Objective To analyze the clinical significance of subjective visual vertical (SVV) tests at different head deflection angles in assessing utricle function in patients with benign paroxysmal positional vertigo (BPPV). Methods A total of 61 BPPV patients who were treated at the Hearing Impairment and Vertigo Diagnosis and Treatment Center of Otolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine from August 2022 to May 2023 were retrospectively included, and 29 healthy adults were selected as controls. SVV tests were performed on all research subjects at different head deflection angles: upright head (0°), left head 45° (L45°), right head 45° (R45°). The test results between the two groups were compared. Results SVV absolute value at R45° in BPPV group was lower than that in the control group (P＝0.003); there was no significant difference in SVV values at 0° and L45° between the two groups. There was no statistical difference in SVV values at different head deflection angles between the control group and the left BPPV group. SVV absolute value at R45° in right BPPV group was lower than that in the control group (P＜0.001); there was no statistical difference in SVV values at 0° and L45° between the two groups. Conclusions SVV test can provide subjective information about the utricle, and SVV tests at different head deflection angles can fine-tune evaluate the function of the utricle in BPPV patients.

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.

ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.

ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.

Rare blood group reagents are characterized by high value, low usage frequency, and strict expiration limitations. These reagents are often imported, and their procurement process faces challenges such as a limited number of suppliers, difficulty in accurately forecasting demand, and logistics affected by international conditions. Inventory management is further complicated by high risks of expiration and stringent storage requirements. This article reviews optimization methods for medical reagent procurement and inventory management. It proposes adopting different ordering models based on the specific characteristics of rare blood group reagents. An intelligent demand forecasting model is developed using historical ordering patterns, seasonal disease trends, and clinical treatment data. Additionally, inventory control strategies are established, including categorized inventory management and joint inventory management. The article also discusses supply chain coordination and traceability mechanisms. Drawing on domestic and international research progress, it explores future directions for development.

Objective To study the construction of risk prediction model for postoperative recurrence of ad-vanced epithelial ovarian cancer based on serum human epididymis protein 4(HE4),platelet count/lymphocyte count ratio(PLR),relaxin(RLX),karyopherin α2(KPNA2).Methods 124 patients with advanced epithelial o-varian cancer diagnosed and treated in Suzhou Municipal Hospital(East District)from January 2016 to January 2019 were selected as the study objects,patients with advanced epithelial ovarian cancer were divided into re-currence group and the non-recurrence group based on whether they had recurred or not.The level of HE4 was detected by electrochemical luminescence immunoassay,PLR was calculated according to the blood routine re-sults,and RLX and KPNA2 levels were detected by enzyme-related immunosorbent assay.Multivariate Logis-tic regression analysis was used to analyze the influencing factors of postoperative recurrence in patients with advanced epithelial ovarian cancer,and establish a risk prediction model for postoperative recurrence of ad-vanced epithelial ovarian cancer.Receiver operating characteristic(ROC)curve was used to evaluate the pre-dictive efficacy of the model for postoperative recurrence of advanced epithelial ovarian cancer,and Hosmer-Lemeshow test was used to analyze the fitting of recurrence risk prediction model for patients with advanced epithelial ovarian cancer.Results There was a statistically significant difference in International Federation of Gynecology and Obstetrics(FIGO)staging and serum levels of carbohydrate antigen 125,HE4,PLR,RLX and KPNA2 between the recurrence group and the non-recurrence group(P＜0.05).FIGO staging Ⅳ of cancer and elevated serum HE4,PLR,RLX and KPNA2 were risk factors for postoperative recurrence in patients with advanced epithelial ovarian cancer(P＜0.05).ROC curve analysis showed that,the area under the curve of the recurrence risk prediction model for postoperative recurrence risk of advanced epithelial ovarian cancer was 0.859,which was significantly higher than that single indicator detected by HE4,PLR,RLX and KP-NA2.Hosmer-Lemeshow test showed that the recurrence risk prediction model of advanced epithelial ovarian cancer had a good fitting(x2=7.869,P=0.437).Conclusion The risk prediction model for postoperative re-currence of advanced epithelial ovarian cancer based on serum HE4,PLR,RLX,KPNA2 and FIGO staging of cancer has high predictive value for evaluating postoperative recurrence of advanced epithelial ovarian cancer,and deserves clinical attention.

Objective To investigate the imaging features of intestinal schwannoma(IS)in order to improve the diagnostic ability of the disease.Methods The clinical and imaging data of 14 patients with surgically and pathologically confirmed IS were retrospectively analyzed,including the location,size,morphology,nature,growth pattern,CT density,MRI signal,PET/CT metabolism and other characteristics of the tumors.Results Of the 14 IS cases,the lesions of 3 cases were located in the duodenum,2 cases in the cecum,8 cases in the colon and 1 case in the rectum.The lesions were all round or oval,with an average maximum diameter of(2.4±1.1)cm.The lesions were solid in 13 cases,extraluminal growth in 10 cases,cystic degeneration in 1 case and myxoid degeneration in 1 case.Chronic inflammatory lymph nodes were seen around the diseased intestines in 9 cases,and the short diameter of lymph nodes was greater than 5 mm in 6 cases.All 14 cases of IS showed low attenuation on plain CT scan,and progressive enhancement after contrast injection,including 1 case of mild enhancement,2 cases of moderate enhancement,and 11 cases of obvious enhancement.Two cases of IS showed low signal intensity on T1WI,slightly high signal intensity on T2WI,significantly high signal intensity on DWI,and obvious progressive enhancement after contrast injection on MRI.Two cases of IS showed high metabolism on 18F-FDG-PET/CT,and the SUVmax was 9.4 and 8.8,respectively.Conclusion The imaging findings of IS were characteristic to a certain extent.They mainly manifested as solid nodules or masses derived from the intestinal submucosa,with uniform attenuation or signal intensity,obvious progressive enhancement after contrast injection,obvious hypermetabolism on 18F-FDG-PET/CT,and slightly larger homogeneous lymph nodes were common around the lesions.

Objective To investigate the value of computer-assisted quantification of pulmonary embolism volume(PEV)in identifying mild-to-high-risk acute pulmonary embolism(APE).Methods We retrospectively enrolled 143 patients with suspected APE confirmed by computed tomography pulmonary angiography(CTPA)at Yan'an University Affiliated Hospital from January 2017 to December 2020.According to the 2018 Chinese Guidelines for Diagnosis,Treatment and Prevention of Pulmonary Thromboembolism,all the patients were divided into low-risk group(n=88)and mild-to-high-risk group(n=55).We collected the patients'basic demographic data,clinical manifestations,and serum levels of N-terminal-B type natriuretic peptide precursor(NT-proBNP)and D-dimer.Based on CTPA images,the degree of pulmonary thromboembolism was artificially evaluated to obtain the pulmonary artery occlusion index(PAOI).The thrombus was segmented using the pulmonary embolism detection tool based on digital lung,and PEV was calculated.We compared the differences in clinical and laboratory indicators and PAOI and PEV between the two risk groups.We analyzed the value of PAOI and PEV in identifying mild-to-high-risk APE using receiver operating characteristic(ROC)curves,and used Logistic regression analysis to identify independent risk factors in predicting mild-to-high-risk APE.Different models were established.Results Compared with the low-risk group,APE patients in the mild-to-high-risk group were older(P＜0.05),had lower diastolic blood pressure(P＜0.05),higher levels of D-dimer and NT-proBNP(P＜0.05),lower levels of platelet count,arterial oxygen partial pressure and arterial carbon dioxide partial pressure(P＜0.05),and higher levels of PAOI and PEV(P＜0.001).ROC curve analysis showed that the area under the curve for PEV in identifying mild-to-high-risk APE was 0.809(95％CI:0.734-0.884),while that for PAOI was 0.753(95％CI:0.667-0.839).Logistic regression analysis showed that PEV and NT-proBNP were independent risk factors for mild-to-high-risk APE(P＜0.05).Conclusion PEV and NT-proBNP are independent risk factors for mild-to-high-risk APE.