Journal of Biomedical Science最新文献

Mass spectrometry-based spatial omics is a powerful approach for visualizing the spatial organization of proteins, metabolites, lipids, and other biomolecules in situ, combining the molecular depth of mass spectrometry with spatially resolved imaging. This systematic review traces the rapid technological and computational evolution of this field, including innovations in mass spectrometry imaging (MSI), labeling-based approaches, and proximity labeling techniques. It also highlights recent advances that enhance spatial resolution, expand molecular coverage, and enable deep molecular characterization and review analytical pipelines that integrate deep learning, cross-modality registration, and cloud-optimized data formats. From the multimodal and practical perspective, the integration of MSI with other spatial omics platforms and its transformative applications in tumor microenvironment profiling, neurodegenerative disease, developmental biology, biomarker discovery, and precision medicine are discussed. Finally, this review outlines challenges and opportunities, emphasizing the need for standardization, clinical validation, and interpretable artificial intelligence to enable broader adoption. These advances position MS-based spatial omics as a foundational pillar for multimodal spatial biology and personalized healthcare.

Neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, Huntington's disease, etc.) are caused by the progressive loss of neurons, which affects many people worldwide. Therefore, many efforts have focused on neurodegenerative disease mechanisms and therapeutic strategies. Moreover, amyloid precursor proteins and their cleaving products, including APP-C31, may play important roles in neurodegeneration. This review provides a comprehensive introduction to the structure, neurotoxicity, regulatory mechanism, and relevance of APP-C31 to clinical diseases and its therapeutic potential as a drug target. This work will bridge the gap in our understanding of the function of APP-C31, which provides an experimental basis for neurodegenerative disease therapeutics. Meanwhile, a hypothesis is postulated that the APP-C31 functions not merely as a byproduct of caspase cleavage, but as the critical "central executioner" bridging upstream triggers and downstream neurodegeneration. Diverse upstream stressors, initiate the cascade to generate APP-C31. Once generated, C31 acts as a multi-functional signalling hub driving four distinct pathogenic pathways. Consequently, APP-C31 is hypothesized to be the essential mediator that amplifies these molecular damages into macroscopic failures.

Background: Cancer cell plasticity enables dynamic transitions between cellular states, contributing to tumor progression and the acquisition of phenotypic traits such as vascular mimicry (VM), which promotes malignancy and resistance to anti-angiogenic therapies. Thrombomodulin (TM), a type I transmembrane glycoprotein known for initiating sprouting angiogenesis, has been implicated in tumor vascularization. However, its role in melanoma progression and VM remains poorly characterized.

Methods: TM expression was evaluated in human cutaneous melanoma biopsies and an endothelial-melanoma co-culture system. Functional assays were conducted to assess the impact of TM knockdown and overexpression on cell adhesion and VM formation. Domain-specific contributions of TM were investigated using constructs targeting its lectin-like domain and ezrin-binding motif. Mechanistic studies involved pharmacological inhibition of focal adhesion kinase (FAK) and siRNA-mediated silencing of ezrin. Therapeutic potential was assessed using a soluble TM lectin domain in both in vitro and in vivo melanoma models.

Results: TM was expressed in both angiogenic and non-angiogenic vessels within melanoma tissues and co-culture systems. TM knockdown impaired cell adhesion and suppressed VM formation, while TM overexpression in TM-null melanoma cells enhanced cellular plasticity via its lectin-like domain and ezrin-binding motif. Inhibition of FAK or silencing of ezrin reversed the TM-induced phenotypic switch. Treatment with a soluble TM lectin domain reduced cancer cell plasticity in vitro and significantly inhibited melanoma tumor growth and metastasis in vivo.

Conclusions: TM promotes melanoma cell plasticity and VM through FAK- and ezrin-dependent pathways. These findings position TM as a key regulator of tumor progression and suggest that targeting TM may offer a novel therapeutic strategy to disrupt cancer cell plasticity and suppress melanoma growth.

Background: Parkinson's disease (PD) is the second most common neurodegenerative disorder, categorized by the loss of dopaminergic neurons in the brain's Substantia Nigra pars compacta (SNpc) due to α-synuclein (α-syn) aggregation, leading to reduced dopamine levels in the striatum. This research study evaluates the neuroprotective potential of the novel peptide osmotin-derived 9-amino-acid (Os_9aa, C-T-Q-G-P-C-G-P-T) against α-syn (neuron-specific enolase promoter human alpha-synuclein (NSE-hαSyn)) and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD models.

Methods: Human neuroblastoma SH-SY5Y cells were employed as an in vitro model, while NSE-hαSyn (α-synuclein) transgenic mice and MPTP-treated mice were used as in vivo models of PD. MPTP was administered intraperitoneally (30 mg/kg) once daily for five consecutive days. Mice were immunized with Os_9aa (15 mg/kg, i.p., twice weekly for five weeks), followed by behavioral assessments including open field test, wire hang test, pole test, and rotarod test, and biochemical analysis using the Triplex Assay, western blotting, and confocal microscopy.

