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Animals occupying higher trophic levels can have disproportionately large influence on ecosystem structure and functioning, owning to intricate behavioral responses to their environment, but the effects of behavioral adaptations on aquatic ecosystem dynamics are underrepresented, especially in model studies. Here, we explore how adaptive behavior of fish can affect the dynamics of aquatics ecosystems. We frame fish behavior in the context of the central trade‐off between feeding and predation, calculating the optimal level of feeding determined by ambient food availability and predation risk. To explore whole‐ecosystem consequences of fish behavior, we embed our behavioral model within the Water Ecosystems Tool (WET), a contemporary end‐to‐end aquatic ecosystem model. The principle of optimality provides a robust and mechanistic framework for representing animal behavior that is relevant for complex models, and can provide a stabilizing effect on model dynamics. The model predicts an emergent functional response similar to Holling type III, but with richer dynamics and a more rigorous theoretical foundation. We show how adaptive fish behavior works to stabilize food web dynamics compared to a control model with no optimal behavior, and how changing the strength of the underlying trade‐off has profound effects on trophic control and food web structure. Furthermore, we demonstrate how including fish behavior allows for an overall more realistic response of the model system to environmental perturbation in the form of nutrient enhancement. We discuss the structuring effects of behavioral adaptations in real ecosystems, and how approaches like this one may benefit aquatic ecological modeling. Our study further highlights how a mechanistic approach based on concepts from theoretical ecology can be successfully implemented in complex operational models resulting in improved dynamics and descriptive power. We investigated how the trade‐off between predator avoidance and feeding in fish can influence the function and structure of a modeled lake ecosystem. The results showcase how more realistic behavior in ecosystem models can have many benefits, including more realistic model responses to perturbation and increased model stability.

Antibodies against programmed cell death-1 (PD-1) have considerably changed the treatment for melanoma. However, many patients do not display therapeutic response or eventually relapse. Moreover, patients treated with anti-PD-1 develop immune-related adverse events that can be cured with anti-tumor necrosis factor α (TNF) antibodies. Whether anti-TNF antibodies affect the anti-cancer immune response remains unknown. Our recent work has highlighted that TNFR1-dependent TNF signalling impairs the accumulation of CD8+ tumor-infiltrating T lymphocytes (CD8+ TILs) in mouse melanoma. Herein, our results indicate that TNF or TNFR1 blockade synergizes with anti-PD-1 on anti-cancer immune responses towards solid cancers. Mechanistically, TNF blockade prevents anti-PD-1-induced TIL cell death as well as PD-L1 and TIM-3 expression. TNF expression positively correlates with expression of PD-L1 and TIM-3 in human melanoma specimens. This study provides a strong rationale to develop a combination therapy based on the use of anti-PD-1 and anti-TNF in cancer patients. Most melanoma patients do not respond to anti-PD1 therapy. Here, the authors show that TNFα blockade synergizes with anti-PD-1 by preventing anti-PD-1-induced CD8+ T cell death and TIM-3 expression on such cells.

In a randomized trial involving more than 900 patients undergoing resection of advanced melanoma, adjuvant nivolumab was associated with a higher rate of 12-month recurrence-free survival than ipilimumab (70.5% vs. 60.8%) and with fewer adverse events.

Cover crops provide many ecosystem services, such as soil protection, nitrate pollution of water mitigation, and green manure effects. However, the impact of cover crops on soil water balance is poorly studied, despite its potential impact on groundwater recharge. Some studies reported a reduction of the water drainage due to an increase of the evapotranspiration by plant cover transpiration. However, there is no real consensus on the intensity of this phenomenon, which highlights the importance to quantify the impact of cover crops on drainage compared to that of bare soil. We performed a meta-analysis of published papers presenting studies on the impact of cover crops on drainage compared to that of bare soil under temperate climates. Of the 436 papers identified, 28 of them were included in the analysis based on criteria required for performing a relevant meta-analysis. The originality of our study lies in two following results: (1) the quantification of drainage reduction with cover crops by a mean effect size of 27 mm compared to that of bare soil and (2) within the large variability of soils, climates, and cropping systems, no main determining factor was found significant to explain the variability of water drainage reduction. The cover crops provide a service of nitrate pollution mitigation, but the drainage reduction could be considered as a disservice, because they can lead to a reduction in groundwater recharge due to a higher evapotranspiration in comparison to bare soil. This highlights the need of research for optimizing trade-offs between services and disservices of cover crops for water balance.

