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    Father Muller Medical College

    991论文总数
    9,650引用总数

    Coordinates: 12°51′58″N 74°51′43″E / 12.86611°N 74.86194°E / 12.86611; 74.86194Father Muller Medical College, (ಫಾದರ್ ಮುಲ್ಲರ್ ಮೆಡಿಕಲ್ ಕಾಲೇಜು) located about a kilometre from the National Highway-66 (the Mumbai-Mangalore highway) at Kankanady in Mangalore, is a religious minority educational institution forming a part of the Father Muller Charitable Institutions (FMCI).

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    Manjeshwar Shrinath Baliga
    Manjeshwar Shrinath Baliga
    Department of Radiotherapy, Mangalore Institute of Oncology;Father Muller Research Centre
    论文:73引用:0H-index:0
    Ramesh Marne Bhat
    Ramesh Marne Bhat
    Father Muller Medical College
    论文:70引用:0H-index:0
    Palatty Princy Louis
    Palatty Princy Louis
    Department of Pharmacology, FMMC
    论文:40引用:0H-index:0
    Shivashankara Arnadi Ramachandrayya
    Shivashankara Arnadi Ramachandrayya
    Department of Biochemistry, Father Muller Medical College
    论文:30引用:0H-index:0
    Sudhan Rackimuthu
    Sudhan Rackimuthu
    Father Muller Medical College
    论文:26引用:0H-index:0
    Bhaskar K Somani
    Bhaskar K Somani
    Faculty of Medicine, University of Southampton;University Hospital Southampton NHS Foundation Trust
    论文:23引用:0H-index:0
    Jacintha Martis
    Jacintha Martis
    Father Muller Medical College
    论文:21引用:0H-index:0
    Raghavendra Haniadka
    Raghavendra Haniadka
    Father Muller Medical College
    论文:21引用:0H-index:0
    Bm Zeeshan Hameed
    Bm Zeeshan Hameed
    Father Muller Medical College
    论文:21引用:0H-index:0

    论文(991)

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    1Epidemiology and Treatment Challenges of Acne, with Insights into the Role of Dermocosmetics: an Expert Consensus from India—A Modified Delphi Method
    Mukta Sachdev,Nina Madnani,Malavika Kohli,Koushik Lahiri, Anurag Tiwari, Kalpana Sarangi,Rajat Kandhari,Rajetha Damisetty, Ramesh Bhat,Delphine Kerob, Shefali Trasi‐Nerurkar

    ABSTRACT Background Acne vulgaris is a common skin condition that typically begins in adolescence but can often persist in adulthood, contributing to significant physical and psychosocial burden. Despite the availability of multiple treatment options, challenges such as poor adherence, treatment‐related side effects, and post‐inflammatory hyperpigmentation remain common in clinical practice. Dermocosmetics are increasingly used in acne management, either alone in mild cases or as adjuncts to medical therapy. Objectives To assess acne prevalence, treatment practices, and key management challenges, along with the role of dermocosmetics, based on expert consensus from India. Methods A panel of 10 dermatologists participated in a modified Delphi process comprising a pre‐meeting survey followed by a structured advisory board discussion, capturing clinical practice patterns, treatment approaches, and perspectives on dermocosmetic use in acne management. Results Experts reported treating a high number of acne patients, primarily adolescents, with a higher proportion of females. Hyperpigmentation and scarring were common sequelae of acne, while treatment adherence and antibiotic resistance, particularly to erythromycin and azithromycin, were noted as key challenges. Procedural interventions, including chemical peels, lasers, and comedone extraction, were increasingly used in early acne management, especially in patients prone to post‐inflammatory hyperpigmentation and relapse. Low‐dose isotretinoin and hormonal therapies were commonly used in acne management, while dermocosmetics were utilized as monotherapy in mild cases and as maintenance therapy following treatment in more severe cases. Lifestyle factors such as high glycaemic diets, whey protein, multivitamins, and steroid‐like drugs were identified as potential contributors to acne exacerbation. Limitations Findings are based on a small expert panel convened with industry support and reflect clinical opinion rather than primary patient data. Conclusion Procedural interventions are becoming more popular, thereby providing an opportunity to incorporate dermocosmetics into acne treatment regimens.

