Objective To evaluate the predictive value of different machine learning models constructed in a multicenter environment for potential organ donors and verify their clinical application feasibility. Methods The study included 2 000 inpatients admitted to five domestic tertiary hospitals from January 2020 to December 2023, who met the criteria for potential organ donation assessment. They were randomly divided into a training set and an internal validation set (7∶3). Another 300 similar patients admitted to the First Affiliated Hospital of Harbin Medical University from January 2024 to April 2025 were included as an external validation set. The area under the curve (AUC), sensitivity, specificity, accuracy and F1-score of three models were compared, and the consistency of the potential organ donor determination process was tested. Multivariate logistic regression analysis was used to identify predictive factors of potential organ donors. Decision curve analysis (DCA) was employed to verify the resource efficiency of each model, and the threshold interval and intervention balance point were assessed. Results Apart from age, there were no significant differences in other basic characteristics among the centers (all P>0.05). The consistency of the potential organ donor determination process among researchers in each center was good [all 95% confidence interval (CI) lower limits >0]. In the internal validation set, the XGBoost model had the best predictive performance (AUC=0.92, 95% CI 0.89-0.94) and the best calibration (P=0.441, Brier score 0.099). In the external validation set, the XGBoost model also had the best predictive performance (AUC=0.91, 95% CI 0.88-0.94), outperforming logistic regression and random forest models. Multivariate logistic regression showed that mechanical ventilation had the greatest impact (odds ratio=2.06, 95% CI 1.54-2.76, P<0.001). DCA indicated that the XGBoost model had the highest net benefit in the threshold interval of 0.2-0.6. The “treat all” strategy only had a slight advantage at extremely low thresholds. The recommended threshold interval, which balances intervention costs and clinical benefits, considers ≥50% positive predictive value (PPV) and ≤50 referrals per 100 high-risk patients. Conclusions The XGBoost model established in a multicenter environment is accurate and well-calibrated in predicting potential organ donors. Combined with DCA, it may effectively guide the timing of clinical interventions and resource allocation, providing new ideas for the assessment and management of organ donation after brain death.

ObjectiveTaking the cuproptosis/oxidative stress pathway as the entry point， this study investigated the effect and mechanism of Liangyi Paste on hepatic lipid deposition in naturally aged mice fed with a high-fat diet. MethodsAfter adaptive feeding， 80 ten-week-old male C57BL/6 mice were used. Thirty of them were randomly divided into three groups （10 mice per group）： The 12-month-old control group （12MCON）， the 15-month-old control group （15MCON）， and the 15-month-old group with a high-fat diet （15MHFD）. The 12MCON and 15MCON groups were continuously fed a standard diet， while the 15MHFD group started receiving a high-fat diet at 12 months of age. Tissue samples were collected at the corresponding time points for each group. The remaining 50 mice were randomly divided into five groups （10 mice per group）： the 20-month-old control group （20MCON）， the model group， and the low-， medium-， and high-dose Liangyi Paste groups （2.91 ， 5.82 ， 11.64 g·kg^-1·d^-1， respectively）. The 20MCON group was continuously fed a standard diet， while the other groups started receiving a high-fat diet at 15 months of age. At 18 months of age， the Liangyi Paste groups were administered the corresponding doses of Liangyi Paste by gavage， while the 20MCON and model groups were given an equal volume of saline by gavage. After 8 weeks of continuous gavage （when the mice reached 20 months of age）， tissue samples were collected. Hepatic TG levels were measured using assay kits； liver histology and lipid deposition were observed via hematoxylin-eosin （HE） and oil red O staining； reactive oxygen species （ROS） were detected by enzyme-linked immunosorbent assay （ELISA）； Cu²⁺， superoxide dismutase （SOD）， and malondialdehyde （MDA） levels were measured by colorimetry； mRNA and protein expression of genes related to cuproptosis and oxidative stress pathways were analyzed by Real-time polymerase chain reaction（Real-time PCR） and Wes automated protein expression system. ResultsCompared with 12MCON， the 15MCON group showed significantly increased hepatic TG， Cu²⁺， ROS， and MDA levels （P<0.01）， decreased SOD （P<0.01）， hepatocyte swelling， and disordered arrangement. The mRNA and protein levels of ferredoxin 1 （FDX1）， dihydrolipoamide S-acetyltransferase （DLAT）， heat shock protein 70 （HSP70）， dihydrolipoamide dehydrogenase （DLD）， pyruvate dehydrogenase E1 subunit-β （PDHB）， nuclear factor erythroid 2-related factor 2 （Nrf2）， and peroxisome proliferator-activated receptor γ （PPARγ） were significantly elevated （P<0.05， P<0.01）. Compared with 15MCON group， the 15MHFD and 20MCON groups exhibited further increases in TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， and aggravated hepatocyte swelling and disorder. There were increased lipid droplets with mild vacuolization in the 15MHFD group， and no significant lipid deposition was observed in the 20MCON group. FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and protein levels were significantly increased （P<0.05， P<0.01）. Compared with 20MCON group， the model group demonstrated markedly elevated TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， severe hepatic steatosis， and upregulated expression of FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and proteins （P<0.05， P<0.01）. All abnormalities were significantly reversed after Liangyi Paste treatment. ConclusionLiangyi paste can ameliorate hepatic lipid deposition in naturally aged mice with a high-fat diet by modulating the cuproptosis/oxidative stress pathway.

