The Integration of Nanomedicine with Traditional Chinese Medicine: Drug Delivery of Natural Products and Other Opportunities

The integration of progressive technologies such as nanomedicine with the use of natural products from traditional medicine (TM) provides a unique opportunity for the longed-for harmonization between traditional and modern medicine. Although several actions have been initiated decades ago, a disparity of reasons including some misunderstandings between each other limits the possibilities of a truly complementation. Herein, we analyze some common challenges between nanomedicine and traditional Chinese medicine (TCM). These challenges, if solved in a consensual way, can give a boost to such harmonization. Nanomedicine is a recently born technology, while TCM has been used by the Chinese people for thousands of years. However, for these disciplines, the regulation and standardization of many of the protocols, especially related to the toxicity and safety, regulatory aspects, and manufacturing procedures, are under discussion. Besides, both TCM and nanomedicine still need to achieve a wider social acceptance. Herein, we first briefly discuss the strengths and weaknesses of TCM. This analysis serves to focus afterward on the aspects where TCM and nanomedicine can mutually help to bridge the existing gaps between TCM and Western modern medicine. As discussed, many of these challenges can be applied to TM in general. Finally, recent successful cases in scientific literature that merge TCM and nanomedicine are reviewed as examples of the benefits of this harmonization

Advancing Translational Research by Enabling Collaborative Teamwork: The TRACT Approach

Background: The work of multidisciplinary research teams (MDRTs) is vital for translational research. The objectives of this study were 1) to understand the structure and function of MDRTs, and 2) to develop effective strategies to enhance collaboration among team members. Methods and Findings: Semi-structured interviews were conducted with 23 participants involved in multidisiplinary research work at two San Antonio, Texas, institutions. Interview materials were tape-recorded, transcribed, and content analyzed using qualitative methods.Themes that emerged from the content analysis were used to develop and refine strategies to enhance the work of MDRTs. The findings showed that MDRTs operate through multiple cycles of: 1) team formation, 2) team collaboration, 3) sustainable collaborative activities, and 4) team maturity. Content analysis identified four interrelated basic elements within the MDRT tract that facilitate team cycles: 1) shared interest/vision among agreeable team leader and members, 2) viable means of communication, 3) available resources, and 4) perceived gain/benefit of teamwork.Conclusions: Our findings highlighted several opportunities and challenges in the formation, dynamics, and growth of MDRTs. Effective strategies to enhance teamwork should levearge these opportunities and address challenges, taking into consideration the interdependent aspects of the basic elements within the MDRTs tract

Knowledge discovery with recommenders for big data management in science and engineering communities

Recent science and engineering research tasks are increasingly becoming dataintensive and use workflows to automate integration and analysis of voluminous data to test hypotheses. Particularly, bold scientific advances in areas of neuroscience and bioinformatics necessitate access to multiple data archives, heterogeneous software and computing resources, and multi-site interdisciplinary expertise. Datasets are evolving, and new tools are continuously invented for achieving new state-of-the-art performance. Principled cyber and software automation approaches to data-intensive analytics using systematic integration of cyberinfrastructure (CI) technologies and knowledge discovery driven algorithms will significantly enhance research and interdisciplinary collaborations in science and engineering. In this thesis, we demonstrate a novel recommender approach to discover latent knowledge patterns from both the infrastructure perspective (i.e., measurement recommender) and the applications perspective (i.e., topic recommender and scholar recommender). In the infrastructure perspective, we identify and diagnose network-wide anomaly events to address performance bottleneck by proposing a novel measurement recommender scheme. In cases where there is a lack of ground truth in networking performance monitoring (e.g., perfSONAR deployments), it is hard to pinpoint the root-cause analysis in a multi-domain context. To solve this problem, we define a "social plane" concept that relies on recommendation schemes to share diagnosis knowledge or work collaboratively. Our solution makes it easier for network operators and application users to quickly and effectively troubleshoot performance bottlenecks on wide-area network backbones. To evaluate our "measurement recommender", we use both real and synthetic datasets. The results show our measurement recommender scheme has high performance in terms of precision, recall, and accuracy, as well as efficiency in terms of the time taken for large volume measurement trace analysis. In the application perspective, our goal is to shorten time to knowledge discovery and adapt prior domain knowledge for computational and data-intensive communities. To achieve this goal, we design a novel topic recommender that leverages a domain-specific topic model (DSTM) algorithm to help scientists find the relevant tools or datasets for their applications. The DSTM is a probabilistic graphical model that extends the Latent Dirichlet Allocation (LDA) and uses the Markov chain Monte Carlo (MCMC) algorithm to infer latent patterns within a specific domain in an unsupervised manner. We evaluate our scheme based on large collections of the dataset (i.e., publications, tools, datasets) from bioinformatics and neuroscience domains. Our experiments result using the perplexity metric show that our model has better generalization performance within a domain for discovering highly-specific latent topics. Lastly, to enhance the collaborations among scholars to generate new knowledge, it is necessary to identify scholars with their specific research interests or cross-domain expertise. We propose a "ScholarFinder" model to quantify expert knowledge based on publications and funding records using a deep generative model. Our model embeds scholars' knowledge in order to recommend suitable scholars to perform multi-disciplinary tasks. We evaluate our model with state-of-the-art baseline models (e.g., XGBoost, DNN), and experiment results show that our ScholarFinder model outperforms state-ofthe-art models in terms of precision, recall, F1-score, and accuracy.Includes bibliographical references (pages 113-124)

