ObjectiveTo analyze the characteristic expression patterns of six neurotransmitters including 5-hydroxytryptamine （5-HT）， dopamine （DA）， acetylcholine （ACh）， norepinephrine （NE）， inhibitory neurotransmitter （INH）， and excitatory neurotransmitter （EXC） in the whole brain and different brain regions of depression patients by Search of Encephalo Telex （SET）， providing new ideas for the study of heterogeneous etiology of depression. Methods（1） A retrospective study was conducted on supra-slow signals of EEG fluctuations in 1 028 patients with depression. The SET system was used to obtain the expression information of six neurotransmitters in the whole brain and 12 brain regions： left frontal region （F3）， right frontal region （F4）， left central region （C3）， right central region （C4）， left parietal region （P3）， right parietal region （P4）， left occipital region （O1）， right occipital region （O2）， left anterior temporal region （F7）， right anterior temporal region （F8）， left posterior temporal region （T5）， and right posterior temporal region （T6）. The expression information of each neurotransmitter was compared with the normal model， and it was found that single neurotransmitter was in one of three states： increased， decreased， or normal expression. The simultaneous expression states of six neurotransmitters in the brain space were referred to as the expression pattern of multiple neurotransmitters. （2） A MySQL database was established to analyze the actual expression patterns of different neurotransmitters in the whole brain of patients with depression. （3） Factor analysis was conducted to further analyze the characteristic rules of 78 variables of neurotransmitters in the whole brain and 12 brain regions in depression patients. Results（1） The expression of single neurotransmitters in the whole brain and different brain regions of the total depression population showed one of three expression states （increased/decreased/normal）， being normal in the majority. The decreased and increased expression of 5-HT， ACh， DA， INH， EXC， and NE in the whole brain occurred in 6% and 25%， 31% and 17%， 36% and 9%， 15% and 31%， 32% and 14%， and 22% and 22%， respectively. （2） The antagonizing pairs of neurotransmitters （EXC/INH， DA/5-HT， and ACh/NE） showed significant antagonistic relationships in the whole brain and different brain regions， with a strong negative correlation between EXC and INH （P<0.01， |r| values ranging from 0.69 to 0.76）， a strong negative correlation between DA and 5-HT （P<0.01， |r| values ranging from 0.83 to 0.90）， and a moderate negative correlation between ACh and NE （P<0.01， with |r| values ranging from 0.56 to 0.66）. Meanwhile， non-antagonizing pairs of neurotransmitters in the whole brain and different brain regions also showed correlations， with DA/NE （P<0.01， |r| values ranging from 0.38 to 0.46） and NE/EXC （P<0.01， |r| values ranging from 0.56 to 0.61） showing weak and moderate negative correlations， respectively， and DA/EXC showing a weak positive correlation （P<0.01， |r| values ranging from 0.38 to 0.47）. （3） The six neurotransmitters in the 1 028 patients with depression presented a total of 170 expression patterns in the whole brain. The top 30 expression patterns were reported in this paper， with a cumulative rate of 60.60%， including patterns ① INH+/5-HT-/ACh+/DA+/NE-/EXC- （9.05%）， ② INH+/5-HT-/ACh↓/DA+/NE-/EXC- （4.57%）， and ③ INH+/5-HT-/ACh+/DA+/NE↓/EXC- （3.31%）. That is， the proportion of depression patients with normal levels of all the six neurotransmitters was 9.05%， and the patients with at least one neurotransmitter abnormality accounted for 91.95%. （4） The factor analysis extracted 22 common factors from 78 variables in the whole brain and different brain regions. These common factors showed the absolute values of loadings ranging from 0.32 to 0.86 and the eigenvalues （F） ranging from 1.03 to 13.43， with a cumulative contribution rate of 76.82%. The characteristic expression patterns included ① ACh_P3↓/ACh_W↓/ACh_C3↓/ACh_F3↓/ACh_O1↓/ACh_T5↓/ACh_F7↓/NE_P3↑/NE_W↑/NE_C3↑/NE_F3↑/NE_O1↑/NE_T5↑/NE_F7↑ （F=13.43， whole brain）， ② 5-HT_O2↑/DA_O2↓/5-HT_P4↑/DA_P4↓/5-HT_W↑/DA_W↓/5-HT_C4↑/DA_C4↓ （F=5.94）， and ③ EXC_F4↓/DA_F4↓/NE_F4↑/INH_F4↑/5-HT_F4↑/ACh_F4↓ （F=5.33）. ConclusionThe actual 170 expression patterns of 6 neurotransmitters in the whole brain of 1 028 depression patients indicate that depression is a heterogeneous disease with individualized characteristics. The 22 characteristic expression patterns in the whole brain and 12 brain regions verify the pathogenesis hypothesis of multi-neurotransmitters oscillation imbalance in brains of depression patients. In summary， this study provides new guidance for the etiology， diagnosis， and treatment of depression and establishes a methodological foundation for the effectiveness evaluation of individualized treatment of depression by traditional Chinese medicine based on the objective biological markers.

