bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel Roles of Nanog in Cancer Cells and Their Extracellular Vesicles
Authors: Saito Mikako
Published: December 2022

The use of extracellular vesicle (EV)-based vaccines is a strategically promising way to prevent cancer metastasis. The effective roles of immune cell-derived EVs have been well understood in the literature. In the present paper, we focus on cancer cell-derived EVs to enforce, more thoroughly, the use of EV-based vaccines against unexpected malignant cells that might appear in poor prognostic patients. As a model of such a cancer cell with high malignancy, Nanog-overexpressing melanoma cell lines were developed. As expected, Nanog overexpression enhanced the metastatic potential of melanomas. Against our expectations, a fantastic finding was obtained that determined that EVs derived from Nanog-overexpressing melanomas exhibited a metastasis-suppressive effect. This is considered to be a novel role for Nanog in regulating the property of cancer cell-derived EVs. Stimulated by this result, the review of Nanog’s roles in various cancer cells and their EVs has been updated once again. Although there was no other case presenting a similar contribution by Nanog, only one case suggested that NANOG and SOX might be better prognosis markers in head and neck squamous cell carcinomas. This review clarifies the varieties of Nanog-dependent phenomena and the relevant signaling factors. The information summarized in this study is, thus, suggestive enough to generate novel ideas for the construction of an EV-based versatile vaccine platform against cancer metastasis.
Comparison of the Immune Response in Vaccinated People Positive and Negative to SARS-CoV-2 Employing FTIR Spectroscopy
Authors: Vazquez-Zapien Gustavo Jesus , Martinez-Cuazitl Adriana , Sanchez-Brito Miguel , Delgado-Macuil Raul Jacobo , Atriano-Colorado Consuelo , Garibay-Gonzalez Francisco , Sanchez-Monroy Virginia , Lopez-Reyes Alberto , Mata-Miranda Monica Maribel
Published: December 2022

Various immunopathological events characterize the systemic acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Moreover, it has been reported that coronavirus disease 2019 (COVID-19) vaccination and infection by SARS-CoV-2 induce humoral immunity mediated by B-cell-derived antibodies and cellular immunity mediated by T cells and memory B cells. Immunoglobulins, cytokines, and chemokines play an important role in shaping immunity in response to infection and vaccination. Furthermore, different vaccines have been developed to prevent COVID-19. Therefore, this research aimed to analyze and compare Fourier-transform infrared (FTIR) spectra of vaccinated people with a positive (V-COVID-19 group) or negative (V-Healthy group) real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR) test, evaluating the immunoglobulin and cytokine content as an immunological response through FTIR spectroscopy. Most individuals that integrated the V-Healthy group (88.1%) were asymptomatic; on the contrary, only 28% of the V-COVID-19 group was asymptomatic. Likewise, 68% of the V-COVID-19 group had at least one coexisting illness. Regarding the immunological response analyzed through FTIR spectroscopy, the V-COVID-19 group showed a greater immunoglobulins G, A, and M (IgG, IgA, and IgM) content, as well as the analyzed cytokines interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-ɑ), and interleukins 1β, 6, and 10 (IL-1β, IL-6, and IL-10). Therefore, we can state that it was possible to detect biochemical changes through FTIR spectroscopy associated with COVID-19 immune response in vaccinated people.
Cathelicidin-Related Antimicrobial Peptide Negatively Regulates Bacterial Endotoxin-Induced Glial Activation
Authors: Bhusal Anup , Nam Youngpyo , Seo Donggun , Lee Won-Ha , Suk Kyoungho
Published: December 2022

Recent studies have suggested that mouse cathelicidin-related antimicrobial peptide (CRAMP) and its human homologue leucine leucine-37 (LL-37) play critical roles in innate immune responses. Here, we studied the role of mouse CRAMP in bacterial endotoxin lipopolysaccharide (LPS)-induced neuroinflammation. CRAMP peptide treatment significantly inhibited LPS-mediated inflammatory activation of glial cells in culture. In the animal model of LPS-induced neuroinflammation, CRAMP expression was highly induced in multiple cell types, such as astrocytes, microglia, and neurons. Injection of exogenous CRAMP peptide significantly inhibited inflammatory cytokine expression and the reactivity of glial cells in the mouse brain following intraperitoneal or intracerebroventricular LPS administration. Altogether, results of the study suggest that CRAMP plays an important part in containment of LPS-induced neuroinflammatory responses, and that CRAMP can be exploited for the development of targeted therapies for neuroinflammatory conditions associated with bacterial infection.
Editing of a Novel Cd Uptake-Related Gene CUP1 Contributes to Reducing Cd Accumulations in Arabidopsis thaliana and Brassica napus
Authors: Yao Junyu , Bai Jiuyuan , Liu Sha , Fu Jingyan , Zhang Ying , Luo Tianshun , Ren Hongpei , Wang Rui , Zhao Yun
Published: December 2022

