bluuebunny/crossref_metadata_2025 huggingface dataset:
Using a flashlight-contingent window paradigm to investigate visual search and object memory in virtual reality and on computer screens
Authors: Beitner Julia , Helbing Jason , David Erwan Joël , Võ Melissa Lê-Hoa
Published: April 2024

A popular technique to modulate visual input during search is to use gaze-contingent windows. However, these are often rather discomforting, providing the impression of visual impairment. To counteract this, we asked participants in this study to search through illuminated as well as dark three-dimensional scenes using a more naturalistic flashlight with which they could illuminate the rooms. In a surprise incidental memory task, we tested the identities and locations of objects encountered during search. Importantly, we tested this study design in both immersive virtual reality (VR; Experiment 1) and on a desktop-computer screen (Experiment 2). As hypothesized, searching with a flashlight increased search difficulty and memory usage during search. We found a memory benefit for identities of distractors in the flashlight condition in VR but not in the computer screen experiment. Surprisingly, location memory was comparable across search conditions despite the enormous difference in visual input. Subtle differences across experiments only appeared in VR after accounting for previous recognition performance, hinting at a benefit of flashlight search in VR. Our findings highlight that removing visual information does not necessarily impair location memory, and that screen experiments using virtual environments can elicit the same major effects as VR setups.
Advancing forensic-based investigation incorporating slime mould search for gene selection of high-dimensional genetic data
Authors: Qiu Feng , Heidari Ali Asghar , Chen Yi , Chen Huiling , Liang Guoxi
Published: April 2024

Modern medicine has produced large genetic datasets of high dimensions through advanced gene sequencing technology, and processing these data is of great significance for clinical decision-making. Gene selection (GS) is an important data preprocessing technique that aims to select a subset of feature information to improve performance and reduce data dimensionality. This study proposes an improved wrapper GS method based on forensic-based investigation (FBI). The method introduces the search mechanism of the slime mould algorithm in the FBI to improve the original FBI; the newly proposed algorithm is named SMA_FBI; then GS is performed by converting the continuous optimizer to a binary version of the optimizer through a transfer function. In order to verify the superiority of SMA_FBI, experiments are first executed on the 30-function test set of CEC2017 and compared with 10 original algorithms and 10 state-of-the-art algorithms. The experimental results show that SMA_FBI is better than other algorithms in terms of finding the optimal solution, convergence speed, and robustness. In addition, BSMA_FBI (binary version of SMA_FBI) is compared with 8 binary algorithms on 18 high-dimensional genetic data from the UCI repository. The results indicate that BSMA_FBI is able to obtain high classification accuracy with fewer features selected in GS applications. Therefore, SMA_FBI is considered an optimization tool with great potential for dealing with global optimization problems, and its binary version, BSMA_FBI, can be used for GS tasks.
Plasminogen degrades α-synuclein, Tau and TDP-43 and decreases dopaminergic neurodegeneration in mouse models of Parkinson’s disease
Authors: Guo Chunying , Wang Ting , Huang Haiyan , Wang Xiaolu , Jiang Yugui , Li Jinan
Published: April 2024

Parkinson's disease (PD) is the second most frequently diagnosed neurodegenerative disease, and it is characterized by the intracellular and extracellular accumulation of α-synuclein (α-syn) and Tau, which are major components of cytosolic protein inclusions called Lewy bodies, in the brain. Currently, there is a lack of effective methods that preventing PD progression. It has been suggested that the plasminogen activation system, which is a major extracellular proteolysis system, is involved in PD pathogenesis. We investigated the functional roles of plasminogen in vitro in an okadaic acid-induced Tau hyperphosphorylation NSC34 cell model, ex vivo using brains from normal controls and methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated mice, and in vivo in a widely used MPTP-induced PD mouse model and an α-syn overexpression mouse model. The in vitro, ex vivo and in vivo results showed that the administered plasminogen crossed the blood‒brain barrier (BBB), entered cells, and migrated to the nucleus, increased plasmin activity intracellularly, bound to α-syn through lysine binding sites, significantly promoted α-syn, Tau and TDP-43 clearance intracellularly and even intranuclearly in the brain, decreased dopaminergic neurodegeneration and increased the tyrosine hydroxylase levels in the substantia nigra and striatum, and improved motor function in PD mouse models. These findings indicate that plasminogen plays a wide range of pivotal protective roles in PD and therefore may be a promising drug candidate for PD treatment.
Prediction error in implicit adaptation during visually- and memory-guided reaching tasks
Authors: Numasawa Kosuke , Miyamoto Takeshi , Kizuka Tomohiro , Ono Seiji
Published: April 2024

Human movements are adjusted by motor adaptation in order to maintain their accuracy. There are two systems in motor adaptation, referred to as explicit or implicit adaptation. It has been suggested that the implicit adaptation is based on the prediction error and has been used in a number of motor adaptation studies. This study aimed to examine the effect of visual memory on prediction error in implicit visuomotor adaptation by comparing visually- and memory-guided reaching tasks. The visually-guided task is thought to be implicit learning based on prediction error, whereas the memory-guided task requires more cognitive processes. We observed the adaptation to visuomotor rotation feedback that is gradually rotated. We found that the adaptation and retention rates were higher in the visually-guided task than in the memory-guided task. Furthermore, the delta-band power obtained by electroencephalography (EEG) in the visually-guided task was increased immediately following the visual feedback, which indicates that the prediction error was larger in the visually-guided task. Our results show that the visuomotor adaptation is enhanced in the visually-guided task because the prediction error, which contributes update of the internal model, was more reliable than in the memory-guided task. Therefore, we suggest that the processing of the prediction error is affected by the task-type, which in turn affects the rate of the visuomotor adaptation.
A reassessment of trends and rural–urban/regional differences in the total fertility rate in China, 2000–2020: analyses of the 2020 national census data
Authors: Li Long , Jin Guangzhao , Lai Xiaozhen , Jing Rize , Zhu He
Published: April 2024

