Cell Therapy in Huntington’s Disease

Huntington’s disease (HD) is a rare neurodegenerative disease inherited in an autosomal dominant pattern. Expanded cytosine-adenine-guanine (CAG) repeats (polyQ) in the huntingtin gene cause the aggregates of abnormally expanded polyQ-containing huntingtin protein, and striatal medium spiny neurons are shown to be the most vulnerable. Affected patients develop cognitive, motor, and psychiatric symptoms typically in middle age, and several pharmacological drugs are currently used for symptomatic relief. Since the effect of current therapies is very limited and there is no way to modify disease progression, there is an unmet need for developing new therapies for HD. Toxin or genetic rodent models are widely used for drug development, and large animal models are also available. Previous studies transplanting cells originating from embryonic or fetal striatal tissues, neural stem cells, mesenchymal stem cells, and induced pluripotent stem cells (iPSCs) in HD animal models have shown the possibilities of clinical trials. Because clinical trials performed using human fetal striatal cells have shown variable outcomes, future directions of cell therapy in HD should consider the reconstitution of a functional dynamic information-processing circuit without ectopic connections. Another major challenge is to achieve controlled differentiation of embryonic stem cells or iPSCs into specific neuronal phenotypes

Effects of driving style and bedding in pigs transported to slaughterhouse in different temperatures

Animal welfare during transport became an largely issue because of increasing demand for improved animal welfare standards. Most studies on the animal welfare during transportation have concentrated on the atmosphere and the temperature of the truck compartments. Thus, the objective of study was to collect and quantify three axis acceleration and determine the effect of bedding for transporting pigs from farm to slaughterhouse. A total of 2,840 crossbred fattening pigs with a live weight of approximately 115 kg were used. They were raised in the same commercial farms and transported to the same commercial slaughterhouse. A 3×2×2 completely randomized factorial design was used to investigate effects of rubber type bedding (bedding or non-bedding) and two levels of driving style (aggressive or normal) in three different time periods with different outside temperatures. Air temperature treatments were as follow: high temperature ([HT] higher than 24°C); low temperature ([LT] lower than 10°C); normal temperature ([NT] 10°C to 24°C). In our experiment, pigs transported under aggressive driving style showed lower (p < 0.05) pH and water holding capacity (WHC) than those transported under normal driving style. Pigs transported under normal driving style showed a lower percentage of drip loss (DL) (p < 0.05) than those transported with an aggressive driving style. Also, transported with bedding showed higher (p < 0.05) lying behavior but lower (p < 0.05) sitting behavior than those transported without bedding. Pigs transported under normal driving style showed lower (p < 0.05) cortisol level than those transported under aggressive driving style. In conclusion, aggressive driving style cause acute stress in pigs, while bedding helps alleviate acute stress in pigs during transportation in LT

iPSC Modeling of Presenilin1 Mutation in Alzheimer's Disease with Cerebellar Ataxia.

Disease modeling of Alzheimer's disease (AD) has been hampered by the lack of suitable cellular models while animal models are mainly based on the overexpression of AD-related genes which often results in an overemphasis of certain pathways and is also confounded by aging. In this study, we therefore developed and used induced pluripotent stem cell (iPSC) lines from a middle-aged AD patient with a known presenilin 1 (PSEN1) mutation (Glu120Lys; PS1-E120K) and as a control, an elderly normal subject. Using this approach, we demonstrated that the extracellular accumulation of Aβ was dramatically increased in PS1-E120K iPSC-derived neurons compared with the control iPSC line. PS1-E120K iPSC-derived neurons also exhibited high levels of phosphorylated tau, as well as mitochondrial abnormalities and defective autophagy. Given that the effect of aging is lost with iPSC generation, these abnormal cellular features are therefore indicative of PSEN1-associated AD pathogenesis rather than primary changes associated with aging. Taken together, this iPSC-based approach of AD modeling can now be used to better understand AD pathogenesis as well as a tool for drug discovery.This work was supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HI14C2746) and a grant (2016-0588) from the Asan Institute for Life Sciences

Spatiotemporally controlled drug delivery via photothermally driven conformational change of self-integrated plasmonic hybrid nanogels

