Covid 19 (coronavirus) exposes the limitations of knowing life by molecules

What do we know about the covid-19 or more popularly the coronavirus that has left the whole world panic struck at the moment.  Well, we know everything! We know its complete genome, we know every molecule that makes it. We know its complete structure. Isn’t that enough?

But we know nothing! We don’t know how and where all it will spread. What will be the overall mortality rate? How many people will get killed? When will it reside? Will it completely go sometime or remain endemic somewhere in some population? May be some other animal? How do we control it? Why are the efforts to control it largely failing in so many countries, particularly the technologically most advanced countries?

The pandemic has brought a very important lesson for science, for biology in particular, in case we want to learn from it. Science should advance by relevance, be driven by questions, be funded according to the importance of the underlying question. But that is not how science progresses in real life. Researchers go by what is easy to work on, what is trendy, what is more prestigious, where things are ready made, paths are well laid out, what will give quick ‘success’. Success, by the way, is not success in resolving the underlying problems, it is success in publishing in high profile journals, getting patents, getting a quick name and fame, making big money, ensuring further funding. Today knowing about the genome, transcriptome, proteins and other molecules has become a routine. What was not easy a few decades ago has now become a routine that anyone can follow and get something in hand. This, in itself, is a big achievement. I have no doubt about it. But does it give us the insights that we need most badly? Well, knowing the molecules of a virus can perhaps expedite vaccine development, but still it will take months or even years to undergo all necessary trials and testing before coming in use. What do we do in the meanwhile?

What we hardly know about the virus is its ecology, its interaction with the host individual as well as the host population. The population level outcomes, how variance within the population affects the virus propagation, infectivity, virulence, asymptomatic infections, interaction with comorbidities, convalescent state, carrier state if any and so on. Does it affect any other animals? Can it remain dormant in any other species? Did it come from any other animal, if yes why didn’t it come earlier? How would the virus evolve now on and how would our prevention and treatment strategies shape its evolution? These questions are about its biotic ecology. The abiotic ecology might appear simpler to study. Its survival in air, on skin, on other surfaces, its susceptibility to natural and man-made conditions, how it varies with ambient conditions, seasonal fluctuations and so on. But looks like, as of now we don’t even know its abiotic ecology sufficiently well. Forget about complex biotic interactions. The result is that we can make no reliable predictions about what course the pandemic will take.  Studying all this is orders of magnitude more difficult and there is no routine protocol that will give us all necessary answers. The only thing we are sure of is that at least at the moment knowing every molecule that makes the virus is not helping us much.

Is the field of science going to learn a broader lesson after the panic subsides? Today all biology is being viewed only in terms of molecules. There is no doubt that molecules are important and we gt to study them. But understanding life is not understanding molecules. It is much beyond molecules. But studying molecules is the current wave on the fashion street.

Are we going to go by the relevance of questions or continue to follow the fashion street? In the current situation fields like disease ecology, epidemiological modelling do exist and there are brilliant brains working there. But there is a big gap between people who do the molecular biology of the virus and those trying to understand its ecology. People on the two ends don’t even talk to each other, if they do, they may not understand each other’s language and concerns. This gap is not created by the limitations of science. It is created by the culture and social behaviour in the field. Of particular importance is the picture of biology that we project for students. Certain fields have a bigger craze among students which again is a societal creation than anything in science itself. Biology curricula are highly biased and these biases follow trends in frontline research. Funding, on the other hand, goes more by the cultural definition of success over real scientific achievements. This course of science is natural since it is simply driven by the evolved behavioural instincts of researchers. But humans have a unique capacity to exceed the instincts and behave thoughtfully. We expect that at least people of science should use this capacity sufficiently frequently.

Predatory journals: simple definition, simple solution.

(Our response to Nature article “Predatory journals: no definition, no defence”

Myself and Sonali Shinde wrote a reply to Nature (an abridged version of the following article) immediately after publication of the article. After two and half months they declined to publish it, on the grounds that they received many responses “making overlapping points” and that they will publish representative ones. Now let us wait and watch whether what we say below is represented in the set of responses they finally publish. I won’t be surprised if it is not because what we suggest here is what the science publishing community is deliberately avoiding to do for quite some time.

Intelligent Martians had been doing research on human behaviour for quite some time. Once a PhD student doing her observations through a superpower telescope, saw a mob of people doing something exciting. She called her mentor,

“Look, what these humans are doing there on earth.”

“Who are they? Men or women?”

“How would I know? They are not wearing any clothes!!”

This is precisely how a committee comprising 43 researchers, publishers, funders and policy makers from 10 countries that met in Ottawa, Canada last April is looking at the problem of predatory journals after two days of brain-storming. They want to identify predatory journals not by what they are but by what clothes they wear. The outcome of this meeting is published as an article in nature (Grudneiwicz et al 2019). The definition of predatory journals they have proposed is so subjective and open to interpretation that with a tighter strain, most mainstream journals can be labeled predatory and with slightly coarse one, none would be filtered out. The definition may not matter so much in practice but the diagnostic criteria would, since that is how one would identify a predatory journal in practice.

What should be the diagnostic criteria for a predatory journal? Charging the authors is a common practice now in so many flagship journals that it cannot be a differentiating criterion. Advertising in some form or the other is also practiced by some mainstream publishers and there is nothing unethical in it. The committee has listed certain other trivial criteria for diagnosis as a predatory journal. These criteria are either difficult to know before submitting (which the article itself acknowledges) or are so superficial that the journals can easily improve upon them and still remain predatory. For example, they list “an unprofessional looking webpage, spelling or grammar mistakes or irrelevant text” as markers of predatory journals. The act of identifying these as diagnostic markers would immediately make them improve on it, but that will not change the predatory nature of these journals. The biggest surprise decision of the committee is to leave out the quality of peer review as the defining or diagnostic marker. The only difference that can exist between mainstream journals and predatory journals is the quality of peer review. But they say “At the moment, journal quality, adequacy of peer review and deceit are too subjective to include……(as diagnostic criteria)”

This is precisely equivalent to identifying someone from the clothes and not from the being that he or she is.

It can be perceived without much difficulty that the main problem does not lie with the predatory journals, it lies with the mainstream journals. There isn’t sufficient transparency in the mainstream journals. The unnecessary confidentiality of the peer review process is the root cause of the problem. One of the reasons there is resistance to transparency is that the quality of peer reviews of the mainstream journals itself is often, if not always, questionable. Whenever an attempt to investigate has been made, biases and unprofessional behaviour of reviewers and editors of the mainstream journals has been found. This is well documented and published independently by several research groups (Campanario 1998; Bornmann et al 2010; Phillips 2011; Tomkins et al. 2017; Haffar et al. 2019; Kuehn 2017; Lee et al. 2013, Silbiger and Stubler 2019, Elson et al 2020). Even a subtle biases can permit persistence of a wrong paradigm and prevent acceptance of truth (Akerlof and Michaillat 2018). So no doubt is left that the peer reviews of mainstream journals are frequently of bad quality and are a major obstacle in the progress of science. Reviewers and editors can easily get away with bad quality reviews simply because they are never exposed. Systematic enquiries in the peer review process are also limited by the confidentiality (Couzin-Frankel 2013). It is most ridiculous that the main pillar of science, which is publishing, is not available for scientific inquiry. Making peer reviews public will certainly make editors and reviewers more responsible.

The threat of predatory journals is unlikely to disappear as long as the review process of mainstream journals remains confidential. Let there be dozens of committees like the Ottawa committee; let there be dozens of attempts to isolate and banish the so called predatory journals; the threat of predatory journals will not vanish as long as the mainstream journals do not themselves improve. If the presence of predatory journal really induces an introspection process in mainstream science publishing, I would say predatory journals is a boon to science.

But mainstream science is reluctant to take up the hard work. They think making superficial efforts like the Ottawa committee will work. They think they can diagnose and isolate predatory journals and then everything will be alright. This is not going to happen. In fact making lists of predatory journals is a dangerous solution since very soon it will become a business opportunity similar to the impact factor business.  On the other hand, in the absence of clear and legally valid definition the agencies making such lists can be easily sued for defamation. So the entire attempt to list predatory journals and warn authors not to publish in them is a dubious affair.

The only long term solution to predatory journals is that mainstream journals make their editorial and review process completely transparent, independent of acceptance or rejection. This can be done using pre-print services and steps towards this goal are already underway (Brainard 2019). The unfortunate but not unexpected fact is that only 17 journals have subscribed to the scheme of open and transparent peer reviews so far. There are other means of making things transparent as well (Watve 2019). The reluctance to make things transparent makes one suspect that something fishy could be going on behind the curtain of confidentiality.

