Boxer shorts for bicycling

Cyclists are supposed to ride ‘commando’ — nothing between cycling short padded lining and the butt.

Me, I don’t like to wash my cycling shorts that often, and sometimes I just ride with regular shorts. I prefer to wear synthetic fabric boxer shorts without seat area seams. I have a few pairs I’ve picked up over the years, but they’re no longer sold. I’ve had a hard time finding seamless shorts. Web sites generally show the front, not the back.

Today I searched harder. After digging past the typically useless few pages of Google pay-to-play-adsearch results here are the options I found, mostly in comments on a Lazy Randonneur blog post

• BOSS cyclist stretch cotton boxer briefs. These are cotton unfortunately. $28 for 3.
• ExOfficio Give-N-Go Boxer Briefs 1241-0020: Blog post. Designed for easy wash/dry, supposedly no seams in contact zone. $23 each. Top selling mens boxer briefs on Amazon. (Amazon has several versions of this underwear, but only one appears on the ExOfficio site. I think a number may be counterfeit, this one is sold by Amazon itself so probably genuine.)
• MEC merino briefs/T1 boxer briefs: Canada only alas.
• Devold multi sport boxer briefs: Blog post. Expensive Norwegian merino wool briefs sold by Rivendell cycle. About $40.
• Bent Scivvies: no longer sold as far as I can tell, once a Target store brand label. These sounded ideal

I ended up ordering one pair of ExOfficio and the set of 3 BOSS underwear. I’d love to find a Target or Walmart equivalent…

PS. I have a vague memory that back in the 70s male cyclists used to wear seamless women’s panties? Probably a false memory. Was a long time ago. I never had the nerve to try.

Apple's CareKit (HealthKit) - what kinds of clinical data does it work with?

I thought Apple had given up on HealthKit, but recently we learned that it’s been rebranded as CareKit and it seems to be going forward.

Since my professional work is in “health informatics”, specifically medical knowledge applications, I was curious what “ontology” (data dictionary, terminology, etc) Apple was using for it’s CareKit work. The concept set is somewhat hidden within Apple’s HealthKit Constants Reference documentation. I auto-expanded the symbols (nice web app Apple!) and make a quick pass at organizing the strings.

For someone like me it’s a fascinating set. The discussion of privacy and FDA device identifiers is noteworthy — in an early implementation it was apparently possible to trace HealthKit data to an individual device (not good, obviously - bold below).

I liked the use of Fitzpatrick Skin Type instead of trying to describe ethnicity/race.

It’s a fun list to scan:

HKMetadataKeyBodyTemperatureSensorLocation
HKMetadataKeyCoachedWorkout
HKMetadataKeyDeviceManufacturerName
HKMetadataKeyDeviceName
HKMetadataKeyDeviceSerialNumber
HKMetadataKeyDigitalSignature
HKMetadataKeyExternalUUID
HKMetadataKeyFoodType
HKMetadataKeyGroupFitness
HKMetadataKeyHeartRateSensorLocation
HKMetadataKeyIndoorWorkout
HKMetadataKeyMenstrualCycleStart
HKMetadataKeyReferenceRangeLowerLimit
HKMetadataKeyReferenceRangeUpperLimit
HKMetadataKeySexualActivityProtectionUsed
HKMetadataKeyTimeZone
HKMetadataKeyUDIDeviceIdentifier
HKMetadataKeyUDIProductionIdentifier
HKMetadataKeyWasTakenInLab
HKMetadataKeyWasUserEntered
HKMetadataKeyWorkoutBrandName

HKCategoryTypeIdentifierAppleStandHour
HKCategoryTypeIdentifierCervicalMucusQuality
HKCategoryTypeIdentifierIntermenstrualBleeding
HKCategoryTypeIdentifierMenstrualFlow
HKCategoryTypeIdentifierOvulationTestResult
HKCategoryTypeIdentifierSexualActivity
HKCategoryTypeIdentifierSleepAnalysis

HKBiologicalSexFemale
HKBiologicalSexMale
HKBiologicalSexNotSet = 0
HKBiologicalSexOther

HKBloodTypeABNegative
HKBloodTypeABPositive
HKBloodTypeANegative
HKBloodTypeAPositive
HKBloodTypeBNegative
HKBloodTypeBPositive
HKBloodTypeNotSet = 0
HKBloodTypeONegative
HKBloodTypeOPositive

HKBodyTemperatureSensorLocationArmpit
HKBodyTemperatureSensorLocationBody
HKBodyTemperatureSensorLocationEar
HKBodyTemperatureSensorLocationEarDrum
HKBodyTemperatureSensorLocationFinger
HKBodyTemperatureSensorLocationForehead
HKBodyTemperatureSensorLocationGastroIntestinal
HKBodyTemperatureSensorLocationMouth
HKBodyTemperatureSensorLocationRectum
HKBodyTemperatureSensorLocationTemporalArtery
HKBodyTemperatureSensorLocationToe

HKCategoryValueCervicalMucusQualityCreamy
HKCategoryValueCervicalMucusQualityDry = 1
HKCategoryValueCervicalMucusQualityEggWhite
HKCategoryValueCervicalMucusQualitySticky
HKCategoryValueCervicalMucusQualityWatery

