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Background: Physical fatigue and cognitive performance have been suggested as risk factors for an anterior cruciate ligament (ACL) injury, and fatigue has also been demonstrated to reduce cognitive processing. The combined effects of fatigue and lower cognitive function during cognitive-challenging movements may increase knee mechanics associated with the ACL injury risk. Hypotheses: We hypothesized that (1) knee mechanics would be detrimentally affected by fatigue and associated with baseline cognitive function and (2) fatigue-induced deleterious changes in cognitive performance and knee mechanics would be correlated. Study Design: Descriptive laboratory study. Methods: A total of 22 athletes completed baseline cognitive testing. After performing maximal vertical jumps, they performed a jump-land-jump task based on unanticipated visual cues. Then, they completed a fatigue protocol including countermovement jumps, among other tasks, until the jump height decreased below 90% of their assessed maximum. Immediately after reaching the first fatigue point, they performed another set of jump-landing tasks, followed by repeating the fatigue protocol until the jump height decreased below 85% of their assessed maximum. After reaching the second fatigue point, they performed a final set of jump-landing tasks and repeated the initial cognitive assessment battery. Results: Mixed-effects models revealed that knee flexion decreased through the fatigue protocol (baseline: 61.8°; midpoint: 61.1°; final: 60.1°; P =.003). Stepwise regression showed that fatigue-worsened attentional control corresponded to smaller knee abduction angles (R 2adjusted = 51.68%; βstandardized = 1.16; P =.001), and worse reaction time after fatigue correlated with increased knee abduction angles (βstandardized = 0.85; P =.006) after accounting for the role of attentional control. Conclusion: Fatigue induced incremental modifications in sagittal-plane knee mechanics during an unanticipated sports movement. In addition, fatigue induced changes in cognitive function related to ACL injury–relevant knee mechanics. Clinical Relevance: The novel findings regarding fatigue-dependent changes in injury-relevant biomechanics during cognitively challenging movements represent an extension of recent developments in understanding the role of cognition in the ACL injury risk. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG)-based motor imagery (MI) is one of brain computer interface (BCI) paradigms, which aims to build a direct communication pathway between human brain and external devices by decoding the brain activities. In a traditional way, MI BCI replies on a single brain, which suffers from the limitations, such as low accuracy and weak stability. To alleviate these limitations, multi-brain BCI has emerged based on the integration of multiple individuals’ intelligence. Nevertheless, the existing decoding methods mainly use linear averaging or feature integration learning from multi-brain EEG data, and do not effectively utilize coupling relationship features, resulting in undesired decoding accuracy. To overcome these challenges, we proposed an EEG-based multi-brain MI decoding method, which utilizes coupling feature extraction and few-shot learning to capture coupling relationship features among multi-brains with only limited EEG data. We performed an experiment to collect EEG data from multiple persons who engaged in the same task simultaneously and compared the methods on the collected data. The comparison results showed that our proposed method improved the performance by 14.23% compared to the single-brain mode in the 10-shot three-class decoding task. It demonstrated the effectiveness of the proposed method and usability of the method in the context of only small amount of EEG data available. [ABSTRACT FROM AUTHOR]

Recently, convolutional neural network (CNN)-based classification models have shown good performance for motor imagery (MI) brain-computer interfaces (BCI) using electroencephalogram (EEG) in end-to-end learning. Although a few explainable artificial intelligence (XAI) techniques have been developed, it is still challenging to interpret the CNN models for EEG-based BCI classification effectively. In this research, we propose 3D-EEGNet as a 3D CNN model to improve both the explainability and performance of MI EEG classification. The proposed approach exhibited better performances on two MI EEG datasets than the existing EEGNet, which uses a 2D input shape. The MI classification accuracies are improved around 1.8% and 6.1% point in average on the datasets, respectively. The permutation-based XAI method is first applied for the reliable explanation of the 3D-EEGNet. Next, to find a faster XAI method for spatio-temporal explanation, we design a novel technique based on the normalized discounted cumulative gain (NDCG) for selecting the best among a few saliency-based methods due to their higher time complexity than the permutation-based method. Among the saliency-based methods, DeepLIFT was selected because the NDCG scores indicated its results are the most similar to the permutation-based results. Finally, the fast spatio-temporal explanation using DeepLIFT provides deeper understanding for the classification results of the 3D-EEGNet and the important properties in the MI EEG experiments. [ABSTRACT FROM AUTHOR]

Recent advancements in immersive virtual reality head-mounted displays allowed users to better engage with simulated graphical environments. Having the screen egocentrically stabilized in a way such that the users may freely rotate their heads to observe virtual surroundings, head-mounted displays present virtual scenarios with rich immersion. With such an enhanced degree of freedom, immersive virtual reality displays have also been integrated with electroencephalograms, which make it possible to study and utilize brain signals non-invasively, to analyze and apply their capabilities. In this review, we introduce recent progress that utilized immersive head-mounted displays along with electroencephalograms across various fields, focusing on the purposes and experimental designs of their studies. The paper also highlights the effects of using immersive virtual reality discovered through the electroencephalogram analysis and discusses existing limitations, current trends as well as future research opportunities that may hopefully act as a useful source of information for further improvement of electroencephalogram-based immersive virtual reality applications. [ABSTRACT FROM AUTHOR]

Rural-dwelling individuals with dementia and their caregivers face unique challenges compared to urban-dwelling peers. Barriers to accessing services and supports are common, and individual resources and informal networks available to support rural families can be difficult to track for providers and healthcare systems outside of the local community. This study uses qualitative data from rural-dwelling dyads, individuals with dementia (n = 12) and informal caregivers (n = 18), to demonstrate how rural patients' daily life needs can be summarized through life-space map visualizations. Thirty semi-structured qualitative interviews were analyzed using a two-step process. First, rapid qualitative analysis was completed to generate daily-life needs of the participants' home and community context. Next, life-space maps were developed to synthesize and visualize dyads' met and unmet needs. Results suggest life-space mapping may offer a pathway for improved needs-based information integration for busy care providers and time-sensitive quality improvement efforts by learning healthcare systems. [ABSTRACT FROM AUTHOR]

