Efficacy and safety of anterior transposition of the ulnar nerve for distal humerus fractures: A systematic review and meta-analysis

BackgroundThis systematic review and meta-analysis was performed to summarize available evidence of anterior transposition of the ulnar nerve for patients with distal humerus fractures.Materials and MethodsThe databases were searched from PubMed, Cochrane, Embase, Scopus, Web of Science, Chinese National Knowledge Infrastructure (CNKI), Chongqing VIP Database (VIP), and Wan Fang Database up to June 2022. The clinical outcome included operation time, fracture healing time, hospital stays, elbow joint function, and ulnar neuritis rate. Statistical analysis was performed with Review Manager 5.3 (Cochrane Collaboration).ResultsA total of 17 studies were included (8 RCTs and 9 retrospective studies), and 1280 patients were analyzed. The results of this meta-analysis showed anterior transposition group had longer operation time (MD = 20.35 min, 95%CI: 12.56–28.14, P < 0.00001). There was no significant difference in fracture healing time (SMD = −0.50, 95%CI: −1.50–0.50, P = 0.33), hospital stays (MD = −1.23 days, 95%CI: −2.72–−0.27, P = 0.11), blood loss (MD = 2.66 ml, 95%CI: −2.45–7.76, P = 0.31), and ulnar neuritis rate (OR = 1.23, 95%CI: 0.63–2.42, P = 0.54) between two groups. Finally, elbow joint motion, elbow joint function, fracture nonunion, and post-operative infection (P > 0.05) between two groups were not significantly statistic difference.ConclusionThis meta-analysis showed that anterior transposition group is not superior to non-transposition group for patients with distal humerus fractures without ulnar nerve injury. On the contrary, non-transposition group have shorter operation time than that of anterior transposition group. Non-transposition group did not increase the post-operative ulnar neuritis rate. Therefore, both anterior transposition group and non- transposition group are the treatment options for patients with distal humerus fractures without ulnar nerve injury. Besides, these findings need to be further verified by multi-center, double-blind, and large sample RCTs

Coping with Stress: How Hotel Employees Fight to Work

Working in hospitality establishments involves high levels of stress, partially due to the anti-social shift rotations and the high levels of emotional labor needed. Unmanaged stress often leads to psychological and even physical diseases, which harm both individual career development and hotel operations. Thus, it is of great importance to identify effective stress coping strategies to maintain a sustainable hotel work force. Stress coping behavior varies among different demographics and generations. Commonly used stress coping scales were established almost 40 years ago, and under the context of daily events, and may not be applicable in today’s hospitality context. Thus, this study was designed to investigate effective stress coping strategies among today’s hotel employees. Data were collected from 470 hotel employees in 37 cities in China. The results identified 12 effective coping strategies that fell under three dimensions: distraction, sharing, and self-indulgence. The findings contribute to scholarly knowledge of stress coping. Managerial implications are also discussed

Evolution of the Construction Industry in China from the Perspectives of the Driving and Driven Ability

The construction industry has been developing in recent years, facilitating economic development in China. However, the industry’s development has been confronted by a series of challenges. Exploring the characteristics of the influences of power and the association structure and their level of correlation in the construction industry is important to improve the understanding of the status and development of laws, to optimize industrial structure, and to improve the efficiency of the construction industry—factors that are fundamental to the realization of an optimized, upgraded construction industry. Therefore, the total consumption coefficient and the total distribution coefficient were calculated to reveal the influencing power of the construction industry. Based on the total consumption coefficient and the total distribution coefficient, the driven coefficient and driving coefficient are used to reflect the general effect on the entire industry network. The driven and driving networks were constructed using the total consumption coefficient and the total distribution coefficient to reveal the critical positions of the networks. The results show that the construction industry has significant driven and driving effects on other industries, which facilitate the improvement of the entire economic industry. However, an obvious gap exists between the driven ability and the driving ability as measured by the complex network. The point degree, betweenness degree, and subgroup cohesive characteristics show that the effect of the driven ability is much greater than that of the driving ability for the construction industry in 30 provinces. The findings provide information for policymaking related to the sustainable development of the construction industry in China

