bluuebunny/crossref_metadata_2025 huggingface dataset:
The Interleukin‐1 Receptor–Associated Kinase 4 Inhibitor PF‐06650833 Blocks Inflammation in Preclinical Models of Rheumatic Disease and in Humans Enrolled in a Randomized Clinical Trial
Authors: Winkler Aaron , Sun Weiyong , De Saurav , Jiao Aiping , Sharif M. Nusrat , Symanowicz Peter T. , Athale Shruti , Shin Julia H. , Wang Ju , Jacobson Bruce A. , Ramsey Simeon J. , Dower Ken , Andreyeva Tatyana , Liu Heng , Hegen Martin , Homer Bruce L. , Brodfuehrer Joanne , Tilley Mera , Gilbert Steven A. , Danto Spencer I. , Beebe Jean J. , Barnes Betsy J. , Pascual Virginia , Lin Lih‐Ling , Kilty Iain , Fleming Margaret , Rao Vikram R.
Published: August 2021

Objective

To investigate the role of PF‐06650833, a highly potent and selective small‐molecule inhibitor of interleukin‐1–associated kinase 4 (IRAK4), in autoimmune pathophysiology in vitro, in vivo, and in the clinical setting.

Methods

Rheumatoid arthritis (RA) inflammatory pathophysiology was modeled in vitro through 1) stimulation of primary human macrophages with anti–citrullinated protein antibody immune complexes (ICs), 2) RA fibroblast‐like synoviocyte (FLS) cultures stimulated with Toll‐like receptor (TLR) ligands, as well as 3) additional human primary cell cocultures exposed to inflammatory stimuli. Systemic lupus erythematosus (SLE) pathophysiology was simulated in human neutrophils, dendritic cells, B cells, and peripheral blood mononuclear cells stimulated with TLR ligands and SLE patient ICs. PF‐06650833 was evaluated in vivo in the rat collagen‐induced arthritis (CIA) model and the mouse pristane‐induced and MRL/lpr models of lupus. Finally, RNA sequencing data generated with whole blood samples from a phase I multiple‐ascending‐dose clinical trial of PF‐06650833 were used to test in vivo human pharmacology.

Results

In vitro, PF‐06650833 inhibited human primary cell inflammatory responses to physiologically relevant stimuli generated with RA and SLE patient plasma. In vivo, PF‐06650833 reduced circulating autoantibody levels in the pristane‐induced and MRL/lpr murine models of lupus and protected against CIA in rats. In a phase I clinical trial (NCT02485769), PF‐06650833 demonstrated in vivo pharmacologic action pertinent to SLE by reducing whole blood interferon gene signature expression in healthy volunteers.

Conclusion

These data demonstrate that inhibition of IRAK4 kinase activity can reduce levels of inflammation markers in humans and provide confidence in the rationale for clinical development of IRAK4 inhibitors for rheumatologic indications.
Measuring the citation context of national self‐references
Authors: Chen Liyue , Ding Jielan , Larivière Vincent
Published: August 2021

The emphasis on research evaluation has brought scrutiny to the role of self‐citations in the scholarly communication process. While author self‐citations have been studied at length, little is known on national‐level self‐references (SRs). This paper analyses the citation context of national SRs, using the full‐text of 184,859 papers published in PLOS journals. It investigates the differences between national SRs and nonself‐references (NSRs) in terms of their in‐text mention, presence in enumerations, and location features. For all countries, national SRs exhibit a higher level of engagement than NSRs. NSRs are more often found in enumerative citances than SRs, which suggests that researchers pay more attention to domestic than foreign studies. There are more mentions of national research in the methods section, which provides evidence that methodologies developed in a nation are more likely to be used by other researchers from the same nation. Publications from the United States are cited at a higher rate in each of the sections, indicating that the country still maintains a dominant position in science. On the whole, this paper contributes to a better understanding of the role of national SRs in the scholarly communication system, and how it varies across countries and over time.
Radical Cyclization of 1,n‐Enynes and 1,n‐Dienes for the Synthesis of 2‐Pyrrolidone
Authors: Jiang Li‐Lin , Hu Sen‐Jie , Xu Qing , Zheng Hongxing , Wei Wen‐Ting
Published: August 2021

2‐Pyrrolidones have aroused enormous interest as a useful structural moiety in drug discovery; however, not only does their syntheses suffer from low selectivity and yield, but also it requires high catalyst loadings. The radical cyclization of 1,n‐enynes and 1,n‐dienes has demonstrated to be an attractive method for the synthesis of 2‐pyrrolidones due to its mild reaction conditions, fewer steps, higher atom economy, excellent functional group compatibility, and high regioselectivity. Furthermore, radical receptors with unsaturated bonds (i. e. 1,n‐enynes and 1,n‐dienes) play a crucial role in realizing radical cyclization because of the ability to selectively introduce one or more radical sources. In this review, we discuss representative examples of methods involving the radical cyclization of 1,n‐enynes and 1,n‐dienes published in the last five years and discuss each prominent reaction design and mechanism, providing favorable tools for the synthesis of valuable 2‐pyrrolidone for a variety of applications.
K2Na3[{B6O10(OH)}{B3O4(OH)3}] ⋅ H2O: A Layered Borate Built by Mixed Oxoboron Clusters with Nonlinear‐Optical Property
Authors: Chen Chong‐An , Qiu Qi‐Ming , Yang Guo‐Yu
Published: August 2021

