Search Results (4,781)

The rapid expansion of peptide libraries and the increasing functional diversity of peptides have highlighted the significance of predicting the multifunctional properties of peptides in bioinformatics research. Although supervised learning methods have made advancements, they typically necessitate substantial amounts of labeled data for yielding accurate prediction. This study presents MvAl-MFP, a multi-label active learning approach that incorporates multiple feature views of peptides. This method takes advantage of the natural properties of multi-view representation for amino acid sequences, meets the requirement of the query-by-committee (QBC) active learning paradigm, and further significantly diminishes the requirement for labeled samples while training high-performing models. First, MvAl-MFP generates nine distinct feature views for a few labeled peptide amino acid sequences by considering various peptide characteristics, including amino acid composition, physicochemical properties, evolutionary information, etc. Then, on each independent view, a multi-label classifier is trained based on the labeled samples. Next, a QBC strategy based on the average entropy of predictions across all trained classifiers is adopted to select a specific number of most valuable unlabeled samples to submit them to human experts for labeling by wet-lab experiments. Finally, the aforementioned procedure is iteratively conducted with a constantly expanding labeled set and updating classifiers until it meets the default stopping criterion. The experiments are conducted on a dataset of multifunctional therapeutic peptides annotated with eight functional labels, including anti-bacterial properties, anti-inflammatory properties, anti-cancer properties, etc. The results clearly demonstrate the superiority of the proposed MvAl-MFP method, as it can rapidly improve prediction performance while only labeling a small number of samples. It provides an effective tool for more precise multifunctional peptide prediction while lowering the cost of wet-lab experiments. Full article

Organoids allow to model healthy and diseased human tissues. and have applications in developmental biology, drug discovery, and cell therapy. Traditionally cultured in immersion/suspension, organoids face issues like lack of standardization, fusion, hypoxia-induced necrosis, continuous agitation, and high media volume requirements. To address these issues, we developed an air–liquid interface (ALi) technology for culturing organoids, termed AirLiwell. It uses non-adhesive microwells for generating and maintaining individualized organoids on an air–liquid interface. This method ensures high standardization, prevents organoid fusion, eliminates the need for agitation, simplifies media changes, reduces media volume, and is compatible with Good Manufacturing Practices. We compared the ALi method to standard immersion culture for midbrain organoids, detailing the process from human pluripotent stem cell (hPSC) culture to organoid maturation and analysis. Air–liquid interface organoids (3D-ALi) showed optimized size and shape standardization. RNA sequencing and immunostaining confirmed neural/dopaminergic specification. Single-cell RNA sequencing revealed that immersion organoids (3D-i) contained 16% fibroblast-like, 23% myeloid-like, and 61% neural cells (49% neurons), whereas 3D-ALi organoids comprised 99% neural cells (86% neurons). Functionally, 3D-ALi organoids showed a striking electrophysiological synchronization, unlike the heterogeneous activity of 3D-i organoids. This standardized organoid platform improves reproducibility and scalability, demonstrated here with midbrain organoids. The use of midbrain organoids is particularly relevant for neuroscience and neurodegenerative diseases, such as Parkinson’s disease, due to their high incidence, opening new perspectives in disease modeling and cell therapy. In addition to hPSC-derived organoids, the method’s versatility extends to cancer organoids and 3D cultures from primary human cells. Full article

Background/Objectives: The detection of ovarian cancer remains challenging due to the lack of reliable serum biomarkers that reflect malignant transformation rather than mere tumor presence. We developed a novel biotest using an immortalized human fallopian tube epithelial cell line (TY), which exhibits anchorage-independent growth (AIG) in response to cancer-associated serum factors. Methods: Sera from ovarian and breast cancer patients, non-cancer controls, and ID8 ovarian cancer-bearing mice were tested for AIG-promoting activity in TY cells. Results: TY cells (passage 96) effectively distinguished cancer sera from controls (68.50 ± 2.12 vs. 17.50 ± 3.54 colonies, p < 0.01) and correlated with serum CA125 levels (r = 0.73, p = 0.03) in ovarian cancer patients. Receiver operating characteristic (ROC) analysis showed high diagnostic accuracy (AUC = 0.85, cutoff: 23.75 colonies). The AIG-promoting activity was mediated by HGF/c-MET and IGF/IGF-1R signaling, as inhibition of these pathways reduced phosphorylation and AIG. In an ID8 mouse ovarian cancer model, TY-AIG colonies strongly correlated with tumor burden (r = 0.95, p < 0.01). Conclusions: Our findings demonstrate that the TY cell-based AIG assay is a sensitive and specific biotest for detecting ovarian cancer and potentially other malignancies, leveraging the fundamental hallmark of malignant transformation. Full article

