bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteomics of High-Grade Serous Ovarian Cancer Models Identifies Cancer-Associated Fibroblast Markers Associated with Clinical Outcomes
Authors: Govindarajan Meinusha , Ignatchenko Vladimir , Ailles Laurie , Kislinger Thomas
Published: December 2022

The tumor microenvironment has recently emerged as a critical component of high-grade serous ovarian cancer (HGSC) disease progression. Specifically, cancer-associated fibroblasts (CAFs) have been recognized as key players in various pro-oncogenic processes. Here, we use mass-spectrometry (MS) to characterize the proteomes of HGSC patient-derived CAFs and compare them to those of the epithelial component of HGSC to gain a deeper understanding into their tumor-promoting phenotype. We integrate our data with primary tissue data to define a proteomic signature of HGSC CAFs and uncover multiple novel CAF proteins that are prognostic in an independent HGSC patient cohort. Our data represent the first MS-based global proteomic characterization of CAFs in HGSC and further highlights the clinical significance of HGSC CAFs.
Genotoxic Effect of Dicyclopropanated 5-Vinyl-2-Norbornene
Authors: Novoyatlova Uliana S. , Kessenikh Andrei G. , Kononchuk Olga V. , Bazhenov Sergey V. , Fomkin Alexander A. , Kudryavtseva Anna A. , Shorunov Sergey V. , Bermeshev Maxim V. , Manukhov Ilya V.
Published: December 2022

Dicyclopropanated 5-vinyl-2-norbornene (dcpVNB) is a strained polycyclic hydrocarbon compound with a high energy content, which makes it promising for the development of propellant components based on it. In this work, the genotoxic properties of dcpVNB were studied using whole-cell lux-biosensors based on Escherichia coli and Bacillus subtilis. It was shown that the addition of dcpVNB to bacterial cells leads to the appearance of DNA damage inducing the SOS response and Dps expression with slight activation of the OxyR-mediated response to oxidative stress. The highest toxic effect of dcpVNB is detected by the following lux-biosensors: E. coli pColD-lux, E. coli pDps, B. subtilis pNK-DinC, and B. subtilis pNK-MrgA, in which the genes of bacterial luciferases are transcriptionally fused to the corresponding promoters: Pcda, Pdps, PdinC, and PmrgA. It was shown that lux-biosensors based on B. subtilis, and E. coli are almost equally sensitive to dcpVNB, which indicates the same permeability to this compound of cell wall of Gram-positive and Gram-negative bacteria. The activation of Pdps after dcpVNB addition maintains even in oxyR mutant E. coli strains, which means that the Pdps induction is only partially determined by the OxyR/S regulon. Comparison of specific stress effects caused by dcpVNB and 2-ethyl(bicyclo[2.2.1]heptane) (EBH), characterized by the absence of cyclopropanated groups, shows that structural changes in hydrocarbons could significantly change the mode of toxicity.
Store-Operated Calcium Entry in Breast Cancer Cells Is Insensitive to Orai1 and STIM1 N-Linked Glycosylation
Authors: Sanchez-Collado Jose , Nieto-Felipe Joel , Jardin Isaac , Bhardwaj Rajesh , Berna-Erro Alejandro , Salido Gines M. , Smani Tarik , Hediger Matthias A , Lopez Jose J. , Rosado Juan A.
Published: December 2022

N-linked glycosylation is a post-translational modification that affects protein function, structure, and interaction with other proteins. The store-operated Ca2+ entry (SOCE) core proteins, Orai1 and STIM1, exhibit N-glycosylation consensus motifs. Abnormal SOCE has been associated to a number of disorders, including cancer, and alterations in Orai1 glycosylation have been related to cancer invasiveness and metastasis. Here we show that treatment of non-tumoral breast epithelial cells with tunicamycin attenuates SOCE. Meanwhile, tunicamycin was without effect on SOCE in luminal MCF7 and triple negative breast cancer (TNBC) MDA-MB-231 cells. Ca2+ imaging experiments revealed that expression of the glycosylation-deficient Orai1 mutant (Orai1N223A) did not alter SOCE in MCF10A, MCF7 and MDA-MB-231 cells. However, expression of the non-glycosylable STIM1 mutant (STIM1N131/171Q) significantly attenuated SOCE in MCF10A cells but was without effect in SOCE in MCF7 and MDA-MB-231 cells. In non-tumoral cells impairment of STIM1 N-linked glycosylation attenuated thapsigargin (TG)-induced caspase-3 activation while in breast cancer cells, which exhibit a smaller caspase-3 activity in response to TG, expression of the non-glycosylable STIM1 mutant (STIM1N131/171Q) was without effect on TG-evoked caspase-3 activation. Summarizing, STIM1 N-linked glycosylation is essential for full SOCE activation in non-tumoral breast epithelial cells; by contrast, SOCE in breast cancer MCF7 and MDA-MB-231 cells is insensitive to Orai1 and STIM1 N-linked glycosylation, and this event might participate in the development of apoptosis resistance.
Epimutations and Their Effect on Chromatin Organization: Exciting Avenues for Cancer Treatment
Authors: Mohammad Asad , Jha Sudhakar
Published: December 2022

