bluuebunny/crossref_metadata_2025 huggingface dataset:
HR+/HER2– Advanced Breast Cancer Treatment in the First-Line Setting: Expert Review
Authors: Jerzak Katarzyna , Bouganim Nathaniel , Brezden-Masley Christine , Edwards Scott , Gelmon Karen , Henning Jan-Willem , Hilton John , Sehdev Sandeep
Published: June 2023

The approval of CDK4/6 inhibitors has dramatically improved care for the treatment of HR+/HER2– advanced breast cancer, but navigating the rapidly-expanding treatment evidence base is challenging. In this narrative review, we provide best-practice recommendations for the first-line treatment of HR+/HER2– advanced breast cancer in Canada based on relevant literature, clinical guidelines, and our own clinical experience. Due to statistically significant improvements in overall survival and progression-free survival, ribociclib + aromatase inhibitor is our preferred first-line treatment for de novo advanced disease or relapse ≥12 months after completion of adjuvant endocrine therapy and ribociclib or abemaciclib + fulvestrant is our preferred first-line treatment for patients experiencing early relapse. Abemaciclib or palbociclib may be used when alternatives to ribociclib are needed, and endocrine therapy can be used alone in the case of contraindication to CDK4/6 inhibitors or limited life expectancy. Considerations for special populations—including frail and fit elderly patients, as well as those with visceral disease, brain metastases, and oligometastatic disease—are also explored. For monitoring, we recommend an approach across CDK4/6 inhibitors. For mutational testing, we recommend routinely performing ER/PR/HER2 testing to confirm the subtype of advanced disease at the time of progression and to consider ESR1 and PIK3CA testing for select patients. Where possible, engage a multidisciplinary care team to apply evidence in a patient-centric manner.
Evolution of Diversity in the Auditory Papillae of Reptiles
Authors: Manley Geoffrey A.
Published: June 2023

The independent origins of middle ears in testudinates, lepidosaurs, and archosaurs in the Triassic led to lineage-specific developments in their auditory epithelia. In comparison to the inferred ancestral state, little changed in testudinates, but archosaurs and most lepidosaurs evolved longer, differentiated auditory papillae. In archosaurs, sensory hair cells specialized across and along the papillae, resulting in mainly sensory tall hair cells and mainly mechanically active short hair cells. Crocodilians have 5 mm-long papillae, but relatively low upper frequency limits at around 4 kHz. Avian papillae are mostly 3 to 5 mm in length, being shorter in small species; in owls they exceptionally reach almost 12 mm and have an upper limit of above 10 kHz. Lepidosaurs retained the ancestral papilla as a low-frequency responsive area with one type of hair cell, but most added newly evolved areas (of max. 2 mm length) consisting of oppositely oriented hair cells responding to frequencies above 1 kHz. Initially, these areas flanked both ends of the ancestral area and were redundant in their responses to sound. The evolution of specific configurations in most families eliminated this redundancy, but the paths taken resulted in diverse anatomies that show high degrees of family specificity. Despite these differences, the high-frequency hearing limit of lepidosaurs rarely exceeds 5 kHz.
Responses of Bird Communities to Habitat Structure along an Aridity Gradient in the Steppes North of the Sahara
Authors: Oñate Juan J. , Suárez Francisco , Calero-Riestra María , Justribó Jorge H. , Hervás Israel , de la Morena Eladio L. García , Ramírez Álvaro , Viñuela Javier , García Jesús T.
Published: June 2023

We explored the influence of habitat structure on bird density and species richness in the poorly known bird communities in the steppes of Eastern Morocco, along a 200 km long N–S gradient of increasing aridity. The birds were surveyed, and habitat structure was measured in 44 transects regularly distributed along the gradient and during the winter and spring seasons in two consecutive years. After applying a principal component analysis (PCA), five axes were identified, including one related to the latitude–altitude–soil-type gradient and another describing the development of herbaceous vegetation. Generalized linear models were used to explore the relations between bird density and species richness with PCA axes in each season, considering both the entire community and groups of granivorous, insectivorous, and mixed-diet species. More than 90% of the birds were year-round residents, with larks dominating the community in both seasons. We conclude that a distinct multifactorial response can be identified for each functional group of species. In the winter, the community is mainly affected by the structure of the habitat, while aridity (and its assumed relation to primary production) is less influential. In the spring, habitat structure continues to have the greatest explanatory power, but location along the aridity gradient becomes more relevant. These findings reveal the interaction of the negative effects of climatic and anthropogenic changes in the habitat available to these bird communities, with a greater impact expected on birds with diets that include seeds, as well as a general shift of optimal breeding conditions toward more northerly latitudes.
Labelled Indoor Point Cloud Dataset for BIM Related Applications
Authors: Abreu Nuno , Souza Rayssa , Pinto Andry , Matos Anibal , Pires Miguel
Published: June 2023

