Nevin Manimala

Adv Exp Med Biol. 2026;1490:145-153. doi: 10.1007/978-3-032-03402-1_16.

ABSTRACT

INTRODUCTION: Visible changes in self-concept among pediatric patients with cancer are a bothersome experience that may accompany them until adulthood.

PURPOSE: To explore the self-concept and in particular the physical appearance and popularity in children with cancer compared to healthy ones.

METHODS AND MATERIAL: A descriptive correlational study of 100 children (50 healthy and 50 diagnosed with different forms of cancer) ages 8 to 10 years. Participants were recruited from a public hospital in Athens Greece. The research instrument was “Piers-Harris Children’s Self-Concept scale” which included patients’ characteristics. The data were analyzed with the SPSS-12 statistical packet by using the following statistical tests: χ²-test, nonparametric Mann-Whitney U-test, Kruskal-Wallis test.

RESULTS: It was found that children with cancer reported more negatively or both physical appearance and popularity (p ≤ 0.001) compared to the healthy ones. Moreover, the 8-year-old children with cancer reported more negatively for physical appearance (p ≤ 0.001) but not for the factor popularity (p = 0.021), while the 10-year-old children with cancer present a more negative body image relative to the healthy ones, only for the factor popularity (p ≤ 0.001) but not for the factor physical appearance (p = 0.134). In terms of gender, female subjects with cancer presented a more negative body image relative to the healthy female subjects for both factors examined (p ≤ 0.001), while male subjects with cancer presented a more negative body image relative to the healthy male subjects only for the factor physical appearance. A positive correlation between popularity and physical appearance was found (p ≤ 0.001) but only among the children with cancer.

CONCLUSIONS: The present results highlight the differences in physical appearance and popularity among children with cancer and their healthy counterparts. The recognition of the role of physical appearance as a significant factor for children with cancer may inform the development of effective interventions for this group of children.

PMID:41479078 | DOI:10.1007/978-3-032-03402-1_16

Adv Exp Med Biol. 2026;1490:25-34. doi: 10.1007/978-3-032-03402-1_4.

ABSTRACT

BACKGROUND: Empathy cultivates deeper interpersonal relationships; however, frequent exposure can trigger the risk of burnout. This study aims to predict empathy, burnout, and syndrome among nursing staff in a university hospital in Central Greece.

MATERIAL AND METHODS: This is a synchronic study on the nursing staff of the university general hospital in central Greece. The sample consisted of 210 nurses who took part in the study by completing a questionnaire that included demographic and social characteristics, the “Copenhagen Burnout Inventory” and the “Composite Empathy Scale.” The Pearson correlation coefficient (r) and linear regression analysis with a statistical significance of 0.05 were used for the statistical analysis. Univariate and multiple logistic regression analyses were used to determine the potential predictive factors associated with burnout and empathy.

RESULTS: The prevalence of burnout and empathy among nursing staff was 62.5%. A significant positive correlation between empathy with burnout was found in almost all dimensions. For burnout subscales, “Personal Burnout” was found to be at 44.1%, Operational Burnout “at 62.5%, and in” Burn related to patients “the average was 58.3%. A higher level of burnout is associated with” Workplace Burnout “for nurses on shift work. There was a significant negative correlation between “Cognitive Personal Empathy” and the “Personal Burnout.” Also, 92.9% of the nursing staff reported suffering from a disease.

CONCLUSION: The nurses in the university hospital are “aged staff” with health problems, high levels of empathy, and burnout.

PMID:41479066 | DOI:10.1007/978-3-032-03402-1_4

Adv Exp Med Biol. 2026;1490:7-13. doi: 10.1007/978-3-032-03402-1_2.

