bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transcriptome changes associated with apple (Malus domestica) root defense response after Fusarium proliferatum f. sp. malus domestica infection
Authors: Duan Yanan , Ma Shurui , Chen Xuesen , Shen Xiang , Yin Chengmiao , Mao Zhiquan 
Published: July 2022

Abstract
Background
Apple replant disease is a soilborne disease caused by Fusarium proliferatum f. sp. malus domestica strain MR5 (abbreviated hereafter as Fpmd MR5) in China. This pathogen causes root tissue rot and wilting leaves in apple seedlings, leading to plant death. A comparative transcriptome analysis was conducted using the Illumina Novaseq platform to identify the molecular defense mechanisms of the susceptible M.26 and the resistant M9T337 apple rootstocks to Fpmd MR5 infection.

Results
Approximately 518.1 million high-quality reads were generated using RNA sequencing (RNA-seq). Comparative analysis between the mock-inoculated and Fpmd MR5 infected apple rootstocks revealed 28,196 significantly differentially expressed genes (DEGs), including 14,572 up-regulated and 13,624 down-regulated genes. Among them, the transcriptomes in the roots of the susceptible genotype M.26 were reflected by overrepresented DEGs. MapMan analysis indicated that a large number of DEGs were involved in the response of apple plants to Fpmd MR5 stress. The important functional groups identified via gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were responsible for fundamental biological regulation, secondary metabolism, plant-pathogen recognition, and plant hormone signal transduction (ethylene and jasmonate). Furthermore, the expression of 33 up-regulated candidate genes (12 related to WRKY DNA-binding proteins, one encoding endochitinase, two encoding beta-glucosidases, ten related to pathogenesis-related proteins, and eight encoding ethylene-responsive transcription factors) were validated by quantitative real-time PCR.

Conclusion
RNA-seq profiling was performed for the first time to analyze response of apple root to Fpmd MR5 infection. We found that the production of antimicrobial compounds and antioxidants enhanced plant resistance to pathogens, and pathogenesis-related protein (PR10 homologs, chitinase, and beta-glucosidase) may play unique roles in the defense response. These results provide new insights into the mechanisms of the apple root response to Fpmd MR5 infection.
Bioactivities evaluation of an endophytic bacterial strain Bacillus velezensis JRX-YG39 inhabiting wild grape
Authors: Feng Baozhen , Chen Dandan , Jin Ruixue , Li Erqin , Li Peiqian 
Published: July 2022

Abstract
Background
Botrytis cinerea can cause serious disease on lots of plant hosts during growth and postharvest storage. Biocontrol is known to be eco-friendly methods to control pathogens. Plant endophytic bacteria are generally considered as beneficial organisms, since they can promote plant growth and enhance plant immune system. Thus, screening biological control agents is very important for sustainable plant protection.

Results
Fifty-six endophytic bacteria were obtained from wild grape. Sixteen isolates and their extracts exhibited significant antifungal activity against B. cinerea. Particularly, strain JRX-YG39 with the strongest inhibition ability had a broad-spectrum antifungal activity. Combining 16S rDNA analysis and the phylogenetic results based on gyrA and gyrB genes, JRX-YG39 was assigned as Bacillus velezensis. JRX-YG39 could produce bioactive VOCs and obviously depressed mycelia growth of B. cinerea. It was confirmed that VOCs released by JRX-YG39 could significantly promote growth and induce defense of Arabidopsis thaliana. Thirty-one bioactive secondary metabolites were further identified from JRX-YG39 culture by gas chromatography–mass spectrometry analysis. Dibutyl phthalate, a potential antifungal substance, was the major compound accounting for 78.65%.

Conclusions
B. velezensis JRX-YG39 has wide broad-spectrum antagonistic activity and significant plant promotion activity. Hence, B. velezensis JRX-YG39 will provide a valuable constituent of modern agricultural practice as biofertilizers and biocontrol agents.
COMPILE: a GWAS computational pipeline for gene discovery in complex genomes
Authors: Hill Matthew J. , Penning Bryan W. , McCann Maureen C. , Carpita Nicholas C. 
Published: July 2022

Abstract
Background
Genome-Wide Association Studies (GWAS) are used to identify genes and alleles that contribute to quantitative traits in large and genetically diverse populations. However, traits with complex genetic architectures create an enormous computational load for discovery of candidate genes with acceptable statistical certainty. We developed a streamlined computational pipeline for GWAS (COMPILE) to accelerate identification and annotation of candidate maize genes associated with a quantitative trait, and then matches maize genes to their closest rice and Arabidopsis homologs by sequence similarity.

