A randomized clinical trial to evaluate the efficacy of L-carnitine L-tartrate to modulate the effects of SARS-CoV-2 infection.

Introduction: L-carnitine (LC) has been associated with inflammatory mediator reduction and with downregulating the angiotensin-converting enzyme-2 (ACE2) receptor, which is the target of SARS-CoV-2 attachment. Methods: This pilot phase 2 randomized, double-blind placebo-controlled trial contained two cohorts. Cohort 1 comprised 101 individuals with negative RT-PCR SARS-CoV-2 test results who cohabitated with an individual diagnosed with SARS-CoV-2 infection. Cohort 2 comprised 122 individuals with positive SARS-CoV-2 RT-PCR test results who were asymptomatic or had mild COVID-19 pneumonia symptoms. Participants in each cohort were randomized 1:1 to receive either 2 g elemental oral LC supplementation or placebo daily for 21 days. Primary endpoints included adverse events, SARS-CoV-2 infection incidence in Cohort 1, and disease progressions in Cohort 2. Secondary endpoints included between-group laboratory profile comparisons and Cohort 2 ACE1/ACE2 plasma levels. Disease progression was compared between the Cohort 2 groups using chest computed tomography. Results: In Cohort 1, two SARS-CoV-2 infections occurred in each group. The common adverse events included headache, dyspnea, and tiredness. In Cohort 2, platelet counts were elevated, and fibrinogen levels reduced in the LC group compared with those of the placebo group. Conclusion: Our study showed that LC was well-tolerated and suggests it modulates coagulation pathways. Furthermore, chest computed tomography images of the Cohort 2 LC group showed significant lung lesion improvement, suggesting that LC may slow COVID-19 progression.

Application of Liposomes in Cancer Therapy: An Assessment of the Advancement of Technology Through Patent Documents.

BACKGROUND: Cancer is caused by mutations in oncogenes and loss of tumor suppressor activity. Despite the efforts of the pharmaceutical industry to fight cancer, it is necessary to investigate new methods to enhance the action against this disease. In this scenario, liposome technology has emerged as a drug delivery system for cancer treatment. The objective of this study was to evaluate the use of liposome technology in the treatment of cancer through analysis of patent documents. METHODS: We analyzed prospective documents in the Derwent Innovation Index database. RESULTS: A total of 203 patent documents were related to the area of interest, published between 2000 and 2020, and the USA and Japan were shown as countries with the largest number of publications. Moreover, most of these publications came from companies, however, also with the representation of important universities, mainly the University of California. According to the International Patent Classification, the codes most applicable to the documents were in the areas of human necessities and chemistry. CONCLUSION: The results of this study showed that the study and application of liposomes for the development of cancer treatment tended to grow, along with the number of related patents.

Tumour doubling times and the length bias in breast cancer screening programmes.

Screening for early detection of breast cancer is considered to be an important element of preventive medicine. In this paper, we use numerical simulations to examine the length bias in regular interval screening programmes, by computing the doubling times of breast cancer tumours detected through regular mammographies compared to self-detection. Our analysis shows that doubling times of tumours detected by a regular screening programme are longer than doubling times in the original whole population and considerably longer than those self-detected. Hence regular interval mammographies may be missing a high proportion of fast growing tumours and therefore the benefits of current screening programmes may need to be re-evaluated. We examine the likely size of the length bias for the present UK breast cancer screening programme and perform a sensitivity analysis by varying the screen detection probabilities to reflect future advances in mammographic detection.