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LncRNA LINC01605 Regulates Smooth Muscle Cell Functions and Participates in the Development of Aortic Dissection Through Regulating SGK1 LncRNA LINC01605通过调节SGK1调控平滑肌细胞功能参与主动脉夹层的发生
IF 4.2 Pub Date : 2025-11-26 DOI: 10.1111/jcmm.70963
Mingliang Li, Ruonan Li, Zihe Zheng, Changbo Xiao, Quanlin Yang, Bo Chen, Xiaofu Dai

Long noncoding RNAs (lncRNAs) are emerging as key regulators in cardiovascular diseases. This study investigated the role of lncRNA LINC01605 in aortic dissection (AD) pathogenesis through its effects on vascular smooth muscle cells (VSMCs). Bioinformatics analysis of GEO datasets (GSE107844, GSE147026) identified LINC01605 as differentially expressed in AD. Its expression was validated in human aortic tissues and VSMCs using RT-qPCR and FISH. Functional assays (CCK-8, Transwell, Western blot) assessed VSMC proliferation, migration, phenotypic switching and autophagy. SGK1 was predicted as a target via bioinformatics and confirmed by RIP assays. Ang II-induced AD mice with LINC01605 knockdown were used for in vivo validation. LINC01605 was significantly upregulated in AD aortic tissues and VSMCs. Functional studies demonstrated that LINC01605 promoted VSMC proliferation, migration, invasion, phenotypic switching and autophagy, particularly under Ang II stimulation. Mechanistically, LINC01605 targeted SGK1 to regulate VSMC function. Knockdown of LINC01605 alleviated AD pathology in mice, modulating synthetic phenotype and autophagy markers. LINC01605 plays an important role in AD. It regulates the function of VSMCs by targeting SGK1 and promotes the pathological process of AD. LINC01605 may be a potential target for AD treatment, providing new directions for the mechanism research and treatment strategies of AD.

长链非编码rna (lncRNAs)正成为心血管疾病的关键调控因子。本研究通过对血管平滑肌细胞(VSMCs)的影响,探讨lncRNA LINC01605在主动脉夹层(AD)发病中的作用。GEO数据集(GSE107844, GSE147026)的生物信息学分析发现LINC01605在AD中存在差异表达。利用RT-qPCR和FISH验证了其在人主动脉组织和VSMCs中的表达。功能分析(CCK-8、Transwell、Western blot)评估VSMC的增殖、迁移、表型转换和自噬。SGK1通过生物信息学预测为靶标,并通过RIP测定证实。用敲低LINC01605的angii诱导的AD小鼠进行体内验证。LINC01605在AD主动脉组织和VSMCs中显著上调。功能研究表明,LINC01605促进VSMC增殖、迁移、侵袭、表型转换和自噬,特别是在Ang II刺激下。机制上,LINC01605靶向SGK1调节VSMC功能。敲低LINC01605可减轻小鼠AD病理,调节合成表型和自噬标志物。LINC01605在AD中起重要作用。它通过靶向SGK1调控VSMCs的功能,促进AD的病理过程。LINC01605可能是阿尔茨海默病治疗的潜在靶点,为阿尔茨海默病的机制研究和治疗策略提供新的方向。
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引用次数: 0
Statins Regulate Stem Cell Growth Factor-β to Balance Osteogenesis and Adipogenesis in Mesenchymal Stem Cells, Endowing Anti-Osteonecrosis Effects 他汀类药物调节干细胞生长因子-β平衡间充质干细胞成骨和脂肪生成,赋予抗骨坏死作用。
IF 4.2 Pub Date : 2025-11-26 DOI: 10.1111/jcmm.70967
Fangzhou Fan, Yu Chen, Weiyan Peng, Wenlong Yan, Hao Tan, Chengxuan Zhang, Siyu Tan, Qian Xiao, Yuan Gao, Jian Zhang, Lei Liu, Chengjie Lian

Dyslipidaemia has been implicated in osteonecrosis through some clinical studies. However, a direct causal relationship between hyperlipidaemia and osteonecrosis remains unconfirmed, and whether lipid-lowering agents could be used to treat osteonecrosis remains unclear. This study aimed to investigate the causal role of lipid traits in osteonecrosis using Mendelian randomisation (MR) analysis, assess the potential effects and mechanisms of lipid-lowering drug targets on osteonecrosis risk and validate these findings through experimental approaches. Genome-wide association study (GWAS) data were used to analyse lipid traits, drug targets and FinnGen osteonecrosis. Statin effects were further studied in a rat model of steroid-induced osteonecrosis and in vitro cell models. MR analysis revealed a significant association between LDL-C and increased osteonecrosis risk. Genetic mimicry of HMGCR inhibitors was associated with reduced osteonecrosis risk, which was validated through colocalisation. Stem cell growth factor-β (SCGF-β) was identified as a mediator of 21.3% of HMGCR inhibitors' effect on osteonecrosis risk. Further studies confirmed simvastatin's alleviating effect on SONFH, suggesting that simvastatin promotes osteogenesis and inhibits adipogenesis of mesenchymal stem cells (MSCs), partly mediated by SCGF-β upregulation, which activates the Wnt signalling pathway. Our findings supported dyslipidaemia as a causal factor for osteonecrosis, highlighting HMGCR as a promising therapeutic target.

