A preliminary study to establish the transfected CHO cell lines which highly express Trastuzumab - A biosimilar product of Herceptin

Human epidermal growth factor receptor 2 (HER2) has been identified as a molecular target for breast cancer therapy, such as Trastuzumab (Herceptin®). This has been shown to improve patient survival substantially. The current study is aiming to locally produce an anti-HER2 monoclonal antibody (named Trastuzumab) which has an equivalent biological properties in comparison with the original version, Herceptin®). In silico design and construction of recombinant vectors, as well as the establishment of transfected cell lines with high expression of Trastuzumab were performed. Based on the protein sequences obtained from the Drugbank, the DNA sequences encoding for the light chain (Tras-Lc) and heavy chain (Tras-Hc) of Trastuzumab were optimized and integrated into pNanogen-Hygro and pNanogen-Puro vectors, respectively. The Neon Transfection System was used to co-transfect the pNanogen-Tras-Lc-Hygro and pNanogen-Tras-Hc-Puro constructs into CHO cells. Different co-transfected single-cell-colonies selected on media supplemented with hygromycin and puromycin were used for ELISA and SDS-PAGE assays to identify the CHO cell lines which highly express Trastuzumab. Based on the present results, 30μg of both constructs were suitable for DNA co-transfection. After 07 days of culture, the highest amount of Trastuzumab (561 µg/ml) was obtained from the H06LD68 cell line

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Liver Tumor Segmentation from MR Images Using 3D Fast Marching Algorithm and Single Hidden Layer Feedforward Neural Network

Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI) image which contains the liver tumor region in the T1-weighted MR image series was extracted by using seed points. The noise in this ROI image was reduced and the boundaries were enhanced. A 3D fast marching algorithm was applied to generate the initial labeled regions which are considered as teacher regions. A single hidden layer feedforward neural network (SLFN), which was trained by a noniterative algorithm, was employed to classify the unlabeled voxels. Finally, the postprocessing stage was applied to extract and refine the liver tumor boundaries. The liver tumors determined by our scheme were compared with those manually traced by a radiologist, used as the “ground truth.” Results. The study was evaluated on two datasets of 25 tumors from 16 patients. The proposed scheme obtained the mean volumetric overlap error of 27.43% and the mean percentage volume error of 15.73%. The mean of the average surface distance, the root mean square surface distance, and the maximal surface distance were 0.58 mm, 1.20 mm, and 6.29 mm, respectively

Fresh and hardened properties of high-performance fiber-reinforced concrete containing fly ash and rice husk ash: Influence of fiber type and content

Although fibers are used only infrequently as an additive in concrete in the construction industry, fiber-enhanced concrete is known to provide a wide range of advantages over conventional concrete. The main objective of this study was to investigate the influences of fiber type and content on the mechanical properties and durability of high-performance fiber-reinforced concrete (HPFRC) designed using a novel densified mixture design algorithm with fly ash and rice husk ash. Three types of fiber, including polypropylene (PP) fiber, steel fiber (SF), and hybrid fiber (HF), were considered. Based on the results, the inclusion of fibers decreased HPFRC flowability, regardless of fiber type. Although the compressive strength of HPFRC with 1.6% PP fiber content was 11.2% below that of the reference HPFRC specimen at 91 d of curing age, the 91-d compressive strengths of both SF and HF-enhanced HPFRC specimens were significantly better than that of the reference HPFRC specimen. Furthermore, the HPFRC specimens incorporating SF and HF both exhibited better splitting tensile and flexural strengths as well as less drying shrinkage than the HPFRC specimens incorporating PP fiber. However, the fiber-enhanced specimens, especially those with added SF, registered less surface electrical resistivity and greater vulnerability to chloride ion penetration than the reference HPFRC specimen.Web of Science16121632162

Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks

Abstract Background Cell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation atlas to TOO detection in low depth cfDNA samples. Methods We constructed a tumor-specific methylation atlas (TSMA) using whole-genome bisulfite sequencing (WGBS) data from five types of tumor tissues (breast, colorectal, gastric, liver and lung cancer) and paired white blood cells (WBC). TSMA was used with a non-negative least square matrix factorization (NNLS) deconvolution algorithm to identify the abundance of tumor tissue types in a WGBS sample. We showed that TSMA worked well with tumor tissue but struggled with cfDNA samples due to the overwhelming amount of WBC-derived DNA. To construct a model for TOO, we adopted the multi-modal strategy and used as inputs the combination of deconvolution scores from TSMA with other features of cfDNA. Results Our final model comprised of a graph convolutional neural network using deconvolution scores and genome-wide methylation density features, which achieved an accuracy of 69% in a held-out validation dataset of 239 low-depth cfDNA samples. Conclusions In conclusion, we have demonstrated that our TSMA in combination with other cfDNA features can improve TOO detection in low-depth cfDNA samples

Effect of calophyllolide on myeloperoxidase (MPO) activity.

<p>All mice were sacrificed on day 1 and day 5 post-operation, and skin tissue samples were collected to assess MPO activity (n = 3 mice per group per experiment). Data are represented as mean ± SEM and compared by one-way ANOVA. *** P<0.001.</p

Effect of calophyllolide on HaCaT and RAW264.7 cell viability.

<p>HPLC chromatograms of the isolated calophyollide <b>(A)</b> and standard control <b>(B)</b>. This compound was recorded at 233 nm, and its retention time is 36.6 min. <b>(C)</b> No effect of CP on the viability of both HaCaT and murine macrophage RAW264.7 cells after 24 h treatment.</p

Anti-inflammatory and wound healing activities of calophyllolide isolated from <i>Calophyllum inophyllum</i> Linn

<div><p>Due to the high-cost and limitations of current wound healing treatments, the search for alternative approaches or drugs, particularly from medicinal plants, is of key importance. In this study, we report anti-inflammatory and wound healing activities of the major calophyllolide (CP) compound isolated from <i>Calophyllum inophyllum</i> Linn. The results showed that CP had no effect on HaCaT cell viability over a range of concentrations. CP reduced fibrosis formation and effectively promoted wound closure in mouse model without causing body weight loss. The underlying molecular mechanisms of wound repair by CP was investigated. CP markedly reduced MPO activity, and increased M2 macrophage skewing, as shown by up-regulation of M2-related gene expression, which is beneficial to the wound healing process. CP treatment prevented a prolonged inflammatory process by down-regulation of the pro-inflammatory cytokines—IL-1β, IL-6, TNF-α, but up-regulation of the anti-inflammatory cytokine, IL-10. This study is the first to indicate a plausible role for CP in accelerating the process of wound healing through anti-inflammatory activity mechanisms, namely, by regulation of inflammatory cytokines, reduction in MPO, and switching of macrophages to an M2 phenotype. These findings may enable the utilization of CP as a potent therapeutic for cutaneous wound healing.</p></div