bluuebunny/crossref_metadata_2025 huggingface dataset:
Computation-Based Discovery of Potential Targets for Rheumatoid Arthritis and Related Molecular Screening and Mechanism Analysis of Traditional Chinese Medicine
Authors: Sun Jijia , Liu Baocheng , Wang Ruirui , Yuan Ying , Wang Jianying , Zhang Lei
Published: June 2022

This study is aimed at screening potential therapeutic ingredients in traditional Chinese medicine (TCM) and identifying the key rheumatoid arthritis (RA) targets using computational simulations. Data for TCM-active ingredients with clear pharmacological effects were collected. Absorption, distribution, metabolism, excretion, and toxicity were evaluated. Potential RA targets were identified using the Gene Expression Omnibus (GEO) database, protein–protein interaction network, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and potential TCM ingredients using AutoDock Vina. To examine the mechanisms underlying small molecules, target prediction, Gene Ontology, KEGG, and network modeling analyses were conducted; the effects were verified in rat synovial cells using cell proliferation assay. The activities of tumor necrosis factor TNF-α and IL-1β and alterations in cellular target protein levels were detected by ELISA and Western blotting, respectively. In total, data for 432 TCM active ingredients with clear pharmacological effects were obtained. Five critical RA-related genes were identified; CCL5 and CXCL10 were selected for molecular docking. Target prediction and network-based proximity analysis showed that dioscin could modulate 22 known RA clinical targets. Dioscin, asiaticoside, and ginsenoside Re could effectively inhibit in vitro cell proliferation and secretion of TNF-α and IL-1β in RA rat synovial cells. Using bioinformatics and computer-aided drug design, the potential small anti-RA molecules and their mechanisms of action were comprehensively identified. Dioscin could significantly inhibit proliferation and induce apoptosis in RA rat synovial cells by reducing TNF-α and IL-1β secretion and inhibiting abnormal CCL5, CXCL10, CXCR2, and IL2 expression.
Research on Action Recognition Based on Deep Learning with Long Short-Term Memory Network and Attention Mechanism
Authors: Feng Wei , Feng Yanshun
Published: June 2022

Action recognition is a basic and challenging task in the field of computer vision. In this paper, a deep learning action recognition method based on attention mechanism is proposed and successfully applied to several public data sets, with outstanding performance. Firstly, the video frames are sampled based on the improved sampling algorithm, and the video data enhancement algorithm is proposed to preprocess the original data, which will reduce the overfitting probability of the recognition model and reduce the white noise of the data. Then, feature selection is carried out through attention-based residual network. Finally, we completed the action classification by LSTM model and softmax. In addition, a series of ablation experiments were designed to verify the validity of the proposed model. The results indicate that compared with the traditional action recognition model, the proposed method can effectively extract key features, reduce the overfitting caused by a small number of samples, reduce the interference of redundant information through the screening of low-information video frames, and complete the action recognition accurately, quickly, and efficiently.
Pose Estimation-Assisted Dance Tracking System Based on Convolutional Neural Network
Authors: Mu Jin
Published: June 2022

In the field of music-driven, computer-assisted dance movement generation, traditional music movement adaptations and statistical mapping models have the following problems: Firstly, the dance sequences generated by the model are not powerful enough to fit the music itself. Secondly, the integrity of the dance movements produced is not sufficient. Thirdly, it is necessary to improve the suppleness and rationality of long-term dance sequences. Fourthly, traditional models cannot produce new dance movements. How to create smooth and complete dance gesture sequences after music is a problem that needs to be investigated in this paper. To address these problems, we design a deep learning dance generation algorithm to extract the association between sound and movement characteristics. During the feature extraction phase, rhythmic features extracted from music and audio beat features are used as musical features, and coordinates of the main points of human bones extracted from dance videos are used for training as movement characteristics. During the model building phase, the model’s generator module is used to achieve a basic mapping of music and dance movements and to generate gentle dance gestures. The identification module is used to achieve consistency between dance and music. The self-encoder module is used to make the audio function more representative. Experimental results on the DeepFashion dataset show that the generated model can synthesize the new view of the target person in any human posture of a given posture, complete the transformation of different postures of the same person, and retain the external features and clothing textures of the target person. Using a whole-to-detail generation strategy can improve the final video composition. For the problem of incoherent character movements in video synthesis, we propose to optimize the character movements by using a generative adversarial network, specifically by inserting generated motion compensation frames into the incoherent movement sequences to improve the smoothness of the synthesized video.
Evaluation of Vision Transformers for Traffic Sign Classification
Authors: Zheng Yuping , Jiang Weiwei
Published: June 2022

Traffic sign recognition is one of the most important tasks in autonomous driving. Camera-based computer vision techniques have been proposed for this task, and various convolutional neural network structures are used and validated with multiple open datasets. Recently, novel Transformer-based models have been proposed for various computer vision tasks and have achieved state-of-the-art performance, outperforming convolutional neural networks in several tasks. In this study, our goal is to investigate whether the success of Vision Transformers can be replicated within the traffic sign recognition area. Based on existing resources, we first extract and contribute three open traffic sign classification datasets. Based on these datasets, we experiment with seven convolutional neural networks and five Vision Transformers. We find that Transformers are not as competitive as convolutional neural networks for the traffic sign classification task. Specifically, there are performance gaps of up to 12.81%, 2.01%, and 4.37% existing for the German, Indian, and Chinese traffic sign datasets, respectively. Furthermore, we propose some suggestions to improve the performance of Transformers.
Design and Implementation of Online Meticulous Painting System Based on Mobile IoT Service
Authors: Xu Cui
Published: June 2022

