1.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
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.
2.Analyzing Differences in Volatile Components of Citri Reticulatae Pericarpium Before and After Being Stir-fried with Halloysitum Rubrum Based on HS-GC-MS and Intelligent Sensory Technology
Li XIN ; Jiawen WEN ; Wenhui GONG ; Beibei ZHAO ; Shihao YAN ; Huashi CHEN ; Haiping LE ; Jinlian ZHANG ; Yanhua XUE
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(7):157-162
ObjectiveTo analyze the differences in color, odor and volatile components of Citri Reticulatae Pericarpium(CRP) before and after being stir-fried with Halloysitum Rubrum, and to explore the material basis of enhancing the effect of strengthening spleen after processing and the scientific connotation of decoction pieces processed with Halloysitum Rubrum as the auxiliary material. MethodsThe volatile components of the samples before and after processing were identified and relatively quantified by headspace gas chromatography-mass spectrometry(HS-GC-MS), and the volatile components were analyzed by principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA). According to the principle of variable importance in the projection(VIP) value>1.5, volatile differential components before and after processing were screened. And combined with intelligent sensory technologies such as colorimeter and electronic nose, the chroma and odor information of CRP before and after being stir-fried with Halloysitum Rubrum were identified. Pearson correlation analysis was used to explore the correlation between volatile differential components and chroma values. ResultsA total of 112 volatile components were identified from CRP and CRP stir-fried with Halloysitum Rubrum, of which 84 were from CRP and 97 were from CRP stir-fried with Halloysitum Rubrum. And 7 differential components were selected, including α-pinene, β-myrcene, linalool, sabinene, ocimene isomer mixture, A-ocimene, and δ-elemene. After being processed with Halloysitum Rubrum, the brightness value(L*), yellow-blue value(b*) and total chromatic value(E*ab) of CRP were decreased(P<0.01), and red-green value(a*) was increased(P<0.01), the response values of S4, S5, S10 and S13 sensors were significantly increased(P<0.05), and the response values of S3 and S8 sensors were significantly decreased(P<0.05). Correlation analysis showed that α-pinene and β-myrcene were negatively correlated with L* and E*ab, but positively correlated with a*. Sabinene was positively correlated with L* and E*ab. Linalool was positively correlated with L* and E*ab, and negatively correlated with a*. The ocimene isomer mixture was positively correlated with the L*. ConclusionAfter being processed with Halloysitum Rubrum, the appearance color, odor and volatile components of CRP change significantly, and α-pinene, β-myrcene, sabinene, linalool and A-ocimene are the characteristic volatile components before and after processing, which can provide references for the quality evaluation and clinical application of CRP and its processed products.
3.Analyzing Differences in Volatile Components of Citri Reticulatae Pericarpium Before and After Being Stir-fried with Halloysitum Rubrum Based on HS-GC-MS and Intelligent Sensory Technology
Li XIN ; Jiawen WEN ; Wenhui GONG ; Beibei ZHAO ; Shihao YAN ; Huashi CHEN ; Haiping LE ; Jinlian ZHANG ; Yanhua XUE
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(7):157-162
ObjectiveTo analyze the differences in color, odor and volatile components of Citri Reticulatae Pericarpium(CRP) before and after being stir-fried with Halloysitum Rubrum, and to explore the material basis of enhancing the effect of strengthening spleen after processing and the scientific connotation of decoction pieces processed with Halloysitum Rubrum as the auxiliary material. MethodsThe volatile components of the samples before and after processing were identified and relatively quantified by headspace gas chromatography-mass spectrometry(HS-GC-MS), and the volatile components were analyzed by principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA). According to the principle of variable importance in the projection(VIP) value>1.5, volatile differential components before and after processing were screened. And combined with intelligent sensory technologies such as colorimeter and electronic nose, the chroma and odor information of CRP before and after being stir-fried with Halloysitum Rubrum were identified. Pearson correlation analysis was used to explore the correlation between volatile differential components and chroma values. ResultsA total of 112 volatile components were identified from CRP and CRP stir-fried with Halloysitum Rubrum, of which 84 were from CRP and 97 were from CRP stir-fried with Halloysitum Rubrum. And 7 differential components were selected, including α-pinene, β-myrcene, linalool, sabinene, ocimene isomer mixture, A-ocimene, and δ-elemene. After being processed with Halloysitum Rubrum, the brightness value(L*), yellow-blue value(b*) and total chromatic value(E*ab) of CRP were decreased(P<0.01), and red-green value(a*) was increased(P<0.01), the response values of S4, S5, S10 and S13 sensors were significantly increased(P<0.05), and the response values of S3 and S8 sensors were significantly decreased(P<0.05). Correlation analysis showed that α-pinene and β-myrcene were negatively correlated with L* and E*ab, but positively correlated with a*. Sabinene was positively correlated with L* and E*ab. Linalool was positively correlated with L* and E*ab, and negatively correlated with a*. The ocimene isomer mixture was positively correlated with the L*. ConclusionAfter being processed with Halloysitum Rubrum, the appearance color, odor and volatile components of CRP change significantly, and α-pinene, β-myrcene, sabinene, linalool and A-ocimene are the characteristic volatile components before and after processing, which can provide references for the quality evaluation and clinical application of CRP and its processed products.
