bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness of pain neuroscience education on somatosensory functioning after surgery for breast cancer: A double‐blinded randomized controlled trial
Authors: Dams Lore , Van der Gucht Elien , Haenen Vincent , Devoogdt Nele , Smeets Ann , Bernar Koen , Morlion Bart , Moloney Niamh , Fieuws Steffen , De Groef An , Meeus Mira 
Published: January 2023

AbstractPain is one of the most prevalent and long‐term adverse effects described by people who have undergone breast cancer surgery. Non‐helpful perceptions and thoughts about pain may contribute to the transition of acute to persistent pain. Adding educational interventions to the current physical therapy program in this population may help to improve or prevent persistent pain. Pain neuroscience education (PNE) is a type of educational intervention that addresses the experience of pain in a broader sense by explaining pain not only from a biomedical perspective, but also from a psychological and social perspective. A double‐blinded randomized controlled trial (EduCan trial) investigated whether PNE, in addition to a standard physiotherapy program immediately after surgery for breast cancer, was more effective on somatosensory functioning in the short (4 months postoperatively) and long term (18 months postoperatively), than providing a biomedical explanation for pain. Somatosensory functioning was evaluated using a self‐reported questionnaire as well as a comprehensive quantitative sensory testing evaluation. The findings of this study revealed that adding six sessions of PNE to a standard physical therapy program (n = 184) did not result in a significantly different course of somatosensory functioning up to 18 months postoperatively as compared to biomedical pain education. These findings provide an interesting basis for future research into who should receive PNE after surgery for breast cancer (e.g., patient profiling or phenotyping) and how we can tailor it to the individual to increase its effectiveness.
Resilient H∞$$ {H}_{\infty } $$ filtering for discrete‐time system with multipath data packet dropout and quantization
Authors: Wang Jian , Chang Xiao‐Heng , Xiong Jun , Li Zhi‐Min 
Published: January 2023

AbstractThis paper proposes a two‐step method to design a resilient filter and two dynamic quantizers for a class of discrete‐time systems. In the first step, a filter is designed to make the discrete‐time system stochastically stable, and make the
norm between the filtering error and the external disturbance less than a given level. In the second step, two dynamic quantizers, which quantify the measurement output signal and the performance output signal, respectively, are designed under the condition that the filter gain matrices are obtained. In addition, the filter adopted in this paper takes the randomly occurring uncertainty into consideration, and the quantizers are designed by an inequality scaling technique which can reduce the complexity of linear matrix inequalities. Furthermore, this paper also considers the data packet dropout that may occur during network transmission. Finally, considering the data packet dropout and quantization of measurement output signal and performance output signal, the effectiveness of the proposed filter design method is demonstrated by two simulation examples.
Cytotoxic Activity of Herbal Medicines as Assessed in Vitro: A Review
Authors: Gavanji Shahin , Bakhtari Azizollah , Famurewa Ademola C. , Othman Eman M. 
Published: January 2023

AbstractSince time immemorial, human beings have sought natural medications for treatment of various diseases. Weighty evidence demonstrates the use of chemical methodologies for sensitive evaluation of cytotoxic potentials of herbal agents. However, due to the ubiquitous use of cytotoxicity methods, there is a need for providing updated guidance for the design and development of in vitro assessment. The aim of this review is to provide practical guidance on common cell‐based assays for suitable assessment of cytotoxicity potential of herbal medicines and discussing their advantages and disadvantages Relevant articles in authentic databases, including PubMed, Web of Science, Science Direct, Scopus, Google Scholar and SID, from 1950 to 2022 were collected according to selection criteria of in vitro cytotoxicity assays and protocols. In addition, the link between cytotoxicity assay selection and different factors such as the drug solvent, concentration and exposure duration were discussed.
Identification of Biologically Diverse Tetrahydronaphthalen‐2‐ols through the Synthesis and Phenotypic Profiling of Chemically Diverse, Estradiol‐Inspired Compounds
Authors: Whitmarsh‐Everiss Thomas , Wang Zhou , Hauberg Hansen Cecilie , Depta Laura , Sassetti Elisa , Rafn Dan Oliver , Pahl Axel , Sievers Sonja , Laraia Luca 
Published: January 2023

