Fault-tolerant aggregation: Flow-Updating meets Mass-Distribution

Flow-Updating (FU) is a fault-tolerant technique that has proved to be efficient in practice for the distributed computation of aggregate functions in communication networks where individual processors do not have access to global information. Previous distributed aggregation protocols, based on repeated sharing of input values (or mass) among processors, sometimes called Mass-Distribution (MD) protocols, are not resilient to communication failures (or message loss) because such failures yield a loss of mass. In this paper, we present a protocol which we call Mass-Distribution with Flow-Updating (MDFU). We obtain MDFU by applying FU techniques to classic MD. We analyze the convergence time of MDFU showing that stochastic message loss produces low overhead. This is the first convergence proof of an FU-based algorithm. We evaluate MDFU experimentally, comparing it with previous MD and FU protocols, and verifying the behavior predicted by the analysis. Finally, given that MDFU incurs a fixed deviation proportional to the message-loss rate, we adjust the accuracy of MDFU heuristically in a new protocol called MDFU with Linear Prediction (MDFU-LP). The evaluation shows that both MDFU and MDFU-LP behave very well in practice, even under high rates of message loss and even changing the input values dynamically.- A preliminary version of this work appeared in [2]. This work was partially supported by the National Science Foundation (CNS-1408782, IIS-1247750); the National Institutes of Health (CA198952-01); EMC, Inc.; Pace University Seidenberg School of CSIS; and by Project "Coral - Sustainable Ocean Exploitation: Tools and Sensors/NORTE-01-0145-FEDER-000036" financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF).info:eu-repo/semantics/publishedVersio

Clinical relevance of timing of assessment of ICU mortality in patients with moderate-to-severe Acute Respiratory Distress Syndrome

Mortality is a frequently reported outcome in clinical studies of acute respiratory distress syndrome (ARDS). However, timing of mortality assessment has not been well characterized. We aimed to identify a crossing-point between cumulative survival and death in the intensive care unit (ICU) of patients with moderate-to-severe ARDS, beyond which the number of survivors would exceed the number of deaths. We hypothesized that this intersection would occur earlier in a successful clinical trial vs. observational studies of moderate/severe ARDS and predict treatment response. We conducted an ancillary study of 1580 patients with moderate-to-severe ARDS managed with lung-protective ventilation to assess the relevance and timing of measuring ICU mortality rates at different time-points during ICU stay. First, we analyzed 1303 patients from four multicenter, observational cohorts enrolling consecutive patients with moderate/severe ARDS. We assessed cumulative ICU survival from the time of moderate/severe ARDS diagnosis to ventilatory support discontinuation within 7-days, 28-days, 60-days, and at ICU discharge. Then, we compared these findings to those of a successful randomized trial of 277 moderate/severe ARDS patients. In the observational cohorts, ICU mortality (487/1303, 37.4%) and 28-day mortality (425/1102, 38.6%) were similar (p = 0.549). Cumulative proportion of ICU survivors and non-survivors crossed at day-7; after day-7, the number of ICU survivors was progressively higher compared to non-survivors. Measures of oxygenation, lung mechanics, and severity scores were different between survivors and non-survivors at each point-in-time (p < 0.001). In the trial cohort, the cumulative proportion of survivors and non-survivors in the treatment group crossed before day-3 after diagnosis of moderate/severe ARDS. In clinical ARDS studies, 28-day mortality closely approximates and may be used as a surrogate for ICU mortality. For patients with moderate-to-severe ARDS, ICU mortality assessment within the first week of a trial might be an early predictor of treatment response

Molecular mechanisms of cell death: recommendations of the Nomenclature Committee on Cell Death 2018.

Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field

Improvement of Duchenne muscular dystrophy phenotype following obestatin treatment

Abstract Background This study was performed to test the therapeutic potential of obestatin, an autocrine anabolic factor regulating skeletal muscle repair, to ameliorate the Duchenne muscular dystrophy (DMD) phenotype. Methods and results Using a multidisciplinary approach, we characterized the ageing‐related preproghrelin/GPR39 expression patterns in tibialis anterior (TA) muscles of 4‐, 8‐, and 18‐week‐old mdx mice (n = 3/group) and established the effects of obestatin administration at this level in 8‐week‐old mdx mice (n = 5/group). The findings were extended to in vitro effects on human immortalized DMD myotubes. An analysis of TAs revealed an age‐related loss of preproghrelin expression, as precursor of obestatin, in mdx mice. Administration of obestatin resulted in a significant increase in tetanic specific force (33.0% ± 1.5%, P < 0.05), compared with control mdx mice. Obestatin‐treated TAs were characterized by reduction of fibres with centrally located nuclei (10.0% ± 1.2%, P < 0.05) together with an increase in the number of type I fibres (25.2% ± 1.7%, P < 0.05) associated to histone deacetylases/myocyte enhancer factor‐2 and peroxisome proliferator‐activated receptor‐gamma coactivator 1α axis, and down‐regulation of ubiquitin E3‐ligases by inactivation of FoxO1/4, indexes of muscle atrophy. Obestatin reduced the level of contractile damage and tissue fibrosis. These observations correlated with decline in serum creatine kinase (58.8 ± 15.2, P < 0.05). Obestatin led to stabilization of the sarcolemma by up‐regulation of utrophin, α‐syntrophin, β‐dystroglycan, and α7β1‐integrin proteins. These pathways were also operative in human DMD myotubes. Conclusions These results highlight the potential of obestatin as a peptide therapeutic for preserving muscle integrity in DMD, thus allowing a better efficiency of gene or cell therapy in a combined therapeutic approach

The NMR structure of human obestatin in membrane-like environments: insights into the structure-bioactivity relationship of obestatin.