Previous electroencephalogram (EEG) emotion recognition relies on single-task learning, which may lead to overfitting and learned emotion features lacking generalization. In this paper, a graph-based multi-task self-supervised learning model (GMSS) for EEG emotion recognition is proposed. GMSS has the ability to learn more general representations by integrating multiple self-supervised tasks, including spatial and frequency jigsaw puzzle tasks, and contrastive learning tasks. By learning from multiple tasks simultaneously, GMSS can find a representation that captures all of the tasks thereby decreasing the chance of overfitting on the original task, i.e., emotion recognition task. In particular, the spatial jigsaw puzzle task aims to capture the intrinsic spatial relationships of different brain regions. Considering the importance of frequency information in EEG emotional signals, the goal of the frequency jigsaw puzzle task is to explore the crucial frequency bands for EEG emotion recognition. To further regularize the learned features and encourage the network to learn inherent representations, contrastive learning task is adopted in this work by mapping the transformed data into a common feature space. The performance of the proposed GMSS is compared with several popular unsupervised and supervised methods. Experiments on SEED, SEED-IV, and MPED datasets show that the proposed model has remarkable advantages in learning more discriminative and general features for EEG emotional signals. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG)-based affective computing has a scarcity problem. As a result, it is difficult to build effective, highly accurate and stable models using machine learning algorithms, especially deep learning models. Data augmentation has recently shown performance improvements in deep learning models with increased accuracy, stability and reduced overfitting. In this paper, we propose a novel data augmentation framework, named the generative adversarial network-based self-supervised data augmentation (GANSER). As the first to combine adversarial training with self-supervised learning for EEG-based emotion recognition, the proposed framework generates high-quality and high-diversity simulated EEG samples. In particular, we utilize adversarial training to learn an EEG generator and force the generated EEG signals to approximate the distribution of real samples, ensuring the quality of the augmented samples. A transformation operation is employed to mask parts of the EEG signals and force the generator to synthesize potential EEG signals based on the unmasked parts to produce a wide variety of samples. A masking possibility during transformation is introduced as prior knowledge to generalize the classifier for the augmented sample space. Finally, numerous experiments demonstrate that our proposed method can improve emotion recognition with an increase in performance and achieve state-of-the-art results. [ABSTRACT FROM AUTHOR]

Epilepsy seizure (ES) monitoring and detection are only two examples of the many problems that may be addressed by combining the Internet of Medical Things (IoMT) with machine learning (ML) techniques and cloud computing services. Epilepsy, a potentially fatal neurological disorder, is a worldwide problem that poses a significant threat to human health. There is an urgent need for a reliable way of identifying epileptic seizures in their early stages to save thousands of epileptic patients every year. With the use of IoMT, several medical treatments, such as epileptic monitoring, diagnosis, and other procedures, may be performed remotely, hence lowering healthcare costs and enhancing service quality. EEG datasets have made use of feature importance-based data reduction to address the problem of a high number of data points and improve the delivery of service to the end user. In this article, we use the feature importance method by applying two popular machine learning techniques extra tree classifier (ETC) and the extreme gradient boosting classifier (XGBoost). Finally, the performance of a number of tests is evaluated using experimental data from Bonn University. Also achieved is a comparison of the two approaches used. The collected findings demonstrate the efficacy of the XGBoost technique and its greater accuracy in comparison to the ETC strategy. [ABSTRACT FROM AUTHOR]

One of the main research questions concerning multi-word expressions (MWEs) is which of them are transparent word combinations created ad hoc and which are multi-word lexical units (MWUs). In this paper, we use selected corpus-linguistic and machine-learning methods to determine which lexicalization criteria guide Polish and English lexicographers in deciding which MWEs (bigrams such as adjective+noun and noun+noun combinations) should be treated as lexical units recorded in dictionaries as MWUs. We analyzed two samples: MWEs extracted from Polish and English monolingual dictionaries, and those created by the annotators, and tested two custom-designed criteria, i.e., intuition and paraphrase, also by using statistical methods (measures of collocational strength: PMI and Jaccard). We revealed that Polish lexicographers have a tendency not to include compositional MWEs as lexical entries in their dictionaries and that the criteria of paraphrase and intuition are important for them: if MWEs are not clearly and unambiguously paraphrasable and compositional, then they are recorded in dictionaries. We found that in contrast to Polish lexicographers English lexicographers tend to record also compositional and partly compositional MWEs. [ABSTRACT FROM AUTHOR]

Emotional content is particularly salient, but situational factors such as cognitive load may disturb the attentional prioritization towards affective stimuli and interfere with their processing. In this study, 31 autistic and 31 typically developed children volunteered to assess their perception of affective prosodies via event-related spectral perturbations of neuronal oscillations recorded by electroencephalography under attentional load modulations induced by Multiple Object Tracking or neutral images. Although intermediate load optimized emotion processing by typically developed children, load and emotion did not interplay in children with autism. Results also outlined impaired emotional integration emphasized in theta, alpha and beta oscillations at early and late stages, and lower attentional ability indexed by the tracking capacity. Furthermore, both tracking capacity and neuronal patterns of emotion perception during task were predicted by daily-life autistic behaviors. These findings highlight that intermediate load may encourage emotion processing in typically developed children. However, autism aligns with impaired affective processing and selective attention, both insensitive to load modulations. Results were discussed within a Bayesian perspective that suggests atypical updating in precision between sensations and hidden states, towards poor contextual evaluations. For the first time, implicit emotion perception assessed by neuronal markers was integrated with environmental demands to characterize autism. [ABSTRACT FROM AUTHOR]

In qualitative research, there is a growing interest in understanding the use of timelines in combination with other qualitative methods. In this paper, we will address how the creation of timelines facilitated and informed the process of semi-structured interviews. We used an interpretive descriptive qualitative study to understand the perceptions and experiences of developing sexuality among female adolescents of Pakistani descent, and timelines were used as a part of the semi-structured interview process. Timelines were created in a participatory way in which girls were asked to recount significant events related to their sexuality. We found that the methodological combinations within qualitative research such as semi-structured interviews and timelines have the potential to advance knowledge regarding the experience of immigrant female adolescents’ sexuality. Using the timeline strategy to collect data helped in building rapport with the participants, allowed the participants to become active partners and navigate the process, and helped them to think about future resolutions through reflection. [ABSTRACT FROM AUTHOR]

