Expression and localization of estrogenic type 12 17β-hydroxysteroid dehydrogenase in the cynomolgus monkey

BACKGROUND: We have recently discovered that human type 12 17β-HSD (h17β-HSD12), a homolog of type 3 17β-HSD, is a new estrogen-specific 17β-hydroxysteroid dehydrogenase involved in the production of estradiol (E2). To further characterize this estradiol-producing enzyme, we have isolated the corresponding cDNA in the cynomolgus monkey (Macaca fascicularis), characterized its enzymatic activities and performed cellular localization using in situ hybridization. RESULTS: Using HEK-293 cells stably expressing Macaca fascicularis type 12 17β-HSD (mf17β-HSD12), we have found that the mf17β-HSD12 catalyzes efficiently and selectively the transformation of El into E2, in analogy with the h17β-HSD12. We have also quantified the mf17β-HSD12 mRNA expression levels in a series of Macaca fascicularis tissues using Quantitative RealTime PCR. The Macaca fascicularis 17β-HSD12 mRNA is widely expressed with the highest levels tissues found in the cerebellum, spleen and adrenal with moderate level observed in all the other examined, namely the testis, ovary, cerebral cortex, liver, heart, prostate, mammary gland, myometrium, endometrium, skin, muscle and pancreas. To gain knowledge about the cellular localization of the mf17β-HSD12 mRNA expression, we performed in situ hybridization using a (35)S-labeled cRNA probe. Strong labeling was observed in epithelial cells and stromal cells of the mammary gland. In the uterus, the labeling is detected in epithelial cells and stromal cells of the endometrium. CONCLUSION: These results strongly suggest that the Macaca fascicularis 17β-HSD12 is an essential partner of aromatase in the biosynthesis of estradiol (E2). It strongly suggests that in the estradiol biosynthesis pathway, the step of 17-ketoreduction comes after the step of the aromatization (the aromatization of 4-androstendione to estrone followed by the conversion of estrone into estradiol by estrogen specific l7β-HSDs) which is in contrast with the hypothesis suggesting that 4-androstenedione is converted to testosterone followed by the aromatization of testosterone

An Inexact Newton-Type Method for Inverse Singular Value

In this paper, an inexact Newton-type approach is proposed for solving inverse singu- lar value problems. We show that the method converges superlinearly. This method can reduce signi¯cantly the oversolving problem of the Newton-type method and improve the e±ciency. Numerical experiments is also presented to illustrate our results

Effect of dietary soy isoflavones on bone loss in ovariectomized rats

Purpose: To determine the effect of dietary soy isoflavone supplementation on bone loss in ovariectomized (OVX) rats.Methods: Forty-eight rats were assigned randomly to groups of OVX rats receiving soy isoflavones (20, 30, or 40 mg/kg of body weight daily), untreated OVX rats, or untreated intact rats. After 8 weeks, bone mineral density (BMD), mineral (Ca, P, Mn, Mg, and Zn) concentrations, and the expression of osteoblast-related genes were measured in femur tissue samples.Results: Eight weeks after OVX, there was a significant decrease in body weight, serum levels of osteocalcin, alkaline phosphatase, and oestradiol, BMD and mineral elements, as well as the expressions of Ctnnb1, Runx2, and Sp7 (all p < 0.05). These decreases were accompanied by reduced maximum load capacity of lumbar vertebrae. Daily supplementation with soy isoflavones dosedependently ameliorated these effects (all p < 0.05). Western blotting revealed that these effects were likely due to the reversal of the OVX-induced decrease in Notch1 proteins in bone and muscle.Conclusion: Soy isoflavone treatment represents a potential therapy for preventing postmenopausal bone loss by stimulating the Notch signalling.Keywords: Mineral elements, Alkaline phosphatase, Isoflavones, Bone loss, Notch pathwa

On Realization of Intelligent Decision-Making in the Real World: A Foundation Decision Model Perspective

