Why the obesity epidemic?

There is no need to start with statistics showing obesity is spreading globally like wildfire. Everyone knows it for sure. What we have failed to understand is why this is happening only today. People have mainly blamed various components of food and various eating habits along with lack of exercise. The energy intake-expenditure based thinking appears to ignore that our body has many evolved mechanisms of food intake regulation. Why these mechanisms fail to work is the real question. Why our body and brain fails to tell us when to stop eating is what a hypothesis should address, not how much we ‘decide’ to eat at a conscious level. Some recent (https://www.annualreviews.org/doi/citedby/10.1146/annurev-psych-122216-011643) neurobiological work shows that the subconscious regulation mechanisms are stronger than the conscious factors such as your desire, taste, thinking, self-control and the like.

While theories proliferate, obesity proliferates at a higher rate. The reason why we have failed to understand obesity is that obesity researchers are cut off completely from behavioural ecology. Human biology viewed without behavioural evolution makes little sense. Only in the light of evolution, obesity will make sense.

It’s not that evolutionary thinking has not gone into the biology of obesity. The problem is that these biologists have never experienced themselves a life in wilderness and therefore fail to appreciate the conditions in which human (or mammalian in the broader sense) physiology evolved. A hypothesis called ‘thrifty gene’ originated in the 1960s which was a quasi-evolutionary hypothesis. ‘Quasi’ because it was based on arm chair evolution. Not on a thorough understanding of life in the wilderness. In the following decades many variations and versions of the thrift family of hypotheses followed but all of them suffered the same fate. Any thrift family hypothesis assumes that human ancestors underwent many cycles of food abundance and scarcity. Therefore we evolved for overeating in days of abundance and build fat which we burn during periods of food scarcity; something that sounds very logical on the face of it but does not stand a serious scrutiny and hard evidence. There are many problems with the concept of thrifty origins of human obesity. Some of the serious objections are that (i) human physiology does not match that of other species that clearly have evolved mechanisms to cope with feast and famine conditions. (ii) Human obesity is marked by impaired fat utilization mechanisms, not by faster fat building. This directly contradicts the expectation of feast and famine adaptation. (iii) Models of overeating during food abundance do not account for the short term cost of over-foraging and overeating, it also does not account for the thermodynamic efficiency of energy storage and reutilization, which is typically very low. When these factors are taken into account the thrift hypothesis and all its variations fail badly even in a mathematical model. If something works in a mathematical model, it may or may not be there in the real world, but if something doesn’t work in a mathematical model, you can be sure it does not work in reality. (iv) Last but not the least; no clear mechanism of thrift has emerged in spite of decades of search. There were many false alarms which did not sustain.

One who has lived in a wilderness environment and experienced the life of hunter-gatherers can have a much deeper vision. Feeding is necessarily related to foraging and foraging is prone to risks. So feeding is to be optimized against the risk of foraging. All mechanisms of human food intake regulation are optimized for an interaction between nutritional benefits and foraging risk.

(a)    There is an optimum energy intake. If there is already some stored energy, the optimum shifts to the left. (b) But if there is risk associated with foraging a trade-off between nutritional optimum and risk minimization exists. This optimum is always to the left of the physiological optimum. Greater the foraging risk (R1 to R3), more leftward shift of the optimum. Also with reserve food, the entire curve shifts to the left along with the optimum. So you eat less and as a result body weight remains stable. So in species that face large foraging risk, the physiological optimum is almost never reached. So food intake regulation mechanisms for the physiological optimum may not evolve at all. Only the risk related regulation works.

I will try to explain here with a little bit of technicality of the model, not mathematically but graphically. A detailed model is published here (. See this figure. There is an optimum food intake for the best physiological state as in the figure ‘a’.  If foraging associated risk wasn’t there any time in our ancestry, we would have evolved mechanisms to ensure the physiological optimum. But if foraging is associated with risk, we have to face a trade-off between what is physiologically good and what is ecologically safe. The new trade-off optimum always lies to the left of the physiological optimum (see B part of the figure). So species that face a foraging related risk should evolve mechanisms for achieving this trade off. Not only that, they might fail to evolve mechanisms to ensure the physiological optimum, since the foraging optimization mechanisms always works before the physiological optimization could work. Something that is never used, may not evolve or degenerate even if it was there earlier.

The interesting thing is that now we know molecular mechanisms by which this foraging optimum is achieved. Leptin is a protein secreted by the fat tissue of our body. More the fat, more is leptin secretion. Leptin gives a signal to suppress hunger. But the action of leptin is crucially dependent on another peptide produced in the brain called CART. CART is expressed in response to risk perception. Whether the risk is because of predator or because of extreme cold or heat doesn’t matter. All potential foraging risks trigger CART expression. And CART and leptin together suppress the hunger sensation. The story does not end there. CART also suppresses risk taking behaviour. CART expression is dependent on leptin levels, such that when leptin in the brain in low, CART expression is reduced. This ensures that when you don’t have stored fat, you are ready to take greater foraging risks. On the other hand when you have enough fat, you will overexpress CART so that you don’t go out for foraging and expose yourself to risk. This is a perfect mechanism to optimize foraging. We modelled the ecological optimum and it turns out that the steady state body weight will be proportional to the inverse square root of risk. We also modelled the leptin CART interaction and it turns out again that body weight will be a function of the inverse square root of risk. So by both proximate and ultimate modelling the result is the same. This is one of the rare examples in evolutionary modelling where the proximate and ultimate converges so nicely.

So we are getting fat not because of any particular food constituent or because we don’t burn enough fat, it is because we have detached feeding from foraging and from risk. Since we hardly face any risk including exposure to extreme heat or cold, our brain does not make sufficient CART so that our leptin levels are ineffective in telling us when to eat and when not. Further the model also explains why some have greater tendency to accumulate fat than others, why we have impaired fat burning and so on. I will not explain these details here. This model explains many known patterns in the obesity epidemic than any previous models have. What is the take home message? The key to control fat is not in what type of food you eat. It is there in your brain peptide levels that are regulated by your behavioural environment. Well, we are not going to go back to stone age life, are we? But we can still bring back the missing components of our hunter gatherer life. Sports activities do precisely the same. Any kind of sports mimics our hunter fighter ancestry. We hit, kick, aim, chase, attack, defend, team up… precisely the same acts. Studies on the brain physiology of sports are limited, but whatever we know indicates that these activities use the same neuroendocrine pathways and thereby are likely to normalize our brain chemistry back to our stone-age physiology. The pro-health effects of sports are not because they burn calories, they are because they bring back the missing behaviours. So engage in active sports and expose the body to the ambient heat and cold as much as it can tolerate. If this normalizes the evolved regulation pathways, you can certainly stop worrying about calories in and eat whatever you like, just listen to the body’s signals as to when and how much.

The innocent clinical diabetologist

I recently saw an interesting video somewhere on social media and shared it. Here is the link. See it to get amazed and amused. But beware. It’s not a comedy show. It has very deep real life relevance. It’s a demonstration of how you can make a cooked up theory explain everything! No counterargument stands.

What immediately came to my mind was that the state of the theory of type 2 diabetes is almost the same. I could imagine the cute little girl in the video to be an innocent clinical diabetologist (ICD) talking to an old tired and frustrated researcher (TiFR). The dialogue would go somewhat like this. (But see the video first in order to understand the dialogue.) https://www.facebook.com/milind.watve.5/videos/10217641702652704/?t=0

TiFR: And this is my lab

ICD: What do you do?

TiFR: I am a diabetes researcher. We address unanswered questions, we try to seek answers and ultimately help patients.

ICD: Unanswered questions? In diabetes? Like what? And what’s the use?

TiFR: For example, how can we prevent the diabetic complications.

ICD: Well we do that by reducing blood sugar. Simple enough!!

TiFR: But that doesn’t work, in clinical trials the result of meticulously regulated sugar is hardly better than the moderately regulated controls. Take the example of ADVANCE trial, in the control group, the rate of developing complications was 20%, in the treated it was 18.1 %, so only 1.9% difference made by the treatment?

ICD: Oh, you don’t know how to use statistics. It is 1.9% of 20 %. So it is about 10 % difference. And 10% lower rate in only 6 years so in the 60 years of lifespan there would be 100% difference.

TiFR: Oh I didn’t know you could calculate that way. But look at the bad effects of treatment. The treatment increased the chance of going in a hypoglycaemic shock by 170% by your calculation. See the UKPDS results.

ICD: You are completely dumb in statistics. Look at the actual frequencies. In the control group the chance is 0.7 %, and in insulin treated it is 1.8%. So it is only a 1.1% difference. 1.8 may be 270% of 0.7. But you don’t look at that. You look at only the absolute values.  

TiFR: This is strange. For the benefit of treatment you take relative difference, for its bad effects, you take absolute difference.

ICD: That’s how researchers should behave. Don’t use statistics indiscriminately. Use the right calculation at the right time. See how the UKPDS groups reports statistics differently to report different outcomes.

TiFR: Oh, so reducing sugar is the right treatment you mean.

