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A green, catalyst-free synthesis of seventeen new 2,9-disubstituted purine-6-carboxamides (5 and 6) designed as EGFR inhibitors in high yields (85-93%) was accomplished. DFT analysis revealed the formation of an energetically favorable oxazolidine transition state with a lower activation barrier compared to alternative pathways, supporting the experimentally observed selectivity. In vitro anticancer activity against A549 lung cancer cells demonstrated dose-dependent growth inhibition, with IC₅₀ values ranging from 4.35 to 22.1 μM, and compound 6E emerged as the most potent derivative. It exhibited superior activity compared to the reference drug erlotinib, with a cellular IC₅₀ of 4.35 μM vs 11.83 μM and an EGFR enzymatic IC₅₀ of 105.96 nM vs 218.47 nM, indicating approximately 2-fold enhanced potency. Flow cytometric analysis demonstrated that compound 6E significantly reduced p-PI3K levels, comparably to erlotinib, indicating effective suppression of EGFR-AKT downstream signaling at the cellular level. Mechanistic investigations demonstrated that 6E increased ROS generation, induced mitochondrial depolarisation, and promoted apoptotic cell death. Further, molecular docking and MD simulations of the 6E-EGFR complex highlighted key amino acid interactions, corroborating the observed in vitro EGFR inhibition.

Cancer stem cells (CSCs) or tumor-initiating cells represent a drug-resistant subpopulation with self-renewal and metastatic capacity. There are no CSC-specific drugs that have been developed so far. Plectin is a cytoskeletal protein that uniquely translocates to the outer cell membrane (surface translocated plectin - STP) in CSCs and contributes to proliferation, migration, invasion, and metastasis. We previously identified an STP targeted peptoid-PCS2, and the dimeric version PCS2D1.2, which selectively binds to non-small cell lung cancer (NSCLC) derived CSCs, displayed both in vitro and in vivo anti-cancer activity. The current study reports the identification of the minimum pharmacophore and the optimization of PCS2D1.2 to obtain an improved version of trimeric peptoid PCS2T3.9. Various multimerization strategies with linker optimization and truncation of non-important residues resulted in PCS2T3.9, which demonstrated 21-fold improvement of the cytotoxic activity against high STP expressing H358 non-small cell lung cancer (NSCLC) cells, while showing minimum effects on low STP expressing H460 cells. PCS2T3.9 had no cytotoxic activity on normal bronchial epithelial HBEC-3KT cells. Furthermore, PCS2T3.9 effectively suppressed colony formation and cell migration-hallmarks of CSC phenotype-specifically in H358 cells but not in H460 cells. These findings strongly correlate high STP expression with cancer stemness characteristics and confirm the selective targeting of PCS2T3.9 on CSCs, producing anti-cancer activity. The highly specific and selective cytotoxic effects of PCS2T3.9 on STP-enriched CSCs offer a significant therapeutic advantage by potentially minimizing off-target effects on normal tissues, establishing this peptoid as a promising candidate for CSC-specific NSCLC therapy development.

Accurate analysis of tumor morphology, vascularity, and tissue stiffness under multimodal ultrasound imaging plays a critical role in the diagnosis of breast cancer. However, manual interpretation across multiple modalities is time-consuming and heavily dependent on the radiologist's expertise. Computer-aided classification offers an efficient alternative, yet remains challenging due to significant modality heterogeneity, inconsistent image quality, and redundant information across modalities. To address these issues, we propose a novel Multimodal Sparse Fusion Transformer Network (MSFT-Net). First, a Spatio-Temporal Decoupling Attention architecture (STDA) is introduced to disentangle and extract dynamic and static features from different modalities along spatial and temporal dimensions, capturing modality-specific motion and morphological characteristics independently. Second, the Mixed-Scale Convolution Module (MSCM) obtains tumor features at multiple scales, enhancing geometric detail representation and improving receptive field coverage. Third, the Sparse Cross-Attention Module (SCAM) adaptively retains the most effective query-key interactions between modalities, thereby facilitating the aggregation of high-quality features for robust multimodal information fusion. MSFT-Net is trained and tested on a curated dataset comprising multimodal breast tumor videos collected from 458 patients, including ultrasound (US), superb microvascular imaging (SMI), and strain elastography (SE), and its generalizability is further validated on the public BraTS'21 MRI dataset. Extensive experiments demonstrate that MSFT-Net achieves superior performance in multimodal breast tumor classification compared to state-of-the-art methods, providing fast and reliable support for radiologists in diagnostic tasks.

PARP inhibitors exert effects synergistically with DNA damage agents; therefore, the present work focused on designing and synthesizing novel olaparib-β-carboline hybrids for the treatment of BRCA-deficient TNBC. Among synthesized compounds, compound 6 substituted with methyl at position 1 of β-carboline had the most potent anti-proliferative activity against BRCA-deficient TNBC cells MDA-MB-436, with an IC50 value of 4.38 ± 0.05 μM. Moreover, compound 6 potently inhibited PARP-1 and PARP-2, with IC50 values of 1.6 ± 0.7 and 0.9 ± 0.2 nM, respectively. Mechanistically, compound 6 could increase DNA damage, induce cell cycle arrest in the G2/M phase, and promote MDA-MB-436 apoptosis. Overall, 6 is a potential hybrid molecule and can be a candidate compound for the treatment of BRCA-deficient TNBC.

