bluuebunny/crossref_metadata_2025 huggingface dataset:
Alternative Biological Process for Livestock Manure Utilization and Energy Production Using Microbial Fuel Cells
Authors: Koleva Ralitza , Stankulov Toma , Boukoureshtlieva Reneta , Yemendzhiev Huseyin , Momchilov Anton , Nenov Valentin
Published: February 2022

Carbon-based porous materials are most widely used for Microbial Fuel Cells (MFC) based on their unique properties facilitating and allowing the development of high surface area electrode. The electrochemically active layer of the electrode was prepared using two types of catalysts: activated carbon (Norit NK) and activated carbon promoted with CoTMPP (AC/CoTMPP). Mobilization of phosphate ions in the liquid phase was observed during the process of livestock manure treatment. From 20 mg l−1 initially, the concentration of dissolved phosphates reached 100 mg l−1 after 96 h. Increased concentration of ammonium ions in the medium was also observed, indicating ongoing anaerobic mineralization of the organic matter. The processes taking place in the bio electrochemical reactor used result in recovery of nutrients and production of energy. A maximum current density of 140 μА cm−2 was reached during the MFC operation. The chemical oxygen demand (COD) removal rates were relatively high (above 2 g O2/L/h) for both differently catalyzed cathode configurations. As widely reported elsewhere, the electrochemical results confirm that a gas-diffusion electrode using activated carbon catalyst is very well suited as a positive electrode for use in bio electrochemical systems.
Modeling Isotope Separation in Electrochemical Lithium Deposition
Authors: Wild Joseph , Wang Peiyu , Jin Tianwei , Yang Yuan
Published: February 2022

Naturally occurring Li consists of two stable isotopes, 6Li with an abundance of about 7.5%, and 7Li making up the remainder with 92.5%. The development of a 6Li enrichment technique, in terms of technical reliability and environmental safety to reach 6Li future requirements, represents a key step in the roadmap for nuclear fusion energy supply worldwide. This paper uses finite element analysis-based models to simulate electrochemical Li isotope separation, which is an attractive method in terms of simplicity, safety, and scalability. In the model, we quantitatively analyze how different electrochemical factors including thermodynamics, charge-transfer kinetics, and diffusivities affect the separation process (separation factor), together with cell parameters, such as cell length and current density. The maximum separation factor of 1.128 could be obtained with the cell under the optimal thermodynamic, kinetic, and diffusive conditions, which is among the highest separation factors ever reported. These results will assist in designing the actual isotope separation setup with large separation factor and appropriate timing for sample collection.
Effect of lung pericyte-like cell ablation on the bleomycin model of injury and repair
Authors: Hung Chi F. , Wilson Carole L. , Chow Yu-Hua , Liles Wayne C. , Gharib Sina A. , Altemeier William A. , Schnapp Lynn M.
Published: February 2022

We previously showed that pericyte-like cells derived from the FoxD1-lineage contribute to myofibroblasts following bleomycin-induced lung injury. However, their functional significance in lung fibrosis remains unknown. In this study, we used a model of lung pericyte-like cell ablation to test the hypothesis that pericyte-like cell ablation attenuates lung fibrosis in bleomycin-induced lung injury. Lung fibrosis was induced by intratracheal instillation of bleomycin. To ablate pericyte-like cells in the lung, diphtheria toxin (DT) was administered to Foxd1-Cre;Rosa26-iDTR mice at two different phases of bleomycin-induced lung injury. For early ablation, we coadministered bleomycin with DT and harvested mice at days 7 and 21. To test the effect of ablation after acute injury, we delivered DT 7 days after bleomycin administration. We assessed fibrosis by lung hydroxyproline content and semiquantitative analysis of picrosirius red staining. We performed bronchoalveolar lavage to determine cell count and differential. We also interrogated mRNA expression of fibrosis-related genes in whole lung RNA. Compared with DT-insensitive littermates where pericyte-like cells were not ablated, DT-sensitive animals exhibited no difference in fibrosis at day 21 both in the early and late pericyte ablation models. However, early ablation of pericytes reduced acute lung inflammation, as indicated by decreased inflammatory cells. Our data confirm a role for pericytes in regulating pulmonary inflammation in early lung injury.
Fibrinogen mediates cadmium-induced macrophage activation and serves as a predictor of cadmium exposure in chronic obstructive pulmonary disease
Authors: Li Fu Jun , Surolia Ranu , Singh Pooja , Dsouza Kevin G. , Stephens Crystal T. , Wang Zheng , Liu Rui-Ming , Bae Sejong , Kim Young-Il , Athar Mohammad , Dransfield Mark T. , Antony Veena B.
Published: February 2022

