bluuebunny/crossref_metadata_2025_split huggingface dataset:
TSPAN6 is a suppressor of Ras-driven cancer
Authors: Humbert Patrick O. , Pryjda Tamara Zoranovic , Pranjic Blanka , Farrell Andrew , Fujikura Kohei , de Matos Simoes Ricardo , Karim Rezaul , Kozieradzki Ivona , Cronin Shane J. F. , Neely G. Gregory , Meyer Thomas F. , Hagelkruys Astrid , Richardson Helena E. , Penninger Josef M. 
Published: February 2022

AbstractOncogenic mutations in the small GTPase RAS contribute to ~30% of human cancers. In aDrosophilagenetic screen, we identified novel and evolutionary conserved cancer genes that affect Ras-driven tumorigenesis and metastasis inDrosophilaincluding confirmation of the tetraspanin Tsp29Fb. However, it was not known whether the mammalian Tsp29Fb orthologue, TSPAN6, has any role in RAS-driven human epithelial tumors. Here we show that TSPAN6 suppressed tumor growth and metastatic dissemination of humanRASactivating mutant pancreatic cancer xenografts. Whole-body knockout as well as tumor cell autonomous inactivation using floxed alleles ofTspan6in mice enhancedKrasG12D-driven lung tumor initiation and malignant progression. Mechanistically, TSPAN6 binds to the EGFR and blocks EGFR-induced RAS activation. Moreover, we show that inactivation ofTSPAN6induces an epithelial-to-mesenchymal transition and inhibits cell migration in vitro and in vivo. Finally, lowTSPAN6expression correlates with poor prognosis of patients with lung and pancreatic cancers with mesenchymal morphology. Our results uncover TSPAN6 as a novel tumor suppressor receptor that controls epithelial cell identify and restrains RAS-driven epithelial cancer.
MicroRNAs serve as prediction and treatment-response biomarkers of attention-deficit/hyperactivity disorder and promote the differentiation of neuronal cells by repressing the apoptosis pathway
Authors: Wang Liang-Jen , Kuo Ho-Chang , Lee Sheng-Yu , Huang Lien-Hung , Lin Yuyu , Lin Pei-Hsien , Li Sung-Chou 
Published: February 2022

AbstractAttention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder. This study aimed to examine whether miRNA expression abundance in total white blood cells (WBCs) facilitated the identification of ADHD and reflected its response to treatment. Furthermore, whether miRNA markers facilitated the growth of the human cortical neuronal (HCN-2) cells was also investigated. Total WBC samples were collected from 145 patients and 83 controls, followed by RNA extraction and qPCR assays. Subsequently, WBC samples were also collected at the endpoint from ADHD patients who had undergone 12 months of methylphenidate treatment. The determined ΔCt values of 12 miRNAs were applied to develop an ADHD prediction model and to estimate the correlation with treatment response. The prediction model applying the ΔCt values of 12 examined miRNAs (using machine learning algorithm) demonstrated good validity in discriminating ADHD patients from controls (sensitivity: 96%; specificity: 94.2%). Among the 92 ADHD patients completing the 12-month follow-up, miR-140-3p, miR-27a-3p, miR-486-5p, and miR-151-5p showed differential trends of ΔCt values between treatment responders and non-responders. In addition, the in vitro cell model revealed that miR-140-3p and miR-126-5p promoted the differentiation of HCN-2 cells by enhancing the length of neurons and the number of junctions. Microarray and flow cytometry assays confirmed that this promotion was achieved by repressing apoptosis and/or necrosis. The findings of this study suggest that the expression levels of miRNAs have the potential to serve as both diagnostic and therapeutic biomarkers for ADHD. The possible biological mechanisms of these biomarker miRNAs in ADHD pathophysiology were also clarified.
Quantitative multidimensional phenotypes improve genetic analysis of laterality traits
Authors: Schmitz Judith , Zheng Mo , Lui Kelvin F. H. , McBride Catherine , Ho Connie S.-H. , Paracchini Silvia 
Published: February 2022

