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| http://dx.doi.org/10.3389/fgene.2024.1494075 | DOI Listing |
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Comparative transcriptomics of a generalist aphid, and a specialist aphid, reveals molecular signatures associated with diversity of their feeding behaviour and other attributes.
Front Plant Sci
December 2024
Department of Botany, University of Delhi, Delhi, India.
Introduction: Aphids are phloem sap-sucking insects and are a serious destructive pest of several crop plants. Aphids are categorized as "generalists" or "specialists" depending on their host range. (Sulz.
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World J Clin Oncol
November 2024
Department of Surgery, University of Medicine and Pharmacy Grigore T. Popa Iaşi, Regional Institute of Oncology Iasi, Iasi 700483, Romania.
Gastric cancer continues to be a significant issue for public health, marked by its widespread occurrence and high mortality rates, even as the incidence of the disease shows a declining trend. The liver is the primary site for metastatic spread, with the peritoneum, lungs, and bones also being common targets. With the advent of biologic treatments and the introduction of immunotherapy for patients with metastatic conditions, the options to treat metastatic gastric cancer have expanded.
View Article and Find Full Text PDFModulation of gut microbiome in response to the combination of Nissle 1917 and sugars: a pilot study using host-free system reflecting impact on interpersonal microbiome.
Front Nutr
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Molecular Biology and Microbial Physiology Division, CSIR-Institute of Microbial Technology, Chandigarh, India.
Introduction: The differential effects of probiotic, prebiotic, and synbiotic formulations on human health are dictated by the inter-individual gut microbial profile. The effects of probiotics such as Nissle 1917 (ECN) on gut microbiota may vary according to the microbiome profiles of individuals and may be influenced by the presence of certain carbohydrates, which can impact microbial community structure and treatment results.
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Understanding the role of machine learning in predicting progression of osteoarthritis.
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Department of Surgery, University of Cambridge, Cambridge, UK.
Aims: Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression.
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Center of Critical Care Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
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