bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling the growth kinetics of cell suspensions of Randia echinocarpa and characterization of their bioactive phenolic compounds.
Authors: Aguilar-Camacho Miguel , Gómez-Sánchez Carlos Eduardo , Cruz-Mendivil Abraham , Guerrero-Analco José Antonio , Monribot-Villanueva Juan Luis , Gutiérrez-Uribe Janet 
Published: May 2023

Abstract
The fruit of Randia echinocarpa is commonly used in the Mexican tradicional medicine to treat different diseases and ailments. So, the establishment of cell suspension cultures (CSC) is a required alternative to obtain bioactive compounds from this plant. Moreover, good kinetic models are necessary good processes control and simulation of plant cell cultures. Therefore, the objective of this study was to model and estimate the growth kinetics of the CSC of R. echinocarpa, as well as characterize their phenolic profile by ultra performance liquid chromatography coupled to mass spectrometry. During the 34 d of culture, CSC of R. echinocarpa reached a dry cell biomass concentration of 15.16 g/L at day 20. The maximum specific growth rate (\({\mu }_{max}\)) was 0.15 d− 1, with a duplication time (\({t}_{d}\)) of 4.62 d. The Logistic model proposed adequately predicts the cell growth changes during the culture and the maximum dry cell content the culture medium can sustain (≈ 13.63 g/L). Ten phenolic compounds were identified in the biomass and four in the supernatants. The major phenolic compound in the biomass was chlorogenic acid (CA), with a concentration of 828.6 µg/g at day 20. In the lyophilized supernatant, the major phenolic compound was salicylic acid (SA) with a concentration of 172.7 µg/g at day 30. The production of CA was a growth-dependent process in contrast to the concentration of SA in the media. Our results indicate CSC of R. echinocarpa could be a sustainable source for the production of bioactive compounds such as CA and SA.
MOLE: Multi-Omics Learning to Extrapolate Proteome Expression
Authors: Pichugin Ilya , Kruglov Dmitrii , Ilgisonis Ekaterina , Ponomarenko Elena 
Published: May 2023

Abstract

Background
Complex multi-omics data requires interpretation on different levels of molecular biology processes. However, genomics and transcriptomics methods are more sensitive than proteomic methods because of PCR reaction and ability to multiply molecules to level enough for a successful detection. This forms the gap between thousands of genes with known RNA expression and hundreds of detected proteins.
Results
To predict a protein abundance by known RNA level in the sample we have used a 10-channels input convolutional model to store label-free LC-MS/MS data, amino acids sequence and database annotations in one tensor. The solution was designed as an extrapolating tool for online public web-usage as only light-weighted deep neural architectures with fast inference were used. The validation set was once created by 20% of proteins in used datasets. Validation results for the healthy human tissues dataset showed 0.58 R2 coefficient of determination and 0.71 Spearman correlation for all samples and up to 0.67 R2 per tissue. For the tumor cell lines dataset 0.54 R2 coefficient of determination and 0.71 Spearman correlation for all validation samples and up to 0.62 R2 per cell line.
Conclusion
The solution allows a researcher to use any annotation collections and modifiable amino acids sequence to extrapolate protein abundances with known RNA quantity in the sample. A one model – many datasets pipeline with comparable metrics was implemented.
WITHDRAWN: Long noncoding RNA Glis2 regulates podocyte apoptosis by mediating mitochondrial function in diabetic nephropathy
Authors: Wang Ting , Chen Yanxia , Liu Zhihong , Li Na , Shan Yue , He Yinxi 
Published: May 2023

