bluuebunny/crossref_metadata_2025 huggingface dataset:
Nuclear Capsid Uncoating and Reverse Transcription of HIV-1
Authors: Müller Thorsten G. , Zila Vojtech , Müller Barbara , Kräusslich Hans-Georg
Published: June 2022

After cell entry, human immunodeficiency virus type 1 (HIV-1) replication involves reverse transcription of the RNA genome, nuclear import of the subviral complex without nuclear envelope breakdown, and integration of the viral complementary DNA into the host genome. Here, we discuss recent evidence indicating that completion of reverse transcription and viral genome uncoating occur in the nucleus rather than in the cytoplasm, as previously thought, and suggest a testable model for nuclear import and uncoating. Multiple recent studies indicated that the cone-shaped capsid, which encases the genome and replication proteins, not only serves as a reaction container for reverse transcription and as a shield from innate immune sensors but also may constitute the elusive HIV-1 nuclear import factor. Rupture of the capsid may be triggered in the nucleus by completion of reverse transcription, by yet-unknown nuclear factors, or by physical damage, and it appears to occur in close temporal and spatial association with the integration process.
Muscular contraction’s therapeutic potential for cancer-induced wasting
Authors: Hardee Justin P. , Carson James A.
Published: June 2022

Skeletal muscle atrophy and dysfunction contribute to morbidity and mortality in patients with cancer. Cachexia pathophysiology is highly complex, given that perturbations to the systemic cancer environment and the interaction with diverse tissues can contribute to wasting processes. Systemic interleukin 6 (IL-6) and glycoprotein 130 (gp130) receptors signaling have established roles in some types of cancer-induced muscle wasting through disruptions to protein turnover and oxidative capacity. Although exercise has documented benefits for cancer prevention and patient survival, there are significant gaps in our understanding of muscle adaptation and plasticity during severe cachexia. Preclinical models have provided valuable insight into the adaptive potential of muscle contraction within the cancer environment. We summarize the current understanding of how resistance-type exercise impacts mechanisms involved in cancer-induced muscle atrophy and dysfunction. Specifically, the role of IL-6 and gp130 receptors in the pathophysiology of muscle wasting and the adaptive response to exercise is explained. The discussion includes current knowledge gaps and future research directions needed to improve preclinical research and accelerate clinical translation in human patients with cancer.
The microRNA-29 family: role in metabolism and metabolic disease
Authors: Dalgaard Louise T. , Sørensen Anja E. , Hardikar Anandwardhan A. , Joglekar Mugdha V.
Published: June 2022

The microRNA-29 family members miR-29a-3p, miR-29b-3p, and miR-29c-3p are ubiquitously expressed and consistently increased in various tissues and cell types in conditions of metabolic disease, obesity, insulin resistance, and type 2 diabetes. In pancreatic β cells, miR-29a is required for normal exocytosis, but increased levels are associated with impaired β-cell function. Similarly, in liver, miR-29 species are higher in models of insulin resistance and type 2 diabetes, and either knock-out or depletion using a microRNA inhibitor improves hepatic insulin resistance. In skeletal muscle, miR-29 family upregulation is associated with insulin resistance and altered substrate oxidation, and similarly, in adipocytes, overexpression of miR-29a leads to insulin resistance. Blocking miR-29a using nucleic acid antisense therapeutics show promising results in preclinical animal models of obesity and type 2 diabetes, although the widespread expression pattern of miR-29 family members complicates the exploration of single target tissues. However, in fibrotic diseases, such as in late complications of diabetes and metabolic disease (diabetic kidney disease, nonalcoholic steatohepatitis), miR-29 species expression is suppressed by TGF-β allowing increased extracellular matrix collagen to form. In the clinical setting, circulating levels of miR-29a and miR-29b are consistently increased in type 2 diabetes and in gestational diabetes and are also possible prognostic markers for deterioration of glucose tolerance. In conclusion, miR-29 family miRNAs play an essential role in various organs relevant to intermediary metabolism and its upregulation contributes to impaired glucose metabolism, whereas it suppresses fibrosis development. Thus, a correct balance of levels of miR-29 family miRNA seems important for cellular and organ homeostasis in metabolism.
Stress alters the transcriptional activity of Leydig cells dependently on the diurnal time
Authors: Medar Marija Lj , Andric Silvana A. , Kostic Tatjana S.
Published: June 2022

