bluuebunny/crossref_metadata_2025_split huggingface dataset:
RETRACTED ARTICLE: Overexpressed transient receptor potential vanilloid 1 (TRPV1) in lung adenocarcinoma harbours a new opportunity for therapeutic targeting
Authors: Nie Yichu , Feng Fenglan , Luo Wei , Sanders Andrew J. , Zhang Yidi , Liang Jiaming , Chen Cheng , Feng Weineng , Gu Weiquan , Liao Weiping , Wang Wei , Chen Jinfeng , Zhang Lijian , Jiang Wen G. , Li Jin 
Published: March 2022

AbstractThe specific biological function of transient receptor potential vanilloid 1 (TRPV1) in pathogenesis of lung adenocarcinoma (LUAD) remains unclear. In this study, TRPV1 expression in tumor tissues, primary cells and cell lines of LUAD, as well as the mechanism mediating its hyperexpression were systematically studied. Multiple models and techniques were adopted to elucidate the relationship between TRPV1 hyperexpression and tumor recurrence and metastasis. Results showed that TRPV1 expression was increased in tumor tissues and primary tumor cells of LUAD patients. The increased expression was associated with worse overall survival outcome and raised HIF1α levels. TRPV1 expression in A549 and NCI-H292 cells was increased after pretreatment with cigarette smoke extract or spermine NONOate. Moreover, A549 cells with TRPV1 overexpression has enhanced tumor growth rates in subcutaneous grafted tumor models, and increased intrapulmonary metastasis after tail vein infusion in nude BALB/c nude mice. Mechanistically, TRPV1 overexpression in A549 cells promoted HIF1α expression and nuclear translocation by promoting CREB phosphorylation and activation of NOS1-NO pathway, ultimately leading to accelerated cell proliferation and stronger invasiveness. In addition, based on photothermal effects, CuS-TRPV1 mAb effectively targeted and induced apoptosis of TRPV1-A549 cells both in vivo and in vitro, thereby mitigating tumor growth and metastasis induced by xenotransplantation of TRPV1-A549 cells. In conclusion, TRPV1 hyperexpression in LUAD is a risk factor for tumor progression and is involved in proliferation and migration of tumor cells through activation of HIF1α. Our study also attempted a new strategy inhibiting the recurrence and metastasis of LUAD: by CuS-TRPV1 mAb precisely kill TRPV1 hyperexpression cells through photothermal effects.
Association among prognostic nutritional index, post-operative infection and prognosis of stage II/III gastric cancer patients following radical gastrectomy
Authors: Xiao Yanping , Wei Gang , Ma Min , Liu Dian , Chen Pan , Quan Hu , Luo Jia , Xiao Hua 
Published: March 2022

Abstract
Background/objective
To investigate the influence of pre-operative immunological and nutritional status, assessed by the prognostic nutritional index (PNI) score, on post-operative infection, and the potential additive effects of low PNI and infection on prognosis after radical resection of stage II/III gastric cancer (GC).

Methods
The medical records of 2352 consecutive stage II/III GC patients who underwent radical gastrectomy were retrospectively reviewed. The independent predictors for infections were identified using univariate and multivariate analyses. Cox regression analysis was used to assess any associations between PNI, infection and OS.

Results
A total of 160 (6.8%) cases developed infections and low PNI (< 43.9) was confirmed as an independent predictor. Both PNI < 43.9 and infections independently predicted poor OS (hazard ratio: 1.163, 95% confidence interval: 1.007–1.343; HR: 1.347, 95%CI: 1.067–1.700), and an additive effect was confirmed as patients with both low PNI and infection had worst OS. Further stratified analyses showed that complete peri-operative adjuvant chemotherapy (PAC, ≥ 6 cycles) could significantly improve OS in patients with low PNI and/or infection, which was comparable to those with PNI ≥ 43.9 and/or infection (P = 0.160).

