bluuebunny/crossref_metadata_2025 huggingface dataset:
Low Grade Endotoxemia and Oxidative Stress in Offspring of Patients with Early Myocardial Infarction
Authors: Cinicola Bianca Laura , Palumbo Ilaria Maria , Pannunzio Arianna , Carnevale Roberto , Bartimoccia Simona , Cammisotto Vittoria , Capponi Martina , Brindisi Giulia , Salvatori Francesca , Barillà Francesco , Martino Francesco , D’Amico Alessandra , Poscia Roberto , Spalice Alberto , Zicari Anna Maria , Violi Francesco , Loffredo Lorenzo
Published: April 2023

Background and aims: Offspring of patients with early myocardial infarction are at higher cardiovascular risk, but the underlying physio-pathological mechanism is unclear. NADPH oxidase-type 2 (NOX-2) plays a pivotal role as mediator of oxidative stress and could be involved in activating platelets in these patients. Furthermore, altered intestinal permeability and serum lipopolysaccharide (LPS) could be a trigger to promote NOX-2 activation and platelet aggregation. This study aims to evaluate the behavior of low grade endotoxemia, oxidative stress and platelet activation in offspring of patients with early myocardial infarction. Methods: We enrolled, in a cross-sectional study, 46 offspring of patients with early myocardial infarction and 86 healthy subjects (HS). LPS levels and gut permeability (assessed by zonulin), oxidative stress (assessed by serum NOX-2-derived peptide (sNOX2-dp) release, hydrogen peroxide (H2O2) production and isoprostanes), serum nitric oxide (NO) bioavailability and platelet activation (by serum thromboxane B2 (TXB2) and soluble P-Selectin (sP-Selectin)) were analyzed. Results: Compared to HS, offspring of patients with early myocardial infarction had higher values of LPS, zonulin, serum isoprostanes, sNOX2-dp H2O2, TXB2, p-selectin and lower NO bioavailability. Logistic regression analysis showed that the variables associated with offspring of patients with early myocardial infarction were LPS, TXB2 and isoprostanes. The multiple linear regression analysis confirmed that serum NOX-2, isoprostanes, p-selectin and H2O2 levels were significantly associated to LPS. Furthermore, serum LPS, isoprostanes and TXB2 levels were significantly associated with sNOX-2-dp. Conclusions: Offspring of patients with early myocardial infarction have a low grade endotoxemia that could generate oxidative stress and platelet activation increasing their cardiovascular risk. Future studies are needed to understand the role of dysbiosis in this population.
A Compact Super-Wideband High Bandwidth Dimension Ratio Octagon-Structured Monopole Antenna for Future-Generation Wireless Applications
Authors: Suguna Naineri , Revathi Senthil
Published: April 2023

A high-dimension ratio, octagonal-shaped, super-wideband (SWB) monopole antenna was proposed in this paper. The proposed antenna was composed of an octagonal-structured radiating patch with a flower-shaped slot fed by a linearly tapering microstrip line and a rectangular partial ground fabricated on a Rogers 5880 dielectric substrate, with an overall dimension of 14 × 16 × 0.787 mm3. The designed antenna exhibits SWB characteristics over the frequency range of 3.71 to 337.88 GHz at |S11| ≤ −10 dB, VSWR < 2, a bandwidth ratio (BR) of 91.07:1, and a very high BDR of 6057.27. The proposed SWB antenna was designed, simulated, and analyzed using Ansys high-frequency structural simulator (HFSS). The simulated and measured findings have good confirmability, making them ideal for future-generation mobile networks, due to their strong radiation properties, compactness, and extremely wide bandwidth.
Two-Dimensional Mechanical Model of Human Stability in External Force-Caused Fall
Authors: Sopa Martyna , Sypniewska-Kamińska Grażyna , Walczak Tomasz , Kamiński Henryk
Published: April 2023

The paper proposes a two-dimensional model of human stability. The model allows for gaining data on forces and moments of forces being the effect of musculoskeletal interactions of body parts at human joints. The necessary input data are registered with the use of an optoelectronic motion capture system, two force plates, and a dynamometer. The latter measures the magnitude of the external force that is randomly applied to cause a backward fall. Therefore, the position of the participant’s body during the experiment, the external force used to cause the fall, and the ground reaction forces are known. The model proposed has the structure of a closed kinematic chain with one loop and two open subchains and uses the Euler–Newton approach to analyse the motion. In addition to external loads, linear and angular accelerations are also needed. To calculate those, we used a variant of approximation. This consists in carrying out a simultaneous approximation of a given function and its first and second derivatives in the subintervals that shift along the whole data range. The experiments conducted include two activities while maintaining a state of equilibrium and the fall itself. This gives the basis for examining whether the internal forces and moments at human joints differ significantly in both these states. The results and conclusions are discussed in the final part of the paper.
The Influence of Air Pollution on Non-Infectious Hospitalizations for Severe Acute Exacerbations of Chronic Obstructive Pulmonary Disease: A Time-Series from Serbia
Authors: Javorac Jovan , Živanović Dejan , Ilić Miroslav , Kašiković Lečić Svetlana , Milenković Ana , Dragić Nataša , Bijelović Sanja , Savić Nevena , Tot Vereš Kristina , Smuđa Mirjana , Stojkov Svetlana , Jevtić Marija
Published: April 2023