The increasing amount of data points to the circadian timing system as an essential part of processes regulating androgen homeostasis. However, the relationship between stress response, timekeeping-, and steroidogenesis-related systems is unexplored. Here, the stress-response of the testosterone-producing rat Leydig cells depending on the time of stressful events was studied. The study analyzes the effects of 3-h immobilization (IMO) applied at different periods during the day. The IMO performed once [1 time immobilization stress (1×IMO)] or repeated in 10 consecutive days [10 time repeated immobilization stress (10×IMO)]. Both types of IMO increased corticosterone and decreased testosterone blood level. However, the effect of 10×IMO occurring in the active phase on blood testosterone was less pronounced. This is related to different sensitivity to IMO-events depending on the diurnal time. Most steroidogenesis-related genes [gene encoding luteinizing hormone/choriogonadotropin receptor ( Lhcgr), gene encoding cytochrome P450, family 11, subfamily a, polypeptide 1 ( Cyp11a1), gene encoding hydroxy-δ-5-steroid dehydrogenase, 3 β- and steroid δ-isomerase 1 ( Hsd3b1/2), and gene encoding cytochrome P450, family 17, subfamily a, polypeptide 1 ( Cyp17a1)] were downregulated in the inactive phase but unchanged or even upregulated in the active phase of the day. Both types of IMO stimulated the expression of clock elements gene encoding aryl hydrocarbon receptor nuclear translocator-like ( Bmal1)/aryl hydrocarbon receptor nuclear translocator-like (BMAL1), gene encoding period circadian regulator 1 ( Per1) /period circadian regulator 1 (PER1) regardless of the day’s stage and reduced gene encoding nuclear receptor subfamily 1, group D, member 1 ( Rev-erba) in the inactive phase. The principal component analysis (PCA) confirmed a major shift, for both IMO-types, in the transcription of the genes across the passive/active stage. Further, 10×IMO changed a diurnal pattern of the glucocorticoid receptor [gene encoding nuclear receptor subfamily 3, group C, member 1 ( Nr3c1)/nuclear receptor subfamily 3, group C, member 1 (GR)] expression, whereas the observed time-dependent IMO-response of the Leydig cells correlated with different corticosterone engagements. Altogether, the Leydig cell’s stress response depends on the daytime of the stressful event, emphasizing the importance of the circadian system in supporting androgen homeostasis and male fertility.
Human anterior insula signals salience and deviations from expectations via bursts of beta oscillations
Authors: Haufler Darrell , Liran Omer , Buchanan Robert J. , Pare Denis
Published: June 2022

Functional imaging studies indicate that the anterior insula encodes salience and deviations from expectations. Beyond changing BOLD signals, however, the physiological underpinnings of these signals are unknown. By recording local field potentials in patients with epilepsy, we found that the anterior insula generates large bursts of beta oscillations whose amplitude is modulated by the salience of outcomes and deviations from expectations. Moreover, insular beta bursts coincide with the activation of many high-order cortical areas.
The potassium channel auxiliary subunit Kvβ2 (Kcnab2) regulates Kv1 channels and dopamine neuron firing
Authors: Yee Joshua X. , Rastani Ariana , Soden Marta E.
Published: June 2022

Here, we utilize CRISPR/Cas9-mediated mutagenesis in dopamine neurons in mice to target the gene encoding Kvβ2, an auxiliary subunit that forms a part of Kv1 channel complexes. We find that the absence of Kvβ2 alters action potential properties by reducing surface expression of pore-forming subunits and shifting the voltage dependence of channel inactivation. This work establishes a new function for Kvβ2 subunits and Kv1 complexes in regulating dopamine neuron activity.
Dynamic Response Analysis of Pile Group Foundation of Super-Giant Sewage Treatment Structure on Hydraulic Fill Foundation
Authors: Huang Yi , Chen Xugang , Cheng Lijuan , Bai Tiyong , Yan Ru
Published: June 2022

In this study, a 3D numerical model, considering the dynamic interaction between soil, pile foundation, and super structure, and the parameter analysis of internal force response of pile group foundation under differences seismic intensity, was established based on the Bangladesh sewage treatment plant project to investigate the dynamic response of pile group foundation of liquid-containing structures. The results show that the internal force of pile gradually increases with time, and the horizontal dynamic displacement peak value appears earlier under different seismic wave responses and seismic intensity. With the increase of seismic time history, the variation degree of dynamic impedance with frequency and impedance peak will increase. The pile group effect and single pile bearing capacity of foundation in hydraulic fill fine sand and silty clay were verified. By comparing numerical simulation and theoretical calculation, the results show that the pile group foundation exerts the soil squeezing effect after pile construction is completed, and the dynamic elastic modulus of the soil layer can be increased. Simultaneously, the soil layer will have a better integral stiffness. The pile group effect coefficient obtained by the solid perimeter method is most consistent with the numerical simulation method.
Rab22a Promotes Epithelial‐Mesenchymal Transition in Papillary Thyroid Carcinoma by Activating PI3K/AKT/mTOR Signaling Pathway
Authors: Luo Xue , Wang Jinping , Lu Jinxi , Wang Xi , Miao Yuan , Li Qingchang , Li Xiaoman , Wang Liang
Published: June 2022

