Unknown Fraction Research Articles

Validation of existing risk scores for worsening renal function in patients with newly diagnosed heart failure: a longitudinal population cohort study

Abstract Background Worsening renal function (WRF) is one of the strongest predictors of outcome in patients with heart failure (HF). The presence of WRF often influences the decision to start, up-titrate, or discontinue disease-modifying HF therapies and is one of the key determinants of suboptimal guideline-directed medical therapy. However, there are now potential cardiovascular pharmacotherapies that have favourable cardiorenal outcomes and reduce the risk of renal decline. It is therefore important to identify patients with HF early in their disease trajectory who are at risk of developing WRF. Purpose The aim of this study was to evaluate two existing WRF risk scores (the Forman risk score and the Basel risk score) in a population-based longitudinal cohort diagnosed with incident HF. Methods Data for individuals with incident HF between 2016 to 2021 were extracted and analysed from the NELSON study conducted in Tayside, Scotland. WRF was defined as a composite event of (i) having two consecutive eGFRs declined by 40% or greater; (ii) having an eGFR < 15mL/min/1.73m2; (iii) initiation of sustained dialysis; (iv) development of end-stage kidney disease; or (v) receiving kidney transplantation. The primary outcome was the occurrence of WRF within 180 days of diagnosis of HF. Among patients hospitalised with HF, in-hospital WRF was also assessed. The area under the curve (AUC) was used to assess the discrimination performance of the two risk scores in individuals with incident HF diagnosed as either in-patients or out-patients. Results 4076 individuals (mean age 72.8 ± 13.2; 58% male; 1081 HFrEF, 646 HFmrEF, 1348 HFpEF, and 1001 HF with unknown ejection fraction (EF)) who were WRF-free at incident HF diagnosis were identified. Of these, 2095 (51.4%) were diagnosed as in-patients, and 1981 (48.6%) were diagnosed as out-patients. 285 (7%) patients developed WRF within 180 days post HF diagnosis. Among the 2,095 HF in-patients, 75 (3.6%) developed WRF before discharge. The Forman risk score had an AUC of 0.618 (95% CI: 0.585 – 0.651) in predicting 180-day WRF, and an AUC of 0.650 (0.587 – 0.713) for in-hospital WRF. The Basel risk score showed similar discriminating performance with an AUC of 0.618 (0.585 – 0.651) for 180-day WRF, and 0.656 (0.593 – 0.719) for in hospital WRF. Conclusions In a contemporary population, conventional risk scores such as the Forman or Basel risk scores have limited discrimination in predicting WRF in incident HF. New models with better discrimination for WRF prediction are therefore needed.

Development and validation of a risk prediction model for worsening renal function in patients with incident heart failure

Abstract Background Worsening renal function (WRF) is one of the strongest predictors of outcome in patients with heart failure (HF). The presence of WRF often influences the decision to start, up-titrate, or discontinue disease modifying HF therapies and is one of the key determinants of suboptimal guideline-directed medical therapy. Existing WRF risk scores were developed in hospitalised HF patients to predict in-hospital WRF. Their performance among incident HF is far from ideal. It is therefore important to develop a new WRF risk prediction model in people with newly diagnosed HF. Purpose This study was to develop and validate a clinical risk prediction model for 180-day WRF post diagnosis of incident HF using data from a population-based longitudinal cohort. Methods We developed and validated a multivariable logistic regression model for WRF in the 180 days post diagnosis of incident HF. Data for individuals with incident HF between 2016 to 2021 were extracted from the NELSON study conducted in Tayside, Scotland. WRF was defined as a composite event of (i) having two consecutive eGFRs declined by 40% or greater; (ii) having an eGFR < 15mL/min/1.73m2; (iii) initiation of sustained dialysis; (iv) development of end-stage kidney disease; (v) receiving kidney transplantation; or (vi) kidney related death. Four candidate models included one model using literature knowledge; one multivariable fractional polynomial (MFP) model; and two stepwise selected models based on either Akaike or Bayesian information criterion (AIC or BIC). Calibration and discrimination were assessed, and performance stability were evaluated using optimism corrected performance via 1000 times bootstrapping. Results 4076 individuals (mean age 72.8 ± 13.2; 58% male; 1081 HF with reduced ejection fraction (HFrEF), 646 with HF with mildly reduced ejection fraction (HFmrEF), 1348 HF with preserved ejection fraction (HFpEF), and 1001 HF with unknown ejection fraction (EF)) who were WRF-free when diagnosed with HF were identified. Of these, 2095 (51.4%) were in-patients, and 1981 (48.6%) were out-patients. 285 (7%) patients developed WRF within 180 days post HF diagnosis. The selected MFP model (comprising 12 predictors, Table 1) showed good calibration (slope = 1.00 [0.86, 1.14]; intercept = 0.0 [-0.13, 0.13]) discrimination (C-statistic = 0.69 [95% CI: 0.65, 0.72]), and stability (optimism corrected: calibration slope = 0.94 [0.80, 1.07]; calibration intercept = -0.14 [-0.50, 0.20]; C-statistic = 0.67 [0.64, 0.71]). Discrimination of the developed model significantly outperformed two existing risk scores (Forman and Basel, both with a C-statistic = 0.62 [0.59 – 0.65]). Conclusions We have shown that the developed model performed better in predicting WRF in individuals with newly diagnosed HF. This could have utility in identifying at risk patients with HF early in the disease trajectory for therapies that can reduce renal decline.Calibration of predicted riskModel estimates for predicting 180d WRF

