bluuebunny/crossref_metadata_2025 huggingface dataset:
Single immunizations of self-amplifying or non-replicating mRNA-LNP vaccines control HPV-associated tumors in mice
Authors: Ramos da Silva Jamile , Bitencourt Rodrigues Karine , Formoso Pelegrin Guilherme , Silva Sales Natiely , Muramatsu Hiromi , de Oliveira Silva Mariângela , Porchia Bruna F. M. M. , Moreno Ana Carolina Ramos , Aps Luana Raposo M. M. , Venceslau-Carvalho Aléxia Adrianne , Tombácz István , Fotoran Wesley Luzetti , Karikó Katalin , Lin Paulo J. C. , Tam Ying K. , de Oliveira Diniz Mariana , Pardi Norbert , de Souza Ferreira Luís Carlos
Published: March 2023

As mRNA vaccines have proved to be very successful in battling the coronavirus disease 2019 (COVID-19) pandemic, this new modality has attracted widespread interest for the development of potent vaccines against other infectious diseases and cancer. Cervical cancer caused by persistent human papillomavirus (HPV) infection is a major cause of cancer-related deaths in women, and the development of safe and effective therapeutic strategies is urgently needed. In the present study, we compared the performance of three different mRNA vaccine modalities to target tumors associated with HPV-16 infection in mice. We generated lipid nanoparticle (LNP)–encapsulated self-amplifying mRNA as well as unmodified and nucleoside-modified non-replicating mRNA vaccines encoding a chimeric protein derived from the fusion of the HPV-16 E7 oncoprotein and the herpes simplex virus type 1 glycoprotein D (gDE7). We demonstrated that single low-dose immunizations with any of the three gDE7 mRNA vaccines induced activation of E7-specific CD8
+
T cells, generated memory T cell responses capable of preventing tumor relapses, and eradicated subcutaneous tumors at different growth stages. In addition, the gDE7 mRNA-LNP vaccines induced potent tumor protection in two different orthotopic mouse tumor models after administration of a single vaccine dose. Last, comparative studies demonstrated that all three gDE7 mRNA-LNP vaccines proved to be superior to gDE7 DNA and gDE7 recombinant protein vaccines. Collectively, we demonstrated the immunogenicity and therapeutic efficacy of three different mRNA vaccines in extensive comparative experiments. Our data support further evaluation of these mRNA vaccines in clinical trials.
Supplemental Material: Metasediments from the lower crust reveal the history of the Picuris orogeny, southwest USA
Authors: Ringwood Mary , et al.
Published: March 2023

Supplemental Data: LASS, EPMA, and XRF data. Supplemental Text: Additional information and figures.
A direct examination of microbial specialized metabolites associated with ocean sediments from Baffin Bay and the Gulf of Maine
Authors: Shaikh Arshad Ali , Verhoeven Joost T. P. , Sinha Rupesh K. , Dufour Suzanne C. , Tahlan Kapil
Published: March 2023

Specialized metabolites produced by microorganisms found in ocean sediments display a wide range of clinically relevant bioactivities, including antimicrobial, anticancer, antiviral, and anti-inflammatory. Due to limitations in our ability to culture many benthic microorganisms under laboratory conditions, their potential to produce bioactive compounds remains underexplored. However, the advent of modern mass spectrometry technologies and data analysis methods for chemical structure prediction has aided in the discovery of such metabolites from complex mixtures. In this study, ocean sediments were collected from Baffin Bay (Canadian Arctic) and the Gulf of Maine for untargeted metabolomics using mass spectrometry. A direct examination of prepared organic extracts identified 1468 spectra, of which ∼45% could be annotated using in silico analysis methods. A comparable number of spectral features were detected in sediments collected from both locations, but 16S rRNA gene sequencing revealed a significantly more diverse bacterial community in samples from Baffin Bay. Based on spectral abundance, 12 specialized metabolites known to be associated with bacteria were selected for discussion. The application of metabolomics directly on marine sediments provides an avenue for culture-independent detection of metabolites produced under natural settings. The strategy can help prioritize samples for novel bioactive metabolite discovery using traditional workflows.
Epigallocatechin-3-Gallate Decreases Hypoxia-Inducible Factor-1 in Pancreatic Cancer Cells
Authors: Hu Lijuan , Xu Xiaoqing , Chen Xijuan , Qiu Shuai , Li Qiuju , Zhang Dapeng , Wang Feng
Published: March 2023

