Ogni giovedì. Lettura archeologica compartecipata della materialità domestica femminile durante il primo lockdown italiano.

In the spring of 2020, Italy was among the first countries to experience home confinement as a public health measure to contain the Covid-19 epidemic. This measure significantly impacted women’s lives and their relationships with space and daily materiality. T his contribution recounts the experience of a participatory archaeological observation project conducted during those weeks of collective ‘anthropause,’ exploring the relationship with a community, both virtual and real, united by the shared experience of home isolation and gender identity. The article describes the context, methods, and data collected through an unprecedented experiment in reading contemporary domestic materiality conducted remotely, without the possibility of direct physical contact with the investigation’s traces, objects, and subjects. The case study presents the work on the extensive data collected between March and July 2020, involving a focus group of Italian women, diverse in age, geographical origin, and profession. In particular, the article outlines the methodological solutions implemented to ontologically manage the large amount of collected data, including creating a dedicated ontology and mapping with existing thesauri. It also provides some interpretative examples of the main elements analysed and the relationships between intimate information and material aspects. Within this context, the article concludes with reflections on the broader methodological theme of conducting archaeology of the present, ranging from considerations related to the abundance of traces and constant immersion in them to the transformation of space and objects in their material and symbolic definition to the determination and impact of temporal references during short and medium-term spans in the interpretative phase

NAVIGATING A NEW DIGITAL INTERFACE: USING AUTOMATED IMAGE RECOGNITION TO IDENTIFY POTTERY IN THE ARCHAIDE PROJECT

Archaeological Automatic Interpretation and Documentation of cEramic (ArchAIDE) is a H2020 funded project (2016-2019) developing digital tools to support archaeologists in recognising and classifying pottery. ArchAIDE is not designed to replace the knowledge of pottery specialists, but seeks to complement by speeding time consuming tasks, provide support for non-specialists, help students learn more about pottery recognition, and aid in the collection of metadata needed to describe the pottery. ArchAIDE is developing a tablet-based mobile app which relies upon image recognition and uses deep learning to narrow and suggest possible matches. While ArchAIDE has been careful to design a tool that allows classification decisions to be made by users at key points in the recording workflow, the app uses digital tools and methods for a significant tasks that were previously carried out using analogue methods. This paper will explore how users are engaging differently with the archaeology when using a digital workflow for identifying, classifying and recording pottery, as observed by the ArchAIDE project partners in early testing. This will include issues around using digitised comparative collections rather than paper catalogues, using the app to identify pottery while still in the field-rather than during post-excavation, how users might ‘see’ pottery differently through a digital rather than analogue analysis, and whether pottery identification using a digital interface changes knowledge transmission and learning processes. While the purpose of the ArchAIDE project is to make pottery identification faster and easier, this paper will pause to reflect and critically engage with moving to a digital workflow, and how this may influence how archaeological knowledge is produced and understood

An Open System for Collection and Automatic Recognition of Pottery through Neural Network Algorithms

In the last ten years, artificial intelligence (AI) techniques have been applied in archaeology. The ArchAIDE project realised an AI-based application to recognise archaeological pottery. Pottery is of paramount importance for understanding archaeological contexts. However, recognition of ceramics is still a manual, time-consuming activity, reliant on analogue catalogues. The project developed two complementary machine-learning tools to propose identifications based on images captured on-site, for optimising and economising this process, while retaining key decision points necessary to create trusted results. One method relies on the shape of a potsherd; the other is based on decorative features. For the shape-based recognition, a novel deep-learning architecture was employed, integrating shape information from points along the inner and outer profile of a sherd. The decoration classifier is based on relatively standard architectures used in image recognition. In both cases, training the algorithms meant facing challenges related to real-world archaeological data: the scarcity of labelled data; extreme imbalance between instances of different categories; and the need to take note of minute differentiating features. Finally, the creation of a desktop and mobile application that integrates the AI classifiers provides an easy-to-use interface for pottery classification and storing pottery data

Verso la rivoluzione. Dall'Open Access all'Open Data: la pubblicazione aperta in archeologia

