bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automated invoice data extraction using image processing
Authors: Manjunath Akanksh Aparna , Nayak Manjunath Sudhakar , Nishith Santhanam , Pandit Satish Nitin , Sunkad Shreyas , Deenadhayalan Pratiba , Gangadhara Shobha 
Published: December 2022

Manually processing invoices which are in the form of scanned photocopies is a time-consuming process. There is a need to automate the task of extraction of data from the invoices with a similar format. In this paper we investigate and analyse various techniques of image processing and text extraction to improve the results of the optical character recognition (OCR) engine, which is applied to extract the text from the invoice. This paper also proposes the design and implementation of a web enabled invoice processing system (IPS). The IPS consists of an annotation tool and an extraction tool. The annotation tool is used to mark the fields of interest in the invoice which are to be extracted. The extraction tool makes use of opensource computer vision library (OpenCV) algorithms to detect text. The proposed system was tested on more than 25 types of invoices with the average accuracy score lying between 85% and 95%. Finally, to provide ease of use, a web application is developed which also presents the results in a structured format. The entire system is designed so as to provide flexibility and automate the process of extracting details of interest from the invoices.
Using skeleton model to recognize human gait gender
Authors: Alsaif Omar Ibrahim , Hasan Saba Qasim , Maray Abdulrafa Hussain 
Published: December 2022

<span lang="EN-US">Biometrics became fairly important to help people identifications persons by their individualities or features. In this paper, gait recognition has been based on a skeleton model as an important indicator in prevalent activities. Using the reliable dataset for the Chinese Academy of Sciences (CASIA) of silhouettes class C database. Each video has been discredited to 75 frames for each (20 persons (10 males and 10 females)) as (1.0), the result will be 1,500 frames. After Pre-processing the images, many features are extracted from human silhouette images. For gender classification, the human walking skeleton used in this study. The model proposed is based on morphological processes on the silhouette images. The common angle has been computed for the two legs. Later, principal components analysis (PCA) <em></em>was <em></em>applied <em></em>to <em></em>reduce <em></em>data <em></em>using <em></em>feature <em></em>selection <em></em>technology <em></em>to <em></em>get <em></em>the <em></em>most <em></em>useful <em></em>information in <em></em>gait <em></em>analysis. Applying two classifiers artificial neural network (ANN) and Gaussian Bayes to distinguish male or female for each classifier. The experimental results for the suggested method provided significant accomplishing about (95.5%), and accuracy of (75%). Gender classification using ANN is more efficient from the Gaussian Bayes technique by (20%), where ANN technique has given a superior performance in recognition.</span>
Repurposing Ivermectin to augment chemotherapy’s efficacy in osteosarcoma
Authors: Hu B , Tan H , Yu L , Liao Q , Guo W 
Published: December 2022

Background Osteosarcoma is the most frequent malignant bone malignancy and the current treatments are ineffective. Ivermectin, an anti-protozoal drug, has been shown to have anti-cancer activity. This work investigated the potential of repurposing ivermectin to augment chemotherapy’s efficacy in osteosarcoma. Methods Proliferation, migration and apoptosis assays were performed in ivermectin-treated osteosarcoma cells. Combination studies were performed. Osteosarcoma xenograft mouse model was established to investigate the in vivo efficacy of ivermectin. Intracellular reactive oxygen species (ROS) and mitochondrial superoxide, membrane potential, ATP, 8-OHdG level, protein carbonylation and lipid peroxidation were determined after ivermectin treatment. Results Ivermectin was effective and acted synergistically with doxorubicin in osteosarcoma cells regardless of cellular origin and genetic profiling. This was achieved through suppressing inhibiting growth and migration, and inducing caspase-dependent apoptosis. Ivermectin also significantly inhibited osteosarcoma growth in vivo and its combination with doxorubicin resulted in much greater efficacy than doxorubicin alone. Importantly, the effective dose of ivermectin was clinically feasible and did not cause significant toxicity in mice. Mechanistical analysis showed that ivermectin induced oxidative stress and damage, and mitochondrial dysfunction. Conclusions Our findings indicate that ivermectin has utility in treating patients with osteosarcoma, especially those resistant to chemotherapy.
Adenine base editor–mediated correction of the common and severe IVS1-110 (G&gt;A) β-thalassemia mutation
Authors: Hardouin Giulia , Antoniou Panagiotis , Martinucci Pierre , Felix Tristan , Manceau Sandra , Joseph Laure , Masson Cécile , Scaramuzza Samantha , Ferrari Giuliana , Cavazzana Marina , Miccio Annarita 
Published: December 2022

