Enhancement of plasmid-mediated stable gene expression by woodchuck hepatitis virus post-transcriptional regulatory element (WPRE) in human embryonic kidney (HEK293) cells

Influence of random integration site on the expression of transgene in mammalian cells makes it a major challenge to achieve high productivity of recombinant proteins. Optimization of expression vector is one of the most popular strategies to resolve this problem. Among this, woodchuck hepatitis virus  post-transcriptional regulatory element (WPRE) is a possible enhancer of gene expression in mammalian  cells that promotes efficient export of unspliced (RNA) into the cytoplasm, as has been proved in  transient transfection. In this study, WPRE was evaluated for enhancing stable gene expression levels in two industrial cell lines, human embryonic kidney (HEK293) and CHO-S, using the enhanced green fluorescent protein (EGFP), prourokinase (pro-UK) and protein C (PC) as the reporter gene. Based on the mean fluorescence intensity (MFI), WPRE exerted a clear positive effect on gene expression in HEK293 cells with an increase of EGFP expression level by approximately 2.5- to 3-fold independent of the  promoter used in plasmid vector. In contrast, in Chinese hamster ovary (CHO)-S cells, only a marginal effect on plasmid-mediated EGFP expression by WPRE was observed. The measurable increase of EGFP expression at the protein level was paralleled by an increase of EGFP RNA. Further test of the effect of WPRE on plasmid-mediated gene expression with two therapeutic proteins showed substantial increase of stable pro-UK and PC expression only in HEK293 by about 2.2-fold and 6.1-fold, respectively. The data of PC expression levels obtained from the random HEK293 cell clones transfected with WPRE-containing or lacking vector further demonstrated the enhancement of stable plasmid-mediated gene expression by WPRE in HEK293 cells. These results in stable transfectants show the positive effect of WPRE on transgene expression is cell-type dependent and promoter-independent, and provide valuable information to improve vectors for efficient and stable gene expression in HEK293 cells.Key words: Mammalian cells, plasmid vector, stable gene expression, protein therapeutics, woodchuck hepatitis virus post-transcriptional regulatory element (WPRE)

A sample-position-autocorrection system with precision better than 1 \um~in angle-resolved photoemission experiments

We present the development of a high-precision sample-position-autocorrection system for photoemission experiments. A binocular vision method based on image pattern matching calculations was realized to track the sample position with an accuracy better than 1 \um, which was much smaller than the spot size of the incident laser. We illustrate the performance of the sample-position-autocorrection system with representative photoemission data on the topological insulator Bi$_2$Se$_3$ and an optimally-doped cuprate superconductor \Bi. Our method provides new possibilities for studying the temperature-dependent electronic structures in quantum materials by laser-based or spatially resolved photoemission systems with high precision and efficiency.Comment: 6 pages, 4 figure

USFM: A Universal Ultrasound Foundation Model Generalized to Tasks and Organs towards Label Efficient Image Analysis

Inadequate generality across different organs and tasks constrains the application of ultrasound (US) image analysis methods in smart healthcare. Building a universal US foundation model holds the potential to address these issues. Nevertheless, the development of such foundational models encounters intrinsic challenges in US analysis, i.e., insufficient databases, low quality, and ineffective features. In this paper, we present a universal US foundation model, named USFM, generalized to diverse tasks and organs towards label efficient US image analysis. First, a large-scale Multi-organ, Multi-center, and Multi-device US database was built, comprehensively containing over two million US images. Organ-balanced sampling was employed for unbiased learning. Then, USFM is self-supervised pre-trained on the sufficient US database. To extract the effective features from low-quality US images, we proposed a spatial-frequency dual masked image modeling method. A productive spatial noise addition-recovery approach was designed to learn meaningful US information robustly, while a novel frequency band-stop masking learning approach was also employed to extract complex, implicit grayscale distribution and textural variations. Extensive experiments were conducted on the various tasks of segmentation, classification, and image enhancement from diverse organs and diseases. Comparisons with representative US image analysis models illustrate the universality and effectiveness of USFM. The label efficiency experiments suggest the USFM obtains robust performance with only 20% annotation, laying the groundwork for the rapid development of US models in clinical practices.Comment: Submit to MedIA, 17 pages, 11 figure

