Tourism industry and employment generation in emerging seven economies: evidence from novel panel methods

To analyze E-7 economies, the authors employ panel data and relevant panel data econometrics approaches for long-run relationships Mean group, fully modified and dynamic OLS (MG, FMOLS, DOLS) to monitor changes over time between variables, which is important in actual studies. The models’ primary findings are as follows: The panel cointegration tests confirm log-run associations among the targeted variables. International tourism has the largest influence on creating direct jobs in the tourist industry. The control variables like FDI and TI increase employment opportunities in the targeted economies. Furthermore, the results confirm that total natural resources reduce employment services in the E-7 economies. Other factors that might affect the performance of the tourist activity are not included in the model. Furthermore, given the availability of official and consistent data, it only includes what has been recorded up to 2020; our target was 2022, but due to data limitation, it covers 2020. The objective is to assess both the significance of tourist-related activities in creating jobs and the effect of tourism on country-level factors where public policy may influence economic activity

Genome mining for anti-CRISPR operons using machine learning

Motivation: Encoded by (pro-)viruses, anti-CRISPR (Acr) proteins inhibit the CRISPR-Cas immune system of their prokaryotic hosts. As a result, Acr proteins can be employed to develop more controllable CRISPR-Cas genome editing tools. Recent studies revealed that known acr genes often coexist with other acr genes and with phage structural genes within the same operon. For example, we found that 47 of 98 known acr genes (or their homologs) co-exist in the same operons. None of the current Acr prediction tools have considered this important genomic context feature. We have developed a new software tool AOminer to facilitate the improved discovery of new Acrs by fully exploiting the genomic context of known acr genes and their homologs. Results: AOminer is the first machine learning based tool focused on the discovery of Acr operons (AOs). A two-state HMM (hidden Markov model) was trained to learn the conserved genomic context of operons that contain known acr genes or their homologs, and the learnt features could distinguish AOs and non-AOs. AOminer allows automated mining for potential AOs from query genomes or operons. AOminer outperformed all existing Acr prediction tools with an accuracy¼0.85. AOminer will facilitate the discovery of novel anti-CRISPR operons

Identification of multi-drug resistant genes in P. aeruginosa isolates from patients under mechanical ventilation and respiratory support in an intensive care unit

Purpose: To determine multi-drug resistant (MDR) and metallo β-lactamase (MBL)-resistant genes from Pseudomonas aeruginosa isolated from intensive care unit (ICU) patients under mechanical ventilation and respiratory support.Methods: P. aeruginosa was isolated from 387 purulent tracheobronchial secretions collected from ICU patients who were intubated and mechanically ventilated for at least 48 h. Antibiotic resistance was determined by minimum inhibitory concentration (MIC) assay while MDR genes, viz, blaTEM, blaOXA, blaVIM, blaCTX-M-15 were determined by polymerase chain reaction (PCR).Results: A total of 144 (37.2 %) P. aeruginosa were isolated from the purulent tracheobronchial secretions. A majority of the isolates (51.4 %) were resistant to gentamicin. Meropenem-gentamicin was the predominant (35.4 %) resistant combination. Out of the 144 isolates, 102 (70.8 %) were positive for blaTEM gene, 51 (35.4 %) for were positive for blaOXA gene, 22 (15.3 %) were positive for blaVIM gene, while 19 (13.2 %) were positive for blaCTX-M gene.Conclusion: The high prevalence of MDR P. aeruginosa indicates the need for continued monitoring of MDR P. aeruginosa especially in ICU patients who are under mechanical respiratory support.Keywords: Multi-drug resistance genes, Mechanical ventilator, Respiratory support, Pseudomonas aeruginos

Retinol binding protein 4 promotes hyperinsulinism-induced proliferation of rat aortic smooth muscle cells

Recent studies have suggested that retinol binding protein 4 (RBP4), an adipocytokine related to insulin resistance (IR), may play an important role in the development of atherosclerosis and cardiovascular diseases (CVD). Abnormal proliferation and migration of vascular smooth muscle cells (VSMCs) is one of the most common causes of atherosclerosis. Hyperinsulinism promotes proliferation of VSMCs through the MAPK pathway. However, whether RBP4 is involved in insulin-induced proliferation of VSMCs leading to atherosclerosis remains unclear. In the present study, we evaluated the role of RBP4 and the potential relevance of signaling pathways in this process. Different concentrations of RBP4 (1 and 4 μg/ml) were added to rat aortic smooth muscle cells (RASMCs) during insulin-induced proliferation. The levels of cell growth signaling pathway proteins ERK1/2, p-ERK1/2, JAK2, p-JAK2, STAT3 and p-STAT3 were assessed by western blotting in order to identify the pathway(s) that are activated during insulin-induced proliferation. The specific inhibitors of ERK1/2 (PD98059) and JAK2 (AG490) were used to confirm our findings. Insulin induced proliferation of RASMCs in a concentration- and time-dependent manner, and increased the expression of ERK1/2, p-ERK1/2, JAK2, p-JAK2, STAT3 and p-STAT3 in a time-dependent manner. RBP4 enhanced insulin-induced proliferation of RASMCs and expression of p-ERK1/2 and p-JAK2. RBP4-induced proliferation of RASMCs was reduced by the ERK1/2 inhibitor, while it was unaffected by the JAK2 inhibitor. These results suggest that RBP4 mediates VSMC proliferation induced by insulin via activation of the MAPK pathway, and highlight RBP4 as a modulator of atherosclerosis in hyperinsulinemia, therby enhancing our understanding on a number of unexpected aspects of CVD

