Nonparametric Statistical Methods Research Articles

Alternative study designs and nonparametric statistical methods for adaptive management studies of invasive plants

Alternative study designs and nonparametric statistical methods for adaptive management studies of invasive plants

MEDICAL-SOCIOLOGICAL ANALYSIS OF HEALTH AND QUALITY OF LIFE OF PERSONS AGE 60+ RESIDING IN THE GRODNO REGION

Aim: to analyze indicators of self-assessment of quality of life, satisfaction with health, their relationship with socio-demographic factors and objective indicators of public health, among people aged 60+ living in the Grodno region. Materials and methods: data from official demographic and health statistics, a representative database of 1270 people aged 60+ of the Grodno region of the Republic of Belarus by gender, residence, age (WHOQOL-BREF tools) were analyzed. Nonparametric statistics methods were used. Results: The Grodno region demonstrates life expectancy at birth values ​​close to the republican average. The minimum values ​​in all regions are detected among men living in the village. In the structure of causes of death rate, diseases of the cardiovascular system lead by far. When self-assessing the quality of life, the options “good” or “neither bad nor good” predominate; satisfaction with the state of health is option “3” of the five-point scale. Men compared to women, rural residents compared to urban residents, unmarried compared to married people rate the quality of life lower. The hypothesis about the positive impact on the quality of life of the respondent having children is confirmed; the hypothesis about the influence of the old-age pension is not confirmed. Health satisfaction reveals resistance to socio-demographic factors. A positive medium-strength correlation is revealed between health satisfaction and self-assessment of quality of life in all socio-demographic groups. With increasing age, there is a decrease in self-esteem of quality of life, and an even more pronounced decrease in satisfaction with health. Conclusion: men aged 60+ living in rural areas are at risk of low self-assessments of quality of life, in connection with low life expectancy; at the same time, health satisfaction does not reveal gender differences.

Research Progress in the Construction of Delirium Risk Warning Model for ICU Patients Based on Decision Tree: A Review of the Literature

Intensive Care Unit (ICU) delirium is a cerebral syndrome characterized by acute disturbance of consciousness, with an incidence of 38%-87%. The occurrence of delirium can lead to prolonged hospital stay, accidental extubation rate, mortality and other adverse consequences. Therefore, early identification of delirium and active correction of reversible causes appear to be particularly important. At present, the risk prediction models for delirium in ICU constructed at home and abroad mainly use logistic regression to build delirium risk prediction models for patients admitted to ICU≥24h. However, studies have found that as many as 25% of critically ill patients will develop delirium within 24h of admission to ICU. Therefore, it is particularly important to construct a delirium early warning model for patients entering ICU24h. Logistic regression model has low processing efficiency for non-linear and interactive data, and can not intuitively show the importance of each variable in the predicted result. As a non-parametric statistical method, decision tree can overcome the disadvantages of Logistic regression model and build a better prediction model. Therefore, this study used 24h after admission to ICU as the segmentation point to build a decision tree model for predicting early and late delirium in ICU patients, forming a corresponding risk level system, and compared it with similar delirium models to verify the predictive value of the decision tree model for early and late delirium in ICU patients, providing a basis for the formulation of further intervention and nursing plans. Thereby reducing the incidence of ICU delirium.

What drives economics students to use generative artificial intelligence?

The increasing integration of Artificial Intelligence (AI) into education requires studying the motives for its use among students. This study aims to identify the key motivations for economics students to use AI and compare these motivations by grade level and gender. The study examines satisfaction with the use of AI and analyzes the number of AI tools used. An anonymous empirical study was conducted among 264 students from the Faculty of Economics at Taras Shevchenko National University of Kyiv, Ukraine. Data analysis included descriptive statistical methods, non-parametric statistical methods, and exploratory factor analysis. The study found that students’ main motivations for using AI are the automation of routine tasks (34.2%) and the need to save time (21.5%), while 18.7% use AI to compensate for lack of experience. Among Bachelor’s students, motivations such as automating routine tasks and saving time increased from 53% to 58% over the course of their studies, while lack of experience decreased from 22% to 15%. In contrast, Master’s students showed a decrease in routine automation (from 36% to 28%) but an increase in the need to compensate for lack of experience (from 15% to 28%) and to save time (from 18% to 25%). In terms of gender, men are more likely to use AI for learning and personal development, while women are slightly more likely to use AI for work. More than 38% of respondents say they need to use at least 2 AIs to achieve their goals. Acknowledgment This publication is based upon work from 24-PKVV-UM-002, ‘Strengthening the Resilience of Universities: Czech-Ukrainian Partnership for Digital Education, Research Cooperation, and Diversity Management,’ supported by the Czech Development Agency and the Ministry of Foreign Affairs under the initiative ‘Capacity Building of Public Universities in Ukraine 2024.’