Contemporary art is gradually diversifying, and the aesthetics of artists have changed and progressed together with the times. Some brush painters, while inheriting the essence of tradition, continue to summarize and search for a painting language in line with the atmosphere of the times, gradually shifting their perspective to a separate, tiny “corner” of life, recording the painter’s own subtle emotional fluctuations through such “tiny” scenes. The approach models services through a context-aware service model and establishes flexible driving relationships between IoT data and services through context and scenario concepts. Moreover, it reduces the amount of business data to be processed by the system through contextual events. The process of the approach for service development is described, and relevant context-aware service development tools are introduced. Finally, the feasibility of the approach proposed in this article is illustrated by a service development example. An event-triggered sensor node clustering algorithm based on beamforming data transmission technology is proposed, which can improve network energy efficiency and clustering success rate. Meanwhile, a clustering algorithm based on the energy consumption rate of sensor nodes is designed to optimize the task allocation and scheduling of mobile node access, reduce the node charging delay, and enable the sensor nodes in the network to get energy replenishment in a timely and reasonable manner according to their own energy consumption rate demand.
Path Planning of Energy Robot Based on Improved Ant Colony Algorithm
Authors: Zhu Bin , Zhang Jianrong , Li Jian , Chen Lei , Wu Jinping , Farisi Zeyad
Published: June 2022

In order to optimize robot road planning, automation will increase production efficiency and reduce production costs. An improved ant colony algorithm based on a two-dimensional flat path planning study divided the three-dimensional space into planes, rasterized each plane, and replaced the original shape by storing a pheromone at the intersection. The pheromone storage space along the route will be reduced, and a three-dimensional space route planning study will be gradually conducted. As complex 3D environments and landscape features change, obstacle avoidance strategies have increased, road heuristics have improved, and new heuristic features have emerged. The initial value of the road node pheromone increases the efficiency of early ant search because of the uneven distribution of starting point, target point location information, and forward direction. After each iteration, the stuck ants that did not reach the target point are discarded according to the high-quality ant renewal rules, the iteration threshold is set, and the pheromone fluctuation coefficient is adjusted as the algorithm tends to merge. Compared with the basic ant colony algorithm, the convergence iteration times of the improved ant colony algorithm in this paper are reduced by about 40%, and the optimal path length is shortened by about 10. The duration of the algorithm increases. In terms of algorithm performance, it takes some time to improve the ant colony algorithm. Because of the complexity of the algorithm, some search strategies are added to the algorithm. The contribution of this article is the basis for the mobile robot to walk accurately from the initial position to the working position and perform various tasks independently.
Industry Development Tendency and Innovation Strategy Preference of Five Typical Industries under the Background of Low‐Carbon Sustainable Development in China
Authors: Tu Yanhong , Zhang Leilei , Li Xue
Published: June 2022

This paper tries to investigate the future development tendency of five typical industries in China and find out whether there exists a different innovation strategy preference between Chinese firms of low‐ and high‐knowledge density industry in the background of low‐carbon sustainable development. First, this paper finds that the innovation driven‐based trend of industrial development is further accelerated in China. Firms in industries with high knowledge and technology density, such as specialized‐supplier, scale‐intensive, and science‐based industries, are more likely to choose exploratory innovation strategy than exploitative innovation strategy. Firms in industries with low knowledge and technology density like service‐ and supplier‐dominated industries are more likely to choose the exploitative innovation strategy. Second, results indicate that exploratory innovation can bring higher technological innovation performance than exploitative innovation. And the effect of the ambidextrous strategy is better than the single exploitative strategy in industries with high knowledge and technology density like specialized‐supplier, scale‐intensive, and science‐based industries. Third, this paper suggests that innovation strategy preference plays a mediating role between industry type and technology innovation and a moderating effect of knowledge management capacity between innovation strategy and firms’ technology innovation.
Research on Direct Braking Force Estimation and Control Strategy Using Tire Inverse Model
Authors: Zhou Zhiguo , Zhu Xiaoning
Published: June 2022

With the rapid development of computer control and vehicle intelligence technology, speed and safety of vehicles have been greatly improved, and the requirements for vehicle control performance are getting higher and higher. For the direct braking force control, in the process of deceleration, a fast braking response can be obtained, which improves the braking performance and vehicle safety. This paper concentrates on direct braking force estimation and control strategy using a tire inverse model based on the antilock braking system, and to solve the problem of the existing ABS system is mainly antilock braking function, no direct braking force control function. Taking magic formula model for reference inverse model, the critical parameters under different road surfaces are obtained according to experience data. Then, the desired slip ratio corresponding to braking force can be obtained via fast tire inverse model look-up table method. The tyre friction self-adjustment decision making is obtained using the tire inverse model method. A direct braking force antilock braking system (DBF-ABS) controller is built using the nonsingular fast terminal sliding mode method. The simulation results indicated that the control strategy has adaptability and stability to the change of road conditions.
An Animation Model Generation Method Based on Gaussian Mutation Genetic Algorithm to Optimize Neural Network
Authors: Liu Jing , Chen Qixing , Zhang Yihua , Tian Xiaoying
Published: June 2022

