Italian register of therapeutic apheresis: 30 years of activity.

The electrophoretic velocity of a charged dielectric particle is independent of its size and shape in a Newtonian fluid under the thin Debye layer limit in the weak-field regime. Our previous paper (Bentor and Xuan, Analytical Chemistry 2024, 96, 3186-3191) reported particle size-dependent electrophoresis in viscoelastic poly(ethylene oxide) (PEO) solutions. We demonstrate herein that the fluid elasticity also induces the particle shape dependence of electrophoretic velocity likely because the polymer stress around a particle varies with its shape. Specifically, altering the shape of a particle from sphere to pear and peanut enhances the electrophoretic velocity in a viscoelastic fluid as the particle becomes slenderer. This phenomenon, which is found absent from a Newtonian fluid, becomes stronger in higher-concentration PEO solutions because of the enhanced fluid elasticity effect. It may be utilized for the label-free electrophoretic separation of particles and cells in non-Newtonian microfluidic devices.

Single cell RNA-seq (scRNA-seq) technologies provide unprecedented resolution representing transcriptomics at the level of single cell. One of the biggest challenges in scRNA-seq data analysis is the cell type annotation, which is usually inferred by cell separation approaches. In-silico algorithms that accurately identify individual cell types in ongoing single-cell sequencing studies are crucial for unlocking cellular heterogeneity and understanding the biological basis of diseases. In this study, we focus on robustly identifying cell types in single-cell RNA sequencing data; we conduct a comparative analysis using methods established in biology, like Seurat, Leiden, and WGCNA, as well as network-based methods Infomap, statistical inference via Stochastic Block Models (SBM), and single-cell Graph Neural Networks (scGNN). We also analyze preprocessing pipelines to identify and optimize key components in the process, explicitly considering their role in mitigating inherent data noise and potential batch effects for robust cell type identification. Leveraging three independent datasets, PBMC, ROSMAP, and MOp, we employ clustering algorithms on cell-cell networks derived from gene expression data. Our findings reveal that clusters identified by multiresolution Infomap and Leiden show a closer alignment, with Infomap standing out as a particularly effective approach. Infomap notably offers valuable insights for the precise characterization of cellular landscapes related to neurodegeneration and immunology in scRNA-seq.

BackgroundProgression and metastasis of solid cancers are orchestrated by activation of epithelial-mesenchymal transition (EMT) in the primary tumor. This process is typically restricted to a limited number of cells that acquire partial or hybrid EMT states to unleash cellular plasticity. Capturing such dynamic and often reversible events in vivo on the single cell level is hampered by the lack of proper labeling tools that yet often induce permanent staining persisting beyond transient EMT activation.MethodsTo enable live-tracking of EMT in vivo, we utilized CRISPaint and homologous recombination to endogenously tag ZEB1, one key transcription factor to activate EMT during tumorigenesis. Using the bright fluorescent protein mNeonGreen, we generated ZEB1-Neon fusion knock-in alleles in MDA-MB-231 and MCF10A cells, as well as in mice.ResultsWe demonstrate that mNeonGreen fluorescence is suitable to faithfully report on ZEB1 expression in vitro over time, becomes properly upregulated by TGFβ, and allows separation of ZEB1hi and ZEB1lo cells to capture different cellular properties, e.g., handling of DNA damage. The fusion does not affect ZEB1 function as evident by proper EMT induction, embryogenesis, and tissue homeostasis when present homozygously. Moreover, introducing Zeb1-Neon into the KPC mouse model of pancreatic cancer permits tracking of ZEB1+ cells in precision-cut slices and time-lapse imaging of isolated tumor cells.ConclusionsIn summary, we provide a versatile tool that allows precise detection and live cell imaging of EMT, which will help to more accurately decipher the role of EMT in tumor progression and to identify therapeutic agents that can specifically manipulate EMT for novel combination therapies.Graphical Supplementary InformationThe online version contains supplementary material available at 10.1186/s12915-026-02629-0.

