bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-parametric synergy modeling of chemical compounds with Gaussian processes
Authors: Shapovalova Yuliya , Heskes Tom , Dijkstra Tjeerd 
Published: January 2022

Abstract
Background
Understanding the synergetic and antagonistic effects of combinations of drugs and toxins is vital for many applications, including treatment of multifactorial diseases and ecotoxicological monitoring. Synergy is usually assessed by comparing the response of drug combinations to a predicted non-interactive response from reference (null) models. Possible choices of null models are Loewe additivity, Bliss independence and the recently rediscovered Hand model. A different approach is taken by the MuSyC model, which directly fits a generalization of the Hill model to the data. All of these models, however, fit the dose–response relationship with a parametric model.

Results
We propose the Hand-GP model, a non-parametric model based on the combination of the Hand model with Gaussian processes. We introduce a new logarithmic squared exponential kernel for the Gaussian process which captures the logarithmic dependence of response on dose. From the monotherapeutic response and the Hand principle, we construct a null reference response and synergy is assessed from the difference between this null reference and the Gaussian process fitted response. Statistical significance of the difference is assessed from the confidence intervals of the Gaussian process fits. We evaluate performance of our model on a simulated data set from Greco, two simulated data sets of our own design and two benchmark data sets from Chou and Talalay. We compare the Hand-GP model to standard synergy models and show that our model performs better on these data sets. We also compare our model to the MuSyC model as an example of a recent method on these five data sets and on two-drug combination screens: Mott et al. anti-malarial screen and O’Neil et al. anti-cancer screen. We identify cases in which the HandGP model is preferred and cases in which the MuSyC model is preferred.

Conclusion
The Hand-GP model is a flexible model to capture synergy. Its non-parametric and probabilistic nature allows it to model a wide variety of response patterns.
LaRA 2: parallel and vectorized program for sequence–structure alignment of RNA sequences
Authors: Winkler Jörg , Urgese Gianvito , Ficarra Elisa , Reinert Knut 
Published: January 2022

Abstract
Background
The function of non-coding RNA sequences is largely determined by their spatial conformation, namely the secondary structure of the molecule, formed by Watson–Crick interactions between nucleotides. Hence, modern RNA alignment algorithms routinely take structural information into account. In order to discover yet unknown RNA families and infer their possible functions, the structural alignment of RNAs is an essential task. This task demands a lot of computational resources, especially for aligning many long sequences, and it therefore requires efficient algorithms that utilize modern hardware when available. A subset of the secondary structures contains overlapping interactions (called pseudoknots), which add additional complexity to the problem and are often ignored in available software.

Results
We present the SeqAn-based software LaRA 2 that is significantly faster than comparable software for accurate pairwise and multiple alignments of structured RNA sequences. In contrast to other programs our approach can handle arbitrary pseudoknots. As an improved re-implementation of the LaRA tool for structural alignments, LaRA 2 uses multi-threading and vectorization for parallel execution and a new heuristic for computing a lower boundary of the solution. Our algorithmic improvements yield a program that is up to 130 times faster than the previous version.

Conclusions
With LaRA 2 we provide a tool to analyse large sets of RNA secondary structures in relatively short time, based on structural alignment. The produced alignments can be used to derive structural motifs for the search in genomic databases.
HESML: a real-time semantic measures library for the biomedical domain with a reproducible survey
Authors: Lastra-Díaz Juan J. , Lara-Clares Alicia , Garcia-Serrano Ana 
Published: January 2022

