Liver transplantation for type IV glycogen storage disease

TYPE IV glycogen storage disease is a rare autosomal recessive disorder (also called Andersen's disease1 or amylopectinosis) in which the activity of branching enzyme alpha-1, 4-glucan: alpha-1, 4-glucan 6-glucosyltransferase is deficient in the liver as well as in cultured skin fibroblasts and other tissues.2,3 This branching enzyme is responsible for creating branch points in the normal glycogen molecule. In the relative or absolute absence of this enzyme, an insoluble and irritating form of glycogen, an amylopectin-like polysaccharide that resembles plant starch, accumulates in the cells. The amylopectin-like form is less soluble than normal glycogen, with longer outer and inner chains. © 1991, Massachusetts Medical Society. All rights reserved

Liver transplantation for type I and type IV glycogen storage disease

Progressive liver failure or hepatic complications of the primary disease led to orthotopic liver transplantation in eight children with glycogen storage disease over a 9-year period. One patient had glycogen storage disease (GSD) type I (von Gierke disease) and seven patients had type IV GSD (Andersen disease). As previously reported [19], a 16.5-year-old-girl with GSD type I was successfully treated in 1982 by orthotopic liver transplantation under cyclosporine and steroid immunosuppression. The metabolic consequences of the disease have been eliminated, the renal function and size have remained normal, and the patient has lived a normal young adult life. A late portal venous thrombosis was treated successfully with a distal splenorenal shunt. Orthotopic liver transplantation was performed in seven children with type N GSD who had progressive hepatic failure. Two patients died early from technical complications. The other five have no evidence of recurrent hepatic amylopectinosis after 1.1–5.8 postoperative years. They have had good physical and intellectual maturation. Amylopectin was found in many extrahepatic tissues prior to surgery, but cardiopathy and skeletal myopathy have not developed after transplantation. Postoperative heart biopsies from patients showed either minimal amylopectin deposits as long as 4.5 years following transplantation or a dramatic reduction in sequential biopsies from one patient who initially had dense myocardial deposits. Serious hepatic derangement is seen most commonly in types T and IV GSD. Liver transplantation cures the hepatic manifestations of both types. The extrahepatic deposition of abnormal glycogen appears not to be problematic in type I disease, and while potentially more threatening in type IV disease, may actually exhibit signs of regression after hepatic allografting

Prediction of water retention of soils from the humid tropics by the nonparametric k-nearest neighbor approach

Nonparametric approaches such as the k-nearest neighbor (k-NN) approach are considered attractive for pedotransfer modeling in hydrology; however, they have not been applied to predict water retention of highly weathered soils in the humid tropics. Therefore, the objectives of this study were: to apply the k-NN approach to predict soil water retention in a humid tropical region; to test its ability to predict soil water content at eight different matric potentials; to test the benefit of using more input attributes than most previous studies and their combinations; to discuss the importance of particular input attributes in the prediction of soil water retention at low, intermediate, and high matric potentials; and to compare this approach with two published tropical pedotransfer functions (PTFs) based on multiple linear regression (MLR). The overall estimation error ranges generated by the k-NN approach were statistically different but comparable to the two examined MLR PTFs. When the best combination of input variables (sand + silt + clay + bulk density + cation exchange capacity) was used, the overall error was remarkably low: 0.0360 to 0.0390 m(3) m(-3) in the dry and very wet ranges and 0.0490 to 0.0510 m(3) m(-3) in the intermediate range (i.e., -3 to -50 kPa) of the soil water retention curve. This k-NN variant can be considered as a competitive alternative to more classical, equation-based PTFs due to the accuracy of the water retention estimation and, as an added benefit, its flexibility to incorporate new data without the need to redevelop new equations. This is highly beneficial in developing countries where soil databases for agricultural planning are at present sparse, though slowly developing

Does Hydro and Osmo-Priming Improve Fennel (Foeniculum vulgare) Seeds Germination and Seedlings Growth?

This experiment was conducted to investigate the effects of hydropriming and osmopriming on germination rate, percentage of, root–shoot length and root–shoot weight of fennel (Foeniculum vulgare) seeds. Priming was done by: hydropriming with distilled water, . osmopriming with NaCl at four levels (-0.3, -0.6, -0.9, -1.2 MPa), osmopriming with K2SO4 in four levels (-0.3, -0.6, -0.9, -1.2 MPa), priming with PEG6000 in four levels (-0.3, -0.6, -0.9, -1.2MPa) and 5. seeds with unprime control at treat. In this study, RCBD experimental design was used for the analysis of experimental factors. The results showed that priming significantly effected at all treatment methods. Maximum and minimum germination percentage were obtained with PEG (-0.9 MPa) applied, and in control. Maximum and minimum germination rates were obtained when K2SO4 (-0.3 MPa), NaCl (-0.3 MPa) were used. Maximum and minimum root length were obtained when NaCl [(-1.2 MPa), PEG (-0.3 MPa)], NaCl (-0.6 MPa) were used. Maximum and minimum shoot length were obtained when PEG (-0.3 MPa), NaCl (-0.6 MPa) were used. Maximum and minimum root weight, root/shoot length were obtained when NaCl (-1.2 MPa), NaCl (-0.6 MPa) were used. Maximum and minimum shoot weight were obtained when NaCl (-1.2 MPa), NaCl (-0.3 MPa) were used. Maximum and minimum root/shoot weight were obtained when [PEG (-0.3 MPa), K2SO4 (-0.3, -0.6, -0.9 MPa), NaCl (-0.6, -0.9 MPa), hydropriming] and [PEG (-0.6, -1.2 MPa), NaCl (-1.2 MPa)] were used

Rainfall variability and drought characteristics in two agro-climatic zones: An assessment of climate change challenges in Africa

This paper aims at examining drought characteristics as an evidence of climate change in two agro-climatic zones of Nigeria and farmers' perceptions of impacts and adaptation strategies. The results show high spatial and temporal rainfall variability for the stations, in consequence, there are several anomalies in rainfall in recent years but much more in the locations around the Guinea savanna. The inter-station and seasonality statistics reveal less variable and wetter early growing seasons and late growing seasons in the Rainforest zone, and more variable and drier growing seasons in other stations. The probability (p) of dry spells exceeding 3, 5 and 10 consecutive days is very high with 0.62≤p≥0.8 in all the stations, though, the p-values for 10day spells drop below 0.6 in Ibadan and Osogbo. The results further show that rainfall is much more reliable from the month of May until July with the coefficient of variance for rainy days 0.30), though CV-RD appears higher in the month of August for all the stations. It is apparent that farmers' perceptions of drought fundamentally mirror climatic patterns from historical weather data. The study concludes that the adaptation facilities and equipment, hybrids of crops and animals are to be provided at a subsidized price by the government, for farmers to cope with the current condition of climate change

Improving the use of crop models for risk assessment and climate change adaptation

Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1. Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk? 2. Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output. 3. Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper

Investigating the Possibility of Autumn-Sown and Determining the Most Suitable Planting Date and the Best Bolt-Resistant Cultivar of Sugar Beet in Khorasan Region

IntroductionSugar beet (Beta vulgaris L.) is the second most important sugar crop after sugarcane, which annually produces about 40% of total sugar production worldwide and is adapted to different climatic conditions (El-Hag et al., 2015). Due to global warming, autumn cultivation of sugar beet is predicted to become more priority in the future, but autumn cultivation is in danger of bolting and flowering in many areas. Excessive bolting reduces sugar content, root yield, and purity of raw syrup. In general, both early sowing and delayed sowing reduce root yield, sugar, and leaf area index and increase the percentage of impurities. Therefore, this experiment was designed and implemented with the aim of feasibility study of autumn cultivation of sugar beet and determination of the best planting date in North, Razavi, and South Khorasan provinces for three new varieties resistant to sugar beet.Materials and MethodsThe experiment was conducted as a split-plot design based on a randomized complete block design with three replications in the provinces of North Khorasan (Shirvan), Khorasan Razavi (Mashhad), and South Khorasan  (Khezri Dasht-e Bayaz) in 2019-2020. The main plots included three planting dates (2, 7, and 12 October) and the subplots included three bolt-resistant sugar beet cultivars (Giada, Merak, and Sharif). Each plot consisted of 6 rows with a length of 5 m, at a distance of 50 cm and a distance between two plants of 20 cm, and planting was done manually. To determine root yield from the middle rows of each plot by eliminating the margin, harvest was done at an area of 4 m2. A sample of root paste of each treatment was sent to the Beta Lizer laboratory of Mashhad Agricultural Research and Agricultural Services Company to determine the percentage of sugar. Other quality parameters were measured by Beta Lizer (Braunschweig method). Using the polarimetry method (Sucromat), the percentage of sugar content and white sugar yield, and other quality parameters were calculated for all experimental plots. Combined analysis of variance for different locations and mean comparison based on least significant difference (LSD) at the level of 5% probability using SAS 9.4 software was performed. Also, the graph plots were performed using Excel software.Results and DiscussionThe results of the analysis of variance showed that the interaction effects of the location and cultivar were significant on bolting percentage, root yield, sugar content, Na content, yield coefficient, and white sugar yield. The first planting date (October 2) in Mashhad region for all three cultivars led to the highest percentage of bolting (78-90%). Delay in planting date from 2 October to 12 October, the bolting percentage of cultivars was reduced, significantly. The bolting percentage in Shirvan region was less than 8%. On the third planting date (October 12) in all regions, cultivars showed also a bolting percentage of less than 10%. Giada cultivar in Mashhad region with 47.3 ton.ha-1 had the highest and Sharif cultivar in Shirvan region with 22.6 ton. ha-1 had the lowest root yield. Shirvan region had less root yield than the other two regions. The highest sugar content (18.78%) belonged to Giada cultivar in Shirvan region and the lowest sugar content (13.01%) was observed in Sharif cultivar in Mashhad region. The planting date of 12 October was significantly lower in impurities, alkalinity coefficient, and molasses compared to earlier planting dates. The first planting date had the lowest (62.3%) and the third planting date had the highest (74.2%) extraction coefficient. Giada cultivar in Shirvan region had the highest extraction coefficient (78.1%) and the lowest extraction coefficient (60.8%) belonged to Sharif cultivar in Mashhad region.ConclusionIn Shirvan and Khezri regions, Giada cultivar but in Mashhad region, Merak cultivars had the highest white sugar yield. In general, the results showed that in Shirvan region, planting on 2 October and in Mashhad and Khezri regions planting on 7 October could lead to reaching maximum white sugar yield

