SIL1 mutations and clinical spectrum in patients with Marinesco-Sjögren syndrome

Marinesco-Sjögren syndrome is a rare autosomal recessive multisystem disorder featuring cerebellar ataxia, early-onset cataracts, chronic myopathy, variable intellectual disability and delayed motor development. More recently, mutations in the SIL1 gene, which encodes an endoplasmic reticulum resident co-chaperone, were identified as the main cause of Marinesco-Sjögren syndrome. Here we describe the results of SIL1 mutation analysis in 62 patients presenting with early-onset ataxia, cataracts and myopathy or combinations of at least two of these. We obtained a mutation detection rate of 60% (15/25) among patients with the characteristic Marinesco-Sjögren syndrome triad (ataxia, cataracts, myopathy) whereas the detection rate in the group of patients with more variable phenotypic presentation was below 3% (1/37). We report 16 unrelated families with a total of 19 different SIL1 mutations. Among these mutations are 15 previously unreported changes, including single- and multi-exon deletions. Based on data from our screening cohort and data compiled from the literature we found that SIL1 mutations are invariably associated with the combination of a cerebellar syndrome and chronic myopathy. Cataracts were observed in all patients beyond the age of 7 years, but might be missing in infants. Six patients with SIL1 mutations had no intellectual disability, extending the known wide range of cognitive capabilities in Marinesco-Sjögren syndrome to include normal intelligence. Modestly constant features were somatic growth retardation, skeletal abnormalities and pyramidal tract signs. Examination of mutant SIL1 expression in cultured patient lymphoblasts suggested that SIL1 mutations result in severely reduced SIL1 protein levels irrespective of the type and position of mutations. Our data broaden the SIL1 mutation spectrum and confirm that SIL1 is the major Marinesco-Sjögren syndrome gene. SIL1 patients usually present with the characteristic triad but cataracts might be missing in young children. As cognitive impairment is not obligatory, patients without intellectual disability but a Marinesco-Sjögren syndrome-compatible phenotype should receive SIL1 mutation analysis. Despite allelic heterogeneity and many families with private mutations, the phenotype related to SIL1 mutations is relatively homogenous. Based on SIL1 expression studies we speculate that this may arise from a uniform effect of different mutations on protein expressio

Powder formulation disintegrating system and method for dry powder

For improving efficiency of the application of medical powder formulations a disintegration means for dry powder inhalers is proposed, comprising a substantially cylindrical air circulation chamber (3) with a height being smaller than its diameter, and at least two air supply channels (2, 9) which enter the chamber (3) as tangents to its cylindrical wall (5) at generally opposite sides of this wall (5), suitable for creating a circular air flow pattern inside the chamber (3), both air channels (2, 9) either having different inlets or alternatively sharing the same inlet which is split up, so as to have one passageway (2) for traversing the dose measuring or dose supplying region of the inhaler for enabling the powder quantity of a single dose dragged into the circulation chamber (3) by air flowing through this passageway (2), and the other passageway to serve as a bypass channel (9) towards the circulation chamber (3) suitable for accelerating the particles and creating a more symmetrical flow pattern inside said chamber (3), and a method

Soil biological, chemical and physical parameters and herbage yield in a field experiment with organic and inorganic fertilizers on peat grassland in the Netherlands

