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Specific immune suppression types have been associated with a greater risk of severe COVID-19 disease and death. We analyzed data from patients >17 years that were hospitalized for COVID-19 at the “Fondazione IRCCS Ca′ Granda Ospedale Maggiore Policlinico” in Milan (Lombardy, Northern Italy). The study included 1727 SARS-CoV-2-positive patients (1,131 males, median age of 65 years) hospitalized between February 2020 and November 2022. Of these, 321 (18.6%, CI: 16.8–20.4%) had at least one condition defining immune suppression. Immune suppressed subjects were more likely to have other co-morbidities (80.4% vs. 69.8%, p

For decades, wavelet theory has attracted interest in several fields in dealing with signals. Nowadays, it is acknowledged that it is not very suitable to face aspects of multidimensional data like singularities and this has led to the development of other mathematical tools. A recent application of wavelet theory is in radiomics, an emerging field aiming to improve diagnostic, prognostic and predictive analysis of various cancer types through the analysis of features extracted from medical images. In this paper, for a radiomics study of prostate cancer with magnetic resonance (MR) images, we apply a similar but more sophisticated tool, namely the shearlet transform which, in contrast to the wavelet transform, allows us to examine variations along more orientations. In particular, we conduct a parallel radiomics analysis based on the two different transformations and highlight a better performance (evaluated in terms of statistical measures) in the use of the shearlet transform (in absolute value). The results achieved suggest taking the shearlet transform into consideration for radiomics studies in other contexts.

The aim of the present study consists of the evaluation of the biodistribution of a novel 68Ga-labeled radiopharmaceutical, [68Ga]Ga-NODAGA-Z360, injected into Balb/c nude mice through histopathological analysis on bioptic samples and radiomics analysis of positron emission tomography/computed tomography (PET/CT) images. The 68Ga-labeled radiopharmaceutical was designed to specifically bind to the cholecystokinin receptor (CCK2R). This receptor, naturally present in healthy tissues such as the stomach, is a biomarker for numerous tumors when overexpressed. In this experiment, Balb/c nude mice were xenografted with a human epidermoid carcinoma A431 cell line (A431 WT) and overexpressing CCK2R (A431 CCK2R+), while controls received a wild-type cell line. PET images were processed, segmented after atlas-based co-registration and, consequently, 112 radiomics features were extracted for each investigated organ / tissue. To confirm the histopathology at the tissue level and correlate it with the degree of PET uptake, the studies were supported by digital pathology. As a result of the analyses, the differences in radiomics features in different body districts confirmed the correct targeting of the radiopharmaceutical. In preclinical imaging, the methodology confirms the importance of a decision-support system based on artificial intelligence algorithms for the assessment of radiopharmaceutical biodistribution.

ABSTRACT The interplay between the intestinal microbiota and host is critical to intestinal ontogeny and homeostasis. MicroRNAs (miRNAs) may be an underlying link. Intestinal miRNAs are microbiota-dependent and, when shed in the lumen, affect resident microorganisms. Yet, longitudinal relationships between intestinal tissue miRNAs, luminal miRNAs, and luminal microorganisms have not been elucidated, especially in early life. Here, we investigated the postnatal cecal miRNA and microbiota populations, their relationship, and their impact on intestinal maturation in specific pathogen-free mice; we also assessed if they can be modified by intervention with allochthonous probiotic lactobacilli. We report that cecal and cecal content miRNA and microbiota signatures are temporally regulated, correlated, and modifiable by probiotics with implications for intestinal maturation. These findings help understand causal relationships within the gut ecosystem and provide a basis for preventing and managing their alterations in diseases throughout life. IMPORTANCE The gut microbiota affects intestinal microRNA (miRNA) signatures and is modified by host-derived luminal miRNA. This suggests the existence of close miRNA-microbiota relationships that are critical to intestinal homeostasis. However, an integrative analysis of these relationships and their evolution during intestinal postnatal maturation is lacking. We provide a system-level longitudinal analysis of miRNA-microbiota networks in the intestine of mice at the weaning transition, including tissue and luminal miRNA and luminal microbiota. To address causality and move toward translational applications, we used allochthonous probiotic lactobacilli to modify these longitudinal relationships and showed that they are critical for intestinal maturation in early life. These findings contribute to understand mechanisms that underlie the maturation of the intestinal ecosystem and suggest that interventions aiming at maintaining, or restoring, homeostasis cannot prescind from considering relationships among its components.

