bluuebunny/crossref_metadata_2025 huggingface dataset:
Functional Foods, Gut Microbiome and Association with Obesity and Metabolic Syndrome: A Literature Review
Authors: Koumpouli Despoina , Koumpouli Varvara , Koutelidakis Antonios E.
Published: June 2024

The human gastrointestinal gut consists of about 100 trillion microorganisms, including up to 5000 different types of bacteria, as well as Archaea, Eukarya, parasites, viruses and bacteriophages that together are called the “gut microbiome”. Changes in gut microorganism composition (dysbiosis) can cause various diseases. The present study aims to investigate if diet, and more specifically, functional foods have an impact on the intestinal microbiome, and whether the intestinal microbiome has an influence on metabolic syndrome (MetS) and obesity. This systematic review was accomplished according to PRISMA guidelines, mostly using the key words functional foods, microbiome, obesity, MetS, and Mediterranean diet. The search focused on recent scientific articles from the Pubmed, Scopus, and Google Scholar databases. Most of the studies discussed showed a potential therapeutic effect of the Mediterranean diet, which is rich in beneficial nutrients, on body weight and fat deposition, through reshaping of the gut microbiome’s synthesis. This literature review showed a possible relationship between microflora metabolites, endotoxemia, obesity and MetS. The role of probiotics, prebiotics, and polyphenols in the prevention of obesity and MetS is of high importance in promoting healthy aging. The future challenge is to comprehend how different dietary patterns could regulate the gut microflora’s composition and whether these changes could be long term.
Breathable Cities: Dynamic Machine Learning Modelling Approaches for Advanced Air Pollution Control
Authors: Zayed Roba , Abbod Maysam
Published: June 2024

This paper discusses air quality index (AQI) representation using a fuzzy logic framework to cover the blurry areas of AQI where indices are in between ranges of values. After studying several standards for air quality prediction (AQP), this research suggested the use of fuzzy logic as an extended method to cover some limitations found in several standards, in which the fuzzy logic represents a more dynamic way to support cross-country comparisons as well. This research expanded upon the United States Environmental Protection Agency (USEPA) standards to address their acknowledged limitations by constructing a fuzzy air quality levels prediction (FAQLP) model, which categorizes air quality into corresponding ranges (actual levels) and classifies new fuzzy levels (predicted levels), using a fuzzy logic model (to enforce more realistic predictions). This model can solve the issue of values at or near boundaries when there is uncertainty about air quality levels. The study aims to incorporate a comparative study of two urban settings providing dynamic machine-learning modeling approaches for advanced air pollution control. The DNN–Markov model is presented in this paper as the selected hybrid model for AQI prediction, and the adaptive neuro-fuzzy inference system (ANFIS) was used to represent AQI. This work presents a novel air quality index framework that consists of a DNN–Markov model for accurate hourly predictions and air quality level representations using ANFIS.
New Technologies and Applications of Edge/Fog Computing Based on Artificial Intelligence and Machine Learning
Authors: Park Ji Su
Published: June 2024

Multi-access edge computing (MEC) is an emerging computing architecture that enhances and extends traditional mobile cloud computing [...]
Emotional Temperature for the Evaluation of Speech in Patients with Alzheimer’s Disease through an Automatic Interviewer
Authors: Alonso-Hernández Jesús B. , Barragán-Pulido María Luisa , Santana-Luis Aitor , Ferrer-Ballester Miguel Ángel
Published: June 2024

In the context of the detection and evolutionary control of Alzheimer’s disease from voice recordings and their automatic processing, this work aims to objectively determine the discriminatory capacity of a set of voice features linked to the emotional load of speech. We use descriptive statistics derived from the concept of emotional temperature as quantifiable characteristics of the voice. We apply a series of parametric and nonparametric analyses to the set of features, both individually and collectively, and explore their potential in relation to the use of different methods of unsupervised classification. With the aim of comparing how the type of interviewer used in the sample collection (i.e., voice recordings) influences the discrimination of AD through emotional speech analysis, we used the CSAP-19 database, which includes voice samples obtained through human interviewer (spontaneous speech samples) and automatic interviewer (induced speech samples) for the three defined populations (HC, mild AD, and moderate AD). In this regard, a comparative analysis is also conducted on the potential of emotional temperature features defined according to the sample collection process (manual or automatic interview process).
Vibration Signal Classification Using Stochastic Configuration Networks Ensemble
Authors: Wang Qinxia , Liu Dandan , Tian Hao , Qin Yongpeng , Zhao Difei
Published: June 2024

For vibration signals, this paper proposes an ensemble classification method based on stochastic configuration networks (SCNs). Firstly, the time–frequency analysis methods are used to obtain the frequency spectrum signal and time–frequency images. The sample data in the frequency domain and the time–frequency domain can characterize fault information from different perspectives. The hybrid data that consist of the sample data from the two domains are used to build a SCN model. Moreover, a SCNs ensemble method is proposed to solve the fault classification problem, and the sub-classifiers are built to extract fault features from different training data. In the experiment, the bearing and gear fault datasets are used for performance comparison. The experimental results show that the proposed SCNs ensemble model obtains good classification results, and compared with the deep learning methods, the SCN modeling process is more simple and effective for industrial data classification.
Validation of Frontal Crashworthiness Simulation for Low-Entry Type Bus Body According to UNECE R29 Requirements
Authors: Holenko Kostyantyn , Dykha Oleksandr , Koda Eugeniusz , Kernytskyy Ivan , Royko Yuriy , Horbay Orest , Berezovetska Oksana , Rys Vasyl , Humenuyk Ruslan , Berezovetskyi Serhii , Żółtowski Mariusz , Markiewicz Anna , Wierzbicki Tomasz
Published: June 2024

