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Excluding direct consideration of vegetation dynamics reduces the accuracy in fire risk estimation. Satellite retrievals of vegetation dynamics can enhance the fire risk prediction when used as indicators of fuel water status and fuel load. However, the fire risk-vegetation relationship carries complexities as different mechanisms dominate during fire risk escalation and decline, with vegetation responding differently to each process. This study investigates whether vegetation parameters can be utilized in fire risk prediction in the absence of fire weather information, and how they can be utilized to effectively reflect on the fire risk increment from a minimum point, which is the concern in bushfire occurrence. Using the McArthur Forest Fire Danger Index (FFDI) as a measure of fire danger, a clear association with the satellite-observed vegetation optical depth (VOD) was noted for segments illustrating risk increment. An application over Australia showed clear improvements when incorporating VOD into a predictive model as compared to the use of fire risk persistence alone. On average, the VOD-induced predictive model exhibited better performance than the persistence model when evaluated over a 12-month lead span. The former model showed higher Nash-Sutcliffe efficiency (NSE) in 55.6% of pixels that indicated VOD causes FFDI. The latter performed better only in 18.2% of those pixels. Across the entire spatial domain, from the first to the ninth lead month, the VOD-induced model showed higher mean NSE (0.65 ± 0.23 to 0.52 ± 0.34) and lower or nearly equal mean root mean square error (RMSE) (4.6 ± 3.7 to 7.9 ± 5.4) than the persistence model. Our study provides insights on fire risk escalation in fire-prone regions in the absence of fire weather data. With further improvements, the proposed method can serve as a foundation for developing a novel forecast index solely based on time series data of fire risk and vegetation dynamics.

Abstract Exosomal PD-L1 (exoPD-L1) has recently received significant attention as a biomarker predicting immunotherapeutic responses involving the PD1/PD-L1 pathway. However, current technologies for exosomal analysis rely primarily on bulk measurements that do not consider the heterogeneity found within exosomal subpopulations. Here, we present a nanoscale cytometry platform NanoEPIC, enabling phenotypic sorting and exoPD-L1 profiling from blood plasma. We highlight the efficacy of NanoEPIC in monitoring anti-PD-1 immunotherapy through the interrogation of exoPD-L1. NanoEPIC generates signature exoPD-L1 patterns in responders and non-responders. In mice treated with PD1-targeted immunotherapy, exoPD-L1 is correlated with tumor growth, PD-L1 burden in tumors, and the immune suppression of CD8+ tumor-infiltrating lymphocytes. Small extracellular vesicles (sEVs) with different PD-L1 expression levels display distinctive inhibitory effects on CD8 + T cells. NanoEPIC offers robust, high-throughput profiling of exosomal markers, enabling sEV subpopulation analysis. This platform holds the potential for enhanced cancer screening, personalized treatment, and therapeutic response monitoring.

Summary: By sorting receptor tyrosine kinases into endolysosomes, the endosomal sorting complexes required for transport (ESCRTs) are thought to attenuate oncogenic signaling in tumor cells. Paradoxically, ESCRT members are upregulated in tumors. Here, we show that disruption of hepatocyte growth factor-regulated tyrosine kinase substrate (HRS), a pivotal ESCRT component, inhibited tumor growth by promoting CD8+ T cell infiltration in melanoma and colon cancer mouse models. HRS ablation led to misfolded protein accumulation and triggered endoplasmic reticulum (ER) stress, resulting in the activation of the type I interferon pathway in an inositol-requiring enzyme-1α (IRE1α)/X-box binding protein 1 (XBP1)-dependent manner. HRS was upregulated in tumor cells with high tumor mutational burden (TMB). HRS expression associates with the response to PD-L1/PD-1 blockade therapy in melanoma patients with high TMB tumors. HRS ablation sensitized anti-PD-1 treatment in mouse melanoma models. Our study shows a mechanism by which tumor cells with high TMB evade immune surveillance and suggests HRS as a promising target to improve immunotherapy.