The three-dimensional architecture of genomes is complex. It is organized as fibers, loops, and domains that form high-order structures. By using different chromosome conformation techniques, the complex relationship between transcription and genome organization in the three-dimensional organization of genomes has been deciphered. Epigenetic changes, such as DNA methylation and histone modification, are the hallmark of cancers. Tumor initiation, progression, and metastasis are linked to these epigenetic modifications. Epigenetic inhibitors can reverse these altered modifications. A number of epigenetic inhibitors have been approved by FDA that target DNA methylation and histone modification. This review discusses the techniques involved in studying the three-dimensional organization of genomes, DNA methylation and histone modification, epigenetic deregulation in cancer, and epigenetic therapies targeting the tumor.
Mineralization of Riluzole by Heterogeneous Fenton Oxidation Using Natural Iron Catalysts
Authors: Bensalah Nasr , Neily Emna , Bedoui Ahmed , Ahmad Mohammad I.
Published: December 2022

Fenton (H2O2/Fe2+) system is a simple and efficient advanced oxidation technology (AOT) for the treatment of organic micropollutants in water and soil. However, it suffers from some drawbacks including high amount of the catalyst, acid pH requirement, sludge formation and slow regeneration of Fe2+ ions. If these drawbacks are surmounted, Fenton system can be the best choice AOT for the removal of persistent organics from water and soil. In this work, it was attempted to replace the homogeneous catalyst with a heterogeneous natural iron-based catalyst for the decomposition of H2O2 into oxidative radical species, mainly hydroxyl (HO•) and hydroperoxyl radicals (HO2•). The natural iron-based catalyst is hematite-rich (α-Fe2O3) and contains a nonnegligible amount of magnetite (Fe3O4) indicating the coexistence of Fe (III) and Fe(II) species. A pseudo-first order kinetics was determined for the decomposition of H2O2 by the iron-based solid catalyst with a rate constant increasing with the catalyst dose. The catalytic decomposition of H2O2 into hydroxyl radicals in the presence of the natural Fe-based catalyst was confirmed by the hydroxylation of benzoic acid into salicylic acid. The natural Fe-based catalyst/H2O2 system was applied for the degradation of riluzole in water. It was demonstrated that the smaller the particle size of the catalyst, the larger its surface area and the greater its catalytic activity towards H2O2 decomposition into hydroxyl radicals. The degradation of riluzole can occur at all pH levels in the range 3.0–12.0 with a rate and efficiency greater than H2O2 oxidation alone, indicating that the natural Fe-based catalyst can function at any pH without the need to control the pH by the addition of chemicals. An improvement in the efficiency and kinetics of the degradation of riluzole was observed under UV irradiation for both homogeneous and heterogeneous Fenton systems. The results chromatography analysis demonstrate that the degradation of riluzole starts by the opening of the triazole ring by releasing nitrate, sulfate, and fluoride ions. The reuse of the catalyst after heat treatment at 500 °C demonstrated that the heat-treated catalyst retained an efficiency >90% after five cycles. The results confirmed that the natural sources of iron, as a heterogeneous catalyst in a Fenton-like system, is an appropriate replacement of a Fe2+ homogeneous catalyst. The reuse of the heterogeneous catalyst after a heat-treatment represents an additional advantage of using a natural iron-based catalyst in Fenton-like systems.
Insight into the Effect of Oxygen Vacancy Prepared by Different Methods on CuO/Anatase Catalyst for CO Catalytic Oxidation
Authors: Chen Wei , Shen Huan , Zhu Xiaoxiao , Liu Guoli , Pan Chuanqi , Huang Fajun , Fang Yarong , Guo Yanbing , Luo Zhu
Published: December 2022

In this study, CuO loaded on anatase TiO2 catalysts (CuO/anatase) with oxygen vacancies was synthesized via reduction treatments by NaHB4 and H2 (CuO/anatase-B, CuO/anatase-H), respectively. The characterizations suggest that different reduction treatments bring different concentration of oxygen vacancies in the CuO/anatase catalysts, which finally affect the CO catalytic performance. The CuO/anatase-B and CuO/anatase-H exhibit CO conversion of 90% at 182 and 198 °C, respectively, which is lower than what occurred for CuO/anatase (300 °C). The XRD, Raman, and EPR results show that the amount of the oxygen vacancies of the CuO/anatase-H is the largest, indicating a stronger reduction effect of H2 than NaHB4 on the anatase surface. The in situ DRIFTS results exhibit that the Cu sites are the adsorption sites of CO, and the oxygen vacancies on the anatase can active the O2 molecules into reactive oxygen species. According to the in situ DRIFTS results, it can be concluded that in the CO oxidation reaction, only the CuO/anatase-H catalyst can be carried out by the Mvk mechanism, which greatly improves its catalytic efficiency. This study explained the reaction mechanisms of CO oxidation on various anatase surfaces, which offers detailed insights into how to prepare suitable catalysts for low-temperature oxidation reactions.
Human Neutrophils Generate Extracellular Vesicles That Modulate Their Functional Responses
Authors: Hurtado Gutiérrez María José , Allard Frédérick L. , Mosha Hugo Tshivuadi , Dubois Claire M. , McDonald Patrick P.
Published: December 2022

