Purpose Paediatric Type 1 Diabetes (T1D) patients are at greater risk for developing severe hypo and hyperglycaemic events due to poor glycaemic control. To reduce the risk of adverse events, patients need to achieve the best possible glycaemic management through frequent blood glucose monitoring with finger prick or Continuous Glucose Monitoring (CGM) systems. However, several non-invasive techniques have been proposed aiming at exploiting changes in physiological parameters based on glucose levels. The overall objective of this study is to validate an artificial intelligence (AI) based algorithm to detect glycaemic events using ECG signals collected through non-invasive device. Methods This study will enrol T1D paediatric participants who already use CGM. Participants will wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glycaemic measurements driven through ECG variables are the main outcomes. Data collected will be used to design, develop and validate the personalised and generalized classifiers based on a deep learning (DL) AI algorithm, able to automatically detect hypoglycaemic events by using few ECG heartbeats recorded with wearable devices. Results Data collection is expected to be completed approximately by June 2023. It is expected that sufficient data will be collected to develop and validate the AI algorithm. Conclusion This is a validation study that will perform additional tests on a larger diabetes sample population to validate the previous pilot results that were based on four healthy adults, providing evidence on the reliability of the AI algorithm in detecting glycaemic events in paediatric diabetic patients in free-living conditions. Trial registration ClinicalTrials.gov identifier: NCT03936634. Registered on 11 March 2022, retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT05278143?titles=AI+for+Glycemic+Events+Detection+Via+ECG+in+a+Pediatric+Population&draw=2&rank=1 .

Artemisia annua L. has long been known for its medicinal properties and isolation of ingredients whose derivatives are used for therapeutic purposes. The CYP2B6 and CYP3A4 enzymes belong to a large family of cytochrome P450 enzymes. These enzymes are involved in the metabolism of drugs and other xeonobiotics. It is known that various compounds can induce or inhibit the activity of these enzymes. The aim of this study was to investigate the nature of the inhibitory effect of Artemisia annua extract on CYP2B6 and CYP3A4 enzymes, as well as the type of inhibition, the presence of reversible or pseudo-irreversible inhibition, and the possible heme destruction. The methanolic extract of Artemisia annua showed an inhibitory effect on CYP2B6 (by almost 90%) and CYP3A4 enzymes (by almost 70%). A significant decrease in heme concentration by 46.8% and 38.2% was observed in different assays. These results clearly indicate that the studied plant extracts significantly inhibited the activity of CYP2B6 and CYP3A4 enzymes. Moreover, they showed irreversible inhibition, which is even more important for possible interactions with drugs and dietary supplements.

With the goal of enhancing the quality of the environment, urban green infrastructure (UGI) is an essential element in sustainable cities, and nature-based solutions (NBS) are being carried out as new infrastructure solutions that increase the resilience of cities. In this research, the method of theoretical analysis and the content analysis as the basic fact-gathering technique was applied to answer to following questions: What are the hindrances and bottlenecks in implementing NBS? Are the current decision-making mechanisms helping NBS get in route to shape cities? Is there any binding policy in practice that promotes NBS? In Belgrade is planned Type 3 of the degree of intervention/level and engineering type—Creation and new ecosystem management in the classifications of intensive urban green space management; urban planning strategies; urban water management; ecological restoration of degraded terrestrial ecosystems; and restoration and creation of semi-natural water bodies and hydrographic networks. In the future, it is essential to implement policies and incentives on national, regional, and local scales that help encourage the usage of NBS in the development of urban infrastructure.

Additive manufacturing (AM) or industrial 3D printing uses cutting-edge technologies and materials to produce a variety of complex products. However, the effects of the unintentionally emitted AM (nano)particles (AMPs) on human cells following inhalation, require further investigations. The physicochemical characterization of the AMPs, extracted from the filter of a Laser Powder Bed Fusion (L-PBF) 3D printer of iron-based materials, disclosed their complexity, in terms of size, shape, and chemistry. Cell Painting, a high-content screening (HCS) assay, was used to detect the subtle morphological changes elicited by the AMPs at the single cell resolution. The profiling of the cell morphological phenotypes, disclosed prominent concentration-dependent effects on the cytoskeleton, mitochondria, and the membranous structures of the cell. Furthermore, lipidomics confirmed that the AMPs induced the extensive membrane remodeling in the lung epithelial and macrophage co-culture cell model. To further elucidate the biological mechanisms of action, the targeted metabolomics unveiled several inflammation-related metabolites regulating the cell response to the AMP exposure. Overall, the AMP exposure led to the internalization, oxidative stress, cytoskeleton disruption, mitochondrial activation, membrane remodeling, and metabolic reprogramming of the lung epithelial cells and macrophages. We propose the approach of integrating Cell Painting with metabolomics and lipidomics, as an advanced nanosafety methodology, increasing the ability to capture the cellular and molecular phenotypes and the relevant biological mechanisms to the (nano)particle exposure.