ObjectiveTo analyze the characteristic expression patterns of six neurotransmitters including 5-hydroxytryptamine （5-HT）， dopamine （DA）， acetylcholine （ACh）， norepinephrine （NE）， inhibitory neurotransmitter （INH）， and excitatory neurotransmitter （EXC） in the whole brain and different brain regions of depression patients by Search of Encephalo Telex （SET）， providing new ideas for the study of heterogeneous etiology of depression. Methods（1） A retrospective study was conducted on supra-slow signals of EEG fluctuations in 1 028 patients with depression. The SET system was used to obtain the expression information of six neurotransmitters in the whole brain and 12 brain regions： left frontal region （F3）， right frontal region （F4）， left central region （C3）， right central region （C4）， left parietal region （P3）， right parietal region （P4）， left occipital region （O1）， right occipital region （O2）， left anterior temporal region （F7）， right anterior temporal region （F8）， left posterior temporal region （T5）， and right posterior temporal region （T6）. The expression information of each neurotransmitter was compared with the normal model， and it was found that single neurotransmitter was in one of three states： increased， decreased， or normal expression. The simultaneous expression states of six neurotransmitters in the brain space were referred to as the expression pattern of multiple neurotransmitters. （2） A MySQL database was established to analyze the actual expression patterns of different neurotransmitters in the whole brain of patients with depression. （3） Factor analysis was conducted to further analyze the characteristic rules of 78 variables of neurotransmitters in the whole brain and 12 brain regions in depression patients. Results（1） The expression of single neurotransmitters in the whole brain and different brain regions of the total depression population showed one of three expression states （increased/decreased/normal）， being normal in the majority. The decreased and increased expression of 5-HT， ACh， DA， INH， EXC， and NE in the whole brain occurred in 6% and 25%， 31% and 17%， 36% and 9%， 15% and 31%， 32% and 14%， and 22% and 22%， respectively. （2） The antagonizing pairs of neurotransmitters （EXC/INH， DA/5-HT， and ACh/NE） showed significant antagonistic relationships in the whole brain and different brain regions， with a strong negative correlation between EXC and INH （P<0.01， |r| values ranging from 0.69 to 0.76）， a strong negative correlation between DA and 5-HT （P<0.01， |r| values ranging from 0.83 to 0.90）， and a moderate negative correlation between ACh and NE （P<0.01， with |r| values ranging from 0.56 to 0.66）. Meanwhile， non-antagonizing pairs of neurotransmitters in the whole brain and different brain regions also showed correlations， with DA/NE （P<0.01， |r| values ranging from 0.38 to 0.46） and NE/EXC （P<0.01， |r| values ranging from 0.56 to 0.61） showing weak and moderate negative correlations， respectively， and DA/EXC showing a weak positive correlation （P<0.01， |r| values ranging from 0.38 to 0.47）. （3） The six neurotransmitters in the 1 028 patients with depression presented a total of 170 expression patterns in the whole brain. The top 30 expression patterns were reported in this paper， with a cumulative rate of 60.60%， including patterns ① INH+/5-HT-/ACh+/DA+/NE-/EXC- （9.05%）， ② INH+/5-HT-/ACh↓/DA+/NE-/EXC- （4.57%）， and ③ INH+/5-HT-/ACh+/DA+/NE↓/EXC- （3.31%）. That is， the proportion of depression patients with normal levels of all the six neurotransmitters was 9.05%， and the patients with at least one neurotransmitter abnormality accounted for 91.95%. （4） The factor analysis extracted 22 common factors from 78 variables in the whole brain and different brain regions. These common factors showed the absolute values of loadings ranging from 0.32 to 0.86 and the eigenvalues （F） ranging from 1.03 to 13.43， with a cumulative contribution rate of 76.82%. The characteristic expression patterns included ① ACh_P3↓/ACh_W↓/ACh_C3↓/ACh_F3↓/ACh_O1↓/ACh_T5↓/ACh_F7↓/NE_P3↑/NE_W↑/NE_C3↑/NE_F3↑/NE_O1↑/NE_T5↑/NE_F7↑ （F=13.43， whole brain）， ② 5-HT_O2↑/DA_O2↓/5-HT_P4↑/DA_P4↓/5-HT_W↑/DA_W↓/5-HT_C4↑/DA_C4↓ （F=5.94）， and ③ EXC_F4↓/DA_F4↓/NE_F4↑/INH_F4↑/5-HT_F4↑/ACh_F4↓ （F=5.33）. ConclusionThe actual 170 expression patterns of 6 neurotransmitters in the whole brain of 1 028 depression patients indicate that depression is a heterogeneous disease with individualized characteristics. The 22 characteristic expression patterns in the whole brain and 12 brain regions verify the pathogenesis hypothesis of multi-neurotransmitters oscillation imbalance in brains of depression patients. In summary， this study provides new guidance for the etiology， diagnosis， and treatment of depression and establishes a methodological foundation for the effectiveness evaluation of individualized treatment of depression by traditional Chinese medicine based on the objective biological markers.