bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiplex Droplet Digital PCR Assay for Detection of MET and HER2 Genes Amplification in Non-Small Cell Lung Cancer
Authors: Oscorbin Igor P. , Smertina Maria A. , Pronyaeva Ksenia A. , Voskoboev Mikhail E. , Boyarskikh Ulyana A. , Kechin Andrey A. , Demidova Irina A. , Filipenko Maxim L.
Published: March 2022

Non-small-cell lung cancer (NSCLC), a subtype of lung cancer, remains one of the most common tumors with a high mortality and morbidity rate. Numerous targeted drugs were implemented or are now developed for the treatment of NSCLC. Two genes, HER2 and MET, are among targets for these specific therapeutic agents. Alterations in HER2 and MET could lead to primary or acquired resistance to commonly used anti-EGFR drugs. Using current methods for detecting HER2 and MET amplifications is time and labor-consuming; alternative methods are required for HER2 and MET testing. We developed the first multiplex droplet digital PCR assay for the simultaneous detection of MET and HER2 amplification in NSCLC samples. The suitability of qPCR was assessed for the optimization of multiplex ddPCR. The optimal elongation temperature, reference genes for DNA quantification, and amplicon length were selected. The developed ddPCR was validated on control samples with various DNA concentrations and ratios of MET and HER2 genes. Using ddPCR, 436 EGFR-negative NSCLC samples were analyzed. Among the tested samples, five specimens (1.15%) showed a higher ratio of MET, and six samples (1.38%) showed a higher ratio of HER2. The reported multiplex ddPCR assay could be used for the routine screening of MET and HER2 amplification in NSCLC samples.
Anabolic Factors and Myokines Improve Differentiation of Human Embryonic Stem Cell Derived Skeletal Muscle Cells
Authors: Ruan Travis , Harney Dylan , Koay Yen Chin , Loo Lipin , Larance Mark , Caron Leslie
Published: March 2022

Skeletal muscle weakness is linked to many adverse health outcomes. Current research to identify new drugs has often been inconclusive due to lack of adequate cellular models. We previously developed a scalable monolayer system to differentiate human embryonic stem cells (hESCs) into mature skeletal muscle cells (SkMCs) within 26 days without cell sorting or genetic manipulation. Here, building on our previous work, we show that differentiation and fusion of myotubes can be further enhanced using the anabolic factors testosterone (T) and follistatin (F) in combination with a cocktail of myokines (C). Importantly, combined TFC treatment significantly enhanced both the hESC-SkMC fusion index and the expression levels of various skeletal muscle markers, including the motor protein myosin heavy chain (MyHC). Transcriptomic and proteomic analysis revealed oxidative phosphorylation as the most up-regulated pathway, and a significantly higher level of ATP and increased mitochondrial mass were also observed in TFC-treated hESC-SkMCs, suggesting enhanced energy metabolism is coupled with improved muscle differentiation. This cellular model will be a powerful tool for studying in vitro myogenesis and for drug discovery pertaining to further enhancing muscle development or treating muscle diseases.
Tissue-Specific Expression of TIGIT, PD-1, TIM-3, and CD39 by γδ T Cells in Ovarian Cancer
Authors: Weimer Pauline , Wellbrock Jasmin , Sturmheit Tabea , Oliveira-Ferrer Leticia , Ding Yi , Menzel Stephan , Witt Marius , Hell Louisa , Schmalfeldt Barbara , Bokemeyer Carsten , Fiedler Walter , Brauneck Franziska
Published: March 2022

Phenotypic characterization of γδ T cells in the MALs (malignant ascites lymphocytes), TILs (tumor infiltrating lymphocytes), and PBLs (peripheral blood lymphocytes) of ovarian cancer (OvCA) patients is lacking. Therefore, we quantified γδ T cell prevalence in MAL, TIL, and PBL specimens from n = 18 OvCA patients and PBL from age-matched healthy donors (HD, n = 14). Multicolor flow cytometry was performed to evaluate the expression of inhibitory receptors (TIGIT, PD-1 and TIM-3), stimulatory receptors (Ox40), and purinergic ectoenzymes (CD39 and CD73) on γδ T cell subsets. We identified an abundant infiltration of Vδ1 T cells in the MALs and TILs. These cells varied in their differentiation: The majority of Vδ1 TILs displayed an effector memory (EM) phenotype, whereas Vδ1 MALs had a more mature phenotype of terminally differentiated effector memory cells (TEMRA) with high CD45RA expression. TIGIT and TIM-3 were abundantly expressed in both MALs and PBLs, whereas Vδ1 TILs exhibited the highest levels of PD-1, CD39, and Ox40. We also observed specific clusters on mature differentiation stages for the analyzed molecules. Regarding co-expression, Vδ1 TILs showed the highest levels of cells co-expressing TIGIT with PD-1 or CD39 compared to MALs and PBLs. In conclusion, the Vδ1 T cell population showed a high prevalence in the MALs and primary tumors of OvCA patients. Due to their (co-)expression of targetable immune receptors, in particular TIGIT with PD-1 and CD39 in TILs, Vδ1 T cell-based approaches combined with the inhibition of these targets might represent a promising strategy for OvCA.
3D In Vitro Platform for Cell and Explant Culture in Liquid-like Solids
Authors: Nguyen Duy T. , Famiglietti Jack E. , Smolchek Ryan A. , Dupee Zadia , Diodati Nickolas , Pedro Diego I. , Urueña Juan M. , Schaller Matthew A. , Sawyer W. Gregory
Published: March 2022

