bluuebunny/crossref_metadata_2025 huggingface dataset:
Lattice distortion SnS2 piezoelectric self-Fenton system for efficient degradation and detoxification of pollutants
Authors: Jiang Runren , Lu Guanghua , Wang Min , Chen Yufang , Liu Jianchao , Yan Zhenhua , Xie Haijiao
Published: November 2023

Both piezoelectricity and self-Fenton catalysis are effective ways to degrade water pollution, but little research has combined them to construct a more efficient water pollution treatment method. Here, a Fe-doped SnS2 (Sn1-xFexS2) piezoelectric self-Fenton system was constructed, which shows superior water treatment performance. The best piezoelectric properties of the Sn0.97Fe0.03S2 system were verified by degrading rhodamine B (RhB). The toxicity analysis of degradation intermediates and solutions confirmed that the toxicity of RhB decreased after degradation. In addition, Kelvin probe force microscopy and photoelectrochemical analysis confirmed the better piezoelectric properties of Sn0.97Fe0.03S2. It has demonstrated the enhancement of systematic piezoelectricity by Fe lattice defects and the formation of self-Fenton by Fe as an active center in the degradation of RhB. In this work, an efficient piezoelectric and self-Fenton technology is constructed to remove organic pollutants from water, which is significant for developing water treatment technology.
High-dimensional multi-pass flow cytometry via spectrally encoded cellular barcoding
Authors: Kwok Sheldon J. J. , Forward Sarah , Fahlberg Marissa D. , Assita Emane Rose , Cosgriff Sean , Lee Seung Hyung , Abbott Geoffrey R. , Zhu Han , Minasian Nicolas H. , Vote A. Sean , Martino Nicola , Yun Seok-Hyun
Published: November 2023

Advances in immunology, immuno-oncology, drug discovery and vaccine development demand improvements in the capabilities of flow cytometry to allow it to measure more protein markers per cell at multiple timepoints. However, the size of panels of fluorophore markers is limited by overlaps in fluorescence-emission spectra, and flow cytometers typically perform cell measurements at one timepoint. Here we describe multi-pass high-dimensional flow cytometry, a method leveraging cellular barcoding via microparticles emitting near-infrared laser light to track and repeatedly measure each cell using more markers and fewer colours. By using live human peripheral blood mononuclear cells, we show that the method enables the time-resolved characterization of the same cells before and after stimulation, their analysis via a 10-marker panel with minimal compensation for spectral spillover and their deep immunophenotyping via a 32-marker panel, where the same cells are analysed in 3 back-to-back cycles with 10–13 markers per cycle, reducing overall spillover and simplifying marker-panel design. Cellular barcoding in flow cytometry extends the utility of the technique for high-dimensional multi-pass single-cell analyses.
Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain
Authors: Bhattacharya Arjun , Vo Daniel D. , Jops Connor , Kim Minsoo , Wen Cindy , Hervoso Jonatan L. , Pasaniuc Bogdan , Gandal Michael J.
Published: November 2023

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power for discovery of trait associations within genome-wide association study loci across 15 neuropsychiatric traits. We illustrate multiple isoTWAS associations undetectable at the gene-level, prioritizing isoforms of AKT3, CUL3 and HSPD1 in schizophrenia and PCLO with multiple disorders. Results highlight the importance of incorporating isoform-level resolution within integrative approaches to increase discovery of trait associations, especially for brain-relevant traits.
AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination
Authors: Terwilliger Thomas C. , Liebschner Dorothee , Croll Tristan I. , Williams Christopher J. , McCoy Airlie J. , Poon Billy K. , Afonine Pavel V. , Oeffner Robert D. , Richardson Jane S. , Read Randy J. , Adams Paul D.
Published: November 2023

Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.
Explained predictions of strong eastern Pacific El Niño events using deep learning
Authors: Rivera Tello Gerardo A. , Takahashi Ken , Karamperidou Christina
Published: November 2023

Global and regional impacts of El Niño-Southern Oscillation (ENSO) are sensitive to the details of the pattern of anomalous ocean warming and cooling, such as the contrasts between the eastern and central Pacific. However, skillful prediction of such ENSO diversity remains a challenge even a few months in advance. Here, we present an experimental forecast with a deep learning model (IGP-UHM AI model v1.0) for the E (eastern Pacific) and C (central Pacific) ENSO diversity indices, specialized on the onset of strong eastern Pacific El Niño events by including a classification output. We find that higher ENSO nonlinearity is associated with better skill, with potential implications for ENSO predictability in a warming climate. When initialized in May 2023, our model predicts the persistence of El Niño conditions in the eastern Pacific into 2024, but with decreasing strength, similar to 2015–2016 but much weaker than 1997–1998. In contrast to the more typical El Niño development in 1997 and 2015, in addition to the ongoing eastern Pacific warming, an eXplainable Artificial Intelligence analysis for 2023 identifies weak warm surface, increased sea level and westerly wind anomalies in the western Pacific as precursors, countered by warm surface and southerly wind anomalies in the northern Atlantic.
Evidence of cochlear neural degeneration in normal-hearing subjects with tinnitus
Authors: Vasilkov Viacheslav , Caswell-Midwinter Benjamin , Zhao Yan , de Gruttola Victor , Jung David H. , Liberman M. Charles , Maison Stéphane F.
Published: November 2023