Conclusions
Infection was the most common complication after gastrectomy and PNI < 43.9 was identified as an independent predictor. Low PNI was associated with poorer OS in stage II/III GC, independent of infections, and low PNI and infections had a synergistic effect that was associated with worst OS. However, complete PAC could significantly improve OS in these patients. Thus, strategies to decrease infection and complete PAC should be further investigated.
Genetic instability from a single S phase after whole-genome duplication
Authors: Gemble Simon , Wardenaar René , Keuper Kristina , Srivastava Nishit , Nano Maddalena , Macé Anne-Sophie , Tijhuis Andréa E. , Bernhard Sara Vanessa , Spierings Diana C. J. , Simon Anthony , Goundiam Oumou , Hochegger Helfrid , Piel Matthieu , Foijer Floris , Storchová Zuzana , Basto Renata 
Published: March 2022

AbstractDiploid and stable karyotypes are associated with health and fitness in animals. By contrast, whole-genome duplications—doublings of the entire complement of chromosomes—are linked to genetic instability and frequently found in human cancers1–3. It has been established that whole-genome duplications fuel chromosome instability through abnormal mitosis4–8; however, the immediate consequences of tetraploidy in the first interphase are not known. This is a key question because single whole-genome duplication events such as cytokinesis failure can promote tumorigenesis9and DNA double-strand breaks10. Here we find that human cells undergo high rates of DNA damage during DNA replication in the first S phase following induction of tetraploidy. Using DNA combing and single-cell sequencing, we show that DNA replication dynamics is perturbed, generating under- and over-replicated regions. Mechanistically, we find that these defects result from a shortage of proteins during the G1/S transition, which impairs the fidelity of DNA replication. This work shows that within a single interphase, unscheduled tetraploid cells can acquire highly abnormal karyotypes. These findings provide an explanation for the genetic instability landscape that favours tumorigenesis after tetraploidization.
Comparison of MRI T1, T2, and T2* mapping with histology for assessment of intervertebral disc degeneration in an ovine model
Authors: Bouhsina Nora , Decante Cyrille , Hardel Jean-Baptiste , Rouleau Dominique , Abadie Jérôme , Hamel Antoine , Le Visage Catherine , Lesoeur Julie , Guicheux Jérôme , Clouet Johann , Fusellier Marion 
Published: March 2022

AbstractAn easy, reliable, and time-efficient standardized approach for assessing lumbar intervertebral disc (IVD) degeneration with relaxation times measurements in pre-clinical and clinical studies is lacking. This prospective study aims to determine the most appropriate method for lumbar IVD degeneration (IDD) assessment in sheep by comparing three quantitative MRI sequences (variable-flip-angle T1 mapping, and multi-echo T2 and T2* mapping), correlating them with Pfirrmann grading and histology. Strong intra- and interrater agreements were found for Nucleus pulposus (NP) regions-of-interest (ROI). T1, T2, and T2* mapping correlated with Pfirrmann grading and histological scoring (p < 0.05) except for the most ventral rectangular ROI on T2 maps. Correlations were excellent for all of the T1 ROIs and the T2* NP ROIs. Highly significant differences in T1 values were found between all Pfirrmann grades except between grades I/II and between grades III/IV. Significant differences were identified in the T2 and the T2* values between all grades except between grades I/III. T1, T2, and T2* relaxation times measurements of the NP are an accurate and time-efficient tool to assess lumbar IDD in sheep. Variable-flip-angle T1 mapping may be further considered as a valuable method to investigate IDD and to assess the efficacy of regenerative treatments in longitudinal studies.
Doxycycline prevents blood–brain barrier dysfunction and microvascular hyperpermeability after traumatic brain injury
Authors: Robinson Bobby D. , Isbell Claire L. , Melge Anu R. , Lomas Angela M. , Shaji Chinchusha Anasooya , Mohan C. Gopi , Huang Jason H. , Tharakan Binu 
Published: March 2022