AbstractCombining natural product fragments to design new scaffolds with unprecedented bioactivity is a powerful strategy for the discovery of tool compounds and potential therapeutics. However, the choice of fragments to couple and the biological screens to employ remain open questions in the field. By choosing a primary fragment containing the A/B ring system of estradiol and fusing it to nine different secondary fragments, we were able to identify compounds that modulated four different phenotypes: inhibition of autophagy and osteoblast differentiation, as well as potassium channel and tubulin modulation. The latter two were uncovered by using unbiased morphological profiling with a cell‐painting assay. The number of hits and variety in bioactivity discovered validates the use of recombining natural product fragments coupled to phenotypic screening for the rapid identification of biologically diverse compounds.
Site‐Specific Labeling of RNAs with Modified and 19F‐Labeled Nucleotides by Chemo‐Enzymatic Synthesis
Authors: Sudakov Alexey , Knezic Bozana , Hengesbach Martin , Fürtig Boris , Stirnal Elke , Schwalbe Harald 
Published: January 2023

AbstractMore than 170 post‐transcriptional modifications of RNAs have currently been identified. Detailed biophysical investigations of these modifications have been limited since large RNAs containing these post‐transcriptional modifications are difficult to produce. Further, adequate readout of spectroscopic fingerprints are important, necessitating additional labeling procedures beyond the naturally occurring RNA modifications. Here, we report the chemo‐enzymatic synthesis of RNA modifications and several structurally similar fluorine‐modified analogs further optimizing a recently developed methodology.[1] This chemo‐enzymatic method allows synthesis of also large RNAs. We were able to incorporate 16 modified nucleotides and 6 19F‐labeled nucleotides. To showcase the applicability of such modified large RNAs, we incorporated a 19F‐labeled cytidine into the aptamer domain of the 2’dG sensing riboswitch (2’dG‐sw) from Mesoplasma florum, enabling characterizing RNA fold, ligand binding and kinetics. Thanks to the large chemical shift dispersion of 19F, we can detect conformational heterogeneity in the apo state of the riboswitch.
Constructing Artificial Nucleobase Compilation to Enable Precise Molecular Medicine†
Authors: Chen Jingqi , Liu Bo , Wang Xuan , Liu Xueliang , Yang Dandan , Yang Yu 
Published: January 2023

Comprehensive SummaryNucleic acids are the hereditary information storage medium of life. Due to its high programmability and good biocompatibility, the applications of nucleic acids are not limited to their natural function. However, the efficiency of nucleic acids is often hampered by inherent limitations in numerous practical applications, including limited access to complex functional patterns due to only four building blocks, facile degradation by nucleases, rapid renal clearance, poor pharmacokinetic properties, and so on. To end this, the researchers developed unnatural base pairs (UBPs) and numerous artificial analogues of nucleosides and oligonucleotides in recent decades. The developed UBPs and nucleoside base analogues together constitute artificial nucleobase compilation, which promotes the development of biomedical sciences. Here, we describe the development of artificial nucleobase compilation and summarized its applications in precise molecular medicine, including PCR‐based diagnostics, aptamer‐based diagnostics, nucleobase analogue drugs construction, ASO modification, aptamer‐based therapeutics and biomaterials construction. This review provides an overview of current opportunities and challenges of artificial nucleobase‐related precise molecular medicine.
An optimized deep network based soil texture prediction and vegetation analysis using satellite image database
Authors: Anand Mallekedi , Jain Anuj , Kumar Shukla Manoj 
Published: January 2023

