Month: February 2021

Researchers from the School of Chinese Medicine (SCM) at Hong Kong Baptist University (HKBU) have developed a Chinese medicine formula named “NeuroDefend” that offers a potential novel treatment for Alzheimer’s disease (AD). Mouse model experiment results showed that the formula reduces the levels of amyloid-beta (Aβ) and insoluble hyperphosphorylated-tau protein, which are the major hallmarks of AD, in mice brains. It also improves cognitive function and memory in mice.

Novel formula combining six Chinese herbal medicines

AD is a chronic neurodegenerative disease that constitutes 60 to 70% of dementia cases worldwide. It is characterized by the “senile plaques” that are formed by the abnormal accumulation of Aβ, and the neurofibrillary tangles associated with the abnormal accumulation of hyperphosphorylated tau-associated neurofibrillary tangles (NFTs) in the brain.

Researchers led by Professor Li Min, Professor of the Teaching and Research Division and Associate Dean of the School of Chinese Medicine at HKBU have found that Huang-Lian-Jie-Du-Tang (HLJDT), a traditional Chinese herbal formula comprised of Huang Lian, Huang Qin, Huang Bai and Zhi Zi that is used to treat cerebral ischemia, could significantly reduce Aβ levels in mouse models when Huang Qin was removed.

They also found that Yan Hu Suo in Yuan-Hu Zhi Tong (YZT), a Chinese herbal formula used to treat pain and neuralgia, can regulate the aggregation of tau proteins. They, therefore, combined the modified HLJDT (HLJDT without Huang Qin) and Yan Hu Suo with two other herbal medicines, namely Dan Shen and Gou Teng, to optimize the formula for AD treatment.

Facilitated by data analysis and modeling techniques, the research team combined the six herbal medicines in different ratios to form 24 different formulas. Three of them were found to be effective in treating Alzheimer’s disease in a cell disease model. After conducting experiments on brain permeability and toxicity, the most promising formula was named NeuroDefend, and it was selected for further studies in pre-clinical mouse models to evaluate its efficacy as an AD treatment.

Reduces Aβ levels and tau protein aggregation

“Traditional Chinese medicine adopts a broad pharmacological approach to treating neurodegenerative diseases by deploying a combination of herbal medicines with different treatment effects. The selection of the six herbal ingredients and their ratios in NeuroDefend is based on the research conducted by our team over the years. NeuroDefend will contribute to the development of novel, effective traditional Chinese medicine for the treatment of AD in humans,” said Professor Li.

In the pre-clinical mouse model experiments, 50 mice in the treatment group were orally given low, medium and high daily dosages of NeuroDefend for three or eight months. Another 40 mice were put in the control group. The results showed that Aβ levels and abnormal tau protein aggregation in the treatment group were both significantly reduced by 30 to 40%. The higher dosage was found to be more effective in reducing Aβ levels and abnormal tau protein aggregation.

Improves memory and learning ability

To evaluate the efficacy of NeuroDefend in improving cognitive behaviors and memory deficits, a water maze experiment was conducted. Mice were trained to swim to a platform and remember its position in a water pool. After the platform was removed, researchers observed whether the mice were able to recall and approach the original position of the platform.

Compared to the control group, mice treated with NeuroDefend stayed 18 to 25 seconds longer probing for the platform’s original position. This showed the efficacy of the formula in improving the memory and learning ability of mice with AD.

In another experiment, mice were exposed to an audio tone followed by a two-second electric shock to their feet from the floor of the chamber. When they were put back into the chamber the next day without any electric shock, the mice were seen to “freeze” their body movements due to the fear of an electric shock. The freezing duration of the mice treated with NeuroDefend was 70 to 80 seconds longer than that of the control group. It demonstrated that the mice treated with NeuroDefend remembered the shock, reflecting the efficacy of the formula in improving their memory deficits.

A patent for the novel invention has been filed in the US and mainland China. The research discovery was published in the Journal of Food and Drug Analysis, an international scientific journal.

Students from the International Institute of Information Technology – Hyderabad (IIIT-H) were part of the team which has bagged second place in a blockchain hackathon, the Babylon Project. The event allowed participants to either build and develop decentralized blockchain applications or apply data science concepts in decentralized applications.

When 4th-year Btech students of IIIT-H, Adhithya Arun and Meher Shashwat Nigam, enrolled in the competition, their original intent was to learn about blockchain and gain more insights into a field in which they had no prior experience.

“As is the norm for most hackathons, this one had a team formation channel on their Discord server where participants can network and find teams to work with,” says Adhithya.

