bluuebunny/crossref_metadata_2025 huggingface dataset:
Cloud-Edge Computing-Based ICICOS Framework for Industrial Automation and Artificial Intelligence: A Survey
Authors: Su Weibin , Xu Gang , He Zhengfang , Machica Ivy Kim , Quimno Val , Du Yi , Kong Yanchun
Published: March 2023

Industrial Automation (IA) and Artificial Intelligence (AI) need an integrated platform. Due to the uncertainty of the time required for training or reasoning tasks, it is difficult to ensure the real-time performance of AI in the factory. Thus in this paper, we carry out a detailed survey on cloud-edge computing-based Industrial Cyber Intelligent Control Operating System (ICICOS) for industrial automation and artificial intelligence. The ICICOS is built based on IEC61499 programming method and used to replace the obsolete Programmable Logic Controller (PLC). It is widely known that the third industrial revolution produced an important device: PLC. But the finite capability of PLC just only adapts automation which will not be able to support AI, especially deep learning algorithms. Edge computing promotes the expansion of distributed architecture to the Internet of Things (IoT), but little effect has been achieved in the territory of PLC. Therefore, ICICOS focuses on virtualization for IA and AI, so we introduce our ICICOS in this paper, and give the specific details.
An Adaptive Learning Environment for Programming Based on Fuzzy Logic and Machine Learning
Authors: Chrysafiadi Konstantina , Virvou Maria , Tsihrintzis George A. , Hatzilygeroudis Ioannis
Published: March 2023

In this paper, we present an Intelligent Tutoring System (ITS), for use in teaching the logic of computer programming and the programming language ‘C’. The aim of the ITS is to adapt the delivered learning material and the lesson sequence to the knowledge level and learning needs of each individual student. The adaptation of the presented ITS is based on fuzzy logic and a machine learning technique. Particularly, the system uses the distance weighted k-nearest neighbor algorithm to detect the learner’s knowledge level and abilities concerning computer programming during her/ his first interaction with the system. Next and during subsequent interactions of the learner with the system, fuzzy logic is used to identify the learner’s current knowledge level and potential misconceptions. The system takes into consideration the knowledge dependencies that exist among the domain concepts of the learning material and, applying fuzzy rules, decides about the learning material that has to be delivered to the learner as well as the lesson sequence. The system has been fully implemented and evaluated through t-tests. The evaluation results show that the combination of machine learning (for initially identifying the student’s learning abilities and needs) with fuzzy logic (for the continuous identification of the learner’s current knowledge level and misconceptions) provides more personalized learning experience, promotes the active participation of students in the learning process and results in decrease in the number of dropouts.
CLASSIFICATION OF GRINDING BURNS IN BEARINGS WITH TRANSFER LEARNING
Authors: CEYLAN NURDOĞAN , KAÇAR SEZGİN , CHU YU-MING , ALOTAIBI NAIF D.
Published: March 2023

Grinding is used to improve surface roughness and dimensioning precision in the metal industry. A large amount of heat is released during grinding. Most of this heat is transferred to the workpiece. In this case, a grinding burn may occur on the workpiece. Grinding burn is a significant issue in the production of bearings. If a burn occurs on the workpiece during grinding, the surface quality deteriorates and the internal structure and mechanical qualities of the material are adversely affected. Therefore, detecting grinding burn is critical for bearing manufacturers. In this study, during the grinding of the bearing parts, the machine conditions were changed in accordance with the real grinding scenario, and burnt and non-burned bearing data were obtained with the acoustic emission sensor. Then, time-frequency representations were obtained from these data with the continuous wavelet transform. These images have been classified in the GoogLeNet Network by transfer learning. Combinations of faulty/ normal data processed under different machine settings and combinations of faulty/ normal data processed with the same machine parameters were classified with the proposed method and compared. Faulty bearings processed with the same machine characteristics were detected with 100% accuracy using the proposed method. This percentage gives a reliable result for bearing producers. This study contributes to the literature in three ways: (a) It is based on data collected under real-world grinding situations. (12 different machine settings were employed.) (b) Various machine conditions were compared. (c) Faulty bearings were detected with high accuracy.
A DIABETES RISK PREDICTING METHOD WITH MULTI-STRATEGY COUNTERFACTUAL-BASED DATA AUGMENTATION
Authors: WANG CHEN , LIU YAN-YI , DIAO ZHAO-SHUO , TANG JIA-WEI , WEN YING-YOU , YANG XIAO-TAO
Published: March 2023