Bioprospecting of microbial strains for biofuel production: metabolic engineering, applications, and challenges

The issues of global warming, coupled with fossil fuel depletion, have undoubtedly led to renewed interest in other sources of commercial fuels. The search for renewable fuels has motivated research into the biological degradation of lignocellulosic biomass feedstock to produce biofuels such as bioethanol, biodiesel, and biohydrogen. The model strain for biofuel production needs the capability to utilize a high amount of substrate, transportation of sugar through fast and deregulated pathways, ability to tolerate inhibitory compounds and end products, and increased metabolic fluxes to produce an improved fermentation product. Engineering microbes might be a great approach to produce biofuel from lignocellulosic biomass by exploiting metabolic pathways economically. Metabolic engineering is an advanced technology for the construction of highly effective microbial cell factories and a key component for the next-generation bioeconomy. It has been extensively used to redirect the biosynthetic pathway to produce desired products in several native or engineered hosts. A wide range of novel compounds has been manufactured through engineering metabolic pathways or endogenous metabolism optimizations by metabolic engineers. This review is focused on the potential utilization of engineered strains to produce biofuel and gives prospects for improvement in metabolic engineering for new strain development using advanced technologies.Instituto de BiotecnologíaFil: Adegboye, Mobolaji Felicia. North-West University. Faculty of Natural and Agricultural Sciences. Food Security and Safety Niche Area; SudáfricaFil: Ojuederie, Omena Bernard. North-West University. Faculty of Natural and Agricultural Sciences. Food Security and Safety Niche Area; SudáfricaFil: Ojuederie, Omena Bernard. Kings University. Faculty of Science. Department of Biological Sciences; NigeriaFil: Talia, Paola Mónica. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular (IABIMO); ArgentinaFil: Talia, Paola Mónica. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Babalola, Olubukola Oluranti. North-West University. Faculty of Natural and Agricultural Sciences. Food Security and Safety Niche Area; Sudáfric

Universal Leadership Model

The Great Commission is the call of Jesus to his people to go out into the world and make disciples. The universal leadership model presents an opportunity for disciples/leaders to step up and fulfill the Great Commission. The church should be involved in discipleship training, outreaches and supporting the issues that are aligned with Christian ideology and important to people in the communities they serve. An effective universal leadership model should include diversity, training, desired change, accountability and effectiveness of change. In so doing, the church can then find parishioners within the church who may be transformed into disciples/leaders and communities will become stronger because of the immersion of disciples into our communities. The researcher utilized a 50-question anonymous survey taken by 161 participants. The questionnaire was presented electronically to Christians and non-Christians over the age of 18. The data gathered should encourage leaders to lead from the top, re-evaluate disciple/leadership training programs and to develop leaders with a heart for fulfilling the Great Commission

Preclinical Development of Therapeutic Strategies Against Triple-Negative and Inflammatory Breast Cancer

Triple-negative (TNBC) and inflammatory (IBC) breast cancer are the most aggressive forms of breast cancer, accounting for 20% and 10% of cancer-related deaths, respectively. Among IBC cases, 30% are additionally classified with TNBC molecular pathology, a diagnosis that significantly worsens patient’s prognosis. The current lack of TNBC and IBC molecular understanding prevents the development of effective therapeutic strategies. To identify effective treatments, we explored aberrant apoptosis pathways and cell membrane fluidity as novel therapeutic targets. We first identified an effective therapeutic strategy against TNBC and IBC by pro-apoptotic protein NOXA-mediated inhibition of the anti-apoptotic protein MCL1 following inhibition of histone deacetylases (HDAC) in combination with inhibition of the oncogenic MEK pathway. In breast cancer patients, low NOXA/high MCL1 tumor expression is indeed associated to poor survival outcomes, supporting the induction of NOXA expression, and subsequent inhibition of MCL1, for the treatment against TNBC and IBC. Secondly, we investigated the role of an anti-inflammatory and non-toxic polyunsaturated fatty acid, eicosapentaenoic acid (EPA), for the development of a treatment strategy against TNBC and IBC. Through a synthetic-lethal siRNA high-throughput screen we identified inhibition of EPHA2, an oncogenic protein specifically associated to poor survival in TNBC patients, to be the top candidate that enhanced EPA cytotoxicity against TNBC and IBC cells. Though functional assays, we identified combination EPA and EPHA2-inhibition to be an effective therapeutic strategy involving the induction of cell death via modulation of cell membrane fluidity by ABCA1 inhibition-mediated intracellular cholesterol accumulation in triple-negative IBC cells. In summary, here we provide robust preclinical evidence that supports the Phase I clinical development of combination HDAC and MEK inhibitors, and of EPA and EPHA2-inhibition, for the treatment of patients with TNBC and IBC

