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Channel

Mustafa Rx

@rx_mus

On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry

1,384subscribers

+192 since we began measuring on 19 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1003969978814
TypeChannel
Username@rx_mus
Created26 July 2026measured — dated from the channel’s first post
First recorded19 August 2026
Last confirmed live31 August 2026
Measurements held7
Confirmed unchanged1 time, most recently 31 August 2026
On Telegramt.me/rx_mus

Topic

Education — a classification, not a measurement. 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

1,1921,3841,28819 August 2026 — 1,192 subscribers19 August 2026 — 1,192 subscribers19 August 2026 — 1,202 subscribers22 August 2026 — 1,257 subscribers25 August 2026 — 1,312 subscribers28 August 2026 — 1,347 subscribers31 August 2026 — 1,384 subscribers19 August 202631 August 2026
7 measurements spanning 13 days, net +192. 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 1,163–1,413 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
31 Aug 2026, 19:451,384+37
28 Aug 2026, 13:371,347+35
25 Aug 2026, 15:051,312+55
22 Aug 2026, 23:481,257+55
19 Aug 2026, 21:131,202+10
19 Aug 2026, 06:151,192no change
19 Aug 2026, 06:001,192first reading

Engagement

15 posts held, back to 26 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
128.6%
avg views ÷ 1,384 subscribers
Avg views / post
1,780
6 posts measured
Reaction rate
0.277%
reactions ÷ views · ER floor
Posts in window
6
of 15 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 3 of 6 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 18 August 2026
Posts held15 (26 July 202618 August 2026)
Views total10,675
Reactions total10
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken19 Aug 2026, 06:15 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.

Reaction mix

99 reactions across 10 posts, in 7 distinct kinds. The most used accounts for 46.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
4646.5%
🍓1919.2%
🙏1616.2%
👏1010.1%
🔥66.06%
💊11.01%
🥰11.01%

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 11 of the 15 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 99 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 26 July 2026 to 18 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.

Recent posts

18 Aug 2026, 20:04 UTC≈1,450 viewsread 19 August 2026

انت واگع دور الثاني وكل ما تريد تبدي مراجعة، تحتار منين تبدي وشنو تقرأ اليوم وشنو تخلي لباجر؟ الفكرة بسيطة جدا أنا أسويلك جدول مراجعة كامل لأي مادة واگع بيها، أقسم لك المادة على الأيام والـ Chapters، وأحددلك شنو مطلوب منك بكل يوم وبعدها ما أخليك وحدك مع الجدول، كل يوم تراجع الجزء المحدد، وأنا أمتحنك عليه حتى تعرف شكد فاهم وشكد تحتاج تراجع وخلال الفترة راح يكون عندك: 📝 Daily Quizzes 📋 Midterms 🔥 Finals يعني تمشي ب

9 Aug 2026, 12:28 UTC≈1,680 viewsread 19 August 2026

هذه المراجعة لمادة الفارما المرحلة الثالثة الكورس الثاني تكون مناسبة لكم؟ يمكنكم اعطائنا آرائكم عبر بوت التواصل: @mussphbot او عبر حسابنا الشخصي: @rx_mustafa

9 Aug 2026, 12:22 UTC≈1,300 views5 reactionsread 19 August 2026

Pharmacology (علم الأدوية) الـ Pharmacology هو العلم اللي يدرس المواد أو الأدوية (Drugs) اللي تتفاعل ويه جسم الإنسان عن طريق تفاعلات كيميائية. هاي الأدوية تشتغل يا إمّا تنشّط (Stimulate) العمليات الطبيعية بالجسم، أو تثبّط (Inhibit) هاي العمليات، وبهيچ تحقق التأثير العلاجي المطلوب دراسة تفاعل الدواء ويه الجسم (Drug Interactions) تنقسم إلى قسمين رئيسيين: أولاً: Pharmacodynamics الـ Pharmacodynamics تعني شنو الدواء

