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Alcohol Use Disorders
No full textOverall, despite the literature so far published seems to report conflicting data, some evidence coming from some retrospective cohort studies provide some data on the effects of maternal alcohol intake during pregnancy and/or breastfeeding. Alcohol use disorder (AUD) during pregnancy and postpartum period may determine the onset of major and/or minor congenital malformations (during the exposition in the first pregnancy trimester), intellectual disability in the newborns exposed throughout pregnancy and the risk of developing a foetal alcohol syndrome (FAS) and foetal alcohol spectrum disorders (FASD). Alcohol use during lactation has also been associated with an increased prevalence of adult deficit hyperactivity disorder (ADHD) and altered infant sleep patterns. Overall, there is little research information and methodologically well-designed clinical studies able to guide clinicians working within Mental Health’s and Drug Addiction’s services regarding clinical decision-making and therapeutic flowchart for the management and treatment of pregnant and/or nursing women affected with AUD. Motivational interviewing and brief interventions have been demonstrated to be more effective than judgmental or punitive approaches in encouraging positive behavioural lifestyle changes. Little evidence is available in the treatment and management of alcohol withdrawal during pregnancy and in the prescription of acamprosate, naltrexone and disulfiram. Overall, the best management approach should be recommended to all clinicians to advise all women who are pregnant or planning a pregnancy the potential risks related to alcohol intake during pregnancy and breastfeeding, the associated risk if a woman is already affected with AUD and she is at-risk to develop alcohol dependence. In particular, women should be recommended that not drinking is the safest option to limit/reduce the risk of fetal malformations, perinatal and/or obstetrician complications and limit the risks on newborns. Similarly, alcohol intake should be greatly avoided during the postpartum period, particularly when the woman decides to breastfeed the newborn. All women should be adequately supported in a non-judgemental manner and help them in the management of alcohol intake throughout the perinatal period
Inferior Alveolar Nerve Impairment Following Third-Molar Extraction: Management of Complications and Medicolegal Considerations
Get PDFBackground: Wisdom tooth extraction is a routine procedure with potential complications. In the lower arch, the displacement of a root or its fragment into the submandibular space is a relatively common occurrence that can lead to permanent damage to peripheral nerve fibers. Recent advancements in dental technologies, including CAD-CAM and artificial intelligence, have contributed to improved clinical outcomes in surgical procedures. Methods: Following a brief introductory narrative review, this clinical case describes the extraction of the left third inferior molar, which was sectioned by the oral surgeon to facilitate its removal. The procedure led to the progressive migration of a root fragment into the submandibular space, triggering an infective process. Efforts to retrieve the root fragment resulted in irreversible damage to the somatosensory motor nerves associated with the inferior alveolar nerve after the second surgery was performed by a maxillofacial surgeon. Results: Determining the responsibility for the damage (caused either by the oral or maxillofacial surgeon) involves both technical and ethical considerations, which are particularly relevant in cases involving re-intervention by different specialists. This case highlights the importance of a thorough preoperative evaluation of the patient’s anatomical, bone, and dental characteristics. The use of new technologies can significantly reduce the risk of complications that may otherwise lead to permanent damage and complex determinations of professional responsibility. Conclusions: Given the potential, albeit rare, for permanent disturbance of sensory and motor functions, managing complications and assessing the resulting damage are critical and sensitive steps in resolving such case both clinically and legally
Advancements and emerging trends in integrating machine learning and deep learning for SHM in mechanical and civil engineering: a comprehensive review
