Objective:To explore the effect of high glucose on formation of endogenetic toxins and expression of intercellular cell adhesion molecule-1(ICAM-1) and vascular cell adhesion molecule-1(VCAM-1) of human brain microvascular endothelial cells.Methods:Cultured HBMEC was used as target cells,anhydrous glucose was added to the cell medium to prepare the injury model of human endothelial cell.Methyl thiazolyl tetrazolium method was used to examine the cell activity in a high glucose environment.Immunocytochemistry method was used to detect the expression of ICAM-1 and VCAM-1 of HBMEC.Results:The expressions of ICAM-1 and VCAM-1of HBMEC were enhanced by high glucose after pretreating HBMEC for 24,48 and 72h(P

Objective:To investigate the value of ADC map-based radiomics model for identifying the ischemic penumbra (IP) in acute ischemic stroke (AIS).Methods:From January 2014 to October 2019, data of 241 patients with AIS involving the anterior cerebral circulation within 24 h after stroke onset in the First People′s Hospital of Nantong City was analyzed retrospectively. All patients received routine T 1WI, T 2WI, DWI and dynamic susceptibility contrast-perfusion weighted imaging (DSC-PWI). Considering the PWI-DWI mismatch model as the gold standard for determining IP, patients were divided into the PWI-DWI mismatch (84 cases) and PWI-DWI non-mismatch (157 cases) groups. The ROI of the low signal area and the surrounding area was drawn by two doctors at the maximum level of the lesions on the ADC maps. Then the images were imported into AK analysis software to extract the features. Firstly, the inter-class correlation coefficient was used to screen out the features with high consistency, then the maximum relevance and minimum redundancy (mRMR) and least absolute shrinkage and selection operator (Lasso) regression analysis were used to screen the features. The selected features were used to construct their own radiomics model. ROC curve was used to evaluate the performance of the models, and Delong test was used to compare the area under the curve (AUC) of the two models. Results:After screening, 12 features (LongRunLowGreyLevelEmphasis_angle135_offset7, LongRunLowGreyLevelEmphasis_AllDirection_offset7, GLCMEntropy_AllDirection_offset4_SD, GLCMEnergy_angle45_offset1, ColGE_W11B25_16, ColGE_W11B25_24, HaraEntropy, SurfaceVolumeRatio, Sphericity, Quantile0.025, uniformity and Percentile75) were used to construct the radiomics model based on the low signal area of the ADC map. The area under the ROC curve in the training set was 0.900, and the sensitivity, specificity and accuracy were 84.5%, 81.4% and 83.4%, respectively. The area under the ROC curve in the validation set was 0.870, and the sensitivity, specificity and accuracy were 80.9%, 84.0% and 81.9%, respectively. Eleven features(RunLengthNonuniformity_AllDirection_offset1_SD, ShortRunLowGreyLevelEmphasis_angle45_offset1, HighGreyLevelRunEmphasis_AllDirection_offset1_SD, ShortRunLowGreyLevelEmphasis_AllDirection_offset7, HaralickCorrelation_AllDirection_offset4_SD, ClusterShade_angle45_offset7, InverseDifferenceMoment_AllDirection_offset7_SD, ColGE_W3B20_0, sumAverage, SurfaceVolumeRatio and VolumeMM) were used to construct the radiomics model based on the surrounding area of ADC map. The area under ROC curve in training set was 0.820, the sensitivity, specificity and accuracy were 80.5%, 80.2% and 80.4%, respectively; the area under ROC curve in validation set was 0.800, the sensitivity, specificity and accuracy were 78.7%, 80.0% and 79.2%, respectively. The AUC of the radiomics model based on the low signal area of the ADC map was larger than that based on the surrounding area of the ADC map (training set: Z=3.017, P=0.003; validation set: Z=0.604, P=0.002). Conclusion:The radiomics model based on ADC map has a good diagnostic efficacyin identifying the IP.

