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Background/Aim: COVID-19 is rapidly spreading, and due to the high morbidity and mortality caused by the pandemic many Governments have introduced social restrictions. Those measures combined with infection-related patient anxiety, led to hiding other diseases. The aim of this study was to evaluate the impact of COVID-19 on numbers and severity of acute appendicitis cases referred during the pandemic. Patients and Methods: Between March 2019 and March 2021, all patients who underwent appendectomy in Tor Vergata Hospital, Rome were included. Patients were divided in two groups (COVID-19/pre-COVID-19). Clinical features, intraoperative findings, hospital stay, and histologic examination data were included in the retrospective analysis. Results: Out of 334 admitted patients, 36 (10.7%) had a diagnosis of acute appendicitis (COVID-19 group) vs. 59(11.2%) in the pre-COVID-19 group. The COVID-19 group presented significantly longer hospitalization, incidence of appendicular abscess, perforation, and severity of inflammation at univariate analysis p=0.002, p=0.021, p=0.001, p=0.006, p=0.001, respectively. At multivariate analysis, appendicular abscess (p=0.015) and higher serum levels of C reactive protein (p

BACKGROUND/AIM: Extraordinary restrictions aimed to limit Sars-CoV-2 spreading; they imposed a total reorganization of the health-system. Oncological treatments experienced a significant slowdown. The aim of our multicentric retrospective study was to evaluate screening suspension and surgical treatment delay during COVID-19 and the impact on breast cancer presentation. PATIENTS AND METHODS: All patients who underwent breast surgery from March 11, 2020 to May 30, 2020 were evaluated and considered as the Lockdown group. These patients were compared with similar patients of the previous year, the Pre-Lockdown group. RESULTS: A total of 432 patients were evaluated; n=223 and n=209 in the Lockdown and Pre-lockdown-groups, respectively. At univariate analysis, waiting times, lymph-nodes involvement and cancer grading, showed a statistically significant difference (p

Highlights • Oncological treatments experienced a significant slowdown due to COVID-19 pandemic. • Breast cancer management has changed according to scientific recommendations. • Breast cancer patients with simultaneous COVID-19 could receive delayed treatments. • Treatments delay could impact breast cancer staging., Introduction Breast cancer management during COVID-19 pandemic has changed and in case of COVID-19 patients with simultaneous neoplasia, it has been strongly recommended to treat Sars-CoV-2 infection firstly. Presentation of case We reported a case of a 53-years-old women with early breast cancer and simultaneous asymptomatic SARS-CoV-2 infection. According to COVID-19 breast cancer recommendations she underwent hormone neoadjuvant treatment as a bridging therapy for surgery. Six months from the diagnosis, after virus eradication, patient underwent breast surgery. No SARS-CoV-2 RNA was found both in the surgical specimen and sentinel lymph node but micrometastasis were reported. During the last follow-up, the patient was in good clinical condition and started the adjuvant chemotherapy. Discussion COVID-19 outbreak determined the publication of temporary recommendation leading to an extensive use of neoadjuvant chemotherapy in breast cancer patients. Although endocrine therapy is a mainstay in the adjuvant treatment, its role in the neoadjuvant schedule is unclear. Conclusion Upfront awake surgery should be preferred especially in asymptomatic COVID-19 patient with early breast cancer when monitoring of tumor response is not feasible.

Highlights • Solitary brain metastasis of breast cancer in a patient with neurological symptoms as first presentation is a rare complication. • Simultaneously perform a metastasectomy surgery plus right mastectomy, right axillary dissection and immediate breast reconstruction is unusual event. • Successful combined surgical approach in a stage IV de novo breast cancer patient with single site brain metastasis at one year follow-up. • Combined surgical approach offers the opportunity to treat two different oncological urgencies, reducing the unnecessary repeated surgical and anesthesiologic trauma., Introduction Breast cancer is the most common malignancy in woman. Approximately 5–10% of breast cancer occurs as de novo stage IV and some studies have shown that from 10% to 30% of those patients presents Brain Metastasis. Presentation of case In this study, we report a case of solitary brain metastasis of breast cancer in a 63-year-old Italian Caucasian woman with neurological symptoms as first clinical presentation. After the correct diagnosis and multidisciplinary meeting it was decided to simultaneously perform a metastasectomy surgery plus right mastectomy, right axillary dissection and immediate breast reconstruction. In our clinical practice we report a successful combined surgical approach in a stage IV de novo breast cancer patient with single site brain metastasis at one year follow-up. Discussion Metastasectomy plus mastectomy provided neurological control of acute complication of metastatic disease and complete breast cancer local control. One-time operation could be the best option when diagnosis of breast cancer is made thanks to the onset of oncological emergency like intracranial hypertension due to single brain metastasis. Conclusion Combined surgical approach offers the opportunity to treat two different oncological urgencies, reducing the unnecessary repeated surgical and anesthesiologic trauma.

