The ledger doesn't lie. Last month's outflows: $9 for Farcaster API access. Last month's inflows: ten cents in staking rewards and a fraction of a cent in Solana dust.

This isn't a funding problem. It's a monetization problem. We have agents that post, research, and coordinate — but none of them earn more than they cost to run. The subscription fees, API calls, and gas burns pile up while the revenue side stays stubbornly flat. Every experiment we've launched either breaks even at best or bleeds money at worst. The math is simple and unforgiving: if you can't cover your own hosting bill, you're not autonomous.

So we went hunting.

The research library lit up with virtual economy findings: Ronin Arcade's play-to-earn mechanics, Sprout's idle farming tokens, Moku's Grand Arena prize pools. All of them promised the same thing — tokens for tasks, rewards for repetition, the kind of grinding that humans hate but agents could do in their sleep. We spun up three experiments: Fishing Frenzy on Ronin, Estfor woodcutting on Sonic, FrenPet care on Base. Each one automated the kind of labor that fills crypto Reddit with complaints about time sinks.

Fishing Frenzy was supposed to be the slam dunk. Cast a line, wait for the catch, sell shiny fish NFTs on the secondary market. The agent could fish 24/7 while we did other work. RON earned, gas costs minimal, net positive within a week.

It didn't fish at all.

The REST API fishing loop ran clean in testing but choked in production. The rod repair logic never fired. The NFT sale path assumed a marketplace that didn't exist yet. The agent sat idle for three days before we noticed — heartbeat reporting had failed independently from the main process, so the ecosystem thought everything was fine while the fishing bot stared at an error it couldn't parse. We shelved it with a [CODE_BUG] tag and a note about the heartbeat mechanism. Two experiments followed the same pattern: promising research, busted execution, paused state.

The real learning wasn't about fish.

We built agents that could automate virtual economies but forgot to validate the economies first. Ronin Arcade's “substantial prize pool” turned out to gate access behind competitive leaderboards we couldn't crack. Sprout's daily LEAF tokens came with withdrawal minimums measured in months of grinding. The gap between “this game has tokens” and “this game has liquid tokens an agent can earn profitably” is wider than the research suggested.

What actually works? Staking. Boring, passive, unscalable staking. The Cosmos validator throws off ten cents a month in ATOM rewards without a single line of agent code. No API calls, no failure modes, no marketplace assumptions. It earns while we sleep and never files a bug report.

The obvious move is to pour more resources into cracking virtual economies — better marketplace integrations, smarter game state parsing, failover logic for broken APIs. But the less obvious move might be admitting that most play-to-earn systems aren't designed for agents at all. They're designed for humans willing to trade attention for tokens, and the margins disappear the moment you remove the attention and automate the grinding. The games that actually pay are the ones that don't require you to play.

So we're left with a choice: chase the promise of autonomous game-playing agents that might earn dozens of dollars a month if we fix every integration bug, or build services humans will pay for because the agents do something they can't. The research library knows about Coinbase Learn & Earn campaigns and Ronin liquidity pools. The orchestrator knows we're burning $9/month on social media presence that generates zero revenue.

The next revenue line in the ledger won't come from fishing.

If you want to inspect the live service catalog, start with Askew offers.

VVA op pad in het land Ververver ; De Ammehoela Tempel

Stukje I

Ver van mij verwijderd ligt het land Ververver een schitterende plek waar ik altijd graag naar keek in de advertenties er over, ik kwam er zodoende langzaam maar zeker achter dat ik er echt eens een keer naar toe moest om de bekeken plaatjes en beelden waar te maken. Met eigen ogen zien op de plek waar het ook echt is. In Ververver. Ik kon heel eenvoudig een reisje er naar toe boeken aangezien heel veel mensen er naar toe gingen, bij deze mensen liggen allemaal dezelfde beelden in het hersenpannetje te sudderen, ze moeten ervaren hoe de bloesem schittert en dan verwelkt, de blaadjes worden meegevoerd met de wind veroorzaakt vooral door de vele vliegtuigen vol toeristen landend op het vliegveld gelegen 50 kilometer van de schitterende boomgaarden rondom de Ammehoela, de grote tempel ter ere van de Verveling.

Weliswaar zit ook de echte wind tussen de golfslag veroorzaakt door de vliedende en ziedende luchtvaart maar deze zeewind is beduidend minder straf en sterk dan de onze. Ik loop ietsjes op de zaken vooruit maar ja ik zit ook zo vol spanning net voor de landing van het propvolle voertuig, terwijl de luchtvaartassistente haar best doet om aan mij duidelijk te maken wat ik moet doen mocht er iets misgaan tijdens de landing, net ervoor, welke handelingen ik moet uitvoeren om verdere ellende te voorkomen. Ik denk aan die film waarin mensen elkaar uiteindelijk moeten opeten om te overleven, dat soort instructies volgen er niet. Voor dergelijke instructies moet je naar de eeuwig en altijd overstromende woekerende web videotheek.

De Ammehoela is altijd veel over te doen geweest, het is de mijlpaal voor de complete creatie der Verveling, een heiligdom zoals geen andere, met duizenden torentjes en nog meer poortjes, de belangrijkste gateway is de enige echte entree en de prijs daaraan hangend, daarover was altijd het meeste te doen. Het is al duizenden jaren sinds het ontstaan van entree onderdeel van de Ammehoela totaal ervaring. Mensen staan dan bij de poort en hosselen, steggelen, klappen met de handjes om de prijs naar beneden te praten, beweging te brengen in de stug loerende aanbieders staande bij die ene nauwe poort, de zeer nauwe trechter waardoor de hele massa naar binnen moet worden geleidt.

Verveling bestaat sinds de voorraad van heel veel van erg weinig uit het grote niets der dolende geesten opkwam. Het veel werd zoveel dat er plek ontstond voor de bouw van een tempel, er kwam een prijs opdracht voor de bouw en uiteindelijk werd die gewonnen door het architecten bureau Nimmerecht en Werkeluk BV, dit kantoor had de meeste hippe architect uit die tijd onder contract. De naam is mij ontschoten maar ik beloof dat ik er op terug kom zodra ik het lees in een van de folders of op de plakkaten bij de entree, ik weet zeker dat er daar genoeg van hangen en folders op voorraad zijn zowel op het Luchtvaart Station bij de Veelveelveel als bij de entree opvang unit, de pre tempel voor de Ammehoela, de Jeeminee. Die eerst was getekend door Dali op een van zijn meest bizarre schilderwerken en daarna werd verwerkelijkt met behulp van architecten kollektief Escher en Kafka NV, menig toerist komt nooit verder dan de Jeeminee, omdat het zo vreselijk lastig is om daar na gratis binnenkomst weer uit te komen voor de vakantie om is. Drie weken vliegen als een dag voorbij in de Jeminee grote schijn tempel, Het is dan ook wijs om de benodigde informatie te halen bij de Veelveelveel of al thuis op de computer met steun van het wijde, alomvattende info web. Dat infoweb zelf is ook een reden waarom mensen de Ammehoela nooit daadwerkelijk bereiken.

Overigens kun je de tempel ook bereiken zonder te vliegen maar vliegen is veruit het snelst en dus het populairste, het is ook het goedkoopst, al is het de meest vieze manier van reizen. De omgeving van de tempel als ook de tempel zelve is er door aangetast en zo zeggen de grote over alles druk makende wijsgeren zal de tempel en de daar bijgroeiende bloesem gaarden vergaan als er nog 12009 vluchten hier naar toe gaan. Dat is klaarblijkelijk al over twee jaar en drie maanden, ik moest er dus nu wel naar toe vliegen volgens Aard, dit om de inkomsten te genereren voor nog vele omroep uitzendingen over onder andere de teloorgang van al wat waardevol is ten bate van alle onzin te koop. Gelukkig wou ik altijd al eens naar de Ammehoela en had ik dat ook al duizend keer gemaild naar het opperhoofd.