Objective: Romania began its COVID-19 immunization programme with approved vaccinations in three stages, as follows: The first step of vaccination is for health and social professionals, the second stage is for high-risk persons and the third stage is for the remainder of the general public. This study aims at assessment of knowledge, attitude and practice towards COVID-19 and vaccination against COVID-19 in the Romanian population during the third wave of the pandemic. Methods: This cross-sectional study was based on a Bosnian and Herzegovinian study on COVID-19 vaccination during the country’s third wave of COVID-19 pandemic. Results: Our study sample, dominantly female (629; 61.0%), with a bachelor’s degree (734; 71.2%), either single (539; 52.3%) or in a relationship (363; 35.2%), engaged in intellectual labour (910; 88.3%) and living in an urban environment (874; 84.8%) with a mean age of 25.07 ± 8.21 years, 294 (28.5%) people with COVID-19 symptoms and 86 (8.3%) were tested COVID-19 positive, had a mean knowledge score of 16.38 ± 4.0 with correct answer rates on questions ranging from 30.1% to 88.2%. Being single (odds ratio = 3.92, p = 0.029) or in a relationship (odds ratio = 3.79, p = 0.034), having a bachelor’s degree and higher (odds ratio = 1.61, p = 0.006) and being COVID-19 tested (odds ratio = 1.82, p < 0.001) were associated with higher knowledge test scores. Our sample had relatively optimistic attitudes towards final COVID-19 disease containment (712; 69.1%) and vaccination programmes (679; 65.9%). The majority of the sample followed socio-epidemiological measures and did not visit places of mass social gatherings (666; 64.1%) and wore masks (992; 95.7%) while being outside their home. In terms of vaccination rates, 382 (37.0%) of the individuals were presently immunized against COVID-19. Higher knowledge test scores (>15 points) (odds ratio = 1.66, p = 0.002) and positive attitudes of this study (odds ratio = 1.59, p = 0.001, odds ratio = 4.16, p < 0.001) were identified as independent predictors for vaccinating against COVID-19. Conclusion: Romanian citizens have had good knowledge, optimistic attitudes and appropriate practices towards COVID-19 vaccination during the third wave of COVID-19 outbreak in the country. Higher knowledge regarding the disease and vaccination against it not only increased attitudes towards the end of the pandemic, but also increased the willingness to be vaccinated and to avoid infection risk factors.

Abstract The use of multi-criteria decision-making (MCDM) methods to select the most appropriate one from a range of alternatives considering multiple criteria is a suitable methodology for making informed decisions. When constructing a decision or objective matrix (DOM) for MCDM procedure, either crisp numerical values or fuzzy linguistic terms can be used. A review of relevant literature indicates that decision experts often prefer to give linguistic terms (instead of crisp numerical values) based on their domain knowledge, to establish a fuzzy DOM. However, previous research articles have not adequately studied the selection between fuzzy and crisp DOM in MCDM, especially under the context of assessing the financial performance (FP) of listed firms – a notably complex decision-making problem. As such, the primary motivation of this study is to bridge this research gap through comparative analyses of fuzzy and crisp DOM in MCDM. Along this path, and in order to handle fuzzy DOM, this work also proposes two new fuzzy MCDM methods: fuzzy preference ranking on the basis of ideal-average distance (PROBID) and fuzzy sPROBID (simpler PROBID), extending the applicability of the original crisp PROBID and sPROBID methods. Moreover, for the first time in the literature, this work compares the FP rankings obtained using fuzzy MCDM methods with an objective benchmark we have identified, i.e., the real-life stock return (SR)-based ranking. The case study of ranking the FP of 32 listed firms demonstrates that the fuzzy MCDM methods produce higher correlation results with the SR-based ranking. The results also suggest that the proposed fuzzy sPROBID method with triangular fuzzy DOM performs the best for assessing the FP of firms in terms of Spearman’s rank correlation coefficient with the SR-based ranking. Overall, the contributions of this work are three-fold: first, it proposes two new fuzzy MCDM methods (i.e., fuzzy PROBID and fuzzy sPROBID); second, it advances the application of fuzzy MCDM methods in assessing and ranking the FP of listed firms to make rational investment decisions in the financial market; third, it studies the selection between fuzzy and crisp DOM through comparisons with an objective benchmark.

