bluuebunny/crossref_metadata_2025 huggingface dataset:
Glycerol as a Binder Additive for Low-Resistance Graphite Anodes in Lithium-Ion Batteries
Authors: Park Kiho , Kim Sungchan , Kim Jaemin , Seo Gyuwon , Baek Minsung , Cho Yunshik , Lee Jungmin , Choi Jang Wook
Published: April 2022

Lithium-ion batteries (LIBs) have matured as a technology and serve as power sources in a wide range of applications. Nonetheless, emerging applications, represented by electric vehicles, have been imposing ever-challenging criteria with regard to the key electrochemical properties. Low-resistance anodes are highly desired for high-power and supercharging capabilities of LIBs, and these properties are collectively determined by the electrolyte composition and electrode binder. Here, we report the use of glycerol as an additive to the conventional styrene-butadiene rubber/carboxymethyl cellulose (SBR/CMC) binder for graphite anodes with the aim of lowering the interfacial resistance and thus improving the operating capability at high C-rates. Glycerol, as a plasticizer, increases the interchain free volume in the binder network and also promotes the dissociation of lithium salt owing to its high dielectric constant, both of which jointly facilitate lithium ion diffusion at the anode interface. As a result, the addition of a small amount (0.18 wt% of the entire electrode) of glycerol enhances the high-rate capability (i.e., >1 C). This study highlights the usefulness of small molecules as binder additives for improving the key performance parameters of LIBs without sacrificing other critical properties.
One percent of the clinical dose used for antenatal steroid therapy is sufficient to induce lung maturation when administered directly to the preterm ovine fetus
Authors: Fee Erin L. , Takahashi Tsukasa , Takahashi Yuki , Carter Sean , Furfaro Lucy , Clarke Michael W. , Milad Mark A. , Usuda Haruo , Newnham John P. , Saito Masatoshi , Jobe Alan H. , Kemp Matthew W.
Published: April 2022

Antenatal steroids (ANSs) are routinely administered to women judged to be at imminent risk of preterm delivery. Their principal benefit is precocious functional maturation of the preterm fetal lung. Current dosing regimens expose the mother and fetus to high steroid levels that may be unnecessary, increasing the potential risks of disruption to the maternal and fetal hypothalamic-pituitary-adrenal (HPA) axis and glucose regulation, alterations in placental function, and reduced fetal growth. Using a sheep model of pregnancy, we tested the hypothesis that direct fetal administration of an ultra-low dose course of betamethasone phosphate (∼0.33 mg) would be sufficient to elicit functional maturation of the fetal lung. A jugular catheter was installed in singleton ovine fetuses at 122-day gestation under general anesthesia. Animals were randomized to receive either: 1) fetal intravenous betamethasone phosphate to target fetal plasma betamethasone mean levels of 2 ng/mL for 26 h (fetal treatment group; n = 16); 2) fetal intravenous saline for 26 h and two maternal intramuscular injections of 0.25 mg/kg betamethasone phosphate + betamethasone acetate, simulating a standard clinical treatment (maternal treatment group; n = 12); or 3) fetal intravenous saline only for 26 h (negative control group; n = 10). Fetuses were delivered 48 h after surgery, ventilated for 30 min to allow the collection of lung function and physiological data, and euthanized. Quantitative PCR and Western blots were used to assess markers of lung maturation. The average total betamethasone phosphate dose for the fetal treatment group was 1% (0.3 mg) of the maternal treatment group (31-mg betamethasone phosphate + betamethasone acetate). At 30 min of ventilation, arterial [Formula: see text], pH, heart rate, and ventilation efficacy index (VEI) were significantly ( P < 0.05) and equivalently improved in both the fetal treatment group and maternal treatment group, relative to the negative control group. Similarly, SP-A, SP-C, and AQ-5 mRNA expression was significantly higher in both the fetal treatment group and maternal treatment group, relative to negative control. Maternal steroid administration was not required to generate preterm fetal lung maturation in sheep. Using a low dose and targeting steroid treatments directly to the fetus has the potential to significantly reduce maternal exposures, while simultaneously reducing the potential risk of adverse outcomes associated with current clinical dosing regimens.
Chloride channel accessory 1 gene deficiency causes selective loss of mucus production in a new pig model
Authors: Keeler Shamus P. , Yantis Jennifer , Gerovac Benjamin J. , Youkilis Samuel L. , Podgorny Stephanie , Mao Dailing , Zhang Yong , Whitworth Kristin M. , Redel Bethany , Samuel Melissa S. , Wells Kevin D. , Prather Randall S. , Holtzman Michael J.
Published: April 2022