Mismatch in Urban Construction Land Use and Economic Growth: Empirical Evidence from China

Seeking land use development strategies is an effective policy tool to support economic development, especially in developing countries. Previous studies evidence the indispensable role of urban construction land use (UCLU) in regional economic development. However, neglecting the two-stage characteristic and mismatch of UCLU could misinterpret the strategy. This study, considering a two-stage characteristic, aims to explore how land use development strategy affects economic development. First, we create a measure for UCLU mismatch. Second, using both linear and nonlinear models, we explore the possible relationship between the land use strategy and economic development. Subsequently, robustness and the potential path-dependent reinforcement loop (PDRL) are discussed further. Finally, the fundamental channels are investigated in the mechanism analysis section. The results confirm that temporary positive effects stimulate economic development, whereas permanent potential negative effects undermine robust economic development. In addition, the PDRL shows that irrational adoption of the strategy would mean succumbing to low- and medium-industries. We also find that land and capital demonstrate exogenous properties that function as visible hands, with economic regulation exploring UCLU mismatches and misallocation of resources. However, the overuse of these two policies could lead to an unhealthy cycle of mutually reinforcing adverse effects. Based on these findings, we propose policy recommendations to support the rational use of this strategy

Identifying MicroRNA Markers That Predict COVID-19 Severity Using Machine Learning Methods

Individuals with the SARS-CoV-2 infection may experience a wide range of symptoms, from being asymptomatic to having a mild fever and cough to a severe respiratory impairment that results in death. MicroRNA (miRNA), which plays a role in the antiviral effects of SARS-CoV-2 infection, has the potential to be used as a novel marker to distinguish between patients who have various COVID-19 clinical severities. In the current study, the existing blood expression profiles reported in two previous studies were combined for deep analyses. The final profiles contained 1444 miRNAs in 375 patients from six categories, which were as follows: 30 patients with mild COVID-19 symptoms, 81 patients with moderate COVID-19 symptoms, 30 non-COVID-19 patients with mild symptoms, 137 patients with severe COVID-19 symptoms, 31 non-COVID-19 patients with severe symptoms, and 66 healthy controls. An efficient computational framework containing four feature selection methods (LASSO, LightGBM, MCFS, and mRMR) and four classification algorithms (DT, KNN, RF, and SVM) was designed to screen clinical miRNA markers, and a high-precision RF model with a 0.780 weighted F1 was constructed. Some miRNAs, including miR-24-3p, whose differential expression was discovered in patients with acute lung injury complications brought on by severe COVID-19, and miR-148a-3p, differentially expressed against SARS-CoV-2 structural proteins, were identified, thereby suggesting the effectiveness and accuracy of our framework. Meanwhile, we extracted classification rules based on the DT model for the quantitative representation of the role of miRNA expression in differentiating COVID-19 patients with different severities. The search for novel biomarkers that could predict the severity of the disease could aid in the clinical diagnosis of COVID-19 and in exploring the specific mechanisms of the complications caused by SARS-CoV-2 infection. Moreover, new therapeutic targets for the disease may be found

Identification of Urban Functional Area by Using Multisource Geographic Data: A Case Study of Zhengzhou, China

The rational allocation of functional areas is the foundation for addressing the sustainable development of cities. Efficient and accurate identification methods of urban functional areas are of great significance to the adjustment and testing of urban planning and industrial layout optimization. Firstly, by employing multisource geographic data, an identification method of urban functional areas was developed. A quantitative measurement approach of the urban functional area was then established considering the comprehensive effects of human-land, space-time, and thematic information to present the covering area of ground objects, public awareness, and empirical research. Finally, the Zhengzhou city, which locates in Henan province of central China, was used to test the method. The results show that the developed method is efficient, accurate, and universal and can identify urban functional areas quickly and accurately. We found that the overall distribution of Zhengzhou’s functional areas presents a spatial pattern of single and multimixed coordinated development. The city’s commercial functional areas and commercial-based mixed functional areas are located in the city’s central area. The green square’s function area occupies relatively low and is mainly distributed in the city’s fringe