AbstractBackgroundOntology-based semantic similarity measures based on SNOMED-CT, MeSH, and Gene Ontology are being extensively used in many applications in biomedical text mining and genomics respectively, which has encouraged the development of semantic measures libraries based on the aforementioned ontologies. However, current state-of-the-art semantic measures libraries have some performance and scalability drawbacks derived from their ontology representations based on relational databases, or naive in-memory graph representations. Likewise, a recent reproducible survey on word similarity shows that one hybrid IC-based measure which integrates a shortest-path computation sets the state of the art in the family of ontology-based semantic measures. However, the lack of an efficient shortest-path algorithm for their real-time computation prevents both their practical use in any application and the use of any other path-based semantic similarity measure.ResultsTo bridge the two aforementioned gaps, this work introduces for the first time an updated version of the HESML Java software library especially designed for the biomedical domain, which implements the most efficient and scalable ontology representation reported in the literature, together with a new method for the approximation of the Dijkstra’s algorithm for taxonomies, called Ancestors-based Shortest-Path Length (AncSPL), which allows the real-time computation of any path-based semantic similarity measure.ConclusionsWe introduce a set of reproducible benchmarks showing that HESML outperforms by several orders of magnitude the current state-of-the-art libraries in the three aforementioned biomedical ontologies, as well as the real-time performance and approximation quality of the new AncSPL shortest-path algorithm. Likewise, we show that AncSPL linearly scales regarding the dimension of the common ancestor subgraph regardless of the ontology size. Path-based measures based on the new AncSPL algorithm are up to six orders of magnitude faster than their exact implementation in large ontologies like SNOMED-CT and GO. Finally, we provide a detailed reproducibility protocol and dataset as supplementary material to allow the exact replication of all our experiments and results.
Protein complexes detection based on node local properties and gene expression in PPI weighted networks
Authors: Yu Yang , Kong Dezhou 
Published: January 2022

AbstractBackgroundIdentifying protein complexes from protein–protein interaction (PPI) networks is a crucial task, and many related algorithms have been developed. Most algorithms usually employ direct neighbors of nodes and ignore resource allocation and second-order neighbors. The effective use of such information is crucial to protein complex detection.ResultBased on this observation, we propose a new way by combining node resource allocation and gene expression information to weight protein network (NRAGE-WPN), in which protein complexes are detected based on core-attachment and second-order neighbors.ConclusionsThrough comparison with eleven methods in Yeast and Human PPI network, the experimental results demonstrate that this algorithm not only performs better than other methods on 75% in terms of f-measure+, but also can achieve an ideal overall performance in terms of a composite score consisting of five performance measures. This identification method is simple and can accurately identify more complexes.
Comparative genomics and phylogenetic relationships of two endemic and endangered species (Handeliodendron bodinieri and Eurycorymbus cavaleriei) of two monotypic genera within Sapindales
Authors: Yang Jiaxin , Hu Guoxiong , Hu Guangwan 
Published: January 2022

Abstract
Background
Handeliodendron Rehder and Eurycorymbus Hand.-Mazz. are the monotypic genera in the Sapindaceae family. The phylogenetic relationship of these endangered species Handeliodendron bodinieri (Lévl.) Rehd. and Eurycorymbus cavaleriei (Lévl.) Rehd. et Hand.-Mazz. with other members of Sapindaceae s.l. is not well resolved. A previous study concluded that the genus Aesculus might be paraphyletic because Handeliodendron was nested within it based on small DNA fragments. Thus, their chloroplast genomic information and comparative genomic analysis with other Sapindaceae species are necessary and crucial to understand the circumscription and plastome evolution of this family.

Results
The chloroplast genome sizes of Handeliodendron bodinieri and Eurycorymbus cavaleriei are 151,271 and 158,690 bp, respectively. Results showed that a total of 114 unique genes were annotated in H. bodinieri and E. cavaleriei, and the ycf1 gene contained abundant SSRs in both genomes. Comparative analysis revealed that gene content, PCGs, and total GC content were remarkably similar or identical within 13 genera from Sapindaceae, and the chloroplast genome size of four genera was generally smaller within the family, including Acer, Dipteronia, Aesculus, and Handeliodendron. IR boundaries of the H. bodinieri showed a significant contraction, whereas it presented a notable expansion in E. cavaleriei cp genome. Ycf1, ndhC-trnV-UAC, and rpl32-trnL-UAG-ccsA were remarkably divergent regions in the Sapindaceae species. Analysis of selection pressure showed that there are a few positively selected genes. Phylogenetic analysis based on different datasets, including whole chloroplast genome sequences, coding sequences, large single-copy, small single-copy, and inverted repeat regions, consistently demonstrated that H. bodinieri was sister to the clade consisting of Aesculus chinensis and A. wangii and strongly support Eurycorymbus cavaleriei as sister to Dodonaea viscosa.

