Abstract: Introduction: In preeclampsia (PE), impaired trophoblast proliferation and differentiation are thought to cause abnormal placentation and subsequent clinical manifestations of the disease—i.e., hypertension, proteinuria, and end-organ damage. Insulin-like growth factor 1 (IGF-1) influences trophoblast cell function, however the mechanisms of IGF-1’s action on trophoblasts is not well understood. Inhibitor of DNA binding protein 2 (ID2) is involved in trophoblast differentiation and implicated in many processes disrupted in PE including placental development, vascular differentiation, and angiogenesis. We hypothesized that IGF-1 regulates trophoblast proliferation and differentiation via ID2. Methods: Immortalized human first trimester trophoblast cells (HTR-8/SVneo) were treated with IGF-1 for 24 hours after serum starvation. ID2 mRNA and protein were measured, as well as trophoblast cell viability, proliferation, tube formation and migration. Results: IGF-1 decreased ID2 expression in a dose-dependent manner. IGF-1 decreased trophoblast proliferation but increased cell viability, differentiation, and migration. ID2 overexpression mitigated the effects of IGF-1 on trophoblast cells. Discussion: These data suggest IGF-1 could regulate trophoblast proliferation and differentiation through ID2. Dysregulation of ID2-mediated IGF-1 signaling in trophoblast cells could be involved in the pathogenesis of pregnancy disorders like uterine growth restriction and PE.

Abstract: Kidney cancer has become a major global health issue over time, showing how early detection can play a very important role in mediating the disease. Traditional histological image analysis is recognized as the clinical gold standard for diagnosis although it is highly manual and labor-intensive. Due to this issue, many are interested in comput-er-aided diagnostics technologies to assist pathologists in their diagnostic. Specifically, deep learning (DL) has become a viable remedy in this field. Nonetheless, the capacity of existing DL models to extract comprehensive visual features for accurate classification is limited. Towards the end, this study proposes using ensemble models that combine the strengths of multiple transformers and deep learning model architectures. By leveraging the collective knowledge of these models, the ensemble enhances classification perfor-mance and enables more precise and effective kidney cancer detection. This study compares the performance of these suggested models to previous studies, all of which used the publicly accessible Dartmouth Kidney Cancer Histology Dataset. This study showed that the Vision Transformers, with an average accuracy of over 99%, were able to achieve high detection accuracy across all complete slide picture patches. In particular, the CAiT, DeiT, ViT, and Swin models outperformed ResNet. All things considered, the vision Transformers consistently produced an average accuracy of 98.51% across all five folds 5 folds. These results demonstrated that Vision Transformers might perform well and successfully identify important features from smaller patches. Through utilizing histo-pathological images, our findings will assist pathologists in diagnosing kidney cancer, resulting in early detection and increased patient survival rates

Abstract: Background Cancer is one of the most concerning public health issues in the world. One of cancer hallmarks wildly accepted is sustaining proliferative signaling, which involved most of the cell cycle biological activities. Centromeric histone, Centromere Protein A (CENPA), a variant of canonical histone H3, plays an essential role in selective chromosome segregation in the cell cycle. However, so far, a systematic pan-cancer bioinformatic analysis has not been done yet. Methods We accessed genome, transcriptome, and clinical information from open databases. The genetic alteration, mRNA expression, functional enrichment, stemness, mutation association, expression in cell populations and cellular locations, cell cycle association, survival association of CENPA, and immune association were analyzed. A prognostic model for glioma patients was constructed as an example application of CENPA as a biomarker. Drugs targeting CENPA in cancer cells were also screened and predicted by the CENPA correlation of drug sensitivity and protein-ligand docking. Results CENPA had low gene mutation in cancers. CENPA was overexpressed in almost all cancer types in TCGA compared to their normal control. CENPA was highly expressed in the nucleus of malignant cells. CENPA was associated with the cell cycle of cancer cells. CENPA is a biomarker for the cell cycle G2 phase in cancer cells. CENPA was a diagnostic and prognostic biomarker across multiple cancer types. The prognosis of glioma with CENPA was reliable and can be applied with other prognostic factors. CENPA was associated with the immune microenvironment. Drugs CD-437, 3-Cl-AHPC, Trametinib, BI-2536, and GSK461364 were predicted to target CENPA in cancer cells. Conclusion CENPA was a cell cycle biomarker in cancers with diagnostic and prognostic value.

