BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

Objectives: . This study aimed to explore the role of the Pcdh15 gene in hearing maintenance and to examine the effects of its deficiency on cochlear structure, cochlear function, and hearing loss in mice. Methods: . CRISPR/Cas9 technology was used to generate Pcdh15 knockout (KO) mice. Auditory function was evaluated using hearing tests, while histological approaches were employed to assess morphological changes in cochlear hair cells and spiral ganglion neurons (SGNs). RNA sequencing (RNA-seq) was performed on cochlear tissue from postnatal day 18 (P18) wild-type (WT) and Pcdh15 KO mice to identify differentially expressed genes (DEGs). These DEGs were subjected to functional annotation and pathway analysis, with particular emphasis on oxidative phosphorylation (OXPHOS). Reactive oxygen species (ROS) levels were quantified using flow cytometry and DCFH-DA assays. Results: . Pcdh15 KO mice exhibited progressive sensorineural hearing loss, which worsened to profound deafness by P18. Notably, cochlear hair cells and SGNs showed substantial loss and pronounced morphological abnormalities, particularly within the basal high-frequency region. RNA-seq analysis identified 1,359 DEGs, including 1,024 downregulated and 335 upregulated genes. Pathway analysis indicated that Pcdh15 deficiency was associated with inhibition of the OXPHOS pathway, potentially disrupting mitochondrial respiratory chain complexes I, III, IV, and V and thereby impairing energy production and ATP metabolism. In addition, early-stage cochleae from KO mice demonstrated elevated ROS levels and increased oxidative stress, suggesting that redox imbalance may contribute to hearing damage. Conclusion . Pcdh15 plays a critical role in hearing maintenance. Its deficiency is associated with severe hearing loss and marked cochlear abnormalities, which are linked to inhibition of OXPHOS, disruption of energy metabolism, and exacerbation of oxidative stress. Together, these findings provide new insights into the mechanisms underlying hearing loss and suggest potential targets for therapeutic intervention.

Background/Aims: Biliary tract cancer (BTC) frequently harbors KRAS mutations, which are associated with resistance to traditional treatment and a poor prognosis. Synthetic lethality (SL) strategy may provide other targets of KRAS. Therefore, we aim to identify and validate potential therapeutic targets of KRAS for the treatment of BTC via SL. Methods: The dependency (DepMap) projects were used to predict the synthetic lethal gene of KRAS. FDA-approved anticancer drug library was applied to screen potential drugs effective against KRAS-mutant BTC. Furthermore, the synthetic lethal effects or corresponding mechanisms of potential genes and drugs on BTC were investigated using KRAS-mutant and KRAS-wild type BTC cell lines, patient-derived xenografts (PDX), and KRAS oncogene-driven tumor models, as well as other KRAS-mutant cancer cell lines. Results: Initially, we discovered that the loss of GATA2 reduced the viability of KRAS-mutant but not KRAS-wild-type BTC. Subsequently, the drug library screened out disulfiram, which primarily exerts a synthetic lethal effect by inhibiting interleukin-1β (IL-1β) in KRAS-mutant BTC. Mechanistically, GATA2 specifically enhanced the transcription of IL-1β to promote NF-κB signaling in KRAS-mutant BTC. IL-1β inhibition phenocopied GATA2 deficiency, leading to reduced KRAS-mutant BTC viability. These synthetically lethal effects were confirmed using PDX, a KRAS oncogene-driven tumor model, as well as in other KRAS-mutant cancer cell lines. Conclusions In summary, these results indicate that inhibiting GATA2/IL1β could be a therapeutic strategy in KRAS-mutant BTC and potentially other cancers.