The available data on the impact of air pollution on acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are inconsistent. We investigated the influence of air pollution on the number of severe AECOPD hospitalizations of non-infectious etiology in patients residing in Novi Sad, Serbia. In this time-series, we used a quasi-Poisson generalized linear model in conjunction with distributed lag non-linear models, after controlling for lag days, seasonal and long-term trends, and meteorological factors (air temperature and humidity), to estimate the relative risk (RR) of AECOPD hospitalization for each increase of 10 μg/m3 in the air pollutant concentration. A total of 552 AECOPD hospitalizations were registered during 2017–2022. With each 10 μg/m3 increase in the selected air pollutants’ concentration, the cumulative RR (lags0–7) in single-predictor models for AECOPD admission were 1.52 (95% CI 0.98–2.35) for PM10, 1.44 (95% CI 0.93–2.25) for PM2.5, 1.13 (95% CI 0.87–1.47) for SO2, and 0.99 (95% CI 0.69–1.42) for NO2. Similar results were found in multi-predictor models as well as in group analyses between smokers and non-smokers. In conclusion, no significant associations between exposure to air pollutants and the daily AECOPD admissions were found. There is an obvious need for additional research on the topic.
A Review on Aerodynamic Characteristics and Wind-Induced Response of Flexible Support Photovoltaic System
Authors: Chen Fubin , Zhu Yuzhe , Wang Weijia , Shu Zhenru , Li Yi
Published: April 2023

Photovoltaic (PV) system is an essential part in renewable energy development, which exhibits huge market demand. In comparison with traditional rigid-supported photovoltaic (PV) system, the flexible photovoltaic (PV) system structure is much more vulnerable to wind load. Hence, it is imperative to gain a better understanding of the aerodynamic characteristics and wind-induced response of flexible photovoltaic system. The main objective of this paper is to provide a comprehensive review on the state-of-the-art studies focusing on the aerodynamic characteristics and wind-induced response of flexible PV system. Relevant studies have been carried out, using either physical or numerical simulation tools, and the effect of a series of governing parameters, such as spacing ratio, angle of attack, inclination and position are considered. In addition, dynamic response of these flexible structures, including buffeting, flutter, vortex-induced vibration, are also discussed and documented.
A Study of Elemental Composition and Risk Assessment Due to Exposure to Indoor PM10 in Two Residences in Mexico City
Authors: Reynoso-Cruces Salvador , Miranda-Martín-del-Campo Javier , Pineda-Santamaría Juan Carlos
Published: April 2023

Samples of airborne particles with aerodynamic diameters smaller than 10 µm (PM10) were collected in 2021 at two households in the Metropolitan Area of Mexico City. Both sites are in areas with different characteristics (residential or industrial zones). Simultaneous sampling indoors and outdoors was carried out at the two locations, using low-volume samplers. The study aimed to determine the indoor and outdoor gravimetric mass and elemental concentrations, identify emitting sources and possible penetration towards the households enhanced by natural ventilation, and assess risks to human health due to inhalation, ingestion, and dermal absorption, through hazard quotients. Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Se, and Pb concentrations were measured with X-ray fluorescence. Mass concentrations were higher indoors than outdoors, and most elemental concentrations had similar values in both environments. Cluster analysis was applied to identify possible emitting sources. The results showed a strong penetration of geogenic and industrial emissions at the Iztapalapa site, while only particles of industrial origin entered the interior of the Tlalnepantla dwelling, in both cases caused by the natural ventilation of the households. Health risks due to exposure to particles containing Fe, Ni, Cu, Zn, and Mn are not significant, and Pb and Cr only pose a risk via ingestion for men and women, although for children, there is a risk due to ingestion of all these elements.
Verification of Education Credentials on European Blockchain Services Infrastructure (EBSI): Action Research in a Cross-Border Use Case between Belgium and Italy
Authors: Tan Evrim , Lerouge Ellen , Du Caju Jan , Du Seuil Daniël
Published: April 2023

The European Blockchain Services Infrastructure (EBSI) is a major policy initiative of the EU and European Blockchain Partnership, to leverage blockchain to create cross-border services for public administrations, businesses, citizens, and their ecosystems, to verify information and increase trust in services. The EBSI aims to provide a secure and interoperable system infrastructure, utilizing new digital technologies such as digital wallets, verifiable credentials, and decentralized identifiers. These technologies are expected to change the way government services are organized between citizens and service providers. This article presents empirical findings from a cross-border pilot that was the first case to utilize this new blockchain infrastructure, and which tested the institutional, technical, and user-specific requirements for wider adoption. The pilot tested and assessed the verification of education credentials through the EBSI blockchain in a cross-border setting between a Belgian and an Italian university. The research was based on action research with the ICT units of the participating universities, wallet solution providers, the Belgian government, and EBSI officials. The findings highlight the following as key challenges for the wider adoption of the EBSI and verification credential use case: (1) onboarding of the EBSI ecosystem governance, (2) issuance of EBSI-compliant digital wallets and data schemes for transcript validation, (3) interoperability issues concerning digital identity systems.
Integration of Chemoinformatics and Multi-Omics Analysis Defines ECT2 as a Potential Target for Cancer Drug Therapy
Authors: Soltan Mohamed A. , Eldeen Muhammad Alaa , Sajer Bayan H. , Abdelhameed Reda F. A. , Al-Salmi Fawziah A. , Fayad Eman , Jafri Ibrahim , Ahmed Hebatallah Emam Mohammed , Eid Refaat A. , Hassan Hesham M. , Al-Shraim Mubarak , Negm Amr , Noreldin Ahmed E. , Darwish Khaled M.
Published: April 2023

