OBJECTIVETo investigate the point mutations and polymorphisms of transforming growth factor beta-induced gene (TGFBI) in Chinese patients with keratoconus and discuss the relationship between the feature of gene mutations and single nucleotide polymorphisms of TGFBI gene and keratoconus.

METHODSPolymerase chain reaction single strand conformation polymorphism and DNA direct sequencing were performed in 30 keratoconus cases and 30 healthy controls. All 17 exons of the TGFBI gene were analyzed for point mutations and single nucleotide polymorphisms.

RESULTSTotally two heterozygous nucleotide changes were identified in exon 12 of the TGFBI gene. The codon 535 is changed from GGA to TGA in 1 patient, leading to a substitution of glycine to a stop codon at the protein level (G535X). The codon 540 is changed from TTT to TTC in 2 patients and 1 control individual, resulting in a nonsense mutation (F54F), and is a single nucleotide polymorphism of the gene.

CONCLUSIONMutation and polymorphisms of the TGFBI gene were detected in Chinese patients with keratoconus in this study. The results suggest that TGFBI gene might play an important role in the pathogenesis of keratoconus.

Adolescent ; Adult ; Case-Control Studies ; Child ; China ; Extracellular Matrix Proteins ; genetics ; Female ; Glycine ; deficiency ; genetics ; Humans ; Keratoconus ; genetics ; Male ; Middle Aged ; Point Mutation ; Polymerase Chain Reaction ; methods ; Polymorphism, Single Nucleotide ; Polymorphism, Single-Stranded Conformational ; Sequence Analysis, DNA ; methods ; Transforming Growth Factor beta ; genetics ; Young Adult

Objective: Stem cell?based therapies are promising in regenerative medicine for protecting and repairing damaged brain tissues after injury or in the context of chronic diseases. Hypoxia can induce physiological and pathological responses. A hypoxic insult might act as a double?edged sword, it induces cell death and brain damage, but on the other hand, sublethal hypoxia can trigger an adaptation response called hypoxic preconditioning or hypoxic tolerance that is of immense importance for the survival of cells and tissues. Data Sources: This review was based on articles published in PubMed databases up to August 16, 2017, with the following keywords:"stem cells," "hypoxic preconditioning," "ischemic preconditioning," and "cell transplantation."Study Selection: Original articles and critical reviews on the topics were selected. Results: Hypoxic preconditioning has been investigated as a primary endogenous protective mechanism and possible treatment against ischemic injuries. Many cellular and molecular mechanisms underlying the protective effects of hypoxic preconditioning have been identified. Conclusions: In cell transplantation therapy, hypoxic pretreatment of stem cells and neural progenitors markedly increases the survival and regenerative capabilities of these cells in the host environment, leading to enhanced therapeutic effects in various disease models. Regenerative treatments can mobilize endogenous stem cells for neurogenesis and angiogenesis in the adult brain. Furthermore, transplantation of stem cells/neural progenitors achieves therapeutic benefits via cell replacement and/or increased trophic support. Combinatorial approaches of cell?based therapy with additional strategies such as neuroprotective protocols, anti?inflammatory treatment, and rehabilitation therapy can significantly improve therapeutic benefits. In this review, we will discuss the recent progress regarding cell types and applications in regenerative medicine as well as future applications.

The portable light-weight magnetic resonance imaging system can be deployed in special occasions such as Intensive Care Unit (ICU) and ambulances, making it possible to implement bedside monitoring imaging systems, mobile stroke units and magnetic resonance platforms in remote areas. Compared with medium and high field imaging systems, ultra-low-field magnetic resonance imaging equipment utilizes light-weight permanent magnets, which are compact and easy to move. However, the image quality is highly susceptible to external electromagnetic interference without a shielded room and there are still many key technical problems in hardware design to be solved. In this paper, the system hardware design and environmental electromagnetic interference elimination algorithm were studied. Consequently, some research results were obtained and a prototype of portable shielding-free 50 mT magnetic resonance imaging system was built. The light-weight magnet and its uniformity, coil system and noise elimination algorithm and human brain imaging were verified. Finally, high-quality images of the healthy human brain were obtained. The results of this study would provide reference for the development and application of ultra-low-field magnetic resonance imaging technology.
Humans ; Magnetic Resonance Imaging/methods* ; Magnetic Resonance Spectroscopy/methods* ; Head ; Equipment Design ; Magnets