一些临床研究表明,血脂异常与骨坏死有关。然而,高脂血症与骨坏死之间的直接因果关系仍未得到证实,降脂药物是否可用于治疗骨坏死仍不清楚。本研究旨在通过孟德尔随机化(MR)分析探讨脂质性状在骨坏死中的因果作用,评估降脂药物靶点对骨坏死风险的潜在影响和机制,并通过实验方法验证这些发现。使用全基因组关联研究(GWAS)数据分析脂质性状、药物靶点和FinnGen骨坏死。他汀类药物的作用在类固醇诱导的大鼠骨坏死模型和体外细胞模型中进一步研究。MR分析显示LDL-C与骨坏死风险增加之间存在显著关联。HMGCR抑制剂的遗传模拟与降低骨坏死风险相关,这一点通过共定位得到了验证。干细胞生长因子-β (SCGF-β)被确定为HMGCR抑制剂对骨坏死风险影响的21.3%的中介。进一步的研究证实了辛伐他汀对SONFH的缓解作用,表明辛伐他汀促进间充质干细胞(MSCs)的成骨和抑制脂肪生成,其部分介导机制是SCGF-β上调,激活Wnt信号通路。我们的研究结果支持血脂异常是骨坏死的一个诱因,强调HMGCR是一个有希望的治疗靶点。
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引用次数: 0
Liposome-Encapsulated Melatonin Mitigates Amoxicillin-Induced Neurotoxicity in a Zebrafish 脂质体包裹褪黑素减轻阿莫西林诱导的斑马鱼神经毒性。
IF 4.2 Pub Date : 2025-11-26 DOI: 10.1111/jcmm.70969
Ranjith Balakrishnan, Rajasekaran Subbarayan, Rupendra Shrestha, Dhasarathdev Srinivasan, Reena Shrestha, Ankush Chauhan, Dinesh Murugan Girija

Amoxicillin (Amx), a β-Lactam antibiotic frequently used to treat bacterial infections, has been linked to neurological effects, including anxiety, hyperactivity, ambiguity, seizures, and behavioural changes. We examined the neurotoxic effects of Amx in zebrafish and investigated the potential of liposome-encapsulated melatonin (L-Mel) as a therapeutic intervention. Computational studies have indicated that Amx and Mel interact with GABA receptors, suggesting the potential of L-Mel in mitigating Amx-induced neurological changes. Our findings demonstrated that the nanoformulated L-Mel showed reduced toxicity in zebrafish larvae. Administration of L-Mel to Amx-affected zebrafish brain tissue significantly lowered the levels of reactive oxygen species, antioxidants (catalase, superoxide dismutase, and nitric oxide), and proinflammatory cytokines (TNF-α, IL-1β, and NF-kB), based on the fixed EC-50. Behavioural assessments revealed that L-Mel treatment notably enhanced the immobility time and swimming performance, improving the movement abilities of zebrafish with Amx-induced neuroinflammation. Moreover, the GABA/glutamate levels in the neural tissues exhibited significant recovery in the L-Mel group. Gene and protein analysis showed substantial increases in BDNF, CREBBP, ASCL, NF-κB and GABA-A R γ2 in L-Mel treated subjects. Histopathological evaluation revealed that L-Mel treatment markedly attenuated Amx-induced neurotoxicity, as evidenced by reduced neuronal degeneration and necrosis in the brain tissue, indicating a pronounced neuroprotective effect. In conclusion, our research suggests that L-Mel is a promising therapeutic agent for mitigating Amx-induced neurotoxicity.