Hypoxia-inducible factor-1 (HIF-1) is an [Formula: see text]/[Formula: see text] heterodimeric transcription factor. In normal mammalian cells, HIF-1[Formula: see text] is hydroxylated and degraded upon biosynthesis. However, HIF-1[Formula: see text] is frequently expressed in cancer and adds to cancer malignancy. In this study, we investigated whether green tea-derived epigallocatechin-3-gallate (EGCG) decreased HIF-1[Formula: see text] in pancreatic cancer cells. After MiaPaCa-2 and PANC-1 pancreatic cancer cells were exposed to EGCG in vitro, we performed a Western blot to determine native and hydroxylated HIF-1[Formula: see text], which was in turn used to assess HIF-1[Formula: see text] production. In order to assess HIF-1[Formula: see text] stability, we determined the HIF-1[Formula: see text] after MiaPaCa-2 and PANC-1 cells were switched from hypoxia to normoxia. We found that EGCG decreased both production and stability of HIF-1[Formula: see text]. Further, the EGCG-induced decrease in HIF-1[Formula: see text] reduced intracellular glucose transporter-1 and glycolytic enzymes and attenuated glycolysis, ATP production, and cell growth. Because EGCG is known to inhibit cancer-induced insulin receptor (IR) and insulin-like growth factor-1 receptor (IGF1R), we created three MiaPaCa-2 sublines whose IR, IGF1R, and HIF-1[Formula: see text] were decreased using RNA interference. From wild-type MiaPaCa-2 cells and these sublines, we found evidence that suggested that the EGCG-induced inhibition of HIF-1[Formula: see text] was both dependent on and independent of IR and IGF1R. In vivo, we transplanted wild-type MiaPaCa-2 cells in athymic mice and treated the mice with EGCG or vehicle. When the resulting tumors were analyzed, we found that EGCG decreased tumor-induced HIF-1[Formula: see text] and tumor growth. In conclusion, EGCG decreased HIF-1[Formula: see text] in pancreatic cancer cells and sabotaged the cells. The anticancer effects of EGCG were both dependent on and independent of IR and IGF1R.
NUMERICAL ANALYSIS OF SOME FRACTIONAL ORDER DIFFERENTIAL EQUATIONS VIA LEGENDRE SPECTRAL METHOD
Authors: KHAN AZIZ , NAZ HAFSA , SARWAR MUHAMMAD , SHAH KAMAL , ALQUDAH MANAR A. , ABDELJAWAD THABET
Published: March 2023

In this research paper, we find the numerical solutions of fractional order scalers and coupled system of differential equations under initial conditions using shifted Legendre polynomials. By using the properties of shifted Legendre polynomials, we establish operational matrices of integration and differentiation in order to simplify our considered problems under initial conditions. In order to check the accuracy of the proposed model, some test problems are solved along with the graphical representations. For coupled system, we applied the algorithm to the Pharmacokinetic two-compartment model. As the proposed method is computer-oriented, we use therefore the MATLAB for required calculations. Numerical results are shown graphically.
Visibility Graph-based Cache Management for DRAM Buffer Inside Solid-state Drives
Authors: Sha Zhibing , Li Jun , Zhang Fengxiang , Huang Min , Cai Zhigang , Trahay Francois , Liao Jianwei
Published: March 2023

Most solid-state drives (SSDs) adopt an on-board Dynamic Random Access Memory (DRAM) to buffer the write data, which can significantly reduce the amount of write operations committed to the flash array of SSD if data exhibits locality in write operations. This article focuses on efficiently managing the small amount of DRAM cache inside SSDs. The basic idea is to employ the visibility graph technique to unify both temporal and spatial locality of references of I/O accesses, for directing cache management in SSDs. Specifically, we propose to adaptively generate the visibility graph of cached data pages and then support batch adjustment of adjacent or nearby (hot) cached data pages by referring to the connection situations in the visibility graph. In addition, we propose to evict the buffered data pages in batches by also referring to the connection situations, to maximize the internal flushing parallelism of SSD devices without worsening I/O congestion. The trace-driven simulation experiments show that our proposal can yield improvements on cache hits by between
0.8
% and
19.8
%, and the overall I/O latency by
25.6
% on average, compared to state-of-the-art cache management schemes inside SSDs.
Exercise training rescues impaired H2O2-mediated vasodilation in porcine collateral-dependent coronary arterioles through enhanced K+ channel activation
Authors: Johnson Kalen A. , Jeffery Elise , Bray Jeff F. , Murphy Malea M. , Heaps Cristine L.
Published: March 2023

The current study reveals that coronary arterioles distal to stenosis display attenuated dilation responses to H2O2 that are restored with endurance exercise training. Enhanced H2O2 dilation after exercise is dependent on Kv and BKCa channels and at least in part on in colocalization of BKCa channel and PKA and independent of PKA dimerization. These findings expand our earlier studies which demonstrated that exercise training drives beneficial adaptive responses of reactive oxygen species in the microvasculature of the ischemic heart.
An Improved Sparrow Search Algorithm and Its Application in HIFU Sound Field
Authors: Yang Yihao , Tao Jinxu , Zhou Jiayu , Wang Jiaqi , Guo Xinyu
Published: March 2023

The sparrow search algorithm (SSA) is a novel swarm intelligence optimization algorithm. It has a fast convergence speed and strong global search ability. However, SSA also has many shortcomings, such as the unstable quality of the initial population, easy to fall into the local optimal solution, and the diversity of the population decreases with the iterative process. In order to solve these problems, this paper proposes an improved sparrow search algorithm (ISSA). ISSA uses Chebyshev chaotic map and elite opposition‐based learning strategy to initialize the population and improve the quality of the initial population. In the process of producer location update, dynamic weight factor and Levy flight strategy are introduced to avoid falling into a local optimal solution. The mutation strategy is applied to the scrounger location update process, and the mutation operation is performed on individuals to increase the diversity of the population. In order to verify the feasibility and effectiveness of ISSA, it is tested on 23 benchmark functions. The results show that compared with other seven algorithms, ISSA has higher convergence accuracy, faster convergence speed, and stronger stability. Finally, ISSA is used to optimize the sound field of high‐intensity focused ultrasound (HIFU). The results show that ISSA can effectively improve the focusing performance and reduce the influence of sound field sidelobe, which is of great benefit for HIFU treatment.
Passenger Flow Scale Prediction of Urban Rail Transit Stations Based on Multilayer Perceptron (MLP)
Authors: Lin Luzhou , Gao Yuezhe , Cao Bingxin , Wang Zifan , Jia Cai
Published: March 2023