Diabetes is a chronic disease that poses a serious threat to health, and its early risk prediction has been a hot research topic in the field of medical artificial intelligence. Routine medical checkups are the most common way to monitor people’s health status, and the data from medical checkups contain rich diagnostic information, which is valuable for diabetes risk prediction. Currently, most of the available studies on diabetes risk prediction are based on publicly available datasets, and the models and algorithms do not work well on real clinical datasets. Real routine checkup data are characterized by complex information, diverse features, high redundancy and poor balance, which pose great challenges for diabetes risk prediction. To address this problem, this paper proposes a multi-strategy data augmentation-based diabetes risk prediction method, after completing data pre-processing and feature selection, a counterfactual-based data balancing strategy is used to augment a minority class of instances, and a density clustering-based supplemental counterfactual data augmentation strategy is proposed to address the problem of insufficient representation of generated instances in the counterfactual method. Moreover, the uncertainty-weighted method is used in the model training phase. Based on the real checkup dataset, five machine learning methods including Logistic Regression (LR), SVM, Decision Tree, Random Forest and Gradient Boosting are used to model and use 5-fold cross-validation to carry out diabetes risk assessment and prediction. The experimental results showed that the sensitivity and precision of the models were significantly improved compared with the existing methods, and the sensitivity of the LR model for diabetes risk prediction on the real routine checkup dataset reached more than 90[Formula: see text], which meet the requirements of clinical application.
MACHINE LEARNING AND IOT-BASED LI-ION BATTERY CLOUD MONITORING SYSTEM FOR 5G BASE STATIONS
Authors: LI XUEGUANG , LI BIFENG , GUO SUFEN , SUN ZHANFANG , WANG QIANQING , DU TONGTONG , LIN PENG , ZHANG DONGFANG
Published: March 2023

With the accelerated construction of 5G and IoT, more and more 5G base stations are erected. However, with the increase of 5G base stations, the power management of 5G base stations becomes progressively a bottleneck. In this paper, we solve the problem of 5G base station power management by designing a 5G base station lithium battery cloud monitoring system. In this paper, first, the lithium battery acquisition hardware is designed. Second, a new communication protocol is established based on Modbus. Third, the windows desktop upper computer software and the cloud-based monitoring system are designed. Finally, this paper designs the improved ResLSTM algorithm which is fused with ResNet algorithm based on Stacked LSTM. The algorithm designed in this paper is tested in comparison with SVM and LSTM. The performance of the algorithm designed in this paper is better than SVM and LSTM. Furthermore, the communication test, as well as the training and testing of the ResLSTM algorithm are outstanding. The 5G base station lithium-ion battery cloud monitoring system designed in this paper can meet the requirements. It has great significance for engineering promotion. More importantly, the ResLSTM algorithm designed in this paper can better guide the method of lithium-ion battery SOC estimation.
Global dynamics analysis for a nonlinear HTLV-I model with logistic proliferation and CTL response
Authors: Chen Siyu , Liu Zhijun , Wang Lianwen , Zhang Xingan
Published: March 2023

It is beyond dispute that cytotoxic T-lymphocytes (CTLs) exert a vital function in the host’s antiviral defense mechanism. With the idea of the above factor and the logistic proliferation of CD4[Formula: see text] T-cells, we establish a HTLV-I (human T-cell leukemia virus type-I) mathematical model. First, two threshold parameters [Formula: see text] and [Formula: see text] (the basic reproduction numbers for viral infection and CTL immune response, respectively) are obtained. Second, sufficient criteria for local and global asymptotic stabilities of the feasible equilibria of the model are deduced, respectively. Third, the sensitivity analyses of [Formula: see text] and [Formula: see text] are performed to better understand the effective strategies for HTLV-I infection. Finally, not only numerical simulations are given to illustrate the stability conclusions, but also the biological significance is stated.
In-situ fabricating CoOOH@ZnxCo1−xS heterostructure via electrochemical oxidation for overall water splitting
Authors: Huang Wangjun , Liang Zhiyu , Wang Ying , Zhao Yan
Published: March 2023

Recently, visible light-driven overall water splitting without any sacrificial reagents has served as a promising technology for utilizing solar energy. Herein, CoOOH@Zn[Formula: see text]Co[Formula: see text]S heterostructure was successfully prepared by in-situ creating CoOOH on the surface of Zn[Formula: see text]Co[Formula: see text]S nanospheres via an electrochemical oxidation route. Such CoOOH@Zn[Formula: see text]Co[Formula: see text]S heterostructure shows an enhanced capacity for overall water splitting under visible light without any sacrificial reagents. Besides, based on the results of linear sweep photovoltammetry (LSV) and open-circuit photovoltage decay (OCVD), the unique cascade charge transport channel between the in-situ creating CoOOH and Zn[Formula: see text]Co[Formula: see text][Formula: see text]S will significantly enhance the transfer behaviors and prolongs the lifetime of photo-generated charge. It is hoped that this work could provide new insight into reasonably designing efficient photocatalytic materials for converting solar energy to chemical energy.
Combining Diverse Meta-Features to Accurately Identify Recurring Concept Drift in Data Streams
Authors: Halstead Ben , Koh Yun Sing , Riddle Patricia , Pechenizkiy Mykola , Bifet Albert
Published: March 2023

Learning from streaming data is challenging as the distribution of incoming data may change over time, a phenomenon known as concept drift. The predictive patterns, or
experience
learned under one distribution may become irrelevant as conditions change under concept drift, but may become relevant once again when conditions reoccur. Adaptive learning methods adapt a classifier to concept drift by identifying which distribution, or
concept
, is currently present in order to determine which experience is relevant. Identifying a concept requires some
representation
to be stored for comparison, with the quality of the representation being key to accurate identification. Existing concept representations are based on meta-features, efficient univariate summaries of a concept. However, no single meta-feature can fully represent a concept, leading to severe accuracy loss when existing representations cannot describe concept drift. To avoid these failure cases, we propose the first general framework for combining a diverse range of meta-features into a single representation. We solve two main challenges, first presenting a method of efficiently computing, storing, and querying an arbitrary set of meta-features as a single representation, showing that a combination of meta-features may successfully avoid failure cases seen with existing methods. Second, we present the first method for dynamically learning which meta-features distinguish concepts in any given dataset, significantly improving performance. Our proposed approach enables state-of-the-art feature selection methods, such as mutual information, to be applied to concept representation meta-features for the first time. We investigate tradeoffs between memory budget and classification performance, observing accuracy increases of up to 16% by dynamically weighting the contribution of each meta-feature.
Insights into the Morphological Evolution of Mossy Dendrites in Lithium Metal Symmetric and Full Cell: A Modelling Study
Authors: Verma Prakhar , Puravankara Sreeraj , Nandanwar Mahendra N. , Chakraborty Jayanta
Published: March 2023

