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Pervasive and recurrent hybridization prevents inbreeding in Europe’s most threatened seabird
Hybridization is a double-edged sword: While it can erode distinct evolutionary lineages, it can also introduce genetic diversity and adaptive potential into dwindling populations. In the Critically Endangered Balearic shearwater ( Puffinus mauretanicus ), this dilemma is exacerbated by a limited understanding of the extent and consequences of hybridization with the Yelkouan shearwater ( Puffinus yelkouan ). This knowledge gap has limited the scope of science-based conservation strategies to avoid the Balearic shearwater’s imminent extinction. Here, we investigate shearwater hybridization dynamics and their effect on genome-wide diversity in the Balearic shearwater. Divergence dating, demographic modeling, and admixture analyses suggest that these two poorly differentiated shearwater lineages have experienced recurrent episodes of divergence and widespread hybridization during glacial cycles. Selection scans reveal a 500 kb region hosting an adaptive haplotype that potentially underpins interspecific differences in migratory behavior and which has been repeatedly introgressed between the two taxa. Moreover, we show that interspecific gene flow has prevented increases in homozygosity and genetic load, and through forward simulations, we illustrate how it can buffer the negative effects of future population bottlenecks in the Balearic shearwater. Our findings illustrate how introgression can be crucial for maintaining genetic diversity in threatened taxa and highlight the need for considering the protection of hybridization in conservation plans.
Roof collapse in a retained top coal roadway induced by high-energy seismic events: implications from a case study
Study on the influencing factors of ecological spatial grouping optimization in the huangshan region based on entropy weight topsis
This study evaluates and analyzes the influencing factors of ecological spatial configuration optimization in the Greater Huangshan Region. By identifying and assessing these factors, it aims to reveal the mechanisms underlying ecological space optimization in the area. The findings provide a theoretical foundation for promoting high-quality development and optimizing ecological spatial governance policies in the Greater Huangshan Region.An index system for ecological space configuration optimization in the Greater Huangshan Region was constructed based on the DPSIR model, and the Entropy Weight-TOPSIS method was applied to evaluate the ecological space from 2018 to 2023. From a temporal dimension, the configuration optimization of ecological space in the Greater Huangshan Region showed an upward trend from 2018 to 2023, with a significant improvement in ES levels. From a spatial dimension, there are certain differences in the group optimization level of ecological space among cities in the region, with the spatial distribution generally showing the characteristics of Anqing > Huangshan > Xuancheng > Chizhou. Although the group optimization of ES in the Greater Huangshan Region has significantly strengthened from 2018 to 2023, the ecological situation remains severe. It is necessary to accelerate socioeconomic development while actively implementing various ecological protection policies, comprehensively improving the group optimization level of ecological space in each city, and thus promoting high-quality development in the Greater Huangshan Region.
A FRET assay to monitor different structural states of human β-cardiac myosin including the interacting-heads motif
In cardiac muscle, myosin molecules exist in multiple structural states as they transit through their ATPase cycle, including an off-cycle resting or OFF-state with their catalytic heads in a folded structure known as the interacting-heads motif (IHM). The blocked head configuration (BHC) of the IHM is unusual because its light chain binding region is held in an exaggerated prestroke angle stabilized by interactions with its own S2 tail. An additional partial OFF-state, where the second head of the IHM is not folded back onto the blocked head, has been proposed, which still has the blocked head interacting with S2. Many mutations in the human β-cardiac myosin gene that cause hypertrophic cardiomyopathy are thought to destabilize (decrease the population of) the OFF-states. The effects of pathogenic mutations on the folded back structural states are often studied using indirect assays, including a single-ATP turnover assay that detects the biochemical state of myosin functionally. Here, we use a fluorescence resonance energy transfer (FRET) based sensor for direct quantification in solution of the myosin BHC state. Using the FRET sensor, we provide evidence that the myosin tail acts as an activator of the recovery stroke transition after ATP binding to poststroke state apomyosin and that BHC formation is rapid after ATP binding and depends on formation of the prestroke state. We propose that the positively charged loop 2 of the prestroke state head interacts with the Ring 2 cluster of negatively charged residues on the S2 tail to form a preBHC state that facilitates BHC state formation.