阿莫西林(Amx)是一种常用于治疗细菌感染的β-内酰胺类抗生素,与神经系统影响有关,包括焦虑、多动、模糊、癫痫发作和行为改变。我们研究了Amx对斑马鱼的神经毒性作用,并研究了脂质体包封褪黑激素(L-Mel)作为治疗干预的潜力。计算研究表明,Amx和Mel与GABA受体相互作用,表明L-Mel有可能减轻Amx诱导的神经系统变化。我们的研究结果表明,纳米配方的L-Mel对斑马鱼幼虫的毒性降低。在固定EC-50的基础上,给amx感染的斑马鱼脑组织注射L-Mel可显著降低活性氧、抗氧化剂(过氧化氢酶、超氧化物歧化酶和一氧化氮)和促炎细胞因子(TNF-α、IL-1β和NF-kB)的水平。行为评估显示,L-Mel治疗显著增加了amx诱导的神经炎症斑马鱼的静止时间和游泳表现,改善了运动能力。此外,L-Mel组神经组织中GABA/谷氨酸水平明显恢复。基因和蛋白分析显示,L-Mel治疗组BDNF、CREBBP、ASCL、NF-κB和GABA-A - R γ2显著升高。组织病理学评估显示,L-Mel治疗显著减轻了amx诱导的神经毒性,脑组织中神经元变性和坏死减少,表明L-Mel具有明显的神经保护作用。总之,我们的研究表明L-Mel是一种很有希望减轻amx诱导的神经毒性的治疗药物。
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引用次数: 0
Quinovic Acid Enhances the Cytotoxicity of KHYG-1 Cells by Modulating the Ras/MAPK Signalling Pathway and Interferon-Gamma Expression 喹啉酸通过调节Ras/MAPK信号通路和干扰素γ表达增强KHYG-1细胞的细胞毒性
IF 4.2 Pub Date : 2025-11-26 DOI: 10.1111/jcmm.70957
Ming-Ju Hsieh, Jen-Tsun Lin, Yi-Ching Chuang, Hsin-Yu Ho, Yu-Sheng Lo, Chia-Chieh Lin, Mu-Kuan Chen

Quinovic acid is a key constituent of cat's claw (Uncaria tomentosa) extract and exhibits antioxidant and anti-inflammatory activities. In this study, we investigated the potential of quinovic acid to enhance natural killer (NK) cell activity by using the KHYG-1 cell line. Our data indicated that quinovic acid increased the expression levels of cytolytic molecules, including perforin, granzymes A and B, Fas ligand, and granulysin, and induced the phosphorylation of the transcription factors CREB and STAT4, thereby enhancing cytotoxic activity against K562 cells. Furthermore, when KHYG-1 cells were cocultured with K562 cells in the presence of quinovic acid, we observed an increase in the expression of t-Bid, cleaved caspases 3, 8, and 9, and PARP, promoting apoptosis in K562 cells. Quinovic acid also reduced the expression of SET, Ape1, and HMGB2, effectively inhibiting the DNA repair mechanism in target cells. Similar results were observed in other cancer cell lines. In addition, quinovic acid induced interferon-gamma secretion by upregulating the Ras/MAPK and PI3K/AKT/mTOR signalling pathways through the activation of NKG2D and other NK receptors. These effects were observed not only in KHYG-1 cells but also in NK cells derived from adult patients with head and neck squamous cell carcinoma. Our findings suggest that quinovic acid enhances NK cell cytotoxicity, showing promise as a potential therapeutic against various cancer cell types.

喹啉酸是猫爪提取物的主要成分,具有抗氧化和抗炎活性。在这项研究中,我们利用KHYG-1细胞系研究了喹诺维奇酸增强自然杀伤细胞(NK)活性的潜力。我们的数据表明,奎诺维奇酸增加了细胞溶解分子的表达水平,包括perforin、颗粒酶A和B、Fas配体和颗粒酶,并诱导转录因子CREB和STAT4的磷酸化,从而增强了对K562细胞的细胞毒活性。此外,当KHYG-1细胞与K562细胞在喹啉酸存在下共培养时,我们观察到t-Bid、cleaved caspases 3、8、9和PARP的表达增加,促进了K562细胞的凋亡。喹啉酸还能降低SET、Ape1和HMGB2的表达,有效抑制靶细胞的DNA修复机制。在其他癌细胞系中也观察到类似的结果。此外,喹啉酸通过激活NKG2D等NK受体,上调Ras/MAPK和PI3K/AKT/mTOR信号通路,诱导干扰素γ分泌。这些影响不仅在KHYG-1细胞中观察到,而且在成年头颈部鳞状细胞癌患者的NK细胞中也观察到。我们的研究结果表明,奎诺维奇酸增强NK细胞的细胞毒性,显示出对各种癌症细胞类型的潜在治疗前景。
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引用次数: 0
Genetic Crosstalk Between Type 1 Diabetes and Sjögren's Syndrome: A Systematic Exploration of Risk Genes and Common Pathways 1型糖尿病和Sjögren综合征之间的基因串扰:风险基因和共同途径的系统探索。
IF 4.2 Pub Date : 2025-11-26 DOI: 10.1111/jcmm.70930
Aamir Fahira, Kai Zhuang, Xuemin Jian, Syed Mansoor Jan, Yong Liu, Jianbo Sun, Yongyong Shi, Zunnan Huang

