Objective To know the stability of 3 kinds of traditional Chinese drug injection with different solvent under different temperature and different storage time,and then reference to safty of clinical durgs. Methods Use particle analyzer,UV SpectropHotometer,pH Determination of three traditional Chinese medicine injection,at different temperatures and different times,the nuanber of particles,pH value,the value of UV absorbance Observe changes. Results The records of experimental data by repeated measures analysis of statistics: Ciwujia Injection,Aidi injection combined with normal saline solution after the particles of ≥ 10μm excess pharmacopoeia standards; ≥ 2μm number of particles is considerable,in the 32～35℃,Ciwujia at T=O min Aidi at T=I80 min ,the number of particles are smaller and with statistical significance,its pH value of the standard range. Xuesaitong injection with glucose injection ≥ 10μm particulate mixture at a higher temperature in excess of pH annacopoeia standards,number of ≥ 2 μm particles in the 4～8℃ and 20～23℃,T=30 min and 60 min time less with statistical significance,and its range of pH value less than pHarmacopoeia. Three kinds of Chinese medicine in the Department's largest UV absorbance peak value and appearance almost unchanged. Conclusions Different drugs in their relative Suggestions of temperature,time and place under intravenous drug use,or better terminal filter,in order to improve the safety of clinical medication.

BACKGROUND:Compared with conventional medications, drug micro-capsule system can control the release of drugs and have wel target properties and biocompatibility. The drugs can be concentrated at the focus and play an important role in clinic. OBJECTIVE:To prepare dacarbazine magnetic micro-capsules with different capsule materials and gelatin complex by coacervation, and to optimize capsule materials and preparation process. METHODS:Fe 3 O 4 RESULTS AND CONCLUSION:The solution complex coacervation method was better than the emulsion coacervation method. As for the solution complex coacervation method, the optimal capsule material was gelatin-sodium alginate, with drug embedding rate 37.90%, the yield rate 72.31%, and the average magnetization intensity 8.53 emu/g. The second material was gelatin-chitosan. As a capsule material, the gelatin was better than chitosan with single coagulation method. Drug embedding rate was 51.58%, the yield rate was 64.50%, and the average magnetization was 6.93 emu/g. Single coagulation method was better than coacervation method. complex coacervation, we prepared the gelatin-Arabic gum magnetic micro-capsule, gelatin-sodium alginate magnetic micro-capsules, gelatin-sodium carboxymethyl cel ulose magnetic micro-capsules, and gelatin-chitosan magnetic micro-capsules. With the emulsion complex coacervation method, we further prepared the gelatin-Arabic gum magnetic micro-capsule, gelatin-sodium alginate magnetic micro-capsules, gelatin-sodium carboxymethyl cel ulose magnetic micro-capsules, and gelatin-chitosan magnetic micro-capsules. The magnetic gelatin micro-capsules and magnetic chitosan micro-capsules were prepared with single coagulation method. The micro-capsules were determined for the embedding rate, the magnetic susceptibility, the micro-capsule size and the release performance, to define the optimal preparation technology of dacarbazine magnetic micro-capsules.