Background/Aim: SARS-CoV-2 pandemic imposed extraordinary restriction measures and a complete reorganization of the Health System. The aim of the study was to evaluate the impact of COVID-19 on emergency surgical department accesses. Patients and Methods: Patients admitted to surgical emergency departments was retrospectively recorded during the Lockdown (March 11, 2020-May 3, 2020) and compared with the same number of days in 2019 and immediately before Lockdown (January 16, 2020-March 10, 2020). Diagnoses, priority levels, modes of patient’s trans-portation, waiting times and outcomes were analysed. Results: During the lockdown phase, we ob-served a reduction in the access to emergency surgical departments of 84.45% and 79.78%, com-pared with the Pre-Lockdown2019 and Pre-Lockdown2020 groups, respectively. Patient’s transportation, hospitalization and patients discharge with indications to an outpatient visit, waiting and total times exhibited a significant difference during the lockdown (p

Background/Aim: Despite the large amount of clinical data available of Coronavirus-19 (COVID-19), not many studies have been conducted about the psychological toll on Health Care Workers (HCWs). Patients and Methods: In this multicentric descriptive study, surveys were distributed among 4 different Breast Cancer Centers (BCC). BCCs were distinguished according to COVID-19 tertiary care hospital (COVID/No-COVID) and district prevalence (DP) (High vs. Low). DASS-21 score, PSS score and demographic data (age, sex, work) were evaluated. Results: A total of 51 HCWs were analyzed in the study. Age, work and sex did not demonstrate statistically significant values. Statistically significant distribution was found between DASS-21-stress score and COVID/No-COVID (p=0.043). No difference was found in the remaining DASS-21 and PSS scores, dividing the HCWs according to COVID-19-hospital and DP. Conclusion: Working in a COVID-19-hospital represents a factor that negatively affects psychosocial well-being. However, DP seems not to affect the psychosocial well-being of BCC HCWs. During the outbreak, psychological support for low risk HCWs should be provided regardless DP.

Energy management is crucial for various activities in the energy sector, such as effective exploitation of energy resources, reliability in supply, energy conservation, and integrated energy systems. In this context, several machine learning and deep learning models have been developed during the last decades focusing on energy demand and renewable energy source (RES) production forecasting. However, most forecasting models are trained using batch learning, ingesting all data to build a model in a static fashion. The main drawback of models trained offline is that they tend to mis-calibrate after launch. In this study, we propose a novel, integrated online (or incremental) learning framework that recognizes the dynamic nature of learning environments in energy-related time-series forecasting problems. The proposed paradigm is applied to the problem of energy forecasting, resulting in the construction of models that dynamically adapt to new patterns of streaming data. The evaluation process is realized using a real use case consisting of an energy demand and a RES production forecasting problem. Experimental results indicate that online learning models outperform offline learning models by 8.6% in the case of energy demand and by 11.9% in the case of RES forecasting in terms of mean absolute error (MAE), highlighting the benefits of incremental learning.

Background/aim Corona virus infection dramatically spread worldwide during 2020 and extraordinary restrictions have been implemented in order to reduce viral transmission. These measures compelled a complete restructuring of the health system, including temporary cancer screening suspension and a significant slow-down in cancer diagnoses and treatments. Case report We report five cases of extremely advanced breast cancer referred to our Department amid the COVID-19 pandemic. These patients exhibited a poor prognosis or worse quality of life due to their oncological disease. Conclusion In our opinion, both the slow-down of diagnosis and treatment of oncological disease and anxiety over COVID-19 influenced this presentation. Moreover, other patients were unable to receive palliative care. Hopefully, these cases will not develop into extremely advanced-stage disease, and we will be able to provide at least the necessary palliative care.

