bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Dry–Wet Cycling and Temperature on Shear Strength and Microscopic Parameters of Coal Measure Soil
Authors: Huang Gang , Zheng Mingxin
Published: December 2022

Exposed coal measure soil (CMS) found in the mountains of Southern China is significantly affected by the seasonal climate, which makes this region prone to frequent shallow landslides. In this regard, very few studies have focused on the shear strength and microscopic characteristics of CMS subjected to dry–wet cycling and temperature. The aim of this study was to experimentally investigate the effects of dry–wet cycling and temperature on shear strength and microscopic parameters of CMS. We carried out an unconsolidated undrained triaxial test and scanning electron microscopy of CMS obtained from the K209 slope on the Chang-li highway. Our results indicated that the soil shear strength and microstructure parameters significantly decreased before three dry–wet cycles. Above 35 °C, the temperature affected mainly the mean fractal dimension. The soil cohesion was negatively correlated with the fractal dimension and positively correlated with the probability entropy. The surface-crack occurred once the stress value of high temperature was greater than 0.57 MPa. Strain-softening, swelling–shrinkage, low soil strength, and high soil temperature formed the main factors underlying rainfall-induced K209 shallow landslides.
Modified Design of Two-Switch Buck-Boost Converter to Improve Power Efficiency Using Fewer Conduction Components
Authors: Kim Sunghwan , Jung Haiyoung , Lee Seok-hyun
Published: December 2022

In this study, a modified design of a two-switch buck-boost (TSBB) converter is proposed to improve power efficiency using fewer conduction components, and the optimal power range is measured. The proposed TSBB converter operates in three topologies: buck, boost, and buck-boost, like the conventional TSBB converter. However, the proposed converter improves the power efficiency in the buck and buck-boost topologies by decreasing conduction loss using the diode in the switch-off section while maintaining the same number of semiconductors as that in the conventional TSBB converter. The power efficiency of the buck topology improves for the power range 10–80 W in the constant voltage (CV) and constant current (CC) modes; it increases on average by 0.75–1.36% and 0.83–2.27% in the CV and CC modes, respectively. The power efficiency of the buck-boost topology step-down improves for the 10–80 W in all modes. This increases the average by 0.73–0.99% and 3.33–4.75% in the CV and CC modes, respectively. The power efficiency of the buck-boost topology step-up increases on average by 1.65–2.00% for 10–80 W in the CV mode. In the CC mode, it increases by 2.17–2.77% on average for 10–50 W.
Special Issue on the Application of Active Noise and Vibration Control
Authors: Chu Yijing , Wu Ming , Sun Hongling
Published: December 2022

Active noise and vibration control aims at attenuating unwanted sound or vibration by automatically generating an anti-sound or vibration [...]
Multi-Granularity Dilated Transformer for Lung Nodule Classification via Local Focus Scheme
Authors: Wu Kunlun , Peng Bo , Zhai Donghai
Published: December 2022

Intelligent lung nodules classification is a meaningful and challenging research topic for early precaution of lung cancers, which aims to diagnose the malignancy of candidate nodules from the pulmonary computed tomography images. Nowadays, deep learning methods have made significant achievements in the medical field and promoted developments of lung nodules classification. Nevertheless, mainstream CNNs-based networks typically excel in learning coarse-grained local feature representations via stacked local-aware and weight-shared convolutions, and cannot practically model the long-range context interaction and the spatial dependencies. To tackle the above difficulties, we innovatively propose an effective Multi-Granularity Dilated Transformer to learn the long-range context relations, and explore fine-grained local details via the proposed Local Focus Scheme. Specifically, we delicately design a novel Deformable Dilated Transformer to incorporate diverse contextual information with self-attention for learning long-range global spatial dependencies. Moreover, numerous investigations indicate that local details are extremely crucial to classify indistinguishable lung nodules. Thus, we propose the Local Focus Scheme to focus on the more discriminative local features by modeling channel-wise grouped topology. Consequently, the Multi-Granularity Dilated Transformer is constructed by leveraging the Local Focus Scheme to guide the Deformable Dilated Transformer for learning fine-grained local cues. Experimental results on the mainstream benchmark LIDC-IDRI demonstrate the superiority of our model compared with the state-of-the-art methods.
Efficient Optimization Algorithm-Based Demand-Side Management Program for Smart Grid Residential Load
Authors: Jasim Ali M. , Jasim Basil H. , Neagu Bogdan-Constantin , Alhasnawi Bilal Naji
Published: December 2022

Incorporating demand-side management (DSM) into residential energy guarantees dynamic electricity management in the residential domain by allowing consumers to make early-informed decisions about their energy consumption. As a result, power companies can reduce peak demanded power and adjust load patterns rather than having to build new production and transmission units. Consequently, reliability is enhanced, net operating costs are reduced, and carbon emissions are mitigated. DSM can be enhanced by incorporating a variety of optimization techniques to handle large-scale appliances with a wide range of power ratings. In this study, recent efficient algorithms such as the binary orientation search algorithm (BOSA), cockroach swarm optimization (CSO), and the sparrow search algorithm (SSA) were applied to DSM methodology for a residential community with a primary focus on decreasing peak energy consumption. Algorithm-based optimal DSM will ultimately increase the efficiency of the smart grid while simultaneously lowering the cost of electricity consumption. The proposed DSM methodology makes use of a load-shifting technique in this regard. In the proposed system, on-site renewable energy resources are used to avoid peaking of power plants and reduce electricity costs. The energy Internet-based ThingSpeak platform is adopted for real-time monitoring of overall energy expenditure and peak consumption. Peak demand, electricity cost, computation time, and robustness tests are compared to the genetic algorithm (GA). According to simulation results, the algorithms produce extremely similar results, but BOSA has a lower standard deviation (0.8) compared to the other algorithms (1.7 for SSA and 1.3 for CSOA), making it more robust and superior, in addition to minimizing cost (5438.98 cents of USD (mean value) and 16.3% savings).
Effect of Different Protection on Lateral Ankle during Landing: An Instantaneous Impact Analysis
Authors: Guo Junchao , Yang Jiemeng , Wang Yawei , Mo Zhongjun , Pu Jingyu , Fan Yubo
Published: December 2022

