Explore the vast range of titles available.

This article focuses on dynamic signatures and their features. It provides a detailed and critical review of dynamic feature variations and circumstantial parameters affecting dynamic signatures. The state of the art summarizes available knowledge, meant to assist the forensic practitioner in cases presenting extraordinary writing conditions. The studied parameters include hardware-related issues, aging and the influence of time, as well as physical and mental states of the writer. Some parameters, such as drug and alcohol abuse or medication, have very strong effects on handwriting and signature dynamics. Other conditions such as the writer’s posture and fatigue have been found to affect feature variation less severely. The need for further research about the influence of these parameters, as well as handwriting dynamics in general is highlighted. These factors are relevant to the examiner in the assessment of the probative value of the reported features. Additionally, methodology for forensic examination of dynamic signatures is discussed. Available methodology and procedures are reviewed, while pointing out major technical and methodological advances in the field of forensic handwriting examination. The need for sharing the best practice manuals, standard operating procedures and methodologies to favor further progress is accentuated.

The emergence of SARS-CoV-2 and the non-pharmacological interventions adopted to counter its spread appear to have led to changes in the normal circulation and seasonality of respiratory viruses. Our study aims to investigate changes related to the circulation of respiratory viruses, not SARS-CoV-2, among hospitalized patients in Perugia, Central Italy, between 2019 and 2023. The samples were collected from individuals who went to the emergency room (ER) or were hospitalized and analyzed using a molecular multiplex test. The results underline that non-pharmaceutical interventions altered the typical seasonal circulation patterns of different respiratory viruses. Those mostly affected were enveloped viruses like influenza viruses that disappeared in 2021; the least impact was recorded for Rhinovirus, which was detected during the pandemic period, maintaining the same seasonality observed in the pre-pandemic period although with a reduction in the number of positive samples. Our data underline the importance of the continuous monitoring of these viruses, especially to understand the timing with which prevention measures, not only non-pharmacological interventions but also the equipment of vaccine doses and monoclonal antibodies, should be adopted to reduce their circulation, particularly in the population at risk of developing severe forms of lower respiratory tract infection.

•Methodic investigation of a probabilistic evidence evaluation methodology.•Application of a probabilistic model allowing use of empirical data for evidence evaluation.•Insights on dealing with data sparsity, different signature styles and combining features.•Preliminary study on 3 dynamic signatures, with high reproducibility and transparency. Forensic handwriting examiners (FHE) activities are focused on comparative analysis of handwritten objects such as signatures. Their role is to provide and evaluate evidence for and against the authenticity of a questioned signature. In recent years, cases involving handwritten signatures captured on electronic devices have become more commonplace. These so-called ‘dynamic signatures’ (also known as ‘digitally captured signatures’) are much different from paper-based signatures. Not only does the medium of recording differ, but also the type, volume of data and features are different from the pattern-based evidence that makes up paper-based signatures. Recent developments in forensic science – including signature examination – have led to the adoption of evaluative probabilistic methodologies in many disciplines [see, e.g. ENFSI 1915 Guidelines]. In the current paper, a probabilistic model to evaluate signature evidence in the form of multivariate data, as proposed and described in Wacom Europe GmbH (2019), is adopted. Topics like data sparsity, joint evaluation of multiple features and feature selection are investigated. Performed experimental studies showed an accuracy rate above 90% even when a limited number (5) of reference signatures was available. The performances of a multivariate approach are compared with those characterizing a so-called multiplicative approach where variables (features) are taken as independent and the Bayes’ factor (BF) is obtained as the product of univariate BFs associated to each selected feature. The simplicity of this latter approach is, however, accompanied by severe issues about the reliability of results. The use of a multivariate approach is therefore highly recommended. Finally, the evidential values in correspondence of alternative feature sets are compared. Results suggest that discriminative features are writer-related and necessitate a case-specific selection.