AbstractHandedness is the most commonly investigated lateralised phenotype and is usually measured as a binary left/right category. Its links with psychiatric and neurodevelopmental disorders prompted studies aimed at understanding the underlying genetics, while other measures and side preferences have been less studied. We investigated the heritability of hand, as well as foot, and eye preference by assessing parental effects (n ≤ 5028 family trios) and SNP-based heritability (SNP-h2,n ≤ 5931 children) in the Avon Longitudinal Study of Parents and Children (ALSPAC). An independent twin cohort from Hong Kong (n = 358) was used to replicate results from structural equation modelling (SEM). Parental left-side preference increased the chance of an individual to be left-sided for the same trait, with stronger maternal than paternal effects for footedness. By regressing out the effects of sex, age, and ancestry, we transformed laterality categories into quantitative measures. The SNP-h2for quantitative handedness and footedness was 0.21 and 0.23, respectively, which is higher than the SNP-h2reported in larger genetic studies using binary handedness measures. The heritability of the quantitative measure of handedness increased (0.45) compared to a binary measure for writing hand (0.27) in the Hong Kong twins. Genomic and behavioural SEM identified a shared genetic factor contributing to handedness, footedness, and eyedness, but no independent effects on individual phenotypes. Our analysis demonstrates how quantitative multidimensional laterality phenotypes are better suited to capture the underlying genetics than binary traits.
Evaluation of tumour surveillance protocols and outcomes in von Hippel-Lindau disease in a national health service
Authors: Maher Eamonn R. , Adlard Julian , Barwell Julian , Brady Angela F. , Brennan Paul , Cook Jackie , Crawford Gillian S. , Dabir Tabib , Davidson Rosemarie , Dyer Rebecca , Harrison Rachel , Forde Claire , Halliday Dorothy , Hanson Helen , Hay Eleanor , Higgs Jenny , Jones Mari , Lalloo Fiona , Miedzybrodzka Zosia , Ong Kai Ren , Pelz Frauke , Ruddy Deborah , Snape Katie , Whitworth James , Sandford Richard N. 
Published: February 2022

Abstract
Background
Von Hippel-Lindau (VHL) disease is an inherited tumour predisposition syndrome and a paradigm for the importance of early diagnosis and surveillance. However, there is limited information on the “real world” management of VHL disease.

Methods
A national audit of VHL disease in the United Kingdom.

Results
VHL disease was managed mostly via specialist clinics coordinated through regional clinical genetics services (but frequently involving additional specialties). Over the study period, 19 genetic centres saw 842 individuals (393 males, 449 females) with a clinical and/or molecular diagnosis of VHL disease and 74 individuals (35 male, 39 female) with a prior risk of 50% (affected parent). All centres offered retinal, central nervous system and abdominal surveillance to affected individuals and at-risk relatives though surveillance details differed between centres (but complied with international recommendations). Renal lesions detected on the first surveillance scan were, on average, larger than those detected during subsequent scans and the larger the diameter at detection the greater the likelihood of early intervention.

Conclusions
In a state-funded health care system individuals with a rare inherited cancer predisposition syndrome are generally able to access appropriate surveillance and patient management is improved compared to historical data. The “real world” data from this study will inform the future development of VHL management protocols.
Targeting autophagy peptidase ATG4B with a novel natural product inhibitor Azalomycin F4a for advanced gastric cancer
Authors: Zhong Lin , Yang Bin , Zhang Zhenhua , Wang Junfeng , Wang Xiaojuan , Guo Yinfeng , Huang Weifeng , Wang Qianqian , Cai Guodi , Xia Fan , Zhou Shengning , Ma Shuai , Nie Yichu , Lei Jinping , Li Min , Liu Peiqing , Deng Wenbin , Liu Yonghong , Han Fanghai , Wang Junjian 
Published: February 2022