The rapid increase of electric vehicles (EVs) penetration represents an important challenge for the distribution system operator (DSO). The main issues arise not only from an optimal grid expansion planning point of view but also for managing the system in the near future. The paper focuses on a short-term period EV penetration scenario and proposes a mechanism of EV charging sessions rescheduling in order to mitigate grid congestions. The collaboration between three actors, namely the DSO, the fleet manager and the end user, allows the DSO to identify rescheduling programs in order to face overload events, that represent the most important issue for the grid caused by the widespread penetration of EVs. The IEEE 33-bus test system is used to check the potential of the proposed mechanism. Load flow simulations show that more than 50% of congestions are avoided by means of this approach. The promising results constitute a base case for a future work in which the optimal rescheduling program would be investigated.

Breast reconstruction plays a fundamental role in the therapeutic process of breast cancer treatment and breast implants represents the leading breast reconstruction strategy. Breast Implant Associated-Anaplastic Large Cell Lymphoma (BIA-ALCL), locoregional recurrence in the skin flap, and skin flap necrosis are well-known complications following mastectomy and immediate breast reconstruction (IBR). We report a case of locoregional cancer recurrence in the mastectomy flap mimicking BIA-ALCL, in a patient who underwent 6 breast procedures in four facilities across 15 years including immediate breast reconstruction with macrotextured breast implants. Despite the rate and onset of the disease, clinicians should be aware of BIA-ALCL. Due to the risk of false negative results of fine needle aspiration, clinical suspicion of BIA-ALCL should drive clinicians' choices, aside from cytological results. In the present case, surgical capsulectomy of the abnormal periprosthesic tissue revealed locoregional recurrence.

This paper presents a statistical analysis on producers’ data collected between 2015 and 2020 by the DSO in the city of Terni (Italy). The integration of prosumers with the electrical system is investigated through appropriate indicators, such as self-consumption and self-sufficiency, the case study is placed within the Italian and International scenario and enriched with comments and observations. In particular, effects of Covid-19 pandemic to prosumers’ behaviour are reported, highlighting an increasing of self-consumption by domestic prosumers, in line with the European and national policy.

Patient: Female, 59-year-old Final Diagnosis: Invasive breast carcinomas of no special type (NST) Symptoms: Recurrent hemorrhagic cystic lesion Medication: — Clinical Procedure: — Specialty: Surgery Objective: Challenging differential diagnosis Background: Breast trauma can always have diagnostic pitfalls. In the presence of a recurrent hemorrhagic cysts, cancer should always be suspected. Case Report: A 59-year-old woman noted a palpable mass after breast trauma from falling at home. Radiological exams showed a breast cyst with well-defined margins, with corpuscular and dense fluid components. First, a conservative approach was implemented. One week later, a fine-needle aspiration cytology (FNAC) of the mass showed bloody fluid without atypical cells. Three weeks later, the patient was emergently evaluated due to increased size of the lesion and anemia. To avoid further blood loss and due to suspected malignancy, an urgent surgical excision biopsy was planned. Histopathology revealed a poorly-differentiated carcinoma and the patient was treated with left modified radical mastectomy with axillary dissection. Adjuvant chemotherapy was administered. At 6-month follow-up, the patient was free from recurrences. Conclusions: Recurrent hemorrhagic cysts should always be investigated and considered as a possible cancer lesion. Sonography and cytological exam are the first steps in case of suspicious cysts, but false-negative results are common. In such cases, resection of the cyst should be considered. Immediate resection is valid in cases of diagnostic uncertainty or inability to assess the cyst with imaging or biopsy.

During an extraordinary event, like the COVID19 pandemic, very rapid changes in consumption profiles and customers behaviors were recorded. This paper investigates the impact of the lockdown on load and production in the distribution system of Terni. From a DSO point of view, no relevant issues were encountered to be faced. The distributed power generation from renewable resources did not affect relevant issues, maintaining the typical annual generation profiles. A domestic consumption increase was replaced by more relevant decrease of industrial processes and commercial activities absorptions. More than 25,000 domestic users increased their consumptions in April 2020 and the overall consumption of domestic customers in March was 1,05 times higher than the 2015 respectively consumption. The power flows at primary substations reveal a relevant electric demand reduction for each point of connection with the high voltage transmission system; especially bar 1 and 2 of the most relevant Terni primary substation, recorded a 15.3% decrease with respect to March 2019, and a 24.25% decrease with respect to April 2019.

