CAM/CAD Point Cloud Part Segmentation via Few-Shot Learning

3D part segmentation is an essential step in advanced CAM/CAD workflow. Precise 3D segmentation contributes to lower defective rate of work-pieces produced by the manufacturing equipment (such as computer controlled CNCs), thereby improving work efficiency and attaining the attendant economic benefits. A large class of existing works on 3D model segmentation are mostly based on fully-supervised learning, which trains the AI models with large, annotated datasets. However, the disadvantage is that the resulting models from the fully-supervised learning methodology are highly reliant on the completeness of the available dataset, and its generalization ability is relatively poor to new unknown segmentation types (i.e. further additional novel classes). In this work, we propose and develop a noteworthy few-shot learning-based approach for effective part segmentation in CAM/CAD; and this is designed to significantly enhance its generalization ability and flexibly adapt to new segmentation tasks by using only relatively rather few samples. As a result, it not only reduces the requirements for the usually unattainable and exhaustive completeness of supervision datasets, but also improves the flexibility for real-world applications. As further improvement and innovation, we additionally adopt the transform net and the center loss block in the network. These characteristics serve to improve the comprehension for 3D features of the various possible instances of the whole work-piece and ensure the close distribution of the same class in feature space.Comment: 7 pages, 5 figure

Prognostic risk analysis related to radioresistance genes in colorectal cancer

BackgroundRadiotherapy (RT) is one of the most important treatments for patients with colorectal cancer (CRC). Radioresistance is the crucial cause of poor therapeutic outcomes in colorectal cancer. However, the underlying mechanism of radioresistance in colorectal cancer is still poorly defined. Herein we established a radioresistant colorectal cancer cell line and performed transcriptomics analyses to search for the underlying genes that contribute to radioresistance and investigate its association with the prognosis of CRC patients.MethodsThe radioresistant cell line was developed from the parental HCT116 cell by a stepwise increased dose of irradiation. Differential gene analysis was performed using cellular transcriptome data to identify genes associated with radioresistance, from which extracellular matrix (ECM) and cell adhesion-related genes were screened. Survival data from a CRC cohort in the TCGA database were used for further model gene screening and validation. The correlation between the risk score model and tumor microenvironment, clinical phenotype, drug treatment sensitivity, and tumor mutation status were also investigated.ResultsA total of 493 different expression genes were identified from the radioresistant and wild-type cell line, of which 94 genes were associated with ECM and cell adhesion-related genes. The five model genes TNFRSF13C, CD36, ANGPTL4, LAMB3, and SERPINA1 were identified for CRC radioresistance via screening using the best model. A ROC curve indicated that the AUC of the resulting prognostic model (based on the 5-gene risk score and other clinical parameters, including age, sex, and tumor stages) was 0.79, 0.77, and 0.78 at 1, 2, and 3 years, respectively. The calibration curve showed high agreement between the risk score prediction and actual survival probability. The immune microenvironment, drug treatment sensitivity, and tumor mutation status significantly differed between the high- and low-risk groups.ConclusionsThe risk score model built with five radioresistance genes in this study, including TNFRSF13C, CD36, ANGPTL4, LAMB3, and SERPINA1, showed favorable performance in prognosis prediction after radiotherapy for CRC

Self-targeting of zwitterion-based platforms for nano-antimicrobials and nanocarriers

Self-targeting antimicrobial platforms have yielded new possibilities for the treatment of infectious biofilms. Self-targeting involves stealth transport through the blood circulation towards an infectious biofilm, where the antimicrobial platform penetrates and accumulates in a biofilm in response to a change in environmental conditions, such as local pH. In a final step, nano-antimicrobials need to be activated or the antimicrobial cargo of nanocarriers released. Zwitterions possess both cationic and anionic groups, allowing full reversal in zeta potential from below to above zero in response to a change in environmental conditions. Electrolyte-based platforms generally do not have the ability to change their zeta potentials from below to above zero. Zwitterions for use in self-targeting platforms are usually hydrophilic and have a negative charge under physiological conditions (pH 7.4) providing low adsorption of proteins and assisting blood circulation. However, near or in the acidic environment of a biofilm, they become positively-charged yielding targeting, penetration and accumulation in the biofilm through electrostatic double-layer attraction to negatively-charged bacteria. Response-times to pH changes vary, depending on the way the zwitterion or electrolyte is built in a platform. Self-targeting zwitterion-based platforms with a short response-time in vitro yield different accumulation kinetics in abdominal biofilms in living mice than platforms with a longer response-time. In vivo experiments in mice also proved that self-targeting, pH-responsive zwitterion-based platforms provide a feasible approach for clinical control of bacterial infections. Clinically however, also other conditions than infection may yield an acidic environment. Therefore, it remains to be seen whether pH is a sufficiently unique recognition sign to direct self-targeting platforms to an infectious biofilm or whether (additional) external targeting through e.g. near-infrared irradiation or magnetic field application is needed