Accurately predicting passenger flow at rail stations is an effective way to reduce operation and maintenance costs, improve the quality of passenger travel while meeting future passenger travel demand. The improvement of data acquisition capability allows fine-grained and large-scale built environment data to be extracted. Therefore, this paper focuses on investigating the relationship between the built environment around the station and the station passenger flow and discusses whether the built environment data can be applied to the station passenger flow prediction. Firstly, the evaluation system of station passenger flow influencing factors is built based on multisource data. The inner relationship between built environment factors and station passenger flow is investigated using the Pearson correlation analysis. Based on this, a multilayer perceptron (MLP)-based passenger flow prediction model was developed to predict the passenger flow at key stations. The study results show that the built environment factors impact station passenger flow, and the MLP prediction model has better prediction accuracy and applicability. The results of the study can be applied to predict the passenger flow scale of rail stations without historical passenger flow data and thus are also applicable to new rail stations.
Machine Learning for Promoting Environmental Sustainability in Ports
Authors: Mansoursamaei Meead , Moradi Mahmoud , González-Ramírez Rosa G. , Lalla-Ruiz Eduardo
Published: March 2023

Maritime transportation is one of the essential drivers of the global economy as it enables both lower transportation costs and intermodal operations across multiple forms of transportation. Maritime ports are essential interfaces that support cargo handling between sea and hinterland transportation. Besides, in this area, environmental protection is becoming extremely important. Global warming, air pollution, and greenhouse gas emissions are all having a detrimental influence on the environment and will most likely continue to do so for future generations. Hence, there is a growing need to promote environmental sustainability in maritime-based transportation. The application of machine learning (ML), as one of the main subdomains of artificial intelligence (AI), can be considered a component within the process of digital transformation to advance green activities in maritime port logistics. Thus, this article presents the results of a systematic literature review of the recent literature on machine learning for promoting environmentally sustainable maritime ports. It collects and analyses the articles whose contributions lie in the interplay between three main dimensions, i.e., machine learning, port-related operations, and environmental sustainability. Throughout a review protocol, this research is constituted on the major focuses of impact, problems, and techniques to discern the current state of the art as well as research directions. The research findings indicate that the articles using polynomial regression models are dominant in the literature, and the recurrent neural network (RNN) and long short-term memory (LSTM) are the most recent approaches. Moreover, in terms of environmental sustainability, emissions and energy consumption are the most studied problems. mAccording to the research gaps observed in the review, two broad directions for future research are identified: (i) altering attention on a greater diversity of machine learning approaches for promoting environmental sustainability in ports and (ii) leveraging new outlooks to perform more green practical works on port-related operations.
Association of MicroRNA-146a with Type 1 and 2 Diabetes and their Related Complications
Authors: Ghaffari Mahyar , Razi Sara , Zalpoor Hamidreza , Nabi-Afjadi Mohsen , Mohebichamkhorami Fariba , Zali Hakimeh
Published: March 2023

Most medical investigations have found a reduced blood level of miR-146a in type 2 diabetes (T2D) patients, suggesting an important role for miR-146a (microRNA-146a) in the etiology of diabetes mellitus (DM) and its consequences. Furthermore, injection of miR-146a mimic has been confirmed to alleviate diabetes mellitus in diabetic animal models. In this line, deregulation of miR-146a expression has been linked to the progression of nephropathy, neuropathy, wound healing, olfactory dysfunction, cardiovascular disorders, and retinopathy in diabetic patients. In this review, besides a comprehensive review of the function of miR-146a in DM, we discussed new findings on type 1 (T1MD) and type 2 (T2DM) diabetes mellitus, highlighting the discrepancies between clinical and preclinical investigations and elucidating the biological pathways regulated through miR-146a in DM-affected tissues.
Bimetallic CoMoO4 Nanosheets on Freestanding Nanofiber as Wearable Supercapacitors with Long-Term Stability
Authors: Khadka Ashwin , Samuel Edmund , Joshi Bhavana , Kim Yong Il , Aldalbahi Ali , El-Newehy Mohamed , Lee Hae-Seok , Yoon Sam S.
Published: March 2023

Currently, lightweight wearable energy storage devices are in great demand owing to their use in wearable electronics and energy-efficient electric vehicles. Freestanding carbon nanofibers replace the need for metal substrates while providing a rapid electrical network owing to their excellent electrical properties. Bimetallic oxides with multivalent oxidation states facilitate the rapid transfer of electrolytic ions owing to efficient Faradaic reactions, thereby enhancing the overall energy storage capability. In this study, CoOx@CNF was derived from ZIF-67 (zeolitic-imidazolate framework) @PAN-2MI fibers that were stabilized in air at 280°C and then annealed in argon at 900°C. Subsequently, Co was seeded on the annealed CoOx@CNF and subjected to a hydrothermal process in sodium molybdate dihydrate solution to grow CoMoO4 nanosheets, eventually forming bimetallic CoMoO4@CNF. The concentration of sodium molybdate solution was varied to determine the optimal growth conditions for CoMoO4 nanosheets. The energy density of the optimal bimetallic CoMoO4@CNF sample was 166.5 μWh cm-2 at a power density of 200 μW cm-2; this represented a nearly twofold increase compared to that of the single metallic CoOx@CNF. Powering humidity sensors using only one CoMoO4@CNF supercapacitor was demonstrated. The optimal sample remained stable during long-term galvanostatic charge and discharge cycles (

