Hepatocellular carcinoma (HCC) is an aggressive primary liver malignancy often diagnosed at an advanced stage, resulting in a poor prognosis. Accurate risk stratification and early detection of HCC are critical unmet needs for improving outcomes. Several blood-based biomarkers and imaging tests are available for early detection, prediction, and monitoring of HCC. However, serum protein biomarkers such as alpha-fetoprotein have shown relatively low sensitivity, leading to inaccurate performance. Imaging studies also face limitations related to suboptimal accuracy, high cost, and limited implementation. Recently, liquid biopsy techniques have gained attention for addressing these unmet needs. Liquid biopsy is non-invasive and provides more objective readouts, requiring less reliance on healthcare professional’s skills compared to imaging. Circulating tumor cells, cell-free DNA, and extracellular vesicles are targeted in liquid biopsies as novel biomarkers for HCC. Despite their potential, there are debates regarding the role of these novel biomarkers in the HCC care continuum. This review article aims to discuss the technical challenges, recent technical advancements, advantages and disadvantages of these liquid biopsies, as well as their current clinical application and future directions of liquid biopsy in HCC.

Occupational pneumoconiosis remains the most common occupational disease in China, with occupational mineral dust exposure being its primary causative factor. Although national standards for online monitoring and early warning systems of coal mine dust concentrations have been established, national occupational health standards for rapid and online monitoring of dust concentration and particle size distribution in other industries are still limited. Among dust concentration sensor technologies, the light scattering method is the preferred choice for online dust monitoring owing to its wide measurement range and low cost. The beta-ray absorption method is mature but highly sensitive to humidity. The electrostatic induction method offers high sensitivity, simple structure, and low maintenance costs but exhibits high errors in low-concentration dust monitoring. The tapered element oscillating microbalance method is highly sensitive but costly. Multi-sensor data fusion technology can improve monitoring reliability, however, mature domestic products are not yet available. For monitoring dust particle size distribution, sieving and sedimentation methods are cumbersome. The aerodynamic method shows broad prospects in the online monitoring of respirable dust but has obvious measurement errors for larger dust particles. The use of optical measurement method is limited by dust morphology and is not suitable for monitoring coal dust particle size distribution. The electrical mobility method is primarily applicable to submicron dust. Future research should focus on promoting the application of monitoring technology for respirable dust particle size distribution in online monitoring of industrial dust. By integrating Internet of Things, data mining, and artificial intelligence technologies, along with multi-sensor data fusion and numerical simulation, dust concentration prediction models can be established to achieve accurate dust concentration monitoring and early warning of exceedances. The advancements of technologies will provide scientific support for the assessment of industrial dust hazards and the prevention and control of occupational pneumoconiosis.

Hepatocellular carcinoma (HCC) is an aggressive primary liver malignancy often diagnosed at an advanced stage, resulting in a poor prognosis. Accurate risk stratification and early detection of HCC are critical unmet needs for improving outcomes. Several blood-based biomarkers and imaging tests are available for early detection, prediction, and monitoring of HCC. However, serum protein biomarkers such as alpha-fetoprotein have shown relatively low sensitivity, leading to inaccurate performance. Imaging studies also face limitations related to suboptimal accuracy, high cost, and limited implementation. Recently, liquid biopsy techniques have gained attention for addressing these unmet needs. Liquid biopsy is non-invasive and provides more objective readouts, requiring less reliance on healthcare professional’s skills compared to imaging. Circulating tumor cells, cell-free DNA, and extracellular vesicles are targeted in liquid biopsies as novel biomarkers for HCC. Despite their potential, there are debates regarding the role of these novel biomarkers in the HCC care continuum. This review article aims to discuss the technical challenges, recent technical advancements, advantages and disadvantages of these liquid biopsies, as well as their current clinical application and future directions of liquid biopsy in HCC.