Objective: To analyze the change trends in the body shape indicators and proportions of students in Harbin from 2010 to 2024, and to investigate ergonomic compatibility of functional dimensions of school desks and chairs with current student shape indicators, so as to provide a reference for revising furniture standards of desks and chairs. Methods: Between September and November of both 2010 and 2024, a combination of convenience sampling and stratified cluster random sampling was conducted across three districts in Harbin, yielding samples of 6 590 and 6 252 students, respectively. Anthropometric shape indicators cluding height, sitting height, crus length, and thigh length-and their proportional changes were compared over the 15-year period. The 2024 data were compared with current standard functional dimensions of school furniture. The statistical analysis incorporated t-test and Mann-Whitney U- test. Results: From 2010 to 2024, average height increased by 1.8 cm for boys and 1.5 cm for girls; sitting height increased by 1.5 cm for both genders; crus length increased by 0.3 cm for boys and 0.4 cm for girls; and thigh length increased by 0.5 cm for both genders. The ratios of sitting height to height, and sitting height to leg length increased by less than 0.1 . The difference between desk chair height and 1/3 sitting height ranged from 0.4-0.8 cm. Among students matched with size 0 desks and chairs, 22.0% had a desk to chair height difference less than 0, indicating that the desk to chair height difference might be insufficient for taller students. The differences between seat height and fibular height ranged from -1.4 to 1.1 cm; and the differences between seat depth and buttock popliteal length ranged from -9.8 to 3.4 cm. Among obese students, the differences between seat width and 1/2 hip circumference ranged from -20.5 to -8.7 cm, while it ranged from -12.2 to -3.8 cm among non obese students. Conclusion Current furniture standards basically satisfy hygienic requirements; however, in the case of exceptionally tall and obese students, ergonomic accommodations such as adaptive seating allocation or personalized adjustments are recommended to meet hygienic requirements.

Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

Purpose: This study aimed to evaluate the contrast-enhanced ultrasound with Sonazoid (Sonazoid-CEUS) features of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: In this retrospective study, patients who underwent surgical resection and were histopathologically diagnosed with NAFLD or cirrhosis-related HCC were included. All patients received Sonazoid-CEUS examinations within 1 week prior to hepatic surgery. The enhancement patterns of HCC lesions were evaluated and compared between the two groups according to the current World Federation for Ultrasound in Medicine and Biology guidelines. Multivariate logistic regression analysis was used to assess the correlations between Sonazoid-CEUS enhancement patterns and clinicopathologic characteristics. Results: From March 2022 to April 2023, a total of 151 patients with HCC were included, comprising 72 with NAFLD-related HCC and 79 with hepatitis B virus (HBV) cirrhosis–related HCC. On Sonazoid-CEUS, more than half of the NAFLD-related HCCs exhibited relatively early and mild washout within 60 seconds (54.2%, 39/72), whereas most HBV cirrhosis–related HCCs displayed washout between 60 and 120 seconds (46.8%, 37/79) or after 120 seconds (39.2%, 31/79) (P<0.001). In the patients with NAFLD-related HCC, multivariate analysis revealed that international normalized ratio (odds ratio [OR], 0.002; 95% confidence interval [CI], 0.000 to 0.899; P=0.046) and poor tumor differentiation (OR, 21.930; 95% CI, 1.960 to 245.319; P=0.012) were significantly associated with washout occurring within 60 seconds. Conclusion Characteristic Sonazoid-CEUS features are useful for diagnosing HCC in patients with NAFLD.

Purpose: This study aimed to evaluate the contrast-enhanced ultrasound with Sonazoid (Sonazoid-CEUS) features of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: In this retrospective study, patients who underwent surgical resection and were histopathologically diagnosed with NAFLD or cirrhosis-related HCC were included. All patients received Sonazoid-CEUS examinations within 1 week prior to hepatic surgery. The enhancement patterns of HCC lesions were evaluated and compared between the two groups according to the current World Federation for Ultrasound in Medicine and Biology guidelines. Multivariate logistic regression analysis was used to assess the correlations between Sonazoid-CEUS enhancement patterns and clinicopathologic characteristics. Results: From March 2022 to April 2023, a total of 151 patients with HCC were included, comprising 72 with NAFLD-related HCC and 79 with hepatitis B virus (HBV) cirrhosis–related HCC. On Sonazoid-CEUS, more than half of the NAFLD-related HCCs exhibited relatively early and mild washout within 60 seconds (54.2%, 39/72), whereas most HBV cirrhosis–related HCCs displayed washout between 60 and 120 seconds (46.8%, 37/79) or after 120 seconds (39.2%, 31/79) (P<0.001). In the patients with NAFLD-related HCC, multivariate analysis revealed that international normalized ratio (odds ratio [OR], 0.002; 95% confidence interval [CI], 0.000 to 0.899; P=0.046) and poor tumor differentiation (OR, 21.930; 95% CI, 1.960 to 245.319; P=0.012) were significantly associated with washout occurring within 60 seconds. Conclusion Characteristic Sonazoid-CEUS features are useful for diagnosing HCC in patients with NAFLD.

