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The magnitude of water vapor content within the near-storm inflow can either support or deter the storm’s upscale growth and maintenance. However, the heterogeneity of the moisture field near storms remains poorly understood because the operational observation network lacks detail. This observational study illustrates that near-storm inflow water vapor environments are both significantly heterogeneous and different than the far-inflow storm environment. This study also depicts the importance of temporal variation of water vapor mixing ratio (WVMR) to instability during the peak tornadic seasons in the U.S. Southeast and Great Plains regions during the Verification of the Origins of Rotation in Tornadoes Experiment Southeast 2018 (VSE18) campaign and the Targeted Observation by Radar and UAS of Supercells (TORUS) campaign, respectively. VSE18 results suggest that the surface processes control WVMR variation significantly in lower levels, with the highest WVMR mainly located near the surface in inflows in the southeast region. In contrast, TORUS results show more vertically homogeneous WVMR profiles and rather uniform water vapor distribution variation occurring in deep, moist stratified inflows in the Great Plains region. Temporal water vapor variations within 5-min periods could lead to over 1000 J kg−1 CAPE changes in both VSE18 and TORUS, which represent significant potential buoyancy perturbations for storms to intensify or decay. These temporal water vapor and instability evolutions of moving storms remain difficult to capture via radiosondes and fixed in situ or profiling instrumentation, yet may exert a strong impact on storm evolution. This study suggests that improving observations of the variability of near-storm inflow moisture can accurately refine a potential severe weather threat. Significance Statement It has long been recognized that better observations of the planetary boundary layer (PBL) inflow near convective storms are needed to improve severe weather forecasting. The current operational networks essentially do not provide profile measurements of the PBL, except for the sparsely spaced 12-hourly sounding network. More frequent geostationary satellite observations do not provide adequately high vertical resolution in the PBL. This study uses airborne lidar profiler measurements to examine moisture in the inflow region of convective storms in the Great Plains and the southeastern United States during their respective tornadic seasons. Rapid PBL water vapor variations on a ∼5 min time scale can lead to CAPE perturbations exceeding 1000 J kg−1, representing significant perturbations that could promote storm intensification or decay. Severe thunderstorms may generate high-impact weather phenomena, such as tornadoes, high winds, hail, and heavy rainfall, which have substantial socioeconomic impacts. Ultimately, by contrasting characteristics of the convective storm inflow in the two regions, this study may lead to a more accurate assessment of severe weather threats.

In this study, all-sky GOES-R ABI infrared radiances at their native resolution are assimilated using an enhanced GSI ensemble Kalman filter (EnKF) data assimilation (DA) system, and the impacts of the data on the analysis and forecast of a mesoscale convective system (MCS) are explored. Results show that all-sky ABI BT data can correctly build up observed storms within the model and effectively remove spurious storms in model background through frequent DA cycles. Both bias and root-mean-squared innovation of the background and analysis are significantly reduced during the DA cycles, and free forecasts are improved when verified subjectively and objectively against observed ABI BTs and independent radar reflectivity observations. A horizontal localization radius of 30 km is found to produce the best results while 5-min DA cycles improve the storm analyses over 15-min cycles, but the differences in forecasts are small. Further analyses show that the clearing of spurious clouds by ABI radiance is correctly accompanied by reduction in moisture through background error cross covariance, but overdrying often occurs, which can cause spurious storm decay in the forecast. The problem is reduced when the ensemble mean of observation prior instead of observation prior of the ensemble mean state is used in the ensemble mean state update equation of EnKF. The significant difference between the two ways that the ensemble mean of observation prior is calculated when the observational operator is very nonlinear has not been recognized in earlier cloudy radiance DA studies. Significance Statement Satellite observations in cloudy regions are not used in most current operational weather prediction systems due to complex nonlinear relations between satellite-observed quantities, the radiances, and model state in such regions. The models also must predict clouds reasonably well for cloudy observations to be effectively assimilated. The latest NOAA geostationary satellites can provide radiance observations at high spatial and temporal resolutions and such data in both cloudy- and clear-air regions are assimilated using an advanced data assimilation method into a model that explicitly represents convection. Forecasts up to 4 h are improved by the assimilation while several issues associated with the assimilation are discussed. The study contributes to the eventual use of all-sky satellite radiance data in operational models.