HKCategoryValueMenstrualFlowHeavy
HKCategoryValueMenstrualFlowLight
HKCategoryValueMenstrualFlowMedium
HKCategoryValueMenstrualFlowUnspecified = 1

HKCategoryValueSleepAnalysisAsleep
HKCategoryValueSleepAnalysisInBed

HKCharacteristicTypeIdentifierBiologicalSex
HKCharacteristicTypeIdentifierBloodType
HKCharacteristicTypeIdentifierDateOfBirth
HKCharacteristicTypeIdentifierFitzpatrickSkinType
HKCorrelationTypeIdentifierBloodPressure
HKCorrelationTypeIdentifierFood

HKFitzpatrickSkinTypeI
HKFitzpatrickSkinTypeII
HKFitzpatrickSkinTypeIII
HKFitzpatrickSkinTypeIV
HKFitzpatrickSkinTypeNotSet = 1
HKFitzpatrickSkinTypeV
HKFitzpatrickSkinTypeVI

HKHeartRateSensorLocationChest
HKHeartRateSensorLocationEarLobe
HKHeartRateSensorLocationFinger
HKHeartRateSensorLocationFoot
HKHeartRateSensorLocationHand
HKHeartRateSensorLocationWrist

HKQuantityTypeIdentifierActiveEnergyBurned
HKQuantityTypeIdentifierAppleExerciseTime
HKQuantityTypeIdentifierBasalBodyTemperature
HKQuantityTypeIdentifierBasalEnergyBurned
HKQuantityTypeIdentifierBloodAlcoholContent
HKQuantityTypeIdentifierBloodGlucose
HKQuantityTypeIdentifierBloodPressureDiastolic
HKQuantityTypeIdentifierBloodPressureSystolic
HKQuantityTypeIdentifierBodyFatPercentage
HKQuantityTypeIdentifierBodyMass
HKQuantityTypeIdentifierBodyMassIndex
HKQuantityTypeIdentifierBodyTemperature
HKQuantityTypeIdentifierDietaryBiotin
HKQuantityTypeIdentifierDietaryCaffeine
HKQuantityTypeIdentifierDietaryCalcium
HKQuantityTypeIdentifierDietaryCarbohydrates
HKQuantityTypeIdentifierDietaryChloride
HKQuantityTypeIdentifierDietaryCholesterol
HKQuantityTypeIdentifierDietaryChromium
HKQuantityTypeIdentifierDietaryCopper
HKQuantityTypeIdentifierDietaryEnergyConsumed
HKQuantityTypeIdentifierDietaryFatMonounsaturated
HKQuantityTypeIdentifierDietaryFatPolyunsaturated
HKQuantityTypeIdentifierDietaryFatSaturated
HKQuantityTypeIdentifierDietaryFatTotal
HKQuantityTypeIdentifierDietaryFiber
HKQuantityTypeIdentifierDietaryFolate
HKQuantityTypeIdentifierDietaryIodine
HKQuantityTypeIdentifierDietaryIron
HKQuantityTypeIdentifierDietaryMagnesium
HKQuantityTypeIdentifierDietaryManganese
HKQuantityTypeIdentifierDietaryMolybdenum
HKQuantityTypeIdentifierDietaryNiacin
HKQuantityTypeIdentifierDietaryPantothenicAcid
HKQuantityTypeIdentifierDietaryPhosphorus
HKQuantityTypeIdentifierDietaryPotassium
HKQuantityTypeIdentifierDietaryProtein
HKQuantityTypeIdentifierDietaryRiboflavin
HKQuantityTypeIdentifierDietarySelenium
HKQuantityTypeIdentifierDietarySodium
HKQuantityTypeIdentifierDietarySugar
HKQuantityTypeIdentifierDietaryThiamin
HKQuantityTypeIdentifierDietaryVitaminA
HKQuantityTypeIdentifierDietaryVitaminB6
HKQuantityTypeIdentifierDietaryVitaminB12
HKQuantityTypeIdentifierDietaryVitaminC
HKQuantityTypeIdentifierDietaryVitaminD
HKQuantityTypeIdentifierDietaryVitaminE
HKQuantityTypeIdentifierDietaryVitaminK
HKQuantityTypeIdentifierDietaryWater
HKQuantityTypeIdentifierDietaryZinc
HKQuantityTypeIdentifierDistanceCycling
HKQuantityTypeIdentifierDistanceWalkingRunning
HKQuantityTypeIdentifierElectrodermalActivity
HKQuantityTypeIdentifierFlightsClimbed
HKQuantityTypeIdentifierForcedExpiratoryVolume1
HKQuantityTypeIdentifierForcedVitalCapacity
HKQuantityTypeIdentifierHeartRate
HKQuantityTypeIdentifierHeight
HKQuantityTypeIdentifierInhalerUsage
HKQuantityTypeIdentifierLeanBodyMass
HKQuantityTypeIdentifierNikeFuel
HKQuantityTypeIdentifierNumberOfTimesFallen
HKQuantityTypeIdentifierOxygenSaturation
HKQuantityTypeIdentifierPeakExpiratoryFlowRate
HKQuantityTypeIdentifierPeripheralPerfusionIndex
HKQuantityTypeIdentifierRespiratoryRate
HKQuantityTypeIdentifierStepCount

