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.

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.

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.

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.

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.

Radiation mainly comes from medical radiation,industrial radiation,nuclear waste and atmospheric ultraviolet radiation,etc.,radiation is divided into ionizing radiation and non-ionizing radiation.Studying the effects of ionizing and non-ionizing radiation on drug metabolism,understanding the absorption and distribution of drugs in the body after radiation and the speed of elimination under radiation conditions can provide reasonable guidance for clinical medication.This article reviews the effects of radiation on the pharmacokinetics of different drugs,elaborates the changes of different pharmacokinetics under radiation state,and discusses the reasons for the changes.

Objective To establish a rapid screening method for 34 emerging contaminants in surface water by ultra-high performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS).Methods The pretreatment conditions of solid phase extraction(SPE)were op-timized by orthogonal experimental design and the surface water samples were concentrated and ex-tracted by Oasis? HLB and Oasis? MCX SPE columns in series.The extracts were separated by Kine-tex? EVO C18 column,with gradient elution of 0.1%formic acid aqueous solution and 0.1%formic acid methanol solution.Q-TOF-MS'fullscan'and'targeted MS/MS'modes were used to detect 34 emerging contaminants and to establish a database with 34 emerging contaminants precursor ion,prod-uct ion and retention times.Results The 34 emerging contaminants exhibited good linearity in the con-centration range respectively and the correlation coefficients(r)were higher than 0.97.The limit of de-tection was 0.2-10 ng/L and the recoveries were 81.2%-119.2%.The intra-day precision was 0.78%-18.70%.The method was applied to analyze multiple surface water samples and 6 emerging contaminants were detected,with a concentration range of 1.93-157.71 ng/L.Conclusion The method is simple and rapid for screening various emerging contaminants at the trace level in surface water.

Objective To investigate the effect and mechanism of Heixiaoyao powder in regulating mitogen-activated protein kinase phosphatase-1(MKP-1)/c-Jun N-terminal kinase(JNK)signaling pathway on the level of Tau protein and neuroinflammation in the hippocampus of Alzheimer's disease(AD)rats.Methods Male Wistar rats with SPF grade were randomly divided into blank,sham-operation,model,control and experimental-L,-M,-H groups with 10 rats per group.In addition to the blank and sham-operation groups,the other 5 groups of rats were injected with β-amyloid 1-42(Aβ1-42)solution in bilateral hippocampus to replicate AD rat model,and the sham-operation group was injected with the same amount of 0.9％NaCl in the same way.Animals successfully replicated in the model were randomly divided into model group,control group(0.5 mg·kg-1 donepezil hydrochloride)and experimental-L,-M,-H groups(3.82,7.65,15.30 g·kg-1 Heixiaoyao powder decoction).The blank,sham-operation and model groups were given equal volume of 0.9％NaCl by gavage.The drug was given by gavage once a day for 42 days.Morris water maze was used to detect the learning and memory ability of rats.The levels of tumor necrosis factor-α(TNF-α)and interleukin-6(IL-6)in hippocampus were detected by enzyme-linked immunosorbent assay.Western blot was used to detect the expression of MKP-1,phospho JNK(p-JNK)and phospho Tau(p-Tau)proteins.Results The escape latency on day 5 of the experimental-M,-H groups,control group,model group,sham-operation group and blank group were(8.28±7.67),(7.89±4.18),(7.86±2.68),(16.55±4.16),(6.46±3.30)and(3.60±1.53)s;the levels of TNF-α in the above groups were(406.56±28.44),(404.17±22.84),(402.28±28.36),(665.89±61.15),(226.44±34.84)and(218.50±30.16)pg·mL-1;IL-6 levels were(136.54±7.04),(121.67±5.19),(119.15±5.87),(166.27±8.91),(88.75±5.28)and(79.58±7.53)ng·L-1;the relative expression levels of MKP-1 protein were 2.31±0.34,2.59±0.38,2.58±0.37,1.23±0.25,2.64±0.19 and 2.84±0.18;the relative expression levels of p-JNK protein were 3.46±0.35,3.45±0.31,3.20±0.23,4.48±0.30,2.87±0.51 and 2.30±0.26;the relative expression levels of p-Tau protein were 3.46±0.33,3.24±0.48,3.09±0.31,4.85±1.06,2.69±0.34 and 2.40±0.55,respectively.Compared with the model group and the normal group,compared with the experimental group and the model group,the differences of above indexes were statistically significant(P＜0.05,P＜0.01).Conclusion Heixiaoyao powder can improve the learning and memory ability of AD rats,and its mechanism may be related to the regulation of MKP-1 and JNK proteins,thus inhibiting the phosphorylation level of Tau protein and alleviating neuroinflammation.

