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At least 19 recordsLinked to original sources

Unraveling cellular dynamic changes in tumor evolution induced by long-term low dose-rate radiation.

BACKGROUND: In recent years, there has been a steady increase in professionals engaged in radioactive work. The biological impacts of long-term exposure to low dose-rate radiation remain elusive, as there is a dearth of systematic research in this field. METHODS: BEAS-2B cells were used to establish a cell model with continuous passaging after radiation exposure, which was subsequently subjected to in vivo tumorigenesis assays and in vitro malignant phenotype experiments. By scRNA-seq, we conducted copy number variation analysis, cell trajectory analysis, and cell communication analysis. Furthermore, we used FACS, molecular docking, multiplex immunohistochemistry, qRT-PCR, and co-immunoprecipitation to validate and further explore the molecular mechanisms driving tumor evolution. RESULTS: Long-term low dose-rate exposure is associated with a higher degree of malignancy, as evidenced by the induction of more CNV and EMT events, as well as the delayed activation of DNA repair pathways, which trigger increased genomic instability. The long-term low dose-rate specific ligand-receptor pair, ANGPTL4-SDC4, enhances cell malignancy by promoting angiogenesis in newly formed lung tumor cells. CONCLUSIONS: This study not only provides the first evidence and mechanistic explanation that long-term low dose-rate radiation leads to increased cellular malignancy but also offers valuable theoretical insights into the dynamic processes of early tumor evolution in lung cancer within the realm of tumor biology.

Humans

Stable chloroform emissions in southeastern China: insights from recent observations.

Chloroform (CHCl3) is a short-lived ozone-depleting substance not currently regulated under the Montreal Protocol. Due to the unique meteorological conditions in East Asia, CHCl3 emitted in this region has a greater potential to reach the stratosphere and contribute to ozone depletion. As an essential component of national CHCl3 emissions, southeastern China has attracted increasing attention. However, long-term observational data in this region remain relatively scarce, with no updates since 2020. In this study, we continuously measured atmospheric CHCl3 concentrations at a remote monitoring station in southeastern China from 1 June 2023 to 31 May 2025. Frequent concentration enhancements were observed during the monitoring period, with mixing ratios ranging from 9.3 to 134.1 ppt and an average value of 36.8 ± 19.7 ppt. Back-trajectory analysis indicated that air masses associated with elevated CHCl3 levels primarily originated from coastal industrial provinces in eastern China. Using the Potential Source Contribution Function and Concentration Weighted Trajectory methods, we identified the Yangtze River Delta (Jiangsu, Anhui, and Zhejiang Provinces) and Jiangxi Province as dominant source regions. Emissions of CHCl3 in southeastern China were estimated using the Tracer Ratio Method to be approximately 30.1 ± 5.3 Gg/yr from 2023-06-01 to 2025-05-31, indicating overall stability relative to earlier estimates and no apparent upward trend. These findings provide updated insights into the current status of CHCl3 emissions in southeastern China and highlight the need for continued monitoring and emission assessment of CHCl3 in East Asia, given its unregulated status and implications for ozone layer recovery.

