bluuebunny/crossref_metadata_2025_split huggingface dataset:
SIRT1 and HSP90α feed-forward circuit safeguards chromosome segregation integrity in diffuse large B cell lymphomas
Authors: Białopiotrowicz-Data Emilia , Noyszewska-Kania Monika , Jabłońska Ewa , Sewastianik Tomasz , Komar Dorota , Dębek Sonia , Garbicz Filip , Wojtas Magdalena , Szydłowski Maciej , Polak Anna , Górniak Patryk , Juszczyński Przemysław 
Published: October 2023

AbstractDiffuse large B-cell lymphoma (DLBCL) is the most common aggressive non-Hodgkin lymphoma in adults, exhibiting highly heterogenous clinical behavior and complex molecular background. In addition to the genetic complexity, different DLBCL subsets exhibit phenotypic features independent of the genetic background. For example, a subset of DLBCLs is distinguished by increased oxidative phosphorylation and unique transcriptional features, including overexpression of certain mitochondrial genes and a molecular chaperone, heat shock protein HSP90α (termed “OxPhos” DLBCLs). In this study, we identified a feed-forward pathogenetic circuit linking HSP90α and SIRT1 in OxPhos DLBCLs. The expression of the inducible HSP90α isoform remains under SIRT1-mediated regulation. SIRT1 knockdown or chemical inhibition reduced HSP90α expression in a mechanism involving HSF1 transcription factor, whereas HSP90 inhibition reduced SIRT1 protein stability, indicating that HSP90 chaperones SIRT1. SIRT1-HSP90α interaction in DLBCL cells was confirmed by co-immunoprecipitation and proximity ligation assay (PLA). The number of SIRT1-HSP90α complexes in PLA was significantly higher in OxPhos- dependent than -independent cells. Importantly, SIRT1-HSP90α interactions in OxPhos DLBCLs markedly increased in mitosis, suggesting a specific role of the complex during this cell cycle phase. RNAi-mediated and chemical inhibition of SIRT1 and/or HSP90 significantly increased the number of cells with chromosome segregation errors (multipolar spindle formation, anaphase bridges and lagging chromosomes). Finally, chemical SIRT1 inhibitors induced dose-dependent cytotoxicity in OxPhos-dependent DLBCL cell lines and synergized with the HSP90 inhibitor. Taken together, our findings define a new OxPhos-DLBCL-specific pathogenetic loop involving SIRT1 and HSP90α that regulates chromosome dynamics during mitosis and may be exploited therapeutically.
PTPN23 ubiquitination by WDR4 suppresses EGFR and c-MET degradation to define a lung cancer therapeutic target
Authors: Singh Shaifali , Yeat Nai Yang , Wang Ya-Ting , Lin Shu-Yu , Kuo I-Ying , Wu Kuen-Phon , Wang Won-Jing , Wang Wen-Ching , Su Wu-Chou , Wang Yi-Ching , Chen Ruey-Hwa 
Published: October 2023

AbstractAberrant overexpression or activation of EGFR drives the development of non-small cell lung cancer (NSCLC) and acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) by secondary EGFR mutations or c-MET amplification/activation remains as a major hurdle for NSCLC treatment. We previously identified WDR4 as a substrate adaptor of Cullin 4 ubiquitin ligase and an association of WDR4 high expression with poor prognosis of lung cancer. Here, using an unbiased ubiquitylome analysis, we uncover PTPN23, a component of the ESCRT complex, as a substrate of WDR4-based ubiquitin ligase. WDR4-mediated PTPN23 ubiquitination leads to its proteasomal degradation, thereby suppressing lysosome trafficking and degradation of wild type EGFR, EGFR mutant, and c-MET. Through this mechanism, WDR4 sustains EGFR and c-MET signaling to promote NSCLC proliferation, migration, invasion, stemness, and metastasis. Clinically, PTPN23 is downregulated in lung cancer and its low expression correlates with WDR4 high expression and poor prognosis. Targeting WDR4-mediated PTPN23 ubiquitination by a peptide that competes with PTPN23 for binding WDR4 promotes EGFR and c-MET degradation to block the growth and progression of EGFR TKI-resistant NSCLC. These findings identify a central role of WDR4/PTPN23 axis in EGFR and c-MET trafficking and a potential therapeutic target for treating EGFR TKI-resistant NSCLC.
Fast generation of Schrödinger cat states using a Kerr-tunable superconducting resonator
Authors: He X. L. , Lu Yong , Bao D. Q. , Xue Hang , Jiang W. B. , Wang Z. , Roudsari A. F. , Delsing Per , Tsai J. S. , Lin Z. R. 
Published: October 2023

