Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Objective To evaluate the value of miniprobe endoscopic ultrasound(EUS)in guiding endoscopic treatment of small-diameter(maximum diameter less than 1 cm)and low-grade(G1 grade)rectum neuroendocrine neoplasm(R-NEN),and to provide evidence and clues for its clinical application and further research.Methods The clinical data of 85 cases of low-grade(G1 grade)R-NEN with a maximum diameter of less than 1 cm who underwent endoscopic treatment in our center from January 2014 to December 2020 were retrospectively analyzed.The patients were divided into the EUS group(37 cases)and control group(48 cases)according to whether EUS was performed before endoscopic treatment.The positive rate of incision margin,the incidence of complications,the recurrence rate,the hospital stay,the cost of hospitalization and endoscopic therapy were compared between the two groups.Results The positive rate of incision margin in the EUS group was significantly lower than that in control group(P<0.05).There was no significant difference in the incidence of complications,tumor recurrence rate,hospital stay or hospital costs between the two groups(P>0.05).There was statistically significant difference in the endoscopic therapy between the two groups(P<0.05).Conclusion Evaluating the lesion depth of small-diameter and low-grade(G1 grade)R-NEN before surgery by miniprobe EUS and selecting endoscopic surgery according to its results of can significantly reduce the residual risk of resection margin tumors.

Transcatheter aortic valve replacement(TAVR)has become one of the effective methods for treating patients with aortic valve disease.With the continuous maturity of technology,innovation of instruments and increasing experience,the indications for TAVR has been expanded.Following international trends,the number of TAVR in China has steadily increased with each passing year.In 2023,the long-term follow-up results of TAVR in low-risk AS patients further confirm the long-term benefits of TAVR.The relevant research on TAVR for patients with aortic regurgitation and patients with bicuspid aortic stenosis provide evidence support for the expansion of TAVR indications.At the same time,the development of valve devices and new technological innovations are emerging in an endless stream,and the new concept of full life cycle management is increasingly being valued.Especially in China,the development of local devices is progressing rapidly,and multiple devices have entered the clinical research stage.The clinical manifestations and research results are worth pursuing.

Jinqi Jiangtang Capsule (JQJTC) is clinically used for the prevention and treatment of type 2 diabetes, but the contents of its main chemical components are not yet clear. In this study, an ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was established for the determination of 15 components in JQJTC, including new chlorogenic acid, chlorogenic acid, cryptochlorogenic acid, formononetin, ononin, calycosin, calycosin-7-glucoside, astragaloside IV, berberine, epiberberine, berberrubine, coptisine, jatrorrhizine, palmatine and magnoflorine. The method was used to determine the contents of 15 components in the capsule and then to investigate the influence of excipients on the contents of the components in JQJTC. The separation was performed on a ACQUITY UPLC BEH C₁₈ column (100 mm × 2.1 mm, 1.7 μm) with a mobile phase consisting of 0.1% acetic acid and 5 mmol·L^-1 ammonium acetate (A) and acetonitrile (B) with gradient elution at a flow rate of 0.3 mL·min^-1 and a column temperature at 40 ℃. Electron spray ionization was used for mass spectrometry in positive ion mode. The established method meets the requirements of methodology of content determination in Chinese pharmacopoeia. The contents of 15 components in JQJTC varied from high to low. The top 5 contents were berberine, chlorogenic acid, magnoflorine, coptisine, and cryptochlorogenic acid, accounting for 87.31% of the total content. The contents of 10 components, including the alkaloids of coptidis rhizoma (berberine, epiberberine, berberrubine, coptisine, jatrorrhizine, palmatine and magnoflorine) and the organic acids of honeysuckle (new chlorogenic acid, chlorogenic acid, and cryptochlorogenic acid) in the whole formula extract without excipients was significantly lower than that in the capsule. These components accounted for 99.20% of the determined component contents. In this experiment, an accurate, sensitive and efficient UHPLC-MS/MS method for the determination of multi-components in JQJTC was established, which stably and reliably detected the contents of 15 components in the capsule and could provide the basis for more comprehensive quality analysis. It was also found that excipients had an increasing effect on the contents of detected alkaloid and organic acid components, which may be beneficial to the effectiveness of the capsules.

Deep vein thrombosis(DVT)is a common peripheral vascular disease in clinical practice.The lack of precise and efficient early diagnostic techniques renders it susceptible to being overlooked or misdiagnosed,and therefore,identifying trustworthy biomarkers is a major issue that has to be resolved.In this study,the endogenous metabolites in the urine of DVT rats were screened by metabolomics technology based on gas chromatograph-mass spectrometry(GC-MS)and the characteristic metabolites were identified by multiple feature selection algorithms and multivariate statistical analysis,for the development of a machine learning-based diagnostic model for DVT.The urine samples in metabolic cage in the thrombus development phase(between 48 and 72 h)of rats were collected,which was used as the models for inferior vena cava ligation.The metabolic profiles of the control group and DVT were obtained using the GC-MS method.A total of 176 kinds of endogenous metabolites were identified in rat urine through comparison with the FiehnLib database,26 kinds of differential metabolites associated with DVT were screened through a combination of the Mann-Whitney U test and orthogonal partial least squares discriminant analysis(OPLS-DA),and 13 kinds of significant metabolites strongly correlated with DVT were further evaluated in conjunction with various machine learning feature selection techniques.For DVT diagnosis,machine learning models such as Gaussian Naive Bayes(GNB),support vector machine(SVM),logistic regression(LR),and linear discriminant analysis(LDA)were developed.The diagnostic model constructed using 13 kinds of key metabolites demonstrated excellent accuracy and stability,and surpassed the predictive performance of the models utilizing 176 kinds of metabolites and 26 kinds of differential metabolites,as evidenced by examination and comparison of each model's efficacy.The study showed that the integration of multiple feature selection algorithms for analyzing metabolite information in DVT rat urine was capable of effectively identifying reliable potential markers of DVT.Furthermore,the developed machine learning model offered a novel technical approach for the automated diagnosis of DVT.

AIM To study the secondary metabolites from the endophytic fungi Candida sp.of Berberis atrocarpa Schneid.METHODS The ethyl acetate fraction and petroleum ether fraction from the secondary metabolites of Candida sp.fermentation extract were separated and purified by silica gel,Sephadex LH-20 and preparative liquid chromatography,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Eighteen compounds were isolated and identified as 1-phenyl-1,2-ethanediol(1),4-hydroxyphenethyl alcohol(2),4-hydroxybenzoic acid(3),4-hydroxyphenylacetic acid(4),3-hydroxyphenylacetic acid(5),3-methylsulfinyl propionic acid(6),phenylacetic acid(7),(S)-N-nitroso-1-amino-p-hydroxy phenylethanol(8),2-phenylacetamide(9),p-hydroxybenzaldehyde(10),ethyl 2-(4-hydroxyphenyl)acetate(11),dibutyl phthalate(12),5,5'-dimethoxybiphenyl-2,2'-diol(13),3-indolealdehyde(14),N-acetyl-L-phenylalanine(15),9-hydroxy-10E,12Z-octadecadienoic acid(16),9-hydroxy-10E,12E-octadecadienoic acid(17),(6E)-5-methylene-6-tetradecenoic acid(18).CONCLUSION Compounds 1,3-8 and 10-18 are isolated from Candida sp for the first time.