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Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by loss of muscle atonia and abnormal behaviors occurring during REM sleep. Idiopathic RBD (iRBD) is recognized as the strongest prodromal hallmark of α-synucleinopathies, with an established conversion rate to a neurodegenerative condition that reaches up to 96.6% at 15 years of follow-up. Moreover, RBD-converters display a more severe clinical trajectory compared to those that do not present with RBD. However, the extent to which iRBD represents a distinct genetic entity or an early manifestation of neurodegeneration remains unclear. To address this, we applied Genomic Structural Equation Modeling (GenomicSEM) using a GWAS-by-subtraction approach to disentangle the genetic architecture of iRBD from the shared genomic liability across α-synucleinopathies. Our findings highlight the SNCA locus as a key genetic regulator of iRBD susceptibility. While iRBD exhibits a partially distinct genetic signature, residual genomic overlap with neurodegenerative traits suggests that its genetic architecture exists along a continuum of α-synucleinopathy risk. In this scenario, the associations with neuroanatomical correlates may serve as early indicators of a trajectory toward future neurodegeneration. These findings provide a framework for identifying biomarkers that could aid in disease stratification and risk prediction, potentially improving early intervention strategies.

BackgroundThe application of massive parallel sequencing technologies in the molecular analysis of Charcot-Marie-Tooth (CMT) has enabled the rapid and cost-effective identification of numerous potentially significant variants for diagnostic purposes. The objective is to reduce the number of variants, focusing only on those with pathogenic significance. The 2015 American College of Medical Genetics and Genomics (ACMG) guidelines aid in achieving this goal, but it is now evident that a pathology or gene-specific review of these rules is essential to avoid misinterpretations that may result from blindly applying the criteria. This study demonstrates how revised ACMG criteria, combined with CMT-specific literature data and expertise, can alter the final classification of a variant.MethodsWe reviewed ACMG criteria based on current knowledge of CMT and provided suggestions for adapting them to the specificities of CMT.ResultsOf the 226 index patients analysed, a diagnostic yield of 20% was obtained. It is worth noting that the 9% of cases had their final diagnosis changed with the application of the revised criteria, often resulting in the loss of the pathogenic classification of a variant.ConclusionsThe widespread availability of high-throughput sequencing technologies has enabled genetic testing even for laboratories without specific disease expertise. Disease-specific ACMG criteria can be a valuable tool to prevent the proliferation of variants of uncertain significance and the misinterpretation of variants.

Decades of work have aimed to genetically reprogram T cells for therapeutic purposes 1 , 2 using recombinant viral vectors, which do not target transgenes to specific genomic sites 3 , 4 . The need for viral vectors has slowed down research and clinical use as their manufacturing and testing is lengthy and expensive. Genome editing brought the promise of specific and efficient insertion of large transgenes into target cells using homology-directed repair 5 , 6 . Here we developed a CRISPR–Cas9 genome-targeting system that does not require viral vectors, allowing rapid and efficient insertion of large DNA sequences (greater than one kilobase) at specific sites in the genomes of primary human T cells, while preserving cell viability and function. This permits individual or multiplexed modification of endogenous genes. First, we applied this strategy to correct a pathogenic IL2RA mutation in cells from patients with monogenic autoimmune disease, and demonstrate improved signalling function. Second, we replaced the endogenous T cell receptor ( TCR ) locus with a new TCR that redirected T cells to a cancer antigen. The resulting TCR-engineered T cells specifically recognized tumour antigens and mounted productive anti-tumour cell responses in vitro and in vivo. Together, these studies provide preclinical evidence that non-viral genome targeting can enable rapid and flexible experimental manipulation and therapeutic engineering of primary human immune cells. A non-viral strategy to introduce large DNA sequences into T cells enables the correction of a pathogenic mutation that causes autoimmunity, and the replacement of an endogenous T-cell receptor with an engineered receptor that can recognize cancer antigens.

