bluuebunny/crossref_metadata_2025_split huggingface dataset:
Information preferences about treatment options in diffuse cutaneous systemic sclerosis: A Delphi consensus study
Authors: Spierings Julia , Nienhuis Hilde , van Lieshout Eva , van Laar Jacob M , Pieterse Arwen H 
Published: September 2021

Objectives: The aim of this study was to identify and prioritize aspects essential for decision making in patients with diffuse cutaneous systemic sclerosis (dcSSc) and to gain insight into information preferences of treatment options which could guide development of a leaflet for patients. Methods: A three-round Delphi study was conducted with a panel of patients with dcSSc. The questionnaire was based on a systematic literature search regarding benefits and harms of four main treatment options in dcSSc: methotrexate, mycophenolate mofetil, cyclophosphamide pulses and stem cell transplantation. Patients were asked to identify information that is essential for making a treatment decision. After the third round, a live, online discussion was held in order to reach consensus on these items and to discuss the content and design of the leaflet. Consensus was defined as ⩾75% agreement among panel members. Results: Of the 36 patients invited, 78% (n = 28) participated in one or more rounds, 67% (n = 24) completed the first, 69% (n = 25) the second and 75% (n = 27) the third round. In the last round, median age of participants was 51 years (interquartile range, 18) and median disease duration 4 years (interquartile range, 5); 52% were female. Patients had been treated with mycophenolate mofetil (67%), methotrexate (44%), cyclophosphamide (41%), autologous stem cell transplantation (26%), rituximab (4%) or were treatment-naïve (7%). Eight patients joined the live panel discussion. The panel reached consensus on seven benefits (prolonged progression-free survival, improved quality of life, improved daily functioning, improved pulmonary function, improved skin thickness, improved mobility and reduced fatigue) and four harms (treatment-related mortality, infections, cardiac damage, increased risk of cancer) as essential information for decision making. Also a design of a leaflet was made. Conclusion: This study identified information about treatment options in dcSSc that should be addressed with patients. Our results can be used to develop effective patient information.
Latent Medical Conditions of Drivers Involved in Road Traffic Collisions in Ghana: Implication from Autopsy Findings
Authors: Ossei Paul Poku Sampene , Agyeman-Duah Eric , Ayibor William Gilbert , Niako Nicholas , Safo Kwakye Foster 
Published: September 2021

Background: Unlike some neighboring countries like Nigeria, few studies on actual causes, impact and the prevention of road traffic collisions have been carried out in Ghana. There is the need for further research and this study sought to link injuries that caused the death of drivers involved in vehicular collisions to the latent possible contributing diseases and medical conditions in these drivers and how these conditions predispose them to the collisions. Methods: This is a retrospective study that used the forensic autopsy records of driver fatalities and various injuries and medical conditions of drivers involved in road traffic collisions. Information on all drivers was retrieved from archives at the Komfo Anokye Teaching Hospital’ Pathology Unit. Demographics and cause of death were used in selecting the cases, including all driver-related road traffic collisions from 2009 to 2014. Results: A total of 1842 road traffic collisions were recorded with 127 of them being driver related. There were 31 cases (24.4%) in 2014; the highest cases recorded for this study, with the least recorded in 2009 with only 12 cases (9.4%). There were 121 (95.3%) male drivers and 6 female drivers (4.7%). Most of the male drivers were between the ages of 30 and 39 with 39 cases, while that of females was between 40 and 49 years with 6 cases. There was no significant statistical correlation between age and sex ( P = .124). No statistical correlation also existed between sex and year ( P = .331). Pathologies of all body systems were established. Cardiovascular diseases were the most prevalent systemic medical condition seen in the drivers with 44.1%. Conclusion: The study established that the drivers had various latent medical conditions and all these could lead to possible incapacitation, affecting driver judgment, leading to collisions on the road. The National Road Safety Commission (NRSC) should request medical screening before issuing driver licenses.
Primary mediastinal large B-cell lymphoma
Authors: Savage Kerry J. 
Published: September 2021

