bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automated food intake tracking requires depth-refined semantic segmentation to rectify visual-volume discordance in long-term care homes
Authors: Pfisterer Kaylen J. , Amelard Robert , Chung Audrey G. , Syrnyk Braeden , MacLean Alexander , Keller Heather H. , Wong Alexander 
Published: January 2022

AbstractMalnutrition is a multidomain problem affecting 54% of older adults in long-term care (LTC). Monitoring nutritional intake in LTC is laborious and subjective, limiting clinical inference capabilities. Recent advances in automatic image-based food estimation have not yet been evaluated in LTC settings. Here, we describe a fully automatic imaging system for quantifying food intake. We propose a novel deep convolutional encoder-decoder food network with depth-refinement (EDFN-D) using an RGB-D camera for quantifying a plate’s remaining food volume relative to reference portions in whole and modified texture foods. We trained and validated the network on the pre-labelled UNIMIB2016 food dataset and tested on our two novel LTC-inspired plate datasets (689 plate images, 36 unique foods). EDFN-D performed comparably to depth-refined graph cut on IOU (0.879 vs. 0.887), with intake errors well below typical 50% (mean percent intake error: $$-4.2$$

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4.2

%). We identify how standard segmentation metrics are insufficient due to visual-volume discordance, and include volume disparity analysis to facilitate system trust. This system provides improved transparency, approximates human assessors with enhanced objectivity, accuracy, and precision while avoiding hefty semi-automatic method time requirements. This may help address short-comings currently limiting utility of automated early malnutrition detection in resource-constrained LTC and hospital settings.
Quantifying the cell morphology and predicting biological behavior of signet ring cell carcinoma using deep learning
Authors: Da Qian , Deng Shijie , Li Jiahui , Yi Hongmei , Huang Xiaodi , Yang Xiaoqun , Yu Teng , Wang Xuan , Liu Jiangshu , Duan Qi , Metaxas Dimitris , Wang Chaofu 
Published: January 2022

AbstractSignet ring cell carcinoma (SRCC) is a malignant tumor of the digestive system. This tumor has long been considered to be poorly differentiated and highly invasive because it has a higher rate of metastasis than well-differentiated adenocarcinoma. But some studies in recent years have shown that the prognosis of some SRCC is more favorable than other poorly differentiated adenocarcinomas, which suggests that SRCC has different degrees of biological behavior. Therefore, we need to find a histological stratification that can predict the biological behavior of SRCC. Some studies indicate that the morphological status of cells can be linked to the invasiveness potential of cells, however, the traditional histopathological examination can not objectively define and evaluate them. Recent improvements in biomedical image analysis using deep learning (DL) based neural networks could be exploited to identify and analyze SRCC. In this study, we used DL to identify each cancer cell of SRCC in whole slide images (WSIs) and quantify their morphological characteristics and atypia. Our results show that the biological behavior of SRCC can be predicted by quantifying the morphology of cancer cells by DL. This technique could be used to predict the biological behavior and may change the stratified treatment of SRCC.
In silico construction of a multiepitope Zika virus vaccine using immunoinformatics tools
Authors: Antonelli Ana Clara Barbosa , Almeida Vinnycius Pereira , de Castro Fernanda Oliveira Feitosa , Silva Jacyelle Medeiros , Pfrimer Irmtraut Araci Hoffmann , Cunha-Neto Edecio , Maranhão Andréa Queiroz , Brígido Marcelo Macedo , Resende Renato Oliveira , Bocca Anamélia Lorenzetti , Fonseca Simone Gonçalves 
Published: January 2022

