bluuebunny/crossref_metadata_2025 huggingface dataset:
Incarceration Trends in Italy Between Rising ‘Punitiveness’ and ‘Penal Moderation’
Authors: Ronco Daniela , Torrente Giovanni
Published: June 2024

The article analyses Italian incarceration trends and the impact of prison population increases on the criminal punishment system as a whole. “Correlating prison and community justice trends: an outline of net-widening” presents the interpretative framework and illustrates four events in recent Italian history that can be considered ‘breaking points’ if compared to the ordinary prison expansionism observed since the 1990s. Moreover, in comparing prison population and alternatives to imprisonment trends, it describes how the considerable expansion of community justice measures in the last ten years can contribute to shaping a net-widening scenario. “Imprisonment trends in Italy: restraint after the boom?” analyses the specificities of the Italian prison system compared to those of other European countries: overcrowding, pre-trial detention rates, migrants’ penal control, and short-term sentences. In the conclusions, we consider the extent to which the recent evolution of prison trends and some Italian specificities can be read in terms of increasing ‘punitiveness’ or, conversely, ‘penal moderation’.
Parameter-Efficient Multi-classification Software Defect Detection Method Based on Pre-trained LLMs
Authors: Wang Xuanye , Lu Lu , Yang Zhanyu , Tian Qingyan , Lin Haisha
Published: June 2024

Software Defect Detection (SDD) has always been critical to the development life cycle. A stable defect detection system can not only alleviate the workload of software testers but also enhance the overall efficiency of software development. Researchers have recently proposed various artificial intelligence-based SDD methods and achieved significant advancements. However, these methods still exhibit limitations in terms of reliability and usability. Therefore, we introduce MSDD-(IA)3, a novel framework leveraging the pre-trained CodeT5+ and (IA)3for parameter-efficient multi-classification SDD. This framework constructs a detection model based on pre-trained CodeT5+ to generate code representations while capturing defect-prone features. Considering the high overhead of pre-trained LLMs, we injects (IA)3vectors into specific layers, where only these injected parameters are updated to reduce the training cost. Furthermore, leveraging the properties of the pre-trained CodeT5+, we design a novel feature sequence that enriches the input data through the combination of source code with Natural Language (NL)-based expert metrics. Our experimental results on 64K real-world Python snippets show that MSDD-(IA)3demonstrates superior performance compared to state-of-the-art SDD methods, including PM2-CNN, in terms of F1-weighted, Recall-weighted, Precision-weighted, and Matthews Correlation Coefficient. Notably, the training parameters of MSDD-(IA)3are only 0.04% of those of the original CodeT5+. Our experimental data and code can be available at (https://gitee.com/wxyzjp123/msdd-ia3/).
CRGF-YOLO: An Optimized Multi-Scale Feature Fusion Model Based on YOLOv5 for Detection of Steel Surface Defects
Authors: Yu Tao , Luo Xu , Li Qiang , Li Lei
Published: June 2024

The identification of imperfections on steel surfaces is vital for ensuring the quality of industrial products. It requires the capability of real-time detection with high accuracy. This paper proposes the CRGF-YOLO (Contextual Reparameterized Generalized Feature) model based on YOLOv5. In the network, BottleneckCSP structures and depthwise separable convolutions utilizing the structural reparameterization are introduced to reduce the model size and improve performance. In addition, contextual transformer modules are employed as self-attention mechanisms to improve feature representations by capturing long-range dependencies, outperforming conventional convolutional networks. Furthermore, the simplified generalized feature pyramid network is embedded to aggregate multi-scale feature maps and enhance the network’s robustness. Finally, four prediction heads with different sizes are employed to predict defects, which are supported by prior bounding boxes generated using k-means clustering algorithm. The Focal-EIOU (Exponential Intersection over Union) loss function is introduced to improve detection accuracy and expedite model convergence. The improved model achieves a mean average precision (mAP) of 82.2% on the NEU-DET dataset, outperforming the baseline YOLOv5s by 7.7% mAP while maintaining real-time speeds. Comparative evaluations demonstrate CRGF-YOLO’s superior performance over previous state-of-the-art methods like Faster R-CNN (77.4% mAP), YOLOv3 (77.4% mAP), YOLOv7s (72.1% mAP), and YOLOv8s (78.7% mAP) for steel surface defect detection. Overall, this study provides valuable insights and practical guidance for the advancement of defect detection technology.
Elucidating the Link Between Anxiety/Depression and Alzheimer’s Dementia in the Australian Imaging Biomarkers and Lifestyle (AIBL) Study
Authors: Ma Liwei , Tan Edwin C. K. , Bush Ashley I. , Masters Colin L. , Goudey Benjamin , Jin Liang , Pan Yijun , Group AIBL Research
Published: June 2024

Background

The associations between mood disorders (anxiety and depression) and mild cognitive impairment (MCI) or Alzheimer’s dementia (AD) remain unclear.

Methods

Data from the Australian Imaging, Biomarker & Lifestyle (AIBL) study were subjected to logistic regression to determine both cross-sectional and longitudinal associations between anxiety/depression and MCI/AD. Effect modification by selected covariates was analysed using the likelihood ratio test.