BIM (building information modelling) has gained wider acceptance in the AEC (architecture, engineering, and construction) industry. Conversion from 3D point cloud data to vector BIM data remains a challenging and labour-intensive process, but particularly relevant during various stages of a project lifecycle. While the challenges associated with processing very large 3D point cloud datasets are widely known, there is a pressing need for intelligent geometric feature extraction and reconstruction algorithms for automated point cloud processing. Compared to outdoor scene reconstruction, indoor scenes are challenging since they usually contain high amounts of clutter. This dataset comprises the indoor point cloud obtained by scanning four different rooms (including a hallway): two office workspaces, a workshop, and a laboratory including a water tank. The scanned space is located at the Electrical and Computer Engineering department of the Faculty of Engineering of the University of Porto. The dataset is fully labelled, containing major structural elements like walls, floor, ceiling, windows, and doors, as well as furniture, movable objects, clutter, and scanning noise. The dataset also contains an as-built BIM that can be used as a reference, making it suitable for being used in Scan-to-BIM and Scan-vs-BIM applications. For demonstration purposes, a Scan-vs-BIM change detection application is described, detailing each of the main data processing steps.
Reliability of Multiparametric Magnetic Resonance Imaging in Patients with a Previous Negative Biopsy: Comparison with Biopsy-Naïve Patients in the Detection of Clinically Significant Prostate Cancer
Authors: Barone Biagio , Napolitano Luigi , Calace Francesco Paolo , Del Biondo Dario , Napodano Giorgio , Grillo Marco , Reccia Pasquale , De Luca Luigi , Prezioso Domenico , Muto Matteo , Crocetto Felice , Ferro Matteo
Published: June 2023

Background: Multiparametric magnetic resonance is an established imaging utilized in the diagnostic pathway of prostate cancer. The aim of this study is to evaluate the accuracy and reliability of multiparametric magnetic resonance imaging (mpMRI) in the detection of clinically significant prostate cancer, defined as Gleason Score ≥ 4 + 3 or a maximum cancer core length 6 mm or longer, in patients with a previous negative biopsy. Methods: The study was conducted as a retrospective observational study at the University of Naples “Federico II”, Italy. Overall, 389 patients who underwent systematic and target prostate biopsy between January 2019 and July 2020 were involved and were divided into two groups: Group A, which included biopsy-naïve patients; Group B, which included re-biopsy patients. All mpMRI images were obtained using three Tesla instruments and were interpreted according to PIRADS (Prostate Imaging Reporting and Data System) version 2.0. Results: 327 patients were biopsy-naïve, while 62 belonged to the re-biopsy group. Both groups were comparable in terms of age, total PSA (prostate-specific antigen), and number of cores obtained at the biopsy. 2.2%, 8.8%, 36.1%, and 83.4% of, respectively, PIRADS 2, 3, 4, and 5 biopsy-naïve patients reported a clinically significant prostate cancer compared to 0%, 14.3%, 39%, and 66.6% of re-biopsy patients (p < 0.0001–p = 0.040). No difference was reported in terms of post-biopsy complications. Conclusions: mpMRI confirms its role as a reliable diagnostic tool prior to performing prostate biopsy in patients who underwent a previous negative biopsy, reporting a comparable detection rate of clinically significant prostate cancer.
Heart Failure Emergency Readmission Prediction Using Stacking Machine Learning Model
Authors: Rahman Md. , Rahman Hasib , Prithula Johayra , Chowdhury Muhammad , Ahmed Mosabber , Kumar Jaya , Murugappan M. , Khan Muhammad
Published: June 2023

Heart failure is a devastating disease that has high mortality rates and a negative impact on quality of life. Heart failure patients often experience emergency readmission after an initial episode, often due to inadequate management. A timely diagnosis and treatment of underlying issues can significantly reduce the risk of emergency readmissions. The purpose of this project was to predict emergency readmissions of discharged heart failure patients using classical machine learning (ML) models based on Electronic Health Record (EHR) data. The dataset used for this study consisted of 166 clinical biomarkers from 2008 patient records. Three feature selection techniques were studied along with 13 classical ML models using five-fold cross-validation. A stacking ML model was trained using the predictions of the three best-performing models for final classification. The stacking ML model provided an accuracy, precision, recall, specificity, F1-score, and area under the curve (AUC) of 89.41%, 90.10%, 89.41%, 87.83%, 89.28%, and 0.881, respectively. This indicates the effectiveness of the proposed model in predicting emergency readmissions. The healthcare providers can intervene pro-actively to reduce emergency hospital readmission risk and improve patient outcomes and decrease healthcare costs using the proposed model.
A Deep-Learning-Based GPS Signal Spoofing Detection Method for Small UAVs
Authors: Sun Yichen , Yu Mingxin , Wang Luyang , Li Tianfang , Dong Mingli
Published: June 2023

The navigation of small unmanned aerial vehicles (UAVs) mainly depends on global positioning systems (GPSs). However, GPSs are vulnerable to attack by spoofing, which causes the UAVs to lose their positioning ability. To address this issue, we propose a deep learning method to detect the spoofing of GPS signals received by small UAVs. Firstly, we describe the GPS signal dataset acquisition and preprocessing methods; these include the hardware system of the UAV and the jammer used in the experiment, the time and weather conditions of the data collection, the use of Spearman correlation coefficients for preprocessing, and the use of SVM-SMOTE to solve the spoofing data imbalance. Next, we introduce a PCA-CNN-LSTM model. We used principal component analysis (PCA) of the model to extract feature information related to spoofing from the GPS signal dataset. The convolutional neural network (CNN) in the model was used to extract local features in the GPS signal dataset, and long short-term memory (LSTM) was used as a posterior module of the CNN for further processing and modeling. To minimize randomness and chance in the simulation experiments, we used the 10-fold cross-validation method to train and evaluate the computational performance of our spoofing machine learning model. We conducted a series of experiments in a numerical simulation environment and evaluated the proposed model against the most advanced traditional machine learning and deep learning models. The results and analysis show that the PCA-CNN-LSTM neural network model achieved the highest accuracy (0.9949). This paper provides a theoretical basis and technical support for spoofing detection for small-UAV GPS signals.
MCST Scheme for UAV Systems over LoRa Networks
Authors: Khun Aung Thura Phyo , Shan Lin , Lim Yuto , Tan Yasuo
Published: June 2023