The duo got in touch with a bunch of like-minded others and a formidable team comprising the following was formed: Ha Linh To, a Singapore resident who is currently pursuing her final year of Bachelor’s in Marketing; Supriya Medapati, an IIT Madras alumnus and incoming MIT Sloan MBA candidate with over 12 years of experience in the tech and emerging tech industry; Suchira Banerjee, Assistant Professor at University of Engineering & Management, Kolkata; and Aryan Vikas Jain, a BTech student from SRM University.

The team selected a prevalent e-learning problem –  too many courses to choose from, lack of motivation to complete them and the absence of a tamper-proof mechanism to store and share learning credentials. Their solution, ‘SkillWallet’ – a decentralized, secure platform which successfully combined blockchain and AI to streamline the e-learning industry.

“The idea was to make the lives of learners, recruiters, and course providers easier and profitable,” says Adhithya.

For learners, the product is a personalized learning path with recommendations and rewards for following through with the goals. For recruiters, it helps in finding suitable candidates and verifying their credentials.  And for course providers, it allows them to create and issue verifiable certificates upon completion of the required learning. All this is a one-stop shop for not only acquiring skills and maintaining educational records, but also for the recruitment process.

The event saw the participation of around 93 teams from over 65 countries, and the finale saw a close contest between the top 6 teams where SkillWallet emerged in second place. With a lot of interest garnered from the community and from the hackathon organizers themselves, the team plans to keep the momentum going. The team has received the opportunity offered by the organizers to issue digital certificates for all participants of the hackathon.

“We had decided to take the idea forward and implement it for widespread usage, and this gesture (by the organizers) will help our product get its pool of initial users,” say Adhithya and Shashwat.

Researchers of the St. Petersburg Electrotechnical University “LETI” together with the Bekhtereva Institute of the Human Brain of the Russian Academy of Sciences are developing a complex information system to monitor the condition of a patient with Parkinson’s disease.

“A smartphone is almost always near the user. The data collected with its help can help doctors diagnose the improvement or worsening of the patient’s condition. A patient can record his condition, take notes for a doctor, etc. Existing mobile apps have limited functionality: they are either designed for physical training, or allow the user to track only individual symptoms of the disease, or provide general information about Parkinson’s disease,” Yulia Shichkina, Professor of Department of Computer Science and Engineering of ETU “LETI,” says.

“The main disadvantage of all these apps is the lack of communication with the doctor and the need to perform certain physical manipulations to assess the symptoms of the disease.”

The software developed by ETU “LETI” researchers significantly exceeds all these applications. It allows monitoring more than 30 parameters; determining the patient’s state in the background (without the patient’s participation); analyzing the patient’s state dynamics in a certain period; sending the results to a doctor and collecting information in a database; using not only phones but also portable devices.

The development includes modules for collection, preprocessing, transfer, and intelligent analysis of data, which authenticate the owner of the device (phone, bracelet) and classify his/her status. The application for Android automatically determines the patient’s state using six built-in sensors of the phone; a mobile device collects data every second in the background without any participation of the patient. Sensors can track the activity of the patient, tremor, dyskinesia, and other symptoms indicating the patient’s condition.

The development is easy to use. The patient can evaluate his state (movement coordination, attention, memory, voice, gait) with just four buttons on the phone. This data is transmitted to the doctor’s computer and to the data center to create the intellectual component of the monitoring system and train of the neural network.

The development is a reliable alternative to the daily doctor’s observation; it automatically provides a comprehensive analytical overview of the patient’s condition for a given period before the appointment. Additional advantages are that the patient is free from the routine manual filling of the diary, no subjective perception of the condition, impossibility to substitute the person filling the diary.

“We made the prototype on neural networks. And we became convinced of the shortcomings of neural networks for safe and reliable system operation. But there is also a positive thing: we have shown neurologists the benefits of our development. Now, we are remodeling the “smart part” of the system by switching to the mathematical apparatus of many-valued and fuzzy logic. This is reliable!” Professor Yulia says.

At present, the module automating the compiling of diaries is ready. A fully working system of data transfer from a mobile device to a computer of a doctor and data center has been built. Work is underway to create a prototype bracelet, develop modules to authenticate the owner of the device, and classify the patient’s condition on the data from sensors built into the device.

In the future, the development of ETU “LETI” researchers will make it possible to analyze the dynamics of the patient’s condition during the whole period of treatment. A doctor will be able to evaluate the treatment process as a whole and correct it. For patients and doctors, the unique system will be free.

