bluuebunny/crossref_metadata_2025_split huggingface dataset:
Silver-catalyzed direct conversion of epoxides into cyclopropanes using N-triftosylhydrazones
Authors: Li Linxuan , Sivaguru Paramasivam , Wei Dandan , Liu Menglin , Zhu Qingwen , Dong Shuai , Casali Emanuele , Li Nan , Zanoni Giuseppe , Bi Xihe 
Published: March 2024

AbstractEpoxides, as a prominent small ring O-heterocyclic and the privileged pharmacophores for medicinal chemistry, have recently represented an ideal substrate for the development of single-atom replacements. The previous O-to-C replacement strategy for epoxides to date typically requires high temperatures to achieve low yields and lacks substrate range and functional group tolerance, so achieving this oxygen-carbon exchange remains a formidable challenge. Here, we report a silver-catalyzed direct conversion of epoxides into trifluoromethylcyclopropanes in a single step using trifluoromethyl N-triftosylhydrazones as carbene precursors, thereby achieving oxygen-carbon exchange via a tandem deoxygenation/[2 + 1] cycloaddition. The reaction shows broad tolerance of functional groups, allowing routine cheletropic olefin synthesis in a strategy for the net oxygen-carbon exchange reaction. The utility of this method is further showcased with the late-stage diversification of epoxides derived from bioactive natural products and drugs. Mechanistic experiments and DFT calculations elucidate the reaction mechanism and the origin of the chemo- and stereoselectivity.
Alternative low-populated conformations prompt phase transitions in polyalanine repeat expansions
Authors: Antón Rosa , Treviño Miguel Á. , Pantoja-Uceda David , Félix Sara , Babu María , Cabrita Eurico J. , Zweckstetter Markus , Tinnefeld Philip , Vera Andrés M. , Oroz Javier 
Published: March 2024

AbstractAbnormal trinucleotide repeat expansions alter protein conformation causing malfunction and contribute to a significant number of incurable human diseases. Scarce structural insights available on disease-related homorepeat expansions hinder the design of effective therapeutics. Here, we present the dynamic structure of human PHOX2B C-terminal fragment, which contains the longest polyalanine segment known in mammals. The major α-helical conformation of the polyalanine tract is solely extended by polyalanine expansions in PHOX2B, which are responsible for most congenital central hypoventilation syndrome cases. However, polyalanine expansions in PHOX2B additionally promote nascent homorepeat conformations that trigger length-dependent phase transitions into solid condensates that capture wild-type PHOX2B. Remarkably, HSP70 and HSP90 chaperones specifically seize PHOX2B alternative conformations preventing phase transitions. The precise observation of emerging polymorphs in expanded PHOX2B postulates unbalanced phase transitions as distinct pathophysiological mechanisms in homorepeat expansion diseases, paving the way towards the search of therapeutics modulating biomolecular condensates in central hypoventilation syndrome.
Widespread stable noncanonical peptides identified by integrated analyses of ribosome profiling and ORF features
Authors: Yang Haiwang , Li Qianru , Stroup Emily K. , Wang Sheng , Ji Zhe 
Published: March 2024

AbstractStudies have revealed dozens of functional peptides in putative ‘noncoding’ regions and raised the question of how many proteins are encoded by noncanonical open reading frames (ORFs). Here, we comprehensively annotate genome-wide translated ORFs across five eukaryotes (human, mouse, zebrafish, worm, and yeast) by analyzing ribosome profiling data. We develop a logistic regression model named PepScore based on ORF features (expected length, encoded domain, and conservation) to calculate the probability that the encoded peptide is stable in humans. Systematic ectopic expression validates PepScore and shows that stable complex-associating microproteins can be encoded in 5’/3’ untranslated regions and overlapping coding regions of mRNAs besides annotated noncoding RNAs. Stable noncanonical proteins follow conventional rules and localize to different subcellular compartments. Inhibition of proteasomal/lysosomal degradation pathways can stabilize some peptides especially those with moderate PepScores, but cannot rescue the expression of short ones with low PepScores suggesting they are directly degraded by cellular proteases. The majority of human noncanonical peptides with high PepScores show longer lengths but low conservation across species/mammals, and hundreds contain trait-associated genetic variants. Our study presents a statistical framework to identify stable noncanonical peptides in the genome and provides a valuable resource for functional characterization of noncanonical translation during development and disease.
Cross-layer transmission realized by light-emitting memristor for constructing ultra-deep neural network with transfer learning ability
Authors: Chen Zhenjia , Lin Zhenyuan , Yang Ji , Chen Cong , Liu Di , Shan Liuting , Hu Yuanyuan , Guo Tailiang , Chen Huipeng 
Published: March 2024

