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The almost complete absence of regulations to protect invertebrates is a common condition in legal systems, including the European one, especially when it comes to invertebrates intended for human consumption. Thus, in the vast majority of cases, edible invertebrates do not receive even the most basic protection at slaughter. Despite recent research indicating that invertebrates are capable of feeling pain and stress, the humane step of stunning is not used on them. This is also the case for land snails, which are gastropod invertebrates whose consumption has now reached significant levels, already involving tonnes and that is expected to increase significantly as edible snail farming becomes more popular as a relatively low-cost, easy-to-perform, and sustainable alternative animal husbandry, thereby making land snails an increasingly economically important species. This paper presents and investigates a proposed stunning method based on the immersion of mollusks in CO 2 -supplemented and refrigerated water that could be used in the snail meat production chain to reduce the slaughter suffering of millions of these invertebrates. To this end, body condition descriptors (hemolymph parameters) in snails were determined before and after CO 2 treatment in cold water, while generating useful data for defining a preliminary set of reference intervals for basal values., (© 2024. The Author(s).)

Glioblastoma multiforme (GBM) is usually treated with surgery followed by adjuvant partial radiotherapy combined with temozolomide (TMZ) chemotherapy. Recent studies demonstrated a better survival and good response to TMZ in methylguanine-DNA methyltransferase ( MGMT )-methylated GBM cases. However, approximately 20% of patients with MGMT -unmethylated GBM display an unexpectedly favorable outcome. Therefore, additional mechanisms related to the TMZ response need to be investigated. As such, we decided to investigate the clinical relevance of six miRNAs involved in brain tumorigenesis (miR-181c, miR-181d, miR-21, miR-195, miR-196b, miR-648) as additional markers of response and survival in patients receiving TMZ for GBM. We evaluated miRNA expression and the interplay between miRNAs in 112 IDH wt GBMs by applying commercial assays. Then, we correlated the miRNA expression with patients' clinical outcomes. Upon bivariate analyses, we found a significant association between the expression levels of the miRNAs analyzed, but, more interestingly, the OS curves show that the combination of low miR-648 and miR-181c or miR-181d expressions is associated with a worse prognosis than cases with other low-expression miRNA pairs. To conclude, we found how specific miRNA pairs can influence survival in GBM cases treated with TMZ.

Plant pathogens pose a persistent threat to grape production, causing significant economic losses if disease management strategies are not carefully planned and implemented. Simulation models are one approach to address this challenge because they provide short-term and field-scale disease prediction by incorporating the biological mechanisms of the disease process and the different phenological stages of the vines. In this study, we developed a Bayesian model to predict the probability of Plasmopara viticola infection in grapevines, considering various disease management approaches. To aid decision-making, we introduced a multi-attribute utility function that incorporated a sustainability index for each strategy. The data used in this study were derived from trials conducted during the production years 2018-2020, involving the application of five disease management strategies: conventional Integrated Pest Management (IPM), conventional organic, IPM with substantial fungicide reduction combined with host-defense inducing biostimulants, organic management with biostimulants, and the use of biostimulants only. Two scenarios were considered, one with medium pathogen pressure (Average) and another with high pathogen pressure (Severe). The results indicated that when sustainability indexes were not considered, the conventional IPM strategy provided the most effective disease management in the Average scenario. However, when sustainability indexes were included, the utility values of conventional strategies approached those of reduced fungicide strategies due to their lower environmental impact. In the Severe scenario, the application of biostimulants alone emerged as the most effective strategy. These results suggest that in situations of high disease pressure, the use of conventional strategies effectively combats the disease but at the expense of a greater environmental impact. In contrast to mechanistic-deterministic approaches recently published in the literature, the proposed Bayesian model takes into account the main sources of heterogeneity through the two group-level effects, providing accurate predictions, although precise estimates of random effects may require larger samples than usual. Moreover, the proposed Bayesian model assists the agronomist in selecting the most effective crop protection strategy while accounting for induced environmental side effects through customizable utility functions., Competing Interests: The authors declare that the research was conducted in theabsence of any commercial or financial relationships that could beconstrued as a potential conflict of interest., (Copyright © 2023 Valleggi, Carella, Perria, Mugnai and Stefanini.)

