Tumor immune homeostasis is a dynamic equilibrium state in which the body removes abnormal mutated cells in time to prevent tumor development without damaging other normal cells under the surveillance of the immune system. It is an important concept to understand the process of tumor development. Programmed cell death （PCD） is a kind of regulable cell death including various forms such as apoptosis， autophagy， pyroptosis， necrosis， and ferroptosis. It is regarded as an important way for the body to remove abnormal or mutated cells. In recent years， modern research has found that PCD has a bi-directional regulatory effect on carcinogenesis and tumor development. In the early stage of tumor formation， PCD can control tumor development in time by playing a specific immune clearance role， while in the later tumorigenic stage， PCD can promote the growth and development of tumor cells by forming a tumor-specific microenvironment， resulting in carcinogenic effects. Therefore， PCD is regarded as an important way to maintain tumor immune homeostasis. Based on the idea of ''supporting the vital Qi and cultivating the root'' by professors Yu Guiqing and Piao Bingkui， the team proposed the theory of ''regulating Qi and resolving toxins'' and applied it to clinical tumor prevention and treatment. Based on the theory of ''regulating Qi and resolving toxins''， the research summarized the current progress of modern medical research on mechanisms related to PCD to explore the role of PCD in the regulation of tumor immune homeostasis. The article believed that the harmonious state of Qi movement was the basic condition for normal PCD to maintain tumor immune homeostasis， while the disorder of Qi movement and the evolution of tumor toxicity were the core processes of abnormal PCD and disorder of tumor immunity homeostasis， which led to the escape and development of tumor cells. Therefore， under the guidance of ''regulating Qi and removing toxins''， the idea of full-cycle prevention and treatment of tumors was proposed summarily. In the early stage of tumor formation， the method of ''regulating Qi movement and strengthening vital Qi'' was applied to reestablish tumor immune homeostasis and to promote the elimination of abnormal cells. In the late tumorigenic stage， the method of ''resolving toxins and dispelling evils'' was applied to reverse the specific microenvironment of tumors and inhibit the development of tumor cells， with a view to providing new theoretical support for the prevention and treatment of tumors through traditional Chinese medicine.

Tumor immune homeostasis is a dynamic equilibrium state in which the body removes abnormal mutated cells in time to prevent tumor development without damaging other normal cells under the surveillance of the immune system. It is an important concept to understand the process of tumor development. Programmed cell death （PCD） is a kind of regulable cell death including various forms such as apoptosis， autophagy， pyroptosis， necrosis， and ferroptosis. It is regarded as an important way for the body to remove abnormal or mutated cells. In recent years， modern research has found that PCD has a bi-directional regulatory effect on carcinogenesis and tumor development. In the early stage of tumor formation， PCD can control tumor development in time by playing a specific immune clearance role， while in the later tumorigenic stage， PCD can promote the growth and development of tumor cells by forming a tumor-specific microenvironment， resulting in carcinogenic effects. Therefore， PCD is regarded as an important way to maintain tumor immune homeostasis. Based on the idea of ''supporting the vital Qi and cultivating the root'' by professors Yu Guiqing and Piao Bingkui， the team proposed the theory of ''regulating Qi and resolving toxins'' and applied it to clinical tumor prevention and treatment. Based on the theory of ''regulating Qi and resolving toxins''， the research summarized the current progress of modern medical research on mechanisms related to PCD to explore the role of PCD in the regulation of tumor immune homeostasis. The article believed that the harmonious state of Qi movement was the basic condition for normal PCD to maintain tumor immune homeostasis， while the disorder of Qi movement and the evolution of tumor toxicity were the core processes of abnormal PCD and disorder of tumor immunity homeostasis， which led to the escape and development of tumor cells. Therefore， under the guidance of ''regulating Qi and removing toxins''， the idea of full-cycle prevention and treatment of tumors was proposed summarily. In the early stage of tumor formation， the method of ''regulating Qi movement and strengthening vital Qi'' was applied to reestablish tumor immune homeostasis and to promote the elimination of abnormal cells. In the late tumorigenic stage， the method of ''resolving toxins and dispelling evils'' was applied to reverse the specific microenvironment of tumors and inhibit the development of tumor cells， with a view to providing new theoretical support for the prevention and treatment of tumors through traditional Chinese medicine.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective: To reveal the molecular biological mechanism of a rare Dc-variant individual using PacBio third-generation sequencing technology. Methods: ABO and Rh blood type identification, DAT, unexpected antibody screening and D antigen enhancement test were conducted by serological testing. The absorption-elution test was used to detect the e antigen. RHCE gene typing was performed by PCR-SSP, and the 1-10 exons of RHCE were sequenced by Sanger sequencing. The full-length sequences of RHCE, RHD and RHAG were detected by PacBio third-generation sequencing technology. Results: Serological findings: Blood type O, Dc-phenotype, DAT negative, unexpected antibody screening negative; enhanced D antigen expression; no detection of e antigen in the absorption-elution test. PCR-SSP genotyping indicated the presence of only the RHCE c allele. Sanger sequencing results: Exons 5-9 of RHCE were deleted, exon 1 had a heterozygous mutation at c. 48G/C, and exon 2 had five heterozygous mutations at c. 150C/T, c. 178C/A, c. 201A/G, c. 203A/G and c. 307C/T. Third-generation sequencing results: RHCE genotype was RHCE 02N. 08/RHCE-D(5-9)-CE; RHD genotype was RHD 01/RHD 01; RHAG genotype was RHAG 01/RHAG 01 (c. 808G>A and c. 861G>A). Conclusion: This Dc-individual carries the allele RHCE 02N. 08 and the novel allele RHCE-D(5-9)-CE. The findings of this study provide data support and a theoretical basis for elucidating the molecular mechanisms underlying RhCE deficiency phenotypes.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