ICD: It is obvious. Diabetes is defined by increased sugar, so when sugar is reduced back to normal, it is under control by definition. Why should other things matter?

TiFR: Then why is mortality in the meticulously sugar controlled group higher than the loosely controlled group? The ACCORD trial was stopped abruptly in three and half years because mortality in treated group increased alarmingly.

ICD: So what is a reliable trial? We believe in trials that were conducted over long time. They show 10-12 % benefit of treatment. Why should we believe in a trial that was aborted in a short time?

TiFR: But the 10-12 % difference could only be placebo. Just the feeling that I have my sugar levels normal can make some difference in health. Why can’t we have another placebo control in which patients are only told that their sugars are normal after treatment? Whatever they may actually be. If they also show 10-12% improvement, it could just be a placebo effect.  

ICD: No that will be unethical. Patients in clinical trials have the right to know.

TiFR: But if you don’t have this placebo, how would we know that the benefit observed is because of reduced sugar, not just a feel good effect?

ICD: May be very meticulous sugar control doesn’t make additional difference. But moderate sugar control would certainly be better than no treatment.

TiFR: But in any of these trials there is no control group with no treatment.

ICD: That’s because It would be unethical to leave a group without treatment.

TiFR: But when you don’t know whether the treatment works or not, how can you say not giving the treatment is not ethical?

ICD: But we know regulating sugar IS effective as a treatment.

 TiFR: Who told you that?

ICD: Our textbooks. We studied that 25 years ago. It’s old knowledge. Time tested !!

TiFR: So you haven’t updated your knowledge in 25 years.

ICD: How can you say that? Pharma companies keep on sending us latest literature. They hold meetings and conferences. So we are always up to date in our knowledge.

TiFR: Ok, so what is the latest view on why blood sugar goes up?

ICD: Well that hasn’t changed. It is insulin resistance and relative insulin deficiency. Obesity leads to insulin resistance. For some time insulin levels increase to compensate insulin resistance. But ultimately they fail and then blood sugar goes up.

TiFR: What is compensation you said?

ICD: The insulin producing beta cells make more insulin to compensate insulin resistance.

TiFR: Wonderful, but how do beta cells know that there is insulin resistance?

ICD: By glucose itself. When there is insulin resistance, glucose is not disposed rapidly. So glucose levels go up. And everybody knows that high glucose stimulates more insulin production. The excess insulin pushes back the glucose to normal so that you have a high-insulin-normal-glucose state prior to diabetes.

TiFR: Aha, I see. But after glucose is back to normal, why should insulin remain high?

ICD: Well, just like that. It might just linger on.

TiFR: But insulin has a short half-life, only 5-6 minutes.

ICD: Oh, all those details are not relevant. We know that there is a high-insulin-normal-sugar phase before diabetes sets in. When the beta cells get exhausted and are unable to produce compensatory insulin, sugar starts rising.

TiFR: Why should beta cells get exhausted?

ICD: because they have to keep on producing more insulin.

TiFR: But that’s not the case. In a high fasting-insulin condition, the number of beta cells increases. The rate of insulin production per cell doesn’t. They are not working more so why should they get exhausted?

ICD: See the cause is not important. Ultimately they make less insulin, that is for sure.

TiFR: Ok, going back to insulin resistance. How do you know that there is insulin resistance and how much?

ICD: When insulin is unable to control sugar, it is insulin resistance. We measure insulin resistance by the inability of insulin to regulate sugar.

TiFR: Amazing logic. Normal or higher amount of insulin fails to regulate glucose because of insulin resistance. And insulin resistance is measured as insulin’s failure to regulate glucose. Let me put the two statements together. It means that insulin is unable to regulate glucose because insulin is unable to regulate glucose. What an infallible logic!!

ICD: Yes. That is the strength of the theory. You will never be able to prove this theory wrong by any experiment. Whenever blood sugar is not controlled by insulin, it will be called insulin resistance. So there is no scope for any other cause for a change in sugar level. This theory just does not allow any other theory to stand. I wish all theories were like this. We won’t have to waste so much money on research then!!

TiFR: But people have done experiments. They knocked out insulin receptors on muscle cells and liver cells but in neither case fasting blood sugar was affected.

ICD: Simple my boy. It means that knocking out insulin receptor does not induce insulin resistance. Insulin may be still acting by some other means. We call it insulin resistance only when we observe insulin resistance.

TiFR: But experimentally increasing or decreasing steady state insulin also does not affect fasting glucose in experiments.

ICD: That is because some other compensation mechanism must be acting.

TiFR: Then why these compensation mechanisms fail in diabetes?

ICD: That is because the insulin resistance is stronger in diabetes than what you could induce experimentally.

TiFR: How do you know insulin resistance is stronger?

ICD: Because the effect is observed. So it must be strong enough to overcome any compensation mechanisms.

TiFR: Ok, but where does all of it begin?

ICD: In eating bad diet. Bad diet induced obesity that leads to insulin resistance.

TiFR: But what diet is a bad diet?

ICD: That depends upon which time you lived. Fat was bad for the past thirty years. For the next thirty years sugars will be bad.

TiFR: After that?

ICD: May be proteins, but can’t say now. You will have to wait till then. In any case avoid eating whatever is considered bad at that time.

TiFR: Ok. On a different line. Over the last decade, so many researchers are talking about the role of brain in regulating hunger, obesity, glucose regulation etc. So many experiments also show that.

ICD: We have a brain so it ought to have some role. But nothing useful comes out of that. The pharmacology of the brain is too tough. It is a nightmare to pursue drug discovery for a brain target. Liver, pancreas, stomach are easier targets. So we target all our treatments on these organs. Brain is useless.

TiFR: Yes, I can see that very clearly!!! Brain is useless!!!

TiFR: So let me have a quick recap. The insulin resistance theory of diabetes is perfect and can never be proved wrong. According to this theory, controlling sugar is the only treatment target and will remain so for ever. Whether it reduces complications and mortality rates or not is not relevant.

ICD: You got everything right.

TiFR: Thanks for explaining me everything.

ICD: you are welcome but you didn’t tell me what do you do exactly?

TiFR: Well, now I will answer more carefully. We do PhD, post doc, generate lots of data, do lots of analysis, publish lots of papers in high rank journals. That is all about research. I learnt something important today. One thing that we researchers should never do is to ask questions. That will spoil research. Thanks for enlightening me about the real world!!

Ethical deterioration enabled by procedural ethics

It is over 6 months that I quit the Institute and about 4 months that I returned the fellowships of both the National Academies that I was a fellow of, namely IASc and INSA. While INSA has formally accepted my resignation, IASc hasn’t replied as yet. I left mainstream science for ethical issues and therefore I have been postponing writing a blog about ethics in science organizations. Since I myself have gone through ethical conflicts, I shouldn’t have passed judgments myself, at least in the heat of the moment.

I am not a person who takes decisions at the spur of the moment to repent later. Still I wanted to give sufficient time for cooling down the heat, if any, in my mind. Now I want to pen down my experiences, observations, anecdotes and interpretations about ethical issues in institutionalized science, and I want to do this in an analytical and critical way, not for defending my own case, or accusing anyone.

When I decided to resign on ethical grounds someone asked me why I didn’t take these issues to any of the ethics committees within the institute. This made me wonder. Was it really possible? Are there any ethics committees with the mandate to cover issues like the ones I was struggling with?

Does science need an ethical foundation and do science organizations need procedures and committees to handle ethics issues?

Hardly anyone will say no. But how to ensure ethical practices in institutionalized science is the real question. All institutes today have their own ethics committees. There are separate committees for animal ethics, human ethics, plagiarism check, gender discrimination and so on. Does that ensure ethical practices in the institute? The answer is tough. There are pros and cons of the ethics committees. Let us assume that they all work with the most honest efforts to fulfil the mandate of the committee. No doubt there are some malpractices somewhere sometime, but I am going to ignore them. The committees do talk about ethical issues in the area of concern for which the committee is constituted. They often make suggestions, warn someone or occasionally recommend action against someone. I am assuming that all this is done fairly well.

Even when all committees function well, at least five different types of problems are still left. One is that all ethical issues are not really covered by these committees. There are many that do not come under the mandate of any of them. The second is that the committees typically make dichotomous judgments, because of which the multi-dimensional and graded concept of ethics is painted in black and white. Realities are not in black and white. The third is that there can be conflicts between the procedures and contexts. Ethical committees follow certain procedures and norms which are designed for certain types of work. A procedure that is logical in one context may completely defeat the purpose in another. The forth and the most important is that it gives a false sense of satisfaction to the institute authorities that we are following all the ethics procedures and therefore we are ethical. By formalizing institutional procedures for ethics everybody is relieved from seriously thinking about ethics. Ethics can be completely driven out from anybody’s conscience for ever. Ethics is now a procedural issue, no more a conscience issue. The last and not the least is whether having ethical clearance for publishable research is sufficient for a researcher. Today most journals need a declaration that your experimental design and procedures were examined and approved by an appropriate ethical committee. So you need to go through the procedures in order to get published. What about the other things that you do in a science institute but not publish in the form of research papers, do they need to be ethical as well?