ABSTRACT

Given the lack of relevant research, the goal of this paper is to present longitudinal data regarding electroencephalograms (EEGs) and financial capacity for amnestic mild cognitive impairment (aMCI) patients in order to examine if there are specific EEG indicators that may reveal financial capacity deficits. A detailed neuropsychological and financial capacity assessment along with EEGs was performed at three time points (baseline, 6-month retest, and 12-month retest). Strong statistically significant correlations were found exclusively for the group of aMCI patients with the lowest financial capacity performance (F1 group) between neuropsychological test performance and EEG recordings. EEGs differentiate aMCI patients into two groups: those with high financial capacity performance and those who fail in financial capacity. For the second group, EEGs measurements can be a promising source of information for predicting those aMCI individuals who need assistance in this complex cognitive domain and in order to prevent financial exploitation.

PMID:41479064 | DOI:10.1007/978-3-032-03402-1_2

Methods Mol Biol. 2026;2989:125-150. doi: 10.1007/978-1-0716-4985-5_7.

ABSTRACT

High-content image-based cytological profiling is a powerful strategy for studying the effects of chemical and genetic perturbations on the cell. Cytological profiling assays illuminate multiple cellular compartments within each cell by multiplex fluorescent staining, followed by automated microscopy and image analysis. In this chapter, we show how to utilize data derived from images of fluorescently labeled cells and organelles while simultaneously addressing common challenges of this data type. We discuss different modes of interpreting raw cellular features and describe statistical methods for using said features to quantitatively evaluate overall assay quality and reproducibility. Data standardization is described as a two-tiered task, and the more recent EMD metric is implemented as a quantitative measure of phenotypic change. We illustrate each technique using data from an osteosarcoma (U-2 OS) high-content screening assay and describe all tools required to reproduce this work.

PMID:41479051 | DOI:10.1007/978-1-0716-4985-5_7

Subcell Biochem. 2026;114:299-353. doi: 10.1007/978-3-032-08530-6_6.

ABSTRACT

This work examined the integration of epigenetics and precision medicine in the management of various blood disorders, including anemias, antiphospholipid syndrome, hemochromatosis, hemophilia, leukemia, lymphoma, multiple myeloma, porphyria, thalassemia, thrombocytopenia, thrombocytosis, polycythemia, von Willebrand disease, and coagulopathy. It begins with an overview of key concepts and the significance of precision medicine in treating blood diseases, supported by current statistics. The role of noncoding RNAs (ncRNAs) is highlighted, detailing their mechanisms of action and clinical implications as potential biomarkers and therapeutic targets. Additionally, the chapter explores natural products used in personalized medicine, examining their sources, mechanisms, and successful case studies in blood disorders. A comprehensive review of recent clinical trials provides insights into the impact of innovative therapies and FDA approvals on treatment protocols, emphasizing the importance of combination therapies. Future directions address emerging research technologies such as clustered regularly interspaced short palindromic repeats (CRISPR) and ethical considerations surrounding genetic testing and patient consent. The synthesis of findings underscores the contributions of epigenetics and precision medicine to blood disease treatment, advocating for interdisciplinary research and ongoing education to enhance patient care and outcomes.

PMID:41479041 | DOI:10.1007/978-3-032-08530-6_6

Methods Mol Biol. 2026;2983:397-447. doi: 10.1007/978-1-0716-4901-5_32.

ABSTRACT

Nucleotide sequence analyses provide insights into changes that might have an impact on proteins and their function. With the rapid accumulation of sequence data, it is now possible to recover the evolutionary history of most genes at the population level to species and beyond. Those sequences can be compared for substitutions that might change or not change the encoded protein and its function, but they can also help to estimate evolutionary relationships. These hypotheses, as phylogenetic trees, provide visual and statistical guidance for characterizing the degree of relatedness among biological entities. In a phylogenetic tree, ancestor-descendant relationships are represented by connections, and closely related entities share most of these links, which represent their evolutionary closeness. In this chapter, I outlined a method to retrieve and label nucleotide sequences of the cytokine IL17A gene, align them to identify substitutions in homologous sites, estimate phylogenetic trees with support values, and visualize these trees as images. The methodology outlined here uses free software packages in the R environment and the Python language.

PMID:41478993 | DOI:10.1007/978-1-0716-4901-5_32

J Prev Alzheimers Dis. 2026 Jan 1:100458. doi: 10.1016/j.tjpad.2025.100458. Online ahead of print.