Neurotoxic mixture effects of chemicals extracted from blood of pregnant women.

Human biomonitoring studies typically capture only a small and unknown fraction of the entire chemical universe. We combined chemical analysis with a high-throughput in vitro assay for neurotoxicity to capture complex mixtures of organic chemicals in blood. Plasma samples of 624 pregnant women from the German LiNA cohort were extracted with a nonselective extraction method for organic chemicals. 294 of >1000 target analytes were detected and quantified. Many of the detected chemicals as well as the whole extracts interfered with neurite development. Experimental testing of simulated complex mixtures of detected chemicals in the neurotoxicity assay confirmed additive mixture effects at concentrations less than individual chemicals' effect thresholds. The use of high-throughput target screening combined with bioassays has the potential to improve human biomonitoring and provide a new approach to including mixture effects in epidemiological studies.

The Saint-Leonard Urban Glaciotectonic Cave Harbors Rich and Diverse Planktonic and Sedimentary Microbial Communities.

The terrestrial subsurface harbors unique microbial communities that play important biogeochemical roles and allow for studying a yet unknown fraction of the Earth's biodiversity. The Saint-Leonard cave in Montreal City (Canada) is of glaciotectonic origin. Its speleogenesis traces back to the withdrawal of the Laurentide Ice Sheet 13,000 years ago, during which the moving glacier dislocated the sedimentary rock layers. Our study is the first to investigate the microbial communities of the Saint-Leonard cave. By using amplicon sequencing, we analyzed the taxonomic diversity and composition of bacterial, archaeal and eukaryote communities living in the groundwater (0.1 µm- and 0.2 µm-filtered water), in the sediments and in surface soils. We identified a microbial biodiversity typical of cave ecosystems. Communities were mainly shaped by habitat type and harbored taxa associated with a wide variety of lifestyles and metabolic capacities. Although we found evidence of a geochemical connection between the above soils and the cave's galleries, our results suggest that the community assembly dynamics are driven by habitat selection rather than dispersal. Furthermore, we found that the cave's groundwater, in addition to being generally richer in microbial taxa than sediments, contained a considerable diversity of ultra-small bacteria and archaea.

Evaluating Development of Empirical Estimates Using Two Top-Down Methods at Midstream Natural Gas Facilities

To align with climate initiatives, multiple reporting programs are transitioning from generic activity-based emission factors to site-specific measured emissions data to estimate greenhouse gas emissions at oil and gas facilities. This study contemporaneously deployed two top-down (TD) aerial methods across 14 midstream facilities, building upon previous research in the field. The methods produced multiple whole-facility estimates at each facility, resulting in 773 individual paired estimates (same facility, same day), and robust mean estimates for each facility. Mean estimates for each facility, aggregated across all facilities, differed by nearly 2:1 (49% [32% to 69%]). At 6 of 14 facilities, the methods produced mean estimates that differed by more than a factor of two. These data suggest that one or both methods did not produce accurate facility-level estimates at a majority of facilities and in aggregate across all facilities. The overall results are augmented with two case studies where TD estimates at two pre-selected facilities were coupled with comprehensive onsite measurements to understand the factors driving the divergence between TD and bottom-up (BU) emissions estimates. In 3 of 4 paired comparisons between the intensive onsite estimates and one of the TD methods, the intensive onsite surveys did not conclusively diagnose the difference in estimates. In these cases, our work suggests that the TD methods mis-estimate emissions an unknown fraction of the time, for unknown reasons. While two methods were selected for this study, it is unlikely that the issues identified here are confined to these two methods; similar issues may exist for other similar whole-facility methods on midstream and/or other facility types. These findings have important implications for the construction of voluntary and regulatory reporting programs that rely on emission estimates for reporting fees or penalties, or for studies using whole-facility estimates to aggregate TD emissions to basin or regional estimates.

