bluuebunny/crossref_metadata_2025 huggingface dataset:
The Use of the TARGET Antibiotic Checklist to Support Antimicrobial Stewardship in England’s Community Pharmacies
Authors: Parekh Sejal , Hayes Catherine V. , Loader Jill , Ashiru-Oredope Diane , Hand Kieran , Hicks Gemma , Lecky Donna
Published: March 2023

Antimicrobial Stewardship (AMS) requires effective teamwork between healthcare professionals, with patients receiving consistent messages from all healthcare professionals on the appropriate antimicrobial use. Patient education may reduce patients’ expectations to receive antibiotics for self-limiting conditions and reduce the pressure on primary care clinicians to prescribe antibiotics. The TARGET Antibiotic Checklist is part of the national AMS resources for primary care and aims to support interaction between community pharmacy teams and patients prescribed antibiotics. The Checklist, completed by the pharmacy staff with patients, invites patients to report on their infection, risk factors, allergies, and knowledge of antibiotics. The TARGET antibiotic checklist was part of the AMS criteria of England’s Pharmacy Quality Scheme for patients presenting with an antibiotic prescription from September 2021 to May 2022. A total of 9950 community pharmacies claimed for the AMS criteria and 8374 of these collectively submitted data from 213,105 TARGET Antibiotic Checklists. In total, 69,861 patient information leaflets were provided to patients to aid in the knowledge about their condition and treatment. 62,544 (30%) checklists were completed for patients with an RTI; 43,093 (21%) for UTI; and 30,764 (15%) for tooth/dental infections. An additional 16,625 (8%) influenza vaccinations were delivered by community pharmacies prompted by discussions whilst using the antibiotic checklist. Community pharmacy teams promoted AMS using the TARGET Antibiotic Checklist, providing indication-specific education and positively impacting the uptake of influenza vaccinations.
Impact of Adding a Rapid PCR-Based Blood Culture Identification Panel to the Antimicrobial Stewardship Program of Patients with Febrile Neutropenia in a Peruvian Referral Hospital
Authors: Pérez-Lazo Giancarlo , del Valle-Mendoza Juana , Sandoval-Ahumada Roxana , Soto-Febres Fernando , Castillo-Córdova Raúl , Zárate-Tantaleán Melissa , Morales-Castillo Liliana , Páucar-Miranda Celia Joanna , Altamirano-Molina Milagros , Pacheco-Modesto Iván , Ruiz de Somocurcio-Cruzado Claudia , Arana-Jurado Denis , del Villar-Alarcón Carmen , Vargas-Castro Olga , Díaz-Bardales Carol , Guerrero-Arismendiz Bruno , Eyzaguirre-Zapata Renee , Aguilar-Luis Miguel Angel , Martins-Luna Johanna , Silva-Caso Wilmer
Published: March 2023

The addition of Biofire® FilmArray® Blood Culture Identification panel 2 (BCID2) to the antimicrobial stewardship program (ASP) could improve outcomes in bloodstream infections (BSI) of patients with febrile neutropenia (FN). A pre- and post-quasi-experimental single-center study was conducted at a reference hospital in Peru. Three groups were considered: patients with BSI before ASP intervention (control group), patients with BSI after ASP intervention (group 1), and patients with BSI after ASP intervention plus BCID2 PCR Panel implementation (group 2). Overall, 93 patients were identified (32 control, 30 group 1, 31 group 2). The median time to effective therapy was significantly shorter in group 2 compared to group 1 and control group, respectively (3.75 vs. 10 h, p = 0.004; 3.75 vs. 19 h, p < 0.001). No significant differences in terms of relapse of bacteremia, in-hospital mortality (all cause), and 30-day-all-cause hospital readmission between the three study periods were found. The appropriateness of empirical antimicrobial use, adding or change, and the following de-escalation or discontinuation was significant when the two intervention periods were compared with the control group (p < 0.001). In addition to the lack of local studies documenting the microbiological profile of FN episodes, adding syndromic panels-based testing could allow for the consolidation of ASP strategies.
Large-Scale Qualitative and Quantitative Assessment of Dityrosine Crosslinking Omics in Response to Endogenous and Exogenous Hydrogen Peroxide in Escherichia coli
Authors: Zhou Xiangzhe , Liu Feng , Li Nuomin , Zhang Yongqian
Published: March 2023

Excessive hydrogen peroxide causes oxidative stress in cells. The oxidation of two tyrosine residues in proteins can generate o,o′-dityrosine, a putative biomarker for protein oxidation, which plays critical roles in a variety of organisms. Thus far, few studies have investigated dityrosine crosslinking under endogenous or exogenous oxidative conditions at the proteome level, and its physiological function remains largely unknown. In this study, to investigate qualitative and quantitative dityrosine crosslinking, two mutant Escherichia coli strains and one mutant strain supplemented with H2O2 were used as models for endogenous and exogenous oxidative stress, respectively. By integrating high-resolution liquid chromatography—mass spectrometry and bioinformatic analysis, we created the largest dityrosine crosslinking dataset in E. coli to date, identifying 71 dityrosine crosslinks and 410 dityrosine loop links on 352 proteins. The dityrosine-linked proteins are mainly involved in taurine and hypotaurine metabolism, citrate cycle, glyoxylate, dicarboxylate metabolism, carbon metabolism, etc., suggesting that dityrosine crosslinking may play a critical role in regulating the metabolic pathways in response to oxidative stress. In conclusion, we have reported the most comprehensive dityrosine crosslinking in E. coli for the first time, which is of great significance in revealing its function in oxidative stress.
Stomatal Responses of Two Drought-Tolerant Barley Varieties with Different ROS Regulation Strategies under Drought Conditions
Authors: Lv Xiachen , Li Yihong , Chen Rongjia , Rui Mengmeng , Wang Yizhou
Published: March 2023

