bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of public-health measures for zeroing out different SARS-CoV-2 variants
Authors: Ge Yong , Wu Xilin , Zhang Wenbin , Wang Xiaoli , Zhang Die , Wang Jianghao , Liu Haiyan , Ren Zhoupeng , Ruktanonchai Nick W. , Ruktanonchai Corrine W. , Cleary Eimear , Yao Yongcheng , Wesolowski Amy , Cummings Derek A. T. , Li Zhongjie , Tatem Andrew J. , Lai Shengjie 
Published: August 2023

AbstractTargeted public health interventions for an emerging epidemic are essential for preventing pandemics. During 2020-2022, China invested significant efforts in strict zero-COVID measures to contain outbreaks of varying scales caused by different SARS-CoV-2 variants. Based on a multi-year empirical dataset containing 131 outbreaks observed in China from April 2020 to May 2022 and simulated scenarios, we ranked the relative intervention effectiveness by their reduction in instantaneous reproduction number. We found that, overall, social distancing measures (38% reduction, 95% prediction interval 31-45%), face masks (30%, 17-42%) and close contact tracing (28%, 24-31%) were most effective. Contact tracing was crucial in containing outbreaks during the initial phases, while social distancing measures became increasingly prominent as the spread persisted. In addition, infections with higher transmissibility and a shorter latent period posed more challenges for these measures. Our findings provide quantitative evidence on the effects of public-health measures for zeroing out emerging contagions in different contexts.
Cobalt-catalyzed atroposelective C−H activation/annulation to access N−N axially chiral frameworks
Authors: Li Tong , Shi Linlin , Wang Xinhai , Yang Chen , Yang Dandan , Song Mao-Ping , Niu Jun-Long 
Published: August 2023

AbstractThe N−N atropisomer, as an important and intriguing chiral system, was widely present in natural products, pharmaceutical lead compounds, and advanced material skeletons. The anisotropic structural characteristics caused by its special axial rotation have always been one of the challenges that chemists strive to overcome. Herein, we report an efficient method for the enantioselective synthesis of N−N axially chiral frameworks via a cobalt-catalyzed atroposelective C-H activation/annulation process. The reaction proceeds under mild conditions by using Co(OAc)2·4H2O as the catalyst with a chiral salicyl-oxazoline (Salox) ligand and O2 as an oxidant, affording a variety of N−N axially chiral products with high yields and enantioselectivities. This protocol provides an efficient approach for the facile construction of N−N atropisomers and further expands the range of of N−N axially chiral derivatives. Additionally, under the conditions of electrocatalysis, the desired N−N axially chiral products were also successfully achieved with good to excellent efficiencies and enantioselectivities.
Barcoded multiple displacement amplification for high coverage sequencing in spatial genomics
Authors: Kim Jinhyun , Kim Sungsik , Yeom Huiran , Song Seo Woo , Shin Kyoungseob , Bae Sangwook , Ryu Han Suk , Kim Ji Young , Choi Ahyoun , Lee Sumin , Ryu Taehoon , Choi Yeongjae , Kim Hamin , Kim Okju , Jung Yushin , Kim Namphil , Han Wonshik , Lee Han-Byoel , Lee Amos C. , Kwon Sunghoon 
Published: August 2023

AbstractDetermining mutational landscapes in a spatial context is essential for understanding genetically heterogeneous cell microniches. Current approaches, such as Multiple Displacement Amplification (MDA), offer high genome coverage but limited multiplexing, which hinders large-scale spatial genomic studies. Here, we introduce barcoded MDA (bMDA), a technique that achieves high-coverage genomic analysis of low-input DNA while enhancing the multiplexing capabilities. By incorporating cell barcodes during MDA, bMDA streamlines library preparation in one pot, thereby overcoming a key bottleneck in spatial genomics. We apply bMDA to the integrative spatial analysis of triple-negative breast cancer tissues by examining copy number alterations, single nucleotide variations, structural variations, and kataegis signatures for each spatial microniche. This enables the assessment of subclonal evolutionary relationships within a spatial context. Therefore, bMDA has emerged as a scalable technology with the potential to advance the field of spatial genomics significantly.
Realizing tight-binding Hamiltonians using site-controlled coupled cavity arrays
Authors: Saxena Abhi , Manna Arnab , Trivedi Rahul , Majumdar Arka 
Published: August 2023

