Keiko Unno | Brain Function | Best Researcher Award

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Dr. Keiko Unno | Brain Function | Best Researcher Award

Doctorate and Tea Sciense Center,  Japan

Dr. Keiko Unno is a renowned researcher in the field of pharmaceutical sciences with a particular focus on brain health and the impact of dietary compounds. With an educational background from Shizuoka College of Pharmacy and the University of Shizuoka, she has dedicated her career to exploring the beneficial effects of green tea and other compounds on brain function and aging. Her extensive research includes studying the impact of green tea on brain aging, the potential of dietary DNA to reduce stress, and the role of coffee polyphenols in preventing oxidative damage. Dr. Unno has been recognized for her contributions with several prestigious awards, including the Society of Tea Science Young Researcher’s Award and the World Green Tea Association’s O-CHA Pioneer Award. Currently, she serves as a Visiting Associate Professor at the Tea Science Center, University of Shizuoka, continuing her impactful research.

Profile
Education

Dr. Keiko Unno obtained her Bachelor of Science (B.S.) degree from Shizuoka College of Pharmacy in 1976. She continued her academic journey and earned a Ph.D. from the University of Shizuoka in 1994, where her research focused on areas pertinent to pharmaceutical sciences.

Professional Experience

Dr. Unno began her career as a Research Associate at Shizuoka College of Pharmacy in 1976, where she worked until 1987. Following this, she joined the University of Shizuoka’s School of Pharmaceutical Sciences, where she held various positions including Research Associate, Assistant Professor, and Associate Professor from 1987 to 2019. In 2019, she transitioned to her current role as a Visiting Associate Professor at the Tea Science Center, University of Shizuoka. Her professional trajectory highlights her extensive experience in pharmaceutical sciences and her specialization in the effects of tea and related compounds on health.

Research Interests

Dr. Unno’s research primarily focuses on:

  1. Prevention Against Brain Dysfunction with Aging: Investigating methods to mitigate cognitive decline associated with aging.
  2. Effect of Psychosocial Stress on Brain Function: Examining how stress impacts brain health and function.
Author Metric

Dr. Unno has authored several notable publications, reflecting her research contributions in the field:

  • 2024: “DNA Mutagenicity of Hydroxyhydroquinone in Roasted Coffee Products and Its Suppression by Chlorogenic Acid, a Coffee Polyphenol, in Oxidative-Damage-Sensitive SAMP8 Mice” in International Journal of Molecular Sciences (25:720).
  • 2023: “Stress Reduction Potential in Mice Ingesting DNA from Salmon Milt” in Biology (12:978).
  • 2022: “Improvement of Depressed Mood with Green Tea Intake” in Nutrients (14:2949).
  • 2021: “Green Tea Suppresses Brain Aging” in Molecules (26:4897).

Dr. Unno’s research has garnered attention in the academic community, as evidenced by her recent publications and the awards she has received for her work. Her contributions continue to advance the understanding of dietary impacts on brain health and aging.

Conclusion

Dr. Unno’s contributions to her field are marked by a dedication to advancing knowledge through rigorous research and a focus on the practical applications of her findings. Her continued work promises to provide valuable insights into the complex interactions between diet, stress, and brain health.

Publications Top Notes

  • “Stress Reduction Potential in Mice Ingesting DNA from Salmon Milt”
  • “Enokitake Mushroom and Its Active Component, Adenosine, Which Restores Testosterone Production in Impaired and Fatigued Mouse Models”
  • “Mouse Models with SGLT2 Mutations: Toward Understanding the Role of SGLT2 beyond Glucose Reabsorption”
    • Journal: International Journal of Molecular Sciences
    • Publication Date: March 27, 2023
    • DOI: 10.3390/ijms24076278
  • “Theanine, a Tea-Leaf-Specific Amino Acid, Alleviates Stress through Modulation of Npas4 Expression in Group-Housed Older Mice”
    • Journal: International Journal of Molecular Sciences
    • Publication Date: February 16, 2023
    • DOI: 10.3390/ijms24043983
  • “Effects of Epigallocatechin-3-Gallate on Matrix Metalloproteinases in Terms of Its Anticancer Activity”