On November 22nd, 1974, the United Nations General Assembly promulgated resolutions No. 3236 and No. 3237, recognizing the political, cultural, and socio-economic rights of the Palestinian people, and formalizing the PLO’s participation in the General Assembly as an observer. These important resolutions were issued following the historic speech given by the President of the Palestine Liberation Organization, Yāsir ʿArafāt, on November 13th, 1974, before the United Nations General Assembly. This paper consists in the rhetorical and linguistic analysis of the main argumentative strategies employed by the Palestinian leader in his speech to achieve his perlocutionary goals. Specifically, the analysis is carried out on the basis of the methodological tools developed by Perelman and Olbrecths-Tyteca in The New Rhetoric: A Treatise on Argumentation (1969). The Perelmanian tools are applied to ʿArafāt’s Arabic speech in order to determine the rhetorical techniques employed to build the audience’s agreement and to persuade them about the necessity to accommodate his people’s requests. From this research emerges the in-depth knowledge that the speaker has of his audience, addressing, from time to time, a particular or a universal audience, in an attempt to reach an agreement that is as broad as possible. For this reason, the speaker carefully chooses the language through which to convey his message, excluding the Islamic formulas and lexicon, which usually characterize his speeches. Furthermore, the agreement with the public is established through the repeated reference to universal values, which allow him to place the Palestinian question in a framework shared by the audience. Finally, the present study illustrates the copious argumentative strategies that ʿArafāt employs to generate a change of perspective on the Palestinian question, facilitating the process of persuasion.

Abstract Discontinuation of antimicrobial stewardship programs (ASPs) and increased antibiotic use were described during SARS-CoV-2 pandemic. In order to measure COVID-19 impact on ASPs in a setting of high multidrug resistance organisms (MDRO) prevalence, a qualitative survey was designed. In July 2021, eighteen ID Units were asked to answer a questionnaire about their hospital characteristics, ASPs implementation status before the pandemic and impact of SARS-CoV-2 pandemic on ASPs after the 1st and 2nd pandemic waves in Italy. Nine ID centres (50%) reported a reduction of ASPs and in 7 cases (38.9%) these were suspended. After the early pandemic waves, the proportion of centres that restarted their ASPs was higher among the ID centres where antimicrobial stewardship was formally identified as a priority objective (9/11, 82%, vs 2/7, 28%). SARS-CoV-2 pandemic had a severe impact in ASPs in a region highly affected by COVID-19 and antimicrobial resistance but weaknesses related to the pre-existent ASPs might have played a role.

Abstract The cancellation of infrared (IR) divergences is an old topic in quantum field theory whose main results are condensed into the celebrated Kinoshita-Lee-Nauenberg (KLN) theorem. In this paper we consider mass-suppressed corrections to the leading (i.e. double-logarithmic) IR divergences in the context of spontaneously broken gauge theories. We work in a simplified theoretical set-up based on the spontaneously broken U′(1) ⨂ U(1) gauge group. We analyze, at the one-loop level and including mass-suppressed terms, the double-logarithmic corrections to the decay channels of an hypothetical heavy Z′ gauge boson coupled to light chiral fermions and mixed with a light massive Z gauge boson. Limited to this theoretical framework, only final state IR corrections are relevant. We find that full exploitation of the KLN theorem requires non-trivial combinations of various decay channels in order to get rid of the mass-suppressed IR corrections. Based on this observation we show that, starting from any two-body decay of the heavy Z′ gauge boson, the cancellation of the mass-suppressed double-logarithmic corrections requires the sum over the full decay width (thus enforcing the inclusion of final states which are naïvely unrelated to the starting one). En route, we prove a number of technical results that are relevant for the computation of mass-suppressed double-logarithms of IR origin. Our results are relevant for models that enlarge the Standard Model by adding a heavy Z′.