SummaryAs one of the largest emitters in the world, the oil and gas industry needs to apply more effort to greenhouse gas (GHG) reduction. Methane, as a potent GHG, could largely determine whether natural gas could serve as a bridging energy toward a sustainable future. In the past decade, oil and gas companies in China have significantly enhanced casing gas recovery and reduced large volume flaring (>2×104 m3/d). However, the remaining low- to mid-volume flaring gas was left for further recovery. Shale gas production in China has met a surge in the number of drilling wells. Those new wells were characterized by a relatively low gas production rate (

A time–space shift method is developed for relocating model-predicted tornado vortices to radar-observed locations to improve the model initial conditions and subsequent predictions of tornadoes. The method consists of the following three steps. (i) Use the vortex center location estimated from radar observations to sample the best ensemble member from tornado-resolving ensemble predictions. Here, the best member is defined in terms of the predicted vortex center track that has a closest point, say at the time of t = t*, to the estimated vortex center at the initial time t0 (when the tornado vortex signature is first detected in radar observations). (ii) Create a time-shifted field from the best ensemble member in which the field within a circular area of about 10-km radius around the vortex center is taken from t = t*, while the field outside this circular area is transformed smoothly via temporal interpolation to the best ensemble member at t0. (iii) Create a time–space-shifted field in which the above time-shifted circular area is further shifted horizontally to co-center with the estimated vortex center at t0, while the field outside this circular area is transformed smoothly via spatial interpolation to the non-shifted field at t0 from the best ensemble member. The method is applied to the 20 May 2013 Oklahoma Newcastle–Moore tornado case, and is shown to be very effective in improving the tornado track and intensity predictions. Significance Statement The time–space shift method developed in this paper can smoothly relocate tornado vortices in model-predicted fields to match radar-observed locations. The method is found to be very effective in improving not only model initial condition but also the subsequent tornado track and intensity predictions. The method is also not sensitive to small errors in radar-estimated vortex center location at the initial time. The method should be useful for future real-time or even operational applications although further tests and improvements are needed (and are planned).

Using social exchange theory, we proposed a moderated mediation model to explore the relationship between unemployment risk perception and employee knowledge hiding under the disruption of artificial intelligence transformation. We conducted an empirical analysis of data from 274 respondents who completed a two-stage survey with an interval of about 2 weeks. The results were as follows: First, unemployment risk perception was positively related to employee knowledge hiding. Second, psychological contract breach mediated the relationship between unemployment risk perception and employee knowledge hiding. Third, mindfulness negatively moderated the relationship between psychological contract breach and employee knowledge hiding. Fourth, mindfulness negatively moderated the strength of the mediated relationship between unemployment risk perception and employee knowledge hiding via psychological contract breach. The research conclusions can help companies formulate policies to guide employees to actively share knowledge in artificial intelligence transformation contexts.

A climatology of significant tornadoes [SIGTOR, tornadoes rated (E)F2+ on the (enhanced) Fujita scale] within China and in three subregions, including northern, central, and southern China, is first presented for the period 1980–2016. In total, 129 SIGTOR are recorded in China, with an average of 3.5 per year. The tornado inflow environments of the south-central and southeast regions of the United States (USC and USSE) are compared with those of China and its subregions based on sounding-derived parameters including shear, storm-relative helicity, convective available potential energy (CAPE), lifting condensation level (LCL), etc. Soundings are extracted from the ERA5 reanalysis dataset. The results confirm that the SIGTOR in USSE are characterized by high shear, low CAPE, and low LCL whereas those in USC are characterized by moderate-to-high shear, high CAPE, and high LCL. The thermodynamic conditions of tornadic cases are favorable for China, with moderate-to-high CAPE and low-to-moderate LCL, but their kinematic conditions are much less favorable than in the United States, a fact that is believed to be primarily responsible for the lower tornado frequency and intensity in China. The high CAPE in China is due mostly to high humidity. For three subregions in China, the central China cases account for 60% of total samples, and its environmental features are similar to those of China. The average shear with northern China cases is stronger than that with the other two subregions, and the midlayer is relatively dry. The southern China SIGTOR have the most conducive humidity conditions, but the CAPE and shear there are the lowest. The northern, central, and southern China environments can be considered as representative of midlatitude, subtropical, and tropical regions. Significance Statement We document the climatological characteristics of significant tornadoes (SIGTOR) within China and compare the inflow environments of SIGTOR in China and its subregions with those in the U.S. central and southeastern regions. The availability of hourly high-resolution ERA5 data makes the environments based on extracted proximity soundings much more accurate than possible with earlier reanalyses. The environmental characteristics show systematic differences in the tornado environments of different regions of China and the United States and suggest different roles played by thermodynamic and kinematic conditions for tornado formation. Overall, the environmental differences are consistent with the resulting frequency and intensities of SIGTOR. The findings are helpful toward improving tornado forecasting and warning or even understanding of potential impacts of climate change on SIGTOR, especially in China, where such studies are rarer.

