This scoping review summarizes evidence regarding the impact of civic and community engagement of young people during the COVID-19 pandemic. Recognizing that the global pandemic not only brought challenges but also new opportunities to take a stance and to actively engage in communities and society, this review assesses the impact of the COVID-19 pandemic on young people's civic engagement across different cultural contexts and identifies key factors and processes that enable young people to engage with their community or society at large. We summarize evidence from 27 original research papers, one thought piece, and four reports conducted by global organizations such as the United Nations and OECD. Relevant research was conducted in the United States, Europe, China, Southeast Asia, South Africa, and New Zealand, addressing the development of leadership skills, civic responsibility, critical consciousness, civic and community engagement, as well as social integration. Key factors that facilitated civic engagement include national investments in online learning facilities, support for basic needs (such as education, health, and employment), and promotion and encouragement of local initiatives. The studies differed in their focus depending on the socio-cultural context encountered and future research needs to consider cultural variations and different demands on young people to inform effective practices for supporting young people's active engagement in society.

• MeSH
• COVID-19 * epidemiologie   psychologie   MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• pandemie MeSH
• SARS-CoV-2 * MeSH
• sociální odpovědnost MeSH
• účast komunity MeSH
• vůdcovství MeSH
• Check Tag
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

INTRODUCTION: The histopathological classification for antineutrophil cytoplasmic autoantibody (ANCA)-associated glomerulonephritis (ANCA-GN) is a well-established tool to reflect the variety of patterns and severity of lesions that can occur in kidney biopsies. It was demonstrated previously that deep learning (DL) approaches can aid in identifying histopathological classes of kidney diseases; for example, of diabetic kidney disease. These models can potentially be used as decision support tools for kidney pathologists. Although they reach high prediction accuracies, their "black box" structure makes them nontransparent. Explainable (X) artificial intelligence (AI) techniques can be used to make the AI model decisions accessible for human experts. We have developed a DL-based model, which detects and classifies the glomerular lesions according to the Berden classification. METHODS: Kidney biopsy slides of 80 patients with ANCA-GN from 3 European centers, who underwent a diagnostic kidney biopsy between 1991 and 2011, were included. We also investigated the explainability of our model using Gradient-weighted Class Activation Mapping (Grad-CAM) heatmaps. These maps were analyzed by pathologists to compare the decision-making criteria of humans and the DL model and assess the impact of different training settings. RESULTS: The DL model shows a prediction accuracy of 93% for classifying lesions. The heatmaps from our trained DL models showed that the most predictive areas in the image correlated well with the areas deemed to be important by the pathologist. CONCLUSION: We present the first DL-based computational pipeline for classifying ANCA-GN kidney biopsies as per the Berden classification. XAI techniques helped us to make the decision-making criteria of the DL accessible for renal pathologists, potentially improving clinical decision-making.

• Publikační typ
• časopisecké články MeSH

PURPOSE OF REVIEW: A critical evaluation of contemporary literature regarding the role of big data, artificial intelligence, and digital technologies in precision cardio-oncology care and survivorship, emphasizing innovative and groundbreaking endeavors. RECENT FINDINGS: Artificial intelligence (AI) algorithm models can automate the risk assessment process and augment current subjective clinical decision tools. AI, particularly machine learning (ML), can identify medically significant patterns in large data sets. Machine learning in cardio-oncology care has great potential in screening, diagnosis, monitoring, and managing cancer therapy-related cardiovascular complications. To this end, large-scale imaging data and clinical information are being leveraged in training efficient AI algorithms that may lead to effective clinical tools for caring for this vulnerable population. Telemedicine may benefit cardio-oncology patients by enhancing healthcare delivery through lowering costs, improving quality, and personalizing care. Similarly, the utilization of wearable biosensors and mobile health technology for remote monitoring holds the potential to improve cardio-oncology outcomes through early intervention and deeper clinical insight. Investigations are ongoing regarding the application of digital health tools such as telemedicine and remote monitoring devices in enhancing the functional status and recovery of cancer patients, particularly those with limited access to centralized services, by increasing physical activity levels and providing access to rehabilitation services. SUMMARY: In recent years, advances in cancer survival have increased the prevalence of patients experiencing cancer therapy-related cardiovascular complications. Traditional cardio-oncology risk categorization largely relies on basic clinical features and physician assessment, necessitating advancements in machine learning to create objective prediction models using diverse data sources. Healthcare disparities may be perpetuated through AI algorithms in digital health technologies. In turn, this may have a detrimental effect on minority populations by limiting resource allocation. Several AI-powered innovative health tools could be leveraged to bridge the digital divide and improve access to equitable care.

