ObjectiveTo observe the effect of Yifei Jianpi prescription on the of signal transducer and activator of transcription protein 1 （STAT1）/interferon regulatory factor 3 （IRF3） signaling pathway in a pneumonia model induced by lipopolysaccharide （LPS） and to explore the mechanism of Yifei Jianpi prescription in improving lung immune and inflammatory responses. MethodsSixty male SPF SD rats were used in this study. Ten rats were randomly assigned to the normal control group， and the remaining 50 were instilled with LPS in the trachea to establish a pneumonia model. After successful modeling， the rats were randomly divided into the model group， dexamethasone group （0.5 mg·kg^-1）， and Yifei Jianpi prescription high-dose （12 mg·kg^-1）， medium-dose （6 mg·kg^-1）， and low-dose （3 mg·kg^-1） groups， with 10 rats in each group. Treatment was administered once daily， and the normal control and model groups received the same volume of normal saline. After 14 days， flow cytometry was used to detect the classification of whole blood lymphocytes. Enzyme-linked immunosorbent assay （ELISA） was used to measure serum levels of immunoglobulin G （IgG）， immunoglobulin A （IgA）， immunoglobulin M （IgM）， and the content of tumor necrosis factor-α （TNF-α）， interleukin-8 （IL-8）， interleukin-6 （IL-6）， and interleukin-10 （IL-10） in alveolar lavage fluid （BALF）. Hematoxylin-eosin （HE） staining was used to observe lung tissue pathology and score the damage. Thymus weight， spleen weight， and wet-to-dry weight ratio （W/D） were recorded. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of STAT1， IRF3， IL-6， and interferon-alpha （IFN-α） in lung tissues， while Western blot was performed to assess the protein expression of STAT1， IRF3， IL-6， and IFN-α. ResultsCompared with the normal control group， the model group showed significantly increased proportion of B lymphocytes in peripheral blood， decreased proportions of NK cells and CD4⁺/CD8⁺ （P<0.05， P<0.01）， decreased serum levels of IgG and IgA， significantly increased IgM levels （P<0.01）， significantly elevated content of TNF-α， IL-6， and IL-8 in BALF， and significantly decreased IL-10 levels （P<0.01）. Lung tissue damage was evident， with significant increases in thymus and spleen weights and a higher W/D ratio （P<0.01）. The mRNA and protein expression of STAT1， IRF3， IFN-α， and IL-6 in lung tissues was significantly upregulated （P<0.05，P<0.01）. Compared with the model group， the Yifei Jianpi prescription groups showed significantly reduced proportions of B lymphocytes in peripheral blood， increased proportions of NK cells and CD4⁺/CD8⁺ ratios （P<0.05， P<0.01）， significantly increased serum levels of IgG and IgA， significantly decreased IgM levels （P<0.05， P<0.01）， significantly reduced levels of TNF-α， IL-6， and IL-8 in BALF， and significantly increased IL-10 levels （P<0.01）. Lung tissue damage was alleviated， thymus and spleen weights were significantly reduced， and the W/D ratio was markedly decreased （P<0.01）. The mRNA and protein expression of STAT1， IRF3， IFN-α， and IL-6 in lung tissues was significantly downregulated （P<0.05， P<0.01）. ConclusionYifei Jianpi prescription can alleviate lung tissue damage and improve immune and inflammatory responses in LPS-induced pneumonia rats. The mechanism may be related to the inhibition of STAT1/IRF3 signaling pathway activation.

AIM:To analyze differential proteins associated with the pathogenesis of dry eye(DE)using bioinformatics methods, in order to reveal their potential molecular mechanisms.METHODS: Articles published in PubMed and EMBASE databases from the inception of the database to August 31, 2023, that used proteomic methods to detect protein expression in clinical samples of dry eye were searched. Differential proteins were selected and further analyzed using the STRING database and Cytoscape software for hub gene screening and module analysis. Protein-protein interaction(PPI)analysis, gene ontology(GO)functional annotation, and Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis were performed.RESULTS: A total of 21 articles were included, identifying 74 differentially expressed proteins. The most frequently occurring differential proteins were calgranulin A(SA1008), lipocalin-1(LCN1), lysozyme C(LYZ), mammaglobin-B(SCGB2A1), proline-rich protein 4(PRR4), transferrin(TF), and calgranulinB(S100A9). The top 10 hub genes were serum albumin(ALB), tumor necrosis factor(TNF), interleukin 6(IL6), IL1B, IL8, matrix metalloproteinase 9(MMP9), alpha-1-antitrypsin(SERPINA1), IL10, complement component 3(C3), and lactotransferrin(LTF). Module analysis suggested MMP9 and PRR4 as seed genes. KEGG analysis showed that differential proteins were mainly enriched in the IL17 signaling pathway(61.9%).CONCLUSION: The results reveal potential molecular targets and pathways for DE and confirm the association between the pathogenesis of DE and inflammation. Further in-depth research is needed to confirm the significance of these biomarkers in clinical practice.

