La-di-da

Finding my space amidst the clutter of life. Studyblr | Medblr | Blahblahblr

[mcavoy]

this is literally the only mood I ever have

[eightacres]

Day after day.

[eightacres]

Still true. Returned to this space after almost 3 years. Sigh.

[eightacres]

After 5.5 years of med school, never once did I think I'd end up going into radiology residency but here I am! It's all the diagnostic fun without the painful (at least for me) patient interaction.

Or so I think.

[macrolit]

Giveaway Contest: We’re giving away twelve Bantam paperback classics by Walt Whitman, Emily Bronte, Edgar Allan Poe, James Joyce, George Eliot, Shakespeare, and others! Won’t this collection look lovely on your shelf? :D To win these classics, you must: 1) be following macrolit on Tumblr (yes, we will check. :P), and 2) reblog this post. We will choose a random winner on September 29, at which time we’ll start a new giveaway. And yes, we’ll ship to any country. Easy, right? Good luck!

[mvrning-coffee-deactivated20250]

Q and A on random facts about me

   And as usual, thank you to the only person who tags me in stuff on tumblr @charakacomplex

Rules: Answer the questions, tag some people.

Relationship status: REALLY COMPLICATED. I recently moved to a different city and my boyfriend and I won’t be i the same city for at least 2 years and even after that we don’t know if we will ever be for multiple reasons and we don’t want to go through the hardships of a long distance relationship but at the same time we’re just too close to be able to move on (we’ve been together for 4 years now). So the two of us are just like -\o_0/-  I guess we’ll just see where it goes.

Favourite colours: All of them ^_^ I Iove painting and I have a Bob Ross worldview on colours. I’ve been loving blush pink lately though.

Lipstick or chapstick: Lipstickk. My lips are colourless and I look like the old pre-surgery Kylie Jenner without it.  

Three favourite foods: SHAWARMAAAAA, chicken biriyani and Thai green curry.

Song stuck in my head: Movie by Tom Misch

Last song I listened to: Bloom by Troye Sivan.

Last movie I watched: Ant Man and the Wasp.

Top 3 TV shows: PARKS AND RECREATION, Fullmetal alchemist: brotherhood and Brooklyn nine-nine.

 Books I’m currently reading: the Second Sex by Simone De Beauvoir. It’s been one of the most enlightening books I’ve ever read and EVERYONE SHOULD READ IT.

Last thing I googled: probably something to do with Voltron: legendary defender. Which is an AMAAAZING show as well.

Time: 7;56 am, 6th August 2018 :)

How many blankets I sleep in: just the one.

Dream trip: Somewhere in Norway probably.

Something I want: not a damn thing. i’m in a very content and happy state of mind. If i had to go for something it’d be a bomb af Step 1 score.

I tag: @eightacres @peachy-learning, @erikhet 

[eightacres]

Man. Thanks @mvrning-coffee for the tag. Final year of med school has been swallowing me whole but I'll get around to doing this Q/A. Love. ❤️

[wildcat2030]

In Human Vs Machine Study, AI Better at Detecting Skin Cancer

An artificial intelligence system accurately detected 95 percent of dangerous skin lesions in more than 100,000 images, compared to 86.6...

A computer was better than human dermatologists at detecting skin cancer in a study that pitted human against machine in the quest for better, faster diagnostics, researchers said Tuesday. A team from Germany, the United States, and France taught an artificial intelligence system to distinguish dangerous skin lesions from benign ones, showing it more than 100,000 images. The machine — a deep-learning, convolutional neural network or CNN — was then tested against 58 dermatologists from 17 countries, shown photos of malignant melanomas and benign moles. Just over half the dermatologists were at “expert” level with more than five years of experience, 19 percent had between two and five years of experience and 29 percent were beginners with less than two years under their belt. “Most dermatologists were outperformed by the CNN,” the research team wrote in a paper published in the journal Annals of Oncology. On average, flesh and blood dermatologists accurately detected 86.6 percent of skin cancers from the images, compared to 95 percent for the CNN.

