Discovery of clinically relevant fusions in pediatric cancer

Background Pediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions. Results Our Ensemble Fusion (EnFusion) approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and Amazon Web Services (AWS) serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a “known fusion list” prevents failure to report known pathogenic events. We have employed the EnFusion pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient’s medical record, both known and novel fusions provided medically meaningful information. Conclusions The EnFusion pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

Optimal Sizing and Assessment of a Renewable Rich Standalone Hybrid Microgrid Considering Conventional Dispatch Methodologies

This paper presents an evaluation of the optimized design of an off-grid hybrid microgrid for alternative load dispatch algorithms with the determination of the most optimal sizing of each equipment, analyzing the voltage and frequency outputs and various costs of the proposed microgrids. Kushighat and Rajendro Bazar, two geographical locations in Bangladesh have been taken as test sites. The proposed microgrids incorporating diesel generator, renewable resources, storage device, and 23.31 kW of demand have been optimized for five conventional load dispatch methodologies: HOMER predictive dispatch, Load Following, Generator Order, Cycle Charging, and Combined Dispatch to reduce the system’s net present cost, gas discharge and cost of energy. HOMER (Hybrid Optimization of Multiple Electric Renewables) software has been used for the analysis to determine the optimal sizes and costing and the voltage-frequency performances of the microgrids are analyzed using MATLAB/Simulink. From our analysis, load following is determined as the superior approach with a minimum operating cost of 3738 USD, net present cost of 152,023 USD, CO2 discharge of 3375 kg/year and cost of energy of 0.208 USD /kWh along with a steady voltage-frequency output. Combined dispatch is determined as the worst strategy for the proposed microgrids with the highest energy cost of 0.532 USD /kWh, the operational cost of 15,394 USD, net present cost of 415,030 USD, and high CO2 discharge. At the end of this work, a comparative analysis between the proposed design, another hybrid, and traditional generation plant is also presented. The findings of this work will be appropriate for any location with an identical demand profile and meteorological estate.

Post-operative Pain Outcomes of Laparoscopic Ventral Hernia Repair (LVHR): An eight-year experience

Objective:To evaluate post-operative pain, recovery time and standard of living in patients undergoing LVHR in detail. Study design and Setting: This prospective cohort study was conducted at a tertiary care hospital of Karachi, Pakistan,after getting approval from the “National Medical Centre EthicalReview Board”, from January 2011 to December 2019, Methodology: Total n= 577 patients undergoing standard LVHR procedure (defect closed with non-absorbable monofilamentsuture, reinforced with intra-abdominal dual layer mesh, anchored with non-absorbable tacks & sutures). Patient demographics,perioperative & postoperative findings and post-operative pain analysis were investigated and presented as descriptivestatistics. Follow-up was carried out at 1stweek, 2ndweek, 3rdmonthly, 6 monthly and 12 monthly post-operative appointments. Results: During the study period of nine years (January 2011 to December 2019), 577 patients (primary ventral hernia n=232, recurrent ventral hernian=188 patients, incisional hernian=157) underwent LVHR. Mean post-operative hospitalstay was 1.53 ± 1.8 days. Mean post-operative pain assessment onvisual analog scale (VAS) after surgery (0-3days) wasreported to be 38.5±29 by 65 patients out of 577 (11.26%), which significantly decreased at the end of 1st week to 27.9 ± 25.6. Only 3 patients (0.51%) reported chronic pain during the span of 3-6 months. Conclusion: LVHR was associated with considerably less post-operative pain, shorter hospital stay and reduced time of convalescence. It is demonstrated that LVHR to be a safe and superior approach for the repair ventral hernias

Predictors and outcomes of TLE via femoral vein bailout

Background Transvenous Lead Extraction (TLE) is usually performed via a superior approach. Predictors and outcomes of TLE via femoral vein bailout are ill defined. Methods A single tertiary center cohort of 426 consecutive patients who underwent TLE between May 2010 and February 2020 were analyzed. Venography was routinely performed before system upgrade to identify occluded veins. Patients were divided into 2 groups on the basis of the need for femoral bailout extraction. Predictors for TLE requiring femoral bailout and outcomes were analysed. Results A total of 928 leads were extracted and femoral bailout approach was needed in 49 patients (11.5%). A higher proportion of RV leads required femoral bailout approach [51/499 (10.2%)]. Femoral bailout was more common among younger patients, longer lead dwell time, more pocket entries, higher number of extracted leads, presence of abandoned leads [14/49 (28.6%)], and among patients with occluded veins [10/22 (45.5%)]. The presence of abandoned leads, vascular occlusion and age remained a significant predictor for femoral bailout in multivariate analysis. Femoral bailout TLE resulted in a relatively higher rate of major complications [5/49 (10.2%) vs 9/377 (2.4%); p=0.02) but had no related intra-procedural mortality (0/3) and no additional 30 day mortality [2/49 (4.1%) vs 33/377 (8.8%); p=0.4]. Conclusion TLE of abandoned leads, occluded veins and younger age were found to be predictors of femoral bailout requirement. Despite higher rates of major complications in femoral TLE bailout this did not result in increased mortality. Venography before TLE should be considered for procedure planning. FUNDunding Acknowledgement Type of funding sources: None.

Customer Behavior Analysis by Intuitionistic Fuzzy Segmentation: Comparison of Two Major Cities in Turkey

The vast quantity of customer data and its ubiquity, as well as the inabilities of conventional segmentation tools, have diverted researchers in search of powerful segmentation techniques for generating managerially meaningful information. Due to its noteworthy practical use, soft computing-based techniques, especially fuzzy clustering, can be considered one of those contemporary approaches. Although there have been various fuzzy-based clustering applications in segmentation, intuitionistic fuzzy sets that have the complimentary feature have appeared in limited studies, especially in a comparative context. Therefore, this study extends the current body of the pertaining literature by providing a comparative assessment of intuitionistic fuzzy clustering. The comparison was carried out with two other well-known segmentation techniques, [Formula: see text]-means and fuzzy [Formula: see text]-means, based on transaction data that belong to Turkey’s two major cities. Over 10,000 records of customers’ data were processed for segmentation purposes, and the comparative approaches were presented. According to the results, the intuitionistic fuzzy clustering approach outperformed the other methods in terms of the clustering efficiency index being utilized. The validity of the segmentation structure obtained by the superior approach was ensured via nonsegmentation variables. The comparative assessment and the potential managerial implications could be considered as a contribution to the corresponding literature. This study also compares the effects of the different parameter values used in the proposed model.

INFLUENCE OF SELECTED MACROECONOMIC INDICATORS ON EMPLOYEE MOTIVATION

Motivation is considered one of the most important prerequisites for the success and effectiveness of the resulting performances. Usually, we meet only with a perspective of employee motivation from inside the company. However, the external environment, i.e. macro-environment, also influences the motivation of employees. We decided to focus on exploring how macroeconomic indicators evolution affects employee motivation. By means of the research conducted in Slovakia during the period from 2008 to 2019 on a sample of more than 30,000 respondents, we define the dependence of selected macroeconomic indicators and employee motivation. The research focuses on the analysis of average annual wage and household debt influence on the most important employees’ motivational factors. Based on our findings, we can state that macroeconomic indicators affect the importance of motivational factors in Slovakia. Especially, the average annual wage strongly influences the six motivational factors (communication at the workplace, duties and type of work, working hours, working environment, superior approach, psychological burden). The results of the research also show that the seven motivational factors (atmosphere at the workplace, good team, communication at the workplace, working hours, working environment, superior approach, psychological burden) strongly depend on the macroeconomic indicator of household debt. Therefore, when creating incentive programs, business managers in Slovakia should take into account not only the effects of the company’s microenvironment on motivation but also the effects of the macro-environment and thus macroeconomic changes in the state. The role of a manager is to keep balance between external environment influence on employee motivation and internal actions. The paper presents inspiring ideas in a field of employee motivation and the influence of external environment on motivation.

Novel Biomimetic Human TLR2-Derived Peptides for Potential Targeting of Lipoteichoic Acid: An in Silico Assessment

Antimicrobial resistance is one of the most significant threats to health and economy around the globe and has been compounded by the emergence of COVID-19, raising important consequences for antimicrobial resistance development. Contrary to conventional targeting approaches, the use of biomimetic application via nanoparticles for enhanced cellular targeting, cell penetration and localized antibiotic delivery has been highlighted as a superior approach to identify novel targeting ligands for combatting antimicrobial resistance. Gram-positive bacterial cell walls contain lipoteichoic acid (LTA), which binds specifically to Toll-like receptor 2 (TLR2) on human macrophages. This phenomenon has the potential to be exploited for the design of biomimetic peptides for antibacterial application. In this study, we have derived peptides from sequences present in human TLR2 that bind to LTA with high affinity. In silico approaches including molecular modelling, molecular docking, molecular dynamics, and thermodynamics have enabled the identification of these crucial binding amino acids, the design of four novel biomimetic TLR2-derived peptides and their LTA binding potential. The outcomes of this study have revealed that one of these novel peptides binds to LTA more strongly and stably than the other three peptides and has the potential to enhance LTA targeting and bacterial cell penetration.

Lentiviral Vectors Delivered with Biomaterials as Therapeutics for Spinal Cord Injury

Spinal cord injury (SCI) is a devastating trauma that can cause permanent disability, life-long chronic issues for sufferers and is a big socioeconomic burden. Regenerative medicine aims to overcome injury caused deficits and restore function after SCI through gene therapy and tissue engineering approaches. SCI has a multifaceted pathophysiology. Due to this, producing therapies that target multiple different cellular and molecular mechanisms might prove to be a superior approach in attempts at regeneration. Both biomaterials and nucleic acid delivery via lentiviral vectors (LVs) have proven to promote repair and restoration of function post SCI in animal models. Studies indicate that a combination of biomaterials and LVs is more effective than either approach alone. This review presents studies supporting the use of LVs and LVs delivered with biomaterials in therapies for SCI and summarises methods to combine LVs with biomaterials for SCI treatment. By summarising this knowledge this review aims to demonstrate how LV delivery with biomaterials can augment/compliment both LV and biomaterial therapeutic effects in SCI.