Predictive biomarkers of COVID-19 prognosis identified in Bangladesh patients and validated in Japanese cohorts.

Despite high vaccination rates globally, countries are still grappling with new COVID infections, and patients diagnosed as mild dying at home during outpatient treatment. Hence, this study aim to identify, then validate, biomarkers that could predict if newly infected COVID-19 patients would subsequently require hospitalization or could recover safely with medication as outpatients. Serum cytokine/chemokine data from 129 COVID-19 patients within 7 days after the onset of symptoms in Bangladesh were used as training data. The majority of patients were infected with the Omicron variant and over 88% were vaccinated. Patients were divided into those with mild symptoms who recovered, and those who deteriorated to moderate or severe illness. Using the Lasso method, 15 predictive markers were identified and used to classify patients into these two groups. The biomarkers were then validated in a cohort of 194 Covid patients in Japan with a predictive accuracy that exceeded 80% for patients infected with Delta and Omicron variants, and 70% for Wuhan and Alpha variants. In an environment of widespread vaccination, these biomarkers could help medical practitioners determine if newly infected COVID-19 patients will improve and can be managed on an out-patient basis, or if they will deteriorate and require hospitalization.

Estimation of spatio-temporal distribution of 137Cs concentrations in litter layer of forest ecosystems in Fukushima using FoRothCs model.

The nuclear power plant accident in Fukushima had led to pollution of forest ecosystems with 137Cs in 2011. In this study, we simulated the spatiotemporal distribution of 137Cs concentrations of litter layer in the contaminated forest ecosystems in two decades from 2011, which is one of the key environmental components of 137Cs migration in the environment due to the high bioavailability of 137Cs in the litter. Our simulations showed that 137Cs deposition is the most important factor in the degree of contamination of the litter layer but vegetation type (evergreen coniferous/deciduous broadleaf) and mean annual temperature are also important for changes over time. Deciduous broadleaf trees had higher initial concentrations in the litter layer due to the direct initial deposition on the forest floor. However, the concentrations remained higher than those in evergreen conifers after 10 years due to redistribution of 137Cs by vegetation. Moreover, areas with lower average annual temperatures and lower litter decomposition activity retained higher 137Cs concentrations in the litter layer. The results of the spatiotemporal distribution estimation of the radioecological model suggest that, in addition to 137Cs deposition, elevation and vegetation distribution should also be considered in the long-term management of contaminated watersheds, which can be informative in identifying hotspots of 137Cs contamination on a long-term scale.

Ten-year trends in vertical distribution of radiocesium in Fukushima forest soils, Japan.

To elucidate interannual changes in the vertical distribution of 137Cs in forest ecosystems contaminated by the Fukushima Dai-ichi Nuclear Power Plant accident, we investigated 137Cs inventories in forest soils (both organic and mineral soil horizons) at 10 sampling plots with different 137Cs deposition levels and dominant species for up to 10 years after the accident. We examined the temporal variation of the 137Cs inventories by depth with exponential regression models (assuming that the transition and partitioning of 137Cs are still active) and exponential offset regression models (assuming a shift to a stable 137Cs distribution, defined as the "quasi-equilibrium steady-state" in the Chernobyl accident). In the organic horizon, the 137Cs inventories were exponentially decreasing, and it might take more time to converge in the quasi-equilibrium steady-state at most plots. In the mineral soil horizon, most of 137Cs was found in the surface layer of the mineral soil horizon (0-5 cm). In this layer, the inventories first increased and then become relatively constant, and the exponential offset model was selected at most plots, suggesting entry into the quasi-equilibrium steady-state over the observation period. Although we also observed exponentially increasing trends in a lower layer (5-10 cm) of the mineral soil horizon, there was no clear increasing or decreasing trend of 137Cs inventory in the deeper mineral soil layers (10-15 and 15-20 cm). Our calculation of the relaxation depth and migration center revealed that downward migration of 137Cs is not significant in terms of the overall 137Cs distribution in the mineral soil horizon over 10 years.

Strategic roadmap to assess forest vulnerability under air pollution and climate change.

