bluuebunny/crossref_metadata_2025_split huggingface dataset:
RNA demethylase ALKBH5 promotes tumorigenesis in multiple myeloma via TRAF1-mediated activation of NF-κB and MAPK signaling pathways
Authors: Qu Jianwei , Hou Yifan , Chen Qingxiao , Chen Jing , Li Yi , Zhang Enfan , Gu Huiyao , Xu Ruyi , Liu Yang , Cao Wen , Zhang Jinna , Cao Liqin , He Jingsong , Cai Zhen 
Published: November 2021

AbstractN6-methyladenosine (m6A), an internal modification in mRNA, plays a critical role in regulating gene expression. Dysregulation of m6A modifiers promotes oncogenesis through enzymatic functions that disrupt the balance between the deposition and removal of m6A modification on critical transcripts. However, the roles of mRNA m6A in multiple myeloma (MM) are poorly understood. The present study showed that RNA demethylase ALKBH5 was overexpressed in MM and associated with a poor prognosis in MM patients. Knocking down ALKBH5 induced apoptosis and inhibited the growth of MM cells in vitro. Xenograft models and gene set enrichment analysis with patient transcriptome datasets also supported the oncogenic role of ALKBH5 in MM. Mechanistic studies showed that ALKBH5 exerted tumorigenic effects in myeloma in an m6A-dependent manner, and TNF receptor-associated factor 1 (TRAF1) was a critical target of ALKBH5. Specifically, ALKBH5 regulated TRAF1 expression via decreasing m6A abundance in the 3'-untranslated region (3'-UTR) of TRAF1 transcripts and enhancing TRAF1 mRNA stability. As a result, ALKBH5 promoted MM cell growth and survival through TRAF1-mediated activation of NF-κB and MAPK signaling pathways. Collectively, our data demonstrated that ALKBH5 played a critical role in MM tumorigenesis and suggested that ALKBH5 could be a novel therapeutic target in MM.
Pharmaco-proteogenomic profiling of pediatric diffuse midline glioma to inform future treatment strategies
Authors: Findlay Izac J. , De Iuliis Geoffry N. , Duchatel Ryan J. , Jackson Evangeline R. , Vitanza Nicholas A. , Cain Jason E. , Waszak Sebastian M. , Dun Matthew D. 
Published: November 2021

AbstractDiffuse midline glioma (DMG) is a deadly pediatric and adolescent central nervous system (CNS) tumor localized along the midline structures of the brain atop the spinal cord. With a median overall survival (OS) of just 9–11-months, DMG is characterized by global hypomethylation of histone H3 at lysine 27 (H3K27me3), driven by recurring somatic mutations in H3 genes including,HIST1H3B/C(H3.1K27M) orH3F3A(H3.3K27M), or through overexpression ofEZHIPin patients harboring wildtype H3. The recent World Health Organization’s 5th Classification of CNS Tumors now designates DMG as, ‘H3 K27-altered’, suggesting that global H3K27me3 hypomethylation is a ubiquitous feature of DMG and drives devastating transcriptional programs for which there are no treatments. H3-alterations co-segregate with various other somatic driver mutations, highlighting the high-level of intertumoral heterogeneity of DMG. Furthermore, DMG is also characterized by very high-level intratumoral diversity with tumors harboring multiple subclones within each primary tumor. Each subclone contains their own combinations of driver and passenger lesions that continually evolve, making precision-based medicine challenging to successful execute. Whilst the intertumoral heterogeneity of DMG has been extensively investigated, this is yet to translate to an increase in patient survival. Conversely, our understanding of the non-genomic factors that drive the rapid growth and fatal nature of DMG, including endogenous and exogenous microenvironmental influences, neurological cues, and the posttranscriptional and posttranslational architecture of DMG remains enigmatic or at best, immature. However, these factors are likely to play a significant role in the complex biological sequelae that drives the disease. Here we summarize the heterogeneity of DMG and emphasize how analysis of the posttranslational architecture may improve treatment paradigms. We describe factors that contribute to treatment response and disease progression, as well as highlight the potential for pharmaco-proteogenomics (i.e., the integration of genomics, proteomics and pharmacology) in the management of this uniformly fatal cancer.
RETRACTED ARTICLE: Targeting KDM4A-AS1 represses AR/AR-Vs deubiquitination and enhances enzalutamide response in CRPC
Authors: Zhang Boya , Zhang Mingpeng , Yang Yanjie , Li Qi , Yu Jianpeng , Zhu Shimiao , Niu Yuanjie , Shang Zhiqun 
Published: November 2021