Background. Rab22a is a member of the RAS superfamily, involved in early endosome formation and intracellular vesicle transport. Rab22a is significantly upregulated in a variety of malignant tumors. However, its function in thyroid cancer has never been addressed. Methods. The expression of Rab22a in paraffin sections of 101 patients was detected by immunohistochemical staining. By upregulating and downregulating the expression of Rab22a in thyroid cancer cell lines, the effect of Rab22a on cell proliferation, invasion, and migration was analyzed. Co‐IP was employed, and the interaction between Rab22a and PI3Kp85α was shown. The function of Rab22a on PI3K/AKT/mTOR signaling and epithelial‐mesenchymal transition (EMT) was further studied by western blot analysis. Results. Immunostaining showed that Rab22a was significantly overexpressed in thyroid cancer tissues but negative in adjacent normal tissues or nodular goiters. The proliferation, migration, invasion, and EMT in papillary thyroid carcinoma cell lines were enhanced upon Rab22a overexpression but inhibited after knocking down Rab22a. The co‐IP assay demonstrated an interaction between Rab22a and PI3K85α, an effector of PI3K. We further found that Rab22a can activate the PI3K/AKT/mTOR signaling pathway. However, the ability of Rab22a to promote the proliferation, invasion, migration, and EMT of papillary thyroid carcinoma cells was significantly inhibited after being treated with LY294002, a PI3K inhibitor. Conclusions. Rab22a can promote the EMT process and enhance proliferation, migration, and invasion of papillary thyroid carcinoma cells by activating the PI3K/AKT/mTOR signaling pathway. Our study provides new pathological diagnosis clues and clinical treatment targets for thyroid cancer.
A Long-Term Shared Autonomous Vehicle System Design Problem considering Relocation and Pricing
Authors: Tian Jingjing , Jia Hongfei , Wang Guanfeng , Lin Yu , Wu Ruiyi , Lv Ao
Published: June 2022

Compared to conventional private vehicles (CPVs), shared autonomous vehicles (SAVs) provide users the potential for the reduced value of time (VoT), improved mobility experience, and less traffic congestion. In the presence of the SAV system, numerous studies have mainly concentrated on the strategic planning and operational decision problem separately while ignoring the complicated interaction between them and the distinct features of autonomous vehicles. It is imperative to determine the relocation and pricing strategies at the operational level. In this study, in terms of the pricing strategy, we formalize a logit model to capture the mode choice behavior in a multimodal network, where the reduced VoT is considered simultaneously. A time-space network is employed to capture the daily operation problem based on the elastic demand. The minimum customer service rate is regarded as a constraint to ensure the system’s reliability. Moreover, a mixed-integer nonlinear programming (MINLP) model is formulated to jointly determine the number of stations and parking spaces, fleet size, relocation, and pricing strategies to maximize the total profit. Then, we integrate the Particle Swarm Optimization (PSO) algorithm with the optimization solver Gurobi to address the complex problem. Numerical experiments and comparative analyses are conducted to demonstrate the feasibility and efficiency of the proposed model.
Cause Analysis of Coal Mine Gas Explosion Based on Bayesian Network
Authors: Li Lei , Fang Zihao
Published: June 2022

As one of the types of coal mine disasters and accidents, gas explosion is an important resistance affecting coal mine safety production. How to effectively identify gas explosion, find out the causes of gas explosion accidents, and make timely prediction and rectification is an urgent problem in coal mine industry. In this paper, the cause model of coal mine gas explosion is constructed based on the Bayesian network, and the cause chain of gas explosion accident is established by SPSS correlation analysis. The main factors leading to gas explosion accidents are found by parameter learning, reverse reasoning, sensitivity analysis, and key cause path. The results show that the main causes of mine gas explosion are gas accumulation and fire source explosion. The main causes of gas accumulation are no wind or breeze caused by local ventilator problems. The generation of electric spark is the main cause of fire source explosion. Cable damage, short circuit, mechanical and electrical equipment explosion, illegal operations, and lack of safety skills are also important factors leading to gas explosion.
A Novel Fast Iterative Learning Control for Linear Discrete Systems with Parametric Disturbance and Measurement Noise
Authors: Lei Tongfei , Riaz Saleem , Manzoor Nadir
Published: June 2022

Precise industrial control technology is constantly in need of accurate and strong control. Error convergence for a typical linear system is very minimal when using a conventional iterative learning control strategy. This study develops a quick iterative learning control law to address this issue. We have presented a new PD iterative learning control approach which is basically grounded on backward error and control parameter rectification for a class of linear discrete time-invariant (LDTI) systems. We have deliberated the repetitive system, which has constraint disturbance and measurement noise. First, we have developed a form of the faster learning law along with a full explanation of the algorithm’s control factor generation process. And then, using the vector method in conjunction with the theory of spectral radius, sufficient conditions for the algorithm’s convergence are introduced for parameter estimation with no noise, parameter uncertainty but excluding the noise, parameter uncertainty with small perturbations, and noise in four different scenarios. Eventually, results show that convergence depends on the control law’s learning factor, the correction term, the factor of association, and the learning interval. Ultimately, the simulation results indicate that suggested approach has a faster error convergence as compared with classical PD algorithm.
The Adaptation of Participation Scale Short Simplified Questionnaire into Indonesian Language and the Psychometric Properties in Individuals with Type 2 Diabetes Mellitus with Vestibular Dysfunction
Authors: Komalasari Dwi Rosella , Vongsirinavarat Mantana , Hiengkaew Vimonwan , Nualnim Nantinee
Published: June 2022

