Objective:To discuss the dynamic three-dimensional reconstruction of tissue Doppler ultrasound cardiac image.Methods: To separate anatomical structure and function parameter information from Doppler ultrasound medical image, and then combines with the three-dimensional distribution to reconstruct it and fuse imaging.Results: Ultimately, it reveals the relationship between function parameter and anatomical structure. The dynamic three-dimensional reconstruction of tissue Doppler ultrasound cardiac image is also expounded in this paper.Conclusion: It scientifically completed the dynamic three-dimensional reconstruction of tissue Doppler ultrasound cardiac image by combining both tissue Doppler imaging and ultrasound medical image reconstruction technique. It is of great significance in clinical medicine.

Chinese medicine and Tibetan medicine both belong to the traditional medicine, and have their unique background and theoretical systems. There are similar features and differences in diagnosis of disease, syndrome and treatment between Chinese medicine and Tibetan medicine. Tibetan Zhenbu disease is common and frequently-occurring in plateau area with high morbidity, which is corresponding to rheumatoid arthritis in modern medicine and the category of Bi syndrome in Chinese medicine. During a long period of clinical efficacy verification, Tibetan treatment of Zhenbu disease presents to be little side effects, good curative effect, safe and economic etc. In the review, according to the introduction of Tibetan medicine and Chinese medicine, Zhenbu disease of Tibetan medicine and Chinese Bi syndrome will be compared in their pathogeneses and treatments to understand advantages and peculiarities of Tibetan medicine. The development of Tibentan medicine in the future will also be pointed out.

OBJECTIVE:To optimize the extraction technology of Duoxuekang. METHODS:Using comprehensive score of salidroside,gallic acid content and extraction yield as indexes,U6(63)uniform design was designed to optimize the liquid-solid ra-tio,ethanol volume fraction and extraction time of Duoxuekang,then optimize extraction times,and verification test was conduct-ed. RESULTS:The optimal extraction technology was as follows as 50% ethanol,liquid-solid ratio of 1:14,soaking time of 1.5 h,reflux extraction for 1 h and repeated twice;the average extraction yield in 3 tests was 50.18%,contents of salidroside and gal-lic acid were 1.82 mg/g,16.54 mg/g (RSD≤0.84%,n=3). CONCLUSIONS:The optimized extraction technology for Duox-uekang is reasonable,simple and feasible.

Objective To construct lentivirus vectors carrying 16 short hairpin RNA (shRNA) expression cassettes targeting histone acetyltransferases and provide a powerful research approach to explore the mechanism of epigenetic genes in regulating hepatitis B virus (HBV).Methods Following the rule of short shRNA primer design,eight-pair primers (A ~ H )for each gene,which had stable interfering efficiency,were designed.The annealed primers were connected to the empty lentiviral vectors of shRNA for transformation.In order to confirm the positive clones,clones were analyzed by real-time polymerase chain reaction (RT-PCR ).Then, qualified plasmids were verified by enzyme digestion technology.Four shRNA lentivirus plasmids against the same gene were mixed to build lentivirus respectively.After the virus transfected into 293T cells for 48 and 72 hours,supernatants were collected to infect HepG2.2.15 cells.The percentage of fluorescent cells were observed and assessed by microscope 72 hours after infection.Results One hundred and twenty-eight lentiviral vectors of RNA interference (RNAi)library were constructed against 16 histone acetyltransferases and more than 80% of HepG2.2.15 cells were infected with lentivirus 72 hours after infection.Conclusions Sixteen shRNA lentivirus vectors against histone acetyltransferase are successfully constructed.Thus,a solid foundation for the study of the effect of human histone deacetylase on HBV replication is established.

Objective To construct a COVID-19 CT image classification model based on lightweight RG DenseNet.Methods A RG-DenseNet model was constructed by adding channel and spatial attention modules to DenseNet121 for minimizing the interference of irrelevant features,and replacing Bottleneck module in DenseNet with pre-activated RG beneck2 module for reducing model parameters while maintaining accuracy as much as possible.The model performance was verified with 3-category classification experiments on the COVIDx CT-2A dataset.Results RG-DenseNet had an accuracy,precision,recall rate,specificity,and F1-score of 98.93%,98.70%,98.97%,99.48%,and 98.83%,respectively.Conclusion Compared with the original model DenseNet121,RG-DenseNet reduces the number of parameters and the computational complexity by 92.7%,while maintaining an accuracy reduction of only 0.01%,demonstrating a significant lightweight effect and high practical application value.

Lung adenocarcinoma is a prevalent histological subtype of non-small cell lung cancer with different morphologic and molecular features that are critical for prognosis and treatment planning. In recent years, with the development of artificial intelligence technology, its application in the study of pathological subtypes and gene expression of lung adenocarcinoma has gained widespread attention. This paper reviews the research progress of machine learning and deep learning in pathological subtypes classification and gene expression analysis of lung adenocarcinoma, and some problems and challenges at the present stage are summarized and the future directions of artificial intelligence in lung adenocarcinoma research are foreseen.

Objective: To quantitatively evaluate the adaptation of polylactic acid (PLA) pattern of mandibular complete denture fabricated by fused deposition modeling (FDM) technology. Methods: A mandibular complete denture digital model was designed through a complete denture design software based on a pair of standard maxillomandibular edentulous plaster model and their occlusion bases. Ten PLA mandibular complete dentures were printed with a FDM machine. The dentures were scanned with and without the plaster model using a three-dimensional (3D) scanner. In Geomagic software, the scanning data of printed dentures were registered to its computer aided design (CAD) data, and the printing error was analyzed using the multipoint registration command. For quantitatively evaluating the adaptation of the denture, the data of plaster model and PLA denture were registered to the whole data of denture located in the plaster model using the best-fit alignment command, the 3D deviation of the plaster model and tissue surface of the denture represent the space between them. The overall area was separated into three parts: primary stress-bearing area, secondary stress-bearing area and border seal area, and the average deviations of these three parts were measured. The values were analyzed using analysis of variance. Results: Compared with the CAD data, the printing error was (0.013±0.004) mm. The overall 3D deviation between PLA denture and plaster model was (0.164±0.033) mm, in which the primary stress-bearing area was (0.165± 0.045) mm, the secondary stress-bearing area was (0.153 ± 0.027) mm, the border seal area was (0.186 ± 0.043) mm. These showed a good fit in the majority parts of the FDM denture to the plaster model. No statistically significant difference was observed between the three areas (F=1.857, P=0.175>0.05). Conclusions Combined with the 3D scanning, CAD and FDM technology, a FDM 3D printing process of complete denture for injection moulding can be established. As a result, high efficiency and low cost can be used to print out the complete denture, to lay the basis for further clinical applications.