BACKGROUND:Bone relies on the close connection between blood vessels and bone cells to maintain its integrity.Bones are in a physiologically hypoxic environment.Therefore,the study of angiogenesis and osteogenesis in hypoxic environment is closer to the microenvironment in vivo. OBJECTIVE:To explore the influence of Wenshen Tongluo Zhitong(WSTLZT)formula on H-type bone microvascular endothelial cell/bone marrow mesenchymal stem cell co-culture system in hypoxia environment and its related mechanism. METHODS:Enzyme digestion method and flow sorting technique were used to isolate and identify H-type bone microvascular endothelial cells.Mouse bone marrow mesenchymal stem cells were isolated and obtained by bone marrow adhesion method.H-type bone microvascular endothelial cell/bone marrow mesenchymal stem cell hypoxic co-culture system was established using Transwell chamber and anoxic culture workstation.WSTLZT formula powder was used to intervene in each group at a mass concentration of 50 and 100 μg/mL.The angiogenic function of H-type bone microvascular endothelial cells in the co-culture system was evaluated by scratch migration test and tube formation test.The osteogenic differentiation ability of bone marrow mesenchymal stem cells in the co-cultured system was evaluated by alkaline phosphatase staining and alizarin red staining.The protein and mRNA expression changes of PDGF/PI3K/AKT signal axis related molecules in H-type bone microvascular endothelial cells in the co-cultured system were detected by Western Blotting and q-PCR,respectively. RESULTS AND CONCLUSION:(1)Compared with the normal oxygen group,the scratch mobility and new blood vessel length of H-type bone microvascular endothelial cells were significantly higher(P<0.05);the osteogenic differentiation capacity of bone marrow mesenchymal stem cells was higher(P<0.05);the expression of PDGF/PI3K/AKT axis-related molecular protein and mRNA increased(P<0.05)in the hypoxia group.(2)Compared with the hypoxia group,scratch mobility and new blood vessel length were significantly increased in the H-type bone microvascular endothelial cells(P<0.05);bone marrow mesenchymal stem cells had stronger osteogenic function(P<0.05);the expression of PDGF/PI3K/AKT axis-related molecular proteins and mRNA further increased(P<0.05)after treatment with different dose concentrations of WSTLZT formula.These findings conclude that H-type angiogenesis and osteogenesis under hypoxia may be related to the PDGF/PI3K/AKT signaling axis,and WSTLZT formula may promote H-type vasculo-dependent bone formation by activating the PDGF/PI3K/AKT signaling axis,thereby preventing and treating osteoporosis.

[Objective] To analyze the influencing factors of repeat blood donor lapsing using a zero-inflated poisson regression model (ZIP). [Methods] The blood donation behavior of 12 498 whole blood donors from 2020 was tracked until December 31, 2023. The factors influencing the frequency of blood donations in a given year was analyzed using ZIP, and donors with 0 blood donation in that year were considered to have lapsed. The changes in relevant influencing factors associated with each blood donation were measured and modeled for analysis. [Results] The zero-inflated part of ZIP showed that the risk of lapsing of male blood donors was 2.24 times that of female blood donors (OR 95% CI:1.864-2.696, P<0.001); the risk of lapsing of the 35-44 age group and over 45 age group was respectively 40% (OR 95% CI:0.455-0.790, P<0.001) and 61%(OR 95% CI:0.268-0.578, P<0.001) lower than that of the under 25 age group; the risk of lapsing for those who have donated blood twice and ≥3 times was respectively 50% (OR 95% CI:0.405-0.609, P<0.001) and 81% (OR 95% CI:0.154-0.225, P<0.001) lower than that of first-time donors; the risk of lapsing of those with junior high or high school education was 1.2 times that of those with a college degree or higher (OR 95% CI:1.033-1.384, P<0.05); the risk of lapsing for the divorced group was 2.02 times that of the married group (OR 95% CI:1.445-2.820, P<0.001); the risk of lapsing for those with an income (Yuan) of 10 000 to 50 000, 50 000 to 100 000 and more than 100 000 was respectively 0.67 (OR 95% CI:0.552-0.818, P<0.001), 0.72 (OR 95% CI:0.591-0.884, P=0.002) and 0.67 (OR 95% CI:0.535-0.834, P<0.001) times that of those with an income (Yuan) of less than 10 000. The results of the Poisson part are consistent with the results of the zero-inflated part in terms of age and education level. [Conclusion] Blood donor lapsing is overall related to factors such as gender, age, donation frequency, education, marital status and family income. It's essential to care for those blood donors prone to lapse to retain more regular blood donors.

