BACKGROUND:Wogonin is a flavonoid extracted from the root of Scutellaria baicalensis.Previous studies have shown that baicalein has protective effects against cerebral ischemia-reperfusion injury,and can also reduce blood sugar and complications in diabetic mice,but its role and mechanism in diabetic cerebral infarction remain unclear. OBJECTIVE:To explore the effect of wogonin on nerve injury in rats with diabetic cerebral infarction and its mechanism. METHODS:Sprague-Dawley rats were randomly divided into six groups:control group,model group,low-dose wogonin group,medium-dose wogonin group,high-dose wogonin group,and high-dose wogonin+Ras homolog gene family member A(RhoA)activator group.Except for the control group,the other rats were established with diabetes and cerebral ischemia models using intraperitoneal injection of streptozotocin and middle cerebral artery occlusion.Low,medium-and high-dose wogonin groups were intragastrically given 10,20,40 mg/kg wogonin,respectively;high-dose wogonin+RhoA activator group was intragastrically given 40 mg/kg wogonin and intraperitoneally injected 10 mg/kg lysophosphatidic acid;control group and model group were given the same amount of normal saline once a day for 7 consecutive days.Rats in each group were evaluated for neurological deficits and their blood glucose levels were measured after the last dose.TTC staining was applied to detect the volume of cerebral infarction.Hematoxylin-eosin staining was applied to observe pathological changes in brain tissue.ELISA kit was applied to detect tumor necrosis factor-α,interleukin-6,malondialdehyde,and superoxide dismutase levels in brain tissue.Western blot was applied to detect the protein expression of RhoA and Rho-associated protein kinase(ROCK)2 in brain tissue. RESULTS AND CONCLUSION:Compared with the control group,the neuronal structure of rats in the model group was severely damaged,with cell necrosis and degeneration,the neurological deficit score,blood glucose level,and infarct volume were significantly elevated(P<0.05),the levels of tumor necrosis factor-α,interleukin-6,and malondialdehyde,and the protein expression of RhoA and ROCK2 in brain tissue were significantly increased(P<0.05),and the superoxide dismutase level was decreased(P<0.05).Compared with the model group,the low-,medium-,and high-dose wogonin groups showed improved neuronal damage,reduced cell degeneration and necrosis,a significant reduction in neurological deficit score,blood glucose level,infarct volume,and the levels of tumor necrosis factor-α,interleukin-6,and malondialdehyde,and the protein expression of RhoA and ROCK2 in brain tissue,and an increase in the superoxide dismutase level(P<0.05).Compared with the high-dose wogonin group,the high-dose wogonin+RhoA activator group significantly weakened the improvement in the above indexes of rats with diabetic cerebral infarction(P<0.05).To conclude,wogonin can improve the blood glucose level in rats with diabetic cerebral infarction,reduce cerebral infarction and nerve injury,and its mechanism may be related to the inhibition of RhoA/ROCK signaling pathway.

BackgroundAtypical antipsychotics have been widely used in patients with chronic schizophrenia， and aripiprazole and risperidone are the most commonly used drugs. The mechanism of action of the two is different， while previous studies have provided insufficient credible evidence from multiple perspectives to support the comparative efficacy of the two drugs in improving symptoms in patients with chronic schizophrenia. ObjectiveTo compare the efficacy of aripiprazole and risperidone on the improvement of symptoms， prepulse inhibition （PPI）， cognitive functioning and neurotrophic factors in patients with chronic schizophrenia， so as to provide effective treatment regimens for these patients. MethodsA total of 86 patients with chronic schizophrenia attending the psychiatry department of the Third People's Hospital of Fuyang from March 2021 to March 2023 and fulfilling the diagnostic criteria of International Classification of Diseases， tenth edition （ICD-10） were enrolled and grouped using random number table method， each with 43 cases. Aripiprazole group was given oral aripiprazole once daily at an initial dose of 5 mg for one week and then gradually increased to a maximum dose of 25 mg. Risperidone group received oral risperidone twice daily at an initial dose of 0.5 mg for one week and then gradually increased to a maximum dose of 3 mg. Treatment in both groups lasted 3 months. Before treatment and 3 months after treatment， Patients were required to complete Positive and Negative Symptom Scale （PANSS）， detection of both strong and weak PPIs in a startle modification passive attention paradigm， Wisconsin Card Sorting Test （WCST） and the measurement of neurotrophic factors at baseline and after treatment. The adverse reactions were recorded. Analysis of covariance was used to test the difference between the PANSS score， PPI， WCST and neurotrophic factor levels of the groups， with the pretest used as the covariate. Results3 months after treatment， no statistical difference was found in the scores of PANSS general psychopathology subscale， positive symptom subscale， negative symptom subscale and total score between two groups after treatment （F=0.621， 0.815， 0.743， 0.752， P>0.05）. There were no statistically significant differences between the two groups in PPI inhibition rate， single intense stimulus amplitude， single intense stimulus latency， prepulse inhibition amplitude， or prepulse inhibition latency （F=0.174， 0.001， 0.183， 0.171， 0.001， P>0.05）. There was no statistically significant difference in the total number of WCST tests between two groups （F=0.512， P>0.05）， whereas aripiprazole group reported significantly larger total numbers of categories completed and correct responses as well as smaller total numbers of random errors and perseverative errors compared to risperidone group （F=3.737， 4.621， 4.892， 5.130， P<0.05）. A significant increase in brain-derived neurotrophic factor （BDNF） and nerve growth factor （NGF） along with a reduction in glial fibrillary acidic protein （GFAP） were documented in risperidone group when compared to risperidone group （F=4.414， 3.781， 6.319， P<0.05）. No significant difference was demonstrated in the incidence of adverse reactions between the two groups （χ²=0.261， P>0.05）. ConclusionAripiprazole may be more beneficial than risperidone in improving cognitive functioning and neurotrophic factor levels in patients with chronic schizophrenia. ［Funded by Scientific Research Project of Fuyang Municipal Health Commission in 2021 （number， FY2021-147）］

