Awareness and Perception Toward Obesity and Knee Osteoarthritis and Their Preventive Measures Among the Adult Population in the Northern Borders Region, Saudi Arabia.

BACKGROUND: Osteoarthritis (OA) of the knee poses a significant public health challenge, with its prevalence escalating globally. This study addresses a critical knowledge gap by investigating the awareness and perceptions of knee OA in the Northern Borders Region, Saudi Arabia, focusing on demographic factors that may influence community perspectives. STUDY AIM: The primary aim of this cross-sectional study is to comprehensively examine the awareness and perceptions of knee OA, exploring the influence of demographic variables, including region, gender, age, nationality, and educational levels. METHODOLOGY: A total of 501 participants from various cities in the Northern Borders Region, Saudi Arabia, were enrolled in this study. Demographic characteristics, including region, gender, age, nationality, and educational levels, were documented. A structured survey instrument was utilized to collect data on awareness and perceptions of knee OA. Statistical analyses included descriptive statistics, chi-square tests, and logistic regression to explore associations. RESULTS: Demographic insights revealed a predominance of participants from Arar (37.50%) and Rafha (36.50%), with a nearly equal gender distribution (52.90% male, 47.10% female). The majority fell within the 31-45 age group (37.50%), and 97.60% were Saudi nationals. Educational levels varied, with 55.30% holding a bachelor's degree. Awareness levels indicated that 75.40% recognized obesity as a significant factor in knee OA. Significant associations were found between gender and acknowledgment of obesity (p = 0.021), as well as between age and awareness of obesity (p = 0.040). Non-Saudi participants exhibited a higher awareness of knee injury as a reason for arthritis (p = 0.028). Educational levels demonstrated significant associations with awareness of rheumatoid arthritis (p = 0.012), growing old as a reason for knee arthritis (p = 0.002), and various preventive measures and treatment options. CONCLUSION: This study provides a nuanced understanding of knee OA awareness and perceptions in the Northern Borders Region, Saudi Arabia. The high recognition of obesity as a risk factor, coupled with demographic variations, highlights the need for tailored health education interventions. Addressing gender-specific, age-related, and educational disparities is crucial for promoting effective community-wide initiatives to prevent and manage knee OA.

Does vitamin C supplementation in milk improve growth and health of diarrheic calves?

The objective of this study was to investigate how supplementing vitamin C (VC) in milk affects growth, starter intake, blood metabolites, and the health of young calves classified into healthy or diarrheic groups. Calves were classified as diarrheic if they experienced diarrhea for at least 3 days from birth to day 7, otherwise, they were classified as healthy (i.e., days with diarrhea < 3). From day 8 of age, a total of 48 Holstein calves were divided into four groups based on a 2 × 2 factorial arrangement, with calf health status (healthy or diarrheic) and VC supplementation (VC+ or VC-) to pasteurized milk (0 or 2 g/d; 50% purity) being the main experimental factors. Calves were fed equal amounts of milk until weaning (d 60). Calves continued to be monitored until they reached 74 days of age. Calves in the VC+ group were heavier at weaning (74.3 vs. 72.2 kg; P = 0.04) compared to those calves that did not receive VC. Blood total antioxidant capacity (d 53 and 67) and superoxide dismutase activity (d 53) were greater (P < 0.01) in VC+ vs. VC- calves. Calf health status and VC supplementation interacted (P = 0.03) for blood ß-hydroxybutyrate on d 53, with the lowest concentration observed in diarrheic/VC- calves. Calves in the diarrheic group had a lower total antioxidant capacity (P = 0.01) but a greater neutrophil-to-lymphocyte ratio on d 53 and 67 (P < 0.01) than calves in the healthy group. Before weaning (d 53), neutrophil-to-lymphocyte ratio was greater, but hemoglobin was lower (P = 0.02) in calves classified into the diarrheic group that did not receive supplemental VC. The number of days medicated for diarrhea treatment was lower in VC+ calves than those in VC- group (1.73 vs. 2.47 days; P = 0.05). Overall, VC supplementation in pasteurized milk improved calf growth and health. Calves that experienced elevated episodes of diarrhea within the first week of life benefited more from supplemental VC than those classified into the healthy group.

Machine learning-based technique for resonance and directivity prediction of UMTS LTE band quasi Yagi antenna.

In this study, we have presented our findings on the deployment of a machine learning (ML) technique to enhance the performance of LTE applications employing quasi-Yagi-Uda antennas at 2100 MHz UMTS band. A number of techniques, including simulation, measurement, and a model of an RLC-equivalent circuit, are discussed in this article as ways to assess an antenna's suitability for the intended applications. The CST simulation gives the suggested antenna a reflection coefficient of -38.40 dB at 2.1 GHz and a bandwidth of 357 MHz (1.95 GHz-2.31 GHz) at a -10 dB level. With a dimension of 0.535λ0×0.714λ0, it is not only compact but also features a maximum gain of 6.9 dB, a maximum directivity of 7.67, VSWR of 1.001 at center frequency and a maximum efficiency of 89.9%. The antenna is made of a low-cost substrate, FR4. The RLC circuit, sometimes referred to as the lumped element model, exhibits characteristics that are sufficiently similar to those of the proposed Yagi antenna. We use yet another supervised regression machine learning (ML) technique to create an exact forecast of the antenna's frequency and directivity. The performance of machine learning (ML) models can be evaluated using a variety of metrics, including the variance score, R square, mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and mean squared logarithmic error (MSLE). Out of the seven ML models, the linear regression (LR) model has the lowest error and maximum accuracy when predicting directivity, whereas the ridge regression (RR) model performs the best when predicting frequency. The proposed antenna is a strong candidate for the intended UMTS LTE applications, as shown by the modeling results from CST and ADS, as well as the measured and forecasted outcomes from machine learning techniques.

