Piper methysticum, traditionally used in the Pacific for religious, medical, and social purposes, has garnered recent fame as a nutraceutical for anxiety treatment. Sansevieria trifasciata (snake plant) has antibacterial, cytotoxic, and wound-healing properties. The ethanolic extracts of both plants were studied for their chemical group, antimicrobial, and CNS depressant effects. The disc diffusion method was used to assess the antimicrobial activity of Piper methysticum and Sansevieria trifasciata. Their central nervous system (CNS) depressant effects were evaluated using classical depression models, including hole cross, elevated maze, forced swimming, and tail suspension tests in Swiss albino mice. Mice were divided into control, positive control, and three test groups, with doses of 250 mg/kg and 500 mg/kg for hole cross and elevated maze tests, and 50, 100, and 200 mg/kg for forced swimming and tail suspension tests. Diazepam was used as the standard drug. Phytochemical screening of both plant extracts revealed the presence of alkaloids, flavonoids, reducing sugars, steroids, saponins, terpenoids, and amino acids. Both ethanolic extracts exhibited strong antibacterial activity in disk diffusion testing. S. trifasciata was most effective against E. coli and S. cerevisiae, while P. methysticum showed significant antimicrobial activity against Shigella dysenteriae and Salmonella typhi. In the hole cross test, both extracts significantly reduced locomotor activity across all doses (P<0.01), indicating CNS depressant effects. However, neither extract showed significant changes in the number of entries or time spent in the open arms during the elevated maze test. Both extracts significantly reduced immobility time in the forced swimming and tail suspension tests (P < 0.01 and P < 0.001), with diazepam increasing immobility time (P < 0.001). These results suggest that both plant extracts have CNS depressive and antidepressant-like effects. Both the ethanolic extracts of P. methysticum and S. trifasciata demonstrate antimicrobial and CNS depressant effects. Further studies are needed to continue pharmacological research for their potential use in medicine.

Abstract
Introduction: Periodontitis is a widespread chronic inflammatory condition characterized by the progressive destruction of periodontal tissues, leading to tooth loss and systemic complications, including adverse effects on cardiac function. Despite the well-documented regenerative potential of mesenchymal stem cells (MSCs), the comparative efficacy of local versus systemic administration of adipose-derived MSCs (AD-MSCs) in addressing both periodontal and cardiac dysfunction remains insufficiently studied. This research aimed to investigate the therapeutic impact of AD-MSCs in mitigating periodontitis and its systemic repercussions, with a focus on cardiac health.

Methods: AD-MSCs were isolated and characterized based on their morphology, surface marker expression (CD29, CD90, and CD45), and multi-lineage differentiation potential. A rat model of ligature-induced periodontitis was established to mimic chronic periodontal inflammation. Following the induction of periodontitis, AD-MSCs were either administered locally or systemically. Periodontal regeneration was assessed using clinical and imaging methodologies, while cardiac function was evaluated through echocardiography to measure systolic and diastolic parameters.

Results: The AD-MSCs retained their mesenchymal properties and regenerative capacity throughout the experiment. Local administration significantly enhanced periodontal regeneration, reduced inflammation, and improved systolic cardiac performance, as evidenced by higher ejection fraction and fractional shortening. Histological analysis revealed reduced myocardial fibrosis and better cardiomyocyte alignment in locally treated groups. However, persistent diastolic abnormalities in both treatment groups highlighted the need for extended therapeutic interventions to achieve comprehensive cardiac recovery.

Conclusions: This study demonstrates that the local delivery of AD-MSCs yields superior outcomes in treating periodontal and systemic inflammatory conditions, including improved cardiac function. These findings emphasize the need for tailored stem cell delivery strategies to optimize regenerative therapies for clinical applications.

Abstract
Introduction: Adipose-derived mesenchymal stem cells (AD-MSCs) have emerged as a promising tool in regenerative medicine, particularly in cardiac repair. These cells are recognized for their capacity to differentiate into cardiomyocyte-like cells under specific conditions. However, the influence of their anatomical origin on their metabolic profiles and differentiation potential has not been fully elucidated. This study investigates AD-MSCs from two distinct anatomical locations—peri-ovarian and peri-renal adipose tissue—to determine how their origin impacts their ability to differentiate into cardiomyocyte-like cells.

Methods: AD-MSCs were isolated from peri-ovarian and peri-renal fat of female rats and characterized by their morphology, surface marker expression, and trilineage differentiation potential. Cardiomyocyte differentiation was induced using 5-azacytidine. Cellular responses were evaluated through morphological analysis, immunofluorescence staining for cardiac troponin T (cTnT), and untargeted metabolomic profiling using gas chromatography–mass spectrometry (GC-MS).

