ObjectiveThis study aims to explore the mechanism by which Yishen Huoxue Tongqiao Formula improves metabolism-neuroplasticity and treats unilateral vestibular labyrinth destruction by regulating the metabolic balance of glutamate （Glu）/γ-aminobutyric acid （GABA）. Methods48 Sprague-Dawley （SD） adult rats were randomly divided into the sham operation group， model group， Yishen Huoxue Tongqiao Formula groups with low， medium， and high doses （9.20， 18.39， 36.78 g·kg^-1）， and betahistine group （1.62 mg·kg^-1）. A unilateral vestibular labyrinth destruction （vestibular dysfunction） model was established by intratympanic injection of chloroform into the right ear， while the control group received intratympanic injection of normal saline. Drugs were administered once daily for seven consecutive days. During the period， behavioral tests were performed to evaluate the behaviors of rats after unilateral vestibular labyrinth destruction. Hematoxylin-eosin （HE） staining and Nissl staining were used to observe the neuronal morphology in the medial vestibular nucleus. Golgi staining was employed to assess the number of dendritic spines of neurons in the medial vestibular nucleus. Ultra-performance liquid chromatography-tandem mass spectrometry （LC-ESI-MS/MS） was utilized to detect Glu/GABA. Immunofluorescence and immunohistochemistry were used to detect the expressions of neuronal nuclei （NeuN）， growth-associated protein 43 （GAP-43）， and glial fibrillary acidic protein （GFAP）. Western blot and real-time fluorescent quantitative polymerase chain reaction （Real-time PCR） were applied to determine the expressions of glutamate-immunoreactive （Glu-IR）， GABA， GFAP， postsynaptic density protein 95 （PSD-95）， and GAP-43. ResultsCompared with the sham operation group， the model group presented with head deviation， balance disorder， increased tail suspension score， nuclear consolidation of medial vestibular nerve neurons， and decreased Nissl bodies （P<0.01）. The number of dendritic spines in neurons and NeuN-positive cells decreased. The content of Glu decreased. The content of GABA increased （Glu/GABA decreased）. The expression of GAP-43 was down-regulated， and GFAP was up-regulated （P<0.05， P<0.01）. The expressions of Glu-IR， PSD-95， and GAP-43 proteins， as well as Glu-IR mRNA decreased， while the expressions of GABA and GFAP proteins and mRNA increased （P<0.05， P<0.01）. Compared with those in the model group， the head deviation， imbalanced behavior， and tail suspension scores in each treatment group decreased， with alleviated neuronal injury and recovered Nissl bodies （P<0.01）. The number of dendritic spines of neurons increased， and the number of NeuN-positive cells rebounded. The content of Glu increased， and the content of GABA decreased （Glu/GABA increased）. GFAP was down-regulated， and GAP-43 was up-regulated （P<0.05， P<0.01）. The expressions of Glu-IR， PMD-95， and GAP-43 proteins， as well as Glu-IR mRNA increased， while the expressions of GABA and GFAP proteins and mRNA decreased. The effect was more significant in the high-dose group （P<0.01）. ConclusionThe Yishen Huoxue Tongqiao Formula can alleviate vestibular dysfunction， and its mechanism may be associated with regulating the metabolic balance of Glu/GABA， mitigating neural damage， improving synaptic plasticity （promoting GAP-43 expression and inhibiting GFAP expression）， and facilitating vestibular compensation.

Poloxamer， as a non-ionic surfactant， exhibits a unique triblock [polyethylene oxide-poly （propylene oxide）-polyethylene oxide] structure， which endows it with broad application potential in various fields， including solid dispersion technology， nanotechnology， gel technology， biologics， gene engineering and 3D printing. As a carrier， it enhances the solubility and bioavailability of poorly soluble drugs. In the field of nanotechnology， it serves as a stabilizer etc.， enriching preparation methods. In gel technology， its self-assembly behavior and thermosensitive properties facilitate controlled drug release. In biologics， it improves targeting efficiency and reduces side effects. In gene engineering， it enhances delivery efficiency and expression levels. In 3D printing， it provides novel strategies for precise drug release control and the production of high-quality biological products. As a versatile material， poloxamer holds promising prospects in the pharmaceutical field.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective To investigate the association between lifestyle and risk of heart disease and diabetes in the elderly population in Xi'an City. Methods From January 2021 to January 2024, a staged cluster sampling method was used to investigate the lifestyle and the occurrence of heart disease and diabetes in elderly population aged 60 years and above in the communities of Xi'an. Multivariate logistic regression was used to analyze the relationship between lifestyle and the risk of heart disease and diabetes. Results A total of 413 elderly people were investigated, of which 31.96% had heart disease, 27.12% had diabetes, and 10.90% had diabetes with heart disease. Multivariate logistic regression analysis revealed that age, BMI, family history, sweet food preference, smoking, and sitting and lying for a long time were risk factors for diabetes in the elderly population (P<0.05). Age, BMI, family history, history of diabetes, preference for salted products, smoking, drinking, and sitting and lying for a long time were risk factors for heart disease in the elderly population (P<0.05). Conclusion The incidence rates of heart disease and diabetes are high in the elderly population in Xi'an City. The risk of diabetes is related to unhealthy lifestyles such as sweet food preference, smoking, and sitting and lying for a long time, while heart disease is related to unhealthy lifestyles such as preference for salted products, smoking, drinking, and sitting and lying for a long time.

