bluuebunny/crossref_metadata_2025_split huggingface dataset:
Loss of sphingosine kinase 2 promotes the expansion of hematopoietic stem cells by improving their metabolic fitness
Authors: Li Changzheng , Wu Binghuo , Li Yishan , Liu Yaxi , Wang Jin , Xie Jiayi , Xu Xi , Tian Xiaobin , Ye Zhitao , Guan Jingjing , Chen Jie , Xie Siyu , Zhang Baolin , Cai Boyong , Wang Qianhao , Yu Haopeng , Lan Tian , Man Cheuk Him , Kang Xunlei , Qian Pengxu , Perry John M. , He Aibin , Jiang Linjia , Zhao Meng 
Published: July 2022

Abstract
Hematopoietic stem cells (HSCs) have reduced capacities to properly maintain and replenish the hematopoietic system during myelosuppressive injury or aging. Expanding and rejuvenating HSCs for therapeutic purposes has been a long-sought goal with limited progress. Here, we show that the enzyme Sphk2 (sphingosine kinase 2), which generates the lipid metabolite sphingosine-1-phosphate, is highly expressed in HSCs. The deletion of Sphk2 markedly promotes self-renewal and increases the regenerative potential of HSCs. More importantly, Sphk2 deletion globally preserves the young HSC gene expression pattern, improves the function, and sustains the multilineage potential of HSCs during aging. Mechanistically, Sphk2 interacts with prolyl hydroxylase 2 and the Von Hippel-Lindau protein to facilitate HIF1α ubiquitination in the nucleus independent of the Sphk2 catalytic activity. Deletion of Sphk2 increases hypoxic responses by stabilizing the HIF1α protein to upregulate PDK3, a glycolysis checkpoint protein for HSC quiescence, which subsequently enhances the function of HSCs by improving their metabolic fitness; specifically, it enhances anaerobic glycolysis but suppresses mitochondrial oxidative phosphorylation and generation of reactive oxygen species. Overall, targeting Sphk2 to enhance the metabolic fitness of HSCs is a promising strategy to expand and rejuvenate functional HSCs.
Quercetin as a JAK–STAT inhibitor: a potential role in solid tumors and neurodegenerative diseases
Authors: Zalpoor Hamidreza , Nabi-Afjadi Mohsen , Forghaniesfidvajani Razieh , Tavakol Chanour , Farahighasreaboonasr Faranak , Pakizeh Farid , Dana Vahid Ghobadi , Seif Farhad 
Published: July 2022

AbstractThe Janus kinase–signal transducer and activator of transcription (JAK–STAT) pathway is involved in many immunological processes, including cell growth, proliferation, differentiation, apoptosis, and inflammatory responses. Some of these processes can contribute to cancer progression and neurodegeneration. Owing to the complexity of this pathway and its potential crosstalk with alternative pathways, monotherapy as targeted therapy has usually limited long-term efficacy. Currently, the majority of JAK–STAT-targeting drugs are still at preclinical stages. Meanwhile, a variety of plant polyphenols, especially quercetin, exert their inhibitory effects on the JAK–STAT pathway through known and unknown mechanisms. Quercetin has shown prominent inhibitory effects on the JAK–STAT pathway in terms of anti-inflammatory and antitumor activity, as well as control of neurodegenerative diseases. This review discusses the pharmacological effects of quercetin on the JAK–STAT signaling pathway in solid tumors and neurodegenerative diseases.
DNA methylation-mediated differential expression of DLX4 isoforms has opposing roles in leukemogenesis
Authors: Zhou Jing-dong , Zhao Yang-jing , Leng Jia-yan , Gu Yu , Xu Zi-jun , Ma Ji-chun , Wen Xiang-mei , Lin Jiang , Zhang Ting-juan , Qian Jun 
Published: July 2022