HKWorkoutActivityTypeAmericanFootball = 1
HKWorkoutActivityTypeArchery
HKWorkoutActivityTypeAustralianFootball
HKWorkoutActivityTypeBadminton
HKWorkoutActivityTypeBaseball
HKWorkoutActivityTypeBasketball
HKWorkoutActivityTypeBowling
HKWorkoutActivityTypeBoxing
HKWorkoutActivityTypeClimbing
HKWorkoutActivityTypeCricket
HKWorkoutActivityTypeCrossTraining
HKWorkoutActivityTypeCurling
HKWorkoutActivityTypeCycling
HKWorkoutActivityTypeDance
HKWorkoutActivityTypeDanceInspiredTraining
HKWorkoutActivityTypeElliptical
HKWorkoutActivityTypeEquestrianSports
HKWorkoutActivityTypeFencing
HKWorkoutActivityTypeFishing
HKWorkoutActivityTypeFunctionalStrengthTraining
HKWorkoutActivityTypeGolf
HKWorkoutActivityTypeGymnastics
HKWorkoutActivityTypeHandball
HKWorkoutActivityTypeHiking
HKWorkoutActivityTypeHockey
HKWorkoutActivityTypeHunting
HKWorkoutActivityTypeLacrosse
HKWorkoutActivityTypeMartialArts
HKWorkoutActivityTypeMindAndBody
HKWorkoutActivityTypeMixedMetabolicCardioTraining
HKWorkoutActivityTypePaddleSports
HKWorkoutActivityTypePlay
HKWorkoutActivityTypePreparationAndRecovery
HKWorkoutActivityTypeRacquetball
HKWorkoutActivityTypeRowing
HKWorkoutActivityTypeRugby
HKWorkoutActivityTypeRunning
HKWorkoutActivityTypeSailing
HKWorkoutActivityTypeSkatingSports
HKWorkoutActivityTypeSnowSports
HKWorkoutActivityTypeSoccer
HKWorkoutActivityTypeSoftball
HKWorkoutActivityTypeSquash
HKWorkoutActivityTypeStairClimbing
HKWorkoutActivityTypeSurfingSports
HKWorkoutActivityTypeSwimming
HKWorkoutActivityTypeTableTennis
HKWorkoutActivityTypeTennis
HKWorkoutActivityTypeTrackAndField
HKWorkoutActivityTypeTraditionalStrengthTraining
HKWorkoutActivityTypeVolleyball
HKWorkoutActivityTypeWalking
HKWorkoutActivityTypeWaterFitness
HKWorkoutActivityTypeWaterPolo
HKWorkoutActivityTypeWaterSports
HKWorkoutActivityTypeWrestling
HKWorkoutActivityTypeYoga

HKWorkoutSessionLocationTypeIndoor
HKWorkoutSessionLocationTypeOutdoor
HKWorkoutSessionLocationTypeUnknown = 1

Old broken person CrossFit - it's fun. Really.

The experimental results are in. Under optimal conditions I can do a CrossFit WOD 4 times in five days and not be obviously injured. 

That’s no trick for under 30, but over 55 there’s a fuzzy border between enough and too much. Shoulders, knees, wrists (again), butt tendons and backs take turns being funky. Not to mention errant barbell strikes. And the unrelated arthritis.

Yeah, that does sound kind of grim, but the body does some of that just sitting around. The knees were from mountain biking, and the piriformis problem was hockey. With my genes, being old* and active is experiential sports medicine.

I like it though. I even like putting a toe over that fuzzy border once in a while.

I don’t want injuries to bench me though, so here’s my year 3 of CrossFit recipe for staying more or less out of trouble. 

• 3 “Workout of the Day” (WOD) every week. Sometimes 4, but I was pushing things this week.
• My WOD target is “Women’s Rx”. I can do that for some movements and weights. This tends to be close to the men’s “master’s Rx” of competitive CrossFit. Muscle fatigue is my main weakness, I think that’s true of most 40+.
• I listen to my coaches. They have good advice.
• 1-2 Open Gym workouts - a light version of a WOD or a special movement or muscle group. Like $*&^% double-unders or bar muscle ups or handstand pushups.
• I started taking one of those whacky protein supplement powders after my big workouts. You can blame that on a recent publication that showed it helping in a small trial of exercise and weight loss. It includes magical arthritis supplements that I’m supposed to take anyway (though they probably don’t do anything)
• Hockey and/or Mountain Biking 1-3 times a week (sub Nordic Skiing**, road biking, swimming, running, underwater hockey, etc)

I think I can keep that going for a few years more, depending on what surprises age brings. I’ve learned that the researchers are right, the body adapts to exercise by increasing energy efficiency — diet is still a challenge. I can’t survive doing CrossFit at the frequency needed to balance my calorie intake, so it has to be supplemented by calorie burning activities that are easier on the old body (bicycling, hockey, etc)

It really is fun.

* 50 is not the new 30. Sorry. Don’t talk about 80. Please.
** Nordic Skiing was my all-time favorite exercise. I’m not a global warming fan.