In recent years, low-power wide-area network (LPWAN) has received widespread popularity with long-range and wide-area communication at low power for the Internet of Things (IoT) systems. Among many vendors of LPWAN, long-range low-power wireless communications, also called LoRa, is one of the competing standards and is well known in both academia and industrial communities as an emerging research area. Among the LoRa applications, unmanned aerial vehicles (UAV) systems are emerging with the benefits of extended battery life and a long communication range. In this paper, we investigate the network capacity with the mixture of concurrent and sequential transmission (MCST) scheme over LoRa networks. From the simulation results, it can be seen that MCST is suitable for implementation in the LoRa network. Specifically, MCST can achieve higher throughput with low transmission latency and energy consumption compared to the existing CSMA approach LoRa MAC. Besides, we also propose a modified MCST over the LoRa (mMCST/LoRa) scheme to mitigate the transmission latency further. The simulation results reveal a better performance in terms of throughput, latency and energy consumption, regardless of the frame payload size and the number of nodes in the network.
UAV-Assisted Traffic Speed Prediction via Gray Relational Analysis and Deep Learning
Authors: Zheng Yanliu , Luo Juan , Qiao Ying , Gao Han
Published: June 2023

Accurate traffic prediction is crucial to alleviating traffic congestion in cities. Existing physical sensor-based traffic data acquisition methods have high transmission costs, serious traffic information redundancy, and large calculation volumes for spatiotemporal data processing, thus making it difficult to ensure accuracy and real-time traffic prediction. With the increasing resolution of UAV imagery, the use of unmanned aerial vehicles (UAV) imagery to obtain traffic information has become a hot spot. Still, analyzing and predicting traffic status after extracting traffic information is neglected. We develop a framework for traffic speed extraction and prediction based on UAV imagery processing, which consists of two parts: a traffic information extraction module based on UAV imagery recognition and a traffic speed prediction module based on deep learning. First, we use deep learning methods to automate the extraction of road information, implement vehicle recognition using convolutional neural networks and calculate the average speed of road sections based on panchromatic and multispectral image matching to construct a traffic prediction dataset. Then, we propose an attention-enhanced traffic speed prediction module that considers the spatiotemporal characteristics of traffic data and increases the weights of key roads by extracting important fine-grained spatiotemporal features twice to improve the prediction accuracy of the target roads. Finally, we validate the effectiveness of the proposed method on real data. Compared with the baseline algorithm, our algorithm achieves the best prediction performance regarding accuracy and stability.
A Robust Scheme for RIS-Assisted UAV Secure Communication in IoT
Authors: Qian Pengzhi , Zhang Yu , Yan Xiaojuan , Chen Yong , Sun Yifu
Published: June 2023

Reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicles (UAV) have been extensively studied on the Internet of Things (IoT) systems to improve communication performance. In this paper, we aimed to counter simultaneous jamming and eavesdropping attacks by jointly designing an active beamforming vector at the base station (BS) and reflect phase shifts at the RIS. Specifically, considering imperfect angular channel state information (CSI), the sum secrecy rate maximization problem in the worst case could be formulated, which is NP-hard and non-convex. To address this problem, we improved the robust enhanced signal-to-leakage-and-noise ratio (E-SLNR) beamforming to reduce the computational complexity and mitigate the impact of interference, eavesdropping and jamming. Furthermore, a genetic algorithm with a tabu search (GA-TS) method was proposed to efficiently obtain an approximate optimal solution. The simulation results demonstrated that the proposed GA-TS method converged faster with better results than conventional GA, while the proposed robust scheme could achieve higher sum secrecy rates than the zero-forcing (ZF) and SLNR schemes.
Using Social Media Camping Data for Evaluating, Quantifying, and Understanding Recreational Ecosystem Services in Post-COVID-19 Megacities: A Case Study from Beijing
Authors: Xu Haiyun , Zhao Guohan , Liu Yan , Miao Meng
Published: June 2023

