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The rapid increase in population accelerates the rate of change of Land use/Land cover (LULC) in various parts of the world. This phenomenon caused a huge strain for natural resources. Hence, continues monitoring of LULC changes gained a significant importance for management of natural resources and assessing the climate change impacts. Recently, application of machine learning algorithms on RS (remote sensing) data for rapid and accurate mapping of LULC gained significant importance due to growing need of LULC estimation for ecosystem services, natural resource management and environmental management. Hence, it is crucial to access and compare the performance of different machine learning classifiers for accurate mapping of LULC. The primary objective of this study was to compare the performance of CART (Classification and Regression Tree), RF (Random Forest) and SVM (Support Vector Machine) for LULC estimation by processing RS data on Google Earth Engine (GEE). In total four classes of LULC (Water Bodies, Vegetation Cover, Urban Land and Barren Land) for city of Lahore were extracted using satellite images from Landsat-7, Landsat-8 and Landsat-9 for years 2008, 2015 and 2022, respectively. According to results, RF is the best performing classifier with maximum overall accuracy of 95.2% and highest Kappa coefficient value of 0.87, SVM achieved maximum accuracy of 89.8% with highest Kappa of 0.84 and CART showed maximum overall accuracy of 89.7% with Kappa value of 0.79. Results from this study can give assistance for decision makers, planners and RS experts to choose a suitable machine learning algorithm for LULC classification in an unplanned urbanized city like Lahore.

Accurate quantification of soil moisture is essential for understanding water and energy exchanges between the atmosphere and the Earth’s surface, as well as for agricultural applications. Predicting soil moisture content is vital for efficient water management, irrigation scheduling, and drought monitoring. Traditional forecasting methods, such as numerical regression models, often struggle due to various influencing factors and poor observation data quality. In contrast, deep learning algorithms, particularly recurrent and convolutional neural networks, show promise in predicting nonlinear data like soil moisture. This study focuses on shallow groundwater regions, using groundwater levels and meteorological data as features while coupling the Transformer model with other neural network structures. We investigate the potential of attention-based neural networks for soil moisture time series prediction. Our findings demonstrate that the Transformer model achieves an average R2 of 0.523 across different time lags, outperforming the LSTM model with an R2 of 0.485. The introduction of LSTM enhances the Transformer’s stability in handling temporal changes. Additionally, we verified the importance of groundwater for soil moisture prediction. This study introduces new methods for soil moisture prediction and offers new insights and recommendations for the development of artificial intelligence technology for soil moisture prediction.

Summary: The cellular source of positive signals that reinvigorate T cells within the tumor microenvironment (TME) for the therapeutic efficacy of programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) blockade has not been clearly defined. We now show that Batf3-lineage dendritic cells (DCs) are essential in this process. Flow cytometric analysis, gene-targeted mice, and blocking antibody studies revealed that 4-1BBL is a major positive co-stimulatory signal provided by these DCs within the TME that translates to CD8+ T cell functional reinvigoration and tumor regression. Immunofluorescence and spatial transcriptomics on human tumor samples revealed clustering of Batf3+ DCs and CD8+ T cells, which correlates with anti-PD-1 efficacy. In addition, proximity to Batf3+ DCs within the TME is associated with CD8+ T cell transcriptional states linked to anti-PD-1 response. Our results demonstrate that Batf3+ DCs within the TME are critical for PD-1/PD-L1 blockade efficacy and indicate a major role for the 4-1BB/4-1BB ligand (4-1BBL) axis during this process.

Partitioning of evapotranspiration (ET) into soil evaporation (E) and plant transpiration (T) poses a significant challenge. This study proposed a novel approach that combines eddy covariance, micro-lysimeter, and high-resolution unmanned aerial vehicle (UAV) images within the flux footprint to optimize the canopy and soil resistances of the Shuttleworth-Wallace model (S-W) using a multi-objective optimization scheme. A two-year experiment was conducted at the Yucheng and Luancheng sites to investigate the effectiveness of the proposed method for the summer maize-wheat winter system in the North China Plain. Our results showed that the S-W model with multi-objective optimization by using high-resolution UAV images within the flux footprint significantly improved the estimation accuracy of ET components compared with the traditional one- and two-objective optimization schemes. The estimation of ET, T, and E of our method had an average root mean square error of 0.67 mm day−1, 0.66 mm day−1, and 0.28 mm day−1, respectively. The optimized S-W model using high-resolution UAV data within the flux footprint produced better ET partitioning than that optimized using Moderate Resolution Imaging Spectroradiometer (MODIS) data. We then applied the proposed method to estimate ET and ET components in the North China Plain. This study highlighted the importance of utilizing multi-source data (especially high-resolution UAV images) and multi-objective optimization for accurate ET partitioning.

