Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
32 measurements spanning 42 days, net -51. 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 24,359–24,525 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
18 Sept 2026, 03:00
24,378
-21
15 Sept 2026, 18:57
24,399
-5
14 Sept 2026, 03:15
24,404
-29
12 Sept 2026, 09:39
24,433
-7
10 Sept 2026, 04:16
24,440
-1
6 Sept 2026, 21:42
24,441
-21
4 Sept 2026, 10:16
24,462
+3
3 Sept 2026, 01:04
24,459
-11
1 Sept 2026, 21:34
24,470
-5
1 Sept 2026, 00:25
24,475
-17
30 Aug 2026, 22:55
24,492
-3
30 Aug 2026, 01:58
24,495
-8
29 Aug 2026, 00:12
24,503
-2
27 Aug 2026, 22:12
24,505
+4
26 Aug 2026, 22:48
24,501
+2
25 Aug 2026, 21:46
24,499
-3
24 Aug 2026, 19:57
24,502
-4
23 Aug 2026, 03:52
24,506
+2
21 Aug 2026, 14:44
24,504
-2
20 Aug 2026, 12:44
24,506
first reading
Engagement
63 posts held, back to 29 July 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 57 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
3.41%
avg views ÷ 24,378 subscribers
Avg views / post
830
27 posts measured
Reaction rate
2.15%
reactions ÷ views · ER floor
Posts in window
27
of 63 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. It is computed over the 26 of 27 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 2 September 2026
Posts held
63 (29 July 2026 – 2 September 2026)
Views total
22,420
Reactions total
461
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 10:42 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
Video runtime
8m 20s
Average length
38s
Measured directly from 13 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
1,269 reactions across 60 posts, in 8 distinct kinds. The most used accounts for 47.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
603
47.5%
🔥
281
22.1%
👍
161
12.7%
😁
72
5.67%
🥰
72
5.67%
👏
70
5.52%
🎉
6
0.473%
👌
4
0.315%
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 60 of the 63 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 1,269 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 63 most recent posts we hold, published 29 July 2026 to 2 September 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
2
across the posts below
Posts paid on
2
of 62 we hold a reading for · 3%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @aynastudy. 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 63 most recent posts we hold for this entry, published 29 July 2026 to 2 September 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.
🍁 Осень — время обновлять знания и внедрять новые протоколы!
Мы собрали самые актуальные темы: от инновационных экзосом и пептидов до разбора сложных клиентских случаев и anti-age протоколов.
Выбирайте мероприятия для себя! 👇
9 сентября в 14:00 (СР) | 💻 Онлайн-вебинар (Бесплатно)
Пептиды нового поколения в косметике: от состава к результату
Спикер: Романис Ботин-Маевски
14 сентября в 12:00 (ПН) | 💻 Онлайн-вебинар…
6 сентября — «Практикум для эстетиста», новый поток
Если обучение позади, но вам не хватает уверенности в руках и и понимания, какие параметры выставлять на аппаратах — этот практикум для вас.
Занятия позволят перевести ваши знания в твердую мышечную память. Теорию вы изучаете дома в записи, а время в классе посвящаете только постановке руки под контролем преподавателя.
Какие методики вы отработаете до автоматизма…
С 1 сентября! К новому бьюти-сезону готовы? 🎓
Школа давно позади, но для настоящего профессионала 1 сентября — это всё еще важный день. Ведь осень в косметологии — это старт нового, самого активного бьюти-сезона! Время мощных пилингов, аппаратных протоколов и обновления знаний.
С праздником, дорогие коллеги! Растите, учитесь, не бойтесь сложных задач и будьте лучшими в своем деле.
ПЕРЕВЕДИТЕ ФРАЗУ НА КОСМЕТОЛОГИЧЕ…
Мы думаем, каждый помнит то самое особенное чувство, когда в детстве приходил к маме или папе на работу. Всё вокруг казалось таким взрослым, важным и немного загадочным.