AbstractDeep neural networks have revolutionized several domains, including autonomous driving, cancer detection, and drug design, and are the foundation for massive artificial intelligence models. However, hardware neural network reports still mainly focus on shallow networks (2 to 5 layers). Implementing deep neural networks in hardware is challenging due to the layer-by-layer structure, resulting in long training times, signal interference, and low accuracy due to gradient explosion/vanishing. Here, we utilize negative ultraviolet photoconductive light-emitting memristors with intrinsic parallelism and hardware-software co-design to achieve electrical information’s optical cross-layer transmission. We propose a hybrid ultra-deep photoelectric neural network and an ultra-deep super-resolution reconstruction neural network using light-emitting memristors and cross-layer block, expanding the networks to 54 and 135 layers, respectively. Further, two networks enable transfer learning, approaching or surpassing software-designed networks in multi-dataset recognition and high-resolution restoration tasks. These proposed strategies show great potential for high-precision multifunctional hardware neural networks and edge artificial intelligence.
Earthquake forecasting from paleoseismic records
Authors: Wang Ting , Griffin Jonathan D. , Brenna Marco , Fletcher David , Zeng Jiaxu , Stirling Mark , Dillingham Peter W. , Kang Jie 
Published: March 2024

AbstractForecasting large earthquakes along active faults is of critical importance for seismic hazard assessment. Statistical models of recurrence intervals based on compilations of paleoseismic data provide a forecasting tool. Here we compare five models and use Bayesian model-averaging to produce time-dependent, probabilistic forecasts of large earthquakes along 93 fault segments worldwide. This approach allows better use of the measurement errors associated with paleoseismic records and accounts for the uncertainty around model choice. Our results indicate that although the majority of fault segments (65/93) in the catalogue favour a single best model, 28 benefit from a model-averaging approach. We provide earthquake rupture probabilities for the next 50 years and forecast the occurrence times of the next rupture for all the fault segments. Our findings suggest that there is no universal model for large earthquake recurrence, and an ensemble forecasting approach is desirable when dealing with paleoseismic records with few data points and large measurement errors.
A structural and dynamic visualization of the interaction between MAP7 and microtubules
Authors: Adler Agnes , Bangera Mamata , Beugelink J. Wouter , Bahri Salima , van Ingen Hugo , Moores Carolyn A. , Baldus Marc 
Published: March 2024

AbstractMicrotubules (MTs) are key components of the eukaryotic cytoskeleton and are essential for intracellular organization, organelle trafficking and mitosis. MT tasks depend on binding and interactions with MT-associated proteins (MAPs). MT-associated protein 7 (MAP7) has the unusual ability of both MT binding and activating kinesin-1-mediated cargo transport along MTs. Additionally, the protein is reported to stabilize MTs with its 112 amino-acid long MT-binding domain (MTBD). Here we investigate the structural basis of the interaction of MAP7 MTBD with the MT lattice. Using a combination of solid and solution-state nuclear magnetic resonance (NMR) spectroscopy with electron microscopy, fluorescence anisotropy and isothermal titration calorimetry, we shed light on the binding mode of MAP7 to MTs at an atomic level. Our results show that a combination of interactions between MAP7 and MT lattice extending beyond a single tubulin dimer and including tubulin C-terminal tails contribute to formation of the MAP7-MT complex.
Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics
Authors: Zhong Zhixing , Hou Junchen , Yao Zhixian , Dong Lei , Liu Feng , Yue Junqiu , Wu Tiantian , Zheng Junhua , Ouyang Gaoliang , Yang Chaoyong , Song Jia 
Published: March 2024