The decline in the total fertility rate (TFR) is a key driver of population change and has important implications for population health and social development. However, China’s TFR has been a considerable controversy due to a lack of high-quality data. Therefore, this study used the 2020 national population census of China (NPCC) data and reverse survival method to reassess temporal trends in the TFRs and to reexamine rural–urban differences and regional variations in TFRs from 2000 to 2020 in China. Overall, there were significant gaps between the estimated and reported TFRs before 2020, and the estimated TFRs based on the 2020 NPCC data remained higher than the reported TFRs from government statistics. Although TFRs rebounded shortly in the years after the two-child policy, they have shown a wavelike decline since 2010. Additionally, the estimated TFRs fluctuated below 1.5 children per woman in urban areas compared to above 1.8 in rural areas, but the rural–urban differences continued to decrease. Regarding geographic regional variations, the estimated TFRs in all regions displayed a declining trend during 2010–2020, especially in rural areas. Large decreases of over 25% in TFRs occurred in the north, east, central, and northwest regions. In addition to changing the birth policy, the government and society should adopt comprehensive strategies, including reducing the costs of marriage, childbearing, and child education, as well as promoting work-family balance, to encourage and increase fertility levels.
Simulation of daily soft multifocal contact lenses using SimVis Gekko: from in-vitro and computational characterization to clinical validation
Authors: Esteban-Ibañez Eduardo , Montagud-Martínez Diego , Sawides Lucie , Zaytouny Amal , de Castro Alberto , Sisó-Fuertes Irene , Barcala Xoana , Piñero David P. , Furlan Walter D. , Dorronsoro Carlos , Gambra Enrique
Published: April 2024

Multifocal contact lenses (MCLs) are one of the solutions to correct presbyopia, but their adoption is not widespread. To address this situation, visual simulators can be used to refine the adaptation process. This study aims to obtain accurate simulations for a visual simulator (SimVis Gekko; 2EyesVision) of daily soft MCL designs from four manufacturers. In-vitro characterization of these MCLs—several powers and additions- was obtained using NIMO TR-1504. From the averaged relative power profiles across powers, phase maps were reconstructed and the Through-Focus Visual Strehl metric was calculated for each MCL design. The SimVis Gekko simulation corresponding to each MCL design was obtained computationally and bench-validated. Finally, the MCL simulations were clinically validated involving presbyopic patients. The clinical validation results show a good agreement between the SimVis Gekko simulations and the real MCLs for through-focus visual acuity (TF-VA) curves and VA at three real distances. All MCL designs showed a partial correlation higher than 0.90 and a Root Mean Square Error below 0.07 logMAR between the TF-VA of simulations and Real MCLs across subjects. The validity of the simulation approach using SimVis Gekko and in-vitro measurements was confirmed in this study, opening the possibility to accelerate the adaptation of MCLs.
An explainable machine learning model for prediction of high-risk nonalcoholic steatohepatitis
Authors: Njei Basile , Osta Eri , Njei Nelvis , Al-Ajlouni Yazan A. , Lim Joseph K.
Published: April 2024

Early identification of high-risk metabolic dysfunction-associated steatohepatitis (MASH) can offer patients access to novel therapeutic options and potentially decrease the risk of progression to cirrhosis. This study aimed to develop an explainable machine learning model for high-risk MASH prediction and compare its performance with well-established biomarkers. Data were derived from the National Health and Nutrition Examination Surveys (NHANES) 2017-March 2020, which included a total of 5281 adults with valid elastography measurements. We used a FAST score ≥ 0.35, calculated using liver stiffness measurement and controlled attenuation parameter values and aspartate aminotransferase levels, to identify individuals with high-risk MASH. We developed an ensemble-based machine learning XGBoost model to detect high-risk MASH and explored the model’s interpretability using an explainable artificial intelligence SHAP method. The prevalence of high-risk MASH was 6.9%. Our XGBoost model achieved a high level of sensitivity (0.82), specificity (0.91), accuracy (0.90), and AUC (0.95) for identifying high-risk MASH. Our model demonstrated a superior ability to predict high-risk MASH vs. FIB-4, APRI, BARD, and MASLD fibrosis scores (AUC of 0.95 vs. 0.50, 0.50, 0.49 and 0.50, respectively). To explain the high performance of our model, we found that the top 5 predictors of high-risk MASH were ALT, GGT, platelet count, waist circumference, and age. We used an explainable ML approach to develop a clinically applicable model that outperforms commonly used clinical risk indices and could increase the identification of high-risk MASH patients in resource-limited settings.
Phenotypic analysis of ataxia in spinocerebellar ataxia type 6 mice using DeepLabCut
Authors: Piotrowski Dennis , Clemensson Erik K. H. , Nguyen Huu Phuc , Mark Melanie D.
Published: April 2024

