bluuebunny/crossref_metadata_2025_split huggingface dataset:
ACTIVE‐BAPO – A Versatile Transfer Agent for Photoactive Bis(acyl)phosphane Oxide Units
Authors: Widera Anna , Conti Riccardo , Cosola Andrea , Fäh Ashling , Thöny Debora , Sangermano Marco , Levalois‐Grützmacher Joëlle , Grützmacher Hansjörg 
Published: February 2023

AbstractA N‐hydroxy succinimide (NHS) ester substituted bis(acyl)phosphane oxide (ACTIVE‐BAPO) was prepared by phospha‐Michael addition and used for an easy one‐step BAPO ligation with substrates containing primary amino groups, such as amino acids, proteins, and poly(amidoamine) (PAMAM) dendrimers. Thereby, a range of new molecular and polymeric photoinitators was obtained. Real‐time photo‐rheology experiments demonstrated the outstanding efficiency of the PAMAM BAPOs as photoinitiators for free radical polymerization. Remarkably, it is found that PAMAM BAPOs also act as crosslinking agents to convert monofunctional methacrylate monomers into thermosetting networks without any further additives. Depending on the number of the attached BAPOs, thermosets with a different degree of crosslinking and swelling capability in water were obtained.
CoNi2S4 Electrode with High Mass‐Loading for High‐Energy‐Density Supercapacitor: Role of S‐Containing Anions Exchange
Authors: Wang Lingfeng , Chen Lu , Chen Shihuan , Ye Qinglan , Xu Xuetang , Wang Fan 
Published: February 2023

AbstractAnion exchange is recognized as an effective method to regulate the composition, electronic conductivity, and electrochemical behavior of the transition metal‐based compounds. In this work, anion exchange is adopted as a rational post‐treatment route to facilitate the capacitive activity of CoNi2S4 nanoparticle arrays grown on carbon cloth (CC) with high mass‐loading. As soaked in saturated Na2S solution, the CoNi2S4/CC electrode showed an increased capacity from 483 C g−1 to 841 C g−1 at 10 mA cm−2 with excellent rate performance and stable cycling performance, which was superior to the CoNi2S4/CC electrode activated by NaBH4 reduction. Anion exchange was beneficial for enhancing the crystallinity, retaining the adhesion of nanoarrays, and realizing low resistance nature in a mild route. The as‐assembled CoNi2S4/CC//activated CC hybrid supercapacitor delivered a high areal capacitance of 1.28 F cm−2 at 5 mA cm−2, and achieved an energy density of 0.58 mWh cm−2 at a power density of 4.5 mW cm−2 with excellent cycle stability with 90.6 % capacity retention after 10000 cycles.
Machine Learning‐Guided Computational Screening of New Candidate Reactions with High Bioorthogonal Click Potential
Authors: Stuyver Thijs , Coley Connor W. 
Published: February 2023

AbstractBioorthogonal click chemistry has become an indispensable part of the biochemist's toolbox. Despite the wide variety of applications that have been developed in recent years, only a limited number of bioorthogonal click reactions have been discovered so far, most of them based on (substituted) azides. In this work, we present a computational workflow to discover new candidate reactions with promising kinetic and thermodynamic properties for bioorthogonal click applications. Sampling only around 0.05 % of an overall search space of over 10,000,000 dipolar cycloadditions, we develop a machine learning model able to predict DFT‐computed activation and reaction energies within ∼2–3 kcal/mol across the entire space. Applying this model to screen the full search space through iterative rounds of learning, we identify a broad pool of candidate reactions with rich structural diversity, which can be used as a starting point or source of inspiration for future experimental development of both azide‐based and non‐azide‐based bioorthogonal click reactions.
Subgroup analysis of linear models with measurement error
Authors: Le Yuan , Bai Yang , Qin Guoyou 
Published: February 2023

AbstractHeterogeneity exists in populations, and people may benefit differently from the same treatments or services. Correctly identifying subgroups corresponding to outcomes such as treatment response plays an important role in data‐based decision making. As few discussions exist on subgroup analysis with measurement error, we propose a new estimation method to consider these two components simultaneously under the linear regression model. First, we develop an objective function based on unbiased estimating equations with two repeated measurements and a concave penalty on pairwise differences between coefficients. The proposed method can identify subgroups and estimate coefficients simultaneously when considering measurement error. Second, we derive an algorithm based on the alternating direction method of multipliers algorithm and demonstrate its convergence. Third, we prove that the proposed estimators are consistent and asymptotically normal. The performance and asymptotic properties of the proposed method are evaluated through simulation studies. Finally, we apply our method to data from the Lifestyle Education for Activity and Nutrition study and identify two subgroups, of which one has a significant treatment effect.
Intelligent credit scoring using deep learning methods
Authors: Gicić Adaleta , Đonko Dženana , Subasi Abdulhamit 
Published: February 2023

