Torque measurement in real time during mixing and kneading of bread dough with high content of resistant maize starch and enzymes

In this work, a methodology to measure torque during dough mixing in large scale was developed and the baking performance of bread dough formulated with resistant starch (RS) and enzymes was evaluated. Dough was formulated with 12.5 g/100 g of RS and 4 mg/100 g of a mixture of enzymes, glucose-oxidase (Gox), tranglutaminase (TG) and xylanase (HE) in proportions according to a three-component mixture design of experiments. Dough was mixed in a large-scale dynamic rheometer measuring instant torque and speed in real time through a personal computer (PC) interface. Maximum torque during mixing and parameters of the dough development curves obtained from rheofermentometer were fit to mathematical models within 95 % of confidence. Gox and TG showed positive effects on the maximum height of dough, while HE showed a negative one. Also, it was found that Gox and TG in the presence of HE could be important for reducing dough weakening.Fil: Altuna, Luz. Universidade de Sao Paulo; BrasilFil: Romano, Roberto C. O.. Universidade de Sao Paulo; BrasilFil: Pileggi, Rafael G.. Universidade de Sao Paulo; BrasilFil: Ribotta, Pablo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; ArgentinaFil: Tadini, Carmen C.. Universidade de Sao Paulo; Brasi

Stimulation of Ca2+-ATPase Transport Activity by a Small-Molecule Drug

The sarco(endo)plasmic reticulum Ca(2+)−ATPase (SERCA) hydrolyzes ATP to transport Ca(2+) from the cytoplasm to the sarcoplasmic reticulum (SR) lumen, thereby inducing muscle relaxation. Dysfunctional SERCA has been related to various diseases. The identification of small‐molecule drugs that can activate SERCA may offer a therapeutic approach to treat pathologies connected with SERCA malfunction. Herein, we propose a method to study the mechanism of interaction between SERCA and novel SERCA activators, i. e. CDN1163, using a solid supported membrane (SSM) biosensing approach. Native SR vesicles or reconstituted proteoliposomes containing SERCA were adsorbed on the SSM and activated by ATP concentration jumps. We observed that CDN1163 reversibly interacts with SERCA and enhances ATP‐dependent Ca(2+) translocation. The concentration dependence of the CDN1163 effect provided an EC(50)=6.0±0.3 μM. CDN1163 was shown to act directly on SERCA and to exert its stimulatory effect under physiological Ca(2+) concentrations. These results suggest that CDN1163 interaction with SERCA can promote a protein conformational state that favors Ca(2+) release into the SR lumen

Oral manifestations in a boy with X-linked reticulate pigmentary disorder

X-linked reticulate pigmentary disorder (XLPDR) is a rare, multi-systemic disease with only a limited number of families described in the literature. XLPDR has a genetic origin and the gene has been mapped to Zp22p21. Dental features resemble those of hypohidrotic ectodermal dysplasia. A case of a 3-years-old boy is described

Characterization of organic matter in spodosol amazonian by fluorescence spectroscopy.

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A novel INDEL mutation in the EDA gene resulting in a distinct X- linked hypohidrotic ectodermal dysplasia phenotype in an Italian family

A novel INDEL mutation in theEDA gene resulting in a distinctX- linked hypohidroticectoder mal dysplasia phenotypein an Italian familyEditorX-Linked Hypohidrotic Ectodermal Dysplasia (XL-HED; MIM305100) is characterized by hypodontia, misshaped teeth, hypo-hidrosis, sparse hair, peculiar facial features,1,2and occurs in lessthan 1 in every 100.000 individuals.1XL-HED is caused bymutations in the Ectodysplasin-A (EDA) gene located at Xq12-q13 with more than 100 causative mutations reported todate.1,3,4The identification of disease-causing mutations con-firms the diagnosis, however, does not automatically imply agenotype\u2013phenotype correlation