This paper investigates the effect of myricetin (MYR) on renal fibrosis induced by unilateral ureteral obstruction (UUO) and common bile duct ligation (CBDL) in mice and its mechanism. The animal experiment has been approved by the Ethics Committee of China Pharmaceutical University (NO: 2022-10-020). Thirty-five ICR mice were divided into control, UUO, UUO+MYR, CBDL and CBDL+MYR groups. H&E and Masson staining were used to detect pathological changes in kidney tissues. Western blot (WB) was used to detect the expression of fibrosis-related proteins in renal tissue, and total superoxide dismutase (SOD) activity detection kit (WST-8) was used to detect the changes of total SOD in renal tissue of CBDL mice. In vitro, HK-2 cells and transforming growth factor beta 1 (TGF-β1, 10 ng·mL^-1) were used to induce fibrotic model, and high glucose (30 mmol·L^-1) was used to induce oxidative stress model, and then treated with different concentrations of MYR, WB was used to detect the expression of fibrosis and oxidative stress-related proteins, while NIH/3T3 cells were treated with different concentrations of MYR, and their effects on cell proliferation were detected by 5-bromo-2′-deoxyuridine (Brdu). The results showed that the renal lesions in UUO group and CBDL group were severe, collagen deposition was obvious, the expression of collagen-Ⅰ (COL-Ⅰ), α-smooth muscle actin (α-SMA), fibronectin (FN), vimentin and plasminogen activator inhibitor-1 (PAI-1) protein was up-regulated, and the activity of SOD enzyme in CBDL group was significantly decreased. MYR partly reversed the above changes after treatment. MYR inhibited the proliferation of NIH/3T3 cells but had no effect on the proliferation of HK-2 cells, and decreased the upregulation of PAI-1, FN and vimentin in HK-2 cells stimulated by TGF-β1. MYR can also up-regulate the down-regulation of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) in HK-2 cells stimulated by high glucose. To sum up, MYR can improve renal fibrosis in vivo and in vitro, probably by inhibiting the proliferation of fibroblasts and activating Nrf2/HO-1 signal pathway to inhibit oxidative stress.

OBJECTIVE: To investigate whether electroacupuncture (EA) at sensitized acupoints could reduce sympathetic-sensory coupling (SSC) and neurogenic inflammatory response by interfering with 5-hydroxytryptamine (5-HT)ergic neural pathways to relieve colitis and somatic referred pain, and explore the underlying mechanisms. METHODS: Rats were treated with 5% dextran sodium sulfate (DSS) solution for 7 days to establish a colitis model. Twelve rats were randomly divided into the control and model groups according to a random number table (n=6). According to the "Research on Rat Acupoint Atlas", sensitized acupoints and non-sensitized acupoints were determined. Rats were randomly divided into the control, model, Zusanli-EA (ST 36), Dachangshu-EA (BL 25), and Xinshu (BL 15) groups (n=6), as well as the control, model, EA, and EA + GR113808 (a 5-HT inhibitor) groups (n=6). The rats in the control group received no treatment. Acupuncture was administered on 2 days after modeling using the stimulation pavameters: 1 mA, 2 Hz, for 30 min, with sparse and dense waves, for 14 consecutive days. GR113808 was injected into the tail vein at 5 mg/kg before EA for 10 min for 7 consecutive days. Mechanical sensitivity was assessed with von Frey filaments. Body weight and disease activity index (DAI) scores of rats were determined. Hematoxylin and eosin staining was performed to observe colon histopathology. SSC was analyzed by immunofluorescence staining. Immunohistochemical staining was performed to detect 5-HT and substance P (SP) expressions. The calcitonin gene-related peptide (CGRP) in skin tissue and tyrosine hydroxylase (TH) protein levels in DRG were detected by Western blot. The levels of hyaluronic acid (HA), bradykinin (BK), prostaglandin I2 (PGI2) in skin tissue, 5-HT, tryptophan hydroxylase 1 (TPH1), serotonin transporters (SERT), 5-HT 3 receptor (5-HT3R), and 5-HT 4 receptor (5-HT4R) in colon tissue were measured by enzyme-linked immunosorbent assay (ELISA). RESULTS: BL 25 and ST 36 acupoints were determined as sensitized acupoints, and BL 15 acupoint was used as a non-sensitized acupoint. EA at sensitized acupoints improved the DAI score, increased mechanical withdrawal thresholds, and alleviated colonic pathological damage of rats. EA at sensitized acupoints reduced SSC structures and decreased TH and CGRP expression levels (P<0.05). Furthermore, EA at sensitized acupoints reduced BK, PGI2, 5-HT, 5-HT3R and TPH1 levels, and increased HA, 5-HT4R and SERT levels in colitis rats (P<0.05). GR113808 treatment diminished the protective effect of EA at sensitized acupoints in colitis rats (P<0.05). CONCLUSION EA at sensitized acupoints alleviated DSS-induced somatic referred pain in colitis rats by interfering with 5-HTergic neural pathway, and reducing SSC inflammatory response.
Rats ; Animals ; Electroacupuncture ; Rats, Sprague-Dawley ; Serotonin ; Acupuncture Points ; Pain, Referred ; Calcitonin Gene-Related Peptide ; Signal Transduction ; Colitis/therapy* ; Indoles ; Sulfonamides

