Metastatic invasiveness emerges from coordinated intrinsic programs and microenvironmental cues that converge on mitochondrial quality control (MQC). Here, we use "context" to denote stage- and site-aware constellations of tumor-intrinsic states (e.g., mtROS tone, mtDNA integrity, epigenetic wiring, cellular stiffness, oncogenic mutations) and extrinsic landscapes (oxygen-nutrient availability, ECM mechanics, stromal/inflammatory signals). These axes jointly shape mitochondrial adaptation by tuning bioenergetics, redox balance, metabolic plasticity, fission-fusion dynamics, mechanosensitive hubs, and Ca2 + homeostasis. As pressures intensify, mitochondrial vulnerabilities-such as mtDNA compromise and mtUPR activation-signal the engagement of mitophagy to preserve organelle fitness under stress. Through these coupled changes in mitochondrial performance and stress responses, context governs EMT/MET plasticity and transitions across migratory, invasive, and proliferative states. Mechanistically, ubiquitin conjugation, via E3 ligases and deubiquitinases, serves as an integrating conduit that links mitochondrial remodeling and mitophagy to cytoskeletal reprogramming and invasive behavior. This ubiquitin-mitochondria interface therefore represents a coherent therapeutic entry point; translational strategies including PROTAC-enabled targeting and selective E3/DUB or mitophagy-pathway modulators may rebalance pathological ubiquitin signaling, restore mitochondrial homeostasis, and constrain tumor dissemination.

Hierarchical extracellular matrix (ECM) cues spanning mechanics, architecture, and matrix–matrix interfaces (MMIs) regulate the directionality and efficiency of tumor-cell migration and invasion. Despite their relevance, the contributions of interfacial structures within 3D ECMs remain under-resolved, particularly whether discrete boundaries serve as “attractor-and-track” drivers. Here, we engineered a polydimethylsiloxane (PDMS) microfluidic platform to create controlled MMIs that emulate the tumor microenvironment (TME)’s mechanical heterogeneity, achieved by sequential collagen gelation to create both planar and curved boundaries. With the system, we quantified how MDA-MB-231 (invasive) and MCF-7 (non-invasive) breast cancer spheroids migrate in uniform matrices of graded stiffness and when encountering soft–stiff boundaries. MDA-MB-231 spheroids demonstrated significantly greater migration in soft matrices and exhibited distinct invasive outgrowth at interfacial boundaries, with soft-top pairings (o–o, t–o) gating early detachment, followed by convergence of outgrowth across stiffness pairings at later times. Spheroids positioned above or below planar or curved MMIs showed directional approach toward the boundary and alignment of trajectories within the interfacial plane, consistent with interface-seeking and interface-parallel migration. In contrast, MCF-7 spheroids displayed minimal migration under all tested conditions, underscoring a phenotype-dependent responsiveness to ECM cues. Overall, our findings highlight the critical role of interfacial structures, in addition to bulk stiffness and architecture, in shaping cancer invasion, supporting a two-phase model in which local bulk mechanics license early outward dissemination, whereas interfacial stiffness increasingly sustains expansion. The proposed microfluidic platform offers a tunable and physiologically relevant model for dissecting 3D cell migration mechanisms within complex ECM environments, with optical access, curvature control, and validated passive gradients enabling future chemotaxis studies.

Multicellular spheroids (MCSs) are increasingly employed as 3D cell culture models in biomedical research due to their ability to effectively replicate in vivo cell interactions, making them suitable for high-throughput drug screening. Accurate cell counting is critical for data normalization, therapeutic evaluation, and exploration of culture conditions; however, affordable software solutions for 3D cell counting using microscopic images are limited. To fill this gap, we created SUNSHINE, an innovative on-chip analytical workflow that uniquely merges optical clearing, histogram matching (HM)-assisted fluorescence calibration, and simple linear iterative clustering (SLIC) supervoxel segmentation. This tool offers an efficient method for analyzing the characteristics and counts of fluorescence-labeled nuclei within MCSs. While optical clearing improves the penetration depth of microscopic imaging, deeper regions of thicker samples often yield faint fluorescence signals. SUNSHINE resolves this issue through the HM image post-processing algorithm. Moreover, SLIC is an effective alternative to traditional contour-wise segmentation, enabling the identification of irregularly shaped fluorescent nuclei. We found that SUNSHINE generated results comparable to commercial software like Imaris and machine learning (ML)-based tools, such as StarDist and Cellpose, in our analysis of the effects of seeding density and cell type on spheroid growth. We also used it to measure the volume and spatial distribution of nuclei, focusing on the hypoxic and peripheral regions of spheroids. Overall, this study finds that SUNSHINE serves as a valuable and economical approach for characterizing cellular activity and interactions in 3D, diminishing the reliance on costly proprietary software.

