Mitochondria, functioning not only as the central hub of cellular energy metabolism but also as semi-autonomous organelles, orchestrate cellular fate decisions through their endogenous mitochondrial DNA (mtDNA), which encodes core components of the electron transport chain. Emerging research has identified microRNAs localized within mitochondria, termed mitochondria-located microRNAs (mitomiRs). Recent studies have revealed that mitomiRs are transcribed from nuclear DNA (nDNA), processed and matured in the cytoplasm, and subsequently transported into mitochondria. mitomiRs regulate mtDNA through diverse mechanisms, including modulation of mtDNA expression at the translational level and direct binding to mtDNA to influence transcription. Aberrant expression of mitomiRs leads to mitochondrial dysfunction and contributes to the pathogenesis of metabolic diseases. Restoring mitomiR expression to physiological levels using mitomiRs mimics or inhibitors has been shown to improve mitochondrial function and alleviate related diseases. Consequently, the regulatory mechanisms of mitomiRs have become a major focus in mitochondrial research. Given that mitomiRs are located in mitochondria, targeted delivery strategies designed for mtDNA can be adapted for the delivery of mitomiRs mimics or inhibitors. However, numerous intracellular and extracellular barriers remain, highlighting the need for more precise and efficient delivery systems in the future. The regulation of mtDNA expression mediated by mitomiRs not only expands our understanding of miRNA functions in post-transcriptional gene regulation but also provides promising molecular targets for the treatment of mitochondrial-related diseases. This review systematically summarizes recent research progress on mitomiRs in regulating mtDNA expression and discusses the underlying mechanisms of mitomiRs-mtDNA interactions. Additionally, it provides new perspectives on precision therapeutic strategies, with a particular emphasis on mitomiRs-based regulation of mitochondrial function in mitochondrial-related diseases.