“If corruption is a disease, transparency is a central part of its treatment.” — Kofi Annan.

“A lack of transparency results in distrust and a deep sense of insecurity.” — Dalai Lama

If transparency becomes the norm of the peer review process, the entire reader community is free to judge the review quality. Then the so called predatory journals will either have to improve their review process, i.e. essentially cease to be predatory, or perish automatically. No formal committees and actions will be needed against them. Thus the definition of predatory journals is very simple- based on peer review quality and the only effective solution is also quite straightforward and that is transparency. But by evading a clear definition as well as the most logical solution, the scientific community is unnecessarily making the matters more complex.

Akerlof G. A. and Michaillat P. (2018) Persistence of false paradigms in low power sciences. PNAS, 115, 13228-33.

Brainard J. In bid to boost transparency bioRxiv begins posting peer reviews next to preprints. Science,

Bornmann L, Mutz R, Daniel H-D (2010) A Reliability-Generalization Study of Journal Peer Reviews: A Multilevel Meta-Analysis of Inter-Rater Reliability
and Its Determinants. PLoS ONE 5(12): e14331. doi:10.1371/journal.pone.0014331

Campanario, J. M.: (1998) Peer Review for Journals as it Stands Today. part 1 and 2. In: Science Communication 19(3) pp. 181–211 and 19(4) pp. 277–306.

Couzin-Frankel J. (2013) Secretive and subjective, peer review proves resistant to study. Science, 341, 1331.

Elson M., Huff M. and Utz S. (2020) Metascience on peer review: testing the effects of a study’s originality and statistical significance in a field experiment. Adv. Methods Practices Psy. Sci.

Grudniewicz, al. nature 576, 210-212 (2019).

Haffar, S., Bazerbachi, F., & Murad, M. H. (2019). Peer Review Bias: A Critical Review. Mayo Clinic Proceedings, 94(4), 670–676.

Kuehn, B. M. (2017). Rooting out bias. ELife, 6, 1–3.

Lee, C. J., Sugimoto, C. R., Zhang, G. & Cronin, B. J.Am.Soc. Info. Sci.Tech 64 (1), 2–17 (2013).

Phillips, J. S. (2011). Expert bias in peer review. Current Medical Research and Opinion, 27(12), 2229–2233.

Silbiger N. J. and Stubler A. D. Unprofessional peer reviews disproportionately harm underrepresented groups in STEM. PeerJ, 7, e8247.

Tomkins, A., Zhang, M., & Heavlin, W. D. (2017). Reviewer bias in single- versus double-blind peer review. Proceedings of the National Academy of Sciences, 114(48),

12708–12713. Watve M. G. (2019) The evolutionary psychology of scientific publishing: cost benefit analysis of different players in the game.

Cancers: Looking beyond molecules

A person on ground has access to many details of what exists on earth, but a drone picture or a satellite image reveals something that you can’t perceive from ground. The drone’s or satellite’s view actually misses so many details but still gives some realizations that one can’t get on the ground. This is applicable to the field of research as well. Some researchers are obsessed by details, their research reveals more and more details and keep on adding to the data. In biology the details are often so intricate that getting lost in details is a commonplace. Having lost thus, the researchers themselves do not know where the research is going. In order to make sense often one has to leave the ground and take a perspective. This comes at a cost of resolution. The details are no more visible but the path which was obscured by the details might be revealed.

Take the example of cancer. We now know so many molecular details about it that understanding the fundamentals of cancer has become almost impossible. In the history of cancer research, some important insights about cancer were obtained before molecular biology came into existence. Cancer was identified as a multi-stage process by mathematical and statistical analysis of population patterns itself.  Then it was realized that a series of mutations are required to transform a normal cell into cancer cell. Later came the tools of molecular biology which revealed that what mathematical models had suspected was actually true. Then on molecular biology kept on adding a huge volume of details, accompanied by much smaller increments in the fundamental understanding.

Cancers arise by a series of mutational and functional changes in some or the other stem cells of the body. These changes are quite like evolution, which happens by a process of random mutations accompanied by natural selection on the mutants. Cancer is nothing else but evolution of normal cells into cancer cells by a similar process of mutations and selection. Cancer researchers, so far have focused their attention on the details of mutational and other molecular changes in cells. Unlike rest of the evolutionary biology, cancer evolutionary biology has paid inadequate attention to selection on the mutants.

Recent research is now converging to show that the rate limiting process in most cancers is not mutation, but selection. Cancer causing mutations can arise in any individual at any time, but most people do not get cancer because their internal environment does not support the mutants. Cancer causing mutations do not have an all-time growth advantage over normal cells. Cancer cells need to compete with normal cells to survive. They can survive and outcompete normal cells only under a certain set of conditions. These conditions are provided by the body’s internal environment. The importance of the tissue microenvironment in the development of cancer is being increasingly recognized only over the last decade, but it was not incorporated adequately in the cancer evolution models.

And now a mathematical model of the cancer evolution process built by us shows that the known population patterns in cancers can be explained only by incorporating different selective forces in different individuals. If the internal environments of all individuals were similar, by all probability almost everyone would get cancer by a threshold age.  The mutation probability alone does not explain why only some individuals get cancer. The population patterns of cancer are matched only when the model considers that every individual has a different tissue environment and thereby different selection on the mutants.  Many other known patterns in cancer biology cannot be explained without taking individual differences in the selective environment of the mutant cells. So our concept that cancer is limited by the process of selection rather than mutation is supported by multiple lines of evidence.

Can cancers be prevented?

In 2017, a paper appeared in the journal Science claiming that cancer is shear bad luck. This implied that perhaps nothing can be done to prevent cancers. The paper immediately attracted substantial criticism because the methods used for analysis were not sound. This paper delighted me since I used to teach a preliminary course in bio-statistics and I got a real life example of how not to use statistics. I could warn my students, beware!! If you use wrong statistics you are likely to get a paper published in Science!!

Now using the same data but analyzing it more carefully, and using novel mathematical approaches we infer exactly the other way. That cancer is only marginally bad luck and potentially largely preventable by maintaining a healthy internal environment. If the internal environment is healthy, mutants may still arise but are unlikely to outcompete normal cells. This paper is published in Nature publication’s Scientific Reports on 6th March 2020. (

Future research in cancer should focus on which factors of the internal environment govern the competition between cells and what regulates these factors. Experiments so far have indicated that the levels of different hormones, expression of a class of molecules called growth factors and the properties of the matrix in which cells of a tissue are embedded are critical components of the selective environment. If maintained at their natural healthy level the tissue environment can prevent cancer causing mutants form growing into a fully evolved cancer cell. Many lifestyle and behavioural factors modulate the tissue microenvironment but our understanding of the links between lifestyle, behaviour and microenvironment is still quite primitive. This understanding will be the key to prevent cancers and future research should mainly focus on this question.

This goes very well with my thinking about the behavioural origins of many of the modern disorders. We evolved for stone age life and a number of behaviours evolved with us to fine tune with that life. Every behaviour is linked to a set of neuro-endocrine pathways and all pathways form a complex network structure. So when we give up certain behaviours for which our body evolved, the entire network changes; the body’s internal environment changes and at least some of these changes set the stage favourable for the cancer driver mutants.

About 10 years ago an interesting paper that appeared in Cell has interesting implications for this theory. In this experiment one group of mice was kept in the conventional caged environment and another group was given a behaviourally rich environment. Both groups were implanted with xenografts and observed for several weeks. In the ones with a behaviourally rich environment the tumours regressed but in those with a monotonous caged environment they grew bigger. Todays human lifestyle is like the monotonous caged mice. We need to gain back the behaviourally rich natural life to get rid of cancers.

Now again, a number of molecular details should follow the new line of thinking. How life-style and behaviours modulate the tissue microenvironment, which microenvironmental factors alter the selective environment for cancer driver mutants, how mutations accumulate and how cancer grows given the selective conditions will make multiple fascinating molecular stories. But the details make sense only when you have the low resolution picture. Unfortunately in today’s science molecular details have become prestigious and perspective taking is not. Both are equally important but not equally prestigious. What you value depends upon whether you want good science or prestigious science.