Brassica napus is a Cd hyperaccumulator, which is a serious threat to food and fodder safety. However, no related studies on developing Cd-safe B. napus have been reported yet. Here, we screened out a novel Cd uptake-related gene, AtCUP1, from the major facilitator superfamily in Arabidopsis thaliana. The mutation of AtCUP1 decreased Cd accumulation, both in roots and shoots of A. thaliana. Furthermore, the disruption of the AtCUP1 gene by the CRISPR/Cas9 system significantly reduced Cd accumulation in A. thaliana. Interestingly, the disruption of the BnCUP1 gene, an orthologous gene of AtCUP1, by the CRISPR/Cas9 system also diminished Cd accumulation in both roots and shoots of B. napus based on the hydroponics assay. Furthermore, for the field experiment, the Cd accumulations of BnCUP1-edited lines were reduced by 52% in roots and 77% in shoots compared to that of wild-type (WT) lines, and the biomass and yield of BnCUP1-edited lines increased by 42% and 47% of that of WT, respectively. Noteworthily, agronomic characteristics of B. napus were not apparently affected by BnCUP1-editing. Thus, BnCUP1-edited lines are excellent non-transgenic germplasm resources for reducing Cd accumulation without a distinct compromise in yield, which could be applied to agricultural production in Cd-contaminated soils.
Propranolol Modulates Cerebellar Circuit Activity and Reduces Tremor
Authors: Zhou Joy , Van der Heijden Meike E. , Salazar Leon Luis E. , Lin Tao , Miterko Lauren N. , Kizek Dominic J. , Perez Ross M. , Pavešković Matea , Brown Amanda M. , Sillitoe Roy V.
Published: December 2022

Tremor is the most common movement disorder. Several drugs reduce tremor severity, but no cures are available. Propranolol, a β-adrenergic receptor blocker, is the leading treatment for tremor. However, the in vivo circuit mechanisms by which propranolol decreases tremor remain unclear. Here, we test whether propranolol modulates activity in the cerebellum, a key node in the tremor network. We investigated the effects of propranolol in healthy control mice and Car8wdl/wdl mice, which exhibit pathophysiological tremor and ataxia due to cerebellar dysfunction. Propranolol reduced physiological tremor in control mice and reduced pathophysiological tremor in Car8wdl/wdl mice to control levels. Open field and footprinting assays showed that propranolol did not correct ataxia in Car8wdl/wdl mice. In vivo recordings in awake mice revealed that propranolol modulates the spiking activity of control and Car8wdl/wdl Purkinje cells. Recordings in cerebellar nuclei neurons, the targets of Purkinje cells, also revealed altered activity in propranolol-treated control and Car8wdl/wdl mice. Next, we tested whether propranolol reduces tremor through β1 and β2 adrenergic receptors. Propranolol did not change tremor amplitude or cerebellar nuclei activity in β1 and β2 null mice or Car8wdl/wdl mice lacking β1 and β2 receptor function. These data show that propranolol can modulate cerebellar circuit activity through β-adrenergic receptors and may contribute to tremor therapeutics.
The Interface of Tumour-Associated Macrophages with Dying Cancer Cells in Immuno-Oncology
Authors: Vanmeerbeek Isaure , Govaerts Jannes , Laureano Raquel S. , Sprooten Jenny , Naulaerts Stefan , Borras Daniel M. , Laoui Damya , Mazzone Massimiliano , Van Ginderachter Jo A. , Garg Abhishek D.
Published: December 2022

Tumour-associated macrophages (TAMs) are essential players in the tumour microenvironment (TME) and modulate various pro-tumorigenic functions such as immunosuppression, angiogenesis, cancer cell proliferation, invasion and metastasis, along with resistance to anti-cancer therapies. TAMs also mediate important anti-tumour functions and can clear dying cancer cells via efferocytosis. Thus, not surprisingly, TAMs exhibit heterogeneous activities and functional plasticity depending on the type and context of cancer cell death that they are faced with. This ultimately governs both the pro-tumorigenic and anti-tumorigenic activity of TAMs, making the interface between TAMs and dying cancer cells very important for modulating cancer growth and the efficacy of chemo-radiotherapy or immunotherapy. In this review, we discuss the interface of TAMs with cancer cell death from the perspectives of cell death pathways, TME-driven variations, TAM heterogeneity and cell-death-inducing anti-cancer therapies. We believe that a better understanding of how dying cancer cells influence TAMs can lead to improved combinatorial anti-cancer therapies, especially in combination with TAM-targeting immunotherapies.
Pro- and Anti-Tumoral Factors Involved in Total Body Irradiation and Interleukin-2 Conditioning in Adoptive T Cell Therapy of Melanoma-Bearing Rag1 Knock-Out Mice
Authors: Kim Seon-Hee , Go Eun Mi , Shin Dong Hoon , Choi Beom K. , Han Chungyong
Published: December 2022

