bluuebunny/crossref_metadata_2025 huggingface dataset:
Highly charged ion optical clocks
Authors: Schmidt Piet O. , Spieß Lukas J. , Wilzewski Alexander , Wehrheim Malte , Chen Shuying , King Steven A. , Micke Peter , Leopold Tobias , Khan Nadir , Crespo López-Urrutia José R.
Published: November 2024

Optical atomic clocks are the most precise and accurate measurement devices, reaching fractional systematic uncertainties below one part in 10−18. Their exceptional performance opens up a wide range of applications in fundamental science and technology. The extreme electronic properties of highly charged ions (HCI) make them highly sensitive probes for tests of fundamental physical theories and significantly lower sensitivity to some of the leading systematic perturbations that affect state-of-the-art optical clocks. This makes them exciting candidates for next-generation clocks. In this contribution, we will briefly review the history of optical spectroscopy of HCI and how scientific advances enabled the first coherent spectroscopy of HCI using quantum logic techniques. A first generation of optical clocks based on HCI with atom-related systematic uncertainties at the 10−18 level and below is demonstrated. Comparisons of the isotope shift between 40Ar13+ and 36Ar13+ as well as g-factor measurements with theory are interpreted as a test of quantum electrodynamic (QED) theory. This demonstrates the suitability of HCI as references for high-accuracy optical clocks and to probe for physics beyond the standard model.
Development of a laser stabilized on an ultra-stable silicon cryogenic Fabry-Perot cavity for dark matter detection
Authors: Hariri Yara , Millo Jacques , Lacroûte Clément , Barbarat Joannès , Kersalé Yann , Gillot Jonathan
Published: November 2024

Astrophysical observations suggest the existence of an unknown kind of matter in the Universe, in the frame of the ΛCDM model. The research field of dark matter covers an energy scale going from massive objects to ultra-light scalar fields, which are the focus of the present work. It is supposed that ultra-light scalar fields affect the length of objects, whereas the speed of light stays unchanged. It follows that Fabry-Perot cavities are ideal tools for ultra-light dark matter detection since the fluctuations in the length of a cavity can be detected on the frequency of the laser stabilized to it. At FEMTO-ST, we have set up an ultra-stable silicon cavity suitable for a test of detection of ultra-light dark matter in an energy range close to 10−10 eV. Our 14 cm cavity is composed of two mirrors optically bonded to an ultra-rigid spacer, with each element made in single-crystal of silicon, and cooled at 17 K in order to cancel the first order thermal expansion coefficient of the silicon spacer. The projected fractional frequency stability of the laser is 3 × 10−17, mainly limited by the thermal noise of the amorphous dielectric reflective coatings. To reach this remarkable stability, several effects have to be reduced below the thermal noise limit. While the contribution of the residual amplitude modulation is now acceptable, we are currently implementing a laser power lock with residual fluctuations lower than 3 nW and a piezoelectric-based servo loop to actively reduce the vibration noise that has to be inferior to -110 dB(m s−2)2/Hz at 1 Hz. Here, we present both the status of the development of our ultra-stable laser and the mechanical response of the cavity in the presence of ultra-light dark matter.
Turbulent cascades in the Atmospheric Boundary Layers
Authors: Wacławczyk M , Nowak J L , Vassilicos J C , Król S , Malinowski S P
Published: November 2024

We investigate the scale-by-scale budget of the turbulence kinetic energy in the Atmospheric Boundary Layer (ABL) using airborne measurements performed by the helicopter-borne measurement system HELiPOD over the Baltic sea. The available, long time series of the turbulent wind velocity, temperature and humidity allow for a detailed study of turbulence properties in the ABL over the Baltic sea. In particular, we calculate the buoyancy forcing term and the third-order velocity structure function. The buoyancy’s production of turbulence energy is only significant at the largest-scales, above L = 100m. Unlike the ABL over the Atlantic in the shallow trade-wind regime, the buoyancy is dominated by temperature variations with little contribution from water-vapour mixing ratio. At the altitudes of the order of 100m studied here, a clear Kolmogorov equilibrium is observed at scales below 100m because of the combined absence of buoyancy and apparent presence of homogeneity and stationarity at these scales.
Touch-down condition control for the bipedal spring-mass model in walking
Authors: Vejdani Hamid , Wu Albert , Geyer Hartmut , W Hurst Jonathan
Published: November 2024

Behaviors of animal bipedal locomotion can be described, in a simplified form, by the bipedal spring-mass model. The model provides predictive power, and helps us understand this complex dynamical behavior. In this paper, we analyzed a range of gaits generated by the bipedal spring-mass model during walking, and proposed a stabilizing touch-down condition for the swing leg. This policy is stabilizing against disturbances inside and outside the same energy level and requires only internal state information. In order to generalize the results to be independent of size and dimension of the system, we nondimensionalized the equations of motion for the bipedal spring-mass model. We presented the equilibrium gaits (a.k.a fixed point gaits) as a continuum on the walking state space showing how the different types of these gaits evolve and where they are located in the state space. Then, we showed the stability analysis of the proposed touch-down control policy for different energy levels and leg stiffness values. The results showed that the proposed touch-down control policy can stabilize towards all types of the symmetric equilibrium gaits. Moreover, we presented how the peak leg force changes within an energy level and as it varies due to the type of the gait since peak force is important as a measurement of injury or damage risk on a robot or animal. Finally, we presented simulations of the bipedal spring-mass model walking on level ground and rough terrain transitioning between different equilibrium gaits as the energy level of the system changes with respect to the ground height. The analysis in this paper is theoretical, and thus applicable to further our understanding of animal bipedal locomotion and the design and control of robotic systems like ATRIAS, Cassie, and Digit.
Empowering multi-source SAR Flood mapping with unsupervised learning
Authors: Jiang Xin , Zeng Zhenzhong
Published: November 2024