Neutrophils influence innate and adaptive immunity by releasing various cytokines and chemokines, by generating neutrophil extracellular traps (NETs), and by modulating their own survival. Neutrophils also produce extracellular vesicles (EVs) termed ectosomes, which influence the function of other immune cells. Here, we studied neutrophil-derived ectosomes (NDEs) and whether they can modulate autologous neutrophil responses. We first characterized EV production by neutrophils, following MISEV 2018 guidelines to facilitate comparisons with other studies. We found that such EVs are principally NDEs, that they are rapidly released in response to several (but not all) physiological stimuli, and that a number of signaling pathways are involved in the induction of this response. When co-incubated with autologous neutrophils, NDE constituents were rapidly incorporated into recipient cells and this triggered and/or modulated neutrophil responses. The pro-survival effect of GM-CSF, G-CSF, IFNγ, and dexamethasone was reversed; CXCL8 and NET formation were induced in otherwise unstimulated neutrophils; the induction of inflammatory chemokines by TNFα was modulated depending on the activation state of the NDEs’ parent cells; and inducible NET generation was attenuated. Our data show that NDE generation modulates neutrophil responses in an autocrine and paracrine manner, and indicate that this probably represents an important aspect of how neutrophils shape their environment and cellular interactions.
The Cytokine Network in Colorectal Cancer: Implications for New Treatment Strategies
Authors: Braumüller Heidi , Mauerer Bernhard , Andris Johanna , Berlin Christopher , Wieder Thomas , Kesselring Rebecca
Published: December 2022

Colorectal cancer (CRC) is one of the most frequent tumor entities worldwide with only limited therapeutic options. CRC is not only a genetic disease with several mutations in specific oncogenes and/or tumor suppressor genes such as APC, KRAS, PIC3CA, BRAF, SMAD4 or TP53 but also a multifactorial disease including environmental factors. Cancer cells communicate with their environment mostly via soluble factors such as cytokines, chemokines or growth factors to generate a favorable tumor microenvironment (TME). The TME, a heterogeneous population of differentiated and progenitor cells, plays a critical role in regulating tumor development, growth, invasion, metastasis and therapy resistance. In this context, cytokines from cancer cells and cells of the TME influence each other, eliciting an inflammatory milieu that can either enhance or suppress tumor growth and metastasis. Additionally, several lines of evidence exist that the composition of the microbiota regulates inflammatory processes, controlled by cytokine secretion, that play a role in carcinogenesis and tumor progression. In this review, we discuss the cytokine networks between cancer cells and the TME and microbiome in colorectal cancer and the related treatment strategies, with the goal to discuss cytokine-mediated strategies that could overcome the common therapeutic resistance of CRC tumors.
Identification of R-Spondin Gene Signature Predictive of Metastatic Progression in BRAFV600E-Positive Papillary Thyroid Cancer
Authors: da Silva Sabrina Daniela , Morand Grégoire B. , Diesel Luciana , de Lima Jefferson Muniz , Bijian Krikor , Kailasam Senthilkumar , Lefebvre Francois , Bourque Guillaume , Hier Michael , Alaoui-Jamali Moulay A.
Published: December 2022

Papillary thyroid carcinoma (PTC) is the most common malignancy of the thyroid gland and early stages are curable. However, a subset of PTCs shows an unusually aggressive phenotype with extensive lymph node metastasis and higher incidence of locoregional recurrence. In this study, we investigated a large cohort of PTC cases with an unusual aggressive phenotype using a high-throughput RNA sequencing (RNA-Seq) to identify differentially regulated genes associated with metastatic PTC. All metastatic PTC with mutated BRAF (V600E) but not BRAF wild-type expressed an up-regulation of R-Spondin Protein 4 (RSPO4) concomitant with an upregulation of genes involved in focal adhesion and cell-extracellular matrix signaling. Further immunohistochemistry validation confirmed the upregulation of these target genes in metastatic PTC cases. Preclinical studies using established PTC cell lines support that RSPO4 overexpression is associated with BRAF V600E mutation and is a critical upstream event that promote activation of kinases of focal adhesion signaling known to drive cancer cell locomotion and invasion. This finding opens up the potential of co-targeting B-Raf, RSPO and focal adhesion proteins as a pharmacological approach for aggressive BRAF V600E PTC.
Cytotoxic CD8+ T Cells Are Involved in the Thrombo-Inflammatory Response during First-Diagnosed Atrial Fibrillation
Authors: Friebel Julian , Witkowski Marco , Wegner Max , Blöbaum Leon , Lammel Stella , Schencke Philipp-Alexander , Jakobs Kai , Puccini Marianna , Reißner Daniela , Steffens Daniel , Moos Verena , Schutheiss Heinz-Peter , Landmesser Ulf , Rauch Ursula
Published: December 2022

Background: Atrial myopathy and atrial fibrillation (AF) accompany thrombo-inflammation. This facilitates disease progression and promotes major adverse cardiovascular events (MACEs). Thrombin receptor (protease-activated receptor 1, PAR1) signalling is central in mediating thrombo-inflammation. We hypothesised that PAR1 signalling links coagulation and inflammation through cytotoxic CD8+ T lymphocytes in patients presenting with first-diagnosed AF (FDAF). Methods: A total of 210 patients were studied. We included data and blood samples from patients presenting with FDAF (n = 160), cardiac tissue from patients with paroxysmal AF (n = 32) and 20 controls. Results: During early AF, a pro-inflammatory and cytotoxic subset of T lymphocytes (CD8+) circulated more frequently when compared to patients with chronic cardiovascular disease but without AF, accompanied by elevated plasma levels of CD8+ effector molecules, which corresponded to biomarkers of adverse cardiac remodelling and atrial dysfunction. Activation of tissue factor (TF) and PAR1 was associated with pro-inflammatory and cytotoxic effector functions. PAR1-related CD8+ cell activation was more frequent in FDAF patients that experienced a MACE. Conclusions: In patients with FDAF, the TF-factor Xa-factor IIa-axis contributes to thrombo-inflammation via PAR1 in CD8+ T cells. Intervening in this cascade might be a promising synergistic approach to reducing disease progression and the vascular complications of AF.
Diverse Begomoviruses Evolutionarily Hijack Plant Terpenoid-Based Defense to Promote Whitefly Performance
Authors: Wang Ning , Zhao Pingzhi , Wang Duan , Mubin Muhammad , Fang Rongxiang , Ye Jian
Published: December 2022

