Biosynthesis of depsipeptides with a 3-hydroxybenzoate moiety and selective anticancer activities involves a chorismatase.

Neoantimycins are anticancer compounds of 15-membered ring antimycin-type depsipeptides. They are biosynthesized by a hybrid multimodular protein complex of nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS), typically from the starting precursor 3-formamidosalicylate. Examining fermentation extracts of Streptomyces conglobatus, here we discovered four new neoantimycin analogs, unantimycins B-E, in which 3-formamidosalicylates are replaced by an unusual 3-hydroxybenzoate (3-HBA) moiety. Unantimycins B-E exhibited levels of anticancer activities similar to those of the chemotherapeutic drug cisplatin in human lung cancer, colorectal cancer, and melanoma cells. Notably, they mostly displayed no significant toxicity toward noncancerous cells, unlike the serious toxicities generally reported for antimycin-type natural products. Using site-directed mutagenesis and heterologous expression, we found that unantimycin productions are correlated with the activity of a chorismatase homolog, the nat-hyg5 gene, from a type I PKS gene cluster. Biochemical analysis confirmed that the catalytic activity of Nat-hyg5 generates 3-HBA from chorismate. Finally, we achieved selective production of unantimycins B and C by engineering a chassis host. On the basis of these findings, we propose that unantimycin biosynthesis is directed by the neoantimycin-producing NRPS-PKS complex and initiated with the starter unit of 3-HBA. The elucidation of the biosynthetic unantimycin pathway reported here paves the way to improve the yield of these compounds for evaluation in oncotherapeutic applications

Memory-enhancing effect of Rhodiola rosea L extract on aged mice

Purpose: The memory-enhancing effects of Rhodiola rosea L. extract (RRLE) on normal aged mice were assessed.Methods: In the open-field test, the effect of RRLE (150 and 300 mg/kg) on mouse locomotive activities was evaluated by investigating the extract’s influence on CAT and AchE activities in the brain tissue of mice.Results: Compared with aged group, high dose of RRLE reduced the total distance (3212.4 ± 123.1 cm, p < 0.05) significantly, increased catalase (CAT) activity (101.4 ± 12.2 U/mg pro, p < 0.05), and inhibited acetyl cholinesterase (AChE) activity (0.94 ± 0.12 U/mg pro, p < 0.05) in the brain tissue of aged mice.Conclusion: The results show that RRLE improves the memory functions of aged mice probably by increasing CAT activity while decreasing AChE activity.Keywords: Rhodiola rosea, Memory function, Catalase, Acetyl cholinesterase, Open-field tes

Autophagy promotes tumor cell survival and restricts necrosis, inflammation, and tumorigenesis

SummaryDefective apoptosis renders immortalized epithelial cells highly tumorigenic, but how this is impacted by other common tumor mutations is not known. In apoptosis-defective cells, inhibition of autophagy by AKT activation or by allelic disruption of beclin1 confers sensitivity to metabolic stress by inhibiting an autophagy-dependent survival pathway. While autophagy acts to buffer metabolic stress, the combined impairment of apoptosis and autophagy promotes necrotic cell death in vitro and in vivo. Thus, inhibiting autophagy under conditions of nutrient limitation can restore cell death to apoptosis-refractory tumors, but this necrosis is associated with inflammation and accelerated tumor growth. Thus, autophagy may function in tumor suppression by mitigating metabolic stress and, in concert with apoptosis, by preventing death by necrosis

Application and Prospect of Flexible Transmission and Distribution Technology in Internet Data Center

[Introduction] As an important thrust of China's "new infrastructure", internet data centers have ushered in opportunities for vigorous development and become new areas of energy use, putting forward higher requirements for the power supply level and capacity of the local distribution network. The innovative application of flexible transmission and distribution technology and key equipment makes the power supply and distribution system more intelligent, more flexible and more reliable, and more able to cope with the challenges brought by the large proportion of DC loads and concentrated high-load energy loads such as Internet data centers, and realize the construction and operation of Internet data centers more low-carbon, more efficient, more reliable and more economical. [Method] Firstly, the basic load requirements of Internet data center were discussed, the overall classification and performance requirements of internet data centers were analyzed. The application of flexible technology in distribution network was studied, with a focus on analyzing and comparing three types of technical routes: "rectification distribution, DC distribution, and AC-DC hybrid power supply and distribution". [Result] The paper provides provides tailored solutions for issues related to system reliability, stability, power quality, power efficiency and acceptance of new energy. [Conclusion] By summarizing the existing research results, flexible transmission and distribution technology is regarded as the core technology of building internet data center. Targeted data center control scheme should be studied from different aspects such as device and algorithms. After summarizing the research results of different aspects, the paper also looks forward to the practice and popularization of head-to-head transmission and distribution technology in internet data center

Heavy ion irradiation simulation of high dose irradiation induced radiation effects in materials