Tinnitus, reduced sound-level tolerance, and difficulties hearing in noisy environments are the most common complaints associated with sensorineural hearing loss in adult populations. This study aims to clarify if cochlear neural degeneration estimated in a large pool of participants with normal audiograms is associated with self-report of tinnitus using a test battery probing the different stages of the auditory processing from hair cell responses to the auditory reflexes of the brainstem. Self-report of chronic tinnitus was significantly associated with (1) reduced cochlear nerve responses, (2) weaker middle-ear muscle reflexes, (3) stronger medial olivocochlear efferent reflexes and (4) hyperactivity in the central auditory pathways. These results support the model of tinnitus generation whereby decreased neural activity from a damaged cochlea can elicit hyperactivity from decreased inhibition in the central nervous system.
Tailoring elastic and inelastic collisions of relativistic antiferromagnetic domain walls
Authors: Otxoa Rubén M. , Tatara Gen , Roy Pierre E. , Chubykalo-Fesenko Oksana
Published: November 2023

Soliton-based computing relies on their unique properties for transporting energy and emerging intact from head-on collisions. Magnetic domain walls are often referred to as solitons disregarding the strict mathematical definition requiring the above scattering property. Here we demonstrate the conditions of elastic and inelastic scattering for spin–orbit torque-induced dynamics of relativistic domain walls on the technologically relevant Mn$$_2$$

2

Au antiferromagnetic material. We show that even domain walls with opposite winding numbers can experience elastic scattering and we present the corresponding phase diagram as a function of the spin–orbit field strength and duration. The elastic collision requires minimum domain walls speed, which we explain assuming an attractive potential created by domain wall pair. On the contrary, when the domain walls move at lower speeds, their collision is inelastic and results in a dispersing breather. Our findings will be important for the development of soliton-based computing using antiferromagnetic spintronics and we discuss their prospects for building NOT and XOR gates.
Undesirable dispersal via a river pathway of a single Argentine ant supercolony newly invading an inland urban area of Japan
Authors: Hayasaka Daisuke , Kato Kenshin , Hiraiwa Masayoshi K. , Kasai Hiro , Osaki Kazutaka , Aoki Retsushi , Sawahata Takuo
Published: November 2023

Invasive ants pose a risk to human well-being and social/ecosystem stability. Linepithema humile Mayr is among the most damaging invasive ants worldwide. Most L. humile populations invade ports/wharfs isolated from surrounding landscapes, but unfortunately, a new population was discovered in an inland urban area (Nara Prefecture) of Japan in 2021. In this study, first, the supercolony type of the Nara L. humile population was identified via a hostility test, and then its distribution pattern was characterized. In aggression tests between L. humile from Nara and four supercolonies (haplotypes LH1, LH2, LH3, LH4), this ant showed extremely strong hostility against all supercolonies exept LH2, which was detected only in Japan in its introduced range. In Nara, L. humile was abundant in and around the urban river. Simulations revealed that using this environment for movement/dispersal increased the annual dispersal ability by 14 times compared with that achieved via ground (125 m), as mentioned in the literature. Therefore, river channels can serve as major pathways of long-distance dispersal for L. humile invading inland urban areas. Since applying chemical strategies around rivers is problematic, preventing L. humile from moving to rivers from initial invasion sites is crucial.
Magneto-hydrodynamic peristaltic flow of a Jeffery fluid in the presence of heat transfer through a porous medium in an asymmetric channel
Authors: Abd-Alla A. M. , Abo-Dahab S. M. , Salah Doaa. M. , Bayones F. S. , Abdelhafez M. A.
Published: November 2023

In the present paper, the effects of magnetic field and heat transfer on the peristaltic flow of a Jeffery fluid through a porous medium in an asymmetric channel have been studied. The governing non-linear partial differential equations representing the flow model are transmuted into linear ones by employing the appropriate non-dimensional parameters under the assumption of long wavelength and low Reynolds number. Exact solutions are presented for the stream function, pressure gradient, and temperature. The frictional force and pressure rise are both computed using numerical integration. Using MATLAB R2023a software, a parametric analysis is performed, and the resulting data is represented graphically. For all physical quantities considered, numerical calculations were made and represented graphically. Trapping phenomena are discussed graphically. The obtained results can be applied to enhance pumping systems in engineering and gastrointestinal functions. This analysis permits body fluids such as blood and lymph to easily move inside the arteries and veins, allowing oxygen supply, waste elimination, and other necessary elements.
Salt wedges and trapped brines of low-latitude endoreic saline lakes as potential modulators of GHG emission
Authors: Gibert-Brunet Elisabeth , Tudryn Alina , Kong Ting , Tucholka Piotr , Motavalli-Anbaran Seyed-Hani , Marlin Christelle , Noret Aurélie , Lankarani Mohammad , Ahmady-Birgani Hesam , Karimi Gilda
Published: November 2023

