bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-Term Outcomes of a Randomized Study of Neoadjuvant Induction Dual HER2 Blockade with Trastuzumab and Lapatinib Followed by Weekly Paclitaxel Plus Dual HER2 Blockade for HER2-Positive Primary Breast Cancer (Neo-Lath Study)
Authors: Tokunaga Eriko , Masuda Norikazu , Yamamoto Naohito , Iwata Hiroji , Bando Hiroko , Aruga Tomoyuki , Ohtani Shoichiro , Fujisawa Tomomi , Takano Toshimi , Inoue Kenichi , Suganuma Nobuyasu , Takada Masahiro , Aogi Kenjiro , Sakurai Kenichi , Shigematsu Hideo , Kuroi Katsumasa , Haga Hironori , Ohno Shinji , Morita Satoshi , Toi Masakazu
Published: August 2021

We conducted the Neo-LaTH study in which patients were randomized to different lengths of neoadjuvant induction anti-HER2 therapy with lapatinib and trastuzumab followed by weekly paclitaxel plus the anti-HER2 therapy, and in estrogen receptor (ER)-positive patients, with or without concurrent endocrine therapy. The use of endocrine therapy did not affect the response; comprehensive pathological complete response (CpCR) plus ypN0 rate was 57.6% and 30.3% in ER-negative and ER-positive patients, respectively. After surgery, patients received an anthracycline-based regimen based on physician’s choice, followed by trastuzumab for 1 year, and in ER-positive patients, endocrine therapy for 5 years. Here, we report the 5-year survival outcomes. Among the followed-up patients (n = 212), the 5-year disease-free survival (DFS), distant DFS, and overall survival rates were 87.8% [95% confidence interval (CI), 82.5–91.6%], 93.7% (95% CI, 89.3–96.3%), and 95.6% (95% CI, 91.7–97.7%), respectively, with no difference between ER-negative and ER-positive patients. The 5-year DFS rate was significantly higher in patients who had a CpCR plus ypN0 after neoadjuvant treatment than in those who did not (91.7% vs. 85.1%; p = 0.0387). The stratified analysis showed better survival outcomes in patients who had CpCRypN0 than in those who did not after neoadjuvant treatment, regardless of use of adjuvant anthracycline therapy.
Safety and Feasibility of Fasting-Mimicking Diet and Effects on Nutritional Status and Circulating Metabolic and Inflammatory Factors in Cancer Patients Undergoing Active Treatment
Authors: Valdemarin Francesca , Caffa Irene , Persia Angelica , Cremonini Anna Laura , Ferrando Lorenzo , Tagliafico Luca , Tagliafico Alberto , Guijarro Ana , Carbone Federico , Ministrini Stefano , Bertolotto Maria , Becherini Pamela , Bonfiglio Tommaso , Giannotti Chiara , Khalifa Amr , Ghanem Moustafa , Cea Michele , Sucameli Marzia , Murialdo Roberto , Barbero Valentina , Gradaschi Raffaella , Bruzzone Francesca , Borgarelli Consuelo , Lambertini Matteo , Vernieri Claudio , Zoppoli Gabriele , Longo Valter D. , Montecucco Fabrizio , Sukkar Samir G. , Nencioni Alessio
Published: August 2021

In preclinical studies, fasting was found to potentiate the effects of several anticancer treatments, and early clinical studies indicated that patients may benefit from regimes of modified fasting. However, concerns remain over possible negative impact on the patients’ nutritional status. We assessed the feasibility and safety of a 5-day “Fasting-Mimicking Diet” (FMD) as well as its effects on body composition and circulating growth factors, adipokines and cyto/chemokines in cancer patients. In this single-arm, phase I/II clinical trial, patients with solid or hematologic malignancy, low nutritional risk and undergoing active medical treatment received periodic FMD cycles. The body weight, handgrip strength and body composition were monitored throughout the study. Growth factors, adipokines and cyto/chemokines were assessed by ELISA. Ninety patients were enrolled, and FMD was administered every three weeks/once a month with an average of 6.3 FMD cycles/patient. FMD was largely safe with only mild side effects. The patients’ weight and handgrip remained stable, the phase angle and fat-free mass increased, while the fat mass decreased. FMD reduced the serum c-peptide, IGF1, IGFBP3 and leptin levels, while increasing IGFBP1, and these modifications persisted for weeks beyond the FMD period. Thus, periodic FMD cycles are feasible and can be safely combined with standard antineoplastic treatments in cancer patients at low nutritional risk. The FMD resulted in reduced fat mass, insulin production and circulating IGF1 and leptin. This trial was registered on Clinicaltrials.gov in July 2018 with the identifier NCT03595540.
Multidisciplinary Management of Retroperitoneal Sarcoma: Diagnosis, Prognostic Factors and Treatment
Authors: Carbone Fabio , Pizzolorusso Antonio , Di Lorenzo Giuseppe , Di Marzo Massimiliano , Cannella Lucia , Barretta Maria Luisa , Delrio Paolo , Tafuto Salvatore
Published: August 2021

Retroperitoneal sarcomas (RPS) are rare cancers whose management can be challenging due to various presentation patterns, multiple organ involvement, and a high local and distant recurrence rate. Histopathology and prognostic factors analysis are essential to predict the behaviour of the disease and plan the best therapeutic strategy. To date, surgery is still the main therapeutic option that guarantees a chance of cure from the primary disease. While chemotherapy and radiotherapy seem to be good options for controlling metastatic and recurrent irresectable disease, their role in the treatment of primary RPS remains unclear. This literature review aims to provide a comprehensive overview of the multidisciplinary aspects of RPS management in high-volume centres, summarising the diagnostic path, the prognostic factors, and the most suitable therapeutic options.
Lipase-Catalyzed Kinetic Resolution of Dimethyl and Dibutyl 1-Butyryloxy-1-carboxymethylphosphonates
Authors: Majewska Paulina
Published: August 2021

