Objective To observe the efficacy of self-made auxiliary reduction device combined with sinus tarsi approach(STA)in the treatment of Sanders type Ⅱ to Ⅳ calcaneal fractures.Methods A total of 40 patients with Sanders type Ⅱ to Ⅳ calcaneal fractures admitted to our hospital from January to June 2023 were selected and divided into the control group and the observation group by the random number table method,with 20 cases in each group.Patients in the control group underwent surgical treatment with the heel extensile lateral approach(ELA),while patients in the observation group underwent surgical treatment with the auxiliary reduction device combined with STA.The surgical-related indicators,postoperative complications and ankle-foot anatomical indicators of patients in the two groups were compared.The recovery of limb function was evaluated by the American Orthopaedic Foot and Ankle Society(AOFAS)ankle-hindfoot scale and Maryland foot function score.Results There was no statistically significant difference in the operation time,postoperative incision drying time,or duration of postoperative pain between the two groups(P>0.05).The postoperative suture removal time of the patients in the observation group was shorter than that of the control group,and the difference was statistically significant(P<0.05).The incidence of skin edge necrosis of incision and the total incidence of complications of patients in the observation group were significantly lower than those in the control group(P<0.05).The B?hler angle and Gissane angle of patients in both groups increased after surgery compared with those before surgery(P<0.05);there was no statistically significant difference in the B?hler angle or Gissane angle after surgery of patients between the two groups(P>0.05).The AOFAS score1 week after surgery of the patients in the observation group was higher than that in the control group(P<0.05),while there were no statistically significant differences in the AOFAS scores or Maryland scores of patients at other time points between the two groups(P>0.05).Conclusion The use of the auxiliary reduction device in surgical treatment with STA for Sanders type Ⅱ to Ⅳ calcaneal fractures can effectively restore the function of the foot and ankle,with short postoperative suture removal time and low incidence of postoperative complications.

This paper reported a case of fetal congenital chloride diarrhea (CCD) indicated by prenatal ultrasound and confirmed by whole-exome sequencing. At 26 weeks and two days of gestation, a routine prenatal ultrasound revealed fetal bowel dilation and numerous floating echogenic particles in the amniotic fluid, suggesting the possibility of CCD. Multiple follow-up ultrasounds in late pregnancy showed persistent bowel dilation, polyhydramnios with numerous floating echogenic particles, and fetal development larger than the gestational age. Whole-exome sequencing and Sanger validation revealed two compound heterozygous mutations in the fetal SLC26A3 gene: c.2006C>A (p.S669*) inherited from the mother and c.1355T>A (p.L452Q) inherited from the father, leading to a diagnosis of CCD. Postnatally, the infant exhibited persistent watery diarrhea. Based on prenatal ultrasound and diagnostic results, the infant was immediately given intravenous and oral electrolyte supplementation after birth, preventing severe electrolyte imbalance. As of June 2024, the infant was five months old, with follow-up showing good growth and development.

Objective To analyze the gene expression characteristics of chronic rhinosinusitis with nasal polyps(CRSwNP)using bioinformatics methods,aim to investigate the potential biomarkers and their diagnostic value of CRSwNP.Methods(1)The CRSwNP Gene expression data set was downloaded from the American Gene Expression Omnibus(GEO)database.The differentially expressed genes(DEGs)between CRSwNP patients and healthy controls were screened through data analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were performed on the identified DEGs.Protein-protein interaction(PPI)networks were constructed utilizing the STRING database,and the key genes were identified by using the cytoHubba plugin.The"Cibersort"package was used to analyze the influence of key genes on common immune cells.(2)Thirty-two patients diagnosed with CRSwNP in the First Affiliated Hospital of Hebei North University from June 2022 to June 2023 were selected as the CRSwNP group,and 21 patients with simple deviation of nasal septum without a history of sinusitis during the same period were selected as control group.The pathological characteristics of specimens in the two groups were examined using hematoxylin-eosin(HE)staining.Immunohistochemistry and Western blotting were used to detect the expression levels of key genes in CRSwNP.The levels of key proteins in plasma were detected using ELISA,and ROC curve was used to analyze its efficacy in diagnosing CRSwNP.Results(1)Analysis of three gene expression database sets(GSE36830,GSE23552,and GSE194282)showed that there were 156 DEGs in CRSwNP.GO functional enrichment and KEGG pathway analysis indicated that the functions of the above DEGs were mostly related to immune functions.Key genes such as cytochrome b-245 β chain(CYBB)and colony-stimulating factor 1 receptor(CSF1R)were identified.(2)The results of HE staining revealed that the epithelial of CRSwNP tissue was metaplastic into stratified squamous epithelium with interstitial edema.Both immunohistochemistry and Western blotting analyses indicated that the expression levels of CYBB and CSF1R in the CRSwNP group were significantly increased compared to control group(P＜0.05).ELISA results demonstrated that CYBB[(21.20±3.00)μg/ml vs.(17.66±1.66)μg/ml,P＜0.05]and CSF1[(477.37±86.63)pg/ml vs.(370.71±66.24)pg/ml,P＜0.05]in CRSwNP group were significantly increased compare to control group.ROC curve analysis showed that plasma concentrations of CYBB and CSF1 had AUCs of 0.888(95%CI 0.802-0.974)and 0.821(95%CI 0.711-0.931)for diagnosing of CRSwNP,respectively;their combined AUC was 0.927(95%CI 0.851-1.000).Conclusions CYBB and CSF1R may be involved in the occurrence and development of CRSwNP.Plasma CYBB and CSF1 have high diagnostic value for CRSwNP.