With the rapid development of computer graphics, 3D animation has been applied to all fields of people’s lives, especially in the industries of film and television works, games, and entertainment. The wide application of animation technology makes it difficult for general 3D animation effects to impress increasingly discerning audiences. Group animation, as a new focus, has received more and more attention and has become a hot issue in computer graphics. Traditional animation production mainly relies on manual drawing and key frame technologies. The limitations of these technologies make the production of group animation consume a lot of manpower, financial resources, and time, and cannot guarantee the intelligence of characters and the authenticity of group behavior. Therefore, in order to end the above issues, this paper proposes an animation model generation method based on Gaussian mutation genetic algorithm to optimize neural network, including obtaining animation scene data, according to the animation scene data, and extracting animation model elements. The elements are input into the model network, the target animation model is generated, and the target animation model is displayed. The method proposed in this paper improves the animation model generation method in the prior art to a certain extent. The proposed animation model is constructed only through fixed rules, and the composition rules of the model cannot be changed according to the historical data of the animation model construction and other factors. Technical issues that reduce the flexibility and accuracy of the animation model generation.
Adult-Onset Acute Disseminated Encephalomyelitis with Epstein-Barr Virus Infection
Authors: Murasawa Emika , Matsuda Masazumi , Ishiyama Koichi , Shinozaki Tetsugaku , Murata Toshiki , Hashimoto Manabu
Published: June 2022

We present the case of a 22-year-old man who was diagnosed with tonsillitis and treated with antibiotics. Although the symptoms subsided, 1 week later, he presented with weakness in the lower limbs and was hospitalized. The weakness in the lower limbs worsened; he developed difficulty speaking and was transferred to our hospital. Laboratory tests showed a white blood cell count of 10,600/μL (24% atypical lymphocytes). Positive results were obtained for immunoglobulin M (IgM) antibody against Epstein-Barr virus (EBV) viral capsid antigen. EBV-deoxyribonucleic acid quantification in blood yielded positive results. Magnetic resonance imaging (MRI) revealed a hyperintensity in the spinal cord at the Th11 level of the lower spine on T2-weighted imaging (T2WI). In addition, T2WI and fluid-attenuated inversion recovery imaging showed hyperintense lesions on the right cerebral peduncle, bilateral thalami, posterior leg of the left internal capsule, and right corona radiata. We diagnosed acute disseminated encephalomyelitis (ADEM) with EBV and initiated steroid pulse therapy. Symptoms, along with the lesions seen on MRI, subsequently ameliorated. This case suggests that ADEM can be difficult to diagnose, but careful diagnosis is crucial since appropriate treatment is necessary to improve the symptoms.
Effects of Calf Blood-Deproteinized Extract Ophthalmic Gel Combined with Sodium Hyaluronate Eye Drops on Conjunctival Hyperemia Score and Tear Film Stability in Patients with Dry Eye
Authors: Wang Hao , Zhou Dong , Sun Zhuo , Sun Shanshan , Deng Guohua
Published: June 2022

Objective. The aim of this paper is to research the impact of calf blood-deproteinized extract ophthalmic gel combined with sodium hyaluronate eye drops on conjunctival hyperemia score and tear film stability in patients having dry eye. Methods. 144 patients having dry eye disease who were hospitalized from July 2018 to July 2021 were chosen as the research targets, which were composed of the control group and research group on the basis of the sequences of hospitalization, and each has 72 cases. The sodium hyaluronate eye drops were gained in the control one. In accordance with the control one, the study ones were given the combined treatment with eye drops of sodium hyaluronate. Treatment of calf blood-deproteinized extract ophthalmic gel, the scores of conjunctival hyperemia, tear film stability, visual function, curative effect, and their adverse reactions were observed and made comparisons among the two groups. Results. After the treatments of 2 weeks and later 1 month, the numerical values of the conjunctival hyperemia were fewer in the categories which had been mentioned above, and in contrast with the control one (P < 0.05), the numerical values of the conjunctival hyperemia in the study one were distinctly fewer. The data of SIt, BUT, and the heights of the central tear river of the lower eyelid were higher than those before cure. In comparison with the control one, the FL of the study one was distinctly lower, and the heights of SIt, BUT, and the central tear river of the lower eyelid were obviously better than the control one (P < 0.05). After therapy, the visual contrast sensitivity of the patients in two categories at 6.4 c/d and 12c/d increased in comparison with those before treatment, and the visual contrast sensitivity of the study group at 6.4 c/d and 12c/d was apparently higher than the data of control one (P < 0.05); the effective rate of treatment in the study one was 97.22%, which had a higher situation than the control one, 88.89% (P < 0.05); the probability of occurrence of the negative events in the study one after treatment was 4.17%, which was distinctly below the control one, 15.28% (P < 0.05). Conclusion. In order for the treatments of patients having dry eye disease, the use of calf blood-deproteinized extract ophthalmic gel having the combinations with eye drops of sodium hyaluronate can enhance the extent of visual impairment and conjunctival hyperemia with effect and improve the stability of tear film, with significant safety and high efficiency.
Prediction of Labor Unemployment Based on Time Series Model and Neural Network Model
Authors: Liu Xitao , Li Lihui
Published: June 2022