Existing 3D cell models and technologies have offered tools to elevate cell culture to a more physiologically relevant dimension. One mechanism to maintain cells cultured in 3D is by means of perfusion. However, existing perfusion technologies for cell culture require complex electronic components, intricate tubing networks, or specific laboratory protocols for each application. We have developed a cell culture platform that simply employs a pump-free suction device to enable controlled perfusion of cell culture media through a bed of granular microgels and removal of cell-secreted metabolic waste. We demonstrated the versatile application of the platform by culturing single cells and keeping tissue microexplants viable for an extended period. The human cardiomyocyte AC16 cell line cultured in our platform revealed rapid cellular spheroid formation after 48 h and ~90% viability by day 7. Notably, we were able to culture gut microexplants for more than 2 weeks as demonstrated by immunofluorescent viability assay and prolonged contractility.
Modulation of the Bile Acid Enterohepatic Cycle by Intestinal Microbiota Alleviates Alcohol Liver Disease
Authors: Ciocan Dragos , Spatz Madeleine , Trainel Nicolas , Hardonnière Kévin , Domenichini Séverine , Mercier-Nomé Françoise , Desmons Aurore , Humbert Lydie , Durand Sylvère , Kroemer Guido , Lamazière Antonin , Hugot Cindy , Perlemuter Gabriel , Cassard Anne-Marie
Published: March 2022

Reshaping the intestinal microbiota by the ingestion of fiber, such as pectin, improves alcohol-induced liver lesions in mice by modulating bacterial metabolites, including indoles, as well as bile acids (BAs). In this context, we aimed to elucidate how oral supplementation of pectin affects BA metabolism in alcohol-challenged mice receiving feces from patients with alcoholic hepatitis. Pectin reduced alcohol liver disease. This beneficial effect correlated with lower BA levels in the plasma and liver but higher levels in the caecum, suggesting that pectin stimulated BA excretion. Pectin modified the overall BA composition, favoring an augmentation in the proportion of hydrophilic forms in the liver, plasma, and gut. This effect was linked to an imbalance between hydrophobic and hydrophilic (less toxic) BAs in the gut. Pectin induced the enrichment of intestinal bacteria harboring genes that encode BA-metabolizing enzymes. The modulation of BA content by pectin inhibited farnesoid X receptor signaling in the ileum and the subsequent upregulation of Cyp7a1 in the liver. Despite an increase in BA synthesis, pectin reduced BA serum levels by promoting their intestinal excretion. In conclusion, pectin alleviates alcohol liver disease by modifying the BA cycle through effects on the intestinal microbiota and enhanced BA excretion.
The Statin Target Hmgcr Regulates Energy Metabolism and Food Intake through Central Mechanisms
Authors: Williams Michael J. , Alsehli Ahmed M. , Gartner Sarah N. , Clemensson Laura E. , Liao Sifang , Eriksson Anders , Isgrove Kiriana , Thelander Lina , Khan Zaid , Itskov Pavel M. , Moulin Thiago C. , Ambrosi Valerie , Al-Sabri Mohamed H. , Lagunas-Rangel Francisco Alejandro , Olszewski Pawel K. , Schiöth Helgi B.
Published: March 2022

The statin drug target, 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), is strongly linked to body mass index (BMI), yet how HMGCR influences BMI is not understood. In mammals, studies of peripheral HMGCR have not clearly identified a role in BMI maintenance and, despite considerable central nervous system expression, a function for central HMGCR has not been determined. Similar to mammals, Hmgcr is highly expressed in the Drosophila melanogaster brain. Therefore, genetic and pharmacological studies were performed to identify how central Hmgcr regulates Drosophila energy metabolism and feeding behavior. We found that inhibiting Hmgcr, in insulin-producing cells of the Drosophila pars intercerebralis (PI), the fly hypothalamic equivalent, significantly reduces the expression of insulin-like peptides, severely decreasing insulin signaling. In fact, reducing Hmgcr expression throughout development causes decreased body size, increased lipid storage, hyperglycemia, and hyperphagia. Furthermore, the Hmgcr induced hyperphagia phenotype requires a conserved insulin-regulated α-glucosidase, target of brain insulin (tobi). In rats and mice, acute inhibition of hypothalamic Hmgcr activity stimulates food intake. This study presents evidence of how central Hmgcr regulation of metabolism and food intake could influence BMI.
Microbiota and Pain: Save Your Gut Feeling
Authors: Morreale Chiara , Bresesti Ilia , Bosi Annalisa , Baj Andreina , Giaroni Cristina , Agosti Massimo , Salvatore Silvia
Published: March 2022