Objective: To identify and describe factors which impact user engagement in reablement from the perspectives of reablement staff, staff in interfacing services, service users and family members. Sample and Methods: A total of 78 staff were recruited from five sites across England and Wales. Twelve service users and five family members were recruited from three of these sites. Data were collected via focus groups with staff and interviews with service users and families, and subject to thematic analysis. Results: The data revealed a complex picture of factors potentially impacting user engagement, ranging from user-, family-, and staff-centered factors, the nature of the relationship between staff and users, and aspects of service organization and delivery across referral and intervention pathways. Many are amenable to intervention. As well as offering a more fine-grained understanding of factors reported by previous research, new factors impacting engagement were identified. These included staff morale, equipment provision systems, assessment and reviewing processes, and attention to social reablement needs. Aspects of the wider service context (eg, degree of integration of health and social care) played a role in determining which factors were pertinent. Conclusion: Findings highlight the complexity of factors influencing engagement with reablement, and the need to ensure features of the wider service context (eg delivery models, referral pathways) do not work against securing and sustaining older people's engagement with reablement. [ABSTRACT FROM AUTHOR]

Background: Lactate, a byproduct of glucose metabolism, is primarily utilized for gluconeogenesis and numerous cellular and organismal life processes. Interestingly, many studies have demonstrated a correlation between lactate metabolism and tumor development. However, the relationship between long non-coding RNAs (lncRNAs) and lactate metabolism in papillary thyroid cancer (PTC) remains to be explored. Methods: Lactate metabolism-related lncRNAs (LRLs) were obtained by differential expression and correlation analyses, and the risk model was further constructed by least absolute shrinkage and selection operator analysis (Lasso) and Cox analysis. Clinical, immune, tumor mutation, and enrichment analyses were performed based on the risk model. The expression level of six LRLs was tested using RT-PCR. Results: This study found several lncRNAs linked to lactate metabolism in both The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets. Using Cox regression analysis, 303 lactate LRLs were found to be substantially associated with prognosis. Lasso was done on the TCGA cohort. Six LRLs were identified as independent predictive indicators for the development of a PTC prognostic risk model. The cohort was separated into two groups based on the median risk score (0.39717 -0.39771). Subsequently, Kaplan-Meier survival analysis and multivariate Cox regression analysis revealed that the high-risk group had a lower survival probability and that the risk score was an independent predictive factor of prognosis. In addition, a nomogram that can easily predict the 1-, 3-, and 5-year survival rates of PTC patients was established. Furthermore, the association between PTC prognostic factors and tumor microenvironment (TME), immune escape, as well as tumor somatic mutation status was investigated in high- and low-risk groups. Lastly, gene expression analysis was used to confirm the differential expression levels of the six LRLs. Conclusion: In conclusion, we have constructed a prognostic model that can predict the prognosis, mutation status, and TME of PTC patients. The model may have great clinical significance in the comprehensive evaluation of PTC patients. [ABSTRACT FROM AUTHOR]

In developed countries, digital technologies are disrupting every facet of students' lives. It is no longer an option to turn off devices and disconnect from the outside world at the school gate. Educators are struggling with the number of technologies being introduced and how to safely and effectively integrate these tools in classrooms that have no boundaries. In an era where it seems that each child takes central place on the world stage; always connecting, learning, creating and sharing, it is timely to investigate the experiences of technology-rich 10–14 years old Australian students' experiences with technology in everyday life, and reflect on the persisting challenges and the new possibilities being created by the myriad choices of technological tools and their uses. The purposive selection of the participants was based on the volunteers' daily access to personal devices and frequent use of applications and various online platforms. This inductive qualitative study used concept mapping as a tool for conducting research and thematic analysis to identify and explore patterns in the data. Our findings reveal the formation of a fluid and hybrid digital rhizomatic non-hierarchical and multiplicitous network that allows students to connect, think, act, interact, access ideas and resources in ways that may assist educators in closing the gap between formal learning and informal learning whilst living in a rich technology world. [ABSTRACT FROM AUTHOR]

Obesity and elevated blood free fatty acid (FFA) levels lead to impaired insulin action causing insulin resistance in skeletal muscle, and contributing to the development of type 2 diabetes mellitus (T2DM). Mechanistically, insulin resistance is associated with increased serine phosphorylation of the insulin receptor substrate (IRS) mediated by serine/threonine kinases including mTOR and p70S6K. Evidence demonstrated that activation of the energy sensor AMP-activated protein kinase (AMPK) may be an attractive target to counteract insulin resistance. We reported previously that rosemary extract (RE) and the RE polyphenol carnosic acid (CA) activated AMPK and counteracted the FFA-induced insulin resistance in muscle cells. The effect of rosmarinic acid (RA), another polyphenolic constituent of RE, on FFA-induced muscle insulin resistance has never been examined and is the focus of the current study. Muscle cell (L6) exposure to FFA palmitate resulted in increased serine phosphorylation of IRS-1 and reduced insulin-mediated (i) Akt activation, (ii) GLUT4 glucose transporter translocation, and (iii) glucose uptake. Notably, RA treatment abolished these effects, and restored the insulin-stimulated glucose uptake. Palmitate treatment increased the phosphorylation/activation of mTOR and p70S6K, kinases known to be involved in insulin resistance and RA significantly reduced these effects. RA increased the phosphorylation of AMPK, even in the presence of palmitate. Our data indicate that RA has the potential to counteract the palmitate-induced insulin resistance in muscle cells, and further studies are required to explore its antidiabetic properties. [ABSTRACT FROM AUTHOR]