Microfluidic technology enables scalable solutions in precision medicine, diagnostics, drug delivery, organ-on-a-chip models, single-cell analysis, high-throughput screening, and environmental monitoring. In fact, many of these applications process fluids with complex rheology, e.g., blood, mucus, bioinks, and polymer or particle suspensions, exhibiting yield stress, viscoelasticity, and shear-thinning that govern transport, mixing, and interfacial dynamics at small scales. However, the interplay of such rheology with microscale confinement, roughness, and surface patterning remains underexplored. In this review, we highlight microfluidic applications where yield stress (and related rheological) properties are pivotal. For instance, we discuss how blood rheology shapes the design of devices for circulating tumor cell separation, and how bioink viscoelasticity balances flowability and shape fidelity in extrusion and embedded bioprinting. We also examine electrorheological fluids as field-tunable media for microvalves, pumps, and mixers, and analyze microorganism and microrobot locomotion in complex fluids, linking physics to biology and targeted delivery. We further consider microscale slip, microrheology platforms, and viscous fingering instabilities, to specifically highlight how rheology controls transport and enables fabrication of channels and hydrogel structures. We conclude that yield-stress (and viscoelastic) effects are not mere complications but they are powerful design variables, and we outline future opportunities for leveraging these properties to advance microfluidic science and technology.

High endothelial venules (HEVs) provide another portal for tumour metastasis. However, whether HEVs and other blood vessels exert different effects on tumour escape remains unknown. Here we show that tumour involvement in HEVs is an independent prognostic marker for patients with lymph node (LN)-positive female breast cancer. Tumour cells that spread via HEVs are less immunogenic and more capable of establishing distant metastases than those that spread through non-HEV blood vessels. Mechanistically, the expression of arachidonate 12-lipoxygenase (ALOX12) in HEVs is promoted by tumour-derived semaphorin 3 C (SEMA3C). Reciprocally, ALOX12-derived metabolite 12-hydroxyeicosatetraenoic acid (12-HETE) promotes ADAR1 p150-dsRNA phase separation in tumour cells by selectively binding to ADAR1 p150. Consequently, the immune recognition of dsRNA is reduced because of the increased adenosine-to-inosine (A-to-I) RNA editing in tumour cells. Collectively, our data indicate that a unique lymphatic anatomical structure mediates specific immune evasion of migrating tumour cells.

Fungal cell walls are dynamic extracellular structures essential for growth and morphogenesis, making them prime targets for antifungal drugs and the host immune system. Although many protein families involved in the synthesis, crosslinking, and degradation of cell wall polymers are known, the molecular functions and structural evolution of most cell wall proteins remain poorly understood. Our in-depth structural, functional, and phylogenetic analysis of the fungal SUN domain protein family sheds light on a central question: how specific protein families have evolved structurally to enable dynamic cell wall remodeling during growth and division. Moreover, this work identifies precise structural targets within the fungal cell wall that could guide the development of novel diagnostics and therapeutics against life-threatening fungal infections.

Enhanced secondary flow-guided microfluidic chip design for cell separation

Ultra-narrow strip-shaped crystalline silicon (c-Si) solar cells are promising for translucent photovoltaic modules but suffer from significant efficiency losses due to edge recombination after cell separation. An additional edge passivation process can alleviate this loss, but it increases cost and process complexity. This study investigates alternative approaches to suppress edge recombination loss without dedicated passivation layers. Strip-shaped silicon heterojunction (SHJ) cells, 3–9 mm wide, were fabricated using laser scribing and mechanical cleaving (LSMC). Experimental results, supported by device simulations, reveal that front-junction configurations and thinner c-Si substrates effectively mitigate efficiency loss associated with cut edges. Two additional design strategies were evaluated. A transparent conductive oxide (TCO) margin approach, which removes the emitter near the edge, improved open-circuit voltage to 715 mV in 5-mm-wide cells, although efficiency was constrained by reduced short-circuit current density. In contrast, the Pre-Grooved LSMC (PG-LSMC) method, enabling in-situ partial edge passivation, suppressed edge recombination and enhanced efficiency, particularly in rear-junction-type cells. These results highlight that optimized device design, thickness reduction, emitter isolation, and in-situ partial passivation can compensate for the absence of dedicated edge passivation. The insights gained from these extreme geometries are broadly applicable to divided and shingled cells, where edge recombination remains a critical loss mechanism. • Front-junction design and thinner substrates reduce edge-related loss in ultra-narrow cells. • TCO margin approach mitigates V OC & FF losses in ultra-narrow cells. • Pre-grooved LSMC method enables in-situ partial edge passivation, enhancing cell efficiency. • The above-mentioned strategies compensate for the absence of dedicated edge passivation.

