Objective To investigate how dietary supplementation with tetrahydrocurcumin(THC)improves kidney injury in type 2 dia-betic mellitus(T2DM)and its mechanism of action using transcriptome sequencing(RNA-seq).Methods C57BL/6J mice were randomly assigned to the control,T2DM,and T2DM+THC groups.After a high-fat meal and streptozotocin injection,the body weights and fasting blood glucose levels of each mouse with T2DM were measured.Hematoxylin and eosin staining,Oil red O staining,and RNA-seq were performed to examine kidney pathology,lipid deposition,and differentially expressed genes,respectively,in the mice.Results Mice in T2DM group exhibited significantly higher fasting blood glucose levels(P＜0.001),renal tubule degeneration,glomeruli enlargement,disordered epithelial cells,and increased kidney lipid deposition after 12 weeks compared with those of the control group.THC adminis-tration alleviated all these conditions(P＜0.001).RNA-seq analysis revealed significant gene expression variations among the control,T2DM,and T2DM+THC groups.THC may protect against T2DM-induced kidney injury and lipid deposition by regulating the cell cycle(apoptosis),P53 signaling pathway,and PPARγ signaling path way,as indicated by Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses.In mice with T2DM,THC intervention may upregulate the expression of Cd36,Lpl,PPARγ,and Plin4 genes in renal tissues,while downregulating Ccnb1,Ccnb2,Cdk1,Bub1,and Cdc25c gene expressions.The proteins encoded by the four upregulated genes interact,as do those encoded by the five downregulated genes.Conclusion THC administration improves fasting blood glucose levels,reduces renal damage,and decreases fat deposition in mice with T2DM.The processes may involve decreasing apoptosis,blocking the P53 signaling pathway,and activating the PPARγ signaling pathway.

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

Objective To investigate how dietary supplementation with tetrahydrocurcumin(THC)improves kidney injury in type 2 dia-betic mellitus(T2DM)and its mechanism of action using transcriptome sequencing(RNA-seq).Methods C57BL/6J mice were randomly assigned to the control,T2DM,and T2DM+THC groups.After a high-fat meal and streptozotocin injection,the body weights and fasting blood glucose levels of each mouse with T2DM were measured.Hematoxylin and eosin staining,Oil red O staining,and RNA-seq were performed to examine kidney pathology,lipid deposition,and differentially expressed genes,respectively,in the mice.Results Mice in T2DM group exhibited significantly higher fasting blood glucose levels(P＜0.001),renal tubule degeneration,glomeruli enlargement,disordered epithelial cells,and increased kidney lipid deposition after 12 weeks compared with those of the control group.THC adminis-tration alleviated all these conditions(P＜0.001).RNA-seq analysis revealed significant gene expression variations among the control,T2DM,and T2DM+THC groups.THC may protect against T2DM-induced kidney injury and lipid deposition by regulating the cell cycle(apoptosis),P53 signaling pathway,and PPARγ signaling path way,as indicated by Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses.In mice with T2DM,THC intervention may upregulate the expression of Cd36,Lpl,PPARγ,and Plin4 genes in renal tissues,while downregulating Ccnb1,Ccnb2,Cdk1,Bub1,and Cdc25c gene expressions.The proteins encoded by the four upregulated genes interact,as do those encoded by the five downregulated genes.Conclusion THC administration improves fasting blood glucose levels,reduces renal damage,and decreases fat deposition in mice with T2DM.The processes may involve decreasing apoptosis,blocking the P53 signaling pathway,and activating the PPARγ signaling pathway.

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

Objective To propose a deep learning neural network approach for transforming megavoltage computed tomography(MVCT)images of cervical cancer into pseudo kilovoltage computed tomography(kVCT)images with high signal-to-noise ratio and contrast-to-noise ratio,thus providing three-dimensional anatomical images and localization information required for adaptive radiotherapy of cervical cancer,and guiding the accelerator to achieve precise treatment.Methods The MVCT and kVCT images of 54 patients treated with cervical cancer radiotherapy were collected,with 44 cases randomly selected as the training set,and the remaining 10 cases as the test set.A cyclic generative adversarial network with gating mechanism and multi-channel data input was used to synthesize pseudo-kVCT images from MVCT images.The network training results were evaluated with imaging quality evaluation parameters,such as mean absolute error(MAE),peak signal-to-noise ratio(PSNR),and structural similarity index(SSIM).Results The MAE,PSNR,and SSIM of MVCT imagesvspseudo-kVCT(5:5)images were(24.9±0.7)HUvs(17.8±0.3)HU,(29.8±0.2)dBvs(30.7±0.2)dB,and 0.841±0.007 vs 0.898±0.003,respectively.Conclusion The generated pseudo-kVCT images have advantages in noise reduction and contrast enhancement,and can reduce the need for additional MV-kVCT electron density calibration in dose calculations.The dose calculation ability of pseudo-kVCT is comparable to that of MVCT,providing a possibility for the application of pseudo-kVCT images in image-guided adaptive radiotherapy.