Purpose: This study aimed to evaluate the contrast-enhanced ultrasound with Sonazoid (Sonazoid-CEUS) features of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: In this retrospective study, patients who underwent surgical resection and were histopathologically diagnosed with NAFLD or cirrhosis-related HCC were included. All patients received Sonazoid-CEUS examinations within 1 week prior to hepatic surgery. The enhancement patterns of HCC lesions were evaluated and compared between the two groups according to the current World Federation for Ultrasound in Medicine and Biology guidelines. Multivariate logistic regression analysis was used to assess the correlations between Sonazoid-CEUS enhancement patterns and clinicopathologic characteristics. Results: From March 2022 to April 2023, a total of 151 patients with HCC were included, comprising 72 with NAFLD-related HCC and 79 with hepatitis B virus (HBV) cirrhosis–related HCC. On Sonazoid-CEUS, more than half of the NAFLD-related HCCs exhibited relatively early and mild washout within 60 seconds (54.2%, 39/72), whereas most HBV cirrhosis–related HCCs displayed washout between 60 and 120 seconds (46.8%, 37/79) or after 120 seconds (39.2%, 31/79) (P<0.001). In the patients with NAFLD-related HCC, multivariate analysis revealed that international normalized ratio (odds ratio [OR], 0.002; 95% confidence interval [CI], 0.000 to 0.899; P=0.046) and poor tumor differentiation (OR, 21.930; 95% CI, 1.960 to 245.319; P=0.012) were significantly associated with washout occurring within 60 seconds. Conclusion Characteristic Sonazoid-CEUS features are useful for diagnosing HCC in patients with NAFLD.

Purpose: This study aimed to evaluate the contrast-enhanced ultrasound with Sonazoid (Sonazoid-CEUS) features of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: In this retrospective study, patients who underwent surgical resection and were histopathologically diagnosed with NAFLD or cirrhosis-related HCC were included. All patients received Sonazoid-CEUS examinations within 1 week prior to hepatic surgery. The enhancement patterns of HCC lesions were evaluated and compared between the two groups according to the current World Federation for Ultrasound in Medicine and Biology guidelines. Multivariate logistic regression analysis was used to assess the correlations between Sonazoid-CEUS enhancement patterns and clinicopathologic characteristics. Results: From March 2022 to April 2023, a total of 151 patients with HCC were included, comprising 72 with NAFLD-related HCC and 79 with hepatitis B virus (HBV) cirrhosis–related HCC. On Sonazoid-CEUS, more than half of the NAFLD-related HCCs exhibited relatively early and mild washout within 60 seconds (54.2%, 39/72), whereas most HBV cirrhosis–related HCCs displayed washout between 60 and 120 seconds (46.8%, 37/79) or after 120 seconds (39.2%, 31/79) (P<0.001). In the patients with NAFLD-related HCC, multivariate analysis revealed that international normalized ratio (odds ratio [OR], 0.002; 95% confidence interval [CI], 0.000 to 0.899; P=0.046) and poor tumor differentiation (OR, 21.930; 95% CI, 1.960 to 245.319; P=0.012) were significantly associated with washout occurring within 60 seconds. Conclusion Characteristic Sonazoid-CEUS features are useful for diagnosing HCC in patients with NAFLD.

Purpose: This study aimed to evaluate the contrast-enhanced ultrasound with Sonazoid (Sonazoid-CEUS) features of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: In this retrospective study, patients who underwent surgical resection and were histopathologically diagnosed with NAFLD or cirrhosis-related HCC were included. All patients received Sonazoid-CEUS examinations within 1 week prior to hepatic surgery. The enhancement patterns of HCC lesions were evaluated and compared between the two groups according to the current World Federation for Ultrasound in Medicine and Biology guidelines. Multivariate logistic regression analysis was used to assess the correlations between Sonazoid-CEUS enhancement patterns and clinicopathologic characteristics. Results: From March 2022 to April 2023, a total of 151 patients with HCC were included, comprising 72 with NAFLD-related HCC and 79 with hepatitis B virus (HBV) cirrhosis–related HCC. On Sonazoid-CEUS, more than half of the NAFLD-related HCCs exhibited relatively early and mild washout within 60 seconds (54.2%, 39/72), whereas most HBV cirrhosis–related HCCs displayed washout between 60 and 120 seconds (46.8%, 37/79) or after 120 seconds (39.2%, 31/79) (P<0.001). In the patients with NAFLD-related HCC, multivariate analysis revealed that international normalized ratio (odds ratio [OR], 0.002; 95% confidence interval [CI], 0.000 to 0.899; P=0.046) and poor tumor differentiation (OR, 21.930; 95% CI, 1.960 to 245.319; P=0.012) were significantly associated with washout occurring within 60 seconds. Conclusion Characteristic Sonazoid-CEUS features are useful for diagnosing HCC in patients with NAFLD.

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.