The main objective of this study is the enantioselective synthesis of carboxyhydroxyphosphonates by lipase-catalyzed reactions. For this purpose, racemic dimethyl and dibutyl 1-butyryloxy-1-carboxymethylphosphonates were synthesized and hydrolyzed, using a wide spectrum of commercially available lipases from different sources (e.g., fungi and bacteria). The best hydrolysis results of dimethyl 1-butyryloxy-1-carboxymethylphosphonate were obtained with the use of lipases from Candida rugosa, Candida antarctica, and Aspergillus niger, leading to optically active dimethyl 1-carboxy-1-hydroxymethylphosphonate (58%–98% enantiomeric excess) with high enantiomeric ratio (reaching up to 126). However, in the case of hydrolysis of dibutyl 1-butyryloxy-1-carboxymethylphosphonate, the best results were obtained by lipases from Burkholderia cepacia and Termomyces lanuginosus, leading to optically active dibutyl 1-carboxy-1-hydroxymethylphosphonate (66%–68% enantiomeric excess) with moderate enantiomeric ratio (reaching up to 8.6). The absolute configuration of the products after biotransformation was also determined. In most cases, lipases hydrolyzed (R) enantiomers of both compounds.
High Glycolytic Activity Enhances Stem Cell Reprogramming of Fahd1-KO Mouse Embryonic Fibroblasts
Authors: Salti Ahmad , Etemad Solmaz , Cubero Marta Suarez , Albertini Eva , Kovacs-Szalka Beata , Holzknecht Max , Cappuccio Elia , Cavinato Maria , Edenhofer Frank , Jansen Dürr Pidder
Published: August 2021

Mitochondria play a key role in metabolic transitions involved in the reprogramming of somatic cells into induced pluripotent stem cells (iPSCs), but the underlying molecular mechanisms remain largely unexplored. To obtain new insight into the mechanisms of cellular reprogramming, we studied the role of FAH domain-containing protein 1 (FAHD1) in the reprogramming of murine embryonic fibroblasts (MEFs) into iPSCs and their subsequent differentiation into neuronal cells. MEFs from wild type (WT) and Fahd1-knock-out (KO) mice were reprogrammed into iPSCs and characterized for alterations in metabolic parameters and the expression of marker genes indicating mitochondrial biogenesis. Fahd1-KO MEFs showed a higher reprogramming efficiency accompanied by a significant increase in glycolytic activity as compared to WT. We also observed a strong increase of mitochondrial DNA copy number and expression of biogenesis marker genes in Fahd1-KO iPSCs relative to WT. Neuronal differentiation of iPSCs was accompanied by increased expression of mitochondrial biogenesis genes in both WT and Fahd1-KO neurons with higher expression in Fahd1-KO neurons. Together these observations establish a role of FAHD1 as a potential negative regulator of reprogramming and add additional insight into mechanisms by which FAHD1 modulates mitochondrial functions.
Differential Response of MDA-MB-231 and MCF-7 Breast Cancer Cells to In Vitro Inhibition with CTLA-4 and PD-1 through Cancer-Immune Cells Modified Interactions
Authors: Grubczak Kamil , Kretowska-Grunwald Anna , Groth Dawid , Poplawska Izabela , Eljaszewicz Andrzej , Bolkun Lukasz , Starosz Aleksandra , Holl Jordan M. , Mysliwiec Marta , Kruszewska Joanna , Wojtukiewicz Marek Z. , Moniuszko Marcin
Published: August 2021

Drugs targeting immune checkpoint molecules have been found effective in melanoma, lung cancer, and other malignancies treatment. Recent studies on breast cancer demonstrated the significance of inhibitory anti-CTLA-4 and anti-PD-1 in the regulation of disease progression. However, seemingly the same types of breast cancer do not always respond unambiguously to immunotherapy. Thus, here we set out to analyze the in vitro effects of inhibiting CTLA-4 and PD-1 on interactions between co-cultured lymphocytes and two selected breast adenocarcinoma cell lines. Breast cancer cells were co-cultured with lymphocytes to evaluate the effects of CTLA-4 and PD-1 inhibition. Proliferation, cell cycle, and viability assessment were measured in cancer cells. IFN-gamma, IL-10, perforin, granzyme B production, and CTLA-4 and PD-1 expression were analyzed in lymphocytes. We found that administration of anti-CTLA-4 improved the anti-cancer activity of T cells with reduced proliferation and viability of MDA-MB-231. Lack of response was observed in the context of MCF-7. In addition, differential expression of checkpoint proteins was found between studied cancer cells lines. Inhibition of molecules was followed by IL-10 and IFN-gamma decrease in lymphocytes co-cultured with MDA-MB-231, not demonstrated in reference to MCF-7. Furthermore, CTLA-4 blockage was associated with reduction of CTLA-4+ and PD-1+ lymphocytes in MDA-MB-231, with a significant increase in MCF-7, reduced by anti-PD-1. Altogether, our study revealed that anti-CTLA-4 and anti-PD-1 treatment can improve lymphocytes effects on breast cancer cells. Favorable effects seemed to be related to breast cancer cells features as differential responses were reported. Novel blocking antibodies strategies should be tested for more effective cancer inhibition.
In Silico Study of the Influence of Various Substrates on the Electronic Properties and Electrical Conductivity of Mono- and Bilayer Films of Armchair Single-Walled Carbon Nanotubes
Authors: Slepchenkov Michael M. , Petrunin Alexander A. , Glukhova Olga E.
Published: August 2021