Results: Our study demonstrated that the novel peptide Os_9aa enhanced cell viability, reduced cytotoxicity, and apoptosis in SH-SY5Y neuroblastoma cells. Os_9aa attenuated synucleinopathy-related pathology in NSE-hαSyn transgenic mice and MPTP-induced PD mouse models. Current findings also highlighted the therapeutic potential of Os_9aa in mitigating behavioral deficits observed in NSE-hαSyn and MPTP mouse models of PD. Furthermore, Os_9aa administration effectively restored key dopaminergic markers, including tyrosine hydroxylase (TH), vesicular monoamine transporter 2 (VMAT2), and dopamine transporter (DAT). Additionally, it reduced neuroinflammation by decreasing the activation of glial cells-ionized calcium-binding adaptor molecule 1 (Iba-1) and glial fibrillary acidic protein (GFAP), as well as pro-inflammatory cytokines, such as phosphorylated nuclear factor-κB (p-NF-кB), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β), in the striatum and SNpc regions. Furthermore, Os_9aa mitigated oxidative stress (OS) by upregulating the expression of nuclear factor erythroid-related factor 2 (Nrf-2) and heme oxygenase 1 (HO-1), and improved cognitive performance.

Conclusion: Collectively, these findings highlight the neuroprotective potential of the Os_9aa, which counteracts α-synuclein- and MPTP-induced neurotoxicity by reducing oxidative stress, glial activation, and neuroinflammation. This multifaceted protection preserves neuronal integrity in both the NSE-hαSyn transgenic and MPTP-induced PD mouse models, underscoring Os_9aa as a promising therapeutic candidate for modifying PD pathogenesis.

Background: Despite therapeutic advances, atherosclerosis remains a major global health challenge. Most current treatments target systemic risk factors rather than the diseased vascular wall. Our previous work identified genistein, a soy isoflavone, as a cannabinoid receptor 1 (CB1) antagonist capable of suppressing CB1-mediated vascular inflammation and atherosclerosis. However, its poor water solubility and low oral bioavailability limit clinical application.

Purpose: We aimed to develop water-soluble, orally bioavailable CB1 antagonists for atherosclerosis and to investigate the role of endothelial CB1 in hemodynamic regulation.

Methods: RNA-sequencing datasets from the NCBI GEO repository were analyzed to assess CB1 expression in atherosclerotic patients. Apolipoprotein E-deficient (Apoe^-/-) mice with or without partial carotid artery ligation (PCAL) were used to model acute and chronic atherosclerosis. A cone-and-plate viscometer was employed to simulate disturbed flow. A ligand-based high-throughput virtual screening approach combined with SWEETLEAD chemical database analysis was used to discover new CB1 antagonists. A biotransformation-based strategy was used to generate isoflavone monophosphate prodrugs.

Results: We found CB1 was upregulated in atherosclerotic lesions from patients and mice, and in endothelial cells exposed to disturbed flow. Mechanistically, this was driven by ZNF610 and Spi1 binding and KLF4 dissociation at the CB1 promoter. Daidzein, a soy isoflavone structurally similar to genistein, was identified as a novel CB1 antagonist. To enhance solubility and bioavailability, we developed genistein 7-O-phosphate (G7P) and daidzein 7-O-phosphate (D7P). Pharmacological treatment with these isoflavone monophosphates or genetic CB1 ablation reversed disturbed flow-induced endothelial dysfunction and endothelial-to-mesenchymal transition (EndMT). Oral administration of G7P and D7P significantly reduced atherosclerotic plaque formation in mice.

Conclusions: This is the first study to identify transcriptional regulators that drive endothelial CB1 upregulation in response to disturbed flow. We further demonstrated that isoflavone monophosphates ameliorate disturbed flow-induced endothelial dysfunction and EndMT via CB1 inhibition, offering promising oral therapeutics for atherosclerosis.

Background: Accurate classification and segmentation of brain tumors in MRI scans are essential for diagnosis and treatment planning. However, the heterogeneous morphology of brain tumors, including irregular shapes, sizes, and spatial variability, makes this task highly challenging. Traditional convolutional neural networks (CNNs) lack rotational and translational invariance, which limits their ability to generalize across different orientations.

