Search Results (6,178)

Gadolinium is a rare-earth element that is promising for the field of biomedicine due to its unique properties that enhance image quality, giving it high potential in targeted cancer therapy, antimicrobial treatments, etc. The disadvantage of Gd-containing materials is their high toxicity. In this work, ensembles of Fe and Al₂O₃ nanoparticles were fabricated by the electric explosion of wire and Gd ribbons using rapid quenching techniques. Stable Fe, Fe/Gd and Fe/Gd/Al₂O₃ aqueous suspensions with a Z-potential of about –54 mV were fabricated by the ball-milling mechanosynthesis of Fe (100%), Fe and Gd (70 and 30 wt. % accordingly) and Fe, Al₂O_3, and Gd (69, 30 and 1 wt.% accordingly). Fillers from suspensions were used for the synthesis of epoxy composites mimicking natural tissue with embedded magnetic particles. The concentration range for synthesized epoxy composites (0, 5, 10, and 15 wt.% of the filler) corresponded to the biomedical range of interest. Thin-film magnetoimpedance (MI) elements were prepared by a sputtering technique: conventional [FeNi/Cu]₅/Cu/[Cu/FeNi]₅ (NP) element and [FeNi/Cu]₅/Cu/[Cu/P{FeNi]₅} element with patterned top multilayer (SqP). They showed a maximum MI ratio of about 160% for NP and about 60% for SqP. MI sensor response was affected by the presence of filled magnetic composites in the shape of cylinders (5 mm × 4 mm) situated at about 1 mm due to the stray fields in the filler. MI response showed a linear dependence on the filler concentration for each selected position. These results open the possibility to develop new iron- and gadolinium-containing materials for simultaneous magnetic imaging and detection by magnetic field sensors, extending the functional properties of Fe/Gd materials for biomedical devices and therapies. Full article

Background: Onconephrology is an emerging field addressing renal and cardiovascular complications in patients with cancer. Kidney disease and cardiovascular risk frequently coexist and may significantly affect oncological outcomes. Methods: We conducted a single-center, prospective, observational study including adult oncological patients. Patients were evaluated at baseline and after 1, 3, and 12 months. Renal outcomes (Acute Kidney Injury (AKI), Chronic Kidney Disease (CKD), AKI on CKD, Acute Kidney Disease (AKD)), cardiovascular risk assessment scores (using the SCORE/SCORE2 systems), and major adverse kidney events (MAKEs) were recorded. Results: Eighty-three patients were enrolled (mean age 69.8 ± 11.6 years, 60.2% male). At baseline, AKI was present in 30.4%, CKD in 27.8%, and AKI on CKD in 16.5% of patients. Overall, 96.7% of the cohort was classified as having a high or very high cardiovascular risk. During follow-up, 18.1% experienced new AKI, and MAKEs occurred in 30.4% of patients, driven primarily by mortality. Male sex emerged as the main predictor of death. Conclusions: Onconephrology patients suffer from a high burden of renal disease and cardiovascular risk. Integrated nephrological and cardiovascular assessment may represent a key component of personalized cancer care. Full article

Background: Actinic keratoses are common keratinocytic precursor lesions arising within chronically ultraviolet-damaged skin and are associated with an increased risk of progression to cutaneous squamous cell carcinoma. The concept of field cancerization has shifted therapeutic strategies from the treatment of isolated visible lesions toward broader field-directed approaches targeting both clinical and subclinical disease. Methods: This narrative review summarizes the rationale, mechanisms of action, efficacy profile, tolerability, and practical limitations of currently available field-directed therapies for actinic keratosis, including 5-fluorouracil, imiquimod, diclofenac, photodynamic therapy, and tirbanibulin. Based on their distinct biological targets, we propose a mechanism-based framework for sequential treatment strategies. Results: Available therapies act through partially non-overlapping mechanisms, including cytotoxic activity, immune activation, cyclooxygenase-2 inhibition, photodynamic oxidative damage, and tubulin/Src pathway inhibition. These complementary effects provide a biological rationale for sequential regimens aimed at addressing the heterogeneity of field cancerization. However, direct clinical evidence supporting specific treatment sequences remains limited, and proposed regimens should be interpreted as hypothesis-generating rather than as validated therapeutic protocols. Conclusions: Mechanism-based sequential field therapy may represent a rational strategy to optimize long-term control of actinic keratosis and field cancerization. Prospective comparative studies are needed to define optimal sequences, treatment intervals, patient selection criteria, and clinically meaningful endpoints, including sustained field clearance, recurrence reduction, tolerability, adherence, and prevention of progression to invasive cutaneous squamous cell carcinoma. Full article