The etiologies of chronic obstructive pulmonary disease (COPD) remain unclear. Cadmium (Cd) causes both pulmonary fibrosis and emphysema; however, the predictors for Cd exposure and the mechanisms by which Cd causes COPD remain unknown. We demonstrated that Cd burden was increased in lung tissue from subjects with COPD and this was associated with cigarette smoking. Fibrinogen levels increased markedly in lung tissue of patients with smoked COPD compared with never-smokers and control subjects. Fibrinogen concentration also correlated positively with lung Cd load, but inversely with the predicted % of FEV1 and FEV1/FVC. Cd enhanced the secretion of fibrinogen in a cdc2-dependent manner, whereas fibrinogen further mediated Cd-induced peptidylarginine deiminase 2 (PAD2)-dependent macrophage activation. Using lung fibroblasts from CdCl2-treated Toll-like receptor 4 (TLR4) wild-type and mutant mice, we demonstrated that fibrinogen enhanced Cd-induced TLR4-dependent collagen synthesis and cytokine/chemokine production. We further showed that fibrinogen complexed with connective tissue growth factor (CTGF), which in turn promoted the synthesis of plasminogen activator inhibitor-2 (PAI-2) and fibrinogen and inhibited fibrinolysis in Cd-treated mice. The amounts of fibrinogen were increased in the bronchoalveolar lavage fluid (BALF) of Cd-exposed mice. Positive correlations were observed between fibrinogen with hydroxyproline. Our data suggest that fibrinogen is involved in Cd-induced macrophage activation and increases in fibrinogen in patients with COPD may be used as a marker of Cd exposure and predict disease progression.
No evidence for pericardial restraint in the snapping turtle (Chelydra serpentina) following pharmacologically induced bradycardia at rest or during exercise
Authors: Smith Brandt , Crossley Dane A. , Wang Tobias , Joyce William
Published: February 2022

Most animals elevate cardiac output during exercise through a rise in heart rate ( fH), whereas stroke volume (VS) remains relatively unchanged. Cardiac pacing reveals that elevating fH alone does not alter cardiac output, which is instead largely regulated by the peripheral vasculature. In terms of myocardial oxygen demand, an increase in fH is more costly than that which would incur if VS instead were to increase. We hypothesized that fH must increase because any substantial rise in VS would be constrained by the pericardium. To investigate this hypothesis, we explored the effects of pharmacologically induced bradycardia, with ivabradine treatment, on VS at rest and during exercise in the common snapping turtle ( Chelydra serpentina) with intact or opened pericardium. We first showed that, in isolated myocardial preparations, ivabradine exerted a pronounced positive inotropic effect on atrial tissue but only minor effects on ventricle. Ivabradine reduced fH in vivo, such that exercise tachycardia was attenuated. Pulmonary and systemic VS rose in response to ivabradine. The rise in pulmonary VS largely compensated for the bradycardia at rest, leaving total pulmonary flow unchanged by ivabradine, although ivabradine reduced pulmonary blood flow during swimming (exercise × ivabradine interaction, P < 0.05). Although systemic VS increased, systemic blood flow was reduced by ivabradine both at rest and during exercise, despite ivabradine’s potential to increase cardiac contractility. Opening the pericardium had no effect on fH, VS, or blood flows before or after ivabradine, indicating that the pericardium does not constrain VS in turtles, even during pharmacologically induced bradycardia.
Physiologically variable ventilation prevents lung function deterioration in a model of pulmonary fibrosis
Authors: Dos Santos Rocha André , Peták Ferenc , Carvalho Tânia , Habre Walid , Balogh Adam L.
Published: February 2022

The superposition of physiological breathing variability onto a conventional pressure signal during prolonged mechanical ventilation prevents atelectasis development in bleomycin-induced lung fibrosis. This advantage is evidenced by reduced deterioration in tissue mechanics, end-expiratory lung volume, ventilation homogeneity, and gas exchange.
The Antiemetic Mechanisms of Gingerols against Chemotherapy-Induced Nausea and Vomiting
Authors: Dai Yongzhao , Zhao Yaozhong , Nie Ke
Published: February 2022

Chemotherapy-induced nausea and vomiting (CINV) is a common and painful side effect that occurs in cancer patients receiving chemotherapeutic drugs. Although an abundance of agents are applied to prevent CINV, there is still lack of effective control in delayed nausea and vomiting. Ginger (Zingiber officinale Rosc.), a traditional antiemetic herb, draws attention due to its therapeutic effect in treating acute and delayed CINV. Its main bioactive pungent constituents, gingerols, contribute to the antiemetic effect against CINV primarily. A growing number of reports have made progress in investigating the mechanisms of gingerols and their single ingredients against CINV. In this review, we searched for relevant studies in PubMed database to summarize the mechanism of gingerols in the prevention of CINV and provided a preliminary prediction on the potential targets and signaling pathways using network pharmacology, laying a foundation for further researches.
Correlation between Endoscopic Morphology and Bleeding of Gastric Ulcer
Authors: Xiaohua He
Published: February 2022