Flood mapping plays a crucial role in effective disaster management, risk assessment, and mitigation planning, given the widespread and destructive nature of floods. However, current synthetic aperture radar (SAR)-based methods face challenges related to extensive labeled training data, compromised classification accuracy, and limited applicability across different satellite systems and resolutions. In response to these challenges, our research introduces a pioneering unsupervised SAR-based flood mapping algorithm, inspired by artificial general intelligence principles. Notably, the innovative method demonstrates flexibility, performing effectively across various SAR satellites with differing resolutions and sensors, eliminating the need for satellite-specific algorithms. Our algorithm enhances processing speed and scalability by eliminating labor-intensive labeling of training data and manual intervention. To validate its performance, we conducted tests in three distinct regions using meter-level imagery from HISEA-1, Gaofen-3, and Sentinel-1 satellites. Consistently outperformed prevalent unsupervised techniques like Kmeans and Otsu, and even a Supervised-convolutional neural network segmentation algorithm by AI-Earth, with F1-scores exceeding 0.91. This outstanding performance showcases its accuracy, irrespective of the satellite systems or regions utilized. Furthermore, the seamless integration of our algorithm with high-performance cloud computing platforms such as Google Earth Engine enhances its adaptability and scalability, enabling continuous monitoring of global floods. This is crucial in understanding flood trends, assessing their impacts, and formulating effective disaster mitigation strategies.
Soil moisture–atmosphere coupling amplifies the change in extreme heat in inner East Asia under rapid summer warming
Authors: Yin Zejiang , Dong Buwen , Yang Song , Wei Wei
Published: November 2024

Inner East Asia (IEA) is an important component of the global grassland ecosystem and has experienced a more rapid increase in extreme surface air temperatures compared to the summer mean in recent decades (2001–2020, relative to 1971–1990). This excess hot-extreme warming (EHEW) is particularly pronounced in the southern IEA, where extremely hot temperatures have increased twice as quickly as the summer mean warming, which itself already exceeds global-land warming by more than threefold. A quantitative analysis based on a Lagrangian temperature-anomaly equation along air-parcel backward trajectories initiated on hot days across IEA reveals that the observed EHEW is primarily attributable to increased diabatic heating, which predominantly occurs from 2 days before to the hot days. Meanwhile, changes in heat-prone synoptic-scale circulation only exert a limited influence on the excess warming. Soil drying within IEA appears to be a critical factor contributing to increased diabatic heating through soil moisture–atmosphere coupling, as it limits evaporation and enhances sensitive heat flux, thereby triggering positive soil moisture-temperature feedback. Our analysis underscores the significant impact of local soil moisture deficits on the intensified extreme heat. Urgent implementation of grassland and livestock management strategies, coupled with drought mitigation measures, is essential for adaptation and ecosystem conservation.
Correlations between propofol concentration in exhaled breath and BIS in patients undergoing thyroid surgery
Authors: Li Xiaoxiao , Chang Pan , Liu Xing , Zhao Zhongjun , Duan Yixiang , Zhang Wensheng
Published: November 2024

Several clinical studies have reported promising correlations between propofol concentration in exhaled breath (Ce-pro) and the bispectral index (BIS) in patients, suggesting the potential of exhaled propofol measurement as a non-invasive method for adjusting anesthesia depth. However, these studies are still in the validation phase of instrument effectiveness, often limited by small sample sizes or inappropriate instrument selection, and thus lack convincing results regarding these correlations. In this study, one hundred patients aged 18–65, undergoing elective thyroid surgery under general anesthesia were included. The vacuum ultraviolet photoionization and time-of-flight mass spectrometry was employed to monitor Ce-pro at 20 s intervals, alongside continuous BIS measurement. The association between Ce-pro and BIS was analyzed using linear mixed-effects models, with marginal R
2 used to assess the correlation. The threshold of Ce-pro at awakening was also explored. Additionally, the univariate and multifactorial diagnostic model, including end-of-surgery Ce-pro, were employed to assess the accuracy of predicting delayed recovery. A weak correlation was observed between intraoperative Ce-pro and BIS (marginal R
2 = 0.348). Predictive models utilizing end-of-surgery Ce-pro levels showed good accuracy (area under the curve (AUC) = 0.75, 95% CI: 0.62–0.89, P = 0.003) in predicting delayed recovery, while the model using end-of-surgery Ce-pro combined with gender, sufentanil dosage, the time from the last administration of sufentanil to the end of surgery, and anesthesia duration demonstrated stronger predicting accuracy (AUC = 0.91, 95% CI: 0.85–0.98, P < 0.001). This study suggests that Ce-pro alone may not reliably predict the depth of anesthesia in clinical practice, but shows promising accuracy in predicting delayed recovery from anesthesia.
Enhancing vaginal reconstruction through 3D bioprinted scaffolds using a novel vECM-GelMA-SF bioink
Authors: Zheng Jiahua , Zhang Xuemei , Guo Kaixuan , Yan Liman , Xu Xiaotong , Shi Wenxin , Zhang Jingkun , Du Yanfang , Zhang Mingle , Huang Xianghua
Published: November 2024