Results
COMPILE executed GWAS using a Mixed Linear Model that incorporated, without compression, recent advancements in population structure control, then linked significant Quantitative Trait Loci (QTL) to candidate genes and RNA regulatory elements contained in any genome. COMPILE was validated using published data to identify QTL associated with the traits of α-tocopherol biosynthesis and flowering time, and identified published candidate genes as well as additional genes and non-coding RNAs. We then applied COMPILE to 274 genotypes of the maize Goodman Association Panel to identify candidate loci contributing to resistance of maize stems to penetration by larvae of the European Corn Borer (Ostrinia nubilalis). Candidate genes included those that encode a gene of unknown function, WRKY and MYB-like transcriptional factors, receptor-kinase signaling, riboflavin synthesis, nucleotide-sugar interconversion, and prolyl hydroxylation. Expression of the gene of unknown function has been associated with pathogen stress in maize and in rice homologs closest in sequence identity.

Conclusions
The relative speed of data analysis using COMPILE allowed comparison of population size and compression. Limitations in population size and diversity are major constraints for a trait and are not overcome by increasing marker density. COMPILE is customizable and is readily adaptable for application to species with robust genomic and proteome databases.
Empirical assessment of alternative methods for identifying seasonality in observational healthcare data
Authors: Molinaro Anthony , DeFalco Frank 
Published: July 2022

Abstract
Background
Seasonality classification is a well-known and important part of time series analysis. Understanding the seasonality of a biological event can contribute to an improved understanding of its causes and help guide appropriate responses. Observational data, however, are not comprised of biological events, but timestamped diagnosis codes the combination of which (along with additional requirements) are used as proxies for biological events. As there exist different methods for determining the seasonality of a time series, it is necessary to know if these methods exhibit concordance. In this study we seek to determine the concordance of these methods by applying them to time series derived from diagnosis codes in observational data residing in databases that vary in size, type, and provenance.

Methods
We compared 8 methods for determining the seasonality of a time series at three levels of significance (0.01, 0.05, and 0.1), against 10 observational health databases. We evaluated 61,467 time series at each level of significance, totaling 184,401 evaluations.

Results
Across all databases and levels of significance, concordance ranged from 20.2 to 40.2%. Across all databases and levels of significance, the proportion of time series classified seasonal ranged from 4.9 to 88.3%. For each database and level of significance, we computed the difference between the maximum and minimum proportion of time series classified seasonal by all methods. The median within-database difference was 54.8, 34.7, and 39.8%, for p < 0.01, 0.05, and 0.1, respectively.

Conclusion
Methods of binary seasonality classification when applied to time series derived from diagnosis codes in observational health data produce inconsistent results. The methods exhibit considerable discord within all databases, implying that the discord is a result of the difference between the methods themselves and not due to the choice of database. The results indicate that researchers relying on automated methods to assess the seasonality of time series derived from diagnosis codes in observational data should be aware that the methods are not interchangeable and thus the choice of method can affect the generalizability of their work. Seasonality determination is highly dependent on the method chosen.
A comparative study on deep learning models for text classification of unstructured medical notes with various levels of class imbalance
Authors: Lu Hongxia , Ehwerhemuepha Louis , Rakovski Cyril 
Published: July 2022