Optical imaging is highly valued for its superior temporal and spatial resolution. This is particularly important in near-infrared II (NIR-II, 1 000-3 000 nm) imaging, which offers advantages such as reduced tissue absorption, minimal scattering, and low autofluorescence. These characteristics make NIR-II imaging especially suitable for deep tissue visualization, where high contrast and minimal background interference are critical for accurate diagnosis and monitoring. Currently, inorganic fluorescent probes—such as carbon nanotubes, rare earth nanoparticles, and quantum dots—offer high brightness and stability. However, they are hindered by ambiguous structures, larger sizes, and potential accumulation toxicity in vivo. In contrast, organic fluorescent probes, including small molecules and polymers, demonstrate higher biocompatibility but are limited by shorter emission wavelengths, lower quantum yields, and reduced stability. Recently, gold clusters have emerged as a promising class of nanomaterials with potential applications in biocatalysis, fluorescence sensing, biological imaging, and more. Water-soluble gold clusters are particularly attractive as fluorescent probes due to their remarkable optical properties, including strong photoluminescence, large Stokes shifts, and excellent photostability. Furthermore, their outstanding biocompatibility—attributed to good aqueous stability, ultra-small hydrodynamic size, and high renal clearance efficiency—makes them especially suitable for biomedical applications. Gold clusters hold significant potential for NIR-II fluorescence imaging. Atomic-precision gold clusters, typically composed of tens to hundreds of gold atoms and measuring only a few nanometers in diameter, possess well-defined three-dimensional structures and clear spatial coordination. This atomic-level precision enables fine-tuned structural regulation, further enhancing their fluorescence properties. Variations in cluster size, surface ligands, and alloying elements can result in distinct physicochemical characteristics. The incorporation of different atoms can modulate the atomic and electronic structures of gold clusters, while diverse ligands can influence surface polarity and steric hindrance. As such, strategies like alloying and ligand engineering are effective in enhancing both fluorescence and catalytic performance, thereby meeting a broader range of clinical needs. In recent years, gold clusters have attracted growing attention in the biomedical field. Their application in NIR-II imaging has led to significant progress in vascular, organ, and tumor imaging. The resulting high-resolution, high signal-to-noise imaging provides powerful tools for clinical diagnostics. Moreover, biologically active gold clusters can aid in drug delivery and disease diagnosis and treatment, offering new opportunities for clinical therapeutics. Despite the notable achievements in fundamental research and clinical translation, further studies are required to address challenges related to the standardized synthesis and complex metabolic behavior of gold clusters. Resolving these issues will help accelerate their clinical adoption and broaden their biomedical applications.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective To observe the effects of amyloid-β(Aβ)receptor PirB on mouse astrocyte proliferation and reactive astrogliosis in vitro.Methods Mouse primary astrocytes were cultured,and divided into control group,Aβ group,Aβ+0.2 μmol/L PEP group,Aβ+0.4 μmol/L PEP group,Aβ+Fluspirilene group,Aβ+GFP-LV group,and Aβ+mPirB-LV group.The mouse astrocytes were treated with soluble PirB extracellular peptide PEP or PirB inhibitor Fluspirilene,respectively,to inhibit endogenous PirB receptor,or overexpressed PirB gene via lentivirus transfection and then treated with Aβ1-42 oligomers.The proliferation of astrocytes was observed by RTCA and EdU methods,and the mRNA expression levels of S-100 calcium-binding protein B(S-100β),Vimentin,Nestin and amyloid precursor protein(APP)associated with reactive astrogliosis of astrocytes were observed by real-time PCR,and the expression level of glial fibrillary acid protein(GFAP)was detected by Western-blotting.Results The results of RTCA monitoring showed that normalized cell index(NCI)values of each group decreased sharply after treatment,and then increased gradually and tended to be stable.The results of EdU staining showed that the proliferative activity of astrocytes was significantly enhanced in the Aβ group(P<0.05)compared with control group;Compared with Aβ group,cell proliferation activity in Aβ + 0.2 μmol/L PEP group,Aβ+0.4 μmol/L PEP group and Aβ+Fluspirilene group were significantly decreased(P<0.01 or P<0.001).The results of real-time PCR showed that compared with control group,mRNA expressions of GFAP,S-100β,Vimentin,Nestin,APP and PirB in Aβ group were significantly increased(P<0.05);Compared with Aβ group,mRNA expressions of GFAP,S-100β,Vimentin,Nestin,APP and PirB in Aβ+0.4 μmol/L PEP group were significantly decreased(P<0.01);Compared with Aβ+GFP-LV group,mRNA expressions of GFAP,S-100β,Vimentin,Nestin,APP and PirB in Aβ +mPirB-LV group were significantly increased(P<0.05).The results of Western blotting showed that compared with control group,the expression of GFAP in Aβ group was significantly increased(P<0.05);Compared with Aβ group,the expression of GFAP in Aβ+0.4 μmol/L PEP group was significantly decreased(P<0.05).Conclusions PirB is an upstream molecule which could regulate astrocyte proliferation and reactive astrogliosis,and inhibiting PirB receptor in astrocytes may be a potential treatment for Alzheimer's disease.

The advent of gene editing represents one of the most transformative breakthroughs in life science, making genome manipulation more accessible than ever before. While traditional CRISPR/Cas-based gene editing, which involves double-strand DNA breaks (DSBs), excels at gene disruption, it is less effective for accurate gene modification. The limitation arises because DSBs are primarily repaired via non-homologous end joining (NHEJ), which tends to introduce indels at the break site. While homology-directed repair (HDR) can achieve precise editing when a donor DNA template is provided, the reliance on DSBs often results in unintended genome damage. HDR is restricted to specific cell cycle phases, limiting its application. Currently, gene editing has evolved to unprecedented levels of precision without relying on DSB and HDR. The development of innovative systems, such as base editing, prime editing, and CRISPR-associated transposases (CASTs), now allow for precise editing ranging from single nucleotides to large DNA fragments. Base editors (BEs) enable the direct conversion of one nucleotide to another, and prime editors (PEs) further expand gene editing capabilities by allowing for the insertion, deletion, or alteration of small DNA fragments. The CAST system, a recent innovation, allows for the precise insertion of large DNA fragments at specific genomic locations. In recent years, the optimization of these precise gene editing tools has led to significant improvements in editing efficiency, specificity, and versatility, with advancements such as the creation of base editors for nucleotide transversions, enhanced prime editing systems for more efficient and precise modifications, and refined CAST systems for targeted large DNA insertions, expanding the range of applications for these tools. Concurrently, these advances are complemented by significant improvements in in vivo delivery methods, which have paved the way for therapeutic application of precise gene editing tools. Effective delivery systems are critical for the success of gene therapies, and recent developments in both viral and non-viral vectors have improved the efficiency and safety of gene editing. For instance, adeno-associated viruses (AAVs) are widely used due to their high transfection efficiency and low immunogenicity, though challenges such as limited cargo capacity and potential for immune responses remain. Non-viral delivery systems, including lipid nanoparticles (LNPs), offer an alternative with lower immunogenicity and higher payload capacity, although their transfection efficiency can be lower. The therapeutic potential of these precise gene editing technologies is vast, particularly in treating genetic disorders. Preclinical studies have demonstrated the effectiveness of base editing in correcting genetic mutations responsible for diseases such as cardiomyopathy, liver disease, and hereditary hearing loss. These technologies promise to treat symptoms and potentially cure the underlying genetic causes of these conditions. Meanwhile, challenges remain, such as optimizing the safety and specificity of gene editing tools, improving delivery systems, and overcoming off-target effects, all of which are critical for their successful application in clinical settings. In summary, the continuous evolution of precise gene editing technologies, combined with advancements in delivery systems, is driving the field toward new therapeutic applications that can potentially transform the treatment of genetic disorders by targeting their root causes.