Study region: North China Plain (NCP), China, a semi-arid region with intense groundwater withdrawals. Study focus: This paper developed a framework using meteorological data, model-simulated terrestrial water storage anomalies (TWSA), and additional in-situ (groundwater level, GL) data to improve the unsatisfactory GRACE-TWSA reconstruction in arid and semi-arid regions due to the intense anthropogenic influence on groundwater. The inconsistency between point-scale data (GL) and grid-scale data (GRACE-TWSA and predictors other than GL) is handled by feature extraction techniques. Moreover, to deal with temporal non-stationarity, the time series are separated into trend and detrended components, the patterns of which are further learned by linear and nonlinear machine learning models, respectively.New hydrological insights for the region: Multi-site GL observations in NCP can not only serve as validation data but also as predictors providing invaluable information on human effects for the reconstructed TWSA improvement (from 6.51 to 3.86 cm for Root Mean Square Error and from 0.56 to 0.82 for Nash-Sutcliffe Efficiency). Our results show that multi-site GL data in NCP are highly inter-correlated and can be represented by several principal components, demonstrating the strong hydraulic connectivity in NCP. We also find a significant one-month lag and linear relationship between the trends of GRACE-TWSA and GL changes in NCP. These deeper understandings of hydrologic processes have implications for enhancing the GRACE-TWSA estimations in other similar regions.

The excessive pumping of groundwater during the dry season in Pakistan is identified as a significant concern for groundwater sustainability. Farmers encounter difficulties in efficiently managing irrigation, and adopting the outputs of Irrigation Advisory System (IAS) to improve irrigation practices. Upgrading the existing IAS can help to identify the regions with over-irrigation issues and optimize outreach efforts. To solve these issues, we define the new concept of integrating Gravity Recovery and Climate Experiment (GRACE) total water storage anomalies (TWSA) and Landsat 8 imageries, which can enhance the IAS efficiency by accurately identifying regions facing groundwater depletion by estimating actual crop water consumption through application of the Simple Algorithm For Evapotranspiration Retrieving (SAFER) on Landsat 8 data and Penman-Monteith (PM) method was used to calculate crop water demand using meteorological forcing data from Global Land Data Assimilation System (GLDAS) over the five selected districts of Punjab during the dry seasons of year 2013–2020. Comparing actual water consumption (SAFER evapotranspiration (ET)) with in-situ groundwater depth, strong correlations were found between them that are supporting the use of Landsat 8 data for irrigation monitoring. Further, compared SAFER ET was with PM ET to calculate the percentage of over/under irrigated regions, and the results revealed that most of the selected districts were over-irrigated, indicating the potential for excessive irrigation water savings. Our results show that the integration of GRACE TWSA and Landsat 8 data enhance the efficiency of operational IAS and can lead to potential savings of 81% (equivalent to 155 million m3) of groundwater during the dry season in the Central Punjab, Pakistan. Satellite data integration globally enhances IAS implementation, aiding regions with unsustainable dry season irrigation. This empowers farmers to optimize agriculture through precise IAS outputs.

Background PD-1 checkpoint blockade therapy (CBT) has greatly benefited patients with select solid tumors and lymphomas but has limited efficacy against diffuse large B-cell lymphoma (DLBCL). Because numerous inhibitory checkpoint receptors have been implicated in driving tumor-specific T cell dysfunction, we hypothesized that combinatorial CBT would enhance the activity of anti-PD-1-based therapy in DLBCL. T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) is a coinhibitory receptor expressed on dysfunctional tumor-infiltrating T cells, and TIGIT blockade has demonstrated encouraging activity in combination with PD-1 blockade in murine tumor models and in clinical studies. However, the degree to which TIGIT mediates T cell dysfunction in DLBCL has not been fully explored.Results Here, we demonstrate that TIGIT is broadly expressed on lymphoma-infiltrating T cells (LITs) across a variety of human lymphomas and is frequently coexpressed with PD-1. TIGIT expression is particularly common on LITs in DLBCL, where TIGIT+ LITs often form distinct cellular communities and exhibit significant contact with malignant B cells. TIGIT+/PD-1+ LITs from human DLBCL and murine lymphomas exhibit hypofunctional cytokine production on ex vivo restimulation. In mice with established, syngeneic A20 B-cell lymphomas, TIGIT or PD-1 mono-blockade leads to modest delays in tumor outgrowth, whereas PD-1 and TIGIT co-blockade results in complete rejection of A20 lymphomas in most mice and significantly prolongs survival compared with mice treated with monoblockade therapy.Conclusions These results provide rationale for clinical investigation of TIGIT and PD-1 blockade in lymphomas, including DLBCL.

