Search Results (11)

Precision neurosurgery is rapidly evolving as a medical specialty by merging genomic medicine, multi-omics technologies, and artificial intelligence (AI) technology, while at the same time, society is shifting away from the traditional, anatomic model of care to consider a more precise, molecular model of care. The general purpose of this review is to contemporaneously reflect on how these advances will impact neurosurgical care by providing us with more precise diagnostic and treatment pathways. We hope to provide a relevant review of the recent advances in genomics and multi-omics in the context of clinical practice and highlight their transformational opportunities in the existing models of care, where improved molecular insights can support improvements in clinical care. More specifically, we will highlight how genomic profiling, CRISPR-Cas9, and multi-omics platforms (genomics, transcriptomics, proteomics, and metabolomics) are increasing our understanding of central nervous system (CNS) disorders. Achievements obtained with transformational technologies such as single-cell RNA sequencing and intraoperative mass spectrometry are exemplary of the molecular diagnostic possibilities in real-time molecular diagnostics to enable a more directed approach in surgical options. We will also explore how identifying specific biomarkers (e.g., IDH mutations and MGMT promoter methylation) became a tipping point in the care of glioblastoma and allowed for the establishment of a new taxonomy of tumors that became applicable for surgeons, where a change in practice enjoined a different surgical resection approach and subsequently stratified the adjuvant therapies undertaken after surgery. Furthermore, we reflect on how the novel genomic characterization of mutations like DEPDC5 and SCN1A transformed the pre-surgery selection of surgical candidates for refractory epilepsy when conventional imaging did not define an epileptogenic zone, thus reducing resective surgery occurring in clinical practice. While we are atop the crest of an exciting wave of advances, we recognize that we also must be diligent about the challenges we must navigate to implement genomic medicine in neurosurgery—including ethical and technical challenges that could arise when genomic mutation-based therapies require the concurrent application of multi-omics data collection to be realized in practice for the benefit of patients, as well as the constraints from the blood–brain barrier. The primary challenges also relate to the possible gene privacy implications around genomic medicine and equitable access to technology-based alternative practice disrupting interventions. We hope the contribution from this review will not just be situational consolidation and integration of knowledge but also a stimulus for new lines of research and clinical practice. We also hope to stimulate mindful discussions about future possibilities for conscientious and sustainable progress in our evolution toward a genomic model of precision neurosurgery. In the spirit of providing a critical perspective, we hope that we are also adding to the larger opportunity to embed molecular precision into neuroscience care, striving to promote better practice and better outcomes for patients in a global sense. Full article

Spinal cord injury (SCI) remains one of the toughest obstacles in neuroscience and regenerative medicine due to both severe functional loss and limited healing ability. This article aims to provide a key integrative, mechanism-focused review of the molecular landscape of SCI and the new disruptive therapy technologies that are now evolving in the SCI arena. Our goal is to unify a fundamental pathophysiology of neuroinflammation, ferroptosis, glial scarring, and oxidative stress with the translation of precision treatment approaches driven by artificial intelligence (AI), CRISPR-mediated gene editing, and regenerative bioengineering. Drawing upon advances in single-cell omics, systems biology, and smart biomaterials, we will discuss the potential for reprogramming the spinal cord at multiple levels, from transcriptional programming to biomechanical scaffolds, to change the course from an irreversible degeneration toward a directed regenerative pathway. We will place special emphasis on using AI to improve diagnostic/prognostic and inferred responses, gene and cell therapies enabled by genomic editing, and bioelectronics capable of rehabilitating functional connectivity. Although many of the technologies described below are still in development, they are becoming increasingly disruptive capabilities of what it may mean to recover from an SCI. Instead of prescribing a particular therapeutic fix, we provide a future-looking synthesis of interrelated biological, computational, and bioengineering approaches that conjointly chart a course toward adaptive, personalized neuroregeneration. Our intent is to inspire a paradigm shift to resolve paralysis through precision recovery and to be grounded in a spirit of humility, rigor, and an interdisciplinary approach. Full article

