Research progress on diagnosis and treatment technology based on structural protein of SARS-CoV-2

Infectious diseases are a type of disease caused by pathogenic microorganisms. Although the discovery of antibiotics changed the treatment of infectious diseases and reduced the mortality of bacterial infections, resistant bacterial strains have emerged. Anti‐infective therapy based on aetiological evidence is the gold standard for clinical treatment, but the time lag and low positive culture rate of traditional methods of pathogen diagnosis leads to relative difficulty in obtaining the evidence of pathogens. Compared with traditional methods of pathogenic diagnosis, next‐generation and third‐generation sequencing technologies have many advantages in the detection of pathogenic microorganisms. In this review, we mainly introduce recent progress in research on pathogenic diagnostic technology and the applications of sequencing technology in the diagnosis of pathogenic microorganisms. This review provides new insights into the application of sequencing technology in the clinical diagnosis of microorganisms.

To analyze the role of artificial intelligence technology in the diagnosis and treatment of the COVID-19. To study the application progress and characteristics of artificial intelligence technology in CT image diagnosis, routine outpatient data diagnosis and complication prediction of COVID-19, and analyze the performance of the algorithm and the clinical benefits obtained in the process of diagnosis and treatment. The performance of artificial intelligence technology in assisted diagnosis of the diagnosis and prediction of complications is relatively satisfactory. Artificial intelligence technology can help medical institutions effectively alleviate the shortage of medical resources, improve diagnosis efficiency and treatment quality in the COVID-19 epidemic. Related models have good clinical application value.

Objective To explore research progress and application prospects of new MRI technologies in diagnosis and treatment of osteoarthritis. Methods A computer-based online search of Medline database was undertaken to identify the articles about cartilage injury/damage and cartilage quantitative MRI published in English from January 2004 to July 2014, with the key words ofCartilage injury/damage, osteoarthritis, T1ρmapping, Sodium MRI, magnetization transfer MRI, Chemical exchange saturation transfer, Ultrashort echo time MRI, DWI, DTI, Pharmacokinetic MRI. And the computer-based online search of CNKI database was also undertaken to identify relevant articles published in Chinese from January 2004 to July 2014 with the key words of软骨损伤,骨关节炎, T1ρ值,钠磁共振成像,磁化传递磁共振成像,化学交换依赖性饱和传递技术,扩散加权成像,扩散张量成像,药物代谢动力学磁共振成像. The first trial involved in 200 articles, and 86 articles of them referred to the experimental and clinical study of cartilage injury/damage and osteoarthritis. In which those had similar content and published on authority magazines in recent 5 years were preferred. Results Cartilage MRI and quantitative analysis have been one of the hot-point academic researchs. In recent years, with the enhancement of MRI hardware and software, the new technology has been applied to cartilage quantitative MRI analysis. In terms of early detection of cartilage damage and cartilage biochemical composition and vascular components, quantitative analysis of these new MRI technologies showed good application and research prospects, but there were still some inherent flaws. Conclusions With MR hardware and software upgrades, the development and application of new MRI sequences and deepening of theoretical studies using these new technologies, parameter values derived these new quantitative MRI analysis techniques may become MRI biomarkers in diagnosis and treatment of osteoarthritis in the future. Key words: Cartilage; Osteoarthritis; Magnetic resonance imaging; Parameter value

Research progress and the application of near-infrared spectroscopy in protein structure and molecular interaction analysis

Ultrasound technology is widely used in the diagnosis and evaluation of kidney diseases and in guiding some invasive procedures. Ultrasound has the advantages of low price, no radiation, convenience, and being easy to operate compared with other imaging methods. In recent years, new ultrasound technology has been developed. For example, studies have shown that ultrasound can protect against acute kidney injury and chronic kidney disease by activating the spleen cholinergic anti-inflammatory pathway. Through microbubble technology, contrast-enhanced ultrasound can more accurately assess the nature of renal lesions. Ultrasound-targeted microbubbles can also direct the release of drugs and genes to the lesions of interest. This article will review the research progress of ultrasound technology in the diagnosis and treatment of kidney diseases. Key words: Ultrasound; Kidney disease; Diagnosis and treatment; Progress