During the winter of 2020/21 an ensemble of FV3-LAM forecasts was produced over the contiguous United States for the Winter Weather Experiment using five physics suites. These forecasts are evaluated with the goal of optimizing physics parameterizations within the future operational Rapid Refresh Forecast System (RRFS) in the Unified Forecast System (UFS) realm and for selecting suitable physics suites for a multiphysics RRFS ensemble. The five physics suites have different combinations of land surface models (LSMs), planetary boundary layer (PBL) parameterizations, and surface layer schemes, chosen from those used in current and possible future operational systems and likely to be supported in the operational UFS. Full-season evaluation reveals a persistent near-surface cold bias in the U.S. Northeast from one suite and a nighttime warm bias in the southern Great Plains in another suite, while other suites have smaller biases. A representative case is chosen to diagnose the cause for each of these biases using sensitivity simulations with different physics combinations or modified parameters and verified with additional mesonet observations. The cold bias in the Northeast is attributed to aspects of the Noah-MP LSM over snow cover, where Noah-MP simulates lower soil water content, and thus lower thermal conductivity than other LSMs, leading to less upward ground heat flux during nighttime and consequently lower surface temperature. The nighttime warm bias found in the southern Great Plains is attributed to overestimation of vertical mixing in the K-profile-based eddy-diffusivity mass-flux (K-EDMF) PBL scheme and insufficient land–atmospheric coupling from the GFS surface layer scheme over short vegetation. A few key parameters driving these systematic biases are identified.

Thin-film-composite (TFC) nanofiltration membranes have found wide uses in environment remediation and industrial separation. There is a growing trend to avoid the use of organic solvents and toxic chemicals during membrane fabrication. Therefore, the aqueous fabrication of TFC membranes receives considerable interest as a green and sustainable process. However, it remains challenging to construct a defect-free and ultrathin film in a homogeneous aqueous phase without the assistance of an interface. The contra-diffusion process provides a special "interface" to confine the film formation within a narrow space by regulating the competition between precursor diffusion and interfacial reactions. Herein, Fe

Integrating metal-organic framework (MOF)-covalent organic framework (COF) allows versatile engineering of hybrid materials with properties superior to pristine components, especially COFs suffered from aggregation-caused quenching (ACQ), unlocking more possibilities to improve the luminescence of COFs. In this work, we prepared various MOF@COF composites with different COF layer thicknesses, in which stable UiO-66-NH

To help inform physics configuration decisions and help design and optimize a multi-physics Rapid Refresh Forecasting System (RRFS) ensemble to be used operationally by the National Weather Service, five FV3-LAM-based convection allowing forecasts were run on 35 cases between October 2020 and March 2021. These forecasts used ∼3-km grid spacing on a CONUS domain with physics configurations including Thompson, NSSL, and Ferrier–Aligo microphysics schemes, Noah, RUC, and NoahMP land surface models, and MYNN-EDMF, K-EDMF, and TKE-EDMF PBL schemes. All forecasts were initialized from the 0000 UTC GFS analysis and run for 84 h. Also, a subset of 8 cases were run with 15 combinations of physics options, also including the Morrison–Gettelman microphysics and Shin–Hong PBL schemes, to help attribute behaviors to individual schemes and isolate the main contributors of forecast errors. Evaluations of both sets of forecasts find that the CONUS-wide 24-h precipitation > 1 mm is positively biased across all five forecasts. NSSL microphysics displays a low bias in QPF along the Gulf Coast. Analyses show that it produces smaller raindrops prone to evaporation. Additionally, TKE-EDMF PBL in combination with Thompson microphysics displays a positive bias in precipitation over the Great Lakes and in the ocean near Florida due to higher latent heat fluxes calculated over water. Furthermore, the K-EDMF PBL scheme produces temperature errors that result in a negative bias in snowfall over the southern Mountain West. Finally, recommendations for which physics schemes to use in future suites and the RRFS ensemble are discussed.