Machine learning-based technique for gain and resonance prediction of mid band 5G Yagi antenna.

In this study, we present our findings from investigating the use of a machine learning (ML) technique to improve the performance of Quasi-Yagi-Uda antennas operating in the n78 band for 5G applications. This research study investigates several techniques, such as simulation, measurement, and an RLC equivalent circuit model, to evaluate the performance of an antenna. In this investigation, the CST modelling tools are used to develop a high-gain, low-return-loss Yagi-Uda antenna for the 5G communication system. When considering the antenna's operating frequency, its dimensions are [Formula: see text]. The antenna has an operating frequency of 3.5 GHz, a return loss of [Formula: see text] dB, a bandwidth of 520 MHz, a maximum gain of 6.57 dB, and an efficiency of almost 97%. The impedance analysis tools in CST Studio's simulation and circuit design tools in Agilent ADS software are used to derive the antenna's equivalent circuit (RLC). We use supervised regression ML method to create an accurate prediction of the frequency and gain of the antenna. Machine learning models can be evaluated using a variety of measures, including variance score, R square, mean square error, mean absolute error, root mean square error, and mean squared logarithmic error. Among the nine ML models, the prediction result of Linear Regression is superior to other ML models for resonant frequency prediction, and Gaussian Process Regression shows an extraordinary performance for gain prediction. R-square and var score represents the accuracy of the prediction, which is close to 99% for both frequency and gain prediction. Considering these factors, the antenna can be deemed an excellent choice for the n78 band of a 5G communication system.

Does honey have any salutary effect against streptozotocin - induced diabetes in rats?

BACKGROUND: Diabetes is a global, growing and costly public health problem. In the literature, there are conflicting reports on the effect of consumption of bee honey on diabetes. We assessed the possible effect of a commercially available bee honey (given orally by gavage at doses of 1 g/kg/day for 4 weeks) on the blood concentrations of glucose, insulin and leptin and body weight of rats with streptozotocin-induced diabetes. METHODS: Thirty-six rats were allocated randomly into six groups equally and treated for 4 weeks as follows: Group.1: non-diabetic rats given distilled water, group.2: non-diabetic rats given honey (1 g/kg), group.3: Diabetic rats given distilled water, group.4: Diabetic rats given honey, group.5: Diabetic rats given insulin (10 IU/kg), and group.6: Diabetic rats given combination of insulin (10 IU/kg) with honey (1 g/kg). The body weight, blood glucose, insulin and leptin concentrations of each rat were measured. RESULTS: Honey treatment did not significantly affect the glucose, leptin and insulin concentrations of diabetic rats. It did not significantly affect the excessive water intake or urinary output in diabetic rats when compared to the insulin-treated groups. Neither honey nor insulin improved body weight in diabetic rats. CONCLUSION: Contrary to the reports of a salutary effect of honey in diabetic humans and rodents, our results showed that consumption of honey caused no significant changes in body weight, or glucose and insulin concentrations. However, further studies with different doses and durations of treatment are warranted.

Comparing orthodontic bond failures of light-cured composite resin with chemical-cured composite resin: A 12-month clinical trial.

INTRODUCTION: In this clinical trial, we evaluated and compared bond failure rates of light-cured composite resin vs chemical-cured composite resin for 12 months. METHODS: Twenty-two subjects (356 stainless steel brackets) were included in this study, and a split-mouth design was used to randomly allocate diagonally opposite quadrants to either chemical-cured (178 brackets) or light-cured (178 brackets) composite resin; the brackets came from the same manufacturer. The survival and failure rates of the brackets were evaluated by the mode of polymerization. The overall bracket survival rates were estimated using the Kaplan-Meier product limit estimate. RESULTS: There were no significant differences in the bond failure rates between the chemical-cured and the light-cured composites (P = 0.52). Bond failures were greater in posterior teeth (6.7%) than in anterior teeth (1.2%). The highest failure rate was observed in the second premolars (7.7%). CONCLUSIONS: The overall failure rate of brackets with the 2 bonding systems was 2.8%, which is acceptable for clinical use. The polymerization mode did not influence the bracket survival rate significantly.

[Puberty, fertility and chronic diseases]. / Puberté, fertilité et maladies chroniques.

The onset of puberty is the sum of complex and multifactorial mechanisms resulting from the action of both activating and inhibiting factors, leading to the maturation of the gonads and the ability to reproduce. Many contributors to pubertal development are involved in fat mass acquisition and their action is relayed through the hypothalamus. It is therefore easy to understand how chronic diseases can affect the development of puberty and fertility apart from the specific impact of their molecular alteration. We have chosen cystic fibrosis and chronic renal disease as examples of chronic disorders affecting puberty through distinct mechanisms. As drugs are undistinguishable from chronic diseases, we also describe the impact of corticosteroids and chemotherapy on reproductive function. Last, we describe the surveillance and care of pubertal delay and its consequences (growth and bone mineralization) of patients affected with chronic disorders during adolescence.