Small Bowel Perforation Due to Renal Carcinoma Metastasis: A Comprehensive Case Study and Literature Review.

This case report presents a unique instance of small bowel perforation caused by solitary metastasis from renal cell carcinoma (RCC), a rare and complex clinical scenario. The patient, a 59-year-old male with a history of RCC treated with nephrectomy four years prior, presented with acute abdomen symptoms. Emergency diagnostic procedures identified a significant lesion in the small intestine. Surgical intervention revealed a perforated jejunal segment due to metastatic RCC. Postoperatively, the patient developed complications, including pneumonia and multi-organ failure, leading to death 10 days after surgery. Histopathological analysis confirmed the metastatic nature of the lesion. This case underscores the unpredictable nature of RCC metastasis and highlights the need for vigilance in post-nephrectomy patients. The rarity of small bowel involvement by RCC metastasis, particularly presenting as perforation, makes this case a significant contribution to medical literature, emphasizing the challenges in the diagnosis and management of such atypical presentations.

High task demand in dual-target paradigm redirects experimentally increased anxiety to uphold goal-directed attention.

Previous research has shown that state anxiety facilitates stimulus-driven attentional capture and impairs goal-directed attentional control by increasing sensitivity to salient distractors or threat cues or narrowing spatial attention. However, recent findings in this area have been mixed, and less is known about how state-dependent anxiety may affect attentional performance. Here, we employed a novel dual-target search paradigm to investigate this relationship. This paradigm allowed us to investigate attentional control and how focus narrows under different anxiety states. Participants watched a short movie-either anxiety-inducing or neutral-before engaging in the dual-target visual search task. We found that they performed faster and more accurately in trials without the salient distractor compared to those with distractors, and they performed better in tasks presented on the center than the periphery. However, despite a significant increase in self-reported anxiety in the anxiety-inducing session, participants' performance in terms of speed and accuracy remain comparable across both anxious and neutral sessions. This resilience is likely due to compensatory mechanisms that offset anxiety, a result of the high demands and working memory load inherent in the dual-target task.

Tuning attention based long-short term memory neural networks for Parkinson's disease detection using modified metaheuristics.

Parkinson's disease (PD) is a progressively debilitating neurodegenerative disorder that primarily affects the dopaminergic system in the basal ganglia, impacting millions of individuals globally. The clinical manifestations of the disease include resting tremors, muscle rigidity, bradykinesia, and postural instability. Diagnosis relies mainly on clinical evaluation, lacking reliable diagnostic tests and being inherently imprecise and subjective. Early detection of PD is crucial for initiating treatments that, while unable to cure the chronic condition, can enhance the life quality of patients and alleviate symptoms. This study explores the potential of utilizing long-short term memory neural networks (LSTM) with attention mechanisms to detect Parkinson's disease based on dual-task walking test data. Given that the performance of networks is significantly inductance by architecture and training parameter choices, a modified version of the recently introduced crayfish optimization algorithm (COA) is proposed, specifically tailored to the requirements of this investigation. The proposed optimizer is assessed on a publicly accessible real-world clinical gait in Parkinson's disease dataset, and the results demonstrate its promise, achieving an accuracy of 87.4187 % for the best-constructed models.

Task-irrelevant valence-preferred colors boost visual search for a singleton-shape target.

Some studies have suggested that emotion-associated features might influence attentional capture. However, demonstrating valence-dependent distractor interference has proven challenging, possibly due to the neglect of individuals' color-valence preferences in standard, averaged reaction-time (RT) measures. To address this, we investigated valence-driven attentional-capture using an association phase in which emotionally neutral vs. positive-feedback photographs were paired with two alternative target colors, red vs. green. This was followed by a test phase requiring participants to search for a pop-out shape target in the presence or absence of an emotion-associated color. In Experiments 1 and 2, this color could only appear in a distractor, while in Experiment 3, it appeared in the target. Analyzing the standard, averaged RT measures, we found no significant valence association or valence-modulated attentional capture. However, correlational analyses revealed a positive relationship between individual participants' color-valence preference during the association phase and their valence-based effect during the test phase. Moreover, most individuals favored red over green in the association phase, leading to marked color-related asymmetries in the average measures. Crucially, the presence of the valence-preferred color anywhere in the test display facilitated RTs. This effect persisted even when the color appeared in one of the distractors (Experiments 1 and 2), at variance with this distractor capturing attention. These findings suggest that task-irrelevant valence-preferred color signals were registered pre-attentively and boosted performance, likely by raising the general (non-spatial) alertness level. However, these signals were likely kept out of attentional-priority computation to prevent inadvertent attentional capture.