Recreational ecosystem services (RESs) are the diverse recreational opportunities provided by nature to humans, which contribute to the improvement of public health and social well-being. The use of online social media is an efficient method for quantifying public perceptions of recreational ecosystem services (RESs) delivered by a given landscape. With the continuously changing demand for nature-focused outdoor recreational activities since COVID-19, camping has become the fastest-growing outdoor leisure activity in megacities and a key indicator for how people perceive and value the RESs provided by the landscape. Such unexpected changings triggered by COVID-19 have further led to an imbalance between demand and supply, which results in fierce conflicts in urban green space management. This study presents a spatial pattern analysis of how people perceive RESs in a megacity-scale case study of Beijing using geo-tagged camping notes posted on Little Red Book (LRB). We employed these camping notes in the context of a megacity to (i) map public camping behaviors patterns in urban green spaces, (ii) evaluate spatial clusters of high/low RESs, and (iii) investigate the relationship between RESs, local landscape features, and gender through correspondence analysis. Our results show that considerable spatial clustering of camping behaviors was observed in both suburban and urban green spaces. However, suburbs revealed a substantially higher RES value than central urban areas. In addition, water bodies were discovered to have remarkably low RES, while grassland and urban forests were found to have a close link with higher RES. In addition, significant gender preferences have been discovered, where female visitors prefer to camp in grassland, and male visitors favor bare ground and urbanized regions. Our findings would assist decision-makers in optimizing urban green space planning and management, adapting to fast-changing public camping demands in the context of the post-COVID-19 era. Findings also contribute to the literature by applying spatial analysis of social media data to understand public outdoor recreation activities and perceived value for megacities’ green space management.
Anomaly Detection for Hydraulic Power Units—A Case Study
Authors: Fic Paweł , Czornik Adam , Rosikowski Piotr
Published: June 2023

This article aims to present the real-world implementation of an anomaly detection system of a hydraulic power unit. Implementation involved the Internet of Things approach. A detailed description of the system architecture is provided. The complete path from sensors through PLC and the edge computer to the cloud is presented. Some technical information about hydraulic power units is also given. This article involves the description of several model-at-scale deployment techniques. In addition, the approach to the synthesis of anomaly and novelty detection models was described. Anomaly detection of data acquired from the hydraulic power unit was carried out using two approaches, statistical and black-box, involving the One Class SVM model. The costs of cloud resources and services that were generated in the project are presented. Since the article describes a commercial implementation, the results have been presented as far as the formal and business conditions allow.
Food Allergens of Plant Origin
Authors: Zhang Yuzhu , Che Huilian , Li Caiming , Jin Tengchuan
Published: June 2023

This review presents an update on the physical, chemical, and biological properties of food allergens in plant sources, focusing on the few protein families that contribute to multiple food allergens from different species and protein families recently found to contain food allergens. The structures and structural components of the food allergens in the allergen families may provide further directions for discovering new food allergens. Answers as to what makes some food proteins allergens are still elusive. Factors to be considered in mitigating food allergens include the abundance of the protein in a food, the property of short stretches of the sequence of the protein that may constitute linear IgE binding epitopes, the structural properties of the protein, its stability to heat and digestion, the food matrix the protein is in, and the antimicrobial activity to the microbial flora of the human gastrointestinal tract. Additionally, recent data suggest that widely used techniques for mapping linear IgE binding epitopes need to be improved by incorporating positive controls, and methodologies for mapping conformational IgE binding epitopes need to be developed.
Comparison of Phenolic and Volatile Compounds in MD2 Pineapple Peel and Core
Authors: Nordin Nur , Sulaiman Rabiha , Bakar Jamilah , Noranizan Mohd
Published: June 2023

The peel and core discarded from the processing of MD2 pineapple have the potential to be valorized. This study evaluated the functional and volatile compounds in the extracts of MD pineapple peel and core (MD2-PPC). The total soluble solids, pH, titratable acidity, sweetness index, and astringency index were 9.34 °Brix, 4.00, 0.74%, 12.84, and 0.08, respectively, for the peel and 12.00 °Brix, 3.96, 0.32%, 37.66, and 0.03, respectively, for the core. The fat and protein contents of the peel and core were found to be significantly different (p < 0.05). The total phenolic (TPC) and flavonoid contents (TFC) were significantly higher in the peel. The peel also showed better antioxidant activity, with a half-maximal inhibitory concentration (IC50) of 0.63 mg/mL for DPPH free radical activity compared with the core. The TPC of different phenolic fractions from peel extract was highest in the glycosylated fraction, followed by the esterified, insoluble-bound, and free phenolic fractions. GC–MS analysis identified 38 compounds in the peel and 23 in the core. The primary volatile compounds were 2-furan carboxaldehyde, 5-(hydroxymethyl), and 2,3-dihydro-3,5-dihydroxy-6-methyl-4H-pyran-4-one (DDMP). The identification of phenolics and volatile compounds provides important insights into the valorization of (MD2-PPC) waste.
Proteins and Minerals in Whey Protein Supplements
Authors: González-Weller Dailos , Paz-Montelongo Soraya , Bethencourt-Barbuzano Elena , Niebla-Canelo Daniel , Alejandro-Vega Samuel , Gutiérrez Ángel J. , Hardisson Arturo , Carrascosa Conrado , Rubio Carmen
Published: June 2023