SummaryThe usage of satellite images has grown rapidly in digital applications. Predicting features in the satellite images using conventional techniques is not an easy task as the images captured from satellites are more complex with highly noisy features. Hence, traditional imaging algorithms cannot analyze the image features and specify the soil textures. In this work, the Tarakeswar satellite images were taken to estimate the soil textures and crops yielding. Hence, to find the soil's chemical properties and suitable crops, the novel bat‐based U‐Net feature prediction system (BUFPS) was developed with the required features. The imported satellite images were initially filtered and entered into the classification phase to forecast the present chemical features and suitable crops in specific soils. After detecting the chemical features, soil textures like sandy, silt, and clay were categorized; the crops like jute, rice, lentil, and potato were considered. Finally, the planned model is executed in the MATLAB environment and has gained outstanding results by achieving the lowest error rate of 8% and a high prediction score of 92%. The proposed model has achieved exact soil texture analysis for complex satellite images. The gained texture analysis outcome is quite better than other existing models.
Humanization of the Shark VNAR Single Domain Antibody Using CDR Grafting
Authors: Zhang Yi‐Fan , Sun Yaping , Hong Jessica , Ho Mitchell 
Published: January 2023

AbstractThe variable domain of the new antigen receptor (VNAR) of shark single domain antibodies is evolutionarily distant from the variable regions (VH) of mammalian immunoglobulins, yet it still has complementarity‐determining regions (CDRs) that are involved in antigen recognition, therefore making it possible to humanize by grafting these CDRs to the framework of human VH homologs. Here, we show the VNAR CDR based on an analysis of currently available VNAR‐antigen structure complexes in the global Protein Data Bank archive of 3D structure data, and describe the detailed protocol to humanize VNAR by CDR grafting, using B6 (an anti‐Pseudomonas exotoxin VNAR), the most common type (Type II) of shark VNARs, as an example. Ongoing efforts will further optimize the protocol for moving shark VNARs to the clinic for treating cancer and other human diseases. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.Basic Protocol: Humanize shark VNAR sequence by CDR graftingSupport Protocol 1: VNAR structure prediction and comparisonSupport Protocol 2: Measure binding kinetics of humanized VNAR using bio‐layer interferometry (BLI)
Modular Synthesis of ortho‐Thiolated Aryl Esters Enabled with Thiocarbonate through Catellani Strategy
Authors: Du Guopeng , Zhu Pingliang , Wang Jing , Li Xinjin , Zhang Dao‐Peng , Wang Chuan‐Zeng , Sun Feng‐Gang 
Published: January 2023

AbstractHerein, we report a palladium/norbornene/copper co‐catalyzed single‐step approach that merges selective ortho C−H bond esterification with ipso thiolation for construction of synthetically versatile 2‐arylthio aryl esters under exceptionally mild conditions. Importantly, this process proceeded in a highly efficient manner, allowing alkoxycarbonyl and thio groups to be installed into one aryl iodides simultaneously by harnessing thiocarbonate as bifunctional reagent. The method has been demonstrated to accommodate good functionalities and features broad substrate scope.
Self‐Catalyzed Hydroxyl‐Yne Click Reaction: A Powerful Tool toward Red‐Emitting Nontraditional Small Organic Luminogens
Authors: Jiang Qimin , Zhang Hongyan , Shi Lingyue , Guan Shuyi , Huang Wenyan , Xue Xiaoqiang , Yang Hongjun , Jiang Li , Jiang Bibiao 
Published: January 2023

AbstractNontraditional small organic luminogens (NTSOLs) without classic conjugated chromophores have attracted significant attention. However, the design and synthesis of NTSOLs with fluorescence in the red region remain significantly challenging. In this study, we established a self‐catalyzed hydroxyl‐yne click reaction for preparing long‐wavelength and red‐emitting NTSOLs. Owing to their perfect reaction selectivity, high efficiency, and excellent universality, a series of compounds with well‐defined structures were obtained in high yields. Moreover, the obtained compounds showed concentration‐enhanced and excitation‐dependent emission characteristics. The compounds also exhibited dramatical chemical structure‐dependent and aggregation‐induced red‐shifted fluorescence properties, based on which we successfully obtained red‐emitting NTSOLs by simply adjusting chemical structure and concentration. Also, the compounds show good cell staining ability, which can be used in cell imaging.
Static droplet array for the synthesis of nonspherical microparticles
Authors: Yang Hang , Jiang Lin , Guo Kefan , Xiang Nan 
Published: January 2023

