Search Results (1,626)

Abstract: The aim of this study was to investigate whether age at introduction of solid foods in preterm infants influences growth in the first year of life. This was a prospective observational study in very low birth weight infants stratified to an early (<17 weeks corrected age) or a late (≥17 weeks corrected age) feeding group according to the individual timing of weaning. In total, 115 infants were assigned to the early group, and 82 were assigned to the late group. Mean birth weight and gestational age were comparable between groups (early: 926 g, 26 + 6 weeks; late: 881 g, 26 + 5 weeks). Mean age at weaning was 13.2 weeks corrected age in the early group and 20.4 weeks corrected age in the late group. At 12 months corrected age, anthropometric parameters showed no significant differences between groups (early vs. late, mean length 75.0 vs. 74.1 cm, weight 9.2 vs. 8.9 kg, head circumference 45.5 vs. 45.0 cm). A machine learning model showed no effect of age at weaning on length and length z-scores at 12 months corrected age. Infants with comorbidities had significantly lower anthropometric z-scores compared to infants without comorbidities. Therefore, regardless of growth considerations, we recommend weaning preterm infants according to their neurological abilities. Full article

Background: the variations in a child’s overall body shape and figure among different countries are attributable to differences in genetics, environmental factors, and the interaction between these elements. This study aims to evaluate the validity, reliability, and appropriateness of applying international growth standards to Jordanian children and adolescents aged 2–19 years old. Methods: 65,828 Jordanian children and adolescents (43% males; 57% females) aged 2–19 years old were selected from the Hakeem Program database and various private schools across Jordan. Height-for-age, weight-for-age, and body mass index (BMI)-for-age were analyzed comparatively for Jordanian children and adolescents against international growth standards. The z-score for each record was computed based on international equations. Results: Mean z-scores for height-for-age, weight-for-age, and BMI-for-age for both genders showed significant deviation from international standards across most age intervals. It was found that in most age groups, Jordanian children and adolescents were shorter and lighter than CDC and WHO standards, except for females at ages ≥ 16 years, who were heavier with higher BMI-for-age values than CDC standards based on weight-for-age and BMI-for-age equations. Moreover, Jordanian males at ages ≥ 12 years had lower BMI-for-age values than CDC standards. Conclusions: Jordanian children and adolescents showed significant deviations in their measurements from international standards and growth reference values. The development of a population-specific growth chart is highly recommended to enhance the accuracy of evaluating children’s and adolescents’ wellness. Full article

Osteoporosis is a multifactorial systemic skeletal disease that is characterized by a low bone mineral density (BMD) and the microarchitectural deterioration of bone tissue, leading to bone fragility. The search for new genes that may play an important role in the regulation of bone mass and the development of osteoporosis is ongoing. Recently, it was found that altering the activity of the endothelin-1-converting enzyme encoded by the ECE1 gene may affect bone mineral density (BMD). Another gene involved in the process of osteoblast differentiation and maturation is believed to be PPARG (peroxisome proliferator-activated receptor gamma). This participates in regulating the transformation of stem cells and affects the process of bone formation and resorption. Therefore, we analyzed the association of the ECE1 and PPARG variants with osteopenia and osteoporosis risk in the Polish population. This study included a group (n = 608) of unrelated Polish women (245 individuals with osteoporosis (aged: 57 ± 9), 109 individuals with osteopenia (aged: 53 ± 8) and 254 healthy controls (aged: 54 ± 8)). The real-time PCR technique was used to determine the genetic variants for rs213045 (-338G>T) and rs213046 (-839A>C) of the ECE1 gene and rs1801282 (Pro12Ala, C>G) of the PPARG gene. Analysis of the PPARG rs1801282 variants did not show any association with the risk of osteoporosis and osteopenia. However, in the densitometric results, lower median Z-score values were observed for the T allele compared to the G allele for the rs213045 variant of the ECE1 gene (−1.11 ± 1.07 vs. −0.78 ± 1.21, p = 0.021). Moreover, the TT genotype for the rs213045 variant was more common in women with osteopenia (13.8%, OR = 2.82, p < 0.05) and osteoporosis (7.8%, OR = 1.38, p > 0.05) compared to the control group (5.5%). Additionally, our results suggested that the T allele of rs213045 was more common in women with osteopenia compared to the controls. We further observed that the haplotype containing two major GA alleles of ECE1 (rs213045, rs213046) could reduce the risk of osteopenia in our population. Finally, we found that women with osteoporosis had statistically significantly lower body mass and BMI values compared to the control group. Our results suggest that the ECE1 rs213045 variant may increase the risk of osteopenia. However, the data obtained require confirmation in further studies. Full article