[neurosciencestuff]

Brain Cells Found to Control Aging

Scientists at Albert Einstein College of Medicine have found that stem cells in the brain’s hypothalamus govern how fast aging occurs in the body. The finding, made in mice, could lead to new strategies for warding off age-related diseases and extending lifespan. The paper was published online in Nature. 

The hypothalamus was known to regulate important processes including growth, development, reproduction and metabolism. In a 2013 Nature paper, Einstein researchers made the surprising finding that the hypothalamus also regulates aging throughout the body. Now, the scientists have pinpointed the cells in the hypothalamus that control aging: a tiny population of adult neural stem cells, which were known to be responsible for forming new brain neurons.  

“Our research shows that the number of hypothalamic neural stem cells naturally declines over the life of the animal, and this decline accelerates aging,” says senior author Dongsheng Cai, M.D., Ph.D., professor of molecular pharmacology at Einstein. “But we also found that the effects of this loss are not irreversible. By replenishing these stem cells or the molecules they produce, it’s possible to slow and even reverse various aspects of aging throughout the body.”

In studying whether stem cells in the hypothalamus held the key to aging, the researchers first looked at the fate of those cells as healthy mice got older. The number of hypothalamic stem cells began to diminish when the animals reached about 10 months, which is several months before the usual signs of aging start appearing. “By old age—about two years of age in mice—most of those cells were gone,” says Dr. Cai.

The researchers next wanted to learn whether this progressive loss of stem cells was actually causing aging and was not just associated with it. So they observed what happened when they selectively disrupted the hypothalamic stem cells in middle-aged mice. “This disruption greatly accelerated aging compared with control mice, and those animals with disrupted stem cells died earlier than normal,” says Dr. Cai.

Could adding stem cells to the hypothalamus counteract aging? To answer that question, the researchers injected hypothalamic stem cells into the brains of middle-aged mice whose stem cells had been destroyed as well as into the brains of normal old mice. In both groups of animals, the treatment slowed or reversed various measures of aging.

Dr. Cai and his colleagues found that the hypothalamic stem cells appear to exert their anti-aging effects by releasing molecules called microRNAs (miRNAs). They are not involved in protein synthesis but instead play key roles in regulating gene expression. miRNAs are packaged inside tiny particles called exosomes, which hypothalamic stem cells release into the cerebrospinal fluid of mice.

The researchers extracted miRNA-containing exosomes from hypothalamic stem cells and injected them into the cerebrospinal fluid of two groups of mice: middle-aged mice whose hypothalamic stem cells had been destroyed and normal middle-aged mice. This treatment significantly slowed aging in both groups of animals as measured by tissue analysis and behavioral testing that involved assessing changes in the animals’ muscle endurance, coordination, social behavior and cognitive ability.

The researchers are now trying to identify the particular populations of microRNAs and perhaps other factors secreted by these stem cells that are responsible for these anti-aging effects—a first step toward possibly slowing the aging process and treating age-related diseases.

[eightacres]

Pink-themed spread for the first week of January.

[eightacres]

Rainbow-themed bookmark for those days when you need to make a boring textbook look more fun.

[neurosciencestuff]

Changes in brain regions may explain why some prefer order and certainty

Why do some people prefer stable, predictable lives while others prefer frequent changes? Why do some people make rational decisions and others, impulsive and reckless ones? UCLA behavioral neuroscientists have identified changes in two brain regions that may hold answers to these questions.

The research — reported by Alicia Izquierdo, UCLA associate professor of psychology and a member of UCLA’s Brain Research Institute, and her psychology graduate student, Alexandra Stolyarova — was published in the open-access online science journal eLife.

The new experiments, which involved studying the orbitofrontal cortex and basolateral amygdala brain regions, assessed the ability of rats to work for rewards under both stable and variable conditions. Rats earned sugar pellets after choosing between two images displayed side by side. The animals made their selections by using their noses to touch a screen the size of an iPad. When a rat touched one image, it received a sugar pellet at a predictable time — generally 10 seconds later. When the rat touched the other image, it received a sugar pellet at a time that varied. This was the riskier option as the rats might have to wait as little as five seconds or as long as 15 seconds. The rats did this for a month at a time, as long as 45 minutes each day.

