ABSTRACT
COVID-19 caused by SARS-CoV-2 has spread around the world at an unprecedented rate. A more homogeneous oligo-porphyran with mean molecular weight of 2.1 kD, named OP145, was separated from Pyropia yezoensis. NMR analysis showed OP145 was mainly composed of →3)-β-d-Gal-(1 → 4)-α-l-Gal (6S) repeating units with few replacement of 3,6-anhydride, and the molar ratio was 1:0.85:0.11. MALDI-TOF MS revealed OP145 contained mainly tetrasulfate-oligogalactan with Dp range from 4 to 10 and with no more than two 3,6-anhydro-α-l-Gal replacement. The inhibitory activity of OP145 against SARS-CoV-2 was investigated in vitro and in silico. OP145 could bind to Spike glycoprotein (S-protein) through SPR result, and pseudovirus tests confirmed that OP145 could inhibited the infection with an EC50 of 37.52 μg/mL. Molecular docking simulated the interaction between the main component of OP145 and S-protein. All the results indicated that OP145 had the potency to treat and prevent COVID-19. Graphical Unlabelled Image
ABSTRACT
Background Asthma patients potentially have impaired adaptive immunity to virus infection. The levels of SARS-CoV-2-specific adaptive immunity between COVID-19 survivors with and without asthma are presently unclear. Methods COVID-19 survivors (patients with asthma n=11, with allergies n=8, and COVID-19 only n=17) and non-COVID-19 individuals (asthmatic patients n=10 and healthy controls n=9) were included. The COVID-19 patients were followed up at about 8 months and 16 months after discharge. The clinical characteristics, lymphocyte subsets, memory T cells, and humoral immunity including SARS-CoV-2 specific antibodies, SARS-CoV-2 pseudotyped virus neutralization assay, and memory B cells were analyzed in these subjects. Results The strength of virus-specific T cell response in COVID-19 survivors was positively correlated with the percentage of blood eosinophils and Treg cells (r=0.4007, p=0.0188;and r=0.4435, p=0.0086 respectively) at 8-month follow-up. There were no statistical differences in the levels of SARS-CoV-2-specific T cell response between the COVID-19 survivors with, and without, asthma. Compared to those without asthma, the COVID-19 with asthma survivors had higher levels of SARS-CoV-2-specific neutralizing antibodies (NAbs) at the 8-month follow-up (p<0.05). Moreover, the level of NAbs in COVID-19 survivors was positively correlated with the percentage of Treg and cTfh2 cells (r=0.5037, p=0.002;and r=0.4846, p=0.0141), and negatively correlated with the percentage of Th1 and Th17 cells (r=-0.5701, p=0.0003;and r=-0.3656, p=0.0308), the ratio of Th1/Th2, Th17/Treg, and cTfh1/cTfh2 cell (r=-0.5356, r=-0.5947, r=-0.4485;all p<0.05). The decay rate of NAbs in the COVID-19 survivors with asthma was not significantly different from that of those without asthma at 16-month follow-up. Conclusion The level of SARS-CoV-2-specific NAbs in COVID-19 survivors with asthma was higher than that of those without asthma at 8-month follow-up. The SARS-CoV-2-specific T cell immunity was associated with blood eosinophils and Treg percentages. The SARS-CoV-2-specific humoral immunity was closely associated with cTfh2/cTfh1 imbalance and Treg/Th17 ratio. According to the findings, asthmatic patients in COVID-19 convalescent period may benefit from an enhanced specific humoral immunity, which associates with skewed Th2/Th1 and Treg/Th17 immune.
ABSTRACT
A global sentiment in early 2022 is that the COVID-19 virus could become endemic just like common cold flu viruses soon. The most optimistic view is that, with minimal precautions, such as vaccination, boosters and optional masking, life for most people will proceed as normal soon. However, as warned by A. Katzourakis of Oxford University recently [1], we must set aside lazy optimism, and must be realistic about the likely levels of death, disability and sickness that will be brought on by a COVID-19 endemic. Moreover, the world must also consider that continual circulation of the virus could give rise to new variants such as the new BA.2 variant (a subvariant of Omicron) continues to spread across the US and parts of Europe. Data from the CDC is already showing that BA.2 has been tripling in prevalence every two weeks [2]. Hence, globally, we must use available and proven weapons to continue to fight the COVID-19 viruses, i.e., effective vaccines, antiviral medications, diagnostic tests and stop an airborne virus transmission through social distancing, and mask wearing. For this work, we have demonstrated a smart mask with an optimally-coupled ultra-thin flexible soundwave sensors for tracking, classifying, and recognizing different respiratory activities, including breathing, speaking, and two-/tri-phase coughing; the masks functionality can also be augmented in the future to monitor other human physiological signals. Although researchers have integrated sensors into masks to detect respiratory activities in the past, they only based on measuring temperature and air flow during coughing, i.e., counting only the number of coughs. However, coughing is a process consisting of several phases, including an explosion of the air with glottal opening producing some noise-like waveform, a decrease of airflow to decrease sound amplitude, and a voiced stage which is the interruption of the air flow due to the closure of glottal and periodical vibration of partly glottis, which is not always present. Therefore, sensors used for cough detection should not be only sensitive to subtle air pressure but also the high-frequency vibrations, i.e., a pressure sensor that needs to be responsive to a wide input amplitude and bandwidth range, in order to detect air flows between hundreds of hertz from breath, and acoustic signals from voice that could reach [~] 8000 Hz. Respiratory activities data from thirty-one (31) human subjects were collected. Machine learning methods such as Support Vector Machines and Convolutional Neural Networks were used to classify the collected sensor data from the smart mask, which show an overall macro-recall of about 93.88% for the three respiratory sounds among all 31 subjects. For individual subjects, the 31 human subjects have the average macro-recall of 95.23% (ranging from 90% to 100%) for these 3 respiratory activities. Our work bridges the technological gap between ultra-lightweight but high-frequency response sensor material fabrication, signal transduction and conditioning, and applying machining learning algorithms to demonstrate a reliable wearable device for potential applications in continual healthy monitoring of subjects with cough symptoms during the eventual COVID-19 endemic. The monitoring and analysis of cough sound should be highly beneficial for human health management. These health monitoring data could then be shared with doctors via cloud storage and transmission technique to help disease diagnosis more effectively. Also, communication barriers caused by wearing masks can be alleviated by combining with the speech recognition techniques. In general, this research helps to advance the wearable device technology for tracking respiratory activities, similar to an Apple Watch or a Fitbit smartwatch in tracking physical and physiological activities.