To evaluate the performance of organic and inorganic fertilizers for regeneration of ecosystem services in peat grasslands with biodiversity goals, we carried out a field experiment in the western peat district in the Netherlands. The fertilizers tested represent the current practice and potential alternatives for regenerative grassland management on drained peat. Experimental setup The field experiment (2013 – 2015) was conducted on a permanent grassland on peat soil (Terric Histosol; SOM 56 g 100 g−1 and pHKCl of 4.5 in 0-10 cm) at the experimental dairy farm at Zegveld (the Netherlands). In March 2013, a randomized block experiment (six blocks) was laid out with six fertilizer treatments and a control treatment (no fertilizer: “Contr”). The fertilizer used were: conventional dairy cattle slurry manure (“Slurry”), mature compost of kitchen and garden waste (“Comp”), dairy cattle farmyard manure (“FYM”), solid fraction of the cattle slurry manure (“SFrac”, obtained by pressurized filtration), inorganic N fertilizer (“IF”; calcium ammonium nitrate, 27% N) and a combination of inorganic N fertilizer and sawdust (“IF+SD”). Plot size was 4 × 10 m; for the Slurry treatment plots were 5.2 × 10 m. Slurry was applied by slit injection, the other fertilizers were applied by hand. Target application rate was 120 kg total N ha−1 yr−1, divided in two applications per year (February/March and May). This is relatively low for conventional grasslands but usual for grasslands with biodiversity goals (Kleijn et al., 2004). The amount of Ctotal applied in Comp was taken for the rate of sawdust to be applied. All plots were fertilized with 200 kg K2O ha−1 yr−1 (applications in March and May) (Commissie Bemesting Grasland en Voedergewassen, 2019). Fertilizer application quantities and organic matter and nutrient inputs are provided in Fertilizer_intput.csv (dataset). The grassland had an history of conventional management with mainly cutting, winter grazing with sheep and a normal fertilization regime with both slurry manure and inorganic fertilizer. The normal cutting and grazing regime was continued in the first two years of the experiment; during 2015, the monitoring year, the plots were not grazed and only cut for herbage measurements. Measurements From April to October 2015, soil and aboveground measurements were carried out. Most soil parameters were measured in October. Earthworms and insect larvae are an important food source for meadow birds during the pre-breeding period in spring (Galbraith, 1989) and were therefore sampled in April. Soil moisture and penetration resistance were measured both in April and October. Soil biological parameters Earthworms and insect larvae were sampled in the top soil layer in two soil cubes (20 × 20 × 20 cm) per plot. Earthworms were hand-sorted, counted, weighed and fixed in alcohol prior to identification. Both adults and juveniles were identified to species (Sims and Gerard, 1985; Stöp-Bowitz, 1969) and classified into functional groups (Bouché, 1977). Crane flies (Tipulidae; leatherjackets) or click beetles (Elateridae; wireworms) larvae were counted. Phospholipid fatty acids (PLFA) were measured in October. PLFA were extracted from 4 g of fresh soil (Palojärvi, 2006), and analyzed by gas chromatography (Hewlett-Packard, USA). PLFA i15:0, a15:0, 15:0, i16:0, 16:1ω9, i17:0, a17:0, cy17:0, 18:1ω7 and cy19:0 were chosen to represent bacteria and PLFA 18:2ω6 was used as a marker of saprotrophic fungi (Hedlund, 2002). The neutral lipid fatty acid (NLFA) 16:1ω5 occurs in storage lipids of arbuscular mycorrhizal fungi (AMF) and was used as marker of AMF (Vestberg et al., 2012). PLFA i15:0, a15:0, i16:0, i17:0 and a17:0 were used as a measure of Gram-positive bacteria, and cy17:0 and cy19:0 for Gram-negative bacteria. PLFA 10Me16:0, 10Me17:0 and 10Me18:0 represented actinomycetes. Soil chemical parameters A soil sample from the 0−10 cm layer (c. 50 randomly taken soil cores) per experimental plot was collected in October (auger diameter 2.3 cm; Eijkelkamp grass plot sampler, Giesbeek, the Netherlands), was sieved (1 cm mesh size) and homogenized. One sub-sample was taken for analysis of hot water extractable carbon (HWC) according to Ghani et al. (2003) and one for chemical analysis. Prior to analysis of soil acidity (pHKCl), soil organic matter (SOM), total carbon (Ctotal), total nitrogen (Ntotal), total phosphorus (Ptotal) and ammonium-lactate extractable P (PAL) by Eurofins Agro (Wageningen, the Netherlands), the sub sample was dried at 40°C. Soil pHKCl was measured according to NEN-ISO 10390 2005. SOM was determined by loss-on-ignition (NEN 5754 2005). Ctotal was measured by incineration at 1150°C, and determination of the CO2 produced by an infrared detector (LECO Corporation, St. Joseph, Mich., USA). For Ntotal, evolved gasses after incineration were reduced to N2 and measured with a thermal-conductivity detector (LECO Corporation, St. Joseph, Mich., USA). Ptotal was analysed with Fleishmann acid (Houba et al., 1997). PAL is used to assess the P