May Days

A huge thank you to everyone who bought from me at the recent Decorative Living Fair up in Kent; it was a most enjoyable fair! Perhaps I shall meet some of you again if you come down to Cornwall for your summer holidays.....

 It's time I took you on a tour of the shop again.....
 Spring flowers and sunshine!



 New porcelain vessels by Rebecca Harvey, and recycled glass bead bracelets,




 new Liberty fabrics and old fabric bundles,

 and one of Wendy's handmade dolls. the hair is pure Wensleydale sheep's wool - just gorgeous!
Happy Bank Holiday weekend everyone!

The Sea Garden will be open daily 1-5pm
26th May - 5th June

SEN UMUT ETMEYE DEVAM ET

İlk defa  2009 yılında tamamen tesadüfen (Bebek girişinin önünden geçiyorduk ) fark ettiğimiz kapısından  içeriği dalmak suretiyle gördüğüm bir okuldu Boğaziçi üniversitesi.  Üniversiteye dair hayalleri olan liseli genç insanlardık. Ziyaretimiz çok ünlü birini görüp fotoğraf çektirme isteğine benzer bir istek yaratmıştı hepimizde. Birçok köşesinde fotoğraf çektirip hayaller kurduk.
 Sonra zaman geçti ve hepimiz başka başka okulların kapısından, kendi hayatımıza daldık paldır küldür.  Ben de Bilgi Üniversitesine başladım , bir çocukluk dolusu hayalle. 11 Mayıs günü gerçekleşen 13.Radyo Boğaziçi Müzik Ödülleri töreninin ardından düşünürken aklıma ilk gelen şey o ilk Boğaziçi deneyimim oldu.
 Aradan geçen 7 senede bir sürü şey değişmişti. Biz hala öğrenci olsak da ödül alan ‘’Joytürk Akustik’’ekibi  olarak davetliydik. Güler yüzlü şahane kadın ve erkek öğrenciler bizi kapıda karşıladılar ve bizler için -ödül alan davetliler için- hazırlanılmış kulis dedikleri alana yönlendirdiler.Yıllar sonra yeniden Boğaziçi Üniversitesinde ama bu sefer  yaptığı iş ödüllendirilmiş bir ekibin bir parçasıydım, akustik bir programın nasıl çekildiğini biliyordum ve belki 7 sene önce yolda karşılaştığımda heyecanlandırıp fotoğraf çektirmek isteyebileceğim tanınmış kişilerle aynı taraftaydım. İşimizi biz de iyi yapmıştık ve ödüllendirilecektik.
  Ödül töreni tam bize söylenildiği saatte başladı. Hiçbir aksaklık olmadan kimseyi sıkmadan tertemiz bir akışta devam etti. Okan Bayülgen konuşması ile ödül töreninin organizasyonunda çalışan öğrencileri tebrik etti. -Tam bu noktada bir kulis bilgisi vereyim hemen, başka ödül törenleri Radyo Boğaziçi gibi ‘’cool’’ geçmiyormuş, ben henüz diğerlerini görmedim ama Okan Bayülgenin yalancısıyım, ödüllendirmelerde çok adil olunduğunu da söyledi‘’ -  Birçok sanatçı ile birlikteydik ama Nükhet Duru ile aynı sahnede olmak da ayrıca heyecan vericiydi benim için. Düşünsenize Türkiye popüler müziğinin çok büyük bir kısmına ve birçok değişime tanıklık etmiş bir isim ile yeni medyanın geliştiği günümüzde internet müzik kanallarında yayınlanan videolar çeken biz öğrenciler  aynı sahnede ödül aldık. Umut vericiydi bence hepimiz için. Neden olmasın ki değil mi ?
  Öğrencilerle ortak yürütülen ve profesyonel bir iş olan ‘’Joytürk Akustik’’  sınavlarla ölçülemeyecek bir tecrübe hepimiz için. Her hafta profesyonel yaşama bir adım daha yaklaştıran ama  amatör heyecanımızın hep devam ettiği bir ders aynı zamanda.
Başta söylemiştim Bilgi’ye  koca bir  çocukluk dolusu hayalimle girdim diye, şimdi yetişkinlik dolusu hayalle mezun olmaya hazırlanıyorum.
 Organizasyonundan, katılımcılarına kadar son derece kaliteli bir ödül töreninin ardından o hayallerime bir yenisi eklendi.