Frontal crash tests are an essential element in assessing vehicle safety. They simulate a collision that occurs when the front of the bus hits another vehicle or an obstacle. In recent years, much attention has been paid to the frontal crash testing of city buses, especially after a series of accidents resulting in deaths and injuries. Unlike car manufacturers, most bus bodybuilders do not include deformation zones in their designs. The next two regulations are widely used to assess whether a structure can withstand impact loading: UNECE Regulation No. 29—United Nations Economic Commission for Europe (UNECE R29) and the New Car Assessment Program (NCAP), which is more typical of car crash tests. The main goal of the research is to develop an applicable methodology for a frontal impact simulation on a city bus, considering UNECE R29 requirements for the passenger’s safety and distinctive features of the low-entry body layout. Among the contributions to current knowledge are such research results as: unlike suburban and intercity buses, city buses are characterized by lower stiffness in the event of a frontal collision, and therefore, when developing new models, it is necessary to lay deformation zones (currently absent from most city buses). Maximum deformation values in the bus front part are reached earlier for R29 (137 ms) than for most impacts tested by NCAP (170–230 ms) but have higher values: 577 mm vs. 150–250 mm for the sills tested. Such a short shock absorption time and high deformations indicate a significantly lighter front part of a low-entry and low-floor bus compared with classic layouts. Furthermore, it is unjustified to use the R29 boundary conditions of trucks to attach the bus with chains behind its frontal axe both in natural tests and appropriate finite element simulation—the scheme of fixing the city bus should be accordingly adapted and normatively revised.
Research on Key Technologies of Data Processing Mechanisms in Ternary Optical Computer
Authors: Li Shuang , Liao Shanchuan , Li Wenjing , Li Luqun , Li Dazhi
Published: June 2024

This paper introduces an arithmetic data file, a key technology for data processing in a ternary optical computer (TOC). The physical form of the ternary optical processor and its data processing characteristics are analyzed. Based on this analysis, the compution-data is constructed, and research is carried out on the format of the compution-data, its generation method, and the expansion of high-level languages transmitted to the ternary optical processor. The calculation rules and the raw data for the ternary optical computer are organized into a file that conforms to the calculation characteristics of the computer. A data processing mechanism based on the compution-data is proposed. Finally, an experimental test was conducted on the platform of a ternary optical computer using specific examples. The results showed that by organizing and transmitting data through the compution-data, the ternary optical computer could fully utilize its computational advantages in data processing while shielding the underlying complex hardware processing. This makes it convenient for users to apply this new type of computer. This data processing mechanism can offer a novel perspective for other heterogeneous systems in data processing.
Skin Lesion Classification Using a Deep Ensemble Model
Authors: Thwin Su Myat , Park Hyun-Seok
Published: June 2024

Skin cancer, particularly melanoma, is a severe health threat that necessitates early detection for effective treatment. This research introduces a skin lesion classification system that harnesses the capabilities of three advanced deep learning models: VGG16, Inception-V3, and ResNet-50. By integrating these models into an ensemble, the system leverages their individual strengths to improve classification accuracy and robustness. Every model in the ensemble brings its distinctive contribution, having undergone pre-training on ImageNet and subsequent fine-tuning using dermoscopic images. We evaluated our ensemble approach using the ISIC 2018 dataset, a standard benchmark for skin lesion classification. By employing a weighted averaging method to merge predictions from the three models, our ensemble model demonstrated superior performance. The results show an improvement in classification accuracy, achieving an accuracy of 91% on the original dataset and 97% on the dataset balanced by oversampling compared to the individual models. This system was then evaluated using the HAM10000 dataset. The results using the HAM10000 dataset show an improvement in classification accuracy, achieving an accuracy of 90% on the original dataset and 96% on the dataset balanced by oversampling compared to the individual models. This enhanced performance highlights the effectiveness of our ensemble method in capturing diverse features of skin lesions, leading to more accurate diagnoses. Our findings suggest that this approach can significantly assist dermatologists in early and precise skin cancer detection, potentially improving patient outcomes.
Prediction and Optimization of Open-Pit Mine Blasting Based on Intelligent Algorithms
Authors: Guo Jiang , Zhao Zekun , Zhao Peidong , Chen Jingjing
Published: June 2024