Conclusion
This study revealed that the cp genome size of the Hippocastanoideae was generally smaller compared to the other subfamilies within Sapindaceae, and three highly divergent regions could be used as the specific DNA barcodes within Sapindaceae. Phylogenetic results strongly support that the subdivision of four subfamilies within Sapindaceae, and Handeliodendron is not nested within the genus Aesculus.
Long range PCR-based deep sequencing for haplotype determination in mixed HCMV infections
Authors: Brait Nadja , Külekçi Büşra , Goerzer Irene 
Published: January 2022

Abstract
Background
Short read sequencing has been used extensively to decipher the genome diversity of human cytomegalovirus (HCMV) strains, but falls short to reveal individual genomes in mixed HCMV strain populations. Novel third-generation sequencing platforms offer an extended read length and promise to resolve how distant polymorphic sites along individual genomes are linked. In the present study, we established a long amplicon PacBio sequencing workflow to identify the absolute and relative quantities of unique HCMV haplotypes spanning over multiple hypervariable sites in mixtures. Initial validation of this approach was performed with defined HCMV DNA templates derived from cell-culture enriched viruses and was further tested for its suitability on patient samples carrying mixed HCMV infections.

Results
Total substitution and indel error rate of mapped reads ranged from 0.17 to 0.43% depending on the stringency of quality trimming. Artificial HCMV DNA mixtures were correctly determined down to 1% abundance of the minor DNA source when the total HCMV DNA input was 4 × 104 copies/ml. PCR products of up to 7.7 kb and a GC content < 55% were efficiently generated when DNA was directly isolated from patient samples. In a single sample, up to three distinct haplotypes were identified showing varying relative frequencies. Alignments of distinct haplotype sequences within patient samples showed uneven distribution of sequence diversity, interspersed by long identical stretches. Moreover, diversity estimation at single polymorphic regions as assessed by short amplicon sequencing may markedly underestimate the overall diversity of mixed haplotype populations.

Conclusions
Quantitative haplotype determination by long amplicon sequencing provides a novel approach for HCMV strain characterisation in mixed infected samples which can be scaled up to cover the majority of the genome by multi-amplicon panels. This will substantially improve our understanding of intra-host HCMV strain diversity and its dynamic behaviour.
Maize/peanut intercropping improves nutrient uptake of side-row maize and system microbial community diversity
Authors: Zhao Xinhua , Dong Qiqi , Han Yi , Zhang Kezhao , Shi Xiaolong , Yang Xu , Yuan Yang , Zhou Dongying , Wang Kai , Wang Xiaoguang , Jiang Chunji , Liu Xibo , Zhang He , Zhang Zhimeng , Yu Haiqiu 
Published: January 2022

Abstract
Background
Intercropping, a diversified planting pattern, increases land use efficiency and farmland ecological diversity. We explored the changes in soil physicochemical properties, nutrient uptake and utilization, and microbial community composition in wide-strip intercropping of maize and peanut.

Results
The results from three treatments, sole maize, sole peanut and intercropping of maize and peanut, showed that intercropped maize had a marginal advantage and that the nutrient content of roots, stems and grains in side-row maize was better than that in the middle row of intercropped maize and sole maize. The yield of intercropped maize was higher than that of sole cropping. The interaction between crops significantly increased soil peroxidase activity, and significantly decreased protease and dehydrogenase activities in intercropped maize and intercropped peanut. The diversity and richness of bacteria and fungi decreased in intercropped maize rhizosphere soil, whereas the richness of fungi increased intercropped peanut. RB41, Candidatus-udaeobacter, Stropharia, Fusarium and Penicillium were positively correlated with soil peroxidase activity, and negatively correlated with soil protease and dehydrogenase activities. In addition, intercropping enriched the functional diversity of the bacterial community and reduced pathogenic fungi.