• Publikační typ
• časopisecké články MeSH

The formation of memories is a complex, multi-scale phenomenon, especially when it involves integration of information from various brain systems. We have investigated the differences between a novel and consolidated association of spatial cues and amphetamine administration, using an in situ hybridisation method to track the short-term dynamics during the recall testing. We have found that remote recall group involves smaller, but more consolidated groups of neurons, which is consistent with their specialisation. By employing machine learning analysis, we have shown this pattern is especially pronounced in the VTA; furthermore, we also uncovered significant activity patterns in retrosplenial and prefrontal cortices, as well as in the DG and CA3 subfields of the hippocampus. The behavioural propensity towards the associated localisation appears to be driven by the nucleus accumbens, however, further modulated by a trio of the amygdala, VTA and hippocampus, as the trained association is confronted with test experience. Moreover, chemogenetic analysis revealed central amygdala as critical for linking appetitive emotional states with spatial contexts. These results show that memory mechanisms must be modelled considering individual differences in motivation, as well as covering dynamics of the process.

• MeSH
• amfetamin farmakologie   MeSH
• amygdala fyziologie   MeSH
• hipokampus * fyziologie   MeSH
• konsolidace paměti * fyziologie   MeSH
• krysa rodu rattus MeSH
• mozek fyziologie   MeSH
• neurony fyziologie   metabolismus   MeSH
• nucleus accumbens * fyziologie   MeSH
• odměna * MeSH
• paměť fyziologie   MeSH
• podněty MeSH
• prefrontální mozková kůra fyziologie   MeSH
• rozpomínání * fyziologie   MeSH
• strojové učení MeSH
• tegmentum mesencephali - area ventralis * fyziologie   MeSH
• zvířata MeSH
• Check Tag
• krysa rodu rattus MeSH
• mužské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

Our aim is to determine the number of leukocytes, T lymphocytes and B lymphocytes and the expression of activation markers CD200 and CD23 on B lymphocytes in atopic dermatitis (AD) patients (treated and not treated with dupilumab) during the pollen season. We examined 29 patients not treated with dupilumab, 24 patients treated with dupilumab and 40 healthy subjects as a control group. The count of T and B lymphocytes and their subsets were assessed by flow cytometry. The non-parametric Kruskal-Wallis one-factor analysis of variance with post hoc by Dunn's test with Bonferroni's modification was used for statistical processing. Although there was a significant improvement in skin findings in patients treated with dupilumab, the changes in immunological profile show a persistent altered immune response characterized by dysregulation and overactivation of B lymphocytes. Dupilumab therapy leads to normalization of relative T regulatory lymphocytes and total memory B lymphocytes and to decreased count of absolute CD8+ T lymphocytes. Why carry out this study?Studies investigating the immunological profile of atopic dermatitis (AD) patients during the pollen season are rare. There are no studies investigating the count of B lymphocytes (CD5+, CD22+ and CD73+ B lymphocytes) and the expression of activation markers CD23 and CD200 on B lymphocytes and on their subsets during pollen season in AD patients treated and non-treated with dupilumab therapy.What was learned from the study?In atopic dermatitis (AD) patients with and without dupilumab therapy, we confirmed the significantly higher count of absolute neutrophils, absolute monocytes, absolute eosinophils, absolute basophils, non-switched B lymphocytes, transitional B lymphocytes, CD23 memory, naive, non-switched, switched and total CD23 B lymphocytes, the relative count of CD200 memory and CD200 switched B lymphocytes.In dupilumab treated patients, we confirmed the significantly higher count of relative eosinophils, relative CD16+ eosinophils, relative CD200 non-switched B lymphocytes and lower count of absolute CD8+ T lymphocytes. Further studies should focus on investigating the effect of dupilumab on CD8+ T lymphocytes and their subpopulations.In patients without dupilumab therapy, we confirmed the significantly higher count of relative neutrophils, relative T regulatory lymphocytes and total memory B lymphocytes.The changes in the count of CD5+, CD22+ and CD73+ B lymphocytes were not observed during pollen season in both groups of AD patients.