Large salt lakes are long-term witnesses to climatic conditions and land use in their basins. The majority are experiencing a drastic drop in water levels due to climate change and human impact. Endoreic Lake Urmia (NW Iran), the sixth largest salt lake worldwide, is a striking example of this decline. Quantification of the relative contributions of natural variability and human impact on the lake's water supply is therefore essential. Here we present isotopic and radiocarbon analyses of surface and groundwater from the Shahr Chay River catchment, entering Lake Urmia on its western shore, and radiocarbon dating of a sedimentary core. Lake Urmia behaves like a large saltwater wedge almost entirely fed by the river and shallow groundwater. This leads to trapping of residual brines and formation of CH4 and secondary CO2 greenhouse gases, impacting sediment geochemical records and corresponding time scales for paleoenvironmental reconstructions. We conclude that (1) salt lakes functioning like a saline wedge, allowing organic matter oxidation, could contribute to increasing methane sources or reducing carbon sinks globally, and (2) endoreic basins worldwide need to be monitored before aridification-related salinization leads to the establishment of a saline wedge precluding any possibility of return to an equilibrium state.
Insufficient sleep and weekend recovery sleep: classification by a metabolomics-based machine learning ensemble
Authors: Gombert Marie , Reisdorph Nichole , Morton Sarah J. , Wright Kenneth P. , Depner Christopher M.
Published: November 2023

Although weekend recovery sleep is common, the physiological responses to weekend recovery sleep are not fully elucidated. Identifying molecular biomarkers that represent adequate versus insufficient sleep could help advance our understanding of weekend recovery sleep. Here, we identified potential molecular biomarkers of insufficient sleep and defined the impact of weekend recovery sleep on these biomarkers using metabolomics in a randomized controlled trial. Healthy adults (n = 34) were randomized into three groups: control (CON: 9-h sleep opportunities); sleep restriction (SR: 5-h sleep opportunities); or weekend recovery (WR: simulated workweek of 5-h sleep opportunities followed by ad libitum weekend recovery sleep and then 2 days with 5-h sleep opportunities). Blood for metabolomics was collected on the simulated Monday immediately following the weekend. Nine machine learning models, including a machine learning ensemble, were built to classify samples from SR versus CON. Notably, SR showed decreased glycerophospholipids and sphingolipids versus CON. The machine learning ensemble showed the highest G-mean performance and classified 50% of the WR samples as insufficient sleep. Our findings show insufficient sleep and recovery sleep influence the plasma metabolome and suggest more than one weekend of recovery sleep may be necessary for the identified biomarkers to return to healthy adequate sleep levels.
A prospective cohort study on the association between dietary fatty acids intake and risk of hypertension incident
Authors: Shakiba Ebrahim , Najafi Farid , Pasdar Yahya , Moradinazar Mehdi , Navabi Jafar , Shakiba Mohammad Hossein , Bagheri Amir
Published: November 2023

There are inconclusive results available on the association between dietary fatty acid intake and the risk of hypertension (HTN) incident. In this study, we investigate the relationship between baseline dietary fatty acids intake including polyunsaturated fatty acid (PUFA), trans fatty acids (TFA), monounsaturated fatty acid (MUFA), and saturated fatty acid (SFA), and the risk of first incidence hypertension. The current prospective cohort study was carried out from the Ravansar Non-Communicable Diseases (RaNCD) cohort. A food frequency questionnaire (FFQ) with 118 items was used for the assessment of dietary data. Cox proportional hazards analyses were done to estimate hazard ratios (HR) and 95% confidence intervals (CIs) of the highest versus lowest quartile intake of SFA, PUFA, MUFA, and SFA and risk of HTN. Out of 7359 eligible participants, 597 new cases of HTN were identified over an average of 6.4 ± 1.33 years of follow-up. No significant relationship was observed between the fourth compared to the first categories of dietary SFA (HR: 0.82, 95% CI 0.55, 1.21; P trend: 0.476), MUFA (HR: 0.71, 95% CI 0.48, 1.06; P trend: 0.252), PUFA (HR: 0.86, 95% CI 0.62, 1.19; P trend: 0.315) and TFA (HR: 0.99, 95% CI 0.76, 1.27; P trend: 0.675), and risk of HTN. However, a significant inverse association between each 1 g per day increase in dietary MUFA intake during 6.4 years of follow up and HTN incident (HR: 0.97; 95% CI 0.94, 0.99; P 0.044) was observed. In brief, our study revealed that higher dietary MUFA intake was protectively associated with HTN incident. Dietary MUFA-rich foods should be encouraged to improve blood pressure.
Evaluation of repositioning care provided by non-professionals using a caregiver-assistive device: an experimental study
Authors: Omura Yuka , Watanabe Atsuko , Shibata Kasumi , Inoue Tomoko
Published: November 2023

As the population ages in Japan and worldwide, the number of informal caregivers, such as family members, providing nursing care to older individuals is increasing. Among caregiving tasks, repositioning care, which causes lower back pain, is frequent and burdensome for caregivers. Therefore, we developed a position-changing device that can adjust and support the care recipient’s body in the lateral position. This was a feasibility study of the device-assisted care provided by non-professionals using the device we developed. Of the 40 healthy volunteers enrolled, 17 simulated caregivers and 17 simulated care recipients finally participated in the study. One caregiver and one care recipient were paired to engage in two types of care: device-assisted care and manual care. Furthermore, the care provided by the caregiver and received by the care recipient were evaluated. Non-professionals were able to use the device successfully and safely after a short period of practice, and both caregivers and care recipients rated the device-assisted care positively. The study results suggest that informal caregivers can also provide safe and comfortable care that is less burdensome than manual care by using a caregiver-assistive device.
Development of postoperative delirium prediction models in patients undergoing cardiovascular surgery using machine learning algorithms
Authors: Nagata Chie , Hata Masahiro , Miyazaki Yuki , Masuda Hirotada , Wada Tamiki , Kimura Tasuku , Fujii Makoto , Sakurai Yasushi , Matsubara Yasuko , Yoshida Kiyoshi , Miyagawa Shigeru , Ikeda Manabu , Ueno Takayoshi
Published: November 2023