Soil moisture and fertility drive earthworm diversity in north temperate semi-natural grasslands

Intensive management of arable land reduces earthworm density and diversity. This may impair earthworm-mediated soil functions, such as nutrient mineralization and soil structure formation. To sustain earthworm source populations for re-colonization of cultivated soils, it is therefore important to preserve habitats with high earthworm diversity. Semi-natural grasslands, with a long continuity without soil disturbance, could serve as such earthworm diversity reservoirs. This is particularly important in mixed agricultural landscapes with elements of multiple land uses. Nonetheless, earthworm density and diversity vary greatly among grasslands. To preserve and optimally manage the most suitable grasslands, knowledge about which grassland characteristics best explain earthworm diversity is needed. Additionally, we have a limited picture of earthworm diversity in general, because previous studies have neglected juvenile earthworms and cryptic species. The juvenile fraction commonly comprises the main part of earthworm samples, whereas morphologically inseparable cryptic species account for an unknown fraction. This fraction is of particular importance, as juveniles reflect the local reproductive and regeneration potential of earthworm populations and communities. To determine the full species composition of earthworm communities, we sampled earthworms from 28 semi-natural grasslands in south-central Sweden and identified them to species by DNA barcoding. To test how grassland characteristics explain earthworm density, diversity, and community composition, we measured several characteristics of soils, vegetation, and management of the grasslands, and descriptors of the surrounding landscape. DNA barcoding revealed nearly twice as many species as were identified morphologically. Earthworm densities were higher in grasslands with higher Ellenberg moisture indicator values and lower soil C:N ratios. The diversity and occurrence of many earthworm species was also higher in grasslands with higher soil moisture indicator values and lower C:N ratios, and further increased with habitat heterogeneity. Certain species occurred more likely in grasslands with higher grazing intensity. Epigeic earthworms, which live in and feed on surface litter, were more common in grasslands with higher moisture indicator values and SOM content. Thus, dry and relatively unproductive semi-natural grasslands, which are common in Sweden, are unlikely to sustain high earthworm diversity – a pattern contrasting to previously reported plant diversity responses. Instead, earthworm diversity seems concentrated to more productive grazed grasslands, with large within-grassland heterogeneity. Therefore, we highlight the importance of considering soil animals in conservation policies for semi-natural grasslands.

Epidemiology of acute heart failure admissions in Iceland: phenotype distribution and prognostic implications

