Current side-channel evaluation methodologies exhibit a gap between inefficient tools offering strong theoretical guarantees and efficient tools only offering heuristic (sometimes case-specific) ...guarantees. Profiled attacks based on the empirical leakage distribution correspond to the first category. Bronchain et al. showed at Crypto 2019 that they allow bounding the worst-case security level of an implementation, but the bounds become loose as the leakage dimensionality increases. Template attacks and machine learning models are examples of the second category. In view of the increasing popularity of such parametric tools in the literature, a natural question is whether the information they can extract can be bounded.In this paper, we first show that a metric conjectured to be useful for this purpose, the hypothetical information, does not offer such a general bound. It only does when the assumptions exploited by a parametric model match the true leakage distribution. We therefore introduce a new metric, the training information, that provides the guarantees that were conjectured for the hypothetical information for practically-relevant models. We next initiate a study of the convergence rates of profiled side-channel distinguishers which clarifies, to the best of our knowledge for the first time, the parameters that influence the complexity of a profiling. On the one hand, the latter has practical consequences for evaluators as it can guide them in choosing the appropriate modeling tool depending on the implementation (e.g., protected or not) and contexts (e.g., granting them access to the countermeasures’ randomness or not). It also allows anticipating the amount of measurements needed to guarantee a sufficient model quality. On the other hand, our results connect and exhibit differences between side-channel analysis and statistical learning theory.
A recent study suggests that arithmetic masking in prime fields leads to stronger security guarantees against passive physical adversaries than Boolean masking. Indeed, it is a common observation ...that the desired security amplification of Boolean masking collapses when the noise level in the measurements is too low. Arithmetic encodings in prime fields can help to maintain an exponential increase of the attack complexity in the number of shares even in such a challenging context. In this work, we contribute to this emerging topic in two main directions. First, we propose novel masked hardware gadgets for secure squaring in prime fields (since squaring is non-linear in non-binary fields) which prove to be significantly more resource-friendly than corresponding masked multiplications. We then formally show their local and compositional security for arbitrary orders. Second, we attempt to >experimentally evaluate the performance vs. security tradeoff of prime-field masking. In order to enable a first comparative case study in this regard, we exemplarily consider masked implementations of the AES as well as the recently proposed AESprime. AES-prime is a block cipher partially resembling the standard AES, but based on arithmetic operations modulo a small Mersenne prime. We present cost and performance figures for masked AES and AES-prime implementations, and experimentally evaluate their susceptibility to low-noise side-channel attacks. We consider both the dynamic and the static power consumption for our low-noise analyses and emulate strong adversaries. Static power attacks are indeed known as a threat for side-channel countermeasures that require a certain noise level to be effective because of the adversary’s ability to reduce the noise through intra-trace averaging. Our results show consistently that for the noise levels in our practical experiments, the masked prime-field implementations provide much higher security for the same number of shares. This compensates for the overheads prime computations lead to and remains true even if / despite leaking each share with a similar Signal-to-Noise Ratio (SNR) as their binary equivalents. We hope our results open the way towards new cipher designs tailored to best exploit the advantages of prime-field masking.
Plants protect themselves against herbivore attacks with physical traits and toxic secondary metabolites. Levels of plant defences and herbivore performance might shift under climate warming, ...particularly in alpine habitats, where herbivore pressure is currently low. Plant responses to warming should be driven by species‐specific shifts in physical and chemical defence traits.
We investigated the association between plant leaf physical and chemical traits and herbivory under current and warmer climates in three grasslands along a subalpine to alpine gradient. Specifically, we measured the rate of in situ natural herbivory, and performed bioassays to measure overall plant species‐level resistance using the extreme generalist non‐native caterpillar Spodoptera littoralis. We simulated warmer conditions by using open‐top chambers and assessed the effect of warming on leaf physical and chemical traits, and how trait changes affect caterpillar performance.