Objectives To perform a comprehensive within-subject image quality analysis of abdominal CT examinations reconstructed with DLIR and to evaluate diagnostic accuracy compared to the routinely applied adaptive statistical iterative reconstruction (ASiR-V) algorithm. Materials and methods Oncologic patients were prospectively enrolled and underwent contrast-enhanced CT. Images were reconstructed with DLIR with three intensity levels of reconstruction (high, medium, and low) and ASiR-V at strength levels from 10 to 100% with a 10% interval. Three radiologists characterized the lesions and two readers assessed diagnostic accuracy and calculated signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), figure of merit (FOM), and subjective image quality, the latter with a 5-point Likert scale. Results Fifty patients (mean age: 70 ± 10 years, 23 men) were enrolled and 130 liver lesions (105 benign lesions, 25 metastases) were identified. DLIR_H achieved the highest SNR and CNR, comparable to ASiR-V 100% ( p  ≥ .051). DLIR_M returned the highest subjective image quality (score: 5; IQR: 4–5; p  ≤ .001) and significant median increase (29%) in FOM ( p  < .001). Differences in detection were identified only for lesions ≤ 0.5 cm: 32/33 lesions were detected with DLIR_M and 26 lesions were detected with ASiR-V 50% ( p  = .031). Lesion accuracy of was 93.8% (95% CI: 88.1, 97.3; 122 of 130 lesions) for DLIR and 87.7% (95% CI: 80.8, 92.8; 114 of 130 lesions) for ASiR-V 50%. Conclusions DLIR yields superior image quality and provides higher diagnostic accuracy compared to ASiR-V in the assessment of hypovascular liver lesions, in particular for lesions ≤ 0.5 cm. Clinical relevance statement Deep learning image reconstruction algorithm demonstrates higher diagnostic accuracy compared to iterative reconstruction in the identification of hypovascular liver lesions, especially for lesions ≤ 0.5 cm. Key Points • Iterative reconstruction algorithm impacts image texture, with negative effects on diagnostic capabilities. • Medium-strength deep learning image reconstruction algorithm outperforms iterative reconstruction in the diagnostic accuracy of ≤ 0.5 cm hypovascular liver lesions (93.9% vs 78.8%), also granting higher objective and subjective image quality. • Deep learning image reconstruction algorithm can be safely implemented in routine abdominal CT protocols in place of iterative reconstruction.

If there is a category of war victims for whom the identification process has been and still remains an extremely challenging issue, it is the soldiers of World War One. There are various reasons for this, including unreliable identity tags, the unprecedented number of casualties, and the level of destruction caused by the massive use of “new” weapons. In Italy, this phenomenon was so severe and well-known that a monument was erected in Rome specifically in memory of those unknown soldiers (“Tomba del Milite Ignoto”). However, modern techniques in forensic archaeology and anthropology can facilitate identification even in this extreme context. In the casework described here, the presence of human remains was reported to the judicial authorities, which were subsequently located and excavated in a remote region of the Italian Alps using a range of techniques, including drone imagery, GPR, and micromorphological surveying. During the archaeological excavation of the human remains, a World War One zinc identification tag in very poor condition was found adjacent to the body. The biological profile was estimated (male, 20–30 years old, 166 cm±3.27 cm), and a trauma survey was performed. Thanks to the restoration of the ID tag, parts of the name and enrolment number were found and cross-referenced with the anthropological data of the subject, matching the information in the available military records. The victim had no siblings or offspring, making it impossible to identify descendants. However, the operation led to a contextual/presumptive identification of the soldier and the discovery of his story. He was a native of Tuscany, who died during the “Punitive Expedition” (1916) and was buried, probably by his comrades, in a small flat area hidden from enemy lines. In investigations like this, the involvement of local communities, whether groups or individuals, is crucial. In this case report, it will be shown how multidisciplinary approaches and collective actions can play a pivotal role in resolving highly intricate scenarios, such as those pertaining to armed conflicts.

A set of about 25,000 residential reinforced concrete (RC) buildings has been investigated in this study to define fragility curves. The sample originates from a wide database, reported in the online Da.D.O. (Database of Observed Damage) platform, related to about 320,000 buildings inspected in the aftermath of the nine most devastating earthquakes occurred in Italy between 1976 and 2012 (Friuli 1976; Irpinia 1980; Abruzzo 1984; Umbria-Marche 1997; Pollino 1998; Molise 2002; Emilia 2003; L’Aquila 2009; Emilia 2012). The coherence of data has been guaranteed by a thorough critical analysis among all databases. Then a refined procedure dealing with the completeness of survey campaigns at Municipality level has been applied to avoid biases in fragility fitting. The final sample is then subdivided in different structural design types, determined as a function of the evolution of seismic classification for investigated areas and the sequence of technical codes enforced through the years. The available shakemaps in terms of PGA values, derived by National Institute of Geophysics and Volcanology, are used to characterize seismic ground motion at buildings’ site. The opportunity of enriching the sample of data with undamaged supplementary buildings, located in areas very far from epicenter but missing in the database (only because survey inspections were not required) is deeply discussed and investigated. Finally, according to such a set of data, different classes of buildings representative of existing RC building portfolio in Italy are defined and relevant vulnerability and fragility curves are determined.