AbstractBackgroundDischarge medical notes written by physicians contain important information about the health condition of patients. Many deep learning algorithms have been successfully applied to extract important information from unstructured medical notes data that can entail subsequent actionable results in the medical domain. This study aims to explore the model performance of various deep learning algorithms in text classification tasks on medical notes with respect to different disease class imbalance scenarios.MethodsIn this study, we employed seven artificial intelligence models, a CNN (Convolutional Neural Network), a Transformer encoder, a pretrained BERT (Bidirectional Encoder Representations from Transformers), and four typical sequence neural networks models, namely, RNN (Recurrent Neural Network), GRU (Gated Recurrent Unit), LSTM (Long Short-Term Memory), and Bi-LSTM (Bi-directional Long Short-Term Memory) to classify the presence or absence of 16 disease conditions from patients’ discharge summary notes. We analyzed this question as a composition of 16 binary separate classification problems. The model performance of the seven models on each of the 16 datasets with various levels of imbalance between classes were compared in terms of AUC-ROC (Area Under the Curve of the Receiver Operating Characteristic), AUC-PR (Area Under the Curve of Precision and Recall), F1 Score, and Balanced Accuracy as well as the training time. The model performances were also compared in combination with different word embedding approaches (GloVe, BioWordVec, and no pre-trained word embeddings).ResultsThe analyses of these 16 binary classification problems showed that the Transformer encoder model performs the best in nearly all scenarios. In addition, when the disease prevalence is close to or greater than 50%, the Convolutional Neural Network model achieved a comparable performance to the Transformer encoder, and its training time was 17.6% shorter than the second fastest model, 91.3% shorter than the Transformer encoder, and 94.7% shorter than the pre-trained BERT-Base model. The BioWordVec embeddings slightly improved the performance of the Bi-LSTM model in most disease prevalence scenarios, while the CNN model performed better without pre-trained word embeddings. In addition, the training time was significantly reduced with the GloVe embeddings for all models.ConclusionsFor classification tasks on medical notes, Transformer encoders are the best choice if the computation resource is not an issue. Otherwise, when the classes are relatively balanced, CNNs are a leading candidate because of their competitive performance and computational efficiency.
Incidence and risk factors of nasogastric feeding intolerance in moderately-severe to severe acute pancreatitis
Authors: Lin Jiajia , Lv Cheng , Wu Cuili , Zhang He , Liu Zirui , Ke Lu , Li Gang , Tong Zhihui , Tu Jianfeng , Li Weiqin 
Published: July 2022

AbstractBackgroundThe importance of enteral nutrition (EN) in acute pancreatitis (AP) has been emphasised. Nasogastric (NG) feeding has been the preferred route for EN delivery in most AP patients intolerant to oral intake. However, gastric feeding intolerance (GFI) was frequently reported, especially in patients with more severe diseases. This study aimed to investigate the incidence and risk factors for GFI in moderately-severe to severe AP.MethodsThis is a single-centre, retrospective study. All the data were extracted from an electronic database from April 2020 to May 2021. Data were prospectively collected during hospitalisation. Patients diagnosed with moderately-severe to severe AP and admitted within seven days from the onset of abdominal pain were assessed for eligibility. Patients who showed signs of intolerance to gastric feeding and required switching to nasojejunal (NJ) feeding were deemed GFI. Multivariable logistic regression was performed to assess potential risk factors of GFI.ResultsA total of 93 patients were analysed, of whom 24 were deemed GFI (25.8%), and the rest tolerated NG feeding well (n = 69). In patients with GFI, the median time of switching to NJ feeding was five days (interquartile range: 4–7 days) after admission. The multivariable analysis showed that respiratory failure (odds ratio = 3.135, 95% CI: 1.111–8.848,P = 0.031) was an independent risk factor for GFI.The mean daily energy delivery in the following three days after switching to NJ feeding was significantly higher than the first three days after initiation of NG feeding in patients with GFI [920.83 (493.33–1326) vs. 465 (252.25–556.67) kcal,P < 0.001].ConclusionGFI is common in moderately-severe to severe AP patients with an incidence of 25.8%, and the presence of respiratory failure may increase the risk of GFI.
The impact of treatment with bile acid sequestrants on quality of life in patients with bile acid diarrhoea
Authors: Kumar Aditi , Galbraith Niall , Al-Hassi Hafid O. , Jain Manushri , Phipps Oliver , Butterworth Jeffrey , Steed Helen , McLaughlin John , Brookes Matthew J. 
Published: July 2022

Abstract
Background
Bile acid diarrhoea (BAD) can be severely debilitating and negatively affect patients’ quality of life (QoL). We carried out a multi-centre prospective study exploring QoL outcomes in patients with BAD after treatment with colesevelam.