Introduction and importance Atraumatic splenic rupture(ASR) is a rare event with challenging management, due to absence of clinical history of trauma and delayed diagnosis. Current clinical report could provide detailed information regarding clinical presentation and management to physicians. Case presentation A 61 years-old woman underwent percutaneous coronary intervention(PTCA) after ST elevation myocardial infarction(STEMI). In the first day after PTCA epigastric abdominal disconfort was reported, and new PTCA excluded early complication. During hospitalization, due to anemization and hypotension CT scan was performed which revealed ASR with large hemoperitoneum. Emergency surgical splenectomy was performed. Postoperative course was uneventful and patient started 90 mg Ticageclor twice daily in the first post-operative day(POD) plus low molecular weight Heparin and restarted dual antiplatelet therapy(DAPT) the seventh POD. During follow up, patient underwent to assessment of platelet function showing normal level of DAPT inhibition. Due to the lack of pathological aggregation activity, DAPT was maintained. Clinical discussion ASR is mainly linked to oncological, malformative, inflammatory and thromboembolic conditions. Despite anticoagulant and anti-aggregating drug-related ASR has been already described, we report the first case of drug-related ASR as immediate complication of PTCA due to DAPT. After surgery, careful anti-aggregating management was required to balance in stent restenosis and hemorragic risk. Assessment of platelet activity was performed to design a tailored anti-aggregating therapy. Conclusion Drug-related ASR is dangerous complication due to the high mortality rate and misleading symptoms. After major bleeding events, such as drug-related ASR, evaluation of platelet function could provide a tailored DAPT., Highlights • Atraumatic splenic rupture (ASR) is a rare event with misleading symptoms. • Our report describes the first case of ASR as an early complication after stenting. • Aggregation test could support a tailored therapy to avoid further bleeding events.

Over the past few decades, industry and academia have made great strides to improve aspects related with optimal energy management. These include better ways for efficient energy asset management, generating great opportunities for optimization of energy distribution, discomfort minimization, energy production, cost reduction and more. This paper proposes a framework for a multi-objective analysis, acting as a novel tool that offers responses for optimal energy management through a decision support system. The novelty is in the structure of the methodology, since it considers two distinct optimization problems for two actors, consumers and aggregators, with solution being able to completely or partly interact with the other one is in the form of a demand response signal exchange. The overall optimization is formulated by a bi-objective optimization problem for the consumer side, aiming at cost minimization and discomfort reduction, and a single objective optimization problem for the aggregator side aiming at cost minimization. The framework consists of three architectural layers, namely, the consumer, aggregator and decision support system (DSS), forming a tri-layer optimization framework with multiple interacting objects, such as objective functions, variables, constants and constraints. The DSS layer is responsible for decision support by forecasting the day-ahead energy management requirements. The main purpose of this study is to achieve optimal management of energy resources, considering both aggregator and consumer preferences and goals, whilst abiding with real-world system constraints. This is conducted through detailed simulations using real data from a pilot, that is part of Terni Distribution System portfolio.

The increasing amount of power plants connected to the distribution networks is pointing out issues about energy balances of local communities as well as observability and management of the energy flows by the Distribution System Operator. This paper presents a real life Demand Response campaign carried out by the local Distribution System Operator to reduce the Reverse Power Flow caused by the increasing amount of energy produced locally by distributed generators from not programmable energy sources. Innovative near-real time smart meters and advanced software developed under the Nobel GRID and the WiseGRID projects were used for the trial. Furthermore, these findings and actual data have been used for running simulations at the primary substation level for a complete year. The encouraging results obtained, especially when large energy consumers are involved, have shown the effectiveness of these tools and how they can enable the Distribution System Operator to use Demand Response strategies for increasing grid efficiency and control.

The lack of interoperability among IoT platforms has led to a fragmented environment, where the users and society as a whole suffer from lock-ins, lack of privacy, and reduced functionality. This paper presents SOFIE, a solution for federating the existing IoT platforms in an open and secure manner using Distributed Ledger Technologies (DLTs) and without requiring modifications to the IoT platforms, and describes how SOFIE is used to enable two complex real life pilots: food supply chain tracking from field to fork and electricity distribution grid balancing with guided electrical vehicle (EV) charging. SOFIE's main contribution is to provide interoperability between IoT systems while also enabling new functionality and business models., Comment: 5 pages. European Conference on Networking and Communications 2019 (EuCNC 2019)

The innovation proposed by modern grid paradigms forces to create cutting-edge solutions for managing and integrating software microgrid technologies, as well as hardware ones. In this view, the possibility of exploiting the flexibility of the smart actors of the power system is a key aspect for designing both technical and economic smart grid scenarios in a wide range of energy contexts. In this paper, a smart ICT platform for the management of the flexibility provided by the actors of a microgrid is proposed. Its architecture, functionalities and tools are presented and widely discussed, along with its implementation in a real-life demonstrator located in Terni, Italy.

