dataesr/scientific-paragraphs-categorization huggingface dataset:
Genomic data and Genome-Wide Association (GWA) analysis The 404 K core SNPs dataset was downloaded from the IRRI SNP-Seek website (https:// snp-seek. irri. org/_ downl y ijk = + g i + s ij + j + jk + e ijk H 2 = 2 g 2 g + 2 s n site + 2 e n block ×n site oad. zul). SNP having more than 5% missing data or a minor allele frequency below 2. 5% were removed, retaining 186,229 SNPs for 3,024 accessions. Remaining missing states were imputed using Beagle v. 4. 1 (21Jan17. 6 cc;  Browning and Browning 2016). Without further filtering, GWA analysis was performed on the 253 accessions with the BLUE values for grain Zn concentrations and the 186 k genotype matrix using the multi-locus random-SNP-effect mixed linear model (mrMLM) software package, which includes the mrMLM, FASTmrMLM, FASTmrEMMA, pkWmEB, pLARmEB, ISIS EM-BLASSO methods (https:// cran.
The allele effect at each locus was determined by calculating the average phenotypic values of all accessions carrying either allele and a box-plot graph was generated using an in-house R script. A graphical representation of subset of SNPs surrounding the significant QTNs was generated by the Haploview 4. 2 software  (Barret et al. 2005). Linkage disequilibrium (LD) blocks were then identified and manually delignated based on the recombination rate, which is displayed using the standard color scheme: D'/LOD (wherein red color reveals linkage disequilibrium between two genetic markers, D' = 1 and LOD > 2).
Genomic prediction Genomic prediction was performed with the GBLUP model  (Bernardo 1994 ) using the rrBLUP package  (Endelman 2011 ): where is the Zn BLUE values, 1 is a vector of ones, μ is the grand mean, is the design matrix, is the vector of genotypic values, is the vector of residuals, 0 is a vector of zeros, is a genomic relationship matrix, σ 2 u is genetic variance, is an identify matrix, and 2 e is the residual variance. The genotypic values and residuals are assumed to follow a = 1μ + + , ∼ MVN 0, σ 2 u , ∼ MVN 0, σ 2 e 1 3 multivariate normal distribution (MVN). The genomic relationship matrix was calculated by using the A. mat function in rrBLUP package, as described in  Tanaka et al. (2021). By using the above GBLUP model, Zn concentrations of the all 3 K accessions were predicted with three slightly different training sets: (1) all phenotyped accessions (n = 253), (2) all phenotyped accessions excluding IRIS_313_9368, which had extremely high Zn concentrations and may therefore be highly influential (n = 252) and (3) excluding the six members of the aus subspecies (n = 247).
Genomic prediction for grain Zn concentrations Utilizing the same GWAS dataset as a training set, a GP model was developed to predict grain Zn concentrations of the entire set of 3 K accessions. The full model including all 253 training accessions predicted grain Zn concentrations to range from 17. 1 µg Zn g -1 to as high as 40. 2 µg Zn g -1 (Fig. 2b ). Differences between subpopulations were pronounced, with the aus group having highest predicted values and an average of 30. 3 µg Zn g -1. The second highest average was predicted for the japonica group (26. 7 µg Zn g -1 ) and the lowest for the indica group (23. 2 µg Zn g -1 ). In fact, only members of the aus sub-species were found among the top 20 predicted accessions (Table  S3 ) and IRIS_313_9368, which had the highest grain Zn concentrations in the training set (42.
These belonged to the aus (n = 30), indica (n = 24) and japonica (n = 7) subpopulations (Table  S4 ). Seeds analyzed had been imported directly from the IRRI genebank and were thus not grown in Madagascar (though there was a small overlap with accessions in the field in Madagascar, n = 11). The correlation between measured and predicted values was r = 0. 74 (Fig. 5 ) and correlations with the 2nd model (r = 0. 66) or 3rd model (r = 0. 35) were lower (data not shown). Predicted mean values separated the aus group (average 31. 3 µg Zn g -1 ) from the indica (23. 6 µg g -1 ) and japonica (25. 1 µg g -1 ) groups and measured means were within 1. 0 µg Zn g -1 of predicted group means (31. 7, 23. 4 and 24. 2 µg Zn g -1 , respectively). For the main locus identified on chromosome 11 in GWAS (QTN_11.
