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Abstract Antarctic biodiversity is affected by seasonal sea-ice dynamics driving basal resource availability. To (1) determine the role of intraspecific dietary variability in structuring benthic food webs sustaining Antarctic biodiversity, and (2) understand how food webs and the position of topologically central species vary with sea-ice cover, single benthic individuals’ diets were studied by isotopic analysis before sea-ice breakup and afterwards. Isotopic trophospecies (or Isotopic Trophic Units) were investigated and food webs reconstructed using Bayesian Mixing Models. As nodes, these webs used either ITUs regardless of their taxonomic membership (ITU-webs) or ITUs assigned to species (population-webs). Both were compared to taxonomic-webs based on taxa and their mean isotopic values. Higher resource availability after sea-ice breakup led to simpler community structure, with lower connectance and linkage density. Intra-population diet variability and compartmentalisation were crucial in determining community structure, showing population-webs to be more complex, stable and robust to biodiversity loss than taxonomic-webs. The core web, representing the minimal community ‘skeleton’ that expands opportunistically while maintaining web stability with changing resource availability, was also identified. Central nodes included the sea-urchin Sterechinus neumayeri and the bivalve Adamussium colbecki, whose diet is described in unprecedented detail. The core web, compartmentalisation and topologically central nodes represent crucial factors underlying Antarctica’s rich benthic food web persistence.

Background: Prior reports have demonstrated underutilization of bystander cardiopulmonary resuscitation (CPR) and automated external defibrillator (AED) use in patients with witnessed out-of-hospital cardiac arrest (OHCA) in Connecticut. This study aimed to identify community-level risk factors that contribute to low rates of bystander intervention to improve statewide OHCA outcomes. Methods: We analyzed 2,789 adult patients with witnessed, non-traumatic OHCA submitted to the Connecticut Cardiac Arrest Registry to Enhance Survival (CARES) between 2013–2022. Patients were grouped by zip code, and associated municipal characteristics were acquired from 2022 United States Census Bureau data. Use of bystander CPR, attempted bystander AED defibrillation, and patient survival with favorable neurological function were determined for 19 of the 20 most populous cities and towns. Pearson correlation tests and linear regression were used to determine associations between OHCA treatment and outcomes with population size, racial/ethnic demographics, language use, income, and educational level. Results: Bystander CPR was lower in municipalities with population size > 100,000 and in communities where > 40% of residents are non-English-speaking. AED use was also lower in these municipalities, as well as those with per capita incomes < $40,000 or > 1/3 Hispanic residents. Communities with populations > 100,000, > 40% non-English-speaking, per capita income < $40,000, and > 1/3 Hispanic residents were all associated with lower survival rates. Conclusions: OHCA pre-hospital treatment and outcomes vary significantly by municipality in Connecticut. Community outcomes might be improved by specifically targeting urban population centers and Hispanic communities with culturally sensitive, low, or no-cost CPR and AED educational programs, using instructional languages other than English.

Squash is a sport where referee decisions are essential to the game. However, these decisions are very subjective in nature. Disputes, both from the players and the audience, regularly occur because the referee made a controversial call. In this study, we propose automating the referee decision process through machine learning. We trained neural networks to predict such decisions using data from 400 referee decisions acquired through extensive video footage reviewing and labeling. Six positional values were extracted, including the attacking player’s position, the retreating player’s position, the ball’s position in the frame, the ball’s projected first bounce, the ball’s projected second bounce, and the attacking player’s racket head position. We calculated nine additional distance values, such as the distance between players and the distance from the attacking player’s racket head to the ball’s path. Models were trained on Wolfram Mathematica and Python using these values. The best Wolfram Mathematica model and the best Python model achieved accuracies of 86% ± 3.03% and 85.2% ± 5.1%, respectively. These accuracies surpass 85%, demonstrating near-human performance. Our model has great potential for improvement as it is currently trained with limited, unbalanced data (400 decisions) and lacks crucial data points such as time and speed. The performance of our model is almost surely going to improve significantly with a larger training dataset. Unlike human referees, machine learning models follow a consistent standard, have unlimited attention spans, and make decisions instantly. If the accuracy is improved in the future, the model can potentially serve as an extra refereeing official for both professional and amateur squash matches. Both the analysis of referee decisions in squash and the proposal to automate the process using machine learning is unique to this study.

