Identifying key sectors using regional input-output model at sub-national level

Since key sectors have high backward and forward linkages with rest of the economy, investment in these sectors is expected to maximize the economic growth, which is extensively meaningful in undeveloped or developing countries with limited resources. Besides, it is considerably necessary and helpful to identify key sectors for analyzing the long-term structural change and economic development strategic policy, both at national and regional level. However, identification of the key sectors is somehow difficult to carry out in practice at regional level due to the absence of regional data at hand. In this study, we employ the traditional backward and forward linkages as indicators to identify the key sectors for sub-national regions, where the input-output (IO) tables are unavailable, along with non-survey techniques. The regional IO tables are produced from adjusting national IO tables with several non-survey techniques. To capture the performance of non-survey techniques on recognizing key sectors, then, the estimated regional backward/forward linkages are computed, which are represented by the output multipliers, and compared with the survey based benchmarks through the rank correlation coefficients. A big value of correlation indicates a high capability of the non-survey techniques on the identification of regional key sectors. At last, empirical study is given with Korean 2005 national and regional IO tables

A Study on the Effect of IL-17A on Phenotypic Transformation of Fibroblasts in Bleomycin-Induced Pulmonary Fibrosis in Mice and Its Mechanism

Objective: In this study, lung fibroblasts were cultured and identified in mice lung fiber model with bleomycin. Under the induction of IL-17A, lung fibroblasts were gradually transformed into myofibroblasts in pulmonary fibrosis, and the specific induction effect of IL-17A in pulmonary fibrosis was analyzed, which could provide ideas for the prevention and treatment of clinical pulmonary fibrosis. Methods: To investigate the transcriptional expression of bleomycin-induced fractional pulmonary fibrosis in different pulmonary fibrosis processes. The 14-day mice model was taken as the research object, and the pulmonary fibrosis model was established by induction of myogenesis. After 14 days of modeling, lung tissue was removed, and after centrifugation and repeated adherent treatment, lung fibroblasts could be cultured at the origin. After three generations of culture, the morphological changes of lung fibroblasts could be observed under a microscope. Indirect immunofluorescence was used to establish the expression of vimentin, and IL-17 was used to stimulate primary cultured lung fibroblasts to detect the expression and specific localization of a-SMA in cells. Western blotting was used to stimulate the expression of lung fibroblast protein by IL-17A at different time points. Results: The typical characteristics of primary culture lung fibroblasts were obtained. After purification and culture, lung fibroblasts were obtained in morphology. The morphology of the 3rd and 4th generation cells was relatively uniform, showing long carboxyform. 1-2 nucleoli can be observed by microscope, which have distinct cell boundary and are lined up like fish schools. The results of indirect immunofluorescence showed that the vimentin staining in the third generation cells was positive, and the plasma was dark red. There were collagenous fibrous septa between the cells, which might make them develop into lung fibroblasts. A-SMA immunofluorescence results showed that in the absence of IL-17A induction, A-SMA signal was relatively weak in the lung fibroblasts of the control group and was in the cytoplasm, while after IL-17A induction, A-SMA signal was stronger in the lung fibroblasts of mice and the whole cells presented spindle structure. Western bletting showed that lung fibroblasts were stimulated by IL-17 in the 0h group. Compared with the 1h, 2h, and 4h groups, the expression of A-SMA in lung fibroblasts was significantly increased in the 1h, 2h, and 4h groups. The fibroblasts were very low in the 2h and 4h groups. There was no significant difference in the expression of AS MA signal. Compared with 0h, protein contents of p-IKB-a and p-p65 were higher in lung fibroblasts at 1h, 2h and 4h. Protein expressions of Acti, 1P6, IKB-a and P65 were different in lung fibroblasts, but there was no significant difference. However, there was no significant statistical difference in the expression of these proteins in lung fibroblasts at different times. Conclusion: By differential centrifugation and repeated adhesion, bleomycin-induced lung fibroblasts can be isolated and purified, and more cell production can be obtained. The staining vimentin was strongly positive after identification by indirect immunofluorescence. The stimulation of IL-17A could gradually transform non-fibroblasts into myofibroblasts and play an important role in pulmonary fibrosis. Therefore, through experimental studies, it was found that IL-17A stimulated F-kB signal and then increased the expression of P-IKB-a and P-P65 proteins, and transformed non-phosphorylated proteins into phosphorylated proteins, thus transforming lung fibroblasts into myofibroblasts and playing a role in pulmonary fibrosis

Genetically predicted N-methylhydroxyproline levels mediate the association between naive CD8+ T cells and allergic rhinitis: a mediation Mendelian randomization study