Associations between delirium and postoperative adverse events in cardiovascular surgery have been reported and the preoperative identification of high-risk patients of delirium is needed to implement focused interventions. We aimed to develop and validate machine learning models to predict post-cardiovascular surgery delirium. Patients aged ≥ 40 years who underwent cardiovascular surgery at a single hospital were prospectively enrolled. Preoperative and intraoperative factors were assessed. Each patient was evaluated for postoperative delirium 7 days after surgery. We developed machine learning models using the Bernoulli naive Bayes, Support vector machine, Random forest, Extra-trees, and XGBoost algorithms. Stratified fivefold cross-validation was performed for each developed model. Of the 87 patients, 24 (27.6%) developed postoperative delirium. Age, use of psychotropic drugs, cognitive function (Mini-Cog < 4), index of activities of daily living (Barthel Index < 100), history of stroke or cerebral hemorrhage, and eGFR (estimated glomerular filtration rate) < 60 were selected to develop delirium prediction models. The Extra-trees model had the best area under the receiver operating characteristic curve (0.76 [standard deviation 0.11]; sensitivity: 0.63; specificity: 0.78). XGBoost showed the highest sensitivity (AUROC, 0.75 [0.07]; sensitivity: 0.67; specificity: 0.79). Machine learning algorithms could predict post-cardiovascular delirium using preoperative data.

Trial registration: UMIN-CTR (ID; UMIN000049390).
LMFD: lightweight multi-feature descriptors for image stitching
Authors: Fan Yingbo , Mao Shanjun , Li Mei , Kang Jitong , Li Ben
Published: November 2023

Image stitching is a fundamental pillar of computer vision, and its effectiveness hinges significantly on the quality of the feature descriptors. However, the existing feature descriptors face several challenges, including inadequate robustness to noise or rotational transformations and limited adaptability during hardware deployment. To address these limitations, this paper proposes a set of feature descriptors for image stitching named Lightweight Multi-Feature Descriptors (LMFD). Based on the extensive extraction of gradients, means, and global information surrounding the feature points, feature descriptors are generated through various combinations to enhance the image stitching process. This endows the algorithm with formidable rotational invariance and noise resistance, thereby improving its accuracy and reliability. Furthermore, the feature descriptors take the form of binary matrices consisting of 0s and 1s, not only facilitating more efficient hardware deployment but also enhancing computational efficiency. The utilization of binary matrices significantly reduces the computational complexity of the algorithm while preserving its efficacy. To validate the effectiveness of LMFD, rigorous experimentation was conducted on the Hpatches and 2D-HeLa datasets. The results demonstrate that LMFD outperforms state-of-the-art image matching algorithms in terms of accuracy. This empirical evidence solidifies the superiority of LMFD and substantiates its potential for practical applications in various domains.
AUCReshaping: improved sensitivity at high-specificity
Authors: Bhat Sheethal , Mansoor Awais , Georgescu Bogdan , Panambur Adarsh B. , Ghesu Florin C. , Islam Saahil , Packhäuser Kai , Rodríguez-Salas Dalia , Grbic Sasa , Maier Andreas
Published: November 2023

The evaluation of deep-learning (DL) systems typically relies on the Area under the Receiver-Operating-Curve (AU-ROC) as a performance metric. However, AU-ROC, in its holistic form, does not sufficiently consider performance within specific ranges of sensitivity and specificity, which are critical for the intended operational context of the system. Consequently, two systems with identical AU-ROC values can exhibit significantly divergent real-world performance. This issue is particularly pronounced in the context of anomaly detection tasks, a commonly employed application of DL systems across various research domains, including medical imaging, industrial automation, manufacturing, cyber security, fraud detection, and drug research, among others. The challenge arises from the heavy class imbalance in training datasets, with the abnormality class often incurring a considerably higher misclassification cost compared to the normal class. Traditional DL systems address this by adjusting the weighting of the cost function or optimizing for specific points along the ROC curve. While these approaches yield reasonable results in many cases, they do not actively seek to maximize performance for the desired operating point. In this study, we introduce a novel technique known as AUCReshaping, designed to reshape the ROC curve exclusively within the specified sensitivity and specificity range, by optimizing sensitivity at a predetermined specificity level. This reshaping is achieved through an adaptive and iterative boosting mechanism that allows the network to focus on pertinent samples during the learning process. We primarily investigated the impact of AUCReshaping in the context of abnormality detection tasks, specifically in Chest X-Ray (CXR) analysis, followed by breast mammogram and credit card fraud detection tasks. The results reveal a substantial improvement, ranging from 2 to 40%, in sensitivity at high-specificity levels for binary classification tasks.
Application of human platelet lysate in chondrocyte expansion promotes chondrogenic phenotype and slows senescence progression via BMP–TAK1–p38 pathway
Authors: Chitchongyingcharoen Narong , Tawonsawatruk Tulyapruek , Phetfong Jitrada , Aroontanee Wrattya , Supokawej Aungkura
Published: November 2023