The housing problem of young people is one of the manifestations of the imbalanced and insufficient development of China’s housing market. Solving housing issues for young people and improving their living conditions is of great significance for promoting the sustainable and healthy development of the real estate market. In order to analyze the housing issues of young people in China during the post-pandemic era, this paper investigates young people in the Nanjing Metropolitan Coordinating Region through questionnaires and interviews. The content of the questionnaire survey mainly includes the current housing situation, choice of renting or purchasing a home, expectations of real estate market, and future plans for purchasing a house of young people. The research results indicate that there are problems in the current housing market, such as strong purchasing preferences, imbalanced supply structure in the rental market, limited financial support for purchasing housing, low housing security levels, and small coverage of the housing provident fund. In order to solve the housing problems of young people, government departments should actively promote the formation of a multi-level housing supply structure, accelerate the promotion of the same rights for renting and purchasing, establish a standardized housing rental market, optimize the housing security policy for young people, and expand the coverage of the housing provident fund. The findings of this study have significant policy implications for easing the housing pressure on young people and building a youth-development-oriented city.

BACKGROUND We previously demonstrated the safety of stereotactic body radiotherapy followed by pembrolizumab (SBRT+P) in patients with advanced solid tumors. This phase I clinical trial was expanded to study the safety of partial tumor irradiation (partial-Rx). We assessed irradiated local failure (LF) and clinical outcomes with correlations to biomarkers including CD8+ T cell radiomics score (RS) and circulating cytokines.METHODS Patients received SBRT to 2–4 metastases and pembrolizumab for up to 7 days after SBRT. Tumors measuring up to 65 cc received the full radiation dose (complete-Rx), whereas tumors measuring more than 65 cc received partial-Rx. Landmark analysis was used to assess the relationship between tumor response and overall survival (OS). Multivariable analysis was performed for RS and circulating cytokines.RESULTS In the combined (expansion plus original) cohort, 97 patients (219 metastases) were analyzed and received SBRT+P. Forty-six (47%) patients received at least 1 partial-Rx treatment. There were 7 (7.2%)dose-limiting toxicities (DLTs). 1-year LF was 7.6% overall, and 13.3% and 5.4% for partial-Rx and complete-Rx tumors, respectively (HR 2.32, 95% CI 0.90–5.97, P = 0.08). The overall, unirradiated, and irradiated objective response rates were 22%, 12%, and 34%, respectively. Irradiated tumor response to SBRT+P was associated with prolonged OS; 1-year OS was 71% (responders), 42% (mixed-responders), and 0% (nonresponders) (P < 0.01). High-RS was significantly associated with improved LF, progression-free survival (PFS), and OS. Elevated circulating IL-8 was independently associated with inferior PFS and OS.CONCLUSION SBRT+P is safe in patients with large, advanced solid tumors. Additional studies are warranted to assess noninferiority of complete versus partial irradiation of tumors in the setting of immunotherapy.TRIAL REGISTRATION Clinicaltrials.gov NCT02608385FUNDING Merck Investigator Studies Program; Hillman Fellows for Innovative Cancer Research Program; NIH grants UM1CA186690-06, P50CA254865-01A1, P30CA047904-32, and R01DE031729-01A1.

Abstract Venous thromboembolism is a significant source of morbidity and mortality worldwide. Catheter-directed thrombolytics is the primary treatment used to relieve critical obstructions, though its efficacy varies based on the thrombus composition. Non-responsive portions of the specimen often remain in situ, which prohibits mechanistic investigation of lytic resistance or the development of diagnostic indicators for treatment outcomes. In this study, thrombus samples extracted from venous thromboembolism patients were analyzed ex vivo to determine their histological properties, susceptibility to lytic therapy, and imaging characteristics. A wide range of thrombus morphologies were observed, with a dependence on age and etymology of the specimen. Fibrinolytic inhibitors including PAI-1, alpha 2-antiplasmin, and TAFI were present in samples, which may contribute to the response venous thrombi to catheter-directed thrombolytics. Finally, a weak but significant correlation was observed between the response of the sample to lytic drug and its magnetic microstructure assessed with a quantitative MRI sequence. These findings highlight the myriad of changes in venous thrombi that may promote lytic resistance, and imaging metrics that correlate with treatment outcomes.