We investigate electronic and electro-physical properties of mono- and bilayer armchair single-walled carbon nanotube (SWCNT) films located on substrates of different types, including substrates in the form of crystalline silicon dioxide (SiO2) films with P42/mnm and P3121 space symmetry groups. The SWCNT films interact with substrate only by van der Waals forces. The densities of electronic states (DOS) and the electron transmission functions are calculated for SWCNT films with various substrates. The electrical conductivity of SWCNT films is calculated based on the electron transmission function. It is found that the substrate plays an important role in the formation of DOS of the SWCNT films, and the surface topology determines the degree and nature of the mutual influence of the nanotube and the substrate. It is shown that the substrate affects the electronic properties of monolayer films, changing the electrical resistance value from 2% to 17%. However, the substrate has practically no effect on the electrical conductivity and resistance of the bilayer film in both directions of current transfer. In this case, the values of the resistances of the bilayer film in both directions of current transfer approach the value of ~6.4 kΩ, which is the lowest for individual SWCNT.
Fluorescence Enhancement via Dual Coupling of Dye Molecules with Silver Nanostructures
Authors: Tran Vien Thi , Ju Heongkyu
Published: August 2021

We demonstrate the enhancement of fluorescence emitted from dye molecules coupled with two surface plasmons, i.e., silver nanoparticles (AgNPs)-induced localized surface plasmons (LSP) and thin silver (Ag) film supported surface plasmons. Excitation light is illuminated to a SiO2 layer that contains both rhodamine 110 molecules and AgNPs. AgNPs enhances excitation rates of dye molecules in their close proximity due to LSP-induced enhancement of local electromagnetic fields at dye excitation wavelengths. Moreover, the SiO2 layer on one surface of which a 50 nm-thick Ag film is coated for metal cladding (air on the other surface), acts as a waveguide core at the dye emission wavelengths. The Ag film induces the surface plasmons which couple with the waveguide modes, resulting in a waveguide-modulated version of surface plasmon coupled emission (SPCE) for different SiO2 thicknesses in a reverse Kretschmann configuration. We find that varying the SiO2 thickness modulates the fluorescent signal of SPCE, its modulation behavior being in agreement with the theoretical simulation of thickness dependent properties of the coupled plasmon waveguide resonance. This enables optimization engineering of the waveguide structure for enhancement of fluorescent signals. The combination of LSP enhanced dye excitation and the waveguide-modulated version of SPCE may offer chances of enhancing fluorescent signals for a highly sensitive fluorescent assay of biomedical and chemical substances.
Thermal Stability of CsPbBr3 Perovskite Quantum Dots Assembled with SBA-15
Authors: Chen Hongyu , Wang Yunfei , Wang Jianing , Liu Wenyan
Published: August 2021

Nowadays, the excellent performance of metal halide perovskite quantum dots (PQDs) has been demonstrated, but the stability is still a perplexing issue. In this paper, the CsPbBr3 QDs were assembled into SBA-15 for the first time. The thermal stability and photoluminescence (PL) intensity of SBA-15@CsPbBr3 QDs were improved. The PL spectra of pure CsPbBr3 QDs have red-shift (~6 nm) with the increasing temperature. However, that of SBA-15@CsPbBr3 QDs have almost no red-shift. The PL intensity of SBA-15@CsPbBr3 QDs decreased slightly after heating and cooling for several times. By comparison, the PL intensity of pure CsPbBr3 QDs decreased more significantly. The experimental results showed that SBA-15 played a significant role in improving the thermal stability of PQDs, which will have an excellent potential for the application of PQDs in the future.
Special Issue “Anti-Icing Coatings and Surfaces”
Authors: Sarkar Dilip Kumar , Noormohammed Saleema
Published: August 2021

It is a known fact that ice adheres to any surface and strongly [...]
Developing Emotional Intelligence with a Game: The League of Emotions Learners Approach
Authors: Santos Jaione , Jesmin Triinu , Martis Antonio , Maunder Michelle , Cruz Sandra , Novo Carolina , Schiff Hannah , Bessa Pedro , Costa Ricardo , Carvalho Carlos Vaz de
Published: August 2021

Being able to understand, express, and communicate emotions is widely recognized as a fundamental competence. For the younger generation entering the professional market, this is particularly relevant as, in this context, emotions are managed and communicated in ways (and channels) that are different from what they are used to and that can easily lead to misunderstandings. Therefore, it is important to analyze how young people deal with, understand, and interpret emotions, particularly in the context of a professional career where the ability to dialogue with different people and how to get around problems in a healthy and resilient way is essential. This analysis will allow one to design and create tools that allow the younger generation to improve their emotional intelligence and competence. This article introduces the League of Emotions Learners (LoEL) project, an innovative initiative that, through a game app, develops the emotional competence and intelligence of young people. The article then presents the results obtained in the initial validation that led to the positive understanding of its impact.
Using Blockchain to Ensure Trust between Donor Agencies and NGOs in Under-Developed Countries
Authors: Rehman Ehsan , Khan Muhammad Asghar , Soomro Tariq Rahim , Taleb Nasser , Afifi Mohammad A. , Ghazal Taher M.
Published: August 2021