Air Pollutants

Ascites reprograms innate lymphoid immune cells in ovarian cancer by promoting ILC2 enrichment and dysfunctional NK-cell states.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is commonly accompanied by malignant ascites, a clinically relevant tumor niche that promotes immune evasion, metastasis, and treatment resistance. Although natural killer (NK)-cell dysfunction has been described in ovarian cancer, the broader innate lymphoid landscape of ascites and the mechanisms linking ascites-derived signals to innate immune suppression remain insufficiently resolved. METHODS: We performed single-cell RNA sequencing of NK/innate lymphoid cells from ovarian cancer ascites to define cellular heterogeneity and differentiation states. Functional assays assessed NK-cell cytotoxicity, degranulation, and receptor expression following exposure to patient-derived ascites, with or without transforming growth factor-β (TGF-β) receptor inhibition. Proteomic profiling was used to characterize the soluble ascites milieu, and clinical associations were examined for innate lymphoid subsets. RESULTS: Single-cell analysis identified eight transcriptionally distinct NK/innate lymphoid states, including cytotoxic, precursor, early-like, tolerant/immunoregulatory, regulatory, proinflammatory, and innate lymphoid populations. Ovarian cancer ascites was characterized by depletion of cytotoxic and precursor NK-cell states together with enrichment of early-like, tolerant, regulatory, pro-inflammatory, and innate lymphoid cell (ILC) populations. Trajectory analysis indicated impaired maturation toward terminally differentiated cytotoxic NK cells. Notably, ascites contained an expanded population of programmed cell death protein 1 (PD-1)+ ILC2s, which were more abundant in patients with shorter progression-free survival. In functional assays, short-term exposure of healthy donor NK cells to ascites suppressed degranulation and tumor-cell killing, reduced expression of activating receptors including NKp30 and DNAM-1, increased inhibitory receptor expression, and shifted NK cells toward a CD56highCD16low phenotype. Proteomic profiling supported a soluble milieu consistent with type 2 immune skewing and NK-cell suppression. Importantly, TGF-β receptor inhibition partially restored NK-cell activation and function in the presence of ascites. CONCLUSIONS: HGSOC ascites establishes a type 2-skewed immunoregulatory niche that coordinately drives NK cell dysfunction and PD-1+ ILC2 accumulation. The findings identify TGF-β-linked suppression and ascites-associated immune regulators as candidate immunotherapeutic vulnerabilities for restoring antitumor immunity in ovarian cancer.

Humans

Contact hypersensitivity promotes hair regeneration through SPP1-secreting macrophages.

Allergic contact dermatitis, or contact hypersensitivity (CHS), is a pathological adaptive immune response that paradoxically induces hair regeneration, yet its underlying mechanisms remain unclear. We integrated high-resolution spatial transcriptomics and single-cell RNA sequencing to map the intricate interactions between immune cells, stroma, and hair follicles during CHS-induced hair growth in mice. Among all immunocytes, macrophages underwent the most prominent compositional and functional remodeling. We resolved five transcriptionally distinct macrophage subsets, with contact hypersensitivity driving a shift from homeostatic antigen-presenting cells toward a pro-inflammatory CD14+SPP1+ population. Trajectory analysis revealed divergent differentiation paths under homeostatic versus allergic conditions, highlighting the plasticity of skin macrophages. Mechanistically, CD14+SPP1+ macrophages secreted SPP1 (osteopontin), which engaged CD44 on hair follicle stem cells to activate PI3K-AKT signaling and trigger their proliferation. Notably, canonical pro-inflammatory cytokine signaling through TNF-α and IL-1 was dispensable for this process, underscoring the specificity of the SPP1-CD44 axis in immune-mediated hair regeneration. These findings reveal a macrophage-dependent mechanism of immune-mediated hair regeneration, offering therapeutic insights into immune-stem cell crosstalk.

Journal Article

Beta cell-derived cholecystokinin drives obesity-associated pancreatic adenocarcinoma development.

Pancreatic endocrine-exocrine crosstalk plays a key role in normal physiology and disease and can be altered by host metabolic states, such as obesity. Classically, endocrine islet beta (β) cell secretion of insulin is thought to promote the development of obesity-associated pancreatic adenocarcinoma (PDAC), an exocrine cell-derived tumor. Here, we show that β cell expression of the peptide hormone cholecystokinin (CCK) is necessary and sufficient for obesity-associated PDAC progression in mice and that CCK expression - rather than insulin - correlates strongly with enhanced tumorigenesis. Single-cell RNA-sequencing, in silico latent-space archetypal and trajectory analysis, and experimental lineage tracing in vivo reveal that obesity induces the expansion of postnatal immature β cells, which adapt to express CCK via stress-responsive JNK/cJun signaling. Finally, obesity perturbs CCK-dependent peri-islet exocrine cell transcriptional states and enhances islet-proximal tumor formation. These results define endocrine-exocrine CCK signaling as a bona fide driver of obesity-associated PDAC development and uncover avenues to target the endocrine pancreas to subvert exocrine tumorigenesis.