Background/Objectives: Intraoperative fluorescence imaging (FI) with tumor-targeted tracers offers a promising approach to improve surgical precision in cancer surgery. cRGD-ZW800-1, an integrin-targeted fluorescent tracer, has previously demonstrated safety, tumor specificity, and utility in detecting inadequate margins in oral cancer. During this study, we observed variability in background fluorescence between different subsites of the oral cavity. Therefore, this study aimed to systematically evaluate intraoperative in vivo and ex vivo mucosal contrast ratios across various oral cavity subsites using FI with cRGD-ZW800-1. Methods: Thirty-one patients with oral squamous cell carcinoma underwent intraoperative FI following intravenous injection of cRGD-ZW800-1 at least 18 h preoperatively. In vivo imaging was performed using the Quest Spectrum platform. In addition, ex vivo FI of the resected specimen was performed using the Pearl Trilogy Small Animal Imaging System. As these ex vivo images were obtained under uniform and controlled acquisition conditions, they allow for direct comparison with the intraoperative fluorescence signals. Fluorescence intensities and tumor-to-background ratios (TBRs) were assessed per oral subsite using manually drawn regions of interest (ROIs) on the tumor and adjacent healthy mucosa using Quest’s Spectrum Software, version 4.8.2, (in vivo images) and the Pearl’s integrated software ImageStudio version 6.2 (ex vivo images). A TBR ≥ 1.5 was considered sufficient. Results: Under uniform imaging settings, all samples exhibited adequate contrast (TBR ≥ 2.3), allowing clear tumor visualization and precise evaluation of mucosal margins on final histopathology. Notably, intraoperative in vivo contrast in the posterior located maxillary alveolar process was comparatively lower, which was attributable to suboptimal imaging conditions and subsite-specific background fluorescence. Conclusions: Our findings indicate that, although contrast varies across different oral subsites, all specimens exhibited sufficient ex vivo mucosal contrast to allow reliable tumor delineation. As in vivo imaging may be affected by subsite-specific background fluorescence and inherent limitations of intraoperative imaging geometry, fluorescence signals should be interpreted in conjunction with standard visual and tactile assessment. Due to anatomical constraints, different oral subsites may appear within the same field of view, which can influence perceived signal intensity. Therefore, intraoperative ex vivo fluorescence evaluation is recommended for signal interpretation. Full article

In 2022, colorectal cancer (CRC) was the third most common type of cancer worldwide and the second most common in Europe. CRC ranked as the second leading cause of cancer-related deaths both worldwide and in Europe, with 904,019 and 247,966 deaths, respectively. The majority of CRC cases are sporadic (60–75%); however, 10–35% of CRC are estimated to result from the interaction of heritable and environmental factors. Among these, 5–6% are caused by inherited variants in genes that predispose to the development of CRC. Among the known inherited causes, Lynch Syndrome (LS), formerly known as Hereditary Nonpolyposis Colorectal Cancer (HNPCC), is the most frequent and accounts for approximately 3% of all CRC. Here we review and update on multiple aspects of LS in the context of CRC, including its genetic and molecular basis, current guidelines for molecular screening and variant classification. Furthermore, we review functional assays that have been used to determine the biological impact of genetic variants of uncertain significance (VUS) and discuss future perspectives in the field. Full article

