bluuebunny/crossref_metadata_2025 huggingface dataset:
Advantages of Dynamic Navigation in Prosthetic Implant Treatment in Terms of the Clinical Evaluation and Salivary Pro-Inflammatory Biomarkers: A Clinical Study
Authors: Wachol Kacper , Morawiec Tadeusz , Szurko Agnieszka , Baldi Domenico , Nowak-Wachol Anna , Śmieszek-Wilczewska Joanna , Mertas Anna
Published: August 2023

Successful implantation in augmented areas relies on adequate bone density and quality, along with thorough planning. The minimisation of the risks involved in the surgery and recovery phases is also of tremendous relevance. The aims of the present research were to clinically and biochemically evaluate the healing process after implant surgery (dental implants) using dynamic surgical navigation following prior bone augmentation. Thirty healthy patients who had implant treatment were analysed. The study participants (30 patients) were randomised between two groups. The 15 patients in the study group were treated with Navident dynamic navigation by using a flapless technique. The control group included 15 subjects in whom the implantation procedure was performed classically using the elevation flap full-thickness method. In all cases, the patient’s clinical condition, the patient’s subjective visual assessment of post-operative pain using the Visual Analogue Scale (VAS), and the levels of the salivary biomarkers interleukin 6 (IL 6) and C-reactive protein (CRP) immediately before surgery on the first post-operative day and on the seventh post-operative day were assessed. The healing process was shown to be faster in patients in the study group due to the low invasiveness of the treatment, which was confirmed by lower levels of pro-inflammatory cytokines in the study group versus the control group. The statistical analysis used Student’s t-test and Mann–Whitney test. The implementation of dynamic navigation and the application of the flapless technique reduced post-operative trauma, leading to a reduced risk of infection, reduced patient discomfort, and faster recovery.
Online Coal Identification Based on One-Dimensional Convolution and Its Industrial Applications
Authors: Ma Shaochen , He Kaixun , Peng Xin
Published: August 2023

In order to improve the utilization rate of coal generation and reduce carbon emissions from coal-fired boilers, the operation parameters of power plant boilers should be matched with the actual burning coal. Due to the complex and high-risk blending process of multiple coal types, the actual application of coal types inconsistent with expectations may lead to low combustion efficiency of boilers, cause disturbances to the normal operation of thermal power units, increased energy waste and carbon emissions, and even lead to serious explosion accidents. Therefore, the online identification of coal types for thermal power units is of great significance. To obtain the precise type of coal online, in the present work, a data-driven coal identification method is proposed based on convolutional networks that do not necessitate additional hardware detection equipment and are easy to implement. Experimental results indicate that the proposed method exhibits superior performance in comparison to traditional methods, thus ultimately improving the performance of thermal power plant.
Spatial Modeling through GIS Analysis of Flood Risk and Related Financial Vulnerability: Case Study: Turcu River, Romania
Authors: Trif Septimius , Bilașco Ștefan , Petrea Dănuț , Roșca Sanda , Fodorean Ioan , Vescan Iuliu
Published: August 2023

The present study is part of the context in which Romania adopted the European Parliament Directive 2007/60/EC on flood risk assessment and management. Therefore, the aim of this research is to assess the risk induced by a hydrological hazard, expressed by a financial value estimation, for the Turcu River in the northern sector of the Bran–Dragoslavele transcarpathian corridor (Romania), an important tourist axis where the pressure on land has increased considerably. As a result, the intra-village areas of Moieciu de Sus, Cheia, Moieciu de Jos, Bran and Tohanu Nou have also expanded into areas vulnerable to flooding. There are currently no studies on the areas potentially affected as well as the extent of the possible damage. For this reason, we proceeded to model the water level corresponding to the maximum flow value with a probability exceeding 1%, using HEC-RAS and ArcGIS software. The results of the implementation of the spatial analysis model resulted in the delineation of the floodplain and the assessment of the potential financial loss related to the minimum market value of the land with the related real estate infrastructures. The research reveals that in the 1% band area (78.7841 ha) with water depth > 0.5 m, more than 433 infrastructures are at high risk of flooding, most of them with high real estate value, i.e., 5.61 km of roads for which a cost of EUR 3,402,666.90 was calculated for restoration. A knowledge of financial vulnerability to flooding becomes important for the community; local authorities involved in making decisions for insuring real estate at risk and planning/managing investments work to prevent/combat the effects of flooding.
The Novel Application of Deep Reinforcement to Solve the Rebalancing Problem of Bicycle Sharing Systems with Spatiotemporal Features
Authors: Pan Baoran , Tian Lixin , Pei Yingdong
Published: August 2023

Facing the Bicycle Rebalancing Problem (BRP), we established a Rebalancing Incentive System (BRIS). In BRIS, the bicycle operator proposes the method of financial compensation to encourage cylclists to detour some specific stations where the number of bikes is excessive or insufficient and access suitable sations. BRIS mainly includes two objects: the Bike Gym imitating the bicycle environment, and the Spatiotemporal Rebalancing Pricing Algorithm (STRPA) determining the amount of money which is given to the cyclist depending on time. STRPA is a deep reinforcement learning model based on the actor–critic structure, which is the core concept of this paper. In STRPA, the hierarchical principle is introduced to solve the dimensional disaster, and the graph matrix A is introduced to solve the complex node relationship. In addition, the traffic data including the bicycle have strong temporal and spatial characteristics. The gated recurrent unit (GRU), the sub-module of STRPA, can extract the temporal characteristics well, and the graph convolution network (GCN), also a sub-module of STRPA, can extract the spatial characteristic. Finally, our model is superior to the baseline model when verified on the the public bicycle data of Nanjing.
Grouped Contrastive Learning of Self-Supervised Sentence Representation
Authors: Wang Qian , Zhang Weiqi , Lei Tianyi , Peng Dezhong
Published: August 2023

