bluuebunny/crossref_metadata_2025 huggingface dataset:
Test–Retest Reliability and Minimal Detectable Change in Chester Step Test and 1-Minute Sit-to-Stand Test in Long COVID Patients
Authors: Sevillano-Castaño Ana Isabel , Peroy-Badal Renata , Torres-Castro Rodrigo , Cañuelo-Márquez Ana María , Rozalén-Bustín Manuel , Modrego-Navarro Ángel , De Sousa-De Sousa Luis , Ramos-Álvarez Juan José , Maté-Muñoz José Luis , García-Fernández Pablo
Published: July 2023

The COVID-19 is a multiorgan disease that appeared in December 2019 in the Chinese province of Wuhan. It produces various clinical manifestations, although it mainly affects the respiratory system. Given these potentially detrimental long-term consequences of COVID-19, an appropriate assessment must be carried out to plan early rehabilitation interventions. To assess the persistent symptoms it produces, as well as exercise tolerance for a given exertion, stress testing is a feasible and cost-effective option. Therefore, the objective of this study was to provide test-retest reliability for the Chester Step Test and 1 minute Sit to Stand tests and to establish the minimum detectable change in Long-COVID patients. Method: This observational, descriptive, cross-sectional study was conducted following the STROBE guidelines. A total of 42 patients carried out, twice per partici-pant, the Chester Step and 1-Minute Sit-to-Stand (1min-STST) tests on two different days, with a five-day time lag between the initial measurement and the second measurement. Results: The Test-retest reliability for the Chester Step was excellent within session ICC (95% CI) 0.96 (0.93 to 0.98), being even better for the 1-STST, ICC (95% CI) 0.98 (0.96 to 0.99). Establishing a change of at least 16.96 steps (MDC90) or 20.15 steps (MDC95) and 1.89 stands (MDC90) or 2.71 stands (MDC95), respectively. Conclusions: The Chester Step and 1min-STST tests are reproducible and reliable tools to measure exercise tolerance in long COVID patients. The minimum detectable changes observed in the values recorded by the participants can be very useful for the evaluation of the effectiveness of interventions applied to these patients.
Application of K-PSO Clustering Algorithm and Game Theory in Rock Mass Quality Evaluation of Maji Hydropower Station
Authors: Ruan Yunkai , Chen Jinzi , Fan Zhongmou , Wang Tanhua , Mu Jianguo , Huo Ranran , Huang Wei , Liu Weicheng , Li Yunjian , Sun Yunqiang
Published: July 2023

In this study, the K-means algorithm based on particle swarm optimization (K-PSO) and game theory are introduced to establish the quality evaluation model of a rock mass. Five evaluation factors were considered, i.e., uniaxial saturated compressive strength of rock, discontinuity spacing, acoustic velocity, rock quality designation (RQD), and integrity coefficient. The rock mass of an elevation adit at the abutment of Maji hydropower station was taken as a case study. The subjective weight of the evaluation factor was determined by the weighted least squares method, and the objective weight of the evaluation factor was determined by the entropy method. The combined weights of each influencing factor were determined by game theory to be 0.142, 0.179, 0.035, 0.116, and 0.108. The rock mass quality evaluation in the study area was analyzed by K-PSO algorithm. The results indicate that the K-PSO clustering results are almost the same as the evaluation results of the traditional basic quality (BQ) classification method and the widely used extension evaluation method and are consistent with the preliminary judgment of the expert field. The results are consistent with the field observation law. It is considered that the K-PSO clustering theory can reflect the engineering geological characteristics of the rock mass of the hydropower project in the rock mass quality evaluation.
New Insight on the Formation of 2-Aminoacetophenone in White Wines
Authors: Radovanović Vukajlović Tatjana , Philipp Christian , Eder Phillip , Šala Martin , Šelih Vid Simon , Vanzo Andreja , Šuklje Katja , Lisjak Klemen , Sternad Lemut Melita , Eder Reinhard , Antalick Guillaume
Published: July 2023

This study aimed to improve the understanding of 2-aminoacetophenone (2-AAP) formation in white wines, a compound responsible for atypical ageing (ATA) associated with a rapid loss of white wine fruity aroma and to the development of unpleasant odors. Two surveys performed in 139 white wines from Central Europe investigated the varietal effect on wine tendency to form 2-AAP during ageing. The role of some antioxidants and important transition metal ions present in wine (Fe, Cu and Mn) in the formation of 2-AAP was also investigated. The surveys highlighted that Muscat and Riesling wines showed significantly higher concentrations of 2-AAP than Chardonnay and some other regional varieties found in Central Europe such as Grüner Veltliner, Welschriesling and Zelen. The origin of such varietal effects could not be related to the level of any 2-AAP precursor. On the other hand, some of the important wine matrix effects were highlighted. A certain variability in capacity of different antioxidants to limit 2-AAP formation was observed. Supplementations of commercial tannins in wines tended to be more efficient than glutathione in preserving wines from the formation of 2-AAP. Transition metal ions significantly impacted 2-AAP synthesis through complex interactions. Generally, Fe and Mn tended to promote formation of 2-AAP, while the presence of Cu limited it. The higher concentration of transition metal ions significantly improved the efficiency of antioxidants to reduce 2-AAP formation. Further studies investigating the origin of varietal effects and the complex matrix effects involving metal ions and antioxidants in 2-AAP production are warranted.
Wettability Alteration of Limestone Carbonate Cores Using Methylene Blue and Alumina-Based Nanofluid: Implications for EOR
Authors: Shar Abdul Majeed , Qureshi Muhammad Furqan , Bhutto Darya khan , Memon Faisal Hussain
Published: July 2023

