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Lung cancer is the deadliest cancer killing almost 1.8 million people in 2020. The new cases are expanding alarmingly. Early lung cancer manifests itself in the form of nodules in the lungs. One of the most widely used techniques for both lung cancer early and noninvasive diagnosis is computed tomography (CT). However, the intensive workload of radiologists to read a large number of scans for nodules detection gives rise to issues like false detection and missed detection. To overcome these issues, we proposed an innovative strategy titled adaptive boosting self-normalized multiview convolution neural network (AdaBoost-SNMV-CNN) for lung cancer nodules detection across CT scans. In AdaBoost-SNMV-CNN, MV-CNN function as a baseline learner while the scaled exponential linear unit (SELU) activation function normalizes the layers by considering their neighbors' information and a special drop-out technique (α-dropout). The proposed method was trained and tested using the widely Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) and Early Lung Cancer Action Program (ELCAP) datasets. AdaBoost-SNMV-CNN achieved an accuracy of 92%, sensitivity of 93%, and specificity of 92% for lung nodules detection on the LIDC-IDRI dataset. Meanwhile, on the ELCAP dataset, the accuracy for detecting lung nodules was 99%, sensitivity 100%, and specificity 98%. AdaBoost-SNMV-CNN outperformed the majority of the model in accuracy, sensitivity, and specificity. The multiviews confer the model's good generalization and learning ability for diverse features of lung nodules, the model architecture is simple, and has a minimal computational time of around 102 minutes. We believe that AdaBoost-SNMV-CNN has good accuracy for the detection of lung nodules and anticipate its potential application in the noninvasive clinical diagnosis of lung cancer. This model can be of good assistance to the radiologist and will be of interest to researchers involved in the designing and development of advanced systems for the detection of lung nodules to accomplish the goal of noninvasive diagnosis of lung cancer.
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In recent years, with being gradually developed, three-dimensional (3D) reconstruction based on pathology and medical imaging technology has shown certain value in the diagnosis and treatment of breast cancer. And with its advantages of providing the spatial location, morphological structure and 3D structure relationships with the surrounding tissues and organs, 3D reconstruction technology has played a key role in the early diagnosis, surgical treatment, and accurate evaluation of the treatment effect after surgery of breast cancer. Although the application of 3D reconstruction technology based on pathology and medical imaging is still inadequate, with the continuous development of science and technology, 3D reconstruction technology will play an increasingly important role in the diagnosis, personalized treatment and prognosis assessment of breast cancer.
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Background@#/Aim: It is known that an imbalance in the intestinal f lora plays a crucial role in colorectal cancer (CRC), but the effect of food consumption patterns on the types of intestinal flora remains to be clarified. We aimed to analyze the associations between food intake and intestinal flora in healthy and CRC individuals. @*Methods@#Food intake data were recorded using the Food Frequency Questionnaire (FFQ). The composition and diversity of the intestinal flora detected by 16S rRNA gene sequencing, and the data were analyzed by R version 3.1.1 software. @*Results@#Higher intake of red meat or pickled foods, and lower intake of white meat, fruits, vegetables, beans, nuts were found in the CRC group compared with the healthy group. Higher levels of Fusobacteria and Proteobacteria, and lower levels of Firmicutes were observed in the CRC group. Partial correlation analysis revealed that the intake of fruits, beans, and nuts was negatively correlated with Proteobacteria and Fusobacteria, but pickled food was positively correlated with Fusobacteria (p < 0.05). Fish, beans, and nuts intake was negatively correlated with Escherichia (p = 0.01). Multiple regression analysis revealed that vegetable oil (odds ratio [OR], 0.26; 95% confidence interval [CI], 0.13 to 0.82), vegetables (OR, 0.26; 95% CI, 0.10 to 0.64), eggs (OR, 0.26; 95% CI, 0.10 to 0.69), pickled foods (OR, 21.02; 95% CI, 6.02 to 73.45), and red meat (OR, 4.23; 95% CI, 1.68 to 10.60) had an impact on CRC risk. @*Conclusions@#The species and abundance of intestinal flora varies between CRC and healthy individuals and may be affected by their food preference.
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Background@#/Aim: It is known that an imbalance in the intestinal f lora plays a crucial role in colorectal cancer (CRC), but the effect of food consumption patterns on the types of intestinal flora remains to be clarified. We aimed to analyze the associations between food intake and intestinal flora in healthy and CRC individuals. @*Methods@#Food intake data were recorded using the Food Frequency Questionnaire (FFQ). The composition and diversity of the intestinal flora detected by 16S rRNA gene sequencing, and the data were analyzed by R version 3.1.1 software. @*Results@#Higher intake of red meat or pickled foods, and lower intake of white meat, fruits, vegetables, beans, nuts were found in the CRC group compared with the healthy group. Higher levels of Fusobacteria and Proteobacteria, and lower levels of Firmicutes were observed in the CRC group. Partial correlation analysis revealed that the intake of fruits, beans, and nuts was negatively correlated with Proteobacteria and Fusobacteria, but pickled food was positively correlated with Fusobacteria (p < 0.05). Fish, beans, and nuts intake was negatively correlated with Escherichia (p = 0.01). Multiple regression analysis revealed that vegetable oil (odds ratio [OR], 0.26; 95% confidence interval [CI], 0.13 to 0.82), vegetables (OR, 0.26; 95% CI, 0.10 to 0.64), eggs (OR, 0.26; 95% CI, 0.10 to 0.69), pickled foods (OR, 21.02; 95% CI, 6.02 to 73.45), and red meat (OR, 4.23; 95% CI, 1.68 to 10.60) had an impact on CRC risk. @*Conclusions@#The species and abundance of intestinal flora varies between CRC and healthy individuals and may be affected by their food preference.