Although it is an integral part of global change, most of the research addressing the effects of climate change on forests have overlooked the role of environmental pollution. Similarly, most studies investigating the effects of air pollutants on forests have generally neglected the impacts of climate change. We review the current knowledge on combined air pollution and climate change effects on global forest ecosystems and identify several key research priorities as a roadmap for the future. Specifically, we recommend (1) the establishment of much denser array of monitoring sites, particularly in the South Hemisphere; (2) further integration of ground and satellite monitoring; (3) generation of flux-based standards and critical levels taking into account the sensitivity of dominant forest tree species; (4) long-term monitoring of N, S, P cycles and base cations deposition together at global scale; (5) intensification of experimental studies, addressing the combined effects of different abiotic factors on forests by assuring a better representation of taxonomic and functional diversity across the ~73,000 tree species on Earth; (6) more experimental focus on phenomics and genomics; (7) improved knowledge on key processes regulating the dynamics of radionuclides in forest systems; and (8) development of models integrating air pollution and climate change data from long-term monitoring programs.

Anti-nucleocapsid antibodies enhance the production of IL-6 induced by SARS-CoV-2 N protein.

A cytokine storm induces acute respiratory distress syndrome, the main cause of death in coronavirus disease 2019 (COVID-19) patients. However, the detailed mechanisms of cytokine induction due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain unclear. To examine the cytokine production in COVID-19, we mimicked the disease in SARS-CoV-2-infected alveoli by adding the lysate of SARS-CoV-2-infected cells to cultured macrophages or induced pluripotent stem cell-derived myeloid cells. The cells secreted interleukin (IL)-6 after the addition of SARS-CoV-2-infected cell lysate. Screening of 25 SARS-CoV-2 protein-expressing plasmids revealed that the N protein-coding plasmid alone induced IL-6 production. The addition of anti-N antibody further enhanced IL-6 production, but the F(ab')2 fragment did not. Sera from COVID-19 patients also enhanced IL-6 production, and sera from patients with severer disease induced higher levels of IL-6. These results suggest that anti-N antibody promotes IL-6 production in SARS-CoV-2-infected alveoli, leading to the cytokine storm of COVID-19.

Pre- and post-accident environmental transfer of radionuclides in Japan: lessons learned in the IAEA MODARIA II programme.

An international review of radioecological data derived after the accident at the Fukushima Daiichi nuclear power plant was an important component of activities in working group 4 of the IAEA Models and data for radiological impact assessment, phase II (MODARIA II) programme. Japanese and international scientists reviewed radioecological data in the terrestrial and aquatic environments in Japan reported both before and after the accident. The environmental transfer processes considered included: (a) interception and retention radionuclides by plants, (b) loss of radionuclides from plant and systemic transport of radionuclides in plants (translocation), (c) behaviour of radiocaesium in soil, (d) uptake of radionuclides from soil by agricultural crops and wild plants, (e) transfer of radionuclides from feedstuffs to domestic and wild animals, (f) behaviour of radiocaesium in forest trees and forest systems, (g) behaviour of radiocaesium in freshwater systems, coastal areas and in the ocean, (h) transport of radiocaesium from catchments through rivers, streams and lakes to the ocean, (i) uptake of radiocaesium by aquatic organisms, and (j) modification of radionuclide concentrations in food products during food processing and culinary preparation. These data were compared with relevant global data within IAEA TECDOC-1927 'Environmental transfer of radionuclides in Japan following the accident at the Fukushima Daiichi Nuclear Power Plant'. This paper summarises the outcomes of the data collation and analysis within MODARIA II work group 4 and compares the Japan-specific data with existing radioecological knowledge acquired from past and contemporary radioecological studies. The key radioecological lessons learned are outlined and discussed.

Effects of species and geo-information on the 137Cs concentrations in edible wild mushrooms and plants collected by residents after the Fukushima nuclear accident.

