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Alergies and Their Causes

Allergies are very common and increasing in Australia and New Zealand, affecting around 1 in 5 people at some time in their lives. There are many different causes of allergy and symptoms vary from mild to potentially life threatening. Allergy is also one of the major factors associated with the cause and persistence of asthma. Effective prevention and treatment options are available for most allergies. Allergy - a definition Allergy occurs when a person's immune system reacts to substances in the environment that are harmless for most people. These substances are known as allergens and are found in dust mites, pets, pollen, insects, ticks, moulds, foods and some medicines. Atopy is the genetic (inherited) tendency to develop allergic diseases. People with atopy are said to be atopic. When atopic people are exposed to allergens they can develop an immune reaction that leads to allergic inflammation (redness and swelling). This can then cause symptoms in the: nose and/or eyes - hay fever (allergic rhinitis/conjunctivitis) skin - eczema, hives (urticaria) lungs - asthma A substance that is an allergen for one person may not be for another - everyone reacts differently. The likelihood (or risk) of developing allergies is increased if other family members suffer from allergy or asthma. What happens when you have an allergic reaction? When a person who is allergic to a particular allergen comes into contact with it, an allergic reaction occurs. This begins when the allergen (for example, pollen) enters the body, triggering an antibody response. The antibodies attach themselves to special cells, called mast cells. When the pollen comes into contact with the antibodies, the mast cells respond by releasing certain substances, one of which is called histamine. When the release of histamine is due to an allergen, the resulting swelling and inflammation is extremely irritating and uncomfortable. The most common causes of allergic reactions in Australia are: dust mites pollen (grass, weed or tree) foods such as peanuts, cow's milk, soy, seafood and eggs cats and other furry or hairy animals such as dogs, horses, rabbits and guinea pigs insect stings and tick bites moulds medicines Similar reactions can occur to some chemicals and food additives, however if they do not involve the immune system, they are known as "adverse reactions" rather than "allergy". Which areas of the body may be affected? Depending on the allergen and where it enters your body, you may experience different symptoms. For example, pollen, when breathed in through the nose, usually causes symptoms in the nose, eyes, sinuses and throat (allergic rhinitis). Allergy to foods usually causes stomach or bowel problems, and may cause hives (urticaria). Allergic reactions can also involve several parts of the body at the same time.

2022-11-25 11:20

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Novartis forms alliance to develop diarrheal disease drug

Novartis has formed a new partnership to support the development of its drug candidate KDU731 to treat cryptosporidiosis, a parasitic disease characterised by diarrhoea. KDU731 is being developed as an inhibitor of the cryptosporidium lipid kinase PI(4)K (phosphatidylinositol-4-OH kinase). The drug candidate demonstrated favourable efficacy for treating cryptosporidium infection in preclinical studies and is currently being evaluated in safety studies before advancing into clinical trials. Diarrhoeal diseases are reported to be the cause of around 525,000 childhood deaths each year, and cryptosporidiosis is said to be the second major factor behind infectious diarrhoea in children aged less than two years. These statistics call for an urgent medical need requiring new and effective medications for cryptosporidiosis. “We are committed to the fight against cryptosporidiosis and other infectious and neglected tropical diseases and are proud to work closely with the Bill & Melinda Gates Foundation and other partners in this effort.” Under the latest collaboration, the firm will receive a $6.5m grant from the Bill & Melinda Gates Foundation intended to advance KDU731 development for treatment by the Novartis Institute for Tropical Diseases (NITD). NITD head Thierry Diagana said: “We are committed to the fight against cryptosporidiosis and other infectious and neglected tropical diseases and are proud to work closely with the Bill & Melinda Gates Foundation and other partners in this effort. “Today’s global health issues cannot be solved by one organisation alone. Private companies, governments, non-governmental organisations, academia, and other stakeholders need to work together to create sustainable solutions.” NITD primarily focuses on the discovery and development of new drugs for malaria, cryptosporidiosis, human African trypanosomiasis (sleeping sickness), chagas disease and leishmaniasis.

2022-11-25 11:20

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Machine learning technology predicts the outcomes of chem...

SHARE The software can predict reaction yields involving four components. Credit: Pixabay Researchers from Princeton University and Merck Research Laboratories have used machine learning technology to predict the outcomes of chemical reactions. The team, led by Abigail Doyle, A. Barton Hepburn professor of chemistry at Princeton and Dr Spencer Dreher of Merck, has developed software that can accurately predict reaction yields of experiments involving up to four components. Their findings are published in ‘Predicting reaction performance in C-N cross-coupling using machine learning’, in the journal Science. Historically, predicting such outcomes has been a challenge due to the difficulties of collecting enough data to establish a ‘training set’ of information that can be used for future predictions. In addition, calculating the effects of changes in quantity and nature of components has been a time-consuming process, only allowing small changes to be made in prediction calculations. “The software that we developed can work for any reaction, any substrate,” said Doyle. “The idea was to let someone apply this tool and hopefully build on it with other reactions.” The project was originally the PhD work of Derek Ahneman, who studied under Doyle in 2017 and now works for IBM; as Doyle puts it, ‘as chemists, we’ve traditionally veered away from multi-dimensional analysis.’ This particular form of multi-dimensional analysis involves random forest prediction models and the Spartan molecular modelling program. The team used Spartan to calculate descriptors for each chemical used in the model to use as inputs. Then, the used a machine learning model called ‘random forest’ – where randomly-selected small samples are used to build a decision tree that predicts the yield for a particular reaction, and then the results of several decision trees are averaged to generate an overall yield prediction – to predict the outcome of specific experiments. The researchers also discovered that the random forest model could work using only hundreds of reactions, as opposed to the usual thousands. They also found that the random forest model can predict yields for chemical compounds not included in the training set, suggesting the program is capable of learning from information that is not provided. “These results are exciting, because they suggest that this method can be used to predict the yield for reactions where the starting material has never been made, which would help minimise the consumption of chemicals that are time-consuming to make,” Ahneman said. “Overall, this methodology holds promise for, one, predicting the yield for reactions using as-yet-unmade starting materials and, two, predicting the optimal conditions for a reaction with a known starting material and product.” Since Ahneman left the laboratory, his work has been continued by graduate student Jesús Estrada, but the team’s goal is for those beyond computer experts such as Ahneman and Estrada to use the software. “The idea is to help people navigate the multi-dimensional space where you can’t intuit the outcomes,” said Doyle.

2022-11-25 11:20