Wettability is a key parameter for optimizing the residual oil recovery from geological rock formations and it provides a path for improved oil recovery and geo-storage of energy. Thus, the key motive behind wettability alteration from hydrophobic to hydrophilic is to enhance the oil productivity. Thus, this work concentrates on Sui main limestone reservoir core samples’ wettability alteration (altering their surface wetting behavior from an oil-wet to water-wet state) for enhanced oil recovery. Hence, we examine the effectiveness of alumina nanofluid as well as a new chemical methyl blue to alter the wettability. Methyl blue is released on a large scale from various industries, i.e., pharma, textile, and food industries, which is a key environmental concern; subsequently, it contaminates the water table. Hence, the study explores the effects of MB and alumina nanofluid on wettability. The effect of nanofluids formulated via dispersing the alumina nanoparticles in aqueous solutions at various concentrations (0. 0.05, 0.3, 0.50, 0.75, and 1.0 wt. %) were tested for wettability modifications under different physio-thermal conditions. Subsequently, the wettability change was examined for these samples treated with different concentrations of MB (10, 15, 30, 50, and 100 mg/L) for 7 days at two different temperatures (25 and 50 °C). The results show that the hydrophobicity of the SML carbonate rock significantly reverses while treating with alumina nanofluids and MB. Thus, the wettability modification/reversal via the treatment of MB and alumina nanofluids can be an effective mechanism for hydrogen injections and EOR processes.
Compressive Behavior of a Novel Hexagonal Nodes-Based 3D Chiral Auxetic Structure
Authors: Gao Dianwei , Zhang Chunwei , Zhang Jianhua
Published: July 2023

The energy absorption capacity of materials with negative Poisson’s ratio (NPR) is attracting interest from both industry and academia due to the excellent impact resistance of the local shrinkage of materials. However, understanding the compressive behavior of 3D auxetic structures at different strain rates and developing design methods are challenging tasks due to the limited literature and insufficient data. This paper presents a study on the behavior of Poisson’s ratio of an advanced 3D chiral structure, which is formed of two orthogonally positioned 2D hexagonal nodes-based chiral structures. Firstly, both theoretical analysis and numerical simulations are conducted to identify the Poisson’s ratio of 2D chiral structures. The same theoretical value of −1 is obtained for 2D chiral structures with a bending-dominated ligaments assumption. Thereafter, the Poisson’s ratio of 3D chiral structures is determined numerically using a low-speed loaded model composed of 5 × 5 × 8 3D unit cells for eliminating the boundary effects. The results show that impact velocity can strongly affect the energy absorption and deformation behavior of the proposed 3D chiral structure. Increasing the beam radius results in reduced energy absorption capability. However, the energy absorption capability of the 3D chiral structure is not sensitive to the yield strength of nodes. Impact direction affects the energy absorption performance of the 3D chiral structure, depending on the crushing strain. The research results could be used to optimize the design of the proposed novel 3D chiral honeycombs for various applications, such as impact energy absorbers and vibration-resistant dampers.
Solving Panel Block Assembly Line Scheduling Problem via a Novel Deep Reinforcement Learning Approach
Authors: Zhou Tao , Luo Liang , He Yuanxin , Fan Zhiwei , Ji Shengchen
Published: July 2023

The panel block is a quite important “intermediate product” in the shipbuilding process. However, the assembly efficiency of the panel block assembly line is not high. Therefore, rational scheduling optimization is of great significance for improving shipbuilding efficiency. Currently, the processing sequence of the panel blocks in the panel block assembly line is mainly determined using heuristic and metaheuristic algorithms. However, these algorithms have limitations, such as small problem-solving capacity and low computational efficiency. To address these issues, this study proposes an end-to-end approach based on deep reinforcement learning to solve the scheduling problem of the ship’s panel block assembly line. First, a Markov decision model is established, and a disjunctive graph is creatively used to represent the current scheduling status of the panel block assembly line. Then, a policy function based on a graph isomorphism network is designed to extract information from the disjunctive graph’s state and train it using Proximal Policy Optimization algorithms. To validate the effectiveness of our method, tests on both real shipbuilding data and publicly available benchmark datasets are conducted. We compared our proposed end-to-end deep reinforcement learning algorithm with heuristic algorithms, metaheuristic algorithms, and the unimproved reinforcement learning algorithm. The experimental results demonstrate that our algorithm outperforms other baseline methods in terms of model performance and computation time. Moreover, our model exhibits strong generalization capabilities for larger instances.
FPGA-Based Methodology for Detecting Positional Accuracy Degradation in Industrial Robots
Authors: Galan-Uribe Ervin , Morales-Velazquez Luis , Osornio-Rios Roque Alfredo
Published: July 2023

