Актуальный и полезный контент на тему иммунодиетологии, персонифицированного питания, нашего здоровья.
№5673934251
Администратор
@vnukovamn_info
https://mnvnukova.ru/
#0WERV
Created
Between 1 April 2019 and 31 October 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Health & wellness — 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 the other topics.
Growth
60 measurements spanning 92 days, net +644. 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 20,805–21,829 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 60
Measured (UTC)
Subscribers
Change
7 Nov 2026, 16:56
21,711
+39
6 Nov 2026, 14:46
21,672
+33
5 Nov 2026, 18:11
21,639
+48
4 Nov 2026, 16:47
21,591
+57
3 Nov 2026, 13:48
21,534
+38
2 Nov 2026, 12:21
21,496
+29
1 Nov 2026, 15:40
21,467
+4
31 Oct 2026, 17:25
21,463
+6
30 Oct 2026, 19:39
21,457
-1
29 Oct 2026, 19:49
21,458
+15
28 Oct 2026, 17:01
21,443
-6
27 Oct 2026, 14:16
21,449
+9
26 Oct 2026, 13:19
21,440
+12
25 Oct 2026, 12:59
21,428
+10
24 Oct 2026, 11:45
21,418
-6
23 Oct 2026, 12:06
21,424
+4
22 Oct 2026, 14:38
21,420
+41
21 Oct 2026, 07:01
21,379
+20
20 Oct 2026, 05:08
21,359
+41
19 Oct 2026, 04:18
21,318
first reading
Engagement
48 posts held, back to 26 June 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 71 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.14%
avg views ÷ 21,711 subscribers
Avg views / post
1,990
15 posts measured
Reaction rate
2.39%
reactions ÷ views · ER floor
Posts in window
15
of 48 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 7 November 2026
Posts held
48 (26 June 2026 – 7 November 2026)
Views total
29,780
Reactions total
713
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Nov 2026, 02:57 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
903
Videos
280
Links
548
Lifetime counters from Telegram’s own channel header, read 8 November 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
2h 10m
Average length
26m 06s
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
2,562 reactions across 48 posts, in 7 distinct kinds. The most used accounts for 42.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,098
42.9%
🔥
663
25.9%
👍
511
19.9%
❤🔥
176
6.87%
👏
76
2.97%
🥰
36
1.41%
🤯
2
0.078%
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 48 of the 48 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 2,562 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 48 most recent posts we hold, published 26 June 2026 to 7 November 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
245
across the posts below
Posts paid on
44
of 48 we hold a reading for · 92%
Most on one post
25
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @mn_vnukova. 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 48 most recent posts we hold for this entry, published 26 June 2026 to 7 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 5 of 15 posts held from the last 30 days (33.3%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
А для того, чтобы не болеть.
Да, пожалуй, это одна из самых важных мыслей всей моей программы.
Потому что обычно человек начинает заниматься собой тогда, когда уже:
🔘болит,
🔘не спит,
🔘страшно,
🔘накрыло,
🔘сил нет,
🔘анализы поползли,
🔘врач назначил очередное лечение.
То есть когда организм уже орёт.
А можно ли раньше заметить:
— что после общения с определённым человеком вы каждый раз выжаты;
— что в каком-то месте ва…
Давайте сегодня проведём очень простую диагностику😌😏
Не крови...
Не гормонов...
Не витаминов...
А своего внимания!
С утра вы открыли Telegram.
Почитали новости.
Потом чей-то конфликт попался в reels.
Возможно заглянули в комментарии.
Потом еще попалась история незнакомого человека, который разводится.
Или чей-то страшный диагноз.
Затем посмотрели пятнадцать коротких видео.
Заполировали очередной проверкой сообщений…
🅰️🅰️🅰️🅰️🅰️🅰️ 🅰️🅰️🅰️🅰️🅰️
История информационной медицины. Что собственно такое Информмед?
🌟 откуда взялось это направление;
🌟 какое место в ней занимают древние знания и современные методы;
🌟 чем информационная медицина отличается от привычного подхода к здоровью;
🌟 какие задачи она решает;
🌟 почему мне особенно важно сегодня учить людей самодиагностике и самопомощи.
🌿🌿и 🌿🌿ноября состоятся оффлайн-занятия по ин…
Информационная медицина — это вообще что?
Таких вопросов мы собираем тоннами и пожалуй, пора начать с начала.
Мы уже говорили о плацебо и ноцебо, биофизике, энергетической гигиене, влиянии информации, различных практиках…
А базовый вопрос всё равно остаётся:
что мы вообще называем информационной медициной и откуда всё это взялось?