AbstractCastration-resistant prostate cancer (CRPC) is a highly malignant type of advanced cancer resistant to androgen deprivation therapy. One of the important mechanisms for the development of CRPC is the persistent imbalanced regulation of AR and AR splice variants (AR/AR-Vs). In this study, we reported KDM4A-AS1, a recently discovered lncRNA, as a tumor promoter that was significantly increased in CRPC cell lines and cancer tissues. Depletion of KDM4A-AS1 significantly reduced cell viability, proliferation, migration in vitro, and tumor growth in vivo. We found that by binding to the NTD domain, KDM4A-AS1 enhances the stability of USP14-AR/AR-Vs complex, and promoted AR/AR-Vs deubiquitination to protect it from MDM2-mediated ubiquitin-proteasome degradation. Moreover, KDM4A-AS1 was found to enhance CRPC drug resistance to enzalutamide by repressing AR/AR-Vs degradation; antisense oligonucleotide drugs targeting KDM4A-AS1 significantly reduced the growth of tumors with enzalutamide resistance. Taken together, our results indicated that KDM4A-AS1 played an important role in the progression of CRPC and enzalutamide resistance by regulating AR/AR-Vs deubiquitination; targeting KDM4A-AS1 has broad clinical application potential.
proBDNF expression induces apoptosis and inhibits synaptic regeneration by regulating the RhoA-JNK pathway in an in vitro post-stroke depression model
Authors: Yang Bangkun , Wang Lesheng , Nie Ying , Wei Wei , Xiong Wenping 
Published: November 2021

AbstractBrain-derived neurotrophic factor (BDNF) plays an important role in the pathophysiology of post-stroke depression (PSD). However, the precise function and potential mechanism of proBDNF, the precursor form of BDNF, are unknown. In our study, a PSD-like model was established by treating neuronal cells with oxygen-glucose deprivation and corticosterone. We found that the protein proBDNF levels were significantly higher in the cortex and hippocampus in the PSD group than in the control group, suggesting that proBDNF plays a role in the pathophysiology of PSD. Furthermore, we re-established the PSD-like cell model using recombinant p75 neurotrophin receptor (p75NTR) or silencing c-Jun N-terminal kinase (JNK), and found that the PSD-induced upregulation of proBDNF was inhibited by recombinant p75NTR and JNK silencing (siJNK), and increased cellular apoptosis. Moreover, the application of recombinant p75NTR and siJNK in the PSD-like cell model significantly reversed the expression of apoptosis-related and depression-related proteins and decreased cellular apoptosis. Our findings suggest that proBDNF is involved in neural plasticity in PSD in vitro. The RhoA-JNK signaling pathway is activated after proBDNF binds to the p75NTR receptor, followed by the expression of apoptosis-related proteins (PSD95, synaptophysin, and P-cofilin), which contribute to PSD progression. The mechanism might involve the promotion of cellular apoptosis and the inhibition of nerve synapses regeneration by proBDNF.
Small nucleolar RNA 42 promotes the growth of hepatocellular carcinoma through the p53 signaling pathway
Authors: Wang Ganggang , Li Jinghua , Yao Ye , Liu Yingyi , Xia Peng , Zhang Hao , Yin Maohui , Qin Zhixiang , Ma Weijie , Yuan Yufeng 
Published: November 2021

AbstractRecent studies show that small nucleolar RNAs (snoRNAs) play an important role in tumorigenesis. SNORA42 is a potential therapeutic target and prognostic biomarker for various cancers, and the aim of the present study was to investigate the function and clinical relevance of SNORA42 in hepatocellular carcinoma (HCC). We detected the expression levels of SNORA42 in HCC and normal liver tissue samples, as well as in tumor and hepatocyte-derived cell lines. SNORA42 was significantly upregulated in the HCC tissues and cells compared to the adjacent liver tissues and normal hepatocytes. Furthermore, overexpression of SNORA42 correlated with poor prognosis in the HCC patients. Knocking down SNORA42 in HCC cell lines decreased their proliferation, migration and invasion in vitro, and inhibited tumor growth and metastasis in vivo. In contrast, ectopic expression of SNORA42 promoted HCC cell proliferation and inhibited apoptosis. Mechanistically, SNORA42 exerted its oncogenic effects by targeting the p53 signaling pathway and cell cycle transition. In conclusion, SNORA42 acted as an oncogene in HCC and was a potential prognostic biomarker and therapeutic target.
Three faces of biofilms: a microbial lifestyle, a nascent multicellular organism, and an incubator for diversity
Authors: Penesyan Anahit , Paulsen Ian T. , Kjelleberg Staffan , Gillings Michael R. 
Published: November 2021