A question of originality was raised concerning the authorship of Molière’s plays. It has been claimed that the plays were written by Corneille in the final part of his life. This controversy is still topical, despite the relevant contributions on the subject (e.g., 1 ). Stylometry is often invoked to identify patterns used within and between words and sentences that describe a personal way of writing texts, and so one’s style. Despite the pioneering contribution of 2 , who promoted a Bayesian procedure for assessing the authorship of disputed documents, a coherent and judicially sound approach for features assessment and authorship attribution is still lacking in current practice. A full Bayesian framework to deal with the questioned authorship of the selected plays is promoted to address this controversy in total respect of (a) international standards for evaluative reporting in forensic science and (b) legal jurisprudence. Results strongly support the hypothesis that Corneille did not write Molière’s literary plays.

The academic and scientific world in general is increasingly concerned about their inability to determine and ascertain the identity of the writer of a text. More and more often the question arises as to whether a scientific article or work handed in by a student was actually produced by the alleged author of the questioned text. The role of artificial intelligence (AI) is increasingly debated due to its dangers of undeclared use. A current example is undoubtedly the undeclared use of ChatGPT to write a scientific text. The article promotes an AI model-independent redundancy measure to support discrimination between hypotheses on authorship of various multilingual texts written by humans or produced by intelligence media such as ChatGPT. The syntax of texts written by humans tends to differ from that of texts produced by AIs. This difference can be grasped and quantified even with short texts (i.e. 1800 characters). This aspect of length is extremely important, because short texts imply a greater difficulty of analysis to characterize authorship. To meet the efficiency criteria required for the evaluation of forensic evidence, a probabilistic approach is implemented. In particular, to assess the value of the redundancy measure and to offer a consistent classification criterion, a metric called Bayes factor is implemented. The proposed Bayesian probabilistic method represents an original approach in stylometry. Analyses performed over multilingual texts (English and French) covering different scientific and human areas of interest (forensic science and socio-psycho-artistic topics) reveal the feasibility of a successful authorship discrimination with limited misclassification rates. Model performance is satisfactory even with small sample sizes.

Breathe easy: why inhaled fungal spores don't provoke an immune reaction Every day we inhale thousands of tiny fungal spores (conidia), originating from many different fungal species. Yet although these spores are packed with antigens and allergens, their inhalation does not continuously activate our innate immune cells or provoke inflammatory responses. A series of immunological, biochemical and genetic experiments shows why: immune recognition of these spores is prevented by a hydrophobic layer of rodlet proteins covering the conidial surface. If this layer is removed, spores activate the immune system. A pathogenic spore equipped with this defensive layer might lie dormant beyond host defences until conditions are suitable for germination. Therapeutically the robust nature of the rodlet proteins might be exploited to generate nanoparticles containing embedded molecules targeted to a specific location in the body, or optimized for sustained delivery. Fungal spores are ubiquitous in the air we breathe and contain many antigens and allergens, and yet they neither continuously activate the host innate immune cells nor induce detrimental inflammatory responses after their inhalation. Here, the surface layer on dormant spores is shown to mask their recognition by the immune system and hence prevent an immune response. The air we breathe is filled with thousands of fungal spores (conidia) per cubic metre, which in certain composting environments can easily exceed 10 9 per cubic metre. They originate from more than a hundred fungal species belonging mainly to the genera Cladosporium , Penicillium , Alternaria and Aspergillus 1 , 2 , 3 , 4 . Although these conidia contain many antigens and allergens 5 , 6 , 7 , it is not known why airborne fungal microflora do not activate the host innate immune cells continuously and do not induce detrimental inflammatory responses following their inhalation. Here we show that the surface layer on the dormant conidia masks their recognition by the immune system and hence prevents immune response. To explore this, we used several fungal members of the airborne microflora, including the human opportunistic fungal pathogen Aspergillus fumigatus , in in vitro assays with dendritic cells and alveolar macrophages and in in vivo murine experiments. In A. fumigatus , this surface ‘rodlet layer’ is composed of hydrophobic RodA protein covalently bound to the conidial cell wall through glycosylphosphatidylinositol-remnants. RodA extracted from conidia of A. fumigatus was immunologically inert and did not induce dendritic cell or alveolar macrophage maturation and activation, and failed to activate helper T-cell immune responses in vivo . The removal of this surface ‘rodlet/hydrophobin layer’ either chemically (using hydrofluoric acid), genetically (Δ rodA mutant) or biologically (germination) resulted in conidial morphotypes inducing immune activation. All these observations show that the hydrophobic rodlet layer on the conidial cell surface immunologically silences airborne moulds.