Drought stress is a major obstacle to agricultural production. Stomata are central to efforts to improve photosynthesis and water use. They are targets for manipulation to improve both processes and the balance between them. An in-depth understanding of stomatal behavior and kinetics is important for improving photosynthesis and the WUE of crops. In this study, a drought stress pot experiment was performed, and a transcriptome analysis of the leaves of three contrasting, cultivated barley genotypes Lumley (Lum, drought-tolerant), Golden Promise (GP, drought-sensitive), and Tadmor (Tad, drought-tolerant), generated by high-throughput sequencing, were compared. Lum exhibited a different WUE at the leaf and whole-plant levels and had greater CO2 assimilation, with a higher gs under drought stress. Interestingly, Lum showed a slower stomatal closure in response to a light–dark transition and significant differences compared to Tad in stomatal response to the exogenous application of ABA, H2O2, and CaCl2. A transcriptome analysis revealed that 24 ROS-related genes were indeed involved in drought response regulation, and impaired ABA-induced ROS accumulation in Lum was identified using ROS and antioxidant capacity measurements. We conclude that different stomatal ROS responses affect stomatal closure in barley, demonstrating different drought regulation strategies. These results provide valuable insight into the physiological and molecular basis of stomatal behavior and drought tolerance in barley.
Release of High-Mobility Group Box-1 after a Raynaud’s Attack Leads to Fibroblast Activation and Interferon-γ Induced Protein-10 Production: Role in Systemic Sclerosis Pathogenesis
Authors: Al-Adwi Yehya , Atzeni Isabella M. , Doornbos-van der Meer Berber , Abdulle Amaal Eman , van Roon Anniek M. , Stel Alja , van Goor Harry , Smit Andries J. , Westra Johanna , Mulder Douwe J.
Published: March 2023

Raynaud’s Phenomenon (RP) leading to repetitive ischemia and reperfusion (IR) stress, is the first recognizable sign of systemic sclerosis (SSc) leading to increased oxidative stress. High-mobility group box-1 (HMGB1) is a nuclear factor released by apoptotic and necrotic cells after oxidative stress. Since HMGB1 can signal through the receptor for advanced glycation end products (RAGE), we investigated whether an RP attack promotes the release of HMGB1, leading to fibroblast activation and the upregulation of interferon (IFN)-inducible genes. A cold challenge was performed to simulate an RP attack in patients with SSc, primary RP (PRP), and healthy controls. We measured levels of HMGB1 and IFN gamma-induced Protein 10 (IP-10) at different time points in the serum. Digital perfusion was assessed by photoplethysmography. In vitro, HMGB1 or transforming growth factor (TGF-β1) (as control) was used to stimulate healthy human dermal fibroblasts. Inflammatory, profibrotic, and IFN-inducible genes, were measured by RT-qPCR. In an independent cohort, sera were obtained from 20 patients with SSc and 20 age- and sex-matched healthy controls to determine HMGB1 and IP-10 levels. We found that HMGB1 levels increased significantly 30 min after the cold challenge in SSc compared to healthy controls. In vitro stimulation with HMGB1 resulted in increased mRNA expression of IP-10, and interleukin-6 (IL-6) while TGF-β1 stimulation promoted IL-6 and Connective Tissue Growth Factor (CTGF). In serum, both HMGB1 and IP-10 levels were significantly higher in patients with SSc compared to healthy controls. We show that cold challenge leads to the release of HMGB1 in SSc patients. HMGB1 induces IP-10 expression in dermal fibroblasts partly through the soluble RAGE (sRAGE) axis suggesting a link between RP attacks, the release of HMGB1 and IFN-induced proteins as a putative early pathogenetic mechanism in SSc.
Preeclampsia Affects Lipid Metabolism and HDL Function in Mothers and Their Offspring
Authors: Stadler Julia T. , Scharnagl Hubert , Wadsack Christian , Marsche Gunther
Published: March 2023

Preeclampsia (PE) is linked to an overall increased cardiovascular risk for both the mother and child. Functional impairment of high-density lipoproteins (HDL) may contribute to the excess cardiovascular risk associated with PE. In this study, we investigated the effects of PE on maternal and neonatal lipid metabolism, and the parameters of HDL composition and function. The study cohort included 32 normotensive pregnant women, 18 women diagnosed with early-onset PE, and 14 women with late-onset PE. In mothers, early- and late-onset PE was associated with atherogenic dyslipidemia, characterized by high plasma triglycerides and low HDL-cholesterol levels. We observed a shift from large HDL to smaller HDL subclasses in early-onset PE, which was associated with an increased plasma antioxidant capacity in mothers. PE was further associated with markedly increased levels of HDL-associated apolipoprotein (apo) C-II in mothers, and linked to the triglyceride content of HDL. In neonates of early-onset PE, total cholesterol levels were increased, whereas HDL cholesterol efflux capacity was markedly reduced in neonates from late-onset PE. In conclusion, early- and late-onset PE profoundly affect maternal lipid metabolism, potentially contributing to disease manifestation and increased cardiovascular risk later in life. PE is also associated with changes in neonatal HDL composition and function, demonstrating that complications of pregnancy affect neonatal lipoprotein metabolism.
Dynamic Offloading Loading Optimization in Distributed Fault Diagnosis System with Deep Reinforcement Learning Approach
Authors: Yu Liang , Guo Qixin , Wang Rui , Shi Minyan , Yan Fucheng , Wang Ran
Published: March 2023