AbstractBiofilms are organised heterogeneous assemblages of microbial cells that are encased within a self-produced matrix. Current estimates suggest that up to 80% of bacterial and archaeal cells reside in biofilms. Since biofilms are the main mode of microbial life, understanding their biology and functions is critical, especially as controlling biofilm growth is essential in industrial, infrastructure and medical contexts. Here we discuss biofilms both as collections of individual cells, and as multicellular biological individuals, and introduce the concept of biofilms as unique incubators of diversity for the microbial world.
Triangulation supports agricultural spread of the Transeurasian languages
Authors: Robbeets Martine , Bouckaert Remco , Conte Matthew , Savelyev Alexander , Li Tao , An Deog-Im , Shinoda Ken-ichi , Cui Yinqiu , Kawashima Takamune , Kim Geonyoung , Uchiyama Junzo , Dolińska Joanna , Oskolskaya Sofia , Yamano Ken-Yōjiro , Seguchi Noriko , Tomita Hirotaka , Takamiya Hiroto , Kanzawa-Kiriyama Hideaki , Oota Hiroki , Ishida Hajime , Kimura Ryosuke , Sato Takehiro , Kim Jae-Hyun , Deng Bingcong , Bjørn Rasmus , Rhee Seongha , Ahn Kyou-Dong , Gruntov Ilya , Mazo Olga , Bentley John R. , Fernandes Ricardo , Roberts Patrick , Bausch Ilona R. , Gilaizeau Linda , Yoneda Minoru , Kugai Mitsugu , Bianco Raffaela A. , Zhang Fan , Himmel Marie , Hudson Mark J. , Ning Chao 
Published: November 2021

AbstractThe origin and early dispersal of speakers of Transeurasian languages—that is, Japanese, Korean, Tungusic, Mongolic and Turkic—is among the most disputed issues of Eurasian population history1–3. A key problem is the relationship between linguistic dispersals, agricultural expansions and population movements4,5. Here we address this question by ‘triangulating’ genetics, archaeology and linguistics in a unified perspective. We report wide-ranging datasets from these disciplines, including a comprehensive Transeurasian agropastoral and basic vocabulary; an archaeological database of 255 Neolithic–Bronze Age sites from Northeast Asia; and a collection of ancient genomes from Korea, the Ryukyu islands and early cereal farmers in Japan, complementing previously published genomes from East Asia. Challenging the traditional ‘pastoralist hypothesis’6–8, we show that the common ancestry and primary dispersals of Transeurasian languages can be traced back to the first farmers moving across Northeast Asia from the Early Neolithic onwards, but that this shared heritage has been masked by extensive cultural interaction since the Bronze Age. As well as marking considerable progress in the three individual disciplines, by combining their converging evidence we show that the early spread of Transeurasian speakers was driven by agriculture.
GPCR activation mechanisms across classes and macro/microscales
Authors: Hauser Alexander S. , Kooistra Albert J. , Munk Christian , Heydenreich Franziska M. , Veprintsev Dmitry B. , Bouvier Michel , Babu M. Madan , Gloriam David E. 
Published: November 2021

AbstractTwo-thirds of human hormones and one-third of clinical drugs activate ~350 G-protein-coupled receptors (GPCR) belonging to four classes: A, B1, C and F. Whereas a model of activation has been described for class A, very little is known about the activation of the other classes, which differ by being activated by endogenous ligands bound mainly or entirely extracellularly. Here we show that, although they use the same structural scaffold and share several ‘helix macroswitches’, the GPCR classes differ in their ‘residue microswitch’ positions and contacts. We present molecular mechanistic maps of activation for each GPCR class and methods for contact analysis applicable for any functional determinants. This provides a superfamily residue-level rationale for conformational selection and allosteric communication by ligands and G proteins, laying the foundation for receptor-function studies and drugs with the desired modality.
Behaviour detection in crowded classroom scenes via enhancing features robust to scale and perspective variations
Authors: Liu Mingyu , Meng Fanman , Wu Qingbo , Xu Linfeng , Liao Qianghua 
Published: November 2021