AbstractSingle-cell and spatial transcriptome sequencing, two recently optimized transcriptome sequencing methods, are increasingly used to study cancer and related diseases. Cell annotation, particularly for malignant cell annotation, is essential and crucial for in-depth analyses in these studies. However, current algorithms lack accuracy and generalization, making it difficult to consistently and rapidly infer malignant cells from pan-cancer data. To address this issue, we present Cancer-Finder, a domain generalization-based deep-learning algorithm that can rapidly identify malignant cells in single-cell data with an average accuracy of 95.16%. More importantly, by replacing the single-cell training data with spatial transcriptomic datasets, Cancer-Finder can accurately identify malignant spots on spatial slides. Applying Cancer-Finder to 5 clear cell renal cell carcinoma spatial transcriptomic samples, Cancer-Finder demonstrates a good ability to identify malignant spots and identifies a gene signature consisting of 10 genes that are significantly co-localized and enriched at the tumor-normal interface and have a strong correlation with the prognosis of clear cell renal cell carcinoma patients. In conclusion, Cancer-Finder is an efficient and extensible tool for malignant cell annotation.
A comprehensive dataset of environmentally contaminated sites in the state of São Paulo in Brazil
Authors: Samlani Nouha , Pino Daphne Silva , Bertolo Reginaldo , Pak Tannaz 
Published: March 2024

AbstractIn the Brazilian state of São Paulo, contaminated sites (CSs) constitute threats to health, environment and socioeconomic situation of populations. Over the past two decades, the Environmental Agency of São Paulo (CETESB) has monitored these known CSs. This paper discusses the produced dataset through digitising the CETESB reports and making them accessible to the public in English. The dataset reports on qualitative aspects of contamination within the registered sites (e.g., contamination type and spread) and their management status. The data was extracted from CETESB reports using a machine-learning computer vision algorithm. It comprises two components: an optical character recognition (OCR) engine for text extraction and a convolutional neural network (CNN) image classifier to identify checked boxes. The digitisation was followed by harmonisation and quality assurance processes to ensure the consistency and validity of the data. Making this dataset accessible will allow future work on predictive analysis and decision-making and will inform the required policy-making to improve the management of the CSs in Brazil.
Interactive design generation and optimization from generative adversarial networks in spatial computing
Authors: Hu Xiaochen , Lin Cun , Chen Tianyi , Chen Weibo 
Published: March 2024

AbstractThis paper focuses on exploring the application possibilities and optimization problems of Generative Adversarial Networks (GANs) in spatial computing to improve design efficiency and creativity and achieve a more intelligent design process. A method for icon generation is proposed, and a basic architecture for icon generation is constructed. A system with generation and optimization capabilities is constructed to meet various requirements in spatial design by introducing the concept of interactive design and the characteristics of requirement conditions. Next, the generated icons can effectively maintain diversity and innovation while meeting the conditional features by integrating multi-feature recognition modules into the discriminator and optimizing the structure of conditional features. The experiment uses publicly available icon datasets, including LLD-Icon and Icons-50. The icon shape generated by the model proposed here is more prominent, and the color of colored icons can be more finely controlled. The Inception Score (IS) values under different models are compared, and it is found that the IS value of the proposed model is 7.05, which is higher than that of other GAN models. The multi-feature icon generation model based on Auxiliary Classifier GANs performs well in presenting multiple feature representations of icons. After introducing multi-feature recognition modules into the network model, the peak error of the recognition network is only 2.000 in the initial stage, while the initial error of the ordinary GAN without multi-feature recognition modules is as high as 5.000. It indicates that the improved model effectively helps the discriminative network recognize the core information of icon images more quickly. The research results provide a reference basis for achieving more efficient and innovative interactive space design.
Reduction of NIFTI files storage and compression to facilitate telemedicine services based on quantization hiding of downsampling approach
Authors: Elhadad Ahmed , Jamjoom Mona , Abulkasim Hussein 
Published: March 2024