Objective: To investigate the current status of iron metabolism among apheresis donors in Guangzhou and analyze the improvement effects of health education on iron deficiency in frequent apheresis donors. Methods: Using a generalized linear mixed model (GLMM), a 180-day follow-up was conducted on 261 eligible apheresis donors at the Guangzhou Blood Center from January to July 2024. Hemoglobin (Hb), serum ferritin (SF), unsaturated iron-binding capacity (UIBC), total iron-binding capacity (TIBC), and transferrin saturation (TS) were selected as outcome variables. The effects of gender, age group, and number of donations within 180 days on these outcomes were analyzed and modeled. A general linear model (GLM) with repeated measures was applied to 55 donors who received health education interventions, comparing changes in Hb and iron metabolism-related indicators before and after follow-up and health education. Results: No significant difference in Hb levels was observed between first-time and regular apheresis donors, but SF levels were significantly higher in first-time donors (F=6.195, P<0.05). The GLMM revealed that female donors exhibited more significant reductions in Hb (T=-12.546) and SF (T=-5.829)(P<0.05 for both). Age group showed no interactive effects on Hb or SF changes. While number of donations within 180 days had no interactive effect on Hb, SF levels significantly decreased with increased number of donations (using ≥9 donations as the reference group; P<0.05 for all groups). After health education, Hb levels remained unchanged, but SF increased compared to pre-intervention levels (mean difference: -18.571, P<0.05), though a declining trend persisted compared to baseline (mean difference from baseline to post-intervention: 23.068,P<0.05). Conclusion: Female and number of donations are primary factors contributing to SF reduction in apheresis donors. Health education interventions promote SF recovery. Extending donation intervals and reinforcing iron deficiency-related health education may improve iron status in donors.

This study analyzes the legal application of a dispute over employer identification in a case of occupational heat illness caused by part-time work to clarifying matters related to employer determination in occupational disease diagnosis using a case analysis method and factual reconstruction. The analysis is based on relevant civil laws and regulations, occupational disease diagnosis laws and regulations, and jurisprudential theories. The occupational disease diagnostic institution identified the part-time employer as responsible for the patient′s heat illness, which was both reasonable and lawful. This attribution safeguarded the rights of the worker, the primary employer, and the part-time entity. In occupational disease diagnosis, attention should be paid to de facto employment relationship, and the principle of "accountability lies with the actual employer at the time of the incident" should be followed to standardize employer identification. The health administrative department has supervisory responsibilities over occupational disease diagnoses. Workers′ compensation rights can be protected through the advance payment mechanism for work-related injury insurance. It is recommended to further improve internal procedures for occupational disease diagnosis, strengthen the dissemination of relevant laws and regulations and enhance the capabilities of occupational disease diagnosis physicians, to further protect workers' occupational health and their associated legal rights.

Although symptomatic treatment is widely applied in clinical practice， it is often regarded as a relatively low-level therapeutic method. Based on Traditional Chinese Medicine （TCM） state theory， the macroscopic， mesoscopic， and microscopic characterization parameters of TCM symptomatology are horizontally integrated， the full life cycle of states （pre-disease， incipient disease， manifest disease， post-disease） is vertically covered， and the cognitive system of "symptoms" is reconstructed from multiple dimensions. Accordingly， the application approach of symptomatic treatment at different state stages is proposed： implementing preventive intervention in the pre-disease state， strengthening the interception of disease progression in the incipient disease state， regulating dynamic development and treatment in the manifest disease state， and formulating a staged diagnosis and treatment strategy which focuses on functional rehabilitation in the post-disease state.

OBJECTIVE To investigate the independent risk factors for carbapenem-resistant Klebsiella pneumoniae （CRKP） infection， develop a nomogram prediction model and validate it. METHODS Clinical data of hospitalized patients infected with CRKP between April 2020 and May 2023 at Kunming First People’s Hospital were retrospectively collected and matched 1∶1 with patients infected with carbapenem-susceptible Klebsiella pneumoniae （CSKP） during the same period as the modeling group. Using the same criteria， data from patients hospitalized and infected with CRKP and matched CSKP between June 2023 and June 2024 were collected as the validation group. Univariate analysis， LASSO regression and multivariate Logistic regression were conducted to identify independent risk factors for CRKP infection and to develop a nomogram prediction model. Internal validation of the model was performed using Bootstrap resampling， and external validation was carried out using the data of validation group. The predictive performance of the model was evaluated using receiver operating characteristic （ROC） curves and calibration plots. RESULTS A total of 530 patients were enrolled， with 372 in the modeling group and 158 in the validation group. Cerebrovascular disease， indwelling gastric tube， mechanical ventilation， exposure to carbapenem antibiotics， and exposure to β-lactamase inhibitor compound agents were identified as independent risk factors for CRKP infection （P＜0.05）. The nomogram predicting CRKP infection risk achieved an area under ROC of 0.729 and 0.803 in internal and external validations， respectively. Calibration curves indicated a high degree of consistency between predicted and observed probabilities. CONCLUSIONS Cerebrovascular disease， indwelling gastric tube， mechanical ventilation， exposure to carbapenem antibiotics， and exposure to β-lactamase inhibitor compound agent are independent risk factors for CRKP infection. The developed nomogram model for predicting CRKP infection risk demonstrates good predictive performance and can aid in the early identification of patients at high risk for CRKP infection.