Epithelial cell transforming 2 (ECT2) is a potential oncogene and a number of recent studies have correlated it with the progression of several human cancers. Despite this elevated attention for ECT2 in oncology-related reports, there is no collective study to combine and integrate the expression and oncogenic behavior of ECT2 in a panel of human cancers. The current study started with a differential expression analysis of ECT2 in cancerous versus normal tissue. Following that, the study asked for the correlation between ECT2 upregulation and tumor stage, grade, and metastasis, along with its effect on patient survival. Moreover, the methylation and phosphorylation status of ECT2 in tumor versus normal tissue was assessed, in addition to the investigation of the ECT2 effect on the immune cell infiltration in the tumor microenvironment. The current study revealed that ECT2 was upregulated as mRNA and protein levels in a list of human tumors, a feature that allowed for the increased filtration of myeloid-derived suppressor cells (MDSC) and decreased the level of natural killer T (NKT) cells, which ultimately led to a poor prognosis survival. Lastly, we screened for several drugs that could inhibit ECT2 and act as antitumor agents. Collectively, this study nominated ECT2 as a prognostic and immunological biomarker, with reported inhibitors that represent potential antitumor drugs.
Climate Change, Extreme Temperatures and Sex-Related Responses in Spiders
Authors: Harvey Jeffrey A. , Dong Yuting
Published: April 2023

Climatic extremes, such as heat waves, are increasing in frequency, intensity and duration under anthropogenic climate change. These extreme events pose a great threat to many organisms, and especially ectotherms, which are susceptible to high temperatures. In nature, many ectotherms, such as insects, may seek cooler microclimates and ’ride out´ extreme temperatures, especially when these are transient and unpredictable. However, some ectotherms, such as web-building spiders, may be more prone to heat-related mortality than more motile organisms. Adult females in many spider families are sedentary and build webs in micro-habitats where they spend their entire lives. Under extreme heat, they may be limited in their ability to move vertically or horizontally to find cooler microhabitats. Males, on the other hand, are often nomadic, have broader spatial distributions, and thus might be better able to escape exposure to heat. However, life-history traits in spiders such as the relative body size of males and females and spatial ecology also vary across different taxonomic groups based on their phylogeny. This may make different species or families more or less susceptible to heat waves and exposure to very high temperatures. Selection to extreme temperatures may drive adaptive responses in female physiology, morphology or web site selection in species that build small or exposed webs. Male spiders may be better able to avoid heat-related stress than females by seeking refuge under objects such as bark or rocks with cooler microclimates. Here, we discuss these aspects in detail and propose research focusing on male and female spider behavior and reproduction across different taxa exposed to temperature extremes.
Implications of the Organ-Specific Immune Environment for Immune Priming Effect of Radiotherapy in Metastatic Setting
Authors: Pierrard Julien , Van Ooteghem Geneviève , Van den Eynde Marc
Published: April 2023

With the development of immune checkpoint inhibitors (ICIs), the tumour immune microenvironment (TIME) has been increasingly considered to improve cancer management. The TIME of metastatic lesions is strongly influenced by the underlying immune contexture of the organ in which they are located. The metastatic location itself appears to be an important prognostic factor in predicting outcomes after ICI treatment in cancer patients. Patients with liver metastases are less likely to respond to ICIs than patients with metastases in other organs, likely due to variations in the metastatic TIME. Combining additional treatment modalities is an option to overcome this resistance. Radiotherapy (RT) and ICIs have been investigated together as an option to treat various metastatic cancers. RT can induce a local and systemic immune reaction, which can promote the patient’s response to ICIs. Here, we review the differential impact of the TIME according to metastatic location. We also explore how RT-induced TIME modifications could be modulated to improve outcomes of RT-ICI combinations.
Angiopoietin-like 2 Protein and Hidradenitis Suppurativa: A New Biomarker for Disease Severity
Authors: Hernández José L. , Ocejo-Vinyals J. Gonzalo , Renuncio-García Mónica , González-López Elena , Blanco Ricardo , González-López Marcos A.
Published: April 2023

Hidradenitis suppurativa (HS) is a chronic inflammatory disease whose pathogenesis is not fully understood at present. The role of proinflammatory cytokines, several adipokines, retinol-binding protein 4, angiopoietin-2 and other molecules has been previously reported. Angiopoietin-like 2 protein (ANGPTL2) is a glycoprotein belonging to the angiopoietin-like family that may play a pivotal role in the pathogenesis of several chronic inflammatory diseases. To our knowledge, the role of serum ANGPTL2 levels in HS has not been assessed to date. In the current case–control study, we aimed to investigate serum ANGPTL2 levels in HS patients and controls and to assess whether ANGPTL2 levels could be associated with the severity of HS. Ninety-four patients with HS and sixty controls of similar age and sex were included in the study. Demographic, anthropometric, and clinical data, as well as routine laboratory parameters and serum concentrations of ANGPTL2, were assessed in all participants. HS patients had significantly higher serum ANGPTL2 levels than controls after adjusting for confounders. Moreover, ANGPTL2 concentrations positively correlated with disease duration and severity. Our results indicate for the first time that serum ANGPTL2 concentrations are elevated in HS patients compared to controls and correlate with the duration of the disease. Besides, ANGPTL2 might serve as a biomarker of HS severity.
The Human Extracellular Matrix Diseasome Reveals Genotype–Phenotype Associations with Clinical Implications for Age-Related Diseases
Authors: Statzer Cyril , Luthria Karan , Sharma Arastu , Kann Maricel G. , Ewald Collin Y.
Published: April 2023

