bluuebunny/crossref_metadata_2025 huggingface dataset:
NFATc1 signaling drives chronic ER stress responses to promote NAFLD progression
Authors: Latif Muhammad Umair , Schmidt Geske Elisabeth , Mercan Sercan , Rahman Raza , Gibhardt Christine Silvia , Stejerean-Todoran Ioana , Reutlinger Kristina , Hessmann Elisabeth , Singh Shiv K , Moeed Abdul , Rehman Abdul , Butt Umer Javed , Bohnenberger Hanibal , Stroebel Philipp , Bremer Sebastian Christopher , Neesse Albrecht , Bogeski Ivan , Ellenrieder Volker
Published: April 2022

Objectives

Non-alcoholic fatty liver disease (NAFLD) can persist in the stage of simple hepatic steatosis or progress to steatohepatitis (NASH) with an increased risk for cirrhosis and cancer. We examined the mechanisms controlling the progression to severe NASH in order to develop future treatment strategies for this disease.

Design

NFATc1 activation and regulation was examined in livers from patients with NAFLD, cultured and primary hepatocytes and in transgenic mice with differential hepatocyte-specific expression of the transcription factor (Alb-cre, NFATc1c.a. andNFATc1Δ/Δ). Animals were fed with high-fat western diet (WD) alone or in combination with tauroursodeoxycholic acid (TUDCA), a candidate drug for NAFLD treatment. NFATc1-dependent ER stress-responses, NLRP3 inflammasome activation and disease progression were assessed both in vitro and in vivo.

Results

NFATc1 expression was weak in healthy livers but strongly induced in advanced NAFLD stages, where it correlates with liver enzyme values as well as hepatic inflammation and fibrosis. Moreover, high-fat WD increased NFATc1 expression, nuclear localisation and activation to promote NAFLD progression, whereas hepatocyte-specific depletion of the transcription factor can prevent mice from disease acceleration. Mechanistically, NFATc1 drives liver cell damage and inflammation through ER stress sensing and activation of the PERK-CHOP unfolded protein response (UPR). Finally, NFATc1-induced disease progression towards NASH can be blocked by TUDCA administration.

Conclusion

NFATc1 stimulates NAFLD progression through chronic ER stress sensing and subsequent activation of terminal UPR signalling in hepatocytes. Interfering with ER stress-responses, for example, by TUDCA, protects fatty livers from progression towards manifest NASH.
Research in the USA on COVID-19’s long-term effects: measures needed to ensure black, indigenous and Latinx communities are not left behind
Authors: Medeiros Michelle , Edwards Hillary Anne , Baquet Claudia Rose
Published: April 2022

The SARS-CoV-2 (COVID-19) pandemic continues to expose underlying inequities in healthcare for black, indigenous and Latinx communities in the USA. The gaps in equitable care for communities of colour transcend the diagnosis, treatment and vaccinations related to COVID-19. We are experiencing a continued gap across racial and socioeconomic lines for those who suffer prolonged effects of COVID-19, also known as ‘Long COVID-19’. What we know about the treatment for Long COVID-19 so far is that it is complex, requires a multidisciplinary approach and there is still much research needed to fully understand the effects. In this paper, we discuss pragmatic considerations for including affected communities, relevant stakeholders, and leaders from communities of colour in the planning and implementation of Long COVID-19 research.
Hyper-dimensional Visualization of Cultural Heritage: A Novel Multi-analytical Approach on 3D Pomological Models in the Collection of the University of Milan
Authors: Grifoni Emanuela , Bonizzoni Letizia , Gargano Marco , Melada Jacopo , Ludwig Nicola , Bruni Silvia , Mignani Ilaria
Published: April 2022

Digital close-range photogrammetry allows us to acquire high-fidelity tridimensional models useful to document cultural heritage objects with an impressive level of detail. In addition, this technique carries a strong analytical potentiality, able to gain improved knowledge of cultural objects and their preservation conditions. This project is focused on a comprehensive diagnostic survey using 3D multispectral modeling, high-resolution digital radiography, pulsed thermography, XRF, FT-IR, and FORS spectroscopies to document and characterize from a conservative point of view the poly-material objects that belong to the “Garnier Valletti” pomological collection—a unique collection from both scientific and artistic points of view. The analytical integration of imaging techniques, 3D modeling, and spectroscopic techniques provides information from the surface, sub-surface, and innermost layers of the object, respectively, capturing both accurate morphometric, spectral, and compositional data. The article presents the results obtained on typical poly-material and multilayered objects of this collection for which the combination of the considered techniques provided important data to the technical knowledge of the realization highlighting a particular predictive ability from a conservative point of view.
A Study on Blockchain Architecture Design Decisions and Their Security Attacks and Threats
Authors: Ahmadjee Sabreen , Mera-Gómez Carlos , Bahsoon Rami , Kazman Rick
Published: April 2022