Inhaled substances, such as consumer products, chemicals at the workplace, and nanoparticles, can affect the lung function in several ways. In this paper, we explore the adverse outcome pathway (AOP) that starts when inhaled substances that reach the alveoli inhibit the function of the lung surfactant, and leads to decreased lung function. Lung surfactant covers the inner surface of the alveoli, and regulates the surface tension at the air–liquid interface during breathing. The inhibition of the lung surfactant function leads to alveolar collapse because of the resulting high surface tension at the end of expiration. The collapsed alveoli can be re-opened by inspiration, but this re-opening causes shear stress on cells covering the alveoli. This can damage the alveolar-capillary membrane integrity, allowing blood components to enter the alveolar airspace. Blood components, such as albumin, can interact with the lung surfactant and further inhibit its function. The collapse of the alveoli is responsible for a decrease in the surface area available for blood oxygenation, and it reduces the volume of air that can be inhaled and exhaled. These different key events lead to decreased lung function, characterized by clinical signs of respiratory toxicity and reduced blood oxygenation. Here we present the weight of evidence that supports the AOP, and we give an overview of the methods available in vitro and in vivo to measure each key event of the pathway, and how this AOP can potentially be used in screening for inhalation toxicity.

Although the process by which the cortical tissues of the brain fold has been the subject of considerable study and debate over the past few decades, a single mechanistic description of the phenomenon has yet to be fully accepted. Rather, two competing explanations of cortical folding have arisen in recent years; known as the axonal tension and the differential tangential expansion models. In the present review, these two models are introduced by analyzing the computational, theoretical, materials-based, and cell studies which have yielded them. Then Four-dimensional bioprinting is presented as a powerful technology which can not only be used to test both models of cortical folding de novo, but can also be used to explore the reciprocal effects that folding associated mechanical stresses may have on neural development. Therein, the fabrication of ‘smart’ tissue models which can accurately simulate the in vivo folding process and recapitulate physiologically relevant stresses are introduced. We also provide a general description of both cortical neurobiology as well as the cellular basis of cortical folding. Our discussion also entails an overview of both 3D and 4D bioprinting technologies, as well as a brief commentary on recent advancements in printed central nervous system tissue engineering.

The carbon balance in Southeast Asia is highly uncertain. Here, the authors show that land use changes and occurrence of strong El Niño control decadal shifts in the carbon balance of this region.

In automotive engineering, the safety aspect has been considered as a number one priority in development of a new vehicle. Each single system has been studied and developed in order to meet safety requirements. Instead of having air bags, good suspension systems, good handling and safe cornering, one of the most critical systems in a vehicle is the brake system. The objective of this work is to investigate and analyze the temperature distribution of rotor disc during braking operation using ANSYS Multiphysics. The work uses the finite element analysis techniques to predict the temperature distribution on the full and ventilated brake discs and to identify the critical temperature of the rotor. The analysis also gives us the heat flux distribution for the two discs.

In recent years, different space agencies have launched satellite missions that carry passive microwave instruments on-board that can measure surface soil moisture. Three currently operational missions are the Soil Moisture and Ocean Salinity (SMOS) mission developed by the European Space Agency (ESA), the Advanced Microwave Scanning Radiometer 2 (AMSR2) developed by the Japan Aerospace Exploration Agency (JAXA), and the Microwave Radiation Imager (MWRI) from China’s National Satellite Meteorological Centre (NSMC). In this study, the quality of surface soil moisture anomalies derived from these passive microwave instruments was sequentially assessed over the mainland of the People’s Republic of China. First, the impact of a recent update in the Land Parameter Retrieval Model (LPRM) was assessed for MWRI observations. Then, the soil moisture measurements retrieved from the X-band observations of MWRI were compared with those of AMSR2, followed by an internal comparison of the multiple frequencies of AMSR2. Finally, SMOS retrievals from two different algorithms were also included in the comparison. For each sequential step, processing and verification chains were specifically designed to isolate the impact of algorithm (version), observation frequency or instrument characteristics. Two verification techniques are used: the statistical Triple Collocation technique is used as the primary verification tool, while the precipitation-based Rvalue technique is used to confirm key results. Our results indicate a consistently better performance throughout the entire study area after the implementation of an update of the LPRM. We also find that passive microwave observations in the AMSR2 C-band frequency (6.9 GHz) have an advantage over the AMSR2 X-band frequency (10.7 GHz) over moderate to densely vegetated regions. This finding is in line with theoretical expectations as emitted soil radiation will become masked under a dense canopy with stricter thresholds for higher passive microwave frequencies. Both AMSR2 and MWRI make X-band observations; a direct comparison between them reveals a consistently higher quality obtained by AMSR2, specifically over semi-arid climate regimes. Unfortunately, Radio Frequency Interference hampers the usefulness of soil moisture products for the SMOS L-band mission, leading to a significantly reduced revisit time over the densely populated eastern part of the country. Nevertheless, our analysis demonstrates that soil moisture products from a number of multi-frequency microwave sensors are credible alternatives for this dedicated L-band mission over the mainland of the People’s Republic of China.