Results

Cross-sectional analysis was performed to explore the association between anxiety/depression and MCI/AD among 2,209 participants with a mean [SD] age of 72.3 [7.4] years, of whom 55.4% were female. After adjusting for confounding variables, we found a significant increase in the odds of AD among participants with two mood disorders (anxiety: OR 1.65 [95% CI 1.04–2.60]; depression: OR 1.73 [1.12–2.69]). Longitudinal analysis was conducted to explore the target associations among 1,379 participants with a mean age of 71.2 [6.6] years, of whom 56.3% were female. During a mean follow-up of 5.0 [4.2] years, 163 participants who developed MCI/AD (refer to as PRO) were identified. Only anxiety was associated with higher odds of PRO after adjusting for covariates (OR 1.56 [1.03–2.39]). However, after additional adjustment for depression, the association became insignificant. Additionally, age, sex, and marital status were identified as effect modifiers for the target associations.

Conclusion

Our study provides supportive evidence that anxiety and depression impact on the evolution of MCI/AD, which provides valuable epidemiological insights that can inform clinical practice, guiding clinicians in offering targeted dementia prevention and surveillance programs to the at-risk populations.
Study on cellular uptake of a hydrophobic near-infrared-absorbing diradical-platinum(II) complex solubilized by albumin using hyperspectral imaging, spectrophotometry, and spectrofluorimetry
Authors: Sawamura Ryota , Masuya-Suzuki Atsuko , Iki Nobuhiko
Published: June 2024

Owing to its biopenetrability and minimal invasiveness, near-infrared (NIR) light in the region between 700–1100 nm has attracted attention in cancer diagnosis and therapy. Our group previously reported that the hydrophobic diradical-platinum(II) complex PtL2 is a promising agent for cancer photothermal therapy (L = 3,5-dibromo-1,2-diiminobenzosemiquinonate radical). Because PtL2 does not fluoresce, its intercellular uptake of PtL2 cannot be observed with a fluorescence microscope. In this study, we clarified the uptake and intracellular behavior of PtL2 solubilized by bovine serum albumin (BSA) using hyperspectral imaging enabling spectrophotometric analysis of the image. The spectral changes in the obtained images indicated that the internalization of PtL2 was followed by crystallization of the complex during the long incubation period (> 4 h). Additionally, the binding constant Kb = 5.91 × 104 M–1 could be estimated upon fluorescence quenching analysis of BSA upon binding of PtL2; Kb is two orders of magnitude smaller than that of albumin–common drugs. Considering the small Kb and low solubility of PtL2 in water, we ultimately proposed the internalization path and fate of PtL2 in the cell: release of PtL2 from BSA near cellular membranes and subsequent cellular uptake via membrane permeation followed by saturation, resulting in crystallization.

Graphical abstract
Growth-induced transformable surfaces realized by bending-active scissors grid
Authors: Ono Fuki , Kamijo Haruto , Kase Miwako , Nishimoto Seri , Sempuku Kotaro , Shigematsu Mizuki , Tachi Tomohiro
Published: June 2024

Ruffled surfaces that appear in biological forms, such as coral and lettuce, are a great source of inspiration for architectural and furniture design. This paper proposes a mechanism based on a bending-active scissors grid that effectively reproduces the process of differential growth. The structure can deploy from a linearly folded state with rotational symmetry to a complex ruffled surface without rotational symmetry. The deployed shape further exhibits a wave-like motion similar to the swimming gait of flatworms or cuttlefish. First, we propose a design method for the mechanism computed from the surface of constant negative Gaussian curvature. We then numerically analyze the symmetry-breaking process of deployment and zero-stiffness wave-like motion after deployment. We built two demonstrators to verify the deployment and the transformation. The first demonstrator with 1.5m diameter was fabricated to verify the symmetry-breaking deployment motion. The second demonstrator with 0.9m diameter was fabricated to demonstrate the wave-like motion by controlled pulling of the group of threads.
Healthcare spending in high-income and upper-middle-income countries: a cross-country analysis
Authors: Jayadevan C. M. , Trung Hoang Nam
Published: June 2024

This research investigates the determinants of government healthcare expenditure in high-income and upper-middle-income countries by exploring economic, demographic, and political influences. By analyzing data from 1990 to 2019 from 28 high-income and 42 upper-middle-income nations, this study employs Bayesian model averaging, the generalized method of moments, and regression discontinuity design. The results reveal that government healthcare spending positively correlates with the previous year's expenditure in both income groups. Additionally, the impact of education on spending differs, while it is positively significant in high-income countries, it is not significant in upper-middle-income countries. The proportion of elderly individuals positively influences healthcare spending in high-income countries but inconsistently influences healthcare spending in upper-middle-income countries. Urbanization significantly impacts spending in upper-middle-income nations. The positive association between industrial employment and spending suggests greater healthcare needs in such areas. Efforts to curb corruption positively affect spending differently for each income group. Out-of-pocket expenses negatively impact spending in both groups, though positively in high-income countries alone. The influence of the young population varies, being negative in high-income countries but positive in upper-middle-income countries. Logistic and probit regression models identify key determinants, including gross domestic product (GDP) per capita, elderly population proportion, out-of-pocket expenses, and corruption control measures in high-income countries. Policymakers can use these findings to tailor strategies, optimize healthcare spending, and ensure equitable access across income levels.
Sustainable approach to quality assurance in cement-improved soil: applications of handheld XRF for geotechnical solutions
Authors: Sindete Mathiro José , Usui Hirofumi , Some Donzala David , Hino Takenori
Published: June 2024