Morbidity and mortality of respiratory diseases are linked to airway obstruction by mucus but there are still no specific, safe, and effective drugs to correct this phenotype. The need for better treatment requires a new understanding of the basis for mucus production. In that regard, studies of human airway epithelial cells in primary culture show that a mucin granule constituent known as chloride channel accessory 1 (CLCA1) is required for inducible expression of the inflammatory mucin MUC5AC in response to potent type 2 cytokines. However, it remained uncertain whether CLCLA1 is necessary for mucus production in vivo. Conventional approaches to functional biology using targeted gene knockout were difficult due to the functional redundancy of additional Clca genes in mice not found in humans. We reasoned that CLCA1 function might be better addressed in pigs that maintain the same four-member CLCA gene locus and the corresponding mucosal and submucosal populations of mucous cells found in humans. Here we develop to our knowledge the first CLCA1-gene-deficient ( CLCA1–/–) pig and show that these animals exhibit loss of MUC5AC+ mucous cells throughout the airway mucosa of the lung without affecting comparable cells in the tracheal mucosa or MUC5B+ mucous cells in submucosal glands. Similarly, CLCA1–/– pigs exhibit loss of MUC5AC+ mucous cells in the intestinal mucosa without affecting MUC2+ mucous cells. These data establish CLCA1 function for controlling MUC5AC expression as a marker of mucus production and provide a new animal model to study mucus production at respiratory and intestinal sites.
Modelling Customs Revenue in Ghana Using Novel Time Series Methods
Authors: Agbenyega Diana Ayorkor , Andoh John , Iddi Samuel , Asiedu Louis
Published: April 2022

Governments across the world rely on their Customs Administration to provide functions that include border security, intellectual property rights protection, environmental protection, and revenue mobilisation amongst others. Analyzing the trends in revenue being collected from Customs is necessary to direct government policies and decisions. Models that can capture the trends being purported from the nominal (nonreal) tax values with respect to the trade volumes (value) over the period are indispensable. Predominant amongst the existing models are the econometric models (the GDP-based model, the monthly receipts model, and the microsimulation model), which are laborious and sometimes unreliable when studying trends in time series data. In this study, we modelled monthly revenue data obtained from the Ghana Revenue Authority-Customs Division (GRA-CD) for the period January 2010 to December 2019 using two traditional time series models, ARIMA model and ARIMA Error Regression Model (ARIMAX), and two machine learning time series models, Bayesian Structural Time Series (BSTS) model and a Neural Network Autoregression model. The Neural Network Autoregression model of the form NNAR (1, 3) provided the best forecasts with the least Mean Squared Error (MSE) of 53.87 and relatively lower Mean Absolute Percentage Error (MAPE) of 0.08. Generally, the machine learning models (NNAR (1, 3) and BSTS) outperformed the traditional time series models (ARIMA and ARIMAX models). The forecast values from the NNAR (1, 3) indicated a potential decline in revenue and this emphasizes the need for relevant authorities to institute measures to improve revenue generation in the immediate future.
Cross-Project Defect Prediction Based on Two-Phase Feature Importance Amplification
Authors: Xing Ying , Lin Wanting , Lin Xueyan , Yang Bin , Tan Zhou
Published: April 2022

As the typical application of computational intelligence in software engineering, cross-project defect prediction (CPDP) uses labeled data from other projects (source projects) for building models to predict the defects in the current projects (target projects), helping testers quickly locate the defective modules. But class imbalance and different data distribution among projects make CPDP a challenging topic. To address the above two problems, we propose a two-phase feature importance amplification (TFIA) CPDP model in this paper which can solve these two problems from domain adaptation phase and classification phase. In the domain adaptation phase, the differences in data distribution among projects are reduced by filtering both source and target projects, and the correlation-based feature selection with greedy best-first search amplifies the importance of features with strong feature-class correlation. In the classification phase, Random Forest works as the classifier to further amplify the importance of highly correlated features and establish a model which is sensitive to highly correlated features. We conducted both ablation experiments and comparison experiments on the widely used AEEEM database. Experimental results show that TFIA can yield significant improvement on CPDP. And the performance of TFIA CPDP model in all experiments is stable and efficient, which lays a solid foundation for its further application in practical engineering.
Application of Emergency Specialist Nursing Combined with Green Channel Mode in Patients with Limb Amputation
Authors: Qian Zaiyun , Wang Min , Xu Tonglong
Published: April 2022

Background. The treatment of limb amputation is always a challenge to emergency medical staff. The success of replantation of severed limbs requires not only emergency professional nursing measures but also rapid transport against time. We that found emergency specialist nursing combined with green channel mode can effectively improve the success rate of amputated limb replantation surgery. Methods. From September 2017 to August 2020, the medical records of 80 patients with severed limb replantation treated by the emergency department of our hospital were collected and divided into the control group and the experimental group. 36 patients in the control group were emergency patients treated from September 2017 to May 2019. These patients did not take appropriate emergency specialist nursing measures and opened green channels at that time; the other 44 patients were in the experimental group, for emergency patients treated from June 2019 to August 2020. These patients have received emergency specialist care and opened a green channel. We recorded the gender, age, preoperative examination time, and success rate of amputated limb replantation surgery of the two groups of patients. Results. The age of the patients in the control group was

41.17
±
8.00

years old, and the age of the patients in the experimental group was

41.07
±
7.31

years old (

P
>
0.05

). The preoperative examination time of the patients in the control group was

46.53
±
4.11

 min, and the preoperative examination time of the patients in the experimental group was

40.34
±
5.85

 min (

P
<
0.05

); the replantation success rate of the control group was 72.2%, and the replantation success rate of the experimental group was 81.8% (

P
<
0.05

). Conclusion. Standardized emergency specialist nursing measures combined with green channel mode can effectively shorten the preoperative examination time and help improve the success rate of amputated limb replantation surgery.
A Novel Continuous Fracture Network Model: Formation Mechanism, Numerical Simulation, and Field Application
Authors: Guo Zixi , Zhao Jinzhou , Sun Xinhao , Wang Chengwang , Guo Dali , Hu Haoran , Wang Hongna , Zeng Qinggang
Published: April 2022