Overcoming the low cell survival rates and insufficient neovascularization associated with tissue engineering of the vagina is crucial for advancing the vaginal reconstruction. In this research, we have developed a unique bioink composed of porcine vaginal extracellular matrix (vECM), gelatin methacrylamide (GelMA), and silk fibroin (SF) to facilitate the bioprinting of a vaginal scaffold. The vECM-GelMA-SF bioink effectively replicates the in vivo microenvironment, supporting the in vitro cultivation of 3D bioprinted vaginal scaffolds. It promotes stem cell viability and enhances neovascularization by harnessing the mechanical properties of GelMA/SF and the tissue specificity of vECM. In vivo orthotopic studies have demonstrated that the use of 3D bioprinted vaginal scaffolds significantly improves the functionality of reconstructed vaginas, promoting angiogenesis, rapid epithelialization, muscle regeneration, glycogen secretion, and nerve repair. The reconstructed vaginal tissues in the 3D cell-loaded scaffold group closely resemble natural vaginal tissues. Differential proteomics analysis has provided insights into the genetic functions and biological pathways involved in vaginal reconstruction. Our study successfully optimized the composition of the vECM-GelMA-SF bioink, achieving a balance between biocompatibility and printability. This bioink is suitable for constructing 3D bioprinted vaginal scaffolds of various dimensions, transplantable in situ in animal models with different degrees of vaginal absence. The bioink may find applications in clinical settings, improving the overall effectiveness and safety of in vivo vaginal reconstruction procedures.
Harmonic achromatic metalens with a wide field of view for AR/VR applications
Authors: Nasir Badar , Javed Isma , Naveed Muhammad Ashar , Aljaloud Khaled A , Alhuwimel Saad , Hussain Rifaqat , Mehmood Muhammad Qasim
Published: November 2024

Metalens is a cutting-edge optical marvel, revolutionizes a plethora of applications like cameras, telescope, augmented reality (AR) and virtual reality (VR). Despite having ultrathin structure, lightweight nature, and multifunctionality, achievement of both achromatic imaging and wide field of view (WFOV) remains a persistent challenge. To address these concerns, here we present a novel approach using a harmonic metalens featuring a quadratic phase profile to achieve achromatic behavior and WFOV simultaneously. This innovation enables WFOV imaging using the Fourier transform of quadratic phase profile and achromatic behavior at RGB wavelengths (blue λ = 488 nm, green λ = 532 nm and red λ = 633 nm) with a WFOV of up to

±

45
∘

. The designed harmonic metalens is polarization-insensitive, with a numerical aperture of 0.79, and it achieves a maximum focusing efficiency of ∼50% at a wavelength of 633 nm under normal incidence. Being polarization insensitive and achromatic, proposed scheme will certainly broaden the utilization of metalenses in AR/VR, displays and applications in imaging. © 2024 Optical Society of America.
Effect of Sn on the microstructure and properties of biodegradable Mg-1.0Zn-0.3Zr magnesium alloy
Authors: Zhao Fei , Li Huan , Yan Chengqi , Song Beibei , Mao Xiangshan
Published: November 2024

In order to prepare a new biodegradable magnesium alloy with high biosafety, better mechanical properties, and lower degradation rate, in this paper, the effect of the non-toxic element Sn (0%∼2%, mass%) on the microstructure, mechanical properties, and corrosion resistance of the Mg-1.0Zn-0.3Zr alloy was investigated using optical microscopy, scanning electron microscopy, x-ray diffraction, tensile testing, and corrosion experiments. The results indicated that the addition of Sn to the alloy resulted in the formation of the Mg2Sn phase, which improved the mechanical properties of the alloy. However, a higher concentration of this phase and its continuous distribution along the grain boundaries decreased the alloy’s corrosion resistance. The mechanical properties and corrosion resistance of the alloy exhibited an increasing trend with the increase of Sn content, followed by a decreasing trend. At an Sn content of 1%, the alloy demonstrated better mechanical properties and corrosion resistance simultaneously. The yield strength, tensile strength, and elongation of the alloy were 114 ± 2 MPa, 164 ± 5 MPa, and 13.3 ± 0.1%, respectively. Additionally, the corrosion rate of the alloy was only 0.61 mm y−1 after being immersed in simulated body fluids for 120 h. These properties represent a significant improvement over those of the Mg-1.0Zn-0.3Zr alloy. Our results indicate that the addition of an appropriate amount of Sn element can improve both the mechanical properties and corrosion resistance of the alloy, supporting the development of new biodegradable magnesium alloys.
Synergistic effects of boron carbide and niobium reinforcements on the mechanical performance of Al-8090 alloys
Authors: Meenuga Shanthi Raju , Birru Anil Kumar , Pulisheru Kumara Swamy , Apparao K Ch , Sridatha Bommidi , Rao Gadudasu Babu , Bannaravuri Praveen Kumar
Published: November 2024

