Search Results (745)

The SCIAMI International Workshop was held in Chieti, Italy, at University G. d’Annunzio, Chieti-Pescara, from 7 to 8 June 2024. It was organized by Simonetta D’Ercole and was funded by the European Union–Next Generation EU, “MUR-Fondo Promozione e Sviluppo–UdA, SCIAMI, Eco-friendly antimicrobial Strategies to fight Chronic wound Infections Associated with Multidrug resistant pathogens for the development of Innovative medical systems”. This conference report is an abstract collection from different sessions of SCIAMI. Full article

Understanding the distribution of electrical potential within neurons is critical for advancing our comprehension of neuronal signaling and communication. Neurons, the fundamental units of the nervous system, rely on complex electrochemical processes to transmit information. The intricate structure of neurons, especially those with multiple dendrites, plays a crucial role in how these electrical signals are generated, propagated, and integrated. Despite significant progress in neuroscience, accurately modeling the electrical potential within neurons with elaborate dendritic architectures remains a challenge. This article introduces a novel approach to modeling the electrical potential in multi-dendritic neurons using Bessel functions, which offers a more precise and detailed representation of these processes. The proposed method involves solving the electric potential diffusion equation in cylindrical coordinates, a mathematical framework that naturally aligns with the geometry of dendrites. The radial and axial components of the solution are expressed using Bessel functions and sinusoidal functions, respectively. Bessel functions are particularly well-suited for this purpose due to their ability to describe waveforms in cylindrical systems, making them ideal for capturing the spatial variations in electrical potential within the cylindrical shape of dendrites. By leveraging this mathematical approach, we obtain a complete representation of the potential distribution across the neuron, from the soma (cell body) through the dendrites to the synaptic terminals. This model accurately captures the spatial variations of electrical potential in different regions of the neuron, including areas with complex dendritic arborizations, which are branching structures that significantly influence the neuron’s electrical characteristics. Simulation results underscore the effectiveness of this approach in reproducing realistic neuronal behavior. The model successfully mimics the way electrical signals propagate and interact within dendritic structures, providing crucial insights into the underlying mechanisms of signal integration and transmission in neurons. Full article

The climate crisis, combined with the COVID-19 lockdown measures, exacerbated pre-existing psychological conditions among young people experiencing climate anxiety due to a lack of information and a diffuse sense of powerlessness. The current study aimed to find correlations between the health status of a community, the environmental determinants among youths, and how these affect their vision of climate change and their mental health. An exploratory survey was conducted among people aged between 18 and 33 years old from three continents, with a focus on emotional states related to natural disasters occurring in their regions. The online survey consisted of six questions. The pilot phase results showed that more females from India experienced stressful situations related to climate change, and that respondents aged between 18 and 20 years old were more informed about eco-anxiety. Given its growing frequency among young adults, further studies should be conducted to address the problem and create alternatives and coping mechanisms such as climate action. Full article

Transboundary water pollution is a major global challenge as its movement and impacts remain unsurveyed. Monitoring pollution along international borders can reveal some of the pathways by which sewage and chemicals enter water bodies, and can hence advance the implementation of measures to prevent leakages and discharges into international waters. In this paper, we surveyed the impacts of sewage pollution and chemicals along the U.S.–Mexico international border, using Imperial Beach (California) as a main case study. Pollution was primarily attributed to the inflow of contaminated waters from the neighboring city of Tijuana (Mexico), where a malfunctioning wastewater treatment plant and a lack of sewage pipes being upgraded have caused direct leakage and toxic discharges into the Tijuana River. Reported effects from water pollution at the Tijuana River estuary in Imperial Beach include frequent beach closure, damages to coastal ecosystems, negative impacts on the fishery industry, and several effects on the health of beach users and surfers. Hence, the situation requires urgent measures oriented at coastal management at the mouth of the Tijuana River as well as the consistent monitoring and reporting of human health effects linked to beach uses. Full article

The 2nd International Electronic Conference on Clinical Medicine: Chronic Diseases—Current State and Future Trends (ECCM 2024) was organized by MDPI and MDPI Journal of Clinical Medicine and took place online from 13 to 15 November 2024. This conference report is an abstract collection from different sessions of ECCM 2024. Full article