Abstract Background/Introduction Contemporary data that describe underlying causes of acute heart failure (AHF) epidemiology in a nation-wide unselected real-life cohort is lacking. Advances in diagnostics, including imaging and genetics, have facilitated the identification of the underlying cause of heart failure (HF). This is the first Icelandic nation-wide study on HF epidemiology of patients hospitalised for AHF. Purpose Investigate the underlying causes of AHF in Iceland and the patients‘ prognosis according to phenotypes. Methods This study used data from the Icelandic Heart Failure Registry (IHFR) and included all hospital admissions for AHF at Landspitali University Hospital from January 2020 to June 2022 (n = 1723). Differences in survival between HF phenotypes were analysed using a multivariate log-rank test, both after diagnosis and after the first discharge. Results The study found that 39.8% of the cases had heart failure with reduced ejection fraction (HFrEF), 17.4% had HF with mildly reduced ejection fraction (HFmrEF), 40.3% had HF with preserved ejection fraction (HFpEF), 0.9% had HF with improved ejection fraction (HFimpEF), and 1.5% had unknown ejection fraction (EF). The average length of hospital admission varied by phenotype, ranging from 8.1 to 15.9 days. Women accounted for 41.15% of all admissions, with the most common phenotype amongst women being HFpEF (57.8%) and the least common being HFrEF (25.1%). The mean age at admission was 75.8 years. Roughly 79% of the whole cohort had NYHA class III-IV at admission; 33% of HFrEF, 13% of HFmrEF and 32% of HFpEF admissions. The most common underlying cause of AHF was coronary artery disease (CAD, 30.9%) followed by atrial fibrillation (15.0%), hypertension (9.8%), diastolic dysfunction (9.4%) and valvular heart disease (9.2%). Other more rare causes were dilated cardiomyopathy (4.4%), amyloidosis (3.2%), broken heart disease (1.5%), myocarditis (0.4%), postpartum cardiomyopathy (0.2%) and Fabry disease (0.1%). During the study period, 422 mortalities were recorded, with 106 in-hospital deaths. After excluding in-hospital mortalities, no significant difference in survival between phenotypes was observed after the first discharge. However, a significant difference in survival was observed with respect to the date of diagnosis (p = 0.0191). Conclusion This study provides new insights into the underlying causes of AHF and patients' prognosis according to phenotypes in Iceland. Our results demonstrate that the most common underlying cause of AHF was CAD, followed by atrial fibrillation and hypertension and that the cohort was highly symptomatic, with a large proportion of patients having NYHA class III-IV at admission. Our findings also highlight significant differences in the prevalence of HF phenotypes between genders, with women more commonly presenting with HFpEF and less commonly with HFrEF.

Calculating the reference intensity ratio of crystalline phases with unknown atomic arrangements using the lattice parameters and chemical information

The reference intensity ratio (RIR) is the intensity ratio of a specified peak of the target crystalline phase to a certain peak of the reference phase in the powder X-ray diffraction pattern of a mixture of the target and reference phases in a weight ratio of 1:1. The RIR represents the diffraction power of the target phase compared with that of the reference phase. A quantitative phase analysis (QPA) can be readily made on the basis of only a powder pattern when the RIR values of all component phases in the mixture are available. The RIR of a target phase can be measured experimentally or calculated in accordance with its crystal structure. RIR values are given in most powder diffraction files (PDFs) published by the International Centre for Diffraction Data, but there are still more than 110 000 PDFs for which the RIR is absent. Newly discovered phases may be present in a mixture as components of unknown weight fractions, for which the RIR values can be neither measured nor calculated with the currently available method. Herein is presented a new method of calculating the RIR of a crystalline phase from its lattice parameters, the chemical content of the unit cell and a list of normalized intensities of reflections over a sufficiently large diffraction angle range. The new method can be used to calculate not only the absent RIRs in the PDFs but also the RIR of a component phase of a mixture of unknown weight fraction when the lattice parameters and chemical content of the unit cell of the corresponding phase are known.

Fibroblast Growth Factor 23 and Risk of Heart Failure Subtype: The CRIC (Chronic Renal Insufficiency Cohort) Study

Heart failure (HF) is an important cause of morbidity and mortality among individuals with chronic kidney disease (CKD). A large body of evidence from preclinical and clinical studies implicates excess levels of fibroblast growth factor 23 (FGF23) in HF pathogenesis in CKD. It remains unclear whether the relationship between elevated FGF23 levels and HF risk among individuals with CKD varies by HF subtype. Prospective cohort study. A total of 3,502 participants were selected in the Chronic Renal Insufficiency Cohort study. Baseline plasma FGF23. Incident HF by subtype and total rate of HF hospitalization. HF was categorized as HF with preserved ejection fraction (HFpEF, ejection fraction [EF]≥ 50%), HF with reduced EF (HFrEF, EF<50%) and HF with unknown EF (HFuEF). Multivariable-adjusted cause-specific Cox proportional hazards models were used to investigate associations between FGF23 and incident hospitalizations for HF by subtype. The Lunn-McNeil method was used to compare hazard ratios across HF subtypes. Poisson regression models were used to evaluate the total rate of HF. During a median follow-up time of 10.8 years, 295 HFpEF, 242 HFrEF, and 156 HFuEF hospitalizations occurred. In multivariable-adjusted cause-specific Cox proportional hazards models, FGF23 was significantly associated with the incidence of HFpEF (HR, 1.41; 95% CI, 1.21-1.64), HFrEF (HR, 1.27; 95% CI, 1.05-1.53), and HFuEF (HR, 1.40; 95% CI, 1.13-1.73) per 1 standard deviation (SD) increase in the natural log of FGF23. The Lunn-McNeil method determined that the risk association was consistent across all subtypes. The rate ratio of total HF events increased with FGF23 quartile. In multivariable-adjusted models, compared with quartile 1, FGF23 quartile 4 had a rate ratio of 1.81 (95% CI, 1.28-2.57) for total HF events. Self-report of HF hospitalizations and possible lack of an echocardiogram at time of hospitalization. In this large multicenter prospective cohort study, elevated FGF23 levels were associated with increased risks for all HF subtypes. Heart failure (HF) is a prominent cause of morbidity and mortality in individuals with chronic kidney disease (CKD). Identifying potential pathways in the development of HF is essential in developing therapies to prevent and treat HF. In a large cohort of individuals with CKD, the Chronic Renal Insufficiency Cohort (N=3,502), baseline fibroblast growth factor-23 (FGF23), a hormone that regulates phosphorous, was evaluated in relation to the development of incident and recurrent HF with reduced, preserved, and unknown ejection fraction. In this large multicenter prospective cohort study, elevated FGF23 levels were associated with increased risk of all HF subtypes. These findings demonstrate the need for further research into FGF23 as a target in preventing the development of HF in individuals with CKD.