AbstractSchrödinger cat states, quantum superpositions of macroscopically distinct classical states, are an important resource for quantum communication, quantum metrology and quantum computation. Especially, cat states in a phase space protected against phase-flip errors can be used as a logical qubit. However, cat states, normally generated in three-dimensional cavities and/or strong multi-photon drives, are facing the challenges of scalability and controllability. Here, we present a strategy to generate and preserve cat states in a coplanar superconducting circuit by the fast modulation of Kerr nonlinearity. At the Kerr-free work point, our cat states are passively preserved due to the vanishing Kerr effect. We are able to prepare a 2-component cat state in our chip-based device with a fidelity reaching 89.1% under a 96 ns gate time. Our scheme shows an excellent route to constructing a chip-based bosonic quantum processor.
Creating tunable lateral optical forces through multipolar interplay in single nanowires
Authors: Nan Fan , Rodríguez-Fortuño Francisco J. , Yan Shaohui , Kingsley-Smith Jack J. , Ng Jack , Yao Baoli , Yan Zijie , Xu Xiaohao 
Published: October 2023

AbstractThe concept of lateral optical force (LOF) is of general interest in optical manipulation as it releases the constraint of intensity gradient in tightly focused light, yet such a force is normally limited to exotic materials and/or complex light fields. Here, we report a general and controllable LOF in a nonchiral elongated nanoparticle illuminated by an obliquely incident plane wave. Through computational analysis, we reveal that the sign and magnitude of LOF can be tuned by multiple parameters of the particle (aspect ratio, material) and light (incident angle, direction of linear polarization, wavelength). The underlying physics is attributed to the multipolar interplay in the particle, leading to a reduction in symmetry. Direct experimental evidence of switchable LOF is captured by polarization-angle-controlled manipulation of single Ag nanowires using holographic optical tweezers. This work provides a minimalist paradigm to achieve interface-free LOF for optomechanical applications, such as optical sorting and light-driven micro/nanomotors.
Structures illustrate step-by-step mitochondrial transcription initiation
Authors: Goovaerts Quinten , Shen Jiayu , De Wijngaert Brent , Basu Urmimala , Patel Smita S. , Das Kalyan 
Published: October 2023

AbstractTranscription initiation is a key regulatory step in gene expression during which RNA polymerase (RNAP) initiates RNA synthesis de novo, and the synthesized RNA at a specific length triggers the transition to the elongation phase. Mitochondria recruit a single-subunit RNAP and one or two auxiliary factors to initiate transcription. Previous studies have revealed the molecular architectures of yeast1 and human2 mitochondrial RNAP initiation complexes (ICs). Here we provide a comprehensive, stepwise mechanism of transcription initiation by solving high-resolution cryogenic electron microscopy (cryo-EM) structures of yeast mitochondrial RNAP and the transcription factor Mtf1 catalysing two- to eight-nucleotide RNA synthesis at single-nucleotide addition steps. The growing RNA–DNA is accommodated in the polymerase cleft by template scrunching and non-template reorganization, creating stressed intermediates. During early initiation, non-template strand scrunching and unscrunching destabilize the short two- and three-nucleotide RNAs, triggering abortive synthesis. Subsequently, the non-template reorganizes into a base-stacked staircase-like structure supporting processive five- to eight-nucleotide RNA synthesis. The expanded non-template staircase and highly scrunched template in IC8 destabilize the promoter interactions with Mtf1 to facilitate initiation bubble collapse and promoter escape for the transition from initiation to the elongation complex (EC). The series of transcription initiation steps, each guided by the interplay of multiple structural components, reveal a finely tuned mechanism for potential regulatory control.
CherryChèvre: A fine-grained dataset for goat detection in natural environments
Authors: Vayssade Jehan-Antoine , Arquet Rémy , Troupe Willy , Bonneau Mathieu 
Published: October 2023

