bluuebunny/crossref_metadata_2025_split huggingface dataset:
Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches
Authors: Bugnon L A , Edera A A , Prochetto S , Gerard M , Raad J , Fenoy E , Rubiolo M , Chorostecki U , Gabaldón T , Ariel F , Di Persia L E , Milone D H , Stegmayer G 
Published: May 2022

Abstract

Motivation
In contrast to messenger RNAs, the function of the wide range of existing long noncoding RNAs (lncRNAs) largely depends on their structure, which determines interactions with partner molecules. Thus, the determination or prediction of the secondary structure of lncRNAs is critical to uncover their function. Classical approaches for predicting RNA secondary structure have been based on dynamic programming and thermodynamic calculations. In the last 4 years, a growing number of machine learning (ML)-based models, including deep learning (DL), have achieved breakthrough performance in structure prediction of biomolecules such as proteins and have outperformed classical methods in short transcripts folding. Nevertheless, the accurate prediction for lncRNA still remains far from being effectively solved. Notably, the myriad of new proposals has not been systematically and experimentally evaluated.

Results
In this work, we compare the performance of the classical methods as well as the most recently proposed approaches for secondary structure prediction of RNA sequences using a unified and consistent experimental setup. We use the publicly available structural profiles for 3023 yeast RNA sequences, and a novel benchmark of well-characterized lncRNA structures from different species. Moreover, we propose a novel metric to assess the predictive performance of methods, exclusively based on the chemical probing data commonly used for profiling RNA structures, avoiding any potential bias incorporated by computational predictions when using dot-bracket references. Our results provide a comprehensive comparative assessment of existing methodologies, and a novel and public benchmark resource to aid in the development and comparison of future approaches.

Availability
Full source code and benchmark datasets are available at: https://github.com/sinc-lab/lncRNA-folding

Contact
lbugnon@sinc.unl.edu.ar
Quantitative estimation of intracellular oxidative stress in human tissues
Authors: Bai Jun , Tan Renbo , An Zheng , Xu Ying 
Published: May 2022

Abstract
Oxidative stress is known to be involved in and possibly a key driver of the development of numerous chronic diseases, including cancer. It is highly desired to have a capability to reliably estimate the level of intracellular oxidative stress as it can help to identify functional changes and disease phenotypes associated with such a stress, but the problem proves to be very challenging. We present a novel computational model for quantitatively estimating the level of oxidative stress in tissues and cells based on their transcriptomic data. The model consists of (i) three sets of marker genes found to be associated with the production of oxidizing molecules, the activated antioxidation programs and the intracellular stress attributed to oxidation, respectively; (ii) three polynomial functions defined over the expression levels of the three gene sets are developed aimed to capture the total oxidizing power, the activated antioxidation capacity and the oxidative stress level, respectively, with their detailed parameters estimated by solving an optimization problem and (iii) the optimization problem is so formulated to capture the relevant known insights such as the oxidative stress level generally goes up from normal to chronic diseases and then to cancer tissues. Systematic assessments on independent datasets indicate that the trained predictor is highly reliable and numerous insights are made based on its application results to samples in the TCGA, GTEx and GEO databases.
Sufficient principal component regression for pattern discovery in transcriptomic data
Authors: Ding Lei , Zentner Gabriel E , McDonald Daniel J 
Published: May 2022

