Assessing immune responses to cytomegalovirus (CMV) after liver transplant in patients on immunosuppressive therapy remains challenging. In this study, employing ELISPOT assays, 52 liver-transplant recipients were evaluated for antiviral T-cell activity in peripheral blood mononuclear cells (PBMCs), measuring interferon-γ (IFN-γ) secretion upon stimulation with CMV-specific peptides (CMV peptide pool, CMV IE-1, and pp65 antigens). Parameters such as stimulation index, mean spot size, and mean spot count were measured. The study found that heightened immunosuppression, especially with prednisolone in triple therapy, significantly dampened CMV-specific immune responses. This was demonstrated by decreased IFN-γ production by CMV-specific T-cells (CMV peptide pool: p = 0.036; OR = 0.065 [95% CI: 0.005–0.840], pp65 antigen: p = 0.026; OR = 0.048 [95% CI: 0.003–0.699]). Increased immunosuppression correlated with reduced IFN-γ secretion per cell, reflected in smaller mean spot sizes for the CMV peptide pool (p = 0.019). Notably, shorter post-transplant intervals correlated with diminished antiviral T-cell IFN-γ release at two years (CMV peptide pool: p = 0.019; IE antigen: p = 0.010) and five years (CMV peptide pool: p = 0.0001; IE antigen: p = 0.002; pp65 antigen: p = 0.047), as did advancing age (pp65 antigen: p = 0.016, OR = 0.932, 95% CI: 0.881–0.987). Patients with undetectable CMV antigens had a notably higher risk of CMV reactivation within six months from blood collection, closely linked with triple immunosuppression and prednisolone use. These findings highlight the intricate interplay between immunosuppression, immune response dynamics, and CMV reactivation risk, emphasizing the necessity for tailored immunosuppressive strategies to mitigate CMV reactivation in liver-transplant recipients. It can be concluded that, particularly in the early months post-transplantation, the use of prednisolone as a third immunosuppressant should be critically reconsidered. Additionally, the use of prophylactic antiviral therapy effective against CMV in this context holds significant importance. Full article

In recent years, machine learning models have become a potential approach in accurately predicting the concrete compressive strength, which is essential for the real-world application of geopolymer concrete. However, the precursor system of geopolymer concrete is known to be more heterogeneous compared to Ordinary Portland Cement (OPC) concrete, adversely affecting the data generated and the performance of the models. To its advantage, data enrichment through deep learning can effectively enhance the performance of prediction models. Therefore, this study investigates the capability of tabular generative adversarial networks (TGANs) to generate data on mixtures and compressive strength of geopolymer concrete. It assesses the impact of using synthetic data with various models, including tree-based, support vector machines, and neural networks. For this purpose, 930 instances with 11 variables were collected from the open literature. In particular, 10 variables including content of fly ash, slag, sodium silicate, sodium hydroxide, superplasticizer, fine aggregate, coarse aggregate, added water, curing temperature, and specimen age are considered as inputs, while compressive strength is the output of the models. A TGAN was employed to generate an additional 1000 data points based on the original dataset for training new predictive models. These models were evaluated on real data test sets and compared with models trained on the original data. The results indicate that the developed models significantly improve performance, particularly neural networks, followed by tree-based models and support vector machines. Moreover, data characteristics greatly influence model performance, both before and after data augmentation. Full article

Different excavation methods lead to substantial changes in the relaxation zone of the surrounding rock. The stress characteristics of the support structure become more complex during the process of excavation method conversion. It is essential to design a well-considered construction plan to minimize the disruptions caused by excavation method conversion. This work takes a tunnel in Jiangsu Province, China, as the engineering background and establishes a numerical model for the conversion from the double-side-drift method to the three-bench method. Based on a numerical investigation, this study analyzed the deformation of surrounding rock and the stress state of the support structure during the excavation method conversion. The results showed that excavation method conversion can accelerate the deformation rate of the surrounding rock, causing the support structure to bear greater pressure. This leads to a significant increase in the circumferential stress at the junction of two excavation methods. Setting up a reinforced area during the process of excavation method conversion can improve the stress state of the support structure. Finally, an analysis of the parameters of the reinforced area was conducted, and a reasonable construction plan was proposed. This study can provide guidance for subsequent construction projects. Full article