See also:

• On knee pain and the state of medical knowledge (updated) 9/2015: turned out to be partly chondromalacia, but weirdly it went away.
• Fixing a painful wrist with high frequency weightlifting and wrist hyperextension. WTF 10/2015: bodies are weird
• Deep Burning Butt Ache review: Piriformis syndrome, sciatica, deep gluteal syndrome, sacroiliac syndrome, deep buttock syndrome: 2/2016. The stretches worked!
• CrossFit at 54 8/2013. I stopped seeing tattoos. That’s odd.
• Growing old grudgingly: The CrossFit Inversion: 12/2015: But this week I had a new record bench press weight.
• Anecdote - exercise and weight control. It takes a lot 12/2014: You can out-eat almost any amount of exertion.
• Exercise on the exit ramp - the 30 year plan: 11/2014 - scaling with age, ending with golf
• Exercising hard as an old person - one year of CrossFit: 4/2014. Then I did 70-80% of women’s Rx.
• Why geezers hit the gym 3/2014

The Obama doctrine -- I will so miss our Vulcan President

From the Obama Doctrine, quoting the President:

… Right now, across the globe, you’re seeing places that are undergoing severe stress because of globalization, because of the collision of cultures brought about by the Internet and social media, because of scarcities—some of which will be attributable to climate change over the next several decades—because of population growth…

… As I survey the next 20 years, climate change worries me profoundly because of the effects that it has on all the other problems that we face. If you start seeing more severe drought; more significant famine; more displacement from the Indian subcontinent and coastal regions in Africa and Asia; the continuing problems of scarcity, refugees, poverty, disease—this makes every other problem we’ve got worse. That’s above and beyond just the existential issues of a planet that starts getting into a bad feedback loop.

By “collision of cultures” I think he means “existential threats to patriarchy” — because he’s obviously reading my mind. Must come with his Vulcan heritage.

We are never ever going to get another President this good (even though he’s wrong about encryption). HRC isn’t bad, but she’s no Obama.

Using Gmail and the link to correspond with patients -- HIPAA 2013 clarification

HIPAA is designed to protect patient confidentiality. It’s widely misunderstood, not least because of the scary fines for violations. I think on balance it’s a good law, but it needs regular adjustment.

Happily in 2013 a major adjustment was made. Rule makers allowed use of conventional email applications, perhaps without robust encryption, for patient communications if informed consent is given and recorded. I recently put together a set of references on this:

https://personcenteredtech.com/2013/10/06/clients-have-the-right-to-receive-unencrypted-emails-under-hipaa/
Covers the 2013 final rule changes.

http://blog.securitymetrics.com/2014/05/hipaa-email-encryption.html
Pretty good discussion of implications

http://www.austinmedclinic.com/hipaa-and-email.pdf
Example of a patient consent to receive unencrypted email

http://www.gpo.gov/fdsys/pkg/FR‐2013‐01‐25/pdf/2013‐01073.pdf
HIPAA language is on page 5634 (I didn’t confirm this, just copied from the Austin Med Clinic consent form.

I’d still worry about risks associated with using Gmail (though communication is now actually well encrypted for most users) — the message will be both sender and receiver’s server forever unless it’s deleted. Tricky business!

Still, it’s encouraging to see this clarification. I hope the HIPAA rules continue to be adjusted. Having robust encryption built into laptops helps — at least until the FBI forces backdoors which will, of course, be widely exploited by hackers.

Phenazopyridine (pyridium, AZO) - yet another example of missing research

Phenazopyridine is an old drug, discovered in the 1930s. Chemically it’s classified as an “azo dye”, these chemicals are usually used to color clothing. Phenazopyridine will stain clothing orange. Another Azo dye was once used a seizure med. 

Two-thirds of a dose is excreted unchanged in the urine (and sweat and tears), the rest is metabolized to unknown substances. It has some sort of anesthetic action on the urinary tract, we don’t know how that works. “Trace amounts” may enter the cerebrospinal fluid. With prolonged use there is injury to both liver and kidney.

Historically phenazopyridine was prescribed for use in the very early stages of a bladder infection, before antibiotics did their job (since it’s older than antibiotics I suspect it was used heavily in the past). It’s over the counter now, to be used for one to two days.

Except some patients use phenazopyridine for longer than a few days. Interstitial cystitis is particularly nasty syndrome. Like many poorly understood disorders (osteoarthritis, autism, etc) it’s probably several different disorders that share common features. One pattern of interstitial cystitis causes severe sleep disruption; patients wake up to void every 10 to 60 minutes with very small volume urination. On bladder biopsy the protective lining of the bladder has been disrupted. 

Sleep deprivation is a well understood and effective form of torture, so it’s not surprising that IC patients get a bit desperate (you would too). Phenazopyridine may allow sleep when all else fails. So it’s used more than it should be, especially since it’s available without a prescription.

Since phenazopyridine has an anesthetic effect, we presume it interacts with the peripheral nervous system.  So what happens to the brain with large lifetime doses of phenazopyridine? I can’t see that this has ever been investigated, even in animal models.  Tartrazine, another azo dye used in food coloring, was associated with oxidative brain damage in one rat study.

Medicine is full of things like phenazopyridine. Medications that were adopted long ago, and have received minimal research review since. We could employ an army of scientists studying these drugs. But then we’d have to figure out how to pay for them…

The Man's Book (1978)

I remember the early 1970s as quite odd - particularly based on the books of the time. I like to pick them up if I can find them, but I think others share my interest. I rarely see them in used book stores.

