Small bowel obstruction (SBO) affects ~ 30% of ovarian cancer (OC) patients, leading to readmission, debilitating symptoms, and death within one year. Cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) effectively controls peritoneal disease. We investigated primary CRS/HIPEC's impact on SBO and obstruction-free survival (OFS) in OC patients.

Women with obesity-driven type 2 diabetes (T2D) face worse breast cancer outcomes, yet metabolic status does not fully inform current standards of care. We previously identified plasma exosomes as key drivers of tumor progression; however, their effect on immune cells within the tumor microenvironment (TME) remains unclear. Using a novel patient-derived organoid (PDO) system that preserves native tumor-infiltrating lymphocytes (TILs), we show that T2D plasma exosomes induce a 13.6-fold expansion of immunosuppressive TILs relative to nondiabetic controls. This immune dysfunction may promote micrometastatic survival and resistance to checkpoint blockade, a known issue in T2D cancer patients. Tumor-intrinsic analysis revealed a 1.5-fold increase in intratumoral heterogeneity and 2.3-fold upregulation of aggressive signaling networks. These findings reveal how T2D-associated metabolic dysregulation alters tumor-immune crosstalk through previously underappreciated exosomal signaling, impairing antitumor immunity and accelerating progression. Understanding these dynamics could inform tailored therapies for this high-risk, underserved patient population.

This study aimed to develop and validate a practical nomogram for differentiating between benign and malignant pancreatic masses. A total of 494 patients with pancreatic mass lesions, confirmed by histopathology, were enrolled from Wuhan Union Medical College Hospital between January 2020 and May 2022. The participants were randomly divided into development and validation groups in a 7:3 ratio. Using multivariate logistic regression, the nomogram was constructed based on five independent predictors: blood type, CA19-9, IgG4, anorexia, and weight loss. The model's performance was assessed using receiver operating characteristic (ROC) curve analysis and calibration curves. In the development and validation sets, the areas under the ROC curve were 0.932 and 0.957, respectively. The nomogram demonstrated a high net benefit in the clinical decision curve analysis. Based on the model, pancreatic malignancy risk was classified as low (< 4%), moderate (4%-71%), and high (> 71%). This nomogram provides an easy-to-use, efficient tool for the early differentiation of pancreatic malignancies and could be implemented in primary, secondary, and emergency care settings to facilitate the timely referral of patients to higher-level hospitals.

This study aimed to elucidate the molecular mechanism through which ARD1 regulates breast cancer (BC) progression via the LRRC75A-AS1/miR-489-3p axis. The expression levels of ARD1, miR-489-3p, and LRRC75A-AS1 in BC cells were quantified using reverse transcription-polymerase chain reaction (RT-PCR). The interaction between miR-489-3p and ARD1 was validated through dual-luciferase reporter assays and RNA-binding protein immunoprecipitation (RIP). The sponge effect of LRRC75A-AS1 on miR-489-3p was confirmed by RNA pull-down assays. Functional roles of LRRC75A-AS1, miR-489-3p, and ARD1 in cell proliferation, invasion, and epithelial-to-mesenchymal transition (EMT) were evaluated using colony formation, Transwell, and western blot assays. Moreover, in vivo tumor xenograft experiments were conducted in BALB/c nude mice to assess the effect of LRRC75A-AS1 knockdown and its interaction with miR-489-3p and ARD1 on tumor growth. ARD1 promoted BC cell proliferation, invasion, and EMT. miR-489-3p was identified as a negative regulator of ARD1, while LRRC75A-AS1 acted as a competing endogenous RNA (ceRNA) that sponged miR-489-3p, thereby restoring ARD1 expression. Rescue experiments confirmed that LRRC75A-AS1 facilitated BC cell malignancy via the miR-489-3p/ARD1 axis. Importantly, in vivo studies demonstrated that silencing LRRC75A-AS1 significantly inhibited tumor growth in nude mice, accompanied by reduced ARD1 expression and increased miR-489-3p levels. The inhibitory effect on tumor growth was reversed by miR-489-3p inhibition and further restored by ARD1 knockdown, validating the functional relevance of this regulatory axis in vivo. Both in vitro and in vivo findings reveal that LRRC75A-AS1 promotes breast cancer progression by sponging miR-489-3p and upregulating ARD1. The LRRC75A-AS1/miR-489-3p/ARD1 ceRNA axis represents a novel regulatory pathway and a promising therapeutic target in BC.