Background/Objectives: Non-coding microRNA-34a (miR-34a) regulates the expression of key factors involved in several cellular processes, such as differentiation, apoptosis, proliferation, cell cycle, and senescence. Deregulation of the expression of these factors is implicated in the onset and progression of several human diseases, including cancer, neurodegenerative disorders, and pathologies associated with viral infections and inflammation. Despite numerous studies, the molecular mechanisms regulated by miR-34a remain to be fully understood. The present study aimed to generate miR-34a knockout cell lines to identify novel genes potentially regulated by its expression. Methods: We employed the CRISPR-Cas9 gene editing system to knock out the hsa-miR-34a gene in HeLa and 293T cell lines, two widely used models for studying molecular and cellular mechanisms. We compared proliferation rates and gene expression profiles via RNA-seq and qPCR analyses between the wild-type and miR-34a KO cell lines. Results: Knockout of miR-34a resulted in a decreased proliferation rate in both cell lines. Noteworthy, the ablation of miR-34a resulted in increased expression of the long non-coding RNA MALAT1. Additionally, miR-34a-5p silencing in the A375 melanoma cell line led to MALAT1 overexpression. Conclusions: Our findings support the role of the miR-34a/MALAT1 axis in regulating proliferation processes. Full article

Background: Immune checkpoint inhibitor therapy in patients with lung cancer and metastatic melanoma is associated with exacerbation of autoimmune-related diseases. The efficacy of treatment targeting the programmed cell death receptor-1 (PD-1) checkpoint relies upon a feedback loop between interferon gamma (IFN-γ) and the interleukin-12 isoform, IL-12p40. Paradoxically, both cytokines and the anti-PD-1 antibody worsen psoriasis. We previously reported an immunomodulating peptide, designated IK14004, that inhibits progression of Lewis lung cancer in mice yet uncouples IFN-γ from IL-12p40 production in human immune cells. Methods: Immune cells obtained from healthy donors were exposed to IK14004 in vitro to further characterise the signalling pathways affected by this peptide. Using C57BL/6 immunocompetent mice, the effect of IK14004 was tested in models of lung melanoma and psoriatic skin. Results: Differential effects of IK14004 on the expression of IFN-α/β, the interleukin-15 (IL-15) receptor and signal transducers and activators of transcription were consistent with immune responses relevant to both cancer surveillance and immune tolerance. Moreover, both melanoma and psoriasis were inhibited by the peptide. Conclusions: Taken together, these findings suggest mechanisms underlying immune homeostasis that could be exploited in the setting of cancer and autoimmune pathologies. Peptide administered together with checkpoint blockers in relevant models of autoimmunity and cancer may offer an opportunity to gain further insight into how immune tolerance can be retained in patients receiving cancer immunotherapy. Full article

Understanding the utilization patterns of nuclear medicine (NM) services is essential for optimizing resource allocation and service provision. This study aimed to address the regional evidence gap by reporting the demand for NM services by sex and age at a public hospital in Jamaica. This was a non-experimental, retrospective study of NM scans that were completed at the University Hospital of the West Indies from 1 June 2022 to 31 May 2024. While all scans were reported in the descriptive totals, for patients with multiple scans during the study period, only the data from the first visit was used in the inferential statistical analysis. This was performed with the IBM SPSS (version 29.0) software and involved the use of chi-square goodness of fit and multinomial logistic regression. A total of 1135 NM scans for 1098 patients were completed (37 patients had more than one scan); 596 (54.3%) were female and 502 (45.7%) were male, with the ages ranging from 3 days to 94 years old. Among the female patients, there was a greater demand in the ≥60 years age group for cardiac amyloid scans (χ² = 6.40, p < 0.05), while females 18–59 years had a greater demand for thyroid scans (χ² = 7.714, p < 0.05) and bone scans (χ² = 3.904, p < 0.05). On the other hand, significantly more males in the ≥60 age group presented for cardiac amyloid (χ² = 4.167; p < 0.05) and bone scans (χ² = 145.79, p < 0.01). Males were significantly less likely to undergo a thyroid scan than females (p < 0.01, OR = 0.072, 95% CI: 0.021, 0.243) while individuals aged 18–59 years were more likely to undergo this scan than patients aged 60 or older (p = 0.02, OR = 3.565, 95% CI: 1.258, 10.104). Males were more likely to do a cardiac amyloid scan (p < 0.05, OR = 2.237, 95% CI: 1.023, 4.891) but less likely to undergo a cardiac rest/stress test than females (p = 0.02, OR = 0.307, 95% CI: 0.114, 0.828). Prolonged life expectancy and an aging population have the potential to impact NM utilization, thus requiring planning for infrastructure, equipment, work force, and supplies. Cancer-related and cardiovascular indications are a top priority at this facility; hence, age- and sex-specific analysis are useful in establishing models for policy makers with regard to the allocation of economic and human resources for the sustainability of this specialized service. Full article

