bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effects of 5 km Interval Running on the Anterior Cruciate Ligament Strain and Biomechanical Characteristic of the Knee Joint: Simulation and Principal Component Analysis
Authors: Shao Enze , Mei Qichang , Ye Tongjun , Kovács Bálint , Baker Julien S. , Liu Wei , Gu Yaodong
Published: June 2023

Interval running methodologies simulate competition and training conditions, with the aim of enhancing an athletes’ ability to cope with constant deceleration, acceleration, and sudden changes in direction, as associated athletic and performance challenges. Fifteen male athletes were recruited in this study, in which the anterior cruciate ligament was modeled as a nonlinear elastic passive soft tissue in OpenSim 4.2. Participants completed 5 km interval running training on a treadmill. Before and after the interval running, kinematics, kinetics, and electromyography activity of the lower leg during the cutting maneuvers were collected simultaneously. After running training, the anterior cruciate ligament strain demonstrated a decreasing trend when performing unexpected cutting maneuvers. Principal component analysis showed significant differences in knee moments during abduction-adduction; knee angles in flexion-extension, external-internal rotation, and abduction-adduction, as well as knee contact forces in the sagittal and coronal planes. The findings of the study highlight that athletes generate greater adduction moment at the onset of the cut, followed by greater abduction moment towards the end of the cut, which may have a substantial impact on the anterior cruciate ligament loading. Furthermore, athletes need to be mindful of changes in coronal plane contact forces.
Cascaded Convolutional Recurrent Neural Networks for EEG Emotion Recognition Based on Temporal–Frequency–Spatial Features
Authors: Luo Yuan , Wu Changbo , Lv Caiyun
Published: June 2023

Emotion recognition is a research area that spans multiple disciplines, including computational science, neuroscience, and cognitive psychology. The use of electroencephalogram (EEG) signals in emotion recognition is particularly promising due to their objective and nonartefactual nature. To effectively leverage the spatial information between electrodes, the temporal correlation of EEG sequences, and the various sub-bands of information corresponding to different emotions, we construct a 4D matrix comprising temporal–frequency–spatial features as the input to our proposed hybrid model. This model incorporates a residual network based on depthwise convolution (DC) and pointwise convolution (PC), which not only extracts the spatial–frequency information in the input signal, but also reduces the training parameters. To further improve performance, we apply frequency channel attention networks (FcaNet) to distribute weights to different channel features. Finally, we use a bidirectional long short-term memory network (Bi-LSTM) to learn the temporal information in the sequence in both directions. To highlight the temporal importance of the frame window in the sample, we choose the weighted sum of the hidden layer states at all frame moments as the input to softmax. Our experimental results demonstrate that the proposed method achieves excellent recognition performance. We experimentally validated all proposed methods on the DEAP dataset, which has authoritative status in the EEG emotion recognition domain. The average accuracy achieved was 97.84% for the four binary classifications of valence, arousal, dominance, and liking and 88.46% for the four classifications of high and low valence–arousal recognition.
Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave Elastography
Authors: Guiban Olga , Rubini Antonello , Vallone Gianfranco , Caiazzo Corrado , Di Serafino Marco , Pediconi Federica , Ballesio Laura , Trenta Federica , De Vito Corrado , Shkelqimi Arenta , Costanzo Ludovica , Fresilli Daniele , Rizzo Veronica , Cantisani Vito , Vergine Massimo
Published: June 2023

Background: Ultrasound plays a crucial role in early diagnosis of breast cancer. The aim of this research is to evaluate the diagnostic performance of BI-RADS classification in comparison with new semi-automatic software Resona R9, Mindray, “SmartBreast” and strain elastography (SE), point shear wave (pSWE), and 2D shear wave (2D SWE) Elastography for breast lesion differentiation. Methods: Ninety-two breast nodules classified according to BI-RADS lexicon by an expert radiologist were evaluated by a second investigator with B-mode ultrasound, color Doppler, “SmartBreast”, and elastography. Histopathology was considered the gold standard. Results: The agreement between software and investigator was excellent in the identification of the posterior features of breast masses (Cohen’s k = 0.94), good for shape and vascular signal (Cohen’s k, respectively, of 0.6 and 0.65), poor for orientation, margins, and echo pattern (Cohen’s k, respectively, of 0.28, 0.33 and 0.48), moderate for dimensions (Lin’s correlation coefficient of 0.90, p = 0.07). SE showed a greater area under curve (AUC) than pSWE and 2D SWE (0.84, 0.64, and 0.61, respectively), with a greater specificity and a comparable sensitivity to pSWE (respectively, of 0.86 and 0.55, 0.81 and 0.84). Conclusions: SE improved the diagnostic performance of BI-RADS classification more than pSWE and 2D SWE; “SmartBreast” showed good agreement only for shape and vascularization but not for the other ultrasound features of breast lesions.
Research on Prediction Method of Bolt Tightening for Aviation Components Based on Neural Network
Authors: Liu Songkai , Chu Jinkui , Wang Yuanyu
Published: June 2023