Ankle sprain is the most common injury during parachute landing. The biomechanical behavior of the tissues can help us understand the injury mechanism of ankle inversion. To accurately describe the injury mechanism of tissues and assess the effect of ankle protection, a stable time of landing was obtained through the dynamic stability test. It was used for the boundary condition of the foot finite element (FE). The FE model was provided a static load equal to half of the bodyweight applied at the distal tibia and fibula; a foot-boot-brace FE model was established to simulate the landing of subjects on an inversion inclined platform of 0–20°, including non-, external, and elastic ankle braces. Compared with the non-ankle brace, both the external and elastic ankle braces decreased the peak strains of the cal-fibular, anterior Ta-fibular, and posterior Ta-fibular ligaments (15.2–33.0%), and of the peak stress of the fibula (15.2–24.5%). For the strain decrement of the aforementioned ligaments, the elastic brace performed better than the external ankle brace under the inversion of the 10° condition. The peak stress of the fibula (15.6 MPa) decreased up to 24.5% with an elastic brace and 5.6–10.3% with an external brace. The findings suggested that the behaviors of lateral ankle ligaments and fibula were meaningful for the functional ability of the ankle. This provides some suggestions regarding the optimal design of ankle protection.
Factors Influencing Pharmacokinetics of Tamoxifen in Breast Cancer Patients: A Systematic Review of Population Pharmacokinetic Models
Authors: Dilli Batcha Jaya , Raju Arun , Matcha Saikumar , Raj S. Elstin , Udupa Karthik , Gota Vikram , Mallayasamy Surulivelrajan
Published: December 2022

Background: Tamoxifen is useful in managing breast cancer and it is reported to have significant variability in its pharmacokinetics. This review aimed to summarize reported population pharmacokinetics studies of tamoxifen and to identify the factors affecting the pharmacokinetics of tamoxifen in adult breast cancer patients. Method: A systematic search was undertaken in Scopus, Web of Science, and PubMed for papers published in the English language from inception to 20 August 2022. Studies were included in the review if the population pharmacokinetic modeling was based on non-linear mixed-effects modeling with a parametric approach for tamoxifen in breast cancer patients. Results: After initial selection, 671 records were taken for screening. A total of five studies were selected from Scopus, Web of Science, PubMed, and by manual searching. The majority of the studies were two-compartment models with first-order absorption and elimination to describe tamoxifen and its metabolites’ disposition. The CYP2D6 phenotype and CYP3A4 genotype were the main covariates that affected the metabolism of tamoxifen and its metabolites. Other factors influencing the drug’s pharmacokinetics included age, co-medication, BMI, medication adherence, CYP2B6, and CYP2C19 genotype. Conclusion: The disposition of tamoxifen and its metabolites varies primarily due to the CYP2D6 phenotype and CYP3A4 genotype. However, other factors, such as anthropometric characteristics and menopausal status, should also be addressed when accounting for this variability. All these studies should be externally evaluated to assess their applicability in different populations and to use model-informed dosing in the clinical setting.
Correction: Wang et al. An Optimization on the Neuronal Networks Based on the ADEX Biological Model in Terms of LUT-State Behaviors: Digital Design and Realization on FPGA Platforms. Biology 2022, 11, 1125
Authors: Wang Yule , Taylan Osman , Alkabaa Abdulaziz S. , Ahmad Ijaz , Tag-Eldin Elsayed , Nazemi Ehsan , Balubaid Mohammed , Alqabbaa Hanan Saud
Published: December 2022

There was an error in the original publication [...]
Genes Modulating Butyrate Metabolism for Assessing Clinical Prognosis and Responses to Systematic Therapies in Hepatocellular Carcinoma
Authors: Chuanbing Zhao , Zhengle Zhang , Ruili Ding , Kongfan Zhu , Jing Tao
Published: December 2022

