Childhood obesity and hormonal abnormalities associated with cancer risk

Observation on Application Effect of Arterial Puncture and Catheterization under Guidance of Intelligent Medical Care Ultrasound in Clinical Anesthesia

In clinical anesthesia and the rescue of critically ill patients, arterial puncture and catheterization are the most commonly chosen ways to establish central arterial access for patients. Invasive arterial puncture and catheterization facilitate the grasp of real-time vital sign information of patients during surgery, which strengthens patient monitoring during surgery and improves safety. However, the traditional method of arterial puncture and cannulation through palpation of the radial artery is often prone to complications related to mechanical injury, such as hemorrhage, hematoma, and accidental perforation of the artery. Studies have shown that ultrasound-guided radial artery puncture and cannulation can shorten the puncture cannulation time, reduce the incidence of complications related to puncture cannulation, and improve the success rate of puncture cannulation. In order to verify it, this paper uses the experimental group and the control group to conduct comparative experiments and uses the neural network method to evaluate the effects of the two methods. As a more mature method of artificial intelligence, BP neural network is widely used in a wide range of applications and has the characteristics of strong generalization ability and fast convergence, so we choose it as the base model. The specific work of this paper is as follows: (1) in-depth study of the relevant theory of BP neural network (BPNN), focusing on the structure of BPNN and the working principle of algorithm; the problems to be solved in the clinical anesthesia effect evaluation have laid a theoretical foundation for the establishment of an improved BPNN evaluation model in the following chapters. (2) introduce the basic principle of genetic neural network, analyze the benefits of combining genetic neural network and BPNN; introduce in detail the process of genetic algorithm to optimize the weights and thresholds of BPNN, and establish a GA-BP evaluation model. The test proves the feasibility and superiority of the model.

Serum Amyloid P and Endocrine Markers in a Cohort of Obese Children

OBJECTIVES

Obesity in children can lead to morbidity and mortality due to metabolic and inflammatory comorbidities.

AIMS

The objective of the study was to investigate the alterations in acute inflammatory markers, serum amyloid P (SAP) and cortisol, and endocrine markers, leptin and insulin, in obese children.

MATERIALS AND METHODS

Serum leptin, insulin, cortisol, and amyloid P concentrations were measured in obese (BMI percentile >85, n = 17) and nonobese (BMI percentile < 75, n = 20) children using ELISA and Bio-Plex Bead-based assay.

STATISTICAL ANALYSIS USED

Serum concentrations of analytes were compared between normal and obese groups using 2-tailed student's t-test.

RESULTS

Mean leptin, insulin, and SAP serum concentrations were significantly higher in obese children as compared to the controls (97.19 vs. 4.06, P < 0.05; 21.31 vs 3.56, P < 0.05; 46.77 vs. 17.89, P < 0.05; respectively). No difference was found in mean serum cortisol levels of the two groups. However, cortisol values were higher in obese subjects compared to the control group (7.89 vs 6.30, P = 0.15). Leptin corelated with insulin (r = 0.42, P = 0.043) and cortisol (r = 0.48, P = 0.025) levels in the obese group. Furthermore, leptin, insulin, and SAP levels were corelated with BMI (r = 0.80, P < 0.000; r = 0.67, P = 0.015, respectively) and body weight (r = 0.52, P = 0.01; r = 0.52, P = 0.002; r = 0.54, P = 0.01, respectively) in the obese group but did not demonstrate a significant relationship in the nonobese group.

CONCLUSION

Elevated SAP levels and increase in leptin and insulin indicated a preeminent disposition of morbidly obese children to the development of low-grade inflammation and metabolic syndrome.

Applications of Machine Learning in Cancer Prediction and Prognosis

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15–25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

Bone maturation along the spectrum from normal weight to obesity: a complex interplay of sex, growth factors and weight gain

BACKGROUND

The aim of the study was to define the prevalence and degree of advanced bone age (ABA) in normal vs. excessive weight children, and identify variables affecting ABA.

METHODS

We studied 167 children (3-18 years) with normal weight (28 F, 28 M), overweight (8 F, 12 M), and obesity (OB) (63 F, 28 M) at AI duPont Hospital for Children. We assessed bone age (BA), insulin, leptin, estradiol (E2), DHEAS, and IGF-1 levels.

RESULTS

Almost 25% of OB children have ABA>2 SDS, 33% >2 years (range 2-6.5 years advanced). ABA correlated with leptin, DHEAS and BMI z-score in girls, and with IGF-1 z-score and BMI z-score in boys (p<0.01). Girls with ABA had higher BMI z-score (p<0.001), insulin levels (p=0.02), and rates of weight gain (p=0.03). Boys with ABA had greater BMI z-score (p<0.001), but rate of weight gain did not differ. The greatest degree of ABA was found combining variables by tertiles. The top tertile of BA/CA had the highest insulin and IGF-1 z-scores. The top combined tertiles of DHEAS and BMI z-score or DHEAS and leptin in girls had the highest BA/CA. In boys, the top tertiles of BMI z-score and IGF-1 z-score produced the highest BA/CA. The lowest combined tertiles of any variables related to the lowest BA/CA.

CONCLUSIONS

Multiple factors influence skeletal maturation. Almost 25% of children with OB have ABA, associated with BMI z-score, and one or more of the following: insulin, leptin, DHEAS, IGF-1, and rate of weight gain. This report delineates the prevalence and degree of ABA by sex, in children with normal versus excessive weight.

Prospective study of body size throughout the life-course and the incidence of endometrial cancer among premenopausal and postmenopausal women

Although adult obesity is known to increase endometrial cancer risk, evidence for childhood obesity is limited. We prospectively examined the association between body fatness throughout life and endometrial cancer risk. 47,289 participants in the Nurses' Health Study (NHS) and 105,386 of the Nurses' Health Study II (NHS II) recalled their body fatness at ages 5, 10 and 20 using a pictogram. Childhood and adolescent body fatness were derived as the average at ages 5 and 10 and ages 10 and 20, respectively. We obtained adult weight from concurrent questionnaires. We calculated hazard ratios (HR) of endometrial cancer using Cox proportional hazards models. During follow-up, 757 incident cases of endometrial cancer were diagnosed. Body fatness in childhood, at age 10, in adolescence and at age 20 were positively associated with endometrial cancer risk (HR for ≥ Level 5 versus ≤ Level 2 in adolescence: 1.83 (95% CI 1.41-2.37). After adjusting for most recent BMI, none of the associations persisted. Weight change since age 18 was positively associated with endometrial cancer risk [HR for ≥ 25 kg gain versus stable: 2.54 (95% CI 1.80-3.59). Adult BMI was strongly associated with endometrial cancer risk [HR BMI ≥ 35 kg/m(2) versus BMI ≤ 25 kg/m(2) : 4.13 (95% CI 3.29-5.16)]. In postmenopausal women, the association with BMI was significantly stronger among non-users of hormone therapy. In conclusion, obesity throughout life is positively associated with endometrial cancer risk, with adult obesity one of the strongest risk factors. Maintaining a healthy weight throughout life remains important.

Machine learning applications in cancer prognosis and prediction

Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in cancer research, as it can facilitate the subsequent clinical management of patients. The importance of classifying cancer patients into high or low risk groups has led many research teams, from the biomedical and the bioinformatics field, to study the application of machine learning (ML) methods. Therefore, these techniques have been utilized as an aim to model the progression and treatment of cancerous conditions. In addition, the ability of ML tools to detect key features from complex datasets reveals their importance. A variety of these techniques, including Artificial Neural Networks (ANNs), Bayesian Networks (BNs), Support Vector Machines (SVMs) and Decision Trees (DTs) have been widely applied in cancer research for the development of predictive models, resulting in effective and accurate decision making. Even though it is evident that the use of ML methods can improve our understanding of cancer progression, an appropriate level of validation is needed in order for these methods to be considered in the everyday clinical practice. In this work, we present a review of recent ML approaches employed in the modeling of cancer progression. The predictive models discussed here are based on various supervised ML techniques as well as on different input features and data samples. Given the growing trend on the application of ML methods in cancer research, we present here the most recent publications that employ these techniques as an aim to model cancer risk or patient outcomes.

Monitoring height and weight: findings from a developmental paediatric service

AIM

To assess the recording of weight and height in children with disabilities and identify subgroups at risk of being either underweight or overweight.