AbstractAdvanced gastric cancer (GCa) remains highly lethal due to the lack of effective therapies. Identifying promising therapeutic targets and developing effective treatment against GCa are urgently needed. Through mRNA and protein analysis of GCa clinical tumor samples, we found that autophagy-related gene 4B (ATG4B) was overexpressed in GCa tumors and that its high expression was associated with patients’ poor prognosis. Knockdown of ATG4B significantly inhibited GCa cell survival and tumor growth. To further probe the role of ATG4B in GCa by pharmacological means, we screened an in-house marine natural compound library against ATG4B and identified Azalomycin F4a (Am-F4a) as a novel and potent ATG4B inhibitor. Am-F4a directly bound to ATG4B with high affinity and effectively suppressed GCa cell autophagy via inhibition of ATG4B both in vitro and in vivo. Moreover, Am-F4a or ATG4B knockdown significantly suppressed tumor growth as well as GCa cell migration and invasion. Am-F4a effectively blocked the metastatic progression of primary GCa and sensitized tumors to chemotherapy. Taken together, our findings indicate that ATG4B is a potential therapeutic target against GCa and the natural product Am-F4a is a novel ATG4B inhibitor that can be further developed for the treatment of GCa.
PINK1-parkin-mediated neuronal mitophagy deficiency in prion disease
Authors: Li Jie , Lai Mengyu , Zhang Xixi , Li Zhiping , Yang Dongming , Zhao Mengyang , Wang Dongdong , Sun Zhixin , Ehsan Sharjeel , Li Wen , Gao Hongli , Zhao Deming , Yang Lifeng 
Published: February 2022

AbstractA persistent accumulation of damaged mitochondria is part of prion disease pathogenesis. Normally, damaged mitochondria are cleared via a major pathway that involves the E3 ubiquitin ligase parkin and PTEN-induced kinase 1 (PINK1) that together initiate mitophagy, recognize and eliminate damaged mitochondria. However, the precise mechanisms underlying mitophagy in prion disease remain largely unknown. Using prion disease cell models, we observed PINK1-parkin-mediated mitophagy deficiency in which parkin depletion aggravated blocked mitochondrial colocalization with LC3-II-labeled autophagosomes, and significantly increased mitochondrial protein levels, which led to inhibited mitophagy. Parkin overexpression directly induced LC3-II colocalization with mitochondria and alleviated defective mitophagy. Moreover, parkin-mediated mitophagy was dependent on PINK1, since PINK1 depletion blocked mitochondrial Parkin recruitment and reduced optineurin and LC3-II proteins levels, thus inhibiting mitophagy. PINK1 overexpression induced parkin recruitment to the mitochondria, which then stimulated mitophagy. In addition, overexpressed parkin and PINK1 also protected neurons from apoptosis. Furthermore, we found that supplementation with two mitophagy-inducing agents, nicotinamide mononucleotide (NMN) and urolithin A (UA), significantly stimulated PINK1-parkin-mediated mitophagy. However, compared with NMN, UA could not alleviate prion-induced mitochondrial fragmentation and dysfunction, and neuronal apoptosis. These findings show that PINK1-parkin-mediated mitophagy defects lead to an accumulation of damaged mitochondria, thus suggesting that interventions that stimulate mitophagy may be potential therapeutic targets for prion diseases.
Ketamine inhibits TNF-α-induced cecal damage by enhancing RIP1 ubiquitination to attenuate lethal SIRS
Authors: Deng Bin , Yang Daowei , Wu Huanghui , Wang Lu , Wu Rui , Zhu Hongrui , Huang Ailing , Song Jingyi , Cai Tieliang , Liu Shanshan , Wu Jingsi , Zhou Huiying , Li Chunhui 
Published: February 2022

AbstractSystemic inflammatory response syndrome (SIRS) is a sepsis-associated inflammatory state and a self-defense mechanism against specific and nonspecific stimuli. Ketamine influences many key processes that are altered during sepsis. However, the underlying mechanisms remain incompletely understood. In this study, TNF-α-treated mice, as well as HT-29 and L929 cell models, were applied to characterize TNF-α-induced systemic and local cecal tissue inflammatory responses. Behavioral, biochemical, histological, and molecular biological approaches were applied to illustrate the related processes. Mice with TNF-α-induced SIRS showed systemic and local cecal tissue inflammatory responses, as indicated by increased levels of high mobility group box 1 protein (HMGB1), chemokines (C-X-C motif) ligand 10 (CXCL10), interleukin-6 (IL-6), and IL-10, as well as high mortality. Ketamine pretreatment alleviated death rates, symptoms, and the production of inflammatory cytokines induced by TNF-α in mice. Moreover, ketamine also protected the mice from TNF-α-induced cecal damage by suppressing the phosphorylation of receptor-interacting serine/threonine-protein kinase 3 (RIP3) and mixed lineage kinase domain-like protein (MLKL). In addition, our results showed that ketamine efficiently inhibited TNF-α-induced necroptosis in HT-29 and L929 cells. Furthermore, we explored the mechanism using different L929 cell lines. The results displayed that ketamine inhibited TNF-α-induced necroptosis by enhancing RIP1 ubiquitination and reducing the RIP1-RIP3 and RIP3-MLKL interactions, as well as the formation of necrosomes. Thus, our study may provide a new theoretical and experimental basis for treating diseases characterized by SIRS-associated inflammatory factor storms. Moreover, our exploration may provide potential molecular mechanisms and targets for therapeutic intervention and clinical application of ketamine.
Microbial communities across activated sludge plants show recurring species-level seasonal patterns
Authors: Peces Miriam , Dottorini Giulia , Nierychlo Marta , Andersen Kasper Skytte , Dueholm Morten Kam Dahl , Nielsen Per Halkjær 
Published: February 2022

