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Abstract The complex dynamics of protein expression in plasma during hyperacute HIV-1 infection and its relation to acute retroviral syndrome, viral control, and disease progression are largely unknown. Here, we quantify 1293 blood plasma proteins from 157 longitudinally linked plasma samples collected before, during, and after hyperacute HIV-1 infection of 54 participants from four sub-Saharan African countries. Six distinct longitudinal expression profiles are identified, of which four demonstrate a consistent decrease in protein levels following HIV-1 infection. Proteins involved in inflammatory responses, immune regulation, and cell motility are significantly altered during the transition from pre-infection to one month post-infection. Specifically, decreased ZYX and SCGB1A1 levels, and increased LILRA3 levels are associated with increased risk of acute retroviral syndrome; increased NAPA and RAN levels, and decreased ITIH4 levels with viral control; and increased HPN, PRKCB, and ITGB3 levels with increased risk of disease progression. Overall, this study provides insight into early host responses in hyperacute HIV-1 infection, and present potential biomarkers and mechanisms linked to HIV-1 disease progression and viral load.

Hepatocellular carcinoma (HCC) is a challenging cancer with high mortality rates, limited predictability, and a lack of effective prognostic indicators. The relationship between small nucleolar RNAs (snoRNAs) and HCC is poorly understood. Based on the literature data, snoRNA studies were primarily focused on viral-related causes of HCC, such as Hepatitis B or C viruses (HBV or HCV). According to these studies, we selected four snoRNAs (snoRA12, snoRA47, snoRA80E, and snoRD126) for exploration in the context of non-viral-related causes, including non-alcoholic steatohepatitis (NASH), non-alcoholic fatty liver diseases (NAFLD), and alcohol steatohepatitis. The primary goal of this study was to gain a deeper understanding of how snoRNA expression affects patient outcomes and whether it can serve as a prognostic tool for non-viral HCC. We conducted a study on tissue samples from 35 HCC patients who had undergone resection at Pilsen University Hospital. SnoRA12, snoRA47, snoRA80E, and snoRD126 were studied by quantitative real-time PCR (qRT-PCR) in tumor and non-tumor adjacent tissue (NTAT) samples. Kaplan-Meier analysis was performed to assess the association of snoRNAs expression levels with patient outcomes: time to recurrence (TTR), disease-free survival (DFS) and overall survival (OS). In tumor tissues, snoRA12, snoRA47 and snoRA80E were upregulated, while snoRD-126 was downregulated compared to NTAT. Low expression of snoRA47 and snoRD126 in patients was associated with longer TTR and DFS. The individual expression of snoRA12 and snoRA80E did not show associations with TTR and DFS. However, a combination of medium expression of snoRD126 and snoRA80E was associated with longer TTR and DFS, while high and low expressions of the combined snoRA126 and snoRA80E showed no significant association with TTR, DFS, and OS. Conversely, a combination of high expression of snoRA12 and snoRD126 was associated with shorter TTR. In conclusion, the results indicate that snoRA47 and snoRD126 exhibit good prognostic power specifically for non-viral related HCC. Both snoRA47 and snoRD126 showed favorable prognostication in single and combined analysis when assessing patient outcomes. Also, in combination analysis, snoRA80E and snoRA12 showed favorable prognosis, but not alone.

Abstract A genomic database of all Earth’s eukaryotic species could contribute to many scientific discoveries; however, only a tiny fraction of species have genomic information available. In 2018, scientists across the world united under the Earth BioGenome Project (EBP), aiming to produce a database of high-quality reference genomes containing all ~1.5 million recognized eukaryotic species. As the European node of the EBP, the European Reference Genome Atlas (ERGA) sought to implement a new decentralised, equitable and inclusive model for producing reference genomes. For this, ERGA launched a Pilot Project establishing the first distributed reference genome production infrastructure and testing it on 98 eukaryotic species from 33 European countries. Here we outline the infrastructure and explore its effectiveness for scaling high-quality reference genome production, whilst considering equity and inclusion. The outcomes and lessons learned provide a solid foundation for ERGA while offering key learnings to other transnational, national genomic resource projects and the EBP.

This study aims to investigate the clinical, endoscopic, biologic and histopathological differences between Helicobacter pylori-associated and autoimmune gastric atrophy.

Abstract Cardiac arrest is a sudden cessation of heart function, leading to an abrupt loss of blood flow and oxygen to vital organs. This life-threatening emergency requires immediate medical intervention and can lead to severe neurological injury or death. Methods and biomarkers to predict neurological outcome are available but lack accuracy. Such methods would allow personalizing healthcare and help clinical decisions. Extensive research has been conducted to identify prognostic omic biomarkers of cardiac arrest. With the emergence of technologies allowing to combine different levels of omics data, and with the help of artificial intelligence and machine learning, there is a potential to use multiomic signatures as prognostic biomarkers after cardiac arrest. This review article delves into the current knowledge of cardiac arrest biomarkers across various omic fields and suggests directions for future research aiming to integrate multiple omics data layers to improve outcome prediction and cardiac arrest patient’s care.

Artificial objects, particularly tunnels used for water transport under pressure, impact the geological and hydrogeological environment to a greater or lesser extent, and it is vital to assess their contributions to groundwater quality. Although tunnels are typically lined with concrete, their interaction with the hydrogeological environment intensifies over time. In this study, the detailed spatiotemporal monitoring of all hydrogeological features within the potential influence zone of the hydraulic tunnel of the Pirot Hydropower Plant has been conducted in order to determine the degree of interaction between the artificial object and the natural environment in real time, and to assess the correlation between monitored parameters. Natural conditions of the environment were defined, as well as potential changes through the observing groundwater regimes. The monitoring network included observations of groundwater regimes at seven springs located in close proximity to the hydraulic tunnel, within the tunnel, at three piezometers, and along the river, while methods employed were hydrological monitoring, physicochemical monitoring, and groundwater piezometer sensing. Cross-correlation analysis has been applied for assessing the impact of precipitation dynamics on the spring discharge regime. The results indicate a direct influence of the tunnel on the hydrogeological environment, proving the consistency and high correlation between the monitored parameters.

Hepatocellular carcinoma (HCC) is primary liver cancer, frequently diagnosed at advanced stages with limited therapeutic options. MicroRNAs (miRNAs) regulate target gene expression and through inhibitory competitive binding of miRNA influence cellular processes including carcinogenesis. Extensive evidence proved that certain miRNA's are specifically expressed in neoplastic tissues of HCC patients and are confirmed as important factors that can participate in the regulation of key signalling pathways in cancer cells. As such, miRNAs have a great potential in the clinical diagnosis and treatment of HCC and can improve the limitations of standard diagnosis and treatment. Long non-coding RNAs (lncRNAs) have a critical role in the development and progression of HCC. HCC-related lncRNAs have been demonstrated to exhibit abnormal expression and contribute to transformation process (such as proliferation, apoptosis, accelerated vascular formation, and gain of invasive potential) through their interaction with DNA, RNA, or proteins. LncRNAs can bind mRNAs to release their target mRNA and enable its translation. These lncRNA-miRNA networks regulate cancer cell expression and so its proliferation, apoptosis, invasion, metastasis, angiogenesis, epithelial-mesenchymal transition (EMT), drug resistance, and autophagy. In this narrative review, we focus on miRNA and lncRNA in HCC tumor tissue and their interaction as current tools, and biomarkers and therapeutic targets unravelled in recent years.

Abstract Background The prognostic significance of mast cells and different phenotypes of macrophages in the microenvironment of hepatocellular carcinoma (HCC) following resection is unclear. We aimed in this study to assess the local distribution of infiltrating macrophages and mast cells of specific phenotypes in tissues of HCC and to evaluate their prognostic values for survival of post-surgical patients. Methods The clinicopathological and follow-up data of 70 patients with HCC, who underwent curative resection of tumor from 1997 to 2019, were collected. The infiltration of CD68+ and CD163+ macrophages and CD117+ mast cells was assessed immunohistochemically in representative resected specimens of HCC and adjacent tissues. The area fraction (AF) of positively stained cells was estimated automatically using QuPath image analysis software in several regions, such as tumor center (TC), inner margin (IM), outer margin (OM), and peritumor (PT) area. The prognostic significance of immune cells, individually and in associations, for time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS) was evaluated using Kaplan-Meier and Cox regression analyses. Results High AF of CD68+ macrophages in TC and IM and high AF of mast cells in IM and PT area were associated with a longer DFS. High AF of CD163+ macrophages in PT area correlated with a shorter DFS. Patients from CD163TChigh & CD68TClow group had a shorter DFS compared to all the rest of the groups, and cases with CD163IMlow & CD68IMhigh demonstrated significantly longer DFS compared to low AF of both markers. Patients from CD68IMhigh & CD163PTlow group, CD117IMhigh & CD163PTlow group, and CD117PThigh & CD163PTlow group had a significantly longer DFS compared to all other combinations of respective cells. Conclusions The individual prognostic impact of CD68+ and CD163+ macrophages and mast cells in the microenvironment of HCC after resection depends on their abundance and location, whereas the cumulative impact is built upon combination of different cell phenotypes within and between regions.

Cycling is a sustainable and healthy form of transportation that is gradually becoming the primary means of transportation over shorter distances in many countries. This paper describes the dataset used to determine the cycling characteristics of seniors in the USA and Canada. For these purposes, a specially created questionnaire was used in a survey conducted from August 2021 to July 2022. The questionnaire contained sections related to the general socio-demographic characteristics of the respondents, general characteristics of cycling (type of bicycle, cycle time, mileage, etc.), and specific characteristics of cycling (riding in night conditions, termination of cycling, motivating and demotivating factors for cycling, etc.). The total sample consisted of 5096 respondents (50+ years old). This database is particularly significant because it represents the first set of publicly available data related to the cycling characteristics of older adults. The database can be used by various researchers dealing with this topic, but also by the decision-makers who want to design a sustainable and accessible cycling infrastructure, respecting the requirements of this category of users. Finally, this dataset can serve as an adequate basis in the process of determining the specificities and understanding the needs of older cyclists in traffic.

The article examines how the crisis phenomenon is discussed in the Romanian public communication environment. The authors argue that in the current context, where society is marked by multiple crises, the term "permacrisis" has become relevant, describing a state of permanent crisis affecting the society at multiple levels. The authors analysed how the topic of crisis has been represented in the Romanian media, focusing on articles published online between 2017 and 2022. Through quantitative and qualitative analysis, the study highlights a significant increase in crisis-related mentions since 2020, in the context of the COVID-19 pandemic. This increase indicates a shift in public perception and media discourse, suggesting the normalisation and acceptance of the crisis as a constant state. Four dominant themes associated with the crisis were identified in media discourse: the economic crisis, the health crisis generated by COVID-19, the domestic political crisis and the crisis generated by the war in Ukraine. These themes illustrate the different facets of the permacrisis in Romania, from the economic and social impact, to political uncertainty and the consequences of pandemics and geopolitical conflicts. The paper highlights the importance of recognising and understanding the phenomenon of permacrisis in Romanian society in order to develop more effective strategies for managing crises and building a more resilient society.

Abstract The advancements in digital technologies, especially for mobile apps, enabled simplified data collection methods. Consequently, through Citizen Science, numerous opportunities arose for citizens to become contributors and not just beneficiaries of scientific research. Furthermore, through such engagement, citizens can participate in decision-making processes at different spatial scales, getting closer to the civic aspiration of a digital agora. This paper offers a systematic review of 303 studies on such initiatives to outline the potential of mobile apps in Citizen Science. Based distinctly on their specificities and the needs they address, three content categories were highlighted: a) monitoring tools, b) validation of techniques and methods to improve mobile technologies for Citizen Science, and c) participatory approaches of citizens employing mobile apps. The review also showed a susceptibility of several domains of activity towards Citizen Science, such as monitoring biodiversity and reconnecting people with nature, environmental risk monitoring or improving well-being. The findings highlight future research potential in addressing topics such as new technologies to increase Citizen Science performance and its contributions to Open Science, as well as diversification and enhancement of citizen scientists’ contributions.

The global community is grappling with a significant increase in forest fires’ frequency, size, and intensity, presenting a profound challenge. To complement existing framing literature on forest fires, this paper examines collective frames applied to forest fires in a broader EU context. Employing a content analysis covering 354 EU policy documents—spanning both soft (non-legally binding) and hard (legally binding) policy documents—via the use of Atlas.ti, six collective frames on forest fires are outlined, identifying four as particularly dominant: ‘climate adaptation and resilience’, ‘risk mitigation and protective governance’, ‘agriculture and rural development’, and ‘technocratic perspectives on forest fires’. These frames capture dominant perspectives promoted within specific policy domains, such as energy and agriculture. Despite the diverse approaches to framing forest fires and their varied objectives, a common thread connects the narratives in these documents, namely, the central theme of ‘risk’. Whether it emerges in the context of reporting or as part of a call to action for adopting certain EU measures, the use of risk operates as a narrative device that negatively frames the discourse, consistently employed to call for action. The findings underscore the importance of considering communication strategies surrounding forest fires, particularly in light of their implications for forest governance.

One of the open challenges in quantum computing is to find meaningful and practical methods to leverage quantum computation to accelerate classical machine-learning workflows. A ubiquitous problem in machine-learning workflows is sampling from probability distributions that we only have access to via their log probability. To this end, we extend the well-known Hamiltonian Monte Carlo (HMC) method for Markov chain Monte Carlo (MCMC) sampling to leverage quantum computation in a hybrid manner as a proposal function. Our new algorithm, Quantum Dynamical Hamiltonian Monte Carlo (QD-HMC), replaces the classical symplectic integration proposal step with simulations of quantum-coherent continuous-space dynamics on digital or analog quantum computers. We show that QD-HMC maintains key characteristics of HMC, such as maintaining the detailed balanced condition with momentum inversion, while also having the potential for polynomial speedups over its classical counterpart in certain scenarios. As sampling is a core subroutine in many forms of probabilistic inference, and MCMC in continuously parametrized spaces covers a large class of potential applications, this work widens the areas of applicability of quantum devices.

Abstract Background Definition of temporal serum proteome profiles after out-of-hospital cardiac arrest may identify biological processes associated with severe hypoxia–ischaemia and reperfusion. It may further explore intervention effects for new mechanistic insights, identify candidate prognostic protein biomarkers and potential therapeutic targets. This pilot study aimed to investigate serum proteome profiles from unconscious patients admitted to hospital after out-of-hospital cardiac arrest according to temperature treatment and neurological outcome. Methods Serum samples at 24, 48, and 72 h after cardiac arrest at three centres included in the Target Temperature Management after out-of-hospital cardiac arrest trial underwent data-independent acquisition mass spectrometry analysis (DIA-MS) to find changes in serum protein concentrations associated with neurological outcome at 6-month follow-up and targeted temperature management (TTM) at 33 °C as compared to 36 °C. Neurological outcome was defined according to Cerebral Performance Category (CPC) scale as “good” (CPC 1–2, good cerebral performance or moderate disability) or “poor” (CPC 3–5, severe disability, unresponsive wakefulness syndrome, or death). Results Of 78 included patients [mean age 66 ± 12 years, 62 (80.0%) male], 37 (47.4%) were randomised to TTM at 36 °C. Six-month outcome was poor in 47 (60.3%) patients. The DIA-MS analysis identified and quantified 403 unique human proteins. Differential protein abundance testing comparing poor to good outcome showed 19 elevated proteins in patients with poor outcome (log2-fold change (FC) range 0.28–1.17) and 16 reduced proteins (log2(FC) between − 0.22 and − 0.68), involved in inflammatory/immune responses and apoptotic signalling pathways for poor outcome and proteolysis for good outcome. Analysis according to level of TTM showed a significant protein abundance difference for six proteins [five elevated proteins in TTM 36 °C (log2(FC) between 0.33 and 0.88), one reduced protein (log2(FC) − 0.6)] mainly involved in inflammatory/immune responses only at 48 h after cardiac arrest. Conclusions Serum proteome profiling revealed an increase in inflammatory/immune responses and apoptosis in patients with poor outcome. In patients with good outcome, an increase in proteolysis was observed, whereas TTM-level only had a modest effect on the proteome profiles. Further validation of the differentially abundant proteins in response to neurological outcome is necessary to validate novel biomarker candidates that may predict prognosis after cardiac arrest.

The objective of the current study was to examine how the expected rewards, theory of mind, and false praise-telling relate to interventional deception that prevents moral transgression. A sample of 114 children aged 4-7 years participated in the study. The expected rewards ratio was a statistically significant predictor of interventional deception, with the children being most likely to deceive to prevent moral transgressions when the deception involved high personal gain. Overall, children who gave false praise and who passed the hidden emotion task were more likely to deceive than those who told another individual an unpleasant truth and failed the emotion understanding task. The results are discussed with respect to diverse developmental conceptions and studies on prosocial behaviors and sociocognitive and cultural factors involved in deception.

The excellent technical parameters of magnesium oxychloride cement (MOC) and its ability to sequester CO2 from the environment predestine its use as an alternative to Portland cement. However, its main shortcomings, low water resistance, and excessive water absorption need to be addressed to enable its wider application in construction. For this reason, the improvement of the water resistance of MOC-based composites through the use of nanosized molybdenum disulfide (MoS2) is the subject of this case study. The MOC-based composites were subjected to experimental testing of their chemical, structural and physical parameters using a wide range of advanced laboratory techniques. The composites enriched by MoS2 nanoadditive exhibited a densified and compact structure with improved mechanical parameters and stiffness. Water transport and storage were significantly decelerated and reduced by the incorporation of MoS2 nanoparticles, resulting in an improvement of water resistance, characterized by the softening coefficient, which was 66.1 % after 24 h of immersion in water, which is about 13.8 % higher than that of the reference MOC-based composite.

Abstract Background Most antidepressant treatment studies have included patients strictly based on the Diagnostic and Statistical Manual of Mental Disorders definition of Major Depressive Disorder (MDD). Given the heterogeneity of MDD, this approach may have obscured inter-patient differences and hampered the development of novel and targeted treatment strategies. An alternative strategy is ​​to use biomarkers to delineate endophenotypes of depression and test if these can be targeted via mechanism-based interventions. Several lines of evidence suggest that “inflammatory depression” is a clinically meaningful subtype of depression. Preliminary data indicate that omega-3 fatty acids, with their anti-inflammatory and neuroprotective properties, may be efficacious in this subtype of depression, and this study aims to test this hypothesis. Method We conduct a match-mismatch-trial to test if add-on omega-3 fatty acid eicosapentaenoic acid (EPA) reduces depressive symptoms in patients with MDD and systemic low-grade inflammation. MDD patients on a stable antidepressant treatment are stratified at baseline on high sensitivity-C-reactive protein (hs-CRP) levels to a high-inflammation group (hs-CRP ≥ 3 mg/L) or a low-inflammation group (hs-CRP

Abstract Habitat fragmentation impacts the distribution of genetic diversity and population genetic structure. Therefore, protecting the evolutionary potential of species, especially in the context of the current rate of human‐induced environmental change, is an important goal. In riverine ecosystems, migration barriers affect the genetic structure of native species, while also influencing the spread of invasive species. In this study, we compare genetic patterns of two native and one highly invasive riverine fish species in a Belgian river basin, namely the native three‐spined stickleback (Gasterosteus aculeatus) and stone loach (Barbatula barbatula), and the non‐native and invasive topmouth gudgeon (Pseudorasbora parva). We aimed to characterize both natural and anthropogenic determinants of genetic diversity and population genetic connectivity. Genetic diversity was highest in topmouth gudgeon, followed by stone loach and three‐spined stickleback. The correlation between downstream distance and genetic diversity, a pattern often observed in riverine systems, was only marginally significant in stone loach and three‐spined stickleback, while genetic diversity strongly declined with increasing number of barriers in topmouth gudgeon. An Isolation‐By‐Distance pattern characterizes the population genetic structure of each species. Population differentiation was only associated with migration barriers in the invasive topmouth gudgeon, while genetic composition of all species seemed at least partially determined by the presence of migration barriers. Among the six barrier types considered (watermills, sluices, tunnels, weirs, riverbed obstructions, and others), the presence of watermills was the strongest driver of genetic structure and composition. Our results indicate that conservation and restoration actions, focusing on conserving genetic patterns, cannot be generalized across species. Moreover, measures might target either on restoring connectivity, while risking a rapid spread of the invasive topmouth gudgeon, or not restoring connectivity, while risking native species extinction in upstream populations.

Abstract The power conversion efficiencies (PCEs) of single‐junction organic solar cells (OSCs) have surpassed 19%, owing to the emerging Y‐series nonfullerene acceptors (NFAs). Undoubtedly, the power and flexibility of chemical design has been a strong driver for this rapid efficiency improvement in the OSC field. Over the course of the past 3 years, a variety of modifications have been made to the structure of the Y6 acceptor, and a large number of Y‐series NFAs have been reported to further improve performance. Herein, we present our insights into the rationale behind the Y6 acceptor and discuss the design principles toward high‐performance Y‐series NFAs. It is clear that structural modifications through choice of heteroatom, soluble chains, π spacers, central cores, and end groups alter the material characteristics and properties, contributing to distinctive photovoltaic performance. Subsequently, we analyze various design strategies of Y‐series‐containing materials, including polymerized small‐molecule acceptors (PSMA), non‐fused‐ring acceptors (NFRA), and all‐fused‐ring acceptors (AFRA). This review is expected to be of value in providing effective molecular design strategies for high‐performance NFAs in future innovations.

Despite normal hearing in one ear, individuals with congenital unilateral aural atresia may perceive difficulties in everyday listening conditions typically containing multiple sound sources. While previous work shows that intervention with bone conduction devices may aid spatial hearing for some children, testing conditions are often arranged to maximize any benefit and are not very similar to daily life. The benefit from amplification on spatial tasks has been found to vary between individuals, for reasons not entirely clear. This study has sought to expand on the limited knowledge on how children with unilateral aural atresia recognize speech masked by competing speech, and how horizontal sound localization accuracy is affected by the degree of unilateral hearing loss and by amplification using unilateral bone conduction devices when fitted before 3 years of age. In a within-subject, repeated measures design, including 11 children (mean age = 7.9 years), bone conduction hearing device (BCD) amplification did not negatively affect horizontal sound localization accuracy. The effect on speech recognition scores showed greater inter-individual variability. No benefit from amplification on a group level was found. There was no association between age at fitting and the benefit of the BCD. For children with poor unaided sound localization accuracy, there was a greater BCD benefit. Unaided localization accuracy increased as a function of decreasing hearing thresholds in the atretic ear. While it is possible that low sound levels in the atretic ear provided access to interaural localization cues for the children with the lowest hearing thresholds, the association has to be further investigated in a larger sample of children.

Recent advances in radar systems have led to the development of radar interferometry (RI) methods for contactless vibration monitoring of large-scale structures, i.e. bridges, water tower reservoirs, and factory chimneys. Interferometric radars are devices capable to measure with 200 Hz sampling frequency and relative movement precision of 0.1 mm up to 0.01 mm. The major part of this paper describes an in-situ footbridge experiment near Hradec Králové. Radar interferometry devices were deployed along with ordinary techniques compounded by accelerometers, wiring, and acquisition station. Experiment was focused on the evaluation of basic dynamic structural properties such as natural frequencies and mode shapes. A lot of attention was also given to the result comparison of these measurement methods. Test results have confirmed the applicability of RI for bridge vibration monitoring.

Photons that decouple from a relativistic jet do so over a range of radii, leading to a spreading in arrival times at the observer. Therefore, changes to the comoving photon distribution across the decoupling zone are encoded in the emitted signal. In this paper, we study such spectral evolution occurring across a pulse. We track the radiation from the deep subphotospheric regions all the way to the observed time-resolved signal, accounting for emission at various angles and radii. We assume a simple power-law photon spectrum injection over a range of optical depths and let the photons interact with the local plasma. At high optical depths, we find that the radiation exists in one of three characteristic regimes, two of which exhibit a high-energy power law. Depending on the nature of the injection, this power law can persist to low optical depths and manifest itself during the rise time of the pulse with a spectral index β ≈ α − 1, where α is the low-energy spectral index. The results are given in the context of a gamma-ray burst jet, but are general to optically thick, relativistic outflows.

Machine learning (ML) methods are commonly applied in the fields of extraterrestrial physics, space science, and plasma physics. In a prior publication, an ML classification technique, the Random Forest (RF) algorithm, was utilized to automatically identify and categorize erroneous signals, including instrument errors, noisy signals, outlier data points, and the impact of solar flares (SFs) on the ionosphere. This data communication includes the pre-processed dataset used in the aforementioned research, along with a workflow that utilizes the PyCaret library and a post-processing workflow. The code and data serve educational purposes in the interdisciplinary field of ML and ionospheric physics science, as well as being useful to other researchers for diverse objectives.

Abstract Background Hepatocellular carcinoma (HCC) is a fatal disease characterized by early genetic alterations in telomerase reverse transcriptase promoter (TERTp) and β-catenin (CTNNB1) genes and immune cell activation in the tumor microenvironment. As a novel approach, we wanted to assess patient survival influenced by combined presence of mutations and densities of CD8+ cytotoxic T cells. Methods Tissue samples were obtained from 67 HCC patients who had undergone resection. We analysed CD8+ T cells density, TERTp mutations, rs2853669 polymorphism, and CTNNB1 mutations. These variables were evaluated for time to recurrence (TTR) and disease free survival (DFS). Results TERTp mutations were found in 75.8% and CTNNB1 mutations in 35.6% of the patients. TERTp mutations were not associated with survival but polymorphism rs2853669 in TERTp was associated with improved TTR and DFS. CTNNB1 mutations were associated with improving TTR. High density of CD8+ T-lymphocytes in tumor center and invasive margin correlated with longer TTR and DFS. Combined genetic and immune factors further improved survival showing higher predictive values. E.g., combining CTNNB1 mutations and high density of CD8+ T-lymphocytes in tumor center yielded HRs of 0.12 (0.03–0.52), p = 0.005 for TTR and 0.25 (0.09–0.74), p = 0.01 for DFS. Conclusion The results outline a novel integrative approach for prognostication through combining independent predictive factors from genetic and immune cell profiles. However, larger studies are needed to explore multiple cell types in the tumor microenvironment.

To solve the problem with the landfilling of waste ash coming from wood chips combustion and to develop construction composites with moderate strength and improved thermal performance, enriched wood chips ash/magnesium oxychloride lightweight composites were designed and thoroughly characterized. As the demand for the thermal effective materials composed of sustainable raw precursors remains a challenge, foamed glass produced from waste glass was used as lightweight aggregate. The experimental analysis of the prepared composites included assessment of phase composition, micro- and macrostructural parameters, mechanical strength, hygric properties, heat transport and storage parameters. The replacement of silica sand with foamed glass enabled the development of materials with high porosity and mechanical strength, moderate water absorption capacity rate, lowered thermal conductivity and high heat storage capacity. As the flexural and compressive strength of the lightened composites remained high, it was possible to further improve thermal insulation performance of the composites by the higher dosage of lightweight aggregate in composite mixture. The wood chips ash greatly improved the mechanical strength of the lightened composites and enabled the development of construction materials with lower environmental damage. The ash acted both as fine filler and reactive material positively influencing the formation of hydration products. The acquired data and results evince that an interesting alternative to Portland cement-based composites were obtained.

Introduction Cervical insufficiency accounts for 15% of recurrent pregnancy losses between 16 and 28 weeks of gestation. The aim of the study is to verify the effectiveness of emergency double-level cerclage with vaginal progesterone in cervical insufficiency treatment in terms of the prevention of preterm delivery before 34 weeks of gestation.Methods and analysis This trial is a multicentre, non-blinded, randomised study with 1:1 allocation ratio. The study is conducted at tertiary perinatal care departments in Poland. It will include patients with cervical insufficiency with the fetal membranes visible in the open cervical canal or protruding into the vagina between 16+0 and 23+6 weeks of pregnancy. They will be randomised into two arms: emergency single-level cerclage with vaginal progesterone or double-level cerclage with vaginal progesterone. All will be administered antibiotics and indomethacin. The primary outcome is the rate of deliveries below 34+0 weeks of gestation, while secondary outcomes include gestational age at delivery, neonatal outcomes, maternal outcomes according to the Core Outcome Set for Evaluation of Interventions to Prevent Preterm Birth and cerclage procedure complications. The planned number of participants according to the power analysis is 78.Ethics and dissemination The study protocol was written in accordance with the Standard Protocol Items: Recommendations for Interventional Trials statement. It was created according to the requirements of the Declaration of Helsinki for Medical Research involving Human Subject. Ethical approval was obtained from the Ethics Committee of the Centre of Postgraduate Medical Education (no. 1/2022). The study protocol was approved and published by ClinicalTrials.gov (posted on 24 February 2022). All participants gave a written informed consent. After completion of the study its results will be published in a peer-reviewed English language journal.Trial registration NCT05268640.

We compared Spanish (L1)–English (L2) bilinguals and Spanish monolinguals in a semantic judgment relationship task in L1 that produced within-language conflict due to the coactivation of the two meanings of a Spanish homophone (e.g., “hola” and “ola” meaning “hello” and “a wave” in English). In this task, participants indicated if pairs of words were related or not (“agua-hola,” “water-hello”). Conflict arose because a word (“agua,” “water”) not related to the orthographic form of a homophone (“hola,” “hello”) was related to the alternative orthographic form (“ola,” “wave”). Compared to a control condition with unrelated word pairs (“peluche-hola,” “teddy-hello”), the behavioral results revealed greater behavioral interference in monolinguals compared to bilinguals. In addition, electrophysiological results revealed N400 differences between monolinguals and bilinguals. These results are discussed around the impact of bilingualism on conflict resolution.

Following solar flares (SF), the abrupt increase in X-radiation and EUV emission generates additional ionization and higher absorption of, e.g., electromagnetic waves in the sunlit hemisphere of the Earth’s ionosphere. The modeling of the ionosphere under solar flares are motivated by new observations with spacecrafts, satellites, and ground-based measurements. The estimation of modeling parameters for the ionospheric D-region during SF events poses a significant challenge, typically requiring a trial-and-error approach. This research presents a machine learning (ML) methodology for modeling the sharpness (β) and reflection height (H′) during SF events occurred from 2008 to 2017. The research methodology was divided into two separate approaches: an instance-based approach, which involved obtaining SF parameters during the peak SF, and a time-series approach, which involved analyzing time-series data during SFs. The findings of the study revealed that the model for the instance-based approach exhibited mean absolute percentage error (MAPE) values of 9.1% for the β parameter and 2.45% for the H′ parameter. The findings from the time-series approach indicated that the model exhibited lower error rates compared to the instance-based approach. However, it was observed that the model demonstrated an increase in β residuals as the predicted β increased, whereas the opposite trend was observed for the H′ parameter. The main goal of the research is to develop an easy-to-use method that provides ionospheric parameters utilizing ML, which can be refined with additional and novel data as well as other techniques for data pre-processing and other algorithms. The proposed method and the utilized workflow and datasets are available at GitHub.

Research background. Considering the importance of consumption of berry fruits with proven health-beneficial properties and difficulties in quality control of products of specific botanical and geographic origin, a fingerprint method was developed, based on advanced data analysis (pattern recognition, classification), in order to relate the variability of nutrients in the selected cultivars to primary metabolite profile. Experimental approach. Forty-five samples of genuine berry fruit cultivars (strawberry, raspberry, blackberry, black currant, blueberry, gooseberry, chokeberry, cape gooseberry and goji berry) were characterized according to chromatographic profiles of primary metabolites (sugars, lipids and fatty acids) obtained by three chromatographic techniques (high-performance thin-layer chromatography, gas chromatography coupled to mass spectrometry, and high-performance anion-exchange chromatography with pulsed amperometric detection). Results and conclusions. Comprehensive analysis allowed monitoring and identification of metabolites belonging to polar lipids, mono-, di- and triacylglycerols, free fatty acids, free sterols, sterol esters, mono- to heptasaccharides and sugar alcohols. Chemical fingerprint of berry seeds showed the uniformity of primary metabolites within each fruit species, but revealed differences depending on the botanical origin. All three chromatographic methods provided a discriminative, informative and predictive metabolomics methodology, which proved to be useful for chemotaxonomic classification. Novelty and scientific contribution. A novel methodology for the identification of bioactive compounds from primary metabolites of natural products was described. The proposed untargeted metabolite profiling approach could be used in the future as a routine method for tracing of novel bioactive compounds. The knowledge of metabolite composition obtained in this study can provide a better assessment of genotypic and phenotypic differences between berry fruit species and varieties, and could contribute to the development of new breeding programs.

The book reviewed here is one of the very rare social scientific analyses of flood-induced disasters in Romania. The monograph is a valuable contribution to the Romanian literature in the social sciences, because the author makes a sustained effort to advance a sociological understanding of the disasters tiggered by floods. In this sense, any given flood is not the disaster but only the trigger of a social disaster. The disaster ensues from the ways in which the flood interacts with pre-existing socio-economic and spatial conditions and inequalities. The book is structured into six chapters and an introductory piece. Its appeal is wide-ranging and it includes all social scientists interested in flood-induced or climate change-induced disasters. Experts and stakeholders involved in the management of floods or similar systemic hazards would also greatly benefit from reading this informative piece.

Abstract Anthropogenic stressors, such as pollutants, act as selective factors that can leave measurable changes in allele frequencies in the genome. Metals are of particular concern among pollutants, because of interference with vital biological pathways. We use the three‐spined stickleback as a model for adaptation to mercury pollution in natural populations. We collected sticklebacks from 21 locations in Flanders (Belgium), measured the accumulated levels of mercury in the skeletal muscle tissue, and genotyped the fish by sequencing (GBS). The spread of muscle mercury content across locations was considerable, ranging from 21.5 to 327 ng/g dry weight (DW). We then conducted a genome‐wide association study (GWAS) between 28,450 single nucleotide polymorphisms (SNPs) and the accumulated levels of mercury, using different approaches. Based on a linear mixed model analysis, the GWAS yielded multiple hits with a single top hit on Chromosome 4, with eight more SNPs suggestive of association. A second approach, a latent factor mixed model analysis, highlighted one single SNP on Chromosome 11. Finally, an outlier test identified one additional SNP on Chromosome 4 that appeared under selection. Out of all ten SNPs we identified as associated with mercury in muscle, three SNPs all located on Chromosome 4 and positioned within a 2.5 kb distance of an annotated gene. Based on these results and the genome coverage of our SNPs, we conclude that the selective effect of mercury pollution in Flanders causes a significant association with at least one locus on Chromosome 4 in three‐spined stickleback.

The process of manually checking, validating, and excluding data in an ionospheric very-low-frequency (VLF) analysis during extreme events is a labor-intensive and time-consuming task. However, this task can be automated through the utilization of machine learning (ML) classification techniques. This research paper employed the Random Forest (RF) classification algorithm to automatically classify the impact of solar flares on ionospheric VLF data and erroneous data points, such as instrumentation errors and noisy data. The data used for analysis were collected during September and October 2011, encompassing solar flare classes ranging from C2.5 to X2.1. The F1-score values obtained from the test dataset displayed values of 0.848; meanwhile, a more detailed analysis revealed that, due to the imbalanced distribution of the target class, the per-class F1-score indicated higher values for the normal data point class (0.69–0.97) compared to those of the anomalous data point class (0.31 to 0.71). Instances of successful and inadequate categorization were analyzed and presented visually. This research investigated the potential application of ML techniques in the automated identification and classification of erroneous VLF amplitude data points; however, the findings of this research hold promise for the detection of short-term ionospheric responses to, e.g., gamma ray bursts (GRBs), or in the analysis of pre-earthquake ionospheric anomalies.

Abstract Early life stress has been linked to increased methylation of the Nuclear Receptor Subfamily 3 Group C Member 1 (NR3C1) gene, which codes for the glucocorticoid receptor. Moreover, early life stress has been associated with substance use initiation at a younger age, a risk factor for developing substance use disorders. However, no studies to date have investigated whether NR3C1 methylation can predict substance use in young individuals. This study included adolescents 13–14 years of age that reported no history of substance use at baseline, (N = 1041; males = 46%). Participants contributed saliva DNA samples and were followed in middle adolescence as part of KUPOL, a prospective cohort study of 7th-grade students in Sweden. Outcome variables were self-reports of (i) recent use, (ii) lifetime use, and (iii) use duration of (a) alcohol, (b) tobacco products, (c) cannabis, or (d) any substance. Outcomes were measured annually for three consecutive years. The predictor variable was DNA methylation at the exon 1 F locus of NR3C1. Risk and rate ratios were calculated as measures of association, with or without adjustment for internalizing symptoms and parental psychiatric disorders. For a subset of individuals (N = 320), there were also morning and afternoon salivary cortisol measurements available that were analyzed in relation to NR3C1 methylation levels. Baseline NR3C1 hypermethylation associated with future self-reports of recent use and use duration of any substance, before and after adjustment for potential confounders. The overall estimates were attenuated when considering lifetime use. Sex-stratified analyses revealed the strongest association for cigarette use in males. Cortisol analyses revealed associations between NR3C1 methylation and morning cortisol levels. Findings from this study suggest that saliva NR3C1 hypermethylation can predict substance use in middle adolescence. Additional longitudinal studies are warranted to confirm these findings.

Abstract The gastric microbiota in Crohn’s disease (CD) has not been studied. The purpose of the study was to evaluate differences of stomach microbiota between CD patients and controls. DNA was extracted from gastric mucosal and fluid samples, from 24 CD patients and 19 controls. 16S rRNA gene sequencing identified 1511 operational taxonomic units (OTUs), of which 239 passed the low abundance and low variance filters. All but one CD patients were HP negative. Fifteen bacterial phyla were identified in at least one mucosal or fluid site. Of these, Bacteroidota and Firmicutes accounted for 70% of all phyla. Proteobacteria, Actinobacteriota, and Fusobacteriota combined accounted for 27%. There was significant difference in the relative abundance of Bacteroidota, Proteobacteria, Fusobacteriota, and Campilobacterota between CD patients and controls only in gastric corpus samples. In gastric liquid, there was a significant difference only in Actinobacteriota. Pairwise comparison identified 67 differentially abundant OTUs in at least one site. Of these, 13 were present in more than one comparison, and four differentiating OTUs (Neisseriaceae, Neisseria, Absconditabacteriales, and Microbacteriaceae) were identified at all tested sites. The results reveal significant changes in gastric microbial profiles (beta diversity, phylum, and individual taxa levels) between H. pylori-negative CD patients and controls.

Abstract Background Intratumoral regulatory T cells (Treg) in colon cancer are a heterogeneous cell population, with potential impact on patient outcome. Generally, a high Treg infiltration has been correlated to a worse patient outcome, but it is still unclear how the composition of different Treg subsets affects patient relapse and survival. In this study, we used mass and flow cytometry to characterize Treg in colon tumors and corresponding unaffected tissue, followed by a correlation to clinical parameters and patient outcome. Results Using mass cytometry, we defined 13 clusters of intestinal Treg, three of which were enriched in the tumors. The two most enriched clusters were defined by their expression of the proliferation marker Ki67 and CD56, respectively. The Treg accumulating in the tumors expressed inducible T-cell co-stimulator (ICOS), OX-40, and CD39, indicating that they were effector Treg (eTreg). Intratumoral CD39+ Treg also had a higher expression of Foxp3, suggesting a higher suppressive activity, and we subsequently used CD39 as a marker for eTreg. Our further studies showed that colon tumors can be divided into two tumor groups, based on the proportion of CD39+ putative eTreg in the tumors. This property was independent of both tumor microsatellite status and tumor stage, which are important factors in predicting cancer disease progression. In a prospective study of forty-four colon cancer patients, we also showed that patients with a high CD39 expression on tumor-infiltrating Treg have a tendency towards a less favorable patient outcome in terms of cumulative cancer-specific survival. Conclusions This study uncovers novel subsets of tumor-infiltrating Treg in colon cancer, and suggests that CD39 may be a potential therapeutic target in patients with microsatellite stable colon tumors, which are usually refractory to checkpoint blockade therapy.

Abstract Background Genome-wide data are invaluable to characterize differentiation and adaptation of natural populations. Reduced representation sequencing (RRS) subsamples a genome repeatedly across many individuals. However, RRS requires careful optimization and fine-tuning to deliver high marker density while being cost-efficient. The number of genomic fragments created through restriction enzyme digestion and the sequencing library setup must match to achieve sufficient sequencing coverage per locus. Here, we present a workflow based on published information and computational and experimental procedures to investigate and streamline the applicability of RRS. Results In an iterative process genome size estimates, restriction enzymes and size selection windows were tested and scaled in six classes of Antarctic animals (Ostracoda, Malacostraca, Bivalvia, Asteroidea, Actinopterygii, Aves). Achieving high marker density would be expensive in amphipods, the malacostracan target taxon, due to the large genome size. We propose alternative approaches such as mitogenome or target capture sequencing for this group. Pilot libraries were sequenced for all other target taxa. Ostracods, bivalves, sea stars, and fish showed overall good coverage and marker numbers for downstream population genomic analyses. In contrast, the bird test library produced low coverage and few polymorphic loci, likely due to degraded DNA. Conclusions Prior testing and optimization are important to identify which groups are amenable for RRS and where alternative methods may currently offer better cost-benefit ratios. The steps outlined here are easy to follow for other non-model taxa with little genomic resources, thus stimulating efficient resource use for the many pressing research questions in molecular ecology.

The paper provides insights into the mental health consequences of the coronavirus disease 2019 (COVID-19) pandemic from the Central, Eastern, Nordic, Southern, and Western subregions of Europe, represented by five member countries of the European Society for Traumatic Stress Studies (ESTSS). On the basis of the existing national research and experiences in these countries, we propose five lessons learned. (1) There is no evidence of a mental health pandemic so far in the countries in focus. No increase in severe mental disorders but some increase in the symptoms of common mental health disorders are observable. More high-quality longitudinal studies are needed to understand the mental health burden of the pandemic. (2) The pandemic affects countries (including the mental health situation) differently, depending on the level of the exposure, management policies, pre-pandemic structural characteristics, and healthcare resources. (3) The pandemic affects people differently: the exposure severity to pandemic-related stressors differs between individuals, as well as individual resources to cope with these stressors. There are winners and losers as well as identifiable at-risk groups that need particular attention. (4) Besides the negative consequences, the pandemic has had a positive impact. The rapidly applied innovations within the system of healthcare responses provide a window of opportunity for positive changes in mental healthcare policies, strategies, and practices. The increased focus on mental health during the pandemic may contribute to the prioritization of mental health issues at policy-making and organizational levels and may reduce stigma. (5) A stress- and trauma-informed response to COVID-19 is required. The European community of psychotraumatologists under the leadership of ESTSS plays an important role in promoting stress- and trauma-informed healthcare and policies of pandemic management. Based on the lessons learned, we propose a stepped-care public mental health model for the prevention of adverse mental health outcomes during pandemics. HIGHLIGHTS Population mental health is affected differently in the COVID-19 pandemic: there are winners and losers, as well as identifiable at-risk groups that need particular attention. A stress- and trauma-informed public mental health stepped-care model can address pandemic-related mental health burden in a systematic way.

Abstract Background Primary splenic lymphoma represents a rare entity that constitutes less than 1% of non-Hodgkin lymphomas, and less than 2% of all lymphomas. Diffuse large B-cell lymphoma (DLBCL) is the most common histological subtype of primary splenic lymphomas. DLBCL encompasses a heterogeneous entity with distinct morphological variants. The anaplastic variant of DLBCL was first defined in the 2017 World Health Organization classification as a rare histological subtype that constitutes less than 3.4% of DLBCL cases. Case presentation A 65-year-old Syrian man presented to our hospital with constant dull localized left upper quadrant abdominal pain for about 20 days accompanied by general weakness, loss of appetite, and rapid weight loss. Clinical examination revealed isolated splenomegaly and left upper abdominal tenderness. Following physical, laboratory, and radiologic examinations, the patient underwent splenectomy. Interestingly, pathological and immunohistochemical examinations of the resected spleen confirmed the diagnosis of a primary anaplastic variant of DLBCL. Conclusions Herein, we aimed to present an unusual combination of a rare splenic neoplasm and a unique lymphoma subtype. Furthermore, we aimed to highlight the difficulties in differential diagnosis and the importance of histological and immunohistochemical examinations with clinical correlation.

Urinary extracellular vesicles (EVs) are an attractive source of bladder cancer biomarkers. Here, a protein biomarker discovery study was performed on the protein content of small urinary EVs (sEVs) to identify possible biomarkers for the primary diagnosis and recurrence of non-muscle-invasive bladder cancer (NMIBC). The sEVs were isolated by ultrafiltration (UF) in combination with size-exclusion chromatography (SEC). The first part of the study compared healthy individuals with NMIBC patients with a primary diagnosis. The second part compared tumor-free patients with patients with a recurrent NMIBC diagnosis. The separated sEVs were in the size range of 40 to 200 nm. Based on manually curated high quality mass spectrometry (MS) data, the statistical analysis revealed 69 proteins that were differentially expressed in these sEV fractions of patients with a first bladder cancer tumor vs. an age- and gender-matched healthy control group. When the discriminating power between healthy individuals and first diagnosis patients is taken into account, the biomarkers with the most potential are MASP2, C3, A2M, CHMP2A and NHE-RF1. Additionally, two proteins (HBB and HBA1) were differentially expressed between bladder cancer patients with a recurrent diagnosis vs. tumor-free samples of bladder cancer patients, but their biological relevance is very limited.

Polycyclic aromatic hydrocarbons (PAHs) refer to a group of several hundred compounds, among which 16 are identified as priority pollutants, due to their adverse health effects, frequency of occurrence, and potential for human exposure. This study is focused on benzo(a)pyrene, being considered an indicator of exposure to a PAH carcinogenic mixture. For this purpose, we have applied the XGBoost model to a two-year database of pollutant concentrations and meteorological parameters, with the aim to identify the factors which were mostly associated with the observed benzo(a)pyrene concentrations and to describe types of environments that supported the interactions between benzo(a)pyrene and other polluting species. The pollutant data were collected at the energy industry center in Serbia, in the vicinity of coal mining areas and power stations, where the observed benzo(a)pyrene maximum concentration for a study period reached 43.7 ngm−3. The metaheuristics algorithm has been used to optimize the XGBoost hyperparameters, and the results have been compared to the results of XGBoost models tuned by eight other cutting-edge metaheuristics algorithms. The best-produced model was later on interpreted by applying Shapley Additive exPlanations (SHAP). As indicated by mean absolute SHAP values, the temperature at the surface, arsenic, PM10, and total nitrogen oxide (NOx) concentrations appear to be the major factors affecting benzo(a)pyrene concentrations and its environmental fate.

Abstract Uncertainty hampers innovative mixed‐fisheries management by the scales at which connectivity dynamics are relevant to management objectives. The spatial scale of sustainable stock management is species‐specific and depends on ecology, life history and population connectivity. One valuable approach to understand these spatial scales is to determine to what extent population genetic structure correlates with the oceanographic environment. Here, we compare the level of genetic connectivity in three codistributed and commercially exploited demersal flatfish species living in the North East Atlantic Ocean. Population genetic structure was analysed based on 14, 14 and 10 neutral DNA microsatellite markers for turbot, brill and sole, respectively. We then used redundancy analysis (RDA) to attribute the genetic variation to spatial (geographical location), temporal (sampling year) and oceanographic (water column characteristics) components. The genetic structure of turbot was composed of three clusters and correlated with variation in the depth of the pycnocline, in addition to spatial factors. The genetic structure of brill was homogenous, but correlated with average annual stratification and spatial factors. In sole, the genetic structure was composed of three clusters, but was only linked to a temporal factor. We explored whether the management of data poor commercial fisheries, such as in brill and turbot, might benefit from population‐specific information. We conclude that the management of fish stocks has to consider species‐specific genetic structures and may benefit from the documentation of the genetic seascape and life‐history traits.

Type 1 diabetes (T1D) is the third most common autoimmune disease which develops due to genetic and environmental risk factors. Based on the World Health Organization (WHO) report from 2014 the number of people suffering from all types of diabetes ascended to 422 million, compared to 108 million in 1980. It was calculated that this number will double by the end of 2030. In 2015 American Diabetes Association (ADA) announced that 30.3 million Americans (that is 9.4% of the overall population) had diabetes of which only approximately 1.25 million had T1D. Nowadays, T1D represents roughly 10% of adult diabetes cases total. Multiple genetic abnormalities at different loci have been found to contribute to type 1 diabetes development. The analysis of genome-wide association studies (GWAS) of T1D has identified over 50 susceptible regions (and genes within these regions). Many of these regions are defined by single nucleotide polymorphisms (SNPs) but molecular mechanisms through which they increase or lower the risk of diabetes remain unknown. Genetic factors (in existence since birth) can be detected long before the emergence of immunological or clinical markers. Therefore, a comprehensive understanding of the multiple genetic factors underlying T1D is extremely important for further clinical trials and development of personalized medicine for diabetic patients. We present an overview of current studies and information about regions in the human genome associated with T1D. Moreover, we also put forward information about epigenetic modifications, non-coding RNAs and environmental factors involved in T1D development and onset.

To mnie zawsze zdumiewało: skłonność intelektualistów walczących o przemiany w świecie do traktowania własnego języka, własnej ideologii (nie ma ideologii bez języka, za pomocą którego się ją tłumaczy) jako jedynego możliwego narzędzia zmiany.

Abstract Background Clostridium difficile (C. difficile) is a major source of healthcare-associated infection with a high risk of recurrence, attributable to many factors such as usage of antibiotics, older age and immunocompromised status of the patients. C. difficile has also a highly diverse genome, which may contribute to its high virulence. Herein we examined whether the genome conservation, measured as non-synonymous to synonymous mutations ratio (dN/dS) in core genes, presence of single genes, plasmids and prophages increased the risk of reinfection in a subset of 134 C. difficile isolates from our previous study in a singly hemato-oncology ward. Methods C. difficile isolates were subjected to whole-genome sequencing (WGS) on Ion Torrent PGM sequencer. Genomes were assembled with MIRA5 and annotated with prokka and VRprofile. Logistic regression was used to asses the relationship between single gene presence and the odds of infection recurrence. DN/dS ratios were computed with codeml. Functional annotation was conducted with eggNOG-Mapper. Results We have found that the presence of certain genes, associated with carbon metabolism and oxidative phosphorylation, increased the odds of infection recurrence. More core genes were under positive selective pressure in recurrent disease isolates – they were mostly associated with the metabolism of aminoacids. Finally, prophage elements were more prevalent in single infection isolates and plasmids did not influence the odds of recurrence. Conclusions Our findings suggest higher genetic plasticity in isolates causing recurrent infection, associated mainly with metabolism. On the other hand, the presence of prophages seems to reduce the isolates’ virulence.

Methods for prediction of fluid responsiveness are needed during shock resuscitation. Fluid therapy remains a cornerstone in the treatment of shock and influences the outcomes directly. Excess or insufficient fluid administration is associated with increased morbidity and mortality. Prediction of fluid responsiveness means that a hemodynamic variable is used to determine how likely a patient is to respond to fluid bolus with a significant increase in their cardiac output. Depending on the response to fluids, patients are either responders or non-responders. Clinicians often rely on static indices of preload, like central venous pressure and pulmonary artery occlusion pressure, as a guide for fluid therapy. Unfortunately, whilst easy for use, these indices are of minimal value as predictors of fluid responsiveness. More recent research highlights hemodynamic variables related to cardiopulmonary interactions during mechanical ventilation. These dynamic indices, viz. stroke volume variation and pulse pressure variation, show a significantly better predictive value. To maximize the predictive value of dynamic indices, several conditions must be fulfilled. Another method for prediction of fluid responsiveness is represented by the functional hemodynamic tests: a heterogenous group of bedside tests for preload responsiveness. Fluid challenges remain popular, although repetitive use can be harmful. Hemodynamic tests, like passive leg raising or end-expiratory occlusion, modify the preload without fluid administration. Regardless of the test used, monitoring of cardiac output is needed to evaluate the heart’s response to changes in preload. This review gives an overview of the methods for fluid responsiveness prediction, including those explored in the COVID-19 context.

Optics: Optimising Luminescent Solar Concentrators for applications in optical systems Modelling the bandwidth limits of Luminescent Solar Concentrators (LSCs) offers vital insights into their behaviour and provides a technique for evaluating their use in various applications. Although LSCs have emerged as a promising receiver technology in free-space optical communications due to their ability to collect light from a wide field-of-view and concentrate it into small areas, the comparably slow timescale of their fluorescence events may pose a bottleneck on the bandwidth of high-speed communication systems. A team of researchers led by Ioannis Papakonstantinou from University College London has developed a technique that delineates the fundamental limits of LSCs as optical detectors and demonstrated time-domain Monte-Carlo simulation for optimising LSC based receiver systems. The work opens the door for the use of LSCs in applications in visible light communications, high-speed video recording, and real-time biological imaging.

Mesoscopic superconducting particles can be used as a model material for the cognition of the properties of a possible superconducting cosmic dust. In order to acquire the desired fraction between 1–10 µm, the method of the grain size separation based on wet sedimentation in isopropanol was developed for the Bi1.8Pb0.26Sr2Ca2Cu3O10+x (BSCCO) high-temperature superconductor. The separated size fractions were characterized by the laser diffraction (LD), SEM-EDS, and XRD measurements. All fractions contained the same amount of major 2223 superconducting phase and the mesoscopic fraction meet the criteria for the cosmic dust simulation. Furthermore, the developed method may be also suitable for other purposes, since various fractions of the sizes can be collected, including the nano-sized fraction. Besides that, this method works without producing any dust or noise, which can be useful for possible larger-scale applications.

Abstract Background Small cell carcinoma of the prostate is a rare condition with important differences from prostatic adenocarcinoma in terms of clinical and prognostic characteristics. A low prostate-specific antigen and a symptomatic patient, including paraneoplastic symptoms, characterize small cell carcinoma of the prostate. Diagnosis is made on the basis of prostate biopsy, and fluorodeoxyglucose positron emission tomography/computed tomography is often used for staging because up to 60% of patients present with de novo metastatic disease. Patients with metastatic disease are usually treated with platinum-based cytotoxic chemotherapy regimens similar to those used for small cell carcinoma of the lung. However, prognosis remains poor, with a median overall survival of 9 to 17 months despite therapy. Case presentation This report describes a case of an 80-year-old Caucasian patient with lymph node and bone metastatic small cell carcinoma of the prostate following low-dose-rate brachytherapy for a low-risk prostate carcinoma and treated with chemotherapy and immunotherapy. Conclusion Low-dose-rate brachytherapy might be an etiology of small cell prostate cancer.