COL4A1, a key component of the basement membrane, has been increasingly implicated in tumor progression, yet its role in colon cancer remains incompletely understood. In this study, we conducted a comprehensive integrative analysis using transcriptomic data from the TCGA-COAD cohort, combined with functional validation in colon cancer cell lines. Gene set enrichment analysis (GSEA) revealed that high COL4A1 expression was associated with oncogenic pathways including epithelial-mesenchymal transition (EMT), KRAS signaling, and inflammatory responses. Immune infiltration analysis indicated that COL4A1 expression negatively correlated with CD8+ T cell infiltration but positively correlated with macrophage subtypes. Immunophenoscore (IPS) analysis further revealed that tumors with high COL4A1 expression exhibited significantly higher IPS values, suggesting altered immunogenicity. Functional assays demonstrated that COL4A1 knockdown reduced cell proliferation, migration, and invasion in vitro. Co-expression analysis of EMT markers showed strong positive correlations between COL4A1 and mesenchymal genes such as VIM, ZEB1, SNAI1, and FN1, supporting its role in EMT-like phenotypes. Collectively, our findings suggest that COL4A1 may serve as a prognostic biomarker and contributor to tumor progression and immune remodeling in colon cancer.

Understanding the viscoelastic properties of cells is essential for studying their mechanical behavior and identifying disease-related biomechanical markers. This paper proposes an integrated framework that combines fractional modeling with automated algorithm design to fit force-relaxation data acquired through atomic force microscopy. We employ the fractional-order zener model to describe cell relaxation curves and formulate the parameter estimation as a black-box optimization problem. To solve it, we implement a Randomized Constructive Hyper-Heuristic with Local Search (RCHH-LS) that automatically generates tailored metaheuristics (MHs) by exploring combinations of search operators. Our results show that the best-performing MH, composed of two swarm-based dynamics and a local random-walk operator ([Formula: see text]), achieves a performance of [Formula: see text], representing a 75% improvement over the mean of all candidate configurations. Subsequent hyperparameter tuning with Optuna reduces this value to [Formula: see text], a further 4.7% gain relative to the untuned version while preserving high stability and repeatability. In an evaluation of 21 instances (force-relaxation curves), the tuned [Formula: see text] provided the best result in 19 cases, achieving an average of [Formula: see text], about 12% better than the best two-operator alternative and a coefficient of variation below 0.01%, underscoring its generalization capability. The FOZ model fitted using this solver generalizes well to independent datasets and captures critical viscoelastic parameters. We also confirm that [Formula: see text], τ, and α are sensitive to the applied force via a statistical analysis, while [Formula: see text] remains stable, reinforcing its association with intrinsic cell properties. These results highlight the effectiveness of combining fractional viscoelastic modeling with automated MH design for robust and interpretable mechanical characterization of cells. The proposed approach reduces manual intervention, ensures generalizability, and offers a scalable solution for computational biomechanics.

Three-dimensional (3D) culture models, particularly multi-spheroid models, are becoming increasingly essential in cancer drug discovery, particularly in stem cell and cancer stem cell (CSC) research. However, analytical methods for 3D multi-spheroid models, especially for single-cell and single-spheroid analysis in CSC research, remain limited. To address this gap we developed 3D multi-spheroid cholangiocarcinoma models that incorporate a CSC live-cell biosensor and a novel analysis method, 3D Surface Integrative Spheroid Profiling (3D-SiSP), utilizing high-content confocal imaging. 3D-SiSP quantifies spheroid area, allowing for both high- and low-throughput analyses. We demonstrate three key applications of 3D-SiSP. First, it outperformed traditional length-based methods for in vitro tumorigenesis measurements, offering greater precision. Second, 3D-SiSP enabled the calculation of individual spheroid areas along with real-time CSC biosensor signals, revealing larger spheroids had more undifferentiated cells. Lastly, 3D-SiSP facilitated simultaneous, real-time quantification of CSC content during anti-cancer drug testing in individual spheroids, providing evaluation of drug responses. Drug response differences across treatments were also quantified. Overall, 3D-SiSP provides a flexible and effective methodology for characterizing cancer cells and CSCs while evaluating anti-cancer drugs, applicable in both high- and low-throughput contexts. This approach enhances our understanding of CSC dynamics and supports the development of anti-CSC therapies.