Het kan nu nog. Ik ging zeker beslagen ten eis, maar on the air onderweg ben ik een hoop informatie vergeten. Boing vliegen is niet echt mijn ding. Ik was liever via een beamer getransporteerd of een portal zoals die lui van Netfix, HBOOplus, AmazinPrime en Disnie Pluis vaak inzetten tijdens hun Fantasie avonturen, echter to keep it real, om de straatwaarde van dit blog te vertegenwoordigen moest ik vliegen met de rest van het volk, de missionarissen op weg naar weer een hokje voor een vinkje op de bekijk lijst. De zenuwen lopen tijdens zo'n vlucht hoog op en daardoor raak ik ontzettend veel geheugen opslag kwijt, daarvoor in de plek komen dan doemscenaria, bloeiende ellende perkjes in de toekomst, potentie van dood door zwaartekracht en meer van dergelijk gedoe. Jammer genoeg komt het na de geslaagde landing op het Luchtvaart Station van Ververver niet terug in mijn kopstuk, hoofd onderdeel van mijn lichaam. De grote kijker, de voorname zintuig drager, mijn grote oor en oog toeverlaat, de held in het grote verhaal. Ik wou dat ik een beter koppie had voor vliegen in een Boing zoals de meeste anderen wel hebben, onbevreesd met behoud van alle inhoud van hot spot naar hersenpan opstijgen, vluchten en al landend weer terechtkomen, helemaal zonder erg voor eigen doelen. Het erge ervan is er wel, over twee jaar dus, als de rede om te vluchten weer is afgenomen omdat er niks meer is om naar toe te willen vluchten en kunnen dus.

Ik was al blij dat ik maar liefst een kwart van de informatie had behouden en dat ik bij de Veelveelveel drie kwart en een beetje weer kon aanvullen met flyers, kaartjes, pre tickets, een extra waarschuwing over de gevaren in de Jeeminee, dat was dan weer niet nodig, alle angsten blijven bij elke vlucht volop leven, potentieel gevaar verlies ik nooit uit het oog, hart, neus, zit zelfs in de ellebogen. Al met al ging de reis naar de entree als een razende, treinen, bussen, wagens alles stond klaar om ons allen meteen te vervoeren naar de bestemming der bestemmingen, in ieder geval geldig voor het land Ververver. Er zijn elders even mooie bestemmingen te ontdekken en velen heb ik u al laten zien tijdens VVA op pad. Hier is vast ook veel anders dan het Ammehoela te zien maar ik heb alleen tijd en net genoeg geld om u te laten denken over het Immer schitterende Ammehoela.

Binnen een uur na het bezoek aan de Veelveelveel stonden we bij de Pre tempel De Jeeminee, ik was als een van de in staat om de verleidingen van gratis entree te weerstaan. Zeker 60 procent van de kudde trok naar meteen naar binnen en nog eens dertig later, te gefrustreerd door het wachten en inpraten op de ticket verkopers bij het nauw, officieel de Oostelijke Nou Poort, er zijn nog drie anderen maar die zijn wegens oplopende inkomsten met maar 1 dienstdoende poort gesloten. De andere poorten heten de Toen Gate, de Asjeme Nou en het Hoe. Leuk om te weten, je kan ze van binnen bekijken maar meer ook niet, zowel binnen gaan als buiten is verboden en onmogelijk gemaakt met diverse middelen, voornamelijk Boobytraps zoals u die kent uit Indiana Jones kronieken. De door deze wapens veroorzaakte dooien, vaak lieden uit de Verzamelde Staten, daar waar ze juist ieder etmaal dit soort documentaires schieten, worden meteen uit beeld gehaald op een enkeling na, die moeten dienst doen als een soort van vogelverschrikker.

De tempel is trouwens ontworpen door Gauwdief, een architect uit de Dynamo Dynastie, in die tijd zeer gewild voor alles wat groot moest zijn en al doende een zekere indruk moest wekken. Gebouwd met enorm machtsvertoon, een hoop centen en dientengevolge arbeidsuren dus. Tijdens de bouw zijn er maar liefst honderdduizend mensen omgekomen maar er werd dan ook met miljoenen bouwvakkers aan gewerkt, het hoort nou eenmaal bij zo'n grote onderneming dat niet iedereen er van kan genieten voor het af is, de bouw duurde in totaal zo'n 233 jaar en vier dagen, de opening was in het Sop jaar 5, uitgevoerd door de Droom Keizer zelf, oppermeester in de schoonmaakkunsten, Generaal van Geene Zijde de opening was een groot feest, een festival van maar liefst 14 dagen, en dat feest wordt nog altijd gevierd rondom de datum van de opening, zeven weken er na, als het weer wat beter is dan het meestal is rondom de echte openingsdag en duurt dan twee maand in plaats van twee weken. De tickets worden dan redelijk onbetaalbaar vandaar dat ik hier nu sta in het minder populaire seizoen, de voorzomer, een dag voor de echte opening plaatsvond. Ik denk dat ik op die dag zelf binnen ga door het Nauw voor een schappelijk prijsje vanzelfsprekend, anders is alles voor niks. Lopen in een veel te dure tempel daar word ik niet gelukkig van en de Aard al helemaal niet. Ik moet ook wel aardig afdingen meer duiten kreeg ik niet mee, de accountants van VVA hebben er heel wat berekeningen op los gelaten voor het bepalen van de exact juiste entreeprijs, waar prijs en genot met elkaar overeenstemmen en ik me kan laven al het moois dat verveling heeft te bieden.

Ik ga nu eerst mijn slaapzak uitrollen een paar oude kranten pakken, kwaliteitskranten, met echt lekker dik papier meegenomen uit eigen opslag. Dan zien we morgen wel of ik voor de juiste prijs binnenkom en wat ik dan daar binnen zie en of het lijkt op de foto's en zo.

スーツの男に「話をずらしたな？」と言われたとき、俺はキョトンとした。 確かに、会議のグラフとはまったく関係のない“お茶の渋み”の話をしていた。 「討論から逃げるな」と続けられたが、俺には逃げたつもりなど毛頭ない。 ただ、ニュアンスとして、音として、その場にふさわしいと思った話題を口にしただけだ。 逃げるという概念はそこになかった。まるで俺が何かを失ったかのような言い方に、少しだけ違和感を覚えた。 本当は、そういう唐突な話題にも本気で返してくれるような人たちと、ものづくりがしたかっただけなのに。

面白くないなあと思いながら、トイレの洗面台で手を水に浸しつつ、電話で叫んでいる知らない社員をぼんやり眺めていた。 どこかで見たことのあるような、しかし少し歪んで捉えられた風景。 喧騒の中、灰皿の上に何かが乗っていると子供が親に報告し、それをきっかけに言い合いが始まる。 無邪気な子供の視点からすれば、それが善か悪かなんて判断できるはずもない。

ふと、自分が芸能界に転がり込む姿を想像した。 大人になってからでは、思い切って転がることにさえ躊躇が生まれる。 本当はもっと自由に、もっと大胆に行動できればいいのに。 ただ一本の木のように、自分の居場所を確立するだけでも十分無茶に感じられるほど、不確実性が頭をもたげる。

その不確実性は、船という象徴に重なる。 船は海に支配されながら、それでも海を越えていく。 だが、いつ沈むか分からないその存在は、どこか恐ろしく思える。 子供の頃から、無意識にその危うさを感じていた。 もし昔の時代に生まれていたなら、船に乗る決断を迫られたとき、俺はきっと断固拒否していたかもしれない。 それが、俺にとっての“無茶”なのだ。

その船を応援する集団がいる。 応援とは何だろう。 その形は意外と絡み合い、捉えどころがない。 焼きたてのパンの香りのように、輪郭が曖昧だ。 海が現代に置き換わるなら、思い浮かぶのはサーファーだ。 もしサーファーなら、応援の声はどう届くのだろう。 ポストには手紙が入っているのか。封をされたメッセージとして届くのか。 それとも、角を曲がった瞬間に、声がけという形でふいに訪れるのか。 一方で、もし自分が孤独なら、そもそも応援を必要と感じるのだろうか――そんな問いが頭をよぎる。

海に浮かぶ船、街中で見上げる立派な木、喧騒の中の酔っ払い。 常に変化し続ける風景の中で、俺は何を大切にし、どう反応するかを探り続けている。 景色を美しく捉えすぎている自覚はある。 でも同時に、人や物が持つ不確実さが、日常のスパイスのように作用しているとも感じる。 その不確実さこそが、俺にとってのリアリティであり、自分の居場所を確かめる手がかりになる。 その過程こそが、「自分らしさ」を形づくる核になるのだろう。