Natural herbivory and caterpillar performance were associated with plant physical traits, including specific leaf area, and with ordination axes representing dimensions of the plant chemical profile. We found that the warming treatment independently decreased the number of distinct chemical compounds per species, and marginally increased specific leaf area. Changes in leaf functional traits were not systematically associated with changes in caterpillar performance.
Synthesis. Plant physical traits and chemical profiles are both related to natural herbivory and plant resistance against Spodoptera littoralis. While leaf physical and chemical traits of high elevation plants were modified by the warming treatment, these changes did not result in predictable effects on plant resistance against herbivores.
This study shows associations between leaf physical and chemical traits and herbivory in subalpine and alpine grasslands, and underlines the importance of plant secondary metabolites in mediating herbivore preferences and performances under current and future climate conditions.
Rationale: Early empirical antimicrobial treatment is frequently prescribed to critically ill patients with coronavirus disease (COVID-19) based on Surviving Sepsis Campaign guidelines. Objectives: ...We aimed to determine the prevalence of early bacterial identification in intubated patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia, as compared with influenza pneumonia, and to characterize its microbiology and impact on outcomes. Methods: A multicenter retrospective European cohort was performed in 36 ICUs. All adult patients receiving invasive mechanical ventilation >48 hours were eligible if they had SARS-CoV-2 or influenza pneumonia at ICU admission. Bacterial identification was defined by a positive bacterial culture within 48 hours after intubation in endotracheal aspirates, BAL, blood cultures, or a positive pneumococcal or legionella urinary antigen test. Measurements and Main Results: A total of 1,050 patients were included (568 in SARS-CoV-2 and 482 in influenza groups). The prevalence of bacterial identification was significantly lower in patients with SARS-CoV-2 pneumonia compared with patients with influenza pneumonia (9.7 vs. 33.6%; unadjusted odds ratio, 0.21; 95% confidence interval CI, 0.15-0.30; adjusted odds ratio, 0.23; 95% CI, 0.16-0.33; P < 0.0001). Gram-positive cocci were responsible for 58% and 72% of coinfection in patients with SARS-CoV-2 and influenza pneumonia, respectively. Bacterial identification was associated with increased adjusted hazard ratio for 28-day mortality in patients with SARS-CoV-2 pneumonia (1.57; 95% CI, 1.01-2.44; P = 0.043). However, no significant difference was found in the heterogeneity of outcomes related to bacterial identification between the two study groups, suggesting that the impact of coinfection on mortality was not different between patients with SARS-CoV-2 and influenza. Conclusions: Bacterial identification within 48 hours after intubation is significantly less frequent in patients with SARS-CoV-2 pneumonia than patients with influenza pneumonia.Clinical trial registered with www.clinicaltrials.gov (NCT 04359693).
Net soil N mineralization is a driver for N uptake and N losses at an annual scale, but is itself dependent on long-term N surplus and C-N storage in agricultural systems. The accurate modelling of N ...mineralization remains challenging. Thus, the STICS research version V1610 that includes modified soil organic nitrogen (SON) mineralization and root biomass turnover modules was assessed in this study regarding its predictions of net N mineralization and long-term N fate in a 34-year experiment comparing crop rotations with or without catch crops (CC) and bare soil. The in situ gross balance method was used as a reference to estimate net N mineralization based on measured N variables (i.e. N uptake, exported N and N leaching). The Index of Agreement (IA) of STICS predictions concerning crop biomass, crop yield, N uptake and exported N ranged between 0.61 and 0.76, 0.79–0.89, 0.49–0.64 and 0.47–0.58, respectively, depending on the crop rotations. STICS also enabled a good simulation of annual drainage and N leaching with IA ranges of 0.92–0.96 and 0.78–0.93, but high leaching values were not captured by the model. The STICS research version simulates the decay of deep roots (below a depth of 25 cm) but it neglects their decomposition. This simplification could cause an underestimation of N leaching. The observed N surplus ranged from 27 to 51 kg N ha−1 yr−1 in the cropped rotations depending on the crop rotations, and the N surplus was accurately simulated with an IA of 0.75–0.84. STICS produced a good prediction of changes in SON stocks under cropped rotations and bare soil, with both the rRMSE and rMBE being lower than 10%. Estimated mean annual N mineralization was 115 kg N ha−1 under cropped rotations and 42 kg N ha−1 under the bare soil treatment. STICS relatively well predicted net N mineralization regarding both differences between crop rotations and over time. Moreover, STICS correctly simulated the long-term effects of CC on drainage, N leaching, SON accumulation and net N mineralization. To conclude, STICS is a useful model to predict net N mineralization and N fate in long-term crop rotations. Moreover, this work raised new questions concerning the long-term fate of N stored in deep dead roots. Further improvements to describe the fate of these residues should enhance the prediction of N leaching by the STICS model and enable the optimization of N management in cropping systems.-
•STICS well simulated N uptake, grain N and N leaching in long term crop rotations.•STICS well predicted soil organic nitrogen stocks and net N mineralization.•STICS captured the long-term catch crops effects on N leaching and N mineralization.•STICS is a useful tool to predict N mineralization and N fate in crop rotations.