After the accident at the Fukushima Daiichi Nuclear Power Plant (FDNPP), much of the wild and edible mushrooms and plants in the surrounding areas were contaminated with radiocesium (137Cs). To elucidate their concentration characteristics, we analyzed 137Cs radioactivity data in edible forest products brought in for food inspection by the residents of Kawauchi Village, 12-30 km away from the FDNPP, from 2012 to 2019. A Bayesian model to estimate 137Cs concentration was constructed. Parameters of the normalized concentration of species (NCsp) for mushrooms were similar to those of the same species obtained in a previous study. Although NCsp values were highly varied among species, mycorrhizal mushrooms tended to have high NCsp values, followed by saprotrophic mushrooms, and wild edible plants values were low. Also, half of mycorrhizal mushroom species (8 of 16) showed an increasing trend in concentration with time; however, saprotrophic mushrooms and wild plants generally demonstrated a decreasing trend (22 of 24). The model considering the sub-village location information decreased the error of individual samples by 40% compared to the model not considering any location information, indicating that the detailed geo-information improved estimation accuracy. Our results indicate that the radioactivity data from samples collected by local residents can be used to accurately assess internal exposure to radiation due to self-consumption of contaminated wild mushrooms and plants.

Verification of our empirical understanding of the physiology and ecology of two contrasting plantation species using a trait database.

The effects of climate change on forest ecosystems take on increasing importance more than ever. Information on plant traits is a powerful predictor of ecosystem dynamics and functioning. We reviewed the major ecological traits, such as foliar gas exchange and nutrients, xylem morphology and drought tolerance, of Cryptomeria japonica and Chamaecyparis obtusa, which are major timber species in East Asia, especially in Japan, by using a recently developed functional trait database for both species (SugiHinokiDB). Empirically, C. obtusa has been planted under drier conditions, whereas C. japonica, which grows faster but thought to be less drought tolerant, has been planted under wetter conditions. Our analysis generally support the empirical knowledge: The maximum photosynthetic rate, stomatal conductance, foliar nutrient content and soil-to-foliage hydraulic conductance were higher in C. japonica than in C. obtusa. In contrast, the foliar turgor loss point and xylem pressure corresponding to 50% conductivity, which indicate drought tolerance, were lower in C. obtusa and are consistent with the drier habitat of C. obtusa. Ontogenetic shifts were also observed; as the age and height of the trees increased, foliar nutrient concentrations, foliar minimum midday water potential and specific leaf area decreased in C. japonica, suggesting that nutrient and water limitation occurs with the growth. In C. obtusa, the ontogenetic shits of these foliar traits were less pronounced. Among the Cupressaceae worldwide, the drought tolerance of C. obtusa, as well as C. japonica, was not as high. This may be related to the fact that the Japanese archipelago has historically not been subjected to strong dryness. The maximum photosynthetic rate showed intermediate values within the family, indicating that C. japonica and C. obtusa exhibit relatively high growth rates in the Cupressaceae family, and this is thought to be the reason why they have been selected as economically suitable timber species in Japanese forestry. This study clearly demonstrated that the plant trait database provides us a promising opportunity to verify out empirical knowledge of plantation management and helps us to understand effect of climate change on plantation forests by using trait-based modelling.

Prompt Reduction in CRP, IL-6, IFN-γ, IP-10, and MCP-1 and a Relatively Low Basal Ratio of Ferritin/CRP Is Possibly Associated With the Efficacy of Tocilizumab Monotherapy in Severely to Critically Ill Patients With COVID-19.