Objective. To improve the safety and reliability of gastric ulcer treatment, the emergence of digestive endoscopy technology in recent years has become a conventional method for the diagnosis of peptic ulcer bleeding. Endoscopic characteristics can judge the severity of patients more accurately and comprehensively, provide a basis for follow-up treatment, and judge the prognosis. Methods. 298 patients with a suspected gastric ulcer who underwent laryngeal gastroduodenal endoscopy and confirmed gastroduodenal ulcer in our hospital in recent half a year were randomly selected. Olympus cv-170 electronic gastroscope machine was used to carry out gastroscopy for patients with gastric ulcers, analyze, and judge the number of bleeding cases in different stages of treatment, such as lesion type, lesion location, patient age, and gender. The statistics of bleeding cycle and bleeding volume, prognosis recovery, and the correlation of different risk levels were analyzed. Results. After examination and diagnosis, the patients were followed up for one year. According to the number of bleeding cases, bleeding cycle, and bleeding volume of patients with different ulcer locations in the acute stage, healing stage, and scar stage, the distribution of bleeding cases of different ulcer locations in different stages was roughly the same, and there was no significant difference. The proportion of bleeding cases in the acute stage was the highest, while the proportion in the healing stage was the lowest. The number of bleeding cases, bleeding cycle, bleeding volume, and related symptoms in patients with gastric ulcers during the treatment were significantly correlated with those in the acute stage, healing stage, and scar stage. There was no significant difference in the distribution of bleeding in one year among different stages of ulcer in the same age group, however, the bleeding in one year would be more serious with the increase of age in different age groups. Gender differences have a great impact on the bleeding of the ulcer within one year. It usually shows that the bleeding of ulcers in males is more serious than that in females. Conclusion. The location and pathological development of gastric ulcers can be found in time through gastroscopy, and the status of gastroscopy can be analyzed. Most gastric ulcers are acute bleeding. The amount of bleeding has little correlation with the stage of gastric ulcer, and it is related to the location of bleeding. The older the age, the greater the amount of bleeding, and the amount of bleeding in men is greater than that in women. In the treatment of gastric ulcers, gastroscopy, as a doctor’s examination and treatment method, effectively improves the safety and reliability of clinical treatment of gastric ulcer bleeding and reduces the adverse risk.
Research Progress and Treatment Status of Liver Cirrhosis with Hypoproteinemia
Authors: Wen Jianxia , Chen Xing , Wei Shizhang , Ma Xiao , Zhao Yanling
Published: February 2022

Liver cirrhosis is the 14th leading cause of death in adults worldwide. The liver is an important organ for the metabolism of sugar, protein, and fat. Liver cirrhosis with hypoproteinemia (LCH) can lead to metabolic disorders of the nutrients such as sugar, protein, and fat, as well as insufficient protein intake, digestion and absorption disorders, and continuous leakage of plasma protein into the abdominal cavity. Severe hypoproteinemia leads to a poor prognosis in patients. For every 10 g/L decrease in peripheral blood albumin, the risk of secondary liver disease complications will increase by 89% and the mortality rate increased by 24%–56%. Therefore, it is necessary to take urgent measures to treat liver cirrhosis with hypoalbuminemia and effectively treat and reverse the deterioration of the disease caused by hypoalbuminemia, so as to reduce the burden of secondary liver disease. Emerging evidence suggests that protein balance disorders, auxin resistance, and hyperleptinemia are key steps in the development of cirrhosis and hypoproteinemia. This study comprehensively analyzed the common complications, pathogenic mechanisms, and treatment status of cirrhosis caused by hypoproteinemia and proposed research prospects for dealing with this increasingly serious problem.
A Multistrategy-Integrated Learning Sparrow Search Algorithm and Optimization of Engineering Problems
Authors: Wang Zikai , Huang Xueyu , Zhu Donglin
Published: February 2022

The swarm intelligence algorithm is a new technology proposed by researchers inspired by the biological behavior of nature, which has been practically applied in various fields. As a kind of swarm intelligence algorithm, the newly proposed sparrow search algorithm has attracted extensive attention due to its strong optimization ability. Aiming at the problem that it is easy to fall into local optimum, this paper proposes an improved sparrow search algorithm (IHSSA) that combines infinitely folded iterative chaotic mapping (ICMIC) and hybrid reverse learning strategy. In the population initialization stage, the improved ICMIC strategy is combined to increase the distribution breadth of the population and improve the quality of the initial solution. In the finder update stage, a reverse learning strategy based on the lens imaging principle is utilized to update the group of discoverers with high fitness, while the generalized reverse learning strategy is used to update the current global worst solution in the joiner update stage. To balance exploration and exploitation capabilities, crossover strategy is joined to update scout positions. 14 common test functions are selected for experiments, and the Wilcoxon rank sum test method is achieved to verify the effect of the algorithm, which proves that IHSSA has higher accuracy and better convergence performance to obtain solutions than 9 algorithms such as WOA, GWO, PSO, TLBO, and SSA variants. Finally, the IHSSA algorithm is applied to three constrained engineering optimization problems, and satisfactory results are held, which proves the effectiveness and feasibility of the improved algorithm.
Image Contrast Enhancement Method Based on Nonlinear Space and Space Constraints
Authors: Zhao Zhanxing , Gao Xia
Published: February 2022

Remote sensing, environmental monitoring, pattern recognition, and other fields all use this critical and indispensable basic technology. The article proposes an image contrast enhancement detection algorithm based on a linear model to address the problem that the current global contrast enhancement detection algorithm does not have high classification accuracy under the low-intensity JPEG compression quality factor. To decompose the original image, use the biorthogonal wavelet transform. The improved fuzzy set enhancement algorithm is used for the low-frequency subband coefficient. The results obtained after simulating this algorithm show that it is very effective in improving contrast, enhancing image details, and suppressing noise. It has the ability to greatly improve the image’s visual effect, as well as the advantages of parameter adaptation and high algorithm efficiency.
Detecting Illegal Online Gambling (IOG) Services in the Mobile Environment
Authors: Min Moohong , Lee Jemin J. , Lee Kyungho
Published: February 2022

