Steatosis, steatohepatitis and cancer immunotherapy: An intricate story

Immune checkpoint inhibitors represent one of the most significant recent advances in clinical oncology, since they dramatically improved the prognosis of deadly cancers such as melanomas and lung cancer. Treatment with these drugs may be complicated by the occurrence of clinically-relevant adverse drug reactions, most of which are immune-mediated, such as pneumonitis, colitis, endocrinopathies, nephritis, Stevens Johnson syndrome and toxic epidermal necrolysis. Drug-induced steatosis and steatohepatitis are not included among the typical forms of cancer immunotherapy-induced liver toxicity, which, instead, usually occurs as a panlobular hepatitis with prominent lymphocytic infiltrates. Nonetheless, non-alcoholic fatty liver disease is a risk factor for immunotherapy-induced hepatitis, and steatosis and steatohepatitis are frequently observed in this condition. In the present review we discuss how these pathology findings could be explained in the context of current models suggesting immune-mediated pathogenesis for steatohepatitis. We also review evidence suggesting that in patients with hepatocellular carcinoma, the presence of steatosis or steatohepatitis could predict a poor therapeutic response to these agents. How these findings could fit with immune-mediated mechanisms of these liver diseases will also be discussed

Deep sequential modeling for recommendation

We propose a model which extends variational autoencoders by exploiting the rich information present in the past preference history. We introduce a recurrent version of the VAE, where instead of passing a subset of the whole history regardless of temporal dependencies, we rather pass the consumption sequence subset through a recurrent neural network. At each time-step of the RNN, the sequence is fed through a series of fully-connected layers, the output of which models the probability distribution of the most likely future preferences. We show that handling temporal information is crucial for improving the accuracy of recommendation

The Relevance of Academic Libraries in the Twenty-First Century

The biggest challenge facing the library profession in the twenty-first century is staying relevant to its users. It is often stated that the Internet and Google have changed librarianship. This challenge, while significant, does not mean that libraries will go away. It is causing us to re-evaluate what we do, how we do it, and what role libraries have in the academy and in our culture at large. This column addresses some of the ways in which academic libraries can stay relevant throughout the twenty-first century

Simulation approach for assessing the performance of the γEWMA control chart

i) Purpose: The purpose of this paper is to evaluate the performance of a modified EWMA control chart ($\gamma$EWMA control chart), which considers data distribution and incorporate its correlation structure, simulating in-control and out-of-control processes and to select an adequate value for smoothing parameter with these conditions. ii) Design/methodology/approach: This paper is based on a simulation approach using the methodology for evaluating statistical methods proposed by Morris et al. (2019). Data were generated from a simulation considering two factors that associated with data: (1) quality variable distribution skewness as an indicator of quality variable distribution; (2) the autocorrelation structure for type of relationship between the observations and modeled by AR(1). In addition, one factor associated with the process was considered, (1) the shift in the process mean. In the following step, when the chart control is modeled, the fourth factor intervenes. This factor is a smoothing parameter. Finally, three indicators defined from the Run Length are used to evaluate γEWMA control chart performance this factors and their interactions. iii) Findings: Interaction analysis for four factor evidence that the modeling and selection of parameters is different for out-of-control and in-control processes therefore the considerations and parameters selected for each case must be carefully analyzed. For out-of-control processes, it is better to preserve the original features of the distribution (mean and variance) for the calculation of the control limits. It makes sense that highly autocorrelated observations require smaller smoothing parameter since the correlation structure enables the preservation of relevant information in past data. iv) Originality/value: The $\gamma$EWMA control chart there has advantages because it gathers, in single chart control: the process and modelling characteristics, and data structure process. Although there are other proposals for modified EWMA, none of them simultaneously analyze the four factors nor their interactions. The proposed $\gamma$EWMA allows setting the appropriate smoothing parameter when these three factors are considered

Venous Congestion in Acute Mechanical Intestinal Obstruction: A Computed Tomography Guided Study

Intestinal mechanical obstruction is often joined with a diffuse venous congestion.Computed Tomography (CT) is helpful in demonstrating this condition,important from a general-clinical,diagnostic and therapeutic point of view

