bluuebunny/crossref_metadata_2025 huggingface dataset:
Forecasting the strength of preplaced aggregate concrete using interpretable machine learning approaches
Authors: Javed Muhammad Faisal , Fawad Muhammad , Lodhi Rida , Najeh Taoufik , Gamil Yaser
Published: April 2024

Preplaced aggregate concrete (PAC) also known as two-stage concrete (TSC) is widely used in construction engineering for various applications. To produce PAC, a mixture of Portland cement, sand, and admixtures is injected into a mold subsequent to the deposition of coarse aggregate. This process complicates the prediction of compressive strength (CS), demanding thorough investigation. Consequently, the emphasis of this study is on enhancing the comprehension of PAC compressive strength using machine learning models. Thirteen models are evaluated with 261 data points and eleven input variables. The result depicts that xgboost demonstrates exceptional accuracy with a correlation coefficient of 0.9791 and a normalized coefficient of determination (R2) of 0.9583. Moreover, Gradient boosting (GB) and Cat boost (CB) also perform well due to its robust performance. In addition, Adaboost, Voting regressor, and Random forest yield precise predictions with low mean absolute error (MAE) and root mean square error (RMSE) values. The sensitivity analysis (SA) reveals the significant impact of key input parameters on overall model sensitivity. Notably, gravel takes the lead with a substantial 44.7% contribution, followed by sand at 19.5%, cement at 15.6%, and Fly ash and GGBS at 5.9% and 5.1%, respectively. The best fit model i.e., XG-Boost model, was employed for SHAP analysis to assess the relative importance of contributing attributes and optimize input variables. The SHAP analysis unveiled the water-to-binder (W/B) ratio, superplasticizer, and gravel as the most significant factors influencing the CS of PAC. Furthermore, graphical user interface (GUI) have been developed for practical applications in predicting concrete strength. This simplifies the process and offers a valuable tool for leveraging the model's potential in the field of civil engineering. This comprehensive evaluation provides valuable insights to researchers and practitioners, empowering them to make informed choices in predicting PAC compressive strength in construction projects. By enhancing the reliability and applicability of predictive models, this study contributes to the field of preplaced aggregate concrete strength prediction.
HARNet in deep learning approach—a systematic survey
Authors: Kumar Neelam Sanjeev , Deepika G. , Goutham V. , Buvaneswari B. , Reddy R. Vijaya Kumar , Angadi Sanjeevkumar , Dhanamjayulu C. , Chinthaginjala Ravikumar , Mohammad Faruq , Khan Baseem
Published: April 2024

A comprehensive examination of human action recognition (HAR) methodologies situated at the convergence of deep learning and computer vision is the subject of this article. We examine the progression from handcrafted feature-based approaches to end-to-end learning, with a particular focus on the significance of large-scale datasets. By classifying research paradigms, such as temporal modelling and spatial features, our proposed taxonomy illuminates the merits and drawbacks of each. We specifically present HARNet, an architecture for Multi-Model Deep Learning that integrates recurrent and convolutional neural networks while utilizing attention mechanisms to improve accuracy and robustness. The VideoMAE v2 method (https://github.com/OpenGVLab/VideoMAEv2) has been utilized as a case study to illustrate practical implementations and obstacles. For researchers and practitioners interested in gaining a comprehensive understanding of the most recent advancements in HAR as they relate to computer vision and deep learning, this survey is an invaluable resource.
Novel T cell exhaustion gene signature to predict prognosis and immunotherapy response in thyroid carcinoma from integrated RNA-sequencing analysis
Authors: Li Yang , Wang Zhen , Lu Fangting , Miao Yahu , Feng Qing , Zhu Weixi , Kang Qingqing , Chen Yijing , Zhang Qiu
Published: April 2024

Exhausted CD8+ T lymphocytes and tumor-associated macrophages play critical roles in determining cancer prognosis and the efficacy of immunotherapy. Our study revealed a negative correlation between exhausted CD8+ T lymphocytes and prognosis in thyroid carcinoma (THCA). Consensus clustering divided patients into two subgroups of exhaustion with different prognoses, as defined by marker genes of exhausted CD8+ T cells. Subsequently, we constructed an eight-gene prognostic signature, and developed a risk score named the exhaustion-related gene score (ERGS) to forecast both prognosis and immunotherapy response in THCA. Bulk RNA sequencing analysis revealed a higher prevalence of M2 macrophages, indicative of an immunosuppressive tumor microenvironment (TME), in the high-ERGS group. Single-cell RNA sequencing showed that SPP1+ macrophages and CD14+ monocytes infiltrations were positively associated with higher ERGS. Functionally, it was determined that SPP1+ macrophages exert an immunosuppressive role, while CD14+ monocytes were implicated in promoting tumor progression and angiogenesis. Analysis of cell–cell interactions between SPP1+ macrophages and T cells highlighted the activation of the SPP1-CD44 and MIF-CD74 axes, both of which could foster an immunosuppressive TME. Therapeutic strategies that target SPP1+ macrophages, CD14+ monocytes, and the SPP1-CD44 and MIF-CD74 axes may potentially improve the prognosis and amplify the immunotherapy response in THCA patients.
Experimental analysis of rotating bridge structural responses to existing railway train loads via time–frequency and Hilbert–Huang transform energy spectral analysis
Authors: Liu Xu , Wu Honggang , Zhao Shouquan , Yang Xuehu
Published: April 2024

