bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mass spectrometry analysis of phosphotyrosine‐containing proteins
Authors: Li Jiajia , Zhan Xianquan 
Published: February 2023

AbstractTyrosine phosphorylation is a crucial posttranslational modification that is involved in various aspects of cell biology and often has functions in cancers. It is necessary not only to identify the specific phosphorylation sites but also to quantify their phosphorylation levels under specific pathophysiological conditions. Because of its high sensitivity and accuracy, mass spectrometry (MS) has been widely used to identify endogenous and synthetic phosphotyrosine proteins/peptides across a range of biological systems. However, phosphotyrosine‐containing proteins occur in extremely low abundance and they degrade easily, severely challenging the application of MS. This review highlights the advances in both quantitative analysis procedures and enrichment approaches to tyrosine phosphorylation before MS analysis and reviews the differences among phosphorylation, sulfation, and nitration of tyrosine residues in proteins. In‐depth insights into tyrosine phosphorylation in a wide variety of biological systems will offer a deep understanding of how signal transduction regulates cellular physiology and the development of tyrosine phosphorylation‐related drugs as cancer therapeutics.
Morphological prognosis prediction of choroid neovascularization from longitudinal SD‐OCT images
Authors: Shen Jiayan , Chen Zhongyue , Peng Yuanyuan , Zhang Siqi , Xu Chenan , Zhu Weifang , Liu Haiyun , Chen Xinjian 
Published: February 2023

AbstractBackgroundChoroid neovascularization (CNV) has no obvious symptoms in the early stage, but with its gradual expansion, leakage, rupture, and bleeding, it can cause vision loss and central scotoma. In some severe cases, it will lead to permanent visual impairment.PurposeAccurate prediction of disease progression can greatly help ophthalmologists to formulate appropriate treatment plans and prevent further deterioration of the disease. Therefore, we aim to predict the growth trend of CNV to help the attending physician judge the effectiveness of treatment.MethodsIn this paper, we develop a CNN‐based method for CNV growth prediction. To achieve this, we first design a registration network to rigidly register the spectral domain optical coherence tomography (SD‐OCT) B‐scans of each subject at different time points to eliminate retinal displacements of longitudinal data. Then, considering the correlation of longitudinal data, we propose a co‐segmentation network with a correlation attention guidance (CAG) module to cooperatively segment CNV lesions of a group of follow‐up images and use them as input for growth prediction. Finally, based on the above registration and segmentation networks, an encoder‐recurrent‐decoder framework is developed for CNV growth prediction, in which an attention‐based gated recurrent unit (AGRU) is embedded as the recurrent neural network to recurrently learn robust representations.ResultsThe registration network rigidly registers the follow‐up images of patients to the reference images with a root mean square error (RMSE) of 6.754 pixels. And compared with other state‐of‐the‐art segmentation methods, the proposed segmentation network achieves high performance with the Dice similarity coefficients (Dsc) of 85.27%. Based on the above experiments, the proposed growth prediction network can play a role in predicting the future CNV morphology, and the predicted CNV has a Dsc of 83.69% with the ground truth, which is significantly consistent with the actual follow‐up visit.ConclusionThe proposed registration and segmentation networks provide the possibility for growth prediction. In addition, accurately predicting the growth of CNV enables us to know the efficacy of the drug against individuals in advance, creating opportunities for formulating appropriate treatment plans.
Immunonutrition vs standard nutrition for patients with cancer
Authors: Kavalukas Sandra , McClave Stephen A. 
Published: February 2023

AbstractThe prevailing belief in the value of immunonnutrition has been questioned as different patient populations show variable responses ranging from no benefit or even harm to significant improvements in clinical outcomes. The subject of this invited review is a previously published meta‐analysis that showed important benefits from the perioperative use of an immunonutrition formula (defined as nutrition therapy that contains specific immune‐modulating agents) in a distinct population: adult patients with cancer undergoing an elective major surgical operation. Findings showed that use of an immunonutrition formula was associated with reduced infectious morbidity, anastomotic leakage, hospital length of stay, and postoperative complications compared with standard formulations. These benefits were seen after adjusting for bias and removal of older publications. Issues, such as dosing, duration of therapy, baseline nutrition status, content of specific immunomodulatory agents, and route of delivery that contributed to the beneficial response, were discussed. Little difference in response was seen between well‐nourished and malnourished patients, but geographic differences were seen, with greater outcome benefits seen in studies originating from Europe than from Asia or the United States. The best results were seen when at least three agents (arginine, fish oil, and RNA nucleotides) were given, with the timing of the delivery occurring throughout the perioperative period. A review of this meta‐analysis is warranted because it shows a consistent benefit from such therapy over 30 years of clinical research, provides a detailed subset analysis of related issues, and highlights its value in improving outcome in this patient population.
Mixed‐methods study protocol for exploring the perception of nurses' resilience in the COVID‐19 pandemic: Designing, implementing and evaluation of intervention
Authors: Hoseini Azizi Tooba , Dehghan Nayeri Nahid , Jackson Alun C. , Bahramnezhad Fatemeh 
Published: February 2023