Background: Osteosarcoma is the most common primary bone tumor, its high incidence of metastasis and poor prognosis have led to a great deal of concern for osteosarcoma. In many cancer types, metabolic processes are important for tumor growth progression, so interfering with the metabolic processes of osteosarcoma may be a therapeutic option to stall osteosarcoma progression. A key mechanism of how metabolic processes contribute to the growth and survival of various cancers, including osteosarcoma, is their ability to support tumor cell metabolism. Research related to this field is a direction of great importance and potential. However, to our knowledge, no bibliometric studies related to this field have been published, and we will fill this research gap. Methods: Publications were retrieved on January 1, 2023 from the 1990-2022 Science Citation Index of the Web of Science Core Collection. The Bibliometrix package in R software, VOSviewer and CiteSpace software were used to analyze our research directions and to visualize global trends and hotspots in osteosarcoma and metabolism related research. Results: Based on the search strategy, 833 articles were finally filtered. In this area of research related to osteosarcoma metabolism, we found that China, the United States and Japan are the top 3 countries in terms of number of articles published, and the journals and institutions that have published the most research in this area are Journal of bone and mineral research, Shanghai Jiao Tong University. In addition, Baldini, Nicola, Reddy, Gs and Avnet, Sofia are the top three authors in terms of number of articles published in studies related to this field. The most popular keywords related to the field in the last 30 years are "metabolism" and "expression", which will guide the possible future directions of the field. Conclusion: We used Bibliometrix, VOSviewer, and Citespace to visualize and bibliometrically analyze the current status and possible future hotspots of research in the field of osteosarcoma metabolism. Possible future hotspots in this field may focus on the related terms "metabolism", "expression", and "migraation". [ABSTRACT FROM AUTHOR]

In medical mycology, the main context of disease is iatrogenic-based disease. However, historically, and occasionally, even today, fungal diseases affect humans with no obvious risk factors, sometimes in a spectacular fashion. The field of "inborn errors of immunity" (IEI) has deduced at least some of these previously enigmatic cases; accordingly, the discovery of single-gene disorders with penetrant clinical effects and their immunologic dissection have provided a framework with which to understand some of the key pathways mediating human susceptibility to mycoses. By extension, they have also enabled the identification of naturally occurring auto-antibodies to cytokines that phenocopy such susceptibility. This review provides a comprehensive update of IEI and autoantibodies that inherently predispose humans to various fungal diseases. [ABSTRACT FROM AUTHOR]

Symmetry belongs to one of the basic principles of the beauty of human and non-human objects since antiquity. Even though its significance has been verified by numerous theories and research studies, there is a number of papers suggesting that this principle may be false. The study identifies five major evolutionary principles, in the context of new approaches and research ambiguities based mainly on neuroscience and evolutionary psychology, that support the thesis that highlights the significance of symmetry in the perception and assessment of attractiveness: 1. symmetry as an honest signal of various health characteristics; 2. symmetry as proof of developmental stability; 3. effectiveness; 4. comprehensibility; 5. predictability. In the context of the mechanisms described above it also seeks possible explanations for the existence of contradictory research results related to the attractiveness of symmetry. The outcome of the study is the postulation of three hypotheses: 1. the naturalness hypothesis (symmetry is only attractive to the same degree that it naturally occurs in the subject); 2. the accent hypothesis (minor asymmetries do not disprove the principles of symmetry, they make them more visible); 3. the ecology hypothesis (the attractiveness of symmetry is conditioned by the situation and depends on the type of subject assessed) that allow us to integrate both past and contemporary (and putatively contradictory) research findings. The paper also provides proposals for the verification of the postulated hypotheses. [ABSTRACT FROM AUTHOR]

Performances of metabolomic methods have been widely studied on biological matrices such as serum, plasma, and urine; but much less on in vitro cell extracts. While the impact of cell culture and sample preparation on results are well-described, the specific effect of the in vitro cellular matrix on the analytical performance remains uncertain. The aim of the present work was to study the impact of this matrix on the analytical performance of an LC-HRMS metabolomic method. For this purpose, experiments were performed on total extracts from two cell lines (MDA-MB-231 and HepaRG) using different cell numbers. Matrix effects, carryover, linearity, and variability of the method were studied. Results showed that the performances of the method depend on the nature of the endogenous metabolite, the cell number, and the nature of the cell line. These three parameters should, therefore, be considered for the processing of experiments and the interpretation of results depending on whether the study focuses on a limited number of metabolites or aims to establish a metabolic signature. [ABSTRACT FROM AUTHOR]

Badminton is very popular on college campuses. In badminton, the anterior cruciate ligament of the players has a higher risk of injury. There are many studies investigating the impact of fatigue on the injury of professional athletes, but few studies focused on college students. We hypothesized that the knee joint would experience greater ground reaction forces, valgus moments, and flexion moments of lunge contact in amateur after fatigue than those indicators before fatigue. Ten male badminton amateurs were enrolled in this study. They performed a lunge to hit the shuttlecock at the designated position and then quickly returned to the starting position before and after fatigue. Fatigue was induced by repeated isokinetic flexion/extension of the knee. Lower body kinematics and ground reaction force (GRF) were collected and further used to calculate the lower body joint moments from initial contact to maximum knee flexion. Compared to the pre-fatigue condition, the peak flexion moment (p = 0.012) and peak abduction moment of knee joint (p = 0.01), and maximum horizontal ground reaction force (p = 0.027) increased significantly at the initial contact (p = 0.01). After muscle fatigue, the knee buckling moment and valgus moment increased significantly at initial contact, and the horizontal backward maximum GRF also increased significantly. These changes might increase the injury risk of anterior cruciate ligament (ACL). The fatigue of the muscles around the knee joint did not change the maximum GRF in the vertical direction at the moment of contact. Combined with the results of our study, badminton coaches and teachers should increase the training of lower extremity muscle strength and endurance in our daily class and training, and also should pay special attention to the coordinated development of muscles. [ABSTRACT FROM AUTHOR]