International youth mental health case study of peer researchers' experiences.

BACKGROUND: The involvement of young people as peer researchers, especially with lived experience, is increasingly considered important in youth mental health research. Yet, there is variation in the understanding of the role, and limited evidence on its implementation across different research systems. This case study focusses on the barriers and enablers of implementing peer researcher roles within and across majority world countries contexts. METHODS: Based on an international youth mental health project involving different levels of peer researchers and participants from eight countries, peer researchers and a co-ordinating career researcher reflect on lessons regarding enabling and challenging factors. These reflections are captured and integrated by a systematic insight analysis process. RESULTS: Building on existing international networks, it was feasible to actively involve peer researchers with lived experience in a multi-country mental health study, who in turn recruited and engaged young participants. Identified challenges include the terminology and definition of the role, cultural differences in mental health concepts, and consistency across countries and sites. DISCUSSION: Peer researchers' role could be strengthened and mainstreamed in the future through ongoing international networks, training, sufficient planning, and active influence throughout the research process. TRIAL REGISTRATION: Not applicable.

The involvement of young people with lived experience as collaborators (peer researchers) in mental health research has become more prominent in recent years. Yet, there is variation in the understanding of this role and how to involve young people. There is also limited evidence on how this role can be applied across different research systems, especially in majority world countries. We share our experience from a youth mental health project involving peer researchers in eight countries. Peer researchers and the co-ordinating career researcher reflected on lessons regarding enabling and challenging factors. Their reflections highlighted that, overall, it is feasible to successfully involve young people with lived experience in international mental health research. Several challenges were also identified, including terminology, definition of roles, cultural differences in understanding mental health, and consistency across participating countries and sites. According to peer researchers' reflections, these challenges can be overcome through the establishment of ongoing international networks, training and support, sufficient planning and peer researchers getting involved at all the stages of the research. Lessons from this case study can be of interest to the international research community in strengthening the involvement of young people in mental health research.

Goal setting with young people for anxiety and depression: What works for whom in therapeutic relationships? A literature review and insight analysis.

BACKGROUND: Goal setting and goal-focused work is widely used in young people's mental health settings. However, little is known about how, why or for whom this is helpful. This study aims to explore the mechanisms of collaborative goal setting as part of therapeutic relationships: is it helpful for young people experiencing anxiety and/or depression, how and why/not, for whom, and under what circumstances? METHODS: Online database searches generated 10,907 records. Seven unique studies are included, combined with insight analysis from directed discussions with international advisors with lived experience of anxiety and/or depression and therapy (N = 8; mean age = 20.8), and mental health academics/clinicians (N = 6). RESULTS: Findings are presented as a narrative synthesis and suggest that goal setting is helpful to young people experiencing anxiety and/or depression because it helps build good therapeutic relationships through open communication and building trust. Goal setting helps make things more manageable, enabling young people to feel supported and have ownership of their care. Individual preferences, or high levels of distress, trauma, low confidence, hopelessness, negative past experiences of goal setting, perfectionism, and rumination are considered limiting factors to goal setting. Additionally, contextual factors including country and long-term therapy are explored. CONCLUSION: Whilst the resultant sample is small, emphasis on the voices of young people in the research is both prominent and of paramount importance. Several key literature gaps are identified, including evidenced links to the reduction in symptoms. Priority must be given to researching unhelpful mechanisms of goal setting for young people experiencing anxiety and/or depression, to avoid any potential iatrogenic effects.

Deep Learning Based SWIR Object Detection in Long-Range Surveillance Systems: An Automated Cross-Spectral Approach.

