bluuebunny/crossref_metadata_2025_split huggingface dataset:
Legionella monitoring in the New York City water distribution system 2017 to 2019
Authors: Omoregie Enoma , Szczerba Adam , Novak John , Rubinstein Inessa , Chuang Yayu , Wu Jing , Wang Jade , Kretz Cecilia , Hughes Scott , Capetanakis Aspa , Freud Salome , Rakeman Jennifer L. 
Published: March 2022

AbstractThis study investigated prevalence of Legionella in the New York City (NYC) water distribution system using International Organization for Standardization 11731:2017 and Legiolert (IDEXX, USA) culture‐based methods and polymerase chain reaction. All water samples met applicable Environmental Protection Agency and New York State water quality guidelines. Eighty‐five percent (448/528) of water samples were positive for Legionella DNA. Despite this, Legionella bacteria were detected in only 2.8% (15/544) of water samples using culture methods. All Legionella pneumophila culture‐positive samples were recovered from a single distribution site, which was undergoing a street reconstruction project. The site had conditions indicative of stagnation, and an adjacent building's service line was periodically backflowing. These factors indicate that L. pneumophila may have been introduced from an external source. The lack of culturable Legionella in samples with detectable Legionella DNA suggests that NYC practices are sufficient to protect against culturable Legionella in NYC's water distribution system.
Translational potential of hiPSCs in predictive modeling of heart development and disease
Authors: Mansfield Corrin , Zhao Ming‐Tao , Basu Madhumita 
Published: March 2022

AbstractCongenital heart disease (CHD) represents a major class of birth defects worldwide and is associated with cardiac malformations that often require surgical intervention immediately after birth. Despite the intense efforts from multicentric genome/exome sequencing studies that have identified several genetic variants, the etiology of CHD remains diverse and often unknown. Genetically modified animal models with candidate gene deficiencies continue to provide novel molecular insights that are responsible for fetal cardiac development. However, the past decade has seen remarkable advances in the field of human induced pluripotent stem cell (hiPSC)‐based disease modeling approaches to better understand the development of CHD and discover novel preventative therapies. The iPSCs are derived from reprogramming of differentiated somatic cells to an embryonic‐like pluripotent state via overexpression of key transcription factors. In this review, we describe how differentiation of hiPSCs to specialized cardiac cellular identities facilitates our understanding of the development and pathogenesis of CHD subtypes. We summarize the molecular and functional characterization of hiPSC‐derived differentiated cells in support of normal cardiogenesis, those that go awry in CHD and other heart diseases. We illustrate how stem cell‐based disease modeling enables scientists to dissect the molecular mechanisms of cell–cell interactions underlying CHD. We highlight the current state of hiPSC‐based studies that are in the verge of translating into clinical trials. We also address limitations including hiPSC‐model reproducibility and scalability and differentiation methods leading to cellular heterogeneity. Last, we provide future perspective on exploiting the potential of hiPSC technology as a predictive model for patient‐specific CHD, screening pharmaceuticals, and provide a source for cell‐based personalized medicine. In combination with existing clinical and animal model studies, data obtained from hiPSCs will yield further understanding of oligogenic, gene–environment interaction, pathophysiology, and management for CHD and other genetic cardiac disorders.
A comprehensive performance measurement framework for business incubation centres: Empirical evidence in an Irish context
Authors: Azadnia Amir Hossein , Stephens Simon , Ghadimi Pezhman , Onofrei George 
Published: March 2022

AbstractDuring the last 20 years, there has been an increased interest among academics and practitioners in the area of business incubation. However, limited attention has been devoted to developing a comprehensive framework that can measure business incubators' performances. Therefore, there is an urgent need for an appropriate, robust and useable performance framework. In this paper, we present a comprehensive framework using a weighted fuzzy inference system for business incubation centres' (BIC) performance measurement. The proposed approach utilises the input of a Delphi panel to identify criteria and subcriteria. Then a fuzzy analytic hierarchy process is used to weigh the criteria. Subsequently, a weighted fuzzy inference system is developed and applied to provide results based on the identified criteria and subcriteria. To show the proficiency and applicability of the proposed framework, a case study of Irish BICs is applied. The comprehensive performance measurement framework presented in this paper provides for accurate evaluation and monitoring across six criteria. The six criteria are facilities and infrastructure; clients; networking and marketing; products and services; finance; and human capital. The results show that although most of the BICs focus on facilities and infrastructure, there is a need to concentrate more on factors such as networking, marketing and finance. The detailed approach presented in this paper can be used by academics and practitioners who wish to apply fuzzy inference systems to performance measurement. In addition, the results from our pilot can be used by BIC managers and policymakers to improve performance.
Optimization of the Extraction of Total Phenols from Medicago sativa and Its Antioxidant Capacity
Authors: Wu Fang , Shi Shangli , Liu Chang , Zhang Huihui , Li Xinglong , Li Zili 
Published: March 2022