Background Coal workers' pneumoconiosis is a serious occupational disease in China. Exhaled volatile organic compounds (VOCs) can serve as the "breath fingerprint" of internal pathological processes, which provides a theoretical basis for exhaled VOCs to be used as potential non-invasive biomarkers for early diagnosis of coal workers' pneumoconiosis. Objective To screen out the characteristic VOCs and important characteristic VOCs of exhaled air in patients with coal workers' pneumoconiosis, and to explore the potential of these VOCs as biomarkers for early non-invasive diagnosis of the disease. Methods In this study, 27 VOCs in the exhaled breath of 22 patients with stage I coal workers' pneumoconiosis, 77 workers exposed to dust, and 92 healthy controls were quantitatively detected by thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Substances with P<0.05 in univariate analysis and variable importance projection (VIP) >1 in supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model were selected as the characteristic VOCs for early diagnosis of coal workers' pneumoconiosis. Age was included in the LASSO regression model as a covariate to screen out important characteristic VOCs, and the diagnostic performance was evaluated by receiver operating characteristic (ROC) curve. Spearman correlation was further used to explore the correlation between important characteristic VOCs and clinical lung function indicators. Results Through univariate analysis and OPLS-DA modeling, 8 VOCs were selected, including 2-methylpentane, 3-methylpentane, n-hexane, methylcyclopentane, n-heptane, methylcyclohexane, 4-methyl-2-pentanone, and 2-hexanone, in exhaled breath of patients with coal workers' pneumoconiosis. The concentrations of 4 VOCs, including 3-methylpentane, n-hexane, 4-methyl-2-pentanone, and 2-hexanone, showed a decreasing trend with the increase of dust exposure years. By LASSO regression, the important characteristic VOCs of the coal workers' pneumoconiosis group and the dust exposure group were n-hexane, methylcyclohexane and 4-methyl-2-pentanone, and the important characteristic VOCs of the coal workers' pneumoconiosis group and the healthy group were 2-methyl-pentane and 4-methyl-2-pentanone. The ROC analysis showed that the area under the curve (AUC) of n-hexane, methylcyclohexane, and 4-methyl-2-pentanone were 0.969, 0.909, and 0.956, respectively, and the AUC of combined diagnosis was 0.988 and its Youden index was 0.961, suggesting that these results can serve as a valuable reference for further research on early diagnosis. The Correlation analysis found that there was a positive correlation between n-hexane and lung function indicators in the important characteristic VOCs, indicating that it could indirectly reflect the obstruction of lung function ventilation, further proving that important characteristic VOCs have the potential to monitor lung function decline. Conclusion Three important characteristic VOCs selected in this study have the potential to be used as non-invasive biomarkers for early diagnosis and disease monitoring of coal workers' pneumoconiosis, and are worthy of further study and verification.

Hepatocellular carcinoma (HCC) is an aggressive primary liver malignancy often diagnosed at an advanced stage, resulting in a poor prognosis. Accurate risk stratification and early detection of HCC are critical unmet needs for improving outcomes. Several blood-based biomarkers and imaging tests are available for early detection, prediction, and monitoring of HCC. However, serum protein biomarkers such as alpha-fetoprotein have shown relatively low sensitivity, leading to inaccurate performance. Imaging studies also face limitations related to suboptimal accuracy, high cost, and limited implementation. Recently, liquid biopsy techniques have gained attention for addressing these unmet needs. Liquid biopsy is non-invasive and provides more objective readouts, requiring less reliance on healthcare professional’s skills compared to imaging. Circulating tumor cells, cell-free DNA, and extracellular vesicles are targeted in liquid biopsies as novel biomarkers for HCC. Despite their potential, there are debates regarding the role of these novel biomarkers in the HCC care continuum. This review article aims to discuss the technical challenges, recent technical advancements, advantages and disadvantages of these liquid biopsies, as well as their current clinical application and future directions of liquid biopsy in HCC.

Objective To identify risk factors associated with lymphatic leakage after laparoscopic radical prostatectomy(LRP)and to develop a machine learning-based nomogram for predicting such outcomes to support clinical prevention strategies.Methods We retrospectively analyzed perioperative data from 248 patients who underwent radical prostatectomy for prostate cancer between January 2020 and January 2024.Independent risk factors were identified through univariate and multivariate logistic regression analyses.A predictive model was developed,and its diagnostic performance was assessed by the area under the receiver operating characteristic curve(AUC).Five-fold cross-validation was performed to evaluate the model's generalizability.A nomogram was subsequently constructed to facilitate individualized risk quantification.Results Among the 248 patients,89(35.9%)developed lymphatic leakage,while 159(64.1%)did not.Independent risk factors for lymphatic leakage included intraopera-tive lymph node dissection(OR=5.415,95%CI:2.167～13.532,P<0.001),intraoperative plasma transfusion(OR=2.952,95%CI:1.524～5.718,P=0.001),and postoperative fasting duration of≥2 days(OR=1.412,95%CI:1.089～1.829,P=0.009).The predictive model showed good discrimination and calibration(AUC=0.711,95%CI:0.647～0.776,P<0.001;sensitivity:0.764;specificity:0.597).Model robustness was confirmed through five-fold cross-validation(training set AUC=0.822;test set AUC=0.829).The nomogram provided a clinically useful tool for quantifying individual risk of lymphatic leakage.Conclusions Intraoperative lymph node dissection,plasma transfusion,and postoperative fasting lasting≥2 days are independent risk factors for lymphatic leakage following radical prostatectomy.The validated predictive model demonstrates favorable clinical utility.