Mossy-dendrite growth is a common phenomenon observed in many lithium metal batteries. A lattice model is presented in this work to understand the morphological changes in mossy dendrites during the plating and stripping of Li metal. The model mimics the mossy dendrite growth by incorporating nucleation and growth of spherical particles at the lattice points. The model can predict the transition between root and tip growth by merely changing the Damköhler number. The mass transfer limitations created by the initiation of the mossy phase are identified as the dominant cause of the decay in cell potential. We also investigate the effect of morphology on the formation of dead lithium during electrodissolution. This is the first attempt to combine pseudo-2D and lattice models to simulate full-cell cycles toward mossy growth.
Construction of Phthalocyanine-Titanium Dioxide/Graphene/Polyaniline Composite Electrodes by Electrochemical Method for Supercapacitor Applications
Authors: Arvas Melih Besir , Artar Emirhan , Gorduk Ozge , Gorduk Semih , Sahin Yucel
Published: March 2023

Supercapacitors (SCs) are the most interesting alternative energy storage and conversion systems to successfully overcome the global energy problem for future generations. A lot of work has been done to improve the capacitive performance of an electrode and to achieve high power and energy density. Herein, for the first time in the literature, we prepared hybrid composite materials consisting of metallo phthalocyanine doped-titanium dioxide (MPc-TiO2) and high conductivity graphene (Gr) and polyaniline (PANI) in a one-step on pencil graphite electrode (PGE) using the cyclic voltammetry method. The microscopic and structural characteristics of the synthesized MPc-TiO2/Gr/PANI/PGE (M=Cu and Co) are analyzed by various spectroscopic and analytical techniques. As a result, the optimized CoPc-TiO2/Gr/PANI/PGE as the electrode shows a highly specific capacitance of 401.5 F g−1 at 5 A g−1 and excellent cyclic stability up to 1000 cycles. The good electrochemical performance could be attributed to the synergistic effect of the high pseudocapacitance and good conductivity of CoPc-TiO2 as well as the capacitive contribution and conductivity of Gr and PANI. Our strategy provides a new avenue to develop high-performance SCs via rational integration of MPc-TiO2 with Gr and PANI.
Heparan sulfate proteoglycan in Alzheimer’s disease: aberrant expression and functions in molecular pathways related to amyloid-β metabolism
Authors: Ozsan McMillan Ilayda , Li Jin-Ping , Wang Lianchun
Published: March 2023

Alzheimer’s disease (AD) is the most common form of dementia. Currently, there is no effective treatment for AD, as its etiology remains poorly understood. Mounting evidence suggests that the accumulation and aggregation of amyloid-β peptides (Aβ), which constitute amyloid plaques in the brain, is critical for initiating and accelerating AD pathogenesis. Considerable efforts have been dedicated to shedding light on the molecular basis and fundamental origins of the impaired Aβ metabolism in AD. Heparan sulfate (HS), a linear polysaccharide of the glycosaminoglycan family, co-deposits with Aβ in plaques in the AD brain, directly binds and accelerates Aβ aggregation, and mediates Aβ internalization and cytotoxicity. Mouse model studies demonstrate that HS regulates Aβ clearance and neuroinflammation in vivo. Previous reviews have extensively explored these discoveries. Here, this review focuses on the recent advancements in understanding abnormal HS expression in the AD brain, the structural aspects of HS-Aβ interaction, and the molecules involved in modulating Aβ metabolism through HS interaction. Furthermore, this review presents a perspective on the potential effects of abnormal HS expression on Aβ metabolism and AD pathogenesis. In addition, the review highlights the importance of conducting further research to differentiate the spatiotemporal components of HS structure and function in the brain and AD pathogenesis.
The cardioprotective role of sirtuins is mediated in part by regulating KATP channel surface expression
Authors: Tuncay Erkan , Gando Ivan , Huo Jian-Yi , Yepuri Gautham , Samper Natalie , Turan Belma , Yang Hua-Qian , Ramasamy Ravichandran , Coetzee William A.
Published: March 2023