Industrial processes involving manipulator robots require accurate positioning and orienting for high-quality results. Any decrease in positional accuracy can result in resource wastage. Machine learning methodologies have been proposed to analyze failures and wear in electronic and mechanical components, affecting positional accuracy. These methods are typically implemented in software for offline analysis. In this regard, this work proposes a methodology for detecting a positional deviation in the robot’s joints and its implementation in a digital system of proprietary design based on a field-programmable gate array (FPGA) equipped with several developed intellectual property cores (IPcores). The method implemented in FPGA consists of the analysis of current signals from a UR5 robot using discrete wavelet transform (DWT), statistical indicators, and a neural network classifier. IPcores are developed and tested with synthetic current signals, and their effectiveness is validated using a real robot dataset. The results show that the system can classify the synthetic robot signals for joints two and three with 97% accuracy and the real robot signals for joints five and six with 100% accuracy. This system aims to be a high-speed reconfigurable tool to help detect robot precision degradation and implement timely maintenance strategies.
A Transferable Prediction Approach for the Remaining Useful Life of Lithium-Ion Batteries Based on Small Samples
Authors: Qin Haochen , Fan Xuexin , Fan Yaxiang , Wang Ruitian , Shang Qianyi , Zhang Dong
Published: July 2023

Predicting the remaining useful life (RUL) of batteries can help users optimize battery management strategies for better usage planning. However, the RUL prediction accuracy of lithium-ion batteries will face challenges due to fewer data samples available for the new type of battery. This paper proposed a transferable prediction approach for the RUL of lithium-ion batteries based on small samples to reduce time in preparing battery aging data and improve prediction accuracy. This approach, based on improvements from the adaptive boosting algorithm, is called regression tree transfer adaptive boosting (RT-TrAdaBoost). It combines the advantages of ensemble learning and transfer learning and achieves high computational efficiency. The RT-TrAdaBoost approach takes the charging voltage and temperature curve as input and utilizes the classification and regression tree (CART) as the base learner, which has better feature capture ability. In the experiment, the working condition migration experiment and battery type migration experiment are conducted on non-overlapping datasets. The verified results revealed that the RT-TrAdaBoost approach could transfer not only the battery aging knowledge between various working conditions but also realize the RUL migration prediction from lithium iron phosphate battery to lithium cobalt oxide battery. The analysis of error and computation time demonstrates the proposed method’s high efficiency and speed.
A Comparative Study of the Presence of Minerals, Flavonoids and Total Phenolic Compounds in the Leaves of Common Traditional Vegetables
Authors: Thovhogi Fhatuwani , Ntushelo Nombasa , Gwata Eastonce T.
Published: July 2023

Indigenous leafy vegetables are used mainly for human consumption since they provide health promoting phytonutrients and bioactive compounds such as antioxidants, flavonoids, minerals and vitamins. However, the phytonutrients and bioactive compounds in the leaves of these vegetables vary widely both quantitatively and qualitatively due to genetic and environmental factors. This study determined the diversity, molecular size variation and the relationships between the minerals and nutrients. Four common leafy vegetables and one standard were used in the study. The mean iron and manganese leaf content was 279.44 mg/kg DW and 247.86 mg/kg DW, respectively. The total phenolic content ranged between 0.37 and 0.50 mg GAE/g. Nineteen different bioactive compounds, varying widely in molecular size, were detected in the four common leafy vegetables. Jute mallow leaves contained only two bioactive molecules which included quercetin-3′-glucoside. None of the eight quercetin-related derivatives that were present among the leafy vegetables were detected in Swiss chard. In cowpea, 2,2 diphenyl-1-picrylhydrazyl free radical scavenging activity was four-fold higher than in pumpkin and Swiss chard leaves. These results demonstrated that the common leafy vegetables varied widely in mineral composition and bioactive compounds, suggesting that a combination of these vegetables in the human diet can provide a wider range of nutrients.
Weak Fault Diagnosis Method of Rolling Bearings Based on Variational Mode Decomposition and a Double-Coupled Duffing Oscillator
Authors: Shan Shijie , Zheng Jianming , Wang Kai , Chen Ting , Shi Yuhua
Published: July 2023

Aiming at the problems of the low detection accuracy and difficult identification of the early weak fault signals of rolling bearings, this paper proposes a method for detecting the early weak fault signals of rolling bearings based on a double-coupled Duffing system and VMD. The influence rule of system initial value on the response characteristics of a double-coupled Duffing system is studied, and the basis for its determination is given. The frequency of the built-in power of the system is normalized, and a variance evaluation standard for the output value of the double-coupled Duffing system for weak fault signals detection is established. In order to solve the interference problem of fault monitoring signals, VMD is proposed to pre-process the fault monitoring signals. The weak fault signal detection method proposed in this paper is tested and verified by simulation signals and rolling bearing fault signals. The results show that the method proposed in this paper can detect the weak fault signal with the lowest signal-to-noise ratio reduced by 2.96 dB compared with the traditional Duffing detection system, and it can accurately detect the early weak fault signal of rolling bearings.
P System with Fractional Reduction
Authors: Nan Hai , Kong Yumeng , Zhan Jie , Zhou Mingqiang , Bai Ling
Published: July 2023