SummaryCredit scoring is one the most important parts of credit risk management in reducing the risk of client defaults and bankruptcies. Deep learning has received much attention in recent years, but it has not been implemented so intensively in credit scoring compared to other financial domains. In this article, stacked unidirectional and bidirectional LSTM (long short‐term memory) networks as a complex area of deep learning are applied in solving credit scoring problems for the first time. The proposed robust model exploits the full potential of the three‐layer stacked LSTM and BDLSTM (bidirectional LSTM) architecture with the treatment and modeling of public datasets in a novel way since credit scoring is not a time sequence problem. Attributes of each loan instance were transformed into a sequence of the matrix with a fixed sliding window approach with a one‐time step. Our proposed models outperform existing and much more complex deep learning solutions thus we succeeded in preserving simplicity. In this article, measures of different types are employed to carry out consistent conclusions. The results by applying three hidden layers on the German Credit dataset showed an accuracy of 87.19%, for Kaggle dataset accuracy reached 93.69%, and for Microcredit dataset accuracy of 97.80%.
Multigraph learning for parallelism discovery in sequential programs
Authors: Shen Yuanyuan , Peng Manman , Wu Qiang , Xie Guoqi 
Published: February 2023

SummaryParallelization is an optimization technique that is playing an increasingly vital role in software applications. Discovering the potential parallelism in sequential programs is of primary importance for parallelization. To this end, various tools have been created to obtain parallelizable targets by analyzing the dependencies in sequential programs. However, the majority are constructed based on manually designed dependence analysis rules. Consequently, they must follow some constraints, which limit the scope of their program analysis capability. Furthermore, constructing a dependency analysis rule is a complicated and highly sophisticated endeavor. In this study, we exploit the fact that neural network models can learn the potential features of programs to tackle the parallelism discovery task in an end‐to‐end manner. Specifically, we developed a multigraph learning architecture on top of multiple abstract code representations in a complementary manner. In the architecture, we equip code representations with different neural network models in a targeted manner, including a deep convolutional neural network for analyzing both control and data flows and a novel neural network for learning the abstract syntax trees. Experimental results obtained on a common parallelism discovery dataset indicate that the developed multigraph learning architecture can learn potential parallelism patterns in sequential programs with high accuracy and efficiency.
Synthesis of Chiral Hypervalent Trifluoromethyl Organobismuth Complexes and Enantioselective Olefin Difluorocarbenation Screenings
Authors: Louis‐Goff Thomas , Trinh Huu Vinh , Chen Eileen , Rheingold Arnold L. , Hyvl Jakub 
Published: February 2023

AbstractTwo hypervalent trifluoromethyl organobismuth complexes were prepared from commercially available chiral amines, (R)‐1‐cyclohexylethylamine and (1R, 2R, 3R, 5S)‐(−)‐isopinocampheylamine; however, only the complex from the latter amine was prepared as a single stereoisomer. Both organobismuth complexes were fully characterized by NMR spectroscopy and single‐crystal X‐ray crystallography, revealing that the structures were similar to previously reported complexes with a hypervalent Bi−N bond. The complexes were catalytically active in olefin difluorocarbenation with Ruppert‐Prakash reagent (TMS‐CF3) used as a terminal source of CF2. The catalyst derived from isopinocampheylamine was screened with three prochiral olefins of various reactivity in DCM and toluene. All reactions afforded the 1,1‐difluorocyclopropanes in good yields, but no enantiomeric excess was observed.
Platelet Functional Testing Via High‐Throughput Microtiter Plate‐Based Assays
Authors: Tamang Hem Kumar , Stringham Emily N. , Tourdot Benjamin E. 
Published: February 2023