 

 

Assist Prof Dr. Umair Ayub | Computational Biology | Best Researcher Award

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Assist Prof Dr. Umair Ayub | Computational Biology | Best Researcher Award

Assist Prof at Computational Biology, Bahria University Lahore Campus, Pakistan

👨‍🎓He remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 He successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Umair Ayub has pursued a Ph.D. in Computer Science from August 2019 to December 2022 at the National University of Computer and Emerging Sciences in Islamabad, Pakistan, achieving an impressive CGPA of 3.95/4.0. His doctoral thesis focused on “Protein-Protein Interaction Network Alignment,” specifically examining the global and local alignment of two PPI networks. Prior to his Ph.D., Umair completed an MS in Computer Science from August 2016 to June 2018, with a CGPA of 3.65/4.0. His master’s thesis centered on the “Optimization of Ant-Miner (a rule-based classifier) Algorithm to Extract Accurate Classification Rules.” Umair initiated his academic journey with a BS in Computer Science from August 2012 to June 2016, earning a CGPA of 2.85/4.0. For his final year project, he worked on the “Automation of University Inventory System with Inventory Utilization Prediction and AI-based Reporting.”

Experience:

Umair Ayub’s professional journey in academia and research includes various significant roles:

  • Assistant Professor at Bahria University Lahore Campus, Lahore, Pakistan, since February 2023. In this role, he teaches computer science and data science courses at both undergraduate and graduate levels. Additionally, he serves as a member of the faculty hiring committee of the computer science department and leads the panel for final year projects.
  • Lecturer to Assistant Professor at the University of Management and Technology, Lahore, Pakistan, from September 2022 to March 2023. Here, he taught computer science courses at the undergraduate level and served as a member of the technical review committee for final-year projects.
  • Visiting Faculty Member at the National University of Computer and Emerging Sciences, Islamabad, from January 2022 to June 2022. In this position, he taught Data Structures and Algorithm Courses at the undergraduate level.
  • Research Associate at the Computational Biology Research Lab, Department of Computing, National University of Computer and Emerging Sciences, Islamabad, Pakistan, from September 2018 to August 2022. During this time, he conducted research in computational biology, machine learning, and deep learning. Additionally, he guided BS/MS students in understanding their research problems and helped them with machine learning models.

Research Projects:

Umair Ayub is currently involved in several research projects, including:

  • 3D Structure Prediction of Beta Barrel Membrane Proteins.
  • Forest of Genetic Algorithm for Functions Optimization.

Additionally, he is supervising the following MS-Thesis projects:

  • An Accurate Structure Aware Graph Convolutional Model for Extraction of Node Embeddings from Large Networks Data.
  • Impact of Different Topological Methods on PPI Network Alignment.
  • Gender and Age Group Identification using Facial Data.
  • Prediction of Autism Spectrum Disorder from Facial Data.

Research Areas:

Umair Ayub’s research areas include Machine Learning, Computational Biology, Networks Analysis, Swarm and Computational Intelligence, Statistical Modeling, and Function Optimization.

He has conducted several training workshops, including:

  • A 4-Day Training Workshop at the Bahria University Lahore Campus, Lahore. The primary objective of the workshop was to introduce students to the tools and techniques used in AI to solve complex problems.
  • A 5-day Training Workshop at the NUCES, Lahore. The primary objective of this workshop was to prepare students for research-related projects in the domain of AI in Healthcare.
  • A 5-day Training Workshop at the NUCES, Islamabad. The primary objective of this workshop was to introduce students to the AI domain with a specialty in healthcare.

 Skills:

Umair Ayub has achieved several distinctions, including being named the Punjab Educational Endowment Fund Scholar from 2016 to 2018 and earning the Bronze Medal in MS(CS) at NUCES, Islamabad. His skills include proficiency in Python, C++, LaTeX, Sklearn, Pytorch, Matplotlib, Numpy, and Linux.