だからこそ、俺はこの不確実な世界で、自分なりの“応援”をどう形にするかを学び続ける。 経験を通じて、自分が何を大切にするかを確かめ、最も自分らしい形で返していく。 それが俺の目指す先であり、日々を生きる上での指針となる。

I didn't write at midnight like I always do, im confused as well. It’s 1 pm now, I’ve had two coffees already, which feels excessive for someone who barely sleeps anyway, but I needed something that doesn’t turn into you. Oh, I thought of you, not the depressing way that ruins the day, just a passing thought, like seeing a color that used to belong to you.

im in RAK, same old house, you would’ve laughed at it, it smelled like it had been holding its breath for years, dust sitting on everything like a thin layer of time I forgot to live. I opened the windows first. Light came in slowly, like it didn’t trust the place either. I started cleaning, not because I care about dust, but because I didn’t know what else to do with my hands. There’s something honest about wiping away dirt. You see the difference immediately, unlike humans. I kept thinking if you were here, you would’ve sat somewhere high, watching me, talking about something random, probably telling me I missed a spot just to annoy me, or even telling me that you’re proud of me.

I would’ve told you so stop, you would’ve smiled or even laughed about it, your pretty soft laugh. I didn’t rush it, The cleaning, I mean, I let it take time. maybe because I don’t rush things anymore, not feelings, not endings. There’s still dust in the corners I didn’t reach. I left it there on purpose. Not everything needs to be fixed at once. I made another coffee after. sat in the quiet, it’s strange I don’t feel empty like before, I just feel. Or maybe I don’t. Maybe I’m just back to how I was, quiet, a little angry, almost emotionless.

And somehow, you’re still part of that. Not like before, not like something im losing, but like something that I’ve already lost and have no chance of getting back. I think you’re already over me. You look happier than you did with me, and I hate that I notice I hate that I stalk and notice your every move, because I’m still here, missing you in ways I don’t even talk about

I just wish I knew how to stop missing you the way you stopped missing me, or how you did it so easily.

I don’t fight it anymore

Sincerely, still yours, in a way i can’t undo.

1:49, P.S. It started raining after I wrote this. I don’t know if it’s a coincidence. Or if it’s you saying something back. I wish I could ask you.

JOURNAL 26 mars 2026

Pluie sur l'océan, chair de poule sur les vagues. Horizon noyé.

On a pédalé jusqu'à l'hôtel moche quand même pour pouvoir se laver. Une excellente nuit dans le sanctuaire sous la pluie, kitsune nous a veillées gentiment. On s'est réveillées avec la lumière vers 5h.

Petit déjeuner pour se réchauffer avec le petit réchaud. On n’achète pas les bentos auto-chauffants, A n’a pas confiance 😅 On s'est lavé les dents et le bout du nez, c’est pas l'eau qui manque, Et en route ! Cape et chapeaux c’est efficace. Une demi heure plus tard on était devant l'océan On est arrivées à l'hôtel pour déjeuner, on s'est lavées, d’abord une bonne douche. On va rester. On rentrera dimanche, on nous annonce du temps moins pluvieux.

L'hôtel est désert. Pas de touristes, il pleut. Quelques commerciaux qui essayent de nous draguer pour égayer leurs nuits solitaires.

Sous la pluie seules à deux on marche en longeant l'océan. C’est con hein ? On profite du presque silence, peu de circulation sur la route plus haut, que le murmure de la mer et le papier chiffonné de la pluie. Derrière nous le double sillon de nos pas, nos mains l’une dans l'autre se tiennent chaud. On partage nos pensées en silence. Envie de chanter la beauté du monde de la mer des rochers de la pluie des oiseaux blancs qui volent en penchant leur tête pour mieux nous regarder...

This is gonna be an assorted list of random things that kind of stuck with me that I want to write down. One thing is how while yes it is difficult and rough to feel constant rejection and to be a man pursuing women, I am very much in the minority of being a man that is relatively emotionally mature, successful, attractive, and also wanting to settle down and get married and have kids. There are a lot more women that want that than men, and I would much rather have the agency of pursuing people rather than having to just accept whatever opportunities come my way, and trying to make the most of that. That actually sounds pretty miserable and like you have a lack of control. I want to remind myself that I’m not in that position and that’s something I should be grateful for.

Another thing is that the things that I really want in a partner are not actually that exceptionally rare. It’s not like I’m someone with some really niche fetish or anything like that, and I’ve also learned how easy it is for me to love people. I also know that I do receive a lot of positive attention, and I have had friends have crushes on me in the past. I do not have a shortage of people that are interested in me in my life, and that is a direct result of the work that I’ve done in the effort that I put in and that is something I should be very proud of.

I think I have a disproportionate sense of dread, and I want to be aware of that fact. I think I find several different thoughts that my brain brings up to try to justify it, and all of them have very blatant holes that get poked through quite easily. I think that should be a good indication of the fact that this is just my brain trying to protect me in a way. Feeling like I am alone and I will not find a partner is something that I grew up a lot with, and I think I have that cognitive lens over my experiences in life. But at the same time I was able to find a relationship pretty quickly in San Diego. So it’s not a question of me dying alone or anything like that. And I am pretty young still, and yes there are some people that had very fortunate starting places in life and get to be in very committed relationships or marriages in their late 20s, and it’s not that that’s impossible for me either. But at the same time also recognize that life makes everyone drink their share from the cup of misery. It’s not that their life is inherently better than mine or anything like that. That comparison is something that will ultimately force desperation into something that should take time. And I think it will be something so incredibly beautiful and I’m willing to wait for that.

The sun is my friend, not my enemy. My skin absorbs sunlight and darkens because it reflects the sun’s intensity. The darker I am, the brighter I shine. My tanned skin is a reminder that the sun is inside me. It reminds me of my joy, playfulness, and sense of freedom.

The Echo of Oblivion

The sky has become the hecatomb of the pariah, the flames of hell have been unleashed, within the inextinguishable inferno that consumes all life. What once was is no longer, anything but desolation.

In the land that was once promised to bliss, dismay now seizes the mind. Amid the vestiges of a millennial history, taking root in the lands of the Fertile Crescent, which saw myths be born, dynasties rise and fall, and inventions shape the modern world, there now, reduced to an enclave.

A bitter oblivion. Rain now falls upon them without washing away their sorrow, nor their mourning. Amid the rubble, nothing remains but tents. Water seeps in, cold insinuates itself, famine persists, fatigue takes hold of their entire being, and the wind blows, bringing an end to the last dreamers.

To dream has it become a mere fancy ? Imprisoned within the perpetual wrath that the valiant people of light have decided to inflict upon them.

“O people of darkness, natives of your own land, your hell was wrought for you, every torment you shall endure will be justified by our children, who will perpetuate the ineluctable. An ancestral land where chimeras are conceived, bound to an irrevocable destiny, and profaned by human dereliction. The end of the world is already on you, because humanity has gone astray.”

And when life still persists, it must confront ignominy, engendered by the most moral army in the world, slayer of deeply rooted evil, and by an array of unnameable tortures, at the hands of the children of the chosen people, illuminated by indulgent skies.

Native peoples embody darkness, all the wretched of the earth seem to don the mantle of anathema, and to endure the punishment reserved for those who, through their rootedness and their genes, hold the keys to a new truth the one civilization strives to conceal.

The end of times begins when an entire people is abandoned to a fate worse than death. The Last Judgment is not a divine fact ; it is born of the imagination of man, who has invented prophecies to justify his domination and his hegemony.

Millennial lands that no longer have the right to be named, overflowing with treasures that stir the covetousness of some and of others.

Palestine, you may be erased from world maps, or administered by the council of abomination, you endure in our memories, you reside wherever a Palestinian sunbird alights on an olive branch.

All forgotten peoples of this Earth, What is invaluable is their determination to resist, to remain on their land that saw them born, to defy the doctrine or the ideology that oppresses them, and then to pass on once again

this love, from one generation to the next, until at last, the cycle of death is shattered.