AbstractWe reported a manually operated static droplet array (SDA)‐based device for the synthesis of nonspherical microparticles with different shapes. The improved SDA structure and reversible bonding between poly(dimethylsiloxane) (PDMS) were used in the device for the large‐scale synthesis and rapid extraction of nonspherical microparticles. To understand the device physics, the effects of flow rate, SDA well size, and shape on droplet generation performances were explored. The results indicated that droplet generation in SDA structures was insensitive to the flow rate, and monodisperse droplets were generated by the SDA‐based device through manually pushing the syringe. Finally, we integrated four kinds of SDA structures in one device and successfully realized the synthesis and extraction of nonspherical microparticles with different shapes and materials. Our SDA‐based device offers numerous advantages, such as simple manual operation, low equipment cost, controllable microparticle shapes and sizes, and large‐scale production. Thus, it holds the potential to be used as a flexible tool for the production of nonspherical microparticles.
An accurate attack detection framework based on exponential polynomial kernel‐centered deep neural networks in the wireless sensor network
Authors: Raveendranadh Bokka , Tamilselvan Sadasivam 
Published: January 2023

AbstractA novel type of wireless network that is rising in popularity with a wide assortment of civilian along with military applications is called WSN. Owing to several factors like nodes with resources that are constrained and packages that are resistant to tamper, WSNs are tremendously vulnerable to internal attacks and mainly external attacks also. Attacks on such critical schemes comprise penetrations into their network along with the installation of malicious tools or programs, which can reveal sensitive data or alter the specific physical equipment's behavior. For their action, the wireless networks are utilized by the threats like spoofing, injection, denial of services, and numerous attacks. Thus, for protecting devices from intruder attacks, security solutions are necessary. An intrusion detection system (IDS), which is wielded for detecting attacks against a system or a network by evaluating their activities along with events, is a tool. In this article, an efficient attack detection technique grounded on exponential polynomial kernel‐centered deep neural networks (EPK‐DNN) is proposed since intrusion detection is crucial in securing the data. Intrusion detection in WSN is extremely intricate for tasks like fault diagnosis, and real‐time monitoring applications, owing to the WSN's dynamicity. To find diverse attacks along with to safeguard WSNs from security risks, numerous detection methodologies are created, because intrusion detection is decisive for protecting the data in WSNs. However, owing to the restricted resources and energy of WSN nodes, widespread computation and so forth, they are inefficient. In this article, an efficient attack detection methodology centered on EPK‐DNN is proposed to lessen these problems. The attack detection system's training is the foremost step in the EPK‐DNN technique. In step one, the input data are preprocessed; and then, in the training process, the preprocessed data are exploited for attribute extraction. In step two, by utilizing the linear scaling based BAT optimization (LS‐BAT), the major attributes are chosen. Then, to detect attacks in WSN, the chosen features are trained by the EPK‐DNN. In step three, by utilizing the Damerau‐Levenshtein‐based K‐means algorithm (DL‐K‐Means), the WSN network is initialized along with the sensor nodes are clustered. To amass the sensor data, the cluster heads are selected by utilizing the swap, displacement, and reversion‐centered rock hyraxes swarm optimization algorithm. After that, for testing, the sensor data are inputted into the trained ADS. The outcomes exhibited that the greatest accuracy rate of 97.21% was attained by the EPK‐DNN technique for the real‐time BC dataset and 96.86% for the real‐time MC dataset. When analogized to the customary deep learning (DL) methodologies, the investigational findings reveal that the EPK‐DNN technique accomplishes desirable detection accuracy.
Application of CRISPR/Cas9 technology in forages
Authors: Bao Qinyan , Wolabu Tezera W. , Zhang Qian , Zhang Tian , Liu Zhipeng , Sun Juan , Wang Zeng‐Yu 
Published: January 2023

