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.

Mitochondria, the primary energy-producing organelles of the cell, also serve as signaling hubs and participate in diverse physiological and pathological processes, including apoptosis, inflammation, oxidative stress, neurodegeneration, and tumorigenesis. As semi-autonomous organelles, mitochondrial functionality relies on nuclear support, with mitochondrial biogenesis and homeostasis being stringently regulated by the nuclear genome. This interdependency forms a bidirectional signaling network that coordinates cellular energy metabolism, gene expression, and functional states. During mitochondrial damage or dysfunction, retrograde signals are transmitted to the nucleus, activating adaptive transcriptional programs that modulate nuclear transcription factors, reshape nuclear gene expression, and reprogram cellular metabolism. This mitochondrion-to-nucleus communication, termed “mitochondrial retrograde signaling”, fundamentally represents a mitochondrial “request” to the nucleus to maintain organellar health, rooted in the semi-autonomous nature of mitochondria. Despite possessing their own genome, the “fragmented” mitochondrial genome necessitates reliance on nuclear regulation. This genomic incompleteness enables mitochondria to sense and respond to cellular and environmental stressors, generating signals that modulate the functions of other organelles, including the nucleus. Evolutionary transfer of mitochondrial genes to the nuclear genome has established mitochondrial control over nuclear activities via retrograde communication. When mitochondrial dysfunction or environmental stress compromises cellular demands, mitochondria issue retrograde signals to solicit nuclear support. Studies demonstrate that mitochondrial retrograde signaling pathways operate in pathological contexts such as oxidative stress, electron transport chain (ETC) impairment, apoptosis, autophagy, vascular tension, and inflammatory responses. Mitochondria-related diseases exhibit marked heterogeneity but invariably result in energy deficits, preferentially affecting high-energy-demand tissues like muscles and the nervous system. Consequently, mitochondrial dysfunction underlies myopathies, neurodegenerative disorders, metabolic diseases, and malignancies. Dysregulated retrograde signaling triggers proliferative and metabolic reprogramming, driving pathological cascades. Mitochondrial retrograde signaling critically influences tumorigenesis and progression. Tumor cells with mitochondrial dysfunction exhibit compensatory upregulation of mitochondrial biogenesis, excessive superoxide production, and ETC overload, collectively promoting metastatic tumor development. Recent studies reveal that mitochondrial retrograde signaling—mediated by altered metabolite levels or stress signals—induces epigenetic modifications and is intricately linked to tumor initiation, malignant progression, and therapeutic resistance. For instance, mitochondrial dysfunction promotes oncogenesis through mechanisms such as epigenetic dysregulation, accumulation of mitochondrial metabolic intermediates, and mitochondrial DNA (mtDNA) release, which activates the cytosolic cGAS-STING signaling pathway. In normal cells, miR-663 mediates mitochondrion-to-nucleus retrograde signaling under reactive oxygen species (ROS) regulation. Mitochondria modulate miR-663 promoter methylation, which governs the expression and supercomplex stability of nuclear-encoded oxidative phosphorylation (OXPHOS) subunits and assembly factors. However, dysfunctional mitochondria induce oxidative stress, elevate methyltransferase activity, and cause miR-663 promoter hypermethylation, suppressing miR-663 expression. Mitochondrial dysfunction also triggers retrograde signaling in primary mitochondrial diseases and contributes to neurodegenerative disorders such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). Current therapeutic strategies targeting mitochondria in neurological diseases focus on 5 main approaches: alleviating oxidative stress, inhibiting mitochondrial fission, enhancing mitochondrial biogenesis, mitochondrial protection, and insulin sensitization. In AD patients, mitochondrial morphological abnormalities and enzymatic defects, such as reduced pyruvate dehydrogenase and α-ketoglutarate dehydrogenase activity, are observed. Platelets and brains of AD patients exhibit diminished cytochrome c oxidase (COX) activity, correlating with mitochondrial dysfunction. To model AD-associated mitochondrial pathology, researchers employ cybrid technology, transferring mtDNA from AD patients into enucleated cells. These cybrids recapitulate AD-related mitochondrial phenotypes, including reduced COX activity, elevated ROS production, oxidative stress markers, disrupted calcium homeostasis, activated stress signaling pathways, diminished mitochondrial membrane potential, apoptotic pathway activation, and increased Aβ42 levels. Furthermore, studies indicate that Aβ aggregates in AD and α‑synuclein aggregates in PD trigger mtDNA release from damaged microglial mitochondria, activating the cGAS-STING pathway. This induces a reactive microglial transcriptional state, exacerbating neurodegeneration and cognitive decline. Targeting the cGAS-STING pathway may yield novel therapeutics for neurodegenerative diseases like AD, though translation from bench to bedside remains challenging. Such research not only deepens our understanding of disease mechanisms but also informs future therapeutic strategies. Investigating the triggers, core molecular pathways, and regulatory networks of mitochondrial retrograde signaling advances our comprehension of intracellular communication and unveils novel pathogenic mechanisms underlying malignancies, neurodegenerative diseases, and type 2 diabetes mellitus. This review summarizes established mitochondrial-nuclear retrograde signaling axes, their roles in interorganellar crosstalk, and pathological consequences of dysregulated communication. Targeted modulation of key molecules and proteins within these signaling networks may provide innovative therapeutic avenues for these diseases.

