Lipid nanoparticle library towards development next generation genomic medicines

Ionizable amino lipids are a major constituent of the lipid nanoparticles for delivering nucleic acid therapeutics (e.g., DLin-MC3-DMA in ONPATTRO , ALC-0315 in Comirnaty , SM-102 in Spikevax ). Scarcity of lipids that are suitable for cell therapy, vaccination, and gene therapies continue to be a problem in advancing many potential diagnostic/therapeutic/vaccine candidates to the clinic. Herein, we describe the development of novel ionizable lipids to be used as functional excipients for designing vehicles for nucleic acid therapeutics/vaccines in vivo or ex vivo use in cell therapy applications. We first studied the transfection efficiency (TE) of LNP-based mRNA formulations of these ionizable lipid candidates in primary human T cells and established a workflow for engineering of primary immune T cells. We then adapted this workflow towards bioengineering of CAR constructs to T cells towards non-viral CAR T therapy. Lipids were also tested in rodents for vaccine applications using self-amplifying RNA (saRNA) encoding various antigens. We have then evaluated various ionizable lipid candidates and their biodistribution along with the mRNA/DNA translation exploration using various LNP compositions. Further, using ionizable lipids from the library, we have shown gene editing of various targets in rodents. We believe that these studies will pave the path to the advancement in nucleic acid based therapeutics and vaccines, or cell gene therapy agents for early diagnosis and detection of cancer, and for targeted genomic medicines towards cancer treatment and diagnosis.

EVALUATING LEARNING EFFECTIVENESS TOWARDS ONLINE LEARNING: APPLICATION OF DESIGN THINKING AND READING COMPREHENSION FOR CASE READING ON ECONOMIC ISSUES DURING COVID-19

This study focuses on developing an effective online teaching strategy to improve students' cognition engagement and application ability by applying design thinking and case readings on current economic issues for private university students in Taiwan during the COVID-19 pandemic. The teaching method combines design thinking and the reading comprehension process by the two principles of divergence and convergence. The design thinking method provides stepwise guidance for building understanding and analyzing competence on current economic issues. The reading comprehension process strengthens students' reading skills and learning capability. This combination increases student engagement and concentration in economic case readings during online learning. The research participants comprised 189 first-year students studying economics courses. After implementing the innovative teaching strategies, the results show that the more students are involved in frequent readings, the better are their economics semester grade. The findings revealed that their post-quiz scores improved significantly, and the semester grade increased by 3.44 points. Increasing the reading engagement on current economic issues cases also affected the learning outcomes for absentees. Using design thinking to introduce case reading comprehension, empathy has been suggested as an essential factor affecting the effectiveness of reading learning. This theoretical model can offer directional insights and guidance on developing an effective strategy in online economics education. © 2022 Conscientia Beam. All Rights Reserved.

Effect of Non-Cavity-Distorting Intramural Myomas on Pregnancy Outcomes in Euploid Frozen Embryo Transfer Cycles: A Prospective Study

Objective: We sought to evaluate the impact of non-cavity-distorting intramural myomas on pregnancy outcomes in an ideal study group: patients undergoing frozen embryo transfer (FET) of a single euploid blastocyst. Material(s) and Method(s): This is an interval analysis of a prospective cohort study at a single large university-affiliated institution from January 2018 to April 2022. There was a hiatus in recruitment from March 2020 to February 2022 due to the COVID-19 pandemic. All patients underwent an autologous natural or programmed FET with endometrial preparation and luteal support per a standardized protocol. Prior to transfer, patients were divided based on the presence (Group A) or absence (Group B) of non-cavity-distorting myomas. All ultrasounds (US) were performed by physicians. If myomas were detected, their number, size, location (FIGO classification system), and distance from the uterine cavity were recorded. The primary outcome was clinical intrauterine pregnancy (IUP). The secondary outcomes were positive human chorionic gonadotropin (hCG) test, biochemical pregnancy, missed abortion, and ongoing pregnancy and live birth rates. A Fisher's exact test was done to compare proportions. A p-value of <0.05 was deemed statistically significant. Result(s): Of the 122 enrolled patients, 19 (15.6%) had a non-cavity-distorting intramural myoma (Group A), while 103 (84.4%) did not have a myoma (Group B). No patients had a cavity-distorting myoma. The patients who had myomas tended to be older with a higher BMI, but otherwise had similar baseline characteristics including gravidity, parity, endometrial thickness, peak estradiol level, and AMH. There was no significant difference in the proportion of patients who achieved a clinical IUP in Group A (52.6%) and Group B (63.1%, p=0.45). There was also no difference in the secondary outcomes (Table 1). Conclusion(s): This prospective observational study has not demonstrated a significant impact of non-cavity-distorting intramural myomas on FET outcomes, although this study is ongoing and will continue to recruit patients. Impact Statement: Non-cavity-distorting myomas do not appear to affect positive hCG, biochemical, clinical IUP rate, miscarriage, or ongoing pregnancy or live birth rates in an ideal study population of single euploid FET transfer cycles. Copyright © 2022

Household Structure Projection: A Monte-Carlo based Approach

The kernel of an agent based simulation system for spreading of infectious disease needs a so called household structure (HSD) of the area being simulated which contains a list of households with the age of each member in the household being recorded. Such a household structure is available in a Census that is usually released every 10 years. Previous researches have shown the changing of the household structure has a great impact on disease spreading patterns. It is observed that the changing of the household structure e.g., the average citizen ages and household size, is at a faster speed. However, serious infectious diseases, such as SARS (year 2002), H1N1 (year 2009) and COVID-19 (year 2019), occur with a higher frequency now than previous eras. For example, it would be bad to use HSD2010 built using Census 2010 to simulate COVID-19. In view of this situation, we need a better way to obtain a good household structure in between the Census years in order for an agent-based simulation system to be effective. Note that though a detailed Census is not available every year, aggregated information such as the number of households with a particular size, and the number of people of a particular age are usually available almost monthly. Given HSDx, the household structure for year x, and the aggregated information from year y where y > x, we propose a Monte-Carlo based approach "patching" HSDx to get an approximated HSDy. To validate our algorithm, we pick x and y - x + 10 which both Censuses are available and find out the root-mean-square error (RMSE) between Census's HSDy and generated HSDy is fairly small for x = 1990 and 2000. The spreading patterns obtained by our simulation system have good matches. We hence obtain HSD2020 to be used in your system for studying the spreading of COVID-19.