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.

Objective:To investigate the effects and underlying mechanisms of Stat3 knockout in donor T cells on acute gastrointestinal graft-versus-host disease (GI-aGVHD) .Methods:BALB/c mice were exposed to lethal irradiation and transplanted with bone marrow and spleen cells from BALB/c mice (syngeneic control group), C57BL/6 mice (wild-type T cell group, WT group), or C57BL/6J-Stat3 em1cyagen mice (Stat3 gene knockout T cell group, Stat3-KO group) via tail vein injection to establish the aGVHD model. The survival rate, body weight changes, and clinical scores of mice were monitored. Cytometric bead array (CBA) was used to detect the concentrations of serum cytokines. Lymphocytes were isolated from tissues for flow cytometric analysis. H&E staining was performed to observe intestinal pathological changes. FITC-dextran assay was conducted to assess intestinal permeability. Immunohistochemistry was used to evaluate the expression of Ki67 and Muc2. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) was employed to analyze the gene expression levels of Olfm4, Lysozyme, and Muc2 in the small intestine. Metabolomics was conducted to detect metabolites in serum and intestinal tissues. An in vitro GI-aGVHD organoid model was established by coculturing intestinal organoids with allogeneic T cells, where the number and area of small intestinal organoids were recorded. The GVL effect was assessed using luciferase-transfected ALL cells (ALL/Luc) and bioluminescent imaging. Results:Compared with the WT group, Stat3 knockout T cells alleviated body weight loss, reduced symptoms—such as hunchback and diarrhea—in mice, improved survival rate ( P<0.05), and reduced serum interleukin (IL) -2, IL-6, interferon-γ, tumor necrosis factor-α, IL-17A, and IL-10 levels (all P<0.05), intestinal inflammatory cell infiltration ( P<0.05), and intestinal mucosal permeability. Further, Muc2 and Ki67 expression levels in the small intestine of the Stat3 knockout group were markedly increased, and Olfm4, Lysozyme, and Muc2 gene expression levels were significantly increased (all P<0.05). In vitro, the Stat3 knockout group demonstrated better organoid development than the WT group. Metabolomic analyses indicated that Stat3 knockout in T cells may affect the pathways associated with bile acid secretion and unsaturated fatty acids. ALL/Luc cells in the GVL mouse model proliferated rapidly in the TCD-BM group; however, 80% of the mice in the Stat3-KO group survived tumor-free for >100 days ( P<0.05) . Conclusion:Knocking out Stat3 in graft T cells reduces T cell damage to intestinal stem cells, thereby ultimately alleviating GI-aGVHD while maintaining a stable GVL effect.

Objective:To investigate the anti-tumor effect of the Histone Deacetylase 6 (HDAC6) inhibitor ACY-738 and its underlying mechanisms in Diffuse Large B-cell Lymphoma (DLBCL) .Methods:The expression of HDAC6 in various tumors and DLBCL was analyzed using bioinformatics. DLBCL cells were treated with different concentrations of ACY-738. Cell viability, DNA synthesis, and clone formation were assessed by CCK-8 assay, EdU assay, and soft agar assay, respectively. Intracellular reactive oxygen species (ROS) levels were detected by fluorescence microscopy. Morphological changes in cells were observed using transmission electron microscopy (TEM). Mitochondrial ROS levels and apoptosis were measured by flow cytometry. The expression levels of apoptosis-related and autophagy-related proteins were detected by Western blotting.Results:HDAC6 was highly expressed in DLBCL ( P<0.05). ACY-738 inhibited the proliferation, DNA synthesis, and colony formation of DLBCL cells in a dose-dependent manner ( P<0.05). Treatment with ACY-738 increased intracellular and mitochondrial ROS levels in DLBCL cells in a dose-dependent manner ( P<0.05). TEM revealed that after ACY-738 treatment, mitochondria in cells were swollen and ruptured, mitochondrial cristae were reduced or absent, autolysosomes appeared, and features characteristic of apoptosis were observed. Western blotting showed that after ACY-738 treatment, the expression of the anti-apoptotic protein BCL-2 was downregulated, while the expression of Cleaved-PARP, Cleaved caspase-3, and BAX was upregulated ( P<0.05). The expression of autophagy-related proteins Atg7, Atg3, LC3B, and P62 was downregulated, and the expression of acetylated P53 protein was upregulated ( P<0.05) . Conclusion:The HDAC6 inhibitor ACY-738 induces mitochondria-dependent apoptosis and autophagy in DLBCL cells by acetylating P53, thereby inhibiting DLBCL cell proliferation.