Pancreatic cancers (PCs) is a common malignant tumor with poor prognosis in the digestive system. Its main treatment methods include surgery, radiotherapy, chemotherapy, and targeted therapy. The early diagnosis rate of hidden onset of PCs is low, and most patients have already lost the opportunity to undergo surgery when diagnosed with PCs. Chemotherapy is still the main treatment for advanced PCs, but the use of chemotherapy drugs in PCs can easily lead to drug resistance. The most significant feature that distinguishes PCs from other tumors is its rich and dense matrix, which not only hinders drug penetration but also impedes the infiltration of immune cells. The above reasons have led to a very low survival rate of PCs patients. Therefore, drug delivery systems are very important in the diagnosis and treatment of PCs. They can improve drug delivery, enhance biological barrier penetration, reduce side effects, and combine multiple treatment methods. Therefore, the treatment prospects of PCs are very broad. Currently, drug delivery systems widely applied in PCs primarily include nanodrug delivery systems, tumor microenvironment-targeted drug delivery system, immunotherapy drug delivery system, gene therapy drug delivery system, and combination therapy drug delivery system that synergize multiple therapeutic modalities. Emerging drug delivery systems (DDSs) have revolutionized PCs treatment by addressing these challenges through multiple mechanisms. Nanoformulations improve drug solubility, prolong circulation time, and reduce systemic toxicity via passive/active targeting. Smart DDSs responsive to PCs-specific stimuli enable extracellular matrix degradation, tumor-associated fibroblasts reprogramming, and vascular normalization to enhance drug accessibility. Last but not least, carrier systems loaded with myeloid-derived suppressor cell inhibitors or T cell activators can reverse immunosuppression and potentiate immunotherapy efficacy. Advanced platforms co-deliver chemotherapeutics with immunomodulators, gene-editing tools, or sonodynamic agents to achieve synergistic antitumor effects. These platforms aim to address critical challenges in PCs treatment, such as enhancing drug bioavailability, overcoming stromal barriers, reprogramming immunosuppressive niches, and achieving multi-mechanistic antitumor effects. This article provides a systematic summary and prospective analysis of the current development status, latest cutting-edge advances, opportunities, and challenges of the above-mentioned drug delivery systems in the field of PCs therapy.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Pyroptosis is the programmed death of cells accompanied by an inflammatory response and is widely involved in the development of a variety of diseases, such as infectious diseases, cardiovascular diseases, and neurodegeneration. It has been shown that cellular scorching is involved in the pathogenesis of pulmonary arterial hypertension ( PAH) in cardiovascular diseases. Patients with PAH have perivascular inflammatory infiltrates in lungs, pulmonary vasculopathy exists in an extremely inflam-matory microenvironment, and pro-inflammatory factors in cellular scorching drive pulmonary vascular remodelling in PAH patients. This article reviews the role of cellular scorch in the pathogenesis of PAH and the related research on drugs for the treatment of PAH, with the aim of providing new ideas for clinical treatment of PAH.

