ObjectiveTo investigate the effects of Maxing Kugan decoction （MKD） on inflammatory response and apoptosis in rats with oleic acid （OA）-induced acute lung injury （ALI） and explore its mechanism of action. MethodsSixty Sprague-Dawley （SD） rats were randomly assigned into six groups： a control group， a model group， a dexamethasone-treated group （2 mg·kg^-1）， and three MKD-treated groups at low， medium， and high doses （3.1， 6.2，12.4 g·kg^-1）. Each group was administered either an equivalent volume of normal saline or the corresponding concentration of MKD by gavage for seven consecutive days. The model group and each administration group were used to establish the ALI model by tail vein injection of OA （0.2 mL·kg^-1）. Twelve hours after modeling， blood gas analyses were conducted， and the wet-to-dry （W/D） weight ratio of lung tissue was measured for each group. Additionally， enzyme-linked immunosorbent assay （ELISA） was employed to quantify the levels of tumor necrosis factor-alpha （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6） in the bronchoalveolar lavage fluid （BALF） of the rats. Cell damage and apoptosis in lung tissue were examined via hematoxylin-eosin （HE） staining and TdT-mediated dUTP-biotin nick end labeling （TUNEL） assays， and the results were subsequently scored. The expression levels of the p38 mitogen-activated protein kinase （p38 MAPK）/nuclear factor kappa-B （NF-κB） signaling pathway and apoptosis-related proteins and mRNAs were assessed using Western blot and real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. ResultsCompared with the control group， the model group exhibited a significant decrease in partial pressure of oxygen （PaO₂）， blood oxygen saturation （SaO₂）， and oxygenation index （PaO₂/FiO₂）， along with a marked increase in partial pressure of carbon dioxide （PaCO₂） and lung W/D ratio （P<0.01）. Additionally， levels of TNF-α， IL-6， and IL-1β in BALF were significantly elevated （P<0.01）. Histopathological analysis of lung tissue showed significant inflammatory infiltration， tissue edema， alveolar septal thickening， and apoptosis of lung tissue. Pronounced increases were observed in the mRNA expression levels of p38 MAPK， NF-κB p65， inhibitor of NF-κB （IκBα）， B-cell lymphoma-2 associated x protein （Bax）， and Caspases-3， as well as the protein expression levels of p-p38 MAPK， p-NF-κB p65， p-IκBα， Bax， Caspases-3， and cleaved Caspases-3， while the mRNA and protein expression of Bcl-2 was downregulated （P<0.01）. Compared with the model group， MKD significantly elevated PaO₂， SaO₂， and PaO₂/FiO₂ while reducing PaCO₂ and W/D ratio in rats （P<0.01）. It also greatly reduced TNF-α， IL-6， and IL-1β levels in BALF （P<0.01） and alleviated inflammatory infiltration， tissue edema， alveolar septal thickening， and apoptosis of lung tissue. Additionally， it downregulated the mRNA expression of p38 MAPK， NF-κB p65， IκBα， Bax， Caspases-3， as well as protein expression of p-p38 MAPK， p-NF-κB p65， p-IκBα， Bax， Caspases-3， and cleaved Caspases-3 in lung tissue （P<0.05， P<0.01）， while significantly upregulating mRNA and protein expression of Bcl-2 （P<0.01）. ConclusionMKD exerts a protective effect on OA-induced ALI rats， potentially through the regulation of the p38 MAPK/NF-κB signaling pathway to inhibit inflammation and apoptosis.

ObjectiveTo investigate the effects of Maxing Kugan decoction （MKD） on inflammatory response and apoptosis in rats with oleic acid （OA）-induced acute lung injury （ALI） and explore its mechanism of action. MethodsSixty Sprague-Dawley （SD） rats were randomly assigned into six groups： a control group， a model group， a dexamethasone-treated group （2 mg·kg^-1）， and three MKD-treated groups at low， medium， and high doses （3.1， 6.2，12.4 g·kg^-1）. Each group was administered either an equivalent volume of normal saline or the corresponding concentration of MKD by gavage for seven consecutive days. The model group and each administration group were used to establish the ALI model by tail vein injection of OA （0.2 mL·kg^-1）. Twelve hours after modeling， blood gas analyses were conducted， and the wet-to-dry （W/D） weight ratio of lung tissue was measured for each group. Additionally， enzyme-linked immunosorbent assay （ELISA） was employed to quantify the levels of tumor necrosis factor-alpha （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6） in the bronchoalveolar lavage fluid （BALF） of the rats. Cell damage and apoptosis in lung tissue were examined via hematoxylin-eosin （HE） staining and TdT-mediated dUTP-biotin nick end labeling （TUNEL） assays， and the results were subsequently scored. The expression levels of the p38 mitogen-activated protein kinase （p38 MAPK）/nuclear factor kappa-B （NF-κB） signaling pathway and apoptosis-related proteins and mRNAs were assessed using Western blot and real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. ResultsCompared with the control group， the model group exhibited a significant decrease in partial pressure of oxygen （PaO₂）， blood oxygen saturation （SaO₂）， and oxygenation index （PaO₂/FiO₂）， along with a marked increase in partial pressure of carbon dioxide （PaCO₂） and lung W/D ratio （P<0.01）. Additionally， levels of TNF-α， IL-6， and IL-1β in BALF were significantly elevated （P<0.01）. Histopathological analysis of lung tissue showed significant inflammatory infiltration， tissue edema， alveolar septal thickening， and apoptosis of lung tissue. Pronounced increases were observed in the mRNA expression levels of p38 MAPK， NF-κB p65， inhibitor of NF-κB （IκBα）， B-cell lymphoma-2 associated x protein （Bax）， and Caspases-3， as well as the protein expression levels of p-p38 MAPK， p-NF-κB p65， p-IκBα， Bax， Caspases-3， and cleaved Caspases-3， while the mRNA and protein expression of Bcl-2 was downregulated （P<0.01）. Compared with the model group， MKD significantly elevated PaO₂， SaO₂， and PaO₂/FiO₂ while reducing PaCO₂ and W/D ratio in rats （P<0.01）. It also greatly reduced TNF-α， IL-6， and IL-1β levels in BALF （P<0.01） and alleviated inflammatory infiltration， tissue edema， alveolar septal thickening， and apoptosis of lung tissue. Additionally， it downregulated the mRNA expression of p38 MAPK， NF-κB p65， IκBα， Bax， Caspases-3， as well as protein expression of p-p38 MAPK， p-NF-κB p65， p-IκBα， Bax， Caspases-3， and cleaved Caspases-3 in lung tissue （P<0.05， P<0.01）， while significantly upregulating mRNA and protein expression of Bcl-2 （P<0.01）. ConclusionMKD exerts a protective effect on OA-induced ALI rats， potentially through the regulation of the p38 MAPK/NF-κB signaling pathway to inhibit inflammation and apoptosis.