Adverse childhood events (ACEs) represent a major public health burden in the United States, as exposure to ACEs increases the risk of mental health disorders, cardiovascular disease, obesity, and cancer and can greatly affect quality of life. Although the effects of ACEs on physiology are complex, significant evidence suggests that ACEs may affect the immune system later in life. As the field of immunotherapy gains prominence in cancer treatment, it becomes imperative to explore how ACEs may impact cancer immunotherapy. Brain cancer, especially glioblastoma multiforme (GBM), has a very poor prognosis and remains a challenging disease to treat. Immunotherapy approaches are being actively investigated. To address this, we aim to raise awareness of the potential connection between ACEs, brain cancer, and cancer immunotherapy. Through a review of the current biomedical literature, we synthesized current findings into a commentary on how early-life adversity may influence the immune response within the central nervous system. It is the intention of this commentary to generate hypothesis-driven research within the nascent and emerging field of neuro-psycho-immunology in neuro-oncology. Given that the relationship between ACEs and brain cancer immunotherapy remains vastly understudied, this commentary has significant potential to generate insightful discussions among clinicians and scientists to guide further clinical and basic research towards anticipating which patients stand to receive the most benefit from immunotherapy. Full article

This study proposes a novel anti-resonant fiber sensing structure based on a composite “egg-shaped” configuration with surface plasmon resonance (SPR) effect. By designing a novel anti-resonant structure consisting of a semicircle and a semi-ellipse and coating its inner surface with a gold film, the optimal structural parameters are determined through three sets of simulation experiments using temperature sensitivity as the criterion. The optimal sensing structure was applied to the simulated detection and analysis of cancer cells, aiming to provide value and reference for the application of high-sensitivity optical fiber sensor in the field of cancer cell detection. Simulation results show that the proposed sensing structure achieves a maximum temperature sensitivity (TS) of 3.86 nm/°C. For the detection of six different types of cancer cells, the maximum wavelength sensitivity (WS), optimal resolution (R), maximum figure of merit (FOM), maximum signal-to-noise ratio (SNR), and best limit of detection (LOD) reach 12,142.86 nm/RIU, 8.24 × 10⁻⁶, 3035.72 RIU⁻¹, 65.50, and 0.94 nm, respectively. Owing to its unique detection mechanism, the proposed sensing structure exhibits label-free characteristics and demonstrates balanced and excellent performance across all metrics for both temperature and cancer cell detection, showing broad application prospects and great potential in the fields of environmental monitoring and medical prevention and treatment. Full article

Background: Gynecological cancers include collections of cancers with diverse cellular and molecular characteristics that often develop drug resistance, making them treatment-resistant. Biomolecule–drug conjugates (BDCs), especially antibody–drug conjugates (ADCs), have revolutionized the targeted therapy of cancer; however, the creation of these entities has so far been achieved by empirical, resource-intensive design methods. Objective: The aim of this review is to critically analyze how AI can be used for the rational design and optimization of high-affinity BDCs for gynecological cancer treatment. Methods and discussion: Recent advances in machine learning (ML)- and deep learning (DL)-based methods to predict biomolecule-target binding affinity, structural compatibility, linker stability, payload selection, trafficking in the cell, and biomolecule resistance mechanisms are summarized. The review also explores the possibilities for incorporation of structural, chemical, biological, and multi-omics data to enhance specificity, efficacy, and safety of conjugates. Besides antibody-based systems, AI-assisted design approaches with peptides, aptamers, and hybrid biomolecular systems are also included. This review also highlights parameters and experimental/numerical validation restrictions related to data quality, interpretability of models, regulatory aspects, etc. Conclusions: AI-based conjugate engineering is increasingly moving BDC development from a largely ‘trial and error’ approach to a more predictive and data-driven approach. While there are still challenges to be addressed in terms of translations and validations, the potential of AI approaches in the field of precision oncology and the development of more personalized treatment is promising in the context of gynecological cancers. Full article