Animals

Cell-body curvature reduces stall frequency to enhance Vibrio cholerae swimming and chemotaxis through hydrogels.

The swimming motility of the bacterial pathogen Vibrio cholerae is a virulence factor that aids in breaching the mucus layer. V. cholerae has a curved cell shape, and previous work demonstrated that loss of curvature decreases infectivity. Here, we investigate the mechanism by which curvature affects single-cell motility. We compared the chemotactic performance of wild-type curved cells and straight mutants. The two exhibit similar swimming properties in liquid and viscous solutions but differ significantly in mucus-mimicking hydrogels, where curved cells demonstrate an 86% increase in chemotactic drift. Trajectory analysis indicates comparable swimming speeds, but straight mutants experience more frequent stalls, reducing total swimming time. Stalls further reduce chemotactic performance by imposing an average reorientation down the chemical gradient, regardless of cell shape. Coarse-grained molecular dynamics simulations corroborate these results across intestinal mucus hydrogel stiffnesses and identify an optimal curvature for movement through hydrogel-like meshes, close to the pathogen's median curvature. These findings highlight cell shape's role in pathogenicity and the need to study bacterial behaviors under conditions more closely mimicking the host environment.

Vibrio cholerae

Conversion of SO2 to sulfur particulate in the Los Angeles atmosphere.

Gas phase and particular phase sulfur have been measured at various locations in the Los Angeles basin to determine atmospheric conversion rates and mechanisms. A new technique was developed for the measurement of particulate sulfur. From measurements of the particulate to gas phase sulfur ratio near the major stationary sources and far downstream and from estimates of travel time determined by air trajectory analysis, it is possible to estimate gas-to-particle conversion rates for sulfur. Such calculations show that automobiles presently contribute a major part of the total sulfur as measured at a receptor site such as Pasadena, while contributing only a small amount to the particulate sulfur loading. The introduction of oxidation catalyst-equipped vehicles may add significantly to the particulate sulfur at downwind receptor sites; predictions of particulate sulfur concentrations near freeways show substantial increases due to such vehicles.

Aerosols

Temperature dependence on the passive and dynamic electrical parameters of muscle cells.

Measurements of the temperature dependence in the range from 10 C to 30 C on the passive and dynamic electrical properties of single frog muscle cell following Arrhenius relation have been made. The propagated responses (V-t) and conduction velocity theta were analyzed following the H-H propagated cable equation. The ionic current-membrane potential relationship (I-t) was calculated from the phase-plane trajectory analysis (V-V) of the action potential curve (V-t). All the rate and time constants of the excitation and propagation processes kr, kNa, kK, tau Na, tau K, the negative conductance (-gNa) and the ionic conductances gNa, gK, influencing the evolution of the curves (V-t), (V-V) and (I-V) are correlated. The magnitudes of the resting (Vr) and action potential amplitude (Vs), the excitation potential (V*), the negative after potential (Vn), and the sodium equilibrium potential (VNa); the magnitudes of the maximum rate of rise and fall of the spike (V+) and (V-) and those corresponding to the inward INa and outward IK ionic currents, were analyzed. Two general classes of findings were obtained. One group of action potential parameters theta, V+, V-, Vn, kr, kNa, kK, tau Na, tau K, -gNa, gNa, gK, INa and IK is strongly temperature dependent with Q 10 S approximately 2 and energy of activation E approximately 10 kcal/mole. The other group of parameters, Gm (passive conductance), Cm (capacitance), tau, Vr, V*, Vs, and VNa are slightly temperature dependent, with Q10's lower than 1.4. This study contributes deeply to the analysis of temperature effects on the electrical cell responses to adequate stimuli. This temperature dependence analysis was designed to detect possible "masked" actions of microwave radiation on cell membrane functions.