I have worked on some of such committees. They work like and are also perceived like rituals. What they discuss are some subtle technical issues and there is hardly any serious “ethics” discussed here. But because a ritual is completed the burden of ethics is removed from one’s shoulders and one doesn’t have to worry about it anymore. The institutes can boast that they have so many ethical committees so they are certified ethical.

I will illustrate all these problems with examples for clarity. Many examples involve more than one of the five, so I need not give five different examples for the five problems. Also my examples come from what I have myself seen and observed. Since I know these cases thoroughly I will prefer to use them as examples. But I just want to use them as examples. This is not intended to accuse anyone personally because I sincerely do not have any complaint against anyone. I am an analyst and critic of the system of science organization and institutionalization. Since I am no more a part of the mainstream science organizations, I have nothing to gain or lose by talking about these cases. In fact this is the true reason why I wanted to quite all organizational entities. This gives me a third party stand now so that I can attempt a more impartial analysis. Whatever happened is history now so justifying my stands, or begging sympathy of anyone by pretending that I suffered injustice is all irrelevant now. Also I don’t intend to project anyone as “guilty”. Instead we all need to analyse and learn from such issues so that tomorrow’s institutions are better than today’s.   

The institute campus had many environmental issues. There was illegal and unnecessary cutting down of over 500 trees and the waste water was being released without treatment. The institute gardeners were made to use this stinking water for gardening. When I was the chairman of the landscape committee, I raised these issues along with a few others. But instead of addressing these issues I was removed from the committee by cooking up false charges against me. At this point I resigned from the institute. The waste treatment plant was made functional immediately after my resignation. I had myself started compensatory tree plantation and planted 1000 saplings while I was there, mainly native endangered species. Now they have planted many more on the same principles. So my resignation had a positive effect and I am happy to have served the institute. This is fine, no serious ethics issues. Academic section of the institute was not involved.

More serious ethical issues cropped up later. The director denied that there was any tree felling at all. By this time the sites of tree felling were cleared and there was no obvious evidence left on the ground. So I got high resolution satellite images to show how many trees were seen in those images earlier which were not there anymore. I mailed the image analysis report to the institute faculty from ecology and earth sciences departments asking them to critically examine my analysis, point out whether I was wrong anywhere in the analysis. There was no response from any of them and in a reply to a separate RTI request the institute continued to deny tree felling. This is the most serious issue for SCIENCE. It is not an administrative issue any more. This is an academic issue. Everyone will agree that ignoring or denying evidence is “bad science”. You may criticise the method of collecting evidence, or suggest alternative interpretations of it. This is how scientific arguments are made. But deliberately ignoring inconvenient evidence is certainly a bad practice in science. Directors of science institutes are scientists themselves and science starts with honest reporting of data. If the director himself propagates bad science by denying evidence, how can the institute claim to do research? How can it be an educational institute that has a mandate to raise scientists for the next generation. This is the real ethical issue, not a general ethics issue but specifically a “scientific ethics” issue. No doubt the director acted unethically. Whether other faculty that had actually witnessed the tree felling on campus but did not react to it, the ones to whom I mailed my image analysis report and who did not respond to it are ethical or not is an open question. I leave it to the readers’ judgment.

What we see in this example is that such ethical issues are not the mandate of any of the ethics committees. Since this is not related either to published research or to the teaching syllabus, this will not be considered as an issue in scientific ethics at all. We are nurtured to believe that only what is published as papers is research and what is asked in the examinations is science education. So this issue is neither a part of research, nor of teaching so nobody in a research and education institute carries any guilt of being unethical. Since no ethics committee has labelled it as unethical, it cannot be unethical!! Everyone is happy.

Here is another anecdote. A student of mine wanted to do some human behavioural experiment. We had a human ethics committee just established by then. So we put a proposal to the committee. The committee had members with prolonged experience in examining research in clinical medicine. Informed consent is a natural and mandatory part of such work. In this case we said that letting the subjects know the purpose of the test is bound to change their behavioural responses, so we cannot reveal the purpose before the test. We are ready to reveal it later. But the committee did not agree. They insisted that subjects need to be informed everything before participating in the study. This defeated the purpose of a behavioural experiment. We could not do the experiment ultimately. This illustrates how following the same norms and procedures in all contexts can undermine science. 

Another issue arose following my resignation. I was the principal investigator for certain on-going projects. The question was: after I left the institute, do the projects get transferred along with me to my new organization or they remain with the institute which appoints a new PI on the project? This is not a new question. So many researchers change the institute/university. The answer should be context dependent. One the one hand there are projects such as the Chandrayaan mission of ISRO. This is necessarily an institutional effort in which individual scientists and engineers may come and go. This is certainly institute centred. On the other hand there are projects whose central idea is conceived by individuals, they get funding for the concept and the institute only hosts the project. In such cases the project is the PIs intellectual property. if the PI left the institute, the institute may not even have anyone else capable of handling the concept efficiently. The decision whether the project grant is transferred with the PI or the institute finds another PI should be based on what will be better for the successful implementation of the project. Among the projects that I was handling, some were of type 1 and others were of type 2. So accordingly they could have appointed another PI for the type 1 components and transferred the grant for the type 2 projects. But when institutes follow rules, thinking is typically not required. Without any distinction between the two types of contexts they decided that the funding will remain with the institute and they would appoint another PI. Bureaucracy is satisfied when one person replaces another. Thinking, capabilities, background, personal research interests are irrelevant. There is a plagiarism issue here when the institute appoints another PI for a project that is 80% completed. But the existing institutional procedures for plagiarism check use a soft-ware to check whether your manuscript resembles any of the previously published papers. If the funding based on one’s concept is used by another person, the plagiarism check procedures do not cover this so it is not considered plagiarism. Procedures are always dumb and when it comes to following rules and procedures the most brilliant scientists become the dumbest brains. If science is to be done by following procedures it will invariably end up being dumb.

Whether I was right or wrong in these issues is not the question that I myself should judge. I am actually saying that the right-wrong dichotomy is wrong. Ethics is a complex concept and making black and white judgments degrades the entire concept. What matters more is transparency. One should make the entire real story transparent so that any interested person is free to access the reality and judge oneself. Ethics committees should make everything transparent and leave the decisions open whenever possible. Whenever there is real need to take dichotomous decision, they should not stop at the yes-no decision but make all facts and documents available to everyone.

The knee jerk reaction of administration to any new issue is to lay more procedures, write more rigid rules and constitute more committees. This makes life easy for the administrators. But for science institutions it is important to realize that rules and regulations are there to support science. Science is not there to follow administrative rules. Making context based decisions with complete transparency on the facts and reasons is a more difficult path to follow. Making and following rules is an easier path. But what will support better science should be more important than what is easy to follow.

What I write here is particularly important for the history of science. I may not be of any relevance in the history of science, but my stories are. They can be important resources to students of the history of science, philosophy of science, policy makers and implementers. Therefore I am making the entire set of documents related to my exit from mainstream science available on the links below. Follow the links to a compilation of all documents related to the issue. I don’t expect many people to be interested in the details, but a rare soul genuinely interested in the organization, structure and working of science institutions would certainly appreciate it as a small but important resource for the history of Science organizations in India.

Links to documents:

Resignation related

Returning INSA and IASc fellowships

Quitting MGB formally, (Informally I will keep on working for the project, since I know that no one else will be able to document and articulate the most important outcomes of the project)

The tree felling case

The gardeners’ case

Science as an emotional endeavour

The interaction between the Chairman of ISRO and the Prime Minister of India on losing contact with the lunar lander Vikram, is witnessed by the entire country. Social media did a very positive job this time. I am moved as much as every Indian. This 50 second clip demonstrates something very important. That science is a highly emotional endeavour. The perception that science and technology is a highly intellectual but emotionally ‘dry’ subject is not true. My own experience is also that of intimate attachment to two things in science. One is the attachment with your own concepts, your own thinking, the beauty of scientific logic, the beauty of its way of thinking, the beauty of the mathematics involved. The other is the attachment with co-workers, in my case mostly students at all levels.

The thought that there is beauty in science is not new. Paul Dirac said “I like to play about with equations, just looking for beautiful mathematical relations which may be don’t have any physical meaning at all. Sometimes they do.” So Dirac says beauty was his first obsession with equations. Their usefulness was secondary.

I had a rather uncommon, if not unique, experience of composing music and poetry along with doing science. I can assure you that the two are emotionally the same. I see poetry in scientific concepts and mathematics in poetry. But for some reason people perceive music and poetry as predominantly emotional endeavours and science as a dry intellectual one. Having engaged in both, I know this differentiation just does not exist. Both are equally emotional and equally analytical. A number of mental processes involved in both are quite the same. But we perceive them differently.

I think the perceived difference is mainly because of packaging. Music, poetry and other arts are packaged in an emotionally appealing cover. Science and technology is packaged differently and there is a reason to it.

