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Abstract Aims Parameters derived from reservoir‐excess pressure analysis have been demonstrated to predict cardiovascular events. Thus, altered reservoir‐excess pressure parameters could have a detrimental effect on highly‐perfused organs like the heart. We aimed to cross‐sectionally determine whether reservoir‐excess pressure parameters were associated with N‐terminal pro‐brain‐type natriuretic peptide (NT‐proBNP) in older adults. Methods We studied 868 older adults with diverse cardiovascular risk. Reservoir‐excess pressure parameters were obtained through radial artery tonometry including reservoir pressure integral, peak reservoir pressure, excess pressure integral (INTXSP), systolic rate constant (SRC) and diastolic rate constant (DRC). Plasma levels of NT‐proBNP, as a biomarker of cardiac overload, were analysed by the Proximity Extension Assay technology. Results Multivariable linear regression analyses revealed that all reservoir‐excess pressure parameters studied were associated with NT‐proBNP after adjusting for age and sex. After further adjustments for conventional cardiovascular risk factors, INTXSP [β = 0.191 (95% confidence interval, CI: 0.099, 0.283), P

Abstract Pathological data showed focal inflammation and regions of diffuse neuronal loss in the cortex of people with multiple sclerosis (MS). In this work, we applied a novel model (“soma and neurite density imaging (SANDI)”) to multishell diffusion-weighted MRI data acquired in healthy subjects and people with multiple sclerosis (pwMS), in order to investigate inflammation and degeneration-related changes in the cortical tissue of pwMS. We aimed to (i) establish whether SANDI is applicable in vivo clinical data; (ii) investigate inflammatory and degenerative changes using SANDI soma fraction (f soma )—a marker of cellularity—in both cortical lesions and in the normal-appearing-cortex and (iii) correlate SANDI f soma with clinical and biological measures in pwMS. We applied a simplified version of SANDI to a clinical scanners. We then provided evidence that pwMS exhibited an overall decrease in cortical SANDI f soma compared to healthy subjects, suggesting global degenerative processes compatible with neuronal loss. On the other hand, we have found that progressive pwMS showed a higher SANDI f soma in the outer part of the cortex compared to relapsing–remitting pwMS, possibly supporting current pathological knowledge of increased innate inflammatory cells in these regions. A similar finding was obtained in subpial lesions in relapsing–remitting patients, reflecting existing pathological data in these lesion types. A significant correlation was found between SANDI f soma and serum neurofilament light chain—a biomarker of inflammatory axonal damage—suggesting a relationship between SANDI soma fraction and inflammatory processes in pwMS again. Overall, our data show that SANDI f soma is a promising biomarker to monitor changes in cellularity compatible with neurodegeneration and neuroinflammation in the cortex of MS patients.

Context: In Uruguay, numerous Pinus taeda plantations are at final-turn age, but they still do not have commercial destination and are exported as green-wood logs. For the development of this sector, it is necessary to strive towards a comprehensive processing of this resource. Method: This work focused on analyzing the use of Pinus taeda wood available in the country to produce brown kraft pulp with a kappa number of 80, which can be used to make packaging paper. As raw materials, we employed by-products from the mechanical wood-transformation industry (wood chips and thinning wood) and final-turn wood. Pulping tests were carried out, varying the alkali charge and the H-factor while aiming for a kappa number of 80. The viscosity, pulping, and rejection yield were measured in the pulps, and the pH and residual alkali content were evaluated in black liquor. Results: Based on the results, the best pulping conditions were an active alkali charge of 14% (Na2O) and an H-factor of 1260 for sawmill chips and thinning wood, as well as an active alkali charge of 14% (Na2O) and an H-factor of 1080 for final-turn wood. The pulp obtained with sawmill chips exhibited the most resistant fibers, and the final-turn wood pulp was the most sensitive to the refining process. Under the aforementioned conditions, the paper properties of laboratory-produced pulp are comparable with those of commercial pulp. Conclusions: This indicates that it is technologically possible to produce brown kraft pulp from Uruguayan Pinus taeda wood, with adequate quality to produce packaging paper