Attitudes to marriage, sexual morality, and parenthood are currently undergoing substantial cultural transformation, noticeable also in mission countries. For this reason, the Catholic Church has in recent years treated pastoral care of married couples and families as an urgent concern. The article presents results of empirical research conducted among a selected group of Catholics in Kenya as well as conclusions and postulates for Catholic formation and pastoral care of families. It indicates a need for education that would help individuals overcome unethical conjugal and familial attitudes. It also emphasizes the value of positive attitudes to parenthood present in African culture and accentuates clear progress in rejecting a conviction that marriage without children is pointless. The text points out urgent need for formative and pastoral work to eradicate corporal punishment of children and indicates challenges related to the education of women.

Abstract Crop disease detection and management is critical to improving productivity, reducing costs, and promoting environmentally friendly crop treatment methods. Modern technologies, such as data mining and machine learning algorithms, have been used to develop automated crop disease detection systems. However, centralized approach to data collection and model training induces challenges in terms of data privacy, availability, and transfer costs. To address these challenges, federated learning appears to be a promising solution. In this paper, we explored the application of federated learning for crop disease classification using image analysis. We developed and studied convolutional neural network (CNN) models and those based on attention mechanisms, in this case vision transformers (ViT), using federated learning, leveraging an open access image dataset from the “PlantVillage” platform. Experiments conducted concluded that the performance of models trained by federated learning is influenced by the number of learners involved, the number of communication rounds, the number of local iterations and the quality of the data. With the objective of highlighting the potential of federated learning in crop disease classification, among the CNN models tested, ResNet50 performed better in several experiments than the other models, and proved to be an optimal choice, but also the most suitable for a federated learning scenario. The ViT_B16 and ViT_B32 Vision Transformers require more computational time, making them less suitable in a federated learning scenario, where computational time and communication costs are key parameters. The paper provides a state-of-the-art analysis, presents our methodology and experimental results, and concludes with ideas and future directions for our research on using federated learning in the context of crop disease classification.

Abstract The skeleton forms from multipotent human mesenchymal stem cells (hMSCs) competent to commit to specific lineages. Long noncoding RNAs (lncRNAs) have been identified as key epigenetic regulators of tissue development. However, regulation of osteogenesis by lncRNAs as mediators of commitment to the bone phenotype is largely unexplored. We focused on LINC01638, which is highly expressed in hMSCs and has been studied in cancers, but not in regulating osteogenesis. We demonstrated that LINC01638 promotes initiation of the osteoblast phenotype. Our findings reveal that LINC01638 is present at low levels during the induction of osteoblast differentiation. CRISPRi knockdown of LINC01638 in MSCs prevents osteogenesis and alkaline phosphatase expression, inhibiting osteoblast differentiation. This resulted in decreased MSC growth rate, accompanied by double-strand breaks, DNA damage, and cell senescence. Transcriptome profiling of control and LINC01638-depleted hMSCs identified > 2000 differentially expressed mRNAs related to cell cycle, cell division, spindle formation, DNA repair, and osteogenesis. Using ChIRP-qPCR, molecular mechanisms of chromatin interactions revealed the LINC01638 locus (Chr 22) includes many lncRNAs and bone-related genes. These novel findings identify the obligatory role for LINC01638 to sustain MSC pluripotency regulating osteoblast commitment and growth, as well as for physiological remodeling of bone tissue.

Quercus ilex L., an evergreen oak species typical of the western and central Mediterranean basin, is facing decline and dieback episodes due to the increase in the severity and frequency of heat waves and drought events. Studying xylogenesis (the wood formation process) is crucial for understanding how trees respond with their secondary growth to environmental conditions and stress events. This study aimed to characterize the wood formation dynamics of Quercus ilex and their relationship with the meteorological conditions in an area experiencing prolonged drought periods. Cambial activity and xylem cell production were monitored during the 2019 and 2020 growing seasons in a Q. ilex forest located at the Vesuvius National Park (southern Italy). The results highlighted the significant roles of temperature and solar radiation in stimulating xylogenesis. Indeed, the correlation tests revealed that temperature and solar radiation positively influenced growth and cell development, while precipitation had an inhibitory effect on secondary wall formation. The earlier cell maturation in 2020 compared to 2019 underscored the impact of global warming trends. Overall, the trees studied demonstrated good health, growth and adaptability to local environmental fluctuations. This research provides novel insights into the intra-annual growth dynamics of this key Mediterranean species and its adaptation strategies to climatic variability, which will be crucial for forest management in the context of climate change.

