Showing posts with label data science. Show all posts

Thursday, February 28, 2019

Hurricane Maria Destroys Puerto Rico's Science Programs Then Presents Unusual Research Opportunities?

The devastation caused by Hurricane Maria is still being revealed nearly a year and a half after the storm ripped through the island. Of course, anyone who has lived through a disaster like this will tell you that the island will probably never recover. Not to mention that the loss of life can never be replaced. With that being said, any community (or island) must find the courage to recover and re-establish life as it were if possible.

Under normal conditions, agencies such as FEMA (Federal Emergency Management Agency) would provide sufficient funds to help the island start the journey toward recovery. Unfortunately, we do not live in normal conditions at the current moment under the current administration. Funding agencies are being stressed beyond reach for existing funds and when this occurs, areas like scientific research usually suffer the most.

How Did Maria Impact Science?

At the very least, the lightest impact (which actually may not be true due to PTSD), the lab members may undergo treatment to make sure that there are no residual medical issues after a storm has hit the island. Of course, if you have no laboratory staff: graduate students, undergraduate students, postdoc's, professional researchers -- then you have no lab. Meaning, all the best equipment can occupy the lab, but without scientists to run and monitor the instruments, then there is no lab.

The second critical component of any scientific laboratory are the scientific instruments and infrastructure in which these along with the supplies (beakers, tubing, cell cultures, glove boxes, etc.) needed to conduct good/sound science. This is sometimes the perceived most critical component of any scientific laboratory. Although, I would argue that the scientists which occupy any laboratory are the most critical components to any scientific instruments. I have yet to see any scientific instrument just start collecting data by itself without any scientist's intervention/initiation.

A recent article in 'The Scientist' titled "Science in Puerto Rico Still Recovering After Hurricane Maria" details some of the disastrous consequences to a scientific laboratory after a storm of a magnitude such as Hurricane Maria. The human damage alone can be irreplaceable not to mention the buildings and local municipal utility grid. And when the destruction to the infrastructure is considered, parameters such as mold and water damage can set a laboratory recovery back several months to years:

Giray’s lab is among 14 or so in the Julio Garcia Diaz biology building, which was among those severely damaged, particularly as it was already undergoing roof repairs when the storm hit. Water seeped in through the roof and windows, damaging costly research equipment, furniture, and lab materials. Toxic mold thrived in the moist, hot climate, creating hazardous conditions that made the building uninhabitable. Power outages cut off researchers’ freezers and fridges, destroying precious genetic and tissue samples for good. The damages are estimated to range from $250,000 up to $2.5 million dollars per lab in that building, says Giray, a behavioral biologist whose main focus is honeybees.

Even more important are samples which are collected outside of the laboratory or purchased for several thousand dollars which are sensitive to temperature/humidity/vibrational fluctuations:

Some of the casualties from the hurricane are less easy to restore: “Collections take much longer time and may never be replaced,” says Giray’s colleague Riccardo Papa, who lost almost all of his DNA samples documenting the diversity of butterflies across South America when his lab’s –80 °C freezer lost electricity. Papa, an evolutionary biologist, didn’t have a lab again until a week ago, and until recently has been meeting with his students and postdocs at coffee shops or places around campus to discuss research. He has been able to do some experiments and genetic analyses in another building. Repairs are still underway for the damaged insectary, in which his team raises butterflies.

Research must go on. With or without the infrastructure. Here in California, after the Northridge Earthquake in 1994, FEMA set up temporary 'mobile homes' to serve as both classrooms and temporary offices along with laboratories in certain circumstances. To hear that 'group meetings' were still being held at coffee shops is a testament to the pace of recovery. In a majority of cases after a disaster, classroom recovery comes first, then eventually research laboratories. Although, it is worth remembering that each research laboratory group is made up of students and research professors who take years (applying for individual grants/writing publications) to acquire the appropriate funding to purchase research scientific instrumentation. Therefore, to put a price on the total loss in the event of a disaster like Hurricane Maria proves extremely difficult.

The total cost to a researcher is really unknowable for years to come. Some researchers never recover and decide to shut down their laboratories after such a storm. Which leaves current graduate students without an end in sight to their degrees (M.A. and PhD). Additionally, staff (professional researchers) might quickly find themselves out of work and have to leave regions like Puerto Rico and find work elsewhere. Which means transplanting their families and children's education to a different geographical location. The cost can be severe not just to the researcher themselves.