This article describes a tool that can be used to improve the effectiveness of the ISCO (in situ chemical oxidation) method. It is an Excel-based application that uses Visual Basic, PHREEQC, and Python. The main functions are feedback control solutions. There are several ideas that can optimise ISCO treatment when using the geochemical model: (i) looping real-time data into the geochemical model and using them to estimate the actual rate, (ii) using spatial distribution maps for delineating zones that are susceptible or resistant to oxidation, (iii) visualising the permanganate consumption that could indicate the right time for further action, and (iv) using alarm reports of the abnormal physico-chemical conditions that jeopardise successful injection. Full article

Owing to the development of technology, the majority of nations throughout the world now rely on fossil fuels and nuclear power plants to meet their energy needs. However, as academic research on this subject has shown, it has become clear that alternative energy uses are necessary due to the gradual depletion of these fuels and their significant negative effects on the environment. In order to ensure energy diversity and end the energy shortage, the development of renewable energy sources is crucial. The prediction of wind power is crucial for effectively utilizing the potential of wind energy. In this study, an adaptive neuro-fuzzy inference system (ANFIS) and an artificial neural network (ANN) have been developed for the prediction of wind power. In this study, data sets were created by taking the daily average wind speeds of the selected wind turbine, the daily average power values it produces, and the daily average wind speed values in the Velimese region. By creating single-hidden layer and multi-hidden layer ANN models, the network was trained multiple times with different activation functions and different numbers of neurons, and wind power prediction was performed. In the ANFIS model, the number of membership functions is kept constant, and wind power prediction is performed using different membership functions. With these ANFIS and ANN models developed with different parameter combinations, it is aimed to determine the most efficient model by performing daily average wind power prediction. Parameter combinations were tested to determine the appropriate models, and as a result, the ANN and ANFIS models were compared with each other. Full article

With the rapid development of automobiles, energy shortages and environmental pollution have become a growing concern. In order to decrease the energy consumption of electric vehicles (EVs), this study aims to improve EV efficiency with AMT and dual-motor systems. Firstly, the paper establishes an Automated Manual Transmission (AMT) model for EVs, which is then simulated using MATLAB R2022a software. In order to eliminate the impact of gear ratio selection, the genetic algorithm is used to optimize the AMT gear ratios. Meanwhile, a dual-motor EV model is constructed, and three different torque distribution schemes are simulated and analyzed. The results indicate that due to the elongation of the energy transmission chain in AMT-equipped EVs, energy losses increase, leading to some improvement in optimized power consumption. However, these EVs remain inferior to those with only a single-stage main reducer. The study also found that the torque distribution based on optimal efficiency further improves results. Full article

Primary progressive apraxia of speech (PPAOS) is a neurodegenerative syndrome characterized by the progressive and initially isolated or predominant onset of difficulties in the planning/programming of movements necessary for speech production and can be accompanied by dysarthria. To date, no study has used an evidence-based treatment to address phonation control in patients with PPAOS. The aim of this study was to evaluate the feasibility and efficacy of LSVT LOUD^® as a treatment for phonatory control in speakers with PPAOS. Three speakers with PPAOS received LSVT LOUD^® therapy, and changes in phonatory control, voice quality and prosody were measured immediately, and one, four and eight weeks after the end of the treatment. Overall, the results suggest that the treatment is feasible and could improve voice quality, intensity, and control in some patients with PPAOS. The generalization of the results is also discussed. Full article

This paper presents a comprehensive study on ultra-high-performance concrete (UHPC) beams without stirrups, where the test data of 487 beams were collected, and an experimental database was established. Four distinct shear strength calculation models for UHPC beams were examined in the study. These models were created from national specification guides. The results indicate that while the code equation is useful for predicting UHPC beam shear capacity, it consistently underestimates actual values, with a mean experimental-to-calculated ratio above 1.5. The database was also used to study the impacts of the compressive strength of UHPC, the shear span-to-depth ratio, the fiber volume fraction, and the reinforcement ratio on the shear strength of UHPC beams. The findings showed that the shear span-to-depth ratio significantly affected the shear load-bearing capacity of UHPC beams. The increase in the compressive strength of UHPC, fiber volume fraction, and reinforcement ratio positively affected the shear strength of UHPC beams to varying degrees. Additionally, there were size effects for beams with a shear span-to-depth ratio of less than 1.5 and an effective depth of more than 300. In addition, coefficients accounting for fiber influence and the shear span-to-depth ratio were incorporated to develop an enhanced formula for UHPC beams. The empirical data from the database tests revealed that the average ratio of the beams’ experimental shear capacity to the values predicted by the modified equation is 1.3, with a standard deviation of 0.74. These results suggest that the refined equation offers improved calculation precision and broader applicability. Eventually, a summary of the issues pertaining to the shear performance of UHPC beams and the key future research directions is provided to facilitate a clearer comprehension and awareness of emerging concepts for scholars within the discipline. Full article

