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Heart disease (HD) is associated with estrogen and therefore gender and menopausal status. In addition, clinical evidence shows that increased serum norepinephrine is found in patients with HD. Therefore, this study aimed to investigate the cardio-protective effect of genistein, a selective estrogen receptor modulator (SERM) from soy bean extract, in H9c2 cardiomyoblast cells treated with isoproterenol (ISO), a norepinephrine analog. In this in vitro model, image data and results from western blotting shown that ISO treatment was capable of inducing cellular apoptosis, especially the mitochondrial dependent pathway. Treatment of genistein could suppress the expression of mitochondrial pro-apoptotic proteins including Bad, caspase-8, caspase-9, and caspase-3 in H9c2 treated with ISO. By contrast, several survival proteins were expressed in H9c2 treated with genistein, such as phosphor (p)-Akt, p-Bad, and p-Erk1/2. Furthermore, we confirmed that the protective role of genistein was partially mediated through the expression of Erk1/2, Akt, and NFκB proteins by adding several pathway inhibitors. These in vitro data suggest that genistein may be a safe and natural SERM alternative to hormone therapy in cardio-protection.

Topological data analysis is a relatively new branch of machine learning that excels in studying high-dimensional data, and is theoretically known to be robust against noise. Meanwhile, data objects with mixed numeric and categorical attributes are ubiquitous in real-world applications. However, topological methods are usually applied to point cloud data, and to the best of our knowledge there is no available framework for the classification of mixed data using topological methods. In this paper, we propose a novel topological machine learning method for mixed data classification. In the proposed method, we use theory from topological data analysis such as persistent homology, persistence diagrams and Wasserstein distance to study mixed data. The performance of the proposed method is demonstrated by experiments on a real-world heart disease dataset. Experimental results show that our topological method outperforms several state-of-the-art algorithms in the prediction of heart disease.

The clinical diagnosis of heart disease in most situations is based on a difficult amalgamation of pathological and clinical information. Because of this complication, there is a significant level of curiosity among many diagnostic healthcare professionals and researchers who are keenly interested in the efficient, accurate, and early-stage forecasting of heart disease. Deep Learning Algorithms aid in the prediction of heart disease. The main focus of this paper is to develop a method for predicting heart disease through Modified Rough K means$++$ (MRK$++$) clustering along with the Restricted Boltzmann Machine (RBM). This paper is categorized into two modules: (1) Propose a clustering component based on Modified Rough K-means$++$; (2) disease prediction based on RBM. The input Cleveland dataset is clustered using the stochastic probabilistic rough k-means$++$ clustering technique in the module for clustering. The clustered data is acquired and used in the RBM, and this hybrid structure is then used in the heart disease forecasting module. Throughout the testing procedure, the most valid result is chosen from the clustered test data, and the RBM classifier that correlates to the nearest cluster in the test data is based on the smallest distance or similar parameters. Furthermore, the output value is used to predict heart disease. There are three different types of experiments that are performed: In the first experiment comprises modifying the rough K-means$++$ clustering algorithm, the second experiment evaluates the classification result, and the third experiment suggests hybrid model representation. When the Hybrid Modified Rough k-means$++$ - RBM model is compared with any single model, it provides the highest accuracy.

High-tech TCM Center Opens in Shenzhen.

Project to Improve Chinese Medicine for Heart Disease and Cancer.

Sarawak Aims to be Major Player in Local Herb Industry.

Australia Helps Map Transcriptome of Mouse Genome.

Blood Cell Protein Mutation Slows Malaria.

Chinese Scientists Complete Detailed Rice Genome Map.

Three New Human Genes Discovered Among Chinese.

Abnormal Chromosomes Related to Habitual Abortion Found.

Rice Genome Sequencing by Japan-led Team Completed.

Study Shows Rats not Affected by Electromagnetic Wave.

Researchers Clone Monkey Embryos.

Folic Acid Reduces Heart Disease Risk.

NZ in International Brain Hemorrhage Study.

NTU and Sun Microsystems Collaborate on High Performance Computing for Life Sciences.

National Cheng Kung University Named as Bioinformatics Center of Excellence.

Carpal Tunnel Effectively Treated with Short-term Steroids.

Taiwan Scientists Clone Liver Cells.

The articles is about how pomegranate is a most potent protector against cardiovascular diseases.

AUSTRALIA – Minimizing Spread of Deadly Hendra Virus.

AUSTRALIA – Breakthrough High Blood Pressure Treatment Trial Down Under.

AUSTRALIA – Australia Sees Rise in Newborn Withdrawal Syndrome.

CHINA – CAS, Hong Kong University Set Up Joint Lab of Natural Medicine.