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Objective@#To establish a labeling method for bacterial outer membrane vesicle (OMV) based on luciferase reporting gene. @*Methods@#By utilizing the characteristics that high abundance of outer membrane protein A (OmpA) presented on the surface of bacterial OMV, the outer membrane protein-luciferase fusion protein was constructed to position the luciferase on the surface of the outer membrane vesicle, and the number of bacterial OMV was evaluated based on the luciferase activity. @*Results@#The OmpA-NanoLuc fusion protein expression vector was constructed successfully, and the outer membrane vesicles secreted by the subject strains after the expression of the fusion protein displayed stable luciferase activity. The number of bacterial outer membrane vesicles was semi-quantitative detrmined by measuring the activity of fluorescein enzyme. @*Conclusion@#A semi-quantitative method based on luciferase labeling was developed for the detection of extracellular vesicles, which could be used to evaluate the secretion level of specific strains.
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Objective The feasibility of predicting the B-cell epitopes of human Neutrophil Gelatinase-Associated Lipocalin (NGAL) was discussed by applicating bioinformatics technology.Linear epitope molecules that have diagnostic value were screened and these recombinant linear multi-epitope peptides were constructed,and expressed.The immunogenicity of the recombinant linear multi-epitope peptides were also identified.Methods NGAL amino acid sequence was got from GenBank in the Department of Clinical Laboratory of the Second Affiliated Hospital of Nanjing Medical University in July 2015,the Predicted,ABCpred,BepiPred,BcePred,and Lasergene softwares were used to predict the linear B cell epitope prediction.The predict epitopes were constructed and prokaryotic expressed,and then the single epitope antigens which could reacted with commercially available polyclonal NGAL antibody were screened out by Western blot.Finally,the multi-epitope peptide was constructed,expressed,and identified through immunoreactions.Results Eight possible epitopes were obtained after prediction.pET32a-N1-N8 prokaryotic expression vector were used to express the predict epitopes.After purification and Western blot analysis,three of the epitopes have strong antigenicity,and then a soluble fusion protein was expressed and obtained from the multi-epitope prokaryotic expression vector pET22b-Ngal_MEP1.The fusion protein was successfully purified by Ni2 + affinity column.Western blot analysis showed that the fusion protein had a strong antigenicity.Conclusions The constructed multi-epitope linear NGAL antigen peptides can obtain high soluble expression in prokaryotic expression system,and have a strong immunoreactivity,which can be used in subsequent antibody preparation.
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Objective To investigate the effect of depression symptoms on surgical outcome of posterior decompression among cervical spondylotic myelopathy (CSM) patients. Methods Between October 2006 and October 2011 in our hospital, lami?nectomy or laminoplasty was performed in 396 cases that were enrolled in the study. There were 132 males and 264 females with an average age of 60.2 years(ranged,39-84 years). All patients were divided into depression group and non?depressed group by the 21?item Beck Depression Inventory (BDI). There were no statistically significant differences between groups in age, sex, smok?ing status, duration of symptoms, and employment status (whether in the current working). The Japanese Orthopedic Association (JOA) scores, Neck disability index (NDI) and visual analogue scale (VAS) were compared after 1.5 months postoperatively. Re?sults All of 396 cases were followed up. The mean follow up duration was 32 months (range,24-50 months). There were no statistically significant differences in the CCI decline (7.1%±2.1% versus 6.8%±1.5%), expansion degree[(130.9±7.0) mm2 versus (150.8 ± 5.2) mm2] and the drift?back distance of the spinal cord [(5.7 ± 1.2) mm versus (6.2 ± 0.8) mm]. However, pa?tients with continuous depression showed poorer improvement than non?depressed patients in the surgery outcome: JOA im?proved (1.42±0.56 versus 6.76±3.12); NDI declined (7.31±2.18 versus 21.11±11.36); and VAS lightened (16.08±19.76 versus 23.85±20.79). Conclusion Depression contributed a dissatisfied surgery outcome after posterior decompression on functional re?covery, disability index and pain scores among patients of the cervical spondylotic myelopathy.
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Golgi protein 73, a novel Golgi-localized transmembrane glycoprotein , is normally expressed in biliary epithelial cells of human tissues.Researches show that GP73 is overexpressed in many tumor tissues, such as hepatocellular carcinoma , prostate cancer, lung adenocarcinoma, renal cell cancer, and so on, which may play on important role in cancer diagnosis as a novel tumor marker.