Unlabeled Imperfect Demonstrations in Adversarial Imitation Learning

Adversarial imitation learning has become a widely used imitation learning framework. The discriminator is often trained by taking expert demonstrations and policy trajectories as examples respectively from two categories (positive vs. negative) and the policy is then expected to produce trajectories that are indistinguishable from the expert demonstrations. But in the real world, the collected expert demonstrations are more likely to be imperfect, where only an unknown fraction of the demonstrations are optimal. Instead of treating imperfect expert demonstrations as absolutely positive or negative, we investigate unlabeled imperfect expert demonstrations as they are. A positive-unlabeled adversarial imitation learning algorithm is developed to dynamically sample expert demonstrations that can well match the trajectories from the constantly optimized agent policy. The trajectories of an initial agent policy could be closer to those non-optimal expert demonstrations, but within the framework of adversarial imitation learning, agent policy will be optimized to cheat the discriminator and produce trajectories that are similar to those optimal expert demonstrations. Theoretical analysis shows that our method learns from the imperfect demonstrations via a self-paced way. Experimental results on MuJoCo and RoboSuite platforms demonstrate the effectiveness of our method from different aspects.

Abundance of humpback whales on the Abrolhos Bank wintering ground, Brazil

Abundance estimates are presented for the humpback whales wintering off Brazil which ‘visit’ a surveyed area off Abrolhos Bank and display fluke-exposing behaviour. The study is based on photo-identification data collected between 1996 and 2000. Chapman-corrected Petersen estimates for all pairs of data result in estimates from 1,948 individuals up to 3,001 with coefficients of variation around 0.25. A more elaborate closed population multiple-recapture maximum-likelihood estimate is 2,393 with 95% profile-likelihood confidence interval (CI=1,924, 3,060). Replacing the closed-population assumption with a population allowed to grow (or decrease) according to some constant rate over the study period, the maximum-likelihood estimate of population size for the year 2000 becomes 3,871 (CI=2,795, 5,542) associated to an estimated annual growth rate of 31% over the study period and in the surveyed area. Although the inclusion of the growth rate results in a less restrictive assumption about population size, it is unclear at this time how to interpret it since the population around the Abrolhos Bank is some (unknown) fraction of whales wintering off Brazil. Alternatively, a fit of Whitehead’s model allowing for emigration and re-immigration gives an estimate of about 3,000 whales (CI=2,500, 3,650).