AbstractAnalog quantum simulators rely on programmable and scalable quantum devices to emulate Hamiltonians describing various physical phenomenon. Photonic coupled cavity arrays are a promising alternative platform for realizing such simulators, due to their potential for scalability, small size, and high-temperature operability. However, programmability and nonlinearity in photonic cavities remain outstanding challenges. Here, using a silicon photonic coupled cavity array made up of $$8$$
8
high quality factor ($$Q$$
Q
up to$$\, \sim 7.1\times {10}^{4}$$

~
7.1
×

10

4

) resonators and equipped with specially designed thermo-optic island heaters for independent control of cavities, we demonstrate a programmable photonic cavity array in the telecom regime, implementing tight-binding Hamiltonians with access to the full eigenenergy spectrum. We report a $$\sim 50\%$$
~
50
%
reduction in the thermal crosstalk between neighboring sites of the cavity array compared to traditional heaters, and then present a control scheme to program the cavity array to a given tight-binding Hamiltonian. The ability to independently program high-Q photonic cavities, along with the compatibility of silicon photonics to high volume manufacturing opens new opportunities for scalable quantum simulation using telecom regime infrared photons.
An interpretable multiparametric radiomics model of basal ganglia to predict dementia conversion in Parkinson’s disease
Authors: Park Chae Jung , Eom Jihwan , Park Ki Sung , Park Yae Won , Chung Seok Jong , Kim Yun Joong , Ahn Sung Soo , Kim Jinna , Lee Phil Hyu , Sohn Young Ho , Lee Seung-Koo 
Published: August 2023

AbstractCognitive impairment in Parkinson’s disease (PD) severely affects patients’ prognosis, and early detection of patients at high risk of dementia conversion is important for establishing treatment strategies. We aimed to investigate whether multiparametric MRI radiomics from basal ganglia can improve the prediction of dementia development in PD when integrated with clinical profiles. In this retrospective study, 262 patients with newly diagnosed PD (June 2008–July 2017, follow-up >5 years) were included. MRI radiomic features (n = 1284) were extracted from bilateral caudate and putamen. Two models were developed to predict dementia development: (1) a clinical model—age, disease duration, and cognitive composite scores, and (2) a combined clinical and radiomics model. The area under the receiver operating characteristic curve (AUC) were calculated for each model. The models’ interpretabilities were studied. Among total 262 PD patients (mean age, 68 years ± 8 [standard deviation]; 134 men), 51 (30.4%), and 24 (25.5%) patients developed dementia within 5 years of PD diagnosis in the training (n = 168) and test sets (n = 94), respectively. The combined model achieved superior predictive performance compared to the clinical model in training (AUCs 0.928 vs. 0.894, P = 0.284) and test set (AUCs 0.889 vs. 0.722, P = 0.016). The cognitive composite scores of the frontal/executive function domain contributed most to predicting dementia. Radiomics derived from the caudate were also highly associated with cognitive decline. Multiparametric MRI radiomics may have an incremental prognostic value when integrated with clinical profiles to predict future cognitive decline in PD.
Shifting the mindset culture to address global educational disparities
Authors: Hecht Cameron A. , Murphy Mary C. , Dweck Carol S. , Bryan Christopher J. , Trzesniewski Kali H. , Medrano Fortunato N. , Giani Matt , Mhatre Pratik , Yeager David S. 
Published: August 2023

AbstractEducational outcomes remain highly unequal within and across nations. Students’ mindsets—their beliefs about whether intellectual abilities can be developed—have been identified as a potential lever for making adolescents’ academic outcomes more equitable. Recent research, however, suggests that intervention programs aimed at changing students’ mindsets should be supplemented by programs aimed at the changing the mindset culture, which is defined as the shared set of beliefs about learning in a school or classroom. This paper reviews the theoretical and empirical origin of the mindset culture and examines its potential to reduce group-based inequalities in education. In particular, experiments have identified two broad ways the mindset culture is communicated by teachers: via informal messages about growth (e.g., that all students will be helped to learn and succeed), and formal opportunities to improve (e.g., learning-focused grading policies and opportunities to revise and earn credit). New field experiments, applying techniques from behavioral science, have also revealed effective ways to influence teachers’ culture-creating behaviors. This paper describes recent breakthroughs in the U.S. educational context and discusses how lessons from these studies might be applied in future, global collaborations with researchers and practitioners.
Anti-cancer potentiality of linoelaidic acid isolated from marine Tapra fish oil (Ophisthopterus tardoore) via ROS generation and caspase activation on MCF-7 cell line
Authors: Dutta Ananya , Panchali Titli , Khatun Amina , Jarapala Sreenivasa Rao , Das Koushik , Ghosh Kuntal , Chakrabarti Sudipta , Pradhan Shrabani 
Published: August 2023