Blasting prediction and parameter optimization can effectively improve blasting effectiveness and control production energy consumption. However, the presence of multiple factors and diverse effects in open-pit blasting increases the difficulty of effective prediction and optimization. Therefore, this study takes blasting fragmentation as the prediction indicator and proposes a hybrid intelligent model based on multiple parameters. The model employs a least squares support vector machine (LSSVM) optimized by a genetic algorithm (GA) for prediction. Additionally, the performance of GA-LSSVM was compared with LSSVM optimized by rime optimization algorithms (RIME-LSSVM) and by particle swarm optimization algorithms (PSO-LSSVM), unoptimized LSSVM, and the Kuz–Ram empirical model. Furthermore, considering both blasting fragmentation and blasting cost, a multi-objective particle swarm optimization (MOPSO) algorithm was used for blasting parameter optimization, followed by field validation. The results indicated that the GA-LSSVM model provided the best prediction of blasting fragmentation, achieving optimal evaluation metrics: a root mean square error (RMSE) of 1.947, a mean absolute error (MAE) of 1.688, and a correlation coefficient (r) of 0.962. Moreover, the MOPSO optimization model yielded the optimal blasting parameter combination: a burden of 5.5 m, spacing of 4.3 m, specific charge of 0.51 kg/m3, and subdrilling of 2.0 m. Field blasting tests confirmed the reliability of these parameters. This study can provide scientific recommendations for open-pit mine blasting design and cost control.
Palatal Graft Harvesting Site Healing and Pain Management: What Is the Best Choice? An Umbrella Review
Authors: D’Ambrosio Francesco , Caggiano Mario , Chiacchio Andrea , Acerra Alfonso , Giordano Francesco
Published: June 2024

The use of free gingival graft (FGG) and connective tissue graft (CTG) from the palate are among the most predictable periodontal and peri-implant plastic surgery procedures. However, palatal harvesting causes severe discomfort in the palatal area in patients undergoing harvesting. The aim of this umbrella review is to evaluate which products or techniques can result in fewer side effects and less morbidity in patients. Systematic reviews, with meta-analysis or not, about postoperative pain and wound healing in patients undergoing surgery to remove a free gingival graft or connective tissue graft from the palatal region, published only in the English language, were electronically searched for on BioMed Central, Scopus, MEDLINE/PubMed, the Cochrane library databases, and PROSPERO register. Of 1153 titles, only 7 articles were included in this review. The reviews included suggest that the more effective interventions for patient-reported outcomes, particularly for pain management, are cyanoacrylate adhesives, platelet-rich fibrin, hyaluronic acid, and the use of palatal stents. Low-level laser therapy also demonstrated good results in palatal wound healing speed after FGG procedures. Also, topical agents were also described. Future studies and more high-quality randomized clinical trials are needed to provide clear descriptions and standardized procedures of interventions to obtain clear results.
Foam-Mat Freeze Drying of Kiwiberry (Actinidia arguta) Pulp: Drying Kinetics, Main Properties and Microstructure
Authors: Bogusz Radosław , Nowacka Małgorzata , Rybak Katarzyna , Witrowa-Rajchert Dorota , Gondek Ewa
Published: June 2024

The kiwiberry is an interesting source of bioactive compounds (micronutrients, polyphenols vitamins and pectins) and enzyme actinidine but has limited durability. The aim of this study was to determine the impact of shelf temperature (10 °C, 25 °C and 40 °C) during freeze drying on the foam-mat kiwiberry pulp drying process and the quality of the obtained material based on analyses such as moisture content, water activity, hygroscopicity, solubility, microstructure and spectral measurement using the FTIR method. The use of higher shelf temperatures during freeze drying positively influenced the drying process, reducing its duration by up to 40.7%. The shelf temperature caused changes in the dry matter content (97.2–99.6%), water activity (0.159–0.221), structure and hygroscopic properties (1.41–4.41 g water/100 g d.m.) of the kiwiberry foam mats. Foam-mat drying at 40 °C exhibited a significantly lower water activity, total porosity and hygroscopicity, providing properties favorable for good microbiological and functional stability during storage. Furthermore, this temperature applied during freeze drying resulted in an increase in the solubility of the obtained material, which indicates its possible use in the matrix of other food products.
Trace Extraction and Repair of the F Layer from Pictorial Ionograms
Authors: Wang Jiayi , Qiao Lei , Yan Chunxiao , Qiu Zhaoyang , Wang Kejie
Published: June 2024

Publicly available ionograms are often in the form of pictures. This paper proposes a novel algorithm for extracting and repairing the F layer traces from pictorial ionograms. Extensive efforts have been invested in ionogram autoscaling and critical parameter identification to improve the efficiency of scaling algorithms. To obtain the parameters of the F layer automatically, it is necessary to accurately extract the F layer trace. However, research on F layer trace extraction with repair is relatively limited. The method employed in this study makes full use of the characteristics of different types of echoes on the ionograms, and the procedure includes noise preprocessing, coupling noise processing, and trace repair. To enhance the applicability of the repair, two different automatic filling algorithms are adopted to repair the F layer trace. The aim of this paper is to present an adaptive algorithm to automatically extract and repair F layer traces from different pictorial ionograms. The results of Hainan Fuke ionograms illustrate the reliability of the F layer trace extraction and trace repair.
Short-Term Exposure to Ambient Air Pollution and Schizophrenia Hospitalization: A Case-Crossover Study in Jingmen, China
Authors: Zhou Yuwei , Yang Jixing , Zhang Jingjing , Wang Yixiang , Shen Jiajun , Zhang Yalin , Tan Yuxi , Zhang Yunquan , Hu Chengyang
Published: June 2024