I remembered on recently. Actually, it’s late 70s, so not nearly as odd, but still quite a long time ago. The topic is what makes it interesting…

The Man’s Book was published in 1978 (ISBN-13: 978-0380018994). There were no later editions, though suspiciously similar books with the same name have been published more recently. I wonder if they just pilfered the original.

It’s a real cultural artifact, required reading for a historian of the era …

and

Some of the contents are very 1970s…

Most of it, however, still works today. That surprised me a bit, but really a lot changed between 1968 and 1978 and the book is written from a liberal perspective. It would have been a very different book if it were written in 1973.

The advice to a man on how to support a working wife is the most dated …

… If you say, “No wife of mine is going to work,” you’ll be considered antiquated …when you both work, something or someone is always getting neglected … The household is often on the brink of chaos …

… To make a two-career marriage work, you both need sensitivity, cooperation, flexibility, and a boundless sense of humor…

… In spite of women’s lib [ed note: at the time that would not have been meant sarcastically] when you run out of catsup … there’s no question, in your mind or hers, whose fault it is … you’ll make it easier on both of you if you pitch in and share responsibility for the household …

… it’s necessary to be willing to share power…

Dated, but perhaps not as dated as we might wish it to be. The rest of the book still kind of works. I’m going to hand it off to my #2 son…

Everyone needs an AI in their pocket

Two articles from my share feed today …

Transit systems are growing too complex for the human mind

… “What makes it messy is the presence of different possibilities," Barthelemy says. "When you arrive at a specific point, you have many choices."

The Paris system has 78 such choice points. The New York subway, the most complex in the world, has 161. New York's system is so sprawling and interconnected, Barthelemy and colleagues Riccardo Gallotti and Mason Porter concluded in a recent analysis, that it approaches the maximum complexity our human minds can handle, the equivalent of about 8 bits of information.

“But then if you add the bus,” Barthelemy warns, “the 8-bit limit is exploded."...

and

Google Research: An Update on fast Transit Routing with Transfer Patterns

What is the best way to get from A to B by public transit? Google Maps is answering such queries for over 20,000 cities and towns in over 70 countries around the world, including large metro areas like New York, São Paulo or Moscow…

… Scalable Transfer Patterns algorithm [2] does just that, but in a smart way. For starters, it uses what is known as graph clustering to cut the network into pieces, called clusters, that have a lot of connections inside but relatively few to the outside…

… Frequency-Based Search for Public Transit [3] is carefully designed to find and take advantage of repetitive schedules while representing all one-off cases exactly. Comparing to the set-up from the original Transfer Patterns paper [1], the authors estimate a whopping 60x acceleration of finding transfer patterns from this part alone….

Humans can’t manage modern transit complexity — but the AIs can. Including the AI in your pocket.

Everyone needs a portable AI, including people with no income and people with cognitive disabilities. That’s one reason I’m writing my smartphone for all book.

See also:

• Life in the post-AI world. What’s next? 9/2011

Minnesota explained: Rubio, Sanders and the President Gordon agenda.

My home state of Minnesota, most annoyingly, uses caucuses. I attend the Dem variety in the bluest of neighborhoods. They are crowded, disorganized and well meaning. When I ride my bike to caucus cars slam to a stop as though I were a family of 5 on foot. Which is wrong and dangerous, but I appreciate the sentiment.

The Dem caucus is not representative of the Dem voter. You have to be very persistent to fight through traffic and crowds to hit the narrow window for voting. Only the most committed can get there. The caucus system is a bad, bad idea. I think the same is true of the GOP caucuses here.

So the caucus results last night were not too surprising.

The GOP, as usual, went for the extreme right candidates. This year there were three of ‘em - Trump, Rubio and Cruz. Since we have one of the strongest economies in the US, with unemployment under 5% for years, Trump didn’t have his usual vote-of-despair left-behind advantage. So the three extremes ended up with fairly similar numbers, but the anti-Trump movement focused on Rubio and he won.

My team went, as usual, for the more left candidate. Sanders won by 20%, so he might even have won a primary. I voted for HRC, but the MN DFL is effectively to the left of me — which is saying a lot.

I’m backing HRC but, in truth, we need to go down some variation of the Sanders road over the next two decades. We’re going to have to bias the post-AI globalized economy to generate jobs for the non-college — even at the cost of economic efficiency. We have to build more social supports for people who aren’t working, with some kind of rethinking of what we do for disabled workers. We may end up with a non-binary definition of disability, or even some kind of guaranteed income.

We will end up taxing wealth in one form or another and we’ll do a  lot more government redistribution. We should also, and this is not so much Sanders, execute on the old Gore “reinventing government” mission, refactoring regulatory systems. We need to break the accounting, tax and regulatory frameworks the mega-corporations (“neo-Chaebol is a term I like) have built; the foundations of a great stagnation ecosystem wherein new companies are built only for acquisition.

We need to build supports that enable entrepreneurial types to pick business designs off a shelf and implement them. We need to strip benefits from employment completely, and both fix and finish the mission the ACA started — while breaking the corporatization of that great compromise.