Ultrafast Switching from the Charge Density Wave Phase to a Metastable Metallic State in 1T-TiSe2_2

The ultrafast electronic structures of the charge density wave material 1T-TiSe$_2$ were investigated by high-resolution time- and angle-resolved photoemission spectroscopy. We found that the quasiparticle populations drove ultrafast electronic phase transitions in 1T-TiSe$_2$ within 100 fs after photoexcitation, and a metastable metallic state, which was significantly different from the equilibrium normal phase, was evidenced far below the charge density wave transition temperature. Detailed time- and pump-fluence-dependent experiments revealed that the photoinduced metastable metallic state was a result of the halted motion of the atoms through the coherent electron-phonon coupling process, and the lifetime of this state was prolonged to picoseconds with the highest pump fluence used in this study. Ultrafast electronic dynamics were well captured by the time-dependent Ginzburg-Landau model. Our work demonstrates a mechanism for realizing novel electronic states by photoinducing coherent motion of atoms in the lattice.Comment: 13 Pages, 10 figure

Effectiveness of artificial intelligence-assisted ultrasound for breast cancer screening in Chinese women

Background and purpose: Artificial intelligence (AI) technology is increasingly being used in the medical field. This study aimed to assess the effectiveness of artificial intelligence ultrasound system for identifying breast lesions in Chinese women and its role in breast cancer early detection. Methods: A prospective study was conducted on healthy women aged 35-74 years who came to Fudan University Shanghai Cancer Center from August 2020 to December 2020 for breast ultrasonography. All the women were examined by AI-assisted ultrasound first, and then by conventional ultrasonography. We compared the differences between AI-assisted ultrasound and conventional ultrasonography in identifying breast lesions in Chinese women. One year later, we looked up the hospital medical history and Shanghai Cancer Registration Management System for the final diagnosis of breast cancer. Results: A total of 360 women were included in the study and received breast examinations using both AI-assisted ultrasound and conventional ultrasound. A total of 2 504 breast lesions were detected, of which, 2 217 were detected by AI-assisted ultrasound, with a lesion recognition rate of 88.5%. Conventional ultrasound identified 1 090 lesions, with a lesion recognition rate of 43.5%. Using conventional ultrasound as the standard, the sensitivity and specificity of AI-assisted ultrasound for Breast Imaging Reporting and Data System (BI-RADS) level 4 and above lesions were 93.3% (95% CI: 80.7-98.3) and 100.0% (95% CI: 99.5-100.0), respectively. During one-year follow-up, 10 patients were diagnosed with breast cancer, and 8 of whom were identified by both AI-assisted ultrasound and conventional B ultrasound. The sensitivity of AI-assisted ultrasound and conventional ultrasound for breast cancer was 80.0% (95% CI: 44.2-96.4), and the specificity was 88.6% (95% CI: 84.6-91.6). Conclusion: AI-assisted ultrasound has good identification ability for breast lesions in Chinese women. The recognition ability for high-risk breast lesions (BI-RADS 4A and above) and early breast cancer is equivalent to that of conventional ultrasound, which is suitable for breast cancer screening in large-scale community of women with general risk

Radiogenomic Analysis of Papillary Thyroid Carcinoma for Prediction of Cervical Lymph Node Metastasis: A Preliminary Study