Drought-rehydration irrigation has an enhancing impact on rice yield, but the current research on its yield-increasing effect is mainly experimental and empirical, lacking mechanism theoretical support. Image-based machine vision is rapidly developing and can estimate crop physical and chemical properties. A novel image processing method has been purposefully carried out to detect the real-time response shape of rice drought-rehydration. By application of this method, two new types of morphological descriptors were proposed to characterize and quantify the vertical phenotypic heterogeneity of rice, in which the relative height of the plant centroid (RHC) locates the growth focus, while the leaf angle distribution model describes the vertical characteristics of the leaf phenotypic traits. We verified the response of the vertical traits to different water treatments through designed experiments. The results showed that the RHC and leaf angle distribution parameters followed divergent trends under water stress, reflecting the drought characteristics of rice at different growth stages. The newly developed indicators were sensitive to drought response at specific growth stages and also efficient for evaluating rice growth, including determination of radiation interception capacity and assessment of nutrient accumulation. Furthermore, through the measurement and analysis of vertical structural traits, we found that a short-term water deficit and reasonable rehydration during the rice heading period could help to extend the spike-growing time and improve photosynthetic efficiency, thus benefiting yield formation.

High-resolution soil moisture (SM) information is essential for regional to global hydrological and agricultural applications. The Soil Moisture Active Passive (SMAP) offers daily global composites of SM at coarse-resolution 9 and 36 km, with data gaps limiting its local application to depict SM distribution in detail. To overcome the aforementioned problem, a downscaling and gap-filling novel approach was adopted, using random forest (RF) and artificial neural network (ANN) algorithms to downscale SMAP SM data, using land-surface variables from moderate-resolution imaging spectroradiometer (MODIS) onboard Aqua and Terra satellites from the years 2018 to 2019. Firstly, four combinations (RF+Aqua, RF+Terra, ANN+Aqua, and ANN+Terra) were developed. Each combination downscaled SMAP SM at a high resolution (1 km). These combinations were evaluated by using error matrices and in situ SM at different scales in the ShanDian River (SDR) Basin. The combination RF+Terra showed a better performance, with a low averaged unbiased root mean square error (ubRMSE) of 0.034 m3/m3 and high averaged correlation (R) of 0.54 against the small-, medium-, and large-scale in situ SM. Secondly, the impact of various land covers was examined by using downscaled SMAP and in situ SM. Vegetation attenuation makes woodland more error-prone and less correlated than grassland and farmland. Finally, the RF+Terra and ANN+Terra combinations were selected for their higher accuracy in gap filling of downscaled SMAP SM. The gap-filled downscaled SMAP SM results were compared spatially with China Land Data Assimilation System (CLDAS) SM and in situ SM. The RF+Terra combination outcomes were more humid than ANN+Terra combination results in the SDR basin. Overall, the RF+Terra combination gap-filled data showed high R (0.40) and less ubRMSE (0.064 m3/m3) against in situ SM, which was close to CLDAS SM. This study showed that the proposed RF- and ANN-based downscaling methods have a potential to improve the spatial resolution and gap-filling of SMAP SM at a high resolution (1 km).

Study region: The North China Plain (NCP) is an important agricultural, social, and economic center in China. Significant statistical independence of the hydrological components in NCP exists due to the high variations of natural conditions and human activities both in the horizontal and vertical directions. Study focus: It is critical to understand the features of terrestrial water storage (TWS) changes in NCP. Gravity Recovery and Climate Experiment (GRACE) mission provides valuable measurements for TWS. In this study, the GRACE RL05 mascon data during 2002–2017 in NCP are analyzed via independent component analysis (ICA) and multi-source data to improve the understanding of underlying physical or human-made processes of the regional TWS change. New hydrological insights for the region: The relatively independent hydrological components in NCP with GRACE measurements are successfully derived, which characterize annual variation, surface water storage (SWS) change, and the shallow and deep groundwater storage (SGWS and DGWS) changes, respectively. Based on them, it is found that SGWS decreases faster before 2009 and then reduces slower and keeps stable while DGWS decreases faster after 2009, especially after 2012. Further investigation shows that the anthropogenic influences significantly enhance the vertical heterogeneity of water storage changes based on their exploitations of different hydrological components, in which the South-to-North Water Diversion of China changes the water-use mode in NCP, especially for the reduction of the SGWS exploitation.