Action Potentials

Early-childhood temperament trajectories map onto transdiagnostic psychiatric risk.

Early-childhood temperament is associated with later mental health. Temperament continues to develop throughout the first years of life, and a single assessment cannot capture its trajectory. Whether departures from an individual's developmental trajectory carry psychiatric risk remains unknown. Using data from more than 50,000 children in the Norwegian Mother, Father and Child Cohort Study, we modeled longitudinal temperament at 1.5, 3, and 5 years of age with the FEMA-Long mixed-effects framework. We then quantified each child's departures from their predicted trajectories. Multivariate analysis revealed two transdiagnostic dimensions linking trajectory departures to psychiatric diagnoses across childhood and adolescence. Higher scores on the first dimension were associated with an increased hazard of subsequent ADHD diagnosis (hazard ratio = 1.54), and higher scores on the second with an increased hazard of Asperger syndrome (hazard ratio = 1.64). To examine the genetic basis of these associations, we performed longitudinal GWAS of temperament and conjunctional FDR analysis to detect loci shared with the associated diagnoses. The effects of these loci changed across early childhood, with some strengthening and others attenuating with age. These findings show that departures from predicted temperament trajectories reflect transdiagnostic psychiatric risk with a shared genetic basis. Longitudinal, trajectory-based monitoring could help identify children at elevated psychiatric risk.

Journal Article

Spectral-Proteomic Integration Analysis (SPIA) Deciphers Molecular Trajectories of Breast Cancer and Enables Multitarget Therapeutic Assessment.

Raman spectroscopy and mass spectrometry-based proteomics offer deeply complementary yet largely disconnected views of cancer biology: the former provides a label-free, real-time biochemical phenotype, while the latter delivers a quantitative inventory of specific protein effectors. Bridging this gap remains a fundamental challenge in analytical biomedicine. Here, we introduce Spectral-Proteomic Integration Analysis (SPIA)─a novel, data-driven integrative framework that systematically links Raman spectroscopic phenotypes with quantitative proteomic profiles through machine learning and statistical correlation. Using a DMBA-induced rat breast cancer model with and without Toremifene (TOR) intervention, SPIA dynamically maps tumor microenvironment remodeling, capturing progressive collagen deposition and lipid metabolic reprogramming. An SVM classifier trained on Raman spectra achieves exceptional diagnostic accuracy (AUC ≥ 99.0%) and successfully predicts TOR therapeutic response. Proteomic analysis identifies 1,350 differentially expressed proteins, with convergent machine learning feature selection (LASSO, Random Forest, XGBoost) pinpointing core regulators including Luc7l2, Nucb1, Cbx3, and Csnk2a1. Crucially, Spearman correlation analysis between key Raman bands and core DEPs reveals strong, statistically robust associations (median ρ ∼ 0.75 in the 1533-1669 cm-1 region), empirically validating SPIA's core integrative logic. Leveraging this multimodal map, we elucidate a multitarget mechanism for TOR involving concurrent suppression of collagen deposition and correction of aberrant lipid metabolism. SPIA establishes a powerful, generalizable paradigm for integrating phenotypic and molecular data, with broad implications for biomarker discovery, drug mechanism elucidation, and precision oncology.

Animals

Identification of Drug-resistant Cell Subpopulations in Colorectal Cancer Through Single-cell Analysis and Exploration of Potential Therapeutic Strategies.