Artificial intelligence and distributed algorithms have been widely used in mechanical fault diagnosis with the explosive growth of diagnostic data. A novel intelligent fault diagnosis system framework that allows intelligent terminals to offload computational tasks to Mobile edge computing (MEC) servers is provided in this paper, which can effectively address the problems of task processing delays and enhanced computational complexity. As the resources at the MEC and intelligent terminals are limited, performing reasonable resource allocation optimization can improve the performance, especially for a multi-terminals offloading system. In this study, to minimize the task computation delay, we jointly optimize the local content splitting ratio, the transmission/computation power allocation, and the MEC server selection under a dynamic environment with stochastic task arrivals. The challenging dynamic joint optimization problem is formulated as a reinforcement learning (RL) problem, which is designed as the computational offloading policies to minimize the long-term average delay cost. Two deep RL strategies, deep Q-learning network (DQN) and deep deterministic policy gradient (DDPG), are adopted to learn the computational offloading policies adaptively and efficiently. The proposed DQN strategy takes the MEC selection as a unique action while using the convex optimization approach to obtain the local content splitting ratio and the transmission/computation power allocation. Simultaneously, the actions of the DDPG strategy are selected as all dynamic variables, including the local content splitting ratio, the transmission/computation power allocation, and the MEC server selection. Numerical results demonstrate that both proposed strategies perform better than the traditional non-learning schemes. The DDPG strategy outperforms the DQN strategy in all simulation cases exhibiting minimal task computation delay due to its ability to learn all variables online.
Effects of Granular Gradation on the Compressibility and Permeability of Lime-Stabilized Slurry with High Water Content
Authors: Weng Zhenqi , Zheng Yueyue , Zhu Qinhao , Sun Honglei , Ni Dingyu
Published: March 2023

Lime stabilization is one of the main methods to achieve efficient treatment and resource utilization of waste slurry. This study investigated the compressibility and permeability of lime-stabilized slurry with different granular gradations based on the ultra-low stress consolidation/permeability test and identified the stabilization mechanism of lime-stabilized slurry with high water content by mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM) tests. The test results indicated that (i) lime-stabilized slurry with high water content showed obvious evidence of remolded yield stress and (ii) the remolded yield stress increased with the increasing lime dosage. Lime was found to induce the flocculation of clay to form aggregates through ion exchange, further stabilizing them through the volcanic ash reaction, thus increasing the remolded yield strength of the stabilized slurry. The remolded yield stress of the Hangzhou stabilized slurry with a 1% lime dosage was shown to increase from 0 kPa to 5.71 kPa, while the compression index CS1 decreased by 68.8%. In addition, the pore volumes and diameters of the soil increased once the flocculation was completed, leading to increased permeability of the stabilized slurry. It was, however, observed that the stabilized slurry permeability did not increase infinitely with the increasing lime dosage, but on the contrary decreased once the lime dosage exceeded a certain threshold value. The permeability of the Hangzhou stabilized slurry was found to be one order of magnitude higher than that of the remolded slurry at the optimal dosage. Whereas for slurry with high clay content, the recommended lime dosage was established to be 2% to reduce its compressibility or enhance its permeability; for slurry with high silt content, the recommended lime dosage was ascertained to be 3%.
Energy Balance of the Dynamic Impact Stressing of Conveyor Belts
Authors: Ambriško Ľubomír , Marasová Daniela , Klapko Peter
Published: March 2023

This paper presents research into the energy balance of stressing conveyor belts by impact processes. Research is described in the areas of measuring the resistance of conveyor belts to puncture, the impact process, and the effect of changes to the impact height on the tensile and impact forces. Measurements were performed on a rubber–textile belt with a polyamide carcass. Hammers with pyramidal and spherical impactors were used to compare the resistance of the examined conveyor. Values were obtained for the maximum energies for the selected impact heights and the residual positional energies for the measured bounce heights. The difference between these energies represents the impact energy. The results confirmed that the impact energy of a hammer with a pyramidal impactor is greater than the impact energy of a hammer with a spherical impactor, while this difference increases with increasing impact height. The shape of the pyramidal impactor simulates sharp-edged materials, which is the cause of greater damage in the tribological interaction with the conveyor belt. This paper provides information for determining the limit conditions for setting appropriate impact heights depending on the weight of the material transported using a given belt conveyor.
Research on the Efficient Space Debris Observation Method Based on Optical Satellite Constellations
Authors: Li Gongqiang , Liu Jing , Jiang Hai , Liu Chengzhi
Published: March 2023