With the advent of big data, statistical accounting based on artificial intelligence can realistically reflect the dynamics of labor force and market segmentation. Therefore, based on the combination of machine learning algorithm and traditional statistical data under big data, a prediction model of unemployment in labor force based on the combination of time series model and neural network model is built. According to the theoretical parameters, the algorithm of the two-weight neural network is proposed, and the unemployment rate in labor force is predicted according to the weight combination of the two. The outcomes show that the fitting effect based on the combined model is superior to that of the single model and the traditional BP neural network model; at the same time, the prediction results with total unemployment and unemployment rate as evaluation indexes are excellent. The model can offer new ideas for assisting to solve the unemployment of the labor force in China.
The Evaluation Value of CT in the Efficacy of Neoadjuvant Chemotherapy in Ovarian Cancer Patients
Authors: Mou Daying , Xie Shengyan , Li Pingyuan
Published: June 2022

Aim. To discuss the evaluation value of CT in the efficacy of neoadjuvant chemotherapy in patients with ovarian cancer. Methods. The clinical, pathological, and CT imaging information of 72 patients with ovarian cancer treated in our hospital from January 2018 to January 2022 were retrospectively analyzed. CT examination and pathological examination were compared to evaluate the efficacy of neoadjuvant chemotherapy. Results. Using the CRS grading system, 26 cases (36.11%) scored 1, 42 cases (58.33%) scored 2, and 4 cases (5.56%) scored 3. CRS grading system scores of 1, 2, 3, and 4–7 patients were compared, P > 0.05. The CT manifestations of lymphadenectasis, degree of peritoneal thickening, ascites, and maximum length diameter of the mass were compared between the patients before and after chemotherapy, P < 0.05. According to RECIST 1.1, there were 1 (1.39%) CR, 38 (52.78%) PR, 29 (40.28%) SD, and 4 (5.56%) PD. The comparison was done between RECIST 1.1 and CRS grading system, P > 0.05. Conclusion. CT could be used to evaluate the efficacy of neoadjuvant chemotherapy for ovarian cancer.
Blood Stasis Syndrome Accelerates the Growth and Metastasis of Breast Cancer by Promoting Hypoxia and Immunosuppressive Microenvironment in Mice
Authors: Jin Lu , Tang Biqiang , Liu Xia , Mao Weiye , Xia Linying , Du Yueguang , Ji Bing , Shou Qiyang , Fu Huiying
Published: June 2022

Blood stasis syndromes (BSSs) are closely related to the occurrence and development of tumors, although the mechanism is still unclear. This study was aimed at exploring the effect and mechanism underlying different BSSs on tumor growth and metastasis. We established four BSS mouse models bred with breast cancer: qi deficiency and blood stasis (QDBS), cold coagulation blood stasis (CCBS), heat toxin and blood stasis (HTBS), and qi stagnation and blood stasis (QSBS). The results showed that microcirculation in the lower limb, abdominal wall, and tumor in situ decreased by varying degrees in the BSS groups. In addition, BSS promoted tumor growth and lung metastasis. The ratio of regulatory T cells in the tumor microenvironment was downregulated. Moreover, hypoxia-inducible factor 1-α, Wnt1, β-catenin, vascular endothelial growth factor, and Cyclin D1 levels increased in the tumors of BSS mice. In conclusion, BSS not only promoted the formation of a hypoxic and immunosuppressive microenvironment but also promoted the neovascularization.
Study on the Mechanism of Diosgenin Targeting STAT3 to Inhibit Colon Cancer Proliferation and Migration
Authors: Lai Zonglang , Wang Huaibi , Tang Xiaohui , Zhang Liufan , Wang Tiantian , Cheng Jun
Published: June 2022

To elucidate regulatory effects and molecular mechanisms of diosgenin on colon cancer, this study administered diosgenin at concentrations of 10 (low), 50 (medium), and 100 μmol/L (high concentration group) at the cell level, respectively. EdU, colony formation, and Transwell assays were implemented to determine SW480 cellular proliferation and migration. Assays of flow cytometry and TUNEL were employed to estimate cell apoptosis. Additionally, nude mouse tumorigenesis assay was used to further verify the regulatory function of diosgenin on colon cancer. The target protein of diosgenin was predicted via molecular docking. The results showed that all three concentrations of diosgenin could reduce colon cancer cellular proliferation and migration, and after diosgenin treatment, colon cancer cellular apoptosis was markedly increased, and the 100 μmol/L diosgenin group produced the most satisfactory inhibition on colon cancer cell proliferation. Ki67 expression was markedly reduced whereas those of Bax and caspase3 were greatly increased after diosgenin treatment. The nude mouse tumorigenesis assay indicated that the parameters of tumorous volume and mass of diosgenin treatment group were greatly decreased as compared to control, and as the concentration of diosgenin increased, the inhibitory effect was more significant. Molecular docking indicated that STAT3 served as a target protein of diosgenin. Moreover, after diosgenin treatment on colon cancer cells, the STAT3 expression was markedly reduced. The STAT3 overexpression would counteract the inhibitory effect of 50 μmol/L diosgenin in both suppressing colon cancer cellular proliferation and migration and promoting apoptosis. Taken together, all our outcomes demonstrated the diosgenin effects in not only inhibiting colon cancer cellular proliferation and migration but also promoting cancerous cellular apoptosis. Diosgenin is a regulatory player in targeting and regulating STAT3.
The Descriptive Data Analysis for the Adoption of Community Cloud in Saudi HEI‐Based Factor Adoption
Authors: Aldahwan Nouf S. , Ramzan Muhammed S.
Published: June 2022