AbstractMotivationMethods for the global measurement of transcript abundance such as microarrays and RNA-Seq generate datasets in which the number of measured features far exceeds the number of observations. Extracting biologically meaningful and experimentally tractable insights from such data therefore requires high-dimensional prediction. Existing sparse linear approaches to this challenge have been stunningly successful, but some important issues remain. These methods can fail to select the correct features, predict poorly relative to non-sparse alternatives or ignore any unknown grouping structures for the features.ResultsWe propose a method called SuffPCR that yields improved predictions in high-dimensional tasks including regression and classification, especially in the typical context of omics with correlated features. SuffPCR first estimates sparse principal components and then estimates a linear model on the recovered subspace. Because the estimated subspace is sparse in the features, the resulting predictions will depend on only a small subset of genes. SuffPCR works well on a variety of simulated and experimental transcriptomic data, performing nearly optimally when the model assumptions are satisfied. We also demonstrate near-optimal theoretical guarantees.Availability and implementationCode and raw data are freely available at https://github.com/dajmcdon/suffpcr. Package documentation may be viewed at https://dajmcdon.github.io/suffpcr.Contactdaniel@stat.ubc.caSupplementary informationSupplementary data are available at Bioinformatics Advances online.
Altered SOD1 maturation and post-translational modification in amyotrophic lateral sclerosis spinal cord
Authors: Trist Benjamin G , Genoud Sian , Roudeau Stéphane , Rookyard Alexander , Abdeen Amr , Cottam Veronica , Hare Dominic J , White Melanie , Altvater Jens , Fifita Jennifer A , Hogan Alison , Grima Natalie , Blair Ian P , Kysenius Kai , Crouch Peter J , Carmona Asuncion , Rufin Yann , Claverol Stéphane , Van Malderen Stijn , Falkenberg Gerald , Paterson David J , Smith Bradley , Troakes Claire , Vance Caroline , Shaw Christopher E , Al-Sarraj Safa , Cordwell Stuart , Halliday Glenda , Ortega Richard , Double Kay L 
Published: May 2022

Abstract
Aberrant self-assembly and toxicity of wild-type and mutant superoxide dismutase 1 (SOD1) has been widely examined in silico, in vitro and in transgenic animal models of amyotrophic lateral sclerosis. Detailed examination of the protein in disease-affected tissues from amyotrophic lateral sclerosis patients, however, remains scarce.
We used histological, biochemical and analytical techniques to profile alterations to SOD1 protein deposition, subcellular localization, maturation and post-translational modification in post-mortem spinal cord tissues from amyotrophic lateral sclerosis cases and controls. Tissues were dissected into ventral and dorsal spinal cord grey matter to assess the specificity of alterations within regions of motor neuron degeneration.
We provide evidence of the mislocalization and accumulation of structurally disordered, immature SOD1 protein conformers in spinal cord motor neurons of SOD1-linked and non-SOD1-linked familial amyotrophic lateral sclerosis cases, and sporadic amyotrophic lateral sclerosis cases, compared with control motor neurons. These changes were collectively associated with instability and mismetallation of enzymatically active SOD1 dimers, as well as alterations to SOD1 post-translational modifications and molecular chaperones governing SOD1 maturation. Atypical changes to SOD1 protein were largely restricted to regions of neurodegeneration in amyotrophic lateral sclerosis cases, and clearly differentiated all forms of amyotrophic lateral sclerosis from controls. Substantial heterogeneity in the presence of these changes was also observed between amyotrophic lateral sclerosis cases.
Our data demonstrate that varying forms of SOD1 proteinopathy are a common feature of all forms of amyotrophic lateral sclerosis, and support the presence of one or more convergent biochemical pathways leading to SOD1 proteinopathy in amyotrophic lateral sclerosis. Most of these alterations are specific to regions of neurodegeneration, and may therefore constitute valid targets for therapeutic development.
Phonemic restoration in Alzheimer’s disease and semantic dementia: a preliminary investigation
Authors: Jiang Jessica , Johnson Jeremy C. S. , Requena-Komuro Maï-Carmen , Benhamou Elia , Sivasathiaseelan Harri , Sheppard Damion L. , Volkmer Anna , Crutch Sebastian J. , Hardy Chris J. D. , Warren Jason D 
Published: May 2022