AbstractThe main objective of this study was to determine the cellular and molecular effects of doxycycline on the blood–brain barrier (BBB) and protection against secondary injuries following traumatic brain injury (TBI). Microvascular hyperpermeability and cerebral edema resulting from BBB dysfunction after TBI leads to elevation of intracranial pressure, secondary brain ischemia, herniation, and brain death. There are currently no effective therapies to modulate the underlying pathophysiology responsible for TBI-induced BBB dysfunction and hyperpermeability. The loss of BBB integrity by the proteolytic enzyme matrix metalloproteinase-9 (MMP-9) is critical to TBI-induced BBB hyperpermeability, and doxycycline possesses anti-MMP-9 effect. In this study, the effect of doxycycline on BBB hyperpermeability was studied utilizing molecular modeling (using Glide) in silico, cell culture-based models in vitro, and a mouse model of TBI in vivo. Brain microvascular endothelial cell assays of tight junction protein immunofluorescence and barrier permeability were performed. Adult C57BL/6 mice were subjected to sham versus TBI with or without doxycycline treatment and immediate intravital microscopic analysis for evaluating BBB integrity. Postmortem mouse brain tissue was collected to measure MMP-9 enzyme activity. It was found that doxycycline binding to the MMP-9 active sites have binding affinity of −7.07 kcal/mol. Doxycycline treated cell monolayers were protected from microvascular hyperpermeability and retained tight junction integrity (p < 0.05). Doxycycline treatment decreased BBB hyperpermeability following TBI in mice by 25% (p < 0.05). MMP-9 enzyme activity in brain tissue decreased with doxycycline treatment following TBI (p < 0.05). Doxycycline preserves BBB tight junction integrity following TBI via inhibiting MMP-9 activity. When established in human subjects, doxycycline, may provide readily accessible medical treatment after TBI to attenuate secondary injury.
StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio
Authors: Wang Jinyin , Lu Miaoshan , Wang Ruimin , An Shaowei , Xie Cong , Yu Changbin 
Published: March 2022

AbstractAs the pervasive, standardized format for interchange and deposition of raw mass spectrometry (MS) proteomics and metabolomics data, text-based mzML is inefficiently utilized on various analysis platforms due to its sheer volume of samples and limited read/write speed. Most research on compression algorithms rarely provides flexible random file reading scheme. Database-developed solution guarantees the efficiency of random file reading, but nevertheless the efforts in compression and third-party software support are insufficient. Under the premise of ensuring the efficiency of decompression, we propose an encoding scheme “Stack-ZDPD” that is optimized for storage of raw MS data, designed for the format “Aird”, a computation-oriented format with fast accessing and decoding time, where the core compression algorithm is “ZDPD”. Stack-ZDPD reduces the volume of data stored in mzML format by around 80% or more, depending on the data acquisition pattern, and the compression ratio is approximately 30% compared to ZDPD for data generated using Time of Flight technology. Our approach is available on AirdPro, for file conversion and the Java-API Aird-SDK, for data parsing.
Predicting financial losses due to apartment construction accidents utilizing deep learning techniques
Authors: Kim Ji-Myong , Bae Junseo , Park Hyunsoung , Yum Sang-Guk 
Published: March 2022

AbstractThis study aims to generate a deep learning algorithm-based model for quantitative prediction of financial losses due to accidents occurring at apartment construction sites. Recently, the construction of apartment buildings is rapidly increasing to solve housing shortage caused by increasing urban density. However, high-rise and large-scale construction projects are increasing the frequency and severity of accidents occurring inside and outside of construction sites, leading to increases of financial losses. In particular, the increase in severe weather and the surge in abnormal weather events due to climate change are aggravating the risk of financial losses associated with accidents occurring at construction sites. Therefore, for sustainable and efficient management of construction projects, a loss prediction model that prevents and reduces the risk of financial loss is essential. This study collected and analyzed insurance claim payout data from a main insurance company in South Korea regarding accidents occurring inside and outside of construction sites. Deep learning algorithms were applied to develop predictive models reflecting scientific and recent technologies. Results and framework of this study provide critical guidance on financial loss management necessary for sustainable and efficacious construction project management. They can be used as a reference for various other construction project management studies.
The dynamic properties of a nuclear coactivator binding domain are evolutionarily conserved
Authors: Karlsson Elin , Sorgenfrei Frieda A. , Andersson Eva , Dogan Jakob , Jemth Per , Chi Celestine N. 
Published: March 2022

