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.

Objective:To construct 68Ga-1, 4, 7-trizacyclononane-1, 4, 7-triacetic acid (NOTA)-CD44 as a novel atherosclerosis tracer targeting hyaluronic acid (HA), and evaluate its biological property and molecular imaging features. Methods:Low molecular weight (LMW) recombinant human CD44 protein was selected, and the C-terminal of the protein was modified by sulfonation and coupled to the bifunctional ligand NOTA to synthesize a novel molecular probe 68Ga-NOTA-CD44 targeting HA. The biological properties of the probe, such as labeling rate and in vitro stability, were studied. Three atherosclerotic plaque model mice and three normal C57BL/6 mice were studied by 68Ga-NOTA-CD44 microPET/CT imaging and pathological examination. Results:68Ga-NOTA-CD44 tracer was synthesized and purified with the radiochemical purity above 99%, and the specific activity was up to 62.22 MBq/nmol. lts stability was good in PBS, and the radiochemical purity was over 90% after incubation for 3 h. After intravenous injection, the probe was metabolized mainly by the kidneys, and its metabolic level decreased successively in the liver, lungs and blood. MicroPET/CT imaging results of atherosclerotic model mice suggested that the uptake in the plaque of abdominal aorta was higher at 60 min after injection, with SUV max and target/background ratio (TBR) max of 1.14±0.02 and 4.95±0.93, and the probe had certain atherosclerotic plaque eroded targeting, which was consistent with the pathological result. Conclusions:As a novel probe, 68Ga-NOTA-CD44 is simple to prepare and has a high labeling rate. It has good physicochemical properties and in vivo biological properties, and can display atherosclerotic eroded plaques sensitively. 68Ga-NOTA-CD44 has a promising prospect to be a new molecular probe for early noninvasive recognition of atherosclerotic eroded plaques.

ObjectiveBased on the network pharmacology system and quantitative spectroscopy of traditional Chinese medicine（TCM） compounds， a topological network analysis method with equilibrium constant as the core was established to further explore the interaction between allergenic components and their network targets in Shuanghuanglian injection（SHLI）， in order to provide new ideas and experimental basis for identifying and screening potential allergens of SHLI. MethodAfter one week of adaptive feeding， 72 SPF-grade SD male rats were randomly divided into blank group， SHLI standard group， Lonicerae Japonicae Flos（LJF） group， Scutellariae Radix（SR） group， Forsythiae Fructus（FF） group， and 7 groups of SHLI matching groups（groups 1-7）， with 6 rats in each group. Rats in each group were administered the drug intravenously and blood samples were taken after steady state， high performance liquid chromatography（HPLC） characterization profiles of the testing drugs and plasma components in each group were established， and the peak area changes of the drugs and plasma components in each group were calculated after the component groups were classified. Enzyme-linked immunosorbent assay（ELISA） was used to determine the changes of immunoglobulin E（IgE）， histamine（HIS）， tryptase（TPS）， total complement（CH50） and terminal complement complex（C5b-9） in animal blood samples. MATLAB R2020b v9.9.0 software was used to calculate the network balance constants of the component groups with the targets， and the eigenvalues of the matrices composed of network equilibrium constants were calculated and ranked according to their values. ResultELISA results showed that， compared with the blank group， groups 1-3 could significantly increase the IgE level， groups 1-2， groups 4-6 and SHLI standard group could significantly increase the HIS level， group 4 could significantly increase the CH50 level， groups 1， 3-4， LJF group and FF group could significantly increase the TPS level， SR group could significantly increase the C5b-9 level， and the differences were all statistically significant（P<0.05）. According to the retention time of chromatographic peaks， it was classified into 6 component groups from C1 to C6 by HPLC. The order of the network balance constants of each component group was C6>C4>C1>C5>C3>C2， indicating that C6 had the greatest effect on the allergic reaction， and was most likely to be the allergen. The sequence of eigenvalues was C2>C5b-9>C3>C1>CH50>C6>C5>IgE>TPS>C4>HIS， indicating that component group C2 had the greatest contribution to the whole network. ConclusionBased on the correlation analysis of SHLI component group and allergy-like target network， this study clarified that component group C6 may be a potential allergen in SHLI， and the component group C2 may be a key node in the mechanism of drug action， which can provide new strategies and methods for the screening of allergens in TCM injections.