N

cyc

=
30,000

) and retained 100% of its specific capacitance.
Nutritional, Physicochemical, Functional, and Textural Properties of Red Pepper (Capsicum annuum L.), Red Onion (Allium cepa), Ginger (Zingiber officinale), and Garlic (Allium sativum): Main Ingredients for the Preparation of Spicy Foods in Ethiopia
Authors: Kefale Biadge , Delele Mulugeta Admasu , Fanta Solomon Workneh , Mekonnen Abate Solomon
Published: March 2023

Spices are known to have important benefits in our daily diet, and it is common to see industrial and traditional spicy foods in our households and markets. In the present work, a systematic profiling of the nutritional, physicochemical, and textural properties of red pepper, garlic, red onion, and ginger was conducted. The detailed data of forty eight (48) parameters that consisted of macronutrients, micronutrients, physicochemical properties, functional property, and rheological properties of each of the components were organized. The result showed that red pepper had the highest content of crude protein (14.7%), crude fat (11.3%), crude fiber (38.57%), ash (6.7%), redness (a

∗

value) (32.5), CI (37.4%), and porosity (37.43%) compared to garlic, ginger, and red onion. Garlic had the highest content of carbohydrate content (76.42%), energy (346.58 kcal), pH (6.03), total soluble solid (26.76), particle size (D90, 561 µm), and volume weighted mean (238 µm) which is related to the high antimicrobial and antioxidant quality of garlic. Red onion had the highest content of Zn (71.16 mg/100 g), Na (94.5 mg/100 g), and Ca (71.16 mg/100 g) indicating that it is a rich source of minerals. The availability of data about the nutritional, physicochemical, functional, and textural properties of the ingredients is crucial for the production and formulation of industrial and traditional spicy foods with the highest quality and stability.
Differentially Expressed Genes Analysis in the Human Small Airway Epithelium of Healthy Smokers Shows Potential Risks of Disease Caused by Oxidative Stress and Inflammation and the Potentiality of Astaxanthin as an Anti-Inflammatory Agent
Authors: Pratomo Irandi Putra , Tedjo Aryo , Noor Dimas R. , Rosmalena
Published: March 2023

Cigarette smoke (CS) was known for its effect of increasing oxidative stress that could trigger tissue injury and endothelial dysfunction mediated by free radicals and reactive oxygen species (ROS). ROS itself is a key signaling molecule that plays a role in the development of inflammatory disorders. Nuclear factor erythroid2 related factor2 (Nrf2) is the main regulator of antioxidant cellular response to cell and tissue-destroying components caused by CS. Nrf2 protein that is significantly activated in the smokers’ small airway epithelium is followed by a series of gene expression changes in the same cells. This study aims to observe differentially expressed genes (DEGs) in the human small airway epithelium of smokers compared to genes whose expression changes due to astaxanthin (AST) treatment, an antioxidant compound that can modulate Nrf2. Gene expression data that was stored in the GEO browser (GSE 11952) was analyzed using GEO2R to search for DEG among smokers and nonsmokers subject. DEG was further compared to those genes whose expression changes due to astaxanthin treatment (AST) that were obtained from the Comparative Toxicogenomics Database (CTD; https://ctdbase.org/). DEG (

p
<
0.05

) analysis result shows that there are 23 genes whose expression regulation is reversed compared to gene expression due to AST treatment. The gene function annotations of the 23 DEGs showed the involvement of some of these genes in chemical and oxidative stress, reactive oxygen species (ROS), and apoptotic signaling pathways. All of the genes were involved/associated with chronic bronchitis, adenocarcinoma of the lung, non-small-cell lung carcinoma, carcinoma, small cell lung carcinoma, type 2 diabetes mellitus, emphysema, ischemic stroke, lung diseases, and inflammation. Thus, AST treatment for smokers could potentially decrease the development of ROS and oxidative stress that leads to inflammation and health risks associated with smoking.
Noninvasive Brain Stimulation for Cancer Pain Management in Nonbrain Malignancy: A Meta-Analysis
Authors: Chien Yung-Jiun , Chang Chun-Yu , Wu Meng-Yu , Chien Yung-Chen , Wu Hsin-Chi , Horng Yi-Shiung
Published: March 2023

Purpose. Noninvasive brain stimulation (NIBS) has been reported to have analgesic effects on fibromyalgia and chronic neuropathic pain; however, its effects on cancer pain have yet to be determined. The present study aimed to evaluate the effects of NIBS on patients with pain secondary to nonbrain malignancy. Methods. Electronic databases including PubMed, Embase, Cochrane Library, and Web of Science were searched from inception through June 5th, 2022. Parallel, randomized, placebo-controlled studies were included that enrolled adult patients with cancer pain, except for that caused by brain tumors, compared NIBS with placebo stimulation, and reported sufficient data for performing meta-analysis. Results. Four parallel, randomized, sham-controlled studies were included: two of repetitive transcranial magnetic stimulation (rTMS), one of transcranial direct current stimulation (tDCS), and one of cranial electrical stimulation (CES). rTMS significantly improved pain in the subgroup analysis (standardized mean difference (SMD): −1.148, 95% confidence interval (CI): −1.660 to −0.637, (