Abstract Over the last few decades, chemical and physical studies on bowed string musical instruments have provided a better understanding of their wooden finished surface. Nevertheless, until now only a few of them investigated the effects of the chemical pre-treatments in the traditional making procedures. Those treatments are believed to affect wood properties, its interaction with the following treatments (i.e. varnish application) and its vibro-mechanical behaviour (that may contribute to the acoustical properties of musical instruments). In this study, two traditional alkaline treatments were applied to reference samples of spruce wood, the wood commonly used to make violins’ soundboards. An integrated analytical strategy, which combines infrared spectroscopy, analytical pyrolysis coupled to gas chromatography-mass spectrometry, and gel permeation chromatography, was employed to investigate the chemical alterations of lignocellulosic polymers (cellulose, hemicellulose, and lignin). Results have shown that the selected alkaline treatments induce the partial hydrolysis of the hemicellulose chains and a slight decrease in the crystallinity of cellulose. We could also prove: (i) the cleavage of lignin-carbohydrate complexes formed by the covalent bonds between hemicellulose and lignin in spruce wood, and (ii) the partial breaking of the hydrogen bonds network in cellulose. According to the literature, the alteration of the lignin-carbohydrate complexes is responsible for changes in wood mechanical behaviour. Hence, future perspectives of this research could outline new knowledge on the vibro-mechanical behaviour of the violin soundboard and the consequent acoustics.

Background: About 50% of cutaneous melanoma (CM) harbors the activating BRAFV600 mutation which exerts most of the oncogenic effects through the MAPK signaling pathway. In the last years, a number of MAPK modulators have been identified, including Spry1. In this context, we have recently demonstrated that knockout of Spry1 (Spry1KO) in BRAFV600-mutant CM led to cell cycle arrest and apoptosis, repressed cell proliferation in vitro, and reduced tumor growth in vivo. Despite these findings, however, the precise molecular mechanism linking Spry1 to BRAFV600-mutant CM remains to be elucidated. Materials and methods: Immunoprecipitation coupled to mass spectrometry was employed to gain insight into Spry1 interactome. Spry1 gene was knocked-out using the CRISPR strategy in the BRAF-mutant cell lines. Transmission electron microscopy was used to assess the relationship between Spry1 expression and mitochondrial morphology. By using in vitro and in vivo models, the effects of Spry1KO were investigated through RNA-sequencing, quantitative real-time PCR, Western blot, and immunofluorescence analyses. The Seahorse XF24 assay allowed real-time measurement of cellular metabolism in our model. Angiogenic potential was assessed through in vitro tube formation assays and in vivo CD31 staining. Results: Spry1 was mainly located in mitochondria in BRAFV600-mutant CM cells where it interacted with key molecules involved in mitochondrial homeostasis. Spry1 loss resulted in mitochondrial shape alterations and dysfunction, which associated with increased reactive oxygen species production. In agreement, we found that nuclear hypoxia-inducible factor-1 alpha (HIF1α) protein levels were reduced in Spry1KO clones both in vitro and in vivo along with the expression of its glycolysis related genes. Accordingly, Ingenuity Pathway Analysis identified "HIF1α Signaling" as the most significant molecular and cellular function affected by Spry1 silencing, whereas the glycolytic function was significantly impaired in Spry1 depleted BRAFV600-mutant CM cells. In addition, our results indicated that the expression of the vascular endothelial growth factor A was down-regulated following Spry1KO, possibly as a result of mitochondrial dysfunction. Consistently, we observed a substantial impairment of angiogenesis, as assessed by the tube formation assay in vitro and the immunofluorescence staining of CD31 in vivo. Conclusions: Altogether, these findings identify Spry1 as a potential regulator of mitochondrial homeostasis, and uncover a previously unrecognized role for Spry1 in regulating nuclear HIF1α expression and angiogenesis in BRAFV600-mutant CM. Significance: Spry1KO profoundly impacts on mitochondria homeostasis, while concomitantly impairing HIF1α-dependent glycolysis and reducing angiogenesis in BRAF-mutant CM cells, thus providing a potential therapeutic target to improve BRAFV600-mutant CM treatment. [ABSTRACT FROM AUTHOR]