Abstract
Phonemic restoration—perceiving speech sounds that are actually missing—is a fundamental perceptual process that ‘repairs’ interrupted spoken messages during noisy everyday listening. As a dynamic, integrative process, phonemic restoration is potentially affected by neurodegenerative pathologies, but this has not been clarified. Here, we studied this phenomenon in 5 patients with typical Alzheimer’s disease and 4 patients with semantic dementia, relative to 22 age-matched healthy controls. Participants heard isolated sounds, spoken real words and pseudowords in which noise bursts either overlaid a consonant or replaced it; a tendency to hear replaced (missing) speech sounds as present signified phonemic restoration. All groups perceived isolated noises normally and showed phonemic restoration of real words, most marked in Alzheimer’s patients. For pseudowords, healthy controls showed no phonemic restoration, while Alzheimer’s patients showed marked suppression of phonemic restoration and patients with semantic dementia contrastingly showed phonemic restoration comparable to real words. Our findings provide the first evidence that phonemic restoration is preserved or even enhanced in neurodegenerative diseases, with distinct syndromic profiles that may reflect the relative integrity of bottom-up phonological representation and top-down lexical disambiguation mechanisms in different diseases. This work has theoretical implications for predictive coding models of language and neurodegenerative disease and for understanding cognitive ‘repair’ processes in dementia. Future research should expand on these preliminary observations with larger cohorts.
Innovating in knowledge-intensive entrepreneurial firms: exploring the effects of a variety of internal and external knowledge sources on goods and service innovations
Authors: Gifford Ethan , Ljungberg Daniel , McKelvey Maureen 
Published: May 2022

AbstractAlthough knowledge-intensive entrepreneurial firms experiencing high growth and generating innovations are widely acknowledged as important for economic growth, surprisingly little is known about how such firms achieve and maintain a high level of knowledge intensity through which to innovate. Our article further develops the concept of knowledge intensity by proposing that it is augmented by external and internal search activities carried out by the entrepreneurial firm and analyzes how these activities affect innovation performance. We use principal component analysis to derive formal and informal search channels from summated rating scales—measuring reliance on internal and external sources of knowledge—and then use fractional logit regression to explore how these channels relate to a firm’s innovative performance, i.e., the share of innovative goods and services sold. We find that searching via informal channels, and formal channels toward scientific and technological knowledge, improves innovation performance of both goods and services, while searching via formal channels toward market knowledge positively affects only innovative goods. Overall, informal channels matter more than formal channels. Lastly, we find substitution rather than complementarity effects between external and internal search channels in their effect on innovation performance in both goods and services. Thus, we interpret that building up knowledge intensity per se through search matters more for innovation performance than whether search is internally or externally focused. Our work contributes to the growing literature on knowledge-intensive entrepreneurship, to the related literature on new technology-based firms and young innovative firms, and to the general understanding of knowledge intensity at the firm level.
Platform competition and complementor responses: insights from combining design rules with the comparative adjustment, transaction, and opportunity cost framework
Authors: Argyres Nicholas , Nickerson Jackson , Ozalp Hakan 
Published: May 2022

Abstract
Platform owners regularly make decisions regarding whether, when, and how to upgrade their platforms as they compete with other platforms. These decisions must consider how platform complementors and rivals are likely to respond to various changes because a platform suffers in competition when the quantity or quality of its complementors is low. This paper analyzes such interactions in the US videogame industry. We show how a combined design rule-comparative adjustment, transaction, and opportunity cost framework can help to explain and predict these interactions in this industry.
Limited airway resection and reconstruction for paediatric tracheobronchial inflammatory myofibroblastic tumour
Authors: Dong Junguo , Gonzalez-Rivas Diego , Lv Pengcheng , Wang Zhexin , He Jiaxi , Yao Feng , Li Shuben 
Published: May 2022

Abstract

OBJECTIVES
The paediatric tracheobronchial inflammatory myofibroblastic tumour (IMT) is a rare disease. Whether limited surgical resection is a feasible surgical approach for these patients remains controversial. The objectives of this study were to report the long-term prognosis after limited surgical resections on paediatric tracheobronchial IMT and provide a surgical management strategy for this rare disease.

METHODS
Paediatric tracheobronchial IMT patients who underwent limited surgical resection from 2012 to 2020 were enrolled in this study. The clinical characteristics, course of treatment and long-term outcomes of all participants were collated. We presented the accumulated data and analysed the feasibility of limited surgical resection on the paediatric tracheobronchial IMT.

RESULTS
A total of 9 children with tracheobronchial IMTs were enrolled in our study. Cough and shortness of breath were the most common symptoms. All 9 participants underwent surgical treatment, including 2 tracheal reconstructions, 4 carinal reconstructions and 3 bronchial sleeve resections. Among the participants, 6/9 (66%) were positive for the anaplastic lymphoma receptor tyrosine kinase gene in terms of immunohistochemistry. None of the participants died of short-term complications. The follow-up period was 5.4 (range, 1.1–9.3) years, during which all participants remained well.