Sirtuins are NAD+-dependent deacetylases with beneficial roles in conditions relevant to human health, including metabolic disease, type II diabetes, obesity, cancer, aging, neurodegenerative diseases, and cardiac ischemia. Since ATP-sensitive K+ (KATP) channels have cardioprotective roles, we investigated whether they are regulated by sirtuins. Nicotinamide mononucleotide (NMN) was used to increase cytosolic NAD+ levels and to activate sirtuins in cell lines, isolated rat and mouse cardiomyocytes or insulin-secreting INS-1 cells. KATP channels were studied with patch clamping, biochemistry techniques, and antibody uptake experiments. NMN led to an increase in intracellular NAD+ levels and an increase in the KATP channel current, without significant changes in the unitary current amplitude or open probability. An increased surface expression was confirmed using surface biotinylation approaches. The rate of KATP channel internalization was diminished by NMN, which may be a partial explanation for the increased surface expression. We show that NMN acts via sirtuins since the increased KATP channel surface expression was prevented by blockers of SIRT1 and SIRT2 (Ex527 and AGK2) and mimicked by SIRT1 activation (SRT1720). The pathophysiological relevance of this finding was studied using a cardioprotection assay with isolated ventricular myocytes, in which NMN protected against simulated ischemia or hypoxia in a KATP channel-dependent manner. Overall, our data draw a link between intracellular NAD+, sirtuin activation, KATP channel surface expression, and cardiac protection against ischemic damage.
Computational modeling of signal transduction networks without kinetic parameters: Petri net approaches
Authors: Koch Ina , Büttner Bianca
Published: March 2023

More and more computational techniques have been applied to model biological systems, especially signaling pathways in medical systems. Due to the large number of experimental data driven by high-throughput technologies, new computational concepts have been developed. Nevertheless, often the necessary kinetic data cannot be determined in sufficient number and quality because of experimental complexity or ethical reasons. At the same time, the number of qualitative data drastically increased, for example, gene expression data, protein-protein interaction data, and imaging data. Especially for large-scale models, the application of kinetic modeling techniques can fail. On the other hand, many large-scale models have been constructed applying qualitative and semiquantitative techniques, for example, logical models or Petri net models. These techniques make it possible to explore system’s dynamics without knowing kinetic parameters. Here, we summarize the work of the last 10 years for modeling signal transduction pathways in medical applications applying Petri net formalism. We focus on analysis techniques based on system’s invariants without any kinetic parameters and show predictions of all signaling pathways of the system. We start with an intuitive introduction into Petri nets and system’s invariants. We illustrate the main concepts using the tumor necrosis factor receptor 1 (TNFR1)-induced nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) pathway as a case study. Summarizing recent models, we discuss the advantages and challenges of Petri net applications to medical signaling systems. In addition, we provide exemplarily interesting Petri net applications to model signaling in medical systems of the last years that use the well-known stochastic and kinetic concepts developed about 50 years ago.
Hydrogen sulfide in health and diseases: cross talk with noncoding RNAs
Authors: Lu Qing-Bo , Ding Yi , Fu Xiao , Sun Hai-Jian , Zhang Ji-Ru
Published: March 2023

Hydrogen sulfide (H2S) is previously described as a potentially lethal toxic gas. However, this gasotransmitter is also endogenously generated by the actions of cystathionine-β-synthase (CBS), cystathionine-γ-lyase (CSE), and 3-mercaptopyruvate sulfurtransferase (3-MST) in mammalian systems, thus belonging to the family of gasotransmitters after nitric oxide (NO) and carbon monoxide (CO). The physiological or pathological significance of H2S has been extensively expanded for decades. Growing evidence has revealed that H2S exerts cytoprotective functions in the cardiovascular, nervous, and gastrointestinal systems by modulating numerous signaling pathways. With the continuous advancement of microarray and next-generation sequencing technologies, noncoding RNAs (ncRNAs) have gained recognition as key players in human health and diseases due to their considerable potential as predictive biomarkers and therapeutic targets. Coincidentally, H2S and ncRNAs are not independent regulators but interact with each other during the development and progression of human diseases. Specifically, ncRNAs might serve as downstream mediators of H2S or act on H2S-generating enzymes to govern endogenous H2S production. The purpose of this review is to summarize the interactive regulatory roles of H2S and ncRNAs in the initiation and development of various diseases and explore their potential health and therapeutic benefits. This review will also highlight the importance of cross talk between H2S and ncRNAs in disease therapy.
METTL14 promotes fibroblast-like synoviocytes activation via the LASP1/SRC/AKT axis in rheumatoid arthritis
Authors: Li Xuan’an , Xu Xuezheng , Zhang Qilei , Ling Min , Li Xian’an , Tan Xiaohua
Published: March 2023

The objective of this study is to explore the specific roles of a crucial N6-methyladenosine (m6A) methyltransferase, methyltransferase-like 14 (METTL14), in fibroblast-like synoviocytes (FLSs) activation of rheumatoid arthritis (RA). RA rat model was induced by administering intraperitoneally collagen antibody alcohol. Primary fibroblast-like synoviocytes (FLSs) were isolated from joint synovium tissues in rats. shRNA transfection tools were used to downregulate METTL14 expression in vivo and vitro. The injury of joint synovium was shown by hematoxylin and eosin (HE) staining. The cell apoptosis of FLSs was determined by flow cytometry. The levels of IL-6, IL-18, and C-X-C motif chemokine ligand (CXCL)10 in serum and culture supernatants were measured by ELISA kits. The expressions of LIM and SH3 domain protein 1 (LASP1), p-SRC/SRC, and p-AKT/AKT in FLSs and joint synovium tissues were determined by Western blots. The expression of METTL14 was greatly induced in the synovium tissues of RA rats compared with normal control rats. Compared with sh-NC-treated FLSs, METTL14 knockdown significantly increased cell apoptosis, inhibited cell migration and invasion, and suppressed the production of IL-6, IL-18, and CXCL10 induced by TNF-α. METTL14 silencing suppresses the expression of LASP1 and the activation of Src/AKT axis induced by TNF-α in FLSs. METTL14 improves the mRNA stability of LASP1 through m6A modification. In contrast, these were reversed by LASP1 overexpression. Moreover, METTL14 silencing clearly alleviates FLSs activation and inflammation in a RA rat model. These results suggested that METTL14 promotes FLSs activation and related inflammatory response via the LASP1/SRC/AKT signaling pathway and identified METTL14 as a potential target for treating RA.
Physiologically relevant culture medium Plasmax improves human placental trophoblast stem cell function
Authors: Avellino Giulia , Deshmukh Ruhi , Rogers Stephanie N. , Charnock-Jones D. Stephen , Smith Gordon C. S. , Tardito Saverio , Aye Irving L. M. H.
Published: March 2023