AbstractGenome editing is an advanced genetic modification tool that facilitates the removal, insertion, or substitution of nucleotides in the genome of an organism for mutation induction. CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR‐associated protein 9) is the most widely used genome editing tool that can precisely modify the specific sequence of a genome. Significant progress has been made in the use of CRISPR/Cas9 for the genetic improvement of food crops. However, in forage crops, the use of CRISPR/Cas9 is still in the infant stage with limited understanding and application. This article reviews current advances in the establishment and application of the CRISPR/Cas9 system in alfalfa, summarizes the application of CRISPR/Cas9 in several other forage legume and grass species, and discusses the prospects of CRISPR/Cas9 in the genetic improvement of forage crops.
Predicting the risk of 7‐day readmission in late preterm infants in California: A population‐based cohort study
Authors: Amsalu Ribka , Oltman Scott P. , Medvedev Melissa M. , Baer Rebecca J. , Rogers Elizabeth E. , Shiboski Stephen C. , Jelliffe‐Pawlowski Laura 
Published: January 2023

AbstractBackground and aimsThe American Academy of Pediatrics describes late preterm infants, born at 34 to 36 completed weeks' gestation, as at‐risk for rehospitalization and severe morbidity as compared to term infants. While there are prediction models that focus on specific morbidities, there is limited research on risk prediction for early readmission in late preterm infants. The aim of this study is to derive and validate a model to predict 7‐day readmission.MethodsThis is a population‐based retrospective cohort study of liveborn infants in California between January 2007 to December 2011. Birth certificates, maintained by California Vital Statistics, were linked to a hospital discharge, emergency department, and ambulatory surgery records maintained by the California Office of Statewide Health Planning and Development. Random forest and logistic regression were used to identify maternal and infant variables of importance, test for association, and develop and validate a predictive model. The predictive model was evaluated for discrimination and calibration.ResultsWe restricted the sample to healthy late preterm infants (n = 122,014), of which 4.1% were readmitted to hospital within 7‐day after birth discharge. The random forest model with 24 variables had better predictive ability than the 8 variable logistic model with c‐statistic of 0.644 (95% confidence interval 0.629, 0.659) in the validation data set and Brier score of 0.0408. The eight predictors of importance length of stay, delivery method, parity, gestational age, birthweight, race/ethnicity, phototherapy at birth hospitalization, and pre‐existing or gestational diabetes were used to drive individual risk scores. The risk stratification had the ability to identify an estimated 19% of infants at greatest risk of readmission.ConclusionsOur 7‐day readmission predictive model had moderate performance in differentiating at risk late preterm infants. Future studies might benefit from inclusion of more variables and focus on hospital practices that minimize risk.
Acidic oxygen evolution reaction: Mechanism, catalyst classification, and enhancement strategies
Authors: Ma Qianli , Mu Shichun 
Published: January 2023

AbstractAs the most desirable hydrogen production device, the highly efficient acidic proton exchange membrane water electrolyzers (PEMWE) are severely limited by the sluggish kinetics of oxygen evolution reaction (OER) at the anode. Rutile IrO2 is a commercial acid‐stable OER catalyst with poor activity and high cost, which has motivated the development of alternatives. However, hitherto most of the designed acidic OER catalysts have disadvantages of low activity or stability, which cannot meet the requirement of industrial applications. Thus, exploring suitable strategies to enhance the activity and stability of cost‐effective acidic OER catalysts is crucial for developing the PEMWE technique. In this review, the main OER mechanisms, different types of catalysts, and their activity and stability characteristics are summarized and discussed, and then possible strategies to improve activity and stability are proposed. Finally, the problems and prospects of such catalysts are generalized to shed some light on the future research of advanced catalysts for acidic OER.