3), the positive minor allele was present in 12 of the 61 accessions. The allelic effect appeared to be significant with an average Zn concentration of 32. 4 µg Zn g -1 for the minor compared to 26. 3 µg Zn g -1 for the major allele (Table  S5 ); however, all accessions with the minor allele belonged to the aus group and within that sub-species, allelic groups did not differ (32. 4 vs. 31. 1 µg Zn g -1 ). The second confirmatory experiment was conducted with potential high-Zn donors at five field sites and with two fertilizer treatments in Madagascar. The ANOVA indicated that genotypic differences were the dominant source of variation in this dataset (Fig. 6 ) and potential high-Zn donor IRIS313-9368 (aus) was consistently superior to other accessions, irrespective of sites and fertilizer treatments.
Background & Aims: Wilson disease (WD) is a rare hereditary, debilitating disease that is fatal if untreated. Given its low prevalence, collecting longitudinal information on large cohorts of patients is challenging. Analysis of health insurance databases offers an approach to meet this challenge. The aim of this study was to evaluate longitudinal trends in the presentation and management of patients with WD identified in the French national health insurance database (SNDS). Methods: This retrospective, longitudinal, observational study identified people with WD in the SNDS database through hospitalisation diagnosis codes and long-term illness status between 2009 and 2019 inclusive. For each patient, data were extracted on hospitalisations, liver transplantation, mortality, WD-specific treatments (D-penicillamine, trientine and zinc), disability status and sick leave.
Medical treatment should never be stopped unless liver transplantation is performed, even during pregnancy. [12]. Discontinuation of treatment may place the patient at high risk of potentially fatal liver injury or severe neurological complications. For example, a case series from the US reported that eight out of eleven patients who stopped their treatment with D-penicillamine died an average of 2. 6 years after treatment cessation  [17]  The prevalence of WD is believed to be in the range of from 1:29,000 to 1:40,000, although the number of large population-based studies on which this estimate is based is limited  [18]. One such population-based study was conducted in France and reported on 906 cases identified in the French national health insurance database (Syst eme National des Donn ees de Sant e ; SNDS) in 2013  [9].
This study reported a crude prevalence of 1:67,000  [9]. In the present study, we evaluated longitudinal trends over an eleven-year follow-up period in the presentation and management of patients with WD in a large cohort of WD patients identified in the SNDS database, with the goal of gaining a better understanding of the disease burden, its complications and its evolution. The specific objectives were to document changes over time in hospitalisations, treatments, disability and mortality.
Materials and methods This retrospective, longitudinal, observational study evaluated the characteristics and healthcare resource consumption by people with WD identified in the SNDS database. Data were extracted for an eleven-year period from 1st January 2009 to 12th December 2019 inclusive. For each patient, the index date was defined as the first date at which WD was documented during the extraction period. All patients were followed from the index date until 31st December 2019, or until death or if no healthcare consumption was documented during 18 consecutive months. The study was conducted in accordance with all relevant regulatory requirements. Use of the SNDS database is regulated by the national Health Data Hub The study was authorised by the CESREES (the French expert ethical committee for health technology studies and evaluations) in July 2020 and by the French national data protection agency (Commission Nationale de l'Informatique et des Libert es) in September 2020.