After a shale gas reservoir is fractured, hydraulic fractures interweave with natural fractures to form a fracture network. Numerical simulation based on the continuous fracture network model is a relatively economical and convenient method to predict fracture network morphology and size in the field application. However, some important factors, such as fracture height variation and filtration loss, have not been considered in the past continuous fracture network models. Therefore, this paper is aimed at establishing a novel continuous fracture network model to improve simulation accuracy. Firstly, this paper established a method to judge whether natural fractures develop or not. Then, a novel continuous fracture network model considering fracture height variation and asymmetry, filtration loss, fluid flow, and other key factors was established, and the forward algorithm and inverse algorithm of the model were proposed. At last, this model was applied in a field case to verify accuracy, and the average accuracy is more than 90%. Compared with the traditional Meyer software, the average error of prediction was reduced by 7.86%.
[Retracted] Relationship between Green Financing and Investment Logic and Effectiveness Evaluation of Financing Decisions
Authors: Kong Lei , Lei Yu , Zhang Qian , Zhang Jing , Guo Xingzhi , Shi Daoyuan
Published: April 2022

Green financing diverts more funds to green industries such as environmental protection, and clean energy, enabling the industries to realize structural adjustment. On green financing, the existing studies at home and abroad mainly focus on the definition of concepts and service scope and system construction. There are few attempts to combined green financing efficacy with corporate investment from the angles of investment level, investment efficiency, and investment risks. This paper associates green financing policy with corporate investment, analyzes the logical connection between the two, and thereby evaluates the effectiveness of green financing decisions. Specifically, a decision model was established for the government participation in green financing via green product subsidy, and a solving algorithm was developed for the model. After that, the authors analyzed the correlations of green financing with the investment level and investment efficiency of green enterprises. Next, the effectiveness of green financing decisions was discussed under dynamic operation risks. Finally, the proposed approach was demonstrated through simulation and empirical analysis.
The Function Improved of the Newly Designed Magnetic‐End Ureteric Stenting Retrieval Device: A Clinical Prospective Randomized and Control Trial in a Multicenter Study
Authors: Zeng Shaohua , Liu Bo , Hu Hu , Shi Jian , Qian Ping , Zhang Xiaoping , Peng Kexue , Yang Sixing , Huang Zheng , Pan Tiejun
Published: April 2022

Objective. To demonstrate the advantage of our newly designed magnetic ureteric stenting retrieval device over traditional nonmagnetic ureteric stents and other retrieval devices without cystoscopy intervention on clinical application and cost‐related outcomes. Patients and Methods. A total of 333 patients were recruited into two study groups: magnetic‐end ureteral stent (Group A) and conventional ureteral stent (Group B). The effects were evaluated by Ureteral Stent Symptom Questionnaire (USSQ) scores, complications of the indwelling stent, visual analog scale (VAS) pain scores at stent removal, and cost‐analysis outcomes between the magnetic ureteric stenting retrieval device and traditional double‐J ureteral stent (DJUS) removed by cystoscopy. Results. The VAS of the pain score of patients undergoing magnetic stent removal with the retrieval device was 2 ± 0.97, whereas that of patients undergoing conventional ureteral stent removal with cystoscopy was 5.76 ± 1.53 (p < 0.001). The removal of magnetic stents by a retrieval device proved to be less painful than cystoscopy‐mediated stent removal (p < 0.001). Obviously, the total cost for the magnetic stent removal was much lower than the conventional ureteral stent removal, although the magnetic stent costs more than the conventional ureteral stent. The improved magnetic stent used in our study showed a remarkable cost saving of 705/111 USD Chinese Yuan (CNY) per patient when compared with the conventional ureteral stent. Conclusion. We reported the integrated design features of the improved magnetic stent in the world, which was granted a patent in China. USSQ scores and rate of complications in the magnetic stent were as equally acceptable as a conventional stent. Furthermore, successful stent insertion rate reached 100% by both the antegrade and retrograde approaches, and no failure case of magnetic stent removal was reported in our study.
Efficacy and Adverse Reactions of Arthroscopic Half-Moon Plate Invasive Surgery in Patients with Acute Knee Pain (AKP): Systematic Review and Meta-Analysis
Authors: Sun Luping , Huang Zhidan
Published: April 2022

