Pakistan Health News API

{
    "totalArticles": 61746,
    "articles": [
        {
            "id": "ec9dd23b398b7fe38c922c279fc5392a",
            "title": "Always online, rarely focused: Is ‘brain rot’ becoming a Saudi problem?",
            "description": "ALKHOBAR: Saudi Arabia’s young, hyper-connected population is spending more time online than ever before. Short videos, constant notifications and algorithm-driven feeds have become part of daily life. Research from the American Psychological Association and the OECD has linked frequent digital interruptions to declining sustained attention, cognitive fatigue and learning",
            "content": "ALKHOBAR: Saudi Arabia’s young, hyper-connected population is spending more time online than ever before. Short videos, constant notifications and algorithm-driven feeds have become part of daily life.\nResearch from the American Psychological Associa... [5445 chars]",
            "url": "https://www.arabnews.pk/node/2638303/saudi-arabia",
            "image": "https://www.arabnews.pk/sites/default/files/styles/660x371_watermarkpakistan/public/main-image/2026/03/31/4698588-1602945103.jpg?itok=jo4SFQcz",
            "publishedAt": "2026-03-31T12:58:28Z",
            "lang": "en",
            "source": {
                "id": "6aa9750dfe0dabd5f047338da68fcf6c",
                "name": "Arab News PK",
                "url": "https://www.arabnews.pk"
            }
        },
        {
            "id": "281a6145fedf87b028d450a32e424730",
            "title": "AI tool could help clinicians detect liver cancer risk earlier",
            "description": "Hepatocellular carcinoma (HCC) is the most common type of liver cancer. It is most common in those with existing liver disease, but can be difficult to detect in people without diagnosed liver disease. Now, a study suggests that an AI can accurately predict liver cancer risk using routine tests.",
            "content": "A machine learning model accurately predicted the risk of hepatocellular carcinoma (HCC) using routine clinical data.\nThe model outperformed existing liver cancer risk tools by identifying more true cases while reducing false positives.\nThe study sug... [6566 chars]",
            "url": "https://www.medicalnewstoday.com/articles/ai-model-accurately-predict-liver-cancer-risk",
            "image": "https://media.post.rvohealth.io/wp-content/uploads/sites/3/2026/03/machine-prediction-GettyImages-2097577413-Facebook.jpg",
            "publishedAt": "2026-03-31T10:49:50Z",
            "lang": "en",
            "source": {
                "id": "c15768d2e47dee90317dd66886f4b1ba",
                "name": "Medical News Today",
                "url": "https://www.medicalnewstoday.com"
            }
        },
        {
            "id": "e4c10320897494d1277a201ec8776471",
            "title": "Single-cell spatial atlas of the aging human breast",
            "description": "Breast cancer can develop over a wide age range and tumors in younger women differ from those in older women. Aging alters the spatial context of early tumors and may explain these differences, but breast tissue aging remains poorly characterized. Here, using imaging mass cytometry to profile the spatial expression of 40 proteins, we explore age-related remodeling of normal breast tissues in over 3 million cells from 527 reduction mammoplasties. Aged breast tissue was less cellular and less proliferative for all cell types (epithelial, stromal and immune). Tissue architecture was restructured with fewer heterotypic epithelial cell–cell interactions, far fewer lobules and increased fat. Older tissues had a more inflammatory microenvironment with increased M2 macrophages and granzyme B+ T cells, contrasted by younger tissues in which B cells were most enriched. Our multiscale atlas extensively details an unexpected general decline of breast tissue with age and reveals its changing spatial context. The dynamics of breast tissue aging are characterized by imaging mass cytometry of over 500 reduction mammoplasties, revealing nonlinear loss of cellularity and a compositional shift favoring inflammation.",
            "content": "Spatial mapping of the aging human breast\nTo chart the cellular spatial dynamics of aging breast tissue, we used IMC to profile in situ expression of 40 proteins in a sample collection from a previously reported cohort5 of 527 women undergoing reduct... [58385 chars]",
            "url": "https://www.nature.com/articles/s43587-026-01104-3?error=cookies_not_supported&code=72982060-6b6c-4dcd-ace4-d2e8150020da",
            "image": "https://media.springernature.com/m685/springer-static/image/art%3A10.1038%2Fs43587-026-01104-3/MediaObjects/43587_2026_1104_Fig1_HTML.png",
            "publishedAt": "2026-03-31T09:08:58Z",
            "lang": "en",
            "source": {
                "id": "7abf0df285fbe93cdccffcc7c4088737",
                "name": "nature.com",
                "url": "https://www.nature.com"
            }
        }
    ]
}