Experimental Data source The SNDS database contains information on all reimbursed health care expenditure by beneficiaries of French national health insurance who subscribe to one or other of a number of different professionally-based national insurance funds. At the time when comprehensive data from the SNDS database was first made available for researchers in 2009, only the largest of these insurance funds, the General Regimen, which insures all salaried workers and their families, was available. This covers around 75% of the total French population. Although the SNDS database now contains information on most insurance funds, the present study was restricted to beneficiaries of the General Regimen, who could be covered throughout the eleven-year study period. Each beneficiary contains a unique anonymised identification number which allows their healthcare consumption to be followed over time until they die (or leave the system).
No sociodemographic information is available with the exception of the beneficiary's age, gender and administrative department of residence. If the beneficiary is eligible for fully reimbursed healthcare due to the presence of a serious chronic disease (ALD status) or due to low income, this is also documented. The SNDS database contains information on reimbursements for hospitalisations in both the public and private sectors, physician consultations, laboratory tests, clinical examinations and procedures, paramedical care and medication prescription. The reason for hospitalization is identified on the hospital discharge summary through a diseaserelated group code based on the World Health Organization's International Classification of Disease 10th Edition (ICD-10). No information is available on the reasons for any tests, medication prescription or procedures, and the results of any tests are not documented.
Participants Patients were eligible for the study if they were a beneficiary of the General Regimen and had at least one medical claim for a hospitalisation with the ICD-10 diagnostic code for WD (E83. 0*: copper metabolism disorder) mentioned on the hospital discharge summary, or were listed as eligible for ALD status for WD. Patients were excluded if they were same-sex multiple births (since they cannot be distinguished in the database), if the patient identifier reference number in the database was a provisional one (for example for migrants). Patients with no documented healthcare reimbursement for at least eighteen months were censored at this time.
Data extraction Information was extracted from the database on age, gender and administrative area of residence. Beneficiaries of ALD status for a serious chronic disease were identified and the associated disease code documented. Disease manifestations of WD were determined using list of hepatic, neurological and psychiatric signs and symptoms potentially attributable to WD. These symptoms were identified in the database through ICD-10 codes documented on hospital discharge summaries or associated with ALD status, or through the ATC codes of medications delivered if relevant (Supplementary Material). All deliveries for specific WD treatments (D-penicillamine, trientine or zinc acetate) were documented by date. Trientine was available as part of a compassionate use programme prior to 2019, and was identified in the SNDS through a specific code for medications for which a final negotiated price had not yet been agreed, and which are only available through a compassionate use or early access programme.
Calculation Derived variables Discontinuation was defined as a period of 90 days without delivery of D-penicillamine or trientine, or of 180 days without delivery of zinc acetate. Combinations of specific WD treatments, and switches between treatments were documented. Incidence of WD was determined as the number of patients with a first documentation of WD in the full SNDS database in each year of inclusion and no such documentation in the preceding two years, divided by the total number of individual insured by national public health insurance (>99% of the total French population) for the same year. Prevalence of WD was defined as the number of patients with WD identified in the database in each year of inclusion, divided by the total number of insurees for the same year.
Study participants Over the eleven-year recruitment period, 1928 patients with WD were identified. Of these, 1520 patients (78. 8%) were analysed, the 408 remaining patients being excluded since they were not insured through the General Regimen at inclusion. Six-hundred and forty patients (44. 1%) were identified during the first year that the database was available (2009). Of the 1520 analysable patients, 1096 patients (72. 1%) could be followed in the database for five years and 519 (34. 1%) for eleven years (the maximum follow-up duration possible). The total number of 1520 patients identified was used to calculate incidence and prevalence rates. The prevalence rate ranged from 1. 3 cases per 100,000 in 2009 to 2. 2 cases per 100,000 in 2019, and the incidence rate varied from 0. 8 cases per million inhabitants per year in 2018 to 2.
0% (68/424) in the eleventh year of follow-up. In the year following the index date, 266 patients (27. 2%) had taken sick leave and this proportion declined somewhat in the years following first documentation in the database Fig. 5 ). Over this period, the mean duration of sick leave taken decreased, from 146 § 300 days in the year following the index date to 58 § 111 days for Year 10 (the last full year available) Fig. 5 ). For example, in 2017,the population of 838 patients with WD were absent for a total of 13,527 days of sick leave (16. 1 days per patient).