This paper proposes a method called Grouped Contrastive Learning of self-supervised Sentence Representation (GCLSR), which can learn an effective and meaningful representation of sentences. Previous works maximize the similarity between two vectors to be the objective of contrastive learning, suffering from the high-dimensionality of the vectors. In addition, most previous works have adopted discrete data augmentation to obtain positive samples and have directly employed a contrastive framework from computer vision to perform contrastive training, which could hamper contrastive training because text data are discrete and sparse compared with image data. To solve these issues, we design a novel framework of contrastive learning, i.e., GCLSR, which divides the high-dimensional feature vector into several groups and respectively computes the groups’ contrastive losses to make use of more local information, eventually obtaining a more fine-grained sentence representation. In addition, in GCLSR, we design a new self-attention mechanism and both a continuous and a partial-word vector augmentation (PWVA). For the discrete and sparse text data, the use of self-attention could help the model focus on the informative words by measuring the importance of every word in a sentence. By using the PWVA, GCLSR can obtain high-quality positive samples used for contrastive learning. Experimental results demonstrate that our proposed GCLSR achieves an encouraging result on the challenging datasets of the semantic textual similarity (STS) task and transfer task.
Non-Probabilistic Reliability Analysis of Slopes Based on a Multidimensional Parallelepiped Model
Authors: Shu Suxun , Qian Jiajun , Gong Wenhui , Yang Zhiquan , Pi Kang
Published: August 2023

Aiming at the problem that the non-probabilistic reliability analysis method of slope engineering, which is based on an interval model, cannot consider the cross-correlation of geotechnical parameters, a non-probabilistic reliability analysis method of slopes based on a multidimensional parallelepiped model is proposed. This method can effectively alleviate the problem of difficult data survey in the field of geotechnical engineering. Using the limited sample data of soil parameters, the multidimensional parallelepiped model is constructed. The performance function of the slope is constructed based on Latin hypercube sampling and the quadratic response surface method. Then, the limit state equation of the slope can be standardized using the multidimensional parallelepiped model. The non-probabilistic reliability indexes of the slope are calculated based on the global optimal solution to judge the stability state of the slope. The example analysis verifies the feasibility of the proposed method. The results show that the correlation of shear strength parameters of soil has a great influence on the non-probabilistic reliability indexes of the slope. When the correlation coefficients of the shear strength parameters are between −1.0 and 0, the smaller the correlation coefficient is, the greater the non-probabilistic reliability index of the slope is; when the correlation coefficients of the shear strength parameters are between 0 and 1.0, the non-probabilistic reliability index of the slope does not change with the correlation coefficient. The non-probabilistic reliability indexes of the slope obtained using the multidimensional parallelepiped model are between the results obtained using an ellipsoid model and those obtained using an interval model, which are validated by Monte Carlo method and relatively more reasonable. In the absence of a large number of geotechnical sample data, this method provides a new way for slope stability analysis and expands the application field of calculation methods based on non-probabilistic theory.
Challenges and Solutions for Autonomous Ground Robot Scene Understanding and Navigation in Unstructured Outdoor Environments: A Review
Authors: Wijayathunga Liyana , Rassau Alexander , Chai Douglas
Published: August 2023

The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, robots have achieved relatively high levels of autonomy. In more unstructured environments, however, the development of fully autonomous mobile robots remains challenging due to the complexity of understanding these environments. Many autonomous mobile robots use classical, learning-based or hybrid approaches for navigation. More recent learning-based methods may replace the complete navigation pipeline or selected stages of the classical approach. For effective deployment, autonomous robots must understand their external environments at a sophisticated level according to their intended applications. Therefore, in addition to robot perception, scene analysis and higher-level scene understanding (e.g., traversable/non-traversable, rough or smooth terrain, etc.) are required for autonomous robot navigation in unstructured outdoor environments. This paper provides a comprehensive review and critical analysis of these methods in the context of their applications to the problems of robot perception and scene understanding in unstructured environments and the related problems of localisation, environment mapping and path planning. State-of-the-art sensor fusion methods and multimodal scene understanding approaches are also discussed and evaluated within this context. The paper concludes with an in-depth discussion regarding the current state of the autonomous ground robot navigation challenge in unstructured outdoor environments and the most promising future research directions to overcome these challenges.
Analysis of Acid Diffusion Effects on Physical Properties of Polymer Composites: A Combined Study of Mechanical and Electrical Characterization
Authors: Tamayo-Vegas Sebastian , Lafdi Khalid , Tarfaoui Mostapha , Lafdi Khalil K. , Daly Mohamed
Published: August 2023