ObjectiveExosomes are microvesicles which could be secreted by all cell types with diameters between 30 and 150 nm. It was widely distributed in body fluids including blood, urine, and breast milk. Exosomes are considered as potential biomarkers and drug carriers by reason of containing nucleic acids, lipids, proteins and other bioactive molecules. Milk-derived exosomes have been widely used as drug delivery carriers to treat targeted diseases with a lower cost, higher biocompatibility and lower immunogenicity. Until now, there is no research about the milk-derived exosomes phosphorylation to reveal the difference of protein phosphorylation in different species of milk. To investigate the pathways and proteins with specific functions, phosphorylated proteomic analysis of milk-derived exosomes from different species is performed, and provide new ideas for exploring diversified treatments of disease. MethodsWhey and exosomes derived from bovine, porcine and caprine milk were performed for proteomics and phosphoproteomics analysis. The relationship between milk exosome proteins from different species and signaling pathways were analyzed using bioinformatics tools. ResultsA total of 4 191 global proteins, 1 640 phosphoproteins and 4 064 phosphosites were identified from 3 species of milk-derived exosomes, and the exosome proteins and phosphoproteins from different species were significantly higher than those of whey. Meanwhile, some special pathways were enriched like Fcγ-mediated phagocytosis from bovine exosomes, pathways related with neural and immune system from caprine exosomes, positive and negative regulation of multiple activities from porcine exosomes. ConclusionIn this study, the proteomic and phosphoproteomic analyses of exosomes and whey from bovine, porcine and caprine milk were carried out to reveal the difference of composition and related signaling pathways of milk exosome from different species. These results provided powerful support for the application of exosomes from different milk sources in the field of disease treatment.

Objective:To explore the prognostic value of MUC13 expression in gastric cancer(GC)patients and its impact on the biological behavior of GC cells.Methods:Comprehensive anal-ysis of the expression pattern of MUC genes in GC tissues based on the TCGA database to screen for differentially expressed genes.Spearman correlation analysis determined the correlation of ex-pression between MUC genes in GC tissues.Gene Ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway(KEGG)enrichment analysis were used to explore the potential biological functions of MUC genes.Univariate COX regression analysis was performed to explore the relationship between all differentially expressed MUC genes and the prog-nosis of GC patients to screen out MUC genes that were significantly related to the prognosis of GC.Clinical GC tissue samples were used to further verify the expression of MUC13 through im-munofluorescence,and its relationship with the clinicopathological characteristics and prognosis of GC was analyzed.siRNA was used to silence the expression of MUC13 in GC cells,and the effect of MUC13 on cell proliferation,migration and invasion was analyzed through CCK-8,colony forma-tion and Transwell experiments.Results:Among all MUC members,the expression levels of MUC1,MUC2,MUC3A,MUC4,MCU5B,MUC12,and MUC13 were significantly upregulated in GC tissues(P＜0.05).There are certain interactions between these MUC genes,and they are mainly en-riched in pathways related to digestive system processes,epithelial structure maintenance,apical plasma membrane,saliva secretion,etc.Importantly,upregulation of MUC13 in GC tissues indicates poor patient prognosis(Log-rank P＜0.05).In addition,MUC13 expression was significantly correlat-ed with the age(P＜0.001)of GC patients and tumor size(P=0.035).Further cell function experiments showed that after silencing MUC13,the proliferation ability of GC cells was significantly reduced(P＜0.05),while their migration and invasion abilities were not significantly affected(P＞0.05).Con-clusions:Highly expressed MUC13 is closely related to the poor prognosis of gastric cancer,par-ticipates in the regulation of tumor progression and is a potential therapeutic target and prognostic marker for gastric cancer.

Objective To systematically evaluate the efficacy and safety of single and bilateral lung transplantation in the treatment of end-stage chronic obstructive pulmonary disease (COPD). Methods Chinese and English databases were searched by computer, including PubMed, Web of Science, The Cochrane Library, EMbase, CNKI, Wanfang database, VIP database and CBM. Case-control studies on single lung transplantation or bilateral lung transplantation for COPD were collected from the inception to July 31, 2022. We evaluated the quality of the literature via Newcastle-Ottawa Scale (NOS). All results were analyzed using Review Manager V5.3 and STATA 17.0. Results A total of 8 studies were included covering 14076 patients, including 8326 patients in the single lung transplantation group and 5750 patients in the bilateral lung transplantation group. NOS scores were≥6 points. The results of meta-analysis showed that there was no statistical difference in the postoperative 1-year survival between the two groups (P=0.070). The 2-year survival rate (P=0.002), 3-year survival rate (P<0.001), 5-year survival rate (P<0.001), overall survival rate (P＜0.001), postoperative forced expiratory volume in one second/predicted value (P<0.001), postoperative forced vital capacity (P<0.001), and postoperative 6-minute walking distance (P=0.002) were lower or shorter than those in the bilateral lung transplantation group, the postoperative intubation time (P=0.030) was longer than that in the bilateral lung transplantation group. Bilateral lung transplantation group showed better surgical results. There was no statistical difference in the mortality, obliterative bronchiolitis, length of hospitalization, primary graft dysfunction, or postoperative adverse events (P>0.05). Conclusion Bilateral lung transplantation is associated with better long-term survival and postoperative lung function compared with single lung transplantation. In-hospital mortality and postoperative complications are similar between them.