In a prior study, GOES-R Geostationary Lightning Mapper (GLM) flash extent density (FED) data were assimilated using ensemble Kalman filter into a convection-allowing model for a mesoscale convective system (MCS) and a supercell storm. The FED observation operator based on a linear relation with column graupel mass was tuned by multiplying a factor to avoid large FED forecast bias. In this study, new observation operators are developed by fitting a third-order polynomial to GLM FED observations and the corresponding FED forecasts of graupel mass of the MCS and/or supercell cases. The new operators are used to assimilate the FED data for both cases, in three sets of experiments called MCSFit, SupercellFit, and CombinedFit, and their performances are compared with the prior results using the linear operator and with a reference simulation assimilating no FED data. The new nonlinear operators reduce the frequency biases (root-mean-square innovations) in the 0–4-h forecasts of the FED (radar reflectivity) relative to the results using the linear operator for both storm cases. The operator obtained by fitting data from the same case performs slightly better than fitting to data from the other case, while the operator obtained by fitting forecasts of both cases produce intermediate but still very similar results, and the latter is considered more general. In practice, a more general operator can be developed by fitting data from more cases. Significance Statement Prior studies found that assimilation of satellite lightning observation can benefit storm forecasts for up to 4 h. A linear lightning observation operator originally developed for assimilating pseudo-satellite lightning observations was tuned earlier through sensitivity experiments when assimilating real lightning data. However, the linear relation does not fit the model and observational data well and significant bias can exist. This study develops new lightning observation operators by fitting a high-order polynomial to satellite lightning observations and model-predicted quantities that directly relate to lightning. The new operator was found to reduce the frequency biases and root-mean-square innovations for lightning and radar reflectivity forecasts, respectively, up to several hours relative to the linear operator. The methodology can be applied to larger data samples to obtain a more general operator for use in operational data assimilation systems.

Intermaxillary fixation screw (IMFS) implantation is a common procedure in orthognathic surgery (OGS) performed to the temporary maxillary-mandibular fixation and stable bite relationships. The study aims to assess the accuracy of IMFS implantation with a digital guide to reduce the occurrence of root damage.This prospective study involved 40 patients undergoing OGS at the Affiliated Hospital of Qingdao University from August 2017 to May 2021. The patients were randomly divided into two groups according to whether the IMFS implantation was with or without digital guide (20 patients in the experimental group and 20 controls). The digital guides used in the experimental group were designed according to a virtual implantation plan and printed using stereolithography. In the control group, IMFSs were directly implanted by a surgeon based on clinical experience. Postoperatively, cone-beam computed tomography was performed to compare root proximity of IMFSs between the two groups and verify the accuracy of IMFS placement.In the experimental group, there was no case of root damage, the incidence of the periodontal ligament (PDL) injured was 22.1%, and 77.9% IMFSs were placed without contacting adjacent anatomic structures. In the control group, the incidence of root damage had been up to 20.8%, 31.7% IMFSs injured the PDL, and only 47.5% IMFSs were placed between the roots (P 0.001).IMFSs can be placed more accurately with surgical guides, reducing the incidence of root and PDL damages.