Background. Type 2 diabetes mellitus (T2DM) has been reported to affect the vestibular system resulting in dizziness and vertigo complaints. This complication is known to disable the social participation. The Participation Scale Short Simplified (PSSS) has been developed to quantify the severity of social participation restrictions. The aim of this study was to translate and cross-culturally adapt the PSSS into Indonesian Bahasa (PSSS-Ina). The measurement properties of the translated version and the factors contributing to the severe participation restriction were determined. Methods. The participants comprised 55 T2DM with vestibular dysfunction (VD) in the community center for diabetes mellitus in Central Java, Indonesia. The signs of VD were confirmed by head impulse test, Dix Hallpike Test, and supine roll test. The PSSS-Ina was administered twice with a four-week interval. The physical examination was also performed to identify the contributing factors. Results. The test–retest reliability of the PSSS Indonesian Bahasa version (PSSS-Ina) between two measurement sessions was excellent (ICC of 0.93,

p
<
0.001

, and 95% CI: 0.88–0.95). The correlation coefficient between two administrations was high (

r
=
0.88

). Based on the demonstrated content validity, the values of the corrected item and total correlation were greater than 0.3. No floor and ceiling effects were observed. The good internal consistency was confirmed with Cronbach’s alpha of 0.84. The factor analysis produced three factors of activity participation, social engagement, and work-related participation. The multiple logistic regression revealed that the balance performance of mCTSIB was the main factor contributing to the severe participation restriction reflected by the PSSS-Ina score. Conclusion. The Indonesian version of the PSSS-Ina demonstrated excellent comprehensibility and reliability in individuals suffering T2DM with VD. This tool is therefore helpful in identifying the participation limitation in individuals with VD.
Comparative Analysis and Evaluation of Bridge Construction Risk with Multiple Intelligent Algorithms
Authors: Wu Ying , Lu Pengzhen
Published: June 2022

Bridge collapse in the construction process is one of the most common bridge accidents; we can see the importance of construction to ensure bridge safety. Site construction safety management mainly relies on checklist evaluation, but the evaluation results are often affected by the ability and experience of the evaluator. Using an artificial intelligence algorithm to realize rapid and accurate risk assessment of the bridge construction process is an effective way and development direction to solve the above problems. In view of the uncertain factors in the process of bridge construction, this paper analyzes and classifies the man-made and environmental risk factors that affect the bridge construction stage by using the 4M1E analysis method. Typical artificial intelligence algorithms are used to construct risk assessment models for bridge construction. And the random forest algorithm is used to analyze and verify the construction example of the FIU bridge.
TET3 Mediates 5hmC Level and Promotes Tumorigenesis by Activating AMPK Pathway in Papillary Thyroid Cancer
Authors: Chi Jiadong , Zhang Wei , Li Yigong , Zhao Jie , Zheng Xiangqian , Gao Ming
Published: June 2022

Thyroid cancer is the most common endocrine malignant tumor. The accurate risk stratification and prognosis assessment is particularly important for patients with thyroid cancer, which can reduce the tumor recurrence rate, morbidity, and mortality effectively. DNA methylation is one of the most widely studied epigenetic modifications. Many studies have shown that 5hmC-mediated demethylation played an important role in tumors. The hydroxylation of 5mC is catalyzed by ten-eleven translocation dioxygenase (TET). In this study, we first found that the abnormal expression of 5hmC was closely related to microcarcinoma, multifocal, extraglandular invasion and lymph node metastasis of thyroid carcinoma. Then, we identified TET3 was differentially expressed in thyroid cancers and normal tissues from the TET family. TET3 can promote the proliferation, migration, and invasion of thyroid cancer. TET3-mediated 5hmC can regulate the transcription of AMPK pathway-related genes to activate the AMPK pathway and autophagy and therefore promote PTC proliferation. These findings provide a preclinical rationale for the design of novel therapeutic strategies for this target to improve the clinical outcome of patients with PTC.
Medical Intelligent System and Orthopedic Clinical Nursing Based on Graph Partition Sampling Algorithm
Authors: Heng Xiucheng , Chen Yufei , Liu Lihong
Published: June 2022

This study summarizes the process of graph partition sampling algorithm. Through studying, observing, and comparing many different types of graph partition sampling algorithms, this study represents the learning process sampling into three steps: sampling process, aggregation process, and the calculation process of loss function. The medical intelligence system developed in this study must provide remote audio and video connections between patients, nurses, and doctors, and requires hardware, software, and network collaboration. The hardware includes a server that keeps the medical intelligence system running. The software includes the operating system and server application software that provide the basic functions of the system. The network platform provides network bandwidth and basic configuration to achieve effective connections between different parts. At the same time, the system also defines audio and video encoding and decoding standards. Orthopedic patients are often accompanied by varying degrees of activity limitation and low self-care ability, the particularity of these patients puts forward higher requirements for orthopedic clinical care management. Orthopedic clinical nursing path is a standardized nursing management method supported by evidence-based medicine. In order to meet the requirements of the system design, the goal of the system design is to use the latest computing and network communication technology to organically “connect” the nursing staff, the nursing staff, and the hospital, so that the nursing staff can enjoy the personalized guidance specially made by the doctor at any time.
Evaluation of Deep Learning and Conventional Approaches for Image Recaptured Detection in Multimedia Forensics
Authors: Hussain Israr , Hussain Dostdar , Kohli Rashi , Ismail Muhammad , Hussain Saddam , Sajid Ullah Syed , Alroobaea Roobaea , Ali Wajid , Umar Fazlullah
Published: June 2022