IL-34 can promote osteoclast differentiation and activation, which may contribute to steroidinduced osteonecrosis of the femoral head (ONFH). Animal model was constructed in both BALB/c and IL-34 deficient mice to detect the relative expression of inflammation cytokines. Micro-CT was utilized to reveal the internal structure. In vitro differentiated osteoclast was induced by culturing bone marrow-derived macrophages with IL-34 conditioned medium or M-CSF. The relative expression of pro-inflammation cytokines, osteoclast marker genes, and relevant pathways molecules was detected with quantitative real-time RT-PCR, ELISA, and Western blot. Up-regulated IL-34 expression could be detected in the serum of ONFH patients and femoral heads of ONFH mice. IL-34 deficient mice showed the resistance to ONFH induction with the up-regulated trabecular number, trabecular thickness, bone value fraction, and down-regulated trabecular separation. On the other hand, inflammatory cytokines, such as TNF-α, IFN-γ, IL-6, IL-12, IL-2, and IL-17A, showed diminished expression in IL-34 deficient ONFH induced mice. IL-34 alone or works in coordination with M-CSF to promote osteoclastogenesis and activate ERK, STAT3, and non-canonical NF-κB pathways. These data demonstrate that IL-34 can promote the differentiation of osteoclast through ERK, STAT3, and non-canonical NF-κB pathways to aggravate steroid-induced ONFH, and IL-34 can be considered as a treatment target.

Objective: The etiology of schizophrenia is unknown and is associated with abnormal spontaneous brain activity. There are no consistent results regarding the change in spontaneous brain activity of people with schizophrenia. In this study, we determined the specific changes in the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF) and regional homogeneity (ReHo) in patients with drug-naïve first-episode schizophrenia (Dn-FES). Methods: A comprehensive search of databases such as PubMed, Web of Science, and Embase was conducted to find articles on resting-state functional magnetic resonance imaging using ALFF/fALFF and ReHo in schizophrenia patients compared to healthy controls (HCs) and then, anatomical/activation likelihood estimation was performed. Results: Eighteen eligible studies were included in this meta-analysis. Compared to the spontaneous brain activity of HCs, we found changes in spontaneous brain activity in Dn-FES based on these two methods, mainly including the frontal lobe, putamen, lateral globus pallidus, insula, cerebellum, and posterior cingulate cortex. Conclusion We found that widespread abnormalities of spontaneous brain activity occur in the early stages of the onset of schizophrenia and may provide a reference for the early intervention of schizophrenia.

Objective:To compare the safety of adrenal central vein treated at different times in laparoscopic adrenal pheochromocytoma resection through abdominal approach.Methods:A study was conducted on 43 patients with adrenal pheochromocytoma admitted to Xijing Hospital, Air Force Military Medical University from June 2012 to June 2019. The included patients were divided into two groups according to the surgical method: observation group ( n=22) and control group ( n=21). The patients of observation group were ligated the central advenal vein before the tumor was completely isolated, and the patients of control group were ligated the central advenal vein after the tumor was isolated. The changes of blood catecholamine levels before anesthesia, before central adrenal vein ligation, and after tumor resection were compared between the two groups, as well as the differences in operative time, intraoperative blood loss, hospital stay, number of cases with intraoperative blood pressure fluctuations and frequency. Measurement data were expressed as mean±standard deviation ( Mean± SD), comparison between groups was by t-test; comparison of count data between groups was by Chi-square. Results:There was no significant difference in the mean operation time, the mean hospital stay, intraoperative blood loss, number of cases with dramatic blood pressure fluctuations between two groups ( P>0.05). The frequency of severe fluctuation of intraoperative blood pressure in observation group and control group was 19 times and 47 times, respectively, the difference was statistically significant ( P<0.05). There was no significant difference in the blood epinephrine and norepinephrine levels between the two groups before anesthesia and after tumor resection ( P>0.05). However, before ligation of the central vein, the epinephrine concentrations in the observation group and the control group were (572.1±282.1) pg/mL and (935.6±417.5) pg/mL, respectively, the noradrenaline concentrations were (8 347.9±4 103.6) pg/mL and (13 695.7 ±3 205.3) pg/mL, respectively, the difference was statistically significant ( P<0.05). Conclusion:Early ligation of the adrenal central vein can improve the safety of the laparoscopic approach to adrenal pheochromocytoma.