During cancer metastasis, tumor cells likely navigate, in a collective manner, discrete tissue spaces comprising inherently heterogeneous extracellular matrix microstructures where interfaces may be frequently encountered. Studies have shown that cell migration modes can be determined by adaptation to mechanical/topographic cues from interfacial microenvironments. However, less attention has been paid to exploring the impact of interfacial mechnochemical attributes on invasive and metastatic behaviors of tumor aggregates. Here, we excogitated a collagen matrix-solid substrate interface platform to investigate the afore-stated interesting issue. Our data revealed that stiffer interfaces stimulated spheroid outgrowth by motivating detachment of single cells and boosting their motility and velocity. However, stronger interfacial adhesive strength between matrix and substrate led to the opposite outcomes. Besides, this interfacial parameter also affected the morphological switch between migration modes of the detached cells and their directionality. Mechanistically, myosin II-mediated cell contraction, compared to matrix metalloproteinases-driven collagen degradation, was shown to play a more crucial role in the invasive outgrowth of tumor spheroids in interfacial microenvironments. Thus, our findings highlight the importance of heterogeneous interfaces in addressing and combating cancer metastasis.

Metastasis is the leading cause of cancer-related deaths. During this process, cancer cells are likely to navigate discrete tissue-tissue interfaces, enabling them to infiltrate and spread throughout the body. Three-dimensional (3D) spheroid modeling is receiving more attention due to its strengths in studying the invasive behavior of metastatic cancer cells. While microscopy is a conventional approach for investigating 3D invasion, post-invasion image analysis, which is a time-consuming process, remains a significant challenge for researchers. In this study, we presented an image processing pipeline that utilized a deep learning (DL) solution, with an encoder-decoder architecture, to assess and characterize the invasion dynamics of tumor spheroids. The developed models, equipped with feature extraction and measurement capabilities, could be successfully utilized for the automated segmentation of the invasive protrusions as well as the core region of spheroids situated within interfacial microenvironments with distinct mechanochemical factors. Our findings suggest that a combination of the spheroid culture and DL-based image analysis enable identification of time-lapse migratory patterns for tumor spheroids above matrix-substrate interfaces, thus paving the foundation for delineating the mechanism of local invasion during cancer metastasis.

Background: Escherichia coli is the most common cause of urinary tract infections (UTIs). It is widely accepted that uropathogenic E. coli (UPEC) mainly emerge from the distal gut microbiota. Identification of bacterial characteristics that are able to differentiate UPEC from fecal commensal strains will facilitate the development of novel strategies to detect and monitor the spread of UPEC. Methods: Fifty fecal commensal, 83 UTI-associated and 40 biliary tract infection (BTI)-associated E. coli isolates were analyzed. The NotI restriction patterns of chromosomal DNA in the isolates were determined by pulse-field gel electrophoresis. The phylogenetic types and the presence of 9 known virulence genes of each isolate were determined by PCR analyses. Additionally, the susceptibilities of the isolates to antibiotics were revealed. Then the associations of NotI resistance with UTI-associated isolates, phylotypes, and antibiotic resistance were assessed. Results: NotI resistance was correlated with UTI-associated isolates, compared to the fecal isolates. Consistently, NotI-resistant isolates harbored a greater number of virulence factors and mainly belonged to phylotype B2. Additionally NotI resistance was correlated with chloramphenicol resistance among the bacteria. Among the fecal, UTI-associated and BTI-associated groups, the distribution of NotI-resistant group B2 isolates was correlated with UTI-associated bacteria. Conclusion: NotI resistance alone is a potential marker for distinguishing fecal strains and UPEC, while the combination of NotI resistance and B2 phylogeny is a candidate marker to differentiate UPEC from fecal and other extraintestinal pathogenic E. coli. Additionally, NotI resistance may be valuable for assessing the potential of chloramphenicol resistance of E. coli.

Abstract Background Silver nanoparticles (AgNPs) are considered a double-edged sword that demonstrates beneficial and harmful effects depending on their dimensions and surface coating types. However, mechanistic understanding of the size- and coating-dependent effects of AgNPs in vitro and in vivo remains elusive. We adopted an in silico decision tree-based knowledge-discovery-in-databases process to prioritize the factors affecting the toxic potential of AgNPs, which included exposure dose, cell type and AgNP type (i.e., size and surface coating), and exposure time. This approach also contributed to effective knowledge integration between cell-based phenomenological observations and in vitro/in vivo mechanistic explorations. Results The consolidated cell viability assessment results were used to create a tree model for generalizing cytotoxic behavior of the four AgNP types: SCS, LCS, SAS, and LAS. The model ranked the toxicity-related parameters in the following order of importance: exposure dose > cell type > particle size > exposure time ≥ surface coating. Mechanistically, larger AgNPs appeared to provoke greater levels of autophagy in vitro, which occurred during the earlier phase of both subcytotoxic and cytotoxic exposures. Furthermore, apoptosis rather than necrosis majorly accounted for compromised cell survival over the above dosage range. Intriguingly, exposure to non-cytotoxic doses of AgNPs induced G2/M cell cycle arrest and senescence instead. At the organismal level, SCS following a single intraperitoneal injection was found more toxic to BALB/c mice as compared to SAS. Both particles could be deposited in various target organs (e.g., spleen, liver, and kidneys). Morphological observation, along with serum biochemical and histological analyses, indicated that AgNPs could produce pancreatic toxicity, apart from leading to hepatic inflammation. Conclusions Our integrated in vitro, in silico, and in vivo study revealed that AgNPs exerted toxicity in dose-, cell/organ type- and particle type-dependent manners. More importantly, a single injection of lethal-dose AgNPs (i.e., SCS and SAS) could incur severe damage to pancreas and raise blood glucose levels at the early phase of exposure.

