DGAT2 Plays a Crucial Role to Control ESRRAPROX1 Transcriptional Network to Maintain Hepatic Mitochondrial Sustainability.

Background: Diacylglycerol O-acyltransferase 2 (DGAT2) synthesizes triacylglycerol (TG) from diacylglycerol; therefore, DGAT2 is considered as a therapeutic target for steatosis. However, the consequence of inhibiting DGAT2 is not fully investigated due to side effects including lethality and lipotoxicity. In this article, we observed the role of DGAT2 in hepatocarcinoma. Methods: The role of DGAT2 is analyzed via loss-of-function assay. DGAT2 knockdown (KD) and inhibitor treatment on HepG2 cell line was analyzed. Cumulative analysis of cell metabolism with bioinformatic data were assessed, and further compared with different cohorts of liver cancer patients and non-alcoholic fatty liver disease (NAFLD) patients to elucidate how DGAT2 is regulating cancer metabolism. Results: Mitochondrial function is suppressed in DGAT2 KD HepG2 cell along with the decreased lipid droplets. In the aspect of the cancer, DGAT2 KD upregulates cell proliferation. Analyzing transcriptome of NAFLD and hepatocellular carcinoma (HCC) patients highlights negatively correlating expression patterns of 73 lipid-associated genes including DGAT2. Cancer patients with the lower DGAT2 expression face lower survival rate. DGAT2 KD cell and patients' transcriptome show downregulation in estrogen- related receptor alpha (ESRRA) via integrated system for motif activity response analysis (ISMARA), with increased dimerization with corepressor prospero homeobox 1 (PROX1). Conclusion: DGAT2 sustains the stability of mitochondria in hepatoma via suppressing ESRRA-PROX1 transcriptional network and hinders HCC from shifting towards glycolytic metabolism, which lowers cell proliferation.

Triamcinolone acetonide alleviates benign biliary stricture by ameliorating biliary fibrosis and inflammation.

We conducted a comprehensive series of molecular biological studies aimed at unraveling the intricate mechanisms underlying the anti-fibrotic effects of triamcinolone acetonide (TA) when used in conjunction with fully covered self-expandable metal stents (FCSEMS) for the management of benign biliary strictures (BBS). To decipher the molecular mechanisms responsible for the anti-fibrotic effects of corticosteroids on gallbladder mucosa, we conducted a comprehensive analysis. This analysis included various methodologies such as immunohistochemistry, ELISA, real-time PCR, and transcriptome analysis, enabling us to examine alterations in factors related to fibrosis and inflammation at both the protein and RNA levels. Overall, our findings revealed a dose-dependent decrease in fibrosisrelated signaling with higher TA concentrations. The 15 mg of steroid treatment (1X) exhibited anti-fibrosis and anti-inflammatory effects after 4 weeks, whereas the 30 mg of steroid treatment (2X) rapidly reduced fibrosis and inflammation within 2 weeks in BBS. Transcriptomic analysis results consistently demonstrated significant downregulation of fibrosis- and inflammation-related pathways and genes in steroid-treated fibroblasts. Use of corticosteroids, specifically TA, together with FCSEMS was effective for the treatment of BBS, ameliorating fibrosis and inflammation. Our molecular biological analysis supports the potential development of steroid-eluted FCSEMS as a therapeutic option for BBS in humans resulting from various surgical procedures. [BMB Reports 2024; 57(4): 200-205].

Toward Advanced Superomniphobicity: Hierarchical Insights from Serif-T Nanostructures to Microscale Wrinkles.

Developing a superomniphobic surface that exceeds the static and dynamic repellency observed in nature's springtails for various liquids presents a significant challenge in the realm of surface and interface science. However, progress in this field has been particularly limited when dealing with low-surface-tension liquids. This is because dynamic repellency values are typically at least 2 orders of magnitude lower than those observed with water droplets. Our study introduces an innovative hierarchical topography demonstrating exceptional dynamic repellency to low-surface-tension liquids. Inspired by the structural advantages found in springtails, we achieve a static contact angle of >160° and the complete rebound of droplet impact with a Weber number (We) of ∼104 using ethanol. These results surpass all existing benchmarks that have been reported thus far, including those of natural surfaces. The key insight from our research is the vital role of the microscale air pocket size, governed by wrinkle wavelength, in both static and dynamic repellency. Additionally, nanoscale air pockets within serif-T nanostructures prove to be essential for achieving omniphobicity. Our investigations into the wetting dynamics of ethanol droplets further reveal aspects such as the reduction in contact time and the occurrence of a fragmentation phenomenon beyond We ∼ 350, which has not been previously observed.