The increasing amount of space debris poses a major threat to the security of space assets. The timely acquisition of space debris orbital data through observations is essential. We established a mathematical model of optical satellite constellations for space debris observation, designed a high-quality constellation configuration, and designed a space debris tracking observation scheduling algorithm. These tools can realize the efficient networking of space debris from a large number of optical satellite observation facilities. We designed a constellation consisting of more than 20 low-Earth orbit (LEO) satellites, mainly dedicated to the observation of LEO space objects. According to the observation scheduling method, the satellite constellation can track and observe more than 93% of the targets every day, increase the frequency of orbital data updates, and provide support for the realization of orbital space debris cataloguing. Designing optical satellite constellations to observe space debris can help realize the advance perception of dangerous collisions, timely detect dangerous space events, make key observations about high-risk targets, greatly reduce the false alarm rate of collisions, and provide observational data support for space collisions.
Railcar Dynamic Response during Braking Maneuvers Based on Frequency Analysis
Authors: Hurtado-Hurtado Gerardo , Morales-Velazquez Luis , Otremba Frank , Jáuregui-Correa Juan C.
Published: March 2023

The dynamic response of a vehicle during braking is influenced by the tangential forces developed at the wheel-rail’s contact surface. The friction coefficient affects the load transfer from the wheel’s tread to the vehicle. In this work, the vibrations of a scale-down railway vehicle are monitored during braking and their relationship with the friction coefficient between wheel and rail is found out. The vehicle is instrumented with encoders, accelerometers, and is controlled via Bluetooth. The tests are carried out with clean and friction-modified rails. The tangential forces transmitted from the wheel to the railcar’s body are visualized in time and frequency using a proposed correlation algorithm based on the outputs of the Continuous Wavelet Transform (CWT). The results demonstrate that tangential forces have a significant impact on railway vehicles under conditions of high friction coefficients and large creep values.
Qualitative and Quantitative Evaluation of Multivariate Time-Series Synthetic Data Generated Using MTS-TGAN: A Novel Approach
Authors: Yadav Parul , Gaur Manish , Fatima Nishat , Sarwar Saqib
Published: March 2023

To obtain high performance, generalization, and accuracy in machine learning applications, such as prediction or anomaly detection, large datasets are a necessary prerequisite. Moreover, the collection of data is time-consuming, difficult, and expensive for many imbalanced or small datasets. These challenges are evident in collecting data for financial and banking services, pharmaceuticals and healthcare, manufacturing and the automobile, robotics car, sensor time-series data, and many more. To overcome the challenges of data collection, researchers in many domains are becoming more and more interested in the development or generation of synthetic data. Generating synthetic time-series data is far more complicated and expensive than generating synthetic tabular data. The primary objective of the paper is to generate multivariate time-series data (for continuous and mixed parameters) that are comparable and evaluated with real multivariate time-series synthetic data. After being trained to produce such data, a novel GAN architecture named as MTS-TGAN is proposed and then assessed using both qualitative measures namely t-SNE, PCA, discriminative and predictive scores as well as quantitative measures, for which an RNN model is implemented, which calculates MAE and MSLE scores for three training phases; Train Real Test Real, Train Real Test Synthetic and Train Synthetic Test Real. The model is able to reduce the overall error up to 13% and 10% in predictive and discriminative scores, respectively. The research’s objectives are met, and the outcomes demonstrate that MTS-TGAN is able to pick up on the distribution and underlying knowledge included in the attributes of the real data and it can serve as a starting point for additional research in the respective area.
Engineering Application of a Product Quality Testing Method within the SCADA System Operator Education Quality Assessment Process
Authors: Dąbrowski Tadeusz , Bednarek Marcin , Rosiński Adam , Olchowik Wiktor
Published: March 2023

An education system can be considered as an anthropotechnical system consisting of an education subject (e.g., trainee, operator), examiner (teacher), system decision maker (e.g., teaching module coordinator), and the environment (e.g., administrative, social, IT). The outcomes of this system are the knowledge and skills acquired by a trained student. The educational effect is usually diagnosed in the form of an exam or test. The study addresses the issue related to the credibility of applied assessment methods, knowledge qualification levels, and assessment errors. The analysis is conducted in accordance with the principles applied in statistical quality control when studying product population defectiveness. Using known methods for testing product defectiveness, the authors characterized the trainee educational effect (i.e., his/her knowledge and skill level) in a technical manner. The probability of an event wherein the examined person demonstrating a specific knowledge level achieves an adequate grade, has been adopted as the reliability measure. The conducted calculations provided graphs of the reliability functions involving the grades received within the “traditional” examination and testing process. The authors suggested an application that tests a SCADA system user, based on tools known to the trainee. The application was developed using the SCADA suite used as a visualization element in distributed control systems. This application enables the automation of the operator diagnosis process.
A Comprehensive Review of Energy Regeneration and Conversion Technologies Based on Mechanical–Electric–Hydraulic Hybrid Energy Storage Systems in Vehicles
Authors: Feng Bingyin , Xu Huijuan , Wang Aobing , Gao Lijun , Bi Yanjun , Zhang Xin
Published: March 2023

