Trend differences in cervical spinal cord injuries before and after the coronavirus disease 2019 pandemic.

STUDY DESIGN: Cross-Sectional Study. OBJECTIVES: To investigate the changes in the characteristics of cervical spinal cord injuries (CSCI) before and after the coronavirus disease 2019 (COVID-19) pandemic among patients transported to our hospital in Japan. SETTING: Hospital with an emergency center in Chiba, Japan. METHODS: Patients eligible for the study were those transported within 24 h of injury and diagnosed with cervical spinal cord injury between January 2018 and December 2021 at our hospital. Medical records were retrospectively examined to investigate the number and characteristics of patients with CSCI. The clinical variables of patients with CSCI were compared according to the time of admission as related to the COVID-19 pandemic: 2018-19 (before) or 2020-21 (after). RESULTS: The total number of patients with CSCI from 2018 to 2021 was 108, with 57 before the COVID-19 pandemic and 51 after the COVID-19 pandemic. The number of severe cases with an injury severity score (ISS) of >16 decreased after COVID-19 (p < 0.05). Falls on level surfaces were the most common cause of injury both before and after COVID-19. Although the ranking of traffic accidents decreased after COVID-19, among those, the number of bicycle injuries tended to increase. CONCLUSIONS: The number of serious cases with an ISS > 16 decreased, presumably because of the decline in high-energy trauma due to the background decrease in the number of traffic accidents.

Locating Transition States by Variational Reaction Path Optimization with an Energy-Derivative-Free Objective Function.

Locating transition states is essential for understanding molecular reactions. We propose a double-ended transition state search method by revisiting a variational reaction path optimization method known as the MaxFlux method. Although its original purpose is to add temperature effects to reaction paths, we conversely let the temperature approach zero to obtain an asymptotically exact minimum energy path and its corresponding transition state in variational formalism with an energy-derivative-free objective function. Using several numerical techniques to directly optimize the objective function, the present method reliably finds transition states with low computational cost. In particular, only three force evaluations per iteration are sufficient. This is confirmed on a variety of molecular reactions where the nudged elastic band method often fails. The present method is implemented in Python using the Atomic Simulation Environment and is available on GitHub.

Conformational Dynamics in Proteins: Entangled Slow Fluctuations and Nonequilibrium Reaction Events.

Proteins exhibit conformational fluctuations and changes over various time scales, ranging from rapid picosecond-scale local atomic motions to slower microsecond-scale global conformational transformations. In the presence of these intricate fluctuations, chemical reactions occur and functions emerge. These conformational fluctuations of proteins are not merely stochastic random motions but possess distinct spatiotemporal characteristics. Moreover, chemical reactions do not always proceed along a single reaction coordinate in a quasi-equilibrium manner. Therefore, it is essential to understand spatiotemporal conformational fluctuations of proteins and the conformational change processes associated with reactions. In this Perspective, we shed light on the complex dynamics of proteins and their role in enzyme catalysis by presenting recent results regarding dynamic couplings and disorder in the conformational dynamics of proteins and rare but rapid enzymatic reaction events obtained from molecular dynamics simulations.

Infectious virus shedding duration reflects secretory IgA antibody response latency after SARS-CoV-2 infection.

Infectious virus shedding from individuals infected with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is used to estimate human-to-human transmission risk. Control of SARS-CoV-2 transmission requires identifying the immune correlates that protect infectious virus shedding. Mucosal immunity prevents infection by SARS-CoV-2, which replicates in the respiratory epithelium and spreads rapidly to other hosts. However, whether mucosal immunity prevents the shedding of the infectious virus in SARS-CoV-2-infected individuals is unknown. We examined the relationship between viral RNA shedding dynamics, duration of infectious virus shedding, and mucosal antibody responses during SARS-CoV-2 infection. Anti-spike secretory IgA antibodies (S-IgA) reduced viral RNA load and infectivity more than anti-spike IgG/IgA antibodies in infected nasopharyngeal samples. Compared with the IgG/IgA response, the anti-spike S-IgA post-infection responses affected the viral RNA shedding dynamics and predicted the duration of infectious virus shedding regardless of the immune history. These findings highlight the importance of anti-spike S-IgA responses in individuals infected with SARS-CoV-2 for preventing infectious virus shedding and SARS-CoV-2 transmission. Developing medical countermeasures to shorten S-IgA response time may help control human-to-human transmission of SARS-CoV-2 infection and prevent future respiratory virus pandemics.