Methods: This study introduces a geometric deep learning framework called Modified Special Euclidean (Mod-SE(2)), which integrates geometric priors to enhance spatial consistency and reduce reliance on data augmentation. By incorporating symmetry-preserving group convolutions and spatial priors, Mod-SE(2) improves the robustness in tumor classification (namely Mod-Cls-SE(2)) and segmentation (mentioned as Mod-Seg-SE(2)). Unlike conventional CNNs, geometric deep learning encodes roto-translation symmetry directly into the architecture. This addresses the spatial variability and orientation sensitivity that are common in MRI-based diagnostics. Mod-SE(2) was evaluated on three MRI datasets and two other medical image datasets for classification and segmentation tasks. It incorporates lifting layers, group convolutions, and feature recalibration. It was benchmarked against U-Net, NN U-Net, VGG16, VGG19, and ResNet architectures.

Results: Mod-Cls-SE(2) achieved an average classification accuracy of 0.914, outperforming ResNet101 with 0.682, VGG16 with 0.705, and their variants. In the binary classification of five tumor types (AVM, Meningioma, Pituitary, Metastases, and Schwannoma) from the private dataset, the model achieved an accuracy of 0.935 and a precision of 0.960 for pituitary tumors and a precision of 0.96. For segmentation tasks, Mod-Seg-SE(2) achieved a dice coefficient of 0.9503 and an IoU of 0.9616 on the BraTS2020 dataset. This result exceeds those of U-Net and NN U-Net with dice scores of 0.797 and 0.815, respectively. The model also reduced inference time and demonstrated strong computational performance.

Conclusions: Mod-SE(2) uses geometric priors to improve the spatial consistency, efficiency, and interpretability in brain tumor analysis. Its symmetry-aware design enables better generalization across tumor shapes and outperforms traditional methods across all key metrics. The Mod-SE(2) CNN ensures accurate boundary delineation, supporting neurosurgical planning, intraoperative navigation, and downstream applications such as Monte Carlo-based radiotherapy simulations and PET-MRI co-registration. Future work will extend the model to 3D volumes and validate its clinical readiness.

Background: Mild traumatic brain injury (mTBI) is the most prevalent form of brain injury. Secondary damage following mTBI contributes to neuronal degeneration by promoting neuroinflammation, amyloid accumulation, and oxidative stress (OS). Microglia exhibit dual roles after injury, contributing to both pro-inflammatory (M1) and anti-inflammation/neuroprotective (M2) responses. Targeting microglial polarization may therefore represent a therapeutic strategy for mitigating secondary damage after TBI.

Methods: A weight-drop mTBI model (30 g, 100 cm) was applied to both C57BL/6 (wild-type) and CCL5 knockout (CCL5-KO) mice. Microglial activation was assessed at 7-, 14-, 21-, and 28-days post-injury using RT-qPCR, immunohistochemistry, and western blotting. Oxidative stress in tissue was detected by Hydroxyprobe™ labeling, ROS detection, NADPH oxidase activity assay, and antioxidant expression. Recombinant CCL5 (rCCL5) was administered intranasally to evaluate its effect on post-injury inflammation. Cortical tissue was subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS) for proteomic profiling. In vitro, BV2 microglial cells were treated with H₂O₂ to model OS. The effects of rCCL5 on cell viability, inflammatory gene expression, and phagocytic activity were assessed via MTT assay, immunocytochemistry, flow cytometry, and RT-qPCR. Pharmacological inhibitors targeting CCR1, CCR3, and CCR5 were used to delineate receptor-specific signaling pathways.

Results: rCCL5 significantly reduced oxidative stress in both neurons and microglia and enhanced expression of antioxidant enzymes such as GPX1, SOD1, and SOD2 in injured cortices. Proteomic analysis revealed upregulation of immune regulatory and phagocytosis-related pathways following rCCL5 treatment. In vitro, rCCL5 conferred cytoprotection against H₂O₂-induced cell death and promoted M2-like microglial polarization. Blockade of CCR5, but not CCR3, abrogated CCL5-induced M2 differentiation, whereas both CCR3 and CCR5 were required for enhanced phagocytosis. CCL5-induced NFATc2 activation was mediated primarily via CCR5.

Conclusions: These findings demonstrate that CCL5 modulates microglial polarization and attenuates oxidative stress in the injured brain through a CCR5-dependent mechanism. Targeting the CCL5-CCR5 signaling axis may offer a promising therapeutic strategy for improving outcomes after mTBI.