Sjögren's Syndrome (SS) and Type 1 Diabetes (T1D) are autoimmune disorders that can co-occur in patients, leading to complex clinical presentations. Despite observational evidence of their co-occurrence, the underlying genetic mechanisms remain poorly understood. To investigate the shared genetic factors and pathways between SS and T1D, we conducted a comprehensive analysis using multiomic approaches. Conditional and conjunctional false discovery rate analyses were performed to identify genetic polygenicity and overlap between the two diseases. Functional annotation and pathway analysis identified SNPs with regulatory potential. Furthermore, Mendelian Randomization (MR) analyses were employed to investigate causal associations between gene expression and disease risk. Single-cell differential gene expression analysis was also employed to validate the associations of risk genes with T1D and SS. Our analysis identified 36 shared loci, revealing common genetic enrichment between SS and T1D. Functional annotation and pathway analysis revealed 52 credible genes involved in cysteine-related processes, apoptotic signalling and immune responses. MR analyses revealed that AC007283.5 was positively linked with both SS and T1D, while PLEKHM1 and CRHR1-T1 were negatively associated. Additionally, CERS2 was positively associated with SS, DEF6 was positively associated with T1D, and KANSL1-AS1 was negatively associated with T1D, indicating the presence of complex regulatory mechanisms. Moreover, Single-cell differential gene expression analysis confirmed the dysregulation of risk genes in SS and T1D. This study identified shared genetic factors and pathways underlying SS and T1D, highlighting cysteine-related processes and apoptotic signalling. The findings underscore the complex interplay of autoimmunity and the need for targeted treatments addressing their common mechanisms.

Sjögren综合征(SS)和1型糖尿病(T1D)是可在患者中同时发生的自身免疫性疾病,导致复杂的临床表现。尽管观察证据表明它们共同发生,但潜在的遗传机制仍然知之甚少。为了研究SS和T1D之间的共同遗传因素和途径,我们使用多组学方法进行了综合分析。进行了条件和联合错误发现率分析,以确定两种疾病之间的遗传多基因性和重叠。功能注释和通路分析鉴定出具有调控潜力的snp。此外,采用孟德尔随机化(MR)分析来研究基因表达与疾病风险之间的因果关系。单细胞差异基因表达分析也用于验证风险基因与T1D和SS的关联。我们的分析鉴定了36个共享位点,揭示了SS和T1D之间共同的遗传富集。功能注释和通路分析揭示了52个可信的基因参与半胱氨酸相关过程、凋亡信号传导和免疫反应。MR分析显示AC007283.5与SS和T1D呈正相关,而PLEKHM1和CRHR1-T1呈负相关。此外,CERS2与SS呈正相关,DEF6与T1D呈正相关,KANSL1-AS1与T1D负相关,表明存在复杂的调控机制。此外,单细胞差异基因表达分析证实了SS和T1D中危险基因的失调。本研究确定了SS和T1D的共同遗传因素和通路,强调了半胱氨酸相关过程和凋亡信号传导。这些发现强调了自身免疫的复杂相互作用,以及针对其共同机制进行靶向治疗的必要性。
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引用次数: 0
Silencing of Cholesterol 25-Hydroxylase Attenuates Lipopolysaccharide-Induced Cardiomyocyte Damage In Vitro 沉默胆固醇25-羟化酶可减轻脂多糖诱导的体外心肌细胞损伤
IF 4.2 Pub Date : 2025-11-26 DOI: 10.1111/jcmm.70959
Yi-jiao Men, Hong-bo Cheng, Yan-ling Dong, Yu Gong, Ya-qing An, Ying-li Jin, Shu-na Hao, Yu Ma, Ying-ping Tian

The underlying mechanisms of sepsis-induced myocardial dysfunction (SIMD) remain elusive, and no targeted therapies currently exist. This study aimed to explore the expression features and functional effects of cholesterol 25-hydroxylase (CH25H) in SIMD in vitro. CH25H was identified as an upregulated gene related to SIMD through bioinformatics analysis. Its upregulation was validated in the myocardial tissue of SIMD mice as well as in lipopolysaccharide (LPS)-induced primary cardiomyocytes and AC16 cells. CH25H overexpression elevated 25-hydroxycholesterol levels and aggravated oxidative stress, mitochondrial dysfunction, apoptosis, and NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome and NF-κB pathway activation in AC16 cells. The effect of CH25H overexpression was similar to that induced by LPS treatment. Conversely, silencing CH25H attenuated these LPS-induced injuries. Furthermore, CH25H overexpression exacerbated oxidative stress, mitochondrial dysfunction, and apoptosis in LPS-stimulated AC16 cells, and these effects of CH25H overexpression can be counteracted by the NLRP3 inhibitor. In conclusion, CH25H may promote LPS-induced cardiomyocyte injury through NLRP3/NF-κB pathway activation.