Recently, a growing body of evidence has emerged regarding the interplay between microbiota and the nervous system. This relationship has been associated with several pathological conditions and also with the onset and regulation of pain. Dysregulation of the axis leads to a huge variety of diseases such as visceral hypersensitivity, stress-induced hyperalgesia, allodynia, inflammatory pain and functional disorders. In pain management, probiotics have shown promising results. This narrative review describes the peripheral and central mechanisms underlying pain processing and regulation, highlighting the role of the gut-brain axis in the modulation of pain. We summarized the main findings in regard to the stress impact on microbiota’s composition and its influence on pain perception. We also focused on the relationship between gut microbiota and both visceral and inflammatory pain and we provided a summary of the main evidence regarding the mechanistic effects and probiotics use.
COVID-19-Related Job Demands and Resources, Organizational Support, and Employee Well-Being: A Study of Two Nordic Countries
Authors: Lilja Johanna , Fladmark Silje , Nuutinen Sanna , Bordi Laura , Larjovuori Riitta-Liisa , Innstrand Siw Tone , Christensen Marit , Heikkilä-Tammi Kirsi
Published: March 2022

The purpose of this study is to examine how COVID-19-related job demands and resources have been associated with employee well-being in Nordic countries across specific occupational groups. The study investigated four occupational groups: (1) professional, scientific, and technical occupations in Norway (n = 301); (2) teachers in Finland (n = 315); (3) health and social service occupations in Norway (n = 267); and (4) geriatric nurses in Finland (n = 105). Hypotheses were tested using two-step hierarchical regression analysis. Work–home imbalance in Groups 1, 2, and 3, workload increase in Groups 1 and 3, and fear of infection in Groups 2 and 3 were positively related with exhaustion. A positive attitude towards digital solutions was positively related to work engagement in Groups 2 and 3. In addition, there was a significant positive relationship between COVID-19-related organizational support and work engagement in Groups 2, 3, and 4, and a negative relationship with exhaustion in Group 2. In conclusion, pandemic-related job demands and resources were differently associated with employee well-being across different occupational groups and countries. Further, organizational support may act as a supportive element for sustaining employee well-being during pandemics.
The SnO2/MXene Composite Ethanol Sensor Based on MEMS Platform
Authors: Wang Chen , Li Runlong , Feng Lingyan , Xu Jiaqiang
Published: March 2022

In recent years, two-dimensional layered material MXene has attracted extensive attention in the fields of sensors due to its large specific surface area and rich active sites. So, we employed multilayer Ti3C2TX and SnO2 microspheres to prepare SnO2/MXene composites for enhancing gas-sensing properties of pristine SnO2. The composite was brushed on a microelectromechanical system (MEMS) platform to make resistance-type gas sensors with low power consumption. The gas-sensing results show that the SnO2/MXene sensor with the best composite ratio (SnO2: MXene mass ratio is 5:1, named SM-5) greatly improves gas sensitivity of SnO2 sensor, among which the sensitivity to ethanol gas is the highest. At the same time, the composite also speeds up the response recovery speed of the sensor. When the SM-5 sensor worked at its optimal temperature 230 °C, its response value to 10 ppm ethanol reaches 5.0, which is twice that of the pristine SnO2 sensor. Its response and recovery time are only 14 s and 26 s, respectively. The sensing mechanism of the composite is discussed according to the classical the space charge or depletion layer model. It is concluded that the Schottky barrier of composites and the metal properties of Ti3C2Tx are responsible for improvement of the gas-sensing properties of the composite.
A Critical Review on the Complex Interplay between Social Determinants of Health and Maternal and Infant Mortality
Authors: Dagher Rada K. , Linares Deborah E.
Published: March 2022

Background: U.S. maternal and infant mortality rates constitute an important public health problem, because these rates surpass those in developed countries and are characterized by stark disparities for racial/ethnic minorities, rural residents, and individuals with less privileged socioeconomic status due to social determinants of health (SDoH). Methods: A critical review of the maternal and infant mortality literature was performed to determine multilevel SDoH factors leading to mortality disparities with a life course lens. Results: Black mothers and infants fared the worst in terms of mortality rates, likely due to the accumulation of SDoH experienced as a result of structural racism across the life course. Upstream SDoH are important contributors to disparities in maternal and infant mortality. More research is needed on the effectiveness of continuous quality improvement initiatives for the maternal–infant dyad, and expanding programs such as paid maternity leave, quality, stable and affordable housing, and social safety-nets (Medicaid, CHIP, WIC), in reducing maternal and infant mortality. Finally, it is important to address research gaps in individual, interpersonal, community, and societal factors, because they affect maternal and infant mortality and related disparities. Conclusion: Key SDoH at multiple levels affect maternal and infant health. These SDoH shape and perpetuate disparities across the lifespan and are implicated in maternal and infant mortality disparities.
Factors to Consider to Study Preductal Oxygen Saturation Targets in Neonatal Pulmonary Hypertension
Authors: Siefkes Heather , Sunderji Sherzana , Vaughn Jessica , Sankaran Deepika , Vali Payam , Vadlaputi Pranjali , Timberline Sage , Bhatt Avni , Tancredi Daniel , Lakshminrusimha Satyan
Published: March 2022