Abstract
β-Thalassemia (BT) is one of the most common genetic diseases worldwide and is caused by mutations affecting β-globin production. The only curative treatment is allogenic hematopoietic stem/progenitor cells (HSPCs) transplantation, an approach limited by compatible donor availability and immunological complications. Therefore, transplantation of autologous, genetically-modified HSPCs is an attractive therapeutic option. However, current gene therapy strategies based on the use of lentiviral vectors are not equally effective in all patients and CRISPR/Cas9 nuclease-based strategies raise safety concerns. Thus, base editing strategies aiming to correct the genetic defect in patients’ HSPCs could provide safe and effective treatment. Here, we developed a strategy to correct one of the most prevalent BT mutations (IVS1-110 [G&gt;A]) using the SpRY-ABE8e base editor. RNA delivery of the base editing system was safe and led to ∼80% of gene correction in the HSPCs of patients with BT without causing dangerous double-strand DNA breaks. In HSPC-derived erythroid populations, this strategy was able to restore β-globin production and correct inefficient erythropoiesis typically observed in BT both in vitro and in vivo. In conclusion, this proof-of-concept study paves the way for the development of a safe and effective autologous gene therapy approach for BT.
OR2AT4 and OR1A2 counterregulate molecular pathophysiological processes of steroid-resistant inflammatory lung diseases in human alveolar macrophages
Authors: Weidinger Daniel , Jamal Jameel Kaschin , Alisch Desiree , Jacobsen Julian , Bürger Paul , Ruhe Matthias , Yusuf Faisal , Rohde Simon , Störtkuhl Klemens , Kaufmann Peter , Kronsbein Juliane , Peters Marcus , Hatt Hanns , Giannakis Nikolaos , Knobloch Jürgen 
Published: December 2022

AbstractBackgroundTherapeutic options for steroid-resistant non-type 2 inflammation in obstructive lung diseases are lacking. Alveolar macrophages are central in the progression of these diseases by releasing proinflammatory cytokines, making them promising targets for new therapeutic approaches. Extra nasal expressed olfactory receptors (ORs) mediate various cellular processes, but clinical data are lacking. This work investigates whether ORs in human primary alveolar macrophages could impact pathophysiological processes and could be considered as therapeutic targets.MethodsHuman primary alveolar macrophages were isolated from bronchoalveolar lavages of 50 patients with pulmonary diseases. The expression of ORs was validated using RT-PCR, immunocytochemical staining, and Western blot. Changes in intracellular calcium levels were analyzed in real-time by calcium imaging. A luminescent assay was used to measure the cAMP concentration after OR stimulation. Cytokine secretion was measured in cell supernatants 24 h after stimulation by ELISA. Phagocytic ability was measured by the uptake of fluorescent-labeled beads by flow cytometry.ResultsWe demonstrated the expression of functional OR2AT4 and OR1A2 on mRNA and protein levels. Both ORs were primarily located in the plasma membrane. Stimulation with Sandalore, the ligand of OR2AT4, and Citronellal, the ligand of OR1A2, triggered a transient increase of intracellular calcium and cAMP. In the case of Sandalore, this calcium increase was based on a cAMP-dependent signaling pathway. Stimulation of alveolar macrophages with Sandalore and Citronellal reduced phagocytic capacity and release of proinflammatory cytokines.ConclusionThese are the first indications for utilizing olfactory receptors as therapeutic target molecules in treating steroid-resistant lung diseases with non-type 2 inflammation.
Deficiency of mindin reduces renal injury after ischemia reperfusion
Authors: Bai Tao , Wang Xiong , Qin Cong , Yang Kang , Duan Zhiguo , Cao Zhixiu , Liang Jiaqian , Wang Lei , Yuan Jingdong , Luo Pengcheng 
Published: December 2022

Abstract
Background
Acute renal injury (AKI) secondary to ischemia reperfusion (IR) injury continues to be a significant perioperative problem and there is no effective treatment. Mindin belongs to the mindin/F-spondin family and involves in inflammation, proliferation, and cell apoptosis. Previous studies have explored the biological functions of mindin in liver and brain ischemic injury, but its role in AKI is unknown.