Canine cognitive dysfunction (CCD) is a progressive neurodegenerative condition that presents many of the behavioral and pathological changes seen in human Alzheimer's dementia. It typically causes significant long-term suffering in both the patient and the caretaker. In patients with CCD and Alzheimer's disease (AD), conventional dietary therapy has been helpful in preventing and slowing cognitive decline. Chinese medical food therapy to balance the body may also be beneficial in these patients. This paper will discuss conventional dietary intervention in dogs, along with traditional Chinese food therapy (CFT) according to pattern diagnosis in CCD. It is possible that a combination of syndrome differentiation in CFT and conventional nutritional therapy may help improve cognition and quality of life in patients with CCD. [ABSTRACT FROM AUTHOR]

Vitamin D deficiency can damage the human immune system, and the complement system is a key component of the immune system. This study aimed to elucidate the mechanism by which vitamin D affects the immune system by analyzing the changes in the protein expression of the complement system under different vitamin D levels. We selected 40 participants and divided them into three groups according to their serum levels of 25-hydroxyvitamin D (25(OH)VD): group A, 25(OH)VD ≥ 40 ng/mL; group B, 30 ng/mL ≤ 25(OH)VD < 40 ng/mL; and group C, 25(OH)VD < 30 ng/mL. Serum samples were subjected to biochemical analysis, followed by proteomic analysis using high-throughput untargeted proteomic techniques. Vitamin D deficiency increased the levels of fasting blood sugar, fasting serum insulin, and homeostasis model assessment (HOMA) of insulin resistance and decreased the secretion of HOMA of β-cell function, which led to insulin resistance and glucose metabolism disorder. Moreover, vitamin D deficiency resulted in the abnormal expression of 56 differential proteins, among which the expression levels of complement factor B, complement component C9, inducible co-stimulator ligand, and peptidase inhibitor 16 significantly changed with the decrease in vitamin D content. Functional enrichment analysis of these differential proteins showed that they were mainly concentrated in functions and pathways related to insulin secretion and inflammation. In conclusion, vitamin D deficiency not only contributes to insulin resistance and glucose metabolism disorder but also causes abnormal protein expression, resulting in the abnormal activation of the complement system. This study provides a novel theoretical basis for further studies on the relationship between vitamin D and the immune system. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is the most common malignancy in women worldwide. While the main systemic treatment option is anthracycline-containing chemotherapy, chemoresistance continues to be an obstacle to patient survival. Carnitine palmitoyltransferase 1C (CPT1C) has been described as a poor-prognosis marker for several tumour types, as it favours tumour growth and hinders cells from entering senescence. At the molecular level, CPT1C has been associated with lipid metabolism regulation and important lipidome changes. Since plasma membrane (PM) rigidity has been associated with reduced drug uptake, we explored whether CPT1C expression could be involved in PM remodelling and drug chemoresistance. Liquid chromatography-high resolution mass spectrometry (LC-HRMS) lipid analysis of PM-enriched fractions of MDA-MB-231 BC cells showed that CPT1C silencing increased PM phospholipid saturation, suggesting a rise in PM rigidity. Moreover, CPT1C silencing increased cell survival against doxorubicin (DOX) treatment in different BC cells due to reduced drug uptake. These findings, further complemented by ROC plotter analysis correlating lower CPT1C expression with a lower pathological complete response to anthracyclines in patients with more aggressive types of BC, suggest CPT1C as a novel predictive biomarker for BC chemotherapy. [ABSTRACT FROM AUTHOR]

Symmetry perception studies have generally used two stimulus types: figural and dot patterns. Here, we designed a novel figural stimulus—a wedge pattern—made of centrally aligned pseudorandomly positioned wedges. To study the effect of pattern figurality and colour on symmetry perception, we compared symmetry detection in multicoloured wedge patterns with nonfigural dot patterns in younger and older adults. Symmetry signal was either segregated or nonsegregated by colour, and the symmetry detection task was performed under two conditions: with or without colour-based attention. In the first experiment, we compared performance for colour-symmetric patterns that varied in the number of wedges (24 vs. 36) and number of colours (2 vs. 3) and found that symmetry detection was facilitated by attention to colour when symmetry and noise signals were segregated by colour. In the second experiment, we compared performance for wedge and dot patterns on a sample of younger and older participants. Effects of attention to colour in segregated stimuli were magnified for wedge compared with dot patterns, with older and younger adults showing different effects of attention to colour on performance. Older adults significantly underperformed on uncued wedge patterns compared with dot patterns, but their performance improved greatly through colour cueing, reaching performance levels similar to young participants. Thus, while confirming the age-related decline in symmetry detection, we found that this deficit could be alleviated in figural multicoloured patterns by attending to the colour that carries the symmetry signal. [ABSTRACT FROM AUTHOR]

Research on embodiment of objects external to the human body has revealed important information about how the human nervous system interacts with robotic lower limb exoskeletons. Typical robotic exoskeleton control approaches view the controllers as an external agent intending to move in coordination with the human. However, principles of embodiment suggest that the exoskeleton controller should ideally coordinate with the human such that the nervous system can adequately model the input-output dynamics of the exoskeleton controller. Measuring embodiment of exoskeletons should be a necessary step in the exoskeleton development and prototyping process. Researchers need to establish high fidelity quantitative measures of embodiment, rather than relying on current qualitative survey measures. Mobile brain imaging techniques, such as high-density electroencephalography, is likely to provide a deeper understanding of embodiment during human-machine interactions and advance exoskeleton research and development. In this review we show why future exoskeleton research should include quantitative measures of embodiment as a metric of success. [ABSTRACT FROM AUTHOR]

For practical motor imagery (MI) brain-computer interface (BCI) applications, generating a reliable model for a target subject with few MI trials is important since the data collection process is labour-intensive and expensive. In this paper, we address this issue by proposing a few-shot learning method called temporal episode relation learning (TERL). TERL models MI with only limited trials from the target subject by the ability to compare MI trials through episode-based training. It can be directly applied to a new user without being re-trained, which is vital to improve user experience and realize real-world MIBCI applications. We develop a new and effective approach where, unlike the original episode learning, the temporal pattern between trials in each episode is encoded during the learning to boost the classification performance. We also perform an online evaluation simulation, in addition to the offline analysis that the previous studies only conduct, to better understand the performance of different approaches in real-world scenario. Extensive experiments are completed on four publicly available MIBCI datasets to evaluate the proposed TERL. Results show that TERL outperforms baseline and recent state-of-the-art methods, demonstrating competitive performance for subject-specific MIBCI where few trials are available from a target subject and a considerable number of trials from other source subjects. [ABSTRACT FROM AUTHOR]