A comprehensive dataset for home appliance control using ERP-based BCIs with the application of inter-subject transfer learning.

Brain-computer interfaces (BCIs) have a potential to revolutionize human-computer interaction by enabling direct links between the brain and computer systems. Recent studies are increasingly focusing on practical applications of BCIs-e.g., home appliance control just by thoughts. One of the non-invasive BCIs using electroencephalography (EEG) capitalizes on event-related potentials (ERPs) in response to target stimuli and have shown promise in controlling home appliance. In this paper, we present a comprehensive dataset of online ERP-based BCIs for controlling various home appliances in diverse stimulus presentation environments. We collected online BCI data from a total of 84 subjects among whom 60 subjects controlled three types of appliances (TV: 30, door lock: 15, and electric light: 15) with 4 functions per appliance, 14 subjects controlled a Bluetooth speaker with 6 functions via an LCD monitor, and 10 subjects controlled air conditioner with 4 functions via augmented reality (AR). Using the dataset, we aimed to address the issue of inter-subject variability in ERPs by employing the transfer learning in two different approaches. The first approach, "within-paradigm transfer learning," aimed to generalize the model within the same paradigm of stimulus presentation. The second approach, "cross-paradigm transfer learning," involved extending the model from a 4-class LCD environment to different paradigms. The results demonstrated that transfer learning can effectively enhance the generalizability of BCIs based on ERP across different subjects and environments.

BRCA1 mutation promotes sprouting angiogenesis in inflammatory cancer-associated fibroblast of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with inferior outcomes owing to its low treatment response and high invasiveness. Based on abundant cancer-associated fibroblasts (CAFs) and frequent mutation of breast cancer-associated 1 (BRCA1) in TNBC, the characteristics of CAFs in TNBC patients with BRCA1 mutation compared to wild-type were investigated using single-cell analysis. Intriguingly, we observed that characteristics of inflammatory CAFs (iCAFs) were enriched in patients with BRCA1 mutation compared to the wild-type. iCAFs in patients with BRCA1 mutation exhibited outgoing signals to endothelial cells (ECs) clusters, including chemokine (C-X-C motif) ligand (CXCL) and vascular endothelial growth factor (VEGF). During CXCL signaling, the atypical chemokine receptor 1 (ACKR1) mainly interacts with CXCL family members in tumor endothelial cells (TECs). ACKR1-high TECs also showed high expression levels of angiogenesis-related genes, such as ANGPT2, MMP1, and SELE, which might lead to EC migration. Furthermore, iCAFs showed VEGF signals for FLT1 and KDR in TECs, which showed high co-expression with tip cell marker genes, including ZEB1 and MAFF, involved in sprouting angiogenesis. Moreover, BRCA1 mutation patients with relatively abundant iCAFs and tip cell gene expression exhibited a limited response to neoadjuvant chemotherapy, including cisplatin and bevacizumab. Importantly, our study observed the intricate link between iCAFs-mediated angiogenesis and chemoresistance in TNBC with BRCA1 mutation.

Effect of Feature Shape and Dimension of a Confinement Geometry on Selectivity of Electrocatalytic CO2 Reduction.

The local confinement effect, which can generate a high concentration of hydroxide ions and reaction intermediates near the catalyst surface, is an important strategy for converting CO2 into multi-carbon products in electrocatalytic CO2 reduction. Therefore, understanding how the shape and dimension of the confinement geometry affect the product selectivity is crucial. In this study, we report for the first time the effect of the shape (degree of confinement) and dimension of the confined space on the product selectivity without changing the intrinsic property of Cu. We demonstrate that geometry influences the outcomes of products, such as CH4 , C2 H4 , and EtOH, in different ways: the selectivity of CH4 and EtOH is affected by shape, while the selectivity of C2 H4 is influenced by dimension of geometry predominantly. These phenomena are demonstrated, both experimentally and through simulation, to be induced by the local confinement effect within the confined structure. Our geometry model could serve as basis for designing the confined structures tailored for the production of specific products.

Study on Rolling Defects of Al-Mg Alloys with High Mg Content in Normal Rolling and Cross-Rolling Processes.