Objective. To evaluate the efficacy and adverse reactions of arthroscopic half-moon plate invasive surgery (DEB) in patients with knee pain (AKP) using meta-analysis techniques. Methods. The computer retrieves from the English databases PubMed, EMBASE, Cochrane Library, and Web of Science and the Chinese databases China Knowledge Network, Wanfang Database, VIP Database, and China Biomedical Literature Database to collect information about DEB therapeutic AKP randomized controlled trial. Develop criteria for documentation inclusion and exclusion, evaluate the quality and bias risk of literature, and compare differences in efficacy and adverse responses before and after DEB treatment and other conservative treatments. Results. A total of 14 randomized controlled trials and 1464 AKP patients were included in the study, with follow-up duration of 1-12 months. The total knee scores for DEB at 1, 3, 6, and 12 months after treatment were significantly better than baseline levels (1 month:WMD=34.56,P=0.02; 3 months:WMD=27.73,P=0.0001; 6 months:SMD=2.38,P=0.0001; 12 months:SMD=1.69,P=0.001). At 6 months of follow-up, DEB improved knee function better than HA (SMD=0.47,P=0.003), and during follow-up for 12 months, DEB relieved knee pain (SMD=0.55,P=0.0007) and improved knee function (SMD=0.88,P=0.0001) which is significantly better than HA. DEB was less effective at improving knee function in 1, 3, and 12 months than DEB joint HA injections (1 monthP=004; 3 monthsP=0.01; 12 monthsP=0.03). At 6 and 12 months of follow-up, DEB was better at pain relief and improved function than ozone (P>0.05). DEB and glucocorticosteroids have similar effects in pain relief and improved function at various follow-up times. In terms of adverse reactions, DEB does not increase the risk of adverse events compared to HA (OR=0.96,P=0.85). Conclusion. Compared to HA and ozone, DEB is a more effective treatment for AKP joints, while DEB is combined with HA. The clinical efficacy of injection therapy AKP is better than that of DEB alone.
Analysis of Artificial Neural Network: Architecture, Types, and Forecasting Applications
Authors: Madhiarasan Manogaran , Louzazni Mohamed
Published: April 2022

The artificial neural network reduces humanity and society’s burden to solve complex problems highly efficiently. Artificial neural networks resemble brain activities based on the acquired training samples used for various applications such as classification, regression, prediction, smart grid, natural language processing, image processing, medical diagnosis, and so on. This paper illustrates the different artificial neural network architectures, types, merits, demerits, and applications. Therefore, this paper provides valuable information to students and researchers to enrich their knowledge about an artificial neural network and research it. This paper also proposed a multilayer-perceptron-neural-network-based solar irradiance forecasting model, an improved backpropagation neural network-based rainfall forecasting model, and an Elman neural network-based temperature forecasting model. The performances of the proposed neural network-based forecasting models are analyzed with various hidden neurons and validated using the acquired real-time meteorological data. The proposed neural network forecasting models achieve rigorous results with reduced errors for the considered applications and aid sustainability.
Diet-Induced Obesity Promotes Liver Metastasis of Pancreatic Ductal Adenocarcinoma via CX3CL1/CX3CR1 Axis
Authors: Sun Yue , Zhang Xiao-Xin , Huang Shan , Pan Hong , Gai Yan-Zhi , Zhou Yao-Qi , Zhu Lei , Nie Hui-Zhen , Li Dong-Xue
Published: April 2022

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, and the patients are generally diagnosed with distant metastasis. Liver is one of the preferred organs of distant metastasis, and liver metastasis is the leading cause of death in PDAC. Diet-induced obesity (DIO) is a risk factor for PDAC, and it remains unclear whether and how DIO contributes to liver metastasis of PDAC. In our study, we found that DIO significantly promoted PDAC liver metastasis compared with normal diet (ND) in intrasplenic injection mouse model. RNA-seq analysis for liver metastasis nodules showed that the various chemokines and several chemokine receptors were altered between ND and DIO samples. The expression levels of CX3CL1 and CX3CR1 were significantly upregulated in DIO-induced liver metastasis of PDAC compared to ND. Increased CX3CL1 promoted the recruitment of CX3CR1-expressing pancreatic tumor cells. Taken together, our data demonstrated that DIO promoted PDAC liver metastasis via CX3CL1/CX3CR1 axis.
Speech as a Biomarker for COVID-19 Detection Using Machine Learning
Authors: Usman Mohammed , Gunjan Vinit Kumar , Wajid Mohd , Zubair Mohammed , Siddiquee Kazy Noor-e-alam
Published: April 2022

The use of speech as a biomedical signal for diagnosing COVID-19 is investigated using statistical analysis of speech spectral features and classification algorithms based on machine learning. It is established that spectral features of speech, obtained by computing the short-time Fourier Transform (STFT), get altered in a statistical sense as a result of physiological changes. These spectral features are then used as input features to machine learning-based classification algorithms to classify them as coming from a COVID-19 positive individual or not. Speech samples from healthy as well as “asymptomatic” COVID-19 positive individuals have been used in this study. It is shown that the RMS error of statistical distribution fitting is higher in the case of speech samples of COVID-19 positive speech samples as compared to the speech samples of healthy individuals. Five state-of-the-art machine learning classification algorithms have also been analyzed, and the performance evaluation metrics of these algorithms are also presented. The tuning of machine learning model parameters is done so as to minimize the misclassification of COVID-19 positive individuals as being COVID-19 negative since the cost associated with this misclassification is higher than the opposite misclassification. The best performance in terms of the “recall” metric is observed for the Decision Forest algorithm which gives a recall value of 0.7892.
Cluster Analysis Algorithm in the Analysis of College Students’ Mental Health Education
Authors: Zheng Wanting
Published: April 2022