Need to revive the “marhaba” culture in science:

Marhaba (مرحبا, मर्हबा), a word of Arabic origin, used in Persian, Urdu and even in Hindi is an expression with multiple contextual meanings. Its original literal meaning is said to be “God is love”; but its use is not religious. The context in which I came across this word is in welcoming and appreciating a novel and somewhat surprising idea, art form or achievement. It’s an appreciation of the idea as well as of the thinker, art as well as artist, achievement as well as achiever. So often used in art, music or poetry appreciation, marhaba comes immediately and spontaneously when an unexpected and pleasant piece of melody, an astonishing phrase of words or an unusual imaginative idea is recited. Appreciation is a universal human attribute but a marhaba kind of appreciation is a different culture, prevalent in certain languages, certain schools of music and certain forms of poetry. A marhaba cannot be replaced by a clapping applause, how so ever loud it is. Clapping is a monotonous collective act. Marhaba has a private, personal, informal and insider’s touch. Clapping is more appropriate at the end of the performance. If people clap in between it is disturbing. A marhaba comes spontaneously the moment you like something and it is not disturbing. There is not one but many phrases of this appreciation including vaah, kya baat hai, shabash, sunder, aha or just with a different shade of meaning which correlates with subtle but wide vocabulary of facial expressions and body language. Unlike clapping, each expression reaches the performer separately as if the performer has a separate receptor for each of these expressions. I am using Marhaba here as a generic name that represents the entire repertoire of dialogues between the artist and the audience. Hindustani classical music, Persian and Urdu poetry had this marhaba culture until very recently, or is still there to some extent, but as the distance between the performer and audience is increasing in the modern theatres, and the audience itself is changing, the clapping culture is rapidly replacing the marhaba culture. Incidentally the same change of scenario seems to be happening in science too.

I am fortunate to have experienced many marhaba responses in music-poetry as well as in science; in both the fields from both sides, as a performer and as an appreciator. I came to science and remained committed to it for life, not because I got a well-paying job as a scientist, or had prestigious publications, breakthrough discoveries or sumptuous funding but because I experienced many marhaba moments. Although qualitatively I experienced them throughout my career, quantitatively, my feeling is that, the marhaba culture is vanishing rapidly and being replaced by a ‘success’ culture. While marhaba is not objectively measurable, ‘success’ is measurable in terms of high impact publications, successful grant proposals, promotions and prestigious positions.

While reading Erwin Chargaff, “…our era is extremely ambivalent when it comes to the problem of how scientific research ought to be supported. … The less the people are willing (to support science), the more promises must be made. Instant longevity, freedom from all diseases, a cure for cancer – soon, perhaps, the abolishment of death – and what else? Whereas, no singer did ever have to promise to make a better man of me if I listen to her trills.” I had to stop at this sentence, it was just impossible to go ahead. Is it possible, I wondered, that listening to science can be as absorbing as listening to music. And I said why not? I have experienced it at times, but at rare times. Throughout so many talks, lectures, seminar and conference presentations not more than a dozen times I felt I was listening to music. Not only there was very interesting science being talked about, but it was being delivered in an artistic way. On at least three occasions, I received precisely this comment after my talks. Three listeners from three different countries and three different cultures expressed it as “There were moments we felt like saying kay baat hai”. In Arizona once an old American lady who knew nothing about me came straight to me after my talk and asked “Are you a singer?” I said “No, my father was.” “But you talk like music.” I still don’t understand why she felt so. Perhaps the performer in me is not dead. So what Chargaff remarked is not a fantasy, science can become music. It would attract people as if music would. Just that it is rare, and the reason it is rare is not that it is uninteresting but because it is not there in the culture of scientists. Science is not dry, scientists are.   

But since the performer culture is lacking, are we trying to engage people in a different way? Are we trying to create a culture where claims of breakthroughs, tall promises, triumphs of publishing in high impact journals, successes of obtaining massive grants overwhelm so much that the joy of understanding some mystery of nature, an opportunity to say marhaba to nature or to oneself for getting insights into one, is of little value?

When in my 20s and 30s I started intermingling with the research community, I could overhear across coffee tables people talking about novel and crazy ideas frequently. My time in the C mess of IISc was always enriched with crazy ideas cutting across all fields of science. If I overhear now, it’s a different picture. I hear more about celebrations of getting papers accepted, remorse over rejections of funding proposals, obsession over getting latest tools and technologies in one’s lab, worries about how to handle notorious students and how to manage the routines. These are being talked about more frequently than ideas and insights. Young researchers are being nurtured to think about how to publish in high impact journals rather than about the feel of the moment of having made sense out of a puzzling data set. My sample size is bound to be small and perhaps biased too. Is this happening everywhere? I have no idea.There is this field of research called meta-science. Researchers in meta-science need to look into whether there really is such a trend in the researcher community. If there is one, it is a matter of serious concern. Are all advances in science henceforth going to be Galisonian over Kuhnian? Tool and data intensive over concept intensive? If yes, people of my nature should better keep away from the field. Is the marhaba culture vanishing from science? Meta-science should answer such questions. But the chains and the handcuffs of objective and measurable variables are so heavy that meta-science is only busy looking at quantifiable trends in published research. Isn’t what goes on in the mind of a researcher worthy of research by itself?

Erwin Chargaff and I

What an unequal comparison!!

Sure, grossly unequal it is. Chargaff happens to be the pioneer of modern biochemistry and particularly the chemistry of DNA, evidently underappreciated by science historians about which he himself was quite aware and somewhat apprehensive; contrasts with the small man that I am with my science that I can’t evaluate myself. If at all I contributed anything that will be seen only 20-30 years from now. But I am still tempted to compare my experiences in the field of science with his, after reading his book “Heraclitean fire: Sketches from a life before nature”. Although I had heard the name Chargaff vaguely before, as every biologist does, I was not aware of this book until Prof. Niranjan Joshi, from whom I mainly learnt the art of making simple but insightful models, referred to it in a thread of Facebook messages. Fortunately the book was free online, but I found it extremely hard to read. The 200 and odd pages took me about a month to finish, I mean only the first reading.

Although the book is supposed to be an autobiography of a scientist, it is far from what one can imagine by the word autobiography of someone who is far from what one can imagine by the word scientist. A stark difference between scientific writing and poetry is that in the former every sentence has only one possible meaning. A characteristic of good poetry is that every time you read it, you perceive a new meaning. “Heraclitean fire” belongs to the latter. You need to read many of the sentences repeatedly and find a deeper meaning every time. That is why I took so long to read.

The reasons I kept on finding my own reflection as I read through are multiple. Chargaff often calls himself a teacher more than a scientist. He says, “A good teacher can only have dissident pupils, and in this respect I may have done some good.” He has a fascination for literature, music and poetry which we share qualitatively but not quantitatively since he knew classical literature from 15 languages and he cites so many paras and phrases from all of them so often.  He could easily have been a celebrated writer or poet. What is evident throughout the book is his deepest engagement with science and at the same time a deepest unhappiness about the working of science organizations and the behaviour of the scientific community.

He thinks that the scientific community is becoming increasingly more arrogant. Peaceful and insightful quest of the mysteries of nature has taken a back seat and dazzling advertisement of ephemeral “breakthroughs” is aggressively on the forefront. He is particularly unhappy about the way in which Universities and Institutes are administered. He is critical of peer reviews and big mega-funded projects which are distorting the spirit of science.

Resentment, bitterness and sarcasm but at the same time a philosopher’s detachment trickles through every chapter of the book. I used to think, believe and experience that when one develops a detachment with oneself, bitterness vanishes. But Chargaff’s case is more complex. You feel the detachment along with bitterness. Bitterness is there everywhere and not there at all.  He sounds sarcastic too often but his sarcastic statements are astonishingly true and convincing. 

A number of times I could find exact parallels between what he writes and what I have written earlier in my talks or in my writing, prose or poetry. So many times I have said in the first year class that I don’t want to teach Biology, I want to teach the principles of science only giving examples from biology. But most students attended to complete the biology curricular course. Chargaff says, “… people came to me not to learn about the chemistry of life but to learn about nucleic acids.” In a blog article earlier I wrote my distinction about doing good science versus doing a successful science career. Chargaff writes, “Here I must immediately make a distinction between science as a profession and science as the expression of some of the faculties of the human mind. The two are not necessarily connected.”

In another blog article I wrote about institutional rituals in science which I thought were not different from religion. He writes, “There can, however, be little doubt that the whole complex of the natural sciences has become a substitute religion, fulfilling the double role of mysterious incomprehensibility to the lay public and a means of livelihood for its practitioners.”

I was uncomfortable with the IISER protocol of selecting PhD candidates. I thought hunting for brilliance alone was not enough. PhD is like marriage. The two need to click. Others cannot tell me which qualities I should be looking for in a student. Chargaff says, “It so happens that I have never been very fond of brilliancy. I have been looking for entirely different qualities and I have often found them in people who were not outstandingly clever.”

One thing he repeatedly says is, “Once you embark, you never land. You will, in fact, after a short time, forget that there is such a thing as land; ever changing unattainable horizons will lure you into the unknown that few people, it is true, really want to know. But you are paid to know.”