Non-governmental organizations (NGOs) in under-developed countries are receiving funds from donor agencies for various purposes, including relief from natural disasters and other emergencies, promoting education, women empowerment, economic development, and many more. Some donor agencies have lost their trust in NGOs in under-developed countries, as some NGOs have been involved in the misuse of funds. This is evident from irregularities in the records. For instance, in education funds, on some occasions, the same student has appeared in the records of multiple NGOs as a beneficiary, when in fact, a maximum of one NGO could be paying for a particular beneficiary. Therefore, the number of actual beneficiaries would be smaller than the number of claimed beneficiaries. This research proposes a blockchain-based solution to ensure trust between donor agencies from all over the world, and NGOs in under-developed countries. The list of National IDs along with other keys would be available publicly on a blockchain. The distributed software would ensure that the same set of keys are not entered twice in this blockchain, preventing the problem highlighted above. The details of the fund provided to the student would also be available on the blockchain and would be encrypted and digitally signed by the NGOs. In the case that a record inserted into this blockchain is discovered to be fake, this research provides a way to cancel that record. A cancellation record is inserted, only if it is digitally signed by the relevant donor agency.
Effects of Trace Amounts of Mn, Zr and Sc on the Recrystallization and Corrosion Resistance of Al-5Mg Alloys
Authors: Lee Sheng-Long , Chiu Yang-Chun , Pan Tse-An , Chen Mien-Chung
Published: August 2021

This study aimed to explore the effects of trace amounts of Mn, Zr, and Sc on the recrystallization behavior and corrosion resistance of Al-5Mg alloys after process annealing by means of alloy design and microstructure analysis of electron backscatter diffraction (EBSD), electron microprobe (EPMA), and electron microscopes (TEM and SEM). The main objective was to obtain alloys with better corrosion resistance. The results show that the fine Al3Zr and Al3Sc precipitated particles were both superior to the MnAl6 particles in inhibiting grain and sub-grain boundary migrations. Therefore, the Zr-containing and Sc-containing alloys were better than the Mn-containing alloy in inhibiting recrystallization. For further comparison, the thermal stability of the Al3Sc particles was better than that of the Al3Zr particles, so the Sc-containing alloy at the high temperature above 350 °C inhibited grain growth better than the Zr-containing alloy. During the recovery stage of the alloy in the recrystallization process, the β-Mg2Al3 phase precipitated on the sub-grain boundary, thus reducing the occurrence of intergranular corrosion. However, in the initial stage of recrystallization, the β-Mg2Al3 phase continuously precipitated on the grain boundary, causing obvious intergranular corrosion. For the Sc-containing alloy, because there was no obvious grain growth stage, the β-Mg2Al3 phase continuously precipitated on the grain boundary, and thereby intergranular corrosion occurred. Therefore, its corrosion resistance was greatly reduced. By contrast, for the alloy containing Mn or Zr, because of obvious grain growth, magnesium atoms aggregated. As a result, the β-Mg2Al3 phase discontinuously precipitated on the grain boundary. The corrosion morphology was local pitting corrosion rather than intergranular corrosion, and thus the corrosion resistance of the alloy was enhanced. As a novelty, this study clearly observed the sensitized precipitation and corrosion morphology of the β-Mg2Al3 phase of Al-5Mg alloy under different recrystallization methods. This will be of benefit to the design of anti-corrosion measures for the future manufacturing and application of Al-5Mg alloy.
Evaluation of Adjuvant Chemotherapy-Associated Steatosis (CAS) in Colorectal Cancer
Authors: Lee Michelle C. M. , Kachura Jacob J. , Vlachou Paraskevi A. , Dzulynsky Raissa , Di Tomaso Amy , Samawi Haider , Baxter Nancy , Brezden-Masley Christine
Published: August 2021

Chemotherapy-associated steatosis is poorly understood in the context of colorectal cancer. In this study, Stage II–III colorectal cancer patients were retrospectively selected to evaluate the frequency of chemotherapy-associated steatosis and to determine whether patients on statins throughout adjuvant chemotherapy develop chemotherapy-associated steatosis at a lower frequency. Baseline and incident steatosis for up to one year from chemotherapy start date was assessed based on radiology. Of 269 patients, 76 (28.3%) had steatosis at baseline. Of the remaining 193 cases, patients receiving adjuvant chemotherapy (n = 135) had 1.57 (95% confidence interval [CI], 0.89 to 2.79) times the adjusted risk of developing steatosis compared to patients not receiving chemotherapy (n = 58). Among patients who underwent chemotherapy, those using statins for pre-existing hyperlipidemia (n = 37) had 0.71 (95% CI, 0.10 to 2.75) times the risk of developing steatosis compared to patients who were not prevalent users of statins (n = 98). Chemotherapeutic treatment of Stage II–III colorectal cancer appears to be consistent with a moderately increased risk of steatosis, although larger studies are necessary to assess the significance of this observation. Prospective trials should be considered to further explore the potential for protective use of statins in this curative patient population.
The Supportive Care Needs of Regional and Remote Cancer Caregivers
Authors: Stiller Anna , Goodwin Belinda C. , Crawford-Williams Fiona , March Sonja , Ireland Michael , Aitken Joanne F. , Dunn Jeff , Chambers Suzanne K.
Published: August 2021