Background: Low back pain is the leading cause of disability worldwide with a significant socioeconomic burden; artificial intelligence (AI) has proved to have a great potential in supporting clinical decisions at each stage of the healthcare process. In this article, we have systematically reviewed the available literature on the applications of AI-based Decision Support Systems (DSS) in the clinical prevention and management of Low Back Pain (LBP) due to lumbar degenerative spine disorders. Methods: A systematic review of Pubmed and Scopus databases was performed according to the PRISMA statement. Studies reporting the application of DSS to support the prevention and/or management of LBP due to lumbar degenerative diseases were included. The QUADAS-2 tool was utilized to assess the risk of bias in the included studies. The area under the curve (AUC) and accuracy were assessed for each study. Results: Twenty five articles met the inclusion criteria. Several different machine learning and deep learning algorithms were employed, and their predictive ability on clinical, demographic, psychosocial, and imaging data was assessed. The included studies mainly encompassed three tasks: clinical score definition, clinical assessment, and eligibility prediction and reached AUC scores of 0.93, 0.99 and 0.95, respectively. Conclusions: AI-based DSS applications showed a high degree of accuracy in performing a wide set of different tasks. These findings lay the foundation for further research to improve the current understanding and encourage wider adoption of AI in clinical decision-making. [ABSTRACT FROM AUTHOR]

The correction notice in Molecular Cancer addresses an error in Figure 8 of the original article, which can be accessed online. The authors identified a duplication of a graph in the production process and have provided the incorrect and correct figures for reference. The correction was made by a group of researchers listed in the notice. [Extracted from the article]

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses a range of histological findings from the generally benign simple steatosis to steatohepatitis (MASH) which can progress to fibrosis and cirrhosis. Several factors, including the microbiome, may contribute to disease progression. Results: Here, we demonstrate links between the presence and abundance of specific bacteria in the adipose and liver tissues, inflammatory genes, immune cell responses, and disease severity. Overall, in MASLD patients, we observed a generalized obesity-induced translocation of gut bacteria to hepatic and adipose tissues. We identified microbial patterns unique to more severely diseased tissues. Specifically, Enterococcus, Granulicatella, and Morganellaceae abundance is positively correlated with immune cell counts and inflammatory gene expression levels, and both genera are significantly enriched in MASH patients. Brevibacterium is enriched in adipose tissues of patients with liver fibrosis. Conclusion: Together, these results provide further insight into the microbial factors that may be driving disease severity. 5gz9zWLTQ4ZzRXZ3CTt_7q Video Abstract [ABSTRACT FROM AUTHOR]

The article discusses the prevalence of schistosomiasis among migrants in Italy, particularly those from West Africa, and the challenges in accessing treatment due to bureaucratic obstacles in Italy. It highlights the importance of early screening and treatment to prevent complications and morbidity. The document also estimates the number of PZQ tablets needed for treatment based on the migrant population in Italy and emphasizes the need for improved access to PZQ to eliminate schistosomiasis and reduce the burden on the healthcare system. The authors advocate for the registration and marketing of PZQ in Italy to address the double neglect of the disease and the migrant population. [Extracted from the article]

Studies on the democratic backsliding in Central Eastern Europe (CEE) often focus on local dysfunctions and idiosyncrasies, and they tend to overlook how those authoritarian tendencies are deeply influenced by European integration. I argue that the wave of authoritarianism in CEE is exacerbated by a shared political culture based on Christian Democracy (CD), and instead of divergence between Western and CEE, a form of convergence is happening. I point to CD's role in responding to the 'polanyian' tensions between democracy and liberalism. CD played an important role in shaping the present constitutional and ideational order of the European Union. The 'illiberal' policies enacted by several member countries—especially in the domains of Christian identity politics, traditional gender roles, and Bismarckian welfare—come out of the Christian-Democratic political toolbox and exemplify a paradoxical regime of authoritarian liberalism (or politics without policies) that does not threaten the (neo)liberal foundations of the EU. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer (PCa) is the second most common cancer in men, and radiotherapy (RT) is one of the main treatment options. Although effective, RT can cause toxic side effects. The accurate prediction of dosimetric parameters, enhanced by advanced technologies and AI-based predictive models, is crucial to optimize treatments and reduce toxicity risks. This study aims to explore current methodologies for predictive dosimetric parameters associated with RT toxicity in PCa patients, analyzing both traditional techniques and recent innovations. Methods: A systematic review was conducted using the PubMed, Scopus, and Medline databases to identify dosimetric predictive parameters for RT in prostate cancer. Studies published from 1987 to April 2024 were included, focusing on predictive models, dosimetric data, and AI techniques. Data extraction covered study details, methodology, predictive models, and results, with an emphasis on identifying trends and gaps in the research. Results: After removing duplicate manuscripts, 354 articles were identified from three databases, with 49 shortlisted for in-depth analysis. Of these, 27 met the inclusion criteria. Most studies utilized logistic regression models to analyze correlations between dosimetric parameters and toxicity, with the accuracy assessed by the area under the curve (AUC). The dosimetric parameter studies included Vdose, Dmax, and Dmean for the rectum, anal canal, bowel, and bladder. The evaluated toxicities were genitourinary, hematological, and gastrointestinal. Conclusions: Understanding dosimetric parameters, such as DVH, Dmax, and Dmean, is crucial for optimizing RT and predicting toxicity. Enhanced predictive accuracy improves treatment effectiveness and reduces side effects, ultimately improving patients' quality of life. Emerging artificial intelligence and machine learning technologies offer the potential to further refine RT in PCa by analyzing complex data, and enabling more personalized treatment approaches. [ABSTRACT FROM AUTHOR]