“How often have I said that only the road counted not the goal”

“I was a monad searching for destiny that did not exist”

Quite independently I too wrote repeatedly

मंज़िल जिसकी अनजानी वो सिरात अभी है मुझमें (A road that does not know a destination is still there in me)

राह जब मंज़िल बने रफ़्तार बेबस हो तो क्या है (When the road itself becomes the destination, how does speed matter?)

What I like the most is his vision of a dark night. He does not think that science is about illuminating the unknown. He thinks it is a search in the darkness. Darkness is what a researcher always lives with and therefore is a friend of. Throwing dazzling lights is not in the spirit of science. “The great biologists worked in the very light of darkness. We have been deprived of this fertile night.”

“Illuminated darkness is not light”

My own favourite couplet is

जुस्ते हक़ की रहगुजर में जो सियाही है, मेरी है

उस मजाज़े आराइश में तेरा ही बस हो तो क्या है

(The darkness on the path to truth is my home-ground. If the dazzling lights in the rest of the world are under your command, why should I care!!)

At many other places, I felt, this is precisely my experience too, but may be I wouldn’t have expressed it this way.

“The sciences are extremely pedigree conscious, and the road to the top of Mount Olympus is paved with letters of recommendation, friendly whispers at meetings, telephone calls at night. From all this I have never been able to benefit. I am, to an unusual extent, my own product.”

“A teacher is one who can show you the way to yourself; and this no one has done for me.”

“At the time the publication appeared, most people – including the Nobel Prize Committee, as it was then constituted – did not pay the slightest attention to it. Those who should have known were all too busy spinning their own tops through the corridors of power. Never having found the entrance to the useful burrows, I was not one of them”

He describes himself as, “…imaginative rather than analytical, apocalyptic rather than dogmatic; brought up to despise publicity; uncomfortable in scientific gatherings; fleeing all contacts; always happier with my younger than with my better….but ever conscious, day and night, that there is more to see than I can see, more to say than I can say and even more to be silent about.”

One characteristic of the Gazal from of poetry is that every couplet is modular. You can interpret it independent of other couplets. Every statement of Chargaff has this modularity. So I will now take the freedom of simply copying some of his lines. There is no risk of interpreting anything out of context.

“Child though I was, I soon became a non-observing spectator, for my eyes had been opened early.”

“My long life in the midst of explanatory sciences has made me tired of explanations”

On the aura created by the DNA double helix model “The orderly, loving and careful study of life had been replaced by a frantic and noisy search for stunts and “break-throughs”.

“Among the thousands of practitioners of science I have met in my life, there were perhaps twenty or thirty to whom I should have granted the name of scientist.”

“The modern American University has become a monstrosity.”

“When I first went to Yale University in 1928, the conviction that wisdom was cheaper wholesale had not yet penetrated to the surface.”

About today’s scientists, “Slaves or prisoners of NIH or NSF, of Xerox and Beckman – they are really the narrowest, the dullest kinds of experts or specialists, they are essentially molecular podiatrists: people who know about the fifteenth foot of the centipede.”

“At the end of the war, hundreds, yes, thousands of “pure scientists” had been used to working in scientific concentration camps.”

“The library is burnt.

……. And still it is too cold here.”

“You always saw both faces of the coin at the same time.

…………. No I was looking for the third face of the coin.”

“The do-gooders have done so much evil that not to do this kind of good has become a virtue”

“Our present natural sciences have nothing to do with nature”

“Every day I am a different man but I wear the same overcoat and that’s what people see.”

“Do you want to imply that most scientists don’t deserve science?

………. Yes but they have made science into something that they deserve”

“I am sure the dinosaurs also had their biohazards committees and they were as effective as ours.”

Black and white perception and the positive side of depression:

In popular literature, movies and theatre, the depicted characters are generally either good or bad. Everything about the good people is good. Everything about the bad people is bad. There is a hero and people on hero’s side are good. There is villain with a set of bad people on his side. The popular perception of good and bad is in black and white. In real life there are all shades of grey, but in popular perception we perceive things in black and white. In the original Mahabharata, for example, we do see the shades of grey for many of the depicted personalities. But in all folk versions of Mahabharata they are all either black or white. Most people perceive political parties and decisions the same way. They are either good or bad.

Why is the popular perception so dichotomous when in reality it is hardly so? Is it because the childhood stories are oversimplified and we grow up listening to them? Is it because things are painted in black and white in stories and movies and therefore we are trained to perceive that way? Or is it because it is in human nature that we innately perceive and label things in black and white and that is simply reflected in literature? Which way goes the arrow of causation? Are we trained to perceive things in black and white because popular literature has it so, or do we have it as an evolved innate tendency and literature only reflects that?

In the first batch of IISER, one student decided to address this question as his final year dissertation project. He had a tough time because in IISER, this was not considered a science question by most faculty. Only molecular biology was science. How can human behaviour be science? But quite undeterred, he pursued the question and had interesting findings. He asked people of various backgrounds to answer a questionnaire. In the questionnaire they had to label various entities as good, bad or shades of intermediate. The entities included mythological characters, historical characters, real life characters along with animals, trees and even non-living entities. It turned out that most people rated everything either as entirely good or entirely bad, very few opting for shades of grey. We expected that with age and with education people will become more realistic and perceive more grey shades, but age and education had little effect. We expected that mythological characters will be viewed more in black and white but real life characters more realistically. That also was not significantly true. The variance in the index of contrast was explained predominantly by the tendency of the respondents. There were some individuals that viewed different shades of grey and this they did for everything real or mythological, human or nonhuman, living or non-living. On the other hand those who viewed in black and white did so across all categories. Our interpretation of the patterns was suggestive of a primary innate human tendency being secondarily reflected in stories. It was an interesting piece of work, no doubt, but a total misfit for IISER. So he got very poor grades for not being able to do good science! Further we also could not publish this study because it did not get the ethics committee clearance.

Nevertheless, I stand amazed at the findings. For an evolutionary biologist it may not be a big surprise. Our perception has not evolved for judgment of truth. It evolved to increase individual fitness. In a social animal that we are, even individual fights quickly take the form of group conflicts. If two individuals fight, others tend to take sides. Taking a side in someone else’s fight has an advantage that you can assess, gain or strengthen your individual social rank at a lower cost. You also build bonds that will help you later if and when you are in conflict yourself. Therefore we have evolved primarily to take sides, not to make impartial judgments. However, the advantage of taking sides aggressively is negatively frequency dependent. As a result, similar to the hawk and dove game, there is frequency dependent selection for some fence-sitters as well. These are presumably people who perceive the shades of grey.

Our tendency to see things in black and white percolates to everything. Cholesterol is seen as bad, although it has so many vital metabolic functions. Dietary sugar or fat is painted as villain. Vitamins are perceived all time good, although hypervitaminosis can cause problems. In psychology people talk about “positive” and “negative” emotions. There are more deceptive terms such as positive or negative energy and so on. Reality is far different than the black and white, positive-negative perception.

Is “depression” good or bad? You might be surprised if I plead for the useful dimension of depression. Again for an evolutionary biologist, it is no surprise. Depression is an evolved state of mind and it evolved because it is adaptive. The adaptive role is quite relevant even today. Depression is demonstrably correlated to creativity and many studies show that. There are several examples of artists, writers, poets and scientists having frequent bouts of depression. The link between depression and creativity is quite natural. You are depressed when your ways to “success” (whatever it means in the prevailing context) are blocked for reasons beyond your control. This is precisely the time to try something new, something unconventional, something that would surprize everyone – perhaps your opponents. This needs creativity. So evolving a neuronal and physiological link between depression and creativity is quite logical.

There is some literature on the depression-creativity link. But there is another “positive” side to depression that I experience, and perhaps has no literature on it. Depression allows me to have a sound sleep. Rarely ever in my life worries and tensions could disturb my sleep. They say sleeplessness increases with age, but so far I have seen no signs. I can still sleep for 10 hours, if I have that much time. Because of a chronic back pain, I can’t lie down for hours. So at times I have to get up in the middle of the night. I have to stand erect, may be walk a few steps like washroom and back, or stretch the body. That generally relieves the pain. Once back to bed, within a few seconds I am fast asleep. What has made me sleepless frequently are ideas, excitements, planning new work, anticipation of exciting results, potentially path breaking results or achievements. Quite a few times solution to a long standing problem has appeared in the middle of the night. I have sometimes got up at midnight to articulate an idea, write a thought or something close to a theorem or may even be a poem.