Butyrate, one of the major products of the gut microbiota, has played notable roles in diverse therapies for multiple tumors. Our study aimed to determine the roles of genes that modulate butyrate metabolism (BM) in predicting the clinical prognosis and responses to systemic therapies in hepatocellular carcinoma (HCC). The genes modulating BM were available from the GeneCard database, and gene expression and clinical information were obtained from TCGA-LIHC, GEO, ICGC-JP, and CCLE databases. Candidate genes from these genes that regulate BM were then identified by univariate Cox analysis. According to candidate genes, the patients in TCGA were grouped into distinct subtypes. Moreover, BM- related gene signature (BMGs) was created via the LASSO Cox algorithm. The roles of BMGs in identifying high-risk patients of HCC, assessing the prognoses, and predicting systematic therapies were determined in various datasets. The statistical analyses were fulfilled with R 4.1.3, GraphPad Prism 8.0 and Perl 5.30.0.1 software. In the TCGA cohort, most butyrate-related genes were over-expressed in the B cluster, and patients in the B cluster showed worse prognoses. BMGs constructed by LASSO were composed of eight genes. BMGs exhibited a strong performance in evaluating the prognoses of HCC patients in various datasets, which may be superior to 33 published biomarkers. Furthermore, BMGs may contribute to the early surveillance of HCC, and BMGs could play active roles in assessing the effectiveness of immunotherapy, TACE, ablation therapy, and chemotherapeutic drugs for HCC. BMGs may be served as novel promising biomarkers for early identifying high-risk groups of HCC, as well as assessing prognoses, drug sensitivity, and the responses to immunotherapy, TACE, and ablation therapy in patients with HCC.
Targeted Epigenetic Interventions in Cancer with an Emphasis on Pediatric Malignancies
Authors: Gaál Zsuzsanna
Published: December 2022

Over the past two decades, novel hallmarks of cancer have been described, including the altered epigenetic landscape of malignant diseases. In addition to the methylation and hyd-roxymethylation of DNA, numerous novel forms of histone modifications and nucleosome remodeling have been discovered, giving rise to a wide variety of targeted therapeutic interventions. DNA hypomethylating drugs, histone deacetylase inhibitors and agents targeting histone methylation machinery are of distinguished clinical significance. The major focus of this review is placed on targeted epigenetic interventions in the most common pediatric malignancies, including acute leukemias, brain and kidney tumors, neuroblastoma and soft tissue sarcomas. Upcoming novel challenges include specificity and potential undesirable side effects. Different epigenetic patterns of pediatric and adult cancers should be noted. Biological significance of epigenetic alterations highly depends on the tissue microenvironment and widespread interactions. An individualized treatment approach requires detailed genetic, epigenetic and metabolomic evaluation of cancer. Advances in molecular technologies and clinical translation may contribute to the development of novel pediatric anticancer treatment strategies, aiming for improved survival and better patient quality of life.
Doppler Ultrasound Selection and Follow-Up of the Internal Mammary Artery as Coronary Graft
Authors: Scicchitano Pietro , De Palo Micaela , Parisi Giuseppe , Gioia Margherita Ilaria , Ciccone Marco Matteo
Published: December 2022

The impact of coronary artery disease (CAD) on all-cause mortality and overall disabilities is well-established. Percutaneous and/or surgical coronary revascularization procedures dramatically reduced the occurrence of adverse cardiovascular events in patients suffering from atherosclerosis. Specifically, guidelines from the European Society of Cardiology on the management of myocardial revascularization promoted coronary artery by-pass graft (CABG) intervention in patients with specific alterations in the coronary tree due to the higher beneficial effects of this procedure as compared to the percutaneous one. The left internal mammary artery (LIMA) is one of the best-performing vessels in CABG procedures due to its location and its own structural characteristics. Nevertheless, the non-invasive assessment of its patency is challenging. Doppler ultrasonography (DU) might perform as a reliable technique for the non-invasive evaluation of the patency of LIMA. Data from the literature revealed that DU may detect severe (>70%) stenosis of the LIMA graft. In this case, pulsed-wave Doppler might show peak diastolic velocity/peak systolic velocity < 0.5 and diastolic fraction < 50%. A stress test might also be adopted for the evaluation of patency of LIMA through DU. The aim of this narrative review is to evaluate the impact of DU on the evaluation of the patency of LIMA graft in patients who undergo follow-up after CABG intervention.
GraphATT-DTA: Attention-Based Novel Representation of Interaction to Predict Drug-Target Binding Affinity
Authors: Bae Haelee , Nam Hojung
Published: December 2022

Drug-target binding affinity (DTA) prediction is an essential step in drug discovery. Drug-target protein binding occurs at specific regions between the protein and drug, rather than the entire protein and drug. However, existing deep-learning DTA prediction methods do not consider the interactions between drug substructures and protein sub-sequences. This work proposes GraphATT-DTA, a DTA prediction model that constructs the essential regions for determining interaction affinity between compounds and proteins, modeled with an attention mechanism for interpretability. We make the model consider the local-to-global interactions with the attention mechanism between compound and protein. As a result, GraphATT-DTA shows an improved prediction of DTA performance and interpretability compared with state-of-the-art models. The model is trained and evaluated with the Davis dataset, the human kinase dataset; an external evaluation is achieved with the independently proposed human kinase dataset from the BindingDB dataset.
New Approach to Chronic Back Pain Treatment: A Case Control Study
Authors: Bonetti Matteo , Lauritano Dorina , Ottaviani Gian Maria , Fontana Alessandro , Frigerio Michele , Zambello Alessio , Della Gatta Luigi , Muto Mario , Carinci Francesco
Published: December 2022