The researchers discovered that the rats learned the task and were able to detect the fluctuations in wait times. When the rats experienced more variation in those wait times for their reward, the amount of the brain protein gephyrin in the basolateral amygdala region doubled, Izquierdo and Stolyarova reported.

In some of the trials, the researchers made one option better than the other, with a shorter wait time. All rats were able to learn the pattern and make the better choice. They showed some evidence of learning on the first day and did better the second day and on subsequent days. In a group of rats without a functional basolateral amygdala, the rats learned more slowly about the changes, but caught up about two days later.

Rats without a functional orbitofrontal cortex, however, did not learn at all, and instead treated each experience as a “reset” button, the researchers report. It is as if these rats did not have a record of the full range of possible outcomes. The important role for the orbitofrontal cortex surprised Izquierdo, who said there was more evidence that the basolateral amygdala would be important in conditions of uncertainty, and not as much for the orbitofrontal cortex.

Stolyarova and Izquierdo are the first scientists to link gephyrin levels to the experience of reward. They report that when the rats experienced risk, the brain protein GluN1 also increased significantly in the basolateral amygdala.

“I think the experience of uncertainty is making these changes occur in these brain regions,” Izquierdo said.

All rats chose the risky option more often. The exception was the rats without a functional basolateral amygdala; those animals stayed risk-averse throughout the experiments.

The orbitofrontal cortex and basolateral amygdala share anatomical connections, and both regions are involved in decision-making, earlier research has shown. The new research indicates this is especially so during changing or uncertain circumstances.

Changes in these brain regions and brain proteins may help to explain a person’s preference for uncertain outcomes, Izquierdo said. Humans have individual differences in orbitofrontal cortex and basolateral amygdala function and in the expression of these proteins, she noted.

For example, variations in the gephyrin gene have been linked to autism, and a feature of the disorder is a strong preference for order and certainty.

In the future, Izquierdo said, precision medicine may be able to target any brain region to treat any disorder, including behavioral addictions such as gambling.

People with obsessive–compulsive disorder also have a strong preference for order and certainty. Future research may answer whether the same brain changes occur in this disorder as well.

[eightacres]

My first bullet journal. The future log is still a work in progress. Purple + Grey

[aspiringdoctors-blog]

Basics for the Wards: How to Read EKGs

I’m on cardiology right now, and yesterday the fellow taught us some basics for interpreting EKGs. The trick is the have a thorough algorithm and do it every time so you don’t miss anything.

Disclaimer: Obviously this is just a cursory intro so folks won’t look like complete fools like me- who, when asked to interpret an EKG, went into a cold sweat and said, “Well, it looks like the heart is beating.” Attendings do NOT like that.

INTRO

This is what a normal lead II EKG one beat reading should look like. TAKE NOTE LITERALLY EVERYONE STOP CALLING YOUR SQUIGGLY LINES HEARTBEATS IT IS WRONG GAAAHHHH.

Normal EKG.

What the various leads are monitoring.

1. Rhythm: Sinus or not- aka, is the SA node talking to the AV node correctly? Check in leads V1 and II- if there is a P wave before every QRS you have sinus rhythm. If this is not the case, you do not have sinus rhythm! A whole discussion on things messing up sinus rhythm will come when I have a better grip on it myself.

2. Rate: How fast is the heart beating- aka, how fast are the ventricles depolarizing? So EKGs are little tiny boxes in bigger boxes, right? There are several methods for calculating rate using the boxes, but the one that works for my brain is to count the big boxes between R’s and divide that by 300. So, 1 big box between R = 300/1 = 300 bpm. 2 big boxes between R= 300/2= 150 bpm. And so on.