Cognitive loads have been shown to influence anterior cruciate ligament (ACL) injury risk. Two main sources of cognitive loads that athletes experience are decision making and dividing attention between multiple tasks. The aim of this paper was to review previous studies examining the effects of decision making and divided attention on lower limb biomechanics during landing and cutting. Previous research has shown decision making to significantly influence a number of biomechanical variables associated with increased risk of ACL injury, such as reduced knee flexion at initial contact, increased knee valgus angles, increased knee extension moment and increased knee valgus moment in decision-making tasks compared to pre-planned tasks. Furthermore, dividing attention between multiple tasks has been shown to result in reduced knee flexion at initial contact, increased vertical ground reaction force, and reduced stability during landing/cutting. The changes in lower limb biomechanics observed as a result of both decision making and dividing attention are likely due to a reduced ability to anticipate ground contact and implement protective movement patterns associated with reduced ACL loading. Collectively, these findings emphasise the need for tasks that incorporate decision making and divided attention when investigating ACL injury mechanisms and developing ACL injury risk screening assessments. [ABSTRACT FROM AUTHOR]

Can objective trust indicators be measured and computed in real time in a within visual range aerial combat "dogfight" scenario consisting of a manned autonomous own-ship versus an adversary? Previous research has focused on human trust of automation during simulated ground combat and human trust of civil aviation automation. Those studies largely consisted of subjective measures of trust analyzed post-hoc. Human trust of autonomy in high-risk situations such as dogfighting had not yet been studied. Nine evaluation pilots participated in an experiment that consisted of nine operationally relevant live-flight vignettes during which they conducted a mission manager task while simultaneously monitoring an autonomous agent controlling their own-ship in an aerial dogfight. Eye tracking, objective real-time mental workload, and mission manager task performance were all recorded. Potential indicators of trust were objectively measured in real-time as a function of autonomy disengagement, human cross-check ratio of autonomy, and real-time objective mental workload, as validated by traditional subjective trust measures. Measured trust still needs to be categorized as appropriate trust, overtrust, or undertrust in future work. This first-ever real-time measure of objective indicators of trust in operationally relevant live-flight paves the way for determining appropriate human trust of autonomy in high-risk situations such as dogfighting. These measures could have utility in high-risk manned-unmanned teaming applications such as working with robots and automated trading. [ABSTRACT FROM AUTHOR]

Planar, orthogonal structures are very common in man-made environments. We often interact with rectangular structures such as doors and walls in our environment. When a rigid, rectangular structure rotates about a pivot axis, there is information in the ambient optic array, that specifies what the rotating structure affords to the observer. Previous studies identified optical information available to detect the position of the axis of rotation of rotating panels and the current study empirically verifies that observers are sensitive to that information. In one desktop-based experiment and two immersive virtual reality experiments, participants indicated the location of the pivot axis of a rotating panel, as quickly and accurately as possible. Factors like texture on the panel, texture on the background, position of axis of rotation, and linear velocity of the farthest edge from the pivot axis were manipulated. Results indicate that participants were sensitive to texture information associated with invariants specifying the axis of rotation. The results suggest the importance of texture information in vision and how optical invariants help us to directly perceive affordances in built environments. [ABSTRACT FROM AUTHOR]

Deep learning for automated interictal epileptiform discharge (IED) detection has been topical with many published papers in recent years. All existing works viewed EEG signals as time-series and developed specific models for IED classification; however, general time-series classification (TSC) methods were not considered. Moreover, none of these methods were evaluated on any public datasets, making direct comparisons challenging. This paper explored two state-of-the-art convolutional-based TSC algorithms, InceptionTime and Minirocket, on IED detection. We fine-tuned and cross-evaluated them on a public (Temple University Events — TUEV) and two private datasets and provided ready metrics for benchmarking future work. We observed that the optimal parameters correlated with the clinical duration of an IED and achieved the best area under precision-recall curve (AUPRC) of 0.98 and F1 of 0.80 on the private datasets, respectively. The AUPRC and F1 on the TUEV dataset were 0.99 and 0.97, respectively. While algorithms trained on the private sets maintained their performance when tested on the TUEV data, those trained on TUEV could not generalize well to the private data. These results emerge from differences in the class distributions across datasets and indicate a need for public datasets with a better diversity of IED waveforms, background activities and artifacts to facilitate standardization and benchmarking of algorithms. [ABSTRACT FROM AUTHOR]

In virtual reality (VR), established perception–action relationships break down because of conflicting and ambiguous sensorimotor inputs, inducing walking velocity underestimations. Here, we explore the effects of realigning perceptual sensory experiences with physical movements via augmented feedback on the estimation of virtual speed. We hypothesized that providing feedback about speed would lead to concurrent perceptual improvements and that these alterations would persist once the speedometer was removed. Ten young adults used immersive VR to view a virtual hallway translating at a series of fixed speeds. Participants were tasked with matching their walking speed on a self-paced treadmill to the optic flow in the environment. Information regarding walking speed accuracy was provided during augmented feedback trials via a real-time speedometer. We measured resulting walking velocity errors, as well as kinematic gait parameters. We found that the concordance between the virtual environment and gait speeds was higher when augmented feedback was provided during the trial. Furthermore, we observed retention effects beyond the intervention period via demonstrated smaller errors in speed perception accuracy and stronger concordance between perceived and actual speeds. Together, these results highlight a potential role for augmented feedback in guiding gait strategies that deviate away from predefined internal models of locomotion. [ABSTRACT FROM AUTHOR]

