Deep mapping of structural perturbations to energetics enables precise TCR design

Luo et al. present mpTCRai, a deep learning framework for predicting TCR-antigen specificity. By mapping sequence mutations to structural perturbations and energetic consequences, mpTCRai serves as a computational pre-filtering engine to narrow down vast mutational spaces, guiding and accelerating the rational design of TCRs.

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Inference of lineage hierarchies, growth, and drug response mechanisms in cancer cell populations without tracking

Piras et al. present a statistical framework to infer lineage hierarchies and phenotypic transition probabilities in heterogeneous cell populations without tracking individual cells. Using multi-type Bienaymé-Galton-Watson branching processes, the method reconstructs growth, plasticity, drug-response mechanisms, and LGR5/KRT20 dynamics in colorectal cancer tumoroids from cell-state abundance data.

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Calibrated simulations for dynamic focusing of ultrasound through the temporal window

Focused ultrasound can target deep brain regions but predicted and delivered pressures often diverge. Dadgar-Kiani et al. introduce a practical calibration framework based on sparse measurements and optimized skull attenuation that reduces this mismatch, enabling safer personalized transcranial ultrasound.

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A sensitive method for profiling cell-type-specific secretomes of rare cells from complex tissues

Shipkovenska et al. present an improved method for profiling cell-type-specific secretomes in complex tissues without the use of viral vectors. The authors perform proof-of-principle validation by profiling the secretomes of two rare cell types with innate immune functions: liver Kupffer cells and airway microfold cells.

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A scalable microarrayed organoid platform for precision modeling of intestinal epithelial damage and recovery

Meyer et al. present a microarrayed human intestinal organoid platform for longitudinal, single-organoid analysis of cytokine-induced epithelial injury and recovery. The study introduces IORS to quantify epithelial restitution and applies the platform to benchmark bioactives that support barrier recovery under controlled inflammatory stress.

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Deep learning-driven multiplexed mycotoxin detection via color-size encoded microbead imaging

Lin et al. develop a color-size two-dimensional (2D)-encoded single-microbead imaging platform for the homogeneous analysis of four mycotoxins. By incorporating the YOLOv11 deep learning model to enable rapid data processing, the method offers a strategy for high-throughput food safety screening.

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Dye-cycling DNA origami rotors for long-term tracking of transcription at base-pair resolution

Wacker et al. present dcORBIT, a single-molecule fluorescence method based on DNA origami rotors that uses dye cycling to enable long-term measurement of DNA rotation at base-pair resolution. dcORBIT extends our toolkit to study molecular rotation and is here used to reveal molecular variability during transcription by E. coli RNAPs.

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Modeling microbiome modulation of tumor metabolic networks to predict synergistic therapies

Badenoch et al. develop a machine learning and metabolic modeling framework that predicts how gut microbes alter colorectal cancer drug response. The model identifies unintuitive drug-microbe synergies and their mechanisms, generalizing across microbial species and treatment modalities, including immunotherapy, to enable microbiome-informed combination therapy.

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AAV-DJ enables efficient, function-preserving neuronal transduction for circuit interrogation in human cortical and thalamic organoids

Adachi et al. systematically benchmark AAV capsids in human cortical and thalamic organoids by integrating gene delivery, cell type tropism, cytotoxicity, and neuronal function. By identifying AAV-DJ as a low-toxicity, function-preserving vector, this study offers a practical platform for imaging, manipulating, and tracing human neural circuits in vitro.

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SwitchClass distinguishes baseline- and perturbation-aligned features across intermediate molecular states

Xiao et al. present SwitchClass, a label-switch classification framework that scores whether molecular features in intermediate states align with baseline or perturbation. Across proteomic, phosphoproteomic, and single-cell transcriptomic datasets, SwitchClass reveals recovered and persistent molecular programs after cancer treatment, dietary reversal, and COVID-19.

