Search

Abstract The platelet-derived growth factor (PDGF) family contributes to the progression of steatohepatitis; however, changes in and the characteristics of isoform-specific expression remain unclear. Since diabetes is a major driver of metabolic dysfunction-associated steatohepatitis (MASH), we characterized the mouse model of diabetic MASH (dMASH) by focusing on PDGF signaling. Pdgfa-d expression was markedly higher in hepatic stellate cells among flow-sorted cells in control mice and also increased in dMASH. In contrast, a reanalysis of human single-cell RNA-Seq data showed the distinct distribution of each PDGF isoform with disease progression. Furthermore, inflammation and fibrosis in the liver were less severe in diabetic MASH using tamoxifen-induced PDGF receptor β (PDGFRβ)-deficient mice (KO) than in control dMASH using floxed mice (FL) at 12 weeks old. Despite the absence of tumors, the expression of tumor-related genes was lower in KO than in FL. Tumorigenesis was significantly lower in 20-week-old KO. An Ingenuity Pathway Analysis of differentially expressed miRNA between FL and KO identified functional networks associated with hepatotoxicity and cancer. Therefore, PDGFRβ signals play important roles in the progression of steatohepatitis and tumorigenesis in MASH, with the modulation of miRNA expression posited as a potential underlying mechanism.

Abstract Estimation of a species sensitivity distribution (SSD) by fitting a statistical distribution to ecotoxicity data is a promising approach to deriving “safe” concentrations for microplastics. However, most existing SSDs do not quantitatively consider the diverse characteristics of microplastics, such as particle size and shape. To address this issue, based on 38 mass-based chronic no observed effect concentrations (NOECs) obtained from a recently created database, we estimated SSDs that quantitatively consider the influences of three types of microplastic characteristics (particle length, shape, and polymer type) and habitat of the test species (freshwater vs. marine) by using Bayesian modeling. We selected the best SSD model among all possible models using the widely applicable information criterion. The best SSD model included particle length (range: 0.05–280 μm) and a binary dummy variable corresponding to the fiber shape. Lower chronic NOECs were associated with decreasing particle size and with toxicity tests that included fibers in this model. Combined with the fact that the null model (i.e., an SSD model with no predictor variable) was ranked 27th among the 64 candidate SSD models, our results support the need to incorporate particle characteristics such as length and shape (e.g., fiber) into estimations of SSDs for microplastics. The medians of the hazardous concentration of 5% of species (HC5) for microplastic spheres and fragments, estimated by the posterior distributions of individual parameters in the best SSD model, ranged from 0.02 to 2 µg/L, depending on the particle length (0.1–100 μm). For microplastic fibers, the HC5 values were estimated to be approximately 100 times lower than those for microplastic spheres and fragments with the same particle length. However, the 95% Bayesian credible intervals for HC5 estimates for fibers were considerable, expanded by up to five orders of magnitude. Despite many remaining challenges, the Bayesian SSD modeling utilized in this study provides unique opportunities to simultaneously investigate the influences of multiple microplastic characteristics on the NOECs of multiple species, which would otherwise be difficult to discern.

Species sensitivity distributions (SSDs) estimated by fitting a statistical distribution to ecotoxicity data are indispensable tools used to derive the hazardous concentration for 5 % of species (HC5) and thereby a predicted no-effect concentration in environmental risk assessment. Whereas various statistical distributions are available for SSD estimation, the fundamental question of which statistical distribution should be used has received limited systematic analysis. We aimed to address this knowledge gap by applying four frequently used statistical distributions (log-normal, log-logistic, Burr type III, and Weibull distributions) to acute and chronic SSD estimation using aquatic toxicity data for 191 and 31 chemicals, respectively. Based on the differences in the corrected Akaike’s information criterion (AICc) as well as visual inspection of the fitting of the lower tails of SSD curves, the log-normal SSD was generally better or equally good for the majority of chemicals examined. Together with the fact that the ratios of HC5 values of other alternative SSDs to those of log-normal SSDs generally fell within the range 0.1–10, our findings indicate that the log-normal distribution can be a reasonable first candidate for SSD derivation, which does not contest the existing widespread use of log-normal SSDs.