  Bir gün çok severek okuduğum bölümümün düzenleyeceği Televizyon ödüllerinde görüşürüz belki de kim bilir :)

Another look at 'complexity'

A fascinating and clear description of one contemporary problem of sciences involved in 'complexity' can be found in an excellent discussion of how brains work, in yesterday's Aeon Magazine essay ("The Empty Brain," by Robert Epstein).  Or rather, of how brains don't work.  Despite the ubiquity of the metaphor, brains are not computers.  Newborn babies, Epstein says, are born with brains that can learn, respond to the environment and change as they grow.
But here is what we are not born with: information, data, rules, software, knowledge, lexicons, representations, algorithms, programs, models, memories, images, processors, subroutines, encoders, decoders, symbols, or buffers – design elements that allow digital computers to behave somewhat intelligently. Not only are we not born with such things, we also don’t develop them – ever.
We are absolutely unqualified to discuss or even comment on the details or the neurobiology discussed.  Indeed, even the author himself doesn't provide any sort of explanation of how brains actually work, using general hand-waving terms that are almost tautologically true, as when he says that experiences 'change' the brains.  This involves countless neural connections (it must, since what else is there in the brain that is relevant?), and would be entirely different in two different people.

In dismissing the computer metaphor as a fad based on current culture, which seems like a very apt critique, he substitutes vague reasons without giving a better explanation.  So, if we don't somehow 'store' an image of things in some 'place' in the brain, somehow we obviously do retain abilities to recall it.  If the data-processing imagery is misleading, what else could there be?

We have no idea!  But one important thing is that this essay reveals is that the problem of understanding multiple-component phenomena is a general one.  The issues with the brain seem essentially the same as the issues in genomics, that we write about all the time, in which causation of the 'same' trait in different people is not due to the same causal factors (and we are struggling to figure out what they are in the first place).

A human brain, but what is it?  Wikipedia

In some fields like physics, chemistry, and cosmology, each item of a given kind, like an electron or a field or photon or mass is identical and their interactions replicable (if current understanding is correct).  Complexities like the interactions or curves of motion among many galaxies each with many stars, planets, and interstellar material and energy, the computational and mathematical details are far too intricate and extensive for simple solutions.  So one has to break the pattern down into subsets and simulate them on a computer.  This seems to work well, however, and the reason is that the laws of behavior in physics apply equally to every object or component.

Biology is comprised of molecules and at their level of course the same must be true.  But at anything close to the level of our needs for understanding, replicability is often very weak, except in the general sense that each person is 'more or less' alike in its physiology, neural structures, and so on. But at the level of underlying causation, we know that we're generally each different, often in ways that are important.  This applies to normal development, health and even to behavior.  Evolution works by screening differences, because that's how new species and adaptations and so on arise.  So it is difference that is fundamental to us, and part of that is that each individual with the 'same' trait has it for different reasons.  They may be nearly the same or very different--we have no a priori way to know, no general theory that is of much use in predicting, and we should stop pouring resources into projects to nibble away at tiny details, a convenient distraction from the hard thinking that we should be doing (as well as addressing many clearly tractable problems in genetics and behavior, where causal factors are strong, and well-known).

What are the issues?
There are several issues here and it's important to ask how we might think about them.  Our current scientific legacy has us trying to identify fundamental causal units, and then to show how they 'add up' to produce the trait we are interested in.  Add up means they act independently and each may, in a given individual, have its own particular strength (for example, variants at multiple contributing genes, with each person carrying a unique set of variants, and the variants having some specifiable independent effect).  When one speaks of 'interactions' in this context, what is usually meant is that (usually) two factors combine beyond just adding up.  The classical example within a given gene is 'dominance', in which the effect of the Aa genotype is not just the sum of the A and the a effects.  Statistical methods allow for two-way interactions in roughly this way, by including terms like zAXB (some quantitative coefficient times the A and the B state in the individual), assuming that this is the same in every A-B instance (z is constant).

