dataesr/scientific-paragraphs-categorization huggingface dataset:
05, Kappa Score of 0. 4 and Benjamini-Hochberg p-value corrections. The obtained networks of the enriched biochemical pathways and reactions contain a variety of functional nodes and edges. All the functional enrichment analysis and visualization of the omics information was carried out as per the recommendation for standardization of the methodology  [33] [34] [35] [36]. Protein-protein interaction amongst the salient genes. To better visualize the role of 126 salient genes in providing functionality to a particular phenotype by interaction amongst them, we evaluate the extent of protein-protein interaction (PPI) among those genes. All the salient protein-coding genes were analyzed for PPI in the STRING database with high confidence (0. 700) as threshold interaction score and all active interaction sources checked  37.
The isolated nodes were removed from the final result. The obtained networks of the enriched biochemical pathways and reactions contain a variety of functional nodes and edges. Various cluster terms were also evaluated, with Benjamini-Hochberg False Discovery Rate (FDR) less than 0. 05 to identify the most significant PPI cluster. Exploratory network analysis and statistics were evaluated using Cytoscape 33 and R 27. Survival analysis of the salient genes for CRC in TCGA data. Survival analysis of the protein-coding genes in CRC patients was evaluated using The Human Protein Atlas tool  38, 39. The CRC datasets available in the webserver contain mRNA expression levels of human genes from TCGA  [40] [41] [42]  of 597 cancer tissue samples from persons belonging to the alive/dead and male/female sub-group.
The effect of the top 10 salient protein-coding genes on these samples was investigated for the overall survival endpoint. Herein, the expression values in FPKM of individual genes in different samples with their clinical outcomes are grouped into lower higher expressions based on median expression value. Log-rank test for Kaplan-Meier plot was utilized to assess these two groups for survival endpoints. The effects of expression of the top 10 salient genes on patients' survival across multiple CRC microarray datasets were retrieved from PrognoScan server  43  to compare, assess and comprehend the novelty in the survival analysis of the genes in TCGA data  38, 39.
GT application in quantitative evaluation of prominence of genes, by considering their relationships with others, in initiation and progression of disease condition contributed immensely in understanding the behaviors of salient genes in manifesting disease  54, 55. Cooperative Game theoretical approaches such as Shapley value and Banzhaf value provided valuable insight into gene expression data analysis by screening the dataset for the most relevant genes involved in the condition of interest  52, 53. Previously, the GT approach exhibited its ability at par with classical centrality indices in evaluating each gene by its relevance. It also emphasized the function of genes as nodes present in the periphery of a co-expression network in modulating the complex biological pathways  56. We adopted a Game Theoretic approach in this model, especially the approach of Network games.
It emphasizes that when we consider such a co-expression network, LRI can substitute Shapley value. This is because LRI focuses on the linking abilities of the genes as a suitable candidate to demonstrate the significance of the genes and is based on the position value (a link based allocation rule)  21  , while Shapley value is based on the Myerson value, which is a player based allocation rule  54, 55. LRI establishes that any network game can precisely describe the gene interactions as it considers the cooperation among genes and how the genes are connected to a network providing a comprehensive description of the genetic markers and their combined effects  21. E-MTAB-6698 is a large (meta-) dataset that comprises gene expression of colorectal tissue samples data with relevant clinical history and conditions of 1566 persons from both the biological gender.
The whole-genome gene expression microarray data built on the GPL570 platform includes 121 colon samples from normal persons (as control), 1393 samples from the diseased part of the CRC patient, 37 samples from Adenoma patients, and 15 samples from patients suffering from Inflammatory bowel diseases. The overall dataset already proved its effectiveness by offering a very high degree of classification accuracy (0. 997) to test the RNAseq dataset during training and modelling the disease condition. It functions as an unmatched cohort data for investigating and determining salient genes crucial for CRC development  22, 23. Herein, we applied this game-theoretic LRI scoring  21  on the high-throughput CRC transcriptomics dataset to identify salient genes in CRC. Contrary to the conventional approach, the Game-Theoretic Link relevance Index identifies a gene's importance by considering genes' contribution to overall disease manifestation.