CHINA – Chinese Researchers Discover 20 Essential Genes in Polyoxin.

CHINA – China Aims to Lead Asia's Stem Cell R&D.

CHINA – China Rural Areas on High Alert for Hand, Foot and Mouth Disease.

CHINA – Hepatitis Infects 64 at China Hospital.

CHINA – China's Colorectal Cancer Drug Market will More Than Double by 2012.

CHINA – Critical Gene for Enhancing China's Super Rice Yield Identified.

CHINA – Chinese Scientists say New Discovery May Yield Clue to Cure Human Infertility.

HONG KONG – Compound to Fight Bird Flu Identified.

INDIA – Yashoda Cancer Institute Treats First Patient In India Using RapidArc Radiotherapy Technology.

INDIA – Indian Pharma Industry May Gain $18.4 bn from Global Market.

INDIA – Philips to Make India Hub for Medical Equipment Manufacturing.

JAPAN – Herbal Medicines to Treat Gastrointestinal Disease.

SINGAPORE – Tetravalent Dengue Vaccine Trial in Singapore.

SINGAPORE – Minimally Invasive Robot-Assisted Surgeries for Heart Patients.

SINGAPORE – US-Based Company Launches Singapore Doctor Search Site for Medical Travelers.

SINGAPORE – Genetic Research: Time for a rethink?

SINGAPORE – Test Kits to be Licensed.

SINGAPORE – Local Team Develops Method to Predict Heart Disease.

SINGAPORE – Consumer Genetic Tests – A Cause for Worry?

SINGAPORE – S'pore Firm's Test Kit Joins the Fight.

SINGAPORE – Singapore Gives New Hope To The Blind.

SINGAPORE – Singapore and Korea Research Institutes Embark on Landmark Collaboration for Breakthroughs in Micro and Nanotechnology.

SOUTH KOREA – Institute Develops Cheap Cholera Vaccine.

TAIWAN – Herbal Substance Developed for Cardiovascular Disease.

TAIWAN – Prototype of Household Breast Cancer Detector Unveiled.

TAIWAN – Breakthrough in New Diabetes Drug.

AUSTRALIA – Brain Gene Can Lead to Testis, Male Genitalia in Females.

AUSTRALIA – ALSIS 2010 Heats Up Aussie Biotech.

AUSTRALIA – World First Research on Jet Fuel Exposure Syndrome.

AUSTRALIA – Genetic Link Found Between Spinal Arthritis and Inflammatory Bowel Disease.

AUSTRALIA – Superbug in Melbourne.

AUSTRALIA – Possible Peanut Allergy Treatment Discovered.

CHINA – Bank to Freeze Eggs of Women Cancer Patients.

INDIA – Asia's First Biodegradable Stent.

INDIA – Swine Flu Returns - 20 Cases in a Week.

INDIA – Rare Double Hip Replacement in Noida.

SINGAPORE – Hydrogel Innovation Promises Multiple Uses.

SINGAPORE – Software Detects Genetic Mutations in Influenza.

SINGAPORE – NCCS to Establish Peritoneal and Pelvic Cancer Center.

OTHER REGIONS – Common Blood Test Could Detect Heart Disease.

INDIA – South Asia waters harbor drug-resistant bugs.

JAPAN – Daiichi Sankyo initiates phase 3 ENSURE-AF study, investigating patients with atrial fibrillation undergoing cardioversion.

SINGAPORE – Scientists discover a number of novel genetic defects which cause esophageal cancer.

SINGAPORE – NUS researchers develop world's first fluorescent sensor to detect common illicit date rape drug.

SINGAPORE – Genome Institute of Singapore partners Nutricia Research to investigate human gut microbiome.

SINGAPORE – Singapore-developed drug coated balloon enrolls its first patients in clinical study.

THE PHILIPPINES – Biodiversity loss linked to outbreaks of diseases.

VIETNAM – Mosquito genes could be key to halting dengue spread.

EUROPE – Curetis obtains key patent for Unyvero™ technology.

NEPAL – Fly ash waste used as water purifier.

UNITED STATES – Researchers discover genetic markers that may predict when people with heart disease are likely to have heart attacks.

UNITED STATES – Celluar ‘counting’ of rhythmic signals synchronizes changes in cell fate.

UNITED STATES – Potential lung cancer vaccine shows renewed promise.

UNITED STATES – Shrink wrap used to enhance detection of infectious disease biomarkers.

UNITED STATES – Triple negative breast cancer's progression and relapse pinned to a gene.

UNITED STATES – Seaweed forests could help power tropical islands.

Nanyang Technological University Smart Chips tells you how healthy your battery is.