This study investigated defect formation and strain distribution in high-Mg-content Al-Mg alloys during normal rolling and cross-rolling processes. The finite element analysis (FEA) revealed the presence of wave defects and strain localization-induced zipper cracks in normal cold rolling, which were confirmed by the experimental results. The concentration of shear strain played a significant role in crack formation and propagation. However, the influence of wave defects was minimal in the cross-rolling process, which exhibited a relatively uniform strain distribution. Nonetheless, strain concentration at the edge and center regions led to the formation of zipper cracks and edge cracks, with more pronounced propagation observed in the experiments compared to FEA predictions. Furthermore, texture evolution was found to be a crucial factor affecting crack propagation, particularly with the development of the Goss texture component, which was observed via electron backscattered diffraction analysis at bending points. The Goss texture hindered crack propagation, while the Brass texture allowed cracks to pass through. This phenomenon was consistent with both FEA and experimental observations. To mitigate edge crack formation and propagation, potential strategies involve promoting the formation of the Goss texture at the edge through alloy and process conditions, as well as implementing intermediate annealing to alleviate stress accumulation. These measures can enhance the overall quality and reliability of Al-Mg alloys during cross-rolling processes. In summary, understanding the mechanisms of defect formation and strain distribution in Al-Mg alloys during rolling processes is crucial for optimizing their mechanical properties. The findings of this study provide insights into the challenges associated with wave defects, strain localization, and crack propagation. Future research and optimization efforts should focus on implementing strategies to minimize defects and improve the overall quality of Al-Mg alloys in industrial applications.

Co-inhibition of glutaminolysis and one-carbon metabolism promotes ROS accumulation leading to enhancement of chemotherapeutic efficacy in anaplastic thyroid cancer.

Anaplastic thyroid cancer (ATC) is one of the most aggressive tumors with an extremely poor prognosis. Based on the several biological features related to glutamine metabolism in ATC, we hypothesized glutaminolysis inhibition induces cell death in ATC cells. However, glutamine metabolism inhibition triggered cell growth arrest independent of cell death in ATC, suggesting that other signaling pathways avoid glutamine metabolism inhibition-induced stress exist. To investigate the functional mechanism against glutamine metabolism inhibition, we conducted mRNA and ATAC-Sequencing data analysis and found that glutamine deprivation increased ATF4-mediated one-carbon metabolism. When we inhibited PHGDH, the first rate-limiting enzyme for one-carbon metabolism, cell growth arrest was promoted upon glutamine metabolism inhibition by accumulating intracellular ROS. We next observed that the co-inhibition of glutamine and one-carbon metabolism could augment the anticancer effects of drugs used in patients with ATC. Finally, single-cell RNA sequencing analysis revealed that one-carbon metabolism was strengthened through the evolutionary process from PTC to ATC. Collectively, our data demonstrate that one-carbon metabolism has a potential role of modulation of cell fate in metabolic stress and can be a therapeutic target for enhancing antitumor effects in ATC.

A Role of ß2-Adrenoreceptor Agonists Related to the Development of Parkinson's Disease.

Background: Several studies have suggested the potential protective role of ß2-adrenoreceptor agonist (ß2AR-agonist) on the development of Parkinson's disease (PD). However, those could not reflect a different epidemiologic background in eastern countries. We explored ß2AR-agonist's effect on PD development by controlling for smoking. Materials and Methods: We used the Korean national sample cohort data (from 2002 to 2013) containing 1,025,340 participants (2.2% of the whole population). The subjects over 60 years were included. PD was defined based on the ICD-10 code, which should be diagnosed by neurologists. Atypical Parkinsonisms or ataxic disorders were excluded. We made Set 1 (from 2003 to 2007) and Set 2 (from 2003 to 2008) based on the exposure period for the sensitivity analysis. We observed whether PD had developed during the follow-up periods in each subset. Results: The PD (Set 1, n = 742; Set 2, n = 699) and non-PD group (Set 1, n = 57,645; Set 2, n = 66,586) were collected. Old age, Medicaid, and asthma were risk factors, whereas smoking was a significant protective factor for PD development. The proportion of ß2AR-agonist use was significantly higher in the PD group than in the non-PD group (Set 1, 3.6% vs. 2.4%; Set 2, 4.1% vs. 2.6%). ß2AR-agonist use still was a risk factor in developing PD from the multiple logistic regression analysis. Conclusions: ß2-AR-agonist looked like a risk factor rather than a protective factor for PD development. Well-controlled studies reflecting various epidemiologic backgrounds are required to confirm the role of ß2AR-agonist.

PHGDH preserves one-carbon cycle to confer metabolic plasticity in chemoresistant gastric cancer during nutrient stress.