Background Tumor-infiltrating CD8+ T cells and neoantigens are predictors of a favorable prognosis and response to immunotherapy with checkpoint inhibitors in many types of adult cancer, but little is known about their role in pediatric malignancies. Here, we analyzed the prognostic strength of T cell-inflamed gene expression and neoantigen load in high-risk neuroblastoma. We also compared transcriptional programs in T cell-inflamed and non-T cell-inflamed high-risk neuroblastomas to investigate possible mechanisms of immune exclusion.Methods A defined T cell-inflamed gene expression signature was used to categorize high-risk neuroblastomas in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program (n=123), and the Gabriella Miller Kids First (GMKF) program (n=48) into T cell-inflamed, non-T cell-inflamed, and intermediate groups. Associations between the T cell-inflamed and non-T cell-inflamed group, MYCN amplification, and survival were analyzed by Cox proportional hazards models. Additional survival analysis was conducted after integrating neoantigen load predicted from somatic mutations. Pathways activated in non-T cell-inflamed relative to T cell-inflamed tumors were analyzed using causal network analysis.Results Patients with T cell-inflamed high-risk tumors showed improved overall survival compared with those with non-T cell-inflamed tumors (p

Abstract Background While cancer immunotherapies including checkpoint blockade antibodies, adoptive T cell therapy, and even some vaccines have given rise to major clinical responses with durability in many cases, a subset of patients who initially respond subsequently develop secondary resistance to therapy. Tumor-intrinsic mechanisms of acquired immunotherapy resistance are incompletely understood. Methods Baseline and treatment-resistant tumors underwent molecular analysis via transcriptional profiling or genomic sequencing for oncogenic alterations and histologic analysis for T cell infiltration to investigate mechanisms contributing to T cell exclusion and acquired resistance to immunotherapy. Results We describe two patients with metastatic melanoma who initially showed a durable partial response to either a melanoma-peptide/interleukin-12 vaccine or combined anti-CTLA-4 + anti-PD-1 therapy, but subsequently developed new treatment-resistant metastases. In the first case, the recurrent tumor showed new robust tumor expression of β-catenin, whereas in the second case genomic sequencing revealed acquired PTEN loss. Both cases were associated with loss of T cell infiltration, and both pathways have been mechanistically linked to immune resistance preclinically. Conclusion Our results suggest that secondary resistance to immunotherapies can arise upon selection for new oncogenic variants that mediate T cell exclusion. To identify the spectrum of underlying mechanisms of therapeutic resistance, similar evaluation for the emergence of tumor-intrinsic alterations in resistant lesions should be done prospectively at the time of relapse in a range of additional patients developing secondary resistance.

Sugarcane is an important sugar source in America and is mainly planted in the states of Florida and Louisiana. The purpose of this study was to predict the sugarcane yield in these two states from 2008 to 2016. Three statistical sugarcane yield models (i.e., the CNDVI, K–M, and SiPAR models) were applied to predict yield in America, using remote sensing and weather data. To verify the robustness of models, model parameters obtained in places (i.e., Reunion Island and Southwestern China) far away from America were used. The results showed that the SiPAR model outperformed the CDNVI and K–M models for yield prediction. Solar radiation was an important constraint factor to ensure the statistical model’s robustness under different conditions. The CNDVI model had the lowest robustness because of the absence of solar radiation, although it could reflect the yield trend to some extent. The K–M model failed to predict the low sugarcane yield, owing to the lack of consideration of temperature and soil water stresses. Florida had a low sugarcane yield in the west and southwest; however, Louisiana had high sugarcane yield in the same directions. This study demonstrated the robustness of the SiPAR model and investigated the sugarcane yield status in Florida and Louisiana. It can be a reference for similar studies in the future.

