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During the warm months of the year in Catalonia, the marine air overcomes the coastal mountain range and reaches the eastern Ebro sub-basin. This phenomenon is called marinada and has recently been thoroughly characterized for the first time by Jiménez et al. (2023), based on surface climatological data. However, the main physical mechanisms involved in its arrival and propagation remain to be discovered. This study aims to understand how the marinada is formed and how it interacts with the already developed atmospheric boundary layer. Surface and atmospheric observations are used in combination with the coupled surface–atmosphere model Meso-NH to reveal the mechanisms at play. It is shown that the marinada is generated by the advection of a cool marine air mass over the Catalan Pre-coastal Range by the action of the sea breeze and the upslope wind. This marine air mass then flows into the Ebro basin, creating what is known as the marinada. The characteristics and dynamics of the marinada allow it to be classified as a fall wind. It is also shown that the arrival, propagation and decay of the marinada is strongly dependent on the larger-scale weather situation: westerlies or thermal low. The current study provides a consistent framework for understanding the marinada, paving the way for better modeling and prediction of the phenomenon.

Soil water drainage is the main source of groundwater recharge and river flow. It is therefore a key process for water resource management. In this study, we evaluate the soil hydrology and the soil water drainage, simulated by the interactions between soil–biosphere–atmosphere (ISBA) land surface model currently used for hydrological applications from the watershed scale to the global scale, where parameters are generally not calibrated. This evaluation is done using seven lysimeters from two long-term model approach sites measuring hourly water dynamics between 2009 and 2019 in northeastern France. These 2 m depth lysimeters are filled with different soil types and are either maintained as bare soil or covered with vegetation. Four closed-form equations describing soil water retention and hydraulic conductivity functions are tested, namely the commonly used equations from Brooks and Corey (1966) and van Genuchten (1980), a combination of the van Genuchten (1980) soil water retention function with the Brooks and Corey (1966) unsaturated hydraulic conductivity function, and, for the very first time in a land surface model (LSM), a modified version of the van Genuchten (1980) equations, with a new hydraulic conductivity curve proposed by Iden et al. (2015). The results indicate good performance by ISBA with the different closure equations in terms of soil volumetric water content and water mass. The drained flow at the bottom of the lysimeter is well simulated, using Brooks and Corey (1966), while some weaknesses appear with van Genuchten (1980) due to the abrupt shape near the saturation of its hydraulic conductivity function. The mixed form or the new van Genuchten (1980) hydraulic conductivity function from Iden et al. (2015) allows the solving of this problem and even improves the simulation of the drainage dynamic, especially for intense drainage events. The study also highlights the importance of the vertical heterogeneity of the soil hydrodynamic parameters to correctly simulate the drainage dynamic, in addition to the primary influence of the parameters characterizing the shape of the soil water retention function.

The Antarctic plateau, characterized by cold and dry weather conditions with very little precipitation, is mostly covered by snow at the surface. This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results of offline numerical simulations, carried out during 15 d in 2009, on a single site on the Antarctic plateau, show that the simplest models are able to reproduce the surface temperature as well as the most complex models provided that their surface parameters are well chosen. Furthermore, it is shown that the diversity of the surface parameters of the models strongly impacts the numerical simulations, in particular the temporal variability of the surface temperature and the components of the surface energy balance. The models tend to overestimate the surface temperature by 2–5 K at night and underestimate it by 2 K during the day. The observed and simulated turbulent latent heat fluxes are small, of the order of a few W m−2, with a tendency to underestimate, while the sensible heat fluxes are in general too intense at night as well as during the day. The surface temperature errors are consistent with too large a magnitude of sensible heat fluxes during the day and night. Finally, it is shown that the most complex multilayer models are able to reproduce well the propagation of the daily diurnal wave, and that the snow temperature profiles in the snowpack are very close to the measurements carried out on site.