Losing sleep for any reason is not good for health, and this is precisely where depression is helping me. After years of experience I have learnt that all those creative ideas and ingenious solutions to problems have no value in the field of research. Nobody wants any. People love problems more than solutions. Those who suffer, try to capitalize on the problem. Poor sufferers get help and charity as long as the problem exists. The rich get a big name from the little charity that they do. Journalists get breaking news from the broken people. Writers, poets and artists get a platform to sell their creations. Politicians get votes by blowing up the problem. Above all, scientists and academicians get more grants by making simple problems look complex. So everyone is happy with the problems, why would anyone want a solution?  If anybody offers a simple but effective solution, everyone will attack the solution and see to it that it won’t be allowed to work. Alternatively they will personally attack the one who suggested the solution. How a good solution can come from a bad person? We all know that this is what happens in politics. But In this regard, the field of research is no different.

Even in the field of pure science, hardly anyone is interested in fundamentally new ideas and simple solutions even when they exist. Complex problems get huge funding, so the attempt is to make a simple problem complex by generating lots of data and leaving it under-interpreted or better un-interpreted. This is precisely the on-going trend in mainstream biology. It is currently a field for data generators, not data interpreters. Complex data and complex analysis without much useful insights is what gets published routinely in all flagship journals. If simple insights are available, opportunities of huge funding would be lost. So researchers resist clean interpretations and just keep on generating complex data. Then we leave interpretations to journalists who make simple and wrong interpretations. That is what common people read and perceive as science.

The above thoughts are typical of a depressed mind that almost invariably turns sarcastic. Perhaps the field out there is not that bad, but one cannot deny that even the perspective of the depressed mind has substantial truth in it. To me the depressed interpretation helps in toning down my excitement of finding new things. Since now I know that no one cares for good science, I have stopped getting excited by new findings. I no more feel the urge to articulate ideas as they arise. I am no more eager to complete a model, write code and see the results. Ideas keep on coming as they used to, since that is in my nature, but they no more give me sleepless nights. I know I have thought of certain questions that science is unlikely to ask for a few more decades. I know I have clean interpretations of the huge amount of data messing around. But things like that hardly matter to me now. As a habit I ask questions, think of ideas, work on solutions, develop insights, stumble upon new findings. All this will continue on its own because it is natural. I won’t have to passionately do it anymore. And now, I don’t care whether it gets published or not. I am neither going to get any career advantage by publishing in a high impact journal nor will I lose anything by not getting published. So I can really enjoy doing uncompromised science, all for myself now and have a sound sleep. There is high cost in being active, creative and passionate. Depression saves the cost when returns are unlikely to come and does a balancing and optimizing job.

The dichotomy of positive and negative feelings is an illusion that we are trained to accept as truth. I just gave one example: that depression is not always bad. This is true of almost everything perceived as good or bad. The dichotomous perception of good versus bad, positive versus negative, right versus wrong, happy versus sad vanishes as you find yourself closer to reality. This reality is difficult to share with someone who has not experienced it, someone who takes the illusion of ideology as truth, someone who is still far away from truth. Most researchers live in a world of illusion of science because that gives them success. So very few researchers are likely to understand what I said in this article. Few will bother to read anyway!!

The healing touch of science:

Recently Nature published a survey of mental health of PhD students ( along with an editorial  ( It shows that an alarming proportion of PhD students (36% in one study and 86% in another) suffer from anxiety, depression or other undesirable mental states; a proportion substantially higher than the general population. This is despite the finding that most perceive research as a fascinating field.

This is a surprise as well as no surprise. It is a surprise because the science I know goes exactly the other way. Science brought beauty to my life. I owe the best moments and memories of my life to science. But more than that as a science teacher I have seen so many problems and agonies of young minds being resolved by the pursuit of science. I have dozens of stories but I will relate just a couple of them.

A girl got married quite early (something not a surprise in the Indian society and this was two decades ago) but soon suffered a family disaster and was completely broke. I suspect I have an eye for talented but derailed students. Even in a class of 60, I could easily note that something was wrong with her. Later I asked her what was wrong. She told her unimaginable story. I don’t feel the need to relate that story here, but just that any girl would have collapsed under such a situation. I spent a lot of time talking to her. The only thing I could do was to engage her in science to keep her mind occupied. It worked surprisingly fast. With some stroke of luck, her exploration returned something exciting. She picked up a curious looking colony from a plate and isolated the organism. There was no specific aim, it looked different so it was just a curiosity pursuit. We found an interesting enzyme in that organism that had a completely novel potential industrial application. She filed a patent while still in her second year of B. Sc., presented a conference paper, got a national level award. We tried to take the process to commercialization which did not materialize. But in the course of these events she got her confidence back, had a new motivation, a new meaning for existence. Something pursued only out of curiosity, with no pre-decided objective, paid an unexpected dividend. In due course she graduated, had a good job, got married again and settled well. I don’t count the failure to find a buyer for the patent. Our failure to scale up the process is not a failure for me. This is a success story. One person going from a totally broke, depressed state to a confident and self-reliant new life is the success of research. A PhD was not the outcome of this research, a new life was.

Another boy was in a typical old Hindi movie situation in which he was involved with a girl, and her father refused to allow her to meet with him. At one stage he was seriously considering suicide. I spent a lot of time with him. Again the only tool I had was science. He was creative, had his own ideas.  He graduated, while still in a bad state of mind, but soon developed a techno-concept of his own into a business proposal. His business plans and the initial success was so impressive that the girl’s father got impressed, changed his mind. Ultimately he married the girl he loved. The change was brought about by his creative ideas in science and technology.

I have witnessed much more bizarre types of problems that youngsters go through. Every time the only tool that I could use to help them was science. Every time what they worked on was different, ways of working were different. The projects “failed” quite often. Experiments did not work, ideas did not materialize. Once in while they did, undergraduate students ended up publishing papers or filing patents. But in almost every case the pursuit of science succeeded in making someone’s life. In dozens of cases I could bring someone out of anxiety, depression, confusion, conflicts, strained relations, stress and what not. I am fully convinced that science has a healing touch. The healing effect is unimaginable, miraculous, almost spiritual.

The students who went through such phases are dispersed globally now but many are still in touch and communicate once in a while. They are as convinced as I am that science made the miracle happen. I have many interesting feedbacks. One girl, who had suffered child abuse at an early age and therefore had closed herself to any kind of relationship with anyone, ultimately ended up being in love with someone, marrying and being a mother. She told me once, “While I worked with you and with the team, at some stage I realized men can be good as well.” Another girl, who had lost her mother quite early messaged me one day after returning from the lab, “I feel like having met my mom again!!” Feedbacks like this are the biggest rewards of my life. Nobel prize doesn’t stand anywhere in comparison with them.

All I did was to get them interested in a question, make them own a question, open for them the beauty of logic, experimental design, pursuit of something unknown, the feeling of having achieved something, the spirit of facing failures, at times facing voids. There was more than that. I was always interested in evolution of behaviour, so I kept on talking about human behaviour. Why people are what they are, what is the meaning of a relation, why conflicts arise, why we feel what we feel and the like. Talking about these things with a logical framework was completely new to them. There is a science of emotions and if you understand that you can manage your emotions better. I believe it gave them a new insight, a different way of looking at themselves, a mature analysis of the problems they were facing.

On this background, it should be a real surprise that research students have so much of stress, anxiety, depression. But it’s no surprise for me because I have seen the other side too. Science is a relief, excitement and enjoyment all the time. But is doing a PhD equal to doing science? Science is an exploration, adventure, a journey of the unknown, uncertainty about what is at the other end, uncertainty about how long it will take to solve a problem. Completely contradictory to that is the expectation of completing a thesis in five years, having a complete research plan right at the beginning. In some universities even the title of the thesis is to be given at the time of registration itself. What can be more ridiculous than this? How can you know what you are going to get at the end, even before you begin the investigation? How can you design your research plan for a long period of 5-6 years? In reality, I can design my next experiment only after getting the results of the first. I should have the freedom to completely change my objectives and start investing something else if I serendipitously discover what look more interesting. Starting with prefixed objectives and not having the freedom to change them is wrong. But universities and institutions expect you to spell out you research plans and even register a title of the thesis in advance. In case you want to change, a committee has to approve it!! All this is in complete contradiction with the spirit of research. What you get out from such a system is lots of data, not necessarily new insights. The PhD system does not prepare you for bigger surprises. PhD programme is a paper mill, not an abode of research.

PhD is bound to be stressful because of the unscientific and ritualistic concept of PhD itself. The rituals that one has to follow to make a career in science are the cause of all problems. After having spent my full life in science, I have still not understood why a PhD is necessary to do a science career. The burden of the stereotyped expectations of “finishing” research in five years, publishing two or three papers in “high impact” journals, generating enough stuff for writing a thesis causes the anxiety. Working hard on one’s own ideas is enjoyable. Compulsion to work hard on someone else’s ideas is torturous. The most illogical and often stupid peer reviews that you get after years of painstaking work are depressing. Rejection recommendation by someone who doesn’t even bother to read your manuscript completely is disheartening. Research by itself is not stressful, the social and institutional rituals are.