The Soil Moisture Active Passive (SMAP) mission with high-precision soil moisture (SM) retrieval products provides global daily composites of SM at 3, 9, and 36 km earth grids measured by L-band active and passive microwave sensors. The capability of passive microwave remote sensing has been recognized for the estimation of SM variations. The purpose of this work was to establish an interaction between the highly variable SM spatial distribution on the ground and the SMAP’s coarse resolution radiometer-based SM retrievals. In this work, SMAP Level 3 (L3) and Level 4 (L4) SM products are validated with in situ datasets observed from the different locations of the Soil Moisture Network within the ShanDian River (SMN-SDR) Basin over the period of January 2018 to December 2019. The values of the unbiased root mean square error (ubRMSE) for L3 (SPL3SMP_E) SM retrievals are close to the standard SMAP mission SM accuracy requirement of 0.04 m3/m3 at the 9-km scale, with an averaged ubRMSE value of 0.041 m3/m3 (0.050 m3/m3) for descending (ascending) SM with the correlation (R) values of 0.62 (0.42) against the sparse network sites. The L4 (SPL4SMGP) Surface and Root-zone SM (RZSM) estimates show less error (ubRMSE < 0.04) and high correlation (R > 0.60) values, and are consistent with the previous SMAP-based SM estimations. The SMAP L4 SM products (SPL4SMGP) performed well compared to the L3 SM retrieval products (SPL3SMP_E). In vegetated land, the variability and compatibility of the SMAP SM estimates with the evaluation metrics for both products (L3 and L4) showed a good performance in the grassland, then in the farmland, and worst in the woodlands. Finally, SMAP algorithm parameters sensitivity analysis of the satellite products was conducted to produce time-series and highly precise SM datasets in China.

Abstract Background Immunotherapies targeting the PD-1 checkpoint pathway have recently gained regulatory approval in numerous cancer types. With the widespread use of immune checkpoint therapies, varying patterns of responses and immune-related adverse events are being observed. Case Presentation In this case, we highlight a patient who developed recurrent, large-volume ascites, while simultaneously having a 49% reduction in peritoneal tumor lesion size by RECIST criteria. Sampling of the fluid revealed high levels of IL-6 and IL-15. Cytology revealed no malignant cells on 4 separate paracenteses over a period of 6 weeks. Cell counts revealed that 45% of cells were lymphocytes, and further analysis was performed by fluorescence-activated cell sorting (FACS). The majority of lymphocytes were CD8+, of which 78% were PD-1+ and 43% were HLA-DR+ indicating an activated phenotype. Conclusions In summary, treatment with anti-PD-1 therapy may result in pseudoprogression manifested by ascitic fluid accumulation due to the influx of activated T cells. Since worsening of ascites is typically associated with disease progression, it is important to consider the possibility of pesudoprogression in such patients undergoing therapy with immune checkpoint inhibitors.

Abstract Background The optimal strategy for vaccination to induce CD8+ T cell responses against WT1 is not known. Methods A pilot randomized study in HLA-A02+ patients to receive vaccination with WT1 in Montanide or in poly ICLC, a TLR3 agonist, to explore the novel immune adjuvant was conducted. Seven patients were randomized. Four patients received WT1 in Montanide, and three with WT1 in poly ICLC. Five patients were in morphologic remission and two had residual morphologic disease at the study entry. Results All patients finished the induction phase without any major toxicity except mild transient local injection reaction. One patient on the Montanide arm developed aseptic ulceration at two vaccine sites which healed without antibiotics. Three of 4 patients on the Montanide arm had a decreased expression of WT1 after WT1 vaccination, and two of them demonstrated generation of WT1-specific cytotoxic CD8+ T cell responses with biased TCR beta chain enrichment. In contrast, no obvious WT1-specific immune responses were detected in two patients on the poly ICLC arm, nor was there clonal enrichment by TCR alpha/beta sequencing; however, these patients did also have decreased WT1 expression and remained in remission several years after the initiation of treatment. Conclusions WT1 peptide vaccine with Montanide as an adjuvant induces detectable WT1-specific CD8+ T cell responses with clonal TCR enrichment, which may be capable of controlling leukemia recurrence in the setting of minimal residual disease. Poly ICLC may induce anti-leukemic activity in the absence of detectable WT1 specific CD8+ T cell responses. Trial registration NCT01842139, 7/3/2012 retrospectively registered; https://clinicaltrials.gov/ct2/show/NCT01842139 .