Aviation components play an important role in national defense and aviation development. Bolt connections are widely used in the assembly of aviation components, due to their simple structure and convenient disassembly. In addition to the impact of elastic interaction, the gap between the tightened parts also makes it very difficult to obtain a uniform bolt load, to achieve the required tightness during the tightening process. However, the impact of elastic interaction can be reduced by selecting the best tightening sequence, and the optimal tightening sequence of aviation components under different gaps can be predicted by constructing a neural network surrogate model. Based on the predicted optimal sequence, the elastic interaction matrix corresponding to the sequence can be obtained. In order to obtain a uniform preload, the initial load of each bolt is calculated according to an elastic interaction matrix. This research has improved the tightness of aviation components and the real-life efficiency of tightening process planning.
Research on an Improved Non-Destructive Detection Method for the Soluble Solids Content in Bunch-Harvested Grapes Based on Deep Learning and Hyperspectral Imaging
Authors: Zhao Junhong , Hu Qixiao , Li Bin , Xie Yuming , Lu Huazhong , Xu Sai
Published: June 2023

The soluble solids content (SSC) is one of the important evaluation indicators for the internal quality of fresh grapes. However, the current non-destructive detection method based on hyperspectral imaging (HSI) relies on manual operation and is relatively cumbersome, making it difficult to achieve automatic detection in batches. Therefore, in this study, we aimed to conduct research on an improved non-destructive detection method for the SSC of bunch-harvested grapes. This study took the Shine-Muscat grape as the research object. Using Mask R-CNN to establish a grape image segmentation model based on deep learning (DL) applied to near-infrared hyperspectral images (400~1000 nm), 35 characteristic wavelengths were selected using Monte Carlo Uninformative Variable Elimination (MCUVE) to establish a prediction model for SSC. Based on the two abovementioned models, the improved non-destructive detection method for the SSC of bunch-harvested grapes was validated. The comprehensive evaluation index F1 of the image segmentation model was 95.34%. The Rm2 and RMSEM of the SSC prediction model were 0.8705 and 0.5696 Brix%, respectively, while the Rp2 and RMSEP were 0.8755 and 0.9177 Brix%, respectively. The non-destructive detection speed of the improved method was 16.6 times that of the existing method. These results prove that the improved non-destructive detection method for the SSC of bunch-harvested grapes based on DL and HSI is feasible and efficient.
An Event-Driven Architecture for Genomics-Based Diagnostic Data Processing
Authors: Krause Thomas , Zickfeld Mike , Bruchhaus Sebastian , Reis Thoralf , Bornschlegl Marco X. , Buono Paolo , Kramer Michael , Mc Kevitt Paul , Hemmje Matthias
Published: June 2023

Genomics-based diagnostic data (GBDD) are becoming increasingly important for laboratory diagnostics. Due to the large quantity of data and their heterogeneity, GBDD poses a big data challenge. Current analysis tools for GBDD are primarily designed for research and do not meet the requirements of laboratory diagnostics for automation, reliability, transparency, reproducibility, robustness, and accessibility. This makes it difficult for laboratories to use these tools in tests that need to be validated according to regulatory frameworks and to execute tests in a time- and cost-efficient manner. In order to better address these requirements, we propose an event-driven workflow-based architecture as the basis for a processing platform that is highly scalable using container technologies and microservices. A prototype implementation of this approach, called GenomicInsights, has been developed and evaluated to demonstrate its feasibility and suitability for laboratory diagnostics.
Evaluation of the Impact of COVID-19 Restrictions on Air Pollution in Russia’s Largest Cities
Authors: Morozova Anna , Sizov Oleg , Elagin Pavel , Lobzhanidze Natalia , Fedash Anatoly , Mironova Marina
Published: June 2023

Governments around the world took unprecedented measures, such as social distancing and the minimization of public/industrial activity, in response to the COVID-19 pandemic in 2020. This provided a unique chance to assess the relationships between key air pollutant emissions and track the reductions in these emissions in various countries during the lockdown. This study considers atmospheric air pollution in the 78 largest Russian cities (with populations over 250,000) in March–June of 2019–2021. This is the first such study for the largest cities in Russia. The initial data were the TROPOMI measurements (Sentinel-5P satellite) of such pollutants as carbon monoxide (CO), formaldehyde (HCHO), nitrogen dioxide (NO2), and sulfur dioxide (SO2), which are the main anthropogenic pollutants. The data were downloaded from the Google Earth Engine’s cloud-based geospatial data platform. This provided L3-level information for subsequent analysis. The TROPOMI data indicated a decrease in the atmospheric content of the air pollutants in the largest Russian cities during the lockdown compared to the pre-pandemic and post-pandemic periods. The reduced economic activity due to the COVID-19 pandemic had the greatest impact on NO2 concentrations. The average reduction was −30.7%, while the maximum reduction was found within Moscow city limits that existed before 01.07.2012 (−41% with respect to the 2019 level). For sulfur dioxide, the average decrease was only 7%, with a further drop in 2021 (almost 20% relative to 2019). For formaldehyde and carbon monoxide, there were no reductions during the 2020 lockdown period (99.4% and 100.9%, respectively, with respect to 2019). The identified impacts of the COVID-19 lockdown on NO2, SO2, HCHO, and CO NO2 concentrations in major Russian cities generally followed the patterns observed in other industrialized cities in China, India, Turkey, and European countries. The COVID-19 pandemic had a local impact on NO2 concentration reductions in major Russian cities. The differences leveled off over time, and the baseline pollution level for each pollutant was restored.
A Mathematical Model for an Inventory Management and Order Quantity Allocation Problem with Nonlinear Quantity Discounts and Nonlinear Price-Dependent Demand
Authors: Alejo-Reyes Avelina , Mendoza Abraham , Cuevas Erik , Alcaraz-Rivera Miguel
Published: June 2023