AbstractZika virus (ZIKV) is an arbovirus from the Flaviviridae family and Flavivirus genus. Neurological events have been associated with ZIKV-infected individuals, such as Guillain-Barré syndrome, an autoimmune acute neuropathy that causes nerve demyelination and can induce paralysis. With the increase of ZIKV infection incidence in 2015, malformation and microcephaly cases in newborns have grown considerably, which suggested congenital transmission. Therefore, the development of an effective vaccine against ZIKV became an urgent need. Live attenuated vaccines present some theoretical risks for administration in pregnant women. Thus, we developed an in silico multiepitope vaccine against ZIKV. All structural and non-structural proteins were investigated using immunoinformatics tools designed for the prediction of CD4 + and CD8 + T cell epitopes. We selected 13 CD8 + and 12 CD4 + T cell epitopes considering parameters such as binding affinity to HLA class I and II molecules, promiscuity based on the number of different HLA alleles that bind to the epitopes, and immunogenicity. ZIKV Envelope protein domain III (EDIII) was added to the vaccine construct, creating a hybrid protein domain-multiepitope vaccine. Three high scoring continuous and two discontinuous B cell epitopes were found in EDIII. Aiming to increase the candidate vaccine antigenicity even further, we tested secondary and tertiary structures and physicochemical parameters of the vaccine conjugated to four different protein adjuvants: flagellin, 50S ribosomal protein L7/L12, heparin-binding hemagglutinin, or RS09 synthetic peptide. The addition of the flagellin adjuvant increased the vaccine's predicted antigenicity. In silico predictions revealed that the protein is a probable antigen, non-allergenic and predicted to be stable. The vaccine’s average population coverage is estimated to be 87.86%, which indicates it can be administered worldwide. Peripheral Blood Mononuclear Cells (PBMC) of individuals with previous ZIKV infection were tested for cytokine production in response to the pool of CD4 and CD8 ZIKV peptide selected. CD4 + and CD8 + T cells showed significant production of IFN-γ upon stimulation and IL-2 production was also detected by CD8 + T cells, which indicated the potential of our peptides to be recognized by specific T cells and induce immune response. In conclusion, we developed an in silico universal vaccine predicted to induce broad and high-coverage cellular and humoral immune responses against ZIKV, which can be a good candidate for posterior in vivo validation.
Factors associated with injury and re-injury occurrence in female pole dancers
Authors: Szopa Andrzej , Domagalska-Szopa Małgorzata , Urbańska Aleksandra , Grygorowicz Monika 
Published: January 2022

AbstractThe aim of the study was to recognise what participant-, training- and post-injury-related factors are associated with an injury and re-injury occurrence in female pole dancers (PDs). 320 female PDs fulfilled a custom survey. 1050 injuries were reported by 276 PDs, 59% of injuries were related to lower extremity, 39% to upper extremity and 10% to spine and trunk. 156 PDs reported sustaining a re-injury, and overall, 628 re-injuries were reported. The median weekly pole-specific training session volume was 90 min and 240 min in the low and high qualified group, respectively. The total training volume was 180 min in the low qualified PDs and 240 min in the high qualified group. PDs with higher height and spending more time on pole-specific training in studio and on other forms of training have higher odds of sustaining an injury. PDs with lower level of experience in training, who sustained an injury, and who had a shorter pause between the moment of injury and the return to performance, and thus who did not fully recover, have higher odds of sustaining a re-injury. Sport-specific injury prevention strategies should be developed and implemented in this cohort, since over 85% of pole dancers reported sustaining some kind of injury.
A scoring system combining clinical, radiological, and histopathological examinations for differential diagnosis between lipoma and atypical lipomatous tumor/well-differentiated liposarcoma
Authors: Asano Yohei , Miwa Shinji , Yamamoto Norio , Hayashi Katsuhiro , Takeuchi Akihiko , Igarashi Kentaro , Yonezawa Hirotaka , Araki Yoshihiro , Morinaga Sei , Nojima Takayuki , Ikeda Hiroko , Tsuchiya Hiroyuki 
Published: January 2022

