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The purpose of this study was to compare an oblique bikini-incision via direct anterior approach (BI-DAA) to a conventional posterolateral approach (PLA) during simultaneous bilateral total hip arthroplasty (simBTHA) in terms of early patient outcomes, postoperative functional recovery, and complications. From January 2017 to January 2020, 106 patients receiving simBTHA were enrolled and randomly allocated to the BI-DAA or PLA group. Primary outcomes were measured using hemoglobin (HGB) drop, transfusion rate, the length of stay (LOS), the visual analog scale (VAS) for pain, the Harris hip score, Western Ontario and McMaster Universities Osteoarthritis Index, and the scar cosmesis assessment and rating scale. Secondary outcomes were the operative time, radiographic measurements, including femoral offset, femoral anteversion, stem varus/valgus angle, and leg length discrepancy (LLD). The occurrence of postoperative complications was also recorded. There were no differences in demographic or clinical characteristics before surgery. Compared to the PLA, the patients in the BI-DAA group had lower HGB drop (24.7 ± 13.3 g/L vs. 34.7 ± 16.7, P <.01) and transfusion rates (9/50 vs. 18/50, P =.04) and a shorter LOS (5.12 ± 1.5 vs. 6.40 ± 2.0 days, P <.01) without increasing the operative time (169.7 ± 17.3 vs. 167.5 ± 21.8 min, P =.58). The BI-DAA group yielded a smaller LLD (2.1 ± 2.3 vs. 3.8 ± 3.0 mm, P <.01) and less variability in component orientation than the PLA group (100% vs. 93%, P =.01). As for the scar, the BI-DAA group produced a shorter incision length (9.7 ± 1.6 vs. 10.8 ± 2.0 mm, P <.01) and higher postoperative recovery satisfaction than the PLA group. Furthermore, the BI-DAA group had a reduced VAS score one week after surgery and had better functional recovery in three months postoperatively. The BI-DAA group had a higher incidence of LFCN dysesthesia (12/100 vs. 0/100 thighs, P <.01), while other complications did not differ significantly between the two groups. For simBTHA, the bikini incision offers early recovery, less variance in components orientation, better postoperative outcomes, and scar healing than the PLA. Therefore, the bikini incision could be a safe and feasible option for simBTHA recipients. [ABSTRACT FROM AUTHOR]

Dominance-based neighborhood rough set (DNRS) is capable to give qualitative and quantitative descriptions of the relations between ordered objects. In spite of its effectiveness in feature selection, DNRS ignores the various significance of features. In fact, different features exert different impacts on decision-making. Once we explore these differences in advance, it is easier to find out features with high correlation and dependency. Likewise, it is inevitable that in big-data era the objects may update from time to time, which calls for efficient attribute reduction. However, the existing approaches are inappropriate for the weighted and ordered data. Motivated by these two deficiencies, first, we assign different weights to conditional attributes and establish the weighted dominance-based neighborhood rough set (WDNRS). Then a kind of conditional entropy in matrix form and ensuing updating principles are put forward to evaluate the significance of the attributes. In addition, grounded on the entropy, we come up with the heuristic algorithm and corresponding incremental mechanism when objects increase. Finally, twelve experiments are carried out to verify that it is effective and efficient for the designed method to select features in dynamic datasets. [ABSTRACT FROM AUTHOR]

With the surge in big data, the complexity of synthesizing information from multiple sources has become a critical challenge for feature selection methodologies. Feature selection is the process of reducing the number of attributes in data. Traditional single-source centric approaches are inefficient, requiring extensive preprocessing for multi-source data consolidation prior to feature selection. At the same time, an information fusion method is needed to transform the multi-source information system with selected features into a single-source information system. This paper introduces a novel multi-source information fusion and feature selection approach that seamlessly integrates the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) with a dynamic adaptation mechanism. This method is adept at addressing the complexities introduced by the evolving nature of feature and information source dimensions. The Attribute Evaluation Matrix (AEM) and the Attribute Preference Degree Matrix (APDM) are proposed to systematically assess and rank the significance of attributes within a static decision-making framework. Following this, an information fusion method using the source center is proposed. The dynamic feature selection and information fusion methods are proposed to deal with the condition when number of attributes and samples change. Extensive experimental validation confirms that this method not only reduces the computational overhead associated with multi-source feature selection but also significantly enhances the efficiency as the volume and variety of data sources increase. [ABSTRACT FROM AUTHOR]

Largemouth bass virus (LMBV) causes high transmission efficiency and mortality in freshwater aquaculture industry. However, the host responses to LMBV infection, particularly the molecular mechanisms involved in vivo, remain largely uncertain. Zebrafish has been developed as a powerful model organism for the study of host inflammation and immune response upon pathogen infections. Here, we evaluated the susceptibility of LMBV to zebrafish larvae and investigated the host response upon virus infection using transcriptomic analysis. LMBV replicated well in larvae by inoculation with LMBV via the brain and the duct of Cuvier, but the later showed more severe systemic infection, evidenced by the cumulative mortality, the increased transcriptions of viral core genes, and the presence of m c p positive signal in infected larvae. After inoculation with LMBV via the duct of Cuvier, we observed numerous viral particles in the head and tail regions of infected larvae. Moreover, ROS and TUNEL positive signaling also significantly increased in LMBV infected larvae. Of note, a great deal of neutrophils migrated towards the virus infected sites during LMBV infection. Transcriptomic analysis showed that a total of 1263 genes were up-regulated and 1039 genes were down-regulated in response to LMBV infection. Enrichment analysis indicated that the majority of the enriched KEGG pathways were associated with metabolism, cell death and immune regulation, such as fatty acid metabolism, steroid hormone biosynthesis, PPAR signaling, apoptosis, necroptosis, phagosome, cytokine-cytokine receptor pathway, NOD-like receptor signaling, and toll-like receptor pathway. For instance, cell death related signaling molecules including c a s p 9 , f a s , t n f α and s q s t m 1 were significantly up-regulated, while c a m k 2 a , s e p t 4 b and a k t 1 were down-regulated in response to LMBV infection. Thus, our data firstly established LMBV-infected model in zebrafish larvae which could provide an alternative means for investigation of LMBV-host interaction in vivo , and application for high throughput drug screening in the future. • LMBV replicated well in zebrafish larvae and the inoculation via duct of curvier induced systemic response. • LMBV infection drove the broad migration of neutrophils. • LMBV infection induced apoptosis and ROS generation. • LMBV infection induced the significantly changes of DEGs in pathways related to cell death and innate immune response. [ABSTRACT FROM AUTHOR]