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.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

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.

To determine the optimal cultivation duration and harvest period for cultivated Notopterygium incisum and promote its industrial development, this study established a characteristic chromatographic profile of cultivated N. incisum and employed chemometrics combined with entropy-weighted grey correlation analysis to assess differences in agronomic traits and quality indicators across different cultivation years and harvest periods. By comparing with reference substances, ten common peaks were identified, including chlorogenic acid, p-coumaric acid, ferulic acid, marmesinin, nodakenin, isochlorogenic acid B, notopterol, phenethyl ferulate, isoimperatorin, and falcarindiol. The similarity between the characteristic chromatographic profiles of N. incisum at different cultivation years and the reference profile was all above 0.932. Principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA) revealed that the quality of 1-to 3-year-old cultivated N. incisum was highly dispersed and unstable, whereas the quality of 4-year-old cultivated N. incisum remained relatively stable across different harvest periods. This suggests that the accumulation of relevant compounds in the medicinal material had reached a plateau, confirming that the optimal cultivation period for N. incisum is four years. Entropy-weighted grey correlation analysis indicated that the quality of 4-year-old cultivated N. incisum across different harvest periods ranked from highest to lowest as follows: November, December, October, August, July, and September, demonstrating that November is the optimal harvest time. The findings of this study establish the suitable cultivation duration and optimal harvest period for N. incisum, providing a scientific basis for cultivation guidance and quality standardization.
Chromatography, High Pressure Liquid/methods* ; Apiaceae/chemistry* ; Entropy ; Chemometrics/methods* ; Drugs, Chinese Herbal/chemistry* ; Principal Component Analysis ; Quality Control

As early mobilization of patients in the intensive care unit(ICU)is increasingly recognized as a key measure for improving patient prognosis and reducing complications,related research is increasing.However,conventional early mobilization methods are often limited by factors such as patient condition,nursing resources,and environmental factors,making it difficult to achieve optimal results.In recent years,virtual reality(VR)technology,owing to its unique immersion and interactive features,has emerged as a focus of research in the field of ICU patient rehabilitation.This review summarizes the advances in the application of VR technology in the early mobilization of ICU patients,focusing on its advantages over traditional methods,specific implementation approaches,clinical outcomes,and challenges encountered during application.By synthesizing existing evidence,this review aims to provide valuable references for clinical practice and to explore future directions for VR technology in ICU rehabilitation,with the goal of promoting its widespread application in the early mobilization of critically ill patients.

Objective To investigate the length of hospital stay,hospitalization expense and mortality attributable to the occurrence of carbapenem-resistant Enterobacterales(CRE)infection in patients in intensive care unit(ICU).Methods Patients admitted to the ICU in a tertiary first-class hospital from 2017 to 2022 were selected for the study.According to whether CRE infection occurred,patients were divided into infected group and non-infected group.Propensity score matching method was used to conduct a 1∶1 match between the infected group and non-infected group.Length of hospital stay,hospitalization expense and mortality of patients after matching were analyzed sta-tistically.A generalized linear model was established to recalculate the odds ratio(OR)of length of hospital stay,hospitalization expense and mortality of patients after matching.Results After propensity score matching,length of hospital stay of patients in the infected group extended by 10.56 days(P＜0.001),hospitalization expense in-creased by 36 021.02 Yuan(P＜0.001),and mortality increased by 6.70％(P=0.035).The results of the gene-ralized linear model indicated that OR for length of hospital stay,hospitalization expense,and mortality were 1.187(95％CI:1.013-1.393),1.134(95％CI:0.975-1.318),and 1.130(95％CI:1.049-1.218)respectively for CRE infected patients,compared with non-infected patients,except for hospitalization expense,length of hospital stay and mortality between two groups were statistically significant(both P＜0.05).Conclusion CRE infection in ICU patients will increase the length of hospital stay,economic burden,and mortality of patients.Measures should be taken to prevent and control CRE infection.

Aim To explore the potential targets and related signaling pathways of Agaricus blazei Murill (AbM ) extract in the treatment of chronic myeloid leukemia (CML) based on liquid chromatography mass spectrometry ( LC-MS ), network pharmacology, molecular docking, and were further verified by experiments in vitro. Methods The active components of AbM extract were retrieved from LC-MS, Swiss Target Prediction database was used to predict related targets, and CML disease target genes were obtained from Gen- eCards and DisGeNET databases. After screening the common targets of drug and CML, the protein-protein interaction network of the common targets was performed by STRING, and GO and KEGG enrichment a- nalysis were done by DAVID database. Cytoscape software was used to construct the network of target protein. Molecular docking was carried out by DockThor, and the Pymol software was used to make a visual picture. The inhibitory effect of AbM extract on leukemia cells K562 was determined by CCK-8 experiment, and the effect of AbM extract on the expression and phosphorylation level of related proteins was verified by Western blot. Results The prediction results showed that 126 active components of AbM extract, and 172 common targets were collected. KEGG pathway analysis results showed that PI3K/Akt/mTOR signaling pathway might play an important role in the treatment of CML disease. The IC