Telegram RegisterThe public register of Telegram
Telegram profile photo for Alehssan First year Library

Channel

Alehssan First year Library

@GeneralLiprary27

On this record: Growth · Engagement · Posts · Citations · Telegram's recommendations · Cite this entry

7,108subscribers

+10 since we began measuring on 3 September 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001111855352
TypeChannel
Username@GeneralLiprary27
CreatedBetween 1 February 2017 and 15 March 2019 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded3 September 2026
Last confirmed live3 September 2026
Measurements held2
Confirmed unchanged1 time, most recently 3 September 2026
On Telegramt.me/GeneralLiprary27

Growth

7,0987,1087,1033 Sept 2026, 05:32 — 7,098 subscribers3 Sept 2026, 23:38 — 7,108 subscribers3 Sept 2026, 05:323 Sept 2026, 23:38
2 measurements taken within a single day, net +10. 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 7,097–7,110 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
3 Sept 2026, 23:387,108+10
3 Sept 2026, 05:327,098first reading

Engagement

20 posts held, back to 15 March 2019the 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
1.83%
avg views ÷ 7,108 subscribers
Avg views / post
130
1 post measured
Reaction rate
this channel exposes no reaction counts
Posts in window
1
of 20 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
WindowRolling 30 days · latest post in window 28 August 2026
Posts held20 (15 March 201928 August 2026)
Views total130
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 05:32 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.

Recent posts

28 Aug 2026, 19:02 UTC130 viewsread 3 September 2026

Medical GPT Pro 🎓 بوت طبي 👨‍⚕ يجاوب أسئلتك بدقة 🎯 من مصادر موثوقة ✅ @AlehssanGPTbot

23 Mar 2026, 19:24 UTC≈2,350 viewsread 3 September 2026
Forwarded from @alehssan_serialPhoto

رابط الإنضمام لجميع قنوات الإحسان الطبية بنقرة واحدة ✅ : https://t.me/addlist/hyCn-j1cgN8zNmI0

12 Jan 2022, 07:17 UTC≈20,400 viewsread 3 September 2026

السلام عليكم ورحمة الله بحمد الله تم الانتهاء من إنشاء القناة الخاصة بكورس ال Physiology and biochemistry 2 لطلاب السنة الأولى وذلك بجهود الفريق الجميل ❤️ One link team بادارة مميزة من فريق One of a kind students وهم المسؤولين عن تحديث وادارة قنوات الاحسان بشكل دوري . نسال الله ان يكون هذا العمل في ميزان حسناتهم . الشكر خاص للزملاء : بابكر يعقوب الدفعة 29 احمد عبد الباقي الدفعة 31 علي جهودهم الكبيرة ❤️🌸 رابط الق

30 Dec 2021, 19:19 UTC≈17,000 viewsread 3 September 2026

Alehssan General Embryology is Now Ready for you 🙃❤️🔥 تم بحمد الله إضافة قناة الإحسان لكورس الإمبريو 👶 معا نتسع حتى النجوم ❤️🔥 تحتوي القناة على كل ما تتمناه و أكثر إبتداءً من مقدمة عن الكورس حتى الإمتحانات و الفيديوهات و الشيتات و الشروحات و الكثير بانتظاركم 🤓 رابط القناة : t.me/Alehssan_Embryo Always ❄️ Beyond Imagination ❄️ Powered by : One of aKind Students 31🔺@ooas31 🔻 @ooalink One Link Team 🔗

24 Oct 2021, 08:11 UTC≈17,500 viewsread 3 September 2026

بحمد الله تمت اضافة قناة الاحسان لل General Anatomy لطلاب السنة الاولى . كبداية لوضع كل كورس في السنة الاولي في قناة منفصلة مما يقلل عبء البحث عن الكورسات داخل القناة الكبرى الخاصة بالسنة الاولي و تعتبر أول قناة بالنظام و الواجهة الجديدة ❤️🔥 تم هذا العمل بمجهود فريق تحديث قنوات االاحسان (one link team) للوصول للقناة قم بزيارة هذا الرابط https://t.me/Alehssan_Anatomy

15 Mar 2019, 15:20 UTC≈36,600 viewsread 3 September 2026
Photo

فهرست كورسات السنة الاولى: #Ferist year library content :- 😍👌

15 Mar 2019, 14:50 UTC≈25,400 viewsread 3 September 2026

الفهرست لكورس الفارما #Pharmacology course :- 😍👌

15 Mar 2019, 14:41 UTC≈10,700 viewsread 3 September 2026

1- Driving force in drug movement in aqueous diffusion model: A) active transport-- energy requiring B) facilitated transport C) drug concentration gradient *C. 2- Renal excretion factor most likely to be sensitive to drug ionization state: A) glomerular filtration B) passive tubular reabsorption * B 3-Drug(s) which exhibit(s) a high hepatic" first-pass" effect: A) lidocaine B) propranolol C) both D)

Showing the 12 most recent of 20 posts we hold for @GeneralLiprary27. 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.

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

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.

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.

فيديوهات د. ايمن خنفور - Ayman khanfour
@ayman_khanfour · 34,652
Telegram ranks this channel #17 of 88 here — alongside 87 others — read 3 September 2026

This channel appears in 1 seed channel's Telegram-generated recommendation list 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 3 September 2026 — this entry's latest reading, not the date you are reading this.

“Alehssan First year Library” (@GeneralLiprary27), 7,108 subscribers as measured 3 September 2026. Telegram Register, tgregister.com/channel/GeneralLiprary27.

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.