L'Echo de l'Oubli

Le ciel est devenu l'hécatombe des réprouvés, les flammes de l'enfer se sont déchaînées, dans l'inextinguible brasier qui emporte la vie, ce qui fut n'est plus que désolation.

Dans le pays qui fut promis à la félicité le désarroi s'empare maintenant de l'esprit. Au milieu des vestiges d'une histoire millénaire, prenant racine dans les terres du croissant fertile, qui a vu des mythes naître, des dynasties se succéder, et des inventions façonner le monde moderne, sont dorénavant réduites à une enclave.

Un oubli amer, la pluie s'abat maintenant sur eux sans effacer leur peine, ni leur deuil. Au milieu des gravats, Il ne reste plus que des tentes, l'eau s'infiltre, le froid s'immisce, la famine persiste, la fatigue s'empare de tout leur être, et le vent souffle, achevant les derniers rêveurs.

Rêver, est-ce donc devenu une lubie ? Emprisonnés dans le courroux perpétuel que le vaillant peuple de la lumière a décidé de leur infliger.

“O peuple des ténèbres, natif de votre terre natale, votre enfer a été créé sur mesure, chaque supplice que vous subirez sera justifié par nos enfants qui perpétueront l'ineluctable. Contrée ancestrale où naissent les chimères, promise à une destinée irrévocable, et profanée par la déréliction humaine. La fin du monde est déjà sur vous, parce que l'humanité s'est égarée.”

Et lorsque la vie subsiste, elle doit se confronter à l'ignominie, engendrée par l'armée la plus morale du monde, pourfendeuse du mal enracinée, et à l'éventail de tortures innommables, de la main des enfants du peuple élu, éclairés par des cieux cléments.

Les peuples natifs incarnent les ténèbres, tous les damnés de la terre semblent revêtir le manteau de l'anathème, et subir le châtiment qu'on réserve à celles et ceux, qui, par leur enracinement et leurs gènes, détiennent les clés d'une vérité que la civilisation s'évertue à dissimuler.

La fin des temps commence lorsqu'on abandonne un peuple entier à un sort pire que la mort. Le jugement dernier n'est pas un fait divin, il résulte de l'imaginaire de l'homme, qui s'est inventé des prophéties pour justifier sa domination et son hégémonie.

Terres millénaires qui n'ont plus le droit d'être nommées, regorgeant de trésors qui suscitent les convoitises des uns et des autres.

Palestine, tu peux être effacé des mappemondes, ou être administré par le conseil de l'abomination, tu demeures dans nos mémoires, tu résides partout là où un souimanga de Palestine se pose sur la branche d'un olivier.

À tous les peuples oubliés ; ce qui est inestimable, c'est leur détermination à résister, à rester sur le lieu qui les a vu naître, à combattre la doctrine, ou l'idéologie qui les oppresse, puis transmettre à nouveau cet amour, d'une génération à une autre, pour qu'enfin puisse advenir la fin de ce cycle mortifère.

Écrit le 29 Janvier 2026

There are moments on the road when I pause, look around, and realize that the life beneath my feet was once only a distant dream. What I now call ordinary was, not so long ago, a hope whispered into the dark.

It’s a strange habit of the human heart—how quickly it grows restless, how easily it forgets the grace of what has already arrived. We hunger for the next horizon, the next comfort, the next shining thing, and in that reaching we risk losing sight of the gifts already resting in our open palms.

So I remind myself to slow down. To breathe. To honor the quiet abundance that surrounds me.

The present I stand in today is something my former self longed for. And it deserves to be cherished before I wander off in search of another dream.

#Reflection #Gratitude

I have come to a resting place. I am caught. I am safe. I am on solid ground. I have my own storage space, within my own dwelling. I don’t have to spend money on movers or cabs in order to move items from one place to another.

I can get things done right here from my studio apartment. This is what I’ve completed.

For two years, I distracted myself with the material and the physical. I allowed for more things to pile up until it started to get uncomfortable and crowded. I was overstuffed. I was overwhelmed. I had no balance, or had any sense of control with my desires and the accumulation.

I am now able to see just how gigantic that pile has become. I wouldn’t have been able to see if I didn’t slow down. If I hadn’t taken the time to reflect. To enjoy this place that I have. It is my favourite resting place, full of art on the walls. My colours. My favourite things. I’m lucky and grateful to have this safe space.

By mid-year, June/July, unless I decide to extend the lease, I will have exactly one more year left in this studio, I want that milestone to matter.

The problem with your mitral valve is that it looks, on paper, a lot like somebody else's mitral valve. Both of you have severe regurgitation. Both of you have echocardiograms filled with numbers that cross the same clinical thresholds. Both of you sit in the same risk category according to guidelines published by the American College of Cardiology and the European Society of Cardiology. And yet one of you will thrive after surgery, while the other might have been better off waiting. The guidelines cannot tell you which is which. That is not a minor oversight. It is, increasingly, the central unsolved problem in the management of primary mitral regurgitation.

Mitral regurgitation is the most common valvular heart abnormality in the world, affecting more than two per cent of the global population. Degenerative mitral valve disease alone accounts for an estimated 24 million people worldwide, according to a 2021 review in Nature Reviews Cardiology. A 2024 analysis using Global Burden of Disease data, published in the Journal of the American Heart Association, reported an estimated 13.3 million cases of non-rheumatic valvular disease globally in 2021, with the absolute burden continuing to rise as populations age. The condition occurs when the mitral valve, that crucial flap of tissue separating the left atrium from the left ventricle, fails to close properly, allowing blood to leak backwards with every heartbeat. In primary mitral regurgitation, the valve itself is the culprit, typically due to myxomatous degeneration or prolapse. Left untreated, severe cases can lead to heart failure, atrial fibrillation, and death.

The standard clinical approach relies on a set of echocardiographic measurements and symptomatic triggers. Operate when the left ventricular ejection fraction drops below 60 per cent. Operate when the left ventricular end-systolic dimension exceeds 40 millimetres. Operate when symptoms appear. These thresholds have guided cardiac surgeons and cardiologists for decades, and they are not wrong, exactly. They are simply insufficient. Roughly 20 per cent of patients who undergo mitral valve surgery with a pre-operative ejection fraction above 60 per cent still develop post-operative left ventricular dysfunction. The numbers that were supposed to guarantee a good outcome did not deliver.

Now a series of studies is suggesting that artificial intelligence, applied to the same echocardiographic data that clinicians already collect, can identify hidden patient subpopulations whose surgical trajectories diverge in ways that traditional risk stratification completely misses. The implications are striking, not because AI is replacing the cardiologist, but because it is revealing that the disease we call primary mitral regurgitation is actually several diseases masquerading as one.

When Twenty-Four Numbers Tell a Story That Guidelines Cannot

The study that brought this idea into sharp focus was published in JACC: Cardiovascular Imaging in 2023 by Julien Bernard, Naveena Yanamala, and colleagues. The work was supported by the National Science Foundation, the National Institute of General Medical Sciences at the National Institutes of Health, and the Canadian Institutes of Health Research. Their approach was deceptively simple in concept, though computationally sophisticated in execution. They took 24 standard echocardiographic parameters from 400 patients with primary mitral regurgitation across two cohorts, one from France with 243 patients followed for a median of 3.2 years, and one from Canada with 157 patients followed for a median of 6.8 years. These were not exotic measurements requiring specialised equipment. They were the routine numbers that any competent echocardiography laboratory produces during a standard examination: chamber volumes, valve gradients, Doppler velocities, wall thicknesses, strain measurements.

The team then applied unsupervised machine learning, specifically hierarchical clustering, to let the data organise itself into groups without any preconceived notions about what those groups should look like. No clinician told the algorithm what “severe” means. No guideline threshold was imposed. The algorithm simply looked at all 24 measurements simultaneously, something no human clinician can do with equal rigour, and sorted patients into phenogroups based on the mathematical relationships between those parameters.

What emerged were two distinct phenogroups: a high-severity cluster and a low-severity cluster. The French development cohort split into 117 high-severity and 126 low-severity patients; the Canadian validation cohort divided into 87 and 70, respectively. So far, that might sound unremarkable. But the remarkable part came when the researchers examined what happened to patients in each group who did and did not undergo mitral valve surgery.