Background/Objectives: Genitourinary cancers are now considered a major problem in modern medicine. In urological oncology, the most frequently occurring diseases are prostate, bladder and renal cancer. Any cancer has a profound effect on the life of a patient. Therefore, disease acceptance and mental adjustment to the condition are the key elements in coping with cancer. Aim: The main aim of the study was the determination of the level of acceptance of illness and mental adjustment to cancer in urological patients undergoing surgical treatment and the assessment of the effect of mental adjustment on disease acceptance. Material and Methods: The study group comprised 150 patients treated at the Department of Urology and Urological Oncology at the Independent Public Clinical Hospital No 2 in Szczecin. The study made use of the diagnostic survey method with the original questionnaire and standardized research tools: Acceptance of Illness Scale (AIS) and Mental Adjustment to Cancer Scale (Mini-MAC). Results: The analysis of mental adjustment to cancer according to Mini-MAC revealed that the respondents most frequently adopted the fighting spirit strategy (M; 22.22). Slightly less frequently adopted strategies were positive re-evaluation (M; 21.28) and anxious preoccupation (M; 17.07). The least frequently adopted strategy was the helplessness-hopelessness strategy (M; 13.14). The analysis of data showed a statistically significant negative correlation (r = −0.245; p = 0.003) between disease acceptance according to AIS and age. The data analysis revealed a statistically significant positive correlation with helplessness-hopelessness and destructive style (p < 0.05). Conclusions: Mental adjustment to cancer was found to affect the acceptance of illness. When providing comprehensive care to cancer patients, it is equally crucial to consider the physical as well as mental health aspect, taking into account the aforementioned factors which affect both acceptance as well as adjustment to disease. Full article

In this study, we sought to evaluate the capabilities of radiomics and machine learning in predicting seropositivity in patients with suspected autoimmune encephalitis (AE) from MR images obtained at symptom onset. In 83 patients diagnosed with AE between 2011 and 2022, manual bilateral segmentation of the amygdala was performed on pre-contrast T2 images using 3D Slicer open-source software. Our sample of 83 patients contained 43 seropositive and 40 seronegative AE cases. Images were obtained at our tertiary care center and at various secondary care centers in North Rhine-Westphalia, Germany. The sample was randomly split into training data and independent test data. A total of 107 radiomic features were extracted from bilateral regions of interest (ROIs). Automated machine learning (AutoML) was used to identify the most promising machine learning algorithms. Feature selection was performed using recursive feature elimination (RFE) and based on the determination of the most important features. Selected features were used to train various machine learning algorithms on 100 different data partitions. Performance was subsequently evaluated on independent test data. Our radiomics approach was able to predict the presence of autoantibodies in the independent test samples with a mean AUC of 0.90, a mean accuracy of 0.83, a mean sensitivity of 0.84 and a mean specificity of 0.82, with Lasso regression models yielding the most promising results. These results indicate that radiomics-based machine learning could be a promising tool in predicting the presence of autoantibodies in suspected AE patients. Given the implications of seropositivity for definitive diagnosis of suspected AE cases, this may expedite diagnostic workup even before results from specialized laboratory testing can be obtained. Furthermore, in conjunction with recent publications, our results indicate that characterization of AE subtypes by use of radiomics may become possible in the future, potentially allowing physicians to tailor treatment in the spirit of personalized medicine even before laboratory workup is completed. Full article

Deep brain stimulation is a treatment that controls symptoms by changing brain activity. The complexity of how to best treat brain dysfunction with deep brain stimulation has spawned research into artificial intelligence approaches. Machine learning is a subset of artificial intelligence that uses computers to learn patterns in data and has many healthcare applications, such as an aid in diagnosis, personalized medicine, and clinical decision support. Yet, how machine learning models make decisions is often opaque. The spirit of explainable artificial intelligence is to use machine learning models that produce interpretable solutions. Here, we use topic modeling to synthesize recent literature on explainable artificial intelligence approaches to extracting domain knowledge from machine learning models relevant to deep brain stimulation. The results show that patient classification (i.e., diagnostic models, precision medicine) is the most common problem in deep brain stimulation studies that employ explainable artificial intelligence. Other topics concern attempts to optimize stimulation strategies and the importance of explainable methods. Overall, this review supports the potential for artificial intelligence to revolutionize deep brain stimulation by personalizing stimulation protocols and adapting stimulation in real time. Full article