Molecular classification of gastric cancer (GC) identified a subgroup of patients showing chemoresistance and poor prognosis, termed SEM (Stem-like/Epithelial-to-mesenchymal transition/Mesenchymal) type in this study. Here, we show that SEM-type GC exhibits a distinct metabolic profile characterized by high glutaminase (GLS) levels. Unexpectedly, SEM-type GC cells are resistant to glutaminolysis inhibition. We show that under glutamine starvation, SEM-type GC cells up-regulate the 3 phosphoglycerate dehydrogenase (PHGDH)-mediated mitochondrial folate cycle pathway to produce NADPH as a reactive oxygen species scavenger for survival. This metabolic plasticity is associated with globally open chromatin structure in SEM-type GC cells, with ATF4/CEBPB identified as transcriptional drivers of the PHGDH-driven salvage pathway. Single-nucleus transcriptome analysis of patient-derived SEM-type GC organoids revealed intratumoral heterogeneity, with stemness-high subpopulations displaying high GLS expression, a resistance to GLS inhibition, and ATF4/CEBPB activation. Notably, coinhibition of GLS and PHGDH successfully eliminated stemness-high cancer cells. Together, these results provide insight into the metabolic plasticity of aggressive GC cells and suggest a treatment strategy for chemoresistant GC patients.

Unsupervised anomaly detection for posteroanterior chest X-rays using multiresolution patch-based self-supervised learning.

The demand for anomaly detection, which involves the identification of abnormal samples, has continued to increase in various domains. In particular, with increases in the data volume of medical imaging, the demand for automated screening systems has also risen. Consequently, in actual clinical practice, radiologists can focus only on diagnosing patients with abnormal findings. In this study, we propose an unsupervised anomaly detection method for posteroanterior chest X-rays (CXR) using multiresolution patch-based self-supervised learning. The core aspect of our approach is to leverage patch images of different sizes for training and testing to recognize diverse anomalies characterized by unknown shapes and scales. In addition, self-supervised contrastive learning is applied to learn the generalized and robust features of the patches. The performance of the proposed method is evaluated using posteroanterior CXR images from a public dataset for training and testing. The results show that the proposed method is superior to state-of-the-art anomaly detection methods. In addition, unlike single-resolution patch-based methods, the proposed method consistently exhibits a good overall performance regardless of the evaluation criteria used for comparison, thus demonstrating the effectiveness of using multiresolution patch-based features. Overall, the results of this study validate the effectiveness of multiresolution patch-based self-supervised learning for detecting anomalies in CXR images.

Exploring Optimal Water Splitting Bifunctional Alloy Catalyst by Pareto Active Learning.

Design of bifunctional multimetallic alloy catalysts, which are one of the most promising candidates for water splitting, is a significant issue for the efficient production of renewable energy. Owing to large dimensions of the components and composition of multimetallic alloys, as well as the trade-off behavior in terms of the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) overpotentials for bifunctional catalysts, it is difficult to search for high-performance bifunctional catalysts with multimetallic alloys using conventional trial-and-error experiments. Here, an optimal bifunctional catalyst for water splitting is obtained by combining Pareto active learning and experiments, where 110 experimental data points out of 77946 possible points lead to effective model development. The as-obtained bifunctional catalysts for HER and OER exhibit high performance, which is revealed by model development using Pareto active learning; among the catalysts, an optimal catalyst (Pt0.15 Pd0.30 Ru0.30 Cu0.25 ) exhibits a water splitting behavior of 1.56 V at a current density of 10 mA cm-2 . This study opens avenues for the efficient exploration of multimetallic alloys, which can be applied in multifunctional catalysts as well as in other applications.

Long Short-Term Memory-Based Deep Learning Models for Screening Parkinson's Disease Using Sequential Diagnostic Codes.

BACKGROUND AND PURPOSE: It is challenging to detect Parkinson's disease (PD) in its early stages, which has prompted researchers to develop techniques based on machine learning methods for detecting PD. However, previous studies did not fully incorporate the slow progression of PD over a long period of time nor consider that its symptoms occur in a time-sequential manner. Contributing to the literature on PD, which has relied heavily on cross-sectional data, this study aimed to develop a method for detecting PD early that can process time-series information using the long short-term memory (LSTM) algorithm. METHODS: We sampled 926 patients with PD and 9,260 subjects without PD using medical-claims data. The LSTM algorithm was tested using diagnostic histories, which contained the diagnostic codes and their respective time information. We compared the prediction power of the 12-month diagnostic codes under two different settings over the 4 years prior to the first PD diagnosis. RESULTS: The model that was trained using the most-recent 12-month diagnostic codes had the best performance, with an accuracy of 94.25%, a sensitivity of 82.91%, and a specificity of 95.26%. The other three models (12-month codes from 2, 3, and 4 years prior) were found to have comparable performances, with accuracies of 92.27%, 91.86%, and 91.81%, respectively. The areas under the curve from our data settings ranged from 0.839 to 0.923. CONCLUSIONS: We explored the possibility that PD specialists could benefit from our proposed machine learning method as an early detection method for PD.