The primary purpose of this paper is to investigate energy regeneration and conversion technologies based on mechanical–electric–hydraulic hybrid energy storage systems in vehicles. There has been renewed interest in hydraulic storage systems since evidence has been presented that shows that they have the distinct advantages of high energy output and energy recuperation compared to electrical energy recovery systems, which are widely applied in electric vehicles; however, they are known to be high-cost, with a complicated structure and not zero carbon. In this paper, we first review recent research on hydraulic energy regeneration and conversion technologies. Secondly, as the main part of this paper, the latest technological progress and breakthroughs of the mechanical–electric–hydraulic hybrid energy storage systems in vehicles—which are divided into four categories: passenger, minibus and bus, commercial vehicle and special vehicle—are analyzed and discussed in depth. In addition, the current research status of energy management techniques is presented and summarized. Finally, prospects and challenges are suggested and explained. It is evident from the literature review that the mechanical–electric–hydraulic hybrid systems perform excellently in vehicles. Clearly, this review will be helpful to understand, explore and define the hydraulic vehicle of the future concerning energy optimization and environmental friendliness.
Data-Driven Fracture Morphology Prognosis from High Pressured Modified Proppants Based on Stochastic-Adam-RMSprop Optimizers; tf.NNR Study
Authors: Wayo Dennis Delali Kwesi , Irawan Sonny , Satyanaga Alfrendo , Kim Jong
Published: March 2023

Data-driven models with some evolutionary optimization algorithms, such as particle swarm optimization (PSO) and ant colony optimization (ACO) for hydraulic fracturing of shale reservoirs, have in recent times been validated as one of the best-performing machine learning algorithms. Log data from well-logging tools and physics-driven models is difficult to collate and model to enhance decision-making processes. The study sought to train, test, and validate synthetic data emanating from CMG’s numerically propped fracture morphology modeling to support and enhance productive hydrocarbon production and recovery. This data-driven numerical model was investigated for efficient hydraulic-induced fracturing by using machine learning, gradient descent, and adaptive optimizers. While satiating research curiosities, the online predictive analysis was conducted using the Google TensorFlow tool with the Tensor Processing Unit (TPU), focusing on linear and non-linear neural network regressions. A multi-structured dense layer with 1000, 100, and 1 neurons was compiled with mean absolute error (MAE) as loss functions and evaluation metrics concentrating on stochastic gradient descent (SGD), Adam, and RMSprop optimizers at a learning rate of 0.01. However, the emerging algorithm with the best overall optimization process was found to be Adam, whose error margin was 101.22 and whose accuracy was 80.24% for the entire set of 2000 synthetic data it trained and tested. Based on fracture conductivity, the data indicates that there was a higher chance of hydrocarbon production recovery using this method.
Rating Prediction Quality Enhancement in Low-Density Collaborative Filtering Datasets
Authors: Margaris Dionisis , Vassilakis Costas , Spiliotopoulos Dimitris , Ougiaroglou Stefanos
Published: March 2023

Collaborative filtering has proved to be one of the most popular and successful rating prediction techniques over the last few years. In collaborative filtering, each rating prediction, concerning a product or a service, is based on the rating values that users that are considered “close” to the user for whom the prediction is being generated have given to the same product or service. In general, “close” users for some user u correspond to users that have rated items similarly to u and these users are termed as “near neighbors”. As a result, the more reliable these near neighbors are, the more successful predictions the collaborative filtering system will compute and ultimately, the more successful recommendations the recommender system will generate. However, when the dataset’s density is relatively low, it is hard to find reliable near neighbors and hence many predictions fail, resulting in low recommender system reliability. In this work, we present a method that enhances rating prediction quality in low-density collaborative filtering datasets, by considering predictions whose features are associated with high prediction accuracy as additional ratings. The presented method’s efficacy and applicability are substantiated through an extensive multi-parameter evaluation process, using widely acceptable low-density collaborative filtering datasets.
Circular RNAs Could Encode Unique Proteins and Affect Cancer Pathways
Authors: Crudele Francesca , Bianchi Nicoletta , Terrazzan Anna , Ancona Pietro , Frassoldati Antonio , Gasparini Paolo , D’Adamo Adamo P. , Papaioannou Dimitrios , Garzon Ramiro , Wójcicka Anna , Gaj Paweł , Jażdżewski Krystian , Palatini Jeffrey , Volinia Stefano
Published: March 2023

circRNAs constitute a novel class of RNA, generally considered as non-coding RNAs; nonetheless, their coding potential has been under scrutiny. In this work, we systematically explored the predicted proteins of more than 160,000 circRNAs detected by exome capture RNA-sequencing and collected in the MiOncoCirc pan-cancer compendium, including normal and cancer samples from different types of tissues. For the functional evaluation, we compared their primary structure and domain composition with those derived from the same linear mRNAs. Among the 4362 circRNAs potentially encoding proteins with a unique primary structure and 1179 encoding proteins with a novel domain composition, 183 were differentially expressed in cancer. In particular, eight were associated with prognosis in acute myeloid leukemia. The functional classification of the dysregulated circRNA-encoded polypeptides showed an enrichment in the heme and cancer signaling, DNA-binding, and phosphorylation processes, and disclosed the roles of some circRNA-based effectors in cancer.
Pressure-Dependent Elevation of Vasoactive Intestinal Peptide Level in Chicken Choroid
Authors: Privalov Evgeny , Zenkel Matthias , Schloetzer-Schrehardt Ursula , Kuerten Stefanie , Bergua Antonio , Hohberger Bettina
Published: March 2023