Accurate brain extraction is crucial for the validity of MRI analyses, particularly in the context of traumatic brain injury (TBI), where conventional automated methods frequently fall short. This study investigates the interplay between intensity normalization, bias-field correction (also called intensity inhomogeneity correction), and automated brain extraction in MRIs of individuals with TBI. We analyzed 125 T1-weighted Magnetization-Prepared Rapid Gradient-Echo (T1-MPRAGE) and 72 T2-weighted Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI sequences from a cohort of 143 patients with moderate to severe TBI. Our study combined 14 different intensity processing procedures, each using a configuration of N3 inhomogeneity correction, Z-score normalization, KDE-based normalization, or WhiteStripe intensity normalization, with 10 different configurations of the Brain Extraction Tool (BET) and the Optimized Brain Extraction Tool (optiBET). Our results demonstrate that optiBET with N3 inhomogeneity correction produces the most accurate brain extractions, specifically with one iteration of N3 for T1-MPRAGE and four iterations for T2-FLAIR, and pipelines incorporating N3 inhomogeneity correction significantly improved the accuracy of BET as well. Conversely, intensity normalization demonstrated a complex relationship with brain extraction, with effects varying by the normalization algorithm and BET parameter configuration combination. This study elucidates the interactions between intensity processing and the accuracy of brain extraction. Understanding these relationships is essential to the effective and efficient preprocessing of TBI MRI data, laying the groundwork for the development of robust preprocessing pipelines optimized for multi-site TBI MRI data. Full article

Infrared (IR) small target detection in sky scenes is crucial for aerospace, border security, and atmospheric monitoring. Most current works are typically designed for generalized IR scenes, which may not be optimal for the specific scenario of sky backgrounds, particularly for detecting small and dim targets at long ranges. In these scenarios, the presence of heavy clouds usually causes significant false alarms due to factors such as strong edges, streaks, large undulations, and isolated floating clouds. To address these challenges, we propose an infrared dim and small target detection algorithm based on morphological filtering with dual-structure elements. First, we design directional dual-structure element morphological filters, which enhance the grayscale difference between the target and the background in various directions, thus highlighting the region of interest. The grayscale difference is then normalized in each direction to mitigate the interference of false alarms in complex cloud backgrounds. Second, we employ a dynamic scale awareness strategy, effectively preventing the loss of small targets near cloud edges. We enhance the target features by multiplying and fusing the local response values in all directions, which is followed by threshold segmentation to achieve target detection results. Experimental results demonstrate that our method achieves strong detection performance across various complex cloud backgrounds. Notably, it outperforms other state-of-the-art methods in detecting targets with a low signal-to-clutter ratio (MSCR ≤ 2). Furthermore, the algorithm does not rely on specific parameter settings and is suitable for parallel processing in real-time systems. Full article

Background: Despite being the most commonly performed valvular intervention, risk prediction for aortic valve replacement in patients with severe aortic stenosis by currently used risk scores remains challenging. The study aim was to develop a biomarker-based risk score by means of a neuronal network. Methods: In this multicenter study, 3595 patients were divided into test and validation cohorts (70% to 30%) by random allocation. Input variables to develop the ABC-AS score were age, the cardiac biomarker high-sensitivity troponin T, and a patient history of cardiac decompensation. The validation cohort was used to verify the scores’ value and for comparison with the Society of Thoracic Surgery Predictive Risk of Operative Mortality score. Results: Receiver operating curves demonstrated an improvement in prediction by using the ABC-AS score compared to the Society of Thoracic Surgery Predictive Risk of Operative Mortality (STS prom) score. Although the difference in predicting cardiovascular mortality was most notable at 30-day follow-up (area under the curve of 0.922 versus 0.678), ABC-AS also performed better in overall follow-up (0.839 versus 0.699). Furthermore, univariate analysis of ABC-AS tertiles yielded highly significant differences for all-cause (p < 0.0001) and cardiovascular mortality (p < 0.0001). Head-to-head comparison between both risk scores in a multivariable cox regression model underlined the potential of the ABC-AS score (HR per z-unit 2.633 (95% CI 2.156–3.216), p < 0.0001), while the STS prom score failed to reach statistical significance (p = 0.226). Conclusions: The newly developed ABC-AS score is an improved risk stratification tool to predict cardiovascular outcomes for patients undergoing aortic valve intervention. Full article