With the rapid development of national infrastructure projects, there has been a significant increase in intersecting lines in transportation construction. As a result, rotating bridges are increasingly used in engineering projects that span existing railway lines. In order to study the spatial response characteristics and vibration wave transmission mechanisms of the rotating bridge structure under the loading of existing railway trains, field experiments and numerical analyses were conducted. The response characteristics of these bridges were investigated under different types and speeds of adjacent existing lines. A comprehensive methodology has been proposed, integrating the time domain spectrum and the Hilbert–Huang Transform (HHT) energy spectrum for signal processing and vibration analysis. The analysis was carried out using MATLAB 2018a software. This methodology was applied to analyze the test data. The results show that significant resonance phenomenon occurs in the girders of the rotating bridge under the loading of trains on the existing line. The low-frequency component f1 (2–5 Hz) is the primary factor contributing to the amplification of the acceleration response in the rotating bridge, while f3 (10–13 Hz) plays a secondary role. The frequency distribution characteristics of vibration waves caused by train loads on the existing line have a significant influence on the acceleration response of the rotating bridge's girders. The predominant frequency of vibration waves at each measuring point along the transmission path shows a trend of decreasing → increasing → decreasing. The impact on the rotating bridge structure of vibration waves generated by low-speed freight trains on existing railways is greater. The research findings are of great importance for studying the dynamic response of rotating bridges adjacent to existing railway lines.
Urban segregation on multilayered transport networks: a random walk approach
Authors: Neira Mateo , Molinero Carlos , Marshall Stephen , Arcaute Elsa
Published: April 2024

We present a novel method for analysing socio-spatial segregation in cities by considering constraints imposed by transportation networks. Using a multilayered network approach, we model the interaction probabilities of socio-economic groups with random walks and Lévy flights. This method allows for evaluation of new transport infrastructure’s impact on segregation while quantifying each network’s contribution to interaction opportunities. The proposed random walk segregation index measures the probability of individuals encountering diverse social groups based on their available means of transit via random walks. The index incorporates temporal constraints in urban mobility with a parameter, $$\alpha \in [0,1)$$

α
∈
[
0
,
1
)

, of the probability of the random walk continuing at each time step. By applying this to a toy model and conducting a sensitivity analysis, we explore how the index changes dependent on this temporal constraint. When the parameter equals zero, the measure simplifies to an isolation index. When the parameter approaches one it represents the city’s overall socio-economic distribution by mirroring the steady-state of the random walk process. Using Cuenca, Ecuador as a case study, we illustrate the method’s applicability in transportation planning as a valuable tool for policymakers, addressing spatial distribution of socio-economic groups and the connectivity of existing transport networks, thus promoting equitable interactions throughout the city.
Fiber optics passive monitoring of groundwater temperature reveals three-dimensional structures in heterogeneous aquifers
Authors: Furlanetto Davide , Camporese Matteo , Schenato Luca , Costa Leonardo , Salandin Paolo
Published: April 2024

Alluvial aquifers often exhibit highly conductive embedded formations that can act as preferential pathways for the transport of solutes. In this context, a detailed subsurface characterization becomes crucial for an effective monitoring of groundwater quality and early detection of contaminants. However, small-scale heterogeneities are seldom detected by traditional nondestructive investigations. Heat propagation in porous media can be a relatively inexpensive tracer for groundwater flow, potentially offering valuable information in various applications. In this study, we applied passive Fiber Optics Distributed Temperature Sensing (FO-DTS) to a group of observation wells in a highly heterogeneous phreatic aquifer to uncover structures with different hydraulic conductivity, relying on their response to temperature fluctuations triggered by natural and anthropogenic forcings. A comprehensive data analysis approach, combining statistical methods and physics-based numerical modeling, allowed for a three-dimensional characterization of the subsurface at the experimental site with unprecedentedly high resolution.
Highly biomimetic spiking neuron using SiGe heterojunction bipolar transistors for energy-efficient neuromorphic systems
Authors: Kim Yijoon , Kim Hyangwoo , Oh Kyounghwan , Park Ju Hong , Baek Chang-Ki
Published: April 2024

We demonstrate a highly biomimetic spiking neuron capable of fast and energy-efficient neuronal oscillation dynamics. Our simple neuron circuit is constructed using silicon–germanium heterojunction based bipolar transistors (HBTs) with nanowire structure. The HBT has a hysteresis window with steep switching characteristics and high current margin in the low voltage range, which enables a high spiking frequency (~ 245 kHz) with low energy consumption (≤ 1.37 pJ/spike). Also, gated structure achieves a stable balance in the activity of the neural system by incorporating both excitatory and inhibitory signal. Furthermore, inhibition of multiple strengths can be realized by adjusting the integration time according to the amplitude of the inhibitory signal. In addition, the spiking frequency can be tuned by mutually controlling the hysteresis window in the HBTs. These results ensure the sparse activity and homeostasis of neural networks.
Antioxidant capacity sources of soils under different land uses
Authors: Ćwieląg-Piasecka Irmina , Łyczko Jacek , Jamroz Elżbieta , Kocowicz Andrzej , Kawałko Dorota
Published: April 2024