p
<
0.001

)), while NIBS was not benefited in reducing pain intensity (SMD: −0.632, 95% CI: −1.356 to 0.092, p = 0.087). Also, NIBS significantly improved depressive symptoms (SMD: −0.665, 95% CI: −1.178 to −0.153, p = 0.011), especially in the form of rTMS (SMD: −0.875, 95% CI: −1.356 to −0.395,

p
<
0.001

) and tDCS (SMD: −1.082, 95% CI: −1.746 to −0.418, p = 0.001). Conclusion. rTMS significantly improved pain secondary to nonbrain malignancy apart from other forms of NIBS without major adverse events.
Assessing the Impact of Common Cause Failures on Site Risk within Level 1 Multi-Unit PSA
Authors: Coleman James F. , Boafo Emmanuel K. , Yamoah S. , Ameyaw F.
Published: March 2023

Common cause failures (CCFs) may lead to the simultaneous unavailability or failure of numerous components in the nuclear power plant because of the existence of a shared cause when an initiating event disrupts the normal functioning of nuclear power plants. The presence of common cause failures (intra-unit and inter-unit) can be recognized in a multi-unit probabilistic safety assessment (MUPSA) as a crucial dependency factor that can influence accident scenarios and the core damage frequency (CDF), as CCF may affect the availability and proper operation of mitigating systems. Since such failures are likely to significantly undermine the benefits of the concept of redundancy in nuclear power plant systems, it is necessary to identify the CCFs that contribute to the core damage in a multi-unit site and analyse their overall quantitative magnitude and qualitative proportions. In this study, a twin-unit generic pressurized water reactor (PWR) nuclear plant is modeled using the AIMS-PSA software. For the loss-of-offsite-power (LOOP) and station blackout (SBO) events, the site CDF was calculated, and the cut-sets produced by this quantification were examined for the modeled CCF basic events in the fault trees. The quantitative and qualitative contributions of the CCFs to the frequency of site core damage were examined. CCFs in the modeled fault trees contributed to 4.58% to the site CDF of the combined LOOP followed by SBO event. In the LOOP event alone that leads to core damage, the CCF contributed 4.58% to the site CDF while CCFs contributed 17.19% to the site CDF in the SBO event alone that leads to core damage. With CCF events considered in the modeling process, the site CDF estimated with CCF events increased by 7.53% in the combined LOOP followed by SBO event. In the LOOP event alone that leads to core damage, inclusion of CCF events in the modeling increased the site CDF by 7.42%. A 15.66% increase in site CDF was recorded in the SBO event alone that leads to core damage as compared to modeling without CCF events. The results show how crucial the common cause failure contribution is to site CDF. The safety of the nuclear plant at a site is impacted by an increase in site CDF when common cause failures are considered. The various CCF fundamental event compositions and their percentage contributions were explicitly examined by the minimal cut-sets which leads to core damage in the units. In conclusion, this study’s findings can help us better understand how CCFs increase multi-unit site risk and can also act as a starting point for future studies on the qualitative and quantitative categorizations of CCF effects within MUPSA.
Multiround Transfer Learning and Modified Generative Adversarial Network for Lung Cancer Detection
Authors: Chui Kwok Tai , Gupta Brij B. , Jhaveri Rutvij H. , Chi Hao Ran , Arya Varsha , Almomani Ammar , Nauman Ali
Published: March 2023

Lung cancer has been the leading cause of cancer death for many decades. With the advent of artificial intelligence, various machine learning models have been proposed for lung cancer detection (LCD). Typically, challenges in building an accurate LCD model are the small‐scale datasets, the poor generalizability to detect unseen data, and the selection of useful source domains and prioritization of multiple source domains for transfer learning. In this paper, a multiround transfer learning and modified generative adversarial network (MTL‐MGAN) algorithm is proposed for LCD. The MTL transfers the knowledge between the prioritized source domains and target domain to get rid of exhaust search of datasets prioritization among multiple datasets, maximizing the transferability with a multiround transfer learning process, and avoiding negative transfer via customization of loss functions in the aspects of domain, instance, and feature. In regard to the MGAN, it not only generates additional training data but also creates intermediate domains to bridge the gap between the source domains and target domains. 10 benchmark datasets are chosen for the performance evaluation and analysis of the MTL‐MGAN. The proposed algorithm has significantly improved the accuracy compared with related works. To examine the contributions of the individual components of the MTL‐MGAN, ablation studies are conducted to confirm the effectiveness of the prioritization algorithm, the MTL, the negative transfer avoidance via loss functions, and the MGAN. The research implications are to confirm the feasibility of multiround transfer learning to enhance the optimal solution of the target model and to provide a generic approach to bridge the gap between the source domain and target domain using MGAN.
Determination of Rock Tensile Strength Based on Arc Loading Splitting Test considering Modulus Effect
Authors: Teng Guirong , Wang Xiaodong , Zhao Zenghui , Sun Zhuoxiu
Published: March 2023

