Advances in experimental medicine and biology最新文献

The diffraction limit of visible light governs the spatial resolution of optical microscopy to roughly half the wavelength of the light, typically around 200 nm in the lateral dimension and 500 nm in the axial dimension. However, many subcellular structures and processes occur on a much smaller length scale. Technological solutions beyond the optical diffraction limit are needed to study subcellular organizations of proteins and their related functions. Super-resolution microscopy (SRM) represents a family of techniques capable of resolving structures and objects below the optical diffraction limit. This chapter provides an overview of three super-resolution techniques, stimulated emission depletion (STED) microscopy, structured illumination microscopy (SIM), and single-molecule localization microscopy (SMLM), and their applications in investigating subcellular protein organizations and related functions in immune cells.

The objective of this study was to evaluate the quality of life (QoL) and to determine the associated factors for sarcopenia in Greek community-dwelling older adults, diagnosed according to EWGSOP2 criteria. A cross-sectional study involving older-adult participants >60 years of age was performed. QoL was assessed using the validated Greek version of the SarQoL questionnaire. Body composition was determined by bioelectrical impedance analysis, and strength assessment was performed via hand-held grip strength. Functional assessments included four-meter (4 m), and Τimed-Up and Go (TUG) test. Participants were 203 community-dwelling older adults, with a mean age of 71.4 ± 8.1 years. The prevalence of sarcopenia was 24.6% (n = 17). Sarcopenic individuals have had significantly lower scores in SarQoL. The findings of this study demonstrated that QoL in patients with sarcopenia was associated with falls and BMI. QoL has significant associations with sarcopenia in Greek older adults. In conclusion, a significantly lower QoL was noted for sarcopenic individuals compared with non-sarcopenic ones. Therefore, appropriate assessments and interventions are needed following evaluation of sarcopenia and QoL among older people.

The aim of this research was the translation, cultural adaptation, and psychometric validity of the WHOQOL-OLD and OPQOL-35 questionnaires. The WHOQOL-OLD and OPQOL-35 questionnaires in their original version are considered appropriate for measuring these factors and aim to demonstrate a reliable measure of quality of life. For their utilization and the expansion of their accessibility by the Greek population, with the ultimate goal of locating and intervening in cases of vulnerability, in the first stage, the forward translation, the reconciliation report, and the backward translation were performed. Then, the translated Greek version was applied in a pilot study. The total sample of the research consisted of 300 people of the population of interest (elderly Greek), of whom 50 participated in the successful pilot research. The majority of the sample lives in the Prefecture of Trikala and identifies with the female sex. The mean age of the individuals who participated in the study anonymously was 72.1 years. SPSS 22.0 and AMOS programs were used for data analysis. In conclusion, the Greek version of the WHOQOL-OLD and OPQOL-35 questionnaires proved to be reliable and valid. The adapted questionnaires are considered equally capable of being used comparatively for intercultural research, as well as for the timely detection of vulnerability of the elderly for immediate intervention, provided that the Greek version proves reliability and validity.

eHealth literacy can enhance behavioral change in health, beliefs, and medication adherence behaviors, or not, in people with chronic diseases. The current study aimed to investigate the effect of eHealth literacy as well as medication beliefs on medication adherence in older people with chronic diseases. A convenient sample of 200 recipients of Primary Health Care (PHC) services with chronic diseases was administered a sociodemographic and clinical characteristics questionnaire, the eHEALS scale, the Morisky Green Levin Adherence Scale (MAQ), and the BMQ scale. The total rate of low and moderate adherence ranged at 58.8% and concerned the majority of older people whose mean age was 68 years. The average score for eHealth literacy was 19.5 points (SD = 9.8 points). High scores were noted in all dimensions of BMQ. People with high medication adherence (41.2%) showed a lower score in the dimensions of "concern", "abuse", and "harmful consequences" (p < 0.001), while they showed a high score in eHealth literacy (p = 0.005). The more they feared the harmful effects of the medication, the less likely they were to have high adherence [OR (95% CI) 0.83 (0.75-0.93), P = 0.001]. The present study highlighted the importance of ehealth literacy for beliefs and medication adherence. Policy makers need to transform public health systems and provide older adults with sufficient knowledge and skills in eHealth literacy so as to promote adherence and increase clinical benefit.