Identification of Smoking-Associated Transcriptome Aberration in Blood with Machine Learning Methods

Long-term cigarette smoking causes various human diseases, including respiratory disease, cancer, and gastrointestinal (GI) disorders. Alterations in gene expression and variable splicing processes induced by smoking are associated with the development of diseases. This study applied advanced machine learning methods to identify the isoforms with important roles in distinguishing smokers from former smokers based on the expression profile of isoforms from current and former smokers collected in one previous study. These isoforms were deemed as features, which were first analyzed by the Boruta to select features highly correlated with the target variables. Then, the selected features were evaluated by four feature ranking algorithms, resulting in four feature lists. The incremental feature selection method was applied to each list for obtaining the optimal feature subsets and building high-performance classification models. Furthermore, a series of classification rules were accessed by decision tree with the highest performance. Eventually, the rationality of the mined isoforms (features) and classification rules was verified by reviewing previous research. Features such as isoforms ENST00000464835 (expressed by LRRN3), ENST00000622663 (expressed by SASH1), and ENST00000284311 (expressed by GPR15), and pathways (cytotoxicity mediated by natural killer cell and cytokine–cytokine receptor interaction) revealed by the enrichment analysis, were highly relevant to smoking response, suggesting the robustness of our analysis pipeline

Uniform Circular-Array-Based Borehole Pulsed Eddy-Current System for Asymmetry Defect Inspection in Downhole Casings

The inspection of wellbore casings has been extensively investigated owing to the increasing concern for safety in oil and gas production. However, efficient techniques for inspecting asymmetry defects have not been achieved. In this study, we developed a uniform circular array (UCA) to address the problem of borehole pulsed eddy current (PEC) techniques for asymmetry defect inspection in downhole casings. Based on the borehole PEC system model, the UCA developed with multiple independent probes was designed to achieve asymmetry defect inspection, and the three-dimensional magnetic field data of borehole depths, circumferential azimuths, and sampling times could be obtained. Furthermore, a multichannel data acquisition circuit, which guarantees downhole operation at 150 °C, was developed for the synthesized UCA. Using azimuth dimension information from the synthesized UCA at a certain borehole depth, we obtained an inspection approach for the width and penetration depth of asymmetry defects in the circumferential and radial directions, respectively. Simulations and field experiments were conducted, and the results demonstrate the effectiveness of the proposed method in inspecting asymmetry defects

Uniform Circular-Array-Based Borehole Pulsed Eddy-Current System for Asymmetry Defect Inspection in Downhole Casings

The inspection of wellbore casings has been extensively investigated owing to the increasing concern for safety in oil and gas production. However, efficient techniques for inspecting asymmetry defects have not been achieved. In this study, we developed a uniform circular array (UCA) to address the problem of borehole pulsed eddy current (PEC) techniques for asymmetry defect inspection in downhole casings. Based on the borehole PEC system model, the UCA developed with multiple independent probes was designed to achieve asymmetry defect inspection, and the three-dimensional magnetic field data of borehole depths, circumferential azimuths, and sampling times could be obtained. Furthermore, a multichannel data acquisition circuit, which guarantees downhole operation at 150 °C, was developed for the synthesized UCA. Using azimuth dimension information from the synthesized UCA at a certain borehole depth, we obtained an inspection approach for the width and penetration depth of asymmetry defects in the circumferential and radial directions, respectively. Simulations and field experiments were conducted, and the results demonstrate the effectiveness of the proposed method in inspecting asymmetry defects