Sustained and controlled release preparation is ideal for reducing the side effects of drugs, improving patient compliance and enhancing efficacy, among which oral sustained-release tablets are the most widely used. The in vitro release of the preparation is closely related to the in vivo absorption of the drug. However, current in vitro release experiments are labor-intensive and destructive, and the lack of big data also makes it difficult to establish good in vivo and in vitro correlations. Computer modeling, as a technical means that can transform objective principles into mathematical models, has great prospects in data prediction. This review explores the existing computer modeling methods that can be used to predict in vitro release profiles of oral sustained-release tablets, and further discusses auxiliary technologies that can improve the accuracy of the models, providing new ideas for drug development.

The incidence of intrahepatic cholangiocarcinoma (ICC) continues to rise, and there are no effective drugs to treat it. The immune microenvironment plays an important role in the development of ICC and is currently a research hotspot. Icaritin (ICA) is an innovative traditional Chinese medicine for the treatment of advanced hepatocellular carcinoma. It is considered to have potential immunoregulatory and anti-tumor effects, which is potentially consistent with the understanding of "Fuzheng" in the treatment of tumor in traditional Chinese medicine. However, whether ICA can be used to treat ICC has not been reported. Therefore, in this study, sgp19/kRas, an in situ ICC mouse model with intact immune system, was selected to evaluate the efficacy of ICA in the treatment of ICC in vivo for the first time, and the effects of ICA on the tumor immune microenvironment of ICC mice were analyzed by flow cytometry. This experiment was approved by the Experimental Animal Ethics Committee of Capital Medical University (approval number: AEEI-2023-138). In this study, sgp19/kRas ICC mouse model was treated with oral gavage of 100 mg·kg^-1 ICA. We found that ICA significantly inhibited tumor growth and tumor cell proliferation in the sgp19/kRas ICC mouse model after 3 weeks of treatment. Flow cytometry analysis indicated that ICA treatment markedly reduced the proportion of M2 macrophages and increased the number of CD3⁺CD4⁺ T cells. In vitro experiments demonstrated that ICA promoted macrophage polarization towards the M1 phenotype while inhibiting polarization towards the M2 phenotype. Furthermore, transcriptomic analysis suggested that ICA enhanced Toll-like receptor 9 (TLR9) expression, influencing macrophage nitric oxide metabolism synthesis pathways and receptor-related activities, thereby regulating macrophage polarization. In summary, this study demonstrates that ICA treatment significantly delays tumor progression in sgp19/kRas ICC mouse models. Mechanistically, ICA may achieve its anti-ICC effects by upregulating TLR9 receptor expression levels, promoting macrophage polarization towards the M1 phenotype, and altering the tumor immune microenvironment.