Results: Both peri-ovarian and peri-renal AD-MSCs displayed characteristic mesenchymal morphology, surface marker profiles, and multi-lineage differentiation potential. While both groups successfully differentiated into cardiomyocyte-like cells, metabolomic profiling revealed distinct metabolic adaptations. Peri-ovarian AD-MSCs demonstrated heightened activity in glycolysis, fructose metabolism, glycerolipid metabolism, and the TCA cycle, suggesting a more robust metabolic reprogramming suited for differentiation. In contrast, peri-renal AD-MSCs showed increased reliance on galactose metabolism. Immunofluorescence staining confirmed the expression of cTnT in differentiated cells from both groups.

Conclusions: These findings highlight the critical role of anatomical origin in shaping the metabolic and differentiation capabilities of AD-MSCs. Peri-ovarian AD-MSCs exhibited superior metabolic reprogramming, positioning them as a more favorable source for cardiac tissue engineering and regenerative applications.

Introduction: Parkinson’s disease (PD), the most common ataxia in the world, occurs as a consequence of the loss of dopaminergic neurons. First-line treatment for PD is focused on dopamine (DA) potentiation, with the administration of levodopa, a DA precursor, and co-administration of inhibitors of the catechol-O-methyl transferase and monoamine oxidase B enzymes. However, prolonged use leads to significant health complications, highlighting the need for alternative pharmacological strategies. Melanostatin (MIF-1), an endogenous hypothalamic neuropeptide, acts as a positive allosteric modulator (PAM) of the dopamine D₂ receptors (D₂R). By enhancing these receptor's affinity for DA, MIF-1 enables their activation at lower DA levels, making it a promising candidate for the treatment of dopamine-related disorders such as PD.

Methodology: In previous studies, our research group developed promising MIF-1 mimetics by bioisosteric substitution of L-Proline (Pro) residue by 2-furoic acid (2-Fu). To study the influence of the position of the oxygen atom in the furanyl motif on PAM activity, eight novel MIF-1 analogs were synthesized by incorporation of 3-furoic acid (3-Fu) as a 2-Fu surrogate, using a previously established protocol. Preliminary pharmacological functional assays were conducted in Chinese hamster ovary cells transfected with human D₂R to assess cyclic adenosine monophosphate (cAMP) mobilization.

Results: Peptidomimetics 4a and 6a statistically increased dopamine potency (EC₅₀ = 0.53 ± 0.17 μM), with EC₅₀ values of 0.28 ± 0.10 and 0.13 ± 0.07 μM, respectively, at 0.01 nM, being comparable with the parent neuropeptide (EC50 = 0.17 ± 0.07 μM). Both peptidomimetics also displayed no agonism effect in the absence of dopamine, confirming their activity as PAMs.

Conclusions: Overall, the remarkable pharmacological profiles of these peptidomimetics validate 3-Fu as a promising Pro bioisostere, paving the way for the rational development of novel PAMs for application in PD.

Acknowledgments: This work received support and help from FCT/MCTES (2023.14440.PEX DOI: 10.54499/2023.14440.PEX, 2022.01175.PTDC DOI: 10.54499/2022.01175.PTDC, LA/P/0008/2020 DOI 10.54499/LA/P/0008/2020, UIDP/50006/2020 DOI 10.54499/UIDP/50006/2020, and UIDB/50006/2020 DOI 10.54499/UIDB/50006/2020), through national funds. I.E.S.-D. thanks FCT for funding through the Individual Call to Scientific Employment Stimulus with Grant 2020.02311.CEECIND/CP1596/CT0004 (DOI: 10.54499/2020.02311.CEECIND/CP1596/CT0004). B.L.P.-L., X.C.C., and H.F.C.-A. thank FCT for the Ph.D. grants 2022.14060.BD, 2024.02245.BD, and UI/BD/154888/2023, respectively. X.G.-M. thanks Xunta de Galicia for financial funding with reference GPC2020/GI1597.

Background: Immunotherapy by Immune Checkpoint Inhibitors (ICIs) has revolutionized the treatment landscape of non-small-cell lung cancer (NSCLC), thereby significantly improving survival outcomes and offering renewed hope to patients with advanced disease. However, patients experience limited long-term benefits from ICIs due to the development of primary or acquired immunotherapy resistance, as well as adverse effects (irAEs). In this study, we investigated the immunological status at baseline and during treatment of NSCLC patients receiving ICI treatment following the prediction of the predictive biomarkers associated with irAEs of an autoimmune nature.

Methods: In the LIMBIO study, NSCLC patients (n=51) received ICI treatment up to X months. Patient samples were collected at baseline and endpoint with or without irAEs and immunologically profiled using biomarker assays, quantitative mass spectrometry-based proteomics, and high-density autoantibody reactive protein arrays to characterize potential irAE biomarker panels.