Abstract
Objectives
Diabetic nephropathy (DN) is one of the most serious microvascular complications of diabetes and the main cause of end-stage kidney disease. Podocyte injury or apoptosis exerts a crucial role in the pathogenesis of DN. Recently, long noncoding RNAs (lncRNAs) have been gradually identified to be functional in a variety of different mechanisms associating with DN. However, the relationship between lncRNAs and podocyte apoptosis in DN is still in its infancy. This study aimed to investigate whether lncRNA Glis2 could regulate podocyte injury via miR-328-5p in DN and uncover the underlying mechanism.
Methods
Normal-glucose or high-glucose cultured podocytes and diabetic db/db mice were used to investigate the exact role and regulatory mechanism of lncRNA Glis2 on podocyte apoptosis in DN. Apoptosis rate of podocyte was detected by flow cytometry. Cell viability was measured using the Cell Counting Kit-8 colorimetric assay (CCK-8). The expressions of lncRNA Glis2 and miR-328-5p were measured by qRT-PCR. The relationship between lncRNA Glis2 and miR-328-5p was examined by dual luciferase reporter assay. Mitochondrial membrane potential (ΔΨM) was measured using JC-1 staining. Mitochondrial morphology was detected by MitoTracker Deep Red staining. Then, the histopathological and ultrastructure changes of renal tissues in diabetic mice were observed using periodic acid-Schiff (PAS) staining and transmission electron microscopy. Finally, the effect of lncRNA Glis2 on podocyte mitochondrial dysfunction and apoptosis through miR-328-5p/Sirt1 was detected by western blot.
Results
We found that lncRNA Glis2 was significantly downregulated in high-glucose cultured podocytes and renal tissues of db/db mice. Furthermore, lncRNA Glis2 overexpression or knockdown was found to regulate podocyte mitochondrial dysfunction and apoptosis. The direct interaction between lncRNA Glis2 and miR-328-5p was confirmed by dual luciferase reporter assay. LncRNA Glis2 overexpression alleviated podocyte mitochondrial dysfunction and apoptosis via miR-328-5p/Sirt1 pathway in podocytes and diabetic mice.
Conclusion
Taken together, this study demonstrated that lncRNA Glis2, acting as a competing endogenous RNA (ceRNA) of miRNA-328-5p, regulated Sirt1 mediated mitochondrial dysfunction and podocyte apoptosis in DN.
Artificial Intelligence and Geographic Analysis of Clinical Genetic Data in California’s Central Valley
Authors: Jackson Suellen , Freeman Rebecca , Noronha Adriana , Jamil Hafsah , Chavez Eric , Carmichael Jason , Ruiz Kaylee M. , Miller Christine , Benke Sarah , Perrot Rosalie , Hockley Maryam , Murphy Kady , Casillan Aimiel , Radanovich Lily , Deforest Roger , Nunes Mark E. , Sidlow Richard , Einhorn Yaron , Woods Jeremy 
Published: May 2023

Abstract
Introduction
Data science methodologies can be utilized to ascertain and analyze clinical genetic data that is often unstructured and rarely used outside of patient encounters.
Methods
Genetic variants from all genetic testing resulting to a large pediatric healthcare system for a five-year period were obtained and variants were reinterpreted utilizing the Franklin© Artificial Intelligence (AI). Utilizing PowerBI©, the data were further matched to patients in the electronic healthcare record and matched to demographic data to generate a variant data table and map variants as a choropleth.
Results
Three thousand sixty-five variants were identified and 98% were matched to patients with geographic data. Franklin© changed the interpretation for 27% of variants. A total of 723 Mendelian genetic disorders were identified with disorder prevalence estimation. Mapping of variants demonstrated hot-spots for pathogenic genetic variation such as PEX6-associated Zellweger Spectrum Disorder. Seven patients were identified with Bardet-Biedl syndrome and seven patients with Rett syndrome amenable to newly FDA-approved therapeutics.
Discussion
Utilizing readily available software we developed a database and Exploratory Data Analysis methodology enabling us to systematically reinterpret variants, estimate variant prevalence, identify patients amenable to new treatments, and localize geographies enriched for pathogenic variants.
Development of 89Zr and 68Ga-anti-CD103 Fab-fragments for PET imaging to non-invasively assess cancer reactive T cell infiltration--- Fab-based CD103 immunoPET
Authors: Fan Xiaoyu , Ważyńska Marta A. , Kol Arjan , Holland Noemi Perujo , Fernandes Bruna , Duijnhoven Sander M. j. van , Plat Annechein , Eenennaam Hans van , Elsinga Philip H. , Nijman Hans W. , de Bruyn Marco 
Published: May 2023