SARS-CoV-2, the causative agent of the ongoing COVID-19 pandemic, has revealed a broader impact beyond the respiratory system, predominantly affecting the vascular system with various adverse manifestations. The infection induces endothelial dysfunction and immune system dysregulation, creating an inflammatory and hypercoagulable state. It affects both microvasculature and macrovasculature, leading to thromboembolic events, cardiovascular manifestations, impaired arterial stiffness, cerebrovascular complications, and nephropathy, as well as retinopathy—frequently observed in cases of severe illness. Evidence suggests that SARS-CoV-2 infection may result in persistent effects on the vascular system, identified as long-term COVID-19. This is characterized by prolonged inflammation, endotheliopathy, and an increased risk of vascular complications. Various imaging modalities, histopathological studies, and diagnostic tools such as video capillaroscopy and magnetic resonance imaging have been employed to visualize vascular alterations. This review aims to comprehensively summarize the evidence concerning short and long-term vascular alterations following COVID-19 infection, investigating their impact on patients’ prognosis, and providing an overview of preventive strategies to mitigate associated vascular complications. Full article

Colombia hosts the largest number of refugees and migrants fleeing the humanitarian emergency in Venezuela, many of whom experience high levels of displacement-related trauma and adversity. Yet, Colombian mental health services do not meet the needs of this population. Scalable, task-sharing interventions, such as Group Problem Management Plus (Group PM+), have the potential to bridge this gap by utilizing lay workers to provide the intervention. However, the current literature lacks a comprehensive understanding of how and for whom Group PM+ is most effective. This mixed methods study utilized data from a randomized effectiveness-implementation trial to examine the mediators and moderators of Group PM+ on mental health outcomes. One hundred twenty-eight migrant and refugee women in northern Colombia participated in Group PM+ delivered by trained community members. Patterns in moderation effects showed that participants in more stable, less marginalized positions improved the most. Results from linear regression models showed that Group PM+-related skill acquisition was not a significant mediator of the association between session attendance and mental health outcomes. Participants and facilitators reported additional possible mediators and community-level moderators that warrant future research. Further studies are needed to examine mediators and moderators contributing to the effectiveness of task-shared, scalable, psychological interventions in diverse contexts. Full article

Initially reported as pneumonia of unknown origin, COVID-19 is increasingly being recognized for its impact on the nervous system, despite nervous system invasions being extremely rare. As a result, numerous studies have been conducted to elucidate the mechanisms of nervous system damage and propose appropriate coping strategies. This review summarizes the mechanisms by which SARS-CoV-2 invades and damages the central nervous system, with a specific focus on aspects apart from the immune response and inflammatory storm. The latest research findings on these mechanisms are presented, providing new insights for further in-depth research. Full article

Magnetic resonance (MR) with sodium (²³Na) is a noninvasive tool providing quantitative biochemical information regarding physiology, cellular metabolism, and viability, with the potential to extend MR beyond anatomical proton imaging. However, when using clinical scanners, the low detectable ²³Na signal and the low ²³Na gyromagnetic ratio require the design of dedicated radiofrequency (RF) coils tuned to the ²³Na Larmor frequency and sequences, as well as the development of dedicated phantoms for testing the image quality, and an MR scanner with multinuclear spectroscopy (MNS) capabilities. In this work, we propose a hardware and software setup for evaluating the potential of ²³Na magnetic resonance imaging (MRI) with a clinical scanner. In particular, the reliability of the proposed setup and the reproducibility of the measurements were verified by multiple acquisitions from a 3T MR scanner using a homebuilt RF volume coil and a dedicated sequence for the imaging of a phantom specifically designed for evaluating the accuracy of the technique. The final goal of this study is to propose a setup for standardizing clinical and research ²³Na MRI protocols. Full article

