bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lilac (Syringa oblata) genome provides insights into its evolution and molecular mechanism of petal color change
Authors: Ma Bo , Wu Jing , Shi Tian-Le , Yang Yun-Yao , Wang Wen-Bo , Zheng Yi , Su Shu-Chai , Yao Yun-Cong , Xue Wen-Bo , Porth Ilga , El-Kassaby Yousry A. , Leng Ping-Sheng , Hu Zeng-Hui , Mao Jian-Feng 
Published: July 2022

AbstractColor change during flower opening is common; however, little is understood on the biochemical and molecular basis related. Lilac (Syringa oblata), a well-known woody ornamental plant with obvious petal color changes, is an ideal model. Here, we presented chromosome-scale genome assembly for lilac, resolved the flavonoids metabolism, and identified key genes and potential regulatory networks related to petal color change. The genome assembly is 1.05 Gb anchored onto 23 chromosomes, with a BUSCO score of 96.6%. Whole-genome duplication (WGD) event shared within Oleaceae was revealed. Metabolome quantification identified delphinidin-3-O-rutinoside (Dp3Ru) and cyanidin-3-O-rutinoside (Cy3Ru) as the major pigments; gene co-expression networks indicated WRKY an essential regulation factor at the early flowering stage, ERF more important in the color transition period (from violet to light nearly white), while the MBW complex participated in the entire process. Our results provide a foundation for functional study and molecular breeding in lilac.
Iron limitation in M. tuberculosis has broad impact on central carbon metabolism
Authors: Theriault Monique E. , Pisu Davide , Wilburn Kaley M. , Lê-Bury Gabrielle , MacNamara Case W. , Michael Petrassi H. , Love Melissa , Rock Jeremy M. , VanderVen Brian C. , Russell David G. 
Published: July 2022

AbstractMycobacterium tuberculosis (Mtb), the cause of the human pulmonary disease tuberculosis (TB), contributes to approximately 1.5 million deaths every year. Prior work has established that lipids are actively catabolized by Mtb in vivo and fulfill major roles in Mtb physiology and pathogenesis. We conducted a high-throughput screen to identify inhibitors of Mtb survival in its host macrophage. One of the hit compounds identified in this screen, sAEL057, demonstrates highest activity on Mtb growth in conditions where cholesterol was the primary carbon source. Transcriptional and functional data indicate that sAEL057 limits Mtb’s access to iron by acting as an iron chelator. Furthermore, pharmacological and genetic inhibition of iron acquisition results in dysregulation of cholesterol catabolism, revealing a previously unappreciated linkage between these pathways. Characterization of sAEL057’s mode of action argues that Mtb’s metabolic regulation reveals vulnerabilities in those pathways that impact central carbon metabolism.
Shell thickness of Nucella lapillus in the North Sea increased over the last 130 years despite ocean acidification
Authors: Mayk Dennis , Peck Lloyd S. , Backeljau Thierry , Harper Elizabeth M. 
Published: July 2022

AbstractOcean acidification and global climate change are predicted to negatively impact marine calcifiers, with species inhabiting the intertidal zone being especially vulnerable. Current predictions of organism responses to projected changes are largely based on relatively short to medium term experiments over periods of a few days to a few years. Here we look at responses over a longer time span and present a 130-year shell shape and shell thickness record from archival museum collections of the marine intertidal predatory gastropodNucella lapillus. We used multivariate ecological models to identify significant morphological trends through time and along environmental gradients and show that, contrary to global predictions, localN. lapilluspopulations built continuously thicker shells while maintaining a consistent shell shape throughout the last century.
Diminished carbon and nitrate assimilation drive changes in diatom elemental stoichiometry independent of silicification in an iron-limited assemblage
Authors: Maniscalco Michael A , Brzezinski Mark A , Lampe Robert H , Cohen Natalie R , McNair Heather M , Ellis Kelsey A , Brown Matthew , Till Claire P , Twining Benjamin S , Bruland Kenneth W , Marchetti Adrian , Thamatrakoln Kimberlee 
Published: July 2022