Antioxidants (AOX) in soils originate mainly from secondary plant metabolites and are pivotal in many redox processes in environment, maintaining soil quality. Still, little is known about the influence of land uses on their accumulation in soil. The aim of the paper was to determine the content of these redox-active compounds in the extracts of A horizons of abandoned fallows, arable and woodland soils. Total antioxidant capacity (TAC) of soils under various uses and vegetation was evaluated in different soil extracts using Folin-Ciocâlteu method. The contribution of humic acids to TAC was determined and antioxidant profiles estimated using the chromatographic GC–MS method. Forest soils exhibited the highest TAC (15.5 mg g−1) and AOX contents (4.34 mg g−1), which were positively correlated with soil organic carbon content. It was estimated that humic acids contribute to over 50% of TAC in soils. The main phenolics in woodland A horizons were isovanillic and p-hydroxybenzoic acid (p-HA), while esculetin and p-HA predominated in the abandoned fallows due to the prevalence of herbaceous vegetation. Cultivated soils were the most abundant in p-HA (56.42%). In the studied topsoils, there were considerable amounts of aliphatic organic matter, which role in redox processes should be further evaluated.
Incidence of coronary heart disease among remote workers: a nationwide web-based cohort study
Authors: Zaitsu Masayoshi , Ishimaru Tomohiro , Tsushima Saki , Muramatsu Keiji , Ando Hajime , Nagata Tomohisa , Eguchi Hisashi , Tateishi Seiichiro , Tsuji Mayumi , Fujino Yoshihisa
Published: April 2024

Coronary heart disease (CHD) risk is influenced by socioeconomic status-related parameters, particularly occupation. We investigated occupational gaps in CHD risk and how the introduction of remote work moderated the observed occupational differences in CHD risk during the coronavirus disease 2019 pandemic in Japan. Data from a web-based, nationwide cohort study, comprising 17,640 workers (aged 20–65 years) with baseline data from December 2020, were analyzed. Participants were grouped by occupation as upper-level nonmanual workers (managers/professionals) and others (reference group). The primary outcome was CHD (angina pectoris/myocardial infarction) onset retrospectively confirmed at the 1-year follow-up survey. Upper-level nonmanual workers exhibited a higher CHD incidence than others (2.3% vs. 1.7%). This association was pronounced in the younger (20–49 years) population, with a significant CHD risk (adjusted risk ratio = 1.88). Upper-level nonmanual workers exhibited nearly 15% higher remote work prevalence, with a significant remote work-related CHD risk (adjusted risk ratio = 1.92). The mediating effects of remote work explained an overall disparity of 32% among the younger population. Occupational gaps in CHD incidence in Japan differ from those in Western countries, where upper-level nonmanual workers have lower cardiovascular risk. In Japan, remote work can mediate CHD risk in the younger population of upper-level nonmanual workers.
Longitudinal markers of cerebral amyloid angiopathy and related inflammation in rTg-DI rats
Authors: Schrader Joseph M. , Xu Feng , Agostinucci Kevin J. , DaSilva Nicholas A. , Van Nostrand William E.
Published: April 2024

Cerebral amyloid angiopathy (CAA) is a prevalent vascular dementia and common comorbidity of Alzheimer’s disease (AD). While it is known that vascular fibrillar amyloid β (Aβ) deposits leads to vascular deterioration and can drive parenchymal CAA related inflammation (CAA-ri), underlying mechanisms of CAA pathology remain poorly understood. Here, we conducted brain regional proteomic analysis of early and late disease stages in the rTg-DI CAA rat model to gain molecular insight to mechanisms of CAA/CAA-ri progression and identify potential brain protein markers of CAA/CAA-ri. Longitudinal brain regional proteomic analysis revealed increased differentially expressed proteins (DEP) including ANXA3, HTRA1, APOE, CST3, and CLU, shared between the cortex, hippocampus, and thalamus, at both stages of disease in rTg-DI rats. Subsequent pathway analysis indicated pathway enrichment and predicted activation of TGF-β1, which was confirmed by immunolabeling and ELISA. Further, we identified numerous CAA related DEPs associate with astrocytes (HSPB1 and MLC1) and microglia (ANXA3, SPARC, TGF-β1) not previously associated with astrocytes or microglia in other AD models, possibly indicating that they are specific to CAA-ri. Thus, the data presented here identify several potential brain protein biomarkers of CAA/CAA-ri while providing novel molecular and mechanistic insight to mechanisms of CAA and CAA-ri pathological progression and glial cell mediated responses.
Microbe cultivation guidelines to optimize rhamnolipid applications
Authors: Kłosowska-Chomiczewska Ilona E. , Macierzanka Adam , Parchem Karol , Miłosz Pamela , Bladowska Sonia , Płaczkowska Iga , Hewelt-Belka Weronika , Jungnickel Christian
Published: April 2024

In the growing landscape of interest in natural surfactants, selecting the appropriate one for specific applications remains challenging. The extensive, yet often unsystematized, knowledge of microbial surfactants, predominantly represented by rhamnolipids (RLs), typically does not translate beyond the conditions presented in scientific publications. This limitation stems from the numerous variables and their interdependencies that characterize microbial surfactant production. We hypothesized that a computational recipe for biosynthesizing RLs with targeted applicational properties could be developed from existing literature and experimental data. We amassed literature data on RL biosynthesis and micellar solubilization and augmented it with our experimental results on the solubilization of triglycerides (TGs), a topic underrepresented in current literature. Utilizing this data, we constructed mathematical models that can predict RL characteristics and solubilization efficiency, represented as logPRL = f(carbon and nitrogen source, parameters of biosynthesis) and logMSR = f(solubilizate, rhamnolipid (e.g. logPRL), parameters of solubilization), respectively. The models, characterized by robust R2 values of respectively 0.581–0.997 and 0.804, enabled the ranking of descriptors based on their significance and impact—positive or negative—on the predicted values. These models have been translated into ready-to-use calculators, tools designed to streamline the selection process for identifying a biosurfactant optimally suited for intended applications.
AI-driven remote sensing enhances Mediterranean seagrass monitoring and conservation to combat climate change and anthropogenic impacts
Authors: Chowdhury Masuma , Martínez-Sansigre Alejo , Mole Maruška , Alonso-Peleato Eduardo , Basos Nadiia , Blanco Jose Manuel , Ramirez-Nicolas Maria , Caballero Isabel , de la Calle Ignacio
Published: April 2024