BackgroundAllergic rhinitis (AR), a prevalent chronic inflammatory condition triggered by immunoglobulin E (IgE), involves pivotal roles of immune and metabolic factors in its onset and progression. However, the intricacies and uncertainties in clinical research render current investigations into their interplay somewhat inadequate.ObjectiveTo elucidate the causal relationships between immune cells, metabolites, and AR, we conducted a mediation Mendelian randomization (MR) analysis.MethodsLeveraging comprehensive publicly accessible summary-level data from genome-wide association studies (GWAS), this study employed the two-sample MR research method to investigate causal relationships among 731 immune cell phenotypes, 1400 metabolite levels, and AR. Additionally, employing the mediation MR approach, the study analyzed potential mediated effect of metabolites in the relationships between immune cells and AR. Various sensitivity analysis methods were systematically employed to ensure the robustness of the results.ResultsFollowing false discovery rate (FDR) correction, we identified three immune cell phenotypes as protective factors for AR: Naive CD8br %CD8br (odds ratio (OR): 0.978, 95% CI = 0.966–0.990, P = 4.5×10–4), CD3 on CD39+ activated Treg (OR: 0.947, 95% CI = 0.923–0.972, P = 3×10–5), HVEM on CD45RA- CD4+ (OR: 0.967, 95% CI = 0.948–0.986, P = 4×10–5). Additionally, three metabolite levels were identified as risk factors for AR: N-methylhydroxyproline levels (OR: 1.219, 95% CI = 1.104–1.346, P = 9×10–5), N-acetylneuraminate levels (OR: 1.133, 95% CI = 1.061–1.211, P = 1.7×10–4), 1-stearoyl-2-arachidonoyl-gpc (18:0/20:4) levels (OR: 1.058, 95% CI = 1.029–1.087, P = 5×10–5). Mediation MR analysis indicated a causal relationship between Naive CD8br %CD8br and N-methylhydroxyproline levels, acting as a protective factor (OR: 0.971, 95% CI = 0.950–0.992, P = 8.31×10–3). The mediated effect was -0.00574, accounting for 26.1% of the total effect, with a direct effect of -0.01626. Naive CD8+ T cells exert a protective effect on AR by reducing N-methylhydroxyproline levels.ConclusionOur study, delving into genetic information, has substantiated the intricate connection between immune cell phenotypes and metabolite levels with AR. This reveals a potential pathway to prevent the onset of AR, providing guiding directions for future clinical investigations

Can we reveal the growth potentials with input-output model at sub-national level?

The regional growth potential, which frequently appears in economic analyses, is notoriously difficult to handle in practice. Estimation of growth potentials for development forecasting and strategic planning remains actual and meaningful, which is especially true for long-term predictions of structural shifts in the economy, both at national and regional level. The Regional Input-Output (RIO) model has been a powerful tool in applications of the industrial interdependence, impact analysis and policy strategies. Also the RIO model can be attempted to identify leading industries through linkage effects. The backward and forward linkages for the sectors in a single economy provide a mechanism for identifying key or leading sectors in the economy. In this study, we try to identify the leading industries by the RIO model along with non-survey techniques to explore growth potentials. The estimated multipliers which represent the backward linkage are compared with the survey based benchmarks through the rank correlation coefficients

Identification of multi-fault in rotor-bearing system using spectral kurtosis and EEMD

Condition monitoring and fault diagnosis via vibration signal processing play an important role to avoid serious accidents. Aiming at the complexity of multiple faults in a rotor-bearing system and drawback, the characteristic frequency of relevant fault could not be determined effectively with traditional method. The Spectral Kurtosis (SK) is useful for the bearing fault detection. Nevertheless, the simulation of experiment in this paper shows that the SK is unable to identify multi-fault of rotor-bearing system fully when different faults excite different resonance frequencies. A new multi-fault detection method based on EEMD and spectral kurtosis (SK) is proposed in order to overcoming the shortcoming. The proposed method is applied to multi-faults of rotor imbalance and faulty bearings. The superiority of the proposed method based on spectral kurtosis (SK) and EEMD is demonstrated in extracting fault characteristic information of rotating machinery

Mixed Starts and Uncertain Futures: Case Studies of Three Chinese Agricultural Investments in Zimbabwe

Chinese agricultural investments in Africa have grown significantly in the past two decades, but there remains very little empirical research on the nature of these investments. This paper aims to address this knowledge gap by looking at three different types of Chinese investors in Zimbabwe’s agricultural sector: a National State Owned Enterprise (SOE), a Provincial SOE and a private company. Collectively, their experiences not only challenge the pervasive view that Chinese companies are progressing at unstoppable rates in African markets, but also raise deeper questions about the importance of company structures, financial stability and the environments in which they operate