Silver nanoparticles (AgNPs) are widely used in the household, medical and industrial sectors due to their effective bactericidal activities and unique plasmonic properties. Despite the promising advantages, safety concerns have been raised over the usage of AgNPs because they pose potential hazards. However, the mechanistic basis behind AgNPs toxicity, particularly the sublethal effects at the organismal level, has remained unclear. In this study, we used a powerful in vivo platform Drosophila melanogaster to explore a wide spectrum of adverse effects exerted by dietary AgNPs at the organismal, cellular and molecular levels. Lethal doses of dietary AgNPs caused developmental delays and profound lethality in developing animals and young adults. In contrast, exposure to sublethal doses, while not deadly to developing animals, shortened the adult lifespan and compromised their tolerance to oxidative stress. Importantly, AgNPs mechanistically resulted in tissue-wide accumulation of reactive oxygen species (ROS) and activated the Nrf2-dependent antioxidant pathway, as demonstrated by an Nrf2 activity reporter in vivo. Finally, dietary AgNPs caused a variety of ROS-mediated stress responses, including apoptosis, DNA damage, and autophagy. Altogether, our study suggests that lethal and sublethal doses of AgNPs, have acute and chronic effects, respectively, on development and longevity by inducing ROS-mediated stress responses.

Safety concerns have been raised over the extensive applications of silver nanoparticles (AgNPs) because nano dimensions make them highly bioactive, being potentially harmful to the exposed humans. Surface physico-chemistry (shape, surface charge, chemical composition, etc.) that mainly dictates nano-bio interactions is relevant for influencing their biocompatibility and toxicity. Although the hazardousness of AgNPs has been demonstrated in vitro and in vivo, mechanistic understanding of the toxicity particularly at the molecular and organismal levels, in addition to oxidative stress and silver ion dissolution, has remained unclear. A growing body of research has elucidated that autophagy, being activated in response to exposure to various nanomaterials, may serve as a cellular defense mechanism against nanotoxicity. Recently, autophagy activation was shown to correlate with AgNPs exposure; however, the subsequent autophagosome-lysosome fusion was defective. As autophagy plays a crucial role in selective removal of stress-mediated protein aggregates and injured organelles, AgNPs-induced autophagic flux defect may consequently lead to aggravated cytotoxic responses. Furthermore, we suggest that p62 accumulation resulting from defective autophagy may also potentially account for AgNPs cytotoxicity. Intriguingly, AgNPs have been shown to interfere with ubiquitin modifications, either via upregulating levels of enzymes participating in ubiquitination, or through impairing the biological reactivity of ubiquitin (due to formation of AgNPs-ubiquitin corona). Ubiquitination both confers selectivity to autophagy as well as modulates stabilization, activation, and trafficking of proteins involved in autophagic clearance pathways. In this regard, we offer a new perspective that interference of AgNPs with ubiquitination may account for AgNPs-induced defective autophagy and cytotoxic effects.

ABSTRACT Escherichia coli is the most common cause of urinary tract infections (UTIs). E. coli genes epidemiologically associated with UTIs are potentially valuable in developing strategies for treating and/or preventing such infections as well as differentiating uropathogenic E. coli from nonuropathogenic E. coli . To identify E. coli genes associated with UTIs in humans, we combined microarray-based and PCR-based analyses to investigate different E. coli source groups derived from feces of healthy humans and from patients with cystitis, pyelonephritis, or urosepsis. The cjrABC-senB gene cluster, sivH , sisA , sisB , eco274 , and fbpB , were identified to be associated with UTIs. Of these, cjrABC-senB , sisA , sisB , and fbpB are known to be involved in urovirulence in the mouse model of ascending UTI. Our results provide evidence to support their roles as urovirulence factors in human UTIs. In addition, the newly identified UTI-associated genes were mainly found in members of phylogenetic groups B2 and/or D.