AbstractBackgroundWhile the necessity for interventions to build resilient nurses in the COVID‐19 pandemic is recognized, there is disagreement about the effective methods for achieving this.AimWe present our research protocol that describes plans to design and test an interventional program for promoting nurses' resilience.DesignThis sequential exploratory interventional mixed‐methods study is conducted in three phases (qualitative, intervention design, and quantitative).MethodsIt was funded from May 2021 for 24 months. In phase 1, we explored strategies for promoting resilience in the COVID‐19 pandemic from nurses' perspectives (through semi‐structured interviews). In phase 2, we will design an interventional program for promoting nurses' resilience (using the qualitative phase and literature review results). We will assess the program's effectiveness on nurses' resilience in a randomized controlled trial in phase 3.DiscussionGiven the different experiences of nurses of resilience in COVID‐19, our innovative program can guide future research to enhance nurses' resilience based on specific situations.
Establishing causal relationships between sleep and adiposity traits using Mendelian randomization
Authors: Hayes Bryony L. , Vabistsevits Marina , Martin Richard M. , Lawlor Deborah A. , Richmond Rebecca C. , Robinson Timothy 
Published: February 2023

AbstractObjectiveThe aim of this study was to systematically evaluate the direction of any potential causal effect between sleep and adiposity traits.MethodsTwo‐sample Mendelian randomization was used to assess the association of genetically predicted sleep traits with adiposity and vice versa. Using data from UK Biobank and 23andMe, the sleep traits explored were morning preference (chronotype; N = 697,828), insomnia (N = 1,331,010), sleep duration (N = 446,118), napping (N = 452,633), and daytime sleepiness (N = 452,071). Using data from the Genetic Investigation of ANthropometric Traits (GIANT) and Early Growth Genetics (EGG) consortia, the adiposity traits explored were adult BMI, hip circumference (HC), waist circumference (WC), waist‐hip ratio (WHR; N = 322,154), and childhood BMI (N = 35,668).ResultsThis study found evidence that insomnia symptoms increased mean WC, BMI, and WHR (difference in means, WC = 0.39 SD [95% CI: 0.13‐0.64], BMI = 0.47 SD [95% CI: 0.22‐0.73], and WHR = 0.34 SD [95% CI: 0.16‐0.52]). Napping increased mean WHR (0.23 SD [95% CI: 0.08‐0.39]). Higher HC, WC, and adult BMI increased odds of daytime sleepiness (HC = 0.02 SD [95% CI: 0.01‐0.04], WC = 0.04 SD [95% CI: 0.01‐0.06], and BMI 0.02 SD [95% CI: 0.00‐0.04]). This study also found that higher mean childhood BMI resulted in lower odds of napping (−0.01 SD [95% CI: 0.02‐0.00]).ConclusionsThe effects of insomnia on adiposity and of adiposity on daytime sleepiness suggest that poor sleep and weight gain may contribute to a feedback loop that could be detrimental to overall health.
New strategies for surface modification of poly (vinyl alcohol) toward click chemistry applications
Authors: Nassar Mahmoud M. A. , Alzebdeh Khalid I. , Awad Sameer A. , Khalaf Eman M. 
Published: February 2023

