bluuebunny/crossref_metadata_2025_split huggingface dataset:
An unusual tandem kinase fusion protein confers leaf rust resistance in wheat
Authors: Wang Yajun , Abrouk Michael , Gourdoupis Spyridon , Koo Dal-Hoe , Karafiátová Miroslava , Molnár István , Holušová Kateřina , Doležel Jaroslav , Athiyannan Naveenkumar , Cavalet-Giorsa Emile , Jaremko Łukasz , Poland Jesse , Krattinger Simon G. 
Published: May 2023

AbstractThe introgression of chromosome segments from wild relatives is an established strategy to enrich crop germplasm with disease-resistance genes1. Here we use mutagenesis and transcriptome sequencing to clone the leaf rust resistance gene Lr9, which was introduced into bread wheat from the wild grass species Aegilops umbellulata2. We established that Lr9 encodes an unusual tandem kinase fusion protein. Long-read sequencing of a wheat Lr9 introgression line and the putative Ae. umbellulata Lr9 donor enabled us to assemble the ~28.4-Mb Lr9 translocation and to identify the translocation breakpoint. We likewise cloned Lr58, which was reportedly introgressed from Aegilopstriuncialis3, but has an identical coding sequence compared to Lr9. Cytogenetic and haplotype analyses corroborate that the two genes originate from the same translocation event. Our work sheds light on the emerging role of kinase fusion proteins in wheat disease resistance, expanding the repertoire of disease-resistance genes for breeding.
Fertilization altered co-occurrence patterns and microbial assembly process of ammonia-oxidizing microorganisms
Authors: Ma Mingchao , Zhao Yubin , Jiang Xin , Guan Dawei , Yuan Ming , Cao Fengming , Li Li , Zhou Jing , Ding Jianli , Li Jun 
Published: May 2023

AbstractAmmonia-oxidizing archaea and bacteria (AOA and AOB, respectively) are important intermediate links in the nitrogen cycle. Apart from the AOA and AOB communities in soil, we further investigated co-occurrence patterns and microbial assembly processes subjected to inorganic and organic fertilizer treatments for over 35 years. The amoA copy numbers and AOA and AOB communities were found to be similar for the CK and organic fertilizer treatments. Inorganic fertilizers decreased the AOA gene copy numbers by 0.75–0.93-fold and increased the AOB gene copy numbers by 1.89–3.32-fold compared to those of the CK treatment. The inorganic fertilizer increased Nitrososphaera and Nitrosospira. The predominant bacteria in organic fertilizer was Nitrosomonadales. Furthermore, the inorganic fertilizer increased the complexity of the co-occurrence pattern of AOA and decreased the complexity pattern of AOB comparing with organic fertilizer. Different fertilizer had an insignificant effect on the microbial assembly process of AOA. However, great difference exists in the AOB community assembly process: deterministic process dominated in organic fertilizer treatment and stochastic processes dominated in inorganic fertilizer treatment, respectively. Redundancy analysis indicated that the soil pH, NO3−N, and available phosphorus contents were the main factors affecting the changes in the AOA and AOB communities. Overall, this findings expanded our knowledge concerning AOA and AOB, and ammonia‐oxidizing microorganisms were more disturbed by inorganic fertilizers than organic fertilizers.
Hybrid quantum-classical machine learning for generative chemistry and drug design
Authors: Gircha A. I. , Boev A. S. , Avchaciov K. , Fedichev P. O. , Fedorov A. K. 
Published: May 2023

AbstractDeep generative chemistry models emerge as powerful tools to expedite drug discovery. However, the immense size and complexity of the structural space of all possible drug-like molecules pose significant obstacles, which could be overcome with hybrid architectures combining quantum computers with deep classical networks. As the first step toward this goal, we built a compact discrete variational autoencoder (DVAE) with a Restricted Boltzmann Machine (RBM) of reduced size in its latent layer. The size of the proposed model was small enough to fit on a state-of-the-art D-Wave quantum annealer and allowed training on a subset of the ChEMBL dataset of biologically active compounds. Finally, we generated 2331 novel chemical structures with medicinal chemistry and synthetic accessibility properties in the ranges typical for molecules from ChEMBL. The presented results demonstrate the feasibility of using already existing or soon-to-be-available quantum computing devices as testbeds for future drug discovery applications.
GPU accelerated digital twins of the human heart open new routes for cardiovascular research
Authors: Viola Francesco , Del Corso Giulio , De Paulis Ruggero , Verzicco Roberto 
Published: May 2023