Phew. It’s a big mission, but it is doable. We have to do it, or we get President Trump. Or worse. Sooner or later. 

So I don’t feel that bad that Sanders won Minnesota. It’s a good sign for the future. I don’t want him to go up against the GOP though. By the time their attack machine is done with him he’ll be hiding in a stone shelter in the wilderness. HRC’s great strength is she’s lived that machine for decades. Nobody short of Obama can equal that. (And, of course, I would love him to keep his job. Alas, even if our constitution allowed that I think he’s ready for a change.)

See also:

• The AI Age: Siri and Me 12/2011
• Causes of the Great Recession: China, GPSII and RCIIIT. Now for Act III. 4/2010. Holds up pretty well, but I now add a third somewhat related factor of a mega-corp created environment that’s toxic to the startups that historically create employment.
• Amerisclerosis? Why US underemployment (and probably inequality) persists 9/2013. Secular stagnation is the current term.
• Mass disability goes mainstream: disequilibria and RCIIT 11/2011. In the new age there jobs for the high EQ/IQ. Others are not so needed.
• Ants, corporations and the great stagnation 12/2011
• Causes of the crash of ’08 - how much fraud? 2/2009. Good to look back, but I know think these were secondary causes. For example, IT enabled complexity and complexity enabled fraud.
• Civilization is stronger than we think: Structural deficits and complex adaptive systems 5/2010. Trumpism is scary, but it’s also the way the “meta-mind” approaches big hard changes.
• Donald Trump is a sign of a healthy democracy. Really. 8/2015. The problem of the unwanted non-college (“working class”) isn’t going to be solved by more education. Remember, the non-sentient AI revolution will come for you too.
• For American adults are poverty and disability the same thing? 10/2013. I think this is true for white and asian men in America, for others racism also drives poverty. (I mention this at the end of the post but should have had it up front.)

Pediatric TMJ disorder and Developmental Dysplasia of the Hip: Separated at birth?

Early onset disruption of the Temperomandibular Joint (TMJ) reminds me of what we once called Congenital Dislocation of the Hip (CDH). That syndrome has since been better named as Developmental Dysplasia of the Hip. Untreated DDH is thought to result in severe early arthritis of the hip.

I wonder if early-onset (pediatric) TMJ syndrome should be renamed Developmental Dysplasia of the Temperomandibular Joint (DDTMJ).

I don’t see any hint of this in my PubMed searches though.

First.

Why Johnny can't make drugs any more ... we need better science from government.

I think of In the Pipeline’s Derek Lowe as a small ‘m’ marketarian. He has more confidence in the “invisible hand” of markets than I, but he’s not a believer in Rand’s Market Divine (the market that can do no evil, so long as government snakes are avoided). He combines critiques of big pharma CEOs with a robust defense of antibiotic development process.

Which may explain why he sort-off calls for more government funding of basic research — without quite getting there…

A Terrific Paper on the Problems in Drug Discovery | In the Pipeline

… Jack Scannell and Jim Bosley … “These kinds of improvements should have allowed larger biological and chemical spaces to be searched for therapeutic conjunctions with ever higher reliability and reproducibility, and at lower unit cost … in contrast many results derived with today’s powerful tools appear irreproducible; today’s drug candidates are more likely to fail in clinical trials than those in the 1970s … some now even doubt the economic viability of R&D in much of the drug industry [22] [23].

The contrasts ..between huge gains in input efficiency and quality, on one hand, and a reproducibility crisis and a trend towards uneconomic industrial R&D on the other, are only explicable if powerful headwinds have outweighed the gains [1], or if many of the “gains” have been illusory …

Shaywitz and Taleb wrote something similar about ten years ago (via Hensley, WSJ, emphases mine)…

… The molecular revolution was supposed to enable drug discovery to evolve from chance observation into rational design, yet dwindling pipelines threaten the survival of the pharmaceutical industry,” say consultant David Shaywitz and Nassim Nicholas Taleb, author of “The Black Swan: The Impact of the Highly Improbable.”

“What went wrong?” they ask in the opinion pages of the Financial Times. “The answer, we suggest, is the mismeasure of uncertainty, as academic researchers underestimated the fragility of their scientific knowledge while pharmaceuticals executives overestimated their ability to domesticate scientific research.”

When you get right down to it, Shaywitz and Taleb say, we still don’t understand the causes of most disease. Even when we think we do, because someone found a relevant gene, we’re not very good at turning the knowledge into a treatment. “Spreadsheets are easy; science is hard,” they tell Big Pharma.

I lived through this, including the 2nd failure of the genomic revolution. In retrospect the years from 1945 through the 1970s were a Golden Age of medicine. I did my medical science in 1982; for my generation the Golden Age was a baseline. We thought we understood so much …

By 2008 we all knew we had a problem. I’d been long out of practice and I was having to catchup on 7 years of medicine for my licensing exam. That turned out to be easier than expected. I wrote then about medications…

1. Lots of new combinations of old drugs, maybe due to co-pay schemes
2. Many new drugs have suicidal ideation as a side-effect.
3. Lots of failed immune related drugs re-purposed with limited focal impact on a few disorders.
4. Probably some improvements in seizure meds. Lots of new Parkinson’s and diabetes meds, but they’ve had limited value. (metformin was a home run, but that was more than 7 years ago).
5. Really lousy progress in antibiotics; there are fewer useful therapies now than 7 years ago. Actually, fewer every year.