The extracellular matrix (ECM) is earning an increasingly relevant role in many disease states and aging. The analysis of these disease states is possible with the GWAS and PheWAS methodologies, and through our analysis, we aimed to explore the relationships between polymorphisms in the compendium of ECM genes (i.e., matrisome genes) in various disease states. A significant contribution on the part of ECM polymorphisms is evident in various types of disease, particularly those in the core-matrisome genes. Our results confirm previous links to connective-tissue disorders but also unearth new and underexplored relationships with neurological, psychiatric, and age-related disease states. Through our analysis of the drug indications for gene–disease relationships, we identify numerous targets that may be repurposed for age-related pathologies. The identification of ECM polymorphisms and their contributions to disease will play an integral role in future therapeutic developments, drug repurposing, precision medicine, and personalized care.
Recent Developments in the Applications of GO/rGO-Based Biosensing Platforms for Pesticide Detection
Authors: Gopal Geetha , Roy Namrata , Mukherjee Amitava
Published: April 2023

Pesticides are often used in different applications, including agriculture, forestry, aquaculture, food industry, etc., for the purpose of controlling insect pests and weeds. The indiscriminate usage of pesticides poses a massive threat to food, environmental, and human health safety. Hence, the fabrication of a sensitive and reliable sensor for the detection of pesticide residues in agro products and environmental samples is a critical subject to be considered. Recently, the graphene family including graphene oxide (GO) and reduced graphene oxide (rGO) have been frequently employed in the construction of sensors owing to their biocompatibility, high surface-area-to-volume ratio, and excellent physiochemical, optical, and electrical properties. The integration of biorecognition molecules with GO/rGO nanomaterials offers a promising detection strategy with outstanding repeatability, signal intensity, and low background noise. This review focuses on the latest developments (2018 to 2022) in the different types of GO/rGO-based biosensors, such as surface plasmon resonance (SPR), fluorescence resonance energy transfer (FRET), and electrochemical-based techniques, among other, for pesticide analysis. The critical discussions on the advantages, limitations, and sensing mechanisms of emerging GO/rGO-based biosensors are also highlighted. Additionally, we explore the existing hurdles in GO/rGO-based biosensors, such as handling difficult biological samples, reducing the total cost, and so on. This review also outlines the research gaps and viewpoints for future innovations in GO/rGO-based biosensors for pesticide determination mainly in areas with insufficient resources.
The Role of High-Resolution Magnetic Resonance Imaging in Cerebrovascular Disease: A Narrative Review
Authors: Li Xiaohui , Liu Chengfang , Zhu Lin , Wang Meng , Liu Yukai , Li Shuo , Deng Qiwen , Zhou Junshan
Published: April 2023

High-resolution magnetic resonance imaging (HRMRI) is the most important and popular vessel wall imaging technique for the direct assessment of vessel wall and cerebral arterial disease. It can identify the cause of stroke in high-risk plaques and differentiate the diagnosis of head and carotid artery dissection, including inflammation, Moya Moya disease, cerebral aneurysm, vasospasm after subarachnoid hemorrhage, reversible cerebral vasoconstriction syndrome, blunt cerebrovascular injury, cerebral arteriovenous malformations, and other stenosis or occlusion conditions. Through noninvasive visualization of the vessel wall in vitro, quantified assessment of luminal stenosis and pathological features of the vessel wall can provide clinicians with further disease information. In this report, technical considerations of HRMRI are discussed, and current clinical applications of HRMRI are reviewed.
Analysis of IoT Security Challenges and Its Solutions Using Artificial Intelligence
Authors: Mazhar Tehseen , Talpur Dhani Bux , Shloul Tamara Al , Ghadi Yazeed Yasin , Haq Inayatul , Ullah Inam , Ouahada Khmaies , Hamam Habib
Published: April 2023

The Internet of Things (IoT) is a well-known technology that has a significant impact on many areas, including connections, work, healthcare, and the economy. IoT has the potential to improve life in a variety of contexts, from smart cities to classrooms, by automating tasks, increasing output, and decreasing anxiety. Cyberattacks and threats, on the other hand, have a significant impact on intelligent IoT applications. Many traditional techniques for protecting the IoT are now ineffective due to new dangers and vulnerabilities. To keep their security procedures, IoT systems of the future will need AI-efficient machine learning and deep learning. The capabilities of artificial intelligence, particularly machine and deep learning solutions, must be used if the next-generation IoT system is to have a continuously changing and up-to-date security system. IoT security intelligence is examined in this paper from every angle available. An innovative method for protecting IoT devices against a variety of cyberattacks is to use machine learning and deep learning to gain information from raw data. Finally, we discuss relevant research issues and potential next steps considering our findings. This article examines how machine learning and deep learning can be used to detect attack patterns in unstructured data and safeguard IoT devices. We discuss the challenges that researchers face, as well as potential future directions for this research area, considering these findings. Anyone with an interest in the IoT or cybersecurity can use this website’s content as a technical resource and reference.
Left-Behind Children’s Positive and Negative Social Adjustment: A qualitative Study in China
Authors: Liu Wen , Wang Yining , Xia Lingxiang , Wang Weiwei , Li Yongqiang , Liang Ye
Published: April 2023