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 predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Objective To evaluate the protective effect of radiation protection safety education (RPSE) on patients with differentiated thyroid carcinoma (DTC) undergoing iodine-131 (¹³¹I) treatment. Methods The DTC patients who undergo ¹³¹I treatment were divided into the control group and the RPSE group using the convenience sampling method, with 142 patients in each group. Patients in the control group received routine health education, while the RPSE group received routine health education combined with RPSE. Dose equivalent rate (DER) on pillows, bed sheets, quilt covers, and household waste of patients were compared between the two groups upon discharge. Results The median (M) DERs of patients' pillows, bed sheets, quilt covers and household waste were 3.86, 3.63, 3.91 and 56.59 times higher in the control group compared with the environmental background level, respectively. The M DERs of patients' pillows, bed sheets, quilt covers were 2.23, 2.18, and 2.55 times higher in the RPSE group compared with the environmental background level, while the M DER of household waste was equivalent to the environmental background level. The DERs of patients' pillows, bed sheets, quilt covers, and household waste in the RPSE group were significantly lower than those in the control group (all P<0.001). The DERs of the above four items were lower in both male and female patients in RPSE group compared with same-gender patients in the control group (all P<0.001). The patients' DERs of the above indicators had no significant difference among different gender in both control group and RPSE group (all P>0.05), except for higher DER of household waste in female patients than that of male patients in the control group (P<0.05). There were no significant differences in the DERs of pillows, bed sheets, quilt covers, and household waste across subgroups, where patients received different treatment doses, of both the control group and the RPSE group (all P>0.05). Conclusion RPSE for DTC patients treated with ¹³¹I, reduces the DERs of pillows, bed sheets, quilt covers, and particularly household waste.

Humans ; Aged ; Lung Diseases ; Pneumonia/drug therapy* ; Adrenal Cortex Hormones/therapeutic use* ; Pulmonary Disease, Chronic Obstructive/drug therapy* ; Administration, Inhalation ; Community-Acquired Infections/drug therapy*

ObjectiveThrough the correlation analysis between intestinal absorption profile and inhibition of macrophage foaming， the pharmacodynamic components of Zhuriheng dripping pills（ZRH） were explored to provide a basis for establishing its quality standard. MethodIntestinal absorption fluids with 0， 5， 10， 15， 20 times clinical equivalent doses were prepared by a rat everted gut sac（EGS）， and the oxidized low density lipoprotein（ox-LDL）-induced RAW264.7 macrophage foaming model was used to investigate the effect of intestinal absorption fluid with different doses on the accumulation of lipids in RAW264.7 cells by oil red O staining and cholesterol content determination， and to screen for the optimal dose. Ultra performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Exactive Orbitrap MS） was used to analyze and identify intestinal absorption fractions of ZRH intestinal absorption fluids， and partial least squares-discriminant analysis（PLS-DA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were performed on different doses of ZRH intestinal absorption fluids using SIMCA 13.0 with peak area as the independent variable and the pharmacodynamic indicators as the dependent variables to screen the compounds with variable importance in the projection（VIP） value>1.0 as contributing components， and Pearson correlation analysis was used to determine the spectral effect relationship， determined the compounds and positive correlation with pharmacodynamic were as active ingredients. Molecular docking was used to verify the binding energy of peroxisome proliferator-activated receptor α（PPARα）， PPARγ， PPARβ， human retinoid X receptor α（RXRA） and nuclear transcription factor-κB（NF-κB） with the active ingredients in ZRH intestinal absorption fluids. Real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was performed to detect the mRNA levels of PPARγ， scavenger receptor A1（SRA1） and adenosine triphosphate-binding cassette transporter A1（ABCA1） in RAW264.7 cells， Westen blot was used to detect the expression level of PPARγ protein in RAW264.7 cells， and enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of interleukin（IL）-1β and NF-κB in RAW264.7 cells. ResultAccording to the results of oil red O staining and cholesterol content determination， the ZRH intestinal absorption fluids could significantly reduce macrophage foaming， and intestinal absorption fluids with 15， 20 times clinical equivalent doses had the best effect， the 15-fold ZRH intestinal absorption fluid was finally determined as the study subject. Spectral effect relationship showed that 52 corresponding peaks in the ZRH-containing intestinal fluid were positively correlated with the efficacy， including organic acids， phenylpropanoids， iridoids， flavonoids， bile acids， coumarins and chromones. Target validation results showed that 86.9%-96.2% of the total components processed good binding activities with the key targets of PPARα， PPARγ， PPARβ， RXRA and NF-κB， and the docking energy values were all less than -6.0 kcal·mol^-1（1 cal≈4.19 J）. The results of validation showed that， compared with the normal group， the model group showed a significant increase in the levels of SRA1 and PPARγ mRNA expression， a significant decrease in ABCA1 mRNA expression， a significant increase in the level of PPARγ protein expression， and a significant increase in the levels of IL-1β and NF-κB（P<0.01）， compared with the model group， the 15-fold intestinal absorption fluid group showed a significant decrease in the levels of SRA1 and PPARγ mRNA expression（P<0.05， P<0.01）， ABCA1 mRNA expression level was significantly up-regulated， the levels of IL-1β and NF-κB were significantly reduced（P<0.01）， and PPARγ protein expression level was significantly reduced（P<0.05）. ConclusionThis study identifies 52 components and their metabolites in ZRH intestinal absorption fluid that are positively correlated with the inhibition of macrophage foaming， which may be related to the regulation of the PPARs pathway in cells and the reduction of the levels of inflammatory factors， and can provide a reference for the quality control and clinical application of ZRH.