METHODS

A retrospective clinical audit was undertaken within the Department of Developmental Medicine at The Royal Children's Hospital, Melbourne. Most recent weight and height measurements and data about the child's underlying condition were collected from the medical records of children attending a clinical appointment over a 3-month period. Primary medical diagnosis, age, gender, mode of feeding and ability to ambulate were recorded. Body mass index was calculated and corrected for age and gender.

RESULTS

 Study sample size was 583 (356 males), mean age was 8.25 years (range 2.8-17.4 years). Body mass index could be calculated for 48%. Height was less commonly measured in those with severe physical impairments. A survey of barriers to weight and height measurement showed that the main barrier to measuring height was practical difficulties. The percentage of children classified as overweight/obese was 26.6% and this was associated with intellectual disabilities, moderately impaired ambulation, older age and female gender; 13.5% of the study group was underweight, the majority of whom were non-ambulant.

CONCLUSIONS

 Although significant rates of underweight and overweight were identified in children with a range of disabilities within our service, monitoring of weight status was suboptimal. Despite this, data indicate that specific subgroups of children with disability appear at risk of being either overweight or underweight. Where height cannot be measured, other anthropometric measures such as waist circumference may be useful in the assessment of children with disabilities.

Effects of body composition, leptin, and adiponectin on bone mineral density in prepubertal girls

Body weight is positively associated with bone mineral density but the relationship between obesity and bone mineral density is unclear. Leptin and adiponectin are potential independent contributors to bone mineral density. We assessed the correlations of body composition, leptin and adiponectin with bone mineral density, and whether leptin, adiponectin and body composition determine bone mineral density independently in prepubertal girls. Forty-eight prepubertal girls were classified into obese and control groups by body mass index. Serum leptin and adiponectin levels were determined by enzyme immunoassay. Bone mineral density was measured using dual energy radiography absorptiometry and body composition was measured using bioelectrical impedance analysis. Lean and fat mass, and leptin were positively correlated with bone mineral density. Lean mass was a positive independent predictor of femoral and L-spine bone mineral density. Serum leptin was a positive independent predictor of femoral bone mineral density. Fat mass was a negative independent predictor of femoral bone mineral density. In prepubertal girls, lean mass has a favorable effect on bone mineral density. Fat mass seems not to protect the bone structure against osteoporosis, despite increased mechanical loading. Serum leptin may play a biological role in regulating bone metabolism.

[Is bariatric surgery in adolescents appropriate?]

Current recommendations for bariatric surgery are limited to patients older than 18 years. Two studies in 2007 showed that bariatric surgery improves survival in adults. Medical management of severe obesity in adolescents is all too often ineffective. For these reasons, early surgical intervention for adolescents with morbid obesity may be expected to prevent or avoid comorbidities, decrease mortality, and improve the quality of life. Several studies have demonstrated the feasibility of adolescent bariatric surgery with morbidity comparable to that seen in adult series. The earlier the surgery, the better the result in terms of prevention or reversal of comorbid conditions. In the USA, a consensus definition of adolescents eligible for bariatric surgery specifies attainment of Tanner Stage IV of sexual maturity and achievement of 95% of axial growth. Just as in adults, bariatric surgery in adolescents requires prolonged follow-up; it is important that such surgery be performed in centers specialized in adult bariatric surgery having the necessary multidisciplinary structure.

Prevalence of overweight and obesity in urban and semi-urban Jordanian children aged 3-6 years

OBJECTIVES

To show the prevalence of overweight and obesity among the Jordanian urban and semi-urban children; to compare their body mass index (BMI) with the international standards of BMI.

METHODS

We measured 1695 healthy children (842 boys and 853 girls) between 3 and 6 years for height, weight and mid upper arm circumference. BMI was calculated and transformed into percentiles. Children were divided into boys and girls.

RESULTS

The mean and SD values of BMI observed in our study were 16.69 +/- 4.9 kg/m(2) for boys and 16.82 +/- 4.77 kg/m(2) for girls aged 3-6 years. The prevalence of obesity and overweight among boys was 20.8% and 3.8% respectively and among girls was 19.1% and 7.2% respectively. In total, 48.0% of boys and 38.1% of girls were of healthy weight.