4.Environmental Temperature and the Risk of Hand, Foot, and Mouth Disease Transmission in the Yangtze River Region of China.
Yan Qing YANG ; Min CHEN ; Jin LI ; Kai Qi LIU ; Xue Yan GUO ; Xin XU ; Qian LIANG ; Xing Lu WU ; Su Wen LEI ; Jing LI
Biomedical and Environmental Sciences 2025;38(3):290-302
OBJECTIVE:
To assess health equity in the Yangtze River region to improve understanding of the correlation between hand, foot, and mouth disease (HFMD) and socioeconomic factors.
METHODS:
From 2014-2016, data on HFMD incidence, population statistics, economic indicators, and meteorology from 26 cities along the Yangtze River were analyzed. A multi-city random-effects meta-analysis was performed to study the relationship between temperature and HFMD transmission, and health equity was assessed with respect to socio-economic impact.
RESULTS:
Over the study period, 919,458 HFMD cases were reported, with Shanghai (162,303) having the highest incidence and Tongling (5,513) having the lowest. Males were more commonly affected (male-to-female ratio, 1.49:1). The exposure-response relationship had an M-shaped curve, with two HFMD peaks occurring at 4 °C and 26 °C. The relative risk had two peaks at 1.30 °C (1.834, 95% CI: 1.204-2.794) and 31.4 °C (1.143, 95% CI: 0.901-1.451), forming an M shape, with the first peak higher than the second. The most significant impact of temperature on HFMD was observed between -2 °C and 18.1 °C. The concentration index (0.2463) indicated moderate concentration differences, whereas the Theil index (0.0418) showed low inequality in distribution.
CONCLUSION
The incidence of HFMD varied across cities, particularly with changes in temperature. Economically prosperous areas showed higher risks, indicating disparities. Targeted interventions in these areas are crucial for mitigating the risk of HFMD.
Female
;
Humans
;
Male
;
China/epidemiology*
;
Cities/epidemiology*
;
Hand, Foot and Mouth Disease/transmission*
;
Incidence
;
Risk Factors
;
Temperature
5.Identifying High-Risk Areas for Type 2 Diabetes Mellitus Mortality in Guangdong, China: Spatiotemporal Clustering and Socioenvironmental Determinants.
Hai Ming LUO ; Wen Biao HU ; Yan Jun XU ; Xue Yan ZHENG ; Qun HE ; Lu LYU ; Rui Lin MENG ; Xiao Jun XU ; Fei ZOU
Biomedical and Environmental Sciences 2025;38(5):585-597
OBJECTIVE:
This study aimed to identify high-risk areas for type 2 diabetes mellitus (T2DM) mortality to provide relevant evidence for interventions in emerging economies.
METHODS:
Empirical Bayesian Kriging and a discrete Poisson space-time scan statistic were applied to identify the spatiotemporal clusters of T2DM mortality. The relationships between economic factors, air pollutants, and the mortality risk of T2DM were assessed using regression analysis and the Poisson Log-linear Model.
RESULTS:
A coastal district in East Guangdong, China, had the highest risk (Relative Risk [RR] = 4.58, P < 0.01), followed by the 10 coastal districts/counties in West Guangdong, China (RR = 2.88, P < 0.01). The coastal county in the Pearl River Delta, China (RR = 2.24, P < 0.01), had the third-highest risk. The remaining risk areas were two coastal counties in East Guangdong, 16 districts/counties in the Pearl River Delta, and two counties in North Guangdong, China. Mortality due to T2DM was associated with gross domestic product per capita (GDP per capita). In pilot assessments, T2DM mortality was significantly associated with carbon monoxide.