Traditional methods for evaluating the quality of the Deep Mixing Method (DMM) in Japan, such as the phenolphthalein tracer method, present limitations in ensuring strength improvement. This study explores handheld X-ray fluorescence (XRF) as a sustainable alternative for quality assessment. The elemental composition of cement-treated soil was investigated, focusing on Calcium (Ca), Silicate (Si), and Sulfate (S), which play crucial roles in the formation of hydrated products, aiming to accurately determine their influence on the strength development of the improved soil. A controlled protocol was employed using commercial Kaolin clay and the needle penetration test for strength assessment. Our laboratory experiments, conducted with a cement-based binder (C) dosage of 110 kg/m3 and a water-cement (W/C) ratio of 1, furthered our understanding of the hydration process. Results indicate an apparent increase in Ca amount over time, correlating with improved strength, while the apparent amount of Si decreases, suggesting its integration into hydration products such as C-S–H gel. Strength assessment rose significantly between day 1 and 28, aligning with variations observed in Si, Ca, and S, underlining their role in strength evolution. This research underscores the potential of handheld XRF as a sustainable substitute for conventional methods in field-quality assurance, offering real-time data on the formation of possible hydrated products during the hydration process for improved soil in geotechnical engineering.
Rethinking the Assessment of Work Intensity
Authors: Soucek Roman , Voss Amanda S.
Published: June 2024

Abstract: Digitalization and flexible work arrangements have profoundly changed workplaces and are often associated with an increasing work intensity, putting employees’ well-being at risk. To respond to increasing work intensity effectively, it is crucial to assess work intensity thoroughly and regularly. However, there are no specific measures that capture work intensity through a comprehensive and contemporary understanding. In two studies, we confirmed the factorial structure of a newly developed questionnaire and pictorial scales on work intensity, providing evidence for the verbal questionnaire’s convergent and incremental validity. The pictorial scales allow for a complementary methodological approach to the assessment of work intensity as measured by the questionnaire. Overall, the questionnaire allows for a comprehensive assessment of work intensity and the pictorial scales meet the demand for a simple and concise instrument suitable for repeated measures such as in the context of diary studies.
Quantifying Volumetric Scattering Bias in ICESat‐2 and Operation IceBridge Altimetry Over Greenland Firn and Aged Snow
Authors: Fair Zachary , Flanner Mark , Neumann Tom , Vuyovich Carrie , Smith Benjamin , Schneider Adam
Published: June 2024

The Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) mission has collected surface elevation measurements for over 5 years. ICESat‐2 carries an instrument that emits laser light at 532 nm, and ice and snow absorb weakly at this wavelength. Previous modeling studies found that melting snow could induce significant bias to altimetry signals, but there is no formal assessment on ICESat‐2 acquisitions during the melting season. We performed two case studies over the Greenland Ice Sheet to quantify bias in ICESat‐2 signals over snow: one to validate Airborne Topographic Mapper (ATM) data against Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS‐NG) grain sizes, and a second to estimate ICESat‐2 bias relative to ATM. We used snow optical grain sizes derived from ATM and AVIRIS‐NG to attribute altimetry bias to snowpack properties. For the first case study, the mean and standard deviation of optical grain sizes were 340 ± 65 µm (AVIRIS‐NG) and 670 ± 420 µm (ATM). A mean altimetry bias of 4.81 ± 1.76 cm was found for ATM, with larger biases linked to increases in grain size. In the second case study, we found a mean grain size of 910 ± 381 µm and biases of 6.42 ± 1.77 cm (ICESat‐2) and 9.82 ± 0.97 cm (ATM). The grain sizes and densities needed to recreate biases with a model are uncommon in nature, so we propose that additional surface attributes must be considered to characterize ICESat‐2 bias over snow. The altimetry biases are within the accuracy requirements of the ICESat‐2 mission, but we cannot rule out more significant errors over coarse‐grained snow.
The Limited Effect of Reduced Typhoon Frequency on Stream Hydrochemistry in a Subtropical Forest Watershed
Authors: Chang Chung‐Te , Huang Jr‐Chuan , Wang Lixin , Wang Hsiang‐Hua , Lee Jun‐Yi , Lin Teng‐Chiu
Published: June 2024

Tropical cyclones are often accompanied by large amount of precipitation potentially impacting stream hydrochemistry. Global warming is altering typhoon disturbance regime. Little is known about how cyclone changes, especially cyclone‐frequency reduction may affect stream hydrochemistry. In this study, we compared water and nutrient input via precipitation and output via streamflow between a frequent‐typhoon period (2013–2017), with 1.2 typhoon yr−1, and a no‐typhoon period (2018–2022) at a long‐term monitoring site, the Fushan Experimental Forest of Taiwan. Precipitation and streamflow quantities were not different between the two periods because typhoons increased the fluctuation but not the mean of monthly precipitation in the major typhoon months (July–September). Inputs of Mg2+, NO3−, and SO42− via precipitation were greater in the frequent‐typhoon period than the no‐typhoon period while inputs of other ions were not different between the two periods. Only the output of Mg2+ was different between the two periods, greater in the frequent‐typhoon period. Output/input ratio of NO3− was greater in the no‐typhoon period than the frequent‐typhoon period despite the greater input in the frequent‐typhoon period, while no differences were found for others. Increases in mineralization rates due to warming is suggested to be the cause of the greater NO3− output/input ratio during the no‐typhoon period. Relationships between stream discharge and ion export were similar between the two periods both with and without removing typhoon events. The limited variation in hydrochemistry between periods of contrasting cyclone activities suggests high resilience of the undisturbed subtropical forests to changes in cyclone frequency at the decadal scale.
Prediction of Solar Wind Speed Through Machine Learning From Extrapolated Solar Coronal Magnetic Field
Authors: Lin Rong , Luo Zhekai , He Jiansen , Xie Lun , Hou Chuanpeng , Chen Shuwei
Published: June 2024