3🔥2

9 Aug 2026, 12:22 UTC≈1,540 views2 reactionsread 19 August 2026

أما عيوبها فهي: 1. مؤلمة 2. بعض المرضى يخافون منها 3. ممكن تسبب Tissue Damage. 4. ممكن تسبب Infections. وإذا انأخذت الجرعة، ما نكدر نسحبها أو نتراجع عنها (Irreversible)

1🔥1

9 Aug 2026, 12:22 UTC765 views3 reactionsread 19 August 2026

بس الله نبدأ مراجعة مادة الفارما الوزارية لطلبة المرحلة الثالثة الدور الثاني:

3

7 Aug 2026, 18:22 UTC≈3,940 viewsread 19 August 2026

عندك دور ثاني وحاير بالمواد ؟ بعدك ما بادي ؟ المواد هواي ؟ تريد شخص يوگف فوگ راسك ويتابعك كل يوم لحد ما تمتحن دور ثاني وتخلص وتضمن نجاحك؟ تريد شخص يمتحنك كل يوم كوزات ومدات وفاينلات ؟ الحل يمي تواصل وياي: @rx_mustafa 📍Telegram: @rx_mus

29 Jul 2026, 20:06 UTC≈1,700 views0 reactionsread 19 August 2026
Photo

الجدول المقترح لأمتحانات التقويمي للدور الثاني للعام 2025-2026

27 Jul 2026, 10:19 UTC≈1,720 views18 reactionsread 19 August 2026
Photo

ملخص الدرس الثاني 🌟 📍Telegram: @rx_mus

9🙏4🍓3👏1🔥1

27 Jul 2026, 10:19 UTC≈1,140 views21 reactionsread 19 August 2026

💊 Chapter 1 – Gastrointestinal Disorders (GIT) 📖 Lesson 2 Gastroesophageal Reflux Disease (GERD) & Heartburn 🎯 أهداف الدرس بعد إكمال هذا الدرس راح تكدر: تعرف شنو هو GERD. تفرق بين Heartburn وGERD. تعرف الأسباب وعوامل الخطورة. تعرف العلاج الدوائي وغير الدوائي. تعرف متى تحول المريض للطبيب. أولًا: شنو هو GERD؟ الGERD هو رجوع حمض المعدة (Stomach Acid) إلى المريء بسبب ضعف الصمام الموجود بين المريء والمعدة (Lower Es

🍓106🙏4🔥1

27 Jul 2026, 10:08 UTC696 views3 reactionsread 19 August 2026

نستقبل اسئلتكم عبر حساب القناة: @rx_mustafa

2👏1

27 Jul 2026, 10:06 UTC782 views15 reactionsread 19 August 2026
Photo

ملخص الدرس الاول 🌟 📍Telegram: @rx_mus

👏8🍓32🥰1🙏1

27 Jul 2026, 10:00 UTC≈3,310 views20 reactionsread 19 August 2026

💊 Chapter 1: Gastrointestinal Disorders (GIT) 🎓 Lesson 1 Introduction to GIT in Community Pharmacy أهداف الدرس بعد هذا الدرس راح تكدر: تعرف أكثر حالات الـ GIT اللي تجي للصيدلية. تميز بين الحالات البسيطة والحالات الخطرة. تعرف شلون تستقبل المريض وتسأله الأسئلة الصحيحة. تعرف متى تصرف دواء OTC ومتى تحوّل المريض للطبيب. أولاً: ليش الـ GIT مهم جدًا؟ تقريبًا 30–40% من مراجعي الصيدليات يجون بسبب مشاكل بالجهاز الهضمي،

13🍓3🙏2💊1🔥1

Showing the 12 most recent of 15 posts we hold for @rx_mus. 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.

Citation-graph rank

Citation-graph rank — 659,745 of 1,629,419 entries 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.

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.

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 31 August 2026 — this entry's latest reading, not the date you are reading this.

“Mustafa Rx” (@rx_mus), 1,384 subscribers as measured 31 August 2026. Telegram Register, tgregister.com/channel/rx_mus.

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.