AbstractThis study evaluated the diagnostic accuracy of clinical, radiological, and histopathological examinations for differential diagnosis between atypical lipomatous tumor (ALT)/well-differentiated liposarcoma (WDLS) and lipoma, and aimed to develop a new combined scoring system for the preoperative diagnosis of ALT/WDLS. Eighty-nine lipomas and 56 ALT/WDLS were included and their clinical characteristics, magnetic resonance imaging (MRI) findings, histological findings by hematoxylin and eosin (HE) staining were investigated. Then, univariate and multivariate logistic regression analyses were performed for the findings, and a combined scoring system consisted of predictive factors of ALT/WDLS was developed. The univariate and multivariate logistic regression analyses revealed that tumor location (lower extremity), deep site, size (> 11 cm), thick septa (> 2 mm), enhancement of septa or nodular lesions, and lipoblasts were significantly different for the diagnosis of ALT/WDLS. We developed a combined scoring system based on the six predictive factors (total 0–16 points, the cutoff was 9 points). The area under the curve was 0.945, and sensitivity was 87.6% and specificity was 91.1% by the receiver operating characteristics curve. This combined scoring system does not require special equipment and reagents such as fluorescence in situ hybridization (FISH), and anyone can use it easily in many medical institutions with high diagnostic accuracy.
Recombinant inbred lines and next-generation sequencing enable rapid identification of candidate genes involved in morphological and agronomic traits in foxtail millet
Authors: Fukunaga Kenji , Abe Akira , Mukainari Yohei , Komori Kaho , Tanaka Keisuke , Fujihara Akari , Yaegashi Hiroki , Kobayashi Michie , Ito Kazue , Ohsako Takanori , Kawase Makoto 
Published: January 2022

AbstractWe constructed recombinant inbred lines (RILs) between a Japanese and a Taiwanese landrace of foxtail millet and employed next-generation sequencing, such as flexible ddRAD-seq and Nanopore sequencing to identify the candidate genes involved in the crop evolution of foxtail millet. We successfully constructed a linkage map using flexible ddRAD-seq with parents and RILs and detected major QTLs for each of three traits: leaf sheath colors, spikelet-tipped bristles (stb), and days to heading (DTH). (1) For leaf sheath colors, we identified the C gene on chromosome IV. (2) We identified a homeobox (HOX14) gene for stb on chromosome II, which shows homology with HvVrs1 in barley. (3) Finally, we identified a QTL with a large effect on DTH on chromosome II. A parent of the RILs from Taiwan and Yugu1 had a Harbinger-like TE in intron 3 of this gene. We also investigated the geographical distribution of the TE insertion type of this gene and found that the insertion type is distributed in the northern part of East Asia and intensively in South and Southeast Asia, suggesting that loss/reduction of function of this gene plays an important role in spreading into the northern part of East Asia and subtropical and tropical zones.
Novel ratio-metric features enable the identification of new driver genes across cancer types
Authors: Sudhakar Malvika , Rengaswamy Raghunathan , Raman Karthik 
Published: January 2022

AbstractAn emergent area of cancer genomics is the identification of driver genes. Driver genes confer a selective growth advantage to the cell. While several driver genes have been discovered, many remain undiscovered, especially those mutated at a low frequency across samples. This study defines new features and builds a pan-cancer model, cTaG, to identify new driver genes. The features capture the functional impact of the mutations as well as their recurrence across samples, which helps build a model unbiased to genes with low frequency. The model classifies genes into the functional categories of driver genes, tumour suppressor genes (TSGs) and oncogenes (OGs), having distinct mutation type profiles. We overcome overfitting and show that certain mutation types, such as nonsense mutations, are more important for classification. Further, cTaG was employed to identify tissue-specific driver genes. Some known cancer driver genes predicted by cTaG as TSGs with high probability are ARID1A, TP53, and RB1. In addition to these known genes, potential driver genes predicted are CD36, ZNF750 and ARHGAP35 as TSGs and TAB3 as an oncogene. Overall, our approach surmounts the issue of low recall and bias towards genes with high mutation rates and predicts potential new driver genes for further experimental screening. cTaG is available athttps://github.com/RamanLab/cTaG.
Activity of vehicles in the bus rapid transit system Metrobús in Mexico City
Authors: Martínez-González Jaspe U. , Riascos Alejandro P. 
Published: January 2022