In adoptive T cell therapy (ACT), the transfer of tumor-specific T cells is paralleled by the conditioning regimen to increase therapeutic efficacy. Pre-conditioning depletes immune-suppressive cells and post-conditioning increases homeostatic signals to improve the persistence of administered T cells. Identifying the favorable immunological factors involved in a conditioning regimen is important to design effective strategies in ACT. Here, by using an ACT model of murine melanoma, we evaluate the effect of the total body irradiation (TBI) and interleukin-2 (IL-2) treatment combination. The use of a Rag1 knock-out strain, which lacks endogenous T cells, enables the identification of factors in a way that focuses more on transferred T cells. We demonstrate that the TBI/IL-2 combination has no additive effect in ACT, although each conditioning improves the therapeutic outcome. While the combination increases the frequency of transferred T cells in lymphoid and tumor tissues, the activation intensity of the cells is reduced compared to that of the sole TBI treatment. Notably, we show that in the presence of TBI, the IL-2 treatment reduces the frequency of intra-tumoral dendritic cells, which are crucial for T cell activation. The current study provides insights into the immunological events involved in the TBI/IL-2 combination in ACT.
Sympathy-Empathy and the Radicalization of Young People
Authors: Lavenne-Collot Nathalie , Dissaux Nolwenn , Campelo Nicolas , Villalon Charlotte , Bronsard Guillaume , Botbol Michel , Cohen David
Published: December 2022

Background: The sympathy-empathy (SE) system is commonly considered a key faculty implied in prosocial behaviors, and SE deficits (also called callous-unemotional traits, CUTs) are associated with nonprosocial and even violent behaviors. Thus, the first intuitive considerations considered a lack of SE among young people who undergo radicalization. Yet, their identification with a cause, their underlying feelings of injustice and grievance, and the other ways in which they may help communities, suggest that they may actually have a lot of empathy, even an excess of it. As a consequence, the links between SE and radicalization remain to be specified. This critical review aims to discuss whether and how SE is associated with developmental trajectories that lead young people to radicalization. Method: We first recall the most recent findings about SE development, based on an interdisciplinary perspective informed by social neuroscience. Then, we review sociological and psychological studies that address radicalization. We will critically examine the intersections between SE and radicalization, including neuroscientific bases and anthropologic modulation of SE by social factors involved in radicalization. Results: This critical review indicates that the SE model should clearly distinguish between sympathy and empathy within the SE system. Using this model, we identified three possible trajectories in young radicalized individuals. In individuals with SE deficit, the legitimization of violence is enough to engage in radicalization. Concerning individuals with normal SE, we hypothesize two trajectories. First, based on SE inhibition/desensitization, individuals can temporarily join youths who lack empathy. Second, based on an SE dissociation, combining emotional sympathy increases for the in-group and cognitive empathy decreases toward the out-group. Conclusions: While confirming that a lack of empathy can favor radicalization, the counterintuitive hypothesis of a favorable SE development trajectory also needs to be considered to better specify the cognitive and affective aspects of this complex phenomenon.
Giant Bilateral Hydronephrosis in A Newborn—A Case Report
Authors: Frech-Dörfler Martina , Durand Sabrina , Prüfer Friederike , Holland-Cunz Stefan , Rudin Christoph
Published: December 2022

Background: Prenatal hydronephrosis is common and may vary in size. Although mostly unproblematic, it may be a sign of urinary tract obstruction of differing severity. Case Diagnosis/Treatment: We present a boy with prenatally detected bilateral giant hydronephrosis. A prenatal ultrasound showed the whole abdominal cavity of the fetus filled with urine. Kidney parenchyma could not be seen. The boy was born at 34 + 1 weeks’ gestation. After delivery, he showed a severely distended abdomen. Insertion of a nasogastric tube was not possible, and he had to be intubated due to respiratory distress. A bilateral percutaneous nephrostomy was performed immediately. After a few hours, he could be stabilized and extubated. An ultrasound on the following day showed two kidney units with normal kidney parenchyma of normal size. The initially slightly elevated serum creatinine level normalized within one week. An antegrade pyelography via the nephrostomy tubes showed bilateral ureteropelvic junction obstruction. Conclusion: Severe bilateral hydronephrosis may be associated with good outcome and well-preserved kidney function. Prenatal counseling should be done carefully, with discussion of different treatment possibilities and without definitive prediction of outcome.
Resin Infiltration of Non-Cavitated Enamel Lesions in Paediatric Dentistry: A Narrative Review
Authors: Dziaruddin Nabihah , Zakaria Ahmad Shuhud Irfani
Published: December 2022

The resin infiltration (RI) technique was introduced as one of the minimal intervention dentistry strategies in addressing dental caries among the paediatric population. This technique used the low-viscosity resin monomer to infiltrate the non-cavitated carious lesion and other developmental enamel porosities, thus allowing the conservation of the tooth structure. This narrative review aims to explore the value of RI in Paediatric Dentistry. Through our search of the literature, the development of the material, their clinical applications and shortcomings, as well as the innovation that has been carried out to improve the current RI, were discussed. There are number of high-level evidence supporting the use of RI in arresting non-cavitated proximal caries lesions in primary and permanent teeth, but its efficacy in managing anterior white spot lesions is still unclear. Limited penetration depth, not radiopaque and questionable long-term colour and material stability were among the limitation of the material. Various laboratory-based studies have been conducted to improve the current properties of RI. Nevertheless, RI has emerged as one of the important micro-invasive techniques in addressing non-cavitated and anterior white-spot enamel lesions in children and adolescents with great success.
Water Asset Transition through Treating Water as a New Asset Class for Paradigm Shift for Climate–Water Resilience
Authors: Elmahdi Amgad , Wang Lixiang
Published: December 2022

