Energy Efficiency Optimization Design of a Forward-Swept Axial Flow Fan for Heat Pump

As one of the key components of the heat pump system, compared to that of a conventional axial fan, the blade tip area of a forward-swept axial fan is much larger than its blade root, which is the main noise source of the fan and also has an important influence on the fan efficiency. Enhancement of the aerodynamic performance and efficiency of a forward-swept axial fan was addressed by utilizing the Bezier function to parameterize the forward-swept curve on blade tops. In order to quickly select an agent model suitable for the project, an ES model was established by integration of the radial basis function model and the Kriging model. When NSGA-II was combined, multi-objective optimization was carried out with the flow rate and total pressure efficiency as optimization goals. Analysis of optimization results revealed that the optimized axial flow fan’s flow rate and total pressure efficiency were improved to some degree. At the design working point, the fan’s flow rate increased by 1.78 m³/min, while the total pressure efficiency increased by 3.0%. These results lay solid foundation for energy saving of the heat pump system

Towards Improving the Expressiveness of Singing Voice Synthesis with BERT Derived Semantic Information

This paper presents an end-to-end high-quality singing voice synthesis (SVS) system that uses bidirectional encoder representation from Transformers (BERT) derived semantic embeddings to improve the expressiveness of the synthesized singing voice. Based on the main architecture of recently proposed VISinger, we put forward several specific designs for expressive singing voice synthesis. First, different from the previous SVS models, we use text representation of lyrics extracted from pre-trained BERT as additional input to the model. The representation contains information about semantics of the lyrics, which could help SVS system produce more expressive and natural voice. Second, we further introduce an energy predictor to stabilize the synthesized voice and model the wider range of energy variations that also contribute to the expressiveness of singing voice. Last but not the least, to attenuate the off-key issues, the pitch predictor is re-designed to predict the real to note pitch ratio. Both objective and subjective experimental results indicate that the proposed SVS system can produce singing voice with higher-quality outperforming VISinger

Risk of cardiovascular disease in Chinese patients with rheumatoid arthritis: a cross sectional study based on hospital medical records in 10 years

Objective: Though the risk of cardiovascular disease (CVD) in rheumatoid arthritis (RA) has been established in Western population, little is known about the risk in Chinese people with RA. Our objective was to estimate the risk of CVD in Chinese people with RA using hospital medical records data. Methods The inpatients medical record database 2005‐2015 of Sichuan provincial people’s hospital was examined. All individuals with a primary diagnosis of RA were included as cases, and those of osteoarthritis (OA) were included as controls, which consisted of the unmatched dataset. Then, RA cases and OA controls were matched by sex and age at 1:1 ratio, forming the matched dataset. The morbidity of CVD (including ischemia heart disease (IHD), congestive heart failure (CHF), et al), stroke and arthrosclerosis were extracted from the database, so as the demographic data and comorbidities related to CVD. Multiple logistic regression analysis was used to estimate the risk of CVD in RA adjusted for demographics and comorbidities using the unmatched dataset. Sensitivity analysis was conducted 1) considering interaction terms between RA and comorbidities, and 2) using multivariable conditional logistic regression for the matched dataset. Results: The unmatched data set comprised of 1824RA cases and 1995 OA controls and the matched dataset comprised of 1022 pairs of sex and age matched RA and OA patients. RA exhibited increased odds of prevalent CVD compared with OA, and the adjusted ORs (95%CIs) for CVD, stroke, IHD, CHF, and atherosclerosis were1.86(1.42‐2.43), 1.11(0.71‐1.74), 1.47(0.97‐2.24), 2.09(1.03‐4.22), and 2.49 (1.97‐3.13), respectively, and was 2.26 (1.29‐3.96) for IHD further adjusted for interaction term. The matched dataset analysis found similar results. Conclusions: Chinese people with RA were approximated 2 times more 1 likely to have CVD, IHD, CHF and atherosclerosis compared with those with OA. The findings justified the need of further longitudinal study to establish the causal‐relationship between RA and CVD and to estimate the precise risk in this population

Risk of cardiovascular disease in Chinese patients with rheumatoid arthritis: a cross sectional study based on hospital medical records in 10 years

Objective: Though the risk of cardiovascular disease (CVD) in rheumatoid arthritis (RA) has been established in Western population, little is known about the risk in Chinese people with RA. Our objective was to estimate the risk of CVD in Chinese people with RA using hospital medical records data.MethodsThe inpatients medical record database 2005‐2015 of Sichuan provincial people’s hospital was examined. All individuals with a primary diagnosis of RA were included as cases, and those of osteoarthritis (OA) were included as controls, which consisted of the unmatched dataset. Then, RA cases and OA controls were matched by sex and age at 1:1 ratio, forming the matched dataset. The morbidity of CVD (including ischemia heart disease (IHD), congestive heart failure (CHF), et al), stroke and arthrosclerosis were extracted from the database, so as the demographic data and comorbidities related to CVD. Multiple logistic regression analysis was used to estimate the risk of CVD in RA adjusted for demographics and comorbidities using the unmatched dataset. Sensitivity analysis was conducted 1) considering interaction terms between RA and comorbidities, and 2) using multivariable conditional logistic regression for the matched dataset.Results: The unmatched data set comprised of 1824RA cases and 1995 OA controls and the matched dataset comprised of 1022 pairs of sex and age matched RA and OA patients. RA exhibited increased odds of prevalent CVD compared with OA, and the adjusted ORs (95%CIs) for CVD, stroke, IHD, CHF, and atherosclerosis were1.86(1.42‐2.43), 1.11(0.71‐1.74), 1.47(0.97‐2.24), 2.09(1.03‐4.22), and 2.49 (1.97‐3.13), respectively, and was 2.26 (1.29‐3.96) for IHD further adjusted for interaction term. The matched dataset analysis found similar results.Conclusions: Chinese people with RA were approximated 2 times more 1 likely to have CVD, IHD, CHF and atherosclerosis compared with those with OA. The findings justified the need of further longitudinal study to establish the causal‐relationship between RA and CVD and to estimate the precise risk in this population