Gastrointestinal stromal tumors (GISTs)—typically found in the stomach and the small intestines—require demanding techniques that are very time-consuming and prolong the diagnosis. Now, to improve GIST diagnosis, Drs. Daiki Sato, Hiroaki Ikematsu, and Takeshi Kuwata from the National Cancer Center Hospital East in Japan, Dr. Hideo Yokota from the RIKEN Center for Advanced Photonics, Japan, and Drs. Toshihiro Takamatsu and Kohei Soga from Tokyo University of Science, Japan, led by Dr. Hiroshi Takemura, have developed a technology that uses near-infrared hyperspectral imaging (NIR-HSI) along with machine learning. Their findings are published in Nature’s Scientific Reports.

“This technique is a bit like X-rays, the idea is that you use electromagnetic radiation that can pass through the body to generate images of structures inside,” Dr. Takemura explains, “The difference is that X-rays are at 0.01–10 nm, but near-infrared is at around 800–2500 nm. At that wavelength, near-infrared radiation makes tissues seem transparent in images. And these wavelengths are less harmful to the patient than even visible rays.”

This should mean that scientists can safely investigate something that is hidden inside tissues, but until the study by Dr. Takemura and his colleagues, no one had attempted to use NIR-HSI on deep tumors like GISTs.

Speaking of what got them to go down this line of investigation, Dr. Takemura pays homage to the late professor who began their journey, “This project has been possible only because of late Prof. Kazuhiro Kaneko, who broke the barriers between doctors and engineers and established this collaboration. We are following his wishes.”

Dr. Takemura’s team performed imaging experiments on 12 patients with confirmed cases of GISTs, who had their tumors removed through surgery. The scientists imaged the excised tissues using NIR-HSI, and then had a pathologist examine the images to determine the border between normal and tumor tissue. These images were then used as training data for a machine-learning algorithm, essentially teaching a computer program to distinguish between the pixels in the images that represent normal tissue versus those that represent tumor tissue.

The scientists found that even though 10 out of the 12 test tumors were completely or partly covered by a mucosal layer, the machine-learning analysis was effective in identifying GISTs, correctly color-coding tumor and non-tumor sections at 86% accuracy.

“This is a very exciting development,” Dr. Takemura explains, “Being able to accurately, quickly, and non-invasively diagnose different types of submucosal tumors without biopsies, a procedure that requires surgery, is much easier on both the patient and the physicians.”

Dr. Takemura acknowledges that there are still challenges ahead, but feels they are prepared to solve them. The researchers identified several areas that would improve on their results, such as making their training dataset much larger, adding information about how deep the tumor is for the machine-learning algorithm, and including other types of tumors in the analysis. Work is also underway to develop an NIR-HSI system that builds on top of existing endoscopy technology.

“We’ve already built a device that attaches an NIR-HSI camera to the end of an endoscope and hope to perform NIR-HSI analysis directly on a patient soon, instead of just on tissues that had been surgically removed,” Dr. Takemura says, “In the future, this will help us separate GISTs from other types of submucosal tumors that could be even more malignant and dangerous. This study is the first step towards much more groundbreaking research in the future, enabled by this interdisciplinary collaboration.”

For now, a means of accurately and non-invasively detecting GISTs early on could be clinically available widely, soon!

The TPU scientists published 189 articles, which ranked in the top 10 percent of the most-cited publications in the world for 2020. The top 1 percent of the most-cited publications in the world included 17 articles by TPU scientists.

Faculty of Business Management (FBM), Universiti Teknologi MARA (UiTM), Malaysia had the privilege to organize a Consumer Advocacy Program involving students and staff of UiTM on 11 March 2020. The program which was organized jointly by FBM, UiTM and the Malaysian Association of Consumer and Family Economics (MACFEA)  was held at UiTM Puncak Alam.

The main aim was to provide exposure and awareness on initiatives being implemented by the Malaysian Ministry of Domestic Trade and Consumer Affairs (KPDNHEP) on Food Bank Program and Cybercrime.

Tuan Ahmad Saifulzaman bin Mahadi, the spokesperson of Yayasan Food Bank, highlighted that this would be the right platform to assist the community of the target group in reducing their burden, especially in facing Covid 19 and the escalating cost of living.

Prof. Dr. Nuraisyah Chua Abdullah, a law lecturer from the Faculty of Law, UiTM Malaysia spoke on “Cybercrime” where she emphasized that “participants must be more thoughtful when engaging with online transactions, especially the threat cybercrime presents, and what are the best ways to protect their computer and their personal data”.

In conjunction with this program, the Ministry had also presented a grant of RM35000 to Prof Faridah Hassan, Associate Prof Dr Erni Suzila Kassim and the FBM team to conduct a study on Food Bank in Malaysia, focusing on the B40 community and the university students.