Despite the extensive ramifications of illegal online gambling (IOG) services, actions taken by government authorities have had little effect in halting these operations. In order to reduce the prevalence of IOG, the ability to detect malicious uniform resource locators (URLs) is crucial. Text mining and binary classification have been widely adopted to detect and prevent spam short message services (SMSs), but government authorities and various task forces that monitor and regulate gambling also rely on the analysis of malicious URLs. This study proposes a novel system to analyse the characteristics of spam URLs, offering a method that can assist government agencies combatting mobile IOG sites.
A New Fractional‐Order Map with Infinite Number of Equilibria and Its Encryption Application
Authors: Gasri Ahlem , Khennaoui Amina-Aicha , Ouannas Adel , Grassi Giuseppe , Iatropoulos Apostolos , Moysis Lazaros , Volos Christos
Published: February 2022

The study of the chaotic dynamics in fractional‐order discrete‐time systems has received great attention over the last years. Some efforts have been also devoted to analyze fractional maps with special features. This paper makes a contribution to the topic by introducing a new fractional map that is characterized by both particular dynamic behaviors and specific properties related to the system equilibria. In particular, the conceived one dimensional map is algebraically simpler than all the proposed fractional maps in the literature. Using numerical simulation, we investigate the dynamic and complexity of the fractional map. The results indicate that the new one‐dimensional fractional map displays various types of coexisting attractors. The approximate entropy is used to observe the changes in the sequence sequence complexity when the fractional order and system parameter. Finally, the fractional map is applied to the problem of encrypting electrophysiological signals. For the encryption process, random numbers were generated using the values of the fractional map. Some statistical tests are given to show the performance of the encryption.
Urtica dioica-Derived Phytochemicals for Pharmacological and Therapeutic Applications
Authors: Taheri Yasaman , Quispe Cristina , Herrera-Bravo Jesús , Sharifi-Rad Javad , Ezzat Shahira M. , Merghany Rana M. , Shaheen Shabnum , Azmi Lubna , Prakash Mishra Abhay , Sener Bilge , Kılıç Mehtap , Sen Surjit , Acharya Krishnendu , Nasiri Azadeh , Cruz-Martins Natália , Tsouh Fokou Patrick Valere , Ydyrys Alibek , Bassygarayev Zhandos , Daştan Sevgi Durna , Alshehri Mohammed M. , Calina Daniela , Cho William C.
Published: February 2022

Urtica dioica belongs to the Urticaceae family and is found in many countries around the world. This plant contains a broad range of phytochemicals, such as phenolic compounds, sterols, fatty acids, alkaloids, terpenoids, flavonoids, and lignans, that have been widely reported for their excellent pharmacological activities, including antiviral, antimicrobial, antihelmintic, anticancer, nephroprotective, hepatoprotective, cardioprotective, antiarthritis, antidiabetic, antiendometriosis, antioxidant, anti-inflammatory, and antiaging effects. In this regard, this review highlights fresh insight into the medicinal use, chemical composition, pharmacological properties, and safety profile of U. dioica to guide future works to thoroughly estimate their clinical value.
Characteristics of Acute Appendicitis before and during the COVID-19 Pandemic: Single Center Experience
Authors: Bosak Veršić A. , Šestan M. , Ćepić I. , Nikolić H. , Bukvić N. , Sršen Medančić S. , Hasandić D. , Zelić M.
Published: February 2022

The aim of the study was to investigate whether the COVID-19 pandemic caused an increased incidence of complicated appendicitis due to the late presentation when compared to the pre-COVID-19 period. Summary Background Data. Acute appendicitis is one of the most common surgical emergencies. During the coronavirus-19 (COVID-19) pandemic, there has been a reported delay in the presentation of some urgencies to the emergency hospital departments. Methods. A total of 427 patients who underwent surgical treatment due to suspected acute appendicitis from June 2019 to November 2020 were retrospectively included in this study. The patients were divided into two groups: the first (pre-COVID-19) group consisted of patients who had surgery before the onset of COVID-19 pandemic (n = 240), while the second (COVID-19) group consisted of those who were operated during the COVID-19 pandemic (n = 187). The primary outcome of the study was to compare the incidence of perforated appendicitis before and during the onset of COVID-19. Results. Overall, 84 patients (19.67%) were diagnosed with perforated appendicitis. We found a weak significance (

p
=
0.085

) in the rate of perforated appendicitis between the pre-COVID-19 (17.08%) and the COVID-19 era (22.99%). Conclusions. We did not observe any significant difference in the complications of acute appendicitis before and during the COVID-19 pandemic in a university hospital in Rijeka. An emergent medical care should always be accessible.
Access-Selection Algorithm for Heterogeneous Wireless Networks Based on Uncertain Network Attribute Values
Authors: Guo Xiaoxue , Omar Mohd. Hasbullah , Zaini Khuzairi Mohd , Gong Jianfeng , Fang Jingcheng , Liang Gen
Published: February 2022

A heterogeneous wireless network (HWN) environment contains many kinds of wireless networks, such as UMTS, LTE, and WLAN, where users move around within their coverage area. How to ensure mobile users select the most suitable network is a hot research topic for HWNs. Owing to the mobility of users, the interference of wireless signals, and the fluctuation of network status, the network attribute values obtained by mobile users are often uncertain. However, the traditional access-selection algorithms assume that mobile users can obtain accurate network attribute values, which makes users unable to access the most appropriate network. To solve this problem, this paper designs an access-selection algorithm for HWNs in the context of inaccurate network attribute values. First, the algorithm calculates the network attribute values based on the hesitant fuzzy theory, then calculates the weights of network attributes using the fuzzy analytic hierarchy process (FAHP), and finally sorts the candidate networks using the hesitant fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. The simulation results show that the proposed algorithm enables users to select the most suitable network to access under the inaccurate network attribute environment and obtain higher gains.
Cysteine Donor-Based Brain-Targeting Prodrug: Opportunities and Challenges
Authors: Ni Gaoyang , Hu Zhenbiao , Wang Ziteng , Zhang Min , Liu Xingyu , Yang Guihong , Yan Zhaowei , Zhang Yang
Published: February 2022

Overcoming blood-brain barrier (BBB) to improve brain bioavailability of therapeutic drug remains an ongoing concern. Prodrug is one of the most reliable approaches for delivering agents with low-level BBB permeability into the brain. The well-known antioxidant capacities of cysteine (Cys) and its vital role in glutathione (GSH) synthesis indicate that Cys-based prodrug could potentiate therapeutic drugs against oxidative stress-related neurodegenerative disorders. Moreover, prodrug with Cys moiety could be recognized by the excitatory amino acid transporter 3 (EAAT3) that is highly expressed at the BBB and transports drug into the brain. In this review, we summarized the strategies of crossing BBB, properties of EAAT3 and its natural substrates, Cys and its donors, and Cys donor-based brain-targeting prodrugs by referring to recent investigations. Moreover, the challenges that we are faced with and future research orientations were also addressed and proposed. It is hoped that present review will provide evidence for the pursuit of novel Cys donor-based brain-targeting prodrug.
Robust International Portfolio Optimization with Worst-Case Mean-LPM
Authors: Luan Fei , Zhang Weiguo , Liu Yongjun
Published: February 2022

This paper proposes a robust international portfolio optimization model with the consideration of worst-case lower partial moment (LPM) and worst-case mean return. In our model, we assume that the distributions and the first- and second-order moments of distributions of returns of assets and exchange rates are all ambiguous. The proposed model can be reformulated into an equivalent semidefinite programming (SDP) problem, which is computationally tractable. For investigation of the performance of our model, we also give two benchmark models. The first benchmark model is a scenario-based model which uses historical observations of returns to approximate the future distributions. The second benchmark model only considers the ambiguity of distributions but does not consider the ambiguity of the first- and second-order moments of distributions. We conduct empirical experiments in a rolling forward way to evaluate the out-of-sample performances of our proposed model, the two benchmark models, and an equally weighted model using the return measures and various risk-adjusted return measures. The result shows that our model has the best performance. It verifies that investors can obtain benefits when employing the robust model and considering the ambiguity of the first- and second-order moments of distributions.
Research on Discrete Dynamic System Modeling of Vocal Performance Teaching Platform Based on Big Data Environment
Authors: Gong Xiaohui
Published: February 2022

The traditional teaching model of national vocal music in colleges and universities has some problems, such as low quality of teaching, poor diversity of teaching, and low interest of students. Based on this, this study studies the innovation of the teaching model of national vocal music in colleges and universities based on the deep recurrent neural network algorithm and designs the teaching quality evaluation model based on the deep recurrent neural network algorithm. The collection of data and information is realized from the aspects of students’ class state, vocal music examination results, classroom interaction, etc., and the comprehensive analysis is carried out using the deep recursive neural network algorithm, to realize the multiple analysis and objective evaluation of the whole process of different teaching modes of national vocal music in music colleges and universities, according to the different characteristics and teaching objectives of the teaching process of national vocal music in music colleges and universities The standard requires accurate analysis and evaluation. The results show that the optimization model based on the deep recurrent neural network algorithm has the advantages of high feasibility, high intelligence, and wide range of applications. The experiments show that the deep recurrent neural network algorithm can analyze the effectiveness of the innovation model, and the fuzzy evaluation method can realize the comprehensive evaluation of the innovation mode, which is conducive to the improvement of students’ vocal music learning ability.
An Efficient CNN for Hand X‐Ray Overall Scoring of Rheumatoid Arthritis
Authors: Wang Zijian , Liu Jian , Gu Zongyun , Li Chuanfu
Published: February 2022

Rheumatoid arthritis (RA) is a progressive systemic autoimmune disease characterized by inflammation of the joints and surrounding tissues, which seriously affects the life of patients. The Sharp/van der Heijde method has been widely used in clinical evaluation for the RA disease. However, this manual method is time‐consuming and laborious. Even if two radiologists evaluate a specific location, their subjective evaluation may lead to low inter‐rater reliability. Here, we developed an efficient model powered by deep convolutional neural networks to solve these problems and automated the overall scoring on hand X‐rays. The depthwise separable (Dwise) convolution technique is used based on ResNet‐50 due to the high resolution of hand X‐rays. An inverted residual block is introduced to devise a ResNet‐Dwise50 model to enhance the efficiency of the model. The model was trained and tested using bilateral posteroanterior (two‐handed, side by side) images of 3818 patients. The experiment results show the ResNet‐Dwise50 model achieved an MAE of 14.90 and RMSE of 22.01 while ensuring high efficiency. There was no statistical difference between the average scores given by two experienced radiologists and predicted scores from our model.
Dexmedetomidine Alleviates Lung Oxidative Stress Injury Induced by Ischemia‐Reperfusion in Diabetic Rats via the Nrf2‐Sulfiredoxin1 Pathway
Authors: Wang Xuan , Zhang Bing , Li Guangqi , Zhao Han , Tian Xiaojun , Yu Junmin , Yin Yanwei , Meng Chao
Published: February 2022