Objective To explore the relevance between gait speed and muscle strength of lower extremities, or several kinds of physical functional tests. Methods 341 community-dwelling individuals (160 males, 181 females) aged 65-94 years were selected. They were divided into suspected sarcopenia group (n=137) and normal group (n=204) by their gait speed less or more than 0.8 m/s. It was compared between both groups with the basic physical characteristics, strength of iliopsoas, quadriceps, hamstrings and tibialis anterior, and the scores of One Leg Standing Test, Berg Balance Scale, Functional Gait Assessment, Functional Stretch Test and Timed Up and Go Test. Results The subjects were older in the suspected sarcopenia group than in the normal group. The difference of body weight, height were not statistically significant between groups. The strength of the muscles in bilateral lower limbs was not significantly different between both groups (P>0.05), while the gait speed positively correlated with the strength of iliopsoas, quadriceps and hamstrings (r=0.121-0.227, P<0.05), but not with the tibialis anterior (P>0.05). Gait speed positively correlated with the scores of One Leg Standing Test, Berg Balance Scale, Functional Gait Assessment, Functional Stretch Test (P<0.05), and negatively correlated with the score of Timed Up and Go Test (r=-0.502, P<0.001). The scores of all the tests were significantly different between 2 groups (P<0.05), except that of Functional Stretch Test (P=0.28). Conclusion Sarcopenia diagnosis is not only depended on the strength of muscle of lower extremity, but also their functions.

Purpose The clinical and dual-layer detector spectral CT(DLCT)features of epidermal growth factor receptor(EGFR)mutation and anaplastic lymphoma kinase(ALK)rearrangement of lung adenocarcinoma were studied by DLCT multi-parameter imaging to explore a non-invasive prediction method for clinical diagnosis of lung adenocarcinoma gene expression.Materials and Methods A total of 98 cases of lung adenocarcinoma diagnosed by pathology in Gansu Provincial Hospital were prospectively collected from August 2020 to March 2022.Clinical parameters(gender,age,lesion morphology,number,mediastinal lymph node metastasis,EGFR and ALK mutations status)and DLCT parameters including slope of the spectrum curve of the arteriovenous phase(λHUA,λHUv),the standard iodine concentration of the arteriovenous phase(NICA,NICv),the 40 keV single-energy CT value of the arteriovenous phase(CTA 40 keV,CTv 40 keV),the active atomic number of the arteriovenous phases were collected,respectively.According to the expression of EGFR and ALK,all patients were divided into three groups:EGFR mutant group[EGFR(+)],ALK rearrangement group[ALK(+)],EGFR/ALK both negative group[EGFR/ALK(-)].Clinical and DLCT parameters of each group were analyzed.Results There were statistical difference in gender between the EGFR(+)group and EGFR/ALK(-)group(x2=11.010,P＜0.05).There were statistical differences in lesion morphology among the three groups(x2=12.858,P＜0.05).The value of CTv 40 keV in the EGFR(+)group was significantly higher than that in EGFR/ALK(-)group(t=1.997,P＜0.05),and the NICv in the ALK(+)group was significantly lower than that in EGFR/ALK(-)group(t=2.155,P＜0.05).The λHUv,NICv,CTv 40 keV of EGFR(+)group were significantly higher than those of ALK(+)group(t=2.613,3.149,3.218,all P＜0.05).The sensitivity and specifiicity to identify EGFR(+)and EGFR/ALK(-)adenocarcinoma were 62.7％and 70.0％,the area under curve(AUC)was 0.634(95％CI 0.516-0.756)when the CTv 40 keV value was 141.070 Hu.The sensitivity and specificity to identify ALK(+)and EGFR/ALK(-)adenocarcinoma were 76.7％and 64.2％,the AUC was 0.706(95％CI 0.536-0.853)when NICv value was 0.287.The sensitivity to identify EGFR(+)and ALK(+)adenocarcinoma were 70.6％,64.7％,72.5％and the specificity was 76.5％,76.5％,82.4％,respectively,the AUC was 0.734(95％CI 0.606-0.829),0.751(95％CI 0.610-0.832),0.773(95％CI 0.649-0.861)when the values of λHUv,NICv and CTv 40 keV were 1.335,0.320 and 132.350,respectively.Delong test showed that the AUC of CTv 40 keV and λHUv was statistically different(Z=2.327,P＜0.05),and the AUC of CTv 40 keV was 0.773.Conclusion The gender,lesion morphology and DLCT parameters(λHUv,CTv 40 keV,NICv)of lung adenocarcinoma have certain predictive value for EGFR and ALK genetic expression,which can help clinical judgment of lung adenocarcinoma gene mutation pattern.

Objective:To investigate the effect of sequential suture and adhesion on craniomaxillofacial skin contusion and laceration.Methods:A total of 189 patients with craniomaxillofacial skin contusion and laceration (CMFSCL) were randomly divided into three groups: 66 cases in SSA group, 63 cases in CS group and 60 cases in TS group. Operation time, visual analogue scale (VAS), Vancouver scar scale (VSS) and adverse reactions incidence were compared and analyzed between the three groups. Effect and satisfactory scale were evaluated.Results:Operation time in SSA group (10.67±1.26) min was significantly less than that in CS (18.91±1.38) min and TS group (17.96±1.43) min ( P<0.05). VAS in SSA group 24 h post-operation (3.11±1.01) was significantly lower than that in CS and TS group ( P<0.05). VSS in SSA group 6 months post-operation (1.18±0.21) was significantly lower than that in CS (3.78±1.01) ( P<0.05) and TS group (5.98±1.06) ( P<0.01). Total effective rate of SSA group (96.5%) was significantly higher than that in CS (85.7%) ( P<0.05) and TS group (56.1%) ( P<0.01); total effective rate in CS group was significantly higher than that in TS group ( P<0.05). Infection and dehiscence rates in SSA group were lower than those in CS and TS group ( P<0.01). Satisfactory rate of SSA group (99%) was significantly higher than that of CS (89.1%) and TS group (71.3%) ( P<0.05); the satisfactory rate of CS group was significantly higher than that of TS group ( P<0.05). Conclusions:Sequential suture and adhesion technique is simple and effective for craniomaxillofacial skin contusion and laceration, which is worthy of clinical promotion.

Objective:To construct an prediction model based on magnetic resonance imaging (MRI) machine learning algorithm and radiomics and investigate its application value in predicting lymphovascular invasion (LVI) status of rectal cancer without lymph node metastasis.Methods:The retrospective cohort study was conducted. The clinicopathological data of 204 rectal cancer patients without lymph node metastasis who were admitted to Gansu Provincial Hospital from February 2016 to January 2024 were collected. There were 123 males and 81 females, aged (61±7)years. All 204 patients were randomly divided into the training dataset of 163 cases and the testing dataset of 41 cases by a ratio of 8∶2 using the electronic computer randomization method. The training dataset was used to construct the prediction model, and the testing dataset was used to validate the prediction model. The clinical prediction model, radiomics model and joint prediction model were constructed based on the selected clinical and/or imaging features. Measurement data with normal distribution were represented as Mean± SD. Count data were described as absolute numbers, and the chi-square test or Fisher exact probability were used for comparison between the groups. Comparison of ordinal data was conducted using the nonparameter rank sum test. The inter-class correlation coefficient (ICC) was used to evaluate the consistency of the radiomics features of the two doctors, and ICC >0.80 was good consistency. Univariate analysis was conducted by corres-ponding statistic methods. Multivariate analysis was conducted by Logistic stepwise regression model. The receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC), Delong test, decision curve and clinical impact curve were used to evaluate the diagnostic efficiency and clinical utility of the model. Result:(1) Analysis of factors affecting LVI status of patients. Of the 204 rectal cancer patients without lymph node metastasis, there were 71 cases with positive of LVI and 133 cases with negative of LVI. Results of multivariate analysis showed that gender, platelet (PLT) count and carcinoembryonic antigen (CEA) were independent factors affecting LVI status of rectal cancer without lymph node metastasis in training dataset [ odds ratio=2.405, 25.062, 2.528, 95% confidence interval ( CI) as 1.093-5.291, 2.748-228.604, 1.181-5.410, P<0.05]. (2) Construction of clinical prediction model. The clinical prediction model was conducted based on the results of multivariate analysis including gender, PLT count and CEA. Results of ROC curve showed that the AUC, accuracy, sensitivity and specificity of clinical prediction model were 0.721 (95% CI as 0.637-0.805), 0.675, 0.632 and 0.698 for the training dataset, and 0.795 (95% CI as 0.644-0.946), 0.805, 1.000 and 0.429 for the testing dataset. Results of Delong test showed that there was no significant difference in the AUC of clinical prediction model between the training dataset and the testing dataset ( Z=-0.836, P>0.05). (3) Construction of radiomics model. A total of 851 radiomics features were extracted from 204 patients, and seven machine learning algorithms, including logistic regression, support vector machine, Gaussian process, logistic regression-lasso algorithm, linear discriminant analysis, naive Bayes and automatic encoder, were used to construct the prediction model. Eight radiomics features were finally selected from the optimal Gaussian process learning algorithm to construct a radiomics prediction model. Results of ROC curve showed that the AUC, accuracy, sensitivity and specificity of radiomics prediction model were 0.857 (95% CI as 0.800-0.914), 0.748, 0.947 and 0.642 for the training dataset, and 0.725 (95% CI as 0.571-0.878), 0.634, 1.000 and 0.444 for the testing dataset. Results of Delong test showed that there was no significant difference in the AUC of radiomics prediction model between the training dataset and the testing dataset ( Z=1.578, P>0.05). (4) Construction of joint prediction model. The joint prediction model was constructed based on the results of multivariate analysis and the radiomics features. Results of ROC curve showed that the AUC, accuracy, sensitivity and specificity of radiomics prediction model were 0.885 (95% CI as 0.832-0.938), 0.791, 0.912 and 0.726 for the training dataset, and 0.857 (95% CI as 0.731-0.984), 0.854, 0.714 and 0.926 for the testing dataset. Results of Delong test showed that there was no significant difference in the AUC of joint prediction model between the training dataset and the testing dataset ( Z=0.395, P>0.05). (5) Performance comparison of three prediction models. Results of the Hosmer-Lemeshow goodness-of-fit test showed that all of the clinical prediction model, radiomics prodiction model and joint prediction model having good fitting degree ( χ2=1.464, 12.763, 10.828, P>0.05). Results of Delong test showed that there was no signifi-cant difference in the AUC between the clinical prediction model and the joint prediction model or the radiomics model ( Z=1.146, 0.658, P>0.05), and there was a significant difference in the AUC between the joint prediction model and the radiomics model ( Z=2.001, P<0.05). Results of calibra-tion curve showed a good performance in the joint prediction model. Results of decision curve and clinical impact curve showed that the performance of joint prediction model in predicting LVI status of rectal cancer without lymph node metastasis was superior to the clinical prediction model and the radiomics model. Conclusions:The clinical prediction model is constructed based on gender, PLT count and CEA. The radiomics predictive model is constructed based on 8 selected radiomics features. The joint prediction model is constructed based on the clinical prediction model and the radiomics predictive model. All of the three models can predict the LVI status of rectal cancer with-out lymph node metastasis, and the joint prediction model has a superior predictive performance.

With the progress of targeted therapy and immunotherapy for lung cancer, the clinical demand for lung biopsy is increasing. An ideal biopsy specimen can be used not only for histopathological diagnosis, but also for biomarker detection. The ideal biopsy specimen should meet two requirements, including more than 60 mm2 of tumor tissue and containing more than 20% of tumor cells. In order to obtain ideal lung cancer biopsy specimens, advanced imaging techniques are needed to help. In this article, we reviewed the requirements for biopsy specimens based on biomarker detection, as well as the current status and research progress of using imaging techniques for preoperative planning and intraoperative real time guidance of lung cancer biopsy.
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Humans ; Lung Neoplasms/diagnostic imaging* ; Biopsy ; Biomarkers ; Immunotherapy

Objective To investigate the effects of platelet-rich plasma-derived exosomes(PRP-Exos)on the proliferation and migration of tendon stem/progenitor cell(TSPC).Methods PRP-Exos were extracted through the combination of polymer-based precipitation and ultracentrifugation.The morphology,concentration,and particle size of PRP-Exos were identified by transmission electron microscopy and nanoparticle tracking analysis.The expression levels of surface marker proteins on PRP-Exos and platelet membrane glycoproteins were deter-mined by Western blot analysis.Rat TSPC was extracted and cultured,and the expression of surface marker mol-ecules on TSPC was detected using flow cytometry and immunofluorescence staining.The proliferation of TSPC in-fluenced by PRP-Exos was evaluated using CCK-8 assay and EdU assay.The effect of PRP-Exos on the migration of TSPC was evaluated by cell scratch assay and Transwell assay.Results The extracted PRP-Exos exhibit typi-cal saucer-like structures,with a concentration of 4.9 ×1011 particles/mL,an average particle size of(132.2±56.8)nm,and surface expression of CD9,CD63 and CD41.The extracted TSPC expressed the CD44 pro-tein.PRP-Exos can be taken up by TSPC,and after co-cultured for 48 h,concentrations of 50 and 100 μg/mL of PRP-Exos significantly promoted the proliferation of TSPC(both P＜0.001),with no statistical difference be-tween the two concentrations(P=0.283).Additionally,after co-cultured for 24 h,50 μg/mL of PRP-Exos significantly promoted the migration of TSPC(P＜0.001).Conclusion Under in vitro culture conditions,PRP-Exos significantly promote the proliferation and migration of rat TSPC.

To investigate the value of injecting a small amount of absolute ethanol into the benign solid nodules of the thyroid before radiofrequency ablation(RFA)to improve the efficiency of radiofrequency ablation. A total of 98 eligible patients(98 nodules)with pathologically confirmed benign solid nodules who were treated in our center from December 2016 to February 2018 were included and randomized into ethanol ablation(EA)combined with radiofrequency ablation(RFA)group(EA+RFA group)and RFA group,with 49 patients in each group.Routine ultrasound,contrast-enhanced ultrasound(CEUS),and thyroid function test were performed before treatment and 1,3,6,and 12 months after treatment.The general information,treatment time,ablation energy,ablation power,postoperative nodule volume reduction ratio(VRR),symptom score(SS)and cosmetic score(CS),thyroid function level,and incidence of complications were compared between these two groups. The mean treatment time [(441.30±243.31)s (790.70±349.82)s;= 4.403, =0.000],mean ablation energy [(3.92±2.01)kJ (5.15±2.12)kJ;=2.709, =0.009],and mean ablation power [(6.07±1.44)W (7.30±1.29)W;=3.612, =0.006] were significantly lower in the EA+RFA group than in the RFA group.At 3,6 and 12 months after surgery,the VRR in the EA+RFA group was(57.73±11.07)%(=-3.16, <0.001),(64.40±10.56)%(=-5.45, <0.001),and(77.29±8.48)%(=-10.46, <0.001),respectively;the VRR in the RFA group was(55.44±13.01)%(=-1.76, <0.001),(65.28±11.33)%(=-5.09, <0.001),and(75.17±9.84)%(=-8.93, <0.001),which were significantly smaller than those before surgery.There was no significant difference in VRR between the EA+RFA group and the RFA group at 1(=3.41, =0.33),3(=2.05, =0.21),6(=2.77, =0.49),and 12 months(=5.05, =0.10)after treatment.During the follow-up,no recurrence of nodules was observed on CEUS.In the EA+RFA group,the SS [(1.77±0.86).(5.54±2.15);=9.63, <0.001] and the CS[(1.39±0.77).(3.32±0.61);=10.09, =0.004]at 12 months after surgery were significantly lower than those before surgery.In the RFA group,SS [(1.63±1.04).(5.90±1.79);=12.72, <0.001] and CS [(1.64±0.83).(3.15±0.72);=8.13, =0.012] at 12 months after surgery were also significantly lower than those before surgery.The CSS in the EA+RFA group was significantly lower than that in the RFA group [(0.93±0.55).(2.44±0.53);=-11.70, =0.007].Both groups had no significant change in thyroid function during the follow-up period,and no serious complications were observed. Anhydrous alcohol injection can effectively improve the efficiency of radiofrequency ablation in treating benign solid thyroid nodules and is effective in reducing nodule volume,alleviating compressive symptoms,and decreasing cosmetic discomfort.
Catheter Ablation ; Ethanol ; Humans ; Neoplasm Recurrence, Local ; Prospective Studies ; Thyroid Nodule ; Treatment Outcome