Hypertension and its associated cardiovascular diseases such as stroke and ischemic heart disease result in a high burden of disease and health losses, making it the most burdensome disease in the world and one of the important public health issues in China. Currently Chinese scholars have carried out a large number of studies on the prevalence of hypertension, including regional and national prevalence studies. However, long-term follow-up studies on incidence of hypertension are relatively few and mostly limited to specific ages and regions. This paper summarizes the prevalence, incidence and epidemiological trend of hypertension in Chinese adults. The hypertension prevalence increased from 5.1% in 1959 to 27.5% in 2018, and presents an overall trend of high in the north and low in the south. The hypertension incidence is at a high level (the cumulative incidence was 33.4% after 22 years-follow-up), but there are few researches on the trend of hypertension incidence in huge region.

Computer-aided diagnosis (CAD) systems play a very important role in modern medical diagnosis and treatment systems, but their performance is limited by training samples. However, the training samples are affected by factors such as imaging cost, labeling cost and involving patient privacy, resulting in insufficient diversity of training images and difficulty in data obtaining. Therefore, how to efficiently and cost-effectively augment existing medical image datasets has become a research hotspot. In this paper, the research progress on medical image dataset expansion methods is reviewed based on relevant literatures at home and abroad. First, the expansion methods based on geometric transformation and generative adversarial networks are compared and analyzed, and then improvement of the augmentation methods based on generative adversarial networks are emphasized. Finally, some urgent problems in the field of medical image dataset expansion are discussed and the future development trend is prospected.
Humans ; Diagnosis, Computer-Assisted ; Diagnostic Imaging ; Datasets as Topic

We reported a 32 years female patient in whom lung metastasis from breast cancer was presented as solitary pulmonary pure ground-glass opacity (GGO) lesion. The patient received rational preoperative examinations and surgery though the preoperative diagnosis was not accurate. Because of different therapy strategies and purposes, it is crucial to make distinction of atypical metastases from primary cancers. Thus, for patients with a history of malignancy, possible metastasis should be taken into consideration if new GGO was found on the CT. Besides this, the follow-up interval of CT should be shortened appropriately, preoperative examinations and surgical procedures should be made according to the suggestions of multidisciplinary team.

Medical image segmentation based on deep learning has become a powerful tool in the field of medical image processing. Due to the special nature of medical images, image segmentation algorithms based on deep learning face problems such as sample imbalance, edge blur, false positive, false negative, etc. In view of these problems, researchers mostly improve the network structure, but rarely improve from the unstructured aspect. The loss function is an important part of the segmentation method based on deep learning. The improvement of the loss function can improve the segmentation effect of the network from the root, and the loss function is independent of the network structure, which can be used in various network models and segmentation tasks in plug and play. Starting from the difficulties in medical image segmentation, this paper first introduces the loss function and improvement strategies to solve the problems of sample imbalance, edge blur, false positive and false negative. Then the difficulties encountered in the improvement of the current loss function are analyzed. Finally, the future research directions are prospected. This paper provides a reference for the reasonable selection, improvement or innovation of loss function, and guides the direction for the follow-up research of loss function.
Algorithms ; Image Processing, Computer-Assisted

OBJECTIVETo establish a polymerase chain reaction sequencing-based typing (PCR SBT) method for HLA-DPB1 exons 2 and 3, and to analyze their polymorphisms.

METHODSBased on the sequences of HLA-DPB1 loci, locus-specific primers were designed and applied to amplify the target sequences encompassing the entire exons 2 and 3 of HLA-DPB1. The amplification products were digested by enzymes and directly sequenced in both directions. The genotype was assigned by Assign 3.5+ SBT software.