Individual interviews were conducted with a total of 66 participants from five groups between May and November 2020: left-behind children, parents, teachers, principals, and community workers. The left-behind children group included 16 primary and secondary school students aged 10–16. Themes in the interviews’ data were identified based on the Grounded Theory. Left-behind children’s social maladjustment manifested as: (1) depression and loneliness; and (2) poor academic performance. Left-behind children’s positive social adjustment manifested as: (1) using adaptive coping strategies; and (2) life skills and independence. Left-behind children’s social adjustment is a dynamic process and has both positive and negative aspects.
Repurposing Sulfasalazine as a Radiosensitizer in Hypoxic Human Colorectal Cancer
Authors: Kerkhove Lisa , Geirnaert Febe , Rifi Amir Laraki , Law Ka Lun , Gutiérrez Adrián , Oudaert Inge , Corbet Cyril , Gevaert Thierry , Dufait Inès , De Ridder Mark
Published: April 2023

xCT overexpression in cancer cells has been linked to tumor growth, metastasis and treatment resistance. Sulfasalazine (SSZ), an FDA-approved drug for the treatment of rheumatoid sarthritis, and inflammatory bowel diseases, has anticancer properties via inhibition of xCT, leading to the disruption of redox homeostasis. Since reactive oxygen species (ROS) are pivotal for the efficacy of radiotherapy (RT), elevated levels of ROS are associated with improved RT outcomes. In this study, the influence of SSZ treatment on the radiosensitivity of human colorectal cancer (CRC) cells was investigated. Our principal finding in human HCT116 and DLD-1 cells was that SSZ enhances the radiosensitivity of hypoxic CRC cells but does not alter the intrinsic radiosensitivity. The radiosensitizing effect was attributed to the depletion of glutathione and thioredoxin reductase levels. In turn, the reduction leads to excessive levels of ROS, increased DNA damage, and ferroptosis induction. Confirmation of these findings was performed in 3D models and in DLD-1 xenografts. Taken together, this study is a stepping stone for applying SSZ as a radiosensitizer in the clinic and confirms that xCT in cancer cells is a valid radiobiological target.
Inflammation-Based Prognostic Scores in Pancreatic Cancer Patients—A Single-Center Analysis of 1294 Patients within the Last Decade
Authors: Neumann Christopher C. M. , Schneider François , Hilfenhaus Georg , Vecchione Loredana , Felsenstein Matthäus , Ihlow Jana , Geisel Dominik , Sander Steffen , Pratschke Johann , Stintzing Sebastian , Keilholz Ulrich , Pelzer Uwe
Published: April 2023

Inflammatory properties are known to promote tumor progression leading to an impaired median overall survival (mOS). Various small studies have focused on a wide range of inflammation-based prognostic indicators. By using sufficient data from 1294 out of 2323 patients diagnosed with pancreatic cancer between 2009 and 2021 at our cancer center, inflammatory markers such as the neutrophil to lymphocyte ratio (NRL), the platelet to lymphocyte ratio (PLR), the lymphocyte to monocyte ratio (LMR) and the CRP to albumin ratio (CAR) were evaluated. We identified a new combined score, termed the inflammatory benchmark index (IBI). We performed univariate and multivariate overall survival analyses and identified optimal prognostic cut-off values for each parameter. In univariate analyses, advanced age (p < 0.001), gender (p < 0.001), tumor stage (p < 0.001), CA19-9 (p = 0.001), NLR (p = 0.001), LMR (p = 0.004), PLR (p = 0.004), CAR (p = 0.001) and IBI (p = 0.001) were identified as prognostic markers. In multivariate analyses advanced age (p < 0.001), gender (p = 0.001), tumor stage (p < 0.001), CA19-9 (p < 0.001), NLR (p = 0.001), LMR (p = 0.038), CAR (p < 0.001) and IBI (p < 0.001) were independent prognostic markers. These findings emphasize the impact of inflammation in pancreatic cancer, provide easily accessible prognostic values for the clinician, and may be useful as stratification parameters for trials aimed at patient inflammation or immune response.
Heterobinuclear Metallocomplexes as Photocatalysts in Organic Synthesis
Authors: Ionova Violetta , Abel Anton , Averin Alexei , Beletskaya Irina
Published: April 2023

Photocatalytic processes under visible light have constantly been finding more and more applications in organic synthesis as they allow a wide range of transformations to proceed under mild conditions. The combination of photoredox catalysis with metal complex catalysis gives an opportunity to employ the advantages of these two methodologies. Covalent bonding of photocatalyst and metal complex catalyst using bridging ligands increases the efficiency of the electron and energy transfer between these two parts of the catalyst, leading to more efficient and selective catalytic systems. Up to now, after numerous investigations of the photocatalytic reduction of CO2 and hydrogen generation, such a strategy was firmly established to substantially increase the catalyst’s activity. This review is aimed at the achievements and perspectives in the field of design and application of heterobinuclear metal complexes as photocatalysts in organic synthesis.
Development of Mathematical Model to Predict Soymilk Fouling Deposit Mass on Heat Transfer Surfaces Using Dimensional Analysis
Authors: Sritham Eakasit , Nunak Navaphattra , Ongwongsakul Ekarin , Chaishome Jedsada , Schleining Gerhard , Suesut Taweepol
Published: April 2023