We analyzed the temporal changes in water quality variables (pH and concentrations of Fe and As) of mine drainages and downstream rivers at the Shojin-gawa Mine in Hokkaido, Japan, based on water quality monitoring data from 1992 to 2020. We also examined the correlations between mine drainages and river waters for these three water quality variables. With some exceptions (e.g., increasing trends in pH for mine drainages in the Shojin-gawa pit area), we found no trend of improvement in the three water quality variables over the studied period in most of the mine drainages and river waters. In addition, water quality variables at the most downstream study site, Orito-gawa A (the target site for achieving environmental water quality standards), showed higher correlations (r > 0.5) with those at the most downstream site of the Amemasu River affected by mine drainages from the Amemasu-gawa pit area than those at the most downstream site of the Shojin River affected by mine drainages from the Shojin-gawa pit area. Fe and As concentrations at the most downstream site of the Amemasu River were largely influenced by mine drainages from the Amemasu-gawa pit area (i.e., Taisei and Chugiri pits). These results highlight the importance of monitoring water quality at the most downstream site of the Amemasu River to assess the influence of mine drainages on the changes in water quality at site Orito-gawa A. Additionally, we observed relatively high correlations between electric conductivity (EC) and concentrations of several elements at the most downstream site of the Amemasu River. Therefore, in-situ measurement of EC may be beneficial for performing screening-level assessments or low-cost monitoring of water quality when considering and implementing sustainable water quality monitoring methods over the long term.

Improving sewage disposal rates is an important policy for maintaining the health of aquatic organisms in river environments. In Japan, the rate is not yet 100 %. Two measures are necessary to eliminate the discharge of untreated greywater: (1) increase the number of households connected to sewage lines in areas with sewage systems, and (2) replace single-type household onsite wastewater treatment systems (OWTSs) with combined-type systems. To estimate the effect of improving the disposal rate on river water quality, we developed a hydrology-based organic pollution assessment model with a gridded spatial resolution of 250 m to estimate the biochemical oxygen demand (BOD) in rivers in Gunma Prefecture, Japan. We considered three scenarios based on the sewage disposal rate of 70.5 % in 2015. In Scenario A, the disposal rate is increased to 75.2 % in 2030 by increasing the connection rate to sewage lines. In Scenario B, the rate is increased to 88.2 % in 2030 through additional progress in converting from single-to combined-type OWTSs. In Scenario C, the rate reaches 100 % by 2040. The ecological status of rivers was evaluated using taxon richness of Ephemeroptera, Plecoptera, and Trichoptera estimated from its reported relationship to BOD. The number of sites in Gunma Prefecture polluted by organic waste classified as III (poor) and IV (very poor) was estimated to be 1610 under the present state (2015) and decreased to 1212 (25 % reduction) in Scenario A, 619 (62 % reduction) in Scenario B, and 50 (97 % reduction) in Scenario C, with the improvements mainly in small branch rivers. The effects of improved disposal rates were mainly evident in areas with relative high population densities using single-type OWTSs outside of areas with a sewage system, and measures taken in these areas were shown to be effective.

