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 feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

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 feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

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 investigate the association of various polycyclic aromatic hydrocarbon (PAH) metabolites with diverse subtypes of cardiovascular disease (CVD) risk. METHODS: A novel predicting risk of cardiovascular disease EVENTs PREVENT equation was used to estimate the 10-year diverse subtypes of CVD risk, and their associations with PAH metabolites were analyzed using multiple logistic regression models, the weighted quantile sum (WQS) model, the quantile g-computation (qgcomp) model, and a stratified analysis of subgroups. RESULTS: For this study, six thousand seven hundred and forty-five participants were selected, and significant positive associations were observed between PAHs, naphthalene (NAP), and fluorene (FLU), and the risks of total CVD, atherosclerotic cardiovascular disease (ASCVD), and heart failure (HF). NAP and FLU were the primary contributors to the effects of PAH mixtures, and their associations with total CVD, ASCVD, and HF risk were significant in younger participants (30 ≤ age < 50 years); however, the associations of phenanthrene (PHEN) with ASCVD, HF, coronary heart disease (CHD), and stroke were dominant in aging participants (age ≥ 50 years). Notably, pyrene (PYR) was negatively associated with the risk of ASCVD, HF, CHD, and stroke. Similarly, negative associations of PYR with the four CVD subtypes were noticeable in aging participants. CONCLUSION Different PAHs metabolites had different impacts on each CVD subtype among different age groups. Notably, the protective effects of PYR on ASCVD, HF, CHD, and stroke were noticeable in aging individuals.
Humans ; Cardiovascular Diseases/chemically induced* ; Middle Aged ; Polycyclic Aromatic Hydrocarbons/metabolism* ; Male ; Female ; Adult ; Aged ; Risk Factors ; China/epidemiology*

Oral squamous cell carcinoma(OSCC)is a malignant lesion originating from the oral mucosal squamous epithelium,account-ing for over 80％of oral and maxillofacial malignancies.Key etiological factors include tobacco,alcohol abuse,and betel quid chewing.In China,its incidence has shown an overall upward trend,posing a significant threat to public health.OSCC exhibits high local invasive-ness,making early diagnosis critical for improving prognosis.Its clinical management requires close multidisciplinary collaboration among oral and maxillofacial surgery,head and neck surgery,radiation oncology,medical oncology,reconstructive surgery,radiology,patholo-gy,and nutritional support teams.Given the increasing disease burden of OSCC and rapid development of multidisciplinary collaborative models,an expert panel has formulated this integrated management consensus based on evidence-based medicine and extensive deliber-ation.Centered on the'Prevention-Screening-Diagnosis-Treatment-Rehabilitation'framework,the consensus provides comprehensive guidance for the entire disease course of OSCC patients,aiming to standardize clinical practice.

Objective:To evaluate whether the reconstructed image on the basis of deep learning(DL)can improve the success rate and display quality of automatic segmentation of computed tomography(CT)with ultralow dose for chest of children on airway.Methods:The clinical data of 41 consecutive cases who adopted ultralow dose CT to underwent reexamination on chest at Beijing Children's Hospital,Capital Medical University from February 2020 to September 2020 were selected,whose average age was(4.43±1.61 years).The scan protocol of ultralow dose CT was(0.05 mGy).The reconstructed images included 6 groups,which were respectively filtered reflection projection(FBP)image with 0.625 mm thickness,50%adaptive iterative recombination(ASIR-V)images,100%ASIR-V images,low energy DL(DL-L),medium energy DL(DL-M),and high energy DL(DL-H).The automatically segmentation software was used to conduct automatically segmentation for airway,and the success rate of automatic segmentation was recorded.For images that were successful segmented,a 5-point scale was adopted to subjectively evaluate the displayed quality for airway(5 point is the best).In addition,the CT values and noise values of the images of 6 groups for airway were objectively measured.Results:The success rate of automatic segmentation of DL-H image was the highest(60.98%),and that of the 100%ASIR-V was the lowest(39.02%).The subjective score of DL-H image of the automatic segmentation was the highest(4.06±0.55)point,and that of 100%ASIR-V was the lowest(2.44±0.76)point.DL-H can display more fine and small airways.The noise values of objective measurement showed that both of DL-H and 100%ASIR-V had the lowest noise value,and there was no statistical difference in that between them.Conclusion:The use of high energy deep learning iterative reconstruction(DLIR)algorithm can improve the success rate and display effect of automatic segmentation of ultralow dose CT for chest of children on airway,and DLIR is contribute to improve the accuracy of automatic segmentation algorithm of artificial intelligence.

The medical mask,which is used as an important tool of preventing the spread of respiratory diseases,can effectively block the transmission of biological aerosols.The detection for the filtration efficiency of bacteria in medical mask is particular importance.The Andersen sampler,is one kind of device that samples microbial aerosols,is widely used in the inspection for the filtration efficiency for bacteria in medical masks.It mainly consists of six impactors with different pore sizes.It simulates the deposition process of the most of particles at different positions in respiratory system through the bacterial particles in biological aerosols impact respectively the surface of petri dishes with agar under different pore sizes.This paper explored the development background,structure and sampling principle,operation and counting procedures of the Andersen sampler,as well as its application and importance in the inspection for the filtration efficiency for bacteria in medical mask.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.