Oxidative stress injury (OSI) is an important pathological process in lung ischemia‐reperfusion injury (LIRI), and diabetes mellitus (DM) can exacerbate this injury. Dexmedetomidine protects against LIRI by reducing OSI. However, the effect of dexmedetomidine on LIRI under diabetic conditions remains unclear. Therefore, this study is aimed at exploring the effects and mechanisms of dexmedetomidine on OSI induced by LIRI in diabetic rats. Rats were randomly divided into control+sham (CS), DM+sham (DS), control+ischemia‐reperfusion (CIR), DM+ischemia‐reperfusion (DIR), and DM+ischemia‐reperfusion+dexmedetomidine (DIRD) groups (n = 6). In the CS and DS groups, the nondiabetic and diabetic rats underwent thoracotomy only without LIRI. In the CIR, DIR, and DIRD groups, LIRI was induced through left hilum occlusion for 60 min, followed by reperfusion for 120 min in nondiabetic and diabetic rats, and rats in the DIRD group were administered dexmedetomidine (3, 5, and 10 μg/kg). Compared with those in the CS group, the OSI, lung compliance, apoptosis, and oxygenation indices deteriorated in the DS group (P < 0.05), and these indices were further aggravated in the CIR and DIR groups (P < 0.05), being the worst in the DIR group (P < 0.05). Compared to those of the DIR group, the OSI, lung compliance (15.8 ± 2.4 vs. 11.6 ± 1.7 ml/kg), apoptosis (22.5 ± 2.6 vs. 51.8 ± 5.7), oxygenation (381 ± 58 vs. 308 ± 78 mmHg), and caspase‐3 and caspase‐9 protein expression indices were attenuated, and Nrf2 and sulfiredoxin1 protein expression was increased in the DIRD group (P < 0.05). And the lung injury, oxygenation, OSI, and Nrf2 and sulfiredoxin1 protein expression changed in a concentration‐dependent manner. In conclusion, dexmedetomidine alleviated lung OSI and improved lung function in a diabetic rat LIRI model through the Nrf2‐sulfiredoxin1 pathway.
TCM-Based Therapy as a Rescue Therapy for Re-Eradication of Helicobacter pylori Infection: A Systematic Review and Meta-Analysis
Authors: Zhong Mao-Feng , Li Jun , Liu Xiao-Lin , Gong Peng , Zhang Xiao-Tian
Published: February 2022

The increase in drug-resistant strains poses a severe challenge for Helicobacter pylori (Hp) treatment, and the failure of traditional triple or bismuth quadruple therapy makes it difficult to eradicate Hp. Tailored therapies should be expanded, and traditional Chinese medicine (TCM) may provide the potential regimen. The aim of the present study is to systematically compare TCM-based therapy (TCM combined with Western medicine) and Western medicine as a rescue therapy for Hp re-eradication. Studies through June 12, 2021, with keywords “Helicobacter pylori,” “medicine, Chinese traditional,” or “rescue treatment” and their related expressions were retrieved from PubMed, SinoMed, China National Knowledge Infrastructure, and Wanfang databases. Randomized clinical trials based on PICOS (population, intervention, comparators, outcomes, and study design) eligibility criteria that evaluated the efficacy and safety of integrated therapy on Hp re-eradication were included. The extracted contents included the demographic data of the participants, specific treatment measures, and the results of outcome indicators and safety indicators. Review Manager 5.3 software was used to perform this meta-analysis. Outcome measures including the HP re-eradication rate, symptom remission rate, and adverse effects were seriously analyzed. Under the guide of PRISMA, 18 studies were finally included. Pooled results showed significant differences in eradication rate between integrated and Western medicine therapy in intention-to-treat (ITT) analysis (OR = 2.21, 95% CI: (1.74, 2.81),

P
<
0.01

). Symptom remission is higher in the administration of integrated therapy than in the administration of Western medicine therapy (OR = 2.45, 95% CI: (1.78, 3.37),

P
<
0.01

). It is also indicated that integrated therapy showed significantly less adverse effects (OR = 0.60, 95% CI: (0.42, 0.84),

P
<
0.01

. In conclusion, compared with Western medicine therapy, integrated therapy yields a higher eradication rate and acceptable safety profiles.
Perinatal Hyperoxia and Developmental Consequences on the Lung-Brain Axis
Authors: Obst Stefanie , Herz Josephine , Alejandre Alcazar Miguel A. , Endesfelder Stefanie , Möbius Marius A. , Rüdiger Mario , Felderhoff-Müser Ursula , Bendix Ivo
Published: February 2022

