Search Results (7,836)

Background/Objectives: Dermatitis is frequently treated with dexamethasone cutaneous application, which causes adverse effects mainly when it is chronically administered. Sesamol is a phytochemical compound known for its anti-inflammatory activity and low toxicity. Therefore, this study reports the optimization of a guar gum hydrogel with enhanced physicochemical and microbiological stability, providing an effective dosage form for topical application of sesamol nanocapsules to treat irritant contact dermatitis. Methods: Nano-based hydrogel containing 1 mg/g sesamol was prepared by adding the nanocapsule suspension to form a 2.5% (w/v) guar gum dispersion. Dynamic rheological analysis indicates that the formulations exhibit a non-Newtonian flow with pseudoplastic behavior. Hydrogels were evaluated by Fourier-transformed infrared (FTIR) spectroscopy, and, following spectrum acquisition, an unsupervised chemometrics model was developed to identify crucial variables. Additionally, the physicochemical and microbiological stability of the hydrogel was evaluated over a 60-day period. Results: ATR-FTIR spectra of all hydrogels evaluated are very similar after preparation and 60 days of storage. However, it showed a slight increase in average diameter and PDI and decreased pH values after 60 days. Microbiological assessment demonstrated that the hydrogel met the requirements for the microbial count over 60 days. The dermatitis model was induced by repeated applications of croton oil in the right ears of mice. The effectiveness of the hydrogels was evaluated by assessing ear edema and migration of polymorphonuclear cells. The nano-based hydrogel exhibited anti-inflammatory properties similar to those of dexamethasone. Conclusions: Therefore, the nano-based hydrogel containing sesamol exhibits therapeutic potential for treating cutaneous inflammatory diseases. Full article

Background/Objectives: Oral diseases are highly prevalent in Hungary and driven in part by unhealthy beverage consumption, smoking, and other behaviors. No prior study has examined the impact of beverage consumption patterns on oral health in a representative Hungarian population. This study investigated the association between beverage intake, lifestyle factors, and oral health outcomes among Hungarian adults. Methods: Data were drawn from the 2019 Hungarian European Health Interview Survey, a nationally representative cross-sectional study. Oral health outcomes and key exposures, including beverage consumption, smoking, alcohol use, and sociodemographic variables, were self-reported. Associations were assessed using multiple logistic regression models. Results: Among 5425 adults, higher dairy intake was linked to less gum bleeding (odds ratio = 0.76; 95% confidence intervals [0.59–0.96]) and lower odds of teeth missing (0.63 [0.47–0.86]). Weekly juice intake reduced gum bleeding (0.62 [0.51–0.76]) and missing teeth (0.83 [0.71–0.96]). Daily soda was associated with more gum bleeding (1.94 [1.53–2.47]), caries (1.57 [1.27–1.94]), and poor self-perceived oral health (1.32 [1.10–1.59]). Alcohol (1–4 times/week) increased gum bleeding (1.38 [1.07–1.77]) and tooth mobility (1.47 [1.02–2.11]). Smoking raised odds for caries (1.42 [1.21–1.66]) and missing teeth (1.81 [1.55–2.10]). Conclusions: Increasing dairy and fresh juice intake while reducing sugar-sweetened and acidic beverages, alongside tobacco and alcohol control and routine oral health screening, are effective strategies for improving population oral health across all sociodemographic groups. Full article

Recent advances in computational biology have provided powerful tools for analyzing, modeling, and optimizing probiotic microorganisms, thereby supporting their development as promising agents for improving human health. The essential role of the microbiota in regulating physiological processes and preventing disease has driven interest in the rational design of next-generation probiotics. This review highlights progress in in silico approaches for enhancing the functionality of probiotic strains. Particular attention is given to genome-scale metabolic models, advanced simulation algorithms, and AI-driven tools that provide deeper insight into microbial metabolism and enable precise probiotic optimization. The integration of these methods with multi-omics data has greatly improved our ability to predict strain behavior and design probiotics with specific health benefits. Special focus is placed on modeling probiotic–prebiotic interactions and host–microbiome dynamics, which are essential for the development of functional food products. Despite these achievements, key challenges remain, including limited model accuracy, difficulties in simulating complex host–microbe systems, and the absence of unified standards for validating in silico-optimized strains. Addressing these gaps requires the development of integrative modeling platforms and clear regulatory frameworks. This review provides a critical overview of current advances, identifies existing barriers, and outlines future directions for the application of computational strategies in probiotic research. Full article

Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive malignancy characterized by complex interactions within the tumor microenvironment (TME) that facilitate immune evasion and tumor progression. The TME consists of diverse cellular components, including cancer-associated fibroblasts, immune and endothelial cells, and extracellular matrix elements, that collectively modulate tumor growth, metastasis, and resistance to therapy. Immune evasion in HNSCC is orchestrated through multiple mechanisms, including the suppression of cytotoxic T lymphocytes, recruitment of immunosuppressive cells, such as regulatory T and myeloid-derived suppressor cells, and upregulation of immune checkpoint molecules (e.g., PD-1/PD-L1 and CTLA-4). Natural killer (NK) cells, which play a crucial role in anti-tumor immunity, are often dysfunctional within the HNSCC TME due to inhibitory signaling and metabolic constraints. Additionally, endothelial cells contribute to tumor angiogenesis and immune suppression, further exacerbating disease progression. Recent advancements in immunotherapy, particularly immune checkpoint inhibitors and NK cell-based strategies, have shown promise in restoring anti-tumor immunity. Moreover, TP53 mutations, frequently observed in HNSCC, influence tumor behavior and therapeutic responses, highlighting the need for personalized treatment approaches. This review provides a comprehensive analysis of the molecular and cellular mechanisms governing immune evasion in HNSCC with a focus on novel therapeutic strategies aimed at improving patient outcomes. Full article

Objectives: Diabetes Mellitus involves demanding challenges that interfere with family functioning and routines. In turn, family and social context impacts individual glycemic control. This study aims to identify this recursive interplay, the mutual influences of family systems and diabetes management. Design: Data was collected through a cross-sectional design comparing patients, aged 22–55, with and without metabolic control. Methods: Participants filled out a set of self-report measures of sociodemographic, clinical and family systems assessment. Patients (91) were also invited to describe their perception about disease management interference regarding family functioning. We first examined the extent to which family variables grouped dataset to determine if there were similarities and dissimilarities that fit with our initial diabetic groups’ classification. Results: Cluster analysis results identify a two-cluster solution validating initial classification of two groups of patients: 49 with metabolic control (MC) and 42 without metabolic control (NoMC). Independent sample tests suggested statistically significant differences between groups in family subscales- family difficulties and family communication (p < 0.05). Binary logistic regression shed light on predictors of explained variance to no metabolic control, in four models: Sociodemographic, Clinical data, SCORE-15/Congruence Scale and Eating Behavior. Furthermore, groups differ on family support, level and sources of family conflict caused by diabetes management issues. Considering only patients who co-habit with a partner for more than one year (N = 44), NoMC patients score lower on marital functioning in all categories (p < 0.05). Discussion: Family-Chronic illness interaction plays a significant role in a patient’s adherence to treatment. This study highlights the Standards of Medical Care for Diabetes, considering caregivers and family members on diabetes care. Full article

Diabetes mellites (DM) is a chronic disease with increasing prevalence worldwide and multiple health implications. Among them, sarcopenia is a metabolic disorder characterized by loss of muscle mass and function. The two age-related diseases, DM and sarcopenia, share underlying pathophysiological pathways. This narrative literature review aims to provide an overview of the existing evidence on metabolomic studies evaluating DM associated with sarcopenia. Advancements in targeted and untargeted metabolomics techniques could provide better insight into the pathogenesis of sarcopenia in DM and describe their entangled and fluctuating interrelationship. Recent evidence showed that sarcopenia in DM induced significant changes in protein, lipid, carbohydrate, and in energy metabolisms in humans, animal models of DM, and cell cultures. Newer metabolites were reported, known metabolites were also found significantly modified, while few amino acids and lipids displayed a dual behavior. In addition, several therapeutic approaches proved to be promising interventions for slowing the progression of sarcopenia in DM, including physical activity, newer antihyperglycemic classes, D-pinitol, and genetic USP21 ablation, although none of them were yet validated for clinical use. Conversely, ceramides had a negative impact. Further research is needed to confirm the utility of these findings and to provide potential metabolomic biomarkers that might be relevant for the pathogenesis and treatment of sarcopenia in DM. Full article