Climate change is evident around the globe, which requires bold actions now to achieve UN-SDGs and Paris Agreement. The water sector is dominated by public finance and is almost subsidised. In addition, there is an increased risk perception surrounding climate investments in developing countries. Pricing climate risks is a daunting challenge for investors and the private sector, who must estimate the likelihood of various climate scenarios and their implications for physical, liability and transition risks at the firm, project, national, and regional scales. In addition, there is a building momentum to scale up global climate response. To translate this momentum into action will require significantly greater investments, investments in a different set of inclusive assets that address water security, mobilise the private sector and provides sector-based or economy-wide co-benefits to direct and indirect beneficiaries, e.g., job creation, health benefits, improved resilience and scaling knowledge and harmonise data and methodologies. Notably, climate–water finance is facing a dual challenge. It will have to both reduce the present water infrastructure financing gap and ensure that this new infrastructure/asset is low-carbon, resilient to climate change, and meets the goals of the UNFCCC and the Paris Agreement. Therefore, there is a need for a paradigm shift in the way how water asset is defined, developed, and financed. This paper presents this novel approach concept and its content and financial structure that enable treating water as a new asset class to enable private sector investment and ensure providing water for domestic, municipal, and industrial purposes and allows municipalities to scale their water reuse, sanitation, and desalination projects in partnership with the private sector and/or governments. It is increasingly important to treat water as a new asset class, particularly as nations around the world (particularly developing countries) are set to experience an anticipated 40% shortfall in water by 2030 due to climate change, economic recovery and growth, population growth and resource competition. Investment in water could be one of the ways of tackling this deficit by treating water as a new asset class.
Optimization of Laser Shock Process Parameters for 40Cr Steel
Authors: Chen Xiuyu , Sun Jie , Xu Zhilong , Chen Junying , Jiang Qingshan , Li Yi , Li Jiayuan , Cheng Jun
Published: December 2022

Laser shock peening (LSP) process parameters have an important influence on the strengthening effect. In this study, theoretical calculations were used to determine a suitable range of stress wave peaks (5.09 GPa–6.36 GPa) for laser shocking, which consider the material properties of alloy steel 40Cr. In addition to theoretical calculations, the finite element numerical simulation of a single-point laser shock was also performed. The residual stresses of specimens under different shock pressure waves were simulated, and then the optimal pulse width was determined as 20 ns and the optimal pulse energy was determined as 10 J. Finally, the influences of different pulse energies on the microhardness, residual stress, microstructure, and shock-affected layer thickness of metallic materials were comprehensively investigated through experiments, and the optimization of the laser shock energy was proved to be 10 J. An optimized combination of parameters of a single-point laser shock for 40Cr was obtained, in which the spot diameter was 3 mm, the pulse width was 20 ns, and the pulse energy was 10 J. The study has implications for the selection of LSP process parameters for alloy steels.
Particles in the Eluate from Double Filtration Plasmapheresis—A Case Study Using Field Emission Scanning Electron Microscopy/Energy-Dispersive X-ray Spectroscopy (FE-SEM/EDX)
Authors: Scholkmann Felix , Gatti Antonietta M.
Published: December 2022

Unwanted substances can be effectively removed from the blood using double-filtration plasmapheresis (DFPP). In our case study, we used field emission scanning electron microscopy/energy-dispersive X-ray analysis (FE-SEM-EDX) to examine if the eluate obtained by a specific type of DFPP (INUSpheresis with a TKM58 filter) contains nano- and microparticles and what chemical composition these particles have. We identified micro- and nanoparticles of various sizes and chemical composition, including microparticles high in the concentration of calcium, iron, silicon, aluminium and titanium. Furthermore, thread-like objects were identified. We discuss the possible origin of the particles and objects, their pathophysiological relevance and the potential of FE-SEM-EDX analysis of the eluate in terms of diagnostics and therapy for environmental medicine applications on patients.
In Vitro and In Silico Evaluations of Boswellia carterii Resin Dermocosmetic Activities
Authors: Hourfane Sohaib , Mechqoq Hicham , Errajouani Fatima , Rocha João , El Aouad Noureddine
Published: December 2022

Boswellia carterii is a plant species belonging to the Burseraceae family. It grows up in trees or shrubs, and it is known for producing an aromatic resin commonly named frankincense or olibanum. This resin has been used in traditional medicine to treat various conditions such as inflammations, gastrointestinal disorders and traumatic injuries. Virtual screening and molecular docking are two in silico approaches used to predict potential interactions between ligands and the active site of a protein. These approaches are mainly used in natural product chemistry and pharmacology as a screening tool to select plant extracts or fractions for in vitro testing, as well as for the prediction of mechanisms of action. The aim of this research is the in silico and in vitro evaluations of the potential collagenase and elastase inhibitory activities of Boswellia carterii resin organic extracts (viz., methanol, n-hexane and ethyl acetate). The obtained results revealed that methanol and n-hexane exhibited the best collagenase inhibitory activity with values superior to 85%, whereas the methanol and ethyl acetate showed the highest elastase inhibition activity with inhibition values ranging between 40 and 60%. The molecular docking prediction confirmed the experimental results; moreover, the visualization of the ligand–protein interactions showed that the main compounds of the organic extracts may have mechanisms of action similar to the positive controls. Those findings are very promising and open new perspectives for the exploitation of Boswellia carterii resin as active agents for the development of anti-aging cosmeceuticals.
Investigating the β-Mg17Al12 Alloy under Pressure Using First-Principles Methods: Structure, Elastic Properties, and Mechanical Properties
Authors: Xiao Chuncai , Tu Zongxing , Liao Luliang , Liu Zhiwen , Wen Yufeng , Zeng Xianshi
Published: December 2022