Materials used for ADS, ITER, fast reactor, etc suffer very high dose irradiations of protons and/or neutrons. The yearly accumulated irradiation doses could reach a couple of hundred dpa in ADS, ~40 dpa in fast reactors and ~30 dpa in ITER’s DEMO, producing severe radiation damage in materials and leading to a breakdown or accident of these installations. Investigation of such high dose irradiation induced radiation damage is a currently interesting topic with great importance. It is deeply hampered for lack of high dose neutron and proton sources. The heavy ion irradiation simulation technique has been developed at HI-13 tandem accelerator to investigate radiation damage encountered in the above mentioned installations. An experiment was carried out to verify the reliability and validity of heavy ion irradiation simulation. A series of experiments were performed by heavy ion irradiation simulation in combination with positron annihilation lifetime spectroscopy to investigate the temperature and dose dependence of radiation damage in stainless steels, tungsten, tantalum, etc. Some experimental results will be presented and discussed.Матеріали, що використовуються в ADS, ITER, швидкому реакторі, піддані високим дозам опромінення протонами та/або нейтронами. Це опромінення викликає серйозне радіаційне пошкодження матеріалів, що призводить до руйнування цих устаткувань або їх аварії. Дослідження радіаційних пошкоджень, зумовлених опроміненням великими дозами, є досить актуальним та важливим завданням. Однак це дослідження гальмується внаслідок відсутності нейтронних та протонних джерел, що мають високі щільності потоків часток. Моделювання з використанням опромінення важкими іонами представляє ефективний шлях такого дослідження. Метод моделювання з використанням опромінення важкими іонами на основі тандемного прискорювача НІ-13 застосовувався в Інституті атомної енергії Китаю для дослідження радіаційних пошкоджень, що спостерігаються у вищезазначених устаткуваннях. Перевірена надійність та достовірність моделювання за допомогою опромінення важкими іонами; виконано низку експериментів шляхом моделювання важкими іонами у поєднанні зі спектроскопією часу життя позитронів для вивчення залежності радіаційних пошкоджень від температури і дози для нержавіючих сталей, вольфраму, танталу і т.д. Представлені і обговорюються деякі експериментальні результати.Материалы, используемые в ADS, ITER, быстром реакторе, подвержены очень высоким дозам облучения протонами и/или нейтронами. Это облучение вызывает серьёзное радиационное повреждение материалов, что приводит к разрушению этих установок или их аварии. Исследование радиационных повреждений, вызванных облучением большими дозами, является весьма актуальной и важной задачей. Однако это исследование тормозится из-за отсутствия нейтронных и протонных источников, имеющих высокие плотности потока частиц. Моделирование с использованием облучения тяжелыми ионами предоставляет эффективный путь такого исследования. Метод моделирования с использованием облучения тяжелыми ионами на основе тандемного ускорителя НI-13 применялся в Институте атомной энергии Китая для исследования радиационных повреждений, встречающихся в вышеупомянутых установках. Проверена надежность и достоверность моделирования с помощью облучения тяжелыми ионами; выполнен ряд экспериментов путем моделирования облучения тяжелыми ионами в сочетании со спектроскопией времени жизни позитронов для изучения зависимости радиационных повреждений от температуры и дозы для нержавеющих сталей, вольфрама, тантала и т.д. Представлены и обсуждаются некоторые экспериментальные результаты

Use of Chlorella for the Treatment of the Soft-shelled Turtle Processing Wastewater

Abstract: The capability of Chlorella vulgaris to remove nitrogen in the form of ammonium ions from the softshelled turtle processing wastewater in a local agricultural products limited company (in Hangzhou, China) was studied. The soft-shelled turtle processing wastewater was found to include high concentrations of nitrogen (107.63±4.84 mg/L) in the form of ammonium (NH 4 + ) with the small amounts of nitrite (0.32±0.04 mg/L on annual average) at pH 6.7 and to be suitable for growing Chlorella vulgaris. When Chlorella vulgaris was cultivated in a batch mode, a majority of the nitrogen concentration was dramatically removed after a lag-phase period. The total biomass weight gained during the entire cultivation period balanced out well with the nitrogen removed from the culture medium. These results indicate that Chlorella vulgaris has potential to remove nitrogen (i.e., ammonium ion) and nitrite at a reasonable uptake rate from wastewater while being cultivated using the soft-shelled turtle processing wastewater

Identification of risk factors for infection after mitral valve surgery through machine learning approaches

BackgroundSelecting features related to postoperative infection following cardiac surgery was highly valuable for effective intervention. We used machine learning methods to identify critical perioperative infection-related variables after mitral valve surgery and construct a prediction model.MethodsParticipants comprised 1223 patients who underwent cardiac valvular surgery at eight large centers in China. The ninety-one demographic and perioperative parameters were collected. Random forest (RF) and least absolute shrinkage and selection operator (LASSO) techniques were used to identify postoperative infection-related variables; the Venn diagram determined overlapping variables. The following ML methods: random forest (RF), extreme gradient boosting (XGBoost), Support Vector Machine (SVM), Gradient Boosting Decision Tree (GBDT), AdaBoost, Naive Bayesian (NB), Logistic Regression (LogicR), Neural Networks (nnet) and artificial neural network (ANN) were developed to construct the models. We constructed receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) was calculated to evaluate model performance.ResultsWe identified 47 and 35 variables with RF and LASSO, respectively. Twenty-one overlapping variables were finally selected for model construction: age, weight, hospital stay, total red blood cell (RBC) and total fresh frozen plasma (FFP) transfusions, New York Heart Association (NYHA) class, preoperative creatinine, left ventricular ejection fraction (LVEF), RBC count, platelet (PLT) count, prothrombin time, intraoperative autologous blood, total output, total input, aortic cross-clamp (ACC) time, postoperative white blood cell (WBC) count, aspartate aminotransferase (AST), alanine aminotransferase (ALT), PLT count, hemoglobin (Hb), and LVEF. The prediction models for infection after mitral valve surgery were established based on these variables, and they all showed excellent discrimination performance in the test set (AUC > 0.79).ConclusionsKey features selected by machine learning methods can accurately predict infection after mitral valve surgery, guiding physicians in taking appropriate preventive measures and diminishing the infection risk