BackgroundInfluenza infection causes a huge burden every year, affecting approximately 8% of adults and approximately 25% of children and resulting in approximately 400,000 respiratory deaths worldwide. However, based on the number of reported influenza cases, the actual prevalence of influenza may be greatly underestimated. The purpose of this study was to estimate the incidence rate of influenza and determine the true epidemiological characteristics of this virus.MethodsThe number of influenza cases and the prevalence of ILIs among outpatients in Zhejiang Province were obtained from the China Disease Control and Prevention Information System. Specimens were sampled from some cases and sent to laboratories for influenza nucleic acid testing. Random forest was used to establish an influenza estimation model based on the influenza-positive rate and the percentage of ILIs among outpatients. Furthermore, the moving epidemic method (MEM) was applied to calculate the epidemic threshold for different intensity levels. Joinpoint regression analysis was used to identify the annual change in influenza incidence. The seasonal trends of influenza were detected by wavelet analysis.ResultsFrom 2009 to 2021, a total of 990,016 influenza cases and 8 deaths were reported in Zhejiang Province. The numbers of estimated influenza cases from 2009 to 2018 were 743,449, 47,635, 89,026, 132,647, 69,218, 190,099, 204,606, 190,763, 267,168 and 364,809, respectively. The total number of estimated influenza cases is 12.11 times the number of reported cases. The APC of the estimated annual incidence rate was 23.33 (95% CI: 13.2 to 34.4) from 2011 to 2019, indicating a constant increasing trend. The intensity levels of the estimated incidence from the epidemic threshold to the very high-intensity threshold were 18.94 cases per 100,000, 24.14 cases per 100,000, 141.55 cases per 100,000, and 309.34 cases per 100,000, respectively. From the first week of 2009 to the 39th week of 2022, there were a total of 81 weeks of epidemics: the epidemic period reached a high intensity in 2 weeks, the epidemic period was at a moderate intensity in 75 weeks, and the epidemic period was at a low intensity in 2 weeks. The average power was significant on the 1-year scale, semiannual scale, and 115-week scale, and the average power of the first two cycles was significantly higher than that of the other cycles. In the period from the 20th week to the 35th week, the Pearson correlation coefficients between the time series of influenza onset and the positive rate of pathogens, including A(H3N2), A (H1N1)pdm2009, B(Victoria) and B(Yamagata), were − 0.089 (p = 0.021), 0.497 (p p = 0.109) and − 0.084 (p = 0.029), respectively. In the period from the 36th week of the first year to the 19th week of the next year, the Pearson correlation coefficients between the time series of influenza onset and the positive rate of pathogens, including A(H3N2), A (H1N1)pdm2009, B(Victoria) and B(Yamagata), were 0.516 (p p p p ConclusionThe disease burden of influenza has been seriously underestimated in the past. An appropriate method for estimating the incidence rate of influenza may be to comprehensively consider the influenza-positive rate as well as the percentage of ILIs among outpatients. The intensity level of the estimated incidence from the epidemic threshold to the very high-intensity threshold was calculated, thus yielding a quantitative standard for judging the influenza prevalence level in the future. The incidence of influenza showed semi-annual peaks in Zhejiang Province, including a main peak from December to January of the next year followed by a peak in summer. Furthermore, the driving factors of the influenza peaks were preliminarily explored. While the peak in summer was mainly driven by pathogens of A(H3N2), the peak in winter was alternately driven by various pathogens. Our research suggests that the government urgently needs to address barriers to vaccination and actively promote vaccines through primary care providers.

Peruvian Andes region has been proven in multiple studies to be one of a few regions have poor performance of many global precipitation estimations, due to its complex terrain and extreme interruption of atmospheric movement by the Andes mountain. This study provides an evaluation over two Peruvian local precipitation products PISCO and RAIN4PE, along with a regional dynamic downscaled WRF model simulation, and GPM-IMERG. The precipitation products were evaluated against local rain gauge data and used as the forcing data for CREST-VEC model to test the uncertainties of the precipitation products in a extremely dry region in Peru. This study readdress the accuracy issue of precipitation products in the Peruvian Andes region, and highlights the importance of using WRF modeling simulation to ‘fill-the-blank’ of heterogenous rain gauge distribution, when remote-sensing technologies fail to perform in this area.