This study emphasizes the benefits of open-source software such as DeepLabCut (DLC) and R to automate, customize and enhance data analysis of motor behavior. We recorded 2 different spinocerebellar ataxia type 6 mouse models while performing the classic beamwalk test, tracked multiple body parts using the markerless pose-estimation software DLC and analyzed the tracked data using self-written scripts in the programming language R. The beamwalk analysis script (BAS) counts and classifies minor and major hindpaw slips with an 83% accuracy compared to manual scoring. Nose, belly and tail positions relative to the beam, as well as the angle at the tail base relative to the nose and tail tip were determined to characterize motor deficits in greater detail. Our results found distinct ataxic abnormalities such as an increase in major left hindpaw slips and a lower belly and tail position in both SCA6 ataxic mouse models compared to control mice at 18 months of age. Furthermore, a more detailed analysis of various body parts relative to the beam revealed an overall lower body position in the SCA684Q compared to the CT-longQ27PC mouse line at 18 months of age, indicating a more severe ataxic deficit in the SCA684Q group.
A cross-sectional analysis of the PURE study on minerals intake among Malaysian adult population with hypertension
Authors: Mat Nasir Nafiza , Md Isa Zaleha , Ismail Noor Hassim , Ismail Rosnah , Mohd Tamil Azmi , Jaafar Mohd Hasni , Mohamed Yassin Mohamed Syarif , Zainol Abidin Najihah , Ab Razak Nurul Hafiza , Zulkifli Aziemah , Yusof Khairul Hazdi
Published: April 2024

Hypertension (HPT) is the leading modifiable risk factor for cardiovascular diseases and premature death worldwide. Currently, attention is given to various dietary approaches with a special focus on the role of micronutrient intake in the regulation of blood pressure. This study aims to measure the dietary intake of selected minerals among Malaysian adults and its association with HPT. This cross-sectional study involved 10,031 participants from the Prospective Urban and Rural Epidemiological study conducted in Malaysia. Participants were grouped into HPT if they reported having been diagnosed with high blood pressure [average systolic blood pressure (SBP)/average diastolic blood pressure (DBP) ≥ 140/90 mm Hg]. A validated food frequency questionnaire (FFQ) was used to measure participants' habitual dietary intake. The dietary mineral intake of calcium, copper, iron, magnesium, manganese, phosphorus, potassium, sodium, and zinc was measured. The chi-square test was used to assess differences in socio-demographic factors between HPT and non-HPT groups, while the Mann–Whitney U test was used to assess differences in dietary mineral intake between the groups. The participants’ average dietary intake of calcium, copper, iron, magnesium, manganese, phosphorus, potassium, selenium, sodium, and zinc was 591.0 mg/day, 3.8 mg/day, 27.1 mg/day, 32.4 mg/day, 0.4 mg/day, 1431.1 mg/day, 2.3 g/day, 27.1 µg/day, 4526.7 mg/day and 1.5 mg/day, respectively. The intake was significantly lower among those with HPT than those without HPT except for calcium and manganese. Continuous education and intervention should be focused on decreasing sodium intake and increasing potassium, magnesium, manganese, zinc, and calcium intake for the general Malaysian population, particularly for the HPT patients.
Impact of species composition on fire-induced stand damage in Spanish forests
Authors: Peris-Llopis Marina , Mola-Yudego Blas , Berninger Frank , Garcia-Gonzalo Jordi , González-Olabarria José Ramón
Published: April 2024

Mixed forests play a fundamental ecological role increasing biodiversity and providing ecosystem services; it has been suggested they have higher resilience and resistance against disturbances, particularly fire. Here, we compare tree mortality in post-fire mixed and pure stands in Spain, on 2,782 plots and 30,239 trees during the period 1986 to 2007. We show evidence that mixed stands can have higher post-fire mortality than pure stands, and specific mixtures of species with different fire-related strategies increase the stand's vulnerability to fire damage versus pure stands of either species, such is the case of Pinus halepensis—Pinus nigra mixtures. Mixtures of two species often had higher mortality than species growing in pure stands. Combinations of species with different fire-related strategies can both enhance or reduce forest resistance. The role and management of mixed forests should be reconsidered after these findings, in order to enhance forest resilience to fires.
Probing the expression and adhesion of glycans involved in Helicobacter pylori infection
Authors: Sijmons Daniel , Collett Simon , Soliman Caroline , Guy Andrew J. , Scott Andrew M. , Durrant Lindy G. , Elbourne Aaron , Walduck Anna K. , Ramsland Paul A.
Published: April 2024