The gray wolf (Canis lupus) expanded its distribution in Europe over the last few decades. To better understand the extent to which wolves could re-occupy their historical range, it is important to test if anthropization can affect their fitness-related traits. After having accounted for ecologically relevant confounders, we assessed how anthropization influenced i) the growth of wolves during their first year of age (n = 53), ii) sexual dimorphism between male and female adult wolves (n = 121), in a sample of individuals that had been found dead in Italy between 1999 and 2021. Wolves in anthropized areas have a smaller overall variation in their body mass, during their first year of age. Because they already have slightly higher body weight at 3-5 months, possibly due to the availability of human-derived food sources. The difference in the body weight of adult females and males slightly increases with anthropization. However, this happens because of an increase in the body mass of males only, possibly due to sex-specific differences in dispersal and/or to "dispersal phenotypes". Anthropization in Italy does not seem to have any clear, nor large, effect on the body mass of wolves. As body mass is in turn linked to important processes, like survival and reproduction, our findings indicates that wolves could potentially re-occupy most of their historical range in Europe, as anthropized landscapes do not seem to constrain such of an important life-history trait. Wolf management could therefore be needed across vast spatial scales and in anthropized areas prone to social conflicts., Competing Interests: The authors declare no competing interest, regarding the study., (Copyright: © 2023 Cerri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Glioblastoma multiforme (GBM) remains one of the tumors with the worst prognosis. In recent years, a better overall survival (OS) has been described in cases subjected to Gross Total Resection (GTR) that were presenting hypermethylation of Methylguanine-DNA methyltransferase (MGMT) promoter. Recently, also the expression of specific miRNAs involved in MGMT silencing has been related to survival. In this study, we evaluate MGMT expression by immunohistochemistry (IHC), MGMT promoter methylation and miRNA expression in 112 GBMs and correlate the data to patients' clinical outcomes. Statistical analyses demonstrate a significant association between positive MGMT IHC and the expression of miR-181c, miR-195, miR-648 and miR-767.3p between unmethylated cases and the low expression of miR-181d and miR-648 and between methylated cases and the low expression of miR-196b. Addressing the concerns of clinical associations, a better OS has been described in presence of negative MGMT IHC, in methylated patients and in the cases with miR-21, miR-196b overexpression or miR-767.3 downregulation. In addition, a better progression-free survival (PFS) is associated with MGMT methylation and GTR but not with MGMT IHC and miRNA expression. In conclusion, our data reinforce the clinical relevance of miRNA expression as an additional marker to predict efficacy of chemoradiation in GBM.

Introduction: Severe respiratory syndrome coronavirus 2 (SARS-CoV-2) uses the androgen receptor (AR), through ACE2 receptor and TMPRSS2, to enter nasal and upper airways epithelial cells. Genetic analyses revealed that HSD3B1 P1245C polymorphic variant increases dihydrotestosterone production and upregulation of TMPRSS2 with respect to P1245A variant, thus possibly influencing SARS-CoV-2 infection. Our aim was to characterize the HSD3B1 polymorphism status and its potential association with clinical outcomes in hospitalized patients with COVID-19 in Southern Switzerland. Materials and Methods: The cohort included 400 patients hospitalized for COVID-19 during the first wave between February and May 2020 in two different hospitals of Canton Ticino. Genomic DNA was extracted from formalin-fixed paraffin-embedded tissue blocks, and HSD3B1 gene polymorphism was evaluated by Sanger sequencing. Statistical associations were verified using different test. Results: HSD3B1 polymorphic variants were not associated with a single classical factor related to worse clinical prognosis in hospitalized patients with SARS-CoV-2. However, in specific subgroups, HSD3B1 variants played a clinical role: intensive care unit admission was more probable in patients with P1245C diabetes compared with P1245A individuals without this comorbidity and death was more associated with hypertensive P1245A>C cases than patients with P1245A diabetes without hypertension. Discussion: This is the first study showing that HSD3B1 gene status may influence the severity of SARS-CoV-2 infection. If confirmed, our results could lead to the introduction of HSD3B1 gene status analysis in patients infected with SARS-CoV-2 to predict clinical outcome., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Epistolio, Ramelli, Ottaviano, Crupi, Marandino, Biggiogero, Maida, Ruinelli, Vogl, Mangan, Pascale, Cantù, Ceschi, Bernasconi, Mazzucchelli, Catapano, Alimonti, Garzoni, Gillessen Sommer, Stefanini, Franzetti-Pellanda, Frattini and Pereira Mestre.)