Abstract
Primary mediastinal large B-cell lymphoma (PMBCL) is a separate entity in the World Health Organization’s classification, based on clinicopathologic features and a distinct molecular signature that overlaps with nodular sclerosis classic Hodgkin lymphoma (cHL). Molecular classifiers can distinguish PMBCL from diffuse large B-cell lymphoma (DLBCL) using ribonucleic acid derived from paraffin-embedded tissue and are integral to future studies. However, given that ∼5% of DLBCL can have a molecular PMBCL phenotype in the absence of mediastinal involvement, clinical information remains critical for diagnosis. Studies during the past 10 to 20 years have elucidated the biologic hallmarks of PMBCL that are reminiscent of cHL, including the importance of the JAK-STAT and NF-κB signaling pathways, as well as an immune evasion phenotype through multiple converging genetic aberrations. The outcome of PMBCL has improved in the modern rituximab era; however, whether there is a single standard treatment for all patients and when to integrate radiotherapy remains controversial. Regardless of the frontline therapy, refractory disease can occur in up to 10% of patients and correlates with poor outcome. With emerging data supporting the high efficacy of PD1 inhibitors in PMBCL, studies are underway that integrate them into the up-front setting.
Micro-scale Realization of Compliant Mechanisms: Manufacturing Processes and Constituent Materials—A Review
Authors: Wang Minchang , Ge Daohan , Zhang Liqiang , Herder Just L. 
Published: September 2021

AbstractCompliant micromechanisms (CMMs) acquire mobility from the deflection of elastic members and have been proven to be robust by millions of silicon MEMS devices. However, the limited deflection of silicon impedes the realization of more sophisticated CMMs, which often require larger deflections. Recently, some novel manufacturing processes have emerged but are not well known by the community. In this paper, the realization of CMMs is reviewed, aiming to provide help to mechanical designers to quickly find the proper realization method for their CMM designs. To this end, the literature surveyed was classified and statistically analyzed, and representative processes were summarized individually to reflect the state of the art of CMM manufacturing. Furthermore, the features of each process were collected into tables to facilitate the reference of readers, and the guidelines for process selection were discussed. The review results indicate that, even though the silicon process remains dominant, great progress has been made in the development of polymer-related and composite-related processes, such as micromolding, SU-8 process, laser ablation, 3D printing, and the CNT frameworking. These processes result in constituent materials with a lower Young’s modulus and larger maximum allowable strain than silicon, and therefore allow larger deflection. The geometrical capabilities (e.g., aspect ratio) of the realization methods should also be considered, because different types of CMMs have different requirements. We conclude that the SU-8 process, 3D printing, and carbon nanotube frameworking will play more important roles in the future owing to their excellent comprehensive capabilities.
Strategies and Structure Feature of the Aboveground and Belowground Microbial Community Respond to Drought in Wild Rice (Oryza longistaminata)
Authors: Xie Jian , Wang Xiaoqing , Xu Jiawang , Xie Hongwei , Cai Yaohui , Liu Yizheng , Ding Xia 
Published: September 2021

Abstract
Background
Drought is global environmental stress that limits crop yields. Plant-associated microbiomes play a crucial role in determining plant fitness in response to drought, yet the fundamental mechanisms for maintaining microbial community stability under drought disturbances in wild rice are poorly understood. We make explicit comparisons of leaf, stem, root and rhizosphere microbiomes from the drought-tolerant wild rice (Oryza longistaminata) in response to drought stress.

Results
We find that the response of the wild rice microbiome to drought was divided into aboveground–underground patterns. Drought reduced the leaf and stem microbial community diversity and networks stability, but not that of the roots and rhizospheres. Contrary to the aboveground microbial networks, the drought-negative response taxa exhibited much closer interconnections than the drought-positive response taxa and were the dominant network hubs of belowground co-occurrence networks, which may contribute to the stability of the belowground network. Notably, drought induces enrichment of Actinobacteria in belowground compartments, but not the aboveground compartment. Additionally, the rhizosphere microbiome exhibited a higher proportion of generalists and broader habitat niche breadth than the microbiome at other compartments, and drought enhanced the proportion of specialists in all compartments. Null model analysis revealed that both the aboveground and belowground-community were governed primarily by the stochastic assembly process, moreover, drought decreased ‘dispersal limitation’, and enhanced ‘drift’.