Blockchain is a disruptive technology intended to implement secure decentralised distributed systems, in which transactional data can be shared, stored, and verified by participants of the system without needing a central authentication/verification authority. Blockchain-based systems have several architectural components and variants, which architects can leverage to build secure software systems. However, there is a lack of studies to assist architects in making architecture design and configuration decisions for blockchain-based systems. This knowledge gap may increase the chance of making unsuitable design decisions and producing configurations prone to potential security risks. To address this limitation, we report our comprehensive systematic literature review to derive a taxonomy of commonly used architecture design decisions in blockchain-based systems. We map each of these decisions to potential security attacks and their posed threats. MITRE’s attack tactic categories and Microsoft STRIDE threat modeling are used to systematically classify threats and their associated attacks to identify potential attacks and threats in blockchain-based systems. Our mapping approach aims to guide architects to make justifiable design decisions that will result in more secure implementations.
Context-aware Emotion Detection from Low-resource Urdu Language Using Deep Neural Network
Authors: Bashir Muhammad Farrukh , Javed Abdul Rehman , Arshad Muhammad Umair , Gadekallu Thippa Reddy , Shahzad Waseem , Beg Mirza Omer
Published: April 2022

Emotion detection (ED) plays a vital role in determining individual interest in any field. Humans use gestures, facial expressions, and voice pitch and choose words to describe their emotions. Significant work has been done to detect emotions from the textual data in English, French, Chinese, and other high-resource languages. However, emotion classification has not been well studied in low-resource languages (i.e., Urdu) due to the lack of labeled corpora. This article presents a publicly available Urdu Nastalique Emotions Dataset (UNED) of sentences and paragraphs annotated with different emotions and proposes a deep learning (DL)-based technique for classifying emotions in theUNEDcorpus. Our annotatedUNEDcorpus has six emotions for both paragraphs and sentences. We perform extensive experimentation to evaluate the quality of the corpus and further classify it using machine learning and DL approaches. Experimental results show that the developed DL-based model performs better than generic machine learning approaches with an F1 score of 85% on the UNED sentence-based corpus and 50% on the UNED paragraph-based corpus.
Predicting a Person’s Next Activity Region with a Dynamic Region-Relation-Aware Graph Neural Network
Authors: Zhu Nengjun , Cao Jian , Lu Xinjiang , Liu Chuanren , Liu Hao , Li Yanyan , Luo Xiangfeng , Xiong Hui
Published: April 2022

The understanding of people’s inter-regional mobility behaviors, such as predicting the next activity region (AR) or uncovering the intentions for regional mobility, is of great value to public administration or business interests. While there are numerous studies on human mobility, these studies are mainly from a statistical view or study movement behaviors within a region. The work on individual-level inter-regional mobility behavior is limited. To this end, in this article, we propose
a dynamic region-relation-aware graph neural network (DRRGNN)
for exploring individual mobility behaviors over ARs. Specifically, we aim at developing models that can answer three questions: (1) Which regions are the ARs? (2) Which region will be the next AR, and (3) Why do people make this regional mobility? To achieve these tasks, we first propose a method to find out people’s ARs. Then, the designed model integrates a dynamic graph convolution network (DGCN) and a recurrent neural network (RNN) to depict the evolution of relations between ARs and mine the regional mobility patterns. In the learning process, the model further considers peoples’ profiles and visited point-of-interest (POIs). Finally, extensive experiments on two real-world datasets show that the proposed model can significantly improve accuracy for both the next AR prediction and mobility intention prediction.
Drop Maslow's Hammer or not
Authors: Huang Jun , Xing Cong-Cong , Gu Shuyang , Baker Erich
Published: April 2022

There is an old saying in America (a.k.a "Maslow's Hammer") "If all you have is a hammer, then every problem you see looks like a nail." While the techniques of machine learning (ML) has attained notable success in the artificial intelligence, and is becoming trendy in the area of resource management for D2D communications, we argue, in this article, that it may not be optimal to use the ML "hammer" to hit the D2D resource management "nail". We support this argument by (1) formulating a D2D resource management problem in terms of the energy efficiency, (2) presenting a ML algorithm to tackle the formulated problem together with testing results, (3) discussing the issues observed in the ML approach, and finally (4) abandoning the ML approach and developing traditional logic-based algorithms to solve the problem. Simulation results demonstrate that the solutions provided by the traditional techniques are effective and efficient.
Design and implementation of information extraction system for scientific literature using fine-tuned deep learning models
Authors: Won Kwanghee , Jang Youngsun , Choi Hyung-do , Shin Sung
Published: April 2022

This paper presents an overview of a quality scoring system that utilizes pre-trained deep neural network models. Two types of DL models, a classification and extractive question answering (EQA) models are used to implement components of the system. The abstracts of the scientific literature are classified into two groups, in-vivo and in-vitro, and a question and answering model architecture is constructed for extracting the following types of information (animal type, the number of animals, exposure dose, and signal frequency). The Bidirectional Encoder Representations of Transformers (BERT) model pre-trained with a large text corpus is used as our baseline model for classification and EQA tasks. The models are fine-tuned with 455 EMF-related research papers.

In our experiments, the fine-tuned model showed improved performance on EQA tasks for the four-categories of questions compared to the baseline, and it also showed improvements on similar questions that were not used in training. This suggests the importance of retraining of deep learning model specifically in some areas requiring domain expertise such as scientific papers. However, additional research is needed on some implementation issues, in such cases where there are still multiple answers, or where there is no answer given in a context.
Kinetic Proofreading
Authors: Boeger Hinrich
Published: April 2022

Biochemistry and molecular biology rely on the recognition of structural complementarity between molecules. Molecular interactions must be both quickly reversible, i.e., tenuous, and specific. How the cell reconciles these conflicting demands is the subject of this article. The problem and its theoretical solution are discussed within the wider theoretical context of the thermodynamics of stochastic processes (stochastic thermodynamics). The solution—an irreversible reaction cycle that decreases internal error at the expense of entropy export into the environment—is shown to be widely employed by biological processes that transmit genetic and regulatory information.
Controversy on Positive Peritoneal Cytology of Endometrial Carcinoma
Authors: Liu Yi-Si , Wang Hui-Min , Gao Yan
Published: April 2022