Objective:To investigate the effects of disialyllacto-N-tetraose (DSLNT) on low molecular weight metabolic profile of intestinal contents in neonatal rats with necrotizing enterocolitis (NEC), in an attempt to explore the protective mechanism of DLSNT on intestinal tract of neonates.Methods:Immediately after birth, SD rats were randomly divided into the control group, the NEC group and the NEC+ DSLNT group according to random number tale method.All rats were hand-fed by special formula milk.Rats in the NEC group and NEC+ DSLNT group were exposed to hypoxia (950 mL/L nitrogen, 10 min, thrice per day) and cold stress (4 ℃, 10 min, thrice per day) for continuous 3 days to establish rodent NEC model.Rats in the NEC+ DSLNT group were hand-fed with special formula containing 300 μmol/L DSLNT.All rats were sacrificed after 72 h, and intestinal contents were collected from ileum and colon, followed by untargeted metabolomic determination with the ultrahigh-performance liquid chromatography Q extractive mass spectrometry (UHPLC-QE-MS) method.The terminal ileum was examined by hematoxylin-eosin staining.The metabolome data were analyzed with multivariable analysis using SIMCA 14.1.The metabolites that met both variable importance in the projection (VIP) >1 in the orthogonal partial least squares analysis (OPLS-DA) model and P<0.05 in the t-test were screened as differential metabolites between groups. Results:DSLNT reduced the incidence of NEC and pathological scores of ileum tissue from neonatal rats with NEC [3.0(2.0, 3.0) scores vs.1.0(1.0, 2.0) scores, P<0.01], and also significantly suppressed inflammatory infiltration.OPLS-DA model based on the metabolome data determined by UHPLC-QE-MS could perform effective discrimination between the NEC group and the control group, as well as the NEC+ DSLNT group and the NEC group.There were 64 differential metabolites between the NEC group and the control group (VIP value>1 and P<0.05 for the OPLS-DA model). These metabolites included docosahexaenoic acid (+ 288.0%, P=0.028), xanthine (+ 372.1%, P=0.007), L-arginine (+ 233.1%, P=0.027), L-leucine (+ 232.7%, P=0.015), N-acetylneuraminic acid (-41.6%, P=0.014), and so forth.These metabolites were associated with 34 metabolic pathways.Among them, such 6 pathways as arginine biosynthesis, arginine and proline metabolism were the most disturbed pathways affected by NEC.There were 15 diffe-rential metabolites in between NEC+ DSLNT group and NEC group, which included D-mannose (-73.5%, P=0.032), xanthine (-63.4%, P=0.008), linoleic acid (+ 137.9%, P=0.047), nicotinamide adenine dinucleotide (+ 278.2%, P=0.005), and so forth.These metabolites were mapped to 7 metabolic pathways, among them, linoleic acid metabolism pathway was the most relevant differential pathway affected by DSLNT.There were 8 overlapped meta-bolites in both comparison strategies, and the variation trend of these overlapped metabolites in the NEC group was significantly reversed by DSLNT supplementation. Conclusions:DSLNT could significantly attenuate the NEC pathological damage caused by hypoxia/cold stress in neonatal rats.This protective effect is associated with the improvement of the metabolic profile of intestinal contents caused by NEC and the modulation of the linoleic acid metabolic pathway.The early preventive supplementation of DSLNT is of great significance in maintaining neonatal intestinal homeostasis and preventing the process of NEC.

Objective To study the change and characterization of metabolic profile of intestinal contents of the neonatal rats with necrotizing enterocolitis (NEC) using metabolomics approach,in order to figure out potential biomarkers of NEC.Method Twenty rats with three-postnatal day-old fed with special formula were assigned to control group (n =8) and NEC group (n =12) randomly.Experimental NEC of rats in NEC group were induced by exposing to cold stimulation at 4 degrees Celsius for 10 minutes and to hypoxia at 95％ nitrogen for 10 minutes,three times a day for three consecutive days.All the rats were sacrificed after model preparation.Segments of the ileum of all the rats were collected for hematoxylin-eosin staining and subsequent pathological damage evaluation.The intestinal contents of the ileum and colon were collected by perfusion,followed by lyophilization and analyzed by UHPLC-QE-MS in order to conduct the non-target metabolomic determination.The information of the metabolites determined was calculated by multivariable analysis using SIMCA software.Result The pathological damage scores of NEC group were higher than those of the control group [(3.13 ± 0.83) vs.(0.25 ± 0.46),P ＜ 0.001].The results of orthogonal partial least squares discriminant analysis (OPLS-DA) model showed that in the ESI + mode,R2(x) =0.604,R2(y) =0.583,Q2 =0.960,while in the ESI-mode,the OPLS-DA model R2(x) =0.828,R2(y) =0.999,and Q2 =0.713,indicating that there is a significant difference in the intestinal content metabolic profile between the control group and the NEC group.Forty-eight differential metabolites related to NEC were identified.In ESI-mode,there were 22 differential metabolites,including L-isoisoleucine (+ 221％) and D-phenylalanine (+ 230％),L-histidine (+ 284％),xanthine (+ 207％),glutamyl leucine (+ 246％),allose (-70％),myristic acid (-57％) and pentadecanoic acid (-35％).What is more,in the ESI + mode,26 other differential metabolites were identified,including ornithine (+ 268％),D-leucine (+ 176％),L-iso Leucine (+ 213％),acetylcholine (+ 195％),nicotinamide adenine dinucleotide (+ 199％),citrulline (+ 158％),cytosine (-58％),xanthoic acid (-64％).These metabolites were reflected to 33 different metabolic pathways in KEGG databases.The pathway enrichment analysis and pathway topology analysis with MetaboAnalyst indicated that the arginine and proline metabolic pathways,histidine metabolic pathways,and glutathione metabolic pathways were the top altered pathways in the condition of NEC.Conclusion The metabolic profile of intestinal contents in NEC rats was significantly different from that in normal rats,which was characterized by amino acid accumulation,mainly involving the metabolic pathways of arginine,proline,histidine and glutathione.The detection of intestinal contents metabolic profile,especially amino acid metabolize group may be of great significance for the diagnosis of NEC,and improving intestinal microenvironment may be the key strategy for the prevention and treatment of NEC.