Results: A total of 76% developed irAEs, whereby a large fraction were autoimmune in nature. Based on the quantitative plasma proteomics data of the NSCLC cohort obtained from investigating the patients, we could not distinguish between the irAE and the non-irAE groups, and the proteins most identified were found from comparisons between endpoint and baseline. Global oncogene-focused protein arrays, however, could identify differentially expressed autoantibodies between the two baselines, suggesting that the patients in the irAE group are predisposed for irAEs due to the high presence of preexisting autoantibodies at baseline.

Conclusions: Our proteomic investigation revealed changes and an association between inflammatory signaling and the dynamic variation of autoantibodies between baseline patients and irAE-affected patients. An elevated level of autoantibodies may serve as predictive biomarker candidates for the prediction of ICI-induced irAEs.

Abnormal cell growth in the brain characterizes brain tumors, which are primarily diagnosed through histopathological examination. Non-invasive neuroimaging techniques, such as MRI, provide critical diagnostic insights; however, the size and complexity of MRI data pose challenges for effective analysis. While traditional AI methods are effective in medical data analysis, factors such as the expansion of high-resolution medical datasets and noise levels in the data impact the diagnostic process. Recent studies have shown that the application of quantum AI technologies in healthcare not only addresses these issues, but also accelerates complex data analyses, providing a significant advantage, especially in dealing with heterogeneous and unevenly distributed datasets. In this study, a quantum deep neural network (QDNN) model is proposed to distinguish four different classes—glioma, meningioma, pituitary tumors, and cases without tumors—based on data from 7023 individuals obtained from the Kaggle open data portal, aiming for the highest accuracy. During preprocessing, image enhancement techniques were applied using the OpenCV library to optimize data quality. Subsequently, the proposed QDNN model was employed for classification. In the model, amplitude encoding was utilized to map MR image data from classical space to quantum Hilbert space, followed by a multi-layer parameterized quantum circuit (multi-layer PQC). The multi-layer PQC model consists of single-qubit Rx gates, along with a CNOT gate that provides circular entanglement between qubits. As a result, the proposed model achieved final training loss and validation loss values of 0.61 and 0.64, respectively, while the training accuracy and validation accuracy values were 0.76 and 0.77, respectively. When compared to a classical DNN model with a similar number of parameters, the proposed quantum model demonstrates superior performance in terms of both accuracy and total processing time. These results highlight the potential of quantum AI in improving diagnostic accuracy in biomedical imaging.

Introduction:

Galectin-3, a β-galactoside-binding protein, plays a crucial role in inflammation and insulin resistance in Type 2 Diabetes Mellitus (T2DM). This study investigated how Retatrutide, a novel GLP-1/GIP/glucagon receptor triple agonist, modulates the Galectin-3 pathway. Recent advances in multi-omics data analysis have highlighted the complexity of Galectin-3 signaling in Type 2 Diabetes Mellitus (T2DM). This bioinformatic study employed network analysis and pathway modeling to elucidate how Retatrutide, a novel triple receptor agonist, influences the Galectin-3 regulatory network.

Methodology:

We developed a computational framework integrating protein--protein interaction networks, pathway enrichment analysis, and dynamic modeling. Gene expression profiles were analyzed. This study incorporated regulatory network construction focusing on LGALS3 and associated genes, pathway topology analysis, and temporal expression pattern modeling. Key pathway components were mapped using directed graph theory and centrality metrics.

Results:

Network analysis identified five major regulatory hubs within the Galectin-3 pathway, with LGALS3 showing high betweenness centrality (0.85). Pathway enrichment revealed significant modulation of inflammatory cascades (p<0.001) and insulin signaling networks (p<0.01). Temporal expression modeling demonstrated biphasic regulation of LGALS3, with early suppression (-40%) followed by sustained down regulation. Graph theory analysis identified novel regulatory motifs linking GLP-1R activation to LGALS3 suppression through cAMP-dependent pathways.

Conclusion:

Our bioinformatic approach revealed previously uncharacterized regulatory mechanisms in Retatrutide's modulation of the Galectin-3 pathway. Network topology analysis suggests that Retatrutide's effects are mediated through coordinated regulation of multiple signaling nodes, rather than linear pathway suppression. These computational findings provide a systems-level understanding of Retatrutide's mechanism of action and identify potential therapeutic targets for experimental validation.

Retatrutide, a novel triple-GIP/GLP-1/glucagon receptor agonist, has emerged as a promising therapeutic agent for type 2 diabetes mellitus (T2DM). This in silico study investigated the molecular mechanisms underlying Retatrutide's effects on insulin resistance pathways through comprehensive bioinformatics analysis. Using molecular docking simulations and protein–ligand interaction studies, we examined Retatrutide's binding affinities to GIP, GLP-1, and glucagon receptors, revealing high-affinity interactions with all three target receptors, demonstrating particularly strong binding to the GLP-1 receptor's extracellular domain.