Small, shallow lakes represent the majority of inland freshwater bodies. However, the effects of climate change on such ecosystems have rarely been quantitatively addressed. We propose a methodology to evaluate the thermal response of small, shallow lakes to long-term changes in the meteorological conditions through model simulations. To do so, a 3D thermal-hydrodynamic model is forced with meteorological data and used to hindcast the evolution of an urban lake in the Paris region between 1960 and 2017. Its thermal response is assessed through a series of indices describing its thermal regime in terms of water temperature, thermal stratification, and potential cyanobacteria production. These indices and the meteorological forcing are first analysed over time to test the presence of long-term monotonic trends. 3D simulations are then exploited to highlight the presence of spatial heterogeneity. The analyses show that climate change has strongly impacted the thermal regime of the study site. Its response is highly correlated with three meteorological variables: air temperature, solar radiation, and wind speed. Mean annual water temperature shows a considerable warming trend of 0.6 ∘C per decade, accompanied by longer stratification and by an increase in thermal energy favourable to cyanobacteria proliferation. The strengthening of thermal conditions favourable for cyanobacteria is particularly strong during spring and summer, while stratification increases especially during spring and autumn. The 3D analysis allows us to detect a sharp separation between deeper and shallower portions of the basin in terms of stratification dynamics and potential cyanobacteria production. This induces highly dynamic patterns in space and time within the study site that are particularly favourable to cyanobacteria growth and bloom initiation.

Lakes are of fundamental importance in the Earth system as they support essential environmental and economic services, such as freshwater supply. Streamflow variability and temporal evolution are impacted by the presence of lakes in the river network; therefore, any change in the lake state can induce a modification of the regional hydrological regime. Despite the importance of the impact of lakes on hydrological fluxes and the water balance, a representation of the mass budget is generally not included in climate models and global-scale hydrological modeling platforms. The goal of this study is to introduce a new lake mass module, MLake (Mass-Lake model), into the river-routing model CTRIP to resolve the specific mass balance of open-water bodies. Based on the inherent CTRIP parameters, the development of the non-calibrated MLake model was introduced to examine the influence of such hydrological buffer areas on global-scale river-routing performance. In the current study, an offline evaluation was performed for four river networks using a set of state-of-the-art quality atmospheric forcings and a combination of in situ and satellite measurements for river discharge and lake level observations. The results reveal a general improvement in CTRIP-simulated discharge and its variability, while also generating realistic lake level variations. MLake produces more realistic streamflows both in terms of daily and seasonal correlation. Excluding the specific case of Lake Victoria having low performances, the mean skill score of Kling–Gupta efficiency (KGE) is 0.41 while the normalized information contribution (NIC) shows a mean improvement of 0.56 (ranging from 0.15 to 0.94). Streamflow results are spatially scale-dependent, with better scores associated with larger lakes and increased sensitivity to the width of the lake outlet. Regarding lake level variations, results indicate a good agreement between observations and simulations with a mean correlation of 0.56 (ranging from 0.07 to 0.92) which is linked to the capability of the model to retrieve seasonal variations. Discrepancies in the results are mainly explained by the anthropization of the selected lakes, which introduces high-frequency variations in both streamflows and lake levels that degraded the scores. Anthropization effects are prevalent in most of the lakes studied, but they are predominant for Lake Victoria and are the main cause for relatively low statistical scores for the Nile River However, results on the Angara and the Neva rivers also depend on the inherent gap of ISBA-CTRIP process representation, which relies on further development such as the partitioned energy budget between the snow and the canopy over a boreal zone. The study is a first step towards a global coupled land system that will help to qualitatively assess the evolution of future global water resources, leading to improvements in flood risk and drought forecasting.

This paper describes the impact of the various changes made to the Safran–Isba–Modcou (SIM) hydrometeorological system and demonstrates that the new version of the model performs better than the previous one by making comparisons with observations of daily river flows and snow depths. SIM was developed and put into operational service at Météo-France in the early 2000s. The SIM application is dedicated to the monitoring of water resources and can therefore help in drought monitoring or flood risk forecasting on French territory. This complex system combines three models: SAFRAN, which analyses meteorological variables close to the surface, the ISBA land surface model, which aims to calculate surface fluxes at the interface with the atmosphere and ground variables, and finally MODCOU, a hydrogeological model which calculates river flows and changes in groundwater levels. The SIM model has been improved first by reducing the infrared radiation bias of SAFRAN and then by using the more advanced ISBA multi-layer surface diffusion scheme to have a more physical representation of surface and ground processes. In addition, more accurate and recent databases of vegetation, soil texture, and orography were used. Finally, in mountainous areas, a sub-grid orography representation using elevation bands was adopted, as was the possibility of adding a reservoir to represent the effect of aquifers in mountainous areas. The numerical simulations carried out with the SIM model covered the period from 1958 to 2018, thereby providing an extensive historical analysis of the water resources over France.