Objective To develop an artificial intelligence (AI)-driven lung cancer database by structuring and standardizing clinical data, enabling advanced data mining for lung cancer research, and providing high-quality data for real-world studies. Methods Building on the extensive clinical data resources of the Department of Thoracic Surgery at Peking Union Medical College Hospital, this study utilized machine learning techniques, particularly natural language processing (NLP), to automatically process unstructured data from electronic medical records, examination reports, and pathology reports, converting them into structured formats. Data governance and automated cleaning methods were employed to ensure data integrity and consistency. Results As of September 2024, the database included comprehensive data from 18 811 patients, encompassing inpatient and outpatient records, examination and pathology reports, physician orders, and follow-up information, creating a well-structured, multi-dimensional dataset with rich variables. The database’s real-time querying and multi-layer filtering functions enabled researchers to efficiently retrieve study data that meet specific criteria, significantly enhancing data processing speed and advancing research progress. In a real-world application exploring the prognosis of non-small cell lung cancer, the database facilitated the rapid analysis of prognostic factors. Research findings indicated that factors such as tumor staging and comorbidities had a significant impact on patient survival rates, further demonstrating the database’s value in clinical big data mining. Conclusion The AI-driven lung cancer database enhances data management and analysis efficiency, providing strong support for large-scale clinical research, retrospective studies, and disease management. With the ongoing integration of large language models and multi-modal data, the database’s precision and analytical capabilities are expected to improve further, providing stronger support for big data mining and real-world research of lung cancer.

Objective: To explore the plasma metabonomic characteristics of patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome. Methods: One hundred and three patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome were enrolled from November 2023 to February 2024 in the First Teaching Hospital of Tianjin University of Traditional Chinese Medicine and 54 healthy individuals were recruited. The general data of the two groups were analyzed, and the plasma metabolite content was detected using ultra-high performance liquid chromatography-Orbitrap mass spectrometry. Construct an orthogonal partial least squares discriminant analysis model to screen metabolites with significant intergroup changes. The variable importance in projection≥ 1, |log2FC|>1, and P<0.05 were used as the criteria for the screening of differential metabolites. Annotate differential metabolites using internal databases and the human metabolome database, and perform pathway analysis using MetaboAnalyst website. Results: There was no statistically significant difference in gender and age between the two groups.Seventeen potential differential metabolites were identified. The D-4′-phosphopantothenate, 2, 6-dichloroindophenol, 4-methylphenol, hypoxanthine, 11, 12-epoxyeicosatrienoic acids, oleamide, 3-phenyllactic acid contents were higher in patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome than in healthy individuals(P<0.05); 3-anisic acid, 3-iodo-octadecanoic acid, mebendazole, β-alanine, citric acid, trans-aconitic acid, geranyl diphosphate, lysophosphatidylcholine(18∶2), phosphatidylethanolamine(18∶1), and caprolactam contents were lower in patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome than in healthy individuals(P<0.05). Ten metabolic pathways were identified, including the key metabolic pantothenate and coenzyme A biosynthesis pathways. Conclusion Metabolic differences were observed between patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome and healthy individuals, and the underlying mechanism may involve the pantothenate and coenzyme A biosynthesis pathways, jointly mediated by D-4′-phosphopantothenate and β-alanine.