脓毒症诱发心肌功能障碍(SIMD)的潜在机制尚不明确,目前尚无靶向治疗方法。本研究旨在探讨胆固醇25-羟化酶(CH25H)在体外SIMD中的表达特点及功能作用。通过生物信息学分析,发现CH25H是一个与SIMD相关的上调基因。在SIMD小鼠的心肌组织以及脂多糖(LPS)诱导的原代心肌细胞和AC16细胞中证实了其上调。在AC16细胞中,CH25H过表达可升高25-羟基胆固醇水平,加重氧化应激、线粒体功能障碍、细胞凋亡、nod样受体家族pyrin结构域3 (NLRP3)炎性体和NF-κB通路激活。CH25H过表达的效果与LPS处理相似。相反,沉默CH25H可减轻lps诱导的损伤。此外,在lps刺激的AC16细胞中,CH25H过表达加重了氧化应激、线粒体功能障碍和细胞凋亡,而NLRP3抑制剂可以抵消CH25H过表达的这些影响。综上所述,CH25H可能通过激活NLRP3/NF-κB通路促进lps诱导的心肌细胞损伤。
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引用次数: 0
Development of a PANoptosis-Related Pathomics Prognostic Model in Ovarian Cancer: A Multi-Omics Study 卵巢癌panoposis相关病理预后模型的建立:多组学研究。
IF 4.2 Pub Date : 2025-11-24 DOI: 10.1111/jcmm.70958
Yangyang Zhang, Mengqi Fang, Xuanyu Wang, Zhiwei Ying, Shufan Jiang, Yangyuxiao Lu, Keren He, Shaocong Mo, Fangfang Tao, Ping Lü

Ovarian cancer (OC) is a high-mortality gynaecological malignancy, and the role of PANoptosis, a comprehensive cell death mechanism, in its prognosis remains unexplored. This study aims to clarify it, potentially guiding OC diagnosis and treatment. We analysed the ovarian data from TCGA and GTEx, and the GSE184880 scRNA-seq dataset from GEO. Spatial data and pathological images were sourced from the 10X Genomics website and GDC Portal. Features were extracted using CellProfiler and ResNet-50, and a PANoptosis-related pathomics prognostic model (PANPM) powered by deep learning was developed. The PANoptosis-related hub gene STAT4 potentially served as a protective factor for patients with OC. A better prognosis in OC was found linked to higher PANoptosis. The PANPM, manifesting distinct advantages for clinical application by accurately extracting pathological features, performed excellently in validation and the high-risk group indicated a poor prognosis. Additionally, STAT4+ T cells may inhibit OC, by activating the PANoptosis of epithelial cells through TNFSF12-TNFRSF12A and TNF-TNFRSF1A, which sheds light on potential therapeutic interventions involving STAT4+ T cells.