The pressure-induced color change in the nitrogen-doped lutetium hydride has triggered extensive discussions about the underlying physics. Here, we study the optical response of LuH$_{2 \pm x}$N$_{y}$ in a broad frequency range at ambient pressure and its evolution with pressure in the visible spectral range. The broad-band optical spectra at ambient pressure reveal a Drude component associated with intra-band electronic transitions and two Lorentz components (L1 and L2) arising from inter-band electronic transitions. The application of pressure causes a spectral weight transfer from L1 to the Drude component, leading to a blue shift of the plasma edge in the reflectivity spectrum alongside a reduction of the high-frequency reflectivity. Our results suggest that the pressure-induced color change in LuH$_{2 \pm x}$N$_{y}$ is closely related to the transformation between intra- and inter-band electronic transitions, providing new insights into the mechanism of the pressure-induced color change in LuH$_{2 \pm x}$N$_{y}$., 20 pages, 4 figures. Comments are welcome and appreciated

Constructed wetland–microbial fuel cell coupling systems (CW–MFCs) have received significant academic interest in the last decade mainly due to the promotion of MFCs in relation to pollutants’ degradation in CWs. Firstly, we investigated the effect of hydraulic retention time (HRT) and electrode configuration on the flow field characteristics of CW–MFCs using graphite rods and plates as electrodes, as well as the optimization of electrode configuration using computational fluid dynamics (CFD) numerical simulation. The results showed that: (1) the apparent HRT was the most influential and decisive factor, with a contribution of over 90% for the average HRT of CW–MFCs; (2) anode spacing was the most influential factor for the hydraulic performance of CW–MFCs, with contributions of over 50% for water flow divergence and hydraulic efficiency (λ) and over 45% for effective volume ratio (e); (3) anode size was significant for e and λ, with a contribution of over 20%; (4) cathode position and cathode size had no statistically significant effect on the hydraulic performance of CW–MFCs. It was mainly through the blocking of water flows, flows around, compressing water flow channels and boundary layer separation that the MFC electrodes influenced the hydraulic characteristics of the flow field in CW–MFCs. Optimizing the flow field by optimizing the electrode configuration helped to facilitate electricity generation and pollutants’ removal in CW–MFCs. This study offers a scientific reference for improving the hydraulic performance of CW–MFCs, and it also provides a new research perspective for improving the wastewater treatment and electricity production performance of CW–MFCs.

The Center for Analysis and Prediction of Storms has recently developed capabilities to directly assimilate radar reflectivity and radial velocity data within the GSI-based ensemble Kalman filter (EnKF) and hybrid ensemble three-dimensional variational (En3DVar) system for initializing convective-scale forecasts. To assess the performance of EnKF and hybrid En3DVar with different hybrid weights (with 100%, 20%, and 0% of static background error covariance corresponding to pure 3DVar, hybrid En3DVar, and pure En3DVar) for assimilating radar data in a Warn-on-Forecast framework, a set of data assimilation and forecast experiments using the WRF Model are conducted for six convective storm cases of May 2017. Using an object-based verification approach, forecast objects of composite reflectivity and 30-min updraft helicity swaths are verified against reflectivity and rotation track objects in Multi-Radar Multi-Sensor data on space and time scales typical of National Weather Service warnings. Forecasts initialized by En3DVar or the best performing EnKF ensemble member produce the highest object-based verification scores, while forecasts from 3DVar and the worst EnKF member produce the lowest scores. Averaged across six cases, hybrid En3DVar using 20% static background error covariance does not improve forecasts over pure En3DVar, although improvements are seen in some individual cases. The false alarm ratios of EnKF members for both composite reflectivity and updraft helicity at the initial time are lower than those from variational methods, suggesting that EnKF analysis reduces spurious reflectivity and mesocyclone objects more effectively.