Source apportionment of anthropogenic and biogenic organic aerosol over the Tokyo metropolitan area from forward and receptor models.

Organic aerosol (OA) is a dominant component of PM2.5, and accurate knowledge of its sources is critical for identification of cost-effective measures to reduce PM2.5. For accurate source apportionment of OA, we conducted field measurements of organic tracers at three sites (one urban, one suburban, and one forest) in the Tokyo Metropolitan Area and numerical simulations of forward and receptor models. We estimated the source contributions of OA by calculating three receptor models (positive matrix factorization, chemical mass balance, and secondary organic aerosol (SOA)-tracer method) using the ambient concentrations, source profiles, and production yields of OA tracers. Sensitivity simulations of the forward model (chemical transport model) for precursor emissions and SOA formation pathways were conducted. Cross-validation between the receptor and forward models demonstrated that biogenic and anthropogenic SOA were better reproduced by the forward model with updated modules for emissions of biogenic volatile organic compounds (VOC) and for SOA formation from biogenic VOC and intermediate-volatility organic compounds than by the default setup. The source contributions estimated by the forward model generally agreed with those of the receptor models for the major OA sources: mobile sources, biomass combustion, biogenic SOA, and anthropogenic SOA. The contributions of anthropogenic SOA, which are the main focus of this study, were estimated by the forward and receptor models to have been between 9 % and 15 % in summer 2019. The observed percent modern carbon data indicate that the amounts of anthropogenic SOA produced during daytime have substantially declined from 2007 to 2019. This trend is consistent with the decreasing trend of anthropogenic VOC, suggesting that reduction of anthropogenic VOC has been effective in reducing anthropogenic SOA in the atmosphere.

Anisotropic and Finite Effects on Intermolecular Vibration and Relaxation Dynamics: Low-Frequency Raman Spectroscopy of Water Film and Droplet on Graphene by Molecular Dynamics Simulations.

The structural and dynamical properties of water can be greatly altered by the anisotropic interfacial environment. Here, we study the intermolecular vibration and relaxation dynamics of a water film and a water droplet on a graphene surface based on low-frequency Raman spectra calculated from molecular dynamics simulations. The calculated Raman spectra of the interfacial water systems show a weakened libration peak and an enhanced intermolecular hydrogen bond (HB) stretching peak compared to the spectrum of bulk water, which are attributed to softened orientation motion. We also find that the collective polarizability relaxation in the droplet is much slower than that in the film and bulk, which is completely different from the collective dipole relaxation. The slow relaxation is due to a positive correlation between the induced polarizabilities of distinct molecules caused by the global and anisotropic structural fluctuations of the water droplet. Furthermore, we find that the two-dimensional HB network by the orientation-ordered interfacial water molecules leads to different intermolecular vibration dynamics between the parallel and perpendicular components. The present theoretical study demonstrates that low-frequency Raman spectroscopy can reveal the anisotropic and finite effects on the intermolecular dynamics of the water film and droplet.

Non-Omicron breakthrough infection with higher viral load and longer vaccination-infection interval improves SARS-CoV-2 BA.4/5 neutralization.

The immune responses to SARS-CoV-2 variants in COVID-19 cases are influenced by various factors including pre-existing immunity via vaccination and prior infection. Elucidating the drivers for upgrading neutralizing activity to SARS-CoV-2 in COVID-19 cases with pre-existing immunity will aid in improving COVID-19 booster vaccines with enhanced cross-protection against antigenically distinct variants, including the Omicron sub-lineage BA.4/5. This study revealed that the magnitude and breadth of neutralization activity to SARS-CoV-2 variants after breakthrough infections are determined primarily by upper respiratory viral load and vaccination-infection time interval. Extensive neutralizing breadth, covering even the most antigenically distant BA.4/5, was observed in cases with higher viral load and longer time intervals. Antigenic cartography depicted a critical role of the time interval in expanding the breadth of neutralization to SARS-CoV-2 variants. Our results illustrate the importance of dosing interval optimization as well as antigen design in developing variant-proof booster vaccines.