In this study, we examined the impact of carbon nanotube (CNT) concentration on the mechanical properties of epoxy/CNT composites under acid exposure. Samples with varying CNT concentrations (0% to 5%) were fabricated and characterized using dynamic mechanical analysis (DMA) and nanoindentation. Beyond the percolation threshold, the composites experienced decreased bulk mechanical properties due to CNT agglomeration. Acid exposure for one week and one month revealed a gradient of properties from the sample’s skin to its core. Overall, the composites exhibited modified physical properties, with degradation influenced by the CNT concentration. Higher concentrations acted as barriers but also created pathways for acid diffusion through pores surrounding CNT agglomerates. The agreement between nanoindentation and vector network analyzer (VNA) measurements further supported our findings. This convergence of mechanical and electromagnetic characterization techniques holds promise for wireless structural health monitoring (SHM) applications. Our study enhances the understanding of epoxy/CNT composites for SHM applications. The relationship between CNT concentration, acid exposure, and mechanical properties guides material selection and the development of real-time damage-detection techniques. Integrating multiple measurement techniques, as demonstrated by the agreement between nanoindentation and VNA data, provides a comprehensive understanding of structural behavior, improving SHM practices.
“Once the Fire Starts Then There Is No Stopping It”: The Revitalization of Chinookan Art in the 21st Century, Conversations with Greg A. Robinson
Authors: Daehnke Jon D. , Robinson Greg A.
Published: August 2023

Chinookan art centered on the Lower Columbia River and was created by Chinookan-speaking people living along the river and its tributaries. The style is unique, focusing on geometric forms, numerical patterns, and anatomical representation. It is embedded in Chinookan mythology and differs considerably from the more widely recognized Formline of Indigenous artists from the northern Pacific Northwest. It also receives less attention, both publicly and scholarly. Due to high rates of death along the Columbia from introduced diseases during colonial invasion, and high levels of looting that followed, Chinookan art nearly disappeared from the landscape. In the 21st century Chinookan art has had a resurgence, led by Chinookan practitioners. The resurgence occurs not only within individual households but also in public settings. This resurgence also includes an emphasis on teaching the style to youth, who learn that this is not just about making art but is integrally attached to culture more broadly, including connection to language, stories, protocols, and Indigenous identity itself. It is ultimately a source of pride, resilience, and resistance. As a result, where there were once generations who never saw a landscape with Chinookan art, there are now generations who will never know a landscape without it.
Simulations of a Heavy Snowfall Event in Xinjiang via the WRF Model Coupled with Different Land Surface Parameterization Schemes
Authors: Ai Guannan , Wang Shuzhou , Zhi Hai
Published: August 2023

Frequent heavy snowfall in Xinjiang plays an important role in the land water cycle. In this study, 18 groups of simulation experiments are conducted on the heavy snowfall event in Xinjiang during 9–13 December of 2015 using the Weather Research and Forecasting (WRF) model. In these experiments, the combination of six land surface parameterization schemes (the Noah scheme, Noah-MP scheme, RUC scheme, CLM4 scheme, PX scheme, and TD scheme) with three microphysical parameterization schemes (the WSM6 scheme, Thompson scheme, and Lin scheme) are adopted, where the observed snowfall data are used for performance evaluation. Results show that the simulated snowfall intensity and snowfall range in different areas are very sensitive to the selection of the land surface scheme. The snowfall in southern Xinjiang is overestimated by almost all six schemes, where the Noah-MP scheme performs more reasonably than the others. The Noah scheme shows its advantage in northwestern Xinjiang. The three different microphysical schemes vary significantly in producing snowfall amount. The WSM6 scheme produced the largest snowfall amount, and the Lin scheme resulted in the smallest snowfall amount. In addition, the accumulated snowfall amounts above 10 mm are generally underestimated by all six land surface schemes, while the accumulated snowfall amounts below 10 mm are overestimated by most of the schemes. The Noah-MP scheme performs the best in the simulation of the snowfall amount in the whole region. However, the Noah scheme shows an advantage in areas with a large snowfall amount.
Evaluation of MERRA-2 Black Carbon Characteristics and Potential Sources over China
Authors: Mao Mao , Zhou Yu , Zhang Xiaolin
Published: August 2023

Black carbon (BC), an important component of atmospheric aerosol, plays a significant role in regional climate, hydrological cycle, variation of monsoon rainfall, and human health. The 40-year detailed atmospheric BC over China from 1981 to 2020 is systematically investigated through the MERRA-2 reanalysis dataset. MERRA-2 BC generally showed a good correlation (R = 0.68) compared with 673 monthly samples from ground-based observation at 35 stations around China. The overall annual average of MERRA-2 BC concentration over China is 1.15 μg/m3, with a fast growth rate during 1981–2007 and a relatively slow decrease after that. The winter season has the highest mean concentration of BC, followed by autumn and spring, whereas summer shows relatively weaker values. The order of annual average BC concentrations during 1981–2020 is Beijing-Tianjin-Hebei region (BTH, 4.02 μg/m3) > Sichuan Basin (SB, 3.94 μg/m3) > Yangtze River Delta (YRD, 2.68 μg/m3) > Pearl River Delta (PRD, 1.47 μg/m3). The monthly mean BC concentrations over the BTH, YRD, PRD and SB are estimated to be smallest 3.18 μg/m3 in May, 1.94 μg/m3 in August, 0.82 μg/m3 in July, 3.04 μg/m3 in June, respectively, whilst largest consistently in December with 5.09 μg/m3, 3.83 μg/m3, 2.12 μg/m3, and 5.41 μg/m3, respectively. Our study indicates the primary potential source areas for BC are concentrated in the research city and its surroundings. Beijing and Chengdu are more BC-polluted areas than Shanghai and Guangzhou. Long-distance, regional transfer from south BTH contributes importantly to BC pollution in Beijing under the influence of prevailing southerly winds. The geographical location of Chengdu causes the transport and accumulation of BC inside the SB.
Metrical Boundedness and Compactness of a New Operator between Some Spaces of Analytic Functions
Authors: Stević Stevo
Published: August 2023