Our situated environment is full of uncertainty and highly dynamic, thus hindering the widespread adoption of machine-led Intelligent Decision-Making (IDM) in real world scenarios. This means IDM should have the capability of continuously learning new skills and efficiently generalizing across wider applications. IDM benefits from any new approaches and theoretical breakthroughs that exhibit Artificial General Intelligence (AGI) breaking the barriers between tasks and applications. Recent research has well-examined neural architecture, Transformer, as a backbone foundation model and its generalization to various tasks, including computer vision, natural language processing, and reinforcement learning. We therefore argue that a foundation decision model (FDM) can be established by formulating various decision-making tasks as a sequence decoding task using the Transformer architecture; this would be a promising solution to advance the applications of IDM in more complex real world tasks. In this paper, we elaborate on how a foundation decision model improves the efficiency and generalization of IDM. We also discuss potential applications of a FDM in multi-agent game AI, production scheduling, and robotics tasks. Finally, through a case study, we demonstrate our realization of the FDM, DigitalBrain (DB1) with 1.2 billion parameters, which achieves human-level performance over 453 tasks, including text generation, images caption, video games playing, robotic control, and traveling salesman problems. As a foundation decision model, DB1 would be a baby step towards more autonomous and efficient real world IDM applications.Comment: 26 pages, 4 figure

Machine learning-based on cytotoxic T lymphocyte evasion gene develops a novel signature to predict prognosis and immunotherapy responses for kidney renal clear cell carcinoma patients

BackgroundImmunotherapy resistance has become a difficult point in treating kidney renal clear cell carcinoma (KIRC) patients, mainly because of immune evasion. Currently, there is no effective signature to predict immunotherapy. Therefore, we use machine learning algorithms to construct a signature based on cytotoxic T lymphocyte evasion genes (CTLEGs) to predict the immunotherapy responses of patients, so as to screen patients effective for immunotherapy.MethodsIn public data sets and our in-house cohort, we used 10 machine learning algorithms to screen the optimal model with 89 combinations under the cross-validation framework, and 101 published signatures were collected. The relationship between the CTLEG signature (CTLEGS) and clinical variables was analyzed. We analyzed the role of CTLES in other types of cancer by pan-cancer analysis. The immune cell infiltration and biological characteristics were evaluated. Moreover, the response to immunotherapy and drug sensitivity of different risk groups were investigated. The key gene closely related to the signature was identified by WGCNA. We also conducted cell functional experiments and clinical tissue validation of key gene.ResultsIn public data sets and our in-house cohort, the CTLEGS shows good prediction performance. The CTLEGS can be regard as an independent risk factor for KIRC. Compared with 101 published models, our signature shows considerable superiority. The high-risk group has abundant infiltration of immunosuppressive cells and high expression of T cell depletion markers, which are characterized by immunosuppressive phenotype, minimal benefit from immunotherapy, and resistance to sunitinib and sorafenib. The CTLEGS was also strongly correlated with immunity in pan-cancer. Immunohistochemistry verified that T cell depletion marker LAG3 is highly expressed in high-risk groups in the clinical in-house cohort. The key CTLEG STAT2 can promote the proliferation, migration and invasion of KIRC cell.ConclusionsCTLEGS can accurately predict the prognosis of patients and their response to immunotherapy. It can provide guidance for the precise treatment of KIRC and help clinicians identify patients who may benefit from immunotherapy

