dataesr/scientific-paragraphs-categorization huggingface dataset:
The p-values were adjusted with the "FDR" method. Taxonomic features with adjusted p-values smaller than 0. 05 were regarded as significantly different in relative abundance between the treatments. We were interested whether variation in T. rugatulus gut communities could be explained by the expression of effector genes involved in antimicrobial immunity. Therefore we looked for the presence of such genes among the contigs and checked whether these contigs were significantly differentially higher expressed in immune-challenged compared to non-immune-challenged individuals. If multiple contigs were annotated with the same effector gene name, we chose the contig with the highest average expression (TPM). With the resulting set of contigs we completed a constrained ordination analysis with the capscale function of the R package vegan (distance-based redundancy analysis, Bray-Curtis)  [89].
Acknowledgements Many thanks to  Marion Kever  for lab support and  Barbara Feldmeyer  for her help with ant collection and her general contributions to the project. We are greatly indebted to  Thomas Onchuru  and  Martin Kaltenpoth  for providing us with the firebug 16S DNA copy mixture and the universal 16S primers. The authors thank the  LOEWE-Centre TBG  funded by the  Hessen State Ministry of Higher Education, Research and the Arts (HMWK).
However, prevalence of ZBTB38 expression in prostate cancer remains to be properly documented. Here, we tested the clinical significance of ZBTB38 expression in prostate cancer, based on the analysis of publicly available and freely re-usable large-scale genomic and clinical datasets. We show that ZBTB38 expression is decreased in localised prostate cancer, and further in metastatic prostate cancer. The low expression of ZBTB38 is associated with increased genomic instability in localised tumours, which may favour cancer progression. We also show that ZBTB38 is an independent marker of prognosis. Gene expression profiling further unravelled a gene signature correlated with ZBTB38 expression in localised tumours that suggests increased efficacy of a ROS-generating drug, doxorubicin, in tumours with low expression levels of ZBTB38.
ZBTB38 Expression Is Lower in Prostate Cancer Compared to Non-Cancerous Prostate Tissues To study ZBTB38 significance in prostate cancer, we exploited publicly available data from several published prostate cancer study cohorts that have both comprehensive molecular and clinico-pathological data. We selected datasets reporting high-throughput gene expression in prostate cancer (localised and metastatic specimens) using benign/normal prostate tissues as controls, with at least five specimens in each group (benign/normal and cancerous) and with gene expression profiling obtained by microarray. We identified nine microarray datasets reporting the expression levels of ZBTB38 in cancerous and non-cancerous specimens with these criteria  [12, 14, [45] [46] [47] [48] [49] [50] [51]. The differential expression of ZBTB38 between control and prostate cancer specimens was computed separately for each cohort.
We found that in eight of these nine cohorts, the expression of ZBTB38 is significantly lower in localised prostate cancer compared to normal/benign prostate tissues (Table  1 ). In the four cohorts reporting gene expression data in metastatic prostate cancer, we observed a significant decrease of ZBTB38 expression levels in metastatic prostate cancer compared to normal/benign prostate tissues, as well as localised prostate cancer (Table  1  and Figure  1a-c ). To extend our analysis, we also interrogated the TCGA database reporting gene expression profiling obtained by RNA-sequencing in 52 normal prostate specimens and 498 localised prostate cancer  [13]. In this cohort, ZBTB38 expression is also significantly lower in prostate cancer compared to normal prostate tissues (Figure  1d ). ZBTB38 mRNA levels is thus consistently lower in prostate cancer compare to non-cancerous prostate tissue.
In Taylor's cohort (GSE21032)  [12]  we observed no correlation between ZBTB38 expression levels and patient's age (p = 0. 160), seminal vesicle invasion (p = 0. 725), lymph node involvement (p = 0. 324), surgical margin status (p = 0. 343), extra capsular extension (p = 0. 267) and clinical grade of the tumour (p = 0. 994) (Table  2 ). Interestingly, we observed clear significant correlation between low expression of ZBTB38 and high PSA levels pre-therapy (p = 0. 013) or at diagnosis (p = 0. 03) and high pathological grade (i. e. , T3/T4) of the tumours (p = 0. 019). We also found a tendency between low expression of ZBTB38 and higher Gleason score (p = 0. 059) (Table  2 ). In Kunderfranco's cohort (GSE14206)  [50] , we observed a tendency between low ZBTB38 expression levels and high Gleason score (p = 0.