Поэтому 5 ноября в 19:00 по Москве встречаемся в прямом эфире «История информационной …
Есть такое выражение: информационная медицина — медицина будущего.
И мне хочется показать на конкретном случае, почему я с этим согласна.
Молодая девушка. Сильнейшая аллергия на протяжении 6 лет: поллиноз, крапивница, отёк Квинке, однажды даже анафилактический шок.
Постоянный прием препаратов, БАДы, попытки как-то удерживать состояние.
Когда она ко мне пришла, иммунодиетологией я ещё не занималась, с Иммунохелс не р…
ПИЯВКИ. СРЕДНЕВЕКОВЬЕ, КОТОРОЕ ОКАЗАЛОСЬ СОВРЕМЕННОЙ МЕДИЦИНОЙ
Если вам кажется, что гирудотерапия — это что-то из серии «бабушка, тазик, пиявочки и XVIII век», у меня для вас новости.
В США медицинская пиявка — вполне себе регулируемый медицинский инструмент.
Её используют хирурги. Не шаманы. Не травницы в избушке. Пластические и реконструктивные хирурги.
Например, когда после сложной операции, пересадки тканей или …
Что сегодня сильнее всего влияет на наше информационное здоровье?
В эфире разобрали:
🧆 как современная пища, информационный шум и электромагнитная нагрузка влияют на состояние и мышление;
🧆 какие факторы здоровья мы постепенно потеряли;
🧆 почему важно защищать не только тело, но и собственное внимание и мышление;
🧆 простые способы самопомощи: заземление, работа с водой и цветом, восстановление сна и состояния.
🌮И г…
Эфиру быть, сегодня 29 октября в 19:00 мск, поговорим открыто об информационной медицине.
Поговорим о том, что сегодня влияет на нас сильнее, чем принято замечать:
⏺ современные угрозы информационному здоровью;
⏺ факторы здоровья, которые человек постепенно утратил;
⏺ взгляд натуропата на доказательную медицину;
⏺ 3 простых метода оздоровления, которые можно начать применять самостоятельно.
Пришло время знать о с…
Если растению плохо на одном месте — мы его пересаживаем.
А себя почему-то продолжаем упорно «выращивать» там, где нам плохо.
Спим на одной и той же стороне комнаты, годами сидим за одним рабочим столом, обустраиваем пространство так, как красиво и удобно по планировке — и редко задаём себе простой вопрос:
А как в этом месте чувствует себя мой организм?
Иногда достаточно изменить положение кровати или рабочего мес…
Я бы вообще не советовала вам верить в информационную медицину.
Верить очень ненадёжный метод познания.
Один человек верит в акупунктуру, другой нет.
Один смеётся над дыхательными практиками, другой без них уже не представляет свою жизнь.
Кому-то слово «энергия» понятно, у кого-то сразу начинает дёргаться глаз.
И знаете что?
Это вообще не имеет значения.
Гораздо интереснее другой вопрос:
что с вами произошло после…
Есть подозрение, что информационной медициной вы уже пользуетесь. Просто не знаете, что это она.
Вы включаете музыку — и через несколько минут состояние меняется.
Зажигаете определенный аромат — и легче расслабиться.
Дышите медленнее, когда нервничаете.
Интуитивно растираете место, которое заболело.
После тяжёлого дня идёте в горячую ванну.
Выходите в лес — и говорите:
«Вот теперь я снова человек».
Кто-то пользуется…
А что, если наша главная задача, не научиться лечить себя от всего на свете, а перестать быть беспомощным перед собственным состоянием?
На одном из эфиров моя ученица Люба открыла конспект с занятий по информационной медицине.
Во время обучения у неё было простое задание: выписать всё, что её наполняет и всё, что забирает энергию.
Получилось 7 пунктов, с которыми хотелось разобраться.
Через два месяца она снова отк…
🔥17❤11👏4
Showing the 12 most recent of 48 posts we hold for @mn_vnukova. 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.
Posts edited after publishing
@mn_vnukova edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
28 August 2026
Most recent edit
1 September 2026
Posts recorded as deleted after publishing
We recorded 4 posts on @mn_vnukova as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
18 August 2026
Most recent seen missing
27 August 2026
Median time before seen missing
4 days
Seen missing in the last 30 days
0
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 6 registered channels — 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.