In the past few decades, different data assimilation methods have been proposed to estimate soil parameters. It is not clear whether a straightforward sampling approach is sufficient or whether a linear filter or even an advanced nonlinear filter is needed to interpret the potential information carried by different data types (e.g., pressure head and water content data from multiple depths, easily available surface soil moisture data, and groundwater level data). In this study, three classical data assimilation methods, i.e., the ensemble Kalman filter (EnKF), the ensemble randomized maximum likelihood filter (EnRML), and the Markov chain Monte Carlo (MCMC), were investigated numerically in terms of the utility to cope with three different types of observations. Results show that, compared with the EnKF approach, EnRML is a superior method to extract the parameter information from observations. The MCMC approach performs well in homogeneous soil but not in heterogeneous soil. Regardless of the data assimilation methods and the soil heterogeneity, point-scale soil water pressure head data are the most valuable in terms of soil parameter estimation, followed by groundwater level data, which require a nonlinear filter to interpret. A smaller observation error for groundwater level data leads to obviously improved parameter estimates by using EnRML with a slight improvement by using EnKF. The stable performance of the EnKF method relies more heavily on a relatively large number of ensembles than the EnRML method, whereas only a few ensemble members are needed for EnRML in a homogeneous soil column.

Preferential flow is common in clay or expansive clay soils, involving water bypassing a large portion of the soil matrix. Dye tracer experiment and numerical modeling are used to simulate the surface runoff and subsurface preferential flow patterns influenced by the soil fracture network of a relatively steep hillslope system (slope angle equals to 10 degrees). The result of the experiments indicates that part of the water is infiltrated through cracks, leading to the delay of the initial runoff-yielding time and reduction of the discharge of the surface runoff. The soil water flow is mainly in the matrix when the intensity of precipitation is low. With the increasing of precipitation, soil water movement may become in the form of preferential flow through cracks. In addition, the nonuniformity of soil water infiltration and the depth of the average water infiltration increase as the precipitation intensity increases. To this end, the complete coupling model was established by using the surface-matrix-crack (SMC) model to simulate water flow within discrete fracture as well as to simulate water flow in the soil matrix based on the concept of dual permeability using the traditional Richards’ equation. In this model, the “cubic law” of fluid motion in cracks within smooth parallel plates and the two-dimensional diffusion wave approximation to Saint-Venant equations with momentum term ignored (two-dimensional shallow water equations) were used. The model divides soil water infiltration into two forms and uses the overall method to calculate the exchange of water between the crack networks and matrix regions as well as the exchange water between surface runoff and infiltration water. Results indicate that the SMC model has better performance compared with the traditional equivalent continuum model when those models are used to simulate the surface runoff movement and the soil water movement in the presence of cracks.

Hydraulic tomography based on geostatistics has proven to be robust in characterizing subsurface heterogeneity in hydraulic conductivity (K) and specific storage (Ss) through the joint inversion of drawdown records from multiple pumping tests. However, the spatially variable estimates can be smooth or even erroneous for areas where pumping/observation data densities are not high. Previous hydraulic tomography surveys conducted at the North Campus Research Site (NCRS) on the University of Waterloo campus in Waterloo, Canada, revealed that the estimated hydraulic parameters were smooth and the known aquitard was erroneously identified as a high K zone. This was likely the consequence of the site being highly heterogeneous, while only utilizing four pumping tests and not having measurable drawdowns in the low K aquitard for inverse modeling. Here, we investigate whether improved K and Ss estimates could be obtained through the inclusion of additional pumping test data by stressing both aquifer and aquitard zones for a sufficiently long period. Specifically, six additional pumping/injection tests were conducted at the site, and a transient hydraulic tomography analysis with 14 tests was completed. Results reveal that there is a significant improvement to the K and Ss tomograms in terms of the visual correspondence with various geologic units, including its connectivity. More importantly, with the availability of additional data, we found that the inverse model now can better capture the high and low K features for nine boreholes when compared with K values obtained from permeameter tests. The estimated K and Ss tomograms are then used for the forward simulation of one additional pumping test not used for model calibration, revealing reasonable predictions. While encouraging results are obtained by including a large number of pumping tests to the transient hydraulic tomography analysis, stratigraphic boundaries are still smoothed, which is a direct consequence of utilizing a geostatistics-based inversion approach that assumes stationarity in statistical properties. To capture such sharp boundaries, incorporation of additional data types, such as geological and geophysical information, may be necessary when data densities are not sufficiently high.