Solid additive-mediated modulation of donor and acceptor aggregation for regulating phase separation in efficient all-polymer solar cells

Safe and clinically useful therapeutic drug delivery systems must be developed to fight fatal diseases and disorders like cancer, hypertension, and diabetes, among others. However, these systems face significant development challenges due to their solubility, stability, permeation, cytotoxicity, drug entrapment, and loading issues. Imitations can be avoided by creating innovative drug delivery systems based on nanomaterials, such as nanoclays. As layered nanostructures, nanoclays have many advantageous qualities, such as chemical inertness, colloids (dispersed in blood plasma), a large surface area, and viscosity. Nanoclays are qualified for use as a drug delivery carrier for anti-cancer, antihypertensive, antioxidant, and anti-diabetes medicines based on these qualities. This study discusses the evolution and use of nanoclay in drug delivery research. Clays of various sorts (kaolinite, halloysite, and montmorillonite) have been employed to generate prolonged and targeted drug delivery with enhanced pharmacokinetic characteristics. The modified clay demonstrated optimal drug loading, trapping, release, electrostatic interaction (van der Waals interaction), ion exchange reaction, and immobilization. Finally, nanoclay was employed to create a drug delivery system with enhanced pharmacokinetic properties for proteins, DNA, and pharmaceuticals. Many earlier research investigations have also reported its usage in bio-imaging, tissue engineering, gene transfer, and stem cell separation.

Time-dependent cell adhesion to lectin-coated surfaces as a predictor of flow-based separation efficiency.

Design and fabrication of a platform for circulating tumor cells (CTCs) isolation and detection by MiRGD@NTA@Au-Fe3O4 nanoparticles.

ConspectusBiomolecular condensates are membrane-less organelles formed via liquid-liquid phase separation (LLPS) in cells, which play crucial roles in organizing biochemical reactions, regulating gene expression, and responding to environmental stimuli. These dynamic membrane-less organelles, such as stress granules and nucleoli, could concentrate specific proteins and nucleic acids for spatiotemporally controlling cellular processes. The engineering of synthetic condensates is beneficial for understanding condensates formation, simulating cellular behavior, and exploration of biological pathologies.Nucleic acid, as an important component of biomolecular condensates in cells, offers a unique platform to engineer synthetic condensates due to its programmability and precise and predictable Watson-Crick base pairing. The nucleic acid-based condensates were assembled through multivalent forces among nucleic acids or nucleic acid-peptide complexes. By designing and modifying nucleic acid sequences, the interaction forces could be regulated with external stimuli to control the formation and decomposition of nucleic acid-based condensates for various fields application. Our group has constructed various nucleic acid-based biomolecular condensates and applied them in biosensing and cellular regulation. We designed CUG repeats-based condensates for improving fluorescent RNA aptamer properties (enzymatic degradation resistance, thermal stability, photostability, and binding affinity to fluorophores) and detecting in vitro and intracellular biomolecules (adenosylmethionine and tetracycline), as well as target cells with overexpressed epithelial cell adhesion molecules. In addition, we leveraged the strong Watson-Crick base pairing ability to recruit the intracellular target RNA into condensates for cellular regulation.In this Account, we give an overview of nucleic acid-based biomolecular condensates. We first discuss the intermolecular interactions and forces involved in the formation of nucleic acid-based biomolecular condensates. Subsequently, we summarize recent research about nucleic acid-based condensates and their applications in the fields of biological imaging and biosensing, cell simulation, cellular regulation, and drug delivery. Finally, we outline the current challenges and future opportunities of nucleic acid-based biomolecular condensates. We hope that this Account will afford significant inspiration in the design of nucleic acid-based condensates and the applications in cell biology and biomedicines.