There are potential benefits and risks to the infant with higher and lower oxygen saturation (SpO2) targets, and the ideal range for infants with pulmonary hypertension (PH) remains unknown. Targeting high SpO2 can promote pulmonary vasodilation but cause oxygen toxicity. Targeting lower SpO2 may increase pulmonary vascular resistance, especially in the presence of acidosis and hypothermia. We will conduct a randomized pilot trial to compare two ranges of target preductal SpO2 in late-preterm and term infants with hypoxic respiratory failure (HRF) and acute pulmonary hypertension (aPH) of the newborn. We will assess the reliability of a newly created HRF/PH score that could be used in larger trials. We will assess trial feasibility and obtain preliminary estimates of outcomes. Our primary hypothesis is that in neonates with PH and HRF, targeting preductal SpO2 of 95–99% (intervention) will result in lower pulmonary vascular resistance and pulmonary arterial pressures, and lower the need for pulmonary vasodilators (inhaled nitric oxide—iNO, milrinone and sildenafil) compared to targeting SpO2 at 91–95% (standard). We also speculate that a higher SpO2 target can potentially induce oxidative stress and decrease response to iNO (oxygenation and pulmonary vasodilation) for those patients that still require iNO in this range. We present considerations in planning this trial as well as some of the details of the protocol design (Clinicaltrials.gov (NCT04938167)).
Prediction of Communicative Disorders Linked to Autistic Spectrum Disorder Based on Early Psychomotor Analysis
Authors: Rincón-Rufo Darío , Vera-Pérez Violeta , Cuesta-Gómez Alicia , Carratalá-Tejada María
Published: March 2022

This systematic review evaluated psychomotor differences between children with and without siblings who have autism spectrum disorder (ASD), as well as the most reliable psychomotor skills that can help predict ASD and its associated language disorders. Literature from 2005 to 2020 was searched using the following databases: PubMed, Trip Medical Database, Cochrane, Web of Science, Science Direct, and Brain. A total 11 papers were included. Fine motor skills and joint attention displayed reliable results in order to predict ASD and its associated language disorders. The period between the first and the second year of life was considered the most appropriate one for the assessment of psychomotor skills. The best period to predict language disorders and ASD diagnosis is around 36 months old.
Intensive Family Intervention as Support for Professional Treatment: Evolution of Symptoms in a Diagnosed Case of Autism Spectrum Disorder
Authors: Salgado-Cacho José María , Moreno-Jiménez María del Pilar , Ríos-Rodríguez María Luisa
Published: March 2022

This article shows the progress achieved in a child who has received professional treatment combined with a family intervention at home. It discusses a 22-month-old patient identified as showing warning signs of autism spectrum disorder (ASD), a diagnosis that was subsequently confirmed through a standardized ADOS-2 test at 31 months of age. To establish the initial working objectives, a functional diagnosis was carried out at 23 months of age using the Battelle Developmental Inventory; a maturational delay was detected, situating the child at an age equivalent to 16 months. A professional intervention was designed in an early childhood care center, complemented by family intervention, so that the hours in which the child participated in learning experiences were increased. Notable advances were made in the areas of cognitive and motor skills, with more standard scores than when initially evaluated. Progress was also observed (though to a lesser extent) in other developmental areas such as language total, adaptive behavior, and self-help, while slight delays in the areas of socio-emotional development and reasoning and academic skills were found.
A Protective Factor for Emotional and Behavioral Problems in Children: The Parental Humor
Authors: León-del-Barco Benito , Mendo-Lázaro Santiago , Polo-del-Río María-Isabel , Fajardo-Bullón Fernando , López-Ramos Víctor-María
Published: March 2022

In order to prevent the development of emotional and behavioral problems, risk and protective factors must be identified. This study aims to establish a link between perceived parental humor and children mental health. The sample comprises 762 pupils aged 10 to 15 (M = 12.23; SD = 1.12), who completed self-reports evaluating perceived parental humor (EEE-H) and their own emotional and behavioral strengths and difficulties (SDQ). The results indicate that parental humor is negatively associated with internalizing problems in children; no association with externalizing problems is observed. According to the study, girls who perceive low parental humor are the most likely to display internalizing problems, while girls perceiving high parental humor are the least likely to do so. Parental humor, characterized by calmness, cheerfulness, and optimism, is a protective factor against internalizing problems in children, especially girls. We recommend training for parents and training and intervention programs for families to encourage activities that boost parental humor.
Influence of Heat Treatment on the Microstructure and Wear Properties of Arc-Sprayed FeCrAl/Al Coating
Authors: Ndumia Joseph , Kang Min , Lin Jinran , Liu Jitao , Li Hao
Published: March 2022

Intermetallic compounds formed during heat treatment of alloy coatings affect the coating structure and properties. In order to determine the phase changes and coating performance, FeCrAl (Fe Bal., Cr 26 wt.%, Al 6 wt.%) and Al (99.9 wt.%) coating was sprayed onto low carbon steel substrates and subsequently heat-treated at different temperatures. The effects of heat treatment on the microstructure, phase composition, tensile bonding strength, microhardness, and wear properties of the coatings were analyzed. The as-sprayed coating had a dense, layered structure with an average porosity of 3.6%. The microhardness of the as-sprayed coating was comprised of hard FeCrAl splats and ductile Al splats with an average microhardness value of 494 HV0.1. The coating at 300 °C had the highest tensile strength of 37.5 MPa. At 500 °C, FeAl intermetallic compounds formed at the phase boundaries due to the diffusion of elements. The coating microhardness and wear resistance were affected by the uniform coating structure and the precipitation of FeAl intermetallic compounds. Compared with the annealed coatings, the as-sprayed coating had the lowest wear rate.
Examining the Potential of Enzyme-Based Detergents to Remove Biofouling from Limestone Heritage
Authors: Schröer Laurenz , Fiers Géraldine , Deprez Maxim , Boon Nico , Cnudde Veerle , Soens Lander , De Kock Tim
Published: March 2022

