ABSTRACT
Antibody titers wane after two-dose COVID-19 vaccinations, but individual variation in vaccine-elicited antibody dynamics remains to be explored. Here, we created a personalized antibody score that enables individuals to infer their antibody status by use of a simple calculation. We recently developed a mathematical model of B cell differentiation to accurately interpolate the longitudinal data from a community-based cohort in Fukushima, Japan, which consists of 2,159 individuals who underwent serum sampling two or three times after a two-dose vaccination with either BNT162b2 or mRNA-1273. Using the individually reconstructed time course of the vaccine-elicited antibody response, we first elucidated individual background factors that contributed to the main features of antibody dynamics, i.e., the peak, the duration, and the area under the curve. We found that increasing age was a negative factor and a longer interval between the two doses was a positive factor for individual antibody level. We also found that the presence of underlying disease and the use of medication affected antibody levels negatively, whereas the presence of adverse reactions upon vaccination affected antibody levels positively. We then applied to these factors a recently proposed computational method to optimally fit clinical scores, which resulted in an integer-based score that can be used to evaluate the antibody status of individuals from their basic demographic and health information. This score can be easily calculated by individuals themselves or by medical practitioners. There is a potential usefulness of this score for identifying vulnerable populations and encouraging them to get booster vaccinations. Significance statementDifferent individuals show different antibody titers even after the same COVID-19 vaccinations, making some individuals more prone to breakthrough infections than others. Such variability remains to be clarified. Here we used mathematical modeling to reconstruct individual post-vaccination antibody dynamics from a cohort of 2,159 individuals in Fukushima, Japan. Machine learning identified several positive and negative factors affecting individual antibody titers. Positive factors included adverse reactions after vaccinations and a longer interval between two vaccinations. Negative factors included age, underlying medical conditions, and medications. We combined these factors and developed an "antibody score" to estimate individual antibody dynamics from basic demographic and health information. This score can help to guide individual decision-making about taking further precautions against COVID-19.
ABSTRACT
Recent studies have provided insights into the effect of vaccine boosters on recall immunity. Given the limited global supply of COVID-19 vaccines, identifying vulnerable populations with lower sustained vaccine-elicited antibody titers is important for targeting individuals for booster vaccinations. Here we investigated longitudinal data in a cohort of 2,526 people in Fukushima, Japan, from April 2021 to December 2021. Antibody titers following two doses of a COVID-19 vaccine were repeatedly monitored and information on lifestyle habits, comorbidities, adverse reactions, and medication use was collected. Using mathematical modeling and machine learning, we stratified the time-course patterns of antibody titers and identified vulnerable populations with low sustained antibody titers. Moreover, we showed that only 5.7% of the participants in our cohort were part of the "durable" population with high sustained antibody titers, which suggests that this durable population might be overlooked in small cohorts. We also found large variation in antibody waning within our cohort. There is a potential usefulness of our approach for identifying the neglected vulnerable population.
ABSTRACT
ObjectivesTo compare the temporal changes of IgM, IgG, and IgA antibodies against the SARS-CoV-2 nucleoprotein, S1 subunit, and receptor binding domain and neutralizing antibodies (NAbs) against SARS-CoV-2 in patients with COVID-19. MethodsA total of five patients in Nissan Tamagawa Hospital, Tokyo, Japan confirmed COVID-19 from August 8, 2020 to August 14, 2020 were investigated. Serum samples were acquired multiple times from 0 to 76 days after symptom onset. Using a fully automated CLIA analyzer, we measured the levels of IgG, IgA, and IgM against the SARS-CoV-2 N, S1, and RBD and NAbs against SARS-CoV-2. ResultsThe levels of IgG antibodies against SARS-CoV-2 structural proteins increased over time in all cases but IgM and IgA levels against SARS-CoV-2 showed different increasing trends among individuals in the early stage. In particular, we observed IgA antibodies increasing before IgG and IgM in 3/5 cases. The NAb levels against SARS-CoV-2 increased and kept above 10 AU/mL more than around 70 days after symptom onset in all cases. Furthermore, in the early stage, NAb levels were more than cut off value in 4/5 COVID-19 patients some of whose antibodies against RBD didnt exceed 10 AU/mL. ConclusionsOur findings indicate that patients with COVID-19 should be examined for IgG, IgA and IgM antibodies against SARS-CoV-2 structural proteins and NAbs against SARS-CoV-2 in addition to conventional antibody testing methods for SARS-CoV-2 (IgG and IgM kits) to analyze the diversity of patients immune mechanisms.