Background Papillary thyroid carcinoma (PTC) is characterized by frequent metastases to cervical lymph nodes (CLNs), and the presence of lymph node metastasis at diagnosis has a significant impact on the surgical approach. Therefore, we established a radiomic signature to predict the CLN status of PTC patients using preoperative thyroid ultrasound, and investigated the association between the radiomic features and underlying molecular characteristics of PTC tumors. Methods In total, 270 patients were enrolled in this prospective study, and radiomic features were extracted according to multiple guidelines. A radiomic signature was built with selected features in the training cohort and validated in the validation cohort. The total protein extracted from tumor samples was analyzed with LC/MS and iTRAQ technology. Gene modules acquired by clustering were chosen for their diagnostic significance. A radiogenomic map linking radiomic features to gene modules was constructed with the Spearman correlation matrix. Genes in modules related to metastasis were extracted for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and a protein-protein interaction (PPI) network was built to identify the hub genes in the modules. Finally, the screened hub genes were validated by immunohistochemistry analysis. Results The radiomic signature showed good performance for predicting CLN status in training and validation cohorts, with area under curve of 0.873 and 0.831 respectively. A radiogenomic map was created with nine significant correlations between radiomic features and gene modules, and two of them had higher correlation coefficient. Among these, MEmeganta representing the upregulation of telomere maintenance via telomerase and cell-cell adhesion was correlated with 'Rectlike' and 'deviation ratio of tumor tissue and normal thyroid gland' which reflect the margin and the internal echogenicity of the tumor, respectively. MEblue capturing cell-cell adhesion and glycolysis was associated with feature 'minimum calcification area' which measures the punctate calcification. The hub genes of the two modules were identified by protein-protein interaction network. Immunohistochemistry validated that LAMC1 and THBS1 were differently expressed in metastatic and non-metastatic tissues (p=0.003; p=0.002). And LAMC1 was associated with feature 'Rectlike' and 'deviation ratio of tumor and normal thyroid gland' (p<0.001; p<0.001); THBS1 was correlated with 'minimum calcification area' (p<0.001). Conclusions The radiomic signature proposed here has the potential to noninvasively predict the CLN status in PTC patients. Merging imaging phenotypes with genomic data could allow noninvasive identification of the molecular properties of PTC tumors, which might support clinical decision making and personalized management

Smyd3 regulates cancer cell phenotypes and catalyzes histone H4 lysine 5 methylation

Smyd3 is a lysine methyltransferase implicated in chromatin and cancer regulation. Here we show that Smyd3 catalyzes histone H4 methylation at lysine 5 (H4K5me). This novel histone methylation mark is detected in diverse cell types and its formation is attenuated by depletion of Smyd3 protein. Further, Smyd3-driven cancer cell phenotypes require its enzymatic activity. Thus, Smyd3, via H4K5 methylation, provides a potential new link between chromatin dynamics and neoplastic disease

Finishing of Additively Manufactured Metal Parts by Abrasive Flow Machining

Surface finishing is still a crucial challenge in metal Additive Manufacturing (AM) as the as-built surface roughness is difficult to fulfill service requirements, due to staircase effect, balling effect inherent to AM. Abrasive flow machining (AFM) is a non-conventional finishing technique that offers better accuracy and efficiency for parts with difficult-to-access structures, and the application of AFM to finishing metal parts of AM process is discussed in this paper. The aluminum and titanium grilles by selective laser melting are taken to explore the finishing effect of outer and inner surfaces. The AFM process parameters of abrasive grits sizes, abrasive media viscosity, and tooling designs are optimized to implement effective material removal from the outer and inner surfaces. The results show that the AM grille parts with non-trial internal structures can be finished efficiently and consistently by AFM.Mechanical Engineerin

Vibration and acoustic noise emitted by dry-type air-core reactors under PWM voltage excitation

According to coupling way between the magnetic field and the structural order, structure mode is discussed by engaging finite element (FE) method and both natural frequency and modal shape for a dry-type air-core reactor (DAR) are obtained in this paper. On the basis of harmonic response analysis, electromagnetic force under PWM (Pulse Width Modulation) voltage excitation is mapped with the structure mesh, the vibration spectrum is gained and the consequences represents that the whole structure vibration predominates in the radial direction, with less axial vibration. Referring to the test standard of reactor noise, the rules of emitted noise of the DAR are measured and analyzed at chosen switching frequency matches the sample resonant frequency and the methods of active vibration and noise reduction are put forward. Finally, the low acoustic noise emission of a prototype DAR is verified by measurement