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Mesenchymal stem cell-derived liver-on-a-chip reconstitutes human liver structure and function

Brooks et al. report a human MSC-derived liver-on-a-chip integrating endothelial cells, hepatocytes, and cholangiocytes from a single donor source. The platform reconstructs the sinusoidal, hepatic, and biliary compartments, supports hepatic uptake and biliary excretion, and models ischemic liver injury with therapeutic cell recruitment for personalized therapy and liver research.

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Strategic enhancement of Cas9 nickase-driven gene amplification

Takesue et al. enhance the nCas9-based gene amplification method BITREx through the development of (1) a plasmid reporter that predicts gRNA performance and (2) BITREx 2.0, a dual-nicking strategy that exploits synergistic interactions between two gRNAs. These advances broaden the utility of BITREx for gene amplification applications.

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Volumetric denoising enables high-throughput volume electron microscopy and efficient downstream analysis

Chen et al. determined the pivotal role of sufficient axial resolution in maintaining data quality of volume electron microscopy despite varying image signal-to-noise ratios and developed a volumetric denoising algorithm. Volumetric denoising enables finer serial block-face cutting and improves organelle and synapse segmentation accuracy.

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Targeting the peripheral nervous system in adipose tissue with engineered AAV vectors

Peripheral innervation of adipose tissue is essential for metabolic regulation, yet gene delivery tools remain underdeveloped. Willows et al. establish a framework for targeting AAV-mediated transgene delivery to nerve subtypes in adipose tissue with Cre drivers, offering a promising tool for mechanistic studies and laying a framework for future therapeutic strategies targeting neuropathic disorders.

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AAV-delivered TurboRFP enables streamlined tracing and analysis of corticospinal tract sprouting

Hernaiz-Llorens et al. establish an AAV1-hSyn-TurboRFP workflow for streamlined corticospinal tract sprouting analysis. The method enables direct visualization of fine CST axons without secondary immunostaining, supports combined tracing and genetic manipulation, and provides reproducible quantification of injury-induced corticospinal remodeling.

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Rapid and reversible regulation of cell cycle progression in budding yeast using optogenetics

Koutsoumpa et al. present OPTO-Cln2, an optogenetic system for light-controlled CLN2 expression in budding yeast based on an EL222-responsive promoter. In G1 cyclin mutant backgrounds, OPTO-Cln2 enables dynamic modulation of G1 progression and light-induced synchronization of cell populations.

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ATP-Red enables single-cell bioenergetic phenotyping by flow cytometry

Marin et al. evaluate ATP-Red as a simple flow-cytometry-based method for measuring ATP-associated bioenergetic states in single cells. The study shows that ATP-Red captures metabolic heterogeneity, immune cell activation, and mitochondrial dysfunction, providing a practical approach for single-cell metabolic profiling in complex biological systems.

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A xeno-free human iPSC-derived prostate organoid platform for multilineage differentiation and genetic manipulation

Shaikh et al. develop a defined, xeno-free, scaffold-free human iPSC-derived prostate organoid platform supporting epithelial and stromal differentiation. Organoids generated through monoculture or modular co-culture approaches enable compartment-specific genetic manipulation and recapitulate key features of prostate tissue organization, providing a reproducible platform for developmental and disease studies.

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Trajectory-informed gene feature selection in single-cell analysis with SEEK-VFI

Danning et al. introduce a feature selection method for single-cell expression analysis that combines statistical and ensemble learning techniques to identify genes that vary across the latent cellular trajectory. This preprocessing method improves downstream tasks including trajectory reconstruction, low-dimensional embedding, and pseudotime analysis.

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Fine-tuned large language models enhance influenza forecasting

Accurate influenza-like illness forecasting is essential for timely public health response but is often limited by scarce and privacy-sensitive surveillance data. Li et al. show that lightweight fine-tuning adapts pre-trained large language models to provide accurate and stable forecasts across diverse real-world surveillance datasets.