Image recaptured from a high-resolution LED screen or a good quality printer is difficult to distinguish from its original counterpart. The forensic community paid less attention to this type of forgery than to other image alterations such as splicing, copy-move, removal, or image retouching. It is significant to develop secure and automatic techniques to distinguish real and recaptured images without prior knowledge. Image manipulation traces can be hidden using recaptured images. For this reason, being able to detect recapture images becomes a hot research topic for a forensic analyst. The attacker can recapture the manipulated images to fool image forensic system. As far as we know, there is no prior research that has examined the pros and cons of up-to-date image recaptured techniques. The main objective of this survey was to succinctly review the recent outcomes in the field of image recaptured detection and investigated the limitations in existing approaches and datasets. The outcome of this study provides several promising directions for further significant research on image recaptured detection. Finally, some of the challenges in the existing datasets and numerous promising directions on recaptured image detection are proposed to demonstrate how these difficulties might be carried into promising directions for future research. We also discussed the existing image recaptured datasets, their limitations, and dataset collection challenges.
SDN-Driven Internet of Health Things: A Novel Adaptive Switching Technique for Hospital Healthcare Monitoring System
Authors: Preveze Barbaros , Alkhayyat Ahmed , Abedi Firas , Jawad Aqeel Mahmood , Abosinnee Ali S.
Published: June 2022

In the last decent, the number of Internet of Things (IoT) health-based paradigm reached to a huge number of users, services, and applications across different disciplines. Thus, hundreds of wireless devices seem to be distrusted over a limited or small area. To provide a more efficient network, the software-defined network (SDN) thought to be a good candidate to deal with these huge number of wireless users. In this work, after a novel SDN algorithm is proposed for the hospital environment, it is also designed and integrated into an Internet of Health Things (IoHT) paradigm. The novel algorithm called adaptive switching (AS) is proposed as a novel adaptive access strategy based on adaptively hoping among existing Go-Back-N and Selective Repeat techniques. Finally, the throughput performance of the proposed AS method is compared with the performances of traditional Go-Back-N and Selective Repeat ARQ methods using the developed MATLAB simulation. For this, an optimal

P

error

rate that the network should prefer to switch either from Go-Back-N to Selective Repeat or from Selective Repeat to Go-Back-N method to maximize the network throughput performance is determined. The evaluated results are also confirmed by theoretical calculation results using well-known Mathis throughput formula. It is observed from the simulation results that the best throughput performance can be evaluated, when AS switches to Go-Back-N if the

P

error

is less than 3.5% and it switches back to Selective Repeat when the

P

error

is greater than 3.5%. By this way, it is also observed that the throughput always has its best possible results for all

P

error

rates and up to 37.52% throughput improvement is provided by the use of novel proposed adaptive switching (AS) algorithm.
Enhanced Lion Optimization with Efficient Path Routing Equalization Technique against DoS Attack in Wireless Sensor Network
Authors: Elavarasan R. , Chitra K. , Adigo Amsalu Gosu
Published: June 2022

In WSN, DoS (denial of service) attack makes shortcoming system. The packets travel over and over in the sensor network. By that, all the assets like data transmission, memory, and vitality are squandered by this attack. However, the attacker ought to optimize its attacker plan for request to boost the impact on the system performance because of the deficiency of vitality at the aggressor side. Denial of service (DoS) attack on the Internet has become a squeezing issue. By staying away from these sorts of attacks, network performance can be improved. Therefore, security is a fundamental requirement for these networks. Effective routing is necessary in order to overcome the issued faced by the crosslayer in the DOS attack of the WSN network for the purpose of good transmission. This research work mainly focuses on performance evaluation using optimization methods. To establish the efficient path in the crosslayer against DoS attack, this paper has proposed enhanced lion optimization with an efficient path routing equalization technique (LOEPRE). If any failure node occurs in the network, then the node is recognized and the transfer of the data packet is done to the other node. Retransmission of data causes overload in the network. The proposed model focuses on these issues and overcomes these issues by improving the path efficiently with robust security. It consists of three phases: the initial phase includes the route discovery in the network. In the second phase, the transfer of data is done in the high router path for security purposes. Finally, the efficient path routing equalization technique is used for minimizing the overload in the network; it provides the equalized path length in the network and is highly efficient. Hence, the proposed LOEPRE technique is used to achieve energy efficiency in wireless network for prolonged network lifetime and minimum packet latency and minimize consumption of energy. Moreover, the simulation outcome of the proposed LOEPRE method is highly robust while comparing to the existing methods EFCRS, SSPRA ELOER, EFLOR, and TSTP. It achieves better performance than existing algorithms in comparing metric connectivity ratio, end-to-end delay, overhead, throughput, and packet delivery ratio.
Current Progress on Neuroprotection Induced by Artemisia, Ginseng, Astragalus, and Ginkgo Traditional Chinese Medicines for the Therapy of Alzheimer’s Disease
Authors: Li Qin , Rubin Limor , Silva Marta , Li Shuai , Yang Chao , Lazarovici Philip , Zheng Wenhua
Published: June 2022

