Objectives This study aimed to determine antibody responses in healthcare workers who receive the BNT162b2 mRNA COVID-19 vaccine and identify factors that predict the response. Methods We recruited healthcare workers receiving the BNT162b2 mRNA COVID-19 vaccine at the Chiba University Hospital COVID-19 Vaccine Center. Blood samples were obtained before the 1 st dose and after the 2 nd dose vaccination, and serum antibody titers were determined using Elecsys® Anti-SARS-CoV-2S, an electrochemiluminescence immunoassay. We established a model to identify the baseline factors predicting post-vaccine antibody titers using univariate and multivariate linear regression analyses. Results Two thousand fifteen individuals (median age 37-year-old, 64.3% female) were enrolled in this study, of which 10 had a history of COVID-19. Before vaccination, 21 participants (1.1%) had a detectable antibody titer (≥0.4 U/mL) with a median titer of 35.9 U/mL (interquartile range [IQR] 7.8 – 65.7). After vaccination, serum anti-SARS-CoV-2S antibodies (≥0.4 U/mL) were detected in all 1,774 participants who received the 2 nd dose with a median titer of 2,060.0 U/mL (IQR 1,250.0 – 2,650.0). Immunosuppressive medication (p<0.001), age (p<0.001), time from 2 nd dose to sample collection (p<0.001), glucocorticoids (p=0.020), and drinking alcohol (p=0.037) were identified as factors predicting lower antibody titers after vaccination, whereas previous COVID-19 (p<0.001), female (p<0.001), time between 2 doses (p<0.001), and medication for allergy (p=0.024) were identified as factors predicting higher serum antibody titers. Conclusions Our data demonstrate that healthcare workers universally have good antibody responses to the BNT162b2 mRNA COVID-19 vaccine. The predictive factors identified in our study may help optimize the vaccination strategy.

Background: The detection of SARS-CoV-2 RNA by real-time reverse transcription-polymerase chain reaction (rRT-PCR) is used to confirm the clinical diagnosis of COVID-19 by molecular diagnostic laboratories. We developed a multiplex rRT-PCR methodology for the detection of SARS-CoV-2 RNA. Methods: Three genes were used for multiplex rRT-PCR: the Sarbecovirus specific E gene, the SARS-CoV-2 specific N gene, and the human ABL1 gene as an internal control. Results: Good correlation of C q values was observed between the simplex and multiplex rRT-PCR methodologies. Low copies (< 25 copies/reaction) of SARS-CoV-2 RNA were detected by the novel multiplex rRT-PCR method. Conclusion:The proposed multiplex rRT-PCR methodology will enable highly sensitive detection of SARS-CoV-2 RNA, reducing reagent use and cost, and time required by clinical laboratory technicians.

Organ and cellular distribution and expression constancy of microsomal cytochrome P450 (CYP) 2C and 3A in humans were studied with new polyclonal antibodies to CYP2C (MP-1) and 3A (NF-2) active in formalin-fixed, paraffin-embedded tissues. Antibodies were raised against purified human CYP2C9 and CYP3A4. On western blotting, MP-1 reacted with 2C8, 2C9, 2C18 and 2C19, and NF-2 with 3A4. In both frozen and paraffin sections, hepatocytes showed diffuse immunoreactivity with MP-1 and centrilobular staining with NF-2. In-paraffin sections of 40 kinds of nonneoplastic tissues, epithelium of the small and large intestine, bile duct, nasal mucosa, kidney and adrenal cortex stained positively with both MP-1 and NF-2 antibodies. Epithelium of gastric fundic glands, salivary glands, tracheobronchial glands, Brunner's glands, the prostate, uterine cervix and nasopharynx showed definite reactivity with MP-1. Epithelium of the gastric mucosa with intestinal metaplasia, duodenum, gallbladder and intercalated ducts of the pancreas and chief cells of the parathyroid and the corpus luteum of the ovary reacted with NF-2. Among the neoplastic tissues, MP-1 reacted with pleomorphic adenoma of the salivary gland and carcinomas of six different organs, and NF-2 with those of 7 different organs. These results indicate that CYP2C and CYP3A are distributed widely and organ specifically, as well as being variably expressed in neoplastic and normal states.

