bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial intelligence defines protein-based classification of thyroid nodules
Authors: Sun Yaoting , Selvarajan Sathiyamoorthy , Zang Zelin , Liu Wei , Zhu Yi , Zhang Hao , Chen Wanyuan , Chen Hao , Li Lu , Cai Xue , Gao Huanhuan , Wu Zhicheng , Zhao Yongfu , Chen Lirong , Teng Xiaodong , Mantoo Sangeeta , Lim Tony Kiat-Hon , Hariraman Bhuvaneswari , Yeow Serene , Alkaff Syed Muhammad Fahmy , Lee Sze Sing , Ruan Guan , Zhang Qiushi , Zhu Tiansheng , Hu Yifan , Dong Zhen , Ge Weigang , Xiao Qi , Wang Weibin , Wang Guangzhi , Xiao Junhong , He Yi , Wang Zhihong , Sun Wei , Qin Yuan , Zhu Jiang , Zheng Xu , Wang Linyan , Zheng Xi , Xu Kailun , Shao Yingkuan , Zheng Shu , Liu Kexin , Aebersold Ruedi , Guan Haixia , Wu Xiaohong , Luo Dingcun , Tian Wen , Li Stan Ziqing , Kon Oi Lian , Iyer Narayanan Gopalakrishna , Guo Tiannan 
Published: September 2022

AbstractDetermination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report the feasibility and clinical utility of developing an AI-defined protein-based biomarker panel for diagnostic classification of thyroid nodules: based initially on formalin-fixed paraffin-embedded (FFPE), and further refined for fine-needle aspiration (FNA) tissue specimens of minute amounts which pose technical challenges for other methods. We first developed a neural network model of 19 protein biomarkers based on the proteomes of 1724 FFPE thyroid tissue samples from a retrospective cohort. This classifier achieved over 91% accuracy in the discovery set for classifying malignant thyroid nodules. The classifier was externally validated by blinded analyses in a retrospective cohort of 288 nodules (89% accuracy; FFPE) and a prospective cohort of 294 FNA biopsies (85% accuracy) from twelve independent clinical centers. This study shows that integrating high-throughput proteomics and AI technology in multi-center retrospective and prospective clinical cohorts facilitates precise disease diagnosis which is otherwise difficult to achieve by other methods.
STING agonism enhances anti-tumor immune responses and therapeutic efficacy of PARP inhibition in BRCA-associated breast cancer
Authors: Pantelidou Constantia , Jadhav Heta , Kothari Aditi , Liu Renyan , Wulf Gerburg M. , Guerriero Jennifer L. , Shapiro Geoffrey I. 
Published: September 2022

AbstractPoly (ADP-ribose) polymerase (PARP) inhibitors exert their efficacy via synthetic lethal effects and by inducing cGAS/STING-mediated immune responses. We demonstrate that compared to monotherapies, combined PARP inhibition and STING agonism results in increased STING pathway activation, greater cytotoxic T-cell recruitment and enhanced dendritic cell activation in BRCA1-deficient breast cancer models. The combination markedly improved anti-tumor efficacy in vivo, with evidence of complete tumor clearance, prolongation of survival and induction of immunologic memory.
Machine learning assisted design of shape-programmable 3D kirigami metamaterials
Authors: Alderete Nicolas A. , Pathak Nibir , Espinosa Horacio D. 
Published: September 2022

AbstractKirigami-engineering has become an avenue for realizing multifunctional metamaterials that tap into the instability landscape of planar surfaces embedded with cuts. Recently, it has been shown that two-dimensional Kirigami motifs can unfurl a rich space of out-of-plane deformations, which are programmable and controllable across spatial scales. Notwithstanding Kirigami’s versatility, arriving at a cut layout that yields the desired functionality remains a challenge. Here, we introduce a comprehensive machine learning framework to shed light on the Kirigami design space and to rationally guide the design and control of Kirigami-based materials from the meta-atom to the metamaterial level. We employ a combination of clustering, tandem neural networks, and symbolic regression analyses to obtain Kirigami that fulfills specific design constraints and inform on their control and deployment. Our systematic approach is experimentally demonstrated by examining a variety of applications at different hierarchical levels, effectively providing a tool for the discovery of shape-shifting Kirigami metamaterials.
Long-term aging of CVD grown 2D-MoS2 nanosheets in ambient environment
Authors: Rajput Nitul S. , Kotbi Ahmed , Kaja Khaled , Jouiad Mustapha 
Published: September 2022