Risks of Heart Failure, Stroke, and Bleeding in Atrial Fibrillation According to Heart Failure Phenotypes

BackgroundThe risks of heart failure (HF) events compared with stroke/systemic embolic events (SEE) or major bleeding (MB) in heart failure with reduced ejection fraction (HFrEF) vs heart failure with preserved ejection fraction (HFpEF) in a large atrial fibrillation (AF) population have not been well-studied. ObjectivesThis study sought to assess HF outcomes, according to HF history and HF phenotypes (HFrEF vs HFpEF), and compare these events with SEE and MB, among patients with AF. MethodsWe analyzed patients enrolled in the ENGAGE-AF TIMI 48 (Effective Anticoagulation with Factor Xa Next Generation in AF-Thrombolysis in Myocardial Infarction 48) trial. Cumulative incidence of heart failure hospitalization (HHF) or HF death was assessed and compared with the rates of fatal and nonfatal stroke/SEE and MB over a median follow-up of 2.8 years. ResultsOverall, 12,124 (57.4%) had a history of HF (37.7% HFrEF, 40.1% HFpEF, 22.1% with unknown ejection fraction). The rate per 100 person-years (py) of HHF or HF death (4.95; 95% CI: 4.70-5.20) was higher than of fatal and nonfatal stroke/SEE (1.77; 95% CI: 1.63-1.92) and MB (2.66; 95% CI: 2.47-2.86) among patients with HF history. HFrEF patients experienced a higher rate of HHF or HF death compared with HFpEF patients (7.15 vs 3.65; P < 0.001), while the rates of fatal and nonfatal stroke/SEE and MB were similar by HF phenotype. Patients with HF history had a higher rate of mortality after a HHF (1.29; 95% CI: 1.17-1.42) than after a stroke/SEE (0.69; 95% CI: 0.60-0.78) or after MB (0.61; 95% CI: 0.53-0.70). Overall, patients with nonparoxysmal AF had a higher rate of HF and stroke/SEE events regardless of HF history. ConclusionsPatients with AF and HF, regardless of ejection fraction, are at a higher risk of HF events with higher subsequent mortality rates than of stroke/SEE or MB. While HFrEF is associated with a higher risk of HF events than HFpEF, the risk of stroke/SEE and MB is similar between HFrEF and HFpEF.

Co-Occurrence of Bromine and Iodine Species in US Drinking Water Sources That Can Impact Disinfection Byproduct Formation.

Bromine and iodine species are precursors for forming disinfection byproducts in finished drinking waters. Our study incorporates spatial and temporal data to quantify concentrations of inorganic (bromide (Br-), iodide (I-), and iodate (IO3-)), organic, and total bromine (BrT) and iodine (IT) species from 286 drinking water sources and 7 wastewater effluents across the United States. Br- ranged from <5-7800 μg/L (median of 62 μg/L in surface water (SW) and 95 μg/L in groundwater (GW)). I- was detected in 41% of SW (1-72 μg/L, median = <1 μg/L) and 62% of GW (<1-250 μg/L, median = 3 μg/L) samples. The median Br-/I- ratio in SW and GW was 22 μg/μg and 16 μg/μg, respectively, in paired samples with detect Br- and I-. BrT existed primarily as Br-, while IT was present as I-, IO3-, and/or total organic iodine (TOI). Inorganic iodine species (I- and IO3-) were predominant in GW samples, accounting for 60-100% of IT; however, they contributed to only 20-50% of IT in SW samples. The unknown fraction of IT was attributed to TOI. In lakes, seasonal cycling of I-species was observed and was presumably due to algal productivity. Finally, Spearman Rank Correlation tests revealed a strong correlation between Br- and IT in SW (RBr-,IT = 0.83) following the log10 (Br-, μg/L) = 0.65 × log10 (IT, μg/L) - 0.17 relationship. Br- and I- in treated wastewater effluents (median Br- = 234 μg/L, median I- = 5 μg/L) were higher than drinking water sources.

Secure Distributed Optimization Under Gradient Attacks

In this paper, we study secure distributed optimization against arbitrary gradient attacks in multi-agent networks. In distributed optimization, there is no central server to coordinate local updates, and each agent can only communicate with its neighbors on a predefined network. We consider the scenario where out of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n$</tex-math></inline-formula> networked agents, a fixed but unknown fraction <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rho$</tex-math></inline-formula> of the agents are under arbitrary gradient attacks in that their stochastic gradient oracles return arbitrary information to derail the optimization process, and the goal is to minimize the sum of local objective functions on unattacked agents. We propose a distributed stochastic gradient method that combines local variance reduction and clipping ( <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CLIP-VRG</small> ). We show that, in a connected network, when the unattacked local objective functions are convex and smooth, share a common minimizer, and their sum is strongly convex, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CLIP-VRG</small> leads to almost sure convergence of the iterates to the exact sum cost minimizer at all agents. We quantify a tight upper bound on the fraction <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rho$</tex-math></inline-formula> of attacked agents in terms of problem parameters such as the condition number of the associated sum cost that guarantee exact convergence of <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CLIP-VRG</small> , and characterize its asymptotic convergence rate. Finally, we empirically demonstrate the effectiveness of the proposed method under gradient attacks on both synthetic and real-world image classification datasets.