Adverse drug events (ADEs) significantly impact patient safety and health outcomes. Manual ADE detection from clinical narratives is time-consuming, labor-intensive, and costly. Recent advancements in large language models (LLMs), including transformer-based architectures such as Bidirectional Encoder Representations from Transformers (BERT) and Generative Pretrained Transformer (GPT) series, offer promising methods for automating ADE extraction from clinical data. These models have been applied to various aspects of pharmacovigilance and clinical decision support, demonstrating potential in extracting ADE-related information from real-world clinical data. Additionally, chatbot-assisted systems have been explored as tools in clinical management, aiding in medication adherence, patient engagement, and symptom monitoring. This narrative review synthesizes the current state of LLMs in ADE detection from a clinical perspective, organizing studies into categories such as human-facing decision support tools, immune-related ADE detection, cancer-related and non-cancer-related ADE surveillance, and personalized decision support systems. In total, 39 articles were included in this review. Across domains, LLM-driven methods have demonstrated promising performances, often outperforming traditional approaches. However, critical limitations persist, such as domain-specific variability in model performance, interpretability challenges, data quality and privacy concerns, and infrastructure requirements. By addressing these challenges, LLM-based ADE detection could enhance pharmacovigilance practices, improve patient safety outcomes, and optimize clinical workflows. Full article

Fungicides are compounds with potentially toxic effects on the human body, but the molecular mechanisms of their action have not yet been explained. The effect of cyprodinil on cell viability, apoptosis level, cell membrane function, cell morphology and expression of antioxidant enzyme genes in the A-375 and DLD-1 cell lines was examined. The cell lines were selected because they can be an excellent in vitro model of neoplastic changes occurring in the skin and large intestine after exposure to a fungicide. The fungicide selected for the study is commonly used in Poland to protect crops against fungi. Our results showed that the tested compound increased cell viability and proliferation, probably activated by mechanisms related to oxidative stress. Cyprodinil caused an increase in glutathione level (in A-375 by about 37% and in DLD-1 by about 28%) and oxidative stress enzymes activity, but not in apoptosis level. Its membrane interactions and its penetration into cells was concentration dependent. It is worth emphasizing that the novelty of our work lies in the use of non-traditional toxicological methods based on molecular analyses using human cell lines. This allowed us to demonstrate not only the toxicity of a single substance but also its behavior within cellular structures. Our findings suggest that cyprodinil may have tumor-promoting properties in skin and colorectal cancer cells. Full article

Bladder cancer pathogenesis is closely linked to epigenetic alterations, particularly DNA methylation and demethylation processes. Environmental carcinogens and persistent inflammatory stimuli—such as recurrent urinary tract infections—can induce aberrant DNA methylation, altering gene expression profiles and contributing to malignant transformation. This review synthesizes current evidence on the role of DNA methyltransferases (DNMT1, DNMT3a, DNMT3b) and the hypermethylation of key tumour suppressor genes, including A2BP1, NPTX2, SOX11, PENK, NKX6-2, DBC1, MYO3A, and CA10, in bladder cancer. It also evaluates the therapeutic application of DNA-demethylating agents such as 5-azacytidine and highlights the impact of chronic inflammation on epigenetic regulation. Promoter hypermethylation of tumour suppressor genes leads to transcriptional silencing and unchecked cell proliferation. Urine-based DNA methylation assays provide a sensitive and specific method for non-invasive early detection, with single-target approaches offering high diagnostic precision. Animal models are increasingly employed to validate these findings, allowing the study of methylation dynamics and gene–environment interactions in vivo. DNA methylation represents a key epigenetic mechanism in bladder cancer, with significant diagnostic, prognostic, and therapeutic implications. Integration of human and experimental data supports the use of methylation-based biomarkers for early detection and targeted treatment, paving the way for personalized approaches in bladder cancer management. Full article