ObjectiveTo reveal the active substances and mechanisms of modified Qing'e formula （MQEF） in delaying skin photoaging by ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry （UPLC-Q-TOF-MS），network pharmacology， and cell experiments. MethodsUPLC-Q-TOF-MS and a literature review were employed to analyze the transdermally absorbed components in mice after the topical application of MQEF. The potential targets of MQEF in treating skin photoaging were retrieved from databases.The compound-potential target network and protein-protein interaction network were constructed to screen the key components and core targets. A photoaging cell model was established by irradiating HaCaT cells with medium-wave ultraviolet B （UVB）. The safe doses of bakuchiol （BAK） and salvianolic acid B （SAB） for treating HaCaT cells and the effects of BAK and SAB on the viability of cells exposed to UVB irradiation were determined by the cell counting kit-8 （CCK-8） method.The reactive oxygen species （ROS） fluorescent probe was used to measure the ROS production in the cells treated with BAK and SAB.The expression levels of genes related to oxidative stress，inflammation，collagen metabolism，and circadian rhythm clock were measured by Real-time PCR. ResultsA total of 24 transdermally absorbed components of MQEF were identified，which acted on 367 potential targets，and 417 targets related to skin photoaging were screened out，among which 47 common targets were predicted as the targets of MQEF in treating skin photoaging. MQEF exerted the anti-photoaging effect via key components such as BAK and SAB，which acted on core proteins such as serine/threonine kinase 1 （Akt1） and mitogen-activated protein kinase 3 （MAPK3） and intervened in core pathways such as the tumor necrosis factor （TNF） and phosphatidylinositol-3-kinase （PI3K）/protein kinase B （Akt） signaling pathways.Compared with the model group，the administration of BAK and SAB increased the survival rate of HaCaT cells （P<0.01），down-regulated the mRNA levels of cyclooxygenase-2 （COX-2），interleukin-6 （IL-6），tumor necrosis factor-α （TNF-α），matrix metalloproteinase-1 （MMP-1），and matrix metalloproteinase-9 （MMP-9） （P<0.01），and up-regulated the mRNA levels of heme oxygenase-1 （HO-1） and NAD（P）H quinone dehydrogenase 1 （NQO-1） （P<0.05，P<0.01） in photoaged HaCaT cells.In addition，it eliminated excess ROS production induced by UVB and up-regulated the mRNA levels of brain and muscle ARNT-like 1 （BMAL1） and circadian locomotor output cycles kaput （CLOCK） associated with circadian clock （P<0.05，P<0.01）. ConclusionMQEF delays skin photoaging through the coordinated effects of various components，multiple targets，and diverse pathways.The key components BAK and SAB in MQEF exhibit anti-photoaging properties，which involve inhibiting oxidative stress，preventing collagen degradation，mitigating inflammation，and maintaining normal skin circadian rhythms by regulating clock gene expression.

Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

AIM: To delineate the specific mutation responsible for retinitis pigmentosa(RP)in a Yi pedigree, and to analyze the correlation of RHO gene mutation with clinical phenotype.METHODS:A comprehensive clinical evaluation was conducted on the proband diagnosed with RP and other familial members, complemented by a thorough ophthalmic examination. Peripheral blood samples were obtained from the proband and familial members, from which genomic DNA was extracte. Subsequent whole exome sequencing(WES)was employed to identify the variant genes in the proband. The identified variant gene was validated through Sanger sequencing, then an in-depth analysis of the mutation genes was carried out using genetic databases to ascertain the pathogenic mutation sites. Furthermore, an exhaustive analysis was performed to delineate the genotype and phenotype characteristics.RESULTS:The RP pedigree encompasses 5 generations with 42 members, including 19 males and 23 females. A total of 13 cases of RP were identified, consisting of 4 males and 9 females, which conforms to the autosomal dominant inheritance pattern. The clinical features of this family include an early onset age, rapid progression, and a more severe condition. The patients were found to have night blindness around 6 years old, representing the earliest reported case of night blindness in RP families. The retina was manifested by progressive osteocytoid pigmentation of the fundus, a reduced visual field, and significantly decreased or even vanished a and b amplitudes of ERG. The combined results of WES and Sanger sequencing indicated that the proband had a heterozygous missense mutation of the RHO gene c.1040C>T:p.P347L, where the 1 040 base C of cDNA was replaced by T, causing codon 347 to encode leucine instead of proline. Interestingly, this mutation has not been reported in the Chinese population.CONCLUSION:This study confirmed that the mutant gene of RP in a Yi nationality pedigree was RHO(c.1040C>T). This variant leads to the change of codon 347 from encoding proline to encoding leucine, resulting in a severe clinical phenotype among family members. This study provides a certain molecular, clinical, and genetic basis for genetic counseling and gene diagnosis of RHO.

Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

AIM: To delineate the specific mutation responsible for retinitis pigmentosa(RP)in a Yi pedigree, and to analyze the correlation of RHO gene mutation with clinical phenotype.METHODS:A comprehensive clinical evaluation was conducted on the proband diagnosed with RP and other familial members, complemented by a thorough ophthalmic examination. Peripheral blood samples were obtained from the proband and familial members, from which genomic DNA was extracte. Subsequent whole exome sequencing(WES)was employed to identify the variant genes in the proband. The identified variant gene was validated through Sanger sequencing, then an in-depth analysis of the mutation genes was carried out using genetic databases to ascertain the pathogenic mutation sites. Furthermore, an exhaustive analysis was performed to delineate the genotype and phenotype characteristics.RESULTS:The RP pedigree encompasses 5 generations with 42 members, including 19 males and 23 females. A total of 13 cases of RP were identified, consisting of 4 males and 9 females, which conforms to the autosomal dominant inheritance pattern. The clinical features of this family include an early onset age, rapid progression, and a more severe condition. The patients were found to have night blindness around 6 years old, representing the earliest reported case of night blindness in RP families. The retina was manifested by progressive osteocytoid pigmentation of the fundus, a reduced visual field, and significantly decreased or even vanished a and b amplitudes of ERG. The combined results of WES and Sanger sequencing indicated that the proband had a heterozygous missense mutation of the RHO gene c.1040C>T:p.P347L, where the 1 040 base C of cDNA was replaced by T, causing codon 347 to encode leucine instead of proline. Interestingly, this mutation has not been reported in the Chinese population.CONCLUSION:This study confirmed that the mutant gene of RP in a Yi nationality pedigree was RHO(c.1040C>T). This variant leads to the change of codon 347 from encoding proline to encoding leucine, resulting in a severe clinical phenotype among family members. This study provides a certain molecular, clinical, and genetic basis for genetic counseling and gene diagnosis of RHO.

Lactate, with a chemical formula of C₃H₆O₃, is an intermediate product of glucose metabolism in the body and a raw material for hepatic gluconeogenesis. Under physiological resting conditions, the body mainly relies on aerobic oxidation of sugar and fat for energy supply, so the blood lactate concentration is lower. However, during exercise, the enhanced glycolysis in skeletal muscles leads to the significant release of lactate into the bloodstream, causing a marked increase in blood lactate concentration. Traditionally, lactate has been regarded as a metabolic waste product of glycolysis and a contributor to exercise-induced fatigue. Nevertheless, recent studies have revealed that, in humans, lactate is a major vehicle for carbohydrate carbon distribution and metabolism, serving not only as an energy substance alongside glucose but also as a vital component in various biological pathways involved in cardiac energetics, muscle adaptation, brain function, growth and development, and inflammation therapy. Two primary pathways can elevate lactate levels in neurons during exercise. One is peripheral skeletal muscle-derived lactate, which can enter the bloodstream and cross the blood-brain barrier into the brain with the assistance of monocarboxylate transporters (MCTs) from the solute carrier family 16 (SLC16). The other is the central brain-derived pathway. During exercise, neuronal activity is enhanced, promoting the secretion of neuroactive substances such as glutamate, norepinephrine, and serotonin in the brain. This activates astrocytes to break down glycogen into lactate and stimulates glutamate from the presynaptic terminal into the synaptic cleft. It upregulates the glucose transport protein-1 (GLUT-1) expression, allowing astrocytes to convert glucose into lactate through glycolysis. The lactate is produced via peripheral pathways and central pathways during exercise are transported by astrocyte membrane monocarboxylate transporters MCT1 and MCT4 to the extracellular space, where neurons take it up through neuronal cell membrane MCT2. The lactate in neurons can serve as an alternative energy source of glucose for neuronal functional activities, meeting the increased energy demands of synaptic activity during exercise, and maintaining energy balance and normal physiological function in the brain. Additionally, acting as a signaling molecule lactate can enhance synaptic plasticity through the SIRT1/PGC-1α/FNDC5 and ERK1/2 signaling pathways, lactate can promote angiogenesis by upregulating VEGF-A expression through the PI3K/Akt and ERK1/2 signaling pathways, stimulate neurogenesis via the Akt/PKB signaling pathway, and reduce neuroinflammation through activation of the “lactate timer”. Overall, lactate contributes to the protection of neurons, the promotion of learning and memory, the enhancement of synaptic plasticity, and the reduction of neuroinflammation in the nervous system. While lactate may serve as a potential mediator for information exchange between the peripheral and central nervous systems during exercise, further experimental research is needed to elucidate its action mechanisms in the nervous system. In addition, future studies should utilize advanced neurophysiological and molecular biology techniques to uncover the importance of lactate in maintaining brain function and preventing neurological diseases. Accordingly, this article first reviews the historical research on lactate, then summarizes the metabolic characteristics and neuronal sources of lactate, and finally explores the role and mechanisms of exercise-induced lactate in the nervous system, aiming to provide new perspectives and targets for understanding the mechanisms underlying exercise promotion of brain health.