Aging is associated with the occurrence of diverse degenerative changes in various tissues and organs and with an increased incidence of neurological disorders, especially neurodegenerative diseases such as Alzheimer’s disease (AD). In recent years, the search for effective components derived from medicinal plants in delaying aging and preventing and treating neurodegenerative diseases has been increasing and the number of related publications shows a rising trend. Here, we present a concise, updated review on the preclinical and clinical research progress in the assessment of the therapeutic potential of different traditional Chinese medicines and derived active ingredients and their effect on the signaling pathways involved in AD neuroprotection. Recognized by their multitargeting ability, these natural compounds hold great potential in developing novel drugs for AD.
Diagnosis of Chronic Ischemic Heart Disease Using Machine Learning Techniques
Authors: Shehzadi Shumaila , Hassan Muhammad Abul , Rizwan Muhammad , Kryvinska Natalia , Vincent Karovič
Published: June 2022

Ischemic heart disease (IHD) causes discomfort or irritation in the chest. According to the World Health Organization, coronary heart disease is the major cause of mortality in Pakistan. Accurate model with the highest precision is necessary to avoid fatalities. Previously several models are tried with different attributes to enhance the detection accuracy but failed to do so. In this research study, an artificial approach to categorize the current stage of heart disease is carried out. Our model predicts a precise diagnosis of chronic diseases. The system is trained using a training dataset and then tested using a test dataset. Machine learning methods such as LR, NB, and RF are applied to forecast the development of a disease. Experimental outcomes of this research study have proven that our strategy has excelled other procedures with maximum accuracy of 99 percent for RF, 97 percent for NB, and 98 percent for LR. With such high accuracy, the number of deaths per year of ischemic heart disease will be slightly decreased.
Deep Learning-Based Crack Monitoring for Ultra-High Performance Concrete (UHPC)
Authors: Wu Dongling , Zhang Hongxiang , Yang Yiying
Published: June 2022

In civil engineering, image recognition technology in artificial intelligence is widely used in structural damage detection. Traditional crack monitoring based on concrete images uses image processing, which requires high image preprocessing techniques, and the results of detection are vulnerable to factors, such as lighting and noise. In this study, the full convolutional neural networks FCN-8s, FCN-16s, and FCN-32s are applied to monitoring of concrete apparent cracks and according to the image characteristics of concrete cracks and experimental results. The FCN-8s model was tested with a correct crack monitoring rate of 0.6721, while the new network model had a correct crack detection rate of 0.7585, a significant improvement in the correct crack detection rate.
Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney
Authors: Hong Ye , Que Yi , Hu Yang , Shi Bo-yun , Zhu Jia , Wang Juan , Huang Jun-ting , Sun Fei-fei , Zhang Lian , Zhou Xin-ke , Lu Su-ying , Zhang Yi-zhuo
Published: June 2022

Background. Immune-related long noncoding RNAs (IrlncRNAs) are recognized as important prognostic factors in a variety of cancers, but thus far, their prognostic value in pediatric rhabdoid tumor of the kidney (pRTK) has not been reported. Here, we clarified the associations between IrlncRNAs and overall survival (OS) of pRTK patients and constructed a model to predict their prognosis. Methods. We accessed RNA sequencing data and corresponding clinical data of pRTK from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. An expression profile of immune-related genes (Irgenes) and lncRNAs of pRTK was extracted from the RNA sequencing data. IrlncRNAs were defined by co-expression analysis of lncRNAs and Irgenes. The limma R package was used to identify differential expression IrlncRNAs. Univariate and multivariate Cox regression analyses were conducted to build a prognostic IrlncRNAs model. The performance of this prognostic model was validated by multimethods, like ROC curve analysis. Results. A total of 1097 IrlncRNAs were defined. Univariate Cox regression analysis identified 7 IrlncRNAs (AC004791.2, AP003068.23, RP11-54O7.14, RP11-680F8.1, TBC1D3P1-DHX40P1, TUNAR, and XXbac-BPG308K3.5) and were significantly associated with OS. Multivariate regression analysis constructed the best prognostic model based on the expression of AC004791.2, AP003068.23, RP11-54O7.14, TBC1D3P1-DHX40P1, and TUNAR. According to the prognostic model, a risk score of each patient was calculated, and patients were divided into high-risk and low-risk groups accordingly. The survival time of low-risk patients was significantly better than high-risk patients (

p
<
0.001

). Univariate (hazard ratio 1.098, 95% confidence interval 1.048–1.149,

p

value <0.001) and multivariate (hazard ratio 1.095, 95% confidence interval 1.043–1.150,

p

value <0.001) analyses confirmed that the prognostic model was reliable and independent in prediction of OS. Time-dependent ROC analysis showed that 1-year survival AUC of prognostic model, stage, age, and sex was 0.824, 0.673, 0.531, and 0.495, respectively, which suggested that the prognostic model was the best predictor of survival in pRTK patients. Conclusions. The prognostic model based on 5 IrlncRNAs was robust and could better predict the survival of pRTK than other clinical factors. Additionally, the mechanism of regulation and action of prognosis-associated lncRNAs could provide new avenues for basic research to explore the mechanism of tumor initiation and development in order to prevent and treat pRTK.
Expression and Regulatory Network Analysis of BICC1 for Aged Sca-1-Positive Bone Narrow Mesenchymal Stem Cells
Authors: Liu Zhongshuang , Ou Chuntao , Xiang Siyu , Xie Qi , Che Shuangjiang , Zhang Dandi , Meng Lingna , Liu Ziqi , Zhang Guohong , Wang Ying , Huang Yun , Zhang Wenjing , Deng Yongqiang
Published: June 2022

