Longevity of memory B cells and antibodies, as well as the polarization of effector memory helper T cells, are associated with disease severity in patients with COVID-19 in Bangladesh

The longevity of immune responses induced by different degrees of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection provides information important to understanding protection against coronavirus disease 2019 (COVID-19). Here, we report the persistence of SARS-CoV-2 spike receptor-binding domain (RBD) specific antibodies and memory B cells recognizing this antigen in sequential samples from patients in Bangladesh with asymptomatic, mild, moderate and severe COVID-19 out to six months following infection. Since the development of long-lived memory B cells, as well as antibody production, is likely to be dependent on T helper (Th) cells, we also investigated the phenotypic changes of Th cells in COVID-19 patients over time following infection. Our results show that patients with moderate to severe COVID-19 mounted significant levels of IgG antibodies out to six months following infection, while patients with asymptomatic or mild disease had significant levels of IgG antibodies out to 3 months following infection, but these then fell more rapidly at 6 months than in patients with higher disease severity. Patients from all severity groups developed circulating memory B cells (MBCs) specific to SARS-CoV-2 spike RBD by 3 months following infection, and these persisted until the last timepoint measured at 6 months. A T helper cell response with an effector memory phenotype was observed following infection in all symptomatic patients, while patients with asymptomatic infection had no significant increases in effector Th1, Th2 and Th17 effector memory cell responses. Our results suggest that the strength and magnitude of antibody and memory B cells induced following SARS-CoV-2 infection depend on the severity of the disease. Polarization of the Th cell response, with an increase in Th effector memory cells, occurs in symptomatic patients by day 7 following infection, with increases seen in Th1, Th2, Th17 and follicular helper T cell subsets.

Recent spatial gradients and time trends in Dhaka, Bangladesh, air pollution and their human health implications

Dhaka, the capital of Bangladesh, is among the most polluted cities in the world. This research evaluates seasonal patterns, day-of-week patterns, spatial gradients, and trends in PM2.5 (<2.5 µm in aerodynamic diameter), PM10 (<10 µm in aerodynamic diameter), and gaseous pollutants concentrations (SO2, NO2, CO, and O3) monitored in Dhaka from 2013 to 2017. It expands on past work by considering multiple monitoring sites and air pollutants. Except for ozone, the average concentrations of these pollutants showed strong seasonal variation, with maximum during winter and minimum during monsoon, with the pollution concentration of PM2.5 and PM10 being roughly five- to sixfold higher during winter versus monsoon. Our comparisons of the pollutant concentrations with Bangladesh NAAQS and U.S. NAAQS limits analysis indicate particulate matter (PM2.5 and PM10) as the air pollutants of greatest concern, as they frequently exceeded the Bangladesh NAAQS and U.S. NAAQS, especially during nonmonsoon time. In contrast, gaseous pollutants reported far fewer exceedances throughout the study period. During the study period, the highest number of exceedances of NAAQS limits in Dhaka City (Darus-Salam site) were found for PM2.5 (72% of total study days), followed by PM10 (40% of total study days), O3 (1.7% of total study days), SO2 (0.38% of total study days), and CO (0.25% of total study days). The trend analyses results showed statistically significant positive slopes over time for SO2 (5.6 ppb yr-1, 95% confidence interval [CI]: 0.7, 10.5) and CO (0.32 ppm yr-1, 95% CI: 0.01, 0.56), which suggest increase in brick kilns operation and high-sulfur diesel use. Though statistically nonsignificant annual decreasing slopes for PM2.5 (-4.6 µg/m3 yr-1, 95% CI: -12.7, 3.6) and PM10 (-2.7 µg/m3 yr-1, 95% CI: -7.9, 2.5) were observed during this study period, the PM2.5 concentration is still too high (~ 82.0 µg/m3) and can cause severe impact on human health. Implications: This study revealed key insights into air quality challenges across Dhaka, Bangladesh, indicating particulate matter (PM) as Dhaka's most serious air pollutant threat to human health. The results of these analyses indicate that there is a need for immediate further investigations, and action based on those investigations, including the conduct local epidemiological PM exposure-human health effects studies for this city, in order to determine the most public health effective interventions.

Prediction of complex two-dimensional trajectories by a cerebellar model of smooth pursuit eye movement

A neural network model based on the anatomy and physiology of the cerebellum is presented that can generate both simple and complex predictive pursuit, while also responding in a feedback mode to visual perturbations from an ongoing trajectory. The model allows the prediction of complex movements by adding two features that are not present in other pursuit models: an array of inputs distributed over a range of physiologically justified delays, and a novel, biologically plausible learning rule that generated changes in synaptic strengths in response to retinal slip errors that arrive after long delays. To directly test the model, its output was compared with the behavior of monkeys tracking the same trajectories. There was a close correspondence between model and monkey performance. Complex target trajectories were created by summing two or three sinusoidal components of different frequencies along horizontal and/or vertical axes. Both the model and the monkeys were able to track these complex sum-of-sines trajectories with small phase delays that averaged 8 and 20 ms in magnitude, respectively. Both the model and the monkeys showed a consistent relationship between the high- and low-frequency components of pursuit: high-frequency components were tracked with small phase lags, whereas low-frequency components were tracked with phase leads. The model was also trained to track targets moving along a circular trajectory with infrequent right-angle perturbations that moved the target along a circle meridian. Before the perturbation, the model tracked the target with very small phase differences that averaged 5 ms. After the perturbation, the model overshot the target while continuing along the expected nonperturbed circular trajectory for 80 ms, before it moved toward the new perturbed trajectory. Monkeys showed similar behaviors with an average phase difference of 3 ms during circular pursuit, followed by a perturbation response after 90 ms. In both cases, the delays required to process visual information were much longer than delays associated with nonperturbed circular and sum-of-sines pursuit. This suggests that both the model and the eye make short-term predictions about future events to compensate for visual feedback delays in receiving information about the direction of a target moving along a changing trajectory. In addition, both the eye and the model can adjust to abrupt changes in target direction on the basis of visual feedback, but do so after significant processing delays.