Emotions play a lead role in the way we perceive new concepts, interpret surprising results, celebrate the so called “success” or get disappointed by the so called “failures”. The reason I put these words within quotes is that they are completely social constructs. There is no success or failure in the intellectual components of science. A so called “failed” experiment also provides new data and uncovers some principles, so it’s a gain for science in any way. Things take the form of success and failures when science becomes business. When it is not a business, science does not know of any failures. The predominant emotions associated with science are curiosity, excitement, passion, awe, attachment, appreciation of beauty, realization, satisfaction and joy. Disappointment or frustration has no place in science.

But this is not the way science institutions, publications and science funding works. In order to get your science funded, you need to pretend that you have been always successful in the past and in the proposed project you have high chances of “succeeding”, whatever it means. In most cases it means nothing. Funding attempts work on the same principles and mind sets as advertising and marketing. Because funding systems work on this unscientific principle, all scientists have to pretend that they are successful. The tragedy of a scientist’s emotional life begins here. Honesty is the foundation of science, but it is extremely difficult to be honest and still get your work funded. The way experiments are perceived, done and results obtained is not always very logical. Often you get something serendipitously. Sometimes you get some result so unexpectedly that you need to change your entire line of thinking. Most often researchers write it as if they always expected this result. Unless you pretend that you derived everything logically, your paper is most unlikely to get published. This hypocrisy is what makes a scientist’s emotional life miserable. Institutionalization, funding and publication are the three organizational elements of science which make the emotional life of a scientist pitiable. As a reaction to this we tend to disown our own emotions and pretend that we are logical intellectual machines. This further leads to more hypocrisy and more pretence in a positive feedback vicious cycle. But this is the reason why we keep on suppressing our emotions.

The reaction of the prime minister of India as well as the common man to the so called failure of Chandrayaan 2 is a glorious exception to all this. We did not end up in a blame game. We did not say “you” have failed. We all said we are with you in all successes and failures. I only hope that what the politicians and laymen of the country understood, is also understood by our agencies that host and fund other sectors of science. Defence and space science has always enjoyed this support. Other branches haven’t. If, in a country, the science funding agencies understand the importance of honesty in science pretty well, nobody can stop the progress of science there. Let the Modi-Sivan exceptional interaction become the rule and the country will progress like anything.

What can bring in a revolution in biomedical science

Kuhnian versus Galisonian revolution: Thomas Kuhn published a book in 1962 “The structure of scientific revolution” which became a landmark in the history and philosophy of science. Kuhn says that science does not progress in a continuous smooth curve. There are periodic quantum jumps in the form of paradigm shifts. Rest is “normal science” which expands at the same level without much vertical rise. A paradigm shift is very difficult in science. For multiple reasons people of science do not easily accept the failure of old theories, although there may be quite convincing falsifying evidence. They do not accept alternative theories readily even if they are more logical and evidence based than the earlier ones. Kuhn, of course, illustrates this marvellously with a number of examples.  Perhaps the best examples of paradigm shifts in the history of science are the shift from geocentric to heliocentric view, theory of relativity and beginning of quantum mechanics.

Then in 1997 came another book, “Image and logic” by Peter Galison, which has a different argument, strengthened by equally convincing examples. In the Galisonian view scientific revolutions are triggers by new tools and technologies which open up new horizons to explore.

Many authors later wrote comparative accounts of the two types of revolutions, a notable name being Freeman Dyson. Interestingly while people talk about examples of Kuhnian revolution, they talk mostly about examples in physics. Whenever they talk about revolutions in biology or even chemistry, they mostly argue that these are Galisonian revolutions, not Kuhnian. There have been debatable arguments that even Darwin’s concept of evolution by natural selection was not a truly Kuhnian revolution. While talking about Kuhnian revolution hardly anyone talks about examples in biology, as if biology was not a science, or biology did not have conceptual  revolutions. A layman’s or even an undergraduate student’s perception of biology is generally that biology has a lot of facts but hardly any laws, theorems and the like. It is data-intensive, not concept-intensive, so one hardly expects conceptual revolutions.  Ashutosh Joglekar in a Scientific American article of 2012 argues that physics is a ‘simple’ science and therefore is more theory driven. Chemistry and Biology are more complex and therefore are more empirical, more information driven.  Therefore major scientific achievements in chemistry or mainly biology are Galisonian, not Kuhnian.

Is this really a difference due to complexity? Is physics really so simple? And is biology ‘conceptually’ that more complex, while in its information content it might be? I think more than the nature of the subject it is the culture of the handlers of the subject that really matters. In my experience the culture of physicists and that of biologists are ploes apart. If there is an experimental result which is anomalous to the prevalent theory, physicists appear to debate it. They may or may not reach any agreement, but they certainly engage in fierce debates. As Thomas Kuhn describes, the anomalous findings keep on piling up so that the theory goes on becoming more and more vulnerable, ultimately paving way to a paradigm shift. Building up a burden of anomalies is an essential pre-requisite for a paradigm shift. For building up that burden, it is necessary that the anomalies are recognized by people in the field.

In my experience, the behaviour of biomedicine researchers contrasts that of physicists. They do not debate anomalous results. They simply ignore them. So the burden of anomalies never builds up, the ‘crisis’ situation that precedes a paradigm shift in a Kuhnian process is never felt by researchers in the field. Biologists isolate the anomalies from the main theory and push them under the carpet. Since there is no burden, even wrong theories do not collapse. There are two possible outcomes of this. Either (i) a true paradigm shift does not happen at all in biomedicine even if it is overdue or (ii) it happens eventually without any debate, arguments or fights. Therefore it does not have the typical Kuhnian characters.

Whether the preceding paradigm and the new paradigm are incommensurable (Kuhn’s favourite term meaning that the concepts of the new paradigm just cannot be explained on the platform of the old one) is, in my view, a matter of culture and behaviour of people in the field and not that of science itself. The culture of biologists is that they just don’t worry about logical contradictions, mutual compatibility or commensurability of two theories. They only go on adding more and more data. Inadvertently sometimes the concept changes so dramatically that the older concept is turned completely upside down. But nobody realizes or explicitly says that this has happened. This is one possible outcome. The other is that anything that is not compatible with the prevalent theory is completely ignored and talking about them is a taboo. In Kuhn’s days peer reviews were not followed by all journals. Today, experiments that contradict prevalent theory are most likely to be filtered out in the peer review process itself, but even when they happen to get published, nobody including the authors say that they contradict the theory, that they are anomalous, that they need to be debated or that the theory needs to be re-examined. The authors have to do this otherwise they are unable to publish. It is easier to publish anomalous data if you don’t state that it is anomalous. Me too have experience of publishing 3-4 papers that obviously involved ‘group selection’. In main stream evolutionary biology ‘group selection’ was a taboo for a long time. But by avoiding the words  ‘group selection’, the same results became publishable.

I will give examples of both types of outcomes of the biomedicine culture. Prior to the elucidation of DNA structure, the nucleus of a cell and the chromosomes in particular were thought to be the decision makers. They were believed to regulate and coordinate all activities in the cell. After a few decades, people started talking about ‘gene regulation’. This was a complete somersault. The regulator became the regulated, but hardly anyone seems to have realized that the paradigm is completely turned upside down. Such paradigm shifts in biology have been silent because biologists avoid debating on any apparent or even true contradictions.

Examples of the other extreme are even more dramatic. Some of the theories in biology or medicine are simply illogical or mathematically incompatible. For example, in a prediabetic state, they say the body becomes insulin resistant, and then in order to compensate insulin resistance, the body produces more insulin. Exactly how does the compensatory insulin response happen? The textbooks say that when insulin action is subnormal, glucose levels increase. Glucose stimulates more insulin production, thereby insulin levels are raised. The higher levels of insulin bring back glucose to normal and you get a hyperinsulinemic normoglycemic (i.e. high insulin but normal glucose) state. A simple unanswered question is that after bringing back glucose to normal, how does insulin remain high? Insulin has a short half-life of 5 minutes. So when glucose is back to normal, insulin should be back to normal quite quickly. But in a prediabetic state we typically get normal fasting glucose but 5 to 10 fold higher fasting insulin. Such a condition can never be obtained in a mathematical model based on the textbook assumptions. The interesting thing is that in biomedicine, nobody has pointed out this paradox, there is no debate, no discussion, it is not considered an anomaly that needs to be addressed. Even when the flaw is obvious, it is simply ignored.

Several dozen such anomalies have actually accumulated in the field of type 2 diabetes. But nobody talks about them. Treatment to bring back sugar levels to normal has failed to reduce diabetic complications in all large scale clinical trials. There is absolutely no evidence that there is any health benefit of bringing the sugar back to normal. But entire diabetes treatment revolves around sugar normalization and this important contradiction remains unrecognized. Almost everything that was believed to happen in type 2 diabetes has been challenged and even falsified by reproducible experiments. There is no sound explanation for these anomalies in the current paradigm. The pre-paradigm-shift ‘crisis’ state described by Kuhn actually exists on ground. Still nobody is upset. No research focuses on addressing the anomalies. Instead people are busy using new tools to generate new data. Now we have genomic, epigenomic, proteomic, metabolomic profiles of diabetics and controls. So much data are generated that nobody knows what to do with it. Is this a revolution? All signs of Galisonian processes are there, but revolution is not on the horizon. Nobody even feels that the classical theory stands challenged.