Objective: As cancer survival rates continue to increase, so will the demand for care from family and friends, particularly in more isolated settings. This study aims to examine the needs of cancer caregivers in regional and remote Australia. Methods: A total of 239 informal (i.e., non-professional) cancer caregivers (e.g., family/friends) from regional and remote Queensland, Australia, completed the Comprehensive Needs Assessment Tool for Cancer Caregivers (CNAT-C). The frequencies of individuals reporting specific needs were calculated. Logistic regression analyses assessed the association between unmet needs and demographic characteristics and cancer type. Results: The most frequently endorsed needs were lodging near hospital (77%), information about the disease (74%), and tests and treatment (74%). The most frequent unmet needs were treatment near home (37%), help with economic burden (32%), and concerns about the person being cared for (32%). Younger and female caregivers were significantly more likely to report unmet needs overall (OR = 2.12; OR = 0.58), and unmet healthcare staff needs (OR = 0.35; OR = 1.99, respectively). Unmet family and social support needs were also significantly more likely among younger caregivers (OR = 0.35). Caregivers of breast cancer patients (OR = 0.43) and older caregivers (OR = 0.53) were significantly less likely to report unmet health and psychology needs. Proportions of participants reporting needs were largely similar across demographic groups and cancer type with some exceptions. Conclusions: Caregiver health, practical issues associated with travel, and emotional strain are all areas where regional and remote caregivers require more support. Caregivers’ age and gender, time since diagnosis and patient cancer type should be considered when determining the most appropriate supportive care.
Alzheimer’s Disease and Frontotemporal Dementia: A Robust Classification Method of EEG Signals and a Comparison of Validation Methods
Authors: Miltiadous Andreas , Tzimourta Katerina D. , Giannakeas Nikolaos , Tsipouras Markos G. , Afrantou Theodora , Ioannidis Panagiotis , Tzallas Alexandros T.
Published: August 2021

Dementia is the clinical syndrome characterized by progressive loss of cognitive and emotional abilities to a degree severe enough to interfere with daily functioning. Alzheimer’s disease (AD) is the most common neurogenerative disorder, making up 50–70% of total dementia cases. Another dementia type is frontotemporal dementia (FTD), which is associated with circumscribed degeneration of the prefrontal and anterior temporal cortex and mainly affects personality and social skills. With the rapid advancement in electroencephalogram (EEG) sensors, the EEG has become a suitable, accurate, and highly sensitive biomarker for the identification of neuronal and cognitive dynamics in most cases of dementia, such as AD and FTD, through EEG signal analysis and processing techniques. In this study, six supervised machine-learning techniques were compared on categorizing processed EEG signals of AD and FTD cases, to provide an insight for future methods on early dementia diagnosis. K-fold cross validation and leave-one-patient-out cross validation were also compared as validation methods to evaluate their performance for this classification problem. The proposed methodology accuracy scores were 78.5% for AD detection with decision trees and 86.3% for FTD detection with random forests.
Skeletal and Bone Mineral Density Features, Genetic Profile in Congenital Disorders of Glycosylation: Review
Authors: Lipiński Patryk , Stępień Karolina M. , Ciara Elżbieta , Tylki-Szymańska Anna , Jezela-Stanek Aleksandra
Published: August 2021

Congenital disorders of glycosylation (CDGs) are a heterogeneous group of disorders with impaired glycosylation of proteins and lipids. These conditions have multisystemic clinical manifestations, resulting in gradually progressive complications including skeletal involvement and reduced bone mineral density. Contrary to PMM2-CDG, all remaining CDG, including ALG12-CDG, ALG3-CDG, ALG9-CDG, ALG6-CDG, PGM3-CDG, CSGALNACT1-CDG, SLC35D1-CDG and TMEM-165, are characterized by well-defined skeletal dysplasia. In some of them, prenatal-onset severe skeletal dysplasia is observed associated with early death. Osteoporosis or osteopenia are frequently observed in all CDG types and are more pronounced in adults. Hormonal dysfunction, limited mobility and inadequate diet are common risk factors for reduced bone mineral density. Skeletal involvement in CDGs is underestimated and, thus, should always be carefully investigated and managed to prevent fractures and chronic pain. With the advent of new therapeutic developments for CDGs, the severity of skeletal complications may be reduced. This review focuses on possible mechanisms of skeletal manifestations, risk factors for osteoporosis, and bone markers in reported paediatric and adult CDG patients.
Diagnostic Properties of Three SARS-CoV-2 Antibody Tests
Authors: Basgalupp Suelen , dos Santos Giovana , Bessel Marina , Garcia Lara , de Moura Ana Carolina , Rocha Ana Carolina , Brito Emerson , de Miranda Giovana , Dornelles Thayane , Dartora William , Pellanda Lucia , Hallal Pedro , Wendland Eliana
Published: August 2021