The answer to the question why I do research should be because I have a question, because there is something funny there which I haven’t understood, because I can see the agonies of someone and feel like trying whether I can find a long term solution. Doing research for getting a PhD is like prostitution, which we institutionalize to replace love.

In literature short stories, poems and even haiku is valid and valued. Writers of these things are no way inferior to writers of novels. But in science only a thesis makes the gateway to a science career. There are short story writers in science as well and that kind of science is very much needed, but they never get a PhD or are not considered for a science position anywhere. If you have a new and interesting theorem that can be stated in three pages, they say it can’t make a “thesis”. I have seen people saying you don’t have sufficient volume of work for a thesis. Is science being sold in gallons? How does the volume of work matter over the novelty of ideas and soundness of logic? I see no basis for the expectation of writing only in the form of a thesis to get a PhD, I don’t see a reason why a PhD should be a necessary qualification for a science career. The only justification is that it is a ritual. It is baptism of the religion of institutionalized science.

People who do science as a religious ritual perhaps deserve all the stress, anxiety and depression.

…. but mangoes are out of syllabus!!

The father of a primary school kid went to his school teacher and said, “ You failed my son in maths? He knew by heart everything that you taught. But you asked a question out of syllabus.”

“No, I didn’t. I only asked whatever was taught in the class.”

“No, he says you taught them sums of purchasing and selling apples, but you asked questions on purchasing and selling mangoes!! How can the kids answer what they have not been taught?”

I am sure you will read this as a joke and would leave it at that. But this is precisely how highly educated people of science often behave. I will relate only a couple of incidents although things like this happen much more frequently.

A few months ago, I communicated a manuscript to BBS (Behavioral and Brain Sciences). This journal publishes many thought provoking articles in the area of psychology, cognition and neuro- behavioural studies. I have thoroughly enjoyed reading many of them quite often. BBS has an impact factor of 15 and odd, if impact factors make any sense. The title of my article was “The evolutionary psychology of scientific publishing: cost-benefit optimization of players in the game”. The article, as the title itself reveals, was about the psychological, behavioural and cognitive aspects of editors’ and reviewers’ decision making. It analysed how optimization principles of behavioural ecology explains the origin of commonly observed biases in peer reviews and editorial decisions. The behavioural and cognitive principles I used in the analysis included many that have been highlighted by articles in BBS itself. I used behavioural optimization models and cited behavioural optimization papers from BBS itself along with others. I also used the principle of “rationalization” again inspired by an excellent article in BBS itself.

I expected a rejection without review for this article and that is precisely what happened. The reason I expected a rejection without review was spelt out in the article itself. Rejection of this article was a testable prediction of the hypothesis in the article itself. So I was glad to receive a rejection, which was very much in support of my hypothesis. But the “reason” given for the rejection was very interesting. It gave a stronger support to the hypothesis in the paper which I had not expected. The email I received from the editor Prof Paul Bloom said “We consider submissions that bear on broad theoretical issues within neuroscience and cognitive science. A discussion of biases in peer review just isn’t a good fit with us.” This is precisely the same phenomenon – mathematics might be the same but mangoes are not in the syllabus. The underlying cognitive processes might be the same, but the example to which you are applying them is not of our interest. The rejection was not based on my analysis being flawed or inadequate. It didn’t say anything about the psychological, cognitive content of the paper. It pretended that there was nothing psychological, behavioural or cognitive in it and it only discussed peer review biases. The article preprint is available here ( ) and the editorial correspondence here ( Readers are free to decided whether the reason or justification given for rejection makes any sense.

Prof Paul Bloom was kind enough this time to allow me publish the correspondence. In an earlier interaction he had objected to make public our correspondence on rejection of an article which was about how alterations in interactions of neuropeptides in the brain that have evolved for foraging optimization are responsible for the prevalent global obesity epidemic. Paul had rejected this paper saying that BBS does not publish many articles on the same topic. In the previous year BBS had published an article on obesity and this was the reason given for rejecting our manuscript. Interestingly within a few months of rejecting our manuscript another one on the same topic was accepted and I happened to receive a call for commentary on that article!! So BBS does not publish more than one article in the same field was obviously not true. Our article on foraging optimization and obesity was published later elsewhere which is available here ( ) and the rejection related correspondence here ( ).

This is not to blame any editor or journal. This is an interesting behavioural phenomenon. Every editor works in a set of constraints and the cost-benefit optimization under those constraints decides how editorial decisions are made. But we all pretend as well as believe that editorial decisions are based on the merit of the manuscript alone. Further by well documented principles of psychology, the contextual behavioural reasons behind the act are not completely known even to the actor. This is a well demonstrated phenomenon in cognitive science. The actor does not know the true reasons behind a decision to act. But if the context demands so, one or more reasons are invented to justify the act. A decision is not based on a set of consciously perceived reasons. The decision comes first and “reasons” come later. BBS itself has published excellent reviews on this phenomenon. If this is a fundamental psychological phenomenon, obviously BBS editors are not an exception. They have a set of reasons for rejecting a manuscript which they themselves are not fully aware. But they are compelled to give some reason so they hunt for one. Fortunately or unfortunately hardly anybody challenges the reason behind the editorial decision. So they can get away by giving illogical or self-contradicting reasons. I did not challenge the editorial decision to reject, but I did challenge the “reason” given with obvious evidence that it was not true. I did not challenge it out of anger or frustration triggered by rejection but because I wanted to probe the editor’s behaviour a little more.

Hopefully the editors of BBS, being psychologists themselves, are in a position to understand the behavioural analysis behind editorial processes and therefore won’t take this as a personal criticism. What interests me is the fact that a person follows the same behavioural patterns even after knowing that it is driven by some evolved subconscious mechanisms. But I don’t believe in behavioural determinism. We do have the ability to consciously control our behaviour, which journal editors certainly have, but currently there is no incentive for doing so. Only if the editorial process is made completely transparent, there will be a pressure on editors to be more responsible, logical, consistent and perhaps somewhat honest in justifying their decisions. Biases in scientific publishing will substantially reduce if not eliminated by this single measure. I have written earlier about how transparency in the editorial process can be brought in (See the preprint and my earlier blog articles: ; ). If we do so, the phenomenon of “mangoes are not in the syllabus” will be seen less commonly.

शेतकरी आधार-ईनाम योजना Farmer Support cum Reward Scheme

शेती अर्थकारण आणि शेतक-याच्या मानसिकतेत आमूलाग्र बदलासाठी:

शेतीवर शासन वेगवेगळ्या स्वरूपात बरीच गुंतवणूक करते. ती सबसीडी, कर्जमाफी, दुष्काळग्रस्तांसाठी योजना, पीक विमा, शेतीविषयक संशोधन अशा अनेकविध स्वरूपामधे केली जाते. तरीही बहुसंख्य शेतक-यांची आर्थिक परिस्थिती दारिद्र्याची आणि अस्थिर आहे. आजच्या परिस्थितीत शेतीला आधाराची आवश्यकता तर आहेच पण आधारचं स्वरुप असं असलं पाहिजे की आधारामुळे परावलंबित्व, दुबळेपणा आणि नेहमीच शासनापुढे हात पसरण्याची वृत्ती वाढता कामा नये. आजपर्यंत शेतक-यांना ज्या स्वरूपात सहाय्य देण्यात आले त्याचे स्वरुप शेतक-याला पांगळे आणि लाचार करणारे होते. शेतक-याला आत्मनिर्भर करणा-या आधाराची योजना इथे मांडत आहोत.