PHFuse: Unsupervised color visible and infrared image fusion with preserved hue
Developing Automatic-Labeled Topic Modeling Based on SAO Structure for Technology Analysis
Topic modeling has become essential for identifying emerging technology trends, detecting technological concepts, and forecasting advancements. This study introduces a subject-action-object (SAO) based approach to overcome the limitations of existing auto-labeling methodologies in patent documents. In particular, by utilizing the “Bag of SAO” concept, the study aims to construct topic modeling itself on an SAO basis, thereby clarifying the complex relationships within technology. Traditional auto-labeling methods often lack sufficient quantitative evaluation metrics and overlook the functional significance and hierarchical structure of technologies. To address these challenges, we propose an auto-labeling methodology that combines SAO-based topic modeling and scoring with text summarization and network analysis. The proposed model’s effectiveness was evaluated using the ROUGE score alongside others such as relevance, coverage, and discrimination, showing its ability to capture functional meanings within the technological context. To enhance interpretability, we integrated a hierarchical structure based on CPC subclasses, offering a more comprehensive view of technological development and trends. This approach is expected to improve the accuracy of topic labels while providing deeper semantic insights, contributing to more efficient technology management. This study illustrates how SAO-based auto-labeling methodologies can be applied in the field of technology management, highlighting their potential applications in technology innovation, policy-making, and industry applications. Furthermore, by integrating the SAO structure, this research is anticipated to lay the groundwork for developing more refined methodologies for technology forecasting and diagnosis in future studies. Through this, we hope to gain a clearer understanding of the directions of technological advancement and provide strategic insights for the development of new technologies.
Danicamtiv reduces myosin’s working stroke but activates the thin filament by accelerating actomyosin attachment
Heart failure is a leading cause of death worldwide, and even with current treatments, the 5-y transplant-free survival rate is only ~50 to 70%. As such, there is a need to develop new treatments for patients that improve survival and quality of life. Recently, there have been efforts to develop small molecules for heart failure that directly target components of the sarcomere, including cardiac myosin. Danicamtiv is one of these molecules; however, its direct effects on myosin’s single molecule mechanics and kinetics are not well understood. Using optical trapping techniques, stopped flow transient kinetics, and in vitro reconstitution assays, we found that danicamtiv reduces the size of cardiac myosin’s working stroke without affecting actomyosin detachment kinetics at the level of individual crossbridges. We demonstrate that danicamtiv accelerates actomyosin association kinetics, leading to increased recruitment of myosin crossbridges and subsequent thin filament activation at physiologically relevant calcium concentrations. We demonstrate important mechanistic differences with another cardiac myosin binding myotrope, omecamtiv mecarbil. Finally, we computationally model how the observed changes in mechanics and kinetics at the level of single crossbridges can contribute to increased cardiac contraction. Taken together, our results have important implications for the design of sarcomeric-targeting compounds for heart failure.
A two stage multi object tracking algorithm with transformer and attention mechanism
Nurse resilience, burnout, pandemic stress, and post-traumatic stress: A secondary analysis of a longitudinal cohort
Background It is estimated that approximately one-fifth of nurses in the United States will leave the profession by 2027 due to stress and burnout caused by the COVID-19 pandemic. It is unknown how burnout, resilience, and post-traumatic stress changed during the first two years of the COVID-19 pandemic in frontline nurses. The primary aim of this study was to evaluate how resilience, burnout, and post-traumatic stress changed in hospital-based nurses from 2020 to 2022. Secondary objectives were to describe the relationships between them and test whether burnout and resilience mediated the relationship between pandemic stress and post-traumatic stress. Methods This was a secondary analysis of a longitudinal cohort study of hospital nurses who participated in the COVID-19 Study and Registry of Healthcare and Support Personnel (CHAMPS) Registry. Changes in resilience, burnout, and post-traumatic stress (PTS) were evaluated using repeated measures ANOVA. Path analysis was conducted using multiple regressions to identify whether burnout and resilience acted as mediators between pandemic stress and post-traumatic stress. Results Thirty-two participants were included in all four waves of the longitudinal study, with a range of 32 to 740 participants across all time points. Changes in PTS were significant, while changes in burnout and resilience were not. Eighty-nine participants were available for the regression models used to answer the secondary objectives. Burnout mediated the relationship between pandemic stress and post-traumatic stress, but resilience did not. In addition, adequate protective equipment was found to be a predictor of lower pandemic stress. Conclusions Post-traumatic stress peaked in 2020 during lockdown in the United States and decreased significantly by 2022. Resilience and burnout did not change between 2020 and 2022. The results of this study can guide healthcare organizations in providing frontline healthcare workers with mental health resources, especially at the outset of a pandemic.
Efficiently quantifying dependence in massive scientific datasets using InterDependence Scores
Large-scale scientific datasets today contain tens of thousands of random variables across millions of samples (for example, the RNA expression levels of 20,000 protein-coding genes across 30 million single cells). Being able to quantify dependencies between these variables would help us discover novel relationships between variables of interest. Simple measures of dependence, such as Pearson correlation, are fast to compute, but limited in that they are designed to detect linear relationships between variables. Complex measures are known with the ability to detect any kind of dependence, but they do not readily scale to many modern datasets of interest. We introduce the InterDependence Score (IDS), a scalable measure of dependence that captures linear and various nonlinear dependencies between random variables. Our IDS algorithm is motivated by a dependence measure defined in infinite-dimensional Hilbert spaces, capable of capturing any type of dependence, and a fast (linear time) algorithm that neural networks natively implement to compute dependencies between random variables. We apply IDS to identify 1) relevant variables for predictive modeling tasks, 2) sets of words forming topics from millions of documents, and 3) sets of genes related to “gene-expression programs” in tens of millions of cells. We provide an efficient implementation that computes IDS between billions of pairs of variables across millions of samples in several hours on a single GPU. Given its speed and effectiveness in identifying nonlinear dependencies, we envision IDS will be a valuable tool for uncovering insights from scientific data.
A new medical image encryption using modular integrated logistic exponential map and multi-level Q-Sequence matrix
A standardized scoring method for measuring white cast of mineral sunscreens and improving user compliance across diverse skin tones
Introduction Using broad-spectrum sunscreen is an effective practice for preventing skin cancers caused by ultraviolet (UV) radiation. Mineral sunscreens containing zinc oxide (ZnO) and titanium dioxide (TiO2) as physical UV filters are suitable for individuals with sensitive skin or allergies to chemical UV filters. Consumer compliance with sunscreen application depends largely on its cosmetic elegance, especially regarding white cast. Despite this, there is no official method to quantify white cast and help design sunscreens for diverse skin tones. Methods To address this gap, we developed white cast scoring protocols that combine 1) inter-rater reliability (ICC) of expert graders and thirteen study volunteers ranking the white cast produced by ZnO test formulations with 2) objective CIEL*a*b* measurements determined after sunscreen application both in vivo and in vitro. Results Our findings demonstrate a significant correlation between increasing ZnO percentages and higher L* values (whiteness) resulting in a more visible white cast, as assessed by Pearson coefficient in vivo (r ≥ 0.822; p < 0.001) and Kruskal-Wallis (p < 0.0001) with Dunn’s post hoc pairwise comparisons. White cast scores for the ZnO formulations were substantially consistent across both in vivo and in vitro methodologies, with higher ZnO concentrations producing unacceptable levels of white cast. Conclusion This study provides a white cast scoring system, based on subjective white cast perception and L* values, as a quantitative tool for evaluating and refining mineral sunscreen formulations, contributing to developing more cosmetically elegant sunscreens suitable for a wide range of skin tones.
Tuning water dissociation at oxide–electrolyte interfaces with electric fields
Understanding how electric fields influence water dissociation at heterogeneous interfaces is crucial for controlling interfacial chemical reactions and advancing next-generation energy technologies. Herein, ab initio–based machine learning simulations show that even small electric field changes can significantly alter the water dissociation fraction at planar TiO 2 –electrolyte interfaces. The resulting free energy difference between undissociated and dissociated interfacial water exhibits a linear dependence on the field change with a slope of 1.97 e Å, which far exceeds the dissociation-induced dipole change of a water molecule. Employing a machine-learned collective variable to investigate the reaction statistics of thousands of water dissociation/recombination events, we find that small electric field changes exert minor effects on individual reaction energy barriers but significantly influence the populations of local configurations associated with initial states that are most favorable for reactions. These findings elucidate the pronounced impact of electric fields on interfacial water dissociation and reveal a mechanism for electric-field-controlled chemical reactions.
Correction: Climate change prediction in Saudi Arabia using a CNN GRU LSTM hybrid deep learning model in al Qassim region
Mental and physical health in persons receiving inpatient pulmonary rehabilitation treatment for post-COVID condition
Background Post-COVID condition is most commonly associated with physical symptoms such as dyspnea on exertion, difficulty in concentration, fatigue, and frailty but meta-analyses also document high rates of mental health problems such as anxiety disorders, depression, and post-traumatic stress disorder (PTSD). Methods and findings In the current study, 140 persons (66% female) receiving inpatient pulmonary rehabilitation treatment for post-COVID condition for an average of 27 days (SD = 11) completed self-report measures on mental and physical health at admission and discharge. At admission, 54%, 36%, 36%, and 14% screened positively for somatoform syndrome, generalized anxiety, depression, and PTSD, respectively. Higher pulmonary functioning related to higher self-reported physical functioning (but not to measures of mental health) at admission. Several self-reported indicators for mental and physical health improved from admission to discharge. Conclusions The current study corroborates findings about the high mental and physical burden of post-COVID condition. However, both mental and physical symptoms show partial improvement during a specialized inpatient pulmonary rehabilitation treatment.
Monoamine-induced diacylglycerol signaling rapidly accumulates Unc13 in nanoclusters for fast presynaptic potentiation
Neuromodulators control mood, arousal, and behavior by inducing synaptic plasticity via G-protein-coupled receptors. While long-term presynaptic potentiation requires structural changes, mechanisms enabling potentiation within minutes remain unclear. Using the Drosophila neuromuscular junction, we show that octopamine, the invertebrate analog of norepinephrine, potentiates evoked neurotransmitter release on the timescale of one minute via a G-protein-coupled pathway involving presynaptic OAMB receptors and phospholipase C. This fast potentiation correlates with elevated signals of the release factor Unc13A and the scaffolding protein Bruchpilot. Live, single-molecule imaging of endogenously tagged Unc13 revealed its instantly reduced motility and increased concentration in synaptic nanoclusters with potentiation. Presynaptic knockdown of Unc13A fully blocked fast potentiation. Moreover, deleting its N-terminal localization sequence mislocalized the protein fragment to the cytosol, but still allowed for rapid plasma membrane recruitment by diacylglycerol (DAG) analog phorbol esters and octopamine, implicating a role of more C-terminal domains. A point mutation of endogenous Unc13 in its DAG-binding C1 domain blocked plasticity-induced nanoscopic enrichment and synaptic potentiation. The mutation increased basal neurotransmission but reduced Unc13 levels, revealing a gain of function and potential homeostatic compensation. The mutation also blocked phorbol ester–induced potentiation, decreased the calcium sensitivity of neurotransmission, and caused short-term synaptic depression. Homeostatic potentiation induced by postsynaptic receptor block mirrored octopamine-induced Unc13 recruitment and required presynaptic OAMB receptors, indicating overlapping machinery. Thus, rapid Unc13 immobilization and nanoscale compaction are salient features of fast presynaptic potentiation.
Advanced smart human activity recognition system for disabled people using artificial intelligence with snake optimizer techniques
Comparison of virtual reality and real environment effects on perception of height in healthy individuals
Purpose The aim of this study was to evaluate the effects of mechanically stimulated sacculus on our height perception. Methods Between 1.09.2022 and 30.06.2023, 52 volunteers, 27 women and 25 men, aged 20–50 years, were included in the study. Pure tone audiometry test, acoustic immittance, vestibular evoked myogenic potentials (VEMP) and mini mental tests (MMSE) were performed on these individuals. Afterwards, height estimations were made by looking from top to bottom and from bottom to top using mechanical stimulation in real environment and elevator simulation in virtual reality (VR) environment. Participants were informed in writing with an informed consent form and their signed consent was obtained. Results The averages of the height estimates made in the VR environment and in the real environment were compared with each other and no significant difference was observed (p > 0.05). When the height estimations made in the VR environment and in the real environment were compared with the current height value, a significant difference was observed only in the height estimation made by looking from the bottom up in the VR environment, and it was found to be higher than the current height (p < 0.05). When the height estimation values in the VR environment and in the real environment were compared with the place where height estimation was started, no significant difference was observed (p > 0.05). Conclusion In our study, the effect of the mechanical effect of the saccule on the height perception was investigated, and no significant difference was obtained in the height estimates made in the VR environment and in the real environment. Mechanical stimulation of the saccule is thought to have a limited role in height perception.
Macrophage TBK1 signaling drives the development and outgrowth of breast cancer brain metastasis
Tumor-associated macrophages (TAMs) are the predominant immune cells in the tumor microenvironment that promote breast cancer brain metastasis (BCBM). Here, we identify TANK-binding kinase (TBK1) as a critical signaling molecule enriched and activated in TAMs of BCBM tumors, playing an indispensable role in BCBM development and metastatic outgrowth in the brain. Mechanistically, BCBM cell-secreted matrix metalloproteinase 1 binds to protease-activated receptor 1 and integrin αVβ5 on macrophages, leading to TBK1 activation mediated by the nuclear factor-kappa B pathway. Reciprocally, TBK1-regulated TAMs produce granulocyte-macrophage colony-stimulating factor (GM-CSF) to drive breast cancer cell epithelial–mesenchymal transition, migration, and invasion, ultimately contributing to BCBM development and brain metastatic outgrowth. Inhibition of TBK1 signaling in TAMs or GM-CSF receptor in cancer cells impedes BCBM development and brain metastatic outgrowth. Correspondingly, the TBK1–GM-CSF signaling axis correlates with lower overall survival in patients with BCBM. Thus, TBK1-mediated tumor-TAM symbiotic interaction provides a promising therapeutic target for patients with BCBM.