Serological assays emerged as complementary tools to RT-PCR in the diagnosis of SARS-CoV-2 as well as being needed for epidemiological studies. This study aimed to assess the performance of a rapid test (RT) compared to that of serological tests using finger prick blood samples. A total of 183 samples were evaluated, 88 of which were collected from individuals with negative RT-PCR and 95 from positive RT-PCR individuals. The diagnostic performance of RT (WONDFO®) and LUMIT (PROMEGA®) were compared to that of ELISA (EUROIMMUN®) for detecting antibodies against SARS-CoV-2 according to time from symptoms onset. The IgG antibody tests were detected in 77.4% (LUMIT), 77.9% (RT), and 80.0% (ELISA) of individuals. The detection of antibodies against SARS-CoV-2 increases in accordance with increasing time from symptoms onset. Considering only time from symptoms onset >21 days, the positivity rate ranged from 81.8 to 97.0% between the three tests. The RT and LUMIT showed high agreement with ELISA (agreement = 91.5%, k = 0.83, and agreement = 96.3%, k = 0.9, respectively) in individuals who had symptoms 15 to 21 days before sample collection. Compared to that of the ELISA assay, our results show sensitivity ranged from 95% to 100% for IgG antibody detection in individuals with symptoms onset between 15 and 21 days before sample collection. The specificity was 100% in individuals with symptoms onset >15 days before serological tests. This study shows good performance and high level of agreement of three immunoassays for the detection of SARS-CoV-2 antibodies.
Aberrant Whole Blood Gene Expression in the Lumen of Human Intracranial Aneurysms
Authors: Tutino Vincent M. , Lu Yongjun , Ishii Daizo , Poppenberg Kerry E. , Rajabzadeh-Oghaz Hamidreza , Siddiqui Adnan H. , Hasan David M.
Published: August 2021

The rupture of an intracranial aneurysm (IA) causes devastating hemorrhagic strokes. Yet, most IAs remain asymptomatic and undetected until they rupture. In the search for circulating biomarkers of unruptured IAs, we previously performed transcriptome profiling on whole blood and identified an IA-associated panel of 18 genes. In this study, we seek to determine if these genes are also differentially expressed within the IA lumen, which could provide a mechanistic link between the disease and the observed circulating gene expression patterns. To this end, we collected blood from the lumen of 37 IAs and their proximal parent vessels in 31 patients. The expression levels of 18 genes in the lumen and proximal vessel were then measured by quantitative polymerase chain reaction. This analysis revealed that the expression of 6/18 genes (CBWD6, MT2A, MZT2B, PIM3, SLC37A3, and TNFRSF4) was significantly higher in intraluminal blood, while the expression of 3/18 genes (ST6GALNAC1, TCN2, and UFSP1) was significantly lower. There was a significant, positive correlation between intraluminal and proximal expression of CXCL10, MT2A, and MZT2B, suggesting local increases of these genes is reflected in the periphery. Expression of ST6GALNAC1 and TIFAB was significantly positively correlated with IA size, while expression of CCDC85B was significantly positively correlated with IA enhancement on post-contrast MRI, a metric of IA instability and risk. In conclusion, intraluminal expression differences in half of the IA-associated genes observed in this study provide evidence for IA tissue-mediated transcriptional changes in whole blood. Additionally, some genes may be informative in assessing IA risk, as their intraluminal expression was correlated to IA size and aneurysmal wall enhancement.
A Promising Approach: Artificial Intelligence Applied to Small Intestinal Bacterial Overgrowth (SIBO) Diagnosis Using Cluster Analysis
Authors: Hao Rong , Zhang Lun , Liu Jiashuang , Liu Yajun , Yi Jun , Liu Xiaowei
Published: August 2021

Small intestinal bacterial overgrowth (SIBO) is characterized by abnormal and excessive amounts of bacteria in the small intestine. Since symptoms and lab tests are non-specific, the diagnosis of SIBO is highly dependent on breath testing. There is a lack of a universally accepted cut-off point for breath testing to diagnose SIBO, and the dilemma of defining “SIBO patients” has made it more difficult to explore the gold standard for SIBO diagnosis. How to validate the gold standard for breath testing without defining “SIBO patients” has become an imperious demand in clinic. Breath-testing datasets from 1071 patients were collected from Xiangya Hospital in the past 3 years and analyzed with an artificial intelligence method using cluster analysis. K-means and DBSCAN algorithms were applied to the dataset after the clustering tendency was confirmed with Hopkins Statistic. Satisfying the clustering effect was evaluated with a Silhouette score, and patterns of each group were described. Advantages of artificial intelligence application in adaptive breath-testing diagnosis criteria with SIBO were discussed from the aspects of high dimensional analysis, and data-driven and regional specific dietary influence. This research work implied a promising application of artificial intelligence for SIBO diagnosis, which would benefit clinical practice and scientific research.
A Simple Spatial Method for Identifying Point Clusters by Neighbourhood Relationships
Authors: Sillero Neftalí
Published: August 2021

Point events can be distributed regularly, randomly, or in clusters. A cluster of points is defined by the distance from which any point included in a cluster is farther from any other point outside the cluster. Many solutions and methods are possible to define clustering distance. I present here a simple method, nearest neighbour index clustering (NNIC), which separately identifies local clusters of points using only their neighbourhood relationships based on the nearest neighbour index (NNI). It computes a Delaunay triangulation among all points and calculates the length of each line, selecting the lines shorter than the expected nearest neighbour distance. The points intersecting the selected Delaunay lines are considered to belong to an independent cluster. I verified the performance of the NNIC method with a virtual and a real example. In the virtual example, I joined two sets of random point processes following a Poisson distribution and a Thomas cluster process. In the real example, I used a point process from the distribution of individuals of two species of Iberian lizards in a mountainous area. For both examples, I compared the results with those of the nearest neighbour cleaning (NNC) method. NNIC selected a different number of clustered points and clusters in each random set of point processes and included fewer points in clusters than the NNC method.
Teaching Style, Coping Strategies, Stress and Social Support: Associations to the Medical Students’ Perception of Learning during the SARS-CoV-2 Pandemic
Authors: Popa-Velea Ovidiu , Pristavu Carmen Andreea , Ionescu Claudiu Gabriel , Mihăilescu Alexandra Ioana , Diaconescu Liliana Veronica
Published: August 2021