Introduction: Circulating tumor DNA (ctDNA) correlates with the response to therapy in different types of cancer. However, in patients with locally advanced rectal cancer (LARC), little is known about how ctDNA levels change with neoadjuvant chemoradiation (Na-ChRT) and how they correlate with treatment response. This work aimed to explore the value of serial liquid biopsies in monitoring response after Na-ChRT with the hypothesis that this could become a reliable biomarker to identify patients with a complete response, candidates for non-operative management., Materials and Methods: Twenty-five consecutive LARC patients undergoing long-term Na-ChRT therapy were included. Applying next-generation sequencing (NGS), we characterized DNA extracted from formalin-fixed paraffin embedded diagnostic biopsy and resection tissue and plasma ctDNA collected at the following time points: the first and last days of radiotherapy (T 0 , T end ), at 4 (T 4 ), 7 (T 7 ) weeks after radiotherapy, on the day of surgery (T op ), and 3-7 days after surgery (T post-op ). On the day of surgery, a mesenteric vein sample was also collected (T IMV ). The relationship between the ctDNA at those time-points and the tumor regression grade (TRG) of the surgical specimen was statistically explored., Results: We found no association between the disappearance of ctDNA mutations in plasma samples and pathological complete response (TRG1) as ctDNA was undetectable in the majority of patients from Tend on. However, we observed that the poor (TRG 4) response to Na-ChRT was significantly associated with a positive liquid biopsy at the T op ., Conclusions: ctDNA evaluation by NGS technology may identify LARC patients with poor response to Na-ChRT. In contrast, this technique does not seem useful for identifying patients prone to developing a complete response., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Roesel, Epistolio, Molinari, Saletti, De Dosso, Valli, Franzetti-Pellanda, Deantonio, Biggiogero, Spina, Popeskou, Cristaudi, Mongelli, Mazzucchelli, Stefanini, Frattini and Christoforidis.)

Background: Cadmium is a widespread carcinogen. We previously showed that the administration of low CdCl 2 doses for 24 h to healthy C3H10T1/2Cl8 mouse embryonic fibroblast cell line at the beginning of Cell Transformation Assay (CTA), up regulates genes involved in metal scavenging and antioxidant defense, like metallothioneines, glutathione S-transferases and heat shock proteins. Still, although most cells thrive normally in the following weeks, malignancy is triggered by CdCl 2 and leads to the appearance of foci of transformed cells at the end of the CTA. In this work we aim at elucidating the early metabolic deregulation induced by cadmium, underlying healthy cell transformation into malignant cells., Methods: Respiratory metabolism was investigated through Seahorse Agilent assays, while oxidative stress level was assessed through fluorescent probes; DNA damage was evaluated by Comet assay, and mitochondrial morphology was analyzed in confocal microscopy., Results: Results show that the initial response to CdCl 2 involves mitochondria rearrangement into a perinuclear network. However, SOD1 and SOD2 activities are inhibited, leading to increased superoxide anion level, which in turn causes DNA strand breaks. From the metabolic point of view, cells increase their glycolytic flux, while all extra NADH produced is still efficiently reoxidized by mitochondria., Conclusions: Our results confirm previously shown response against cadmium toxicity; new data about glycolytic increase and mitochondrial rearrangements suggest pathways leading to cell transformation., General Significance: In this work we exploit the widely used, well known CTA, which allows following healthy cells transformation into a malignant phenotype, to understand early events in cadmium-induced carcinogenesis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The number of spots to monitor to evaluate soil respiration (R s ) is often chosen on an empirical or conventional basis. To obtain an insight into the necessary number of spots to account for R s variability in a Mediterranean pine-dominated mixed forest, we measured R s all year long on sixteen dates with a portable gas-analyser in 50 spots per date within an area 1/3 ha wide. Linear mixed-effects models with soil temperature and litter moisture as descriptors, were fitted to the collected data and then evaluated in a Monte Carlo simulation on a progressively decreasing number of spots to identify the minimum number required to estimate R s with a given confidence interval. We found that monitoring less than 14 spots would have resulted in a 10% probability of not fitting the model, while monitoring 20 spots would have reduced the same probability to about 5% and was the best compromise between field efforts and quality of the results. A simple rainfall index functional to select sampling dates during the summer drought is proposed.