CellMarker is an enormous curated database of biomarkers, especially at the single-cell level containing more than 22,000 cell markers of different cell types, including cancer cells  30. To assess the uniqueness and novelty of the result in the present investigation, we extracted information of all the known biomarkers from the CellMarker database. Information of all the markers genes for cell types including Cancer cell, Cancer stem cell, Cancer stemlike cell, Tumor endothelial cell, and Tumor-propagating cell from the CellMarker database was retrieved. All the cell type individually provided information of 180 genes, which were further reduced to 171 after removing duplicates. We mapped 126 salient genes to Entrez ID for maintaining uniformity. One hundred twenty-four genes mapped to their corresponding Entrez ID except for two Genes IDs viz, LOC100129461 and LOC400965.
4 ; Supplementary File Table  S5 ). Acylglycerol catabolic process has been used as a biomarker for the diagnosis and/or prognosis of CRC, and the enzymes of acylglycerols are involved in CRC tumor growth survival and metastasis  74. Changes in the cellular carbohydrate metabolic process may precede the acquisition of driver mutations, ultimately leading to colonocyte transformation. These changes may not be uniform but rely on different pathways to adapt to nutrient availability  75. Muscular contraction was found to be enriched in the signal pathway of the differentially expressed genes associated with the early onset of CRC  29. Table  2. DEGs (Differentially Expressed Genes) in the CRC dataset. The genes that exhibited adjusted p-value of ≤ 0. 05 and Log2 Fold Change (LFC) ≥ 2 (two) were considered as DEG in the CRC dataset.
DEGs that are also present in the list of salient genes are denoted by (*). We searched for enriched Reactome pathways using all available genes as a reference from the database. Three terms viz. Muscle contraction, Smooth Muscle Contraction, Ion homeostasis exhibited high significant enrichment (Fig. 5A ; Supplementary File Table  S6 ). All the three Reactome pathway terms revealed equal enrichment with 33. 33% of the total terms distributed per group. Five (5) genes, viz. ACTG2, LMOD1, MYL9, TPM1, VCL are associated with Smooth Muscle Contraction (R-HSA:445355), four (4) genes viz. CASQ2, FXYD6, PLN, RYR3 are associated with Ion homeostasis (R-HSA:5578775) and ten (10) genes, viz, ACTC1, ACTG2, CASQ2, FXYD6,  LMOD1, MYL9, PLN, RYR3, TPM1, VCL, are associated with Muscle contraction (R-HSA:397014).
Genes We also searched for enriched Reactome reactions using all available genes as a reference from the database. Five (5) genes viz. LMOD1, TPM1, VCL, ACTG2, and MYL9 contributed towards very high significant enrichment (100% of the terms per group) exhibited by the term ' ATP Hydrolysis By Myosin (R-HSA:445699)' (Fig. 5B ; Supplementary File Table  S7 ). With Kappa Score of 0. 4, which is used to define term-term interrelations (edges) and functional groups based on shared genes between the terms, Reactome reactions viz. ATP Hydrolysis by Myosin (R-HSA:445699), Myosin Binds ATP (R-HSA:445700), Calcium Binds Caldesmon (R-HSA:445704), Release of ADP From Myosin (R-HSA:445705) exhibited high enrichment suggesting that the salient genes majorly associated with smooth muscle contractions activity.
Results obtained recently also suggest that the Muscle contraction and vascular smooth muscle contraction pathway as major affected molecular mechanisms in CRC  29  , which corroborate the inference of our present work. We investigated protein-protein interaction (PPI) among the salient genes (Fig. 6 ). STRING database  37  was able to identify 116 protein-coding genes as nodes and presented the PPI network. At a threshold confidence score of 0. 700 (high confidence score), a total of 26 edges were formed with an average node degree equal to 0. 448, the average local clustering coefficient of 0. 198. With expected number of edges equals 9, the network exhibited significant enrichment (p-value = 0. 00000141 < 0. 05). Total ten clusters were found with FDR p-value less than    S8  The most prominent clusters, CL:1326 and CL: 1328, consist of 10 and 8 protein-coding genes, respectively, and are associated with 'Muscle protein and Myofbril assembly'.