Abstract: Background and Objective: Chronic Obstructive Pulmonary Disease (COPD) remains a critical global health challenge, char-acterized by high morbidity, mortality, and healthcare costs. Current guidelines may overlook pa-tients who present with only one moderate exacerbation or frequent short-acting beta-agonist (SABA) use. Building on findings from the Seleida study, this research refines the criteria for poor COPD control to include these patients, aiming to improve early identification of high-risk cases in primary care. Methods: A retrospective, multicenter study was conducted using data from 110 COPD patients in Spain. Poor control was redefined as having at least one moderate exacerbation or using three or more SABA inhalers annually. Key predictors, such as SABA/short-acting muscarinic antagonist (SAMA) inhalers and antibiotic prescriptions, were identified using logistic regression and LASSO regular-ization to enhance predictive accuracy. Results: The model demonstrated excellent predictive performance with an AUC-ROC of 0.978, sensitivity of 92.86%, and specificity of 87.50%. Key predictors effectively identified high-risk patients, facili-tating timely interventions. Although the variable ‘daily inhalation frequency’ (categorized as 1 vs. >1 inhalation/day) showed that patients using a single inhalation daily had significantly better control than those requiring multiple doses (p = 0.018), it was excluded to avoid model overfitting. Conclusions: By refining the criteria for COPD control to include patients with at least one moderate exacerbation or frequent SABA use, this model provides a practical tool for early risk stratification in primary care, particularly in resource-limited settings. Early identification of high-risk patients can reduce hospitalizations and healthcare costs, supporting a proactive approach to COPD management. Further validation in larger cohorts is essential to confirm its broader applicability.

Abstract: Objective: This study aimed to compare the early maladaptive schemas and adult attachment profiles of patients with major depressive disorder with healthy controls and to determine their relationships with disease variables. Method: The study included 118 patients with major depressive disorder and 92 healthy volunteers, and the Sociodemographic and Clinical Data Form, Young Schema Scale Short Form-3, Inventory of Experiences in Close Relationships II and Beck Depression Inventory were administered. Results: The patient group had higher scores than the control group for all schema subtypes and attachment scores. Significant differences were found for some schemas between patients with chronic depression and patients with recurrent depressive episodes, between patients with a history of one hospitalization and patients with a history of multiple hospitalizations, and between patients with suicide attempts and patients with no suicidal ideation attempts. Significant positive correlations were found between the attachment scores, schema scores and depression severity of the patients and the control group. Conclusion: Further research is needed to determine the role of schemas and attachment styles in the development of depression in more detail and to focus on schema and attachment-based therapies in treatment.

Abstract: A growing body of evidence indicates a link between circulating neurotoxic lipids and the development of chronic neuroinflammatory diseases in the peripheral and central nervous systems. Therefore, strategies to modify circulating lipid profiles may complement the management of neuroinflammatory diseases, including neuropathic pain. In a previous study, we observed a sig-nificant shift in the metabolomic profile of patients' plasma with symptoms of painful diabetic neuropathy (pDN) following three months of docosahexaenoic acid (DHA)-rich supplementation, leading to improved pDN symptoms. However, it is important to identify the specific lipid mediators responsible for this therapeutic effect and elucidate potential mechanism(s). This study investigates whether DHA-rich supplementation reduces neurotoxic lipid mediators associated with pDN in individuals with type 2 diabetes mellitus (T2DM). Forty volunteers diagnosed with type 2 diabetes were enrolled in the "En Balance-PLUS" diabetes education study. The volunteers participated in weekly lifestyle/nutrition education and daily supplementation with 1000 mg DHA and 200 mg eicosapentaenoic acid. The Short-Form McGill Pain Questionnaire validated the clinical determination of baseline and post-intervention pain complaints. Untargeted Lipidomic analyses were conducted using blood serum collected at baseline and after three months of participation in the dietary regimen. The lipidomic data were analyzed using a non-parametric paired Wilcoxon rank-sum test and random forest analysis. ELISA further eval-uated participant serum samples to investigate associated biomarkers of necrosis (MLKL), autophagy (ATG5), and lipid chaperone protein (FABP5). Untargeted lipidomic analysis revealed that several neurotoxic-associated lipids significantly decreased after DHA-rich supplementation. Also, circulating levels of MLKL were reduced, while protein levels of ATG5 and FABP5 significantly increased. The reduction of circulating neurotoxic lipids and increase of neuroprotective lipids following DHA-rich supplementation is consistent with the reported roles of omega-3 polyunsaturated fatty acids (PUFAs) in reducing adverse symptoms associated with neuroinflammatory diseases and painful neuropathy.

Abstract: B3 breast lesions, classified as lesions of uncertain malignant potential, present a significant di-agnostic and therapeutic challenge due to their heterogeneous nature and variable risk of pro-gression to malignancy. These lesions, which include atypical ductal hyperplasia (ADH), papil-lary lesions (PL), flat epithelial atypia (FEA), radial scar (RS), lobular neoplasia (LN), and phyl-lodes tumors (PT), occupy a "grey zone" between benign and malignant pathologies, making their management complex and often controversial. This article explores the diagnostic difficul-ties associated with B3 lesions, focusing on the limitations of current imaging techniques, in-cluding mammography, ultrasound, and magnetic resonance imaging (MRI), as well as the chal-lenges in histopathological interpretation. Core needle biopsy (CNB) and vacuum-assisted bi-opsy (VAB) are widely used for diagnosis, but both methods have inherent limitations, includ-ing sampling errors and the inability to determine malignancy in some cases definitively. The therapeutic approach to B3 lesions is nuanced, with treatment decisions strongly influenced by factors such as lesion size, radiological findings, histopathological characteristics, and patient factors. While some lesions can be safely monitored with watchful waiting, others may require vacuum-assisted excision (VAE) or surgical excision to rule out malignancy. The deci-sion-making process is further complicated by the discordance between the BIRADS score and biopsy results, as well as the presence of additional risk factors, such as microcalcifications. This review provides an in-depth analysis of the current diagnostic challenges and treatment strate-gies for B3 lesions, emphasizing the importance of a multidisciplinary approach to management. By synthesizing the most recent research, the article aims to provide clinicians with a clearer understanding of the complexities involved in diagnosing and treating B3 breast lesions while highlighting areas for future research, such as Artificial Intelligence and Genomics, to improve diagnostic accuracy and patient outcomes.