Considering the fact that Toxoplasma is a common parasite of humans and Toxoplasma bradyzoites can reside in skeletal muscle, T. gondii-mediated immune responses may modulate the progression and pathophysiology of another musculoskeletal disorder, osteoporosis. In the current study, we investigated the association of bone health and Toxoplasma gondii infection status. A total of 138 patients living in Germany with either osteopenia or osteoporosis were included in the study, and they were categorized into two groups, T. gondii uninfected (n = 74) and infected (n = 64), based on the presence of T. gondii-specific IgG antibodies. The demographic and clinical details of the study subjects were collected from the medical records. Logistic regression analysis was performed to delineate the association of bone health parameters with the infection status. The prevalence of toxoplasmosis was 46.4% in the study participants. The infected individuals with osteopenia and osteoporosis showed higher levels of mean spine and femoral T score, Z score, and bone mineral density (BMD), indicating improved bone health compared to the uninfected group. Logistic regression analysis showed that subjects with T. gondii infection displayed increased odds of having a higher mean femur T score, femur BMD, and femur Z score even after adjusting for age, creatinine, and urea levels. However, when the duration of drug intake for osteoporosis was taken into account, the association lost statistical significance. In summary, in this study, an improvement in osteopenia and osteoporosis was observed in Toxoplasma-infected patients, which may be partly due to the longer duration of drug intake for osteoporosis in the infected patient group. Full article

Background: Kawasaki disease (KD) is a syndrome primarily affecting young children, typically under the age of five, and is characterized by the development of acute vasculitis. Through extensive research conducted on both murine and human subjects, it has been demonstrated that heightened levels of reactive oxygen species (ROS) play a pivotal role in the development of KD, especial coronary artery lesions (CALs). Hydrogen gas exhibits potent antioxidant properties that effectively regulate ROS production and the inflammatory response. Methods: We used Lactobacillus casei cell wall extract (LCWE)-induced vasculitis in mice as an animal model of KD and treated the mice with hydrogen gas inhalation. Results: We observed significant dilatation and higher Z scores in the left coronary artery (LCA) in D21 and D28 in mice after LCWE treatment compared to the control group (p < 0.001) and a significant resolution of LCA diameters (p < 0.01) and Z scores (p < 0.01) after treatment with inhaled hydrogen gas. We further demonstrated that serum IL-6 expression was higher in mice after LCWE treatment (p < 0.01) and IL-6 significantly decreased after inhaled hydrogen gas therapy (p < 0.001). Conclusion: According to our literature review, this is the first report where hydrogen gas inhalation has been demonstrated to be effective for the treatment of coronary artery dilatation in a KD murine model. Full article

Four glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have been used in children and adolescents with obesity or overweight. This network meta-analysis was conducted to compare the efficacy and safety of these regimens. Embase, PubMed, and Scopus were searched on March 2023 and updated in June 2024 for eligible randomized controlled trials (RCTs). The primary efficacy outcomes were mean difference in actual body weight, BMI (body mass index), BMI z score, and waist circumference. Safety outcomes included nausea, vomiting, diarrhea, abdominal pain, injection-site reaction, and hypoglycemia. Eleven RCTs with 953 participants were eligible. Semaglutide exhibited greater effects in reducing weight, BMI, and BMI z score versus the placebo. Semaglutide was associated with greater weight loss and BMI z score reduction in comparison with exenatide, liraglutide, and dulaglutide. Semaglutide also significantly decreased BMI than exenatide. None of the four GLP-1 RAs were associated with higher risks of diarrhea, headache, and abdominal pain versus the placebo. Liraglutide was more likely to cause nausea, vomiting, hypoglycemia, and injection-site reactions than the placebo. Liraglutide also had higher odds of causing injection-site reactions than other GLP-1 RAs. Semaglutide appeared to be the most effective and safe option among four GLP-1 RAs in children and adolescents with obesity or overweight. Full article