Doctor of Philosophy

dissertationThe purpose of this study was to determine the efficacy of and participant experiences with the Live Health Positive (LHP) program, a positive health education program that aimed to improve psychological wellbeing and physical health behaviors by incorporating lessons from non-diet approaches, resilience, and self-compassion. This program was implemented with employees of an institute of higher education in northern Utah. The study employed a mixed methods experimental design. Employees were randomized to either the LHP program or a non-diet comparison program (NDP); 29 participants completed the study (LHP: 17, NDP: 12). Surveys conducted at three time-points (pretest, posttest, follow-up) and focus groups were used to evaluate the program and understand participants’ experiences. This dissertation is presented in a three-article format. Chapters 2, 3, and 4 are intended for publication in health education literature. Chapter 2 is a commentary on the need to include psychological wellbeing modules in health education programs due to its relationship with health-enhancing behaviors and improved physiological function. Chapter 3 presents participants’ experiences with the LHP program. Participants reported high levels of program satisfaction, particularly in regards to connectedness, self-awareness, and self-kindness. Chapter 4 compares the outcomes of the LHP and NDP programs. Intuitive eating significantly improved in both groups from pretest to posttest (LHP: M = .615, 95% CI [0.305, 0.925], p<.001; NDP: M = .522, 95% CI [0.186, 0.858], p=.003), and from pretest to follow-up (LHP: M = .518, 95% CI [0.177, 0.858], p=.003; NDP: M = .445, 95% CI [0.185, 0.705], p=.002). In addition, enjoyment motivations for physical activity significantly improved in the LHP group from pretest to posttest (M = 1.084, 95% CI [0.380, 1.788], p=.002). At posttest, the LHP group reported significantly higher enjoyment motivations for engaging in physical activity than NDP, M=.751, 95% CI [0.108, 1.393], t(25.528) = 2.403, p=.024. Participants’ experiences with maintaining health behavior changes are also described, including themes of lifestyle barriers, support needs, resonation to course content, and standing up for one’s needs. Finally, Chapter 5 summarizes the study and offers directions for future research on positive health education programs

Overcoming primary and acquired erlotinib resistance with epidermal growth factor receptor (EGFR) and phosphoinositide 3-kinase (PI3K) co-inhibition in pancreatic cancer

PI3K/Akt is over-expressed in 50-70% of pancreatic ductal adenocarcinoma (PDAC). The hypothesis of this study is that PI3K and EGFR co-inhibition may be effective in PDAC with upregulated PI3K/Akt/mTOR (PAM) signaling. Five primary PDAC and two erlotinib acquired resistant (ER) cell lines with significantly over-expressed AKT2 gene, total Akt and pAkt, were used. Multiple inhibitors of the MAPK and PAM were tested alone or in combination by western blotting, cell proliferation, cell cycle, clonogenic, apoptosis, and migration assays. Erlotinib acted synergistically with PI3Kα inhibitor BYL in both ER cell lines (synergy index, SI=1.71 and 1.44 respectively). Treatment of ER cell lines by this dual blockade caused significant G1 cell cycle arrest (71%, P<0.001; 58%, P=0.003), inhibition of colony formation (69% and 72%, both P<0.001), and necrosis and apoptosis (75% and 53%, both P<0.001), more so compared to parent cell lines. In primary patient-derived tumor subrenal capsule (n=90) and subcutaneous (n=22) xenografts, Erlotinib plus BYL significantly reduced tumor volume (P=0.005). Strong pEGFR and pAkt immunostaining (2+/3+) was correlated with high response to erlotinib and low response to erlotinib plus BYL respectively. In conclusion, PDAC with increased expression of the PAM signaling were susceptible to PI3K/ EGFR co-inhibition suggesting oncogenic dependence. Erlotinib plus BYL should be considered for a clinical study in PDAC; further evaluation of pEGFR and pAkt expression as potential predictive biomarkers is warranted

2022 Summer Experience Program Abstracts

The mission of the MD Anderson Summer Experience Program is to eliminate cancer, through training of high School, undergraduates and first year medical students to make a lasting impact on training the next generation of scientist and physicians through research and education. The MD Anderson Summer Experience is an umbrella program that comprises 18 summer academic programs at MD Anderson. The summer research program is an 8-10 week program that offers hands-on experience in biomedical, translational or clinical research. In this program, students are matched with a mentor from MD Anderson’s research or clinical faculty. Participants work alongside the mentor in a lab or clinic, on projects designed by faculty to reflect current research. Workshops and lectures provide opportunities to connect with faculty, residents, postdoctoral and clinical fellows, and other participants. Through the program, students assess goals related to careers in oncology research and patient care. The program culminates with a symposium in which participants present talks and posters on their research projects to peers and faculty.https://openworks.mdanderson.org/sumexp22/1061/thumbnail.jp