Purification of plant-derived anti-virus mAb through optimized pH conditions for coupling between protein A and epoxy-activated beads.

The main goal of this research was to determine optimum pH conditions for coupling between protein A and epoxy-activated Sepharose beads for purification of monoclonal antibodies (mAbs) expressed in plants. To confirm the effect of pH conditions on purification efficacy, epoxy-activated agarose beads were coupled to protein A under the pH conditions of 8.5, 9.5, 10.5, and 11.5 (8.5R, 9.5R, 10.5R, and 11.5R, respectively). A total of 300 g of fresh leaf tissue of transgenic Arabidopsis expressing human anti-rabies mAb (mAbP) SO57 were harvested to isolate the total soluble protein (TSP). An equal amount of TSP solution was applied to five resin groups including commercial protein A resin (GR) as a positive control. The modified 8.5R, 9.5R, 10.5R, and 11.5R showed delayed elution timing compared to the GR control resin. Nano-drop analysis showed that the total amount of purified mAbPSO57 mAbs from 60 g of fresh leaf mass were not significantly different among 8.5R (400 µg), 9.5R (360 µg), 10.5R (380 µg), and GR (350 µg). The 11.5R (25 µg) had the least mAbPSO57. SDS-PAGE analysis showed that the purity of mAbPSO57 was not significantly different among the five groups. Rapid fluorescent focus inhibition tests revealed that virus-neutralizing efficacies of purified mAbPSO57 from all the five different resins including the positive control resin were similar. Taken together, both pH 8.5 and 10.5 coupling conditions with high recovery rate should be optimized for purification of mAbPSO57 from transgenic Arabidopsis plant, which will eventually reduce down-stream cost required for mAb production using the plant system.

Enhanced Piezoelectricity in a Robust and Harmonious Multilayer Assembly of Electrospun Nanofiber Mats and Microbead-Based Electrodes.

Here, we present a simple yet highly efficient method to enhance the output performance of a piezoelectric device containing electrospun nanofiber mats. Multiple nanofiber mats were assembled together to harness larger piezoelectric sources in the as-spun fibers, thereby providing enhanced voltage and current outputs compared to those of a single-mat device. In addition to the multilayer assembly, microbead-based electrodes were integrated with the nanofiber mats to deliver a complexed compression and tension force excitation to the piezoelectric layers. A vacuum-packing process was performed to attain a tight and well-organized assembly of the device components even though the total thickness was several millimeters. The integrated piezoelectric device exhibited a maximum voltage and current of 10.4 V and 2.3 µA, respectively. Furthermore, the robust integrity of the device components could provide high-precision sensitivity to perceive small pressures down to approximately 100 Pa while retaining a linear input-output relationship.

Detection of Stress Levels from Biosignals Measured in Virtual Reality Environments Using a Kernel-Based Extreme Learning Machine.

Virtual reality (VR) is a computer technique that creates an artificial environment composed of realistic images, sounds, and other sensations. Many researchers have used VR devices to generate various stimuli, and have utilized them to perform experiments or to provide treatment. In this study, the participants performed mental tasks using a VR device while physiological signals were measured: a photoplethysmogram (PPG), electrodermal activity (EDA), and skin temperature (SKT). In general, stress is an important factor that can influence the autonomic nervous system (ANS). Heart-rate variability (HRV) is known to be related to ANS activity, so we used an HRV derived from the PPG peak interval. In addition, the peak characteristics of the skin conductance (SC) from EDA and SKT variation can also reflect ANS activity; we utilized them as well. Then, we applied a kernel-based extreme-learning machine (K-ELM) to correctly classify the stress levels induced by the VR task to reflect five different levels of stress situations: baseline, mild stress, moderate stress, severe stress, and recovery. Twelve healthy subjects voluntarily participated in the study. Three physiological signals were measured in stress environment generated by VR device. As a result, the average classification accuracy was over 95% using K-ELM and the integrated feature (IT = HRV + SC + SKT). In addition, the proposed algorithm can embed a microcontroller chip since K-ELM algorithm have very short computation time. Therefore, a compact wearable device classifying stress levels using physiological signals can be developed.

Enhancement of skin permeation of vitamin C using vibrating microneedles.

This study was performed to evaluate the use of vibrating microneedles for the transdermal delivery of vitamin C. The microneedles were designed to vibrate at three levels of intensity. In vitro permeation by vitamin C was evaluated according to the specific conditions such as vibration intensity (levels 1, 2 and 3), application time (1, 3, 5, 7 and 10 min), and application power (500, 700 and 1,000 g). The highest permeation of vitamin C was observed at level 3 of vibration intensity, 5 min of application, and 1,000 g of application power. Vitamin C gel showed no cytotoxic effect against Pam212 cells or skin irritation effects. A pharmacokinetic study of the gel in rats was conducted under optimized conditions. The AUC0-∞ and Cmax increased 1.35-fold and 1.44-fold, respectively, compared with those after vitamin C gel without application with vibrating microneedles. The present study suggests that vibrating microneedles can be used to facilitate the skin permeability of vitamin C under optimal conditions.

Flexible and Stretchable Piezoelectric Sensor with Thickness-Tunable Configuration of Electrospun Nanofiber Mat and Elastomeric Substrates.

Here, we developed highly sensitive piezoelectric sensors in which flexible membrane components were harmoniously integrated. An electrospun nanofiber mat of poly(vinylidenefluoride-co-trifluoroethylene) was sandwiched between two elastomer sheets with sputtered electrodes as an active layer for piezoelectricity. The developed sensory system was ultrasensitive in response to various microscale mechanical stimuli and able to perceive the corresponding deformation at a resolution of 1 µm. Owing to the highly flexible and resilient properties of the components, the durability of the device was sufficiently stable so that the measuring performance could still be effective under harsh conditions of repetitive stretching and folding. When employing spin-coated thin elastomer films, the thickness of the entire sandwich architecture could be less than 100 µm, thereby achieving sufficient compliance of mechanical deformation to accommodate artery-skin motion of the heart pulse. These skin-attachable film- or sheet-type mechanical sensors with high flexibility are expected to enable various applications in the field of wearable devices, medical monitoring systems, and electronic skin.

Compensation Method for Die Shift Caused by Flow Drag Force in Wafer-Level Molding Process.

Wafer-level packaging (WLP) is a next-generation semiconductor packaging technology that is important for realizing high-performance and ultra-thin semiconductor devices. However, the molding process, which is a part of the WLP process, has various problems such as a high defect rate and low predictability. Among the various defect factors, the die shift primarily determines the quality of the final product; therefore, predicting the die shift is necessary to achieve high-yield production in WLP. In this study, the die shift caused by the flow drag force of the epoxy molding compound (EMC) is evaluated from the die shift of a debonded molding wafer. Experimental and analytical methods were employed to evaluate the die shift occurring during each stage of the molding process and that resulting from the geometrical changes after the debonding process. The die shift caused by the EMC flow drag force is evaluated from the data on die movements due to thermal contraction/expansion and warpage. The relationship between the die shift and variation in the die gap is determined through regression analysis in order to predict the die shift due to the flow drag force. The results can be used for die realignment by predicting and compensating for the die shift.