With the rapid development of curricula, a large number of studies are emerging to assist in the development of curricula. But in an information society, in the face of rapid learning and increased life expectancy, students face the pressure not to forget; the mental health status as a result of our curricula is closely related to our learning. The research and application of the integration algorithm plays an important role in the analysis of the mental health education system. The purpose of this work is to study the application analysis algorithm in the students’ context. This work applies the integration analysis algorithm to students’ mental health analysis and identifies students’ mental health problems using the integration analysis algorithm so that students are well informed and guided. Based on the system engineering method, using the data mining clustering method, a detailed analysis and research on the mental health of college students is done. In this work, a method of student behavior analysis and statistical tools are used to collect mental health data to find common features of different groups of students, in order to better visualize and investigate the mental health of these students on a scientific basis. The results of this study are as follows: a general analysis algorithm application on the analysis of students’ mental health education system allows for an effective understanding of scientific data. FCM and FCM algorithms based on the density of information entropy characteristics were used to investigate the effect of mental health factors on the results of the study and the practicality of the algorithm used, which provided an effective method for the prevention of student mental problems. Assisting the school in formulating corresponding new methods of early prevention and intervention of college students’ psychological disorders will create a good and healthy atmosphere for college students’ study and life. The research results provide a reliable basis for managing and cultivating students.
Arabic Validity of the (CARE) Measure for Improving Medical and Mental Health Services
Authors: Elfaki Abdelaziz , AlQarni Amani M , AlGhamdi Amal A. , AlShammari Malak A. , Nasir Farheen , Alabdulqader Rana
Published: April 2022

Aim of the Study. To construct then examine the internal consistency, reliability and validity of the Arabic consultation and relational empathy (CARE) measurement tool. Design and Methodology. The CARE measurement tool was translated into Arabic version and examined on 1245 patients of a primary health care center in the eastern province of Saudi Arabia. Results. The majority of the item’s responses showed high level of satisfaction. The coronach alpha of our study that examines the Arabic version of the CARE measurement tool 10 items was 0.96 showing an excellent internal consistency. The Kaiser-Meyer-Olkin measure was 0.96 indicating the adequacy of the data for factor analysis and the Bartlett test of sphericity shows (x2(45) = 8743.126,

p
<
0.001

) indicating the adequacy of the correlation matrix for analysis. Conclusion. The Arabic version of CARE Measure seems to be consistent and reliable in the primary health care setting.
A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos‐Based Quantum Map
Authors: Alharbi Adel R. , Ahmad Jawad , Arshad  , Jamal Sajjad Shaukat , Masood Fawad , Ghadi Yazeed Yasin , Pitropakis Nikolaos , J Buchanan William
Published: April 2022

With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy‐preserving cryptosystem is necessary. Such a solution relies on chaos encryption algorithms over standard cryptographic methods that possess multistage encryption levels, including high speed, high security, low compute overheads, and procedural power, among other characteristics. In this work, a secure image encryption scheme is proposed using linear feedback shift register (LFSR) and chaos‐based quantum chaotic map. The focus of the scheme is mainly dependent on the secret keys from the input of the algorithm. The threat landscape, the statistical test analysis, along critical comparisons with other schemes indicate that the presented algorithm is significantly secure and is resistant to a wide range of different attacks such as differential and statistical attacks. The proposed method has sufficiently higher sensitivity and security when compared to existing encryption algorithms. Several security parameters validated the security of proposed work such as correlation coefficient analyses among the neighboring pixels, entropy, the number of pixels change rate (NPCR), unified average change intensity (UACI), mean square error (MSE), brute force, key sensitivity, and peak signal to noise ratio (PSNR) analyses. The randomness of the ciphers produced by the proposed technique is also passed through NIST‐800‐22. The results of NIST indicate that the ciphers are highly random and do not produce any type of periodicity or pattern.
Paeoniflorin Attenuated TREM-1-Mediated Inflammation in THP-1 Cells
Authors: Cao Li , Yang Kerong
Published: April 2022

Sepsis is caused by bacterial infections or viral infections. Clinically, there exist confirmed or highly suspected infection foci. Mortality caused by septic shock remains in a high rate even though antibiotic treatment works effectively. In this study, we treat THP-1 cells with 1 ug/mL LPS (lipopolysaccharide) and add paeoniflorin or LR-12 inhibitor. TREM-1 (triggering receptor expressed on myeloid cells-1), IL-6, IL-1β, and TNF-α (tumour necrosis factor alpha (a)-cachectin) were detected by ELISA and qRT-PCR, and western blotting is performed to detect related proteins in the NF-κB signaling pathway. As a result, paeoniflorin can significantly reduce the production of LPS-stimulated TREM-1 as well as inflammatory factors and attenuate the phosphorylation of NF-κB signaling pathway-related factors, such as p65 and IκBα. At the same time, the combined effect of paeoniflorin and LR-12 is more significant. The results of this study solidly prove that paeoniflorin plays a role in inhibiting TREM-1-mediated inflammation and the NF-κB pathway could be a potential mechanism of action.
Evolutionary Game and Simulation Research of Blockchain‐Based Co‐Governance of Emergency Supply Allocation
Authors: Zhao Huawei , Ma Lili
Published: April 2022