With Lowe’s latest we learn what has come from 8+ years of digging into our research flail (emphases mine):

… this paper is also a great source for what others have had to say about these issues, too (and since it’s in PLoS, it’s open-access). But the heart of the paper is a series of attempts to apply techniques from decision theory/decision analysis to these problems …

 

… Let’s all say “Alzheimer’s!” together, because I can’t think of a better example of a disease where people use crappy models because that’s all they have. This brings to mind Bernard Munos’ advice that (given the state of the field), drug companies would be better off not going after Alzheimer’s at all until we know more about what we’re doing, because the probability of failure is just too high…

 

… I’ve long thought that a bad animal model (for example) is much worse than no animal model, and I’m glad to see some quantitative backup for that view. The same principle applies all the way down the process, but the temptation to generate numbers is sometimes just too high, especially if management really wants lots of numbers. So how’s that permeability assay do at predicting which of your compounds will have decent oral absorption? Not so great? Well, at least you got it run on all your compounds…

 

… there’s no cure for the physical world, either, at least until we get better informed about it, which is not a fast process and does not fit well on most Gantt charts. Interestingly, the paper notes that the post-2012 uptick in drug approvals might be due to concentration on rare diseases and cancers that have a strong genetic signature …

 

… in drug discovery, we have areas that where our models (in vitro and in vivo) are fairly predictive and areas where they really aren’t…

I think what Lowe is telling us that we need more basic science work because drug development has raced ahead of the science-road it runs on. On the other hand, being a believer in markets and enterprise, he doesn’t quite come out and say that government needs to fund this work, even though he knows pharma won’t.

 

Or perhaps he has such a low opinion of current US government funded research that he doesn’t think our NIH will help. I see his point.  So we need government, but we need better government science …

 

It’s a tough one.

 

But… I just did my board exams again. Seven more years have passed. This time I had to learn more things. Maybe, when we look back, we’ll say that genomics science began to pay dividends around 2010. I think that’s not enough though. If the US is ungovernable, maybe we need to look for others to lead…

See also:

• Rebooting medical research - the world needs Canada 2/2016
• Why did medical progress slow after 1984? 12/2010
• Challenges to medicine and science – medication invention hits a brick wall 7/2008
• A peculiar finding of a 2010 RSV infection and transient autoimmune diabetes leads to … nothing. 2/2016

A peculiar finding of a 2010 RSV infection and transient autoimmune diabetes leads to ... nothing.

In March of 2012 we learned that a researcher identified a striking relationship between a RSV (respiratory syncytial virus) respiratory infection and development of transient auto-immune diabetes mellitus. You can read the companion article online, the ’54-year-old male volunteer” was Michael Snyder, one of the researchers.

I came across my old blog post on this today, so I looked to see what we’ve learned since about this peculiar relationship. I did a PubMed literature search on “respiratory syncytial virus” and “diabetes”. I found that 2012 article … and nothing else.

I reviewed the 100 or so subsequent article extracts that cited the 2012 paper. There didn’t seem to be any follow-up research.

Maybe the article was badly mistaken. Or maybe this is related to our post-70s research problem.

Red Cross Basic Life Support training: avoid the Flash based simulation option

The American Red Cross runs classes in basic life support (CPR/AED). I’m doing the professional course. 

Historically these courses have been quite good, but these days they are sometimes (always?) offered as a combined online training module and a class-based skills portion.

Which would be a good idea — if the module weren’t buggy. It’s a Flash based program, and on my new MacBook Air Flash/Chrome misses trackpad clicks. Not something one would normally notice, but the simulation requires one tap 30 times at a rate of 100-120 taps/minute. When the tap frequency exceeds about 105 clicks get dropped. One can hear the pad click, but the simulation doesn’t respond.

Two counting errors means repeating the simulation. With this bug counting errors are common.

I’ve done one module, the last one left, at least 4 times. Once my wife, watching me, saw it miss 6 of 30 clicks.

Software is hard. Server side software is very hard. It’s expensive to develop, but it’s even more expensive to maintain and revise. We compare software development to building bridges, but really it’s more like building a fancy English garden. Hard to plan, hard to create, but it’s the maintenance that really hurts.

The Red Cross shouldn’t be running this simulation. They can’t afford it. They’re not alone though. The American Board of Family Medicine recently deprecated a very ambitious patient simulation software project. They really needed to do that, but it must have been a hard call. They’d invested a lot of work and money. The reality was, they couldn’t afford the maintenance.

There’s nothing easy about software. We need less of it, done better.

Tip: If you do have to do this, try a mouse instead of the trackpad. I found the glitches distracting and stopped watching the animated hands, but that was a mistake. Click the mouse but count on the hand movement. 

PS. When it comes to abdominal trust vs. back blows for chocking adult/child the downloadable text is internally inconsistent and also inconsistent with the abdominal thrust only simulation…

Update 2/12/2016: Our in-person class had 6 participants. One didn’t realize there was an online portion — I can see missing it, communications and the web site are both confusing. At least one other person had to call support to find the online portion. Everyone had click-count problem; one young person described the simulation as the worst experience of her life (she is young).