Object recognition algorithms and datasets based on point cloud data have been mainly designed for autonomous vehicles. When applied to the construction industry, they face challenges due to the origin of point cloud data from large earthwork sites, resulting in high volumes of data and density. This research prioritized the development of 3D point cloud datasets specifically for heavy construction equipment, including dump trucks, rollers, graders, excavators, and dozers; all of which are extensively used in earthwork sites. The aim was to enhance the efficiency and productivity of machine learning (ML) and deep learning (DL) research that relies on 3D point cloud data in the construction industry. Notably, unlike conventional approaches to acquiring point cloud data using UAVs (Unmanned Aerial Vehicles) and UGVs (Unmanned Ground Vehicles), the datasets for the five types of heavy construction equipment established in this research were generated using 3D-scanned diecast models of heavy construction equipment to create point cloud data. Full article

The expression of polysialic acid (polySia) on the neuronal cell adhesion molecule (NCAM) is called NCAM-polysialylation, which is strongly related to the migration and invasion of tumor cells and aggressive clinical status. Thus, it is important to select a proper drug to block tumor cell migration during clinical treatment. In this study, we proposed that lactoferrin (LFcinB11) may be a better candidate for inhibiting NCAM polysialylation when compared with CMP and low-molecular-weight heparin (LMWH), which were determined based on our NMR studies. Furthermore, neutrophil extracellular traps (NETs) represent the most dramatic stage in the cell death process, and the release of NETs is related to the pathogenesis of autoimmune and inflammatory disorders, with proposed involvement in glomerulonephritis, chronic lung disease, sepsis, and vascular disorders. In this study, the molecular mechanisms involved in the inhibition of NET release using LFcinB11 as an inhibitor were also determined. Based on these results, LFcinB11 is proposed as being a bifunctional inhibitor for inhibiting both NCAM polysialylation and the release of NETs. Full article

With increasing numbers of parents choosing to home-school their child, currently there is very limited information about how this is implemented. Utilizing the recently developed Parents’ Perceptions of Home-Schooling scale (PPHS), a survey of 93 home-schooling parents in Western Australia was undertaken. Data were collected using five Likert scales to obtain information concerned with a range of implementation aspects. Key findings were related to the process for registering and providing an appropriate learning program, the role of the home-educator moderator, the type of study and support utilized, and whether the student had a disability or ALNs. The discussion considers links to inclusion and how the heightened uptake of home-schooling can be monitored effectively. Full article

Previous studies on consumer perceptions and behaviors of salmon have often neglected Indigenous rights within the Canadian salmon sector. This study innovatively addresses this gap by integrating Indigenous rights into the current analysis, alongside considerations of sustainability practices, socio-economic impacts, and consumer motivations. Our research objectives aim to fit three consumer perceptions—environmental sustainability, economic considerations, and Indigenous rights—and to evaluate their associations, alongside perception of a price increase, socio-demographics, and consumer motivation factors, with purchasing behaviors related to Canadian salmon products. Data for this study was collected from a nationwide online survey. Responses to Question 2 and Question 35 are encoded with numerical values ranging from 1 to 5, where larger numbers indicate stronger agreement with the statement. The inclusion of methodologies such as the Graded Response Model (GRM) and Cumulative Link Models (CLM) adds another innovative dimension to this study. Our findings demonstrate how consumer profiles are associated with these four perceptions and their underlying determinants. Furthermore, the study quantifies the influence of these four perceptions on each consumer purchase behavior. The implications of these findings extend to the realm of mathematical modeling in consumer decision-making processes, offering practical insights for businesses and marketers, and emphasizing the importance of implementing regulatory frameworks and initiatives that promote sustainability, safeguard Indigenous rights, and address socio-economic disparities. Full article

Aiming at effectively generating safe and reliable motion paths for quadruped robots, a hierarchical path planning approach driven by dynamic 3D point clouds is proposed in this article. The developed path planning model is essentially constituted of two layers: a global path planning layer, and a local path planning layer. At the global path planning layer, a new method is proposed for calculating the terrain potential field based on point cloud height segmentation. Variable step size is employed to improve the path smoothness. At the local path planning layer, a real-time prediction method for potential collision areas and a strategy for temporary target point selection are developed. Quadruped robot experiments were carried out in an outdoor complex environment. The experimental results verified that, for global path planning, the smoothness of the path is improved and the complexity of the passing ground is reduced. The effective step size is increased by a maximum of 13.4 times, and the number of iterations is decreased by up to 1/6, compared with the traditional fixed step size planning algorithm. For local path planning, the path length is shortened by 20%, and more efficient dynamic obstacle avoidance and more stable velocity planning are achieved by using the improved dynamic window approach (DWA). Full article

