dataesr/scientific-paragraphs-categorization huggingface dataset:
| Study design and setting Participating registries linked their live born cases to mortality records. Eleven registries linked their data to vital statistics databases, which contain data on birth and death registrations. Six registries linked their data only to mortality databases. For registries linking to vital statistics databases, it was possible to determine the proportion of successful linkages, as any live births not identified in the database were linkage failures. However, when only a mortality database was used, a case without a death certificate could have been alive or could have been a linkage failure. A detailed description and results of the linkage process have been reported elsewhere. 25 A total of 17 registries in 12 different European countries successfully linked their live births with CA to mortality records.
In only one registry (Malta), termination of pregnancy is illegal. All participating registries followed a common procedure of data collection, standardisation, quality control and statistical analyses, defined in the EUROlinkCAT protocol and reported in detail in a recent paper. 20 Data from each registry were locally analysed by the registry using common Stata syntax scripts, aggregate data and analytic results were then provided to a Central Results Repository based at Ulster University, UK. All live births with CA from 2005 to 2014 were included for all registries except for Emilia Romagna (Italy), Valencian Region (Spain), Thames Valley (UK), East Midlands and South Yorkshire (EMSY) (UK) and OMNI-Net (Ukraine), for which data were available for a shorter birth period (Table  1 ). All live births were linked to mortality records up to 2015, so that all live births had information on at least the first year's survival.
For the nine registries with data on live births during 1995-2004, Cox's proportional hazards models were fitted to compare survival of children born in 1995-2004 with those in 2005-2014. As different factors may influence infant and childhood mortality, survival from birth to 1 year was analysed separately from survival from 1 year up to 10 years. Therefore, two hazard ratios (HRs) for mortality of children with CAs born during 2005-2014 compared with those born during 1995-2004 at 1 year and 1-9 years of age were estimated for each registry. The HRs were combined across registries using a random-effects meta-analysis. Infant mortality (at <1 year of age) in children with CAs was calculated per 10,000 live births in the whole population births covered by each registry. Deaths occurring during the first 7 and 28 days of TA B L E 1 Study period, linkage data source, number of live birth cases, live birth prevalence per 10,000 births, proportion of termination of pregnancy for foetal anomaly and proportion of linked live births, by registry a For Netherlands: Northern, due to small number restrictions for all values the last digits are rounded to 0 or 5.
| Missing data Missing data in this study arose solely due to linkage not occurring. Eleven congenital anomaly registries linked to vital statistics databases and six of these had over 96% linkage success. For the remaining five registries all births in years in which the linkage success was lower than 85% were excluded. The registries who linked their data only to mortality databases were assumed to have linkage success above 85%. The Registry of Zagreb (Croatia) was unable to obtain identifiers for more than 20% of the children to link to the local death records and, therefore, was excluded from this study. A detailed description of the quality of linkage has published elsewhere. 25 Multiple imputation was not performed on any of the survival analysis as a failed linkage resulted in no covariates being available to use in the imputations.
| RE SULTS A total of 17 EUROCAT registries from 12 European countries were included in the study and provided survival data for a total of 115,219 children born with a major CA (Table  1 ). The live birth prevalence of 'All anomalies' per 10,000 births ranged from 146. 3 for the Thames Valley registry (UK) to 454. 7 for the Finnish registry.
| Strengths of the study The main strength of this study is that population-based data from CA registries were linked to local mortality data sources and national/vital statistics using a standardised method developed within EUROlinkCAT project. 20 This can be considered the most accurate approach for investigating survival of children born with CAs. Another strength is the inclusion of specialist high-quality CA data as the EUROCAT registries all follow standard procedures of coding and Data not available for Antwerp (Belgium). a In Malta termination of pregnancy is illegal. b For Netherlands: Northern, due to small number restrictions for all values the last digits are rounded to 0 or 5.
EUROCAT issues coding guidelines concerning classifying the CAs. However, the classification of children with CAs is likely to vary between registries, particularly for affiliate registries that only submit aggregate data to EUROCAT and whose individual case data cannot be examined to confirm consistency of coding. We observed high rates of survival for Finland (an affiliate registry), which cannot be due to linkage problems as the quality of the linkage with national vital statistics was 100%. In this case, the total live birth prevalence observed for the Finnish registry was much higher than for the other registries (Table  1 ), possibly due to the inclusion of more children with less severe CAs. Figure  2  indicates this may be the explanation as both the 5-year survival and the live birth prevalence in Finland were very high.
More precise survival estimates of individual CAs, even if rare, can be calculated pooling data from different registries using a metaanalytical approach as performed in studies of the EUROlinkCAT project. 33, 34 Therefore, the purpose of this study was to examine potential sources of bias in sufficiently large samples, to establish recommendations for future meta-analyses across registries. It is hoped that the assessment of survival of CAs across different geographic areas, after a careful evaluation of the impact of the methodological factors described above, may provide useful information for making inferences about the quality of care provided to children born with CAs. However, additional factors not measured in detail in this study, such as socio-economic inequalities in child mortality,  13, 35, 36  may also need to be considered.
9 99. 9 UK: Thames Valley 2005-2013 VS 3818 146. 3 27. 4 96. 5 UK: Wessex 2005-2014 VS 4015 147. 3 29. 9 92. 2 UK: East Midlands and 2005-2012 VS 9269 161. 9 21. 1 97. 4 South Yorkshire Ukraine: OMNI-Net 2006-2014 MR 5835 204. 7 13. 8 NA Total 115,219 231. 1 17. 6 LB, live birth; TOPFA, terminations of pregnancy for foetal anomaly following prenatal diagnosis; NA, Not available as linkage only to mortality database; MR, registry linked to mortality record database; VS, registry linked to national/vital statistics database.
5, 7, 8, 14 Data were obtained through medical record review for best-corrected visual acuity (VA), refractive error, pigmentation of eyes, skin, and hair, slit lamp examination, ophthalmoscopy, fundus photography, optical coherence tomography (OCT) scans, and multichannel Visual Evoked Potentials (VEPs) tests. We used a grading scheme for foveal hypoplasia previously described by Thomas et al. , with grade 0 indicating normal foveal structure, grades 1 and 2 not having incursion of the inner retinal layers, and grades 3 and 4 also affecting the photoreceptor differentiation (Supplementary Table  S1 ). 21 ultichannel VEPs were obtained with Espion E2 or E3 (Diagnosys LLC, Cambridge, UK), according to ISCEV standards. 22 A chiasm coefficient was calculated and the cutoff values were used from the study of Kruijt et al.
FHONDA Versus Albinism We compared the phenotypic spectrum of FHONDA to that of 133 patients with genetically confirmed albinism, 99 male patients and 34 female patients, aged 0 to 77 years (median age 10 years). These patients had either two mutations in TYR (49 patients) or OCA2 (41 patients), or a mutation in GPR143 (43 patients). Mutations in TYR and OCA2 cause oculocutaneous albinism (OCA) type 1 and 2, respectively, and those in GPR143 cause ocular albinism (OA1), the 3 most common types of albinism in the Netherlands. We used IBM SPSS Statistics software version 22 to perform statistical analysis. Data were not normally distributed, and therefore we used nonparametric tests.
Acknowledgments The authors thank  Herman Talsma  for his insightful help with the creation of the illustrations. The authors would also like to thank  Herman Talsma ,  Frans Riemslag , and  Frank Hoeben  for performing many of the visually evoked potentials recordings. Supported by the following foundations in the form of unrestricted funds: ODAS,  Vereniging Bartiméus Sonneheerdt  and  Landelijke Stichting Blinden en Slechtzienden  (via contributions through UitZicht). The funding organizations had no role in the design or conduct of this research. Disclosure:  C. C. Kruijt , None;  L. Gradstein , None;  A. A. Bergen , None;  R. J. Florijn , None;  B. Arveiler , None;  E. Lasseaux , None;  X. Zanlonghi , None;  L. Bagdonaite-Bejarano , None;  A. B. Fulton , None;  C. Yahalom , None;  A. Blumenfeld , None;  Y.
Finally, the cohort reported in this study included 66 patients (19 children, 47 adults). According to the French law on ethics, the patients were informed that their codified data was to be used for the study. According to the French ethical and regulatory law (public health code), retrospective studies based on the exploitation of routine care data do not have to be submitted at an ethics committee, but they must be declared or covered by the reference methodology of the French National Commission for Informatics and Liberties (CNIL). The personal and medical data were collected and computer-processed to analyse the results of the research. Toulouse University Hospital signed a commitment of compliance to the reference methodology MR-004 of the French National Commission for Informatics and Liberties (CNIL).
Personal history and clinical evaluation For each patient, the following data were collected by retrospective chart review: family history of fracture and osteoporosis, fracture history (age at first fracture, number and site), personal history, mineral homeostasis and bone marker levels before any treatment, bone parameters evaluated by DXA and genetic analysis. Vertebral fractures were defined as >20% vertebral height loss involving the anterior, posterior, and/or middle vertebral body. French reference data were used to convert height, weight and BMI measurements to age and gender-specific Z-scores.
Biochemical measurements Fasting blood samples were obtained as part of the patients' clinical follow-up. Total serum calcium, phosphate and alkaline phosphatase were measured using colorimetric methods. Serum concentrations of 25hydroxy vitamin D (25-OHD) and serum carboxy-terminal collagen crosslinks (CTX) were measured using automated chemiluminescence immunoassay systems (Cobas 8000 modular analyser series, Roche Diagnostics; iSYS, Immunodiagnostic Systems). The Quidel enzyme immunoassay (San Diego, CA, USA) was used to determine bone alkaline phosphatase (BAP) levels. BAP and CTX serum concentrations were converted to age-and gender-specific Z-scores based on published reference data  (Koay et al. , 2004). The following cut-off points were used for the serum 25-OHD levels: sufficiency above 75 nmol/L (>30 ng/mL), insufficiency between 50 and 75 nmol/L (20-30 ng/mL) and deficiency below 50 nmol/L (<20 ng/mL).
Dual-energy X-ray absorptiometry Bone mineral density (BMD) of the lumbar spine (LS-BMD), the total body less head (TB-BMD), and total hip levels (TH-BMD) were measured via DXA using a Lunar Prodigy device (GE Healthcare). The BMD results were converted to age-specific Z-scores using data provided by the densitometer manufacturer and published reference data  (Fan et al. , 2014).
Fastq files were generated by using Miseqreporter (Illumina) and then aligned with SeqNext (JSI Medical Systems, Ettenheim, Germany) based on BWA aligner and GATK Hap-lotypeCaller (Broad Institute (GATK 3. 8. 1)). The Copy Number Variations (CNV) were also determined using this software and a multiplex ligation-dependent probe amplification (MLPA) reagent for LRP5, COL1A1 and COL1A2 on the ABI3130 sequencer with Coffalyser software (MRC, Amsterdam, Netherlands). Variant pathogenicity was evaluated using the prediction software Polyphen (http://genetics. bwh. harvard. edu/pph2), CADD (https://cadd. gs. washington. edu) Mutation taster, and SIFT (http://sift. bii. a-star. edu. sg). The known pathogenic mutations were searched for in the professional Human Gene Mutation database (HGMD-pro) or Leiden Open Variation Database (LOVD).
All novel variants will be reported in the ClinVar database. Identified variants were classified according to the American College of Medical Genetics (ACMG) classification: classes 1 and 2 of the ACMG were considered as non-pathogenics, class 3 as a variant of unknown significance (VUS) and classes 4 and 5 as pathogenics. If a patient had two variants, the most pathogenic was taken into account when classifying the mutations.
Statistical Analysis Five variables were selected to determine the feasibility of this research program: acceptability, adoption, adequacy, fidelity, cost and impact. Analyses were performed on SPSS version 25 (IBM SPSS Statistics for Windows). The Student's t-test was used to compare normally distributed continuous variables between two groups, the ANOVA to compare three groups or more, and the Chi-square for binary and/or categorical variables. Data were analyzed according to gender, age, stage of the disease, presence of a caregiver, duration of illness and medical coverage. P value less than 0. 05 (≤ 0. 05) is considered statistically significant.
| Search The following databases were searched: PubMed/MEDLINE, EMBASE, CINAHL, PsycINFO, and Scopus. Additionally, reference lists of included articles and relevant systematic reviews  43, [47] [48] [49] [50] [51] [52]  were crosschecked, with any potentially eligible papers screened using standard methodology. Finally, experts in the field including the current authors (e. g. KDH & RL have authored previous systematic reviews on similar topics) and members of the LifeCycle Project-EU Child Cohort Network within which this work was nested were consulted to identify any other papers that should be included in the screening. The search was performed 7th January 2022 and included articles from peer-reviewed English language journals published since 1990 (inclusive). The search strategy is detailed in Supplementary document S2.
| Study selection The references retrieved from the database searches were transferred to Covidence (https://www. covidence. org) for eliminating duplicates and screening. Two authors (FH and SL) independently screened the titles and abstracts, then read full-text articles of the remaining references to confirm their eligibility. During the whole process, summarized in a PRISMA chart  44, 45  (Figure  1 ), any disagreement between FH and SL was flagged in Covidence, and solved through specific discussions, without needing a third reviewer.
| Data extraction An Excel template was used to extract data, which included the following fields: country, study design and methodology, enrolment and recruitment details, population and participant demographics, baseline characteristics, intervention details according to TIDieR guidelines,  53  control conditions (if any), outcomes (measures and times of measurement) and measures of engagement, adherence and acceptability to users, retention in the study, results, and conclusions. All published articles and supplementary data related to the selected study, i. e. protocol paper; study registration website; pilot, qualitative, implementation and long-term follow-up studies; were considered for data extraction. SL cross-checked the data extracted by FH, after reading all articles and supplementary material.
| Identification of studies The database searches yielded 8,517 records, of which 1,270 duplicates were removed. An additional 7,060 records were excluded after titles and abstracts screening, resulting in 190 full-text articles to be read in full. A further 157 articles were excluded for various reasons detailed in the PRISMA flow chart (Figure  1 ). Overall, 33 studies (35 including two erratum articles) met the eligibility criteria, including 3 identified through reference lists. We extracted data from an additional 55 supplementary materials (other articles related to the intervention and protocol registration websites).
ACKNOWLEDGMENT This work was carried out within the  LifeCycle  European project that was funded through both the  European Union 's  Horizon 2020 Research and Innovation Programme  (grant agreement no. 733206 ) and the  French National Research Agency  ( ANR-19-CE36-0006 ). Kylie Hesketh  is supported by a  Future Leader Fellowship  from the  National Heart Foundation of Australia  ( 105929 ). We thank  Catherine Weill  for her valuable support in the search of references through the various databases.
tive synthesis of findings. Still, the search from five different databases over the last 30 years, the thorough data extraction, the comprehensive internal and external validity assessment of the individual studies included, and their narrative synthesis, provide important insights into ingredients and processes that seem valuable to consider in future interventions aimed at tackling social inequalities in perinatal health. The registration into PROSPERO prior to the screening and adherence to PRISMA and AMSTAR-2 guidelines reinforced the rigorousness and quality of the analysis undertaken.
Among carbohydrate active enzymes, glycoside phosphorylases (GPs) are valuable catalysts for white biotechnologies, due to their exquisite capacity to efficiently re-modulate oligo-and polysaccharides, without the need for costly activated sugars as substrates. The reversibility of the phosphorolysis reaction, indeed, makes them attractive tools for glycodiversification. However, discovery of new GP functions is hindered by the difficulty in identifying them in sequence databases, and, rather, relies on extensive and tedious biochemical characterization studies. Nevertheless, recent advances in automated tools have led to major improvements in GP mining, activity predictions, and functional screening. Implementation of GPs into innovative in vitro and in cellulo bioproduction strategies has also made substantial advances.