Membrane computing is a branch of natural computing, which is a new computational model abstracted from the study of the function and structure of living biological cells. The study of numerical computation based on membrane computation has received increasing attention in recent years, where maximum parallelism in the execution of evolutionary rules plays an important role in improving the efficiency of numerical computation. Numbers in numerical computation are usually represented as decimals or fractions, and this paper investigates the fundamental problem in fraction representation and operations—fraction simplification. By improving the parallelization of two traditional fractional reduction algorithms, we design the corresponding fractional reduction class cells P System Π1 and P System Π2. Combining these two P Systems, this paper designs P System Π3. The feasibility and effectiveness of the P System designed in this paper are verified experimentally with the simulation software UPSimulator, and the characteristics and application scenarios of the three P Systems are analyzed.
Code Similarity and Location-Awareness Automatic Program Repair
Authors: Cao Heling , Han Dong , Liu Fangzheng , Liao Tianli , Zhao Chenyang , Shi Jianshu
Published: July 2023

Automatic program repair has drawn more and more attention since software quality is facing increasing challenges. In existing approaches, the unlimited search space is considered to be the main limitation in finding the correct patch. So how to reduce the search space to improve the efficiency of automatic program repair remains a problem to be solved. In this work, we represent a similarity-based and location-awareness-based automatic program repair (SLARepair). SLARepair takes the similarity between codes as important search information. The search space is further subdivided by the location-awareness strategy to improve search efficiency. In addition, to better guide the search process, a new fitness function is designed for genetic programming, which brings notable improvements. Moreover, the patch verification time is further reduced by utilizing the test case prioritization approach combined with test case filtering. Extensive experiments demonstrate that our SLARepair outperforms the state-of-the-art approaches on the Defects4J benchmark and achieves competitive performances.
Greenhouse Gas Emissions Forecasts in Countries of the European Union by Means of a Multifactor Algorithm
Authors: Marotta Antonio , Porras-Amores César , Rodríguez Sánchez Antonio Rodríguez , Villoria Sáez Paola Villoria , Masera Gabriele
Published: July 2023

A novel multifactor algorithm is developed with the aim of estimating GHG emissions in the EU countries and forecasting different future scenarios. This is created starting from (1) GDP, (2) population and (3) renewable energy share (RES). The determination coefficient (R2) of the multiple regression adopted reaches a value of 0.96; thus, only 4% of the GHG variation cannot be explained by the combination of the three variables. Germany is removed from the model after analysing the statistical outliers, as it presents an unusual behaviour within the European context. Also, France, Italy and Ireland are removed in the forecast analysis since they are characterised by corrected weighting values above the threshold value of the algorithm (0.156). The results show that GHG emissions decrease 14% in a low-growth-rate scenario, increase 24% in an average-growth scenario and increase 104% in a high-growth-rate scenario. Countries that improve the most are the ones that are currently underdeveloped in RES and are expected to decrease their population in the future (Croatia, Latvia, Cyprus and Greece). Other countries currently well positioned but with expected population growth (Sweden, Luxemburg and Denmark) or with expected intense GDP growth (Estonia and Malta) may lack decarbonisation levers. Therefore, policy makers should introduce additional subsidy schemes and tax exemptions in both developed and less developed countries to meet EU decarbonisation targets.
Deep Learning-Based Classification of High-Resolution Satellite Images for Mangrove Mapping
Authors: Wei Yidi , Cheng Yongcun , Yin Xiaobin , Xu Qing , Ke Jiangchen , Li Xueding
Published: July 2023

Detailed information about mangroves is crucial for ecological and environmental protection and sustainable development. It is difficult to capture small patches of mangroves from satellite images with relatively low to medium resolution. In this study, high-resolution (0.8–2 m) images from Chinese GaoFen (GF) and ZiYuan (ZY) series satellites were used to map the distribution of mangroves in coastal areas of Guangdong Province, China. A deep-learning network, U2-Net, with attention gates was applied to extract multi-scale information of mangroves from satellite images. The results showed that the attention U2-Net model performed well on mangrove classification. The overall accuracy, precision, and F1-score values were 96.5%, 92.0%, and 91.5%, respectively, which were higher than those obtained from other machine-learning methods such as Random Forest or U-Net. Based on the high-resolution mangrove maps generated from long satellite image time series, we also investigated the spatiotemporal evolution of the mangrove forest in Shuidong Bay. The results can provide crucial information for government administrators, scientists, and other stakeholders to monitor the dynamic changes in mangroves.
The Wolf King’s Leisure Estate: An Andalusi Agricultural and Palatine Project (Murcia, 12th Century)
Authors: Navarro-Palazón Julio , Jiménez-Castillo Pedro
Published: July 2023

The Castillejo de Monteagudo, which has been well known since excavations began in 1924, is a palatial residence built on a promontory. However, the fact that it was part of an extensive agricultural estate, known as Ḥiṣn al-Faraj, which included dry-farming, orchards, gardens, woodland, hunting areas, and marshes, as well as important hydraulic infrastructures, has not been sufficiently emphasised to date. Archaeological research on the irrigated plain during 2018 and 2019 has brought to light part of the palatine area, which was organised around a large garden presided by a residential complex with a porticoed pavilion and a pool at the centre. All known buildings date to the reign of Emir Ibn Mardanīš (1147–1171), although the possibility that the estate was created earlier cannot be ruled out. It was destroyed twice by the Almohads (1165 and 1171) and reused by the Castilian King Alfonso X, perhaps after being restored by Ibn Hūd al-Mutawakkil (1228–1238).
Impact of Temperature Extremes on Carbon Emissions from Crop Production in Hebei Province, China
Authors: Shao Shuai , Qiao Hongwu
Published: July 2023