This article focuses on solving the order quantity allocation problem for retailers. It considers factors such as quality constraints, nonlinear quantity discounts, and price-dependent demand. By formulating it as a nonlinear maximization problem, the article aims to find the best combination of suppliers and order quantity out of infinite solutions to maximize the retailer’s profit. The main contribution of this research is a new mathematical model that can solve the problem of quality constraint and demand in a single step. This problem is complex due to the number of equations, their nonlinear nature, and the various trade-offs given by the market. Additionally, this research considers demand as output and includes price-dependent demand, which is more realistic for retailers. The proposed model was tested using an example from the recent literature and showed better results than the previously published best solution regarding profit maximization.
Machine Learning Techniques for the Performance Enhancement of Multiple Classifiers in the Detection of Cardiovascular Disease from PPG Signals
Authors: Palanisamy Sivamani , Rajaguru Harikumar
Published: June 2023

Photoplethysmography (PPG) signals are widely used in clinical practice as a diagnostic tool since PPG is noninvasive and inexpensive. In this article, machine learning techniques were used to improve the performance of classifiers for the detection of cardiovascular disease (CVD) from PPG signals. PPG signals occupy a large amount of memory and, hence, the signals were dimensionally reduced in the initial stage. A total of 41 subjects from the Capno database were analyzed in this study, including 20 CVD cases and 21 normal subjects. PPG signals are sampled at 200 samples per second. Therefore, 144,000 samples per patient are available. Now, a one-second-long PPG signal is considered a segment. There are 720 PPG segments per patient. For a total of 41 subjects, 29,520 segments of PPG signals are analyzed in this study. Five dimensionality reduction techniques, such as heuristic- (ABC-PSO, cuckoo clusters, and dragonfly clusters) and transformation-based techniques (Hilbert transform and nonlinear regression) were used in this research. Twelve different classifiers, such as PCA, EM, logistic regression, GMM, BLDC, firefly clusters, harmonic search, detrend fluctuation analysis, PAC Bayesian learning, KNN-PAC Bayesian, softmax discriminant classifier, and detrend with SDC were utilized to detect CVD from dimensionally reduced PPG signals. The performance of the classifiers was assessed based on their metrics, such as accuracy, performance index, error rate, and a good detection rate. The Hilbert transform techniques with the harmonic search classifier outperformed all other classifiers, with an accuracy of 98.31% and a good detection rate of 96.55%.
Maximizing Biomass with Agrivoltaics: Potential and Policy in Saskatchewan Canada
Authors: Jamil Uzair , Pearce Joshua
Published: June 2023

Canada is a leading global agricultural exporter, and roughly half of Canada’s farmland is in Saskatchewan. New agrivoltaics research shows increased biomass for a wide range of crops. This study looks at the potential increase in crop yield and livestock in Saskatchewan through agrivoltaics along with its financial implications. Then, the legislation that could influence the adoption of agrivoltaics in Saskatchewan is reviewed. Specifically, experimental results from agrivoltaic wheat production are analyzed for different adoption scenarios. The impact of converting the province’s pasture grass areas to agrivoltaics and using sheep to harvest them is also examined. The results indicate that approximately 0.4 million more tons of wheat, 2.9 to 3.5 million more tons of forage and 3.9 to 4.6 million additional sheep can be grazed using agrivoltaics in Saskatchewan. Only these two agrivoltaics applications, i.e., wheat farmland and pastureland, result in potential additional billions of dollars in annual provincial agricultural revenue. The Municipalities Act and the Planning and Development Act were found to have the most impact on agrivoltaics in the province as official community plans and zoning bylaws can impede diffusion. Agrivoltaics can be integrated into legislation to avoid delays in the adoption of the technology so that the province reaps all of the benefits.
Functional Connectivity of the Anterior Cingulate Cortex and the Right Anterior Insula Differentiates between Major Depressive Disorder, Bipolar Disorder and Healthy Controls
Authors: Todeva-Radneva Anna , Kandilarova Sevdalina , Paunova Rositsa , Stoyanov Drozdstoy , Zdravkova Tina , Sladky Ronald
Published: June 2023

Background: This study aimed to explore possible differences of the whole-brain functional connectivity of the anterior cingulate cortex (ACC) and anterior insula (AI), in a sample of depressed patients with major depressive disorder (MDD), bipolar disorder (BD) and healthy controls (HC). Methods: A hundred and three subjects (nMDD = 35, nBD = 25, and nHC = 43) between the ages of eighteen and sixty-five years old underwent functional magnetic resonance imaging. The CONN Toolbox was used to process and analyze the functional connectivity of the ACC and AI. Results: The comparison between the patients (MDD/BD) and HC yielded increased resting-state functional connectivity (rsFC) between the ACC and the motor and somatosensory cortices (SSC), superior parietal lobule (SPL), precuneus, and lateral occipital cortex, which was driven by the BD group. In addition, hyperconnectivity between the right AI and the motor and SSC was found in BD, as compared to HC. In MDD, as compared to HC, hyperconnectivity between ACC and SPL and the lateral occipital cortex was found, with no statistical rsFC differences for the AI seed. Compared to BD, the MDD group showed ACC–cerebellum hyperconnectivity and a trend for increased rsFC between the right AI and the bilateral superior frontal cortex. Conclusions: Considering the observed hyperconnectivity between the ACC/somatosensory cortex in the patient group, we suggest depression may be related to an impairment of the sensory-discriminative function of the SSC, which results in the phenomenological signature of mental pain in both MDD and BD. These findings suggest that future research should investigate this particular network with respect to motor functions and executive control, as a potential differential diagnostic biomarker for MDD and BD.
Mechanisms of Action and Limitations of Monoclonal Antibodies and Single Chain Fragment Variable (scFv) in the Treatment of Cancer
Authors: Rodríguez-Nava Cynthia , Ortuño-Pineda Carlos , Illades-Aguiar Berenice , Flores-Alfaro Eugenia , Leyva-Vázquez Marco Antonio , Parra-Rojas Isela , del Moral-Hernández Oscar , Vences-Velázquez Amalia , Cortés-Sarabia Karen , Alarcón-Romero Luz del Carmen
Published: June 2023