Approximately 11.1% of all newborns worldwide are born preterm. Improved neonatal intensive care significantly increased survival rates over the last decades but failed to reduce the risk for the development of chronic lung disease (i.e., bronchopulmonary dysplasia (BPD)) and impaired neurodevelopment (i.e., encephalopathy of prematurity (EoP)), two major long-term sequelae of prematurity. Premature infants are exposed to relative hyperoxia, when compared to physiological in-utero conditions and, if needed to additional therapeutic oxygen supplementation. Both are associated with an increased risk for impaired organ development. Since the detrimental effects of hyperoxia on the immature retina are known for many years, lung and brain have come into focus in the last decade. Hyperoxia-induced excessive production of reactive oxygen species leading to oxidative stress and inflammation contribute to pulmonary growth restriction and abnormal neurodevelopment, including myelination deficits. Despite a large body of studies, which unraveled important pathophysiological mechanisms for both organs at risk, the majority focused exclusively either on lung or on brain injury. However, considering that preterm infants suffering from BPD are at higher risk for poor neurodevelopmental outcome, an interaction between both organs seems plausible. This review summarizes recent findings regarding mechanisms of hyperoxia-induced neonatal lung and brain injury. We will discuss common pathophysiological pathways, which potentially link both injured organ systems. Furthermore, promises and needs of currently suggested therapies, including pharmacological and regenerative cell-based treatments for BPD and EoP, will be emphasized. Limited therapeutic approaches highlight the urgent need for a better understanding of the mechanisms underlying detrimental effects of hyperoxia on the lung-brain axis in order to pave the way for the development of novel multimodal therapies, ideally targeting both severe preterm birth-associated complications.
Effectiveness of Artificial Intelligence Models for Cardiovascular Disease Prediction: Network Meta-Analysis
Authors: Baashar Yahia , Alkawsi Gamal , Alhussian Hitham , Capretz Luiz Fernando , Alwadain Ayed , Alkahtani Ammar Ahmed , Almomani Malek
Published: February 2022

Heart failure is the most common cause of death in both males and females around the world. Cardiovascular diseases (CVDs), in particular, are the main cause of death worldwide, accounting for 30% of all fatalities in the United States and 45% in Europe. Artificial intelligence (AI) approaches such as machine learning (ML) and deep learning (DL) models are playing an important role in the advancement of heart failure therapy. The main objective of this study was to perform a network meta-analysis of patients with heart failure, stroke, hypertension, and diabetes by comparing the ML and DL models. A comprehensive search of five electronic databases was performed using ScienceDirect, EMBASE, PubMed, Web of Science, and IEEE Xplore. The search strategy was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. The methodological quality of studies was assessed by following the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) guidelines. The random-effects network meta-analysis forest plot with categorical data was used, as were subgroups testing for all four types of treatments and calculating odds ratio (OR) with a 95% confidence interval (CI). Pooled network forest, funnel plots, and the league table, which show the best algorithms for each outcome, were analyzed. Seventeen studies, with a total of 285,213 patients with CVDs, were included in the network meta-analysis. The statistical evidence indicated that the DL algorithms performed well in the prediction of heart failure with AUC of 0.843 and CI [0.840–0.845], while in the ML algorithm, the gradient boosting machine (GBM) achieved an average accuracy of 91.10% in predicting heart failure. An artificial neural network (ANN) performed well in the prediction of diabetes with an OR and CI of 0.0905 [0.0489; 0.1673]. Support vector machine (SVM) performed better for the prediction of stroke with OR and CI of 25.0801 [11.4824; 54.7803]. Random forest (RF) results performed well in the prediction of hypertension with OR and CI of 10.8527 [4.7434; 24.8305]. The findings of this work suggest that the DL models can effectively advance the prediction of and knowledge about heart failure, but there is a lack of literature regarding DL methods in the field of CVDs. As a result, more DL models should be applied in this field. To confirm our findings, more meta-analysis (e.g., Bayesian network) and thorough research with a larger number of patients are encouraged.
QPRT Acts as an Independent Prognostic Factor in Invasive Breast Cancer
Authors: Zhou Lili , Mu Lin , Jiang Wenyan , Yang Qi
Published: February 2022

Background. Quinolinic acid phosphoribosyltransferase (QPRT) is a rate-limiting enzyme that encodes the uronic acid pathway, which is involved in cell cycle progression and cancer cell metabolism. Some studies have demonstrated the progrowth effect of QPRT on breast cancer (BRCA) tumour cells, but its mechanism of action requires further exploration. Methods. We investigated the expression of QPRT and the prognosis of patients with different tumours by performing a pan-cancer analysis of QPRT. Prognostic values for overall survival (OS) were determined using uni- and multivariate Cox proportional hazard analyses. The prognostic survival of patients with a different pathological staging of BRCA and with QPRT high and low expression was also analysed. We also explored the relevant pathways by which QPRT affected BRCA tumorigenesis by gene set enrichment analysis (GSEA) and western blotting. The impact of QPRT on the PI3K/Akt pathway was also evaluated. Results. Pan-cancer analysis revealed significant QPRT expression in pan-cancer and correlated with prognosis in most tumour patients. QPRT was also highly expressed in BRCA when patients had poor prognoses, and its expression was associated with different pathological BRCA subtypes. GSEA revealed an association between BRCA progression and the cell cycle and the phosphatidylinositol 3-kinase (PI3K)/Akt signalling pathway, and this association was confirmed by western blotting. Conclusion. QPRT is highly expressed in breast cancer and particularly in HER2 breast cancer. Upregulated QPRT expression is an independent predictor of breast cancer prognosis and promotes breast cancer progression by activating the PI3K/Akt signalling pathway.
Fixed Point Theory and the Liouville–Caputo Integro-Differential FBVP with Multiple Nonlinear Terms
Authors: Rezapour Shahram , Boulfoul Ali , Tellab Brahim , Samei Mohammad Esmael , Etemad Sina , George Reny
Published: February 2022

This work is reserved for the study of a special category of boundary value problems (