In a typical Galisonian process the rate at which data grow is not at all matched by the rate at which insights grow. Genomic information is growing exponentially today. Initially people hoped that they will get major insights into complex diseases after having genomic information on human populations. But hardly any insights were obtained about the origins of disorders like diabetes. Then they argued that if it is not genetic, it must be epigenetic. Again epigenetics of obesity and diabetes is adding to the data pool exponentially. Any major insights? No luck.  Any chance of appropriately addressing the anomalies? Zero. But flashy publications? Yes. Promotions, awards, funds? Almost certain. Is this the revolution?

This is the culture of researchers in biomedicine. Addressing an anomaly is simply not in the culture. A paper exposing anomalies and raising difficult questions faces hard times getting published. But a paper giving lots of new data using latest tools with zero insightful impact will get readily published in high “impact” journals. Everyone is happy generating new data using new tools, while patients keep on spending money on useless medicines and still keep suffering from complications. So Galisonian revolution is not sufficient for biomedicine. It needs to be realized that Kuhnian ones are as essential in biology as in physics.

Kuhn correctly points out that a paradigm shift would happen only if a better alternative paradigm is available. Evidence falsifying the preceding paradigm is not enough. But there is a hen and egg problem here. Unless the preceding paradigm is perceived as inappropriate, they won’t feel the need for an alternative. Research based on any alternative way of thinking will be neither funded nor published. Even an existing sound alternative will remain ignored if the need for a change is not felt. So although there is plenty of evidence for a ‘crisis’ state and the need for a paradigm shift in type 2 diabetes research, as long as the cultural practice of playing ostrich does not change, the actual shift will never happen.

The biomedicine researcher is an anomaly for the Kuhn’s paradigm itself.

आहार ते लट्ठपणा: मार्गे – मेंदू

सगळ्या जगात आज लट्ठपणाची मोठी लाट आली आहे आणि आरोग्य क्षेत्रात प्रत्येकजण त्याविषयी बोलतोय. त्यातल्यात्यात भारतात तिचा प्रभाव मर्यादित आहे. तरी शहरी सुखवस्तू समाजात खूपजण लट्ठपणाची वाटचाल करताना दिसताहेत. मधुमेहासारख्या आजाराला लट्ठपणाच जबाबदार असल्याचं इतक्या छातीठोकपणे सांगितलं जातं की बारीक असूनही मधुमेही असलेल्यांचा सुद्धा त्यावर विश्वास बसतो. त्यामुळे डाएटिंगची मोठीच चलती आहे. पण आहारातला बदल नक्की काय आणि कसा करायचा याच्याबद्दल खूपच उलट सुलट सल्ले दिले जाताहेत. सामान्य माणसाला नायक आणि खलनायक असलेल्या गोष्टी ऐकायला आवडतात. त्यामुळे आहारातल्या एखाद्या घटकाला खलनायक ठरविणा-या गोष्टी पटकन लोकप्रिय होतात. त्यामुळे गोष्ट तीच ठेवून खलनायकाचं नाव बदलून परत परत नाटकं केली तर ती सगळीच हाउसफुल चालतात.

सुमारे तीस वर्षं आहारातील स्निग्ध पदार्थांना खलनायक करून प्रयोग रंगत गेले. प्रयोगाला लोकप्रियता मिळाली पण समाजाच्या आरोग्यावर काही अनुकूल परिणाम झाल्याचं दिसलं नाही. उलट लट्ठपणाचं आणि मधुमेहाचं प्रमाण वाढतच गेलं. अंड्यामधे कोलेस्टेरोल असतं म्हणून त्याची गणना खलनायकांमधे झाली पण आता त्याची खलनायकाची भूमिका काढून घेतली गेली आहे. आता स्निग्ध पदार्थ किंवा कोलेस्टेरोल असलेले पदार्थ मुळात वाईट नाहीत असं म्हटलं जातय. साखर हा सध्याचा लोकप्रिय खलनायक आहे. कदाचित पुढील तीस वर्षे तो गाजेल. नाटक चांगलं चालेल, आरोग्य आणखी बिघडेल. पण याखेरीज इतर अनेक छोटे मोठे खलनायक पण आहेत. कुणी म्हणतो तळलेले खाऊ नका, पांढरे खाऊ नका, आम्लधर्मी खाऊ नका, विदेशी गाईचं दूध पिऊ नका, फास्ट फूड खाऊ नका, प्रक्रिया केलेले खाऊ नका, मांसाहार करू नका, रेड मीट तर नकोच नको. 

पण आहारातील घटकांवर सगळा ठपका ठेऊन भागत नाही असंही अनेकांच्या लक्षात आलं आहे. मग सकाळची न्याहारी करू नका असा सल्ला देणारे तज्ज्ञ आहेत. न्याहारी कधीही चुकवू नका असं सांगणारेही तज्ज्ञच आहेत. दर दोन तासांनी थोडे थोडे खा म्हणणारे तज्ज्ञ आपल्या सल्यामुळे किती लोकांना फायदा झाला याची आकडेवारी देतात, आणि दिवसातून फक्त दोनदाच जेवा म्हणणारे तज्ज्ञही तितकीच डोळे दिपवणारी आकडेवारी देतात. जपान मधले सुमो पैलवान भारी वजनाला फार महत्व देतात. तो कुस्तीचा प्रकारच असा आहे की जेवढं वजन अधिक तेवढा कुस्तीतला वरचश्मा अधिक. त्यांचा वजन वाढविण्याचा जो मंत्र आहे तो आहे दिवसातून फक्त दोनदाच खायचं. भरपूर खायचं पण फक्त दोनदाच. यानी त्यांचं वजन हमखास वाढतं. याउलट दोनदा जेवून वजन कमी झाल्याची ग्वाही देणारेही खूप आहेत. त्यांचाही अनुभव काही खोटा म्हणता येत नाही. एकीकडे बरोब्बर परस्परविरोधी सल्ला देणारे लोक आपल्याला नेत्रदीपक यश मिळाल्याचे दावे करताहेत आणि दुसरीकडे एकच मंत्र वापरून परस्पर विरोधी परिणाम झाल्याची उदाहरणेही आहेत. याचं मर्म नक्की काय आहे?

याच महिन्यात प्रसिद्ध झालेला बल्गेरियामधला एक प्रयोग काही वेगळंच सुचवतो. व्हेलेंटिन पनायोतोव्ह नावाच्या संशोधकानी काय केलं, चौदा लट्ठ माणसांचे दोन गट केले. दोन्ही गटांना सारखाच आहार नेमून दिला पण त्यापैकी एका गटाला सांगितलं की तुम्हाला दिलेला आहार कमी उष्मांकवाला आहे त्यानी तुमचं वजन कमी होईल. दुस-या गटाला सांगितलं की तुम्हाला अगदी मोजून उष्मांक दिले आहेत. त्यानी तुमचं वजन आहे तेवढच राहील. प्रत्यक्षात आहार नेमून देण्याआधी प्रत्येकाचं रोजचं उर्जाज्वलन किती आहे याचं मोजमाप करून आहार ठरवला होता. तो असा होता की कुणाचंही वजन कमी होण्याची अपेक्षा नव्हती. हा प्रयोग आठ आठवडे चालला. दर दोन आठवड्यांनी प्रत्येकाचा आहार व्यायाम सांगितल्याप्रमाणे चालू आहे ना हे तपासून पहिलं जात होतं. शरीरावरचे परिणामही पाहिले जात होते. सगळ्या गोष्टी ठरल्याप्रमाणे काटेकोरपणे केल्या जातील याची शक्य तितकी काळजी घेतली जात होती.

