Antenatal sonographic assessment of cross sectional area of umbilical cord components and its reference value in normal pregnancy

Background: Measuring the cross-sectional area of umbilical components in normal pregnant women helps in assessing the fetal abnormalities. Very few literatures were available on evaluation of reference values of cross sectional areas of umbilical cord components. The present study was conducted with the aim to determine the normal reference values of cross sectional areas of umbilical arteries, umbilical vein and Wharton’s jelly and to correlate them with the gestational age of the fetus.Methods: A cross sectional study was conducted on 300 normal pregnant women at the Department of Radiodiagnosis, Sri Siddhartha Medical College, Tumakuru, Karnataka to assess the reference range of cross sectional areas of umbilical cord arteries, umbilical vein and Wharton’s jelly at different gestational age of the fetus to analyze their growth.Results: A statistically significant correlation was observed between cross sectional areas of umbilical artery and vein and gestational age before and after 34 weeks (p=0.005 and 0.006 respectively) but no significant correlation was noticed with the cross-sectional area of Wharton’s jelly (p=0.088).Conclusions: Cross sectional area measurements of umbilical cord components can be considered as important tools for estimation of fetal growth

Postoperative outcomes in oesophagectomy with trainee involvement

BACKGROUND: The complexity of oesophageal surgery and the significant risk of morbidity necessitates that oesophagectomy is predominantly performed by a consultant surgeon, or a senior trainee under their supervision. The aim of this study was to determine the impact of trainee involvement in oesophagectomy on postoperative outcomes in an international multicentre setting. METHODS: Data from the multicentre Oesophago-Gastric Anastomosis Study Group (OGAA) cohort study were analysed, which comprised prospectively collected data from patients undergoing oesophagectomy for oesophageal cancer between April 2018 and December 2018. Procedures were grouped by the level of trainee involvement, and univariable and multivariable analyses were performed to compare patient outcomes across groups. RESULTS: Of 2232 oesophagectomies from 137 centres in 41 countries, trainees were involved in 29.1 per cent of them (n = 650), performing only the abdominal phase in 230, only the chest and/or neck phases in 130, and all phases in 315 procedures. For procedures with a chest anastomosis, those with trainee involvement had similar 90-day mortality, complication and reoperation rates to consultant-performed oesophagectomies (P = 0.451, P = 0.318, and P = 0.382, respectively), while anastomotic leak rates were significantly lower in the trainee groups (P = 0.030). Procedures with a neck anastomosis had equivalent complication, anastomotic leak, and reoperation rates (P = 0.150, P = 0.430, and P = 0.632, respectively) in trainee-involved versus consultant-performed oesophagectomies, with significantly lower 90-day mortality in the trainee groups (P = 0.005). CONCLUSION: Trainee involvement was not found to be associated with significantly inferior postoperative outcomes for selected patients undergoing oesophagectomy. The results support continued supervised trainee involvement in oesophageal cancer surgery

Design of Aquila Optimization Heuristic for Identification of Control Autoregressive Systems

Swarm intelligence-based metaheuristic algorithms have attracted the attention of the research community and have been exploited for effectively solving different optimization problems of engineering, science, and technology. This paper considers the parameter estimation of the control autoregressive (CAR) model by applying a novel swarm intelligence-based optimization algorithm called the Aquila optimizer (AO). The parameter tuning of AO is performed statistically on different generations and population sizes. The performance of the AO is investigated statistically in various noise levels for the parameters with the best tuning. The robustness and reliability of the AO are carefully examined under various scenarios for CAR identification. The experimental results indicate that the AO is accurate, convergent, and robust for parameter estimation of CAR systems. The comparison of the AO heuristics with recent state of the art counterparts through nonparametric statistical tests established the efficacy of the proposed scheme for CAR estimation

Design of Aquila Optimization Heuristic for Identification of Control Autoregressive Systems

Swarm intelligence-based metaheuristic algorithms have attracted the attention of the research community and have been exploited for effectively solving different optimization problems of engineering, science, and technology. This paper considers the parameter estimation of the control autoregressive (CAR) model by applying a novel swarm intelligence-based optimization algorithm called the Aquila optimizer (AO). The parameter tuning of AO is performed statistically on different generations and population sizes. The performance of the AO is investigated statistically in various noise levels for the parameters with the best tuning. The robustness and reliability of the AO are carefully examined under various scenarios for CAR identification. The experimental results indicate that the AO is accurate, convergent, and robust for parameter estimation of CAR systems. The comparison of the AO heuristics with recent state of the art counterparts through nonparametric statistical tests established the efficacy of the proposed scheme for CAR estimation

Dwarf Mongoose Optimization Metaheuristics for Autoregressive Exogenous Model Identification