Method
To investigate whether mindin has a pathogenic role, mindin knockout (KO) and wild-type (WT) mice were used to establish renal IR model. After 30 min of ischemia and 24 h of reperfusion, renal histology, serum creatinine, and inflammatory response were examined to assess kidney injury. In vitro, proinflammatory factors and inflammatory signaling pathways were measured in mindin overexpression or knockdown and vector cells after hypoxia/reoxygenation (HR).

Results
Following IR, the kidney mindin level was increased in WT mice and deletion of mindin provided significant protection for mice against IR-induced renal injury as manifested by attenuated the elevation of serum creatinine and blood urea nitrogen along with less severity for histological alterations. Mindin deficiency significantly suppressed inflammatory cell infiltration, TNF-α and MCP-1 production following renal IR injury. Mechanistic studies revealed that mindin deficiency inhibits TLR4/JNK/NF-κB signaling activation. In vitro, the expression levels of TNF-α and MCP-1 were increased in mindin overexpression cells compared with vector cells following HR. Moreover, TLR4/JNK/NF-κB signaling activation was elevated in the mindin overexpression cells in response to HR stimulation while mindin knockdown inhibited the activation of TLR4/JNK/ NF-κB signaling after HR in vitro. Further study showed that mindin protein interacted directly with TLR4 protein. And more, mindin protein was confirmed to be expressed massively in renal tubule tissues of human hydronephrosis patients.

Conclusion
These data demonstrate that mindin is a critical modulator of renal IR injury through regulating inflammatory responses. TLR4/JNK/NF-κB signaling most likely mediates the biological function of mindin in this model of renal ischemia.
Oxidized LDL promotes EMS-induced angiogenesis by increasing VEGF-A expression and secretion by endometrial cells
Authors: Ma Caiqi , Huang Wei , Wang Hui , Yao Wenxia , Liang Min , Yu Guifang , Zhou Xinke 
Published: December 2022

Abstract
Background
Endometriosis (EMS) is a “tumour-like” gynaecological disease with distant metastasis, and studies have shown that EMS can induce distant metastasis through vascular vessels, but the driving factors and their mechanism are not clear.

Methods
We used an EMS animal model and gene knockout technique to explore the role of EMS-induced angiogenesis in EMS metastasis in vivo and in vitro and clarify the role and molecular mechanism of oxLDL in promoting EMS-induced angiogenesis.

Results
We found that microvascular density (MVD) in metastasized ectopic endometrium and eutopic endometrial tissue was higher than that in normal endometrial tissue, and plasma oxLDL was positively correlated with the distant metastasis of EMS. Furthermore, we clarified that oxLDL enhanced the MVD of endometrial tissue by increasing VEGF-A expression and secretion in endometrial cells. Finally, we illustrated the mechanism by which oxLDL promotes VEGF-A expression through the AKT-HIF-1α signalling pathway.

Conclusion
OxLDL is a risk factor promoting distant EMS metastasis by increasing VEGF-A expression and secretion through AKT-HIF-1α signalling. This finding may provide theoretical support and therapeutic targets for the clinical prevention and treatment of EMS.
Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques
Authors: Cappelletti Luca , Petrini Alessandro , Gliozzo Jessica , Casiraghi Elena , Schubach Max , Kircher Martin , Valentini Giorgio 
Published: December 2022

Abstract
Background
Cis-regulatory regions (CRRs) are non-coding regions of the DNA that fine control the spatio-temporal pattern of transcription; they are involved in a wide range of pivotal processes such as the development of specific cell-lines/tissues and the dynamic cell response to physiological stimuli. Recent studies showed that genetic variants occurring in CRRs are strongly correlated with pathogenicity or deleteriousness. Considering the central role of CRRs in the regulation of physiological and pathological conditions, the correct identification of CRRs and of their tissue-specific activity status through Machine Learning methods plays a major role in dissecting the impact of genetic variants on human diseases. Unfortunately, the problem is still open, though some promising results have been already reported by (deep) machine-learning based methods that predict active promoters and enhancers in specific tissues or cell lines by encoding epigenetic or spectral features directly extracted from DNA sequences.