Tensile strength is an important control parameter for the design and stability analysis in rock engineering. In order to reveal the influence of elastic modulus on tensile strength test results, Brazilian splitting tests were carried out on specimens with different strengths, such as mudstone, white sandstone, green sandstone, red sandstone, and marble. Longitudinal and transverse strains were monitored to analyze the influence of elastic modulus on the maximum contact angle and peak contact load between head and disc. A numerical model of Brazilian splitting tests was built, and the contact load between the head and rock disc were detailed revealed. Based on the experimental and numerical results, a modified formula to calculate tensile strength considering the modulus effect was proposed theoretically. Results show that the maximum pressure between the head and disc increases and the contact angle decreases with the increasing of elastic modulus, which show great influence on the splitting failure; the distribution of contact load can be divided into three types: parabolic I, sinusoidal, and parabolic II, which are suitable for soft rock, medium-hard rock, and hard rock, respectively; the new models can improve the calculation accuracy of rock tensile strength.
High School Students’ Depression Literacy about Interventions and Prevention: A Survey in Tehran
Authors: Khorrami Zahra , Sayarifard Azadeh , Ghahari Shahrbanoo , Memaryan Nadereh , Pirmoradi Mohammadreza , Ghadirian Laleh
Published: March 2023

Background. Given the high prevalence of depressive disorders in the present world and the lack of adequate awareness about prevention and appropriate interventions, increasing mental health literacy is vital for promoting mental health to reduce depression and its consequences. Methods. In this descriptive cross-sectional study, participants were recruited among the second high school students in the 2018-2019 academic year. The sample size was 2038, and samples were selected by multistage cluster sampling from different areas of Tehran. Demographic variables like age, gender, level of education, and parents’ characteristics and mental health literacy questions in treatment and prevention areas were evaluated. Results. Analyses showed that of high school students, 83% considered getting help from psychiatrists and 80% considered learning stress management as the best preventive measures, while as the best treatment measures, 79.5% considered counseling the best place to refer for visiting a professional and 45% selected general counseling centers. Conclusion. The study results showed that high school students have a positive attitude toward preventing and treating depressive disorders, getting help from specialists, and useful measures for depressed people. But they did not know enough about preventive measures, including learning effective coping skills, reading self-help books, and continuing to take psychiatric medications. Planning and providing the necessary training are important, especially for high school students.
Mathematical Model and Analysis on the Impacts of Vaccination and Treatment in the Control of the COVID-19 Pandemic with Optimal Control
Authors: Ayalew Alemzewde , Molla Yezbalem , Tilahun Tenaw , Tesfa Tadele
Published: March 2023

In this study, a nonlinear deterministic mathematical model that evaluates two important therapeutic measures of the COVID-19 pandemic: vaccination of susceptible and treatment for infected people who are in quarantine, is formulated and rigorously analyzed. Some of the fundamental properties of the model system including existence and uniqueness, positivity, and invariant region of solutions are proved under a certain meaningful set. The model exhibits two equilibrium points: disease-free and endemic equilibrium points under certain conditions. The basic reproduction number,

R

0

, is derived via the next-generation matrix approach, and the dynamical behavior of the model is explored in detail. The analytical analysis reveals that the disease-free equilibrium solution is locally as well as globally asymptotically stable when the associated basic reproduction number is less than unity which indicates that COVID-19 dies out in the population. Also, the endemic equilibrium point is globally asymptotically stable whenever the associated basic reproduction number exceeds a unity which implies that COVID-19 establishes itself in the population. The sensitivity analysis of the basic reproduction number is computed to identify the most dominant parameters for the spreading out as well as control of infection and should be targeted by intervention strategies. Furthermore, we extended the considered model to optimal control problem system by introducing two time-dependent variables that represent the educational campaign to susceptibles and continuous treatment for quarantined individuals. Finally, some numerical results are illustrated to supplement the analytical results of the model using MATLAB ode45.
Anti-dsDNA Is Associated with Favorable Prognosis in Myasthenia Gravis: A Retrospective Study
Authors: Li Shiyin , Chen Jiaxin , Yang Xu , Huang Xin , Wang Haiyan , Feng Huiyu
Published: March 2023

Objectives. To investigate the presence of serum antinuclear antibody (ANA) and anti-double-stranded DNA antibody (anti-dsDNA) in patients with myasthenia gravis (MG) and analyze the clinical characteristics and prognostic factors associated with MG. Methods. We retrospectively enrolled 363 patients with MG and analyzed the clinical characteristics and follow-up data between patients positive and negative for ANA and anti-dsDNA. We defined a Myasthenia Gravis Activities of Daily Living (MG-ADL) reduction as a main prognosis predictor and used logistic regression to determine independent factors associated with prognosis. We built a nomogram to predict prognosis and evaluate the internal validity of the model. Results. Ninety-eight (27.0%) patients were positive for ANA, and 51 (14.0%) were positive for anti-dsDNA. Patients positive for ANA and anti-dsDNA antibodies tended to be female and positive for acetylcholine receptor antibody (AChR-Ab). The rate of thymoma was higher in anti-dsDNA-positive patients with MG (p-dsDNA-MG) than in patients negative for anti-dsDNA (49.0% vs. 26.0%,

p
=
0.001

), and p-dsDNA-MG was associated with reduced MG-ADL score. Regression analysis showed that except for age of onset (

OR
=
0.986

,

95
%
CI
=
0.973
–
0.999

,

p
=
0.037

), anti-dsDNA (

OR
=
2.800

,

95
%
CI
=
1.381
–
5.679

,

p
=
0.004

), ptosis (

OR
=
2.930

,

95
%
CI
=
1.827
–
4.699

,

p
<
0.001

), and eye movement disorder (

OR
=
2.815

,

95
%
CI
=
1.672
–
4.741

,

p
<
0.001

) were independent predictive factors of a favorable prognosis of MG. These predictors were used to generate a nomogram with an excellent predictive value. Conclusions. Being female and the presence of AChR-Ab were features of ANA- or anti-dsDNA-positive MG. The presence of anti-dsDNA was associated with a favorable prognosis of MG.
Linking Physical Activity to Breast Cancer Risk via Inflammation, Part 1: The Effect of Physical Activity on Inflammation
Authors: Swain Christopher T.V. , Drummond Ann E. , Milne Roger L. , English Dallas R. , Brown Kristy A. , Lou Makayla W.C. , Boing Leonessa , Bageley Amy , Skinner Tina L. , van Roekel Eline H. , Moore Melissa M. , Gaunt Tom R. , Martin Richard M. , Lewis Sarah J. , Lynch Brigid M.
Published: March 2023

The protective effect of physical activity on breast cancer incidence may partially be mediated by inflammation. Systematic searches of Medline, EMBASE, and SPORTDiscus were performed to identify intervention studies, Mendelian randomization studies, and prospective cohort studies that examined the effects of physical activity on circulating inflammatory biomarkers in adult women. Meta-analyses were performed to generate effect estimates. Risk of bias was assessed, and the Grading of Recommendations Assessment, Development, and Evaluation system was used to determine the overall quality of the evidence. Thirty-five intervention studies and one observational study met the criteria for inclusion. Meta-analyses of randomized controlled trials (RCT) indicated that, compared with control groups, exercise interventions reduced levels of C-reactive protein (CRP) [standardized mean difference (SMD) = −0.27, 95% confidence interval (CI) = −0.62 to 0.08), tumor necrosis factor alpha (TNFα, SMD = −0.63, 95% CI = −1.04 to −0.22), interleukin-6 (IL6, SMD = −0.55, 95% CI = −0.97 to −0.13) and leptin (SMD = −0.50, 95% CI = −1.10 to 0.09). Owing to heterogeneity in effect estimates and imprecision, evidence strength was graded as low (CRP, leptin) or moderate (TNFα and IL6). High-quality evidence indicated that exercise did not change adiponectin levels (SMD = 0.01, 95% CI = −0.14 to 0.17). These findings provide support for the biological plausibility of the first part of the physical activity—inflammation—breast cancer pathway.
Linking Physical Activity to Breast Cancer via Inflammation, Part 2: The Effect of Inflammation on Breast Cancer Risk
Authors: Lou Makayla W.C. , Drummond Ann E. , Swain Christopher T.V. , Milne Roger L. , English Dallas R. , Brown Kristy A. , van Roekel Eline H. , Skinner Tina L. , Moore Melissa M. , Gaunt Tom R. , Martin Richard M. , Lewis Sarah J. , Lynch Brigid M.
Published: March 2023

This review synthesized and appraised the evidence for an effect of inflammation on breast cancer risk. Systematic searches identified prospective cohort and Mendelian randomization studies relevant to this review. Meta-analysis of 13 biomarkers of inflammation were conducted to appraise the evidence for an effect breast cancer risk; we examined the dose–response of these associations. Risk of bias was evaluated using the ROBINS-E tool and the quality of evidence was appraised with Grading of Recommendations Assessment, Development, and Evaluation. Thirty-four observational studies and three Mendelian randomization studies were included. Meta-analysis suggested that women with the highest levels of C-reactive protein (CRP) had a higher risk of developing breast cancer [risk ratio (RR) = 1.13; 95% confidence interval (CI), 1.01–1.26] compared with women with the lowest levels. Women with highest levels of adipokines, particularly adiponectin (RR = 0.76; 95% CI, 0.61–0.91) had a reduced breast cancer risk, although this finding was not supported by Mendelian randomization analysis. There was little evidence of an effect of cytokines, including TNFα and IL6, on breast cancer risk. The quality of evidence for each biomarker ranged from very low to moderate. Beyond CRP, the published data do not clearly support the role of inflammation in the development of breast cancer.
Eosinophilic Fasciitis Presenting as an Ichthyosiform Eruption of the Bilateral Ankles
Authors: Ivanov Nedyalko N. , Garvin Ashley , Mahon Michael J. , Stephenson Sean
Published: March 2023

Eosinophilic fasciitis (EF) is a rare connective tissue disease which closely resembles other scleroderma-like diseases. EF presents with painful swelling and hardening of the distal limbs and is often preceded by a history of strenuous exercise. The marked fascial fibrosis in EF can lead to joint contractures and causes significant morbidity in affected individuals. The authors present a rare case of EF presenting as an ichthyosiform eruption of the bilateral ankles with gradual improvement after the implementation of oral prednisone, hydroxychloroquine, and methotrexate.
Gastrointestinal Involvement of Eosinophilic Granulomatosis with Polyangiitis with Histological Evidence of Treatment Response
Authors: Lai Mark , He Tony , Wright Emily K.
Published: March 2023

Eosinophilic granulomatosis with polyangiitis (EGPA) is a rare systemic vasculitis of small to medium vessels. Gastrointestinal involvement is uncommon and is associated with higher mortality. Treatment is based on empiric evidence. In this article, we report a case of EGPA-related pancolitis and stricturing small bowel disease managed with a combination of mepolizumab and surgical resection.
Socially Assistive Robots for People Living with Dementia in Long-Term Facilities: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Hsieh Chia-Jung , Li Pei-Shan , Wang Chia-Hui , Lin Shu-Ling , Hsu Tzu-Chi , Tsai Chia-Mei Tsai
Published: March 2023