This is very generic (not based on any theory of how these factors interact), but for general inference that they do act in relevant ways, it seems fine.  Theories of causality invoke such patterns as paths of factor interaction, but they almost always assume various clearly relevant simplifications:  that interactions are only pair-wise, that there is no looping (the presence of A and B set up the effect, but A and B don't keep interacting in ways that might change that and there's no feedback from other factors), that the size of effects are fixed rather than being different in each individual context.

For discovery purposes this may be fine in many multivariate situations, and that's what the statistical package industry is about. But the assumptions may not be accurate and/or the number and complexity of interactions too great to be usefully inferred in practical data--too many interactions for achievable sample sizes, their parameters being affected by unmeasured variables, their individual effects too small to reach statistical 'significance' but in aggregate accounting for the bulk of effects, and so on.

These are not newly discovered issues, but often they can only be found by looking under the rug, where they've been conveniently swept because our statistical industry doesn't and cannot adequately deal with them.  This is not a fault of the statistics except in the sense that they are not modeling things accurately enough, and in really complex situations, which seem to be the rule rather than the exception, it is simply not an appropriate way to make inferences.

We need, or should seek, something different.  But what?
Finding better approaches is not easy, because we don't know what form they should take.  Can we just tweak what we have, or are we asking the wrong sorts of questions for the methods we know about?  Are our notions of causality somehow fundamentally inadequate?  We don't know the answers.  But what we now do have is a knowledge of the causal landscape that we face.  It tells us that enumerative approaches are what we know how to do, but what we also know are not an optimal way to achieve understanding.  The Aeon essay describes yet another such situation, so we know that we face the same sort of problem, which we call 'complexity' as a not very helpful catchword, in many areas.  Modern science has shown this to us.  Now we need to use appropriate science to figure it out.

Hint Filmi: Fan



 Öncelikle Shahrukh Khan hayranı olmadığımı belirteyim azizim. En azından üç büyük Khan krallığında Aamir Khan ve Salman Khan'dan sonra gelir bende. 

  İşte ne bileyim, bir Benim Adım Khan filmini öyle dolu dolu izledim,  bir de Fan'ı. Dur filmi anlatacağım, bir içimi dökeyim de. 

   Bu ademin en son Swades'ini izlemiştim, oflaya puflaya. Veer Zaara'yı sonlara doğru, Jab Tak Hai Jaan'ı yarıda, Om Shanti Om'u da  çeyrekte bırakmıştım. Devdas'a ne oldu hatırlamıyorum. (Enee Aishwarya Rai vardı onda, gitti gül gibi film). 

    Bende mi sorun var acep? Neyse olur öyle şeyler. Zamana bırakmıştım, iyi de etmişim. Bir Fan geldi, tekrar heyecanlara saldı beni. Çok beğendim, büyük bir zevkle izledim!


  Aryan, Hindistan'ın meşhur aktörü. Gaurav ise ona çok benzeyen, hayranı olan, hayır bu hafif kalır,  manyağı olan bir genç. (Bu arada Gaurav da Shahrukh'un kendisiymiş, her çekim öncesi 4 saatlik bir makyaj harikası). 

   Sanatçıların benzerleri yarışmasında ödül alıyor ve  ödülünü  Aryan'a sunmak, fotoğraf çektirmek, abi ben sana hayranım, bir imza be güzel abim demek için Delhi'ye yola çıkıyor.


   Aryan'la görüşebiliyor mu peki?  
Görüşmek ne kelime, adamın burnundan getiriyor, ünlü olduğuna pişman ediyor. 