Ecological impacts of chemicals such as metal mixtures in the field are predicted by one of two approaches: component-based and whole-mixture approaches. Knowledge about how to relate results of these approaches to field effect levels is limited. We aimed to examine the ability of two methods to discriminate field effect levels: (1) a component-based approach that calculates a cumulative criterion unit (CCU) equal to the sum of the ratios of four trace-metal concentrations (Cd, Cu, Zn, and Pb) to the corresponding US EPA hardness-adjusted water quality criterion, and (2) a whole-mixture approach that employs three ambient toxicity levels based on acute and chronic toxicity tests with cladocerans. To assess field effect levels, we used data from benthic macroinvertebrate surveys conducted at 26 sites, including 13 metal-contaminated sites, in four river basins across Japan. Based on decreases in mayfly richness and abundances of two metal-sensitive mayfly families, we defined four field effect levels 0–3: (0) no significant effect; (1) a significant decrease in ephemerellid and/or heptageniid mayfly abundance; (2) a significant decrease in mayfly richness; and (3) no mayflies or a few baetid mayfly species present. Sites with CCU values of ∼5–10 were assigned to either field effect level 1 or 2, while a site with a CCU value of 27 was assigned to field effect level 3. Sites with significant chronic toxicity to cladocerans (ambient toxicity level 1) were assigned to field effect level 1 or 2, whereas those with significant acute and chronic toxicity (ambient toxicity level 2) were assigned to field effect level 2 or 3. CCU values and ambient toxicity levels were both significantly correlated with field effect levels. These results provide encouraging evidence that field effect levels such as losses of species richness can be approximately discriminated by CCU values and ambient toxicity levels.

For a total of 80 legacy mines in Japan, by assuming that untreated mine drainages were discharged and that metal loadings from sources other than mine drainage were negligibly small, we estimated seven element concentrations (Cd, Pb, As, Cu, Zn, Fe, and Mn) at water quality monitoring (WQM) river sites closest to individual mines (hereinafter referred to as the closest WQM sites) based on a simple dilution approach. In addition, for zinc as an example, the concentrations at the closest WQM sites were estimated by taking account into estimated zinc loadings from sources other than mine drainage. Results of the former analysis showed that the concentrations of all four elements (Cd, Pb, As, and Zn) at the closest WQM sites were predicted to be below Japanese environmental water quality standards in 50% of the legacy mines analyzed, which is not a small percentage. However, the result of the latter analysis showed that the contributions of treated mine drainages to the total loadings of zinc at the closest WQM sites were less than 50% in approximately 88% of the legacy mines analyzed. This result suggests that metal loadings from sources other than mine drainages at the closest WQM sites are not trivial in many legacy mines. Even if untreated mine drainages were discharged, estimated zinc concentrations in 72% of the WQM sites, where the annual average of measured concentrations of total zinc was below the environmental water quality standard (0.03 mg/L), were still below the standard. Despite a screening-level assessment based on multiple assumptions such as the simple dilution, results of the present study should be valuable for understanding the impact of discharging untreated mine drainages on metal concentrations in rivers receiving those from the legacy mines toward applying the water-quality management that secures the protection of downstream water use.

To use species sensitivity distributions (SSDs) for ecological risk assessment, there are various uncertainties, which require applying assessment factors (AFs) accordingly. This study aims to quantify the uncertainty of estimating statistical distributions. Given a management goal of protecting 95% of species, the concentration that affects 5% of the species (HC5) is estimated. Since the true concentration affecting 5% of the species (population HC5) is unknown, the estimated HC5 is divided by an AF to derive the predicted no-effect concentration (PNEC), which is set as the protection goal, to compensate for the deviation in the estimated HC5 from the population HC5. Although the deviation between these two HC5 values depends on the sample size and the variation in sensitivity (standard deviation of the distribution) among species, there has been little discussion of how to quantify the degree of uncertainty. By assuming that toxicity values are a random sample from a lognormal distribution, we mathematically analyzed the SSD to derive the magnitude of AF needed to achieve a given protection goal (as an example, the protection of 95% of species with a probability of 95%). We successfully derived an equation that explicitly relates the magnitude of AF to the sample size and the variation in species sensitivity, providing a new basis to statistically determine the magnitude of AF for ecological risk assessments.