Platelets are an active component of the tumor microenvironment (TME), involved in the regulation of multiple tumor processes, including angiogenesis. They are generated rich in angiogenic factors in their granules to actively participate in the hemostatic process by megakaryocytes and further enriched in angiogenic factors by all components of the tumor microenvironment to control the angiogenic process because of their preferential relationship with the endothelial component of vessels. In recent decades, the literature has reported a great deal of evidence on the role of platelets in tumor angiogenesis; however, it is unclear whether the number or mean volume of platelets and/or their content and localization in TME may have clinical relevance in the choice and management of therapy for the cancer patient. In this scoping review, we collected and critically reviewed the scientific evidence supporting a close relationship between platelets, cancer, and angiogenesis. The aim of this work was to define the landscape of platelet-activated angiogenesis in cancer progression and analyze what and how much evidence is present in the last 20 years in the literature at both the preclinical and clinical levels, to answer whether platelets could be a useful determinant for analyzing tumor angiogenesis. In conclusion, this scoping review indicates that there is much evidence, both preclinical and clinical, but in the preclinical context, studies demonstrate the direct involvement of platelets in tumor angiogenesis; in the clinical context the evidence is indirect, though strong, and the indication of how and to what extent platelet content contributes to tumor angiogenesis is lacking. So, do we need more evidence or better analysis? More molecular and quali-quantitative data is needed to translate the results obtained in preclinical studies into the clinical setting. This information about platelets, if correlated with tumor type and its biology, including tumor vasculature, type of angiogenesis, and patient characteristics (age, sex, comorbidities, drug treatments for chronic diseases) could be an important pa- rameter for correlating platelet biology to angiogenesis, for personalizing cancer therapy, and for clinical prognosis.

Minerals have key roles in the body’s metabolism and homeostasis. Biostimulants application to vegetables, such as seaweed extracts derived from Ecklonia maxima (SwE), is a useful agronomic approach to improve crop yield and quality by a naturally functionalizing process. We hypothesized that SwE biostimulants would impact the minerals profile of the lettuce and the consumption of lettuce with SwE application would affect blood minerals concentration in the health population. This in turn would impact metabolic pathways essential for human homeostasis. A group 48 healthy adults, of both sexes, was allocated in a double-blinded manner into groups that consumed 100 g a day of control lettuce, lettuce with SwE application or an iron tablet (30 mg) for four weeks. Blood samples were collected at baseline (T0) and at the end of the trial (T2) and compared for differences in serum mineral concentrations, iron, lipid and glucose homeostasis. In lettuce, SwE biostimulant enhanced iron concentration by about 63%. The consumption of lettuce with SwE application increased serum iron by about 38%, transferrin saturation by about 47%, and reduced total cholesterol by about 19% and Low-density lipoprotein by about 22%. Supplementation of iron in tablets has similar effects to lettuce with SwE application but with side effects (diarrhea or constipation). The study offers an innovative perspective by assessing lettuce with SwE application as a natural alternative to iron supplements that are commonly associated with gastrointestinal side effects. The results are of interest in the context of dietary iron deficiency especially among populations that avoid meat-based diets. This research could have broad implications for enhancing the nutritional value of plant-based foods to support dietary health by promoting intersection of sustainable agriculture and human nutrition. Clinical trial registration number : NCT06656871.

The Bayesian information criterion (BIC), the Akaike information criterion (AIC), and some other indicators derived from them are widely used for model selection. In their original form, they contain the likelihood of the data given the models. Unfortunately, in many applications, it is practically impossible to calculate the likelihood, and, therefore, the criteria have been reformulated in terms of descriptive statistics of the residual distribution: the variance and the mean-squared error of the residuals. These alternative versions are strictly valid only in the presence of additive noise of Gaussian distribution, not a completely satisfactory assumption in many applications in science and engineering. Moreover, the variance and the mean-squared error are quite crude statistics of the residual distributions. More sophisticated statistical indicators, capable of better quantifying how close the residual distribution is to the noise, can be profitably used. In particular, specific goodness of fit tests have been included in the expressions of the traditional criteria and have proved to be very effective in improving their discriminating capability. These improved performances have been demonstrated with a systematic series of simulations using synthetic data for various classes of functions and different noise statistics.

This study focuses on the seismic vulnerability of masonry buildings damaged by the 2009 L’Aquila earthquake. A geo-referenced database of 32,520 masonry residential buildings was compiled in the aftermath of the earthquake under the coordination of the Italian Department of Civil Protection through the AeDES survey form. The availability of this enormous amount of data provides an exceptional opportunity to examine in depth damage data and their correlation with the main parameters available from the post-earthquake survey. The original database was grouped into 20 building classes, defined as a function of vertical and horizontal structural types. Damage levels defined according to the European Macroseismic Scale classification are used to derive damage probability matrices and relevant vulnerability curves for these classes. The influences of connection systems, the quality/regularity of the masonry wall layout and the horizontal structural type on the building response are analysed in detail. A vulnerability classification, also supported by the use of statistical post hoc tests, is used to detect a reduced number of independent classes. The parameters of the non-crossing fragility curves are determined via the maximum likelihood estimation method by adopting a lognormal cumulative function to determine the exceedance probabilities of the considered damage levels. The impact of “mixed” classes, characterized by multiple vertical and/or horizontal structural types, on the derivation of the fragility curves is also investigated. Finally, the adaptation of the general version of the fragility curves to large-scale applications based on poor (census) data is also demonstrated, leading to curves that are easily usable in regional/national seismic loss assessments.