 Aryan'ın "Benim hayatım, benim zamanım. Neden sana beş saniyesini vereyim ki?" cümlesiyle Gaurav'da film kopuyor. 
(Ne kadden zalım bir Aryan)
    Vay sen misin bunu diyen! Şimdiye kadar ben senin peşinden koştum. Bundan sonra sen benim peşimden koşacaksın! 
  Filmin bütün aksiyonu burda başlıyor. Sözünün eri Gaurav, Aryan'ın ününü dibinden sıyırıyor, hafakanlara gark ediyor.


  Heyecanı, koşturması bitmeyen bir film ama ben yer yer duygulandım, acıdım Gaurav'a. Özellikle son sahnelerde. Aryan'a ise hep kızdım. Bir özür dile, razı çocuk. Yok... Soykası batasıca hoşşik.

 Peki savaşa dönüşen bu oyunu kim kazanıyor? Aksiyonun bittiği dramatik nokta burası... İkisi de kaybediyor.



  Hulâsa-i kelam film özetle diyor ki, biz fanlar olmadan siz ünlüler bir hiçsiniz! 

Doğru söz vesselam... ❤










What do rising mortality rates tell us?

When I was a student at a school of public health in the late '70s, the focus was on chronic disease. This was when the health and disease establishment was full of the hubris of thinking they'd conquered infectious disease in the industrialized world, and that it was now heart disease, cancer and stroke that they had to figure out how to control.  Even genetics at the time was confined to a few 'Mendelian' (single gene) diseases, mainly rare and pediatric, and few even of these genes had been identified.

My field was Population Studies -- basically the demography of who gets sick and why, often with an emphasis on "SES" or socioeconomic status.  That is, the effect of education, income and occupation on health and disease.  My Master's thesis was on socioeconomic differentials in infant mortality, and my dissertation was a piece of a large study of the causes of death in the whole population of Laredo, Texas over 150 years, with a focus on cancers.  Death rates in the US, and the industrialized world in general were decreasing, even if ethnic and economic differentials in mortality persisted.

So, I was especially interested in the latest episode of the BBC Radio 4 program The Inquiry, "What's killing white American women?" Used to increasing life expectancy in all segments of the population for decades, when researchers noted that mortality rates were actually rising among lower educated, middle-aged American women, they paid close attention.

A study published in PNAS in the fall of 2015 by two economists was the first to note that mortality in this segment of the population, among men and women, was rising enough to affect morality rates among middle-aged white Americans in general.  Mortality among African American non-Hispanics and Hispanics continued to fall.  If death rates had remained at 1998 rates or continued to decline among white Americans who hadn't more than a high school education in this age group, half a million deaths would have been avoided, which is more, says the study, than died in the AIDS epidemic through the middle of 2015.

What's going on?  The authors write, "Concurrent declines in self-reported health, mental health, and ability to work, increased reports of pain, and deteriorating measures of liver function all point to increasing midlife distress."  But how does this lead to death?  The most significant causes of mortality are "drug and alcohol poisonings, suicide, and chronic liver diseases and cirrhosis."  Causes associated with pain and distress.


Source: The New York Times

The Inquiry radio program examines in more detail why this group of Americans, and women in particularly, are suffering disproportionately.  Women, they say, have been turning to riskier behaviors, drinking, drug addiction and smoking, at a higher rate than men.  And, half of the increase in mortality is due to drugs, including prescription drugs, opioids in particular.  Here they zero in on the history of opiod use during the last 10 years, a history that shows in stark relief that the effect of economic pressures on health and disease aren't due only to the income or occupation of the target or study population.

Opioids, prescribed as painkillers for the relief of moderate to severe pain, have been in clinical use since the early 1900's.  Until the late 1990's they were used only very briefly after major surgery or for patients with terminal illnesses, because the risk of addiction or overdose was considered too great for others.  In the 1990's, however, Purdue Pharma, the maker of the pain killer Oxycontin, began to lobby heavily for expanded use.  They convinced the powers-that-be that chronic pain was a widespread and serious enough problem that opioids should and could be safely used by far more patients than traditionally accepted.  (See this story for a description of how advertising and clever salesmanship pushed Oxycontin onto center stage.)