ABSTRACT
1) Children's data (10-18 years old) of back strength, height, grip strength and running long jump from data book of Japan Education Ministry (1964-1981) were analyzed. Back strength was mainly studied and was compared with other data (grip strength etc.) . The groups with high average values for back strength at 10-14 years old did not necessarily show high values for back strength at 17 years old, or vice versa. Values for back strength at 10-14 years old were not significantly correlated with those at 17 years old.<BR>2) Using the data from data book mentioned above, tension of deep back muscle (FMUS) was calculated based on kinetic models (FMUS. I, II, III) . Calculated FMUS values were 3-5 times larger than measured back strength values at each age.<BR>3) Relative change of back strength and FMUS in 1964-1981 were compared. All values for back strength were lower than those for FMUS except in 1967. During the late 1960th and the 1970th, average back strength values gradully decreased, but the decrease of FMUS was less obvious than that of back strength.<BR>4) Based on the data of 422 children (7-12 years old, male and femele), values of diaphragm area were approximated with some assumptions, and then FMUS values were calculated. FMUS values calculated by approximate diaphragm area were significantly larger than those calculated by constant diaphragm area (465 cm2) .<BR>The figure for getting FMUS values easily was offered to avoid troublesome calculation. This consists of two graphs, and one can read FMUS values with reasonable precision. Parameters needed for getting FMUS values are sexuality, height, body weight and back strength.
ABSTRACT
Long term physical training is known to cause a change of cardiac functions and this effect is observed at various levels of the heart (from whole heart to subcellular level), although its mechanism is not fully understood. It is reported that cardiac hypertrophy and decreased heart rate can be observed as effects of long term physical training, but change of the catecholamine content in heart tissue induced by training is controversial.<BR>In the present experiment, long schedule of short daily swimming episodes was employed to observe the effect of mild physical training on cardiac functions of rats in the growing stage. We measured body weight, heart weight, heart rate under light anesthesia, variation of R-R-interval of electrocardiogram, and catecholamine contents in cardiac muscle.<BR>1) Wister rats were divided into 2 groups 3 weeks after birth. One group rats was kept sedentary in cages, and the other group was required to free swim in a tank containing water at 30°C. At the beginning of the programme, swimming time was 10 min. Swimming was applied 5 days a week for up to 14 weeks, and swimming time was gradually increased to 30 min.<BR>2) Body weight of rats in the trained group was significantly less than that of the controls, and the heart weight to body weight ratio in the trained rats was significantly higher than in the controls.<BR>3) In the exercised rats, the R-R interval of the ECG was longer than that of the controls, and there was a tendency for the variation of R-R interval in the trained group to be larger than that of the controls.<BR>4) At 10 and 17 weeks, rats from each group were sacrificed after or without a 30 min test swim for measurement of catecholamine content of the ventricular muscle. One time swimming for 30 min increased dopamine content, but did not change norepinephrine content except for the trained group at 10 weeks. There was no significant difference in cardiac catecholamine contents in the rested state of the control and trained groups at 10 and 17 weeks.<BR>5) Results were interpreted as follows: One time swimming for 30 min influences the activity of the autonomic nervous system innervating the heart, and catecholamine metabolism at nerve terminals of the sympathetic nervous system. Long term mild swimming does not cause permanent change of catecholamine contents, and the low heart rate in the trained group cannot be soley explained by the decreased activity of the sympathetic nervous system.