Helicobacter pylori infects approximately half the human population and has an unusual infective niche of the human stomach. Helicobacter pylori is a major cause of gastritis and has been classified as a group 1 carcinogen by the WHO. Treatment involves triple or quadruple antibiotic therapy, but antibiotic resistance is becoming increasingly prevalent. Helicobacter pylori expresses certain blood group related antigens (Lewis system) as a part of its lipopolysaccharide (LPS), which is thought to assist in immune evasion. Additionally, H. pylori LPS participates in adhesion to host cells alongside several adhesion proteins. This study profiled the carbohydrates of H. pylori reference strains (SS1 and 26695) using monoclonal antibodies (mAbs) and lectins, identifying interactions between two carbohydrate-targeting mAbs and multiple lectins. Atomic force microscopy (AFM) scans were used to probe lectin and antibody interactions with the bacterial surfaces. The selected mAb and lectins displayed an increased adhesive force over the surface of the curved H. pylori rods. Furthermore, this study demonstrates the ability of anti-carbohydrate antibodies to reduce the adhesion of H. pylori 26695 to human gastric adenocarcinoma cells via AFM. Targeting bacterial carbohydrates to disrupt crucial adhesion and immune evasion mechanisms represents a promising strategy for combating H. pylori infection.
Cullin-3 proteins be a novel biomarkers and therapeutic targets for hyperchloremia induced by oral poisoning
Authors: Duan Hui , Li Na , Qi Jia , Li Xi , Zhou Kun
Published: April 2024

Oral poisoning can trigger diverse physiological reactions, determined by the toxic substance involved. One such consequence is hyperchloremia, characterized by an elevated level of chloride in the blood and leads to kidney damage and impairing chloride ion regulation. Here, we conducted a comprehensive genome-wide analysis to investigate genes or proteins linked to hyperchloremia. Our analysis included functional enrichment, protein–protein interactions, gene expression, exploration of molecular pathways, and the identification of potential shared genetic factors contributing to the development of hyperchloremia. Functional enrichment analysis revealed that oral poisoning owing hyperchloremia is associated with 4 proteins e.g. Kelch-like protein 3, Serine/threonine-protein kinase WNK4, Serine/threonine-protein kinase WNK1 and Cullin-3. The protein–protein interaction network revealed Cullin-3 as an exceptional protein, displaying a maximum connection of 18 nodes. Insufficient data from transcriptomic analysis indicates that there are lack of information having direct associations between these proteins and human-related functions to oral poisoning, hyperchloremia, or metabolic acidosis. The metabolic pathway of Cullin-3 protein revealed that the derivative is Sulfonamide which play role in, increasing urine output, and metabolic acidosis resulted in hypertension. Based on molecular docking results analysis it found that Cullin-3 proteins has the lowest binding energies score and being suitable proteins. Moreover, no major variations were observed in unbound Cullin-3 and all three peptide bound complexes shows that all systems remain compact during 50 ns simulations. The results of our study revealed Cullin-3 proteins be a strong foundation for the development of potential drug targets or biomarker for future studies.
Practical application of quantum neural network to materials informatics
Authors: Hirai Hirotoshi
Published: April 2024

Quantum neural network (QNN) models have received increasing attention owing to their strong expressibility and resistance to overfitting. It is particularly useful when the size of the training data is small, making it a good fit for materials informatics (MI) problems. However, there are only a few examples of the application of QNN to multivariate regression models, and little is known about how these models are constructed. This study aims to construct a QNN model to predict the melting points of metal oxides as an example of a multivariate regression task for the MI problem. Different architectures (encoding methods and entangler arrangements) are explored to create an effective QNN model. Shallow-depth ansatzs could achieve sufficient expressibility using sufficiently entangled circuits. The “linear” entangler was adequate for providing the necessary entanglement. The expressibility of the QNN model could be further improved by increasing the circuit width. The generalization performance could also be improved, outperforming the classical NN model. No overfitting was observed in the QNN models with a well-designed encoder. These findings suggest that QNN can be a useful tool for MI.
Non-preventable cases of breast, prostate, lung, and colorectal cancer in 2050 in an elimination scenario of modifiable risk factors
Authors: Palshof Frederik Knude , Mørch Lina Steinrud , Køster Brian , Engholm Gerda , Storm Hans Henrik , Andersson Therese M.-L. , Kroman Niels
Published: April 2024

Most Western countries have increasing number of new cancer cases per year. Cancer incidence is primarily influenced by basically avoidable risk factors and an aging population. Through hypothetical elimination scenarios of multiple major risk factors for cancer, we estimated the number of new cancer cases that are non-preventable in 2050. We compare numbers of new postmenopausal breast, prostate, lung, and colorectal cancer cases in 2021 to projected numbers of new cases in 2050 under prevention scenarios regarding smoking, overweight and obesity, and alcohol consumption: no intervention, 50%, and 100% instant reduction. Cancer incidence data were derived from NORDCAN, and risk factor prevalence data from the Danish National Health Survey. Cancer projections were calculated with the Prevent program. Hypothetical 100% instant elimination of major risk factors for cancer in Denmark in 2022 will result in unchanged numbers of new breast and colorectal cancers in 2050. The number of new prostate cancers will increase by 25% compared to 2021. Unchanged risk factor levels will result in noticeable increase in cancer burden. Increase in life expectancy and age will entail an increase in cancer incidence, despite maximum effect of preventive actions in the population. Our results are important when planning future health care.
Effects of green tea and roasted green tea on human responses
Authors: Kurosaka Chie , Tagata Chika , Nakagawa Sae , Kobayashi Makoto , Miyake Shinji
Published: April 2024