Hyperspectral imaging has shown significant applicability in the medical field, particularly for its ability to represent spectral information that can differentiate specific biomolecular characteristics in tissue samples. However, the complexity of analyzing HSI data, due to its high dimensionality and the large volume of information, presents significant challenges. At the same time, deep learning, particularly convolutional neural networks and recurrent neural networks, has become an essential tool in medical diagnostics, providing detailed analysis across various contexts. These techniques enable the analysis of complex information often unattainable through traditional methods. This paper introduces a novel approach that integrates micro-FTIR spectroscopy with three different deep learning architectures, namely RNN, FCNN, and 1D-CNN, to compare their performance in region-based classification of thyroid tissues, including goiter, cancerous, and healthy types. The proposed deep learning methods were developed on a dataset of 60 patients and evaluated using grouped 10-fold cross-validation. The 1D-CNN achieved the highest scores in classifying the spectral data provided by micro-FTIR, enabling more precise and accurate region-based tissue classification. The 1D-CNN achieved an accuracy of 97.60%, while RNN and FCNN achieved 96.88% and 93.66%, respectively. These results highlight the effectiveness of this approach in enhancing the precision of thyroid pathology analysis.

This study aims to investigate and compare the diagnostic performance, disease interpretation reliability, and treatment recommendation capabilities of multiple advanced large language models (GPT-4o, DeepSeek-R1, and DeepSeek-V3) in breast tumor cases. It retrospectively collected comprehensive clinical records of patients with breast tumors treated at Taizhou Cancer Hospital between January and April 2024. The study evaluated the accuracy of tumor classification (benign vs. malignant), the quality of disease interpretation, and the appropriateness of treatment recommendations generated by each model. To assess the clinical interpretability and utility of the models, a comprehensive performance analysis was conducted using statistical methods. A total of 45 patients with breast tumors were included, comprising 37 benign and 8 malignant cases (43 females, 2 males). GPT-4o achieved the highest area under the curve (AUC) for tumor classification (AUC = 0.848), outperforming DeepSeek-R1 (AUC = 0.736) and DeepSeek-V3 (AUC = 0.723). However, DeLong's test indicated that the differences in AUCs among the models were not statistically significant (p > 0.05). In addition, subjective evaluations by doctors indicated that DeepSeek-R1 received the highest scores for disease interpretation (4.73 ± 0.46) and treatment recommendations (4.70 ± 0.51), with consistent ratings.

In this paper, we developed a cancer dynamical system that incorporates the interaction of tumor cells, immune systems, and drug reaction systems to investigate the impact and therapeutic implications of a fractional order Caputo derivative's with memory effects. The solutions of the proposed system are shown to be bounded and positive. The existence and uniqueness of the solutions of the suggested model are examined using a few fixed-point theorems. The global stability of the system is examined through the use of Lyapunov's first derivative functions. For various fractional values, solutions to the fractional order system are obtained with the help of a fractional operator with a power law kernel. The kernel also checks for unique solutions and verification of the scheme through mathematical analysis using novel approaches. Next, a simulation of the derived iterative technique is made for various fractional orders against the real data at different fractional order values. This fractional order model can be used to investigate the dynamics of tumor cells, the interactions between tumor cells and immune cells, and the effects of medications on the disease. The proposed system's controllability and observability are further addressed by using various therapies as inputs and normal cells as output. A linear control system with a closed-loop design, in which the drug is the input and treated cells are the output, is used to investigate the influence of cancer treatments on different patients.

Cholangiocarcinoma (CCA) is an aggressive bile duct malignancy with poor survival rates due to late detection, rapid metastasis, and treatment resistance. Therefore, new therapeutic strategies are needed to improve treatment outcomes. Previous studies have reported that mesenchymal stem cells (MSCs) secrete several soluble factors that modulate intracellular signaling pathways that are critical for the regulation of cancer cell function. The present study aimed to investigate the effects and molecular mechanisms of conditioned media from chorion-derived human MSCs (CH-CM) and placenta-derived human MSCs (PL-CM) on the migration and invasion of human CCA cells. We found that both CH-CM and PL-CM suppress cell migration and invasion in three CCA cell lines (KKU100, KKU213A and KKU213B) by increasing E-cadherin expression and decreasing the expression of several factors involved in the epithelial-mesenchymal transition process, including ZEB1, ZEB2, N-cadherin, vimentin, and MMP-2. The effects of CH-CM and PL-CM were mediated, at least in part, through the suppression of the PI3K/AKT signaling pathway in CCA cells. Our findings suggest that soluble factors derived from CH-MSCs and PL-MSCs could be used in combination with other conventional treatments to diminish the invasiveness of CCA cells, thus improving the therapeutic outcome and increasing survival in CCA patients.