An accurate solar wind (SW) speed model is important for space weather predictions, catastrophic event warnings, and other issues concerning SW—magnetosphere interaction. In this work, we construct a model based on convolutional neural network (CNN) and Potential Field Source Surface (PFSS) magnetic field maps, considering a SW source surface of RSS = 2.5R⊙, aiming to predict the SW speed at the Lagrange‐1 (L1) point of the Sun‐Earth system. The input of our model consists of four PFSS magnetic field maps at RSS, which are three, four, five, and six days before the target epoch. Reduced maps are used to promote the model's efficiency. We use the Global Oscillation Network Group (GONG) photospheric magnetograms and the potential field extrapolation model to generate PFSS magnetic field maps at the source surface. The model provides predictions of the quasi‐continuous test data set, which is generated by randomly assigning 120 data segments that are individually continuous in time, with an averaged correlation coefficient (CC) of 0.53 ± 0.07 and a root mean square error (RMSE) of 80.8 ± 4.8 km/s in an eight‐fold validation training scheme with the time resolution of the data as small as one hour. The model also has the potential to forecast high speed streams of the SW, which can be quantified with a general threat score of 0.39.
Distribution‐Based Model Evaluation and Diagnostics: Elicitability, Propriety, and Scoring Rules for Hydrograph Functionals
Authors: Vrugt Jasper A.
Published: June 2024

Distribution forecasts P over future quantities or events are routinely made in hydrology but usually traded for a (likelihood‐weighted) mean or median prediction to accommodate error measures or scoring functions such as the mean absolute error or mean squared error. Case in point is the so‐called KG efficiency (KGE) of Gupta et al. (2009, https://doi.org/10.1016/j.jhydrol.2009.08.003) and improvements thereof (Lamontagne et al., 2020, https://doi.org/10.1029/2020wr027101), which have rapidly gained popularity among hydrologists as alternative scoring functions to the commonly used Nash and Sutcliffe (1970, https://doi.org/10.1016/0022‐1694(70)90255‐6) efficiency, but are equally exclusive in how they quantify model performance using only single‐valued output of the quantities of interest. This point‐valued mapping necessarily implies a loss of information about model performance. This paper advocates the use of probabilistic watershed model training, evaluation and diagnostics. Distribution evaluation opens a mature literature on scoring rules whose strong statistical underpinning provides, as we will demonstrate, the theory, context and guidelines necessary for the development of robust information‐theoretically principled metrics for watershed signatures. These so‐called hydrograph functionals are scalar‐valued mappings of major behavioral watershed functions embodied in a strictly proper scoring rule. We discuss past developments that led to the current state‐of‐the‐art of distribution evaluation in hydrology and review scoring rules for dichotomous and categorical events, quantiles (intervals) and density forecasts. We are particularly concerned with elicitable functionals and scoring rule propriety, discuss the decomposition of scoring rules into a sharpness, reliability and entropy term and present diagnostically appealing strictly proper divergence scores of hydrograph functionals for flood frequency analysis, flow duration and recession curves. The usefulness and power of distribution‐based model evaluation and diagnostics by means of scoring rules is demonstrated on simple illustrative problems and discharge distributions simulated with watershed models using random sampling and Bayesian model averaging. The presented theory (a) enables a more complete evaluation of distribution forecasts, (b) offers a statistically principled means for watershed model training, evaluation, diagnostics and selection using hydrograph functionals and/or extreme events and (c) provides a universal framework for metric development of watershed signatures, promoting metric standardization and reproducibility.
In Situ Observations of Magnetic Reconnection Caused by the Interactions of Two Dipolarization Fronts
Authors: Jiang K. , Huang S. Y. , Wei Y. Y. , Yuan Z. G. , Xiong Q. Y. , Xu S. B. , Zhang J.
Published: June 2024

Using high‐resolution data from the Magnetospheric Multiscale mission, an electron‐only reconnection current sheet is found between two successive dipolarization fronts (DFs). The electron‐only reconnection occurs between the northward component of the magnetic field of the flux pileup region (FPR) of the first DF (DF1) and the southward component of the magnetic dip of the second DF (DF2). The faster DF2 compresses the FPR of DF1, which constitutes an anti‐parallel topology and reduces the thickness of the current sheet. Further analysis shows that the current sheet is unstable to the electron tearing instability, which may power the onset of the reconnection. Our results suggest that these two DFs may merge into one by the reconnection, which sheds light on the evolution of DFs during their earthward propagation.
A Multi‐Model Ensemble System for the Outer Heliosphere (MMESH): Solar Wind Conditions Near Jupiter
Authors: Rutala M. J. , Jackman C. M. , Owens M. J. , Tao C. , Fogg A. R. , Murray S. A. , Barnard L.
Published: June 2024

