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.

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Objective To analyze the basic conditions and pathological characteristics of the samples in the Human Brain Bank of Hebei Medical University,which were pathologically diagnosed as cerebral amyloid angiopathy,and to provide reference for the research of related diseases.Methods The basic data of gender,age,apolipoprotein E genotype,pathological classification of cerebral amyloid angiopathy,Alzheimer's disease-related pathological change score,comorbidities and other pathological information were analyzed.Results Up to October 2024,twenty samples were confirmed by pathological diagnosis,with a male to female ratio of 3:1 and an average age of(80.90±8.08)years.Involve three kinds of apolipoprotein E subtype,5 kinds of genotypes(ε2/ε3 xε2/ε4、ε3/ε3 xε3/ε4、ε4/ε4);There were 2 pathologic types,including 6 cases of type 1 and 14 cases of type 2.The pathological grade included 3 grades.The severity grade and subtype classification of cerebral amyloid vascular disease were correlated with the degree of pathological changes of Alzheimer's disease.Cerebral amyloid angiopathy samples could coexist with other degenerative diseases with high comorbidity.Conclusion The incidence of cerebral amyloid angiopathy is higher in the aged samples collected based on Brain Bank,which coexists with conditions such as Alzheimer's disease and microbleeds,etc.It provides more detailed pathological diagnosis basis for further scientific research sharing of samples.

Objective To investigate the population composition,seasonal dynamics,and infestation levels of cockroaches in Lanzhou,China,and to provide information for the scientific development of cockroach control strategies.Methods Monitoring was conducted at three locations using the sticky trap method.Habitats included farm product markets,catering establishments,hotels,hospitals,and residential areas.Results From 2016 to 2023,the average cockroach density was 0.77 insects per board,with an average infestation rate of 10.84%.Blattella germanica was the dominant species.Seasonal density of cockroaches showed an approximately unimodal distribution,peaking in September.The highest average density and infestation rates were observed in farm product markets.Conclusions Cockroach density and infestation levels in Lanzhou remained relatively low.A comprehensive prevention and control strategy focusing on environmental management in key areas should be implemented according to the seasonal fluctuations.

BACKGROUND: The effects of acupuncture have varied in different randomized controlled trials (RCTs), and there are many factors that influence treatment effect of acupuncture in different outcomes, with conflicting results. OBJECTIVE: To identify factors and their impact on the treatment effect of acupuncture in different outcomes. METHODS: Acupuncture RCTs were searched from 7 databases including Medline (PubMed), Embase, Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, Wanfang Database, VIP Database, and China Biology Medicine disc between January 1st, 2015 and December 31st, 2019. Eligible studies must compare acupuncture to no acupuncture, sham acupuncture, or waiting lists, and report at least 1 patient-important outcome. A multi-level meta-regression was conducted using a 3-level robust mixed model and univariate analyses were performed for all independent variables, even those excluded from the multivariable model due to collinearities. We used thresholds of 0.2 and 0.4 for the difference of standardized mean differences (SMDs), categorising them as small (<0.2), moderate (0.2-0.4), or large (>0.4) effects. RESULTS: The pain construct analysis involved 211 effect estimates from 153 studies and 14 independent variables. High-frequency acupuncture treatment sessions produced larger effects compared to low-frequency sessions [large magnitude, the difference of adjusted SMDs 0.46, 95% confidence interval (CI) 0.07 to 0.84; P=0.02]. The non-pain symptoms construct analysis comprised 323 effect estimates from 231 studies and 15 independent variables. Penetrating acupuncture showed moderately larger effects when compared to non-penetrating acupuncture (0.30, 95% CI 0.06 to 0.53; P=0.01). The function construct analysis included 495 effect estimates from 274 studies and 14 independent variables. Penetrating acupuncture and the flexible acupuncture regimen showed moderately larger effects, compared to non-penetrating acupuncture and fixed regimen, respectively (0.40, 95% CI 0 to 0.80; P=0.05; 0.29, 95% CI 0.06 to 0.53; P=0.01). CONCLUSIONS High-frequency acupuncture sessions appear to be a more effective approach to managing painful symptoms. Penetrating acupuncture demonstrated greater effect in relieving non-painful symptoms. Both penetrating acupuncture type and flexible acupuncture regimen were linked to significant treatment effects in function outcomes. Future studies should consider the factors that are significantly associated with the effects of acupuncture in patient-important outcomes.
Humans ; Randomized Controlled Trials as Topic ; Acupuncture Therapy/methods* ; Pain ; Pain Management ; China

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.