Soil moisture is an important variable in the coupled hydrologic and climate system. In recent years, microwave-based soil moisture products have been shown to be a viable alternative to in situ measurements. A popular way to measure the performance of soil moisture products is to calculate the temporal correlation coefficient (R) against in situ measurements or other appropriate reference datasets. In this study, an existing linear combination method improving R was modified to allow for a non-static or nonstationary model combination as the basis for improving remotely-sensed surface soil moisture. Previous research had noted that two soil moisture products retrieved using the Japan Aerospace Exploration Agency (JAXA) and Land Parameter Retrieval Model (LPRM) algorithms from the same Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor are spatially complementary in terms of R against a suitable reference over a fixed period. Accordingly, a linear combination was proposed to maximize R using a set of spatially-varying, but temporally-fixed weights. Even though this approach showed promising results, there was room for further improvements, in particular using non-static or dynamic weights that take account of the time-varying nature of the combination algorithm being approximated. The dynamic weighting was achieved by using a moving window. A number of different window sizes was investigated. The optimal weighting factors were determined for the data lying within the moving window and then used to dynamically combine the two parent products. We show improved performance for the dynamically-combined product over the static linear combination. Generally, shorter time windows outperform the static approach, and a 60-day time window is suggested to be the optimum. Results were validated against in situ measurements collected from 124 stations over different continents. The mean R of the dynamically-combined products was found to be 0.57 and 0.62 for the cases using the European Centre for Medium-Range Weather Forecasts Reanalysis-Interim (ERA-Interim) and Modern-Era Retrospective Analysis for Research and Applications Land (MERRA-Land) reanalysis products as the reference, respectively, outperforming the statically-combined products (0.55 and 0.54).

To improve the understanding of water–vegetation relationships, direct comparative studies assessing the utility of satellite remotely sensed soil moisture, gridded precipitation products, and land surface model output are needed. A case study was investigated for a water-limited, lateral inflow receiving area in northeastern Australia during December 2008 to May 2009. In January 2009, monthly precipitation showed strong positive anomalies, which led to strong positive soil moisture anomalies. The precipitation anomalies disappeared within a month. In contrast, the soil moisture anomalies persisted for months. Positive anomalies of Normalized Difference Vegetation Index (NDVI) appeared in February, in response to water supply, and then persisted for several months. In addition to these temporal characteristics, the spatial patterns of NDVI anomalies were more similar to soil moisture patterns than to those of precipitation and land surface model output. The long memory of soil moisture mainly relates to the presence of clay-rich soils. Modeled soil moisture from four of five global land surface models failed to capture the memory length of soil moisture and all five models failed to present the influence of lateral inflow. This case study indicates that satellite-based soil moisture is a better predictor of vegetation water availability than precipitation in environments having a memory of several months and thus is able to persistently affect vegetation dynamics. These results illustrate the usefulness of satellite remotely sensed soil moisture in ecohydrology studies. This case study has the potential to be used as a benchmark for global land surface model evaluations. The advantages of using satellite remotely sensed soil moisture over gridded precipitation products are mainly expected in lateral-inflow and/or clay-rich regions worldwide.

