La mobilita’ della cultura comica come segno della sua eterogeneita’

В России восемнадцатого века любительский театр представляет собой идеальное поприще для необычайно продуктивного „диалога культур”, когда проявляется ярче „свое” и охотно перенимается „чужое”. С этой точки зрения любительский театр – одно из наиболее богатых явлений комедийной культуры, дающее простор сложному процессу экспериментирования и переработки направлений различного происхождения. В частности, в комедийных сценах и интермедиях смешиваются воедино разные традиции, такие как школьный театр, повесть, демократическая сатира, народный театр, комедия дель арте и т.д., образуя чрезвычайно подвижный (живой) узел, который сплетается, вбирая в себя самые разнородные влияния, и вновь распускается, чтобы тут же опять туго стянуться вокруг новой связки мотивов, давая тем самым жизнь новому произведению. Подобная подвижность и разнородность мотивов наблюдается и в лубке: интермедия и лубок обнаруживают множество общих аспектов – и потому, что лубок часто изображает те же сюжеты, что и интермедия, и потому, что составляющие его элементы организованы по-театральному в плане семиотики.Università degli Studi di Trieste - Scuola Superiore di Lingue Moderne per Interpreti e Traduttori. Università degli Studi di Bergamo - Dipartimento di Linguistica e Letterature comparat

Genomic and Epigenomic study of Stage I Epithelial Ovarian Carcinomas to Implement Novel Prognostic Molecular Biomarkers

Stage I epithelial ovarian carcinomas represent the earliest stage of ovarian carcinoma, when the disease is confined to the ovaries, and is amenable to efficient treatment by cytoreductive surgery followed by adjuvant chemotherapy in cases considered at high- risk of relapse. It is generally characterized by a favourable outcome; with just about 20% of relapse. However, the staging of the tumour is often suboptimal causing on one hand over-treatment of many who receive adjuvant chemotherapy to prevent recurrence, and on the other hand under-treatment of those improperly defined as "low risk", who experience relapses with a much poorer prognosis. The histologically heterogeneity of stage I epithelial ovarian tumours further complicates the development of efficient prognostic markers. Nevertheless, previous results on the transcriptomic signatures of stage I tumours obtained in the hosting Lab, prompted us to extend the current knowledge about the molecular landscape of stage I tumours to potentially identify novel parameters able to stratify patients based on the prognosis. In my PhD project, I exploited high-throughput Next Generation Sequencing approaches to evaluate the most recurrent Single Nucleotide Variants in a subset of frequently altered genes in ovarian cancer and the Somatic Copy Number Alterations distribution across the genome on a unique cohort of 205 stage I epithelial ovarian cancer patients. These analyses revealed the existence of three different genomic instability patterns namely stable, unstable and highly unstable, based on the on the percentage of genome affected by copy number alterations and their length. These patterns are strictly related to distinct etiopathogenetic processes that drive tumour evolutionary routes. In an effort to define potential mechanisms involved in the generation of genomic instability, five copy number signatures related to different mutational pathways were defined and global DNA methylation was assessed through LINE1 promoter methylation status. The significant association of the genome instability with a reduction in global methylation levels by LINE-1 retrotransposons supports a close relationship between the genomic landscape and tumour epigenetic regulation. Finally, the three SCNA patterns were correlated to patients’ survival and resulted strongly predictive of patients’ prognosis also in multivariate models with the currently used clinical variables. These results show that genomic and epigenomic analyses offer novel possibilities to identify markers useful for the management of the disease, offering an improved patient prognosis prediction

Reusable Cavitand‐Based Electrospun Membranes for the Removal of Polycyclic Aromatic Hydrocarbons from Water

