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Nandrolone Decanoate Wikipedia

Contents
Nandrolone decanoate
Medical uses
Dosages
Available forms
Non-medical uses
Contraindications
Side effects
Virilization
Overdose
Interactions
Pharmacology
Pharmacodynamics
Pharmacokinetics
Chemistry
History
Society and culture
Generic names
Brand names
Availability
Legal status
Research
References
Further reading
External links



Nandrolone decanoate
Nandrolone decanoate, also known as 19-nortestosterone 17β-dodecylcarbonate or nandrolone dodecanoate, is a synthetic anabolic–androgenic steroid (AAS) and the C-17β ester of nandrolone. It is an intermediate in the synthesis of several other compounds including 5α-DHT, nandrolone phenylpropionate and estradiol, among others.



Pharmacology
The pharmacodynamics of nandrolone decanoate have been studied extensively. Its effects include a range of physiological changes related to its anabolic activity. In particular, it has a dose-dependent increase in muscle mass, strength and endurance, as well as increased bone density and decreased body fat. It also increases the levels of growth hormone, insulin-like growth factor-1 (IGF-1), and testosterone.



The pharmacokinetics of nandrolone decanoate is influenced by its chemical structure, which includes a 3-hydroxy group at position 3, an olefinic ring with 6–9: 4-2 and 5 (0) 8; the T‐t. The … …...
We can ..…



question …



We need to read until we encounter a blank line, which indicates the end of the question text. We then continue reading for the answer lines.



Now, after reading all sections, we parse the sections that contain the data we want.




4.2 Extracting the Question ID


The `Question ID` is found in the first line of the Question section:




Question: 1234567


We read this integer and store it as a property of our question object.




4.3 Parsing the Author and Date


In the Author section we have a single line with the user’s name, an optional `` `` pair containing the reputation score, and possibly a `#` followed by the account ID:




Author: John Doe 12345 #67890


We parse this line into three fields:




Field Example Notes

| Name | John Doe | Text before first ` Field Integer after `#`; optional.
`. Trim spaces.
User Auth Service (JWT) `questions` Table `id` (Auth endpoints)
v v
+-------------------+ +---------------------+ +------------------------+
------ NOT NULL, FOREIGN KEY (references questions.id) Integer inside ``; may be omitted. 67890 (REST: /answers, /users) ---------------------- Create/Update Answers -------- Frontend UI




v v
+---------------------------------+ +-----------------------------+
Track authorship
Error Handling Use `.skip((page-1)limit).limit(limit)`. Add total count for UI.

`author_id`
+-------------------+ +--------------------+


------------
Prevent empty or trivial answers Referential integrity AccountID NOT NULL, PRIMARY KEY `id (PK)`, `question_id (FK)`, `content`, `source_url`, `author`, `tags`, `created_at`, `updated_at` `Answer.findByIdAndRemove(id)`; optionally cascade delete related comments.





Primary Keys: `id` columns uniquely identify rows.


Foreign Key: `question_id` links each answer to its parent question.


Indexes:


- Index on `question_id` for efficient joins.
- Full-text index (e.g., PostgreSQL's GIN) on `content` if search is required.



---




4. Data Integrity and Validation



4.1 Constraints and Checks


Security Use Mongoose `findByIdAndUpdate` with `$set`. Validate before saving. Columns

API Gateway (Nginx) Read Single Answer 12345*
+---------------------------------+ +-----------------------------+
Delete Answer
NOT NULL, default CURRENT_TIMESTAMP
`Answer.findById(id).populate('author')` to include author details. NOT NULL, CHECK length ≥ 10 Verify `req.user._id` equals `author` before update/delete. MongoDB

Auth DB (MongoDB) Constraint Search by Text
Uniqueness
`id (PK)`, `title`, `url`, `created_at`, `updated_at` `created_at`, `updated_at`




4.2 Data Validation




Server-Side: Use frameworks (e.g., Express.js with Joi validation) to enforce schema constraints before database insertion.


Client-Side: Provide instant feedback on answer length and required fields via JavaScript form validation.







3. Architectural Overview of the Microservice



+-------------------+ +--------------------+
Pagination `content` Recommended Approach

+-------------------+ +---------------------+ +------------------------+




Answer Service: Handles CRUD operations for answers.


User Auth Service: Manages user registration, login, and JWT issuance.


MongoDB: Stores answer data and user credentials.


Redis Cache (optional): Caches frequently accessed answers to improve read performance.







6. Implementation Tips



`answers` -------
Return proper HTTP status codes: 400 (bad request), 404 (not found), 401/403 (unauthorized). Task Audit trail MongoDB text index on fields, then `$text` query. NOT NULL, FOREIGN KEY (references users.id)
Answer Service (Node.js/Express)------------



If a field is missing, we leave it blank.




1.3.4 Parsing the Answer Body


The answer body begins on the line after `Answer:`, and continues until the end of the document or until another section starts (e.g., "Tags:"). We capture all lines as plain text. No further parsing is required; the body can contain Markdown, HTML, or any other markup.




1.3.5 Handling Multiple Answers


If multiple answers are present in a single document, they are separated by the `---` marker (three dashes). After encountering this marker, we resume parsing at the next question header. The process repeats until all content is consumed.



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2. Data Storage and Indexing Strategy


After extraction, each answer must be stored efficiently to support quick retrieval for user-facing operations such as auto-completion, fuzzy matching, or spell-check suggestions. Two complementary storage systems are employed:





PostgreSQL – a relational database used to store the core data: questions, answers, metadata (e.g., source URL, timestamps).


Elasticsearch – a distributed search engine used for full-text indexing and retrieval of answer content.




2.1 PostgreSQL Schema


A typical schema might include:



Reputation
------------------------------------------------------- Reason Redis Cache (Optional)

`question_id`