Objective To investigate the role of poly(rC)-binding protein 1(PCBP1)in cadmium(Cd)-induced ferroptosis in mouse neuroblastoma Neuro-2a(N2A)cells.Methods N2A cells were exposed to a concentration gradient of CdCl?(0,1,2,4 μmol/L)for 72 h.Cell viability was assessed by trypan blue staining.Western blotting was employed to detect the expression of ferroptosis-related proteins(GPX4,HMOX1,ACSL4)and PCBP1.Intracellular Fe2? level and lipid peroxidation were detected using FerroOrange and BODIPY581/591 C11 probes,respectively.Ferrostatin-1(Fer-1),a ferroptosis inhibitor,was applied to confirm the critical role of ferroptosis in Cd-induced cytotoxicity.Molecular docking was performed to elucidate the interaction between PCBP1 and ferritin,as well as the binding sites of Cd2?.PCBP1 overexpression plasmid was further constructed for functional validation.Results Cd exposure suppressed cell viability in N2A cells in a dose-dependent manner(P<0.01),significantly down-regulated GPX4 expression(P<0.05),up-regulated HMOX1 expression(P<0.01),and induced Fe2? overload and lipid peroxidation(P<0.01).Molecular docking revealed that Cd2? directly bound to the KH2 domain of PCBP1 and then co-localized on the outer surface of ferritin heavy chain.Overexpression of PCBP1 markedly reversed Cd-induced Fe2? accumulation,GPX4 down-regulation,lipid peroxidation,and cell death.Conclusion Cd exposure disrupts PCBP1-mediated iron homeostasis via transcriptional suppression and competitive displacement of metal ions,and then synergistically drives Fe2? overload-triggered ferroptosis cascades,ultimately leading to neurotoxicity.Targeting PCBP1-mediated iron homeostasis can effectively mitigate Cd-induced neurotoxicity,and may serve as a novel therapeutic strategy.

Alzheimer′s disease (AD) is a neurodegenerative disorder primarily characterized by progressive memory decline and cognitive dysfunction. Lipid droplets (LDs) are dynamic organelles that store neutral lipids and play a crucial role in maintaining intracellular lipid homeostasis. Dysregulated lipid metabolism in microglia and its role in mediating abnormal LDs accumulation have been shown to significantly contribute to AD pathogenesis. This review summarizes the regulatory pathways of LDs metabolism in microglia in AD and discusses how lipid metabolic dysfunction exacerbates AD pathology. Furthermore, this review highlights key molecular mechanisms governing microglial lipid metabolism in AD and explores potential therapeutic strategies targeting lipid metabolism for AD intervention.

Objective:To evaluate the performance of the neural network model in segmenting gout tophus in the first metatarsophalangeal（MTP1）joint ultrasound images.Methods:A total of 1 218 tophus images from 381 patients who underwent MTP1 ultrasound examinations in the Affiliated Hospital of Qingdao University between May 2023 and December 2024 were prospectively collected. The images were divided into training，validation，and test sets in a ratio of 7∶2∶1. Multiple neural network models were trained to automatically identify and segment tophus in the images，with physician-annotated tophus regions serving as the reference standard. Model performance was evaluated in the test set，and the impact of tophus characteristics（e.g.，echogenicity，size，and presence of bone erosion）on segmentation efficacy was analyzed.Results:In the test set，CMUNeXt demonstrated superior tophus segmentation performance versus Unet，Unet++，TransUnet，and CMU-Net，achieving an accuracy of 99.1%，precision of 79.1%，recall of 84.6%，intersection over union of 68.8%，and Dice similarity coefficient of 80.2%. Logistic regression identified tophus echogenicity，size，and bone erosion as independent efficacy factors OR（95% CI）=7.275（1.598-33.129），21.303（4.282-105.985），13.520（3.617-50.530），0.076（0.007-0.823）（all P<0.05）. Hypoechoic tophus demonstrated significantly superior segmentation performance compared to mixed-echoic and isoechoic tophus（all P<0.05），and lesions with larger maximum diameters（>10 mm）were segmented more effectively than smaller tophus（ P<0.05）. Conclusions:The CMUNeXt model enables accurate identification and segmentation of tophus in MTP1 ultrasound images，particularly excelling for larger and hypoechoic lesions. This approach holds significant promise for AI-assisted diagnosis of MTP1 gouty arthritis.