The study investigated the impact of temperature extremes on carbon emissions (CE) from crop production. (1) Background: Many scholars have studied climate extremes. However, the research on the relationship between temperature extremes and CE is not extensive, which deserves attention. (2) Methods: The study adopted a fixed-effect model to analyze the impact of temperature extremes on CE from crop production, and the moderating effect was tested using total factor productivity (TFP) in agriculture. (3) Results: Temperature extremes in Hebei Province were mainly reflected in a decline in the cold day index (TX10p) and a rise in the warm spell duration index (WSDI) and the number of summer days (SU25). Additionally, TX10p was positively correlated with CE. For every 1% reduction in TX10p, CE dropped by 0.237%. There was no significant correlation between WSDI and CE. Finally, the agricultural TFP had a significant moderating effect on CE, with each 1% increase resulting in a corresponding 0.081% decrease in CE. (4) Conclusions: The results indicated a warming trend in Hebei Province, which resulted in a decrease in the number of winter days, and reduced CE from crop production. The improvement of input efficiency in agricultural production factors helped moderate the CE.
Recognition of Arboviruses by the Mosquito Immune System
Authors: Prince Brian C. , Walsh Elizabeth , Torres Tran Zen B. , Rückert Claudia
Published: July 2023

Arthropod-borne viruses (arboviruses) pose a significant threat to both human and animal health worldwide. These viruses are transmitted through the bites of mosquitoes, ticks, sandflies, or biting midges to humans or animals. In humans, arbovirus infection often results in mild flu-like symptoms, but severe disease and death also occur. There are few vaccines available, so control efforts focus on the mosquito population and virus transmission control. One area of research that may enable the development of new strategies to control arbovirus transmission is the field of vector immunology. Arthropod vectors, such as mosquitoes, have coevolved with arboviruses, resulting in a balance of virus replication and vector immune responses. If this balance were disrupted, virus transmission would likely be reduced, either through reduced replication, or even through enhanced replication, resulting in mosquito mortality. The first step in mounting any immune response is to recognize the presence of an invading pathogen. Recent research advances have been made to tease apart the mechanisms of arbovirus detection by mosquitoes. Here, we summarize what is known about arbovirus recognition by the mosquito immune system, try to generate a comprehensive picture, and highlight where there are still gaps in our current understanding.
Decreased Platelet Aggregation in Patients with Decompensated Liver Cirrhosis and TIPS Implantation
Authors: Nassar Asala , Huber Jan Patrick , Stallmann Daniela , Sharipova Diana , Hamad Muataz Ali , Schultheiss Michael , Thimme Robert , Duerschmied Daniel , Scharf Rüdiger Eberhard , Bettinger Dominik , Krauel Krystin
Published: July 2023

Transjugular intrahepatic portosystemic shunt (TIPS) implantation is an effective treatment of portal hypertension in patients with decompensated liver cirrhosis. However, some patients develop TIPS thrombosis with recurrence of portal hypertension. The role of platelets in TIPS thrombosis and the necessity of antiplatelet therapy is unclear. Therefore, we aimed to study platelet function in patients with liver cirrhosis prior to and after TIPS implantation. Platelet aggregation was tested in peripheral and portal-vein blood patient samples on the day (D) of TIPS implantation (D0), D4 and D30 following the procedure (platelet count above 100 × 103/µL, aspirin starting on D5) using whole-blood impedance aggregometry (WBIA) and light transmission aggregometry (LTA). In addition, surface platelet activation markers (P-selectin, activated GPIIb/IIIa) and platelet–neutrophil complexes (PNCs) were assessed by flow cytometry. Thrombin receptor activating peptide 6 (TRAP-6), adenosine diphosphate (ADP) and arachidonic acid (AA) were used as agonists. Healthy subjects were included as controls. Agonist-induced platelet aggregation was reduced (WBIA: TRAP-6 p < 0.01, ADP p < 0.01, AA p < 0.001; LTA: TRAP-6 p = 0.13, ADP p = 0.05, AA p < 0.01) in patients (D0, n = 13) compared with healthy subjects (n = 9). While surface activation markers at baseline were negligibly low, the percentage of PNCs was higher in patients than in controls (p < 0.05). ADP-induced P-selectin expression was increased (p < 0.001), whereas TRAP-6-induced GPIIb/IIIa activation was impaired (p < 0.001) in patients versus controls. PNC formation in response to agonists was not different between groups. Results did not differ between peripheral and portal-vein blood of patients (D0, n = 11) and did not change over time (D0, D4, D30) following TIPS implantation (n = 9). In summary, patients with decompensated liver cirrhosis display in vitro platelet aggregation defects in response to various agonists. Defective aggregation persists upon TIPS implantation. Therefore, we conclude that antiplatelet treatment to prevent TIPS thrombosis is questionable.
Interleukin-19 Gene-Deficient Mice Promote Liver Fibrosis via Enhanced TGF-β Signaling, and the Interleukin-19-CCL2 Axis Is Important in the Direction of Liver Fibrosis
Authors: Ono Naoshige , Fujita Takashi , Miki Mariko , Nishiyama Kazuhiro , Izawa Takeshi , Aoyama Tomoko , Kuwamura Mitsuru , Fujii Hideki , Azuma Yasu-Taka
Published: July 2023