In general, any heart rate above 100 is tachycardia, and any heart rate below 60 is bradycardia. These values may vary (ex: SIRS criteria counts heart rate above 90 as tachy). Normal heart rate is around 75 (exceptions include athletes- look up athletic heart syndrome)

3. QRS Complex: Wide or narrow- aka, is the Bundle of His bossing the ventricles around? Basically, a nice narrow QRS complex generally indicates the bundle of His is intact and operating how it is supposed to. A wide QRS complex indicates something is awry with the Bundle of His- could be an organic pathology, could be a medication side effect (ex: antiarrythmics, TCAs, quinidine, to name a few), could be an electrolyte imbalance (ex: hyperkalemia), could be other things.

4. Axis: Is the heart depolarizing the way it should- aka right shoulder to left nipple. I, personally, am still sorting out the axis system, and it’s hard to do in this format. The first, most basic place to start is checking if lead I and aVF are POSITIVE, meaning their QRS complexes go ABOVE the isoelectric line. If that is the case, you are probably ok axis-wise.

Essentially, lead I’s vector goes from left to right, and aVF’s vector goes from head to toe. So the average of those vectors is the general path of depolarization of the heart. You want the axis to be between -30 and +90.  So, if aVF is positive, but lead I is negative (the QRS is below the isoelectric line) that means it is going from left to right instead and would be classified as a right shift. Likewise, if lead I is positive, but aVF is negative, that means it is going down to up and would be classified as a left shift. There is soooo much more to axis interpretation, this is just a starting point.

5. Intervals: Again with the conduction system, it’s, like, totally important that it obeys all the rules every time. PR= <.2 seconds, or one big box QRS= <.12 seconds, or 3 small boxes QT= < ½ the RR interval

6. ST segment changes: checking for CAD- aka, is the myocardium getting enough blood/oxygen?  Since the folks in the South seem to consider butter a food group and know that if it can’t be fried it’s not worth eating, CAD is a huuuuuuuuge issue here. When blood supply to the myocardium is compromised, there will usually be characteristic EKG changes. Note- not every episode of angina/MI will have EKG changes though! - Inferior leads –> right coronary artery. - lateral leads –> circumflex artery - anteroseptal leads –> left anterior descending. Disclaimer: does not apply to everyone all the time, some folks have variant coronary anatomy.

So the EKG changes to look for must be seen in two contiguous leads, aka, two inferior leads or two lateral leads. - Ischemia (low oxygen) = ST depression or T wave inversion (EXCEPT T wave inversions are ok in leads V1 and aVR)

- Injury = ST elevation

- Old infarct/dead myocardium = pathologic Q waves. Basically that first negative vector (aka, the Q of the QRS complex) should never be bigger than one tiny box.

And, that, friends, is a basic algorithm for reading EKGs! There is a lot more, but if you follow these steps every time, you will look like a rock star on wards. Good luck!

[eightacres]

All* About Me

Thanks @oneirophobe-studies for tagging me. :) I haven’t done this before, so here goes.

Where are you from?

Mumbai, India.

How old are you?

I’m 21.

Are you an applicant, student or medical professional?

I am a medical student, in my third year right now. In another two years I will be a doctor.

When did you decide you wanted to be a medical professional?

I decided when I was 15. In India, once you finish school (10th grade), most people have to choose their junior college subjects according to the stream they wish to take up later. I had to study physics, chemistry, biology and mathematics for two years which is when I realised that I actually liked biology a LOT. Ideally I wished to study pure biology and later study ethology in depth, but medicine felt like a safer option, financially. Let’s see how it pans out though.😅

 What did you do before deciding to go to medical school?

I was in junior college/ high school.

What area of medicine are you really interested in?

Right now, neurology. But it keeps changing withe every rotation. I did love pediatrics too and pediatric neurology would be a nice amalgamation. Again, life is uncertain so I like to keep myself open to everything. Oh, no surgery, though. I feel like I am not meant for it, even though I enjoy studying or watching it.

Do you plan to/ Do you/ Did you work through medical school? If so what as?

Nope.

What’s your most rewarding moment working/ studying in health care?