How the solar wind influences the magnetospheres of the outer planets is a fundamentally important question, but is difficult to answer in the absence of consistent, simultaneous monitoring of the upstream solar wind and the large‐scale dynamics internal to the magnetosphere. To compensate for the relative lack of in‐situ solar wind data, propagation models are often used to estimate the ambient solar wind conditions at the outer planets for comparison to remote observations or in‐situ measurements. This introduces another complication: the propagation of near‐Earth solar wind measurements introduces difficult‐to‐assess uncertainties. Here, we present the Multi‐Model Ensemble System for the outer Heliosphere (MMESH) to begin to address these issues, along with the resultant multi‐model ensemble (MME) of the solar wind conditions near Jupiter. MMESH accepts as input any number of solar wind models together with contemporaneous in‐situ spacecraft data. From these, the system characterizes typical uncertainties in model timing, quantifies how these uncertainties vary under different conditions, attempts to correct for systematic biases in the input model timing, and composes a MME with uncertainties from the results. For the Juno‐era (04/07/2016–04/07/2023) MME hindcast for Jupiter presented here, three solar wind propagation models were compared to in‐situ measurements from the near‐Jupiter spacecraft Ulysses and Juno spanning diverse geometries and phases of the solar cycle across >14,000 hr of data covering 2.5 decades. The MME gives the most‐probable near‐Jupiter solar wind conditions for times within the tested epoch, outperforming the input models and returning quantified estimates of uncertainty.
Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States
Authors: Huber Daniel E. , Kort Eric A. , Steiner Allison L.
Published: June 2024

Agricultural soils containing nitrogen‐rich fertilizers are a substantial source of reactive nitrogen to the atmosphere with potential to impact air quality. One form of reactive nitrogen, nitrogen oxides (NOx = NO + NO2), are a harmful air pollutant and form secondary pollutants, including particulate matter (PM) and ozone (O3). Soil nitrogen oxide emissions (SNOx) are heavily influenced by environmental conditions, however the understanding of the influence of environmental drivers on the behavior of SNOx is limited. Here, we implement a modified soil moisture‐dependent SNOx parameterization into the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) and investigate the impact on regional air quality in the central U.S. Evaluating against TROPOspheric Monitoring Instrument (TROPOMI) column NO2 observations, WRF‐Chem columns better capture the TROPOMI column magnitudes earlier in the growing season when using the updated SNOx parametrization, with modeled column bias improved to −1.1% over the most heavily fertilized regions. Evaluating against Environmental Protection Agency (EPA) surface NO2 observations, the relationship between surface NO2 and soil moisture is better represented in agriculturally‐dominant regions when using the updated parameterization, with greatest surface NO2 concentrations at moderate soil moisture and lower concentrations at wetter or drier soil conditions. In simulations, these SNOx lead to increased O3 in select urban regions, with more than double the occurrences of O3 exceeding the EPA 8‐hr O3 standard of 70 ppb.
Modeling Salt‐Verde Watershed Winter Precipitation Using Convection‐Permitting WRF‐Simulations With Water Vapor Tracers
Authors: Salamanca‐Palou Francisco , Svoma Bohumil , Walter James , Insua‐Costa Damian , Miguez‐Macho Gonzalo , Karanja Joseph , Georgescu Matei
Published: June 2024

This study characterizes moisture source regions for wintertime precipitation across the Salt‐Verde watershed and Arizona (USA) through use of convection‐permitting numerical experiments. We dynamically downscale three four‐month‐long (i.e., December‐January‐February‐March, or DJFM) winter periods: a representative warm (DJFM 1997–1998), cold (DJFM 1999–2000), and neutral (DJFM 2016–2017) winter, as diagnosed by the mean Sea Surface Temperature (SST) across the El Niño 3.4 region compared to a 1995 to 2019 baseline. We utilize the Weather Research and Forecasting (WRF) model with water vapor tracers (WVTs) to distinguish moisture source contributions to total precipitation across Arizona, as originating from land evapotranspiration, sea evaporation, and external advection. Analysis of our numerical experiments demonstrates that WRF is able to capture the day‐to‐day precipitation events across the complex terrain that is characteristic of the Salt‐Verde watershed, but seasonal accumulated precipitation is consistently overestimated compared to individual station observations. The spatial distribution of wintertime monthly accumulated precipitation across Arizona is well captured by WRF, although the total amount of rainfall is overestimated in some confined areas across the highlands of Arizona. Our convection‐permitting WRF experiments also demonstrate that WVT contributions to total wintertime precipitation are apportioned roughly equally between sea evaporation (contributing 45.6%) across the North America west coast and external advection (contributing 48.1%), with land evapotranspiration playing a minimal role (i.e., the remaining 6.3%). We further conduct single‐domain WRF experiments at non‐convection‐permitting resolution and conclude that local sea evaporation, bounded by 140°W and 100°W, is the primary moisture source region to total wintertime precipitation across the Salt‐Verde watershed and Arizona independent of the remote tropical SST across the El Niño 3.4 region.
Inhibition abilities and functional brain connectivity in school-aged term-born and preterm-born children
Authors: Disselhoff Vera , Jakab Andras , Latal Beatrice , Schnider Barbara , Wehrle Flavia M. , Hagmann Cornelia F. ,   the EpoKids Research Group, Held Ulrike , O’Gorman Ruth Tuura , Fauchère Jean-Claude , Hüppi Petra
Published: June 2024

Background

Inhibition abilities are known to have impact on self-regulation, behavior, and academic success, and they are frequently impaired in children born preterm. We investigated the possible contributions of resting-state functional brain connectivity to inhibition following preterm birth.

Methods

Forty-four preterm and 59 term-born participants aged 8–13 years were administered two inhibition tasks and resting-state functional MRI was performed. Functional connectivity (FC) networks were compared between groups using network-based statistics. Associations of FCNs and inhibition abilities were investigated through multivariate linear regression models accounting for the interaction between birth status and inhibition.

