2 measurements spanning 1 day. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 125–127 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
9 Aug 2026, 02:17
126
no change
7 Aug 2026, 22:26
126
first reading
Engagement
17 posts held, back to 10 March 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
84.9%
avg views ÷ 126 subscribers
Avg views / post
107
1 post measured
Reaction rate
7.48%
reactions ÷ views · ER floor
Posts in window
1
of 17 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 1 August 2026
Posts held
17 (10 March 2026 – 1 August 2026)
Views total
107
Reactions total
8
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
9 Aug 2026, 02:17 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
11
Videos
5
Links
6
Lifetime counters from Telegram’s own channel header, read 9 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
10m 38s
Average length
2m 08s
Measured directly from 5 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
108 reactions across 17 posts, in 8 distinct kinds. The most used accounts for 37.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
💊
40
37.0%
🏆
22
20.4%
💯
14
13.0%
❤
13
12.0%
🆒
12
11.1%
🔥
5
4.63%
👏
1
0.926%
🥰
1
0.926%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 17 of the 17 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 108reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 17 most recent posts we hold, published 10 March 2026 to 1 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram Stars
Stars received
1
across the posts below
Posts paid on
1
of 17 we hold a reading for · 6%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @trenfi1. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 17 most recent posts we hold for this entry, published 10 March 2026 to 1 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Давно меня не было. Кипиш в жизни.
✅️ Поэтому короткий пост про магний:
Эффекты:
• Снижение тревожности
• Сокращение быстрого потока лишних мыслей
• Улучшение сна
• Уменьшение судорог
• Снижение эксайтотоксичности
• Улучшение ГАМК-системы
• Улучшение адаптации во время стресса
Механизмы:
1) Блокада NMDA-рецепторов (основной механизм снижения возбуждения)
NMDA-рецепторы — ионотропные рецепторы глутамата (главного во…
Вот и новый формат 📱
Идеально подойдёт тем, кто любит поглощать информацию по 3 часа)
В серии онлайн-подкастов «ПНД» с Ярославом мы в основном будем затрагивать тему ноотропов и биохакинга в контексте спорта. Но про учеников не забываю и иногда буду забирать себе тайм-код, чтобы рассказать что-то для тех, кто качает мозг 🧠
В конце всегда будем отвечать на вопросы, которые накопились. Поэтому милости прошу в коммен…
Срочно! Эфир с Ярославом Завражневым 🔥
https://youtube.com/live/qhpIsiqZxFs?feature=share
27 июня в 21:00 по МСК
Отвечаем на все ваши вопросы.
Пишите их заранее в комментариях к этому посту 👇🏻
Что будем разбирать:
✅ Биохакинг
✅ Тренировки и качалка
✅ Ноотропы
✅ Психика и ментальное здоровье
✅ Теория + реальная практика
✅ СМАЕВ
✅ Лучший проект «База знаний»
Кто такой Ярослав Завражнев?
Пришел к идее тренинга в 17 …
Вот все ссылки на проект Ярослава.
Скидка 20% и +7 дней по промокоду: TRENFIL20
Бот: https://t.me/Benzoate_bot?start=ref_1014397855
Канал: https://t.me/biohackyar
Сайт: https://yarohack.ru/
❗️ +7 дней можно получить только при оформлении подписки по этой ссылке:
https://t.me/Benzoate_bot?start=ref_1014397855
Всего 50 активаций. Одна активация на аккаунт. До 25.07.2026. Если вам зайдёт и будет выхлоп, то акция ст…
Друзья, сегодня поговорим о метаболических ноотропах (или энерготропных средствах) — веществах, которые работают не через нейротрансмиттеры напрямую, а через клеточную энергию. 🔋
🧠 Мозг — самый энергозатратный орган: он потребляет ~20-25% всей энергии тела, несмотря на малый вес. Когда митохондрии работают плохо, снижается АТФ (главная "валюта" клетки), появляется усталость, туман в голове, падает концентрация, памя…
🎮 Идеальный стек для геймеров: мой проверенный вариант
Пост с подробным объяснением каждой позиции. Почему именно эти вещества лучше всего подходят для долгих и регулярных игровых сессий.
Сначала разберёмся со спецификой
Вся деятельность проходит сидя. Главная нагрузка — на мозг и нервную систему. Туда и нужно направлять максимум энергии и восстановления.
Что критично для геймера:
- Мотивация
- Быстрая реакция
- С…
🔥 Есть отличный ноотроп, который улучшает и психическое, и физическое здоровье. И этого уже было бы достаточно. Но есть ещё один жирный плюс — он растит нейроны 🧠. И это не препарат и не добавка. Это баня.
Давно знаю и очень ценю ноотропные свойства бани, а после сегодняшнего хамама решил наконец рассказать вам. (Естественно, потому что за секунду у меня выросли новые нейронные связи, и весь этот пост я уже написал …
Никотин как ноотроп: как он работает и стоит ли его использовать? 🧠⚡
Никотин — это алкалоид, который в первую очередь известен по табаку. Но в малых дозах (особенно в чистом виде — жвачки, пластыри, снюс) он проявляет выраженные ноотропные свойства 🔥. Его активно используют программисты, шахматисты и другие когнитивные работники для фокуса и продуктивности.
Как работает никотин в мозге? 🧬
Никотин имитирует нейроме…
Ноотропные связки из двух позиций. Низ айсберга 💊 🧠
Сразу уточню: это «низ айсберга» не потому, что препараты опасные, а потому что их сложнее достать и они менее известны. Плюс эффект часто неочевиден (для новичков), если неправильно подобрать или использовать.
Разберём самые интересные и рабочие связки:
1) Йохимбин гидрохлорид + Кофеин 🐺☕
Йохимбин даёт мощную норадреналиновую стимуляцию — гормон «хищника». Ты в…
как и обещал
Ноотропные связки из двух позиций.
Верхушка айсберга: 🧊
Теанин + Кофеин ☕
Классика жанра. Кофеин даёт энергию и бодрость, теанин добавляет концентрацию и спокойствие. В итоге — чистая работоспособность без трясущихся рук, нервозности и желания пылесосить всю квартиру в 3 часа ночи.
Тирозин + Кофеин ⚡
Тирозин — предшественник дофамина. Даёт более «дофаминовую» энергию, без сильного истощения ЦНС. Эф…
Как обещал, вот все ссылки на исследования и обзоры.
Омберацетам:
https://nnp.ima-press.net/nnp/article/view/1784
https://pubmed.ncbi.nlm.nih.gov/39298839/
https://cyberleninka.ru/article/n/primenenie-preparata-noopept-pri-kognitivnyh-narusheniyah-razlichnogo-geneza
https://cyberleninka.ru/article/n/molekulyarnyy-mehanizm-deystviya-noopepta-zameschennogo-pro-gly-dipeptida
Фонтурацетам:
https://cyberleninka.ru/ar…
❤2💊1
Showing the 12 most recent of 17 posts we hold for @trenfi1. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank
Citation-graph rank — 1,300,340 of 1,480,944entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 9 August 2026 — this
entry's latest reading, not the date you are reading this.
“тренфил” (@trenfi1), 126 subscribers as measured 9 August 2026. Telegram Register, tgregister.com/channel/trenfi1.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.