Monoclonal antibodies are among the most effective tools for detecting tumor-associated antigens. The U.S. Food and Drug Administration (FDA) has approved more than 36 therapeutic antibodies for developing novel alternative therapies that have significant success rates in fighting cancer. However, some functional limitations have been described, such as their access to solid tumors and low interaction with the immune system. Single-chain variable fragments (scFv) are versatile and easy to produce, and being an attractive tool for use in immunotherapy models. The small size of scFv can be advantageous for treatment due to its short half-life and other characteristics related to the structural and functional aspects of the antibodies. Therefore, the main objective of this review was to describe the current situation regarding the mechanisms of action, applications, and limitations of monoclonal antibodies and scFv in the treatment of cancer.
Therapeutic Approaches in Pancreatic Cancer: Recent Updates
Authors: Kumar Lokender , Kumar Sanjay , Sandeep Kumar , Patel Sanjay Kumar Singh
Published: June 2023

Cancer is a significant challenge for effective treatment due to its complex mechanism, different progressing stages, and lack of adequate procedures for screening and identification. Pancreatic cancer is typically identified in its advanced progression phase with a low survival of ~5 years. Among cancers, pancreatic cancer is also considered a high mortality-causing casualty over other accidental or disease-based mortality, and it is ranked seventh among all mortality-associated cancers globally. Henceforth, developing diagnostic procedures for its early detection, understanding pancreatic cancer-linked mechanisms, and various therapeutic strategies are crucial. This review describes the recent development in pancreatic cancer progression, mechanisms, and therapeutic approaches, including molecular techniques and biomedicines for effectively treating cancer.
Autosomal Dominant Non-Syndromic Hearing Loss (DFNA): A Comprehensive Narrative Review
Authors: Aldè Mirko , Cantarella Giovanna , Zanetti Diego , Pignataro Lorenzo , La Mantia Ignazio , Maiolino Luigi , Ferlito Salvatore , Di Mauro Paola , Cocuzza Salvatore , Lechien Jérôme René , Iannella Giannicola , Simon Francois , Maniaci Antonino
Published: June 2023

Autosomal dominant non-syndromic hearing loss (HL) typically occurs when only one dominant allele within the disease gene is sufficient to express the phenotype. Therefore, most patients diagnosed with autosomal dominant non-syndromic HL have a hearing-impaired parent, although de novo mutations should be considered in all cases of negative family history. To date, more than 50 genes and 80 loci have been identified for autosomal dominant non-syndromic HL. DFNA22 (MYO6 gene), DFNA8/12 (TECTA gene), DFNA20/26 (ACTG1 gene), DFNA6/14/38 (WFS1 gene), DFNA15 (POU4F3 gene), DFNA2A (KCNQ4 gene), and DFNA10 (EYA4 gene) are some of the most common forms of autosomal dominant non-syndromic HL. The characteristics of autosomal dominant non-syndromic HL are heterogenous. However, in most cases, HL tends to be bilateral, post-lingual in onset (childhood to early adulthood), high-frequency (sloping audiometric configuration), progressive, and variable in severity (mild to profound degree). DFNA1 (DIAPH1 gene) and DFNA6/14/38 (WFS1 gene) are the most common forms of autosomal dominant non-syndromic HL affecting low frequencies, while DFNA16 (unknown gene) is characterized by fluctuating HL. A long audiological follow-up is of paramount importance to identify hearing threshold deteriorations early and ensure prompt treatment with hearing aids or cochlear implants.
Thickness and Volume of Epicardial Adipose Tissue in Relation to Stiffness and Elasticity of Aorta Assessed by Computed Tomography Angiography
Authors: Gać Paweł , Hajdusianek Wojciech , Żórawik Aleksandra , Macek Piotr , Poręba Małgorzata , Poręba Rafał
Published: June 2023

Purpose. The aim of the study was to assess the importance of the measurements of thickness and volume of epicardial adipose tissue (EAT) in coronary computed tomography angiography (CCTA) as a predictive factor of increased stiffness and impaired elasticity of aorta. Methods and materials. The study involved a group of 97 patients (63.48 ± 8.50 years). In accordance with the medians of epicardial adipose tissue (EAT) parameters, aortic elasticity and stiffness parameters, patients were divided into subgroups: EAT thickness median 9.40 mm, EAT volume median 61.95 mL, EAT thickness index 5.08 mm/m2 and EAT volume index 34.33 mL/m2. Results. The mean coronary artery calcium score was 162.24 (±317.69). The mean aortic stiffness index was 4.18 (±0.81). The assessed mean aortic elasticity parameters were 3.29% (±2.37) and 0.12 cm2/dyn (±0.09) for strain and distensibility, respectively. A positive linear correlation was observed between EAT parameters and aortic stiffness (0.21), volume (0.51), thickness index (0.24), volume index (0.55) and, for aorta elasticity, a negative linear correlation between the following EAT parameters was observed: thickness (−0.32 and −0.30), volume (−0.49 and −0.48), thickness index (−0.34 and −0.31), volume index (−0.51 and −0.49) and aortic elasticity parameters (aorta strain and aorta distensibility, respectively). Conclusion. The study showed that CCTA illustrates a relationship between the parameters of EAT and an increased stiffness of the aorta, while the most predictive factor of stiffness was the volume index.
Opiate Antagonists for Chronic Pain: A Review on the Benefits of Low-Dose Naltrexone in Arthritis versus Non-Arthritic Diseases
Authors: Dara Praneet , Farooqui Zeba , Mwale Fackson , Choe Chungyoul , van Wijnen Andre J. , Im Hee-Jeong
Published: June 2023

