Methods: Our study applied spatio-temporal enhanced resolution omics-sequencing (Stereo-seq) to investigate the interactions between fibroblasts and lung cancer cells. A co-culture system of A549 lung cancer cells and HFL1 fibroblasts was established to validate the functional roles of identified fibroblast subtypes. Gene knockdown, proliferation, migration, invasion, and ELISA assays were conducted to investigate underlying mechanisms.

Results: Spatial transcriptomics revealed significant heterogeneity in LUAD tissues, with identification of a novel fibroblast cluster (C0) characterized by high expression of POSTN, THY1, BGN, and COL1A1, which co-localized with malignant epithelial cells (C5) in high-malignancy regions. Public dataset analysis confirmed C0 as CAFs, enriched in LUAD and associated with poor prognosis. Ligand-receptor analysis highlighted collagen I- and fibronectin 1-mediated interactions between C0 and C5. In vitro, co-culture with A549 induced differentiation of HFL1 into CAFs, with upregulation of COL1A1, COL1A2, and CAF markers. Knockdown of COL1A1 or COL1A2 in fibroblasts significantly reduced collagen I secretion and attenuated cancer cell proliferation, migration, and invasion, while exerting minimal effects on angiogenesis.

Conclusions: These findings not only provide a molecular map of lung cancer tissues for further study but also illustrate a novel co-location relationship between fibroblasts and cancer cells within the TME. Our results highlight the potential of CAFs as a promising therapeutic target, complementing existing approaches targeting genetic mutations and immune cells.

Background: Long non-coding RNAs (lncRNAs) are key regulators of gene expression and emerging evidence implicates their dysregulation in the pathogenesis of gestational diabetes mellitus (GDM), a common metabolic disorder threatening maternal and foetal health. This review explores how lncRNAs are involved in GDM.

Methods: A comprehensive literature search was performed in the PubMed database using combinations of keywords “lncRNA”, “long non-coding RNA”, “gestational diabetes mellitus”, and “GDM”. Relevant English original articles were screened, and non-relevant studies were excluded.

Results: In GDM, several lncRNAs including MALAT1, MEG8, and SOX2OT are upregulated, while HCG27, GAS5, and PAX-AS1 are downregulated. These dysregulated lncRNAs play mechanistic roles in regulating trophoblast proliferation, insulin signaling, neonatal and offspring health, and other GDM-related complications. Such alterations were associated with dysregulation of IGF-1, PI3K/Akt, MAPK, miRNAs, and other signaling pathways.

Conclusion: LncRNAs regulate key pathways involved in insulin resistance, placental dysfunction, and inflammation in GDM. Dysregulated lncRNAs are promising biomarkers and therapeutic targets. Future multi-center and mechanistic studies are needed to enable precision medicine for GDM.

Background: Triggering receptor expressed on myeloid cells 2 (TREM2) is a microglia-enriched surface receptor that plays a central role in sensing lipid ligands and damage-associated molecular patterns within the central nervous system. Growing evidence has expanded our understanding of TREM2 in both physiological homeostasis and a broad range of neurological disorders, and has further identified TREM2 as a promising therapeutic target.

Objective: This review aims to provide an updated overview of TREM2 signaling in microglial physiology and pathology, and to summarize the therapeutic potential of TREM2-targeted interventions across neurological diseases.

Methods: A narrative synthesis of recent literature was performed to examine TREM2 signaling, its context-dependent functions in both physiological and pathological states, and emerging advances in TREM2-targeted therapeutic strategies for neurological disorders.

Key Findings: Under physiological conditions, TREM2 maintains microglial survival, homeostatic surveillance, and synaptic pruning. In pathological contexts, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, stroke, and glioblastoma, TREM2 signaling regulates microglial activation, promotes the clearance of pathological substrates, and shapes neuroinflammatory responses.

Conclusions: TREM2-mediated microglial responses are highly context dependent and may exert distinct or even opposing functions across different disease types. A major challenge for future research is to tailor TREM2-based interventions to the specific disease context, timing, and microenvironment in order to maximize their neuroprotective and immunomodulatory effects.