A new acentric borate, K2Na3[{B6O10(OH)}‐{B3O4(OH)3}] ⋅ H2O (1) has been made under solvothermal condition. 1 has layered structure made by B6O13(OH)‐based chains and B3O5(OH)3‐bridging clusters. Second‐harmonic generation (SHG) measurements reveal that 1 is a phase‐matchable nonlinear optical (NLO) material, showing the SHG signal intensity of 1.8 times that of KDP (KH2PO4). Besides, UV‐Vis diffuse reflectance spectrum shows that 1 has the short deep UV (DUV) absorption cutoff edge of 198 nm. Thermogravimetric analysis reveals it has good thermal stability. Also 1 represents firstly mixed oxoboron clusters‐made 2D layered borate with NLO property.
Optimal interpregnancy interval in autism spectrum disorder: A multi‐national study of a modifiable risk factor
Authors: Pereira Gavin , Francis Richard W. , Gissler Mika , Hansen Stefan N. , Kodesh Arad , Leonard Helen , Levine Stephen Z. , Mitter Vera R. , Parner Eric T. , Regan Annette K. , Reichenberg Abraham , Sandin Sven , Suominen Auli , Schendel Diana
Published: August 2021

It is biologically plausible that risk of autism spectrum disorder (ASD) is elevated by both short and long interpregnancy intervals (IPI). We conducted a retrospective cohort study of singleton, non‐nulliparous live births, 1998–2007 in Denmark, Finland, and Sweden (N = 925,523 births). Optimal IPI was defined as the IPI at which minimum risk was observed. Generalized additive models were used to estimate relative risks (RR) of ASD and 95% Confidence Intervals (CI). Population impact fractions (PIF) for ASD were estimated under scenarios for shifts in the IPI distribution. We observed that the association between ASD (N = 9302) and IPI was U‐shaped for all countries. ASD risk was lowest (optimal IPI) at 35 months for all countries combined, and at 30, 33, and 39 months in Denmark, Finland, and Sweden, respectively. Fully adjusted RRs at IPIs of 6, 12, and 60 months were 1.41 (95% CI: 1.08, 1.85), 1.26 (95% CI: 1.02, 1.56), and 1.24 (95% CI: 0.98, 1.58) compared to an IPI of 35 months. Under the most conservative scenario PIFs ranged from 5% (95% CI: 1%–8%) in Denmark to 9% (95% CI: 6%–12%) in Sweden. The minimum ASD risk followed IPIs of 30–39 months across three countries. These results reflect both direct IPI effects and other, closely related social and biological pathways. If our results reflect biologically causal effects, increasing optimal IPIs and reducing their indications, such as unintended pregnancy and delayed age at first pregnancy has the potential to prevent a salient proportion of ASD cases.

Lay Summary

Waiting 35 months to conceive again after giving birth resulted in the least risk of autism. Shorter and longer intervals resulted in risks that were up to 50% and 85% higher, respectively. About 5% to 9% of autism cases might be avoided by optimizing birth spacing.
Optimization, extraction, and purification of three bioactive compounds from Entada phaseoloides by high‐speed countercurrent chromatography
Authors: Zhou Yan , Shan Hu , Lü Haitao
Published: August 2021

The objective of this paper was to develop a preparative method for the separation and purification of phaseoloidin, entadamide A, and entadamide A‐β‐D‐glucopyranoside from the crude extract of Entada phaseoloides by high‐speed countercurrent chromatography (HSCCC) for the first time. Optimized by orthogonal experiments, the extraction conditions were extraction temperature of 65°C, solid‐to‐liquid ratio of 1:15 (g/mL), ethanol concentration of 40%, and extraction time of 2.5 h. Using n‐butanol‐acetic acid‐water (4:1:5, v/v/v) as the two‐phase solvent system, 38.79 mg phaseoloidin (the purity was 99.3% with a recovery of 98.1%), 34.85 mg entadamide A (the purity was 96.4% with a recovery of 98.5%), and 33.97 mg entadamide A‐β‐D‐glucopyranoside (the purity was 98.6% with a recovery of 97.7%) were obtained from 500 mg crude extract by HSCCC in head‐to‐tail elution mode. The retention ratio of stationary phase was 51.0%. According to the antioxidant activity assays, phaseoloidin, entadamide A, and entadamide A‐β‐D‐glucopyranoside had certain scavenging abilities on 1,1‐diphenyl‐2‐picrylhydrazyl free radicals and hydroxyl free radicals.
The safety and efficacy of botulinum toxin A on the treatment of depression
Authors: Zhang Qilin , Wu Wenqi , Fan Yuxin , Li Yang , Liu Jing , Xu Yingying , Jiang Caixia , Tang Zhen , Cao Cong , Liu Tong , Chen Li‐Hua , Hu Hua , Luo Weifeng
Published: August 2021

Objectives

Effective strategy for the treatment of depression is limited. This study was to evaluate the safety and efficacy of botulinum toxin A (BoNT/A) in the treatment of depression.

Methods

Seventy‐six patients were assigned to the BoNT/A group (n = 52) and sertraline control group (n = 24). For the BoNT/A group, BoNT/A was injected into the frowning muscle, depressor muscle, occipital frontalis muscle, lateral canthus, and bilateral temporal region at 20 sites. Five units per site and a total of 100 units of BoNT/A were given. Patients in the sertraline control group were medicated with sertraline 50–200 mg (114.58 ± 52.08 mg) per day. Depression was assessed by the 17‐item Hamilton Depression Scale (HAMD‐17), 14‐item Hamilton Anxiety Scale (HAMA‐14), Self‐rating Depression Scale (SDS), and Self‐rating Anxiety Scale (SAS). All participants were followed up for 12 weeks.