Objective:To investigate the efficacy of lightroom therapy on depressive mood and sleep problems in patients with depression, and the potential effects on physiological indices related to circadian rhythms.Methods:From October 2021 to July 2023, 54 patients with acute-phase depression hospitalized in the Mental Health Center of the First Hospital of Hebei Medical University were recruited. The participants were randomly assigned to either medication combined with the bright light therapy group (bright light group, n=36) or medication combined with the dim light therapy group (dim light group, n=18). Both groups received light therapy for 2 weeks, at 10 000 lx in the bright light group and 300 lx in the dim light group. Both groups received 30 minutes of light therapy from 7:30-8:00 a.m daily over two weeks, followed up for 1 week post-treatment. The Hamilton Depression Rating Scale (HAMD 17) was used to assess patients′ depressive symptoms, and the Pittsburgh Sleep Quality Index (PSQI) was used to assess patients′ sleep quality at baseline, at the end of every week. The 32-Item Hypomania Checklist (HCL-32) was used at the end of week 2 to assess the risk of manic switching after treatment. Daily measurements of body temperature, heart rate, and blood pressure were taken before and after light therapy, along with recording adverse events related to the therapy. Paired t- tests were used to compare changes in physiological indicators before and after treatment, and repeated measures ANOVA was applied to compare clinical symptom changes between the two groups. Results:Thirty-one and fifteen patients completed this study in the bright light and dim light groups, respectively, with no statistically significant difference in dropout rates( P>0.05). There were significant interaction effects between the time and group for HAMD 17 and PSQI score( F=5.51,4.11, both P<0.05). Both groups showed significant reductions in HAMD 17 and PSQI scores at baseline, week 1, week 2, and week 3 ( P<0.001). In the bright light group, body temperature increased significantly post-treatment on days 1-4, day 7, and day 12 (all P<0.05). Heart rate elevated on day 5 ( P<0.05).Systolic blood pressure decreased on days 4, 5, 11, and 12 compared to the pre-treatment baseline(all P<0.05). In the dim light group, systolic blood pressure increased on day 11 ( P<0.05). Diastolic blood pressure in the bright light group decreased on days 1, 5, and 6( P<0.05). No serious adverse events, vision loss, ocular structural changes occurred in either group. No hypomania or mania episodes were observed. The incidence of adverse events did not differ significantly ( P>0.05). Conclusion:Medication combined with indoor bright light is more effective than the combination of dim light for depressive symptoms and sleep problems in patients with depression. Patients receiving bright light also may exhibit a higher body temperature, accelerated heart rate, and reduced blood pressure.

Objective:To evaluate the value of multi-slice spiral CT (MSCT) in the diagnosis of liver metastases with rich blood supply.Methods:The clinical data and imaging data of 19 patients with liver metastases with rich blood supply admitted to the 921st Hospital of the Joint Logistics Support Force of Chinese People′s Liberation Army from September 2018 to September 2023 were retrospectively analyzed, and the number, location, shape, size of the lesions and the images of CT plain scan and dynamic enhanced scan were analyzed.Results:Among the 19 patients, there were 18 multiple cases and 1 single case. A total of 108 lesions were found. There were 62 cases (57.4%) in the right lobe of liver and 87 cases (80.6%) in the peripheral part of liver. The form of circular or quasi-circular, there were 99, irregular shape or lobed 9. The focal diameter was 0.6-6.8 cm. CT plain scan showed that 99 lesions showed slightly low density, and the other 9 lesions showed equal density relative to the background liver. In the dynamic enhanced scan, 108 lesions in arterial stage showed high-density enhancement, 97 lesions showed circular enhancement, and 11 lesions showed nodular enhancement. Among them, 77 lesions had moderate to obvious intensification density. Of the 108 lesions in the portal vein stage, 31 lesions showed moderate to obvious enhancement density, 49 lesions showed slightly low clearance density, and 28 lesions showed continuous enhancement density. In the delayed stage, all 108 lesions showed slightly low density.Conclusions:The main features of liver metastases with rich blood supply are: low density on plain CT scan, annular or nodular enhancement in the arterial phase of enhanced CT scan, and the peak of enhanced density can be in the arterial phase or the portal vein phase. Combined with clinical data, CT can make a correct diagnosis.

