Publications by authors named "R Q Lombardi"

Head and neck cancers (HNCs) are the sixth most commonly diagnosed cancer and the eighth leading cause of cancer-related mortality worldwide, with squamous cell carcinoma being the most prevalent type. The global incidence of HNCs is steadily increasing, projected to rise by approximately 30% per year by 2030, a trend observed in both developed and undeveloped countries. This study involved serum proteomic profiling to identify predictive clinical biomarkers in cancer patients undergoing chemoradiotherapy (CRT).

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Background: Hereditary transthyretin (ATTRv) amyloidosis is rare, autosomal dominant disease with a fatal outcome if left untreated. Early stages detection is crucial for intervention. We aimed identifying early indexes of cardiac involvement and their eventual correlation with neurological indexes, in pre-symptomatic subjects with TTR gene mutation.

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Background: Despite advancements in therapeutic approaches, including taxane-based chemotherapy and androgen receptor-targeting agents, metastatic castration-resistant prostate cancer (mCRPC) remains an incurable tumor, highlighting the need for novel strategies that can target the complexities of this disease and bypass the development of drug resistance mechanisms. We previously demonstrated the synergistic antitumor interaction of valproic acid (VPA), an antiepileptic agent with histone deacetylase inhibitory activity, with the lipid-lowering drug simvastatin (SIM). This combination sensitizes mCRPC cells to docetaxel treatment both in vitro and in vivo by targeting the cancer stem cell compartment via mevalonate pathway/YAP axis modulation.

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Article Synopsis
  • The study investigates the use of Artificial Intelligence (AI) to assess liver fibrosis in patients with Metabolic-Associated Steatotic Hepatitis (MASH) more accurately than traditional methods.
  • Out of 60 patients, biopsies were analyzed using AI technology to measure features like collagen area and entropy, revealing significant differences across fibrosis stages and treatment responses.
  • Results showed that AI could identify changes in fibrosis in 76% of cases post-treatment, suggesting it offers a more reliable way to evaluate disease progression and treatment efficacy.
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