The smallest clusters, CL:25786, CL:1449, CL:1577, CL:6451, consist of only two protein-coding genes each. All the 10 clusters exhibited cluster value greater than 1 for Strength which is a measure of enrichment effect and is expressed as Log10 value of the ratio between observed gene count in the network and expected gene count suggesting and value lesser than 0. 05 for FDR, suggesting the results of high enrichments are statistically significant (Supplementary File Table  S8 ). It is also pertinent to note that some in vitro and in vivo reports suggest the top three genes viz. MIR143HG, AMOTL1, and ACTG2 may be associated with other cancer subtypes. However, after a thorough literature survey, we were not able to mine any data suggesting their etiological role in CRC development. MIR143HG (LRI = 0.
Our data mining suggests the unavailability of any previous information indicating the role of FAM219B in any cancer type. Notwithstanding the potential role of salient genes in other cancer types, the central role of MiR143HG, AMOTL1, ACTG2, FILIP1, ARHGEF17, FAM219B in the progression of CRC is inadequate and lacking in previous reports. Previous reports on TOP2A  100, 101  , ITPKB 101 , HAND1 102 , SERINC2  [103] [104] [105]  present a conjectural view of the importance of the gene in the progression of the CRC. Identifying the top salient genes as diapeutics biomarkers for CRC will be critical to diagnostics, predicting the disease's occurrence/recurrence, and improvising the therapeutics. Major statistical difference in weak expression and high expression of genes in Kaplan-Meier (KM) survival analysis highlights the importance of genes with respect to their significant contribution to cancer progression and development  50.
The median survival time between lower and higher expression of the genes are significantly different. Among the top 10 salient proteincoding genes, AMOTL1, ACTG2, FILIP1, ARHGEF17, FAM219B, ITPKB, HAND1 exhibited reduced survival probability with higher expression, contrary to the rest of the other genes, viz. TOP2A, TRAP1, SERINC2, which exhibited reduced survival probability with lower gene expression (Fig. 7 , also refer Supplementary File Figure  S1 -S10 for enlarged view). All the genes exhibit a distinct difference in the survival endpoints between the two expressions. The KM plot of the top 10 protein-coding salient genes (highlighted by the LRI score) revealed a significant contribution to the CRC patients' overall outcome. A survey of these top 10 salient genes in PrognoScan, a server to search relationship between expression of genes and patients' overall and disease-free survival across an ensemble of microarray datasets  43  , revealed variation in the results between the microarray datasets (Supplementary spreadsheet).
This variation in the results can be attributed (to some extent) to sampling error owing to the small-scale nature of the microarray dataset. Moreover, as most of these genes do not qualify characteristics of a DEG (t-test adjusted p-value of ≤ 0. 5 and Log Fold Change more than 2), they are not considered to be associated with the manifestation of disease outcome when applying conventional microarray analysis technique. MalaCards 106 is a comprehensive human disease/maladies database integrating data from more than seventy sources, including GeneCards 107 and GeneAnalytics  108. It provides 'MalaCards InFormaTion (MIFT) Score' , which signifies the richness of the gene's information against each disease associated with it; the higher the MIFT score, the more significant the annotation results of the gene is to the disease based on previously published literature  106.
The top 15 genes with the highest LRI score were further evaluated in the MalaCards database  106  to assess their annotation of the disease to the Gene to verify the significance of the results (Supplementary File Table  S9 ). Though varying MIFT score against major cancer is evident from multiple reports on the involvement in major cancer type, seven (7) genes viz. MIR143HG, AMOTL1, FILIP1, FAM219B, SERINC2, APOBR, MRPS9 exhibited no MIFT score and no results against CRC (aqua blue rows in Table  S9  of Supplementary File). Another seven (7) genes viz. TRAP1, ACTG2, HAND1, ITPKB, PAG1, CAMSAP1, ARHGEF17 are known to be associated with other cancer types as evident by the existence of prior reports on these genes; yet they exhibited low MIFT score against CRC, suggesting these genes lacks sufficient annotated information on the genes' involvement in CRC owing to the scanty number of the report as strong conclusive evidence to corroborate (olive green rows in Table  S9  of Supplementary File).