A 3D printable adapter for solid-state fluorescence measurements: the case of an immobilized enzymatic bioreceptor for organophosphate pesticides detection

The widespread use of pesticides in the last decades and their accumulation into the environment gave rise to major environmental and human health concerns. To address this topic, the scientific community pointed out the need to develop methodologies to detect and measure the presence of pesticides in different matrices. Biosensors have been recently explored as fast, easy, and sensitive methods for direct organophosphate pesticides monitoring. Thus, the present work aimed at designing and testing a 3D printed adapter useful on different equipment, and a membrane support to immobilize the esterase-2 from Alicyclobacillus acidocaldarius (EST2) bioreceptor. The latter is labelled with the IAEDANS, a bright fluorescent probe. EST2 was selected since it shows a high specificity toward paraoxon. Our results showed good stability and replicability, with an increasing linear fluorescent intensity recorded from 15 to 150 pmol of labelled EST2. Linearity of data was also observed when using the immobilized labelled EST2 to detect increasing amounts of paraoxon, with a limit of detection (LOD) of 0.09 pmol. This LOD value reveals the high sensitivity of our membrane support when mounted on the 3D adapter, comparable to modern methods using robotic workstations. Notably, the use of an independent support significantly simplified the manipulation of the membrane during experimental procedures and enabled it to match the specificities of different systems. In sum, this work emphasizes the advantages of using 3D printed accessories adapted to respond to the newest research needs. Graphical abstract: [Figure not available: see fulltext.

A FRET Approach to Detect Paraoxon among Organophosphate Pesticides Using a Fluorescent Biosensor

The development of faster, sensitive and real-time methods for detecting organophosphate (OP) pesticides is of utmost priority in the in situ monitoring of these widespread compounds. Research on enzyme-based biosensors is increasing, and a promising candidate as a bioreceptor is the thermostable enzyme esterase-2 from Alicyclobacillus acidocaldarius (EST2), with a lipase-like Ser–His–Asp catalytic triad with a high affinity for OPs. This study aimed to evaluate the applicability of Förster resonance energy transfer (FRET) as a sensitive and reliable method to quantify OPs at environmentally relevant concentrations. For this purpose, the previously developed IAEDANS-labelled EST2-S35C mutant was used, in which tryptophan and IAEDANS fluorophores are the donor and the acceptor, respectively. Fluorometric measurements showed linearity with increased EST2-S35C concentrations. No significant interference was observed in the FRET measurements due to changes in the pH of the medium or the addition of other organic components (glucose, ascorbic acid or yeast extract). Fluorescence quenching due to the presence of paraoxon was observed at concentrations as low as 2 nM, which are considered harmful for the ecosystem. These results pave the way for further experiments encompassing more complex matrices

A deep learning approach for detecting security attacks on blockchain

In these last years, Blockchain technologies have been widely used in several application fields to improve data privacy and trustworthiness and security of systems. Although the blockchain is a powerful tool, it is not immune to cyber attacks: for instance, recently (January 2019) a successful 51% attack on Ethereum Classic has revealed security vulnerabilities of its platform. Under a statistical perspective, attacks can be seen as an anomalous observation, with a strong deviation from the regular behavior. Machine Learning is a science whose goal is to learn insights, patterns and outliers within large data repositories; hence, it can be exploit for blockchain attack detection. In this work, we define an anomaly detection system based on a encoder-decoder deep learning model, that is trained exploiting aggregate information extracted by monitoring blockchain activities. Experiments on complete historical logs of Ethereum Classic network prove the capability of the our model to effectively detect the publicly reported attacks. To the best of our knowledge, our approach is the first one that provides a comprehensive and feasible solution to monitor the security of blockchain transactions

Small Bowel Mechanical Occlusion and Computed Tomography Severity Indicators: What to Look for

Computed Tomography (CT) allows detecting different aspects of small bowel pathology in course of mechanical obstruction, principally correlated to circulatory disturbances, giving useful indications for a surgical treatment