This study examines the multifaceted field of injuries and their impacts on performance in the National Basketball Association (NBA), leveraging a blend of Data Science, Data Mining, and Sports Analytics. Our research is driven by three pivotal questions: Firstly, we explore how Association Rule Mining can elucidate the complex interplay between players’ salaries, physical attributes, and health conditions and their influence on team performance, including team losses and recovery times. Secondly, we investigate the relationship between players’ recovery times and their teams’ financial performance, probing interdependencies with players’ salaries and career trajectories. Lastly, we examine how insights gleaned from Data Mining and Sports Analytics on player recovery times and financial influence can inform strategic financial management and salary negotiations in basketball. Harnessing extensive datasets detailing player demographics, injuries, and contracts, we employ advanced analytic techniques to categorize injuries and transform contract data into a format conducive to deep analytical scrutiny. Our anomaly detection methodologies, an ensemble combination of DBSCAN, isolation forest, and Z-score algorithms, spotlight patterns and outliers in recovery times, unveiling the intricate dance between player health, performance, and financial outcomes. This nuanced understanding emphasizes the economic stakes of sports injuries. The findings of this study provide a rich, data-driven foundation for teams and stakeholders, advocating for more effective injury management and strategic planning. By addressing these research questions, our work not only contributes to the academic discourse in Sports Analytics but also offers practical frameworks for enhancing player welfare and team financial health, thereby shaping the future of strategic decisions in professional sports. Full article

Pulmonary function tests (PFTs) are pivotal in diagnosing and managing a broad spectrum of respiratory disorders. These tests provide critical insights into lung health, guiding diagnoses, assessing disease severity, and shaping patient management strategies. This review addresses the complexities and nuances inherent in interpreting PFT data, particularly in light of recent updates from the European Respiratory Society (ERS) and American Thoracic Society (ATS). These updates have refined interpretive strategies, moving away from definitive diagnostic uses of spirometry to a more probabilistic approach that better accounts for individual variability through the use of Z-scores and lower limits of normal (LLNs). Significantly, this narrative review delves into the philosophical shift in spirometry interpretation, highlighting the transition from direct clinical diagnostics to a more nuanced evaluation geared towards determining the likelihood of disease. It critiques the reliance on fixed ratios and emphasizes the need for reference values that consider demographic variables such as age, sex, height, and ethnicity, in line with the latest Global Lung Function Initiative (GLI) equations. Despite these advances, challenges remain in ensuring uniformity across different predictive models and reference equations, which can affect the accuracy and consistency of interpretations. This paper proposes a streamlined three-step framework for interpreting PFTs, aiming to unify and simplify the process to enhance clarity and reliability across various medical specialties. This approach not only aids in accurate patient assessments but also mitigates the potential for misdiagnosis and ensures more effective patient management. By synthesizing contemporary guidelines and integrating robust physiological principles, this review fosters a standardized yet flexible approach to PFT interpretation that is both scientifically sound and practically feasible. Full article

Aim: Remethylation disorders such as 5,10-methylenetetrahydrofolate reductase (MTHFR) deficiency reduce the remethylation of homocysteine to methionine. The resulting hyperhomocysteinemia can lead to serious neurological consequences and multisystem toxicity. The role of MTHFR genotypes has not been investigated in patients with Rett Syndrome (RTT). In this study, we sought to assess the impact of co-occurring MTHFR genotypes on symptom profiles in RTT. Method: Using pharmacogenomic (PGx) testing, the MTHFR genetic polymorphisms rs1801133 (c.665C>T mutation) and rs1801131 (c.1286A>C mutation) were determined in 65 patients (18.7 years ± 12.1 [mean ± standard deviation]) with RTT as part of routine clinical care within the Centre for Interventional Paediatric Psychopharmacology (CIPP) Rett Centre, a National and Specialist Child and Adolescent Mental Health Service (CAMHS) in the UK. The clinical severity of patients was assessed using the RTT-anchored Clinical Global Impression Scale (RTT-CGI). Results: The clinical severity symptom distribution varied between the homozygous and heterozygous MTHFR rs1801133 and rs1801131 genotypes. Those with the homozygous genotype had a narrower spread of severity scores across several domains (language and communication, ambulation, hand-use and eye contact clinical domains). Patients with the homozygous genotype had statistically significantly greater CGI-Severity scores than individuals with a non-homozygous MTHFR genotype (Z = −2.44, p = 0.015). When comparing the ratings of moderately impaired (4), markedly impaired (5), severely impaired (6) and extremely impaired (7), individuals with the homozygous MTHFR genotype were more impaired than those with the non-homozygous MTHFR genotype (Z = −2.06, p = 0.039). There was no statistically significant difference in the number of prescribed anti-epileptic drugs between the genotypes. Conclusions: Our findings show that in those with a pathogenic RTT genetic variant, co-occurring homozygotic MTHFR rs1801133 and rs1801131 polymorphisms may act as associative genetic modifiers of clinical severity in a subset of patients. Profiling of rs1801133 and rs1801131 in RTT may therefore be useful, especially for high-risk patients who may be at the most risk from symptom deterioration. Full article