AbstractThe phenolic compounds from alfalfa (Medicago sativa L.) are used as antioxidants and in native medicine. They play an indispensable role in defense and signal transduction of the plant under stress conditions. This exploration of the optimal extraction parameters of the total phenols from alfalfa by using ultrasonic‐assisted extraction (UAE) was aimed at providing a theoretical basis for better utilization of the total phenols in alfalfa. In this study, the effects of solvent volume fraction (A), extraction time (B), solid‐liquid ratio (C) and extraction temperature (D) on the total phenols content and the total antioxidant capacity of Medicago sativa L. WL363HQ after thrips infestation were determined through single‐factor experiments. Additionally, the extraction conditions of total phenols were optimized by using Box‐Behnken design (BBD) of response surface methodology (RSM). The results showed that the proposed model had a good fitting degree for total phenols extraction (R2=0.9564). The total phenols extraction from WL363HQ had significant relationship with solid‐liquid ratio (C) and extraction temperature (D) (P<0.05). The influence levels of the four factors on total phenols extraction were as follows: extraction temperature (D) > solid‐liquid ratio (C)>acetone volume fraction (A)>extraction time (B). The optimum extraction conditions of total phenols from WL363HQ were 50 % acetone, solid‐liquid ratio of 1 : 20 (g/mL), extraction time of 45 min and extraction temperature of 60 °C. The corresponding content and total antioxidant capacity under the optimized conditions were 15.76 mg g−1 and 28.79 μmol Trolox g−1. These results provided a new extraction method of total phenols from alfalfa.
Strategies to Reduce the On‐Target Platelet Toxicity of Bcl‐xL Inhibitors: PROTACs, SNIPERs and Prodrug‐Based Approaches
Authors: Negi Arvind , Voisin‐Chiret Anne Sophie 
Published: March 2022

AbstractApoptosis is a highly regulated cellular process. Aberration in apoptosis is a common characteristic of various disorders. Therefore, proteins involved in apoptosis are prime targets in multiple therapies. Bcl‐xL is an antiapoptotic protein. Compared to other antiapoptotic proteins, the expression of Bcl‐xL is common in solid tumors and, to an extent, in some leukemias and lymphomas. The overexpression of Bcl‐xL is also linked to survival and chemoresistance in cancer and senescent cells. Therefore, Bcl‐xL is a promising anticancer and senolytic target. Various nanomolar range Bcl‐xL inhibitors have been developed. ABT‐263 was successfully identified as a Bcl‐xL/Bcl‐2 dual inhibitor. But it failed in the clinical trial (phase‐II) because of its on‐target platelet toxicity, which also implies an essential role of Bcl‐xL protein in the survival of human platelets. Classical Bcl‐xL inhibitor designs utilize occupancy‐driven pharmacology with typical shortcomings (such as dose‐dependent off‐target and on‐target platelet toxicities). Hence, event‐driven pharmacology‐based approaches, such as proteolysis targeting chimeras (PROTACs) and SNIPERs (specific non‐genetic IAP‐based protein erasers) have been developed. The development of Bcl‐xL based PROTACs was expected, as 600 E3‐ligases are available in humans, while some (such as cereblon (CRBN), von Hippel‐Lindau (VHL)) are relatively less expressed in platelets. Therefore, E3 ligase ligand‐based Bcl‐xL PROTACs (CRBN: XZ424, XZ739; VHL: DT2216, PZ703b, 753b) showed a significant improvement in platelet therapeutic index than their parent molecules (ABT‐263: DT2216, PZ703b, 753b, XZ739, PZ15227; A1155463: XZ424). Other than their distinctive pharmacology, PROTACs are molecularly large, which limits their cell permeability and plays a role in improving their cell selectivity. We also discuss prodrug‐based approaches, such as antibody‐drug conjugates (ABBV‐155), phosphate prodrugs (APG‐1252), dendrimer conjugate (AZD0466), and glycosylated conjugates (Nav‐Gal). Studies of in‐vitro, in‐vivo, structure‐activity relationships, biophysical characterization, and status of preclinical/clinical inhibitors derived from these strategies are also discussed in the review.
Prediction of wheat quality parameters combining Raman, fluorescence, and near‐infrared spectroscopy (NIRS)
Authors: Nagel‐Held Johannes , Kaiser Leonie , Longin Carl Friedrich Horst , Hitzmann Bernd 
Published: March 2022