supply capacity of grassland soils (Reijneveld et al., 2014) and was determined according to Egnér et al. (1960) (NEN 5793). Soil physical parameters Soil moisture was determined in April and October in a homogenized 0−10 cm soil sample after drying at 105°C for 24 hrs. Moisture content was expressed as percentage of fresh soil weight. Penetration resistance was measured (April and October) with a penetrologger (Eijkelkamp, Giesbeek, the Netherlands; cone of 2.0 cm2 penetration surface and 60° apex angle. Penetration resistance was expressed as an average of 7 penetrations per plot and per soil layer of 0−10, 10−20, and 20−30 cm. Soil structure and rooting density were assessed in October in the 0−10 cm and 10−25 cm layers. The percentage of crumbs, sub-angular blocky elements and angular blocky elements was estimated by one experienced person as described by Peerlkamp (1959) and Shepherd (2000), Root density was estimated by scoring visible roots (score 1–10; 1 for no roots and 10 for above average). Water infiltration rate was measured in October at three spots per experimental plot in 5 of the 6 blocks (35 plots). A PVC pipe (15 cm high, 15 cm diameter) was pushed into the soil to a depth of 10 cm. 500 ml water was poured into each pipe and the infiltration time was recorded. If the infiltration time exceeded 15 min, the remaining water volume was estimated to calculate the infiltration rate (mm min−1). Grass yield and botanical composition Grass dry matter (DM) and N yield were determined during 2015 with a Haldrup plot harvester (J. Haldrup a/s, Løgstør, Denmark). The four harvest dates were May 15, June 29, August 19 and September 30. Fresh biomass, DM content (70°C for 24 hrs) and total N content (Kjeldahl) were determined for each harvest. Herbage DM yield (Mg DM ha−1) and herbage N yield (kg N ha−1) were calculated. Apparent N recovery (ANR; kg N.kg N−1) was calculated as (N yield(fertilized) – N yield(non-fertilized))/(N fertilization rate) (Vellinga and André, 1999). In June 2015, botanical composition was measured by visually estimating the relative soil cover of the sward and the proportion of each species therein (Sikkema, 1997). Data files Data_soil_grass.csv Content: Dataset with soil biological (earthworms, microbial PLFA), soil chemical, soil physical parameters, herbage dry matter and N yields, and botanical parameters. Column names and units: plot: Experimental plot number (1-42) treatment: Treatment code (see text) block: Block number (1-6) EW_species_number: Earthworm - number of species EW_totalnumber: Earthworm - total number per m2 EW_epigeic: Earthworm - number of epigeic adults and juveniles per m2 EW_endogeic: Earthworm - number of endogeic adults and juveniles per m2 EW_adults: Earthworm - number of adults per m2 EW_juveniles: Earthworm - number of juveniles per m2 EW_adult_epigeic: Earthworm - number of epigeic adults per m2 EW_adult_endogeic: Earthworm - number of endogeic adults per m2 EW_juven_epigeic: Earthworm - number of epigeic juveniles per m2 EW_juven_endogeic: Earthworm - number of endogeic juveniles per m2 EW_L_rubellus: Earthworm - number of L. rubellus adults and juveniles per m2 EW_A_chlorotica: Earthworm - number of A. chlorotica adults and juveniles per m2 EW_A_caliginosa: Earthworm - number of A. caliginosa adults and juveniles per m2 EW_O_lacteum: Earthworm - number of O. lacteum adults and juveniles per m2 EW_A_rosea: Earthworm - number of A. rosea adults and juveniles per m2 EW_O_cyaenum: Earthworm - number of O. cyaneum adults and juveniles per m2 EW_L_castaneus: Earthworm - number of L. castaneus adults and juveniles per m2 EW_D_rubida: Earthworm - number of D. rubida adults and juveniles per m2 EW_adult_L_rubellus: Earthworm - number of L. rubellus adults per m2 EW_adult_A_chlorotica: Earthworm - number of A. chlorotica adults per m2 EW_adult_A_caliginosa: Earthworm - number of A. caliginosa adults per m2 EW_adult_O_lacteum: Earthworm - number of O. lacteum adults per m2 EW_adult_A_rosea: Earthworm - number of A. rosea adults per m2 EW_adult_O_cyaenum: Earthworm - number of O. cyaneum adults per m2 EW_adult_L_castaneus: Earthworm - number of L. castaneus adults per m2 EW_adult_D_rubida: Earthworm - number of D. rubida adults per m2 EW_juven_L_rubellus: Earthworm - number of L. rubellus juveniles per m2 EW_juven_A_chlorotica: Earthworm - number of A. chlorotica juveniles per m2 EW_juven_A_caliginosa: Earthworm - number of A. caliginosa juveniles per m2 EW_non_determined: Earthworm - number of non determined individuals per m2 EW_total_biomass: Earthworm - total fresh biomass per m2 Leatherjackets: number of leatherjackets per m2 Wireworms: number of wireworms per m2 TOTmicrPLFA: total microbial PLFA in nmol.g-1 dry soil bactPLFA: bacterial PLFA in nmol.g-1 dry soil saprofungPLFA: saprotrophic fungal PLFA in nmol.g-1 dry soil Fung_bactPLAF_ratio: ratio of fungal to bacterial PLFA GramPLUSplfa: gram positive PLFA in nmol.g-1 dry soil GramMINplfa: gram negative PLFA in nmol.g-1 dry soil ratioGram_PLUS_MIN: ratio of gram