Endometrial carcinoma (EC) is one of the most common gynecological malignancies. Its incidence rate has been increasing year by year. The prognostic factors and treatment strategies of EC have aroused wide concern. The effects of peritoneal cytology on the prognosis and treatment of EC remain controversial. Some factors, such as differentiation degree, muscle invasion, and tumor size, are related to positive peritoneal cytology. Hysteroscopy is commonly used in the diagnosis and treatment of endometrial cancer, but hysteroscopic surgery may cause the tumor to spread into the abdominal cavity, resulting in positive peritoneal cytology. In this review, we discuss the factors related to positive peritoneal cytology and the influence of positive peritoneal cytology on the prognosis of endometrial cancer. Suspicious positive peritoneal cytology may be an independent risk factor for endometrial cancer. The positive rate of peritoneal tumor cells in type II endometrial cancer is higher than other cells and is an independent risk factor for type II endometrial cancer. We also discuss the effects of peritoneal cytology on treatment decisions. Aggressive treatments seem to be more beneficial for patients with positive ascites cytology, but there is a lack of large-scale prospective clinical studies on their effectiveness and safety. The application of peritoneal cytology for endometrial cancer has been decreased in recent years. We believe that peritoneal cytology is necessary for this type of cancer. However, more studies on peritoneal cytology in endometrial cancer should be carried out.
Bidirectional Mendelian Randomization Analysis for Vitamin D and Thyroid Peroxidase Antibody
Authors: Chen Yingchao , Han Bing , Zhu Chunfang , Li Qin , Chen Chi , Zhai Hualing , Wang Ningjian , Chen Yi , Lu Yingli
Published: April 2022

Purpose. Whether Vitamin D deficiency or insufficiency is associated with thyroid autoimmunity was debated for long time. This study was still to explore the causal relationship of 25 (OH) D with a thyroid peroxidase antibody (TPOAb). Methods. The data were obtained from a cross-sectional study, SPECT-China study, which was performed in 23 sites in East China during 2014 to 2016. 10636 participants were finally included in this study. Genotyped four 25 (OH) D-related and four TPOAb-associated single nucleotide polymorphisms (SNPs) created their genetic risk scores (GRS). Bidirectional mendelian randomization (MR) analysis was used in this study. Results. 25 (OH) D GRS was significantly associated with 25 (OH) D (B −0.093, 95% CI −0.111, −0.074) and TPOAb level (B 0.067, 95% CI 0.002 to 0.132). TPOAb GRS was significantly associated with TPOAb concentration (B 0.345, 95% CI 0.135 to 0.556), but not 25 (OH) D (B −0.030, 95% CI −0.091 to 0.030). Using 25 (OH) D_GRS as instrumental variable in the MR analysis, a causal relationship of genetically determined 25 (OH) D with increased TPOAb concentration (B −0.720, 95% CI −1.429 to −0.012). No relation was found between genetically instrumented TPOAb and 25 (OH) D. Conclusion. A higher VD_GRS was associated with higher risk of increased TPOAb concentration, which supports a causal association between decreased vitamin D and increased concentration of TPOAb in an eastern Chinese population.
Risk-Based Dynamic Identity Authentication Method Based on the UCON Model
Authors: Liu Jing , Liu Rongchao , Lai Yingxu
Published: April 2022

With the continuous progress of computer technology, static identity authentication technology has encountered challenges in practical applications; in addition, it has deficiencies in continuity and mutability. For these reasons, we propose a risk-based dynamic identity authentication method based on the Usage Control (UCON) model. When authenticating a user, we consider their access rights based on the degree of risk, except in case of password authentication. We propose a risk assessment method, and blockchain technology is used in the scheme to provide a reliable process for risk assessment and authorization. Our scheme represents an improvement in traditional identity authentication, resulting in higher continuity and mutability. We also prove that the scheme has high security and scalability.
Perceived Caregiver Strain, 3- and 18-Month Poststroke, in a Cohort of Caregivers from the Life after Stroke Trial (LAST)
Authors: Langhammer Birgitta , Ihle Hansen Hege , Indredavik Bent , Askim Torunn
Published: April 2022

Aim. To gain more knowledge of caregiver strain in the Life After Stroke Trial (LAST) population. Methods. This is a substudy of the LAST study, including all caregivers’ reports of perceived Caregiver Strain Index (CSI) at inclusion and 18-month follow-up irrespective of group allocation. The checklist “STROBE Statement—Checklist of items that should be included in reports of cohort studies” was used. Caregivers to adults (age ≥18 years), here defined as the person living with, a patient with a first-ever or recurrent stroke, community dwelling, with modified Rankin Scale (mRS) <5 and no serious comorbidities, was invited to fill out the Caregiver Strain Index at three months (10–16 weeks) poststroke. Domains indicating differences of change in perceived strain in the total sample were analyzed in a linear regression analysis. Results. Caregiver strain (n = 147) varying from 5% to 27% was reported by the caregivers at baseline and between 2% to18% at 18-month follow-up. The items indicating the highest level of strain at baseline and 18 months were as follows: “Care giving is confining,” “There have been changes in personal plans,” “There have been emotional adjustments,” and “I feel completely overwhelmed.” The samples were divided into age groups 0–79 years and 80–100 years, indicating a higher strain on the caregiver for persons 80–100 years at 18 months. Conclusion. Caregiver strain was relatively low both at baseline and at 18-month follow-up. Main caregiver strains were reported in terms of a sense of confinement, a tendency of emotional strain, and the altering of plans at both time points. Depression was one of the main explanatory factors for the perceived caregiver strain. The perception of caregiver strain was higher in age groups 80–100 years than age groups 0–79 years.
Substance Misuse Decreases Heart Rate Variability
Authors: Lu Ming-Kuei , Chou Li-Wei , Chang Kang-Ming , Lee Hsin-Yi , Kang Hui-Jen
Published: April 2022