Objective To explore the biological mechanism of radiation resistance in esophageal squamous cell carcinoma(ESCC)and search for effective sensitization targets.Methods We retrieved 186 signaling pathways and related gene information from the MSigDB database.We also obtained RNA transcriptome data of ESCC patients using the Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)databases.We collected clinical pathological characteristics and tissue samples of 97 ESCC patients in our hospital from 2013 to 2020.Gene set variation analysis(GSVA)was made to calculate KEGG signaling pathway score,radiotherapy resistance related signaling pathways were screened through random forest algorithm,key genes in the pathway were screened using DESeq2,and a radiotherapy efficacy prediction model was constructed based on support vector machine-recursive feature elimination(SVM-RFE).The results were validated through experiments such as Western blotting and clonogenic assay.Results Based on the KEGG signaling pathway and GSVA enrichment score,random forest analysis showed that in the TCGA and GSE45670 cohorts,the contribution of tryptophan metabolism pathway enrichment values to radiation resistance in ESCC was significantly better than that of the other pathways.DESeq2 analysis revealed that key molecules in the tryptophan metabolism pathway,namely,IDO1,ALDH1B1,AOC1,INMT,AFMID and ALDH7A1,were significantly differentially expressed in the resistant and sensitive groups of ESCC.Based on the SVM-RFE algorithm,the AUC was 0.77,which could accurately predict the radiotherapy efficacy of ESCC.Western blotting experiments showed that IDO1 was highly expressed in ESCC cells,and IDO1 inhibitor treatment significantly inhibited the survival ability and radiosensitivity of KYSE-410 cells.In the enrolled patients of our hospital,immunohistochemical studies showed that IDO1 was highly expressed in the radiotherapy resistant group of ESCC and was associated with poor radiotherapy prognosis in ESCC patients.In addition,further testing showed that the expression of IDO1 in patient samples from our hospital was positively correlated with its PD-L1 expression,but negatively correlated with the infiltration ratio of CD3/CD8 immune cells.Conclusion Tryptophan catabolism is associated with radiation resistance in ESCC,and the key enzyme IDO1 in tryptophan metabolism can be used as a therapeutic target for radiosensitization in ESCC.

Objective:It aims to give full play to the role of financial supervision in promoting strict financial discipline,main-taining financial order,and realizing the high-quality development of the health system,and help financial and accounting supervi-sion take root in the daily management of public hospitals.Methods:Based on the strategic theory and guided by the problems faced by public hospitals,the objectives,paths and means of financial and accounting supervision were integrated into the strategic layout with"overall strategy,competitive strategy,functional strategy,and support strategy"as the chain.Results:A financial and accounting supervision system for public hospitals was formed with"one basic program,three core functions,five management tools,and four types of basic work"as the basic framework.Conclusion:Managers can effectively help public hospitals stabilize their income,optimize their structure,reduce costs,enhance their competitive advantages,and promote their own high-quality development by optimizing their work around the supervision system,deepening reform,and insisting on innovation.

A complete plant body consists of elements on different scales, including microscopic molecules, mesoscopic multicellular structures, and macroscopic tissues and organs, which are interconnected to form complex biological networks. The growth and development of plants involve the regulation of elements on different scales and their biological networks, which requires the coordinated operation of multiple molecules, cells, tissues, and organs. It is difficult to reveal the essence of multi-level life activities by a single method or technology. In recent years, the development of various novel imaging technologies has provided new approaches for revealing the complex life activities in plants. Using multi-modal imaging technologies to study the cross-scale network connections of plants from the microscopic, mesoscopic, and macroscopic levels is crucial for understanding the complex internal connections behind biological functions. This paper first summarizes multi-modal cross-scale imaging technologies, three-dimensional reconstruction, and image processing methods, outlines the basic framework of cross-scale network connection properties, and then summarizes the applications of multi-modal imaging technologies in elucidating plant multi-scale networks. Finally, this review systematically integrates the combined analysis of cross-scale 3D spatial structural data and single-cell omics, laying a theoretical foundation for the innovation of novel plant imaging technologies. Furthermore, it provides a new research paradigm for in-depth exploration of the interaction mechanisms among cross-scale elements and the principles of biological network connectivity in plant life activities.
Plants/metabolism* ; Imaging, Three-Dimensional/methods* ; Image Processing, Computer-Assisted/methods* ; Multimodal Imaging/methods* ; Plant Physiological Phenomena

Objective:It aims to give full play to the role of financial supervision in promoting strict financial discipline,main-taining financial order,and realizing the high-quality development of the health system,and help financial and accounting supervi-sion take root in the daily management of public hospitals.Methods:Based on the strategic theory and guided by the problems faced by public hospitals,the objectives,paths and means of financial and accounting supervision were integrated into the strategic layout with"overall strategy,competitive strategy,functional strategy,and support strategy"as the chain.Results:A financial and accounting supervision system for public hospitals was formed with"one basic program,three core functions,five management tools,and four types of basic work"as the basic framework.Conclusion:Managers can effectively help public hospitals stabilize their income,optimize their structure,reduce costs,enhance their competitive advantages,and promote their own high-quality development by optimizing their work around the supervision system,deepening reform,and insisting on innovation.