Down syndrome (DS), stemming from the triplication of human chromosome 21, results in intellectual disability, with early mid-life onset of Alzheimer’s disease (AD) pathology. Early interventions to reduce cognitive impairments and neuropathology are lacking. One modality, maternal choline supplementation (MCS), has shown beneficial effects on behavior and gene expression in neurodevelopmental and neurodegenerative disorders, including trisomic mice. Loss of basal forebrain cholinergic neurons (BFCNs) and other DS/AD relevant hallmarks were observed in a well-established trisomic model (Ts65Dn, Ts). MCS attenuates these endophenotypes with beneficial behavioral effects in trisomic offspring. We postulate MCS ameliorates dysregulated cellular mechanisms within vulnerable BFCNs, with attenuation driven by novel gene expression. Here, choline acetyltransferase immunohistochemical labeling identified BFCNs in the medial septal/ventral diagonal band nuclei of the basal forebrain in Ts and normal disomic (2N) offspring at ~11 months of age from dams exposed to MCS or normal choline during the perinatal period. BFCNs (~500 per mouse) were microisolated and processed for RNA-sequencing. Bioinformatic assessment elucidated differentially expressed genes (DEGs) and pathway alterations in the context of genotype (Ts, 2N) and maternal diet (MCS, normal choline). MCS attenuated select dysregulated DEGs and relevant pathways in aged BFCNs. Trisomic MCS-responsive improvements included pathways such as cognitive impairment and nicotinamide adenine dinucleotide signaling, among others, indicative of increased behavioral and bioenergetic fitness. Although MCS does not eliminate the DS/AD phenotype, early choline delivery provides long-lasting benefits to aged trisomic BFCNs, indicating that MCS prolongs neuronal health in the context of DS/AD. Full article

Background/Objectives: Neuromedin U (NMU) is a highly conserved gene encoding a neuropeptide involved in the regulation of feeding behavior and energy homeostasis. We aimed to analyze the association between NMU genetic and epigenetic variations and cardio-metabolic parameters in an Italian population to identify the role of these variants in cardio-metabolic risk. Methods: A total of 4028 subjects were randomly selected from the Moli-sani study cohort. NMU haplotypes were estimated using seven SNPs located in the gene body and in the promoter region; DNA methylation levels in the promoter region, previously associated with lipid-related variables in the same population, were also used. Results: Among the haplotypes inferred, the haplotype carrying the highest number of minor variants (frequency 16.6%), when compared with the most frequent haplotype, was positively associated with insulin levels, HOMA-IR, and diastolic blood pressure, and negatively with HDL-cholesterol. The multivariable analysis that considered methylation levels along with their interactions with SNPs showed that increased methylation levels in two close CpG sites were associated with higher levels of lipid-related variables. Conclusions: This study supports a role for NMU as a regulator of human metabolism. This finding suggests that NMU could be a potential target for preventive interventions against coronary and cerebrovascular diseases, and that NMU genetic and epigenetic variability may serve as a biomarker for cardio-metabolic risk. Full article

Accurate detection of Alzheimer’s disease (AD) is critical yet challenging for early medical intervention. Deep learning methods, especially convolutional neural networks (CNNs), have shown promising potential for improving diagnostic accuracy using magnetic resonance imaging (MRI). This study aims to identify the most informative combination of MRI slice orientation and anatomical location for AD classification. We propose an automated framework that first selects the most relevant slices using a feature entropy-based method applied to activation maps from a pretrained CNN model. For classification, we employ a lightweight CNN architecture based on depthwise separable convolutions to efficiently analyze the selected 2D MRI slices extracted from preprocessed 3D brain scans. To further interpret model behavior, an attention mechanism is integrated to analyze which feature level contributes the most to the classification process. The model is evaluated on three binary tasks: AD vs. mild cognitive impairment (MCI), AD vs. cognitively normal (CN), and MCI vs. CN. The experimental results show the highest accuracy (97.4%) in distinguishing AD from CN when utilizing the selected slices from the ninth axial segment, followed by the tenth segment of coronal and sagittal orientations. These findings demonstrate the significance of slice location and orientation in MRI-based AD diagnosis and highlight the potential of lightweight CNNs for clinical use. Full article