AbstractA chemically vapor deposited MoS2 nanosheets (NSs) is aged in the laboratory at ambient and at 40% average humidity for ~36 months. Nanorods of few microns in length and few nanometers in diameter are found to grow from the MoS2 seeds. They have been growing as a result of the chemical reaction between the MoS2 NSs and ambient O2 and moisture, they exhibit an amorphous phase structure in the stoichiometric form of MoO3. Density functional theory simulations further reveal the role of H2O and O2 in the transformation of the MoS2 NSs. The adsorption energy of O2 molecules on the MoS2 sites is Ead = −1.09 eV as compared to lowest absolute Ead = −0.10 eV of H2O indicating the favorable adsorption of O2 and subsequent Mo oxidation. This study provides valuable insight into the aging phenomenon of MoS2 exposed to O2 and moisture which might limit their application.
Tissue-wide cell-specific proteogenomic modeling reveals novel candidate risk genes in autism spectrum disorders
Authors: Doostparast Torshizi Abolfazl , Wang Kai 
Published: September 2022

AbstractAutism spectrum disorders (ASD) are a set of complex neurodevelopmental diseases characterized with repetitive behavioral patterns and communication disabilities. Using a systems biology method called MAPSD (Markov Affinity-based Proteogenomic Signal Diffusion) for joint modeling of proteome dynamics and a wide array of omics datasets, we identified a list of candidate ASD risk genes. Leveraging the collected biological signals as well as a large-scale protein-protein interaction network adjusted based on single cell resolution proteome properties in four brain regions, we observed an agreement between the known and the newly identified candidate genes that are spatially enriched in neuronal cells within cerebral cortex at the protein level. Moreover, we created a detailed subcellular localization enrichment map of the known and the identified genes across 32 micro-domains and showed that neuronal cells and neuropils share the largest fraction of signal enrichment in cerebral cortex. Notably, we showed that the identified genes are among the transcriptional biomarkers of inhibitory and excitatory neurons in human frontal cortex. Intersecting the identified genes with a single cell RNA-seq data on ASD brains further evidenced that 20 candidate genes, including GRIK1, EMX2, STXBP6, and KCNJ3 are disrupted in distinct cell-types. Moreover, we showed that ASD risk genes are predominantly distributed in certain human interactome modules, and that the identified genes may act as the regulator for some of the known ASD loci. In summary, our study demonstrated how tissue-wide cell-specific proteogenomic modeling can reveal candidate genes for brain disorders that can be supported by convergent lines of evidence.
Characterization of the core microbial community governing acidogenic processes for the production of valuable bioproducts
Authors: Yin Qidong , Wu Guangxue , Lens Piet N. L. 
Published: September 2022

AbstractVolatile fatty acids (VFAs) and alcohols generated from acidogenic processes are valuable bioresources. However, how the diversity of acidogenic microorganisms and environmental factors affect their generation are still poorly understood. In this study, 18 different inocula and 42 sludges from acidogenic lab-scale reactors were collected to analyze the microbial communities and their metabolic potential using 16S rRNA genes high throughput sequencing coupled with PICRUSt2. 23 out of 30732 distinctive amplicon sequence variants were identified as the core features and 34.8% of them (e.g., Clostridium spp.) were positively correlated with the generation of the most common product acetate. PICRUSt2 shows that an average of 27% of predicted fermentation-pathway genes was assigned to the core features, suggesting their crucial roles in acidogenesis. From the network aspect, the acidogenic network had a slightly higher number of nodes (12%), but significantly lower numbers of edges (109%) and neighbors (132%) compared with the inoculum network. A total of 28 independent subnetworks from large to small scales were extracted from the acidogenic network. The decentralized distribution of core features in these subnetworks emphasized their non-co-occurring relationships. The electrode potential was the most significant environmental variable (48.2–49.3% of the explanation), positively affecting the distribution of more than 50% of the core features and fermentation pathways. Results of this study emphasized the importance of core features rather than microbial diversity in acidogenic performance and highlighted the response of the core microbial community to environmental changes, which may be applied in practical applications to optimize acidogenic performance.
Morphometrics in three dimensional choroidal vessel models constructed from swept-source optical coherence tomography images
Authors: Sugano Yukinori , Maeda Shunsuke , Kato Yutaka , Kasai Akihito , Tsuji Shingo , Okamoto Masahiro , Sekiryu Tetsuju 
Published: September 2022