Background and Objective: The purpose of our study was to explore the immediate and long-term effects of socially assistive robots (SARs) on neuropsychiatric symptoms (NPSs), behavioral and psychological symptoms of dementia (BPSD), positive emotional experiences, and social interaction in older people living with dementia. Methods: We set keywords and used Boolean operators to search the CINAHL, Cochrane Library, EMBASE, IEEE Digital Library, MEDLINE, PsycINFO, PubMed, Web of Science, Scopus, and Chinese Electronic Periodical Service from inception to February 2022 for randomized controlled trials. The Cochrane Collaboration bias assessment tool was used to assess article quality, and RevMan 5.4.1 software was used to conduct the meta-analysis. Results: A total of 14 studies were included in the meta-analysis. SARs can help people living with dementia reduce their NPS of depression and anxiety, provide happiness from positive emotional experiences, and improve their social interaction through conversation. However, there was no significant improvement in agitation behavior, overall BPSD, or quality of life in people living with dementia. In follow-up, it was found that the effect of SRT was limited. Conclusion: SARs can reduce depression and increase positive emotions in people living with dementia. They may also reduce the burden on healthcare workers during the COVID-19 pandemic. This research was registered on PROSPERO CRD42020169340.
Identification of the Immune Subtypes for the Prediction of Metastasis in Pancreatic Neuroendocrine Tumors
Authors: Meng Di , Zhao Lei , Liu Jinyang , Ge Chunlin , Zhang Cheng
Published: March 2023

Introduction: Most patients with pancreatic neuroendocrine tumors (pNETs) present with unresectable or metastatic disease. Increasing evidence shows that the immune cell infiltration patterns play a pivotal role in tumor progression in pNETs. Nonetheless, there has been no comprehensive analysis of the effect of immune infiltration patterns on metastasis. Methods: The gene expression profiling dataset and clinical data were obtained from the Gene Expression Omnibus database. Estimation of Stromal and Immune Cells in Malignant Tumors using the Expression Data and single-sample Gene Set Enrichment Analysis were used to uncover the landscape of the tumor immune microenvironment. Subtypes based on the immune infiltration patterns were identified by the unsupervised clustering algorithm. Differentially expressed genes were identified using the limma packages of R. Functional enrichment analyses of these genes were carried out using STRING, Kyoto Encyclopedia of Genes and Genomes, and Reactome. Results: The landscape of immune cells in pNET samples was constructed, and three immune cell infiltration subtypes (Immunity-H, Immunity-M, and Immunity-L) were identified. Immune cell infiltration degrees and metastasis were positively correlated. A protein-protein interaction network containing 80 genes was constructed, and functional enrichment revealed that these genes were mainly enriched in immune-related pathways. Eleven metastasis-related genes were differentially expressed among three subtypes, including MMP14, MMP2, MMP12, MMP7, SPARC, MMP19, ITGAV, MMP23B, MMP1, MMP25, and MMP9. There is a certain consistency of immune infiltration pattern between the primary tumor and metastatic tumor samples. Conclusion: Our findings may deepen the understanding of the immune-mediated regulatory mechanisms underlying pNETs and may provide some promising targets for immunotherapy.
Antispoofing in face biometrics: a comprehensive study on software-based techniques
Authors: H Vinutha , G Thippeswamy
Published: March 2023

The vulnerability of the face recognition system to spoofing attacks has piqued the biometric community's interest, motivating them to develop anti-spoofing techniques to secure it. Photo, video, or mask attacks can compromise face biometric systems (types of presentation attacks). Spoofing attacks are detected using liveness detection techniques, which determine whether the facial image presented at a biometric system is a live face or a fake version of it. We discuss the classification of face anti-spoofing techniques in this paper. Anti-spoofing techniques are divided into two categories: hardware and software methods. Hardware-based techniques are summarized briefly. A comprehensive study on software-based countermeasures for presentation attacks is discussed, which are further divided into static and dynamic methods. We cited a few publicly available presentation attack datasets and calculated a few metrics to demonstrate the value of anti-spoofing techniques.
Fine grained irony classification through transfer learning approach
Authors: Shirahatti Abhinandan , Rajpurohit Vijay , Sannakki Sanjeev
Published: March 2023

Nowadays irony appears to be pervasive in all social media discussion forums and chats, offering further obstacles to sentiment analysis efforts. The aim of the present research work is to detect irony and its types in English tweets We employed a new system for irony detection in English tweets, and we propose a distilled bidirectional encoder representations from transformers (DistilBERT)light transformer model based on the bidirectional encoder representations from transformers (BERT) architecture, this is further strengthened by the use and design of bidirectional long-short term memory (Bi-LSTM) network this configuration minimizes data preprocessing tasks proposed model tests on a SemEval-2018 task 3, 3,834 samples were provided. Experiment results show the proposed system has achieved a precision of 81% for not irony class and 66% for irony class, recall of 77% for not irony and 72% for irony, and F1 score of 79% for not irony and 69% for irony class since researchers have come up with a binary classification model, in this study we have extended our work for multiclass classification of irony. It is significant and will serve as a foundation for future research on different types of irony in tweets.