ABSTRACT

Alzheimer’s disease (AD) is a heterogeneous neurodegenerative disease driven by pathological depositions of proteins that accumulate over decades. Compelling genetic and neurobiological evidence suggests that amyloid accumulation in the brain initiates and drives early-stage AD. Measurement of fibrillar amyloid has been pivotal to the development and approval of disease-slowing treatments. Various biomarkers of AD pathophysiology provide evidence of target engagement and downstream effects on disease progression, and their use as surrogate endpoints may help identify and expeditiously bring new treatments to patients. In clinical trials, a surrogate endpoint serves as a substitute for a direct measurement of a patient’s clinical status, and its use can provide ethical, logistical, and economic advantages. Establishing biomarkers as surrogate endpoints involves evaluating scientific evidence through diverse statistical approaches to demonstrate their predictivity of clinical benefit. This article evaluated evidence supporting amyloid β plaque reduction as a surrogate endpoint in symptomatic AD by exploring regulatory considerations and guidelines for surrogate endpoints, examining the amyloid hypothesis and the current therapeutic landscape in AD, and presenting supporting evidence of surrogate endpoints from a recent clinical development program of AD.

PMID:41478826 | DOI:10.1016/j.tjpad.2025.100458

J Prev Alzheimers Dis. 2026 Jan 1:100467. doi: 10.1016/j.tjpad.2025.100467. Online ahead of print.

ABSTRACT

BACKGROUND: Young-onset dementia (YOD) directly affects the working-age population. The premature onset of dementia intensifies peer caregiving responsibilities and diverts medical and nursing resources. While modifiable risk factors for late-onset dementia have been well established, uncertainty remains regarding the applicability of these findings to YOD. We aim to identify modifiable risk factors for YOD and evaluate the strength of evidence.

METHODS: We searched PubMed, Embase, Web of Science, and Ovid Medline from inception to 22 May 2025 for epidemiological studies on non-genetic risk factors for YOD. We used random-effects meta-analyses with the inverse variance method to pool relative risks (RRs) and 95% confidence intervals (CIs). A series of statistical tests were designed to classify the strength of evidence of significant associations as convincing, highly suggestive, suggestive, or weak evidence.

RESULTS: From 25,731 initial and 2289 updated search records, 36 studies examining 31 non-genetic risk factors for YOD were identified. Of the 31 associations examined, 21 were nominally statistically significant at P < 0.05 based on random-effects models. Prior stroke was convincingly associated with an increased risk of YOD. Evidence of association was highly suggestive for alcohol use disorders, diabetes, depression, mood disorders, Parkinson’s disease, multiple sclerosis, use of antidepressants/antipsychotics, and asthma.

CONCLUSION: We found that the risk of dementia in young individuals may be closely related to neuropsychiatric symptoms and clinical alcohol disorders. Future research should further validate these findings and explore intervention strategies to reduce dementia risk in younger individuals.

PMID:41478824 | DOI:10.1016/j.tjpad.2025.100467

J Prev Alzheimers Dis. 2026 Jan 1:100452. doi: 10.1016/j.tjpad.2025.100452. Online ahead of print.

ABSTRACT

BACKGROUND: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by widespread gray matter volume (GMV) reductions. Emerging evidence links glucose and lipid metabolic dysregulation to AD pathophysiology. However, the extent to which AD-related GMV alterations and metabolic traits share a common genetic basis remains poorly understood.

OBJECTIVES: To explore the shared genetic architecture between GMV alterations in AD and metabolites related to glucose and lipid metabolism, aiming to provide biological insights into the prevention and treatment of AD.

DESIGN: This is a multimodal, cross-disciplinary study combining neuroimaging meta-analysis, transcriptome-neuroimaging association analysis, conjunctional false discovery rate (conjFDR) analysis, and functional enrichment analysis to identify the shared genetic architecture between AD-related brain structural alterations and metabolic traits.

SETTING: Public databases and European populations.