AbstractMicrobial communities in activated sludge (AS) are the core of sanitation in wastewater treatment plants (WWTPs). Microbial communities in AS have shown seasonal changes, however, long-term experiments (&gt;2 years) are rarely conducted, limiting our understanding of the true seasonal dynamics in WWTPs. In this study, we resolved the microbial seasonal dynamics at the species level in four municipal full-scale WWTPs, sampled every 7–10 days, during 3–5 consecutive years. By applying a new time-series analysis approach, we revealed that the seasonal pattern was species-specific, where species belonging to the same functional guild or genus may show different seasonal dynamics. Species could be grouped into cohorts according to their seasonal patterns, where seasonal cohorts showed repeatable annual dynamics across years and plants. Species were also grouped according to their net growth rate in the AS (i.e., growing species and disappearing species). Growing species were more prevailing in spring and autumn cohorts, while disappearing species, which were only present due to the continuous immigration from influent wastewater, were mostly associated with winter and spring cohorts. Most known process-critical species, such as nitrifiers, polyphosphate accumulating organisms and filamentous organisms, showed distinct species-specific patterns. Overall, our study showed that overarching seasonal patterns affected microbial species in full-scale AS plants, with similar seasonal patterns across plants for many dominant species. These recurrent seasonal variations should be taken into account in the operation, understanding and management of the WWTPs.
Distributed model predictive control for multi‐robot systems with conflicting signal temporal logic tasks
Authors: Zhou Xiaoyi , Zou Yuanyuan , Li Shaoyuan , Li Xianwei , Fang Hao 
Published: February 2022

AbstractIn this paper, the control problem of multi‐robot systems under temporal logic tasks with limited time and logic constraints is studied, where each robot is required to reach the specified region in a given time and avoid collision all the time. Since the cooperative collision avoidance task of one robot depends on other robots' behaviors, the satisfaction of all the tasks may be conflicting. In this work, a distributed model predictive control (DMPC) strategy is proposed for conflicting temporal logic tasks. First, signal temporal logic (STL) is adopted to formally describe the temporal logic tasks. Based on robust semantics of STL formulas, a reference trajectory for the satisfaction degree of the task is designed to determine the short‐term task in the optimization horizon. In the DMPC optimization problem, the compatibility constraints are introduced to redesign the collision avoidance constraints, such that the collision avoidance tasks can be fulfilled using neighbouring robots' predicted information of the last time instant. Then, the terminal constraint is designed by the short‐term motion task which enforces each robot to move towards the goal region within the specified time interval. For conflicting tasks, a slack parameter is introduced in the terminal set to relax the motion task of each robot. The recursive feasibility of the DMPC algorithm is guaranteed, and the relaxed temporal logic tasks are fulfilled. In the proposed method, the discrete events including limited time and logic requirements are incorporated into the DMPC optimization problem, such that the motion task can be satisfied as much as possible and safety requirements are fulfilled. The effectiveness of the algorithm is illustrated by simulation and experiment results.
On recognition of multiple power quality disturbance events in electricity networks
Authors: Le Vinh Hao , Ma Hui , Ekanayake Chandima , Saha Tapan 
Published: February 2022