Myelodysplastic syndromes (MDS) and acute myeloid leukaemia (AML) arise as a consequence of acquisition and progressive accumulation of genetic and epigenetic modifications by haematopoietic stem and progenitor cells (HSPC) which result in an impaired cell differentiation and the clonal expansion of myeloid progenitors leading to blast-cell accumulation in bone marrow (BM) and myelodysplasia. TLRs are expressed on HSPC and play a role in modulating haematopoiesis by instructing commitment to the myeloid lineage, and therefore may have potential therapeutic application. We have determined the in vitro effect of R848 (TLR7/TLR8 agonist) and Imiquimod (TLR7 agonist), on differentiation, apoptosis and cell viability in primary cultures of bone marrow samples from MDS (n = 6) and AML patients (n = 13). Differentiation was determined by a combined approach of conventional flow cytometry and t-SNE (t-distributed stochastic neighbour embedding) analysis based on the expression of cell markers (CD34, CD11b, CD13, CD117 and CD45). Cell viability and apoptosis were determined according to standard procedures. Statistical analyses were performed according to the two-tailed Student's t test for dual comparison (treated versus control samples). All major cell populations of the differentiation path from blasts towards neutrophils were found. Treatment with R848 or with Imiquimod did not induce significant changes in cell differentiation in AML samples. However, both R848 and, to a lesser extent, Imiquimod were able to induce differentiation of bone marrow cells from MDS patients from myelocytes to mature neutrophils in five out of six samples. Results also showed absence of toxic effects of both ligands on cells from MDS patients, as both apoptosis and cell viability were not altered by treatments. As for the differentiation assays, the effect of both ligands on apoptosis and cell viability in primary cultures from AML patients was not significant. Treatment with TLR7/8 ligands can revert the blockade of myeloid differentiation in most MDS samples and increase the amount of neutrophils, and therefore could represent a potential alternative treatment for MDS patients.

Objective To investigate the role and mechanism of miR-6767-5p in breast cancer (BC).

Mutations in the Kras oncogene are present in approximately 25% of tumors, while defective primary cilium can either promote or suppress specific cancer types. In the present study, we investigated whether mutations in Kras and genes important for primary cilium formation could collaboratively contribute to pancreatic cancer. Using mouse models, we found the presence of collaboration when these mutations were induced in the pancreas during embryogenesis, whereas no collaboration was observed when they were induced after birth. These results help to understand why mutations in ciliary genes do not appear in the mutational landscape of human pancreatic cancer.

Glioblastomas are the most prevalent and malignant primary cancers in the brain. Given the promising prospects of immunotherapeutic approaches, there is increasing interest in obtaining precise knowledge of the immunologic status of the tumour microenvironment for each individual. We explored the feasibility of inferring this tumour immune component in a minimally invasive manner prior to any clinical intervention, taking advantage of the preoperative immune cell counts that can be easily obtained from the clinical records of the patients. The neutrophil-to-lymphocyte ratio (NLR) is the most extensive measure calculated from complete counts of peripheral blood. Despite there was an increase in the NLR in high grade tumours of our cohorts of study, we did not find evidence of any correlation between the NLR and different degrees of tumour immune infiltration in glioblastoma. The same negative result was obtained with the monocyte-to-lymphocyte ratio (MLR). In addition, glioblastomas associated with extreme values of peripheral NLR did not exhibit substantial gene expression differences that could be linked to distinct tumourigenic properties. Overall, these results suggest that peripheral immune cell ratios cannot be used to reliably infer the immune microenvironment within the tumour, underscoring the complexity of using peripheral markers to assess local tumour immunity.

Lung recurrence following hepatectomy is a common and clinically significant complication in patients with hepatocellular carcinoma (HCC), often leading to poor prognosis. However, the underlying mechanisms and reliable predictive biomarkers remain poorly defined. We performed cDNA microarray analysis to identify genes associated with lung recurrence after hepatectomy in HCC patients and identified lysyl oxidase (LOX) as a candidate. We further evaluated the association between LOX expression, circulating tumor cell (CTC), and microvessel density (MVD). The predictive value of serum LOX levels was assessed in both training and validation cohorts. LOX expression was significantly elevated in HCC patients who developed lung recurrence post-hepatectomy and was associated with worse prognosis. High intratumoral LOX expression correlated with increased CTC counts and elevated MVD. In vitro, LOX overexpression enhanced HCC cell migration and invasion, while LOX knockdown suppressed these phenotypes. Serum LOX levels demonstrated predictive potential for postoperative lung recurrence in both cohorts. LOX overexpression is closely associated with lung recurrence after hepatectomy in HCC patients. LOX may serve as a potential biomarker, and its serum level could be used to predict postoperative lung recurrence.