The impact of short-term exposure to air pollutants on the morbidity of schizophrenia, particularly in low- and middle-income countries, remains inadequately explored. The objective of this research was to investigate the relationship between short-term exposure to ambient air pollutants and the risk of schizophrenia hospitalization in Jingmen, China. We performed a time-stratified case-crossover study using daily records of hospital admissions due to schizophrenia in Jingmen Mental Health Center from 2015 to 2017. Environmental exposures to air pollutants and meteorological conditions on case and control days were estimated on the basis of measurements from ground monitoring stations. To investigate the relationship between short-term exposure to ambient air pollutants and the risk of hospitalization for schizophrenia, a conditional logistic regression model was employed. We performed subgroup analyses stratified according to sex, age groups, and season. In total, 4079 schizophrenia hospitalizations were recorded during the designated period. Increased risk of schizophrenia was merely associated with short-term exposure to SO2 and NO2. The estimated odds per interquartile range (IQR) increase in exposure was 1.112 (95% confidence interval (CI): 1.033, 1.196) for SO2 (IQR = 12 µg/m3) and 1.112 (95% CI: 1.033, 1.197) for NO2 (IQR = 18 µg/m3) on lag-0 day. Greater air pollution-schizophrenia associations were observed among middle-aged and older adults (over 45 years of age) and during the cold season. This study added case-crossover evidence indicating that short-term exposure to ambient air pollution, specifically SO2 and NO2, is linked to a higher risk of hospital admissions for schizophrenia. These findings contribute to a better understanding of the detrimental effects of air pollution on neuropsychiatric health conditions.
A Study of Structural Stability on the Bidispersive Flow in a Semi-Infinite Cylinder
Authors: Li Yuanfei
Published: June 2024

We consider the bidispersive flow with nonlinear boundary conditions in a bounded region. By using the differential inequality technique, we get the bound for the L4-norm of the salinity which plays an important role. The continuous dependence and the convergence results on the Soret coefficient are established.
On Bivariate Distributions with Singular Part
Authors: Cuadras Carles M.
Published: June 2024

There are many families of bivariate distributions with given marginals. Most families, such as the Farlie–Gumbel–Morgenstern (FGM) and the Ali–Mikhail–Haq (AMH), are absolutely continuous, with an ordinary probability density. In contrast, there are few families with a singular part or a positive mass on a curve. We define a general condition useful to detect the singular part of a distribution. By continuous extension of the bivariate diagonal expansion, we define and study a wide family containing these singular distributions, obtain the probability density, and find the canonical correlations and functions. The set of canonical correlations is described by a continuous function rather than a countable sequence. An application to statistical inference is given.
Are Hyperglycemia-Induced Changes in the Retina Associated with Diabetes-Correlated Changes in the Brain? A Review from Zebrafish and Rodent Type 2 Diabetes Models
Authors: Augustine-Wofford Kaylee , Connaughton Victoria P. , McCarthy Elizabeth
Published: June 2024

Diabetes is prevalent worldwide, with >90% of the cases identified as Type 2 diabetes. High blood sugar (hyperglycemia) is the hallmark symptom of diabetes, with prolonged and uncontrolled levels contributing to subsequent complications. Animal models have been used to study these complications, which include retinopathy, nephropathy, and peripheral neuropathy. More recent studies have focused on cognitive behaviors due to the increased risk of dementia/cognitive deficits that are reported to occur in older Type 2 diabetic patients. In this review, we collate the data reported from specific animal models (i.e., mouse, rat, zebrafish) that have been examined for changes in both retina/vision (retinopathy) and brain/cognition, including db/db mice, Goto-Kakizaki rats, Zucker Diabetic Fatty rats, high-fat diet-fed rodents and zebrafish, and hyperglycemic zebrafish induced by glucose immersion. These models were selected because rodents are widely recognized as established models for studying diabetic complications, while zebrafish represent a newer model in this field. Our goal is to (1) summarize the published findings relevant to these models, (2) identify similarities in cellular mechanisms underlying the disease progression that occur in both tissues, and (3) address the hypothesis that hyperglycemic-induced changes in retina precede or predict later complications in brain.
The Role of Hyperuricemia in Cardiac Diseases: Evidence, Controversies, and Therapeutic Strategies
Authors: Zheng Yue , Chen Zhirui , Yang Jinya , Zheng Jing , Shui Xiaorong , Yan Yiguang , Huang Shian , Liang Zheng , Lei Wei , He Yuan
Published: June 2024