Chronic pain conditions create major financial and emotional burdens that can be devastating for individuals and society. One primary source of pain is arthritis, a common inflammatory disease of the joints that causes persistent pain in affected people. The main objective of pharmacological treatments for either rheumatoid arthritis (RA) or osteoarthritis (OA) is to reduce pain. Non-steroidal anti-inflammatory drugs, opioids, and opioid antagonists have each been considered in the management of chronic pain in arthritis patients. Naltrexone is an oral-activated opioid antagonist with biphasic dose-dependent pharmacodynamic effects. The molecule acts as a competitive inhibitor of opioid receptors at high doses. However, naltrexone at low doses has been shown to have hormetic effects and provides relief for chronic pain conditions such as fibromyalgia, multiple sclerosis (MS), and inflammatory bowel disorders. Current knowledge of naltrexone suggests that low-dose treatments may be effective in the treatment of pain perception in chronic inflammatory conditions observed in patients with either RA or OA. In this review, we evaluated the therapeutic benefits of low-dose naltrexone (LDN) on arthritis-related pain conditions.
Sex Differences in the Anti-Hypertensive Effect of Calcium-Channel Blockers: A Systematic Review and Meta-Analysis
Authors: van Luik Eveline M. , Vaes Esmée W. P. , Vesseur Maud A. M. , Wilmes Nick , Meijs Daniek A. M. , Laven Sophie A. J. S. , Mohseni-Alsalhi Zenab , de Haas Sander , Spaanderman Marc E. A. , Ghossein-Doha Chahinda
Published: June 2023

Cardiovascular disease (CVD) is the number one cause of death worldwide, with hypertension as the leading risk factor for both sexes. As sex may affect responsiveness to antihypertensive compounds, guidelines for CVD prevention might necessitate divergence between females and males. To this end, we studied the effectiveness of calcium channel blockers (CCB) on blood pressure (BP), heart rate (HR) and cardiac function between sexes. We performed a systematic review and meta-analysis on studies on CCB from inception to May 2020. Studies had to present both baseline and follow-up measurements of the outcome variables of interest and present data in a sex-stratified manner. Mean differences were calculated using a random-effects model. In total, 38 studies with 8202 participants were used for this review. In females as compared to males, systolic BP decreased by −27.6 mmHg (95%CI −36.4; −18.8) (−17.1% (95%CI −22.5;−11.6)) versus −14.4 mmHg (95%CI −19.0; −9.9) (−9.8% (95%CI −12.9;−6.7)) (between-sex difference p < 0.01), diastolic BP decreased by −14.1 (95%CI −18.8; −9.3) (−15.2%(95%CI −20.3;−10.1)) versus −10.6 mmHg (95%CI −14.0; −7.3) (−11.2% (95%CI −14.8;−7.7)) (between-sex difference p = 0.24). HR decreased by −1.8 bpm (95%CI −2.5; −1.2) (−2.5% (95%CI −3.4; −1.6)) in females compared to no change in males (0.3 bpm (95% CI −1.2; 1.8)) (between-sex difference p = 0.01). In conclusion, CCB lowers BP in both sexes, but the observed effect is larger in females as compared to males.
Detection of Biological Molecules Using Nanopore Sensing Techniques
Authors: Șoldănescu Iuliana , Lobiuc Andrei , Covașă Mihai , Dimian Mihai
Published: June 2023

Modern biomedical sensing techniques have significantly increased in precision and accuracy due to new technologies that enable speed and that can be tailored to be highly specific for markers of a particular disease. Diagnosing early-stage conditions is paramount to treating serious diseases. Usually, in the early stages of the disease, the number of specific biomarkers is very low and sometimes difficult to detect using classical diagnostic methods. Among detection methods, biosensors are currently attracting significant interest in medicine, for advantages such as easy operation, speed, and portability, with additional benefits of low costs and repeated reliable results. Single-molecule sensors such as nanopores that can detect biomolecules at low concentrations have the potential to become clinically relevant. As such, several applications have been introduced in this field for the detection of blood markers, nucleic acids, or proteins. The use of nanopores has yet to reach maturity for standardization as diagnostic techniques, however, they promise enormous potential, as progress is made into stabilizing nanopore structures, enhancing chemistries, and improving data collection and bioinformatic analysis. This review offers a new perspective on current biomolecule sensing techniques, based on various types of nanopores, challenges, and approaches toward implementation in clinical settings.
The Use of Hydrogel Dressings in Sulfur Mustard-Induced Skin and Ocular Wound Management
Authors: Caffin Fanny , Boccara David , Piérard Christophe
Published: June 2023