AbstractIn the California Current Ecosystem, upwelled water low in dissolved iron (Fe) can limit phytoplankton growth, altering the elemental stoichiometry of the particulate matter and dissolved macronutrients. Iron-limited diatoms can increase biogenic silica (bSi) content &gt;2-fold relative to that of particulate organic carbon (C) and nitrogen (N), which has implications for carbon export efficiency given the ballasted nature of the silica-based diatom cell wall. Understanding the molecular and physiological drivers of this altered cellular stoichiometry would foster a predictive understanding of how low Fe affects diatom carbon export. In an artificial upwelling experiment, water from 96 m depth was incubated shipboard and left untreated or amended with dissolved Fe or the Fe-binding siderophore desferrioxamine-B (+DFB) to induce Fe-limitation. After 120 h, diatoms dominated the communities in all treatments and displayed hallmark signatures of Fe-limitation in the +DFB treatment, including elevated particulate Si:C and Si:N ratios. Single-cell, taxon-resolved measurements revealed no increase in bSi content during Fe-limitation despite higher transcript abundance of silicon transporters and silicanin-1. Based on these findings we posit that the observed increase in bSi relative to C and N was primarily due to reductions in C fixation and N assimilation, driven by lower transcript expression of key Fe-dependent genes.
Comparative analyses of eighteen rapid antigen tests and RT-PCR for COVID-19 quarantine and surveillance-based isolation
Authors: Wells Chad R. , Pandey Abhishek , Moghadas Seyed M. , Singer Burton H. , Krieger Gary , Heron Richard J. L. , Turner David E. , Abshire Justin P. , Phillips Kimberly M. , Michael Donoghue A. , Galvani Alison P. , Townsend Jeffrey P. 
Published: July 2022

Abstract
Background
Rapid antigen (RA) tests are being increasingly employed to detect SARS-CoV-2 infections in quarantine and surveillance. Prior research has focused on RT-PCR testing, a single RA test, or generic diagnostic characteristics of RA tests in assessing testing strategies.

Methods
We have conducted a comparative analysis of the post-quarantine transmission, the effective reproduction number during serial testing, and the false-positive rates for 18 RA tests with emergency use authorization from The United States Food and Drug Administration and an RT-PCR test. To quantify the extent of transmission, we developed an analytical mathematical framework informed by COVID-19 infectiousness, test specificity, and temporal diagnostic sensitivity data.

Results
We demonstrate that the relative effectiveness of RA tests and RT-PCR testing in reducing post-quarantine transmission depends on the quarantine duration and the turnaround time of testing results. For quarantines of two days or shorter, conducting a RA test on exit from quarantine reduces onward transmission more than a single RT-PCR test (with a 24-h delay) conducted upon exit. Applied to a complementary approach of performing serial testing at a specified frequency paired with isolation of positives, we have shown that RA tests outperform RT-PCR with a 24-h delay. The results from our modeling framework are consistent with quarantine and serial testing data collected from a remote industry setting.

Conclusions
These RA test-specific results are an important component of the tool set for policy decision-making, and demonstrate that judicious selection of an appropriate RA test can supply a viable alternative to RT-PCR in efforts to control the spread of disease.
Lumped and distributed‐parameter pipe model framework for thermal transients: State‐space and transfer function theory and application to multi‐energy systems
Authors: Liu Xiu , Strunz Kai 
Published: July 2022

AbstractThe accurate prediction and simulation of thermal transients in district heating networks is essential for the meaningful analysis of combined heat and power systems. For this purpose, the focus of this paper lies on the development of a consistent and comprehensive modelling framework that links diverse pipe model categories to specific applications where flows are driven by forced convection. The framework considers pipe modelling based on lumped and distributed parameters. Related state‐space and transfer function representations are formulated, and model performances are validated. The comparative analysis of the distributed‐parameter versus the lumped‐parameter categories is shown to be insightful. For the latter category, thermal transients in the form of changing temperature distributions may be observed along the spatial extension of the pipe. In the distributed‐parameter pipe model, only the input and output temperatures are presented. On the other hand, the distributed‐parameter pipe model offers higher computational efficiency. This is confirmed by the equivalent floating‐point operation (eFLOP) count that is newly introduced to quantify the integer multiple of computation time needed for a mathematical operation with respect to the time needed for an elementary addition. The application of the models is illustrated for a combined heat and power network involving diverse transients.
Artificial intelligence technology in electronic communication engineering for medical applications
Authors: Lin Youwen , Zhang Zhijie , Jagota Vishal , Rakhra Manik , Singh Bhupesh Kumar 
Published: July 2022

AbstractIn order to solve the problem of high frame error rate in electronic communication engineering, the application of artificial intelligence technology in electronic communication engineering is proposed. Taking LPWAN technology in artificial intelligence technology as an example, a new architecture is proposed to improve the security of wireless communication system of internet of things. The architecture is mainly composed of business layer, data processing layer, terminal access layer and communication technology layer. The experimental results show that the system configuration sends four kinds of information transmission instructions of “temperature, light, air pressure and humidity” every 30 s, and the receiving port collects the above command data continuously for 4 h, compared with the traditional architecture (15.6%), and the packet loss rate is 4%, which can effectively improve the throughput and processing efficiency of the system. The designed architecture runs stably, has low bit error rate, and can better support the wireless communication. It is proved that the new architecture with LPWAN technology as an example has large overall capacity and excellent performance of its electronic communication engineering interface. The frame number error rate is greatly reduced and the result of signal frame number is more accurate.
Host diversity positively affects the temporal stability of foliar fungal diseases in a Tibetan alpine meadow
Authors: Liu Xiang , Lu Yawen , Huang Mengjiao , Zhou Shurong 
Published: July 2022

Abstract

Background and Aims
Plant disease can dramatically affect population dynamics, community composition and ecosystem functions. However, most empirical studies focus on diseases at a certain time point and largely ignore their temporal stability, which directly affects our ability to predict when and where disease outbreaks will occur.