Conclusion
Intercropping changed the composition and diversity of the bacterial and fungal communities in rhizosphere soil, enriched beneficial microbes, increased the nitrogen content of intercropped maize and provided a scientific basis for promoting intercropping in northeastern China.
Microbiome analyses of 12 psyllid species of the family Psyllidae identified various bacteria including Fukatsuia and Serratia symbiotica, known as secondary symbionts of aphids
Authors: Nakabachi Atsushi , Inoue Hiromitsu , Hirose Yuu 
Published: January 2022

Abstract
Background
Psyllids (Hemiptera: Psylloidea) comprise a group of plant sap-sucking insects that includes important agricultural pests. They have close associations not only with plant pathogens, but also with various microbes, including obligate mutualists and facultative symbionts. Recent studies are revealing that interactions among such bacterial populations are important for psyllid biology and host plant pathology. In the present study, to obtain further insight into the ecological and evolutionary behaviors of bacteria in Psylloidea, we analyzed the microbiomes of 12 psyllid species belonging to the family Psyllidae (11 from Psyllinae and one from Macrocorsinae), using high-throughput amplicon sequencing of the 16S rRNA gene.

Results
The analysis showed that all 12 psyllids have the primary symbiont, Candidatus Carsonella ruddii (Gammaproteobacteria: Oceanospirillales), and at least one secondary symbiont. The majority of the secondary symbionts were gammaproteobacteria, especially those of the family Enterobacteriaceae (order: Enterobacteriales). Among them, symbionts belonging to “endosymbionts3”, which is a genus-level monophyletic group assigned by the SILVA rRNA database, were the most prevalent and were found in 9 of 11 Psyllinae species. Ca. Fukatsuia symbiotica and Serratia symbiotica, which were recognized only as secondary symbionts of aphids, were also identified. In addition to other Enterobacteriaceae bacteria, including Arsenophonus, Sodalis, and “endosymbionts2”, which is another genus-level clade, Pseudomonas (Pseudomonadales: Pseudomonadaceae) and Diplorickettsia (Diplorickettsiales: Diplorickettsiaceae) were identified. Regarding Alphaproteobacteria, the potential plant pathogen Ca. Liberibacter europaeus (Rhizobiales: Rhizobiaceae) was detected for the first time in Anomoneura mori (Psyllinae), a mulberry pest. Wolbachia (Rickettsiales: Anaplasmataceae) and Rickettsia (Rickettsiales: Rickettsiaceae), plausible host reproduction manipulators that are potential tools to control pest insects, were also detected.

Conclusions
The present study identified various bacterial symbionts including previously unexpected lineages in psyllids, suggesting considerable interspecific transfer of arthropod symbionts. The findings provide deeper insights into the evolution of interactions among insects, bacteria, and plants, which may be exploited to facilitate the control of pest psyllids in the future.
Rhizosphere analysis of field-grown Panax ginseng with different degrees of red skin provides the basis for preventing red skin syndrome
Authors: Dong Ling , Bian Xingbo , Zhao Yan , Yang He , Xu Yonghua , Han Yongzhong , Zhang Lianxue 
Published: January 2022

Abstract
Background
Ginseng red skin root syndrome (GRS) is one of the most common ginseng (Panax ginseng Meyer) diseases. It leads to a severe decline in P. ginseng quality and seriously affects the P. ginseng industry in China. However, as a root disease, the characteristics of the GRS rhizosphere microbiome are still unclear.

Methods
The amplicon bacterial 16 S rRNA genes and fungal ITS (Internal Transcribed Spacer) regions Illumina sequencing technology, combined with microbial diversity and composition analysis based on R software, was used to explore the relationship between soil ecological environment and GRS.

Results
There were significant differences in the diversity and richness of soil microorganisms between the rhizosphere with different degrees of disease, especially between healthy P. ginseng (HG) and heavily diseased groups. The variation characteristics of microbial abundance in different taxa levels were analyzed. The interaction network of rhizosphere microorganisms of P. ginseng under GRS background was established. We also found that different P. ginseng rhizosphere microbial communities have multiple changes in stability and complexity through the established interaction network. Microbes closely related to potential pathogenic fungi were also identified according to the interaction network, which provided clues for looking for biological control agents. Finally, the Distance-based redundancy analysis (dbRDA) results indicated that total phosphorus (TP), available potassium (AK), available phosphorus (AP), catalase (CAT), invertase (INV) are the key factors that influence the microbial communities. Moreover, the content of these key factors in the rhizosphere was negatively correlated with disease degrees.