Seagrasses are undergoing widespread loss due to anthropogenic pressure and climate change. Since 1960, the Mediterranean seascape lost 13–50% of the areal extent of its dominant and endemic seagrass-Posidonia oceanica, which regulates its ecosystem. Many conservation and restoration projects failed due to poor site selection and lack of long-term monitoring. Here, we present a fast and efficient operational approach based on a deep-learning artificial intelligence model using Sentinel-2 data to map the spatial extent of the meadows, enabling short and long-term monitoring, and identifying the impacts of natural and human-induced stressors and changes at different timescales. We apply ACOLITE atmospheric correction to the satellite data and use the output to train the model along with the ancillary data and therefore, map the extent of the meadows. We apply noise-removing filters to enhance the map quality. We obtain 74–92% of overall accuracy, 72–91% of user’s accuracy, and 81–92% of producer’s accuracy, where high accuracies are observed at 0–25 m depth. Our model is easily adaptable to other regions and can produce maps in in-situ data-scarce regions, providing a first-hand overview. Our approach can be a support to the Mediterranean Posidonia Network, which brings together different stakeholders such as authorities, scientists, international environmental organizations, professionals including yachting agents and marinas from the Mediterranean countries to protect all P. oceanica meadows in the Mediterranean Sea by 2030 and increase each country’s capability to protect these meadows by providing accurate and up-to-date maps to prevent its future degradation.
Occurrence, distribution, and ecological risk assessment of heavy metals in Chao Phraya River, Thailand
Authors: Niampradit Sarima , Kiangkoo Nuttapohn , Mingkhwan Rachaneekorn , Kliengchuay Wissanupong , Worakhunpiset Suwalee , Limpananont Yanin , Hongsibsong Surat , Inthorn Duangrat , Tantrakarnapa Kraichat
Published: April 2024

Understanding heavy metals in rivers is crucial, as their presence and distribution impact water quality, ecosystem health, and human well-being. This study examined the presence and levels of nine heavy metals (Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn) in 16 surface water samples along the Chao Phraya River, identifying Fe, Mn, Zn, and Cr as predominant metals. Although average concentrations in both rainy and dry seasons generally adhered to WHO guidelines, Mn exceeded these limits yet remained within Thailand’s acceptable standards. Seasonal variations were observed in the Chao Phraya River, and Spearman’s correlation coefficient analysis established significant associations between season and concentrations of heavy metals. The water quality index (WQI) demonstrated varied water quality statuses at each sampling point along the Chao Phraya River, indicating poor conditions during the rainy season, further deteriorating to very poor conditions in the dry season. The hazard potential index (HPI) was employed to assess heavy metal contamination, revealing that during the dry season in the estuary area, the HPI value exceeded the critical threshold index, indicating the presence of heavy metal pollution in the water and unsuitable for consumption. Using the species sensitivity distribution model, an ecological risk assessment ranked the heavy metals’ HC5 values as Pb > Zn > Cr > Cu > Hg > Cd > Ni, identifying nickel as the most detrimental and lead as the least toxic. Despite Cr and Zn showing a moderate risk, and Cu and Ni posing a high risk to aquatic organisms, the main contributors to ecological risk were identified as Cu, Ni, and Zn, suggesting a significant potential ecological risk in the Chao Phraya River’s surface water. The results of this study provide fundamental insights that can direct future actions in preventing and managing heavy metal pollution in the river ecosystem.
Overburden failure and water–sand mixture outburst conditions of weakly consolidated overlying strata in Dananhu No.7 coal mine
Authors: Zhu Jingzhong , Li Wenping , Teng Bo , Lu Qinggang , Li Dongding , Li Liangning
Published: April 2024

This study presents a case of weakly consolidated strata developed in Dananhu No.7 coal mine. Using a combination of numerical simulation, field measurement comparison, and the critical hydraulic gradient criterion, we investigate the overburden failure and the risk possibility of water–sand mixture inrush during excavation. The following are the principal findings: (1) Weakly consolidated rocks have poor physical characteristics, particularly when they are mudded and disintegrated after encountering water, which may become a favorable source of water–sand inrush; (2) The water-conducting zone develops to a height of 160.5 m with a crack-mining ratio of 15.29 times, extending upward to Toutunhe Formation aquifer. The predictions are consistent with measurements in adjacent mines with similar geological conditions; (3) Cracks without larger subsidence are developed at the front edge of the mining direction, and some parallel stepped cracks behind the goaf could be easily observed. Ground subsidence along the goaf center finally displays a symmetrically wide-gentle U shape; (4) The critical hydraulic gradient of Toutunhe Formation aquifer, aquifer above 3# coal seam, and aquifer of 3#–7# coal seam in Xishanyao Formation is 1.314, 1.351, and 1.380, the actual value is 0.692, 2.089, and 7.418 accordingly. It is inferred water–sand mixture outburst will not occur in Toutunhe Formation aquifer, while the potential risk exists in the aquifers of Xishanyao Formation. Through drainage and depressurization projects, a water–sand mixture outburst accident does not occur during excavation. This study reveals the overburden failure characteristics and the initiation mechanism of water–sand inrush in weakly cemented strata, as well as the internal relationship between them, which provides new research ideas for safe operation in other mining areas with similar geological conditions. The research work has certain practical guiding significance.
Understanding the errors made by artificial intelligence algorithms in histopathology in terms of patient impact
Authors: Evans Harriet , Snead David
Published: April 2024

