Human Neural Stem Cell-Based Drug Product: Clinical and Nonclinical Characterization

Translation of cell therapies into clinical practice requires the adoption of robust production protocols in order to optimize and standardize the manufacture and cryopreservation of cells, in compliance with good manufacturing practice regulations. Between 2012 and 2020, we conducted two phase I clinical trials (EudraCT 2009-014484-39, EudraCT 2015-004855-37) on amyotrophic lateral sclerosis secondary progressive multiple sclerosis patients, respectively, treating them with human neural stem cells. Our production process of a hNSC-based medicinal product is the first to use brain tissue samples extracted from fetuses that died in spontaneous abortion or miscarriage. It consists of selection, isolation and expansion of hNSCs and ends with the final pharmaceutical formulation tailored to a specific patient, in compliance with the approved clinical protocol. The cells used in these clinical trials were analyzed in order to confirm their microbiological safety; each batch was also tested to assess identity, potency and safety through morphological and functional assays. Preclinical, clinical and in vitro nonclinical data have proved that our cells are safe and stable, and that the production process can provide a high level of reproducibility of the cultures. Here, we describe the quality control strategy for the characterization of the hNSCs used in the above-mentioned clinical trials.     

Aerobic Oxidation of Glucose with Gold Catalyst: Hydrogen Peroxide as Intermediate and Reagent

Careful analytical determinations show that the gold‐catalysed aerobic oxidation of glucose occurs through a two‐electrons mechanism leading to gluconate and hydrogen peroxide. This latter decomposes before reaching the critical concentration for competing with O₂ in glucose oxidation. A mechanism of glucose oxidation on gold nanoparticles is presented.     

An SLA-based Broker for Cloud Infrastructures

The breakthrough of Cloud comes from its service oriented perspective where everything, including the infrastructure, is provided “as a service”. This model is really attractive and convenient for both providers and consumers, as a consequence the Cloud paradigm is quickly growing and widely spreading, also in non commercial contexts. In such a scenario, we propose to incorporate some elements of volunteer computing into the Cloud paradigm through the Cloud@Home solution, involving into the mix nodes and devices provided by potentially any owners or administrators, disclosing high computational resources to contributors and also allowing to maximize their utilization. This paper presents and discusses the first step towards Cloud@Home: providing quality of service and service level agreement facilities on top of unreliable, intermittent Cloud providers. Some of the main issues and challenges of Cloud@Home, such as the monitoring, management and brokering of resources according to service level requirements are addressed through the design of a framework core architecture. All the tasks committed to the architecture’s modules and components, as well as the most relevant component interactions, are identified and discussed from both the structural and the behavioural viewpoints. Some encouraging experiments on an early implementation prototype deployed in a real testing environment are also documented in the paper.     

Augmentative Pharmacological Strategies in Treatment-Resistant Major Depression: A Comprehensive Review

Treatment resistant depression (TRD) is associated with poor outcomes, but a consensus is lacking in the literature regarding which compound represents the best pharmacological augmentation strategy to antidepressants (AD). In the present review, we identify the available literature regarding the pharmacological augmentation to AD in TRD. Research in the main psychiatric databases was performed (PubMed, ISI Web of Knowledge, PsychInfo). Only original articles in English with the main topic being pharmacological augmentation in TRD and presenting a precise definition of TRD were included. Aripiprazole and lithium were the most investigated molecules, and aripiprazole presented the strongest evidence of efficacy. Moreover, olanzapine, quetiapine, cariprazine, risperidone, and ziprasidone showed positive results but to a lesser extent. Brexpiprazole and intranasal esketamine need further study in real-world practice. Intravenous ketamine presented an evincible AD effect in the short-term. The efficacy of adjunctive ADs, antiepileptic drugs, psychostimulants, pramipexole, ropinirole, acetyl-salicylic acid, metyrapone, reserpine, testosterone, T3/T4, naltrexone, SAMe, and zinc cannot be precisely estimated in light of the limited available data. Studies on lamotrigine and pindolol reported negative results. According to our results, aripiprazole and lithium may be considered by clinicians as potential effective augmentative strategies in TRD, although the data regarding lithium are somewhat controversial. Reliable conclusions about the other molecules cannot be drawn. Further controlled comparative studies, standardized in terms of design, doses, and duration of the augmentative treatments, are needed to formulate definitive conclusions.     