Human trophoblast cultures provide powerful tools to model key processes of placental development. In vitro trophoblast studies to date have relied on commercial media that contains nonphysiological levels of nutrients, and the impact of these conditions on trophoblast metabolism and function is unknown. Here, we show that the physiological medium (Plasmax) with nutrient and metabolite concentrations recapitulating human plasma improves human trophoblast stem cell (hTSC) proliferation and differentiation compared with standard medium (DMEM-F12). hTSCs cultured in Plasmax-based medium also show altered glycolytic and mitochondrial metabolism, as well as reduced S-adenosylmethionine/S-adenosyl-homocysteine ratio compared with DMEM-F12-based medium. These findings demonstrate the importance of the nutritional environment for phenotyping cultured human trophoblasts.
Myeloid-specific fatty acid transport protein 4 deficiency induces a sex-dimorphic susceptibility for nonalcoholic steatohepatitis in mice fed a high-fat, high-cholesterol diet
Authors: Göcebe Deniz , Jansakun Chutima , Zhang Yuling , Staffer Simone , Tuma-Kellner Sabine , Altamura Sandro , Muckenthaler Martina U. , Merle Uta , Herrmann Thomas , Chamulitrat Walee
Published: March 2023

FATP4 deficiency in BMDMs and Kupffer cells led to increased proinflammatory response. Fatp4M−/− mice displayed thrombocytopenia, splenomegaly, and elevated liver enzymes. In response to HFHC feeding, male mutants were prone to hepatic steatosis, whereas female mutants showed exaggerated fibrosis. Our study provides insights into a sex-dimorphic susceptibility to NASH by myeloid-FATP4 deficiency.
Rat bronchoalveolar lavage proteome changes following e-cigarette aerosol exposures
Authors: Day Nicholas J. , Wang Juan , Johnston Carl J. , Kim So-Young , Olson Heather M. , House Emma L. , Attah Isaac Kwame , Clair Geremy C. , Qian Wei-Jun , McGraw Matthew D.
Published: March 2023

E-cigarette liquids are complex mixtures of chemicals consisting of humectants, such as propylene glycol (PG) and vegetable glycerin (VG), with nicotine or flavorings added. Published literature emphasizes the toxicity of e-cigarette aerosols with flavorings whereas much less attention has been given to the biologic effects of humectants. The purpose of the current study was to provide a comprehensive view of the acute biologic effects of e-cigarette aerosols on rat bronchoalveolar lavage (BAL) using mass spectrometry-based global proteomics. Sprague–Dawley rats were exposed to e-cigarette aerosol for 3 h/day for three consecutive days. Groups included: PG/VG alone, PG/VG + 2.5% nicotine (N), or PG/VG + N + 3.3% vanillin (V). Right lung lobes were lavaged for BAL and supernatants prepared for proteomics. Extracellular BAL S100A9 concentrations and BAL cell staining for citrullinated histone H3 (citH3) were also performed. From global proteomics, ∼2,100 proteins were identified from rat BAL. The greatest change in number of BAL proteins occurred with PG/VG exposures alone compared with controls with biological pathways enriched for acute phase responses, extracellular trap formation, and coagulation. Extracellular BAL S100A9 concentrations and the number of citH3 + BAL cells also increased significantly in PG/VG and PG/VG + 2.5% N. In contrast to PG/VG or PG/VG + N, the addition of vanillin to PG/VG + N increased BAL neutrophilia and downregulated lipid transport proteins. In summary, global proteomics support e-cigarette aerosol exposures to PG/VG alone as having a significant biologic effect on the lung independent of nicotine or flavoring with increased markers of extracellular trap formation.
A proinflammatory long noncoding RNA Lncenc1 regulates inflammasome activation in macrophage
Authors: Han Yohan , Zhu Yin , Dutta Saugata , Almuntashiri Sultan , Wang Xiaoyun , Zhang Duo
Published: March 2023