Dabrafenib plus trametinib improves clinical outcomes in BRAFV600-mutant metastatic melanoma without brain metastases; however, the activity of dabrafenib plus trametinib has not been studied in active melanoma brain metastases. Here, we report results from the phase 2 COMBI-MB trial. Our aim was to build on the current body of evidence of targeted therapy in melanoma brain metastases through an evaluation of dabrafenib plus trametinib in patients with BRAFV600-mutant melanoma brain metastases. This ongoing, multicentre, multicohort, open-label, phase 2 study evaluated oral dabrafenib (150 mg twice per day) plus oral trametinib (2 mg once per day) in four patient cohorts with melanoma brain metastases enrolled from 32 hospitals and institutions in Europe, North America, and Australia: (A) BRAFV600E-positive, asymptomatic melanoma brain metastases, with no previous local brain therapy, and an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1; (B) BRAFV600E-positive, asymptomatic melanoma brain metastases, with previous local brain therapy, and an ECOG performance status of 0 or 1; (C) BRAFV600D/K/R-positive, asymptomatic melanoma brain metastases, with or without previous local brain therapy, and an ECOG performance status of 0 or 1; and (D) BRAFV600D/E/K/R-positive, symptomatic melanoma brain metastases, with or without previous local brain therapy, and an ECOG performance status of 0, 1, or 2. The primary endpoint was investigator-assessed intracranial response in cohort A in the all-treated-patients population. Secondary endpoints included intracranial response in cohorts B, C, and D. This study is registered with ClinicalTrials.gov, number NCT02039947. Between Feb 28, 2014, and Aug 5, 2016, 125 patients were enrolled in the study: 76 patients in cohort A; 16 patients in cohort B; 16 patients in cohort C; and 17 patients in cohort D. At the data cutoff (Nov 28, 2016) after a median follow-up of 8·5 months (IQR 5·5–14·0), 44 (58%; 95% CI 46–69) of 76 patients in cohort A achieved an intracranial response. Intracranial response by investigator assessment was also achieved in nine (56%; 95% CI 30–80) of 16 patients in cohort B, seven (44%; 20–70) of 16 patients in cohort C, and ten (59%; 33–82) of 17 patients in cohort D. The most common serious adverse events related to study treatment were pyrexia for dabrafenib (eight [6%] of 125 patients) and decreased ejection fraction (five [4%]) for trametinib. The most common grade 3 or worse adverse events, regardless of study drug relationship, were pyrexia (four [3%] of 125) and headache (three [2%]). Dabrafenib plus trametinib was active with a manageable safety profile in this melanoma population that was consistent with previous dabrafenib plus trametinib studies in patients with BRAFV600-mutant melanoma without brain metastases, but the median duration of response was relatively short. These results provide evidence of clinical benefit with dabrafenib plus trametinib and support the need for additional research to further improve outcomes in patients with melanoma brain metastases. Novartis.

Background: Immune checkpoint inhibitors (anti-PD1 or anti-CTLA-4) are increasingly used in various cancers. Immune checkpoint inhibitors (ICI)-related renal disorders are poorly described (9 cases) and were only related to Ipilimumab. Methods: Retrospective collection of clinical charts of all the patients admitted for renal disorders following ICI in the University Hospital of Toulouse (France). Results: We report on adverse renal events that occurred in three patients treated with anti-PD1 (nivolumab or pembrolizumab) or anti-CTLA-4 (ipilimumab). Acute kidney injury occurred at 4–12 weeks after initiation of treatment, and harbored features of tubulo-interstitial nephritis (interstitial polymorphic inflammatory infiltrate with predominant CD3+ CD4+ T cells, associated with granuloma in one). Following withdrawal of ICI and steroid intake, estimated glomerular-filtration rate had improved in all patients. Conclusions: These data suggest that all ICI can lead to acute interstitial nephritis, possibly related to the presence of autoreactive clonal T cells. We recommend that patients receiving ICI should undergo renal monitoring every 2 weeks for 3–6 months.