(1) Background: Nonalcoholic Steatohepatitis/Nonalcoholic Fatty Liver Disease (NASH/NAFLD) is the most recurrent chronic liver disease. NASH could present with a cholestatic (C) or hepatic (H) pattern of damage. Recently, we observed that increased Epithelial Cell Adhesion Molecule (EpCAM) expression was the main immunohistochemical feature to distinguish C from H pattern in NASH. (2) Methods: In the present study, we used digital pathology to compare the quantitative results of digital image analysis by QuPath software (Q-results), with the semi-quantitative results of observer assessment (S-results) for cytokeratin 7 and 19, (CK7, CK19) as well as EpCAM expression. Patients were classified into H or C group on the basis of the ratio between alanine transaminase (ALT) and alkaline phosphatase (ALP) values, using the “R-ratio formula”. (3) Results: Q- and S-results showed a significant correlation for all markers (p < 0.05). Q-EpCAM expression was significantly higher in the C group than in the H group (p < 0.05). Importantly ALP, an indicator of hepatobiliary disorder, was the only biochemical parameter significantly correlated with Q-EpCAM. Instead, Q-CK7, but not Q-CK19, correlated only with γGlutamyl-Transferase (γGT). Of note, Stage 4 fibrosis correlated with Q-EpCAM, Q-CK19, and ALP but not with γGT or ALT. Conclusions: Image analysis confirms the relation between cholestatic-like pattern, associated with a worse prognosis, with increased ALP values, EpCAM positive biliary metaplasia, and advanced fibrosis. These preliminary data could be useful for the implementation of AI algorithms for the assessment of cholestatic NASH.

Resveratrol is a polyphenolic compound that has gained considerable attention in the past decade due to its multifaceted therapeutic potential, including anti-inflammatory and anticancer properties. However, its anticancer efficacy is impeded by low water solubility, dose-limiting toxicity, low bioavailability, and rapid hepatic metabolism. To overcome these hurdles, various nanoparticles such as organic and inorganic nanoparticles, liposomes, polymeric nanoparticles, dendrimers, solid lipid nanoparticles, gold nanoparticles, zinc oxide nanoparticles, zeolitic imidazolate frameworks, carbon nanotubes, bioactive glass nanoparticles, and mesoporous nanoparticles were employed to deliver resveratrol, enhancing its water solubility, bioavailability, and efficacy against various types of cancer. Resveratrol-loaded nanoparticle or resveratrol-conjugated nanoparticle administration exhibits excellent anticancer potency compared to free resveratrol. This review highlights the latest developments in nanoparticle-based delivery systems for resveratrol, focusing on the potential to overcome limitations associated with the compound’s bioavailability and therapeutic effectiveness.