Over one century after its first military use on the battlefield, sulfur mustard (SM) remains a threatening agent. Due to the absence of an antidote and specific treatment, the management of SM-induced lesions, particularly on the skin and eyes, still represents a challenge. Current therapeutic management is mainly limited to symptomatic and supportive care, pain relief, and prevention of infectious complications. New strategies are needed to accelerate healing and optimize the repair of the function and appearance of damaged tissues. Hydrogels have been shown to be suitable for healing severe burn wounds. Because the same gravity of lesions is observed in SM victims, hydrogels could be relevant dressings to improve wound healing of SM-induced skin and ocular injuries. In this article, we review how hydrogel dressings may be beneficial for improving the wound healing of SM-induced injuries, with special emphasis placed on their suitability as drug delivery devices on SM-induced skin and ocular lesions.
The Use of 3D Printed Models for Surgical Simulation of Cranioplasty in Craniosynostosis as Training and Education
Authors: Uhl Jean Francois , Sufianov Albert , Ruiz Camillo , Iakimov Yuri , Mogorron Huerta Jose , Encarnacion Ramirez Manuel , Prat Guillermo , Lorea Barbara , Baldoncini Matias , Goncharov Evgeniy , Ramirez Issael , Céspedes José Rafael Cerda , Nurmukhametov Renat , Montemurro Nicola
Published: June 2023

Background: The advance in imaging techniques is useful for 3D models and printing leading to a real revolution in many surgical specialties, in particular, neurosurgery. Methods: We report on a clinical study on the use of 3D printed models to perform cranioplasty in patients with craniosynostosis. The participants were recruited from various medical institutions and were divided into two groups: Group A (n = 5) received traditional surgical education (including cadaveric specimens) but without using 3D printed models, while Group B (n = 5) received training using 3D printed models. Results: Group B surgeons had the opportunity to plan different techniques and to simulate the cranioplasty. Group B surgeons reported that models provided a realistic and controlled environment for practicing surgical techniques, allowed for repetitive practice, and helped in visualizing the anatomy and pathology of craniosynostosis. Conclusion: 3D printed models can provide a realistic and controlled environment for neurosurgeons to develop their surgical skills in a safe and efficient manner. The ability to practice on 3D printed models before performing the actual surgery on patients may potentially improve the surgeons’ confidence and competence in performing complex craniosynostosis surgeries.
Cognitive Load Moderates the Effects of Total Sleep Deprivation on Working Memory: Evidence from Event-Related Potentials
Authors: Yin Ying , Chen Shufang , Song Tao , Zhou Qianxiang , Shao Yongcong
Published: June 2023

Purpose: The function of working memory (WM) is impaired by total sleep deprivation (TSD) and cognitive load. However, it is unclear whether the load modulates the effect of TSD on WM. We conducted a pilot study to investigate the effects of 36 h of TSD on WM under different load levels. Materials and methods: Twenty-two male students aged 18–25 years were enrolled, who underwent two types of sleep conditions (baseline and 36 h TSD), where they performed two N-back WM tasks (one-back task and two-back task) with simultaneous electroencephalography recordings. Results: Repeated measures analysis of variance (ANOVA) indicated that, with the increasing load, the reaction time increased and the accuracy decreased. After TSD, the correct number per unit time decreased. The significant interaction effect of the P3 amplitudes between the load level and the sleep condition showed that the reduction in the amplitude of P3 in the two-back task due to TSD was more obvious than that in the one-back task. Conclusions: Our results provided evidence for the moderation of load on the impairment of TSD on WM. The degree of TSD-induced impairment for a higher load was greater than that for a lower load. The current study provides new insights into the mechanisms by which sleep deprivation affects cognitive function.
Relationship between COVID-19 Pandemic Confinement and Worsening or Onset of Depressive Disorders
Authors: Camargo Daniela , Navarro-Tapia Elisabet , Pérez-Tur Jordi , Cardona Fernando
Published: June 2023

Several studies indicate that the pandemic and associated confinement measures may have had an impact on mental health, producing the onset or persistence of symptoms such as stress, anxiety, depression, and fear. This systematic review aims to identify the factors influencing the onset or worsening of depressive symptoms during COVID-19-related confinement. Our systematic search produced 451 articles from selected databases, 398 of which were excluded based on established criteria, while 53 were selected for review. Most studies have reported an increase in the prevalence of depressive symptoms in the general population during the first weeks of confinement. The predominant risk factors associated with the appearance of depressive symptoms included female sex, low educational level, young age, economic difficulties, comorbidities, and a history of previous depressive episodes. People with a pre-existing diagnosis of depressive disorder generally experienced a worsening of their symptoms during confinement in most of the reviewed studies. Moreover, symptomatology persisted at higher levels post-confinement, without significant improvement despite relief in confinement measures. Therefore, ongoing evaluations of post-pandemic depressive symptoms are necessary to advance the knowledge of the relationship between pandemics and depression, allowing accurate conclusions and associations to be made.
Reactivity of Rare-Earth Oxides in Anhydrous Imidazolium Acetate Ionic Liquids
Authors: Shah Sameera , Pietsch Tobias , Herz Maria Annette , Jach Franziska , Ruck Michael
Published: June 2023