Discussion This study identified 1928 WD patients in France and included 1520 patients with WD for whom complete data Fig. 4  Change in long-term disease status over time Grey columns: all patients with ALD status; red columns: patients with ALD status for Wilson's disease; green columns: patients with ALD status for another reason. were available and who were followed for up to eleven years, making this one of the largest population-based studies of WD to have been published to date. The prevalence rate observed in the most recent year available (2. 2 cases per 100,000 is 2019) is consistent with current estimates of the prevalence of WD (1:30,000 À 1:50,000 cases, equivalent to 2. 0 À3. 3 cases per 100,000)  [18]. The disease burden in these patients was already high when they were first documented in the database.
The median age at which the patients was first documented with WD in the SNDS was 38 years, which is late for a disease that generally presents in the late teens or early twenties  [20] , and late compared to the mean age at diagnosis in an earlier German cohort, which was 20 years  [21] , as well as in a contemporary Korean study also performed in an national health insurance claims database (24 years in men and 26 years in women)  [22]. This may suggest that many patients with WD in France are not diagnosed in a timely fashion or are misdiagnosed, such that the disease has progressed considerably before the patient is identified and treated. In the above Korean study  [22] , around 70% of the patients receiving symptomatic treatments for neurological and psychiatric manifestations of WD were prescribed these treatments prior to the diagnosis of WD being made, and without WD being considered as a causative factor.
Again, this may be suggestive of a significant diagnostic delay following the appearance of first symptoms. Since appropriate and timely treatment to restore copper homoeostasis can allow most patients with WD to lead normal lives, it will be important to improve standards of care with respect to diagnosis and treatment of this potentially severely debilitating and life-threatening hereditary disease. We observed that the age of first documentation in the database declined over the inclusion period from around 2014 onwards, from around 40 years in the early period to around 25 years at the end of the inclusion period. Part of this change may be due to 'catch-up' capture of older patients diagnosed prior to 2009 in the earlier part of the study. In addition, 2014 is the year in which reference centres for rare diseases such as WD were reorganised in France with increased roles and responsibilities, and this may have led to improved diagnosis and management of patients with WD.
7%  [22]. Liver transplantation is the only option to cure WD, although this is a burdensome surgical procedure which carries its own complications. We found that 10% of our cohort had undergone a documented or suspected liver transplant, with 59 incident patients (3. 9%) having a documented transplant over the ten-year follow-up period. This number of transplant recipients is consistent with the findings of an earlier French study which identified 121 patients receiving a liver transplant for WD between 1985 and 2009 in the French transplantation database (Agence de la Biom edicine)  [24]. Similar rates of liver transplantation have also been reported in cohorts of WD patients from the Czech Republic  [25] , Austria  [26]  and Germany  [21]. In the earlier French cohort  [24] , as well as in a contemporaneous German one  [27] , liver transplantation was undertaken as a rescue procedure following acute hepatic failure in around half the cases.
It was not possible to assess whether this was the case in our population as this information is not readily available in the SNDS database. Another surprising finding of the study was the low proportion of patients who received a specific treatment for WD (a copper chelator or zinc salts). Over the follow-up period, 665 patients (43. 8%) were delivered a specific treatment at least once, and this proportion actually declined over the course of the study. A low proportion of treated patients (37. 2% treated with D-penicillamine and 14. 3% with zinc acetate) was also noted in the previous French general population study of WD  [9] , which also used the SNDS database, as well as in the South Korean study (34. 9% receiving a specific WD treatment; 18. 2% prescribed D-penicillamine alone or in combination)  [22].
