A key element of the Quality-by-Design initiative set forth by the pharmaceutical regulatory agencies (such as the U.S. Food and Drug Administration) is the determination of the design space (DS) for a new pharmaceutical product. When the determination of the DS cannot be assisted by the use of a first-principles model, one must heavily rely on experiments. In many cases, the DS is found using experiments carried out within a domain of input combinations (e.g., raw materials properties and process operating conditions) that result from similar products already developed. This input domain is the so-called knowledge space, and the related experimentation can be very demanding, especially if the number of inputs is large. To limit the extension of the domain over which the experiments are carried out (hence, to reduce the experimental effort), a methodology is proposed that aims at segmenting the knowledge space in such a way as to identify a subspace of it (which we call the experiment space) that most likely brackets the DS. The methodology relies on the exploitation of historical databases on products that have already been developed and are similar to the new one, and is based on the inversion of a latent-variable model. The relationship between the regulatory concept of DS and the mathematical concept of null space is discussed for products characterized by one equality constraint specification, and the effect of model prediction uncertainty is accounted for. Three simulated examples are used to test the effectiveness of the proposed segmentation methodology. The segmentation results are shown to be effective, in that the designated experiment space is able to effectively bracket the DS and is much narrower than the historical knowledge space.
The possibility of using near-infrared spectroscopy (NIRS) for the authentication of wild European sea bass ( Dicentrarchus labrax ) was investigated in this study. Three different chemometric techniques to process the NIR spectra were developed, and their ability to discriminate between wild and farmed sea bass samples was evaluated. One approach used spectral information to directly build the discrimination model in a latent variable space; the second approach first used wavelets to transform the spectral information and subsequently derived the discrimination model using the transformed spectra; in the third approach a cascaded arrangement was proposed whereby very limited chemical information was first estimated from spectra using a regression model, and this estimated information was then used to build the discrimination model in a latent variable space. All techniques showed that NIRS can be used to reliably discriminate between wild and farmed sea bass, achieving the same classification performance as classification methods that use chemical properties and morphometric traits. However, compared to methods based on chemical analysis, NIRS-based classification methods do not require reagents and are simpler, faster, more economical, and environmentally safer. All proposed techniques indicated that the most predictive spectral regions were those related to the absorbance of groups CH, CH(2), CH(3), and H(2)O, which are related to fat, fatty acids, and water content.
Vibrio is a very diverse genus that is responsible for different human and animal diseases. The accurate identification of Vibrio at the species level is important to assess the risks related to public health and diseases caused by aquatic organisms. The ecology of Vibrio spp., together with their genetic background, represents an important key for species discrimination and evolution. Thus, analyses of population structure and ecology association are necessary for reliable characterization of bacteria and to investigate whether bacterial species are going through adaptation processes. In this study, a population of Vibrionaceae was isolated from shellfish of the Venice lagoon and analyzed in depth to study its structure and distribution in the environment. A multilocus sequence analysis (MLSA) was developed on the basis of four housekeeping genes. Both molecular and biochemical approaches were used for species characterization, and the results were compared to assess the consistency of the two methods. In addition, strain ecology and the association between genetic information and environment were investigated through statistical models. The phylogenetic and population analyses achieved good species clustering, while biochemical identification was demonstrated to be imprecise. In addition, this study provided a fine-scale overview of the distribution of Vibrio spp. in the Venice lagoon, and the results highlighted a preferential association of the species toward specific ecological variables. These findings support the use of MLSA for taxonomic studies and demonstrate the need to consider environmental information to obtain broader and more accurate bacterial characterization. Vibrio spp. are Gram-negative halophilic bacteria belonging to the class Gammaproteobacteria. Vibrio is one of the most studied and diverse genera of microorganisms found in aquatic ecosystems and comprises the major culturable bacteria in marine and estuarine environments (1). According to the Association of Vibrio Biologists (AViB; http://www2.ioc.fiocruz.br/vibrio/AVib /species.html), there are 99 accepted or proposed Vibrio species, although the recent description of new species has led to a constantly changing taxonomy. Vibrio spp. are frequently isolated from fish, fish products, and edible shellfish, and a large number of species are pathogenic to different hosts. Some species, such as V. cholerae, V. parahaemolyticus, and V. vulnificus, cause serious food-borne gastroenteritis in humans. Other species, such as V. anguillarum and V. salmonicida, are pathogenic for fish; V. splendidus-related species are pathogenic for bivalves, and V. harveyi and V. campbellii are pathogenic for shrimps (1, 2, 3). Recently, Austin suggested a classification of zoonotic Vibrio in two classes named "higher-risk" vibrios (V. cholerae, V. parahaemolyticus, and V. vulnificus) and "lower-risk" vibrios (V. alginolyticus, V. fluvialis, V. furnissii, V. harveyi, and V. mimicus) (4). Bivalve mollusks such as clams and mussels represent products of great econ...
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