Женское здоровье | Ольга Андросова @drandrosova · 8,287#93
Ободзинская Татьяна Евгеньевна @obodzinskaya · 7,933#94
Эксперт по предназначению |Ведический астролог | Анастасия @gen_pasport · 3,030#95
Read from Telegram’s recommendation API, most recently 25 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.
dals_zdorovye @dals_zdorovye · 1 Telegram ranks this channel #6 of 87 here — alongside 86 others — read 29 September 2026
UniProf для врачей @uniprof_med · 31,744 Telegram ranks this channel #9 of 93 here — alongside 92 others — read 5 September 2026
🦋 Библиотека АИТ @ms_hashimoto · 19,525 Telegram ranks this channel #13 of 91 here — alongside 90 others — read 1 October 2026
Химия Пищи/Биохакинг/ А.Родионова @ximiya_tasya_ro · 24,185 Telegram ranks this channel #15 of 93 here — alongside 92 others — read 16 September 2026
Gastrosmile🌱Гастросмайл🌱Венера Хабирова🌱Интегративный Гастроэнтеролог @gastrosmile · 40,987 Telegram ranks this channel #15 of 93 here — alongside 92 others — read 29 August 2026
Женское здоровье @pro_zhenskoe_zdorovie · 21,206 Telegram ranks this channel #20 of 95 here — alongside 94 others — read 24 September 2026
Полезные заметки доктора Голевой @zametkidoctora · 48,304 Telegram ranks this channel #21 of 90 here — alongside 89 others — read 6 September 2026
Доктор Павлов @doc_gastro_life · 77,492 Telegram ranks this channel #21 of 94 here — alongside 93 others — read 19 August 2026
ИЗБА МОЛОДИЛЬНЯ @izbamolodilnya · 21,101 Telegram ranks this channel #24 of 86 here — alongside 85 others — read 26 September 2026
Аюрведа и интегративная нутрициология / Крушанова Юлия @krushanova · 21,498 Telegram ranks this channel #29 of 92 here — alongside 91 others — read 22 September 2026
Эндокринолог Либеранская @liberanskaya · 25,626 Telegram ranks this channel #30 of 88 here — alongside 87 others — read 14 September 2026
Доктор Владимир Попов | detsdoc @detsdoc · 58,245 Telegram ranks this channel #31 of 91 here — alongside 90 others — read 22 August 2026
Ирина Шиманская Holistica @tibetdoc · 78,900 Telegram ranks this channel #31 of 96 here — alongside 95 others — read 18 August 2026
Ирина Баранова🇷🇺 Врач anti-age @baranovaia · 31,064 Telegram ranks this channel #32 of 92 here — alongside 91 others — read 6 September 2026
Предзапись в институт МИФИМ 🎓 @doctor_zubareva_brand · 18,962 Telegram ranks this channel #35 of 95 here — alongside 94 others — read 1 October 2026
Доктор Марина Мальцева|🌿Интегративная медицина @mvmaltseva · 39,897 Telegram ranks this channel #37 of 82 here — alongside 81 others — read 30 August 2026
Первая Школа Биохакинга | Здоровье @pervayashkola · 23,756 Telegram ranks this channel #38 of 90 here — alongside 89 others — read 17 September 2026
Заметки невролога Овсянникова КС @zametki_nevrologa · 72,056 Telegram ranks this channel #38 of 85 here — alongside 84 others — read 20 August 2026
Здравомыслие в еде @zdravomislievede · 31,920 Telegram ranks this channel #39 of 97 here — alongside 96 others — read 6 September 2026
Doclana.mornatural @doclana_mornatural · 31,968 Telegram ranks this channel #39 of 80 here — alongside 79 others — read 6 September 2026
Клиника Калинченко @kalinchenko_dlya_pacientov · 40,777 Telegram ranks this channel #39 of 91 here — alongside 90 others — read 30 August 2026
Кардиолог Чайковская @cardiolog_chaykovskaya · 57,948 Telegram ranks this channel #42 of 94 here — alongside 93 others — read 23 August 2026
Leonov chef @leonovchef · 51,021 Telegram ranks this channel #51 of 92 here — alongside 91 others — read 25 August 2026
ПланетаМед - клиники сложного диагноза @planetamed · 34,939 Telegram ranks this channel #58 of 83 here — alongside 82 others — read 2 September 2026
This channel appears in 29 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 7 November 2026 — this
entry's latest reading, not the date you are reading this.
“Здоровье и не только с Мариной Внуковой” (@mn_vnukova), 21,711 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/mn_vnukova.
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.