Abstract
Background CD103 is an integrin specifically expressed on the surface of cancer-reactive T cells. CD103 has been linked with better disease-specific survival in patients with ovarian, cervical, and endometrial cancer. The number of CD103+ T cells significantly increases during successful immunotherapy across human malignancies and therefore might be an attractive biomarker for non-invasive immune PET imaging of T cell infiltration. Indeed, we previously demonstrated that zirconium-89 (89Zr) radiolabeled anti-CD103 antibodies could be used for PET imaging of CD103+ T cells at relevant cell densities. However, the long half-life of antibodies precluded repeat imaging of CD103+ T cell dynamics early in therapy, and is associated with a significant radiation burden.Methods Two different anti-human CD103 Fab fragments radiolabeled with 89Zr or 68Ga were developed, namely 89Zr- hCD103 Fab and 68Ga-hCD103 Fab respectively. In vivo evaluation of these tracers was performed in nude mice (BALB/cOlaHsd-Foxn1nu) with established CD103-expressing CHO (CHO.CD103) or CHO wildtype (CHO.K1) xenografts, followed by serial PET imaging and ex vivo bio-distribution.Results In vivo, both 89Zr- and 68Ga- hCD103 Fab tracers showed high target-to-background ratios, high target site selectivity and high sensitivity in human CD103 positive xenografts.Conclusion We conclude that the two novel human CD103 immuno-PET tracers may be used for future non-invasive assessment of cancer reactive T cell infiltration. Consequently, both 89Zr and 68Ga- hCD103 Fab PET tracers should be explored in the clinical setting for stratification of patients who could benefit from immune checkpoint inhibition therapy.
Does the strategic use of Big Data alter outcomes in degenerative spine surgery? A study protocol for a multicenter clinical trial testing the Swespine Dialogue Support
Authors: Enger Eric Brisby , Valentin-Askman Ludvig , Hägg Olle , Fritzell Peter , Parai Catharina 
Published: May 2023

Abstract

Background

Patients surgically treated for lumbar spinal stenosis or cervical radiculopathy report improvement in approximately two out of three cases. Advancements in Machine Learning and the utility of large datasets have enabled the development of prognostic prediction models within spine surgery. This trial investigates if the use of the postoperative outcome prediction model, the Dialogue Support, can alter patient-reported outcome and satisfaction compared to current practice.

Methods

This is a prospective, multicenter clinical trial. Patients referred to a spine clinic with cervical radiculopathy or lumbar spinal stenosis will be screened for eligibility. Participants will be assessed at baseline upon recruitment and at 12 months follow-up. The Dialogue Support will be used on all participants, and they will thereafter be placed into either a surgical or a non-surgical treatment arm, depending on the decision made between patient and surgeon. The surgical treatment group will be studied separately based on diagnosis of either cervical radiculopathy or lumbar spinal stenosis. Both the surgical and the non-surgical group will be compared to a retrospective matched control group retrieved from the Swespine register, on which the Dialogue Support has not been used.
The primary outcome measure is global assessment regarding leg/arm pain in the surgical treatment group. Secondary outcome measures include patient satisfaction, Oswestry Disability Index (ODI), EQ-5D, and Numeric Rating Scales (NRS) for pain. In the non-surgical treatment group primary outcome measures are EQ-5D and mortality, as part of a selection bias analysis.

Discussion

The findings of this study may provide evidence on whether the use of an advanced digital decision tool can alter patient-reported outcomes after surgery.

Trial registration

The trial was retrospectively registered at ClinicalTrials.gov on April 17th, 2023, NCT05817747.
Cinderella wears hijab: Profiling and clustering the global market for hijabistas via Twitter text analytics
Authors: Mostafa Mohamed M. , Alanadoly Alshaimaa Bahgat 
Published: May 2023

AbstractConsumer-generated data provides a massive amount of market data that helps improve brands' decision-making processes within a highly demanding marketplace. This paper aims to investigate the dynamics behind Twitter user-generated content in relation to hijab/modest fashion based on a random sample of 144,800 tweets. Sentiment analysis was conducted, while a detection algorithm was implemented to identify the main influencers in relation to the hijab/modest fashion market. Results identify and profile the influencers and opinion leaders in the hijab/modest fashion global market. Results also show a high diversity of emojis usage in hijab-related tweets which highlighted the advantage of using them within hijab fashion brands’ communications. Finally, a partitioning around medoids (PAM) clustering method was applied to define consumer clusters. The clustering algorithm used highlights the heterogeneity and diversity of the global hijab fashion market. This study advances prior literature on the understanding of hijab/modest-fashion consumers and their opinions towards hijab brands. The study also helps marketers and decision-makers to understand consumer trends in this significant and emerging market.
X-Linked Alport Syndrome in girls: Clinicopathology, Genotype-phenotype analysis and Diagnostic Advantage of a5(IV) chain Staining on Paraffin section
Authors: Yang Xiaoqing , Shen Qian , Liu Jiaojiao , Yang Yueli , Ren Xianqing , Zhai Wensheng , Ding Ying , Zhang Xia , Yang Meng , Zhang Jian , Liu Bo , Xu Hong , Huang Yanjie 
Published: May 2023