Objective To identify risk factors associated with lymphatic leakage after laparoscopic radical prostatectomy(LRP)and to develop a machine learning-based nomogram for predicting such outcomes to support clinical prevention strategies.Methods We retrospectively analyzed perioperative data from 248 patients who underwent radical prostatectomy for prostate cancer between January 2020 and January 2024.Independent risk factors were identified through univariate and multivariate logistic regression analyses.A predictive model was developed,and its diagnostic performance was assessed by the area under the receiver operating characteristic curve(AUC).Five-fold cross-validation was performed to evaluate the model's generalizability.A nomogram was subsequently constructed to facilitate individualized risk quantification.Results Among the 248 patients,89(35.9%)developed lymphatic leakage,while 159(64.1%)did not.Independent risk factors for lymphatic leakage included intraopera-tive lymph node dissection(OR=5.415,95%CI:2.167～13.532,P<0.001),intraoperative plasma transfusion(OR=2.952,95%CI:1.524～5.718,P=0.001),and postoperative fasting duration of≥2 days(OR=1.412,95%CI:1.089～1.829,P=0.009).The predictive model showed good discrimination and calibration(AUC=0.711,95%CI:0.647～0.776,P<0.001;sensitivity:0.764;specificity:0.597).Model robustness was confirmed through five-fold cross-validation(training set AUC=0.822;test set AUC=0.829).The nomogram provided a clinically useful tool for quantifying individual risk of lymphatic leakage.Conclusions Intraoperative lymph node dissection,plasma transfusion,and postoperative fasting lasting≥2 days are independent risk factors for lymphatic leakage following radical prostatectomy.The validated predictive model demonstrates favorable clinical utility.

Objective:To investigate the effect of hUCMSC-exos on the expression levels of HDAC in different isotypes of RA FLSs, and to elucidate the possible mechanism of hUCMSC-exos on the apoptosis of RA FLSs by regulating HDAC.Methods:hUCMSC and hUCMSC-Exos were isolated and identified. RT-qPCR was used to detect the changes in HDAC mRNA expression levels in FLSs after hUCMSC-Exos intervention, and the most affected HDAC types were identified. Western blot was used to detect the levels of FLS HDAC1 protein and the expression levels of NF-κB p65 and phospho-NF-κB p65 (Ser 536) in the blank control group, hUCMSC group, hUCMSC-Exos group, Trichostatin A (TSA) group and HDAC1 Inhibitor (Pyroxamide) group. To investigate the effects of hUCMSC-Exos on HDAC expression and NF-κB activity in FLSs. Flow cytometry was used to detect the effect of hUCMSC-Exos on the apoptosis of FLSs. ELISA was used to detect the effects of hUCMSC-Exos on the secretion of TNF-α, IL-6, IL-1β and IL-8 by FLSs. Flow cytometry and ELISA were used to detect the apoptosis level and pro-inflammatory cytokine secretion level of RA FLSs in the blank control group, NF-κB Inhibitor (pyrrolidine dithiocarbamate (PDTC) group, hUCMSC-Exos group and PDTC+hUCMSC-Exos co-intervention group. Whether inhibition of NF-κB affects the regulatory effect of hUCMSC-Exos on RA FLSs was further explored. All experimental data conforming to the normal distribution were compared by one-way ANOVA. LSD- t test was used for pin-group comparison, and independent sample t test was used for two-sample comparison. Results:Cultured primary hUCMSC were adherently grown spindle-shaped cells, and hUCMSC-Exos were saucer-shaped membranous vesicles, both of which met the identification criteria. hUCMSC-Exos reduced the expression level of HDCA1 mRNA [(0.932±0.091), t=2.19, P<0.001] and protein [(0.204±0.012), t=8.28, P<0.001] in RA FLSs, and the inhibitory effect was stronger than that of hUCMSC ( t=1.09, P=0.009) and HDAC1 ( t=11.29, P=0.013) Inhibitor. hUCMSC-Exos increased the apoptosis rate of RA FLSs [(48.68±0.84)%, t=12.33, P<0.001]. hUCMSC-Exos reduced the secretion levels of TNF-α [(29.6±1.0)pg/ml, t=10.78, P<0.001], IL-6 [(20.1±0.7)pg/ml, t=7.96, P<0.001], IL-1β [(9.28±0.23)pg/ml, t=6.14, P<0.001] and IL-8 [(108.0±3.8)pg/ml, t=1.21, P<0.001] in the supernatant of RA FLSs. hUCMSC-Exos reduced the expression level of p-NF-κB-p65/NF-κB-p65 in RA FLSs(0.351±0.024, t=17.67, P<0.001), and its inhibitory effect was stronger than that of hUCMSC (0.515±0.064, t=8.07, P=0.009) and HDAC1 inhibitor(0.411±0.033, t=2.44, P=0.04). After use of NF-κB inhibitors, hUCMSC-Exos weakened the promotion of apoptosis of RA FLSs [(29.0±0.5)%, t=10.63, P<0.001] and weakened the inhibitory effect of IL-8 secretion in the supernatant of RA FLSs [(125.5±3.2)pg/ml, t=2.63, P=0.002]. Conclusion:hUCMSC-Exos can mimic maternal cells to effectively inhibit the aberrant expression of HDAC1 in RA FLSs. hUCMSC-Exos may affect the apoptosis of RA FLSs and the secretion of pro-inflammatory cytokines by inhibiting the HDAC1/NF-κB pathway.