Hyperuricemia (HUA) may lead to myocardial cell damage, thereby promoting the occurrence and adverse outcomes of heart diseases. In this review, we discuss the latest clinical research progress, and explore the impact of HUA on myocardial damage-related diseases such as myocardial infarction, arrhythmias, and heart failure. We also combined recent findings from basic research to analyze potential mechanisms linking HUA with myocardial injury. In different pathological models (such as direct action of high uric acid on myocardial cells or combined with myocardial ischemia-reperfusion model), HUA may cause damage by activating the NOD-like receptor protein 3 inflammasome-induced inflammatory response, interfering with cardiac cell energy metabolism, affecting antioxidant defense systems, and stimulating reactive oxygen species production to enhance the oxidative stress response, ultimately resulting in decreased cardiac function. Additionally, we discuss the impact of lowering uric acid intervention therapy and potential safety issues that may arise. However, as the mechanism underlying HUA-induced myocardial injury is poorly defined, further research is warranted to aid in the development novel therapeutic strategies for HUA-related cardiovascular diseases.
Structural and Thermodynamic Insights into Dimerization Interfaces of Drosophila Glutathione Transferases
Authors: Schwartz Mathieu , Petiot Nicolas , Chaloyard Jeanne , Senty-Segault Véronique , Lirussi Frédéric , Senet Patrick , Nicolai Adrien , Heydel Jean-Marie , Canon Francis , Sonkaria Sanjiv , Khare Varsha , Didierjean Claude , Neiers Fabrice
Published: June 2024

This study presents a comprehensive analysis of the dimerization interfaces of fly GSTs through sequence alignment. Our investigation revealed GSTE1 as a particularly intriguing target, providing valuable insights into the variations within Delta and Epsilon GST interfaces. The X-ray structure of GSTE1 was determined, unveiling remarkable thermal stability and a distinctive dimerization interface. Utilizing circular dichroism, we assessed the thermal stability of GSTE1 and other Drosophila GSTs with resolved X-ray structures. The subsequent examination of GST dimer stability correlated with the dimerization interface supported by findings from X-ray structural analysis and thermal stability measurements. Our discussion extends to the broader context of GST dimer interfaces, offering a generalized perspective on their stability. This research enhances our understanding of the structural and thermodynamic aspects of GST dimerization, contributing valuable insights to the field.
Electroceuticals and Magnetoceuticals in Gastroenterology
Authors: Song Gengqing , Sclocco Roberta , Sharma Amol , Guerrero-López Ingrid , Kuo Braden
Published: June 2024

In the realm of gastroenterology, the inadequacy of current medical treatments for gastrointestinal (GI) motility disorders and inflammatory bowel disease (IBD), coupled with their potential side effects, necessitates novel therapeutic approaches. Neuromodulation, targeting the nervous system’s control of GI functions, emerges as a promising alternative. This review explores the promising effects of vagal nerve stimulation (VNS), magnetic neuromodulation, and acupuncture in managing these challenging conditions. VNS offers targeted modulation of GI motility and inflammation, presenting a potential solution for patients not fully relieved from traditional medications. Magnetic neuromodulation, through non-invasive means, aims to enhance neurophysiological processes, showing promise in improving GI function and reducing inflammation. Acupuncture and electroacupuncture, grounded in traditional medicine yet validated by modern science, exert comprehensive effects on GI physiology via neuro-immune-endocrine mechanisms, offering relief from motility and inflammatory symptoms. This review highlights the need for further research to refine these interventions, emphasizing their prospective role in advancing patient-specific management strategies for GI motility disorders and IBD, thus paving the way for a new therapeutic paradigm.
Concentrations of Glypican-4, Irisin and Total Antioxidant Status in Women with Metabolic Syndrome: Influence of Physical Activity
Authors: Grzelak Teresa , Sperling Marcelina , Pelczyńska Marta , Mikulska-Sauermann Aniceta Ada , Bogdański Paweł , Czyżewska Krystyna , Mądry Edyta
Published: June 2024

Glypican-4 belongs to a group of poorly understood adipokines, with potential importance in people with metabolic syndrome, especially in groups of patients with glucose metabolism disorder. This study aimed to assess the effect of physical activity on serum glypican-4 and irisin levels and total antioxidant status (TAS) in plasma and saliva in women with metabolic syndrome (MetS). Seventy-two Caucasian women aged 25–60 were included in the study (36 women with MetS and 36 women without MetS (control group, CONTR)). The glypican-4 and irisin concentrations, total antioxidant status, glycemia, lipid profile, anthropometric parameters, and blood pressure were analyzed before and after 28 days of controlled physical activity. Serum glypican-4 and plasma TAS levels were higher (p = 0.006 and p = 0.043, respectively) on the 28th day than on the first day of the study only in the CONTR group. In the MetS group, 28 days of physical activity caused a reduction in body fat mass (p = 0.049) without changes in glypican-4, irisin, or TAS levels. In both groups, glypican-4 levels correlated positively with irisin levels and negatively with Waist-Hip Ratio (WHR), while irisin levels correlated positively with High-Density Lipoprotein Cholesterol (HDL-C) levels and negatively with waist circumference (WC) and WHR values on the 28th day of the study. To summarize, a 28-day moderate training, accompanied by a reduction in body fat mass, stabilized glypican-4 levels and TAS in female patients with MetS.
The Sweet Relationship between the Endometrium and Protein Glycosylation
Authors: Zhang Linyu , Feng Ying , Zhang Yue , Sun Xinrui , Ma Qianhong , Ma Fang
Published: June 2024