Tumour metabolomics and transcriptomics co-expression network as related to biological folate alteration and cancer malignancy remains unexplored in human non-small cell lung cancers (NSCLC). To probe the diagnostic biomarkers, tumour and pair lung tissue samples (n = 56) from 97 NSCLC patients were profiled for ultra-performance liquid chromatography tandem mass spectrometry (UPLC/MS/MS)-analysed metabolomics, targeted transcriptionomics, and clinical folate traits. Weighted Gene Co-expression Network Analysis (WGCNA) was performed. Tumour lactate was identified as the top VIP marker to predict advance NSCLC (AUC = 0.765, Sig = 0.017, CI 0.58–0.95). Low folate (LF)-tumours vs. adjacent lungs displayed higher glycolytic index of lactate and glutamine-associated amino acids in enriched biological pathways of amino sugar and glutathione metabolism specific to advance NSCLCs. WGCNA classified the green module for hub serine-navigated glutamine metabolites inversely associated with tumour and RBC folate, which module metabolites co-expressed with a predominant up-regulation of LF-responsive metabolic genes in glucose transport (GLUT1), de no serine synthesis (PHGDH, PSPH, and PSAT1), folate cycle (SHMT1/2 and PCFR), and down-regulation in glutaminolysis (SLC1A5, SLC7A5, GLS, and GLUD1). The LF-responsive WGCNA markers predicted poor survival rates in lung cancer patients, which could aid in optimizing folate intervention for better prognosis of NSCLCs susceptible to folate malnutrition. [ABSTRACT FROM AUTHOR]

While computer-mediated user studies tend to rely on surveys, observations, focus groups, and ethnography, participant-generated mental model diagrammatic representation can yield valuable data involving complex and abstract user practices and behaviour. Computer-mediated research has struggled with eliciting users' beliefs of concrete representations in technology interactions. Using an investigation of authentication and user perceptions of security, we tested a method to elicit user mental model representations. We asked this overarching question: What are user perceptions of security when logging in to third-party apps and services via existing Facebook, Google, and Twitter accounts? Drawing from approaches to researching technology from the sub-fields of human-computer interaction, user studies, visual and risk communication, while incorporating methodological techniques from psychology on mental models, we offer a methodological innovation. We found evidence suggesting that a diagrammatic approach to representing mental models is feasible in addressing some of the challenges faced by existing computer-mediated approaches. [ABSTRACT FROM AUTHOR]

The alpha and theta frequency brainwave activity in electroencephalogram (EEG) signal is proven to correlate with attention, inhibitory processes, memory, perceptual abilities, and sleep. The decreasing of brainwaves is demonstrated to be the reason of aging and even Alzheimer's disease, so triggering alpha and theta brainwave activity may bring positive behavioral modifications such as promoting health care and a quick sleep. Herein, it is discovered that infrared radiation from multilayer graphene electrothermal film can obviously promote the appearance of alpha and theta brainwaves in the human brain. In particular, the occurrence frequency and duration time of the alpha and theta waves in EEG can be effectively enhanced up to 2.3/2.9 and 3.0/4.1 times, respectively. The comparative effect of different working temperatures and heating materials is systematically investigated, indicating efficient infrared radiation from the multilayer graphene electrothermal film, which coincides with the human‐body thermal‐radiation wavelength range from 7 to 14 μm, may be the main mechanism for this enhancement. The multilayer graphene film electrical heater represents a convenient and surprising way for triggering alpha and theta brainwaves, which has many potential applications in the area of enlarged healthcare requirements. [ABSTRACT FROM AUTHOR]

Simple Summary: Lung cancer remains the first cause of cancer worldwide. The main reason for this high rate of death from lung cancer is dissemination of the disease at the time of presentation to hospital due to late diagnosis. The aim of this article is to review and assess the effectiveness of different techniques, currently in use and that are upcoming, in early detection of lung cancer. We will present and evaluate the principles of developing such techniques and how to overcome challenges frequently facing researchers in the field of early lung cancer detection. Improvement in early detection would lower the rate of death and the societal burden of this often lethal condition. Worldwide, lung cancer (LC) is the most common cause of cancer death, and any delay in the detection of new and relapsed disease serves as a major factor for a significant proportion of LC morbidity and mortality. Though invasive methods such as tissue biopsy are considered the gold standard for diagnosis and disease monitoring, they have several limitations. Therefore, there is an urgent need to identify and validate non-invasive biomarkers for the early diagnosis, prognosis, and treatment of lung cancer for improved patient management. Despite recent progress in the identification of non-invasive biomarkers, currently, there is a shortage of reliable and accessible biomarkers demonstrating high sensitivity and specificity for LC detection. In this review, we aim to cover the latest developments in the field, including the utility of biomarkers that are currently used in LC screening and diagnosis. We comment on their limitations and summarise the findings and developmental stages of potential molecular contenders such as microRNAs, circulating tumour DNA, and methylation markers. Furthermore, we summarise research challenges in the development of biomarkers used for screening purposes and the potential clinical applications of newly discovered biomarkers. [ABSTRACT FROM AUTHOR]

Objective: This study examined therapists' dispositional empathy profiles and how they differ based on professional and personal characteristics., Method: A total of 376 clinicians was recruited for this study. Dispositional empathy was assessed with the Interpersonal Reactivity Index (IRI). Profiles were generated using latent profile analysis. Predictors of profiles were assessed with multiple self-report questionnaires measuring demographic and professional characteristics, romantic attachment styles, five-factor personality traits and vulnerable narcissism., Results: A four-profile solution was retained with the following proportions: rational empathic (20%), disengaged/detached (10%), empathic immersion (35%) and insecure/self-absorbed (35%). Overall, few relationships were found regarding demographic and professional characteristics. In contrast, significant relationships were found between profile membership and personal characteristics, including avoidant and anxious attachment, agreeableness, conscientiousness, neuroticism, intellect/imagination and vulnerable narcissism., Conclusion: The findings show that differences in therapists' empathic dispositions are linked to personality dimensions. Implications for psychotherapy research, practice and training are discussed., (© 2024 John Wiley & Sons Ltd.)