Background and aims: During the pandemic, the immediate adoption of restrictive measures to reduce the spread of the virus, brought into action measures by those responsible for public health issues, such as the shutdown of most economic activities, which also happened for the retail sector. The aim of this study was to investigate the impacts of the Pandemic Covid-19 on the psycho-emotional status of individuals employed in Stores, of a municipal district area.

Methods: The study involved 262 employees working in the shops of the city of Corinth, in Peloponnese prefecture. In addition to the sociodemographic questions, the distributed questionnaire included five psychometric tools/scales (The Fear Scale for COVID-19, the Covid-19 Stigma Questionnaire, the Connor-Davidson Resilience Scale, the Coping Orientations to Problems Experienced (COPE) questionnaire, the Self-Esteem Scale for Anxiety). Data processing and the extraction of statistical results were done using SPSS 25.0 software.

Results: Regarding the status of the respondents in relation to the pandemic, 8.78% stated that they have been sick with coronavirus. For protection against the coronavirus, the respondents stated their habits as a priority. Respondents said they were moderately scared, in general, about the Covid-19 pandemic. However, fear causes them insecurity to some extent and does not lead to extraordinary situations of anxiety and panic. Most of the sample (88.17%) believed that people suffering from COVID-19 can be neighbors of those who do not suffer from this disease. Stigma was observed to differ based on whether one had been ill or vaccinated. Examining the anxiety score about the demographic data of the participants, it emerged that there is a statistically significant difference in the average anxiety score in terms of gender, as well as age. Also, it appears that the strategies of acceptance (5.87), positive perspective and reassessment of things (5.84), planning (5.74), active coping (5.67), and distraction (5.57). Respondents' resilience to escape difficult situations was measured, and the results showed that the degree of personal ability in building resilience is moderate to high.

Conclusions: It seems that workers were affected by the pandemic as much as other professional groups, such as health professionals.

Introduction: The use of PET-CT combined with Fluorodeoxyglucose (FDG) has enhanced the detection and management of conditions like vasculitis and lymphoma. However, the current approach to measuring standardized uptake value (SUV) requires manual selection of Regions of Interest (ROI), which is time-intensive. This study introduces an automated method to measure tracer uptake in the aorta, aiming to improve efficiency and accuracy.

Methods: We conducted a proof-of-concept study on PET-CT scans, including those with vasculitis, lymphoma, and healthy controls. A UNET model with a ResNet-18 backbone was used for automated aorta segmentation and SUVmax calculation. We assessed the model's performance using the Intersection over Union (IoU) and compared SUVmax results from automated and manual methods.

Results: The model achieved an IoU score of 0.905 in the validation slides set, reflecting strong segmentation performance. The mean SUVmax between automated and manual methods showed no significant difference (2.75 vs 2.28, p = 0.38). The automated process significantly reduced segmentation time from 36.3 minutes to 4.8 minutes.

Conclusions: Automated aortic segmentation and SUV calculation using deep learning techniques can enhance PET-CT diagnostic workflows by matching the accuracy of manual methods while greatly reducing processing time.

Several volumetric and qualitative bone limitations may contraindicate the use of bone-supported oral rehabilitation, which remains the gold standard for edentulous ridges. However, oral bone regeneration is a multifaceted process influenced by immune responses, cellular dynamics, and systemic factors. Moreover, its predictability in clinical settings remains limited, leading to challenges in consistently achieving the desired regenerative outcomes. This chapter explores immunomodulation strategies as innovative approaches to enhance alveolar bone regeneration, addressing the challenges of bone healing and repair. Traditional methods such as grafting and biomaterials, while effective, face limitations, including donor site morbidity and immune rejection. Thus, immunotherapy approaches emphasizing cell-based therapies (macrophage polarization, cytokines, and mesenchymal stem cells), material-based strategies (bioactive scaffolds and nanoparticles), and other supporting approaches like anti-inflammatory drugs and lifestyle interventions will be outlined. Even though preclinical studies suggest that some of these techniques can be crucial in the maintenance or resolution of the inflammation and thereby directing bone healing, several uncertainties remain regarding their clinical validation. Additionally, insights on the role of emerging strategies, such as photodynamic therapy (PDT) and near-infrared light (NIR) therapy, will be explored, considering their impact on immunity, infection, and bone repair. All these strategies can be combined to synergistically and positively affect outcomes in bone regeneration.