AbstractEvolution of proteins is constrained by their structure and function. While there is a consensus that the plasticity of intrinsically disordered proteins relaxes the structural constraints on evolution there is a paucity of data on the molecular details of these processes. The Nuclear Coactivator Binding Domain (NCBD) from CREB-binding protein is a protein interaction domain, which contains a hydrophobic core but is not behaving as a typical globular domain, and has been described as ‘molten-globule like’. The highly dynamic properties of NCBD makes it an interesting model system for evolutionary structure-function investigation of intrinsically disordered proteins. We have here compared the structure and biophysical properties of an ancient version of NCBD present in a bilaterian animal ancestor living around 600 million years ago with extant human NCBD. Using a combination of NMR spectroscopy, circular dichroism and kinetics we show that although NCBD has increased its thermodynamic stability, it has retained its dynamic biophysical properties in the ligand-free state in the evolutionary lineage leading from the last common bilaterian ancestor to humans. Our findings suggest that the dynamic properties of NCBD have been maintained by purifying selection and thus are important for its function, which includes mediating several distinct protein-protein interactions.
Bacterial communities associated with wood rot fungi that use distinct decomposition mechanisms
Authors: Haq Irshad Ul , Hillmann Benjamin , Moran Molly , Willard Samuel , Knights Dan , Fixen Kathryn R , Schilling Jonathan S 
Published: March 2022

Abstract
Wood decomposer fungi are grouped by how they extract sugars from lignocellulose. Brown rot fungi selectively degrade cellulose and hemicellulose, leaving lignin intact, and white rot fungi degrade all components. Many trees are susceptible to both rot types, giving carbon in Earth’s woody biomass, specifically lignin, a flexible fate that is affected not only by the fungal decomposition mechanism but also the associated microbial community. However, little is understood about how rot type may influence the microbial community in decaying wood. In this study, we quantified bacterial communities associated with Fomes fomentarius (white rot) and Fomitopsis betulina (brown rot) found on a shared tree host species, birch (Betula papyrifera). We collected 25 wood samples beneath sporocarps of F. fomentarius (n = 13) and F. betulina (n = 12) on standing dead trees, and coupled microbial DNA sequencing with chemical signatures of rot type (pH and lignin removal). We found that bacterial communities for both fungi were dominated by Proteobacteria, a commonly reported association. However, rot type exerted significant influence on less abundant taxa in ways that align logically with fungal traits. Amplicon sequence variants (ASVs) were enriched in Firmicutes in white-rotted wood, and were enriched in Alphaproteobacteria, Actinobacteria and Acidobacteria in lower pH brown rot. Our results suggest that wood decomposer strategies may exert significant selection effects on bacteria, or vice versa, among less-abundant taxa that have been overlooked when using abundance as the only measure of influence.
In situ construction of self-supporting Ni–Fe sulfide for high-efficiency oxygen evolution
Authors: Hao Mingxin , Wang Huizhen , Zhang Xiaoling , Qu Yangdong , Xuan Cuijuan , Wu Zexing , Cui Min , Wang Jie 
Published: March 2022

2D nanosheet arrays comprising the self-supporting (Fe,Ni)3S4 composite not only exhibit excellent OER activity but also superior reaction stability due to the combined effect of mesopore-containing 2D nanosheets and the binary metal species.
MIAM: Motion information aggregation module for action recognition
Authors: Cheng Qin , Ren Ziliang , Liu Zhen , Cheng Jun , Zhang Qieshi , Liu Jianming 
Published: March 2022

AbstractIn the field of action recognition based on RGB videos, it is infeasible to train deep networks on dozens or hundreds of frames because of limits on computational complexity and memory. Previous works commonly adopted a sparse sampling strategy, which unfortunately leads to missing crucial frames and insufficient modelling for short‐range motions. In this letter, an effective motion information aggregation module (MIAM) that utilises convolutional neural networks to aggregate motion information from multiple frames into one single frame is proposed. This allows to train deep networks end‐to‐end with densely sampled frames efficiently. The MIAM enables the model to gather motion information at every instant of action, which avoids missing subtle movements. Experiments on the NTU RGB+D 60 and NTU RGB+D 120 datasets verify that the MIAM significantly improves the recognition accuracy with very limited extra computational cost and exhibits unique advantages for recognising subtle actions.
A single‐stage face detection and face recognition deep neural network based on feature pyramid and triplet loss
Authors: Tsai Tsung‐Han , Chi Po‐Ting 
Published: March 2022