AbstractThe recruitment of patients for rare or complex cardiovascular diseases is a bottleneck for clinical trials and digital twins of the human heart have recently been proposed as a viable alternative. In this paper we present an unprecedented cardiovascular computer model which, relying on the latest GPU-acceleration technologies, replicates the full multi-physics dynamics of the human heart within a few hours per heartbeat. This opens the way to extensive simulation campaigns to study the response of synthetic cohorts of patients to cardiovascular disorders, novel prosthetic devices or surgical procedures. As a proof-of-concept we show the results obtained for left bundle branch block disorder and the subsequent cardiac resynchronization obtained by pacemaker implantation. The in-silico results closely match those obtained in clinical practice, confirming the reliability of the method. This innovative approach makes possible a systematic use of digital twins in cardiovascular research, thus reducing the need of real patients with their economical and ethical implications. This study is a major step towards in-silico clinical trials in the era of digital medicine.
Adaptive fuzzy sliding mode control of an actuator powered by two opposing pneumatic artificial muscles
Authors: Duong Minh-Duc , Pham Quang-Thuyet , Vu Tuan-Chien , BUI Ngoc-Tam , Dao Quy-Thinh 
Published: May 2023

AbstractPneumatic artificial muscle (PAM) is a potential actuator in human–robot interaction systems, especially rehabilitation systems. However, PAM is a nonlinear actuator with uncertainty and a considerable delay in characteristics, making control challenging. This study presents a discrete-time sliding mode control approach combined with the adaptive fuzzy algorithm (AFSMC) to deal with the unknown disturbance of the PAM-based actuator. The developed fuzzy logic system has parameter vectors of the component rules that are automatically updated by an adaptive law. Consequently, the developed fuzzy logic system can reasonably approximate the system disturbance. When operating the PAM-based system in multi-scenario studies, experimental results confirm the efficiency of the proposed strategy.
Unlocking multidimensional cancer therapeutics using geometric data science
Authors: Parashar Deepak 
Published: May 2023

AbstractPersonalised approaches to cancer therapeutics primarily involve identification of patient sub-populations most likely to benefit from targeted drugs. Such a stratification has led to plethora of designs of clinical trials that are often too complex due to the need for incorporating biomarkers and tissue types. Many statistical methods have been developed to address these issues; however, by the time such methodology is available research in cancer has moved on to new challenges and therefore in order to avoid playing catch-up it is necessary to develop new analytic tools alongside. One of the challenges facing cancer therapy is to effectively and appropriately target multiple therapies for sensitive patient population based on a panel of biomarkers across multiple cancer types, and matched future trial designs. We present novel geometric methods (mathematical theory of hypersurfaces) to visualise complex cancer therapeutics data as multidimensional, as well as geometric representation of oncology trial design space in higher dimensions. The hypersurfaces are used to describe master protocols, with application to a specific example of a basket trial design for melanoma, and thus setup a framework for further incorporating multi-omics data as multidimensional therapeutics.
Intra-group competition and social dynamics regarding dispersal and maturation in wild Javan gibbon (Hylobates moloch)
Authors: Choi Ahyun , Yi Yoonjung , Mardiastuti Ani , Choe Jae C. 
Published: May 2023