La pubblicazione congiunta di articoli e datasets, che è ormai prassi in molte disciplinescientifiche, fa ancora fatica ad affermarsi in campo umanistico e in archeologia in particolare. L’articolo analizza i principali ostacoli e propone soluzioni basandosi su tre principifondamentali. 1) Il principio di scientificità: i dati sono essenziali per verificare l’attendibilitàdelle conclusioni. 2) Il principio di condivisione: in una disciplina basata su metodi distrut-tivi, la mancanza di condivisione delle informazioni non solo inibisce la ricerca, ma rappre-senta anche una tragica perdita di insostituibile conoscenza culturale e storica. 3) Il principio di riuso: poiché i dati archeologici sono di pubblico interesse, devono essere apertamente riutilizzabil

MAPPA. Metodologie Applicate alla Predittività del Potenziale Archeologico. 2

La carta di potenziale archeologico della città di Pisa. L'algoritmo elaborato ad hoc per il calcolo del potenziale archeologico. Il MOD: il primo archivio italiano open data di documenti archeologici

Antibody dependent cellular cytotoxicity-inducing anti-EGFR antibodies as effective therapeutic option for cutaneous melanoma resistant to BRAF inhibitors

Introduction: About 50% of cutaneous melanoma (CM) patients present activating BRAF mutations that can be effectively targeted by BRAF inhibitors (BRAFi). However, 20% of CM patients exhibit intrinsic drug resistance to BRAFi, while most of the others develop adaptive resistance over time. The mechanisms involved in BRAFi resistance are disparate and globally seem to rewire the cellular signaling profile by up-regulating different receptor tyrosine kinases (RTKs), such as the epidermal growth factor receptor (EGFR). RTKs inhibitors have not clearly demonstrated anti-tumor activity in BRAFi resistant models. To overcome this issue, we wondered whether the shared up-regulated RTK phenotype associated with BRAFi resistance could be exploited by using immune weapons as the antibody-dependent cell cytotoxicity (ADCC)-mediated effect of anti-RTKs antibodies, and kill tumor cells independently from the mechanistic roots. Methods and results: By using an in vitro model of BRAFi resistance, we detected increased membrane expression of EGFR, both at mRNA and protein level in 4 out of 9 BRAFi-resistant (VR) CM cultures as compared to their parental sensitive cells. Increased EGFR phosphorylation and AKT activation were observed in the VR CM cultures. EGFR signaling appeared dispensable for maintaining resistance, since small molecule-, antibody- and CRISPR-targeting of EGFR did not restore sensitivity of VR cells to BRAFi. Importantly, immune-targeting of EGFR by the anti-EGFR antibody cetuximab efficiently and specifically killed EGFR-expressing VR CM cells, both in vitro and in humanized mouse models in vivo, triggering ADCC by healthy donors' and patients' peripheral blood cells. Conclusion: Our data demonstrate the efficacy of immune targeting of RTKs expressed by CM relapsing on BRAFi, providing the proof-of-concept supporting the assessment of anti-RTK antibodies in combination therapies in this setting. This strategy might be expected to concomitantly trigger the crosstalk of adaptive immune response leading to a complementing T cell immune rejection of tumors

A microRNA prognostic signature in patients with diffuse intrinsic pontine gliomas through non-Invasive liquid biopsy

