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Lucrezia Stefanini wygrała w radomskim turnieju

Włoszka Lucrezia Stefanini wygrała turnieju pań PZT Polish Tour W25 Radom. W finale Lucrezia Stefanini pokonała w trzech setach Czeszkę Miriam Kolodziejovą 4:6, 6:2, 6:3.

Turniej został rozegrany na kortach MOSiR na Borkach. W rywalizacji wzięło udział ponad siedemdziesiąt zawodniczek z ponad dwudziestu krajów.

 
 
Przypomnijmy, że w turnieju deblistek zwyciężyły Japonki Mana Kawamura i Funa Kozaki.

 

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    # Steroids in Clinical Practice
    **Mechanisms, Therapeutic Applications, Safety Considerations, and Practical Guidance**

    ## 1. Introduction

    Steroid hormones (glucocorticoids, mineralocorticoids, progestins, estrogens) are indispensable tools in modern medicine.
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    | **Clinical Scenario** | **Hormone Involved** | **Key Points to Remember** |
    |————————|———————-|—————————|
    | Primary adrenal insufficiency (Addison’s)
    | Aldosterone, cortisol | **Low aldosterone → hyperkalemia, hyponatremia; low cortisol → hypoglycemia,
    fatigue**. Treat with glucocorticoids + mineralocorticoid.
    |
    | Congenital adrenal hyperplasia (21‑hydroxylase deficiency) | 17α‑OHP | Elevated 17α‑OHP → androgen excess →
    ambiguous genitalia in females, precocious puberty in males.
    Treatment: glucocorticoids to suppress ACTH;
    fludrocortisone if needed. |
    | Hyperaldosteronism (Conn’s syndrome) | Aldosterone ↑ | **Hypertension,
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    |
    | Cushing’s disease | Cortisol ↑ | **Central obesity,
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    |

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    | Category | Main Take‑aways |
    |———-|—————–|
    | **Metabolism** | Cortisol → gluconeogenesis, lipolysis, proteolysis;
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    | **Regulation** | HPA axis (CRH → ACTH) and RAAS for aldosterone.
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    renin. |
    | **Clinical Relevance** | Addison’s disease, Cushing syndrome, hyper‑/hypoaldosteronism, hypertension, electrolyte disturbances.
    |
    | **Key Pathways** | HPA axis (CRH → ACTH → cortisol);
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    ## 3. How the Model Works – Step‑by‑Step

    | Phase | What the model does | Output produced |
    |——-|——————–|—————–|
    | **1️⃣ Initialization** | • Loads a high‑resolution graph of adrenal steroidogenesis (nodes = enzymes,
    substrates; edges = reactions).
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    | Ready to simulate hormone production. |
    | **2️⃣ Parameter Setting** | • Accepts user‑defined inputs:
    • *Plasma ACTH* (ng/mL),
    • *Cortisol baseline* (µg/dL).
    • Optional modulation of key enzymes (e.g., up‑regulate CYP11B1 by 20%).
    | Creates a custom simulation scenario. |
    | **3️⃣ Forward Simulation** | • Uses differential equations to propagate ACTH → adrenal steroidogenesis:
     `dCortisol/dt = f(ACTH, enzyme activities)`
    • Solves the system over a defined time horizon (e.g., 24 h).
    | Computes predicted cortisol trajectory. |
    | **4️⃣ Output Generation** | • Provides:
     – Cortisol vs. time plot.
     – Summary statistics (peak value, AUC, time‑to‑peak).

     – Sensitivity analysis results for each enzyme parameter.
    | Delivers actionable insights to clinicians. |

    ## 4. **Potential Clinical Use Cases**

    | Scenario | What the Tool Helps With |
    |———-|————————|
    | **Cushing’s Disease Management** | Predict how changes in ACTH production (e.g.,
    after pituitary surgery or radiation) will affect
    cortisol levels, guiding postoperative monitoring. |
    | **Adrenal Insufficiency Titration** | Simulate dose adjustments of glucocorticoid replacement therapy and assess the impact on downstream enzyme activity
    and cortisol output. |
    | **Pharmacological Intervention Planning** | Evaluate potential effects of
    drugs that modulate CYP11B1 or CYP17A1 (e.g., steroidogenesis inhibitors)
    before initiating therapy. |
    | **Educational Tool for Clinicians** | Visualize the endocrine
    feedback loop, reinforcing understanding of how upstream hormone changes propagate through the
    system. |

    ## 5. Implementation Roadmap

    ### 5.1 System Architecture Overview

    „`
    +——————+
    | User Interface |
    | (Web/Mobile App) |
    +——–+———+
    |
    v
    +——————+
    | API Gateway | (Microservices)
    +——–+———+
    |
    v
    +——————+
    | Data Layer |
    | (PostgreSQL) |
    +——–+———+
    „`

    – **User Interface**: Responsive web app + optional mobile app.
    Uses standard authentication flows.
    – **API Gateway**: Exposes endpoints for CRUD operations on `person` and `address`.
    Handles rate limiting, caching.
    – **Business Logic Layer**: Enforces business rules (e.g.,
    unique email per person). Could be split into microservices if needed.

    – **Data Layer**: PostgreSQL relational database. Indexes on `email`, `uuid`.

    #### 4.2 Data Modeling

    „`sql
    CREATE TABLE person (
    id BIGSERIAL PRIMARY KEY,
    uuid UUID NOT NULL UNIQUE DEFAULT gen_random_uuid(),

    first_name TEXT NOT NULL,
    last_name TEXT NOT NULL,
    email TEXT NOT NULL UNIQUE,
    created_at TIMESTAMP WITH TIME ZONE DEFAULT now()
    );

    CREATE TABLE address (
    id BIGSERIAL PRIMARY KEY,
    person_id BIGINT REFERENCES person(id) ON DELETE CASCADE,
    uuid UUID NOT NULL UNIQUE DEFAULT gen_random_uuid(),
    street TEXT NOT NULL,
    city TEXT NOT NULL,
    state TEXT NOT NULL,
    zip_code TEXT NOT NULL,
    country TEXT NOT NULL,
    created_at TIMESTAMP WITH TIME ZONE DEFAULT now()
    );
    „`

    ### Step 2: Configure the Database Connection

    Create a `.env` file to store your database credentials securely:

    „`plaintext
    DATABASE_URL=postgres://username:password@localhost:5432/your_database_name
    „`

    Then, set up a database client in your application. For example, using `pg`
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    „`javascript
    const Pool = require(’pg’);
    require(’dotenv’).config();

    const pool = new Pool(
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    module.exports =
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    „`

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    async function getAllUsers()
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    users’);
    return result.rows;

    module.exports = getAllUsers;

    // updateUser.js
    const db = require(’./db’);

    async function updateUser(id, name, email)
    const result = await db.query(
    'UPDATE users SET name = $1, email = $2 WHERE id = $3 RETURNING *’,
    name, email, id
    );
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    // deleteUser.js
    const db = require(’./db’);

    async function deleteUser(id)
    const result = await db.query(’DELETE FROM users WHERE
    id = $1 RETURNING *’, id);
    return result.rows0;

    module.exports = deleteUser;
    „`

    ### Explanation

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    – `readUsers.js`: Retrieves all users from the database.

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    „`

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    If you have more details or need specific code snippets, let me
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    If there’s anything else you’d like to explore or if you need additional clarification on any part of these concepts, feel free to ask!

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