Biomedical research requires both in vitro and in vivo studies in order to explore disease processes or drug interactions. Foundational investigations have been performed at the cellular level using two-dimensional cultures as the gold-standard method since the early 20th century. However, three-dimensional (3D) cultures have emerged as a new tool for tissue modeling over the last few years, bridging the gap between in vitro and animal model studies. Cancer has been a worldwide challenge for the biomedical community due to its high morbidity and mortality rates. Various methods have been developed to produce multicellular tumor spheroids (MCTSs), including scaffold-free and scaffold-based structures, which usually depend on the demands of the cells used and the related biological question. MCTSs are increasingly utilized in studies involving cancer cell metabolism and cell cycle defects. These studies produce massive amounts of data, which demand elaborate and complex tools for thorough analysis. In this review, we discuss the advantages and disadvantages of several up-to-date methods used to construct MCTSs. In addition, we also present advanced methods for analyzing MCTS features. As MCTSs more closely mimic the in vivo tumor environment, compared to 2D monolayers, they can evolve to be an appealing model for in vitro tumor biology studies.

Inflammatory Bowel Diseases (IBDs) are characterized by chronic intestinal inflammation and fibrosis, the latter being the predominant denominator for long-term complications. Epithelial and mesenchymal 2D cultures are highly utilized in vitro models for the preclinical evaluation of anti-inflammatory and antifibrotic therapies. More recently, human intestinal organoids (HIOs), a new 3D in vitro model derived from pluripotent stem cells, have the advantage to closely resemble the architecture of the intestinal mucosa. However, the appropriate timing for the study of inflammatory and fibrotic responses, during HIO development, has not been adequately investigated. We developed HIOs from the human embryonic stem cell line, H1, and examined the expression of mesenchymal markers during their maturation process. We also investigated the effect of inflammatory stimuli on the expression of fibrotic and immunological mediators. Serial evaluation of the expression of mesenchymal and extracellular matrix (ECM) markers revealed that HIOs have an adequately developed mesenchymal component, which gradually declines through culture passages. Specifically, CD90, collagen type I, collagen type III, and fibronectin were highly expressed in early passages but gradually diminished in late passages. The proinflammatory cytokines IL-1α and TNF-α induced the mRNA expression of fibronectin, collagen types I and III, tissue factor (TF), and alpha-smooth muscle actin (α-SMA) primarily in early passages. Similarly, HIOs elicited strong mRNA and protein mesenchymal (CXCL10) and epithelial (CXCL1, CCL2, CXCL8, and CCL20) chemokine responses in early but not late passages. In contrast, the epithelial tight junction components, CLDN1 and JAMA, responded to inflammatory stimulation independently of the culture passage. Our findings indicate that this HIO model contains a functional mesenchymal component, during early passages, and underline the significance of the mesenchymal cells fitness in inflammatory and fibrotic responses. Therefore, we propose that this model is suitable for the study of epithelial-mesenchymal interactions in early passages when the mesenchymal component is active.

Biofilm-forming pathogens are a major cause of persistent infections, showing limited response to antibiotic treatment. The search for alternative strategies has therefore driven extensive research into the antimicrobial potential of beneficial microorganisms. In the present study, the antibacterial and antibiofilm activity of the commercial probiotic strain Lacticaseibacillus casei ATCC 393 (Lc393) was examined against clinical isolates of Staphylococcus aureus, Salmonella enterica subsp. enterica serovar Enteritidis and Escherichia coli. Lc393 reduced pathogen viability and attachment to the colon adenocarcinoma cell line HT-29, with maximal effects recorded against S. aureus. Confocal microscopy visualization of the lactobacilli-pathogens-host interface revealed that Lc393 binds loosely to both host cells and pathogens. The Lc393 cell-free culture supernatant (CFCS) significantly reduced planktonic growth, biofilm mass, and viability of cells in biofilm (>2 logCFU reduction, p < 0.05) and downregulated genes involved in the early stages of biofilm formation in S. aureus (i.e., icaA, fnbpA, eno). In silico analysis of the Lc393 genome identified two bacteriocin clusters, along with genes related to ethanol and organic acid production. Based on in silico predictions and a bacteriocin zymogram, the strain cannot produce functional antimicrobial peptides. Untargeted metabolomics based on UPLC/MS further revealed the presence of putative antimicrobial metabolites. Collectively, our findings highlight the antimicrobial potential of Lc. casei ATCC 393 and support its further investigation for combating clinically relevant human pathogens.

Chromosomal instability (CIN) arising from mitotic errors is a hallmark of cancer progression. Hepatoma Upregulated Protein (HURP), a microtubule-associated protein essential for spindle assembly, is frequently overexpressed in aggressive cancers. Here, we investigated HURP's role in breast cancer progression using a cell line model of increasing metastatic potential: immortalized MCF10A, low-metastatic T47D, and highly metastatic MDA-MB-231 cells. Elevated HURP expression was observed in cancer cells, with MDA-MB-231 showing the highest levels. Paradoxically, spindle-bound HURP was reduced in MDA-MB-231 cells despite increased total protein, suggesting cytoplasmic mislocalization. HURP silencing induced cell line-specific effects: moderate spindle defects in MCF10A and T47D cells, but severe abnormalities, apoptosis, and G2/M arrest in MDA-MB-231 cells. Mechanistically, HURP depletion perturbed spindle-bound NuMA, TPX2, and Aurora-A levels, implicating HURP in mitotic regulation and metastatic behavior. HURP silencing also impaired collective migration and converted MDA-MB-231 cells from super-diffusive to sub-diffusive motility, while having minimal effects on less aggressive cell lines. These findings establish HURP as a multifunctional regulator coordinating mitotic fidelity, migration plasticity, and tissue architecture in breast cancer, with pronounced effects in highly metastatic cells, positioning it as a promising therapeutic target for aggressive breast cancers.

Deep vein thrombosis (DVT) is characterized by the formation of blood clots in the deep veins, most commonly in the lower limbs, obstructing blood flow. In about 50% of cases, the clot dislodges and travels to the lungs, causing potentially fatal pulmonary embolism. Diagnosing DVT is challenging, as up to half of cases are asymptomatic. Early and accurate diagnosis is critical, but the current state of the art in ultrasound and plethysmography is insufficient for continuous, operator-independent, point-of-care monitoring. This paper introduces the concept and advances of the ThrombUS+ Horizon Europe project, which aims to innovate toward modular and wearable system for continuous, point-of-care DVT monitoring. The system leverages a multimodal approach, incorporating compression ultrasonography, electrical impedance plethysmography, and light reflection rheography, by re-engineering these clinical technologies for seamless integration into a wearable architecture. Manual compression of an ultrasound transducer is replaced by a sophisticated actuator, enabling precise pressure control via a piezoelectric micropump with feedback signals. The same actuator supports plethysmography modules, providing additional data for DVT assessment. These inputs, combined with physical movement monitoring, are processed by an artificial intelligence-driven central intelligence unit for DVT detection, risk assessment, and prevention. Preliminary laboratory testing of the individual modules highlights the system’s potential for autonomous DVT monitoring and detection. The ThrombUS+ uses big datasets for machine learning training collected in the project via 3 large-scale clinical studies. The entire system will be validated in the clinical setting via an early feasibility study and a multicenter clinical trial.