The removal of toxic and carcinogenic polycyclic aromatic hydrocarbons (PAHs) from water is one of the most intractable environmental problems nowadays, because of their resistance to remediation. This work introduces a highly efficient, regenerable membrane for the removal of PAHs from water, featuring excellent filter performance and pH-driven release, thanks to the integration of a cavitand receptor in electrospun polyacrylonitrile (PAN) fibers. The role of the cavitand receptor is to act as molecular gripper for the uptake/ release of PAHs. To this purpose, the deep cavity cavitand BenzoQxCav is designed and synthetized and its molecular structure is elucidated via X-Ray diffraction. The removal efficiency of the new adsorbent material toward the 16 priority PAHs is demonstrated via GC-MS analyses at ng L−1 concentration. A removal efficiency in the 32%, to 99% range is obtained. The regeneration of the membrane is performed by exploiting the pH-driven conformational switching of the cavitand between the vase form, where the PAHs uptake takes place, to the kite one, where the PAHs release occurs. The absorbance and regeneration capability of the membrane are successfully tested in four uptake/release cycles and the morphological stability

The open abdomen, indications, management and definitive closure

The indications for Open Abdomen (OA) are generally all those situations in which is ongoing the development an intra-abdominal hypertension condition (IAH), in order to prevent the development of abdominal compartmental syndrome (ACS). In fact all those involved in care of a critically ill patient should in the first instance think how to prevent IAH and ACS. In case of ACS goal directed therapy to achieve early opening and early closure is the key: paradigm of closure shifts to combination of therapies including negative pressure wound therapy and dynamic closure, in order to reduce complications and avoid incisional hernia. There have been huge studies and progress in survival of critically ill trauma and septic surgical patients: this in part has been through the great work of pioneers, scientific societies and their guidelines; however future studies and continued innovation are needed to better understand optimal treatment strategies and to define more clearly the indications, because OA by itself is still a morbid procedure.Peer reviewe

Impact of the COVID-19 outbreak on severe trauma trends and healthcare system reassessment in Lombardia, Italy: an analysis from the regional trauma registry

Backgrounds: The COVID-19 pandemic drastically strained the health systems worldwide, obligating the reassessment of how healthcare is delivered. In Lombardia, Italy, a Regional Emergency Committee (REC) was established and the regional health system reorganized, with only three hospitals designated as hubs for trauma care. The aim of this study was to evaluate the effects of this reorganization of regional care, comparing the distribution of patients before and during the COVID-19 outbreak and to describe changes in the epidemiology of severe trauma among the two periods. Methods: A cohort study was conducted using retrospectively collected data from the Regional Trauma Registry of Lombardia (LTR). We compared the data of trauma patients admitted to three hub hospitals before the COVID-19 outbreak (September 1 to November 19, 2019) with those recorded during the pandemic (February 21 to May 10, 2020) in the same hospitals. Demographic data, level of pre-hospital care (Advanced Life Support-ALS, Basic Life Support-BLS), type of transportation, mechanism of injury (MOI), abbreviated injury score (AIS, 1998 version), injury severity score (ISS), revised trauma score (RTS), and ICU admission and survival outcome of all the patients admitted to the three trauma centers designed as hubs, were reviewed. Screening for COVID-19 was performed with nasopharyngeal swabs, chest ultrasound, and/or computed tomography. Results: During the COVID-19 pandemic, trauma patients admitted to the hubs increased (46.4% vs 28.3%, p < 0.001) with an increase in pre-hospital time (71.8 vs 61.3 min, p < 0.01), while observed in hospital mortality was unaffected. TRISS, ISS, AIS, and ICU admission were similar in both periods. During the COVID-19 outbreak, we observed substantial changes in MOI of severe trauma patients admitted to three hubs, with increases of unintentional (31.9% vs 18.5%, p < 0.05) and intentional falls (8.4% vs 1.2%, p < 0.05), whereas the pandemic restrictions reduced road- related injuries (35.6% vs 60%, p < 0.05). Deaths on scene were significantly increased (17.7% vs 6.8%, p < 0.001). Conclusions: The COVID-19 outbreak affected the epidemiology of severe trauma patients. An increase in trauma patient admissions to a few designated facilities with high level of care obtained satisfactory results, while COVID-19 patients overwhelmed resources of most other hospitals

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients

IntroductionArtificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods. MethodsWe prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions. ResultsOf 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models' prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR. ConclusionsIn this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients

Unstable Maternal Environment, Separation Anxiety, and Heightened CO2 Sensitivity Induced by Gene-by-Environment Interplay