AbstractBackgroundPreviously, we reported the expression ofDLX4isoforms (BP1andDLX7) in myeloid leukemia, but the functional role ofDLX4isoforms remains poorly understood. In the work described herein, we further determined the underlying role ofDLX4isoforms in chronic myeloid leukemia (CML) leukemogenesis.MethodsThe expression and methylation ofDLX4isoforms were detected by real-time quantitative PCR (RT-qPCR) and real-time quantitative methylation-specific PCR (RT-qMSP) in patients with CML. The functional role ofDLX4isoforms was determined in vitro and in vivo. The molecular mechanism ofDLX4isoforms in leukemogenesis was identified based on chromatin immunoprecipitation with high-throughput sequencing (ChIP-Seq)/assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-Seq) and RNA sequencing (RNA-Seq).ResultsBP1expression was increased in patients with CML with unmethylated promoter, butDLX7expression was decreased with hypermethylated promoter. Functionally, overexpression ofBP1increased the proliferation rate of K562 cells with S/G2 promotion, whereasDLX7overexpression reduced the proliferation rate of K562 cells with G1 arrest. Moreover, K562 cells withBP1overexpression increased the tumorigenicity in NCG mice, whereas K562 cells withDLX7overexpression decreased the tumorigenicity. Mechanistically, a total of 91 genes including 79 messenger RNAs (mRNAs) and 12 long noncoding RNAs (lncRNAs) were discovered by ChIP-Seq and RNA-Seq as direct downstream targets ofBP1. Among the downstream genes, knockdown ofRREB1andSGMS1-AS1partially revived the proliferation caused byBP1overexpression in K562 cells. Similarly, using ATAC-Seq and RNA-Seq, a total of 282 genes including 151 mRNA and 131 lncRNAs were identified as direct downstream targets ofDLX7. Knockdown of downstream genesPTPRBandNEAT1partially revived the proliferation caused byDLX7overexpression in K562 cells. Finally, we also identified and validated aSGMS1-AS1/miR-181d-5p/SRPK2competing endogenous RNA (ceRNA) network caused byBP1overexpression in K562 cells.ConclusionsThe current findings reveal that DNA methylation-mediated differential expression ofDLX4isoformsBP1andDLX7plays opposite functions in leukemogenesis.BP1plays an oncogenic role in leukemia development, whereasDLX7acts as a tumor suppressor gene. These results suggestDLX4as a therapeutic target for antileukemia therapy.
A novel biomarker selection method combining graph neural network and gene relationships applied to microarray data
Authors: Xie Weidong , Li Wei , Zhang Shoujia , Wang Linjie , Yang Jinzhu , Zhao Dazhe 
Published: July 2022

Abstract
Background
The discovery of critical biomarkers is significant for clinical diagnosis, drug research and development. Researchers usually obtain biomarkers from microarray data, which comes from the dimensional curse. Feature selection in machine learning is usually used to solve this problem. However, most methods do not fully consider feature dependence, especially the real pathway relationship of genes.

Results
Experimental results show that the proposed method is superior to classical algorithms and advanced methods in feature number and accuracy, and the selected features have more significance.

Method
This paper proposes a feature selection method based on a graph neural network. The proposed method uses the actual dependencies between features and the Pearson correlation coefficient to construct graph-structured data. The information dissemination and aggregation operations based on graph neural network are applied to fuse node information on graph structured data. The redundant features are clustered by the spectral clustering method. Then, the feature ranking aggregation model using eight feature evaluation methods acts on each clustering sub-cluster for different feature selection.

Conclusion
The proposed method can effectively remove redundant features. The algorithm’s output has high stability and classification accuracy, which can potentially select potential biomarkers.
IDPsBind: a repository of binding sites for intrinsically disordered proteins complexes with known 3D structures
Authors: Sun CanZhuang , Feng YongE , Fan GuoLiang 
Published: July 2022

Abstract
Background
Intrinsically disordered proteins (IDPs) lack a stable three-dimensional structure under physiological conditions but play crucial roles in many biological processes. Intrinsically disordered proteins perform various biological functions by interacting with other ligands.

Results
Here, we present a database, IDPsBind, which displays interacting sites between IDPs and interacting ligands by using the distance threshold method in known 3D structure IDPs complexes from the PDB database. IDPsBind contains 9626 IDPs complexes and 880 intrinsically disordered proteins verified by experiments. The current release of the IDPsBind database is defined as version 1.0. IDPsBind is freely accessible at http://www.s-bioinformatics.cn/idpsbind/home/.