Object: The treatment of choice in glioblastoma (GBM) is the maximal surgical extent of resection (EOR) followed by adjuvant chemo-radiotherapy. Furthermore, methylguanine-DNA methyltransferase (MGMT) promoter methylation is associated with prolonged overall survival (OS) and progression free survival (PFS). The objective of the present study is correlate the biomolecular aspects in relation with EOR. Materials and methods: We analyzed a series of 116 patients with IDH-1 wild type GBM and different EOR (Gross Total Resection-GTR-, Partial Resection-PR- and Biopsy), treated with adjuvant chemo-radiotherapy. The MGMT status was analyzed in terms of promoter methylation and protein expression. Results: When GTR was possible, OS and PFS were significantly better compared to the other two groups ( p = 0.001 and p = 0.035, respectively). MGMT methylation was significantly associated with better OS in the biopsy group ( p = 0.022) and better OS and PFS in PR ( p = 0.02 and p = 0.012, respectively), but not in the GTR group ( p = 0.252 for OS, p = 0.256 for PFS) nor the PFS in the biopsy group ( p = 0.259). MGMT protein expression levels do not show any association with OS and PFS, regardless of the type of surgery. Conclusions: Our study confirms the positive association of a safe maximal EOR with better OS and PFS, and indicates a positive prognostic value of MGMT methylation status only in case of the presence of residual tumor tissue. MGMT protein expression seems not to play a clinical role in relation with the type of surgery., (Copyright © 2020 Marchi, Sahnane, Cerutti, Cipriani, Barizzi, Stefanini, Epistolio, Cerati, Balbi, Mazzucchelli, Sessa, Pesce, Reinert and Frattini.)

Background: Aberrant sialylation is a characteristic feature associated with cancer. The four types of mammalian sialidases identified to date have been shown to behave in different manners during carcinogenesis. While NEU1, NEU2 and NEU4 have been observed to oppose malignant phenotypes, the membrane-bound sialidase NEU3 was revealed to promote cancer progression., Objectives: With the aim of improving the knowledge about sialidases deregulation in various cancer types, we investigated the amount of NEU1, NEU3 and NEU4 transcripts in paired normal and tumor tissues from 170 patients with 11 cancer types., Methods: mRNA was extracted from patients' tissue specimens and retrotranscribed into cDNA, which was quantified by Real-Time PCR., Results: We found NEU1 and NEU3 to be up regulated, while NEU4 was down regulated in most cancer types. In particular, colorectal cancer tissues showed the highest increase in NEU3 expression. Both NEU1 and NEU3 showed a strong up-regulation in ovarian cancer., Conclusions: Our data show that human sialidases are expressed at different levels in healthy tissues and are strongly deregulated in tumors. Moreover, sialidases expression in our European cohort showed significant differences from Asian populations. Some of these peculiar features open potential applications of sialidases in cancer diagnosis and therapy.