ObjectiveThe chemical exchange saturation transfer (CEST) technique has become a valuable tool in diagnosing metabolic changes associated with cerebral and systemic diseases, leveraging the calculation of compounds with exchangeable protons in proximity to water molecules. Specifically, the amide proton transfer (APT) CEST technique has shown promise in diagnosing cerebral strokes and tumors by comparing altered endogenous proteins or peptides with normal tissues. Reduced field of view (rFOV) imaging technology has been widely used in the diagnosis of small organ lesions in the body. In this study, we aim to apply the rFOV imaging to identify CEST signals in the rectum, investigating the potential utility of rFOV technique in clinical diagnosis of rectal diseases and providing metabolic insights for chemoradiotherapy. MethodsMRI images of eleven healthy volunteers were acquired using transverse Full_FOV and rFOV CEST imaging on a 3T scanner. The resolution was set at 2.5×2.5×6 mm³ and 1.5×1.5×6 mm³ for Full_FOV or the rFOV method. Saturation powers of 0.7 μT and 2 μT were applied. For the 2 μT saturation, MTRasym at ±3.5 ppm was employed, while for 0.7 μT saturation, Lorentzian difference was used for CEST quantification of the contrast maps and curves. ResultsThe rFOV method has the advantage of halving the scan time while maintaining the same contrast as the Full_FOV method. When compared to Full_FOV methods, rFOV methods exhibited nearly identical Z_spec and very similar MTRasym curves. Additionally, rFOV with a 1.5 mm×1.5 mm in-plane resolution could be achieved in approximately 3 min. rFOV method displayed better structural details for the entire rectum, including CEST contrast maps and quantitative curves. ConclusionCEST MRI proves valuable in diagnosing rectal diseases, and employing the rFOV technique could provide higher spatial and temporal resolution. CEST MRI should be the preferred choice for offering improved diagnostic capabilities with its potential for rectal disease diagnosis.

Objective To compare the effects of 20 mg qd and 10 mg bidadministration of iprrazole enteric-coated tablets on the control of gastric acid in healthy subjects.Methods A randomized,single-center,parallel controlled trial was designed to include 8 healthy subjects.Randomly divided into 2 groups,20 mg qd administration group:20 mg enteric-coated tablets of iprrazole in the morning;10 mg bid administration group:10 mg enteric-coated tablets of iprrazole in the morning and 10 mg in the evening.The pH values in the stomach of the subjects before and 24 h after administration were monitored by pH meter.The plasma concentration of iprazole after administration was determined by HPLC-MS/MS.The main pharmacokinetic parameters were calculated by Phoenix WinNonlin(V8.0)software.Results The PK parameters of iprrazole enteric-coated tablets and reference preparations in fasting group were as follows:The Cmax of 20 mg qd group and 10 mg bid group were(595.75±131.15)and(283.50±96.98)ng·mL-1;AUC0-t were(5 531.94±784.35)and(4 686.67±898.23)h·ng·mL-1;AUC0-∞ were(6 003.19±538.59)and(7 361.48±1 816.77)h·ng·mL-1,respectively.The mean time percentage of gastric pH＞3 after 20 mg qd and 10 mg bid were 82.64％and 61.92％,and the median gastric pH within 24 h were 6.25±1.49 and 3.53±2.05,respectively.The mean gastric pH values within 24 h were 5.71±1.36 and 4.23±1.45,respectively.The correlation analysis of pharmacokinetic/pharmacodynamics showed that there was no significant correlation between the peak concentration of drug in plasma and the inhibitory effect of acid.Conclusion Compared with the 20 mg qd group and the 10 mg bid group,the acid inhibition effect is better,the administration times are less,and the safety of the two administration regimes is good.