SWIR imaging bears considerable advantages over visible-light (color) and thermal images in certain challenging propagation conditions. Thus, the SWIR imaging channel is frequently used in multi-spectral imaging systems (MSIS) for long-range surveillance in combination with color and thermal imaging to improve the probability of correct operation in various day, night and climate conditions. Integration of deep-learning (DL)-based real-time object detection in MSIS enables an increase in efficient utilization for complex long-range surveillance solutions such as border or critical assets control. Unfortunately, a lack of datasets for DL-based object detection models training for the SWIR channel limits their performance. To overcome this, by using the MSIS setting we propose a new cross-spectral automatic data annotation methodology for SWIR channel training dataset creation, in which the visible-light channel provides a source for detecting object types and bounding boxes which are then transformed to the SWIR channel. A mathematical image transformation that overcomes differences between the SWIR and color channel and their image distortion effects for various magnifications are explained in detail. With the proposed cross-spectral methodology, the goal of the paper is to improve object detection in SWIR images captured in challenging outdoor scenes. Experimental tests for two object types (cars and persons) using a state-of-the-art YOLOX model demonstrate that retraining with the proposed automatic cross-spectrally created SWIR image dataset significantly improves average detection precision. We achieved excellent improvements in detection performance in various variants of the YOLOX model (nano, tiny and x).

Distributed Spectrum Management in Cognitive Radio Networks by Consensus-Based Reinforcement Learning.

In this paper, we propose a new algorithm for distributed spectrum sensing and channel selection in cognitive radio networks based on consensus. The algorithm operates within a multi-agent reinforcement learning scheme. The proposed consensus strategy, implemented over a directed, typically sparse, time-varying low-bandwidth communication network, enforces collaboration between the agents in a completely decentralized and distributed way. The motivation for the proposed approach comes directly from typical cognitive radio networks' practical scenarios, where such a decentralized setting and distributed operation is of essential importance. Specifically, the proposed setting provides all the agents, in unknown environmental and application conditions, with viable network-wide information. Hence, a set of participating agents becomes capable of successful calculation of the optimal joint spectrum sensing and channel selection strategy even if the individual agents are not. The proposed algorithm is, by its nature, scalable and robust to node and link failures. The paper presents a detailed discussion and analysis of the algorithm's characteristics, including the effects of denoising, the possibility of organizing coordinated actions, and the convergence rate improvement induced by the consensus scheme. The results of extensive simulations demonstrate the high effectiveness of the proposed algorithm, and that its behavior is close to the centralized scheme even in the case of sparse neighbor-based inter-node communication.

A conceptual critique of brain lateralization models in emotional face perception: Toward a hemispheric functional-equivalence (HFE) model.

The present review proposes a novel dynamic model of brain lateralization of emotional (happy, surprised, fearful, sad, angry, and disgusted) and neutral face perception. Evidence to date suggests that emotional face perception is lateralized in the brain. At least five prominent hypotheses of the lateralization of emotional face perception have been previously proposed; the right-hemisphere hypothesis; the valence-specific hypothesis; the modified valence-specific hypothesis; the motivational hypothesis; and behavioral activation/inhibition system hypothesis. However, a growing number of recent replication studies exploring those hypotheses frequently provide inconsistent or even contradictory results. The latest neuroimaging and behavioral studies strongly demonstrate the functional capacity of both hemispheres to process emotions relatively successfully. Moreover, the flexibility of emotional brain-networks in both hemispheres is functionally high even to the extent of a possible reversed asymmetry of the left and the right hemisphere performance under altered neurophysiological and psychological conditions. The present review aims to a) provide a critical conceptual analysis of prior and current hypotheses of brain lateralization of emotional and neutral face perception; b) propose an integrative introduction of a novel hemispheric functional-equivalence (HFE) model in emotional and neutral face perception based on the evaluation of theoretical considerations, behavioral and neuroimaging studies: the brain is initially right-biased in emotional and neutral face perception by default; however, altered psychophysiological conditions (e.g., acute stress, a demanding emotional task) activate a distributed brain-network of both hemispheres toward functional equivalence that results in relatively equalized behavioral performance in emotional and neutral face perception. The proposed novel model may provide a practical tool in further experimental investigation of brain lateralization of emotional face perception.

Functional brain asymmetry for emotions: psychological stress-induced reversed hemispheric asymmetry in emotional face perception.