BACKGROUND:Studies have exhibited that inhibiting apoptosis caused by endoplasmic reticulum stress can save part of nerve function.Epigallocatechin-3-gallate can inhibit endoplasmic reticulum stress,but it has poor bioavailability and is difficult to penetrate the blood-brain barrier.In combination with exosomes targeting spinal cord repair and high-potency drug loading,theoretically,the combination of the two can play a greater role in spinal cord protection. OBJECTIVE:To investigate the effects of epigallocatechin-3-gallate combined with bone marrow mesenchymal stem cell exosomes on endoplasmic reticulum stress and neurological function in rats with spinal cord ischemia/reperfusion injury. METHODS:Fifty SD male rats were randomly divided into sham surgery group,model group,epigallocatechin-3-gallate group,exosome group,and combined treatment group,with 10 rats in each group.The spinal cord ischemia/reperfusion injury model was made in the other four groups except for the sham surgery group.Local injection of physiological saline,exosomes,epigallocatechin-3-gallate,epigallocatechin-3-gallate + bone marrow mesenchymal stem cell exosomes was performed 2 hours after surgery through a caudal vein.Neurological function scores were performed on 7,14 and 28 days after spinal cord injury.14 days after spinal cord injury,hematoxylin-eosin staining,Nissl staining,and immunofluorescence staining of endoplasmic reticulum stress markers such as ATF6 and GADD153 were performed in the spinal cord tissues. RESULTS AND CONCLUSION:(1)Compared with the sham surgery group,neurological function scores of the model group,exosome group,epigallocatechin-3-gallate group and combined treatment group all decreased to different degrees.The neurological function score of combined treatment group was better than that of the epigallocatechin-3-gallate group,exosome group and model group 14 days after surgery(P<0.05).The neurological function score of the combined treatment group was better than that of the model group and epigallocatechin-3-gallate group 28 days after surgery(P<0.05).(2)Hematoxylin-eosin staining and Nissl staining displayed that the number of neurons in the model group decreased,with a large number of cavity necrosis and scar hyperplasia in the spinal cord injury area.The number of neurons and peripheral cavity necrosis improved to varying degrees in the epigallocatechin-3-gallate group,exosome group,and combined treatment group,with the most significant improvement in the combined treatment group.(3)The expression of endoplasmic reticulum stress-related proteins ATF6 and GADD153:14 days postoperatively,the expression of GADD153 in the combined treatment group was lower than that in the model group and epigallocatechin-3-gallate group(P<0.05),and the expression of ATF6 in the combined treatment group was lower than that in the model group,exosome group,and epigallocatechin-3-gallate group(P<0.05).(4)These findings confirm that epigallocatechin-3-gallate combined with bone marrow mesenchymal stem cell exosome can enhance the neurological function in rats with spinal cord ischemia/reperfusionn injury,which may be associated with the inhibition of the expression of endoplasmic reticulum stress-related proteins ATF6 and GADD153.

Objective To compare the effects of two arc(TA)and dual arc(DA)techniques on the dose distribution to the planning target volume(PTV)and organs at risk(OAR)in volumetric modulated arc therapy(VMAT)for lower mid-thoracic esophageal cancer.Methods Ten patients with lower mid-thoracic esophageal cancer who received radiation therapy at some hospital from July 2020 to June 2022 were selected retrospectively.A TA radiation therapy plan and a DA radiation therapy plan were developed for each patient using the Ray Arc module of RayStation 4.7.5.4 planning system,and the two kinds of radiation plans were compared in terms of dosimetric parameters including D2,D5,D50,D95,D98,homogeneity index(HI),conformity index(CI),beam-on time and total monitor unit for PTV and lung V5,V10,V20,V30 and Dmean and heartV30,V40 and Dmean and spine cord Dmax for OAR.SPSS 22.0 was used for statistical analysis.Results TA and DA radiation therapy plans had no significant differences in PTV CI,HI,D2,D5,D50,D95 and beam-on time(P＞0.05),and DA plan had D98 and total monitor unit higher obviously than those of TA plan(P＜0.05).In terms of OARs protection,DA plan had heart V30,V40 and Dmean slightly lower than those of TA plan with non-significantly differences(P＞0.05),while lung V5,V30 and Dmean and spine cordDmax significantly lower(P＜0.05).Conclusion DA technique gains advantages over TA technique in PTV dose distribution and dose to OAR,and the involvement of DA technique in preparing the VMAT plan for esophageal cancer contributes to enhancing the treatment efficacy.[Chinese Medical Equipment Journal,2024,45(1):62-66]