Conclusions
IDPsBind provides more comprehensive interaction sites for IDPs complexes of known 3D structures. It can not only help the subsequent studies of the interaction mechanism of intrinsically disordered proteins but also provides a suitable background for developing the algorithms for predicting the interaction sites of intrinsically disordered proteins.
Artemisia argyi allelopathy: a generalist compromises hormone balance, element absorption, and photosynthesis of receptor plants
Authors: Li Jinxin , Zhao Tingting , Chen Le , Chen Hong , Luo Dandan , Chen Changjie , Miao Yuhuan , Liu Dahui 
Published: July 2022

Abstract
Background
Allelopathy is expressed through the release of plant chemicals and is considered a natural alternative for sustainable weed management. Artemisia argyi (A. argyi) is widely distributed throughout Asia, and often dominates fields due to its strong allelopathy. However, the mechanism of A. argyi allelopathy is largely unknown and need to be elucidated at the physiological and molecular levels.

Results
In this study, we used electron microscopy, ionomics analysis, phytohormone profiling, and transcriptome analysis to investigate the physiological and molecular mechanisms of A. argyi allelopathy using the model plant rice (Oryza sativa) as receptor plants. A. argyi water extract (AAWE)-treated rice plants grow poorly and display root morphological anomalies and leaf yellowing. We found that AAWE significantly inhibits rice growth by destroying the root and leaf system in multiple ways, including the integrity of ultrastructure, reactive oxygen species (ROS) homeostasis, and the accumulation of soluble sugar and chlorophyll synthesis. Further detection of the hormone contents suggests that AAWE leads to indole-3-acetic acid (IAA) accumulation in roots. Moreover, ionomics analysis shows that AAWE inhibits the absorption and transportation of photosynthesis-essential mineral elements, especially Mg, Fe, and Mn. In addition, the results of transcriptome analysis revealed that AAWE affects a series of crucial primary metabolic processes comprising photosynthesis in rice plants.

Conclusions
This study indicates that A. argyi realizes its strongly allelopathy through comprehensive effects on recipient plants including large-scale IAA synthesis and accumulation, ROS explosion, damaging the membrane system and organelles, and obstructing ion absorption and transport, photosynthesis and other pivotal primary metabolic processes of plants. Therefore, AAWE could potentially be developed as an environmentally friendly botanical herbicide due to its strong allelopathic effects.
Adaptive responses of carbon and nitrogen metabolisms to nitrogen-deficiency in Citrus sinensis seedlings
Authors: Huang Wei-Tao , Zheng Zhi-Chao , Hua Dan , Chen Xu-Feng , Zhang Jiang , Chen Huan-Huan , Ye Xin , Guo Jiu-Xin , Yang Lin-Tong , Chen Li-Song 
Published: July 2022

Abstract
Background
In China, nitrogen (N)-deficiency often occurs in Citrus orchards, which is one of the main causes of yield loss and fruit quality decline. Little information is known about the adaptive responses of Citrus carbon (C) and N metabolisms to N-deficiency. Seedlings of ‘Xuegan’ (Citrus sinensis (L.) Osbeck) were supplied with nutrient solution at an N concentration of 0 (N-deficiency), 5, 10, 15 or 20 mM for 10 weeks. Thereafter, we examined the effects of N supply on the levels of C and N in roots, stems and leaves, and the levels of organic acids, nonstructural carbohydrates, NH4+-N, NO3−-N, total soluble proteins, free amino acids (FAAs) and derivatives (FAADs), and the activities of key enzymes related to N assimilation and organic acid metabolism in roots and leaves.

Results
N-deficiency elevated sucrose export from leaves to roots, C and N distributions in roots and C/N ratio in roots, stems and leaves, thus enhancing root dry weight/shoot dry weight ratio and N use efficiency. N-deficient leaves displayed decreased accumulation of starch and total nonstructural carbohydrates (TNC) and increased sucrose/starch ratio as well as a partitioning trend of assimilated C toward to sucrose, but N-deficient roots displayed elevated accumulation of starch and TNC and reduced sucrose/starch ratio as well as a partitioning trend of assimilated C toward to starch. N-deficiency reduced the concentrations of most FAADs and the ratios of total FAADs (TFAADs)/N in leaves and roots. N-deficiency reduced the demand for C skeleton precursors for amino acid biosynthesis, thus lowering TFAADs/C ratio in leaves and roots. N-deficiency increased (decreased) the relative amounts of C-rich (N-rich) FAADs, thus increasing the molar ratio of C/N in TFAADs in leaves and roots.