The new AquiFR hydrometeorological modelling platform was developed to provide short-to-long-term forecasts for groundwater resource management in France. This study aims to describe and assess this new tool over a long period of 60 years. This platform gathers in a single numerical tool several hydrogeological models covering much of the French metropolitan area. A total of 11 aquifer systems are simulated through spatially distributed models using either the MARTHE (Modélisation d'Aquifères avec un maillage Rectangulaire, Transport et HydrodynamiquE; Modelling Aquifers with Rectangular cells, Transport and Hydrodynamics) groundwater modelling software programme or the EauDyssée hydrogeological platform. A total of 23 karstic systems are simulated by a lumped reservoir approach using the EROS (Ensemble de Rivières Organisés en Sous-bassins; set of rivers organized in sub-basins) software programme. AquiFR computes the groundwater level, the groundwater–surface-water exchanges and the river flows. A simulation covering a 60-year period from 1958 to 2018 is achieved in order to evaluate the performance of this platform. The 8 km resolution SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) meteorological analysis provides the atmospheric variables needed by the SURFEX (SURFace EXternalisée) land surface model in order to compute surface runoff and groundwater recharge used by the hydrogeological models. The assessment is based on more than 600 piezometers and more than 300 gauging stations corresponding to simulated rivers and outlets of karstic systems. For the simulated piezometric heads, 42 % and 60 % of the absolute biases are lower than 2 and 4 m respectively. The standardized piezometric level index (SPLI) was computed to assess the ability of AquiFR to identify extreme events such as groundwater floods or droughts in the long-term simulation over a set of piezometers used for groundwater resource management. A total of 56 % of the Nash–Sutcliffe efficiency (NSE; Ef) coefficient calculations between the observed and simulated SPLI time series are greater than 0.5. The quality of the results makes it possible to consider using the platform for real-time monitoring and seasonal forecasts of groundwater resources as well as for climate change impact assessments.

In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the interactions between soil–biosphere–atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth). A sensitivity test of the Jacobians over 2000–2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM) from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A comprehensive evaluation of the assimilation impact is conducted using (i) agricultural statistics over France, (ii) river discharge observations, (iii) satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project and (iv) spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

The transfer of photosynthetically produced organic carbon from surface to mesopelagic waters draws carbon dioxide from the atmosphere1. However, current observation-based estimates disagree on the strength of this biological carbon pump (BCP)2. Earth system models (ESMs) also exhibit a large spread of BCP estimates, indicating limited representations of the known carbon export pathways3. Here we use several decades of hydrographic observations to produce a top-down estimate of the strength of the BCP with an inverse biogeochemical model that implicitly accounts for all known export pathways. Our estimate of total organic carbon (TOC) export at 73.4 m (model euphotic zone depth) is 15.00 ± 1.12 Pg C year-1, with only two-thirds reaching 100 m depth owing to rapid remineralization of organic matter in the upper water column. Partitioned by sequestration time below the euphotic zone, τ, the globally integrated organic carbon production rate with τ > 3 months is 11.09 ± 1.02 Pg C year-1, dropping to 8.25 ± 0.30 Pg C year-1 for τ > 1 year, with 81% contributed by the non-advective-diffusive vertical flux owing to sinking particles and vertically migrating zooplankton. Nevertheless, export of organic carbon by mixing and other fluid transport of dissolved matter and suspended particles remains regionally important for meeting the respiratory carbon demand. Furthermore, the temperature dependence of the sequestration efficiency inferred from our inversion suggests that future global warming may intensify the recycling of organic matter in the upper ocean, potentially weakening the BCP.

In this study we analyzed how an improved representation of snowpack processes and soil properties in the multilayer snow and soil schemes of the Interaction Soil-Biosphere-Atmosphere (ISBA) land surface model impacts the simulation of soil temperature profiles over northern Eurasian regions. For this purpose, we refine ISBA's snow layering algorithm and propose a parameterization of snow albedo and snow compaction/densification adapted from the detailed Crocus snowpack model. We also include a dependency on soil organic carbon content for ISBA's hydraulic and thermal soil properties. First, changes in the snowpack parameterization are evaluated against snow depth, snow water equivalent, surface albedo, and soil temperature at a 10 cm depth observed at the Col de Porte field site in the French Alps. Next, the new model version including all of the changes is used over northern Eurasia to evaluate the model's ability to simulate the snow depth, the soil temperature profile, and the permafrost characteristics. The results confirm that an adequate simulation of snow layering and snow compaction/densification significantly impacts the snowpack characteristics and the soil temperature profile during winter, while the impact of the more accurate snow albedo computation is dominant during the spring. In summer, the accounting for the effect of soil organic carbon on hydraulic and thermal soil properties improves the simulation of the soil temperature profile. Finally, the results confirm that this last process strongly influences the simulation of the permafrost active layer thickness and its spatial distribution.

SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D runs) or in coupled mode (from mesoscale models to numerical weather prediction and climate models). An assimilation mode is included for numerical weather prediction and monitoring. In addition to momentum, heat and water fluxes, SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. The main principles of the organisation of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally, the main applications of the code are summarised. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage.

The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1 km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and normalized difference vegetation index (NDVI) from SPOT/Vegetation (a global monitoring system of vegetation) yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 plant functional types (PFTs) representing generic vegetation types – principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land – as incorporated by the SVAT model ISBA (Interactions Surface Biosphere Atmosphere) developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land occupation nomenclatures.

Detailed studies of snow cover processes require models that offer a fine description of the snow cover properties. The detailed snowpack model Crocus is such a scheme, and has been run operationally for avalanche forecasting over the French mountains for 20 yr. It is also used for climate or hydrological studies. To extend its potential applications, Crocus has been recently integrated within the framework of the externalized surface module SURFEX. SURFEX computes the exchanges of energy and mass between different types of surface and the atmosphere. It includes in particular the land surface scheme ISBA (Interactions between Soil, Biosphere, and Atmosphere). It allows Crocus to be run either in stand-alone mode, using a time series of forcing meteorological data or in fully coupled mode (explicit or fully implicit numerics) with atmospheric models ranging from meso-scale models to general circulation models. This approach also ensures a full coupling between the snow cover and the soil beneath. Several applications of this new simulation platform are presented. They range from a 1-D stand-alone simulation (Col de Porte, France) to fully-distributed simulations in complex terrain over a whole mountain range (Massif des Grandes Rousses, France), or in coupled mode such as a surface energy balance and boundary layer simulation over the East Antarctic Ice Sheet (Dome C).

A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France) is used to simulate photosynthesis and Leaf Area Index (LAI) in southwestern France for a 3-year period (2001–2003). A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the interannual variability of LAI at a regional scale, is assessed with satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and two products are based on MODIS data. The comparison reveals discrepancies between the satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops than the satellite observations, which may be due to a saturation effect within the satellite signal or to uncertainties in model parameters. The simulated leaf onset presents a significant delay for C3 crops and mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

The sensitivity of an operational CO2-responsive land surface model (the ISBA-A-gs model of Météo-France) to the atmospheric CO2 concentration, (CO2), is investigated for 3 vegetation types (winter wheat, irrigated maize, coniferous forest). Past (1960) and future (2050) scenarios of (CO2) corresponding to 320 ppm and 550 ppm, respectively, are explored. The sensitivity study is performed for 4 annual cycles presenting contrasting conditions of precipitation regime and air temperature, based on continuous measurements performed on the SMOSREX site near Toulouse, in southwestern France. A significant CO2-driven reduction of canopy conductance is simulated for the irrigated maize and the coniferous forest. The reduction is particularly large for maize, from 2000 to 2050 (−18%), and triggers a drop in optimum irrigation (−30 mm y−1). In the case of wheat, the response is more complex, with an equal occurrence of enhanced or reduced canopy conductance.

A soil-vegetation-atmosphere transfer model coupled with a macroscale distributed hydrological model was used to simulate the water cycle for a large region in Bulgaria. To do so, an atmospheric forcing was built for two hydrological years (1 October 1995 to 30 September 1997), at an eight km resolution. The impact of the human activities on the rivers (especially hydropower or irrigation) was taken into account. An improvement of the hydrometeorological model was made: for better simulation of summer riverflow, two additional reservoirs were added to simulate the slow component of the runoff. Those reservoirs were calibrated using the observed data of the 1st year, while the 2nd year was used for validation. 56 hydrologic stations and 12 dams were used for the model calibration while 41 river gauges were used for the validation of the model. The results compare well with the daily-observed discharges, with good results obtained over more than 25% of the river gauges. The simulated snow depth was compared to daily measurements at 174 stations and the evolution of the snow water equivalent was validated at 5 sites. The process of melting and refreezing of snow was found to be important in this region. The comparison of the normalized values of simulated versus measured soil moisture showed good correlation. The surface water budget shows large spatial variations due to the elevation influence on the precipitation, soil properties and vegetation variability. An inter-annual difference was observed in the water cycle as the first year was more influenced by Mediterranean climate, while the second year was characterised by continental influence. The energy budget shows a dominating sensible heat component in summer, due to the fact that the water stress limits the evaporation. This study is a first step for the implementation of an operational hydrometeorological model that could be used for real time monitoring and forecasting of water budget components and river flow in Bulgaria.