Background The World Health Organization declared the novel coronavirus outbreak (COVID-19) to be a pandemic on March 11, 2020. Large-scale monitoring for capturing the current epidemiological situation of COVID-19 in Japan would improve preparation for and prevention of a massive outbreak. Methods A chatbot-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And care seeking) was developed using the LINE app to evaluate the current Japanese epidemiological situation. LINE users could participate in the system either though a QR code page in the prefectures’ websites or a banner at the top of the LINE app screen. COOPERA asked participants questions regarding personal information, preventive actions, and non-specific symptoms related to COVID-19 and their duration. We calculated daily cross correlation functions between the reported number of infected cases confirmed using polymerase chain reaction and the symptom-positive group captured by COOPERA. Results We analyzed 206,218 participants from three prefectures reported between March 5 and 30, 2020. The mean age of participants was 44.2 (standard deviation, 13.2) years. No symptoms were reported by 96.93% of participants, but there was a significantly positive correlation between the reported number of COVID-19 cases and self-reported fevers, suggesting that massive monitoring of fever might help to estimate the scale of the COVID-19 epidemic in real time. Conclusions COOPERA is the first real-time system being used to monitor trends in COVID-19 in Japan and provides useful insights to assist political decisions to tackle the epidemic.

There is no detailed information on the association between age, time of disease, and HIV-associated neurocognitive disorders (HAND). In this prospective study involving 17 medical facilities across Japan, we recruited HIV-infected patients to complete a 14-test neuropsychological battery that assess eight neurocognitive domains. HAND were diagnosed by the Frascati criteria. Of 1399 recruited patients, 728 were enrolled. The prevalence of HAND was 25.3% [13.5% asymptomatic neurocognitive impairment, 10.6% mild neurocognitive disorder (MND), and 1.2% HIV-associated dementia (HAD)]. Tests that assess executive and visuospatial functions showed better diagnostic accuracy than other tests for HAND. Multivariate analysis identified age (≥ 50 years) and incomplete virological suppression as risk factors for MND and HAD and current ART as a protective factor. The prevalence of MND and HAD was low in the early stage of infection (6.3% in ≥ 2 to < 6 years), then increased in the later stage [17.3% in ≥ 11 years, p = 0.001 (vs. ≥ 2 to < 6 years)], independent of age or treatment. Older patients were more likely to show MND or HAD in the early stage of HIV infection (26.7 vs. 8.7% for < 2 years and 17.4 vs. 3.1% for ≥ 2 to < 6 years, p = 0.040 and 0.004, respectively) compared to younger ones. In conclusion, MND and HAD were more commonly found in later years since diagnosis of HIV infection and older patients are at risk of neurocognitive impairment at the early stage of HIV infection. Tests for executive and visuospatial functions seem more sensitive than other tests for diagnosing HAND.

Objectives Among persons in current HIV outpatient care, data on opioid prescribing are lacking. This study aims to evaluate predictors of repeat opioid prescribing and to characterize outpatient opioid prescribing practices. Methods Retrospective cross-sectional study of persons ≥ 18 years in HIV outpatient care who completed an annual behavioral assessment between June 2008 and June 2009. Persons were grouped by ≤ 1 and ≥ 2 opioid prescriptions (no-repeat-opioid and repeat-opioids, respectively). Independent predictors for repeat-opioids were evaluated. Opioid prescribing practices were characterized in a sub-study of persons prescribed any opioid. Results Overall, 659 persons were included, median age 43 years, 70% men, and 68% African American. Independent predictors of repeat-opioids (88 [13%] persons) included opportunistic illnesses (both current and previous), depression, peripheral neuropathy, and hepatitis C coinfection (P < 0.05). In the subgroup, 140 persons received any opioid prescription (96% short-acting, 33% tramadol). Indications for opioid prescribing were obtained in 101 (72%) persons, with 97% for noncancer-related pain symptoms. Therapeutic response was documented on follow-up in 67 (48%) persons, with no subjective relief of symptoms in 63%. Urine drug screens were requested in 6 (4%) persons, and all performed were positive for illicit drugs. Conclusions Advanced HIV disease and greater medical and neuropsychiatric comorbidity predict repeat opioid prescribing, and these findings reflect the underlying complexities in managing pain symptoms in this population. We also highlight multiple deficiencies in opioid prescribing practices and nonadherence to guidelines, which are of concern as effective and safe pain management for our HIV-infected population is an optimal goal.