Background and Aim: Tocilizumab, a humanized anti-IL-6 receptor antibody, has been used to treat severely to critically ill patients with COVID-19. A living systematic review with meta-analysis of recent RCTs indicates that the combination therapy of corticosteroids and tocilizumab produce better outcomes, while previous observational studies suggest that tocilizumab monotherapy is beneficial for substantial numbers of patients. However, what patients could respond to tocilizumab monotherapy remained unknown. Methods: In this retrospective study we evaluated the effects of tocilizumab monotherapy on the clinical characteristics, serum biomediator levels, viral elimination, and specific IgG antibody induction in 13 severely to critically ill patients and compared with those of dexamethasone monotherapy and dexamethasone plus tocilizumab. Results: A single tocilizumab administration led to a rapid improvement in clinical characteristics, inflammatory findings, and oxygen supply in 7 of 11 patients with severe COVID-19, and could recover from mechanical ventilation management (MVM) in 2 patients with critically ill COVID-19. Four patients exhibited rapidly worsening even after tocilizumab administration and required MVM and additional methylprednisolone treatment. Tocilizumab did not delay viral elimination or inhibit IgG production specific for the virus, whereas dexamethasone inhibited IgG induction. A multiplex cytokine array system revealed a significant increase in the serum expression of 54 out of 80 biomediators in patients with COVID-19 compared with that in healthy controls. Compared with those who promptly recovered in response to tocilizumab, patients requiring MVM showed a significantly higher ratio of basal level of ferritin/CRP and a persistent increase in the levels of CRP and specific cytokines and chemokines including IL-6, IFN-γ, IP-10, and MCP-1. The basal high ratio of ferritin/CRP was also associated with clinical deterioration even in patients treated with dexamethasone and tocilizumab. Conclusion: Tocilizumab as monotherapy has substantial beneficial effects in some patients with severe COVID-19, who showed a relatively low level of the ratio of ferritin/CRP and prompt reduction in CRP, IL-6, IFN-γ, IP-10, and MCP-1. The high ratio of ferritin/CRP is associated with rapid worsening of pneumonia. Further evaluation is warranted to clarify whether tocilizumab monotherapy or its combination with corticosteroid is preferred for severely to critically ill patients with COVID-19.

Dynamics of radiocaesium within forests in Fukushima-results and analysis of a model inter-comparison.

Forests cover approximately 70% of the area contaminated by the Fukushima Daiichi Nuclear Power Plant accident in 2011. Following this severe contamination event, radiocaesium (137Cs) is anticipated to circulate within these forest ecosystems for several decades. Since the accident, a number of models have been constructed to evaluate the past and future dynamics of 137Cs in these forests. To explore the performance and uncertainties of these models we conducted a model inter-comparison exercise using Fukushima data. The main scenario addressed an evergreen needleleaf forest (cedar/cypress), which is the most common and commercially important forest type in Japan. We also tested the models with two forest management scenarios (decontamination by removal of soil surface litter and forest regeneration) and, furthermore, a deciduous broadleaf forest (konara oak) scenario as a preliminary modelling study of this type of forest. After appropriate calibration, the models reproduced the observed data reliably and the ranges of calculated trajectories were narrow in the early phase after the fallout. Successful model performances in the early phase were probably attributable to the availability of comprehensive data characterizing radiocaesium partitioning in the early phase. However, the envelope of the calculated model end points enlarged in long-term simulations over 50 years after the fallout. It is essential to continue repetitive verification/validation processes using decadal data for various forest types to improve the models and to update the forecasting capacity of the models.

Tree manipulation experiment for the short-term effect of tree cutting on N2O emission: A evaluation using Bayesian hierarchical modeling.

Considerable uncertainty exists with regard to the effects of thinning and harvesting on N2O emissions as a result of changes caused in the belowground environment by tree cutting. To evaluate on the effects of changes in the belowground environment on N2O emissions from soils, we conducted a tree manipulation experiment in a Japanese cedar (Cryptomeria japonica) stand without soil compaction or slash falling near measurement chambers and measured N2O emission at distances of 50 and 150 cm from the tree stem (stump) before and after cutting. In addition, we inferred the effects of logging on the emission using a hierarchical Bayesian (HB) model. Our results showed that tree cutting stimulated N2O emission from soil and that the increase in N2O emission depended on the distance from the stem (stump); increase in N2O emission was greater at 50 than at 150 cm from the stem. Tree cutting caused the estimated N2O emission at 0-40 cm from the stem to double (the % increase in N2O emission by tree cutting was 54%-213%, 95% predictive credible interval) when soil temperature was 25 °C and WFPS was 60%. Posterior simulation of the HB model predicted that 30% logging would cause a 57% (47%-67%) increase in N2O emission at our study site (2000 trees ha-1) considering only the effects of belowground changes by tree cutting during the measurement period.

Scoring system for identifying Japanese patients with COVID-19 at risk of requiring oxygen supply: A retrospective single-center study.