Background: In man, many different events implying childhood separation from caregivers/unstable parental environment are associated with heightened risk for panic disorder in adulthood. Twin data show that the occurrence of such events in childhood contributes to explaining the covariation between separation anxiety disorder, panic, and the related psychobiological trait of CO2 hypersensitivity. We hypothesized that early interference with infant-mother interaction could moderate the interspecific trait of response to CO2 through genetic control of sensitivity to the environment. Methodology: Having spent the first 24 hours after birth with their biological mother, outbred NMRI mice were crossfostered to adoptive mothers for the following 4 post-natal days. They were successively compared to normally-reared individuals for: number of ultrasonic vocalizations during isolation, respiratory physiology responses to normal air (20%O2), CO2-enriched air (6% CO2), hypoxic air (10%O2), and avoidance of CO2-enriched environments. Results: Cross-fostered pups showed significantly more ultrasonic vocalizations, more pronounced hyperventilatory responses (larger tidal volume and minute volume increments) to CO2-enriched air and heightened aversion towards CO2- enriched environments, than normally-reared individuals. Enhanced tidal volume increment response to 6%CO2 was present at 16–20, and 75–90 postnatal days, implying the trait’s stability. Quantitative genetic analyses of unrelated individuals, sibs and half-sibs, showed that the genetic variance for tidal volume increment during 6%CO2 breathing was significantly higher (Bartlett x = 8.3, p = 0.004) among the cross-fostered than the normally-reared individuals, yielding heritability of 0.37 and 0.21 respectively. These results support a stress-diathesis model whereby the genetic influences underlying the response to 6%CO2 increase their contribution in the presence of an environmental adversity. Maternal grooming/licking behaviour, and corticosterone basal levels were similar among cross-fostered and normally-reared individuals. Conclusions: A mechanism of gene-by-environment interplay connects this form of early perturbation of infant-mother interaction, heightened CO2 sensitivity and anxiety. Some no

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients

IntroductionArtificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods.MethodsWe prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions.ResultsOf 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models’ prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR.ConclusionsIn this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients

Sigh in patients with acute hypoxemic respiratory failure and acute respiratory distress syndrome: the PROTECTION pilot randomized clinical trial

Background: Sigh is a cyclic brief recruitment manoeuvre: previous physiological studies showed that its use could be an interesting addition to pressure support ventilation to improve lung elastance, decrease regional heterogeneity and increase release of surfactant. Research question: Is the clinical application of sigh during pressure support ventilation (PSV) feasible? Study design and methods: We conducted a multi-center non-inferiority randomized clinical trial on adult intubated patients with acute hypoxemic respiratory failure or acute respiratory distress syndrome undergoing PSV. Patients were randomized to the No Sigh group and treated by PSV alone, or to the Sigh group, treated by PSV plus sigh (increase of airway pressure to 30 cmH2Ofor 3 seconds once per minute) until day 28 or death or successful spontaneous breathing trial. The primary endpoint of the study was feasibility, assessed as non-inferiority (5% tolerance) in the proportion of patients failing assisted ventilation. Secondary outcomes included safety, physiological parameters in the first week from randomization, 28-day mortality and ventilator-free days. Results: Two-hundred fifty-eight patients (31% women; median age 65 [54-75] years) were enrolled. In the Sigh group, 23% of patients failed to remain on assisted ventilation vs. 30% in the No Sigh group (absolute difference -7%, 95%CI -18% to 4%; p=0.015 for non-inferiority). Adverse events occurred in 12% vs. 13% in Sigh vs. No Sigh (p=0.852). Oxygenation was improved while tidal volume, respiratory rate and corrected minute ventilation were lower over the first 7 days from randomization in Sigh vs. No Sigh. There was no significant difference in terms of mortality (16% vs. 21%, p=0.342) and ventilator-free days (22 [7-26] vs. 22 [3-25] days, p=0.300) for Sigh vs. No Sigh. Interpretation: Among hypoxemic intubated ICU patients, application of sigh was feasible and without increased risk