Recently, with the spread of COVID‐19 pandemic, emergency supply allocation system is drawing more and more social attention. Emergency supply allocation system is an important part of emergency governance system. It reflects social organizations’ credibility, public safety, and the modernization level of social governance. However, emergency supply allocation system still has some problems, such as information asymmetry, different desires of participants, unreasonable allocation, and so on. At present, it is widely accepted that the advantage of blockchain in co‐governance could be of great help in solving above problems. And in order to distinguish the effect of blockchain to the emergency supply allocation, the paper builds a tripartite evolutionary game model among the government, social organizations, and the public to analyse the impact of blockchain platform on emergency supply allocation. The simulation analysis shows the following: (1) The strategy choices of the government have a crucial impact on the evolution and stability of social organizations’ strategies. It needs a long‐term process to guide social organizations practicing active allocation, and the government should accelerate to build the blockchain platform to promote this process. (2) With the help of blockchain platform, the increment of penalty intensity of the government is conductive to increasing the probabilities that social organizations practice active allocation and the government practices strict supervision. (3) Blockchain platform has a significant impact on social organizations’ choice for active allocation in many aspects, such as the positive and negative effects of social organizations, effect’s increasing multiple, and the cost of the public informing. In the end, some suggestions are presented to improve the co‐governance of emergency supply allocation.
Optimization and Design of College Students’ Innovation and Entrepreneurship System Based on Computational Intelligence
Authors: Bai Lijun , Wang Chuanchao , Zhang Lili
Published: April 2022

At present, college students’ innovation and entrepreneurship has gradually become a hot topic nowadays, and the popularity of related knowledge of college students’ innovation and entrepreneurship is getting higher and higher, and more college students have joined in independent innovation and entrepreneurship. In order to alleviate a series of problems in college students’ innovation and entrepreneurship, we design an SD model under computational intelligence to put forward corresponding solutions to the problems faced in innovation and entrepreneurship, through the establishment of relevant models and experiments to verify that SD model is based on computational intelligence to optimize the design of college students’ innovation and entrepreneurship system. We know that the dimensions of tools include three dimensions: supply, demand, and environment. With the change of time, college students’ choice of tools for innovation and entrepreneurship has developed from a single supply tool to a multidimensional tool choice. Through the establishment of SD computational intelligence model to optimize the innovation and entrepreneurship system of college students, through the survey data, it can be seen that the prediction error value of SD model is about 9% and less than 10%, which is within the negligible error range, indicating that SD model has an optimization effect on the innovation and entrepreneurship system of college students. According to the survey, the three dimensions of capital investment, experience, and education level have an impact on college students’ innovation and entrepreneurship, accounting for 45%, 25%, and 30%, respectively. By comparing GW model, FIT model, and PBL model with SD model proposed in this paper, the data of precision, recall rate, accuracy rate, and F1 are compared and analyzed under the condition of changing the three dimensions of capital investment, experience, and education level, so as to select the best optimization model of innovation and entrepreneurship system for computational intelligence college students. Experiments show that when the capital investment increases by 10%, the relevant data of SD model is the best, with accuracy of 0.8761, recall rate of 0.9563, accuracy rate of 0.8972, and F1 of 0.8773; When the experience is increased by 10%, the optimization efficiency of SD model is the best, with its accuracy of 0.8660, recall rate of 0.9462, accuracy rate of 0.8871, and F1 of 0.8672. When the education level is increased by 10%, the optimization efficiency of SD model is the best, with accuracy of 0.8921, recall rate of 0.9762, accuracy rate of 0.8762, and F1 of 0.8861.
An Efficient Design of Adaptive Model Predictive Controller for Load Frequency Control in Hybrid Power System
Authors: Gulzar Muhammad Majid , Sibtain Daud , Ahmad Arslan , Javed Imran , Murawwat Sadia , Rasool Imran , Hayat Aamir
Published: April 2022

The technology has proceeded so much that the power system should be substantial and explicit to give optimal results. Ever-increasing complexities of the power system and load disparity cause frequency fluctuations leading to efficiency degradation of the power system. In order to give a suitable real power output, the system entails an extremely perceptive control technique. Consequently, an advanced control method, that is, an adaptive model predictive controller (AMPC), is suggested for load frequency control (LFC) of the series power system which comprises photovoltaic (PV), wind, and thermal power. The suggested method is considered to enhance the power system execution as well as to decrease the oscillations due to a discrepancy in the system parameters and load disturbance under a multi-area power system network. The AMPC design verifies the constant frequency by maintaining a minimum steady state error under varying load conditions. The proposed control approach pledge that the steady-state error of frequencies and interchange of tie line powers is maintained in a given tolerance constraint. The effectiveness of the proposed controller is scrutinized by conventional controllers like genetic algorithm-tuned PI (GA-PI), firefly algorithm-tuned PI (FA-PI), and model predictive controller (MPC) to show the competence of the proposed method.
The Molecular Mechanism of Retina Light Injury Focusing on Damage from Short Wavelength Light
Authors: Fan Bin , Zhang ChunXia , Chi Jing , Liang Yang , Bao XiaoLi , Cong YunYi , Yu Bo , Li Xun , Li Guang-Yu
Published: April 2022

Natural visible light is an electromagnetic wave composed of a spectrum of monochromatic wavelengths, each with a characteristic color. Photons are the basic units of light, and their wavelength correlates to the energy of light; short-wavelength photons carry high energy. The retina is a fragile neuronal tissue that senses light and generates visual signals conducted to the brain. However, excessive and intensive light exposure will cause retinal light damage. Within the visible spectrum, short-wavelength light, such as blue light, carries higher energy, and thus the retinal injury, is more significant when exposed to these wavelengths. The damage mechanism triggered by different short-wavelength light varies due to photons carrying different energy and being absorbed by different photosensitive molecules in the retinal neurons. However, photooxidation might be a common molecular step to initiate cell death. Herein, we summarize the historical understanding of light, the key molecular steps related to retinal light injury, and the death pathways of photoreceptors to further decipher the molecular mechanism of retinal light injury and explore potential neuroprotective strategies.
Examining the Association of Food Insecurity and Being Up-to-Date for Breast and Colorectal Cancer Screenings
Authors: Mendoza Jason A. , Miller Carrie A. , Martin Kelly J. , Resnicow Ken , Iachan Ronaldo , Faseru Babalola , McDaniels-Davidson Corinne , Deng Yangyang , Martinez Maria Elena , Demark-Wahnefried Wendy , Leader Amy E. , Lazovich DeAnn , Jensen Jakob D. , Briant Katherine J. , Fuemmeler Bernard F.
Published: April 2022