Background. The impaired osteoblastic differentiation of bone marrow mesenchymal stem cells (BMSCs) is a major cause of bone remodeling imbalance and osteoporosis. The bicaudal C homologue 1 (BICC1) gene is a genetic regulator of bone mineral density (BMD) and promotes osteoblast differentiation. The purpose of this study is to explore the probable function of BICC1 in osteoporosis and osteogenic differentiation of aged BMSCs. Methods. We examined the GSE116925 microarray dataset obtained from the Gene Expression Omnibus (GEO) database. The GEO2R algorithm identified differentially expressed genes (DEGs) in Sca-1+ BMSCs from young (3 months old) and old (18 months old) mice. Then, to identify the most crucial genes, we used pathway enrichment analysis and a protein-protein interaction (PPI) network. Furthermore, starBase v2.0 was used to generate the regulatory networks between BICC1 and related competing endogenous RNAs (ceRNAs). NetworkAnalyst was used to construct TF-gene networks and TF-miRNA-gene networks of BICC1 and ceRNA. Furthermore, we investigated the Bicc1 expression in aged Sca-1-positive BMSCs. Result. We detected 923 DEGs and discovered that epidermal growth factor receptor (EGFR) was the top hub gene with a high degree of linkage. According to the findings of the PPI module analysis, EGFR was mostly engaged in cytokine signaling in immune system and inflammation-related signaling pathways. 282 ceRNAs were found to interact with the BICC1 gene. EGFR was not only identified as a hub gene but also as a BICC1-related ceRNA. Then, we predicted 11 common TF-genes and 7 miRNAs between BICC1 and EGFR. Finally, we found that BICC1 mRNA and EGFR mRNA were significantly overexpressed in aged Sca-1-positive BMSCs. Conclusion. As a genetic gene that affects bone mineral density, BICC1 may be a new target for clinical treatment of senile osteoporosis by influencing osteogenic differentiation of BMSCs through EGFR-related signaling. However, the application of the results requires support from more experimental data.
Hybrid Approach for Shelf Monitoring and Planogram Compliance (Hyb-SMPC) in Retails Using Deep Learning and Computer Vision
Authors: Saqlain Mehwish , Rubab Saddaf , Khan Malik M. , Ali Nouman , Ali Shahzeb
Published: June 2022

In retail management, the continuous monitoring of shelves to keep track of the availability of the products and following proper layout are the two important factors that boost the sales and improve customer’s level of satisfaction. The studies conducted earlier were either performing shelf monitoring or verifying planogram compliance. As both the activities are important, to tackle this problem, we presented a deep learning and computer vision-based hybrid approach called Hyb-SMPC that deals with both activities. The Hyb-SMPC approach consists of two modules: The first module detects fine-grained retail products using one-stage deep learning detector. For the detection part, the comparison of three deep learning-based detectors, You Only Look Once (YOLO V4), YOLO V5, and You Only Learn One Representation (YOLOR), is provided and the one giving the best result will be selected. The selected detector will perform detection of different categories of SKUs and racks. The second module performs planogram compliance; for this purpose, the company-provided layout is first converted to JavaScript Object Notation (JSON) and then the matching is performed with the postprocessed retail images. The compliance reports will be generated at the end for indicating the level of compliance. The approach is tested in both quantitative and qualitative manners. The quantitative analysis demonstrates that the proposed approach achieved an accuracy up to 99% on the provided dataset of retail, whereas the qualitative evaluation indicates increase in sales and customers’ satisfaction level.
Cluster-Based Authentication Process in a Smart City
Authors: Islam Md. Rafiqul , Adnan Md. Nasim , Islam Md. Ezazul , Ali A B M Shawkat
Published: June 2022

The widespread deployment of the Internet of Things in any smart city provides a regular flow of huge amount of data in server(s) that poses challenges for effective and efficient management to improve the quality of citizens’ life. To maintain the privacy and security of these data, a proper and secured identification and authentication process is very essential. In this paper, we propose a cluster-based identification and authentication process for the users, edge servers, and service servers, which are engaged in storing, processing, and accessing data. The proposed identification and authentication process is secured due to some codes (values), which are not possible to compute except by the concerned entities. For the proposed trust evaluation method (which actually strengthens the proposed authentication process), we consider major components and their integration in the model very carefully so that the simulation results become credible. Hence, we hope that the simulation results will be useful for the readership. As a whole, the proposed approach has potentials of being implemented in real-time applications.
Energy Saving via a Minimal Structure
Authors: Almarri B. , Azzam A. A.
Published: June 2022

Not only mathematical statistics, differential equations, and mathematical models were used to analyze and reduce data, but a rough set model is also employed in medical, engineering, and other fields to analyze and reduce them. The goal of this paper is to introduce a minimal structure concept to produce new rough set models and show that it is suitable for analyzing most real-life problems, reduction of attributes, and decision making. We examine the effectiveness of the following method in the problem of electric power generators and decision making. We also offer a comparison of our method and Pawlak’s method. Finally, the variable precision model improves the accuracy of decision making.
Multiscale-Band K-Distribution Model for Molecules in High-Temperature Gases
Authors: Shi Lei , Zhang Yuyue , Li Fangyan , Du Yuefan , Yao Bo
Published: June 2022