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Subtype-resolved norepinephrine imaging with an engineered α1D-adrenergic receptor indicator

Rohner et al. develop Alpha1DLight, an α1D-adrenergic receptor-derived fluorescent indicator that enables subtype-resolved norepinephrine imaging. The sensor shows high affinity, reversible responses, and α1D-like pharmacological sensitivity and reports norepinephrine dynamics across cells, brain slices, and behaving mice, enabling investigation of sustained noradrenergic engagement and drug effects.

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HIT-MAP: A scalable approach to multimodal mapping of subcellular organization

Understanding how proteins organize inside cells requires combining imaging and interaction data, yet doing so at scale remains technically demanding. Qian et al. present HIT-MAP, a streamlined pipeline that tags proteins at native genomic sites and acquires both modalities from one cell line, broadening access to multimodal cell mapping.

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Efficient generation of human cDC1-like cells to detect and enhance tumor-reactive T cells via CD4+ T cell help

Wang et al. describe a methodology to generate cDC1-like cells from hematopoietic progenitors in non-mobilized human blood. These cDC1-like cells can be licensed by activated CD4+ T cells to detect rare tumor-specific CD8+ T cells in blood and prime functional tumor-reactive cytotoxic T cells. This platform supports immune monitoring and cell therapies in cancer.

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A single-component optogenetic toolkit for reversible visualization and programmable control of microtubule dynamics

Lan et al. develop a single-component optogenetic toolkit that uses light to visualize, modify, transport along, and remodel microtubules in living cells. This modular platform links local cytoskeletal changes to organelle positioning and signaling, providing a flexible way to study how cell architecture controls function.

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Off-target effects of DREADD ligands revealed by an anesthesia emergence paradigm in mice

Moreno-Gomez et al. demonstrate that CNO, C21, and DCZ delay anesthesia emergence in mice. They show that subcutaneous administration mitigates CNO effects and provide an open-source deep learning pipeline to rigorously screen chemogenetic tools. Overall, they demonstrate that rigorous chemogenetic research requires mitigating off-target actions via careful dosing and DREADD-free controls.

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SpaDiff denoises sequence-based spatial transcriptomics via diffusion process

Sequence-based spatial transcriptomics suffers from spot-swapping, where RNA molecules drift to neighboring spots and blur tissue patterns. Cai et al. introduce SpaDiff, a diffusion-based denoiser that reverses this spreading along a learned spatial gradient. It sharpens tissue domains, preserves total molecular counts exactly, and recovers within-region heterogeneity that other methods erase.

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Benchmarking dynamic analysis methods in diffusion-based single-molecule FRET

Crossley benchmarks widely used dynamic analysis methods for diffusion-based smFRET using simulated datasets, clarifying the timescales, burst number requirements, and FRET state separation each approach demands. The results offer practical guidelines for selecting analysis strategies and accurately interpreting conformational dynamics in biomolecules.

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ABA-AA: A simple, reversible, and non-toxic anchor-away system for effective nuclear protein depletion

Esteban-Serna et al. describe an anchor-away system that uses the plant hormone abscisic acid (ABA) to rapidly deplete proteins from the nucleus in budding yeast. Unlike existing approaches, the system is inexpensive, non-toxic, fully reversible, and works across different genetic backgrounds, making it broadly applicable for studying dynamic cellular processes.

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GenART: Reading the genome’s language with adaptive “words”

Chen et al. develop GenART, a genomic language model that dynamically segments raw DNA into biologically meaningful “words.” This adaptive approach overcomes arbitrary sequence splitting, boosting predictive performance across diverse tasks while autonomously capturing functional genomic boundaries to enhance interpretability.

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Framework for evaluating in vitro vasculogenic mimicry using structural and metabolic parameters

Vasculogenic mimicry remains difficult to define because short-term Matrigel assays often overestimate network formation. Using cancer, trophoblast, murine, and patient-derived models, Santander et al. show that lumen-containing structures, not superficial networks, define bona fide VM and identify matrix and metabolic conditions regulating its formation.

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