Sports nutrition supplementation is a widespread practice. Whey protein supplements contribute not only to protein intake but also to dietary exposure to minerals. The labelling present provides the percentage of protein and rarely refers to other components, such as potentially toxic elements such as B, Cu, Mo, Zn, and V that present tolerable upper intake levels set by the European Food Safety Authority. The percentage of protein declared on supplement labelling was checked using the Kjeldahl method, and the levels of Ca, Mg, K, Na, Ba, B, Co, Cu, Cr, Sr, Fe, Li, Mn, Mo, Ni, V, Zn, and Al were analyzed by ICP-OES with the aim of characterizing the protein and mineral contents of isolate and concentrate whey protein supplements representative of the European market. The protein content was 70.9% (18–92.3%) and statistically significant differences were observed between the declared and real protein percentages. Among the minerals, K (4689.10 mg/kg) and Ca (3811.27 mg/kg) presented the highest levels, whereas Co (0.07 mg/kg) and V (0.04 mg/kg) showed the lowest levels. It was concluded that the quality and safety of these products needs to be monitored and regulated. A high degree of non-compliance with labelling claims was detected. Furthermore, the contributions to the recommended and tolerable intakes among regular consumers need to be assessed.
Serotypes, Antimicrobial Resistance Profiles, and Virulence Factors of Salmonella Isolates in Chinese Edible Frogs (Hoplobatrachus rugulosus) Collected from Wet Markets in Hong Kong
Authors: Boss Sara , Stephan Roger , Horlbog Jule Anna , Magouras Ioannis , Colon Violaine Albane , Lugsomya Kittitat , Stevens Marc J. A. , Nüesch-Inderbinen Magdalena
Published: June 2023

Salmonella is an important agent of gastrointestinal disease in humans. While livestock, such as cattle, poultry, and pigs, are well-recognised animal reservoirs of Salmonella, there is a lack of data on Salmonella in edible frogs, even though frog meat is a popular food worldwide. In this study, 103 live edible Chinese frogs (Hoplobatrachus rugulosus) were collected from wet markets throughout Hong Kong. After euthanasia, faeces or cloacal swabs were examined for Salmonella. Overall, Salmonella spp. were isolated from 67 (65%, CI: 0.554–0.736) of the samples. The serotypes included S. Saintpaul (33%), S. Newport (24%), S. Bareilly (7%), S. Braenderup (4%), S. Hvittingfoss (4%), S. Stanley (10%), and S. Wandsworth (16%). Many isolates were phylogenetically related. A high number of genes encoding for resistance to clinically relevant antimicrobials, and a high number of virulence determinants, were identified. Antimicrobial susceptibility testing (AST) identified multidrug resistance (MDR) in 21% of the isolates. Resistance to ampicillin, ciprofloxacin, nalidixic acid, and tetracycline was common. These results demonstrate that a high percentage of live frogs sold for human consumption in wet markets are carriers of multidrug-resistant Salmonella. Public health recommendations for handling edible frogs should be considered, to mitigate the risk of Salmonella transmission to humans.
The Effects of Synbiotics on Dextran-Sodium-Sulfate-Induced Acute Colitis: The Impact of Chitosan Oligosaccharides on Endogenous/Exogenous Lactiplantibacillus plantarum
Authors: Zhao Yunjiao , Xue Liangyu , Li Shunqin , Wu Tao , Liu Rui , Sui Wenjie , Zhang Min
Published: June 2023

In this work, Lactiplantibacillus plantarum (L. plantarum) isolated from mice feces (LP-M) and pickles (LP-P) were chosen as the endogenous and exogenous L. plantarum, respectively, which were separately combined with chitosan oligosaccharides (COS) to be synbiotics. The anti-inflammatory activity of LP-M, LP-P, COS, and the synbiotics was explored using dextran-sodium-sulfate (DSS)-induced acute colitis mice, as well as by comparing the synergistic effects of COS with LP-M or LP-P. The results revealed that L. plantarum, COS, and the synbiotics alleviated the symptoms of mice colitis and inhibited the changes in short-chain fatty acids (SCFAs), tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, IL-6, IL-10, and myeloperoxidase (MPO) caused by DSS. In addition, the intervention of L. plantarum, COS, and the synbiotics increased the relative abundance of beneficial bacteria Muribaculaceae and Lactobacillus and suppressed the pathogenic bacteria Turicibacter and Escherichia-Shigella. There was no statistically difference between LP-M and the endogenous synbiotics on intestinal immunity and metabolism. However, the exogenous synbiotics improved SCFAs, inhibited the changes in cytokines and MPO activity, and restored the gut microbiota more effectively than exogenous L. plantarum LP-P. This indicated that the anti-inflammatory activity of exogenous LP-P can be increased by combining it with COS as a synbiotic.
Local Error Estimate of an L1-Finite Difference Scheme for the Multiterm Two-Dimensional Time-Fractional Reaction–Diffusion Equation with Robin Boundary Conditions
Authors: Hou Jian , Meng Xiangyun , Wang Jingjia , Han Yongsheng , Yu Yongguang
Published: June 2023

In this paper, the numerical method for a multiterm time-fractional reaction–diffusion equation with classical Robin boundary conditions is considered. The full discrete scheme is constructed with the L1-finite difference method, which entails using the L1 scheme on graded meshes for the temporal discretisation of each Caputo fractional derivative and using the finite difference method on uniform meshes for spatial discretisation. By dealing with the discretisation of Robin boundary conditions carefully, sharp error analysis at each time level is proven. Additionally, numerical results that can confirm the sharpness of the error estimates are presented.
Efficient and Specific Generation of MSTN-Edited Hu Sheep Using C-CRISPR
Authors: Guo Rihong , Wang Huili , Meng Chunhua , Gui Hongbing , Li Yinxia , Chen Fang , Zhang Chenjian , Zhang Han , Ding Qiang , Zhang Jianli , Zhang Jun , Qian Yong , Zhong Jifeng , Cao Shaoxian
Published: June 2023