Methods
Patients with or without a positive 23-seleno-25-homotaurocholic acid (SeHCAT) scan were recruited and categorised into four groups: SeHCAT negative control group (CG), idiopathic BAD, post-cholecystectomy (PC) and post-terminal ileal resection for Crohn’s disease (CD). Patients with a positive SeHCAT were treated with colesevelam and dosing was titrated to symptomatic response. Patients were reviewed at 4- and 8-weekly intervals and QoL was evaluated by EQ-5D-3L, SF-36, IBDQ-32 at each visit (where relevant). Patients with a negative SeHCAT (CG cohort) completed one set of questionnaires before being discharged from the study.

Results
47 patients (BAD = 24, PC = 12, CD = 11) completed paired QoL questionnaires before and after treatment and 30 CG patients completed a baseline questionnaire. There was a significant improvement in IBDQ-32 mean scores before and after treatment in CD patients [134.6 (95%CI 112.5–156.6) and 158.4 (136.1–180.6), respectively (p = 0.007). Following treatment, BAD patients had significantly improved mean SF-36 scores in the “Role limitation due to physical health” dimension (p = 0.02) and in the overall mental component summary (p = 0.03). Prior to starting treatment, BAD patients had the lowest scores in the ‘activity’ dimension of the EQ-5D-3L (p = 0.04), which improved significantly after treatment (p = 0.002). Overall, the BAD and CD cohort showed improved mean scores with treatment in all components of the SF-36 and EQ-5D-3L, while the PC cohort showed a general decline in mean scores after treatment. 55% of patients clinically responded to treatment of which 41.7%, 58.3% and 81.8% responded from the BAD, PC and CD groups respectively. Correlations between those deemed as responders with improvements on the SF-36 and EQ-5D dimensions were not statistically significant.

Conclusion
Our results demonstrate improved QoL in the BAD and CD cohort with treatment. Further larger studies are recommended specifically investigating the PC cohort and whether patients may improve with newer treatments such as FXR agonists.
Trial registration Ethical approval REC Ref: 16/LO/1325.
Alternative splicing of Apoptosis Stimulating Protein of TP53-2 (ASPP2) results in an oncogenic isoform promoting migration and therapy resistance in soft tissue sarcoma (STS)
Authors: Tsintari Vasileia , Walter Bianca , Fend Falko , Overkamp Mathis , Rothermundt Christian , Lopez Charles D. , Schittenhelm Marcus M. , Kampa-Schittenhelm Kerstin M. 
Published: July 2022

Abstract
Background
Metastatic soft tissue sarcoma (STS) are a heterogeneous group of malignancies which are not curable with chemotherapy alone. Therefore, understanding the molecular mechanisms of sarcomagenesis and therapy resistance remains a critical clinical need. ASPP2 is a tumor suppressor, that functions through both p53-dependent and p53-independent mechanisms. We recently described a dominant-negative ASPP2 isoform (ASPP2κ), that is overexpressed in human leukemias to promote therapy resistance. However, ASPP2κ has never been studied in STS.

Materials and methods
Expression of ASPP2κ was quantified in human rhabdomyosarcoma tumors using immunohistochemistry and qRT-PCR from formalin-fixed paraffin-embedded (FFPE) and snap-frozen tissue. To study the functional role of ASPP2κ in rhabdomyosarcoma, isogenic cell lines were generated by lentiviral transduction with short RNA hairpins to silence ASPP2κ expression. These engineered cell lines were used to assess the consequences of ASPP2κ silencing on cellular proliferation, migration and sensitivity to damage-induced apoptosis. Statistical analyses were performed using Student’s t-test and 2-way ANOVA.

Results
We found elevated ASPP2κ mRNA in different soft tissue sarcoma cell lines, representing five different sarcoma sub-entities. We found that ASSP2κ mRNA expression levels were induced in these cell lines by cell-stress. Importantly, we found that the median ASPP2κ expression level was higher in human rhabdomyosarcoma in comparison to a pool of tumor-free tissue. Moreover, ASPP2κ levels were elevated in patient tumor samples versus adjacent tumor-free tissue within individual patients. Using isogenic cell line models with silenced ASPP2κ expression, we found that suppression of ASPP2κ enhanced chemotherapy-induced apoptosis and attenuated cellular proliferation.