Mammalian genomes encode thousands of long noncoding RNAs (lncRNAs). LncRNAs are extensively expressed in various immune cells. The lncRNAs have been reported to be involved in diverse biological processes, including the regulation of gene expression, dosage compensation, and genomic imprinting. However, very little research has been conducted to explore how they alter innate immune responses during host-pathogen interactions. In this study, we found that a lncRNA, named long noncoding RNA, embryonic stem cells expressed 1 (Lncenc1), was strikingly increased in mouse lungs after gram-negative (G−) bacterial infection or exposure to lipopolysaccharides (LPS). Interestingly, our data indicated that Lncenc1 was upregulated in macrophages but not in primary epithelial cells (PECs) or polymorphonuclear leukocytes (PMN). The upregulation was also observed in human THP-1 and U937 macrophages. Besides, Lncenc1 was highly induced during ATP-induced inflammasome activation. Functionally, Lncenc1 showed proinflammatory effects in macrophages as demonstrated by increased expressions of cytokine and chemokines, as well as enhanced NF-κB promoter activity. Overexpression of Lncenc1 promoted the releases of IL-1β and IL-18, and Caspase-1 activity in macrophages, suggesting a role in inflammasome activation. Consistently, knockdown of Lncenc1 inhibited inflammasome activation in LPS-treated macrophages. Moreover, knockdown of Lncenc1 using antisense oligo (ASO)-loaded exosomes (EXO) attenuated LPS-induced lung inflammation in mice. Similarly, Lncenc1 deficiency protects mice from bacteria-induced lung injury and inflammasome activation. Taken together, our work identified Lncenc1 as a modulator of inflammasome activation in macrophages during bacterial infection. Our study suggested that Lncenc1 could serve as a therapeutic target for lung inflammation and injury.
GPx3 deficiency exacerbates maladaptive right ventricular remodeling in experimental pulmonary artery banding
Authors: Covington Taylor A. , Pilz Patrick M. , Mulhern Ryan M. , Ngoy Soeun , Loscalzo Alex , Liu Jing , Fisch Sudeshna , Grune Jana
Published: March 2023

The stressed right ventricle (RV) is particularly susceptible to producing and accumulating reactive oxygen species, leading to extracellular matrix deposition and secretion of natriuretic peptides. The role of specific enzymes with antioxidative capacity, like glutathione peroxidase 3 (GPx3), in RV pathogenesis is currently unknown. Here, we use a murine model of pulmonary artery banding (PAB) to study the role of GPx3 in isolated RV pathology. Compared with wild-type (WT) mice undergoing PAB surgery, GPx3-deficient PAB mice presented with higher RV systolic pressure and higher LV eccentricity indices. PAB-induced changes in Fulton’s Index, RV free wall thickness, and RV fractional area change were more pronounced in GPx3-deficient mice compared with WT controls. Adverse RV remodeling was enhanced in GPx3-deficient PAB animals, evidenced by increased RV expression levels of connective tissue growth factor ( CTGF), transforming growth factor-β ( TGF-β), and atrial natriuretic peptide ( ANP). In summary, GPx3 deficiency exacerbates maladaptive RV remodeling and causes signs of RV dysfunction.
Sepsis: network pathophysiology and implications for early diagnosis
Authors: Arora Jaskirat , Mendelson Asher A. , Fox-Robichaud Alison
Published: March 2023

Sepsis, a medical emergency, is the overwhelming host response to infection leading to organ failure. The pathophysiology of this heterogeneous disease includes an inflammatory response that stimulates a complex interaction between endothelial and complements with associated coagulation abnormalities. Despite a more comprehensive understanding of sepsis pathophysiology, there exists a translational gap to improve sepsis diagnosis clinically. Many of the proposed biomarkers to diagnose sepsis lack sufficient specificity and sensitivity to be used in routine clinical practice. There has also been a lack of progress in diagnostic tools due to the focus on the inflammatory pathway. Inflammation and coagulation are known to be linked to the innate immune response. Early immunothrombotic changes could result in the early switch from infection to sepsis and aid in sepsis diagnosis. This review integrates both preclinical and clinical studies that highlight sepsis pathophysiology providing a framework for how the development of immunothrombosis could be used as a starting point to investigate biomarkers for early sepsis diagnosis.
Attenuated cardiac autonomic function in humans with high-affinity hemoglobin and compensatory polycythemia
Authors: Pruter Wyatt W. , Klassen Stephen A. , Dominelli Paolo B. , Wiggins Chad C. , Senefeld Jonathon W. , Roy Tuhin K. , Joyner Michael J. , Baker Sarah E.
Published: March 2023

During hypoxic exposure, humans with high-affinity hemoglobin (and compensatory polycythemia) have blunted increases in heart rate compared with healthy humans with typical oxyhemoglobin dissociation curves. This response may be associated with altered autonomic control of heart rate. Our hypothesis-generating study aimed to investigate cardiac baroreflex sensitivity and heart rate variability among nine humans with high-affinity hemoglobin [6 females, O2 partial pressure at 50% [Formula: see text] (P50) = 16 ± 1 mmHg] compared with 12 humans with typical affinity hemoglobin (6 F, P50 = 26 ± 1 mmHg). Participants breathed normal room air for a 10-min baseline, followed by 20 min of isocapnic hypoxic exposure, designed to lower the arterial partial pressure O2 ([Formula: see text]) to ∼50 mmHg. Beat-by-beat heart rate and arterial blood pressure were recorded. Data were averaged in 5-min periods throughout the hypoxia exposure, beginning with the last 5 min of baseline in normoxia. Spontaneous cardiac baroreflex sensitivity and heart rate variability were determined using the sequence method and the time and frequency domain analyses, respectively. Cardiac baroreflex sensitivity was lower in humans with high-affinity hemoglobin than controls at baseline and during isocapnic hypoxic exposure (normoxia: 7 ± 4 vs. 16 ± 10 ms/mmHg, hypoxia minutes 15–20: 4 ± 3 vs. 14 ± 11 ms/mmHg; group effect: P = 0.02, high-affinity hemoglobin vs. control, respectively). Heart rate variability calculated in both the time (standard deviation of the N-N interval) and frequency (low frequency) domains was lower in humans with high-affinity hemoglobin than in controls (all P < 0.05). Our data suggest that humans with high-affinity hemoglobin may have attenuated cardiac autonomic function.
Icing after skeletal muscle injury with necrosis in a small fraction of myofibers limits inducible nitric oxide synthase-expressing macrophage invasion and facilitates muscle regeneration
Authors: Nagata Itsuki , Kawashima Masato , Miyazaki Anna , Miyoshi Makoto , Sakuraya Tohma , Sonomura Takahiro , Oyanagi Eri , Yano Hiromi , Arakawa Takamitsu
Published: March 2023