Objective To evaluate the application value of the MR three-dimensional double inversion recovery(3D DIR)sequence in the diagnosis of optic neuritis(ON).Methods A retrospective analysis was conducted on MRI images from 40 patients with sus-pected ON.All patients underwent conventional T2 WI fat suppression(FS)and 3D DIR sequences.The lesion detection rate and diag-nostic accuracy of the intraorbital,intracanalicular,and intracranial segments of the optic nerve were compared between the two sequences,respectively.The receiver operating characteristic(ROC)curves were used to assess the diagnostic performance,and the intraclass correlation coefficient(ICC)were used to analyze interobserver consistency.Imaging assessments were independently performed by two senior and two junior radiologists.Results The sensitivity(SEN),specificity(SPE),and accuracy(ACC)in lesion detection of 3D DIR sequence were significantly better than those of conventional T2 WI FS sequence[odds ratio(OR)221 vs 104,P＜0.001].Notably,3D DIR sequence exhibited superior performance in detecting lesions in the intraorbital segment[area under the curve(AUC)0.915,OR=102]and intracanalicular segment(AUC 0.858,OR=51)compared with conventional T2WI FS sequence.Additionally,3D DIR sequence significantly improved diagnostic consistency among junior radiologists(ICC value increased from 0.469 to 0.655),bring-ing their diagnostic performance closer to that of senior radiologists(AUC improved to 0.883,ACC reached 90.1％).Conclusion The 3D DIR sequence has outstanding diagnostic efficacy in detecting ON lesions,significantly improving ACC and interobserver consistency,thereby offering strong support for the precise diagnosis of ON.

Objective To evaluate the application value of the MR three-dimensional double inversion recovery(3D DIR)sequence in the diagnosis of optic neuritis(ON).Methods A retrospective analysis was conducted on MRI images from 40 patients with sus-pected ON.All patients underwent conventional T2 WI fat suppression(FS)and 3D DIR sequences.The lesion detection rate and diag-nostic accuracy of the intraorbital,intracanalicular,and intracranial segments of the optic nerve were compared between the two sequences,respectively.The receiver operating characteristic(ROC)curves were used to assess the diagnostic performance,and the intraclass correlation coefficient(ICC)were used to analyze interobserver consistency.Imaging assessments were independently performed by two senior and two junior radiologists.Results The sensitivity(SEN),specificity(SPE),and accuracy(ACC)in lesion detection of 3D DIR sequence were significantly better than those of conventional T2 WI FS sequence[odds ratio(OR)221 vs 104,P＜0.001].Notably,3D DIR sequence exhibited superior performance in detecting lesions in the intraorbital segment[area under the curve(AUC)0.915,OR=102]and intracanalicular segment(AUC 0.858,OR=51)compared with conventional T2WI FS sequence.Additionally,3D DIR sequence significantly improved diagnostic consistency among junior radiologists(ICC value increased from 0.469 to 0.655),bring-ing their diagnostic performance closer to that of senior radiologists(AUC improved to 0.883,ACC reached 90.1％).Conclusion The 3D DIR sequence has outstanding diagnostic efficacy in detecting ON lesions,significantly improving ACC and interobserver consistency,thereby offering strong support for the precise diagnosis of ON.

