BACKGROUND: It has been reported that chitosan can inhibit scar formation and promote wound healing. Medical invisible antimicrobial film is a new type of membrane materials which comprises chitosan as ground substance.OBJECTIVE: To determine the inhibitory effects of medical invisible antimicrobial film on the operative incision scar, and to observe its effects on wound healing.DESIGN, TIME AND SETTING: A controlled animal study was conducted at the IVC Experimental Animal Room, West China School of Pharmacy, Sichuan University from August to October 2007.MATERIALS: Medical invisible antimicrobial film stock solution was colorless transparent sticking solution, which formed colorless transparent film following spray painting (specification: 40 mL), provided by Chengdu Chaojl Technology Co., Ltd. (lot number 070501).METHODS: A total of 16 healthy Sprague Dawley rats aged 20 to 23 days were selected. Full linear skin incisions were operated in aseptic condition. After operation, the experimental group (right side) was sprayed medical invisible antimicrobial film 0.5 mL/time, once a day, for totally 3 days. The control group (left side) received an equal volume of 0.9% sodium chloride injection, with natural cure.MAIN OUTCOME MEASURES: At 3, 7 and 14 days following surgery, incision skin specimens were obtained, and subjected to hematoxylin-eosin staining and Masson staining was applied to observe wound healing and the formation of scar, then the scar area was analyzed.RESULTS: The scar relative mean area of control group was 154 069±51 356 and the experimental group was 98 200±34 719 on the postoperative 14~(th) day. The two groups were significantly different (P < 0.05). At 14 days following surgery, optical microscope showed that the experiment group had less collagen fibers and fibroblast accumulation. At 3 days, compared with the control group, the experimental group had less epithelization period, more granulation tissue and less inflammatory cell infiltration.CONCLUSION: The medical invisible antimicrobial film has inhibitory effect of the formation of operative incision scar, and no influence on wound healing of operative incision.

Fumonisin B1 (FB1) is a carcinogenic mycotoxin found in commodities such as corn and corn-originated products. An aptamer-based method for detection of FB1 was developed using the fluorescent dye PicoGreen, which can recognize and bind double-stranded DNA. A peak fluorescence of PicoGreen was obtained in 15 min in the presence of FB1 aptamer, which formed a double-stranded hybridizer DNA with its complementary strand. The excitation and emission wavelengths for PicoGreen detection were 480 nm and 520 nm, respectively. The sensitivity of this aptamer/PicoGreen-based method was 0.1 μg/L. This method showed a good linearity for FB1 concentration ranging from 0.1 to 1 μg/L. The entire detection procedure for FB1 could be completed within 40 min. No cross reactions were observed with any other mycotoxins against aflatoxin B1, ochratoxin A, citrinin and zearalenone, demonstrating high specificity towards FB1 aptamer. Agreement between commercial, antibody-based enzyme-linked immunosorbent assay (ELISA) kit and aptamer method was excellent with a kappa value of 0.857. Taken together, this aptamer/PicoGreen-based method is more cost-effective, time-saving and useful than ELISA for detection of FB1.
Aflatoxin B1 ; Enzyme-Linked Immunosorbent Assay ; Fluorescence ; Fluorescent Dyes ; chemistry ; Fumonisins ; analysis ; Mycotoxins ; analysis ; Ochratoxins ; Organic Chemicals ; chemistry ; Staining and Labeling ; Zea mays

Objective To explore the effect of melatonin(MT)-modified PEEK implant assisted by polydopamine(PDA)coating on osteointegration in osteoporotic rats.Methods MT was adhered to PEEK implants with PDA coating as carrier.The physicochemical properties of the materials were analyzed by SEM image,water contact angle,FTIR and protein adsorption experiment.OVX-rBMSCs were inoculated on the surface of PEEK sheet and cultured.The cytoskeleton was stained and cell adhesion morphology was observed.Cell proliferation activity was evaluated by CCK-8 assay;key enzyme activities for osteogenic differentiation were analyzed by ALP stai-ning,and expression levels of osteoblast-related genes COL-1,Runx2,OPN,OCN,BMP-2 and ALP were detected by quantitative real-time PCR.In addition,implants were implanted into the femur of osteoporotic rats and bone volume on the implant surface was de-tected and quantified by Micro-CT.Results MT was successfully loaded on PEEK;the cell adhesion was better,and the proliferation activity and osteogenic differentiation ability were significantly higher than those of control group(P＜0.01).In the rat osteoporosis mod-el,there was more new bone formation around the modified PEEK implant(P＜0.01).Conclusion MT-modified PEEK implants have excellent biocompatibility and improve osteointegration in an osteoporotic environment.