AbstractPlatelets play a critical role in hemostasis and thrombosis; therefore, in vitro assays that measure platelet reactivity are fundamental tools to gain insight into these physiologic processes, to diagnose platelet disorders, and to develop antithrombotic therapies. However, conventional platelet assays such as aggregometry, the clinical gold standard for assessing platelet function, are low throughput and require specialized equipment. Since platelets have a finite life span ex vivo, processes to miniaturize and multiplex assays allow a much broader overview of platelet function in significantly less time than conventional assays. Several groups have developed simplified, high‐throughput approaches to quantify platelet activation with standard laboratory equipment to lower the barrier of entry to study platelet biology. This article describes a panel of optimized and validated high‐throughput microplate assays to comprehensively assess platelet functionality, independently or in combination, to increase throughput and reduce costs. Specifically, following stimulation of platelets, a plate reader can be used to measure light transmission aggregation via absorbance; dense‐granule secretion based on ATP‐dependent luminescence generation; and cytosolic calcium levels with a cell‐permeant, fluorescent Ca2+‐sensitive dye. Additionally, platelets are an easily accessible component of the blood that share signaling pathways with other cells, making them ideal for high‐throughput drug screens. The highly adaptable and complementary assays presented in this article can be used to decipher the molecular mechanism underlying platelet activation or to identify novel inhibitors. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.Basic Protocol 1: Microtiter plate–based light transmission aggregometryBasic Protocol 2: Measuring dense‐granule secretion in high‐throughput microplate assaysBasic Protocol 3: Microtiter plate–based calcium mobilizationSupport Protocol: Platelet isolation and enumeration
Bach2 in CD4+ T cells from SLE patients modulates B‐cell differentiation and IgG production
Authors: Long Di , Yang Bingyi , Yang Ming , Xiong Feng , Zhu Xuejing , Tan Yixin , Wu Haijing 
Published: February 2023

AbstractT and B cells participate in the development of systemic lupus erythematosus (SLE). BTB and CNC homology 2 (Bach2) is an irreplaceable regulator in the T and B lineages that helps to maintain immune homeostasis. However, the function of Bach2 in the pathogenesis of SLE has not been studied in depth. Flow cytometry and qRT‒PCR were used to assess Bach2 levels, bisulfite sequencing PCR was used to measure the methylation level, and silencing by electroporation and stimulation with a cytokine concentration gradient were used to investigate the effect of Bach2 on T cells. Bach2 expression was elevated in the helper T‐cell subsets (T follicular helper, Th1, Th2, Th17, and Treg cells) of SLE patients and negatively correlated with disease severity and autoantibody levels. CD4+ T cells from SLE patients had decreased methylation levels in the Bach2 promoter region. Silencing Bach2 in CD4+ T cells induced increases in the CD19+ B‐cell count, plasmablasts, and secretion of IgG by prompting the secretion of cytokines. The activation signals CD3/CD28, IL‐6, and IL‐21 upregulated Bach2 expression in CD4+ T cells. The regulation of Bach2 by cytokines and T‐cell activation signals in CD4+ T cells was shown to act on B cells and play a protective role against SLE.
Enhanced capsule generative adversarial network for spectrum and energy efficiency of cooperative spectrum prediction framework in cognitive radio network
Authors: D Chandra Mohan , Reddy B. V. Ramana 
Published: February 2023

AbstractCognitive radio network (CRN) is an intellective technology that frequently monitors the unused licensed spectrum in a particular frequency band. When more count of secondary users enters inside the channel may results in collisions. So, the secondary user may not sense the state of inactive and busy state of the primary user resulting reduces the spectrum efficiency (SE) and energy efficiency (EE) of CRN. To overcome these issues, an enhanced capsule generative adversarial network (ECGAN) for spectrum and energy efficiency of cooperative spectrum prediction (CSP) framework in CRN is proposed to improve the channel occupancy. Initially, CRN system is designed to improve the spectrum efficiency and energy efficiency. Then, channel state of primary user is predicted by using the coupled hidden Markov model (CHMM) and ECGAN predictors. Hence, the correlation among the secondary user predict the next channel status, like AND, OR, majority rule fusion methods. The prediction error, spectrum efficiency, energy efficiency based these methods are compared with CHMM and ECGAN predictors as the process of channel occupancy based on. Also, the effect of busy and idle state prediction errors on SE is detected. The proposed method is simulated in MATLAB. Then, the performance of the proposed method shows higher energy efficiency 13.86%, 24.84%, 34.75%, compared with existing methods, such as spectrum and energy efficiency of CSP in CRN (SEE‐CSP‐CRN‐HMM), (SEE‐CSP‐CRN‐MLP), differential evolution based machine learning scheme for secure cooperative spectrum sensing system (SEE‐CSP‐CRN‐EML), cooperative spectrum sensing for primary user detection in CRN utilizing support vector machine (SEE‐CSP‐CRN‐SVM), respectively.
A bi‐level ensemble learning approach to complex time series forecasting: Taking exchange rates as an example
Authors: Hao Jun , Feng Qian Qian , Li Jianping , Sun Xiaolei 
Published: February 2023