CONCLUSIONS
Limited surgical resection is preferred for paediatrics with tracheobronchial IMTs. Meanwhile, patients with complete resection have an excellent long-term prognosis.
“Groups Can Change, Therefore War is Avoidable”: How Confidence in National Identity Can Reduce Public Support for Militant Internationalism
Authors: Chung Eunbin 
Published: May 2022

AbstractAs a way to alleviate interstate aggression, researchers have proposed a submergence of existing national identities and promotion of universalism instead. In contrast, this study suggests that strong national identities can reduce public support for militaristic foreign policy. I examine the mechanism of this relationship, proposing that the affirmation of national identities increases beliefs that the nature of other groups is malleable rather than fixed. The belief of the malleability of group nature opens a possibility for negotiation and peacebuilding between rival states, as conflict with the other side becomes an avoidable option. Integrating theories of political psychology and conflict resolution, I conduct novel survey experiments with a sample of 944 Japanese participants. Results revealed that Japanese respondents who reflected on the positive aspects of their national identity tended to hold lower levels of support for militaristic foreign policy. These effects were transmitted via an increase in beliefs that the nature of groups is malleable and beliefs of war avoidability.
Antimicrobial resistance in commensal Escherichia coli from humans and chickens in the Mekong Delta of Vietnam is driven by antimicrobial usage and potential cross-species transmission
Authors: Nhung Nguyen Thi , Yen Nguyen Thi Phuong , Dung Nguyen Thi Thuy , Nhan Nguyen Thi Minh , Phu Doan Hoang , Kiet Bach Tuan , Thwaites Guy , Geskus Ronald B. , Baker Stephen , Carrique-Mas Juan , Choisy Marc 
Published: May 2022

Abstract

Objectives
To investigate phenotypic antimicrobial resistance (AMR) in relation to antimicrobial use (AMU) and potential inter-species transmission among Escherichia coli from humans and chickens located in the same households in the Mekong Delta of Vietnam.

Methods
We collected data on AMU and faecal swabs from humans (N = 426) and chickens (N = 237) from 237 small-scale farms. From each sample, one E. coli strain was isolated and tested for its susceptibility against 11 antimicrobials by Sensititre AST. The association between AMR and AMU was investigated by logistic regression modelling. Using randomization, we compared the degree of similarity in AMR patterns between human and chicken E. coli from the same farms compared with isolates from different farms.

Results
The AMU rate was ∼19 times higher in chickens (291.1 per 1000 chicken-days) than in humans (15.1 per 1000 person-days). Isolates from chickens also displayed a higher prevalence of multidrug resistance (63.3%) than those of human origin (55.1%). AMU increased the probability of resistance in isolates from human (ORs between 2.1 and 5.3) and chicken (ORs between 1.9 and 4.8). E. coli from humans and chickens living on same farms had a higher degree of similarity in their AMR patterns than isolates from humans and chicken living on different farms.

Conclusions
We demonstrated the co-influence of AMU and potential transmission on observed phenotypic AMR patterns among E. coli isolates from food-producing animals and in-contact humans. Restricting unnecessary AMU alongside limiting interspecies contact (i.e. increasing hygiene and biocontainment) are essential for reducing the burden of AMR.
Developing an integrated model for planning the delivery of construction materials to post-disaster reconstruction projects
Authors: Gharib Zahra , Yazdani Maziar , Bozorgi-Amiri Ali , Tavakkoli-Moghaddam Reza , Taghipourian Mohammad Javad 
Published: May 2022