Methods
Using a removal experiment that manipulates plant diversity (i.e. a plant biodiversity and ecosystem function experiment) and a fertilization experiment in a Tibetan alpine meadow, we investigated how different plant biodiversity indices and nitrogen fertilization affect the temporal stability of foliar fungal diseases (measured as the mean value of community pathogen load divided by its standard deviation) over seven consecutive years.

Key Results
We found that the temporal stability of foliar fungal diseases increased with plant diversity indices in the plant biodiversity and ecosystem function experiment. Meanwhile, we observed a weakly positive relationship between host diversity and temporal stability in the fertilization experiment. However, the nitrogen treatment did not affect temporal stability, given that fertilization increased both the mean and standard deviation of pathogen load by roughly the same magnitude.

Conclusions
We conclude that host diversity regulates the temporal stability of pathogen load, but we note that this effect may be attenuated under rapid biodiversity loss in the Anthropocene.
Nonverbal Neurocognitive Assessment during the Coronavirus Disease of 2019 Pandemic: the Effect of Personal Protective Equipment
Authors: Lichtenstein Jonathan , Niemczak Christopher , Bowers Caitlin , Magohe Albert , Fellows Abigail , Ealer Christin , Massawe Enica , Moshi Ndeserua , Buckey Jay 
Published: July 2022

Abstract

Objective
The coronavirus disease of 2019 pandemic has increased personal protective equipment (PPE) use in medical settings. The current study examined the effect of PPE on a nonverbal measure of neurocognitive functioning.

Methods
The Leiter International Performance Scale, Third Edition (Leiter-3) was administered to 125 children between the ages of three and eight. Fifty-nine children were assessed twice without any PPE and 66 were assessed once without and once with PPE. Group differences on composite scores were evaluated using a repeated measures design, accounting for sex, school attendance, socioeconomic status, and HIV status.

Results
Nonverbal IQ scores increased significantly between test administrations for both groups, but no significant interaction between PPE group and scores on Leiter-3 composites was found.

Conclusions
No main effect of PPE on Leiter-3 outcomes was found. These results suggest clinical and research work using a nonverbal neurocognitive assessment can be completed when PPE is required.
Multiomics technologies: role in disease biomarker discoveries and therapeutics
Authors: Dar Mashooq Ahmad , Arafah Azher , Bhat Kaisar Ahmad , Khan Andleeb , Khan Mosin Saleem , Ali Aarif , Ahmad Syed Mudasir , Rashid Shahzada Mudasir , Rehman Muneeb U 
Published: July 2022

Abstract Medical research has been revolutionized after the publication of the full human genome. This was the major landmark that paved the way for understanding the biological functions of different macro and micro molecules. With the advent of different high-throughput technologies, biomedical research was further revolutionized. These technologies constitute genomics, transcriptomics, proteomics, metabolomics, etc. Collectively, these high-throughputs are referred to as multi-omics technologies. In the biomedical field, these omics technologies act as efficient and effective tools for disease diagnosis, management, monitoring, treatment and discovery of certain novel disease biomarkers. Genotyping arrays and other transcriptomic studies have helped us to elucidate the gene expression patterns in different biological states, i.e. healthy and diseased states. Further omics technologies such as proteomics and metabolomics have an important role in predicting the role of different biological molecules in an organism. It is because of these high throughput omics technologies that we have been able to fully understand the role of different genes, proteins, metabolites and biological pathways in a diseased condition. To understand a complex biological process, it is important to apply an integrative approach that analyses the multi-omics data in order to highlight the possible interrelationships of the involved biomolecules and their functions. Furthermore, these omics technologies offer an important opportunity to understand the information that underlies disease. In the current review, we will discuss the importance of omics technologies as promising tools to understand the role of different biomolecules in diseases such as cancer, cardiovascular diseases, neurodegenerative diseases and diabetes.Summary Points
Adaptive sequencing using nanopores and deep learning of mitochondrial DNA
Authors: Danilevsky Artem , Polsky Avital Luba , Shomron Noam 
Published: July 2022