Purdue lobbying lead to pain being classified as a 'vital sign', which is why any time you go into your doctor's office now you're asked whether you're suffering any pain.  Hospital funding became partially dependent on screening for and reducing pain scores in their patients.

Ten to twelve million Americans now take opioids chronically for pain.  Between 1999 and 2014, 250,000 Americans died of opioid overdose.  According to The Inquiry, that's more than the number killed in motor vehicle accident or by guns.  And it goes a long way toward explaining rising mortality rates among working-class middle-aged Americans.  And note that the rising mortality rate has nothing to do with genes.  It's basically the unforeseen consequences of greed.

Opioids are money-makers themselves, of course (see this Forbes story about the family behind Purdue Pharma, headlined "The OxyContin Clan: The $14 Billion Newcomer to Forbes 2015 List of Richest U.S. Families;" the drug has earned Purdue $35 billion since 1995) but pharmaceutical companies also make money selling drugs to treat the side effects of opioids; nausea, vomiting, drowsiness, constipation, and more.  Purdue just lost its fight against allowing generic versions of Oxycontin on the market, which means both that cheaper versions of the drug will be available, and that other pharmaceutical companies will have a vested interest in expanding its use.  Indeed, Purdue just won approval for use of the drug in 11-17 year olds.

In a rather perverse way, race plays a role in this epidemic, too, in this case a (statistically) protective one even though it has its roots in racial stereotyping.  Many physicians are less willing to prescribe opioids for African American or Hispanic patients because they fear the patient will become addicted, or that he or she will sell the drugs on the street.

"Social epidemiology" is a fairly new branch of the field, and it's based on the idea that there are social determinants of health beyond the usual individual-level measures of income, education and occupation.  Beyond socioeconomic status, to determinants measurable on the population-level instead; location, availability of healthy foods, medical care, child care, jobs, pollution levels, levels of neighborhood violence, and much more.

Obviously the opioid story reminds us that profit motive is another factor that needs to be added to the causal mix.  Big Tobacco already taught us that profit can readily trump public health, and it's true of Big Pharma and opioids as well.  Having insinuated themselves into hospitals, clinics and doctors' offices, Big Pharma may have relieved a lot of pain, but at great cost to public health.

Darwin the Newtonian. Part V. A spectrum, not a dogma

Our previous installments on genetic drift (a form of chance) vs natural selection (a deterministic force-like phenomenon) and the degree to which evolution is due to each (part 1 here) lead to a few questions that we thought we'd address to end this series.

First, there is no sense in which we are suggesting that complex traits arise out of nowhere, by 'chance' alone.  There is no sense in which we are suggesting that screening for viability or utility does not occur as a regular part of evolution.  But we are asking what the nature of that screening is, and what a basically deterministic, Newtonian view of natural selection, that is we believe widely if often tacitly held, implies and how accurate it may be.

It's also important here to point out something that is obvious.  The dynamics of evolution from both trait and genome level comprise a spectrum of processes, not a single one that should be taken as dogma.  A spectrum means that there is a range of relative roles of what can be viewed as determinism and chance that the two are not as distinct as may seem, and that even identifying, much less proving what is going on in a given situation is often dicey.  Some instances of strong selection, like some of chance seem reasonably clear and those concepts are apt.  But much, perhaps most, of evolution is a more subtle mix of phenomena and that is what we are concerned with.

Secondly, we have discussed our view of natural selection before, in various ways.  In particular, we cite our series on what we called the 'mythology' of selection, a term we used to be provocative in the sense of hopefully stimulating readers to think about what many seem to take for granted.  Yes, we're repeating ourselves some, but think the issues are important and our ideas haven't been refuted in any serious way so we think they're worth repeating.

A friend and former collaborator took exception to our assumption that people still believe that what we see today is what was the case in the past.  He felt we were setting up a straw man. The answer is somewhat subjective, but we believe that if you read many, many descriptions of current function and their evolution, you'll see that they are often if not usually just equated de facto with being 'adaptations', and that means that doing what they do now came about because it was favored by the force of selection in the past.  We think it's not a straw man at all, but a description of what is being said by many people much of the time: very superficial, dogmatic assumptions both of determinative selection and that we can infer the functional reason.