This study assessed the learning perception of undergraduate medical students on three types of teaching (classical/online/hybrid), in relation to coping strategies, stress, and social support, in the context of the SARS-CoV-2 pandemic. Additionally, we explored gender differences and the perceived usefulness of teaching. 201 students (48 men, 153 women; mean age = 22.900, SD = 2.830) participated in the study. They answered a Multidimensional Scale of Perceived Social Support, a Brief Cope Scale, a Student-life Stress Inventory, a visual analog scale for usefulness, and a survey collecting their perceptions about learning across teaching types. Results point out a preference for classical teaching, followed by the hybrid and online formats. Online teaching was identified as more advantageous in terms of time management and seeking information. Denial and substance use were statistically associated with poor communication, bad time using, and impaired learning. Both stress and social support had ambivalent associations with learning perceptions. Gender differences were limited to behavioral disengagement and higher social support perceived by women. Although classical teaching was globally perceived as the most useful, online teaching was considered desirable by male urban respondents. These data may contribute to the strategic growth and refinement of web-based teaching methods in medical universities.
Smartphone Use among Undergraduate STEM Students during COVID-19: An Opportunity for Higher Education?
Authors: Mella-Norambuena Javier , Cobo-Rendon Rubia , Lobos Karla , Sáez-Delgado Fabiola , Maldonado-Trapp Alejandra
Published: August 2021

Due to the COVID-19 pandemic, students worldwide have continued their education remotely. One of the challenges of this modality is that students need access to devices such as laptops and smartphones. Among these options, smartphones are the most accessible because of their lower price. This study analyzes the usage patterns of smartphone users of undergraduate Science, Technology, Engineering, and Math (STEM) students during the COVID-19 pandemic. This cross-sectional descriptive study included 365 students: 162 (44.4%) women and 203 (55.6%) men from a Chilean university. The results revealed that students often accessed the learning management system (LMS) with their computers rather than with their smartphones. Students were connected to the LMS for more hours on their computers than on their smartphones. However, they spent more hours simultaneously connected on their computers and smartphones than just on their computers. During the day, students accessed the LMS mainly from 13:00 to 1:00. The number of connections decreased from 1:00 to 8:00 and increased from 8:00 to 13:00. The LMS resource that students accessed the most using smartphones was discussion forums, while the one they accessed the least was wiki pages. We expect these results to motivate faculties to schedule their activities during the hours students tend to be online and promote discussion forums.
Transforming Learning Spaces on a Budget: Action Research and Service-Learning for Co-Creating Sustainable Spaces
Authors: Montiel Isabel , Mayoral Asunción M. , Navarro-Pedreño Jose , Maiques Silvia
Published: August 2021

Transforming learning spaces has become a priority for many schools, not only for implementing emerging methodologies but also for sanitary reasons due to the COVID-19 pandemic. Schools struggle to find solutions for the lack of space in order to respect the required safety distance, especially public schools with a very tight budget and many administrative barriers to overcome. From participatory action research, findings confirmed that expanding and refurbishing indoor and outdoor space in many public high schools is urgent. Then, an opportunity emerged to develop a new learning space in one of the high schools in touch with the research team at Miguel Hernandez University working on educational spaces since 2017. This article describes the action research (AR) carried out, its main results regarding needs and deficiencies in public high schools in our surroundings, and a subsequent Service-Learning experience promoted by the research group as a solution for upgrading and extending educational spaces and simultaneously developing students’ soft skills, empowering youth, participation, local partnerships and other sustainable development goals meeting 2030 Agenda.
A Domain-Independent Ontology Learning Method Based on Transfer Learning
Authors: Xie Kai , Wang Chao , Wang Peng
Published: August 2021

Ontology plays a critical role in knowledge engineering and knowledge graphs (KGs). However, building ontology is still a nontrivial task. Ontology learning aims at generating domain ontologies from various kinds of resources by natural language processing and machine learning techniques. One major challenge of ontology learning is reducing labeling work for new domains. This paper proposes an ontology learning method based on transfer learning, namely TF-Mnt, which aims at learning knowledge from new domains that have limited labeled data. This paper selects Web data as the learning source and defines various features, which utilizes abundant textual information and heterogeneous semi-structured information. Then, a new transfer learning model TF-Mnt is proposed, and the parameters’ estimation is also addressed. Although there exist distribution differences of features between two domains, TF-Mnt can measure the relevance by calculating the correlation coefficient. Moreover, TF-Mnt can efficiently transfer knowledge from the source domain to the target domain and avoid negative transfer. Experiments in real-world datasets show that TF-Mnt achieves promising learning performance for new domains despite the small number of labels in it, by learning knowledge from a proper existing domain which can be automatically selected.
Best Practices for the Deployment of Edge Inference: The Conclusions to Start Designing
Authors: Flamis Georgios , Kalapothas Stavros , Kitsos Paris
Published: August 2021

The number of Artificial Intelligence (AI) and Machine Learning (ML) designs is rapidly increasing and certain concerns are raised on how to start an AI design for edge systems, what are the steps to follow and what are the critical pieces towards the most optimal performance. The complete development flow undergoes two distinct phases; training and inference. During training, all the weights are calculated through optimization and back propagation of the network. The training phase is executed with the use of 32-bit floating point arithmetic as this is the convenient format for GPU platforms. The inference phase on the other hand, uses a trained network with new data. The sensitive optimization and back propagation phases are removed and forward propagation is only used. A much lower bit-width and fixed point arithmetic is used aiming a good result with reduced footprint and power consumption. This study follows the survey based process and it is aimed to provide answers such as to clarify all AI edge hardware design aspects from the concept to the final implementation and evaluation. The technology as frameworks and procedures are presented to the order of execution for a complete design cycle with guaranteed success.
Analysis and Verification of a Cogging Torque Reduction Method for Variable Flux Memory Permanent Magnet Machine
Authors: Cui Yingjie , Zhang Fei , Huang Lei , Chen Zhongxian
Published: August 2021