卵巢癌(OC)是一种高死亡率的妇科恶性肿瘤,PANoptosis是一种全面的细胞死亡机制,在其预后中的作用仍未被探索。本研究旨在对其进行澄清,以指导卵巢癌的诊断和治疗。我们分析了TCGA和GTEx的卵巢数据,以及GEO的GSE184880 scRNA-seq数据集。空间数据和病理图像来源于10X Genomics网站和GDC Portal。使用CellProfiler和ResNet-50提取特征,并开发了基于深度学习的panopsis相关病理预后模型(PANPM)。panoptosis相关中枢基因STAT4可能是OC患者的保护因子。OC患者预后较好与PANoptosis增高有关。PANPM准确提取病理特征,具有明显的临床应用优势,验证效果良好,高危组预后较差。此外,STAT4+ T细胞可能通过TNFSF12-TNFRSF12A和TNF-TNFRSF1A激活上皮细胞的PANoptosis,从而抑制OC,这揭示了涉及STAT4+ T细胞的潜在治疗干预措施。
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引用次数: 0
BioEmu: AI-Powered Revolution in Scalable Protein Dynamics Simulation BioEmu: ai驱动的可扩展蛋白质动力学模拟革命。
IF 4.2 Pub Date : 2025-11-24 DOI: 10.1111/jcmm.70960
Tianming Han, Min Wu, Qi Zhao
<p>In drug discovery and biotechnology, protein dynamics are essential for understanding functional mechanisms. However, traditional methods, such as molecular dynamics (MD) simulations, are time- and resource-intensive, which often require supercomputers and months of computation. Recently, Lewis et al. [<span>1</span>] brought a giant advance in the journal of <i>Science</i>: BioEmu, a diffusion model-based generative AI system. It simulates protein equilibrium ensembles with 1 kcal/mol accuracy using a single GPU, achieving a 4–5 orders of magnitude speedup for equilibrium distributions in folding and native-state transitions. This approach reduces high computational costs and enables genome-scale protein function prediction, akin to equipping biology with an accelerator.</p><p>Simulating protein dynamics is crucial for revealing functional mechanisms in drug development and biotechnology. Advances in deep learning tools, such as AlphaFold [<span>2</span>], enable genome-scale prediction of protein sequences and static structures. However, quantitative analysis of dynamic equilibrium ensembles remains a bottleneck in this field [<span>3</span>]. Protein functions often emerge from transitions between conformational states and their probability distributions (Figure 1A) [<span>4</span>]. These transitions are regulated by factors like temperature, solvent, and concentration. Biophysical experiments, such as single-molecule fluorescence or cryo-EM, offer high precision but have low throughput and high costs [<span>5</span>]. MD simulations are versatile in principle, yet sampling challenges require massive computational resources. These often involve millisecond-scale simulations, even with dedicated supercomputers or enhanced techniques. Prior to the Lewis et al. study, generative AI models could approximate protein shapes but failed to match experimental data precisely, especially for complex motions like domain rearrangements or cryptic pocket formation.</p><p>BioEmu's architecture combines protein sequence encoding with a generative diffusion model (Figure 1B). This system uses AlphaFold2's Evoformer module to convert the input sequence into single and pairwise representations. These representations capture deep associations between sequence and structure and are then fed into a diffusion-based denoising model, which uses coarse-grained backbone frames for protein structures to enhance computational efficiency. The diffusion process generates independent structural samples in 30–50 denoising steps on a single GPU. This design overcomes the sampling bottleneck of traditional MD simulations. As a result, BioEmu samples thousands of structures per hour on a single GPU, compared to months on supercomputing resources.</p><p>BioEmu's training comprises three stages (Figure 1C). First, it involves pretraining on a processed AlphaFold database (AFDB) with data augmentation to link sequences to diverse structures. This enhances the model's generalisa