Calculations of first principles were employed to explore the elastic constants of the β-Mg17Al12 intermetallic complex under pressure, along with several related physical parameters, including the bulk modulus, the shear modulus, Young’s modulus, Poisson’s ratio, and the anisotropy index. The volume of the β-Mg17Al12 crystal in the ground state was V0 = 1180.353 Å3, and the lattice parameter was 10.57 Å. This is in agreement with the available results in the literature, which indicate that the calculations were correct. The three independent elastic constants, C11, C12, and C44, increased with increasing pressure. The bulk modulus B, shear modulus G, and Young’s modulus E increased with increasing pressure, indicating that the bulk deformation resistance, shear deformation resistance, and stiffness of the β-Mg17Al12 phase increased with increasing pressure. The phase had a B/G > 1.75 and a Poisson’s ratio of ν > 0.26 and increased with pressure, indicating that the β-Mg17Al12 crystals were ductile and that the ductility increased with pressure. The Cauchy pressure C12–C44 increased with increasing pressure. The anisotropy coefficients A(100) and A(110) deviated further from 1, and the anisotropy increased. The electronic structure calculations showed that the total density of the states (TDOS) was achieved mainly by the Mg-3p and Al-3p states, and the total density of states moved toward the higher energy regions under pressure, with enhanced interatomic bonding, leading to an increase in the elastic constants and ultimately to an increase in each physical property with increasing pressure.
Preventing Crack in an Aluminum Alloy Complex Structure during Welding Process Based on Numerical Simulation Technology
Authors: Zhang Yuelai , Luo Wenze , Zeng Jiongmeng , Li Xixian , Hu Long , Deng Dean
Published: December 2022

Aluminum alloy structures are widely used for weight reduction in aviation, shipbuilding, rail vehicles and automotive industries. Fusion welding technology is one of the most important joining methods for lightweight structure assembly due to its advantages such as flexibility in design, high production efficiency, and low cost. However, the local centralized heating during fusion welding inevitably produces residual stress and welding deformation. For actual engineering structures, if the product design is unreasonable or the external restraint is inappropriate, the transient stress or residual stress become a key factor resulting in cracking during the assembly process. In the current study, an effective computational approach was developed based on the MSC Marc software to simulate transient and residual stress fields for complex aluminum alloy structures during the welding process. In the developed computational approach, according to the location and arrangement of welding lines, an instantaneous heat source model was used to replace the traditional moving heat source model, and as a result significanlty improved the calculation efficiency to meet actual engineering needs. The welding stresses, including transient and residual stress, of an A6061 aluminum alloy complex structure were calculated by the developed numerical simulation technology. The simulation results indicated that the cracking was produced by excessive transient stress during welding process. Subsequently, the effect of external restraint intensity on welding stress at the key location was examined numerically. Based on the simulation results, measures to reduce welding stress and cracking risk were put forward based on adjusting the external restraint intensity.
Distribution of Gutless Siboglinid Worms (Annelida, Siboglinidae) in Russian Arctic Seas in Relation to Gas Potential
Authors: Karaseva Nadezda P. , Rimskaya-Korsakova Nadezhda N. , Smirnov Roman V. , Udalov Alexey A. , Mokievsky Vadim O. , Gantsevich Mikhail M. , Malakhov Vladimir V.
Published: December 2022

In the Russian Arctic seas and adjacent areas of the Arctic basin, 120 sites of siboglinid records are currently known. Individuals belonging to 15 species have been collected. The largest number (49.2%) of records were made in the Barents Sea, followed by the Laptev Sea (37.5%) and the Arctic basin (10 records; 8.3%). No siboglinids have been reported from the Chukchi Sea. The largest number of species has been identified in both the Laptev Sea and Arctic basin (seven species each). Seventy-eight percent of the records were discovered at water depths down to 400 m. Many of the siboglinid records in the Arctic seas of Russia are associated with areas of high hydrocarbon concentrations. In the Barents Sea, Nereilinum murmanicum has been collected near the largest gas fields. The records of Oligobrachia haakonmosbiensis, N. murmanicum, Siboglinum ekmani, Siboglinum hyperboreum, Siboglinum norvegicum, as well as two undetermined species of siboglinids are associated with the marginal areas of bottom gas hydrates where methane emissions can occur. The Arctic seas of Russia feature vast areas of permafrost rocks containing gas hydrates flooded by the sea. Under the influence of river runoff, gas hydrates dissociate, and methane emissions occur. Crispabrachia yenisey and Galathealinum karaense were found in the Yenisei estuary, and O. haakonmosbiensis was found in the Lena estuary.
Value of CT Perfusion for Collateral Status Assessment in Patients with Acute Ischemic Stroke
Authors: Prasetya Haryadi , Tolhuisen Manon L. , Koopman Miou S. , Kappelhof Manon , Meijer Frederick J. A. , Yo Lonneke S. F. , á Nijeholt Geert J. Lycklama , van Zwam Wim H. , van der Lugt Aad , Roos Yvo B. W. E. M. , Majoie Charles B. L. M. , van Bavel Ed T. , Marquering Henk A. ,   on behalf of the MR CLEAN Registry Investigators
Published: December 2022