Conclusions
Our results provide new insight into the different strategies and assembly mechanisms of the above and belowground microbial community in response to drought, including enrichment of taxonomic groups, and highlight the important role of the stochastic assembly process in shaping microbial community under drought stress.
An iteration model for identifying essential proteins by combining comprehensive PPI network with biological information
Authors: Li Shiyuan , Zhang Zhen , Li Xueyong , Tan Yihong , Wang Lei , Chen Zhiping 
Published: September 2021

AbstractBackgroundEssential proteins have great impacts on cell survival and development, and played important roles in disease analysis and new drug design. However, since it is inefficient and costly to identify essential proteins by using biological experiments, then there is an urgent need for automated and accurate detection methods. In recent years, the recognition of essential proteins in protein interaction networks (PPI) has become a research hotspot, and many computational models for predicting essential proteins have been proposed successively.ResultsIn order to achieve higher prediction performance, in this paper, a new prediction model called TGSO is proposed. In TGSO, a protein aggregation degree network is constructed first by adopting the node density measurement method for complex networks. And simultaneously, a protein co-expression interactive network is constructed by combining the gene expression information with the network connectivity, and a protein co-localization interaction network is constructed based on the subcellular localization data. And then, through integrating these three kinds of newly constructed networks, a comprehensive protein–protein interaction network will be obtained. Finally, based on the homology information, scores can be calculated out iteratively for different proteins, which can be utilized to estimate the importance of proteins effectively. Moreover, in order to evaluate the identification performance of TGSO, we have compared TGSO with 13 different latest competitive methods based on three kinds of yeast databases. And experimental results show that TGSO can achieve identification accuracies of 94%, 82% and 72% out of the top 1%, 5% and 10% candidate proteins respectively, which are to some degree superior to these state-of-the-art competitive models.ConclusionsWe constructed a comprehensive interactive network based on multi-source data to reduce the noise and errors in the initial PPI, and combined with iterative methods to improve the accuracy of necessary protein prediction, and means that TGSO may be conducive to the future development of essential protein recognition as well.
DI2: prior-free and multi-item discretization of biological data and its applications
Authors: Alexandre Leonardo , Costa Rafael S. , Henriques Rui 
Published: September 2021

Abstract
Background
A considerable number of data mining approaches for biomedical data analysis, including state-of-the-art associative models, require a form of data discretization. Although diverse discretization approaches have been proposed, they generally work under a strict set of statistical assumptions which are arguably insufficient to handle the diversity and heterogeneity of clinical and molecular variables within a given dataset. In addition, although an increasing number of symbolic approaches in bioinformatics are able to assign multiple items to values occurring near discretization boundaries for superior robustness, there are no reference principles on how to perform multi-item discretizations.

Results
In this study, an unsupervised discretization method, DI2, for variables with arbitrarily skewed distributions is proposed. Statistical tests applied to assess differences in performance confirm that DI2 generally outperforms well-established discretizations methods with statistical significance. Within classification tasks, DI2 displays either competitive or superior levels of predictive accuracy, particularly delineate for classifiers able to accommodate border values.

Conclusions
This work proposes a new unsupervised method for data discretization, DI2, that takes into account the underlying data regularities, the presence of outlier values disrupting expected regularities, as well as the relevance of border values. DI2 is available at https://github.com/JupitersMight/DI2
RPocket: an intuitive database of RNA pocket topology information with RNA-ligand data resources
Authors: Zhou Ting , Wang Huiwen , Zeng Chen , Zhao Yunjie 
Published: September 2021

Abstract
Background
RNA regulates a variety of biological functions by interacting with other molecules. The ligand often binds in the RNA pocket to trigger structural changes or functions. Thus, it is essential to explore and visualize the RNA pocket to elucidate the structural and recognition mechanism for the RNA-ligand complex formation.