No full textThe safety of structures heavily relies on the crucial role of structural health monitoring (SHM), reliability, and longevity of mechanical and civil infrastructure. Traditional methods of SHM often rely on manual inspection and monitoring techniques, which can be time-consuming, expensive, and prone to human error. In recent years, the integration of machine learning (ML) and deep learning (DL) techniques has shown great promise in revolutionizing SHM by enabling automated and accurate monitoring of structural conditions. This review paper provides a comprehensive analysis of the application of ML and DL algorithms, such as artificial neural networks (ANN), convolutional neural networks (CNN), and deep neural networks (DNN), in SHM. It explores the various approaches and methodologies employed in the field, including supervised, unsupervised, and reinforcement learning techniques. The paper discusses the advantages and limitations of ML and DL in SHM, highlighting their ability to handle large volumes of data, extract complex features, and provide real-time monitoring and predictive capabilities. Moreover, it addresses the challenges associated with implementing ML and DL in SHM, including data limitations, model complexity, interpretability, and the integration of domain knowledge. By reviewing a wide range of studies and applications, this paper aims to provide valuable insights into the current state-of-the-art, emerging trends, and future directions in ML and DL-based SHM
Transforming cities - Cities as transformers
No full textTRANSFORMERS is a DAAD higher education dialogue between Germany and Italy about the role and agency of cities to reach climate neutrality. The project focuses on the interrelation and dynamics between urban fabric, architecture, and communities, searching for new transformative knowledge
Repeatome Analysis of Plasma Circulating DNA in Patients with Cardiovascular Disease: Variation with Cell-Free DNA Integrity/Length and Clinical Parameters
Get PDFRepetitive DNA represents over 50% of the human genome and is an abundant component of circulating cell-free DNA (cfDNA). We previously showed that cfDNA levels and integrity can predict survival in elderly patients with cardiovascular disease. Here, we aimed to clarify whether a low-pass next-generation sequencing (NGS) approach can characterize the repeat content of cfDNA. Considering the bimodal distribution of cfDNA fragment lengths, we examined the occurrence of repetitive DNA subfamilies separately in dinucleosomal (>250 bp) and mononucleosomal (≤250 bp) cfDNA sequences from 24 patients admitted for heart failure. An increase in the relative abundance of Alu repetitive elements was observed in the longer fraction, while alpha satellites were enriched in the mononucleosomal fraction. The relative abundance of Alu, ALR, and L1HS DNA in the dinucleosomal fraction correlated with different prognostic biomarkers, and Alu DNA was negatively associated with the presence of chronic kidney disease comorbidity. These results, together with the observed inverse correlation between Alu DNA abundance and cfDNA integrity, suggest that the composition of plasma cfDNA could be determined by multiple mechanisms in different physio-pathological conditions. In conclusion, low-pass NGS is an inexpensive method to analyze the cfDNA repeat landscape and identify new cardiovascular disease biomarkers
High-Accuracy Detection of Bottlenose Dolphin Whistle Using AI
No full textThe persistent interaction between dolphins and commercial fishing operations has led to ecological and socio-economic challenges, primarily through bycatch and depredation. Traditional mitigation strategies have shown limited success, needing innovative solutions. Intelligent robotic systems capable of identifying and consequently responding to dolphin vocalizations seem to be a promising approach to mitigate dolphin interactions with fishing operations. The core of this intelligent system should be an advanced algorithm or an artificial intelligence architecture capable of identifying dolphin vocalizations and distinguishing them from other underwater sounds. Thus, this study proposes a novel approach to detect dolphin whistles using a convolutional neural network (CNN) paired with advanced spectrogram processing techniques. The method utilizes audio recordings of common bottlenose dolphins (Tursiops truncatus) from Oltremare marine park in Italy. Whistle detection was enhanced by applying edge-detection filters to spectrograms, which highlights characteristic of dolphin whistles while filtering out noise. The processed spectrograms served as inputs to a CNN with a three-layer architecture optimized for binary classification of dolphin whistles. The model achieved very promising results, with accuracy, precision, recall, and F1-scores around 99% across a 10-fold cross-validation. The findings demonstrate the method robustness, offering potential applications in conservation efforts and real-time monitoring. Future research will focus on adapting the approach to field conditions where real-time processing and non-ideal whistle recording pose additional challenges
Disease Phenotype Significantly Influences the Outcome After Discontinuation of Ruxolitinib in Chronic Phase Myelofibrosis