Influenza A virus (IAV) infection is a significant risk factor for invasive pulmonary aspergillosis, particularly in severe influenza patients, where the incidence and mortality of influenza-associated pulmonary aspergillosis (IAPA) are markedly elevated. IAPA creates a state of acute acquired immunodeficiency in patients who were previously healthy, challenging the traditional view of fungal disease as a condition restricted to the classically immunocompromised. Drawing on emerging evidence, this review maps out the pathogenesis of IAPA as a specific, sequential cascade of host failure. The process begins with barrier disruption, where the virus induces Type III interferons and interleukin-1β (IL-1β) signalling to arrest epithelial repair and compromise tissue integrity. This is followed by recognition failure, characterized by the specific depletion of innate B1a lymphocytes and natural IgG antibodies, rendering fungal spores undetectable to phagocytes. The final stage is effector paralysis, where a cytokine storm drives neutrophil oxidative shutdown and transcriptional suppression. Ultimately, IAPA is a disorder of functional dissociation: The body is hyper-inflamed, yet its antimicrobial metabolism is paralysed. Understanding this framework reveals precise therapeutic windows for host-directed interventions, such as timed IL-1 receptor blockade or nebulized immunostimulants, which can restore immune competence and improve clinical outcomes.

Background: DNA damage-regulated autophagy modulator 1 (DRAM1) is a lysosomal protein involved in autophagy regulation, yet its comprehensive role across human cancers, particularly within the TIME, remains systematically uncharacterized.

Methods: We performed an integrated pan-cancer analysis of DRAM1 across 33 malignancies using multi-omics data from TCGA, GTEx, and other platforms. Our approach included expression profiling, survival analysis, genomic and epigenetic characterization, functional enrichment, immune infiltration assessment, and therapy response prediction. The DRAM1-JAK-STAT axis was experimentally validated by DRAM1 knockdown in A549 cells, and STAT3 phosphorylation was assessed by Western blot.

Results: DRAM1 demonstrated pervasive dysregulation across cancers with strong context-dependent prognostic significance, serving as a favourable factor in UCEC (HR = 0.34) but unfavourable in PDAC (HR = 1.90). We confirmed DRAM1’s central positioning within autophagy networks and discovered its significant association with an immunosuppressive axis connecting IFN-γ signalling, JAK-STAT activation, and Tregs recruitment, supported by strong correlations with IFNG (ρ = 0.742 in DLBC), JAK1, STAT3, and Tregs markers (FOXP3 and CTLA4). These correlations were experimentally supported by demonstrating that DRAM1 knockdown in A549 cells attenuated STAT3 phosphorylation. DRAM1 expression correlated with multiple immune checkpoint molecules and predicted resistance to several chemotherapeutic agents. Importantly, DRAM1 showed significant predictive value for immunotherapy response across multiple cohorts, with an AUC of 0.742 in gastric cancer.

Conclusion: Our study suggests DRAM1 as a context-dependent regulator of the tumour immune microenvironment, with associations involving an IFN-γ/JAK-STAT/Tregs immunosuppressive axis. These findings nominate DRAM1 as a promising biomarker for immunotherapy response prediction and suggest its potential as a target for combination immunotherapy strategies.

Thoracic aortic aneurysm (TAA) is a life-threatening cardiovascular disorder characterized by progressive aortic dilation that often culminates in dissection or rupture, with few effective pharmacological interventions currently available. Vascular smooth muscle cells (VSMCs)-the predominant cellular component of the aortic media-undergo extensive phenotypic modulation during TAA development. However, the heterogeneity of VSMC populations and the molecular mechanisms regulating their fate decisions remained poorly understood until the emergence of single-cell technologies. Single-cell RNA sequencing, single-nucleus assay for transposase-accessible chromatin sequencing, and spatial transcriptomics have revolutionized the understanding of VSMC diversity at an unprecedented resolution. These approaches have revealed a complex spectrum of VSMC phenotypic states that extend beyond the classical contractile–synthetic dichotomy, including fibroblast-like, macrophage-like, and chondrocyte-like subpopulations that arise through distinct differentiation trajectories. This review systematically summarizes recent progress in elucidating VSMC phenotypic switching in TAA, emphasizing developmental trajectories reconstructed through pseudotime analyses, the gene regulatory networks controlling fate decisions, and the spatial microenvironmental cues influencing VSMC behaviour. Furthermore, it discusses the translational implications of these insights for identifying novel diagnostic biomarkers and developing therapeutic strategies aimed at stabilizing VSMC phenotypes.

Background and aims: Reproducible external benchmarks for pneumothorax-related lung ultrasound (LUS) AI are scarce, and binary lung-sliding classification may obscure clinically important signs. We therefore developed a manifest-based external benchmark and used it to test both cross-domain generalisation and task validity.