An increasing number of artificial intelligence (AI) tools are moving towards the clinical realm in histopathology and across medicine. The introduction of such tools will bring several benefits to diagnostic specialities, namely increased diagnostic accuracy and efficiency, however, as no AI tool is infallible, their use will inevitably introduce novel errors. These errors made by AI tools are, most fundamentally, misclassifications made by a computational algorithm. Understanding of how these translate into clinical impact on patients is often lacking, meaning true reporting of AI tool safety is incomplete. In this Perspective we consider AI diagnostic tools in histopathology, which are predominantly assessed in terms of technical performance metrics such as sensitivity, specificity and area under the receiver operating characteristic curve. Although these metrics are essential and allow tool comparison, they alone give an incomplete picture of how an AI tool’s errors could impact a patient’s diagnosis, management and prognosis. We instead suggest assessing and reporting AI tool errors from a pathological and clinical stance, demonstrating how this is done in studies on human pathologist errors, and giving examples where available from pathology and radiology. Although this seems a significant task, we discuss ways to move towards this approach in terms of study design, guidelines and regulation. This Perspective seeks to initiate broader consideration of the assessment of AI tool errors in histopathology and across diagnostic specialities, in an attempt to keep patient safety at the forefront of AI tool development and facilitate safe clinical deployment.
A multifunctional display based on photo-responsive perovskite light-emitting diodes
Authors: Bao Chunxiong , Yuan Zhongcheng , Niu Wenxiao , Yang Jie , Wang Zijian , Yu Tao , Wang Jianpu , Gao Feng
Published: April 2024

Current display screens are typically only used for information display, but can have a range of different sensors integrated into them for functions such as touch control, ambient light sensing and fingerprint sensing. Photo-responsive light-emitting diodes (LEDs), which can display information and respond to light excitation, could be used to develop future ultra-thin and large screen-to-body ratio screens. However, photo-response is difficult to achieve with conventional display technologies. Here, we report a multifunctional display that uses photo-responsive metal halide perovskite LEDs as pixels. The perovskite LED display can be simultaneously used as a touch screen, ambient light sensor and image sensor (including for fingerprint drawing) without integrating any additional sensors. The light-to-electricity conversion efficiency of the pixels also allow the display to act as a photovoltaic device that can charge the equipment.
Genetic associations of risk behaviours and educational achievement
Authors: Arellano Spano Michelle , Morris Tim T. , Davies Neil M. , Hughes Amanda
Published: April 2024

Risk behaviours are common in adolescent and persist into adulthood, people who engage in more risk behaviours are more likely to have lower educational attainment. We applied genetic causal inference methods to explore the causal relationship between adolescent risk behaviours and educational achievement. Risk behaviours were phenotypically associated with educational achievement at age 16 after adjusting for confounders (−0.11, 95%CI: −0.11, −0.09). Genomic-based restricted maximum likelihood (GREML) results indicated that both traits were heritable and have a shared genetic architecture (Risk $${{{{{{\boldsymbol{h}}}}}}}^{{{{{{\boldsymbol{2}}}}}}}$$

h

2

 = 0.18, 95% CI: −0.11,0.47; education $${{{{{{\boldsymbol{h}}}}}}}^{{{{{{\boldsymbol{2}}}}}}}$$

h

2

 = 0.60, 95%CI: 0.50,0.70). Consistent with the phenotypic results, genetic variation associated with risk behaviour was negatively associated with education ($${{{{{{\boldsymbol{r}}}}}}}_{{{{{{\boldsymbol{g}}}}}}}$$

r

g

 = −0.51, 95%CI: −1.04,0.02). Lastly, the bidirectional MR results indicate that educational achievement or a closely related trait is likely to affect risk behaviours PGI (β=−1.04, 95% CI: −1.41, −0.67), but we found little evidence that the genetic variation associated with risk behaviours affected educational achievement (β=0.00, 95% CI: −0.24,0.24). The results suggest engagement in risk behaviour may be partly driven by educational achievement or a closely related trait.
Revealing myopathy spectrum: integrating transcriptional and clinical features of human skeletal muscles with varying health conditions
Authors: Zhong Huahua , Sian Veronica , Johari Mridul , Katayama Shintaro , Oghabian Ali , Jonson Per Harald , Hackman Peter , Savarese Marco , Udd Bjarne
Published: April 2024