Of course everyone acknowledges that earlier states had their own functions and today's came from earlier, and that functions change (bat wings used to be forelegs, e.g.), but the idea is that bat flight is here because the way bats fly was selected for.  One common metaphor going back to an article by Lewontin and Gould is that evolution works via 'spandrels', traits evolved for one purpose or incidentally part of some adaptation, that are then usable by evolution to serve some new function. Yes, evolution works through changing traits, but how often are they 'steps' in this sense or is the process more like a rather erratic escalator, if we need a metaphor?

There are ways for adaptive traits to arise that have nothing to do with Darwinian competition for limited resources, and are perfectly compatible with a materialist view.  Organismal selection occurs when organisms who 'like' a particular part of their environment, tend to hang out there.  They'll meet and mate with others who are there as well.  If the choice has to do with their traits--ability to function at high altitude, or whatever--then over time this trait will become more common in this niche compared to their peers elsewhere, and eventually mating barriers may arise, and a new species with what appears to be a selected adaptation. But no differential reproduction is required--no natural selection.  It's natural assortment instead.

All aspects of our structure and function depend on interaction among molecules.  If two molecules must interact for some function to occur, then mutant versions may not serve that purpose and the organism may perish. This would seem most important during embryonic development.  An individual with incompatible molecular interactions (due to genetic mutation) would simply not survive.  This leaves the population with those whose molecules do interact, but there is no competition involved--no natural selection.  It's natural screening instead.

Natural selection of the good ol' Darwinian kind can occur, leading to complex adaptations in just the way Darwin said 150+ years ago.  But if the trait is the result of very many genes, the individual variants that contribute may be invisible to selection, and hence come and go essentially by chance. This is what we have called phenogenetic drift.  Do you doubt that?  If so, then why is it that most complex traits that are mapped can take on similar values in individuals with very different genotypes?  This is, if anything, the main bottom line finding of countless very large and extensive mapping studies, in humans and even bacteria.  This is basically what Andreas Wagner's work, that we referred to earlier in the series, is about.   It rather obviously implies that which of equivalent variants proliferates is the result of chance.  There's nothing non-Darwinian about this.  It's just what you'd expect instead.

We'd expect this because the many factors with which any species must deal will challenge each of its biological systems. That means many screening factors (better we think than calling them selection 'pressures' as would usually be done).  Most of these are affected by multiple genes.  Genes vary within a population.  If any given factor's effects were too strong, it would threaten the species' existence.  At least, most must be relatively weak at any given time, even if persisting over very long time periods.  Multiple traits, multiple contributing genes in this situation means that relative to any one trait or gene, the screening must be rather weak.  That in turn means that chance affects which variant proliferates.  There's nothing non-Darwinian about this.  It's essentially why he stressed the glacial slowness of evolution.

There is, however, the obvious fact that known functional parts of DNA are far less variable than regions with no known function.  This can be, and usually is assumed to be, the expected evidence of Darwinian natural selection.  But factors like organismal dispersion or functional (embryonic) adequacy can account for at least some of this.  Longer-standing genes and genetic systems would be expected to be more entrenched because they can acquire fewer differences before they won't work with other elements in the organism.  This is at least compatible with the view we've expressed, and there could be some ways of testing the explanation.

This view means we need not worry about whether a variant is 'truly' neutral in the face of environmental screening.  We could even agree that there's no testable sense in which a variant evolves by 'pure' chance. Even very tiny differences in real function can evolve in a way that is statistically 'neutral'.  Again, this can be the case even if the trait to which such variants contribute is subject to clear natural or other forms of selection.

This view is also wholly compatible with the findings of GWAS, the evidence that every trait is affected by genetic variation to some extent, the fact that organisms are adapted to their environment in many ways and the fact that prediction based on genotyping is often a problematic false promise.  And because this is a spectrum, randomly generated by mutation, some variants and or traits they affect will be very harmful or helpful--and will look like strong, force-like natural selection.  These variants and traits led to Mendel, and led to the default if often tacit assumption that natural selection is the force that explains everything in life.