Conclusions
In this study, we comprehensively analyzed the rhizosphere characteristics of P. ginseng with different levels of disease, and explored the interaction relationship among microorganisms. These results provide a basis for soil improvement and biological control of field-grown in the future.
Chlorosis seedling lethality 1 encoding a MAP3K protein is essential for chloroplast development in rice
Authors: Liang Jiayan , Zhang Qiuxin , Liu Yiran , Zhang Jingjing , Wang Wenyi , Zhang Zemin 
Published: January 2022

Abstract
Background
Mitogen-activated protein kinase (MAPK) cascades are conserved signaling modules in eukaryotic organisms and play essential roles in immunity and stress responses. However, the role of MAPKs in chloroplast development remains to be evidently established.

Results
In this study, a rice chlorosis seedling lethality 1 (csl1) mutant with a Zhonghua11 (ZH11, japonica) background was isolated. Seedlings of the mutant were characterized by chlorotic leaves and death after the trefoil stage, and chloroplasts were observed to contain accumulated starch granules. Molecular cloning revealed that OsCSL1 encoded a MAPK kinase kinase22 (MKKK22) targeted to the endoplasmic reticulum (ER), and functional complementation of OsCSL1 was found to restore the normal phenotype in csl1 plants. The CRISPR/Cas9 technology was used for targeted disruption of OsCSL1, and the OsCSL1-Cas9 lines obtained therein exhibited yellow seedlings which phenocopied the csl1 mutant. CSL1/MKKK22 was observed to establish direct interaction with MKK4, and altered expression of MKK1 and MKK4 was detected in the csl1 mutant. Additionally, disruption of OsCSL1 led to reduced expression of chloroplast-associated genes, including chlorophyll biosynthetic genes, plastid-encoded RNA polymerases, nuclear-encoded RNA polymerase, and nuclear-encoded chloroplast genes.

Conclusions
The findings of this study revealed that OsCSL1 played roles in regulating the expression of multiple chloroplast synthesis-related genes, thereby affecting their functions, and leading to wide-ranging defects, including chlorotic seedlings and severely disrupted chloroplasts containing accumulated starch granules.
Non-parametric estimation of reference adjusted, standardised probabilities of all-cause death and death due to cancer for population group comparisons
Authors: Rutherford Mark J. , Andersson Therese M.-L. , Myklebust Tor Åge , Møller Bjørn , Lambert Paul C. 
Published: January 2022

Abstract
Background
Ensuring fair comparisons of cancer survival statistics across population groups requires careful consideration of differential competing mortality due to other causes, and adjusting for imbalances over groups in other prognostic covariates (e.g. age). This has typically been achieved using comparisons of age-standardised net survival, with age standardisation addressing covariate imbalance, and the net estimates removing differences in competing mortality from other causes. However, these estimates lack ease of interpretability. In this paper, we motivate an alternative non-parametric approach that uses a common rate of other cause mortality across groups to give reference-adjusted estimates of the all-cause and cause-specific crude probability of death in contrast to solely reporting net survival estimates.

Methods
We develop the methodology for a non-parametric equivalent of standardised and reference adjusted crude probabilities of death, building on the estimation of non-parametric crude probabilities of death. We illustrate the approach using regional comparisons of survival following a diagnosis of rectal cancer for men in England. We standardise to the covariate distribution and other cause mortality of England as a whole to offer comparability, but with close approximation to the observed all-cause region-specific mortality.

Results
The approach gives comparable estimates to observed crude probabilities of death, but allows direct comparison across population groups with different covariate profiles and competing mortality patterns. In our illustrative example, we show that regional variations in survival following a diagnosis of rectal cancer persist even after accounting for the variation in deprivation, age at diagnosis and other cause mortality.

Conclusions
The methodological approach of using standardised and reference adjusted metrics offers an appealing approach for future cancer survival comparison studies and routinely published cancer statistics. Our non-parametric estimation approach through the use of weighting offers the ability to estimate comparable survival estimates without the need for statistical modelling.