Background:

Food insecurity (FI) has been associated with poor access to health care. It is unclear whether this association is beyond that predicted by income, education, and health insurance. FI may serve as a target for intervention given the many programs designed to ameliorate FI. We examined the association of FI with being up-to-date to colorectal cancer and breast cancer screening guidelines.

Methods:

Nine NCI-designated cancer centers surveyed adults in their catchment areas using demographic items and a two-item FI questionnaire. For the colorectal cancer screening sample (n = 4,816), adults ages 50–75 years who reported having a stool test in the past year or a colonoscopy in the past 10 years were considered up-to-date. For the breast cancer screening sample (n = 2,449), female participants ages 50–74 years who reported having a mammogram in the past 2 years were up-to-date. We used logistic regression to examine the association between colorectal cancer or breast cancer screening status and FI, adjusting for race/ethnicity, income, education, health insurance, and other sociodemographic covariates.

Results:

The prevalence of FI was 18.2% and 21.6% among colorectal cancer and breast cancer screening participants, respectively. For screenings, 25.6% of colorectal cancer and 34.1% of breast cancer participants were not up-to-date. In two separate adjusted models, FI was significantly associated with lower odds of being up-to-date with colorectal cancer screening [OR, 0.7; 95% confidence interval (CI), 0.5–0.99)] and breast cancer screening (OR, 0.6; 95% CI, 0.4–0.96).

Conclusions:

FI was inversely associated with being up-to-date for colorectal cancer and breast cancer screening.

Impact:

Future studies should combine FI and cancer screening interventions to improve screening rates.
The Landscape of Immune Microenvironments in Racially Diverse Breast Cancer Patients
Authors: Hamilton Alina M. , Hurson Amber N. , Olsson Linnea T. , Walens Andrea , Nsonwu-Farley Joseph , Kirk Erin L. , Abdou Yara , Downs-Canner Stephanie M. , Serody Jonathan S. , Perou Charles M. , Calhoun Benjamin C. , Troester Melissa A. , Hoadley Katherine A.
Published: April 2022

Background:

Immunotherapy is a rapidly evolving treatment option in breast cancer; However, the breast cancer immune microenvironment is understudied in Black and younger (<50 years) patients.

Methods:

We used histologic and RNA-based immunoprofiling methods to characterize the breast cancer immune landscape in 1,952 tumors from the Carolina Breast Cancer Study (CBCS), a population-based study that oversampled Black (n = 1,030) and young women (n = 1,039). We evaluated immune response leveraging markers for 10 immune cell populations, compared profiles to those in The Cancer Genome Atlas (TCGA) Project [n = 1,095 tumors, Black (n = 183), and young women (n = 295)], and evaluated in association with clinical and demographic variables, including recurrence.

Results:

Consensus clustering identified three immune clusters in CBCS (adaptive-enriched, innate-enriched, or immune-quiet) that varied in frequency by race, age, tumor grade and subtype; however, only two clusters were identified in TCGA, which were predominantly comprised of adaptive-enriched and innate-enriched tumors. In CBCS, the strongest adaptive immune response was observed for basal-like, HER2-positive (HER2+), triple-negative breast cancer (TNBC), and high-grade tumors. Younger patients had higher proportions of adaptive-enriched tumors, particularly among estrogen receptor (ER)-negative (ER−) cases. Black patients had higher frequencies of both adaptive-enriched and innate-enriched tumors. Immune clusters were associated with recurrence among ER− tumors, with adaptive-enriched showing the best and innate-enriched showing the poorest 5-year recurrence-free survival.

Conclusions:

These data suggest that immune microenvironments are intricately related to race, age, tumor subtype, and grade.

Impact:

Given higher mortality among Black and young women, more defined immune classification using cell-type–specific panels could help explain higher recurrence and ultimately lead to targetable interventions.
Occupational Exposure to Polycyclic Aromatic Hydrocarbons and Lung Cancer Risk: Results from a Pooled Analysis of Case–Control Studies (SYNERGY)
Authors: Olsson Ann , Guha Neela , Bouaoun Liacine , Kromhout Hans , Peters Susan , Siemiatycki Jack , Ho Vikki , Gustavsson Per , Boffetta Paolo , Vermeulen Roel , Behrens Thomas , Brüning Thomas , Kendzia Benjamin , Guénel Pascal , Luce Danièle , Karrasch Stefan , Wichmann Heinz-Erich , Consonni Dario , Landi Maria Teresa , Caporaso Neil E. , Merletti Franco , Mirabelli Dario , Richiardi Lorenzo , Jöckel Karl-Heinz , Ahrens Wolfgang , Pohlabeln Hermann , Tardón Adonina , Zaridze David , Field John K. , Lissowska Jolanta , Świątkowska Beata , McLaughlin John R. , Demers Paul A. , Bencko Vladimir , Foretova Lenka , Janout Vladimir , Pándics Tamás , Fabianova Eleonora , Mates Dana , Forastiere Francesco , Bueno-de-Mesquita Bas , Schüz Joachim , Straif Kurt
Published: April 2022

Background:

Exposure to polycyclic aromatic hydrocarbons (PAH) occurs widely in occupational settings. We investigated the association between occupational exposure to PAH and lung cancer risk and joint effects with smoking within the SYNERGY project.