Pore-scale flow velocity is an essential parameter in determining transport through porous media, but it is often miscalculated. Researchers use a static porosity value to relate volumetric or superficial velocities to pore-scale flow velocities. We know this modeling assumption to be an oversimplification. The variable fraction of porosity conducive to flow, what we define as hydrodynamic porosity, θmobile, exhibits a quantifiable dependence on the Reynolds number (i.e., pore-scale flow velocity) in the Laminar flow regime. This fact remains largely unacknowledged in the literature. In this work, we quantify the dependence of θmobile on the Reynolds number via numerical flow simulation at the pore scale for rectangular pores of various aspect ratios, i.e., for highly idealized dead-end pore spaces. We demonstrate that, for the chosen cavity geometries, θmobile decreases by as much as 42% over the Laminar flow regime. Moreover, θmobile exhibits an exponential dependence on the Reynolds number, Re = R. The fit quality is effectively perfect, with a coefficient of determination (R2) of approximately 1 for each set of simulation data. Finally, we show that this exponential dependence can be easily fitted for pore-scale flow velocity through use of only a few Picard iterations, even with an initial guess that is 10 orders of magnitude off. Not only is this relationship a more accurate definition of pore-scale flow velocity, but it is also a necessary modeling improvement that can be easily implemented. In the companion paper (Part 2), we build upon the findings reported here and demonstrate their applicability to media with other pore geometries: rectangular and non-rectangular cavities (circular and triangular).

Phenology monitoring allows a better understanding of forest functioning and climate impacts. Satellite indicators are used to upscale ground phenological observations, but often differential responses are observed, and data availability can be limited. In view of climate impacts, new tools capable to detect rapid phenological changes and to work at single species level are needed. This research compares indices derived by the TreeTalker© (TT + ) below canopy upward-looking spectral data and Sentinel 2 satellite data, used to assess the phenological behavior and changepoints in several European beech forests. Overall, a mismatch between the information derived by the two sensor types is evidenced, with main differences in: start/end and length of season and phenology changepoints; larger variability captured by TT + with respect to Sentinel 2 especially in the leaf on period; mixed signal response from multiple vegetation layers in Sentinel 2 data. The complementarity of satellite and TT + indices allow exploring the phenological responses from different vegetation layers. TT + higher temporal resolution demonstrates precision in capturing the phenological changepoints in beech forests, especially if satellite image availability is limited by cloud cover and leads to miss critical phenological dates. The best settings for TT + data collection and the advantages to have two spectral data sources for improved forest phenology monitoring are also commented. The TT+, collecting additional tree parameters, can be a valuable tool for an integrated monitoring system based on spectral signals from above and below the canopy, at high temporal frequency and high spatial resolution.

Abstract Intra-Annual Density Fluctuations (IADFs) are an important wood functional trait that determine trees’ ability to adapt to climatic changes. Here, we use a large tree-ring database of 11 species from 89 sites across eight European countries, covering a climatic gradient from the Mediterranean to northern Europe, to analyze how climate variations drive IADF formation. We found that IADF occurrence increases nonlinearly with ring width in both gymnosperms and angiosperms and decreases with altitude and age. Recently recorded higher mean annual temperatures facilitate the formation of IADFs in almost all the studied species. Precipitation plays a significant role in inducing IADFs in species that exhibit drought tolerance capability, and a growth pattern known as bimodal growth. Our findings suggest that species with bimodal growth patterns growing in western and southern Europe will form IADFs more frequently, as an adaptation to increasing temperatures and droughts.