Results
We present the experiments we performed to compare two Deep Neural Networks, a Feed-Forward Neural Network model working on epigenomic features, and a Convolutional Neural Network model working only on genomic sequence, targeted to the identification of enhancer- and promoter-activity in specific cell lines. While performing experiments to understand how the experimental setup influences the prediction performance of the methods, we particularly focused on (1) automatic model selection performed by Bayesian optimization and (2) exploring different data rebalancing setups for reducing negative unbalancing effects.

Conclusions
Results show that (1) automatic model selection by Bayesian optimization improves the quality of the learner; (2) data rebalancing considerably impacts the prediction performance of the models; test set rebalancing may provide over-optimistic results, and should therefore be cautiously applied; (3) despite working on sequence data, convolutional models obtain performance close to those of feed forward models working on epigenomic information, which suggests that also sequence data carries informative content for CRR-activity prediction. We therefore suggest combining both models/data types in future works.
SC3s: efficient scaling of single cell consensus clustering to millions of cells
Authors: Quah Fu Xiang , Hemberg Martin 
Published: December 2022

Abstract
Background
Today it is possible to profile the transcriptome of individual cells, and a key step in the analysis of these datasets is unsupervised clustering. For very large datasets, efficient algorithms are required to ensure that analyses can be conducted with reasonable time and memory requirements.

Results
Here, we present a highly efficient k-means based approach, and we demonstrate that it scales favorably with the number of cells with regards to time and memory.

Conclusions
We have demonstrated that our streaming k-means clustering algorithm gives state-of-the-art performance while resource requirements scale favorably for up to 2 million cells.
DiviK: divisive intelligent K-means for hands-free unsupervised clustering in big biological data
Authors: Mrukwa Grzegorz , Polanska Joanna 
Published: December 2022

AbstractBackgroundInvestigating molecular heterogeneity provides insights into tumour origin and metabolomics. The increasing amount of data gathered makes manual analyses infeasible—therefore, automated unsupervised learning approaches are utilised for discovering tissue heterogeneity. However, automated analyses require experience setting the algorithms’ hyperparameters and expert knowledge about the analysed biological processes. Moreover, feature engineering is needed to obtain valuable results because of the numerous features measured.ResultsWe propose DiviK: a scalable stepwise algorithm with local data-driven feature space adaptation for segmenting high-dimensional datasets. The algorithm is compared to the optional solutions (regular k-means, spatial and spectral approaches) combined with different feature engineering techniques (None, PCA, EXIMS, UMAP, Neural Ions). Three quality indices: Dice Index, Rand Index and EXIMS score, focusing on the overall composition of the clustering, coverage of the tumour region and spatial cluster consistency, are used to assess the quality of unsupervised analyses. Algorithms were validated on mass spectrometry imaging (MSI) datasets—2D human cancer tissue samples and 3D mouse kidney images. DiviK algorithm performed the best among the four clustering algorithms compared (overall quality score 1.24, 0.58 and 162 ford(0, 0, 0), d(1, 1, 1) and the sum of ranks, respectively), with spectral clustering being mostly second. Feature engineering techniques impact the overall clustering results less than the algorithms themselves (partial$$\eta ^2$$η2effect size: 0.141 versus 0.345, Kendall’s concordance index: 0.424 versus 0.138 ford(0, 0, 0)).ConclusionsDiviK could be the default choice in the exploration of MSI data. Thanks to its unique, GMM-based local optimisation of the feature space and deglomerative schema, DiviK results do not strongly depend on the feature engineering technique applied and can reveal the hidden structure in a tissue sample. Additionally, DiviK shows high scalability, and it can process at once the big omics data with more than 1.5 mln instances and a few thousand features. Finally, due to its simplicity, DiviK is easily generalisable to an even more flexible framework. Therefore, it is helpful for other -omics data (as single cell spatial transcriptomic) or tabular data in general (including medical images after appropriate embedding). A generic implementation is freely available under Apache 2.0 license athttps://github.com/gmrukwa/divik.
Regulation of feather follicle development and Msx2 gene SNP degradation in Hungarian white goose
Authors: Song Yupu , Liu Chang , Zhou Yuxuan , Lin Guangyu , Xu Chenguang , Msuthwana Petunia , Wang Sihui , Ma Jingyun , Zhuang Fangming , Fu Xianou , Wang Yudong , Liu Tuoya , Liu Qianyan , Wang Jingbo , Sui Yujian , Sun Yongfeng 
Published: December 2022