BVP

s) consisting of Liouville–Caputo integro-differential equations with multiple nonlinear terms. This fractional model and its boundary value conditions (BVCs) involve different simple

BVP

s, in which the second BVC as a linear combination of two Caputo derivatives of the unknown function equals a nonzero constant. The Banach principle gives a unique solution for this Liouville–Caputo

BVP

. Further, the Krasnoselskii and Leray–Schauder criteria give the existence property regarding solutions of the mentioned problem. For each theorem, we provide an example based on the required hypotheses and derive numerical data in the framework of tables and figures to show the consistency of results from different points of view.
Adherence to Medication among Parkinson’s Disease Patients Using the Adherence to Refills and Medications Scale
Authors: Radojević Branislava , Dragašević-Mišković Nataša T. , Milovanović Andona , Svetel Marina , Petrović Igor , Pešić Maja , Tomić Aleksandra , Stanisavljević Dejana , Savić Miroslav M. , Kostić Vladimir S.
Published: February 2022

Objectives. Adherence to medication is an important factor that can influence Parkinson’s disease (PD) control. We aimed to explore patients’ adherence to antiparkinsonian medication and determine factors that might affect adherence to medications among PD patients. Methods. A cross-sectional, exploratory survey of PD patients treated with at least one antiparkinsonian drug and with a total score of MoCA (Montreal Cognitive Assessment) ≥26 was conducted. The final sample included 112 PD patients. A patient’s adherence was assessed through ARMS (Adherence to Refills and Medications Scale). ARMS scores higher than 12 were assumed lower adherence. In addition, each patient underwent neurological examination, assessment of depression, anxiety, and evaluation of the presence of PD nonmotor symptoms. Results. The mean ARDS value in our cohort was 14.9 ± 2.5. Most PD patients (74.1%) reported lower adherence to their medication. Participants in the lower adherence group were younger at PD onset, had significantly higher UPDRS (Unified PD Rating Scale) scores, as well as UPDRS III and UPDRS IV subscores, HARS (Hamilton Anxiety Rating Scale), and NMSQuest (Non-Motor Symptoms Questionnaire for PD) scores compared to the fully adherent group (

p
=
0.013

,

p
=
0.017

,

p
=
0.041

,

p
=
0.043

, and

p
=
0.023

, respectively). Among nonmotor PD symptoms, the presence of cardiovascular, apathy/attention-deficit/memory disorders, hallucinations/delusions, and problems regarding changes in weight, diplopia, or sweating were associated with lower adherence. Multivariate regression analysis revealed depression as the strongest independent predictor of lower adherence. Conclusion. Depressed PD patients compared to PD patients without clinical depression had a three times higher risk for lower adherence to pharmacotherapy. Recognition and adequate treatment of depression might result in improved adherence.
Bibliometric and Visualized Analyses of Research Studies on Different Analgesics in the Treatment of Orthopedic Postoperative Pain
Authors: Cheng Yunzhong , Yang Honghao , Guan Li , Hai Yong , Pan Aixing
Published: February 2022

Background. Pain following orthopedic surgery has always been a critical issue, which caused great distress to the patients. Analgesics in the treatment of postoperative pain following orthopedic surgery have aroused great attention from scholars, and numerous studies have been published in recent years. Bibliometrics could assist scholars in understanding the scope of research topics better, identifying research focuses and key literature, and analyzing the development and trend of analgesics in the treatment of postoperative pain following orthopedic surgery. Methods. Literature data were retrieved from the Science Citation Index Expanded (SCI-E) of Web of Science (WOS) Core collection database. The articles from 1992 to December 2021 on analgesics in the treatment of postoperative pain following orthopedic surgery were recruited. The citation reports including the publication numbers, h-index, total citations, and average citations in terms of authors, organizations, and countries were obtained. Top 20 research directions, funds, and journals with the most publications were charted. The co-authorship relations in the analysis units of authors, organizations, and countries were analyzed by the online bibliometric tool and VOSviewer software. The author’s keywords co-occurrence overlay map was visualized by the VOSviewer software. Results. A total of 406 articles were retrieved from 1992 to December 4th, 2021, with 11,655 times cited, average citations of 28.57 per item, and an h-index of 55. The most high-yield publication year, authors, organizations, countries, research directions, funds, and journals were 2020 (n = 887), Ilfeld BM from University of California San Diego (n = 7), University of California System (n = 21), the USA (n = 178), Anesthesiology (n = 161), National Institutes of Health (NIH), USA, and United States Department of Health Human Services (n = 12), and Anesthesia and Analgesia (n = 29), respectively. Similarly, co-authoring analysis of publications regarding on different analgesics showed that the authors and countries with the most co-authorship strength were Carr Daniel B (total link strength = 6) and the USA (total link strength = 30), respectively. The highest occurrence keywords were “postoperative pain” with 135 occurrences (total link strength = 784). The future research hotspots might be “acute pain,” “outcomes,” “oxycodone,” “total hip,” “replacement,” and “United States.” Conclusion. Analgesics in the treatment of postoperative pain following orthopedic surgery can be observed in this study by employing the online bibliometric tool and VOSviewer software, which established the relationship between the units of analysis. It can provide a meaningful resource with detailed information for orthopedic surgeons who would like to understand the trend in this field better. They can also benefit from the emphasis on citation count to carry out high-level research in the future.