Simple versus optimal rules as guides to policy

This paper contributes to the policy evaluation literature by developing new strategies to study alternative policy rules. We compare optimal rules to simple rules within canonical monetary policy models. In our context, an optimal rule represents the solution to an intertemporal optimization problem in which a loss function for the policymaker and an explicit model of the macroeconomy are specified. We define a simple rule to be a summary of the intuition policymakers and economists have about how a central bank should react to aggregate disturbances. The policy rules are evaluated under minimax and minimax regret criteria. These criteria force the policymaker to guard against a worst-case scenario, but in different ways. Minimax makes the worst possible model the benchmark for the policymaker, while minimax regret confronts the policymaker with uncertainty about the true model. Our results indicate that the case for a model-specific optimal rule can break down when uncertainty exists about which of several models is true. Further, we show that the assumption that the policymaker’s loss function is known can obscure policy trade-offs that exist in the short, medium, and long run. Thus, policy evaluation is more difficult once it is recognized that model and preference uncertainty can interact.

Decoding post-stroke motor function from structural brain imaging

AbstractClinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine learning in structural imaging to investigate diseases that involve brain injury presents an additional challenge, especially in conditions like stroke, due to the high variability across patients regarding characteristics of the lesions. Extracting data from anatomical images in a way that translates brain damage information into features to be used as input to learning algorithms is still an open question. One of the most common approaches to capture regional information from brain injury is to obtain the lesion load per region (i.e. the proportion of voxels in anatomical structures that are considered to be damaged). However, no systematic evaluation has yet been performed to compare this approach with using patterns of voxels (i.e. considering each voxel as a single feature). In this paper we compared both approaches applying Gaussian Process Regression to decode motor scores in 50 chronic stroke patients based solely on data derived from structural MRI. For both approaches we compared different ways to delimit anatomical areas: regions of interest from an anatomical atlas, the corticospinal tract, a mask obtained from fMRI analysis with a motor task in healthy controls and regions selected using lesion-symptom mapping. Our analysis showed that extracting features through patterns of voxels that represent lesion probability produced better results than quantifying the lesion load per region. In particular, from the different ways to delimit anatomical areas compared, the best performance was obtained with a combination of a range of cortical and subcortical motor areas as well as the corticospinal tract. These results will inform the appropriate methodology for predicting long term motor outcomes from early post-stroke structural brain imaging

Numerical Investigation of Al-Reinforced CFRP Composite under Low-Velocity Impact

Fibre-reinforced composite materials are widespread in lightweight, high-performance applications. However, polymeric composites generally exhibit a brittle behaviour, which makes them susceptible to impact damage. Even low-velocity impacts can produce delaminations, which cause a substantial reduction of the compressive mechanical properties. Metallic layers have been embedded in composite laminates with the aim to improve their fracture behaviour: aluminium plies can be employed to increase the indentation resistance of Carbon Fibre Reinforced Polymers (CFRP) specimens. For this reason, hybrid fibre-metal laminates are expected to be a viable solution to reduce the damage caused by low-velocity impacts. In this work, CFRP specimens reinforced with aluminium plies were modelled using the finite element method and a cohesive zone model. Cohesive elements based on a traction-separation formulation were embedded at each ply-to-ply interface to enforce delamination damage. Different configurations of the Al reinforcements were studied by varying the position of the aluminium layers between the CFRP plies

Post-partum anoestrus in Anglo-Nubian and Saanen goats raised in semi-arid of North-eastern Brazil.

The aim of this study was to verify the length of post-partum anoestrus (PPA) in Anglo-Nubian and Saanen goats raised in North-eastern Brazi

The peripheral blood transcriptome in septic cardiomyopathy: an observational, pilot study.