Myopathy refers to a large group of heterogeneous, rare muscle diseases. Bulk RNA-sequencing has been utilized for the diagnosis and research of these diseases for many years. However, the existing valuable sequencing data often lack integration and clinical interpretation. In this study, we integrated bulk RNA-sequencing data from 1221 human skeletal muscles (292 with myopathies, 929 controls) from both databases and our local samples. By applying a method similar to single-cell analysis, we revealed a general spectrum of muscle diseases, ranging from healthy to mild disease, moderate muscle wasting, and severe muscle disease. This spectrum was further partly validated in three specific myopathies (97 muscles) through clinical features including trinucleotide repeat expansion, magnetic resonance imaging fat fraction, pathology, and clinical severity scores. This spectrum helped us identify 234 genuinely healthy muscles as unprecedented controls, providing a new perspective for deciphering the hallmark genes and pathways among different myopathies. The newly identified featured genes of general myopathy, inclusion body myositis, and titinopathy were highly expressed in our local muscles, as validated by quantitative polymerase chain reaction.
Functionalizing tandem mass tags for streamlining click-based quantitative chemoproteomics
Authors: Burton Nikolas R. , Backus Keriann M.
Published: April 2024

Mapping the ligandability or potential druggability of all proteins in the human proteome is a central goal of mass spectrometry-based covalent chemoproteomics. Achieving this ambitious objective requires high throughput and high coverage sample preparation and liquid chromatography-tandem mass spectrometry analysis for hundreds to thousands of reactive compounds and chemical probes. Conducting chemoproteomic screens at this scale benefits from technical innovations that achieve increased sample throughput. Here we realize this vision by establishing the silane-based cleavable linkers for isotopically-labeled proteomics-tandem mass tag (sCIP-TMT) proteomic platform, which is distinguished by early sample pooling that increases sample preparation throughput. sCIP-TMT pairs a custom click-compatible sCIP capture reagent that is readily functionalized in high yield with commercially available TMT reagents. Synthesis and benchmarking of a 10-plex set of sCIP-TMT reveal a substantial decrease in sample preparation time together with high coverage and high accuracy quantification. By screening a focused set of four cysteine-reactive electrophiles, we demonstrate the utility of sCIP-TMT for chemoproteomic target hunting, identifying 789 total liganded cysteines. Distinguished by its compatibility with established enrichment and quantification protocols, we expect sCIP-TMT will readily translate to a wide range of covalent chemoproteomic applications.
Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors
Authors: Pata Joosep , Wulff Eric , Mokhtar Farouk , Southwick David , Zhang Mengke , Girone Maria , Duarte Javier
Published: April 2024

Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models for event reconstruction in electron-positron collisions based on a full detector simulation. Particle-flow reconstruction can be formulated as a supervised learning task using tracks and calorimeter clusters. We compare a graph neural network and kernel-based transformer and demonstrate that we can avoid quadratic operations while achieving realistic reconstruction. We show that hyperparameter tuning significantly improves the performance of the models. The best graph neural network model shows improvement in the jet transverse momentum resolution by up to 50% compared to the rule-based algorithm. The resulting model is portable across Nvidia, AMD and Habana hardware. Accurate and fast machine-learning based reconstruction can significantly improve future measurements at colliders.
Ocean acidification offsets the effect of warming on sediment denitrification and associated nitrous oxide production
Authors: Simone Michelle Nicole , Erler Dirk Vincent , Schulz Kai Georg , Oakes Joanne Margaret , Eyre Bradley David
Published: April 2024

Rates of denitrification and associated nitrous oxide (N2O) production are expected to increase with global warming, leading to positive climate feedback. However, previous studies have not considered the combined effect of ocean acidification (OA, pCO2 ~ 900 µatm) and warming on denitrification rates and N2O production. Here we used a series of whole core incubation studies to assess the combined impact of warming and OA on estuarine sediment denitrification rates and N2O production. Strong warming (+5 °C over mean in situ conditions) increased N2O production by ~4.2 µmol-N m−2 d−1 and denitrification by ~43 µmol-N m−2 d−1, fuelled by water column nitrate (Dw), but decreased rates of nitrification-coupled denitrification in the sediment (Dn) by ~82 µmol-N m−2 d−1. While Dn was not affected by OA, Dw decreased significantly by 51 µmol-N m−2 d−1 when OA was coupled with warmer temperatures. We estimate that OA may offset the increase in estuarine sediment denitrification and N2O production expected from warming alone by up to 64% and reduce a potential positive climate feedback loop by inhibiting denitrification pathways.
Statistically significant difference between earthquake size distributions of independent and triggered seismicity
Authors: Taroni Matteo , Console Rodolfo , Montuori Caterina , Murru Maura , Falcone Giuseppe , Chiaraluce Lauro , Pastoressa Anna Eliana
Published: April 2024

The Alto Tiberina Fault system, located in Central Italy, is an active structure about 60 km long composed of a principal low-angle normal fault and several minor synthetic and antithetic splays. The system is monitored by a dense seismic network, giving us the opportunity to construct high-definition seismic catalogs with a low completeness magnitude. We analyze the clustering properties of the 2010-2015 seismicity by using a 3D stochastic declustering algorithm that also includes the earthquakes’ depth. We demonstrate that the earthquake size distribution is strongly correlated with the clustering of seismic events and their depth; in particular, the principal fault and secondary faults show an opposite behavior both in terms of earthquake size distribution and clustering properties.
Are there distinct levels of language comprehension in autistic individuals – cluster analysis
Authors: Vyshedskiy Andrey , Venkatesh Rohan , Khokhlovich Edward
Published: April 2024