Arthropod-borne pathogens and parasites are major threats to human health and global agriculture. They may directly or indirectly manipulate behaviors of arthropod vector for rapid transmission between hosts. The largest genus of plant viruses, Begomovirus, is transmitted exclusively by whitefly (Bemisia tabaci), a complex of at least 34 morphologically indistinguishable species. We have previously shown that plants infected with the tomato yellowleaf curl China virus (TYLCCNV) and its associated betasatellite (TYLCCNB) attract their whitefly vectors by subverting plant MYC2-regulated terpenoid biosynthesis, therefore forming an indirect mutualism between virus and vector via plant. However, the evolutionary mechanism of interactions between begomoviruses and their whitefly vectors is still poorly understood. Here we present evidence to suggest that indirect mutualism may happen over a millennium ago and at present extensively prevails. Detailed bioinformatics and functional analysis identified the serine-33 as an evolutionary conserved phosphorylation site in 105 of 119 Betasatellite species-encoded βC1 proteins, which are responsible for suppressing plant terpenoid-based defense by interfering with MYC2 dimerization and are essential to promote whitefly performance. The substitution of serine-33 of βC1 proteins with either aspartate (phosphorylation mimic mutants) or cysteine, the amino acid in the non-functional sβC1 encoded by Siegesbeckia yellow vein betasatellite SiYVB) impaired the ability of βC1 functions on suppression of MYC2 dimerization, whitefly attraction and fitness. Moreover the gain of function mutation of cysteine-31 to serine in sβC1 protein of SiYVB restored these functions of βC1 protein. Thus, the dynamic phosphorylation of serine-33 in βC1 proteins helps the virus to evade host defense against insect vectors with an evolutionarily conserved manner. Our data provide a mechanistic explanation of how arboviruses evolutionarily modulate host defenses for rapid transmission.
Single-Cell Analysis 2.0
Authors: Santra Tuhin Subhra , Tseng Fan-Gang
Published: December 2022

In 1665, Robert Hooke published his revolutionary book Micrographia [...]
University Students’ Satisfaction with the Quality of Primary Dental Healthcare Services and Dentists in Croatia: A Cross-Sectional Study
Authors: Tadin Antonija , Dadic Marijeta , Gavic Lidia
Published: December 2022

Measuring satisfaction can be an essential method for evaluating and improving healthcare quality. Therefore, this survey aimed to determine university students’ satisfaction with dental care at the primary healthcare level and the factors that influence students’ decisions when choosing a dental provider. A cross-sectional survey was conducted using a self-administered electronic questionnaire that assessed satisfaction with various aspects of dental care (patient–staff interaction, professional and technical competence, and administrative efficiency) on a 5-point Likert scale. A total of 806 students participated in the survey, of whom 56.6% were from a biomedical science background, and 43.4% from other scientific fields. Near-minimal differences were found between respondents studying in biomedical fields and those from other scientific fields, when evaluating satisfaction with dental services. More significant differences were found in the factors influencing their choice of dentist. The dentist’s experience (p = 0.031), cost of service (p ≤ 0.001), office location (p = 0.034), waiting time (p = 0.029), qualifications (p = 0.033), and gender (p = 0.007) were more important for students pursuing one of the non-health-related majors. Overall, respondents were very satisfied with their dentists and the services provided. The highest satisfaction score was found on the “professional and technical competence” and “administrative efficiency” subscales, while the lowest satisfaction score was found on the “patient–staff interaction” subscale.
Anti-Fouling Behaviors of a Modified Surface Induced by an Ultrasonic Surface Rolling Process for 304 Stainless Steel
Authors: Sui Rongjuan , Zhang Guanghui , Liu Haiyan
Published: December 2022

This research aimed to investigate the effects of an ultrasonic surface rolling process (USRP) on the deposition behaviors in CaCO3 crystallization fouling for 304 stainless steel (304SS). The microstructure, surface morphology, and hydrophobic properties of the modified layer were characterized with optical microscopy, a roughness profile measurement instrument, and a contact angle measurement instrument. The corrosion and fouling behaviors of different surfaces were studied in simulated cooling water. The polarization curves and electrochemical impedance spectroscopy (EIS) were used to evaluate the electrochemical properties. The results showed that USRP-treated surfaces had better anti-corrosion and anti-fouling performance. The improvement in anti-fouling performance was attributed to the weakening of peaks and valleys, the reduction of surface defects, and the improvement of corrosion resistance.
Optical Properties of ITO/Glass Substrates Modified by Silver Nanoparticles for PV Applications
Authors: Wisz Grzegorz , Potera Piotr , Sawicka-Chudy Paulina , Gwóźdź Katarzyna
Published: December 2022