7 ) with significance assessment using Log-Rank tests  50, 116. The novelty of the method can be assessed from the fact that majority (except two) of the salient genes are absent in the existing knowledge database of cancer biomarkers (Fig. 1D ). The resulting salient genes showed a dearth of the previous reports in a highly cited and manually curated biomarkers database of repute  30. The report opens up new dimensions in investigating these salient genes by in vitro and in vivo experiments and ushers new hope in diapeutics by providing novel gene targets for mitigating the development and metastasis of CRC. The report also stresses the algorithm's effectiveness in assessing the importance of individual genes in cancer etiology, utilizing only expression patterns at the molecular scale. This report also presents an opportunity to pounder over the use of non-conventional GT approaches in assessing genes' relevance using genome-wide expression dataset for application in diapeutics to conquer this and other dreaded diseases.
Finally, we can conclude that the mortality caused by cancer can be checked by early diagnostic screening with the help of biomarkers and effective targeted therapeutics. The knowledge discovery of salient genes associated with CRC can fill many voids related to biomarkers, perturbed biochemical pathways, and genes' action during and prior to cancer development. We employed a game-theoretic link relevance Index (LRI) scoring approach on the high-throughput transcriptomics dataset to identify salient genes in CRC. One hundred and twenty-six (126) salient genes demonstrated a positive LRI score (LRI > 0), indicating the significance of these genes in network games of genes. Investigation of the diverse gene ontology revealed eleven overrepresentations for major Biological processes. GO term for regulation of ion transmembrane transporter activity (GO:0032412) exhibited overrepresentation of the Molecular Function while six overrepresentations were obtained for major Cellular Component.
Although considerable enrichment was observed for thirty-eight KEGG pathways and three Reactome pathways, no enrichment was observed for the salient genes concerning chromosome location. The investigation reports the centrality nature of MiR143HG, AMOTL1, ACTG2, FILIP1, ARHGEF17, FAM219B, and other genes in CRC progression, which is lacking in previous studies and public repositories. Furthermore, the resulting information will enhance and supplement the existing knowledge base on CRC and aid future diapeutics investigations. The robustness of the present findings provides the opportunity to re-evaluate the genes associated with diseases and expand the gene-disease databases. The report also highlights LRI algorithms aided genes assessment to evaluate their contribution as a major factor with an etiological role in complex human disease conditions.
Acknowledgements VJB and BS thankfully acknowledge research grants provided by the  Department of Biotechnology, Government of India  (Grant No. BT/PR25099/NER/95/1014/2017 ). SB and RK are greatly indebted to  UK-India Education and Research Initiative (UKIERI)  for their generosity and financial support (Grant No. 184-15/2017(IC) ). SB also extends appreciation and acknowledgement for the financial support received from  Assam Science Technology & Environment Council (ASTEC), Government of Assam  (Grant No. ASTEC/S&T/192(171)/2019-20/2762 ).
Data availability The meta-dataset analysed (E-MTAB-6698) during the current study are available in the [Arrayexpress] repository, [https:// www. ebi. ac. uk/ array expre ss/ exper iments/ E-MTAB-6698/]. All data generated during this study are included in this published article [and its supplementary information files]. The in-house script for calculating the LRI is available at https:// github. com/ Vishw abaru ah/ GT_ LRI.
Data and data sources Vaccination data of different countries of the world are available through several sources including WHO, UNICEF and country-level immunisation programmes. The WHO/UNICEF Estimates of National Immunization Coverage (WUENIC) is the principal source of information for this analysis. 27 The WUENIC information goes through a few quality checks including the consideration of contextual factors like stock-outs. In case of very few missing information, country-level programme information was accessed to obtain a complete set of vaccine coverage data by antigens for the years 1980-2018. Information on economic status of the countries around 2018 was obtained from the World Development Indicators of the World Bank. 28 Based on the World Bank classification, countries were categorised as either low income, lower middle income, upper middle income and high income.