Results
In this work, we developed one user-friendly bioinformatics tool, RPocket. This database provides geometrical size, centroid, shape, secondary structure element for RNA pocket, RNA-ligand interaction information, and functional sites. We extracted 240 RNA pockets from 94 non-redundant RNA-ligand complex structures. We developed RPDescriptor to calculate the pocket geometrical property quantitatively. The geometrical information was then subjected to RNA-ligand binding analysis by incorporating the sequence, secondary structure, and geometrical combinations. This new approach takes advantage of both the atom-level precision of the structure and the nucleotide-level tertiary interactions. The results show that the higher-level topological pattern indeed improves the tertiary structure prediction. We also proposed a potential mechanism for RNA-ligand complex formation. The electrostatic interactions are responsible for long-range recognition, while the Van der Waals and hydrophobic contacts for short-range binding and optimization. These interaction pairs can be considered as distance constraints to guide complex structural modeling and drug design.

Conclusion
RPocket database would facilitate RNA-ligand engineering to regulate the complex formation for biological or medical applications. RPocket is available at http://zhaoserver.com.cn/RPocket/RPocket.html.
An integrated strategy for target SSR genotyping with toleration of nucleotide variations in the SSRs and flanking regions
Authors: Huo Yongxue , Zhao Yikun , Xu Liwen , Yi Hongmei , Zhang Yunlong , Jia Xianqing , Zhao Han , Zhao Jiuran , Wang Fengge 
Published: September 2021

Abstract
Background
With the broad application of high-throughput sequencing and its reduced cost, simple sequence repeat (SSR) genotyping by sequencing (SSR-GBS) has been widely used for interpreting genetic data across different fields, including population genetic diversity and structure analysis, the construction of genetic maps, and the investigation of intraspecies relationships. The development of accurate and efficient typing strategies for SSR-GBS is urgently needed and several tools have been published. However, to date, no suitable accurate genotyping method can tolerate single nucleotide variations (SNVs) in SSRs and flanking regions. These SNVs may be caused by PCR and sequencing errors or SNPs among varieties, and they directly affect sequence alignment and genotyping accuracy.

Results
Here, we report a new integrated strategy named the accurate microsatellite genotyping tool based on targeted sequencing (AMGT-TS) and provide a user-friendly web-based platform and command-line version of AMGT-TS. To handle SNVs in the SSRs or flanking regions, we developed a broad matching algorithm (BMA) that can quickly and accurately achieve SSR typing for ultradeep coverage and high-throughput analysis of loci with SNVs compatibility and grouping of typed reads for further in-depth information mining. To evaluate this tool, we tested 21 randomly sampled loci in eight maize varieties, accompanied by experimental validation on actual and simulated sequencing data. Our evaluation showed that, compared to other tools, AMGT-TS presented extremely accurate typing results with single base resolution for both homozygous and heterozygous samples.

Conclusion
This integrated strategy can achieve accurate SSR genotyping based on targeted sequencing, and it can tolerate single nucleotide variations in the SSRs and flanking regions. This method can be readily applied to divergent sequencing platforms and species and has excellent application prospects in genetic and population biology research. The web-based platform and command-line version of AMGT-TS are available at https://amgt-ts.plantdna.site:8445 and https://github.com/plantdna/amgt-ts, respectively.
How the seed coat affects the mother’s oviposition preference and larval performance in the bean beetle (Acanthoscelides obtectus, Coleoptera: Chrysomelidae, Bruchinae) in leguminous species
Authors: Szentesi Árpád 
Published: September 2021

Abstract
Background
The host specificity and host range of the dry bean beetle, Acanthoscelides obtectus (Coleoptera: Chrysomelidae, Bruchinae), a seed predator of beans, is poorly known. In addition, the female oviposition preference and larval performance relationship is complicated by the respective importance of seed coat and cotyledon, because, paradoxically, females lay eggs on the basis of stimuli of the seed coat alone, without directly being able to assess the quality of the cotyledon’s suitability for larval development. Conversely, the thickness of seed coat may prevent first instar larvae from entering the seeds, even if cotyledons are suitable for development.