IL-19 is a cytokine discovered by homologous searching with IL-10 and is produced by non-immune cells, such as keratinocytes, in addition to immune cells, such as macrophages. Liver fibrosis results from the inflammation and activation of hepatic stellate cells via chronic liver injury. However, the participation of IL-19 in liver fibrosis remains to be sufficiently elucidated. Our group studied the immunological function of IL-19 in a mouse model of carbon tetrachloride (CCl4)-induced liver fibrosis. IL-19 gene-deficient (KO) mice and body weight-matched wild-type (WT) mice were used. A liver fibrosis mouse model was created via CCl4 administration (two times per week) for 8 weeks. In CCl4-induced liver fibrosis, serum analysis revealed that IL-19 KO mice had higher ALT levels compared to WT mice. IL-19 KO mice had worse fibrosis, as assessed by morphological evaluation of total area stained positive with Azan and Masson trichrome. In addition, the expression of α-SMA was increased in liver tissues of IL-19 KO mice compared to WT mice. Furthermore, mRNA expression levels of TGF-β and α-SMA were enhanced in IL-19 KO mice compared to WT mice. In vitro assays revealed that IL-19-high expressing RAW264.7 cells inhibited the migration of NIH3T3 cells via the inhibited expression of CCL2 in the presence of CCl4 and IL-4. These findings indicate that IL-19 plays a critical role in liver fibrosis by affecting TGF-β signaling and the migration of hepatic stellate cells during liver injury. Enhancement of the IL-19 signaling pathway is a potential treatment for liver fibrosis.
The Unfolded Protein Response and Its Implications for Novel Therapeutic Strategies in Inflammatory Bowel Disease
Authors: Verjan Garcia Noel , Hong Kyung U. , Matoba Nobuyuki
Published: July 2023

The endoplasmic reticulum (ER) is a multifunctional organelle playing a vital role in maintaining cell homeostasis, and disruptions to its functions can have detrimental effects on cells. Dysregulated ER stress and the unfolded protein response (UPR) have been linked to various human diseases. For example, ER stress and the activation of the UPR signaling pathways in intestinal epithelial cells can either exacerbate or alleviate the severity of inflammatory bowel disease (IBD), contingent on the degree and conditions of activation. Our recent studies have shown that EPICERTIN, a recombinant variant of the cholera toxin B subunit containing an ER retention motif, can induce a protective UPR in colon epithelial cells, subsequently promoting epithelial restitution and mucosal healing in IBD models. These findings support the idea that compounds modulating UPR may be promising pharmaceutical candidates for the treatment of the disease. In this review, we summarize our current understanding of the ER stress and UPR in IBD, focusing on their roles in maintaining cell homeostasis, dysregulation, and disease pathogenesis. Additionally, we discuss therapeutic strategies that promote the cytoprotection of colon epithelial cells and reduce inflammation via pharmacological manipulation of the UPR.
Impact of HPV-16 Lineages Infection in Response to Radio-Chemotherapy in Cervical Cancer
Authors: de Figueiredo Fábio Vidal , Santos Gerusinete Rodrigues Bastos dos , Vidal Flávia Castello Branco , da Silva Marcos Antonio Custódio Neto , da Silva Rodrigo Lopes , da Silva Batista Zulmira , de Andrade Marcelo Souza , Barbosa Maria do Carmo Lacerda , Maniçoba Anna Cyntia Brandão Nascimento , da Silva Mayara Cristina Pinto , Nascimento Maria do Desterro Soares Brandão
Published: July 2023

Background: HPV is strongly related to cervical cancer. HPV lineages can contribute to a response to cervical cancer therapy. The aim of this research was to estimate the frequency of human papillomavirus (HPV)-16 lineages in specimens of cervical cancer, relate the pathological factors in these variants, and assess their response to treatment with radical chemoradiotherapy. Methods: Samples of cervical cancer were collected from women who were referred to a reference cancer hospital to test the presence of human papillomavirus-type DNA. The standard protocol of this service consisted of cisplatin-based chemotherapy of 40 mg/m2, plus conventional pelvic irradiation in doses of 45–50.4 Gy and high dose-rate brachytherapy of 28–30 Gy to Point A. The response to chemotherapy was evaluated after three months in patients with the HPV-16 lineage. Results: HPV DNA was detected in 104 (88.1%) of the 118 patients. HPV-16 was present in 63 patients (53%). Lineages of HPV-16 were identified in 57 patients and comprised 33 instances of (57.8%) lineage A, 2 instances of lineage B (3.5%), 2 instances of lineage C (3.5%), and 20 instances of (35.0%) lineage D. The median age of the patients was 48.4 years (range 25–85 years). Squamous cell carcinoma was detected 48 times (84.2%). Adenocarcinoma was more likely to occur in lineage D, as three of the four cases occurred in this lineage. A total of 11 patients with the HPV-16 variant were treated with chemoradiotherapy. After three months, it was observed that nine of the eleven patients (81.8%) achieved a complete response, five with the lineage A type, two with the lineage C type, and two with the lineage D type. The two cases of partial response and disease progression, one of each, occurred in lineage A. Conclusions: In addition to the small number of patients and HPV variants, we noticed a better response in patients with the HPV-16 lineage A. Increasing the sample size could be helpful to better assess the impact of HPV variants on cervical cancer treatment.
The Potential Influence of Uremic Toxins on the Homeostasis of Bones and Muscles in Chronic Kidney Disease
Authors: Hung Kuo-Chin , Yao Wei-Cheng , Liu Yi-Lien , Yang Hung-Jen , Liao Min-Tser , Chong Keong , Peng Ching-Hsiu , Lu Kuo-Cheng
Published: July 2023