Autism is a neurodevelopmental condition characterized by deficits in social communication. We assessed 14-language comprehension abilities in 31,845 autistic individuals 4 to 21 years of age using parent-generated reports. Data-driven cluster analysis identified three distinct levels of language comprehension: (1) individuals in the command-language-phenotype were limited to comprehension of simple commands; (2) individuals in the modifier-language-phenotype showed additional comprehension of color, size, and number modifiers; 3) individuals in the most-advanced syntactic-language-phenotype added comprehension of spatial prepositions, verb tenses, flexible syntax, possessive pronouns, and complex narratives. The observation of three distinct language levels was consistent across different age groups. Autistic individuals’ communication level is currently commonly characterized as nonverbal, minimally-verbal, or verbal. This one-dimensional description is not ideal for characterizing an individual’s communication ability. In fact, a nonverbal individual with syntactic-language-phenotype may have normal ability to communicate albeit nonverbally, while a verbal person with command-language-phenotype does not have a normal ability to communicate by any means. Identification of the three distinct language-comprehension-phenotypes provides an opportunity to enhance characterization of individuals’ communication level. A composite description in terms of both, verbal abilities and a language-comprehension-level, will not only be more precise, but can improve language therapy by focusing it on both aspects of language development.
DNAJC9 prevents CENP-A mislocalization and chromosomal instability by maintaining the fidelity of histone supply chains
Authors: Balachandra Vinutha , Shrestha Roshan L , Hammond Colin M , Lin Shinjen , Hendriks Ivo A , Sethi Subhash Chandra , Chen Lu , Sevilla Samantha , Caplen Natasha J , Chari Raj , Karpova Tatiana S , McKinnon Katherine , Todd Matthew AM , Koparde Vishal , Cheng Ken Chih-Chien , Nielsen Michael L , Groth Anja , Basrai Munira A
Published: April 2024

The centromeric histone H3 variant CENP-A is overexpressed in many cancers. The mislocalization of CENP-A to noncentromeric regions contributes to chromosomal instability (CIN), a hallmark of cancer. However, pathways that promote or prevent CENP-A mislocalization remain poorly defined. Here, we performed a genome-wide RNAi screen for regulators of CENP-A localization which identified DNAJC9, a J-domain protein implicated in histone H3–H4 protein folding, as a factor restricting CENP-A mislocalization. Cells lacking DNAJC9 exhibit mislocalization of CENP-A throughout the genome, and CIN phenotypes. Global interactome analysis showed that DNAJC9 depletion promotes the interaction of CENP-A with the DNA-replication-associated histone chaperone MCM2. CENP-A mislocalization upon DNAJC9 depletion was dependent on MCM2, defining MCM2 as a driver of CENP-A deposition at ectopic sites when H3–H4 supply chains are disrupted. Cells depleted for histone H3.3, also exhibit CENP-A mislocalization. In summary, we have defined novel factors that prevent mislocalization of CENP-A, and demonstrated that the integrity of H3–H4 supply chains regulated by histone chaperones such as DNAJC9 restrict CENP-A mislocalization and CIN.
The phosphatase inhibitor LB-100 creates neoantigens in colon cancer cells through perturbation of mRNA splicing
Authors: Dias Matheus H , Liudkovska Vladyslava , Montenegro Navarro Jasmine , Giebel Lisanne , Champagne Julien , Papagianni Chrysa , Bleijerveld Onno B , Velds Arno , Agami Reuven , Bernards René , Cieśla Maciej
Published: April 2024

Perturbation of protein phosphorylation represents an attractive approach to cancer treatment. Besides kinase inhibitors, protein phosphatase inhibitors have been shown to have anti-cancer activity. A prime example is the small molecule LB-100, an inhibitor of protein phosphatases 2A/5 (PP2A/PP5), enzymes that affect cellular physiology. LB-100 has proven effective in pre-clinical models in combination with immunotherapy, but the molecular underpinnings of this synergy remain understood poorly. We report here a sensitivity of the mRNA splicing machinery to phosphorylation changes in response to LB-100 in colorectal adenocarcinoma. We observe enrichment for differentially phosphorylated sites within cancer-critical splicing nodes of U2 snRNP, SRSF and hnRNP proteins. Altered phosphorylation endows LB-100-treated colorectal adenocarcinoma cells with differential splicing patterns. In PP2A-inhibited cells, over 1000 events of exon skipping and intron retention affect regulators of genomic integrity. Finally, we show that LB-100-evoked alternative splicing leads to neoantigens that are presented by MHC class 1 at the cell surface. Our findings provide a potential explanation for the pre-clinical and clinical observations that LB-100 sensitizes cancer cells to immune checkpoint blockade.
Exploring the oxidation behavior of undiluted and diluted iron particles for energy storage: Mössbauer spectroscopic analysis and kinetic modeling
Authors: Spielmann Jonas , Braig Daniel , Streck Antonia , Gustmann Tobias , Kuhn Carola , Reinauer Felix , Kurnosov Alexandr , Leubner Oliver , Potapkin Vasily , Hasse Christian , Deutschmann Olaf , Etzold Bastian J. M. , Scholtissek Arne , Kramm Ulrike I.
Published: April 2024

Measuring the composition at different stages of oxidation enables extracting the kinetics and highlighting differences and similarities of iron particles to bulk material.
Two-dimensional half-metals MSi2N4 (M = Al, Ga, In, Tl) with intrinsic p-type ferromagnetism and ultrawide bandgaps
Authors: Ding Yi-min , Huo Yiqi , Fang Gaojing , Yan Luo , Wu Yu , Zhou Liujiang
Published: April 2024