There are few biomarkers to reflect the physiological conditions for substance misuse. In this study, autonomic nervous and cardiovascular parameters were measured for participants in deferred prosecution programs. The goal of this study is to develop significant biomarkers of the above subjects and enhance their motivation to join further substance misuse disorder treatment program. This study recruited 34 participants with a mean age of 35.1 years. The participants spent approximately five minutes filling in the basic information form and another five minutes filling in the Pittsburgh Sleep Quality Index (PSQI). Blood pressure, heart rate, and heart rate variability data were also measured. Their sleep quality was measured by the Pittsburgh Sleep Quality Inventory (PSQI) with an average score of 8.6 and average systolic and diastolic pressure measured of 116.1 (

standard
 
deviation
 

SD

=
13.7

) and 77.9 mmHg (

SD
=
8.1

) during resting, respectively. Average heartbeat rates are 90.4 beats per minute (

SD
=
17.0

); and average low-frequency power ratio is 56.4% (

SD
=
19.8

%). Of the participants, 35% exhibited a low-frequency power rate below 30% and above 70%. The average biological HRV age of the participants was 46.0 years (

SD
=
22.9

), which was significantly older than their average actual age (

p
=

0.002

∗

∗

). The biological HRV age of the participants is 10 years older than their own actual age, and it effectively reflects the physiological conditions of participants in deferred prosecution programs. These physiological parameters, especially the biological HRV age, can be used in future treatment for substance use disorder counseling programs to increase the illness insight of program participants and increase their motivation to join further substance misuse disorder treatment program.
Optimization of Traffic Congestion Management in Smart Cities under Bidirectional Long and Short-Term Memory Model
Authors: Zhai Yujia , Wan Yan , Wang Xiaoxiao
Published: April 2022

To solve the increasingly serious traffic congestion and reduce traffic pressure, the bidirectional long and short-term memory (BiLSTM) algorithm is adopted to the traffic flow prediction. Firstly, a BiLSTM-based urban road short-term traffic state algorithm network is established based on the collected road traffic flow data, and then the internal memory unit structure of the network is optimized. After training and optimization, it becomes a high-quality prediction model. Then, the experimental simulation verification and prediction performance evaluation are performed. Finally, the data predicted by the BiLSTM algorithm model are compared with the actual data and the data predicted by the long short-term memory (LSTM) algorithm model. Simulation comparison shows that the prediction results of LSTM and BiLSTM are consistent with the actual traffic flow trend, but the data of LSTM deviate greatly from the real situation, and the error is more serious during peak periods. BiLSTM is in good agreement with the real situation during the stationary period and the low peak period, and it is slightly different from the real situation during the peak period, but it can still be used as a reference. In general, the prediction accuracy of the BiLSTM algorithm for traffic flow is relatively high. The comparison of evaluation indicators shows that the coefficient of determination value of BiLSTM is 0.795746 greater than that of LSTM (0.778742), indicating that BiLSTM shows a higher degree of fitting than the LSTM algorithm, that is, the prediction of BiLSTM is more accurate. The mean absolute percentage error (MAPE) value of BiLSTM is 9.718624%, which is less than 9.722147% of LSTM, indicating that the trend predicted by the BiLSTM is more consistent with the actual trend than that of LSTM. The mean absolute error (MAE) value of BiLSTM (105.087415) is smaller than that of LSTM (106.156847), indicating that its actual prediction error is smaller than LSTM. Generally speaking, BiLSTM shows advantages in traffic flow prediction over LSTM. Results of this study play a reliable reference role in the dynamic control, monitoring, and guidance of urban traffic, and congestion management.
Mechanism of the Treatment of Irritable Bowel Syndrome with Sini Powder and Tong Xie Yao Fang Decoction Based on Network Pharmacology
Authors: Tang Rong , Peng Xiaoqing , Zhou Xiaohong , Zheng Zhimin , Yin Jiayu , Liu Hong
Published: April 2022

This study used a network pharmacology approach to investigate the potential active ingredients of Sini Powder and Tong xie yao fang decoction and the underlying mechanisms in irritable bowel syndrome (IBS) treatment. The potential active ingredients of Sini Powder and Tong xie yao fang decoction were obtained from TCMSP databases, and the potential targets of the active ingredients were predicted and analyzed by using the Swiss Target Prediction database. T Genecard, DisGeNET, and OMIM databases were processed to screen the potential therapeutic targets in IBS. The interaction of overlapped candidates between the potential biotarget of herb extracts and the potential therapeutic target of IBS were analyzed by STRING website and visualized by the Cytoscape V3.8.0 software. Gene ontology (GO) analysis and Kyoto Genomics and Genomics Encyclopedia (KEGG) pathway were processed to categorize and map the potential biofunctions and effects of these candidates by using David database. Result. There were 139 predicted active components and 248 related biotargets of Sini Powder and Tong xie yao fang decoction which were involved in IBS treatment, and 522 annotations and 101 related pathways are obtained by enrichment analysis (