Approximately 30% of all human cancers are driven by mutations in RAS genes, KRAS, HRAS, and NRAS, resulting in the constitutive activation of RAS proteins and stimulation of MAPK/AKT signaling. Non-mutant, i.e., wild-type (WT) RAS can also become activated through mechanisms such as gene amplification or excessive stimulation by mutated or overexpressed receptor tyrosine kinases (e.g., EGFR), thereby promoting cancer progression. Mutant or activated RAS contributes to multiple hallmarks of cancer, including unchecked cellular proliferation, reprogrammed cellular metabolism, immunosuppression, and metastasis. Hence, RAS is of immense clinical importance, with hundreds of laboratories studying various aspects of RAS biology or developing RAS inhibitors. There is perhaps no greater unmet medical need in oncology than the need for a broadly efficacious but safe inhibitor of mutant and activated RAS. Mutant-specific KRAS G12C inhibitors have shown promising therapeutic efficacy, leading to FDA approval of sotorasib and adagrasib, although their use is limited to patients with the relatively rare G12C KRAS mutation. Mutant-specific KRAS inhibitors are also susceptible to adaptive resistance, in part, due to secondary RAS mutations, and compensatory signaling from WT RAS isozymes. A pan-RAS inhibitor capable of blocking all RAS isozymes, regardless of the underlying mutation, offers the potential for broader efficacy and capacity to avert resistance. While just a few years ago, pan-RAS inhibitors were predicted to be severely toxic or even fatal, the apparent safety profile of RMC-6236 (daraxonrasib), a pan-RAS inhibitor currently in clinical trials, suggests otherwise. Indeed, pan-RAS inhibitors are now considered by many in the RAS field to be the most promising class in development. In this review, we summarize the evolution and current status of pan-RAS and pan-KRAS inhibitors in preclinical and clinical development and highlight emerging human-relevant tumor models that are advancing preclinical evaluation. Full article

Cells operate as open thermodynamic systems where energy transformations and transport processes occur across membranes, exhibiting distinct thermo-electro-biochemical behaviours in healthy versus diseased states. Living organisms generate waste heat due to internal irreversibility, which dissipates into the environment and serves as an observable flow of information. By analysing this heat loss and its changes under external influences, new insights into cellular behaviour can be gained. This paper highlights recent advances in this thermodynamic approach, which frames living systems as black boxes, focusing on their input–output dynamics and introducing the emerging field of bioengineering thermodynamics. A key challenge in applying extremely low-frequency electromagnetic fields (ELF-EMF) to proliferative disorders has been the empirical selection of effective field parameters. To address this, we employed a bio-thermodynamic engineering model to calculate the ELF frequency that maximizes mean entropy changes based on cellular biophysical parameters. This entropy change corresponds to a metabolic shift that reduces cell proliferation. Experimental validation was performed on six human cancer cell lines, where proliferation rates served as indicators confirming the model’s predictions. For the first time, this approach enabled the calculation and experimental validation of ELF frequencies selectively effective on different cell types, demonstrating a promising method for targeted therapeutic applications. Full article

The gut microbiome has emerged as one of the most promising sources of non-invasive biomarkers for colorectal cancer (CRC). Over the past decade, fecal metagenomic studies have consistently identified a core CRC-associated signature enriched with oral-typical, biofilm-forming species, most notably Fusobacterium nucleatum, Parvimonas micra, Peptostreptococcus stomatis, and Bacteroides fragilis. The recent landmark pooled analysis by Piccinno et al., which combined 3741 metagenomes from 18 international cohorts, offers the most methodologically solid confirmation of this signature to date. It achieved a leave-one-dataset-out area under the curve (AUC) of around 0.85 and expanded resolution to previously unclassified species-level genome bins (SGBs) and strain-level phylogenies. In this narrative review, we critically evaluate the evidence supporting current universal CRC microbiome signatures, explore the mechanistic basis of the oral-to-gut microbial axis and the immunometabolic tumor microenvironment, and argue that increasing evidence indicates the field is nearing a point where investigating patient-level heterogeneity could be the most valuable next step. Because a strong average CRC signal has been convincingly established, an important next direction is to examine how much these signatures’ impact varies among individual patients, considering tumor molecular subtype, immune environment, metabolic profile, and host genetics. We review emerging evidence of such patient-level heterogeneity, outline analytical methods to assess it, and discuss its importance for developing microbiome-based screening, prognostics, and therapeutic strategies in CRC. Full article