AbstractForecasting complex time series faces a huge challenge due to its high volatility. To improve the accuracy and robustness of prediction, this paper proposes a bi‐level ensemble learning approach by combining decomposition‐ensemble forecasting and resample strategies. The bi‐level ensemble approach consists of four steps: data decomposition via singular spectrum analysis (SSA), resampling by employing a bagging algorithm, individual forecasting utilizing extreme learning machine (ELM), and introducing sorting‐pruning and simple addition ensemble strategies for integrating the inner and outer results, respectively. To verify the effectiveness of the established forecasting approach, three exchange rate time series are selected as samples. The results reveal that the proposed model is significantly better than the other benchmarks at different lead times, which indicates that it can be regarded as an effective and promising tool for complex time series forecasting.
Nickel‐Photoredox‐Catalyzed Synthesis of sp2−sp3 Fragments and the Impact of Bicycloalkane Isosteric Replacement on Their Physical‐Chemical Properties
Authors: Lefebvre Quentin , Bocu Mina , Giorgiutti Christophe , Fessard Thomas C. 
Published: February 2023

AbstractBicycloalkanes are well‐known isosteres of alkynes and aromatic rings and their use in the field of medicinal chemistry and drug discovery has been on the rise in the past ten years. Herein, we report the modular and practical synthesis of bicycloalkane‐containing fragments using nickel‐photoredox catalysis. The comparison of their relevant physical‐chemical properties with their aromatic counterparts shows a substantial improvement in LogP and aqueous solubility for bicyclo[1.1.1]pentane derivatives, but not for bicyclo[2.2.2]octane derivatives.
COVID‐19 does not impact on outcome of myeloma patients infected while undergoing autologous stem cell transplantation
Authors: Masina Lorenzo , Bianchetti Nicola , Passi Angela , Bottelli Chiara , Bagnasco Samuele , Spolzino Angelica , Oberti Margherita , Chiarini Marco , Belotti Angelo , Voltolini Simone , Faglioni Laura , Rossi Giuseppe , Tucci Alessandra , Cattaneo Chiara 
Published: February 2023

AbstractHere we report two cases of myeloma patients who became positive for SARS‐CoV‐2 infection during the acute phase of autologous stem cell transplant. Both patients were promptly treated with monoclonal antibodies and remdesivir, and, despite the profound neutropenia and lymphopenia, they did not develop respiratory failure and they remained paucisymptomatic during the entire period of aplasia. Neutrophil engraftment took place as expected and the patients were discharged quickly and did not experience adverse effects after discharge.
DPP8/9 are not Required to Cleave Most Proline‐Containing Peptides
Authors: Bhattacharjee Abir , Bachovchin Daniel A. 
Published: February 2023

AbstractSmall molecule inhibitors of the intracellular serine peptidases DPP8 and DPP9 (DPP8/9) activate the NLRP1 and CARD8 inflammasomes, but the key DPP8/9 substrates have not yet been identified. DPP8/9 cleave after proline to remove N‐terminal dipeptides from peptides or proteins, and studies using pseudo‐peptide reporter substrates have suggested that these enzymes may play key roles in the catabolism of many proline‐containing peptides generated by the proteasome. Here, we evaluated the degradation of a wide array of actual peptides in cell lysates, and discovered that DPP8/9 are not in fact involved in the processing of the vast majority of proline‐containing peptides. Overall, these results indicate that DPP8/9 have a much more limited substrate scope than previously thought, and likely specifically cleave some critically important, but as yet unknown, intracellular peptide or protein that regulates inflammasome activation.
Selected Personal Memories of my Life with Helmut: Served as Facts in Homeopathic Doses and Highly Diluted with Fiction and Nonsense
Authors: Weiske Thomas 
Published: February 2023