065) and a significant correlation with patient's age (p = 0. 044). We also observed that "ZBTB38-low" tumours are significantly associated to higher pathological grade (p = 0. 023) (Table  2 ). In Ross-Adams' cohort (GSE70770)  [48] , we observed no correlation between ZBTB38 expression level and patient's age (p = 0. 373), extra capsular extension (p = 0. 54), Gleason score (p = 0. 918), clinical grade (p = 0. 681), pathological grade of the tumour (p = 0. 194) and PSA levels at diagnosis (p = 0. 289) (Table  2 ). The only correlation we observed is with surgical margin status (p = 0. 0003) (Table  2 ). In the TCGA cohort  [13]  (reporting gene expression values by RNA-sequencing) we observed no correlation between ZBTB38 expression levels and patient's age (p = 0. 584) and PSA levels at diagnosis (p = 0.
Cancers 2020, 12, x 7 of 23 In Ross-Adams' cohort (GSE70770)  [48] , we observed no correlation between ZBTB38 expression level and patient's age (p = 0. 373), extra capsular extension (p = 0. 54), Gleason score (p = 0. 918), clinical grade (p = 0. 681), pathological grade of the tumour (p = 0. 194) and PSA levels at diagnosis (p = 0. 289) (Table  2 ). The only correlation we observed is with surgical margin status (p = 0. 0003) (Table  2 ). In the TCGA cohort  [13]  (reporting gene expression values by RNA-sequencing) we observed no correlation between ZBTB38 expression levels and patient's age (p = 0. 584) and PSA levels at diagnosis (p = 0. 449). By contrast, we observed a significant association of "ZBTB38-low" tumours to positive surgical margin status (p = 0. 014) and high Gleason score (p = 0.
ZBTB38 Expression Level Is an Independent Prognostic Factor of Disease-Free Survival Our data show a significant association between low ZBTB38 expression levels and more aggressive and recurrent prostate tumours. We thus used the C-index to measure the prognostic performance of ZBTB38 mRNA expression. The C-indexes were 0. 76, 0. 791 and 0. 716 in the Taylor, TCGA and Ross-Adams cohorts respectively (Table  3 ). Low ZBTB38 expression is thus a good predictor of disease-recurrence, as Gleason score and PSA levels at diagnosis (Table  3 ). Multivariate cox analyses were also used to examine association between disease-free survival, ZBTB38 mRNA expression and other clinico-pathological factors. We demonstrated that ZBTB38 mRNA expression level predicted disease-free survival independently of Gleason score, PSA levels and positive margin status, in the Taylor's cohort and the TCGA cohort (Table  3 ).
Low Expression of ZBTB38 Associates with Genomic Instability in Localised Prostate Cancer To explore a possible mechanism linking ZBTB38 low expression with prostate cancer aggressiveness, we investigated whether ZBTB38 expression levels were associated with specific molecular features of prostate cancer. This analysis was done in Taylor and TCGA cohorts, which integrate large-scale prostate cancer genome characterization  [12, 13]. We first investigated the correlation between ZBTB38 expression levels with genome-wide instability and mutational burden. In the cohort of Taylor et al. (GSE21034)  [12]  we noticed that tumours with low expression of ZBTB38 (using the median expression value of ZBTB38 in the cohort) present high level of genomic instability define by heightened copy number aberrations (p = 0.
ZBTB38 Expression Is Not a Marker of Chromosomal Instability in Metastatic Prostate Cancer The comparison of clinical and molecular data between localised and metastatic tumours showed similarities and many differences  [13, 53]. We thus investigated the relationship between ZBTB38 expression and genomic parameters in metastatic tumours from three different datasets  [17, 26, 53]. We did not find significant association between ZBTB38 expression levels and patient's age, the proportion of the genome altered and the count of somatic mutations per tumour in the different datasets (Table  S5 ). Our analysis revealed that ZBTB38 expression correlates with overall genomic instability in localised but not in metastatic tumours. This observation suggests that low expression of ZBTB38 might contribute to increase chromosomal instability at early stages of the disease.
Our analysis identified 216 genes differentially expressed between tumours expressing low and high levels of ZBTB38 in at least three cohorts; and five genes differentially expressed in the four cohorts. These latter genes are the disintegrin metalloprotease (ADAM10), the armadillo repeat containing protein 8 (ARMC8), the NF-kB regulator COMM domain containing protein 8 (COMMD8), the early endosome antigen 1 (EEA1) and protein phosphatase 1 B (PPM1B). To validate these findings, we investigated the expression of these five genes in the RNA-sequencing datasets produced by TCGA (Figure  S1 ). We observed that the five genes were positively correlated with ZBTB38 expression in this cohort, indicating that their expression is down-regulated in "ZBTB38-low" tumours and strongly suggesting that they are co-regulated with ZBTB38 in prostate tumours.
