Vulnerability Assessment of Industrial and Agricultural Control Systems within the IoT Framework

Industrial Control Systems (ICS) increasingly rely on Internet of Things (IoT) communication systems to forward information among all their components mainly through wireless channels. The agricultural sector evolved from a manual occupation to a highly technological environment that exploits a wide variety of sensors and automated machines. The evaluation of cybersecurity issues in wireless channels becomes crucial. In this context, a very useful tool to perform vulnerability assessments and penetration testing are Software Defined Radio (SDR). In this work, we highlight the importance of properly evaluating the security level of ICS focusing on the agricultural scenario and propose an SDR-based framework to assess the cybersecurity of these systems. We consider two use cases: an agricultural vehicle that can move autonomously or be remotely managed by an authorised operator through a proper controller; a sensor network deployed in a rural area and composed of Long Range Wide Area Network (LoRaWAN)-based sensors. We show how SDR can be used to perform a wide set of attacks and how to evaluate their potential impact on the considered systems

GenIA, the Genetic Immunology Advisor database for inborn errors of immunity

Background: To date, no publicly accessible platform has captured and synthesized all of the layered dimensions of genotypic, phenotypic, and mechanistic information published in the field of inborn errors of immunity (IEIs). Such a platform would represent the extensive and complex landscape of IEIs and could increase the rate of diagnosis in patients with a suspected IEI, which remains unacceptably low. Objective: Our aim was to create an expertly curated, patient-centered, multidimensional IEI database that enables aggregation and sophisticated data interrogation and promotes involvement from diverse stakeholders across the community. Methods: The database structure was designed following a subject-centered model and written in Structured Query Language (SQL). The web application is written in Hypertext Preprocessor (PHP), Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript. All data stored in the Genetic Immunology Advisor (GenIA) are extracted by manually reviewing published research articles. Results: We completed data collection and curation for 24 pilot genes. Using these data, we have exemplified how GenIA can provide quick access to structured, longitudinal, more thorough, comprehensive, and up-to-date IEI knowledge than do currently existing databases, such as ClinGen, Human Phenotype Ontology (HPO), ClinVar, or Online Mendelian Inheritance in Man (OMIM), with which GenIA intends to dovetail. Conclusions: GenIA strives to accurately capture the extensive genetic, mechanistic, and phenotypic heterogeneity found across IEIs, as well as genetic paradigms and diagnostic pitfalls associated with individual genes and conditions. The IEI community's involvement will help promote GenIA as an enduring resource that supports and improves knowledge sharing, research, diagnosis, and care for patients with genetic immune disease

Electrophysiological and morphological modulation of neuronal-glial network by breast cancer and nontumorigenic mammary cell conditioned medium

: Breast cancer is a significant global health concern, with the overexpression of human epidermal growth factor receptor 2 (HER2/ERBB2) being a driver oncogene in 20%-30% of cases. Indeed, HER2/ERBB2 plays a crucial role in regulating cell growth, differentiation, and survival via a complex signaling network. Overexpression of HER2/ERBB2 is associated with more aggressive behavior and increased risk of brain metastases, which remains a significant clinical challenge for treatment. Recent research has highlighted the role of breast cancer secretomes in promoting tumor progression, including excessive proliferation, immune invasion, and resistance to anti-cancer therapy, and their potential as cancer biomarkers. In this study, we investigated the impact of ERBB2+ breast cancer SKBR-3 cell line compared with MCF10-A mammary non-tumorigenic cell conditioned medium on the electrophysiological activity and morphology of neural networks derived from neurons differentiated from human induced pluripotent stem cells. Our findings provide evidence of active modulation of neuronal-glial networks by SKBR-3 and MCF10-A conditioned medium. These results provide insights into the complex interactions between breast cancer cells and the surrounding microenvironment. Further research is necessary to identify the specific factors within breast cancer conditioned medium that mediate these effects and to develop targeted therapies that disrupt this interaction

Oxidative Stress Induced by Cortisol in Human Platelets

Hypercortisolism is known to affect platelet function. However, few studies have approached the effect of exogenous cortisol on human platelets, and the results obtained are conflicting and unconvincing. In this study, the effect of exogenous cortisol on several parameters indicative of oxidative status in human platelets has been analysed. We have found that cortisol stimulates ROS production, superoxide anion formation, and lipid peroxidation, with these parameters being in strict correlation. In addition, cortisol decreases GSH and membrane SH-group content, evidencing that the hormone potentiates oxidative stress, depleting platelet antioxidant defence. The involvement of src, syk, PI3K, and AKT enzymes in oxidative mechanisms induced by cortisol is shown. The main sources of ROS in cells can include uncontrolled increase of NADPH oxidase activity and uncoupled aerobic respiration during oxidative phosphorylation. Both mechanisms seem to be involved in ROS formation induced by cortisol, as the NADPH oxidase 1 inhibitor 2(trifluoromethyl)phenothiazine, and rotenone and antimycin A, complex I and III inhibitor, respectively, significantly reduce oxidative stress. On the contrary, the NADPH oxidase inhibitor gp91ds-tat, malate and NaCN, complex II and IV inhibitor, respectively, have a minor effect. It is likely that, in human platelets, oxidative stress induced by cortisol can be associated with venous and arterial thrombosis, greatly contributing to cardiovascular diseases