Empirical evidence has demonstrated functional (mostly right-biased) brain asymmetry for emotion perception, whereas recent studies indicate that acute stress may modulate left and/or right hemisphere activation. However, it is still unknown whether emotion perception can be influenced by stress-induced hemispheric activation since behavioral studies report inconsistent or even contradictory results. We sought to reevaluate this gap. Eighty-eight healthy Caucasian university students participated in the study. In half of the randomly selected participants, acute psychological stress was induced by displaying a brief stressful movie clip (the stress condition), whereas the other half were shown a neutral movie clip (the non-stress condition). Prior to (the baseline) and following the movie clip display an emotion perception task was applied by presenting an emotional (happy, surprised, fearful, sad, angry, or disgusted) or neutral face to the left or right visual field. We found a more accurate perception of emotional and neutral faces presented to the LVF (the right hemisphere) in the baseline. However, we revealed that after watching a neutral movie clip, behavioral performance in emotional and neutral face perception accuracy became relatively equalized for both visual fields, whereas after watching a stressful movie clip, the RVF (the left hemisphere) even became dominant in emotional face perception. We propose a novel hemispheric functional-equivalence model: the brain is initially right-biased in emotional and neutral face perception by default; however, psychophysiological activation of a distributed brain-network due to watching neutral movie clips redistributes hemispheric performance toward relative equivalence. Moreover, even reversed hemispheric asymmetry may occur.

IL-33/IL-33R in various types of carotid artery atherosclerotic lesions.

OBJECTIVE: Inflammation plays a crucial role in the progression of atherosclerotic plaques. The aim of the study was to investigate serum levels and expression of Interleukin-33 (IL-33) and ST2 receptor in atherosclerotic plaques and to analyze correlation with the type of the carotid plaques in patients with carotid disease. METHODS: This study included 191 consecutive patients submitted for carotid endarterectomy (CEA). Preoperative serum levels of IL-33 and soluble ST2 (sST2) were measured. Atherosclerotic plaques obtained during surgery were initially histologically classified and immunohistochemical analyzes of IL-33, IL-33R, CD68 and alpha-SMA expression was performed. Ultrasound assessment of the level of carotid stenosis in each patient was performed prior to carotid surgery. Demographic and clinical data such as gender, age, smoking status, blood pressure, glycaemia, hemoglobin and creatinine levels, and comorbidities were collected and the comparisons between variables were statistically evaluated. RESULTS: Serum levels of IL-33 (35.86 ±â€¯7.93 pg/ml vs.12.29 ±â€¯1.8 pg/ml, p < 0.05) and sST2 (183 ±â€¯8.03 pg/ml vs. 122.31 ±â€¯15.89 pg/ml, p < 0.05) were significantly higher in the group of CEA patients vs. healthy subjects. We demonstrated abundant tissue expression of IL-33 and ST2 in atherosclerotic carotid artery lesions. The levels of IL-33 and IL-33R expression were significantly higher in vulnerable plaques and significantly correlated with the degree of inflammatory cells infiltration in these plaques (R = 0.579, p = 0.049). Immunohistochemical analysis also revealed that cells responsible for IL-33 expression are not only mononuclear cells confined to inflammatory atherosclerotic lesions, but also smooth muscle cells which gained phenotypic characteristics of foam cells and were loaded with lipid droplets. CONCLUSION: The obtained results confirm the importance of IL-33/ST2 axis in the process of atherosclerosis, and indicate its ambiguous function in immune response, whether as proinflammatory cytokine in advanced atherosclerotic lesions, or as profibrotic, in early lesions.

On Consensus-Based Distributed Blind Calibration of Sensor Networks.

This paper deals with recently proposed algorithms for real-time distributed blind macro-calibration of sensor networks based on consensus (synchronization). The algorithms are completely decentralized and do not require a fusion center. The goal is to consolidate all of the existing results on the subject, present them in a unified way, and provide additional important analysis of theoretical and practical issues that one can encounter when designing and applying the methodology. We first present the basic algorithm which estimates local calibration parameters by enforcing asymptotic consensus, in the mean-square sense and with probability one (w.p.1), on calibrated sensor gains and calibrated sensor offsets. For the more realistic case in which additive measurement noise, communication dropouts and additive communication noise are present, two algorithm modifications are discussed: one that uses a simple compensation term, and a more robust one based on an instrumental variable. The modified algorithms also achieve asymptotic agreement for calibrated sensor gains and offsets, in the mean-square sense and w.p.1. The convergence rate can be determined in terms of an upper bound on the mean-square error. The case when the communications between nodes is completely asynchronous, which is of substantial importance for real-world applications, is also presented. Suggestions for design of a priori adjustable weights are given. We also present the results for the case in which the underlying sensor network has a subset of (precalibrated) reference sensors with fixed calibration parameters. Wide applicability and efficacy of these algorithms are illustrated on several simulation examples. Finally, important open questions and future research directions are discussed.