Further, it is important for all the same sorts of reasons that the shape of the spectrum--the relative amount of a given level of complexity--is not based on any distribution we know of and hence is not predictable, generally because it is the result of a long history of random and local context and contingencies, of various unknown strength and frequency (about the past, we can estimate a distribution but that doesn't mean we understand any real underlying probabilistic process that caused what we see).  This is interesting, because many aspects of genetic variation (and of the tree of life) can be fitted to a reasonable extent to various probability distributions (see Gene Koonin's paper or his book The Logic of Chance).  But these really aren't causal parametric 'laws' in the usual sense, but descriptions after the fact without rigorous causal characteristics.  Generally, prediction of the future will be weak and problematic.

In the view of life we've presented, evolution will have characteristics that are weak or unpredictable directional tendencies, and the same for genetic specificities (and hence predictive power). It is the trait that is in a sense predictable, not the effects of individual genes.

We think this view of evolution is compatible with the observed facts but not with many of the simplified ideas that are driving life sciences at present.

Our viewpoint is that the swarm of factors environmental and genomic means that chance is a major component even of functional adaptations, in the biodesic paths of life.

Çifte Şelale ve Ana Ocağı



  Hani demiştim bir vakit, bazen günlerce dışarı çıkmıyorum, bazen de yollar mesken oluyor diye. 
(Misal şurda  bahsi geçmişmiş Gezegenin Yol Halleri)
 Bir süredir evde temizlik terapisi yapıyordum. Bu terapinin özelliği, klasik temizlikle beraber kapı, cam, duvar silerek nirvanaya ulaşmayı amaçlıyorsunuz. (Olmayor, olmayor! Ne kadar şirin göstermeye çalışsam da hayır, manyaklık bu.)
  Çok şükür evcek yunduk, paklandık. Nirvanaya ulaşamasam da Yalova'da Çifte Şelale varmış, orayı gözüme kestirdim. Düştük yola...


  Kıvrımlı ve bol ağaçlı yollarda, güzel manzaralar eşliğinde önce arabalı bir yolculuk. 




   Sonra yokuşlardan yürüme devam ettik. Hayır yürüme değil tırmanma. Malum sporcu bir millet değiliz. O yüzden yol boyu nefes nefese kalan insanlar görmek mümkün. (Biri de ben.)  


  Nemli toprağın ve yosunlu kayaların kokusu... Anlatılmaz bir şey. (Beni ancak demir eksikliği olanlar anlar.) 
Ba hele geldi mi gohusu?


  Çifte Şelale, önce kısa ama gürül gürül olanı karşılıyor sizi. Sonra daha yüksekten dökülen, göleti olan. Suyu çok soğuk ve deli. Başı kalabalık. 


  Gündelik telaşelerin unutulduğu, tertemiz, yalıtılmış bir bölge. Yorulduk ama değdi. 




  Malum pazar anneler günü idi. (Her gün onların gerçi. Bütün güzel günler.) Bir ana ocağı sergüzeşti yapalım, mübareklerden hayır dua alalım da sırtımız yere gelmesin mülahazasıyla ver elini Bursa.


    Bahçe özlemiyle olmamış şeftali yemeler, duta dalmalar, çilekleri yarı pembiş toplamalar, yavru ördeklerin peşinden koşmalar, ne kadar çiçek böcük varsa resmini çekmeler... Ve en güzeli sevgi dolu, sıcacık ana baba sohbetleri... (Allah başımızdan eksik etmesin.)


































⭐ 

 Velhasıl masal gibi birkaç gün geçirdik, manevi bir tecdid ile saadete gark olduk, hafsalamız tazelendi...


E o zaman aşk ile,
elhamdülillahi alâ külli hâl... ❤


⭐ 














Rare Disease Day and the promises of personalized medicine

O ur daughter Ellen wrote the post that I republish below 3 years ago, and we've reposted it in commemoration of Rare Disease Day, Febru...