More can be written in future articles on this theme of disasters and research laboratories. Either together or separately. The total cost to a geographical location from a disaster such as Hurricane Maria can only be estimated at the beginning (a very rough approximation). The price tag evolves over time with the disbursement of emergency funds by organizations such as FEMA along with other federal organizations or the Congress. The terrible destruction to a scientific institution is terrible to say the least. Restoring science should be a high priority among others on the island of Puerto Rico.

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Tuesday, January 8, 2019

The Futuristic Visit To The Physician Is Here!

Source: IUVM TECH

The world is in the midst of a gigantic 'data revolution' right now. What does that entail? There is a massive collection of data going on around us at any given moment. From the geographical location at which you are located to the subject matter which you are searching for using a search engine such as Google or Bing. What benefits might arise out of such a revolution? Many have been proposed. The overall concept to understand why such benefits arise was written about in an article titled "The 7 Industries That Benefit Most From Big Data" on the website 'Smart Collective' in 2016:

Generally, the more data you have, the more specific and accurate insights you’ll be able to generate, which is why big data has become such a powerful tool (and buzzword) in recent years

More data points equals more accuracy. Which promotes the largest benefit which serves as a feedback into all of the industries mentioned in the article above: 'artificial intelligence.' A pathway toward the benefits of artificial intelligence exists and is currently being taken by technology groups around the world. On this pathway toward 'artificial intelligence' playing a larger role in our society has been the concept of 'deep learning':

Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised.[1][2][3]

Deep learning architectures such as deep neural networks, deep belief networks and recurrent neural networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases superior to human experts.[4][5][6]

Deep learning models are vaguely inspired by information processing and communication patterns in biological nervous systems yet have various differences from the structural and functional properties of biological brains (especially human brains), which make them incompatible with neuroscience evidences.[7][8][9]

Again, the amount of data which serves as an 'input' will greatly affect the accuracy of the 'output' the intelligent (computation) answer given to us after the algorithm is executed.

How does all of this play out in the immediate future?

One example is the field of medicine. During a recent break, I was perusing through Facebook and found the following video by an organization called 'Forward'. The video below gives us a glimpse into technology which has already been developed and is out on the market right now. A glimpse of a 'future visit to the doctor' for a health check up. The video is less than 10 minutes in length and worth watching.

Wow right? For those who are uninterested in viewing the entire video here are the basics:

1) No receptionist to check in with. Just an equivalent of an iPad.

2) A Body scan with infrared radiation. While placing a single hand on a sensor, blood oxygen levels, heart rate, metabolic rate, and a body composition -- fat tissue, muscle and bone tissue.

3) Up to 3 visits normally to the center per month. Although, a patient may come and get a body scan anytime. Remember, more data more accuracy.

4) A Body scan creates a 3D model of your body.

5) The Information gathered in the body scan is synced with exam room digital display (i.e. monitor, tv screen) at which time the patient can view results with a physician. Additionally, the information is also synced with the mobile app on your smartphone.

6) Patient goes into exam room and discusses data.

7) Patient and physician review body scan data and blood work (all on the same day) to come up with a plan to achieve health goals which lead to better health.

8) Planning is individual based. No two plans are equal.

Having the ability to reduce time or redundancy with having an on site laboratory (for blood work), a visit to the 'futuristic physician' provided by 'Forward' is greatly enhanced. Plus, as pointed out in the video above, the language which enters into the patient file is the patient's own language -- which is recorded on the screen during discussion with physician. Additionally, all data and discussion is forwarded to your mobile app for your personal viewing and stay plugged into continuously. Awesome. This is the future of medicine.

Conclusion...

The data revolution has the ability to transform our daily lives in many ways. As shown in the video above, the access of big data in real-time is effective in treating an individual patient with the patient's own needs based on the data collected. Additionally, that data is compiled with the ability (upon patient approval) to be used in conjunction with other patients for research and discovery purposes.

One main obstacle with the deluge of big data are the different file types in which the data exists currently. In order to make meaningful discoveries using the big data files, the processing/algorithms need to be able to read the file format. With the collection of data in this forma (a single format), this represents a solution to an existing problem.

Of course, that means still processing old data from decades in the past. Although, after processing old data and combining it with new data compiled in the new format, powerful advances will be able to be made by mining the data for medical research and drug discovery purposes (to name just two). The future of medicine is truly exciting and should be embraced by each of us.

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