Knock-Down of ZBTB38 Promotes ROS Accumulation, Cell Migration and Doxorubicin Toxicity in Prostate Cancer Cells. We further explored the role of ZBTB38 in prostate cancer by transfecting siRNA to knock-down ZBTB38 expression in prostate cancer cell lines, representative of different cancerous and hormonal status. RT-qPCR analysis indicated a strong down-regulation of ZBTB38 expression 48h post- Gene ontology analysis of the 216 differentially expressed genes reveals an enrichment for genes involved in cellular macromolecule catabolic process (FDR q-value = 6. 73 × 10 -8 ), proteosomal protein catabolic process (FDR q-value = 1. 21 × 10 -5 ), organelle assembly (FDR q-value = 3. 48 × 10 -6 ) and mitotic cell cycle (FDR q-value = 1. 43 × 10 -5 ) (Figure  4b ). An interrogation of the collection of gene sets in the molecular signatures database (MSigDB) further indicates an enrichment for genes regulated upon doxorubicin-induced cells death (q-value = 1.
ZBTB38 Expression Correlates with Prostate Cancer Progression and Is an Independent Prognostic Marker In the present study, we exploited 10 publicly available and well-annotated datasets (including gene expression, genomic information and clinico-pathological data) to unravel a function of ZBTB38 in prostate cancer. We observed that ZBTB38 is rarely mutated or rearranged in localised and metastatic prostate cancer. However, we observed that ZBTB38 has significantly lower level of expression in localised prostate cancer compare to benign tissues and the difference is extended in metastatic prostate cancer, whether ZBTB38 expression was monitored by micro-array or RNA-sequencing technology. We have also found that "ZBTB38-low" tumours are significantly associated with T3-T4 pathological grade, high PSA levels at diagnosis, positive surgical status, and higher Gleason score.
Microarray Databases and Selection of Datasets Microarray datasets were collected from the GEO repository (https://www. ncbi. nlm. nih. gov/ gds), the cBioPortal for Cancer Genomics portal (http://cbioportal. org) and the web-based cancer genomics resource Oncomine (https://www. oncomine. org/) [66] [67] [68]. We selected all datasets reporting high-throughput gene expression in localised and metastatic prostate tumours using normal (or benign) prostate tissues as controls, with at least five specimens in each group (benign/normal and cancerous). Twenty-six datasets met these requirements but array platforms often lack probes to monitor ZBTB38 expression (e. g. , GSE6099, GSE62872 and GSE6919). We eventually considered for our analysis the following datasets: GSE21032 (ZBTB38 ID: 4299)  [12] , GSE14206 (ZBTB38 ID: A_23_P212025)  [50] , GSE55945 (ZBTB38 ID: 15558733_at) [49], GSE3325 (ZBTB38 ID: 15558733_at)  [47] , GSE3933 (ZBTB38 ID: IMAGE50920)  [45] , Oncomine dataset VanajaProstate (ZBTB38 ID:22512_at)  [51] , GSE68545 (ZBTB38 ID:RC_AA465527)  [46] , GSE35988 (ZBTB38 ID: A_23_P380076)  [14]  and GSE70770 (ZBTB38 ID: ILMN_2248843)  [48].
A full description of the experimental protocols (including the number of samples, the methods to isolate RNA samples and the technology platform used for gene expression analysis) and clinical review of these datasets is available elsewhere  [1]  and in the respective GSE reports. Gene expression values from the Prostate Cancer and PanCancer TCGA cohorts were retrieved through the cBioPortal for Cancer Genomics portal  [13, 52]. Expression value were determined by RNA sequencing and expressed as mRNA gene expression (quantified using the RSEM package; https://github. com/deweylab/RSEM). Comparison between normal (N = 52) and prostate cancer (N = 498) specimen was directly retrieved from the Firebrowse website reporting processed TCGA data (http://firebrowse. org).
Clinical and Genomic Data Correlations Genomic and clinical data analysed are freely available, re-usable and anonymised. The following detailed parameters were extracted: GEO accession number, PubMed identified (PMID), sample type, sample size, age, cancer clinical and pathological stage, disease-free survival and gene expression values by using the GEO2R from the National Center for Biotechnology Information (NCBI), the cBioPortal for Cancer Genomics and online information associated with each dataset. We also downloaded copy number aberrations, recurrent ETS transcription factor gene fusions, mutational landscape, DNA methylation patterns and previously performed unsupervised clustering analysis when available  [12, 13, 17, 26, 53]. Somatic mutations are rare in prostate cancer patients.