Background and objective: Our study compares the clinical outcome of chronic low back pain present for over six months treated with alpha-lipoic acid (ALA) + palmitoylethanolamide (PEA) and myrrh and periradicular infiltrations of oxygen-ozone under CT guide to periradicular steroidal infiltrations in a short (one week), medium (three months) and long-term period (six months). Methods: We enrolled 246 patients (Group A) with low back pain treated with periradicular infiltrations of oxygen-ozone under CT guide combined with 800 mg/day of ALA + 600 mg/day of PEA + 200 mg/day of myrrh orally. Group B consisted of 176 patients with low back pain treated with periradicular infiltrations of steroids. Patients were clinically monitored one week after the end of treatment, at three months, and at six months using a modified version of McNab’s method. Results: In Group A, the one-week clinical follow-up registered a complete remission of painful symptoms in 206 patients (83.7%), and this manifestation remained optimal in 191 patients at the three-month follow-up (77.6%) and in 178 at six months (72.3%). While the results were satisfactory in 28 patients (10.9%) at one week, 32 (13%) in the medium term, and 41 (16.6%) in the long term, non-significant results were found in 12 patients in the control at one week (4.6%), in 23 at three months (9.3%) and in 27 at six months (10.9%). In Group B, at the short-term follow-up we obtained an excellent clinical result in 103 patients (80.5%), while at three months 85 patients reported the persistence of clinical benefit (66.4%) and at six months, 72 (56.2%) reported the same result. The result was rated satisfactory in 11 (8.5%) and poor in 4 (3%). At the three-month follow-up, 23 (18%) reported a satisfactory result, and 20 (15.6%) had a poor result. At six months, 24 (18.8%) reported the persistence of a satisfactory result while for 32 the result was poor (25%). Conclusion: The results highlight how the treatment associated with ozone therapy and oral administration of alpha-lipoic acid + palmitoylethanolamide and myrrh can be considered a valid alternative to common therapeutic approaches in the treatment of chronic low back pain.
Recent Advances in Self-Powered Wearable Sensors Based on Piezoelectric and Triboelectric Nanogenerators
Authors: Rayegani Arash , Saberian Mohammadmohsen , Delshad Zahra , Liang Junwei , Sadiq Muhammad , Nazar Ali Matin , Mohsan Syed Agha Hassnain , Khan Muhammad Asghar
Published: December 2022

Early clinical diagnosis and treatment of disease rely heavily on measuring the many various types of medical information that are scattered throughout the body. Continuous and accurate monitoring of the human body is required in order to identify abnormal medical signals and to locate the factors that contribute to their occurrence in a timely manner. In order to fulfill this requirement, a variety of battery-free and self-powered methods of information collecting have been developed. For the purpose of a health monitoring system, this paper presents smart wearable sensors that are based on triboelectric nanogenerators (TENG) and piezoelectric nanogenerators (PENG), as well as hybrid nanogenerators that combine piezoelectric and triboelectric nanogenerators (PTNG). Following the presentation of the PENG and TENG principles, a summary and discussion of the most current developments in self-powered medical information sensors with a variety of purposes, structural designs, and electric performances follows. Wearable sensors that generate their own electricity are crucial not only for the proper development of children and patients with unique conditions, but for the purpose of maintaining checks on the wellbeing of the elderly and those who have recently recovered from illness, and for administering any necessary medical care. This work sought to do two things at once: provide perspectives for health monitoring, and open up new avenues for the analysis of long-distance biological movement status.
Enhanced Therapeutic Potential of Irreversible Electroporation under Combination with Gold-Doped Mesoporous Silica Nanoparticles against EMT-6 Breast Cancer Cells
Authors: Jiang Yixin , Jenjob Ratchapol , Yang Su-Geun
Published: December 2022

Irreversible electroporation (IRE) is a non-thermal tumor ablation technique that delivers short pulses of strong electric fields to cancer tissues and induces cell death through the destruction of cell membranes. Here, we synthesized gold-doped mesoporous silica nanoparticles (Au-MSNs) via incipient wetness impregnation and evaluated the therapeutic potentials of combination therapy with IRE. The fabricated Au-MSNs had around 80–100 nm of particle size and were successfully end-doped with Au nanoparticles. Combination treatment of IRE (800 V/cm) and Au-MSNs (100 μg/mL) increased cell membrane permeability by 25-fold compared with single IRE treatment. Cellular reactive oxygen species (ROS) and lipid peroxidation of EMT-6 cells were significantly increased by 14- and 265-fold, respectively, under combination treatment of IRE (800 V/cm) and Au-MSNs (100 µg/mL). Cytotoxic cell death increased by 28% under a combination treatment of IRE (800 V/cm) and Au-MSNs (100 ug/mL) over single IRE. Our studies suggest that the combination treatment of IRE with Au-MSNs can enhance the therapeutic efficacy of IRE for breast cancer.
Assessment of Web Panel Zone in Built-up Box Columns Subjected to Bidirectional Cyclic Loads
Authors: Mata Ramón , Nuñez Eduardo , Sanhueza Frank , Maureira Nelson , Roco Ángel
Published: December 2022

The behavior of the web panel zone has a direct effect on the cyclic performance of steel moment connections. While the mechanisms of web panel zone failure are known under cyclic load, little is known about the behavior of the web panel zone under bidirectional loads in bolted connections. Using experimental tests and calibrated numerical models, this research evaluated the web panel zone behavior under unidirectional and bidirectional cyclic loads. The results showed that bidirectional load can modify the stress and strain distribution in the web panel zone. Moreover, the increasing of the width-to-thickness ratio of the column influences the failure mechanism of the joint configuration and increases the plastic incursion in the column. These data demonstrate that bidirectional effects improve the web panel zone performance under cyclic loads.
Oxidation of Alcohols into Carbonyl Compounds Using a CuO@GO Nano Catalyst in Oxygen Atmospheres
Authors: Malik Maqsood Ahmad , Surepally Ravikumar , Akula Nagarjuna , Cheedarala Ravi Kumar , Alshehri Abdulmohsen Ali , Alzahrani Khalid Ahmed
Published: December 2022