Our pathway enrichment analysis revealed significant modulation of key insulin signaling cascades, particularly the PI3K/AKT and MAPK pathways. A network analysis identified 47 differentially expressed genes in insulin-responsive tissues, with notable upregulation of glucose transporter GLUT4 and insulin receptor substrate proteins. The analysis also revealed significant changes in genes that are involved in mitochondrial function and lipid metabolism, suggesting broader metabolic effects beyond glucose homeostasis.

Protein–protein interaction networks, constructed using the STRING database, highlighted the central role of AKT2 and AMPK as downstream effectors of Retatrutide's triple-receptor activation. Our gene ontology analysis demonstrated enrichment in biological processes related to glucose homeostasis, insulin sensitivity, and energy metabolism, with particular emphasis on pathways that are involved in β-cell preservation and adipose tissue remodeling.

Molecular dynamics simulations over 100ns revealed stable binding conformations of Retatrutide with all three target receptors, suggesting sustained activation of complementary metabolic pathways. The simulations also identified the key residues that are involved in receptor activation and signal transduction. The systems biology analysis indicated synergistic effects of triple-receptor agonism, leading to enhanced insulin sensitivity through multiple mechanisms, including improved β-cell function, reduced glucagon secretion, and enhanced glucose uptake in peripheral tissues.

These findings provide novel insights into Retatrutide's molecular mechanism of action and support its therapeutic potential in T2DM treatment through comprehensive modulation of insulin resistance pathways. Further experimental validation is warranted to confirm these in silico predictions.

Objectives

Experimental evidence has shown that environmental exposure to the fibrous amphibole fluoro-edenite (FE) leads to the development of chronic respiratory diseases and causes carcinogenic effects (1). This silicate has a number of characteristics similar to the asbestos group (2), and scientific evidence has led to the classification of FE fibers as carcinogenic to humans, i.e., Group 1 (3). Furthermore, exposure to FE fibers is causally related to the onset of malignant mesothelioma, but this is not established for lung cancer. Most aspects, in fact, remain unknown (4).

Lung cancer is currently the second cause of cancer worldwide, with over 1.7 million deaths per year (5). Many studies have now demonstrated the role of epigenetics in the development and progression of various pathologies, including cancer (6).

Materials and Methods

On this basis, the aim of this study was to evaluate the expression levels of non-coding RNAs (ncRNAs), in particular microRNAs and transferRNAs, in order to identify a panel potentially involved in the development and progression of lung cancer and to evaluate the pro-tumor epigenetic modulation induced by exposure to FE fibers. In this regard, in vitro functional experiments were performed on the lung cell line (HBEC3-KT) and on the lung cancer cell line (A549) after exposure to FE fibers. The same unexposed cell lines were used as controls.

Results

An analysis of the results allowed us to identify that ncRNAs strictly involved in lung cancer also differentiated exposure to FE fibers. Furthermore, once the differentially expressed ncRNAs were identified for each comparison, the impact of their dysregulation in metabolic and signaling pathways was also evaluated.

Conclusions

The data obtained in vitro could be validated on a subset of subjects (workers and non-workers) exposed to FE fibers to verify the clinical role of these ncRNAs and their potential use as biomarkers of exposure and/or pathology.

Fluoro-edenite (FE) is an asbestiform mineral fiber identified in lava rocks extracted from a quarry in Biancavilla, Italy. The material derived from these rocks has historically been utilized for construction purposes in the area, exposing the local population to potential health risks. Previous research has demonstrated that asbestos exposure can trigger autoimmune responses, including an increased frequency of anti-nuclear autoantibodies (ANAs). This study aimed to investigate the potential link between exposure to FE and autoimmune reactions in a population at risk.
A total of 120 participants, comprising 60 residents of Biancavilla and 60 individuals from a control group, were randomly selected for inclusion. All of the participants underwent complimentary medical evaluations, including spirometry and high-resolution computed tomography (HRCT) chest scans, to assess potential respiratory or pleural abnormalities. Their ANA levels were determined via indirect immunofluorescence, a reliable method for detecting autoimmune activity. No clinical signs or symptoms of illness were observed in any participant during the medical examination. ANA positivity was detected in 70% (n=42) of the exposed subjects compared to 25% (n=15) of the control group (p<0.05). Pleural plaques (PPs) were identified in 21 (30%) of the exposed individuals and in 2 (3%) of the controls, with all PP-positive subjects also testing positive for ANAs.
These findings suggest a significant association between FE exposure and elevated ANA levels, mirroring observations in populations exposed to asbestos fibers. Furthermore, the co-occurrence of PP and ANA positivity highlights the need for further exploration into the potential relationship between environmental exposure to asbestiform fibers and autoimmune dysregulation. This study provides a foundational step for future research into the health effects of FE exposure and its broader implications for public health.