Objective:To evaluate the effect of radical image-guided radiotherapy (IGRT) on the target dose in cervical cancer and investigate the appropriate application mode.Methods:Twenty patients with cervical cancer treated with helical tomotherapy (HT) in Seventh Medical Center of PLA General Hospital from 2012 to 2016 were selected. A megavoltage CT (MVCT) scan was performed before each treatment. The obtained MVCT images were used for dose parameter in the adaptive module of HT to obtain the actual dose (Plan 1) and the non-image-guided dose parameter was simulated (Plan 2). Each single dose distribution and the corresponding fused CT images were transferred to the software Mimvista 6.5 to obtain the total radiation dose parameter by dose superposition.Results:The motion of CTV, uterus and GTV in Plan 2 was significantly larger than that of Plan 1(all P<0.05), and the largest changes were seen in the ventrodorsal and uterine direction. The V 45Gy, V 50Gy, D 98% and D mean of CTV and uterus and V 50Gy of GTV in Plan 2 were significantly decreased compared with those in Plan 1(all P<0.05). The left-right motion of Plan 1 was negatively correlated with D 2% and D 98% of CTV and uterus (both P<0.05). The head-foot motion was negatively associated with V 45Gy and V 50Gy of GTV (both P<0.05). The ventrodorsal motion was negatively correlated with D 98% of uterus ( P<0.05). The left-right motion of Plan 2 was negatively correlated with D 2% of CTV and V 50Gy of uterus (both P<0.05). The head-foot motion was negatively associated with D 98% of CTV, and D 98%, D mean, V 45Gy and V 50Gy of uterus (all P<0.05). The ventrodorsal motion was negatively correlated with D 98% of CTV, D 98%, D mean, V 45Gy and V 50Gy of uterus, and D mean and V 45Gy of GTV (all P<0.05). Conclusions:In intensity-modulated radiotherapy for cervical cancer, the uterine body displacement is large and the low CTV area is mainly located in the uterine body. IGRT can significantly reduce the dosimetric deviation induced by organ movement.

Objective:To investigate the normal range of exhaled nitric oxide (FeNO) in 6-18-year-old children in China, so as to provide a data base for the establishment of FeNO standards for Chinese children.Methods:A multi-center study was conducted on 5 949 children aged 6-18 (3 101 males and 2 848 females) in 16 pro-vinces of 7 administrative districts in China.According to the technical standard recommended by American Thoracic Society/European Respiratory Association, FeNO was measured, and the relationship of FeNO with the sex, age, height, weight, body mass index and region was discussed.Results:The geometric mean FeNO value of Chinese children aged 6-18 was 14.1 ppb, and its 95% confidence interval (skewness distribution) was 1.0-38.2 ppb.The geometric mean FeNO values of children aged 6-11 and 12-18 were 13.1 ppb and 15.7 ppb, respectively, and their 95% confidence intervals (skewness distribution) were 1.0-38.1 ppb and 2.0-38.2 ppb.For children at and under 11 years old, FeNO decreased with age, with a mean decline of 1 ppb per year.The multiple linear regression results suggested that there was a significant correlation between FeNO and age for children aged 6-11, and FeNO of children aged 12-18 was significantly correlated with the gender, height, and region(all P<0.01). Conclusions:FeNO values of Chinese children and adolescents in this study are higher than those obtained by the previous study conducted from 2010 to 2012.For children aged 12-18, 16 ppb is recommended as the clinical cut-off point.For children at or under 11 years old, the influence of age on FeNO should be considered, and the cut-off point of FeNO decreases by 1 ppb as the age is reduced by one year.