Purpose: Autonomic control is important in maintaining ocular integrity. As recent data suggested that intrinsic choroidal neurons (ICN), an intrinsic choroidal autonomic control, may regulate choroidal thickening via release of the vasodilative vasoactive intestinal peptide (VIP), it was the aim of the study to investigate the level of choroidal VIP (VIPchor) in the presence of an increased atmospheric pressure in a chicken model. Methods: Chicken choroidal whole mounts were exposed to ambient pressure (n = 20) and 40 mm Hg (n = 20) in a PC-controlled, open chamber system for 24 and 72 h, respectively. The VIP concentration was analyzed by ELISA, and the total protein concentration was measured by the BCA assay. Statistical analysis was done using an unpaired two-tailed t-test. Results: The pressurization systems enabled choroidal whole mount pressurization (40 mm Hg) with humidifying, pressure, temperature, and gas exchange. Overall, the VIPchor level concentration was significantly increased at 40 mmHg compared to the ambient pressure (30.09 ± 7.18 pg vs. 20.69 ± 3.24 pg; p < 0.0001). Subgroup analysis yielded a significantly increased VIPchor level at 40 mmHg compared to the ambient pressure after 24 h (28.42 ± 6.03 pg vs. 20.76 ± 4.06 pg; p = 0.005) and 72 h (31.77 ± 7.82 pg vs. 20.61 ± 2.12 pg; p = 0.002), respectively. The VIPchor elevation at 40 mm Hg ranged between 1.37- (24 h) and 1.54-fold (72 h) compared to the ambient pressure. No difference was observed between the VIPchor level at 24 h and 72 h (p > 0.05). Conclusions: The increase of the total choroidal VIP level, representing the intracellular VIP content, in the presence of an increased ambient pressure argues for a retention of VIP within the neurons, decreasing both vasodilatation and, consequently, choroid thickness. This finding might be a passive or even active function of ICN in the regulation of choroidal thickness, ocular integrity and IOP.
Proteasome-Associated Proteins, PA200 and ECPAS, Are Essential for Murine Spermatogenesis
Authors: Sato Ban , Kim Jiwoo , Morohoshi Kazunori , Kang Woojin , Miyado Kenji , Tsuruta Fuminori , Kawano Natsuko , Chiba Tomoki
Published: March 2023

Proteasomes are highly sophisticated protease complexes that degrade non-lysosomal proteins, and their proper regulation ensures various biological functions such as spermatogenesis. The proteasome-associated proteins, PA200 and ECPAS, are predicted to function during spermatogenesis; however, male mice lacking each of these genes sustain fertility, raising the possibility that these proteins complement each other. To address this issue, we explored these possible roles during spermatogenesis by producing mice lacking these genes (double-knockout mice; dKO mice). Expression patterns and quantities were similar throughout spermatogenesis in the testes. In epididymal sperm, PA200 and ECPAS were expressed but were differentially localized to the midpiece and acrosome, respectively. Proteasome activity was considerably reduced in both the testes and epididymides of dKO male mice, resulting in infertility. Mass spectrometric analysis revealed LPIN1 as a target protein for PA200 and ECPAS, which was confirmed via immunoblotting and immunostaining. Furthermore, ultrastructural and microscopic analyses demonstrated that the dKO sperm displayed disorganization of the mitochondrial sheath. Our results indicate that PA200 and ECPAS work cooperatively during spermatogenesis and are essential for male fertility.
Oral Treatment with d-RD2RD2 Impedes Early Disease Mechanisms in SOD1*G93A Transgenic Mice but Does Not Prolong Survival
Authors: Wintz Katharina , Post Julia , Langen Karl-Josef , Willbold Dieter , Willuweit Antje , Kutzsche Janine
Published: March 2023

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting upper and lower motor neurons, thus, progressing to complete muscle loss until the patient dies from respiratory arrest. The disease is not curable, and patients die approximately 2–5 years after diagnosis. Studying the underlying disease mechanisms to get access to new treatment options is, therefore, essential for patients’ benefit. However, so far, only three drugs that alleviate the symptoms have been approved by the U.S. Food and Drug Administration (FDA). A new drug candidate for the treatment of ALS is the all-d-enantiomeric peptide RD2RD2. In this study, we investigated the therapeutic effect of RD2RD2 in two setups. First, we analyzed disease progression and survival in 7 week-old B6.Cg-Tg(SOD1*G93A)1Gur/J mice. Second, we confirmed the result of the survival analysis in the B6SJL-Tg(SOD1*G93A)1Gur/J mouse line. Shortly before disease onset, the mice were treated daily with an oral dose of 50 mg/kg body weight. Treatment with RD2RD2 led to a delayed disease onset and reduced motor phenotype as shown using the SHIRPA test, the splay reflex test, and the pole test, but did not affect survival. In conclusion, RD2RD2 has the ability to delay the onset of symptoms.
A Novel Benchtop Device for Efficient and Simple Purification of Cytokines, Growth Factors and Stem Cells from Adipose Tissue
Authors: Semenzato Martina , Zambello Ludovica , Fumarola Stefania , Motta Enrico , Piroli Luana , Scorrano Luca , Bean Camilla
Published: March 2023

