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Background After the first cases of coronaviruses disease 2019 (COVID-19) in China in January 2020, the epidemic spread around the world. Few data are available from Central Africa. We conducted a study to monitor this emerging disease in Gabon, a Central Africa country. Methods In order to set up an epidemiological surveillance of COVID-19 in Gabon, we led molecular investigations on nasopharyngeal and oropharyngeal samples from the 1161 first suspected cases of COVID-19. A Reverse Ttranscriptase Polymerase Chain Reaction (RT-PCR) was performed using primers and probes targeted the E gene and polymerase gene according to the kit Tib-Molbiol. Results We diagnosed the first case of COVID-19 on March, 12 2020. Among those suspected cases, 83 were confirmed cases. There was no significant difference in prevalence of SARS-CoV-2 between age groups (p = 0.14). Seventy-three percent were asymptomatic. The viral loads were significantly higher in the nasopharyngeal samples than in the oropharyngeal samples (p=0.03). There was no significant difference in viral loads between age groups (p=0.9895) and no correlation between clinical symptoms and viral loads (p=0.06042). Conclusion In conclusion, this study provides the first molecular data from Gabon concerning the COVID-19 pandemic. The data showed that most of the infected people were asymptomatic. The viral load was higher in the nasopharyngeal samples.

Background After the first cases of coronaviruses disease 2019 (COVID-19) in China in January 2020, we conducted an epidemiological surveillance of COVID-19 in Gabon. Methods We led molecular investigations on nasopharyngeal and oropharyngeal samples from the 1161 first suspected cases of COVID-19. We diagnosed the first case of COVID-19 on March, 12 2020. Results Among those suspected cases, 83 were confirmed cases. There was no significant difference in prevalence of SARS-CoV-2 between age groups (p=0.14). 73% were asymptomatic. The viral loads were significantly higher in the nasopharyngeal samples than in the oropharyngeal samples (p=0.03). There was no significant difference in viral loads between age groups (p=0.9895) and no correlation between clinical symptoms and viral loads (p=0.06042). A phylogenetic analysis performed with five sequences of the spike S gene showed that two sequences had the D614G mutation. Conclusion In conclusion, this study provides the first molecular data from Gabon concerning the COVID-19 pandemic. The data showed that most of the infected people were asymptomatic. The viral load was higher in the nasopharyngeal samples. The S gene analyzed suggested both introduction of the D614 and G614 variant in Gabon.

Background: Fc-mannose-binding lectin (FcMBL), an engineered version of the blood opsonin MBL that contains the carbohydrate recognition domain (CRD) and flexible neck regions of MBL fused to the Fc portion of human IgG1, has been shown to bind various microbes and pathogen-associated molecular patterns (PAMPs). FcMBL has also been used to create an enzyme-linked lectin sorbent assay (ELLecSA) for use as a rapid ( Methods: Here we extended this work by using the ELLecSA to test FcMBL’s ability to bind to more than 190 different isolates from over 95 different pathogen species. Results: FcMBL bound to 85% of the isolates and 97 of the 112 (87%) different pathogen species tested, including bacteria, fungi, viral antigens and parasites. FcMBL also bound to PAMPs including, lipopolysaccharide endotoxin (LPS) and lipoteichoic acid (LTA) from Gram-negative and Gram-positive bacteria, as well as lipoarabinomannan (LAM) and phosphatidylinositol mannoside 6 (PIM 6) from Mycobacterium tuberculosis. Conclusions: The efficiency of pathogen detection and variation between binding of different strains of the same species could be improved by treating the bacteria with antibiotics, or mechanical disruption using a bead mill, prior to FcMBL capture to reveal previously concealed binding sites within the bacterial cell wall. As FcMBL can bind to pathogens and PAMPs in urine as well as blood, its broad-binding capability could be leveraged to develop a variety of clinically relevant technologies, including infectious disease diagnostics, therapeutics, and vaccines.

Extracellular vesicles (EV’s) are membrane surrounded structures released by different cell types and are emerging as potential therapeutic and diagnostic targets in cancer. In the present study, plasma samples derived from 7 patients with metastatic and non-metastatic ER+ (estrogen receptor positive) breast cancer (BC) were collected and their respective (EVs) isolated and the protein content analyzed by mass spectrometry and FunRich analysis. Two putative plasma biomarkers (absent in healthy controls samples) were identified which could be used to detect early ER+ breast cancer and for those with lymph node (LN) involvement However, given the current limitations of the EV isolation method used, it is possible that these biomarkers did not originate from EVs and may represent blood-derived extracellular proteins. Further work in a larger patient cohort is warranted to confirm these findings and examine the diagnostic potential of these biomarkers.

Extracellular vesicles (EV’s) are membrane surrounded structures released by different cell types and are emerging as potential therapeutic and diagnostic targets in cancer. In the present study, plasma samples derived from 7 patients with metastatic and non-metastatic ER+ (estrogen receptor positive) breast cancer (BC) were collected and their respective (EVs) isolated and the protein content analyzed by mass spectrometry and FunRich analysis. Here we report on the presence of two putative plasma EV biomarkers (which were absent in healthy controls samples) that could be used to detect early ER+ breast cancer and for those with lymph node (LN) involvement However, given the preliminar nature of the work, further investigation in a larger patient cohort is warranted to corroborate these findings. If confirmed, these biomarkers could be incorporated into simple blood test kit for the early detection of those with ER+ breast cancer and lymph node involvement.

Extracellular vesicles (EV’s) are membrane surrounded structures released by different cell types and are emerging as potential therapeutic and diagnostic targets in cancer. In the present study, plasma samples derived from 7 patients with metastatic and non-metastatic ER+ (estrogen receptor positive) breast cancer (BC) were collected and their respective (EVs) isolated and the protein content analyzed by mass spectrometry and FunRich analysis. Here we report on the presence of two putative plasma EV biomarkers (which were absent in healthy controls samples) that could be used to detect early ER+ breast cancer and for those with lymph node (LN) involvement However, given the preliminar nature of the work, further investigation in a larger patient cohort is warranted to corroborate these findings. If confirmed, these biomarkers could be incorporated into simple blood test kit for the early detection of those with ER+ breast cancer and lymph node involvement.

Background: Gait is a powerful tool to identify ageing and track disease progression. Yet, its high resolution measurement via traditional instruments remains restricted to the laboratory or bespoke clinical facilities. The potential for that to change is due to the advances in wearables where the synergy between devices and smart algorithms has provided the potential of ‘a gait lab on a chip’. Methods: Commercially available wearables for gait quantification remain expensive and are restricted to a limited number of characteristics unsuitable for a comprehensive assessment required within intervention or epidemiological studies. However, the increasing demand for low-cost diagnostics has fuelled the shift in how health-related resources are distributed. As such we adopt open platform technology and validated research methodologies to harmonise engineering solutions to satisfy current epidemiological needs. Results: We provide an introduction to conduct a routine instrumented gait assessment with a discrete, low-cost, accelerometer-based wearable. We show that the capture and interpretation of raw gait signals with a common scripting language can be straightforward and suitable for use within modern studies. We highlight the best approaches and hope that this will help compliment any analytical tool-kit as part of future cohort assessments. Conclusions: Deployment of wearables can allow accurate gait assessment in accordance with advocated methods of data collection as there is a strong demand for sensitive outcomes derived from pragmatic tools. This tutorial shows that instrumentation of gait using a single open source wearable is pragmatic due to low-cost and translational analytical methods to derive sensitive outcomes.