आठ आठवडयानंतर असं झालेलं दिसलं की ज्यांना तुमचा आहार कमी ऊष्मांकाचा आहे असा विश्वास दिला गेला होता त्यांचं सरासरी वजन सुमारे दहा किलोंनी कमी झालं. दुस-या गटात काही दिसेलसा फरक पडला नाही. म्हणजे प्रत्यक्षात डाएटिंग करत नसून आपण डाएटिंग करत आहोत अशा नुसत्या विश्वासानी वजन कमी झालं. ते सुद्धा थोडं थोडकं नाही तर आठ आठवडयात दहा किलोंनी, म्हणजे आठवडयाला सरसरी सव्वा किलो. वैद्यकशास्त्राला ही गोष्ट नवीन नाही. आपल्यावर उपचार केले जाताहेत या भावनेनी सुद्धा माणसाला बरं वाटू लागतं. नुसतं मानसिक बरं वाटतं असं नाही तर त्याचे शारीरिक परिणामही दिसू लागतात. याला वैद्यकशास्त्रात प्लासेबो परिणाम असं म्हणतात. नुसत्या प्लासेबो परिणामामुळे दोन आठवड्यात दहा किलोनी वजन कमी होणं शक्य आहे असे हे प्रयोग दाखवतात. अशा प्रकारचे प्रयोग इतरत्र करून त्याची विश्वासार्हता तपासून पाहिली पाहिजे ही गोष्ट खरी. पण हा प्रयोग विश्वासार्ह मानला तर यातून आहार आणि लट्ठपणा यांच्या संबंधातली अनेक न सुटलेली कोडी सुटू शकतात. वेगवेगळ्या आणि परस्परविरुद्ध आहारतत्वांचा पुरस्कार करणा-या लोकांना तितकेच चांगले रिझल्ट मिळू शकतात ते या प्लासेबो परिणामामुळेच. पण प्रत्येक पठडीमधे ते काही जणांमधेच मिळतात काहींमधे नाही. याची कारणं त्या आहारतत्वांपेक्षा माणसांच्या मानसिकतेत असावीत असं दिसतं.

जगाच्या पाठीवर निरनिराळे समाज काय काय आणि कशा प्रकारे खात आले आहेत हे पाहिलं तर थक्क व्हायला होतं. त्यात वनस्पतिज अन्न क्वचितच पहायला मिळणारे एस्किमो आहेत. ज्यांच्या उर्जेचा ७० % पुरवठा प्राणिज चरबीमधूनच होतो असे मसाई समाज आहेत, ६०% तेलबियाच खाऊन जगणारे कलहारी कुंग तर ८५ % पिष्टमय पदार्थांवर जगणा-या काही अफ्रीकन जमाती आहेत. या कुणामधेही आत्ता आत्तापर्यंत म्हणजे शहरीकरणापर्यंत लट्ठपणा आणि मधुमेह सहसा सापडत नव्हते. याचा अर्थ माणूस मुळात खूप वेगवेगळ्या प्रकारचे आहार पचवायला समर्थ आहे. जगाच्या पाठीवर माणूस काय काय खात आला आहे त्या आहारातली विविधता पाहिली तर गेल्या पाच पन्नास वर्षात आपल्या आहारात झालेला बदल किस झाडकी पत्ती. म्हणजे आहाराचा प्रकार आणि लट्ठपणा यांचा फार घट्ट संबंध असावा असे पुरावे नाहीत. लट्ठपणा आणि मधुमेह यांचा संबंध तरी कुठे इतका बळकट आहे? लट्ठपणामुळेच मधुमेह होतो असा एकेकाळी समज होता. अजूनही बरेच लोक या समजातून बाहेर पडलेले नाहीत. पण छप्पन अभ्यासांची आकडेवारी एकत्र अभ्यासल्यानंतर असं दिसून आलं आहे की लट्ठपणा आणि मधुमेह यांचा परस्पर संबंध फक्त १५ % आहे. लट्ठपणाचं मूळ आहारात आहे या समजाला जसा सज्जड पुरावा मिळत नाही तसा मधुमेहाचं मूळ आहारात आहे किंवा लट्ठपणात आहे या समजुतीलाही मिळत नाही. मिळतात ते फक्त परस्परविरोधी दावे आणि धार्मिक श्रद्धांना मागे टाकतील अशा छद्मवैज्ञानिक श्रद्धा.

आता नव्यानी वाढू लागलेली समज अशी आहे की या दोन्हीचं मूळ मेंदूमधल्या प्रक्रियांमधे आहे. आपण लट्ठ व्हायचं की बारीक आणि रक्तातली साखर कमी ठेवायची की जास्ती हे प्रत्यक्ष आणि अप्रत्यक्षपणे आपला मेंदू ठरवत असतो. आता यात सहभाग असलेल्या मज्जापेशी कोणत्या, त्या कशी कशी मज्जा करतात आणि का करतात अशा गोष्टींवर संशोधन सुरु झाले आहे. शेवटी आपण किती खावे, सकाळी रक्तामधली साखर किती असावी, इन्सुलिन तयार करणा-या पेशींनी कसे वागावे, कधी आणि किती इन्सुलिन सोडावे हे शेवटी बऱ्याच अंशी मेंदूच ठरवत असतो हे स्पष्ट झाले आहे. मेंदूला बाजूला ठेवून मधुमेह समजण्याची सुतराम शक्यता नाही हे संशोधनाने स्पष्ट केले आहे. आपला मेंदू कधी आणि का असे करतो याचे सिद्धांत मांडलेही गेले आहेत. पण त्यावर अजून एकमत झालेले नाही. ते झालं तर मधुमेहावरची उपचारपद्धती पूर्णपणे बदलेल. ती बदलणं हे आजच्या औषध कंपन्यांच्या हिताचं नाही, त्यामुळे त्या वैज्ञानिकांसकट सर्वांची दिशाभूल करण्याचा प्रयत्न करीत राहतील. पण आज ना उद्या विज्ञानाचा जोर एवढा वाढेल की त्यांना ते मान्य करावं लागेल. तूर्तास आपण एक नक्की करू शकतो की पाठ्यपुस्तकांनी तीस वर्षांपूर्वी मधुमेहाविषयीआम्हाला जे शिकवलं ते अंतिम सत्य होतं असं न समजता नव्या संशोधनाबरोबर उभ्या राहणा-या नवीन शक्यतांना सामोरं जावं, पण त्याही आंधळेपणानी न स्वीकारता अभ्यास आणि पुरावे काय म्हणतात ते पहावं. आज ना उद्या आपण आज असाध्य समजल्या जाणा-या मधुमेहासारख्या रोगांवर निश्चितच मात करू शकू आणि लट्ठपणालाही आपल्या आज्ञेत रहायला लावू शकू.

Doing good science versus doing a successful science career

A former student of mine wrote to me a few days ago, saying that he was on career cross roads. He could see different opportunities, different paths and wanted my advice on which path he should take.

While I like questions, I always encouraged students to ask questions, questions like this make me nervous. Apart from the risk of someone faithfully following your advice and then failing badly, with or without blaming you, what makes me uncomfortable is the thought: should I pretend to know the answer? Even probabilistically? Did I myself take ‘right’ career decisions in my life? But even more fundamentally, is there really anything called ‘right decision’?

At first year of college, the stage at which important educational decisions happen, I had no idea what carriers are and why does one need to worry about them in an age when we should have been enjoying more than worrying. My mother was a medical practitioner and wanted me to get into medicine. I had nothing much to say for or against that so I tried preparing for the exam. I did work surprisingly seriously for my nature. Today I feel I was very fortunate to score less than what was required to get into medicine. But that time I had no clue. So I didn’t feel much good or bad myself except sharing my mother’s and other relatives’ disappointment. At that time almost everyone who missed medicine used to take microbiology and so I did. There was hardly any question of decision making. After completing Bachelors one is naturally pushed to Masters so was I. No hard decision making was involved.

I did make hard decisions later in life. Having one business proposal, one research position and a teaching job, I preferred to be a teacher and that was a conscious decision. I loved teaching and this remained unchanged till the end. But after 10 years of teaching I thought I was getting stagnant, wanted a change and joined PhD in wildlife. Fortunately there were no age bars for PhD that time. But I wasn’t very serious about finishing PhD. I was keener on living in a forest and working with wildlife full time for a few years. PhD came as a bi-product. On a couple of occasions my PhD was in danger but I felt nothing about it. I got it ultimately. Those years were so enjoyable and enlightening that PhD was a minor and sparable reward. At a later stage, a faculty position at IISc was almost in hand, but I decided to continue with teaching. During my teaching years, on three occasions I had requests from three different quite well known organizations to apply for Director’s positions in which I didn’t show much interest. Two even more difficult decisions were to resign from Garware College in 2008 and then resign from IISER-Pune in 2018, without having any alternative job in hand.

Were they the right career decisions? This I can’t answer, but I didn’t ever feel in my life, “I shouldn’t have done this or I should have done that”. Looking back, I realize one thing. I always weighed my interest in science over prospects of doing better science career. Doing good science and making a successful science career are two independent things. At times they do coexist no doubt; but at other times the two stand in conflict. What is good for science may be bad for making a science career and what needs to be done in order to make a successful career is not necessarily good for science. This is because science has an organizational structure and you need to mold yourself into that structure for making a career. Not everything in the organizational structure is scientific. The two main pillars of organized science, namely publication and funding do not operate on scientific principles. Both rely on peer reviews in different ways and the peer reviews are confidential. They are never made public. So whether they work fairly or not can never be scientifically tested. And the entire structure relies on something that has never been tested. How can it be called scientific?

Well, it is not true that it has never been tested. There have been a handful of attempts of testing whether the peer reviews work in an unbiased manner. All the attempts so far have ended up detecting significant biases in the system. So actually science organizations are standing on pillars that have been shown to be rotten. How can one expect good science coming from systems that have either not been tested, or whenever tested, proved to be biased.  But science continues to stand on the same pillars and people continue to believe that they work. This belief is not different from religious beliefs or from superstitions. So mainstream science has become a religion by itself because it stands on untested beliefs.