In this article, the oxidation of alcohols into carbonyl compounds was studied in oxygen atmospheres using a copper oxide on graphene oxide (CuO@GO) nano composites catalyst, synthesized by the wet chemistry method. CuO@GO nano composites were prepared from GO, and CuO NPs by the sol-gel method. The transformation of aromatic alcohols into corresponding carbonyl compounds in good-to-high yields were observed using the CuO@GO catalyst under an oxygen atmosphere. Synthesized CuO@GO was confirmed by FT-IR, XRD, XPS, TEM, FE-SEM, TEM, and SEM analyses, and revealed intercalation of CuO-NPs on/in GO nano sheets through the chelation of Cu+2 ions with CO, COOH, and OH groups presenting on the GO nano sheets. The catalytic activity of CuO@GO nano composites for the conversion of alcohols into carbonyl compounds were evaluated through TOF (2.56 × 10−3 mol g−1 min−1). The use of CuO@GO has shown catalytic activity and recyclability with a high conversion of alcohols to ketones. We assume that the proposed CuO@GO catalyst can be used for other key organic transformations and will be evaluated in the future.
iNOS Deletion in Alveolar Epithelium Cannot Reverse the Elastase-Induced Emphysema in Mice
Authors: Gredic Marija , Sharma Vinita , Hadzic Stefan , Wu Cheng-Yu , Pak Oleg , Kojonazarov Baktybek , Duerr Julia , Mall Marcus A. , Guenther Andreas , Schermuly Ralph T. , Grimminger Friedrich , Seeger Werner , Kraut Simone , Sommer Natascha , Weissmann Norbert
Published: December 2022

Background: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. In addition to chronic bronchitis and emphysema, patients often develop at least mild pulmonary hypertension (PH). We previously demonstrated that inhibition of inducible nitric oxide synthase (iNOS) prevents and reverses emphysema and PH in mice. Interestingly, strong iNOS upregulation was found in alveolar epithelial type II cells (AECII) in emphysematous murine lungs, and peroxynitrite, which can be formed from iNOS-derived NO, was shown to induce AECII apoptosis in vitro. However, the specific cell type(s) that drive(s) iNOS-dependent lung regeneration in emphysema/PH has (have) not been identified yet. Aim: we tested whether iNOS knockout in AECII affects established elastase-induced emphysema in mice. Methods: four weeks after a single intratracheal instillation of porcine pancreatic elastase for the induction of emphysema and PH, we induced iNOS knockout in AECII in mice, and gave an additional twelve weeks for the potential recovery. Results: iNOS knockout in AECII did not reduce elastase-induced functional and structural lung changes such as increased lung compliance, decreased mean linear intercept and increased airspace, decreased right ventricular function, increased right ventricular systolic pressure and increased pulmonary vascular muscularization. In vitro, iNOS inhibition did not reduce apoptosis of AECII following exposure to a noxious stimulus. Conclusion: taken together, our data demonstrate that iNOS deletion in AECII is not sufficient for the regeneration of emphysematous murine lungs, and suggest that iNOS expression in pulmonary vascular or stromal cells might be critically important in this regard.
SR Protein Kinase 1 Inhibition by TAF15
Authors: Koukiali Anastasia , Daniilidou Makrina , Mylonis Ilias , Giannakouros Thomas , Nikolakaki Eleni
Published: December 2022

Although SRPKs were discovered nearly 30 years ago, our understanding of their mode of regulation is still limited. Regarded as constitutively active enzymes known to participate in diverse biological processes, their prominent mode of regulation mainly depends on their intracellular localization. Molecular chaperones associate with a large internal spacer sequence that separates the bipartite kinase catalytic core and modulates the kinases’ partitioning between the cytoplasm and nucleus. Besides molecular chaperones that function as anchoring proteins, a few other proteins were shown to interact directly with SRPK1, the most-studied member of SRPKs, and alter its activity. In this study, we identified TAF15, which has been involved in transcription initiation, splicing, DNA repair, and RNA maturation, as a novel SRPK1-interacting protein. The C-terminal RGG domain of TAF15 was able to associate with SRPK1 and downregulate its activity. Furthermore, overexpression of this domain partially relocalized SRPK1 to the nucleus and resulted in hypophosphorylation of SR proteins, inhibition of splicing of a reporter minigene, and inhibition of Lamin B receptor phosphorylation. We further demonstrated that peptides comprising the RGG repeats of nucleolin, HNRPU, and HNRNPA2B1, were also able to inhibit SRPK1 activity, suggesting that negative regulation of SRPK1 activity might be a key biochemical property of RGG motif-containing proteins.
Evaluation of WRF Microphysics Schemes Performance Forced by Reanalysis and Satellite-Based Precipitation Datasets for Early Warning System of Extreme Storms in Hyper Arid Environment
Authors: Mekawy Mohamed , Saber Mohamed , Mekhaimar Sayed A. , Zakey Ashraf Saber , Robaa Sayed M. , Abdel Wahab Magdy
Published: December 2022