We have designed a class of new two-dimensional p-type half-metals, MSi2N4 (M = Al, Ga, In and Tl), with large half-metallic gaps (0.75–1.47 eV) and ferromagnetic orderings with Curie temperatures of 35–140 K.
Zn-based batteries for sustainable energy storage: strategies and mechanisms
Authors: Tang Lei , Peng Haojia , Kang Jiarui , Chen Han , Zhang Mingyue , Liu Yan , Kim Dong Ha , Liu Yijiang , Lin Zhiqun
Published: April 2024

This review systematically summarizes various redox mechanisms in Zn-based batteries and design strategies to improve their electrochemical performance, which provides a reference for future development of high-performance Zn-based batteries.
SERS-based microdevices for use as in vitro diagnostic biosensors
Authors: Lee Sungwoon , Dang Hajun , Moon Joung-Il , Kim Kihyun , Joung Younju , Park Sohyun , Yu Qian , Chen Jiadong , Lu Mengdan , Chen Lingxin , Joo Sang-Woo , Choo Jaebum
Published: April 2024

This review explores various microdevices developed for applying SERS technology to in vitro diagnostics and delves into their clinical applications.
Theoretical and computational methods for tip- and surface-enhanced Raman scattering
Authors: Duan Sai , Tian Guangjun , Luo Yi
Published: April 2024

The effective field Hamiltonian can rigorously treat the quantum interactions between all components of localized optical fields and molecules, which predicts the breakdown of diverse selection rules and extends the application of optical techniques.
Innovative, combinatorial and high-throughput approaches to degrader synthesis
Authors: Stevens Rebecca , Thompson James D. F. , Fournier Julie C. L. , Burley Glenn A. , Battersby David J. , Miah Afjal H.
Published: April 2024

In this review we highlight how the synthesis of degraders has evolved in recent years, in particular the application of high-throughput chemistry and screening approaches such as D2B and DEL technologies to expedite discovery timelines.
Optimization of a single-step enzymatic beamhouse: toward eco-friendly leather manufacturing
Authors: Zhang Mingrui , Tang Chao , Liu Hui , Qin Shufa , Liu Jie , Albu Kaya Mǎdǎlina Georgiana , Tang Keyong
Published: April 2024

The eco-friendly application of an α-amylase/neutral protease system (ANS) in a single-step process for unhairing, fiber opening, and bating, provides an effective alternative to the conventional complex chemical-based lime-sulfide system (LSS).
Detection and identification of single ribonucleotide monophosphates using a dual in-plane nanopore sensor made in a thermoplastic via replication
Authors: Rathnayaka Chathurika , Chandrosoma Indu A. , Choi Junseo , Childers Katie , Chibuike Maximillian , Akabirov Khurshed , Shiri Farhad , Hall Adam R. , Lee Maxwell , McKinney Collin , Verber Matthew , Park Sunggook , Soper Steven A.
Published: April 2024

We report the generation of ∼8 nm dual in-plane pores fabricated in a thermoplastic via nanoimprint lithography (NIL). This device was used to detect and identify single rNMP molecules via resistive pulse sensing.
Highly sensitive and selective electrochemical detection of caffeine, theophylline and guaiacol in green tea, green coffee, coffee, and tea extracts using a SnS2 nanoflake-modified electrode
Authors: Kushwaha Amisha , Singh Gajendar , Gaur Umesh Kumar , Sharma Manu
Published: April 2024

Tin(iv) sulfide (SnS2) nanoflakes modified glassy carbon electrode was utilized for the electrochemical detection of caffine, theophylline and guaiacol. This study was carried out using commercially available samples of green tea, green coffee, tea and coffee extracts.
Biomaterial strategies for regulating the neuroinflammatory response
Authors: Galindo Alycia N. , Frey Rubio David A. , Hettiaratchi Marian H.
Published: April 2024

This review highlights recent breakthroughs in biomaterial-based strategies for modulating neuroinflammation in central nervous system injury and disease, including nanoparticles, hydrogels, neural probe coatings, and implantable scaffolds.
Synthesis and functional evaluation of proteinogenic amino acid-derived synthetic cannabinoid receptor agonists related to MPP-5F-PICA, MMB-5F-PICA, and MDMB-5F-PICA
Authors: Sparkes Eric , Markham Jack W. , Boyd Rochelle , Udoh Michael , Gordon Rebecca , Zaman Humayra , Walker Katelyn A. , Dane Chianna , Kevin Richard C. , Santiago Marina J. , Hibbs David E. , Banister Samuel D. , Ametovski Adam , Cairns Elizabeth A.
Published: April 2024

α-Amino acid derived synthetic cannabinoid receptor agonists.
Development of robust proton exchange membranes using a sPVA–silica composite with different crosslinkers and evaluation of their fuel cell performance
Authors: Hegde Sachin , Munavalli Balappa , Achari Divya , Gowda Ranjith , Kariduraganavar Mahadevappa
Published: April 2024

Nano-silica incorporated sPVA membranes with different crosslinkers were developed. Among these, TEOS crosslinked membrane has shown an excellent performance. Thus, TEOS could be a potential crosslinker for nano-silica incorporated sPVA membranes for fuel cell applications.
Coupling the high-temperature Fischer–Tropsch synthesis and the skeletal isomerization reaction at optimal operation conditions in the Power-to-Fuels process route for the production of sustainable aviation gasoline
Authors: Dhamo Dorela , Kühn Jannis , Lüttin Simon , Rubin Michael , Dittmeyer Roland
Published: April 2024

Power-to-Fuels route for the production of aviation gasoline: stable operation of the coupled high-temperature Fischer–Tropsch synthesis and the skeletal isomerization reaction, at optimal operating conditions respectively.