But if you are away from the mainstream, you can be free of those unsupported beliefs, which means you are free to do better science. In this case, the mainstream science community will not accept your science since for them only the science published by the peer reviewed journals, i. e. only the science based on religious beliefs is science. But that is their loss, not yours. The primary quality of science is that it is immensely enjoyable. If you are out of the mainstream science organizations, you can enjoy science orders of magnitude better because you don’t have to compromise your science in order to get published or get funded. But if you do so, if you decide to enjoy your science without compromising, you can’t make a career in science.

The organizational structure of science is changing towards complete monopolization. In the history of science there are examples of great contributions to science from “non-scientists”. Darwin was a school dropout and had no formal education in science.  Mendel was not connected with any University or the like. Today it is next to impossible to find such examples. Not because science cannot be done outside universities and institutes, but because it cannot be published or funded. I have seen many farmers, tribals, illiterates innovating or inquiring into a question, observing, experimenting and inferring from it. Interesting science and technology can certainly come from anyone but it is unlikely to be counted as ‘science’, only because it does not follow the rituals of the scientific religion. Today, for publishing a paper in most journals, the authors have to pay huge amounts of author charges, which anyone outside the funded science organizations cannot afford. Funding agencies will not fund even a brilliant person with proven research record if he/she is not within a formal science organization. Monopolization is a smart business tactic which is used by science organizations for preventing others from doing science.

If you want to do a successful science career, you have to be one of them. You can do good science from anywhere, but for a good career you have to be a part of that community. There is no other go. But you will not have any guilt feeling as long as you are within that community. This is because the human mind rationalizes everything and convinces itself that whatever we do is correct. By the very nature of the human mind we do this quite innocently and ‘honestly’. When you have to live in the biased world of peer reviewed journals and funding, you mold your thinking accordingly. You may yourself have seen and faced the biases but you keep on believing that the system is fair. You write projects which are more likely to get funded rather than writing it on a question that genuinely troubles you. While designing experiments, more than thinking about the real and natural underlying questions you will first think whether this will bring you a good publication. Rather than thinking what is a logical and sound design of an experiment, you would think what peer reviewers are likely to object to. You ignore a fundamental question asked by an undergraduate that you could not answer and instead think of what is currently fashionable in the funding market. On top of all you believe that this is the only way science can be done. Once the thinking itself is molded this way and you make yourself believe that this is the right way of doing science, it becomes increasingly more difficult to do good science. But you can be a successful scientist and if you are successful, how can something that made you successful be wrong? If you are confident about the soundness of your work but fail to get published or funded because you are not doing the then fashionable science, you may realize what is wrong with the system, but then you are a failure so nobody will listen to you. So the system continues to be what it is. It perpetuates along with all of its flaws and biases.

So there is indeed a conflict between doing good science and doing a good science career. It must be my sheer luck that my mind voted for good science over a successful career on every occasion. I had not explicitly thought of all this when I took all those insane decisions.

Now I can write back to that former student with sufficient clarity, “first decide whether you want to do good science or you want to do a bright science career. If you vote the former, I would be glad to talk to you for hours. If you are asking my advice with the latter in mind, I am afraid you are asking the wrong person. I have no first-hand experience of what needs to be done for a successful science career. I am afraid, I can offer no advice for you!!”

What science can learn from Imran Khan’s US visit?

One of the things I feel least interested in, is politics. But of late, I have been watching politics related news on channels and YouTube videos so much that my wife was worried whether her crazy hubby had any thoughts of joining politics. The reason I am watching them is because I am a student of behaviour and I always have a child like curiosity about why people behave the way they do. Whatever I do, ultimately relates to science in some form or the other.

Look at the media coverage of the US visit of Pakistan’s prime-minister Imran Khan. After landing up the in US, he travelled in metro and stayed in Pakistan embassy instead of a hotel. There is one sect of news channels and media that are interested in projecting this as an insult to Imran and to pakistan. They say this reflects the begging bowl state of the country. Diametrically opposite are the titles of the obviously pro-Imran Khan media that are projecting it as a noble austerity act of him in the light of the economic situation of his country. Imran Khan’s Jalsa is similarly portrayed in two diametrically opposite ways; some videos focussing on the 30,000 crowd of Pakistani Americans gathered and others focus on the Baloch slogans being shouted somewhere in the crowd. Everyone makes a highly selective story to highlight one side of the picture. This is certainly amazing, though not very surprising. It is a typical evolved trait of human behaviour. The human mind is not evolved for reasoning and judging. It is evolved for taking sides. After having taken sides we gather news, facts, evidence and logic selectively to support our side. We do not take rational decisions, we rationalize our decisions after they are taken. We do not make judgments based on perceivable facts. We perceive facts according to the “judgements” that we have already committed to.

This is not new to science. The journal Behavioural and Brain Sciences (BBS) has accepted for publication a paper by Fiery Cushman of Harvard University. It will soon come in print. The title of the paper is “Rationalization is rational”. It is known for quite some time and demonstrated with many interesting experiments that humans do not take decisions by rational thinking. They shape their thinking in order to justify their already taken decision. In soft rationalization the human mind is only seeking socially acceptable justifications for their decisions or acts. In hard rationalization we actually make ourselves believe that the stories concocted for justifying our act are true. Our acts often shape our beliefs although most people typically like to believe in the upside down view. The main role of conscious thinking in human life is to find justifications of our already performed acts that most others will find acceptable.

Cushman in the BBS article takes a right stand that it is not sufficient to describe the phenomenon of rationalization. We need to wonder why and how it evolved. He raises the right question but his attempt to explain the evolutionary origin is quite primitive and fails to capture the complexity of selection for rationalization. His evolutionary justification is that rationalization evolved for “transferring information between the different kinds of processes and representations that influence our behaviour”. We need to look beyond that. The human species evolved as social species and we do almost everything that we do in the context of others. The context of the group almost never vanishes.

When two individuals fight, the fights quickly transform themselves in group fights, because people take sides. (There are some fence sitters, and the advantages of side taking versus fence sitting are negatively frequency dependent, but that apart). Whose side one takes depends upon so many factors, but you first take a side and then justify. Whose side you take depends upon kinship, reciprocity, green beard effects, perceived individual benefits from specific persons and groups. The justification is adaptive because you need to recruit more people on your side, for which you need to concoct reasons which are acceptable to them rather than which are “true”. The number certainly matters in a group combat. So better your skills of rationalization, more likely you are to win the fight. So there is a strong selection on the ability to concoct convincing reasons.

Your ability to make others believe can be better if you yourself believe in it. Moreover altering one’s own beliefs makes positive feedback loops that ultimately build a personality. Taking one decision changes your personality in such a way that you are more likely to take a similar decision again. Stabilizing personality by positive feedbacks is important because the body physiology is fine tuned to the personality. So manipulating your own beliefs is the first step in convincing and recruiting others on your side on the one hand and stabilizing your own personality and physiology on the other. Others will join you based on their own cost-benefit calculations, but they also quickly start believing that they are on your side because it is “true”. So everyone except truth believes to be on the side of truth. This process is an important component of multilevel selection.

Evolved psychological mechanisms would favour what is good for an individual, which need not be good for the group. Inevitable conflicts between individual benefit and group benefit can lead to multiple conflicts and such conflicts can be dampened, at least at the perceptional level by rationalizing. Multi-level selection has certainly played a significant role in human biological and cultural evolution, and by altering conflicts between levels, rationalization can change the nature of multilevel selection. Thus not only selection has shaped rationalization, rationalization has shaped selection acting on the human society. 

This may not mean that an impartial and unprejudiced search for truth is impossible, it can be certainly said to be difficult thought. This is important for science, which is a quest for “truth” in a practical sense. Let us not bring in here the philosophical meaning of truth and whether it can really be perceived. For the time being truth is a model that is fairly realistic so that you can use it to make the system sufficiently predictable and comprehensible. It is about being able to solve a problem, such as effectively prevent or cure a disease. However, pursuit of a practical truth does not happen naturally. Researchers are humans and their natural tendency is not to go by reason but as far as possible take a side in a debate and selectively look for evidence, reason and justifications to support one’s side in the debate.

This is beautifully illustrated by a paper by Trinquart et al in 2016, in which they show the current status of the salt and hypertension controversy. There are clearly two sides in the debate and majority of researchers take either this or that side. Researchers who believe salt causes hypertension and salt restriction can cure it, selectively cite references favourable to them. The other side which believes salt intake has nothing to do with hypertension and its ill-effects also do cherry picking and only cite papers from their group. Nobody seems to have an interest in finding the truth; they only want support for their side.