This study investigated the role of calpain in Eimeria tenella-induced host cell apoptosis. Chick embryo cecal epithelial cell culture technology, flow cytometry, enzyme-linked immunosorbent assays, and fluorescence quantitative PCR were used to detect the E. tenella host cell apoptotic rate, Bax and Bid expression levels, and calpain activity. The results demonstrated that Bax, Bid, and calpain levels were upregulated and apoptosis was increased following E. tenella infection at 24-120 h. Calpain levels were reduced by pharmacological inhibition of calpain using SJA6017 or by blocking Ca

BACKGROUND: Ferroptosis has attracted increasing interest in cancer therapy. Emerging evidences suggest that naturally occurring naphthoquinones exhibit potent anti-glioma effects via various mechanisms. METHODS: The anti-glioma effects of plumbagin were evaluated by in vitro and in vivo experiments. Anti-glioma mechanism of plumbagin was studied by proteomics, flow cytometry, MDA assay, western blot, and RT-PCR. Gene knockdown/overexpression, molecular docking, PharmMappper database, and coimmunoprecipitation were used to study the targets of plumbagin. RESULTS: Plumbagin showed higher blood–brain barrier penetration ability than that of lapachol and shikonin and elicited significant growth inhibitory effects in vitro and in vivo. Ferroptosis was the main mechanism of plumbagin-induced cell death. Mechanistically, plumbagin significantly downregulated the protein and mRNA levels of xCT and decreased GPX4 protein levels. NAD(P)H quinone dehydrogenase 1 (NQO1) was revealed as a plumbagin predictive target using PharmMappper database and molecular docking. Plumbagin enhanced NQO1 activity and decreased xCT expression, resulting in NQO1-dependent cell death. It also induced GPX4 degradation via the lysosome pathway and caused GPX4-dependent cell death. CONCLUSIONS: Plumbagin inhibited in vitro and in vivo glioma growth via targeting NQO1/GPX4-mediated ferroptosis, which might be developed as a novel ferroptosis inducer or anti-glioma candidate.

When using a double-moment microphysics scheme, both hydrometeor mixing ratios and number concentrations are part of the state variables that are needed to initialize convective-scale forecasting. In the Thompson microphysics scheme, both mixing ratio and total number concentration of rainwater (Ntr) are predicted and they are also involved in the reflectivity observation operator. In such a case, when directly assimilating reflectivity using Ntr as the control variable (denoted as CVnr) within a variational framework, the large dynamic range of Ntr and the nonlinear relationship between reflectivity and Ntr prevent efficient minimization convergence. Using logarithmic Ntr as the control variable (CVlognr) alleviates the problem to some extent but can produce spurious analysis increments in Ntr. In this study, a general power transform of Ntr is proposed as the new control variable for Ntr (CVpnr) where the nonlinearity of transform can be adjusted by tuning the exponent parameter. This formulation is implemented within the Gridpoint Statistical Interpolation ensemble-3DVar system. The performance of CVpnr with an optimal exponent parameter value of 0.4 is compared with those of CVnr and CVlognr for the analysis and prediction of a supercell case of 16 May 2017 in more detail. CVpnr with optimal exponent yields faster convergence of cost function minimization than CVnr. Subjective and objective evaluations of analyzed and predicted reflectivity and hourly precipitation indicate that the optimized CVpnr outperforms the other two methods. When applied to five additional cases from May 2017, overall statistics show that CVpnr produces generally superior forecasts and is therefore the preferred choice.

The assimilation of reflectivity (Z) within 3DVar or hybrid ensemble-3DVar (En3DVar) requires the adjoint of the Z observation operator. With the 3DVar or En3DVar method, previous studies often use Z operators consistent with a single-moment microphysics scheme even when the forecast model uses a double-moment scheme. As such, only the mixing ratios of hydrometeors are directly updated by the data assimilation (DA) system, leading to inconsistency between the analyzed microphysics state variables and the microphysics scheme in the prediction model. In this study, we formulated a Z operator consistent with the double-moment Thompson microphysics used in the numerical integrations; in the operator the snow and graupel reflectivity components are simplified using functions fitted to T-matrix simulation results. This operator and its adjoint are implemented within the GSI hybrid En3DVar DA system to enable direct assimilation of Z with a consistent operator. The impacts of this new operator on convective storm analysis through DA cycles, and on the ensuing 3-h forecasts are first examined in detail for a tornado outbreak case of 16 May 2017 in Texas and Oklahoma, and then for five additional thunderstorm cases. Forecast reflectivity, hourly precipitation, and updraft helicity tracks are subjectively evaluated, while neighborhood ETSs and performance diagrams are examined for reflectivity and/or precipitation. Compared to experiments using a Z operator consistent with a single-moment microphysics scheme, the Z operator consistent with double-moment Thompson microphysics used in the forecast model produces better forecasts of reflectivity, hourly precipitation, and updraft helicity tracks with smaller biases, and the improvement is somewhat larger for a higher Z threshold.