Extracellular matrix protein 1 (ECM1) has a variety of biological functions like promoting angiogenesis and endochondral bone formation.Recently, several studies reported that ECM1 protein is frequently overexpressed in many tumors, which associated with tumorigenesis and metastases. Thus, further studying the correlation between ECM1 and tumorigenesis may provide a novel therapeutic target for tumor treatment. This study aims to summarize the relationship between ECM1 and tumor. Key words: Extracelhlar matrix protein 1; Protein structure; Protein function; Tumor

Human parainfluenza viruses (hPIVs), a series of single-stranded RNA viruses of Paramyxoviridae, are the main pathogen of respiratory tract infection. hPIV3 is the main cause of lower respiratory tract infection leading to bronchiolitis and pneumonias in young children under the age of six months, and it is the second major pathogen only next to respiratory syncytial virus (RSV). In this paper, we mainly discuss two kinds of virulence-related surface glycoprotein of hPIV3: hemagglutinin-neuraminidase (HN) protein and fusion protein (F) by briefly introducing the protein structure and physiological functions of HN and F. According to the latest research progress, we focus on the models which have been postulated to explain how F and HN work in concert to bring about membrane fusion. Key words: Parainfluenza virus; HN protein; F protein; Interaction mechanism; Membrane fusion

Sepsis is caused by infection, which can ultimately lead to multiple organ dysfunction and even life-threatening. Early recognition and early treatment can significantly improve the prognosis of sepsis patients. However, the effect of using a single biomarker for early diagnosis of sepsis is still not ideal. In recent years, researchers have turned their attention to artificial intelligence technology for early diagnosis of sepsis. This paper briefly introduces the advantages and disadvantages of sepsis related inflammatory indicators, biomarkers, and scoring systems of disease severity for early identification of sepsis, and focuses on the research progress and limitations of artificial intelligence technology for early diagnosis of sepsis, aiming to seek new methods and ideas for early diagnosis of sepsis.

Multiparametric magnetic resonance imaging (mpMRI) has emerged as a first-line screening and diagnostic tool for prostate cancer, aiding in treatment selection and noninvasive radiotherapy guidance. However, the manual interpretation of MRI data is challenging and time-consuming, which may impact sensitivity and specificity. With recent technological advances, artificial intelligence (AI) in the form of computer-aided diagnosis (CAD) based on MRI data has been applied to prostate cancer diagnosis and treatment. Among AI techniques, deep learning involving convolutional neural networks contributes to detection, segmentation, scoring, grading, and prognostic evaluation of prostate cancer. CAD systems have automatic operation, rapid processing, and accuracy, incorporating multiple sequences of multiparametric MRI data of the prostate gland into the deep learning model. Thus, they have become a research direction of great interest, especially in smart healthcare. This review highlights the current progress of deep learning technology in MRI-based diagnosis and treatment of prostate cancer. The key elements of deep learning-based MRI image processing in CAD systems and radiotherapy of prostate cancer are briefly described, making it understandable not only for radiologists but also for general physicians without specialized imaging interpretation training. Deep learning technology enables lesion identification, detection, and segmentation, grading and scoring of prostate cancer, and prediction of postoperative recurrence and prognostic outcomes. The diagnostic accuracy of deep learning can be improved by optimizing models and algorithms, expanding medical database resources, and combining multi-omics data and comprehensive analysis of various morphological data. Deep learning has the potential to become the key diagnostic method in prostate cancer diagnosis and treatment in the future.

Neurosurgery is a vital branch of medicine that deals with the surgical management of brain disorders. The increasing demand for clinical solutions drives technological innovation, and the rapid progress in science and technology enables new discoveries, knowledge, techniques, and instruments in neurosurgery, expanding the scope and accuracy of diagnosis and treatment, and enhancing therapeutic outcomes. The author team combines domestic and international literature and previous clinical and scientific research experience, focusing on practical clinical problems in several subspecialties, including neuroimaging, neuronavigation and surgical robot assistance, central nervous system tumors, surgical treatment of cerebrovascular disease, functional neurosurgery, neuroinjury and neural repair, and digital neurosurgery. The paper summarizes in detail the research hotspots and puts forward the research direction prospects, including the innovative application of imaging technology, the development of fine surgery, the innovation of neuro-oncology diagnosis and treatment, the surgical standardization of cerebrovascular disease, the progress of neuromodulation, the individualized neurological alternative treatment and the digitalization of multi-dimensional information in neurosurgery.