The endometrium is an important part of women’s bodies for menstruation and pregnancy. Various proteins are widely expressed on the surface of endometrial cells, and glycosylation is an important post-translational modification of proteins. Glycosylation modification is closely related not only to endometrial receptivity but also to common diseases related to endometrial receptivity. Glycosylation can improve endometrial receptivity, promote embryo localization and trophoblast cell adhesion and invasion, and contribute to successful implantation. Two diseases related to endometrial receptivity include endometriosis and endometrial cancer. As a common benign disease in women, endometriosis is often accompanied by an increased menstrual volume, prolonged menstrual periods, progressive and aggravated dysmenorrhea, and may be accompanied by infertility. Protein glycosylation modification of the endometrial surface indicates the severity of the disease and may be an important pathogenesis of endometriosis. In cancer, glycosylation modifications on the surface of tumor cells can be a marker to distinguish the type and severity of endometrial cancer. This review highlights the role of protein glycosylation in embryo–maternal endometrial dialogue and explores its potential mechanisms in diseases related to endometrial receptivity, which could provide a new clinical approach for their diagnosis and treatment.
School Participation Questionnaire (SPQ): Italian Translation, Cultural Adaptation, and Pilot Testing in Children with Neurodevelopmental Disorders
Authors: Pietragalla Giorgia , Galeoto Giovanni , Moresi Marco , Ruffini Martina , Simeon Rachele , Panuccio Francescaroberta , Valente Donatella , Berardi Anna
Published: June 2024

Introduction: According to leading occupational therapy models, the environment appears to be a key element in fostering occupational performance and participation. There is an emerging need to identify an instrument that can assess these aspects in the school environment. Currently, there are no rating scales in Italy for the school participation of children with neurodevelopmental disorders. For this reason, this study aims to culturally adapt and translate the School Participation Questionnaire (SPQ) to Italian and to pilot test the translated Italian version on children with neurodevelopmental disorders. Methods: The original scale was translated from English to Italian using the guidelines “Translation and Cultural Adaptation of Patient Reported Outcomes Measures—Principles of Good Practice”. The psychometric properties analyzed were the following: content validity, construct validity, cross-cultural validity, and internal consistency. Construct validity was assessed using the Italian version of the Sensory Processing Measure (SPM). Results: The Italian version of the SPQ was administered to 22 children. The mean ± SD of the score was 9.32 ± 1.36; Cronbach’s α was 0.935 (p < 0.01). The Pearson’s correlation coefficient with the SPM scores was −0.622 (p < 0.01). Conclusions: This pilot testing study for the validation of the Italian version of the SPQ showed good validity and reliability results. Thanks to this study, it would be possible to further analyze the tool for the evaluation of the environment and school participation of children with neurodevelopmental disorders, in particular autism spectrum disorder. It is a quick and easy instrument that focuses on the environment as an active variable in the child’s occupational performance.
Translating Molecular Approaches to Oligodendrocyte-Mediated Neurological Circuit Modulation
Authors: Song Jingwei , Saglam Aybike , Zuchero J. Bradley , Buch Vivek P.
Published: June 2024

The central nervous system (CNS) exhibits remarkable adaptability throughout life, enabled by intricate interactions between neurons and glial cells, in particular, oligodendrocytes (OLs) and oligodendrocyte precursor cells (OPCs). This adaptability is pivotal for learning and memory, with OLs and OPCs playing a crucial role in neural circuit development, synaptic modulation, and myelination dynamics. Myelination by OLs not only supports axonal conduction but also undergoes adaptive modifications in response to neuronal activity, which is vital for cognitive processing and memory functions. This review discusses how these cellular interactions and myelin dynamics are implicated in various neurocircuit diseases and disorders such as epilepsy, gliomas, and psychiatric conditions, focusing on how maladaptive changes contribute to disease pathology and influence clinical outcomes. It also covers the potential for new diagnostics and therapeutic approaches, including pharmacological strategies and emerging biomarkers in oligodendrocyte functions and myelination processes. The evidence supports a fundamental role for myelin plasticity and oligodendrocyte functionality in synchronizing neural activity and high-level cognitive functions, offering promising avenues for targeted interventions in CNS disorders.
Machine Learning Classification of Patients with Amnestic Mild Cognitive Impairment and Non-Amnestic Mild Cognitive Impairment from Written Picture Description Tasks
Authors: Kim Hana , Hillis Argye E. , Themistocleous Charalambos
Published: June 2024

Individuals with Mild Cognitive Impairment (MCI), a transitional stage between cognitively healthy aging and dementia, are characterized by subtle neurocognitive changes. Clinically, they can be grouped into two main variants, namely patients with amnestic MCI (aMCI) and non-amnestic MCI (naMCI). The distinction of the two variants is known to be clinically significant as they exhibit different progression rates to dementia. However, it has been particularly challenging to classify the two variants robustly. Recent research indicates that linguistic changes may manifest as one of the early indicators of pathology. Therefore, we focused on MCI’s discourse-level writing samples in this study. We hypothesized that a written picture description task can provide information that can be used as an ecological, cost-effective classification system between the two variants. We included one hundred sixty-nine individuals diagnosed with either aMCI or naMCI who received neurophysiological evaluations in addition to a short, written picture description task. Natural Language Processing (NLP) and a BERT pre-trained language model were utilized to analyze the writing samples. We showed that the written picture description task provided 90% overall classification accuracy for the best classification models, which performed better than cognitive measures. Written discourses analyzed by AI models can automatically assess individuals with aMCI and naMCI and facilitate diagnosis, prognosis, therapy planning, and evaluation.
Effectiveness of the Use of Virtual Reality Rehabilitation in Children with Dyslexia: Follow-Up after One Year
Authors: Maresca Giuseppa , Corallo Francesco , De Cola Maria Cristina , Formica Caterina , Giliberto Silvia , Rao Giuseppe , Crupi Maria Felicita , Quartarone Angelo , Pidalà Alessandra
Published: June 2024