Gene Expression Analysis of Localised Tumours and Functional Annotation of Differentially Expressed Genes Gene expression datasets were filtered to compare localised tumours with highest expression levels of ZBTB38 (4 th quartile) and tumours with lowest expression levels of ZBTB38 (1 st quartile). GEO2R was used to identify differentially expressed genes in the different cohorts, using p < 0. 001 as cut-off. Five studies report gene expression by array for >50 patients with localised tumours (see Figure  1a ). We excluded the Lapointe The web-based g-profiler portal (https://biit. cs. ut. ee/gprofiler/gost) was used to homogenise gene names and perform subsequent overlaps between the different lists of differentially expressed genes  [69]. The list of differentially expressed genes was further validated using the TCGA cohorts (i.
Cell Parameters Analysis by Fluorescent Activated Cell Sorting (FACS) Propidium iodide (P4170) and 2 ,7 -Dichlorofluorescin diacetate (D6883) were purchased from Sigma-Aldrich (Merck KGaA, Darmstadt, Germany). Propidium iodide (PI) is a membrane impermeant dye that is generally excluded from viable cells. 10 µL of PI staining solution (concentration: 10 µg/mL) was added to 1 × 10 6 harvested cells in 1 mL PBS just prior to analysis by FACS. 2 ,7 -Dichlorofluorescin diacetate (DCFDA) is a cell permeant fluorogenic dye that measures reactive oxygen species within the cell. DCFDA (20 µM) was added for 30 minutes at 37 • C before harvesting the siRNA transfected cells. Cell were then directly processed by FACS. FACS analysis was performed using a BD FACSCalibur TM flow cytometer (BD Biosciences, San Jose, CA 95131, USA) and the data were analysed using BD CellQuest Software.
Acknowledgments: The results shown in here are based upon data generated by the  TCGA research network  and other clinical centres. We thank these networks for making genomic and clinical information re-usable without restriction. We thank  Pierre-Antoine Defossez  (" Epigenetic and Cell Fate" laboratory ,  UMR7216 ,  Paris, French) , the members of the team "Epigenetics, DNA replication and Cancer" and colleagues at  Institut Cochin (INSERM U1016, Paris, French)  for suggestions and critical reading of the manuscript.
Taylor et al. 2010 (GSE21032) Kunderfranco et al. 2010 (GSE14206) Ross-Adams et al. 2015 (GSE70770) TCGA. 2015 (cBioPortal) ZBTB38 Expression (N) Chi2 p- Value ZBTB38 Expression (N) Chi2 p- Value ZBTB38 Expression (N) Chi2 p- Value ZBTB38 Expression (N) Cancers 2020, 12, 1106 Chi2 p-Value Low High Low High Low High Low High Age (year) at diagnostics <50 4 11 3 3 2 4 6 10 50-60 35 30 22 14 24 17 50 48 >60 25 24 3. 66 0. 160 2 9 6. 21 0. 044 30 33 1. 96 0. 373 62 60 1. 07 0. 584 Seminal Vesicle Invasion (SVI) Negative 56 59 - - - - - - Positive 7 6 0. 12 0. 725 - - - - - - - - - - - - Lymph Node Involvement (LNI) Normal 46 54 - - - - - - Abnormal 4 2 0. 97 0. 324 - - - - - - - - - - - - Surgical Margin Status (SMS) Negative 51 48 - - 35 51 70 87 Positive 13 17 0. 61 0. 432 - - - - 21 5 12. 8 0.
The dilated B6N hearts were hypofunctional, reflected in the reduced ejection fraction and fractional shortening (Fig  S3K  and L ). At 18 mo, there was far more intragroup variability (Table  S1C ), which may explain the slightly higher significance values at this age compared with 12 mo (Fig S1A  -M ). Dilation of the ventricles and thinning of the walls in the B6N may indicate a difference in the heart size, commonly measured by heart weight. Although all three groups exhibited a progressive increase in heart weight as they got older (Figs 1O, S1N, S2O, and S3O), there was no significant difference amongst groups at any time point. Body size, assessed by tibia length, was no different between B6N and B6J substrains, indicating no change in the heart weight:tibia length ratio in the B6Ns (data not shown).
This appears to be true with other mouse strains, as the authors found 58. 5% of all methods sections did not report the exact substrain with sufficient completeness. Aided by next-generation sequencing approaches, there are now sizeable databases documenting the many genetic differences between mouse substrains, including those involving the B6J and B6N  (23, 33, 60, 61, 62). These produce remarkably different phenotypes regarding weight, blood pressure, bone density, blood glucose, and cardiovascular traits  (3, 17, 23, 63, 64, 65, 66, 67, 68). In this regard, using the partly compromised B6N model, phenotypic effects may be more apparent and may help us unveil new important cardiac genes, and hence new therapies. However, caution must be advised, as researchers may want to avoid labelling effector genes as "causative" of CM or "essential" for cardiac function when made on the 6N background.