Lipoaspirates represent a source of adult stem cells, cytokines, and growth factors of adipocyte origin with immunomodulation and regenerative medicine potential. However, rapid and simple protocols for their purification using self-contained devices that can be deployed at the points of care are lacking. Here, we characterize and benchmark a straightforward mechanical dissociation procedure to collect mesenchymal stem cells (MSCs) and soluble fractions from lipoaspirates. IStemRewind, a benchtop self-contained cell purification device, allowed a one-procedure purification of cells and soluble material from lipoaspirates with minimal manipulation. The recovered cellular fraction contained CD73+, CD90+, CD105+, CD10+ and CD13+ MSCs. These markers were comparably expressed on MSCs isolated using IstemRewind or classic enzymatic dissociation procedures, apart from CD73+ MSCs, which were even more abundant in IStemRewind isolates. IstemRewind-purified MSCs retained viability and differentiation into adipocytes and osteocytes, even after a freezing-thawing cycle. Levels of IL4, IL10, bFGF and VEGF were higher compared to the pro-inflammatory cytokines TNFα, IL1β and IL6 in the IStemRewind-isolated liquid fraction. In sum, IStemRewind can be useful for straightforward, rapid, and efficient isolation of MSCs and immunomodulatory soluble factors from lipoaspirates, opening the possibility to directly isolate and employ them at the point-of-care.
Aerodynamic System Machine Learning Modeling with Gray Wolf Optimization Support Vector Regression and Instability Identification Strategy of Wavelet Singular Spectrum
Authors: Zhang Mingming , Kong Pan , Xia Aiguo , Tuo Wei , Lv Yongzhao , Wang Shaohong
Published: March 2023

The prediction of a stall precursor in an axial compressor is the basic guarantee to the stable operation of an aeroengine. How to predict and intelligently identify the instability of the system in advance is of great significance to the safety performance and active control of the aeroengine. In this paper, an aerodynamic system modeling method combination with the wavelet transform and gray wolf algorithm optimized support vector regression (WT-GWO-SVR) is proposed, which breaks through the fusion technology based on the feature correlation of chaotic data. Because of the chaotic characteristic represented by the sequence, the correlation-correlation (C-C) algorithm is adopted to reconstruct the phase space of the spatial modal. On the premise of finding out the local law of the dynamic system variety, the machine learning method is applied to model the reconstructed low-frequency components and high-frequency components, respectively. As the key part, the parameters of the SVR model are optimized by the gray wolf optimization algorithm (GWO) from the biological view inspired by the predatory behavior of gray wolves. In the definition of the hunting behaviors of gray wolves by mathematical equations, it is superior to algorithms such as differential evolution and particle swarm optimization. In order to further improve the prediction accuracy of the model, the multi-resolution and equivalent frequency distribution of the wavelet transform (WT) are used to train support vector regression. It is shown that the proposed WT-GWO-SVR hybrid model has a better prediction accuracy and reliability with the wavelet reconstruction coefficients as the inputs. In order to effectively identify the sign of the instability in the modeling system, a wavelet singular information entropy algorithm is proposed to detect the stall inception. By using the three sigma criteria as the identification strategy, the instability early warning can be given about 102r in advance, which is helpful for the active control.
Natural Oscillatory Frequency Slowing in the Premotor Cortex of Early-Course Schizophrenia Patients: A TMS-EEG Study
Authors: Donati Francesco L. , Mayeli Ahmad , Sharma Kamakashi , Janssen Sabine A. , Lagoy Alice D. , Casali Adenauer G. , Ferrarelli Fabio
Published: March 2023

Despite the heavy burden of schizophrenia, research on biomarkers associated with its early course is still ongoing. Single-pulse Transcranial Magnetic Stimulation coupled with electroencephalography (TMS-EEG) has revealed that the main oscillatory frequency (or “natural frequency”) is reduced in several frontal brain areas, including the premotor cortex, of chronic patients with schizophrenia. However, no study has explored the natural frequency at the beginning of illness. Here, we used TMS-EEG to probe the intrinsic oscillatory properties of the left premotor cortex in early-course schizophrenia patients (<2 years from onset) and age/gender-matched healthy comparison subjects (HCs). State-of-the-art real-time monitoring of EEG responses to TMS and noise-masking procedures were employed to ensure data quality. We found that the natural frequency of the premotor cortex was significantly reduced in early-course schizophrenia compared to HCs. No correlation was found between the natural frequency and age, clinical symptom severity, or dose of antipsychotic medications at the time of TMS-EEG. This finding extends to early-course schizophrenia previous evidence in chronic patients and supports the hypothesis of a deficit in frontal cortical synchronization as a core mechanism underlying this disorder. Future work should further explore the putative role of frontal natural frequencies as early pathophysiological biomarkers for schizophrenia.
Longitudinal Coupling between Eating Disorder Psychopathology and Depression in Patients with Anorexia Nervosa and Bulimia Nervosa Treated with Enhanced Cognitive Behavior Therapy: A One-Year Follow-Up Study
Authors: Cassioli Emanuele , Rossi Eleonora , Martelli Michela , Arganini Francesca , Giuranno Gabriele , Siviglia Serena , Tarchi Livio , Faldi Marco , Castellini Giovanni , Ricca Valdo
Published: March 2023