Hyperspectral imaging (HSI) has emerged as an effective tool to obtain spatially resolved spectral information of artworks by combining optical imaging with spectroscopy. This technique has proven its efficacy in providing valuable information both at the large and microscopic scale. Interestingly, the macro scale has yet to be thoroughly investigated using this technology. While standard HSI methods include the use of spatial or spectral filters, alternative methods based on Fourier-transform interferometry have also been utilised. Among these, a hyperspectral camera employing a birefringent common-path interferometer, named TWINS, has been developed, showing a high robustness and versatility. In this paper, we propose the combination of TWINS with a macro imaging system for the study of cultural heritage (CH). We will show how the macro-HSI system was designed, and we will demonstrate its efficient capabilities to collect interferometric images with high visibility and good signal of both reflectance and fluorescence on the same field of view, even on non-flat samples. Our hyperspectral camera for macro studies of both reflectance and fluorescence data is a completely new asset in the CH panorama and beyond. The relevance of the macro technology is demonstrated in two case studies, aiding in the analysis of biofilms on stone samples and of the degradation of dyed textiles.

This paper introduces a novel multimodal optical microscope, integrating Raman and laser-induced photoluminescence (PL) spectroscopy for the analysis of micro-samples relevant in Heritage Science. Micro-samples extracted from artworks, such as paintings, exhibit intricate material compositions characterized by high complexity and spatial heterogeneity, featuring multiple layers of paint that may be also affected by degradation phenomena. Employing a multimodal strategy becomes imperative for a comprehensive understanding of their material composition and condition. The effectiveness of the proposed setup derives from synergistically harnessing the distinct strengths of Raman and laser-induced PL spectroscopy. The capacity to identify various chemical species through the latter technique is enhanced by using multiple excitation wavelengths and two distinct excitation fluence regimes. The combination of the two complementary techniques allows the setup to effectively achieve comprehensive chemical mapping of sample through a raster scanning approach. To attain a competitive overall measurement time, we employ a short integration time for each measurement point. We further propose an analysis protocol rooted in a multivariate approach. Specifically, we employ non-negative matrix factorization as the spectral decomposition method. This enables the identification of spectral endmembers, effectively correlated with specific chemical compounds present in samples. To demonstrate its efficacy in Heritage Science, we present examples involving pigment powder dispersions and stratigraphic micro-samples from paintings. Through these examples, we show how the multimodal approach reinforces material identification and, more importantly, facilitates the extraction of complementary information. This is pivotal as the two optical techniques exhibit sensitivity to different materials. Looking ahead, our method holds potential applications in diverse research fields, including material science and biology.

Throughout the 20th Century, plastics found extensive use in fashion, art, and design due to their versatile nature. However, their degradation over time poses challenges, impacting material integrity, particularly in museum collections. To tackle this issue, different scientific techniques have been employed to study polymers. In this work, a complementary multi-analytical approach is proposed to investigate the light stability of ABS compounds, selecting LEGO® bricks as reference material. The method is based on fluorescence emission and lifetime integrating point-like analysis and imaging systems to corroborate chemical and spatial information specifically addressed at the surface level. The latter has shown promising results in studying ABS objects, offering insights into degradation and aiding conservation efforts.

This work introduces a novel method to multivariate analysis applied to fused hyperspectral datasets in the field of Cultural Heritage (CH). Hyperspectral Imaging is a well-established approach for the non-invasive examination of artworks, offering insights into their composition and conservation status. In CH field, a combination of hyperspectral techniques is usually employed to reach a comprehensive understanding of the artwork. To deal with hyperspectral data, multivariate statistical methods are essential due to the complexity of the data. The process involves factorizing the data matrix to highlight components and reduce dimensionality, with techniques such as Non-negative Matrix Factorization (NMF) gaining prominence. To maximize the synergies between multimodal datasets, the fusion of hyperspectral datasets can be coupled with multivariate analysis, with potential applications in CH. In this work, I will show examples of this approach with different combinations of datasets, including reflectance and transmittance spectral imaging, Fluorescence Lifetime Imaging and Time-Gated Hyperspectral Imaging, and Raman and fluorescence spectroscopy micro-mapping.

Ultramarine Blue (UB) pigment, derived from lapis lazuli, holds a significant place in the history of late medieval and Renaissance Europe, owing to its unusually bright colour and stability. Its prohibitive price, which equalled that of gold, meant that it was only used by estimated artists. In this work we present a non-invasive, multimodal approach to the characterization of the photoluminescent properties of different variants of the pigment. The ultimate goal of this research is to propose a protocol for the identification of UB in artworks thanks to the combination of Raman spectroscopy and time resolved-photoluminescence spectroscopy and imaging.