Cdx4 and Menin Co-Regulate Hoxa9 Expression in Hematopoietic Cells

BACKGROUND: Transcription factor Cdx4 and transcriptional coregulator menin are essential for Hoxa9 expression and normal hematopoiesis. However, the precise mechanism underlying Hoxa9 regulation is not clear. METHODS AND FINDINGS: Here, we show that the expression level of Hoxa9 is correlated with the location of increased trimethylated histone 3 lysine 4 (H3K4M3). The active and repressive histone modifications co-exist along the Hoxa9 regulatory region. We further demonstrate that both Cdx4 and menin bind to the same regulatory region at the Hoxa9 locus in vivo, and co-activate the reporter gene driven by the Hoxa9 cis-elements that contain Cdx4 binding sites. Ablation of menin abrogates Cdx4 access to the chromatin target and significantly reduces both active and repressive histone H3 modifications in the Hoxa9 locus. CONCLUSION: These results suggest a functional link among Cdx4, menin and histone modifications in Hoxa9 regulation in hematopoietic cells

FeAl-based Metallic-Intermetallic Laminate (MIL) Composites

FeAl-based Metallic-Intermetallic Laminate (MIL) composites and FeAl/FeAl2 eutectoid MIL composites of various iron alloys were fabricated with an innovative “multiple-thin-foil” configuration and “two-stage reaction” strategy. Alternating stacked metal foils were reactive sintered via spark plasma sintering (SPS) (a.k.a. field assisted sintering) to grow intermetallics. The “multiple-thin-foil” configuration reduces reaction time, enables local chemical composition control and allows metal/intermetallic combinations, which cannot be produced via the conventional methods. Fe-FeAl, 430SS-FeAl, and 304SS-FeAl MIL composites can be synthesized with desired metallic/intermetallic ratios, where FeAl is the single intermetallic phase present in the composites. The deformation and fracture evolution of the FeAl-based MIL composites is investigated here via incremental compression testing. Geometrically necessary dislocation (GND) analysis indicates the FeAl regions deform in similar manners for the three MIL composites, and each fails in a similar mode. Single-phase intermetallic FeAl layered material is also synthesized using a similar approach to study the fracture mechanisms of FeAl-based MIL composites. Mesoscale hetero-deformation induced (HDI) stress, which is tensile on the FeAl layers of MIL composites, accelerates crack nucleation and crack propagation, eventually inducing failure. The HDI stress evaluated via finite element analysis (FEA) simulation explains the difference between 430SS-FeAl and 304SS-FeAl MIL composites, which possess similar microstructure and composition, but very different strengths. Meanwhile, the electromigration effect in SPS is quantitively analyzed in the Fe-Al diffusion couple system. In SPS, the samples are heated by the applied voltage and a high electric current, which can lead to an electromigration effect. FEA simulation is utilized to determine the voltage applied to the Fe-Al diffusion couple, which is found to be extremely small to induce any voltage effect. Additionally, the simulation suggests the temperature and current density distribution is uniform across the metallic diffusion couple, which makes quantitative measurement feasible. For the first time, a mathematic algorithm, which allows diffusivity and electromigration coefficients to be solved, is developed for the system with multiple reactive layers

Deletion of the Men1 Gene Prevents Streptozotocin-Induced Hyperglycemia in Mice

Diabetes ultimately results from an inadequate number of functional beta cells in the islets of Langerhans. Enhancing proliferation of functional endogenous beta cells to treat diabetes remains underexplored. Here, we report that excision of the Men1 gene, whose loss-of-function mutation leads to inherited multiple endocrine neoplasia type 1 (MEN1), rendered resistant to streptozotocin-induced hyperglycemia in a tamoxifen-inducible and temporally controlled Men1 excision mouse model as well as in a tissue-specific Men1 excision mouse model. Men1 excision prevented mice from streptozotocin-induced hyperglycemia mainly through increasing the number of functional beta cells. BrdU incorporation by beta cells, islet size, and circulating insulin levels were significantly increased in Men1-excised mice. Membrane localization of glucose transporter 2 was largely preserved in Men1-excised beta cells, but not in Men1-expressing beta cells. Our findings suggest that repression of menin, a protein encoded by the Men1 gene, might be a valuable means to maintain or increase the number of functional endogenous beta cells to prevent or ameliorate diabetes