AbstractIn the context of this special issue of the Israel Journal of Chemistry on the occasion and in honor of the 80th birthday of Prof. Helmut Schwarz, this article takes aim at some selected personal and occasionally fancifully embellished reminiscences from decades of interaction of the jubilarian with members of his research group.
FIGO recommendations: Use of midurethral slings for the treatment of stress urinary incontinence
Authors: Lau Hui‐Hsuan , Davila G. Willy , Chen Ying‐Yu , Sartori Marair G. F. , Jármy‐Di Bella Zsuzsanna I. K. , Tsai Jung‐Mei , Liu Yu‐Min , Su Tsung‐Hsien ,   for the FIGO Urogynecology and Pelvic Floor Committee
Published: February 2023

AbstractBackgroundStress urinary incontinence (SUI) is a global problem. It can significantly adversely impact a woman's quality of life. The use of synthetic mesh in vaginal surgery is controversial, especially when used for pelvic organ prolapse surgery. Although negative effects have been reported, the synthetic mesh midurethral sling (MUS) is considered to be safe and effective in the surgical treatment of SUI.ObjectivesTo provide evidence‐based data and recommendations for the obstetrician/gynecologist who treats women with SUI and performs or plans to perform MUS procedures.MethodsAcademic searches of MEDLINE, the Cochrane Library, Embase, and Google Scholar articles published between 1987 and March 2020 were performed by a subgroup of the Urogynecology and Pelvic Floor Committee, International Federation of Gynecology and Obstetrics (FIGO).Selection CriteriaThe obtained scientific data were associated with a level of evidence according to the Oxford University Centre for Evidence‐Based Medicine and GRADE Working Group system. In the absence of concrete scientific evidence, the recommendations were made via professional consensus.ResultsThe FIGO Urogynecology and Pelvic Floor Committee reviewed the literature and prepared this evidence‐based recommendations document for the use of MUS for women with SUI.ConclusionsDespite the extensive literature, there is a lack of consensus in the optimal surgical treatment of SUI. These recommendations provide a direction for surgeons to make appropriate decisions regarding management of SUI. The MUS is considered safe and effective in the treatment of SUI, based on many high‐quality scientific publications and professional society recommendations. Comprehensive long‐term data and systemic reviews are still needed, and these data will become increasingly important as women live longer. These recommendations will be continuously updated through future literature reviews.
Childhood Family Environment and Osteoporosis in a Population‐Based Cohort Study of Middle‐to Older‐Age Americans
Authors: Courtney Margaret Gough , Roberts Josephine , Quintero Yadira , Godde K. 
Published: February 2023

ABSTRACTDemographic and early‐life socioeconomic and parental investment factors may influence later‐life health and development of chronic and progressive diseases, including osteoporosis, a costly condition common among women. The “long arm of childhood” literature links negative early‐life exposures to lower socioeconomic attainment and worse adult health. We build on a small literature linking childhood socioeconomic status (SES) and bone health, providing evidence of whether associations exist between lower childhood SES and maternal investment and higher risk of osteoporosis diagnosis. We further examine whether persons identifying with non‐White racial/ethnic groups experience underdiagnosis. Data from the nationally representative, population‐based cohort Health and Retirement Study (N = 5,490–11,819) were analyzed for participants ages 50–90 to assess these relationships. Using a machine learning algorithm, we estimated seven survey‐weighted logit models. Greater maternal investment was linked to lower odds of osteoporosis diagnosis (odds ratio [OR] = 0.80, 95% confidence interval [CI] = 0.69, 0.92), but childhood SES was not (OR = 1.03, 95% CI = 0.94, 1.13). Identifying as Black/African American (OR = 0.56, 95% CI = 0.40, 0.80) was associated with lower odds, and identifying as female (OR = 7.22, 95% CI = 5.54, 9.40) produced higher odds of diagnosis. There were differences in diagnosis across intersectional racial/ethnic and sex identities, after accounting for having a bone density scan, and a model predicting bone density scan receipt demonstrated unequal screening across groups. Greater maternal investment was linked to lower odds of osteoporosis diagnosis, likely reflecting links to life‐course accumulation of human capital and childhood nutrition. There is some evidence of underdiagnosis related to bone density scan access. Yet results demonstrated a limited role for the long arm of childhood in later‐life osteoporosis diagnosis. Findings suggest that (1) clinicians should consider life‐course context when assessing osteoporosis risk and (2) diversity, equity, and inclusivity training for clinicians could improve health equity. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.