As is typical once one person spoke of having problems everyone joined in. It seems I got off lightly.

The logic and consistency errors around foreign body/choking management are well known. The course is scheduled to be rebooted in a month; i hope the simulations will be redone or eliminated. I’d suggest the American Heart Association course instead.

Aspirin, NSAIDs, cell death and the treatment of arthritis and interstitial cystitis

While doing some research on interstitial cystitis Google uncovered an extraordinary claim by the Cleveland Clinic’s Raymond Rackley:

Microsoft Word - Transcript for IC Video.doc

… exposure to TNF−α produces a dysfunctional activation pattern in IC urothelial cells that leads to cellular apoptosis…

Aberrant NF−κB signaling activation may be responsible for the imbalance of apoptotic and survival mechanism of the bladder epithelium that gives rise to the pathogenesis of IC … asking all IC patients to avoid aspirin or aspirins like products such as NSAIDs that block normal NF- B signaling …

I can’t tell when this transcript was created, there’s no date information on the PDF. As of Feb 2016 Rackley has 71 publications, but the only one that might lead in this direction was from 2011. I don’t think there have been any publications out of this particular video presentation.

The claim is extraordinary for two reasons. The first is that interstitial cystitis is a common cause of significant suffering, we have no good treatments (see also), and patients often use NSAIDs or even aspirin (which acidifies urine, for some that might help). If this claim were true those people should all switch to acetaminophen.

The other reason, of course, is that the transcript notes that aspirin and NSAIDS (ibuprofen, etc) have a significant effect on the mechanisms that influence cell death (apoptosis). This is mentioned as though it were common knowledge, but it was a surprise to me. Perhaps it shouldn’t have been, I know here has been a suspicion for at least 10 years that NSAIDs slow tendon injury healing. I’m also aware of epidemiology studies of an inverse association between colon cancer and aspirin use, and recently the USPSTF added colorectal cancer prevention to its draft aspirin use guidelines.

I suppose, in retrospect, if aspirin reduces the risk of colorectal cancer it may well do so by empowering our cellular level anti-cancer controls (vs. say, altering the microbiome). One way to empower those controls is to bias our cellular monitoring systems towards more aggressive cellicide (apoptosis) — and away from healing.

This has occurred to researchers. A search on apoptosis and aspirin returns 181 results starting in 1995 and accelerating in 2008 (NSAIDs) with a flurry of publications in the past few years. So among researchers, the idea that aspirin and NSAIDs shift our cellular systems away from healing and towards apoptosis (for better or worse) is probably not so surprising.

For clinicians however, this is potentially significant. We use aspirin for heart disease of course, but only in modest doses. More importantly, we use NSAIDs extensively for arthritic conditions where we may want more rather than less healing. (Not to mention interstitial cystitis).

It would be good to know how real this effect is. As Emily reminds me it is perilous to extrapolate from basic research to clinical practice. Even so, I would suggest people suffering from interstitial cystitis may want to consider acetominophen, assuming their liver is in good health.

Rebooting medical research - the world needs Canada.

My mother had a bottle of thalidomide on the shelf.

It was her first pregnancy and she was sick. Thalidomide was the hot new treatment for morning sickness. It wasn’t approved in the US, but Canada was ahead of the curve and a keen young obstetrician gave her the meds. 

Being a nurse she was suspicious of physicians, so she never took them and my arms and legs developed normally. I don’t know why thalidomide helped with morning sickness, but it was quite toxic to the developing fetus. 

Thalidomide had a second life though. Over the past 50 years it’s come to be used for a complication of Leprosy, for early multiple myeloma and for a few other conditions. Research has led to development of several related drugs.

It all took a long time though. There’s not much money to be made from off-patent medications, so there’s no funding from drug companies. There’s not a lot of support from traditional government sources either — there’s nothing exciting or sexy about this kind of costly, slow, research. Individual clinicians might do small trials on their own initiative, but unless the results are extremely positive nothing more will come of them. Worse, those small trials are increasingly hard to do in an era of humane and ethical research. Perhaps these are some of the reasons medical process has slowed since the early 1980s.

There are lots of odd drugs out there that have accumulated small research results but languish for lack of further investigation. Cimetidine was popular in the 1980s for ulcer disease, but in it’s off-patent life it’s been used for interstitial cystitis, persistent calcific tendinitis, animal studies of the innate immune system, eosinophilic fasciitis, warts, herpes simplex cold sores and doubtless other unpublished experiments. It probably doesn’t work for warts, but does it work for any of these conditions? We don’t know. There’s no money for the boring and expensive animal model development and clinical trials.

There are many drugs like cimetidine. They show up as “possible treatments” in the extensive literature around diseases we can’t fix. They are shots in the dark often based on biological plausibility, chance observations, and unreplicated animal experiments.

We can do better than this.

And by “we” I mean the world, not the United States. Our peculiar strain of anti-government and anti-science politics makes it hard for the US to play a leadership role in rebooting practical medical research. Other nations are in a better place to lead. Canada, the UK, Germany and the Nordics come to mind, but perhaps also Brazil, Israel, and India.

Canada, the world needs you.