The metrical boundedness and metrical compactness of a new operator from the weighted Bergman-Orlicz spaces to the weighted-type spaces and little weighted-type spaces of analytic functions are characterized.
Enhanced Remora Optimization with Deep Learning Model for Intelligent PMSM Drives Temperature Prediction in Electric Vehicles
Authors: Latif Abdul , Mehedi Ibrahim M. , Vellingiri Mahendiran T. , Meem Rahtul Jannat , Palaniswamy Thangam
Published: August 2023

One of the widespread electric motors for electric vehicles (EVs) is permanent magnet synchronous machine (PMSM) drives. It is because of the power density and high energy of the PMSM with moderate assembly cost. The widely adopted PMSM as the motor of choice for EVs, together with variety of applications urges stringent monitoring of temperature to ignore high temperatures. Temperature monitoring of the PMSM is highly complex to accomplish because of complex measurement device for internal components of the PMSM. Temperature values beyond a certain range might result in additional maintenance costs together with major operational problems in PMSM. The latest developments in artificial intelligence (AI) and deep learning (DL) methods pave a way for accurate temperature prediction in PMSM drivers. With this motivation, this article introduces an enhanced remora optimization algorithm with stacked bidirectional long short-term memory (EROA-SBiLSTM) approach for temperature prediction of the PMSM drives. The presented EROA-SBiLSTM technique mainly focuses on effectual temperature prediction using DL and hyperparameter tuning schemes. To accomplish this, the EROA-SBiLSTM technique applies Pearson correlation coefficient analysis for observing the correlation among various features, and the p-value is utilized for determining the relevant level. Next, the SBiLSTM model is used to predict the level of temperature that exists in the PMSM drivers. Finally, the EROA based hyperparameter tuning process is carried out to adjust the SBiLSTM parameters optimally. The experimental outcome of the EROA-SBiLSTM technique is tested using electric motor temperature dataset from the Kaggle dataset. The comprehensive study specifies the betterment of the EROA-SBiLSTM technique.
Multitask Attention-Based Neural Network for Intraoperative Hypotension Prediction
Authors: Shi Meng , Zheng Yu , Wu Youzhen , Ren Quansheng
Published: August 2023

Timely detection and response to Intraoperative Hypotension (IOH) during surgery is crucial to avoid severe postoperative complications. Although several methods have been proposed to predict IOH using machine learning, their performance still has space for improvement. In this paper, we propose a ResNet-BiLSTM model based on multitask training and attention mechanism for IOH prediction. We trained and tested our proposed model using bio-signal waveforms obtained from patient monitoring of non-cardiac surgery. We selected three models (WaveNet, CNN, and TCN) that process time-series data for comparison. The experimental results demonstrate that our proposed model has optimal MSE (43.83) and accuracy (0.9224) compared to other models, including WaveNet (51.52, 0.9087), CNN (318.52, 0.5861), and TCN (62.31, 0.9045), which suggests that our proposed model has better regression and classification performance. We conducted ablation experiments on the multitask and attention mechanisms, and the experimental results demonstrated that the multitask and attention mechanisms improved MSE and accuracy. The results demonstrate the effectiveness and superiority of our proposed model in predicting IOH.
Continuous Motion Estimation of Knee Joint Based on a Parameter Self-Updating Mechanism Model
Authors: Li Jiayi , Li Kexiang , Zhang Jianhua , Cao Jian
Published: August 2023

Estimation of continuous motion of human joints using surface electromyography (sEMG) signals has a critical part to play in intelligent rehabilitation. Traditional methods always use sEMG signals as inputs to build regression or biomechanical models to estimate continuous joint motion variables. However, it is challenging to accurately estimate continuous joint motion in new subjects due to the non-stationarity and individual differences in sEMG signals, which greatly limits the generalisability of the method. In this paper, a continuous motion estimation model for the human knee joint with a parameter self-updating mechanism based on the fusion of particle swarm optimization (PSO) and deep belief network (DBN) is proposed. According to the original sEMG signals of different subjects, the method adaptively optimized the parameters of the DBN model and completed the optimal reconstruction of signal feature structure in high-dimensional space to achieve the optimal estimation of continuous joint motion. Extensive experiments were conducted on knee joint motions. The results suggested that the average root mean square errors (RMSEs) of the proposed method were 9.42° and 7.36°, respectively, which was better than the results obtained by common neural networks. This finding lays a foundation for the human–robot interaction (HRI) of the exoskeleton robots based on the sEMG signals.
Effects of tDCS on Foot Biomechanics: A Narrative Review and Clinical Applications
Authors: Xiao Songlin , Shen Bin , Zhang Chuyi , Xu Zhen , Li Jingjing , Fu Weijie , Jin Jing
Published: August 2023

In recent years, neuro-biomechanical enhancement techniques, such as transcranial direct current stimulation (tDCS), have been widely used to improve human physical performance, including foot biomechanical characteristics. This review aims to summarize research on the effects of tDCS on foot biomechanics and its clinical applications, and further analyze the underlying ergogenic mechanisms of tDCS. This review was performed for relevant papers until July 2023 in the following databases: Web of Science, PubMed, and EBSCO. The findings demonstrated that tDCS can improve foot biomechanical characteristics in healthy adults, including proprioception, muscle strength, reaction time, and joint range of motion. Additionally, tDCS can be effectively applied in the field of foot sports medicine; in particular, it can be combined with functional training to effectively improve foot biomechanical performance in individuals with chronic ankle instability (CAI). The possible mechanism is that tDCS may excite specific task-related neurons and regulate multiple neurons within the system, ultimately affecting foot biomechanical characteristics. However, the efficacy of tDCS applied to rehabilitate common musculoskeletal injuries (e.g., CAI and plantar fasciitis) still needs to be confirmed using a larger sample size. Future research should use multimodal neuroimaging technology to explore the intrinsic ergogenic mechanism of tDCS.
Biodiversity of Skin Microbiota as an Important Biomarker for Wound Healing
Authors: Ersanli Caglar , Tzora Athina , Voidarou Chrysoula (Chrysa) , Skoufos Stylianos , Zeugolis Dimitrios I. , Skoufos Ioannis
Published: August 2023

Cutaneous wound healing is a natural and complex repair process that is implicated within four stages. However, microorganisms (e.g., bacteria) can easily penetrate through the skin tissue from the wound bed, which may lead to disbalance in the skin microbiota. Although commensal and pathogenic bacteria are in equilibrium in normal skin, their imbalance in the wound area can cause the delay or impairment of cutaneous wounds. Moreover, skin microbiota is in constant crosstalk with the immune system and epithelial cells, which has significance for the healing of a wound. Therefore, understanding the major bacteria species in the cutaneous wound as well as their communication with the immune system has gained prominence in a way that allows for the emergence of a new perspective for wound healing. In this review, the major bacteria isolated from skin wounds, the role of the crosstalk between the cutaneous microbiome and immune system to heal wounds, the identification techniques of these bacteria populations, and the applied therapies to manipulate the skin microbiota are investigated.
Bull Shark (Carcharhinus leucas) Occurrence along Beaches of South-Eastern Australia: Understanding Where, When and Why
Authors: Smoothey Amy F. , Niella Yuri , Brand Craig , Peddemors Victor M. , Butcher Paul A.
Published: August 2023

Unprovoked shark bites have increased over the last three decades, yet they are still relatively rare. Bull sharks are globally distributed throughout rivers, estuaries, nearshore areas and continental shelf waters, and are capable of making long distance movements between tropical and temperate regions. As this species is implicated in shark bites throughout their range, knowledge of the environmental drivers of bull shark movements are important for better predicting the likelihood of their occurrence at ocean beaches and potentially assist in reducing shark bites. Using the largest dataset of acoustically tagged bull sharks in the world, we examined the spatial ecology of 233 juvenile and large (including sub-adult and adult) bull sharks acoustically tagged and monitored over a 5.5-year period (2017–2023) using an array of real-time acoustic listening stations off 21 beaches along the coast of New South Wales, Australia. Bull sharks were detected more in coastal areas of northern NSW (<32° S) but they travelled southwards during the austral summer and autumn. Juveniles were not detected on shark listening stations until they reached 157 cm and stayed north of 31.98° S (Old Bar). Intra-specific diel patterns of occurrence were observed, with juveniles exhibiting higher nearshore presence between 20:00 and 03:00, whilst the presence of large sharks was greatest from midday through to 04:00. The results of generalised additive models revealed that large sharks were more often found when water temperatures were higher than 20 °C, after >45 mm of rain and when swell heights were between 1.8 and 2.8 m. Understanding the influence that environmental variables have on the occurrence of bull sharks in the coastal areas of NSW will facilitate better education and could drive shark smart behaviour amongst coastal water users.
Infection, Inflammation, and Immunity in Sepsis
Authors: Das Undurti N.
Published: August 2023

Sepsis is triggered by microbial infection, injury, or even major surgery. Both innate and adaptive immune systems are involved in its pathogenesis. Cytoplasmic presence of DNA or RNA of the invading organisms or damaged nuclear material (in the form of micronucleus in the cytoplasm) in the host cell need to be eliminated by various nucleases; failure to do so leads to the triggering of inflammation by the cellular cGAS-STING system, which induces the release of IL-6, TNF-α, and IFNs. These cytokines activate phospholipase A2 (PLA2), leading to the release of polyunsaturated fatty acids (PUFAs), gamma-linolenic acid (GLA), arachidonic acid (AA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA), which form precursors to various pro- and anti-inflammatory eicosanoids. On the other hand, corticosteroids inhibit PLA2 activity and, thus, suppress the release of GLA, AA, EPA, and DHA. PUFAs and their metabolites have a negative regulatory action on the cGAS-STING pathway and, thus, suppress the inflammatory process and initiate inflammation resolution. Pro-inflammatory cytokines and corticosteroids (corticosteroids > IL-6, TNF-α) suppress desaturases, which results in decreased formation of GLA, AA, and other PUFAs from the dietary essential fatty acids (EFAs). A deficiency of GLA, AA, EPA, and DHA results in decreased production of anti-inflammatory eicosanoids and failure to suppress the cGAS-STING system. This results in the continuation of the inflammatory process. Thus, altered concentrations of PUFAs and their metabolites, and failure to suppress the cGAS-STING system at an appropriate time, leads to the onset of sepsis. Similar abnormalities are also seen in radiation-induced inflammation. These results imply that timely administration of GLA, AA, EPA, and DHA, in combination with corticosteroids and anti-IL-6 and anti-TNF-α antibodies, may be of benefit in mitigating radiation-induced damage and sepsis.
ABCD1 Transporter Deficiency Results in Altered Cholesterol Homeostasis
Authors: Buda Agnieszka , Forss-Petter Sonja , Hua Rong , Jaspers Yorrick , Lassnig Mark , Waidhofer-Söllner Petra , Kemp Stephan , Kim Peter , Weinhofer Isabelle , Berger Johannes
Published: August 2023