Objective To analyze the biological activity of bioactive peptides in human breast milk and to find the polypeptides so as to investigate the preventive and therapeutic effects of breast milk-derived bioactive peptides on neonatal necrotizing enterocolitis(NEC).Methods Six mothers who gave birth to preterm neonates were enrolled in this study and 5 mL of their breast milk secreted within 2-5 postnatal days were collected for 6 times and blended subsequently.Bioactive peptides from maternal milk of the preterm infants were separated by ultrafiltration and analyzed by using tandem mass spectrometry.Polypeptides possibly with biological function were screened out by using bioinformatics software and the protein function cluster online analysis software was used to predict the polypeptides associated with infection according to the biological function of their precursor proteins.The ATCC25922,an Escherichia coli strain commonly associated with infection in NEC and drug solution (sulbactarr/cefoperazone) were used to conduct the drug susceptibility testing and bactericidal kinetics testing,so as to verify the antibacterial effects of bioactive peptides in the breast milk.Results Four thousand three hundred and eleven peptides contained in breast milk were identified successfully,of which 1 370 were non-differential peptides,and 188 peptides possibly with biological activity and 11 peptides were associated with infection.The peptide compound in the breast milk had antimicrobial activity and bactericidal power against Escherichia coli.Conclusions The active peptide compounds in the breast milk have antimicrobial activity,which play an important role in the prevention of NEC.Finding the true antimicrobial peptides with in vivo and in vitro biological activity by using antimicrobial spectrum test is expected.

Objective To evaluate the effectiveness of deep learning methods to detect subsolid nodules from chest X-ray images.Methods The building,training,and testing of the deep learning model were performed using the research platform developed by Infervision,China.The training dataset consisted of 1 965 chest X-ray images, which contained 85 labeled subsolid nodules and 1 880 solid nodules. Eighty-five subsolid nodules were confirmed by corresponding CT exams. We labeled each X-ray image using the corresponding reconstructed coronal slice from the CT exam as the gold standard,and trained the deep learning model using alternate training.After the training,the model was tested on a different dataset containing 56 subsolid nodules,which were also confirmed by corresponding coronal slices from CT exams. The model results were compared with an experienced radiologist in terms of sensitivity,specificity,and test time. Results Out of the testing dataset that contained 56 subsolid nodules, the deep learning model marked 72 nodules,which consisted of 39 true positives(TP)and 33 false positives(FP).The model took 17 seconds.The human radiologist marked 39 nodules,with 31 TP and 8 FP.The radiologist took 50 minutes and 24 seconds. Conclusions Subsolid nodules are prone to mis-diagnosis by human radiologists. The proposed deep learning model was able to effectively identify subsolid nodules from X-ray images.