Since IL-37 transgenic mice possesses broad anti-inflammatory properties, we assessed whether recombinant IL-37 affects inflammation in a murine model of invasive pulmonary aspergillosis. Recombinant human IL-37 was injected intraperitoneally into mice prior to infection and the effects on lung inflammation and inflammasome activation were evaluated. IL-37 markedly reduced NLRP3-dependent neutrophil recruitment and steady state mRNA levels of IL-1β production and mitigated lung inflammation and damage in a relevant clinical model, namely aspergillosis in mice with cystic fibrosis. The anti-inflammatory activity of IL-37 requires the IL-1 family decoy receptor TIR-8/SIGIRR. Thus, by preventing activation of the NLRP3 inflammasome and reducing IL-1β secretion, IL-37 functions as a broad spectrum inhibitor of the innate response to infection-mediated inflammation, and could be considered to be therapeutic in reducing the pulmonary damage due to non-resolving Aspergillus infection and disease.

\"This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation\"Dr. Ian Evett, Principal Forensic Services Ltd, London, UKContinuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing.The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision.Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system.Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks.Includes self-contained introductions to probability and decision theory.Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models.Features implementation of the methodology with reference to commercial and academically available software.Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases.Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning.Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them.Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background.Includes a foreword by Ian Evett.The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

The pathogenesis of coronavirus disease 2019 (COVID-19) is associated with a hyperinflammatory response. The mechanisms of SARS-CoV-2-induced inflammation are scantly known. Methylglyoxal (MG) is a glycolysis-derived byproduct endowed with a potent glycating action, leading to the formation of advanced glycation end products (AGEs), the main one being MG-H1. MG-H1 exerts strong pro-inflammatory effects, frequently mediated by the receptor for AGEs (RAGE). Here, we investigated the involvement of the MG-H1/RAGE axis as a potential novel mechanism in SARS-CoV-2-induced inflammation by resorting to human bronchial BEAS-2B and alveolar A549 epithelial cells, expressing different levels of the ACE2 receptor (R), exposed to SARS-CoV-2 spike protein 1 (S1). Interestingly, we found in BEAS-2B cells that do not express ACE2-R that S1 exerted a pro-inflammatory action through a novel MG-H1/RAGE-based pathway. MG-H1 levels, RAGE and IL-1β expression levels in nasopharyngeal swabs from SARS-CoV-2-positive and -negative individuals, as well as glyoxalase 1 expression, the major scavenging enzyme of MG, seem to support the results obtained in vitro. Altogether, our findings reveal a novel mechanism involved in the inflammation triggered by S1, paving the way for the study of the MG-H1/RAGE inflammatory axis in SARS-CoV-2 infection as a potential therapeutic target to mitigate COVID-19-associated pathogenic inflammation.

A new polysaccharide secreted by the human opportunistic fungal pathogen Aspergillus fumigatus has been characterized. Carbohydrate analysis using specific chemical degradations, mass spectrometry, ¹H and ¹³C nuclear magnetic resonance showed that this polysaccharide is a linear heterogeneous galactosaminogalactan composed of α1-4 linked galactose and α1-4 linked N-acetylgalactosamine residues where both monosacharides are randomly distributed and where the percentage of galactose per chain varied from 15 to 60%. This polysaccharide is antigenic and is recognized by a majority of the human population irrespectively of the occurrence of an Aspergillus infection. GalNAc oligosaccharides are an essential epitope of the galactosaminogalactan that explains the universal antibody reaction due to cross reactivity with other antigenic molecules containing GalNAc stretches such as the N-glycans of Campylobacter jejuni. The galactosaminogalactan has no protective effect during Aspergillus infections. Most importantly, the polysaccharide promotes fungal development in immunocompetent mice due to its immunosuppressive activity associated with disminished neutrophil infiltrates.