Objective:To establish a predictive model for myocardial contusion (MC) in patients with rib fractures and evaluate its clinical application value.Methods:A retrospective case-control study was conducted to analyze the clinical data of 370 patients with rib fractures admitted to the Affiliated Jiangsu Shengze Hospital of Nanjing Medical University from January 2017 to December 2019, including 257 males and 113 females, aged 18-95 years [(56.5±14.0)years]. All the patients underwent electrocardiogram examination and myocardial biomarker test within 24 hours on admission, of whom 159 were diagnosed with MC, and 211 with non-MC (NMC). The 370 patients were divided into a training set of 264 patients (106 with MC, 158 with NMC) and a validation set of 106 patients (53 with MC, 53 with NMC) at a ratio of 7∶3 through the completely randomized method. In the training set, the MC group and NMC group were compared in terms of their demographic characteristics, vital signs on admission, types of rib fractures, number of rib fractures, locations of rib fractures, associated thoracic injuries, trauma scores, and laboratory indices. Variables of positive correlation with MC in patients with rib fractures were screened by Spearman correlation analysis, followed by univariate binary Logistic regression analysis for these variables to determine the risk factors for MC in patients with rib fractures. LASSO regression analysis and multivariate Logistic regression analysis were applied to identify the independent risk factors for MC in patients with rib fractures, and the regression equation was constructed. A nomogram prediction model was plotted based on the regression equation with R software. The receiver operating characteristic (ROC) curve was plotted to evaluate the model′s discriminability. Hosmer-Lemeshow (H-L) goodness-of-fit test and calibration curves of 1000 repeated samplings by the Bootstrap method were used to evaluate the calibration of the model. The decision curve analysis (DCA) and clinical impact curve analysis (CIC) were plotted to evaluate its clinical efficacy. A risk scoring was performed according to the assigned β coefficient of independent risk factors. Accordingly, the 370 selected patients with rib fractures were divided into low-risk subgroup of 202 patients, moderate-risk subgroup of 108 patients, high-risk subgroup of 50 patients, and extremely high-risk subgroup of 10 patients. The incidence of MC and in-hospital mortality were compared among different subgroups so as to further verify the clinical application value of the predictive model.Results:In the training set, there were significant differences between the MC group and NMC group in bilateral rib fractures, flail chest, number of rib fractures, upper chest proximal sternum segment, upper chest anterolateral segment, upper chest proximal spinal segment, middle chest anterolateral segment, middle chest proximal spinal segment, lower chest anterolateral segment, pneumothorax, mediastinal emphysema, hemothorax, sternal fractures, chest abbreviated injury scale (c-AIS), injury severity score (ISS), new injury severity score (NISS), white blood cell counts, hemoglobin, hematocrit, total cholesterol, low density lipoprotein, albumin, aspartate aminotransferase, alanine aminotransferase, and blood urea nitrogen ( P<0.05 or 0.01). Spearman correlation analysis showed that the bilateral rib fractures, flail chest, number of rib fractures, upper chest proximal sternum segment, upper chest anterolateral segment, upper chest proximal spinal segment, middle chest anterolateral segment, middle chest proximal spinal segment, lower chest anterolateral segment, pneumothorax, hemothorax, sternal fractures, c-AIS, ISS, NISS, white blood cell count, aspartate aminotransferase and blood urea nitrogen were positively correlated with MC ( P<0.05 or 0.01). Univariate binary Logistic regression analysis verified that the above variables with positive correlation were significantly correlated with MC in patients with rib fractures ( P<0.05 or 0.01). The 4 predictor variables screened by LASSO regression analysis were the upper chest anterolateral segment, middle chest proximal spinal segment, pneumothorax, and sternal fractures. Multivariate Logistic regression analysis confirmed that the aforementioned 4 predictor variables were independent risk factors for MC in patients with rib fractures ( P<0.05 or 0.01). The regression equation of the training set was established based on the above independent risk factors: P=e x/(1+e x), with the x=1.57×"upper chest anterolateral segment"+0.73×"middle chest proximal spinal segment"+1.36×"pneumothorax"+2.16×"sternal fractures"-1.10. In the predictive model for MC in patients with rib fractures established based on the equation, the area under the ROC curve (AUC) was 0.77 (95% CI 0.72, 0.83) and 0.77 (95% CI 0.71, 0.82) in the training set and validation set. The H-L goodness-of-fit test showed χ2=2.77, P=0.429 in the training set, and χ2=1.33, P=0.515 in the validation set, indicating that there was no significant difference between the predicted probability and the actual probability of the model ( P>0.05). The calibration curves showed that the bias-corrected curves of the training set and validation set were in good consistency with the actual curves and were both close to the ideal curves. The DCA of the training set and the validation set showed that within the threshold probability range of 0.2-0.8, the predictive model could obtain good net clinical benefits. The CIC of the training set and the validation set indicated that when the threshold probability was >0.4, the population identified as high-risk MC patients by the predictive model highly matched the actual MC patients. Risk scoring of subgroups found that the incidence of MC and in-hospital mortality among the patients with rib fractures were 80.0% and 6.0% in the high-risk subgroup and 90.0% and 20.0% in the extremely high-risk subgroup, significantly higher than those in the low-risk subgroup (24.8%, 1.0%) and the moderate-risk subgroup (55.6%, 1.9%) ( P<0.05). Conclusions:The predictive model for MC in patients with rib fractures constructed based on the upper chest anterolateral segment, middle chest proximal spinal segment, pneumothorax, and sternal fractures has good predictive efficacy and clinical application value.

We aimed to obtain the recombinant aminopeptidase encoded by Listeria monocytogenes (L. monocytogenes) gene lmo1711, and characterized the enzyme. First, the amino acid sequences of Lmo1711 from L. monocytogenes EGD-e and its homologues in other microbial species were aligned and the putative active sites were analyzed. The putative model of Lmo1711 was constructed through the SWISS-MODEL Workspace. Then, the plasmid pET30a-Lmo1711 was constructed and transformed into E. coli for expression of the recombinant Lmo1711. The his-tagged soluble protein was purified using the nickel-chelated affinity column chromatography. With the amino acid-p-nitroaniline as the substrate, Lmo1711 hydrolyzed the substrate to free p-nitroaniline monomers, whose absorbance measured at 405 nm reflected the aminopeptidase activity. The specificity of Lmo1711 to substrates was then examined by changing various substrates, and the effect of metal ions on the catalytic efficiency of this enzyme was further determined. Based on the bioinformatics data, Lmo1711 is a member of the M29 family aminopeptidases, containing a highly conserved catalytic motif (Glu-Glu-His-Tyr-His-Asp) with typical structure arrangements of the peptidase family. The recombinant Lmo1711 with a size of about 49.3 kDa exhibited aminopeptidase activity and had a selectivity to the substrates, with the highest degree of affinity for leucine-p-nitroaniline. Interestingly, the enzymatic activity of Lmo1711 can be activated by Cd²⁺, Zn²⁺, and is strongly stimulated by Co²⁺. We here, for the first time demonstrate that L. monocytogenes lmo1711 encodes a cobalt-activated aminopeptidase of M29 family.