Current practice guidelines emphasise that all patients with WD should be treated, with the exceptions of young asymptomatic patients during their very first years of life, typically identified by family screening, and patients who have undergone liver-transplantation. However, our patients were generally not young children (15% aged >16 years), and only 10% had received a liver transplant. Further research is needed to understand why the treatment rate for WD is apparently so low in France and its consequences in terms of disease burden and early mortality. The data obtained on burden of disease in the present study can be compared with those reported for multiple sclerosis (MS), again obtained from analysis of the data in the SNDS database  [28]. For example, in 2013, 45% of patients with MS were hospitalised, 30% received a disability pension and 21% took sick-leave with a median duration of 29 days per sick-leave.
Although the proportion of patients taking sick-leave are quite similar for WD and MS, the duration of sick leave was five times longer in WD, perhaps representing the severity of complications of WD. The study has a number of limitations. Several of these reflect the organisation and content of the SNDS database. Notably, individual medical conditions (such as WD) are only identified if they are associated with a hospitalisation or with attribution of ALD status, so the number of cases may be underestimated. Individual patient records cannot be accessed through the database, which limits the amount of information available. The date of diagnosis is not   documented and diagnostic tests or consultations for WD and outpatient care of the condition are not specifically identified. No information is available on severity of symptoms.
A further limitation is that, during the period of the study, complete data were only available in the SNDS database for individuals insured through the General Regimen of French health insurance. Individual insurance funds in France are organised by profession, and professional classes other than salaried workers (such as agricultural workers, the self-employed, civil servants and the military) have not been included in our study. However, there is no particular reason to think that the findings of the study would be influenced by professional status. Since the inclusion criteria were based on hospitalisation or ALD codes, it is possible that certain patients not benefitting from ALD status and who were never hospitalised, whose disease was managed by community physicians, may have been missed, and that the prevalence of WD has thus been underestimated.
Nonetheless, as stated above, the prevalence rate identified in this study is consistent with previously published data  [18]. Interpretation of the study is complicated by the absence of data in the SNDS prior to 2009. In consequence, there is a large cohort of patients identified in the first year of the study who may have been hospitalised several times in the past, and these events cannot be identified. Secondly, as the diagnosis of WD is not explicitly documented, patients may have been diagnosed for a long, and unknown, period before they are hospitalised or obtain ALD status. This may particularly be the case for asymptomatic patients or those with mild symptoms, or presymptomatic patients diagnosed through genetic testing. Indeed, the median age of our patients at the index date was 39 years, whereas WD is generally diagnosed before the age of thirty  [20].
1g  and S3 ). Minor elements Ca and, to a lesser extent Fe, are negatively correlated to other elements in many organs (Fig. 1g ). The metallome fingerprint is highly conserved across different studies. We compared our results with a recent mouse study  14  , which measured a smaller subset of the metallome in mouse organs at different ages. With the same set of metals and organs, the respective PCAs agree almost perfectly, demonstrating a highly conserved metallome distribution in mouse organs (Fig. 2a, b ). For a given organ, age effects converged in both studies despite very different timepoints (16 timepoints at 2 months intervals  14  versus 3 timepoints in this study) and different diets (NIH-31  14  vs Teklad 18% protein) (Fig. 2c ). After age correction, the correlation networks generated with both datasets still converge in most organs (Figs.
The organs were flash frozen in liquid nitrogen (N 2 ), and stored at -80 °C, to promote their conservation before chemical and metabolomics analyses. In vivo phenotyping. All phenotype data used in this paper was previously published in Houtkooper et al. 39  , but a brief description of the procedures is provided here. Body composition was determined by Echo-MRI (Echo Medical Systems, Houston, TX, USA) and oxygen consumption (VO 2 ), respiratory exchange ratios (RER), activity levels and activity were monitored by indirect calorimetry using the comprehensive laboratory animal monitoring system (CLAMS) (Columbus Instruments, Columbus, OH, USA). Glucose tolerance was analyzed by measuring blood glucose and insulin following intraperitoneal injection of 2 g/kg glucose after an overnight fast.