Background Spatiotemporal regulation is one of the major considerations for developing a controlled and targeted drug delivery system to treat diseases efficiently. Light-responsive plasmonic nanostructures take advantage due to their tunable optical and photothermal properties by changing size, shape, and spatial arrangement. Results In this study, self-integrated plasmonic hybrid nanogels (PHNs) are developed for spatiotemporally controllable drug delivery through light-driven conformational change and photothermally-boosted endosomal escape. PHNs are easily synthesized through the simultaneous integration of gold nanoparticles (GNPs), thermo-responsive poly (N-isopropyl acrylamide), and linker molecules during polymerization. Wave-optic simulations reveal that the size of the PHNs and the density of the integrated GNPs are crucial factors in modulating photothermal conversion. Several linkers with varying molecular weights are inserted for the optimal PHNs, and the alginate-linked PHN (A-PHN) achieves more than twofold enhanced heat conversion compared with others. Since light-mediated conformational changes occur transiently, drug delivery is achieved in a spatiotemporally controlled manner. Furthermore, light-induced heat generation from cellular internalized A-PHNs enables pinpoint cytosolic delivery through the endosomal rupture. Finally, the deeper penetration for the enhanced delivery efficiency by A-PHNs is validated using multicellular spheroid. Conclusion This study offers a strategy for synthesizing light-responsive nanocarriers and an in-depth understanding of light-modulated site-specific drug delivery.This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (Ministry of Science, ICT and Future Planning, No. 2023R1A2C2003947) for S.L., D.K., H.K., and I.C. This work was supported by the Samsung Research Funding and Incubation Center for Future Technology (SRFC-IT1802-03) for S.L., J.Y., H.K., and I.C. This work was supported by Basic Science Research Program through the NRF funded by the MSIT (No. 2021R1F1A1062856) and was also supported by Regional Innovation Strategy (RIS) through the NRF funded by the Ministry of Education (MOE) (2021RIS-004) for S.K. and J.S

ISSCR standards for the use of human stem cells in basic research.

The laboratory culture of human stem cells seeks to capture a cellular state as an in vitro surrogate of a biological system. For the results and outputs from this research to be accurate, meaningful, and durable, standards that ensure reproducibility and reliability of the data should be applied. Although such standards have been previously proposed for repositories and distribution centers, no widely accepted best practices exist for laboratory research with human pluripotent and tissue stem cells. To fill that void, the International Society for Stem Cell Research has developed a set of recommendations, including reporting criteria, for scientists in basic research laboratories. These criteria are designed to be technically and financially feasible and, when implemented, enhance the reproducibility and rigor of stem cell research

Updating Probabilistic Model of Traffic Loads on Bridges Using In-Service WIM Data

These days, a Weigh-In-Motion (WIM) system enables us to estimate traffic loads on a bridge based on site-specific traffic environment. However, since the traffic environment of a bridge may change significantly during its service life, it is necessary to monitor the in-service traffic environment and to update the probabilistic model of traffic load. This study aims to develop a methodology to update distribution parameters of random variables in the probabilistic traffic load model by Bayesian inference. Three main methods are used together to establish the updating methodology: conjugate prior distributions, Bayesian linear regression, and Gibbs sampling. The proposed method is demonstrated by numerical examples using WIM data from two sites in South Korea.The authors would like to gratefully acknowledge the support by the research project, Development of Life-cycle Engineering Techniques and Construction Methods for Global Competitiveness Upgrades of Cable Bridges of the Ministry of Land, Infrastructure and Transport (MOLIT) of the Korean Government (Grant No. 19SCIP-B119960-04)

Bayesian updating methodology for probabilistic model of bridge traffic loads using in-service data of traffic environment

The traffic environment of a bridge generally varies over its lifetime and can be affected by unexpected changes in the surroundings such as the construction of new roads. Therefore, for accurate estimation of traffic loads, changes in the traffic environment need to be continuously monitored and incorporated into traffic load predictions. To this end, this study first further develops the comprehensive probabilistic model of bridge traffic loads by introducing micro-simulation models to describe accurately congestion state. Next, a Bayesian methodology is proposed to update the parameters of the distributions in the probabilistic model of bridge traffic loads based on in-service data representing the traffic environment. Three Bayesian inference methods are used: conjugate prior distributions, Bayesian linear regression, and Gibbs sampling. Hyper-parameters of the prior model are set up appropriately based on the measurement accuracy and the degrees of belief in the prior model. The proposed Bayesian updating methodology is demonstrated by numerical examples with various scenarios of traffic environment changes and in-service weigh-in-motion (WIM) data measured on a real bridge. The results confirm that the proposed methodology can successfully incorporate changes of the traffic environment into the estimation of traffic load effects on bridges in operation.N

Multi-Scale Coupled Mechanical-Electrochemical Modeling for Study on Stress Generation and its Impact on Multi-Layered Electrodes in Lithium-Ion Batteries

This study develops a physics-based mechanical-electrochemical coupled modeling framework to investigate the stress generation and its impact on cell performance. This framework is based on a multi-scale approach, from particle to cell level, and includes several layers of electrodes in lithium-ion batteries (LIBs). In LIBs, (de)intercalation-induced stress plays a significant role in battery performance and degradation; however, the key challenge is that its impact occurs across multiple scales. The model integrates particle-level volume expansion into cell-level deformation, stress, and electrochemical performances. The study reveals that the volume changes due to lithium intercalation generate significant stress, which can easily break the binder and in-between particles. Compared with the substantial stress generated from active particles, the external pressure is much smaller and has an insignificant influence on the cell performance. However, these external pressures decrease the total thickness of the multi-layered electrodes and their variation. Inhomogeneous current inputs were also applied between the electrode layers, which showed a considerable degradation of cell performance. The developed model captures the effects of external pressure, the number of electrode layers, and inhomogeneous current inputs on the electrochemical-mechanical behaviors, which are critical for battery design and management from the particle level to larger-scale battery structures