Transcription factors play crucial roles in regulating gene expression, and any dysregulation in their levels could be involved in cancer progression. The role of androgen receptors (AR) and zinc finger (ZNF) proteins in tumors, like prostate cancer (PC), remains poorly understood. Moreover, due to the multifaceted transcriptional behavior of ARs and ZNFs, their biological role in cancer progression may also depend on the interplay with micro-RNAs (miRNAs). Based on The Cancer Genome Atlas (TCGA) database, we analyzed the expression levels of zinc finger transcripts and ARs in PC. Specifically, exploring their involvement in cancer progression and regulation by miRNAs. The analysis relied on several tools to create a multivariate combination of the original biomarkers to improve their diagnostic efficacy. Multidimensional Scaling (MDS) identified two new dimensions that were entered into a regression analysis to determine the best predictors of overall survival (OS) and disease-free interval (DFI). A combination of both dimensions predicted almost 50% (R² = 0.46) of the original variance of OS. Kaplan–Meier survival analysis also confirmed the significance of these two dimensions regarding the clinical output. This study showed preliminary evidence that several transcription factor expression levels belonging to the zinc family and related miRNAs can effectively predict patients’ overall PC survivability. Full article

Background/Objective: Understanding how chronic conditions such as knee osteoarthritis (OA) and chronic obstructive pulmonary disease (COPD) influence long-term physical activity (PA) is essential for developing condition-specific rehabilitation strategies. This study aimed to examine whether baseline diagnoses of knee OA and COPD are independently associated with the trajectories of PA decline over five years in U.S. adults, informed by the disablement process model. Methods: We analyzed data from 855 adults aged ≥45 years enrolled in the Osteoarthritis Initiative (OAI). The participants were categorized into three baseline groups, control (n = 122), knee OA (n = 646), and COPD (n = 87), based on self-reports and prior clinical assessments. PA was measured annually for five years using the Physical Activity Scale for the Elderly (PASE). General linear mixed models assessed changes in PA over time, adjusting for demographic, behavioral, and clinical covariates. Results: Compared to the controls, participants with knee OA had a significant decline in PA over time (β = −6.62; 95% CI: −15.4 to −2.19; p = 0.014). Those with COPD experienced an even greater decline compared to the knee OA group (β = −11.2; 95% CI: −21.7 to −0.67; p = 0.037). These associations persisted after adjusting for age, sex, body mass index, comorbidities, and smoking. Conclusions: Baseline knee OA and COPD were independently associated with long-term reductions in PA. These findings underscore the importance of early, tailored rehabilitation strategies, particularly pulmonary rehabilitation, in preserving functional independence among older adults with chronic conditions. Full article

Background/Objectives: Pulmonary typical carcinoid (TC) is a rare type of primary neuroendocrine neoplasm of the lung with indolent behavior and a good prognosis. The main treatment strategy is surgery, the extent of which is controversial given the nature of the disease. The aim of this study is to assess whether the extent of resection influences survival and recurrence in patients undergoing lung resection and lymphadenectomy for TC and to investigate negative prognostic factors for OS. Methods: A single-centre retrospective study of 15 years’ experience was conducted. Data from all patients who underwent lung resection and lymphadenectomy for TC were collected. Patients were divided into two groups: anatomical and non-anatomical resections. Perioperative and long-term oncological results were analyzed. Results: In total, 115 patients were surgically treated for TC, of whom 83 (72%) underwent anatomical resection and 32 (28%) non-anatomical resection. Univariate analyses showed that age, left lower lobe, and many comorbidities had a detrimental effect on OS, whereas on multivariate analysis, only left lower lobe location and a high Charlson–Deyo comorbidity index (CCI) were confirmed as negative prognostic factors for OS. At a median follow-up of 93 months (IQR 57-129), the OS survival curves show a slightly lower trend for non-anatomical resections (p 0.152), while no differences were found for DFS. Conclusions: The results of this study confirm that in selected patients at risk for major resections, non-anatomical resection can be used to treat TC when R0 is achievable. These data, together with evidence from the literature, highlight the importance of patient-centred care in this rare disease. Full article

