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The Former Yugoslav Republic of Macedonia is a country with huge interest in accession to the great family of the European Union, which now counts about 500 million people. The paper aims to explain this interest and to give detailed arguments to all the expectations, by focusing on the process of accession of the country to the European Union and giving examples of other countries‘ similar efforts from wider region. This process represents the culmination of more than two decades of economic, social and political transformation of the country. The membership in the European Union, according to the theoretical knowledge and comparative experience, should bring convenience for Macedonia and its citizens, including prosperity, more intensive relations with its European neighbours and contribution to shaping the political, social and economic development of Europe. The accession process is long and difficult, partly because of the necessity to adopt many laws and regulations of the European Union for new member states, contained in the Acquis communautaire.

Contamination by heavy metals is one of the major threats to soil and water as well as human health. Much attention is being paid to metal-accumulating plants that may be used for the phytoremediation of contaminated soils. Some plants can accumulate remarkable levels of metals, 100-1000-fold the levels normally accumulated in most species. This study evaluated the potential of mercury accumulation of 17 plant species growing on contaminated sites in the ex-industrial area of the PVC Factory, Vlora, Albania. Plant roots, shoots and soil samples were collected and analyzed for the selected metal concentration values. The biological accumulation coefficient (BAC) was calculated to evaluate the potential use of plant species for phytoremediation purposes. The concentration of Hg in soils inside the contaminated area varied from 45-301 mg/kg-1. The concentration of Hg in plant shoots and roots varied from 0.1 to 12.9 mg/kg-1 and 0.1 to 4.2 mg/kg-1, respectively. Species Medicago sativa L. and Dittrichia viscosa (L.) W. Greuter were found to be the most suitable plants for phytoremediation of the site contaminated with mercury (BAC values varied from 30-10 percent, respectively). Considering the BAC values, none of the plant species was found to be a hyperaccumulator; however, plants with high BCF (metal concentration ratio of plant root to soil) and low BTC (metal concentration ratio of plant shoots to roots) have the potential for phytostabilization and phytoextraction. The results of this study can be used for the management and decontamination of soils with mercury using plant species having phytoremediation potential/characteristics.

Basil is an important medicinal and aromatic plant. This paper presents quantitative and qualitative analyses of the essential oils obtained from an autochthon cultivar of Ocimum basilicum L. and two other Italian cultivars, O. basilicum L. cv. purple and O. basilicum L green basil with wide leaves .In the volatile oil of O. basilicum L. cv. with green wide leaves, twelve components were characterized, representing 90% of the total oil, of which linalool (45.3 %) and eugenol (42.06 %) were the major components. In the volatile oil of O. basilicum L. cv. purple, nine components were characterized representing 90% of the total oil, of which farnesene (14.94%), elemol (11.29%) and carvacrol (9%) were the major components. In the O. basilicum L. cv. (autochthon) cultivar with green narrow leaves, twelve components were characterized representing 90% of the total oil, with. Linalool (48 %) and eugenol (36.09 %) as the major components. Linalool (Raguso et. al., 1999) is the dominant constituent in the two cultivars; There was no big difference between the two green cultivars with different leaf morphology in their oil content. These results suggest that further research to improve the quality of the essential oil content is necessary.

This paper analyses monthly price persistence in the EU27 countries over the period 2010–2022 using a fractional integration framework, where the measure of persistence is the fractional differencing parameter d. In addition to full sample estimates, subsample and recursive ones are obtained to examine time variation. On the whole, the results provide clear evidence that both the exogenous shocks considered (namely, the COVID-19 pandemic and the Russia-Ukraine war) have generally increased price persistence in the EU27 (despite their heterogeneity), although the recursive estimates suggest that their impact might have peaked and might now be decreasing. Therefore, any policies adopted to counteract those shocks should be gradually phased out. The exceptions are the Southern European countries, where price persistence appears to have decreased, though in Italy the recursive analysis indicates that it is now rising sharply.