Behaviour Factor of code-designed steel moment-resisting frames

Current seismic codes are based on force-controlled design or capacity design, using the base shear concept. The most important parameter in this approach is the response modification factor, also called behaviour factor, which is used to design the structure at the ultimate limit state by taking into account its capacity to dissipate energy by means of plastic deformations. In this paper overstrength, redundancy and ductility response modification factors of steel moment resisting frames are evaluated. In order to cover a wide range of structural characteristics, 12 steel moment-resisting frames (6 regular and 6 irregular in elevation) have been designed and analysed. Both static pushover analyses and nonlinear incremental dynamic analyses have been performed. The investigation focuses on the effects of some parameters influencing the responsemodification factor, including the regularity, the number of spans and the number of storeys. As a conclusion, a local ductility criterion has been proposed to improve the provisions given in the Italian seismic code.     

Data Fusion for Food Authentication: Fresh/Frozen–Thawed Discrimination in West African Goatfish (Pseudupeneus prayensis) Fillets

The substitution of fresh fish with frozen–thawed fish is a typical fraud that not only damages consumers from an economical point of view, but also causes safety issues. Furthermore, fish authentication is important for correct product labeling, as promoted by recent regulatory actions. In this paper, we present the results of the authentication of fresh west African goatfish (Pseudupeneus prayensis) fillets using different analytical technologies, namely a portable visible/near-infrared spectrometer, a compact digital camera, and a texture analyzer. First, the classification performance of the abovementioned analytical technologies is evaluated and compared. Then, it is shown how the fusion of different technologies can be effectively used to improve the classification accuracy. Particularly, spectra and color features extracted from digital images returned a classification accuracy of 100 and 98.5 %, respectively, when considered separately. However, the classification accuracy fell to 80 % when considering measurements taken with a 24-h delay. Data fusion, instead, allowed a classification accuracy of 100 % also after 24 h. Hence, the combination of a spectrometer and a digital camera is very promising for cost-effective on-line/at-line applications, as both sensors are rapid, non-invasive, and do not require sample preparation. Furthermore, since more than 200 samples were collected over a prolonged period of time (1 year), the classification models encompassed some sources of variability (seasonality effects and size) that are not usually accounted for in similar studies.     

PLUMED 2: New feathers for an old bird

Enhancing sampling and analyzing simulations are central issues in molecular simulation. Recently, we introduced PLUMED, an open-source plug-in that provides some of the most popular molecular dynamics (MD) codes with implementations of a variety of different enhanced sampling algorithms and collective variables (CVs). The rapid changes in this field, in particular new directions in enhanced sampling and dimensionality reduction together with new hardware, require a code that is more flexible and more efficient. We therefore present PLUMED 2 here—a complete rewrite of the code in an object-oriented programming language (C++). This new version introduces greater flexibility and greater modularity, which both extends its core capabilities and makes it far easier to add new methods and CVs. It also has a simpler interface with the MD engines and provides a single software library containing both tools and core facilities. Ultimately, the new code better serves the ever-growing community of users and contributors in coping with the new challenges arising in the field.     

Labeling source code with information retrieval methods: an empirical study

To support program comprehension, software artifacts can be labeled—for example within software visualization tools—with a set of representative words, hereby referred to as labels. Such labels can be obtained using various approaches, including Information Retrieval (IR) methods or other simple heuristics. They provide a bird-eye’s view of the source code, allowing developers to look over software components fast and make more informed decisions on which parts of the source code they need to analyze in detail. However, few empirical studies have been conducted to verify whether the extracted labels make sense to software developers. This paper investigates (i) to what extent various IR techniques and other simple heuristics overlap with (and differ from) labeling performed by humans; (ii) what kinds of source code terms do humans use when labeling software artifacts; and (iii) what factors—in particular what characteristics of the artifacts to be labeled—influence the performance of automatic labeling techniques. We conducted two experiments in which we asked a group of students (38 in total) to label 20 classes from two Java software systems, JHotDraw and eXVantage. Then, we analyzed to what extent the words identified with an automated technique—including Vector Space Models, Latent Semantic Indexing (LSI), latent Dirichlet allocation (LDA), as well as customized heuristics extracting words from specific source code elements—overlap with those identified by humans. Results indicate that, in most cases, simpler automatic labeling techniques—based on the use of words extracted from class and method names as well as from class comments—better reflect human-based labeling. Indeed, clustering-based approaches (LSI and LDA) are more worthwhile to be used for source code artifacts having a high verbosity, as well as for artifacts requiring more effort to be manually labeled. The obtained results help to define guidelines on how to build effective automatic labeling techniques, and provide some insights on the actual usefulness of automatic labeling techniques during program comprehension tasks.