Conclusion
Detection of oncogenic ASPP2κ in human sarcoma provides new insights into sarcoma tumor biology. Our data supports the notion that ASPP2κ promotes sarcomagenesis and resistance to therapy. These observations provide the rationale for further evaluation of ASPP2κ as an oncogenic driver as well as a prognostic tool and potential therapeutic target in STS.
Electronic patient-reported monitoring of symptoms during follow-up of ovarian cancer patients: a feasibility study
Authors: Kennedy Fiona , Shearsmith Leanne , Holmes Marie , Rogers Zoe , Carter Rob , Hofmann Uschi , Velikova Galina 
Published: July 2022

Abstract
Background
Ovarian cancer patients require monitoring for relapse. Innovative follow-up methods are increasingly being explored. An electronic patient-reported outcome (ePRO) follow-up pathway was developed for women treated for ovarian cancer. This feasibility study explored patient acceptability and compliance.

Methods
A single-arm non-blinded prospective feasibility study was undertaken at two hospitals. Participants were women who had completed treatment for ovarian cancer whose clinician was happy for them to be monitored remotely. Automated 3-monthly reminders were sent to participants to complete an ePRO questionnaire and obtain blood tests. Participants were reviewed over the phone by their clinical nurse specialist instead of attending clinic-based follow-up. The primary outcome was compliance (expected ePRO completions/blood tests) across the 12-month study period. Secondary outcomes were recruitment, attrition, resource use, symptom severity/alerts and patient acceptability.

Results
Twenty-four women consented (50% consent rate), and 13 remained on study at 12 months. Seven women relapsed, 3 chose to withdraw, and 1 withdrew for other clinical reasons. ePRO compliance was high and consistent at 75-82%, although the two hospitals differed. Adherence to the clinical protocol was evident for blood tests and contacts with staff (fewer visits, more phonecalls compared to an earlier audit). End-of-study feedback indicated high patient satisfaction.

Conclusions
Remote ePRO follow-up for ovarian cancer is feasible and acceptable to patients who are able and willing to participate. However, the low recruitment rate (ineligible + declined) indicate it is not suitable/acceptable to all patients immediately post-treatment. Further large-scale research and implementation work is required, especially in a post-COVID era.

Trial registration
ClinicalTrials.gov ID: NCT02847715 (first registered 19/05/2016).
Genetic analysis of Japanese patients with small bowel adenocarcinoma using next-generation sequencing
Authors: Tatsuguchi Atsushi , Yamada Takeshi , Ueda Koji , Furuki Hiroyasu , Hoshimoto Aitoshi , Nishimoto Takayoshi , Omori Jun , Akimoto Naohiko , Gudis Katya , Tanaka Shu , Fujimori Shunji , Shimizu Akira , Iwakiri Katsuhiko 
Published: July 2022

Abstract
Background
Small bowel adenocarcinomas (SBAs) are rare and there is little comprehensive data on SBA genomic alterations for Asian patients. This study aimed to profile genomic alterations of SBA in Japanese patients using targeted next-generation sequencing (NGS).

Methods
We examined 22 surgical resections from patients with primary SBA. SBA genomic alterations were analyzed by NGS. Mismatch repair (MMR) status was determined by immunohistochemical analysis. Mucin phenotypes were classified as gastric (G), intestinal (I), gastrointestinal (GI), and null (N) types on MUC2, MUC5AC, MUC6, and CD10 immunostaining.

Results
The most common genomic alterations found in SBA tumors were TP53 (n = 16), followed by KRAS (n = 6), APC (n = 5), PIK3CA (n = 4), CTNNB1 (n = 3), KIT (n = 2), BRAF (n = 2), CDKN2A (n = 2), and PTEN (n = 2). Deficient MMR tumors were observed in 6 out of 22 patients. Tumor mucin phenotypes included 2 in G-type, 12 in I-type, 3 in GI-type, and 5 in N-type. APC and CTNNB1 mutations were not found in G-type and GI-type tumors. KRAS mutations were found in all tumor types except for G-type tumors. TP53 mutations were found in all tumor types. Although no single gene mutation was associated with overall survival (OS), we found that KRAS mutations were associated with significant worse OS in patients with proficient MMR tumors.

Conclusions
SBA genomic alterations in Japanese patients do not differ significantly from those reports in Western countries. Tumor localization, mucin phenotype, and MMR status all appear to impact SBA gene mutations.