AbstractEffective power quality disturbance (PQD) events recognition is important for electricity network operation. This paper proposes an improved methodology for detecting and classifying multiple PQD events, which may simultaneously occur in the electricity network. It employs an adaptive dual resolution Stockwell‐transform for signal processing and a short‐term Renyi entropy estimation for feature extraction. Also, a multi‐class support vector machine is employed to classify the types of PQD events. A variety of power quality disturbance signals are synthesized to evaluate the effectiveness and efficiency of the proposed method. These signals include both single fault/abnormal event and mixed events (e.g. a mixture of several PQD events occurring simultaneously). Real‐life disturbance recordings from a transmission network service provider are also collected and used to verify the proposed method. The results show that the proposed method can achieve high classification accuracy at noisy environment. Especially, it is capable of identifying the disturbance signals comprising both harmonics with low total harmonic distortion levels and transients. Moreover, the algorithms developed in this paper can achieve a high computational efficiency.
Optimal design of electrical power distribution grid spacers using finite element method
Authors: Stefenon Stéfano Frizzo , Seman Laio Oriel , Pavan Bruno Antonio , Ovejero Raúl García , Leithardt Valderi Reis Quietinho 
Published: February 2022

AbstractSpacers in the compact power distribution network are essential components for the support, organization, and spacing of conductors. To improve the reliability of these components and have an optimized network design, it is necessary to evaluate the performance of the variation of their geometric parameters. The analysis of these components is fundamental, considering that there are several models available that are validated by the electric power utilities. Due to the various possible design shapes, it is necessary to use an optimized model to reduce the electric potential located in specific sites, improving the reliability in the component, as the higher electrical potential results in a greater chance of failure to occur. The finite element method (FEM) stands out for evaluating the distribution of electrical potential. In this paper, an FEM is used to evaluate variations in vertical and horizontal dimensions in spacers used in the 13.8 kV power grid. The models are analyzed in relation to their behavior regarding the potential distribution on their surface. From the results of these variations, the model is optimized by means of a mixed‐integer linear problem (MILP), replacing the FEM output with a ReLU network substitute model, to obtain a spacer with more efficiency to be used in semi‐insulated distribution networks.
Three‐phase overvoltage at lightning strike point due to direct triggered lightning to the phase wire of 10 kV power distribution line
Authors: Wang Jianguo , Zhao Yating , Cai Li , Fang Yuqian , Li Quanxin , Su Rui , Wang Shoupeng , Zhou Mi 
Published: February 2022

AbstractThis paper reports the observation results of three‐phase overvoltage at the lightning strike point of a 1.5 km, 10 kV power distribution line that was struck directly by rocket triggered lightning to its phase wire C. The arrester of the direct struck phase at the lightning strike point operated in all return strokes corresponding to return stroke current from −3.3 kA to −32.9 kA. The waveform of direct struck phase includes an initial spike before negative peak, operation area of metal oxide varistor, and the final attenuation with oscillation. The overvoltage waveforms of the indirect struck phase at the lightning strike point show a small initial negative peak, rapid transition to a large positive peak, and the final negative attenuation with oscillation. The negative peak value of the indirect struck phase at lightning strike point ranged from −4.1 kV to −25.2 kV and that of the direct struck phase was between −78.1 kV and −167.8 kV. The positive peak value of indirect struck phase was between 0.2 kV and 49.8 kV. The negative peak value, zero‐crossing time and the peak‐to‐peak value of voltage all have a good linear relation with the peak value of lightning return stroke current.
A dynamic object filtering approach based on object detection and geometric constraint between frames
Authors: Wei Jiansheng , Pan Shuguo , Gao Wang , Zhao Tao 
Published: February 2022

AbstractIn order to eliminate the influence of moving targets in visual positioning, a dynamic object filtering approach based on object detection and inter‐frame geometric constraints is proposed to filter the dynamic objects in monocular images. The object detection algorithm is firstly used to identify and locate objects in the single‐frame image, and the object matching between frames is performed. Then, the depth estimation network and pose recovery network are trained jointly to output estimated depth along with transformation matrix of object centroids between frames respectively. Finally, the mapping centroid is obtained from the estimated depth and inter‐frame transformation matrix. The joint constraint function is performed to complete the detection and filtering of dynamic objects. The experimental results show that the proposed dynamic object filtering approach not only can filter moving objects in sequence images accurately but also allows to reserve the dynamic objects that are temporarily in the stop state. The generalization ability of this approach is also verified in a real urban road scene and meets the requirements of follow‐up research in visual positioning.