Theory predicts that a large fraction of phytochemical diversity—the richness of individual chemical compounds produced by plants—governs the complexity of interactions between plants and their ...herbivores. While the effect of specific classes of chemical compounds on plant resistance against herbivores has been largely documented, the effect of community‐level variation in phytochemical diversity on plant–herbivore interactions has so far received minimal consideration.
We hypothesized that plant communities bearing on average higher levels of phytochemical diversity should sustain lower herbivory rates, overall. Yet, the magnitude of this effect could vary across different environmental conditions, potentially because of climate‐mediated effects on phytochemical production and changes in herbivore community richness and composition.
To address these hypotheses, we used previous knowledge of species‐level phytochemical make‐up for more than 400 plant species of the Swiss Alps. Using common garden experiments, we estimated season‐wide herbivore damage on low (average 3,500 unique molecules) and high (average 4,500 unique molecules) phytochemical diversity plant communities that were planted in the colline, mountain and alpine vegetation sites along two elevation transects in the Alps.
We found that high phytochemical diversity plant communities showed reduced levels of herbivore damage in the colline (low elevation) sites, but this pattern reversed in the alpine (high elevation) sites. Our results suggest that the outcome of phytochemical diversity on plant–herbivore interactions depends on the characteristics of the local herbivore communities, together with trade‐offs between chemical defences and other plant traits (i.e. physical defences and plant palatability).
Synthesis. Phytochemical diversity is a key component of functional diversity, influencing community composition and dynamics. We show that the effect of phytochemical diversity on herbivory is environmental‐dependent, generating ecological switches when moving from low to high elevation. Through upward movement of plants under climate change, phytochemical community structure will be likely modified, ultimately disrupting local community assembly processes.
Phytochemical diversity is a key component of functional diversity, influencing community composition and dynamics. We show that the effect of phytochemical diversity on herbivory is environmental‐dependent, generating ecological switches when moving from low to high elevation. Through upward movement of plants under climate change, phytochemical community structure will be likely modified, ultimately disrupting local community assembly processes.
Several studies report an increased susceptibility to SARS-CoV-2 infection in cancer patients. However, data in the intensive care unit (ICU) are scarce.
We aimed to investigate the association ...between active cancer and mortality among patients requiring organ support in the ICU.
In this ambispective study encompassing 17 hospitals in France, we included all adult active cancer patients with SARS-CoV-2 infection requiring organ support and admitted in ICU. For each cancer patient, we included 3 non cancer patients as controls. Patients were matched at the same ratio using the inverse probability weighting approach based on a propensity score assessing the probability of cancer at admission. Mortality at day 60 after ICU admission was compared between cancer patients and non-cancer patients using primary logistic regression analysis and secondary multivariable analyses.