AbstractWe created three types of vessel models: vessel volume, surface, and line models from swept-source optical coherence tomography images and tested experimentally calculated three-dimensional (3D) biomarkers. The choroidal volume (CVolume), surface area (VSurface), and vessel length-associated index (VLI) were measured. The calculated 3D parameters were the mean choroidal thickness, choroidal vascularity index (CVI), vessel length density index (VLDI), vessel length to the stromal (VL–S) ratio, surface-to-volume ratio (S–V ratio), and vessel diameter index (VDI). Cluster analysis showed that the parameters were classified into two clusters: one was represented by the VVolume including the CVolume, VSurface, CVI, S–V ratio, VLI, VDI, and subfoveal choroidal thickness and the other by the VL–S ratio including the VLDI. Regarding the regional distribution, the VVolume, CVolume, VSurface, CVI, VLI, VL–S ratio, and VDI at the foveal center were higher than at the parafovea (P < 0.01). Although the VVolume decreased with age and axial length (AL) elongation, the association of the 3D parameters with age and AL elongation differed. The VLI, VLDI, VL–S ratio, and CVI decreased with age (P < 0.01) but not with AL elongation. The results suggested a structural difference in the choroidal vessel volume reduction between aging and AL elongation. The 3D parameters may provide additional information about the choroidal vasculature.
High-precision robust monitoring of charge/discharge current over a wide dynamic range for electric vehicle batteries using diamond quantum sensors
Authors: Hatano Yuji , Shin Jaewon , Tanigawa Junya , Shigenobu Yuta , Nakazono Akimichi , Sekiguchi Takeharu , Onoda Shinobu , Ohshima Takeshi , Arai Keigo , Iwasaki Takayuki , Hatano Mutsuko 
Published: September 2022

AbstractAccurate prediction of the remaining driving range of electric vehicles is difficult because the state-of-the-art sensors for measuring battery current are not accurate enough to estimate the state of charge. This is because the battery current of EVs can reach a maximum of several hundred amperes while the average current is only approximately 10 A, and ordinary sensors do not have an accuracy of several tens of milliamperes while maintaining a dynamic range of several hundred amperes. Therefore, the state of charge has to be estimated with an ambiguity of approximately 10%, which makes the battery usage inefficient. This study resolves this limitation by developing a diamond quantum sensor with an inherently wide dynamic range and high sensitivity for measuring the battery current. The design uses the differential detection of two sensors to eliminate in-vehicle common-mode environmental noise, and a mixed analog–digital control to trace the magnetic resonance microwave frequencies of the quantum sensor without deviation over a wide dynamic range. The prototype battery monitor was fabricated and tested. The battery module current was measured up to 130 A covering WLTC driving pattern, and the accuracy of the current sensor to estimate battery state of charge was analyzed to be 10 mA, which will lead to 0.2% CO2 reduction emitted in the 2030 WW transportation field. Moreover, an operating temperature range of − 40 to + 85 °C and a maximum current dynamic range of ± 1000 A were confirmed.
Adaptive sampling during sequencing reveals the origins of the bovine reproductive tract microbiome across reproductive stages and sexes
Authors: Ong Chian Teng , Ross Elizabeth M. , Boe-Hansen Gry , Turni Conny , Hayes Ben J. , Fordyce Geoffry , Tabor Ala E. 
Published: September 2022