Maternal Exposure to Fine Particulate Matter and Its Chemical Components Increasing the Occurrence of Gestational Diabetes Mellitus in Pregnant Japanese Women.

Introduction: PM2.5 exposure is a suspected risk factor for diabetes. It is hypothesized that maternal PM2.5 exposure contributes to the development of gestational diabetes mellitus (GDM). The association between PM2.5 exposure and GDM is controversial and limited evidence is available for the exposure to PM2.5 chemical components. We investigated the association between maternal exposure to total PM2.5 mass and its components, particularly over the first trimester (early placentation period), and GDM. Methods: Data were obtained from the Japan Perinatal Registry Network database, which includes all live births and stillbirths after 22 weeks of gestation at 39 cooperating hospitals in 23 Tokyo wards (2013-2015). At one fixed monitoring site, we performed daily filter sampling of fine particles and measured daily concentrations of carbon and ion components. The average concentrations of total PM2.5 and its components over the 3 months before pregnancy and the first (0-13 gestational weeks) and second (14-27 gestational weeks) trimesters were calculated and assigned to each woman. We estimated the odds ratios (ORs) of GDM in a multilevel logistic regression model. Results: Among 82,773 women (mean age at delivery = 33.7 years) who delivered singleton births, 3,953 (4.8%) had GDM. In the multiexposure period model, an association between total PM2.5 exposure and GDM was observed for exposure over the first trimester (OR per interquartile range (IQR = 3.63 µg/m3) increase = 1.09; 95% confidence interval (CI) = 1.02-1.16), but not for the 3 months before pregnancy or the second trimester. For PM2.5 components, only organic carbon exposure over the first trimester was positively associated with GDM (OR per IQR (0.51 µg/m3) increase = 1.10; 1.00-1.21). Conclusions: This is the first evidence that exposure to total PM2.5 and one of its components, organic carbon, over the first trimester increases GDM occurrence in Japan.

Intranasal vaccination induced cross-protective secretory IgA antibodies against SARS-CoV-2 variants with reducing the potential risk of lung eosinophilic immunopathology.

To control the coronavirus disease 2019 (COVID-19) pandemic, there is a need to develop vaccines to prevent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. One candidate is a nasal vaccine capable of inducing secretory IgA antibodies in the mucosa of the upper respiratory tract, the initial site of infection. However, regarding the development of COVID-19 vaccines, there is concern about the potential risk of inducing lung eosinophilic immunopathology as a vaccine-associated enhanced respiratory disease as a result of the T helper 2 (Th2)-dominant adaptive immune response. In this study, we investigated the protective effect against virus infection induced by intranasal vaccination of recombinant trimeric spike protein derived from SARS-CoV-2 adjuvanted with CpG oligonucleotides, ODN2006, in mouse model. The intranasal vaccine combined with ODN2006 successfully induced not only systemic spike-specific IgG antibodies, but also secretory IgA antibodies in the nasal mucosa. Secretory IgA antibodies showed high protective ability against SARS-CoV-2 variants (Alpha, Beta and Gamma variants) compared to IgG antibodies in the serum. The nasal vaccine of this formulation induced a high number of IFN-γ-secreting cells in the draining cervical lymph nodes and a lower spike-specific IgG1/IgG2a ratio compared to that of subcutaneous vaccination with alum as a typical Th2 adjuvant. These features are consistent with the induction of the Th1 adaptive immune response. In addition, mice intranasally vaccinated with ODN2006 showed less lung eosinophilic immunopathology after viral challenge than mice subcutaneously vaccinated with alum adjuvant. Our findings indicate that intranasal vaccine adjuvanted with ODN2006 could be a candidate that can prevent the infection of antigenically different variant viruses, reducing the risk of vaccine-associated enhanced respiratory disease.

Molecular Insights into the Intrinsic Dynamics and Their Roles During Catalysis in Pin1 Peptidyl-prolyl Isomerase.