Patients with chronic kidney disease (CKD) often experience a high accumulation of protein-bound uremic toxins (PBUTs), specifically indoxyl sulfate (IS) and p-cresyl sulfate (pCS). In the early stages of CKD, the buildup of PBUTs inhibits bone and muscle function. As CKD progresses, elevated PBUT levels further hinder bone turnover and exacerbate muscle wasting. In the late stage of CKD, hyperparathyroidism worsens PBUT-induced muscle damage but can improve low bone turnover. PBUTs play a significant role in reducing both the quantity and quality of bone by affecting osteoblast and osteoclast lineage. IS, in particular, interferes with osteoblastogenesis by activating aryl hydrocarbon receptor (AhR) signaling, which reduces the expression of Runx2 and impedes osteoblast differentiation. High PBUT levels can also reduce calcitriol production, increase the expression of Wnt antagonists (SOST, DKK1), and decrease klotho expression, all of which contribute to low bone turnover disorders. Furthermore, PBUT accumulation leads to continuous muscle protein breakdown through the excessive production of reactive oxygen species (ROS) and inflammatory cytokines. Interactions between muscles and bones, mediated by various factors released from individual tissues, play a crucial role in the mutual modulation of bone and muscle in CKD. Exercise and nutritional therapy have the potential to yield favorable outcomes. Understanding the underlying mechanisms of bone and muscle loss in CKD can aid in developing new therapies for musculoskeletal diseases, particularly those related to bone loss and muscle wasting.
A Review of Myoelectric Control for Prosthetic Hand Manipulation
Authors: Chen Ziming , Min Huasong , Wang Dong , Xia Ziwei , Sun Fuchun , Fang Bin
Published: July 2023

Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation. Intuitive and intelligent myoelectric control can help amputees to regain upper limb function. However, current research efforts are primarily focused on developing rich myoelectric classifiers and biomimetic control methods, limiting prosthetic hand manipulation to simple grasping and releasing tasks, while rarely exploring complex daily tasks. In this article, we conduct a systematic review of recent achievements in two areas, namely, intention recognition research and control strategy research. Specifically, we focus on advanced methods for motion intention types, discrete motion classification, continuous motion estimation, unidirectional control, feedback control, and shared control. In addition, based on the above review, we analyze the challenges and opportunities for research directions of functionality-augmented prosthetic hands and user burden reduction, which can help overcome the limitations of current myoelectric control research and provide development prospects for future research.
Exploring the Dynamics of Holo-Shikimate Kinase through Molecular Mechanics
Authors: Ojeda-May Pedro
Published: July 2023

Understanding the connection between local and global dynamics can provide valuable insights into enzymatic function and may contribute to the development of novel strategies for enzyme modulation. In this work, we investigated the dynamics at both the global and local (active site) levels of Shikimate Kinase (SK) through microsecond time-scale molecular dynamics (MD) simulations of the holoenzyme in the product state. Our focus was on the wild-type (WT) enzyme and two mutants (R116A and R116K) which are known for their reduced catalytic activity. Through exploring the dynamics of these variants, we gained insights into the role of residue R116 and its contribution to overall SK dynamics. We argue that the connection between local and global dynamics can be attributed to local frustration near the mutated residue which perturbs the global protein dynamics.
What Dietary Vitamins and Minerals Might Be Protective against Parkinson’s Disease?
Authors: Alizadeh Mohammad , Kheirouri Sorayya , Keramati Majid
Published: July 2023

Background and Objective: Dietary constituents may affect the progression of Parkinson’s disease (PD). This study aimed to assess the contribution of dietary intake of vitamins and minerals to the severity, motor and non-motor symptoms, and risk of PD. Methods: In this case-control study, 120 patients with PD and 50 healthy participants participated. Dietary intake of vitamins and minerals was determined using a 147-item food frequency questionnaire. The severity of PD was determined by the Unified Parkinson’s Disease Rating Scale (UPDRS). Results: Patients with PD had lower intake of several vitamins and minerals including lycopene, thiamine, vitamin B6, vitamin B12, pantothenic acid, magnesium, zinc, manganese, selenium, chromium, and phosphorus, but had higher intake of α-tocopherol. High dietary intake of vitamin A, α-carotene, β-cryptoxanthin, vitamin C, and α-tocopherol were correlated with increased odds of PD. High intake of lycopene, thiamin, vitamin B6, pantothenic acid, magnesium, zinc, manganese, chromium, and phosphorous correlated with reduced odds of PD. The predictive power of α-tocopherol concerning the risk of PD was stronger relative to other vitamins. Dietary intake of pantothenic acid was negatively correlated with PD severity and symptoms of motor examination and complication. The severity and motor symptoms of PD were also negatively correlated with β-carotene, vitamin C, riboflavin, vitamin B6, and biotin intake. The UPDRS total score and motor symptoms in PD patients were negatively correlated with phosphorus, magnesium, zinc, manganese, and chromium, and strongly with potassium intake. Conclusion: The findings indicate that adequate dietary intake of vitamins and minerals may have a preventive effect on developing PD and progression of motor decline.
Estimating the Concrete Ultimate Strength Using a Hybridized Neural Machine Learning
Authors: Zhang Ziwei
Published: July 2023