In the literature on the safety of ursodeoxycholic acid (UDCA) during breastfeeding, insufficient data has been reported to date. Thus, the aim of our study was to analyze bile acid (BA) concentrations in breast milk in a cohort of patients, treated with UDCA, and with various cholestatic liver diseases. The study was carried out on a cohort of 20 patients with various cholestatic diseases. All the patients were treated with UDCA (500–1500 mg daily). Concentrations of BA, sampled on day 3 after delivery were analyzed using the GS-MS technique, and then compared to untreated women. Total BA concentrations in the breast milk of the UDCA-treated patients were equal to those of the untreated women controls (3.2 ± 1 vs. 3.2 ± 0.2 µmol/L, respectively). The UDCA concentrations in breast milk remained negligible in UDCA-treated patients (0.69 µmol/L), and in any event did not contribute to the newborn BA pool. No apparent side-effects of the maternal UDCA treatment were observed in any newborn infant, and no deterioration in postnatal development was observed during the routine 1-year follow-ups. Therapeutic administration of UDCA during lactation is safe for breastfed babies since UDCA only gets into breast milk in negligible amounts. UDCA treatment should be allowed and included into the guidelines for the therapy of cholestatic diseases in breastfeeding mothers. [ABSTRACT FROM AUTHOR]

Cancer cells reprogram their metabolism to support growth and invasion. While previous work has highlighted how single altered reactions and pathways can drive tumorigenesis, it remains unclear how individual changes propagate at the network level and eventually determine global metabolic activity. To characterize the metabolic lifestyle of cancer cells across pathways and genotypes, we profiled the intracellular metabolome of 180 pan‐cancer cell lines grown in identical conditions. For each cell line, we estimated activity for 49 pathways spanning the entirety of the metabolic network. Upon clustering, we discovered a convergence into only two major metabolic types. These were functionally confirmed by 13C‐flux analysis, lipidomics, and analysis of sensitivity to perturbations. They revealed that the major differences in cancers are associated with lipid, TCA cycle, and carbohydrate metabolism. Thorough integration of these types with multiomics highlighted little association with genetic alterations but a strong association with markers of epithelial–mesenchymal transition. Our analysis indicates that in absence of variations imposed by the microenvironment, cancer cells adopt distinct metabolic programs which serve as vulnerabilities for therapy. Synopsis: Metabolomics and computational analysis of 180 cell lines grown under the same condition reveals the activity of over 45 metabolic pathways and identifies two major metabolic types. Metabolic activity, termed pathway scores, was inferred from metabolite levels.The emergence of only two conserved intrinsic metabolic types reveals that the major differences in the metabolism of cancers are associated with lipid and carbohydrate metabolism.Each metabolic type has a different sensitivity to gene knock‐out and drug response, matching their metabolic program which was confirmed by 13C labeling.Omics integration reveals that the main determinant of metabolic types is their epithelial‐mesenchymal transition status. [ABSTRACT FROM AUTHOR]

During development, hematopoietic stem cells (HSCs) are produced from the hemogenic endothelium and will expand in a transient hematopoietic niche. Prostaglandin E2 (PGE2) is essential during vertebrate development and HSC specification, but its precise source in the embryo remains elusive. Here, we show that in the zebrafish embryo, PGE2 synthesis genes are expressed by distinct stromal cell populations, myeloid (neutrophils, macrophages), and endothelial cells of the caudal hematopoietic tissue. Ablation of myeloid cells, which produce the PGE2 precursor prostaglandin H2 (PGH2), results in loss of HSCs in the caudal hematopoietic tissue, which could be rescued by exogeneous PGE2 or PGH2 supplementation. Endothelial cells contribute by expressing the PGH2 import transporter slco2b1 and ptges3, the enzyme converting PGH2 into PGE2. Of note, differential niche cell expression of PGE2 biosynthesis enzymes is also observed in the mouse fetal liver. Taken altogether, our data suggest that the triad composed of neutrophils, macrophages, and endothelial cells sequentially and synergistically contributes to blood stem cell expansion during vertebrate development. Synopsis: The microenvironmental signals supporting hematopoietic stem cell (HSC) expansion during development in the hemogenic endothelium and specific niche cell contributions remain debated. Here, biosynthesis of the critical HSC control factor prostaglandin E2 (PGE2) is shown to be functionally divided across stromal cell populations, shedding new light on stem cell niche cooperation in establishing the blood system.PGE2 production enzymes are distinctly expressed in neutrophils, myeloid and endothelial cells in the zebrafish caudal hematopoietic niche.Depletion of the transporter Slco2b1 or myeloid cells impairs import of the PGE2 precursor PGH2 into endothelial cells and HSC expansion, which can be rescued by exogeneous PGE2.Niche distribution of PGE2 biosynthesis enzymes is conserved in the mouse fetal liver. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Few studies have evaluated the effect of phenobarbital (PB) on elevated direct bilirubin (DB) plasma concentrations in neonates and infants, and none have compared its effect with a control group with matched study baseline DB values. The purpose of this study was to quantify changes in elevated DB plasma concentrations (=2 mg/dL) in neonates and infants between a PB-treated and control group. METHODS: A retrospective, observational, matched, cohort study was performed comparing patients between a PB-treated group and a control group with similar study baseline plasma DB values =2 mg/dL over an 8-week period. The percent change in DB plasma concentrations from study baseline was compared for each week of the study period. RESULTS: During the 8-year study period, 310 patients had DB plasma concentrations =2 mg/dL, of which 26 remained in each group after exclusions. The PB group had increased DB concentrations and the control group had decreased DB concentrations when compared with their study baseline DB concentrations each week of the study period. By study end, the mean DB concentration increased by 11.2% in the PB group and decreased by 48.5% in the control group (p = 0.02). In multiple regression analysis, only birth weight (standardized coefficient = 0.44, p = 0.02), and gastrointestinal obstruction (standardized coefficient = -0.4, p = 0.03) were associated with significant percent change in DB concentrations. CONCLUSIONS: This study demonstrated PB does not improve cholestasis in neonates and infants. [ABSTRACT FROM AUTHOR]