AbstractDetecting human behaviours in images of crowded classroom scenes is a challenging task, due to the large variations of humans in scale and pose perspective. In this paper, two modules are proposed to tackle these two variations. First, an attention‐based RoI (region‐of‐interest) extractor is designed to handle scale variation. Feature fusion and attention mechanism are used to improve the RoI feature with more local and global information. Second, a transformation‐based detection head is introduced to handle perspective variation. The spatial transformation is adopted to extract consistent representation under various perspectives. Moreover, since there is a lack of proper datasets for human behaviour detection in classroom scenes, a new dataset is created, namely CLBD. The experiments on the proposed dataset demonstrate that the modules obtain significant improvements of performance over the state‐of‐the‐art detectors.
Multiple object tracking based on multi‐task learning with strip attention
Authors: Song Yaoye , Zhang Peng , Huang Wei , Zha Yufei , You Tao , Zhang Yanning 
Published: November 2021

AbstractMultiple object tracking (MOT) framework based on bifurcate strategy was usually challenged by data association of different model path, which work for object localisation and appearance embedding independently. By incorporating the re‐identification (re‐ID) as appearance embedding model, more recent studies on task combination of a single network have made a great progress in tracking performance. Unfortunately, the contributive improvement from re‐ID model is hard to balance the accuracy and efficiency for the whole framework. For more effective enhancement of the overall tracking performance, a real‐time detection needs to be taken into consideration with other auxiliary means for MOT modelling. Therefore, in this study, a one‐shot multiple object tracking is proposed based on multi‐task learning to obtain satisfactory performance in both speed and robustness. With updated re‐training strategy for the backbone model of detection, a D2LA network is proposed to achieve more characteristic fine‐grained feature extraction in branching task of pedestrian recognition. Additionally, a strip attention module is also introduced to further strengthen the feature discriminative capability of the tracking framework in occlusion. Experiments on the 2DMOT15, MOT16, MOT17, and MOT20 benchmark data sets have shown a superior performance in comparison to other state‐of‐the‐art tracking approaches.
Quasi Z‐source inverter with switched‐capacitor‐inductor for enhancing boost factor
Authors: Abbasi Bolaghi Jamal , Taheri Asghar , Babaei Mohammad Hosein , Gholami Masoumeh 
Published: November 2021

AbstractTwo structures are proposed based on the quasi Z‐source inverter (qZSI), which can significantly raise the output voltage in applications, including photovoltaic and fuel cells, in which the input voltage is low. The proposed inverters provide a continuous input current and reduce the voltage stress on capacitor. Besides, the proposed switched‐capacitor‐inductor qZSI (SCL‐qZSI) can suppress inrush current at the start up moment as this current might damage the devices. The performance of the proposed structures is investigated at different operating modes, and the voltage equations are calculated. The voltage stress on switches, the voltage stress on capacitors, the voltage stress on diodes, and the current stress on inductor, as well as the average DC‐link current, the gain voltage (G), and the boost factor (B) of the proposed inverters, are analysed and derived. They are then compared with similar converters. To confirm the performance of the proposed converters, a laboratory sample of converters is made, which with output voltages, capacitors voltages, input and output current for the proposed converters. The DC‐link (Vi) voltage is 95 with boost factor 1.6 for SCL‐qZSI, and the DC‐link voltage is 216 with boost factor 3.6 for the enhance switched‐capacitor‐inductor qZSI (ESCL‐qZSI), which confirms the relationships obtained from the proposed converters. Also, the abbreviation for this paper is shown in table 1.
Infrared-radio relation in the local Universe
Authors: Tisanić K. , De Zotti G. , Amiri A. , Khoram A. , Tavasoli S. , Vidović-Tisanić Z. 
Published: November 2021

