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Forma di governo delle Regioni: una valutazione dei suoi risultati e una proposta di riforma
Full text linkL’articolo ricostruisce innanzitutto l’evoluzione nel tempo della forma di governo delle Regioni a statuto ordinario, da un iniziale modello parlamentare a tendenza assembleare a un modello pseudoparlamentare basato sull’elezione diretta del Presidente, sull’elezione della maggioranza consiliare in collegamento con la elezione del Presidente e sullo scioglimento automatico del Consiglio in caso di sfiducia e conseguenti dimissioni del Presidente eletto. L’articolo valuta poi i risultati di queste forme di governo in termini di politica istituzionale, evidenziando che la forma standard attualmente adottata ha bensì garantito la stabilità degli esecutivi, ma a eccessivo detrimento del ruolo legislativo e di controllo dei Consigli, dell’equilibrio istituzionale tra i poteri, dell’effettiva capacità rappresentativa delle istituzioni e della partecipazione democratica dei
cittadini e degli enti locali alla formazione delle scelte regionali.
L’articolo propone quindi una riforma della forma di governo delle Regioni, secondo la quale spetterebbe all’autonomia statutaria regionale la scelta fra una forma di governo presidenziale classica, fondata sulla separazione e sul bilanciamento dei poteri fra Presidente e Consiglio, e una forma di governo parlamentare, razionalizzata in modo da conciliare rappresentatività delle istituzioni regionali, stabilità delle Giunte, riacquisizione di un ruolo ai Consigli, valorizzazione della partecipazione dei cittadini e degli enti locali: per il raggiungimento di questi obiettivi di politica istituzionale servono anche alcune importanti riforme “di contorno”, che l’articolo esamina nel suo paragrafo finale
Clinical trial eligibility in PSP: Population representativeness and potential criteria adjustment based on PSP-NET findings
No full textBackground: Progressive Supranuclear Palsy (PSP) is a rare, heterogeneous neurodegenerative disease for which no treatment is currently available. In the context of clinical trials, the representativeness of the included patients is crucial for the generalizability of the results. Herein, we present results from a multicenter perspective study to identify the most restrictive criteria for patient selection and to assess the representativeness of eligible patients. Methods: we enrolled 221 PSP patients diagnosed according to the MDS clinical criteria. All patients were screened with a set of inclusion and exclusion criteria based on previous and ongoing clinical trials in PSP and underwent motor and cognitive evaluation with the Montreal Cognitive Assessment battery and the PSP rating scale, respectively. Then, clinical features of eligible and non-eligible patients were compared at baseline and after 15,93 ± 8,77 months follow up. Results: Eligible (28 patients, 12,6 %) patients were younger, showed shorter disease duration and lower severity but similar distribution of PSP phenotype and disease progression rates compared to non-eligible patients. The most restrictive non-modifiable criteria were independent gait, disease duration and cognitive status. Willingness to undergo lumbar puncture and treatment stability for previous 60 days represented potentially modifiable criteria. Conclusion: Overall, PSP eligible for clinical trials are representative of the general PSP population. While motor and cognitive impairment represent the most important non-modifiable barriers to enter a clinical trial, other criteria as willingness to undergo lumbar puncture and treatment stability are potentially modifiable. Specific strategies are discussed to increase the number of eligible patients working on potentially modifiable criteria
Deep-Learning-Based Land Cover Mapping in Franciacorta Wine Growing Area
Full text linkLand cover mapping is essential to understanding global land-use patterns and studying biodiversity composition and the functioning of eco-systems. The introduction of remote sensing technologies and artificial intelligence models made it possible to base land cover mapping on satellite imagery in order to monitor changes, assess ecosystem health, support conservation efforts, and reduce monitoring time. However, significant challenges remain in managing large, complex satellite imagery datasets, acquiring specialized datasets due to high costs and labor intensity, including a lack of comparative studies for the selection of optimal deep learning models. No less important is the scarcity of aerial datasets specifically tailored for agricultural areas. This study addresses these gaps by presenting a methodology for semantic segmentation of land covers in agricultural areas using satellite images and deep learning models with pre-trained backbones. We introduce an efficient methodology for preparing semantic segmentation datasets and contribute the “Land Cover Aerial Imagery” (LICAI) dataset for semantic segmentation. The study focuses on the Franciacorta area, Lombardy Region, leveraging the rich diversity of the dataset to effectively train and evaluate the models. We conducted a comparative study, using cutting-edge deep-learning-based segmentation models (U-Net, SegNet, DeepLabV3) with various pre-trained backbones (ResNet, Inception, DenseNet, EfficientNet) on our dataset acquired from Google Earth Pro. Through meticulous data acquisition, preprocessing, model selection, and evaluation, we demonstrate the effectiveness of these techniques in accurately identifying land cover classes. Integrating pre-trained feature extraction networks significantly improves performance across various metrics. Additionally, addressing challenges such as data availability, computational resources, and model interpretability is essential for advancing the field of remote sensing, in support of biodiversity conservation and the provision of ecosystem services and sustainable agriculture