CONCLUSION
High mortality from T2DM occurred in the coastal areas of East and West Guangdong, especially where the economy was progressing towards the upper middle-income level.
Diabetes Mellitus, Type 2/epidemiology*
;
China/epidemiology*
;
Humans
;
Risk Factors
;
Spatio-Temporal Analysis
;
Air Pollutants/analysis*
;
Socioeconomic Factors
;
Bayes Theorem
;
Female
;
Male
;
Middle Aged
6.Association between Serum Chloride Levels and Prognosis in Patients with Hepatic Coma in the Intensive Care Unit.
Shu Xing WEI ; Xi Ya WANG ; Yuan DU ; Ying CHEN ; Jin Long WANG ; Yue HU ; Wen Qing JI ; Xing Yan ZHU ; Xue MEI ; Da ZHANG
Biomedical and Environmental Sciences 2025;38(10):1255-1269
OBJECTIVE:
To explore the relationship between serum chloride levels and prognosis in patients with hepatic coma in the intensive care unit (ICU).
METHODS:
We analyzed 545 patients with hepatic coma in the ICU from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Associations between serum chloride levels and 28-day and 1-year mortality rates were assessed using restricted cubic splines (RCSs), Kaplan-Meier (KM) curves, and Cox regression. Subgroup analyses, external validation, and mechanistic studies were also performed.
RESULTS:
A total of 545 patients were included in the study. RCS analysis revealed a U-shaped association between serum chloride levels and mortality in patients with hepatic coma. The KM curves indicated lower survival rates among patients with low chloride levels (< 103 mmol/L). Low chloride levels were independently linked to increased 28-day and 1-year all-cause mortality rates. In the multivariate models, the hazard ratio ( HR) for 28-day mortality in the low-chloride group was 1.424 (95% confidence interval [ CI]: 1.041-1.949), while the adjusted hazard ratio for 1-year mortality was 1.313 (95% CI: 1.026-1.679). Subgroup analyses and external validation supported these findings. Cytological experiments suggested that low chloride levels may activate the phosphorylation of the NF-κB signaling pathway, promote the expression of pro-inflammatory cytokines, and reduce neuronal cell viability.
CONCLUSION
Low serum chloride levels are independently associated with increased mortality in patients with hepatic coma.
Humans
;
Male
;
Female
;
Middle Aged
;
Intensive Care Units
;
Prognosis
;
Chlorides/blood*
;
Aged
;
Coma/blood*
;
Adult
7.Research on Two-Dimensional Convolutional Neural Network Model for Near Infrared Spectroscopy Analysis Based on Competitive Adaptive Reweighted Sampling and Gramian Angular Difference Field
Xiao-Song ZENG ; Ke-Wei HUAN ; Xiao-Xi LIU ; Xian-Wen CAO ; Xue-Yan HAN
Chinese Journal of Analytical Chemistry 2025;53(6):955-966
Near infrared spectroscopy(NIRS)analysis technology has become an important process analysis tool in industrial and agricultural production,and has been widely used for qualitative and quantitative analysis in the fields of tobacco,agriculture,and pharmaceuticals.To address issues such as poor generalization ability and low prediction accuracy in NIRS modeling,a two-dimensional convolutional neural network(2DCNN)quantitative analysis model based on competitive adaptive reweighted sampling(CARS)and Gramian angular difference field(GADF)(CARS-GADF-2DCNN)was proposed.CARS-GADF-2DCNN used the CARS method to select an optimal wavelength set from the full spectrum,then employed GADF to encode the selection results into two-dimensional images,and finally used 2DCNN for prediction analysis.The 2DCNN model consisted of convolutional layers,parallel convolution modules,flattening layer,and fully connected layers.Simulation experiments were conducted on three public near-infrared(NIR)spectral datasets encompassing soil,tablet,and grain datasets to evaluate the CARS-GADF-2DCNN model.The results demonstrated that,compared to the one-dimensional convolutional neural network(1DCNN),the GADF-2DCNN model achieved 16.74%,23.40%,and 7.13%improvement in prediction accuracy for the soil,tablet,and grain datasets,respectively.Compared to GADF-2DCNN,VCPA-GADF-2DCNN,and IRIV-GADF-2DCNN models,the CARS-GADF-2DCNN model further improved prediction accuracy.For the soil dataset,prediction accuracy improved by 39.00%,30.78%and 4.13%;for the tablet dataset,the improvements were 9.52%,6.94%and 2.56%;for the grain dataset,the improvements were 20.57%,9.85%and 15.66%.In conclusion,CARS-GADF-2DCNN effectively selected the optimal wavelength subset from near infrared spectra,and revealed the latent features between different wavelengths.CARS-GADF-2DCNN addresses the issues of high complexity in prediction models and low prediction accuracy in near infrared spectral modeling,and could be effectively applied to near infrared spectral prediction analysis of different substances.