In this paper, the development of a probabilistic network for the diagnosis of acute cardiopulmonary diseases is presented in detail. A panel of expert physicians collaborated to specify the qualitative part, which is a directed acyclic graph defining a factorization of the joint probability distribution of domain variables into univariate conditional distributions. The quantitative part, which is a set of parametric models defining these univariate conditional distributions, was estimated following the Bayesian paradigm. In particular, we exploited an original reparameterization of Beta and categorical logistic regression models to elicit the joint prior distribution of parameters from medical experts, and updated it by conditioning on a dataset of hospital records via Markov chain Monte Carlo simulation. Refinement was iteratively performed until the probabilistic network provided satisfactory concordance index values for several acute diseases and reasonable diagnosis for six fictitious patient cases. The probabilistic network can be employed to perform medical diagnosis on a total of 63 diseases (38 acute and 25 chronic) on the basis of up to 167 patient findings., (© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The identification of the carcinogenic risk of chemicals is currently mainly based on animal studies. The in vitro Cell Transformation Assays (CTAs) are a promising alternative to be considered in an integrated approach. CTAs measure the induction of foci of transformed cells. CTAs model key stages of the in vivo neoplastic process and are able to detect both genotoxic and some non-genotoxic compounds, being the only in vitro method able to deal with the latter. Despite their favorable features, CTAs can be further improved, especially reducing the possible subjectivity arising from the last phase of the protocol, namely visual scoring of foci using coded morphological features. By taking advantage of digital image analysis, the aim of our work is to translate morphological features into statistical descriptors of foci images, and to use them to mimic the classification performances of the visual scorer to discriminate between transformed and non-transformed foci. Here we present a classifier based on five descriptors trained on a dataset of 1364 foci, obtained with different compounds and concentrations. Our classifier showed accuracy, sensitivity and specificity equal to 0.77 and an area under the curve (AUC) of 0.84. The presented classifier outperforms a previously published model., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Cell Transformation Assays (CTAs) have long been proposed for the identification of chemical carcinogenicity potential. The endpoint of these in vitro assays is represented by the phenotypic alterations in cultured cells, which are characterized by the change from the non-transformed to the transformed phenotype. Despite the wide fields of application and the numerous advantages of CTAs, their use in regulatory toxicology has been limited in part due to concerns about the subjective nature of visual scoring, i.e. the step in which transformed colonies or foci are evaluated through morphological features. An objective evaluation of morphological features has been previously obtained through automated digital processing of foci images to extract the value of three statistical image descriptors. In this study a further potential of the CTA using BALB/c 3T3 cells is addressed by analysing the effect of increasing concentrations of two known carcinogens, benzo[a]pyrene and NiCl 2 , with different modes of action on foci morphology. The main result of our quantitative evaluation shows that the concentration of the considered carcinogens has an effect on foci morphology that is statistically significant for the mean of two among the three selected descriptors. Statistical significance also corresponds to visual relevance. The statistical analysis of variations in foci morphology due to concentration allowed to quantify morphological changes that can be visually appreciated but not precisely determined. Therefore, it has the potential of providing new quantitative parameters in CTAs, and of exploiting all the information encoded in foci. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

The in vitro Cell Transformation Assay (CTA) is a powerful tool for mechanistic studies of carcinogenesis. The endpoint is the classification of transformed colonies (foci) by means of standard morphological features. To increase throughput and reliability of CTAs, one of the suggested follow-up activities is to exploit the comprehension of the mechanisms underlying cell transformation. To this end, we have performed CTAs testing CdCl2, a widespread environmental contaminant classified as a human carcinogen with the underlying mechanisms of action not completely understood. We have isolated and re-seeded the cells at the end (6weeks) of in vitro CTAs to further identify the biochemical pathways underlying the transformed phenotype of foci. Morphological evaluations and proliferative assays confirmed the loss of contact-inhibition and the higher proliferative rate of transformed clones. The biochemical analysis of EGFR pathway revealed that, despite the same initial carcinogenic stimulus (1μM CdCl2 for 24h), transformed clones are characterized by the activation of two different molecular pathways: proliferation (Erk activation) or survival (Akt activation). Our preliminary results on molecular characterization of cell clones from different foci could be exploited for CTAs improvement, supporting the comprehension of the in vivo process and complementing the morphological evaluation of foci., (Copyright © 2016. Published by Elsevier Ltd.)

Carcinogenesis is a multi-step process involving genetic alterations and non-genotoxic mechanisms. The in vitro cell transformation assay (CTA) is a promising tool for both genotoxic and non-genotoxic carcinogenesis. CTA relies on the ability of cells (e.g. BALB/c 3T3 mouse embryo fibroblasts) to develop a transformed phenotype after the treatment with suspected carcinogens. The classification of the transformed phenotype is based on coded morphological features, which are scored under a light microscope by trained experts. This procedure is time-consuming and somewhat prone to subjectivity. Herewith we provide a promising approach based on image analysis to support the scoring of malignant foci in BALB/c 3T3 CTA. The image analysis system is a quantitative approach, based on measuring features of malignant foci: dimension, multilayered growth, and invasivity into the surrounding monolayer of non-transformed cells. A logistic regression model was developed to estimate the probability for each focus to be transformed as a function of three statistical image descriptors. The estimated sensitivity of the derived classifier (untransformed against Type III) was 0.9, with an Area Under the Curve (AUC) value equal to 0.90 under the Receiver Operating Characteristics (ROC) curve., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Bayesian networks are possibly the most successful graphical models to build decision support systems. Building the structure of large networks is still a challenging task, but Bayesian methods are particularly suited to exploit experts' degree of belief in a quantitative way while learning the network structure from data. In this paper details are provided about how to build a prior distribution on the space of network structures by eliciting a chain graph model on structural reference features. Several structural features expected to be often useful during the elicitation are described. The statistical background needed to effectively use this approach is summarized, and some potential pitfalls are illustrated. Finally, a few seminal contributions from the literature are reformulated in terms of structural features.