Objective To explore the biological mechanism of radiation resistance in esophageal squamous cell carcinoma(ESCC)and search for effective sensitization targets.Methods We retrieved 186 signaling pathways and related gene information from the MSigDB database.We also obtained RNA transcriptome data of ESCC patients using the Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)databases.We collected clinical pathological characteristics and tissue samples of 97 ESCC patients in our hospital from 2013 to 2020.Gene set variation analysis(GSVA)was made to calculate KEGG signaling pathway score,radiotherapy resistance related signaling pathways were screened through random forest algorithm,key genes in the pathway were screened using DESeq2,and a radiotherapy efficacy prediction model was constructed based on support vector machine-recursive feature elimination(SVM-RFE).The results were validated through experiments such as Western blotting and clonogenic assay.Results Based on the KEGG signaling pathway and GSVA enrichment score,random forest analysis showed that in the TCGA and GSE45670 cohorts,the contribution of tryptophan metabolism pathway enrichment values to radiation resistance in ESCC was significantly better than that of the other pathways.DESeq2 analysis revealed that key molecules in the tryptophan metabolism pathway,namely,IDO1,ALDH1B1,AOC1,INMT,AFMID and ALDH7A1,were significantly differentially expressed in the resistant and sensitive groups of ESCC.Based on the SVM-RFE algorithm,the AUC was 0.77,which could accurately predict the radiotherapy efficacy of ESCC.Western blotting experiments showed that IDO1 was highly expressed in ESCC cells,and IDO1 inhibitor treatment significantly inhibited the survival ability and radiosensitivity of KYSE-410 cells.In the enrolled patients of our hospital,immunohistochemical studies showed that IDO1 was highly expressed in the radiotherapy resistant group of ESCC and was associated with poor radiotherapy prognosis in ESCC patients.In addition,further testing showed that the expression of IDO1 in patient samples from our hospital was positively correlated with its PD-L1 expression,but negatively correlated with the infiltration ratio of CD3/CD8 immune cells.Conclusion Tryptophan catabolism is associated with radiation resistance in ESCC,and the key enzyme IDO1 in tryptophan metabolism can be used as a therapeutic target for radiosensitization in ESCC.

Alzheimer′s disease (AD) is a neurodegenerative disorder primarily characterized by progressive memory decline and cognitive dysfunction. Lipid droplets (LDs) are dynamic organelles that store neutral lipids and play a crucial role in maintaining intracellular lipid homeostasis. Dysregulated lipid metabolism in microglia and its role in mediating abnormal LDs accumulation have been shown to significantly contribute to AD pathogenesis. This review summarizes the regulatory pathways of LDs metabolism in microglia in AD and discusses how lipid metabolic dysfunction exacerbates AD pathology. Furthermore, this review highlights key molecular mechanisms governing microglial lipid metabolism in AD and explores potential therapeutic strategies targeting lipid metabolism for AD intervention.

Objective:To evaluate the performance of the neural network model in segmenting gout tophus in the first metatarsophalangeal（MTP1）joint ultrasound images.Methods:A total of 1 218 tophus images from 381 patients who underwent MTP1 ultrasound examinations in the Affiliated Hospital of Qingdao University between May 2023 and December 2024 were prospectively collected. The images were divided into training，validation，and test sets in a ratio of 7∶2∶1. Multiple neural network models were trained to automatically identify and segment tophus in the images，with physician-annotated tophus regions serving as the reference standard. Model performance was evaluated in the test set，and the impact of tophus characteristics（e.g.，echogenicity，size，and presence of bone erosion）on segmentation efficacy was analyzed.Results:In the test set，CMUNeXt demonstrated superior tophus segmentation performance versus Unet，Unet++，TransUnet，and CMU-Net，achieving an accuracy of 99.1%，precision of 79.1%，recall of 84.6%，intersection over union of 68.8%，and Dice similarity coefficient of 80.2%. Logistic regression identified tophus echogenicity，size，and bone erosion as independent efficacy factors OR（95% CI）=7.275（1.598-33.129），21.303（4.282-105.985），13.520（3.617-50.530），0.076（0.007-0.823）（all P<0.05）. Hypoechoic tophus demonstrated significantly superior segmentation performance compared to mixed-echoic and isoechoic tophus（all P<0.05），and lesions with larger maximum diameters（>10 mm）were segmented more effectively than smaller tophus（ P<0.05）. Conclusions:The CMUNeXt model enables accurate identification and segmentation of tophus in MTP1 ultrasound images，particularly excelling for larger and hypoechoic lesions. This approach holds significant promise for AI-assisted diagnosis of MTP1 gouty arthritis.