SIMPLE SUMMARY: Diffuse intrinsic pontine glioma (DIPG) is a neuro-radiologically defined tumor of the brainstem, primarily affecting children, with most diagnoses occurring between 5 and 7 years of age. Surgical removal in DIPGs is not feasible. Subsequent tumor progression is almost universal and no biomarker for predicting the course of the disease has entered into clinical practice so far. Under these premises, it is essential to develop reliable biomarkers that are able to improve outcomes and stratify patients using non-invasive methods to determine tumor profiles. We designed a study assessing circulating miRNA expression by a high-throughput platform and divided patients into training and validation phases in order to disclose a potential signature with clinical impact. Our results for the first time have proved the usefulness of blood-circulating nucleic acids as powerful, easy-to-assay molecular markers of disease status in DIPG. ABSTRACT: Diffuse midline gliomas (DMGs) originate in the thalamus, brainstem, cerebellum and spine. This entity includes tumors that infiltrate the pons, called diffuse intrinsic pontine gliomas (DIPGs), with a rapid onset and devastating neurological symptoms. Since surgical removal in DIPGs is not feasible, the purpose of this study was to profile circulating miRNA expression in DIPG patients in an effort to identify a non-invasive prognostic signature with clinical impact. Using a high-throughput platform, miRNA expression was profiled in serum samples collected at the time of MRI diagnosis and prior to radiation and/or systemic therapy from 47 patients enrolled in clinical studies, combining nimotuzumab and vinorelbine with concomitant radiation. With progression-free survival as the primary endpoint, a semi-supervised learning approach was used to identify a signature that was also tested taking overall survival as the clinical endpoint. A signature comprising 13 circulating miRNAs was identified in the training set (n = 23) as being able to stratify patients by risk of disease progression (log-rank p = 0.00014; HR = 7.99, 95% CI 2.38–26.87). When challenged in a separate validation set (n = 24), it confirmed its ability to predict progression (log-rank p = 0.00026; HR = 5.51, 95% CI 2.03–14.9). The value of our signature was also confirmed when overall survival was considered (log-rank p = 0.0021, HR = 4.12, 95% CI 1.57–10.8). We have identified and validated a prognostic marker based on the expression of 13 circulating miRNAs that can shed light on a patient’s risk of progression. This is the first demonstration of the usefulness of nucleic acids circulating in the blood as powerful, easy-to-assay molecular markers of disease status in DIPG. This study provides Class II evidence that a signature based on 13 circulating miRNAs is associated with the risk of disease progression

Developing the ArchAIDE Application: A digital workflow for identifying, organising and sharing archaeological pottery using automated image recognition

Pottery is of fundamental importance for understanding archaeological contexts, facilitating the understanding of production, trade flows, and social interactions. Pottery characterisation and the classification of ceramics is still a manual process, reliant on analogue catalogues created by specialists, held in archives and libraries. The ArchAIDE project worked to streamline, optimise and economise the mundane aspects of these processes, using the latest automatic image recognition technology, while retaining key decision points necessary to create trusted results. Specifically, ArchAIDE worked to support classification and interpretation work (during both fieldwork and post-excavation analysis) with an innovative app for tablets and smartphones. This article summarises the work of this three-year project, funded by the European Union's Horizon 2020 Research and Innovation Programme under grant agreement N.693548, with a consortium of partners representing both the academic and industry-led ICT (Information and Communications Technology) domains, and the academic and development-led archaeology domains. The collaborative work of the archaeological and technical partners created a pipeline where potsherds are photographed, their characteristics compared against a trained neural network, and the results returned with suggested matches from a comparative collection with typical pottery types and characteristics. Once the correct type is identified, all relevant information for that type is linked to the new sherd and stored within a database that can be shared online. ArchAIDE integrated a variety of novel and best-practice approaches, both in the creation of the app, and the communication of the project to a range of stakeholders

Clinical Features, Cardiovascular Risk Profile, and Therapeutic Trajectories of Patients with Type 2 Diabetes Candidate for Oral Semaglutide Therapy in the Italian Specialist Care

Introduction: This study aimed to address therapeutic inertia in the management of type 2 diabetes (T2D) by investigating the potential of early treatment with oral semaglutide. Methods: A cross-sectional survey was conducted between October 2021 and April 2022 among specialists treating individuals with T2D. A scientific committee designed a data collection form covering demographics, cardiovascular risk, glucose control metrics, ongoing therapies, and physician judgments on treatment appropriateness. Participants completed anonymous patient questionnaires reflecting routine clinical encounters. The preferred therapeutic regimen for each patient was also identified. Results: The analysis was conducted on 4449 patients initiating oral semaglutide. The population had a relatively short disease duration (42%  60% of patients, and more often than sitagliptin or empagliflozin. Conclusion: The study supports the potential of early implementation of oral semaglutide as a strategy to overcome therapeutic inertia and enhance T2D management

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening