dataesr/scientific-paragraphs-categorization huggingface dataset:
Processing at the 5 end of genes takes place only through tRNA punctuation, thus the 5 UTR of rnl and cox3 are not processed further and the small amount of cox1-cox3 bi-cistronic transcript produced from the major promoter remains stable. For more details see  (22 and references therein). LSU: large ribosomal subunit. units to their assembly into the corresponding OXPHOS complex or into the mitoribosome  (16, 13, (17) (18) (19) ; and references therein). Unlike the OXPHOS assembly factors that are generally highly conserved from yeast to human, the translational activators from S. cerevisiae appear to rapidly diverge in evolution, as shown by sequence homology searches in humans, or the fission yeast Schizosaccharomyces pombe databases  (20). This could be due to co-evolution with their RNA target or to the replacement by other factors recruited to regulate mitochondrial translation.
6 to 1. 4 V s/cm 2. MS/MS spectra were acquired with the PASEF (Parallel Accumulation Serial Fragmentation) ion mobility-based acquisition mode using a number of PASEF MS/MS scans set as 10. MS and MSMS raw data were processed and converted into mgf files with DataAnalysis software (Bruker). Protein identifications were performed using the MAS-COT search engine (Matrix Science, London, UK) against Swissprot database and S. pombe taxonomy. Database searches were performed using trypsin cleavage specificity with two possible missed cleavages. Carbamidomethylation of cysteines was set as fixed modification and oxidation of methionines as variable modification. Peptide and fragment tolerances were set at 10 ppm and 0. 05 Da, respectively. Proteins were validated when identified with at least two unique peptides.
Only ions with a score higher than the identity threshold and a false-positive discovery rate of less than 1% (Mascot decoy option) were considered. Both mascot error tolerant and semi-specific cleavages searches were performed to characterize the N-terminal of Mrp51. Mass spectrometry based-quantification was performed by label-free quantification using spectral count method. Total MS/MS spectral count values were extracted from Scaffold software (version Scaffold 4. 11. 1, Proteome software Inc, Portland, OR) filtered with 95% probability and 0. 1% FDR for protein and peptide thresholds, respectively. For statistical analysis, missing values occurring in spectral count datasets at protein-level were imputed by a constant value fixed at 0. 1. In order to take into account withinsample variation in spectral count datasets, a beta-binomial test was performed based on triplicates MS/MS analyses with P-values calculated using R package 'ibb' (version 13.
Immunoprecipitation of Cbp7 identifies Cbp8, a new factor essential for Cytb accumulation To find physical partners of Cbp7 in S. pombe, we performed anti-c-Myc immunoprecipitation (IP) followed by mass spectrometry LC-MS/MS analysis on tagged S. pombe Cbp7-cMyc mitochondria. Mitochondria from the untagged wt served as control. Whereas Cytb itself was never enriched in IPs of Cbp7-cMyc compared to wt, a protein of unknown function, Spac22h10. 09, was strongly and significantly enriched in all experiments (Figure  3A ). In our mass spectrometry analyses, the absolute spectral counts for Spac22h10. 09 remained low (Supplementary Table  S2 ), which correlates with the fact that in PomBase it is reported to be of very low abundance, like Cbp7. Thus, we tentatively called this factor Cbp8, since our data suggest that it could form a complex with Cbp7.
Together, these data show that Mrh5 is required for Cox1 synthesis, like Ppr4 and Mtf2. Strikingly, in presence of the suppressor mutation mrh5-G230E, Cytb synthesis was dramatically increased, and this effect was still visible in presence of the Δcbp7 allele, suggesting that this might be part of the mechanism of suppression. Finally, cMyc-tagged Mrh5 was subjected to IP in presence of EDTA, in strains also HA-tagged for Mrp51 or Mug178. The results of the cMyc-and HA-IPs showed that Mrh5 clearly co-precipitates with proteins of the small ribosomal subunit, including mS45, Mug178 and Mrp51, but no co-IP signal was observed with Cox1. Thus, Mrh5 interacts with the mitoribosomal SSU and is required primarily for cox1 translation.
In S. cerevisiae, no isoforms of mitoribosomal proteins have been described and in plants, eight genes coding organellar uL18 are found, however only uL18m and uL18c have so far been confirmed to be mitochondrial and chloroplastic ribosomal proteins respectively  (90). In humans, there are three mitoribosomal proteins related to bS18, however these are not mutually exclusive isoforms like Mrp51 and Mug178. Instead, all three proteins are associated at the same time with the ribosome but at different locations, and correspond to the canonical bS18c and two proteins specific to humans, mS40 and mL66  (91). Interestingly, for the human bS1m, seven smaller computationally mapped isoforms of various sizes (83 to 162 residues) are currently reported in the UniProt database, in addition to the representative 187 aa sequence and their possible roles, if any, is unknown.
ACKNOWLEDGEMENTS We are grateful to  Thomas D. Fox ,  Rudolf Schweyen ,  Inge Kühl  and  Jean Velours  for the generous gift of antibodies, to  Bénédicte Barrault  for providing some of the plasmids used for gene tagging, to  Brigitte Meunier  for all the supplies to measure respiratory complex activities and to  Isabelle Hatin  for help with accessing a Typhoon Phosphorimager. The  National BioResource  Project (Japan) dispatched the pAL-KS plasmid and pTN-L1 library. This work has benefited from the facilities and expertise of the I2BC High-throughput  Sequencing Platform (Next Generation Sequencing Core  facility), as well as from the facilities and expertise of the I2BC proteomic platform ( Proteomic-Gif , SICaPS) supported by  IBiSA ,  Ile de France Region ,  Plan Cancer ,  CNRS  and  Paris-Sud University.
DATA AVAILABILITY The Mass Spectrometry data are available at the database Pride of ProteomeXchange under the accession number PXD025400. Supplementary Tables S2, S4 and S5 provide the statistical analysis for the IPs of Cbp7-cMyc versus wt, Mrh5-cMyc versus wt and Ppr4-cMyc versus wt respectively. Raw data for LC-MS/MS analyses of IPs from Mrh5-cMyc, Ppr4-cMyc and wt are provided in Supplementary Table  S3.
RNA-Seq and bioinformatics analysis Complementary DNA (cDNA) libraries were prepared from RNA isolated from mice tissues using the Illumina TruSeq protocol. RNA-Seq was performed on the Illumina HiSeq platform to generate w40Mio 125 nt single-end reads per sample. Reads were mapped and quantified with STAR-2. 5. 3a software  [8]  using M. musculus-mm10 as reference genome and GRCm38. 83 from ENSEMBL as the reference annotation index. For each sample, quality control included verification of the total number of reads, percent of uniquely mapped reads, number of detected expressed genes, gene body coverage, and cumulative gene diversity. The resulting counts per gene from different samples were integrated to construct a single count matrix for each tissue that was filtered, excluding those genes with <1 count per million with 'edgeR'  [9].
We excluded three clear outliers identified by PCA and hierarchical clustering in the islets data set. The count matrix was normalized using the trimmed mean (TMM) normalization method. Differentially expressed genes (DEGs) comparing HF and RC, and the different strains were detected using the Limma package in R  [10]. P-values were adjusted for multiple comparisons with the Benjamini-Hochberg procedure, and those genes with adjusted p-value of 0. 05 were considered as differentially expressed. Weighted gene correlation network analysis (WGCNA) was performed on the RNA-Seq dataset from all time points, mouse strains, and diets to generate modules of co-expressed genes. Co-expression networks for each tissue were constructed by calculating signed adjacency matrices using a soft-thresholding power of six and a pair-wise Pearson correlation among all genes.
A signed topological overlap matrix (TOM) was then calculated from each adjacency matrix, converted to distances, and clustered by hierarchical clustering using average linkage clustering. Modules were identified in the resulting dendrogram by the Dynamic Hybrid tree cut with a cut height of 0. 995 and a minimum module size of 20 genes. The correlation between the resulting modules and plasma lipids was calculated in two steps for the liver data set, and the three steps for the islets data set are as follows: first, a PCA was calculated for each module in each data set using only module constituent genes. Second, the Spearman correlation coefficient was calculated between the summarized values of expression of each module (the first principal component or eigenvalue) and plasma lipids. In the islets data set, an intermediate step was added because plasma lipidomics and islet transcriptomics data were derived from different mouse individuals and direct correlation was not possible.
Thus, 18 mouse groups were defined by the three strains, two diets, and three-time points of harvesting. Module eigenvalues and plasma lipid concentrations were summarized per mouse group using the mean, which yielded 18 pairs of values to be considered per lipid and module. Student asymptotic p-values were calculated for the given correlations and were adjusted for multiple comparisons using the Benjamini-Hochberg procedure  [11]. The functional enrichment analysis was performed using the R library "clusterProfiler"  [12]. Pathways from KEGG and GO databases were searched using a hypergeometric test to examine the overrepresentation of the terms within the functional annotation and to determine the p-values using the hypergeometric distribution. P-values were adjusted for multiple comparisons by the Benjamini-Hochberg procedure.
Insulin secretion and cellular insulin content were measured by ELISA according to the manufacturer's protocols using the Human Insulin kit (Mercodia). 2. 9. Glucose-stimulated insulin secretion statistics Data were analyzed using R software (v. 3. 6. 1) and are presented as the means AE S. E. M. from three independent experiments. Comparisons were performed using two-sample unpaired t-tests, and the pvalues adjusted for multiple comparisons. Statistically significant differences are indicated with asterisks (*p < 0. 05; **p < 0. 01; ***p < 0. 001; ****p < 0. 0001).
Islet transcriptomic analysis Islet transcriptomic data were obtained from islets isolated from 3 to 6 randomly fed mice for each of the 18 experimental groups. A total of 69 islet transcriptomic data sets were used for the subsequent analysis as three samples were rejected after quality control. PCA showed that the islets transcriptomic was influenced mostly by the mouse genetic backgrounds and to a lower extent by the feeding conditions (Figure  1E ). The Venn diagrams of Figure  S3A  show that differential gene expression between islets from RC-and HFD-fed mice was dependent on strains and period of HFD feeding (Suppl. Table  3 ). The highest number of differentially regulated genes was found at day 5 of HFD feeding. Islets from C57Bl/6J mice displayed the highest number of differentially expressed genes (354 vs.
Correlation between plasma TAGs and islet transcripts in humans We next assessed whether similar correlations between plasma TAGs and key functional b-cell genes could be observed in humans. To this end, we analyzed RNA-Seq data generated from laser capture microdissected islets and quantitative plasma lipidomic data obtained from a cohort of 60 partially pancreatectomized patients  [31]. For correlation analysis, we selected the aforementioned human orthologues of the mouse islet mRNAs that encode components of the GSIS pathway, lipid metabolic enzymes, and proteins of the insulin signaling pathway. Out of the 86 considered mouse genes, 85 had human orthologs that were expressed in the human islets data set. Figure  6  shows the heatmap of the correlation between plasma TAGs and 44 of the most highly correlated human islet mRNAs.
FUNDING This project has received funding from the  Innovative Medicines Initiative 2 Joint Undertaking  under grant agreement No  115881  (RHAPSODY). This Joint Undertaking receives support from the  European Union 's  Horizon 2020 Research and Innovation Program  and  EFPIA. This work is also supported by the  Swiss State Secretariat for Education, Research and Innovation (SERI)  under contract number  16. 0097. The opinions expressed and arguments employed herein do not necessarily reflect the official views of these funding bodies. B. T. also received support from a  Swiss National Science Foundation  Grant ( 310030_1824969 ).
DATA AVAILABILITY The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus  (59)  and are accessible through GEO Series accession number GSE164673 (https://www. ncbi. nlm. nih. gov/geo/ query/acc. cgi?acc¼GSE164673). Pancreatic islets expression data SubSeries are available with the accession number GSE140369 (https://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc¼GSE140369) and liver expression with accession number GSE164672 (https://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc¼GSE164672).
Introduction There have been public health concerns about a potential association between human papillomavirus (HPV) vaccines and premature ovarian failure (POF) in young women. Objective To identify a potential safety signal of POF after HPV vaccination using the United States (US) Vaccine Adverse Event Reporting System (VAERS) database. Methods We manually selected relevant MedDRA preferred terms related to POF and identified in VAERS all POF reports in women less than 40 years of age between 2 July 1990 and 14 May 2018, followed by a review of narratives to confirm the cases. We conducted descriptive analyses on age, POF type, HPV vaccine type (HPV2, HPV4, HPV9), time to onset of POF, and dose rank. We described trends in reporting over time and assessed a potential safety signal using the proportional reporting ratio (PRR).
Concerns raised by the observations of cases of female infertility after human papillomavirus (HPV) vaccination emerged following the publication of two case series, respectively in 2013 and 2014, involving POF in 14-to 21-yearolds  [1, 5]. Subsequently, safety statements on the absence of risk of infertility after HPV vaccination were made by the World Health Organization (WHO) Global Advisory Committee on Vaccine Safety (GACVS) as well as by the Centers for Disease Control and Prevention (CDC) and the US Food and Drug Administration (FDA)  [6, 7]. In addition, a review of the POF cases reported to the United States (US) Vaccine Adverse Event Reporting System (VAERS) database was conducted. In this study there were 17 cases of POF identified, of which 15 were excluded because of insufficient information to confirm the diagnosis  [8].
Data Source We used the VAERS, created in 1990 in the US to fulfil a requirement of the National Childhood Vaccine Injury Act of 1986, which consists of a spontaneous and voluntary reporting system for any suspected adverse drug reaction (ADR) associated with vaccine use  [10]. The system can receive reports of suspected ADRs from healthcare professionals, manufacturers, patients, parents, and caregivers  [11]. The reporting form includes fields that capture information on the person who experienced the suspected ADR, the reporter, the suspected ADR, and the vaccine. Reports are coded using the Preferred Terms (PTs) of the Medical Dictionary for Regulatory Activities (MedDRA)  [12]. Data from primary reports, after the removal of patient sensitive information, are publicly available on the VAERS website and through the CDC Wide Online Data for Epidemiologic Research (WONDER) tool.
Eligibility Criteria Relevant PTs for POF events were manually identified a priori by two medical doctors with respective expertise in vaccinology (CT) and pharmacovigilance (GC) using Standardized MedDRA Queries (SMQs) and examination of all PTs for either a symptom or a sign of POF. Events were divided into four categories: proportion of POF reports among HPV vaccine-associated reports, proportion of non-POF events in HPV vaccines, proportion of POF in other vaccines, and proportion of non-POF events in other vaccines. The denominator for proportions was restricted to women below 40 years of age or of unknown age between 2 July 1990 (i. e. , the date an adverse event was first reported in VAERS) and 14 May 2018 (i. e. , the date of data extraction). We defined exposure to HPV vaccination by the mention, in a case report, of an exposure of at least one dose of any HPV vaccine type (bivalent, quadrivalent, or nonavalent) for which the ADR was suspected to have occurred.
Data Analysis We used frequencies and percentages to describe reports of POF associated with HPV vaccination, according to patient age, time between vaccination and onset of POF event, POF event type, HPV vaccine type (HPV2, HPV4, HPV9), dose rank, time period, and region (whether US or non-US). An analysis of all POF events (regardless of the suspected vaccine) was also undertaken in order to compare the annual number of POF case reports in the period before the launch of the first HPV vaccine  (1990) (1991) (1992) (1993) (1994) (1995) (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004) (2005) (2006)  to the annual number post-launch (2006-2018) and used Fisher's exact test to assess the statistical significance of the differences. Disproportionality was evaluated using the proportional reporting ratio (PRR), which is the ratio of the proportion of reports of POF events suspected to be associated with HPV vaccination to the proportion of reports of POF events suspected to be associated with all other vaccination in women age < 40 years or unknown age only  [13].
0% of cases for blood follicle-stimulating hormone increased, 1. 4% cases for estradiol decreased, and, 0. 4% cases each for blood follicle-stimulating hormone abnormal and estradiol abnormal. In relation to POF reports suspected to be associated with other vaccines between 1990 and 2018, there were 30 reports, out of which 23 (76. 7%) had data for age with a median of 25 years (range: 12-38 years). There were 21 (70. 0%) reports with data on duration from exposure to other vaccines to POF onset with a median of 11 days (range: 0-1951 days). Only four POF event types were recorded, with the majority being amenorrhea in about 83. 3% (25/30) of cases, while the rest were premature menopause (3. 3%, one report), oligomenorrhoea (10. 0%, three reports), and decreased estradiol level (3. 3%, one report).
Discussion Using the US VAERS data, a high disproportionality in the reports was found, which suggests the presence of a potential signal of an association between HPV vaccine and POF events. To address some of the limitations of spontaneous data, such as missing data in the reports, namely unknown sex or age, sensitivity analyses were conducted, which yielded similar results of disproportionality. Applying a stricter definition of POF (amenorrhea, premature menopause, ovarian failure) or restricting the time period postlaunch of HPV vaccines, the PRRs increased, but as shown by very broad 95% CIs, the estimates were very imprecise. In relation to sensitivity analysis involving unknown sex, even if the 14 POF events were assigned to females and the 80,119 other events to males, the signal was still present.
While published case series described cases that received HPV4 vaccines only, the current study identified reports of POF events not only for HPV4 vaccine but also for HPV2 and HPV9 vaccines, even if substantially less. It is important to note that the case series referred to were published in 2013 and 2014, respectively, at the time when both HPV2 and HPV4 were already on the market  [1, 5]. Also, the study showed that among the 281 reports, POF events were suspected of HPV vaccine irrespective of dose rank. Cases where POF occurred following the first, second, or third dose could not be reliably derived from VAERS. The use of amenorrhea as a proxy for POF identification is supported by the fact that it is the main initial symptom in women with POF  [2] , which was also the main observed POF in our data (i.
Thus, pharmacoepidemiological studies based on data sources including information about vaccination, events, and potential confounders at patient level are required by using large cohorts and a long duration of follow-up. Following the published case series, the CDC and FDA addressed public concerns on POF after HPV vaccination through a VAERS review and a Vaccine Safety Datalink study. According to the VAERS review, there were three reports among 29 million doses of HPV9 vaccine administered in the population (1 December 2014-31 December 2017)  [7]. All three were determined as unconfirmed (lacking sufficient information to confirm a diagnosis of POI). Among 17 reports following 60 million HPV4 vaccine doses (January 2006-2015), two had a physician diagnosis of POF, whereas the remaining 15 did not have enough information to confirm the diagnosis.
This study appears to be the first to quantitatively identify a potential safety signal of disproportionate reporting of POF events following HPV vaccination using a spontaneous reporting database (VAERS). VAERS is a national database that covers over 300 million inhabitants, supplemented by non-US cases that may also be reported. Such a large coverage also enables the detection of rare adverse events, including POF events. More specific to VAERS is the length of coverage, as data are available since its inception in 1990, which allows the investigation of safety reports of HPV vaccines from the time they were launched on the market.
There was a variability in the quality and completeness of POF case reports, such as absence of information on folliclestimulating hormone and estrogen hormone levels in the majority of the reports. Incomplete data call into question whether or not the identified reports for HPV vaccine and POF events are actually valid cases, with POF as the true diagnosis. Finally, VAERS cannot be used to determine whether a vaccine caused an AE as it could be due to chance, confounders, or bias. Therefore, this study only generated the hypothesis that there may be a signal of disproportionate reporting for POF events and HPV vaccine that warrants further investigation.
Conclusion This study has detected a strong disproportionality in the reporting of POF events after HPV vaccine in VAERS. Besides amenorrhea, which is the most frequently mentioned POF event, other events such as ovarian failure, premature menopause, oligomenorrhea, and blood follicle hormone and estrogen hormone levels were also reported. These findings along with other sources of evidence such as the published case series and the biological plausibility lend support to the presence of a safety signal. The public has been reassured by health authorities of the absence of a causal relationship between HPV vaccine and POF not only based on safety studies that lacked data on ovarian dysfunction but also on those studies with sources of data that were insufficiently powered to detect events of declining ovarian function.
Acknowledgements No funding was received for the conduct of this study. Collins Tatang  (CT) was on a Master Scholarship program in Vaccinology and Pharmaceutical Clinical Development at the  University of Siena, Italy  funded by  Fondazione Sclavo. We thank  Dr. Genaro Castillon  (GC) from  YOLARX Consultants  for his valuable advice and contribution to the analysis of VAERS data.
The median age of patients was 15 years at the time of reporting (range: 11-39 years). Over half of the cases (58. 0%) were in the younger age group (< 20 years) and age was unknown for a large portion (27. 0%). There were 228,341 AE reports for females less than 40 years of age or of unknown age recorded in the VAERS database between 2 July 1990 and 14 May 2018. Of those, 311 (0. 14%) were POF events.