The quest for therapeutic applications of obestatin involves, as a first step, the determination of its 3D solution structure and the relationship between this structure and the biological activity of obestatin. On this basis, we have employed a combination of circular dichroism (CD), nuclear magnetic resonance (NMR) spectroscopy, and modeling techniques to determine the solution structure of human obestatin (1). Other analogues, including human non-amidated obestatin (2) and the fragment peptides (6-23)-obestatin (3), (11-23)-obestatin (4), and (16-23)-obestatin (5) have also been scrutinized. These studies have been performed in a micellar environment to mimic the cell membrane (sodium dodecyl sulfate, SDS). Furthermore, structural-activity relationship studies have been performed by assessing the in vitro proliferative capabilities of these peptides in the human retinal pigmented epithelial cell line ARPE-19 (ERK1/2 and Akt phosphorylation, Ki67 expression, and cellular proliferation). Our findings emphasize the importance of both the primary structure (composition and size) and particular segments of the obestatin molecule that posses significant α-helical characteristics. Additionally, details of a species-specific role for obestatin have also been hypothesized by comparing human and mouse obestatins (1 and 6, respectively) at both the structural and bioactivity levels

Predicting ICU mortality in acute respiratory distress syndrome patients using machine learning: The Predicting Outcome and STratifiCation of severity in ARDS (POSTCARDS) Study

Objectives: To assess the value of machine learning approaches in the development of a multivariable model for early prediction of ICU death in patients with acute respiratory distress syndrome (ARDS). Design: A development, testing, and external validation study using clinical data from four prospective, multicenter, observational cohorts. Setting: A network of multidisciplinary ICUs. Patients: A total of 1,303 patients with moderate-to-severe ARDS managed with lung-protective ventilation. Interventions: None. Measurements and Main Results: We developed and tested prediction models in 1,000 ARDS patients. We performed logistic regression analysis following variable selection by a genetic algorithm, random forest and extreme gradient boosting machine learning techniques. Potential predictors included demographics, comorbidities, ventilatory and oxygenation descriptors, and extrapulmonary organ failures. Risk modeling identified some major prognostic factors for ICU mortality, including age, cancer, immunosuppression, Pao2/Fio2, inspiratory plateau pressure, and number of extrapulmonary organ failures. Together, these characteristics contained most of the prognostic information in the first 24 hours to predict ICU mortality. Performance with machine learning methods was similar to logistic regression (area under the receiver operating characteristic curve [AUC], 0.87; 95% CI, 0.82–0.91). External validation in an independent cohort of 303 ARDS patients confirmed that the performance of the model was similar to a logistic regression model (AUC, 0.91; 95% CI, 0.87–0.94). Conclusions: Both machine learning and traditional methods lead to promising models to predict ICU death in moderate/severe ARDS patients. More research is needed to identify markers for severity beyond clinical determinants, such as demographics, comorbidities, lung mechanics, oxygenation, and extrapulmonary organ failure to guide patient management

Analysis of the expression and functionality of GPR39 in ARPE-19 cells.

<p>(A) Immunocytochemical detection of GPR39 in ARPE-19 cells (objective magnification of 20x). (B) The effect of siRNA depletion of GPR39 on pAkt(S473) and pERK1/2(T202/Y204) in ARPE-19 cells after human obestatin treatment (<b>1</b>, 100 nM, 10 min). The ARPE-19 cells were transfected with GPR39 siRNA prior to obestatin <b>1</b> treatment. Equal amounts of protein in each sample were used to assess the expression of GPR39 by western blotting. The GPR39 level was expressed as the fold change relative to the control siRNA-transfected cells (mean ± SE). The protein expression was normalized relative to actin. The data are expressed as the mean ± SE. The asterisk (*) denotes <i>P</i><0.05 when comparing the treated control siRNA group with the control siRNA group; the dagger (#) denotes <i>P</i><0.05 when comparing the GPR39 siRNA group with the control siRNA group.</p

Primary structure of the obestatins used in this work: human obestatin (1), human non-amidated obestatin (2), human (6–23)-obestatin (3), human (11–23)-obestatin (4), human (16–23)-obestatin (5) and mouse obestatin (6).

<p>The red-labeled residues in <b>6</b> are different from those of <b>1</b>.</p