As new SARS-CoV-2 variants emerge and as treatment of COVID-19 ARDS remains exclusively supportive, there is an unmet need to better characterize its different phenotypes to tailor personalized treatments. Clinical, biological, spirometric and CT data hardly allow deciphering of Heavy (H), Intermediate (I) and Light (L) phenotypes of COVID-19 ARDS and the implementation of tailored specific strategies (prone positioning, PEEP settings, recruitment maneuvers). We hypothesized that the ratio of two pivotal COVID-19 biomarkers (interleukin 6 [IL-6] and Krebs von den Lungen 6 [KL-6], related to inflammation and pneumocyte repair, respectively) would provide a biologic insight into the disease timeline allowing 1) to differentiate H, I and L phenotypes, 2) to predict outcome and 3) to reflect some of CT findings. This was a retrospective analysis of prospectively acquired data (COVID HUS cohort). Inclusion concerned any patient with severe COVID-19 pneumonia admitted to two intensive care units between March 1st and May 1st, 2020, in a high-density cluster of the first epidemic wave (Strasbourg University Hospital, France). Demographic, clinical, biological (standard, IL-6 [new generation ELISA], KL-6 [CLEIA technique]), spirometric (driving pressure, respiratory system compliance) and CT data were collected longitudinally. CT analysis included semi-automatic and automatic lung measurements and allowed segmentation of lung volumes into 4 (poorly aerated, non-aerated, overinflated and normally aerated) and 3 (ground-glass, restricted normally aerated, and overinflated) zones, respectively. The primary outcome was to challenge the IL-6/KL-6 ratio capacity to decipher the three COVID-19 ARDS phenotypes (H, I and L) defined on clinical, spirometric and radiologic grounds. Secondary outcomes were the analysis of the prognostic value of the IL-6/KL-6 ratio and its correlates with CT-acquired data. Multivariate analysis was based on principal component analysis. One hundred and forty-eight ventilated COVID-19 ICU patients from the COVID HUS cohort were assessed for eligibility and 77 were included in the full analysis. Most were male, all were under invasive mechanical ventilation and vasopressor therapy and displayed high severity scores (SAPSII: 48 [42-56]; SOFA: 8 [7-10]). The L, I and H COVID ARDS phenotypes were identified in 11, 15 and 48 patients, respectively. In three patients, the phenotype could not be defined precisely. Thirty patients (39%) died in the ICU and the number of ventilator-free days was 2 [0-2] days. The IL-6/KL-6 ratio was not significantly different between the L, I and H phenotypes and evolved according to similar patterns over time. Surviving and deceased patients displayed an inverse kinetic of KL-6. IL-6 and the IL-6/KL-6 ratio were linearly associated with ground-glass volume on semi-automatic and automatic CT lung measurements. In our population of severe ventilated COVID ARDS patients, the IL-6/KL-6 ratio was not clue to differentiate the H, I and L phenotypes and tailor a personalized ventilatory approach. There was an interesting correlation between IL-6/KL-6 ratio and ground-glass volume as determined by automated lung CT analysis. Such correlation deserves more in-depth pathophysiological study, at best gathered from a prospective cohort with a larger sample size and histological analysis. COVID HUS Trial registration number: NCT04405726.

Immune checkpoint inhibitors (ICIs) have dramatically modified the prognosis of several advanced cancers, however many patients still do not respond to treatment. Optimal results might be obtained by targeting cancer cell metabolism to modulate the immunosuppressive tumor microenvironment. Here, we identify sphingosine kinase-1 (SK1) as a key regulator of anti-tumor immunity. Increased expression of SK1 in tumor cells is significantly associated with shorter survival in metastatic melanoma patients treated with anti-PD-1. Targeting SK1 markedly enhances the responses to ICI in murine models of melanoma, breast and colon cancer. Mechanistically, SK1 silencing decreases the expression of various immunosuppressive factors in the tumor microenvironment to limit regulatory T cell (Treg) infiltration. Accordingly, a SK1-dependent immunosuppressive signature is also observed in human melanoma biopsies. Altogether, this study identifies SK1 as a checkpoint lipid kinase that could be targeted to enhance immunotherapy. There are many patients who do not respond to immune checkpoint inhibitor (ICI) immunotherapy. Here, the authors show a significant negative correlation between sphingosine kinase-1 (SK1) expression and survival for ICI-treated melanoma patients, and further show that targeting SK1 improves response to ICI in mouse cancer models.

An unresolved issue in contemporary biomedicine is the overwhelming number and diversity of complex images that require annotation, analysis and interpretation. Recent advances in Deep Learning have revolutionized the field of computer vision, creating algorithms that compete with human experts in image segmentation tasks. However, these frameworks require large human-annotated datasets for training and the resulting “black box” models are difficult to interpret. In this study, we introduce Kartezio , a modular Cartesian Genetic Programming-based computational strategy that generates fully transparent and easily interpretable image processing pipelines by iteratively assembling and parameterizing computer vision functions. The pipelines thus generated exhibit comparable precision to state-of-the-art Deep Learning approaches on instance segmentation tasks, while requiring drastically smaller training datasets. This Few-Shot Learning method confers tremendous flexibility, speed, and functionality to this approach. We then deploy Kartezio to solve a series of semantic and instance segmentation problems, and demonstrate its utility across diverse images ranging from multiplexed tissue histopathology images to high resolution microscopy images. While the flexibility, robustness and practical utility of Kartezio make this fully explicable evolutionary designer a potential game-changer in the field of biomedical image processing, Kartezio remains complementary and potentially auxiliary to mainstream Deep Learning approaches. Deep learning frameworks require large human-annotated datasets for training and the resulting ‘black box’ models are difficult to interpret. Here, the authors present Kartezio; a modular Cartesian Genetic Programming-based computational strategy that generates fully transparent and easily interpretable image processing pipelines.