The formation of fouling deposits on heat exchanger surfaces is one of the major concerns in thermal processes. The fouling behavior of food materials is complex, and its mechanism remains, in general, unclear. This study was aimed at developing a predictive model for soymilk fouling deposit formed on heated surfaces using dimensional analysis. Relevant variables affecting fouling deposit mass could be grouped into six dimensionless terms using Buckingham’s pi-theorem. Experimental data were obtained from a lab-scale plate heat exchanger. A simple model developed using the experimental data under the process conditions with the product inlet temperature, the product outlet temperature, and plate surface temperature in the ranges of 50–55 °C, 65–70 °C, and 70–85 °C, respectively, exhibited a good performance in the prediction of soymilk fouled mass. The correlation coefficient between the predicted and experimental values of fouled mass was 0.97 with an average relative error of 9.03%. Within the ranges of product inlet temperature and plate surfaces temperature studied, this model offers an opportunity to estimate soymilk fouling mass with acceptable accuracy.
Budget Impact Analysis of Adopting a One-Step Nucleic Acid Amplification Testing (NAAT) Alone Diagnostic Pathway for Clostridioides difficile in Japan Compared to a Two-Step Algorithm with Glutamate Dehydrogenase/Toxin Followed by NAAT
Authors: Lim Vanessa W. , Tomaru Takeshi , Chua Brandon , Ma Yan , Yanagihara Katsunori
Published: April 2023

Clostridioides difficile infection (CDI) is a major healthcare-associated infection that leads to a significant health economic burden in Japan. Using a decision tree model, we evaluated the budget impact of adopting a one-step nucleic acid amplification test (NAAT) alone pathway compared to a two-step diagnostic algorithm with glutamate dehydrogenase (GDH) and toxin antigen, followed by NAAT. The analysis was conducted from the government payer’s perspective for 100,000 symptomatic, hospitalized adults requiring a CDI diagnostic test. One-way sensitivity analysis was conducted for all data inputs. The NAAT alone strategy costed JPY 225,886,360 (USD 2,424,714) more, but was more effective, resulting in 1749 more patients accurately diagnosed and 91 fewer deaths compared to the two-step algorithm. Additionally, the NAAT alone pathway costed JPY 26,146 (USD 281) less per true positive CDI diagnosed. The total budget impact, and cost per CDI diagnosed was most sensitive to GDH sensitivity in one-way sensitivity analysis, where a lower GDH sensitivity resulted in greater cost savings with the NAAT alone pathway. Findings from this budget impact analysis can guide the adoption of a NAAT alone pathway for CDI diagnosis in Japan.
MoS2-ZnO Nanocomposite Mediated Immunosensor for Non-Invasive Electrochemical Detection of IL8 Oral Tumor Biomarker
Authors: Vetrivel Cittrarasu , Sivarasan Ganesan , Durairaj Kaliannan , Ragavendran Chinnasamy , Kamaraj Chinnaperumal , Karthika Sankar , Lo Huang-Mu
Published: April 2023

In order to support biomolecule attachment, an effective electrochemical transducer matrix for biosensing devices needs to have many specialized properties, including quick electron transfer, stability, high surface area, biocompatibility, and the presence of particular functional groups. Enzyme-linked immunosorbent assays, gel electrophoresis, mass spectrometry, fluorescence spectroscopy, and surface-enhanced Raman spectroscopy are common techniques used to assess biomarkers. Even though these techniques provide precise and trustworthy results, they cannot replace clinical applications because of factors such as detection time, sample amount, sensitivity, equipment expense, and the need for highly skilled individuals. For the very sensitive and targeted electrochemical detection of the salivary oral cancer biomarker IL8, we have created a flower-structured molybdenum disulfide-decorated zinc oxide composite on GCE (interleu-kin-8). This immunosensor shows very fast detection; the limit of detection (LOD) for interleukin-8 (IL8) detection in a 0.1 M phosphate buffer solution (PBS) was discovered to be 11.6 fM, while the MoS2/ZnO nanocomposite modified glassy carbon electrode (GCE) demonstrated a high catalytic current linearly from 500 pg to 4500 pg mL−1 interleukin-8 (IL8). Therefore, the proposed biosensor exhibits excellent stability, high accuracy sensitivity, repeatability, and reproducibility and shows the acceptable fabrication of the electrochemical biosensors to detect the ACh in real sample analysis.
Interleukin-4 Gene Polymorphisms in Romanian Patients with Inflammatory Bowel Diseases: Association with Disease Risk and Clinical Features
Authors: Olteanu Andrei , Ionescu Elena , Tieranu Cristian , Popa Luis , Andrei Silvia , Preda Carmen , Dutescu Monica , Bojinca Mihai , Tieranu Ioana , Popa Olivia
Published: April 2023