The paper describes the research on optical properties of glass/ITO/Ag thin layers obtained on glass/ITO substrates with different properties. The authors will discuss the influence of silver particles and silver layer thickness on the transmission and reflection spectra of the layers and parameters, such as the width of the optical band gap, refractive index, and dieelectric function. For example, the presence of silver leads to a decrease in the transmission of the layers (compared to ITO/glass) regardless of the thickness of the silver layer, and in the case of reflection, both its increase and decrease were observed, depending on the thickness of the silver layer and the type of glass/ITO substrate used. The average transmission value in the visible region depends on the thickness of the silver nanoparticle layer and varies from ~50% to ~90%. The average refractive index takes values from the range ~1.4 to ~1.65 and does not depend on the presence and thickness of the silver layer.
Influence of Temperature and Flow Ratio on the Morphology and Uniformity of 4H-SiC Epitaxial Layers Growth on 150 mm 4° Off-Axis Substrates
Authors: Tang Zhuorui , Gu Lin , Ma Hongping , Mao Chaobin , Wu Sanzhong , Zhang Nan , Huang Jiyu , Fan Jiajie
Published: December 2022

The homoepitaxial growth of 4H-SiC films was conducted on 4H-SiC 150 mm 4° off-axis substrates by using a home-made hot-wall chemical vapor deposition (CVD) reactor. Special attention was paid to the influence of the growth temperature on the surface morphology, growth rate, doping efficiency, and structural uniformity of the films. Among the above factors, growth temperature and flow ratio were shown to be the essential parameters to produce high-quality homoepitaxial layers. Furthermore, a two-side flow tunnel was introduced to control the growth temperature nonuniformity in the reactor. The influence of flow ratio on the epitaxial layer uniformity was also studied. It was found that the surface roughness increased with the increasing temperature, achieving its minimum value of 0.183 nm at 1610 °C. Besides that, the film growth rate decreased with the increase in growth temperature, whereas the degrees of thickness non-uniformity, N2 doping non-uniformity, and doping efficiency increased. Meanwhile, both the thickness and doping uniformity can be improved by adjusting H2 and N2 flow ratios, respectively. In particular, the use of the H2 ratio of 1.63 and N2 ratio of 0.92 enabled one to increase the degree of uniformity of thickness and doping by 0.79% (standard deviation/mean value) and 3.56% (standard deviation/mean value), respectively, at the growth temperature of 1630 °C.
New Spin on Metal-Insulator Transitions
Authors: Pustogow Andrej
Published: December 2022

Metal-insulator transitions (MITs) constitute a core subject of fundamental condensed-matter research [...]
Effect of the Initial Grain Size on Laser Beam Weldability for High-Entropy Alloys
Authors: Park Cheolho , Hwang Taewoo , Kim Gi-Dong , Nam Hyunbin , Kang Namhyun
Published: December 2022

This study investigated the effect of the initial grain size on the laser beam weldability of CoCrFeMnNi high-entropy alloys (HEAs). Cold-rolled, annealed, and cast HEAs with different initial grain sizes exhibited clear differences in weldability. The cold-rolled, annealed, and cast HEAs exhibited grain sizes of 1.5, 8.1, and 1.1 mm, respectively. The grain size of the weld metal (WM) in cold-rolled/annealed HEAs was coarser than that of the base metal (BM), whereas the grain size of the WM in the cast HEA was finer than that of the BM. Shrinkage voids were present in the central region of all laser WMs. The cold-rolled and annealed HEA exhibited a tensile strength greater than 600 MPa owing to the grain size of the coarse WM and the presence of shrinkage voids; however, tensile fracture occurred in the central region of the WM. However, because the grain size of the cast HEA BM was finer than that of the WM, the tensile fracture occurred in the BM, and it had the same tensile properties as the BM. Therefore, the laser weldability of the HEA depended on the initial grain size, and the grain refinement of the WM was essential for improving the weldability.
Morphological and Genetic Differentiation of Loliolus (Nipponololigo) beka (Cephalopoda: Loliginidae) in Coastal China
Authors: Li Shuwen , Lyu Yuhan , Zhang Chi , Zheng Xiaodong
Published: December 2022

The population genetic structure of 211 samples of Loliolus (Nipponololigo) beka, which were selected from across seven geographic localities—in the Bohai Sea, the Yellow Sea and the East China Sea—were analyzed using mitochondrial COI and 16S rRNA gene markers. Phylogenetic trees and a haplotype network both showed that the L. (N.) beka localities were genetically distinct, forming two homogeneous lineages: Lineage A and Lineage B. The results of an AMOVA showed that the genetic variation in the L. (N.) beka populations was dominated by the genetic variation between the two lineages, and both the genetic distance and genetic differentiation indices indicated that the genetic differentiation between the two lineages of L. (N.) beka in Chinese waters had reached the level of species divergence. To further confirm the differences between the two lineages shown in the molecular results, we performed a detailed analysis based on morphometric observations and a multivariate statistical analysis to compare the morphology characteristics of Lineage A and Lineage B. The results showed that there were significant differences (p < 0.05) in the ventral mantle length (VML); the mantle width index (MWI); the fin width index (FWI); the head length index (HLI); the left Arm IV length index (LALI4), the right Arm III length index (RALI3), the right Arm IV length index (RALI4), and the hectocotylized proportion of the left Arm IV length (HcL%) between the two lineages. The differences between the two lineages were also supported by the analysis results for the number of sucker ring teeth. Accordingly, the results of the morphological analysis further confirmed the molecular analysis and provided additional evidence for the presence of the cryptic species of L. (N.) beka in the coastal areas of China.
Threatened Trees Characteristic of Mexican Tropical Montane Cloud Forests
Authors: Luna-Vega Isolda , Alcántara-Ayala Othón , García-Morales Leccinum , Espinosa David , Ramírez-Martínez Julio , Contreras-Medina Raúl
Published: December 2022