Osteoarthritis (OA) is one of the most common musculoskeletal degenerative. OA treatments are aiming to slow down disease progression; however, lack of cartilage regeneration efficacy. Autologous chondrocyte implantation (ACI) is a promising cartilage-regeneration strategy that uses human articular chondrocytes (HACs) as cellular materials. However, the unreadiness of HACs from prolonged expansion, cellular senescence, and chondrogenic dedifferentiation occurred during conventional expansion, thus, minimizing the clinical efficacy of ACI. We aimed to examine the effects of a human platelet lysate (HPL) as an alternative human-derived HAC medium supplement to overcome the limitations of conventional expansion, and to explain the mechanism underlying the effects of HPL. During passages 2–4 (P2-P4), HPL significantly increased HAC proliferation capacities and upregulated chondrogenic markers. Simultaneously, HPL significantly reduced HAC senescence compared with conventional condition. HACs treated with LDN193189 exhibited a reduction in proliferation capacity and chondrogenic marker expression, whereas the HAC senescence increased slightly. These findings indicated involvement of BMP-2 signaling transduction in the growth-assistive, anti-senescent, and chondrogenic-inductive properties of HPL, which demonstrated its beneficial effects for application as HAC medium supplement to overcome current expansion limitations. Finally, our findings support the roles of platelets in platelet-rich plasma as a promising treatment for patients with OA.
Investigation of an efficient multi-modal convolutional neural network for multiple sclerosis lesion detection
Authors: Raab Florian , Malloni Wilhelm , Wein Simon , Greenlee Mark W. , Lang Elmar W.
Published: November 2023

In this study, an automated 2D machine learning approach for fast and precise segmentation of MS lesions from multi-modal magnetic resonance images (mmMRI) is presented. The method is based on an U-Net like convolutional neural network (CNN) for automated 2D slice-based-segmentation of brain MRI volumes. The individual modalities are encoded in separate downsampling branches without weight sharing, to leverage the specific features. Skip connections input feature maps to multi-scale feature fusion (MSFF) blocks at every decoder stage of the network. Those are followed by multi-scale feature upsampling (MSFU) blocks which use the information about lesion shape and location. The CNN is evaluated on two publicly available datasets: The ISBI 2015 longitudinal MS lesion segmentation challenge dataset containing 19 subjects and the MICCAI 2016 MSSEG challenge dataset containing 15 subjects from various scanners. The proposed multi-input 2D architecture is among the top performing approaches in the ISBI challenge, to which open-access papers are available, is able to outperform state-of-the-art 3D approaches without additional post-processing, can be adapted to other scanners quickly, is robust against scanner variability and can be deployed for inference even on a standard laptop without a dedicated GPU.
Association between invasively measured central aortic pulse pressure and diameter of ascending aorta
Authors: Kim Hack-Lyoung , Joh Hyun Sung , Lim Woo-Hyun , Seo Jae-Bin , Kim Sang-Hyun , Zo Joo-Hee , Kim Myung-A
Published: November 2023

Data on the relationship between arterial pulsatile hemodynamics and aortic root geometry, using invasive hemodynamic measurement, has been scarce. Thus, this study aimed to assess the relationship between invasively measured aortic pulse pressure (aPP) and the diameter of ascending aorta (AoD). We analyzed 665 subjects (64.3 ± 11.0 years; 34.6% female) who underwent elective invasive coronary angiography (ICA) for the evaluation of coronary artery disease. Transthoracic echocardiography was performed on the same day, and AoD was measured at the level of 1 cm above the sinotubular junction at the end-diastole. Body surface area (BSA)-adjusted AoD (AoD/BSA) was used for the analysis. A pig-tail catheter was used to measure aortic pressures at a level approximately 3 cm above the aortic valve just before ICA. aPP was calculated as the difference between systolic and diastolic pressures of the aorta. In multiple linear regression analyses, aPP (β = 0.259; P < 0.001) was found to be significantly correlated with AoD/BSA even after controlling for potential confounders. This correlation power was stronger than aortic systolic pressure (β = 0.189; P < 0.001) and brachial pulse pressure (β = 0.091; P = 0.018) at the same multivariable analyses. In conclusion, our study demonstrated a significant association between invasively measured aPP and AoD/BSA, providing stronger evidence for the link between central aortic pulsatile hemodynamics and aortic root geometry.
Single-molecule visualization of human A2A adenosine receptor activation by a G protein and constitutively activating mutations
Authors: Wei Shushu , Pour Niloofar Gopal , Tiruvadi-Krishnan Sriram , Ray Arka Prabha , Thakur Naveen , Eddy Matthew T. , Lamichhane Rajan
Published: November 2023