Concrete is a highly regarded construction material due to many advantages such as versatility, durability, fire resistance, and strength. Hence, having a prediction of the compressive strength of concrete (CSC) can be highly beneficial. The new generation of machine learning models has provided capable solutions to concrete-related simulations. This paper deals with predicting the CSC using a novel metaheuristic search scheme, namely the slime mold algorithm (SMA). The SMA retrofits an artificial neural network (ANN) to predict the CSC by incorporating the effect of mixture ingredients and curing age. The optimal configuration of the algorithm trained the ANN by taking the information of 824 specimens. The measured root mean square error (RMSE = 7.3831) and the Pearson correlation coefficient (R = 0.8937) indicated the excellent capability of the SMA in the assigned task. The same accuracy indicators (i.e., the RMSE of 8.1321 and R = 0.8902) revealed the competency of the developed SMA-ANN in predicting the CSC for 206 stranger specimens. In addition, the used method outperformed two benchmark algorithms of Henry gas solubility optimization (HGSO) and Harris hawks optimization (HHO) in both training and testing phases. The findings of this research pointed out the applicability of the SMA-ANN as a new substitute to burdensome laboratory tests for CSC estimation. Moreover, the provided solution is compared to some previous studies, and it is shown that the SMA-ANN enjoys higher accuracy. Therefore, an explicit mathematical formula is developed from this model to provide a convenient CSC predictive formula.
Autophagy Inhibition with Chloroquine Increased Pro-Apoptotic Potential of New Aziridine-Hydrazide Hydrazone Derivatives against Glioblastoma Cells
Authors: Witusik-Perkowska Monika , Głowacka Pola , Pieczonka Adam M. , Świderska Ewa , Pudlarz Agnieszka , Rachwalski Michał , Szymańska Julia , Zakrzewska Magdalena , Jaskólski Dariusz J. , Szemraj Janusz
Published: July 2023

Tumor therapy escape due to undesired side effects induced by treatment, such as prosurvival autophagy or cellular senescence, is one of the key mechanisms of resistance that eventually leads to tumor dormancy and recurrence. Glioblastoma is the most frequent and practically incurable neoplasm of the central nervous system; thus, new treatment modalities have been investigated to find a solution more effective than the currently applied standards based on temozolomide. The present study examined the newly synthesized compounds of aziridine–hydrazide hydrazone derivatives to determine their antineoplastic potential against glioblastoma cells in vitro. Although the output of our investigation clearly demonstrates their proapoptotic activity, the cytotoxic effect appeared to be blocked by treatment-induced autophagy, the phenomenon also detected in the case of temozolomide action. The addition of an autophagy inhibitor, chloroquine, resulted in a significant increase in apoptosis triggered by the tested compounds, as well as temozolomide. The new aziridine–hydrazide hydrazone derivatives, which present cytotoxic potential against glioblastoma cells comparable to or even higher than that of temozolomide, show promising results and, thus, should be further investigated as antineoplastic agents. Moreover, our findings suggest that the combination of an apoptosis inducer with an autophagy inhibitor could optimize chemotherapeutic efficiency, and the addition of an autophagy inhibitor should be considered as an optional adjunctive therapy minimizing the risk of tumor escape from treatment.
Preparation and Hydrogen-Sensitive Property of WO3/Graphene/Pd Ternary Composite
Authors: Wang Lin , An Fei , Liu Xinmei , Zhang Dongzhi , Yang Zhe
Published: July 2023

Hydrogen (H2) is a renewable energy source that has the potential to reduce greenhouse gas emissions. However, H2 is also highly flammable and explosive, requiring sensitive and safe sensors for its detection. This work presents the synthesis and characterization of WO3/graphene binary and WO3/graphene/Pd (WG-Pd) ternary nanocomposites with varying graphene and Pd contents using the microwave-assisted hydrothermal method. The excellent catalytic efficacy of Pd nanoparticles facilitated the disintegration of hydrogen molecules into hydrogen atoms with heightened activity, consequently improving the gas-sensing properties of the material. Furthermore, the incorporation of graphene, possessing high conductivity, serves to augment the mobility of charge carriers within the ternary materials, thereby expediting the response/recovery rates of gas sensors. Both graphene and Pd nanoparticles, with work functions distinct from WO3, engender the formation of a heterojunction at the interface of these diverse materials. This enhances the efficacy of electron–hole pair separation and further amplifies the gas-sensing performance of the ternary materials. Consequently, the WG-Pd based sensors exhibited the best gas-sensing performance when compared to anther materials, such as a wide range of hydrogen concentrations (0.05–4 vol.%), a short response time and a good selectivity below 100 °C, even at room temperature. This result indicates that WG-Pd ternary materials are a promising room-temperature hydrogen-sensing materials for H2 detection.