BACKGROUND:Septic cardiomyopathy (SCM) is common in sepsis and associated with increased morbidity and mortality. Left ventricular global longitudinal strain (LV GLS), measured by speckle tracking echocardiography, allows improved identification of impaired cardiac contractility. The peripheral blood transcriptome may be an important window into SCM pathophysiology. We therefore studied the peripheral blood transcriptome and LV GLS in a prospective cohort of patients with sepsis. RESULTS:In this single-center observational pilot study, we enrolled adult patients (age > 18) with sepsis within 48 h of admission to the ICU. SCM was defined as LV GLS > - 17% based on echocardiograms performed within 72 h of admission. We enrolled 27 patients, 24 of whom had high-quality RNA results; 18 (75%) of 24 had SCM. The group was 50% female and had a median (IQR) age of 59.5 (48.5-67.0) years and admission APACHE II score of 21.0 (16.0-32.3). Forty-six percent had septic shock. After filtering for low-expression and non-coding genes, 15,418 protein coding genes were expressed and 73 had significantly different expression between patients with vs. without SCM. In patients with SCM, 43 genes were upregulated and 30 were downregulated. Pathway analysis identified enrichment in type 1 interferon signaling (adjusted p < 10-5). CONCLUSIONS:In this hypothesis-generating study, SCM was associated with upregulation of genes in the type 1 interferon signaling pathway. Interferons are cytokines that stimulate the innate and adaptive immune response and are implicated in the early proinflammatory and delayed immunosuppression phases of sepsis. While type 1 interferons have not been implicated previously in SCM, interferon therapy (for viral hepatitis and Kaposi sarcoma) has been associated with reversible cardiomyopathy, perhaps suggesting a role for interferon signaling in SCM

PSMA-Specific CAR-Engineered T Cells Eradicate Disseminated Prostate Cancer in Preclinical Models.

Immunology-based interventions have been proposed as a promising curative chance to effectively attack postoperative minimal residual disease and distant metastatic localizations of prostate tumors. We developed a chimeric antigen receptor (CAR) construct targeting the human prostate-specific membrane antigen (hPSMA), based on a novel and high affinity specific mAb. As a transfer method, we employed last-generation lentiviral vectors (LV) carrying a synthetic bidirectional promoter capable of robust and coordinated expression of the CAR molecule, and a bioluminescent reporter gene to allow the tracking of transgenic T cells after in vivo adoptive transfer. Overall, we demonstrated that CAR-expressing LV efficiently transduced short-term activated PBMC, which in turn were readily stimulated to produce cytokines and to exert a relevant cytotoxic activity by engagement with PSMA+ prostate tumor cells. Upon in vivo transfer in tumor-bearing mice, CAR-transduced T cells were capable to completely eradicate a disseminated neoplasia in the majority of treated animals, thus supporting the translation of such approach in the clinical setting

Virtual Drug Repositioning as a Tool to Identify Natural Small Molecules That Synergize with Lumacaftor in F508del-CFTR Binding and Rescuing

Cystic fibrosis is a hereditary disease mainly caused by the deletion of the Phe 508 (F508del) of the cystic fibrosis transmembrane conductance regulator (CFTR) protein that is thus withheld in the endoplasmic reticulum and rapidly degraded by the ubiquitin/proteasome system. Cystic fibrosis remains a potentially fatal disease, but it has become treatable as a chronic condition due to some CFTR-rescuing drugs that, when used in combination, increase in their therapeutic effect due to a synergic action. Also, dietary supplementation of natural compounds in combination with approved drugs could represent a promising strategy to further alleviate cystic fibrosis symptoms. On these bases, we screened by in silico drug repositioning 846 small synthetic or natural compounds from the AIFA database to evaluate their capacity to interact with the highly druggable lumacaftor binding site of F508del-CFTR. Among the identified hits, nicotinamide (NAM) was predicted to accommodate into the lumacaftor binding region of F508del-CFTR without competing against the drug but rather stabilizing its binding. The effective capacity of NAM to bind F508del-CFTR in a lumacaftor-uncompetitive manner was then validated experimentally by surface plasmon resonance analysis. Finally, the capacity of NAM to synergize with lumacaftor increasing its CFTR-rescuing activity was demonstrated in cell-based assays. This study suggests the possible identification of natural small molecules devoid of side effects and endowed with the capacity to synergize with drugs currently employed for the treatment of cystic fibrosis, which hopefully will increase the therapeutic efficacy with lower doses

Pushing the mass limit for intact launch and photoionization of large neutral biopolymers

Since their first discovery by Louis Dunoyer and Otto Stern, molecular beams have conquered research and technology. However, it has remained an outstanding challenge to isolate and photoionize beams of massive neutral polypeptides. Here we show that femtosecond desorption from a matrix-free sample in high vacuum can produce biomolecular beams at least 25 times more efficiently than nanosecond techniques. While it has also been difficult to photoionize large biomolecules, we find that tailored structures with an abundant exposure of tryptophan residues at their surface can be ionized by vacuum ultraviolet light. The combination of these desorption and ionization techniques allows us to observe molecular beams of neutral polypeptides with a mass exceeding 20,000 amu. They are composed of 50 amino acids – 25 tryptophan and 25 lysine residues – and 26 fluorinated alkyl chains. The tools presented here offer a basis for the preparation, control and detection of polypeptide beams