So researchers are no better than most media covering political news. Scientists are not rational by nature. They are primarily side takers, not impartial judges. It takes substantial efforts to be impartial and only a minority can perhaps achieve it. But is this a pessimistic note? Does it mean one can’t do an unbiased scientific pursuit of a question? On the contrary, if you know how human nature evolved, if you know the strengths as well as weaknesses of the only tool you have, that is your mind, you can utilize it in a better way. If you hold on to the false assumption that you are rational by nature, you will almost certainly be misled. If you know that you are born as a side taker and need efforts to rise above biases and prejudices, you are more likely to take those efforts. Science is not only about theorems, proofs, experiments, evidence and laws, it is about human behaviour and one cannot understand how science works without understanding human behaviour.


Cushman, Fiery (2019) Rationalization is rational. Behav Brain Sci, in press

Trinquart L., Johns D. M. and Galea S. (2016) Why do we think we know what we know? A meta-knowledge analysis of the salt controversy. Int. J. Epidemiol. 45, 251–260.

The paucity of research on research:

Research is an interesting phenomenon in human evolution. I am not separating biological evolution from cultural evolution here, because it is essentially impossible to segregate the two. But there are multiple reasons to believe that research evolved with us. It is there in human nature right from our hunter gatherer life. Today, mainstream research is bound by a fairly rigid structure for hosting, funding and publishing research. This has no doubt boosted research output. But do we “understand” research? I have serious doubts.

Successful researchers do not necessarily “understand” research. Just as an experienced cricketer can take a fine catch with amazing skills, but he need not understand which rules of physics govern the trajectory of the ball and which motor neurons he needs to activate to instruct the right muscles to enable the dive and catch. Physics knows the forces acting on the ball fairly well, but our understanding of nerve muscle coordination is still quite primitive, and limping to progressing.

The analogy is quite good for research.  We often develop a fair amount of understanding of the subject of investigation like the physics of the forces acting on the ball, but have little understanding of the how the mind of an individual researcher works and how the community of researchers interact. Not knowing something is fair. But that is not how things are. The community of researchers pretends to be what it is not. Also the way science is published is not the way it is actually done. In a research lab, more often than not, things develop rather chaotically, new findings are often serendipitous, experimental work does not always progress in a logical sequence. Often one gets an interesting result first and then wonders how it came about. Still when a research paper is written, it is written as if everything was logical and sequential. Not only that, if a researcher does not pretend that everything was done in a logical sequence, he/she is unable to publish it.

This pretence (if it is better to avoid using the word hypocrisy) is so common that researchers themselves do not know at what stage they start the self-deception game. They make themselves believe that they are logical. But this is not how research actually progresses. Research progresses through complex behavioural, psychological and social interactions that have been little studied. Hardly any one seems to be interested in studying and documenting them. It is ironic that researchers themselves are not interested in research on research.

Formally there is a branch of science called meta-science or science of science. There is a Wikipedia page on Metascience and it cites some landmark papers in this area. There are a handful of good researchers in this field. Intermittently they have published good papers in journals like Nature – Science. Science organizations and leading journals have intermittently worried about how to improve doing science and publishing science. But reading through this literature my feel is that they are too superficial. They are not yet addressing the human behavioural principles that govern science. They haven’t yet asked how these principles evolved. They are still pretending to be very ‘logical’.

I was fortunate that I took a late and backdoor entry into science. My science training began after having completed my degrees in science. I had no aspirations of doing a PhD. I got into it only because I saw an opportunity to stay in a wildlife rich forest for a few years, with stipend! That was my motivation, not PhD. After PhD I did not do a post doc anytime. I liked teaching and was also lucky to get a teacher’s job quite quickly. I realized in my first few years of teaching that research was the best tool in science education and undergraduates the best persons to do research. That was my back door entry into the field of research. Not having followed the routine path of research career, I always looked at the research field as an outside observer mainly triggered by my own curiosity about how the field works, than by any aspiration of making a bright and successful research career. I discovered eventually that this field was a highly fascinating subject to study the principles of behaviour. The researcher community was more fascinating to observe and experiment on than the elephant social life, multispecies interactions or the social insect colonies that I was fascinated by.  So I have seen things that the most people within the community haven’t.

Of late I have started writing about it. One paper was published a couple of years ago and a second one I just communicated to a journals and also posted on preprint. This work is very preliminary, but the whole field itself is preliminary. I know that this manuscripts will face a very hard time getting published for reasons I have spelt out in the manuscript itself. But here is an interesting situation. If my manuscript gets rejected, it strengthens the hypothesis states in the paper. If it is accepted, it means it is agreeable. Does that make it right or wrong? You decide.

The link to the paper published in the Journal of genetics is Here, and the one to the latest manuscript on pre-print Here.

A teacher never dies:

I have been a science teacher all my life and the day I left IISER-Pune, my formal career as a science teacher came to an end. IISER was not a good environment for a science teacher anyway, but that apart, I am surprised that I am not missing my classrooms very much. Feeling good on the one hand that I won’t have to correct papers anymore, which I never liked, I also won’t be teaching in a classroom which I loved all my life. I still love that but it is strange that I am not missing much when I no more do that!

Perhaps I know the reason. A number of things that I did as a teacher continue even today. One is the katta. Now there is a katta at home every Saturday night, post dinner (no…no…. we don’t serve dinner. You have to have your dinner and then come). Interestingly some of the very first generation katta members, who are now well settled in their profession, have joined once again. Very soon, I believe their next generation will join. We have a more varied group now ranging from 12th entrants to grandmas, academicians to businessmen, students and housewives. First year collegians and their parents become katta members together.  So katta isn’t dead, it has expanded.

Farmers’ meeting at Wadala Tukum, 30th June 2019.

The classroom is also still there, though less frequent. Now the class is attended by farmers, tribals and illiterates. Last week we had a meeting with a group of farmers that I have been working with for the past many years. Until the last meeting with them, I was a professor, with substantial research funding. Unlike most social science or agriculture researchers, my farmers are not my ‘subjects’ of research. They are my research partners, colleagues and collaborators. Over the last few years an interesting chemistry had been built between me representing a research institute, an active local NGO called Paryavaran Mitra and its insightful social workers, Poorva Joshi of Bioconcepts Pune and a group of over 70 farmers. Now only the research institute has backed out. The rest of the group remains the same. A few years ago we started with the spirit that let us study and understand our problems ourselves and seek solutions.

Although the intention was to build a spirit of working together, I always had some doubts in my mind. I belonged to an elite class of scientists and professors in a prestigious institute, whether I liked it or not. I brought funding for the research. In fact, because of the funding we could organize lunch at the farmers’ meetings. Officially farmers were the ‘beneficiaries’ of the funded project (although I don’t like the word) and they were getting the due benefits. I thought that majority of farmers might be coming because they see those benefits. By our principles we, the researchers, are trying to create a spirit of working together, facilitating collective intelligence, community governance and so on. But that might just be our perception. Farmers might simply be coming because they get free lunch, some money or other benefits at the end.

When I resigned from IISER, the funding ended. IISER took a very strange decision to continue utilizing my grants by appoint another principal investigator on the project. This is not the norm in the field of science. This was only a move to channelize money elsewhere. Research projects are researcher centred, the institute only hosts them. The institute has no rights to appoint a new investigator on an already running project, without even asking the consent of the original investigator who wrote the project proposal and mobilized the grants. But big people of science don’t need any norms. Whatever they wish is the rule, whatever they do is the procedure. The fact relevant here is only that now I was left with no funding.

Last week right at the beginning of the farmers’ meeting I told everyone that I have no money in hand. Now I can’t give any ‘benefit’ to anyone. Your work will not have any remuneration that we used to give from the project funding. Now you have to make a decision. Do we continue the work without any money or do we stop the project here? This was the acid test. My doubts whether the farmers are participating out of a spirit of co-working or they only come to get the ‘benefit’ would have been clear in no time.

And then came the biggest pleasant surprise. The moment I explained that we have no more funding and asked them whether they wanted to continue working, without a millisecond delay 80 hands were thrown in air in unanimity to say, nothing will stop us. We will continue working together. What I could read on those raised hands was, “We are not here because we get some money. We are here because we discuss our problems here. Someone listens to us and tries to understand us. He says let us all study the problems, try to understand and seek solutions. He doesn’t pretend to be a messiah; doesn’t give us any magic wand solutions, but only says let us work out our solutions together. This is what we come here for. Not because we get some free lunch and some money”.

I can see big parallels with my interaction with students throughout my teaching career. I never promised them good grades and further admission to best Institutes or good career opportunities. I interacted with students with a promise of doing good science, opening up new questions and addressing them. I never promised answers to their questions but said let us find ways to address them. I am not here to answer your question. I am here to share your questions and share the efforts to investigate and seek an answer. The classroom and the farmers’ group are not different in any way.

The response that let us continue working together, we don’t care whether there is funding or not, is the best reward that a science teacher can ever get in life, the true Nobel for a scientist. And here lies the difference. I am tempted to compare the response of farmers to that of students when they learnt that I was leaving and that I won’t have funding anymore. They were more worried about their incomplete degree and their career than about the problems that we were investigating. I feel the illiterate farmers are better researchers than the top grade Masters and PhDs in science.

Farmers have given me another assurance. The science teacher in me hasn’t died and will not die.