AbstractWe introduce a new dataset for goat detection that contains 6160 annotated images captured under varying environmental conditions. The dataset is intended for developing machine learning algorithms for goat detection, with applications in precision agriculture, animal welfare, behaviour analysis, and animal husbandry. The annotations were performed by expert in computer vision, ensuring high accuracy and consistency. The dataset is publicly available and can be used as a benchmark for evaluating existing algorithms. This dataset advances research in computer vision for agriculture.
H19 encourages aerobic glycolysis and cell growth in gastric cancer cells through the axis of microRNA-19a-3p and phosphoglycerate kinase 1
Authors: Chen Siche , Wang Haiping , Xu Peiren , Dang Shengchun , Tang Yongqin 
Published: October 2023

AbstractNumerous studies have been conducted on long non-coding RNAs (lncRNAs) in human tumors like gastric cancer (GC). Our research uncovers how aerobic glycolysis and cell proliferation in gastric cancer cells are related to H19. We discovered that H19 was highly expressed in tumor tissues and that patients with higher H19 expression have a poorer prognosis. Intriguingly, we applied the subcellular isolation, luciferase reporter, western blot analysis, MTT, colony formation experiments, and CDX Model in Mice to verify that H19 regulates aerobic glycolysis towards GC cell growth by H19/microRNA (miR)-19a-3p/phosphoglycerate kinase 1 (PGK1) axis. Together, our research offers proof that the H19/miR-19a-3p/PGK1 pathway aids in the regulation of aerobic glycolysis and cell proliferation in GC. This may offer an opportunity for novel therapeutic approaches to the treatment of GC.
Robust genetic machine learning ensemble model for intrusion detection in network traffic
Authors: Akhtar Muhammad Ali , Qadri Syed Muhammad Owais , Siddiqui Maria Andleeb , Mustafa Syed Muhammad Nabeel , Javaid Saba , Ali Syed Abbas 
Published: October 2023

AbstractNetwork security has developed as a critical research subject as a result of the Rapid advancements in the development of Internet and communication technologies over the previous decades. The expansion of networks and data has caused cyber-attacks on the systems, making it difficult for network security to detect breaches effectively. Current Intrusion Detection Systems (IDS) have several flaws, including their inability to prevent attacks on their own, the requirement for a professional engineer to administer them, and the occurrence of false alerts. As a result, a plethora of new attacks are being created, making it harder for network security to properly detect breaches. Despite the best efforts, IDS continues to struggle with increasing detection accuracy while lowering false alarm rates and detecting new intrusions. Therefore, network intrusion detection enhancement by preprocessing and generation of highly reliable algorithms is the main focus nowadays. Machine learning (ML) based IDS systems have recently been implemented as viable solutions for quickly detecting intrusions across the network. In this study, we use a combined data analysis technique with four Robust Machine learning ensemble algorithms, including the Voting Classifier, Bagging Classifier, Gradient Boosting Classifier, and Random Forest-based Bagging algorithm along with the proposed Robust genetic ensemble classifier. For each algorithm, a model is created and tested using a Network Dataset. To assess the performance of both algorithms in terms of their ability to anticipate the anomaly occurrence, graphs of performance rates have been evaluated. The suggested algorithm outperformed other methods as it shows the lowest values of mean square error (MSE) and mean absolute error (MAE). The experiments were conducted on the Network traffic dataset available on Kaggle, on the Python platform, which has limited samples. The proposed method can be applied in the future with more machine learning ensemble classifiers and deep learning techniques.
Unsupervised machine learning method for indirect estimation of reference intervals for chronic kidney disease in the Puerto Rican population
Authors: Velev Julian , LeBien Jack , Roche-Lima Abiel 
Published: October 2023

AbstractReference intervals (RIs) for clinical laboratory values are extremely important for diagnostics and treatment of patients. However, the determination of these ranges is costly and time-consuming. As a result, often different unverified RIs are used in practice for the same analyte and the same range is used for all patients despite evidence that the values are gender, age, and ethnicity dependent. Moreover, the abnormal flags are rudimentary, merely indicating if a value is within the RI. At the same time, clinical lab data generated in the everyday medical practice contains a wealth of information, that given the correct methodology, can help determine the RIs for each specific segment of the population, including populations that suffer from health disparities. In this work, we develop unsupervised machine learning methods, based on Gaussian mixtures, to determine RIs of analytes related to chronic kidney disease, using millions of routine lab results for the Puerto Rican population. We show that the measures are both gender and age dependent and we find evidence for normal age-related organ function deterioration and failure. We also show that the joint distribution of measures improves the diagnostic value of the lab results.
Characteristics and risk of interstitial lung disease in dermatomyositis and polymyositis: a retrospective cohort study in Japan
Authors: Hu Qingqing , Huang Kuan-Chih , Goh Choo Hua , Tsuchiya Yumi , Liu Yanfang , Qiu Hong 
Published: October 2023

AbstractDermatomyositis and polymyositis are rare, idiopathic inflammatory myopathies. Interstitial lung disease is one of the most common and potentially severe extra-muscular manifestations of dermatomyositis and polymyositis and is strongly linked to poor prognosis and early mortality. We aimed to characterise the demographic and clinical characteristics, incidence, and treatment of interstitial lung disease in patients with dermatomyositis or polymyositis. We conducted a retrospective cohort study using the Japan Medical Data Center healthcare claims database. Patients in the database with dermatomyositis (International Classification of Disease version 10 M33.0, M33.1, M33.9) or polymyositis (M33.2) from 01-Jan-2011 until 31-Dec-2019 were identified and followed-up for interstitial lung disease (J84.x) until death, dis-enrolment, or study end (31 December 2020). Cumulative risk curves compared interstitial lung disease risk in dermatomyositis versus polymyositis. Risk factors were evaluated by Cox proportional hazard models. There were 886 patients with dermatomyositis and 745 patients with polymyositis included in the cohort analysis. Mean (standard deviation) age at dermatomyositis/polymyositis diagnosis was 46.0 (16.0)/49.7 (13.3) years and 300 (34%)/104 (14%) developed interstitial lung disease during follow-up. The incidence rate of interstitial lung disease per 100 person-years was 18.42 (95% CI 16.42–20.59) for dermatomyositis and 5.39 (95% CI 4.43–6.50) for polymyositis. In the analysis adjusted for sex, age, and comorbidity score, the risk of interstitial lung disease was significantly higher in patients with dermatomyositis than with polymyositis (hazard ratio 2.72, 95% CI 2.18–3.41). The rate diverged markedly between the groups in the first year after diagnosis. Risk factors for interstitial lung disease were older age in dermatomyositis, female sex and rheumatoid arthritis in polymyositis. Glucocorticoids with/without tacrolimus were the most common newly prescribed drugs after the interstitial lung disease diagnosis. In conclusion, the risk of developing interstitial lung disease was significantly higher in patients with dermatomyositis than with polymyositis, and risk factors were different in the 2 patient groups.
New approaches to selecting a scan-sampling method for chicken behavioral observations and their practical implications
Authors: Cartoni Mancinelli Alice , Trocino Angela , Menchetti Laura , Chiattelli Diletta , Ciarelli Claudia , Castellini Cesare 
Published: October 2023

AbstractThe use of the scan-sampling method, especially when a large amount of data is collected, has become widespread in behavioral studies. However, there are no specific guidelines regarding the choice of the sampling interval in different conditions. Thus, establishing a standard approach for video analysis represents an important step forward within the scientific community. In the present work, we hypothesized that the length of the sampling interval could influence the results of chicken behavioral study, for which we evaluated the reliability, accuracy, and validity of three different sampling intervals (10, 15 and 30 min). The Bland–Altman test was proposed as an innovative approach to compare sampling intervals and support researcher choices. Moreover, these sampling intervals were applied to compare the behavior of 4 chicken genotypes kept under free-range conditions. The Bland–Altman plots suggested that sampling intervals greater than 10 min lead to biases in the estimation of rare behaviors, such as “Attacking”. In contrast, the 30-min sampling interval was able to detect differences among genotypes in high-occurrence behaviors, such as those associated with locomotory activity. Thus, from a practical viewpoint, when a broad characterization of chicken genotypes is required, the 30-min scan-sampling interval might be suggested as a good compromise between resources and results.
Genetic structure and kdr mutations in Aedes aegypti populations along a road crossing the Amazon Forest in Amapá State, Brazil
Authors: Souza Barbara S. , Lima Leticia F. , Galardo Allan K. R. , Corbel Vincent , Lima Jose Bento P. , Martins Ademir J. 
Published: October 2023