INTRODUCTION: The therapeutic efficacy of Colorectal Cancer (CRC) is often compromised by resistance to the standard chemotherapy agent oxaliplatin. METHODS: This study obtained single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database. Differentially Expressed Genes (DEGs) between resistant and sensitive epithelial subpopulations were identified, followed by enrichment analysis. Pseudotemporal trajectory and cell-cell communication were analyzed using Monocle2 and CellChat, respectively. The candidate drug was predicted by Connectivity Map (cMAP) analysis. External validation included assessment of the EpC2 signature in an oxaliplatin-resistant cell line dataset (GSE76092), survival analysis using The Cancer Genome Atlas (TCGA) cohorts, and re-analysis of the GSE179784 dataset to assess the reproducibility of EpC2-like subpopulations and their DNA Damage Repair (DDR) scores. RESULTS: Cell subpopulations were divided into 10 clusters. Among them, epithelial cells comprised 5 subpopulations, with EPC2 identified as a potential oxaliplatin-resistant subset. DEGs were enriched in the TNF and IL-17 pathways. External validation confirmed the enrichment of EpC2 in resistant cell lines and its association with poor survival. Pseudotemporal trajectory revealed that epithelial cells underwent state transitions, forming two distinct branches. The resistant group exhibited enrichment in RNA splicing and NF-κB pathways. Cell-cell communication analysis revealed interactions involving MDK- NCL and PPIA-BSG. Dasatinib was predicted as a candidate drug. DISCUSSION: We identified an oxaliplatin-resistant subpopulation of Epithelial Cells (EpC2) in CRC, elucidated its multi-layered resistance mechanisms, and integrated multi- omics and cMAP database analyses to predict a potential intervention drug. CONCLUSION: This study provided potential therapeutic possibilities for oxaliplatin resistance, contributing to CRC treatment.

Humans

Deep learning-assisted, pathogenesis-informed lung histopathology scoring in preclinical mouse models of SARS-CoV-2 and influenza A infection.

INTRODUCTION: SARS-CoV-2 and influenza A virus (IAV) cause viral pneumonia, yet their lung lesions evolve with distinct spatial organization and resolution-phase architecture. In preclinical murine studies, H&E histopathology is a primary endpoint, but burden-focused semiquantitative scoring can miss pathogen- and phase-specific differences in lesion topology, compartmental involvement, inflammatory organization, and repair. We aimed to define virus- and phase-specific morphologic signatures and translate them into a practical, pathogenesis-informed scoring guide, supported by whole-slide convolutional neural network (CNN) analysis with class activation mapping (CAM). METHODS: Mice were infected under standardized conditions and evaluated during the early, peak-injury, and late phases of infection, corresponding to 2~3, 5~8, and 14 days post-infection (dpi), respectively. Lungs were assessed by H&E with semiquantitative scoring and by immunostaining to map viral antigen distribution and epithelial tropism. Whole-slide CNN models were trained for virus- and phase-specific classification, and CAM localized discriminative regions. RESULTS: Dose titration established reproducible lethal and sublethal infection conditions for both viruses. Viral antigen kinetics diverged, with SARS-CoV-2 peaking early and declining toward clearance by the resolution phase, whereas IAV peaked later and declined by the resolution phase, paralleling distinct injury-repair trajectories. CNN/CAM analysis distinguished virus- and phase-specific histologic patterns across the early, peak-injury, and resolution phases of infection and highlighted spatial signatures consistent with expert review. At the peak-injury phase, SARS-CoV-2 lungs showed broad alveolar/interstitial involvement, whereas IAV exhibited bronchocentric inflammatory organization. During the resolution phase, IAV showed prominent epithelial regeneration with remodeling-forward architecture, while SARS-CoV-2 more often retained localized residual inflammatory foci. Across both infections, tissue inflammatory composition shifted over time, with higher neutrophil representation during the peak-injury phase and a relative increase in lymphocytic representation during the resolution phase. Integrating lesion topology/distribution, edema, epithelial injury-regeneration, remodeling features, and lymphocyte predominance, we proposed a pathogen-resolved, phase-informed histopathology scoring guide with recommended evaluation windows for each model. CONCLUSION: Together, these findings define virus- and phase-specific morphologic programs that inform respiratory virus pathogenesis in mice and can be translated into practical scoring criteria for preclinical respiratory virus studies.

Animals

Early-stage trajectories of social-occupational functioning and long-term functional outcome prediction in early psychosis: A 12-year follow-up of the randomized controlled trial on extended early intervention.