Background Volatile organic compounds (VOCs) in exhaled breath are closely associated with respiratory diseases and are linked to various metabolic reactions in the human body. A quantitative analytical method can provide technical support for studying VOCs related to various diseases. Objective To establish a thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) method for the determination of 27 VOCs in exhaled breath. Methods VOCs in exhaled breath were collected using a Bio-VOC sampler and enriched with Tenax TA thermal desorption tubes before TD-GC-MS analysis. Standards were collected using thermal desorption tubes and optimized for thermal desorption conditions as well as chromatographic and mass spectrometric conditions: The separation of the 27 VOCs was achieved by an optimized temperature program, the improvement of sensitivity by optimizing quantitative ions, and the increase of VOCs desorption efficiency by optimizing thermal desorption time and temperature. Limit of detection, limit of quantification, accuracy, precision, and stability of the proposed method were investigated by spiking with a blank gas bag, and exhaled breath samples from 20 healthy individuals were collected for an application study of the proposed method. Results The thermal desorption temperature was 280 ℃, and desorption time was 6 min. A VF-624ms chromatographic column was selected for the separation of target substances. The initial temperature of heating program was 35 ℃, maintained for 1 min, and then increased to 100 ℃ at a heating rate of 3 ℃·min⁻¹ for 1 min, followed by increasing to 210 ℃ at a heating rate of 28 ℃·min⁻¹ for 5 min. A quantitative analysis was conducted with a single ion monitoring (SIM) mode. Under these conditions, the 27 VOCs showed good linear relationships in their respective concentration ranges and the correlation coefficients were higher than 0.9990. The limits of detection of the method were in the range of 0.01-0.13 nmol·mol⁻¹, the limits of quantification were in the range of 0.02-0.44 nmol·mol⁻¹, and the spiked recoveries were in the range of 80.1%-120.5%, with intra-batch and inter-batch precision ≤ 18.8% and 17.9% respectively. All substances can be stored at room temperature (23-28 °C) for 7 d and at 4 °C for 14 d. The proposed method was applied to exhaled breath samples from 20 subjects with detection rates≥ 80% (except for trans-2-pentene and decane) and a concentration range of 0.00-465.50 nmol·mol⁻¹. Conclusion The established TD-GC-MS method for quantification of VOCs in exhaled breath is characterized by high sensitivity and good accuracy, and is suitable for quantitative determination of VOCs in exhaled breath, which can provide technical support for the study of exhaled breath VOCs.