P
<
0.01

, FDR < 0.05). The underlying mechanisms of Sini Powder and Tong xie yao fang decoction may be related to neuroactive ligand-receptor interaction, calcium, cAMP, and HIF-1 signaling pathways. In conclusion, our results showed that the effect and mechanism of Sini Powder and Tong xie yao fang decoction in IBS treatment were in multi-ingredient, multitargets and multipathways, which would provide several potential and promising strategies for the further research and development of Sini Powder and Tong xie yao fang decoction on IBS treatment.
Effects of Acupuncture Combined with Moxibustion on Reproductive and Metabolic Outcomes in Patients with Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis
Authors: Li Peishuang , Peng Jiahua , Ding Zhiling , Zhou Xu , Liang Ruining
Published: April 2022

Objectives. In this systematic review, the effects of acupuncture combined with moxibustion on reproductive and metabolic outcomes in patients with polycystic ovary syndrome (PCOS) were evaluated. Methods. Randomized controlled trials (RCTs) assessing acupuncture combined with moxibustion + basic treatment (experimental group) versus basic treatment alone (control group) for treating PCOS were identified from English and Chinese databases up to November 3, 2021. Outcomes related to pregnancy, ovulation, miscarriage, sex hormones, and metabolic disorders were of interest. In the meta-analysis, risk ratios (RRs) and mean differences (MDs) and their 95% confidence intervals (CIs) were used as effect measures. Results. Twenty-five RCTs (n = 1991) were included. The pooled results showed that the experimental group had significant increases in the pregnancy rate (RR 1.81, 95% CI 1.58 to 2.08) and ovulation rate (RR 1.31, 95% CI 1.22 to 1.40) and decreases in the miscarriage rate (RR 0.45, 95% CI 0.28 to 0.73), and ovarian volume (MD −0.75 cm3, 95% CI −1.30 to −0.20). In the experimental group, improvements in the luteinizing hormone (LH) level, the LH-to-follicle-stimulating hormone (FSH) ratio, total testosterone level, fasting insulin level, and body mass index, but not in FSH, oestradiol, or dehydroepiandrosterone sulfate levels, were significantly greater. All reported adverse events were mild. Based on the limitations of risk of bias, inconsistency, imprecision, and/or publication bias, the level of evidence was judged to be moderate for the pregnancy rate, ovulation rate, miscarriage rate, LH level, and LH/FSH ratio and very low for the other outcomes. Conclusion. Among patients with PCOS, using acupuncture combined with moxibustion as a complementary therapy to basic treatments can improve pregnancy, ovulation, and miscarriage rates, the levels some sex hormones, and metabolic indicators, with good safety. Additionally, this combination therapy may have no effect on the FSH, oestradiol, or dehydroepiandrosterone sulfate level.
Plin5 Bidirectionally Regulates Lipid Metabolism in Oxidative Tissues
Authors: Zhang Xinqing , Xu Wu , Xu Rui , Wang Zhen , Zhang Xinyan , Wang Peng , Peng Ke , Li Meiling , Li Jing , Tan Yanfei , Wang Xiong , Pei Haifeng
Published: April 2022

Cytoplasmic lipid droplets (LDs) can store neutral lipids as an energy source when needed and also regulate the key metabolic processes of intracellular lipid accumulation, which is associated with several metabolic diseases. The perilipins (Plins) are a family of proteins that associate with the surface of LDs. As a member of Plins superfamily, perilipin 5 (Plin5) coats LDs in cardiomyocytes, which is significantly related to reactive oxygen species (ROS) production originated from mitochondria in the heart, consequently determining the progression of diabetic cardiomyopathy. Plin5 may play a bidirectional function in lipid metabolism which is in a state of dynamic balance. In the basic state, Plin5 inhibited the binding of comparative gene identification-58 (CGI-58) to adipose triglyceride lipase (ATGL) by binding CGI-58, thus inhibiting lipolysis. However, when the body is under stress (such as cold, fasting, exercise, and other stimuli), protein kinase A (PKA) phosphorylates and activates Plin5, which then causes Plin5 to release the binding site of CGI-58 and ATGL, prompting CGI-58 to bind to ATGL and activate ATGL activity, thus accelerating the lipolysis process, revealing the indispensable role of Plin5 in lipid turnover. Here, the purpose of this review is to summarize the present understanding of the bidirectional regulation role of Plin5 in oxidative tissues and to reveal its potential role in diabetic cardiomyopathy protection.
Optimization of Mental Health-Related Critical Barriers in IoT-Based Teaching Methodology
Authors: Juneja Abhinav , Turabieh Hamza , Upadhyay Hemant , Kiros Bitsue Zelalem , Hoang Vinh Truong , Trung Kiet Tran
Published: April 2022