Rare-earth metal sesquioxides (RE2O3) are stable compounds that require high activation energies in solid-state reactions or strong acids for dissolution in aqueous media. Alternatively, dissolution and downstream chemistry of RE2O3 have been achieved with ionic liquids (ILs), but typically with additional water. In contrast, the anhydrous IL 1-butyl-3-methylimidazolium acetate [BMIm][OAc] dissolves RE2O3 for RE = La–Ho and forms homoleptic dinuclear metal complexes that crystallize as [BMIm]2[RE2(OAc)8] salts. Chloride ions promote the dissolution without being included in the compounds. Since the lattice energy of RE2O3 increases with decreasing size of the RE3+ cation, Ho2O3 dissolves very slowly, while the sesquioxides with even smaller cations appear to be inert under the applied conditions. The Sm and Eu complex salts show blue and red photoluminescence and Van Vleck paramagnetism. The proton source for the dissolution is the imidazolium cation. Abstraction of the acidic proton at the C2-atom yields an N-heterocyclic carbene (imidazole-2-ylidene). The IL can be regenerated by subsequent reaction with acetic acid. In the overall process, RE2O3 is dissolved by anhydrous acetic acid, a reaction that does not proceed directly.
Pediatric Elbow Dislocations and Associated Fractures
Authors: Lewallen Laura , Elliott Marilyn E. , McIntosh Amy , Ho Christine A.
Published: June 2023

The objective was to evaluate pediatric patients with acute elbow dislocation and/or associated fracture to determine which were indicated for surgical intervention, using a single institution, Institutional Review Board (IRB) approved retrospective review of patients who presented to the Emergency Department (ED) with an acute elbow dislocation. Inclusion criteria were age ≤ 18 years, acute elbow dislocation injury, and appropriate imaging. A total of 117 patients were included 37 had a simple elbow dislocation, 80 had an associated fracture (medial epicondyle 59, lateral condyle 9, radial head/neck 7, other 5). A total of 62% (73/117) were male. The average age was 10.3 years (range 4–17). Mechanisms of injury included: falls from height/playground equipment (46), trampoline (14), and sports (57). All 37 patients with a simple elbow dislocation were successfully treated with closed reduction. Of the 80 patients with an associated fracture, 30 (38%) went on to open reduction internal fixation (ORIF). A total of 59 patients had an associated medial epicondyle fracture; 24 (41%) of whom went on to ORIF. Nine patients had an associated lateral condyle fracture, five (56%) of whom went on to ORIF. Patients with a simple elbow dislocation can be successfully treated with a closed reduction in the ED. However, 30/80 patients with an associated fracture (medial epicondyle, lateral condyle, or radial neck) required operative management.
Early Development of Spinal Deformities in Children Severely Affected with Spinal Muscular Atrophy after Gene Therapy with Onasemnogene Abeparvovec—Preliminary Results
Authors: Soini Venla , Schreiber Gudrun , Wilken Bernd , Hell Anna Kathrin
Published: June 2023

Spinal muscular atrophy (SMA) is a rare genetic disorder, with the most common form being 5q SMA. Survival of children with severe SMA is poor, yet major advances have been made in recent years in pharmaceutical treatment, such as gene-therapy, which has improved patient survival. Therefore, clinical problems, such as the development of spinal deformities in these genetically treated SMA children represent an unknown challenge in clinical work. In a retrospective case series, the development of spinal deformities was analyzed in 16 SMA children (9 male, 7 female) treated with onasemnogene abeparvovec in two institutions during the years 2020 to 2022. Ten out of sixteen patients had a significant kyphosis, and nine out of sixteen patients had significant scoliosis, with the mean curvature angles of 24 ± 27° for scoliosis, and 69 ± 15° for kyphosis. Based on these preliminary data, it can be assumed that early-onset kyphosis presents a clinical challenge in gene-therapy-treated SMA children. Larger datasets with longer follow-up times need to be collected in order to verify these preliminary observations.
Prevalence and Associated Factors of Dental Caries in Syrian Immigrant Children Aged 6–12 Years
Authors: Altaş Zeynep , Sezerol Mehmet
Published: June 2023

Immigrant children are among the groups that are sensitive to problems related to dental health. The aim of this study was to examine the dental caries of Syrian immigrant children. The study is a descriptive and retrospective study. Its population consists of Syrian immigrant children aged 6–12 years who were screened for dental health in the year 2022 in Istanbul. DMF-T (permanent teeth) and dmf-t (milk teeth) indices were used, which are the (t-T) criteria obtained by dividing the sum of caries (d-D), caries extracted (m-M) and caries-filled (f-F) teeth by the number of people examined. Higher dmft and DMFT scores indicate worse dental health. Dental screening was performed on 549 Syrian immigrant children. In total, 27.2% (n = 149) were brushing their teeth once a day and 97.3% of the children (n = 534) had at least one decayed tooth. The dmft score for the 6–7 year age (6.45 ± 3.33) group was significantly higher than the 8–9 year (4.98 ± 2.78) and 10–12 year (3.22 ± 2.02) age groups (p < 0.001). In our study, the dental caries were seen at a very-high frequency among immigrant children and the habit of tooth brushing remains at a low level. Lower age was the relevant factor for dental caries in our study.
Attitudes of Non-Disabled Pupils towards Disabled Pupils to Promote Inclusion in the Physical Education Classroom
Authors: Delgado-Gil Serafín , Mendoza-Muñoz David Manuel , Galán-Arroyo Carmen , Denche-Zamorano Ángel , Adsuar Jose Carmelo , Mañanas-Iglesias Carlos , Castillo-Paredes Antonio , Rojo-Ramos Jorge
Published: June 2023