Results

Scores of HAMD, HAMA, SDS, and SAS decreased significantly in both BoNT/A and sertraline groups after treatment for 12 weeks. Overall, there were no differences in decreased magnitude between the two groups (p > .05). The HAMA, SDS, and SAS results showed that the onset time of BoNT/A was earlier than that of sertraline. Side effects rates were 15.38% for BoNT/A and 33.33% for sertraline.

Conclusion

This study demonstrated significant antidepressant effects of BoNT/A. The efficacy of BoNT/A was comparable with established antidepressant sertraline. The onset time of BoNT/A was earlier than sertraline, and the proportion of side effects was less than sertraline. Therefore, BoNT/A could be a safe and effective option for the treatment of depression.
Strategic ambidexterity in green product innovation: Obstacles and implications
Authors: Peters Kristian , Buijs Paul
Published: August 2021

Scholars and managers routinely point to various uncertainties in explaining why manufacturing firms struggle with green product innovation and why green product innovation is different from conventional product innovation. This explanation is yet unsatisfactory as a thorough understanding of how a firm deals with uncertainty exists in conventional innovation literature. At the same time, there is a lack of agreement and understanding how a firm's capabilities shape its green product innovation practices, which could contribute to this gap. Based on a case study at five multinational manufacturers, this paper sets out to contribute to the capability perspective on green product innovation by understanding how manufacturing firms learn and innovate in order to make and sell greener products. A powerful and favored way for firms to learn and innovate under uncertainty is through strategic ambidexterity. With this learning strategy, firms rely on existing competences in one area (exploitation) while they simultaneously explore new competences in another area (exploration). However, our results show that strategic ambidexterity is oftentimes unachievable due to several factors, and as result, firms are forced to choose between a highly uncertain and risky alternative strategy and a more conservative but also less green strategy based on exploitation only, which is often the preferred option. In addition, our findings shed a new light on the role of uncertainty in green product innovation as we conclude that uncertainties firms face in green product innovation are indeed abundant, but are fundamentally not new nor caused by external sources only.
Study on the Composition and Physiological Activity of the Essential Oils and Extracts of Cinnamomum camphora Fruit
Authors: Lv Chenyuan , Hao Linyu , Cui Xinang , Yi Fengping , Su Chang
Published: August 2021

Supercritical carbon dioxide (SC‐CO2), hydrodistillation (HDO), ethanol extraction (EE), and petroleum ether extraction (PE) were used to extract the essential oil and extracts of Cinnamomum camphora fruit in this study. Gas chromatography‐mass spectrometry was used to identify the volatile components of essential oils and extracts, and 63 compounds were identified. 2,2‐Diphenyl‐1‐picrylhydrazyl (DPPH) and 2,2′‐azinobis(3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS) radical scavenging assay and Ferric reducing ability of plasma (FRAP) assays and the inhibition experiment of bacteria and fungi (Staphylococcus aureus (S. aureus), Hay bacillus (H. bacillus), Escherichia coli (E. coli), Aspergillus niger (A. niger), Candida albicans (C. albicans)) showed these essential oils and extracts indicated antioxidant and antibacterial activities. S. aureus was the most sensitive to the essential oil (MIC=0.08 mg/ml). Combined with the Brine Shrimp Lethality Test (BSLT) experiment, HDO (LD50=68.21 μg/ml) was considered to have the most potential natural preservative. Subsequently, the inhibitory mechanism of HDO on bacteria and fungi was explored through extracellular conductivity and SEM, and the possibility of HDO to preserve the freshness of bananas was verified through banana shelf‐life experiments. The results suggested these essential oils and extracts of Cinnamomum camphora fruit indicated effectively inhibit the growth of microorganisms on the surface of bananas, extend the shelf‐life, and have the potential to become a natural antiseptic ingredient.
Simultaneous separation of atenolol enantiomers and its acid/alkaline degradation impurities on mixed‐mode chiral ligand exchange stationary phases
Authors: Bai Hui , Chen Lei
Published: August 2021

Simultaneous separation of the enantiomer and impurities is a huge challenge for the quality control of the chiral drug. In this work, mixed‐mode chiral ligand exchange stationary phases (CSPs) modified by octyl and sulfhydryl ligands were prepared by vapor deposition and click chemistry methods. Qualitative and quantitative determination of the prepared CSPs were achieved by Fourier transform infrared spectroscopy, solid‐state 13C CP/MAS NMR, and elemental analysis. The chiral resolution of CSPs was investigated through a comprehensively chromatographic evaluation of various racemates. Besides, the thermodynamic experiment was carried out to elucidate the contribution of hydrophobic ligand to the improvement of chiral recognition and selectivity. Atenolol and its degradation products were analyzed on the synthesized CSPs and compared with the commercial chiral column. A good separation of atenolol enantiomers from its acid and alkaline degradation impurities was simultaneously achieved on the C8/L‐Hypro CSP. This new CSP is expected to have more applications in the quality control of other chiral drugs.
Accelerating high‐order stencils on GPUs
Authors: Sai Ryuichi , Mellor‐Crummey John , Meng Xiaozhu , Zhou Keren , Araya‐Polo Mauricio , Meng Jie
Published: August 2021

Finite‐difference methods based on high‐order stencils are commonly used for modeling of seismic wave propagation, weather forecasting, computational fluid dynamics, convolutional neural networks, and others. Nowadays, the community commonly employs graphics processing units (GPUs) to accelerate such stencil computations. As a result, knowing how to write efficient stencil computations for GPUs is of significant interest. While high‐performance, low‐order stencils on GPUs have been studied extensively in the literature, not all proposed approaches work well for high‐order stencils. Furthermore, coping with boundary conditions used with stencils for seismic modeling makes it challenging to efficiently exploit thread‐level parallelism on GPUs. In this article, we describe several implementations of a 25‐point stencil. We evaluate our stencil code shapes, memory hierarchy usage, data access patterns, and other performance attributes on several modern GPUs and compare them with machine rooflines. On average, our top‐performing kernels achieve six times the performance of a 25‐point stencil code developed in C and mapped to GPUs using OpenACC. Several of our implementations have excellent performance portability across multiple generations of both NVIDIA and AMD GPUs.
Metal‐Organic‐Framework Based Functional Materials for Uranium Recovery: Performance Optimization and Structure/Functionality‐Activity Relationships
Authors: Zhao Zhiwei , Cheng Gong , Zhang Yizhe , Han Bing , Wang Xiangke
Published: August 2021