Esophageal cancer (ESCA) is a significant malignancy with rising global incidence rates and considerable impacts on patient survival and quality of life. Current diagnostic and therapeutic strategies face limitations, necessitating research into its underlying mechanisms and potential biomarkers for early diagnosis. This study aims to investigate the role of perfluorooctane sulfonate (PFOS), an environmental toxicant, in the development of ESCA through a comprehensive bioinformatics approach. Using the TCGA-ESCA dataset, we identified differentially expressed genes (DEGs) and intersected them with PFOS-related toxicity targets predicted via Comparative Toxicogenomics Database (CTD) and SuperPred. Machine learning (Random Forest, XGBoost, LASSO, SVM) were applied to prioritize core targets. Survival analysis, in vitro qPCR (ESO-26/FLO-1 cells), and molecular docking were performed. Immune infiltration and pathway activity (GSVA) were assessed. We identified 98 PFOS-related DEGs in ESCA, enriched in hypoxia response, epithelial migration, and cancer-associated pathways (e.g., AGE-RAGE, PI3K-Akt). Machine learning highlighted three core targets: PLAU, TOP2A, and BAX. High expression of these genes correlated with poor survival (PLAU, p = 0.047) and was upregulated in ESCA tissues. PFOS exposure significantly elevated their expression in esophageal cancer cells. Molecular docking revealed strong binding affinities between PFOS and core targets. GSVA linked PLAU/TOP2A/BAX to oncogenic pathways (angiogenesis, DNA repair), while immune analysis showed PLAU's association with stromal infiltration and TOP2A's negative correlation with CD8 + T cells. PFOS exacerbates ESCA by dysregulating PLAU, TOP2A, and BAX, which drive tumor progression via immune modulation, genomic instability, and oncogenic signaling. These targets may serve as biomarkers and therapeutic vulnerabilities for PFOS-associated ESCA, underscoring the need for environmental regulation and targeted therapies.

To investigate the effects of Siglec-5 on hepatocellular carcinoma and the mechanism of action. The interactions and expression changes between Siglec-5 and Siglec-14 not only affect immune cell function, but may also influence tumor progression. A deeper understanding of the mechanisms regulating their balance could provide new insights and strategies for hepatocellular carcinoma treatment.

Breast cancer is the uncontrolled growth of breast cells in the lobules or the inner lining of milk ducts due to dysfunction of regulatory genes. The drugs currently used in breast cancer treatment have severe limitations. The study aimed to test 10 new synthetic forms of pyrazole clubbed pyrazoline thiazole derivatives for their ability to kill tumor cells, reduce inflammation, fight free radicals, and other important factors linked to breast cancer. The study involved computational models to assess ligand-binding affinities and pharmacokinetic properties. Later, we evaluated cytotoxicity using a human breast cancer cell line, MCF-7. In a preclinical model, the levels of vital cytokines like Transforming Growth Factor-β (TGF-β), Tumor Necrosis Factor alpha (TNF-α), and Interleukin- 6 were used to test the anticancer activity. The antioxidant activity is evaluated by malondialdehyde (MDA) levels. Changes in body weight, tumor weight and volume, inflammatory cytokine concentrations, and histology were among the measurements taken in rats. In result, we found compound 5E [5-(2-fluorophenoxy)-4-(3-(4-fluorophenyl)-1-(4-(4-fluorophenyl)thiazol-2-yl)-4,5-dihydro-1 H-pyrazol-5-yl)-3-methyl-1-phenyl-1 H-pyrazole] has best antitumor activity by decreasing the levels of TNF-α, IL-6, MDA, and TGF-β. It was observed that compound 5E contains potential in vitro and in vivo anticancer activity.

This study aimed to compare the safety and efficacy of robot-assisted partial nephrectomy with the two Chinese Robotic systems versus the da Vinci Xi Surgical System. This prospective analytical study included 170 patients who underwent robotic-assisted partial nephrectomy between February 2023 to June 2024. The study included 85 patients who received treatment using two Chinese robotic systems (KangDuo SR 2000: KD-SR-2, EDGE MP1000) and 85 who underwent the da Vinci (DV) surgical system during the same period. The demographic and clinical characteristics of the patients and the intraoperative and follow-up results were compared between the groups. In our study, statistically significance (p < 0.05) were observed between the Chinese robotic group and the da Vinci group in terms of operative time, intraoperative blood loss, and docking time. Among the 170 patients, there were no cases of positive surgical margins or major postoperative complications Clavien-Dindo ≥ 3. Multivariate logistic regression analysis confirmed that operative time, intraoperative blood loss, and docking time were statistically significant variables for evaluating the safety and effectiveness of both robotic systems. RAPN with Chinese robotic systems demonstrated comparable preoperative outcomes in selected parameters (operative time, blood loss, docking time) to the da Vinci system in this exploratory study.