PARTICIPANTS: The meta-analysis included 49 studies (1945 CE patients and 2598 controls). The largest genome-wide association study (GWAS) summary statistics were used for AD (N_case = 39,918; N_control =358,140), two glycemic traits-glucose (GLU, N = 459,772) and glycated hemoglobin (HbA1c, N = 146,864), and three lipid traits (N = 1320,016)-high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG).

MEASUREMENTS: We conducted a voxel-based morphometric meta-analysis of GMV in AD by systematically reviewing 49 neuroimaging studies, identified through a literature search in PubMed and Web of Science using a predefined search strategy. Building upon these neuroanatomical findings, we performed a transcriptome-neuroimaging association analysis using data from the Allen Human Brain Atlas to identify genes spatially correlated with GMV alterations. To further explore the shared genetic architecture, we integrated GWAS summary statistics for AD and five metabolic markers using conjFDR analysis. Finally, functional enrichment analyses were performed to elucidate the biological relevance of the identified genes through this integrative framework.

RESULTS: Consistent GMV reductions in AD were observed in the bilateral middle temporal gyrus, right superior temporal gyrus, and other key subcortical regions. The conjFDR analysis identified 20, 17, 78, 87, and 82 genes shared between AD-related GMV reductions and GLU, HbA1c, HDL-C, LDL-C, and TG, respectively. Notably, 6 genes were shared across all five metabolic markers. Enrichment analysis implicated these genes in biological processes related to Aβ aggregation and phosphatidylinositol metabolism.

CONCLUSIONS: This study reveals a convergent genetic architecture underlying AD-related GMV atrophy and metabolic dysfunction. These findings may offer novel insights into the molecular interplay between systemic metabolism and neurodegeneration in AD and highlight potential targets for therapeutic strategies.

PMID:41478820 | DOI:10.1016/j.tjpad.2025.100452

J Prev Alzheimers Dis. 2026 Jan 1:100450. doi: 10.1016/j.tjpad.2025.100450. Online ahead of print.

ABSTRACT

BACKGROUND: The magnitude of cognitive change before and after incident heart failure (HF) is unclear. We investigated whether incident HF is associated with changes in cognitive function at the time of diagnosis and accelerated trajectory in cognitive decline in the subsequent years.

METHODS: We used data from the Health and Retirement Study, a nationally representative survey of US adults aged 50 years or older. Participants underwent a cognitive assessment at baseline (wave 5, 2000), and at least 1 other time point (from wave 6 [2002] to wave 15 [2020]). The outcomes were change in global cognition, memory, and executive function. Outcomes were standardized into Z-scores, with higher scores indicating better cognitive performance. Linear mixed-effects models estimated changes in cognition at the time of HF (change in the intercept) and the rate of cognitive change over the years after HF (change in the slope), after adjusting for pre-HF cognitive trajectories and potential confounders.

RESULTS: We included 12 850 adults (mean [SD] age, 66.1 [9.4] years; 61.8 % women). Over a median follow-up of 16 years (interquartile range: 8 to 20 years), 1457 participants had incident HF. The annual rate of cognitive decline before HF diagnosis among individuals with incident HF was similar to that of participants who remained HF-free throughout follow-up. However, incident HF was associated with subsequent decreases in global cognition (-0.073 SD [95 % CI -0.109 to -0.038]), memory (-0.070 SD [95 % CI -0.108 to -0.032]), and executive function (-0.054 SD [95 % CI -0.092 to -0.016]) around the time of the HF diagnosis. Moreover, individuals with incident HF vs those without HF demonstrated faster and long-term declines in global cognition (-0.011 SD/year [95 % CI -0.018 to -0.004]) and executive function (-0.008 SD/year [95 % CI -0.015 to -0.001]), but not in memory (-0.006 SD/year [95 % CI -0.013 to 0.001]) over the years after HF compared with pre-HF slopes.

CONCLUSIONS: Incident HF was associated with subsequent decreases in cognitive function at the time of diagnosis and accelerated cognitive decline over the following years.

PMID:41478819 | DOI:10.1016/j.tjpad.2025.100450