Intensive dairying has diminished infectious disease resistance in dairy cattle and increased the risk of disorders affecting milk quality and productive life. Development of novel health monitoring technologies, optimization of disease treatment protocols using novel biomarkers, and development of antibiotic substitutes are necessary to further enhance the productivity of dairy cattle. Extracellular vesicles (EVs) are key mediators of cellular communication and are essential for maintaining intracellular homeostasis and regulating various physiological and pathological processes. Establishing a network of mechanisms by which EVs regulate physiological processes in dairy cattle will contribute to the development of new technologies for early disease diagnosis and disease treatment. This review summarizes the molecular characterization and advances in the study of EVs in dairy cattle and focuses on the reported mechanisms of action. Prospects and limitations for the application of EVs in monitoring health status, disease treatment and assisted reproduction are discussed.

With the progress of research on structural analysis of proteins, a large number of studies have been conducted on extracting the protein interaction information from literature. For automatic extraction of interaction information, the machine learning approach is useful. Generally, linguistic features obtained directly from the literature are used for learning, but a non-linguistic feature such as the atomic distance calculated from the protein structure data is often very effective for learning and classification. We call this type of feature a “key feature” in this study. In the machine learning approach, preparing enough training instances to train the classifier is important, but this often requires great cost. In such a situation, transfer learning is one of the better approaches. However, it is difficult to apply a simple transfer learning algorithm to a task in which the key feature cannot be prepared in the source domain. In this study, we propose a new transfer learning method called STEK (Selective Transfer learning based on Effectiveness of a Key feature). In this method, we focus on the effectiveness of the key feature, and divide a set of instances into two categories. One is a set of instances applying transfer learning and the other is a set of instances avoiding the use of transfer learning. The proposed method with the InstPrune algorithm showed stably high precision, recall and F-measure on average.

Infectious hypodermal and hematopoietic necrosis virus (IHHNV) is one of the major viral pathogens of penaeid shrimps worldwide, which has resulted in severe mortalities of up to 90% in cultured Penaeus (Litopenaeus) stylirostris from Hawaii and hence designated Penaeus stylirostris densovirus (PstDNV). IHHNV is distributed in shrimp culture facilities worldwide. It causes large economic loss to the shrimp farming industry. Our knowledge about the natural reservoirs of IHHNV is still scarce. Recent studies suggest that there is sufficient sequence variation among the isolates from different locations in Asia, suggesting multiple geographical strains of the virus. Four complete genomes and several partial sequences of the virus are available in the GenBank. Complete genome information would be useful for assessing the specificity of diagnostics for viruses from different geographical areas. Comparisons of complete genome sequences will help us gain insights into point mutations that can affect virulence of the virus. In addition, because of unavailability of shrimp cell lines for culturing IHHNV in vitro, quantification of virus is difficult. The recent progress in research regarding clinical signs, geographical distribution, complete genome sequence and genetic variation, transmission has made it possible to obtain information on IHHNV. A comprehensive understanding of IHHNV infection process, pathogenesis, structural proteins and replication is essential for developing prevention measures. To date, no effective prophylactic measure for IHHNV infection is available for shrimp to reduce its impact. This review provides an overview of key issues regarding IHHNV infection and disease in commercially important shrimp species.

The incidence rate of metabolic associated fatty liver disease (MAFLD) in our country has risen rapidly and has developed into the largest chronic liver disease with the rise of obesity and type 2 diabetes mellitus. Although obesity is closely related to the occurrence of MAFLD, there are still some MAFLD patients whose body mass index does not meet the criteria for obesity or overweight, which is referred to as lean MAFLD. With the continuous advancement of pathological mechanisms and clinical diagnosis and treatment technologies, relevant research on lean MAFLD has made certain progress. This article reviews the epidemiological status, pathological mechanisms and clinical diagnosis and treatment of lean MAFLD in detail.

Extraction, structure, pharmacological activities and applications of polysaccharides and proteins isolated from snail mucus