A vast bibliography on nutrient effects on high-density cultures exists, while it has been overlooked that low densities of starving cells are often the rule in natural environments. By means of a novel sensitive β-galactosidase assay, we examined Escherichia coli transitions to minimal media when the cell concentration was 100 to 10,000 cells per ml. As in high-density cultures, the enzyme activity depended on amino acid availability and was subject to catabolite repression and stringent control. In all conditions tested, despite the presence of other nutrient sources, the relationship between β-galactosidase activity and the l -amino acid pool was hyperbolic. The affinity constant when the amino acid pool was the only nutrient source averaged 14 μM after 90 min and increased up to 222 μM after 4.5 h. While investigating the transition from lag phase to exponential phase, we observed that the cells did not enter into starvation mode in the presence of amino acids, even when the nutrient amount was insufficient to support full survival. Based on these premises, the switch from starvation to hunger was investigated in relation to the amino acid pools. A critical range of concentrations at which E. coli linearly synthesized β-galactosidase despite, at the same time, suffering a large decrease in cell viability was then recognized. Since both β-galactosidase production and the dilution rate were reduced by more than half in the absence of leucine, we examined the contribution of leucine to cell recovery capabilities.

KlADH4 is a gene of Kluyveromyces lactis encoding a mitochondrial alcohol dehydrogenase activity, which is specifically induced by ethanol and insensitive to glucose repression. In this work, we report the molecular analysis of UAS E , an element of the KlADH4 promoter which is essential for the induction of KlADH4 in the presence of ethanol. UAS E contains five stress response elements (STREs), which have been found in many genes of Saccharomyces cerevisiae involved in the response of cells to conditions of stress. Whereas KlADH4 is not responsive to stress conditions, the STREs present in UAS E seem to play a key role in the induction of the gene by ethanol, a situation that has not been observed in the related yeast S. cerevisiae . Gel retardation experiments showed that STREs in the KlADH4 promoter can bind factor(s) under non-inducing conditions. Moreover, we observed that the RAP1 binding site present in UAS E binds KlRap1p.

The mammalian transcription activator protein UBF contains five tandemly repeated HMG homology domains which are required for DNA binding. We have used highly purified RNA polymerase I (Pol I) and upstream binding factor (UBF) and investigated whether these two proteins interact in solution. We show by a variety of different experimental approaches, such as immunoprecipitation, glycerol gradient sedimentation, affinity chromatography and protein blotting, that UBF physically associates with Pol I. Mutational analysis reveals that the HMG boxes play an important role in this specific interaction. UBF binds to mouse and yeast Pol I, demonstrating that the interaction of UBF with Pol I has been conserved during evolution. Interestingly, in both species one Pol I-specific subunit (34.5 kDa in yeast and 62 kDa in mouse) was recognized by UBF. No specific interaction was observed with Pol II. Unexpectedly, UBF was found to associate also with a unique subunit of yeast Pol III. This apparent specific interaction of UBF with the two classes of RNA polymerases may reflect functionally important interactions of HMG box-containing transcription factors with the transcriptional apparatus.

This paper proposes an innovative use of the 2nd life Li-ion batteries, enabling "Storage as a service" for enhancing distribution network operations. Two different use cases have been evaluated at the Distribution System Operator (DSO) of the city of Terni (Italy) during the H2020 ELSA project: in the first one, the DSO manages the battery storage system to provide ancillary services (e.g., balance of Reactive Power, primary reserve) in order to increase the power quality and improve of the Low Voltage management efficiency; in the second use case, the batteries are leveraged by the District Energy Manager in order to perform peak shaving and power smoothing, implementing a power profile requested by the DSO. Test results have shown that 2nd life Li-ion batteries are suitable for some services and their usage in the power distribution network is promising for widespread applications. The experimentation on District Energy Manager is being continued under the work of the H2020 eDREAM project.

Recent progress in communication and digital technologies are pushing the ongoing modernization of power systems and energy markets, introducing advanced controls strategies of the energy flows, new actors, and innovative business models. The so-called energy transition is built on a heavy support of ICT technology and software platforms will play a crucial role in power flows monitoring and control. In this paper an innovative, multi-purpose and open source platform called FUSE is presented. The platform design has been conceived taking into account the most relevant needs and requirements from the ongoing modernization of distribution systems. A preliminary test in a real environment is described with a big data analytics tool aimed at clustering measurements of prosumers through smart meters data.