AbstractBackground and ObjectivesA high amount of the world wheat production is used for bread making. Due to its simplicity, wheat samples are traded based on protein content, although this is only an indirect measurement of baking quality. As direct bread quality traits like loaf volume, water absorption, and dough properties are cumbersome to measure along wheat supply chains and in wheat breeding programs, this study aims to predict directly dough properties and baking behavior by combining complementary information from near‐infrared, Raman, and fluorescence spectroscopy. Several proven data preprocessing and regression algorithms were evaluated, including partial least‐squares regression (PLSR) and genetic algorithm (GA).FindingsA highly diverse sample set of 415 wheat samples from a wheat hybrid breeding program was analyzed as whole grain, whole grain flour, and extracted flour. The best predictive models yielded a 10‐fold cross‐validated coefficient of determination R2 of .973, .873, .774, .835, .369, .447, .311, .512, .536, .723, and .715 for protein content, wet gluten, loaf volume, water uptake, elongation resistance to extension, extensibility, ratio number, extensograph energy, maltose number, plant height, and grain yield, respectively.ConclusionThe prediction accuracies are well suited for screening purposes in wheat breeding and allow better quality assessment compared to protein content along wheat supply chains.Significance and NoveltyIn this study, complementary spectroscopic techniques are combined for the first time to achieve higher prediction accuracy for a wide range of wheat quality parameters. In addition, Raman and fluorescence spectroscopy were used to predict quality data from a large sample set.
Disclosing Cyclic(Alkyl)(Amino)Carbenes as One‐Electron Reductants: Synthesis of Acyclic(Amino)(Aryl)Carbene‐Based Kekulé Diradicaloids
Authors: Maiti Avijit , Elvers Benedict J. , Bera Sachinath , Lindl Felix , Krummenacher Ivo , Ghosh Prasanta , Braunschweig Holger , Yildiz Cem B. , Schulzke Carola , Jana Anukul 
Published: March 2022

AbstractHerein, we disclose cyclic(alkyl)(amino)carbenes (CAACs) to be one‐electron reductants under the formation of a transient radical cation as indicated by EPR spectroscopy. The disclosed CAAC reducing reactivity was used to synthesize acyclic(amino)(aryl)carbene‐based Thiele and Chichibabin hydrocarbons, a new class of Kekulé diradicaloids. The results demonstrate CAACs to be potent organic reductants. Notably, the acyclic(amino)(aryl)carbene‐based Chichibabin's hydrocarbon shows an appreciable population of the triplet state at room temperature, as evidenced by both variable‐temperature NMR and EPR spectroscopy.
Ligand‐Induced Donor State Destabilisation – A New Route to Panchromatically Absorbing Cu(I) Complexes
Authors: Tran Jens H. , Traber Philipp , Seidler Bianca , Görls Helmar , Gräfe Stefanie , Schulz Martin 
Published: March 2022

AbstractThe intense absorption of light to covering a large part of the visible spectrum is highly desirable for solar energy conversion schemes. To this end, we have developed novel anionic bis(4H‐imidazolato)Cu(I) complexes (cuprates), which feature intense, panchromatic light absorption properties throughout the visible spectrum and into the NIR region with extinction coefficients up to 28,000 M−1 cm−1. Steady‐state absorption, (spectro)electrochemical and theoretical investigations reveal low energy (Vis to NIR) metal‐to‐ligand charge‐transfer absorption bands, which are a consequence of destabilized copper‐based donor states. These high‐lying copper‐based states are induced by the σ‐donation of the chelating anionic ligands, which also feature low energy acceptor states. The optical properties are reflected in very low, copper‐based oxidation potentials and three ligand‐based reduction events. These electronic features reveal a new route to panchromatically absorbing Cu(I) complexes.
Stereodivergent Desymmetrization of Simple Dicarboxylates via Branch‐Selective Pd/Cu Catalyzed Allylic Substitution
Authors: Li Guanlin , Zhao Ling , Luo Yicong , Peng Youbin , Xu Kai , Huo Xiaohong , Zhang Wanbin 
Published: March 2022

AbstractAsymmetric desymmetrization has been demonstrated to be a powerful strategy for building stereocenters in asymmetric synthesis. Herein, a Pd/Cu catalyzed asymmetric desymmetrization reaction with a simple geminal dicarboxylate is reported. A wide scope of imino esters bearing an aryl or heteroaromatic group were compatible with this bimetallic catalytic system. The reactions proceeded smoothly, giving the desired products in good yields with high to excellent regio‐, diastereo‐, and enantioselectivity (up to 20 : 1 branched:linear, >20 : 1 dr, >99 % ee). Notably, the reaction favored branched selectivity, which is unusual for the Pd‐catalyzed allylic alkylation reaction. In addition, the standard product could be easily transformed to other valuable molecules such as chiral allylic alcohols, carbamates, and organic boron compounds. Furthermore, DFT calculations were conducted to explain the origin of the branched selectivity.
Catalytic Depolymerization of Polyolefinic Plastic Waste
Authors: Seitz Mathias , Schröter Stephan 
Published: March 2022

AbstractIn a circular economy, processes such as the pyrolysis of polyolefin plastic waste must be established for naphtha cracker feedstock production. However, the composition of the plastic waste used has a strong influence on the conversion process and the heteroatom content, and thus on the quality of the pyrolysis oils. In this work, the influence of critical plastic components (e.g., polyamide 6) on the catalytic cracking of polyethylene (PE‐HD) in a batch rotary kiln reactor was investigated and a cost‐effective concept for integrating chemical recycling into a steam cracking plant was proposed.
A novel feature selection with stochastic gradient descent logistic regression for multilabeled stress prediction in working employees
Authors: Anitha Swaminathan , Vanitha Muthuraman 
Published: March 2022

AbstractIn the recent times, stress prediction becomes a hot research area and several research works have been developed to address it. The advent of machine learning (ML) models assists the stress prediction process to understand the patterns effectively and offer effective perceptions about possible future intervention. In this view, this article presents a multi‐labeled stress prediction in working employee using extremely randomized tree (ET) based feature selection (FS) and stochastic gradient descent (SGD) with logistic regression (LR), called ETSGD‐LR model. First, the ET based FS technique can be used to compute impurity‐based feature importance, which in turn can be used to discard irrelevant features. In addition, the SGD‐LR model is used to classify the feature reduced subset into different class labels. For experimental validation, we have collected our own stress prediction dataset with 1197 records of employees collected from schools, banks, universities, and so forth from different institutions. Among them 1197 records are filtered with various diseases and work pressure. A detailed set of simulations were carried out in Python Programming tool, and the results are analyzed in terms of sensitivity, specificity, accuracy, precision, F‐score, and kappa. The obtained simulation outcome ensured the superior performance of the ETSGD‐LR model over the compared methods with the maximum sensitivity, specificity, and accuracy of 0.980, 0.900, and 0.972, respectively. The experimental results shown that the inclusion of FS process helps to improve the classification performance.
Deoxydehydration of Biomass‐Derived Polyols Over Silver‐Modified Ceria‐Supported Rhenium Catalyst with Molecular Hydrogen
Authors: Yamaguchi Kosuke , Cao Ji , Betchaku Mii , Nakagawa Yoshinao , Tamura Masazumi , Nakayama Akira , Yabushita Mizuho , Tomishige Keiichi 
Published: March 2022

AbstractOlefin production from polyols via deoxydehydration (DODH) was carried out over Ag‐modified CeO2‐supported heterogeneous Re catalysts with H2 as a reducing agent. Both high DODH activity and low hydrogenation ability for C=C bonds were observed in the reaction of erythritol, giving a 1,3‐butadiene yield of up to 90 % under “solvent‐free” conditions. This catalyst is applicable to other substrates such as methyl glycosides (methyl α‐fucopyranoside: 91 % yield of DODH product; methyl β‐ribofuranoside: 88 % yield), which were difficult to be converted to the DODH products over the DODH catalysts reported previously. ReOx‐Ag/CeO2 was reused 3 times without a decrease of activity or selectivity after calcination as regeneration. Although the transmission electron microscopy energy‐dispersive X‐ray spectroscopy and X‐ray absorption fine structure analyses showed that Re species were highly dispersed and Ag was present as metal particles with various sizes from well‐dispersed species (<1 nm) to around 5 nm particles, the catalysts prepared from size‐controlled Ag nanoparticles showed similar performance, indicating that the catalytic performance is insensitive to the Ag particle size.
k‐means clustering based energy and trust management routing algorithm for mobile ad‐hoc networks
Authors: C Gopala krishnan , A.H Nishan , Theerthagiri Prasannavenkatesan 
Published: March 2022

SummaryMANETs (Mobile Ad‐Hoc Networks) have limited energy and are unable to energize themselves. This work aims to create a power management strategy for the MANET that saves energy. While routing based on the cluster, the cluster heads may fail or work improperly by the cause of power issues. As a result, the cluster heads experience instability when gathering information and interacting. The main focus of this research is identifying the unstable cluster heads and replacing them with other nodes that implement the self‐configurable cluster method. For defining the cluster heads successfully, we presented a k‐means protocol approach. The proposed k‐means technique identifies the abnormal or unnecessary variations of the cluster heads and the change in cluster count. A node is designated as a cluster head (CH) in MANET after the cluster value remains lesser than the existing routing threshold value. Information gathering, computing trust levels, and trust‐based configuration are the three key elements of the proposed trust management system, which communicates with each node to establish secure network connections. Finally, the testing results show that the proposed approach uses less energy and effectively manages trust in MANET.
Detection of insulin analogues and large peptides >2 kDa in urine
Authors: Cox Holly D. , Knussmann Graham N. , Moore Chad , Eichner Daniel 
Published: March 2022

AbstractInsulin analogues and large bioactive peptides may be used by athletes to enhance performance and are banned by the World Anti‐Doping Agency (WADA). In addition to insulin analogues, the large peptides include a structurally diverse set of peptides including analogues of growth hormone releasing hormone (GHRH), insulin‐like growth factor‐1 (IGF‐1), and mechano‐growth factor (MGF). Detection of this class of peptides is difficult due to their absorptive losses and presence at very low concentrations in urine. In this report, a high throughput method is described that allows sensitive detection of four classes of large peptides in one assay. Sample extraction is performed by ultrafiltration to concentrate the urine followed by solid phase extraction in a 96‐well micro‐elution plate. Peptides in the urine samples are detected on a triple quadrupole mass spectrometer coupled to standard flow liquid chromatography. The method was validated and evaluated for limit of detection, limit of identification, specificity, precision, carryover, recovery, matrix interference, and post‐extraction stability. The limit of detection for insulin analogues is between 5 and 25 pg/ml and between 5 and 50 pg/ml for the other peptide classes. Specificity was good with no detection of interfering peaks in blank urine samples. Carryover from a high concentration sample was not observed and the post‐extraction stability was between 77% and 107%. The method was able to detect insulin analogues in three diabetic urine samples. Increased screening for this class of peptides will improve detection and deterrence.
Protein kinases and protein phosphatases encoded in the Ciona robusta genome
Authors: Tokuoka Miki , Kobayashi Kenji , Lemaire Patrick , Satou Yutaka 
Published: March 2022

SummaryProtein kinases (PKs) and protein phosphatases (PPs) regulate the phosphorylation of proteins that are involved in a variety of biological processes. To study such biological processes systematically, it is important to know the whole repertoire of PKs and PPs encoded in a genome. In the present study, we surveyed the genome of an ascidian (Ciona robusta or Ciona intestinalis type A) to comprehensively identify the genes that encoded PKs and PPs. Because ascidians belong to the sister group of vertebrates, a comparison of the whole repertoire of PKs and PPs of ascidians with those of vertebrates may help to delineate the complements of these proteins that were present in the last common ancestor of these two groups of animals. Our results show that the repertory of PPs was much more expanded in vertebrates than the repertory of PKs. We also showed that approximately 75% of PKs and PPs were expressed during development from eggs to larvae. Thus, the present study provides catalogs for PKs and PPs encoded in the ascidian genome. These catalogs will be useful for systematic studies of biological processes that involve phosphorylation and for evolutionary studies of the origin of vertebrates.