Mutations that constitutively activate G protein-coupled receptors (GPCRs), known as constitutively activating mutations (CAMs), modify cell signaling and interfere with drugs, resulting in diseases with limited treatment options. We utilize fluorescence imaging at the single-molecule level to visualize the dynamic process of CAM-mediated activation of the human A2A adenosine receptor (A2AAR) in real time. We observe an active-state population for all CAMs without agonist stimulation. Importantly, activating mutations significantly increase the population of an intermediate state crucial for receptor activation, notably distinct from the addition of a partner G protein. Activation kinetics show that while CAMs increase the frequency of transitions to the intermediate state, mutations altering sodium sensitivity increase transitions away from it. These findings indicate changes in GPCR function caused by mutations may be predicted based on whether they favor or disfavor formation of an intermediate state, providing a framework for designing receptors with altered functions or therapies that target intermediate states.
Extreme heat and drought typical of an end-of-century climate could occur over Europe soon and repeatedly
Authors: Suarez-Gutierrez Laura , Müller Wolfgang A. , Marotzke Jochem
Published: November 2023

Extreme heat and drought typical of an end-of-century climate could soon occur over Europe, and repeatedly. Despite the European climate being potentially prone to multi-year successive extremes due to the influence of the North Atlantic variability, it remains unclear how the likelihood of successive extremes changes under warming, how early they could reach end-of-century levels, and how this is affected by internal climate variability. Using the Max Planck Institute Grand Ensemble, we find that even under moderate warming, end-of-century heat and drought levels virtually impossible 20 years ago reach 1-in-10 likelihoods as early as the 2030s. By 2050–2074, two successive years of single or compound end-of-century extremes, unprecedented to date, exceed 1-in-10 likelihoods; while Europe-wide 5-year megadroughts become plausible. Whole decades of end-of-century heat stress could start by 2040, by 2020 for drought, and with a warm North Atlantic, end-of-century decades starting as early as 2030 become twice as likely.
Nuclear localization signal-tagged systems: relevant nuclear import principles in the context of current therapeutic design
Authors: Goswami Ritabrita , Gupta Aarohi , Bednova Olga , Coulombe Gaël , Patel Dipika , Rotello Vincent M. , Leyton Jeffrey V.
Published: November 2023

Nuclear targeting of therapeutics provides a strategy for enhancing efficacy of molecules active in the nucleus and minimizing off-target effects.
Retention time prediction and MRM validation reinforce the biomarker identification of LC-MS based phospholipidomics
Authors: Zhang Jiangang , Zhou Yu , Lei Juan , Liu Xudong , Zhang Nan , Wu Lei , Li Yongsheng
Published: November 2023

Dysfunctional lipid metabolism plays a crucial role in the development and progression of various diseases.
A validated eco-friendly HPLC-FLD for analysis of the first approved antiviral remdesivir with other potential add-on therapies for COVID-19 in human plasma and pharmaceuticals
Authors: Taha Asmaa M. , Hassan Wafaa S. , Elmasry Manal S. , Sayed Rania A.
Published: November 2023

An HPLC-FLD method was proposed to determine remdesivir, hydroxychloroquine, and levofloxacin in their pure form and in human plasma, with high sensitivity and a wide linear range. Validation was done as per ICH and FDA guidelines, and the method greenness was evaluated.
Prediction of novel ground-state structures and analysis of phonon transport in two-dimensional GexSy compounds
Authors: Ali Asad , Shin Young-Han
Published: November 2023

Exploring novel ground-state structures in variable-composition of 2D GexSyunveils GeS and GeS2 with low and anisotropic lattice thermal conductivity.
Tunable Li-ion diffusion properties in MoSSe bilayer anodes by strain gradient
Authors: Zhong Li , Li Xiaobao , Pu Yuxue , Wang Meiqin , Zhan Chunxiao , Xiao Xinle
Published: November 2023

The diffusion energy barrier of Li-ion in layered MoSSe anode can be effectively tuned by strain gradient.
Electron-level insight into efficient synergistic oxygen evolution catalysis at multimetallic sites in PtNiFeCoCu high-entropy alloys
Authors: Ming Sen , Meng Kun , Hou Chengyi , Qin Lei , Wang Shitao , Rong Ju , Yu Xiaohua , Hou Hongying
Published: November 2023

High entropy alloys (HEA) applied to oxygen evolution reactions in electrocatalysis.
Tunable long-range spin transport in a van der Waals Fe3GeTe2/WSe2/Fe3GeTe2 spin valve
Authors: Singh Anil Kumar , Gao Weibo , Deb Pritam
Published: November 2023

A schematic representation of tunnelling magnetoresistance under an external electric field in the FGT/WSe2/FGT vdW spin valve. This predicts superior spin transport along with sign reversal in the observed TMR.
Promising TMDC-like optical and excitonic properties of the TiBr2 2H monolayer
Authors: Batista André L. de O. , Palheta João Marcos T. , Piotrowski Maurício J. , Rêgo Celso R. C. , Guedes-Sobrinho Diego , Dias Alexandre C.
Published: November 2023

Our simulation protocol allows exploring promising 2D materials for optoelectronic applications, like the TiBr2 2H monolayer, demonstrating TMDC-like optical and excitonic properties.
Chiral amino acid-templated tin fluorides tailoring nonlinear optical properties, birefringence, and photoluminescence
Authors: Jung Ahyung , Li Yang , Ok Kang Min
Published: November 2023

The new chiral amino acid-templated polar tin fluoride crystals, (R)-[C8H10NO3]Sn(ii)F3 and (S)-[C8H10NO3]Sn(ii)F3, reveal enhanced second-harmonic generation, photoluminescence, and birefringence.
The {Cu2I2} cluster bearing metal organic frameworks: crystal structures and fluorescence detecting performances towards cysteine and explosive molecules
Authors: Jiang Jiang , Li Zi-Wei , Zhang Zhi-Zhuan , Tan Bin , Wu Zhao-Feng , Huang Xiao-Ying
Published: November 2023