Results

NBS revealed weaker FC in children born preterm compared to term-born peers in connections between motor and supplementary motor regions, frontal lobe, precuneus, and insula. Irrespective of birth status, connections between the cerebellum, frontal, and occipital lobes and inter-lobar, subcortical, intra-hemispheric long-range connections were positively correlated with one of the two inhibition tasks.

Conclusions

Preterm birth results in long-term alterations of FC at network level but these FCN alterations do not specifically account for inhibition problems in children born very preterm.

Impact

Irrespective of birth status, significant associations were found between the subdomain of response inhibition and functional connectivity in some subnetworks.

A group comparisons of functional brain connectivity measured by rsfMRI in school-aged children born very preterm and at term.

The investigation of network-level functional connectivity at rest does not appear adequate to explain differences in inhibition abilities between children born very preterm and at term, hence other imaging techniques might be more suited to explore the underlying neural mechanisms of inhibition abilities in school-aged children born very preterm.
Identifying the role of (dis)inhibition in the vicious cycle of substance use through ecological momentary assessment and resting-state fMRI
Authors: Chirokoff Valentine , Berthoz Sylvie , Fatseas Melina , Misdrahi David , Dupuy Maud , Abdallah Majd , Serre Fuschia , Auriacombe Marc , Pfefferbaum Adolf , Sullivan Edith V. , Chanraud Sandra
Published: June 2024

Functional inhibition is known to improve treatment outcomes in substance use disorder (SUD), potentially through craving management enabled by underlying cerebral integrity. Whereas treatment is challenged by a multitude of substances that patients often use, no study has yet unraveled if inhibition and related cerebral integrity could prevent relapse from multiples substances, that is, one’s primary drug of choice and secondary ones. Individuals with primary alcohol, cannabis, or tobacco use disorders completed intensive Ecological Momentary Assessment (EMA) coupled with resting-state functional MRI (rs-fMRI) to characterize the extent to which inhibition and cerebral substrates interact with craving and use of primary and any substances. Participants were 64 patients with SUD and 35 healthy controls who completed one week EMA using Smartphones to report 5 times daily their craving intensity and substance use and to complete Stroop inhibition testing twice daily. Subsamples of 40 patients with SUD and 34 control individuals underwent rs-fMRI. Mixed Model Analysis revealed that reported use of any substance by SUD individuals predicted later use of any and primary substance, whereas use of the primary substance only predicted higher use of that same substances. Craving and inhibition level independently predicted later use but did not significantly interact. Preserved inhibition performance additionally influenced use indirectly by mediating the link between subsequent uses and by being linked to rs-fMRI connectivity strength in fronto-frontal and cerebello-occipital connections. As hypothesized, preserved inhibition performance, reinforced by the integrity of inhibitory neurofunctional substrates, may partake in breaking an unhealthy substance use pattern for a primary substance but may not generalize to non-target substances or to craving management.
Healthcare professionals’ perspectives on oral health care in acute stroke patients: a qualitative study
Authors: Konadu Akua Boakyewaa , Iwuozo Emmanuel U. , Sunkwa-Mills Gifty , Ayoola Yekeen A. , Manu Ewura A. , Hewlett Sandra A. , Dedey Florence , Abdulkadir Mohammed B. , Ogedegbe Olugbenga
Published: June 2024

Background

Stroke is a major public health problem, with the disabilities of the patients increasing their risk of poor oral health. Currently, in Ghana and Nigeria, no guideline exists for oral health care in stroke patients, while most of our acute stroke care settings have no documented protocol.

Aim

This study sought to understand the perspectives of healthcare professionals in Ghana and Nigeria about oral healthcare in acute stroke patients.

Methods

A qualitative inductive approach was employed to explore healthcare professionals’ perspectives. After obtaining informed consent, in-depth interviews were conducted among doctors, nurses, and physiotherapists using semi-structured question guides. Participants’ responses were audiotaped for transcription and analysis. Interviews were conducted until data saturation was reached. Data were analyzed thematically to generate themes and sub-themes using an inductive approach.

The results

Twenty-five (25) health care professionals (HCP) aged 25–60 years with a mean age of 36.2 ± 4.2 years were interviewed. There were 15 (60.0%) males and 10 (40.0%) females. HCP included nurse practitioners 14 (56.0%), medical doctors 7 (28.0%), and physiotherapists 4 (16.0%). The HCP demonstrated adequate knowledge of stroke and considered oral health important for esthetic and clinical reasons. They, however, reported being unable to give it the required attention due to inadequate collaboration between the various professional cadres, insufficient equipment, and a skewed focus on other clinical needs of the acute stroke patients.