In this study, we document the distribution, current knowledge, and conservation of twenty-six tree species of gymnosperms (four species) and angiosperms (twenty-two species) characteristic of the Mexican cloud forests and most endemic to Mexico. Many species are threatened and included in international and national Red Data List, such as the IUCN, and the Mexican Official Norm (NOM-059-SEMARNAT-2010). Distribution maps of these 26 species were generated based on information from herbarium specimens, specialized literature, web databases, and our own field surveys. All records were displayed on a map of the Mexican territory divided into grid cells of 15 × 20 min of latitude/longitude (a spatial resolution of approximately 27.75 km × 36.75 km) to obtain the richness patterns. Additionally, these records were displayed on the map of the current Mexican System of Natural Protected Areas (NPAs) to evaluate their representativeness in these areas of in situ conservation. We also include information on populations and the habitat status of these tree species in some Mexican locations. Most species studied here require particular policies for their conservation due to the problems affecting their natural populations and habitat. Our results indicate that three species are not represented in the Mexican System of NPAs and that some are underrepresented.
Cross Cultivation on Homologous/Heterologous Plant-Based Culture Media Empowers Host-Specific and Real Time In Vitro Signature of Plant Microbiota
Authors: Elsawey Hend , Nour Eman H. , Elsayed Tarek R. , Nemr Rahma A. , Youssef Hanan H. , Hamza Mervat A. , Abbas Mohamed , El-Tahan Mahmoud , Fayez Mohamed , Ruppel Silke , Hegazi Nabil A.
Published: December 2022

Alliances of microbiota with plants are masked by the inability of in vitro cultivation of their bulk. Pure cultures piled in international centers originated from dissimilar environments/hosts. Reporting that plant root/leaf-based culture media support the organ-specific growth of microbiota, it was of interest to further investigate if a plant-based medium prepared from homologous (maize) supports specific/adapted microbiota compared to another prepared from heterologous plants (sunflower). The culture-independent community of maize phyllosphere was compared to communities cross-cultivated on plant broth-based media: CFU counts and taxa prevalence (PCR-DGGE; Illumina MiSeq amplicon sequencing). Similar to total maize phyllospheric microbiota, culture-dependent communities were overwhelmed by Proteobacteria (>94.3–98.3%); followed by Firmicutes (>1.3–3.7%), Bacteroidetes (>0.01–1.58%) and Actinobacteria (>0.06–0.34%). Differential in vitro growth on homologous versus heterologous plant-media enriched/restricted various taxa. In contrast, homologous cultivation over represented members of Proteobacteria (ca. > 98.0%), mainly Pseudomonadaceae and Moraxellaceae; heterologous cultivation and R2A enriched Firmicutes (ca. > 3.0%). The present strategy simulates/fingerprints the chemical composition of host plants to expand the culturomics of plant microbiota, advance real-time in vitro cultivation and lab-keeping of compatible plant microbiota, and identify preferential pairing of plant-microbe partners toward future synthetic community (SynComs) research and use in agriculture.
Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions
Authors: Anton Nicoleta , Doroftei Bogdan , Curteanu Silvia , Catãlin Lisa , Ilie Ovidiu-Dumitru , Târcoveanu Filip , Bogdănici Camelia Margareta
Published: December 2022

Background: Having several applications in medicine, and in ophthalmology in particular, artificial intelligence (AI) tools have been used to detect visual function deficits, thus playing a key role in diagnosing eye diseases and in predicting the evolution of these common and disabling diseases. AI tools, i.e., artificial neural networks (ANNs), are progressively involved in detecting and customized control of ophthalmic diseases. The studies that refer to the efficiency of AI in medicine and especially in ophthalmology were analyzed in this review. Materials and Methods: We conducted a comprehensive review in order to collect all accounts published between 2015 and 2022 that refer to these applications of AI in medicine and especially in ophthalmology. Neural networks have a major role in establishing the demand to initiate preliminary anti-glaucoma therapy to stop the advance of the disease. Results: Different surveys in the literature review show the remarkable benefit of these AI tools in ophthalmology in evaluating the visual field, optic nerve, and retinal nerve fiber layer, thus ensuring a higher precision in detecting advances in glaucoma and retinal shifts in diabetes. We thus identified 1762 applications of artificial intelligence in ophthalmology: review articles and research articles (301 pub med, 144 scopus, 445 web of science, 872 science direct). Of these, we analyzed 70 articles and review papers (diabetic retinopathy (N = 24), glaucoma (N = 24), DMLV (N = 15), other pathologies (N = 7)) after applying the inclusion and exclusion criteria. Conclusion: In medicine, AI tools are used in surgery, radiology, gynecology, oncology, etc., in making a diagnosis, predicting the evolution of a disease, and assessing the prognosis in patients with oncological pathologies. In ophthalmology, AI potentially increases the patient’s access to screening/clinical diagnosis and decreases healthcare costs, mainly when there is a high risk of disease or communities face financial shortages. AI/DL (deep learning) algorithms using both OCT and FO images will change image analysis techniques and methodologies. Optimizing these (combined) technologies will accelerate progress in this area.
Primary Tumor Radiomic Model for Identifying Extrahepatic Metastasis of Hepatocellular Carcinoma Based on Contrast Enhanced Computed Tomography
Authors: Chan Lawrence Wing Chi , Wong Sze Chuen Cesar , Cho William Chi Shing , Huang Mohan , Zhang Fei , Chui Man Lik , Lai Una Ngo Yin , Chan Tiffany Yuen Kwan , Cheung Zoe Hoi Ching , Cheung Jerry Chun Yin , Tang Kin Fu , Tse Man Long , Wong Hung Kit , Kwok Hugo Man Fung , Shen Xinping , Zhang Sailong , Chiu Keith Wan Hang
Published: December 2022