8.AuNPs-FeCDs Dual Nanozyme Cascade System Integrated with A Smartphone Platform for Sensitive Detection of Glucose
Qing-Jing YE ; Xue-Ying ZHOU ; Yan-Ying ZHENG ; Yun ZHANG ; Wen-Ying JIN ; Ya-Li YUAN
Chinese Journal of Analytical Chemistry 2025;53(9):1457-1466
A centrifugation-free,single-reaction colorimetric method for detection of glucose,utilizing a dual nanozyme cascade system based on gold nanoparticles(AuNPs)and iron-doped carbon dots(FeCDs),was developed in this work.The AuNPs exhibited glucose oxidase-like activity to catalyze glucose oxidation for generation of H2O2,while the FeCDs demonstrated peroxidase-like activity to subsequently catalyze the H2O2-mediated oxidation of 3,3',5,5'-tetramethylbenzidine(TMB).To prevent interference from the blue signal generated by self-aggregation of AuNPs in subsequent quantitative detection,the reaction system was terminated with HCl,converting oxTMB into a stable yellow product.Based on changes in the absorbance at 450 nm of this yellow solution,a quantitative relationship was established between glucose concentration and absorbance at 450 nm(A450).Experimental results demonstrated that this sensor achieved a linear detection range of 44 μmol/L to 11.11 mmol/L(R2=0.993)with a detection limit of 30.68 μmol/L and spiked recoveries of 97.9%-104.7%.By integrating smartphone-based color recognition capabilities,a rapid visual detection platform was established for quantification of glucose through RGB analysis.The validation experimental results using commercial glucose injection samples further confirmed the practical application potential of this methodology.
9.Predictive value of automatic breast ultrasound features combined with Ki-67 for pathological complete response after neoadjuvant chemotherapy in triple negative breast cancer
Yang ZHAO ; Ying-Cong XIAO ; Yan JU ; Xiao-Zhi DANG ; Wen-Xin XUE ; Yang LI ; Hong-Ping SONG
Medical Journal of Chinese People's Liberation Army 2025;50(6):695-702
Objective To explore the predictive value of automated breast ultrasound(ABUS)features combined with Ki-67 in predicting pathological complete response(pCR)after neoadjuvant chemotherapy(NAC)in triple-negative breast cancer(TNBC).Methods A retrospective analysis was conducted on 127 female TNBC patients treated at Xijing Hospital,Air Force Medical University from March 2019 to December 2023.All patients underwent NAC and surgical treatment after ABUS examination.Based on postoperative pathological results,patients were divided into pCR group(n=60)and non-pathological complete response(npCR)group(n=67).Differences in various parameters before NAC were compared between the two groups.LASSO regression was used to identify independent factors influencing pCR after NAC in TNBC patients,and a predictive model was constructed using multivariate logistic regression.The prediction model was internally validated using the Bootstrap method(1000 resamples).The discriminative ability of the model was evaluated using receiver operating characteristic(ROC)curves,and the area under the curves(AUCs)of different prediction models were compared using De-long's test.The accuracy of the model was assessed using calibration curves,and the clinical benefit of the model was evaluated using clinical decision curve analysis(DCA).Results Significant differences were observed between two groups in terms of age,Ki-67,menopausal status,tumor type,posterior echo,coronal plane convergence sign,coronal plane skip sign,and coronal plane white wall sign before NAC(P<0.05).LASSO regression analysis showed that Ki-67,coronal plane convergence sign,and coronal plane white wall sign were independent influencing factors of pCR after NAC in TNBC patients(P<0.05).The AUC of the multivariate logistic regression model based on Ki-67 was 0.733(95%CI 0.646-0.819),the AUC of ABUS model was 0.777(95%CI 0.695-0.858),and the AUC of ABUS combined with Ki-67 model was 0.816(95%CI 0.741-0.890).De-long's test showed that the AUC of the combined model was higher than those of ABUS feature model and Ki-67 model,with statistically significant differences(P<0.05).There was no significant difference in the AUC between ABUS feature model and Ki-67 model(P=0.40).Hosmer-Lemeshow test indicated that the combined model had a good fit(P=0.304).Internal validation results showed that the combined model had a good stability with a consistency index(C-index)of 0.820(95%CI 0.726-0.879).The calibration curve demonstrated good consistency between the predicted and actual probabilities of the combined prediction model,and the DCA curve indicated that the model had favorable clinical benefit.Conclusion The combined ABUS feature and Ki-67 model can be used to predict the probability of pCR after NAC in TNBC patients,providing a reference for the formulation of clinical treatment plans in TNBC patients.