Since previous studies, mostly performed in healthy adults, show that sleep restriction around time of vaccination impairs antibody response and shift work affects sleep, aim of the study was to test the hypothesis that the antibody response to vaccination is impaired in shift workers, when compared to non-shift workers.Employees (n = 445; mean age 44 ± 11 years; 35 % men) of the Centro Cardiologico Monzino, IRCCS (Milan, Italy) were vaccinated against SARS-CoV2 in February 2021 with an mRNA-based vaccine. Antibody titers were assayed 1 and 7 months later. Differences between groups were assessed using ANOVA, after log-transformation of variables with right-skewed distribution.We report that the antibody titer was significantly higher in shift workers (33 % of employees) compared to non-shift workers at first assay [median (IQR): 2495 (1700; 4665) vs 2060 (1619; 2970) BAU/mL, p = 0.0123], as well as at the second one, and that this difference was abolished after adjustment for previous development of symptomatic COVID-19. Results were not affected by age or sex at birth.These results show that shift workers were able to mount an unimpaired antibody response to vaccination. Since vaccinations were performed during the pandemic urgency, our retrospective study has several limitations, nevertheless it underlines the need for large prospective, controlled studies on the effects of acute and chronic sleep restriction on response to vaccination in the general population and on the impact of shift work on immune response.

PurposeThe ability to generate natural killer (NK) cells from induced pluripotent stem cells (iPSCs) has given rise to new possibilities for the large-scale production of homogeneous immunotherapeutic cellular products and opened new avenues towards the creation of “off-the-shelf” cancer immunotherapies. However, the differentiation of NK cells from iPSCs remains poorly understood, particularly regarding the ontogenic landscape of iPSC-derived NK (iNK) cells produced in vitro and the influence that the differentiation strategy employed may have on the iNK profile. MethodsTo investigate this question, we conducted a comparative analysis of two sets of iNK cells generated from the same iPSC line using two different protocols: (i) a short-term, clinically compatible feeder-free protocol corresponding to primitive hematopoiesis, and (ii) a lymphoid-based protocol representing the definitive hematopoietic step. Results and discussionOur work demonstrated that both protocols are capable of producing functional iNK cells. However, the two sets of resulting iNKs exhibited distinct phenotypes and transcriptomic profiles. The lymphoid-based differentiation approach generated iNKs with a more mature and activated profile, which demonstrated higher cytotoxicity against cancer cell lines compared to iNK cells produced under short-term feeder-free conditions suggesting that the differentiation strategy must be considered when designing iNK cell–based adoptive immunotherapies.

The national or local lockdowns in response to COVID-19 forced education systems to rapidly shift from in-person to distance learning. The hasty transition undoubtedly imposed tremendous challenges on teachers, students and distance learning infrastructure. The purpose of this study was to investigate how high school science teachers who had previously been trained in flipped-learning and advanced educational technology through the Science Teaching Excites Medical Interest (STEMI) program perceived their transition to distance learning during this pandemic. In this study eleven teachers were interviewed with a semi-structured interview guide. Data were analyzed using the deductive-inductive content analytic approach. Our results indicated that teachers reported having more confidence in using technology for teaching online due in part to their participation in the STEMI program. They also reported internet access as one of the most significant barriers, both for students and teachers. While some teachers thought that students may feel more in control of learning due to absence of time and place limits with distance learning, others may struggle to stay engaged without the classroom support they would normally have received. Teachers generally experienced increased workloads and harder work--life balance with online teaching. In spite of the unforeseen challenges, the pandemic situation afforded teachers with opportunities to adopt different technology in teaching and foresee the need for technology integration in order to better prepare for the unexpected in the future.