Meanwhile, this program also featured the presentation of prizes for the Creative Video Competition in conjunction with the Consumer Advocacy Program. With the theme on cybercrime, Miss Nur Wahida Binti Wahab and her team were crowned the winner with RM500.00 cash prize. Muhammad Shafiq Bin Zainal Abidin and  Aidiel bin Asri bagged second and third place, with RM400 and RM300 cash prizes respectively. All participants were treated with lucky draws sponsored by the Ministry.

The main aim of this meaningful program was to help the participants, especially from the B40 community to be vigilant and not to be easily influenced by the content of adverts displayed on social media, in addition to the initiatives provided by the Ministry on the Food Bank program.

Prajwal K R and Rudrabha Mukhopadyay, researchers at the Centre for Visual Information Technology, International Institute of Information Technology Hyderabad (IIITH) under the guidance of Prof. C V Jawahar and Prof. Vinay Namboodiri (University of Bath) are using a sophisticated AI framework and technique that enables one to synchronize lip movements of a person in a video to match it with any audio clip.

The IIITH AI model can be applied to create videos of any face, in any voice or language throwing open endless possibilities. While the implications for entertainment are mind-boggling, there’s something even closer to Prof. Jawahar’s heart that has spurred this particular research in the first place and that is using AI in the context of education. With his vision of easy availability and access to educational online content to all, the professor is of the opinion that language should be the least of the barriers to gaining knowledge.

Thanks to this technology, well-made lectures by prominent professors or experts on certain topics can be translated into any language of your choice. Or better still, highly accented English videos themselves can be recreated into an accent more comprehensible to the Indian populace.

In the current context of a wholesale virtual education across the country, the technology has the potential in making education more inclusive, especially for rural students. In situations where there is low internet bandwidth and other connectivity issues, lessons with only audio content can be streamed while the AI algorithm could generate the corresponding video accurately matching the original audio.

Such a novel approach can make the learning experience a fulfilling one. In a world where online interactions are the new normal, the researchers foresee its applications in video calls and conferencing where the tech comes to the rescue in case of video glitches. That is, if the incoming video signal is lost, the AI model can automatically plug in a synthetic video with accurate lip sync, enabling the work-from-home situation.

The Education University of Hong Kong (EdUHK) participated for the first time in the International Innovation and Invention Competition (IIIC) Taiwan held in November 2020. Six innovations covering education technology, wellness, and environmental science received four gold and two silver medals, including three out of a possible four gold medals in the EdTech innovation category.

Congratulating the winners, Professor Lui Tai-lok, Vice President (Research and Development), said, “The integration of technology in education enriches the educational experience. The IIIC accolades demonstrate the influential role of EdUHK in EdTech, as well as the favorable reception the innovations received from the Chinese user market. We will continue to innovate and advance education in Hong Kong and in the Asia-Pacific region.”

OASIS, an online assessment system for individual scores, has won a gold medal. The principal investigator for this project is Professor Woo Chi-keung, Department of Asian and Policy Studies, and co-investigators are Dr Henry So Chi-fuk, Lecturer, Department of Mathematics and Information Technology; external partners Dr Alice Shiu and Dr Liu Yun.

The Mandarin Spoken Word-Picture Identification Test in Noise – Adaptive (MAPID-A) is another innovation that has bagged gold. Dr Kevin Yuen Chi-pun, Associate Professor, Department of Special Education and Counselling is the principal investigator.

VocabGO, an augmented reality English vocabulary learning app also won a gold medal. Dr Song Yanjie, Associate Professor, Department of Mathematics and Information Technology was the principal investigator, and the co-investigators were Dr Lai Yiu-chi, Associate Professor; Dr Alpha Ling Man-ho, Associate Professor; Mr Wu Kaiyi, Research Assistant, Department of Mathematics and Information Technology; external partners Dr Walter Ng Wing-shui and Dr Hiroaki Ogata.

The fourth gold medal was bagged by the university for the innovation- portable interactive & meditative mirror. Dr Hung Keung, Associate Professor, Department of Cultural and Creative Arts was the principal investigator on this research.

An emotion recognition system based on the deep neural network bagged a silver medal. The principal investigator for this was Dr Zou Di, Assistant Professor, Department of English Language Education while the co-investigators were Professor Chou Kee-lee, Chair Professor of Social Policy, Department of Asian and Policy Studies; and external partner Dr Xie Haoran.

The innovative eco-concrete block made by utilizing waste sludge won the other silver medal. Dr Tsang Yiu-fai, Associate Professor, Department of Science and Environmental Studies was the principal investigator while EdUHK alumnus Cheng Wai-nam was the co-investigator.