In this paper, we will investigate the influence of the microphysics schemes on the rainfall pattern of the extreme storm that impacted Egypt on 12 March 2020. The aim is to improve rainfall forecasting using the numerical Weather Research and Forecasting (WRF) model for an effective Early Warning System (EWS). The performance of six microphysics schemes were evaluated using the Model Object-based Evaluation analysis tool (MODE) forced by three selected satellite-based datasets (CMORPH, PERSIANN, PERSIANN-CCS, etc.) and one reanalysis dataset (ERA5). Six numerical simulations were performed using the WRF model, considering the following microphysics schemes: Lin, WSM6, Goddard, Thompson, Morrison, and NSSL2C. The models were evaluated using both conventional statistical indices and MODE, which is much more suitable in such studies. The results showed that the Lin scheme outperformed the other schemes such as WSM6, Goddard, Thompson, Morrison, and NSSL2C, in rainfall forecasting. The Thompson scheme was found to be the least reliable scheme. An extension for this study is recommended in other regions where the observational rain gauges data are available.
Metabolomics Unravels Grazing Interactions under Nutrient Enrichment from Aquaculture
Authors: Escobar-Sierra Camilo , de Kock Willemien , Hasler-Sheetal Harald , Holmer Marianne , Chatzigeorgiou Giorgos , Tsapakis Manolis , Apostolaki Eugenia T.
Published: December 2022

Our goal was to understand the mechanisms behind the impact of nutrient enrichment at intermediate distances from aquaculture on the interactions of a subtidal macroalgae community with its main grazer, the sea urchin Paracentrotus lividus. We assessed the diversity and cover of the macroalgal community, the abundance and biometrics of the sea urchins, the carbon and nitrogen elemental and isotopic compositions, and their metabolome in two stations, at an intermediate distance (station A) and away (station B) from a fish cage facility in the Aegean Sea (Greece), during the warm and cold seasons. The nutrient input at station A favored a shift to a macroalgal assemblage dominated by turf-forming species, depleted of native-erected species and with a higher abundance of invasive algae. A stable isotope analysis showed fish-farm-associated nitrogen enrichment of the macroalgae and trophic transfer to P. lividus. A decrease in metabolites related to grazing, reproduction, and energy reserves was found in P. lividus at station A. Furthermore, the metabolomic analysis was able to pinpoint stress in P. lividus at an intermediate distance from aquaculture. The chosen combination of traditional ecology with omics technology could be used to uncover not only the sublethal effects of nutrient loading but also the pathways for species interactions.
The Influence of Volcanism, Soils, and Climate in the Endemicity Levels of Asteraceae in the Arequipa Region (Southern Peru)
Authors: Galán-de-Mera Antonio , Linares-Perea Eliana , Beltrán Hamilton
Published: December 2022

We present the diversity of Asteraceae in the Arequipa Region of southern Peru, an area strongly influenced by volcanism, which has given rise to different soil types and has determined a very wide bioclimatic and vegetational zonation. We present the distribution of Asteraceae endemisms of Peru and Arequipa, and of the dry puna. For this purpose, we have used the bioclimatic methodology of Rivas-Martínez, the characteristic soils of each collection point, and the distance of the collection localities from the volcanoes. In the Arequipa Region, we found 232 species of Asteraceae, of which 49 are endemic to Peru or to the dry puna and 7 are endemic to the studied area. Of these endemics, 10 are thermotropical, 1 is mesotropical, 3 are supratropical, and 3 are orotropical bioindicators, being mainly distributed in two large groups of soils: sandy and saline or gypsiferous soils, mostly located within the thermotropical belt of the coastal desert, and andosols and cambisols distributed from the thermotropical to the cryorotropical belts of the Andes. The greatest number of endemics and semi-endemics are found in the vicinity of the arc formed by the Misti, Chachani and Pichu-Pichu volcanoes.
Reference Probe for TcpO2 at Rest: A Systematic Review
Authors: Catella Judith , Mahé Guillaume , Leftheriotis Georges , Long Anne
Published: December 2022

(1) Background: Transcutaneous oxygen pressure (TcpO2) is used to determine the severity of lower extremity arterial disease (LEAD). Many authors used a ratio of limb to chest TcpO2, also called the regional perfusion index (RPI), which should be independent of variations in oxygen delivery and reflective of local limb oxygen supply. The relevance of a reference probe-positioned TcpO2 electrode is debated. We aimed to review the relevance of the reference probe in previous studies using rest TcpO2. (2) Methods: We searched Medline and the Cochrane Central Register of Controlled Trials on 22 September 2022 using keywords related to TcpO2, reference probe and LEAD. (3) Results/Discussion: Fifteen studies were included in the review. Nine studies investigated LEAD severity (n = 9), amputation healing predication (n = 4), surgical outcome prediction (n = 2), therapeutic effect (n = 3) and difference according to diabetic status (n = 1). Four studies investigated more than 1 indication. Among 12 (16.7%) studies using RPI, only two authors found a benefit of using RPI instead of absolute TcpO2. Using only univariate analysis, one author reported that RPI was significantly related to viability at 1 year, while distal TcpO2 was not, on 13 limbs. The following year, the same author published a new study including 118 limbs that reported that RPI and absolute TcPO2 were both prognostic factors for limb viability at 1 year using a multivariate model. (4) Conclusions: Only one study firmly supporting the use of RPI, calculated using a reference probe on the arm, to predict BKA healing. Prospective studies are needed to validate this result; for other indications there is insufficient data supporting the use of a TcpO2 reference probe at rest.
An Alternative Diagnostic Method for C. neoformans: Preliminary Results of Deep-Learning Based Detection Model
Authors: Seyer Cagatan Ayse , Taiwo Mustapha Mubarak , Bagkur Cemile , Sanlidag Tamer , Ozsahin Dilber Uzun
Published: December 2022