This experimental study investigates the impact of boron carbide (B4C) and Niobium (Nb) reinforcement particles on the microstructural, mechanical and surface properties of Al-8090 base alloy. The inclusion of B4C and Nb particles significantly refines the structure which enhances the properties via nucleation and dispersion strengthening effects. Optical microstructures and Scanning Electron Microscopy images show that an increase in reinforcement percentages precedes finer grains and uniform particle distribution. Energy Dispersive x-ray Spectroscopy analysis highlights a predominant aluminium (Al) peak in the Al-8B4C-5 Nb sample and Nb and Fe minor peaks indicate potential diffusion interaction. Mechanical tests reveal substantial improvements in hardness, tensile strength, and density of the Al-7B4C-3 Nb sample obtained the highest values. However, increasing reinforcement content causes agglomeration which declines the hardness and increases porosity. The wear test demonstrates that the reinforced composites perform superior properties, with B4C providing surface layer protection and Nb refining the grain structure. Corrosion analysis reveals that inclusion reinforcements act as initiation sites for intergranular and localized corrosion due to the galvanic interaction effect. These findings recommend that an optimized reinforcement content in Al-8090 base alloy yields better mechanical performance and wear resistance for high-strength applications.
Design of insulation support system of 120 keV positive ion source accelerator
Authors: DENG 邓 Wen 文 , XIE 谢 Yahong 亚红 , GU 顾 Yuming 玉明 , JIANG 江 Yunfei 云飞 , LIU 刘 Longbin 龙斌 , WANG 王 Fang 昉 , WEI 韦 Jianglong 江龙 , HU 胡 Chundong 纯栋
Published: November 2024

In order to support the physical research on the EAST tokamak, a new positive ion source with designed beam energy of 120 keV was proposed to be developed. Accelerator structure is one of the key components of the ion source. Through the finite element analysis method, the electrostatic analyses of insulators and grid plates were carried out, the material and structure parameters of insulators were determined. The maximum electric field around each insulator is about 4 kV/mm, and the maximum electric field between grids is about 14 kV/mm, which can meet the 120 keV withstand voltage holding. The insulation system for the positive ion source accelerator with 120 keV is designed, and the connection and basic parameters of insulators and support flanges are analyzed and determined.
Hydroeconomic insights for transboundary water challenges and potential collaboration in the Tigris-Euphrates river basin
Authors: Taheripour Farzad , Haqiqi Iman , Golub Alla A , Sajedinia Ehsanreza , Karami Omid
Published: November 2024

For countries sharing transboundary water resources, measuring changes in water availability and ensuing economic outcomes is challenging due to downstream impacts and interconnected agricultural markets. Using a coupled modeling approach that combines a detailed multi-sector model of international trade with a gridded hydrological model, this paper quantifies the impacts of climate change and anthropogenic activities on water scarcity and its economy-wide consequences for the riparian countries in the Tigris-Euprates (TE) river basin and evaluates scenarios of collaboration in basin water management as an adaptation strategy. By mid-century climate change will significantly increase water scarcity in the basin: up to 30% in Iran, 27% in Türkiye, 17% in Iraq, and 14% in Syria. Depending on the climate change scenario, average annual GDP losses from water scarcity and changes in crop yields range from 12 to 84 billion USD for these economies. However, collaboration among the TE river basin riparian countries in water allocation and use could mitigate the adverse economic effects and, relative to the status quo, generate direct GDP gain in the 42–58 billion USD range for these countries and indirect gains for other countries in the Middle East region. The results suggest that collaboration in water management in the TE river basin is an effective option to tackle emerging challenges such as the impact of climate change on water availability.
Mathematical models on bone cell homeostasis and kinetics in the presence of electric fields: a review
Authors: Lee Poh Soo , Sriperumbudur Kiran K , Dawson Jonathan , van Rienen Ursula , Appali Revathi
Published: November 2024

The role of bioelectricity in regulating various physiological processes has attracted increasing scientific interest in implementing exogenous electrical stimulations as a therapeutic approach. In particular, electrical stimuli are used clinically in pre-/post-surgery patient care for the musculoskeletal tissues. The reported potential of electric fields (EF) to regulate bone cell homeostasis and kinetics in vitro has further provoked more studies in this field of research. Various customised apparatuses have been developed, and a range of parameters for the applied EFs have been investigated in vitro with bone cells or mesenchymal stem cells. Additionally, biomaterials with conductive or piezo-electric properties have been designed to complement the enhancing effects of the EF on bone regeneration. Despite much research, there remained a significant gap in knowledge due to the diverse range of EF parameters available. Mathematical models are built to facilitate further understanding and zero in on an effective range of EF parameters in silico. However, the diverse range of EF parameters, experimental conditions, and reported analytical output of different works of literature were reported to possess significant variance, making it challenging to accurately model the field in silico. This review categorises the existing experimental approaches and the parameters used to distinguish the potential variables that apply to mathematical modelling. Furthermore, we will discuss existing modelling approaches and models available in the literature. With this, we will concisely highlight the need to categorise EF parameters, osteogenic differentiation initiators and research output.
Exploring temporal dynamics of ice melting through dynamic laser speckle imaging
Authors: S H Keerthana , Radhakrishnan P , Mujeeb A
Published: November 2024

Dynamic laser speckle imaging (DLSI) is an emerging non-destructive imaging technique used for characterizing rough surfaces. High spatio-temporal resolution and cost effective nature make this imaging technique more attractive in optical metrology. In this study, DLSI is utilized to monitor the intermittent dynamics of ice during its melting process. In DLSI, image processing algorithms such as Time History of Speckle Patterns and Co-Occurrence Matrices are generally employed to process the speckle images. However, these algorithms are limited to gather information from specific regions of the speckle images. To overcome this limitation, frequency domain algorithms are employed to analyse the activity across all frequency bands. In this work, we utilized Wavelet-Based Entropy for the analysis of speckle images captured from the surface of ice during its melting process. Wavelet-Based Entropy is a powerful frequency domain tool for exploring dynamic processes, offering superior capability in capturing spatial and spectral variations, making it particularly well-suited for the analysis of speckle images. The results were also compared with Probability density function and Co-Occurrence Matrices and demonstrated consistent agreement.
Fusion of improved RRT and ant colony optimization for robot path planning
Authors: Chang Zhen , Wang Yi , Cai Ying , Li Siquan , Gao Fangzheng
Published: November 2024

To address the issues of poor guidance at the beginning of the Ant Colony Optimization (ACO) algorithm, non-smooth paths, and its tendency to fall into local optima, this paper proposes a path planning approach based on the Rapidly-exploring Random Tree (RRT) and Ant Colony Optimization (ACO). Firstly, obstacles are inflated to set a safety distance, and a differentiated pheromone distribution is created using the sub-optimal trajectory produced by the improved RRT, guiding the initial direction of the ant colony. Secondly, dynamic strategies are introduced into the evaporation coefficient and heuristic factor, adjusting their weights according to the number of iterations to enhance the attraction of the target point to the ants. Then, a reward-punishment mechanism is used to update the pheromone, solving the problem of local optima. Finally, a pruning optimization strategy based on the maximum turning angle is employed to remove redundant nodes, making the path smoother. Multiple simulation results confirm that the algorithm possesses good global search capabilities and robustness under various conditions.
Illuminating new and known relations between knot invariants
Authors: Craven Jessica , Hughes Mark , Jejjala Vishnu , Kar Arjun
Published: November 2024

We automate the process of machine learning correlations between knot invariants. For nearly 200 000 distinct sets of input knot invariants together with an output invariant, we attempt to learn the output invariant by training a neural network on the input invariants. Correlation between invariants is measured by the accuracy of the neural network prediction, and bipartite or tripartite correlations are sequentially filtered from the input invariant sets so that experiments with larger input sets are checking for true multipartite correlation. We rediscover several known relationships between polynomial, homological, and hyperbolic knot invariants, while also finding novel correlations which are not explained by known results in knot theory. These unexplained correlations strengthen previous observations concerning links between Khovanov and knot Floer homology. Our results also point to a new connection between quantum algebraic and hyperbolic invariants, similar to the generalized volume conjecture.
Urban scaling of water and electricity demand across the United States
Authors: Adul Joy , Bhaskar Chiluveru Vijay , Obringer Renee
Published: November 2024

As urban populations continue to grow, ensuring an adequate supply of water and electricity will be imperative. However, these resources are generally extracted in rural areas, creating tension during periods of limited availability. It has been argued, however, that urban areas are more efficient users of various resources in spite of their large populations. Here, we test this argument for water and electricity consumption across 46 US cities. Leveraging urban scaling theory, we show that water and electricity consumption scale sublinearly with population. This suggests that cities are using water and electricity more efficiently as their population increases. Further, the results show that this sublinear scaling exists regardless of season or year. Nonetheless, there were cities that deviated from the expected consumption value that would have been predicted by this model. We explored the role that precipitation and temperature might have on these deviates and found that temperature, in particular, can help explain why certain cities consume more electricity than expected based on their population. Understanding the relationship between consumption patterns and population is critical for planning investments for future infrastructure systems that will need to service higher populations with more limited resources.
Impact of the urban heat island on heat-related mortality in the Tokyo Metropolitan Area, Japan
Authors: He Jinyu , Madaniyazi Lina , Chua Paul L C , Kim Yoonhee , Milojevic Ai , Oka Kazutaka , Honda Yasushi , Hashizume Masahiro
Published: November 2024

With global temperatures rising, urban heat islands (UHIs) intensify heat exposure in cities, potentially elevating heat-related mortality. However, the specific burden of UHI-attributable mortality remains inadequately quantified. This study investigates the impact of UHIs on heat-related mortality in the Tokyo Metropolitan Area (TMA), Japan, from 2010 to 2019. Daily time series data on maximum and mean ambient temperatures and all-cause mortality were obtained for 149 municipalities. Urban municipalities were identified by the presence of densely inhabited districts, with adjacent non-urban municipalities at similar elevations serving as a baseline (Zone 1). UHI intensity was quantified by calculating municipality-specific UHI anomalies (UHIa) as the deviation of daily maximum temperatures in each urban municipality from the average mean temperatures of Zone 1. Based on UHIa values, urban municipalities were grouped into nine zones (Zones 2–10). Heat-mortality relationships across zones were estimated using distributed lag nonlinear models, with relative risks (RRs) calculated at 30 °C using 26 °C as the reference. Heat-related mortality was computed for observed and counterfactual scenarios, the latter assuming urban temperatures matched non-urban levels. Differences in estimated mortality represented UHI-attributable impacts in the TMA. A mean UHIa difference of 0.72 °C was observed between Zones 2 and 10, with UHIa values ranging from 4.77 °C to 5.49 °C. No significant heterogeneity in RRs was observed across zones. UHI-attributable mortality was estimated at 2207 deaths (95% empirical confidence interval (eCI): 1200, 3119), accounting for 30.0% of urban heat-related deaths from 2010 to 2019. Zone-specific UHI-attributable mortality ranged from 9 deaths (95% eCI: 5, 13) to 593 deaths (95% eCI: 323, 839). These findings highlight the potential health impact of UHIs in the TMA and underscore the importance of integrating UHI effects into future temperature-mortality assessments to better understand urban heat-related health risks.
World delirium awareness and quality survey in 2023—a worldwide point prevalence study
Authors: Lindroth Heidi , Liu Keibun , Szalacha Laura , Ashkenazy Shelly , Bellelli Giuseppe , van den Boogaard Mark , Caplan Gideon , Chung Chi Ryang , Elhadi Muhammed , Gurjar Mohan , Heras-La-Calle Gabriel , Hoffman Magdalena , Jeitziner Marie-Madlen , Krewulak Karla , Mailhot Tanja , Morandi Alessandro , Nawa Ricardo Kenji , Oh Esther S , Collet Marie Oxenboell , Paulino Maria Carolina , von Haken Rebecca , Nydahl Peter ,   For the WDAD Study Team
Published: November 2024

Background

Delirium, an acute brain dysfunction, is proposed to be highly prevalent in clinical care and shown to significantly increase the risk of mortality and dementia.

Objectives

To report on the global prevalence of clinically documented delirium and delirium-related clinical practices in wards caring for paediatric and adult patients in healthcare facilities.

Design

A prospective, cross-sectional, 39-question survey completed on World Delirium Awareness Day, 15 March 2023.

Participants

Clinicians or researchers with access to clinical data.

Main Outcome and Measure

The primary outcome was the prevalence of clinically documented delirium at 8:00 a.m. (4 h) and 8:00 p.m. (±4 h). Secondary outcomes included delirium-related care practices and barriers to use. Descriptive statistics were calculated and multilevel modelling was completed.

Results

1664 wards submitted surveys from 44 countries, reporting on delirium assessments at 8:00 a.m. (n = 36 048) and 8:00 p.m. (n = 32 867); 61% reported use of validated delirium assessment tools. At 8:00 a.m., 18% (n = 2788/15 458) and at 8:00 p.m., 17.7% (n = 2454/13 860) were delirium positive. Top prevention measures were pain management (86.7%), mobilisation (81.4%) and adequate fluids (80.4%). Frequently reported pharmacologic interventions were benzodiazepines (52.7%) and haloperidol (46.2%). Top barriers included the shortage of staff (54.3%), lack of time to educate staff (48.6%) and missing knowledge about delirium (38%).

Conclusion and Relevance

In this study, approximately one out of five patients were reported as delirious. The reported high use of benzodiazepines needs further evaluation as it is not aligned with best-practice recommendations. Findings provide a benchmark for future quality improvement projects and research.
Local adaptation and phenotypic plasticity in two forest understorey herbs in response to forest management intensity
Authors: Møller Charlotte , March-Salas Martí , De Frenne Pieter , Scheepens J F
Published: November 2024

Local adaptation is a common phenomenon that helps plant populations to adjust to broad-scale environmental heterogeneity. Given the strong effect of forest management on the understorey microenvironment and often long-term effects of forest management actions, it seems likely that understorey herbs may have locally adapted to the practiced management regime and induced environmental variation. We investigated the response of Anemone nemorosa and Milium effusum to forest management using a transplant experiment along a silvicultural management intensity gradient. Genets were sampled from sites with contrasting management intensities and transplanted sympatrically, near allopatrically and far allopatrically along the management intensity gradient to test for local adaptation and phenotypic plasticity, as well as to sites where the species were absent to test for recruitment versus dispersal limitations. We then measured survival and fitness traits over two growing seasons. We found only little evidence of local adaptation in A. nemorosa and M. effusum, whereas various traits in both species showed linear plastic changes in response to transplantation along the forest management intensity gradient. Furthermore, A. nemorosa performed worse when transplanted to unoccupied sites, suggesting recruitment limitation, whereas M. effusum performed better in unoccupied sites, suggesting dispersal limitation. Altogether, our results underpin the importance of forest management to indirectly drive phenotypic variation among populations of forest plants.
Improved prediction of post-translational modification crosstalk within proteins using DeepPCT
Authors: Huang Yu-Xiang , Liu Rong
Published: November 2024

Motivation

Post-translational modification (PTM) crosstalk events play critical roles in biological processes. Several machine learning methods have been developed to identify PTM crosstalk within proteins, but the accuracy is still far from satisfactory. Recent breakthroughs in deep learning and protein structure prediction could provide a potential solution to this issue.

Results

We proposed DeepPCT, a deep learning algorithm to identify PTM crosstalk using AlphaFold2-based structures. In this algorithm, one deep learning classifier was constructed for sequence-based prediction by combining the residue and residue pair embeddings with cross-attention techniques, while the other classifier was established for structure-based prediction by integrating the structural embedding and a graph neural network. Meanwhile, a machine learning classifier was developed using novel structural descriptors and a random forest model to complement the structural deep learning classifier. By integrating the three classifiers, DeepPCT outperformed existing algorithms in different evaluation scenarios and showed better generalizability on new data owing to its less distance dependency.

Availability and implementation

Datasets, codes, and models of DeepPCT are freely accessible at https://github.com/hzau-liulab/DeepPCT/.
Sparse Neighbor Joining: rapid phylogenetic inference using a sparse distance matrix
Authors: Kurt Semih , Bouchard-Côté Alexandre , Lagergren Jens
Published: November 2024

Motivation

Phylogenetic reconstruction is a fundamental problem in computational biology. The Neighbor Joining (NJ) algorithm offers an efficient distance-based solution to this problem, which often serves as the foundation for more advanced statistical methods. Despite prior efforts to enhance the speed of NJ, the computation of the n2 entries of the distance matrix, where n is the number of phylogenetic tree leaves, continues to pose a limitation in scaling NJ to larger datasets.

Results

In this work, we propose a new algorithm which does not require computing a dense distance matrix. Instead, it dynamically determines a sparse set of at most O(n log n) distance matrix entries to be computed in its basic version, and up to O(n log 2n) entries in an enhanced version. We show by experiments that this approach reduces the execution time of NJ for large datasets, with a trade-off in accuracy.

Availability and implementation

Sparse Neighbor Joining is implemented in Python and freely available at https://github.com/kurtsemih/SNJ.
Attenuation of Ampullary Anoctamin 1 by the peritoneal fluid in rhesus macaques with spontaneous endometriosis
Authors: Luo Fangzhou , Slayden Ov
Published: November 2024

Altered peristaltic and ciliary dysfunction is a feature of females with endometriosis. To further explore this premise, we examined the ampulla of rhesus macaques (Macaca mulatta) with and without spontaneous endometriosis for the expression of adenylate kinase 7 (AK7), a mitochondrial-dwelling nucleotide converting enzyme with critical roles in cellular kinesis, forkhead protein box J1 (FOXJ1), a marker of cilia abundance, and Anoctamin 1 (ANO1) as a marker of both smooth muscle contraction and ciliogenesis. We further performed an in vitro experiment that treated ampullary segments with peritoneal fluid from animals with and without endometriosis. We report significantly downregulated expression of ANO1 in the ampulla of monkeys with endometriosis (in vivo), and in the ampullary segments exposed to peritoneal fluid of animals with endometriosis. We did not observe statistically significant differences in the expression of AK7 or FOXJ1 both in vivo and in vitro. This highlights potentially essential roles of ANO1 in the oviduct, the dampening of which may lead to a specific subtype of endometriosis-caused subfertility.
On Rosenbaum’s rank-based matching estimator
Authors: Cattaneo Matias D , Han Fang , Lin Zhexiao
Published: November 2024

In two influential contributions, Rosenbaum (2005, 2020a) advocated for using the distances between componentwise ranks, instead of the original data values, to measure covariate similarity when constructing matching estimators of average treatment effects. While the intuitive benefits of using covariate ranks for matching estimation are apparent, there is no theoretical understanding of such procedures in the literature. We fill this gap by demonstrating that Rosenbaum’s rank-based matching estimator, when coupled with a regression adjustment, enjoys the properties of double robustness and semiparametric efficiency without the need to enforce restrictive covariate moment assumptions. Our theoretical findings further emphasize the statistical virtues of employing ranks for estimation and inference, more broadly aligning with the insights put forth by Peter Bickel in his 2004 Rietz lecture.
Lewy pathology formation in patient-derived GBA1 Parkinson’s disease midbrain organoids
Authors: Frattini Emanuele , Faustini Gaia , Lopez Gianluca , Carsana Emma V , Tosi Mattia , Trezzi Ilaria , Magni Manuela , Soldà Giulia , Straniero Letizia , Facchi Daniele , Samarani Maura , Martá-Ariza Mitchell , De Luca Chiara M G , Vezzoli Elena , Pittaro Alessandra , Stepanyan Astghik , Silipigni Rosamaria , Rosety Isabel , Schwamborn Jens C , Sardi Sergio P , Moda Fabio , Corti Stefania , Comi Giacomo P , Blandini Fabio , Tritsch Nicolas X , Bortolozzi Mario , Ferrero Stefano , Cribiù Fulvia M , Wisniewski Thomas , Asselta Rosanna , Aureli Massimo , Bellucci Arianna , Di Fonzo Alessio
Published: November 2024

Fibrillary aggregation of α-synuclein in Lewy body inclusions and nigrostriatal dopaminergic neuron degeneration define Parkinson’s disease neuropathology. Mutations in GBA1, encoding glucocerebrosidase, are the most frequent genetic risk factor for Parkinson’s disease. However, the lack of reliable experimental models able to reproduce key neuropathological signatures has hampered the clarification of the link between mutant glucocerebrosidase and Parkinson’s disease pathology. Here, we describe an innovative protocol for the generation of human induced pluripotent stem cell-derived midbrain organoids containing dopaminergic neurons with nigral identity that reproduce characteristics of advanced maturation. When applied to patients with GBA1-related Parkinson’s disease, this method enabled the differentiation of midbrain organoids recapitulating dopaminergic neuron loss and fundamental features of Lewy body pathology observed in human brains, including the generation of α-synuclein fibrillary aggregates with seeding activity that also propagate pathology in healthy control organoids. Still, we observed that the retention of mutant glucocerebrosidase in the endoplasmic reticulum and increased levels of its substrate glucosylceramide are determinants of α-synuclein aggregation into Lewy body-like inclusions. Consistently, the reduction of glucocerebrosidase activity accelerated α-synuclein pathology by promoting fibrillary α-synuclein deposition. Finally, we demonstrated the efficacy of ambroxol and GZ667161 – two modulators of the glucocerebrosidase pathway in clinical development for the treatment of GBA1-related Parkinson’s disease – in reducing α-synuclein pathology in this model, supporting the use of midbrain organoids as a relevant pre-clinical platform for investigational drug screening.
Neuropathic pain relief and altered brain networks after dorsal root entry zone microcoagulation in patients with spinal cord injury
Authors: Falci Scott , Morse Leslie , Berliner Jeffrey , Murakami Mario , Welch Abigail , Barnkow David , Nguyen Nguyen , Battaglino Ricardo , Linnman Clas
Published: November 2024

Spinal cord injury (SCI) below-level neuropathic pain is a difficult condition to treat both pharmacologically and surgically. Successful treatment using surgically created lesions of the spinal cord dorsal root entry zone (DREZ), guided by intramedullary monitoring of neuronal electrical hyperactivity, has shown that DREZs both cephalad and caudal to the level of injury can be the primary generators of SCI below-level pain. Below-level pain perception follows a unique somatotopic map of DREZ pain generators, and neuronal transmission to brain pain centres can occur primarily through sympathetic nervous system (SNS) pathways. This study evaluated changes in brain resting-state and task-based functional magnetic resonance imaging responses before and after neuroelectrically guided DREZ microcoagulation surgery. Eight persons with clinically complete SCI who suffered chronic, severe and unrelenting below-level neuropathic pain refractory to all pharmacological management were investigated before and after the surgical intervention. Baseline differences between DREZ subjects, group-matched low pain SCI and healthy controls were observed in medial primary somatosensory and motor cortex connectivity to the hippocampus, amygdala and medial prefrontal cortex. The DREZ surgery led to short-term (12 days) almost complete pain relief in all participants and long-term (1+ year) pain relief in all participants receiving DREZ lesioning both cephalad and caudal to the level of injury (six out of eight participants). Follow-up 12 days post-operatively indicated that DREZ surgery normalized prior negative functional coupling between primary sensory (S1) and motor (M1) cortices to the hippocampus, amygdala and the medial prefrontal cortex, increased M1 to putamen and amygdala connectivity and decreased limbic to cerebellar connectivity. DREZ hyperactivity was found both cephalad and caudal to the level of injury. The regional distribution of hyperactive regions corresponded not to classical dermatomes but rather mapped on to intermediolateral (IML) cell column end organ innervation of body regions of below-level pain perception, consistent with a non-classical SNS-mediated somatotopic map of DREZ below-level pain generators. The results indicate that neuroelectrically guided DREZ microcoagulation alters a medial prefrontal–somatosensory–limbic network that is separate from classical pain pathways. This provides further evidence that below-level SCI pain originates in hyperactive DREZs and can be relayed to the brain via the SNS.
Itching for innovation: the role of aryl hydrocarbon receptor agonists as a future therapy for atopic dermatitis
Authors: Wazir Areen , O’Toole Edel A
Published: November 2024

Atopic dermatitis (AD) is a chronic, inflammatory skin condition that affects over 200 million people worldwide. Patients commonly present with dry, itchy and sore skin. The challenge in finding optimal treatment for AD stems from the heterogeneous nature of the disease and its multifaceted aetiology: skin barrier dysfunction, immune system dysregulation, genetic factors, environmental factors and alterations in skin microorganisms. Traditional treatments for AD, such as corticosteroids, calcineurin inhibitors and immunosuppressants, have several limitations, such as the reoccurrence of symptoms when discontinued, lack of targeted action and risk of adverse effects. The aim of this literature review was to explore and summarize the role of aryl hydrocarbon receptor (AHR) agonists (namely tapinarof) as potential future therapy for AD. It is hoped that AHR agonists will overcome the limitations of traditional AD therapies and exert their therapeutic value by maintaining the integrity of the skin barrier, defending against oxidative stress, modulating immune activity and inflammation and restoring a healthy skin microbiome. Tapinarof, a topical AHR agonist, is showing promising results and has recently concluded its long-term extension phase III trial (ADORING 3). For tapinarof to be integrated into the AD treatment pathway, robust research evidence must be presented on its efficacy, durability, potential remittive effect and safety across different AD subtypes in a large, diverse patient population. In addition, the cost-effectiveness of tapinarof compared with its topical counterparts needs to be considered and multidisciplinary collaboration is required between researchers, clinicians and policymakers.