AbstractIn this study, new synthesis strategies for poly (vinyl alcohol) (PVA) functionalized with azidation (Az) and alkynation (Alk) were carried out for surface functionality modification. These two functionalization routes utilize azide and alkyne groups, respectively, and offer simple way to enhance the PVA crosslinking capabilities toward producing new functional polymer‐based materials. The Az functionalized PVA was prepared in two steps and denoted by PVA‐Az, while Alk functionalized PVA was prepared in one step to produce PVA‐Alk. Surfaces modification of PVA by using Az and Alk functional groups was confirmed by spectral analysis (Fourier transform infrared and 13C‐NMR). Results showed that Alk prompted excellent chemical modifications on the surface of PVA while the thermal stability was enhanced by functionalizing the Az and Alk into PVA. Furthermore, X‐ray photoelectron spectroscopy investigations showed a successful functionalization and new functional groups addition to PVA surface. Scanning electron microscope images were used to analyze the surface morphology of PVA by incorporating the Az and Alk groups, which indicated rougher surfaces compared to that of PVA backbone. In terms of efficiency and simplicity, the techniques used in this study appear to be entirely satisfactory.
Design, synthesis and characterization of novel fluorinated polyimide membranes with bulky pendant for gas transport
Authors: Wu Weilian , Lai Shiqing , Niu Hongchao , Liu Chanjuan , Huang Zengfang , Zhou Li , Huang Xiaohua 
Published: February 2023

AbstractThree novel fluorinated polyimides (PIs) were synthesized via one‐step solution polycondensation from a new diamine monomer, 4‐(3‐methoxy‐4‐(difluoromethoxy)phenyl)‐2,6‐bis(4‐aminophenyl)pyridine, and three commercially available aromatic dianhydrides. The solubility, thermal, optical, hydrophobic and gas transport properties of the obtained PIs were investigated. The results demonstrated that these polymers present good solubility in dimethylformamide, N‐methylpyrrolidone, dimethylsulfoxide, dimethylacrylamide, CHCl3, tetrahydrofuran and CH2Cl2 at room temperature or upon heating. Meanwhile, they displayed excellent thermal properties with glass transition temperature of 261–345 °C, weight loss temperatures at 10% of 518–523 °C as well as char yield of 60–62% at 800 °C in nitrogen atmosphere. Furthermore, the PI membranes have good hydrophobic properties with water contact angle value in the range 90.1–92.0°. Moreover, they show excellent optical properties, with cut‐off wavelength (λcut‐off) values of 368–381 nm and wavelength values at 80% transmittance (λ80%) of 421–462 nm. The pure gas permeabilities of He, CO2, O2 and N2 of the PI membranes were measured by the method of constant volume–variable pressure. The PI containing 4,4′‐(hexafluoroisopropyl)diphthalic anhydride moiety exhibits the largest molecular chain spacing and free volume, giving the best gas transport performance in this work. Molecular simulation results show that the introduction of fluorine‐containing structure and bulky pendant into polymer backbones is beneficial for gas transport. © 2023 Society of Industrial Chemistry.
Insights into the sulfur metabolism of Chlorobaculum tepidum by label‐free quantitative proteomics
Authors: Lyratzakis Alexandros , Meier‐Credo Jakob , Langer Julian D , Tsiotis Georgios 
Published: February 2023

AbstractChlorobaculum tepidum is an anaerobic green sulfur bacterium which oxidizes sulfide, elemental sulfur, and thiosulfate for photosynthetic growth. It can also oxidize sulfide to produce extracellular S0 globules, which can be further oxidized to sulfate and used as an electron donor. Here, we performed label‐free quantitative proteomics on total cell lysates prepared from different metabolic states, including a sulfur production state (10 h post‐incubation [PI]), the beginning of sulfur consumption (20 h PI), and the end of sulfur consumption (40 h PI), respectively. We observed an increased abundance of the sulfide:quinone oxidoreductase (Sqr) proteins in 10 h PI indicating a sulfur production state. The periplasmic thiosulfate‐oxidizing Sox enzymes and the dissimilatory sulfite reductase (Dsr) subunits showed an increased abundance in 20 h PI, corresponding to the sulfur‐consuming state. In addition, we found that the abundance of the heterodisulfide‐reductase and the sulfhydrogenase operons was influenced by electron donor availability and may be associated with sulfur metabolism. Further, we isolated and analyzed the extracellular sulfur globules in the different metabolic states to study their morphology and the sulfur cluster composition, yielding 58 previously uncharacterized proteins in purified globules. Our results show that C. tepidum regulates the cellular levels of enzymes involved in sulfur metabolism in response to the availability of reduced sulfur compounds.
On the BPS Sector in AdS3/CFT2 Holography
Authors: Martinec Emil J. , Massai Stefano , Turton David 
Published: February 2023