Diabetic macular edema(DME), a serious complication of diabetic retinopathy(DR), is a chronic condition caused by multiple factors. Throughout its progression, inflammatory factors and vascular endothelial growth factor(VEGF)play a critical role. Anti-VEGF drugs have shown significant effectiveness in the treatment of DME; however, some patients may experience persistent DME after injection or require frequent injections. Dexamethasone intravitreal implants(DEX implants)serve as a sustained-release implant characterized by a reasonable release profile and high bioavailability. They offer safe, effective, and prolonged anti-inflammatory effects, aiding in the repair of retinal barrier and reduction of exudation. To further enhance patients' visual quality, exploring the efficacy of DEX implants in combination with existing treatment regimens has great clinical significance. This review primarily discusses the research advancements in DEX implants, focusing on their pharmacological properties, indications for use, and their combination with existing drugs and treatment methods. It also evaluates the advantages and disadvantages of combination therapy or switching to DEX implants compared to current standard treatments, aiming to provide guidance for personalized treatment options for patients with DME.

Objective To analyze the adverse reaction reports （ADRs） of drug-induced liver injury in recent ten years, explore the characteristics and related rules of drug-induced liver injury, and provide reference for clinical safe drug use. Methods ADRs in our hospital from 2011 to 2021 which belonged to drug-induced liver injuries were collected, and Pareto analysis was carried on. Results In 259 ADR reports, the most common type of drug-induced liver injury was hepatocellular injury （37.84%）. The age of drug-induced liver injury was mainly over 46 years, totaling 195 （75.28%）. Drugs were mainly distributed in cardiovascular system medicine （44.02%）, anti-infective medicine （23.94%）and anti-tumor medicine （11.58%）. Among the cardiovascular drugs, atorvastatin calcium 40mg and over 40mg were the highest proportion, with 53 cases （46.49%）. The main anti-infectious drugs were cephalosporins （29.03%）, carbapenem （19.35%）， antifungal （17.74%）and quinolones （11.29%）. Adverse reactions occurred within 6 days （69.88%）, the duration of adverse reactions was 1-2 weeks （31.66%）, and most patients were improved （47.88%） or cured （37.07%）. Conclusion For middle-aged and elderly patients, when the application of cardiovascular system drugs, anti-infective drugs or anti-tumor drugs, it is necessary to monitor the liver function changes of patients for at least 6 days. If there are abnormalities, the drugs should be stopped or given treatment in time, to avoid the progress of drug-induced liver injury.

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.

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the application of blood conservation measures in obstetric patients with different red blood cell transfusion volumes and to assess the impact of different transfusion volumes on postpartum outcomes. Methods: A retrospective investigation was conducted on 448 obstetric patients who received blood transfusions at the Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine from January 2016 to December 2022. Patients were divided into four groups (1-2 units group, 3-4 units group, 5-6 units group, and >6 units group) based on the volumes of red blood cells (RBCs) transfused during and within 7 days after delivery. The maternal physiological indicators, pre- and postpartum laboratory test indicators, obstetric complications, application of blood conservation measures, use of blood products, and postpartum outcomes were reviewed. The clinical characteristics, application of blood conservation measures, and their impact on postpartum outcomes were compared among different transfusion groups. Results: There were statistically significant differences in the multivariate logistic analysis of history of previous cesarean section (OR=1.781), eclampsia/pre-eclampsia/(OR=1.972) and postpartum blood loss>1 000 mL（OR=1.699）(P<0.05) among different transfusion groups. In terms of blood conservation measures, the more RBCs transfused, the higher the rate of mothers receiving blood conservation measures such as balloon occlusion, arterial ligation, autologous blood transfusion with a cell saver, and hysterectomy. With the increase in the volume of RBCs transfusion, the demand for fresh frozen plasma（FFP）, cryoprecipitate, and platelet transfusions also increased. The hospitalization days for the four groups of parturients were 6.0 (4.0-9.0), 7.5 (5.0-14.8), 7.0 (4.5-13.0) and 11.0 (9.0-20.5), respectively (P<0.05) and the rates of ICU transfer were 2.0% (5/250), 9.4% (12/128),18.2% (6/33) and 51.4% (19/37), respectively (P<0.05). Both increased significantly with the increase in the volume of RBCs transfusion, and the differences between groups were statistically significant. Conclusion: Parturients who received higher volume of RBCs had multiple risks factors for bleeding before childbirth, had higher postpartum blood loss, and had a higher rate of application of various blood conservation measures. In addition, an increase in the volume of RBCs transfusion may have adverse effects on postpartum recovery.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.