Drosophila melanogaster is one of the most known and used organisms worldwide, not just to study general biology problems but above all for modeling complex human diseases. During the decades, it has become a central tool to understand the genetics of human disease, how mutations alter the behavior and health of cells, tissues, and organs, and more recently to test new compounds with a potential therapeutic use. But how did this small insect become so crucial in genetics? And how is it currently used in the study of human conditions affecting millions of people? In this review, we retrace the historical origins of its adoption in genetics laboratories and list all the advantages it provides to scientific research, both for its daily usage and for the fine tuning of gene regulation through genetic engineering approaches. We also provide some examples of how it is used to study human diseases such as cancer, neurological and infectious diseases, and its importance in drug discovery and testing. Full article

Cell culture models are of central importance for the investigation of cellular metabolism, proliferation and stress responses. In this study, the effects of different concentrations of glucose (1 g/L vs. 4.5 g/L) and fetal bovine serum (FBS; 5%, 10%, 15%) on viability, mitochondrial function and autophagy are investigated in four human cell lines: MRC-5, HeLa, Caco-2 and SW-620. Cells were cultured in defined media for 72 h, and viability was assessed by LDH release, mitochondrial membrane potential using Rhodamine 123, ATP content by luminescence and autophagy activity by dual fluorescence staining. The results showed that HeLa and SW-620 cancer cells exhibited increased proliferation and mitochondrial activity under high glucose conditions, while low glucose media resulted in decreased ATP content and increased membrane permeability in HeLa cells. MRC-5 fibroblasts and Caco-2 cells showed greater resilience to nutrient stress, with minimal changes in LDH release and consistent proliferation. Autophagy was activated under all conditions, with a significant increase only in selected cell-medium combinations. These results highlight the importance of medium composition in influencing cellular bioenergetics and stress responses, which has implications for cancer research, metabolic disease modelling and the development of serum-free culture systems for regenerative medicine. Full article

Background: Lung cancer ranks as the leading cause of cancer-related mortality worldwide. The complexity of tumor delineation, crucial for radiation therapy, requires expertise often unavailable in resource-limited settings. Artificial Intelligence (AI), particularly with advancements in deep learning (DL) and natural language processing (NLP), offers potential solutions yet is challenged by high false positive rates. Purpose: The Oncology Contouring Copilot (OCC) system is developed to leverage oncologist expertise for precise tumor contouring using textual descriptions, aiming to increase the efficiency of oncological workflows by combining the strengths of AI with human oversight. Methods: Our OCC system initially identifies nodule candidates from CT scans. Employing Language Vision Models (LVMs) like GPT-4V, OCC then effectively reduces false positives with clinical descriptive texts, merging textual and visual data to automate tumor delineation, designed to elevate the quality of oncology care by incorporating knowledge from experienced domain experts. Results: The deployment of the OCC system resulted in a 35.0% reduction in the false discovery rate, a 72.4% decrease in false positives per scan, and an F1-score of 0.652 across our dataset for unbiased evaluation. Conclusions: OCC represents a significant advance in oncology care, particularly through the use of the latest LVMs, improving contouring results by (1) streamlining oncology treatment workflows by optimizing tumor delineation and reducing manual processes; (2) offering a scalable and intuitive framework to reduce false positives in radiotherapy planning using LVMs; (3) introducing novel medical language vision prompt techniques to minimize LVM hallucinations with ablation study; and (4) conducting a comparative analysis of LVMs, highlighting their potential in addressing medical language vision challenges. Full article