Objective:To investigate the effects and underlying mechanisms of Stat3 knockout in donor T cells on acute gastrointestinal graft-versus-host disease (GI-aGVHD) .Methods:BALB/c mice were exposed to lethal irradiation and transplanted with bone marrow and spleen cells from BALB/c mice (syngeneic control group), C57BL/6 mice (wild-type T cell group, WT group), or C57BL/6J-Stat3 em1cyagen mice (Stat3 gene knockout T cell group, Stat3-KO group) via tail vein injection to establish the aGVHD model. The survival rate, body weight changes, and clinical scores of mice were monitored. Cytometric bead array (CBA) was used to detect the concentrations of serum cytokines. Lymphocytes were isolated from tissues for flow cytometric analysis. H&E staining was performed to observe intestinal pathological changes. FITC-dextran assay was conducted to assess intestinal permeability. Immunohistochemistry was used to evaluate the expression of Ki67 and Muc2. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) was employed to analyze the gene expression levels of Olfm4, Lysozyme, and Muc2 in the small intestine. Metabolomics was conducted to detect metabolites in serum and intestinal tissues. An in vitro GI-aGVHD organoid model was established by coculturing intestinal organoids with allogeneic T cells, where the number and area of small intestinal organoids were recorded. The GVL effect was assessed using luciferase-transfected ALL cells (ALL/Luc) and bioluminescent imaging. Results:Compared with the WT group, Stat3 knockout T cells alleviated body weight loss, reduced symptoms—such as hunchback and diarrhea—in mice, improved survival rate ( P<0.05), and reduced serum interleukin (IL) -2, IL-6, interferon-γ, tumor necrosis factor-α, IL-17A, and IL-10 levels (all P<0.05), intestinal inflammatory cell infiltration ( P<0.05), and intestinal mucosal permeability. Further, Muc2 and Ki67 expression levels in the small intestine of the Stat3 knockout group were markedly increased, and Olfm4, Lysozyme, and Muc2 gene expression levels were significantly increased (all P<0.05). In vitro, the Stat3 knockout group demonstrated better organoid development than the WT group. Metabolomic analyses indicated that Stat3 knockout in T cells may affect the pathways associated with bile acid secretion and unsaturated fatty acids. ALL/Luc cells in the GVL mouse model proliferated rapidly in the TCD-BM group; however, 80% of the mice in the Stat3-KO group survived tumor-free for >100 days ( P<0.05) . Conclusion:Knocking out Stat3 in graft T cells reduces T cell damage to intestinal stem cells, thereby ultimately alleviating GI-aGVHD while maintaining a stable GVL effect.

Objective:To investigate the anti-tumor effect of the Histone Deacetylase 6 (HDAC6) inhibitor ACY-738 and its underlying mechanisms in Diffuse Large B-cell Lymphoma (DLBCL) .Methods:The expression of HDAC6 in various tumors and DLBCL was analyzed using bioinformatics. DLBCL cells were treated with different concentrations of ACY-738. Cell viability, DNA synthesis, and clone formation were assessed by CCK-8 assay, EdU assay, and soft agar assay, respectively. Intracellular reactive oxygen species (ROS) levels were detected by fluorescence microscopy. Morphological changes in cells were observed using transmission electron microscopy (TEM). Mitochondrial ROS levels and apoptosis were measured by flow cytometry. The expression levels of apoptosis-related and autophagy-related proteins were detected by Western blotting.Results:HDAC6 was highly expressed in DLBCL ( P<0.05). ACY-738 inhibited the proliferation, DNA synthesis, and colony formation of DLBCL cells in a dose-dependent manner ( P<0.05). Treatment with ACY-738 increased intracellular and mitochondrial ROS levels in DLBCL cells in a dose-dependent manner ( P<0.05). TEM revealed that after ACY-738 treatment, mitochondria in cells were swollen and ruptured, mitochondrial cristae were reduced or absent, autolysosomes appeared, and features characteristic of apoptosis were observed. Western blotting showed that after ACY-738 treatment, the expression of the anti-apoptotic protein BCL-2 was downregulated, while the expression of Cleaved-PARP, Cleaved caspase-3, and BAX was upregulated ( P<0.05). The expression of autophagy-related proteins Atg7, Atg3, LC3B, and P62 was downregulated, and the expression of acetylated P53 protein was upregulated ( P<0.05) . Conclusion:The HDAC6 inhibitor ACY-738 induces mitochondria-dependent apoptosis and autophagy in DLBCL cells by acetylating P53, thereby inhibiting DLBCL cell proliferation.