Due to its increased reliability, adaptability, scalability, availability, and processing capacity, cloud computing is rapidly becoming a popular trend around the world. One of the major issues with cloud computing is making informed decision about adoption of community cloud (CC) computing (ACCC). To date, there are various technology acceptance theories and models to validate perspective of ACCC at both organizational and individual levels. However, no experimental studies have been carried out to provide a comprehensive assessment of the factors of ACCC, specifically in the area of the Saudi Higher Education (HEI) Institution. Thus, this research was aimed at exploring the factors of ACCC and the relationship to the experiences of the employees. The analysis of the employee context was driven by the success factors of technological, organizational, environmental, human, security, and advantage contexts on community cloud computing adoption in HEI. The data collection was a questionnaire‐based survey based on 106 responses. We present findings based on descriptive analysis in identifying the significant component that contributed to the effective implementation of ACCC. Security concerns are a significant influencing element in the adoption of community cloud technology.
Prediction of Mg Alloy Corrosion Based on Machine Learning Models
Authors: Lu Zhenxin , Si Shujing , He Keying , Ren Yang , Li Shuo , Zhang Shuman , Fu Yi , Jia Qi , Jiang Heng Bo , Song Haiying , Hao Mailing
Published: June 2022

Magnesium alloy is a potential biodegradable metallic material characterized by bone-like elastic modulus, which has great application prospects in medical, automotive, and aerospace industries owing to its bone-like elastic modulus, biocompatibility, and lightweight properties. However, the rapid corrosion rates of magnesium alloys seriously limit their applications. This study collected magnesium alloys’ corrosion data and developed a model to predict the corrosion potential, based on the chemical composition of magnesium alloys. We compared four machine learning algorithms: random forest (RF), multiple linear regression (MLR), support vector machine regression (SVR), and extreme gradient boosting (XGBoost). The RF algorithm offered the most accurate predictions than the other three machine learning algorithms. The input effects on corrosion potential have been investigated. Moreover, we used feature creation (transforming chemical component characteristics into atomic and physical characteristics) so that the input characteristics were not limited to specific chemical compositions. From this result, the model’s application range was widened, and machine learning was used to verify the accuracy and feasibility of predicting corrosion of magnesium alloys.
Effectiveness of Comfort Nursing Combined with Continuous Nursing on Patients with Colorectal Cancer Chemotherapy
Authors: Miao Jing , Liu Mengting , Ma Jie , Wang Han
Published: June 2022

Purpose. To analyze the application effect of continuous nursing combined with comfort nursing on patients with colorectal cancer chemotherapy and its influence on sleep quality and immune function. Methods. The data of 96 patients with colorectal cancer in the Oncology Department of Peking Union Medical College Hospital from July 2018 to July 2020 were collected and randomized into the control group and study group according to the odd and even numbers, with 48 cases in each group. The control group received routine care during chemotherapy, and the study group implemented continuous care combined with comfort care. Results. After intervention, the results were in favor of the study group than the control group with higher compliance, higher level of various immune indicators, higher quality of life scores, and higher nursing satisfaction rate. In addition, the Generalized Anxiety Disorder (GAD-7) scores and the average Pittsburgh Sleep Quality Index (PSQI) score of the study group after intervention was drastically lower than the control groupP<0.001. Conclusion. The implementation of continuous care combined with comfort care for patients with colorectal cancer undergoing chemotherapy can effectively improve sleep quality and quality of life, relieve anxiety, and yield high patient compliance, which is worthy of clinical promotion.
On Properties of Length-Biased Exponential Model
Authors: Ben Ghorbal Anis
Published: June 2022

The type II half logistic length-biased exponential distribution, which extends the length-biased exponential model, is introduced and examined. This model's statistical features, such as moments, conditional moments, mean order statistics, and entropy, are derived. To estimate distribution parameters, statistical inference employs three estimation methods: maximum likelihood, Cramer–von Mises, and Anderson–Darling. To evaluate the performance of the aforementioned estimators, we run simulation experiments based on the graphical results. The TIIHLLBE model's adaptability has been demonstrated through applications to real-world datasets.
Altered Hsp90 function in cancer: A unique therapeutic opportunity
Authors: Bagatell Rochelle , Whitesell Luke
Published: June 2022