Cryptococcus neoformans is an opportunistic fungal pathogen with significant medical importance, especially in immunosuppressed patients. It is the causative agent of cryptococcosis. An estimated 220,000 annual cases of cryptococcal meningitis (CM) occur among people with HIV/AIDS globally, resulting in nearly 181,000 deaths. The gold standards for the diagnosis are either direct microscopic identification or fungal cultures. However, these diagnostic methods need special types of equipment and clinical expertise, and relatively low sensitivities have also been reported. This study aims to produce and implement a deep-learning approach to detect C. neoformans in patient samples. Therefore, we adopted the state-of-the-art VGG16 model, which determines the output information from a single image. Images that contain C. neoformans are designated positive, while others are designated negative throughout this section. Model training, validation, testing, and evaluation were conducted using frameworks and libraries. The state-of-the-art VGG16 model produced an accuracy and loss of 86.88% and 0.36203, respectively. Results prove that the deep learning framework VGG16 can be helpful as an alternative diagnostic method for the rapid and accurate identification of the C. neoformans, leading to early diagnosis and subsequent treatment. Further studies should include more and higher quality images to eliminate the limitations of the adopted deep learning model.
Differential Diagnosis of Thoracoacromial Artery Pseudoaneurysm from Shoulder Inflammatory Pseudotumor: A Case Report
Authors: Huang Tzu-Yen , Feng Pin-Chao , Wang Yao-Chang , Su Chun-Yi
Published: December 2022

Diagnosing shoulder tumors is a challenge because the joint is very complex, and a static examination can misdiagnose some tumors. However, we found that a pseudoaneurysm provides a differential diagnosis of a tumor, and to that end, we present a case that mimics shoulder infection. The patient was an 80-year-old female who had a history of coronary artery disease and end-stage renal disease under regular hemodialysis and complained of right shoulder swelling and progression. A magnetic resonance imaging (MRI) scan revealed an abscess, inflammatory pseudotumor (IPT), and osteomyelitis of the humerus. Computed tomography (CT)-guided pigtail drainage was performed twice without significant improvement. An angiogram revealed a right shoulder pseudoaneurysm fed by the acromial branch of the thoracoacromial artery. After endovascular coiling, the patient was discharged and outpatient follow-up was arranged. If aspiration of the abscess leads to only mild improvement in shoulder swelling, further evaluation should be arranged. An angiogram examination is a good method for diagnosing and designing operations, and endovascular treatment is good for preventing injury to the muscle, tendon, nerve, or blood vessels.
An Automatic Premature Ventricular Contraction Recognition System Based on Imbalanced Dataset and Pre-Trained Residual Network Using Transfer Learning on ECG Signal
Authors: Ullah Hadaate , Heyat Md Belal Bin , Akhtar Faijan , Muaad Abdullah Y. , Ukwuoma Chiagoziem C. , Bilal Muhammad , Miraz Mahdi H. , Bhuiyan Mohammad Arif Sobhan , Wu Kaishun , Damaševičius Robertas , Pan Taisong , Gao Min , Lin Yuan , Lai Dakun
Published: December 2022

The development of automatic monitoring and diagnosis systems for cardiac patients over the internet has been facilitated by recent advancements in wearable sensor devices from electrocardiographs (ECGs), which need the use of patient-specific approaches. Premature ventricular contraction (PVC) is a common chronic cardiovascular disease that can cause conditions that are potentially fatal. Therefore, for the diagnosis of likely heart failure, precise PVC detection from ECGs is crucial. In the clinical settings, cardiologists typically employ long-term ECGs as a tool to identify PVCs, where a cardiologist must put in a lot of time and effort to appropriately assess the long-term ECGs which is time consuming and cumbersome. By addressing these issues, we have investigated a deep learning method with a pre-trained deep residual network, ResNet-18, to identify PVCs automatically using transfer learning mechanism. Herein, features are extracted by the inner layers of the network automatically compared to hand-crafted feature extraction methods. Transfer learning mechanism handles the difficulties of required large volume of training data for a deep model. The pre-trained model is evaluated on the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia and Institute of Cardiological Technics (INCART) datasets. First, we used the Pan–Tompkins algorithm to segment 44,103 normal and 6423 PVC beats, as well as 106,239 normal and 9987 PVC beats from the MIT-BIH Arrhythmia and IN-CART datasets, respectively. The pre-trained model employed the segmented beats as input after being converted into 2D (two-dimensional) images. The method is optimized with the using of weighted random samples, on-the-fly augmentation, Adam optimizer, and call back feature. The results from the proposed method demonstrate the satisfactory findings without the using of any complex pre-processing and feature extraction technique as well as design complexity of model. Using LOSOCV (leave one subject out cross-validation), the received accuracies on MIT-BIH and INCART are 99.93% and 99.77%, respectively, suppressing the state-of-the-art methods for PVC recognition on unseen data. This demonstrates the efficacy and generalizability of the proposed method on the imbalanced datasets. Due to the absence of device-specific (patient-specific) information at the evaluating stage on the target datasets in this study, the method might be used as a general approach to handle the situations in which ECG signals are obtained from different patients utilizing a variety of smart sensor devices.
Correcting Diagnostic Test Sensitivity and Specificity for Patient Misclassifications Resulting from Use of an Imperfect Reference Standard
Authors: Sherwin Paul F.
Published: December 2022

Investigational diagnostic tests are validated by using a reference standard (RS). If the RS is imperfect (i.e., it has sensitivity [Se] and/or specificity [Sp] < 1), incorrect values for the investigational test’s Se and Sp may result because of patient misclassification by the RS. Formulas were derived to correct a test’s Se and Sp that were determined by using an imperfect RS. The following derived formulas correct for misclassification and give the true numbers of disease-positive [nDP] and disease-negative patients [nDN] from the apparent number of disease-positive and disease-negative patients (anDP and anDN), and the Se and Sp of the RS (SeR, SpR): nDP = (anDP × SpR + anDN × SpR − anDN)/JR; nDN = (anDP × SeR + anDN × SeR − anDP)/JR, where JR is Youden’s Index for the RS (JR = SeR + SpR − 1). The following derived formulas give the correct Se and Sp of an investigational test (SeI and SpI): SeI = (anTPI × SpR − nDP × SeR × SpR + nDP × JR + nDN × SpR2 − nDN × SpR − SpR × anTNI + anTNI)/(nDP × JR); SpI = (anTPI − anTPI × SeR + nDP × SeR2 −  nDP × SeR − SeR × nDN × SpR + nDN × JR + SeR × anTNI)/(nDN × JR), where anTPI is the apparent number of true-positive test results, and anTNI is the apparent number of true-negative test results. The derived formulas correct for patient misclassification by an imperfect RS and give the correct values of a diagnostic test’s Se and Sp.
On Spatiotemporal Overdispersion and Macroparasite Accumulation in Hosts Leading to Aggregation: A Quantitative Framework
Authors: Rabajante Jomar Fajardo
Published: December 2022

In many host–parasite systems, overdispersion in the distribution of macroparasites leads to parasite aggregation in the host population. This overdispersed distribution is often characterized by the negative binomial or by the power law. The aggregation is shown by a clustering of parasites in certain hosts, while other hosts have few or none. Here, I present a theory behind the overdispersion in complex spatiotemporal systems as well as a computational analysis for tracking the behavior of transmissible diseases with this kind of dynamics. I present a framework where heterogeneity and complexity in host–parasite systems are related to aggregation. I discuss the problem of focusing only on the average parasite burden without observing the risk posed by the associated variance; the consequences of under- or overestimation of disease transmission in a heterogenous system and environment; the advantage of including the network of social interaction in epidemiological modeling; and the implication of overdispersion in the management of health systems during outbreaks.
Expression of MUC-2, MUC-6, NAPE-PLD, IL-6 and IL-13 in Healthy and Metaplastic Bronchial Epithelium
Authors: Lohova Elizabeta , Pilmane Mara
Published: December 2022

Background: The normal tissue structure of the respiratory system is necessary to provide adequate protection of the airways and lungs. Prolonged exposure to trigger factors can result in adaptive mechanism activation and lead to the development of chronic pulmonary diseases or even dysplastic changes. Materials and methods: Respiratory system material with a pseudostratified ciliated epithelium was obtained from 12 patients (aged 16 to 95), and material with a stratified squamosa epithelium was obtained from six patients (aged 23 to 93). Routine staining was performed, and an immunohistochemistry was conducted for MUC-2, MUC-6, NAPE-PLD, IL-6 and IL-13. Results: Inflammatory processes were not detected in any of the specimens. A number of correlations were identified, with the most important being a strong positive correlation for IL-13 between the alveolar epithelium and alveolar macrophages and a strong positive correlation for IL-6 between the alveolar epithelium and alveolar macrophages in the stratified squamous epithelium group. We also detected a statistically significant difference in IL-6 in alveolar macrophages. Conclusions: There were no signs of dysplastic changes in either group. Increased secretion of IL-13 in the stratified squamous epithelium group shows its involvement in metaplastic changes in the bronchial epithelium. The secretion of atypical factors by hyaline cartilage demonstrates its plasticity and adaptability.
Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation
Authors: Zheng Xin , Zhang Xiaodong
Published: December 2022

Cloud manufacturing systems (CMSs) are networked, distributed and loosely coupled, so they face great uncertainty and risk. This paper combines the complex network model with multi-agent simulation in a novel approach to the robustness analysis of CMSs. Different evaluation metrics are chosen for the two models, and three different robustness attack strategies are proposed. To verify the effectiveness of the proposed method, a case study is then conducted on a cloud manufacturing project of a new energy vehicle. The results show that both the structural and process-based robustness of the system are lowest under the betweenness-based failure mode, indicating that resource nodes with large betweenness are most important to the robustness of the project. Therefore, the cloud manufacturing platform should focus on monitoring and managing these resources so that they can provide stable services. Under the individual server failure mode, system robustness varies greatly depending on the failure behavior of the service provider: Among the five service providers (S1–S5) given in the experimental group, the failure of Server 1 leads to a sharp decline in robustness, while the failure of Server 2 has little impact. This indicates that the CMS can protect its robustness by identifying key servers and strengthening its supervision of them to prevent them from exiting the platform.