Background In the absence of widespread testing, symptomatic monitoring efforts may allow for understanding the epidemiological situation of the spread of coronavirus disease 2019 (COVID-19) in Japan. We obtained data from a social networking service (SNS) messaging application that monitors self-reported COVID-19 related symptoms in real time in Fukuoka Prefecture, Japan. We aimed at not only understanding the epidemiological situation of COVID-19 in the prefecture, but also highlighting the usefulness of symptomatic monitoring approaches that rely on self-reporting using SNS during a pandemic, and informing the assessment of Japan's emergency declaration over COVID-19. Methods We analysed symptoms data (fever over 37.5° and a strong feeling of weariness or shortness of breath), reported voluntarily via SNS chatbot by 227,898 residents of Fukuoka Prefecture during March 27 to May 3, 2020, including April 7, when a state of emergency was declared. We estimated the spatial correlation coefficient between the number of the self-reported cases of COVID-19 related symptoms and the number of PCR confirmed COVID-19 cases in the period (obtained from the prefecture website); and estimated the empirical Bayes age- and sex-standardised incidence ratio (EBSIR) of the symptoms in the period, compared before and after the declaration. The number of symptom cases was weighted by age and sex to reflect the regional population distribution according to the 2015 national census. Findings Of the participants, 3.47% reported symptoms. There was a strong spatial correlation of 0.847 (p < 0.001) at municipality level between the weighted number of self-reported symptoms and the number of COVID-19 cases for both symptoms. The EBSIR at post-code level was not likely to change remarkably before and after the declaration of the emergency, but the gap in EBSIR between high-risk and low-risk areas appeared to have increased after the declaration. Interpretation While caution is necessary as the data was limited to SNS users, the self-reported COVID-19 related symptoms considered in the study had high epidemiological evaluation ability. In addition, though based on visual assessment, after the declaration of the emergency, regional containment of the infection risk might have strengthened to some extent. SNS, which can provide a high level of real-time, voluntary symptom data collection, can be used to assess the epidemiology of a pandemic, as well as to assist in policy assessments such as emergency declarations. Funding The present work was supported in part by a grant from the Ministry of Health, Labour and Welfare of Japan (H29-Gantaisaku-ippan-009).

Background On April 7, 2020, the Japanese government declared a state of emergency regarding the novel coronavirus (COVID-19). Given the nation-wide spread of the coronavirus in major Japanese cities and the rapid increase in the number of cases with untraceable infection routes, large-scale monitoring for capturing the current epidemiological situation of COVID-19 in Japan is urgently required. Methods A chatbot-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And AN care seeking) was developed to surveil the Japanese epidemiological situation in real-time. COOPERA asked questions regarding personal information, location, preventive actions, COVID-19 related symptoms and their residence. Empirical Bayes estimates of the age-sex-standardized incidence rate and disease mapping approach using scan statistics were utilized to identify the geographical distribution of the symptoms in Tokyo and their spatial correlation r with the identified COVID-19 cases. Findings We analyzed 353,010 participants from Tokyo recruited from 27th March to 6th April 2020. The mean (SD) age of participants was 42.7 (12.3), and 63.4%, 36.4% or 0.2% were female, male, or others, respectively. 95.6% of participants had no subjective symptoms. We identified several geographical clusters with high spatial correlation ( r = 0.9), especially in downtown areas in central Tokyo such as Shibuya and Shinjuku. Interpretation With the global spread of COVID-19, medical resources are being depleted. A new system to monitor the epidemiological situation, COOPERA, can provide insights to assist political decision to tackle the epidemic. In addition, given that Japan has not had a strong lockdown policy to weaken the spread of the infection, our result would be useful for preparing for the second wave in other countries during the next flu season without a strong lockdown. Funding The present work was supported in part by a grant from the Ministry of Health, Labour and Welfare of Japan (H29-Gantaisaku-ippan-009).