AbstractCattle enterprises are one of the major livestock production systems globally and are forecasted to have stable growth in the next decade. To facilitate sustainable live weight production, optimal reproductive performance is essential. Microbial colonisation in the reproductive tract has been demonstrated as one of the factors contributing to bovine reproductive performance. Studies also implied that reproductive metagenomes are different at each stage of the estrous cycle. This study applied Oxford Nanopore Technologies’ adaptive long-read sequencing to profile the bovine reproductive microbiome collected from tropical cattle in northern Queensland, Australia. The microbiome samples were collected from cattle of different sexes, reproductive status and locations to provide a comprehensive view of the bovine reproductive microbiome in northern Australian cattle. Ascomycota, Firmicutes and Proteobacteria were abundant phyla identified in the bovine reproductive metagenomes of Australian cattle regardless of sexes, reproductive status and location. The species level taxonomical investigation suggested that gastrointestinal metagenome and the surrounding environment were potentially the origins of the bovine reproductive metagenome. Functional profiles further affirmed this implication, revealing that the reproductive metagenomes of the prepubertal and postpartum animals were dominated by microorganisms that catabolise dietary polysaccharides as an energy substrate while that of the pregnant animals had the function of harvesting energy from aromatic compounds. Bovine reproductive metagenome investigations can be employed to trace the origins of abnormal metagenomes, which is beneficial for disease prevention and control. Additionally, our results demonstrated different reproductive metagenome diversities between cattle from two different locations. The variation in diversity within one location can serve as the indicator of abnormal reproductive metagenome, but between locations inferences cannot be made. We suggest establishing localised metagenomic indices that can be used to infer abnormal reproductive metagenomes which contribute to abortion or sub-fertility.
The impact of 4D-Flow MRI spatial resolution on patient-specific CFD simulations of the thoracic aorta
Authors: Cherry Molly , Khatir Zinedine , Khan Amirul , Bissell Malenka 
Published: September 2022

AbstractMagnetic Resonance Imaging (MRI) is considered the gold standard of medical imaging technologies as it allows for accurate imaging of blood vessels. 4-Dimensional Flow Magnetic Resonance Imaging (4D-Flow MRI) is built on conventional MRI, and provides flow data in the three vector directions and a time resolved magnitude data set. As such it can be used to retrospectively calculate haemodynamic parameters of interest, such as Wall Shear Stress (WSS). However, multiple studies have indicated that a significant limitation of the imaging technique is the spatiotemporal resolution that is currently available. Recent advances have proposed and successfully integrated 4D-Flow MRI imaging techniques with Computational Fluid Dynamics (CFD) to produce patient-specific simulations that have the potential to aid in treatments,surgical decision making, and risk stratification. However, the consequences of using insufficient 4D-Flow MRI spatial resolutions on any patient-specific CFD simulations is currently unclear, despite being a recognised limitation. The research presented in this study aims to quantify the inaccuracies in patient-specific 4D-Flow MRI based CFD simulations that can be attributed to insufficient spatial resolutions when acquiring 4D-Flow MRI data. For this research, a patient has undergone four 4D-Flow MRI scans acquired at various isotropic spatial resolutions and patient-specific CFD simulations have subsequently been run using geometry and velocity data produced from each scan. It was found that compared to CFD simulations based on a $$1.5\,{\text {mm}} \times 1.5\,{\text {mm}} \times 1.5\,{\text {mm}}$$

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, using a spatial resolution of $$4\,{\text {mm}} \times 4\,{\text {mm}} \times 4\,{\text {mm}}$$

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substantially underestimated the maximum velocity magnitude at peak systole by $$110.55\%$$

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. The impacts of 4D-Flow MRI spatial resolution on WSS calculated from CFD simulations have been investigated and it has been shown that WSS is underestimated in CFD simulations that are based on a coarse 4D-Flow MRI spatial resolution. The authors have concluded that a minimum 4D-Flow MRI spatial resolution of $$1.5\,{\text {mm}} \times 1.5\,{\text {mm}} \times 1.5\,{\text {mm}}$$