Objective To explore the mechanism of TPT1-AS1 targeting miR-324/TWIST1 axis to regulate the proliferation, invasion, migration and angiogenesis of epithelial ovarian cancer (EOC) cells, thereby affecting ovarian cancer (OC) progression. Methods RT-qPCR was used to detect the expression of TPT1-AS1 and miR-324 in 29 OC lesions and adjacent tissue samples. The two OC cell models of TPT1-AS1 overexpression and miRNA324 knockdown were constructed, and the cell proliferation, invasion and migration abilities were detected by CCK-8, Transwell^TM and scratch test. Western blot analysis was used to detect the protein expression levels of TWIST1, epithelial cadherin (E-cadherin), Vimentin, and vascular endothelial growth factor A (VEGF-A) in OC cells. Fluorescence in situ hybridization (FISH) and RNA pull-down experiments were used to verify the interaction between TPT1-AS1 and miR-324. Immunohistochemistry and Targetscan bioinformatics analysis were used to verify the negative regulatory role of miR-324 in the epithelial-mesenchymal transition (EMT) process. Results The TPT1-AS1 expression was significantly higher in OC tissues than that in para-cancerous tissues, while the miR-324 expression was significantly lower. In SKOV3 cells with TPT1-AS1 overexpression, the miR-324 expression decreased significantly, and TPT1-AS1 was negatively correlated with miR-324. It was also found that TPT1-AS1 and miR-324 were co-expressed in OC cells, and there was a direct binding relationship between them. Down-regulation of miR-324 significantly promoted the proliferation, invasion and migration of SKOV3 cells. Further studies revealed that miR-324 had a binding site at the 3'-UTR end of the TWIST1, a key transcription factor for EMT. Inhibiting miR-324 expression increased the transcription level of TWIST1, leading to a decrease in E-cadherin protein expression and an increase in Vimentin protein expression. Additionally, the downregulation of miR-324 resulted in an increased expression level of VEGF-A protein, which in turn enhanced angiogenesis of OC. Conclusion TPT1-AS1 promotes EOC cell proliferation, invasion, migration and angiogenesis by negatively regulating the miR-324/TWIST1 axis, thus promoting the development of OC. These findings provide new potential targets for the diagnosis and treatment of OC.
Humans ; MicroRNAs/metabolism* ; Female ; Cell Movement/genetics* ; Ovarian Neoplasms/blood supply* ; Twist-Related Protein 1/metabolism* ; Cell Line, Tumor ; Neovascularization, Pathologic/genetics* ; Neoplasm Invasiveness ; Carcinoma, Ovarian Epithelial/metabolism* ; Nuclear Proteins/metabolism* ; Cell Proliferation/genetics* ; Epithelial-Mesenchymal Transition/genetics* ; Gene Expression Regulation, Neoplastic ; RNA, Long Noncoding/metabolism* ; Cadherins/genetics* ; Vascular Endothelial Growth Factor A/genetics* ; Vimentin/genetics* ; Angiogenesis

Objective:This article reports a case of right sinonasal teratocarcinosarcoma. The patient was admitted to the hospital with symptoms of persistent nasal obstruction in both nostrils. Nasal endoscopy revealed the presence of new growths in the right nasal cavity and nasopharynx. Sinus CT imaging showed that the nasal cavity, paranasal sinuses, and nasopharynx were filled with soft tissue density shadows, with evidence of bone destruction. Transnasal endoscopic sinonasal surgery was performed, and postoperative pathology, along with immunohistochemical results, confirmed a diagnosis of sinonasal teratocarcinosarcoma. This case is analyzed, and relevant literature is reviewed.
Humans ; Carcinosarcoma ; Paranasal Sinus Neoplasms ; Nose Neoplasms ; Male ; Teratoma ; Middle Aged

OBJECTIVES: To investigate the effect of orexin-A-mediated regulation of ionotropic glutamate receptors for promoting motor function recovery in rats with spinal cord injury (SCI). METHODS: Thirty-six newborn SD rats (aged 7-14 days) were randomized into 6 groups (n=6), including a normal control group, a sham-operated group, and 4 SCI groups with daily intrathecal injection of saline, DNQX, orexin-A, or orexin-A+DNQX for 3 consecutive days after PCI. Motor function of the rats were evaluated using blood-brain barrier (BBB) score and inclined plane test 1 day before and at 1, 3, and 7 days after SCI. For patch-clamp experiment, spinal cord slices from newborn rats in the control, sham-operated, SCI, and SCI+orexin groups were prepared, and ventral horn neurons were acutely isolated to determine the reversal potential and dynamic indicators of glutamate receptor-mediated currents under glutamate perfusion. RESULTS: At 3 and 7 days after SCI, the orexin-A-treated rats showed significantly higher BBB scores and grip tilt angles than those with other interventions. Compared with those treated with DNQX alone, the rats receiving the combined treatment with orexin and DNQX had significantly higher BBB scores and grip tilt angles on day 7 after PCI. In the patch-clamp experiment, the ventral horn neurons from SCI rat models exhibited obviously higher reversal potential and greater rise slope of glutamate current with shorter decay time than those from sham-operated and orexin-treated rats. CONCLUSIONS Orexin-A promotes motor function recovery in rats after SCI possibly by improving the function of the ionotropic glutamate receptors.
Animals ; Spinal Cord Injuries/drug therapy* ; Rats ; Rats, Sprague-Dawley ; Receptors, Ionotropic Glutamate/metabolism* ; Recovery of Function/drug effects* ; Orexins/pharmacology* ; Male ; Female ; Animals, Newborn ; Neuropeptides/pharmacology* ; Intracellular Signaling Peptides and Proteins/pharmacology*