Introduction Huntington’s disease (HD) is an inherited neurodegenerative disease causing progressive cognitive and motor decline, largely due to basal ganglia (BG) atrophy. Rhythmic training offers promise as therapy to counteract BG-regulated deficits. We have developed HD-DRUM, a tablet-based app to enhance movement synchronisation skills and improve cognitive and motor abilities in people with HD. This paper outlines a randomised controlled unblinded trial protocol to determine the feasibility of a larger effectiveness trial for HD-DRUM. Additionally, the trial investigates cognitive and motor function measures, along with brain microstructure, aiming to advance our understanding of the neural mechanisms underlying training effects.Methods, design and analysis 50 individuals with HD, confirmed by genetic testing, and a Total Functional Capacity (TFC) score of 9–13, will be recruited into a two-arm randomised controlled feasibility trial. Consenting individuals with HD will be randomised to the intervention group, which entails 8 weeks of at-home usage of HD-DRUM or a usual-activity control group. All participants will undergo cognitive and motor assessments, alongside ultra-strong gradient (300 mT/m) brain microstructural MRI before and after the 8-week period. The feasibility assessment will encompass recruitment, retention, adherence and acceptability of HD-DRUM following prespecified criteria. The study will also evaluate variations in cognitive and motor performance and brain microstructure changes resulting from the intervention to determine effect size estimates for future sample size calculations.Ethics and dissemination The study has received favourable ethical opinion from the Wales Research Ethics Committee 2 (REC reference: 22/WA/0147) and is sponsored by Cardiff University (SPON1895-22) (Research Integrity, Governance and Ethics Team, Research & Innovation Services, Cardiff University, second Floor, Lakeside Building, University Hospital of Wales, Cardiff, CF14 4XW). Findings will be disseminated to researchers and clinicians in peer-reviewed publications and conference presentations, and to participants, carers and the general public via newsletters and public engagement activities. Data will be shared with the research community via the Enroll-HD platform.Trial registration number ISRCTN11906973.

ABSTRACT: This study aimed to evaluate the effect of bovine leukemia virus (BLV) on the systemic profile of naturally infected dairy heifers during the transition period. Pregnant Holstein and Jersey heifers (n=24) were distributed in pairs into two experimental groups: (BLV+) and (BLV-). Animals in the BLV+ group were divided into two subgroups based on the median BLV proviral load (high and low). The animals were then assessed at weeks -3, -2, -1, calving time (0), +1, +2, and +3. Blood samples were obtained for hematological and biochemical analyses, as well as haptoglobin measurements. Farm BLV screening revealed a herd BLV prevalence of 57.25% and heifer BLV prevalence of 38.7%. Mean corpuscular hemoglobin concentration was the only hematological variable for which group interaction was observed, with BLV+ cattle having higher values (33.29 ± 3.39%) than BLV- cattle (31.08 ± 2.31%). Aspartate aminotransferase activity was higher in the BLV+ heifers. The BLV+ group had greater incidence of inflammation (haptoglobin ≥ 2.0 mg/dL). Fibrinogen concentrations were also higher at weeks 0 and +1 in BLV+ heifers than in BLV- heifers. A high proviral load affected total leukocyte and lymphocyte count; however, this profile was not observed in the low proviral load and paired BLV- heifers. To our knowledge, this is the first study to report the impact of BLV infection on the health of dairy heifers during the transition period, demonstrating the effect of proviral load on white blood cell changes and early inflammation in infected animals.

In the last decades, agroecological and permacultural initiatives and organizations have grown. These initiatives attend to notions of food sovereignty and alternative models of agricultural production. The confluence of different actors and social initiatives through which experiences and knowledge of cultivating food are shared, and new ones are created, reveals a high educational potential. In light of impending global catastrophes such as climate change and pressing inequalities, new alternatives and diverse forms of sociability are necessary to open up possible futures for life on a damaged planet. Freirean approaches to science education must align with transdisciplinary social and political movements, and generate reflective practices and methods. This article addresses the case of an art and permaculture cooperative (APC) to analyze how communities work together to disrupt and dismantle inequities in science and education and make a more livable world. We offer a critical and contra-hegemonic pedagogical perspective on science education, one that forges new epistemic territories grounded in cooperation, art, permaculture, relationship, and diverse ecologies. The APC is the only one of its kind in Argentina. It has carried out its socio-ecological activities and interventions in ways that respect the characteristics of the natural ecosystem, agriculture and permaculture. We use narratives and case study methods to reveal how people's subjective narratives give meaning to their experiences and learnings. The APC as a learning context has the potential to transform reality, promoting the development and strengthening of popular science education for liberation, one that honors diverse ecologies, and meaningfully addresses new socio-environmental challenges and concerns.

Abstract Background The Algerian honey bee population is composed of two described subspecies A. m. intermissa and A. m. sahariensis, of which little is known regarding population genomics, both in terms of genetic differentiation and of possible contamination by exogenous stock. Moreover, the phenotypic differences between the two subspecies are expected to translate into genetic differences and possible adaptation to heat and drought in A. m. sahariensis. To shed light on the structure of this population and to integrate these two subspecies in the growing dataset of available haploid drone sequences, we performed whole-genome sequencing of 151 haploid drones. Results Integrated analysis of our drone sequences with a similar dataset of European reference populations did not detect any significant admixture in the Algerian honey bees. Interestingly, most of the genetic variation was not found between the A. m. intermissa and A. m. sahariensis subspecies; instead, two main genetic clusters were found along an East–West axis. We found that the correlation between genetic and geographic distances was higher in the Western cluster and that close-family relationships were mostly detected in the Eastern cluster, sometimes at long distances. In addition, we selected a panel of 96 ancestry-informative markers to decide whether a sampled bee is Algerian or not, and tested this panel in simulated cases of admixture. Conclusions The differences between the two main genetic clusters suggest differential breeding management between eastern and western Algeria, with greater exchange of genetic material over long distances in the east. The lack of detected admixture events suggests that, unlike what is seen in many places worldwide, imports of queens from foreign countries do not seem to have occurred on a large scale in Algeria, a finding that is relevant for conservation purposes. In addition, the proposed panel of 96 markers was found effective to distinguish Algerian from European honey bees. Therefore, we conclude that applying this approach to other taxa is promising, in particular when genetic differentiation is difficult to capture.

Abstract Hospital-acquired diarrhoea (HAD) is common, and often associated with gut microbiota and metabolome dysbiosis following antibiotic administration. Clostridioides difficile is the most significant antibiotic-associated diarrhoeal (AAD) pathogen, but less is known about the microbiota and metabolome associated with AAD and C. difficile infection (CDI) with contrasting antibiotic treatment. We characterised faecal microbiota and metabolome for 169 HAD patients (33 with CDI and 133 non-CDI) to determine dysbiosis biomarkers and gain insights into metabolic strategies C. difficile might use for gut colonisation. The specimen microbial community was analysed using 16 S rRNA gene amplicon sequencing, coupled with untargeted metabolite profiling using gas chromatography-mass spectrometry (GC-MS), and short-chain fatty acid (SCFA) profiling using GC-MS. AAD and CDI patients were associated with a spectrum of dysbiosis reflecting non-antibiotic, short-term, and extended-antibiotic treatment. Notably, extended antibiotic treatment was associated with enterococcal proliferation (mostly vancomycin-resistant Enterococcus faecium) coupled with putative biomarkers of enterococcal tyrosine decarboxylation. We also uncovered unrecognised metabolome dynamics associated with concomitant enterococcal proliferation and CDI, including biomarkers of Stickland fermentation and amino acid competition that could distinguish CDI from non–CDI patients. Here we show, candidate metabolic biomarkers for diagnostic development with possible implications for CDI and vancomycin-resistant enterococci (VRE) treatment.

Green hydrogen technologies are crucial for decarbonization purposes, while cogeneration offers efficient heat and power generation. Integrating green hydrogen and cogeneration brings numerous benefits, optimizing energy utilization, reducing emissions, and supporting the transition to a sustainable future. While there are numerous studies examining the integration of combined heat and power with Power to Gas, certain aspects still requires a more detailed analysis, especially for internal combustion engines fuelled by natural gas, due to their widespread adoption as one of the primary technologies in use. Therefore, this paper presents a comprehensive numerical 0-D dynamic simulation model, implemented within the TRNSYS environment, considering internal combustion engines fuelled by natural gas. Specifically, the study focuses on capturing CO2 from exhaust gases and producing green hydrogen from electrolysis. Based on these considerations, two configurations are proposed: the first involves the methanation reaction, while the second entails the production of a hydromethane mixture. The aim is to evaluate the technical and economic feasibility of these configurations and compare their performance within the Power to Gas framework. Self-sufficiency from the national electricity grid has been almost achieved for the two configurations, considering an industrial case. The production of hydromethane allows smaller photovoltaic plant (81 kWp) compared to the production of synthetic methane (670 kWp) where a high quantity of hydrogen is required, especially if all the carbon dioxide captured is used in the methanation process. Encouraging economic results with payback times below ten years have been obtained with the use of hydromethane. Moreover, hydromethane shows potential residential applications, with small required photovoltaic sizes.

We investigated the activity of cefiderocol/β-lactamase inhibitor combinations against clinical strains with different susceptibility profiles to cefiderocol to explore the potentiality of antibiotic combinations as a strategy to contain the major public health problem of multidrug-resistant (MDR) pathogens. Specifically, we evaluated the synergistic activity of cefiderocol with avibactam, sulbactam, or tazobactam on three of the most “Critical Priority” group of MDR bacteria (carbapenem-resistant Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumannii). Clinical isolates were genomically characterized by Illumina iSeq 100. The synergy test was conducted with time-kill curve assays. Specifically, cefiderocol/avibactam, /sulbactam, or /tazobactam combinations were analyzed. Synergism was assigned if bacterial grow reduction reached 2 log10 CFU/mL. We reported the high antimicrobial activity of the cefiderocol/sulbactam combination against carbapenem-resistant Enterobacterales, P. aeruginosa, and A. baumannii; of the cefiderocol/avibactam combination against carbapenem-resistant Enterobacterales; and of the cefiderocol/tazobactam combination against carbapenem-resistant Enterobacterales and P. aeruginosa. Our results demonstrate that all β-lactamase inhibitors (BLIs) tested are able to enhance cefiderocol antimicrobial activity, also against cefiderocol-resistant isolates. The cefiderocol/sulbactam combination emerges as the most promising combination, proving to highly enhance cefiderocol activity in all the analyzed carbapenem-resistant Gram-negative isolates, whereas the Cefiderocol/tazobactam combination resulted in being active only against carbapenem-resistant Enterobacterales and P. aeruginosa, and cefiderocol/avibactam was only active against carbapenem-resistant Enterobacterales.

The wound management field faces significant challenges due to antimicrobial resistance (AMR) and the complexity of chronic wound care. Effective wound treatment requires antimicrobial dressings to prevent bacterial infections. However, the rise of AMR necessitates new antimicrobial agents for wound dressings, particularly for addressing bacterial pathogens like methicillin-resistant Staphylococcus aureus (MRSA). Endophytic fungi, known for producing diverse bioactive compounds, represent a promising source of such new agents. This study tested thirty-two endophytic fungi from thirteen distinct Australian native plants for their antibacterial activity against S. aureus. Ethyl acetate (EtOAc) extracts from fungal culture filtrates exhibited inhibitory effects against both methicillin-sensitive S. aureus ATCC 25923 (MIC = 78.1 µg/mL) and MRSA M180920 (MIC = 78.1 µg/mL). DNA sequence analysis was employed for fungal identification. The most active sample, EL 19 (Chaetomium globosum), was selected for further analysis, revealing that its EtOAc extracts reduced S. aureus ATCC 25923 biofilm formation by 55% and cell viability by 57% to 68% at 12 × MIC. Furthermore, cytotoxicity studies using the brine shrimp lethality test demonstrated low cytotoxicity up to 6 × MIC (25% mortality rate) with an LC50 value of 639.1 µg/mL. Finally, the most active sample was incorporated into polycaprolactone (PCL) fiber mats via electrospinning, with resultant inhibition of S. aureus species. This research underscores the potential of endophytic fungi from Australian plants as sources of substances effective against common wound pathogens. Further exploration of the responsible compounds and their mechanisms could facilitate the development of wound dressings effective against MRSA and innovative biofilm-resistant electrospun fibers, contributing to the global efforts to combat AMR.

Despite its high importance for crop yield prediction and monitoring, early-season crop mapping is severely hampered by the absence of timely ground truth. To cope with this issue, this study aims at evaluating the capability of PRISMA hyperspectral satellite images compared with Sentinel-2 multispectral imagery to produce early- and in-season crop maps using consolidated machine and deep learning algorithms. Results show that the accuracy of crop type classification using Sentinel-2 images is meaningfully poor compared with PRISMA (14% in overall accuracy (OA)). The 1D-CNN algorithm, with 89%, 91%, and 92% OA for winter, summer, and perennial cultivations, respectively, shows for the PRISMA images the highest accuracy in the in-season crop mapping and the fastest algorithm that achieves acceptable accuracy (OA 80%) for the winter, summer, and perennial cultivations early-season mapping using PRISMA images. Moreover, the 1D-CNN algorithm shows a limited reduction (6%) in performance, appearing to be the best algorithm for crop mapping within operational use in cross-farm applications. Machine/deep learning classification algorithms applied on the test fields cross-scene demonstrate that PRISMA hyperspectral time series images can provide good results for early- and in-season crop mapping.