A predictive model for freshwater bioassessment (Mondego River,Portugal)

We sampled macroinvertebrates at 75 locations in the Mondego river catchment, Central Portugal, and developed a predictive model for water quality assessment of this basin, based on the Reference Condition Approach. Sampling was done from June to September 2001. Fifty-five sites were identified as “Reference sites” and 20 sites were used as “Test sites” to test the model. At each site we also measured 40 habitat variables to characterize water physics and chemistry, habitat type, land use, stream hydrology and geographic location. Macroinvertebrates were generally identified to species or genus level; a total of 207 taxa were found. By Unweighted Pair Group Method with Arithmetic mean (UPGMA) clustering and analysis of species contribution to similarities percentage (SIMPER), two groups of reference sites were established. Using Discriminant Analysis (stepwise forward), four variables correctly predicted 78% of the reference sites to the appropriate group: stream order, pool quality, substrate quality and current velocity. Test sites’ environmental quality was established from their relative distance to reference sites, in MDS ordination space, using a series of bands (BEAST methodology). The model performed well at upstream sites, but at downstream sites it was compromised by the lack of reference sites. As with the English RIVPACS predictive model, the Mondego model should be continually improved with the addition of new reference sites. The adaptation of the Mondego model methodology to the Water Framework Directive is possible and would consist mainly of the integration of the WFD typology and increasing the number of ellipses that define quality bands. Handling editor: K. Martens     

The Pressurized Porous Surface Model: An improved tool to study bacterial behavior under a wide range of environmentally relevant matric potentials

To study bacterial behavior under varying hydration conditions similar to surface soil, we have developed a system called the Pressurized Porous Surface Model (PPSM). Thin liquid films created by imposing a matric potential of − 0.4 MPa impact gene expression and colony development in Pseudomonas putida.     

The biogeochemistry of nitrogen in freshwater wetlands

The biogeochemistry of N in freshwater wetlands is complicated by vegetation characteristics that range from annual herbs to perennial woodlands; by hydrologic characteristics that range from closed, precipitation-driven to tidal, riverine wetlands; and by the diversity of the nitrogen cycle itself. It is clear that sediments are the single largest pool of nitrogen in wetland ecosystems (100's to 1000's g N m^-2) followed in rough order-of-magnitude decreases by plants and available inorganic nitrogen. Precipitation inputs (< 1–2 g N m^-2 yr^-1) are well known but other atmospheric inputs, e.g. dry deposition, are essentially unknown and could be as large or larger than wet deposition. Nitrogen fixation (acetylene reduction) is an important supplementary input in some wetlands (< < 1–3 g N m^-2 yr^-1) but is probably limited by the excess of fixed nitrogen usually present in wetland sediments.Plant uptake normally ranges from a few g N m^-2 yr^-1 to 35 g N m^-2 yr^-1 with extreme values of up to 100g N m^-2 yr^-1 Results of translocation experiments done to date may be misleading and may call for a reassessment of the magnitude of both plant uptake and leaching rates. Interactions between plant litter and decomposer microorganisms tend, over the short-term, to conserve nitrogen within the system in immobile forms. Later, decomposers release this nitrogen in forms and at rates that plants can efficiently reassimilate.The NO₃ formed by nitrification (< 0.1 to 10 g N m^-2 yr^-1 has several fates which may tend to either conserve nitrogen (uptake and dissimilatory reduction to ammonium) or lead to its loss (denitrification). Both nitrification and denitrification operate at rates far below their potential and under proper conditions (e.g. draining or fluctuating water levels) may accelerate. However, virtually all estimates of denitrification rates in freshwater wetlands are based on measurements of potential denitrification, not actual denitrification and, as a consequence, the importance of denitrification in these ecosystems may have been greatly over estimated.In general, larger amounts of nitrogen cycle within freshwater wetlands than flow in or out. Except for closed, ombrotrophic systems this might seem an unusual characteristic for ecosystems that are dominated by the flux of water, however, two factors limit the opportunity for N loss. At any given time the fraction of nitrogen in wetlands that could be lost by hydrologic export is probably a small fraction of the potentially mineralizable nitrogen and is certainly a negligible fraction of the total nitrogen in the system. Second, in some cases freshwater wetlands may be hydrologically isolated so that the bulk of upland water flow may pass under (in the case of floating mats) or by (in the case of riparian systems) the biotically active components of the wetland. This may explain the rather limited range of N loading rates real wetlands can accept in comparison to, for example, percolation columns or engineered marshes.     

Enumeration of Bacteroides succinogenes in the rumen of sheep fed maize-straw diets

Abstract Estimates of Bacteroides succinogenes in the rumen of two sheep fed a maize-straw diet exceeded 10⁸ per g of rumen ingesta and were even higher when the straw was supplemented with pelleted maize grain. A number of B. succinogenes strains were characterized in some detail and very few were found to ferment starch. Cells of freshly isolated strains lost viability more rapidly when grown on agar medium than did cells of strains which had been subjected to more transfers.     

Best Linear Unbiased Prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis

Multilocation trials are often used to analyse the adaptability of genotypes in different environments and to find for each environment the genotype that is best adapted; i.e. that is highest yielding in that environment. For this purpose, it is of interest to obtain a reliable estimate of the mean yield of a cultivar in a given environment. This article compares two different statistical estimation procedures for this task: the Additive Main Effects and Multiplicative Interaction (AMMI) analysis and Best Linear Unbiased Prediction (BLUP). A modification of a cross validation procedure commonly used with AMMI is suggested for trials that are laid out as a randomized complete block design. The use of these procedure is exemplified using five faba bean datasets from German registration trails. BLUP was found to outperform AMMI in four of five faba bean datasets.     

A real-time database/models base/expert system in predictive microbiology

Summary This paper describes the development and operation of a database/models base/expert system funded by the Ministry of Agriculture, Fisheries and Food in the UK. As part of an on-going coordinated program on predictive microbiology, the system being established involves storage of data and models relevant to changes in populations of food-borne pathogens under given conditions. The system is due to be completed by March 1994.     

Development and use of probability models: The industry perspective

Summary In the processed meat industry, food safety and microbiological shelf life issues lend themselves to the use of probability modeling. Our research concentrated on predicting the effectiveness of sodium lactate as an antibotulinal agent in vacuum packaged, uncured and cured turkey breast model systems. In uncured turkey breast containing 1.4% NaCl, 0.3% Na phosphate, and 0–3% Na lactate, the antibotulinal effect of sodium lactate can be predicted using the following model: Days to toxicity = 3.13+0.39(Na lactate)². Using cured turkey breast with 0.3% Na phosphate, 0.2% sucrose, 0–3% Na lactate, the time to toxicity can be predicted from the following model: Days to toxicity = 1.69+4.88(NaCl)–11.16(Na lactate)+7.23(Na lactate)². Probability models have also been developed to predict the refrigerated shelf life of specific processed meat products. The usefulness of the predictive modeling for food safety and quality in the food industry will also be discussed.This paper was presented at The International Conference on the Application of Predictive Microbiology and Computer Modeling Techniques to the Food Industry, April 12–15 1992, Hyatt Regency Hotel, Tampa, FL, USA.     

尿铜蓝蛋白、肾损伤因子1与糖尿病肾病患者肾功能的关系及对预后不良的预测价值研究

摘要 目的：探讨尿铜蓝蛋白（CP）、肾损伤因子1（KIM-1）与糖尿病肾病（DKD）患者肾功能的关系及对预后不良的预测价值。方法：回顾性分析2017年1月～2019年1月陆军第八十二集团军医院肾内科收治的160例DKD患者（DKD组）的临床资料,随访3年,根据是否发展为终末期肾脏疾病（ESRD）分为预后不良组42例和预后良好组118例,另选取同期56例单纯2型糖尿病（T2DM）患者作为T2DM组和47例体检健康者作为对照组。采用微量法和酶联免疫吸附试验法检测尿CP、KIM-1水平,并计算尿白蛋白/肌酐比值（UACR）和估算肾小球滤过率（eGFR）。通过Spearman相关性分析DKD患者尿CP、KIM-1与UACR、eGFR的相关性,单因素和多因素Logistic回归分析DKD患者预后不良的影响因素,受试者工作特征（ROC）曲线分析尿CP、KIM-1对DKD患者预后不良的预测价值。结果：随访3年,160例DKD患者有42例发展为ESRD,预后不良发生率为26.25％（42/160）。DKD组尿CP、KIM-1、UACR高于T2DM组、对照组,eGFR低于T2DM组、对照组（P＜0.05）;T2DM组尿CP、KIM-1、UACR高于对照组,eGFR低于对照组（P＜0.05）。Spearman相关性分析显示,DKD患者尿CP、KIM-1与UACR呈正相关（P均＜0.001）,与eGFR呈负相关（P均＜0.001）。多因素Logistic回归分析显示,高血压、DKD分期4期和糖化血红蛋白（HbA1c）（较高）、低密度脂蛋白胆固醇（LDL-C）（较高）、UACR（较高）、尿CP（较高）、尿KIM-1（较高）为DKD患者预后不良的独立危险因素（P＜0.05）,eGFR（较高）为独立保护因素（P＜0.05）。ROC曲线分析显示,尿CP、KIM-1联合预测DKD患者预后不良的曲线下面积大于各指标单独预测。结论：DKD患者尿CP、KIM-1升高与肾功能降低和预后不良密切相关,尿CP、KIM-1联合预测DKD患者预后不良的价值较高。     