Methods:

We pooled 14 case–control studies with information on lifetime occupational and smoking histories conducted between 1985 and 2010 in Europe and Canada. Exposure to benzo[a]pyrene (BaP) was used as a proxy of PAH and estimated from a quantitative general population job-exposure matrix. Multivariable unconditional logistic regression models, adjusted for smoking and exposure to other occupational lung carcinogens, estimated ORs, and 95% confidence intervals (CI).

Results:

We included 16,901 lung cancer cases and 20,965 frequency-matched controls. Adjusted OR for PAH exposure (ever) was 1.08 (CI, 1.02–1.15) in men and 1.20 (CI, 1.04–1.38) in women. When stratified by smoking status and histologic subtype, the OR for cumulative exposure ≥0.24 BaP μg/m3-years in men was higher in never smokers overall [1.31 (CI, 0.98–1.75)], for small cell [2.53 (CI, 1.28–4.99)] and squamous cell cancers [1.33 (CI, 0.80–2.21)]. Joint effects between PAH and smoking were observed. Restricting analysis to the most recent studies showed no increased risk.

Conclusions:

Elevated lung cancer risk associated with PAH exposure was observed in both sexes, particularly for small cell and squamous cell cancers, after accounting for cigarette smoking and exposure to other occupational lung carcinogens.

Impact:

The lack of association between PAH and lung cancer in more recent studies merits further research under today's exposure conditions and worker protection measures.
FDA Approval Summary: Decitabine and Cedazuridine Tablets for Myelodysplastic Syndromes
Authors: Kim Nina , Norsworthy Kelly J. , Subramaniam Sriram , Chen Haiyan , Manning Michael L. , Kitabi Eliford , Earp Justin , Ehrlich Lori A. , Okusanya Olanrewaju O. , Vallejo Jonathon , Gehrke Brenda J. , de Claro R. Angelo , Pazdur Richard
Published: April 2022

On July 7, 2020, the Food and Drug Administration approved Inqovi (Otsuka Pharmaceutical Co.), an oral fixed-dose combination tablet comprising 35 mg decitabine, a hypomethylating agent, and 100 mg cedazuridine, a cytidine deaminase inhibitor (abbreviated DEC-C) for treatment of adult patients with myelodysplastic syndromes (MDS). Evidence of effectiveness of DEC-C was established in phase III ASTX727-02 (N = 133) in adults with MDS. The study involved a two-sequence crossover comparing DEC-C and intravenous (IV) decitabine 20 mg/m2 once daily for the first 5 days of each 28-day cycle in the first 2 cycles. From cycle 3 onward, patients received DEC-C. Five-day cumulative area under the curve (5-d AUC) of decitabine for DEC-C was similar to that of IV decitabine, with geometric mean ratio 0.99 (90% confidence interval: 0.93–1.06). Clinical benefit was supported by study ASTX727-02 and the similarly designed phase II study ASTX727-01-B (n = 80), with complete remission (CR) of 21% and 18% and median duration of CR 7.5 and 8.7 months, respectively. Adverse reactions were consistent with IV decitabine. Postmarketing assessments were issued to address the effect of cedazuridine on QT prolongation, food effect, moderate and severe hepatic impairment, and severe renal impairment on the pharmacokinetics and safety of DEC-C.
A Ménage à Trois of Cytotoxic Effector Cells: γδ T Cells Suppress NK Cells but Not CTLs
Authors: Kabelitz Dieter
Published: April 2022

Three types of cytotoxic effector cells can kill tumor cells: innate natural killer (NK) cells, CD8+ CTL, and γδ T cells. In this issue, Walwyn-Brown and colleagues report new insights into the interplay between these three cell types that are integral to antitumor immunity, finding that γδ T cells can specifically suppress NK cells but not CD8+ CTLs. These results are relevant in view of the so far limited efficacy of γδ T-cell immunotherapy.

See related article by Walwyn-Brown et al., p. 558 (3).
Regression of Bilateral Peripapillary Choroidal Neovascularization Associated with Idiopathic Intracranial Hypertension after Systemic Acetazolamide Treatment
Authors: Trivizki Omer , Wang Liang , Iyer Prashanth , Shi Yingying , Rosenfeld Philip J. , Rabinovitch David , Townsend Justin
Published: April 2022

A rare occurrence of bilateral peripapillary choroidal neovascularization (CNV) in an 18-year-old idiopathic intracranial hypertension (IIH) patient regressed with systemic acetazolamide treatment alone. Multimodal imaging was done, including OCT angiography (OCTA), which showed CNV. No injections were given even though she had macular fluid in her left eye. Nonetheless, the subretinal fluid resolved, and visual acuity improved. This report shows that CNV secondary to IIH can be managed with systemic therapy alone. Moreover, we showed for the first time the ability to diagnose IIH-associated CNV using OCTA.