AbstractNatal dispersal is an important life-history trait in all animal taxa. In pair-living species, parent–offspring competition derived from the offspring’s maturity can motivate the natal dispersal of offspring. However, not much has been known about the dispersal mechanisms of pair-living gibbons. To test food and mate competition as potential reasons for dispersal, we investigated the effect of the offspring age and sex on relationships between parents and offspring in wild Javan gibbon (Hylobates moloch) in Gunung Halimun-Salak National Park, Indonesia. We collected behavioral data for two years between 2016 and 2019. We found that aggression from parents toward offspring increased in both feeding and non-feeding context as the offspring got older. Offspring received more aggression from the parent of the same sex in the general context. While offspring decreased co-feeding and grooming time with parents as they got older, there was no change in the proximity and approach to parents. The results imply the presence of both intra-group food and mate competition which increase with the offspring’s age. We highlight that increased competition between maturing offspring and parents changes their social relationships and peripheralizes offspring from the natal group which will eventually motivate offspring to disperse in Javan gibbons.
Using remotely monitored patient activity patterns after hospital discharge to predict 30 day hospital readmission: a randomized trial
Authors: Patel Mitesh S. , Volpp Kevin G. , Small Dylan S. , Kanter Genevieve P. , Park Sae-Hwan , Evans Chalanda N. , Polsky Daniel 
Published: May 2023

AbstractHospital readmission prediction models often perform poorly, but most only use information collected until the time of hospital discharge. In this clinical trial, we randomly assigned 500 patients discharged from hospital to home to use either a smartphone or wearable device to collect and transmit remote patient monitoring (RPM) data on activity patterns after hospital discharge. Analyses were conducted at the patient-day level using discrete-time survival analysis. Each arm was split into training and testing folds. The training set used fivefold cross-validation and then final model results are from predictions on the test set. A standard model comprised data collected up to the time of discharge including demographics, comorbidities, hospital length of stay, and vitals prior to discharge. An enhanced model consisted of the standard model plus RPM data. Traditional parametric regression models (logit and lasso) were compared to nonparametric machine learning approaches (random forest, gradient boosting, and ensemble). The main outcome was hospital readmission or death within 30 days of discharge. Prediction of 30-day hospital readmission significantly improved when including remotely-monitored patient data on activity patterns after hospital discharge and using nonparametric machine learning approaches. Wearables slightly outperformed smartphones but both had good prediction of 30-day hospital-readmission.
The first-trimester serum high-temperature requirement protease A4 and uterine artery Doppler for the prediction of preeclampsia
Authors: Siricharoenthai Patcharaporn , Phupong Vorapong 
Published: May 2023

AbstractThe objective of this study was to investigate the predictive value of serum high-temperature requirement protease A4 (HtrA4) and the first-trimester uterine artery in predicting preeclampsia in singleton pregnancy. Pregnant women at gestational age 11–13+6 weeks, who visited the antenatal clinic at King Chulalongkorn Memorial Hospital, Department of Obstetrics and Gynecology, Faculty of Medicine, Chulalongkorn University during April 2020–July 2021 were included. Serum HtrA4 levels and transabdominal uterine artery Doppler ultrasound were performed to evaluate this combination for calculating the predictive value of preeclampsia. While 371 singleton pregnant women enrolled in this study, 366 completed it. Thirty-four (9.3%) women had preeclampsia. Mean serum HtrA4 levels were higher in the preeclampsia group than in the control group (9.4 ± 3.9 vs 4.6 ± 2.2 ng/ml, p < 0.001). The mean uterine artery pulsatility index (UtA-PI) was higher in the group with early onset preeclampsia than in the control group (2.3 ± 0.5 vs 1.7 ± 0.5, p = 0.002). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 76.5%, 90.7%, 45.6%, and 97.4%, respectively, when using serum HtrA4 levels above 1.8 multiples of the median for the gestational age as a cut-off value for predicting preeclampsia. A combination of serum HtrA4 levels and UtA-PI > 95th percentile yielded sensitivity, specificity, PPV, and NPV of 79.4%, 86.1%, 37% and 97.6%, respectively, for the prediction of preeclampsia. A combination of serum HtrA4 levels and uterine artery Doppler in the first trimester had good sensitivity for predicting preeclampsia.
Deep learning to detect macular atrophy in wet age-related macular degeneration using optical coherence tomography
Authors: Wei Wei , Southern Joshua , Zhu Kexuan , Li Yefeng , Cordeiro Maria Francesca , Veselkov Kirill 
Published: May 2023