不同病情急性呼吸窘迫综合征患者血清铁蛋白、血管生成素样蛋白4、降钙素原与白蛋白比值的变化及对预后的评估价值

摘要 目的：探讨不同病情急性呼吸窘迫综合征（ARDS）患者血清铁蛋白、血管生成素样蛋白4（ANGPTL4）、降钙素原与白蛋白比值（PAR）的变化及对预后的评估价值。方法：选取2019年3月至2022年6月四川大学华西第四医院重症医学科收治的109例ARDS患者,根据氧合指数（PaO₂/FiO₂）将患者分为轻度组（200 mmHg＜PaO₂/FiO₂≤300 mmHg,38例）、中度组（100 mmHg＜PaO₂/FiO₂≤200 mmHg,42例）、重度组（≤100 mmHg,29例）。检测所有ARDS患者血清铁蛋白、ANGPTL4水平及PAR,根据患者入院后28 d内生存状况将其分为存活组（69例）、死亡组（40例）。多因素Logistic回归分析ARDS患者入院后28 d内死亡的危险因素。受试者工作特征（ROC）曲线分析血清铁蛋白、ANGPTL4、PAR评估ARDS患者预后的预测价值。结果：重度组血清铁蛋白、ANGPTL4、降钙素原及PAR高于中度组和轻度组（P＜0.05）,血清白蛋白水平低于中度组和轻度组（P＜0.05）。死亡组血清铁蛋白、ANGPTL4、降钙素原及PAR高于存活组（P＜0.05）,血清白蛋白水平低于存活组（P＜0.05）。高SOFA评分、高PAR及血清铁蛋白、ANGPTL4水平升高是 ARDS患者入院28 d内死亡的危险因素（P＜0.05）。联合血清铁蛋白、ANGPTL4、PAR三项指标预测ARDS患者预后的曲线下面积为0.867,高于单独指标预测的0.775、0.727、0.776。结论：ARDS患者血清铁蛋白、ANGPTL4水平及PAR增高与病情加重以及预后不良有关,联合检测三项指标在ARDS患者预后评估中具有较高价值。     

25OH维生素D水平检测与自闭症评定量表（CARS）评分的相关性及预测模型研究

摘要 目的：探究25OH维生素D（25(OH) D）水平检测与自闭症评定量表（CARS）评分的相关性及其评估自闭症严重程度的价值。方法：选取2020年4月~2022年3月在我院确诊的自闭症谱系障碍（ASD）患儿67例作为ASD组,并按照病情严重程度将所有患儿分为轻中度组46例,重度组36例。另募集来我科就诊无精神病史及家族史的健康查体儿童93例作为对照组。对比ASD组与对照组、ASD患儿轻中度组与重度组25(OH) D水平差异,分析ASD组患儿25(OH)D水平的影响因素,比较ASD组不同25(OH)D水平患儿CARS评分差异性,分析ASD患儿血清25(OH)D水平与CARS评分的相关性,并采用ROC曲线评估血清25(OH)D水平预估ASD严重程度的效能。结果：ASD组患儿血清25(OH) D水平显著低于于对照组（P<0.05）。相较于轻中度组,重度孤独症组患儿血清25(OH) D水平显著降低（P<0.05）。25(OH) D异常组患儿中母乳喂养、偏食及腹泻发生率显著高于25(OH) D正常组（P<0.05）。25(OH) D异常组患儿中CARS评分中的人际关系、模仿、情感反应、肢体动作、使用物体、对变化的适应、视觉反应、听觉反应及总分显著高于25(OH) D正常组（P<0.05）。CARS总分分与血清25(OH)D水平的成负相关性（r=-0.367,P=0.004）。血清25(OH)D水平预估ASD严重程度的AUC为0.716,敏感度为72.48%,特异度为78.65%。结论：血清25(OH)D在ASD患儿中成低表达,而且不同严重程度患儿血清25(OH)D差异表达,而且血清25(OH)D水平与CARS总分成负相关性,其作为评估ASD严重程度的生物标志物具有一定价值。