Proteins are intrinsically dynamic and change conformations over a wide range of time scales. While the conformational dynamics have been realized to be important for protein functions, e.g., in activity-stability trade-offs, how they play a role during enzyme catalysis has been of debate over decades. By studying Pin1 peptidyl-prolyl isomerase using extensive molecular dynamics simulations, here we discuss how the slow intrinsic dynamics of Pin1 observed in the NMR relaxation dispersion experiment occur and couple to isomerization reactions in molecular detail. In particular, we analyze the angular correlation functions of the backbone N-H bonds and find that slow conformational transitions occur at about the 310 helix in the apo state. These events at the helical region further affect the residues at about the ligand binding site. Unfolding of this helix leads to a tight hydrogen bond between the helical region and the ligand binding loop, thus forming a stable coiled structure. The helical and coiled structures are found to be characteristic of the Pin1-ligand complex with the ligand in the trans and cis states, respectively. These results indicate that the changes in the slow dynamics of Pin1 by the isomerization reaction occur via the shift in populations of the helical and coiled states, where the balance is dependent on the ligand isomerization states.

Regulation mechanisms of the dual ATPase in KaiC.

KaiC is a dual adenosine triphosphatase (ATPase), with one active site in its N-terminal domain and another in its C-terminal domain, that drives the circadian clock system of cyanobacteria through sophisticated coordination of the two sites. To elucidate the coordination mechanism, we studied the contribution of the dual-ATPase activities in the ring-shaped KaiC hexamer and these structural bases for activation and inactivation. At the N-terminal active site, a lytic water molecule is sequestered between the N-terminal domains, and its reactivity to adenosine triphosphate (ATP) is controlled by the quaternary structure of the N-terminal ring. The C-terminal ATPase activity is regulated mostly by water-incorporating voids between the C-terminal domains, and the size of these voids is sensitive to phosphoryl modification of S431. The up-regulatory effect on the N-terminal ATPase activity inversely correlates with the affinity of KaiC for KaiB, a clock protein constitutes the circadian oscillator together with KaiC and KaiA, and the complete dissociation of KaiB from KaiC requires KaiA-assisted activation of the dual ATPase. Delicate interactions between the N-terminal and C-terminal rings make it possible for the components of the dual ATPase to work together, thereby driving the assembly and disassembly cycle of KaiA and KaiB.

A Case-Crossover Analysis of the Association between Exposure to Total PM2.5 and Its Chemical Components and Emergency Ambulance Dispatches in Tokyo.

A limited number of studies have investigated the association between short-term exposure to PM2.5 components and morbidity. The present case-crossover study explored the association between exposure to total PM2.5 and its components and emergency ambulance dispatches, which is one of the indicators of morbidity, in the 23 Tokyo wards. Between 2016 and 2018 (mean mass concentrations of total PM2.5 13.5 µg/m3), we obtained data, from the Tokyo Fire Department, on the daily cases of ambulance dispatches. Fine particles were collected at a fixed monitoring site and were analyzed to estimate the daily mean concentrations of carbons and ions. We analyzed 1038301 cases of health-based all-cause ambulance dispatches by using a conditional logistic regression model. The average concentrations of total PM2.5 over one and the previous day were positively associated with the number of ambulance dispatches. In terms of PM2.5 components, the percentage increase per interquartile range (IQR) increase was 0.8% for elemental carbon (IQR = 0.8 µg/m3; 95% CI = 0.3-1.3%), 0.9% for sulfate (2.1 µg/m3; 0.5-1.4%), and 1.1% for ammonium (1.3 µg/m3; 0.4-1.8%) in the PM2.5-adjusted models. This is the first study to find an association between some specific components in PM2.5 and ambulance dispatches.

Excited states of chlorophyll a and b in solution by time-dependent density functional theory.

The ground state and excited state electronic properties of chlorophyll (Chl) a and Chl b in diethyl ether, acetone, and ethanol solutions are investigated using quantum mechanical and molecular mechanical calculations with density functional theory (DFT) and time-dependent DFT (TDDFT). Although the DFT/TDDFT methods are widely used, the electronic structures of molecules, especially large molecules, calculated with these methods are known to be strongly dependent on the functionals and the parameters used in the functionals. Here, we optimize the range-separated parameter, µ, of the CAM-B3LYP functional of Chl a and Chl b to reproduce the experimental excitation energy differences of these Chl molecules in solution. The optimal values of µ for Chl a and Chl b are smaller than the default value of µ and that for bacteriochlorophyll a, indicating the change in the electronic distribution, i.e., an increase in electron delocalization, within the molecule. We find that the electronic distribution of Chl b with an extra formyl group is different from that of Chl a. We also find that the polarity of the solution and hydrogen bond cause the decrease in the excitation energies and the increase in the widths of excitation energy distributions of Chl a and Chl b. The present results are expected to be useful for understanding the electronic properties of each pigment molecule in a local heterogeneous environment, which will play an important role in the excitation energy transfer in light-harvesting complex II.