Circulating tumor cells (CTCs) are valuable liquid-biopsy biomarkers, yet their extreme rarity makes high-purity, high-throughput enrichment challenging. In spiral inertial microfluidics, high cell loading induces long-range hydrodynamic interactions that broaden the focused blood-cell stream; consequently, a subpopulation completes the ~0.5 and ~1.0 Dean-cycle migrations with a phase delay, compressing the CTC-blood cell gap and degrading purity. Here we propose a Dean-cycle phase-regulated double-spiral design informed by this phenomenon. This design aims to mitigate the stream-broadening effect by boosting the Dean number during the first half-cycle to promote synchronized blood-cell migration and shifting the CTC equilibrium position near one full cycle to further widen the CTC-blood cell separation. We implement this strategy in a second-generation double-spiral microfluidic chip (SDMC) and scale it to a four-channel parallel array (ASDMC). Under optimized conditions, ASDMC processes diluted whole blood (hematocrit = 4%) without the need for red blood cell (RBC) lysis or antibody labeling, achieving a sample throughput of 1200 μL·min-1. Specifically, it exhibits a mean recovery rate of 98.8% across three spiked tumor cell lines (MCF-7, PC-9, and Mahlavu) and a mean white blood cell (WBC) depletion efficiency of 93.3%. In a pilot clinical testing of 20 patients (NSCLC and HCC), enriched fractions enabled immunofluorescence identification of CK+CD45-DAPI+ CTCs, with an exploratory trend of increasing CTC counts with advanced disease stage (4-34 cells·mL-1). These results describe a scalable, label-free platform, and the observed purification performance aligns with our proposed mechanism: Dean-cycle phase regulation to mitigate blood-cell migration lag. Our findings support further technical validation and clinical assessment in larger cohorts.

Synchrotron phase-contrast microtomography reveals the impact of degeneration on the 3D structure of human articular cartilage.

NCOA4-Mediated Ferritinophagy Induces Ferroptosis and Enriches Ferritin-Containing EVs via Ferritin Phase Separation to Promote Mechanical Ventilation-Induced Pulmonary Fibrosis.

Constriction-induced capture of rare cells using interdigitated microchannels with bidirectionally perforated thin honeycomb films.

Sickle cell disease is a hereditary hemoglobinopathy commonly seen in sub-Saharan Africa, India, and the Middle East. It is caused by a mutation in the β-globin gene and is associated with both acute and chronic multiorgan complications, including severe anemia and stroke. Materials and methods: This cross-sectional study was carried out over a period ofone year (2022-2023) among patients with sickle cell disease. Automated red cell exchange was performed using a continuous-flow cell separator to assess the procedural efficiency. A total of 30 male and female patients with sickle cell disease from districts surrounding Indore were included. The mean age was 23.4 years, and procedures were performed for various indications as per the American Society for Apheresis (ASFA) guidelines. Most cases, 27 (90%), fell under category II.Thirty automated red cell exchange procedures were performed. Among these, 17 (57%) patients achieved a hemoglobin S (HbS) reduction of 71-80%, eight (27%) >81% reduction, four (13%) 61-70% reduction, and one (3%) <60% reduction. Automated red cell exchange led to significant improvement in multiple hematological parameters, including hemoglobin levels, hematocrit, indirect bilirubin, and HbS percentage, supporting its effectiveness in the management of sickle cell disease.

Progress in sperm cell separation and analytical techniques for semen-epithelial mixed stains: a forensic perspective.