High-throughput sequencing provides sufficient means for determining genotypes of clinically important pharmacogenes that can be used to tailor medical decisions to individual patients. However, pharmacogene genotyping, also known as star-allele calling, is a challenging problem that requires accurate copy number calling, structural variation identification, variant calling, and phasing within each pharmacogene copy present in the sample. Here we introduce Aldy 4, a fast and efficient tool for genotyping pharmacogenes that uses combinatorial optimization for accurate star-allele calling across different sequencing technologies. Aldy 4 adds support for long reads and uses a novel phasing model and improved copy number and variant calling models. We compare Aldy 4 against the current state-of-the-art star-allele callers on a large and diverse set of samples and genes sequenced by various sequencing technologies, such as whole-genome and targeted Illumina sequencing, barcoded 10x Genomics, and Pacific Biosciences (PacBio) HiFi. We show that Aldy 4 is the most accurate star-allele caller with near-perfect accuracy in all evaluated contexts, and hope that Aldy remains an invaluable tool in the clinical toolbox even with the advent of long-read sequencing technologies.

Background: Response to the outbreak of poliomyelitis in mid-1950 led to recognition and consequent development of critical care. Seventy years later the humankind was struck by COVID-19, another major challenge for critical care medicine which was especially big in Low-Resources-Settings where more than two thirds of the world population live, including the population of the Republic of Srpska (RS). Design and methods: The main aim was to show an overview of all interventions in order to boost hospitals’ capacities to the level which is sufficient to manage high amount of critically ill COVID-19 patients in the RS. A before-after cohort study design was conducted to evaluate the effects of interventions for increase in preparedness and capacity of ICUs for admission and treatment of COVID-19 critically ill patients in nine hospitals in the RS. Results: Following interventions, the biggest and university affiliated hospital in the RS has increased ICU capacities: total number of ICU beds increased by 38% and number of ventilators by 114%. Availability of machines for veno-venous extracorporeal membrane oxygenation (vvECMO) increased by 100%. Number of doctors who were involved in treatment of critically ill patients increased by 47% and nurse/patient’s ratio reached 1:2.5. Similarly, all other hospitals experienced boosting of ICU beds by 189% and ventilators by 373% while number of doctors increased by 108% and nurse/patient’s ratio reached 1:4. Conclusion: All interventions implemented during COVID-19 pandemic outbreak in the RS resulted in increasing capacity for treatment of critically ill patients, but the education of health care professionals was identified as the most important conducted intervention.

With no expected vaccine for HIV in the near future, we aimed to define the current situation and challenges for pre- and post-exposure prophylaxis (PrEP and PEP) in Central and Eastern Europe (CEE). The Euroguidelines CEE Network Group members were invited to respond to a 27-item survey including questions on PrEP (response rate 91.6%). PrEP was licensed in 68.2%; 95 centers offered PrEP and the estimated number on PrEP was around 9000. It was available in daily (40.1%), on-demand (13.3%), or both forms (33.3%). The access rate was <1–80%. Three major barriers for access were lack of knowledge/awareness among people who are in need (59.1%), not being reimbursed (50.0%), and low perception of HIV risk (45.5%). Non-occupational PEP was available in 86.4% and was recommended in the guidelines in 54.5%. It was fully reimbursed in 36.4%, only for accidental exposures in 40.9%, and was not reimbursed in 22.72%. Occupational PEP was available in 95.5% and was reimbursed fully. Although PrEP scale-up in the region has gained momentum, a huge gap exists between those who are in need of and those who can access PrEP. Prompt action is required to address the urgent need for PrEP scale-up in the CEE region.