Uranium recovery has profound significance in both uranium resource acquisition and pollution treatment. In recent years, metal‐organic frameworks (MOFs) have attracted much attention as potential uranium adsorbents owing to their tunable structural topology and designable functionalities. This review explores the research progress in representative classic MOFs (MIL‐101, UiO‐66, ZIF‐8/ZIF‐67) and other advanced MOF‐based materials for efficient uranium extraction in aqueous or seawater environments. The uranium uptake mechanism of the MOF‐based materials is refined, and the structure/functionality‐property relationship is further systematically elucidated. By summarizing the typical functionalization and structure design methods, the performance improvement strategies for MOF‐based adsorbents are emphasized. Finally, the present challenges and potential opportunities are proposed for the breakthrough of high‐performance MOF‐based materials in uranium extraction.
Longitudinal Data Discontinuity in Electronic Health Records and Consequences for Medication Effectiveness Studies
Authors: Joshua Lin Kueiyu , Jin Yinzhu , Gagne Joshua , Glynn Robert J. , Murphy Shawn N. , Tong Angela , Schneeweiss Sebastian
Published: August 2021

Electronic health record (EHR) discontinuity (i.e., receiving care outside of the study EHR system), can lead to information bias in EHR‐based real‐world evidence (RWE) studies. An algorithm has been previously developed to identify patients with high EHR‐continuity. We sought to assess whether applying this algorithm to patient selection for inclusion can reduce bias caused by data‐discontinuity in four RWE examples. Among Medicare beneficiaries aged >=65 years from 2007 to 2014, we established 4 cohorts assessing drug effects on short‐term or long‐term outcomes, respectively. We linked claims data with two US EHR systems and calculated %bias of the multivariable‐adjusted effect estimates based on only EHR vs. linked EHR‐claims data because the linked data capture medical information recorded outside of the study EHR. Our study cohort included 77,288 patients in system 1 and 60,309 in system 2. We found the subcohort in the lowest quartile of EHR‐continuity captured 72–81% of the short‐term and only 21–31% of the long‐term outcome events, leading to %bias of 6–99% for the short‐term and 62–112% for the long‐term outcome examples. This trend appeared to be more pronounced in the example using a nonuser comparison rather than an active comparison. We did not find significant treatment effect heterogeneity by EHR‐continuity for most subgroups across empirical examples. In EHR‐based RWE studies, investigators may consider excluding patients with low algorithm‐predicted EHR‐continuity as the EHR data capture relatively few of their actual outcomes, and treatment effect estimates in these patients may be unreliable.
Enhanced collision resolution and throughput analysis for the 802.11 distributed coordination function
Authors: Kobbaey Thaeer , Hamzaoui Raouf , Ahmad Shakeel , Al‐Fayoumi Mustafa , Thomos Nikolaos
Published: August 2021

The IEEE 802 standards rely on the distributed coordination function (DCF) as the fundamental medium access control method. DCF uses the binary exponential backoff (BEB) algorithm to regulate channel access. The backoff time determined by BEB depends on a contention window (CW) whose size is doubled if a station suffers a collision and reset to its minimum value after a successful transmission. Doubling the size of CW reduces channel access time, which decreases the throughput. Resetting it to its minimum value harms fairness since the station will have a better chance of accessing the channel compared to stations that suffered a collision. We propose an algorithm that addresses collisions without instantly increasing the CW size. Our algorithm aims to reduce the collision probability without affecting the channel access time and delay. We present extensive simulations for fixed and mobile scenarios. The results show that, on average, our algorithm outperforms BEB in terms of throughput and fairness. Compared to exponential increase exponential decrease (EIED), our algorithm improves, on average, throughput and delay performance. We also propose analytical models for BEB, EIED and our algorithm. Our models extend Bianchi's popular Markov chain‐based model by using a collision probability that is dependent on the station transmission history. Our models provide a better estimation of the probability that a station transmits in a random slot time, which allows a more accurate throughput analysis. Using our models, we show that both the saturation throughput and maximum throughput of our algorithm are higher than those of BEB and EIED.
Cloning capacity helps seeds of Garcinia xanthochymus counter animal predation
Authors: Wang Zhen‐yu , Cao Lin , Yan Chuan , Niu Yu‐da , Chong Kang , Zhang Zhi‐bin
Published: August 2021

Seed predators have the potential to act as agents of natural selection that influence seed traits and seed fates, which in turn affect the whole plant population dynamic. Accordingly, plants deploy a variety of mechanisms (e.g., resistance and tolerance strategies) to lessen the impact of predation on seed crop or on an individual seed. In this study, we described a novel mechanism, seed cloning strategy, in a tropical plant species in countering animal predation. By conducting field‐ and laboratory‐based germination experiments, we found that both rodent damaged and artificially damaged seed fragments of a large‐seeded tree Garcinia xanthochymus (Clusiaceae) could successfully germinate and establish as seedlings. Tissue culture experiments revealed that G. xanthochymus has no endosperm in seeds, and its seed fragments own strong capacity of differentiation and cloning. Seed damage negatively affected seedling growth and germination, but the seed germination rate was remarkably high. Our study suggests that, seed cloning capacity, adopted by the large‐seeded tree G. xanthochymus may act as a novel strategy counteract for seed predation and would play a significant role in stabilizing the mutualism between plant and animals.
Bifunctional Cs−Au/Co3O4 (Basic and Redox)‐Catalyzed Oxidative Synthesis of Aromatic Azo Compounds from Anilines
Authors: Oseghale Charles O. , Fapojuwo Dele Peter , Alimi Oyekunle Azeez , Akinnawo Christianah Aarinola , Mogudi Batsile M. , Onisuru Oluwatayo Racheal , Meijboom Reinout
Published: August 2021

An eco‐friendly alkali‐promoted (Cs−Au/Co3O4) catalyst, with redox and basic properties for the oxidative dehydrogenative coupling of anilines to symmetrical and unsymmetrical aromatic azo compounds, was developed. We realized a base additive‐ and molecular O2 oxidant‐free process (using air), with reasonable reusability of the catalyst achieved under milder reaction conditions. Notably, the enhanced catalytic activity was also linked to the increased basic site concentration, low reduction temperatures, and the effect of lattice oxygen on the nanomaterials. The increased basic strength of the cation‐promoted catalyst improved the electron density of the active Au species, resulting in higher yields of the desired aromatic azo compounds.
Machine learning‐based automated fungal cell counting under a complicated background with ilastik and ImageJ
Authors: Li Chenxi , Ma Xiaoyu , Deng Jing , Li Jiajia , Liu Yanjie , Zhu Xudong , Liu Jin , Zhang Ping
Published: August 2021

Measuring the concentration and viability of fungal cells is an important and fundamental procedure in scientific research and industrial fermentation. In consideration of the drawbacks of manual cell counting, large quantities of fungal cells require methods that provide easy, objective and reproducible high‐throughput calculations, especially for samples in complicated backgrounds. To answer this challenge, we explored and developed an easy‐to‐use fungal cell counting pipeline that combined the machine learning‐based ilastik tool with the freeware ImageJ, as well as a conventional photomicroscope. Briefly, learning from labels provided by the user, ilastik performs segmentation and classification automatically in batch processing mode and thus discriminates fungal cells from complex backgrounds. The files processed through ilastik can be recognized by ImageJ, which can compute the numeric results with the macro ‘Fungal Cell Counter’. Taking the yeast Cryptococccus deneoformans and the filamentous fungus Pestalotiopsis microspora as examples, we observed that the customizable software algorithm reduced inter‐operator errors significantly and achieved accurate and objective results, while manual counting with a haemocytometer exhibited some errors between repeats and required more time. In summary, a convenient, rapid, reproducible and extremely low‐cost method to count yeast cells and fungal spores is described here, which can be applied to multiple kinds of eucaryotic microorganisms in genetics, cell biology and industrial fermentation.
OAAE: Optimized adaptive anomaly detection ensemble—Base model boosting by parameter optimization
Authors: Bii Joash Kiprotich , Rimiru Richard , Mwangi Ronald Waweru
Published: August 2021

Irregular data or anomalies may occur due to human error, miscalculation, or malicious system behavior. The detection of anomalies is a difficult task that requires the use of multiple strategic methods and models. The ideal detection model should assess the strengths and optimize the results of its base models before making final decisions. This task of optimizing the results of the base models contributes to the generation of more accurate results overall. This work presents an optimized adaptive anomaly detection ensemble using heterogeneous algorithms. In the first stage, it adaptively boosts the outcomes of preceding models by weighting their decisions and finding high‐performance ones, and in the second stage, it optimizes the base models by score margin maximization, which enlarges the contrast between the scores of the anomalies and other data prior to fusion to improve detection accuracy. To validate the model, baselines and test results from 10 benchmark datasets are compared. To assess its effectiveness in terms of distinguishing anomalies, the proposed model is tested and evaluated. The analyzed data are presented as cross‐tabulations, with detailed explanations and interpretations. The experiments show an improvement in results even when the least of anomalies (single cases up to 10%) are used.
Flame whirling characteristics of fire in a room with vent
Authors: Fan Wei Peng , Wang Ya Wei , Gao Ye , Chow Wan Ki , Lai Joseph Hung Kit , Chow Cheuk Lun , Cheng Chi Honn
Published: August 2021

Velocity distribution and motion of a whirling flame in a room fire with vent were studied analytically in this article. Using Rankine vortex model, whirling flame models with and without decay of the rotation velocity were established. The whirling flame model and the cross‐wind velocity boundary conditions were used to study the velocity distribution of the rotating flame under the action of side wind. When there is a linear velocity gradient in the lateral wind, the whirling flame still revolves around the same axis at different heights in the model without attenuation of rotation velocity, but the axis becomes tilted. In the rotation velocity attenuation model, the axis of the whirling flame changes from a straight line to a curve, and the change of the shape of the whirling flame is related to the flame height, the rotation angular velocity, and the maximum wind velocity. Under the assumption of Rankine vortex model with the same rotation angular velocity, the uniform lateral wind and lateral wind with linear velocity gradient can only affect the position and shape of the whirling flame axis but not change the rotation angular velocity.
An assessment of large‐scale flood modelling based on LiDAR data
Authors: Choné Guénolé , Biron Pascale M. , Buffin‐Bélanger Thomas , Mazgareanu Iulia , Neal Jeff C. , Sampson Christopher C.
Published: August 2021