Our objective was to elucidate the effects of tea consumption on refreshment and stress reduction/recovery through examining the multiple associations among factors such as various physiological responses and task performance. Participants included 20 healthy young men who performed a mental arithmetic task while 11 physiological responses were measured. The experiments were conducted twice under different beverage consumption conditions on separate days. The mental arithmetic task was executed six times in 1 day; participants ingested hot water, green tea, or roasted green tea (hojicha) before each task. Several subjective assessments: subjective fatigue, stress, mental workload, and flow were evaluated after each task. The R–R intervals, heart rate variability spectral components, the Poincaré plot indices (SD1 and SD2) and plethysmogram amplitude tended to decrease during task periods compared to resting periods. Tissue blood volume/flow (TBV, TBF) and near-infrared spectroscopy responses (NIRS) were lower in the tea condition than in the hot water condition. By scrutinizing various indicators, we found that aromatic stimulation of Japanese tea beverages has the potential to induce positive effects, enhance mental task performance, promote refreshment, and alleviate feelings of fatigue. These positive effects were observed even in small quantities and within a short duration, mirroring responses observed in daily consumption.
Climate warming contributes to the record-shattering 2022 Pakistan rainfall
Authors: You Yujia , Ting Mingfang , Biasutti Michela
Published: April 2024

A sequence of torrential rainstorms pounded Pakistan in the summer of 2022, shattering records by massive margins (7 sigma). The severe socioeconomic damages underscore the urgency of identifying its dynamic drivers and relationship with human-induced climate change. Here, we find that the downpours were primarily initiated by the synoptic low-pressure systems, whose intensity and longevity far exceeded their counterparts in history as fueled by a historically-high cross-equatorial moisture transport over the Arabian Sea. The moisture transport has been trending upward since the 1960s and, in 2022, along with the anomalous easterly moisture influx caused by the combination of La Niña and negative Indian Ocean Dipole events, created a corridor of heavy rainfall extending from central India toward southern Pakistan. While it is not yet established whether the observed trend of the cross-equatorial moisture transport has exceeded natural variability, model-based analysis confirms that it is consistent with the fingerprint of anthropogenic climate warming and will raise the likelihood of such rare events substantially in the coming decades.
Significant contribution of fractal morphology to aerosol light absorption in polluted environments dominated by black carbon (BC)
Authors: Romshoo Baseerat , Müller Thomas , Ahlawat Ajit , Wiedensohler Alfred , Haneef M. V. , Imran Mohd. , Warsi Aisha Baig , Mandariya Anil Kumar , Habib Gazala , Pöhlker Mira L.
Published: April 2024

In recent years, researchers have emphasized the use of fractal aggregate morphology instead of the core-shell morphology in global climate models for estimating black carbon (BC) forcing. This study confirms that fractal morphology plays an important role in reducing the overestimation of aerosol light absorption calculations in the case of an urban polluted environment. During periods of high anthropogenic BC emissions at Delhi, the particle light absorption is overestimated by 50 to 200% by assumptions of both external mixing and internal core-shell mixing. While incorporating the aggregate morphology model into light absorption simulations is beneficial in such cases, it comes with a high computational burden. To address this, we propose a metric known as morphology index (MI). This index distributes the weightage between the two extreme cases of core-shell and fractal aggregate to obtain accurate particle light absorption. Long-range transported aerosols were estimated to have an MI of 0.78, and fresh local emissions had an MI of 0.48. A BC-based aerosol classification approach was developed to determine the most relevant particle size mode for light absorption. The method is based on patterns found between the correlations of the BC mass concentrations and aerosol number concentrations at the different particles sizes (BC-size correlation spectra). BC-size correlation spectra are introduced as a concept that may be used (i) independently to understand the size-dependent heterogeneous distribution of aerosol light absorption and (ii) in conjunction with MI to accurately model the optical properties of aerosols in different BC regimes.
Deep learning evaluation of echocardiograms to identify occult atrial fibrillation
Authors: Yuan Neal , Stein Nathan R. , Duffy Grant , Sandhu Roopinder K. , Chugh Sumeet S. , Chen Peng-Sheng , Rosenberg Carine , Albert Christine M. , Cheng Susan , Siegel Robert J. , Ouyang David
Published: April 2024

Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic echocardiograms (TTEs), which have structural information, could help identify occult AF. We created a two-stage deep learning algorithm using a video-based convolutional neural network model that (1) distinguished whether TTEs were in sinus rhythm or AF and then (2) predicted which of the TTEs in sinus rhythm were in patients who had experienced AF within 90 days. Our model, trained on 111,319 TTE videos, distinguished TTEs in AF from those in sinus rhythm with high accuracy in a held-out test cohort (AUC 0.96 (0.95–0.96), AUPRC 0.91 (0.90–0.92)). Among TTEs in sinus rhythm, the model predicted the presence of concurrent paroxysmal AF (AUC 0.74 (0.71–0.77), AUPRC 0.19 (0.16–0.23)). Model discrimination remained similar in an external cohort of 10,203 TTEs (AUC of 0.69 (0.67–0.70), AUPRC 0.34 (0.31–0.36)). Performance held across patients who were women (AUC 0.76 (0.72–0.81)), older than 65 years (0.73 (0.69–0.76)), or had a CHA2DS2VASc ≥2 (0.73 (0.79–0.77)). The model performed better than using clinical risk factors (AUC 0.64 (0.62–0.67)), TTE measurements (0.64 (0.62–0.67)), left atrial size (0.63 (0.62–0.64)), or CHA2DS2VASc (0.61 (0.60–0.62)). An ensemble model in a cohort subset combining the TTE model with an electrocardiogram (ECGs) deep learning model performed better than using the ECG model alone (AUC 0.81 vs. 0.79, p = 0.01). Deep learning using TTEs can predict patients with active or occult AF and could be used for opportunistic AF screening that could lead to earlier treatment.
Towards a common European ethical and legal framework for conducting clinical research: the GATEKEEPER experience
Authors: Maccaro Alessia , Tsiompanidou Vasiliki , Piaggio Davide , Gallego Montejo Alba M. , Cea Sánchez Gloria , de Batlle Jordi , Quesada Rodriguez Adrian , Fico Giuseppe , Pecchia Leandro
Published: April 2024