The extracellular matrix (ECM) provides critical biochemical and biophysical cues that regulate cell behavior in health and disease. Collagens dominate in abundance and structural importance, shaping tissue-specific ECM signatures that guide cellular behavior. Two major and distinct transmembrane receptor families, integrins and discoidin domain receptors (DDRs), serve as primary sensors for collagens, yet they employ fundamentally distinct binding mechanisms and signaling kinetics. While both can activate shared downstream pathways, their functional interplay remains complex and context-dependent, with the potential to fine-tune cellular responses to ECM cues. This review deciphers the nuanced crosstalk between integrin β1 and DDRs, with a particular focus on the understudied DDR2, across physiological and pathological processes. We discuss how this interplay, which evolves from cooperative to compensatory or even antagonistic signaling, is influenced by variables,  such as tissue specificity, developmental timing, and pathological context, dictating cell adhesion, migration, and ECM remodeling. Key examples include DDRs acting as allosteric regulators to license integrin activation, their partnership in mechanotransduction during development, and their divergent roles in aging tissues, where altered collagen mechanics shift the receptor hierarchy. In pathology, the DDR-integrin axis is pivotal in fibrosis and cancer, influencing fibroblast activation, drug resistance, metastatic outgrowth, and immune suppression within the tumor microenvironment. Notably, the receptors can function both independently and synergistically; for instance, DDR2 in cancer-associated fibroblasts regulates integrin-mediated mechanosignaling to promote metastasis, while in other contexts, both receptors activate distinct survival pathways. Understanding the signaling dynamics and mechanisms of these receptors is necessary for deciphering how cells interpret ECM signals and how these mechanisms contribute to disease progression, especially in those diseases marked by collagen remodeling. This comprehension is crucial for developing novel therapeutic strategies. Emerging evidence suggests that combined targeting DDRs and integrins can synergistically overcome ECM-mediated therapy resistance, enhance immune infiltration, and reprogram pathological microenvironments, offering a promising approach for treating fibrosis and collagen-rich cancers.

Background: Cancer is the second leading cause of death worldwide. While significant progress has been made in early detection and treatment, metastasis remains the major cause of cancer-related morbidity and mortality. In the last decade the rate of long-term survivorship of metastatic cancer has continued to improve and overcoming resistance to therapy has now become a challenge. Developing strategies to prevent and treat metastatic disease is a priority for public health and requires a thorough understanding of the mechanisms driving progression of a specific patient's tumor and the rapid identification of targetable cancer drivers and drug resistance genes.

Discussion: Custom bioprinted tumors, which recreate the interactions between tumors and surrounding tissues, can be integrated into organ-on-chip platforms, and leveraging molecular pathology and OMICS data, can provide highly realistic patient-specific models. These biomimetic tools enable the investigation of metastasis organotropism, the identification of therapeutic targets and the design of drug administration protocols to prevent metastasis and to overcome resistance. Benefits, limitations, and challenges to address for an efficient and routine application of this cutting-edge approach, together with the role of Artificial-Intelligence (AI) in managing the complex datasets generated by OMICS technologies will be highlighted in this review, as well as their real-life implications and evolutionary prospects.

Conclusion: Applying patient-derived bioprinted tumors and organs for clinical purpose and developing standardized 4D and 5D bioprinting protocols would allow assessment of cancer response to treatments in a dynamic and faithfully reconstructed microenvironment. Integration of advanced molecular diagnostics and multi-OMICS data, with customized small-scale tumor models, assisted by AI-powered tools, requires a multidisciplinary framework. This integrated approach can upgrade clinical management of metastatic diseases, by accelerating the identification of actionable biomarkers and resistance mechanisms for timely therapy adjustments, thus enabling tailored treatment regimens based on individual tumor behavior.

Phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme of the serine biosynthesis pathway (SSP), is a central metabolic hub and multifunctional oncoprotein that drives tumorigenesis through both canonical and non-canonical mechanisms. This review outlines the multi-level regulation of PHGDH, covering epigenetic remodeling (DNA hypomethylation, H3K4me3/H3K36me3 dynamics), transcriptional control (ATF4, MYC, EWS-FLI1), post-transcriptional fine-tuning (m⁶A/m⁵C modifications, RNA-binding proteins), and post-translational modifications (ubiquitination, methylation, phosphorylation). Together, these regulatory layers allow cancer cells to adapt metabolically to microenvironmental stress. Beyond its fundamental role in supplying nucleotides, maintaining redox homeostasis, and supporting one-carbon metabolism, PHGDH also performs moonlighting function. For example, its translocation to the nucleus inhibits PARP1 to sustain oncogenic transcription, while its presence in mitochondria helps remodel electron transport chains to promote metastasis. Critically, PHGDH exhibits a therapeutic paradox wherein its inhibition can synergize with chemotherapy, radiotherapy, and immunotherapy across diverse malignancies, yet tumors develop resistance via metabolic plasticity, or by selection of PHGDH-low metastatic clones. The clinical translation of PHGDH inhibitors is further challenged by inherent neurotoxicity risks, as neurons rely on de novo serine synthesis. To address these challenges, we propose a precision roadmap that integrates spatial multi-omics, AI-driven allosteric inhibitor design, dynamic biosensing (e.g., ¹⁸F-metabolite PET), and biomarker-stratified clinical trials. By reconciling the dual nature of PHGDH biology, we can transform this metabolic linchpin from a confounding paradox into a clinically actionable vulnerability.