Molecular chaperones or so-called heat shock proteins serve as central integrators of protein homeostasis within cells. In performing this function, they guide the folding, intracellular disposition, and proteolytic turnover of many key regulators of cell growth, differentiation, and survival. Recent data show essential roles for the chaperones in facilitating malignant transformation at the molecular level and support the concept that their altered utilization during oncogenesis is critical to the development of human cancers. The field is evolving rapidly, but it has become apparent that chaperones can serve as biochemical buffers at the phenotypic level for the genetic instability that is characteristic of many human cancers. Chaperone proteins thus allow tumor cells to tolerate the mutation of multiple critical signaling molecules that would otherwise be lethal. Much of the recent progress in understanding the complex role of heat shock proteins in tumorigenesis has been made possible by the discovery of several natural product antitumor antibiotics that selectively inhibit the function of the chaperone Hsp90. These agents have been used as probes to define the biological functions of Hsp90 at the molecular level and to validate it as a novel target for anticancer drug action. One of these agents, 17-allylamino,17-demethoxygeldanamycin (NSC 330507) has begun phase II clinical trials, and several second-generation compounds are now in late preclinical development. The best way to use Hsp90 inhibitors as anticancer agents remains to be defined. Trials accomplished to date, however, serve as proof of principle that Hsp90 function can be modulated pharmacologically without undue toxicity in humans. Given the redundancy and complexity of the signaling pathway abnormalities present in most cancers, the ability of Hsp90 inhibitors to alter the activity of multiple aberrant signaling molecules instead of just one or two (as most current-generation molecular therapeutics have been designed to do) may prove of unique therapeutic benefit.
Biological evaluation of cryptophycin 52 fragment A analogues: Effect of the multidrug resistance ATP binding cassette transporters on antitumor activity
Authors: Al-awar Rima S. , Corbett Thomas H. , Ray James E. , Polin Lisa , Kennedy Joseph H. , Wagner Margaret M. , Williams Daniel C.
Published: June 2022

Cryptophycin 52 (LY355703) is a potent antiproliferative analogue of the marine natural product cryptophycin 1. It has been shown to have a broad range of antitumor activity against human tumor xenografts and murine tumors including tumors resistant to Taxol and Adriamycin. Its mechanism of action involves arresting cells in the G2-M phase of the cell cycle by binding to microtubules and suppressing their dynamics. This 16-membered depsipeptide can be divided into four major subunits or fragments (A–D). We reported previously on our synthetic efforts around fragment A and discovered that this region of the molecule was amenable to a structure-activity relationship study that resulted in highly active antiproliferative agents when evaluated in the CEM leukemia cell line. The synthetic analogues were designed to help improve the efficacy and aqueous solubility of the parent compound; therefore, many in this series contained ionizable functional groups such as an amino group, a hydroxy group, or a carboxylic acid. Although several of these analogues showed improvements in potency over cryptophycin 52 in drug-sensitive tumor xenograft models, many lost their activity against Adriamycin-resistant tumor lines. It was discovered on additional in vitro evaluation that these analogues became good substrates of the multidrug resistance transporter P-glycoprotein.
Secretory phospholipase A2 as a tumor-specific trigger for targeted delivery of a novel class of liposomal prodrug anticancer etherlipids
Authors: Jensen Simon S. , Andresen Thomas L. , Davidsen Jesper , Høyrup Pernille , Shnyder Steven D. , Bibby Michael C. , Gill Jason H. , Jørgensen Kent
Published: June 2022

The use of many common clinically relevant chemotherapeutics is often limited due to insufficient delivery to the tumor and dose-limiting systemic toxicities. Therefore, therapeutics that specifically target tumor cells and are nontoxic to normal cells are required. Here, we report the development of a novel class of liposomes composed of lipid prodrugs, which use the increased secretory phospholipase A2 type IIA (sPLA2) activity of the tumor microenvironment as a trigger for the release of anticancer etherlipids (AEL). Treatment of sPLA2-secreting tumor cells in vitro with liposomes consisting of proAELs resulted in growth inhibition comparable with addition of the AELs alone. Using a specific sPLA2 inhibitor, we showed the low cytotoxicity of the nonhydrolyzed proAEL liposomes and have proven the sPLA2 dependency of the activation of proAELs to cytotoxic AELs. In addition, we showed that our proAEL liposomes circumvent the inherent hemolytic toxicities associated with the use of etherlipids, thereby allowing i.v. administration of such therapeutics as nontoxic prodrug liposomes. Furthermore, using a sPLA2-secreting human colon cancer xenograft model, we showed that the proAEL liposomes are capable of inducing a tumor growth delay in vivo. Taken together, these data support the validity of this novel tumor-selective liposomal prodrug delivery strategy. This new approach also provides a promising system for tumor-selective delivery and release of conventional chemotherapeutics encapsulated in the sPLA2-degradable prodrug liposomes.
(−)-Gossypol acts directly on the mitochondria to overcome Bcl-2- and Bcl-XL-mediated apoptosis resistance
Authors: Oliver Christopher L. , Miranda Michelle B. , Shangary Sanjeev , Land Stephanie , Wang Shaomeng , Johnson Daniel E.
Published: June 2022