Hybrid Monte Carlo method with potential scaling for sampling from the canonical multimodal distribution and imitating the relaxation process.

Hybrid methods that combine molecular dynamics methods capable of analyzing dynamics with Monte Carlo (MC) methods that can efficiently treat thermodynamically stable states are valuable for understanding complex chemical processes in which an equilibrium state is reached through many elementary processes. The hybrid MC (HMC) method is one such promising method; however, it often fails to sample configurations properly from the canonical multimodal distribution due to the rugged potential energy surfaces. In this paper, we extend the HMC method to overcome this difficulty. The new method, which is termed potential scaling HMC (PS-HMC), makes use of an artificially modulated trajectory to propose a new configuration. The trajectory is generated from Hamilton's equations, but the potential energy surface is scaled to be gradually flattened and then recovered to the original surface, which facilitates barrier-crossing processes. We apply the PS-HMC method to three kinds of molecular processes: the thermal motion of argon particles, butane isomerization, and an atom transfer chemical reaction. These applications demonstrate that the PS-HMC method is capable of correctly constructing the canonical ensemble with a multimodal distribution. The sampling efficiency and accepted trajectories are examined to clarify the features of the PS-HMC method. Despite the potential scaling, many reactive atom transfer trajectories (elementary processes) pass through the vicinity of the minimum energy path. Furthermore, we demonstrate that the method can properly imitate the relaxation process owing to the inherent configurational continuity. By comparing the PS-HMC method with other relevant methods, we can conclude that the new method is a unique approach for studying both the dynamic and thermodynamic aspects of chemical processes.

Duration of Infectious Virus Shedding by SARS-CoV-2 Omicron Variant-Infected Vaccinees.

To determine virus shedding duration, we examined clinical samples collected from the upper respiratory tracts of persons infected with severe acute respiratory syndrome coronavirus 2 Omicron variant in Japan during November 29-December 18, 2021. Vaccinees with mild or asymptomatic infection shed infectious virus 6-9 days after onset or diagnosis, even after symptom resolution.

Vaccination-infection interval determines cross-neutralization potency to SARS-CoV-2 Omicron after breakthrough infection by other variants.

Background: The immune profile against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has dramatically diversified due to a complex combination of exposure to vaccines and infection by various lineages/variants, likely generating a heterogeneity in protective immunity in a given population. To further complicate this, the Omicron variant, with numerous spike mutations, has emerged. These circumstances have created the need to assess the potential of immune evasion by Omicron in individuals with various immune histories. Methods: The neutralization susceptibility of the variants, including Omicron and their ancestors, was comparably assessed using a panel of plasma/serum derived from individuals with divergent immune histories. Blood samples were collected from either mRNA vaccinees or from those who suffered from breakthrough infections of Alpha/Delta with multiple time intervals following vaccination. Findings: Omicron was highly resistant to neutralization in fully vaccinated individuals without a history of breakthrough infections. In contrast, robust cross-neutralization against Omicron was induced in vaccinees that experienced breakthrough infections. The time interval between vaccination and infection, rather than the variant types of infection, was significantly correlated with the magnitude and potency of Omicron-neutralizing antibodies. Conclusions: Immune histories with breakthrough infections can overcome the resistance to infection by Omicron, with the vaccination-infection interval being the key determinant of the magnitude and breadth of neutralization. The diverse exposure history in each individual warrants a tailored and cautious approach to understanding population immunity against Omicron and future variants. Funding: This study was supported by grants from the Japan Agency for Medical Research and Development (AMED).

Multimeric structure enables the acceleration of KaiB-KaiC complex formation induced by ADP/ATP exchange inhibition.