AbstractThe implication of inflammation in the pathophysiology of several types of cancers has been under intense investigation. Conjugated fatty acids can modulate inflammation and present anticancer effects, promoting cancer cell death. In this paper, we evaluated the efficacy of new conjugated fatty acids isolated from marine Opisthopterus tardoore (Tapra fish) in human breast cancer cell lines MCF-7. Linoelaidic acid, a marine fish (O. tardoore) derived unsaturated fatty acids, showed effective anticancer activity against MCF-7. Cell viability (MTT) assay revealed a dose-dependent decline in cancer cell viability. It was noteworthy that 5 µM linoelaidic acid decreased the MCF-7 cell viability by 81.82%. Besides that, linoelaidic acid significantly (P< 0.05) increased the level of tumor necrosis factor-α (TNF-α) and interleukin-1 receptor antagonist (IL-1ra) studied by ELISA. Not only that, linoelaidic acid significantly decreased the reduced glutathione level and increased the oxidized glutathione level in MCF-7 cells indicating the oxidative stress inside the cell. Two different cell staining methods with acridine orange-ethidium bromide and DAPI confirmed that the linoelaidic acid rendered their detrimental effect on cancer cells. To decipher the mode of apoptosis Western blotting was performed in which the expression pattern of several proteins (p53, IL-10, and IL-1ra) established the apoptosis in the studied cell lines after linoelaidic acid exposure. Hence it may be conferred that linoelaidic acid has prompt anticancer activity. Therefore this drug can be used further for the treatment of cancer.
Ion-acoustic waves in weakly ionized plasmas with charge-exchange collisions
Authors: Alharbi Abdulrahman , Schiesko L. , Minea T. 
Published: August 2023

AbstractIon-neutral charge-exchange collisions in plasmas of laboratory, space, and astrophysical origins are fundamental to understanding wave dissipation and wave generation phenomena. This paper implements a charge-exchange collision operator in the Boltzmann–Poisson system equations for a weakly ionized plasma. When considering an electric field perturbation, the governing kinetic equations provide significant results concerning the plasma conductivity and the dielectric function, appearing in simple, sensible forms. The present analysis reveals a backward wave propagation phenomenon at maximum conductivity when the wavenumber of the plasma wave is smaller than the reciprocal of the ion-neutral collisions mean free path. In addition, it is shown that ion-neutral coupling resulting from charge-exchange collisions enhances ion-acoustic waves below and beyond the ion plasma frequency and leads to the onset of a fundamental instability that overcomes Landau damping under certain circumstances. The collisionless model is recovered as a limiting case, i.e., in the asymptotic limit of a long mean free path.
Estimation and mapping of soil texture content based on unmanned aerial vehicle hyperspectral imaging
Authors: Song Qi , Gao Xiaohong , Song Yuting , Li Qiaoli , Chen Zhen , Li Runxiang , Zhang Hao , Cai Sangjie 
Published: August 2023