Pregnancy is a complex physiological state characterized by a series of intricate changes across the physiological, immunological, and endocrine systems that are critical for successful fetal development. However, these profound modifications also increase the mother's susceptibility to a variety of systemic and oral health conditions. This chapter explores the nuanced relationships between systemic health issues, such as gestational diabetes mellitus, and periodontal disease, with a particular emphasis on periodontitis, which is recognized as a chronic inflammatory condition that exacerbates systemic inflammatory responses during pregnancy. The oral microbiota undergoes significant alterations due to the hormonal shifts and immunological adjustments that occur during gestation. These changes can disrupt the balance of microbial communities, potentially leading to periodontal disease, which has been linked to a range of adverse maternal and neonatal outcomes. In conjunction with the physiological changes associated with pregnancy, such as endothelial dysfunction and elevated levels of pro-inflammatory cytokines, the risk of cardiovascular, metabolic, and infectious complications is markedly increased. Notably, periodontitis is a contributing factor to systemic health issues that negatively influence maternal and neonatal health. For instance, periodontitis has been associated with adverse events such as low birth weight, preterm delivery, and fetal growth restriction. By examining these interconnections, this chapter provides a comprehensive understanding of the implications of periodontal health on maternal and fetal well-being, elucidating the underlying mechanisms that may contribute to adverse pregnancy outcomes. Through this lens, clinicians and healthcare providers can develop more effective strategies to mitigate risks associated with pregnancy-related complications.

Tooth formation is a complex and multifaceted biological process, intricately regulated by a diverse array of molecular entities and signaling pathways. Within this context, amelogenesis specifically refers to the development of enamel, an essential structure that provides protection and structural integrity to teeth. During amelogenesis, various mediators of the immune response, including transforming growth factor-β (TGF-β), tumor necrosis factor-α (TNF-α), and c-Jun N-terminal kinase (JNK), play critical roles. Disruptions occurring during the crucial secretion and biomineralization phases of enamel development can lead to a spectrum of dental enamel defects, which are often characterized by structural anomalies. The etiology of these defects is inherently complex and multifactorial, encompassing genetic predispositions, systemic influences, and local environmental factors, which may act individually or in combination to contribute to the adverse outcomes observed. Recent investigations have begun to uncover the significant influence of immune response mechanisms on amelogenesis, suggesting that these immunological factors may play a substantial role in the pathogenesis of dental enamel defects. This chapter aims to elucidate the diverse roles of specific components of the immune system in the context of dental enamel development. Furthermore, it explores the intricate interactions between various molecular mediators and signaling pathways, detailing their collective influence on amelogenesis. A thorough understanding of the interplay between immunological factors and tooth development is critical for advancing the frontiers of diagnostic and therapeutic strategies. Such insights may pave the way for innovative approaches to address enamel defects and enhance oral health outcomes in affected individuals.

Oral cancer (OC) is one of the most commonly diagnosed head and neck cancers and includes malignancies arising from the tongue, lips, floor of the mouth, buccal mucosa, hard palate, alveolar ridge, gingiva, and oropharynx. The most common histological type is squamous cell carcinoma, which originates from squamous cells lining the mouth and throat and accounts for over 90% of all OC cases. Notably, OC, with a five-year survival rate of approximately 68% represents a significant health burden worldwide. Biomarkers are used as molecular signatures, enabling the objective differentiation between normal and pathological conditions as well as quantifiable characteristics of disease processes, pharmacological responses to therapeutic interventions, prediction of clinically relevant endpoints, and development of personalized therapies. In the intricate landscape of OC progression, inflammation within the tumor microenvironment emerges as a central player. Predictive biomarkers include tumor necrosis factor-alpha (TNF-α), interleukin (IL)-17, and interferon-gamma (IFN-γ), which modulate tumor growth and affect response to cancer therapy. Prognostic biomarkers, such as IL-6, IL-8, IL-1α, IL-1β, cyclooxygenase (COX)-2, C-reactive protein (CRP), and hematological parameters, such as neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and monocyte-to- lymphocyte ratio provide insights into clinical outcomes. Diagnostic biomarkers, such as IL-1β, IL-8, TNF-α, and COX-2, assist in predicting carcinogenesis or determining cancer subtypes. Monitoring biomarkers, including salivary cytokines (IL-1β, IL-8, and IL-6) and TNF-α, help evaluate changes in disease status. Overall, emerging data suggest that biomarkers of inflammation provide invaluable tools for the evaluation of cancer progression, prognosis, and clinical outcomes.