In this paper, an analytical method based on the series transform and skewed slot structure of rotor is adopted to reduce the cogging torque of the variable flux memory permanent magnet (VFMPM) machine. Firstly, the theory analysis of the cogging torque of the VFMPM machine was completed. Secondly, a simulation model of the VFMPM machine was established, aiming at calculating the cogging torque of the VFMPM machine and verifying the correctness of the above analytical method. Thirdly, a prototype of 14 rotor slots and 12 stator slots of the VFMPM machine was manufactured, and the experimental results of the cogging torque of the VFMPM machine further verified the effectiveness of the above mentioned theory analysis. Besides, the load force of the VFMPM machine including the cogging torque was also tested and analyzed in this paper.
Cyber-Attack Detection in DC Microgrids Based on Deep Machine Learning and Wavelet Singular Values Approach
Authors: Dehghani Moslem , Niknam Taher , Ghiasi Mohammad , Bayati Navid , Savaghebi Mehdi
Published: August 2021

Nowadays, the role of cyber-physical systems (CPSs) is of paramount importance in power system security since they are more vulnerable to different cyber-attacks. Detection of cyber-attacks on a direct current microgrid (DC-MG) has become a pivotal issue due to the increasing use of them in various electrical engineering applications, from renewable power generations to the distribution of electricity and power system of public transportation and subway electric network. In this study, a novel strategy was provided to diagnose possible false data injection attacks (FDIA) in DC-MGs to enhance the cyber-security of electrical systems. Accordingly, to diagnose cyber-attacks in DC-MG and to identify the FDIA to distributed energy resource (DER) unit, a new procedure of wavelet transform (WT) and singular value decomposition (SVD) based on deep machine learning was proposed. Additionally, this paper presents a developed selective ensemble deep learning (DL) approach using the gray wolf optimization (GWO) algorithm to identify the FDIA in DC-MG. In the first stage, in the paper, to gather sufficient data within the ordinary performance required for the training of the DL network, a DC-MG was operated and controlled with no FDIAs. In the information generation procedure, load changing was considered to have diagnosing datasets for cyber-attack and load variation schemes. The obtained simulation results were compared with the new Shallow model and Hilbert Huang Transform methods, and the results confirmed that the presented approach could more precisely and robustly identify multiple forms of FDIAs with more than 95% precision.
5G UFMC Scheme Performance with Different Numerologies
Authors: Sakkas Lambros , Stergiou Eleftherios , Tsoumanis Georgios , Angelis Constantinos T.
Published: August 2021

5G is the latest mobile communications standard that is spreading fast across the world. Recently defined requirements for 5G systems have led to higher applications’ requirements regarding data rates, lower requirements for latency, and higher efficiency regarding the spectrum usage. Universal Filtered Multi-Carrier (UFMC) is one new candidate modulation scheme for emergent Fifth Generation (5G) communication systems. This paper focuses on Universal Filtered Multi-Carrier (UFMC) design aspects in terms of Bit Error Rate (BER) performance in relation to the filter length used in subband filtering. Simulation results show that BER and CCDF performance varies for different filter lengths and modulation schemes. The main achievement of this work is that the results show that different Dolph–Chebyshev FIR filter lengths do not affect the BER performance both for the 64 and 256 QAM.
Offloading Data through Unmanned Aerial Vehicles: A Dependability Evaluation
Authors: Brito Carlos , Silva Leonardo , Callou Gustavo , Nguyen Tuan Anh , Min Dugki , Lee Jae-Woo , Silva Francisco Airton
Published: August 2021

Applications in the Internet of Things (IoT) context continuously generate large amounts of data. The data must be processed and monitored to allow rapid decision making. However, the wireless connection that links such devices to remote servers can lead to data loss. Thus, new forms of a connection must be explored to ensure the system’s availability and reliability as a whole. Unmanned aerial vehicles (UAVs) are becoming increasingly empowered in terms of processing power and autonomy. UAVs can be used as a bridge between IoT devices and remote servers, such as edge or cloud computing. UAVs can collect data from mobile devices and process them, if possible. If there is no processing power in the UAV, the data are sent and processed on servers at the edge or in the cloud. Data offloading throughout UAVs is a reality today, but one with many challenges, mainly due to unavailability constraints. This work proposes stochastic Petri net (SPN) models and reliability block diagrams (RBDs) to evaluate a distributed architecture, with UAVs focusing on the system’s availability and reliability. Among the various existing methodologies, stochastic Petri nets (SPN) provide models that represent complex systems with different characteristics. UAVs are used to route data from IoT devices to the edge or the cloud through a base station. The base station receives data from UAVs and retransmits them to the cloud. The data are processed in the cloud, and the responses are returned to the IoT devices. A sensitivity analysis through Design of Experiments (DoE) showed key points of improvement for the base model, which was enhanced. A numerical analysis indicated the components with the most significant impact on availability. For example, the cloud proved to be a very relevant component for the availability of the architecture. The final results could prove the effectiveness of improving the base model. The present work can help system architects develop distributed architectures with more optimized UAVs and low evaluation costs.