Background: Health is a value of paramount importance for human existence. It has a special place in every religious system, both on the doctrinal and practical levels. Most religions view health as a priority value to be cared for, and require followers of individual religious groups to take care of their physical and mental health, and to maintain a balance between body and spirit. The aim of the study was to verify whether the level of religious commitment significantly influences health behaviors and whether in selected religions the faithful have a different approach to health behaviors. Methods: This cross-sectional study was conducted on a group of 296 people—118 Seventh-day Adventists (SDA), 134 Catholics, and 14 Jews living in southern Poland, and 31 Muslims living in southern and north-eastern Poland. The following research tools were used as part of the diagnostic survey method: a questionnaire survey designed by us; the International Physical Activity Questionnaire (IPAQ); the Inventory of Health Behaviours (IHB); the Perceived Stress Scale (PSS 10) and anthropometric measurements, physical examination, laboratory tests. Results: Only 75% of Catholics who participated in the study declared a high level of religious commitment. On the other hand, all (100%) of SDA, Jews, and Muslim respondents declared their religious commitment at a high level. SDA were characterized by the most desirable health behaviors on the IHB (high and average levels), especially eating habits. They did not consume alcohol, did not smoke cigarettes. The physical activity of most ADS was high and moderate. Most of the SDA subjects were characterized by an average and low level of stress intensity. The most common correct scores for homocysteine, triglycerides, and CRP were SDA, cholesterol by Jews, glucose by Muslims, and HDL by Catholics. The most common negative results were: homocysteine, glucose and triglycerides among Jews, cholesterol and CRP among Catholics, HDL among Muslims. Optimal blood pressure was most common among Catholics, and hypertension was most often diagnosed among Jews. Most often, Muslims had the correct body weight, and at the same time it was the group of respondents most often diagnosed with obesity. In contrast, underweight was observed only among Catholics. The SDA subjects were most often overweight. Conclusions: The results suggest that public health professionals and nurses should develop culturally specific educational interventions, especially among Catholics. Full article

In the spirit of initiating a new journal for Rheumato, it is pertinent to review the attention to the basics that first established the field as an evidence-based approach to recognition and treatment of arthritis and multisystem diseases and the reputation of its disciples as resources for solving diagnostic dilemmas [...] Full article

A cutaneous squamous cell carcinoma (cSCC) derived from keratinocytes is the second most common cause of non-melanoma skin cancer. The accumulation of the mutational burden of genes and cellular DNA damage caused by the risk factors (e.g., exposure to ultraviolet radiation) contribute to the aberrant proliferation of keratinocytes and the formation of a cSCC. A cSCC encompasses a spectrum of diseases that range from recursor actinic keratosis (AK) and squamous cell carcinoma (SCC) in situ (SCCIS) to invasive cSCCs and further metastatic SCCs. Emerging evidence has revealed that lncRNAs are involved in the biological process of a cSCC. According to the ceRNA regulatory theory, lncRNAs act as natural miRNA sponges and interact with miRNA response elements, thereby regulating the mRNA expression of their down-stream targets. This study was designed to search for the potential lncRNAs that may become potential therapeutic targets or biomarkers of a cSCC. Considering the spirit of the study to be adequately justified, we collected microarray-based datasets of 19 cSCC tissues and 12 normal skin samples from the GEO database (GSE42677 and GSE45164). After screening the differentially expressed genes via a limma package, we identified 24 differentially expressed lncRNAs (DElncRNAs) and 3221 differentially expressed mRNAs (DEmRNAs). The miRcode, miRTarBase, miRDB and TargetScan databases were used to predict miRNAs that could interact with DElncRNAs and DEmRNAs. A total of 137 miRNA-lncRNA and 221 miRNA-mRNA pairs were retained in the ceRNA network, consisting of 31 miRNAs, 11 DElncRNAs and 155 DEmRNAs. For the functional analysis, the top enriched biological process was enhancer sequence-specific DNA binding in Gene Ontology (GO) terms. The FoxO signaling pathway, autophagy and cellular senescence were the top enrichment terms based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The combination of a STRING tool and Cytoscape software (plug-in MCODE) identified five core mRNAs and built a core mRNA-associated ceRNA network. The expression for five identified core mRNAs and their related nine lncRNAs was validated using the external dataset GSE7553. Finally, one lncRNA HLA-F-AS1 and three mRNAs named AGO4, E2F1 and CCND1 were validated with the same expression patterns. We speculate that lncRNA HLA-F-AS1 may sponge miR-17-5p or miR-20b-5p to regulate the expression of CCND1 and E2F1 in the cSCC. The present study may provide potential diagnostic and therapeutic targets for cSCC patients. Full article