AbstractInsecticide resistance in Aedes aegypti poses a significant threat to disease control. One form of resistance, caused by kdr mutations in the NaV gene, hinders vector control efforts in Brazil. Despite genetic differences typically accumulating among isolated populations, this mosquito can actively and passively disperse through human transportation. Our study investigated the genetic structure and spread of kdr mutations in Ae. aegypti populations across six localities in Amapá State, Brazil, within the Amazonian Forest. Using 12 microsatellite loci and qPCR methods, we assessed genetic structure and identified three common kdr mutations (V410L, V1016I, and F1534C). High prevalence of kdr alleles was observed in all localities, indicating widespread distribution in Amapá State. Microsatellite analysis revealed differentiation among mosquito populations, dividing them into two distinct clusters supported by Bayesian and DAPC analyses. Oiapoque, located along the northern border with French Guiana, exhibited the highest kdr frequencies and genetic differentiation compared to other localities. Our findings suggest genetic structure in Ae. aegypti populations in Amapá State, with some passive gene flow between clusters. The study underscores the need for continuous surveillance of Ae. aegypti populations to monitor the spread of insecticide resistance and inform effective vector control strategies.
Effects of NMDA-receptor blockade by ketamine on mentalizing and its neural correlates in humans: a randomized control trial
Authors: Wasserthal Sven , Lehmann Mirko , Neumann Claudia , Delis Achilles , Philipsen Alexandra , Hurlemann René , Ettinger Ulrich , Schultz Johannes 
Published: October 2023

AbstractSchizophrenia is associated with various deficits in social cognition that remain relatively unaltered by antipsychotic treatment. While faulty glutamate signaling has been associated with general cognitive deficits as well as negative symptoms of schizophrenia, no direct link between manipulation of glutamate signaling and deficits in mentalizing has been demonstrated thus far. Here, we experimentally investigated whether ketamine, an uncompetitive N-methyl-D-aspartate receptor antagonist known to induce psychotomimetic effects, influences mentalizing and its neural correlates. In a randomized, placebo-controlled between-subjects experiment, we intravenously administered ketamine or placebo to healthy participants performing a video-based social cognition task during functional magnetic resonance imaging. Psychotomimetic effects of ketamine were assessed using the Positive and Negative Syndrome Scale. Compared to placebo, ketamine led to significantly more psychotic symptoms and reduced mentalizing performance (more “no mentalizing” errors). Ketamine also influenced blood oxygen level dependent (BOLD) response during mentalizing compared to placebo. Specifically, ketamine increased BOLD in right posterior superior temporal sulcus (pSTS) and increased connectivity between pSTS and anterior precuneus. These increases may reflect a dysfunctional shift of attention induced by ketamine that leads to mentalizing deficits. Our findings show that a psychotomimetic dose of ketamine impairs mentalizing and influences its neural correlates, a result compatible with the notion that deficient glutamate signaling may contribute to deficits in mentalizing in schizophrenia. The results also support efforts to seek novel psychopharmacological treatments for psychosis and schizophrenia targeting glutamatergic transmission.
Correlation of procalcitonin and c-reactive protein levels with pathogen distribution and infection localization in urinary tract infections
Authors: Shi Jing , Zhan Zhi-Song , Zheng Zu-Shun , Zhu Xue-Xia , Zhou Xin-Yi , Zhang Shi-Yan 
Published: October 2023

AbstractAimed to explore the relationships between infection localization, bacterial species, and procalcitonin (PCT) and C-reactive protein (CRP) levels in urinary tract infections (UTIs). A retrospective study included 314 UTI hospitalized patients divided into two groups (268 with lower UTI, 46 with upper UTI) in a tertiary care hospital. PCT and CRP were performed. Bacterial isolates were identified using standard microbiological techniques, and statistical analyses were performed to assess associations between infection localization, bacterial species, PCT, and CRP levels. Age and gender showed no significant differences between the lower and upper UTIs. Escherichia coli dominated as the leading UTI pathogen. A positive correlation (r = 0.646, P < 0.001) between PCT and CRP levels was found. The subgroup with ureteritis in the upper UTI category exhibited the highest PCT and CRP levels. PCT and CRP exhibited favorable diagnostic potential in predicting upper UTIs, with AUCs of 0.644 and 0.629, respectively. The optimal cutoff values were 0.21 ng/mL for PCT and 60.77 mg/L for CRP. Sensitivities were 69.03% and 77.99%, while specificities were 56.52% and 47.83%, respectively. E. coli emerged as the predominant bacterium in UTIs. PCT and CRP demonstrated moderate diagnostic efficacy in distinguishing between upper and lower UTIs. Notably, PCT and CRP exhibited enhanced utility in identifying ureteritis.