Access to hepatitis C virus (HCV) testing and treatment is limited in Myanmar. We assessed an integrated HIV and viral hepatitis testing and HCV treatment strategy. Sofosbuvir/velpatasvir (SOF/VEL) ± weight-based ribavirin for 12 weeks was provided at three treatment sites in Myanmar and sustained virologic response (SVR) assessed at 12 weeks after treatment. Participants co-infected with HBV were treated concurrently with tenofovir. Cost estimates in 2018 USD were made at Yangon and Mandalay using standard micro-costing methods. 803 participants initiated SOF/VEL; 4.8% were lost to follow-up. SVR was achieved in 680/803 (84.6%) by intention-to-treat analysis. SVR amongst people who inject drugs (PWID) was 79.7% (381/497), but 92.5% among PWID on opioid substitution therapy (OST) (74/80), and 97.4% among non-PWID (298/306). Utilizing data from 492 participants, of whom 93% achieved SVR, the estimated average cost of treatment per patient initiated was $1030 (of which 54% were medication costs), with a production cost per successful outcome (SVR) of $1109 and real-world estimate of $1250. High SVR rates were achieved for non-PWID and PWID on OST. However, the estimated average cost of the intervention (under the assumption of no genotype testing and reduced real-world effectiveness) of $1250/patient is unaffordable for a national elimination strategy. Reductions in the cost of antivirals and linkage to social and behavioural health services including substance use disorder treatment to increase retention and adherence to treatment are critical to HCV elimination in this population.

Elevated CO2 (eCO2) experiments provide critical information to quantify the effects of rising CO2 on vegetation1–6. Many eCO2 experiments suggest that nutrient limitations modulate the local magnitude of the eCO2 effect on plant biomass1,3,5, but the global extent of these limitations has not been empirically quantified, complicating projections of the capacity of plants to take up CO27,8. Here, we present a data-driven global quantification of the eCO2 effect on biomass based on 138 eCO2 experiments. The strength of CO2 fertilization is primarily driven by nitrogen (N) in ~65% of global vegetation and by phosphorus (P) in ~25% of global vegetation, with N- or P-limitation modulated by mycorrhizal association. Our approach suggests that CO2 levels expected by 2100 can potentially enhance plant biomass by 12 ± 3% above current values, equivalent to 59 ± 13 PgC. The global-scale response to eCO2 we derive from experiments is similar to past changes in greenness9 and biomass10 with rising CO2, suggesting that CO2 will continue to stimulate plant biomass in the future despite the constraining effect of soil nutrients. Our research reconciles conflicting evidence on CO2 fertilization across scales and provides an empirical estimate of the biomass sensitivity to eCO2 that may help to constrain climate projections.

Oil sands development in the Athabasca and Cold Lake oil sands regions of Alberta has raised concerns about potential impacts to groundwater and groundwater dependent ecosystems. This review summarizes the current state of understanding as to how oil sands mining and in situ activities can affect groundwater systems using a stressor-mechanism-response framework. Specific oil sands activities and practices are reviewed, and where possible, described in terms of how they can impact hydraulic head, the hydraulic properties of aquifers, recharge and transport of constituents of concern and linked to observed or potential impacts to groundwater quantity and quality. Groundwater is an important component of the water balance in boreal ecosystems, and specific vulnerabilities related to development are reviewed, including water use, landscape disturbance, groundwater withdrawals, tailings pond seepage, deep well disposal and thermal impacts. Knowledge gaps include lack of baseline data and monitoring of the quantity and quality of groundwater discharge to rivers, lakes and wetlands. One key monitoring challenge is attribution of hydrogeologic responses to specific oil sands stressors given the range of other natural and anthropogenic factors contributing to their variability. Quantitative groundwater exchange mapping, regional-scale isotope mass balance assessment, and broader incorporation of isotopic and geochemical tracers for fingerprinting water sources and incorporation of Indigenous Knowledge appear promising for improved effectiveness of monitoring. [ABSTRACT FROM AUTHOR]

An integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks.