bluuebunny/crossref_metadata_2025 huggingface dataset:
Whole genome sequencing in adults with clinical hallmarks of hypophosphatasia negative for ALPL variants
Authors: Seefried Lothar , Petryk Anna , del Angel Guillermo , Reder Felix , Bauer Peter
Published: September 2024

Background

Hypophosphatasia (HPP) is a rare disease caused by deficient activity of tissue-nonspecific alkaline phosphatase (ALP), encoded by the ALPL gene. The primary objective was to explore novel ALPL variants by whole genome sequencing (WGS) in patients with HPP who previously tested negative by standard methods for ALPL variants. The secondary objective was to search for genes beyond ALPL that may reduce ALP activity or contribute to HPP symptoms.

Methods and results

WGS was performed in 16 patients clinically diagnosed with HPP who had ALP activity below the normal range and tested negative for ALPL variants. Genetic variants in ALPL and genes possibly associated with low ALP activity or phenotypic overlap with HPP were assessed. All 16 patients had ALP activity below the normal range. WGS did not identify any novel disease-causing ALPL variants. Positive findings for other gene variants were identified in 4 patients: 1 patient presented with variants in COL1A1, NLRP12, and SCN9A, coding for collagen, type, I alpha-1 chain, nod-like receptor pyrin domain containing 12, and sodium voltage-gated channel alpha subunit 9, respectively; 1 presented with a heterozygous, likely pathogenic variant in P3H1 coding for prolyl 3 hydroxylase 1; 1 presented with a heterozygous pathogenic variant in SGCE, coding for sarcoglycan epsilon; and 1 presented with a heterozygous variant of uncertain significance in VDR, encoding vitamin D receptor.

Conclusion

Genomic analysis did not identify novel ALPL variants or a pattern of disease-causing variants in genes other than ALPL to explain the HPP phenotype in these patients.

Registration

Clinicaltrials.gov identifier: NCT04925804.
The Art of Soft Systems Inquiry: Retracing the Footsteps of Churchman and Checkland
Authors: Stowell Frank
Published: September 2024

In this paper I reflect upon soft-systems inquiry. To do this I revisit Churchman’s discourse on the philosophical ideas underpinning inquiring systems and then discuss the practical application of soft inquiry pioneered by Checkland. This body of work suggested ontological models of organisational behavior were inappropriate and only by adopting an epistemological perspective would provide the basis for understanding complex systems that characterise human society. These ideas motivated a new way of addressing complexity. This work created a difficulty for action research since to be faithful to this discovery meant that any method of inquiry should be one that could cope with such complexity. One outcome was Soft Systems Methodology (SSM). Paradoxically the success of SSM has restrained further discussion of these ideas. The purpose of this paper is to revisit the ideas of Churchman and Checkland as a means of returning to first principles. In this paper I reassess their ideas and those of Husserl and Gadamer and suggest there is more to be gained from this rich seam of systems thinking.
Multiscale neural dynamics in sleep transition volatility across age scales: a multimodal EEG-EMG-EOG analysis of temazepam effects
Authors: Sirpal Parikshat , Sikora William A. , Refai Hazem H.
Published: September 2024

Recent advances in computational modeling techniques have facilitated a more nuanced understanding of sleep neural dynamics across the lifespan. In this study, we tensorize multiscale multimodal electroencephalogram (EEG), electromyogram (EMG), and electrooculogram (EOG) signals and apply Generalized Autoregressive Conditional Heteroskedasticity (GARCH) modeling to quantify interactions between age scales and the use of pharmacological sleep aids on sleep stage transitions. Our cohort consists of 22 subjects in a crossover design study, where each subject received both a sleep aid and a placebo in different sessions. To understand these effects across the lifespan, three evenly distributed age groups were formed: 18–29, 30–49, and 50–66 years. The methodological framework implemented here employs tensor-based machine learning techniques to compute continuous wavelet transform time–frequency features and utilizes a GARCH model to quantify sleep signal volatility across age scales. Support Vector Machines are used for feature ranking, and our analysis captures interactions between signal entropy, age, and sleep aid status across frequency bands, sleep transitions, and sleep stages. GARCH model results reveal statistically significant volatility clustering in EEG, EMG, and EOG signals, particularly during transitions between REM and non-REM sleep. Notably, volatility was higher in the 50–66 age group compared to the 18–29 age group, with marked fluctuations during transitions from deep sleep to REM sleep (standard deviation of 0.35 in the older group vs. 0.30 in the 18–29 age group, p < 0.05). Statistical comparisons of volatility across frequency bands, age scales, and sleep stages highlight significant differences attributable to sleep aid use. Mean conditional volatility parameterization of the GARCH model reveals directional influences, with a causality index of 0.75 from frontal to occipital regions during REM sleep transition periods. Our methodological framework identifies distinct neural behavior patterns across age groups associated with each sleep stage and transition, offering insights into the development of targeted interventions for sleep regularity across the lifespan.
Perturbations of exponential maps: Non-recurrent dynamics
Authors: Aspenberg Magnus , Cui Weiwei
Published: September 2024

We study perturbations of non-recurrent parameters in the exponential family. It is shown that the set of such parameters has Lebesgue measure zero. This particularly implies that the set of escaping parameters has Lebesgue measure zero, which complements a result of Qiu from 1994. Moreover, we show that non-recurrent parameters can be approximated by hyperbolic ones.
On the injectivity of the shifted Funk–Radon transform and related harmonic analysis
Authors: Rubin Boris
Published: September 2024

Necessary and sufficient conditions are obtained for injectivity of the shifted Funk–Radon transform associated with k-dimensional totally geodesic submanifolds of the unit sphere Sn in ℝn+1. This result generalizes the well known statement for the spherical means on Sn and is formulated in terms of zeros of Jacobi polynomials. The relevant harmonic analysis is developed, including a new concept of induced Stiefel (or Grassmannian) harmonics, the Funk–Hecke type theorems, addition formula, and multipliers. Some perspectives and conjectures are discussed.
The roles of AI and educational leaders in AI-assisted administrative decision-making: a proposed framework for symbiotic collaboration
Authors: Dai Ruixun , Thomas Matthew Krehl Edward , Rawolle Shaun
Published: September 2024

Education has always been in a state of flux because of technological disruption. As schools head towards a present in which digital technology is normalised as part of the fabric of everyday society, a post-digital paradigm, Artificial Intelligence (AI) is changing the educational administration and leadership. It is crucial to find ways to coexist with AI while striving for a human-centric future. While numerous studies advocate for a collaborative synergy between AI and human leaders in educational governance, there is a gap in explicating the precise roles they undertake. This paper aims to address the void by providing a conceptual framework for the symbiotic roles of AI and educational leaders in the administrative decision-making process. This paper views administrative decision-making in schools as a political process involving negotiations among administrators, teachers, students, and parents. Within the framework, AI shoulders informational roles such as collecting and analysing data with its data analysis capability. Conversely, educational leaders are tasked with establishing the vision, disseminating information, managing conflicts, identifying new opportunities, negotiating and allocating decision-making authority to stakeholders. Moreover, educational leaders should encourage and supervise the implementation of AI in schools. The framework serves as a theoretical lens for prospective studies of AI impacts on education leadership and administration and bears practical implications for the preparation of future school leaders, contributing to the creation of a scenario where AI augments, rather than replaces educational leadership.
Grewiifopenes A–K, bioactive clerodane diterpenoids from Casearia grewiifolia Vent.
Authors: Pailee Phanruethai , Batsomboon Paratchata , Yaosanit Wiriya , Thananthaisong Theerawat , Mahidol Chulabhorn , Ploypradith Poonsakdi , Reuk-ngam Nanthawan , Khlaychan Panita , Techasakul Supanna , Ruchirawat Somsak , Prachyawarakorn Vilailak
Published: September 2024

Eleven novel clerodane-type diterpenoids, grewiifopenes A–K (1–4 and 12–18), along with nine known compounds (5–11, 19, and 20) were purified from the dichloromethane extract of the twigs and stems of Casearia grewiifolia Vent. (Salicaceae). Their spectroscopic data, including the NMR, HRESIMS, and electronic circular dichroism calculations were employed to completely characterize and elucidate the chemical structures and absolute configurations. The clerodane diterpenoids possessing a 6-OH group and no substitution at C-7 exhibited greater cytotoxic activity than others, with their IC50 values ranging from 0.3 to 2.9 μM. Isocaseamembrin E (7) exhibited antibacterial activity against Staphylococcus aureus, while isocaseamembrin E (7), corymbulosin X (8), caseargrewiin A (9), kurzipene A (10), and balanspene F (11) exhibited antibacterial activity against Bacillus cereus.

Graphical Abstract
The Time Course of Injury Risk After Return-to-Play in Professional Football (Soccer)
Authors: Zhang Guangze , Brink Michel , aus der Fünten Karen , Tröß Tobias , Willeit Peter , Meyer Tim , Lemmink Koen , Hecksteden Anne
Published: September 2024

Background

Injury risk in professional football (soccer) is increased in the weeks following return-to-play (RTP). However, the time course of injury risk after RTP (the hazard curve) as well as its influencing factors are largely unknown. This knowledge gap, which is arguably due to the volatility of instantaneous risk when calculated for short time intervals, impedes on informed RTP decision making and post-RTP player management.

Objectives

This study aimed to characterize the hazard curve for non-contact time-loss injuries after RTP in male professional football and to investigate the influence of the severity of the index injury and playing position.

Methods

Media-based injury records from the first German football league were collected over four seasons as previously published. Time-to-event analysis was employed for non-contact time-loss injury after RTP. The Kaplan–Meier survival function was used to calculate the cumulative hazard function, from which the continuous hazard function was retrieved by derivation.

Results

There were 1623 observed and 1520 censored events from 646 players analyzed. The overall shape of the hazard curve was compatible with an exponential decline of injury risk, from an approximately two-fold level shortly after RTP towards baseline, with a half-time of about 4 weeks. Interestingly, the peak of the hazard curve was slightly delayed for moderate and more clearly for severe index injuries.

Conclusions

The time course of injury risk after RTP (the hazard curve) can be characterized based on the Kaplan–Meier model. The shape of the hazard curve and its influencing factors are of practical as well as methodological relevance and warrant further investigation.
Effect of kaolin-nano-silica mixture on geomechanical properties enhancement of soils
Authors: Shalaby Ola Bakr , Elkady Hala M. , Salah Mohamed , Nagy Nabil M. , Fayed Ayman L.
Published: September 2024

Weak soil is a major obstacle facing the urban development of any site with other exceptional merits. The current study aims to investigate the utilization of nano-silica in enhancing the mechanical properties of weak kaolin soils. Design mixes using different percentages of nano-silica were investigated in the range between 0.25–1.20% from the dry weight of the kaolin soil. Various chemical, physical, and mechanical properties of each mixture have been investigated. The obtained results indicated that nano-silica addition to such kaolin soils decreased the plasticity index and the maximum dry density while increasing the plastic limit, the Liquid limit, and the optimum moisture content. In different curing days of the tested mixtures, maximum dry density was decreased, while the optimum moisture content increased. The optimum value of added nano-silica was less than 1% of the soil dry weight. In the modified kaolin soil with 0.9% nano-silica, the plastic limit was increased by 29%, while the liquid limit decreased by 13% in comparison with the untreated sample. After 28 days of the cured sample, the unconfined compressive strength readings increased by almost 14% compared to its reading on day one. Also, the California bearing ratio results recorded significant enhancement with nano-silica additives in comparison with the untreated kaolin soil. After 28 curing days, the sonicated samples recorded enhancement in the unconfined compressive strength readings by more than 5% and 9% with the additive N-Si (0.3% and 0.9%), respectively, when compared with the unsonicated samples.

Graphical Abstract
Measuring Business Cycle Stylized Facts in Selected Oil-Producing Economies: A Comparative Study
Authors: Chukwu Chigozie , Vasilev Aleksandar , Saha Shrabani
Published: September 2024

We document the stylized facts relating to the contemporary business cycle in eleven oil-producing economies that account for over 65% of global oil production using a set of macroeconomic aggregates covering the period 1981 to 2021. In the context of Nigeria, a vector autoregression analysis is used to measure a one standard deviation oil price shock on time series such as trade balance, real GDP, inter alia. Our study is unique in that we compared four different detrending techniques, including Hodrick–Prescott (HP), Baxter-King, Christiano–Fitzgerald, and Butterworth filters. This is a departure from the conventional method of relying on the HP filter, which has been known to have limitations, particularly in the context of oil-producing economies. Our findings indicate that the selected oil-producing economies with countercyclical inflation patterns suggest that supply shocks drive the business cycles. Conversely, the oil-producing economies with inflation in sync (procyclical) with the business cycle suggest that demand shocks may be the primary driver of business cycle variations. Additionally, our study shows that oil price innovations lead to higher inflation in Nigeria.
Efficient path algorithms for clustered Lasso and OSCAR
Authors: Takahashi Atsumori , Nomura Shunichi
Published: September 2024

In high dimensional regression, clustering features according to their effects on outcomes is often as important as feature selection. For example, insurance premiums are set for each rate class pertaining to risk factors related to claim risk. To calculate reliable insurance premiums, it is often necessary to group the numerous rate classes into fewer classes. However, the combinations of ways to consolidate rate classes are vast, and it is computationally challenging to consider each combination individually. Under such circumstances, sparse regularization techniques for feature clustering are extremely useful as methods that automatically consolidate rate classes with no significant differences in risk levels during the estimation process. For this purpose, clustered Lasso and octagonal shrinkage and clustering algorithm for regression (OSCAR) can be used to generate feature groups automatically using pairwise $$L_1$$

L
1

norm and pairwise $$L_\infty $$

L
∞

norm, respectively. This paper proposes efficient path algorithms for clustered Lasso and OSCAR to construct solution paths with respect to their regularization parameters. Despite the excessive terms in exhaustive pairwise regularization, their computational costs are reduced by using the symmetry of those terms. Simple equivalent conditions to check subgradient equations in each feature group are derived using the graph theory. The proposed algorithms are shown to be more efficient than existing algorithms via numerical experiments.
Distributed hybrid quantum-classical performance prediction for hyperparameter optimization
Authors: Wulff Eric , Garcia Amboage Juan Pablo , Aach Marcel , Gislason Thorsteinn Eli , Ingolfsson Thorsteinn Kristinn , Ingolfsson Tomas Kristinn , Pasetto Edoardo , Delilbasic Amer , Riedel Morris , Sarma Rakesh , Girone Maria , Lintermann Andreas
Published: September 2024

Hyperparameter optimization (HPO) of neural networks is a computationally expensive procedure, which requires a large number of different model configurations to be trained. To reduce such costs, this work presents a distributed, hybrid workflow, that runs the training of the neural networks on multiple graphics processing units (GPUs) on a classical supercomputer, while predicting the configurations’ performance with quantum-trained support vector regression (QT-SVR) on a quantum annealer (QA). The workflow is shown to run on up to 50 GPUs and a QA at the same time, completely automating the communication between the classical and the quantum systems. The approach is evaluated extensively on several benchmarking datasets from the computer vision (CV), high-energy physics (HEP), and natural language processing (NLP) domains. Empirical results show that resource costs for performing HPO can be reduced by up to 9% when using the hybrid workflow with performance prediction, compared to using a plain HPO algorithm without performance prediction. Additionally, the workflow obtains similar and in some cases even better accuracy of the final hyperparameter configuration, when combining multiple heuristically obtained predictions from the QA, compared to using just a single classically obtained prediction. The results highlight the potential of hybrid quantum-classical machine learning algorithms. The workflow code is made available open-source to foster adoption in the community.
The role of adsorbent microstructure and its packing arrangement in optimising the performance of an adsorption column
Authors: Valverde Abel , Griffiths Ian M.
Published: September 2024

Physical adsorption takes place inside narrow pores where the attractive interaction between the surface of the adsorbent and the contaminant molecules is strong enough to retain the molecules. Adsorption columns involve a range of mass-transport mechanisms: advection through the free spaces between the adsorbent pellets, diffusion through the macro/mesopores of the adsorbent, and adsorption at the surface, where the micropores exist. The adsorbent specifications along with its assembly within the sorption column are key factors when optimizing the filtration of pollutants. In this work we present a mathematical model based on advection–diffusion equations coupled with Langmuir kinetics that accounts for a geometrical approach to the porosity structure inside the adsorbent, formed by a radial lattice of cylinders, and the channels through which the fluid flows surrounding the cylindrical pellets. The model is tested using typical lab-scale values based on VOC adsorption, and we use it to identify optimal macro/mesopore size and column porosity for energetic considerations.
Time-restricted feeding relieves high temperature-induced impairment on meat quality by activating the Nrf2/HO-1 pathway, modification of muscle fiber composition, and enriching the polyunsaturated fatty acids in pigs
Authors: Li Zhaojian , Wang Yiting , Yuan Peng , Zhu Yanli , Hu Ping , Song Tongxing , Liu Rui , Liu Hao-Yu , Cai Demin
Published: September 2024

To assess the effects of a time-restricted feeding (TRF) regimen on meat quality of pigs exposed to high ambient temperature, a two-month feeding and heat treatment (HT) trial was conducted using a 2 × 2 factorial design. A total of 24 growing pigs (11.0 ± 1.9 kg) were randomly divided into four groups: thermal neutral group (NT, 24 ± 3 °C), HT group (exposed to a high temperature at 35 ± 2 °C from 11:00 to 15:00), TRF group and HT + TRF group (HT and TRF co-treatment group, n = 6 for each group). Pigs in TRF groups got access to feed within 5 h from 9:00 to14:00, while the others were fed at 6:00, 11:30, and 16:00. All pigs received the same diet during the trail. The results showed that HT increased the drip loss, shear force, lightness, and malondialdehyde production in Longissimus thoracis et lumborum (LTL) muscle. TRF reversely reduced the shear force and drip loss, accompanied by decreased intramuscular fat and increased moisture content. Enhanced fiber transformation from type 1 to type 2b and down-regulated expression of muscle growth-related genes were observed by HT, while TRF suppressed the fiber transformation and expression of muscle atrophy-related genes. Furthermore, TRF restored the diminished protein expressions of Nrf2 and HO-1 in LTL muscle by chronic HT. Accumulation of HSP70 in muscle of HT group was reduced by treatment of TRF. HT declined the expression of vital genes involved in fatty acids poly-desaturation and the proportion of (polyunsaturated fatty acids) PUFAs, mainly omega-6 in LTL muscle, while TRF group promoted the expression of poly-desaturation pathway and displayed the highest proportion of PUFAs. These results demonstrated that TRF relieved the chronic high temperature affected meat quality by the restored expression of Nrf2/HO-1 anti-oxidative cascade, modified muscle fiber composition, and enriched PUFAs in LTL muscle.
Urban system equilibrium model in an asymmetric polycentric city and the influence of rail transit investment
Authors: Chen Yajuan , Tian Xin , Huang Han
Published: September 2024

Taking bus and subway into account, an asymmetric polycentric urban system equilibrium model is constructed to explore the impacts of rail transit on the distribution of residents and labor force in a linear polycentric urban system. By comparing the urban system equilibria before and after the introduction of rail transit, the influence of rail transit on urban performance is analyzed. The results show that the introduction of rail transit makes the advantaged center more attractive for the labor force, and further widens the economic level gap between the two business centers. Specifically, larger distance between the two commercial centers and the higher subway travel cost would strengthen the polarization effect caused by rail transit investment. Since the improvement of transportation makes it easier for residents to accept long-distance commuting and they are more willing to choose the jobs in the advanced center.
Class size and its influence on examination results in higher education
Authors: Abrahamsen Eirik Bjorheim , Moen Vegard , Asche Frank
Published: September 2024

In this article, we analyze the relationship between class sizes and examination results in higher education. Data from the University of Stavanger, collected in the Common Student System (FS) in the period from 2011 to 2021, shows that there is a negative correlation between the number of students enrolled on courses and examination results. An increase in the number of students taking a course reduces the average scores. We also show that the difference in examination results for different class sizes decreases when the course level increases.
Virtual Reflection Height of Nighttime Equatorial Ionosphere Estimated With Low‐Frequency Magnetic Sferics Measured in Malacca
Authors: Wang Yongping , Lu Gaopeng , Cheng Zhengwei , Niu Ziru , Chen Yazhou , Peng Kang‐Ming , York Seah Boon , Ahmad Mohd Riduan
Published: September 2024

The return stroke of cloud‐to‐ground (CG) lightning is an impulsive radiator of very low‐frequency/low‐frequency (VLF/LF) electromagnetic signals allowing for the remote sensing of lower ionosphere over large spatial coverage. In this study, we examined the LF magnetic fields measured in Malacca, Malaysia, to probe reflection heights of the lower ionosphere near the equator on three different nights in 2021. The results show that the virtual ionospheric height at nighttime typically ranged from 82.0 to 90.0 km, with a mean value of 85.3 km. Our measurements also revealed significant variations in the virtual ionospheric height across different regions over a spatial scale of about 800 km. The maximum height difference was about 5.0 km. Moreover, the fluctuation characteristics are observed in both estimated ionospheric height and calculated peak reflection ratio during similar periods. This fluctuation may be related to atmospheric gravity waves in the nighttime ionosphere. In addition, we compared the virtual ionospheric height estimated from CG strokes of different polarities, and the results showed that the virtual reflection height for positive CG strokes is lower than that for negative ones.
Streamflow Prediction in Human‐Regulated Catchments Using Multiscale Deep Learning Modeling With Anthropogenic Similarities
Authors: Tursun Arken , Xie Xianhong , Wang Yibing , Peng Dawei , Liu Yao , Zheng Buyun , Wu Xinran , Nie Cong
Published: September 2024

Accurate streamflow prediction in human‐regulated catchments remains a formidable challenge due to the complex disturbance of hydrological processes. To consider human disturbance in hydrological modeling, this study introduces a novel static attribute collection that combines river‐reach attributes with catchment attributes, referred to as multiscale attributes. The attribute collection is assembled into two deep learning (DL) methods, that is, the Long Short‐Term Memory (named as Multiscale LSTM) and the Differentiable Parameter Learning (DPL) model, and the performance is evaluated across 95 human‐regulated catchments in the United States (USA) and 24 catchments in the Yellow River Basin in China. In the USA, the Multiscale LSTM and the DPL models achieve similar performance with median Kling‐Gupta Efficiency (KGE) of 0.78 and 0.71, respectively. However, in the Yellow River Basin, the KGE values are 0.58 for Multiscale LSTM and 0.24 for DPL. These results highlight the DL models' ability to leverage multiscale attributes for improved performance compared to traditional catchment attributes. The performance of Multiscale LSTM and DPL models is predominantly influenced by river‐scale attributes, encompassing factors such as connectivity status index (CSI), degree of regulation (DOR), sediment trapping (SED), and number of dams. Additionally, satellite‐derived attributes such as mean and maximum river width (Width), slope and mean water surface elevation (WSE) from the Surface Water and Ocean Topography River Database (SWORD) contribute valuable insights into anthropogenic influences. Moreover, our study highlights the significance of selecting the appropriate training data period, which emerges as the most dominant factor affecting model performance across human‐regulated catchments. The diversity of data during the training period enables the model to capture a broad spectrum of hydrological signatures within these catchments. Consequently, this study emphasizes the advantages of Multiscale LSTM and underscores the significance of considering both natural and anthropogenic signatures to enhance hydrological predictions within human‐regulated environments.
The Response of the Venusian Upper Atmosphere During the Passage of Interplanetary Coronal Mass Ejections
Authors: Rout Diptiranjan , Thampi Smitha V. , Miyoshi Yoshizumi , Pant Tarun Kumar , Bhardwaj Anil
Published: September 2024

The current study explores the dynamic interaction between Interplanetary coronal mass ejections (ICMEs) and the induced magnetosphere of Venus, utilizing measurements from the Venus Express (VEX) mission. We have investigated 16 ICME events during the period 2006–2013. The altitude of the inbound bow shock and ionopause at Venus are comprehensively studied during the passage of these ICMEs. The ionosphere is found to be highly magnetized due to the very high magnetic pressure of the induced magnetosphere. Remarkably, the altitude of the ionopause is found to be significantly changed as compared to the previous quiet day due to the increased solar wind dynamic pressure . The ratio of the altitude of ionopause and magnitude of the magnetic field at ionopause on the event days to the quiet days shows a strong anti‐correlation which indicates the ionopause height is inversely related to the magnetic field. Intriguingly, the position of the bow shock exhibited minimal deviations compared to typical quiet days, underscoring that, during ICME events, the ionopause location is more responsive to solar wind pressure fluctuations than the bow shock location. Additionally, the heavy‐ion density near and above the ionopause is found to be significantly higher than that observed on previous quiet days. This substantial increase implies that ICMEs can induce atmospheric loss in Venus's atmosphere and also cause a significant reduction in the ionopause location.
Spatial Distribution and Wave Property of Dual‐Frequency EMIC Waves: Swarm Observations
Authors: Wang C. Z. , Wang H. , Zhang K. D. , Zhong Y. F. , Xia H. , Sun Y. , Cheng Q. H. , Leng Z. Y.
Published: September 2024

The spatial distributions of single‐frequency and dual‐frequency Electromagnetic ion cyclotron (EMIC) waves in the subauroral ionosphere are investigated under varying geomagnetic activities, using high‐resolution magnetic field data from dual Swarm satellites spanning from 2015 to 2017. Single‐frequency EMIC waves predominantly occur in the dawn sector, whereas dual‐frequency waves exhibit peaks around both dawn and dusk. The occurrence rate of dual‐frequency waves shows a more pronounced increase with increasing geomagnetic activity. As magnetic storms evolve, both types of EMIC waves shift from dusk to dawn. The South Atlantic Anomaly (SAA) emerges as a high‐incidence region for ionospheric EMIC waves. Dual‐frequency EMIC waves display lower frequencies compared to other regions. Additionally, the low‐frequency components of dual‐frequency waves observed at higher latitudes demonstrate greater power density and longer durations than their high‐frequency counterparts. This suggests that higher frequency waves experience more significant damping during propagation. Most dual‐frequency EMIC waves observed in the ionosphere belong to the O‐band and He‐band waves, indicating that magnetospheric bands below the cyclotron frequency of H+ are more likely to propagate into the ionosphere.
Tropical Cyclone‐Induced Ecological Responses and Their Feedback on Physical Fields: A Case Study for Hurricane Fernanda (2017)
Authors: Ye Shuoni , Zhang Rong‐Hua , Wang Hongna , Tian Feng , Shi Qidong
Published: September 2024

Tropical cyclones (TCs) are known to trigger chlorophyll bloom and boost local primary productivity. The characteristics of ocean ecological responses to TCs and their feedback on physical fields in the northeastern Pacific are investigated using a coupled ocean general circulation model‐ocean ecosystem model. A case study is carried out on Hurricane Fernanda (2017), which formed in the northeastern tropical Pacific. TC‐induced mixing and upwelling act to transport subsurface cold and nutrient‐rich waters into the mixed layer, leading to surface cooling and chlorophyll (CHL) bloom. The phytoplankton budget analyses indicate that the CHL bloom is dominated by small phytoplankton (PS) growth term, which is modulated by biological consumption terms (i.e., small zooplankton grazing and PS mortality) and physical processes‐related terms (i.e., advection and vertical mixing); biological consumption terms and physical processes tend to mainly offset the contributions from the PS growth term. Furthermore, CHL is found to exert feedback on physical fields. The CHL bloom mainly contributes to a decrease in surface temperature, thereby enhancing the temperature structure induced physically by TCs. This biofeedback on physical fields involves two mechanisms: a direct heating (OBH) due to ocean biology‐induced effect, and an indirect cooling effect due to dynamic processes associated with vertical mixing and advection. In particular, the CHL bloom‐induced sea surface temperature cooling is dominated by vertical mixing and modulated by the OBH effect and advection. These findings offer novel perspectives on TC‐induced ecological responses, as well as the related mechanisms for biofeedback on physical fields.
Large Eddy Simulations of the Interaction Between the Atmospheric Boundary Layer and Degrading Arctic Permafrost
Authors: Schlutow M. , Stacke T. , Doerffel T. , Smolarkiewicz P. K. , Göckede M.
Published: September 2024

Arctic permafrost thaw holds the potential to drastically alter the Earth's surface in Northern high latitudes. We utilize high‐resolution large eddy simulations to investigate the impact of the changing surfaces onto the neutrally stratified atmospheric boundary layer (ABL). A stochastic surface model based on Gaussian Random Fields modeling typical permafrost landscapes is established in terms of two land cover classes: grass land and open water bodies, which exhibit different surface roughness length and surface sensible heat flux. A set of experiments is conducted where two parameters, the lake areal fraction and the surface correlation length, are varied to study the sensitivity of the boundary layer with respect to surface heterogeneity. Our key findings from the simulations are the following: The lake areal fraction has a substantial impact on the aggregated sensible heat flux at the blending height where surface heterogeneities become horizontally homogenized. The larger the lake areal fraction, the smaller the sensible heat flux. This result gives rise to a potential feedback mechanism. When the Arctic dries due to climate heating, the interaction with the ABL may accelerate permafrost thaw. Furthermore, the blending height shows significant dependency on the correlation length of the surface features. A longer surface correlation length causes an increased blending height. This finding is of relevance for land surface models concerned with Arctic permafrost as they usually do not consider a heterogeneity metric comparable to the surface correlation length.
Assessing the Variability of Aerosol Optical Depth Over India in Response to Future Scenarios: Implications for Carbonaceous Aerosols
Authors: Anchan Nidhi L. , Swain Basudev , Sharma Amit , Singh Aishwarya , Malasani Chakradhar Reddy , Chandrasekharan Arundathi , Kumar Utkarsh , Ojha Narendra , Liu Pengfei , Vountas Marco , Gunthe Sachin S.
Published: September 2024

Air pollution caused by various anthropogenic activities and biomass burning continues to be a major problem in India. To assess the effectiveness of current air pollution mitigation measures, we used a 3D global chemical transport model to analyze the projected optical depth of carbonaceous aerosol (AOD) in India under representative concentration pathways (RCP) 4.5 and 8.5 over the period 2000–2100. Our results show a decrease in future emissions, leading to a decrease in modeled AOD under both RCPs after 2030. The RCP4.5 scenario shows a 48%–65% decrease in AOD by the end of the century, with the Indo‐Gangetic Plain (IGP) experiencing a maximum change of 25% by 2030 compared to 2010. Conversely, RCP8.5 showed an increase in AOD of 29% by 2050 and did not indicate a significant decrease by the end of the century. Our study also highlights that it is likely to take three decades for current policies to be effective for regions heavily polluted by exposure to carbonaceous aerosols, such as the IGP and eastern India. We emphasize the importance of assessing the effectiveness of current policies and highlight the need for continued efforts to address the problem of air pollution from carbonaceous aerosols, both from anthropogenic sources and biomass burning, in India.
HDAC7 is a potential therapeutic target in acute erythroid leukemia
Authors: Zhang Wenyu , Yamamoto Keita , Chang Yu-Hsuan , Yabushita Tomohiro , Hao Yangying , Shimura Ruka , Nakahara Jakushin , Shikata Shiori , Iida Kohei , Chen Qianyi , Zhang Xichen , Kitamura Toshio , Goyama Susumu
Published: September 2024

Acute erythroleukemia (AEL) is a rare subtype of acute myeloid leukemia with a poor prognosis. In this study, we established a novel murine AEL model with Trp53 depletion and ERG overexpression. ERG overexpression in Trp53-deficient mouse bone marrow cells, but not in wild-type bone marrow cells, leads to AEL development within two months after transplantation with 100% penetrance. The established mouse AEL cells expressing Cas9 can be cultured in vitro, induce AEL in vivo even in unirradiated recipient mice, and enable efficient gene ablation using the CRISPR/Cas9 system. We also confirmed the cooperation between ERG overexpression and TP53 inactivation in promoting the growth of immature erythroid cells in human cord blood cells. Mechanistically, ERG antagonizes KLF1 and inhibits erythroid maturation, whereas TP53 deficiency promotes proliferation of erythroid progenitors. Furthermore, we identified HDAC7 as a specific susceptibility in AEL by the DepMap-based two-group comparison analysis. HDAC7 promotes the growth of human and mouse AEL cells both in vitro and in vivo through its non-enzymatic functions. Our study provides experimental evidence that TP53 deficiency and ERG overexpression are necessary and sufficient for the development of AEL and highlights HDAC7 as a promising therapeutic target for this disease.
Deep-trap ultraviolet persistent phosphor for advanced optical storage application in bright environments
Authors: Lv Xulong , Liang Yanjie , Zhang Yi , Chen Dongxun , Shan Xihui , Wang Xiao-Jun
Published: September 2024

Extensive research has been conducted on visible-light and longer-wavelength infrared-light storage phosphors, which are utilized as promising rewritable memory media for optical information storage applications in dark environments. However, storage phosphors emitting in the deep ultraviolet spectral region (200–300 nm) are relatively lacking. Here, we report an appealing deep-trap ultraviolet storage phosphor, ScBO3:Bi3+, which exhibits an ultra-narrowband light emission centered at 299 nm with a full width at half maximum (FWHM) of 0.21 eV and excellent X-ray energy storage capabilities. When persistently stimulated by longer-wavelength white/NIR light or heated at elevated temperatures, ScBO3:Bi3+ phosphor exhibits intense and long-lasting ultraviolet luminescence due to the interplay between defect levels and external stimulus, while the natural decay in the dark at room temperature is extremely weak after X-ray irradiation. The impact of the spectral distribution and illuminance of ambient light and ambient temperature on ultraviolet light emission has been studied by comprehensive experimental and theoretical investigations, which elucidate that both O vacancy and Sc interstitial serve as deep electron traps for enhanced and prolonged ultraviolet luminescence upon continuous optical or thermal stimulation. Based on the unique spectral features and trap distribution in ScBO3:Bi3+ phosphor, controllable optical information read-out is demonstrated via external light or heat manipulation, highlighting the great potential of ScBO3:Bi3+ phosphor for advanced optical storage application in bright environments.
Lanthanide ion-doped upconversion nanoparticles for low-energy super-resolution applications
Authors: Lamon Simone , Yu Haoyi , Zhang Qiming , Gu Min
Published: September 2024

Energy-intensive technologies and high-precision research require energy-efficient techniques and materials. Lens-based optical microscopy technology is useful for low-energy applications in the life sciences and other fields of technology, but standard techniques cannot achieve applications at the nanoscale because of light diffraction. Far-field super-resolution techniques have broken beyond the light diffraction limit, enabling 3D applications down to the molecular scale and striving to reduce energy use. Typically targeted super-resolution techniques have achieved high resolution, but the high light intensity needed to outperform competing optical transitions in nanomaterials may result in photo-damage and high energy consumption. Great efforts have been made in the development of nanomaterials to improve the resolution and efficiency of these techniques toward low-energy super-resolution applications. Lanthanide ion-doped upconversion nanoparticles that exhibit multiple long-lived excited energy states and emit upconversion luminescence have enabled the development of targeted super-resolution techniques that need low-intensity light. The use of lanthanide ion-doped upconversion nanoparticles in these techniques for emerging low-energy super-resolution applications will have a significant impact on life sciences and other areas of technology. In this review, we describe the dynamics of lanthanide ion-doped upconversion nanoparticles for super-resolution under low-intensity light and their use in targeted super-resolution techniques. We highlight low-energy super-resolution applications of lanthanide ion-doped upconversion nanoparticles, as well as the related research directions and challenges. Our aim is to analyze targeted super-resolution techniques using lanthanide ion-doped upconversion nanoparticles, emphasizing fundamental mechanisms governing transitions in lanthanide ions to surpass the diffraction limit with low-intensity light, and exploring their implications for low-energy nanoscale applications.
Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy
Authors: Wang Shu , Pan Junlin , Zhang Xiao , Li Yueying , Liu Wenxi , Lin Ruolan , Wang Xingfu , Kang Deyong , Li Zhijun , Huang Feng , Chen Liangyi , Chen Jianxin
Published: September 2024

Diagnostic pathology, historically dependent on visual scrutiny by experts, is essential for disease detection. Advances in digital pathology and developments in computer vision technology have led to the application of artificial intelligence (AI) in this field. Despite these advancements, the variability in pathologists’ subjective interpretations of diagnostic criteria can lead to inconsistent outcomes. To meet the need for precision in cancer therapies, there is an increasing demand for accurate pathological diagnoses. Consequently, traditional diagnostic pathology is evolving towards “next-generation diagnostic pathology”, prioritizing on the development of a multi-dimensional, intelligent diagnostic approach. Using nonlinear optical effects arising from the interaction of light with biological tissues, multiphoton microscopy (MPM) enables high-resolution label-free imaging of multiple intrinsic components across various human pathological tissues. AI-empowered MPM further improves the accuracy and efficiency of diagnosis, holding promise for providing auxiliary pathology diagnostic methods based on multiphoton diagnostic criteria. In this review, we systematically outline the applications of MPM in pathological diagnosis across various human diseases, and summarize common multiphoton diagnostic features. Moreover, we examine the significant role of AI in enhancing multiphoton pathological diagnosis, including aspects such as image preprocessing, refined differential diagnosis, and the prognostication of outcomes. We also discuss the challenges and perspectives faced by the integration of MPM and AI, encompassing equipment, datasets, analytical models, and integration into the existing clinical pathways. Finally, the review explores the synergy between AI and label-free MPM to forge novel diagnostic frameworks, aiming to accelerate the adoption and implementation of intelligent multiphoton pathology systems in clinical settings.
Prenatal cannabis exposure is associated with alterations in offspring DNA methylation at genes involved in neurodevelopment, across the life course
Authors: Noble Alexandra J. , Adams Alex T. , Satsangi Jack , Boden Joseph M. , Osborne Amy J.
Published: September 2024

Prenatal cannabis exposure (PCE) is of increasing concern globally, due to the potential impact on offspring neurodevelopment, and its association with childhood and adolescent brain development and cognitive function. However, there is currently a lack of research addressing the molecular impact of PCE, that may help to clarify the association between PCE and neurodevelopment. To address this knowledge gap, here we present epigenome-wide association study data across multiple time points, examining the effect of PCE and co-exposure with tobacco using two longitudinal studies, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Christchurch Health and Development Study (CHDS) at birth (0 y), 7 y and 15–17 y (ALSPAC), and ~27 y (CHDS). Our findings reveal genome-wide significant DNA methylation differences in offspring at 0 y, 7 y, 15–17 y, and 27 y associated with PCE alone, and co-exposure with tobacco. Importantly, we identified significantly differentially methylated CpG sites within the genes LZTS2, NPSR1, NT5E, CRIP2, DOCK8, COQ5, and LRP5 that are shared between different time points throughout development in offspring. Notably, functional pathway analysis showed enrichment for differential DNA methylation in neurodevelopment, neurotransmission, and neuronal structure pathways, and this was consistent across all timepoints in both cohorts. Given the increasing volume of epidemiological evidence that suggests a link between PCE and adverse neurodevelopmental outcomes in exposed offspring, this work highlights the need for further investigation into PCE, particularly in larger cohorts.
Orexin receptor antagonists in the treatment of insomnia associated with psychiatric disorders: a systematic review
Authors: Kishi Taro , Koebis Michinori , Sugawara Michiko , Kawatsu Yuka , Taninaga Takehiro , Iwata Nakao
Published: September 2024

Insomnia is highly comorbid in patients with psychiatric disorders, including depression, bipolar disorder, and substance use disorders, and should be treated as an independent condition. Dual orexin receptor antagonists (DORAs) have been investigated as a treatment for chronic insomnia. The objective of this systematic review was to examine evidence for two DORAs, lemborexant and suvorexant, as treatments for insomnia comorbid with a psychiatric disorder. We searched PubMed, Cochrane, and Embase from their inception until January and April 2023, and included studies examining suvorexant and lemborexant for treating insomnia comorbid with psychiatric disorders. We also manually searched clinical trial registries (https://clinicaltrials.gov and https://www.umin.ac.jp/ctr). Randomized clinical trials and observational/cohort studies were included. We identified 18 studies from PubMed, Cochrane, and Embase and three studies from clinicaltrials.gov and UMIN. Of the 21 reports, four were completed/terminated randomized clinical trials, eight were ongoing clinical trials, and nine were observational studies. We identified evidence for switching from benzodiazepine receptor agonists to a DORA, or using a DORA as add-on therapy and, therefore, discuss this topic as well. Two studies examined switching to or adding on a DORA in patients being treated with a benzodiazepine receptor agonist. DORAs may be as effective and safe for treating psychiatric comorbid insomnia (for most psychiatric conditions) as they are for treating primary insomnia. However, the evidence is limited to a few small studies. Further investigation of DORAs for the treatment of comorbid insomnia in those with coexisting psychiatric conditions is warranted.