A Fully-Human Antibody Specifically Targeting a Membrane-Bound Fragment of CADM1 Potentiates the T Cell-Mediated Death of Human Small-Cell Lung Cancer Cells

Small-cell lung cancer (SCLC) is the most aggressive form of lung cancer and the leading cause of global cancer-related mortality. Despite the earlier identification of membrane-proximal cleavage of cell adhesion molecule 1 (CADM1) in cancers, the role of the membrane-bound fragment of CAMD1 (MF-CADM1) is yet to be clearly identified. In this study, we first isolated MF-CADM1-specific fully human single-chain variable fragments (scFvs) from the human synthetic scFv antibody library using the phage display technology. Following the selected scFv conversion to human immunoglobulin G1 (IgG1) scFv-Fc antibodies (K103.1–4), multiple characterization studies, including antibody cross-species reactivity, purity, production yield, and binding affinity, were verified. Finally, via intensive in vitro efficacy and toxicity evaluation studies, we identified K103.3 as a lead antibody that potently promotes the death of human SCLC cell lines, including NCI-H69, NCI-H146, and NCI-H187, by activated Jurkat T cells without severe endothelial toxicity. Taken together, these findings suggest that antibody-based targeting of MF-CADM1 may be an effective strategy to potentiate T cell-mediated SCLC death, and MF-CADM1 may be a novel potential therapeutic target in SCLC for antibody therapy.     

The Role of Polymorphisms at the Interleukin-1, Interleukin-4, GATA-3 and Cyclooxygenase-2 Genes in Non-Surgical Periodontal Therapy

Periodontitis is a multifactorial disease. The aim of this explorative study was to investigate the role of Interleukin-(IL)-1, IL-4, GATA-3 and Cyclooxygenase-(COX)-2 polymorphisms after non-surgical periodontal therapy with adjunctive systemic antibiotics (amoxicillin/metronidazole) and subsequent maintenance in a Caucasian population. Analyses were performed using blood samples from periodontitis patients of a multi-center trial (ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00707369","term_id":"NCT00707369"}}NCT00707369=ABPARO-study). Polymorphisms were analyzed using quantitative real-time PCR. Clinical attachment levels (CAL), percentage of sites showing further attachment loss (PSAL) ≥1.3 mm, bleeding on probing (BOP) and plaque score were assessed. Exploratory statistical analysis was performed. A total of 209 samples were genotyped. Patients carrying heterozygous genotypes and single-nucleotide-polymorphisms (SNP) on the GATA-3-IVS4 +1468 gene locus showed less CAL loss than patients carrying wild type. Heterozygous genotypes and SNPs on the IL-1A-889, IL-1B +3954, IL-4-34, IL-4-590, GATA-3-IVS4 +1468 and COX-2-1195 gene loci did not influence CAL. In multivariate analysis, CAL was lower in patients carrying GATA-3 heterozygous genotypes and SNPs than those carrying wild-types. For the first time, effects of different genotypes were analyzed in periodontitis progression after periodontal therapy and during supportive treatment using systemic antibiotics demonstrating a slight association of GATA-3 gene locus with CAL. This result suggests that GATA-3 genotypes are a contributory but non-essential risk factor for periodontal disease progression.     

Development of Deep-Learning-Based Single-Molecule Localization Image Analysis

Recent developments in super-resolution fluorescence microscopic techniques (SRM) have allowed for nanoscale imaging that greatly facilitates our understanding of nanostructures. However, the performance of single-molecule localization microscopy (SMLM) is significantly restricted by the image analysis method, as the final super-resolution image is reconstructed from identified localizations through computational analysis. With recent advancements in deep learning, many researchers have employed deep learning-based algorithms to analyze SMLM image data. This review discusses recent developments in deep-learning-based SMLM image analysis, including the limitations of existing fitting algorithms and how the quality of SMLM images can be improved through deep learning. Finally, we address possible future applications of deep learning methods for SMLM imaging.     

Next-Generation Grade and Survival Expression Biomarkers of Human Gliomas Based on Algorithmically Reconstructed Molecular Pathways

In gliomas, expression of certain marker genes is strongly associated with survival and tumor type and often exceeds histological assessments. Using a human interactome model, we algorithmically reconstructed 7494 new-type molecular pathways that are centered each on an individual protein. Each single-gene expression and gene-centric pathway activation was tested as a survival and tumor grade biomarker in gliomas and their diagnostic subgroups (IDH mutant or wild type, IDH mutant with 1p/19q co-deletion, MGMT promoter methylated or unmethylated), including the three major molecular subtypes of glioblastoma (proneural, mesenchymal, classical). We used three datasets from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas, which in total include 527 glioblastoma and 1097 low grade glioma profiles. We identified 2724 such gene and 2418 pathway survival biomarkers out of total 17,717 genes and 7494 pathways analyzed. We then assessed tumor grade and molecular subtype biomarkers and with the threshold of AUC > 0.7 identified 1322/982 gene biomarkers and 472/537 pathway biomarkers. This suggests roughly two times greater efficacy of the reconstructed pathway approach compared to gene biomarkers. Thus, we conclude that activation levels of algorithmically reconstructed gene-centric pathways are a potent class of new-generation diagnostic and prognostic biomarkers for gliomas.     