Considering the impact of pandemic condition on mental health and functioning in daily life, the main purpose of this study was to investigate the relationship between Big Five personality traits, coping strategies and emotional problems such as symptoms of depression and anxiety, during the COVID-19 pandemic period. Specifically, the purpose of this study is to create a model of the impact of coping strategies as mediating factors in the relationship between Big Five personality traits personality traits and emotional problems. For the purposes of this study, a sample of 200 Kosovar respondents was used, where the age of the participants varies from 18 to 54 years. As a result of the pandemic situation created, the method of data collection for this study was done in the form of self-reporting, divided into physical questionnaires and online ones. The BFI Personality Inventory is used to classify Big Five personality traits, the Coping Control Checklist (WCCL) to classify coping strategies, and the Adult Self-Reporting Questionnaire (ASR) used to identify emotional problems. The analysis of the results in this study was done by means of the statistical package of SPSS and R program. After the analysis, it is seen that there is a significant correlation between Big Five personality traits (extraversion and neuroticism) and coping strategies (seeking social support and avoidance), as well as there is a correlation between Big Five personality traits (compliance and neuroticism) and emotional problems (symptoms of anxiety and depression). An association was also found between coping strategies (avoidance) and emotional problems (anxiety symptoms). As for gender differences in experiencing anxiety and depression symptoms and using desired thoughts as coping strategies, it was found that women are more predisposed to experience anxiety symptoms and use desired thoughts than men. The findings highlighted the part that coping strategies are significant mediator factors in the relationship between Big Five personality traits and emotional problems., Author(s): Donjeta Gashi [sup.1] , Florim Gallopeni [sup.1] , Greta Imeri [sup.1] , Mimoza Shahini [sup.2] , Shegë Bahtiri [sup.1] [sup.3] Author Affiliations: (1) Heimerer College, , Prishtina, Kosovo (2) [...]

The subject of the research refers to the aspect of digital forensics and computer crime and the latter is one of the reasons for the evolution of crime in general. Based on the growing trend of technology development and the increase in the number of digital crimes, a special emphasis is given to the statistical aspect of computer crime as well as measures to reduce the impact of computer crime, including the ethical and legal aspects in the Republic of North Macedonia (RNM).

Abstract Background The covid-19 pandemic has highlighted the role of living systematic reviews. The speed of evidence generated during the covid-19 pandemic accentuated the challenges of managing high volumes of research literature. Methods In this article, we summarise the characteristics of ongoing living systematic reviews on covid-19, and we follow a life cycle approach to describe key steps in a living systematic review. Results We identified 97 living systematic reviews on covid-19, published up to 7th November 2022, which focused mostly on the effects of pharmacological interventions (n = 46, 47%) or the prevalence of associated conditions or risk factors (n = 30, 31%). The scopes of several reviews overlapped considerably. Most living systematic reviews included both observational and randomised study designs (n = 45, 46%). Only one-third of the reviews has been updated at least once (n = 34, 35%). We address practical aspects of living systematic reviews including how to judge whether to start a living systematic review, methods for study identification and selection, data extraction and evaluation, and give recommendations at each step, drawing from our own experience. We also discuss when it is time to stop and how to publish updates. Conclusions Methods to improve the efficiency of searching, study selection, and data extraction using machine learning technologies are being developed, their performance and applicability, particularly for reviews based on observational study designs should improve, and ways of publishing living systematic reviews and their updates will continue to evolve. Finally, knowing when to end a living systematic review is as important as knowing when to start.

During the last two decades, the introduction of tyrosine kinase inhibitors (TKIs) to the therapy has changed the natural history of CML but progression into accelerated and blast phase (AP/BP) occurs in 3-5% of cases, especially in patients resistant to several lines of TKIs. In TKI-refractory patients in advanced phases, the only curative option is hematopoietic stem cell transplantation. We and others have shown the relevance of the expression of the Interleukin-2-Receptor α subunit (IL2RA/CD25) as a biomarker of CML progression, suggesting its potential use as a therapeutic target for CAR-based therapies. Here we show the development of a CAR-NK therapy model able to target efficiently a blast crisis cell line (K562). The design of the CAR was based on the scFv of the clinically approved anti-CD25 monoclonal antibody (Basiliximab). The CAR construct was integrated into NK92 cells resulting in the generation of CD25 CAR-NK92 cells. Target K562 cells were engineered by lentiviral gene transfer of CD25. In vitro functionality experiments and in vivo leukemogenicity experiments in NSG mice transplanted by K562-CD25 cells showed the efficacy and specificity of this strategy. These proof-of-concept studies could represent a first step for further development of this technology in refractory/relapsed (R/R) CML patients in BP as well as in R/R acute myeloblastic leukemias (AML).

Abstract Background The COVID-19 pandemic has led to an unprecedented amount of scientific publications, growing at a pace never seen before. Multiple living systematic reviews have been developed to assist professionals with up-to-date and trustworthy health information, but it is increasingly challenging for systematic reviewers to keep up with the evidence in electronic databases. We aimed to investigate deep learning-based machine learning algorithms to classify COVID-19-related publications to help scale up the epidemiological curation process. Methods In this retrospective study, five different pre-trained deep learning-based language models were fine-tuned on a dataset of 6365 publications manually classified into two classes, three subclasses, and 22 sub-subclasses relevant for epidemiological triage purposes. In a k-fold cross-validation setting, each standalone model was assessed on a classification task and compared against an ensemble, which takes the standalone model predictions as input and uses different strategies to infer the optimal article class. A ranking task was also considered, in which the model outputs a ranked list of sub-subclasses associated with the article. Results The ensemble model significantly outperformed the standalone classifiers, achieving a F1-score of 89.2 at the class level of the classification task. The difference between the standalone and ensemble models increases at the sub-subclass level, where the ensemble reaches a micro F1-score of 70% against 67% for the best-performing standalone model. For the ranking task, the ensemble obtained the highest recall@3, with a performance of 89%. Using an unanimity voting rule, the ensemble can provide predictions with higher confidence on a subset of the data, achieving detection of original papers with a F1-score up to 97% on a subset of 80% of the collection instead of 93% on the whole dataset. Conclusion This study shows the potential of using deep learning language models to perform triage of COVID-19 references efficiently and support epidemiological curation and review. The ensemble consistently and significantly outperforms any standalone model. Fine-tuning the voting strategy thresholds is an interesting alternative to annotate a subset with higher predictive confidence.

Abstract Optical interferometry-based techniques are ubiquitous in various measurement, imaging, calibration, metrological, and astronomical applications. Repeatability, simplicity, and reliability of measurements have ensured that interferometry in its various forms remains popular—and in fact continues to grow—in almost every branch of measurement science. In this paper, we propose a novel actively-controlled optical interferometer in the Twyman–Green configuration. The active beam control within the interferometer is a result of using an actively-controlled tunable focus lens in the sample arm of the interferometer. This innovation allows us to characterize transparent samples cut in the cubical geometry without the need for bulk mechanical motion within the interferometer. Unlike thickness/refractive index measurements with conventional Twyman–Green interferometers, the actively-tunable interferometer enables bulk-motion free thickness or refractive index sample measurements. With experimental demonstrations, we show excellent results for various samples that we characterized. The elimination of bulk motion from the measurement process promises to enable miniaturization of actively-tunable Twyman–Green interferometers for various applications.

AbstractThis paper examines tourism persistence in a group of Southeastern European (SEE) countries (Albania, Bosnia, Bulgaria, Croatia, Montenegro, North Macedonia, Serbia and Slovenia) by applying fractional integration methods to monthly data on foreign tourist arrivals and overnight stays. The results indicate that the COVID-19 pandemic has increased the degree of persistence of these series as measured by the fractional differencing parameter; specifically, it has removed the mean reversion property in some countries. In addition, it has reduced the importance of the seasonal component.