Nature-inspired metaheuristic algorithms have gained great attention over the last decade due to their potential for finding optimal solutions to different optimization problems. In this study, a metaheuristic based on the dwarf mongoose optimization algorithm (DMOA) is presented for the parameter estimation of an autoregressive exogenous (ARX) model. In the DMOA, the set of candidate solutions were stochastically created and improved using only one tuning parameter. The performance of the DMOA for ARX identification was deeply investigated in terms of its convergence speed, estimation accuracy, robustness and reliability. Furthermore, comparative analyses with other recent state-of-the-art metaheuristics based on Aquila Optimizer, the Sine Cosine Algorithm, the Arithmetic Optimization Algorithm and the Reptile Search algorithm—using a nonparametric Kruskal–Wallis test—endorsed the consistent, accurate performance of the proposed metaheuristic for ARX identification

Nonlinear Hammerstein System Identification: A Novel Application of Marine Predator Optimization Using the Key Term Separation Technique

The mathematical modelling and optimization of nonlinear problems arising in diversified engineering applications is an area of great interest. The Hammerstein structure is widely used in the modelling of various nonlinear processes found in a range of applications. This study investigates the parameter optimization of the nonlinear Hammerstein model using the abilities of the marine predator algorithm (MPA) and the key term separation technique. MPA is a population-based metaheuristic inspired by the behavior of predators for catching prey, and utilizes Brownian/Levy movement for predicting the optimal interaction between predator and prey. A detailed analysis of MPA is conducted to verify the accurate and robust behavior of the optimization scheme for nonlinear Hammerstein model identification

HIGH-RESOLUTION MOLECULAR ALLELOKARYOTYPING IDENTIFIES NOVEL UNIPARENTAL DISOMY AND FOCAL COPY NUMBER ALTERATIONS IN ACUTE PROMYELOCYTIC LEUKEMIA (APL)

Introduction: Experimental evidence obtained in transgenic mice revealed that PML-RARA is necessary but not sufficient for the development of APL, suggesting that additional genetic mutations are also required for its development. Aim: To define whether additional submicroscopic genomic alterations may characterize APL and may be used to better classify the disease by dissection of genomic subsets. Patients and Methods: 105 adult patients with acute myeloid leukemia were analyzed. These cases included all French-American-British subtypes, miscellaneous cytogenetic abnormalities and normal karyotype subgroups. Among these, the M3 subtype included 28 patients, representing the 33% of the whole study population. Genomic DNA was isolated from blast cells and applied to Genome-Wide Human SNP 6.0 array (Affymetrix, Santa Clara, CA) following the manufacturer’s instructions. Fluorescence in situ hybridization, quantitative PCR and nucleotide sequencing were used to confirm genomic alterations. Results: A wide spectrum of different copy number alterations (CNAs) were identified in all cases and no significant difference in the average number of alterations was detected among different leukemia cytogenetic subgroups except for the complex subgroup, which had an average of 55 CNA/patient. In APL cases an average of 8 CNAs per case (range, 1-24) was found. The macroscopic alterations were rare, confirmed conventional cytogenetics and involved trisomy of chromosome 8 in 3 cases, loss of chromosome 6, loss of chromosome 20 and deletions on chromosome 9 and 7. Microscopic CNAs (< 1.5 Mbps) involved every chromosome at least once and predominantly chromosomes 1, 2, 9, 15 and 17. For each alteration we interrogated a collated library of copy-number variants (CNVs, Database of Genomics Variants and USCS Genome Browser) to assure that these regions were not known as CNVs and therefore to decrease the noise of raw copy number data. Genetic gains were more common than losses and their median size was 300 kb (range 0.2- 1.4 Mb). The majority of lesions were not recurrent, being identified in only a single patient. Focal genetic alterations were detected at the breakpoints of t(15;17)(q22;q21) in PML and RARA genes, in genes involved in activation of transcription (loss of LMX1 on 1q23.3, loss of MLXIPL and BCL7 on 7q11.23), regulation of cell cycle (gain of PVT1 and MYC on 8q24) and cell adhesion (gain of NCAM1 on 11q23). In order to identify potential pathogenetic alterations, all microscopic CNAs were compared with the list of genes from the Cancer genome project (http://www.sanger.ac.uk/genetics/CPG/Census) finding out that six alterations involved a known cancer-related gene. Most of these genes encode tyrosine kinase proteins (ERBB4) or transcription factors (ETV1, ETV6, ERG). Copy neutral loss of heterozygosity events affected 1p34.2-1p32.3, 10p11.2 (MLLT10), 11p11.2 (WT1, CDKN1C, HRAS). Finally, patients with more than 10 CNAs were found to be associated with a worse prognosis. Conclusions: These data demonstrate that different cooperating events may be involved in the generation of APL. Furthermore, these novel findings may be used to stratify patients according to genomic changes. Supported by: European LeukemiaNet, AIL, AIRC, Fondazione Del Monte di Bologna e Ravenna, FIRB 2006, Ateneo RFO grants