Abstract

Background
X-linked Alport syndrome (XLAS) has been poorly studied in girls. The aim of this study was to investigate the clinicopathological features of XLAS in girls, and find out whether α5(IV) chain immunofluorescence staining on paraffin sections have a diagnositic advantage than on frozen sections.
Methods
The clinicopathological features and genotype-phenotype correlation were investigated retrospectively in 10 girls with XLAS. The expression of α5(IV) chain was compared between paraffin and frozen sections. The percentage of mosaic-positive glomeruli on paraffin sections was counted, and the correlation with proteinuria and age were evaluated. The literature on females with XLAS was reviewed.
Results
Among 10 girls with XLAS, 6 patients (60%) had intermittent attacks macroscopic hematuria with proteinuria or nephrotic-range proteinuria. Genotype–phenotype correlation was conducted and the results showed that the clinical manifestations of 3 girls with nonsense variants were all severe. Paraffin-embedded sections showed betterpreserved tissue architecture and more glomeruli than frozen sections. The detection rate of mosaic positive glomeruli on the paraffin sections was obviously increased from 60–100% when compared with the frozen section. The glomerular percentage of α5(IV) chain segmental deletion on the paraffin sections varied from 10.53–87.50% in different patients, and the percentage was not related with proteinuria and age.
Conclusions
Severe clinical manifestations can be seen in girls with XLAS, and nonsense mutant genotype may indicate severe clinical phenotypes. For girls with XLAS, α5(IV) chain staining should be done on paraffin sections to increase the detective rate of mosaic-positive glomeruli.
An expert generation model for accident analysis based on text data
Authors: Dongyang Yan , Li Keping , Qiaozhen Zhu , Gu Shuang , Liu Yanyan 
Published: May 2023

Abstract
As the narrative part to extend the accident-related content, text data can help understand the mechanism of accidents, which is always neglected in quantitative accident analysis. This paper presents a novel expert generation model to extract incidents from text reports for accident analysis. By using expert knowledge to complete the text labeling work, this paper uses a supervised text mining method to train the expert generation model. Then, the pre-trained language model is used to train the model for incident and relationship extraction. An application based on text dataset of Beijing metros is implemented to certify the effectiveness of the proposed methods. Two lines in Beijing metro are analyzed and the results of path analysis model show that different mechanism exists in the two lines, indicating that the high-order information extracted from text data is significant for understanding the incident, accident analysis, and accident prevention.
Association between the tumor lesion spatial distribution shown in PET/CT and the prognosis of patients with DLBCL receiving CAR T cell therapy
Authors: Dang Xiuyong , Li Ping , Zhu Zeyv , Zhang Min , Qian Wenbin , Liang Ai-Bin , Zhang Wenjun 
Published: May 2023

Abstract
Chimeric antigen receptor (CAR) T cell therapy improved the prognosis of patients with relapsed/refractory diffuse large B-cell lymphoma (DLBCL) significantly. Bulky disease and disease stage, as qualitative indicators of the spatial characteristic and distribution status of lymphoma lesions, have not been consistently confirmed to be associated with CAR T cell efficacy. Some researchers have proposed the conception of ‘tumor fragmentation’ and ‘lesion dissemination’, and suggested the association between those indicators and the prognosis of patients receiving chemotherapy. In this study, we reviewed and analysed the PET/CT of patients with DLBCL receiving CAR T cell therapy. We qualitatively described the tumor fragmentation using the tumor volume surface ratio (TVSR), which is the ratio of total metabolic tumor volume to total tumor surface, and we semi-quantitatively described the lesion dissemination using dissemination index (DI), which is the count of lesion invasion sites. We found that lower TVSR or lower DI indicates superior progression-free survival (PFS). Taking these two indicators into account at the same time, patients with lower TVSR and DI have the best prognosis, while patients with higher TVSR and DI have the worst. Overall, the tumor lesion spatial distribution shown in PET/CT before CAR T cell infusion are associated with the prognosis of patients with DLBCL receiving CAR T cell therapy. The lower the degree of tumor fragmentation or the higher the degree of lesion dissemination, the worse the prognosis of patients. They can jointly predict the prognosis.
Synphilin-1 as a modulator of aSyn assembly
Authors: Amen Triana , Gerhardt Ellen , Santos Patrícia , Milovanovic Dragomir , Höglinger Günter , Outeiro Tiago F. , Lazaro Diana 
Published: May 2023