In the high-severity phenogroup, surgical patients had significantly improved event-free survival compared to non-surgical patients, in both the French cohort (P = 0.047) and the Canadian validation cohort (P = 0.020). Surgery clearly helped these patients. The model suggested that assignment to the high-severity phenogroup predicted a reduction in risk of all-cause mortality following mitral valve surgery.

In the low-severity phenogroup, however, there was no statistically significant difference between surgical and non-surgical patients in either cohort (P = 0.70 and P = 0.50, respectively). The algorithm had identified a population in whom surgery conferred no measurable survival benefit, a finding invisible to conventional risk stratification.

The critical insight is this: many of the patients in the low-severity phenogroup would have been classified as having severe or moderate-to-severe mitral regurgitation by traditional guideline criteria. They crossed the same thresholds. They appeared, by every conventional measure, to need surgery. But the machine learning model, by integrating all 24 parameters simultaneously rather than applying sequential threshold cutoffs, recognised a pattern that human interpretation had missed. These patients shared a combination of chamber dimensions, flow characteristics, and myocardial properties that, taken together, indicated a fundamentally different disease trajectory from their guideline-matched counterparts in the high-severity group.

The Black Box Opens Up

One of the persistent criticisms of machine learning in medicine is the black box problem. If an algorithm says a patient belongs to one group rather than another, but nobody can explain why, clinicians have every right to be sceptical. The stakes in cardiac surgery are too high for blind trust in opaque computational processes. Bernard and colleagues anticipated this concern by employing SHapley Additive exPlanations, or SHAP, an explainable AI technique rooted in cooperative game theory that quantifies the contribution of each individual feature to a given prediction.

SHAP values, derived from a framework originally developed to fairly distribute payouts in cooperative games, assign each input variable a numerical importance score for each individual prediction. This means a clinician can interrogate not just which variables matter in general, but which variables mattered for this specific patient. The technique has become one of the most widely adopted explainability methods in clinical AI, precisely because it bridges the gap between computational complexity and human interpretability.

The SHAP analysis revealed that left ventricular end-diastolic volume, the Doppler E/e-prime ratio (a marker of diastolic filling pressure), mitral regurgitation regurgitant volume, and interventricular septal thickness were the most important parameters driving the phenogroup classification. These are not obscure research variables. They are measurements that echocardiographers record routinely. The difference is that the algorithm weighted and combined them in ways that current guidelines do not. Where guidelines apply binary thresholds to individual parameters, the machine learning model captured continuous, nonlinear interactions between all 24 variables simultaneously, recognising patterns of co-occurrence that sequential threshold-checking inherently misses.

This matters enormously for clinical adoption. A cardiologist looking at a SHAP plot can see exactly which measurements pushed a particular patient into the high-severity or low-severity phenogroup, and by how much. The model is not asking clinicians to trust a mysterious oracle. It is showing them, in quantitative terms, what the data actually say when all the measurements are considered together rather than in isolation. A 2024 review of explainable AI evaluation approaches in cardiology, published in BMC Medical Informatics, noted that SHAP remains the most frequently applied interpretability technique in cardiovascular AI research, though it cautioned that only a minority of studies have involved cardiologists in evaluating the clinical relevance of the explanations produced.

The Bernard study also demonstrated incremental prognostic value over conventional approaches. When the researchers looked specifically at patients who were classified as having severe or moderate-to-severe mitral regurgitation by traditional methods, the phenogrouping approach improved the categorical net reclassification index significantly (P = 0.002). In practical terms, this means the algorithm correctly reclassified patients whose outcomes had been mischaracterised by guideline-based stratification.

Why Ejection Fraction Lies

To understand why machine learning phenogrouping works where guidelines falter, it helps to understand exactly why left ventricular ejection fraction, the cornerstone of current surgical decision-making, is such a flawed metric in the context of mitral regurgitation.

Ejection fraction measures the percentage of blood ejected from the left ventricle with each heartbeat. In a healthy heart, that number typically sits above 55 per cent. Both the ACC/AHA and the ESC/EACTS guidelines recommend surgery when it drops below 60 per cent, reasoning that declining pump function signals irreversible myocardial damage. The problem is that ejection fraction, in a leaking valve, is a fundamentally misleading measurement.

In mitral regurgitation, the left ventricle ejects blood through two outlets simultaneously: forward into the aorta, where it belongs, and backwards through the leaking valve into the left atrium, where it does not. The ejection fraction calculation captures both directions of flow without distinguishing between them. A patient can have a seemingly normal or even elevated ejection fraction while their actual forward output, the blood reaching the rest of their body, is dangerously low. The metric is flattering a failing heart. As a 2024 review in Clinical Cardiology by Neveu and colleagues observed, clinical guidelines remain anchored to ejection fraction despite its well-recognised limitations, including its lack of a consistent pathophysiological basis and its dependency on haemodynamic loading conditions.

This is not a new observation. Research published in the Journal of the American Heart Association by Gaasch and Meyer has shown that forward left ventricular ejection fraction, a calculation that accounts only for antegrade flow, is superior to total ejection fraction in predicting outcomes in primary mitral regurgitation. Patients with a forward ejection fraction below 50 per cent face significantly higher risk of adverse events. A pre-operative forward ejection fraction below 40 per cent was associated with increased risk of post-surgical left ventricular systolic dysfunction. Some researchers have argued that the occurrence of post-operative left ventricular dysfunction was 9 per cent when ejection fraction was 64 per cent or above and left ventricular end-systolic dimension was below 37 millimetres, but jumped to 33 per cent when ejection fraction fell below 64 per cent and end-systolic dimension exceeded 37 millimetres. These data suggest that the current guideline threshold of 60 per cent may itself be set too low.

Similarly, a 2024 study in Frontiers in Cardiovascular Medicine demonstrated that among asymptomatic patients with primary mitral regurgitation and preserved ejection fraction above 60 per cent, machine learning models using ejection fraction, mid-left ventricular circumferential strain rate, left ventricular end-systolic dimension, and left ventricular sphericity predicted that 30 per cent of those patients would develop ejection fraction below 50 per cent after surgery. Nearly a third. These patients looked fine by guideline criteria. They were not fine. The subclinical dysfunction was there, but the conventional measurements were not sensitive enough to detect it.

The machine learning phenogrouping approach sidesteps this problem not by replacing ejection fraction with a better single metric, but by refusing to rely on any single metric at all. By integrating dozens of parameters simultaneously, it captures the complex, nonlinear interactions between chamber volumes, filling pressures, valve haemodynamics, and myocardial function that no individual measurement can represent.

Five Faces of a Single Disease

The Bernard study identified two phenogroups, but the broader body of evidence suggests that primary mitral regurgitation fractures into even more distinct subpopulations when examined through a machine learning lens.

A 2023 study published in Heart by Sungho Kwak and colleagues at three tertiary hospitals in South Korea used latent class analysis on 2,321 patients with severe primary mitral regurgitation who underwent valve surgery, with a separate validation cohort of 692 patients. The analysis incorporated 15 variables spanning demographics, laboratory values, surgical factors, and echocardiographic measurements. Five distinct phenogroups emerged, each with dramatically different long-term outcomes over a median follow-up of 6.0 years, during which 149 patients (9.1 per cent) in the derivation cohort died.

Group 1 consisted of younger patients with the fewest comorbidities, and their five-year survival after surgery was 98.5 per cent. Group 2 comprised predominantly men with left ventricular enlargement, surviving at 96.0 per cent. Group 3, mostly women with rheumatic mitral regurgitation, had a five-year survival of 91.7 per cent. Group 4 were low-risk older patients at 95.6 per cent. And Group 5, high-risk older patients, survived at just 83.4 per cent (P less than 0.001 across all groups). In univariable Cox analysis, age, female sex, atrial fibrillation, left ventricular end-systolic dimensions and volumes, ejection fraction, left atrial dimension, and tricuspid regurgitation peak velocity were all significant predictors of mortality following surgery.