Good collateral status in acute ischemic stroke patients is an important indicator for good outcomes. Perfusion imaging potentially allows for the simultaneous assessment of local perfusion and collateral status. We combined multiple CTP parameters to evaluate a CTP-based collateral score. We included 85 patients with a baseline CTP and single-phase CTA images from the MR CLEAN Registry. We evaluated patients’ CTP parameters, including relative CBVs and tissue volumes with several time-to-maximum ranges, to be candidates for a CTP-based collateral score. The score candidate with the strongest association with CTA-based collateral score and a 90-day mRS was included for further analyses. We assessed the association of the CTP-based collateral score with the functional outcome (mRS 0–2) by analyzing three regression models: baseline prognostic factors (model 1), model 1 including the CTA-based collateral score (model 2), and model 1 including the CTP-based collateral score (model 3). The model performance was evaluated using C-statistic. Among the CTP-based collateral score candidates, relative CBVs with a time-to-maximum of 6–10 s showed a significant association with CTA-based collateral scores (p = 0.02) and mRS (p = 0.05) and was therefore selected for further analysis. Model 3 most accurately predicted favorable outcomes (C-statistic = 0.86, 95% CI: 0.77–0.94) although differences between regression models were not statistically significant. We introduced a CTP-based collateral score, which is significantly associated with functional outcome and may serve as an alternative collateral measure in settings where MR imaging is not feasible.
Improved Detection of Herpesviruses from Diluted Vitreous Specimens Using Hydrogel Particles
Authors: Belanger Nicole L. , Barbero Robbie , Barclay Robert , Lepene Benjamin , Sobrin Lucia , Bispo Paulo J. M.
Published: December 2022

Infectious uveitis is a sight-threatening infection commonly caused by herpesviruses. Vitreous humor is often collected for molecular confirmation of the causative agent during vitrectomy and mixed in large volumes of buffered saline, diluting the pathogen load. Here, we explore affinity-capture hydrogel particles (Nanotrap®) to concentrate low abundant herpesviruses from diluted vitreous. Simulated samples were prepared using porcine vitreous spiked with HSV-1, HSV-2, VZV and CMV at 105 copies/mL. Pure undiluted samples were used to test capturing capability of three custom Nanotrap particles (red, white and blue) in a vitreous matrix. We found that all particles demonstrated affinity to the herpesviruses, with the Red Particles having both good capture capability and ease of handling for all herpesviruses. To mimic diluted vitrectomy specimens, simulated-infected vitreous were then serially diluted in 7 mL TE buffer. Diluted samples were subjected to an enrichment protocol using the Nanotrap Red particles. Sensitivity of pathogen detection by qPCR in diluted vitreous increased anywhere between 2.3 to 26.5 times compared to non-enriched specimens. This resulted in a 10-fold increase in the limit of detection for HSV-1, HSV-2 and VZV. These data demonstrated that Nanotrap particles can capture and concentrate HSV-1, HSV-2, VZV and CMV in a vitreous matrix.
Correlation of Shear-Wave Elastography and Apparent Diffusion Coefficient Values in Breast Cancer and Their Relationship with the Prognostic Factors
Authors: Orguc Sebnem , Açar Çağdaş Rıza
Published: December 2022

Background: Diffusion-weighted imaging and elastography are widely accepted methods in the evaluation of breast masses, however, there is very limited data comparing the two methods. The apparent diffusion coefficient is a measure of the diffusion of water molecules obtained by diffusion-weighted imaging as a part of breast MRI. Breast elastography is an adjunct to conventional ultrasonography, which provides a noninvasive evaluation of the stiffness of the lesion. Theoretically, increased tissue density and stiffness are related to each other. The purpose of this study is to compare MRI ADC values of the breast masses with quantitative elastography based on ultrasound shear wave measurements and to investigate their possible relation with the prognostic factors and molecular subtypes. Methods: We retrospectively evaluated histopathologically proven 147 breast lesions. The molecular classification of malignant lesions was made according to the prognostic factors. Shear wave elastography was measured in kiloPascal (kPa) units which is a quantitative measure of tissue stiffness. DWI was obtained using a 1.5-T MRI system. Results: ADC values were strongly inversely correlated with elasticity (r = −0.662, p < 0.01) according to Pearson Correlation. In our study, the cut-off value of ADC was 1.00 × 10−3 cm2/s to achieve a sensitivity of 84.6% and specificity of 75.4%, and the cut-off value of elasticity was 105.5 kPa to achieve the sensitivity of 96.3% and specificity 76.9% to discriminate between the malignant and benign breast lesions. The status of prognostic factors was not correlated with the ADC values and elasticity. Conclusions: Elasticity and ADC values are correlated. Both cannot predict the status of prognostic factors and differentiate between molecular subtypes.
Rational and Moral Considerations in Organic Coffee Purchase Intention: Evidence from Indonesia
Authors: Wibowo Setyo , Najib Mukhamad , Sumarwan Ujang , Asnawi Yudha
Published: December 2022