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must be used when acquiring 4D-Flow MRI data to perform patient-specific CFD simulations. A coarser spatial resolution will produce substantial differences within the flow field and geometry.
Cord blood adiponectin and leptin are associated with a lower risk of stunting during infancy
Authors: Park Sangshin , Vargas Zorimel , Zhao Anne , Baltazar Palmera I. , Friedman Jennifer F. , McDonald Emily A. 
Published: September 2022

AbstractUndernutrition is responsible for up to 45% of deaths in children under five, with low- and middle-income countries disproportionately affected. Adipokines are known modulators of metabolism and have been linked to growth rates and neurocognition during infancy. We examined the relationship(s) between cord blood adiponectin and leptin and both longitudinal growth and cognition during the first year of life using generalized estimating equations. Infants were classified as underweight (weight-for-age z-score [WAZ]), stunted (height-for-age z-score [HAZ]) or wasted (weight-for-height z-score [WHZ]) using WHOAnthro software. Cord blood adiponectin and leptin levels were highly correlated (r = 0.35, P < 0.0001) and positively associated with birth WAZ (r = 0.34 and r = 0.45, P < 0.0001, respectively). Adipokines were independently, inversely associated with weight gain. Infants in the highest quintile of adipokine production had a lower risk of being stunted, while neither was associated with lower WAZ or WHZ in final adjusted models. Cognition was not found to be independently related to cord blood leptin or adiponectin. The negative association with adipokines and rate of weight gain during infancy may reflect heightened nutritional status at birth rather than a direct hormonal influence. The relationship between leptin or adiponectin and longitudinal length gains suggests that both adipokines may promote linear growth during infancy.
12-month prevalence of atopic dermatitis in resource-rich countries: a systematic review and meta-analysis
Authors: Volke Annika , Toompere Karolin , Laisaar Kaja-Triin , Oona Marje , Tisler Anna , Johannson Annika , Kallavus Kadi , Lang Katrin , Kiisk Ele , Uusküla Anneli 
Published: September 2022

AbstractThere is a lack of robust prevalence estimates of atopic dermatitis (AD) globally and trends over time due to wide variation of populations and age groups studied, different study methodologies and case definitions used. We sought to characterize 12-month AD prevalence across the life span and change over time in resource-rich countries focusing on population-based studies and using a standardized AD case definition. This systematic review was conducted according to PRISMA guidelines. Medline (Ovid), Embase, WOS core collection, Cinahl, and Popline were searched for studies published since inception through August 15, 2016. Studies were synthesized using random effects meta-analysis. Sources of heterogeneity were investigated using subgroup analyses and meta-regression. From 12,530 records identified, 45 studies met the inclusion criteria. Meta-analysis with random effects revealed the 12-month period prevalence of 9.2% (95% confidence interval 8.4–10.1%). The prevalence was significantly higher among 0–5-year-old children (16.2%; 95% confidence interval 14.2–18.7%) than in older age groups. Studies using a random sampling strategy yielded lower prevalence estimates than studies relying on other sampling methods. There was no clear time trend in AD prevalence over the period of 1992–2013.
Choice of Voxel-based Morphometry processing pipeline drives variability in the location of neuroanatomical brain markers
Authors: Zhou Xinqi , Wu Renjing , Zeng Yixu , Qi Ziyu , Ferraro Stefania , Xu Lei , Zheng Xiaoxiao , Li Jialin , Fu Meina , Yao Shuxia , Kendrick Keith M. , Becker Benjamin 
Published: September 2022

AbstractFundamental and clinical neuroscience has benefited tremendously from the development of automated computational analyses. In excess of 600 human neuroimaging papers using Voxel-based Morphometry (VBM) are now published every year and a number of different automated processing pipelines are used, although it remains to be systematically assessed whether they come up with the same answers. Here we examined variability between four commonly used VBM pipelines in two large brain structural datasets. Spatial similarity and between-pipeline reproducibility of the processed gray matter brain maps were generally low between pipelines. Examination of sex-differences and age-related changes revealed considerable differences between the pipelines in terms of the specific regions identified. Machine learning-based multivariate analyses allowed accurate predictions of sex and age, however accuracy differed between pipelines. Our findings suggest that the choice of pipeline alone leads to considerable variability in brain structural markers which poses a serious challenge for reproducibility and interpretation.