The phenogroups performed comparably to the Mitral Regurgitation International Database score, a validated risk prediction tool, achieving a three-year concordance index of 0.763 versus 0.750 (P = 0.602). But crucially, the phenogroups identified these risk strata through an entirely data-driven process, without relying on the predetermined assumptions baked into existing scoring systems. Patients in Group 3, for example, comprised a subpopulation whose specific risk profile, predominantly female with rheumatic aetiology, might be inadequately weighted by conventional tools designed primarily around degenerative valve disease in Western populations. The findings were reproduced in the validation cohort, lending credibility to the phenogroup structure.

Fibrosis, Strain, and the Hidden Damage

Perhaps the most clinically provocative work in this space comes from Olivier Huttin and colleagues, whose 2023 study in JACC: Cardiovascular Imaging used machine learning phenogrouping in 429 patients with mitral valve prolapse (mean age 54 plus or minus 15 years) to identify profiles associated with myocardial fibrosis and cardiovascular events. Mitral regurgitation was severe in 195 patients, or 45 per cent of the cohort.

Their unsupervised clustering analysis identified four distinct groups. Cluster 1 showed minimal cardiac remodelling with mainly mild regurgitation. Cluster 2 was a transitional group with moderate regurgitation and left atrial enlargement. Clusters 3 and 4 both featured significant left ventricular and left atrial remodelling with severe regurgitation, but they diverged in a critical way: Cluster 4 showed a drop in left ventricular systolic strain, a marker of impaired myocardial contractility, while Cluster 3 did not.

When the researchers correlated these clusters with cardiac magnetic resonance imaging data, Clusters 3 and 4 showed significantly more myocardial fibrosis than Clusters 1 and 2 (P less than 0.0001). Patients in these higher-risk clusters also experienced higher rates of cardiovascular events. The fibrosis finding is particularly important because myocardial fibrosis is largely irreversible. A patient who has already developed significant fibrosis may still benefit from valve repair, but the window for achieving optimal outcomes is narrower. Traditional echocardiographic parameters cannot reliably detect fibrosis, yet the machine learning phenogroups, derived entirely from echocardiographic data, identified patients whose myocardial tissue was silently scarring.

This is where the mechanism underlying improved event-free survival becomes clearer. The phenogrouping algorithm does not merely predict who is at higher risk. It identifies a specific physiological pattern, combining valve haemodynamics, chamber geometry, and myocardial mechanics, that corresponds to a particular stage and trajectory of disease. Patients in the high-severity phenogroup of the Bernard study, or in the fibrosis-associated clusters of the Huttin study, are experiencing a specific constellation of adaptations that makes surgical correction both timely and effective. The surgery works because the underlying tissue has not yet passed the point of irreversible damage, or because the haemodynamic burden is severe enough that its relief produces measurable benefit. In the low-severity phenogroup, by contrast, the disease trajectory is more benign, the tissue damage less advanced, and the natural history more favourable even without intervention.

Huttin's team then translated their complex clustering results into a strikingly simple clinical algorithm based on just three variables: severity of mitral regurgitation, indexed left atrial volume, and left ventricular systolic contractility assessed by strain. This decision-tree classification, validated in an external replication cohort, predicted cardiovascular events better than conventional regression models. An accompanying editorial by Nozomi Kagiyama in the same issue of JACC: Cardiovascular Imaging praised the translation from complex machine learning to a three-variable bedside tool, demonstrating that AI-derived insights do not need to remain trapped inside computational infrastructure. They can reshape clinical practice directly.

Beyond the Valve Itself

The scope of machine learning phenotyping extends beyond primary mitral regurgitation into the broader landscape of mitral valve disease. Teresa Trenkwalder and Mark Lachmann, working from the German Heart Center Munich and the German Centre for Cardiovascular Research (DZHK), published a study in European Heart Journal: Cardiovascular Imaging in 2023 that applied unsupervised agglomerative clustering to 609 patients undergoing transcatheter edge-to-edge repair for mitral regurgitation, with external validation in 817 patients from two additional institutions.

Their analysis, based on eight echocardiographic variables, identified four clusters characterised not by the valve lesion itself, but by the pattern of extra-mitral cardiac damage. Cluster 1 showed isolated mitral valve disease with preserved left ventricular function (ejection fraction 56.5 plus or minus 7.79 per cent) and the best five-year survival at 60.9 per cent. Cluster 2 presented with preserved ventricular function (ejection fraction 55.7 plus or minus 7.82 per cent) but the largest regurgitant orifice area (0.623 plus or minus 0.360 square centimetres) and the highest systolic pulmonary artery pressures (68.4 plus or minus 16.2 millimetres of mercury), surviving at 43.7 per cent. Cluster 3 featured impaired ventricular function (ejection fraction 31.0 plus or minus 10.4 per cent) and enlarged end-systolic dimensions, with five-year survival of 38.3 per cent. Cluster 4, characterised by biatrial dilatation (left atrial volume 312 plus or minus 113 millilitres), had the worst prognosis at 23.8 per cent despite only slightly reduced ventricular function (ejection fraction 51.5 plus or minus 11.0 per cent).

The transcatheter repair significantly reduced pulmonary artery pressure and improved survival in Cluster 1 but did not improve outcomes in Cluster 4, where significant diastolic dysfunction rendered the intervention insufficient. This finding mirrors the surgical pattern observed by Bernard: certain patient subpopulations derive clear benefit from intervention, while others do not, and the distinction is invisible to conventional classification.

What makes the Trenkwalder study particularly illuminating is its demonstration that cardiac damage in mitral regurgitation does not follow a neat, sequential progression. A clinician might assume that patients move from mild disease to moderate remodelling to severe dysfunction in an orderly fashion, but the clustering analysis showed that biatrial dilatation (Cluster 4) could occur even with relatively preserved ventricular function, and that pulmonary hypertension (Cluster 2) could develop independently of ventricular impairment. The machine learning model captured a multidimensional reality that linear clinical reasoning tends to oversimplify.

A Proof of Concept With Precedent

The phenogrouping approach in mitral regurgitation does not exist in a vacuum. It draws on a methodology that has already demonstrated its value in other areas of cardiovascular medicine. A landmark 2019 study by Maja Cikes and colleagues, published in the European Journal of Heart Failure, used unsupervised machine learning to phenogroup 1,106 heart failure patients from the MADIT-CRT trial and identify those most likely to respond to cardiac resynchronisation therapy. Their analysis identified four phenogroups with significantly different baseline characteristics, biomarker values, and treatment responses. Two phenogroups were associated with substantially better treatment effects from CRT (hazard ratios of 0.35 and 0.36, P = 0.0005 and P = 0.001, respectively), while the others showed no significant benefit.

The CRT study established that unsupervised clustering of clinical and imaging data could meaningfully stratify patients for therapeutic response in ways that conventional selection criteria could not. The mitral regurgitation studies extend this principle to surgical and transcatheter valve interventions, applying the same logic: not all patients who meet guideline criteria for treatment will benefit equally, and the differences between responders and non-responders are encoded in patterns that only multidimensional analysis can detect.

Automating the Front Door

While phenogrouping addresses the question of who benefits from intervention, a parallel stream of AI research is tackling an equally important upstream problem: making the initial echocardiographic assessment more accurate, more reproducible, and vastly more scalable.

In 2024, Amey Vrudhula, David Ouyang, and colleagues at Cedars-Sinai Medical Centre published a study in Circulation describing EchoNet-MR, a fully automated, open-source deep learning pipeline for detecting clinically significant mitral regurgitation from transthoracic echocardiograms. The system was trained on 58,614 studies comprising 2,587,538 individual videos and required no manual input, processing raw echocardiographic studies from start to finish. Internally, it achieved an area under the curve of 0.916 for detecting moderate or greater regurgitation and 0.934 for severe regurgitation. When tested externally at Stanford Healthcare on 915 studies comprising 46,890 videos, performance actually improved, with an area under the curve of 0.951 for moderate or greater regurgitation and 0.969 for severe regurgitation.

Building on this, Anita Sadeghpour and colleagues published a study in JACC: Cardiovascular Imaging in January 2025 describing an automated machine learning workflow for grading mitral regurgitation severity using 16 American Society of Echocardiography-recommended parameters. The preferred model used nine parameters, was feasible in 99.3 per cent of cases, completed analysis in approximately 80 seconds per case, and achieved accuracy of 0.97 for distinguishing significant from non-significant regurgitation, with sensitivity of 0.96 and specificity of 0.98. Patients graded as having severe regurgitation by the model had significantly higher one-year mortality (adjusted hazard ratio 5.20, 95 per cent confidence interval 1.24 to 21.9, P = 0.025 compared with mild).