AbstractA practical deep learning face recognition system can be divided into several tasks. These tasks can be time‐consuming if each task is executed with the original image as the input data. And the feature extractors used by different tasks may duplicate its function. In this paper, a multi‐task training method based on feature pyramid and triplet loss to train a single‐stage face detection and face recognition deep neural network is proposed. As a single‐stage work, every task's data is passed through the same backbone network to avoid duplicate computation by sharing the weights and computation. The whole network is established using feature pyramid and anchor boxes to localise the face position, using triplet loss to establish the feature extractor, and finally matching the feature through a simple math function. The benefits of the approach are faster computation speed and less memory usage. On an Nvidia 2080Ti GPU accelerator, this system can achieve 212 FPS for a 640 × 640 resolution input and maintains 92.4% accuracy on the LFW data set.
Automatic geo‐localization framework without GNSS data
Authors: Tang Jin , Gong Cheng , Guo Fan , Yang Zirong , Wu Zhihu 
Published: March 2022

AbstractThe information unavailability of a global navigation satellite system (GNSS) for geo‐localization in many military and tourism applications implies the need to employ other applicable types of information, such as automatic image‐based location recognition. Unlike most existing localization methods that use GNSS information to locate an initial position, this paper proposes an automatic geo‐localization framework that does not require GNSS data. The proposed framework is a two‐stage pipeline that uses a query image and digital elevation model (DEM) data as input. The authors frame automatic geo‐localization without GNSS recordings as a skyline matching problem. By extracting the skyline from the DEM data and query images, the query image can be localized by matching the query skyline feature to the DEM skyline database. It has been demonstrated that this low‐cost approach can perform efficiently in mountainous or hilly areas to produce reliable localization results. The system was tested on 50 testing site points within a large‐scale area (China, 202.6 km2), and an average position error of 43.13 m was detected within 4.5 s.
Fast frequency response provision from commercial demand response, from scheduling to stability in power systems
Authors: Misaghian M. Saeed , O'Dwyer Ciara , Flynn Damian 
Published: March 2022

AbstractReduced numbers of online conventional generators, due to increasing shares of renewable energy sources, are increasing the requirement for a fast frequency response capability from reserve providers when a large infeed/outfeed trips. The commercial demand‐side sector, considering its size (MW/MWh) and existing communication and control infrastructure, makes it a potential valuable source of flexibility provision. Supermarket refrigeration systems are considered here as being representative of commercial end‐uses, with individual devices stochastically simulated under different ambient conditions, supermarket occupancy, food categories, and refrigeration performance. An aggregated fleet of supermarket loads are then created to provide a system‐wide reserve response. The all‐island power system of Northern Ireland and Republic of Ireland, with a horizon of 2030, is considered as a representative case study. Three distinct demand‐side frequency control methods, including static, droop, and hybrid control are presented and developed within a stability analysis platform. Year‐long simulation results show a general improvement in the frequency nadir and (maximum) rate of change of frequency when supermarkets are providing fast frequency response services to the grid, with the likelihood of severe transients (frequency nadir <49 Hz) greatly reduced (82% improvement), depending on the FFR control design, and associated speed of response.
Developments in the Alkynyltrifluoromethylations of Alkenes and Alkynes
Authors: Kiss Loránd , Remete Attila M. , Nonn Melinda , Volk Balázs 
Published: March 2022

AbstractAs a consequence of the expanding relevance of fluorine-containing organic molecules in drug research, the synthesis of organofluorine scaffolds has high significance in synthetic organic chemistry. Trifluoromethylative difunctionalizations of carbon–carbon multiple bonds, with the simultaneous introduction of a CF3 group and another function, have considerable potential. Considering the high importance of carbon–carbon bond-forming reactions in organic synthesis, carbotrifluoromethylations and, in particular, alkynyltrifluoromethylations have increasing interest in synthetic chemistry. Alkynyltrifluoromethylation is a narrow area and a relatively new approach in synthetic chemistry­; however it has not been reviewed so far. Our goal in this short review is to summarize recent developments in alkynyltrifluoromethylation reactions by considering: (a) alkynyltrifluoromethylation reactions of alkenes, including reactions involving either intramolecular alkynyl migration or intermolecular transformation, and (b) alkynyltrifluoromethylation reactions of alkynes.1	Introduction2	Alkynyltrifluoromethylation Reactions of Alkenes2.1	Reactions Involving Intramolecular Alkynyl Migration2.2	Intermolecular Reactions3	Alkynyltrifluoromethylation Reactions of Alkynes4	Summary and Outlook