Glucose promotes cell proliferation, glucose uptake and invasion in endometrial cancer cells via AMPK/mTOR/S6 and MAPK signaling

Obesity and diabetes are well-known risk factors for the development of endometrial cancer. A high rate of aerobic glycolysis represents a key mechanism by which endometrial cancer cells consume glucose as its primary energy source. The up-regulated glycolytic pathway is a common therapeutic target whose inhibition has implications for anti-tumor activity in cancer cells. This study aimed to investigate the effect of various concentrations of glucose on cell proliferation in endometrial cancer

Knockdown of hTERT and Treatment with BIBR1532 Inhibit Cell Proliferation and Invasion in Endometrial Cancer Cells

Telomerase activity and expression of the catalytic protein hTERT are associated with cell proliferation and advanced stage in endometrial cancer. Our objective was to evaluate the effect of inhibition of hTERT by siRNA and BIBR1532 on cell growth, apoptosis and invasion in endometrial cancer cells. Knockdown of hTERT or treatment of the cells with BIBR1532 decreased telomerase activity, inhibited cell proliferation, induced apoptosis, and reduced cell invasion in Ishikawa and ECC-1 cells. Either hTERT siRNA or BIBR1532 in combination with paclitaxel promoted a synergistic inhibitory effect on cell growth through induction of Annexin V expression and a remarkable reduction in cell invasion through reduction of protein expression of MMP9, MMP2, and MMP3. Increased telomerase activity and hTERT protein expression by transfections enhanced the protein expression of MMPs and increased the cell invasion ability. BIBR1532 significantly antagonized cell invasion induced by increased hTERT expression. These findings suggest that telomerase and hTERT facilitate cell invasion via MMP family in human endometrial cancer cells

<html>Increased efficacy of metformin corresponds to differential metabolic effects in the ovarian tumors from obese <i>versus</i> lean mice</html>

Obesity is a significant risk factor for ovarian cancer (OC) and associated with worse outcomes for this disease. We assessed the anti-tumorigenic effects of metformin in human OC cell lines and a genetically engineered mouse model of high grade serous OC under obese and lean conditions. Metformin potently inhibited growth in a dose-dependent manner in all four human OC cell lines through AMPK/mTOR pathways. Treatment with metformin resulted in G1 arrest, induction of apoptosis, reduction of invasion and decreased hTERT expression. In the K18-gT121+/-; p53fl/fl; Brca1fl/fl (KpB) mouse model, metformin inhibited tumor growth in both lean and obese mice. However, in the obese mice, metformin decreased tumor growth by 60%, whereas tumor growth was only decreased by 32% in the lean mice (p=0.003) compared to vehicle-treated mice. The ovarian tumors from obese mice had evidence of impaired mitochondrial complex 2 function and energy supplied by omega fatty acid oxidation rather than glycolysis as compared to lean mice, as assessed by metabolomic profiling. The improved efficacy of metformin in obesity corresponded with inhibition of mitochondrial complex 1 and fatty acid oxidation, and stimulation of glycolysis in only the OCs of obese versus lean mice. In conclusion, metformin had anti-tumorigenic effects in OC cell lines and the KpB OC pre-clinical mouse model, with increased efficacy in obese versus lean mice. Detected metabolic changes may underlie why ovarian tumors in obese mice have heightened susceptibility to metformin

Neuropeptidomic Components Generated by Proteomic Functions in Secretory Vesicles for Cell–Cell Communication

Diverse neuropeptides participate in cell–cell communication to coordinate neuronal and endocrine regulation of physiological processes in health and disease. Neuropeptides are short peptides ranging in length from ~3 to 40 amino acid residues that are involved in biological functions of pain, stress, obesity, hypertension, mental disorders, cancer, and numerous health conditions. The unique neuropeptide sequences define their specific biological actions. Significantly, this review article discusses how the neuropeptide field is at the crest of expanding knowledge gained from mass-spectrometry-based neuropeptidomic studies, combined with proteomic analyses for understanding the biosynthesis of neuropeptidomes. The ongoing expansion in neuropeptide diversity lies in the unbiased and global mass-spectrometry-based approaches for identification and quantitation of peptides. Current mass spectrometry technology allows definition of neuropeptide amino acid sequence structures, profiling of multiple neuropeptides in normal and disease conditions, and quantitative peptide measures in biomarker applications to monitor therapeutic drug efficacies. Complementary proteomic studies of neuropeptide secretory vesicles provide valuable insight into the protein processes utilized for neuropeptide production, storage, and secretion. Furthermore, ongoing research in developing new computational tools will facilitate advancements in mass-spectrometry-based identification of small peptides. Knowledge of the entire repertoire of neuropeptides that regulate physiological systems will provide novel insight into regulatory mechanisms in health, disease, and therapeutics