Dyslexia is a common learning disorder that hinders reading fluency and comprehension. Traditional treatments can be tedious for children, limiting their effectiveness. This study investigated the one-year effects of rehabilitation treatment with a virtual reality rehabilitation system (VRRS) on children with dyslexia. Twenty-four children were divided into control (CG) and experimental (EG) groups. The CG underwent conventional neuropsychological treatment (CNT), while the EG underwent VR neurorehabilitation training (VRNT) using the VRRS. Neuropsychological evaluation was conducted before treatment, after six months, and again after one year for both groups. Compared to the control group, children who received VR training showed significant improvement in reading skills, especially in non-word reading and reading speed, even after one year without further VR intervention. VRRS can improve treatment adherence and minimize symptoms by offering engaging activities for children. These findings suggest VRRS may be a valuable tool for dyslexia rehabilitation with long-lasting effects.
High-Rise Timber Offices: Main Architectural and Structural Design Parameters
Authors: Ilgın Hüseyin Emre , Aslantamer Özlem Nur
Published: June 2024

High-rise office structures constructed using timber material (with a minimum of eight stories) signify a burgeoning and favorable sector, mainly owing to their ability to offer substantial environmental and economic advantages across their lifespan. However, it is crucial to recognize that the current corpus of scholarly literature lacks a thorough investigation into vital aspects concerning the architectural and structural planning of these sustainable structures. In an effort to fill this gap and augment the understanding of advancing international tendencies, this paper delved into data originating from 27 high-rise offices on a worldwide scale. The primary findings were: (i) Central core arrangements were the most popular, accounting for 67%, followed by peripheral types at 22%. (ii) Prismatic designs were the most frequently used at 85%, with free forms making up 11%. (iii) Material combinations involving timber and concrete were widely prevalent, making up 70% of composite constructions, which were 74% of the sample group, with pure timber constructions at 26%. (iv) Structural systems predominantly utilized shear walled frame systems, comprising 85% of the total. This article serves as a valuable resource for architectural designers, offering guidance on planning and executing future sustainable developments in the domain of high-rise timber office.
Investigating the Influence of Oil Shale Ash and Basalt Composite Fibres on the Interfacial Transition Zone in Concrete
Authors: Nováková Iveta , Jhatial Ashfaque Ahmed , Kekez Sofija , Gjerløw Eirik , Gulik Volodymyr , Kannathasan Karunamoorthy Rengasamy , Vaišnoras Mindaugas , Krasnikovs Andrejs
Published: June 2024

The interfacial transition zone (ITZ) is the weakest phase in concrete, characterised by higher porosity and being prone to microcrack formation. Additionally, the ITZ is created when dispersed fibre reinforcement is present. Although fibres improve flexural strength, they can negatively impact other properties. This research investigates the ITZ of fibre-reinforced concrete where macro-basalt fibres (BFs) and oil shale ash (OSA), as an SCM, were used with the aim of modifying the properties of concrete, enhancing the ITZ, and reducing its carbon footprint. Six different concrete mixes with OSA doses between 10% and 30% and a constant BF dose of 8.0 kg per 1 m3 of concrete were prepared and tested. The ITZ was analysed with SEM images and verified through its mechanical properties. The results showed that the presence of OSA improved bonding and densified the microstructure of the paste, especially in the ITZ, resulting in a nearly constant flexural strength at up to a 20% replacement and only a 6.7% decrease in compressive strength while reducing the global warming potential by 19.24 kg CO2 equivalent in the mix with 10% OSA replacement. Higher replacement ratios had a negative impact on the mechanical properties, as the OSA had not reacted entirely and served partly as an inert filler.
Settlement Calculation of Semi-Rigid Pile Composite Foundation on Ultra-Soft Soil under Embankment Load
Authors: Cao Fengxu , Ye Chaoliang , Wu Zhenxu , Zhao Zitong , Sun Hao
Published: June 2024