BACKGROUND: Functional impairment in psychosis often persists despite symptomatic remission. There is a paucity of research examining early-course psychosocial functioning trajectories, and none has been conducted to examine relationship between the trajectories and prospective long-term functional outcomes in early psychosis sample. METHODS: We conducted 12-year follow-up of a randomized controlled trial on extended early intervention for first-episode psychosis to identify early-course social-occupational functioning trajectories and their baseline predictors and associations with 12-year outcomes. Participants who completed Social and Occupational Functioning Scale (SOFAS) scores at three or more timepoints between baseline and 3-year follow-up were included in the study. Premorbid adjustment, illness characteristics, symptom severity, functioning, and treatment profiles were assessed. Latent growth mixture modeling was employed to derive early-course social-occupational functioning trajectories based on SOFAS scores over 3-year follow-up. RESULTS: A total of 148 participants were included in this study, with 106 patients having completed the 12-year follow-up. Our results identified four distinct trajectories, including persistently-good class, gradually-improved class, suboptimal-stable class, and persistently-poor class. Patients in persistently-poor class had more severe negative symptoms at baseline compared to patients in persistently-good class. Patients with persistently-poor trajectory had worse long-term outcomes than those with other classes in the majority of functional measures at 12-year follow-up. CONCLUSIONS: The majority of patients were classified in early-stage suboptimal or poor functional trajectories. Above one-fourth of the participants exhibited persistently-poor social-occupational functioning trajectory, which predicted worse functional outcomes at 12-year follow-up. These findings highlighted the importance of tracking functional changes during the initial years of illness.

Humans

Inferring cell trajectories of spatial transcriptomics via optimal transport analysis.

The integration of cell transcriptomics and spatial position to organize differentiation trajectories remains a challenge. Here, we introduce SpaTrack, which leverages optimal transport to reconcile both gene expression and spatial position from spatial transcriptomics into the transition costs, thereby reconstructing cell differentiation. SpaTrack can construct detailed spatial trajectories that reflect the differentiation topology and trace cell dynamics across multiple samples over temporal intervals. To capture the dynamic drivers of differentiation, SpaTrack models cell fate as a function of expression profiles influenced by transcription factors over time. By applying SpaTrack, we successfully disentangle spatiotemporal trajectories of axolotl telencephalon regeneration and mouse midbrain development. Diverse malignant lineages expanding within a primary tumor are uncovered. One lineage, characterized by upregulated epithelial mesenchymal transition, implants at the metastatic site and subsequently colonizes to form a secondary tumor. Overall, SpaTrack efficiently advances trajectory inference from spatial transcriptomics, providing valuable insights into differentiation processes.

Animals

The cost and cost trajectory of genome sequencing and bioinformatics analysis for Indigenous children with suspected rare diseases.

PURPOSE: Indigenous peoples are underrepresented in reference genome libraries. Consequently, rare disease diagnosis may require bespoke bioinformatics analyses of genome sequences. Establishing diagnostic cost is crucial to support policy development for equitable diagnosis of rare diseases. We estimated the cost and cost trajectory of diagnostic genome sequencing and bioinformatics for Indigenous participants with suspected rare diseases. METHODS: We conducted a microcosting study of Indigenous children and their families receiving genome sequencing through Canada's Silent Genomes Project. Invoice data informed the costs of genome sequencing. We conducted a time-and-motion study for bioinformatics analyses, including labor, computing, and data storage costs. RESULTS: With standard bioinformatics, costs ranged from C$3645 (SD: 455) for singletons to C$7402 (SD: 566) for trios. With advanced, bespoke bioinformatics, costs ranged from C$5344 (SD: 634) for singletons to C$9760 (SD: 822) for trios. Genome sequencing was a primary cost driver; however, sequencing costs decreased by 61% over 4 years. Bioinformatics costs ranged from 21.3% to 58.3% of the total costs. The time required for bioinformatics ranged from 71 hours to 215 hours for standard and advanced analyses, respectively. CONCLUSION: Genome sequencing costs decreased over time. Bioinformatics is a significant cost driver, particularly for bespoke analyses arising from nonrepresentative reference libraries.