positive to gram negative PLFA AMFsporNLFA: AMF spores NLFA in nmol.g-1 dry soil ActinomPLFA: Actinomycetes PLFA in nmol.g-1 dry soil ShannonPLFA: PLFA shannon diversity index SOM: soil organic matter in g.100 g-1 dry soil Ctotal: total C in g.100 g-1 dry soil HWC: hot water extractable C in μg.100 g-1 dry soil Ntotal: total N in g.100 g-1 dry soil Ptotal: total P2O5 in mg.100 g-1 dry soil P_AL: total P-AL in mg.100 g-1 dry soil pH_KCl: pH-KCl CN_ratio: C:N ratio C_SOM: C:SOM ratio Soilmoisture_April: soil moisture content in April in g.100g-1 fresh soil Penetrationresistance_April_cm010: penetration resistance in April in 10-20 cm in Newton Penetrationresistance_April_cm1020: penetration resistance in April in 20-30 cm in Newton Penetrationresistance_April_cm2030: penetration resistance in April in 0-10 cm in Newton Soilmoisture_October: soil moisture content in October in g.100g-1 fresh soil Penetrationresistance_October_cm010: penetration resistance in October in 10-20 cm in Newton Penetrationresistance_October_cm1020: penetration resistance in October in 20-30 cm in Newton Penetrationresistance_October_cm2030: penetration resistance in October in 0-10 cm in Newton crumb_struct_cm010: percentage of crumb elements in 0-10 cm round_struct_cm011: percentage of sub-angular elements in 0-10 cm rootdensity_cm010: score (1-10) of root density in 0-10 cm crumb_struct_cm1025: percentage of crumb elements in 10-25 cm round_struct_cm1025: percentage of sub-angular elements in 10-25 cm sharp_struct_cm1025: percentage of angular elements in 10-25 cm rootdensity_cm1025: score (1-10) of root density in 10-25 cm water_infiltration: water infiltration rate in mm per minute DM_yield_year: total herbage dry matter yield in kg.ha-1 per year DM_yield_H1: herbage dry matter yield of harvest 1 in kg.ha-1 DM_yield_H2: herbage dry matter yield of harvest 2 in kg.ha-1 DM_yield_H3: herbage dry matter yield of harvest 3 in kg.ha-1 DM_yield_H4: herbage dry matter yield of harvest 4 in kg.ha-1 N_yield_year: total herbage N yield in kg.ha-1 per year N_yield_H1: herbage N yield of harvest 1 in kg.ha-1 N_yield_H2: herbage N yield of harvest 2 in kg.ha-1 N_yield_H3: herbage N yield of harvest 3 in kg.ha-1 N_yield_H4: herbage N yield of harvest 4 in kg.ha-1 DMperc_yield_year: herbage dry matter content (per year; weighed average over the 4 harvests) in g.100g-1 fresh weight DMperc_yield_H1: herbage dry matter content of harvest 1 in g.100g-1 fresh weight DMperc_yield_H2: herbage dry matter content of harvest 2 in g.100g-1 fresh weight DMperc_yield_H3: herbage dry matter content of harvest 3 in g.100g-1 fresh weight DMperc_yield_H4: herbage dry matter content of harvest 4 in g.100g-1 fresh weight Ncontent_yield_year: herbage N content (per year; weighed average over the 4 harvests) in g.kg-1 dry matter Ncontent_yield_H1: herbage N content of harvest 1 in g.kg-1 dry matter Ncontent_yield_H2: herbage N content of harvest 2 in g.kg-1 dry matter Ncontent_yield_H3: herbage N content of harvest 3 in g.kg-1 dry matter Ncontent_yield_H4: herbage N content of harvest 4 in g.kg-1 dry matter fresh_yield_H1: herbvage fresh yield of harvest 1 in Mg.ha-1 ANR: apparent N recovery in kg N.kg N-1 productive_grasses: cover percentage of L. perenne and P trivialis monocotyledons: cover percentage of monocotyledons dicotyledons: cover percentage of dicotyledons plant_species: number of plant species monocot_species: number of monocotyledon species dicot_species: number of dicotyledon species Lolium_perenne: plant cover % Poa_trivialis: plant cover % Phleum_pratense: plant cover % Elytrigia_repens: plant cover % Poa_annua: plant cover % Agrostis_stolonifera: plant cover % Holcus_lanatus: plant cover % Alopecurus_pratensis: plant cover % Alopecurus_geniculatus: plant cover % Trifolium_repens: plant cover % Taraxacum_officinale: plant cover % Ranunculus_arvensis: plant cover % Rumex_obtusifolius: plant cover % Rumex_crispus: plant cover % Ranunculus_acris: plant cover % Stellaria_media: plant cover % Cardamine_pratensis: plant cover % Bellis_perennis: plant cover % Rumex_acetosa: plant cover % Ranunculus_sceleratus: plant cover % Polygonum_aviculare: plant cover % Capsella_bursa-pastoris: plant cover % Glechoma_hederacea: plant cover % Geranium_molle: plant cover % Fertilizer_input.csv Content: Application quantities of fertilizers and ash, organic matter, C and mineral inputs, and fertilizer C:N ratio. Total N input is the sum of mineral N (Nmin) and organic N (Norg). Average values per hectare and per year over the years 2013−2015. Column names and units: Treatment: Treatment code (see text) Fertilizer_fresh: Applied fertilizer in Mg.ha-1 per year (fresh weight) Fertilizer_DM: Applied fertilizer in Mg.ha-1 per year (dry matter weight); for IF+SD this is the sum of 2.72 Mg sawdust + 0.45 Mg N fertilizer Ash: Mineral fraction in kg.ha-1 per year OM: Organic matter in kg.ha-1 per year C: Total C in kg.ha-1 per year Nmin: Mineral N in kg.ha-1 per year Norg: Organic N in kg.ha-1 per year P2O5: kg.ha-1 per year C_N_ratio: C:N rati