Objective: To explore the molecular features of chronic myelomonocytic leukemia (CMML) . Methods: According to 2022 World Health Organization (WHO 2022) classification, 113 CMML patients and 840 myelodysplastic syndrome (MDS) patients from March 2016 to October 2021 were reclassified, and the clinical and molecular features of CMML patients were analyzed. Results: Among 113 CMML patients, 23 (20.4%) were re-diagnosed as acute myeloid leukemia (AML), including 18 AML with NPM1 mutation, 3 AML with KMT2A rearrangement, and 2 AML with MECOM rearrangement. The remaining 90 patients met the WHO 2022 CMML criteria. In addition, 19 of 840 (2.3%) MDS patients met the WHO 2022 CMML criteria. At least one gene mutation was detected in 99% of CMML patients, and the median number of mutations was 4. The genes with mutation frequency ≥ 10% were: ASXL1 (48%), NRAS (34%), RUNX1 (33%), TET2 (28%), U2AF1 (23%), SRSF2 (21.1%), SETBP1 (20%), KRAS (17%), CBL (15.6%) and DNMT3A (11%). Paired analysis showed that SRSF2 was frequently co-mutated with ASXL1 (OR=4.129, 95% CI 1.481-11.510, Q=0.007) and TET2 (OR=5.276, 95% CI 1.979-14.065, Q=0.001). SRSF2 and TET2 frequently occurred in elderly (≥60 years) patients with myeloproliferative CMML (MP-CMML). U2AF1 mutations were often mutually exclusive with TET2 (OR=0.174, 95% CI 0.038-0.791, Q=0.024), and were common in younger (<60 years) patients with myelodysplastic CMML (MD-CMML). Compared with patients with absolute monocyte count (AMoC) ≥1×10(9)/L and <1×10(9)/L, the former had a higher median age of onset (60 years old vs 47 years old, P<0.001), white blood cell count (15.9×10(9)/L vs 4.4×10(9)/L, P<0.001), proportion of monocytes (21.5% vs 15%, P=0.001), and hemoglobin level (86 g/L vs 74 g/L, P=0.014). TET2 mutations (P=0.021) and SRSF2 mutations (P=0.011) were more common in patients with AMoC≥1×10(9)/L, whereas U2AF1 mutations (P<0.001) were more common in patients with AMoC<1×10(9)/L. There was no significant difference in the frequency of other gene mutations between the two groups. Conclusion: According to WHO 2022 classification, nearly 20% of CMML patients had AMoC<1×10(9)/L at the time of diagnosis, and MD-CMML and MP-CMML had different molecular features.
Humans ; Aged ; Middle Aged ; Leukemia, Myelomonocytic, Chronic/genetics* ; Prognosis ; Splicing Factor U2AF/genetics* ; Mutation ; Myelodysplastic Syndromes/genetics* ; Leukemia, Myeloid, Acute/genetics*

Objective: To evaluate the prognostic value of left ventricular ejection fraction (LVEF) reserve assessed by gated SPECT myocardial perfusion imaging (SPECT G-MPI) for major adverse cardiovascular event (MACE) in patients with coronary artery disease. Methods: This is a retrospective cohort study. From January 2017 to December 2019, patients with coronary artery disease and confirmed myocardial ischemia by stress and rest SPECT G-MPI, and underwent coronary angiography within 3 months were enrolled. The sum stress score (SSS) and sum resting score (SRS) were analyzed by the standard 17-segment model, and the sum difference score (SDS, SDS=SSS-SRS) was calculated. The LVEF at stress and rest were analyzed by 4DM software. The LVEF reserve (ΔLVEF) was calculated (ΔLVEF=stress LVEF-rest LVEF). The primary endpoint was MACE, which was obtained by reviewing the medical record system or by telephone follow-up once every twelve months. Patients were divided into MACE-free and MACE groups. Spearman correlation analysis was used to analyze the correlation between ΔLVEF and all MPI parameters. Cox regression analysis was used to analyze the independent factors of MACE, and the optimal SDS cutoff value for predicting MACE was determined by receiver operating characteristic curve (ROC). Kaplan-Meier survival curves were plotted to compare the difference in the incidence of MACE between different SDS groups and different ΔLVEF groups. Results: A total of 164 patients with coronary artery disease [120 male; age (58.6±10.7) years] were included. The average follow-up time was (26.5±10.4) months, and a total of 30 MACE were recorded during follow-up. Multivariate Cox regression analysis showed that SDS (HR=1.069, 95%CI: 1.005-1.137, P=0.035) and ΔLVEF (HR=0.935, 95%CI: 0.878-0.995, P=0.034) were independent predictors of MACE. According to ROC curve analysis, the optimal cut-off to predict MACE was a SDS of 5.5 with an area under the curve of 0.63 (P=0.022). Survival analysis showed that the incidence of MACE was significantly higher in the SDS≥5.5 group than in the SDS<5.5 group (27.6% vs. 13.2%, P=0.019), but the incidence of MACE was significantly lower in the ΔLVEF≥0 group than in theΔLVEF<0 group (11.0% vs. 25.6%, P=0.022). Conclusions: LVEF reserve (ΔLVEF) assessed by SPECT G-MPI serves as an independent protective factor for MACE, while SDS is an independent risk predictor in patients with coronary artery disease. SPECT G-MPI is valuable for risk stratification by assessing myocardial ischemia and LVEF.
Humans ; Male ; Middle Aged ; Aged ; Coronary Artery Disease/diagnostic imaging* ; Stroke Volume ; Myocardial Perfusion Imaging ; Retrospective Studies ; Ventricular Function, Left ; Myocardial Ischemia