Large‐scale flood modelling approaches designed for regional to continental scales usually rely on relatively simple assumptions to represent the potentially highly complex river bathymetry at the watershed scale based on digital elevation models (DEMs) with a resolution in the range of 25–30 m. Here, high‐resolution (1 m) LiDAR DEMs are employed to present a novel large‐scale methodology using a more realistic estimation of bathymetry based on hydrogeomorphological GIS tools to extract water surface slope. The large‐scale 1D/2D flood model LISFLOOD‐FP is applied to validate the simulated flood levels using detailed water level data in four different watersheds in Quebec (Canada), including continuous profiles over extensive distances measured with the HydroBall technology. A GIS‐automated procedure allows to obtain the average width required to run LISFLOOD‐FP. The GIS‐automated procedure to estimate bathymetry from LiDAR water surface data uses a hydraulic inverse problem based on discharge at the time of acquisition of LiDAR data. A tiling approach, allowing several small independent hydraulic simulations to cover an entire watershed, greatly improves processing time to simulate large watersheds with a 10‐m resampled LiDAR DEM. Results show significant improvements to large‐scale flood modelling at the watershed scale with standard deviation in the range of 0.30 m and an average fit of around 90%. The main advantage of the proposed approach is to avoid the need to collect expensive bathymetry data to efficiently and accurately simulate flood levels over extensive areas.
Feature‐versus deep learning‐based approaches for the automated detection of brain tumor with magnetic resonance images: A comparative study
Authors: Raghavendra U. , Gudigar Anjan , Rao Tejaswi N. , Rajinikanth V. , Ciaccio Edward J. , Yeong Chai Hong , Satapathy Suresh Chandra , Molinari Filippo , Acharya U. Rajendra
Published: August 2021

The public health is significantly affected by development of brain tumors in human patients. Glioblastoma (GBM) is a relatively common, malignant form of brain tumor, which is currently challenging to treat and cure. In contrast, Lower Grade Gliomas (LGGs) originate from glial cells and can mostly be treated and cured in the initial stages if they are detected early. A computer‐aided diagnostics (CAD) tool may help to test for the presence and extent of any such tumor, and thus can be assistive in the clinical diagnostic process. Herein, we compare handcrafted versus non‐handcrafted features‐based CAD to characterize GBM and LGG. Our machine learning‐based handcrafted model uses quantitative techniques of enhanced elongated quinary patterns and entropies analysis. We have also developed a non‐handcrafted deep learning model using Visual Geometry Group‐16 architecture for segregating GBM and LGG subjects results in 94.25% accuracy using k‐nearest neighbor classifier.
Edge and anomaly detection of brain magnetic resonance images in a distributed environment
Authors: Chaoui Cherifa Nabila , Ghomari Abdelghani , Meftah Boudjelal
Published: August 2021

Today, all scientific advancements related to medical image processing aim to develop a unique computational model. The latter will mimic the way humans interpret images. In the present paper, we propose a formal approach biologically inspired by the human natural vision system’s mechanisms. To that end, we use the spiking neural network model for edge detection in brain MRI images. The optimal results provided by this last step increase performance, and facilitate the process of anomaly detection. For that, we have developed a tool called Edge and Anomaly Detection of Brain MRI Images in Distributed Environment (EADBMIDE). It is tested on an MRI brain tumour dataset, which shows the effectiveness of the proposed methods. Each stage in this tool is compared separately with similar approaches in the literature. The obtained results show a significant improvement, making this a recommended tool for edge and anomaly detection methods in MRI images.
Direct synthesis of 3,5‐diaryl‐1,2,4‐oxadiazoles using 1‐(2‐oxo‐2‐arylethyl)pyridin‐1‐iums with benzamidines
Authors: Zhang Yue , Wu Chengjun , Wan Xinyi , Wang Cunde
Published: August 2021

An efficient domino protocol for the synthesis of 1,2,4‐oxadiazole derivatives from readily available 1‐(2‐oxo‐2‐arylethyl)pyridin‐1‐iums and amidine hydrochlorides was developed. In this practical approach, N‐acyl amidine precursors were formed firstly via a simple nucleophilic substitution, without the purification of N‐acylamidine intermediates, and the following intramolecularly dehydrative cyclization gave 1,2,4‐oxadiazole derivatives in the presence of I2/K2CO3/DMSO, which exhibited excellent functional group tolerance and proceeded under simple experimental conditions.
Histone methyltransferase Ezh2 negatively regulates NK cell terminal maturation and function
Authors: Yu Minghang , Su Ziyang , Huang Xuefeng , Zhou Yujie , Zhang Xulong , Wang Bingbing , Wang Zihan , Liu Yi , Xing Nianzeng , Xia Miaoran , Wang Xi
Published: August 2021

NK cells are innate lymphoid cells that play important roles in tumor eradication and viral clearance. We previously found that deletion or inhibition of the histone methyltransferase Ezh2 (enhancer of zeste homolog 2) in hematopoietic stem and progenitor cells (HSPCs) from both mice and humans enhanced the commitment and cytotoxicity of NK cells to tumor cells. This study tested the hypothesis that inhibiting Ezh2, especially in NK lineage cells, could also affect NK cell development and function. We crossed Ezh2fl/fl mice with Ncr1iCre mice to delete the Ezh2 gene in immature NK cells and downstream progeny. Ezh2 deficiency increased the total number of NK cells and promoted NK cell terminal differentiation, as the percentages of the most mature CD27–CD11b+ subsets were increased. The NK cell cytotoxicity against tumor cells in vitro was enhanced, with increased degranulation and IFN-γ production. In addition, during the process of human NK cells differentiating from HSPCs, inhibiting EZH2 catalytic activity at day 14 (when NK lineage commitment began) also resulted in increased proportions of mature NK cells and cytotoxicity. Furthermore, RNA-seq and CUT&RUN-qPCR assays showed that the effects of Ezh2 may be based on its direct modulation of the expression of the transcription factor Pbx1 (pre-B-cell leukemia transcription factor 1), which has been reported to promote NK cell development. In summary, we demonstrate that Ezh2 is a negative regulator of NK cell terminal maturation and function.
Using UAV image data to monitor the effects of different nitrogen application rates on tea quality
Authors: Luo Danni , Gao Yuan , Wang Yu , Shi Yujie , Chen Sizhou , Ding Zhaotang , Fan Kai
Published: August 2021