यापूर्वी २००८ सालापासून आम्ही वन्यजीव अभयारण्याजवळील शेतक-यांबरोबर काम करताना वन्यप्राण्यांपासून होंणा-या पीक विनाशावर तोडगा शोधण्याचा प्रयत्न केला. यातून एक अभिनव योजना सुचली आणि ती आम्ही गेली दोन वर्षे दोन गावांमध्ये राबवीत आहोत. या योजनेमुळे वन्यप्राण्यांचा उपद्रव तसाच असूनही दोन वर्षांत शेतीचे उत्पादन लक्षणीय रित्या वाढले. या योजनेमुळे अधिक चांगल्या पद्धतीने शेती करणे, उत्पादन वाढवणे आणि अधिक स्वयंपूर्ण होण्याच्या दिशेने शेतक-यांची मानसिकता तयार झाली. या अनुभवावरून असे वाटले की वन्यजीवांच्या समस्येच्या पलिकडे जाऊन शेतीच्या सर्वंकष विकासासाठी अशाच तत्वांवर आधारित योजना राबविता येईल. त्यातून दुष्काळ, पिकांचे रोग, पूर आणि इतर कोणत्याही प्रकारचे नुकसान झाल्यास आधार मिळेल आणि त्याचबरोबर कष्टाने अधिक उत्पादन घेणा-यास उत्पादकतेच्या प्रमाणात ईनामही मिळेल. संकटाच्या प्रमाणात आधार मिळेल आणि घेतलेल्या कष्टांच्या प्रमाणात ईनाम. त्यामुळे अधिक कष्ट आणि योग्य मशागत करण्यास प्रोत्साहन मिळेल आणि त्याचबरोबर नुकसान करणारे संकट आल्यास सर्वनाशाला सामोरे जावे लागणार नाही. ही सर्व योजना संगणकाकडून स्वयंचालित रीतीने राबविणे शक्य असल्यामुळे शासनयंत्रणांवर कमीतकमी ताण पडेल आणि भ्रष्टाचार होण्यास वाव राहणार नाही. शासन कृषि क्षेत्रासाठी सबसिडी, कर्जमाफी या स्वरूपात जो खर्च करते तो या मार्गाने केल्यास तेवढ्याच खर्चाचे अधिक फळ पदरी पडेल. सर्व प्रकारच्या नुकसानीविरुद्ध आधार आणि अधिक उत्पादकता दाखविणा-यास पारितोषिक एकाच योजनेमधून मिळत असल्यामुळे वेगळ्या पीक विमा, सबसिडी, कर्जमाफी सारख्या योजनांची गरज कालांतराने संपून जाईल.

शेतीचे नुकसान दोन प्रकारच्या कारणांनी होते. एका प्रकारची कारणे पूर्णपणे दैवाधीन असतात. पूर, गारपीट, तीव्र दुष्काळ अशा गोष्टी यात येतात. दुस-या प्रकारची कारणे अशी असतात की योग्य वेळी योग्य प्रयत्न केले तर नुकसान पूर्णपणे नाही तरी ब-याच प्रमाणात टाळता येते. पिकांचे रोग, कीड, वन्यप्राण्यांकडून होणारे नुकसान हे यात येतात. पाण्याच्या योग्य नियोजनाने दुष्काळाचे परिणामही कमीतकमी कसे जाणवतील हे पाहता येते. या सगळ्या संकटांमधे शेतक-याच्या कष्टाला आणि शहाणपणाला महत्व आहे. असे प्रयत्न करूनही नुकसान पूर्णपणे टाळता येत नाही. पण ज्याने शहाणपणा आणि कष्टानी जास्तीत जास्त पीक वाचवलं आहे त्याच्या कष्टांचं कौतुक व्हायला हवं म्हणजे इतरांना त्याचं अनुकरण करण्याची प्रेरणा मिळेल. सगळ्यांना सरसकट भरघोस मदत दिली तर असं होणार नाही. सरसकट सारखी मदत देणे हा अधिक कष्ट घेणा-या शेतक-यावर एक प्रकारे अन्यायच आहे. आपली योजना अशी पाहिजे की अधिक कष्ट घेणा-या शेतक-याला अधिक मिळेल. हेच आमच्या मॉडेलचं तत्व आहे.  

ही योजना गणित, संख्याशास्त्र, अर्थशास्त्र आणि मानसशास्त्रातील तत्वांवर आधारित असून शेतकरी गट ती थोडया प्रशिक्षणानंतर स्वतःच राबवू शकणार आहेत. सर्व व्यवस्थेचे संगणकीकरण शक्य असून शेतकरी गटाला internet किंवा mobile app वरतीसुद्धा त्याचा लाभ घेता येईल. यासाठी लागणारा data शेतका-यांनीच संघटितपणे गोळा करायचा असून त्यावर आधार तथा ईनाम रक्कम संगणकीय प्रणालीद्वारे ठरवली जाऊन शेतका-याच्या बैंक खात्यात परस्पर जमा होईल. कुणाकडे तक्रार करण्याचं, कुणाचे उपकार घेण्याचं, आंदोलन करण्याचं, त्यावरून राजकारण करण्याचं कारणच राहणार नाही. स्वतःच्या data ची नोंदणी करताना शेतकरी ती प्रमाणिकपणे करतील याची व्यवस्था या योजनेत अंगभूत आहे कारण त्यातील विशिष्ट गणिती तत्वाप्रमाणे प्रमाणिक नोंद करणा-यास सर्वाधिक लाभ मिळेल. या योजनेसाठी निधी शासनाने उपलब्ध करावयाचा असला तरी शासकीय यंत्रणांवर त्याच्या अंमलबजावणीचा ताण कमीतकमी असेल. कारण जवळ जवळ सर्व व्यवहार गणिती आणि संख्याशास्त्रीय तत्वांप्रमाणे संगणक आपोआप करेल. या योजनेमागाची तत्वे आणि थोडक्यात अंमलबजावणीचे स्वरुप खालीलप्रमाणे.

योजनेचे मूळ सूत्र असे की एखाद्या वर्षी शेतीच्या एका पट्ट्यामधील एका प्रकारच्या पिकाच्या सरासरी उत्पादनात तूट असल्यास त्या तुटीच्या प्रमाणात आधार रक्कमेची टक्केवारी ठरवली जाईल. प्रत्येक शेतक-याला त्याच्या स्वतःच्या उत्पादनाच्या तितके टक्के ही रक्कम दिली जाईल. त्यामुळे ज्या प्रांतात दुष्काळ, पिकाचे रोग, वन्य प्राण्यांकडून पिक खाल्ले जाणे इत्यादी कारणांमुळे नुकसान झाले असेल तिथे सरासरी नुकसानीच्या प्रमाणात आधार रक्कम मिळेल. पण ज्याने त्या संकटामधूनही अधिक चांगले उत्पादन घेतले असेल त्याला उत्पादकतेच्या प्रमाणात अधिक लाभ मिळेल. जिथे सरसरीमधे घट नाही तिथे काही देण्याची गरज राहणार नाही. म्हणजे कोणत्या भागात मदतीची गरज आहे आणि ती किती प्रमाणात आहे याचा निर्णय data प्रमाणे संगणकाकडून आपोआप घेतला जाईल. यावर राजकारण होऊ शकणार नाही.

  • योजना राबविणारी मुख्य यंत्रणा शेतक-यांचे गट ही असेल. एका भागात राहणा-या एक प्रकारच्या माती आणि पाऊसमानात शेती करणा-या आणि सारखे पीक घेणा-या शेतक-यांचा एक गट अशी गटाची व्याख्या असेल. गटाची बांधणी शेतक-यांनी स्वतःच्या पुढाकाराने करावयाची असून ती शेतीच्या हंगामाला सुरुवात होण्यापूर्वीच करावयाची आहे. साधारणतः सारखा धोका सारखी परिस्थिती असलेल्या शेतक-यानी एक गट करावयाचा आहे. गटात सामिल होणे पूर्णपणे ऐत्छिक राहील. या गटाची अत्यंत साध्या पद्धतीने ऑनलाइन नोंदणी होईल. त्यात प्रत्येकाचा सात बारा, घेत असलेले पीक, पिकाखालील क्षेत्र, बैंक खाते क्रमांक, आधार क्रमांक असा आवश्यक तेवढाच data असेल.
  • हंगामाच्या शेवटी प्रत्येक शेतकरी आपले एकूण उत्पादन नोंदवेल. त्यावर जवळील पाच शेतकरी ही नोंद बरोबर असल्याचे प्रमाणित करतील. ही स्वयंनोंदणी हा dataचा मुख्य source असेल. ही नोंदणी ऑनलाइन किंवा mobile app वरून सुद्धा करता येईल. आवश्यकता वाटल्यास गटातील फक्त २ ते ५ शेतक-यांच्या उत्पादनाचा पंचनामा शासकीय अधिकारी करू शकतील.
  • या नोंदणीप्रमाणे या भागातील सरासरी उत्पादनात तूट आहे का व आधार देण्याची आवश्यकता आहे का याचा निर्णय संगणकीय प्रकिया आपोआपच घेईल आणि जेथे आवश्यक तेथे प्रत्येक शेतका-यास देय रक्कम काढेल. याचे सोपे सूत्र असे.

Xavg = average expected yield or productivity standard determined a priori.

Yavg = average yield per unit area from all farmers of the group computed from the uploaded data.

Yi = ith farmer’s yield.

v = market value/standard rate of the produce.