X-linked adrenoleukodystrophy (X-ALD), the most common peroxisomal disorder, is caused by mutations in the peroxisomal transporter ABCD1, resulting in the accumulation of very long-chain fatty acids (VLCFA). Strongly affected cell types, such as oligodendrocytes, adrenocortical cells and macrophages, exhibit high cholesterol turnover. Here, we investigated how ABCD1 deficiency affects cholesterol metabolism in human X-ALD patient-derived fibroblasts and CNS tissues of Abcd1-deficient mice. Lipidome analyses revealed increased levels of cholesterol esters (CE), containing both saturated VLCFA and mono/polyunsaturated (V)LCFA. The elevated CE(26:0) and CE(26:1) levels remained unchanged in LXR agonist-treated Abcd1 KO mice despite reduced total C26:0. Under high-cholesterol loading, gene expression of SOAT1, converting cholesterol to CE and lipid droplet formation were increased in human X-ALD fibroblasts versus healthy control fibroblasts. However, the expression of NCEH1, catalysing CE hydrolysis and the cholesterol transporter ABCA1 and cholesterol efflux were also upregulated. Elevated Soat1 and Abca1 expression and lipid droplet content were confirmed in the spinal cord of X-ALD mice, where expression of the CNS cholesterol transporter Apoe was also elevated. The extent of peroxisome-lipid droplet co-localisation appeared low and was not impaired by ABCD1-deficiency in cholesterol-loaded primary fibroblasts. Finally, addressing steroidogenesis, progesterone-induced cortisol release was amplified in X-ALD fibroblasts. These results link VLCFA to cholesterol homeostasis and justify further consideration of therapeutic approaches towards reducing VLCFA and cholesterol levels in X-ALD.
Characterization of the Abracl-Expressing Cell Populations in the Embryonic Mammalian Telencephalon
Authors: Troumpoukis Dimitrios , Vasileiou Andreas Rafail , Siskos Nikistratos , Stylianopoulou Electra , Ypsilantis Petros , Skavdis George , Grigoriou Maria E.
Published: August 2023

Abracl (ABRA C-terminal-like protein) is a small, non-typical winged-helix protein that shares similarity with the C-terminal domain of the protein ABRA (Actin-Binding Rho-Activating protein). The role of Abracl in the cell remains elusive, although in cancer cells, it has been implicated in proliferation, migration and actin dynamics. Our previous study showed that Abracl mRNA was expressed in the dividing cells of the subpallial subventricular zone (SVZ), in the developing cortical plate (CP), and in the diencephalic SVZ; however, the molecular identities of the Abracl-expressing cell populations were not defined in that work. In this study, we use double immunofluorescence to characterize the expression of Abracl on sections of embryonic murine (E11.5-E18.5) and feline (E30/31-E33/34) telencephalon; to this end, we use a battery of well-known molecular markers of cycling (Ki67, Ascl1, Dlx2) or post-mitotic (Tubb3, Gad65/67, Lhx6 and Tbr1) cells. Our experiments show that Abracl protein has, compared to the mRNA, a broader expression domain, including, apart from proliferating cells of the subpallial and diencephalic SVZ, post-mitotic cells occupying the subpallial and pallial mantle (including the CP), as well as subpallial-derived migrating interneurons. Interestingly, in late embryonic developmental stages, Abracl was also transiently detected in major telencephalic fiber tracts.
Prevalence of Unfavorable Video-Urodynamic Findings and Clinical Implications in Patients with Minimally Conscious State/Unresponsive Wakefulness Syndrome: A Retrospective Descriptive Analysis
Authors: Leboutte Francois , Engesser Christian , Zahiti Leutrim , Rentsch Cyrill A. , Seifert Helge , Anding Ralf , Hund-Georgiadis Margret , Möhr Sandra , Walter Matthias
Published: August 2023