Two metal organic frameworks bearing {Cu2I2} cluster modules are presented, in which Sr-K-CuI-INA emits red luminescence and exhibits fluorescence sensing towards cysteine (Cys) and explosive molecules.
Coordination chemistry and FLP reactivity of 1,1- and 1,2-bis-boranes
Authors: Yeganeh-Salman Amir , Yeung Jason , Miao Linkun , Stephan Douglas W.
Published: November 2023

The coordination, Lewis acidity and frustrated Lewis pair (FLP) chemistry of PhCH2CH(B(C6F5)2)21 and Me3SiCH(B(C6F5)2)CH2B(C6F5)22 are studied.
MFI zeolite with confined adjustable synergistic Cu sites for the hydrogenation of levulinic acid
Authors: Liang Wanying , Xu Guangyue , Zhang Xiang , Chen Huiyong , Fu Yao
Published: November 2023

MFI confined Cu zeolites ZKD-5 were synthesized and employed in the selective hydrogenation of levulinic acid. The synergistic catalysis of Cu on different active sites was realized on this catalyst, and the synergistic mechanism was studied.
A hybrid fluorescent nanofiber membrane integrated with microfluidic chips towards lung-on-a-chip applications
Authors: Kanabekova Perizat , Dauletkanov Bereke , Bekezhankyzy Zhibek , Toktarkan Sultanali , Martin Alma , Pham Tri T. , Kostas Konstantinos , Kulsharova Gulsim
Published: November 2023

Here, we report a fluorescent electrospun nanofiber membrane for integration with microfluidic chips towards lung-on-a-chip applications complemented with computational fluid dynamics modelling. Created with https://BioRender.com.
Correction: Green pepper-derived hierarchical porous carbon for supercapacitors with high performance
Authors: Zeng Yicheng , Zhang Fuming , Wu Jinggao , Huang Jing
Published: November 2023

Correction for ‘Green pepper-derived hierarchical porous carbon for supercapacitors with high performance’ by Yicheng Zeng et al., Mater. Adv., 2023, 4, 2192–2200, https://doi.org/10.1039/D3MA00045A.
Scaffold hopping based designing of selective ALDH1A1 inhibitors to overcome cyclophosphamide resistance: synthesis and biological evaluation
Authors: Narendra Gera , Raju Baddipadige , Verma Himanshu , Kumar Manoj , Jain Subheet Kumar , Tung Gurleen Kaur , Thakur Shubham , Kaur Rasdeep , Kaur Satwinderjeet , Sapra Bharti , Silakari Om
Published: November 2023

Bioisosteric replacement-based novel benzimidazole derivatives were designed, Synthesized, and evaluated. Combining these ALDH1A1 inhibitors with mafosfamide mitigated cyclophosphamide resistance in A549 and Mia PaCa-2 cell lines.
Furaldehyde-based magnetic supported palladium nanoparticles as an efficient heterogeneous catalyst for Mizoroki–Heck cross-coupling reaction
Authors: Hegde Sumanth , Nizam Aatika , Vijayan Ajesh
Published: November 2023

Novel furaldehyde-based magnetic nanoparticles are used as an efficient catalyst for the Mizoroki–Heck reaction of arylhalide and olefins.
Atomically accurate site-specific ligand tailoring of highly acid- and alkali-resistant Ti(iv)-based metallamacrocycle for enhanced CO2 photoreduction
Authors: Tian Yi-Qi , Dai Lin-Fang , Mu Wen-Lei , Yu Wei-Dong , Yan Jun , Liu Chao
Published: November 2023

An eye-catching titanium-oxo cluster, embellished with a calix[8]arene-stabilized metallamacrocycle structure, remains resilient in the face of harsh acid and alkali solutions.
Rheological effects on purely-elastic flow asymmetries in the cross-slot geometry
Authors: Yokokoji Arisa , Varchanis Stylianos , Shen Amy Q. , Haward Simon J.
Published: November 2023

Experiments and numerical simulations reveal how purely-elastic flow asymmetries in the cross-slot geometry are affected by the shear thinning properties of viscoelastic fluids. A physical mechanism for the transition to steady asymmetry is proposed.
Construction of nano-silica particle clusters and their effects on the shear thickening properties of liquids
Authors: Zhang Xingmin , Zheng Jian , Pan Jianjun , Zhang Xiaoting , Fang Jin , Min Jie , Yu Chengbing
Published: November 2023

In this study, silica particle clusters (SPC) are prepared by the reaction of amino-modified silica with polyethylene glycol diglycidyl ether. The shear thickening fluid with SPC as the dispersed phase can produce faster and stronger shear thickening response.
Solvent-induced luminescence behavior of Ce/Eu@Gd-MOF for ratiometric detection of D2O in H2O
Authors: Fan Xiaoxuan , Guo Zhiqiang , Wen Xiaokun , Liu Wen , Guan Baijie , Yin Feifei , Hong Xia , Tan Tianya , Wang Kexin , Wang Jiwei
Published: November 2023