Conclusions
Our findings corroborated our hypothesis that C and N metabolisms displayed adaptive responses to N-deficiency in C. sinensis seedlings, and that some differences existed between roots and leaves in N-deficiency-induced alterations of and C and N metabolisms.
Early and midterm results of frozen elephant trunk operation with Evita open stent-graft in patients with Marfan syndrome: results of a multicentre study
Authors: Widenka Kazimierz Jan , Kosiorowska Monika , Jakob Heinz , Pacini Davide , Hemmer Wolfgang , Grabenwoeger Martin , Sioris Thanos , Moritz Anton , Tsagakis Konstantinos 
Published: July 2022

Abstract
Background
Endovascular treatment of patients with Marfan syndrome (MFS) is not recommended. Hybrid procedures such as frozen elephant trunk (FET), which combines stent-graft deployment with an integrated non-stented fabric graft for proximal grafting and suturing, have not been previously evaluated. The aim of this study was to assess the safety and feasibility of FET operation in patients with MFS.

Methods
Patients enrolled in the International E-vita Open Registry (IEOR) who underwent FET procedure between January 2001 and February 2020 meeting Ghent criteria for MFS were included in the study. Early and midterm results were retrospectively analyzed. Preoperative, postoperative and follow-up computed tomography angiography scans were analysed.

Results
We analyzed 37 patients [mean age 38 ± 11 years, 65% men]. Acute or chronic aortic dissection was present in 35 (95%) patients (14 and 21 patients respectively). Two (5%) patients had an aneurysm without dissection. Malperfusion syndrome was present in 4 patients. Twenty-nine (78%) patients had history of aortic surgical interventions. The 30-day and in-hospital mortality amounted to 8 and 14% respectively. False lumen exclusion was present in 73% in stented segment in last postoperative CT. The overall 5-year survival was 71% and freedom from reintervention downstream was 58% at 5 years. Of the nine patients who required reintervention for distal aortic disease, one patient died.

Conclusions
FET operation for patients with MFS can be performed with acceptable mortality and morbidity. In long-term follow-up no reinterventions on the aortic arch were required. FET allows for easier second stage operations providing platform for surgical and endovascular reinterventions.
Survival prediction models: an introduction to discrete-time modeling
Authors: Suresh Krithika , Severn Cameron , Ghosh Debashis 
Published: July 2022

AbstractBackgroundPrediction models for time-to-event outcomes are commonly used in biomedical research to obtain subject-specific probabilities that aid in making important clinical care decisions. There are several regression and machine learning methods for building these models that have been designed or modified to account for the censoring that occurs in time-to-event data. Discrete-time survival models, which have often been overlooked in the literature, provide an alternative approach for predictive modeling in the presence of censoring with limited loss in predictive accuracy. These models can take advantage of the range of nonparametric machine learning classification algorithms and their available software to predict survival outcomes.MethodsDiscrete-time survival models are applied to a person-period data set to predict the hazard of experiencing the failure event in pre-specified time intervals. This framework allows for any binary classification method to be applied to predict these conditional survival probabilities. Using time-dependent performance metrics that account for censoring, we compare the predictions from parametric and machine learning classification approaches applied within the discrete time-to-event framework to those from continuous-time survival prediction models. We outline the process for training and validating discrete-time prediction models, and demonstrate its application using the open-source R statistical programming environment.ResultsUsing publicly available data sets, we show that some discrete-time prediction models achieve better prediction performance than the continuous-time Cox proportional hazards model. Random survival forests, a machine learning algorithm adapted to survival data, also had improved performance compared to the Cox model, but was sometimes outperformed by the discrete-time approaches. In comparing the binary classification methods in the discrete time-to-event framework, the relative performance of the different methods varied depending on the data set.ConclusionsWe present a guide for developing survival prediction models using discrete-time methods and assessing their predictive performance with the aim of encouraging their use in medical research settings. These methods can be applied to data sets that have continuous time-to-event outcomes and multiple clinical predictors. They can also be extended to accommodate new binary classification algorithms as they become available. We provide R code for fitting discrete-time survival prediction models in a github repository.
The effects of family-centered empowerment model on depression, anxiety, and stress of the family caregivers of patients with COVID-19: a randomized clinical trial
Authors: Nia Mohammad Namazi , Mohajer Samira , Bagheri Nasser , Sarboozi-hoseinabadi Tahere 
Published: July 2022

Abstract
Background
Taking care of patients with Covid-19 is regarded as a challenging task for family caregivers. Hence, a Family-Centered Empowerment Model (FCEM) should help them achieve greater psychological strength throughout the home healthcare process.