1. Introduction. Multiple cytokines have been studied for their role in the propagation of the inflammatory process related to inflammatory bowel diseases (IBD), but the role of interleukin-4 remains controversial. The aim of this study was to evaluate the role of two IL-4 gene single nucleotide polymorphisms (SNPs) in disease susceptibility and phenotypic expression. 2. Materials and Methods. A group of 160 patients with IBD (86CD/74UC) and 160 healthy controls were genotyped for IL-4 rs2243250/−590C/T and rs2070874/−34C/T using real-time polymerase chain reaction with TaqMan assay. 3. Results. The analysis of IBD patients and controls revealed a significantly reduced frequency of the minor allele T of both SNPs in CD patients (p = 0.03, OR 0.55 and p = 0.02, OR 0.52) and for the entire IBD group (p = 0.01, OR 0.57 and p = 0.01, OR 0.55). Haplotype analysis identified the most frequent haplotype (rs2243250/rs2070874 CC) associated with a high risk for developing IBD (either UC or CD) (p = 0.003). IBD patients with extraintestinal manifestations had significantly increased frequency of the minor alleles T. We also found an association between the presence of allele C of rs2070874 and response to antiTNF treatment. 4. Conclusions. This is the first study to investigate the IL-4 gene’s relation to IBD susceptibility conducted in Romania. Both SNPs were found to be associated with disease susceptibility and phenotypic features, such as extraintestinal manifestations and response to antiTNF agents.
Semi-Supervised KPCA-Based Monitoring Techniques for Detecting COVID-19 Infection through Blood Tests
Authors: Harrou Fouzi , Dairi Abdelkader , Dorbane Abdelhakim , Kadri Farid , Sun Ying
Published: April 2023

This study introduces a new method for identifying COVID-19 infections using blood test data as part of an anomaly detection problem by combining the kernel principal component analysis (KPCA) and one-class support vector machine (OCSVM). This approach aims to differentiate healthy individuals from those infected with COVID-19 using blood test samples. The KPCA model is used to identify nonlinear patterns in the data, and the OCSVM is used to detect abnormal features. This approach is semi-supervised as it uses unlabeled data during training and only requires data from healthy cases. The method’s performance was tested using two sets of blood test samples from hospitals in Brazil and Italy. Compared to other semi-supervised models, such as KPCA-based isolation forest (iForest), local outlier factor (LOF), elliptical envelope (EE) schemes, independent component analysis (ICA), and PCA-based OCSVM, the proposed KPCA-OSVM approach achieved enhanced discrimination performance for detecting potential COVID-19 infections. For the two COVID-19 blood test datasets that were considered, the proposed approach attained an AUC (area under the receiver operating characteristic curve) of 0.99, indicating a high accuracy level in distinguishing between positive and negative samples based on the test results. The study suggests that this approach is a promising solution for detecting COVID-19 infections without labeled data.
A Method for High-Frequency Mechanical Scanning Ultrasonic Flow Imaging with Motion Compensation
Authors: Heng Jiaming , Li Chenxi , Chu Tianxiang , Xu Yiwen , Jian Xiaohua
Published: April 2023

Mechanical scanning with a single transducer is an alternative method for high-frequency ultrasound imaging, which is simple in structure, convenient to implement, and low in cost. However, traditional mechanical scanning ultrasonic imaging introduces additional Doppler shift due to the movement of the transducer, which brings a challenge for blood velocity measurement. An improved mechanical scanning system for high-frequency ultrasonic color Doppler flow imaging is developed in this paper. The mechanical scanning system has a scanning stroke range of 15 mm, a maximum scanning speed of 168 mm/s, and an imaging depth of 20 mm. Since the mechanical scanning of the system is not in uniform motion, motion compensation was applied to achieve high-precision imaging both in B-mode and Doppler mode. The experiment results show that the system imaging resolution can reach about 140 μm in B-mode imaging, the relative velocity error is less than 5% in color Doppler flow imaging at different flow rates, and the CNR of power Doppler flow imaging of this system is greater than 15 dB. The proposed mechanical scanning imaging system can achieve high-resolution structure imaging and color flow imaging, which can provide more diagnostic information for the practical diagnosis and broaden the application range of mechanical scanning ultrasound imaging.
On the Lift, Related Privacy Measures, and Applications to Privacy–Utility Trade-Offs
Authors: Zarrabian Mohammad Amin , Ding Ni , Sadeghi Parastoo
Published: April 2023

This paper investigates lift, the likelihood ratio between the posterior and prior belief about sensitive features in a dataset. Maximum and minimum lifts over sensitive features quantify the adversary’s knowledge gain and should be bounded to protect privacy. We demonstrate that max- and min-lifts have a distinct range of values and probability of appearance in the dataset, referred to as lift asymmetry. We propose asymmetric local information privacy (ALIP) as a compatible privacy notion with lift asymmetry, where different bounds can be applied to min- and max-lifts. We use ALIP in the watchdog and optimal random response (ORR) mechanisms, the main methods to achieve lift-based privacy. It is shown that ALIP enhances utility in these methods compared to existing local information privacy, which ensures the same (symmetric) bounds on both max- and min-lifts. We propose subset merging for the watchdog mechanism to improve data utility and subset random response for the ORR to reduce complexity. We then investigate the related lift-based measures, including ℓ1-norm, χ2-privacy criterion, and α-lift. We reveal that they can only restrict max-lift, resulting in significant min-lift leakage. To overcome this problem, we propose corresponding lift-inverse measures to restrict the min-lift. We apply these lift-based and lift-inverse measures in the watchdog mechanism. We show that they can be considered as relaxations of ALIP, where a higher utility can be achieved by bounding only average max- and min-lifts.
The Integral Role of Intelligent IoT System, Cloud Computing, Artificial Intelligence, and 5G in the User-Level Self-Monitoring of COVID-19
Authors: Ahmed Sajjad , Yong Jianming , Shrestha Anup
Published: April 2023