Conclusions

The findings indicate that HCPs perceived oral health care as very important among patients with acute stroke. However, they reported a lack of collaboration and integration of oral health care in routine stroke care as a major impediment.
CXCR7 activation evokes the anti-PD-L1 antibody against glioblastoma by remodeling CXCL12-mediated immunity
Authors: Liu Chan-Chuan , Yang Wen-Bin , Chien Chia-Hung , Wu Cheng-Lin , Chuang Jian-Ying , Chen Pin-Yuan , Chu Jui-Mei , Cheng Siao Muk , Qiu Li-Ying , Chang Yung-Chieh , Hwang Daw-Yang , Huang Chih-Yuan , Lee Jung-Shun , Chang Kwang-Yu
Published: June 2024

The interaction between glioblastoma cells and glioblastoma-associated macrophages (GAMs) influences the immunosuppressive tumor microenvironment, leading to ineffective immunotherapies. We hypothesized that disrupting the communication between tumors and macrophages would enhance the efficacy of immunotherapies. Transcriptomic analysis of recurrent glioblastoma specimens indicated an enhanced neuroinflammatory pathway, with CXCL12 emerging as the top-ranked gene in secretory molecules. Single-cell transcriptome profiling of naïve glioblastoma specimens revealed CXCL12 expression in tumor and myeloid clusters. An analysis of public glioblastoma datasets has confirmed the association of CXCL12 with disease and PD-L1 expression. In vitro studies have demonstrated that exogenous CXCL12 induces pro-tumorigenic characteristics in macrophage-like cells and upregulated PD-L1 expression through NF-κB signaling. We identified CXCR7, an atypical receptor for CXCL12 predominantly present in tumor cells, as a negative regulator of CXCL12 expression by interfering with extracellular signal-regulated kinase activation. CXCR7 knockdown in a glioblastoma mouse model resulted in worse survival outcomes, increased PD-L1 expression in GAMs, and reduced CD8+ T-cell infiltration compared with the control group. Ex vivo T-cell experiments demonstrated enhanced cytotoxicity against tumor cells with a selective CXCR7 agonist, VUF11207, reversing GAM-induced immunosuppression in a glioblastoma cell-macrophage-T-cell co-culture system. Notably, VUF11207 prolonged survival and potentiated the anti-tumor effect of the anti-PD-L1 antibody in glioblastoma-bearing mice. This effect was mitigated by an anti-CD8β antibody, indicating the synergistic effect of VUF11207. In conclusion, CXCL12 conferred immunosuppression mediated by pro-tumorigenic and PD-L1-expressing GAMs in glioblastoma. Targeted activation of glioblastoma-derived CXCR7 inhibits CXCL12, thereby eliciting anti-tumor immunity and enhancing the efficacy of anti-PD-L1 antibodies.
CSTF3 contributes to platinum resistance in ovarian cancer through alternative polyadenylation of lncRNA NEAT1 and generating the short isoform NEAT1_1
Authors: Luo Xin , Wei Qinglv , Jiang Xiaoyan , Chen Ningxuan , Zuo Xinzhao , Zhao Hongyan , Liu Yujiao , Liu Xiaoyi , Xie Lingcui , Yang Yu , Liu Tao , Yi Ping , Xu Jing
Published: June 2024

Platinum-based chemotherapy is the standard postoperative adjuvant treatment for ovarian cancer (OC). Despite the initial response to chemotherapy, 85% of advanced OC patients will have recurrent disease. Relapsed disease and platinum resistance are the major causes of death in OC patients. In this study, we compared the global regulation of alternative polyadenylation (APA) in platinum-resistant and platinum-sensitive tissues of OC patients by analyzing a set of single-cell RNA sequencing (scRNA-seq) data from public databases and found that platinum-resistant patients exhibited global 3’ untranslated region (UTR) shortening due to the different usage of polyadenylation sites (PASs). The APA regulator CSTF3 was the most significantly upregulated gene in epithelial cells of platinum-resistant OC. CSTF3 knockdown increased the sensitivity of OC cells to platinum. The lncRNA NEAT1 has two isoforms, short (NEAT1_1) and long (NEAT1_2) transcript, because of the APA processing in 3’UTR. We found that CSTF3 knockdown reduced the usage of NEAT1 proximal PAS to lengthen the transcript and facilitate the expression of NEAT1_2. Downregulation of the expression of NEAT1 (NEAT1_1/_2), but not only NEAT1_2, also increased the sensitivity of OC cells to platinum. Overexpressed NEAT1_1 reversed the platinum resistance of OC cells after knocking down CSTF3 expression. Furthermore, downregulated expression of CSTF3 and NEAT1_1, rather than NEAT1_2, was positively correlated with inactivation of the PI3K/AKT/mTOR pathway in OC cells. Together, our findings revealed a novel mechanism of APA regulation in platinum-resistant OC. CSTF3 directly bound downstream of the NEAT1 proximal PAS to generate the short isoform NEAT1_1 and was conducive to platinum resistance, which provides a potential biomarker and therapeutic strategy for platinum-resistant OC patients.
Hippo kinases Mst1 and Mst2 maintain NK cell homeostasis by orchestrating metabolic state and transcriptional activity
Authors: Feng Peiran , Luo Liang , Yang Quanli , Meng Wanqing , Guan Zerong , Li Zhizhong , Sun Guodong , Dong Zhongjun , Yang Meixiang
Published: June 2024

Natural killer (NK) cells play a crucial role in immune response against viral infections and tumors. However, further investigation is needed to better understand the key molecules responsible for determining the fate and function of NK cells. In this study, we made an important discovery regarding the involvement of the Hippo kinases Mst1 and Mst2 as novel regulators in maintaining mouse NK cell homeostasis. The presence of high Mst1 and Mst2 (Mst1/2) activity in NK cells is essential for their proper development, survival and function in a canonical Hippo signaling independent mode. Mechanistically, Mst1/2 induce cellular quiescence by regulating the processes of proliferation and mitochondrial metabolism, thereby ensuring the development and survival of NK cells. Furthermore, Mst1/2 effectively sense IL-15 signaling and facilitate the activation of pSTAT3-TCF1, which contributes to NK cell homeostasis. Overall, our investigation highlights the crucial role of Mst1/2 as key regulators in metabolic reprogramming and transcriptional regulation for mouse NK cell survival and function, emphasizing the significance of cellular quiescence during NK cell development and functional maturation.
Mechanism of motoneuronal and pyramidal cell death in amyotrophic lateral sclerosis and its potential therapeutic modulation
Authors: Nógrádi Bernát , Nógrádi-Halmi Dóra , Erdélyi-Furka Barbara , Kádár Zalán , Csont Tamás , Gáspár Renáta
Published: June 2024