Effects of organic and inorganic fertilizers on soil properties related to the regeneration of ecosystem services in peat grasslands

Worldwide, agricultural grasslands on drained peat contribute to CO2 emission but provide also provisioning and supporting ecosystem services that are managed by farmers. This paper evaluates the performance of organic and inorganic fertilizers in relation to soil biotic and abiotic properties linked to soil ecosystem services of peat grasslands with biodiversity goals. Effects of cattle slurry, compost, farmyard manure, solid fraction of cattle slurry and inorganic nitrogen (N) fertilizer with and without added sawdust were compared to those of an unfertilized control in a three-year field experiment. Total N input was targeted at 120 kg N ha−1 year−1; total carbon (C) input was variable due to different C:N ratios of source materials. The abundance of earthworms in spring was increased with solid fraction (+35 % as compared to the control), which had the largest C input, and was reduced with inorganic N (−24 %). Combining inorganic N with sawdust did not affect earthworm abundance. Bacteria (determined by phospholipid fatty acid analysis) were increased following inorganic N fertilizer application with (+65 %) or without (+52 %) sawdust. Arbuscular mycorrhizal fungi were reduced by all fertilizers (−40 to −88 %), but less so by those with large C input (solid fraction) or with lignin-rich C input (sawdust + inorganic N fertilizer). Physical and chemical soil properties related to water infiltration and soil organic matter (SOM) decomposition were marginally influenced by fertilizers. The measured changes in soil pH, P availability and (micro)biology may affect SOM dynamics in the longer term. Grass dry matter yield was similarly increased by all fertilizers (+7 to 11 %) whereas grass N yield was increased by fertilizers only when the applied N was in mineral form (+16 to 20 %). From our results, we propose that the moderate use of organic fertilizers with a high and non-humified organic matter content such as solid fraction of cattle slurry can be part of a regeneration strategy in peat grasslands with biodiversity goals