Understanding the components of the diet, food groups, and nutritional strategies that help prevent MASLD (Metabolic Dysfunction-Associated Steatotic Liver Disease) is essential for identifying dietary behaviors that can stop the progression of this condition, which currently affects over one-quarter of the global population. This review highlights the importance of including antioxidant nutrients in the diet, such as vitamins C and E, CoQ10, and polyphenolic compounds. It also emphasizes substances that support lipid metabolism, including choline, alpha-lipoic acid, and berberine. Among food groups, it is crucial to choose those that help prevent metabolic disturbances. Among carbohydrate-rich foods, vegetables, fruits, and high-fiber products are recommended. For protein sources, eggs, fish, and white meat are preferred. Among fat sources, plant oils and fatty fish are advised due to their content of omega-3 and omega-6 fatty acids. Various dietary strategies aimed at preventing MASLD should include elements of the Mediterranean diet or be personalized to provide anti-inflammatory compounds and substances that inhibit fat accumulation in liver cells. Other recommended dietary models include the DASH diet, the flexitarian diet, intermittent fasting, and diets that limit fructose and simple sugars. Additionally, supplementing the diet with spirulina or chlorella, berberine, probiotics, or omega-3 fatty acids, as well as drinking several cups of coffee per day, may be beneficial. Full article

Background: Chlamydia trachomatis is the most prevalent bacterial sexually transmitted infection (STI) globally, linked to severe complications such as pelvic inflammatory disease and infertility. In the Brazilian Amazon, socioeconomic vulnerability and the absence of screening policies exacerbate risks, particularly among female sex workers (FSWs). Objective: This study aimed to determine the seroprevalence of anti-C. trachomatis IgG antibodies among FSWs in five municipalities of Pará State, Brazilian Amazon, and identify epidemiological factors associated with infection. Methods: A retrospective cross-sectional study (2005–2007) included 348 FSWs recruited via convenience sampling. Sociodemographic and behavioral data were collected through questionnaires, and blood samples were analyzed by ELISA for anti-C. trachomatis IgG. Statistical analyses included Fisher’s exact tests, odds ratios (ORs), and 95% confidence intervals (CIs), using SPSS 21.0. Results: Overall seroprevalence was 93.9% (327/348; 95% CI: 83.1–90%). Significant associations included a household income of 1–3 minimum wages (98.4%; p = 0.0002), sexual partners from the same region (98.8%; p = 0.0421), and age >42 years (96.3%). Most reported inconsistent condom use (43.7%), multiple monthly partners (54.6%), and illicit drug use (53.4%). Discussion: The extremely high seroprevalence reflects chronic C. trachomatis exposure, driven by socioeconomic deprivation and limited healthcare access. Comparisons with global data underscore the urgent need for screening policies, absent in Brazil for FSWs, and highlight the vulnerability of this population. Conclusions: The findings reveal an alarming burden of C. trachomatis exposure among Amazonian FSWs. Integrated strategies, including routine screening, sexual health education, and inclusion of FSWs in priority health programs, are critical to reduce transmission and associated complications. Full article

A multilayer linear response model (MLRM) is proposed to generate time-series data based on linear response theory. The proposed MLRM is designed to generate data for anomalous dynamics by extending the conventional single-layer linear response model (SLRM) into multiple layers. While the SLRM is a linear equation with respect to external forces, the MLRM introduces nonlinear interactions, enabling the generation of a wider range of dynamics. The MLRM is applicable to various fields, such as finance, as it does not rely on machine learning techniques and maintains interpretability. We investigated whether the MLRM could generate anomalous dynamics, such as those observed during the coronavirus disease 2019 (COVID-19) pandemic, using pre-pandemic data. Furthermore, an analysis of the log returns and realized volatility derived from the MLRM-generated data demonstrated that both exhibited heavy-tailed characteristics, consistent with empirical observations. These results indicate that the MLRM can effectively reproduce the extreme fluctuations and tail behavior seen during high-volatility periods. Full article