This study presents internet of things (IOT) and artificial intelligence technologies that are critical in reducing the harmful effects of this illness and assisting its recovery. It explores COVID-19’s economic impacts before learning about new technologies and potential solutions. The research objective was to propose a solution for self-diagnosis, self-monitoring, and self-management of COVID-19 with personal mobiles and personal data using cloud solutions and mobile applications with the help of an intelligent IoT system, artificial intelligence, machine learning, and 5G technologies. The proposed solution based on self-diagnosis without any security risk for users’ data with low cost of cloud-based data analytics by using handsets only is an innovative approach. Since the COVID-19 outbreak, the global social, economic, religious, and cultural frameworks and schedules have been affected adversely. The fear and panic associated with the new disease, which the world barely knew anything about, amplified the situation. Scientists and epidemiologists have traced the first outbreak of COVID-19 at Wuhan, China. A close examination of the genetic makeup of the virus showed that the virus is zoonotic, meaning that the virus changed hosts from animals to humans. The uncertainty associated with the above features and characteristics of the virus, as well as the high mortality rates witnessed in many parts of the globe, significantly contributed to the widespread global panic that brought the world to a standstill. Different authorities and agencies associated with securing the public have implemented different means and methods to try and mitigate the transmission of the infection as scientists and medical practitioners work on remedies to curb the spread of COVID-19. Owing to different demographics, different parts of the globe have attempted to effectively implement locally available resources to efficiently fight and mitigate the adverse effects of the COVID-19 pandemic. The general framework provided by the World Health Organization (WHO) has been implemented or enhanced in different parts of the globe by locally available resources and expertise to effectively mitigate the impact of COVID-19. There is currently no effective vaccine for COVID-19, but new technology can be available within weeks to reduce the spread of the disease; current approaches such as contact tracing and testing are not secure, and the cost of testing is high for end users. The proposed solution based on self-diagnosis without any security risk for users’ data with low cost of cloud-based data analytics functions by using an intelligent internet of things (IOT) system for collecting sensors data and processing them with artificial intelligence to improve efficiency and reduce the spread of COVID-19.
IoT System for Gluten Prediction in Flour Samples Using NIRS Technology, Deep and Machine Learning Techniques
Authors: Jossa-Bastidas Oscar , Sanchez Ainhoa Osa , Bravo-Lamas Leire , Garcia-Zapirain Begonya
Published: April 2023

Gluten is a natural complex protein present in a variety of cereal grains, including species of wheat, barley, rye, triticale, and oat cultivars. When someone suffering from celiac disease ingests it, the immune system starts attacking its own tissues. Prevalence studies suggest that approximately 1% of the population may have gluten-related disorders during their lifetime, thus, the scientific community has tried to study different methods to detect this protein. There are multiple commercial quantitative methods for gluten detection, such as enzyme-linked immunosorbent assays (ELISAs), polymerase chain reactions, and advanced proteomic methods. ELISA-based methods are the most widely used; but despite being reliable, they also have certain constraints, such as the long periods they take to detect the protein. This study focuses on developing a novel, rapid, and budget-friendly IoT system using Near-infrared spectroscopy technology, Deep and Machine Learning algorithms to predict the presence or absence of gluten in flour samples. 12,053 samples were collected from 3 different types of flour (rye, corn, and oats) using an IoT prototype portable solution composed of a Raspberry Pi 4 and the DLPNIRNANOEVM infrared sensor. The proposed solution can collect, store, and predict new samples and is connected by using a real-time serverless architecture designed in the Amazon Web services. The results showed that the XGBoost classifier reached an Accuracy of 94.52% and an F2-score of 92.87%, whereas the Deep Neural network had an Accuracy of 91.77% and an F2-score of 96.06%. The findings also showed that it is possible to achieve high-performance results by only using the 1452–1583 nm wavelength range. The IoT prototype portable solution presented in this study not only provides a valuable contribution to the state of the art in the use of the NIRS + Artificial Intelligence in the food industry, but it also represents a first step towards the development of technologies that can improve the quality of life of people with food intolerances.
Construction of Personalized Bus Travel Time Prediction Intervals Based on Hierarchical Clustering and the Bootstrap Method
Authors: Yin Zhenzhong , Zhang Bin
Published: April 2023

Providing accurate bus travel time information is very important to help passengers plan their trips and reduce waiting times. Due to the uncertainty of the bus travel time, the traditional prediction value of the travel time point cannot accurately describe the reliability of the prediction result, which is not conducive to passengers waiting for the bus according to the prediction result. At the same time, due to the large differences in the individual driving styles of the bus drivers, the travel time data fluctuate greatly, and the accuracy and reliability of the point prediction results are further reduced. To address this issue, this study develops a personalized bus travel time prediction intervals model for different drivers based on the bootstrap method. Personalized travel time prediction intervals were constructed for drivers with different driving styles. To further improve the quality of travel time prediction intervals, this study optimizes training data sets considering driving style factors. Then, this paper integrates hierarchical clustering, an artificial neural network, and the bootstrap method to construct another prediction intervals model for bus travel time based on driver driving style clustering and the bootstrap method. The real−world driving data sets of the No. 239 bus in Shenyang, China, were used for experimental verification. The results showed that the two models constructed in this paper can effectively quantify the uncertainty of the point prediction results, the PICP of each interval exceeding the confidence level set (80%). It was also found that the quality of the prediction intervals constructed by clustering the driving style data is better (MPIW values decreased by 23.33%, 54.24%, and 28.61 respectively, and the corresponding NMPIW values also decreased by 18.93%, 10.39%, and 14.19%, respectively), which can provide passengers with more reasonable suggestions for waiting time.