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.

The innate immune sensor NLRP3 inflammasome overactivation is involved in the pathogenesis of ulcerative colitis. PGAM5 is a mitochondrial phosphatase involved in NLRP3 inflammasome activation in macrophages. However, the role of PGAM5 in ulcerative colitis and the mechanisms underlying PGAM5 regulating NLRP3 activity remain unknown. Here, we show that PGAM5 deficiency ameliorates dextran sodium sulfate (DSS)-induced colitis in mice via suppressing NLRP3 inflammasome activation. By combining APEX2-based proximity labeling focused on PGAM5 with quantitative proteomics, we identify NEK7 as the new binding partner of PGAM5 to promote NLRP3 inflammasome assembly and activation in a PGAM5 phosphatase activity-independent manner upon inflammasome induction. Interfering with PGAM5-NEK7 interaction by punicalagin inhibits the activation of the NLRP3 inflammasome in macrophages and ameliorates DSS-induced colitis in mice. Altogether, our data demonstrate the PGAM5-NEK7 interaction in macrophages for NLRP3 inflammasome activation and further provide a promising therapeutic strategy for ulcerative colitis by blocking the PGAM5-NEK7 interaction.

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.

Risks of food safety induced by small molecule drug residues in animal food and environment have become an increasing public concern,so it is necessary to develop highly sensitive and easy-to-operate techniques to detect small molecules.Herein,a metasurface plasma resonance(MetaSPR)sensor chip coupled with gold nanoparticles(AuNPs)was developed for detection of enrofloxacin(ENR)based on competitive immunoassay.The detection range of the sensor for ENR was 0.025-3.2 ng/mL,and the detection limit(3σ)was 20 pg/mL.The biosensor showed excellent performance including high selectivity,good stability,ease to operate and high throughput,etc.The developed method was applied to detection of ENR residues in real samples,with recoveies of 96.0% -105.0%.The proposed sensing strategy provided new technique reference for detection of other small molecules in the field of residue analysis in food safety and environment monitoring.

AIM To optimize the extraction process for total polyphenols from Conioselinum vaginatu(Spreng.)Thell.,make component analysis,and evaluate their anti-oxidant,hypoglycemic activities.METHODS The effects of ultrasound,enzymatic hydrolysis,acid hydrolysis,alcohol extraction and hydrolysis processes on the extraction quantity of total polyphenols were investigated,respectively.With extraction temperature,extraction time,ethanol concetration and liquid-solid ratio as influencing factors,extraction quantity of total polyphenols as an evaluation index,the extraction process was optimized by response surface method.HPLC was adopted in the identification of polyphenolic composition and determination of their contents.Subsequently,total polyphenols' scavenging capacities on DPPH,ABTS,OH free radicals,total reducing power and inhibitory capacity on α-glucosidase were determined.RESULTS The highest extraction quantity of total polyphenols was observable when extraction process was employed.The optimal conditions were determined to be 62 ℃ for extraction temperature,54 min for extraction time,69％for ethanol concentration,and 50∶1 for liquid-solid ratio,the extraction quantity of total polyphenols was(9.51±0.2)mg GAE/g.Seven constituents existed in C.vaginatu,among which ferulic acid demonstrated the highest content,followed by that of myricetin,while D-tryptophan content was the lowest.At the concentration of 7.61 mg/L,total polyphenols displayed the scavenging rates on DPPH,ABTS,OH free radicals of 80.70％,85.97％,28.60％,total reducing power of 0.22,and inhibition rate on α-glucosidase of 77.23％,respectively.CONCLUSION This stable and reliable method can be used for the extraction of total polyphenols from C.vaginatum with strong anti-oxidant,hypoglycemic activities.