In vitro cell transformation assays (CTAs) have been shown to model important stages of in vivo carcinogenesis and have the potential to predict carcinogenicity in humans. Advantages of CTAs are their ability of revealing both genotoxic and non-genotoxic carcinogens while reducing both experimental costs and the number of animals used. The endpoint of the CTA is foci formation, and requires classification under light microscopy based on morphology. Thus current limitations for the wide adoption of the assay partially depend on a fair degree of subjectivity in foci scoring. An objective evaluation may be obtained after separating foci from background monolayer in the digital image, and quantifying values of statistical descriptors which are selected to capture eye-scored morphological features. The aim of this study was to develop statistical descriptors to be applied to transformed foci of BALB/c 3T3, which cover foci size, multilayering and invasive cell growth into the background monolayer. Proposed descriptors were applied to a database of 407 foci images to explore the numerical features, and to illustrate open problems and potential solutions., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

In a recent series of papers written by Jaworska with different coauthors, compelling reasons for adopting a probabilistic approach to Integrated Testing Strategies were detailed. In a case study on skin sensitization, a Bayesian Network proved to be effective in adapting testing strategies to the available evidence. There is no doubt that probabilistic Integrated Testing Strategies are one way to pursue the goals of 3Rs effectively; nevertheless, some issues deserve further comment to pinpoint statistical criticalities and to widen the methodological perspective towards Bayesian graphical models.

The human carcinogenicity evaluation of chemicals has a great impact on public health. In vitro methods, such as the cell transformation assay (CTA), allow for a fast and reliable assessment of the carcinogenic potential of a chemical compound in comparison with the standard two-year bioassay. The scoring and classification of foci in selected cell lines is performed, after staining, by light microscopy. Foci can be separated into three classes: type I, which are scored as non-transformed, and types II and III that are considered to include fully transformed foci. However, in a number of cases, even an expert is uncertain about the attribution of a focus to a given class, due to its mixed or intermediate nature. Here, we suggest a simple approach to classifying mixed or intermediate foci by exploiting the quantitative information available from images, which is captured by statistical descriptors. A quantitative index is proposed, to describe the degree of dissimilarity of mixed and intermediate images to the three well-distinguished classes., (2011 FRAME.)

The associations existing among different biomarkers are important in clinical settings because they contribute to the characterisation of specific pathways related to the natural history of the disease, genetic and environmental determinants. Despite the availability of binary/linear (or at least monotonic) correlation indices, the full exploitation of molecular information depends on the knowledge of direct/indirect conditional independence (and eventually causal) relationships among biomarkers, and with target variables in the population of interest. In other words, that depends on inferences which are performed on the joint multivariate distribution of markers and target variables. Graphical models, such as Bayesian Networks, are well suited to this purpose. Therefore, we reconsidered a previously published case study on classical biomarkers in breast cancer, namely estrogen receptor (ER), progesterone receptor (PR), a proliferative index (Ki67/MIB-1) and to protein HER2/neu (NEU) and p53, to infer conditional independence relations existing in the joint distribution by inferring (learning) the structure of graphs entailing those relations of independence. We also examined the conditional distribution of a special molecular phenotype, called triple-negative, in which ER, PR and NEU were absent. We confirmed that ER is a key marker and we found that it was able to define subpopulations of patients characterized by different conditional independence relations among biomarkers. We also found a preliminary evidence that, given a triple-negative profile, the distribution of p53 protein is mostly supported in 'zero' and 'high' states providing useful information in selecting patients that could benefit from an adjuvant anthracyclines/alkylating agent-based chemotherapy.

Carcinogenesis is a multi-step process involving genetic alterations and non-genotoxic mechanisms. The in vitro cell transformation assay allows the monitoring of the neoplastic phenotype by foci formation in suitable cells (e.g. C3H10T1/2 mouse embryo fibroblasts) showing aberrant morphology of massive build-up, polar and multi-layered densely stained cells. The classification of transformed foci in C3H cells relies on light microscopy scoring by a trained human expert based on standard rules. This procedure is time-consuming and prone, in some cases, to subjectivity, thereby leading to possible over- or under-estimation of the carcinogenic potential of tested compounds. Herewith we describe the in vitro neoplastic transformation induced by B[a]P and CdCl2, and the development of a foci classifier based on image analysis and statistical classification. The image analysis system, which relies on 'spectrum enhancement', is quantitative and extracts descriptors of foci texture and structure. The statistical classification method is based on the Random Forest algorithm. We obtained a classifier trained by using expert's supervision with a 20% classification error. The proposed method could serve as a basis to automate the in vitro cell transformation assay.