Veolia Water Technologies Hosts First Think Tank Asia.

Treeway Announces Positive Data from Two Separate Phase I TW001 Clinical Trials.

Amgen and Merck Team up Two Cancer Studies.

BIOTRONIK Announces Start of New Study Evaluating whether Pacemakers with Closed Loop Stimulation Prevent Reflex Syncope.

BeiGene selects GE's FlexFactory™ biomanufacturing platform for pilot cGMP production facility in China.

Pass the Seaweed – And Reduce Your Risk for Heart Disease.

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Immunovaccine Publishes Findings Unique to DepoVax™ Technology on Potential of MRI Scans to Predict and Optimize Cancer Vaccine Response.

Singapore-Based Asian American Medical Group and Rich Tree Holdings Break Ground on Zhuhai-Singapore Life Science Park; Advanced Diagnostic and Wellness Medical Centre Will Bring World-Class Services to Southern China in 2018.

ASLAN Pharmaceuticals Opens China Office.

China to Improve Basic Science Research.

Chinese Scientists Edit Genes to Resist HIV in Embryos.

Scientists Find How Red Wine Compound Protects Heart.

Alliance for Stem Cell Technologies Established in Guangzhou.

China and Germany Keen to Deepen R&D Cooperation.

Study Unveils Novel Crosstalk Mechanism between Mitochondrial Translation and Cytoplasmic Translation.

China's Seed Haven Protects Endangered Plants.

Scientists Find that miR-155 Suppresses ErbB2-induced Malignant Transformation.

Nectar and Scent Secretion Patterns Reflect Floral Color Change Rhythm in Quisqualis indica.

Enhance clinical laboratory practice in Vietnam through LEAN

Industry and academia must work together; an interview with Prof Carolyn Lam

The following topics are under this section:

• Asia-Pacific — Stresses of parenting may negatively affect the parent-child relationship
• Asia-Pacific — Duke-NUS holds first regional ageing and health conference for policymakers and researchers in Singapore
• Asia-Pacific — Science, Tech, and policies convene for a sustainable future
• Asia-Pacific — Researchers uncover the mechanism behind cancer-causing E.coli toxin setting the path to new preventive measures for colorectal cancer
• Asia-Pacific — Novel technology to determine classification of cancer cells through DNA barcodes
• Asia-Pacific — Identification of specific proteins can aid in development of novel therapeutic targets for heart diseases
• Asia-Pacific — How evolutionarily conserved genetic material determines reproductive ability of plants
• Asia-Pacific — Scientists call for bolder actions to protect coral reefs
• Asia-Pacific — International research team develops breakthrough technology for auto-detection of heart disease
• Rest of the World — New clinical guidelines for patients at high risk of heart attacks, stroke
• Rest of the World — For gut microbes, not all types of fibre are created equal

The following topics are under this section:

• ASIA-PACIFIC — Collaborative research effort reveals chemical compound that kills drug-resistant bacteria
• ASIA-PACIFIC — Big Data Analytics used for Personalized Assessment Tool for Cancer Diagnosis
• ASIA-PACIFIC — Identifying the Molecular Mechanisms of Creating a Memory
• ASIA-PACIFIC — Funding for New Stem Cell Research provides Hope for Premature Born Babies
• ASIA-PACIFIC — Human Cortical Organoids used to Identify Mechanisms behind Epilepsy in Angelman Syndrome
• ASIA-PACIFIC — The Future of Contact Lenses: Self-Moisturising Technology
• ASIA-PACIFIC — Glycosylation of Protein Structure on Virus provide Insight to Molecular Understanding
• ASIA-PACIFIC — Comprehensive Mapping of the Human Brain using Synchrotron X-rays
• REST OF THE WORLD — Uncovering New Tricks for Old Drugs
• REST OF THE WORLD — Combination of Prenatal Smoking and Drinking adds on to Risk of SIDS
• REST OF THE WORLD — Blood Pressure Readings Could Provide Valuable Information on Early Warning Signs of Heart Disease
• REST OF THE WORLD — Study finds Households in the United States Wastes nearly a Third of the Food they Buy

The following topics are under this section:

• Asia needs to wake up to the threat of peripheral artery disease
• TurtleTreeLabs – Changing the Course of the Dairy Industry

The following topics are under this section:

• Open Source AI-Powered Tool by Tencent for COVID-19 Preliminary Self Evaluation
• The Effort to Measure Black Carbon in Antarctica
• Visualizing Core-Shell Formation by in situ Liquid Cell TEM
• Novel Strategy to Create 2D Magnetic Order
• Solid-State Photosensitizer for Singlet Oxygen Generation
• Warming Arctic Mitigates Global Warming
• Self-Activation Loop Maintains Stem Cells for Plant Branching
• Graphene-based Actuator Swarm Enables Programmable Complex Deformation
• Optimal Egg Consumption to Lower Risk of Cardiovascular Disease