Classification and Substrate Specificity In the Carbohydrate-Active Enzymes (CAZy) Database, GPs are classified into a total of 11 CAZymes families (Table  1 ). It is worth noting that a N-acetylglucosaminidase from the GH84 family has recently been converted into an efficient GP by a single point mutation  [176]. However, as GH84 enzymes do not include any native GP, this family will not be further mentioned.
These Leishmania enzymes bear the same fold and adopt a similar reaction mechanism as bacterial GH130 mannan phosphorylases or hydrolases. However, their significant difference at the sequence level justified classifying them in another family  [174]. Taken together, these studies show that GPs can, thus, degrade and synthesize a large array of glycosidic linkages, with the notable exceptions of α-/β-1,6 and β-1,1 linkages. As of November 2021, only 1893 phosphorylases had been characterized (Table  1 ), which represents about 1% of all the characterized CAZymes  [192, 193]. Taking into consideration the huge number of GTs and GHs that are listed in the CAZy database, many GPs with novel specificities might remain to be discovered.
Tertiary and Quaternary Structures With the exception of GT4 retaining trehalose phosphorylases and GH161 inverting β-1,3 glucan phosphorylases, for which no structure has been elucidated yet, at least one GP crystallographic structure is available for each family in the protein data bank (PDB) (Table  2 , Figure  3 ). Thanks to these structures, in particular the ones in complex with substrates and products, the catalytic residues have been identified, such as those involved in phosphate binding. These structures complement the site-directed mutagenesis studies that have been performed to identify the critical residues for GP activity (e. g. ,  [109]  for the GH130 family). Additionally, when several GP members from the same family have been both functionally and structurally characterized, the structural comparison not only allows identifying the molecular determinants of GP activity but also those establishing donor and acceptor specificities (  [189, 194]  for the GH130 family, for example), or even allows prediction of the phosphorolytic or hydrolytic nature of sequence clusters, together with the linkage specificity of the reactions  [112].
To date, only three activity-based functional metagenomic studies have been performed to discover GPs. In the first one, a new sucrose-phosphorylase (Genbank accession FJ472846, not listed in the CAZy database, but likely a GH13_18 member) was isolated from a 5000-clone metagenomic library constructed from a sucrose refinery sample. In this case the screen consisted in a positive selection assay on a solid mineral medium containing sucrose as sole-carbon source  [49]. More recently, the S. Withers group has started to use metagenomics to mine various ecosystems for GPs. Their first study was based on the screening of 17,168 clones library obtained from a passive mine tailings biochemical reactor system, on the activated substrate 2,4-dinitrophenyl β-D-glucoside (DNPGlc) and inorganic phosphate, leading to the discovery of the retaining β-glucoside-phosphorylase BglP, a rare GP from the GH3 family  [30].
Several databases, including COGs, Pfam, and KEGG, allow for automated functional annotation of metagenomic sequences. COGs identifies orthologous genes that typically share the same general function, such as carbohydrate transport and metabolism for the G cluster, in which CAZymes are found  [296]. Pfam contains nearly 18,000 protein families (Pfam 32. 0)  [297]. Each family is created based on multiple sequence alignments and hidden Markov models (HMMs)  [298]. Since Pfam families (like CAZy families) contain members with several activities, the activity of an enzyme cannot be deduced from the family it belongs to. Finally, KEGG can provide information on the involvement of a protein in the metabolism of an organism or an ecosystem  [298]. Nevertheless, sequence similarity-based methods leave orphan genes (genes which do not share significant sequence similarity with any known sequence) without annotation.
Furthermore, due (and participating in) to the amplification of incorrect functional annotations in databases, these tools can generate annotation mistakes in the preliminary functional annotation of sequences. For instance, when searching for the GH130 β-1,4-mannoside-phosphorylase Uhgb_MP (Genbank accession number ADD61463. 1) in these databases, the results are the following: • COG: the protein belongs to COG2152: Predicted glycosyl hydrolase, GH43/DUF377 family (Carbohydrate transport and metabolism). The biochemical characterization of this enzyme  [109] , indicated that these results are false, this enzyme being a mannosidephosphorylase of the GH130 family, which does not contain a GH43 module.