HCO+ Dissociative Recombination: A Significant Driver of Nonthermal Hydrogen Loss at Mars

AbstractHydrogen escape to space has shaped Mars' atmospheric evolution, driving significant water loss. An unknown fraction of atmospheric H lost acquires its escape energy from photochemical processes, with multiple observational studies suggesting much higher densities of such “hot” H than models predict. Here, we show that a previously unconsidered mechanism, HCO+ dissociative recombination, produces more escaping hot H than any previously studied process, potentially accounting for more than 50% of escape during solar minimum aphelion conditions and ∼5% of the expected long‐term average loss. This hot H is predicted to impact observed brightness profiles negligibly, posing a significant challenge to the interpretation of spacecraft remote sensing observations. This mechanism's efficiency is largely due to the high (63%–83%) albedo of the planet to H at 1–10 eV energies, indicating the likely importance of dozens of similar photochemical mechanisms for the desiccation of Mars, Venus and planets throughout the universe.

Direct dynamic tomographic reconstruction without explicit blood input function

With dynamic positron emission tomography (PET), we study the metabolic processes by monitoring the uptake of a radioactive tracer. The goal is to reconstruct the time-activity curves (TACs) of the voxels, from which the relevant kinetic parameters can be obtained. These curves are assumed to have the algebraic form of a pre-determined kinetic model. Plausible algebraic forms have a limited number of free parameters and thus can be used even for low-statistic measurements. The kinetic model typically involves the amount of radiotracer in the blood, which should be determined either by direct measurement or by extracting it from the PET data using image-derived or model-based methods. However, the direct measurement of the blood concentration is complicated, and the results of the image-derived and the model-based methods are also not reliable because of the partial volume effect and the unknown fraction of blood in the voxels. Moreover, in direct dynamic tomography, the kinetic model is fit from the very beginning of the reconstruction, thus the blood input function is needed even before the image-derived or model-based approaches can provide it. In this paper, we propose a method that is based on compartmental modeling and the Feng blood input function model defined by a fourth-order exponential equation with a pair of repeated eigenvalues, but does not require the blood input function and the fraction of blood parameters explicitly. Thus, the model can be used in cases when we wish to have the robustness and advantages of compartmental modeling, but no blood input function measurement is available. The test results show that the added error in the TACs of not knowing the blood input is reduced in comparison with the spline-based TAC representation. The method can be applied in reference tissue analysis and in image-derived input function approaches.

Characteristics and management of very elderly patients with heart failure: a retrospective, population cohort study.

Unmet needs exist in the diagnosis and treatment of heart failure (HF) in the elderly population. Our aim was to analyse and compare data of diagnostics and management of very elderly patients (aged ≥85years) compared with younger patients (aged 18-84years) with HF in Sweden. Incidence of ≥2 HF diagnosis (ICD-10) was identified from primary/secondary care in Uppsala and Västerbotten during 2010-2015 via electronic medical records linked to data from national health registers. Analyses investigated the diagnosis, treatment patterns, hospitalizations and outpatient visits, and mortality. Of 8702 patients, 27.7% were ≥85years old, women (60.2%); most patients (80.7%) had unknown left ventricular ejection fraction; key co-morbidities comprised anaemia, dementia, and cerebrovascular disease. More very elderly patients received cardiovascular disease (CVD)-related management after diagnosis in primary care (13.6% vs. 6.5%; P<0.0001), but fewer patients underwent echocardiography (19.3% vs. 42.9%; P<0.0001). Within 1year of diagnosis, very elderly patients were less likely to be hospitalized (all-cause admissions per patient: 1.9 vs. 2.3; P<0.0001; CVD-related admissions per patient: 1.8 vs. 2.1; P=0.0004) or prescribed an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB) plus a β-blocker (45.2% vs. 56.9%; P<0.0001) or an ACEI/ARB plus a β-blocker plus a mineralocorticoid receptor antagonist (15.4% vs. 31.7%; P<0.0001). One-year mortality was high in patients ≥85years old, 30.5% (CI: 28.3-32.7%) out of 1797 patients. Despite the large number of very elderly patients with newly diagnosed HF in Sweden, poor diagnostic work-up and subsequent treatment highlight the inequality of care in this vulnerable population.