Humans

Dandelion uses the single-cell adaptive immune receptor repertoire to explore lymphocyte developmental origins.

Assessment of single-cell gene expression (single-cell RNA sequencing) and adaptive immune receptor (AIR) sequencing (scVDJ-seq) has been invaluable in studying lymphocyte biology. Here we introduce Dandelion, a computational pipeline for scVDJ-seq analysis. It enables the application of standard V(D)J analysis workflows to single-cell datasets, delivering improved V(D)J contig annotation and the identification of nonproductive and partially spliced contigs. We devised a strategy to create an AIR feature space that can be used for both differential V(D)J usage analysis and pseudotime trajectory inference. The application of Dandelion improved the alignment of human thymic development trajectories of double-positive T cells to mature single-positive CD4/CD8 T cells, generating predictions of factors regulating lineage commitment. Dandelion analysis of other cell compartments provided insights into the origins of human B1 cells and ILC/NK cell development, illustrating the power of our approach. Dandelion is available at https://www.github.com/zktuong/dandelion .

Humans

Seawater immersion reshapes the temporal dynamics of traumatic brain injury and reveals mitochondrial oxidative stress as a modifiable therapeutic target.

Traumatic brain injury (TBI) evolves through time-dependent secondary injury, but whether seawater (SW) immersion merely amplifies pathology or reshapes the temporal trajectory of post-traumatic biology remains unclear. Here, we applied time-resolved proteomics to mouse brains after controlled cortical impact (CCI) with or without artificial SW immersion at 1, 3, 7, and 28 days post-injury. Trajectory-based proteomic analysis revealed that SW immersion altered the direction, magnitude, timing, persistence, and recovery of protein responses, rather than simply intensifying TBI-induced changes. This remodeled trajectory exhibited phase-specific patterns, including SW-dominant, synergistically enhanced, and attenuated responses, highlighting mitochondrial oxidative stress, inflammatory activation, complement/coagulation disturbance, and impaired structural repair. Phenotypic validation confirmed phase-specific deficits, including acute inflammatory-redox injury, impaired neuronal survival, chronic axon-myelin disruption, and incomplete behavioral recovery. SS-31 partially mitigated selected inflammatory, redox, neuronal, and white matter abnormalities, supporting mitochondrial oxidative stress as a modifiable node rather than the sole driver of trajectory remodeling. These findings identify seawater immersion as a temporal modifier of secondary injury and emphasize that environmental trauma may require trajectory-informed, phase-specific therapeutic interventions.

Animals

Single-cell analysis of the human retina reveals stage-linked microglial states and neural-immune circuit rewiring in diabetic retinopathy.

Diabetic retinopathy (DR) is a major cause of vision loss worldwide. Here, we conduct single-cell RNA sequencing of twenty human retina samples (from living and post-mortem donors) across non-diabetic, diabetic, and DR states to create a comprehensive transcriptomic atlas. We identify two stable microglial populations-homeostatic and inflammatory-that exist along a functional continuum, plus a neutrophil cluster within C1QA+ myeloid cells with dynamic transitions occurring throughout disease progression. Module-level analysis reveals divergent transcriptional trajectories: homeostatic microglia maintain energetic programs while selectively upregulating stress elements, whereas inflammatory microglia layer additional pro-inflammatory programs onto preserved biosynthetic foundations. Eleven co-expression modules organize into two major axes: an inflammatory-stress axis, and a regulatory/metabolic-motility axis, with a stable translation module persisting across disease stages. Cell communication analysis further highlights sophisticated neural-immune interactions, particularly between photoreceptors and microglia. Our findings provide insights into the complex cellular dynamics of DR progression and suggest potential therapeutic targets for early intervention.

Humans