10.Effect of sodium cantharidinate and vitamin B6 injection on human hepatocellular carcinoma cells and its mechanism
Lan-Lan SI ; Wen XU ; Le LI ; Dong JI ; Xue-Yuan CHEN ; Jiu-Zeng DAI ; Zeng-Tao YAO ; Wei-Wei CHEN ; Yan LIU
Medical Journal of Chinese People's Liberation Army 2025;50(6):747-755
Objective To analyze the effect of sodium cantharidinate and vitamin B6 injection(SCV)on four human hepatocellular carcinoma(HCC)cell lines(SMMC-7721,Bel-7402,Huh7,and HepG2)and explore its mechanism.Methods Normal hepatic cell line L02 was treated with SCV at concentrations of 0 μmol/L(control),0.5,1,2,4,8,16,and 32 μmol/L,and the cytotoxicity of SCV on L02 cells was detected using CCK-8 assay.Human HCC cell lines(SMMC-7721,Bel-7402,Huh7,and HepG2)were cultured.SCV-untreated control group(0 μmol/L)and 2,4,and 8 μmol/L SCV-treated groups were set up.CCK-8 assay,plate cloning formation assay,Transwell assay,wound healing assay,and flow cytometry were used to detect the effects of SCV on the growth and proliferation capacity,colony formation ability,invasion and migration capabilities,cell cycle,and apoptosis of the four hepatocellular carcinoma cell lines,respectively.Western blotting was performed to detect the expression levels of apoptosis-related proteins,including nuclear factor kappa-B subunit p65(p65),B-cell lymphoma 2(Bcl-2),and Caspase-3,and to preliminarily explore the underlying mechanism.Results The CCK-8 assay showed that SCV at 0.5,1,2,4,and 8 μmol/L had no significant cytotoxic effect on L02 cells compared with untreated control group,so 2,4,and 8 μmol/L SCV were selected for subsequent experiments.Compared with the untreated control group(0 μmol/L),SCV at different concentrations(2,4,and 8 μmol/L)significantly inhibited the proliferation of the four HCC cell lines(P<0.001).The plate cloning formation assay showed that SCV at different concentrations(2,4,and 8 μmol/L)significantly reduced the colony formation ability of the four HCC cell lines(P<0.05 or P<0.01 or P<0.001).In addition,Transwell and wound healing assays revealed that SCV at different concentrations(2,4,and 8 μmol/L)significantly inhibited the invasion and migration of HCC cells(P<0.05 or P<0.01 or P<0.001).In the above results,the inhibitory effect of SCV was concentration-dependent.Flow cytometry analysis indicated that SCV arrested cells in the G2/M phase(P<0.05 or P<0.01 or P<0.001)and significantly promoted cell apoptosis(P<0.05 or P<0.01 or P<0.001).Western blotting showed that SCV significantly down-regulated the expression of p65(P<0.05 or P<0.01)and Bcl-2(P<0.05),and up-regulated the expression of Caspase-3(P<0.05 or P<0.01).Conclusions SCV can significantly inhibit the proliferation,colony formation,invasion,and migration of multiple human HCC cell lines and arrest the cell cycle.SCV may inhibit the expression of p65 and Bcl-2,thereby lifting their inhibitory effect on the apoptotic pathway and activating Caspase-3 to promote apoptosis.

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