Methods
This study is a randomized clinical trial with two groups; besides, pre-test and post-test designs were conducted based on the CONSORT checklist from April to July 2020, in Iran. Seventy family caregivers were randomly assigned to FCEM (n = 35) and control (n = 35) groups. Then, four stages of FCEM in four online sessions were provided to the participants of the intervention group via WhatsApp messenger. The procedure started at the patient's discharge and continued for two weeks. The demographic information questionnaire and Depression Anxiety Stress Scale (DASS-21) were employed before and five days after the FCEM sessions to gather the required data.

Results
The sample was made up of 55.8% women and 44.2% men caregivers, with a mean age of 42.5 years. The results demonstrated a substantial difference in the average score of stress (p = 0.023), anxiety (p = 0.003), and depression (p = 0.012).

Conclusions
The combination of a face-to-face orientation session and online methods of FCEM is likely to lower stress, anxiety, and depression in family caregivers, which can be contributed to the practicability, simplicity, and effectiveness of this home health intervention.

Trial registration
This study (no. IRCT20180429039463N2) was registered in the Iranian Registry of Clinical Trials on 10/04/2020.
Prediction of the therapeutic efficacy of epirubicin combined with ifosfamide in patients with lung metastases from soft tissue sarcoma based on contrast-enhanced CT radiomics features
Authors: Miao Lei , Ma Shu-Tao , Jiang Xu , Zhang Huan-Huan , Wang Yan-Mei , Li Meng 
Published: July 2022

Abstract
Objective
To investigate the value of contrast-enhanced computed tomography (CECT) radiomics features in predicting the efficacy of epirubicin combined with ifosfamide in patients with pulmonary metastases from soft tissue sarcoma.

Methods
A retrospective analysis of 51 patients with pulmonary metastases from soft tissue sarcoma who received the chemotherapy regimen of epirubicin combined with ifosfamide was performed, and efficacy was evaluated by Recist1.1. ROIs (1 or 2) were selected for each patient. Lung metastases were used as target lesions (86 target lesions total), and the patients were divided into a progression group (n = 29) and a non-progressive group (n = 57); the latter included a stable group (n = 34) and a partial response group (n = 23). Information on lung metastases was extracted from CECT images before chemotherapy, and all lesions were delineated by ITK-SNAP software manually or semiautomatically. The decision tree classifier had a better performance in all radiomics models. A receiver operating characteristic curve was plotted to evaluate the predictive performance of the radiomics model.

Results
In total, 851 CECT radiomics features were extracted for each target lesion and finally reduced to 2 radiomics features, which were then used to construct a radiomics model. Areas under the curves of the model for predicting lesion progression were 0.917 and 0.856 in training and testing groups, respectively.

Conclusion
The model established based on the radiomics features of CECT before treatment has certain predictive value for assessing the efficacy of chemotherapy for patients with soft tissue sarcoma lung metastases.
A case of Gitelman syndrome with membranous nephropathy
Authors: Guo Xiafei , Yu Shanshen , Sun Jia , Mou Lijun 
Published: July 2022

Abstract
Background
Gitelman syndrome (GS) is a rare autosomal recessive inherited salt-losing tubulopathy (SLT). Here, we report, for the first time, a case of GS overlapping nephrotic syndrome (NS) related to PLA2R-associated membranous nephropathy (MN).

Case presentation
We described a male patient had a 4-year history of recurrent fatigue. Serum biochemistry revealed hypokalemia with renal potassium wasting, hypomagnesemia, metabolic alkalosis, hyperreninemia, hypocalciuria, as well as nephrotic-range proteinuria, hypoalbuminemia, and elevated serum anti-phospholipase A2 receptor (PLA2R) antibody. Gene sequencing identified compound heterozygous mutations in SLC12A3 [c.536T > A(p.V179D) and c.1456G > A(p.D486N)]. The unusual association of SLTs and nephrotic-range glomerular proteinuria prompted us to perform a renal biopsy. Renal biopsy showed idiopathic MN. Due to the potential to activate the sodium-chloride co-transporter (NCC) and cause hyperkalemia, tacrolimus was selected to treat NS. Following treatment with potassium chloride, magnesium oxide, low-dose glucocorticoid combined with tacrolimus, the fatigue significantly improved, and concurrently hypokalemia, hypomagnesemia were corrected and NS was remitted.

Conclusions
Renal biopsy should be warranted for GS patients with moderate to nephrotic-range proteinuria. Tacrolimus was preferred to the management of GS patients with NS.