Heart disease kills more people around the world than any other disease, and it is one of the leading causes of death in the UK, triggering up to 74,000 deaths per year. An essential part in the prevention of deaths by heart disease and thus heart disease itself is the analysis of biomedical markers to determine the risk of a person developing heart disease. Lots of research has been conducted to assess the accuracy of detecting heart disease by analyzing biomedical markers. However, no previous study has attempted to identify the biomedical markers which are most important in this identification. To solve this problem, we proposed a machine learning-based intelligent heart disease prediction system called BioLearner for the determination of vital biomedical markers. This study aims to improve upon the accuracy of predicting heart disease and identify the most essential biological markers. This is done with the intention of composing a set of markers that impacts the development of heart disease the most. Multiple factors determine whether or not a person develops heart disease. These factors are thought to include age, history of chest pain (of different types), fasting blood sugar of different types, heart rate, smoking, and other essential factors. The dataset is analyzed, and the different aspects are compared. Various machine learning models such as $K$ Nearest Neighbours, Neural Networks, Support Vector Machine (SVM) are trained and used to determine the accuracy of our prediction for future heart disease development. BioLearner is able to predict the risk of heart disease with an accuracy of 95%, much higher than the baseline methods.

Rheumatic Heart Disease (RHD) is a disorder of heart caused by streptococcal throat infection followed by the organ damage, irreversible valve damage and heart failure. Acute Rheumatic Fever (ARF) is a precursor to the disease. Sometimes, RHD can occur without any signs or symptoms, and if there are any symptoms, they occur with the infection in the heart valves and fever. Due to these issues, respiratory problems occur with chest pain and tremors. Additionally, the symptoms include faint, heart murmurs, stroke and unexpected collapse. The techniques available try to detect the RHD as early as possible. Although the recent medical health care department uses crucial techniques, they are not accurate in terms of symptom classification, precision and prediction. On the scope, we are developing Multi-Layered Acoustic Neural (MLAN) Networks to detect the RHD symptoms using heart beat sound and Electrocardiogram (ECG) measurements. In this proposed MLAN system, the novel techniques such as multi-attribute acoustic data sampling model, heart sound sampling procedures, ECG data sampling model, RHD Recurrent Convolutional Network (RRCN) and Acoustic Support Vector Machine (ASVM) are used for increasing the accuracy. In the implementation section, the proposed model has been compared to the Long Short-Term Memory-based Cardio (LSTC) data analysis model, Cardio-Net and Video-Based Deep Learning (VBDL) techniques. In this comparison, the proposed system has 10%–17% higher accuracy in RHD detection than existing techniques.

Recent years have seen a renewed interest in the theories of extended continuum mechanics. These allow for a finer and relatively simple modeling of physical phenomena occurring on the microscopic level. The Eringen’s micromorphic medium belongs to this class and allows accounting for the material microstructure. A subclass of this model was applied to model the mechanical behavior of cardiac tissue. With the aid of a specifically developed numerical tool, the validity of the approach is demonstrated using different myocardial infarct scenario.

Mortality rate due to fatal heart disease (HD) or cardiovascular disease (CVD) has increased drastically over the world in recent decades. HD is a very hazardous problem prevailing among people which is treatable if detected early. But in most of the cases, the disease is not diagnosed until it becomes severe. Hence, it is requisite to develop an effective system which can accurately diagnosis HD and provide a concise description for the underlying causes [risk factors (RFs)] of the disease, so that in future HD can be controlled only by managing the primary RFs. Recently, researchers are using various machine learning algorithms for HD diagnosis, and neural network (NN) is one among them which has attracted tons of people because of its high performance. But the main obstacle with a NN is its black-box nature, i.e., its incapability in explaining the decisions. So, as a solution to this pitfall, the rule extraction algorithms can be very effective as they can extract explainable decision rules from NNs with high prediction accuracies. Many neural-based rule extraction algorithms have been applied successfully in various medical diagnosis problems. This study assesses the performance of rule extraction algorithms for HD diagnosis, particularly those that construct rules recursively from NNs. Because they subdivide a rule’s subspace until the accuracy improves, recursive algorithms are known for delivering interpretable decisions with high accuracy. The recursive rule extraction algorithms’ efficacy in HD diagnosis is demonstrated by the results. Along with the significant data ranges for the primary RFs, a maximum accuracy of 82.59% is attained.