The theory of planned behavior is broadly used to study the buying behavior of green products. However, the theory has been criticized for ignoring moral considerations in the purchase decision and not sufficiently explaining the influence of personal factors such as consumers’ product attributes evaluation. This study aims to build a structural model to explain the causality of factors influencing consumer intention to buy organic coffee in Indonesia. Organic coffee has a bright business prospect, but there was only limited evidence of academic studies on organic coffee from a consumer’s perspective. Thus, this study is one of the attempts to explain organic coffee purchase intention from the perspective of rational and moral consideration. The sample of 500 coffee consumers aged 18 years and more who live or do activities (work/study) in Jakarta were recruited using the purposive sampling technique. Structural equation modeling was utilized for data analysis. The results demonstrated that attitude, subjective norms, perceived behavioral control, and values orientation affected purchase intention. The study successfully explains the role of moral considerations in organic coffee purchase intention. These findings suggest managerial implications, including marketing communication and distribution strategy. Future research suggestions were also discussed.
Automatic Knee Injury Identification through Thermal Image Processing and Convolutional Neural Networks
Authors: Trejo-Chavez Omar , Amezquita-Sanchez Juan P. , Huerta-Rosales Jose R. , Morales-Hernandez Luis A. , Cruz-Albarran Irving A. , Valtierra-Rodriguez Martin
Published: December 2022

Knee injury is a common health problem that affects both people who practice sports and those who do not do it. The high prevalence of knee injuries produces a considerable impact on the health-related life quality of patients. For this reason, it is essential to develop procedures for an early diagnosis, allowing patients to receive timely treatment for preventing and correcting knee injuries. In this regard, this paper presents, as main contribution, a methodology based on infrared thermography (IT) and convolutional neural networks (CNNs) to automatically differentiate between a healthy knee and an injured knee, being an alternative tool to help medical specialists. In general, the methodology consists of three steps: (1) database generation, (2) image processing, and (3) design and validation of a CNN for automatically identifying a patient with an injured knee. In the image-processing stage, grayscale images, equalized images, and thermal images are obtained as inputs for the CNN, where 98.72% of accuracy is obtained by the proposed method. To test its robustness, different infrared images with changes in rotation angle and different brightness levels (i.e., possible conditions at the time of imaging) are used, obtaining 97.44% accuracy. These results demonstrate the effectiveness and robustness of the proposal for differentiating between a patient with a healthy knee and an injured knee, having the advantages of using a fast, low-cost, innocuous, and non-invasive technology.
Implementation and Experimental Verification of Resistorless Fractional-Order Basic Filters
Authors: Patrinos Dimitrios , Tsirmpas Georgios , Bertsias Panagiotis , Psychalinos Costas , Elwakil Ahmed S.
Published: December 2022

Novel structures of fractional-order differentiation and integration stages are presented in this work, where passive resistors are not required for their implementation. This has been achieved by considering the inherent resistive behavior of fractional-order capacitors. The implementation of the presented stages is performed using a current feedback operational amplifier as active element and fractional-order capacitors based on multi-walled carbon nano-tubes. Basic filter and controller stages are realized using the introduced fundamental blocks, and their behavior is evaluated through experimental results.
A Platform for Analysing Huge Amounts of Data from Households, Photovoltaics, and Electrical Vehicles: From Data to Information
Authors: Cano-Ortega Antonio , García-Cumbreras Miguel A. , Sánchez-Sutil Francisco , Hernández Jesús C.
Published: December 2022

Analytics is an essential procedure to acquire knowledge and support applications for determining electricity consumption in smart homes. Electricity variables measured by the smart meter (SM) produce a significant amount of data on consumers, making the data sets very sizable and the analytics complex. Data mining and emerging cloud computing technologies make collecting, processing, and analysing the so-called big data possible. The monitoring and visualization of information aid in personalizing applications that benefit both homeowners and researchers in analysing consumer profiles. This paper presents a smart meter for household (SMH) to obtain load profiles and a new platform that allows the innovative analysis of captured Internet of Things data from smart homes, photovoltaics, and electrical vehicles. We propose the use of cloud systems to enable data-based services and address the challenges of complexities and resource demands for online and offline data processing, storage, and classification analysis. The requirements and system design components are discussed.
Macro Model for Discrete-Time Sigma‒Delta Modulators
Authors: Lee Kye-Shin
Published: December 2022