INTRODUCTION: Japan is facing the threat of medical system collapse due to the rapid spread of coronavirus disease 2019 (COVID-19). The present scoring system may help assess disease severity and oxygen supply requirements in COVID-19 patients. METHODS: Data on patient characteristics at baseline and throughout hospitalization for COVID-19 were extracted from medical records. Disease severity was dichotomized into two categories without or with oxygen supply as asymptomatic, mild, and moderate illness (AMMI), and severe and critical illness (CSI). The AMMI and CSI groups were compared. Predictors of disease severity, previously identified in the outpatient setting, were included in multivariable logistic regression analysis; the obtained coefficients were converted to integers and assigned a score. RESULTS: A total of 206 patients diagnosed with COVID-19 were included in this study. Correlation between COVID-19 severity and medical information was examined by comparing AMMI and CSI. Age, hemodialysis, and C-reactive protein (CRP) levels were candidate predictors of the need for oxygen supply in patients with COVID-19. Coefficients associated with age, hemodialysis, and CRP were as follows: 1 × age (in years, coded as 0 for values of <50, and as 1 for values of ≥50) + 1 × hemodialysis (coded as 0 for "no", and as 1 for "yes") + 1 × CRP (in mg/dL, coded as 0 for values of <1.0, and as 1 for values of ≥1.0). Patients with scores of ≥2 points required oxygen supply (sensitivity, 68.4%; specificity, 79.0%) CONCLUSION: The present model can help predict disease severity and oxygen requirements in COVID-19 patients in Japan.

Clinical COVID-19 diagnostic methods: Comparison of reverse transcription loop-mediated isothermal amplification (RT-LAMP) and quantitative RT-PCR (qRT-PCR).

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is a major public health concern. Accurate and rapid diagnosis of COVID-19 is critical for disease control. Reverse transcription loop-mediated isothermal amplification (RT-LAMP) is a nucleic acid amplification assay similar to reverse transcription-polymerase chain reaction (RT-PCR), the former being a simple, low cost, and rapid method. OBJECTIVES: This study aimed to compare the RT-LAMP assay with RT-PCR using the Loopamp™ SARS-CoV-2 Detection Kit. STUDY DESIGN: One hundred and fifty-one nasopharyngeal swab and 88 sputum samples obtained from individuals with suspected or confirmed COVID-19 were examined. RESULTS: RT-LAMP had high specificity (98.5 % (95 % CI: 96.9-100 %)), sensitivity (87.0 % (95 % CI: 82.8-91.3 %)), positive predictive value (97.9 % (95 % CI: 96.1-99.7 %)), negative predictive value (90.2 % (95 % CI: 86.4-94.0 %)), and concordance rate (93.3 % (95 % CI: 90.1-96.5 %)). Nasopharyngeal and sputum samples positive in RT-LAMP contained as few as 10.2 and 23.4 copies per 10 µL, respectively. RT-LAMP showed similar performance to RT-PCR for samples with cycle threshold value below 36. CONCLUSIONS: These results indicate that RT-LAMP is a highly reliable and at least equivalent to RT-PCR in utility, and potentially applicable in settings that are more diverse as a point-of-care tool.

Estimating spatial variation in the effects of climate change on the net primary production of Japanese cedar plantations based on modeled carbon dynamics.

Spatiotemporal prediction of the response of planted forests to a changing climate is increasingly important for the sustainable management of forest ecosystems. In this study, we present a methodology for estimating spatially varying productivity in a planted forest and changes in productivity with a changing climate in Japan, with a focus on Japanese cedar (Cryptomeria japonica D. Don) as a representative tree species of this region. The process-based model Biome-BGC was parameterized using a plant trait database for Japanese cedar and a Bayesian optimization scheme. To compare productivity under historical (1996-2000) and future (2096-2100) climatic conditions, the climate scenarios of two representative concentration pathways (i.e., RCP2.6 and RCP8.5) were used in five global climate models (GCMs) with approximately 1-km resolution. The seasonality of modeled fluxes, namely gross primary production, ecosystem respiration, net ecosystem exchange, and soil respiration, improved after two steps of parameterization. The estimated net primary production (NPP) of stands aged 36-40 years under the historical climatic conditions of the five GCMs was 0.77 ± 0.10 kgC m-2 year-1 (mean ± standard deviation), in accordance with the geographical distribution of forest NPP estimated in previous studies. Under the RCP2.6 and RCP8.5 scenarios, the mean NPP of the five GCMs increased by 0.04 ± 0.07 and 0.14 ± 0.11 kgC m-2 year-1, respectively. The increases in annual NPP were small in the southwestern region because of the decreases in summer NPP and the small increases in winter NPP under the RCP2.6 and RCP8.5 scenarios, respectively. Under the RCP2.6 scenario, Japanese cedar was at risk in the southwestern region, in accordance with previous studies, and monitoring and silvicultural practices should be modified accordingly.