Aims: To assess the effect of different concentrations of gossypol (0, 2, 4, 10 and 20 mg l(-1)) in combination with NaCl and Na(2)SO(4) (20 mS cm(-1)) on the conidial germination and viability of Fusarium oxysporum f.sp. vasinfectum (Fov)., Methods and Results: A multinomial logistic model was developed to estimate the germination probability of Fov. The inhibitory effect was markedly evident at the two highest concentrations of gossypol; it varied among the isolates tested and with time, and it was attenuated by the presence of sodium salts. The inhibition was temporary as the germination probability increased after 8 h. Fluorescent staining revealed that gossypol either killed the conidia or retarded the elongation of the germ tubes., Conclusion: Fov showed the ability to overcome gossypol inhibition over time, and the inhibitory effect is reduced under saline conditions. Differential responses among Fov isolates to the presence of gossypol suggest that gossypol tolerance is genetically determined in the pathogen., Significance and Impact of the Study: This study suggests that selecting for high plant gossypol cultivars would have minimal effect on the overall Fov resistance of cotton. A new statistical model was developed to explore the statistical significance of plant-pathogen interactions.

Motivation: Molecular profiles (DNA fingerprints) may be used to allocate an individual of unknown membership to one among the known groups of a reference population. Time and costs of profile assessment may be reduced by identifying informative profile components (markers)., Results: A genetic algorithm (GA) is proposed to identify promising candidate markers from a pilot experiment in which observations are supposed to be without measurement error. The analysis of simulated datasets suggests reasonable values for GA parameters and confirms that the GA finds components of the profile showing association with the considered groups. Our GA may be used to perform a first screening of candidate markers to be included in subsequent experiments., Availability: The 32-bit executable (Windows 95, 98 and NT) is available at http://www.ds.unifi.it/ approximately stefanin/bioinformatics.htm.

Microsatellite loci have become important in population genetics because of their high level of polymorphism in natural populations, very frequent occurrence throughout the genome, and apparently high mutation rate. Observed repeat numbers (alleles size) in natural populations and expectations based on computer simulations suggest that the range of repeat numbers at a microsatellite locus is restricted. This range is a key parameter that should be properly estimated in order to proceed with calculations of divergence times in phylogenetic studies and to better investigate the within- and between-population variability. The 'plug-in' estimate of range based on the minimum and maximum value observed in a sample is not satisfactory because of the relatively large number of alleles in comparison with typical sample sizes. In this paper, a set of data from 30 dinucleotide microsatellite loci is analysed under the assumption of independence among loci. Bayesian inference on range for one locus is obtained by assuming that constraints on range values exist as sharp bounds. Closed-form calculations and robustness revealed by our analysis suggest that the proposed Bayesian approach might be routinely used by researchers to classify microsatellite loci according to the estimated value of their allelic range.

Problem-solving and modelling within a biological context often need a level of descriptive accuracy that is unlikely to be capable of analytical treatment, especially if the mathematical background of the biologist is poor. Furthermore solver-model maintenance is often difficult without the availability of trained specialists. Better prospects are found in the genetic algorithm field. Genetic algorithms are a set of procedures formulated to solve complex problems without specifying rules for intermediate steps. This approach becomes feasible performing a Monte Carlo simulation of the natural evolution process, in which population improvement (search for solutions) in a considered environment (the specific problem domain) is achieved by following the genetic paradigm. Starting with a randomly constituted sample of individuals, drawn from the population of admissible values and expressed as binary strings, random mating brings about individuals of the next generation. Parents are chosen with a greater probability as the number of constraints violated by each individual becomes smaller. During the constitution of each generation the presence of some genetic operators causes the improvement of population diversity and its maintenance. Genetic operators are simple string transformation rules, generally independent of a specific context. We have developed the constant core of a minimal genetic algorithm, from which can be derived genetic problem-solvers in specific domains. An applicative example--a constrained matrix equation on signed integers--is also realized to show graphically the algorithm dynamics.