• MeSH
• atopická dermatitida * farmakoterapie   imunologie   MeSH
• B-lymfocyty imunologie   MeSH
• CD antigeny MeSH
• dospělí MeSH
• humanizované monoklonální protilátky * terapeutické užití   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• pyl imunologie   MeSH
• receptory IgE MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Text představí ketaminem asistovanou psychoterapii (KAP) jako novou léčebnou modalitu v psychiatrii pro široké diagnostické spektrum. Tato metoda má odlišné charakteristiky i indikace od použití esketaminu či racemického ketaminu v off-label use u deprese. Je unikátní kombinací farmakologického i psychoterapeutického přístupu tím, že aktivně využívá změněný stav vědomí vyvolaný ketaminem k zásadní akceleraci a prohloubení psychoterapeutického procesu. Podkladem této akcelerace je indukce neuroplastického procesu, zvýšená schopnost učení, a tím pádem efektivnější psychoterapie. Metoda částečně navazuje jednak na objev rychlého antidepresivního a anxiolytického účinku ketaminu z přelomu tisíciletí, jednak na metodiku psychedelické psychoterapie 50. a 60. let 20. století. V současné době se rychle rozvíjí především v USA; v ČR implementuje tento model do zdravotní péče Psyon – Psychedelická klinika, ale v poslední době vznikají i další takto specializovaná pracoviště. Text je krátkým přehledem využití ketaminu v psychiatrii a souhrnem dosavadního výzkumu o použití ketaminu v psychoterapii, představí východiska KAP a odliší KAP od jiných přístupů práce s ketaminem.

The text introduces Ketamine-Assisted Psychotherapy (KAP) as a new therapeutic modality in psychiatry for a broad diagnostic range. This method has distinct characteristics and indications compared to the use of esketamine or racemic ketamine off-label for depression. KAP uniquely combines pharmacological and psychotherapeutic approaches by actively utilizing the altered state of consciousness induced by ketamine to significantly accelerate and deepen the psychotherapeutic process. The foundation of this acceleration lies in the induction of neuroplastic processes, enhanced learning capacity, and thereby more effective psychotherapy. The method partially builds on the discovery of ketamine's rapid antidepressant and anxiolytic effects from the turn of the millennium, as well as on the methodology of psychedelic psychotherapy from the 1950s and 1960s. Currently, it is rapidly developing, especially in the United States. In the Czech Republic, this model is being implemented into healthcare by Psyon – Psychedelic Clinic, and recently, other specialized centers have also emerged. The text is a brief overview of the use of ketamine in psychiatry and a summary of the current research on the application of ketamine in psychotherapy. It introduces the principles of KAP and distinguishes KAP from other approaches to working with ketamine.

The majority of motor tasks in sports are executed unilaterally, however research on the impact of unilateral conditioning activities (CAs) on both unilateral and bilateral sports tasks remains limited. Therefore, the aim of this study was to evaluate the effects of isometric and plyometric unilateral CAs on unilateral and bilateral jumping performance. The study involved fifteen resistance-trained males who participated in three experimental sessions: 3 sets of 3 s of maximum isometric single-leg quarter-squats or 3 sets of 5 single-leg tuck jumps as CAs, along with a control condition without CA. Measurements of single-leg jump (SLJ) and countermovement jump (CMJ) were taken 5 min before, and at approximately the 3th, 6th and 9th minute after the CA. The analysis did not show any statistically significant interactions nor a main effect of condition or time (p > 0.05) for CMJ height and relative peak power. However, a main effect of time (p = 0.02) to increase non-dominant SLJ height from baseline to best post-CA time-point was found (+ 0.8 ± 2.5 cm; Cohen's d = 0.22). Neither isometric nor plyometric CAs significantly affected CMJ and SLJ performance. The observed increase in jump height for the non-dominant leg is likely due to motor learning rather than the effects of the applied CAs.

• MeSH
• dospělí MeSH
• kosterní svaly fyziologie   MeSH
• lidé MeSH
• mladý dospělý MeSH
• odporový trénink metody   MeSH
• plyometrická cvičení MeSH
• sportovní výkon fyziologie   MeSH
• svalová síla * fyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Publikace se zaměřuje na paměť, vzpomínky, zapomínání a mozek. Určeno široké veřejnosti.; Paměť je víc než jen dokonalý záznam minulosti. Lze ho úspěšně cvičit, abychom si zapamatovali to, co je pro život skutečně důležité. Neurovědec a psycholog boří zažité mýty o vzpomínkách, zapomínání i efektivním učení.

• MeSH
• mozek MeSH
• paměť MeSH
• učení MeSH
• výzkum MeSH
• Publikační typ
• monografie MeSH
• populární práce MeSH

• Konspekt
• Psychologie
• NLK Obory
• psychologie, klinická psychologie

Background/Objectives: Gastric cancer remains a leading cause of cancer-related deaths worldwide and surgical resection represents the mainstay of treatment procedures. However, despite the advancements noted in the field of surgical oncology, perioperative complications and variability in the perioperative care provided persist. To address the challenges caused by non-standardized perioperative care for gastric surgery across European healthcare systems, the EUropean PErioperative MEdical Networking (EUPEMEN) protocol has been developed. The present study concisely provides the EUPEMEN protocol's development, implementation, and impact on perioperative management in gastric resections. Methods: The EUPEMEN protocol was developed through a multidisciplinary collaboration involving five academic healthcare professionals from four European countries. The main activities of the collaborative group included a literature review, consensus development, the creation of multimodal rehabilitation manuals, and the development of an online learning platform. The EUPEMEN project aims for the uniform adoption of evidence-based practices across preoperative, intraoperative, and postoperative phases, leading in nutritional, psychological, and physiological optimization. Results: The implementation of the EUPEMEN protocol aims to optimize perioperative outcomes, including reduced postoperative complications, a shorter length of hospitalization, and improved recovery trajectories. The above have been achieved through structured guidelines that ensure consistent care delivery across diverse healthcare settings and tools such as rehabilitation manuals and a free-access online educational platform. Conclusions: The EUPEMEN protocol represents a new standard for perioperative care in the field of gastric surgery that is based on multidisciplinary collaboration and evidence-based practices. While challenges such as resource constraints and variability in adherence remain, the protocol demonstrates significant potential to improve patient outcomes and streamline perioperative management. Future research should focus on long-term effects and adaptation challenges in the setting of non-European healthcare systems.

• Publikační typ
• časopisecké články MeSH

Electroencephalography (EEG) experiments typically generate vast amounts of data due to the high sampling rates and the use of multiple electrodes to capture brain activity. Consequently, storing and transmitting these large datasets is challenging, necessitating the creation of specialized compression techniques tailored to this data type. This study proposes one such method, which at its core uses an artificial neural network (specifically a convolutional autoencoder) to learn the latent representations of modelled EEG signals to perform lossy compression, which gets further improved with lossless corrections based on the user-defined threshold for the maximum tolerable amplitude loss, resulting in a flexible near-lossless compression scheme. To test the viability of our approach, a case study was performed on the 256-channel binocular rivalry dataset, which also describes mostly data-specific statistical analyses and preprocessing steps. Compression results, evaluation metrics, and comparisons with baseline general compression methods suggest that the proposed method can achieve substantial compression results and speed, making it one of the potential research topics for follow-up studies.

• MeSH
• dospělí MeSH
• elektroencefalografie * metody   MeSH
• komprese dat * metody   MeSH
• lidé MeSH
• neuronové sítě * MeSH
• počítačové zpracování signálu MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH