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Abstract. Climate change is increasing the frequency and intensity of wildfires globally, with significant impacts on society and the environment. However, our understanding of the global distribution of extreme fires remains skewed, primarily influenced by media coverage and regional research concentration. This inaugural State of Wildfires report systematically analyses fire activity worldwide, identifying extreme events from the March 2023–February 2024 fire season. We assess the causes, predictability, and attribution of these events to climate change and land use, and forecast future risks under different climate scenarios. During the 2023–24 fire season, 3.9 million km2 burned globally, slightly below the average of previous seasons, but fire carbon (C) emissions were 16 % above average, totaling 2.4 Pg C. This was driven by record emissions in Canadian boreal forests (over 9 times the average) and dampened by reduced activity in African savannahs. Notable events included record-breaking wildfire extent and emissions in Canada, the largest recorded wildfire in the European Union (Greece), drought-driven fires in western Amazonia and northern parts of South America, and deadly fires in Hawai’i (100 deaths) and Chile (131 deaths). Over 232,000 people were evacuated in Canada alone, highlighting the severity of human impact. Our analyses revealed that multiple drivers were needed to cause areas of extreme fire activity. In Canada and Greece a combination of high fire weather and an abundance of dry fuels increased the probability of fires by 4.5-fold and 1.9–4.1-fold, respectively, whereas fuel load and direct human suppression often modulated areas with anomalous burned area. The fire season in Canada was predictable three months in advance based on the fire weather index, whereas events in Greece and Amazonia had shorter predictability horizons. Formal attribution analyses indicated that the probability of extreme events has increased significantly due to anthropogenic climate change, with a 2.9–3.6-fold increase in likelihood of high fire weather in Canada and a 20.0–28.5-fold increase in Amazonia. By the end of the century, events of similar magnitude are projected to occur 2.22–9.58 times more frequently in Canada under high emission scenarios. Without mitigation, regions like Western Amazonia could see up to a 2.9-fold increase in extreme fire events. For the 2024–25 fire season, seasonal forecasts highlight moderate positive anomalies in fire weather for parts of western Canada and South America, but no clear signal for extreme anomalies is present in the forecast. This report represents our first annual effort to catalogue extreme wildfire events, explain their occurrence, and predict future risks. By consolidating state-of-the-art wildfire science and delivering key insights relevant to policymakers, disaster management services, firefighting agencies, and land managers, we aim to enhance society’s resilience to wildfires and promote advances in preparedness, mitigation, and adaptation.

Climate change contributes to the increased frequency and intensity of wildfires globally, with significant impacts on society and the environment. However, our understanding of the global distribution of extreme fires remains skewed, primarily influenced by media coverage and regionalised research efforts. This inaugural State of Wildfires report systematically analyses fire activity worldwide, identifying extreme events from the March 2023–February 2024 fire season. We assess the causes, predictability, and attribution of these events to climate change and land use and forecast future risks under different climate scenarios. During the 2023–2024 fire season, 3.9×106 km2 burned globally, slightly below the average of previous seasons, but fire carbon (C) emissions were 16 % above average, totalling 2.4 Pg C. Global fire C emissions were increased by record emissions in Canadian boreal forests (over 9 times the average) and reduced by low emissions from African savannahs. Notable events included record-breaking fire extent and emissions in Canada, the largest recorded wildfire in the European Union (Greece), drought-driven fires in western Amazonia and northern parts of South America, and deadly fires in Hawaii (100 deaths) and Chile (131 deaths). Over 232 000 people were evacuated in Canada alone, highlighting the severity of human impact. Our analyses revealed that multiple drivers were needed to cause areas of extreme fire activity. In Canada and Greece, a combination of high fire weather and an abundance of dry fuels increased the probability of fires, whereas burned area anomalies were weaker in regions with lower fuel loads and higher direct suppression, particularly in Canada. Fire weather prediction in Canada showed a mild anomalous signal 1 to 2 months in advance, whereas events in Greece and Amazonia had shorter predictability horizons. Attribution analyses indicated that modelled anomalies in burned area were up to 40 %, 18 %, and 50 % higher due to climate change in Canada, Greece, and western Amazonia during the 2023–2024 fire season, respectively. Meanwhile, the probability of extreme fire seasons of these magnitudes has increased significantly due to anthropogenic climate change, with a 2.9–3.6-fold increase in likelihood of high fire weather in Canada and a 20.0–28.5-fold increase in Amazonia. By the end of the century, events of similar magnitude to 2023 in Canada are projected to occur 6.3–10.8 times more frequently under a medium–high emission scenario (SSP370). This report represents our first annual effort to catalogue extreme wildfire events, explain their occurrence, and predict future risks. By consolidating state-of-the-art wildfire science and delivering key insights relevant to policymakers, disaster management services, firefighting agencies, and land managers, we aim to enhance society's resilience to wildfires and promote advances in preparedness, mitigation, and adaptation. New datasets presented in this work are available from https://doi.org/10.5281/zenodo.11400539 (Jones et al., 2024) and https://doi.org/10.5281/zenodo.11420742 (Kelley et al., 2024a).

Abstract Background Amyotrophic Lateral Sclerosis (ALS) is a highly heterogenous neurodegenerative disorder that primarily affects upper and lower motor neurons, affecting additional cell types and brain regions. Underlying molecular mechanisms are still elusive, in part due to disease heterogeneity. Molecular disease subtyping through integrative analyses including RNA editing profiling is a novel approach for identification of molecular networks involved in pathogenesis. Methods We aimed to highlight the role of RNA editing in ALS, focusing on the frontal cortex and the prevalent molecular disease subtype (ALS-Ox), previously determined by transcriptomic profile stratification. We established global RNA editing (editome) and gene expression (transcriptome) profiles in control and ALS-Ox cases, utilizing publicly available RNA-seq data (GSE153960) and an in-house analysis pipeline. Functional annotation and pathway analyses identified molecular processes affected by RNA editing alterations. Pearson correlation analyses assessed RNA editing effects on expression. Similar analyses on additional ALS-Ox and control samples (GSE124439) were performed for verification. Targeted re-sequencing and qRT-PCR analysis targeting CACNA1C, were performed using frontal cortex tissue from ALS and control samples (n = 3 samples/group). Results We identified reduced global RNA editing in the frontal cortex of ALS-Ox cases. Differentially edited transcripts are enriched in synapses, particularly in the glutamatergic synapse pathway. Bioinformatic analyses on additional ALS-Ox and control RNA-seq data verified these findings. We identified increased recoding at the Q621R site in the GRIK2 transcript and determined positive correlations between RNA editing and gene expression alterations in ionotropic receptor subunits GRIA2, GRIA3 and the CACNA1C transcript, which encodes the pore forming subunit of a post-synaptic L-type calcium channel. Experimental data verified RNA editing alterations and editing-expression correlation in CACNA1C, highlighting CACNA1C as a target for further study. Conclusions We provide evidence on the involvement of RNA editing in the frontal cortex of an ALS molecular subtype, highlighting a modulatory role mediated though recoding and gene expression regulation on glutamatergic synapse related transcripts. We report RNA editing effects in disease-related transcripts and validated editing alterations in CACNA1C. Our study provides targets for further functional studies that could shed light in underlying disease mechanisms enabling novel therapeutic approaches.

Automated machine learning (AutoML) is considered the next advancement in artificial intelligence due to its commitment to delivering high-performance end-to-end machine learning pipelines with minimal user input. Although AutoML has demonstrated significant potential in computer vision tasks, as far as current knowledge extends, there is currently no study that has applied AutoML specifically to hyperspectral imaging for fertilization level classification. To address this information gap, the use of AutoML for classifying fertilization levels using a hyperspectral and CIELAB color space dataset was investigated. A comparative analysis was conducted between the performance of an open-source AutoML framework, PyCaret, and traditional machine learning using the PLS-DA algorithm. PyCaret achieved the highest accuracy (1.00) in classifying different fertilization levels using the hyperspectral dataset, while PLS-DA attained an accuracy of 0.91. However, the CIELAB dataset was not as effective for this classification task, achieving an accuracy of only 0.72. It is worth noting that the hyperspectral dataset outperformed the CIELAB dataset in both AutoML and PLS-DA analyses. Finally, the findings suggest that AutoML holds substantial potential to enhance the use of hyperspectral imaging in agriculture, particularly for fertilization tasks.

Prion diseases, also known as Transmissible Spongiform Encephalopathies (TSEs), are protein-based neurodegenerative disorders (NDs) affecting humans and animals. They are characterized by the conformational conversion of the normal cellular prion protein, PrPC, into the pathogenic isoform, PrPSc. Prion diseases are invariably fatal and despite ongoing research, no effective prophylactic or therapeutic avenues are currently available. Anthocyanins (ACNs) are unique flavonoid compounds and interest in their use as potential neuroprotective and/or therapeutic agents against NDs, has increased significantly in recent years. Therefore, we investigated the potential anti-oxidant and anti-prion effects of Oenin and Myrtillin, two of the most common anthocyanins, using the most accepted in the field overexpressing PrPSc in vitro model and a cell free protein aggregation model. Our results, indicate both anthocyanins as strong anti-oxidant compounds, upregulating the expression of genes involved in the anti-oxidant response, and reducing the levels of Reactive Oxygen Species (ROS), produced due to pathogenic prion infection, through the activation of the Keap1-Nrf2 pathway. Importantly, they showcased remarkable anti-prion potential, as they not only caused the clearance of pathogenic PrPSc aggregates, but also completely inhibited the formation of PrPSc fibrils in the Cerebrospinal Fluid (CSF) of patients with Creutzfeldt–Jakob disease (CJD). Therefore, Oenin and Myrtillin possess pleiotropic effects, suggesting their potential use as promising preventive and/or therapeutic agents in prion diseases and possibly in the spectrum of neurodegenerative proteinopathies.

This review aims to examine the impact of increasing energy costs on the global economy, social cohesion, economic growth, and capital markets, with a particular focus on the consequences of the COVID-19 pandemic and the energy crisis intensified by the war in Ukraine. The methodology involves an extensive review of recent academic literature to cast light on these impacts. The study identifies significant disruptions in supply chains and heightened volatility in international capital markets due to these crises. Furthermore, the findings highlight the resulting challenges for policymakers, academics, market analysts, and professionals in addressing corporate sustainability in an increasingly uncertain environment. This paper underscores the continued relevance of energy issues as a central concern, both independently and in connection with broader economic sectors. Additionally, it discusses the importance of policy measures to enhance energy security and the transition towards sustainable energy solutions to mitigate these challenges and foster economic resilience.

Objective: To address positive airway pressure (PAP) adherence in adolescents diagnosed with obstructive sleep apnoea (OSA) by pilot testing a novel, online, facilitated, peer-support and health education programme for families. Design, setting, and methods: Families participated in separate Facebook peer-groups (adolescent [n = 6] and parent [n = 6]) for 4 weeks, followed by face-to-face interviews. Participants received OSA and PAP educational videos and posts, engaged with questions and polls, and viewed de-identified postings of peer PAP use data. Results: Adolescent participants were young Black men aged 13-17 years (n = 6) with obesity (n = 5), severe sleep apnoea (100%) and 4-15 months of prior PAP use. Parent participants were mothers (n = 4) and fathers (n = 2). Four of six young men increased their mean PAP use during the intervention period. Overall, parents were more engaged with the Facebook group page than adolescents, but interviews revealed the online group/peer-support and education provided was highly regarded and appreciated by families. Parents were particularly appreciative of being involved in care and diagnosis in this way. Conclusion: Results of this pilot trial provide important data regarding intervention design, content and delivery approaches to be considered in the development of future interventions aiming to engage families and improve adolescent PAP adherence.

Background: This meta-analysis and systematic review aim to consolidate evidence on cardiotoxicity prevention and treatment strategies in patients receiving anthracyclines or HER2 receptor inhibitors, vital treatments for breast cancer and hematologic malignancies. By synthesizing existing research, the goal is to provide impactful insights that enhance patient care and outcomes. Methods: Comprehensive research across PubMed, Scopus, EMBASE, and the Cochrane Central Register for Controlled Trials was conducted, selecting clinical trials focusing on cardioprotection in anthracyclines or HER2 inhibitor-treated individuals. Effect sizes were computed using OpenMeta (Analyst), with leave-out meta-analysis to assess potential small study effects. Meta-regression explored treatment duration and sample size effects. Evidence quality for primary outcomes was evaluated using ROB, Robins 2, and Newcastle-Ottawa tools. Results: Twenty -three studies involving a total of 14,652 patients (13,221 adults and 1431 kids) were included in the current systematic review and meta-analysis. The risk of bias and methodological quality of the included studies suggested good and moderate quality. Patients prescribed β-blockers demonstrated a 74% lower likelihood of exhibiting cardiotoxicity symptoms (OR 1.736). Similarly, the use of dexrazoxane was linked to a threefold decrease in cardiac abnormalities risk (OR 2.989), and ACE inhibitor administration showed half the risk compared with the control group (OR 1.956). Conclusions: Through this systematic review and meta-analysis, it was shown that there is a reduction in cardiotoxicity from either anthracyclines or HER2 inhibitors in patients receiving pharmacoprophylaxis.

Background: Accurate diagnosis of Alzheimer’s disease (AD) and frontotemporal dementia (FTD) represents a health issue due to the absence of disease traits. We assessed the performance of a SIMOA panel in cerebrospinal fluid (CSF) from 43 AD and 33 FTD patients with 60 matching Control subjects in combination with demographic–clinical characteristics. Methods: 136 subjects (AD: n = 43, FTD: n = 33, Controls: n = 60) participated. Single-molecule array (SIMOA), glial fibrillary acidic protein (GFAP), neurofilament light (NfL), TAU, and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) in CSF were analyzed with a multiplex neuro 4plex kit. Receiver operating characteristic (ROC) curve analysis compared area under the curve (AUC), while the principal of the sparse partial least squares discriminant analysis (sPLS-DA) was used with the intent to strengthen the identification of confident disease clusters. Results: CSF exhibited increased levels of all SIMOA biomarkers in AD compared to Controls (AUCs: 0.71, 0.86, 0.92, and 0.94, respectively). Similar patterns were observed in FTD with NfL, TAU, and UCH-L1 (AUCs: 0.85, 0.72, and 0.91). sPLS-DA revealed two components explaining 19% and 9% of dataset variation. Conclusions: CSF data provide high diagnostic accuracy among AD, FTD, and Control discrimination. Subgroups of demographic–clinical characteristics and biomarker concentration highlighted the potential of combining different kinds of data for successful and more efficient cohort clustering.

Background/Objectives: The aim of this study was to examine the association between in-hospital initiation of sodium glucose co-transporter 2 inhibitors (SGLT2is) and outcomes in hospitalized heart failure (HHF) patients utilizing data from a Greek center. Methods: The present work was a single-center, retrospective, observational study of consecutive HF patients hospitalized in a tertiary center. The study endpoint was all-cause mortality or HF rehospitalization. Univariate and multivariate Cox proportional-hazard models were conducted to investigate the association between SGLT2i administration at discharge and the study endpoint. Results: Sample consisted of 171 patients, 55 of whom (32.2%) received SGLT2is at discharge. Overall, mean follow-up period was 6.1 months (SD = 4.8 months). Patients who received SGLT2is at discharge had a 43% lower probability of the study endpoint compared to those who did not receive SGLT2is at discharge (HR = 0.57; 95% CI: 0.36–0.91; p = 0.018). After adjusting for age, gender, smoking, hemoglobin (Hgb), use of SGLT2is at admission, use of Angiotensin-Converting Enzyme Inhibitors (ACEI-Is)/Angiotensin Receptor Blockers (ARBs) at discharge and Sacubitril/Valsartan at discharge, the aforementioned result remained significant (HR = 0.38; 95% CI: 0.19–0.73; p = 0.004). The 55 patients who received SGLT2is at discharge were propensity score matched with the 116 patients who did not receive SGLT2is at discharge. Receiving SGLT2is at discharge continued to be significantly associated with a lower probability of the study endpoint (HR= 0.43; 95% CI: 0.20–0.89; p = 0.024). Conclusions: Initiation of SGLT2is in HHF patients may be associated with better outcomes.

Background/Objectives: As heart failure (HF) patients face increased vulnerability to respiratory infections, optimizing pneumococcal and influenza vaccination coverage becomes pivotal for mitigating additional health risks and reducing hospitalizations, morbidity, and mortality rates within this population. In this specific subpopulation of patients, vaccination coverage for pneumococcal and influenza holds heightened significance compared to other vaccines due to their susceptibility to respiratory infections, which can exacerbate existing cardiovascular conditions and lead to severe complications or even death. However, despite the recognized benefits, vaccination coverage among HF patients remains below expectations. The aim of the present systematic review was to assess the vaccination coverage for influenza and pneumococcus in HF patients from 2005 to 2023 and the vaccination’s effects on survival and hospitalizations. Methods: The authors developed the protocol of the review in accordance with the PRISMA guidelines, and the search was performed in databases including PubMed and Scopus. After the initial search, 851 studies were found in PubMed Library and 1961 in Scopus (total of 2812 studies). Results: After the initial evaluation, 23 publications were finally included in the analysis. The total study population consisted of 6,093,497 participants. Regarding the influenza vaccine, vaccination coverage ranged from low rates of 2.5% to very high rates of 97%, while the respective pneumococcal vaccination coverage ranged from 20% to 84.6%. Most studies demonstrated a beneficial effect of vaccination on survival and hospitalizations. Conclusions: The present systematic review study showed a wide variety of vaccination coverage among patients with heart failure.

Prions are proteinaceous pathogens responsible for a variety of devastating diseases in mammals, including scrapie in sheep and goats, chronic wasting disease in cervids, and Creutzfeldt–Jakob disease (CJD) in humans. They are characterized by their exceptional persistence to common inactivation procedures. This applies to all possible sources of prion contamination as prions may be present in the tissues and biological fluids of infected individuals. Hence, efficient prion inactivation procedures are still being sought to minimize the risk of intra- or inter-species transmission. In the past, photocatalytic treatment has been proven to be capable of efficiently oxidizing and inactivating prions. In the present study, the efficacy of homogeneous photo-Fenton-based photocatalysis as well as heterogeneous photocatalysis with TiO2 in reducing RML mouse scrapie infectivity was evaluated. Prion inactivation was assessed by means of a bioassay, and the results were confirmed by in vitro experiments. While the prion infectivity of the RML mouse scrapie was reduced after treatment with the photo-Fenton reagent, the heterogeneous photocatalytic treatment of the same prion strain completely eliminated prion infectivity.

Gold nanoparticles (AuNPs) radiolabeled with therapeutic and diagnostic radioisotopes have been broadly studied as a promising platform for early diagnosis and treatment of many diseases including cancer. Our main goal for this study was the comparison of the biodistribution profiles of four different concentrations of gold nanoconjugates radiolabeled with Technetium-99m (99mTc). More specifically, AuNPs with an average diameter of 2 nm were functionalized with a tridentate thiol ligand. Four different concentrations were radiolabeled with 99mTc-tricarbonyls with high radiolabeling yields (>85%) and were further purified, leading to radiochemical purity of >95%. In vitro stability of the radiolabeled nanoconstructs was examined in cysteine and histidine solutions as well as in human serum, exhibiting robust radiolabeling up to 24 h post-preparation. Moreover, in vitro cytotoxicity studies were carried out in 4T1 murine mammary cancer cells. In vivo tracking of the radiolabeled nanoconjugates at both concentrations was examined in normal mice in order to examine the effect of AuNPs’ concentration on their in vivo kinetics. Our work demonstrates that varying concentrations of radiolabeled AuNPs lead to notably different biodistribution profiles.

In times of intense economic variability and social turbulence worldwide, this paper aims to examine the existence of transient correlations and interdependencies between the most important MSCI ESG indices worldwide and the most important commodities’ index, economic uncertainty, natural gas, gold, and VIX, in a geographical and social context during two recent crises: the COVID-19 pandemic and the energy crisis due to the Ukrainian war. Using daily data from 3 January 2020 and extending until 23 August 2022, this study applies a wavelet coherence approach to analyze time series co-movements, in order to emphasize all possible combinations’ correlations and achieve more accurate outcomes at any given time and frequency band simultaneously and spontaneously. The results show robust coherence between different geographical areas, time, and frequency bands, indicating both positive and negative correlations with most of the combined ESG indices and other economic indicators. The study suggests that stock indices of leading ESG companies in North America and Europe constitute a safe investment haven during major upheavals and crises, providing a way for investors to manage risk and generate positive returns while contributing to economic sustainability.

Background: Hepatopancreato and biliary (HPB) tumors represent some of the leading cancer-related causes of death worldwide, with the majority of patients undergoing surgery in the context of a multimodal treatment strategy. Consequently, the implementation of an accurate risk stratification tool is crucial to facilitate informed consent, along with clinical decision making, and to compare surgical outcomes among different healthcare providers for either service evaluation or clinical audit. Perioperative troponin levels have been proposed as a feasible and easy-to-use tool in order to evaluate the risk of postoperative myocardial injury and 30-day mortality. The purpose of the present study is to validate the perioperative troponin levels as a prognostic factor regarding postoperative myocardial injury and 30-day mortality in Greek adult patients undergoing HPB surgery. Method: In total, 195 patients undergoing surgery performed by a single surgical team in a single tertiary hospital (2020–2022) were included. Perioperative levels of troponin before surgery and at 24 and 48 h postoperatively were assessed. Model accuracy was assessed by observed-to-expected (O:E) ratios, and area under the receiver operating characteristic curve (AUC). Survival at one year postoperatively was compared between patients with high and normal TnT levels at 24 h postoperatively. Results: Thirteen patients (6.6%) died within 30 days of surgery. TnT levels at 24 h postoperatively were associated with excellent discrimination and provided the best-performing calibration. Patients with normal TnT levels at 24 h postoperatively were associated with higher long-term survival compared to those with high TnT levels. Conclusions: TnT at 24 h postoperatively is an efficient risk assessment tool that should be implemented in the perioperative pathway of patients undergoing surgery for HPB cancer.

Spinocerebellar ataxia type 1 (SCA1) is an autosomal dominant neurodegenerative disease caused by a trinucleotide (CAG) repeat expansion in the ATXN1 gene. It is characterized by the presence of polyglutamine (polyQ) intranuclear inclusion bodies (IIBs) within affected neurons. In order to investigate the impact of polyQ IIBs in SCA1 pathogenesis, we generated a novel protein aggregation model by inducible overexpression of the mutant ATXN1(Q82) isoform in human neuroblastoma SH-SY5Y cells. Moreover, we developed a simple and reproducible protocol for the efficient isolation of insoluble IIBs. Biophysical characterization showed that polyQ IIBs are enriched in RNA molecules which were further identified by next-generation sequencing. Finally, a protein interaction network analysis indicated that sequestration of essential RNA transcripts within ATXN1(Q82) IIBs may affect the ribosome resulting in error-prone protein synthesis and global proteome instability. These findings provide novel insights into the molecular pathogenesis of SCA1, highlighting the role of polyQ IIBs and their impact on critical cellular processes.

Aim: to understand how wildfire risk policies are designed to mitigate11 The goal of the analysis here is not to promote wildfire exclusion, but to reduce the likelihood of fire ignition and manage the growth and intensity of wildfire events. the impacts of wildfires. Wildfires are a growing threat in many parts of the world, posing significant risks to human life, and the environment. In recent years, wildfires have increased, driven largely by climate change, human activity, and changes in land-use patterns. Wildfire risk adaptation and mitigation measures vary widely between countries and regions around the world. Therefore, it is essential to develop a comprehensive policy approach to mitigate wildfire risks and promote sustainable forest and land management practices. This article aims to provide insight into wildfire policies, implementation actions, and their effectiveness by describing wildfire policies centered mainly on exclusion and wildfire risk mitigation. Methodology: the article examines existing wildfire-related policies and relevant literature based on 10 systematic factors. Further exploring how these policies can be enhanced to meet the challenges of the coming years for six European countries (Cyprus, France, Greece, Italy, Portugal, UK) as well as Australia, Canada, USA, and South Africa. Results: The status quo, perceived strengths, weaknesses, and recommendations from key-informants were presented to enhance wildfire policies in each country. Conclusions: The article analyses current wildfire policies in fire-prone countries, highlighting regional variations and the need for an integrated management strategy. It offers country-specific recommendations based on the participants viewpoints, for coordinated efforts to mitigate wildfire risks and promote sustainable forest management.

Robinia pseudoacacia L. (black locust) has been extensively used for restoring degraded lands, following anthropogenic interventions like coal mining. Here we have addressed the contribution of black locust restoration plantations, established on overburden post-mining material, to carbon storage and to soil nitrogen enrichment at the largest lignite center in Greece. Carbon stocks and fluxes in all pools of the ecosystem, as well as the foliar nitrogen resorption efficiency and soil N stocks were quantified and the effect of plantations’ age was tested. The young age of the plantations (4–24 years) resulted in a relatively low total ecosystem C stock (56.7 t ha−1), which was partitioned among the different pools in the following order: above-ground biomass (50%) > black locust-derived SOC (24%) > coarse roots (14%) > deadwood (6%) > forest floor (5%) > fine roots (less than 1%). Litterfall started early in the growing season and together with fine roots that had a turnover rate of 0.62 yr−1, fueled soil organic carbon. SOC accrual, referring to the accumulation of SOC derived by black locust, declined with age. However, further SOC accumulation is expected, based on the potential SOC storage capacity of soil at the area. C stocks in above- and below-ground biomass increased linearly with age. The same response was observed for soil N stock and NRE, indicating that despite the N2-fixing capacity of black locust, there was still a poor pedospheric N supply and a need for efficient N cycling. Overall, the studied restoration plantations have a considerable contribution to C and N accumulation at the degraded post-mining sites. These positive effects are expected to further increase at least until the plantations reach maturity.

Abstract Background Amyotrophic lateral sclerosis (ALS) is a rare progressive neurodegenerative disease that affects upper and lower motor neurons. As the molecular basis of the disease is still elusive, the development of high-throughput sequencing technologies, combined with data mining techniques and machine learning methods, could provide remarkable results in identifying pathogenetic mechanisms. High dimensionality is a major problem when applying machine learning techniques in biomedical data analysis, since a huge number of features is available for a limited number of samples. The aim of this study was to develop a methodology for training interpretable machine learning models in the classification of ALS and ALS-subtypes samples, using gene expression datasets. Methods We performed dimensionality reduction in gene expression data using a semi-automated preprocessing systematic gene selection procedure using Statistically Equivalent Signature (SES), a causality-based feature selection algorithm, followed by Boosted Regression Trees (XGBoost) and Random Forest to train the machine learning classifiers. The SHapley Additive exPlanations (SHAP values) were used for interpretation of the machine learning classifiers. The methodology was developed and tested using two distinct publicly available ALS RNA-seq datasets. We evaluated the performance of SES as a dimensionality reduction method against: (a) Least Absolute Shrinkage and Selection Operator (LASSO), and (b) Local Outlier Factor (LOF). Results The proposed methodology achieved 85.18% accuracy for the classification of cerebellum or frontal cortex samples as C9orf72-related familial ALS, sporadic ALS or healthy samples. Importantly, the genes identified as the most determinative have also been reported as disease-associated in ALS literature. When tested in the evaluation dataset, the methodology achieved 88.89% accuracy for the classification of sporadic ALS motor neuron samples. When LASSO was used as feature selection method instead of SES, the accuracy of the machine learning classifiers ranged from 74.07 to 96.30%, depending on tissue assessed, while LOF underperformed significantly (77.78% accuracy for the classification of pooled cerebellum and frontal cortex samples). Conclusions Using SES, we addressed the challenge of high dimensionality in gene expression data analysis, and we trained accurate machine learning ALS classifiers, specific for the gene expression patterns of different disease subtypes and tissue samples, while identifying disease-associated genes.

Heart failure with reduced ejection fraction (HFrEF) is a complex clinical syndrome with significant morbidity and mortality and seems to be responsible for approximately 50% of heart failure cases and hospitalizations worldwide. First-line treatments of patients with HFrEF, according to the ESC and AHA guidelines, include β-blockers, angiotensin receptor/neprilysin inhibitors, sodium-glucose cotransporter 2 inhibitors, and mineralocorticoid receptor antagonists. This quadruple therapy should be initiated during hospital stay and uptitrated to maximum doses within 6 weeks after discharge according to large multicenter controlled trials. Quadruple therapy improves survival by approximately 8 years for a 55-year-old heart failure patient. Additional therapeutic strategies targeting other signaling pathways such as ivabradine, digoxin, and isosorbide dinitrate and hydralazine combination for African Americans, as well as adjunctive symptomatic therapies, seem to be necessary in the management of HFrEF. Although second-line medications have not achieved improvements in mortality, they seem to decrease heart failure hospitalizations. There are novel medical therapies including vericiguat, omecamtiv mecarbil, genetic and cellular therapies, and mitochondria-targeted therapies. Moreover, mitraclip for significant mitral valve regurgitation, ablation in specific atrial fibrillation cases, omecamtiv mecarbil are options under evaluation in clinical trials. Finally, the HeartMate 3 magnetically levitated centrifugal left ventricular assist device (LVAD) has extended 5-year survival for stage D HF patients who are candidates for an LVAD.

Indication to perform surgical explantation of TAVR is becoming increasingly more frequent, due to the higher number of transcatheter procedures performed in patients with longer life expectancy. We proposed to perform a systematic review and meta-analysis with metaregression to identify potential factors that can determine an increase in the high mortality and morbidity that characterize these surgical procedures. MEDLINE and Embase were searched for relevant studies. Twelve studies were eligible according to our inclusion criteria. TAVR explantation was confirmed as a procedure with high 30-day mortality (0.17; 95% CI, 0.14–0.21) and morbidity (stroke incidence 5%; 95% CI, 0.04–0.07; kidney injury incidence 16%; 95% CI, 0.11–0.24). The type of transcatheter valve implanted during the index procedure did not influence the outcomes after surgical explantation. The role of these high-risk operations is growing, and it will likely expand in the coming years. Specific tools for risk stratification are required.

The use of conventional methods for the treatment of cancer, such as chemotherapy or radiotherapy, and approaches such as brachytherapy in conjunction with the unique properties of nanoparticles could enable the development of novel theranostic agents. The aim of our current study was to evaluate the potential of iron oxide nanoparticles, coated with alginic acid and polyethylene glycol, functionalized with the chemotherapeutic agent doxorubicin and the monoclonal antibody bevacizumab, to serve as a nanoradiopharmaceutical agent against breast cancer. Direct radiolabeling with the therapeutic isotope Lutetium-177 (177Lu) resulted in an additional therapeutic effect. Functionalization was accomplished at high percentages and radiolabeling was robust. The high cytotoxic effect of our radiolabeled and non-radiolabeled nanostructures was proven in vitro against five different breast cancer cell lines. The ex vivo biodistribution in tumor-bearing mice was investigated with three different ways of administration. The intratumoral administration of our functionalized radionanoconjugates showed high tumor accumulation and retention at the tumor site. Finally, our therapeutic efficacy study performed over a 50-day period against an aggressive triple-negative breast cancer cell line (4T1) demonstrated enhanced tumor growth retention, thus identifying the developed nanoparticles as a promising nanobrachytherapy agent against breast cancer.

This study aims to deepen our understanding of the evolving landscape of public procurement (PP) and emerging technologies (ET). It addresses the critical gap in scholarly production analysis, author collaborations, and thematic trends in PP and ET, providing valuable insights for researchers, policymakers, and practitioners. Employing a methodology inspired by prior research, this study leveraged advanced bibliometric tools, including Studio R and the Biblioshiny app, for data retrieval, processing, and visualization. This approach facilitated co-citation, source coupling, and network collaboration analyses. Thematic maps and correspondence analysis were used to explore research themes in depth. The findings highlight a significant surge in research interest in the integration of ET in PP since 2018, underlining the growing importance of technology-driven advancements in the field. These insights are vital for shaping policy decisions, spurring innovation, and enhancing PP processes’ efficiency, transparency, and sustainability, which are crucial for effective governance and economic growth.

Heart transplantation (HTx) remains the last therapeutic resort for patients with advanced heart failure. The present work is a clinically focused review discussing current issues in heart transplantation. Several factors have been associated with the outcome of HTx, such as ABO and HLA compatibility, graft size, ischemic time, age, infections, and the cause of death, as well as imaging and laboratory tests. In 2018, UNOS changed the organ allocation policy for HTx. The aim of this change was to prioritize patients with a more severe clinical condition resulting in a reduction in mortality of people on the waiting list. Advanced heart failure and resistant angina are among the main indications of HTx, whereas active infection, peripheral vascular disease, malignancies, and increased body mass index (BMI) are important contraindications. The main complications of HTx include graft rejection, graft angiopathy, primary graft failure, infection, neoplasms, and retransplantation. Recent advances in the field of HTx include the first two porcine-to-human xenotransplantations, the inclusion of hepatitis C donors, donation after circulatory death, novel monitoring for acute cellular rejection and antibody-mediated rejection, and advances in donor heart preservation and transportation. Lastly, novel immunosuppression therapies such as daratumumab, belatacept, IL 6 directed therapy, and IgG endopeptidase have shown promising results.

In recent times, there have been notable changes in cardiovascular medicine, propelled by the swift advancements in artificial intelligence (AI). The present work provides an overview of the current applications and challenges of AI in the field of heart failure. It emphasizes the “garbage in, garbage out” issue, where AI systems can produce inaccurate results with skewed data. The discussion covers issues in heart failure diagnostic algorithms, particularly discrepancies between existing models. Concerns about the reliance on the left ventricular ejection fraction (LVEF) for classification and treatment are highlighted, showcasing differences in current scientific perceptions. This review also delves into challenges in implementing AI, including variable considerations and biases in training data. It underscores the limitations of current AI models in real-world scenarios and the difficulty in interpreting their predictions, contributing to limited physician trust in AI-based models. The overarching suggestion is that AI can be a valuable tool in clinicians’ hands for treating heart failure patients, as far as existing medical inaccuracies have been addressed before integrating AI into these frameworks.

Background and Objectives: Remote ischemic preconditioning (RIPC) has demonstrated efficacy in protecting against myocardial ischemia–reperfusion injury when applied before percutaneous coronary revascularization. Ranolazine, an anti-ischemic drug, has been utilized to minimize ischemic events in chronic angina patients. However, there is a lack of trials exploring the combined effects of ranolazine pretreatment and RIPC in patients undergoing percutaneous coronary interventions (PCIs). Materials and Methods: The present study is a prospective study which enrolled 150 patients scheduled for nonemergent percutaneous coronary revascularization. Three groups were formed: a control group undergoing only PCIs, an RIPC group with RIPC applied to either upper limb before the PCI (preconditioning group), and a group with RIPC before the PCI along with prior ranolazine treatment for stable angina (ranolazine group). Statistical analyses, including ANOVAs and Kruskal–Wallis tests, were conducted, with the Bonferroni correction for type I errors. A repeated-measures ANOVA assessed the changes in serum enzyme levels (SGOT, LDH, CRP, CPK, CK-MB, troponin I) over the follow-up. Statistical significance was set at p < 0.05. Results: The ranolazine group showed (A) significantly lower troponin I level increases compared to the control group for up to 24 h, (B) significantly lower CPK levels after 4, 10, and 24 h compared to the preconditioning group (p = 0.020, p = 0.020, and p = 0.019, respectively) and significantly lower CPK levels compared to the control group after 10 h (p = 0.050), and (C) significantly lower CK-MB levels after 10 h compared to the control group (p = 0.050). Conclusions: This study suggests that combining RIPC before scheduled coronary procedures with ranolazine pretreatment may be linked to reduced ischemia induction, as evidenced by lower myocardial enzyme levels.

Integrating turbulence into stellarator optimization is achieved by targeting the onset for the ion-temperature-gradient mode, highlighting effects of field line curvature, parallel connection length, local magnetic shear, and flux surface expansion. The result is two compact quasihelically symmetric stellarator configurations, one of which admits a set of modular coils, with significantly reduced turbulent heat fluxes compared to a known stellarator. This new configuration combines low values of neoclassical transport, good alpha particle confinement, and Mercier stability at a plasma beta of almost 2%.