BACKGROUND

Accurate and efficient evaluation of the effect of nitrogen application rate on tea quality is of great significance for nitrogen management in a tea garden. However, previous methods were all through soil or leaf sampling, using biochemical methods for laboratory testing. These methods are not only less one‐time detection samples, but also time‐consuming, laborious and inefficient. Therefore, the development of fast, efficient and non‐destructive diagnostic methods is an important goal in this field.

RESULTS

We obtained spectral information on the tea canopy using a multispectral camera carried by an unmanned aerial vehicle (UAV), and extracted the average DN value of the experimental plot by environmental visual imagery (ENVI); we finally obtained 28 spectral parameters. By analyzing the correlation between spectral parameters and ground parameters measured synchronously, five spectral parameters with high correlation were selected. Finally, the prediction models of tea nitrogen, polyphenol and amino acid content were established by using support vector machine (SVM), partial least squares and backpropagation neural network. Through modeling comparison and coefficient verification, the results show that the ground parameters measured in the laboratory were in good agreement with the results estimated by the model. The SVM model had the best performance in predicting nitrogen and tea polyphenol content, with R2 = 0.7583 and 0.7533, root mean square error of prediction (RMSEP) = 0.4086 and 0.3392, and normalized RMSEP (NRMSEP) = 1.23 and 1.28, respectively. The partial least squares regression model had the best performance in predicting amino acid content, with R2 = 0.7597, RMSEP = 0.1176 and NRMSEP = 4.10.

CONCLUSION

The results show that the model based on UAV image data and machine learning algorithm can effectively detect the main biochemical components of the tea plant, which provides an important basis for tea garden management. © 2021 Society of Chemical Industry.
Total elbow arthroplasty for tumors of the distal humerus and elbow
Authors: Kruckeberg Bradley M. , Lee Dustin R. , Barlow Jonathan D. , Morrey Mark E. , Rose Peter S. , Sanchez‐Sotelo Joaquin , Houdek Matthew T.
Published: August 2021

Introduction

The elbow is a rare location for primary and metastatic tumors in the upper extremity. The goal of reconstruction is to provide painless motion and stability for hand function. Total elbow arthroplasty (TEA) is commonly utilized, with either off‐the‐self components, modular segmental endoprosthesis, or allograft‐prosthesis composites (APC). The purpose of this study was to analyze and compare commonly utilized elbow reconstructions and report outcomes of (1) patient function and (2) implant survival and complications.

Methods

We reviewed 33 patients (18 females and 15 males) undergoing elbow arthroplasty for reconstruction of an underlying oncologic process including linked TEA (n = 22, 67%), APC (n = 9, 27%), and endoprosthesis (n = 2, 6%). The most common indication was metastatic disease (n = 17, 52%), with 24 patients (73%) presenting with a pathologic fracture.

Results

Five‐year implant survival was following elbow reconstruction was 88%. The mean most recent Mayo Elbow Performance Score and Musculoskeletal Tumor Society Score were 84 ± 18 and 78 ± 15%. Postoperative complications occurred in 15 elbows (45%), most commonly periprosthetic fracture (n = 5, 15%), leading to reoperation in six elbows (18%).

Conclusion

Although elbow arthroplasty is associated with a high incidence of complications, it provides a stable platform for upper extremity function in patients with oncologic processes of the elbow.
Impact of Aortic Diameter Measurements at Three Anatomical Landmarks on Left Ventricular Output Calculation in Neonates
Authors: Ficial Benjamim , Bonafiglia Elena , Gangemi Antonella , Clemente Maria , Cappelleri Alessia , Corsini Iuri , Biban Paolo
Published: August 2021

Objectives

To assess reproducibility and accuracy of left ventricular output (LVO) quantifications in neonates, when left ventricular outflow tract diameter (LVOTD) was measured at the hinges of the aortic valve (AV), at the aortic sinus (AS), and at the sinotubular junction (STJ).

Methods

This was an observational study. In the first cohort of very preterm neonates, we assessed intraobserver and interobserver repeatability of LVOTD measured at the AV, AS, and STJ and of the corresponding LVO. In the second cohort of older neonates, we compared paired LVO measurements by echo and magnetic resonance imaging (MRI).

Results

In the first cohort of 48 neonates, mean (standard deviation) weight and age at scan were 1046 (302) g and 28.1 (2.7) weeks. Interobserver bias (95% limits of agreement [LOA]) for LVOTD at the AV, AS, and STJ was 0 (−0.3 to 0.3) mm, 0 (−0.7 to 0.7) mm, and 0 (−0.8 to 0.7) mm, respectively. Interobserver bias (95% LOA) for the corresponding LVO was −1.3 (−31 to 33) ml/kg/min, −0.5 (−88 to 87) ml/kg/min, and −7.2 (−83 to 69) ml/kg/min, respectively. In the second cohort of 10 neonates, median (range) weight and age at scan were 1942 (970–3640) g and 37.2 (31.7–39.8) weeks. LVO measured at the AV showed stronger agreement with MRI: bias (LOA) −10.6 (−74 to 52) ml/kg/min, compared to LVO measured at AS and STJ: 194 (−0.5 to 388) ml/kg/min and 43 (−72 to 159) ml/kg/min respectively.