Abstract
Background
Hungarian white goose has excellent down production performance and was introduced to China in 2010. The growth and development of feather follicles has an important impact on down production. Goose feather follicles can be divided into primary and secondary feather follicles, both of which originate in the embryonic stage. Msx2 (Msh Homeobox 2) plays a regulatory role in tissues and organs such as eyes, teeth, bones and skin. However, its regulatory mechanism on goose feather follicles development remains unclear.

Results
Msx2 gene first increased, then decreased and increased at the end (E13, E18, E23, E28) during embryonic feather follicle development, and the expression level was the highest at E18. The pEGFP-N1-Msx2 overexpression vector and si-Msx2 siRNA vector were constructed to transfect goose embryo dermal fibroblasts. The results showed that the cell viability of ov-Msx2 group was significantly increased, and the gene expression levels of FGF5 and TGF-β1 genes were significantly down-regulated (P < 0.05), the expressions of PCNA, Bcl2, CDK1, FOXN1 and KGF genes were significantly up-regulated (P < 0.05). After transfection of siRNA vector, the cell viability of the si-Msx2 group was significantly decreased (P < 0.01) compared with the si-NC group. TGF-β1 expression was significantly up-regulated (P < 0.05), FGF5 expression was extremely significantly up-regulated (P < 0.01), while PCNA, Bcl2, CDK1, FOXN1 and KGF gene expression was significantly down-regulated (P < 0.05). High-throughput sequencing technology was used to mine the exon SNPs of Msx2. A total of 11 SNP loci were screened, four of the SNPs located in exon 1 were missense mutations. The feather follicle diameter of the GC genotype at the G78C site is significantly larger than that of the other two genotypes.

Conclusions
Msx2 maybe inhibit the apoptosis of goose dermal fibroblasts and promotes their proliferation. G78C can be used as a potential molecular marker for downy Variety.
RpoN is required for the motility and contributes to the killing ability of Plesiomonas shigelloides
Authors: Yan Junxiang , Guo Xueqian , Li Jinghao , Li Yuehua , Sun Hongmin , Li Ang , Cao Boyang 
Published: December 2022

AbstractBackgroundRpoN, also known as σ54, first reported inEscherichia coli, is a subunit of RNA polymerase that strictly controls the expression of different genes by identifying specific promoter elements. RpoN has an important regulatory function in carbon and nitrogen metabolism and participates in the regulation of flagellar synthesis, bacterial motility and virulence. However, little is known about the effect of RpoN inPlesiomonas shigelloides.ResultsTo identify pathways controlled by RpoN, RNA sequencing (RNA-Seq) of the WT and therpoNdeletion strain was carried out for comparison. The RNA-seq results showed that RpoN regulates ~ 13.2% of theP. shigelloidestranscriptome, involves amino acid transport and metabolism, glycerophospholipid metabolism, pantothenate and CoA biosynthesis, ribosome biosynthesis, flagellar assembly and bacterial secretion system. Furthermore, we verified the results of RNA-seq using quantitative real-time reverse transcription PCR, which indicated that the absence ofrpoNcaused downregulation of more than half of the polar and lateral flagella genes inP. shigelloides, and the ΔrpoN mutant was also non-motile and lacked flagella. In the present study, the ability of the ΔrpoNmutant to kill E. coliMG1655 was reduced by 54.6% compared with that of the WT, which was consistent with results in RNA-seq, which showed that the type II secretion system (T2SS-2) genes and the type VI secretion system (T6SS) genes were repressed. By contrast, the expression of type III secretion system genes was largely unchanged in the ΔrpoNmutant transcriptome and the ability of the ΔrpoNmutant to infect Caco-2 cells was also not significantly different compared with the WT.ConclusionsWe showed that RpoN is required for the motility and contributes to the killing ability ofP. shigelloidesand positively regulates the T6SS and T2SS-2 genes.