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Lignans are a powerful weapon for plants to resist stresses and have diverse bioactive functions to protect human health. Elucidating the mechanisms of stereoselective biosynthesis and response to stresses of lignans is important for the guidance of plant improvement. Here, we identified the complete pathway to stereoselectively synthesize antiviral (-)-lariciresinol glucosides in Isatis indigotica roots, which consists of three-step sequential stereoselective enzymes DIR1/2, PLR, and UGT71B2. DIR1 was further identified as the key gene in respoJanuary 2024nse to stresses and was able to trigger stress defenses by mediating the elevation in lignan content. Mechanistically, the phytohormone-responsive ERF transcription factor LTF1 colocalized with DIR1 in the cell periphery of the vascular regions in mature roots and helped resist biotic and abiotic stresses by directly regulating the expression of DIR1. These systematic results suggest that DIR1 as the first common step of the lignan pathway cooperates with PLR and UGT71B2 to stereoselectively synthesize (-)-lariciresinol derived antiviral lignans in I. indigotica roots and is also a part of the LTF1-mediated regulatory network to resist stresses. In conclusion, the LTF1-DIR1 module is an ideal engineering target to improve plant Defenses while increasing the content of valuable lignans in plants.

Objective To investigate the predictive value of new simplified insulin resistance(IR)assessment indexes in identifying subclinical left ventricular systolic function impairment in patients with type 2 diabetes mellitus(T2DM).Methods A total of 150 T2DM patients with preserved left ventricular ejection fraction(LVEF≥50%)who were admitted to Department of Endocrinology of the First Affiliated Hospital of Air Force Medical University from June 2021 to December 2021 were retrospectively analyzed.All patients underwent two-dimensional speckle tracking echocardiography to measure left ventricular global longitudinal strain(GLS).According to GLS value,the subjects were divided into the normal group(GLS≥18%group,n=80)and the impaired group(GLS<18%group,n=70).Some new simplified IR assessment indicators were calculated and compared between the two groups,including body mass index(BMI),TG/HDL-C ratio,triglyceride-glucose(TyG)index,TyG-BMI index,TyG-WHR and metabolic score for IR(METS-IR).Correlation between the GLS and the new simplified IR assessment indexes was analyzed.The receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficacy of different simplified IR assessment indexes,with the area under the curve(AUC)calculated.Furthermore,according to whether the subjects were complicated with hypertension,binary logistics regression analysis was performed to explore the independent correlation between the simplified IR assessment index and GLS<18%.Results Total 150 were included with aged(54.5±13.7)years with 96(64.0%)men and 54(36.0%)women.Compared with the GLS≥18%group,the TG/HDL-C ratio,TyG index,TyG-BMI,and METS-IR of subjects in the GLS<18%group were significantly increased(P<0.05).Pearson correlation analysis showed that TG/HDL-C ratio,TyG index,TyG-BMI,TyG-WHR,and METS-IR were negatively correlated with GLS(P<0.05).ROC analysis showed that TyG index had a certain predictive value for the evaluation of GLS<18%(AUC=0.678,95%CI 0.591-0.765,P<0.001).Stratification based on hypertension and further adjusting for confounding factors,TyG index remains significantly associated with GLS<18%(OR=3.249,95%CI 1.045-10.103,P=0.042).Conclusions The novel simplified insulin resistance evaluation indexes are closely associated with left ventricular subclinical systolic dysfunction in T2DM patients with preserved ejection fraction.TyG index is an effective index to identify left ventricular subclinical dysfunction in these populations.