CONCLUSIONS

The mean BMI observed in our study's children aged 3-6 years was higher than the expected 50th percentile of the (World Health Organization/Centers for Disease Control and Prevention) reference values for a similar age range but, it was equivalent to the 75th percentile values. Obesity was more frequent than overweight among boys and girls aged 3-6 years.

Randomised controlled trial: A parent-based group education programme for overweight children

AIM

Childhood overweight and obesity is a significant community health problem with severe long-term complications. This paper aims to evaluate a four-by-two-hour weekly group parent education programme targeting children who are overweight.

METHODS

A randomised time series design with wait-list controls was conducted for overweight and obese children aged 3-10 years.

RESULTS

A statistically significant reduction in child body mass index and energy intake was found post treatment; no differences were reported for child sedentary electronic media time, physical activity and waist circumference. Children's baseline activity levels were found to be at or slightly above national recommended standards. No change occurred in primary parent body mass index or waist circumference after treatment.

CONCLUSIONS

A brief group education programme for parents was effective in reducing childhood overweight at 3 months follow-up.

Enhancing lifestyle for individuals with haemophilia through physical activity and exercise: the role of physiotherapy

For individuals with haemophilia, the benefits of many forms of physical activity outweigh their risks. Although activities with significant trauma risk should be avoided, persons who have haemophilia can participate in, enjoy and even excel in a variety of physical activities and sports. Both the National Hemophilia Foundation and the World Foundation of Hemophilia have produced documents to guide individuals with haemophilia and their healthcare professionals, coaches and parents in developing physical activity programmes and participation in sports. Physical activity guidelines for promoting health benefits exist worldwide and can be incorporated into individualized exercise programmes to ensure that a person with haemophilia is not only choosing appropriate activities, but also improving overall health and preparing the body to manage haemophilia better. Physiotherapy treatment is paramount in helping individuals prevent, manage and optimally recover from bleeds. Furthermore, the physical therapist, along with the haemophilia care team, can assist in preparing an individual to begin or progress to a physical activity programme that enhances fitness level, body composition and overall well-being. This article presents the unique role of the physiotherapist in facilitating safe participation in quality physical activity in the context of risks, benefits and activity recommendations. Participation in physical activity from an early age is ideal to facilitate the development of body awareness and capability and to foster the adoption of a physically active lifestyle; however, it is never too late to start. Consistent participation in quality physical activity beginning at any age is central to managing haemophilia and, equally important, to achieving overall health and well-being.

Fat mass is not beneficial to bone in adolescents and young adults

CONTEXT

Although muscle mass is beneficial to bone, studies on the effect of fat mass on bone have yielded conflicting results.

OBJECTIVE

The aim of this study was to assess the relations between lean and fat mass and bone structure.

DESIGN

This study was cross-sectional.

SETTING

The study was conducted in a general community.

SUBJECTS

Subjects included 300 healthy sexually mature adolescents and young adults (150 males and 150 females) between the ages of 13 and 21 yr.

MAIN OUTCOME MEASURE

We investigated the relation between dual-energy x-ray absorptiometry (DXA) measures of total body fat and lean mass and bone values obtained with DXA (legs and lumbar spine bone mineral density and bone mineral content) and computed tomography (CT) (cross-sectional and cortical bone areas of the femurs and cross-sectional area and cancellous bone density of the vertebrae).

RESULTS

Simple and multiple linear regression analyses showed significant positive relations between DXA lean mass and all CT and DXA measures of bone in the axial and appendicular skeletons (all P < 0.005). In contrast, whereas Pearson correlations between DXA measures of fat mass and bone parameters were generally positive, multiple regression analyses showed that fat mass, after accounting for lean mass, trunk height/leg length, had a negative, or no, correlation with CT and DXA values for bone.

CONCLUSIONS

Our findings provide compelling evidence that, despite increased mechanical loading and independent of lean mass, adipose tissue is not beneficial to bone structure.

Pediatric Obesity: Impact and Surgical Management

The incidence of children in the United States who are overweight or obese is increasing at an alarming rate, and many obesity-related complications are now being described in children. There appears to be no current pharmacologic treatment or surgical procedure that is both safe and effective for millions of obese children. Bariatric surgery may be useful, however, in carefully selected obese children with associated serious comorbidities unresponsive to medical or dietary interventions. The complications of pediatric obesity are discussed, as well as current medical and surgical management of this disorder.