14 For antigens being used for many years prior to the introduction of combination vaccines, the effect on coverage is modest but still significant. 1] [22] [23]  This aligns well with the WHO recommendation of including at least one dose of IPV worldwide. The empirical results of this research imply that the introduction of wP-hexavalent vaccine will likely improve the coverage of IPV compared with IPV as a standalone. Such combination vaccines will also help sustain the high coverage of polio vaccination in the longer run worldwide. The study has various limitations. Although the data quality used in the analysis is presumed to be good, there are still few missing data on vaccine coverage. The number of missing values, however, is not large enough to create estimation problem. For this study, information on the year of introduction of wP-pentavalent vaccines was collected from various sources including Gavi; but for a limited number of countries, the year of introduction of pentavalent vaccines was found to be inconsistent with the vaccine coverage data on HepB and Hib.
In any case, logistic model shows very similar results as the linear model in terms of effect of introduction of pentavalent vaccine on coverage rates of DTP3, HepB3 and Hib3. Interpreting the coefficients of linear model is also easier than interpreting logistic function coefficients. The fourth limitation is the 'reduced' number of sample countries and years in the data set for the estimation of HepB and Hib coverage equations. The reduced sample size lowered the relative importance of low-income countries in the data set. The HepB coverage model was based on 67 countries while the Hib coverage model had only 17 countries. If the number and country characteristics create any bias in the empirical estimation, the bias should be lower for HepB. The estimates suggest that the incremental coverage effect of both HepB and Hib was probably about 10 percentage points suggesting that the potential bias, if any, is likely to be very small.
Acknowledgements We thank  Carole Doudet  and  Marsha Ginson  for their contributions to the conception of the study and data gathering. We thank  Roopsha Brahma , for editorial assistance and manuscript coordination on behalf of  Sanofi Pasteur. We thank  Rama Mylapuram  and  Saili Dharadhar  for providing editorial support for this manuscript. Contributors MMK and LC contributed to the conceptualisation of the paper. MMK, JCV-Z and LC contributed to the empirical methodology development, formal analysis, drafting, reviewing and editing the paper. MMK, JCV-Z and LC are responsible for the conduct of the study, had access to the data, reviewed the manuscript and had responsibility for the decision to submit for publication.
Animal preparation We obtained data from 9 healthy adult Merino ewes included in an experimental study of sheep undergoing aseptic surgical procedures under general anesthesia  [18]. The study was approved by the Animal Ethics Committee of the Florey Institute of Neuroscience and Mental Health under guidelines laid down by the National Health and Medical Research Council of Australia. A similar fiberoptic luminescence optode (Oxford Optronix, Abingdon, UK) used in human patients was inserted into the lumen of the urinary catheter and surgically inserted into the renal medulla. The tissue oxygen tension was continuously recorded at 100 Hz on a computer using a CED micro 1401 interface with Spike 2 software (Cambridge Electronic Design, Cambridge, United Kingdom).
Experimental protocol for the variation of FiO2 The protocol had 4 components of 20-min duration: a 10-min period to allow oxygen levels to stabilize followed by a 10-min experimental period. Our primary experimental stabilization criteria included renal medullary PO 2 and urinary PO 2. This timing was determined by assessing the medullary and urinary PO 2 values over time. A block randomization was used to set FiO 2 at 0. 21, 0. 40, 0. 60 and 1. 0. The total gas flow on the mechanical ventilator was maintained at a constant rate of 1. 5 L/min, whilst the ratio of the individual oxygen-to-air gas volumes was altered to achieve the target FiO 2. For the current analysis, we obtained data from the periods when FiO 2 levels were 0. 21 and 0. 40.
Key findings We conducted an observational study in human septic patients to determine whether PuO 2 is affected by changes in systemic oxygenation during routine care of patients with septic shock. As expected, changes of FiO 2 resulted in significant changes in PaO 2. However, we found no significant differences between PuO 2 measured before and after the interventions occurred. We supported our clinical findings with data from an experimental sheep experiment showing that medullary and urinary oxygen tension measurements did not differ within a similar range of FiO 2 variation.
Patients Sixty eligible patients were enrolled in the study. Patient demographics, enrollment, and follow-up flow are summarized in Table  1  and Supplemental Figure  2 , Supplementary Digital Content 1, http://links. lww. com/CTG/A833. Of the 60 enrolled patients, 52 completed the study. Of those, 50 patients had evaluable MRE examination and histological data available for correlation assessments. Two patients had unevaluable histological samples because of missing bowel wall layers.