Humans ; Lung Neoplasms/surgery* ; Pneumonectomy ; Thermography ; Thoracic Surgery, Video-Assisted

Objective:To explore the optimal labeling conditions of 177Lu-1, 4, 7-triazacyclononane-1, 4, 7-triacetic acid (NOTA)- D-Phe1-Tyr3-Thr8-octreotide (TATE), and evaluate its biodistribution and imaging characteristics in mice. Methods:The reaction temperature, pH, reaction time and other labeling conditions were changed to realize the rapid labeling of NOTATATE by 177Lu. The optimal labeling conditions, radiochemical purity, in vitro stability, plasma protein binding rate, and lipid-water partition coefficient were determined. Twenty-four normal KM mice were divided into 6 groups by random number table method. After injected with 3.7 MBq 177Lu-NOTATATE through tail vein, they were sacrificed at 0.5, 1, 4, 24 h and 4, 6 d respectively to research the biological distribution (injection dose rate per gram of tissue percentage, %ID/g). Six normal mice were randomly divided into 2 groups and injected with 11.1 MBq 177Lu-NOTATATE and 177Lu-1, 4, 7, 10-tetraazacyclododecane-1, 4, 7, 10-tetraacetic acid (DOTA)TATE, respectively. SPECT planar imaging was performed at 1, 2, 3 h after injection. Another 8 mice were divided into 4 groups, injected with 3.7, 7.4, 18.5 MBq 177Lu-NOTATATE and saline respectively for an acute toxicity test. Results:At pH 5 and reaction temperature between 95 ℃ and 100 ℃ for 15 min, the labeling rate could reach more than 98%. After being placed in human serum for 24 h, the radiochemical purity was still higher than 95%. The plasma protein binding rate of 177Lu-NOTATATE was (58.6±1.9)% and the lipid-water partition coefficient was 0.048±0.014. In normal mice, the concentration of radioactivity is mainly in the liver, kidney and spleen, especially in the kidney (up to (29.120±1.204) %ID/g after 0.5 h of injection), which is less distributed in the blood and excreted rapidly. Compared with 177Lu-DOTATATE, 177Lu-NOTATATE was excreted faster by the kidney. The toxicity study results revealed that no damage was observed in mice of each group, and no obvious damage or inflammatory changes were observed in organ tissue sections. Conclusions:The optimal labeling condition of 177Lu-NOTATATE were determined in this study. The physical, chemical, and biological properties of 177Lu-NOTATATE were proved to be good and safe, and it was excreted faster by the kidney than 177Lu-DOTATATE. The results of this study lay a foundation for further clinical transformation research.

Objective To evaluate the performance of a clinical-radiomics model for differentiating focal organizing pneumonia(FOP)and lung adenocarcinoma(LUAD).Methods We retrospectively analyzed the data of 60 patients with FOP confirmed by postoperative pathology at the First Medical Center of the Chinese PLA General Hospital from January,2019 to December,2022,who were matched with 120 LUAD patients using propensity score matching in a 1∶2 ratio.The independent risk factors for FOP were identified by logistic regression analysis of the patients'clinical data.The cohort was divided into a training set(144 patients)and a test set(36 patients)by random sampling.Python 3.7 was used for extracting 1835 features from CT image data of the patients.The radiographic features and clinical data were used to construct the model,whose performance was validated using ROC curves in both the training and test sets.The diagnostic efficacy of the model for FOP and LUAD was evaluated and a diagnostic nomogram was constructed.Results Statistical analysis revealed that an history of was an independent risk factor for FOP(P=0.016),which was correlated with none of the hematological findings(P>0.05).Feature extraction and dimensionality reduction in radiomics yielded 30 significant labels for distinguishing the two diseases.The top 3 most discriminative radiomics labels were GraylevelNonUniformity,SizeZoneNonUniformity and shape-Sphericity.The clinical-radiomics model achieved an AUC of 0.909(95%CI:0.855-0.963)in the training set and 0.901(95%CI:0.803-0.999)in the test set.The model showed a sensitivity of 85.4%,a specificity of 83.5%,and an accuracy of 84.0%in the training set,as compared with 94.7%,70.6%,and 83.3%in the test set,respectively.Conclusion The clinical-radiomics nomogram model shows a good performance for differential diagnosis of FOP and LUAD and may help to minimize misdiagnosis-related overtreatment and improve the patients'outcomes.

Objective To evaluate the performance of a clinical-radiomics model for differentiating focal organizing pneumonia(FOP)and lung adenocarcinoma(LUAD).Methods We retrospectively analyzed the data of 60 patients with FOP confirmed by postoperative pathology at the First Medical Center of the Chinese PLA General Hospital from January,2019 to December,2022,who were matched with 120 LUAD patients using propensity score matching in a 1∶2 ratio.The independent risk factors for FOP were identified by logistic regression analysis of the patients'clinical data.The cohort was divided into a training set(144 patients)and a test set(36 patients)by random sampling.Python 3.7 was used for extracting 1835 features from CT image data of the patients.The radiographic features and clinical data were used to construct the model,whose performance was validated using ROC curves in both the training and test sets.The diagnostic efficacy of the model for FOP and LUAD was evaluated and a diagnostic nomogram was constructed.Results Statistical analysis revealed that an history of was an independent risk factor for FOP(P=0.016),which was correlated with none of the hematological findings(P>0.05).Feature extraction and dimensionality reduction in radiomics yielded 30 significant labels for distinguishing the two diseases.The top 3 most discriminative radiomics labels were GraylevelNonUniformity,SizeZoneNonUniformity and shape-Sphericity.The clinical-radiomics model achieved an AUC of 0.909(95%CI:0.855-0.963)in the training set and 0.901(95%CI:0.803-0.999)in the test set.The model showed a sensitivity of 85.4%,a specificity of 83.5%,and an accuracy of 84.0%in the training set,as compared with 94.7%,70.6%,and 83.3%in the test set,respectively.Conclusion The clinical-radiomics nomogram model shows a good performance for differential diagnosis of FOP and LUAD and may help to minimize misdiagnosis-related overtreatment and improve the patients'outcomes.

A series of 2-(((5-akly/aryl-1-pyrazol-3-yl)methyl)thio)-5-alkyl-6-(cyclohexylmethyl)-pyrimidin-4(3)-ones were synthesized and their anti-HIV-1 activities were evaluated. Most of these compounds were highly active against wild-type (WT) HIV-1 strain (IIIB) with EC values in the range of 0.0038-0.4759 μmol/L. Among those compounds, had an EC value of 3.8 nmol/L and SI (selectivity index) of up to 25,468 indicating excellent activity against WT HIV-1. anti-HIV-1 activity and resistance profile studies suggested that compounds and displayed potential anti-HIV-1 activity against laboratory adapted strains and primary isolated strains including different subtypes and tropism strains (ECs range from 4.3 to 63.6 nmol/L and 18.9-219.3 nmol/L, respectively). On the other hand, it was observed that those two compounds were less effective with EC values of 2.77 and 4.87 μmol/L for HIV-1A (K103N + Y181C). The activity against reverse transcriptase (RT) was also evaluated for those compounds. Both and obtained sub-micromolar IC values showing their potential in RT inhibition. The pharmacokinetics examination in rats indicated that compound has acceptable pharmacokinetic properties and bioavailability. Preliminary structure-activity relationships and molecular modeling studies were also discussed.