用响应面法进行压缩机环状管*的设计优化

从结构振动和结构噪声的角度来看,压缩机的环状管是电冰箱中最重要的部件。压缩机内部机体产生的振动能量通过环状管传到壳体和外界,因此压缩机环状管的设计非常重要。但是,由于环状管几何形状的复杂性和运动的非线性,分析和设计环状管十分困难,往往不得不用统计法和试验法进行系统设计。对于类似环状管这样的复杂系统,响应面法(RSM)是常用的建模技术。用有限元模型和简单的试验模型代替环状管的实际模型作为环状管优化的起点。建立RS模型以后,用Sensitivity-based优化法进行优化。采用动态最小二乘法(MLSM)减少逼近误差。     

Leak detection in pipe using transient flow and genetic algorithm

An inverse transient method with genetic algorithm (GA) was applied to leak detection in pipeline. Transient flow caused by valve operation was calculated using the characteristics method. The location and discharge of leak were determined so that the difference of the calculated pressure may be minimized from the reference pressure calculated under a given leak condition. Calculations were done for the leak at one and two locations in pipeline. Furthermore, the effect of noise in pressure data was discussed, and the leak locations and leak discharges can be predicted precisely even in the case of noisy data. This paper was presented at the 9^th Asian International Conference on Fluid Machinery (AICFM9), Jeju Korea, October 16–19, 2007.     

Kinematics, kinetics and muscle activities of the lower extremity during the first four steps from gait initiation to the steady-state walking

In this study, biomechanical characteristics during the whole process of gait initiation for twenty normal healthy volunteers were determined by the motion analysis with six near-infrared cameras, four forceplates, and an EMG system. Gait initiation, a transitional movement phenomenon from quiet stance to steady-state walking, involves a series of muscular activities, GRFs, movements of COP and COM, and joint motions. Results showed that the location of the net COP to be most lateral during double limb stance at the beginning of gait initiation. During gait initiation, changes in anteroposterior components of GRFs were first found and then changes in vertical components followed. Hip and knee motions were found before the ankle joint motion. Walking speed, step length, and stride length gradually increased until the second step. The interaction between the COM and COP is tightly regulated to control the trajectory of the COM and thereby control total body balance. This paper was recommended for publication in revised form by Associate Editor Hong Hee Yoo Sun-Woo Park received a B.S. degree in Biomedical Engineering from Yonsei University in 2006. He is currently a M.S. candidate in the Department of Biomedical Engineering, Yonsei University, Korea. His research interests in the area of Human Movement and detection of gait phase using motion sensors. Hue-Seok Choi received a B.S. degree in Computer Engineering from Daejeon University in 2004. He is currently a P.D. candidate at the Department of Biomedical Engineering at Yonsei University, Korea. His research interests are in the area of Human Movement and Rehabilitation Engineering. Ki-Hong Ryu received a B.S. and M.S. degrees in Biomedical Engineering from Yonsei University in 1998 and 2001, respectively. He is currently a P.D. candidate in the Department of Biomedical Engineering, Yonsei University, Korea. His research interests are in the area of Human Movement and Gait Training System using Functional Electrical Stimulation. Sa-Yup Kim received a B.S. degree in Electrical Engineering from Yeungnam University in 2002 and M.S. degrees in Biomedical Engineering from Yonsei University in 2006. He is currently working from Korea Institute of Industrial Technology in Cheonan, Korea. Young-Ho Kim received a B.S. degree in Mechanical Engineering from Hanyang University in 1982. He then went on to receive his M.S. and Ph.D. degrees from University of Iowa in 1989 and 1991, respectively. He is currently a Professor in the Department of Biomedical Engineering, Yonsei University, Korea. His research interests are in the area of Human Movement, Rehabilitation Engineering, and Biomechanics.     

Endometrial Epithelial ARID1A Is Required for Uterine Immune Homeostasis during Early Pregnancy

A growing body of work suggests epigenetic dysregulation contributes to endometriosis pathophysiology and female infertility. The chromatin remodeling complex subunit AT-rich interaction domain 1A (ARID1A) must be properly expressed to maintain normal uterine function. Endometrial epithelial ARID1A is indispensable for pregnancy establishment in mice through regulation of endometrial gland function; however, ARID1A expression is decreased in infertile women with endometriosis. We hypothesized that ARID1A performs critical operations in the endometrial epithelium necessary for fertility besides maintaining gland function. To identify alterations in uterine gene expression resulting from loss of epithelial ARID1A, we performed RNA-sequencing analysis on pre-implantation uteri from Ltf^iCre/+Arid1a^f/f and control mice. Differential expression analysis identified 4181 differentially expressed genes enriched for immune-related ingenuity canonical pathways including agranulocyte adhesion and diapedesis and natural killer cell signaling. RT-qPCR confirmed an increase in pro-inflammatory cytokine and macrophage-related gene expression but a decrease in natural killer cell signaling. Immunostaining confirmed a uterus-specific increase in macrophage infiltration. Flow cytometry delineated an increase in inflammatory macrophages and a decrease in uterine dendritic cells in Ltf^iCre/+Arid1a^f/f uteri. These findings demonstrate a role for endometrial epithelial ARID1A in suppressing inflammation and maintaining uterine immune homeostasis, which are required for successful pregnancy and gynecological health.