Cells are assaulted daily by stresses that jeopardize genome integrity. Primary human cells adapt their response to the intensity of replication stress (RS) in a diphasic manner: below a stress threshold, the canonical DNA damage response (cDDR) is not activated, but a noncanonical cellular response, low-level stress-DDR (LoL-DDR), has recently been described. LoL-DDR prevents the accumulation of premutagenic oxidized bases (8-oxoguanine) through the production of ROS in an adaptive way. The production of RS-induced ROS (RIR) is tightly controlled: RIR are excluded from the nucleus and are produced by the NADPH oxidases DUOX1/DUOX2, which are controlled by NF-κB and PARP1; then, RIR activate the FOXO1-detoxifying pathway. Increasing the intensity of RS suppresses RIR via p53 and ATM. Notably, LoL-DDR is dysregulated in cancer cell lines, in which RIR are not produced by NADPH oxidases, are not detoxified under high-level stress, and favor the accumulation of 8-oxoguanine. LoL-DDR dysregulation occurred at an early stage of cancer progression in an in vitro model. Since, conversely, ROS trigger RS, this establishes a vicious cycle that continuously jeopardizes genome integrity, fueling tumorigenesis. These data reveal a novel type of ROS-controlled DNA damage response and demonstrate the fine-tuning of the cellular response to stress. The effects on genomic stability and carcinogenesis are discussed here. Full article

Background/Objectives: Gut microbiota research has gained momentum in recent years broadening knowledge of microbial components and their potential effects on health and well-being. Strong association between explicit microbes and metabolic diseases associated with obesity and type 2 diabetes mellitus, gastrointestinal disorders, neurodegenerative diseases, and even cancers have been established. Akkermansia muciniphila is a budding next-generation probiotic that plays an important role in systemic metabolism, intestinal health, and immune regulation, establishing strong implications for its use as a potent therapeutic intervention in diverse diseases. This project aimed at evaluating whether bacterial cell extracts of VH Akkermansia muciniphila (Vidya Strain; VS) can stimulate insulin secretion in INS-1 pancreatic beta cells and GLP-1 secretion in NCI-H716 human L-cells, both established in vitro models for studying metabolic regulation. Methods: Cultured VH Akkermansia muciniphila extracts were administered in a dose-dependent manner on INS-1 cells, and glucose-stimulated insulin secretion (GSIS) was measured via ELISA. Treated Human L-cell lines (NCI-H716) were analyzed for GLP-1 secretion. Results: Our study demonstrated that VH Akkermansia muciniphila extracts modestly increase insulin secretion from INS-1 beta cells and, more notably, induce a robust, dose-dependent rise in GLP-1 secretion from NCI-H716 L-cells, with the highest dose achieving over a 2000% increase comparable to glutamine. Conclusions: These findings suggest that VH A. muciniphila extracts may offer metabolic benefits by enhancing GLP-1 release, highlighting their potential for managing type 2 diabetes and obesity. Full article

Pancreatic cancer is frequently accompanied by cancer-associated cachexia, a debilitating metabolic syndrome marked by progressive skeletal muscle wasting and systemic metabolic dysfunction. This study presents a systems biology framework to simultaneously identify therapeutic targets for both pancreatic ductal adenocarcinoma (PDAC) and its associated cachexia (PDAC-CX), using cell-specific genome-scale metabolic models (GSMMs). The human metabolic network Recon3D was extended to include protein synthesis, degradation, and recycling pathways for key inflammatory and structural proteins. These enhancements enabled the reconstruction of cell-specific GSMMs for PDAC and PDAC-CX, and their respective healthy counterparts, based on transcriptomic datasets. Medium-independent metabolic biomarkers were identified through Parsimonious Metabolite Flow Variability Analysis and differential expression analysis across five nutritional conditions. A fuzzy multi-objective optimization framework was employed within the anticancer target discovery platform to evaluate cell viability and metabolic deviation as dual criteria for assessing therapeutic efficacy and potential side effects. While single-enzyme targets were found to be context-specific and medium-dependent, eight combinatorial targets demonstrated robust, medium-independent effects in both PDAC and PDAC-CX cells. These include the knockout of SLC29A2, SGMS1, CRLS1, and the RNF20–RNF40 complex, alongside upregulation of CERK and PIKFYVE. The proposed integrative strategy offers novel therapeutic avenues that address both tumor progression and cancer-associated cachexia, with improved specificity and reduced off-target effects, thereby contributing to translational oncology. Full article