AbstractThe BPS sector in duality has been fertile ground for the exploration of gauge/gravity duality, from the match between black hole entropy and the CFT elliptic genus to the construction of large families of geometrical microstates and the identification of the corresponding states in the CFT. Worldsheet methods provide a tool to further explore the relation between string theory in the bulk and corresponding CFT quantities. We show how to match individual BPS strings to their counterparts in the symmetric product orbifold CFT. In the process, we find an exact match between known constructions of microstate geometries and condensates of BPS supergraviton strings, and discuss their role in the broader collection of BPS states. In particular, we explore how microstate geometries develop singularities; and how string theory resolves these singularities through the appearance of “tensionless” string dynamics, which is the continuation of structures found in the weak‐coupling CFT into the strongly coupled regime described by string theory in the bulk. We argue that such “tensionless” strings are responsible for black hole microstructure in the bulk description.
Population pharmacokinetic modeling and simulation of maribavir to support dose selection and regulatory approval in adolescents with posttransplant refractory cytomegalovirus
Authors: Sun Kefeng , Hayes Siobhan , Farrell Colm , Song Ivy H. 
Published: February 2023

AbstractMaribavir was approved by the US Food and Drug Administration for the treatment of patients aged ≥12 years and weighing ≥35 kg with posttransplant cytomegalovirus infection/disease refractory (with/without resistance) to valganciclovir, ganciclovir, cidofovir, or foscarnet, with an oral dose of 400 mg twice daily. With no pediatric clinical data available and difficulty in trial recruitment, population pharmacokinetic modeling and simulations were conducted to predict the pharmacokinetics and inform maribavir dosing in adolescents.
Traditional medicine herbs as natural product matrices in cancer chemoprevention: A trans pharmacological perspective (scoping review)
Authors: Kalachaveedu Mangathayaru , Senthil Reshma , Azhagiyamanavalan Sowndarya , Ravi Ramnarayanan , Meenakshisundaram Harikrishnan , Dharmarajan Arunasalam 
Published: February 2023

AbstractEmerging evidence on molecular biology related to tumors, inflammation, and immunity, highlights their architectural commonality shifting cancer treatment paradigms toward more economical prevention than treatment. Statistical surveys reveal exponentially growing herbal drug supplementation in cancer worldwide as vast pre‐clinical and clinical data unravel their multi‐mechanistic pharmacology. The integrative oncological approach calls for more “holistic” principles to be amalgamated into cancer care. New cancer drug development from herbs need not be limited by the archetypal ‘RCT‐Standardization’ bottlenecks. Based on comprehensive literature scoping as per Prisma‐ScR guidelines, we herein concurrently reviewed evidence‐based research reports of selected Indian Traditional Medicine (ITM) herbs of anticancer repute in parallel with their holistic therapeutics; a rationalistic exploration of ITM's scientific genre. Their synergy effect on cancer revisited using a trans‐pharmacological approach validates ITM's seemingly simplistic health/disease equation model, showing a fresh new avenue for re‐purposing whole herbal drug complexes in cancer management. Herbal drugs as per ITM are natural matrices whose dynamics of interaction in the etiopathology of cancer are conceptually and mechanistically integrative. Lateral perspective to the same as laid out in this review holds the key to their effectual development as more tangible cancer chemopreventives/new drug targets/leads if not as new pharmacological tools.
The effect of lung recruitment manoeuvre in COVID‐19 induced acute respiratory distress syndrome
Authors: Lin Wei‐Chiang , Lin Shang‐Yi , Tsai Meng‐Che , Chung Fu‐Tsai , Chang Hsiu‐Mei 
Published: February 2023

AbstractCoronavirus disease‐2019 (COVID‐19) is a highly spread infectious disease around the world. This infectious disease impacts whole body systems, specifically on respiratory system. This 57‐year‐old women had diagnosed COVID‐19 positive and progress to acute respiratory distress syndrome (ARDS) within 1 week. Mechanical ventilation with protective lung strategy, prone position could not reverse the worsen hypoxemia and bilateral lung infiltration. Recruitment manoeuvre was proceeded with 40–40 strategy and protective/ventilation tool (P/V tool). After 4 days (8 rounds) of recruitment manoeuvre, oxygenation level and lung compliance showed dramatic improvement. The patient was finally extubated at COVID‐19 Day 40 and discharged with long term oxygen use at COVID‐19 Day 60. In this case, we report how recruitment manoeuvre can improve severe hypoxemia and bilateral lung infiltration dramatically in ARDS.
Secure formation control for resilient multi‐agent cyber‐physical systems under DoS attacks and faults
Authors: Liu Yishi , Dong Xiwang , Ren Zhang , Liu Jianwei 
Published: February 2023