Online learning has changed all elements of teaching of entire learning structure from primary to university level all around the world so that the challenges of online teaching are required to be optimized. The prominent objective of this manuscript is to optimize the issues of online teaching-learning in online education. Twelve issues of online teaching-learning are shortlisted by performing deep reviewing of the literature and grouping into three categories: “Students’ issues,” “Common issues,” and “Teachers’ issues” using the opinions of expert people. The analytical hierarchy process method is chosen for ranking of issues of online teaching. The findings can become effective in planning to get solution of the challenges of online teaching. These challenges of online teaching may lead to fragmental illness mentally over a long period of time. Because social media platforms may become an efficient tool for incorporating into online education, social media is a vital aspect of online learning. Over time, social media use may have an effect on the human brain in one way or another. The given work’s exploration of online teaching-learning challenges could lead to a social media-based examination of mental illness.
CCNA2 as an Immunological Biomarker Encompassing Tumor Microenvironment and Therapeutic Response in Multiple Cancer Types
Authors: Jiang Aimin , Zhou Ye , Gong Wenliang , Pan Xin , Gan Xinxin , Wu Zhenjie , Liu Bing , Qu Le , Wang Linhui
Published: April 2022

Background. Cancer is a major threat to human health worldwide. Although recent innovations and advances in early detection and effective therapies such as targeted drugs and immune checkpoint inhibitors have saved more lives of cancer patients and improved their quality of life, our knowledge about cancer remains largely unknown. CCNA2 belongs to the cell cyclin family and has been demonstrated to be a tumorigenic gene in multiple solid tumor types. The aim of the present study was to make a comprehensive analysis on the role of CCNA2 at a pancancer level. Methods. Multidatabases were collected to evaluate the different expression, prognostic value, DNA methylation, tumor mutation burden, microsatellite instability, mismatch repair, tumor immune microenvironment, and drug sensitivity of CCNA2 across pancancer. IHC was utilized to validate the expression and prognostic value of CCNA2 in ccRCC patients from SMMU cohort. Results. CCNA2 was differentially expressed in most cancer types vs. normal tissues. CCNA2 may significantly influence the prognosis of multiple cancer types, especially clear cell renal cell carcinoma (ccRCC). CCNA2 was also frequently mutated in most cancer types. Notably, CCNA2 was significantly correlated with immune cell infiltration and immune checkpoint inhibitory genes. In addition, CCNA2 was also strongly related to drug resistance. Conclusion. CCNA2 may prove to be a new biomarker for prognostic prediction, tumor immunity assessment, and drug susceptibility evaluation in pancancer level, especially in ccRCC.
Analysis of Key Commuting Routes Based on Spatiotemporal Trip Chain
Authors: Yao Wenbin , Chen Caijun , Su Hongyang , Chen Nuo , Jin Sheng , Bai Congcong
Published: April 2022

Commuting pattern is one of the most important travel patterns on the road network; the analysis of commuting pattern can provide support for public transport system optimization, policy formulation, and urban planning. In this study, a framework of the key commuting route mining algorithm based on license plate recognition (LPR) data is proposed. And the proposed algorithm framework can be migrated to any similar spatiotemporal data, such as GPS trajectory data. Commuting pattern vehicles are first extracted, and then, the spatiotemporal trip chains of all commuting pattern vehicles are mined. Based on the spatiotemporal trip chains, the spatiotemporal similarity matrix is constructed by dynamic time warping (DTW) algorithm. Finally, the characteristics of commuting pattern are analysed by the density-based spatial clustering of applications with noise (DBSCAN) algorithm. Different from other researches that analyse the commuting pattern using machine learning algorithms based on all data, this study first extracts commuting pattern vehicles and then designs a key commuting route mining algorithm framework for commuting pattern vehicles. Taking Hangzhou as an example, through the framework of mining algorithm proposed in this study, the commuting pattern characteristics and key commuting routes in Hangzhou have been successfully excavated, and policy suggestions based on the analysis results have also been put forward.
Blockchain-Based Trust Verification and Streaming Service Awareness for Big Data-Driven 5G and Beyond Vehicle-to-Everything (V2X) Communication
Authors: Rasheed Iftikhar , Asif Muhammad , Khan Wali Ullah , Ihsan Asim , Ullah Kalim , Ali Md. Sadek
Published: April 2022

Vigorous security and transparency with minimum latency and a high data rate are some of the key requirements for 5G and beyond vehicular networks especially in case of big data-driven vehicle-to-everything (V2X) communication applications which plays an important role in enabling advance intelligent transportation systems (ITS) and Internet of Vehicle (IoV) based network. The trace-ability in blockchain makes it one of the vital options, back-boned by the decentralized network to ensure independent security and privacy by exploiting the hash of a previous transaction with the time stamp and announcing it publicly for rejection of possible adversary attack. Therefore, in this work, we have opted for blockchains for trusted authentication and service awareness in 5G and beyond vehicle-to-everything (V2X) communication-based vehicular networks to stream blocks by certifying privacy and security. Here, we have considered blockchain as intermediary trusted agent to witness communication between a vehicle node and edge node, where edge node also uploads microservices along with calling figure of microservices to the blockchain. Furthermore, to ensure vehicle privacy with joint verification of vehicular network and server, we have devised a mechanism in which every vehicle nodes anonymously ask for services from the edge server along with signing an individual’s identity. Moreover, based on generated vehicle requests and service awareness, we devised an improved edge cache scheme for the prior compilation of services at each edge. In comparison to the previous state-of-art work, the result shows that our proposed work handles the requests more efficiently to achieve a better service request cache hit rate generated by vehicles at the edge server.
Comparison of CRP, Procalcitonin, Neutrophil Counts, Eosinophil Counts, sTREM-1, and OPN between Pneumonic and Nonpneumonic Exacerbations in COPD Patients
Authors: Mou Shan , Zhang Wei , Deng Yan , Tang Zhijun , Jiang Depeng
Published: April 2022