Ultra-soft soil is distributed in coastal areas around the world and has poor engineering properties. There is a significant difference in settlement between semi-rigid pile and surrounding soil under embankment load. Based on existing research results, the settlement calculation formula of ultra-soft soil composite foundation reinforced by semi-rigid pile is derived in this paper. Based on the Alamgir displacement model, assuming a three-zone model of pile skin friction with a negative skin friction plastic zone in the upper part of the pile, an elastic zone in the middle part of the pile, and a skin friction-bearing plastic zone in the lower part of the pile, the upward and downward penetrations of pile, and pile–soil slip deformation characteristics are considered. Analytical expressions for settlement calculations of semi-rigid pile composite foundations under embankments were derived based on differential equations for pile–soil load transfer in the unit cell. The influences of pile diameter and the compression modulus of the underlying layer at the pile end on the settlement characteristics of the semi-rigid pile composite foundation are discussed. The results show that the derived theoretical calculation method is in good agreement with the field measurement and laboratory model test results. Ultra-soft soil composite foundations have long settlement stabilization times and large settlement deformations. Penetration deformation occurs at the semi-rigid pile end. The relationship between pile end resistance and pile end piercing deformation is hyperbolic. The compression modulus of the underlying layer has a great influence on pile end penetration. The lower the compression modulus of the underlying layer, the larger the penetration deformation of pile end. The larger the pile diameter is, the smaller the penetration deformation is.
Three-Dimensional Printable Concrete by an Ultra-Thin Nozzle and Fully Sealed Extrusion
Authors: Shen Jing , Li Yujia , Zhang Xiaoman , Li Yangbo , Huang Chaohui , Luo Wei
Published: June 2024

Due to the molding-free property and dry shrinkage of extrusion-based three-dimensional printable concrete (3DPC), the precision issues of 3DPC have not been solved effectively. One of the viable solutions for 3DPC precision improvement is to print using ultra-thin filaments. The challenges of ultra-thin-filament printing are extrudability, flowability, and fast solidification. To overcome these challenges and enhance precision, a customized 3D concrete printer with an ultra-thin diameter nozzle (6 mm) and fully sealed extrusion system was developed, and the mix design of ultra-thin-filament 3DPC (UTF-3DPC) was studied, including ingredients such as fly ash (FA), silica fume (SF), ordinary Portland cement (OPC), sodium dodecyl sulfate and cellulose (SDSC), water reducer, water, and sand. The function of UTF-3DPCs flowability and fast solidification with the proportion of water and SDSC was explored to obtain the optimal mix design. The standard compressive and flexural strengths of UTF-3DPC specimens were compared with the mold-cast vibrated and the mold-cast non-vibrated concrete. Their meso-scale and micro-scale structures were analyzed to expose the strength mechanism, according to the scanning electron microscope (SEM) images. A suitable mix design of UTF-3DPC was obtained and UTF-3DPC strength reached 80% of standard mold-cast concrete. The findings reported here provide a pathway to improve the precision of 3DPC and extend the application of 3D printing technology in engineering.
Preliminary Study of Interactive Local Buckling for Aluminium Z-Section
Authors: Piluso Vincenzo , Pisapia Alessandro
Published: June 2024

In this study, a theoretical investigation is conducted on the local buckling resistance of aluminium Z-sections subjected to uniform compression. A method is developed based on the J2 deformation theory of plasticity (DTP) to calculate the critical buckling load within the elastic–plastic range. The deformation theory of plasticity relies on the assumption that the strain state is uniquely defined by the stress state. Consequently, it serves as a specific path-independent non-linear constitutive model. The study commences with the elastoplastic differential equation for a single compressed plate. By incorporating the boundary conditions and the interaction between plate elements, the interactive buckling load is determined. An example is provided to illustrate the incremental nature of the numerical procedure. Additionally, numerical analyses are performed to examine the impact of the strain-hardening properties of aluminium alloys on local buckling resistance. In the final stage, the theoretical results are compared with those found in existing scientific literature. This comparison serves to evaluate the accuracy of the DTP procedure.
Primary Tumor Characteristics as Biomarkers of Immunotherapy Response in Advanced Melanoma: A Retrospective Cohort Study
Authors: Goodman Rachel S. , Jung Seungyeon , Fletcher Kylie , Burnette Hannah , Mohyuddin Ismail , Irlmeier Rebecca , Ye Fei , Johnson Douglas B.
Published: June 2024

Identifying patients likely to benefit from immune checkpoint inhibitor (ICI) treatment remains a crucial goal for melanoma. The objective of this study is to assess the association between primary tumor features and immunotherapy response and survival in advanced melanoma patients. In this single-center retrospective cohort study, disease characteristics, response to immunotherapy, PFS, and OS were assessed among melanoma patients (excluding mucosal and uveal primaries) treated with ICI. Among 447 patients, 300 (67.1%) received anti-PD-1 monotherapy and 147 (32.9%) received ipilimumab/nivolumab. A total of 338 (75.6%) had cutaneous melanoma, 29 (6.5%) had acral melanoma, and 80 (17.9%) had melanoma of unknown primary. Ulceration and stage at initial presentation were associated with inferior outcomes on univariate analysis. However, on multivariate analysis, this result was not observed, but cutaneous melanoma and each of its subtypes (superficial spreading, nodular, other, unknown) were positively associated with response, longer PFS, and longer OS. Metastatic stage (M1c, M1d) at presentation (OR = 1.8, p < 0.05) and BRAFV600E mutation status (OR = 1.6, p < 0.001) were associated with shorter PFS. This study is limited by its retrospective and single-center design. Cutaneous melanoma and its subtypes were significantly associated with response, PFS, and OS compared with acral or unknown primary melanoma.