MOFs@MOFs (metal-organic frameworks, MOFs) possess precise customized functionalities and predesigned structures that enable the implementation of structure and property regulation for specific functions in comparison to traditional single MOFs. However, the synthesis and fluorescence properties of multilayer MOFs@MOFs are still worth improving. Herein, a fluorescent raspberry-shaped MOF@MOF was constructed via optimized seed-mediated synthesis by tuning the reaction time, reaction mode, and reaction concentration, involving the initial synthesis of the UiO-66-NH

Pulmonary microvascular endothelial cells (PMVECs) were not complex, and the endothelial barrier was destroyed in the pathogenesis progress of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). Previous studies have demonstrated that hepatocyte growth factor (HGF), which was secreted by bone marrow mesenchymal stem cells, could decrease endothelial apoptosis. We investigated whether mTOR/STAT3 signaling acted in HGF protective effects against oxidative stress and mitochondria-dependent apoptosis in lipopolysaccharide (LPS)-induced endothelial barrier dysfunction and ALI mice.In our current study, we introduced LPS-induced PMEVCs with HGF treatment. To investigate the effects of mammalian target of rapamycin (mTOR)/signal transducer and activator of transcription 3 (STAT3) pathway in endothelial oxidative stress and mitochondria-dependent apoptosis, mTOR inhibitor rapamycin and STAT3 inhibitor S3I-201 were, respectively, used to inhibit mTOR/STAT3 signaling. Moreover, lentivirus vector-mediated mTORC1 (Raptor) and mTORC2 (Rictor) gene knockdown modifications were introduced to evaluate mTORC1 and mTORC1 pathways. Calcium measurement, reactive oxygen species (ROS) production, mitochondrial membrane potential and protein, cell proliferation, apoptosis, and endothelial junction protein were detected to evaluate HGF effects. Moreover, we used the ALI mouse model to observe the mitochondria pathological changes with an electron microscope in vivo.Our study demonstrated that HGF protected the endothelium via the suppression of ROS production and intracellular calcium uptake, which lead to increased mitochondrial membrane potential (JC-1 and mitochondria tracker green detection) and specific proteins (complex I), raised anti-apoptosis Messenger Ribonucleic Acid level (B-cell lymphoma 2 and Bcl-xL), and increased endothelial junction proteins (VE-cadherin and occludin). Reversely, mTOR inhibitor rapamycin and STAT3 inhibitor S3I-201 could raise oxidative stress and mitochondria-dependent apoptosis even with HGF treatment in LPS-induced endothelial cells. Similarly, mTORC1 as well as mTORC2 have the same protective effects in mitochondria damage and apoptosis. In in vivo experiments of ALI mouse, HGF also increased mitochondria structural integrity via the mTOR/STAT3 pathway.In all, these reveal that mTOR/STAT3 signaling mediates the HGF suppression effects to oxidative level, mitochondria-dependent apoptosis, and endothelial junction protein in ARDS, contributing to the pulmonary endothelial survival and barrier integrity.

Hyperbranched polysaccharides (HBPSs) are the main components in cell wall and exopolysaccharide (EPS) of Pleurotus tuber-regium. To enhance the yield of these macromolecules, corn oil at 4% addition exhibited the best effect for production of mycelial biomass at 20.49 g/L and EPS at 0.59 g/L, which was 2.56 folds and 1.90 folds of the control, respectively. The treated hyphae were much thicker with smooth surface, while its cell wall content (43.81 ± 0.02%) was 1.96 times of the control (22.34 ± 0.01%). Moreover, a large number of lipid droplets could be visualized under the view of confocal laser scanning microscopy (CLSM). RNA-seq analysis revealed that corn oil could enter the cells and result in the up-regulation of genes on cell morphology and membrane permeability, as well as the down-regulation on expression level of polysaccharide hydrolase and genes involved in the MAPK pathway, all of which probably contribute to the increase of polysaccharides production.