This study aimed to identify radiomic features of primary tumor and develop a model for indicating extrahepatic metastasis of hepatocellular carcinoma (HCC). Contrast-enhanced computed tomographic (CT) images of 177 HCC cases, including 26 metastatic (MET) and 151 non-metastatic (non-MET), were retrospectively collected and analyzed. For each case, 851 radiomic features, which quantify shape, intensity, texture, and heterogeneity within the segmented volume of the largest HCC tumor in arterial phase, were extracted using Pyradiomics. The dataset was randomly split into training and test sets. Synthetic Minority Oversampling Technique (SMOTE) was performed to augment the training set to 145 MET and 145 non-MET cases. The test set consists of six MET and six non-MET cases. The external validation set is comprised of 20 MET and 25 non-MET cases collected from an independent clinical unit. Logistic regression and support vector machine (SVM) models were identified based on the features selected using the stepwise forward method while the deep convolution neural network, visual geometry group 16 (VGG16), was trained using CT images directly. Grey-level size zone matrix (GLSZM) features constitute four of eight selected predictors of metastasis due to their perceptiveness to the tumor heterogeneity. The radiomic logistic regression model yielded an area under receiver operating characteristic curve (AUROC) of 0.944 on the test set and an AUROC of 0.744 on the external validation set. Logistic regression revealed no significant difference with SVM in the performance and outperformed VGG16 significantly. As extrahepatic metastasis workups, such as chest CT and bone scintigraphy, are standard but exhaustive, radiomic model facilitates a cost-effective method for stratifying HCC patients into eligibility groups of these workups.
Multi-Stage Temporal Convolutional Network with Moment Loss and Positional Encoding for Surgical Phase Recognition
Authors: Park Minyoung , Oh Seungtaek , Jeong Taikyeong , Yu Sungwook
Published: December 2022

In recent times, many studies concerning surgical video analysis are being conducted due to its growing importance in many medical applications. In particular, it is very important to be able to recognize the current surgical phase because the phase information can be utilized in various ways both during and after surgery. This paper proposes an efficient phase recognition network, called MomentNet, for cholecystectomy endoscopic videos. Unlike LSTM-based network, MomentNet is based on a multi-stage temporal convolutional network. Besides, to improve the phase prediction accuracy, the proposed method adopts a new loss function to supplement the general cross entropy loss function. The new loss function significantly improves the performance of the phase recognition network by constraining un-desirable phase transition and preventing over-segmentation. In addition, MomnetNet effectively applies positional encoding techniques, which are commonly applied in transformer architectures, to the multi-stage temporal convolution network. By using the positional encoding techniques, MomentNet can provide important temporal context, resulting in higher phase prediction accuracy. Furthermore, the MomentNet applies label smoothing technique to suppress overfitting and replaces the backbone network for feature extraction to further improve the network performance. As a result, the MomentNet achieves 92.31% accuracy in the phase recognition task with the Cholec80 dataset, which is 4.55% higher than that of the baseline architecture.
Interpretable Machine Learning Techniques in ECG-Based Heart Disease Classification: A Systematic Review
Authors: Ayano Yehualashet Megersa , Schwenker Friedhelm , Dufera Bisrat Derebssa , Debelee Taye Girma
Published: December 2022

Heart disease is one of the leading causes of mortality throughout the world. Among the different heart diagnosis techniques, an electrocardiogram (ECG) is the least expensive non-invasive procedure. However, the following are challenges: the scarcity of medical experts, the complexity of ECG interpretations, the manifestation similarities of heart disease in ECG signals, and heart disease comorbidity. Machine learning algorithms are viable alternatives to the traditional diagnoses of heart disease from ECG signals. However, the black box nature of complex machine learning algorithms and the difficulty in explaining a model’s outcomes are obstacles for medical practitioners in having confidence in machine learning models. This observation paves the way for interpretable machine learning (IML) models as diagnostic tools that can build a physician’s trust and provide evidence-based diagnoses. Therefore, in this systematic literature review, we studied and analyzed the research landscape in interpretable machine learning techniques by focusing on heart disease diagnosis from an ECG signal. In this regard, the contribution of our work is manifold; first, we present an elaborate discussion on interpretable machine learning techniques. In addition, we identify and characterize ECG signal recording datasets that are readily available for machine learning-based tasks. Furthermore, we identify the progress that has been achieved in ECG signal interpretation using IML techniques. Finally, we discuss the limitations and challenges of IML techniques in interpreting ECG signals.
GAR-Net: Guided Attention Residual Network for Polyp Segmentation from Colonoscopy Video Frames
Authors: Raymann Joel , Rajalakshmi Ratnavel
Published: December 2022