Conclusions

Reproducibility and accuracy of LVO quantification by echo were better when aortic diameter was measured at AV.
Contrast‐Enhanced Ultrasound for Differentiation Between Poorly Differentiated Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma
Authors: Guo Huan‐Ling , Zheng Xin , Cheng Mei‐Qing , Zeng Dan , Huang Hui , Xie Xiao‐Yan , Lu Ming‐De , Kuang Ming , Wang Wei , Xian Meng‐Fei , Chen Li‐Da
Published: August 2021

Purpose

To evaluate the diagnostic performance of LR‐5 for diagnosing poorly differentiated hepatocellular carcinoma (p‐HCC). To build a contrast‐enhanced ultrasound (CEUS) signature for improving the differential diagnostic performance between p‐HCC and intrahepatic cholangiocarcinoma (ICC).

Methods

The B‐mode ultrasound (BUS) and CEUS features of 60 p‐HCCs and 56 ICCs were retrospectively analyzed. The CEUS LI‐RADS category was assigned according to CEUS LI‐RADS v2017. A diagnostic CEUS signature was built based on the independent significant features. An ultrasound (US) signature combining both BUS and CEUS features was also built. The diagnostic performances of the CEUS signature, US signature, and LR‐5 were evaluated by receiver operating characteristic (ROC) analysis.

Results

One (1.7%) p‐HCC and 26 (46.4%) ICC patients presented cholangiectasis or cholangiolithiasis (P < .001). Fifty‐four (90.0%) p‐HCCs and 8 (14.3%) ICCs showed clear boundaries in the artery phase (P < .001). The washout times of p‐HCCs and ICCs were 81.0 ± 42.5 s and 34.7 ± 8.6 s, respectively (P < .001). The AUC, sensitivity, and specificity of the CEUS signature, US signature, and LR‐5 were 0.955, 91.67%, and 90.57% versus 0.976, 96.67%, and 92.45% versus 0.758, 51.67%, and 100%, respectively. The AUC and sensitivity of CEUS LI‐RADS were much lower than those of the CEUS and US signatures (P < .001).

Conclusion

LR‐5 had high specificity but low sensitivity in diagnosing p‐HCC. When the washout time and tumor boundary were included in the CEUS signature, the sensitivity and AUC were remarkably increased in the differentiation between p‐HCC and ICC.
Monte Carlo Assisted FTIR Spectroscopy: A Python Tool for the Determination of the Constituents in Blended Biopolymer Samples
Authors: Souza Fernando Gomes , Cunha Cláudia Duarte , Pereira Emiliane Daher , Dias Diogo Simas Bernardes , Pal Kaushik , Pereira Michelle Colão , Silva Rebecca Alves
Published: August 2021

A massive number of biopolymers and complex polymer blends are being developed every day. One of the significant challenges related to these materials is their characterization. In more specific terms, estimating the composition of polymeric mixtures is a substantial challenge for the technologist, who must understand the nuances of the material's composition for its proper application. Thus, this work develops a Python code capable of handling the composition analysis using the FTIR spectra of some biopolymers found in the literature. Through the Monte Carlo method associated with the Mixture Rule, these spectra are combined, generating a myriad of signals referring to different compositions. These signals are compared with the one from the FTIR spectrum of the mixture, allowing the root‐mean‐square error (RMSE) calculation. Finally, minimizing the RMSE value leads to the final composition of the material, which is presented and saved in a text file.
Geopolymer Microparticles as Up‐and‐Coming H2S Sorbers
Authors: Maranhão Fabíola da Silveira , Almeida Thuanny Moraes , de Souza Fernando Gomes , Batista Daniela , de Carvalho Felipe Ferreira , Pal Kaushik , Thomas Sabu
Published: August 2021

Geopolymers are materials composed of aluminosilicates, which upon activation by the alkaline solution, form repeating units, being classified as inorganic polymers. Geopolymers have gained prominence due to obtaining the raw material that can be natural or residual, the ease of production, and cost‐effective. These materials are widely used in civil construction for the replacement of Portland cement and also in the environmental area for the remediation of toxic compounds. However, there is a lack in the literature about the applications of these materials. Thus, this work deals with geopolymers for the sorption of hydrogen sulfide gas.
Magnetic Porous Geopolymer: A Cheaper and Efficient Environmental Tool for Heavy Metal Sorption
Authors: Maranhão Fabíola Silveira , de Souza Junior Fernando Gomes , Filho Sérgio Thode , de Oliveira Athayde Bryan Henrique , de Carvalho Felipe Ferreira , Lino Adam , Malm Olaf
Published: August 2021

Sorption of heavy metals is a crucial controller method for environmental pollution. Contamination by heavy metals is one of the most critical and discussed environmental issue nowadays that fits in the context of bioaccumulation. Some examples of these contaminants are lead, cadmium, and chromium. In order to avoid increasing the level of these contaminants in rainwater networks, the Brazilian Council of Environment (CONAMA) establishes that it is essential that industries that produce effluents remove these metals before returning the effluent to the network. Given this, a new technology is proposed for the removal of heavy metals. A magnetic nanocomposite is produced by adding maghemite nanoparticles to an aluminosilicate matrix and subjected to heavy metal‐contaminated effluents to sorption through this material. In order to evaluate the efficiency of removal of heavy metals by aluminosilicates, the effluents are analyzed by atomic absorption spectroscopy, and the results show a 99% sorption capacity. Finally, lethality tests, using Artemia salina, are performed. The best results are from the chromium and lead absorption tests.