Methods: We curated 280 clips from 190 publicly accessible LUS source videos and released a reconstruction manifest containing URLs, timestamps, crop coordinates, labels, and probe shape. Labels were normal lung sliding, absent lung sliding, lung point, and lung pulse. A previously published single-site binary classifier was evaluated on this benchmark; challenge-state analysis examined lung point and lung pulse using the predicted probability of absent sliding, P(absent).

Results: The single-site comparator achieved Receiver Operating Characteristic–Area Under the Curve (ROC-AUC) 0.9625 in-domain but 0.7050 on the heterogeneous external benchmark; restricting external evaluation to linear clips still yielded ROC-AUC 0.7212. In challenge-state analysis, mean P(absent) ranked absent (0.504) > lung point (0.313) > normal (0.186) > lung pulse (0.143). Lung pulse differed from absent clips (p = 0.000470) but not from normal clips (p = 0.813), indicating that the binary model treated pulse as normal-like despite absent sliding. Lung point differed from both absent (p = 0.000468) and normal (p = 0.000026), supporting its interpretation as an intermediate ambiguity state rather than a clean binary class.

Conclusion: A manifest-based, multi-source benchmark can support reproducible external evaluation without redistributing source videos. Binary lung-sliding classification is an incomplete proxy for pneumothorax reasoning because it obscures blind-spot and ambiguity states, such as lung pulse and lung point.

Background: Urinary proteins could be useful as noninvasive biomarkers for the detection of oesophageal squamous cell carcinoma (ESCC). We assessed the levels of secreted phosphoprotein 1 (SPP1) in urine samples from patients with ESCC and evaluated its potential as a diagnostic biomarker.

Methods: Urinary SPP1 levels were measured in 29 ESCC patients and 30 healthy controls using an enzyme-linked immunosorbent assay. SPP1 expression was subsequently examined in tumour tissues and paired peritumoural normal tissue from the patients via immunohistochemistry. The diagnostic performance of SPP1 for ESCC was evaluated using receiver operating characteristic curve analysis.

Results: Urinary SPP1 levels were significantly higher in the ESCC group than in the control group. This parameter demonstrated discriminatory power between the groups, with an area under the curve of 0.7. Furthermore, immunohistochemical analysis confirmed that SPP1 expression was markedly upregulated in ESCC tissues compared with that in paired normal tissues. Moreover, subgroup analysis revealed that urinary SPP1 also effectively identified patients with stage III ESCC.

Conclusion: Our study suggests that urinary SPP1 may serve as a novel biomarker for the detection of ESCC.

Background: Nanorobotic systems represent an emerging and disruptive paradigm in nanomedicine for precision drug delivery, controlled therapeutic release, and minimally invasive biomedical interventions. Recent advances in materials engineering, bioinspired design, and external actuation techniques have greatly improved the functionality, navigation, and targeting capabilities of nanorobots for biomedical applications in recent years.

Objectives: This review aims to give a comprehensive overview of the major classes of nanorobotic systems, their propulsion mechanisms, biomedical applications, safety considerations, and translational potential in drug delivery and therapeutic interventions.

Methods: A critical review of recent literature was carried out to evaluate various nanorobotic platforms including DNA-based, magnetic, catalytic, biohybrid, ultrasound-driven, light-responsive and stimuli-responsive nanorobots. Their composition, propulsion mechanism, functional dynamics and therapeutic performance were studied systematically.

Results: Nanorobotic systems have shown great potential for targeted drug delivery, site-specific therapeutic release, enhanced tissue penetration, and improved treatment precision. The comparative analysis has revealed the differences between the nanorobotic platforms in terms of controllability, biocompatibility, targeting efficiency and translational feasibility. However, a number of challenges remain including biodistribution, immune recognition, reticuloendothelial system clearance, long-term toxicity, biodegradability, large-scale manufacturing and regulatory approval.

Conclusions: Nanorobotic systems have shown great potential for targeted drug delivery, site-specific therapeutic release, enhanced tissue penetration, and improved treatment precision. The comparative analysis has revealed the differences between the nanorobotic platforms in terms of controllability, biocompatibility, targeting efficiency and translational feasibility. However, a number of challenges remain including biodistribution, immune recognition, reticuloendothelial system clearance, long-term toxicity, biodegradability, large-scale manufacturing and regulatory approval.