Colorectal Cancer is one of the most common cancers found in human beings, and polyps are the predecessor of this cancer. Accurate Computer-Aided polyp detection and segmentation system can help endoscopists to detect abnormal tissues and polyps during colonoscopy examination, thereby reducing the chance of polyps growing into cancer. Many of the existing techniques fail to delineate the polyps accurately and produce a noisy/broken output map if the shape and size of the polyp are irregular or small. We propose an end-to-end pixel-wise polyp segmentation model named Guided Attention Residual Network (GAR-Net) by combining the power of both residual blocks and attention mechanisms to obtain a refined continuous segmentation map. An enhanced Residual Block is proposed that suppresses the noise and captures low-level feature maps, thereby facilitating information flow for a more accurate semantic segmentation. We propose a special learning technique with a novel attention mechanism called Guided Attention Learning that can capture the refined attention maps both in earlier and deeper layers regardless of the size and shape of the polyp. To study the effectiveness of the proposed GAR-Net, various experiments were carried out on two benchmark collections viz., CVC-ClinicDB (CVC-612) and Kvasir-SEG dataset. From the experimental evaluations, it is shown that GAR-Net outperforms other previously proposed models such as FCN8, SegNet, U-Net, U-Net with Gated Attention, ResUNet, and DeepLabv3. Our proposed model achieves 91% Dice co-efficient and 83.12% mean Intersection over Union (mIoU) on the benchmark CVC-ClinicDB (CVC-612) dataset and 89.15% dice co-efficient and 81.58% mean Intersection over Union (mIoU) on the Kvasir-SEG dataset. The proposed GAR-Net model provides a robust solution for polyp segmentation from colonoscopy video frames.
Sustainability in Digital Education: A Systematic Review of Innovative Proposals
Authors: García-Hernández Alién , García-Valcárcel Muñoz-Repiso Ana , Casillas-Martín Sonia , Cabezas-González Marcos
Published: December 2022

In the last decade, the extensive use of new Information and Communication Technologies (ICT) in education in recent years has changed the nature of the teaching–learning environment. However, the adequate use of ICT is necessary for promoting educational practices that contribute to sustainable development. The systematization of the research in this area is presented as an opportunity to provide a contribution to the already existing theories and practices related to the use of ICT and the development of the Sustainable Development Goals (SDGs). The aim of this study is to conduct a systematic review of articles that address innovative approaches to sustainability in digital education. The PRISMA 2020 guidelines were used to review the literature of articles published in the last decade in the Web of Science (WoS) and Scopus databases. The results presented are based on the research questions that will guide the search and analysis of the information. They are divided into theoretical and practical research, giving relevance to the relationship between educational innovation with ICT and sustainability. The main variables that are taken into account in contributing to the SDGs through the use of ICT in educational practice are also presented. A critical discussion on this topic is elaborated, which will help to support a solid theoretical framework. Last, a conclusion on the effectiveness of digital education and its contribution to a sustainable development are provided.
Can Teleworking Lead to Economic Growth during Pandemic Times? Empirical Evidence at the European Union Level
Authors: Robu Ioan-Bogdan , Dicu Roxana-Manuela , Herghiligiu Ionuț Viorel , Sahlian Daniela Nicoleta , Vuță Mihai
Published: December 2022

Teleworking is known as a way of the future that enhances economic growth as an accumulation of physical as well as human capital. Using digitalization that increase the procedures and services efficiency and reduce the repetitive work of employers by using technology, teleworking improves firm performance by enhancing efficiency, motivation, and knowledge creation. This paper aims to analyze the influence of teleworking, based on its characteristics and determinants under the influence of financial and pandemic crises, on economic growth as measured by GDP growth; this was performed using econometric models from the literature and fuzzy logic. The econometric analysis included a two-step approach regarding the years 2008–2020 (including COVID-19 pandemic period) for the 27 member states of the EU. The research results suggest that access to the Internet, employment ratio, and average wage significantly influenced the teleworking ratio of the employees. Furthermore, the access to the Internet made a significant difference in using teleworking, given the infrastructure that was already created in the first COVID-19 pandemic wave. Employees took advantage of it and continued, at a lower scale, to maintain social distancing, although the measures taken in the second wave were not perceived to be as tough as in the first one.
From Beginning to BEGANing: Role of Adversarial Learning in Reshaping Generative Models
Authors: Bhandari Aradhita , Tripathy Balakrushna , Adate Amit , Saxena Rishabh , Gadekallu Thippa Reddy
Published: December 2022

Deep generative models, such as deep Boltzmann machines, focused on models that provided parametric specification of probability distribution functions. Such models are trained by maximizing intractable likelihood functions, and therefore require numerous approximations to the likelihood gradient. This underlying difficulty led to the development of generative machines such as generative stochastic networks, which do not represent the likelihood functions explicitly, like the earlier models, but are trained with exact backpropagation rather than the numerous approximations. These models use piecewise linear units that are having well behaved gradients. Generative machines were further extended with the introduction of an associative adversarial network leading to the generative adversarial nets (GANs) model by Goodfellow in 2014. The estimations in GANs process two multilayer perceptrons, called the generative model and the discriminative model. These are learned jointly by alternating the training of the two models, using game theory principles. However, GAN has many difficulties, including: the difficulty of training the models; criticality in the selection of hyper-parameters; difficulty in the control of generated samples; balancing the convergence of the discriminator and generator; and the problem of modal collapse. Since its inception, efforts have been made to tackle these issues one at a time or in multiples at several stages by many researchers. However, most of these have been handled efficiently in the boundary equilibrium generative adversarial networks (BEGAN) model introduced by Berthelot et al. in 2017. In this work we presented the advent of adversarial networks, starting with the history behind the models and c developments done on GANs until the BEGAN model was introduced. Since some time has elapsed since the proposal of BEGAN, we provided an up-to-date study, as well as future directions for various aspects of adversarial learning.