Climate Change Impact on Cereal Production in Northern Africa: A Comprehensive Modeling and Control Approach
No full textConcurrent RB1 and P53 pathway disruption predisposes to the development of a primitive neuronal component in high-grade gliomas depending on MYC-driven EBF3 transcription
Full text linkThe foremost feature of glioblastoma (GBM), the most frequent malignant brain tumours in adults, is a remarkable degree of intra- and inter-tumour heterogeneity reflecting the coexistence within the tumour bulk of different cell populations displaying distinctive genetic and transcriptomic profiles. GBM with primitive neuronal component (PNC), recently identified by DNA methylation-based classification as a peculiar GBM subtype (GBM-PNC), is a poorly recognized and aggressive GBM variant characterised by nodules containing cells with primitive neuronal differentiation along with conventional GBM areas. In addition, the presence of a PNC component has been also reported in IDH-mutant high-grade gliomas (HGGs), and to a lesser extent to other HGGs, suggesting that regardless from being IDH-mutant or IDH-wildtype, peculiar genetic and/ or epigenetic events may contribute to the phenotypic skewing with the emergence of the PNC phenotype. However, a clear hypothesis on the mechanisms responsible for this phenotypic skewing is still lacking. We assumed that the biphasic nature of these entities represents a unique model to investigate the relationships between genetic alterations and their phenotypic manifestations. In this study we show that in HGGs with PNC features both components are highly enriched in genetic alterations directly causing cell cycle deregulation (RB inactivation or CDK4 amplification) and p53 pathway inactivation (TP53 mutations or MDM2/4 amplification). However, the PNC component displays further upregulation of transcriptional pathways associated with proliferative activity, including overexpression of MYC target genes. Notably, the PNC phenotype relies on the expression of EBF3, an early neurogenic transcription factor, which is directly controlled by MYC transcription factors in accessible chromatin sites. Overall our findings indicate that the concomitant presence of genetic alterations, impinging on both cell cycle and p53 pathway control, strongly predisposes GBM to develop a concomitant poorly differentiated primitive phenotype depending on MYC-driven EBF3 transcription in a subset of glioma stem-like progenitor cells
Comparison of different fragmentation techniques for the production of true-to-life microplastics
No full text: Microplastics are small plastic particles found widely in the environment, posing significant challenges as diverse environmental contaminants. Their pervasive presence and potential impacts on ecosystems and human health underscore the importance of research in this field. However, working with microplastics in the laboratory and field can be challenging due to the difficulty in creating particles that are similar to those found in the environment. The advancement of research in this area is, therefore, dependent on the availability of reference materials or representative test materials that can simulate real-world conditions. One of the biggest challenges in creating more relevant test microplastics is investigating processes that can mimic as close as possible the environmental counterpart. To tackle this challenge, we have explored three distinct cryogenic grinding techniques for generating microplastics on a laboratory scale (ultracentrifugal mill, immersion blender, mixer mill). The resulting products were examined, and the advantages and limitations of the technologies were analyzed to gain deeper insights into the correlation between the various techniques utilized and the distinctive characteristics of the "true-to-life" microplastics produced. This allows us to tailor the production of test materials to the specific research questions they are intended to address. Furthermore, by understanding the characteristics of true-to-life microplastics, we can gain insights into their behavior under various environmental conditions. This knowledge can help in developing better methods for detecting and monitoring microplastics in the environment, as well as developing more effective mitigation strategies to reduce their impact
Oncological Feasibility of Limited Neck Dissection in cN0 Supraglottic Laryngeal Cancer
No full textBackground: Supraglottic squamous cell carcinoma (SCC) is a significant portion of head and neck cancers, with the management of clinically negative necks (cN0) through selective neck dissection (SND) being debated due to potential morbidities and low metastasis rates in levels IIb and IV. Methods: This study is a retrospective, multicenter examination of the potential feasibility of limited neck dissection (LND), including only levels IIa and III in cN0 supraglottic SCC patients. It analyzed occult metastasis rates and explored relapse occurrences alongside potential predictors of lymph node metastasis. Results: Among 425 patients, predominantly male (85.6%) with a mean age of 63 years, the occult metastasis rate was 28.9%, and 13.7% experienced relapses during a mean follow-up of 52 months. Advanced clinical stage, higher grading, and other risk factors emerged as predictors of occult lymph node metastasis at level IIb. Conclusions: The study supports LND potential feasibility for cN0 supraglottic SCC, suggesting level IIb dissection can be omitted in specific early-stage cases to reduce morbidity without affecting outcomes