AbstractIn this paper, we analyze a massive dataset with registers of the movement of vehicles in the bus rapid transit system Metrobús in Mexico City from February 2020 to April 2021. With these records and a division of the system into 214 geographical regions (segments), we characterize the vehicles’ activity through the statistical analysis of speeds in each zone. We use the Kullback–Leibler distance to compare the movement of vehicles in each segment and its evolution. The results for the dynamics in different zones are represented as a network where nodes define segments of the system Metrobús and edges describe similarity in the activity of vehicles. Community detection algorithms in this network allow the identification of patterns considering different levels of similarity in the distribution of speeds providing a framework for unsupervised classification of the movement of vehicles. The methods developed in this research are general and can be implemented to describe the activity of different transportation systems with detailed records of the movement of users or vehicles.
BIRC2–BIRC3 amplification: a potentially druggable feature of a subset of head and neck cancers in patients with Fanconi anemia
Authors: Roohollahi Khashayar , de Jong Yvonne , Pai Govind , Zaini Mohamad Amr , de Lint Klaas , Sie Daoud , Rooimans Martin A. , Rockx Davy , Hoskins Elizabeth E. , Ameziane Najim , Wolthuis Rob , Joenje Hans , Wells Susanne I. , Dorsman Josephine 
Published: January 2022

AbstractHead-and-neck squamous cell carcinomas (HNSCCs) are relatively common in patients with Fanconi anemia (FA), a hereditary chromosomal instability disorder. Standard chemo-radiation therapy is not tolerated in FA due to an overall somatic hypersensitivity to such treatment. The question is how to find a suitable alternative treatment. We used whole-exome and whole genome mRNA sequencing to identify major genomic and transcriptomic events associated with FA-HNSCC. CRISPR-engineered FA-knockout models were used to validate a number of top hits that were likely to be druggable. We identified deletion of 18q21.2 and amplification of 11q22.2 as prevailing copy-number alterations in FA HNSCCs, the latter of which was associated with strong overexpression of the cancer-related genes YAP1, BIRC2, BIRC3 (at 11q22.1-2). We then found the drug AZD5582, a known small molecule inhibitor of BIRC2-3, to selectively kill FA tumor cells that overexpressed BIRC2-3. This occurred at drug concentrations that did not affect the viability of untransformed FA cells. Our data indicate that 11q22.2 amplifications are relatively common oncogenic events in FA-HNSCCs, as holds for non FA-HNSCC. Therefore, chemotherapeutic inhibition of overexpressed BIRC2-3 may provide the basis for an approach to develop a clinically realistic treatment of FA-HNSCCs that carry 11q22.2 amplifications.
Objective to identify and verify the regulatory mechanism of DTNBP1 as a prognostic marker for hepatocellular carcinoma
Authors: Cheng Xianyi , Li Dezhi , Qi Tiangyang , Sun Jia , Zhou Tao , Zheng Wei V. 
Published: January 2022

AbstractAlthough the overall survival of hepatocellular carcinoma (HCC) patients has been significantly improved, prognostic clinical evaluation remains a substantial problem owing to the heterogeneity and complexity of tumor. A reliable and accurate predictive biomarker may assist physicians in better monitoring of patient treatment outcomes and follow the overall survival of patients. Accumulating evidence has revealed that DTNBP1 plays functional roles in cancer prognosis. Therefore, the expression and function of DTNBP1in HCC was systematically investigated in our study. The expression and prognostic value of DTNBP1 were investigated using the data from Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) cohorts and clinical samples. A series of cellular function assays were performed to elucidate the effect of DTNBP1 on cellular proliferation, apoptosis and metastasis. Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment and Protein–protein interaction (PPI) network construction were performed to screen the genes with highest interaction scores with DTNBP1. Finally, the underlying mechanism was also analyzed using Gene Set Enrichment Analysis (GSEA) and confirmed using RT-qPCR and western blotting. DTNBP1 was upregulated in many types of cancers, especially in HCC. The DTNBP1 expression levels is associated with clinicopathologic variables and patient survival status. The differential expression of DTNBP1 could be used to determine the risk stratification of patients with HCC. DTNBP1 deficiency inhibited cell proliferation and metastasis, but promoted cell apoptosis. Mechanistically, DTNBP1 regulated the cell cycle progression through affecting the expression of cell cycle-related genes such as CDC25A, CCNE1, CDK2, CDC20, CDC25B, CCNB1, and CDK1. DTNBP1, which regulates the cell cycle progression, may be used as a prognostic marker for HCC.
Insights into opium poppy (Papaver spp.) genetic diversity from genotyping-by-sequencing analysis
Authors: Hong Uyen Vu Thuy , Tamiru-Oli Muluneh , Hurgobin Bhavna , Okey Christopher R. , Abreu Artur R. , Lewsey Mathew G. 
Published: January 2022