The aim of this retrospective exploratory study was to investigate the prevalence of unfavorable findings during video-urodynamic studies (VUDS) in patients with minimally conscious state (MCS)/unresponsive wakefulness syndrome (UWS) and whether management of the lower urinary tract (LUT) was adjusted accordingly. A retrospective chart review was conducted to screen for patients diagnosed with MCS/UWS at our rehabilitation center between 2011 and 2020. Patients 18 years or older were included and underwent baseline VUDS after being diagnosed with MCS/UWS. We analyzed urodynamic parameters and subsequent changes in LUT management in this cohort. In total, 32 patients (7 females, 25 males, median age 37 years) with MCS/UWS were included for analysis. While at least one unfavorable VUDS finding (i.e., neurogenic detrusor overactivity [NDO], detrusor sphincter dyssynergia {DSD, high maximum detrusor pressure during storage phase [>40 cmH2O], low-compliance bladder [<20 mL/cmH2O], and vesico–uretero–renal reflux [VUR]) was found in each patient, NDO (78.1%, 25/32) and DSD (68.8%, 22/32) were the two most frequent unfavorable VUDS findings. Following baseline VUDS, new LUT treatment options were established in 56.3% (18/32) of all patients. In addition, bladder-emptying methods were changed in 46.9% (15/32) of all patients, resulting in fewer patients relying on indwelling catheters. Our retrospective exploratory study revealed a high prevalence of NDO and DSD in patients with MCS/UWS, illustrating the importance of VUDS to adapt LUT management in this cohort accordingly.
Cut-off Value for Thyroglobulin Washout Concentration in the Detection of Cervical Lymph Node Metastases in Patients after Thyroidectomy Due to Differentiated Thyroid Cancer
Authors: Mikosiński Paweł , Wołowiec-Korecka Emilia , Pomorski Lech , Mikosińska Agnieszka , Kaczka Krzysztof , Mikosiński Sławomir
Published: August 2023

The aim of this study was to establish the cut-off value for the thyroglobulin (Tg) concentration in washout fluid from fine needle aspiration biopsy (FNA-Tg) in the detection of cervical lymph node metastases of differentiated thyroid cancer (DTC). We evaluated the validity and clinical utility of fine needle aspiration biopsy cytology (FNAB-C), FNA-Tg, and the combined method in detecting DTC recurrences. The study included 82 patients after the total thyroidectomy and elective and, in some cases, also selective cervical lymphadenectomy. The majority of patients also underwent subsequent 131I ablative therapy. The patients presented with 1–6 enlarged and/or ultrasonographically suspicious cervical lymph nodes. One to four aspirates of each lymph node were taken, with a total of 297 samples. An FNA-Tg of 4.34 ng/mL was established as the cut-off value for detecting cervical lymph node DTC metastases for the IRMA Brahms DYNO test, Tg-S. FNAB-C is highly specific (91–99%) but not sensitive enough (53–69%) to be used as a standalone method in the detection of cervical lymph node metastases. FNA-Tg is more sensitive (91%), but caution should be taken when selecting patients for surgery with an FNA-Tg higher than the established cut-off value but lower than the serum Tg concentration. To select patients for lymphadenectomy, we recommend using the combined method (FNAB-C and FNA-Tg) with a sensitivity of 96% and specificity of up to 97%. More than one sample should be taken with each fine needle aspiration biopsy (FNAB) to obtain a representative set of samples.
Mesenchymal Stem Cells Derived from Human Periapical Cysts and Their Implications in Regenerative Medicine
Authors: Roi Alexandra , Roi Ciprian , Negruțiu Meda Lavinia , Rusu Laura Cristina , Riviș Mircea
Published: August 2023

Mesenchymal stem cells currently play an important role in the tissue engineering field in developing new regenerative approaches. The oral cavity is a rich source of mesenchymal stem cells, and introducing the use of dental stem cells, characterized by a multilineage differentiation potential, immunomodulatory activity and repair capacity, offers a good perspective for clinical dentistry. Human periapical cyst mesenchymal stem cells (hPCy-MSCs) represent a new category of dental stem cells, being collected from pathological tissue and exhibiting MSCs-like properties. As studies have described, these new identified cells possess the same characteristics as those described in MSCs, exhibiting plasticity, a high proliferation rate and the potential to differentiate into osteogenic, adipogenic and neural lineages. Reusing the biological tissue that is considered pathologic offers a new perspective for the development of further clinical applications. The identification and characterization of MSCs in the human periapical cysts allows for a better understanding of the molecular interactions, the potential healing capacity and the mechanisms of inducing the local osteogenic process, integrated in the microenvironment. Although their involvement in regenerative medicine research is recent, they exhibit important properties that refer them for the development of clinical applications in dentistry.
Biomarkers for Kidney-Transplant Rejection: A Short Review Study
Authors: Sharaby Israa , Alksas Ahmed , Abou El-Ghar Mohamed , Eldeeb Mona , Ghazal Mohammed , Gondim Dibson , El-Baz Ayman
Published: August 2023

Kidney transplantation is the preferred treatment for end-stage renal failure, but the limited availability of donors and the risk of immune rejection pose significant challenges. Early detection of acute renal rejection is a critical step to increasing the lifespan of the transplanted kidney. Investigating the clinical, genetic, and histopathological markers correlated to acute renal rejection, as well as finding noninvasive markers for early detection, is urgently needed. It is also crucial to identify which markers are associated with different types of acute renal rejection to manage treatment effectively. This short review summarizes recent studies that investigated various markers, including genomics, histopathology, and clinical markers, to differentiate between different types of acute kidney rejection. Our review identifies the markers that can aid in the early detection of acute renal rejection, potentially leading to better treatment and prognosis for renal-transplant patients.
Multi-Center Real-World Outcomes of Nivolumab Plus Ipilimumab and Chemotherapy in Patients with Metastatic Non-Small-Cell Lung Cancer
Authors: Shalata Walid , Yakobson Alexander , Dudnik Yulia , Swaid Forat , Ahmad Mohammad Sheikh , Abu Jama Ashraf , Cohen Ahron Yehonatan , Agbarya Abed
Published: August 2023