याप्रमाणे योग्य रक्कम शेतक-याच्या बैंक खात्यात शासकीय निधीमधून आपोआपच जमा होईल. ही सर्व व्यवस्था संगणकीकृत आणि सम्पूर्ण स्वयंचलित असेल. त्यामुळे या निर्णयावर राजकारण होऊ शकणार नाही. सर्व नोंदणी, हिशेब व व्यवहार पारदर्शक असतील आणि सर्वांना सर्व माहिती ऑनलाइन उपलब्ध असेल.

शेतकरी आपल्या उत्पादनाची नोंदणी प्रमाणिकपणे करतील कशावरून? या प्रश्नाचे उत्तर सोपे आहे. आधार रक्कम स्वतःच्या उत्पादनाच्या टक्केवारीप्रमाणे मिळत असल्यामुळे उत्पादन कमी दाखविण्यात शेतक-याचा स्वतःचाच तोटा आहे. त्यामुळे खोटे नुकसान दाखवून अधिक शासकीय मदतीचा दावा करण्यावर आपोआपच आळा बसेल. स्वतःचे उत्पादन जास्ती दाखविण्याचा मोह शेतक-याला होऊ शकेल. पण उत्पादन जास्ती दाखवल्यावर सरासरीमधील तफावत कमी होउन प्रत्येकालाच कमी लाभ मिळेल. प्रत्येक शेतक-याची स्वयंनोंदणी इतर पाच शेतक-यांनी प्रमाणित करावयाची असल्यामुळे तेच याला आळा घालतील. तसे न केल्यास त्या गटाचा लाभ आपोआपच कमी होइल. म्हणून प्रामाणिक नोंदणी हाच या योजनेचा लाभ घेण्याचा सर्वोत्तम मार्ग आहे. प्रत्यक्षातल्या उत्पादनापेक्षा कमी उत्पादन दाखवणा-या किंवा जास्त दाखवणा-याचा आपोआपच तोटा होणार  आहे. त्यामुळे प्रमाणिकपणे स्वतःच्या उत्पादकतेची नोंदणी करणे हा एकमेव लाभाचा पर्याय शेतक-याला उपलब्ध असणार आहे. योजना प्रमाणिकपणे राबविली जाते आहे याची खात्री करण्यासाठी फारफार तर थोडया नमूना केसेसचे प्रत्यक्ष पंचनामे आधी न कळवता करता येतील. म्हणजे तसा अधिकार शासकीय यंत्रणांकडे राहील पण त्याचा उपयोग करण्याची गरज क्वचितच पडेल. एखाद्या गटाने अप्रामाणिकपणे वागून योजनेचा गैरफायदा घेण्याचा प्रयत्न केला तर त्याचे प्रतिबिंब विशिष्ट संख्याशास्त्रीय मानकांमधे पडतेच (The nature and parameters of statistical distributions will be different if people enter cooked up data) आणि संगणकाला ते ओळखता ही येते. त्यामुळे कुठे अप्रामाणिकपणा वाढू लागलाच तर संगणक आपणहोउनच धोक्याची घंटा वाजवेल. थोडक्यात अप्रामाणिकपणा आणि भ्रष्टाचार याला मुळातूनच वाव राहणार नाही आणि कुठे झालच तर ते ओळखणंही अवघड राहणार नाही. (पण कदाचित याच कारणासाठी राजकीय पक्ष आणि नोकरशाहीचा अशा योजनांना विरोध राहील. काळ्याचे पांढरे करण्यासाठी शेती उत्पन्न दाखवणा-यांनाही या योजनेतून काही फायदा नाही. त्यामुळे अशा घटकांचा या योजनेला विरोधच राहील. पण सामान्य लोकांच्या दबावामधूनच अशा योजना अमलात येऊ शकतील.)

सर्वात महत्वाचे म्हणजे आपल्या उत्पादकतेच्या प्रमाणात लाभ मिळत असल्यामुळे उत्पादकतावाढीला प्रत्यक्ष उत्तेजन मिळेल. आधीच्या दोन गावांमधील दोन वर्षांच्या चाचणीमध्ये उत्पादन वाढल्याचे दिसून आलेच आहे. पण त्याहून महत्वाचे म्हणजे आपण स्वतःच अभ्यास व मोजमापे करून काटेकोर नोंदणी ठेवण्यास शेतक-यांनी पुढाकार घेण्यास सुरुवात केल्याचे दिसून आले आहे. त्यासाठी शेतकरी समाजामधील तरुणांनी जीपीएस वापरणे आणि लैपटॉपवर data entry करायला शिकण्याची तयारीही दाखवली. हा मोठाच सकारात्मक बदल आहे. आमच्याकडून या योजनेचा बारकाईने विचार आणि अभ्यास करण्यात आला असून या योजनेचा गैरफायदा घेण्याचे कुठले मार्ग असू शकतात आणि ते प्रभावीपणे कसे बंद करता येतील यावरचा एक शोधनिबंध प्रसिद्ध झाला आहे.

या योजनेला दुसरा एक मोठा data चा स्रोत साथ देऊ शकतो तो म्हणजे सॅटॅलाइट कडून मिळणा-या जमिनीच्या प्रतिमा. सर्व प्रकारचे नुकसान यात कळत नाही पण महापूर अतिवृष्टी सारख्या संकटांचे स्पष्ट चित्र उमटते. ज्याच्यावर आपले काहीच नियंत्रण नसते अशा कारणांनी नुकसान झाले असेल तर वापरले जाणारे गणिती सूत्र थोडे वेगळे असेल. त्यात स्वतःच्या उत्पादनाच्या प्रमाणात ईनाम मिळणे असणार नाही. म्हणजे एकीकडे शेतक-यांनी गट करून स्वतः केलेल्या नोंदी आणि दूसरीकडे सॅटॅलाइट कडून मिळणारी माहिती याचे योग्य प्रकारे एकत्रीकरण करण्याचे गणित बांधले तर संगणकच कुठे, कुणाला किती मदत हवी ते ठरवू शकतो. ते सुद्धा शेतीतील शहाणपण, समजूत, कष्ट यांना झुकते माप देउन. पंचनामे आणि त्यावर राजकारण करण्याची गरज राहणारच नाही.

शेतक-याला किती पैसे मिळाले यापेक्षा कितीतरी अधिक महत्वाचा मानसिक घटक या योजनेत आहे. तक्रार अर्ज दाखल करून त्यावर कुणाचे तरी उपकार घेण्यामधे एक प्रकारची भिकेची भावना असते. या योजनेत अर्ज करायचा नाहीये. कष्ट करूनही दुर्दैव आड आलं तर त्या दुर्दैवाच्या प्रमाणात सारा देश आपण होउन शेतक-याला त्याच्या कष्टाचं हुकलेलं फळ देऊ करतो आहे असा त्याचा भावनिक अर्थ आहे. भीक आणि कष्टाचं फळ यातला फरक शेतक-याला फार चांगला समजतो. समाजानी, राज्यकर्त्यांनी शेतक-याला मदतीची भीक घालायची नाहीये, त्याच्या कष्टाच्या फलाचा भरोसा द्यायचाय, तो ही न मागता असा या योजनेचा अर्थ आहे.

योजनेच्या धोरणात्मक भागामध्ये वेगवेगळ्या क्षेत्रात कोणत्या पिकाला उत्तेजन द्यावे, पिकाचे उत्पादनउद्दिष्ट काय ठेवावे, पिकाचे अधारमूल्य ठरवावे की नाही अशा गोष्टींबद्दल धोरणात्मक निर्णय घेऊन, शेतक-याच्या व्यक्तीस्वातंत्र्याला धक्का न लावता राज्यातील शेतीला योग्य व भविष्यवेधी आकार देता येईल. योजनेला मूर्त स्वरुप देण्यासाठी अनेक बारकाव्यांचा विचार करून योग्य प्रकारची संगणकीय प्रणाली बनवून घेऊन त्याचे व्यवस्थापन करावे लागेल. एकदा व्यवस्थापकीय ढाचा काळजीपूर्वक तयार केला की त्यापुढचे व्यवस्थापन स्वयंचलित प्रणालींमुळे अगदी सोपे असेल. त्यासाठी कमीतकमी माणसे आणि कमीतकमी शासनयंत्रणा लागेल. एकीकडे अत्यंत सोप्या आणि प्रभावी पद्धतीने शेतीला संकटात विम्यापेक्षा प्रभावी आधार देणारी, दुसरीकडे उत्पादकतेला प्रोत्साहन देणारी आणि त्यावर शेतका-याला सक्षम, प्रमाणिक आणि संघटित राहण्यास उत्तेजन देणारी ही योजना भारतीय शेतीमधे आमूलाग्र बदल घडवून आणू शकेल.

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 ( 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.