Adversarial attacks have received much attention as communication network applications rise in popularity. Connected and Automated Vehicles (CAVs) must be protected against adversarial attacks to ensure passenger and vehicle safety on the road. Nevertheless, CAVs are susceptible to several types of attacks, such as those that target intra- and inter-vehicle networks. These harmful attacks not only cause user privacy and confidentiality to be lost, but they also have more grave repercussions, such as physical harm and death. It is critical to precisely and quickly identify adversarial attacks to protect CAVs. This research proposes (1) a new dataset comprising three adversarial attacks in the CAV network traffic and normal traffic, (2) a two-phased adversarial attack detection technique named TAAD-CAV, where in the first phase, an ensemble voting classifier having three machine learning classifiers and one separate deep learning classifier is trained, and the output is used in the next phase. In the second phase, a meta classifier (i.e., Decision Tree is used as a meta classifier) is trained on the combined predictions from the previous phase to detect adversarial attacks. We preprocess the dataset by cleaning data, removing missing values, and adjusting the Z-score normalization. Evaluation metrics such as accuracy, recall, precision, F1-score, and confusion matrix are employed to evaluate and compare the performance of the proposed model. Results reveal that TAAD-CAV achieves the highest accuracy with a value of 70% compared with individual ML and DL classifiers. Full article

Background: Previous infection with Adenovirus-36 (HAdv-D36) has been associated with adipogenesis and glycemic regulation in cell culture and animal models. In humans, HAdv-D36 antibodies correlate with increased obesity risk yet paradoxically enhance glycemic control across various demographics. This study assesses the association of HAdv-D36 seropositivity with obesity, lipid, and glycemic profiles among school-aged children. Methods: We evaluated 208 children aged 9–13, categorized by BMI z-scores into normal weight (−1 to +1), overweight (+1 to +2), and obese (>+3). Assessments included anthropometry, Tanner stage for pubertal development, and biochemical tests (relating to lipids, glucose, and insulin), alongside HAdv-D36 seropositivity checked via ELISA. Insulin resistance was gauged using Chilean pediatric criteria. Results: The cohort displayed a high prevalence of overweight/obesity. HAdv-D36 seropositivity was 5.4%, showing no correlation with nutritional status. Additionally, no link between HAdv-D36 seropositivity and lipid levels was observed. Notably, insulin levels and HOMA-RI were significantly lower in HAdv-D36 positive children (p < 0.001). No cases of insulin resistance were reported in the HAdv-D36 (+) group in our population. Conclusions: HAdv-D36 seropositivity appears to decrease insulin secretion and resistance, aligning with earlier findings. However, no association with obesity development was found in the child population of southern Chile. Full article

Heart rate variability (HRV) is related to cardiac vagal control and emotional regulation and an index for cardiac vagal control and cardiac autonomic activity. This study aimed to develop the Taiwan HRV normative database covering individuals aged 20 to 70 years and to assess its diagnosing validity in patients with major depressive disorder (MDD). A total of 311 healthy participants were in the HRV normative database and divided into five groups in 10-year age groups, and then the means and standard deviations of the HRV indices were calculated. We recruited 272 patients with MDD for cross-validation, compared their HRV indices with the normative database, and then converted them to Z-scores to explore the deviation of HRV in MDD patients from healthy groups. The results found a gradual decline in HRV indices with advancing age in the HC group, and females in the HC group exhibit higher cardiac vagal control and parasympathetic activity than males. Conversely, patients in the MDD group demonstrate lower HRV indices than those in the HC group, with their symptoms of depression and anxiety showing a negative correlation with HRV indices. The Taiwan HRV normative database has good psychometric characteristics of cross-validation. Full article