Contralateral Hemisphere Activation by Unilateral Hand Contraction: ReExamining Global and Local Attention.

While previous studies have shown that left- (vs. right-) hand contractions can improve the performance of global (vs. local) attention, these results were inconsistent in certain behavioral studies in which the left cerebral hemisphere was found to be specialized for local attention, while the right hemisphere was not specialized for global attention. Thus, we reexamined whether different global (vs. local) attention performances follow left- (vs. right-) hand contractions due to right (vs. left) hemisphere activation. We recruited 100 right-handed healthy female, university student (aged 19-26 years) participants. We used the Navon task to present 80 letter-stimuli (40 in the global task; 40 in the local task) to either the participants' left or right visual fields. Half of the participants (randomly selected) were instructed to squeeze a dynamometer with the left hand, while the other half squeezed with the right hand, prior to completing the Navon task. In line with previous research, we observed a perceptual advantage of global (large letters) over local (small letters) stimuli. Participants who contracted the right hand showed an enhanced local attention performance (from left hemisphere activation), whereas those who contracted the left hand did not improve global attention performance (from right hemisphere activation). Thus, we supported prior behavioral research suggesting that hemispheric asymmetry for attention processing is evident for left but not right cortical hemisphere processing.

Mental health provision in schools: priority, facilitators and barriers in 10 European countries.

BACKGROUND: Although schools are a key setting for the provision of mental health support for young people, little is known about the facilitators and barriers for providing such support. This study aimed to collect information from schools in 10 European countries regarding the priority given to mental health support for students, existence of a mental health-related school policy, links with relevant external agencies, schools' perceptions on whether they are providing sufficient mental health support and the barriers to provision of mental health support. METHODS: Data from 1346 schools were collected in France, Germany, Ireland, the Netherlands, Poland, Serbia, Spain, Sweden, United Kingdom and Ukraine through an online survey. RESULTS: Around 3% of the surveyed schools indicated that mental health provision was not a priority, compared to 47% indicating that it was a high/essential priority. More than half the surveyed schools did not implement a school policy regarding mental health. Half the surveyed schools reported not providing sufficient support with the key barriers identified including limited staff capacity, funding, access to specialists and lack of national policy and less than a third of schools reported good or excellent links with local mental health services. However, the responses varied by country with 8-19% between-country variation across the study outcomes. Secondary schools reported significantly better links with agencies, were more likely to have a school policy and were less likely to indicate having sufficient existing support compared to primary schools. Privately funded schools reported that mental health support was a higher priority and identified less barriers to provision compared to publicly funded schools. CONCLUSIONS: This study provides an up-to-date and cross-country insight into schools' perceptions regarding priority given to mental health support and the barriers they face in providing sufficient mental health and wellbeing support for their students. The cross-country comparisons allow for a better understanding of the relationships between policy, practice and implementation and provide a platform for shared experiences and learning.

A Distributed Support Vector Machine Learning Over Wireless Sensor Networks.

This paper is about fully-distributed support vector machine (SVM) learning over wireless sensor networks. With the concept of the geometric SVM, we propose to gossip the set of extreme points of the convex hull of local data set with neighboring nodes. It has the advantages of a simple communication mechanism and finite-time convergence to a common global solution. Furthermore, we analyze the scalability with respect to the amount of exchanged information and convergence time, with a specific emphasis on the small-world phenomenon. First, with the proposed naive convex hull algorithm, the message length remains bounded as the number of nodes increases. Second, by utilizing a small-world network, we have an opportunity to drastically improve the convergence performance with only a small increase in power consumption. These properties offer a great advantage when dealing with a large-scale network. Simulation and experimental results support the feasibility and effectiveness of the proposed gossip-based process and the analysis.