AbstractMagnetic resonance imaging is a medical imaging technique to create comprehensive images of the tissues and organs in the body. This study presents an advanced approach for storing and compressing neuroimaging informatics technology initiative files, a standard format in magnetic resonance imaging. It is designed to enhance telemedicine services by facilitating efficient and high-quality communication between healthcare practitioners and patients. The proposed downsampling approach begins by opening the neuroimaging informatics technology initiative file as volumetric data and then planning it into several slice images. Then, the quantization hiding technique will be applied to each of the two consecutive slice images to generate the stego slice with the same size. This involves the following major steps: normalization, microblock generation, and discrete cosine transformation. Finally, it assembles the resultant stego slice images to produce the final neuroimaging informatics technology initiative file as volumetric data. The upsampling process, designed to be completely blind, reverses the downsampling steps to reconstruct the subsequent image slice accurately. The efficacy of the proposed method was evaluated using a magnetic resonance imaging dataset, focusing on peak signal-to-noise ratio, signal-to-noise ratio, structural similarity index, and Entropy as key performance metrics. The results demonstrate that the proposed approach not only significantly reduces file sizes but also maintains high image quality.
Copper oxides supported sulfur-doped porous carbon material as a remarkable catalyst for reduction of aromatic nitro compounds
Authors: Amirjan Marzie , Nemati Firouzeh , Elahimehr Zeinab , Rangraz Yalda 
Published: March 2024

AbstractSynthesis and manufacturing of metal–organic framework derived carbon/metal oxide nanomaterials with an advisable porous structure and composition are essential as catalysts in various organic transformation processes for the preparation of environmentally friendly catalysts. In this work, we report a scalable synthesis of sulfur-doped porous carbon-containing copper oxide nanoparticles (marked CuxO@CS-400) via direct pyrolysis of a mixture of metal–organic framework precursor called HKUST-1 and diphenyl disulfide for aromatic nitro compounds reduction. X-ray diffraction, surface area analysis (BET), X-ray energy diffraction (EDX) spectroscopy, thermal gravimetric analysis, elemental mapping, infrared spectroscopy (FT-IR), transmission electron microscope, and scanning electron microscope (FE-SEM) analysis were accomplished to acknowledge and investigate the effect of S and CuxO as active sites in heterogeneous catalyst to perform the reduction-nitro aromatic compounds reaction in the presence of CuxO@CS-400 as an effective heterogeneous catalyst. The studies showed that doping sulfur in the resulting carbon/metal oxide substrate increased the catalytic activity compared to the material without sulfur doping.
Numerical flow experiment for assessing predictors for cerebrovascular accidents in patients with PHACES syndrome
Authors: Wiśniewski Karol , Tyfa Zbigniew , Reorowicz Piotr , Brandel Michael G. , Adel Thomas , Obidowski Damian , Jóźwik Krzysztof , Levy Michael L. 
Published: March 2024

AbstractThere is an increased risk of cerebrovascular accidents (CVA) in individuals with PHACES, yet the precise causes are not well understood. In this analysis, we aimed to examine the role of arteriopathy in PHACES syndrome as a potential contributor to CVA. We analyzed clinical and radiological data from 282 patients with suspected PHACES syndrome. We analyzed clinical features, including the presence of infantile hemangioma and radiological features based on magnetic resonance angiography or computed tomography angiography, in individuals with PHACES syndrome according to the Garzon criteria. To analyze intravascular blood flow, we conducted a simulation based on the Fluid–Structure Interaction (FSI) method, utilizing radiological data. The collected data underwent statistical analysis. Twenty patients with PHACES syndrome were included. CVAs were noted in 6 cases. Hypoplasia (p = 0.03), severe tortuosity (p < 0.01), absence of at least one main cerebral artery (p < 0.01), and presence of persistent arteries (p = 0.01) were associated with CVAs, with severe tortuosity being the strongest predictor. The in-silico analysis showed that the combination of hypoplasia and severe tortuosity resulted in a strongly thrombogenic environment. Severe tortuosity, combined with hypoplasia, is sufficient to create a hemodynamic environment conducive to thrombus formation and should be considered high-risk for cerebrovascular accidents (CVAs) in PHACES patients.
Physician marriage survey reveals sex and specialty differences in marital satisfaction factors
Authors: Dutta Rajeev R. , Wu Anthony T. , Picton Bryce , Shah Saloni , Chernyak Michelle , Bauer Kelly , Solomon Sean , Chang Josephine , Nguyen Britney , Jiang Mio , Hurria Anju 
Published: March 2024