Background: The relationship between eating disorder (ED) specific psychopathology and depressive symptomatology in EDs is often debated. The aim of this study was to provide an explicative model regarding the mechanisms by which enhanced cognitive-behavior therapy (CBT-E) might determine an amelioration of depressive symptoms in patients with anorexia nervosa (AN) or bulimia nervosa (BN). Methods: A total of 157 women with AN or BN and no history of childhood trauma or bipolar disorder were evaluated before treatment and after 12 months of CBT-E. Self-administered questionnaires were used to measure ED psychopathology and depressive symptoms. Results: All psychopathological measures improved after treatment, with no significant additional improvement with the concomitant use of antidepressants. Structural equation modeling using the bivariate latent change score approach showed that higher levels of depressive symptoms at baseline were associated with a worse longitudinal trend of ED psychopathology, and vice versa. Finally, the amelioration of ED psychopathology predicted the improvement in depressive symptoms at follow-up, whereas data did not support the inverse path. Conclusion: This study elucidated the complex longitudinal interplay between ED psychopathology and depression during CBT-E, underlining the importance of addressing ED symptoms as a primary target in the case of comorbidity between AN or BN and depressive symptoms.
Electrophysiological Characterization of Cerebellar Responses during Exploration and Grooming Behaviors in a Rat Model of Parkinsonism
Authors: Vásquez-Celaya Lizbeth , Marín-Márquez Gerardo , Manzo Jorge , Carrillo-Castilla Porfirio , Martínez Armando Jesús , Ortiz Pulido Ricardo , Zempoalteca Ramírez René , Coria-Avila Genaro A. , García Luis I.
Published: March 2023

Parkinson’s disease is currently a global public health challenge due to the rapid growth of aging populations. To understand its pathophysiology is necessary to study the functional correlation between the basal ganglia (BG) and the cerebellum, which are involved in motor control. Herein, we explored multiunit electrical activity (MUA) in the cerebellum of rats with induced Parkinsonism as a result of lesions following bilateral placement of electrodes and passing of current in the ventrolateral striatum (VLS). In one control group, the electrodes descended without electrical current, and another group was left intact in VLS. MUA was recorded in Sim B and Crus II lobes, and in the dentate nucleus (DN) during the execution of exploration behaviors (horizontal and vertical) and grooming. The lesioned and sham groups showed a decrease in MUA amplitude in the Crus II lobe compared to the intact group in all recorded behaviors. However, Sim B and DN did not express differences. Both electrical and physical insults to the VLS induced Parkinsonism, which results in less MUA in Crus II during the execution of motor behaviors. Thus, this type of Parkinsonism is associated with a decrease in the amplitude of Crus II.
Community-Focused Renewable Energy Transition with Virtual Power Plant in an Australian City—A Case Study
Authors: Liu Chengyang , Yang Rebecca , Wang Kaige , Zhang Jiatong
Published: March 2023

The global transition to a renewable-powered economy is gaining momentum as renewable energy becomes more cost-effective and energy-efficient. Renewable-energy-integrated Virtual Power Plants (VPPs) are capable of facilitating renewable transition, reducing distributed generator impacts, and creating value for prosumers and communities by producing renewable energy, engaging in the electricity market, and providing electricity network functions. In this paper, we conducted a case study in the City of Greater Bendigo to evaluate the challenges and opportunities of the community-focused renewable energy transition through establishing VPP with community-based renewable generators and storage systems. A reinforcement learning algorithm was formulated to optimise the energy supply, load shifting, and market trading in the VPP system. The proposed VPP system has great potential to improve the economic value and carbon emission reduction performance of local renewable resources: it can reduce 50–70% of the case study city’s carbon emissions in 10 years and lower the electricity price from the current range of 0.15 AUD/kWh (off-peak) −0.30 AUD/kWh (peak) as provided by Victorian Essential Services Committee to 0.05 AUD/kWh (off-peak) (peak). Overall, this study proposed a comprehensive framework to investigate community-based VPP in a complex urban environment and validated the capability of the VPP in supporting the renewable transition for Australian communities.
Strategies for Sustainable Urban Development—Addressing the Challenges of the 21st Century
Authors: Shen Liyin , Ochoa J. Jorge , Bao Haijun
Published: March 2023

Urbanisation has been one of the most transformative processes of our time, and in recent decades has led to significant changes in the way we live, work, and interact with the world around us [...]
An Integrated Multi-Criteria Decision Model to Select Sustainable Construction Projects under Intuitionistic Fuzzy Conditions
Authors: Salimian Sina , Mousavi Seyed Meysam , Tupenaite Laura , Antucheviciene Jurgita
Published: March 2023

Choosing a proper construction project is a vital subject for entrepreneurs to reduce their costs. In real cases, vagueness and uncertain data drive decisions based on uncertainty. The intuitionistic fuzzy sets (IFSs) theory could assist decision-makers (DMs) in inscribing inadequate knowledge. Nevertheless, this paper provides a new integrated decision analysis model with IFSs. The suggested procedure includes a new decision flow under uncertain situations to define the significance of criteria. In this regard, the weighting of subjective DMs is required for this manner; the only input data needed are an alternative evaluation matrix. Then, a case study on sustainable energy project selection is explained to show the purpose of the suggested model. In this regard, four main criteria, technological, economic, social, and environmental, and seven alternatives from different kinds of energies are introduced to select the appropriate energy project. In this model, the weights of criteria are defined based on a new combined method based on two CRITIC and ideal points approaches. The proposed soft computing model computed the ranking of main alternatives by integrating the ARAS and EDAS approaches; the final outcomes indicate that the second alternative has higher values than other alternatives concerning nuclear energy. Afterward, sensitivity and comparative analyses are generated to determine the efficiency and validity of the proposed model. The sensitivity analysis changes the criteria weights. The comparative analysis compares the IF-TOPSIS method and the proposed model and computes the different degrees to confirm the efficiency of the introduced soft computing model.