Publications:

Title: “Predicting crop diseases using data mining approaches: classification” Authors: U Ayub, SA Moqurrab Year: 2018 Citations: 41

Title: “An accurate deep learning model for clinical entity recognition from clinical notes” Authors: SA Moqurrab, U Ayub, A Anjum, S Asghar, G Srivastava Year: 2021 Citations: 25

Title: “SAlign–a structure aware method for global PPI network alignment” Authors: U Ayub, I Haider, H Naveed Year: 2020 Citations: 12

Title: “PRRAT_AM—an advanced ant-miner to extract accurate and comprehensible classification rules” Authors: U Ayub, H Naveed, W Shahzad Year: 2020 Citations: 4

Title: “Opinion and emotion mining for Pakistan general election 2018 on Twitter data” Authors: S Khan, SA Moqurrab, R Sehar, U Ayub Year: 2019 Citations: 4

Title: “AMclr an improved ant-miner to extract comprehensible and diverse classification rules” Authors: U Ayub, A Ikram, W Shahzad Year: 2019 Citations: 3

Title: “BioAlign: An Accurate Global PPI Network Alignment Algorithm” Authors: U Ayub, H Naveed Year: 2022 Citations: 2

Title: “GSLAlign: community detection and local PPI network alignment” Authors: U Ayub Year: Not provided Citations: Not provided

 

Mr. Sebastian Vacca | Neuroimaging

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🎉🏆 Congratulations, Mr. Sebastian Vacca , on Your Outstanding Achievement as the Best Researcher! 🏆🎉
Mr. Sebastian Vacca : Leading Researcher in Social Work

Medical Student at Neuroimaging, Università degli Studi di Cagliari, Italy

Your remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 Your successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Research Collaborator at Mayo Clinic

At Mayo Clinic, I serve as a Research Collaborator, contributing to a focused Deep Learning Project aimed at enhancing the segmentation of brain tumors, with a particular emphasis on intracranial meningiomas. Under the guidance of Supervisor Gian Marco Conte, MD PhD, my role involves applying advanced techniques to improve the accuracy of brain tumor segmentation.

Research Assistant at Cagliari State University – Radiology Department

As a Research Assistant at Cagliari State University’s Radiology Department, I actively participate in multiple projects investigating radiological anomalies. Employing Statistical methods and Machine Learning models, I analyze clinical and imaging data from patients with neurologic lupus. Additionally, I lead efforts in conducting systematic reviews with meta-analysis, specifically focusing on the application of radiomics in carotid atherosclerotic disease. I am also involved in constructing a machine learning model based on radiomics and automated segmentation to predict atherosclerotic plaque at risk for stroke, working under the guidance of Professor Luca Saba, MD.

Scientific Collaborator at One Medic – The One Health Community

In my role as a Scientific Collaborator at One Medic, I am an active member of the Research and Podcast Team. I contributed to a Bibliometric study, exploring the most cited articles in the field of One Health. Additionally, I played a crucial role in organizing and supporting podcast activities, combining research insights with effective communication strategies.

Diverse Research and Academic Contributions

Research Trainee – International Journal of Clinical Research [ 03/2023 – 12/2023 ] As the Group Leader for a Neurology Research Working Group, I led a comprehensive review on treatment options for Multiple Sclerosis. This role allowed me to delve into the intricacies of neurological research, contributing valuable insights to the field.

Visiting Medical Student – Technische Universität München [ 01/09/2022 – 30/11/2022 ] During my tenure as a student researcher in the Functional Neuronavigation and Monitoring Working Group, I played a crucial role in analyzing clinical, DTI, and Tractography data from patients with a Corpus Callosum GBM. Responsible for data collection, I also contributed to CC segmentation using ITK-SNAP, tumor segmentation, Fiber-Tracking on BrainLab Elements, and performed statistical analysis under the guidance of Prof Dr. Med Sebastian Ille.

Publication

Title: SBM vs VBM for highlighting similarities and differences between Chronotype and Parkinson’s MRI scans: a preliminary analysis

Publication Date: 2023

Authors: Sebastiano Vacca, Jyoti Suri, Luca Saba

Journal: International Journal of Neuroscience