Maternal health is a serious concern for many nations due to a lack of appropriate healthcare facilities, healthcare staff, and late diagnoses of life-threatening diseases. Pregnant women suffer with numerous challenges during the pregnancy and childbirth. Non-communicable diseases, a lack of nutrition in diets, and unawareness of the risks associated with pregnancy are the primary reasons for these challenges. Sometimes these reasons become a direct cause of maternal mortality as well. Awareness of the risks and early detection may contribute to a reduction in maternal deaths during pregnancy and childbirth. Various ICTs have been incorporated into the healthcare industry to diagnose the issue as quickly as is feasible and an appropriate remedy can be initiated to treat diseases. Machine Learning (ML) techniques have the potential to predict the probable risk factors for timely interventions; however, challenge arises when the data are limited and unstructured. The Decision Tree (DT), Naive Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Linear Discriminant Analysis (LDA) algorithms, with 10-fold cross validation, are used in this study. The dataset utilized in this study included both the present and past medical histories and important vitals of pregnant women. With a test score of 98.8%, the Decision Tree (DT) algorithm outperformed other algorithms, according to the results. Based on the predicted result, pregnant women can consult with medical specialists for their consultation to reduce the potential difficulties in the near future. Full article

The growth of the world’s population and the reduction in the average annual global individual carbon footprint are current issues. With the aim of assessing nutritional protein values, we developed a sensitive analytical methodology for the identification and quantification of amino acids. Strategies have been developed to reduce sample complexity and improve detection for analysis by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The method is suitable for the purpose and is a useful tool for protein value assessment, according to the Food and Agriculture Organization of the United Nations. Full article

The World Health Organization has highlighted the substantial impact of viral hepatitis on individuals, healthcare systems, and economies worldwide. This study’s objective is to monitor disease notifications to assess their trends. Data from infectious disease notifications detected in the Marche Region (Italy) were analyzed and entered into the Nuovo Sistema Informativo Sanitario portal between 1 January 2012 and 31 December 2021. In this period, there were 399 confirmed reports, of which 47.9% were for hepatitis A, 26.8% were for hepatitis B, 7% were for hepatitis C, and 18.3% were for hepatitis E; 67.4% of the afflicted individuals were male, and the average age was 43.5 years old. The year with the highest peak was 2017, accounting for 18% of the reports, while the year with the lowest number was 2020, followed by 2021, accounting for 3.8% and 4.5%, respectively. Effective surveillance systems are key to combating the spread of hepatitis and reducing its impact, although they have been affected by the SARS-CoV-2 pandemic, with many cases remaining undetected. Full article

The Autumn Meeting of the British Society for Cardiovascular Research in 2023 was organized by Carolyn Carr, Lisa Heather and Claudia Montes Aparicio at Wadham College at the University of Oxford and was the 50th Anniversary Meeting of the Society. The theme of the meeting was “The impact of dysregulated metabolism on cardiovascular function” and included an early career symposium on “Life in academia and beyond”. The Annual Bernard and Joan Marshall Distinguished Investigator Lecture was given by Professor Doug Lewandowski on “Metabolic flux in the driver’s seat during cardiac health and disease”. This paper presents the abstracts selected for oral and poster presentation. Full article

The Autumn Meeting of the British Society for Cardiovascular Research in 2022 was organized by David Grieve, Lauren Kerrigan, Claire Tonry and Chris Watson and held at the Wellcome-Wolfson Institute for Experimental Medicine, Queen’s University Belfast. The theme of the meeting was ‘Cardiac remodeling—basic mechanisms to clinical management’ and included an early career symposium. The Annual Bernard and Joan Marshall Distinguished Investigator Lecture was given by Professor Merry Lindsey on ‘Extracellular matrix remodeling in heart failure’. This paper presents the abstracts selected for oral and poster presentation. Full article

The Autumn Meeting of the British Society for Cardiovascular Research in 2021 was a virtual meeting organised by Andrew Bond, Anita Thomas, Elisa Avolio, Michele Carrabba, Raimondo Ascione, and Paolo Madeddu of the Bristol Medical School. The theme of the meeting was ‘Tissue engineering and regenerative medicine in cardiovascular disease’ and included an early career symposium. The Annual Bernard and Joan Marshall Distinguished Investigator Lecture was given by Professor Toshiharu Shinoka. This paper presents the abstracts selected for oral and poster presentations. Full article

Soil use and its proper management are key elements of sustainable development. However, given the complexity of the issue, it is necessary to address it using an interdisciplinary approach. The proposed work aims to analyze the consequences, in terms of damage assessment, of two different soil management systems of a cereal crop through the use of Life Cycle Assessment (LCA) methodology. One system follows a traditional approach and the other utilizes a Decision Support System (DSS). The long-term impacts on human health, ecosystems, and resource availability are calculated by employing the ReCiPe 2016 endpoint method. The results show notable reductions in resource use and environmental impacts with DSS, with a 41% decrease in damage to human health, a 24% reduction in ecosystem damage, and a 23% reduction in resource use. Hence, implementing new technologies and new management strategies in agriculture can lead to more sustainable management choices and can avoid long-term burdens compared to a traditional approach. Full article