Inclusive education for disabled people is becoming increasingly important globally. Improving the factors that support the inclusion of people with disabilities in education is one of the main objectives. In addition to teachers, another major factor is how the attitudes of students without disabilities affect those with disabilities, which should be considered in maintaining an inclusive classroom climate. The aim of the study was to analyse the attitudes of non-disabled students towards the inclusion disabled students in Physical Education (PE) and to investigate differences according to gender and school location. A total of 805 girls and boys participating in PE in public secondary schools (12–18 years old) in Extremadura were analysed through the AISDPE (Attitudes towards the Inclusion of Students with Disabilities in PE) questionnaire. The results show students without disabilities have positive attitudes towards the inclusion of students with disabilities. The majority were female. No significant differences were found regarding the location of the school. There are positive attitudes towards the inclusion of students with disabilities in the PE classroom, but these could be improved, especially in aspects more related to cognitive factors. For this, it is necessary for teachers to provide their students with the necessary tools and knowledge to better understand the possibilities and difficulties presented to students with disabilities, thus promoting a more inclusive classroom.
Alternative Fuel Substitution Improvements in Low NOx In-Line Calciners
Authors: Beguedou Essossinam , Narra Satyanarayana , Agboka Komi , Kongnine Damgou Mani , Afrakoma Armoo Ekua
Published: June 2023

The process of making cement clinker uses a lot of energy and produces a lot of pollution. Currently, cement companies use a combination of traditional fossil fuels and alternative fuels (AF-Fuels) to lower their energy consumption and environmental footprint by improving the pyro-system. In a calciner, AF-Fuels can reach a thermal substitution rate (TSR) of up to 80–100%. However, a kiln burner can only achieve a TSR of 50–60%. High TSR values have been provided by improvements in multi-channel burners, proper AF-Fuel feeding point setups, and various AF pre-combustion methods. Significant modeling of the calciner burner and system has also improved TSRs. However, the cement industry has encountered operational problems such as kiln coating build-up, reduced flame temperatures, higher specific heat consumption, and incomplete combustion. There is growing interest in waste substitution, a promising source of AF-Fuel that needs to be integrated into the current cement plant design to solve the calciner operational problems of the cement industry. This study discusses the latest developments and different experimental and modeling studies performed on the direct burning/co-firing of AF-Fuel in the cement industry as well as the incorporation of gasification in cement manufacturing. Based on this, a technically and environmentally improved solution is proposed. The characteristics of both approaches towards pre-calciner function and optimization are critically assessed. The many in-line cement calciner integration technologies and their various configurations for the long-term problems of cement plants are discussed. This project report also focuses on the necessity of creating appropriate calciner models for forecasting calciner production based on various AF-Fuels and their feeding positions in the calciner.
Distribution Patterns of Large Jellyfish and Their Effects on the Zooplankton Community in the Northern Chinese Coastal Seas during the Summer of 2021
Authors: Guo Dongjie , Zhang Fang , Wang Pengpeng , Sun Song
Published: June 2023

The northern Chinese coastal seas have been observed to constitute a large jellyfish blooming hotspots during the las decades. The spatial distribution of the abundance and biomass of large jellyfish was investigated in this area through a bottom trawl survey during the summer of 2021. Nemopilema nomurai, Cyanea spp., Aurelia coerulea, Aequorea spp., and Ulmaridae (undefined sp.) were identified during the investigation. The realized niches of the three most abundant species (N. nomurai, Cyanea spp., and A. coerulea) were measured through the maximum entropy (MaxEnt) model to explain their spatial distribution patterns. Nemopilema nomurai was used as a representative species to estimate the feeding rate and feeding pressure of large jellyfish on the zooplankton. During N. nomurai blooms, the potential consumption of zooplankton by N. nomurai was enormous and even exceeded the zooplankton productivity in regions where N. nomurai assembled in this study. Reductions in absolute and relative abundance were noted in small copepods at mid-bloom and bloom stations compared to non-bloom stations. The realized niches of large jellyfish and their relationships with the zooplankton in this study would be helpful for understanding their biogeographic distribution and ecological roles in the northern Chinese coastal seas under future climate change scenarios.
Spatial Ecology of Reddish-Brown Cuxiú Monkeys (Chiropotes sagulatus, Pitheciidae) in an Isolated Forest Remnant: Movement Patterns and Edge Effects
Authors: Boyle Sarah A. , Lourenço Waldete C. , da Silva Lívia R. , Spironello Wilson R.
Published: June 2023

Habitat loss, and subsequent fragmentation, can increase the amount of forest edge. Primate species vary in their responses to such changes in their habitat. We studied the movement ecology of a group of reddish-brown cuxiú monkeys (Chiropotes sagulatus, Pitheciidae) in a small (13 ha), isolated forest remnant that was <3% of the species’ typical home range in the region. Every 5 min we recorded the group’s latitude and longitude, and the behavior of all individuals in sight. We calculated distance, speed, and trajectory of travel routes, and distance from every location to the nearest forest edge. Using Lidar data, we calculated canopy height. Cuxiús traveled in all cardinal directions, but they turned left more often than right, and they traveled at a faster speed to locations where the monkeys fed than where they did not eat. Although cuxiús used forest from the edge to the interior, they concentrated their movements and activities >30 m from the forest edge. Furthermore, their food sites were located less often near the forest edge, and canopy height of food trees near the forest edge was lower than canopy height of food trees at a greater distance from the edge. Although edge effects impacted the monkeys’ movement, trees >15 m at the forest edge can provide resources. Future research can examine ecological variables in more detail with the movement patterns.