Introduction. The patients with community-acquired pneumonia (CAP) and acute exacerbations of COPD (AECOPD) could have a higher risk of acute and severe respiratory illness than those without CAP in AECOPD. Consequently, early identification of pneumonia in AECOPD is quite important. Methods. 52 subjects with AECOPD + CAP and 93 subjects with AECOPD from two clinical centers were enrolled in this prospective observational study. The values of osteopontin (OPN), soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), C-reactive protein (CRP), procalcitonin (PCT), eosinophil (EOS) counts, and neutrophil (Neu) counts in blood on the first day of admission and clinical symptoms were compared in AECOPD and AECOPD + CAP. In addition, subgroup analyses of biomarker difference were conducted based on the current use of inhaled glucocorticoids (ICS) or systemic corticosteroids (SCS). Results. Patients with AECOPD + CAP had increased sputum volume, sputum purulence, diabetes mellitus, and longer hospital stays than AECOPD patients (

p
<
0.05

). A clinical logistic regression model showed among the common clinical symptoms, purulent sputum can independently predict pneumonia in AECOPD patients after adjusting for a history of diabetes. At day 1, AECOPD + CAP patients had higher values of Neu, CRP, PCT, and OPN, while serum sTREM-1 levels and EOS counts were similar in the two groups. CRP fared best at predicting AECOPD with CAP (

p
<
0.05

for the test of difference), while OPN had similar accuracy with Neu, PCT, and purulent sputum (

p
>
0.05

for the test of difference). Multivariate analysis, including clinical symptoms and biomarkers, suggested that CRP ≥15.8 mg/dL at day 1 was a only promising predictor of pneumonia in AECOPD. CRP and OPN were not affected by ICS or SCS. Conclusions. CRP ≥15.8 mg/dL is an ideal promising predictor of pneumonia in AECOPD, and its plasma level is not affected by ICS or SCS. The diagnostic performance of CRP is not significantly improved when combined with clinical symptoms or other markers (OPN, PCT, and Neu).
Encapsulation of Different Types of Probiotic Bacteria within Conventional/Multilayer Emulsion and Its Effect on the Properties of Probiotic Yogurt
Authors: Mahmoodi Pour Hamed , Marhamatizadeh Mohammad Hossein , Fattahi Hossein
Published: April 2022

Microencapsulation of probiotic cells within emulsion is an efficient method to enhance the viability of probiotic bacteria. In the present study, free and encapsulated probiotic cells (Lactobacillus rhamnosus and Lactobacillus plantarum) in simple and multilayer emulsions were used to produce a set of probiotic yogurts. In all samples, an increasing trend in syneresis and acidity values and a decreasing trend in pH and viability of probiotic cells were observed during the storage time. However, the changes in these parameters were more significant for free-loaded probiotic samples. Moreover, the free cells showed poor survival in the yogurt samples by decreasing the viable cell count of probiotics from 7.71–7.59 logs CFU/mL to 6.93–6.82 log CFU/mL during storage, while encapsulation in the multilayer emulsion showed an insignificant reduction from 7.65–7.59 logs CFU/mL to 7.55–7.45 log CFU/mL at the end of storage. The obtained results showed that the type of probiotic bacteria had no significant effects on the physicochemical and structural properties of samples. However, encapsulating probiotics in multilayer emulsion led to a more homogenous structure in yogurt. The sensorial properties were also not affected by the probiotic type and the encapsulation method. Consequently, the multilayer emulsion can provide an ideal delivery carrier for encapsulating probiotic bacteria in dairy products.
Environmental Impact and Carbon Footprint Assessment of Sustainable Buildings: An Experimental Investigation
Authors: Chukka Naga Dheeraj Kumar Reddy , Arivumangai A. , Kumar Sanjeev , Subashchandrabose R. , Reddy Yeddula Bharath Simha , Natrayan L. , Debela Geleta Chala
Published: April 2022

Carbon emission has been considerably higher in India in the last few decades. The greenhouse gases increased to an imaginary volume, a major contributor to global warming. Chennai is one of India’s large cosmopolitan cities, contributing more Gross Domestic Product (G.D.P.) and carbon to the atmosphere. The infrastructure sector is always a booming sector in and around Chennai, which requires more construction materials. In turn, the construction of new buildings expands the city with a large area of urban and suburban Chennai, where I.T. division, automobile division, and industrial estates are available. Hence, this study deals with the carbon emission of a residential building constructed with conventional materials in and around Chennai. So, one can estimate the emission of carbon by the conventional building, which leads to global warming and climate change.
Energy-Efficient Hierarchical Collaborative Scheme for Content Delivery in Mobile Edge Computing
Authors: Fang Chao , Huang Xiaojie , Huang Jingjing , Hu Zhaoming , Sun Yanhua , Cai Jun , Wang Zhuwei , Chen Huamin , Zhang Jianchuan , Xu Fangmin
Published: April 2022