AbstractOpium poppy (Papaver somniferum) is one of the world’s oldest medicinal plants and a versatile model system to study secondary metabolism. However, our knowledge of its genetic diversity is limited, restricting utilization of the available germplasm for research and crop improvement. We used genotyping-by-sequencing to investigate the extent of genetic diversity and population structure in a collection of poppy germplasm consisting of 91 accessions originating in 30 countries of Europe, North Africa, America, and Asia. We identified five genetically distinct subpopulations using discriminate analysis of principal components and STRUCTURE analysis. Most accessions obtained from the same country were grouped together within subpopulations, likely a consequence of the restriction on movement of poppy germplasm. Alkaloid profiles of accessions were highly diverse, with morphine being dominant. Phylogenetic analysis identified genetic groups that were largely consistent with the subpopulations detected and that could be differentiated broadly based on traits such as number of branches and seed weight. These accessions and the associated genotypic data are valuable resources for further genetic diversity analysis, which could include definition of poppy core sets to facilitate genebank management and use of the diversity for genetic improvement of this valuable crop.
Atypical dependence of excited exciton energy levels and electron-hole correlation on emission energy in pyramidal InP-based quantum dots
Authors: Gawełczyk Michał 
Published: January 2022

AbstractWe calculate the spectrum of excited exciton states in application-relevant self-assembled pyramidal quantum dots grown in InAs/InP and InAs/AlGaInAs material systems. These types of dots have been recently shown to combine the emission in the third optical fiber window with low surface density and a reasonable level of in-plane symmetry of emitters, which predestines them for studies on single- and entangled-photon emission and for corresponding applications. The spectrum of optically active excited states is crucial for successful resonant and quasi-resonant excitation of emitters, allowing for conservation of angular momentum and addressing individual selected quantum states. Here, we show that in both types of studied dots, due to their specific morphology of truncated pyramid, the density of excited-state ladder, especially the s–p shell splitting may follow an unconventional dependence on emission energy, opposite to the one typically met in regular quantum dots. We obtain this result via modeling based on available morphological data and calculation within the multi-band $${{\varvec{k}} {\cdot } {\varvec{p}}}$$

k

·

p

envelope-function theory combined with the configuration-interaction method used to calculate exciton states. Then, we explain this observation in purely geometric terms, as a result of an increasing effective quantum confinement width in a pyramid that is progressively cut from the top. Additionally, we show that the inverted trend is also manifested in the amount of electron-hole correlation in the exciton ground state, which also shows an anomalous dependence on emission energy and quantum dot volume.
PEA-15 engages in allosteric interactions using a common scaffold in a phosphorylation-dependent manner
Authors: Ikedife Joyce , He Jianlin , Wei Yufeng 
Published: January 2022

AbstractPhosphoprotein enriched in astrocytes, 15 kDa (PEA-15) is a death-effector domain (DED) containing protein involved in regulating mitogen-activated protein kinase and apoptosis pathways. In this molecular dynamics study, we examined how phosphorylation of the PEA-15 C-terminal tail residues, Ser-104 and Ser-116, allosterically mediates conformational changes of the DED and alters the binding specificity from extracellular-regulated kinase (ERK) to Fas-associated death domain (FADD) protein. We delineated that the binding interfaces between the unphosphorylated PEA-15 and ERK2 and between the doubly phosphorylated PEA-15 and FADD are similarly composed of a scaffold that includes both the DED and the C-terminal tail residues of PEA-15. While the unphosphorylated serine residues do not directly interact with ERK2, the phosphorylated Ser-116 engages in strong electrostatic interactions with arginine residues on FADD DED. Upon PEA-15 binding, FADD repositions its death domain (DD) relative to the DED, an essential conformational change to allow the death-inducing signaling complex (DISC) assembly.