Objective To investigate disease characteristics and hospitalization costs of children with Mycoplasma Pneumoniae pneumonia(MPP)admitted to Shanghai municipal medical hospitals from 2019 to 2023.Methods Depending on the Shanghai Municipal Hospital Pediatric Alliance,we retrospectively investigated community acquired MPP pediatric patients hospitalized in 22 municipal hospitals with pediatric qualifications(including 4 children's hospitals)in Shanghai from Jan 2019 to Dec 2023.We collected the patients'diagnosis codes,gender,age,length of hospital stay,hospitalization costs,and whether they progressed to severe Mycoplasma pneumoniae pneumonia(SMPP).Results From 2019 to 2023,a total of 29 045 hospitalized children with MPP were treated,with 6 035 cases(20.8%)identified as SMPP in the 22 hospitals.Trend analysis revealed a rising trend with years in the proportion of SMPP patients(χ2trend=365.498,P<0.001).Among the 4 children's hospitals,there were 18 710 cases with MPP,including 4 078 cases(21.8%)of SMPP.The proportion of SMPP patients also showed an increasing trend with years(χ2trend=14.548,P<0.001),and the proportion in 2023(23.0%)was higher than that in previous years with statistical significance.There were statistical differences in the seasonal distribution of MPP cases between different years,with higher proportions in summer and autumn overall.The age distribution of hospitalized MPP children varied among different years,with school-age children accounting for the majority(56.8%)in 2023.There was no difference in the distribution of severe cases between different genders,but there were differences in the proportion of severe cases among different age groups in different years,with a gradual increase in severe cases among children aged 1 to 3 years(χ2trend=191.567,P<0.001).The average length of hospital stay for MPP during the epidemic was higher than that during non-epidemic periods,and there were statistically significant differences in the average length of hospital stay between different years(P<0.001).The individual hospitalization costs during the epidemic were higher than in other years,and there were statistically significant differences in individual hospitalization costs between different years(P<0.001).The total hospitalization costs were still higher in 2019 and 2023.The individual hospitalization costs for SMPP were higher than for non-SMPP cases.Conclusion MPP outbreaks occurred in Shanghai in 2019 and 2023,with the higher proportions in summer and autumn overall.Compared to previous years,the number of hospitalized MPP children in Shanghai was higher in 2023,with a higher proportion of SMPP cases,especially among children under 3 years old.The individual per capita hospitalization expenses for SMPP cases were higher than for non-SMPP cases.

Objective To analyze the stress changes of thoracic vertebra(T)11-sacrum(S)titanium rods in patients with ankylosing spondylitis after vertebral column decancellation(VCD)osteotomy,and provide reference for the selection and improvement of titanium rods before surgery.Methods The original data of the continuous scanning tomographic images of patients with ankylosing spondylitis after VCD osteotomy were imported into Mimics 21.0 in DICOM format,and T11-S vertebrae,screws and titanium rods were respectively reconstructed.They were imported into 3-Matic to establish a preliminary geometric modeling,and then processed with noise removal,paving,smoothing,etc.The improved model was imported into Hypermesh 10 software for grid division,and the material was imported into ANSYS 19.2 to display the finite element model after attribute assignment,Set the boundary and load conditions,and measure the stress value at the connection between the screw and the titanium rod.Results Under neutral position,forward bending,lateral bending,and axial rotation conditions,the titanium rod had the highest stress at the upper vertebrae(T11)and the lowest stress at the top vertebrae(L3);Under the backward extension condition,the titanium rod has the highest stress at the lower end vertebra(L5).Conclusion In the upper and lower vertebrae,it is possible to consider increasing the diameter of the titanium rod,enhancing its hardness,or changing it to a double rod.

Objective Pancreatic cancer(PC)is a malignant tumor of the digestive tract that is difficult to diagnose early,easily metastasizes and relapses,and resistant to conventional chemotherapy.PC is a very difficult disease to treat.The key regulatory factors of PC resistance,such as epithelial-mesenchymal transition phenotypic cells,tumor stem cells,and miRNAs,have been reviewed in the past few years,and some new regulatory factors have been discovered as supplements.This review mainly focuses on the characteristics and properties of the key regulatory factors of PC chemotherapy resistance including long noncoding RNAs,nuclear factor KB and exosomes,drug resistance mechanisms,and treatment related strategies,and future treatment directions were predicted.