No full textIntroduction: In patients with myelofibrosis (MF), overall survival (OS) after ruxolitinib discontinuation is poor, with leukemic transformation, clonal evolution and thrombocytopenia as the main factors worsening prognosis. Patients and methods: To assess the impact of disease phenotype on outcome after ruxolitinib discontinuation in chronic phase patients, we performed a sub-analysis of the "RUX-MF" study (NCT06516406), which now includes 1055 MF patients who received ruxolitinib in a real-life context. Results: After a median follow-up of 3.3 years, 397 patients discontinued ruxolitinib therapy while in chronic phase. At treatment end, 208 patients (52.4%) had a severely cytopenic phenotype (defined as platelets < 100 × 109/L and/or hemoglobin < 8 g/dL); among the remaining myeloproliferative 189 patients, 97 had no cytopenia (51.3%) and 92 (48.7%) had mild anemia only (hemoglobin between 8 and 10 g/dL). Overall, 175 patients (44.1%) had a large splenomegaly (palpable at ≥ 10 cm below costal margin). After ruxolitinib discontinuation, 3-year OS was 33.4% in severely cytopenic and 54.4% in myeloproliferative patients (P < .001); this was confirmed after adjustment for risk categories. Noncytopenic and mildly anemic patients had comparable OS (P = .73). Patients with large splenomegaly had significantly poorer OS compared to nonsplenomegalic patients (OS: 33.5% vs. 51.6% P = .01). Large splenomegaly confirmed its negative prognostic impact on OS of patients with myeloproliferative MF (60.7% vs. 44.5%, P = .05). In patients with severe cytopenia, the presence of a large splenomegaly did not influence OS (41.7% vs. 26.1%, P = .26). Conclusions: Cytopenic phenotype and large splenomegaly in myeloproliferative MF are key prognostic determinants of outcome after ruxolitinib discontinuation
Stochastic assessment of groundwater PFAS concentrations in North-Eastern Italy
No full textPer- and poly-fluoroalkyl substances (PFAS) and in particular their perfluoroalkyl acids (PFAA), are among the most concerning sources of groundwater pollution, due to their persistence and to their negative effects on human health. Since 2013 the Regional Agency for Environmental Protection of the Veneto Region (North-Eastern Italy) systematically monitors groundwater PFAA concentrations at water-supply wells. The present work is the first stochastic assessment, based on real data, of spatially distributed hazardous areas ever made for this territory. A geostatistical variogram-based approach has been employed to appraise the spatial correlation of quality data, and stochastically simulated concentrations at a scale of 1 km2, through Sequential Gaussian Simulations. The results have been evaluated upon multiple hazardousness criteria, coming from exceeding threshold concentrations provided by the latest regulations defined by (i) the European Union, (ii) the United States Environmental Protection Agency (USEPA), and (iii) the Veneto Region (Italy). Simulations’ results enabled the evaluation of best-estimated concentration spreads and the probability of exceeding EU, EPA, or Veneto Region limits. Moreover, the role of these regulation limits in delineating the spatial extension of probable over-threshold groundwater contaminated areas was evaluated. Only Verona and Vicenza provinces, located within the Adige and Brenta river basins, significantly exceed regulatory limits. Particularly high PFAA concentrations are estimated to occur in the aquifers underlying the medium-high reaches of the Adige, Brenta, and Agno-Guà-Frassine-Gorzone rivers. The soundness of the results and the methodological approach was supported by demonstrating the consistency of widespread contamination across the domain with groundwater flow directions inferred from the most recent numerical model available. This work provides an example of how to deal with PFAA groundwater contamination from a stochastic and probabilistic perspective through geostatistics and to spatially appraise groundwater contamination leveraging available data
Investigation of Water and Mud Effects on the Propagation of Real 5G Signal by Using the Reverberation Chamber
Get PDFWe investigated the propagation condition in a particular environment, such as an area covered by water or mud. In particular, we analyzed the effect on signal propagation in a fifth-generation (5G) wireless communication system in that scenario. The experiments were carried out in a laboratory inside a reverberation chamber that emulates a complex propagation environment, equipped with a 5G base station connected to the TIM live network. We measured: 1) the permittivity of the medium under investigation; 2) the effects of the presence of such mixtures within the propagation environment to test the 5G system by checking the key performance indicators. The chosen situations emulate the radio channel propagation in a hostile scenario such as during a flood, to evaluate the performance of a 5G base station. For the characterization of the medium, we considered its physical properties such as the permittivity, conductivity, and reflection coefficients. Moreover, to assess radio performance of the 5G system, we report the following key performance indicators: RSRP, SINR, CQI, MCS and BLER. Experimental results show that water creates a greater multipath than mud, confirmed by direct measurements of permittivity and conductivity. Furthermore, experiments conducted in the laboratory reveal the same behavior of the propagation scenario in a realistic flood such as the lowering of about 3 dB in terms of RSRP between the normal situation and the flooded scenario