Hu sheep, an indigenous breed in China known for its high fecundity, are being studied to improve their growth and carcass traits. MSTN is a negative regulator of muscle development, and its inactivation results in muscularity. The C-CRISPR system, utilizing multiple neighboring sgRNAs targeting a key exon, has been successfully used to generate genes for complete knockout (KO) monkeys and mice in one step. In this study, the C-CRISPR system was used to generate MSTN-edited Hu sheep; 70 embryos injected with Cas9 mRNA and four sgRNAs targeting exon 3 of sheep MSTN were transferred to 13 recipients. Out of 10 lambs born from five recipients after full-term pregnancies, nine had complete MSTN KO with various mutations. No off-target effects were found. These MSTN-KO Hu sheep showed a double-muscled (DM) phenotype, characterized by a higher body weight at 3 and 4 months old, prominent muscular protrusion, clearly visible intermuscular groves, and muscle hypertrophy. The molecular analysis indicated enhanced AKT and suppressed ERK1/2 signaling in the gluteus muscle of the edited Hu sheep. In conclusion, MSTN complete KO Hu sheep with a DM phenotype were efficiently and specifically generated using C-CRISPR, and the C-CRISPR method is a promising tool for farm animal breeding.
Case Report—An Inherited Loss-of-Function NRXN3 Variant Potentially Causes a Neurodevelopmental Disorder with Autism Consistent with Previously Described 14q24.3-31.1 Deletions
Authors: Feichtinger René G. , Preisel Martin , Brugger Karin , Wortmann Saskia B. , Mayr Johannes A.
Published: June 2023

Background: Heterozygous, large-scale deletions at 14q24.3-31.1 affecting the neurexin-3 gene have been associated with neurodevelopmental disorders such as autism. Both “de novo” occurrences and inheritance from a healthy parent suggest incomplete penetrance and expressivity, especially in autism spectrum disorder. NRXN3 encodes neurexin-3, a neuronal cell surface protein involved in cell recognition and adhesion, as well as mediating intracellular signaling. NRXN3 is expressed in two distinct isoforms (alpha and beta) generated by alternative promoters and splicing. MM/Results: Using exome sequencing, we identified a monoallelic frameshift variant c.159_160del (p.Gln54AlafsTer50) in the NRXN3 beta isoform (NM_001272020.2) in a 5-year-old girl with developmental delay, autism spectrum disorder, and behavioral issues. This variant was inherited from her mother, who did not have any medical complaints. Discussion: This is the first detailed report of a loss-of-function variant in NRXN3 causing an identical phenotype, as reported for heterozygous large-scale deletions in the same genomic region, thereby confirming NRXN3 as a novel gene for neurodevelopmental disorders with autism.
Identification of MicroRNA Expression Profiles Related to the Aggressiveness of Salivary Gland Adenoid Cystic Carcinomas
Authors: Zanon Maicon Fernando , Scapulatempo-Neto Cristovam , Gama Ricardo Ribeiro , Marques Márcia Maria Chiquitelli , Reis Rui Manuel , Evangelista Adriane Feijó
Published: June 2023

Adenoid cystic carcinoma (ACC) has been reported as the second most common carcinoma of the salivary glands. Few studies have associated miRNA expression with ACC aggressiveness. In this study, we evaluated the miRNA profile of formalin-fixed, paraffin-embedded (FFPE) samples of salivary gland ACC patients using the NanoString platform. We studied the miRNA expression levels associated with the solid growth pattern, the more aggressive histologic feature of ACCs, compared with the tubular and cribriform growth patterns. Moreover, the perineural invasion status, a common clinicopathological feature of the disease that is frequently associated with the clinical progression of ACC, was investigated. The miRNAs showing significant differences between the study groups were selected for target prediction and functional enrichment, which included associations with the disease according to dedicated databases. We observed decreased expression of miR-181d, miR-23b, miR-455, miR-154-5p, and miR-409 in the solid growth pattern compared with tubular and cribriform growth patterns. In contrast, miR-29c, miR-140, miR-195, miR-24, miR-143, and miR-21 were overexpressed in patients with perineural invasion. Several target genes of the miRNAs identified have been associated with molecular processes involved in cell proliferation, apoptosis, and tumor progression. Together, these findings allowed the characterization of miRNAs potentially associated with aggressiveness in salivary gland adenoid cystic carcinoma. Our results highlight important new miRNA expression profiles involved in ACC carcinogenesis that could be associated with the aggressive behavior of this tumor type.
Associations between Physical Activity and Health-Related Quality of Life among Community-Dwelling Older Adults: A Cross-Sectional Study in Urban Greece
Authors: Psarrou Anna , Adamakidou Theodoula , Apostolara Paraskevi , Koreli Alexandra , Drakopoulou Marianna , Plakas Sotirios , Mastrogiannis Dimos , Mantoudi Alexandra , Parissopoulos Stelios , Zartaloudi Afroditi , Mantzorou Marianna
Published: June 2023