Objective To study the feasibility on automatic contouring of pelvic intestinal tube based on deep learning for radiotherapy images.Methods A total of 100 patients with diagnosis of rectal cancer,received radiotherapy in Zhongshan Hospital,Fudan University from 2019 to 2021,were randomly selected.Sixty cases were randomly enrolled to train the models,and the other 40 cases were applied to test.Based on the original small intestine model in automatic segmentation software AccuContour,60,40 and 20(2 groups)cases in the model cases were used to train the models Rec60,Rec40,Rec20A and Rec20B with manual contouring as ground truth.Other 40 cases for test were applied to evaluate the Dice similarity coefficient(DSC),95%Hausdorff distance(HD95)and average symmetric surface distance(ASSD)between the manual contouring and original model along with model Rec60.The DSC of the 5 groups of auto-segmentations were compared as well.The paired t tests were performed for each pair of the original model and 4 trained models.Results The small bowel contoured by trained models were more similar to the manual contouring.They could distinguish the boundary of the intestinal tube better and distinguish the small bowel from the colon.The average DSC,HD95 and ASSD of Rec60 were 0.16 higher(P＜0.001),12.4 lower(P＜0.001)and 5.14 lower(P＜0.001)than the original model respectively.According to the paired t tests,there were no statistical differences in DSC between the 4 training models and the original model.No statistical difference was observed between Rec60 and Rec40,while they were both significantly different from the two Rec20 models.There was no statistical difference between Rec20B and Rec20B.Conclusion For radiotherapy images,model training can effectively improve the accuracy of intestinal tube delineation.Forty cases were enough for training an optimal model of automatic segmentation for pelvic intestinal tube in AccuContour software.

ObjectiveTo investigate the induction of ferroptosis by polyphyllin Ⅱ （PPⅡ） in hepatocellular carcinoma HepG2 cells and its underlying mechanism. MethodThe effect of PPⅡ （0， 1.5， 3.0， 4.5， 6.0， 9.0， 18.0 mg·L^-1） on the in vitro proliferation of HepG2 cells was assessed using the methyl thiazolyl tetrazolium （MTT） assay. Colony formation ability of HepG2 cells was evaluated through a colony formation assay. Cell migration ability was assessed via a scratch assay. Lactate dehydrogenase （LDH） content in HepG2 cells was measured using a kit. Reactive oxygen species （ROS） levels in HepG2 cells were observed using a fluorescence inverted microscope. Malondialdehyde （MDA）， glutathione （GSH）， and free Fe²⁺ content in HepG2 cells were detected using respective kits. The mitochondrial ultrastructure in HepG2 cells was observed by transmission electron microscopy. The expression of ferroptosis-related proteins p53， solute carrier family 7 member 11 （SLC7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， and transferrin receptor 1 （TFR1） in HepG2 cells was detected using Western blot. ResultCompared with the control group， the PPⅡ treatment groups showed significantly decreased survival rate of HepG2 cells in a dose-dependent manner （P<0.01）， significantly reduced number of cell colonies （P<0.01）， significantly shortened scratch healing distance， inverse correlation of the migration distance with drug concentration （P<0.01）， significantly increased LDH leakage in cells （P<0.01）， significantly enhanced relative fluorescence intensity of intracellular ROS， and significantly increased accumulation of lipid peroxide MDA （P<0.01）， decreased intracellular GSH content with increasing drug concentration （P<0.01）， and significantly enhanced fluorescence intensity of FeRhoNox-1 in cells （P<0.01）. Moreover， cells exhibited vacuolation， and mitochondria showed significant shrinkage with reduced or even disappeared cristae. Compared with the results in the control group， the expression of p53， ACSL4， and TFR1 proteins significantly increased， while the expression of SLC7A11 and GPX4 proteins significantly decreased in the PPⅡ treatment groups （P<0.05）. ConclusionIn summary， PPⅡ induces ferroptosis in HepG2 cells by regulating the p53/SLC7A11/GPX4 signaling axis， promoting ACSL4 expression and Fe³⁺ uptake， leading to an imbalance in the antioxidant system.

Objective Tissue uptake and distribution of nano-/microplastics was studied at a single high dose by gavage in vivo.Methods Fluorescent microspheres (100 nm, 3 μm, and 10 μm) were given once at a dose of 200 mg/(kg·body weight). The fluorescence intensity (FI) in observed organs was measured using the IVIS Spectrum at 0.5, 1, 2, and 4 h after administration. Histopathology was performed to corroborate these findings.Results In the 100 nm group, the FI of the stomach and small intestine were highest at 0.5 h, and the FI of the large intestine, excrement, lung, kidney, liver, and skeletal muscles were highest at 4 h compared with the control group (P < 0.05). In the 3 μm group, the FI only increased in the lung at 2 h (P < 0.05). In the 10 μm group, the FI increased in the large intestine and excrement at 2 h, and in the kidney at 4 h (P < 0.05). The presence of nano-/microplastics in tissues was further verified by histopathology. The peak time of nanoplastic absorption in blood was confirmed.Conclusion Nanoplastics translocated rapidly to observed organs/tissues through blood circulation;however, only small amounts of MPs could penetrate the organs.