在药物发现和生物技术中,蛋白质动力学对于理解功能机制至关重要。然而,传统的方法,如分子动力学(MD)模拟,是时间和资源密集型的,通常需要超级计算机和数月的计算。最近,Lewis等人在《科学》杂志上取得了巨大进展:BioEmu,一个基于扩散模型的生成式人工智能系统。它使用单个GPU以1 kcal/mol的精度模拟蛋白质平衡集成,实现了折叠和原生状态转换平衡分布的4-5个数量级的加速。这种方法降低了高昂的计算成本,并使基因组规模的蛋白质功能预测成为可能,类似于为生物学配备加速器。模拟蛋白质动力学对于揭示药物开发和生物技术中的功能机制至关重要。深度学习工具的进步,如AlphaFold[2],使蛋白质序列和静态结构的基因组级预测成为可能。然而,动态平衡系综的定量分析仍然是该领域的瓶颈。蛋白质功能通常出现在构象状态和它们的概率分布之间的转换(图1A)[4]。这些转变受温度、溶剂和浓度等因素的调节。生物物理实验,如单分子荧光或低温电镜,精度高,但通量低,成本高。MD模拟原则上是通用的,但采样挑战需要大量的计算资源。这些通常涉及毫秒级的模拟,甚至使用专用的超级计算机或增强的技术。在Lewis等人的研究之前,生成式人工智能模型可以近似蛋白质形状,但无法精确匹配实验数据,特别是对于复杂的运动,如结构域重排或隐口袋形成。BioEmu的结构结合了蛋白质序列编码和生成扩散模型(图1B)。该系统使用AlphaFold2的Evoformer模块将输入序列转换为单个和成对的表示。这些表征捕获了序列和结构之间的深层关联,然后将其输入到基于扩散的去噪模型中,该模型使用粗粒度的骨干框架来处理蛋白质结构,以提高计算效率。扩散过程在单个GPU上以30-50个去噪步骤生成独立的结构样本。该设计克服了传统MD仿真的采样瓶颈。因此,BioEmu在单个GPU上每小时采样数千个结构,而在超级计算资源上则需要数月。BioEmu的培训包括三个阶段(图1C)。首先,它涉及在经过处理的AlphaFold数据库(AFDB)上进行预训练,并对数据进行扩充,以将序列链接到不同的结构。这增强了模型对构象变化的泛化,并防止了对静态结构的过度拟合。其次,在总计超过200 ms的数千个蛋白质MD数据集上进行进一步的训练,使用马尔可夫状态模型(MSM)[6]进行重新加权以获得平衡分布。最后,利用MEGAscale数据集[7]的50万个实验稳定性测量值对模型进行属性预测微调(PPFT)。PPFT将实验观察(例如,熔化温度)纳入扩散训练。它通过最小化预测值和实验值之间的差异来优化集合分布。这确保了生成结构的多样性和热力学约束。为了评估BioEmu的性能,Lewis等人开发了几个基准数据集。这些数据集强调分布外(OOD)的泛化和不同的构象状态。结构域运动通过允许在构象状态之间的灵活重排,如开闭转换,使蛋白质能够执行酶催化、配体结合和信号转导等基本功能。在区域运动基准中,BioEmu有效地采样了大规模的开闭转换,覆盖了参考实验结构(RMSD≤3 Å),对于已知构象变化的总体成功率为55%-90%。这种性能超过了AFCluster和DiG等基线,后者允许在单个GPU上进行以前不可行的基因组尺度蛋白质功能预测,揭示底物诱导的自由能转移和药物靶向的隐藏袋。通过将计算时间从几个月减少到几个小时,该平台可能会加速药物发现和生物技术,尽管更大的复合物仍然存在挑战。局部展开基准评估BioEmu模拟灵活区域的能力。Ras p21的开关II区在GTP/GDP结合时进行局部展开,其变化调节癌症相关的信号通路。 bioemu生成的结构表明在活性状态下形成短α-螺旋,但在非活性状态下仍部分展开。这些发现与实验数据一致。BioEmu通过预测隐口袋的开放状态,也揭示了在静态结构中难以进入的药物结合位点,从而加速了药物设计。在唾液酸结合因子中,该工具可以发现设计小分子抑制剂来阻断唾液酸结合的新位点,从而削弱细菌的生存能力,特别是有助于开发针对耐药菌株的新型抗生素。同时,在fasin蛋白中,开放状态暴露了新的结合位点,允许设计抑制剂来破坏其捆绑功能并抑制肿瘤细胞的迁移和转移。现有的研究已经开发出了fasin的抗转移抑制剂,而BioEmu可以快速模拟动态口袋来优化药物(例如通过虚拟筛选),这对于难以治疗的转移性癌症尤其有价值,因为传统的靶点(如激酶)已经饱和。BioEmu可以准确预测唾液酸结合因子和筋膜蛋白的口袋打开状态。抽样成功率从55%到80%不等。它优于AlphaFlow等模型,特别是在OOD蛋白上,后者似乎对未知或复杂的蛋白质更实用。蛋白质模拟中的热力学精度是指能够可靠地预测构象状态之间的自由能差(ΔG),决定这些状态在平衡状态下的概率。这是至关重要的,因为蛋白质的功能往往取决于状态之间的罕见转变,受温度、溶剂化和结合伙伴的影响。高精度确保模型能够量化稳定性和动态,将静态结构从AlphaFold等工具连接到功能洞察。如果没有这一特征,预测可能会错过低概率但生物学上关键的状态,导致对酶催化或信号传导等机制的不完整理解。BioEmu在定量预测任务中表现出优异的热力学精度。PPFT微调通过将实验稳定性数据(如熔化温度)转换为集合权重来实现这一点。这优化了低概率状态的采样。作者研究了数据规模如何影响准确性。随着总MD模拟时间从50毫秒增加到200毫秒,预测误差线性下降。这凸显了成本分摊策略的有效性,高昂的初始数据成本支持了大量蛋白质预测。PPFT算法是一项重要的方法论创新。它可以通过性能预测头(MLP)和扩散损失的联合优化来使用非结构化数据。具体来说,在微调过程中,它最大限度地减少了生成的样本属性(例如,ΔG)和实验标签之间的KL差异。这保证了分布的热力学一致性。与传统的监督学习不同,这种方法避免了过拟合,提高了对未知序列的泛化。在预测蛋白质稳定性方面,PPFT显著增强了模型拟合实验数据的能力,突出了其在优化集合分布和热力学精度方面的关键作用。在以前的蛋白质生成模型中,热力学约束的缺乏源于几个因素。首先,数据的可用性是有限的:像PDB这样的结构化数据库通常提供单一的、静态的构象,没有集合概率。通过实验或长时间MD模拟获得高通量热力学数据(例如,ΔG或ΔΔG)在计算上是禁止的。其次,在整合物理尺度时出现了方法上的挑战,例如在保持等方差的同时将模型概率与玻尔兹曼分布对齐。第三,评估规范倾向于几何度量(例如RMSD, TM-score)而不是热力学验证,后者更需要资源。最近的进展使显式热力学校准成为可能。这些包括大规模MD数据集、高通量稳定性分析、成熟的等变扩散/流动模型,以及药物设计和突变预测方面日益增长的需求。BioEmu通过将alphafold衍生的序列表示与等变扩散相结合来产生序列条件平衡集成。它根据大量的MD轨迹和实验数据进行校准,在相对自由能方面达到小于1 kcal/mol的精度。这标志着首次实现了在单gpu上以高吞吐量生成全蛋白集合的热力学缩放。然而,BioEmu主要针对单链蛋白。推广到更大的复合物(≥500个残基)、多链系统或长序列可能需要进一步优化。整合多模态实验数据,如低温电镜或单分子荧光,提出了额外的挑战[8]。 这突出了大型系统在采样和泛化方面的瓶颈。研究表明,通过更长的MD模拟和实
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引用次数: 0
PTGER4 Governs Immune Evasion and Therapy Resistance in Kidney Cancer via Ribosome Biogenesis Dysregulation PTGER4通过核糖体生物发生失调调控肾癌的免疫逃避和治疗抵抗。
IF 4.2 Pub Date : 2025-11-24 DOI: 10.1111/jcmm.70956
Hanjing Zhou, Zirui Li, Jun Ying, Yan Liu, Xuchun Xu, Jian Huang