Context.The Square Kilometer Array (SKA) is expected to detect high-redshift galaxies with star formation rates (SFRs) up to two orders of magnitude lower thanHerschelsurveys and will thus boost the ability of radio astronomy to study extragalactic sources. The tight infrared-radio correlation offers the possibility of using radio emission as a dust-unobscured star formation diagnostic. However, the physics governing the link between radio emission and star formation is poorly understood, and recent studies have pointed to differences in the exact calibration required when radio is to be used as a star formation tracer.Aims.We improve the calibration of the relation of the local radio luminosity–SFR and to test whether there are nonlinearities in it.Methods.We used a sample ofHerschelAstrophysical Terahertz Large Area Survey (H-ATLAS) sources and investigated their radio luminosity, which was derived using the NRAO VLA Sky Survey (NVSS) and Faint Images of the Radio Sky at Twenty-cm (FIRST) maps. We stacked the bins of infrared luminosity and SFR and accounted for bins with no detections in the stacked images using survival analysis fitting. This approach was tested using Monte Carlo simulations.Results.After removing sources from the sample that have excess radio emission, which is indicative of nuclear radio activity, we found no deviations from linearity of the mean relations between radio luminosity and either SFR or infrared luminosity.Concluisions.We analyzed the link between radio emission and SFR or infrared luminosity using a local sample of star-forming galaxies without evidence of nuclear radio activity and found no deviations from linearity, although our data are also consistent with the small nonlinearity reported by some recent analyses. The normalizations of these relations are intermediate between those reported by earlier works.
Operationalisierung von Qualitätsindikatoren mittels
Routinedaten am Beispiel der Evaluation der „Integrierten Versorgung
Gesundes Kinzigtal“
Authors: Köster Ingrid , Mehl Claudia , Siegel Achim , Graf Erika , Stelzer Dominikus , Farin-Glattacker Erik , Geraedts Max , Schubert Ingrid 
Published: November 2021

Zusammenfassung
Ziel Für die 10-Jahres-Evaluation der Integrierten Versorgung
„Gesundes Kinzigtal“ (IVGK, Innovationsfonds-Projekt 01VSF16002)
konsentierte eine multidisziplinäre Expertengruppe 101
Qualitätsindikatoren (QI), mit denen die Qualität der regional
integrierten Versorgung mit ihrer Ausrichtung auf Gesundheits- und
Präventionsprogramme evaluiert werden sollte. Ein Kriterium war, dass
sich diese QI prinzipiell für eine Abbildung mittels Routinedaten eignen
sollten. Ziel der Studie war es, zu prüfen, wie viele der und auf welche
Weise die entwickelten QI in Deutschland tatsächlich mit Routinedaten
abgebildet werden können und aus welchen Gründen eine
Operationalisierung eingeschränkt oder nicht möglich war.
Material und Methode Die Operationalisierung der QI erfolgte mittels
pseudonymisierten Abrechnungsdaten der AOK Baden-Württemberg der Jahre
2006–2015, die das Wissenschaftliche Institut der AOK (WIdO) dem
Evaluationsteam zur Verfügung stellte. Alle operationalisierten
Indikatoren waren binär kodiert (Kriterium erfüllt
ja/nein). Die in den Zähler- und Nennerdefinitionen benannten
Diagnosen, Prozeduren oder Arzneimittel wurden über ICD-10-Kodes (Ein-
und Ausschlussdiagnosen), EBM-Kennziffern, OPS-Schlüssel und ATC-Kodes
operationalisiert. Indikatorprävalenzen wurden im zeitlichen Verlauf zur
Prüfung von Auffälligkeiten als Hinweis auf mögliche
Fehlkodierung untersucht.
Ergebnisse 90 der 101 Indikatoren waren mit Routinedaten
operationalisierbar. 14 der 90 Indikatoren konnten nur mit
Einschränkungen operationalisiert werden, da entsprechende
Leistungsziffern erst im Beobachtungszeitraum eingeführt oder bestehende
Ziffern verändert wurden. 76 der 90 Indikatoren konnten
uneingeschränkt operationalisiert werden, davon waren bei 15 Indikatoren
Vor- und Nachbeobachtungszeiten notwendig, wodurch sie nicht für alle
Jahre dargestellt werden konnten. 11 von 101 QI waren nicht operationalisierbar,
da EBM-Ziffern erst nach 2015 eingeführt oder nicht als Einzelleistung
für alle Arztgruppen erfasst wurden (z. B. Spirometrie und
Langzeit-EKG). Auffällige Verläufe in den
Indikatorprävalenzen waren erklärbar.
Schlussfolgerung Routinedaten ermöglichen ein ressourcensparendes
Qualitätsmonitoring. Eine Veränderung der Datengrundlage im
Beobachtungszeitraum, wie etwa durch Neueinführung oder Streichung von
Abrechnungsziffern, erschwert die longitudinale, routinedatenbasierte
Qualitätsbewertung, ermöglicht aber ggfs. für
spätere Zeiträume die Operationalisierung weiterer oder neuer
Indikatoren.