🔔К 1 сентября наше подрастающее поколение решило пойти ещё дальше и провести настоящее расследование на нашем производстве — куда уходит мама каждое утро? 🕵️♀️
Наш юный ревизор выяснил, что технологи не просто «нажимают кнопочки», а управляют насто…
😃😃😃😃 Набор пептидной косметики за 1 фото
Рабочее место косметолога — это настоящий храм красоты. Мы хотим полюбоваться вашими кабинетами и порадовать вас подарками.
Что нужно сделать?
Просто отправьте в комментарии под этим постом фото вашего рабочего места (главное условие — в кадре должна быть косметика MESOMATRIX).
Приз того стоит!
Случайным образом среди фотографий рандомайзер выберет счастливчика, который по…
ПРОТОКОЛ MESOMATRIX Dermatology Peptide System
Кому подходит: коже с возрастными изменениями, обезвоженностью, тусклым тоном, снижением упругости и пастозностью.
Главная ценность пептидной системы — возможность менять акценты с учётом состояния кожи.
⏩ Очищающий гель с комбучей и зеленым чаем
⏩ Липосомальный тонер с церамидами
⏩ Сыворотка-бустер с экзосомами
Крем выбирайте в зависимости от задачи и состояния кожи…
Ретинол без раздражений? Знакомимся с HPR — ретиноидом нового поколения 🧬
Все знают: ретиноиды — золотой стандарт anti-age. Но у них есть обратная сторона — сухость, шелушение и период адаптации.
Сегодня в фокусе косметологии Hydroxypinacolone Retinoate (HPR). Если вы попытались прочитать это название вслух, то наверняка поняли, почему наши технологи ласково называют его «пина коладой» 🍹
Почему это прорыв?
Класси…
Законы, новые активы, тренды... У вас есть время следить за всем этим?
Обычно на это уходят часы, которых у косметолога просто нет.
Мы уже проанализировали инфополе и готовы выдать вам самую суть на эфире «Горячий понедельник» 🔥
Всего за 1 час вы узнаете:
▫️ Что изменилось в косметологии за месяц.
▫️ Какие тренды принесут вам деньги в августе.
▫️ Как избежать новых юридических ошибок.
Готовьте кофе, блокнот и жми…
Презентация прошла, но самое интересное впереди
Мы благодарны за то, как тепло вы встретили MESOMATRIX Dermatology Peptide System.
Для нас важна ваша обратная связь. Пробуйте разные протоколы и обязательно рассказывайте, как продукты показывают себя в деле.
Для тех, кто хочет погрузиться в новинки еще глубже, у нас две отличные новости:
1️⃣ 2 сентября бесплатный вебинар для косметологов Премьера MESOMATRIX Derma…
ЭКЗОСОМЫ. Как объяснить клиенту, что это такое?
Записали для вас небольшую видео-шпаргалку, почему экзосомы корректнее называть растительными везикулами и как грамотно (и безопасно) преподносить этот ингредиент.
➡️Сыворотка-бустер с экзосомами MMD
Слушаем и запоминаем 👂
👏5🔥4❤2
Showing the 12 most recent of 63 posts we hold for @aynastudy. 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.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Сторис для Бьюти-мастеров | Готовые посты для Бьюти-мастеров @content_like · 17,449#55
Read from Telegram’s recommendation API, most recently 22 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
КОСМЕТОЛОГИЯ КОНТЕНТ @cosmetology_content · 23,995 Telegram ranks this channel #13 of 57 here — alongside 56 others — read 22 September 2026
Косметология | Дерматология @lubaeva · 28,753 Telegram ranks this channel #24 of 65 here — alongside 64 others — read 22 September 2026
Клиенты и деньги | Ольга Полякова @polyakovacash · 33,482 Telegram ranks this channel #35 of 56 here — alongside 55 others — read 22 September 2026
Косметология и здоровый образ жизни @kosmetologia_ru · 158,870 Telegram ranks this channel #36 of 52 here — alongside 51 others — read 22 September 2026
This channel appears in 4 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“Академия косметологии АЮНА” (@aynastudy), 24,378 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/aynastudy.
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.