Study of Changes in Long-term Wheat Production Trend and Factors Affecting it in North Khorasan Province: I- Irrigated Wheat

IntroductionOne of the main challenges of modern agriculture in ensuring food security is development of strategies to deal with potential negative impacts and adapt to climate change. To address this challenge, it is crucial to investigate the effects of climatic factors on agricultural production at a spatiotemporal dimension, develop and utilize crop management decision-support tools, and support targeted agronomic research and policy. These endeavors necessitate the availability of accurate and standardized meteorological data.Studying growth degree days and wheat phenology can significantly enhance our understanding of how wheat growth responds to climate change and aid farmers in adapting to and effectively mitigating its influence.Materials and MethodsTo determine the environmental and management factors affecting the yield of irrigated and rainfed wheat in different regions of North Khorasan province, we investigated the trend of yield changes from 1980 to 2009. Subsequently, we simulated the wheat plant growth stages using the DSSAT model and analyzed the impact of temperature and rainfall changes on yield through panel data analysis. Panel data analysis is a widely used statistical method in social science, epidemiology, and econometrics for analyzing two-dimensional (typically cross-sectional and longitudinal) panel data. This method involves collecting data over time from the same individuals and conducting regression analysis across these two dimensions.Results and DiscussionAccording to the results of this study, 63% of the changes in irrigated wheat yield between the years 1980-2009 can be attributed to environmental factors (temperature and precipitation), while 37% can be attributed to management factors. When comparing environmental parameters, it was observed that the number of temperatures above 30°C (N30TMAX), mean temperature (GSTMEAN), interaction of amount and frequency of precipitation (TPRAT * NPRAT) significantly affect yield (p ≤ 0.05). Bojnord, Shirvan, and Esfarayen regions exhibited significant positive cross-sectional effects in terms of environmental parameters, whereas Farooj, Raz-Jargalan, Maneh Semelghan, and Jajarm regions displayed negative cross-sectional fixed effects.A study examining the critical stages of wheat growth during good years (with high wheat grain yield) and poor years (with low wheat grain yield) revealed that in all weak years, the minimum temperatures fell below the critical level (-11°C). The occurrence of very low temperatures during the early stages of growth and primary leaf production, which is the plant establishment stage, resulted in reduced photosynthesis levels and subsequently severe yield reduction.In all regions and for 100% of the studied years, irrigated wheat in the grain-filling stage experienced temperatures above 30°C, leading to negative cross-sectional effects in Farooj, Raz-Jargalan, Maneh-Semelghan, and Jajarm. The frequency of temperatures above 30°C during the hard dough stage of irrigated wheat was higher than that during the soft dough stage in all regions. Therefore, delaying the planting date from October (the common planting date in the studied areas) would result in conflicts with high temperatures during the soft dough stage and negative temperatures during the primary leaf production stage and plant establishment at the beginning of the growing season, severely reducing yield.ConclusionIn general, the results of this study demonstrated that implementing effective management methods, particularly selecting the appropriate planting date, can lead to better adaptation of wheat's phenological stages to environmental conditions. This, in turn, has the potential to enhance wheat yield