Suggestions on the development strategy of shale gas in China

AbstractFrom the aspects of shale gas resource condition, main exploration and development progress, important breakthrough in key technologies and equipment, this paper systematically summarized and analyzed current situation of shale gas development in China and pointed out five big challenges such as misunderstandings, lower implementation degree and higher economic uncertainty of shale gas resource, and still no breakthrough in exploration and development core technologies and equipment for shale gas buried depth more than 3500 m, higher cost and other non-technical factors that restrict the development pace. Aiming at the above challenges, we put forward five suggestions to promote the shale gas development in China: (1) Make strategies and set goals according to our national conditions and exploration and development stages. That is, make sure to realize shale gas annual production of 20 × 109 m3, and strives to reach 30 × 109 m3. (2) Attach importance to the research of accumulation and enrichment geological theory and exploration & development key engineering technologies for lower production and lower pressure marine shale gas reservoir, and at the same time orderly promote the construction of non-marine shale gas exploration & development demonstration areas. (3) The government should introduce further policies and set special innovation funds to support the companies to carry out research and development of related technologies and equipment, especially to strengthen the research and development of technology, equipment and process for shale gas bellow 3500 m in order to achieve breakthrough in deep shale gas. (4) Continue to promote the geological theory, innovation in technology and management, and strengthen cost control on drilling, fracturing and the whole process in order to realize efficient, economic and scale development of China's shale gas. (5) Reform the mining rights management system, establish information platform of shale gas exploration and development data, and correctly guide the non-oil and gas companies to participate in shale gas exploration and development

Concept for a Future Super Proton-Proton Collider

Following the discovery of the Higgs boson at LHC, new large colliders are being studied by the international high-energy community to explore Higgs physics in detail and new physics beyond the Standard Model. In China, a two-stage circular collider project CEPC-SPPC is proposed, with the first stage CEPC (Circular Electron Positron Collier, a so-called Higgs factory) focused on Higgs physics, and the second stage SPPC (Super Proton-Proton Collider) focused on new physics beyond the Standard Model. This paper discusses this second stage.Comment: 34 pages, 8 figures, 5 table

Characterization of Adenocarcinoma\u27s Autofluorescence Properties Using Multiexcitation Analysis Method

General purpose of this research is to get an early cancer detection method based on the properties of optical analysis between normal and adenocarsinoma tissue using the multiexcitation autofluorescence method. Observation of autofluorescence properties was done on the biopsy sample of adenocarcinoma tissues, GR mice transplanted by adenocarsinoma, and cell culture SM 1. Excitation on tissue was done by using  the lamp Light Emitting Diode (LED) at some visible light wavelength range. This research obtained that the value of Intensity Auto fluorescence (IAF) at range red wavelength of cells and adenocarsinoma tissues tend to lower compared to the cells normal tissues if its were excited by blue LED. On the contrary, the value of IAF at infra red wavelength from cells and carcinoma tissues tend to higher compared to the cells and normal tissues if its were excited by red LED

Can the Chinese study on the normal range of FeNO in children evaluate standardized asthma treatment efficacy in 6- to 12-year-old children?

ObjectiveBy examining fractional exhaled nitric oxide (FeNO) levels and performing pulmonary function testing, this study explored whether the multicenter study on the normal range of FeNO in children in China can be used to evaluate standardized treatment efficacy in 6- to 12-year-old children with asthma.MethodsA total of 115 children aged 6–12 years old who were first diagnosed with asthma and received standardized asthma treatment from April 2018 to July 2022 were selected. According to the FeNO level at the first visit, the subjects were divided into different high- and low-FeNO groups according to the American Thoracic Society (ATS) guidelines and the Chinese multicenter study recommendations. The consistency of the two grouping methods and the differences between the high- and low-FeNO groups were compared after standardized treatment. The grouping method that was the most suitable for children in the cross group was discussed.Results(i) There was fair consistency between the Chinese multicenter study recommendations and the ATS guidelines regarding the classification of high- and low-FeNO groups (Kappa = 0.338). (ii) Repeated-measures ANOVA showed that the level of improvement in FVC%, FEV1%, FEF25%, FEF50%, and FeNO in the American high- and low-FeNO groups differed with the duration of therapy (P < 0.05), however, there was no significant difference between the Chinese groups. (iii) FEV1% and FeNO improved more after treatment in the fixed high-FeNO group than in the cross group (P < 0.05).ConclusionThe Chinese multicenter study on the normal range of FeNO in children in China has a limited role in evaluating standardized asthma treatment efficacy in 6- to 12-year-old children. The ATS guidelines are currently recommended for clinical assessment of asthma treatment efficacy