Background: Positive and Negative Syndrome Scale (PANSS) data from a pivotal phase 3 study in participants with schizophrenia of RBP-7000, a recently marketed long-acting subcutaneous injectable risperidone formulation, were examined to determine if dose-response relationships existed for different items of the PANSS. Methods: Changes in the 30 PANSS items were analyzed individually and using the 5 factor-analysis-derived dimensions defined by Marder and colleagues. Subgroups of patients who could benefit from the RBP-7000 120 mg dose were investigated. Results: 337 participants were randomized and received study medication (RBP-7000 90 mg n = 111, RBP-7000 120 mg n = 114, placebo n = 112). Dose-dependent responses were observed in items from the study-specified PANSS positive and general psychopathology exploratory subscales. Dose-dependent responses were observed across all 5 Marder dimensions, with the largest effect sizes observed with the 120 mg dose in the uncontrolled hostility/excitement (UHE) and anxiety/depression dimensions. Participants with baseline UHE dimension scores ≥ 9 demonstrated greater improvement in PANSS total score at the 120 mg dose compared to the 90 mg dose. Conclusions: RBP-7000 demonstrated efficacy across both the primary and exploratory PANSS study endpoints and the post hoc Marder dimensions. Schizophrenia patients with higher baseline Marder UHE scores may benefit from initiation of treatment at the 120 mg dose. Trial Registration: ClinicalTrials.gov identifier: NCT02109562.

B acute lymphoblastic leukemia (B-ALL) cells are distinctively vulnerable to endoplasmic reticulum (ER) stress. Recently, inhibition of p97 was shown to induce ER stress and subsequently cell death in solid tumors and in multiple myeloma. We investigated the role of a novel, orally available, p97 inhibitor (CB-5083; Cleave Biosciences) in B-ALL. CB-5083 induced a significant reduction in viability in 10 human B-ALL cell lines, harboring the most common fusion-genes involved in pediatric and adult B-ALL, with IC50s ranging from 0.34 to 0.76 μM. Moreover, CB-5083 significantly reduced the colony formation of OP1 and NALM6 cells. Early and strong induction of apoptosis was demonstrated in BALL1 and OP1 cells, together with a robust cleavage of PARP. CB-5083 induced ER stress, as documented through: 1) prominent expression of chaperones (GRP78, GRP94, PDI, DNAJC3, and DNAJB9); 2) increased activation of IRE1-alpha, as demonstrated by the splicing of XBP1; and 3) activation of PERK, which resulted in a significant overexpression of CHOP, and its downstream genes. CB-5083 reduced the viability also in GRP78-/-, GRP94-/-, and XBP1-/- cells, suggesting that none of these proteins alone was strictly required for CB-5083 activity. Moreover, we showed that the absence of XBP1 (XBP1-/-) increased the sensitivity to CB-5083, leading to the hypothesis that XBP1 splicing counteracts the activity of CB-5083, probably mitigating ER stress. Finally, vincristine was synergistic with CB-5083 in both BALL1 and OP1 cells. In summary, the targeting of p97 with CB-5083 is a novel promising therapeutic approach that should be further evaluated in B-ALL.

To better appreciate the contribution of the "paradigm of complexity" in Educational sciences, this paper proposes a framework discussing its cultural and historical roots. First, it focuses on Giambattista Vico's (1668-1744) critique of René Descartes' method (1637), contrasting Cartesian's principles (evidence, disjunction, linear causality and enumeration), with the open rationality of the "ingenium" (capacity to establish relationships and contextualize). Acknowledging the teleological character of scientific inquiry (Bachelard) and the inseparability between "subject" and "object", the second part of the text explores the relevance of "designo" (intentional design) implemented by Leonardo da Vinci (1453-1519) in order to identify and formulate problems encountered by researchers. Referring to contemporary epistemologists (Bachelard, Valéry, Simon, Morin), this contribution finally questions the relationships between the "ingenio" (pragmatic intelligence), the "designo" (modeling method) and ethics. It proposes one to conceive the paradigm of complexity through the relationships it establishes between (pragmatic) action, (epistemic) reflection and meditation (ethics).

p97 is a AAA-ATPase with multiple cellular functions, one of which is critical regulation of protein homeostasis pathways. We describe the characterization of CB-5083, a potent, selective, and orally bioavailable inhibitor of p97. Treatment of tumor cells with CB-5083 leads to accumulation of poly-ubiquitinated proteins, retention of endoplasmic reticulum-associated degradation (ERAD) substrates, and generation of irresolvable proteotoxic stress, leading to activation of the apoptotic arm of the unfolded protein response. In xenograft models, CB-5083 causes modulation of key p97-related pathways, induces apoptosis, and has antitumor activity in a broad range of both hematological and solid tumor models. Molecular determinants of CB-5083 activity include expression of genes in the ERAD pathway, providing a potential strategy for patient selection.