Abstract
Alpha-synuclein (aSyn) is an intrinsically disordered protein associated with Parkinson’s disease and other synucleinopathies, where it accumulates in pathognomonic protein inclusions in the brain. However, both the physiological function and the pathological role of aSyn are still elusive. Unlike other proteins also prone to aggregation, expression of aSyn in cell models does not readily result in inclusion formation, and additional insults are required to induce aggregation. In this study, we report for the first time a model that recapitulates the aggregation cascade of aSyn. Our study sheds light on the role of synphilin-1 (Sph1) in aSyn assembly and localization. We show that Sph1 acts as a protein-adaptor for aSyn, and that the coiled-coil domain of Sph1 is essential for inducing inclusion formation. We also demonstrate that the interaction between Sph1 and aSyn can be modulated (genetically, protein levels and heat shock proteins), and that altering the expression levels of each protein affects inclusion size and number per cell. Our study highlights the potential importance of membrane binding for inclusion formation and the presence of lysosomes and AP-1 vesicles in the inclusions. Finally, our study demonstrates that further investigation is necessary to decipher the role of Sph1 and other aSyn-interacting proteins on its biology and pathobiology.
Real-life exposure to Fusarium toxins deoxynivalenol and zearalenone triggers apoptosis and activates NLRP3 inflammasome in bovine primary theca cells.
Authors: Cai Guodong , Guerrero-Netro Hilda Morayma , Bian Jianchun , Oswald Isabelle P , Price Christopher , Alassane-Kpembi Imourana 
Published: May 2023

Abstract
Cattle are deemed less susceptible to mycotoxins due to the limited internal exposure resulting from rumen microbiota activity. However, the significant amounts of Fusarium mycotoxins deoxynivalenol (DON) and zearalenone (ZEN) frequently detected in bovine follicular fluid samples suggest that they could affect ovarian function. Both mycotoxins trigger several patterns of cell death and activate the NLRP3 inflammasome in the intestine. In vitro studies have reported a number of adverse effects on bovine oocytes. However, the biological relevance of such findings with regard to realistic concentrations of DON and ZEN in bovine follicular fluid is still not clear. Hence, it is important to better characterize the effects of dietary exposure to DON and ZEN on the bovine ovary. Using bovine primary theca cells, this study investigated the effects of real-life patterns for bovine ovary exposure to DON and ZEN, but also DON metabolite DOM-1, on cell death and NLRP3 inflammasome activation. Exposure to DON starting from 0.1µM significantly decreased theca cell viability. The kinetics of phosphatidylserine translocation and loss of membrane integrity showed that ZEN and DON, but not DOM-1, induce an apoptotic phenotype. qPCR analysis of the expression of NLRP3, PYCARD, IL-1β, IL-18, and GSDMD in primary theca cells at concentrations of mycotoxin previously reported in cow follicular fluid clearly indicated that DON and DOM-1 individually and in mixture, but not ZEN, activate NLRP3 inflammasome. Altogether, these results suggest that current European Union guidance values for DON may not protect the bovine ovary from inflammatory disorders.
Backbone resonance assignments of the C-terminal region of human translation initiation factor eIF4B
Authors: Mondal Somnath , Rousseau Sabrina , Talenton Vincent , Thiam Cheikh Ahmadou Bamba , Aznauryan Mikayel , Mackereth Cameron D. 
Published: May 2023

Abstract
Translation initiation in eukaryotes is an early step in protein synthesis, requiring multiple factors to recruit the ribosomal small subunit to the mRNA 5’ untranslated region. One such protein factor is the eukaryotic translation initiation factor 4B (eIF4B), which increases the activity of the eIF4A RNA helicase, and is linked to cell survival and proliferation. We report here the protein backbone chemical shift assignments corresponding to the C-terminal 279 residues of human eIF4B. Analysis of the chemical shift values identifies one main helical region in the area previously linked to RNA binding, and confirms that the overall C-terminal region is intrinsically disordered.