Objective To develop and validate the radiomics nomogram on the discrimination of lung invasive adenocarcinoma from'non-invasive'lesion manifesting as ground glass nodule(GGN)and compare it with morphological features and quantitative imaging. Methods One hundred and sixty pathologically confirmed lung adenocarcinomas from November 2011 to December 2014 were included as primary cohort. Seventy-six lung adenocarcinomas from November 2014 to December 2015 were set as an independent validation cohort. Lasso regression analysis was used for feature selection and radiomics signature building. Radiomics score was calculated by the linear fusion of selected features. Multivariable logistic regression analysis was performed to develop models. The prediction performances were evaluated with ROC analysis and AUC,and the different prediction performance between different models and mean CT value were compared with Delong test. The generalization ability was evaluated with the leave-one-out cross-validation method. The performance of the nomogram was evaluated in terms of its calibration. The Hosmer-Lemeshow test was used to evaluate the significance between the predictive and observe values.Results Four hundred and eighty-five 3D features were extracted and reduced to 2 features as the most important discriminators to build the radiomics signatures. The individualized prediction model was developed with age, radiomics signature, spiculation and pleural indentation, which had the best discrimination performance(AUC=0.934)in comparison with other models and mean CT value(P<0.05)and showed better performance compared with the clinical model(AUC=0.743,P<0.001).The radiomics-based nomogram demonstrated good calibration in the primary and validation cohort, and showed improved differential diagnosis performance with an AUC of 0.956 in the independent validation cohort. Conclusion Individualized prediction model incorporating with age, radiomics signature, spiculation and pleural indentation, presenting with radiomics nomogram, could differentiate IAC from'non-invasive'lesion manifesting as GGN with the best performance in comparison with morphological features and quantitative imaging.

Objective:To investigate the value of CT features in predicting visceral pleural invasion (VPI) in clinical stage ⅠA peripheral lung adenocarcinoma under the pleura.Methods:The CT signs of 274 patients with clinical stage ⅠA peripheral lung adenocarcinoma under the pleura diagnosed in Changzheng Hospital of Naval Medical University from January 2015 to November 2021 were retrospectively analyzed. According to the ratio of 6∶4, 164 patients collected from January 2015 to August 2019 were used as the training group, and 110 patients collected from August 2019 to November 2021 were used as the validation group. The maximum diameter of the tumor (T), the maximum diameter of the consolidation part (C), and the minimum distance between the lesion and the pleura (DLP) were quantitatively measured, and the proportion of the consolidation part was calculated (C/T ratio, CTR). The CT signs of the tumor were analyzed, such as the relationship between the tumor and the pleura classification, the presence of a bridge tag sign, the location of the lesion, density type, shape, margin, boundary and so on. Variables with significant difference in the univariate analysis were entered into multivariate logistic regression analysis to explore predictors for VPI, and a binary logistic regression model was established. The predictive performance of the model was analyzed by receiver operating characteristic curve in the training and validation group.Results:There were 121 cases with VPI and 153 cases without VPI among the 274 patients with lung adenocarcinoma. There were 79 cases with VPI and 85 cases without VPI in the training group. Univariate analysis found that the maximum diameter of the consolidation part, CTR, density type, spiculation sign, vascular cluster sign, relationship of tumor and pleura and bridge tag sign between patients with VPI and those without VPI were significantly different in the training group( P<0.05). Multivariate logistic regression analysis found the relationship between tumor and pleura [taking type Ⅰ as reference, type Ⅱ (OR=6.662, 95%CI 2.364-18.571, P<0.001), type Ⅲ (OR=34.488, 95%CI 8.923-133.294, P<0.001)] and vascular cluster sign (OR=4.257, 95%CI 1.334-13.581, P=0.014) were independent risk factors for VPI in the training group. The sensitivity, specifcity, and area under curve (AUC) for the logistic model in the training group were 62.03%, 89.41% and 0.826, respectively, using the optimal cutoff value of 0.504. The validation group obtained an sensitivity, specifcity, and AUC of 92.86%, 47.06%, and 0.713, respectively, using the optimal cutoff value of 0.449. Conclusion:The relationship between the tumor and the pleura and the vascular cluster sign in the CT features can help to predict visceral pleural invasion in the clinical stage ⅠA peripheral lung adenocarcinoma under the pleura.