AbstractHere, we have developed a deep learning method to fully automatically detect and quantify six main clinically relevant atrophic features associated with macular atrophy (MA) using optical coherence tomography (OCT) analysis of patients with wet age-related macular degeneration (AMD). The development of MA in patients with AMD results in irreversible blindness, and there is currently no effective method of early diagnosis of this condition, despite the recent development of unique treatments. Using OCT dataset of a total of 2211 B-scans from 45 volumetric scans of 8 patients, a convolutional neural network using one-against-all strategy was trained to present all six atrophic features followed by a validation to evaluate the performance of the models. The model predictive performance has achieved a mean dice similarity coefficient score of 0.706 ± 0.039, a mean Precision score of 0.834 ± 0.048, and a mean Sensitivity score of 0.615 ± 0.051. These results show the unique potential of using artificially intelligence-aided methods for early detection and identification of the progression of MA in wet AMD, which can further support and assist clinical decisions.
Research on the spatial correlation and formation mechanism between traditional villages and rural tourism
Authors: Li ZiYang , Yang MeiYu , Zhou XianLan , Li ZhiGang , Li HaiDong , Zhai FeiFei , Zhang Yan , Zhang YunXing 
Published: May 2023

AbstractIn recent years, the survival and development of traditional villages in China have been serious challenges. Rural tourism is regarded as an important way to solve rural problems, and the combination of rural culture and tourism has become a new power point for rural development. Therefore, it is necessary to explore the spatial distribution structure between traditional villages and rural tourism. In this paper, rural tourism was represented by the rural tourism characteristic village (RTCV), and Henan Province, China, was taken as a study area to analyze the distribution pattern and spatial correlation of rural tourism and traditional village (TV) and discuss the relationship between the spatial correlation and regional natural environment and socioeconomic factors. The results show that the coupling of the spatial correlation between RTCVs and TVs in Henan was clear. They could be divided into 5 regions based on geographical factors. In addition, the research summarized 4 typical spatial structures between TVs and RTCVs in Henan based on the regional symbiosis theory, and the spatial pattern formation mechanism of TVs and RTCVs was discussed based on three driving mechanisms. The spatial structure of the two can provide reference value for other developing countries and regions to achieve sustainable rural development.
Synthesis of N-Phenylcarbamate by C–N Coupling Reaction without Metal Participation
Authors: Ablajan Keyume , Ji Long 
Published: May 2023

AbstractWe have developed a new method for the synthesis of carbamates from amine and hydrazine formate. The reaction occurs in the presence of iodine and tert-butyl hydroperoxide, in which carbazates are produced via alkoxycarbonyl radical formation for cross-coupling reaction. The method exhibits broad functional group tolerance and affords a series of N-phenylcarbamates in moderate to good yields. Remarkably, our approach is metal free and utilizes cheap, readily available raw materials and relatively universal substrates.
Spectral and Electrochemical Properties of Common Photocatalysts in Water: A Compendium for Aqueous Photoredox Catalysis
Authors: Gary Samuel , Landry Melinda , Bloom Steven 
Published: May 2023

AbstractElectrochemical potentials of photocatalysts are solvent dependent. One of the largest discrepancies is observed when water is used in place of organic solvents as the reaction media. Unfortunately, the redox potentials for many photocatalysts in water have not been determined, at least under one unifying set of conditions, and this greatly hinders the rational design of sustainable and biocompatible photoredox reactions. Herein, we measure the spectral and electrochemical properties of the most common photoredox catalysts in water and catalog their absorption and fluorescence maxima and ground- and excited-state potentials.
Early Postpartum Hospital Encounters among Patients with Genitourinary and Wound Infections during Hospitalization for Birth
Authors: Leonard Stephanie A. , Girsen Anna I. , Trepman Paula , Carmichael Suzan L. , Darmawan Kelly , Butwick Alexander J. , Gibbs Ronald S. 
Published: May 2023

