispiro‐fused heterocycles merging four pharmacophores with moderate to excellent yields (50–96 %) and diastereoselectivities (up to 99 : 1 dr). The reaction mechanism was preliminarily clarified by controlled experiments and dynamic high‐resolution mass spectrometry studies. The synthetic potential of this protocol was proved by a gram‐scale reaction which furnished the product with comparable results (85 % yield and 72 : 28 dr). Moreover, the catalyst could be recovered just through filtering, washing and drying process, and reused five times with the catalytic activity remaining in an acceptable range (from 93 % to 73 % yield).
Visible‐Light Photoredox‐Catalyzed Acyl Lactonization of Alkenes with Acyl Chlorides
Authors: Rao Wei‐Hao , Li Qi , Li Ying‐Ge , Jiang Li‐Li , Yue Ming‐Xiao , Zou Guo‐Dong , Cao Xinhua 
Published: April 2023

AbstractA photocatalytic acyl lactonization of unsaturated carboxylic acids using simple and inexpensive acyl chlorides has been developed for a modular synthesis of acyl lactones. Significantly, the simple protocol could allow an efficient construction of biologically important phthalide framework. The transformation could be extended to a wide variety of unsaturated carboxylic acids, including substituted 2‐vinyl benzoic acids and different types of alkenoic acids. Moreover, a series of aroyl, heteroaroyl chlorides could serve as coupling partners. Notably, functional groups including MeO, F, Cl and Br could survive. It is believed that acyl radicals generated from acyl chlorides under photoredox catalysis reacted with alkenes via atom‐transfer radical addition (ATRA) and triggered subsequent lactonization in the process. Preliminary mechanistic investigations revealed that the transformation probably proceeded through a free radical pathway.
Exploitation of Dimeric Cyclic Cysteine as Helix Inducer in Ultra‐Short Peptides for Cu(II)‐Catalyzed Asymmetric Michael Addition on Chalcones
Authors: Facchetti Giorgio , Vitoria Jaime Gracia , Moraschi Martina , Bucci Raffaella , Abel Anne Catherine , Pieraccini Stefano , Pellegrino Sara , Rimoldi Isabella 
Published: April 2023

AbstractA dimeric cyclic cysteine analogue, i.e. (1R,1′R,2R,2′R)‐2,2′‐disulfanediylbis (aminocyclohexane‐1‐carboxylic acid), was used as a constrained unnatural amino acid and as a folding inducer in ultra‐short Leu‐Val‐containing peptide. Our results showed that both free dimer amino acid L1 and its peptide derivative L2 are able to chelate Cu(II). The obtained complexes resulted to be catalytically active in Michael addition reaction of nitromethane on different types of chalcones. L1‐Cu(II) was shown more reactive in terms of conversion, while, in neat conditions, L2‐Cu(II) allows to obtain an interesting 60 % e.e. on pyridine chalcone.
Drainage development on the northern Tibetan Plateau controlled by the Altyn Tagh Fault: Insights from analogue modelling
Authors: Yan Bing , Jia Dong , Wang Maomao 
Published: April 2023

AbstractAlong the northern margin bounded by the Altyn Tagh Fault, the Tibetan Plateau has been uplifted relative to the Tarim Basin and horizontally extruded to the east for hundreds of kilometres. The Altyn Tagh Fault separates the western Kunlun Shan and Altyn Shan from the Tibetan Plateau, and these two mountain ranges form a topographic window through which river sources from the northern Tibetan Plateau flow into the Tarim Basin. In this study, we designed a specialized geomorphic sandbox to investigate major factors controlling the drainage development on the northern Tibetan Plateau. The modelling results revealed that the Altyn Tagh Fault and preexisting topography played dominant roles in reorganization and divide migration. This strike‐slip fault together with the topographic window has controlled the formation and frequent reorganization of two disproportional fault‐related drainage basins, with the eastern one much larger than the western one. Large‐scale horizontal slip along the fault has resulted in an asymmetric distribution of the drainage area, which showed eastward deviation relative to the topographic window. The modelling results are supported by the observed fluvial landforms as well as evidence of captured channels in nature. Rightward decreasing of the denudation and headward erosion rates in three‐step patterns in the model showed that the slip direction of the main plateau relative to the position of the topographic window influences the erosional dynamics. We conclude that the tectonic activity along the Altyn Tagh Fault, together with the preexisting topography, controlled the drainage development and dynamics in the northern Tibetan Plateau in the late Cenozoic.