Between March 12, 2020 and March 8, 2021, 2608 patients were admitted with SARS-CoV-2 infection in our study, accounting for 2.8% of the total population of patients with SARS-CoV-2 admitted in all French ICUs within the same period. Among them, 105 (n=4%) presented with cancer (51 patients had hematological malignancy and 54 patients had solid tumors). 409 of 420 patients were included in the propensity score matching process, of whom 307 patients in the non-cancer group and 102 patients in the cancer group. 145 patients (35%) died in the ICU at day 60, 59 (56%) with cancer and 86 (27%) without cancer. In the primary logistic regression analysis, the odds ratio for death associated to cancer was 2.3 (95%CI 1.24 - 4.28, p=0.0082) higher for cancer patients than for a non-cancer patient at ICU admission. Exploratory multivariable analyses showed that solid tumor (OR: 2.344 (0.87-6.31), p=0.062) and hematological malignancies (OR: 4.144 (1.24-13.83), p=0.062) were independently associated with mortality.
Patients with cancer and requiring ICU admission for SARS-CoV-2 infection had an increased mortality, hematological malignancy harboring the higher risk in comparison to solid tumors.
Background and Objective
EpiGETIF is a web‐based, multicentre clinical database created in 2019 aiming for prospective collection of data regarding therapeutic rigid bronchoscopy (TB) for malignant ...central airway obstruction (MCAO).
Methods
Patients were enrolled into the registry from January 2019 to November 2022. Data were prospectively entered through a web‐interface, using standardized definitions for each item. The objective of this first extraction of data was to describe the population and the techniques used among the included centres to target, facilitate and encourage further studies in TB.
Results
Overall, 2118 patients from 36 centres were included. Patients were on average 63.7 years old, mostly male and smokers. Most patients had a WHO score ≤2 (70.2%) and 39.6% required preoperative oxygen support, including mechanical ventilation in 6.7%. 62.4% had an already known histologic diagnosis but only 46.3% had received any oncologic treatment. Most tumours were bronchogenic (60.6%), causing mainly intrinsic or mixed obstruction (43.3% and 41.5%, respectively). Mechanical debulking was the most frequent technique (67.3%), while laser (9.8%) and cryo‐recanalization (2.7%) use depended on local expertise. Stenting was required in 54.7%, silicone being the main type of stent used (55.3%). 96.3% of procedure results were considered at least partially successful, resulting in a mean 4.1 points decrease on the Borg scale of dyspnoea. Complications were noted in 10.9%.
Conclusion
This study exposes a high volume of TB that could represent a good source of future studies given the dismal amount of data about the effects of TB in certain populations and situations.
The EpiGETIF registry has so far prospectively collected data from 2118 patients treated with therapeutic rigid bronchoscopy (TB) for malignant central airway obstruction (MCAO). This first report gives a picture of this population's epidemiological characteristics', anatomical presentations of MCAOs, techniques used during TB and main outcomes.
See related editorial
Predicting variation in plant functional traits related to anti-herbivore defences remains a major challenge in ecological research, considering that multiple traits have evolved in response to both ...abiotic and biotic conditions. Therefore, understanding variation in plant anti-herbivore defence traits requires studying their expression along steep environmental gradients, such as along elevation, where multiple biotic and abiotic factors co-vary. We expand on plant defence theory and propose a novel conceptual framework to address the sources of variations of plant resistance traits at the community level. We analysed elevation patterns of within-community trait dissimilarity using the RaoQ index, and the community-weighted-mean (CWM) index, on several plant functional traits: plant height, specific leaf area (SLA), leaf-dry-matter-content (LDMC), silicium content, presence of trichomes, carbon-to-nitrogen ratio (CN) and total secondary metabolite richness. We found that at high elevation, where harsh environmental conditions persist, community functional convergence is dictated by traits relating to plant growth (plant height and SLA), while divergence arises for traits relating resource-use (LDMC). At low elevation, where greater biotic pressure occurs, we found a combination of random (plant height), convergence (metabolite richness) and divergence patterns (silicium content). This framework thus combines community assembly rules of ecological filtering and niche partition with plant defence hypotheses to unravel the relationship between environmental variations, biotic pressure and the average phenotype of plants within a community.
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