Growing evidence from animal experiments suggests that icing after skeletal muscle injury is harmful to muscle regeneration. However, these previous experimental models yielded massive necrotic myofibers, whereas muscle injury with necrosis in a small myofiber fraction (<10%) frequently occurs in human sports activities. Although macrophages play a proreparative role during muscle regeneration, they exert a cytotoxic effect on muscle cells through an inducible nitric oxide synthase (iNOS)-mediated mechanism. In this study, we established an animal injury model with necrosis limited to a small myofiber fraction and investigated the effect of icing on muscle regeneration with a focus on macrophage-related events. Icing after muscle injury of this model resulted in an enlarged size of regenerating myofibers compared with those in untreated animals. During the regenerative process, icing attenuated the accumulation of iNOS-expressing macrophages, suppressed iNOS expression in the whole damaged muscle, and limited the expansion of the injured myofiber area. In addition, icing increased the ratio of M2 macrophages within the injured site at an earlier time point than that in untreated animals. Following these phenomena in icing-treated muscle regeneration, an early accumulation of activated satellite cells within the damaged/regenerating area occurred. The expression level of myogenic regulatory factors, such as MyoD and myogenin, was not affected by icing. Taken together, our results suggest that icing after muscle injury with necrosis limited to a small fraction of myofibers facilitates muscle regeneration by attenuating iNOS-expressing macrophage invasion, limiting muscle damage expansion, and accelerating the accumulation of myogenic cells which form regenerating myofibers.
Integrated Geoelectrical and Geological Investigation of a Quaternary Paleo-Depositional Environment in the Haripur Basin, Northern Pakistan: Implications for Groundwater System
Authors: Nisar Umair Bin , Ehsan Siddique Akhtar , Farooq Muhammad , Pant Ramesh Raj , Khan Nangyal Ghani , Qaiser Faizan Ur Rehman , Butt Furqan Mahmud
Published: March 2023

The deposition in Haripur basin not only provides a contemporary insight into old fluvial depositional sequences of the Himalayan foreland but also sheds light on the important continental depositions in a monsoon controlled foreland system. The present study emphasizes the evaluation of the paleo-depositional architecture for sustainable groundwater availability by utilizing a total of four field-based geological observations, eleven boreholes, and fifty-nine vertical electrical sounding (VES) datasets. The acquired surface geological data well correlate with resistivity and borehole data. The derived results of the lithostratigraphic cross-sections and spatial distribution maps reveal three-sided closure depositional. These depositional directions indicate thick successions of coarser sediments near the foothills and interbedded mixture of coarser and finer sediments toward the central and southern parts of the basin. The former conditions provide maximum groundwater yielding capacity for sustainable groundwater supply in the north-eastern and north-western parts of the basin. On the contrary, in the central and southern parts of the basin, the groundwater yielding capacities have drastically decreased due to deposition of finer sediments.
Integrated Navigation Method of Aerospace Vehicle Based on Rank Statistics
Authors: Kang Jun , Xiong Zhi , Wang Rong , Zhang Xinrui
Published: March 2023

The large dynamic and high-speed flight of aerospace vehicle will bring unpredictable conditions to its navigation system, resulting in that its system random noise probability distribution will no longer meet the preconditions of Gaussian distribution preset by the existing filter algorithm, thus reducing the accuracy of the navigation system. So, it is very important to propose an effective method to solve the filter problem of the navigation system in non-Gaussian distribution to improve the accuracy of the navigation system. Therefore, an integrated navigation method of aerospace vehicle based on rank statistics (LRF) has been proposed in this paper. Firstly, based on the flight characteristics of aerospace vehicles, an accurate gravity calculation model has been established to improve the accuracy of system modelling. Then, the state equation and measurement equation of integrated navigation system have been established. In combination with the rank filter algorithm as well as the determined weights, sampling points are calculated and nonlinearly propagated through the transition matrix to achieve an accurate estimation about the predicted values of the state quantities and measurement quantities and the covariance matrix. In turn, it simulates the probability distribution of the system state effectively. Therefore, when the system random noise probability distribution of the aerospace vehicle does not meet the Gaussian distribution due to various interference factors in the actual flight process, the algorithm can simulate the probability distribution of the actual system to the greatest extent, to improve the accuracy of the integrated navigation system and enhance the reliability of the navigation system ultimately.
Social Media, New Cultures, and New Threats: Impact on University Students in Bangladesh
Authors: Ferdous Ashfaq , Huda Zeenat
Published: March 2023

In addition to its use as an effective means of communication, the versatility of social media—probably the most salient technological development of recent times—has gradually increased its popularity over the years. But while it has been instrumental in the emergence of numerous new cultures, the use of social media has also posed a number of threats to individuals, societies, countries, and the world as a whole. It has been revealed through various literature reviews that no specific research has been done before on social media regarding its ability to simultaneously create new cultures and new threats. Therefore, the current research was conducted among university-level students in Bangladesh keeping this issue in mind. The study was designed in light of an appropriate theoretical framework, and as part of the quantitative method, an online survey was carried out to collect data from 217 university students who are studying at different public and private universities in the country. Besides, case studies were administered to 20 students for in-depth understanding. Findings uncovered that most romantic relationships formed through social media are problematic and many people have had bad experiences with such relationships. Most participants are victims of cyberstalking and varied forms of harassment and social stigma. In spite of being an epoch-making medium for education, its use is also responsible for the poor academic performance of many students, and despite its emergence as a new platform for journalism, social media has boosted yellow journalism as well. While its use in product marketing has grown exponentially and shown considerable positive impact, consumer fraud has also become common. Furthermore, although the number of social media entrepreneurs is constantly increasing and many are succeeding, the number of failures is not insignificant. It is evident from the research that the negative impact of social media use is expanding day by day in new directions, and it is urgent to ensure its proper use for the greater good.
Power Optimization for Mixed Polarity Reed–Muller Circuits Based on Multilevel Adaptive Memetic Algorithm
Authors: Zhou Yuhao , He Zhenxue , Zhang Yan , Liu Jia , Wang Tao , Xiao Limin , Wang Xiang
Published: March 2023

Power optimization can reduce heat dissipation costs and has become an important step of circuit logic synthesis. Because the power optimization for mixed polarity Reed–Muller (MPRM) circuits is a combinatorial optimization problem, in this paper, we first propose a multilevel adaptive memetic algorithm (MAMA), which includes global exploration optimizer, local heuristic optimizer, and initial population optimizer. We use the proposed differential evolution optimization, simulated annealing optimization, and data matching algorithm to make the population evolve. Moreover, based on the proposed matrix decomposition strategy and parallel polarity conversion algorithm, we propose a power optimization approach (POA) for MPRM circuits, which searches for an MPRM circuit with a minimum power using the MAMA. Experimental results demonstrated the effectiveness and superiority of the POA in optimizing the power of MPRM circuits.
Evaluation of Autism Spectrum Disorder Based on the Healthcare by Using Artificial Intelligence Strategies
Authors: Sundas Amit , Badotra Sumit , Rani Shalli , Gyaang Raymond
Published: March 2023

The behaviors of children with autism spectrum disorder (ASD) are often erratic and difficult to predict. Most of the time, they are unable to communicate effectively in their own language. Instead, they communicate using hand gestures and pointing phrases. Because of this, it can be difficult for caregivers to grasp their patients’ requirements, although early detection of the condition can make this much simpler. Assistive technology and the Internet of Things (IoT) can alleviate the absence of verbal and nonverbal communication in the community. The IoT‐based solutions use machine Learning (ML) and deep learning (DL) algorithms to diagnose and enhance the lives of patients. A thorough review of ASD techniques in the setting of IoT devices is presented in this research. Identifying important trends in IoT‐based health care research is the primary objective of this review. There is also a technical taxonomy for organizing the current articles on ASD algorithms and methodologies based on different factors such as AI, SS network, ML, and IoT. On the basis of criteria such as accuracy and sensitivity, the statistical and operational analyses of the examined ASD techniques are presented.
Risk and Protective Factors for Cancer Mortality among United States Service Members and Veterans (2001–2018)
Authors: Sharifian Neika , Carey Felicia R. , Seay Julia S. , Castañeda Sheila F. , Boyko Edward J. , Rull Rudolph P. ,   for the Millennium Cohort Study Team
Published: March 2023

Background:

Prior research linking military factors with cancer-specific mortality has shown inconsistent findings, with few studies examining these associations among U.S. service members and veterans who served in Operation Iraqi Freedom/Operation Enduring Freedom conflicts.

Methods:

Cancer mortality between 2001 and 2018 was ascertained from the Department of Defense Medical Mortality Registry and National Death Index for 194,689 Millennium Cohort Study participants. Cause-specific Cox proportional hazard models were used to examine links between military characteristics and cancer mortality [overall, early (<45 years), and lung].

Results:

Compared with individuals who deployed with no combat experiences, non-deployers had a greater risk of overall [HR = 1.34; 95% confidence interval (CI) = 1.01–1.77] and early cancer mortality (HR = 1.80; 95% CI = 1.06–3.04). Enlisted individuals had a greater risk of lung cancer mortality compared with officers (HR = 2.65; 95% CI = 1.27–5.53). No associations by service component, branch, or military occupation and cancer mortality were observed. Higher education was associated with reduced overall, early and lung cancer mortality risk and smoking and life stressors were associated with elevated overall and lung cancer mortality risk.

Conclusions:

These findings are consistent with the healthy deployer effect in which military personnel who were deployed tend to be healthier than those who did not deploy. Further, these findings highlight the importance of considering socioeconomic factors, such as military rank, that may have long-term implications for health.

Impact:

These findings highlight military occupational factors that may predict long-term health outcomes. Additional work is necessary to investigate more nuanced environmental and occupational military exposures and cancer mortality.