Circadian clocks tick a rhythm with a nearly 24-hour period in a variety of organisms. In the clock proteins of cyanobacteria, KaiA, KaiB, and KaiC, known as a minimum circadian clock, the slow KaiB-KaiC complex formation is essential in determining the clock period. This complex formation, occurring when the C1 domain of KaiC hexamer binds ADP molecules produced by the ATPase activity of C1, is considered to be promoted by accumulating ADP molecules in C1 through inhibiting the ADP/ATP exchange (ADP release) rather than activating the ATP hydrolysis (ADP production). Significantly, this ADP/ATP exchange inhibition accelerates the complex formation together with its promotion, implying a potential role in the period robustness under environmental perturbations. However, the molecular mechanism of this simultaneous promotion and acceleration remains elusive because inhibition of a backward process generally slows down the whole process. In this article, to investigate the mechanism, we build several reaction models of the complex formation with the pre-binding process concerning the ATPase activity. In these models, six KaiB monomers cooperatively and rapidly bind to C1 when C1 binds ADP molecules more than a given threshold while stabilizing the binding-competent conformation of C1. Through comparison among the models proposed here, we then extract three requirements for the simultaneous promotion and acceleration: the stabilization of the binding-competent C1 by KaiB binding, slow ADP/ATP exchange in the binding-competent C1, and relatively fast ADP/ATP exchange occurring in the binding-incompetent C1 in the presence of KaiB. The last two requirements oblige KaiC to form a multimer. Moreover, as a natural consequence, the present models can also explain why the binding of KaiB to C1 reduces the ATPase activity of C1.

Two Cases of Breakthrough Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infections Caused by the Omicron Variant (B.1.1.529 Lineage) in International Travelers to Japan.

In November 2021, the World Health Organization designated a new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant of concern, Omicron (PANGO lineage B.1.1.529). We report on the first 2 cases of breakthrough coronavirus disease 2019 (COVID-19) caused by Omicron in Japan among international travelers returning from the country with undetected infection. The spread of infection by Omicron were considered.

A Case for Electron-Astrophysics.

The smallest characteristic scales, at which electron dynamics determines the plasma behaviour, are the next frontier in space and astrophysical plasma research. The analysis of astrophysical processes at these scales lies at the heart of the research theme of electron-astrophysics. Electron scales are the ultimate bottleneck for dissipation of plasma turbulence, which is a fundamental process not understood in the electron-kinetic regime. In addition, plasma electrons often play an important role for the spatial transfer of thermal energy due to the high heat flux associated with their velocity distribution. The regulation of this electron heat flux is likewise not understood. By focussing on these and other fundamental electron processes, the research theme of electron-astrophysics links outstanding science questions of great importance to the fields of space physics, astrophysics, and laboratory plasma physics. In this White Paper, submitted to ESA in response to the Voyage 2050 call, we review a selection of these outstanding questions, discuss their importance, and present a roadmap for answering them through novel space-mission concepts.

Exposure to chemical components of fine particulate matter and ozone, and placenta-mediated pregnancy complications in Tokyo: a register-based study.

BACKGROUND: Maternal exposure to fine particulate matter (PM2.5) was associated with pregnancy complications. However, we still lack comprehensive evidence regarding which specific chemical components of PM2.5 are more harmful for maternal and foetal health. OBJECTIVE: We focused on exposure over the first trimester (0-13 weeks of gestation), which includes the early placentation period, and investigated whether PM2.5 and its components were associated with placenta-mediated pregnancy complications (combined outcome of small for gestational age, preeclampsia, placental abruption, and stillbirth). METHODS: From 2013 to 2015, we obtained information, from the Japan Perinatal Registry Network database, on 83,454 women who delivered singleton infants within 23 Tokyo wards (≈627 km2). Using daily filter sampling of PM2.5 at one monitoring location, we analysed carbon and ion components, and assigned the first trimester average of the respective pollutant concentrations to each woman. RESULTS: The ORs of placenta-mediated pregnancy complications were 1.14 (95% CI = 1.08-1.22) per 0.51 µg/m3 (interquartile range) increase of organic carbon and 1.11 (1.03-1.18) per 0.06 µg/m3 increase of sodium. Organic carbon was also associated with four individual complications. There was no association between ozone and outcome. SIGNIFICANCE: There were specific components of PM2.5 that have adverse effects on maternal and foetal health.