This work presents a macro model for discrete-time sigma‒delta modulators, which can significantly reduce the simulation time compared to transistor level circuits. The proposed macro model is realized by effectively combining active and passive ideal circuit components with Verilog-A modules. As such, since the macro model is a true representation of the actual transistor level circuit, a moderately good accuracy can be obtained. In addition, the proposed macro model includes the major amplifier, comparator, and switch‒capacitor non-idealities of the sigma‒delta modulator such as amplifier DC gain, GBW, slewrate, comparator bandwidth, hysteresis, parasitic capacitance, and switch-on resistance. The results show the simulation time of the proposed macro model sigma‒delta modulator is only 6.43% of the transistor level circuit with comparable accuracy. As a result, the proposed macro model can facilitate the circuit design and leverage non-ideality analysis of discrete-time sigma‒delta modulators. As a practical design example, a second order discrete-time sigma‒delta modulator with a five-level quantizer is realized using the propose macro model for GSM and WCDMA applications.
Study on Score Prediction Model with High Efficiency Based on Deep Learning
Authors: Yang Lihong , Bai Zhiming
Published: December 2022

In the problem of unified classroom performance prediction, there is a certain lag in the prediction, and there are also problems such as the data sparsity and single feature in the data. In addition, feature engineering is often carried out manually in modeling, which highly depends on the professional knowledge and experience of engineers and affects the accuracy of the prediction to a certain extent. To solve the abovementioned gaps, we proposed an online course score prediction model with a high time efficiency that combines multiple features. The model uses a deep neural network, which can automatically carry out feature engineering and reduce the intervention of artificial feature engineering, thus significantly improving the time efficiency. Secondly, the model uses a factorization machine and two kinds of neural networks to consider the influence of first-order features, second-order features, and higher-order features at the same time, and it fully learns the relationship between the features and scores, which improves the prediction effect of the model compared to using only single feature learning. The performance of the model is evaluated on the learning analysis dataset from Fall 2015 to Spring 2021 and includes 412 courses with 600 students. The experimental results show that the performance of the prediction model based on the feature combination proposed in the present study is better than the previous performance prediction model. More importantly, our model has the best time efficiency of below 0.3 compared to the other models.
Teacher–Student Behavior Recognition in Classroom Teaching Based on Improved YOLO-v4 and Internet of Things Technology
Authors: Chen Henghuai , Guan Jiansheng
Published: December 2022

Based on the classroom teaching scenarios, an improved YOLO-v4 behavior detection algorithm is proposed to recognize the behaviors of teachers and students. With the development of CNN (Convolutional Neural Networks) and IoT (Internet of Things) technologies, target detection algorithms based on deep learning have become mainstream, and typical algorithms such as SSD (Single Shot Detection) and YOLO series have emerged. Based on the videos or images collected in the perception layer of the IoT paradigm, deep learning models are used in the processing layer to implement various intelligent applications. However, none of these deep learning-based algorithms are perfect, and there is room for improvement in terms of detection accuracy, computing speed, and multi-target detection capabilities. In this paper, by introducing the concept of cross-stage local network, embedded connection (EC) components are constructed and embedded at the end of the YOLO-v4 network to obtain an improved YOLO-v4 network. Aiming at the problem that it is difficult to quickly and effectively identify the students’ actions when they are occluded, the Repulsion loss function is connected in series on the basis of the original YOLO-v4 loss function. The newly added loss function consists of two parts: RepGT loss and RepBox loss. The RepGT loss function is used to calculate the loss values between the target prediction box and the adjacent ground truth boxes to reduce false positive detection results; the RepBox loss function is used to calculate the loss value between the target prediction box and other adjacent target prediction boxes to reduce false negative detection results. The training and testing are carried out on the classroom behavior datasets of teachers and students, respectively. The experimental results show that the average precision of identifying various classroom behaviors of different targets exceeds 90%, which verifies the effectiveness of the proposed method. The model performs well in sustainable classroom behavior recognition in educational context, accurate recognition of classroom behaviors can help teachers and students better understand classroom learning and promote the development of intelligent classroom model.
Design and Evaluation of a Personal Robot Playing a Self-Management for Children with Obesity
Authors: Alhmiedat Tareq , Alotaibi Mohammed
Published: December 2022

The preponderance of obesity and being overweight among children has increased significantly during the last two decades in Saudi Arabia and United Arab Emirates (UAE) with overwhelming consequences to public health. Most recommended approaches have paid attention to a healthier diet and physical activity (PA) to reduce obesity. Recent research shows that the use of social robots could play a vital role in encouraging children to improve their skills in self-management. As children need to be surprised and feel a sense of enjoyment when involved in any activity where they can spend time and actively engage in activities, social robots could be an effective intervention for this purpose. In this context, the current project aimed to build an innovation social robot system to offer a set of activities to help obese children improve their capabilities to manage their selves properly and increase their obesity knowledge. This study aimed to determine the perceptions of obese children towards the NAO robot, a new medical technology, and analyze their responses to the robot’s advice and education-related activities. A proposed model of the intervention using the NAO robot is discussed in this study, and a pilot study was conducted to assess the performance of the proposed system. The obtained results showed an average acceptability of 89.37% for social robots to be involved in obesity management.