Physical activity is an important factor in achieving healthy aging, offering older persons multiple benefits in terms of maintaining and improving their health and wellbeing. The aim of this study was to investigate the effect of physical activity on the quality of life of older adults. A cross-sectional study was conducted from February to May 2022, using the Short-Form Health Survey (SF-36) and the International Physical Activity Questionnaire (IPAQ). A total of 124 people aged 65 and over participated in the survey. The average age of the participants was 71.6 years, and 62.1% were women. Participants showed a moderate quality of life with regard to the physical health dimension (mean score 52.4) and a higher quality of life with regard to the mental health dimension (mean score 63.1) compared to the expected values of the population. Low levels of physical activity were recorded among older adults, reaching a rate of 83.9%. A moderate or high level of physical activity has been found to contribute to a better physical functioning (p = 0.03), vitality (p = 0.02) and general health (p = 0.01). Finally, comorbidity had a negative impact on physical activity (p = 0.03) and quality of life regarding mental and physical health in older adults. The study showed very low levels of physical activity in older Greek adults. The management of this problem, which was intensified during the COVID-19 pandemic, should be a high priority in public health programs focusing on healthy aging, as physical activity affects and promotes many of the basic aspects of quality of life.
Impact of Medical Specialties on Diagnostic and Therapeutic Management of Elderly Cancer Patients
Authors: Lafaie Ludovic , Chanelière-Sauvant Anne-Françoise , Magné Nicolas , Bouleftour Wafa , Tinquaut Fabien , Célarier Thomas , Bertoletti Laurent
Published: June 2023

The management (diagnostic and therapeutic) of cancer in the geriatric population involves a number of complex difficulties. The aim of this study was to assess the impact of a medical specialty on the diagnostic and therapeutic management of elderly cancer patients. Four clinical scenarios of cancer in the geriatric population, with a dedicated survey to gather information regarding each clinical case’s diagnostic and therapeutic approaches, as well as the different criteria influencing physicians’ therapeutic decisions, were exposed to geriatricians, oncologists, and radiotherapists in Saint-Etienne. The surveys were filled out by 13 geriatricians, 11 oncologists, and 7 radiotherapists. There was a homogeneity of responses regarding the confirmation of cancer diagnostics in the elderly. There were strong disparities (inter- and intra-specialties) for several clinical situations regarding the therapeutic management of cancer. There were significant disparities in terms of surgical management, the implementation of a chemotherapy protocol, and the adaptation of the chemotherapy dosage. Contrary to oncologists, who primarily consider the G8 and the Karnofsky score, geriatric autonomy scores and frailty with cognitive assessment were the key factors determining diagnostic/therapeutic therapy for geriatricians. These results raise important ethical questions, requiring specific studies in geriatric populations to provide the homogenous management of elderly patients with cancer.
Contribution of Different Brain Disorders and Multimorbidity to Delirium Superimposed Dementia (DSD)
Authors: Wetterling Tilman , Junghanns Klaus
Published: June 2023

Delirium, an acute neuropsychiatric disorder characterized by a disturbance of attention and awareness, is often superimposed on dementia with its progressive cognitive decline. Despite the high frequency and clinical relevance of this condition, often called delirium-superimposed dementia (DSD), little is known about possible triggers. In this study using the GePsy-B databank, we investigated the impact of the underlying brain disorder and multimorbidity (MM) on DSD. MM was measured by CIRS and the number of ICD-10 diagnoses. Dementia was diagnosed by CDR, and delirium by DSM IV TR criteria. A total of 218 patients were diagnosed with DSD and these were compared to 105 patients with only dementia, 46 with only delirium, and 197 patients suffering from other psychiatric diseases, mainly depression. No significant differences between groups were found concerning CIRS scores. Based on CT scans, DSD cases were grouped into those with cerebral atrophy only (probably pure neurodegenerative), with brain infarction, or with white matter hyperintensities (WMH), but no between-group differences regarding the MM indices could be found. Regression analysis only revealed age and dementia stage as influencing factors. Conclusion: Our results suggest that neither MM nor morphologic changes in the brain are predisposing factors for DSD.
Factors Influencing Infection Anxiety in Korean Male Firefighters Due to COVID-19 Infection Status
Authors: Han Seung-Woo , Jung Hyun-Ok
Published: June 2023

This paper describes descriptive research to identify the effects of job stress, COVID-19 self-care behavior, and COVID-19 vaccination status according to the infection and non-infection of COVID-19 on anxiety about the COVID-19 infection among firefighters in South Korea. Data from 205 firefighters working at 10 fire stations were collected from 26 January to 16 February 2023. The variables used were job stress, COVID-19 self-care behavior, COVID-19 vaccination status, and COVID-19 infection anxiety. The collected data were analyzed using descriptive statistics, t-test, one-way ANOVA, Pearson’s correlation coefficient, and multiple linear regression. In subjects who were infected with COVID-19, the factors that significantly affected infection anxiety were job stress (β = 0.247, p = 0.011) and self-care behavior (β = 0.343, p = 0.011). In subjects who were not infected with COVID-19, the factors that significantly affected infection anxiety were marriage status (unmarried) (β = −0.260, p = 0.005) and self-care behavior (β = 0.374, p = 0.001). These results demonstrate that the infection anxiety of firefighters should be prevented, and their physical and mental health should be promoted by considering job stress, self-care behavior, and personal environment.
Demographic, Psychosocial, and Lifestyle-Related Characteristics of Forest Therapy Participants in Italy: A Multicenter Cross-Sectional Survey
Authors: Antonelli Michele , Donelli Davide , Maggini Valentina , Gallo Eugenia , Mascherini Vittorio , Firenzuoli Fabio , Gavazzi Gioele , Zabini Federica , Venturelli Emanuela , Margheritini Giovanni , Bassi Ivana , Iseppi Luca , Meneguzzo Francesco
Published: June 2023

