The plant-derived triterpenoid, cucurbitacin B, but not cucurbitacin E, inhibits the developmental transition associated with ecdysone biosynthesis in Drosophila melanogaster

In insects, some sterols are essential not only for cell membrane homeostasis, but for biosynthesis of the steroid hormone ecdysone. Dietary sterols are required for insect development because insects cannot synthesize sterols de novo. Therefore, sterol-like compounds that can compete with essential sterols are good candidates for insect growth regulators. In this study, we investigated the effects of the plant-derived triterpenoids, cucurbitacin B and E (CucB and CucE) on the development of the fruit fly, Drosophila melanogaster. To reduce the effects of supply with an excess of sterols contained in food, we reared D. melanogaster larvae on low sterol food (LSF) with or without cucurbitacins. Most larvae raised on LSF without supplementation or with CucE died at the second or third larval instar (L2 or L3) stages, whereas CucB-administered larvae mostly died without molting. The developmental arrest caused by CucB was partially rescued by ecdysone supplementation. Furthermore, we examined the effects of CucB on larval-prepupal transition by transferring larvae from LSF supplemented with cholesterol to that with CucB just after the L2/L3 molt. L3 larvae raised on LSF with CucB failed to pupariate, with a remarkable developmental delay. Ecdysone supplementation rescued the developmental delay but did not rescue the pupariation defect. Furthermore, we cultured the steroidogenic organ, the prothoracic gland (PG) of the silkworm Bombyx mori, with or without cucurbitacin. Ecdysone production in the PG was reduced by incubation with CucB, but not with CucE. These results suggest that CucB acts not only as an antagonist of the ecdysone receptor as previously reported, but also acts as an inhibitor of ecdysone biosynthesis

The nucleotide and deduced amino acid sequences of porcine liver proline-β-naphthylamidase swEvidence for the identity with carboxylesterase

AbstractA cDNA clone for porcine liver proline-β-naphthylamidase was isolated and sequenced. The deduced amino acid sequence of 567 residues was highly homologous with those of carboxylesterases (EC 3.1.1.1) previously reported for other species. In addition, proline-β-naphthylamidase purified from porcine liver was shown to have strong activity towards p-nitrophenylacetate, a representative substrate for carboxylesterases. These results suggest that proline-β-naphthylamidase is identical with carboxylesterase

Prediction Model of Amyotrophic Lateral Sclerosis by Deep Learning with Patient Induced Pluripotent Stem Cells

Deep LearningとALS iPS細胞を用いた疾患予測テクノロジー --人工知能のALS検知・診断への応用--. 京都大学プレスリリース. 2021-02-24.Deep learning amyotrophic lateral sclerosis by taking pictures. 京都大学プレスリリース. 2021-02-24.In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence‐based prediction model of ALS using induced pluripotent stem cells (iPSCs). Images of spinal motor neurons derived from healthy control subject and ALS patient iPSCs were analyzed by a convolutional neural network, and the algorithm achieved an area under the curve of 0.97 for classifying healthy control and ALS. This prediction model by deep learning algorithm with iPSC technology could support the diagnosis and may provide proactive treatment of ALS through future prospective research. ANN NEUROL 202

Deep Learning and ALS

In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence-based prediction model of ALS using induced pluripotent stem cells (iPSCs). Images of spinal motor neurons derived from healthy control subject and ALS patient iPSCs were analyzed by a convolutional neural network, and the algorithm achieved an area under the curve of 0.97 for classifying healthy control and ALS. This prediction model by deep learning algorithm with iPSC technology could support the diagnosis and may provide proactive treatment of ALS through future prospective research

Protein S-guanylation by the biological signal 8-nitroguanosine 3\u27,5\u27-cyclic monophosphate

The signaling pathway of nitric oxide (NO) depends mainly on guanosine 3′,5′-cyclic monophosphate (cGMP, 1). Here we report the formation and chemical biology of a nitrated derivative of cGMP, 8-nitroguanosine 3′,5′-cyclic monophosphate (8-nitro-cGMP, 2), in NO-mediated signal transduction. Immunocytochemistry demonstrated marked 8-nitro-cGMP production in various cultured cells in an NO-dependent manner. This finding was confirmed by HPLC plus electrochemical detection and tandem mass spectrometry. 8-Nitro-cGMP activated cGMP-dependent protein kinase and showed unique redox-active properties independent of cGMP activity. Formation of protein Cys-cGMP adducts by 8-nitro-cGMP was identified as a new post-translational modification, which we call protein S-guanylation. 8-Nitro-cGMP seems to regulate the redox-sensor signaling protein Keap1, via S-guanylation of the highly nucleophilic cysteine sulfhydryls of Keap1. This study reveals 8-nitro-cGMP to be a second messenger of NO and sheds light on new areas of the physiology and chemical biology of signal transduction by NO

Enrichment in axial direction of aqueous foam in continuous foam separation

Estimation of overhead production enrichment in continuous foam separation was conducted with a surfactant: sodium n-dodecylbenzenesulfonate (SDBS), and soluble proteins: ovalbumin (OA) and hemoglobin (HB). Axial profiles of the volumetric flow rate and the concentration of the collapsed foam liquid within the column were measured, and the enrichment ratio and the liquid holdup in axial direction were determined experimentally. The proposed model was fitted to the experimental results obtained with various experimental conditions (superficial gas velocity, feed concentration, and pH) and was in reasonable agreement with the experimental data by using the least square regression. The present model makes it possible to estimate the foamate concentration at a desired foam height

Batch foam separation of a soluble protein

Removal of protein dissolved in water by batch foam separation was conducted with using ovalbumin (OA) as a model protein in the light of wastewater treatment reducing organic loading. The removal efficiency had a maximum value near the i.e.p. of OA (pH 4.6); thus, most experiments were conducted at pH 4.6. Typical experimental conditions; superficial gas velocity, Ug: 1.97×10–2–5.37×10–2 cm/s; initial bulk concentration of OA, Ci: ca. 0.05–0.25 g/L; liquid volume, V: 600 cm3. A model estimating bulk concentration profile was proposed by taking into account a mass balance of the present system. The model predicted that OA could be removed perfectly, however, was not all removed experimentally. The residual OA concentration of the bulk liquid within the column reached plateau value, which correspond to ca. 18% of the initial OA concentration. The plateau value of the bulk concentration was attained for ca. 100–500 min with Ug=1.97×10–2—5.37×10–2 cm/s. Foaming ability test revealed that the foaming limit concentration of OA at pH 4.6 was 9.72×10–3 g/L. These results suggested that OA molecules could be damaged by interaction of bubble surface in the dispersed phase, since there were the residual OA concentrations over the limit concentration. To take account of this phenomena and correct the model, average surface density, Xd, which should convert protein molecule into the denatured protein molecule, was introduced. The corrected model could explain well the time profile of OA bulk concentration