Influence of the adopted rheological model of plant suspension on the predicted resistance of its flow in the pipe

The work discusses the pressure required for forcing diluted suspensions of plant particles in a pipe. Their volume increases under the effect of the interface with the liquid. An aqueous suspension of hay particles with a size of up to 106 μm and an initial volume fraction of 10% was investigated for this purpose. Standard measuring instruments were applied for testing the rheological properties of the prepared substance, i.e. a Höppler viscometer and a rheometer with coaxial cylinders. The measurement results were utilized throughout several procedures for calculating flow resistance. It was found that the hasty application of commonly known and practically used simplifying assumptions or inadequate interpretation of the rheological properties of the substance lead to significant design errors of the flow system. As a result of imbibition, the volume fraction of the solid phase varies, and thus it becomes difficult to predict the rheological properties of the suspension. • Swelling of plant particles in water. • Unknown actual volume fraction of solids phase. • Difficulties in predicting the rheological properties of plant suspension. • Ambiguous assessment of the demand for pumping power.

Fresh Versus Frozen Stool for Fecal Microbiota Transplantation-Assessment by Multimethod Approach Combining Culturing, Flow Cytometry, and Next-Generation Sequencing.

The objective of this work was to compare the quality of FMT preparations made from fresh feces with those made from feces frozen at –30°C without any pre-processing or cryopreservation additives. The research hypothesis was that such preservation protocol (frozen whole stool, then thawed and processed) is equipotent to classical fresh FMT preparation. For that, three complementary methods were applied, including: (i) culturing in aerobic and anaerobic conditions, (ii) measuring viability by flow cytometry, and (iii) next-generation sequencing. Flow cytometry with cell staining showed that the applied freezing protocol causes significant changes in all of the observed bacterial fractions. Alive cell counts dropped four times, from around 70% to 15%, while the other two fractions, dead and unknown cell counts quadrupled and doubled, with the unknown fraction becoming the dominant one, with an average contribution of 57.47% per sample. It will be very interesting to uncover what this unknown fraction is (e.g., bacterial spores), as this may change our conclusions (if these are spores, the viability could be even higher after freezing). Freezing had a huge impact on the structure of cultivable bacterial communities. The biggest drop after freezing in the number of cultivable species was observed for Actinobacteria and Bacilli. In most cases, selected biodiversity indices were slightly lower for frozen samples. PCoA visualization built using weighted UniFrac index showed no donor-wise clusters, but a clear split between fresh and frozen samples. This split can be in part attributed to the changes in the relative abundance of Bacteroidales and Clostridiales orders. Our results clearly show that whole stool freezing without any cryoprotectants has a great impact on the cultivability and biodiversity of the bacterial community, and possibly also on the viability of bacterial cells.

The black hole population in low-mass galaxies in large-scale cosmological simulations

ABSTRACT Recent systematic searches for massive black holes (BHs) in local dwarf galaxies led to the discovery of a population of faint active galactic nuclei (AGNs). We investigate the agreement of the BH and AGN populations in the Illustris, TNG, Horizon-AGN, EAGLE, and SIMBA simulations with current observational constraints in low-mass galaxies. We find that some of these simulations produce BHs that are too massive, and that the BH occupation fraction (OF) at z = 0 is not inherited from the simulation seeding modelling. The ability of BHs and their host galaxies to power an AGN depends on BH and galaxy subgrid modelling. The fraction of AGN in low-mass galaxies is not used to calibrate the simulations, and thus can be used to differentiate galaxy formation models. AGN fractions at z = 0 span two orders of magnitude at fixed galaxy stellar mass in simulations, similarly to observational constraints, but uncertainties and degeneracies affect both observations and simulations. The agreement is difficult to interpret due to differences in the masses of simulated and observed BHs, BH OF affected by numerical choices, and an unknown fraction of obscured AGN. Our work advocates for more thorough comparisons with observations to improve the modelling of cosmological simulations, and our understanding of BH and galaxy physics in the low-mass regime. The mass of BHs, their ability to efficiently accrete gas, and the AGN fraction in low-mass galaxies have important implications for the build-up of the entire BH and galaxy populations with time.