Objectives This study aimed to assess the associations between genitourinary and wound infections during the birth hospitalization and early postpartum hospital encounters, and to evaluate clinical risk factors for early postpartum hospital encounters among patients with genitourinary and wound infections during the birth hospitalization.
Study Design We conducted a population-based cohort study of births in California during 2016 to 2018 and postpartum hospital encounters. We identified genitourinary and wound infections using diagnosis codes. Our main outcome was early postpartum hospital encounter, defined as a readmission or emergency department (ED) visit within 3 days after discharge from the birth hospitalization. We evaluated the association of genitourinary and wound infections (overall and subtypes) with early postpartum hospital encounter using logistic regression, adjusting for sociodemographic factors and comorbidities and stratified by mode of birth. We then evaluated factors associated with early postpartum hospital encounter among patients with genitourinary and wound infections.
Results Among 1,217,803 birth hospitalizations, 5.5% were complicated by genitourinary and wound infections. Genitourinary or wound infection was associated with an early postpartum hospital encounter among patients with both vaginal births (2.2%; adjusted risk ratio [aRR[: 1.26; 95% confidence interval [CI]: 1.17–1.36) and cesarean births (3.2%; aRR: 1.23; 95% CI: 1.15–1.32). Patients with a cesarean birth and a major puerperal infection or wound infection had the highest risk of an early postpartum hospital encounter (6.4 and 4.3%, respectively). Among patients with genitourinary and wound infections during the birth hospitalization, factors associated with an early postpartum hospital encounter included severe maternal morbidity, major mental health condition, prolonged postpartum hospital stay, and, among cesarean births, postpartum hemorrhage (p-value < 0.05).
Conclusion Genitourinary and wound infections during hospitalization for birth may increase risk of a readmission or ED visit within the first few days after discharge, particularly among patients who have a cesarean birth and a major puerperal infection or wound infection.
Key Points
Application and realization of Norland optical adhesive 73 novel photosensitive macromolecular material for the rapid preparation of periodically tunable nanoscale gratings
Authors: Nan Xueli , Wang Xin , Zhang Jiale , Kang Tongtong , Dong Lanxiao , Duan Qikai , Dong Jinfeng , Cao Xinxin , Xu Zhikuan , Qin Bolin , Jia Qikun , Hao Jinjin , Mei Shixuan 
Published: May 2023

Periodically tunable nano-gratings have an irreplaceable role in spectral scanning and optical communication, but the performance of gratings manufactured from different materials varies considerably, and the development of superior materials has energized the preparation of high-precision devices. This paper presents a nanoscale preparation process based on Norland Optical Adhesive 73 (NOA73), which enables the rapid preparation of periodically tunable nano-gratings with up to 100% light transmission. The powerful fluidity and shear rate of NOA73 make it uniquely suited to the preparation of precision devices, allowing the production of up to dense grating structures and offering the possibility of making nanoscale gratings. This paper uses multi-angle hierarchical lithography, die stretching, and replication to achieve further improvements in accuracy and successfully prepare gratings with a period of 500 nm. The successful preparation of NOA73 nano-gratings demonstrates the practicality of NOA73 as a material for precision device fabrication.
Cryo-EM structure of the Mon1–Ccz1–RMC1 complex reveals molecular basis of metazoan RAB7A activation
Authors: Yong Xin , Jia Guowen , Liu Zhe , Zhou Chunzhuang , Yi Jiamin , Tang Yingying , Chen Li , Chen Lu , Wang Yuan , Sun Qingxiang , Billadeau Daniel D. , Su Zhaoming , Jia Da 
Published: May 2023

Understanding of the evolution of metazoans from their unicellular ancestors is a fundamental question in biology. In contrast to fungi which utilize the Mon1–Ccz1 dimeric complex to activate the small GTPase RAB7A, metazoans rely on the Mon1–Ccz1–RMC1 trimeric complex. Here, we report a near-atomic resolution cryogenic-electron microscopy structure of the
Drosophila
Mon1–Ccz1–RMC1 complex. RMC1 acts as a scaffolding subunit and binds to both Mon1 and Ccz1 on the surface opposite to the RAB7A-binding site, with many of the RMC1-contacting residues from Mon1 and Ccz1 unique to metazoans, explaining the binding specificity. Significantly, the assembly of RMC1 with Mon1–Ccz1 is required for cellular RAB7A activation, autophagic functions and organismal development in zebrafish. Our studies offer a molecular explanation for the different degree of subunit conservation across species, and provide an excellent example of how metazoan-specific proteins take over existing functions in unicellular organisms.