Transbronchial Cryobiopsy for Miliary Tuberculosis Mimicking Hypersensitivity Pneumonitis.

Miliary tuberculosis is a potentially lethal type of tuberculosis that results from the hematogenous dissemination of Mycobacterium tuberculosis bacilli. We herein describe the case of a 34-year-old man that presented with a one-month history of cough and fever, while his sputum smear results were negative. Chest computed tomography revealed bilateral centrilobular ground-glass opacification (GGO), suggestive of hypersensitivity pneumonitis; thus, bronchoscopy was performed. Cryobiopsy specimens revealed necrotic granulomas. A re-examination of sputum after bronchoscopy identified Mycobacterium tuberculosis, and miliary tuberculosis was diagnosed. A cryobiopsy might be useful for diagnosing miliary tuberculosis pathologically, particularly when miliary nodules may be masked by GGO.

Factors significantly associated with COVID-19 severity in symptomatic patients: A retrospective single-center study.

INTRODUCTION: The severity of coronavirus disease (COVID-19) in Japanese patients is unreported. We retrospectively examined significant factors associated with disease severity in symptomatic COVID-19 patients (COVID-Pts) admitted to our institution between February 20 and April 30, 2020. METHODS: All patients were diagnosed based on the genetic detection of severe acute respiratory syndrome coronavirus 2. Information on the initial symptoms, laboratory data, and computed tomography (CT) images at hospitalization were collected from the patients' records. COVID-Pts were categorized as those with critical or severe illness (Pts-CSI) or those with moderate or mild illness (Pt-MMI). All statistical analyses were performed using R software. RESULTS: Data from 61 patients (16 Pt-CSI, 45 Pt-MMI), including 58 Japanese and three East Asians, were analyzed. Pt-CSI were significantly older and had hypertension or diabetes than Pt-MMI (P < 0.001, 0.014 and < 0.001, respectively). Serum albumin levels were significantly lower in Pt-CSI than in Pt-MMI (P < 0.001), whereas the neutrophil-to-lymphocyte ratio and C-reactive protein level were significantly higher in Pt-CSI than in Pt-MMI (P < 0.001 and P < 0.001, respectively). In the CT images of 60 patients, bilateral lung lesions were more frequently observed in Pt-CSI than in Pt-MMI (P = 0.013). Among the 16 Pt-CSI, 15 received antiviral therapy, 12 received tocilizumab, five underwent methylprednisolone treatment, six received mechanical ventilation, and one died. CONCLUSIONS: The illness severity of Japanese COVID-Pts was associated with older age, hypertension and/or diabetes, low serum albumin, high neutrophil-to-lymphocyte ratio, and C-reactive protein.

A dataset of 137Cs activity concentration and inventory in forests contaminated by the Fukushima accident.

The majority of the area contaminated by the Fukushima Daiichi Nuclear Power Plant accident is covered with forests. We developed a dataset for radiocaesium (137Cs) in trees, soil, and mushrooms measured at numerous forest sites. The 137Cs activity concentration and inventory data reported in scientific journal papers written in English and Japanese, governmental reports, and governmental monitoring data on the web were collated. The ancillary information describing the forest stands were also collated, and further environmental information (e.g. climate) was derived from the other databases using longitude and latitude coordinates of the sampling locations. The database contains 8593, 4105, and 3189 entries of activity concentration data for trees, soil, and mushrooms, and 471 and 3521 entries of inventory data for trees and soil, respectively, which were collected from 2011 to 2017, and covers the entire Fukushima prefecture. The data can be used to document and understand the spatio-temporal dynamics of radiocaesium in the affected region and to aid the development and validation of models of radiocaesium dynamics in contaminated forests.