Immune checkpoint inhibitors have become the standard of care in the treatment of metastatic non-small-cell lung cancer (NSCLC). The combination of nivolumab plus ipilimumab and chemotherapy has been shown to improve outcomes in terms of overall survival (OS) and progression-free survival (PFS). The aim of this study was to evaluate the outcomes of metastatic NSCLC treated in routine practice on the treatment regimen of the CheckMate 9LA protocol. Medical records of 58 patients treated at Soroka and Bnai Zion Medical Centers between May 2020 and February 2022 were analyzed. All patients were treated with a regimen of platinum-based chemotherapy combined with immunotherapy of nivolumab every three weeks and ipilimumab every 6 weeks. The patients received 2–3 cycles of chemotherapy according to the physician’s choice: platinum-based cisplatin or carboplatin with either pemetrexed or paclitaxel. The median PFS was 10.2 months, longer than that of the 9LA trial (6.7 months). Adenocarcinoma patients exhibited a higher median OS of 13.7 (range 5–33) months than squamous cell carcinoma (SCC) patients at 12.3 (5–20) months and PFS of 10.3 (4–33) months, while squamous cell carcinoma patients had a PFS of 9.2 (4–18) months. Patients whose programmed death ligand-1 (PD-L1) tumor expression level was ≥1% showed a higher median OS than those with PD-L1 expression of less than 1%. Treatment-related adverse events (TRAEs) were reported in 93.1% of patients, mostly grade 1 in severity. The first-line treatment of metastatic NSCLC patients in combination with nivolumab plus ipilimumab and chemotherapy can be given safely in routine clinical practice, with results comparable to those achieved in clinical trials of the regimen.
Conversion and Obsessive–Phobic Symptoms Predict IL-33 and IL-28A Levels in Individuals Diagnosed with COVID-19
Authors: Stoyanova Kristina , Stoyanov Drozdstoy , Petrov Steliyan , Baldzhieva Alexandra , Bozhkova Martina , Murdzheva Mariana , Kalfova Teodora , Andreeva Hristina , Taskov Hristo , Vassilev Petar , Todev Angel
Published: August 2023

The first epidemiological wave of the incidence of COVID-19 in Bulgaria was registered in June 2020. After the wave peak, we conducted a study in persons diagnosed with COVID-19 (N = 52). They were assessed with the anxiety–depressive scale (ADS), including basic (BS), vegetative (VS), conversion (CS), obsessive–phobic (OPS), and depressive (DS) symptoms. ADS assessment of individuals diagnosed with SARS-CoV-2 indicated a correlation between OPS and IL-33 values. IL-10 levels were higher than reference ranges in all patients. Multiple linear regression analyses demonstrated that combination of CS and OPS explained 28% of IL-33 levels, while combination of symptoms from all ADS dimensions explained 24% of IL-33 levels. It was also found that 21% of IL-28A levels was explained from the combination by all ADS dimensions, whereas OPS was the predictor for lower concentrations. The obtained results revealed meaningful correlations between psycho neuro–immunological factors in pathogenesis of illness from the coronavirus infection.
Optimal Cable Force Adjustment for Long-Span Concrete-Filled Steel Tube Arch Bridges: Real-Time Correction and Reliable Results
Authors: Yu Mengsheng , Yao Xinyu , Deng Nianchun , Hao Tianzhi , Wang Longlin , Wang Hua
Published: August 2023

For complex structures, the existing optimization method for suspender cable forces involves extensive matrix operations during the solution process, requiring high computational power and time. As a result, obtaining a more accurate solution becomes challenging. To address this issue and improve the stress distribution of suspenders in the completed state, while minimizing the need for frequent cable force adjustments and grid beam elevation changes during construction, a novel method for cable force optimization is proposed. In this study, the Pingnan Third Bridge, which is the world’s longest large span arch bridge with a span of 575 m, is taken as the engineering background. This study combines finite element analysis and multi-objective optimization methods to develop a cable force optimization approach for real-time correction during the panel girder lifting of long-span concrete-filled steel tube (CFST) arch bridges. The optimization method involves treating the panel girder weight and displacement during construction as parameter variables, and considering the displacement and unevenness of the panel girder in the completed state as constraint conditions. The objective equation is defined based on the displacement and cable force during the lifting construction process and, through optimization, the cable forces and displacements of each lifting section are calculated. The results demonstrate the feasibility of integrating optimization theory into the cable force optimization process during panel girder lifting. In this study, we have taken into account the characteristics of real-world engineering and focused on specific key points to reduce the order of the influence matrix. Consequently, the computational costs are reduced, facilitating the development of a multi-objective tension optimization program. By minimizing segment displacement variations and ensuring even cable force distribution in the completed state, the method ensures that the bridge meets the required completion requirements without the need for repetitive iterations or cumbersome calculations. It provides higher optimization efficiency and superior outcomes, offering significant value for cable force calculations during suspender construction of similar bridge types and guiding construction processes.