To identify potential countermeasures for coronavirus disease (COVID-19), we determined the air exchange rates in stationary and moving train cars under various conditions in July, August, and December 2020 in Japan. When the doors were closed, the air exchange rates in both stationary and moving trains increased with increasing area of window-opening (0.23–0.78/h at 0 m2, windows closed to 2.1–10/h at 2.86 m2, fully open). The air exchange rates were one order of magnitude higher when doors were open than when closed. With doors closed, the air exchange rates were higher when the centralized air conditioning (AC) and crossflow fan systems (fan) were on than when off. The air exchange rates in moving trains increased as train speed increased, from 10/h at 20 km/h to 42/h at 57 km/h. Air exchange rates did not differ significantly between empty cars and those filled with 230 mannequins representing commuters. The air exchange rates were lower during aboveground operation than during underground. Assuming that 30–300 passengers travel in a train car for 7–60 min and that the community infection rate is 0.0050–0.30%, we estimated that commuters’ infection risk on trains was reduced by 91–94% when all 12 windows were opened (to a height of 10 cm) and the AC/fan was on compared with that when windows were closed and the AC/fan was off.

Estimation of species sensitivity distributions (SSDs) is a crucial approach to predicting ecological risks and water quality benchmarks, but the amount of data required to implement this approach is a serious constraint on the application of SSDs to chemicals for which there are few or no toxicity data. The development of statistical models to directly estimate the mean and standard deviation (SD) of the logarithms of log-normally distributed SSDs has recently been proposed to overcome this problem. To predict these two parameters, we developed multiple linear regression models that included, in addition to readily obtainable descriptors, the mean and SD of the logarithms of the concentrations that are acutely toxic to one algal, one crustacean, and one fish species, as predictors. We hypothesized that use of the three species’ mean and SD would improve the accuracy of the predicted means and SDs of the logarithms of the SSDs. We derived SSDs for 60 chemicals based on quality-assured acute toxicity data. Forty-five of the chemicals were used for model fitting, and 15 for external validation. Our results supported previous findings that models developed on the basis of only descriptors such as log KOW had limited ability to predict the mean and SD of SSD (e.g., r2 = 0.62 and 0.49, respectively). Inclusion of the three species’ mean and SD, in addition to the descriptors, in the models markedly improved the predictions of the means and SDs of SSDs (e.g., r2 = 0.96 and 0.75, respectively). We conclude that use of the three species’ mean and SD is promising for more accurately estimating an SSD and thus the hazardous concentration for 5% of species in cases where limited ecotoxicity data are available.

A medial collateral ligament (MCL) tear is common in cases of isolated injury or in those combined with anterior cruciate ligament injury. Although conservative treatment for an MCL tear is popular, some cases result in residual instability. Thus, the treatment approach of grade III MCL injury remains controversial. In this Technical Note, we present the technique of arthroscopic primary MCL repair with suture anchor. With this technique, proximal MCL injuries can be repaired with minimal invasion. This technique improves valgus stability and enables early rehabilitation, including range of motion and weight-bearing exercise.

Hypermobile meniscus is known as one of the causes of knee pain and locking or limitation of the range of motion during knee flexion, even when there is no evidence of meniscus tear on magnetic resonance imaging (MRI). Most such cases show excessive hypermobility of the posterior part of the lateral meniscus. This case report presented a rare case of a hypermobile anterior horn of the lateral meniscus. An 18-year-old woman visited our hospital for left knee pain without trauma. Her physical examination showed a limited range of motion and tenderness in the lateral joint space. However, her MRI did not show any abnormalities. After conservative treatment failed, we performed arthroscopic surgery. The arthroscopic evaluation showed no meniscus and no other intraarticular injury. However, the anterior horn of the lateral meniscus was easily translated beyond the lateral condyle by using a probe. Thus, hypermobile anterior horn of the lateral meniscus was diagnosed. The meniscus was stabilized by the outside-in technique. Immediately after surgery, the catching symptom and pain were alleviated. After three-and-a-half months, she returned to work. The Lysholm score improved from 55, preoperatively, to 100, 1-year postoperatively. In conclusion, careful arthroscopic evaluation is essential for the diagnosis of a hypermobile anterior horn of the lateral meniscus. Arthroscopic meniscus stabilization provides a good outcome for hypermobile meniscus.