With the rapid growth of Internet traffic and smart mobile terminals, ultradense networks are adopted as the key technology of the fifth generation to enhance resource utilization and content distribution while causing serious energy efficiency problem. Mobile edge computing has recently drawn great attention for its advantages in reducing transmission delay and network energy consumption by implementing caching and computing abilities at the edge of mobile networks. To improve network energy efficiency and content transmission, in this paper, we propose a novel energy-efficient hierarchical collaborative scheme by considering the in-network caching, request aggregation, and joint allocation of caching, computing, and communication resources in a layered heterogeneous network including mobile users, small base stations, macro base stations, and the cloud. We formulate the energy consumption problem as a queuing theory-based centralized model, where the same content requests can be aggregated in the queue of each base station. Then, the optimal solution is analyzed based on the distribution characteristic of content popularity at the base stations. Simulation results show that the performance of our proposed model is much better than the existing cloud-edge cooperation solutions without considering the deployment of caching resource and request aggregation policies.
Template-Aware Transformer for Person Reidentification
Authors: Zheng Yanwei , Zhao Zengrui , Yu Xiaowei , Yu Dongxiao
Published: April 2022

Person reidentification (ReID) is a challenging computer vision task for identifying or verifying one or more persons when the faces are not available. In ReID, the indistinguishable background usually affects the model’s perception of the foreground, which reduces the performance of ReID. Generally, the background of the same camera is similar, whereas that of different cameras is quite different. Based on this finding, we propose a template-aware transformer (TAT) method which can learn intersample indistinguishable features by introducing a learnable template for the transformer structure to cut down the model’s attention to regions of the image with low discrimination, including backgrounds and occlusions. In the multiheaded attention module of the encoder, this template directs template-aware attention to indistinguishable features of the image and gradually increases the attention to distinguishable features as the encoder block deepens. We also increase the number of templates using side information considering the characteristics of ReID tasks to adapt the model to backgrounds that vary significantly with different camera IDs. Finally, we demonstrate the validity of our theories using various public data sets and achieve competitive results via a quantitative evaluation.
Application of Laparoscopic Gastric Jejunum Uncut Roux-en-Y Anastomosis
Authors: Yu Chao , Yang Tian , Yan Qiang , Li Deguan , Wang Yigao , Yang Xiaodong , Zhang Shangxin , Zhang Yonghong , Zhang Zhen
Published: April 2022

Background. Uncut Roux-en-Y gastrojejunostomy, recently developed in China, is useful in the treatment of distal gastric cancer. This study is aimed at comparing laparoscopic gastric jejunum uncut Roux-en-Y anastomosis with conventional anastomosis in the surgical treatment of distal gastric malignancy. Methods. In this retrospective study, the clinical data of 178 patients and their follow-up records were analyzed. 112 cases (uncut group) were the observation group for stomach jejunum uncut Roux-en-Y anastomosis, the control group for the stomach, 66 cases (conventional group) were for jejunum Roux-en-Y anastomosis and Billroth I and Billroth II anastomosis. A comparison between the two groups was conducted based on the general situation of the patients, TNM stage, and one-year survival rate. Results. There was no significant difference reported between the two groups in terms of the general situation and TNM stage. A comparison on postoperative complications between the two groups revealed that the postoperative bleeding was 0.9% and 6.1%, the bile reflux gastritis was 1.8% and 9.1%, the anastomotic leakage was 0.0% and 3.0%, the delayed gastric emptying was 0.9% and 7.6%, and the overall complications was at 3.6% and 25.8%, which was significantly lower in the observation group than in the control group, and the difference was statistically significant. Notably, there was no significant difference in 1-year survival rate between the two groups. Conclusion. Laparoscopic gastric jejunal uncut Roux-en-Y anastomosis significantly reduces the risk of postoperative complications of the digestive tract. Its operation is easy and exhibits an effective curative effect.
Simulación remota con feedback asincrónico como estrategia de enseñanza para entrenar habilidades prácticas en kinesiología
Authors: Villagrán -Gutierrez Ignacio , Antúnez Marcela , Fuentes-Cimma Javiera , Del Valle Javiera , Gregorio de las Heras Sofía , Pozo Liliana , Rammsy Francisca , Torres Gustavo , Escalona Gabriel , Varas Julián
Published: April 2022

Introducción: en los escenarios de reducción de la presencialidad como los provocados por la pandemia de COVID-19, la carrera de kinesiología incorporó la metodología de simulación remota con feedback asincrónico con una plataforma que considera la práctica remota de habilidades prácticas, y un proceso de retroalimentación con el propósito de mejorar el desempeño y aprendizaje de los estudiantes. El objetivo del estudio es describir la implementación y resultados de esta metodología. Métodos: se realizó un entrenamiento remoto piloto con estudiantes de kinesiología de la Pontificia Universidad Católica de Chile, el cuál consistió en 7 etapas de diferentes técnicas manuales musculoesqueléticas. Se aplicó una encuesta final para conocer la percepción de los estudiantes y se realizó un análisis descriptivo de los resultados. Resultados: se evaluaron 468 videos de 78 estudiantes a través de 4040 inputs de retroalimentación. La mayoría de los estudiantes reportó una percepción positiva respecto a la metodología (92,7%)  y feedback recibido (71,4%). Un 60% de los estudiantes reportó sentir seguridad al realizar las técnicas por última vez. Un porcentaje (%) bajo de estudiantes reportó haber tenido dificultades con el entrenamiento. Conclusión: la implementación de la metodología propuesta permitió que los estudiantes siguieran adquiriendo habilidades prácticas en técnicas manuales musculoesqueléticas en un contexto donde el aprendizaje presencial no era posible, con una alta valoración. Esta metodología, relevó la existencia de un entrenamiento oculto previo a la evaluación del instructor, lo que permitiría que los estudiantes transiten hacia una curva de aprendizaje autónoma para una posterior transferencia en contexto real.