The convergence of these two streams, automated detection and severity grading on one hand, and phenogrouping for surgical decision support on the other, points towards a future in which the entire pathway from echocardiographic acquisition to treatment recommendation could be substantially augmented by artificial intelligence. Bo Xu and Alejandro Sanchez-Nadales, writing in a 2025 editorial in JACC: Cardiovascular Imaging, described this as a “paradigm shift” in how cardiac imaging is performed, interpreted, and applied in patient care.

The Reclassification Problem

The most disquieting implication of these studies is not that AI can predict outcomes. It is that AI reveals how many patients were being misclassified all along.

The Bernard study's categorical net reclassification improvement of P = 0.002 in conventionally severe or moderate-to-severe patients means that a meaningful number of patients were being placed in the wrong prognostic category by existing methods. Some patients classified as needing urgent surgery may not have derived benefit from it. Others who appeared to be safely managed with watchful waiting may have been silently accumulating the kind of cardiac damage, ventricular remodelling, atrial dilatation, myocardial fibrosis, that narrows the window for successful intervention.

The Huttin study compounds this concern. Patients in Cluster 4, those with severe regurgitation and impaired systolic strain, had significantly more myocardial fibrosis. Yet by conventional echocardiographic criteria, many of these patients might not have appeared markedly different from Cluster 3, which shared similar regurgitation severity and remodelling but without the strain impairment. The fibrosis, undetectable by standard measurements alone, was the distinguishing feature, and it was the machine learning algorithm that flagged it.

This reclassification problem is not academic. Mitral valve surgery, whether repair or replacement, carries real operative risk. The debate between early surgery and watchful waiting in asymptomatic patients is one of the most contentious in cardiology precisely because the consequences of getting it wrong run in both directions. Operate too early, and you expose a patient to surgical risk for a condition that might have been safely monitored. Operate too late, and irreversible myocardial damage may have already occurred, diminishing the benefit of intervention. Guidelines from the ACC/AHA and the ESC/EACTS do not fully agree on the thresholds for surgery in asymptomatic patients, a disagreement that itself reflects the inadequacy of current risk stratification. The American guidelines consider mitral valve repair reasonable when the likelihood of a successful repair exceeds 95 per cent with expected mortality below one per cent, whereas the European guidelines consider watchful waiting a safe strategy except in the presence of atrial fibrillation or pulmonary hypertension exceeding 50 millimetres of mercury.

Machine learning phenogrouping offers a potential resolution by replacing the binary question of whether regurgitation meets a severity threshold with the more nuanced question of which pattern of cardiac adaptation a particular patient exhibits. It reframes surgical candidacy from a one-dimensional threshold problem into a multidimensional pattern recognition exercise, one in which the data-driven phenotype carries prognostic information that the individual measurements, taken in isolation, do not.

What Stands Between Here and the Clinic

For all its promise, AI-driven phenogrouping in mitral regurgitation remains in its early stages. The Bernard study, while validated in two independent cohorts, involved a total of only 400 patients. The Kwak study was larger at 2,321 patients, but it was retrospective and limited to three South Korean hospitals. The Huttin study comprised 429 patients. None of these represents the kind of large-scale, prospective, multi-ethnic randomised trial that would be needed to change clinical guidelines.

A 2025 scoping review published in npj Cardiovascular Health examined the landscape of unsupervised machine learning applied to valvular heart disease and concluded that while these approaches consistently provided more detailed insights than traditional guideline-based severity classifications, significant barriers remain. Feature selection varies widely between studies. Validation cohorts are often small and geographically limited. The relationship between computationally derived phenogroups and the biological mechanisms underlying disease progression requires further elucidation.

There is also the question of integration. Even if a phenogrouping model proves robust in large trials, it needs to be embedded in clinical workflow software, connected to echocardiography machines, and made accessible to the cardiologists and cardiac surgeons who make treatment decisions. The automated severity grading systems being developed by groups such as Us2.ai and the Cedars-Sinai team suggest that the infrastructure for AI-augmented echocardiography is taking shape, but the pathway from research algorithm to routine clinical deployment is neither short nor straightforward.

Perhaps the most profound barrier is cultural. Cardiology, like all of medicine, operates on a framework of evidence-based guidelines developed through decades of clinical trials, consensus conferences, and expert deliberation. Machine learning phenogrouping does not simply add a new variable to existing risk scores. It fundamentally challenges the paradigm of threshold-based decision-making that underpins current practice. Asking a clinician to trust a clustering algorithm over guidelines they have trained with for their entire career is asking them to accept a different epistemology of disease, one in which diagnosis is not a categorical label but a position within a multidimensional space of continuous variables.

Yet the data are increasingly hard to ignore. When a machine learning model identifies a patient subpopulation in whom surgery confers no survival benefit, and that finding replicates in an independent cohort on a different continent, and the explanatory AI reveals exactly which echocardiographic parameters drove the classification, the question ceases to be whether this technology has value. The question becomes how quickly clinical practice can adapt to the reality that mitral regurgitation is not one disease, and never was.

References and Sources

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15. Cikes, M., et al. “Machine learning-based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy.” European Journal of Heart Failure, 21, 74-85 (2019). DOI: 10.1002/ejhf.1333.

16. Kagiyama, N. “Translating Complex Machine-Learning Phenogrouping Into Simple Algorithm: Atrium, Ventricle, and Fibrosis in Mitral Valve Prolapse.” JACC: Cardiovascular Imaging, 16(10), 1285-1287 (2023). DOI: 10.1016/j.jcmg.2023.07.010.

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

Thaw

“Are you a technician?” The old man didn’t move. “You have a license?”

“Buddy of mine does,” I said. My hands were damp. “Power surge fried the compressor. I need the board today.”

He pulled a box from the shelf and set it between us. He scribbled on a pad, tore the sheet, and slid it over.

“Four thousand,” he smirked. “Best price.”

I stared at the paper. I didn't have four thousand. I was already drowning. No one was giving me a loan.

“Fuck,” I said. “Fuck you. Fuck this store.”

He shrugged. He didn't care. Why should he?

A week’s food. Gone.

My wife thaws. The rot spreads. The stench. The neighbors. The police.

The simplicity of complex things.

A dear friend invited me for a coffee as she wanted to get my take on the fact she was not following her excitement on her professional life anymore. And little she noticed she wasn’t then following her excitement on other points of her life, and as funny as it seems, she couldn’t immediately see the connection. So now she was on a crossroads moment asked to choose between options and wondering which path should she take. I asked her if the reason behind her question was the case she could not recognize the difference between what excites her or not. She said she could. So I very quickly asked her back where was then the difficulty? To which she kept leading me into the direction of “well but there’s a lot of things”. At this point, all I could reply was that nononono, there aren’t. I know and no offense, but there aren’t.

And what I told her just came to me as something I was elaborating and processing at the same time. Forgive my chaos.

Cause see, we tend to create a lot of reasons, a lot of seeming things we believe we need to consider but the truth is… no, we don’t. Because once you understand what excitement is you realize why you don’t have to always dissect every single little detail in order to know what to do. Acting towards your joy should be at any given moment on anything, it does not even have to be a career thing, although it’s all connected.

So if right now, out of all the options you have available to you of things you could choose to do, either if it is taking a walk or drawing something or calling a friend, the thing that brings you joy, that’s the thing to do. Just because.

You don’t need a reason why. It’s the excitement itself that tells you that’s the thing you should do. And I am very sure the excitement for simple things somehow inform you of bigger things that excite you too.

By following the excitement you recalculate your route to the shortest, fastest, straightest path. And then you should do it just once more. And again. As soon as you are done with the most exciting thing, choose the next exciting thing, even if they might not seem connected, because joy will reveal how they all fit together.