    2026Journal of Cosmetic Dermatology(2026)
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    2Dosimetric Parameters Predicting Oral Mucositis in Locally Advanced Laryngeal and Hypopharyngeal Cancer Using Volumetric Modulated Arc Therapy
    R. R. Roshni, B. Sandesh Rao, Zalfa Abdul Azeez, Lanisha Jolitha Sequeira, H. K Krishnaraj, Tony Jacob

    A BSTRACT Background: In locally advanced Laryngeal and hypopharyngeal cancer, definitive chemoradiation therapy has become the preferred treatment owing to its organ preservation advantages. It is recognized for inducing considerable short- and long-term toxicity when administered at extreme dosages. Research indicates that patients undergoing radiation therapy (RT) in conjunction with chemotherapy experienced more severe toxicity, such as mucositis. Associated radiation exposure to the buccal mucosa during treatment with radiation for carcinomas of the larynx and pharynx leads to acute radiation-induced oral mucositis (RIOM). Objectives: To assess the dose received by buccal mucosa and oral mucositis in patients receiving combined chemoradiation for treatment of laryngeal and hypopharyngeal cancers with volumetric modulated arc therapy (VMAT). Materials and Methods: Forty-five patients with histologically proven squamous cell carcinoma of the larynx and hypopharyx cancer, who received chemoradiation therapy by VMAT were analyzed. The total prescribed dose was 70 Gy delivered in 2 Gy daily fractions with concurrent weekly injection cisplatin (35 mg/m 2 )/carboplatin area under the curve 2 (AUC 2). Dosimetric parameters of right and left buccal mucosa (V 15 Gy and V 30 Gy) were recorded and correlated with grades of RIOM as per CTCAE v5.0. Results: Mucositis and weight loss were assessed from week 1 to 7. Grade 2 and 3 mucositis was observed in 66.7% ( n = 30) and 4.4% ( n = 2). None of the patients developed Grade 4 or more. Weight loss of Grade 2 and 3 was observed in 42.2% ( n = 19) and 57.8 ( n = 26). Increase in dose to buccal mucosa showed a significant ( P < 0.001) with oral mucositis. Conclusion: The incidence of various RIOM was evaluated in this study as a predictor of the dosage administered to the buccal mucosa in patients with laryngeal and hypopharyngeal cancer. In HNCs receiving radical chemoradiation therapy, our data showed a correlation between buccal mucosa V15Gy and V30Gy and oral mucosal toxicity.

    2026Journal of Radiation and Cancer Research(2026)
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    3Guidelines for Geriatric Oncology in India: Recommendations for Clinical Practice (version 1)
    Vanita Noronha, Abhijith Rao, Anupa Pillai,Anant Ramaswamy,Vikram Gota,Sharada Mailankody,Deepam Pushpam, Arshiya Sehgal,Joyita Banerjee,Akhil Kapoor,Amit Kumar,Minit Shah,
    2026Journal of geriatric oncology(2026)
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    4Poikilodermatous Mycosis Fungoides – A Rare and Challenging Diagnosis
    Varsha M. Shetty, Raghavendra Rao,Kanthilatha Pai, Kiran, Sushena Mahapatra
    2026Indian Journal of Postgraduate Dermatology(2026)
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    5Leveraging a Hybrid AI Modeling Technique in Detection of Helicobacter Pylori in Gastric Biopsies.
    S Ruban, Akshay Louis Dias, V Varenya, Hilda Shanthini, Sunanda Nandika, Joanne Juliet Sequeira

    BACKGROUND:Helicobacter pylori is a major causative factor in gastric carcinoma, making detection in gastric biopsies a matter of great interest and need. Traditional diagnostic techniques such as endoscopy-guided gastric biopsy, rapid urease test, polymerase chain reaction, or tissue culture often face turnaround time and accuracy challenges. METHODS:This study explores the development of advanced hybrid AI modeling using deep learning algorithms to enhance precision in detecting HP in histological specimens. Retrospectively collected images from endoscopic biopsies, stained with Giemsa and hematoxylin and eosin, were analyzed and marked by a pathologist to classify HP as positive or negative cases. The study used 1395 images from a medical college hospital. A hybrid AI model was created to improve classification accuracy. RESULTS:Performance metrics for the hybrid model revealed exceptional results: an overall accuracy of 99.6%, sensitivity of 99.3%, specificity of 100%, precision of 100%, and F1-score of 99.7%. The receiver operating characteristic curve analysis showed an Area Under the Curve of 1.00, indicating perfect classification ability. CONCLUSION:This paper highlights the opportunities of AI technologies to simplify and enhance the diagnostic workflow in busy laboratories, in turn, to help clinical decision-makers decide to manage HP accurately and effectively.

    2026Indian journal of pathology & microbiology(2026)
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    合作机构(100)

    卡斯图尔巴医学院,马尼帕尔合作论文 31
    Manipal Academy of Higher Education合作论文 30
    Kasturba Medical College合作论文 19
    Manipal Institute of Technology合作论文 17
    Maharani Lakshmi Ammani Women's College合作论文 14
    Father Muller Medical College Hospital,Father Muller Charitable Institutions合作论文 11
    Defence Research and Development Organisation,Ministry of Defence合作论文 10
    All India Institute of Medical Sciences合作论文 10
    夸祖鲁 - 纳塔尔大学合作论文 9
    Astana Medical University合作论文 9

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