Wireless dielectrophoresis trapping and remote impedance sensing via resonant wireless power transfer.

Nearly all biosensing platforms can be described using two fundamental steps-collection and detection. Target analytes must be delivered to a sensing element, which can then relay the transduced signal. For point-of-care technologies, where operation is to be kept simple, typically the collection step is passive diffusion driven-which can be slow or limiting under low concentrations. This work demonstrates an integration of both active collection and detection by using resonant wireless power transfer coupled to a nanogap capacitor. Nanoparticles suspended in deionized water are actively trapped using wireless dielectrophoresis and positioned within the most sensitive fringe field regions for wireless impedance-based detection. Trapping of 40 nm particles and larger is demonstrated using a 3.5 VRMS, 1 MHz radiofrequency signal delivered over a distance greater than 8 cm from the nanogap capacitor. Wireless trapping and release of 1 µm polystyrene beads is simultaneously detected in real-time over a distance of 2.5 cm from the nanogap capacitor. Herein, geometric scaling strategies coupled with optimal circuit design is presented to motivate combined collection and detection biosensing platforms amenable to wireless and/or smartphone operation.

Practical Manipulation for the Preparation of Mesoporous Silica Nanoparticles for Drug Delivery Vehicles.

BACKGROUND: Optimization of MSNs is the most important process for efficient and safe drug delivery systems. OBJECTIVE: In this study, the physicochemical properties of MSNs were evaluated using various compositions of individual reagents. METHODS: MSNs were synthesized according to a modified Stöber method. The physicochemical properties of MSNs were evaluated. Spherical uniform particles were observed in the scanning electron microscope (SEM) and transmission electron microscopy (TEM) image and the meso-structure of MSNs was confirmed. The amorphous and specific hexagonal structure of MSNs was confirmed through Xray diffraction (XRD) and SAXRD. RESULTS: The particle size and surface area according to changes in amounts of reagents ranged from 34.5 ± 2.3 to 216.0 ± 17.1 nm and from 549.79 to 1154.26 m2/g, respectively. A linear relationship was found between the surface area of MSNs and the adsorption rate of methylene blue (MB). MSNs exhibited no apparent cytotoxic effect on Caco-2 cell up to 200 µg/mL. The amounts of tetramethyl ammonium silicate and tetraethyl ortho silicate (TEOS), NaOH, and hexadecyl trimethyl ammonium bromide (CTAB) were adjusted to control the particle size and surface area of MSNs, and it was found that the amounts of synthetic reagents affected the physicochemical properties such as particle size and surface area of MSNs. MSNs with a large surface area adsorbed a large amount of MB. CONCLUSION: These results indicated that drug adsorption is related to the surface area of MSNs. MSNs did not show cytotoxicity to Caco-2 cells. MSNs may be a promising nanomaterial that could be applied as a carrier for various drugs.

EEG-controlled tele-grasping for undefined objects.

This paper presents a teleoperation system of robot grasping for undefined objects based on a real-time EEG (Electroencephalography) measurement and shared autonomy. When grasping an undefined object in an unstructured environment, real-time human decision is necessary since fully autonomous grasping may not handle uncertain situations. The proposed system allows involvement of a wide range of human decisions throughout the entire grasping procedure, including 3D movement of the gripper, selecting proper grasping posture, and adjusting the amount of grip force. These multiple decision-making procedures of the human operator have been implemented with six flickering blocks for steady-state visually evoked potentials (SSVEP) by dividing the grasping task into predefined substeps. Each substep consists of approaching the object, selecting posture and grip force, grasping, transporting to the desired position, and releasing. The graphical user interface (GUI) displays the current substep and simple symbols beside each flickering block for quick understanding. The tele-grasping of various objects by using real-time human decisions of selecting among four possible postures and three levels of grip force has been demonstrated. This system can be adapted to other sequential EEG-controlled teleoperation tasks that require complex human decisions.