Commonwealth war cemeteries commemorate the fallen of both world wars. Every casualty is remembered with a memorial or on a headstone. However, the headstones need to be maintained extensively, as microorganisms easily colonise them, affecting legibility and the stone substrate in the longer term. In the past, pesticides and other chemicals were popular to clean headstones, but due to raised environmental concerns, new treatment strategies are necessary. Within conservation science, enzymes have emerged as a popular tool for restoration. However, studies related to the use of enzymes for stone conservation are limited. Within this preliminary study, we applied commercially available enzyme-based treatments on biofouled natural building stones in the laboratory and in situ. Photography and spectrophotometry were used to monitor the effect of the treatment. The application of enzymes resulted in rapid disintegration of biological pigments, whereas visual improvement occurred more gradually. The successful application of enzymes suggests their potential to replace pesticides as the principal cleaning agent for headstones and natural building stones in a more general fashion.
Deep Q-Learning Based Reinforcement Learning Approach for Network Intrusion Detection
Authors: Alavizadeh Hooman , Alavizadeh Hootan , Jang-Jaccard Julian
Published: March 2022

The rise of the new generation of cyber threats demands more sophisticated and intelligent cyber defense solutions equipped with autonomous agents capable of learning to make decisions without the knowledge of human experts. Several reinforcement learning methods (e.g., Markov) for automated network intrusion tasks have been proposed in recent years. In this paper, we introduce a new generation of the network intrusion detection method, which combines a Q-learning based reinforcement learning with a deep feed forward neural network method for network intrusion detection. Our proposed Deep Q-Learning (DQL) model provides an ongoing auto-learning capability for a network environment that can detect different types of network intrusions using an automated trial-error approach and continuously enhance its detection capabilities. We provide the details of fine-tuning different hyperparameters involved in the DQL model for more effective self-learning. According to our extensive experimental results based on the NSL-KDD dataset, we confirm that the lower discount factor, which is set as 0.001 under 250 episodes of training, yields the best performance results. Our experimental results also show that our proposed DQL is highly effective in detecting different intrusion classes and outperforms other similar machine learning approaches.
Inverse Colloidal Crystal Polymer Coating with Monolayer Ordered Pore Structure
Authors: Wang Likun , Chu Zhaoran , Ning Xuanjun , Huang Ziwei , Tang Wenwei , Jiang Weizhong , Ye Jiayi , Chen Cheng
Published: March 2022

A functional lens coating, based on the structure of inversed colloidal photonic crystals, is proposed. The color-reflecting colloidal crystal was first prepared by self-assembly of nano-colloids and was infiltrated by adhesive polymer solution. As the polymer was crosslinked and the crystal array was removed, a robust mesh-like coating was achieved. Such a functional coating has good transmittance and has a shielding efficiency of ~9% for UV–blue light according to different particle sizes of the nano-colloids, making it an ideal functional material.
Isolation, Identification, Spectral Studies and X-ray Crystal Structures of Two Compounds from Bixa orellana, DFT Calculations and DNA Binding Studies
Authors: Parveen Mehtab , Azeem Mohammad , Aslam Afroz , Azam Mohammad , Siddiqui Sharmin , Tabish Mohammad , Malla Ali Mohammad , Min Kim , Rodrigues Vitor Hugo , Al-Resayes Saud I. , Alam Mahboob
Published: March 2022

4,6-Diacetylresorcinol (1) and 3-O-methylellagic acid dihydrate (2), both biologically significant compounds, were extracted from Bixa orellana and studied using IR, 1H, and 13C NMR, and UV-vis spectroscopic techniques. X-ray crystallographic techniques were also used to establish the molecular structure of the isolated compounds 1 and 2. Geometric parameters, vibrational frequencies, and gauge including atomic orbital (GIAO) 1H and 13C NMR of 1 and 2 in the ground state were computed by the density functional theory (DFT) using B3LYP/6-311G(d,p) basis set backing up experimental studies and established the correct structure of isolated compounds. The parameters obtained from the combined DFT, and X-ray diffraction studies are mutually agreed to establish correct structures of 1 and 2. In addition, an electrostatic potential map and HOMO−LUMO energy gap were made using the DFT calculation to determine the distribution of energy and the chemical reactivity region of the isolated compounds. The current study also provides further insights into the interaction of compound 2 with ct-DNA using numerous biophysical and in silico techniques. Moreover, in silico studies indicate that compound 2 binds to the DNA in the minor groove. Lipinski’s rule of five revealed a higher tendency of compound 2 towards drug-likeness. The bioavailability and synthetic accessibility score for compound 2 was found to be 0.55 and 3.21, suggesting that compound 2 could serve as an effective therapeutic candidate.
Yeast and Lactic Acid Bacteria Dominate the Core Microbiome of Fermented ‘Hairy’ Tofu (Mao Tofu)
Authors: Benucci Gian Maria Niccolò , Wang Xinxin , Zhang Li , Bonito Gregory , Yu Fuqiang
Published: March 2022

The process of fermenting tofu extends back thousands of years and is an indispensable part of Chinese culture. Despite a cultural resurgence in fermented foods and interest in microbiomes, there is little knowledge on the microbial diversity represented in fermented ‘hairy’ tofu, known locally in China as Mao tofu. High-throughput metagenomic sequencing of the ITS, LSU and 16S rDNA was used to determine Mao tofu’s fungal and bacterial community diversity across four wet markets in Yunnan, China. The results show that hairy tofu in this region consists of around 170 fungal and 365 bacterial taxa, and that microbial taxa differ between markets. Diversity also differed based on the specific niche of the tofu block, comparing the outside rind-like niche to that of the inside of the tofu block. Machine learning random forest models were able to accurately classify both the market and niche of sample origin. An over-abundance of yeast and Geotrichum was found, and Mucor (Mucoromycota) was abundant in the outside rind-like niche, which consists of the visible ‘hairy’ mycelium. The majority of the bacterial OTUs belonged to Proteobacteria, Firmicutes, and Bacteroidetes, with Acinetobacter, Lactobacillus, Sphingobacterium and Flavobacterium the most abundant genera. Putative fungal pathogens of plants (Cercospora, Diaporthe, Fusarium) and animals (Metarhizium, Entomomortierella, Pyxidiophora, Candida, Clavispora) were also detected, as were putative bacterial pathogens identified as Legionella. Non-fungal eukaryotic taxa detected by LSU amplicon sequencing included soybean (Glycine max), Protozoa, Metazoa (e.g., Nematoda and Platyhelminthes), Rhizaria and Chromista, indicating that additional biodiversity exists in the hairy tofu microbiome.
Plant Species Turnover on Forest Gaps after Natural Disturbances in the Dinaric Fir Beech Forests (Omphalodo-Fagetum sylvaticae)
Authors: Ravnjak Blanka , Bavcon Jože , Čarni Andraž
Published: March 2022

We studied species turnover and changes of ecological conditions and plant strategies on forest gaps created by natural disturbances (sleet, windthrow). We studied five forest gaps and a control plot within in the Dinaric silver fir-beech forest in the southern part of Slovenia. Forest gaps varied in age and size. The total number of recorded species in gaps was 184, with the highest number (106) at the largest forest gap and with the 58 species at the control locality in a juvenile beech forest. Forest gaps were predominantly colonised mostly by species of understory, forest margins, and forest clearings. The species presented in all forest gaps are representatives of the understory of beech forests. Species colonising forest gaps prefer habitats with more sunlight, medium wet to dry soil, and are tolerant to high daily and seasonal temperature fluctuations. In gaps, the community of plant species has a competitive strategy, which is also complemented with a stress-tolerator strategy. We determined that a forest gap represents a significant habitat patch, especially for those plant species which were not present there before.
Microsatellite Genotyping of Two Bulgarian Sheep Breeds
Authors: Odjakova Tsonka , Todorov Pavel , Radoslavov Georgi , Hristov Peter
Published: March 2022

The aim of this study was to compare the genetic structure and genetic diversity of two Bulgarian sheep breeds. A total of 41 individuals from a modern Bulgarian sheep population (Rhodopean Tsigai, RT) and 46 representatives of a local Bulgarian sheep population (Middle Rhodopean Sheep, MRS) were investigated based on 12 STR (short tandem repeat, also known as microsatellite) markers. In total, 121 alleles were found in the two populations using 12 microsatellite loci. The mean number of alleles, the effective number of alleles, and the polymorphism information content (PIC) values per loci were 10.08, 4.96, and 0.73, respectively. When comparing the allelic diversity across the populations, the highest Na was observed in the MRS breed (10.58 ± 0.87), while the value of this parameter in the RT breed was 9.58 ± 0.71. The largest genetic diversity was found at locus INRA005 with 14.5 alleles and the smallest polymorphism was noted for locus ETH152 with 5.5 alleles. The level of observed heterozygosity was in the range of 0.60 to 0.860. The expected heterozygosity level range was 0.62 to 0.87. When 12 microsatellite loci were compared, the INRA005 locus showed the highest level of genetic variability. Using Nei’s standard genetic distance, the observed genetic distance between the RT and MRS breeds was 0.103. Both sheep breeds demonstrated mixed genetic profiles based on the studied microsatellite markers. The clustering obtained by STRUCTURE analysis showed that the MRS breed is a more homogenous population, whereas the RT breed is more heterogenous.
Diversity and Biosynthetic Activities of Agarwood Associated Fungi
Authors: Du Tian-Ye , Dao Cheng-Jiao , Mapook Ausana , Stephenson Steven L. , Elgorban Abdallah M. , Al-Rejaie Salim , Suwannarach Nakarin , Karunarathna Samantha C. , Tibpromma Saowaluck
Published: March 2022

Agarwood is a fragrant dark resin produced in plants belonging to the family Thyme-laeaceae and which has a high economic value. The unique fragrance and medicinal applications intensify the value of agarwood. The wild populations of agarwood trees are highly threatened by high economic demand. Therefore, it is worthwhile to develop an artificial agarwood induction technology for the countries that rely on agarwood from the natural habitat of the plants. Fungal induction of agarwood has been shown to be an efficient method. Interestingly, most of the fungi known from agarwood are endophytic. In this paper, we supplement and update the bioactivity of fungi associated with agarwood and their ability to induce agarwood formation. According to the existing literature, 59 endophytic fungal strains of 16 genera induce agarwood production, most of which belong to Fusarium (28 identified strains). Hence, Fusarium is a good candidate for further studies on fungal induced agarwood production.
Multiple Genetic Alterations as Resistance Mechanism during Second-Line Lorlatinib for Advanced ALK-Rearranged Lung Adenocarcinoma: A Case Report
Authors: Catino Annamaria , Lacalamita Rosanna , De Summa Simona , Pesola Francesco , Tommasi Stefania , Galetta Domenico
Published: March 2022

Second and third-generation ALK-TKI inhibitors have showed better activity and have replaced crizotinib in most of cases of advanced ALK-rearranged lung adenocarcinoma. The emergence of resistance adversely affects also the activity of these newer drugs; in particular, lorlatinib often shows multiple and complex resistance mechanisms. The case reported here highlights the importance of reassessing the biomolecular profile during the disease course, both by tissutal and liquid biopsy, with the aim of improving the knowledge of these resistance mechanisms, and so identifying new drugs or sequences able to optimize the management of these patients.
Current Advancement in Diagnosing Atrial Fibrillation by Utilizing Wearable Devices and Artificial Intelligence: A Review Study
Authors: Wang Yu-Chiang , Xu Xiaobo , Hajra Adrija , Apple Samuel , Kharawala Amrin , Duarte Gustavo , Liaqat Wasla , Fu Yiwen , Li Weijia , Chen Yiyun , Faillace Robert T.
Published: March 2022

Atrial fibrillation (AF) is a common arrhythmia affecting 8–10% of the population older than 80 years old. The importance of early diagnosis of atrial fibrillation has been broadly recognized since arrhythmias significantly increase the risk of stroke, heart failure and tachycardia-induced cardiomyopathy with reduced cardiac function. However, the prevalence of atrial fibrillation is often underestimated due to the high frequency of clinically silent atrial fibrillation as well as paroxysmal atrial fibrillation, both of which are hard to catch by routine physical examination or 12-lead electrocardiogram (ECG). The development of wearable devices has provided a reliable way for healthcare providers to uncover undiagnosed atrial fibrillation in the population, especially those most at risk. Furthermore, with the advancement of artificial intelligence and machine learning, the technology is now able to utilize the database in assisting detection of arrhythmias from the data collected by the devices. In this review study, we compare the different wearable devices available on the market and review the current advancement in artificial intelligence in diagnosing atrial fibrillation. We believe that with the aid of the progressive development of technologies, the diagnosis of atrial fibrillation shall be made more effectively and accurately in the near future.
A Regulatory Readiness Assessment Framework for Blockchain Adoption in Healthcare
Authors: Sanda Olanrewaju , Pavlidis Michalis , Polatidis Nikolaos
Published: March 2022

Blockchain is now utilized by a diverse spectrum of applications and is proclaimed as a technological innovation that transforms the way that data are stored. This technology has the potential to transform the healthcare sector, especially the prevalent issues of patient’s data-privacy and fragmented healthcare data. However, there is no evidence-based effort to develop a readiness assessment framework for blockchain that combines all the different social and economic factors and involves all stakeholders. Based on a systematic literature review, the proposed framework is applied to Portugal’s healthcare sector and its applicability is outlined. The findings in this paper show the unique importance of regulators and the government in achieving a globally acceptable regulatory framework for the adoption of blockchain technology in healthcare and other sectors. The business entities and solution providers are ready to leverage the opportunities of blockchain, but the absence of a widely acceptable regulatory framework that protect stakeholders’ interests is slowing down the adoption of blockchain. There are several misconceptions regarding blockchain laws and regulations, which has slowed stakeholder readiness. This paper will be useful as a guideline and knowledge base to reinforce blockchain adoption.
Association of Dental Fear with Caries Status and Self-Reported Dentition-Related Well-Being in Finnish Conscripts
Authors: Kämppi Antti , Tanner Tarja , Viitanen Olavi , Pohjola Vesa , Päkkilä Jari , Tjäderhane Leo , Anttonen Vuokko , Patinen Pertti
Published: March 2022

The main aim of this cross-sectional study was to examine the prevalence of dental fear among Finnish conscripts. Other aims were to study the association between dental fear and cariological status as well as their self-reported, dentition-related well-being. The study material consisted of 13,564 men and 255 women conscripts who underwent oral examinations. Of those, 8713 responded to a computer-based questionnaire. The mean number of decayed teeth (DT) was used in analyses for cariological status. Self-reported dental fear, dentition-related well-being and regular check-ups were analysed. Data were analysed with cross tables, Pearson Chi-Square tests, Fisher’s exact test and binary logistic regressive analysis. High dental fear or finding dental visits very scary was associated with DT > 2 both among women (14.6%, when DT = 0; 33.3%, when DT > 2) and men conscripts (2.3% and 10.8%, respectively). In addition, those reporting that dental health had a negative impact on their well-being and had no regular check-ups were more likely to need cariological treatment than the rest. A high education level, both one’s own and parental, was a protective factor for restorative treatment need in male conscripts. The findings of this study support the concept of a vicious cycle of dental fear and dental caries. A preventive, interactive way of work by dental teams would most likely be beneficial for dental health, avoiding the development of dental fear, and dentition-related well-being.
Empowering College Students’ Problem-Solving Skills through RICOSRE
Authors: Mahanal Susriyati , Zubaidah Siti , Setiawan Deny , Maghfiroh Hidayati , Muhaimin Fahrul Ghani
Published: March 2022

