P53 mutations in human adrenocortical neoplasms

The mechanisms of tumorigenesis of adrenocortical neoplasms have not been elucidated as yet. However, loss of heterozygosity at chromosomal locus 17p has been consistently observed in adrenocortical cancer. p53 is a recessive tumor suppressor gene located on chromosome 17p. Mutations in the p53 gene play an important role in the tumorigenesis of diverse types of human neoplasms including breast and colon cancers. More than 90% of all mutations discovered in such tumors have been detected in 4 hot spot areas that lie between exons 5 and 8. In contrast to wild-type p53, mutant p53 accumulates intracellularly and can be easily detected by immunohistochemistry. We therefore investigated the frequency of p53 mutations in human adrenocortical neoplasms using molecular biology and immunohistochemistry techniques. Five patients with adrenocortical adenomas (5 female; ages 39-72 yr), 11 patients with adrenocortical carcinomas (8 female, 3 male; ages 15- 50 yr), and two adrenocortical tumor cell lines were studied. After DNA extraction from frozen tumor tissue or paraffin-embedded material, exons 5 through 8 were amplified using the polymerase chain reaction and directly sequenced by the dideoxy termination method. Immunohistochemistry was performed on paraffin-embedded tumor specimens obtained during adrenalectomy using a monoclonal antibody reacting with both wild-type and mutant p53. Prevalence of mutations was adenomas, 0/5, carcinomas, 3/11, and adrenocortical cell lines, 2/2. Single point mutations were detected in 3 cases (exons 5, 6, and 7, respectively), and rearrangements of exon 7/8 and 8 were found in 2 cases. Immunohistochemistry detected strong nuclear and/or cytoplasmic p53 immunoreactivity in all adrenocortical carcinomas with point mutations of the p53 gene but not in adenomas and carcinomas with the wild-type sequence or with deletion/rearrangement of the p53 gene. We conclude that p53 plays a role in the tumorigenesis of adrenocortical carcinomas but is of less importance to benign adenomas

UAV trajectory optimisation in smart cities using modified A* algorithm combined with Haversine and Vincenty formulas

It is anticipated that the backbone of Smart Cities concerning automation and networking will be formed by Unmanned Aerial Vehicles in the imminent future. Therefore, our research focuses on developing advanced microcontrollers embedded with Artificial Intelligence techniques for self-governing Unmanned Aerial Vehicles. The main objective of this research was to enable full automation for the execution of flight paths with non-trivial sequences that will be performed with centimetre-level accuracy. Also, by utilising dynamic flight plans and trajectories, we aim to secure autonomous aviation based on norms, with control loops and fundamental constraints. More specifically, we evolved a novel algorithmic technique for trajectory optimisation, which deploys a modification to the A* search algorithm, implemented by the Haversine formula and enhances accuracy using Vincenty’s formula. Furthermore, realistic values for trajectory optimisation and obstacle avoidance were found through the implementation of a simulative investigation. The outcomes of our methodology indicate that the safety constraints associated with the integration of Unmanned Aerial Vehicles in the urban environment can be significantly mitigated. Consequently, their effectiveness will be increased in realising their diverse operations and capabilities

Radial Basis Function Artificial Neural Network for the Investigation of Thyroid Cytological Lesions

Objective. This study investigates the potential of an artificial intelligence (AI) methodology, the radial basis function (RBF) artificial neural network (ANN), in the evaluation of thyroid lesions. Study Design. The study was performed on 447 patients who had both cytological and histological evaluation in agreement. Cytological specimens were prepared using liquid-based cytology, and the histological result was based on subsequent surgical samples. Each specimen was digitized; on these images, nuclear morphology features were measured by the use of an image analysis system. The extracted measurements (41,324 nuclei) were separated into two sets: the training set that was used to create the RBF ANN and the test set that was used to evaluate the RBF performance. The system aimed to predict the histological status as benign or malignant. Results. The RBF ANN obtained in the training set has sensitivity 82.5%, specificity 94.6%, and overall accuracy 90.3%, while in the test set, these indices were 81.4%, 90.0%, and 86.9%, respectively. Algorithm was used to classify patients on the basis of the RBF ANN, the overall sensitivity was 95.0%, the specificity was 95.5%, and no statistically significant difference was observed. Conclusion. AI techniques and especially ANNs, only in the recent years, have been studied extensively. The proposed approach is promising to avoid misdiagnoses and assists the everyday practice of the cytopathology. The major drawback in this approach is the automation of a procedure to accurately detect and measure cell nuclei from the digitized images

Fall prevention intervention technologies: A conceptual framework and survey of the state of the art