This paper examines the ethical and legal challenges encountered during the GATEKEEPER Project and how these challenges informed the development of a comprehensive framework for future Large-Scale Pilot (LSP) projects. GATEKEEPER is a LSP Project with 48 partners conducting 30 implementation studies across Europe with 50,000 target participants grouped into 9 Reference Use Cases. The project underscored the complexity of obtaining ethical approval across various jurisdictions with divergent regulations and procedures. Through a detailed analysis of the issues faced and the strategies employed to navigate these challenges, this study proposes an ethical and legal framework. This framework, derived from a comparative analysis of ethical application forms and regulations, aims to streamline the ethical approval process for future LSP research projects. By addressing the hurdles encountered in GATEKEEPER, the proposed framework offers a roadmap for more efficient and effective project management, ensuring smoother implementation of similar projects in the future.
Neural circuits regulating visceral pain
Authors: Chang Xiaoli , Zhang Haiyan , Chen Shaozong
Published: April 2024

Visceral hypersensitivity, a common clinical manifestation of irritable bowel syndrome, may contribute to the development of chronic visceral pain, which is a major challenge for both patients and health providers. Neural circuits in the brain encode, store, and transfer pain information across brain regions. In this review, we focus on the anterior cingulate cortex and paraventricular nucleus of the hypothalamus to highlight the progress in identifying the neural circuits involved in visceral pain. We also discuss several neural circuit mechanisms and emphasize the importance of cross-species, multiangle approaches and the identification of specific neurons in determining the neural circuits that control visceral pain.
Three-dimensional spontaneous flow transition in a homeotropic active nematic
Authors: Pratley Vincenzo J. , Caf Enej , Ravnik Miha , Alexander Gareth P.
Published: April 2024

Active nematics are driven, non-equilibrium systems relevant to biological processes including tissue mechanics and morphogenesis, and to active metamaterials in general. We study the three-dimensional spontaneous flow transition of an active nematic in an infinite slab geometry using a combination of numerics and analytics. We show that it is determined by the interplay of two eigenmodes – called S- and D-mode – that are unstable at the same activity threshold and spontaneously breaks both rotational symmetry and chiral symmetry. The onset of the unstable modes is described by a non-Hermitian integro-differential operator, which we determine their exponential growth rates from using perturbation theory. The S-mode is the fastest growing. After it reaches a finite amplitude, the growth of the D-mode is anisotropic, being promoted perpendicular to the S-mode and suppressed parallel to it, forming a steady state with a full three-dimensional director field and a well-defined chirality. Lastly, we derive a model of the leading-order time evolution of the system close to the activity threshold.
Recent increase in the surface mass balance in central East Antarctica is unprecedented for the last 2000 years
Authors: Ekaykin Alexey A. , Veres Arina N. , Wang Yetang
Published: April 2024

The Antarctic Ice Sheet’s reaction on the continuing global warming is crucial to project the future sea level rise. The increasing air temperature causes both accelerating mass loss on the Antarctica’s margins and increased surface mass balance in its interior. Here, we use data from firn cores drilled near Vostok station (central East Antarctica) to analyze the surface mass balance variability over the past 2200 years. We show a 24% increase of snow accumulation rate since early 19 century confirmed by the instrumental data for the last 52 years. The mean surface mass balance value in 1970–2021 (2.25 ± 0.064 g cm−2 yr−1) is very likely unprecedented in the pre-industrial era. The surface mass balance growth is accompanied by the air temperature increase with the sensitivity of 11 ± 2% per 1 °C. These results will help to constrain the potential magnitude of Antarctic snowfall mitigation of future sea level rise.
Large transboundary health impact of Arctic wildfire smoke
Authors: Silver Ben , Arnold Steve R. , Reddington Carly L. , Emmons Louisa K. , Conibear Luke
Published: April 2024

Rapid warming at high latitudes, particularly in Siberia, has led to large wildfires in recent years that cause widespread smoke plumes. These fires lead to substantial deterioration in summer air quality in the region, with a factor 4 increase in summer fine particulate matter (PM2.5) concentrations in parts of Siberia during 1998–2020. Exposure to PM2.5 is associated with increased risk of mortality due to cardiovascular and respiratory disease, and the atmospheric lifetime of PM2.5 means that it can be efficiently transported between regions and nations. We used the Community Earth System Model to quantify the fraction of PM2.5 attributed to high latitude wildfires that occur in the Arctic Council member states and estimated the attributable health impact locally and in neighbouring countries. During 2001–2020 we attribute ~21,000 excess deaths to Arctic Council wildfires on average each year, of which ~8000 occur in countries outside the Arctic Council. Our analysis shows that the health impact of Arctic wildfires decreased during 2001–2020, despite the increase of wildfire-sourced PM2.5, which we suggest is due to a northwards shift in the average latitude of Siberian wildfires, reducing their impact on more densely populated regions.
Balancing resistor-based online electrochemical impedance spectroscopy in battery systems: opportunities and limitations
Authors: Blömeke Alexander , Zappen Hendrik , Ringbeck Florian , Frie Fabian , Wasylowski David , Sauer Dirk Uwe
Published: April 2024