Derivatives 2-11 were evaluated for cytotoxicity against the human lung (A549), breast (MCF-7), colorectal (HCT-116) and hepatocellular (HepG2) cancer cell lines. The compounds were also evaluated through enzymatic assays as dual mutated epidermal growth factor receptor (EGFRT790M) and vascular endothelial growth factor receptor 2 (VEGFR-2) inhibitors. Cytotoxic effects on A549 cell lines, compared to sorafenib (4.04 μM) and erlotinib (5.49 μM), showed that compounds 4, 5, 6, 7, 8, 10 and 11 with the IC50 values of 5.50-8.00 μM exhibited very high activities. Cytotoxicity on MCF-7 cell lines, compared to sorafenib (5.58 μM) and erlotinib (8.20 μM), showed that compounds 5, 6 and 7 established very high activities with the IC50 values of 7.55, 6.95 and 5.60 μM, respectively. Cytotoxicity on HCT-116, compared to sorafenib (5.05 μM) and erlotinib (13.91 μM), showed that compound 7 with the IC50 value of 9.50 μM, showed very good cytotoxicity. Compounds 5, 6, 7, 8 and 10 exhibited very high cytotoxic activities against HepG2 cell line with the IC50 values in the range 8.00-9.65 μM, compared to sorafenib (4.00 μM) and erlotinib (7.73 μM). Moreover, the estimated structures 3, 4, 5, 6, 7, 8 and 10 indicated low toxicity on VERO cells with the IC50 values of 48.80-52.50 μM. Furthermore, compounds 7, 6, 5 and 10 showed very good VEGFR-2 inhibitions at IC50 = 0.96, 1.10, 1.35 and 1.90 μM, respectively. As well, Structures 10, 7 and 6 highly inhibit EGFRT790M at IC50 = 0.30, 0.35 and 0.40 μM respectively. Molecular docking was carried out for all derivatives to show their binding affinities and orientations inside the active sites of VEGFR-2 and EGFRT790M receptors to support the in vitro results. The data obtained from docking is highly matched with that obtained from biological testing.

Targeted tropomyosin receptor kinase (TRK) inhibitors represent a therapeutic approach for cancers with NTRK gene fusions. However, the therapeutic efficacy of first-generation inhibitors is limited by the emergence of acquired drug resistance. Through the application of scaffold-hopping and conformational-flexibility design strategies, we identified a series of novel non-macrocyclic inhibitors, which showed enhanced activity against the TRKAG595R and TRKAG667C. The best TRK inhibitor 5c had IC50 values of 0.75 and 0.96 nM against TRKAG595R and TRKAG667C, showing better potency than drugs larotrectinib (approximately 87- and 46-fold improvement) and selitrectinib (approximately 10- and 13-fold improvement). 5c also strongly suppressed the proliferation of Ba/F3 cells transfected with TRKAWT/595R 667C with IC50 values of 3 - 41 nM. More importantly, 5c demonstrated favorable in vivo pharmacokinetic properties and antitumor efficacy (tumor growth inhibition (TGI) of 91% at 30 mg/kg and 115% at 60 mg/kg with 4 of 6 partial regression) in a BaF3-TMP3-TRKAG667C xenograft mouse model, which is greatly superior to that of selitrectinib (TGI of 2% at 30 mg/kg). Compound 5c exhibits significant potential to overcome clinical acquired multiple resistance to TRK inhibitors.

Urinary incontinence (UI) in women with a history of hysterectomy represents a significant global health concern. It is crucial to clarify the association between hysterectomy for benign indications and UI to avoid unnecessary surgery. This study aimed to develop a machine learning (ML) model to identify factors associated with UI in women with a history of hysterectomy. We analyzed 2021 patients from the National Health and Nutrition Examination Survey (NHANES) database who underwent hysterectomy for benign indications as our derivation cohort. Thirteen demographic and clinical features were evaluated: age, educational, anthropometric measurements (height, weight, waist), medical history diabetes mellitus (DM), and reproductive history. Six ML algorithms were employed: logistic regression (LR), naïve Bayes (NB), multilayer perceptron (MLP), extreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM). External validation was performed on a cohort consisting of 556 patients from the Second Qilu Hospital of Shandong University. To improve interpretability, the predictive process was graphically illustrated employing a nomogram and SHapley Additive exPlanations (SHAP). Finally, the model was deployed as an online clinical decision support platform for applications. A comparison of receiver operating characteristic (ROC) curves using LR as the reference model revealed no statistically significant differences across the six ML algorithms. In the internal validation cohorts, the models achieved area-under-the-curve (AUC) values of 0.753-0.763 and accuracies between 0.627 and 0.664. This predictive performance was sustained in the external-validation cohort, with AUC values ranging from 0.702 to 0.718 and accuracies ranging from 0.661 to 0.697. Our findings demonstrated that ML models could effectively identify UI in women with a history of hysterectomy. This approach, facilitated by the nomogram and online tool, enhanced the feasibility and accessibility of identifying women at risk.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype associated with a poor prognosis and limited treatment options. Current clinical management relies primarily on surgical resection and adjuvant chemotherapy, underscoring the urgent need for novel therapeutic strategies. Through systematic pharmacological screening, we reveal that fenticonazole, a widely used imidazole antifungal, functions as a potent suppressor of TNBC cell growth. Mechanistic studies revealed that fenticonazole directly binds to NF-κB p105, impairing its processing into p50. Consequently, the formation of the p50-p65 heterodimer is suppressed, accompanied by enhanced p65 activation and inhibition of NRF2 transcription. These molecular alterations drive the accumulation of mitochondrial reactive oxygen species (ROS), resulting in endoplasmic reticulum (ER) stress and ultimately apoptosis in TNBC cells. Our results not only elucidate a previously unrecognized antitumor mechanism of fenticonazole but also provide a compelling rationale for its drug repurposing as a promising therapeutic option for TNBC.