Aberrant overexpression of antiapoptotic members of the Bcl-2 protein family, including Bcl-2 and Bcl-XL, contributes to malignant transformation and subsequent resistance to traditional chemotherapeutics. Thus, these proteins represent attractive targets for novel anticancer agents. The small molecule, gossypol, was initially investigated as a contraceptive agent, but subsequently has been shown to possess anticancer properties in vitro and in vivo. Recently gossypol has been found to bind to Bcl-XL and, with less affinity, to Bcl-2. Here we investigate the ability of the (−) enantiomer of gossypol, (−)-gossypol, to overcome the apoptosis resistance conferred by Bcl-2 or Bcl-XL overexpression in Jurkat T leukemia cells. (−)-Gossypol potently induced cell death in Jurkat cells overexpressing Bcl-2 (IC50, 18.1 ± 2.6 μmol/L) or Bcl-XL (IC50, 22.9 ± 3.7 μmol/L). Vector-transfected control cells were also potently killed by (−)-gossypol (IC50, 7.0 ± 2.7 μmol/L). By contrast, the chemotherapy drug etoposide only induced efficient killing of vector-transfected cells (IC50, 9.6 ± 2.3μmol/L). Additionally, (−)-gossypol was more efficient than etoposide at inducing caspase-3 activation and phosphatidylserine externalization in the setting of Bcl-2 or Bcl-XL overexpression. (−)-Gossypol-induced apoptosis was associated with Bak activation and release of cytochrome c from mitochondria, suggesting a mitochondrial-mediated apoptotic mechanism. Moreover, (−)-gossypol treatment of isolated mitochondria purified from Bcl-2-overexpressing cells also resulted in cytochrome c release, indicating a possible direct action on Bcl-2 present in the mitochondrial outer membrane. Taken together, these results suggest that (−)-gossypol is a potent and novel therapeutic able to overcome apoptosis resistance by specifically targeting the activity of antiapoptotic Bcl-2 family members. (−)-Gossypol may be a promising new agent to treat malignancies that are resistant to conventional therapies.
A new class of peroxisome proliferator-activated receptor γ (PPARγ) agonists that inhibit growth of breast cancer cells: 1,1-Bis(3′-indolyl)-1-(p-substituted phenyl)methanes
Authors: Qin Chunhua , Morrow Derek , Stewart Jessica , Spencer Kyle , Porter Weston , Smith Roger , Phillips Timothy , Abdelrahim Maen , Samudio Ismael , Safe Stephen
Published: June 2022

1,1-Bis(3′-indolyl)-1-(p-trifluoromethylphenyl)methane (DIM-C-pPhCF3) and several p-substituted phenyl analogues have been investigated as a new class of peroxisome proliferator-activated receptor γ (PPARγ) agonists. Structure-activity studies in PPARγ-dependent transactivation assays in MCF-7 breast cancer cells show that 5–20 μm concentrations of compounds containing p-trifluoromethyl, t-butyl, cyano, dimethylamino, and phenyl groups were active, whereas p-methyl, hydrogen, methoxy, hydroxyl, or halogen groups were inactive as PPARγ agonists. Induction of PPARγ-dependent transactivation by 15-deoxy-Δ12,14-prostaglandin J2 (PGJ2) and DIM-C-pPhCF3 was inhibited in MCF-7 cells cotreated with the PPARγ-specific antagonist N-(4′-aminopyridyl)-2-chloro-5-nitrobenzamide. In mammalian two-hybrid assays, DIM-C-pPhCF3 and PGJ2 (5–20 μm) induced interactions of PPARγ with steroid receptor coactivator (SRC) 1, SRC2 (TIFII), and thyroid hormone receptor-associated protein 220 but not with SRC3 (AIB1). In contrast, DIM-C-pPhCF3, but not PGJ2, induced interactions of PPARγ with PPARγ coactivator-1. C-substituted diindolylmethanes inhibit carcinogen-induced rat mammary tumor growth, induce differentiation in 3T3-L1 preadipocytes, inhibit MCF-7 cell growth and G0/G1-S phase progression, induce apoptosis, and down-regulate cyclin D1 protein and estrogen receptor α in breast cancer cells. These compounds are a novel class of synthetic PPARγ agonists that induce responses in MCF-7 cells similar to those observed for PGJ2.
Acyclic retinoid activates retinoic acid receptor β and induces transcriptional activation of p21CIP1 in HepG2 human hepatoma cells
Authors: Suzui Masumi , Shimizu Masahito , Masuda Muneyuki , Lim Jin T. E. , Yoshimi Naoki , Weinstein I. Bernard
Published: June 2022