Problem-solving skills are advantageous when resolving complicated and multidimensional challenges. Problem-solving skills can be developed through active learning models that engage students in the learning process. One active learning model is RICOSRE. The main focus of RICOSRE is problem-solving activities in (1) reading; (2) identifying the problem; (3) constructing the solution; (4) solving the problem; (5) reviewing the solution; and (6) extending the solution. The purpose of this study was to assess the ongoing development of problem-solving skills of students with upper, middle, and lower academic abilities at the Department of Biology Education in a state university in Indonesia. This study employed a concurrent embedded mixed-methods design. The repeated-measures ANOVA was used to test the hypothesis for the quantitative data, and NVivo 12 was utilized to analyze the qualitative data. The participants’ problem-solving skills were determined by their responses to items on RICOSRE-integrated worksheets. The students’ responses were graded using a validated and reliable problem-solving rubric. The findings indicated that the students’ problem-solving skills improved consistently in the upper, middle, and lower academic groups that were taught by implementing RICOSRE.
Training in Mathematics Education from a Sustainability Perspective: A Case Study of University Teachers’ Views
Authors: Moreno-Pino Francisco Manuel , Jiménez-Fontana Rocío , Domingo José María Cardeñoso , Goded Pilar Azcárate
Published: March 2022

Humankind is faced with major global challenges to ensure the future of our planet. Target 4.7 of Sustainable Development Goal 4 (quality education) of the 2030 Agenda establishes the importance of ensuring that all learners acquire the theoretical and practical knowledge needed to promote sustainable development through education for sustainable development, human rights, gender equality, and global citizenship, amongst others. The research presented in this article is based on an exploratory study on the views of a group of university teachers from the area of Didactics of Mathematics in the Faculty of Education Sciences at Universidad de Cádiz with regard to Education for Sustainability and its integration in the field of training future teachers in mathematics education. It aims to analyse the perceptions teachers have regarding the subject of study, the work methodologies they use, etc. in greater depth. The authors of the research later interviewed three teachers in the area of Didactics of Mathematics who teach in different education degrees: bachelor’s degree in early childhood education, bachelor’s degree in primary education, and master’s degree in teacher training for compulsory secondary education and baccalaureate. Three instruments were used to collect data: the syllabi of the subjects for which the teachers were responsible, an initial exploratory questionnaire, and a semi-structured personal interview. The instrument employed to analyse the information was the Tool for Methodological Analysis through Sustainability (Herramienta de Análisis Metodológico desde la Sostenibilidad, HAMS in Spanish). The results show the different views and positions the university teachers in the area of Didactics of Mathematics at Universidad de Cádiz have with respect to integrating sustainability into future teachers’ training in mathematics education. It is concluded that the effective integration of sustainability into mathematics education requires university teachers to change and to work together from the same perspective—the one they intend to promote.
Impacts on Students’ Academic Performance Due to Emergency Transition to Remote Teaching during the COVID-19 Pandemic: A Financial Engineering Course Case Study
Authors: Nazempour Rezvan , Darabi Houshang , Nelson Peter C.
Published: March 2022

The COVID-19 pandemic has enforced higher education institutions to adopt emergency remote teaching (ERT) as the substitution for traditional face-to-face (F2F) classes. A lot of concerns have been raised among education institutions, faculty, and students regarding the effectiveness of this sudden shift to online learning. This study aims to statistically investigate the impacts of such a transition on the academic performance of undergraduate students enrolled in the Financial Engineering course. A novel rank percentage measure is proposed and employed to compare the academic performance of around 500 students who attended the course during the four semesters, including the transitional disrupted semester by the pandemic, two consecutive online semesters, and the traditional face-to-face classroom. Our analysis emphasizes the significance of the differences between specific subgroups of the students. In particular, academically average to good students with cumulative GPAs greater than 2.90 have been negatively impacted by the transition to online learning, whereas the results for students with cumulative GPAs less than 2.90 are not very conclusive. Realizing the effects of such closures on the academic performance of students is considered important, since the results might have some merits for other courses and instructors. The template model can be transferred to other courses, and employed by the university administrators, specifically for developing policies in emergency circumstances that are not limited to pandemics.
Improved k-Means Clustering Algorithm for Big Data Based on Distributed SmartphoneNeural Engine Processor
Authors: Awad Fouad H. , Hamad Murtadha M.
Published: March 2022

Clustering is one of the most significant applications in the big data field. However, using the clustering technique with big data requires an ample amount of processing power and resources due to the complexity and resulting increment in the clustering time. Therefore, many techniques have been implemented to improve the performance of the clustering algorithms, especially for k-means clustering. In this paper, the neural-processor-based k-means clustering technique is proposed to cluster big data by accumulating the advantage of dedicated machine learning processors of mobile devices. The solution was designed to be run with a single-instruction machine processor that exists in the mobile device’s processor. Running the k-means clustering in a distributed scheme run based on mobile machine learning efficiently can handle the big data clustering over the network. The results showed that using a neural engine processor on a mobile smartphone device can maximize the speed of the clustering algorithm, which shows an improvement in the performance of the cluttering up to two-times faster compared with traditional laptop/desktop processors. Furthermore, the number of iterations that are required to obtain (k) clusters was improved up to two-times faster than parallel and distributed k-means.