AbstractA distributed cyber‐security and fault tolerance formation problem is considered in this paper. This is done though a multi‐agent system in which all agents concentrate on a formation reference function and accomplish a desired time‐varying formation even in the presence of malicious attacks and multiple faults. To achieve the resilient control task, a distributed control protocol using an event‐triggered technique and active reconfigurable strategy is proposed in the face of adverse effects for the overall system. When denial of service is launched by adversaries, the attack parameters are bounded by analyzing the Lyapunov stability theorem and the property of the Laplacian matrix. To improve the capability of fault‐tolerance, an observer‐based fault estimator is used to calculate fault values. The simulation results validate that the presented scheme can perfectly address the distributed formation issue with faults over attack intervals.
Adaptive optimal formation control for unmanned surface vehicles with guaranteed performance using actor‐critic learning architecture
Authors: Chen Lin , Dong Chao , He Shude , Dai Shi‐Lu 
Published: February 2023

SummaryIn this article, an optimized formation control algorithm is presented for unmanned surface vehicles (USVs) with collision avoidance and prescribed performance. The prescribed formation geometry is designed in the leader‐follower formation architecture, in which each vehicle tracks its intermediary leader with preserving a desired separation. A prescribed performance control design technique is introduced to guarantee the transient and steady‐state performance specifications on formation errors. Radial basis function neural networks (NNs) are employed to approximate modeling uncertainties including damping terms and unmodeled dynamics. Based on an actor‐critic learning strategy, a reinforcement learning (RL) algorithm is proposed to ensure the optimality of formation control and the specified tracking accuracy simultaneously, in which actor NNs take appropriate control behaviors by interacting with the external environment, and critic NNs evaluate the control performance and generate a reinforcement signal to actor NNs for facilitating the improvement of subsequent behaviors. Stability analysis shows that the proposed optimal formation controller achieves semi‐global uniform ultimate boundedness of closed‐loop adaptive systems with prescribed performance. Comparative simulation results illustrate the effectiveness and superiority of the presented control algorithm.
Adaptive fuzzy fixed‐time control for non‐triangular structural stochastic switching nonlinear systems
Authors: Xu Ke , Wang Huanqing , Liu Peter Xiaoping 
Published: February 2023

AbstractIn this article, the problem of adaptive fixed‐time tracking control is addressed for non‐triangular structural stochastic switching nonlinear systems. Fuzzy logic systems are used to compensate for unknown nonlinearities, and in the meantime, to avoid the algebraic loop problem, which exists in traditional backstepping controller design processes for non‐triangular structural nonlinear systems. The unknown control gain problem is addressed by the construction of proper Lyapunov function candidates. By employing Lyapunov stability theorem, all the closed‐loop signals can be ensured to be semi‐globally practical fixed‐time stable, the output signal can track the desired signal, and the tracking error can converge to a small zone around the origin. The effectiveness of the developed control approach is verified through simulation results.
Validation of the harmonized partial factor method for design and assessment of concrete structures as proposed for fib model code 2020
Authors: Caspeele Robby , Van Den Hende Karel 
Published: February 2023

AbstractWhen considering the assessment of concrete structures, a consistent approach to assess the safety level of existing structures in an objective and well‐founded way is currently still lacking in practice. As such, fib TG3.1 has developed proposals for the quantification of adjusted partial factors for the assessment of existing structures and has harmonized these proposals with partial factors for design. This resulted in a set of equations and tabulated values for the determination of partial factors for the design of new structures as well as the assessment of existing structures, currently under consideration for the fib Model Code 2020 (MC2020). In this contribution, the equations and tabulated values for partial factors as proposed for MC2020 are briefly summarized and applied in a full‐probabilistic first order reliability method (FORM) analysis in order to assess the accuracy of the proposal with respect to reaching chosen target reliability levels. The proposals appear to lead to a consistent and adequate framework for both design and assessment, that enables targeted safety levels to be achieved.