Prediction of heavy metal bioavailability in intact soil is important to manage soil pollution risks. We developed a regression model for representative Japanese soils to judge their potential vulnerability to cadmium (Cd) pollution. We added four rates of Cd to 17 sample soils to mimic artificial contamination. After aging the contaminated soils, we measured Cd's bioavailability using the diffusive gradients in thin-films (DGT) technique. We then evaluated the relationships between bioavailability of Cd ([CdDGT]) and intact soil properties by statistical analyses. Cation exchange capacity (CEC) and pH emerged as significant factors to explain the cadmium bioavailability in Japanese soils. Specifically, lower CEC and lower pH were associated with higher [CdDGT], which poses a higher risk for soil ecosystems. The correlation between pH and [CdDGT] had a high dependence on [CdAdd], whereas that for CEC did not. Regression analysis also showed that the interaction between intact soil pH and spiked concentration ([CdAdd]) had a significant contribution to [CdDGT]. The regression model developed was rationally supported by a biotic ligand model. This simplified but realistic model would be useful in estimating the vulnerability of representative Japanese soils and determining the risk for Japanese soils in relation to Cd contamination.

This paper proposes a novel seismometer-type absolute displacement sensor aimed at detecting earthquake waves with a large magnitude and long period. However, since the measuring range of the conventional displacement sensor is higher than the natural frequency of itself, it is difficult to detect a low frequency vibration below 1Hz using conventional seismic-type displacement sensors. In order to provide an absolute displacement detection which is capable of lowering the natural frequency and enlarging the detectable amplitude without causing a structural defect, the relative signals of displacement, velocity, and acceleration between a detected object and the auxiliary mass of the sensor are fed back into the sensor. In addition, a phase lag compensation is inserted to adjust phase angles, which are below a frequency lower than 1Hz. Theoretically, this sensor is able to detect a lower frequency range from 0.2Hz to 10Hz and large amplitude with 100 times to the movable range of the sensor. It has been demonstrated by experiments that the developed sensor with a small size and lightweight has a detecting range from 0.2 Hz to 10Hz for absolute displacement and velocity. As an additional advantage, the measurement displacement amplitude has been expanded to about 40dB (100 times) for detecting earthquake waves with large magnitude and long period. As the typical application example of the developed absolute displacement sensor, a seismic wave based on Hachinohe wave is used with well observation results.

Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov-Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities.

The gigantic and long-period earthquake motions were observed in Tokyo, Osaka and other by the East Japan Earthquake of March 11, 2011. Therefore, the super high-rise buildings located in Tokyo were excited by large amplitude with about 1m and long time over 10minite. As the result, the life lines of the super high-rise buildings were took large damages. For corresponding to such an accident, it is important to measure the displacement vibration instantly and take a controlling technology. However, such devices are not yet exist to measure the displacement vibration waves with large magnitude and long period. This paper proposes a novel seismometer-type absolute displacement sensor aimed at detecting earthquake waves with a large magnitude and long period. The seismometer-type absolute displacement sensor is consisted of a sensor body with a moving mass and its supporting springs, feedback control circuits and a third order phase lag compensator. The natural frequency of the sensor body located at 6.4Hz originally is reduced to 0.23Hz using by acceleration feedback mainly and then moving stroke of the moving mass is compressed to 1mm to 1/630mm. Moreover the new natural frequency of 0.23Hz developed by feedback control is sifted to 0.055Hz by the third order phase lag compensator. Therefore the sensor has a measuring range from 0.08Hz to 10Hz, in addition to no drift problems by the use of feedback control way. In this way, the seismometer-type absolute displacement sensor with the amazing ability has been realized to measure the long period over 10 second of earthquake waves. In addition, the large magnitude to measure 630mm is expected, nevertheless a small size with moving stroke of 1mm. So far as we know, such a sensor for measuring absolute displacement is very novel in the world. In this paper the ability of the sensor will be shown by simulation and experiment.