AbstractConstruction material delivery to post-disaster reconstruction projects is challenging because of the resource and time limitations that follow a large-scale disaster. There is compelling evidence that inadequate planning jeopardises the success of a large number of post-disaster reconstruction projects. Thus, the current study proposes an integrated approach to facilitate the procurement planning of construction materials following a large-scale disaster. The proposed approach clustered the location of construction projects using a differential evolution (DE)-K-prototypes, a new partitional clustering algorithm based on DE and K-prototypes, method. Then, using a permanent matrix prioritises cluster points based on route reliability-affecting factors. The model’s objectives are to minimise the total travel time, maximise the reliability of the route, and minimise the total weighted undelivered materials to projects. In the case of distribution of material through land vehicles, the possibility of breakdowns in the vehicle is considered, allowing for the determination of vehicle breakdown under various scenarios and the minimisation of undelivered materials to projects. As a result of the uncertain character of the disaster, the demands of construction projects are fuzzy, and Jimenez’s method is used to handle it. Due to the complexity of the problem, two algorithms are proposed, a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and a non-dominated sorting genetic algorithm-II (NSGA-II). The results confirm that the proposed MOEA/D has a higher accuracy while NSGA-II has a shorter computational time. By providing new theoretical perspectives on disaster recovery strategies in the construction sector, this study contributes to the growing body of knowledge about disaster recovery strategies in the sector. The findings of this study can be employed to develop an integrated planning system for the delivery of construction materials to post-disaster reconstruction projects in disaster-prone countries.
Synthesis and signalling of strigolactone and KAI2-ligand signals in bryophytes
Authors: Bonhomme Sandrine , Guillory Ambre 
Published: May 2022

AbstractStrigolactones (SLs), long known as butenolide rhizospheric signals, have been recognized since 2008 as a class of hormones regulating many aspects of plant development. Many authors also anticipate ‘KAI2-ligand’ (KL) as a novel class of phytohormones; however, this ligand remains elusive. Core genes of SL and KL pathways, first described in angiosperms, are found in all land plants and some even in green algae. This review reports current knowledge of these pathways in bryophytes. Data on the pathways mostly come from two models: the moss Physcomitrium patens and the liverwort Marchantia. Gene targeting methods have allowed functional analyses of both models. Recent work in Marchantia suggests that SLs’ ancestral role was to recruit beneficial microbes as arbuscular mycorrhizal fungi. In contrast, the hormonal role of SLs observed in P. patens is probably a result of convergent evolution. Evidence for a functional KL pathway in both bryophyte models is very recent. Nevertheless, many unknowns remain and warrant a more extensive investigation of SL and KL pathways in various land plant lineages.
ROOT PENETRATION INDEX 3, a major quantitative trait locus associated with root system penetrability in Arabidopsis
Authors: Bello Bello Elohim , Rico Cambron Thelma Y , Ortiz Ramírez Lesly Abril , Rellán Álvarez Rubén , Herrera-Estrella Luis 
Published: May 2022

Abstract
Soil mechanical impedance precludes root penetration, confining root system development to shallow soil horizons where mobile nutrients are scarce. Using a two-phase-agar system, we characterized Arabidopsis responses to low and high mechanical impedance at three root penetration stages. We found that seedlings whose roots fail to penetrate agar barriers show a significant reduction in leaf area, root length, and elongation zone and an increment in root diameter, while those capable of penetrating show only minor morphological effects. Analyses using different auxin-responsive reporter lines, exogenous auxins, and inhibitor treatments suggest that auxin responsiveness and PIN-mediated auxin distribution play an important role in regulating root responses to mechanical impedance. The assessment of 21 Arabidopsis accessions revealed that primary root penetrability varies widely among accessions. To search for quantitative trait loci (QTLs) associated to root system penetrability, we evaluated a recombinant inbred population derived from Landsberg erecta (Ler-0, with a high primary root penetrability) and Shahdara (Sha, with a low primary root penetrability) accessions. QTL analysis revealed a major-effect QTL localized in chromosome 3, ROOT PENETRATION INDEX 3 (q-RPI3), which accounted for 29.98% (logarithm of odds=8.82) of the total phenotypic variation. Employing an introgression line (IL-321) with a homozygous q-RPI3 region from Sha in the Ler-0 genetic background, we demonstrated that q-RPI3 plays a crucial role in root penetrability. This multiscale study reveals new insights into root plasticity during the penetration process in hard agar layers, natural variation, and genetic architecture behind primary root penetrability in Arabidopsis.