Dynamic analysis and energy management strategies of micro gas turbine systems integrated with mechanical, electrochemical and thermal energy storage devices

The growing concern related to the rise of greenhouse gases in the atmosphere has led to an increase of share of renewable energy sources. Due to their unpredictability and intermittency, new flexible and efficient power systems need to be developed to compensate for this fluctuating power production. In this context, micro gas turbines have high potential for small-scale combined heat and power (CHP) applications considering their fuel flexibility, quick load changes, low maintenance, low vibrations, and high overall efficiency. Furthermore, the combination of micro gas turbines with energy storage systems can further increase the overall system flexibility and the response to rapid load changes. This thesis aims to analyse the integration of micro gas turbines with the following energy storage systems: compressed air energy storage (CAES), chemical energy storage (using hydrogen and ammonia), battery storage, and thermal energy storage. In particular, micro gas turbines integrated with CAES systems and alternative fuels operate in different working conditions compared to their standard conditions. Applications requiring increased mass flow rate at the expander, such as CAES and the use of fuels with low LHV, such as ammonia, can potentially reduce the compressor surge margin. Conversely, sudden composition changes of high LHV fuels, such as hydrogen, can cause temperature peaks, detrimental for the turbine and recuperator life. A validated model of a T100 micro gas turbine is used to analyse transitions between different conditions, identify operational limits and test the control system. Starting from the dynamic constraints defined in the related chapters, in the final part, an optimisation tool for energy management is developed to couple the micro gas turbine with energy storage systems, maximizing the plant profitability and satisfying the local electrical and thermal demands. For the modelling of the CAES system and alternative fuels, the operating constraints obtained from the initial analyses are implemented in the optimisation tool. In addition, a battery and thermal energy storage system are also considered. In the first part, a comprehensive analysis of the T100 combined with a second-generation CAES system showed enhanced efficiency, reduced fuel consumption, reduced thermal power output and increased maximum electrical power output due to the reduction of the rotational speed. The study identified optimal air injection constraints, demonstrating a +3.23% efficiency increase at 80 kW net power with a maximum mass flow rate of 50 g/s. The dynamic analysis exposed potential instabilities issues during air step injections, mitigated by using ramps at a rate of +0.5 (g/s)/s for safe and rapid dynamic mode operation. The second part explored the effects of varying H2-NG and NH3-NG blends on the T100 mGT. Steady-state results showed increased power output with hydrogen or ammonia, notably +6.1 kW for 100% H2 and up to +11.3 kW for 100% NH3. Transient power steps simulations showed surge margin reductions, especially at lower power levels with high concentrations of ammonia, highlighting the need for controlled transitions. Controlled ramps were effective in preventing extreme temperature peaks during fuel composition changes. The final chapter focused on developing an energy scheduler for different plant setups, evaluating four configurations. For a typical day of the month of April of the Savona Campus, the integration of the CAES lead to relative savings of +8.1% and power-to-H2 of +5.3% when surplus electricity was not sold to the grid. Conversely, with the ability to sell excess electricity, CAES and battery energy storage (BES) systems exhibit modest savings of +1.2% and +2.4%, respectively, while the power-to-H2 system failed to provide economic advantages

Prevalence of Non-alcoholic Fatty Liver Disease in Iran: A Systematic Review and Meta-analysis

Background: Non-alcoholic fatty liver disease (NAFLD) has a benign course in several patients; however, a serious form of this disease can turn into liver failure, liver cirrhosis, and hepatocellular carcinoma. Aim: This study aims to estimate the prevalence of NAFLD in Iran. Method: We searched the following databases from January 2000 to December 2022: Scopus, Pubmed/Medline, Embase, Web of Sciences, the Cochrane Library, and Google Scholar also a number of Iranian databases, namely MagIran, SID, and Elmnet. Additionally, the quality of the included studies was evaluated through the Newcastle-Ottawa Scale. We estimated heterogeneity between studies using the I2 statistic. Furthermore, we performed a synthesis of prevalence estimates through the random-effects DerSimonian and Laird model across the included studies with a 95% confidence interval. To assess the publication bias, we also used Egger's test. Results: Thirty-one studies were eligible for inclusion. The overall number of participants in the present study was 41,971. The overall prevalence of NAFLD in Iran was 33% [CI: 27–37%], with I2 = 99.7% (P < 0.01). The prevalence was 35% [CI: 27–43%] and 37% [CI: 27–47%] in males and females, respectively. We used Egger's test, and no significant publication bias was identified in the overall prevalence (P = 0.45). Conclusion: According to the results of this study, the prevalence of NAFLD in Iran is not only high but alsoa growing trend. Effective strategies for changing lifestyles, changing eating habits, and encouraging physical activities among Iranians are recommended. Also, providing screening tests, especially among high-risk groups, has a significant effect on early diagnosis and NAFLD control