Reliable testing of aviation components depends on the quality and configuration flexibility of measurement systems. In a typical approach to test instrumentation, there are tens or hundreds of sensors on the test head and test facility, which are connected by wires to measurement cards in control cabinets. The preparation of wiring and the setup of measurement systems are laborious tasks requiring diligence. The use of smart wireless transducers allows for a new approach to test preparation by reducing the number of wires. Moreover, additional functionalities like data processing, alarm-level monitoring, compensation, or self-diagnosis could improve the functionality and accuracy of measurement systems. A combination of low power consumption, wireless communication, and wireless power transfer could speed up the test-rig instrumentation process and bring new test possibilities, e.g., long-term testing of moving or rotating components. This paper presents the design of a wireless smart transducer dedicated for use with sensors typical of aviation laboratories such as thermocouples, RTDs (Resistance Temperature Detectors), strain gauges, and voltage output integrated sensors. The following sections present various design requirements, proposed technical solutions, a study of battery and wireless power supply possibilities, assembly, and test results. All presented tests were carried out in the Components Test Laboratory located at the Łukasiewicz Research Network–Institute of Aviation.

What are the differences in how public and private institutions of higher education, with religious schools as a subset of private colleges and universities, approach on-campus protests in a framework of civic engagement? Unfortunately, public, private, and religious schools have all restricted opportunities of speech, assembly, and protest, despite in many cases state and federal courts ruling that this is against the law. With the goal of increasing the civic capacities of students at all institutions of higher education, we propose a mechanism of partial revocation of tax exemptions at universities that do not currently uphold a robust understanding of civic engagement opportunities for all students, which will apply to any college or university receiving federal funding, consistent with the constitutional tradition of free speech still exemplified by Brandenburg v. Ohio and the “national policy” test of Bob Jones University vs. United States. In doing so, we build on the critique of exemptions in the recent work of Vincent Phillip Munoz on religious liberty. By opting only for incentives and by not even incentivizing private institutions that continue to restrict civic engagement but that do not accept federal dollars, we affirm and support a mutually beneficial ongoing dialogue among public, private, and religious schools. This dialogue, as it is sharpened and maintained in place by our recommended policies, is also consistent with pluralism as conceptualized by Jacob Levy.

In recent years, several drought events hit Poland, affecting its forests. In Opole, Poland, tons of Pinus sylvestris L. deadwood is removed every year due to drought. Understanding the physiological mechanisms underlying tree vulnerability to drought, and tree responses, is important to develop forest management strategies to face the ongoing climate change. This research provides comprehensive local-scale analyses of the sensitivity of healthy and declining trees to drought. We used dendrochronology and stable isotope analysis to compare five healthy and five declining trees. The analysis focused particularly on comparisons of basal area increment (BAI), δ13C, and intrinsic water-use efficiency (iWUE), as well as tree resistance, resilience, and recovery in response to drought events and sensitivity to selected meteorological parameters. We observed a significant reduction in BAI values in declining trees after 2000. Fifteen years later, the reduction was also visible in the iWUE values of these trees. Despite similar δ13C chronology patterns, declining trees showed higher δ13C correlations with meteorological parameters. We have shown that dendrochronology enables early detection of poor forest health conditions. Differences in iWUE chronologies occurring in recent years suggest that trees of both groups have chosen different adaptive strategies to cope with drought stress.

A l’automne de l’année 1992, les espaces géographiques en proie à l’instabilité sont le plus souvent des zones grises, des régions trans-étatiques exposées à une guerre inter ou intra-étatiques ainsi qu’à la mafieurisation des sociétés, des espaces géographiques qui sont confrontés à des crises flagrantes ou latentes lors de conflits gelés et deviennent peu à peu de véritables espaces de non-droit. C’est le cas de la République Démocratique du Congo.

Acute kidney injury (AKI) is a serious health concern with high morbidity and high mortality worldwide. Recently, sexual dimorphism has become increasingly recognized as a factor influencing the severity of the disease. This study explores the gender-specific renoprotective pathways in αMUPA transgenic mice subjected to AKI. αMUPA transgenic male and female mice were subjected to ischemia–reperfusion (I/R)-AKI in the presence or absence of orchiectomy, oophorectomy, and L-NAME administration. Blood samples and kidneys were harvested 48 h following AKI for the biomarkers of kidney function, renal injury, inflammatory response and intracellular pathway sensing of or responding to AKI. Our findings show differing responses to AKI, where female αMUPA mice were remarkably protected against AKI as compared with males, as was evident by the lower SCr and BUN, normal renal histologically and attenuated expression of NGAL and KIM-1. Moreover, αMUPA females did not show a significant change in the renal inflammatory and fibrotic markers following AKI as compared with wild-type (WT) mice and αMUPA males. Interestingly, oophorectomized females eliminated the observed resistance to renal injury, highlighting the central protective role of estrogen. Correspondingly, orchiectomy in αMUPA males mitigated their sensitivity to renal damage, thereby emphasizing the devastating effects of testosterone. Additionally, treatment with L-NAME proved to have significant deleterious impacts on the renal protective mediators, thereby underscoring the involvement of eNOS. In conclusion, gender-specific differences in the response to AKI in αMUPA mice include multifaceted and keen interactions between the sex hormones and key biochemical mediators (such as estrogen, testosterone and eNOS). These novel findings shed light on the renoprotective pathways and mechanisms, which may pave the way for development of therapeutic interventions.

Patterned membrane surfaces offer a hydrodynamic approach to mitigating concentration polarization and subsequent surface fouling. However, when subjected to steady crossflow conditions, surface patterns promote particle accumulation in the recirculation zones of cavity-like spaces. In order to resolve this issue, we numerically subject a two-dimensional, patterned membrane surface to a rapidly pulsed crossflow. When combined with cavity-like spaces, such as the valleys of membrane surface patterns, a rapidly pulsed flow generates mixing mechanisms (i.e., the deep sweep and the vortex ejection) and disrupts recirculation zones. In only four pulses, we demonstrate the ability of these mechanisms to remove over half of the particles trapped in recirculation zones via massless particle tracking studies (i.e., numerical integration of the simulated velocity field). The results of this work suggest that when combined with a rapidly pulsed inlet flow, patterned membrane surfaces can not only alleviate concentration polarization and the surface fouling that follows but also reduce the need for traditional cleaning methods that require operational downtime and often involve the use of abrasive chemical agents.

Aviation testing is intrinsically connected with rotary telemetry, which enables engineers to measure and verify parameters of high-speed aircraft engines components during laboratory testing. The main purpose of this article is to propose new design concept of smart telemetry module for temperature measurements, which could be easily adapted to various demands of high-speed rotary components tests and is more handful, functional and affordable than other solutions on the market. The result of the work is a telemetry system in form of light weight, PCB-based, wireless powered, smart transducer. Article presents state of art analysis, design and manufacturing steps, test results and conclusions.

Interactions between clouds, aerosol, and precipitation are crucial aspects of weather and climate. The simple Koren–Feingold conceptual model is important for providing deeper insight into the complex aerosol–cloud–precipitation system. Recently, artificial neural networks (ANNs) and physics-informed neural networks (PINNs) have been used to study multiple dynamic systems. However, the Koren–Feingold model for aerosol–cloud–precipitation interactions has not yet been studied with either ANNs or PINNs. It is challenging for pure data-driven models, such as ANNs, to accurately predict and reconstruct time series in a small data regime. The pure data-driven approach results in the ANN becoming a “black box” that limits physical interpretability. We demonstrate how these challenges can be overcome by combining a simple ANN with physical laws into a PINN model (not purely data-driven, good for the small data regime, and interpretable). This paper is the first to use PINNs to learn about the original and modified Koren–Feingold models in a small data regime, including external forcings such as wildfire-induced aerosols or the diurnal cycle of clouds. By adding external forcing, we investigate the effects of environmental phenomena on the aerosol–cloud–precipitation system. In addition to predicting the system’s future, we also use PINN to reconstruct the system’s past: a nontrivial task because of time delay. So far, most research has focused on using PINNs to predict the future of dynamic systems. We demonstrate the PINN’s ability to reconstruct the past with limited data for a dynamic system with nonlinear delayed differential equations, such as the Koren–Feingold model, which remains underexplored in the literature. The main reason that this is possible is that the model is non-diffusive. We also demonstrate for the first time that PINNs have significant advantages over traditional ANNs in predicting the future and reconstructing the past of the original and modified Koren–Feingold models containing external forcings in the small data regime. We also show that the accuracy of the PINN is not sensitive to the value of the regularization factor (λ), a key parameter for the PINN that controls the weight for the physics loss relative to the data loss, for a broad range (from λ=1×103 to λ=1×105).

Metachrony is defined as coordinated asynchronous movement throughout multiple appendages, such as the cilia of cells and swimmerets of crustaceans. Used by species of crustaceans and microscopic cells to move through fluid, the process of metachronal propulsion was investigated. A rigid crustacean model with paddles moving in symmetric strokes was created to simulate metachronal movement. Coupled with the surrounding fluid domain, the immersed boundary method was employed to analyze the fluid–structure interactions. To explore the effect of a nonlinear morphology on the efficiency of metachronal propulsion, a range of crustacean body shapes was generated and simulated, from upward curves to downward curves. The highest propulsion velocity was found to be achieved when the crustacean model morphology was a downward curve, specifically a parabola of leading coefficient k = −0.4. This curved morphology resulted in a 4.5% higher velocity when compared to the linear model. As k deviated from −0.4, the propulsion velocity decreased with increasing magnitude, forming a concave downward trend. The impact of body shape on propulsion velocity is shown by how the optimal velocity with k = −0.4 is 71.5% larger than the velocity at k = 1. Overall, this study suggests that morphology has a significant impact on metachronal propulsion.

Understanding public opinion on ChatGPT is crucial for recognizing its strengths and areas of concern. By utilizing natural language processing (NLP), this study delves into tweets regarding ChatGPT to determine temporal patterns, content features, and topic modeling and perform a sentiment analysis. Analyzing a dataset of 500,000 tweets, our research shifts from conventional data science tools like Python and R to exploit Wolfram Mathematica’s robust capabilities. Additionally, with the aim of solving the problem of ignoring semantic information in the LDA model feature extraction, a synergistic methodology entwining LDA, GloVe embeddings, and K-Nearest Neighbors (KNN) clustering is proposed to categorize topics within ChatGPT-related tweets. This comprehensive strategy ensures semantic, syntactic, and topical congruence within classified groups by utilizing the strengths of probabilistic modeling, semantic embeddings, and similarity-based clustering. While built-in sentiment classifiers often fall short in accuracy, we introduce four transfer learning techniques from the Wolfram Neural Net Repository to address this gap. Two of these techniques involve transferring static word embeddings, “GloVe” and “ConceptNet”, which are further processed using an LSTM layer. The remaining techniques center on fine-tuning pre-trained models using scantily annotated data; one refines embeddings from language models (ELMo), while the other fine-tunes bidirectional encoder representations from transformers (BERT). Our experiments on the dataset underscore the effectiveness of the four methods for the sentiment analysis of tweets. This investigation augments our comprehension of user sentiment towards ChatGPT and emphasizes the continued significance of exploration in this domain. Furthermore, this work serves as a pivotal reference for scholars who are accustomed to using Wolfram Mathematica in other research domains, aiding their efforts in text analytics on social media platforms.

Biological invasions in fresh waters cause biodiversity loss and impairment of ecosystem functioning. Many freshwater invasive species are fish, including the largemouth bass Micropterus salmoides, which is considered one of the 100 worst invasive species in the world. Fast individual growth rates, high dispersal ability, ecological tolerance, and trophic plasticity are among the characteristics contributing to its success. The negative impact of M. salmoides on littoral fish communities is believed to be mitigated by habitat structural complexity resulting from aquatic vegetation and coarse woody debris, while the main limits on its spread seem to be strong water flows and high turbidity, which impairs visual predation. Together with the human overexploitation of its potential fish antagonists, habitat alteration could result in M. salmoides having seriously detrimental effects on native biodiversity. The purpose of this study is to critically review the life history and ecology of M. salmoides, its impact on ecosystems outside North America, and the effects of anthropogenic activities on its spread. This will highlight environmental factors that favor or limit its invasive success, helping to identify management measures that might mitigate its negative effects on freshwater biodiversity.

Despite the high prevalence of acute kidney injury (AKI), the therapeutic approaches for AKI are disappointing. This deficiency stems from the poor understanding of the pathogenesis of AKI. Recent studies demonstrate that αMUPA, alpha murine urokinase-type plasminogen activator (uPA) transgenic mice, display a cardioprotective pathway following myocardial ischemia. We hypothesize that these mice also possess protective renal pathways. Male and female αMUPA mice and their wild type were subjected to 30 min of bilateral ischemic AKI. Blood samples and kidneys were harvested 48 h following AKI for biomarkers of kidney function, renal injury, inflammatory response, and intracellular pathways sensing or responding to AKI. αMUPA mice, especially females, exhibited attenuated renal damage in response to AKI, as was evident from lower SCr and BUN, normal renal histology, and attenuated expression of NGAL and KIM-1. Notably, αMUPA females did not show a significant change in renal inflammatory and fibrotic markers following AKI as compared with wild-type (WT) mice and αMUPA males. Moreover, αMUPA female mice exhibited the lowest levels of renal apoptotic and autophagy markers during normal conditions and following AKI. αMUPA mice, especially the females, showed remarkable expression of PGC1α and eNOS following AKI. Furthermore, MUPA mice showed a significant elevation in renal leptin expression before and following AKI. Pretreatment of αMUPA with leptin-neutralizing antibodies prior to AKI abolished their resistance to AKI. Collectively, the kidneys of αMUPA mice, especially those of females, are less susceptible to ischemic I/R injury compared to WT mice, and this is due to nephroprotective actions mediated by the upregulation of leptin, eNOS, ACE2, and PGC1α along with impaired inflammatory, fibrotic, and autophagy processes.

The Mediterranean basin is an area particularly exposed to fire risk due to its climate and fire-prone vegetation. In recent decades, the frequency and intensity of wildfires increased, leading to negative effects on forests, such as a decrease in tree growth or an increase in tree mortality, producing a relevant loss of carbon sequestration ecosystem service. This study of the impacts of fires on forests is fundamental for planning adequate forest management strategies aimed at recovering and restoring the affected areas. In this framework, our research delves into the effects of a forest fire that, in 2017, affected a forest of black pine (Pinus nigra Arnold) in Central Italy. Combining satellite and terrestrial analyses, this study evaluated the impact of the fire on tree growth, water use efficiency and carbon sequestration capacity. Our findings highlight the importance of using remote sensing for the accurate identification of fire-affected areas and precise planning of ground-based activities. However, the integration of satellite data with forest surveys and sampling has proven crucial for a detailed understanding of fire’s effects on trees. Dendrochronology and stable isotopes have revealed the post-fire growth decline and altered water usage of defoliated trees. Furthermore, the quantification of CO2 sequestration highlighted a significant reduction in carbon uptake by damaged trees, with severe implications for this ecosystem service.

Abstract Bone formation requires osteogenic differentiation of multipotent mesenchymal stromal cells (MSCs) and lineage progression of committed osteoblast precursors. Osteogenic phenotype commitment is epigenetically controlled by genomic (chromatin) and non-genomic (non-coding RNA) mechanisms. Control of osteogenesis by long non-coding RNAs remains a largely unexplored molecular frontier. Here, we performed comprehensive transcriptome analysis at early stages of osteogenic cell fate determination in human MSCs, focusing on expression of lncRNAs. We identified a chromatin-bound lncRNA (MIR181A1HG) that is highly expressed in self-renewing MSCs. MIR181A1HG is down-regulated when MSCs become osteogenic lineage committed and is retained during adipogenic differentiation, suggesting lineage-related molecular functions. Consistent with a key role in human MSC proliferation and survival, we demonstrate that knockdown of MIR181A1HG in the absence of osteogenic stimuli impedes cell cycle progression. Loss of MIR181A1HG enhances differentiation into osteo-chondroprogenitors that produce multiple extracellular matrix proteins. RNA-seq analysis shows that loss of chromatin-bound MIR181A1HG alters expression and BMP2 responsiveness of skeletal gene networks (e.g., SOX5 and DLX5). We propose that MIR181A1HG is a novel epigenetic regulator of early stages of mesenchymal lineage commitment towards osteo-chondroprogenitors. This discovery permits consideration of MIR181A1HG and its associated regulatory pathways as targets for promoting new bone formation in skeletal disorders.

Quercus ilex L., an evergreen oak species typical of the western and central Mediterranean basin, is facing decline and dieback episodes due to the increase in the severity and frequency of heat waves and drought events. Studying xylogenesis (the wood formation process) is crucial for understanding how trees respond with their secondary growth to environmental conditions and stress events. This study aimed to characterize the wood formation dynamics of Quercus ilex and their relationship with the meteorological conditions in an area experiencing prolonged drought periods. Cambial activity and xylem cell production were monitored during the 2019 and 2020 growing seasons in a Q. ilex forest located at the Vesuvius National Park (southern Italy). The results highlighted the significant roles of temperature and solar radiation in stimulating xylogenesis. Indeed, the correlation tests revealed that temperature and solar radiation positively influenced growth and cell development, while precipitation had an inhibitory effect on secondary wall formation. The earlier cell maturation in 2020 compared to 2019 underscored the impact of global warming trends. Overall, the trees studied demonstrated good health, growth and adaptability to local environmental fluctuations. This research provides novel insights into the intra-annual growth dynamics of this key Mediterranean species and its adaptation strategies to climatic variability, which will be crucial for forest management in the context of climate change. [ABSTRACT FROM AUTHOR]

In this work, we build upon our previous finding that hydrodynamic porosity is an exponential function of pore-scale flow velocity (or interstitial Reynolds number). We previously discovered this relationship for media with a square cavity geometry—a highly idealized case of the dead-ended pore spaces in a porous medium. Thus, we demonstrate the applicability of this relationship to media with other cavity geometries. We do so by applying our previous analysis to rectangular and non-rectangular cavity geometries (i.e., circular, and triangular). We also study periodic flow geometries to determine the effect of upstream cavities on those downstream. We show that not only does our exponential relationship hold for media with a variety of cavity geometries, but it does so almost perfectly with a coefficient of determination (R2) of approximately one for each new set of simulation data. Given this high fit quality, it is evident that the exponential relationship we previously discovered is applicable to most, if not all, unwashed media. [ABSTRACT FROM AUTHOR]

Congestive heart failure (CHF) is often associated with impaired kidney function. Over- activation of the renin–angiotensin–aldosterone system (RAAS) contributes to avid salt/water retention and cardiac hypertrophy in CHF. While the deleterious effects of angiotensin II (Ang II) in CHF are well established, the biological actions of angiotensin 1-7 (Ang 1-7) are not fully characterized. In this study, we assessed the acute effects of Ang 1-7 (0.3, 3, 30 and 300 ng/kg/min, IV) on urinary flow (UF), urinary Na+ excretion (UNaV), glomerular filtration rate (GFR) and renal plasma flow )RPF) in rats with CHF induced by the placement of aortocaval fistula. Additionally, the chronic effects of Ang 1-7 (24 µg/kg/h, via intra-peritoneally implanted osmotic minipumps) on kidney function, cardiac hypertrophy and neurohormonal status were studied. Acute infusion of either Ang 1-7 or its agonist, AVE 0991, into sham controls, but not CHF rats, increased UF, UNaV, GFR, RPF and urinary cGMP. In the chronic protocols, untreated CHF rats displayed lower cumulative UF and UNaV than their sham controls. Chronic administration of Ang 1-7 and AVE 0991 exerted significant diuretic, natriuretic and kaliuretic effects in CHF rats, but not in sham controls. Serum creatinine and aldosterone levels were significantly higher in vehicle-treated CHF rats as compared with controls. Treatment with Ang 1-7 and AVE 0991 reduced these parameters to comparable levels observed in sham controls. Notably, chronic administration of Ang 1-7 to CHF rats reduced cardiac hypertrophy. In conclusion, Ang 1-7 exerts beneficial renal and cardiac effects in rats with CHF. Thus, we postulate that ACE2/Ang 1-7 axis represents a compensatory response to over-activity of ACE/AngII/AT1R system characterizing CHF and suggest that Ang 1-7 may be a potential therapeutic agent in this disease state.