Active dissipative balancing systems are essential in battery systems, particularly for compensating the leakage current differences in battery cells. This study focuses on using balancing resistors to stimulate battery cells for impedance measurement. The value of impedance spectroscopy for in-depth battery cell diagnostics, such as temperature or aging, is currently being demonstrated and recognized by vehicle manufacturers, chip producers, and academia. Our research systematically explores the feasibility of using existing balancing resistors in battery management systems and identifies potential limitations. Here we propose a formula to minimize hardware requirements through signal processing techniques. A quadrupling of the sampling rate, number of averaging values, or the size of the fast Fourier transform is equivalent, concerning the signal-to-noise ratio, to increasing the analog resolution by one bit or reducing the input filter bandwidth by a quarter.
Reverse water–gas shift catalyzed by RhnVO3,4− (n = 3–7) cluster anions under variable temperatures
Authors: Zhao An , Liu Qing-Yu , Li Zi-Yu , Li Xiao-Na , He Sheng-Gui
Published: April 2024

A fundamental understanding of the exact structural characteristics and reaction mechanisms of interface active sites is vital to engineering an energetic metal–support boundary in heterogeneous catalysis.
Cyano-functionalized pyrazine: an electron-deficient unit as a solid additive enables binary organic solar cells with 19.67% efficiency
Authors: Tu Lijun , Wang Hao , Duan Weixu , Ma Ruijie , Jia Tao , Dela Peña Top Archie , Luo Yongmin , Wu Jiaying , Li Mingjie , Xia Xiaomin , Wu Siqi , Chen Kai , Wu Yue , Huang Yulin , Yang Kun , Li Gang , Shi Yongqiang
Published: April 2024

A strong electron-deficient unit CNPz as a solid additive was developed in PTQ10/m-BTP-PhC6 binary organic solar cells. A high PCE of 19.67% was achieved with a significant increase of the JSC and FF (81.8%).
A continuous flow electrochemical reactor using readily available metal wires and carbon fibers as electrodes: environmentally benign halogenations of alkenes, alkynes, and aromatics
Authors: Xie Yinqing , Lin Long , Xu Bo
Published: April 2024

We have developed a new continuous-flow electrochemical reactor using readily available metal wires and carbon fibers as electrodes. Environmentally benign halogenations were used as a proof of concept.
A pyrrolo[3,2-b]pyrrole core containing a covalent triazine-based framework (CTF) for photocatalytic H2 production
Authors: Ali Osman , Jana Anupam , Das Aruntima , Dey Sandeep Kumar , Bhunia Asamanjoy
Published: April 2024

We report herein a novel pyrrolo[3,2-b]pyrrole core containing CTF and its Pd NP or Pt NP incorporation for efficient H2 production under visible light irradiation.
Optical study of Te8 ring clusters: comparison with density functional theory and a step towards materials design using nanoporous zeolite space
Authors: Poborchii Vladimir , Rappoport Dmitrij
Published: April 2024

We report an experimental and theoretical study of a regular array of oriented Te8 rings formed in the ~1.14 nm diameter cavities of zeolite LTA.
RAFT/ROP binary polymerization towards well-defined graft copolymers
Authors: Zhang Shuang , Ren Ning , Li Xiaoyu , Xiao Yan , Lang Meidong , Zhu Xinyuan
Published: April 2024

The RAFT/ROP binary polymerization enables the efficient synthesis of controlled and well-defined poly(N-hydroxyethyl acrylamide)–poly(ε-caprolactone) (PHEAA-g-PCL) as compared to the conventional “two-step” method.
Anisotropic ZSM-5 nanorod assemblies: facile synthesis, epitaxial growth, and strikingly enhanced stability in benzene alkylation
Authors: Zhu Peng , Yu Yiren , Gao Guoshu , Zhao Yumeng , Jiao Yuting , Liu Haiou , Liu Guodong , Zhang Xiongfu , Yang Guohui
Published: April 2024

A novel bundle-like ZSM-5 nanorod assembly was facilely synthesized by adopting a CTAB-aided seed-induced strategy for highly efficient alkylation of benzene with ethanol.
Modified synthetic peptides: from therapeutics to chemosensors
Authors: Wynne Conor , Elmes Robert B. P.
Published: April 2024

Modified synthetic peptides have emerged as an exciting avenue for enhancing therapeutic efficacy and expanding the scope of applications in various disease contexts.
Photosynthesis of urea from N2 and CO2 using dual active site SiW6Mo6@MIL-101(Cr) at room temperature
Authors: Su Senda , Li Xiaoman , Ding Wenming , Cao Yue , Yuan Shengbo , Liu Zhenyu , Yang Yang , Ding Yi , Luo Min
Published: April 2024

SiW6Mo6@MIL-101(Cr) serves as a bifunctional photocatalyst, offering dual active sites for the reduction of N2 and CO2 to photosynthesize urea.
Application of 3D, 4D, 5D, and 6D bioprinting in cancer research: what does the future look like?
Authors: Khorsandi Danial , Rezayat Dorsa , Sezen Serap , Ferrao Rafaela , Khosravi Arezoo , Zarepour Atefeh , Khorsandi Melika , Hashemian Mohammad , Iravani Siavash , Zarrabi Ali
Published: April 2024