In recent years, an ever increasing range of technology-based applications have been developed with the goal of assisting in the delivery of more effective and efficient fall prevention interventions. Whilst there have been a number of studies that have surveyed technologies for a particular sub-domain of fall prevention, there is no existing research which surveys the full spectrum of falls prevention interventions and characterises the range of technologies that have augmented this landscape. This study presents a conceptual framework and survey of the state of the art of technology-based fall prevention systems which is derived from a systematic template analysis of studies presented in contemporary research literature. The framework proposes four broad categories of fall prevention intervention system: Pre-fall prevention; Post-fall prevention; Fall injury prevention; Cross-fall prevention. Other categories include, Application type, Technology deployment platform, Information sources, Deployment environment, User interface type, and Collaborative function. After presenting the conceptual framework, a detailed survey of the state of the art is presented as a function of the proposed framework. A number of research challenges emerge as a result of surveying the research literature, which include a need for: new systems that focus on overcoming extrinsic falls risk factors; systems that support the environmental risk assessment process; systems that enable patients and practitioners to develop more collaborative relationships and engage in shared decision making during falls risk assessment and prevention activities. In response to these challenges, recommendations and future research directions are proposed to overcome each respective challenge.The Royal Society, grant Ref: RG13082

Fall Detection with Unobtrusive Infrared Array Sensors

As the world’s aging population grows, fall is becoming a major problem in public health. It is one of the most vital risks to the elderly. Many technology based fall detection systems have been developed in recent years with hardware ranging from wearable devices to ambience sensors and video cameras. Several machine learning based fall detection classifiers have been developed to process sensor data with various degrees of success. In this paper, we present a fall detection system using infrared array sensors with several deep learning methods, including long-short-term-memory and gated recurrent unit models. Evaluated with fall data collected in two different sets of configurations, we show that our approach gives significant improvement over existing works using the same infrared array sensor

SMILE: Search for MIlli-LEnses

ABSTRACTDark matter (DM) haloes with masses below ∼108 M⊙, which would help to discriminate between DM models, may be detected through their gravitational effect on distant sources. The same applies to primordial black holes, considered as an alternative scenario to DM particle models. However, there is still no evidence for the existence of such objects. With the aim of finding compact objects in the mass range of ∼106–109 M⊙, we search for strong gravitational lenses on milliarcsec scales (</p

Perturbation of lipids and glucose metabolism associated with previous 2,4-D exposure: a cross-sectional study of NHANES III data, 1988-1994

<p>Abstract</p> <p>Background</p> <p>Results from previous population studies showed that mortality rates from acute myocardial infarction and type-2 diabetes during the 1980s and 1990s in rural, agricultural counties of Minnesota, Montana, North and South Dakota, were higher in counties with a higher level of spring wheat farming than in counties with lower levels of this crop. Spring wheat, one of the major field crops in these four states, was treated for 85% or more of its acreage with chlorophenoxy herbicides. In the current study NHANES III data were reviewed for associations of 2,4-dichlorophenoxy acetic acid (2,4-D) exposure, one of the most frequently used chlorophenoxy herbicides, with risk factors that are linked to the pathogenesis of acute myocardial infarction and type-2 diabetes, such as dyslipidemia and impaired glucose metabolism.</p> <p>Methods</p> <p>To investigate the toxicity pattern of chlorophenoxy herbicides, effects of a previous 2,4-D exposure were assessed by comparing levels of lipids, glucose metabolism, and thyroid stimulating hormone in healthy adult NHANES III subjects with urinary 2,4-D above and below the level of detection, using linear regression analysis. The analyses were conducted for all available subjects and for two susceptible subpopulations characterized by high glycosylated hemoglobin (upper 50^thpercentile) and low thyroxine (lower 50^thpercentile).</p> <p>Results</p> <p>Presence of urinary 2,4-D was associated with a decrease of HDL levels: 8.6% in the unadjusted data (p-value = 0.006), 4.8% in the adjusted data (p-value = 0.08), and 9% in the adjusted data for the susceptible subpopulation with low thyroxine (p-value = 0.02). An effect modification of the inverse triglycerides-HDL relation was observed in association with 2,4-D. Among subjects with low HDL, urinary 2,4-D was associated with increased levels of triglycerides, insulin, C-peptide, and thyroid stimulating hormone, especially in the susceptible subpopulations. In contrast, subjects with high HDL did not experience adverse 2,4-D associated effects.</p> <p>Conclusions</p> <p>The results indicate that exposure to 2,4-D was associated with changes in biomarkers that, based on the published literature, have been linked to risk factors for acute myocardial infarction and type-2 diabetes.</p