Based on the data of Sichuan Province from 2007 to 2021, the extreme climate events in Sichuan Province was identified by statistical method, and the coupling coordination degree of water resources-climate system and separate water resource system was analyzed. Based on the difference of coupling coordination degree under these two systems, the influence mechanism of extreme climate factors on the water resource system is analyzed. The results show that the extreme climate types in Sichuan Province gradually transition from extreme drought to extreme precipitation and from extreme low temperature to extreme high temperature. When climate factors are not considered, the coupling coordination degree of the water resource system is generally improved and the distribution is more concentrated. Moreover, the influence of climate factors on the water resource system is not a simple linear relationship. Full article

The objective of this study was to analyze the prognostic factors that influence the outcome of periapical surgery. A systematic search of the literature was carried out using PubMed and Scopus databases between January 2000 and December 2023 with no language limitations. The PICO question of the present systematic review was: What prognostic factors may influence the outcome of periapical surgery? The most relevant randomized controlled clinical trials (RCTs), prospective clinical trials, retrospective studies, and meta-analyses (n = 44) were selected from 134 articles. The reviewed literature evidenced that bone-lesion healing could significantly be improved by the absence of deep periodontal pockets (>4 mm), localization in anterior teeth, the absence of pain and/or preoperative symptoms, a size of bone lesion < 5 mm, the use of ultrasound, the correct placement of retrograde filling material, and the use of different biomimetic membranes for guided tissue regeneration (GTR). Some preoperative and intraoperative factors could significantly improve the prognosis of periapical surgery. However, these results were not conclusive, and further high-quality research is required. Full article

Background: Loss of the p53-inducible LINC01021 in p53-proficient CRC cell lines results in increased sensitivity to DNA-damaging chemotherapeutics. Here, we comprehensively analyze how LINC01021 affects the p53-induced transcriptional program. Methods: Using a CRISPR/Cas9-approach, we deleted the p53 binding site in the LINC01021 promoter of SW480 colorectal cancer cells and subjected them to RNA-Seq analysis after the activation of ectopic p53. RNA affinity purification followed by mass spectrometry was used to identify proteins associated with LINC01021. Results: Loss of the p53-inducibility of LINC01021 resulted in an ~1.8-fold increase in the number of significantly regulated mRNAs compared to LINC01021 wild-type cells after ectopic activation of p53. A subset of direct p53 target genes, such as NOXA and FAS, displayed significantly stronger induction when the p53-inducibility of LINC01021 was abrogated. Loss of the p53-inducibility of LINC01021 resulted in alternative splicing of a small number of mRNAs, such as ARHGAP12, HSF2, and LYN. Several RNA binding proteins involved in pre-mRNA splicing were identified as interaction partners of LINC01021 by mass spectrometry. Conclusions: Our results suggest that LINC01021 may restrict the extent and strength of p53-mediated transcriptional changes via context-dependent regulation of the expression and splicing of a subset of p53-regulated genes. Full article

The COVID-19 pandemic has underscored the critical need for the advancement of diagnostic and therapeutic platforms. These platforms rely on the rapid development of molecular binders that should facilitate surveillance and swift intervention against viral infections. In this study, we have evaluated by three independent research groups the binding characteristics of various published RNA and DNA aptamers targeting the spike protein of the SARS-CoV-2 virus. For this comparative analysis, we have employed different techniques such as biolayer interferometry (BLI), enzyme-linked oligonucleotide assay (ELONA), and flow cytometry. Our data show discrepancies in the reported specificity and affinity among several of the published aptamers and underline the importance of standardized methods, the impact of biophysical techniques, and the controls used for aptamer characterization. We expect our results to contribute to the selection and application of suitable aptamers for the detection of SARS-CoV-2. Full article

Flexible electronics, also referred to as printable electronics, represent an interesting technology for implementing electronic circuits via depositing electronic devices onto flexible substrates, boosting their possible applications. Among all flexible electronics, interdigitated electrodes (IDEs) are currently being used for different sensor applications since they offer significant benefits beyond their functionality as capacitors, like the generation of high output voltage, fewer fabrication steps, convenience of application of sensitive coatings, material imaging capability and a potential of spectroscopy measurements via electrical excitation frequency variation. This review examines the role of IDEs in printed and flexible electronics since they are progressively being incorporated into a myriad of applications, envisaging that the growth pattern will continue in the next generations of flexible circuits to come. Full article