AbstractPhysician marriage is a valuable indicator of how vocational factors (e.g. work hours, stressors) impact satisfaction in relationships and physician wellness overall. Previous studies suggest that gender and specialty influence marriage satisfaction for physicians, though these often come from limited, local, cohorts. A cross-sectional survey was designed and distributed to publicly available email addresses representing academic and private practice physician organizations across the United States, receiving 321 responses (253 complete). Responses included data on demographics, medical specialty, age at marriage, stage of training at marriage, number of children, and factors leading to marital satisfaction/distress. A multivariable ordinal logistic regression was conducted to find associations between survey variables and marriage satisfaction. Survey results indicated that 86.5% of physicians have been married (average age at first marriage was 27.8 years old), and the rate of first marriages ending is at least 14.7%. Men had significantly more children than women. Physicians married at least once averaged 1.98 children. “Other” specialty physicians had significantly more children on average than psychiatrists. Marrying before medical school predicted practicing in private practice settings. Job stress, work hours, children, and sex were most frequently sources of marital distress, while strong communication, finances, and children were most frequently sources of marital stability. Sex differences were also found in distressing and stabilizing marital factors: Female physicians were more likely to cite their spouse’s work hours and job stress as sources of marital distress. Finally, surgery specialty and Judaism were associated with higher marriage satisfaction, whereas possession of an M.D. degree was associated with lower marriage satisfaction. This study elucidated new perspectives on physician marriage and families based on specialty, practice setting, and stage of training at marriage. Future studies may focus on factors mediating specialty and sex’s impact on having children and marriage satisfaction. To our knowledge, this study is the first physician marriage survey which integrates multiple factors in the analysis of physician marriages.
Optimizing lifestyle profiles is potential for preventing nonalcoholic fatty liver disease and enhancing its survival
Authors: Tu Beilin , Li Wei , Xiao Haitao , Xu Xuewen , Zhang Yange 
Published: March 2024

AbstractThe aim of this study was to evaluate the association between lifestyle profile and disease incidence/mortality in patients with non-alcoholic fatty liver disease (NAFLD). Lifestyle profiles ascertainment was based on the latent profile analysis. The associations of lifestyle profile and outcomes were analyzed by multivariate logistic or Cox regressions. Four lifestyle profiles (profile 1 and 2 for male, profile 3 and 4 for female) were established for all participants. Compared to profile 1, profile 2 (P = 0.042) and profile 3 (P = 0.013) had lower incidence for NAFLD. In contrast, profile 4 showed similar NAFLD prevalence compared to profile 1 (P = 0.756). Individuals with NAFLD within profile 3 had the best long-term survival, and the HR was 0.55 (95% CI 0.40–0.76) for all-cause mortality (compared to profile 1). Profile 4 (P = 0.098) and profile 2 (P = 0.546) had similar all-cause survival compared to profile 1. We explored the associations of healthy lifestyle score with mortality and incidence of NAFLD stratified by lifestyle profiles. We observed that with the increase of healthy lifestyle score, participants within profile 2 did not display lower NAFLD incidence and better long-term survival in NAFLD cases. In this study, lifestyle profiles were constructed in NHANES participants. The distinct lifestyle profiles may help optimize decision-making regarding lifestyle management in preventing NAFLD development, as well as selection of a more personalized approach for improving NAFLD survival.