Identification of entomopathogenic fungus Metarhizium rileyi infested in fall armyworm in the cornfield of Korea, and evaluation of its virulence.

The fall armyworm (FAW) Spodoptera frugiperda is an important invasive pest in Africa and Asia. It is a polyphagous pest with at least 353 recorded host plant species, including corn. Chemical control of this pest is unsuccessful because of a developed resistance and harmful effects on the environment. Entomopathogenic fungi are potential biological control agents for FAW. In this study, the native strain of Metarhizium rileyi (KNU-Ye-1), collected from a cornfield at Yeongcheon, Korea, was identified by morphological and molecular characterization. The susceptibility of the fourth-instar larvae of FAW to the native strain M. rileyi was examined in the laboratory. The results showed that the Korean strain of M. rileyi (KNU-Ye-1) was highly virulent to FAW larvae, causing 89% mortality 7 days posttreatment. Therefore, M. rileyi (KNU-Ye-1) identified in this study is highly valuable for the biological control of FAW in the field.

Efficient Wear Simulation Methodology for Predicting Nonlinear Wear Behavior of Tools in Sheet Metal Forming.

In conventional wear simulation, the geometry must be updated for succeeding iterations to predict the accumulated wear. However, repeating this procedure up to the desired iteration is rather time consuming. Thus, a wear simulation process capable of reasonable quantitative wear prediction in reduced computational time is needed. This study aimed to develop an efficient wear simulation method to predict quantitative wear reasonably in reduced computational time without updating the geometry for succeeding iterations. The wear resistance of a stamping tool was quantitatively evaluated for different punch shapes (R3.0 and R5.5) and coating conditions (physical vapor deposition of CrN and AlTiCrN coatings) by using a progressive die set. To capture the nonlinear wear behavior with respect to strokes, a nonlinear equation from a modified form of Archard's wear model was proposed. By utilizing the scale factor representing the changes in wear properties with respect to wear depth as input, the simulation can predict the behavior of rapidly increasing wear depth with respect to strokes after failure initiation. Furthermore, the proposed simulation method is efficient in terms of computational time because it does not need to perform geometry updates.

Structural insights into ClpP protease side exit pore-opening by a pH drop coupled with substrate hydrolysis.

The ClpP serine peptidase is a tetradecameric degradation molecular machine involved in many physiological processes. It becomes a competent ATP-dependent protease when coupled with Clp-ATPases. Small chemical compounds, acyldepsipeptides (ADEPs), are known to cause the dysregulation and activation of ClpP without ATPases and have potential as novel antibiotics. Previously, structural studies of ClpP from various species revealed its structural details, conformational changes, and activation mechanism. Although product release through side exit pores has been proposed, the detailed driving force for product release remains elusive. Herein, we report crystal structures of ClpP from Bacillus subtilis (BsClpP) in unforeseen ADEP-bound states. Cryo-electron microscopy structures of BsClpP revealed various conformational states under different pH conditions. To understand the conformational change required for product release, we investigated the relationship between substrate hydrolysis and the pH-lowering process. The production of hydrolyzed peptides from acidic and basic substrates by proteinase K and BsClpP lowered the pH values. Our data, together with those of previous findings, provide insight into the molecular mechanism of product release by the ClpP self-compartmentalizing protease.

Springback Reduction of Ultra-High-Strength Martensitic Steel Sheet by Electrically Single-Pulsed Current.

This paper investigates the reduction of springback by an electrically single-pulsed current for an ultra-high-strength martensitic steel sheet, MART1470 1.2t. In order to evaluate the springback reduction by the electric current, V-bending tests were performed with various parameter-sets (current density and pulse duration). The amount of springback reduction was then calculated from the measured bent-angle of tested specimens. Experimental results show the springback is reduced with the increase in the current density, the pulse duration, and the electric energy density. In order to clarify thermal and athermal portions in the effect of electric current on the springback reduction, two ratios of force and isothermal flow stress were calculated based on bending theory. From the comparison of the ratios, it is noted that the athermal portion mainly contributes to the force relaxation, so the springback amount decreases. The athermal portion significantly increases as the electric energy density increases. Microstructures and micro-Vickers hardness were observed to confirm the applicability of the single-pulsed current to forming processes in practice. The springback reduction can be achieved up to 37.5% without severe changes in material properties when the electric energy density increases up to 281.3 mJ/mm3. Achievable reduction is 85.4% for the electric energy density of 500 mJ/mm3, but properties remarkably change.