Methods
The seeds of 62 leguminous species and 75 cultivars and accessions occurring in Hungary were evaluated for preference-performance relations. The preference of female bean beetles for seeds was measured in no-choice egg-laying tests. The ability of first instar larvae to overcome the seed coat as a physical barrier was tested with intact seed coat, while pre-drilled seed coats allowed the larvae to assess the suitability of cotyledon for development. The number of emerging adults was recorded. The thickness of seed coats and the weight of seeds were measured. Nonparametric tests and logistic regression were used for the statistical analyses of data and effect sizes were also calculated.

Results
Seeds of 18 leguminous species (35% of them Lathyrus) supported larval development to adults if the seed coat was pre-drilled; however, only nine leguminous species supported development to adults if the seed coat was intact. Seed coat thickness beyond a critical threshold of 0.1 mm strongly influenced survival of first instar larvae. There was no overall positive correlation between oviposition preference and larval performance, except for 16 so-called acceptable non-hosts (Kendall’s τ = 0.3088). A. obtectus females also showed an ovipositional hierarchy of legume species even in no-choice tests.

Conclusions
The results suggest that whereas the use of some acceptable non-host species by the A. obtectus is possible in seed stores, the same is unlikely under outdoor conditions, where the recognition of a diverse set of seed pod-related compounds would be necessary to induce egg-laying.
Association between the modified Nutrition Risk in Critically Ill (mNUTRIC) score and clinical outcomes in the intensive care unit: a secondary analysis of a large prospective observational study
Authors: Wang Na , Wang Mei-Ping , Jiang Li , Du Bin , Zhu Bo , Xi Xiu-Ming 
Published: September 2021

Abstract
Background
Malnutrition in intensive care unit (ICU) patients is associated with adverse clinical outcomes. The modified nutrition risk in the critically ill score (mNUTRIC) was proposed as an appropriate nutritional assessment tool in critically ill patients, but it has not been fully demonstrated and widely used. Our study was conducted to identify the nutritional risk in ICU patients using the mNUTRIC score and explore the relationship between 28-day mortality and high mNUTRIC scores.

Methods
This study is a secondary analysis, the data were extracted from The Beijing Acute Kidney Injury Trial (BAKIT). In total, 9049 patients were admitted consecutively, and 3107 patients with complete clinical data were included in this study. We divided the study population into high nutritional risk (mNUTRIC score ≥ 5 points) and low nutritional risk (mNUTRIC score < 5 points) groups. The predictive capacity of the mNUTRIC score was studied by receiver operating characteristic (ROC) curve analysis, appropriate cut-off was identified by highest combined sensitivity and specificity using Youden’s index. The significance level was set at 5%.

Results
Among the 3107 patients, the 28-day mortality rate was 17.4% (540 patients died). Nearly 28.2% of patients admitted to the ICU were at risk of malnutrition, high nutritional risk patients were older (P < 0.001), with higher illness severity scores than low nutritional risk patients. Multivariate analysis revealed that the mNUTRIC score was an independent risk factor for 28-day mortality and mortality increased with increasing scores (p = 0.000). The calculated area under curve (AUC) for the mNUTRIC score was 0.763 (CI 0.740–0.786). According to Youden’s index, we found a suitable cut-off > 4 for the mNUTRIC score to predict the 28-day mortality.

Conclusions
Patients admitted to the ICU were at high risk of malnutrition, and a high mNUTRIC score was associated with increased ICU length of stay and higher mortality. More large prospective studies are needed to demonstrate the validity of this score.

Trial registration
This study was registered at www.chictr.org.cn (registration number Chi CTR-ONC-11001875). Registered on 14 December 2011.