Background Depletion of CD25+ Tregs improves anti-tumor immunity in preclinical models. Denileukin diftitox is a recombinant fusion protein of human IL-2 and diptheria toxin fragment that also can kill CD25+ T cells. Prior clinical trials of denileukin diftitox suggested reduction of FoxP3+ Tregs and some clinical responses.Method To investigate the immunologic effects of denileukin difitox on vaccine-specific immune responses in melanoma, a randomized clinical trial of single dose denileukin diftitox prior to vaccination versus vaccination alone in subjects with HLA-A2+ metastatic melanoma was performed. Treatment included randomization to a 4-peptide vaccine (Melan-A, gp100, MAGE3 and NA17 with GM-CSF emulsified in Montanide) alone or after single dose of denileukin diftitox (18 mcg/kg). Vaccine was given every 2 weeks for 3 doses and, absent clinical progression, continued every 2 weeks. Blood and tumor biopsies were obtained pretreatment and after 3 vaccinations for immunologic assessments.Results In 17 treated subjects there were no drug-related G3-4 adverse events. One partial response and 8 stable disease were observed in 9 subjects (4 DD: 5 vaccine only) with no impact of denileukin diftitox on time to progression. Total peripheral Tregs were not significantly altered, and in 1 patient biopsy intra-tumoral FoxP3 transcripts were not reduced following denileukin diftitox. ELISA for IL2R-α demonstrated no impact on outcomes by soluble CD25 level. Immune monitoring suggested the development of modest vaccine-specific CD8+ T cell responses in the control group, however immunization efficacy was actually reduced in the denileukin diftitox group.Conclusion Our results indicate that denileukin diftitox did not effectively deplete Tregs, augment T cell responses, or improve clinical activity in melanoma. Clinicaltrials.gov ID: NCT00515528; Registered August 9, 2007.

Monitoring and improving environmental stress in crops is vital for the sustainable development of agriculture and food security. Traditional experimental methods are costly and time-consuming, yet crop growth models focus mainly only on water and nutrient stresses. In this study, a new World Food Studies (WOFOST) model, WOFOST-ES, was developed by the addition of a general environmental stress factor (ES). To calibrate and validate WOFOST-ES, two-year micro-plot experiments and one-year field experiments with sunflower were conducted in the Hetao Irrigation District, China. The results of the micro-plot experiments indicated that the WOFOST model failed to simulate sunflower growth correctly but that the WOFOST-ES model was highly accurate in simulating both yield (R2 = 0.99, root mean square error (RMSE) = 56 kg/ha) and leaf area index (LAI) (R2 = 0.86, RMSE = 0.44). A statistical method for estimating ESs based on the dominant stress factor (salt at our study site) was also proposed as a supplemental tool for WOFOST-ES, and micro-plot and field experiments conducted in 2013 and 2017 both proved acceptable accuracy of the statistical method when using WOFOST-ES. Comparison between ESs and the water and salt stress factors of Feddes-type stress reduction functions indicated that ESs failed to reveal actual environmental stresses during the sunflower seeding stage but did reflect other environmental stresses in addition to water and salt during the bud, flowering, and maturity stages. Although the present WOFOST-ES model proved to be accurate, stable, and practical, future studies should be performed, focusing on the physical separation of ESs, their mechanistic quantification, and their evaluation at small time steps using more observations.

Crop coefficients (Kc) are important for the development of irrigation schedules, but few studies on Kc focus on saline soils. To propose the growth-stage-specific Kc values for sunflowers in saline soils, a two-year micro-plot experiment was conducted in Yichang Experimental Station, Hetao Irrigation District. Four salinity levels including non-salinized (ECe = 3.4–4.1 dS·m–1), low (ECe = 5.5–8.2 dS·m–1), moderate (ECe = 12.1–14.5 dS·m–1), and high (ECe = 18.3–18.5 dS·m–1) levels were arranged in 12 micro-plots. Based on the soil moisture observations, Vensim software was used to establish and develop a physically-based water flow in the soil-plant system (WFSP) model. Observations in 2012 were used to calibrate the WFSP model and acceptable accuracy was obtained, especially for soil moisture simulation below 5 cm (R2 > 0.6). The locally-based Kc values (LKc) of sunflowers in saline soils were presented according to the WFSP calibration results. To be specific, LKc for initial stages (Kc1) could be expressed as a function of soil salinity (R2 = 0.86), while R2 of LKc for rapid growth (Kc2), middle (Kc3), and mature (Kc4) stages were 0.659, 1.156, and 0.324, respectively. The proposed LKc values were also evaluated by observations in 2013 and the R2 for initial, rapid growth, middle, and mature stages were 0.66, 0.68, 0.56 and 0.58, respectively. It is expected that the LKc would be of great value in irrigation management and provide precise water application values for salt-affected regions.