RESULTSSpecific target fragment was obtained with the PCR amplification, and good quality electropherogram was derived by direct sequencing. Among 242 individuals from Zhejiang Han population, 18 HLA-DPB1 alleles were detected. Alleles with a frequency of > 0.05 have included DPB1*05:01:01/135:01 (0.4112), DPB1*02:01:02 (0.1901), DPB1*04:01:01 (0.1136) and DPB1*02:02 (0.0620). A novel HLA-DPB1*168:01 allele has also been identified. Nine polymorphism sites were founded in the exon 3 region, which included a new SNP site 517 A>T.

CONCLUSIONThe PCR-SBT method for exons 2 and 3 of HLA-DPB1 is reliable, which allowed detection of polymorphisms in exon 3 of the HLA-DPB1 gene.

Alleles ; Exons ; HLA-DP beta-Chains ; genetics ; Humans ; Polymerase Chain Reaction ; Polymorphism, Genetic

Objective To explore the diagnosis and treatment strategies for elderly patients with ground-glass opacity (GGO). Methods The imaging features and postoperative pathological findings of the elderly patients with pulmonary GGO receiving surgery in our hospital from 2017 to 2019 were retrospectively analyzed. The patients were divided into an elderly patient group and a non-elderly patient group based on their age. Results Finally 575 patients were included in the study. There were 281 elderly patients, including 83 males and 198 females, with an average age of (67.0±5.3) years. There were 294 non-elderly patients, including 88 males and 206 females, with an average age of (49.1±7.3) years. Compared with the non-elderly patients, elderly GGO patients showed the following distinct clinical features: long observation time for lesions (P=0.001), high proportion of rough edges of GGO (P<0.001), significant pleural signs (P＜0.001) and bronchial signs (P＜0.001), and high proportion of type Ⅱ-Ⅳ GGO (P<0.001), lobectomy type (P=0.013), and invasive lesions reported in postoperative pathology (P<0.001). There was no statistical difference in the average hospital stay between the two groups (P=0.106). Multivariate logistic regression analysis showed that GGO diameter and GGO type were the main factors affecting the operation. Observation time, GGO diameter, GGO type and pleural signs were the main influencing factors for postoperative pathological infiltrative lesions. The cut-off value of GGO diameter in predicting infiltrating lesions was 10.5 mm in the elderly patients group. Conclusion The size and type of GGO are important factors in predicting invasive lesions and selecting surgical methods. Elderly patients with radiographic manifestations of type Ⅱ-Ⅳ GGO lesions with a diameter greater than 10.5 mm should be closely followed up.

Corona virus disease 2019 (COVID-19) is an acute respiratory infectious disease with strong contagiousness, strong variability, and long incubation period. The probability of misdiagnosis and missed diagnosis can be significantly decreased with the use of automatic segmentation of COVID-19 lesions based on computed tomography images, which helps doctors in rapid diagnosis and precise treatment. This paper introduced the level set generalized Dice loss function (LGDL) in conjunction with the level set segmentation method based on COVID-19 lesion segmentation network and proposed a dual-path COVID-19 lesion segmentation network (Dual-SAUNet++) to address the pain points such as the complex symptoms of COVID-19 and the blurred boundaries that are challenging to segment. LGDL is an adaptive weight joint loss obtained by combining the generalized Dice loss of the mask path and the mean square error of the level set path. On the test set, the model achieved Dice similarity coefficient of (87.81 ± 10.86)%, intersection over union of (79.20 ± 14.58)%, sensitivity of (94.18 ± 13.56)%, specificity of (99.83 ± 0.43)% and Hausdorff distance of 18.29 ± 31.48 mm. Studies indicated that Dual-SAUNet++ has a great anti-noise capability and it can segment multi-scale lesions while simultaneously focusing on their area and border information. The method proposed in this paper assists doctors in judging the severity of COVID-19 infection by accurately segmenting the lesion, and provides a reliable basis for subsequent clinical treatment.
Humans ; COVID-19/diagnostic imaging* ; Respiratory Rate ; Tomography, X-Ray Computed