RNAseq variant calling We followed GATK pipeline for variant calling in RNAseq (https:// software. broadinstitute. org/gatk/documentation/article. php? id=3891). We used the STAR 2-pass method from STAR aligner  (76, 77)  to align the quality filtered reads to the reference genome downloaded from ftp://ftp-mouse. sanger. ac. uk/ref/GRCm38_68. fa. Then, we used Picard to add read groups, sort, and mark duplicates (https://broadinstitute. github. io/picard/). We used SplitNCigarReads from GATK  (78, 79, 80) , to split reads into exon segments and hard-clip any sequences overhanging into the intronic regions. We then applied indel realignment and base recalibration from GATK. Finally, we used HaplotypeCaller (81 Preprint) for variant calling. Variants were validated by visualising alignments in the Integrative Genomics Viewer browser  (82)  from the Broad Institute.
Western blotting Protein lysates were obtained by homogenising and lysing tissues in radio immunoprecipitation assay buffer for 2 h at 4°C. The lysates were sonicated at 20 kHz twice for 10 s, then centrifuged at 16,000g for 15 min, and the resultant supernatants were normalised for total protein concentration with a bicinchoninic acid assay. Protein lysates were added to an equal volume of Laemmli buffer. Lysates were heated at 95°C for 5 min and then loaded into 4-12% SDS gels. Immunoblots for NNT were performed with unheated samples. Proteins were then separated based on size using electrophoresis and transferred to a nitrocellulose membrane (Sigma-Aldrich) by semidry transfer blot (Bio-Rad) at 15 V for 1 h. Membranes were probed with a target antibody and GAPDH. Antibodies used are as follows: mouse anti-NNT (1:1,000, HPA004829; Sigma-Aldrich), mouse anti-TNNT2 (1:2,000, Cat.
H&E Freshly isolated hearts were immersed in 4% PFA on ice overnight. Tissues were then dehydrated and embedded in paraffin wax. We cut 7-μm sagittal sections through the tissues, making note of serial section number. Sections obtained at similar planes were then used for haematoxylin and eosin staining using a Leica Autostainer  (87). Briefly, tissue sections were washed in distilled water followed by staining with Gill's 3 Hematoxylin to stain nuclei and Eosin Y to counterstain cytoplasmic regions. We imaged stained sections using a Panoramic 250 (3D Histech) slide scanner with CaseViewer software.
Masson's Trichrome We stained paraffin-embedded heart sections as described in reference 88. Briefly, we fixed sections in Bouin's solution for 1 h followed by intense washing. We then stained fixed sections with Weigert's haematoxylin (nuclei), Biebrich scarlet-acid fuchsin solution (plasma), and Aniline Blue (collagen). We imaged stained sections using a Panoramic 250 (3D Histech) slide scanner with Panoramic Viewer software. We assessed fibrosis in these images in ImageJ using a colour threshold-detecting blue staining, determined by a prenominated window for colour hue, and passing a fixed intensity threshold.
Immunohistochemistry We used two detection methods for protein localisation, one using chromogenic diaminobenzidine oxidation assays and the other epifluorescence coupled with conjugate fluorescent dyes. Chromogenic diaminobenzidine staining of MYLK3 was performed by a Ventana automated staining station using the OmniMap Rabbit HRP (Roche). We imaged stained sections using a Panoramic 250 (3D Histech) slide scanner with CaseViewer software. Individual gene names with corresponding forward and reverse primer sequences for RT-qPCR. Sequences are all expressed 59 -> 39.
Specimens were then blocked in a BSA-serum mixture, followed by primary antibody incubation overnight. Samples were washed and incubated with secondary antibody, washed and finally mounted in an aqueous mountant. For immunofluorescent sections, tissues were counterstained with DAPI and wheat germ agglutinin Alexa Fluor 555 conjugate (Thermo Fisher Scientific) before background removal with TrueView Autofluorescence quenching kit (Vector Labs) followed by mounting in VectaShield mounting medium. Fluorescent slides were imaged on a Zeiss LSM 880 with Airyscan and quantified by MyofibrilJ package in ImageJ. DABstained slides were imaged using a Panoramic 250 (3D Histech) slide scanner with CaseViewer software. For sarcomeric morphometrics, longitudinal and transverse heart sections were used to measure the long axis (longitudinal sections) and CSA (transverse section) of individual cardiomyocytes delineated by WGA, alphaactinin (1:5,000, Cat.