Objective To develop and validate a fatigue risk nomogram model in Chronic Obstructive Pulmonary Disease(COPD)patients.Methods A prospective study design was adopted,and 430 COPD patients recruited from a tertiary A hospital in Huzhou City from January to December 2022 were conveniently selected for model construction,and 129 patients were recruited from the same hospital from January to June 2023 for external validation of the model.The general information questionnaire,Pittsburgh Sleep Quality Index,2-item Generalized Anxiety Disorder Scale,2-item Patient Health Questionnaire,modified British Medical Research Council Dyspnea Index,International Physical Activity Questionnaire,and Fatigue Severity Scale were used for questionnaire survey.The risk prediction model and nomograms model were constructed using Logistic regression analysis and R 4.3.2 software,and the area under the receiver operating characteristic(ROC)curve was used to test the prediction effect of the model.Results Univariate and binary logistic regression analysis results showed that age(OR=1.095),gender(OR=2.077),dyspnea(OR=3.309),sleep quality(OR=1.979),anemia(OR=3.289),the number of acute exacerbation(OR=2.991)were independent influencing factors for fatigue in COPD patients.The internal evaluation and external validation results of the model showed that the areas under the curve are 0.912 and 0.844 respectively,and the Hosmer-Lemeshow goodness of fit test P values were 0.806 and 0.526 respectively.The average absolute errors were 0.013 and 0.019 respectively.Conclusion The COPD fatigue risk prediction model constructed in this study has good prediction effect.The visual nomogram is intuitive,convenient and easy to operate.It can provide a tool for early screening of fatigue in COPD patients.

Anti-tumor traditional Chinese medicine has a long history of clinic application, in which the star molecules have always been the hotspot of modern drug research, but they are limited by the solubility, stability, targeting, bioactivity or toxicity of the monomer components of traditional Chinese medicine anti-tumor star molecules and other pharmacokinetic problems, which hinders the traditional Chinese medicine anti-tumor star molecules for further clinical translation and application. Currently, the nanosystems prepared by supramolecular technologies such as molecular self-assembly and nanomaterial encapsulation have broader application prospects in improving the anti-tumor effect of active components of traditional Chinese medicine, which has attracted extensive attention from scholars at home and abroad. In this paper, we systematically review the research progress in preparation of supramolecular nano-systems from anti-tumor star molecule of traditional Chinese medicine, and summarize the two major categories and ten small classes of carrier-free and carrier-based supramolecular nanosystems and their research cases, and the future development direction is put forward. The purpose of this paper is to provide reference for the research and clinical transformation of using supramolecular technology to improve the clinical application of anti-tumor star molecule of traditional Chinese medicine.

Lipopolysaccharides (LPS) are major outer membrane components of Gram-negative bacteria. Unlike most Gram-negative bacteria, Acinetobacter baumannii can still survive and acquire polymyxin resistance after complete loss of LPS. Previous studies of LPS-deficient Acinetobacter baumannii mostly focused on LPS-deficient strains induced by polymyxin, whose background was complex and unstable. To investigate LPS loss-mediated polymyxin resistant-Acinetobacter baumannii, this study constructed a stable and clear background LPS-deficient strain by knocking out lpxC gene in Acinetobacter baumannii ATCC 19606 with CIRSPR/Cas9, and then studied the phenotypic changes of the lpxC-deficient strain including morphology, growth rate, antibiotic susceptibility, virulence, membrane permeability, and membrane potential. Animal experiments were approved by the Animal Care and Welfare Committee Institute of Medicinal Biotechnology, CAMS and PUMC (approval number: IMB-20240119D₉). The results indicated that the lpxC gene of Acinetobacter baumannii ATCC 19606 was successfully knocked out. After losing the lpxC, the strain underwent the morphological change from rod-shaped to spherical. Furthermore, it leads to reduced growth rate, enhanced membrane permeability, decreased membrane potential, lower virulence, and increased antibiotic susceptibility to β-lactams, quinolones, aminoglycosides, macrolides, glycopeptides. The lpxC deletion results in significant changes in membrane homeostasis and adaptability of Acinetobacter baumannii. Understanding the phenotypic changes of colistin-resistant Acinetobacter baumannii mediated by LPS loss is useful for exploring the resistance mechanism of Acinetobacter baumannii and developing new therapeutic strategies.