Follistatin-like protein-1 (FSTL-1) is emerging as a myokine linking skeletal and muscle biology. We investigated the relationship between circulating FSTL-1 levels and muscle mass and quality, using an artificial intelligence (AI)-enhanced ultrasonographic evaluation of the rectus femoris in patients with cancer-related disease-related malnutrition. A total of 91 patients diagnosed with cancer and disease-related malnutrition were included in the study. Muscle mass assessment was performed through US evaluation of the rectus femoris, using an AI-based analytical ultrasound system. Complementary evaluations comprised BIA to determine skeletal muscle mass, appendicular skeletal muscle mass, and the appendicular skeletal muscle mass index, with determination of circulating FSTL-1 concentrations. Thirty-seven women and 54 men, with a mean age of 69.5 ± 10.6 years were enrolled. Sarcopenia was identified in 41 individuals (45.9%). Patients with sarcopenia showed significantly reduced values: body weight (-4.1 ± 1.0 kg; P = 0.02), calf circumference (-2.5 ± 0.3 cm; P = 0.03), phase angle (-0.7 ± 0.2°; P = 0.01), and reactance (-6.3 ± 1.3 Ω; P = 0.03), skeletal muscle mass (-2.3 ± 0.3 kg; P = 0.03), appendicular skeletal muscle mass (-3.7 ± 0.1 kg; P = 0.02), and appendicular skeletal muscle mass index (-1.3 ± 0.3 kg/m²; P = 0.02), cross-sectional area (-0.4 ± 0.2 cm²; P = 0.04), and y-axis (-0.27 ± 0.1 cm; P = 0.03), and pennation angle (-1.1 ± 0.2°; P = 0.02). Circulating levels of FSTL-1 were markedly reduced in patients with sarcopenia. In the multivariate logistic regression model, lower FSTL-1 concentrations remained significantly associated with an increased likelihood of sarcopenia (OR = 1.63, 95% CI: 1.10-4.21; P = 0.03. FSTL-1 demonstrated a moderate discriminative capacity for identifying sarcopenia, with an area under the receiver operating characteristic curve of 0.69 (95% CI: 0.51-0.73; P = 0.03). Reduced circulating FSTL-1 levels were independently associated with sarcopenia in patients with cancer-related malnutrition. These results indicate that FSTL-1 may act as a biomarker of impaired muscle quality and mass, as reflected by AI-assisted ultrasound and bioimpedance parameters.

Small-bowel capsule endoscopy (SBCE) has transformed small-intestine diagnostics by enabling direct, noninvasive mucosal visualization. As healthcare systems increasingly prioritize value-based and sustainable care, this review explores recent advances in SBCE, focusing on home-delivery models, telemedicine, artificial intelligence (AI), and environmental impact. Life-cycle analyses estimate ~20 kgCO 2 per SBCE, ~18 kgCO 2 arising from patient travel. Transitioning from hospital attendance to home-delivery models can materially reduce this footprint. Feasibility studies report high acceptability for remote delivery, teleconsultation, and decentralized reading. AI-assisted reading platforms have recently shown significant reductions in reporting time, improving workflow efficiency. Rural modelling suggests travel emissions for colon capsule endoscopy (CCE) can exceed colonoscopy (~19.2 kgCO 2 e) but fall to ~5.3 kgCO 2 e with optimized courier logistics, despite >50% follow-up endoscopy rate. SBCE now stands at the nexus of technological innovation, clinical utility, and environmental accountability. Its journey from hospital corridors to home settings exemplifies a diagnostic paradigm built on accessibility, efficiency, and ecological integrity. Realizing this vision requires multicentre trials that incorporate life cycle, cost-effectiveness, and patient-reported outcomes. The capsule of the future will not merely image the intestine - it will symbolize medicine's evolution toward intelligent, zero-waste diagnostics.