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder clinically characterized by muscle atrophy and progressive paralysis. Loss of motoneurons and pyramidal cells is thought to be the center piece of the complex and multifaceted ALS pathology, however, the exact mechanisms laying behind motoneuronal cell death in the spinal cord and motor cortex are still unknown. It was originally proposed that apoptosis plays a fundamental role in motoneuronal demise, nonetheless, later it became clear that other forms of regulated cell death, including necroptosis, pyroptosis, ferroptosis, and autophagy-dependent cell death, may also contribute to motoneuron loss. Over the past years, multiple studies aimed to improve our understanding of the contributory role of these mechanisms as well as to offer novel targets for potential therapeutic interventions. The pharmacological inhibition of the ferroptotic pathway and the modulation of the autophagic machinery seem to have particularly promising effects, reducing motoneuron loss and slowing disease progression in transgenic models of ALS. Nevertheless, the potential beneficial effects of necroptosis-targeting interventions were mostly disproven in the latest studies. In this review we aim to summarize the current view on regulated cell death mechanisms that lead to motoneuronal and pyramidal cell degeneration in ALS and showcase their applicability as future drug targets.
High-entropy relaxor ferroelectric ceramics for ultrahigh energy storage
Authors: Peng Haonan , Wu Tiantian , Liu Zhen , Fu Zhengqian , Wang Dong , Hao Yanshuang , Xu Fangfang , Wang Genshui , Chu Junhao
Published: June 2024

Dielectric ceramic capacitors with ultrahigh power densities are fundamental to modern electrical devices. Nonetheless, the poor energy density confined to the low breakdown strength is a long-standing bottleneck in developing desirable dielectric materials for practical applications. In this instance, we present a high-entropy tungsten bronze-type relaxor ferroelectric achieved through an equimolar-ratio element design, which realizes a giant recoverable energy density of 11.0 J·cm−3 and a high efficiency of 81.9%. Moreover, the atomic-scale microstructural study confirms that the excellent comprehensive energy storage performance is attributed to the increased atomic-scale compositional heterogeneity from high configuration entropy, which modulates the relaxor features as well as induces lattice distortion, resulting in reduced polarization hysteresis and enhanced breakdown endurance. This study provides evidence that developing high-entropy relaxor ferroelectric material via equimolar-ratio element design is an effective strategy for achieving ultrahigh energy storage characteristics. Our results also uncover the immense potential of tetragonal tungsten bronze-type materials for advanced energy storage applications.
Broad-spectrum activity against mosquito-borne flaviviruses achieved by a targeted protein degradation mechanism
Authors: Liu Han-Yuan , Li Zhengnian , Reindl Theresia , He Zhixiang , Qiu Xueer , Golden Ryan P. , Donovan Katherine A. , Bailey Adam , Fischer Eric S. , Zhang Tinghu , Gray Nathanael S. , Yang Priscilla L.
Published: June 2024

Viral genetic diversity presents significant challenges in developing antivirals with broad-spectrum activity and high barriers to resistance. Here we report development of proteolysis targeting chimeras (PROTACs) targeting the dengue virus envelope (E) protein through coupling of known E fusion inhibitors to ligands of the CRL4CRBN E3 ubiquitin ligase. The resulting small molecules block viral entry through inhibition of E-mediated membrane fusion and interfere with viral particle production by depleting intracellular E in infected Huh 7.5 cells. This activity is retained in the presence of point mutations previously shown to confer partial resistance to the parental inhibitors due to decreased inhibitor-binding. The E PROTACs also exhibit broadened spectrum of activity compared to the parental E inhibitors against a panel of mosquito-borne flaviviruses. These findings encourage further exploration of targeted protein degradation as a differentiated and potentially advantageous modality for development of broad-spectrum direct-acting antivirals.
Proteome allocation is linked to transcriptional regulation through a modularized transcriptome
Authors: Patel Arjun , McGrosso Dominic , Hefner Ying , Campeau Anaamika , Sastry Anand V. , Maurya Svetlana , Rychel Kevin , Gonzalez David J. , Palsson Bernhard O.
Published: June 2024

It has proved challenging to quantitatively relate the proteome to the transcriptome on a per-gene basis. Recent advances in data analytics have enabled a biologically meaningful modularization of the bacterial transcriptome. We thus investigate whether matched datasets of transcriptomes and proteomes from bacteria under diverse conditions can be modularized in the same way to reveal novel relationships between their compositions. We find that; (1) the modules of the proteome and the transcriptome are comprised of a similar list of gene products, (2) the modules in the proteome often represent combinations of modules from the transcriptome, (3) known transcriptional and post-translational regulation is reflected in differences between two sets of modules, allowing for knowledge-mapping when interpreting module functions, and (4) through statistical modeling, absolute proteome allocation can be inferred from the transcriptome alone. Quantitative and knowledge-based relationships can thus be found at the genome-scale between the proteome and transcriptome in bacteria.