I find that the knowledge that we take back from the textbooks and the wards is so unique to each one of us that the best results always come from teamwork. Before I started med school, I was positively averse to team projects or anything that involved working in a group. But now I see the value of collective wisdom.

What’s your most embarrassing moment working/studying in health care?

When I tried to lie about having attended an autopsy. To my Forensics professor! (We have to attend 20 autopsies in our second year) He knew right away I was lying and quizzed me about the details of the autopsy. I had gotten basic details like male/female, cause of death from one of my friends. Then he asked me if the deceased had a beard. I stared him in the face and said NO as confidently as I could. Thought I had a 50% chance of being right. He HAD a beard. 🤦

Whats the best piece of advice you have ever received?

No one really told me this, but maybe I read this somewhere or something- Don’t fixate on the future because that way you are already ruining it. All you ever have is the present. Make the best of it.

What advice would you give others?

Everything comes to pass. If you feel like shit sometimes, know that it will end. If you feel super happy sometimes, know that it will end too. That’s life, peeps.

I’m tagging: @chocolatesofamedstudent

[mcavoy]

this is literally the only mood I ever have

[eightacres]

Day after day.

[eightacres]

When your emotional state is controlled by the approval of others, you are effectively a slave

Ed Latimore

[neurosciencestuff]

Mathematical modeling uncovers mysteries of HIV infection in the brain

After uncovering the progression of HIV infection in the brain thanks to a new mathematical model developed by a UAlberta research team, clinicians and researchers are developing a nasal spray to administer drugs more effectively.

The group that developed the model—led by PhD student Weston Roda and Michael Li, a professor in the Department of Mathematical and Statistical Sciences—used data from patients who died five to 15 years after they were infected, as well as known biological processes for the HIV virus to build the model that predicts the growth and progression of HIV in the brain, from the moment of infection onward. It is the first model of an infectious disease in the brain.

HIV infection in the brain has been a proverbial black box for scientists since the development of antiretroviral therapy in the 1990s.

“The nature of the HIV virus allows it to travel across the blood-brain barrier in infected macrophage—or white blood cells—as early as two weeks after infection. Antiretroviral drugs, the therapy of choice for HIV, cannot enter the brain so easily,” said Roda.

This creates what is known as a viral reservoir, a place in the body where the virus can lay dormant and is relatively inaccessible to drugs. Prior to this study, scientists could only study brain infection at autopsy. The new model allows scientists to backtrack, seeing the progression and development of HIV infection in the brain. Using this information, researchers can determine what level of effectiveness is needed for antiretroviral therapy in the brain to decrease active infection.

“The more we understand and can target treatment toward viral reservoirs, the closer we get to developing total suppression strategies for HIV infection,” said Roda. In fact, his results are already being put to use in a University of Alberta lab.

A research team led by Chris Power, Roda’s co-supervisor who is a professor in the Division of Neurology, is planning clinical trials for a nasal spray that would get the drugs into the brain faster—with critical information on dosage and improvement rate provided by Roda’s model.

“Our next steps are to understand other viral reservoirs, like the gut, and develop models similar to this one, as well as understand latently infected cell populations in the brain,” said Roda. “With the antiretroviral therapy, infected cells can go into a latent stage. The idea is to determine the size of the latently infected population so that clinicians can develop treatment strategies.”

The paper, “Modeling brain lentiviral infections during antiretroviral therapy in AIDS,” was published in the Journal of Neurovirology.

[tastefullyoffensive]

(via DrMassicotte)

[livebloggingmydescentintomadness]

i just feel like you guys should see this thread about foxes

[elodieunderglass]

For some reason, when biologists want to describe “the assemblage of morphological features shared among many members of a phylum-level group” we say bauplan. Which is German for “body plan.” But even if you don’t speak German you say “bauplan” anyway. So this is a very hilarious Social Media Discourse from someone who has forgotten that the word “bauplan” is an instant giveaway that you are actually a biologist and that makes it fantastic it’s like when robots try to pretend that they’re human but better