BACKGROUND:Transferrin (Tf) is one suitable ligand to be conjugated to drug delivery systems to achieve site-specific targeting and desired therapeutic effect, due to its specific binding to transferrin receptors (TfR), and high expression on the surface of tumor cells. Contrast agents are also modified with Tf to achieve specific tumor imaging. OBJECTIVE:To prepare Tf-labeled magnetoliposomes (MLs), and characterize their utility as TfR targeted MR specific contrast agent in vitro. METHODS:MLs and Tf-MLs were prepared by lipid film hydration method and covalent coupling method, respectively. Tf-MLs were characterized by their mean size, zeta potential, polyindex, r2 relaxivity, Tf-binding efficacy and cytotoxicity.In vitro MRI contrasting properties of the suspended nanoparticles incubated with HepG2 cells were determined. RESULTS AND CONCLUSION:The mean diameter, polydisperisity index, zeta potential and r2 relexivity of Tf-ML were 95.1 nm, 0.21,-1.25 mv and 94.62 mmol-1/s, respectively. The coupling efficiency was calculated and the values obtained were 59.4 μg Tf/μmol phospholipid corresponding to about 27 molecules of Tf-MLs. After a 2-hour incubation with rhodamine-labeled Tf-MLs, rhodamine fluorescence was detected intensively in the plasma membrane and the cytoplasm of the TfR-overexpressing HepG2 cells. In contrast, Tf-ML showed little binding in MCF-7 cells that had low TfR level. HepG2 cels incubated with Tf-ML showed much higher intracellualar iron density than incubated with non-targeted MLs.In vitro MR T2WI of cells demonstrated the centrifuge tube containing HepG2 cells incubated with Tf-MLs produced a lower visible signal intensity than that treated with non-targeted MLs. Tf-MLs showed their potentials such as high r2 relaxivity, specific binding ability characteristics. These results suggest the availability of Tf-MLs to serve as a targeted contrast agent.

OBJECTIVETo observe the impacts on pain matrix (PM) brain area in the patients of cervical spondylosis of neck type treated with acupuncture at single point and the multiple points.

METHODSForty-nine patients of cervical spondylosis of neck type were randomized into a single-point group (25 cases) and a multiple-point group (24 cases), and treated with acupuncture at Bailao (EX-HN 15) singly or Bailao (EX-HN 15) and Hegu (LI 4) in combination correspondingly. At the same time, 19 healthy people were selected as a control group. The resting state functional magnetic resonance imaging (fMRI) was conducted in each group before and after treatment. The changes in the regional homogeneity (ReHo) of brain area PM were analyzed in terms of the different therapeutic programs. The relevant analysis was on the scores of the Northwick Park neck pain questionnaire (NPQ) and short form 36 questionnaire (SF-36) for life quality.

RESULTSCompared with the control group, ReHo value was increased in supplementary motor area (SMA) of PM in the patients, of cervical spondylosis of neck type. In the single-point group, after treatment, ReHo value was reduced in the bilateral medial superior frontal gyri of patients. In the multiple-point group, ReHo values were reduced in the left medial superior frontal gyrus and right SMA in PM area after treatment. In the single-point group, ReHo value in each brain area of PM was not significantly correlated with NPQ and SF-36 scores. In the multiple-point group, the changes of ReHo value in superior frontal gyrus were positively correlated with those of NPQ scores.

CONCLUSIONConsidering the clinical efficacy of acupunctrue for cervical spondylosis of neck type, the overall result in the multiple-point group is better than that in the single-point group. It is deduced that the advantages of the therapeutic program in the multiple-point group is relevant with the cooperative integration of the stimulation at multiple points in cerebral analgesic center.

Acupuncture Points ; Acupuncture Therapy ; Adult ; Brain ; diagnostic imaging ; Female ; Humans ; Magnetic Resonance Imaging ; Male ; Neck Pain ; diagnostic imaging ; therapy ; Radiography ; Spondylosis ; diagnostic imaging ; therapy ; Treatment Outcome ; Young Adult

Objective:To explore the application effect of patient mutual assistance model guided by the hierarchy of needs theory in patients with acute myocardial infarction.Methods:Using the convenient sampling method, 40 patients with acute myocardial infarction in the Fourth People's Hospital of Haikou from September 2018 to October 2019 were selected as the control group and 40 patients with acute myocardial infarction from November 2019 to January 2021 were selected as the intervention group. The control group implemented the conventional nursing model, and the intervention group implemented the patient mutual assistance model guided by the hierarchy of needs theory on this basis. Perceived Stress Scale (PSS) , SDS and Herth Hope Scale (HHI) were used to evaluate the effect of intervention.Results:After the intervention, the total scores of PSS of patients in the two groups were lower than those before the intervention, and the difference was statistically significant ( P<0.01) . And the total PSS score of the intervention group was lower than that of the control group, and the difference was statistically significant ( P<0.01) . After the intervention, the total SDS score of patients of the two groups was lower than that before the intervention, and the difference was statistically significant ( P<0.01) . And the total SDS score of the intervention group was lower than that of the control group, and the difference was statistically significant ( P<0.01) . After intervention, the scores of HHI dimensions and total scores in two groups were higher than before intervention, and the differences were statistically significant ( P<0.01) . The scores of HHI dimensions and the total score of the intervention group were higher than those in the control group, and the differences were statistically significant ( P<0.01) . Conclusions:The patient mutual assistance model guided by the hierarchy of needs theory can effectively reduce the self-perceived pressure of patients with acute myocardial infarction after PCI, improve their depression and increase the level of hope.

Objective:To investigate the feasibility of a three-dimensional no new U-Net (3D nnU-Net) deep learning (DL) network for the automatic segmentation of colorectal cancer (CRC) based on abdominal CT images.Methods:This was a cross-sectional study. From January 2018 to May 2023, a total of 2180 primary CRC patients, confirmed by pathology at the Guangdong Provincial Hospital of Traditional Chinese Medicine (center 1, n=777), Nanfang Hospital, Southern Medical University (center 2, n=732), and Sun Yat-sen Memorial Hospital (center 3, n=671), were enrolled in this retrospective study. The baseline abdominal CT examination of each patient was conducted using CT equipment from 7 different models across 4 vendors, at the 3 centers, encompassing both the arterial phase (AP) and venous phase (VP). Two radiologists manually delineated the volume of interest to circumscribe the entire tumors in dual-enhanced phase CT images. The CT data of CRC patients from center 1 and center 3 were merged and divided into a training set ( n=1 159) and a validation set ( n=289) using a weighted random method with a ratio of 4∶1. The patients from center 2 were used as an independent external test set ( n=732). The 3D nnU-Net segmentation model was trained and tested. Using manually annotated label data as the benchmark, segmentation performance of the model was evaluated based on different phases and tumor locations. The segmentation coverage rate (SCR), Dice similarity coefficient (DSC), recall (REC), precision (PRE), F1-score, and 95% Hausdorff distance (HD 95) were calculated. The mean manual segmentation time and the mean automatic time were compared using independent samples t-test. Results:In the independent external test set, the performance of the 3D nnU-Net model based on the AP CT images was superior to that based on the VP CT images. On the AP images, the SCR, DSC, REC, PRE, F1-score, and HD 95 were 0.865, 0.714, 0.716, 0.736, 0.714, and 27.228, respectively; on the VP images, they were 0.834, 0.679, 0.710, 0.675, 0.679, and 29.358, respectively. The model achieved the best performance on right-sided colon cancer, with SCR, DSC, REC, PRE, F1-score, and HD95 on the AP CT images at 0.901, 0.775, 0.780, 0.787, 0.775, and 21.793, respectively. Next were left-sided colon cancer and rectal cancer, while the segmentation performance for transverse colon cancer was the worst (SCR, DSC, REC, PRE, F1-score, and HD 95 were 0.731, 0.631, 0.641, 0.630, 0.631 and 38.721, respectively). The automatic segmentation time on a single phase was (1.0±0.3) min, while the manual segmentation time was (17.5±6.0) min ( t=128.24, P<0.001). Conclusions:After training and validating on a dataset from multiple centers with various CT scanner vendors, the 3D nnU-Net DL model demonstrates the capability to automatically segment CRC based on abdominal CT images, while also showcasing commendable robustness and generalization ability.

Purpose To explore the value of dual-layer spectral detector CT(DLSCT)in evaluating preoperative tumor staging in rectal adenocarcinoma(RA).Materials and Methods A total of 78 patients with pathologically confirmed RA in Guangdong Provincial Hospital of Chinese Medicine from May 2021 to March 2022 were involved in this retrospective study.All the patients underwent plain and dual-phase contrast-enhanced scans by DLSCT within one week before surgery.Taking pathological results as the golden standard,the accuracy rates of tumor staging were calculated and compared between the multiple-parameter maps derived from DLSCT and 120 kVp polyenergetic image.The effective atomic number(Z-eff)from plain scan,iodine concentration(IC)from arterial phase(AP)and venous phase(VP)were measured.The normalized iodine concentration(NIC)in AP and VP were calculated.The differences of Z-eff,NICAP and NICVP were compared among the pT1-2,pT3 and pT4 groups.The correlation between the pT stages and above values was assessed and the diagnostic efficiencies were analyzed.Results The overall accuracy rate(88.46%vs.67.95%;χ2=9.628,P=0.002),the pT1-2 staging accuracy rate(80.00%vs.40.00%;χ2=6.667,P=0.01),and the pT3 staging accuracy rate(88.10%vs.69.05%;χ2=4.525,P=0.033)of multiple-parameter maps derived from DLSCT were significantly higher than those of 120 kVp polyenergetic image,respectively.The Z-eff,NICAP and NICVP were significantly different among pT stage groups(F=6.456,11.029,12.698,all P<0.05)and exhibited a positive correlation with pT stages(r=0.371,0.367,0.363,all P<0.01).The areas under the curve of Z-eff,NICAP and NICVP to assess pT3-4 staging RA were 0.77,0.71 and 0.74,respectively.Conclusion The multiple-parameter maps derived from DLSCT can significantly improve the diagnostic accuracy of preoperative tumor staging of RA.Z-eff from plain scan and NIC from dual-phase helps differentiate pT1-2 from pT3-4 staging RA.

Objective:To explore the value of dual-layer detector spectral CT quantitative parameters in evaluating the treatment response of neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).Methods:The study was a cross-sectional study. From May 2021 to March 2023, a total of 52 patients with LARC who received complete nCRT and were pathologically confirmed rectal adenocarcinoma at the Guangdong Province Hospital of Traditional Chinese Medicine were retrospectively enrolled. Each patient underwent spectral CT examination before and after nCRT, including plain scan, arterial phase (AP), and venous phase (VP) scans. According to the tumor regression grade, the patients were divided into the good response ( n=20) and the poor response group ( n=32). Measurements of the primary tumor′s spectral CT parameters, including effective atomic number (Z eff) at plain scan, iodine concentration (IC), CT values of 40 keV and 100 keV virtual monochromatic image (VMI) at dual-enhanced phases, were taken before and after nCRT. Additionally, the normalized iodine concentration (NIC), spectral curve slope (λHU), and the change rate of the above parameters before and after nCRT were calculated. The independent sample t-test or Mann-Whitney U test was used to compare the differences between the two groups. The receiver operating characteristic (ROC) curve was used to assess the efficacy of various metrics in evaluating the tumor treatment response of nCRT. A binary logistic regression analysis of combined parameter results was performed for the parameters with the areas under curve (AUC)>0.75, and the AUC of the combined parameter was evaluated. Results:There were significant differences in NIC AP and λHU VP before nCRT, NIC VP and λHU VP after nCRT, and the change rates of Z eff, NIC AP, NIC VP and λHU AP between the good response group and the poor response group ( P<0.05). The remaining parameters showed no statistically significant difference ( P>0.05). The ROC curve results showed that the AUCs of the above 8 parameters for evaluating tumor treatment response of nCRT were 0.702, 0.655, 0.695, 0.769, 0.738, 0.807, 0.791, and 0.677, respectively. The AUC of the combined model of the three parameters with AUC>0.75 (λHU VP after nCRT, the change rate of NIC AP and NIC VP) was 0.869, with 80.0% sensitivity and 84.4% specificity. Conclusion:The quantitative parameters derived from spectral CT may provide new markers for evaluating the response to nCRT treatment in patients with LARC. The multi-parameter combined model can improve diagnostic efficacy.