This research aims to provide a comprehensive overview of the key demographic, psychosocial, and lifestyle-related characteristics of forest therapy participants in Italy. A survey was conducted among 1070 adults who had engaged in standardized forest therapy experiences between June 2021 and October 2022. The findings indicate that most forest therapy participants in Italy share certain distinctive traits. They are primarily female, aged between 45 and 54 years, employed, and unmarried. Moreover, they possess a high level of education, predominantly reside in urban areas, demonstrate a strong environmental awareness, maintain a nature-oriented attitude, and typically exhibit moderate levels of trait anxiety. Additionally, they tend to be nonsmokers, possess a healthy BMI within the normal range, and consume an adequate quantity of fruits and vegetables on a daily basis. However, it should be noted that their male counterparts tend to be overweight and exhibit poorer dietary habits. Irrespective of gender, approximately 40% of forest therapy participants in Italy live with a chronic disease that requires daily medicinal treatment. Subsequent research should investigate whether these characteristics hold true in different countries. Furthermore, exploring the potential effectiveness of health-promoting interventions integrated with forest therapy sessions could prove beneficial in addressing these specific issues among forest therapy participants. By doing so, such interventions have the potential to contribute significantly to public health promotion and overall community well-being.
Clinical Features and Treatment Outcomes of COVID-19 Admissions in the Can Tho City Hospital of Tuberculosis and Respiratory Diseases, Vietnam: A Hospital-Based Observational Study
Authors: Tran Hung Do , Hung Tran Thanh , Thuy Phuong Tran Hoang , Tam Le Thanh , Tran Hung Gia , Le Phuoc Huu
Published: June 2023

Background: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, is among the top global health crises. As confirmed by the Vietnam Ministry of Health on 25th January 2023, Vietnam had a cumulative total of more than 11.52 million COVID-19 patients, including 10.61 million recoveries and 43,186 deaths. Objectives: This study aimed to describe the clinical and subclinical characteristics, treatment progress, and outcomes of 310 cases of SARS-CoV-2 infection. Methods: A total of 310 patients with medical records of SARS-CoV-2 were admitted to Can Tho City Hospital of Tuberculosis and Lung Diseases, Can Tho city, Vietnam, between July 2021 and December 2021. Demographic and clinical data, including laboratory examinations, of all the patients were collected and analyzed. Results: The median duration of hospital stay was 16.4 ± 5.3 days. There were 243 (78.4%) patients with clinical symptoms of COVID-19 and 67 (21.6%) patients without clinical symptoms. The common symptoms included cough (71.6% of 310 patients), fever (35.4%), shortness of breath (22.6%), sore throat (21.4%), loss of smell/taste (15.6%), and diarrhea (14.4%). Regarding treatment outcomes, 92.3% of the patients were discharged from the hospital, 1.9% of the patients suffered a more severe illness and were transferred to a higher-level hospital, and 5.8% of the patients died. The RT-PCR results were negative in 55.2% of the patients, and 37.1% of the patients had positive RT-PCR results with Ct values of >30 on the discharge/transfer day. Multivariate logistic regression analyses showed that comorbidity and decreased blood pH were statistically significantly related to the treatment outcomes of the patients with COVID-19 (p < 0.05). Conclusions: This study provides useful information (i.e., the clinical characteristics and treatment outcomes) on the COVID-19 pandemic in Vietnam during its biggest outbreak; the information may be used for reference and for making improvements in the handling of future health crises.
Driving Rehabilitation for Stroke Patients: A Systematic Review with Meta-Analysis
Authors: Hwang Sujin , Song Chiang-Soon
Published: June 2023

Driving enables stroke survivors to freely participate in social integration. The purpose of this review was to summarize the evidence for the therapeutic effects of driving rehabilitation for patients when they return to driving after stroke and evaluate the predictors of returning to driving to identify the factors impacting their driving rehabilitation. This study employed a systematic review and meta-analysis. PubMed and four other databases were searched until 31 December 2022. Our review included randomized controlled trials (RCT) and non-RCTs that investigated driving rehabilitation for stroke and observational studies. A total of 16 studies (two non-RCT and 14 non-RCT) were reviewed; two RCTs investigated the effect of driving rehabilitation with a simulator system, and eight and six non-RCTS evaluated the predictive factors of driving return post-stroke and compared the effects of driving rehabilitation for stroke, respectively. The National Institute of Health Stroke Scale (NIHSS) and Mini Mental State Examination (MMSE) scores and having paid employment were significant predictors of resuming driving after stroke. The results suggest that NIHSS, MMSE, and paid employment are predictors of returning to driving post-stroke. Future research should investigate the effect of driving rehabilitation on the resumption of driving in patients with stroke.