Recent advancements pertaining to the application of 3D, 4D, 5D, and 6D bioprinting in cancer research are discussed, focusing on important challenges and future perspectives.
Fabrication of a novel palladium membrane sensor for its determination in environmental and biological samples
Authors: Bahathiq Adil O. S. , Babalghith Ahmad O. , Amin Alaa S. , Askar Abdelrazek M.
Published: April 2024

A novel sensitive, specific, and reversible optical sensor for the palladium(ii) ion was created by impregnating an agarose membrane with 4-(2-amino-3-hydroxypyridine-4-ylazo)1,5-dimethyl-2-phenyl-1,2-dihydropyrazol-3-one (AHDDO).
Optimizing transmission line parameter estimation with hybrid evolutionary techniques
Authors: Shaikh Muhammad Suhail , Raj Saurav , Abdul Latif Shah , Mbasso Wulfran Fendzi , Kamel Salah
Published: April 2024

Power flow, planning, economics, dispatch, and stability analysis rely on accurate transmission line parameters (TLPE). Standard optimization methods are employed to develop such analyses and obtain TLPE. Additionally, these methods have limitations, including precision, accuracy, and time complexity. It is challenging to find improved solutions using standard optimization methods due to slow convergence and limitations in identifying local optima. Concerned with these challenges, the study suggest a new application for an effective hybrid optimization method capable of addressing such limitations. The hybrid algorithm, named the Salp Swarm Algorithm with Sine Cosine Algorithm (HSSASCA), that aims to tackle the issues of slow convergence and local optima. The Sine Cosine Algorithm (SCA) is employed after the Salp Swarm Algorithm (SSA), and Salp integration is utilized to successfully explore and analyze the search space. To enhance the performance of HSSASCA, the hybrid technique aims to provide expanded exploration capabilities, effective exploitation of the search space, and a better convergence rate. These key features position the HSSASCA algorithm as an effective solution to complex optimization problems. To assess the efficiency of the HSSASCA algorithm, six different test systems are employed. Initially, the evaluation of exploration, exploitation, and minimized local optima is conducted using the CEC 2019 benchmark functions. Secondly, efficiency monitoring and verification of HSSASCA across different scenarios occur by comparing it with established optimization algorithms such as SSA, SCA, firefly optimization algorithm (FFO), Grey Wolf Optimization (GWO), student psychology‐based optimization (SPBO), and Symbiotic Organisms Search (SOS). Finally, statistical analysis is performed, revealing that the HSSASCA outperforms SSA, SCA, FFO, GWO, SPBO, and SOS. In terms of statistical results and convergence curves, the HSSASCA demonstrates superior performance in searching efficiency, convergence accuracy, and local optimum avoidance ability.
A state‐space average model of a three‐level PV inverter for transient short‐circuit currents analysis
Authors: Yuan Shuai , Wen Bing , Zhang Jian‐Ying , Li Zhimin
Published: April 2024

This paper presents a state‐space average model of a three‐level photovoltaic (PV) inverter to understand short‐circuit currents transient characteristics. Analytical solution of the model is also derived. The proposed model is validated with PV system controller hardware in‐loop (HIL) test method. The errors between simulation and HIL tests results under various conditions are evaluated, testifying the validity of the proposed model. With the model and analytical solution, the decaying time constants of sub‐transient and transient processes are derived, which shows that the time constants of a three‐level PV inverter are not fixed and they vary with voltage dips. The analytical expression of short‐circuit currents is also formulated. The findings from this study are essential to short‐circuit current calculations of a power grid with large‐scale PV plants, coordination of power system protections, and grid planning.
VGA‐Net: Vessel graph based attentional U‐Net for retinal vessel segmentation
Authors: Jalali Yeganeh , Fateh Mansoor , Rezvani Mohsen
Published: April 2024

Segmentation is crucial in diagnosing retinal diseases by accurately identifiying retinal vessels. This paper addresses the complexity of segmenting retinal vessels, highlighting the need for precise analysis of blood vessel structures. Despite the progress made by convolutional neural networsks (CNNs) in image segmentation, their limitations in capturing the global structure of retinal vsessels and maintaining segmentation continuity present challenges. To tackle these issues, our proposed network integrates graph convolutional networks (GCNs) and attention mechansims. This allows the model to consider pixel relationships and learn vessel graphical structures, significantly improving segmentation accuracy. Additionally, the attentional feature fusion module, including pixel‐wise and channel‐wise attention mechansims within the U‐Net architecture, refines the model's focus on relevant features. This paper emphasizes the importance of continuty preservation, ensuring an accurate representation of pixel‐level information and structural details during sefmentation. Therefore, our method performs as an effective solution to overcome challenges in retinal vessel segmentation. The proposed method outperformed the state‐of‐the‐art approaches on DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (Structed Analysis of the Retina) datasets with accuracies of 0.12% and 0.14%, respecttively. Importantly, our proposed approach excelled in delineating slender and diminutive blood vessels, crucial for diagnosing vascular‐related diseases. Implementation is accessible on https://github.com/CVLab‐SHUT/VGA‐Net.