Productivity and topsoil quality of young and old permanent grassland : An on-farm comparison

Renewing agricultural grasslands for improved yields and forage quality generally involves eliminating standing vegetation with herbicides, ploughing and reseeding. However, grassland renewal may negatively affect soil quality and related ecosystem services. On clay soil in the north of the Netherlands, we measured grass productivity and soil chemical parameters of 'young' (5-15 years since last grassland renewal) and 'old' (>20 years since last grassland renewal) permanent grasslands, located as pairs at 10 different dairy farms. We found no significant difference with old permanent grassland in herbage dry matter yield and fertilizer nitrogen (N) response, whereas herbage N yield was lower in young permanent grassland. Moreover, the young grassland soil contained less soil organic matter (SOM), soil organic carbon (C) and soil organic N compared to the old grassland soil. Grass productivity was positively correlated with SOM and related parameters such as soil organic C, soil organic N and potentially mineralizable N. We conclude that on clay soils with 70% desirable grasses (i.e., Lolium perenne and Phleum pratense) or more, the presumed yield benefit of grassland renewal is offset by a loss of soil quality (SOM and N-total). The current practice of renewing grassland after 10 years without considering the botanical composition, is counter-productive and not sustainable.</p

Effects of Ca:Mg ratio and pH on soil chemical, physical and microbiological properties and grass N yield in drained peat soil

In three dairy grasslands on peat, minerals were added to manipulate the soil Ca:Mg ratio with or without effect on pH. The responses of soil properties and grass N yield were measured. CaCO3 application led to higher soil Ca:Mg ratio and pHKCl compared to the untreated control, decreased Ntotal and Ctotal, and increased P availability. Grass N yield increased in the first year by only 6% of the reduction in soil Ntotal, but not in the second year. A higher pH increased SOM decomposition, especially in soils with high P availability. MgCO3 reduced the Ca:Mg ratio, had little influence on soil parameters and no effect on grass N yield. In contrast, CaSO4 and MgSO4 did not influence pHKCl but reduced grass N yield in most cases. Results suggest stabilisation of organic matter by Ca binding in treatments with added Ca. We conclude that grass N yield was not linked with changes in Ca:Mg ratio but with soil pH. The pH effects on SOM decomposition depended on P availability and Ca binding. Hence, to avoid potentially large soil losses of C and N, the current agricultural advice on pH management in peat grasslands should be better adapted to local edaphic characteristics

Productivity and topsoil quality of young and old permanent grassland : An on-farm comparison

Renewing agricultural grasslands for improved yields and forage quality generally involves eliminating standing vegetation with herbicides, ploughing and reseeding. However, grassland renewal may negatively affect soil quality and related ecosystem services. On clay soil in the north of the Netherlands, we measured grass productivity and soil chemical parameters of 'young' (5-15 years since last grassland renewal) and 'old' (>20 years since last grassland renewal) permanent grasslands, located as pairs at 10 different dairy farms. We found no significant difference with old permanent grassland in herbage dry matter yield and fertilizer nitrogen (N) response, whereas herbage N yield was lower in young permanent grassland. Moreover, the young grassland soil contained less soil organic matter (SOM), soil organic carbon (C) and soil organic N compared to the old grassland soil. Grass productivity was positively correlated with SOM and related parameters such as soil organic C, soil organic N and potentially mineralizable N. We conclude that on clay soils with 70% desirable grasses (i.e., Lolium perenne and Phleum pratense) or more, the presumed yield benefit of grassland renewal is offset by a loss of soil quality (SOM and N-total). The current practice of renewing grassland after 10 years without considering the botanical composition, is counter-productive and not sustainable.</p