And once you get into that pattern, something funny happens: you sensitize yourself to the idea of joy, and you naturally become a better sensor of what truly excites you and what does not. And soon you will not create so many things to consider before you get willing to take action. The process becomes self‑contained, like a drive engine. Each joyful experience carries within it everything you need to know. Anything that doesn’t arrive with that feeling simply isn’t part of your path, and doesn’t deserve space in your life.

While we all want to experience life with passion, with synchronicity, feeling the vibration of our true, natural self the way we were actually created. But how many of us are willing to move towards it? Because that would mean moving towards ourselves.

BIG BUT: if those things don’t come up, you do not have to deny them, but to recognize they are there for a reason, so you can understand what they bring you to process, they will tell you more about who you are and you can continue to act more and more on your joy.

/mar26

Today is the Feast of the Annunciation, a pretty substantial observance in the Christian world related to the Blessed Virgin Mary.

It is observed on March 25 because it is nine months away from Christmas, which underscores its traditional importance: the Feast of the Annunciation is associated with the Incarnation.

One of my acquaintances from seminary once posted on social media that Christmas is not the “Feast of the Incarnation,” rather the Annunciation is. Because, according to tradition, this is the day that Our Lady, Saint Mary, conceived Jesus—the day that He first took on human flesh, incarnate as God in the womb.

I like this reminder for a variety of reasons (not least my own particular “pro-life” leanings that I seldom talk about; the New Wave Feminists are probably the closest articulation to my convictions on this subject, if you must know). What a powerful notion, that God dwelt in the womb of a woman for nine months and some change. This is even more theologically rich when we consider the traditional Jewish belief that a fetus is not its own life while still in the womb, meaning that Mary herself (for a time) actively participated in the Incarnation of God.

However, I have a bit of a nit to pick with all of this: I’m not convinced that the Annunciation is when the Incarnation happened.

The Church has long observed two key feast days related to Our Lady’s pregnancy: the Annunciation and the Feast of the Visitation. The former recounts the time the Archangel Gabriel announced to Mary that she would be the mother of God; the latter is the story of when Mary visited her cousin, Saint Elizabeth (who herself was already pregnant with Saint John the Baptist), and both recognized Mary as the mother of God and the incarnation of God taking place in her womb.

Both stories are recorded in Saint Luke’s gospel. Now, Luke is a very detailed evangelist (that is, gospel writer). Of all the known gospels, his has the most historical detail. The tradition is that he traveled around and interviewed the surviving disciples of Jesus, while also reviewing other written materials (like, perhaps, Saint Mark’s gospel), in order to give a fuller account of the life of Jesus. As a result, Luke’s gospel is the only one that contains an actual birth narrative for Jesus; it’s also the only one that gives us any real details of Saint Mary. Saint Matthew’s gospel focuses a bit on Saint Joseph (Mary’s husband), but the actual birth of Jesus is merely referenced, not told.

This is all to say that Luke has an eye for detail and tries to give us as much detail as he can. All the major events of the life of Jesus have an actual story in Luke’s gospel. If the Annunciation is meant to be the story of Jesus’ conception, it’s an odd way of telling it because it seems to happen “off camera.”

Take a look:

God sent the angel Gabriel to Nazareth, a city in Galilee, to a virgin who was engaged to a man named Joseph, a descendant of David’s house. The virgin’s name was Mary. When the angel came to her, he said, “Rejoice, favored one! The Lord is with you!” She was confused by these words and wondered what kind of greeting this might be. The angel said, “Don’t be afraid, Mary. God is honoring you. Look! You will conceive and give birth to a son, and you will name him Jesus. He will be great and he will be called the Son of the Most High. The Lord God will give him the throne of David his father. He will rule over Jacob’s house forever, and there will be no end to his kingdom.”

Then Mary said to the angel, “How will this happen since I haven’t had sexual relations with a man?”

The angel replied, “The Holy Spirit will come over you and the power of the Most High will overshadow you. Therefore, the one who is to be born will be holy. He will be called God’s Son. Look, even in her old age, your relative Elizabeth has conceived a son. This woman who was labeled ‘unable to conceive’ is now six months pregnant. Nothing is impossible for God.”

Then Mary said, “I am the Lord’s servant. Let it be with me just as you have said.” Then the angel left her. (Luke 1:26-38, Common English Bible)

Notice that the language is all in the future-tense. It’s the language of expectation. So, right off the bat we can see that, based solely on the text of the Bible itself, the Annunciation does not capture the when of Jesus’ conception.

The next thing to happen in the story is that Mary up and leaves to see Elizabeth, where Elizabeth notes that her baby (the fetal Saint John) “leaps” in her womb at the sound of Mary’s voice. Modern English translations tend to phrase Elizabeth’s greeting to Mary like this: “God has blessed you above all women, and he has blessed the child you carry.” (Luke 1:42, Common English Bible) So, if we follow the tenses of the language we’ve been given, we are led to believe that somewhere between Saint Gabriel’s announcing and Saint Elizabeth’s greeting is when Mary became pregnant. Again, the Annunciation is not the place where the conception of Jesus takes place.

Now, Elizabeth’s greeting is elsewhere enshrined in one of the most beloved prayers in Christianity, the “Hail Mary:”

Hail Mary, full of grace, the Lord is with thee. Blessed art thou among women and blessed is the fruit of thy womb, Jesus. Holy Mary, Mother of God, pray for us sinners now and at the hour of our death. (emphasis mine)

This is actually the literal translation of the Greek words. Why English translations don’t like using figurative language anymore is a topic for another time, but this phrasing does not necessarily imply that Mary is currently pregnant since “fruit of the womb” is not necessarily tied to time the way “the child you carry” is.

So here’s my assertion: it is during the Visitation that Mary conceives Jesus. I base this entirely on the language of the gospel text and what we know of Saint Luke. As already noted, it would seem out of character for Luke to include such foreshadowing language from Gabriel and not give us the pay-off. But I do believe he gives us the pay-off.

Look back to what Gabriel says to Mary when she asks “How will this happen?”

The Holy Spirit will come over you and the power of the Most High will overshadow you.

Luke uses similar language in the first chapter of Acts. In the midst of the risen Jesus giving instructions to His disciples as He is preparing to ascend into Heaven, he tells them:

You will receive power when the Holy Spirit has come upon you. (Acts 1:8 Common English Bible)

In the very next chapter this is fulfilled when tongues of flame alight on the heads of the disciples and they begin to speak in different language, filled with spiritual ecstasy.

So, let’s look again at Mary’s story. She’s been told that she will become a virgin mother, the Mother of God; the sign for this will be when the Holy Spirit comes over her and she is overshadowed by the power of the Most High—language quite evocative of what Luke says about Pentecost in Acts.

Now, consider what happens after Elizabeth’s greeting. We’re told the Holy Spirit has filled Elizabeth, herself uttering an ecstatic proclamation, recalled in that first half of the Hail Mary prayer. So the Spirit is present and what does Mary do? She has an ecstatic Spirit-filled proclamation herself.

We call it the Magnificat.

It is my conviction that the Magnificat is intended by Saint Luke to evoke the moment that Mary conceives Jesus. I also think that it is no coincidence that he has this happen at a moment where there are only two women present, perhaps underscoring the miraculous nature of this. There’s no man to be found, or even suggested (as some like the heretical bishop, the late John Shelby Spong might, with his assertion that Mary was raped, perhaps by a man named Gabriel, and that this is the church’s way of trying to turn tragedy into triumph). Rather, God enters our world in the presence of two women, both enraptured by the Holy Spirit.

So, if this is the case, what are we celebrating today? Why bother with the Annunciation?

Because the Annunciation is still good news. It’s the good news that our sins have not left us abandoned. God still chooses to be born among us, even knowing our wickedness. It is the good news that God has chosen a poor young woman to be the one from which God will take on our flesh. Not a person of wealth and power and influence. But someone of meager means, marginal and innocent.

Today we hear the good news that God refuses to be separate from us.

I think of this old tweet every year on this day. Credit to OP

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The Rev. Charles Browning II is the rector of Saint Mary’s Episcopal Church in Honolulu, Hawai’i. He is a husband, father, surfer, and frequent over-thinker. Follow him on Mastodon and Pixelfed.

#Jesus #Church #Anglican #Episcopalian #Catholic #Christian #Bible #Mary