Acyclic retinoid (ACR), a novel synthetic retinoid, has recently been demonstrated by us to inhibit the in vitro growth of human hepatoma cells, and this effect was associated with decreased expression of cell cycle-related molecules. These results, taken together with previous in vitro and clinical studies with ACR, suggest that this agent may be useful in the chemoprevention and therapy of hepatoma and possibly other human malignancies. In the present study, we further examined the molecular effects of ACR on the HepG2 human hepatoma cell line, focusing on the expression of nuclear retinoid receptors and the cell cycle inhibitor protein p21CIP1. Reverse transcription-PCR assays and Western blot analyses indicated that these cells express retinoic acid receptors (RARs) α, β, and γ, retinoid X receptors (RXRs) α and β, and peroxisome proliferator-activated receptors (PPAR) γ mRNA. Treatment with ACR caused a rapid induction within 3 h of RARβ mRNA and the related protein, but there was no significant change in the levels of the mRNA or proteins for RARs α and γ, RXRs α and β, and PPARγ. There was also a rapid increase in p21CIP1 mRNA and protein in HepG2 cells treated with ACR, and this induction occurred via a p53-independent mechanism. In transient transfection reporter assays, we cotransfected the retinoic acid response element-chloramphenicol acetyltransferase (CAT) reporter gene into HepG2 cells together with a RARβ expression vector. RARβ expression markedly stimulated CAT activity (up to about 4-fold) after the addition of ACR. However, CAT activity in the presence of ACR was only about 2-fold higher than that in the absence of ACR, when cells were cotransfected with RARs α and γ or RXRα. These findings suggest that the growth inhibitory effects of ACR are mediated at least in part through RARβ and that both RARβ and p21CIP1 play critical roles in the molecular mechanisms of growth inhibition induced by ACR.
In vitroevaluation of dimethane sulfonate analogues with potential alkylating activity and selective renal cell carcinoma cytotoxicity
Authors: Mertins Susan D. , Myers Timothy G. , Holbeck Susan L. , Medina-Perez Wilma , Wang Elaine , Kohlhagen Glenda , Pommier Yves , Bates Susan E.
Published: June 2022

We identified five structurally related dimethane sulfonates with putative selective cytotoxicity in renal cancer cell lines. These compounds have a hydrophobic moiety linked to a predicted alkylating group. A COMPARE analysis with the National Cancer Institute Anticancer Drug Screen standard agent database found significant correlations between the IC50 of the test compounds and the IC50 of alkylating agents (e.g., r = 0.68, P < 0.00001 for chlorambucil). In this report, we examined whether these compounds had activities similar to those of conventional alkylating agents. In cytotoxicity studies, chlorambucil-resistant Walker rat carcinoma cells were 4- to 11-fold cross-resistant to the test compounds compared with 14-fold resistant to chlorambucil. To determine effects on cell cycle progression, renal cell carcinoma (RCC) line 109 was labeled with bromodeoxyuridine prior to drug treatment. Complete cell cycle arrest occurred in cells treated with an IC90 dose of NSC 268965. p53 protein levels increased as much as 5.7-fold in RCC line 109 and as much as 20.4-fold in breast cancer line MCF-7 following an 18-hour drug exposure. Finally, DNA-protein cross-links were found following a 6-hour pretreatment with all compounds. Thus, the dimethane sulfonate analogues have properties expected of some alkylating agents but, unlike conventional alkylating agents, appear to possess activity against RCC.
Structural and Functional Characteristics of Cerebral Arteries as an Explanation for Clinical Syndromes Limited to the Brain
Authors: Salehi Omran Setareh , Gutierrez Jose , Mohr Jay P. , Elkind Mitchell S.V.
Published: June 2022

Vascular disease affects many different arterial beds throughout the body. Yet the brain is susceptible to several vascular disorders that either are not found in other parts of the body or when found are much less likely to cause clinical syndromes in other organs. This specific vulnerability of the brain may be explained by structural and functional differences between the vessels of the brain and those of vessels in other parts of the body. In this review, we focus on how cerebrovascular anatomy and physiology may make the brain and its vessels more susceptible to unique vascular pathologies. To highlight these differences, we use our knowledge of five diseases and syndromes that most commonly manifest in the intracranial vasculature. For each, we identify characteristics of the intracranial arteries that make them susceptible to these diseases, while noting areas of uncertainty requiring further research.
Solution of load frequency control through jaya technique with unified power flow controller and redox flow battery
Authors: Panwar Avinash , Agarwal Vinesh , Sharma Gulshan , Akindeji Kayode Timothy , Krishnan Narayanan
Published: June 2022

This paper proposes the initial strategy of designing two degree of freedom proportional integral derivative (2DOF-PID) made load frequency control (LFC) action optimized using Jaya optimization algorithm for a hydro-hydro system. At first, the PID optimized through Jaya is used for hydro-dominated system, and the comparative analysis of all possible error definitions are carried out to show the benefits of selecting integral time absolute error (ITAE) for LFC. Then, 2DOF-PID is designed for the hydro governing system, and its performance is compared with other designs to show the efficacy of the present LFC about computed error values gain of the various models via graphical LFC. The results obtained through simulations are promising but oscillatory with greater settling time. Hence, the proposed controller is retuned by considering the unified power flow control (UPFC) in arrangement with the tie-line and redox flow battery (RFB) units in area-2, and it is further seen that the outcomes of the application show the prevalence of the proposed work.
Design of a compact and miniature band-pass filter for global positioning system applications
Authors: Kadiri Amal , Tajmouati Abdelali , Zbitou Jamal , Zahraoui Issam , Latrach Mohamed
Published: June 2022

In this paper, a novel compact band pass filter (BPF) is proposed for global positioning system (GPS) applications. The proposed filter which is based on a microstrip resonator is mounted on a low cost RO4000 substrate with a dielectric constant εr=3.5, a thickness h=1.542 mm, a loss tangent tan (δ)=0.0027. It has a bandwidth from 1.55 GHz to 1.72 GHz. This filter is optimized and validated by using two electromagnetic solvers. The area occupied by this BPF is 33.6×41.24 mm2. The final circuit is a low cost BPF and can be associated with passive and active circuits due to the miniature dimensions.