Abstract: Introduction: Obstructive sleep apnea (OSA) is a condition characterized by intermittent airway obstructions, leading to reduced oxygen levels and increased sympathetic nervous system activity. OSA can cause a range of health problems, including an increased risk of cardiovascular diseases and mortality. Galectin-3, a member of the galectin family, plays a significant role in inflammation and fibrosis. It is elevated in various conditions, including heart and lung diseases. The aim of this study was to determine whether galectin-3 levels are related to the severity of sleep apnea. Materials and methods: A total of 191 participant from University Clinical Hospital Center Bezanijska Kosa, Belgrade, Serbia, between January 2023, and May 2024. was included in the analyses. All patients have been hospitalized under suspicion of OSA, and they have all undergone a polysomnography test. Various demographic, respiratory, laboratory, and clinical parameters were obtained. Correlations between numerical variables and galectin-3 were assessed by the Pearson or Spearman correlation coefficient. Univariate and multivariate linear regression models were used to assess predictors of galectin-3 values. In all analyses, the significance level was set at 0.05. Results: The mean age of study participants was 56.2 years, mostly male (68.9%). Of comorbidities, two thirds of patients had hypertension (66.1%), 46.8% had hyperlipoproteinemia, and 21.1% had diabetes mellitus. Galectin-3 values significantly differed according to the examined groups (p=0.038), where patients who had an AHI of less than fifteen events per hour more often had lower values of galectin-3 in contrast to patients who had AHI of at least 15 events per hour, but fewer than 30 (p=0.019) and an AHI of at least 30 events per hour (p=0.046). In multivariate linear regression analysis significant independant predictors of higher galectin-3 values were older age, presence of coronary disease, hypoventilation syndrome, higher BMI, NTproBNP, lactate, creatinine, lower LDL, and lower FEV1 (p<0.05). Conclusion: The present study demonstrated that galectin-3 is linked to the severity of OSA and plays a crucial role in inflammation induced by intermittent hypoxia in OSA. Further screening and interventions targeting galectin-3 could aid in preventing inflammatory diseases related to sleep disturbances.

Abstract:

Background and Objectives: This study aims to assess the bone implant osseointegration after the healing process of machined, reabsorbable blast material (RBM) and sandblasted and large acid grid (SLA) surface titanium implants placed simultaneously using graft material in rat tibias. Materials and Methods: The study involved 30 Sprague Dawley rats that were divided into three groups: machined surfaced (MS) (n = 10), resorbable blast material (RBM) (n = 10), and sandblasted and large acid grid (SLA) surfaced (n = 10). The titanium implants were inserted into the bone sockets along with the graft, and the rats were euthanized after a 4-week experimental period. The implants and the bone tissue surrounding them were extracted for reverse torque analysis (Newton’s). Results: The biomechanical bone implant contact rate was greater in SLA-surfaced implants than in RBM and machined surface implants (P<0.05). Conclusions: The application of graft material may be more effective in implants with SLA and RBM surfaces when used locally, as per the biomechanical parameters.

Abstract: Background/Objetives: Elderly populations are under-represented in inflammatory bowel disease (IBD) clinical trials, with limited data on phenotype, treatment patterns, outcomes and comorbidities. The main objective of this study was to evaluate, in an elderly cohort with IBD, demographic and disease characteristics, comorbidity, polypharmacy and treatment patterns according to the development of IBD at or before old age. Secondarily, the same analysis was done based on the type of IBD: ulcerative colitis (UC) or Crohn's disease (CD).Material and methods: Observational, single-center, retrospective study including 118 patients diagnosed with IBD and aged 65 years or older seen at the IBD office of the Regional University Hospital of Malaga between September and November 2022. Data were recorded on demographic, disease-related and IBD treatment-related variables, comorbidities and polypharmacy. A descriptive and analytical study was undertaken according to the age of IBD onset and type of IBD.Results: Of the patients included, 50.8% were male, 55.1% had CD and 44.9% UC. IBD onset was before age 65 years in 69.5% and ≥65 years in 30.5%. Elderly with IBD who debuted