Expression and aberrant promoter methylation of Wnt inhibitory factor-1 in human astrocytomas

<p>Abstract</p> <p>Background</p> <p>Wnt inhibitory factor-1(WIF-1) acts as a Wnt-antagonists and tumor suppressor, but hypermethylation of WIF-1 gene promoter and low expression activate Wnt signaling aberrantly and induce the development of various human tumors. With this work we intended to investigate the expression and promoter methylation status of WIF-1 gene in human astrocytomas.</p> <p>Methods</p> <p>The tissue samples consisted of 53 astrocytomas and 6 normal brain tissues. The expression levels of WIF-1 were determined by immunohistochemistry and semiquantitative RT-PCR. The results were analyzed in correlation with clinicopathological data. Methylation status of WIF-1 gene promoter was investigated using methylation specific PCR. The relationship between methylation and expression of the genes was analyzed.</p> <p>Results</p> <p>The average expression levels of WIF-1 protein and mRNA in astrocytomas were decreased significantly compared with normal control tissues. The protein and mRNA expression of WIF-1 gene in astrocytomas was decreased with the increase of pathological grade. Furthermore, WIF-1 promoter methylation was observed by MS-PCR in astrocytomas which showed significant reduction of WIF-1 expression. The WIF-1 promoter hypermethylation was associated with reduced expression of WIF-1 expression.</p> <p>Conclusion</p> <p>Our results demonstrate that the WIF-1 gene is frequently down-regulated or silenced in astrocytomas by aberrant promoter methylation. This may be an important mechanism in astrocytoma carcinogenesis.</p

Expression Patterns of ABA and GA Metabolism Genes and Hormone Levels during Rice Seed Development and Imbibition: A Comparison of Dormant and Non-Dormant Rice Cultivars

Seed dormancy is an important agronomic trait in cereals. Using deep dormant (N22), medium dormant (ZH11), and non-dormant (G46B) rice cultivars, we correlated seed dormancy phenotypes with abscisic acid (ABA) and gibberellin (GA) metabolism gene expression profiles and phytohormone levels during seed development and imbibition. A time course analysis of ABA and GA content during seed development showed that N22 had a high ABA level at early and middle seed developmental stages, while at late developmental stage it declined to the level of ZH11; however, its ABA/GA ratio maintained at a high level throughout seed development. By contrast, G46B had the lowest ABA content during seed development though at early developmental stage its ABA level was close to that of ZH11, and its ABA/GA ratio peaked at late developmental stage that was at the same level of ZH11. Compared with N22 and G46B, ZH11 had an even and medium ABA level during seed development and its ABA/GA ratio peaked at the middle developmental stage. Moreover, the seed development time-point having high ABA/GA ratio also had relatively high transcript levels for key genes in ABA and GA metabolism pathways across three cultivars. These indicated that the embryo-imposed dormancy has been induced before the late developmental stage and is determined by ABA/GA ratio. A similar analysis during seed imbibition showed that ABA was synthesized in different degrees for the three cultivars. In addition, water uptake assay for intact mature seeds suggested that water could permeate through husk barrier into seed embryo for all three cultivars; however, all three cultivars showed distinct colors by vanillin-staining indicative of the existence of flavans in their husks, which are dormancy inhibition compounds responsible for the husk-imposed dormancy

A Novel Fluorogenic Coumarin Substrate for Monitoring Acid Phosphatase Activity at Low pH Environment

This article described the synthesis and application of 6-chloro-8-fluoro-4-methylumbelliferone phosphate (CF-MUP) in analyzing acid phosphatase activity. Compared to the existing MUP, the new coumarin phosphate, CF-MUP, demonstrateed much higher sensitivity and was more robust for detecting the activity of acid phosphatase than the classic substrate 4-methylumbelliferone phosphate (MUP). The product of enzyme reaction, 6-chloro-8-fluoro-4-methylumbelliferone (CF-MU) possesses strong fluorescence at ~450 nm with low pKa (4.7), high fluorescence quantum yield and pH independence in the physiological pH range. This new fluorescence dye, CF-MU, is a convenient tool for assays with buffer pH between 4.5 and 8

Real-time Multi-person Eyeblink Detection in the Wild for Untrimmed Video

Real-time eyeblink detection in the wild can widely serve for fatigue detection, face anti-spoofing, emotion analysis, etc. The existing research efforts generally focus on single-person cases towards trimmed video. However, multi-person scenario within untrimmed videos is also important for practical applications, which has not been well concerned yet. To address this, we shed light on this research field for the first time with essential contributions on dataset, theory, and practices. In particular, a large-scale dataset termed MPEblink that involves 686 untrimmed videos with 8748 eyeblink events is proposed under multi-person conditions. The samples are captured from unconstrained films to reveal "in the wild" characteristics. Meanwhile, a real-time multi-person eyeblink detection method is also proposed. Being different from the existing counterparts, our proposition runs in a one-stage spatio-temporal way with end-to-end learning capacity. Specifically, it simultaneously addresses the sub-tasks of face detection, face tracking, and human instance-level eyeblink detection. This paradigm holds 2 main advantages: (1) eyeblink features can be facilitated via the face's global context (e.g., head pose and illumination condition) with joint optimization and interaction, and (2) addressing these sub-tasks in parallel instead of sequential manner can save time remarkably to meet the real-time running requirement. Experiments on MPEblink verify the essential challenges of real-time multi-person eyeblink detection in the wild for untrimmed video. Our method also outperforms existing approaches by large margins and with a high inference speed.Comment: Accepted by CVPR 202