AbstractSoil texture is one of the important physical and natural properties of soil. Much of the current research focuses on soil texture monitoring using non-imaging geophysical spectrometers. However there are fewer studies utilizing unmanned aerial vehicle (UAV) hyperspectral data for soil texture monitoring. UAV mounted hyperspectral cameras can be used for quickly and accurately obtaining high-resolution spatial information of soil texture. A foundation has been laid for the realization of rapid soil texture surveys using unmanned airborne hyperspectral data without field sampling. This study selected three typical farmland areas in Huangshui Basin of Qinghai as the study area, and a total of 296 soil samples were collected. Data calibration of UAV spectra using laboratory spectra and field in situ spectra to explore the feasibility of applying laboratory soil texture models directly to field conditions. This results show that UAV hyperspectral imagery combined with machine learning can obtain a set of ideal processing methods. The pre-processing of the spectral data can obtain high accuracy of soil texture estimation and good mapping effect. The results of this study can provide effective technical support and decision-making assistance for future agricultural land planning on the Tibetan Plateau. The main innovation of this study is to establish a set of processing procedures and methods applicable to UAV hyperspectral imagery to provide data reference for monitoring soil texture in agricultural fields on the Tibetan Plateau.
Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT dataset
Authors: Järnstedt Jorma , Sahlsten Jaakko , Jaskari Joel , Kaski Kimmo , Mehtonen Helena , Hietanen Ari , Sundqvist Osku , Varjonen Vesa , Mattila Vesa , Prapayasatok Sangsom , Nalampang Sakarat 
Published: August 2023

AbstractPreoperative radiological identification of mandibular canals is essential for maxillofacial surgery. This study demonstrates the reproducibility of a deep learning system (DLS) by evaluating its localisation performance on 165 heterogeneous cone beam computed tomography (CBCT) scans from 72 patients in comparison to an experienced radiologist’s annotations. We evaluated the performance of the DLS using the symmetric mean curve distance (SMCD), the average symmetric surface distance (ASSD), and the Dice similarity coefficient (DSC). The reproducibility of the SMCD was assessed using the within-subject coefficient of repeatability (RC). Three other experts rated the diagnostic validity twice using a 0–4 Likert scale. The reproducibility of the Likert scoring was assessed using the repeatability measure (RM). The RC of SMCD was 0.969 mm, the median (interquartile range) SMCD and ASSD were 0.643 (0.186) mm and 0.351 (0.135) mm, respectively, and the mean (standard deviation) DSC was 0.548 (0.138). The DLS performance was most affected by postoperative changes. The RM of the Likert scoring was 0.923 for the radiologist and 0.877 for the DLS. The mean (standard deviation) Likert score was 3.94 (0.27) for the radiologist and 3.84 (0.65) for the DLS. The DLS demonstrated proficient qualitative and quantitative reproducibility, temporal generalisability, and clinical validity.
Structure and conductivity of ionomer in PEM fuel cell catalyst layers: a model-based analysis
Authors: Olbrich W. , Kadyk T. , Sauter U. , Eikerling M. , Gostick J. 
Published: August 2023

AbstractEfforts in design and optimization of catalyst layers for polymer electrolyte fuel cells hinge on mathematical models that link electrode composition and microstructure with effective physico-chemical properties. A pivotal property of these layers and the focus of this work is the proton conductivity, which is largely determined by the morphology of the ionomer. However, available relations between catalyst layer composition and proton conductivity are often adopted from general theories for random heterogeneous media and ignore specific features of the microstructure, e.g., agglomerates, film-like structures, or the hierarchical porous network. To establish a comprehensive understanding of the peculiar structure-property relations, we generated synthetic volumetric images of the catalyst layer microstructure. In a mesoscopic volume element, we modeled the electrolyte phase and calculated the proton conductivity using numerical tools. Varying the ionomer morphology in terms of ionomer film coverage and thickness revealed two limiting cases: the ionomer can either form a thin film with high coverage on the catalyst agglomerates; or the ionomer exists as voluminous chunks that connect across the inter-agglomerate space. Both cases were modeled analytically, adapting relations from percolation theory. Based on the simulated data, a novel relation is proposed, which links the catalyst layer microstructure to the proton conductivity over a wide range of morphologies. The presented analytical approach is a versatile tool for the interpretation of experimental trends and it provides valuable guidance for catalyst layer design. The proposed model was used to analyze the formation of the catalyst layer microstructure during the ink stage. A parameter study of the initial ionomer film thickness and the ionomer dispersion parameter revealed that the ionomer morphology should be tweaked towards well-defined films with high coverage of catalyst agglomerates. These implications match current efforts in the experimental literature and they may thus provide direction in electrode materials research for polymer electrolyte fuel cells.
2-Photon imaging of fluorescent proteins in living swine
Authors: Costine-Bartell Beth A. , Martinez-Ramirez Luis , Normoyle Kieran , Stinson Tawny , Staley Kevin J. , Lillis Kyle P. 
Published: August 2023

AbstractA common point of failure in translation of preclinical neurological research to successful clinical trials comes in the giant leap from rodent models to humans. Non-human primates are phylogenetically close to humans, but cost and ethical considerations prohibit their widespread usage in preclinical trials. Swine have large, gyrencencephalic brains, which are biofidelic to human brains. Their classification as livestock makes them a readily accessible model organism. However, their size has precluded experiments involving intravital imaging with cellular resolution. Here, we present a suite of techniques and tools for in vivo imaging of porcine brains with subcellular resolution. Specifically, we describe surgical techniques for implanting a synthetic, flexible, transparent dural window for chronic optical access to the neocortex. We detail optimized parameters and methods for injecting adeno-associated virus vectors through the cranial imaging window to express fluorescent proteins. We introduce a large-animal 2-photon microscope that was constructed with off-the shelf components, has a gantry design capable of accommodating animals > 80 kg, and is equipped with a high-speed digitizer for digital fluorescence lifetime imaging. Finally, we delineate strategies developed to mitigate the substantial motion artifact that complicates high resolution imaging in large animals, including heartbeat-triggered high-speed image stack acquisition. The effectiveness of this approach is demonstrated in sample images acquired from pigs transduced with the chloride-sensitive fluorescent protein SuperClomeleon.
Prospective pilot study on the relationship between seminal HIV-1 shedding and genital schistosomiasis in men receiving antiretroviral therapy along Lake Malawi
Authors: Kayuni Sekeleghe A. , Abdullahi Adam , Alharbi Mohammad H. , Makaula Peter , Lampiao Fanuel , Juziwelo Lazarus , LaCourse E. James , Kumwenda Johnstone J. , Leutscher Peter Derek Christian , Geretti Anna Maria , Stothard J. Russell 
Published: August 2023

AbstractMale genital schistosomiasis (MGS) is hypothesized to increase seminal shedding of HIV-1. This prospective pilot study assessed seminal HIV-1 RNA shedding in men on long-term ART with and without a diagnosis of MGS. Study visits occurred at 0, 1, 3, 6 and 12 months. MGS was diagnosed by egg positivity on semen microscopy or PCR of seminal sediment. After optimization of the HIV-RNA assay, we examined 72 paired plasma and semen samples collected from 31 men (15 with and 16 without MGS) over 12 months. HIV-1 RNA was detected in 7/72 (9.7%) seminal samples and 25/72 (34.7%) plasma samples. When comparing sample pairs, 5/72 (6.9%) showed HIV-1 RNA detection only in the seminal sample. Overall, 3/31 (9.7%) participants, all with MGS, had detectable HIV-1 RNA in semen while plasma HIV-1 RNA was undetectable (< 22 copies/mL), with seminal levels ranging up to 400 copies/mL. Two participants showing HIV-1 RNA in seminal fluid from the MGS-negative group also had concomitant HIV-1 RNA detection in plasma. The findings suggest that MGS can be associated with low-level HIV-1 RNA shedding despite virologically suppressive ART. Further studies are warranted to confirm these observations and assess its implications.
Dynamozones are the most obvious sign of the evolution of conformational dynamics in HIV-1 protease
Authors: Rahimi Mohammad , Taghdir Majid , Abasi Joozdani Farzane 
Published: August 2023

AbstractProteins are not static but are flexible molecules that can adopt many different conformations. The HIV-1 protease is an important target for the development of therapies to treat AIDS, due to its critical role in the viral life cycle. We investigated several dynamics studies on the HIV-1 protease families to illustrate the significance of examining the dynamic behaviors and molecular motions for an entire understanding of their dynamics-structure–function relationships. Using computer simulations and principal component analysis approaches, the dynamics data obtained revealed that: (i) The flap regions are the most obvious sign of the evolution of conformational dynamics in HIV-1 protease; (ii) There are dynamic structural regions in some proteins that contribute to the biological function and allostery of proteins via appropriate flexibility. These regions are a clear sign of the evolution of conformational dynamics of proteins, which we call dynamozones. The flap regions are one of the most important dynamozones members that are critical for HIV-1 protease function. Due to the existence of other members of dynamozones in different proteins, we propose to consider dynamozones as a footprint of the evolution of the conformational dynamics of proteins.