Radiation heat transfer plays a dominant role in high-temperature flow field. Rapid and reliable calculation of spectral radiation properties is beneficial for thermal analysis and detection of radiation target. In this paper, a multiscale-band k-distribution model is proposed for the study of radiation properties in high-temperature gases. The accurate absorption coefficients are firstly calculated using the line-by-line model. The slope of the accurate absorption coefficient line and its slope threshold are then extracted and analyzed, which act as a basis to divide the absorption coefficient line into multiple segments. For different segments, different bandwidths are chosen for the corresponding band k-distribution model. In the model, the 7-point Gauss–Lobatto method is employed to obtain the optimized absorption coefficients. These optimized absorption coefficients formed the absorption coefficient database. The radiation intensities of gases are finally calculated and analyzed based on the optimized database. Experimental results suggest that the multiscale-band k-distribution model can improve the efficiency up to 35% compared with the widely used narrow-band k-distribution model. Simultaneously, the relative calculation error is less than 5% compared with the most accurate line-by-line model.
Mechanism of a Herbal Formula Associated with Prognosis and Immune Infiltration in LIHC: Transcriptomics Analysis and Molecular Dynamics Simulations
Authors: Xu Jiankun , Liu Defu , Liu Zhanhua , Yang Jing , Chen Hanrui
Published: June 2022

Background. The aim of this study is to explore the interactions between effective monomers of herbal formulas and their therapeutic targets using systems biology approaches which may be a promising approach to unraveling their underlying mechanisms. Shentao Ruangan decoction (STRGD), which has been experimentally, clinically demonstrated to be effective in treating liver hepatocellular carcinoma (LIHC), was selected. Methods. Bioactive ingredients and drug targets of STRGD were retrieved from the traditional Chinese medicine systems pharmacology database and analysis platform and BATMAN-TCM databases. LIHC-related differentially expressed genes (DEGs) and key modules were identified by a weighted gene coexpression network analysis using The Cancer Genome Atlas data. The Kaplan–Meier analysis was used to investigate the relationship between STRGD tumor targets and patients survival. The CIBERSORT deconvolution algorithm was used to analyze the correlation between STRGD tumor targets and infiltrating immune cells. Enrichment analysis was used to analyze biological functions. Interactions between STRGD compounds and LIHC-immune-related genes were investigated using molecular docking and MDS. Results. We identified 24 STRGD tumor targets, which were found to be correlated with survival and the level of immune cell infiltration in LIHC patients. Immune infiltration, gene set enrichment, and Kyoto Encyclopedia of Genes and Genomes analyses highlighted the roles of T and B cell subsets, which were both related to activator protein 1 (AP1), in STRGD action. Docking studies and HPLC indicated that tanshinone IIA is the main compound of STRGD in LIHC treatment, and MDS showed that the potential LIHC-immune-related targets 1FOS and 1JUN firmly bind to tanshinone IIA. Conclusions. The mechanisms of STRGD in improving the immune and survival status of LIHC patients include interactions between STRGD compounds and LIHC-immune-related targets. The findings of this study can guide research studies on the potential usefulness of tanshinone IIA in the development of drugs targeting 1JUN and 1FOS for the treatment of LIHC.
Comparative Evaluation of Azadirachta indica (Neem) Chip and Soft Tissue Diode Lasers as a Supplement to Phase I Periodontal Therapy in Localized Chronic Moderate Periodontitis: A Randomized Controlled Clinical Trial
Authors: Ganvir Minal N. , Parwani Simran R. , Chaudhary Dhanashree S. , Parwani Rajkumar , Dadlani Himanshu , Vikey Ashok K. , Kawadkar Kshipra P. , Jaju Nishita S. , Armogida Niccoló Giuseppe , Spagnuolo Gianrico
Published: June 2022

Introduction. The current trial aimed to assess and compare the efficacy of neem chip and diode laser as a local drug delivery (LDD) agent as a supplement to phase I periodontal therapy in treatment of localized chronic moderate periodontitis. Materials and Methodology. Fourteen systemically healthy participants with 4–6 mm deep periodontal pockets at least in three quadrants (with no alveolar bony defect amenable to respective or regenerative osseous surgery, as seen in orthopantomograph) were selected for the trial. One week after phase I therapy, 10% absorbable chip of neem (commercially prepared by staff of a pharmacy college, Sheriguda, India) was placed in the periodontal pocket on one site, and soft tissue diode laser pocket sterilization was performed on the other site of the arch. Remaining one site was considered as a control. Parameters recorded clinically were plaque index (PI), papillary bleeding index (PBI), probing pocket depth (PPD), and relative attachment level (RAL) measured at baseline, 21st day, and one month postoperatively. Results. Statistically significant improvements were observed in all clinical parameters at one month as compared to baseline for both treatment groups. Conclusion. Neem chip supplemented with phase I therapy showed best improvement in clinical parameters followed by laser supplemented with phase I therapy in comparison to phase I therapy alone at one month follow-up. Clinical Significance. Neem chips are nature’s products, affordable without side effects, with a potential to be used as a local drug delivery agent in treating moderate chronic periodontitis.