Kidney renal clear cell carcinoma (KIRC) is associated with abnormal ribosome production (RiboSis), but how this affects tumour growth and response to immunotherapy is still unclear. In this study, we analysed large-scale multi-omics data using machine learning. Using single-cell RNA sequencing and gene network analysis (hdWGCNA), we found a key RiboSis-related gene group. We then classified KIRC tumours into two subtypes based on RiboSis activity. Patients with subtype 1 lived significantly longer, and this group showed activation of tumour-promoting pathways. Using machine learning, we identified PTGER4 as a potential tumour suppressor. Higher PTGER4 levels were linked to better survival in multiple patient groups. Tumours with high PTGER4 also had stronger immune cell activity and higher levels of immunotherapy-related markers, suggesting they may respond better to immune-based treatments. PTGER4 also predicted better outcomes with certain chemotherapy drugs. Further analysis confirmed that PTGER4 is involved in immune-related pathways and is often reduced in tumours, supporting its role in slowing cancer progression. Lab experiments confirmed that PTGER4 helps block tumour growth. These findings suggest PTGER4 plays a central role in KIRC progression and treatment response. Targeting RiboSis-related mechanisms and PTGER4-related pathways could lead to better therapies for KIRC patients.

肾透明细胞癌(KIRC)与异常核糖体产生(RiboSis)有关,但这如何影响肿瘤生长和对免疫治疗的反应尚不清楚。在这项研究中,我们使用机器学习分析了大规模的多组学数据。通过单细胞RNA测序和基因网络分析(hdWGCNA),我们发现了一个关键的核糖核酸相关基因群。然后,我们根据核糖核酸活性将KIRC肿瘤分为两种亚型。亚型1患者的寿命明显延长,并且该组显示肿瘤促进途径的激活。通过机器学习,我们发现PTGER4是一种潜在的肿瘤抑制因子。在多个患者组中,较高的PTGER4水平与更好的生存率有关。具有高PTGER4的肿瘤也具有更强的免疫细胞活性和更高水平的免疫治疗相关标志物,这表明它们可能对免疫治疗有更好的反应。PTGER4也预测了某些化疗药物的更好结果。进一步的分析证实,PTGER4参与免疫相关途径,在肿瘤中经常减少,支持其在减缓癌症进展中的作用。实验室实验证实,PTGER4有助于阻止肿瘤生长。这些发现表明PTGER4在KIRC进展和治疗反应中起核心作用。靶向ribosis相关机制和ptger4相关途径可能为KIRC患者带来更好的治疗方法。
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引用次数: 0
Unveiling the Role of circRNAs in Pyroptotic Signalling: From Molecular Crosstalk to Disease Modulation 揭示环状rna在热亡信号传导中的作用:从分子串扰到疾病调节。
IF 4.2 Pub Date : 2025-11-24 DOI: 10.1111/jcmm.70954
Tengyu Jin, Guodong Xu, Wanru Zhou, Yige Shi, Hebo Wang

Pyroptosis is a gasdermins-dependent programmed cell death (PCD) characterised by progressive cellular swelling and plasma membrane rupture (PMR). This process releases intracellular contents that amplify inflammatory cascades and immune activation, involving the pathogenesis of various disorders such as tumours, heart and vascular diseases, diabetic complications and inflammatory/infectious disorders. With the advancement of research, the regulatory role of noncoding RNA (ncRNA) in the pyroptosis pathway was delineated. Among, studies have demonstrated that circular RNAs (circRNAs) regulate the pyroptosis cascade mainly through three principal mechanisms: functioning as miRNA sponges, modulating protein activity and encoding functional polypeptides. Numerous circRNAs regulating pyroptosis have been characterised, indicating their significant role in this process and associated disease progression. This review systematically summarised current knowledge on the regulatory mechanisms of circRNAs in canonical, noncanonical and caspase-3/8-mediated pyroptosis pathways. We further discussed their pathophysiological roles in disease development and potential clinical applications, aiming to advance mechanistic understanding, facilitate clinical translation and inform diagnostic and therapeutic strategies.

焦亡是一种依赖于气真皮的程序性细胞死亡(PCD),其特征是进行性细胞肿胀和质膜破裂。这一过程释放细胞内内容物,放大炎症级联反应和免疫激活,涉及各种疾病的发病机制,如肿瘤、心脏和血管疾病、糖尿病并发症和炎症/感染性疾病。随着研究的深入,非编码RNA (ncRNA)在细胞焦亡通路中的调控作用逐渐明晰。其中,研究表明环状rna (circRNAs)主要通过miRNA海绵功能、调节蛋白活性和编码功能多肽三种主要机制调控焦亡级联。已经鉴定了许多调节焦亡的环状rna,表明它们在这一过程和相关疾病进展中起着重要作用。这篇综述系统地总结了circrna在规范、非规范和caspase-3/8介导的焦亡途径中的调控机制。我们进一步讨论了它们在疾病发展中的病理生理作用和潜在的临床应用,旨在促进机制理解,促进临床翻译,为诊断和治疗策略提供信息。
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