Energy transfer efficiency between Ce3+ and Eu3+ and photoluminescence of Ce/Eu@Gd-MOFs are enhanced in D2O compared with those in H2O.
Statistical inversion of normal‐mode interference spectral parameter in ocean waveguide
Authors: Gao Wei , Zhu Shuping , Li Xiaolei
Published: November 2023

A statistical inversion method of estimating normal mode interference spectral parameters (including waveguide invariance and interference frequency) from one‐dimensional broadband sound intensity spectrum (1D BSIS) is presented. First, the interference phase of 1D BSIS is compensated by a non‐linear factor for each pair of unknown parameters in a prior parameter space. Second, the singular value decomposition is performed for a data matrix, which is constructed by the phase‐compensated BSIS. Then, a misfit function is defined based on both the maximum singular value and the corresponding singular vector of the data matrix. Finally, the posterior probability distributions of unknown parameters are analysed based on statistical inversion theory. This method is suitable for the situation using a single receiver and without any environmental information. Numerical simulations illustrate the validity of the presented method.
Design and optimisation of oil injection pipe cooling structure for permanent magnet synchronous motors in hybrid electric vehicles
Authors: Xie Ying , Zhao Xiangmin , Cai Wei , Qi Guoliang , Wang Zebing , Zhang Yi , Yang Yanhui
Published: November 2023

In recent years, with the continuous improvement of motor power density, oil cooling technology has been widely used in permanent magnet synchronous motors (PMSMs) for electric vehicles (EVs) as an efficient cooling method. A PMSM with a rated capacity of 53kW for hybrid electric vehicles (HEVs) is designed, and the motor is cooled by the oil injection pipe. In order to improve the heat dissipation efficiency of the end winding, the number of injection pipes and the structure of the nozzle are optimised, and a novel nozzle structure is proposed. By using the moving particle solution (MPS) method to simulate the fluid flow, the optimal cooling structure of the motor is determined. In addition, different from the equivalent winding model in the traditional temperature field simulation, a hairpin winding model that can more realistically reflect the geometry of the end winding is established. On this basis, the temperature field of the motor is simulated. It is verified that the cooling structure designed can effectively improve the thermal performance of the end winding.
Optimal electric vehicle scheduling in unbalanced distribution system by spatial and temporal data mining and bi‐level particle swarm optimisation
Authors: Piamvilai Nattavit , Sirisumrannukul Somporn
Published: November 2023

This research proposes a new comprehensive methodology aimed at optimally managing electric vehicle (EV) charging in an unbalanced distribution system with consideration of grid capacity and voltage quality constraints as well as the stochastic driving and charging behaviour of EV users. A data mining algorithm is designed to generate suitable spatial and temporal EV and charger input data for EV scheduling that is decomposed into two subproblems. The lower‐level subproblem identifies the maximum load at each node and time and the upper‐level subproblem allocates charging slots for each EV being charged. Both subproblems are solved by developed particle swarm optimisation (PSO) algorithms. The effectiveness and robustness of the algorithms have been thoroughly validated by conducting rigorous tests on a modified IEEE 37‐bus distribution system with different EV penetration scenarios. The test results have confirmed the algorithms' performance in accommodating the increasing load associated with EV charging and successfully improving the system performance by maximising the system load factor, minimising load unbalance, and reducing the system power loss. All operational constraints on node voltages, and distribution transformer and feeder capacities of the existing power distribution infrastructure are fully respected while maintaining high user satisfaction represented by the average state of charge (SoC) of all EVs.
Emergence and cosmic evolution of the Kennicutt–Schmidt relation driven by interstellar turbulence
Authors: Kraljic Katarina , Renaud Florent , Dubois Yohan , Pichon Christophe , Agertz Oscar , Andersson Eric , Devriendt Julien , Freundlich Jonathan , Kaviraj Sugata , Kimm Taysun , Martin Garreth , Peirani Sébastien , Segovia Otero Álvaro , Volonteri Marta , Yi Sukyoung K.
Published: November 2023

The scaling relations between the gas content and star formation rate of galaxies provide useful insights into the processes governing their formation and evolution. We investigated the emergence and the physical drivers of the global Kennicutt–Schmidt (KS) relation at 0.25 ≤ z ≤ 4 in the cosmological hydrodynamic simulation NEWHORIZON, capturing the evolution of a few hundred galaxies with a resolution down to 34 pc. The details of this relation vary strongly with the stellar mass of galaxies and the redshift. A power-law relation ΣSFR ∝ Σgasa with a ≈ 1.4, like that found empirically, emerges at z ≈ 2 − 3 for the more massive half of the galaxy population. However, no such convergence is found in the lower-mass galaxies, for which the relation gets shallower with decreasing redshift. At galactic scales, the star formation activity correlates with the level of turbulence of the interstellar medium, quantified by the Mach number, rather than with the gas fraction (neutral or molecular), confirming the conclusions found in previous works. With decreasing redshift, the number of outliers with short depletion times diminishes, reducing the scatter of the KS relation, while the overall population of galaxies shifts toward low densities. Our results, from parsec-scale star formation models calibrated with local Universe physics, demonstrate that the cosmological evolution of the environmental (e.g., mergers) and internal conditions (e.g., gas fractions) conspire to shape the KS relation. This is an illustration of how the interplay of global and local processes leaves a detectable imprint on galactic-scale observables and scaling relations.