The article focuses on how capitalist restructurings since the early 1970s have led to the urban landscape's transformation and shifts in power dynamics between Black and Latino populations in South Central Los Angeles, California on the retreat of the welfare state driven by neoliberal policies.

Background: Admission to the hospital is a major risk factor for the development of venous thromboembolism (VTE). Whether thromboprophylaxis with low-molecular-weight heparin prevents symptomatic VTE in medically ill, hospitalized older adults remains debated. Methods: In a prospective, randomized, placebo-controlled, double-blind, multicenter trial, older adults (>70 years of age) hospitalized for acute medical conditions were randomly assigned to receive 40 mg a day of low-molecular-weight heparin (enoxaparin) or placebo for 6 to 14 days. The primary efficacy outcome was the cumulative incidence of symptomatic VTE (distal or proximal deep vein thrombosis, fatal or nonfatal pulmonary embolism) at 30 days. The primary safety outcome was major bleeding. Secondary outcomes included efficacy and safety outcomes at 90 days. Results: The trial was prematurely discontinued in September 2020, 5 years after enrollment began, because of drug supply issues. By the time of trial discontinuation, 2559 patients had been randomly assigned at 47 centers. Median age was 82 years and 60% of patients were female. In the intention-to-treat population, the primary efficacy outcome occurred in 22 out of 1278 (cumulative incidence, 1.8%) patients in the enoxaparin group and in 27 out of 1263 (cumulative incidence, 2.2%) patients in the placebo group (cumulative incidence difference, -0.4 percentage points; 95% confidence interval, -1.5 to 0.7), with no significant difference in time to VTE (P=0.46). The incidence of major bleeding was 0.9% in the enoxaparin group and 1.0% in the placebo group. At 90 days there were 14 symptomatic pulmonary emboli in the enoxaparin group and 25 in the placebo group; all 39 pulmonary embolism events resulted in hospital readmission and/or death, with 5 deaths from pulmonary embolism in the enoxaparin group and 11 deaths in the placebo group. Conclusions: This trial of thromboprophylaxis in medically ill, hospitalized older adults did not demonstrate that enoxaparin reduced the risk of symptomatic VTE after 1 month. Because the trial was prematurely discontinued, larger trials are needed to definitively address this question. (Funded by the French Ministry of Health Programme Hospitalier de Recherche Clinique, grant number PHRC-N-13-0283; ClinicalTrials.gov number, NCT02379806.) [ABSTRACT FROM AUTHOR]

Objectives: Individuals in recovery from opioid use disorder (OUD) are vulnerable to the impacts of the COVID-19 pandemic. Recent findings suggest increased relapse risk and overdose linked to COVID-19–related stressors. We aimed to identify individual-level factors associated with COVID-19–related impacts on recovery. Methods: This observational study (NCT04577144) enrolled 216 participants who previously partook in long-acting buprenorphine subcutaneous injection clinical trials (2015–2017) for OUD. Participants indicated how COVID-19 affected their recovery from substance use. A machine learning approach Classification and Regression Tree analysis examined the association of 28 variables with the impact of COVID-19 on recovery, including demographics, substance use, and psychosocial factors. Ten-fold cross-validation was used to minimize overfitting. Results: Twenty-six percent of the sample reported that COVID-19 had made recovery somewhat or much harder. Past-month opioid use was higher among those who reported that recovery was harder compared with those who did not (51% vs 24%, respectively; P < 0.001). The final classification tree (overall accuracy, 80%) identified the Beck Depression Inventory (BDI-II) as the strongest independent risk factor associated with reporting COVID-19 impact. Individuals with a BDI-II score ≥10 had 6.45 times greater odds of negative impact (95% confidence interval, 3.29–13.30) relative to those who scored <10. Among individuals with higher BDI-II scores, less progress in managing substance use and treatment of OUD within the past 2 to 3 years were also associated with negative impacts. Conclusions: These findings underscore the importance of monitoring depressive symptoms and perceived progress in managing substance use among those in recovery from OUD, particularly during large-magnitude crises. [ABSTRACT FROM AUTHOR]