Background: It would be clinically useful to prospectively identify the risk of disease progression in chronic myeloid leukaemia (CML). Overexpression of cancerous inhibitor of protein phosphatase 2A (PP2A) (CIP2A) protein is an adverse prognostic indicator in many cancers. Methods: We examined CIP2A protein levels in diagnostic samples from the SPIRIT2 trial in 172 unselected patients, of whom 90 received imatinib and 82 dasatinib as first-line treatment. Results: High CIP2A levels correlated with inferior progression-free survival (p = 0.04) and with worse freedom from progression (p = 0.03), and these effects were confined to dasatinib recipients. High CIP2A levels were associated with a six-fold higher five-year treatment failure rate than low CIP2A levels (41% vs. 7.5%; p = 0.0002), in both imatinib (45% vs. 11%; p = 0.02) and dasatinib recipients (36% vs. 4%; p = 0.007). Imatinib recipients with low CIP2A levels had a greater risk of treatment failure (p = 0.0008). CIP2A levels were independent of Sokal, Hasford, EUTOS (EUropean Treatment and Outcome Study), or EUTOS long-term survival scores (ELTS) or the presence of major route cytogenetic abnormalities. No association was seen between CIP2A levels and time to molecular response or the levels of the CIP2A-related proteins PP2A, SET, SET binding protein 1 (SETBP1), or AKT. Conclusions: These data confirm that high diagnostic CIP2A levels correlate with subsequent disease progression and treatment failure. CIP2A is a simple diagnostic biomarker that may be useful in planning treatment strategies. Full article

Ethanol is the direct by-product of distillation. The vast majority of straight spirit beverages are bottled at 40%+ ABV (alcohol by volume). Aficionados, critics, spirits judges, and a significant percentage of drinkers choose to drink and evaluate spirits at bottled strength from traditional vessels. Olfactory perceptions are quickly compromised by abundant ethanol, numbing olfactory sensors and severely inhibiting aroma detection during evaluation. Traditional vessel redesigns have concentrated on minor styling changes, ignoring olfactory and physical sciences. Consumers’ continued search for value and quality and increased dependency on spirits competitions as a primary source of ratings emphasizes the need for a functional diagnostic vessel which displays and delivers aromas unobscured by ethanol olfactory numbing. The application of olfactory and physical science creates an engineered tasting vessel which eliminates severe ethanol olfactory numbing, optimizes aroma definition, and significantly improves diagnostics for those who evaluate, judge, rate, distill, and enjoy flavor nuances of spirits. Full article

The objective of the article is to present the slow sport movement as a phenomenon developing in the postmodern era in opposition to the idea of citius, altius, fortius (Eng. faster, higher, stronger). The theoretical part of the article describes the health repercussions of slow movement and its implications for the sports industry and sports tourism. It also points to new challenges in sports management and sports tourism implemented in the slow style. The empirical part of the article aims at determining what influence the achievement of a self-set sports goal has on the degree of satisfaction with participation in a running event among runners. Could runners who did not set themselves any sports goal and ran for pleasure (according to the idea of slow sport) achieve the same degree of satisfaction as runners who set themselves an ambitious sports goal and achieved it (according to the idea of citius, altius, fortius)? The case study is the 6th Poznan Half Marathon, a cyclical, popular running event taking place in Poland. A total of 560 runners (n = 560) took part in the diagnostic survey conducted using the interview technique. The ANOVA Rang Kruskal-Wallis test and Dunn’s test were used in the study. The results show that athletes who did not set a sporting goal (ran for pleasure, company, atmosphere, participation, etc.) experienced the same level of satisfaction as athletes who achieved their intended sporting goal. It turns out, therefore, that sport and physical activity done for pleasure in accordance with the slow sport idea can provide the same level of satisfaction as sport practiced in the spirit of citius, altius, fortius. Full article