Objective:To explore the differences of functional small airway and pulmonary vascular parameters in chronic obstructive pulmonary disease (COPD) of different imaging phenotypes.Methods:One hundred and thirty COPD patients underwent biphasic CT scanning in Shanghai Changzheng Hospital from August 2018 to August 2020 were analyzed retrospectively. The patients were classified into three phenotypes based on the presence of emphysema and bronchial wall thickening on CT images. Phenotype A: no emphysema or mild emphysema, with or without bronchial wall thickening; Phenotype E: obvious emphysema without bronchial wall thickening; phenotype M: significant emphysema and bronchial wall thickening were present. Parametric response map (PRM) and pulmonary vascular parameters were quantitatively measured at the whole lung level. PRM parameters included the volume of emphysema (PRMV Emphysema), the volume of functional small airway (PRMV fSAD), the volume of normal pulmonary parenchyma (PRMV Normal) and its volume percentage (%). Pulmonary vascular parameters included the number of vessels (N) and cross-sectional area vessels<5 mm 2 (N -CSA<5) at 6, 9, 12, 15, 18 21, 24 mm distance from the pleura. ANOVA or Kruskal-Wallis H tests were used to compare the differences for PRM and pulmonary vascular parameters among the three phenotypes, and LSD or Bonferroni tests were used for multiple comparisons. Results:There were significant differences among the three phenotypes for PRMV fSAD, PRMV Emphysema, PRMV fSAD%, PRMV Emphysema%, and PRMV Normal% at the whole lung level ( P<0.05). PRMV Emphysema, PRMV Emphysema%, PRMV Fsad, PRMV fSAD% of phenotype A were lower than those of phenotype E and M ( P<0.001), while there was no significant difference for PRMV Emphysema, PRMV Emphysema%, PRMV fSAD, PRMV fSAD% between phenotype E and phenotype M ( P>0.05). There were significant differences in N and N -CSA<5 that 6 mm distance from the pleura among the three groups( P<0.05). Among them, N and N -CSA<5 that 6 mm distance from pleura in phenotype M were significantly lower than those in phenotype A( P<0.001,0.002); No significant differences was found in N between phenotype M and phenotype E( P>0.05), while there was significant differences in N -CSA<5 between phenotype M and phenotype E( P=0.034). Conclusion:Biphasic quantitative CT analysis can reflect the heterogeneity of the functional small airways and pulmonary vascular abnormality in COPD with different phenotypes, and provide objective evidence for individualized diagnosis and treatment.

【Objective】 To explore the effects of breastfeeding on the immune response of CD4⁺T lymphocytes in infants in non-inflammatory state, and to analyze the immunomodulatory significance of the whole composition of breast milk. 【Methods】 A retrospective cohort study was conducted. From January to September 2022, six-month-old infants who took physical examination in the Child Healthcare Department of Changzhou Children′s Hospital Affiliated to Nantong University, were selected based on inclusion criteria, and were divided into breastfeeding group (n=33) and formula feeding group (n=27) based on their feeding patterns. Flow cytometry was used to detect the percentage of CD4⁺ T cells, including helper T cell (Th) 1, Th2, Th17, regulatory T cell (Treg), and the levels of related cytokines interleukin (IL)-2, IL-4, IL-6, IL-10, tumor necrosis factor (TNF)-α, interferon (IFN)-γ, IL-17 in peripheral blood. The differences in these indicators between the two groups were compared. 【Results】 Compared with the formula feeding group, the breastfeeding group showed significantly higher percentages of Th1(t=3.038), Treg (t=2.088). The ratio of Th1 to Th2(Z=2.756), IL-10(Z=2.297) and IFN-γ (Z=2.076) in the peripheral blood of the breastfeeding group were also significantly higher. Conversely, the breastfeeding group had significantly lower percentage of Th17(Z=2.704) and IL-17A (t=2.187) (P<0.05). There was no significant difference the percentage of Th2, as well as in the levels of IL-2, IL-4, IL-6 and TNF-α between the two groups (P>0.05). 【Conclusions】 Breastfeeding has a regulatory effect on the immune response of infant CD4⁺ T lymphocytes. It promotes the development of Th1/Th2 towards Th1 and the immunomodulatory effect of Treg. Moreover, it inhibits the Th17 type immune response. These findings suggest that the complete composition of breast milk contributes to the development and maturation of infant immune system, enhancing immune defense and immune tolerance.