Biosensor analysis technology is a kind of technology with high specificity that can convert biological reactions into optical and electrical signals. In the development of drugs for Alzheimer's disease (AD), according to different disease hypotheses and targets, this technology plays an important role in confirming targets and screening active compounds. This paper briefly describes the pathogenesis of AD and the current situation of therapeutic drugs, introduces three biosensor analysis techniques commonly used in the discovery of AD drugs, such as surface plasmon resonance (SPR), biolayer interferometry (BLI) and fluorescence analysis technology, explains its basic principle and application progress, and summarizes their advantages and limitations respectively.

Due to the advancement of 16S rRNA sequencing technology, the lower respiratory tract microbiota, which was considered non-existent, has been revealed. The correlation between these microorganisms and diseases such as tumor has been a hot topic in recent years. As the bacteria in the surrounding can infiltrate the tumors, researchers have also begun to pay attention to the biological behavior of tumor bacteria and their interaction with tumors. In this review, we present the characteristic of the lower respiratory tract bacteria and summarize recent research findings on the relationship between these microbiota and lung cancer. On top of that, we also summarize the basic feature of bacteria in tumors and focus on the characteristic of the bacteria in lung cancer. The relationship between bacteria in lung cancer and tumor development is also been discussed. Finally, we review the potential clinical applications of bacterial communities in the lower respiratory tract and lung cancer, and summarize key points of sample collection, sequencing, and contamination control, hoping to provide new ideas for the screening and treatment of tumors.
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Humans ; Lung Neoplasms ; RNA, Ribosomal, 16S/genetics* ; Bacteria/genetics* ; Microbiota ; Respiratory System ; Lung/microbiology*

Based on UPLC-Q-orbitrap-MS and biological network analysis tools, the mechanism of Xihuang Pill in improving hyperplasia of mammary glands was systematically analyzed. The rat model of hyperplasia of mammary glands was established by intramuscular injection of estradiol benzoate and progesterone. LC-MS tissue metabolomics was used to explore the key metabolites and metabolic pathways of Xihuang Pill in improving hyperplasia of mammary glands in rat. The network analysis of the key metabolites regulated by Xihuang Pill was carried out by integrating biological network analysis tools, focusing on the key metabolic pathways, and exploring the potential targets of Xihuang Pill to improve hyperplasia of mammary glands. Compared with the control group, there were significant differences in the content of 49 differential metabolites in the tissues of the model group (P < 0.05). Xihuang Pills could significantly call back 17 metabolites such as L-alanine, threonine, indole-3-carboxylic aldehyde, lysine, arginine, alanylleucine, glycyltyrosine, γ-glutamyl leucine, vitamin B3, serine leucine, threonine leucine, isoleucine glutamic acid, γ-glutamyl tyrosine, decanoyl-L-carnitine, uric acid, leucylleucine, S-adenosyl-methionine. Further network analysis and literature research on the key metabolites regulated by Xihuang Pills showed that the AGE-RAGE signaling pathway may be one of the important pathways for Xihuang Pills to improve hyperplasia of mammary glands. STAT3, MAPK1, EGFR, CASP3, CASP8, PRKCA and JUN in the AGE-RAGE signaling pathway may be potential targets for Xihuang Pills to improve hyperplasia of mammary glands. The animal experiment operations involved in this paper follow the provisions of the Animal Ethics Committee of Gansu University of Traditional Chinese Medicine and pass the ethical review of animal experiments (approval number: 2022-705).