Abstract
Nanopore sequencing is an emerging technology that reads DNA by utilizing a unique method of detecting nucleic acid sequences and identifies the various chemical modifications they carry. Deep learning has increased in popularity as a useful technique to solve many complex computational tasks. ‘Adaptive sequencing’ is an implementation of selective sequencing, intended for use on the nanopore sequencing platform. In this study, we demonstrated an alternative method of software-based selective sequencing that is performed in real time by combining nanopore sequencing and deep learning. Our results showed the feasibility of using deep learning for classifying signals from only the first 200 nucleotides in a raw nanopore sequencing signal format. This was further demonstrated by comparing the accuracy of our deep learning classification model across data from several human cell lines and other eukaryotic organisms. We used custom deep learning models and a script that utilizes a ‘Read Until’ framework to target mitochondrial molecules in real time from a human cell line sample. This achieved a significant separation and enrichment ability of 2.3-fold. In a series of very short sequencing experiments (10, 30 and 120 min), we identified genomic and mitochondrial reads with accuracy above 90%, although mitochondrial DNA comprised only 0.1% of the total input material. The uniqueness of our method is the ability to distinguish two groups of DNA even without a labeled reference. This contrasts with studies that required a well-defined reference, whether of a DNA sequence or of another type of representation. Additionally, our method showed higher correlation to the theoretically possible enrichment factor, compared with other published methods. We believe that our results will lay the foundation for rapid and selective sequencing using nanopore technology and will pave the approach for clinical applications that use nanopore sequencing data.
SYSMut: decoding the functional significance of rare somatic mutations in cancer
Authors: Khalighi Sirvan , Joseph Peronne , Babu Deepak , Singh Salendra , LaFramboise Thomas , Guda Kishore , Varadan Vinay 
Published: July 2022

AbstractCurrent tailored-therapy efforts in cancer are largely focused on a small number of highly recurrently mutated driver genes but therapeutic targeting of these oncogenes remains challenging. However, the vast number of genes mutated infrequently across cancers has received less attention, in part, due to a lack of understanding of their biological significance. We present SYSMut, an extendable systems biology platform that can robustly infer the biologic consequences of somatic mutations by integrating routine multiomics profiles in primary tumors. We establish SYSMut’s improved performance vis-à-vis state-of-the-art driver gene identification methodologies by recapitulating the functional impact of known driver genes, while additionally identifying novel functionally impactful mutated genes across 29 cancers. Subsequent application of SYSMut on low-frequency gene mutations in head and neck squamous cell (HNSC) cancers, followed by molecular and pharmacogenetic validation, revealed the lipidogenic network as a novel therapeutic vulnerability in aggressive HNSC cancers. SYSMut is thus a robust scalable framework that enables the discovery of new targetable avenues in cancer.
High-quality pan-genome of Escherichia coli generated by excluding confounding and highly similar strains reveals an association between unique gene clusters and genomic islands
Authors: Yang Tong , Gao Feng 
Published: July 2022

Abstract
The pan-genome analysis of bacteria provides detailed insight into the diversity and evolution of a bacterial population. However, the genomes involved in the pan-genome analysis should be checked carefully, as the inclusion of confounding strains would have unfavorable effects on the identification of core genes, and the highly similar strains could bias the results of the pan-genome state (open versus closed). In this study, we found that the inclusion of highly similar strains also affects the results of unique genes in pan-genome analysis, which leads to a significant underestimation of the number of unique genes in the pan-genome. Therefore, these strains should be excluded from pan-genome analysis at the early stage of data processing. Currently, tens of thousands of genomes have been sequenced for Escherichia coli, which provides an unprecedented opportunity as well as a challenge for pan-genome analysis of this classical model organism. Using the proposed strategies, a high-quality E. coli pan-genome was obtained, and the unique genes was extracted and analyzed, revealing an association between the unique gene clusters and genomic islands from a pan-genome perspective, which may facilitate the identification of genomic islands.
RNAloops: a database of RNA multiloops
Authors: Wiedemann Jakub , Kaczor Jacek , Milostan Maciej , Zok Tomasz , Blazewicz Jacek , Szachniuk Marta , Antczak Maciej 
Published: July 2022

AbstractMotivationKnowledge of the 3D structure of RNA supports discovering its functions and is crucial for designing drugs and modern therapeutic solutions. Thus, much attention is devoted to experimental determination and computational prediction targeting the global fold of RNA and its local substructures. The latter include multi-branched loops—functionally significant elements that highly affect the spatial shape of the entire molecule. Unfortunately, their computational modeling constitutes a weak point of structural bioinformatics. A remedy for this is in collecting these motifs and analyzing their features.ResultsRNAloops is a self-updating database that stores multi-branched loops identified in the PDB-deposited RNA structures. A description of each loop includes angular data—planar and Euler angles computed between pairs of adjacent helices to allow studying their mutual arrangement in space. The system enables search and analysis of multiloops, presents their structure details numerically and visually, and computes data statistics.Availability and implementationRNAloops is freely accessible at https://rnaloops.cs.put.poznan.pl.Supplementary informationSupplementary data are available at Bioinformatics online.