Cancer research has undergone a fundamental transformation in recent decades due to the integration of artificial intelligence (AI) models into the study of tumor biology. However, tumor evolution, driven by genetic and phenotypic alterations leading to heterogeneity, resistance and metastasis, remains a major challenge in oncology. To understand these processes is crucial for developing effective therapeutic strategies and improving patient outcomes. Conventional methods often fail to capture the complexity and dynamics of these processes. In contrast, AI tools have the ability to integrate and analyze large-scale multi-omics, imaging and clinical data, offering the capability to decode tumor complexity. AI-driven methods facilitate multi-modal data integration, enabling the recognition of patterns that connect molecular alterations with phenotypic outcomes. In functional genomics, AI tools predict the effects of genetic variants, identify regulatory elements and map dysregulated pathways, thus clarifying mechanisms underlying tumor development and resistance. In the imaging field, deep learning techniques improve tumor segmentation, characterization and longitudinal monitoring, providing more accurate insights into tumor progression and treatment response. Predictive modeling could allow the anticipation of tumor evolution and drug response, supporting adaptive therapeutic plans and real-time treatment adjustments. Moreover, AI supports biomarker discovery, patient stratification and decision support systems that can improve clinical trial design and accelerate the development of personalized therapies. However, these advances raise important ethical challenges, including data privacy, algorithmic bias and the preservation of patient autonomy. Addressing these concerns is essential to ensure the responsible deployment of AI in oncology. Full article

Quasi-static ultrasound elastography (USE) is a promising imaging technique for detecting malignancies by assessing tissue stiffness, but its accuracy heavily depends on the quality of radio-frequency (RF) frame pairs used for displacement estimation. A major challenge in quasi-static USE is signal decorrelation, which is primarily caused by out-of-plane motion during manual probe compression, leading to unreliable displacement fields and degraded elastography images. This paper introduces a novel, displacement estimator-agnostic method for assessing RF frame pair quality by measuring the similarity between the measured post-compression RF frame and a warped version of the pre-compression frame generated using the estimated displacement field. The proposed approach employs computationally efficient metrics such as mean squared error (MSE) and correlation, demonstrating robustness against signal decorrelation in both synthetic and clinical datasets. Additionally, we present a method to simulate realistic RF data corruption via controlled out-of-plane displacements, facilitating the development of robust motion-tracking algorithms. Validation using in silico phantoms, tissue-mimicking phantoms and clinical breast cancer and liver cancer cases confirm the method’s efficacy in identifying high-quality frame pairs, significantly improving strain image accuracy. Threshold values of 1.4 and 0.5 were determined for MSE and correlation, respectively, as being effective to differentiate between good vs. bad RF data frame pairs. This work lays the foundation for automated frame selection in USE, enhancing its diagnostic reliability and clinical utility. Full article

The tumor microenvironment of breast cancer presents high complexity and resistance to conventional therapies. Ferroptosis, a programed cell death that is dependent on iron and characterized by lipid peroxidation, arises as a promising therapeutic goal. This scoping review mapped evidence on the exogenous use of iron and selenium, in conventional or nano-particulated forms, in the modulation of ferroptosis as therapeutic strategy for breast cancer treatment, identifying knowledge gaps and opportunities for future research. We performed a scoping review and the methodology followed the guidelines of the Joanna Briggs Institute (JBI) and PRISMA-ScR. We made a systematic search in five data bases (Embase, Lilacs, PubMed (MEDLINE), Scopus, and Web of Science) between the years 2012 and 2025. Among 2.723 identified publications, we selected 48 studies. The results revealed predominance of nanoplatforms of iron (97.9%), focused on the Fenton reaction. The modulation of selenium for inactivation of GPX4 was shown to be effective, though still little-explored (n = 1). We evidenced that the induction of ferroptosis potentializes tumor immunogenicity and the effectiveness of combined therapies. We conclude that the field is under development; thus, the diversification of metabolic targets and trials of chronic toxicity are fundamental steps for future clinical research. Full article