Severe Uncontrolled Asthma: A Longitudinal Retrospective Study Illustrating the Experience of the Pulmonology Clinic of Târgu-Mureș, Romania.

Introduction: Severe uncontrolled asthma (SUA) affects approximately 5% of asthma patients, leading to frequent exacerbations, reduced lung function, and lower quality of life. Recent biologic therapies target specific inflammatory pathways, offering new options for SUA. Objective: This study aimed to evaluate clinical characteristics, treatment outcomes, and biomarkers in patients with SUA treated with biologics (Omalizumab, Benralizumab, and Dupilumab) at our clinic. Material and Methods: A six-month retrospective longitudinal study was conducted on 28 patients aged 36-83 years with SUA. Patients were divided into three groups: Omalizumab (n = 4), Benralizumab (n = 18), and Dupilumab (n = 6). Lung function tests and biomarkers such as eosinophil and IgE levels were measured over 3-month periods (T0, T1, and T2). Asthma control was assessed using asthma control tests (ACT), and non-parametric statistical methods were applied. Results: The median patient age was 64 years, with 75% showing elevated eosinophil counts (>300 cells/µL). Benralizumab significantly improved lung function (p < 0.05) and ACT scores (p < 0.001), reducing eosinophil counts to zero (p < 0.001). Patients on Dupilumab and Omalizumab showed improved asthma control (p < 0.05) and reduced exacerbations, albeit to a lesser extent (p > 0.05). Conclusions: Biologics, particularly Benralizumab and Dupilumab, improved asthma control, lung function, and quality of life in SUA patients, with improved ACT scores and spirometry values. Some patients remained poorly controlled, emphasizing the need for personalized treatment and regular biomarker monitoring. Multidisciplinary management and lifestyle changes are critical for better outcomes in SUA.

Cytokine profiling of plasma in patients with viral hepatitis C

Chronic hepatitis C (CHC) represents a significant public health concern. In the majority of cases, the infection progresses to a chronic form, which is characterised by the development of fibrosis and cirrhosis of the liver. A plethora of cytokines and chemokines are generated as a consequence of inflammatory processes within the liver. These can exert a dual effect, both protective and damaging, particularly in relation to the death of hepatocytes and the progression of liver fibrosis. Furthermore, a number of growth factors have been identified as playing a role in the pathogenesis of CHC. The objective of the study was a comprehensive evaluation of a wide range of cytokines, chemokines and growth factors in the blood plasma of patients with CHC at varying stages of liver fibrosis. The study cohort comprised 63 patients diagnosed with CHC, who were divided into three groups according to the stage of liver fibrosis. The control group comprised healthy individuals (n = 32). Concentrations of the following cytokines were determined in plasma: Interleukins and some cytokines (IL-1α, IL-1β, IL-1ra, IL-2, IL-4, IL-5, IL-6, IL-7, IL-9, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-17A, IL-17-E/IL-25, IL-17F, IL-18, IL-27, IFNα, IFNγ, TNFα, TNFβ); chemokines (CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROα, CXCL8/IL-8, CXCL9/MIG, CXCL10/IP-10, CX3CL1/Fractalkine) and growth factors (EGF, FGF-2, Flt-3L, G-CSF, M-CSF, PDGF-AA, PDGF-AB/BB, TGF-α, VEGF-A) by multiplex analysis based on xMAP technology. Nonparametric statistics methods were used for statistical analysis. As a result of the study, increased concentrations of cytokines IL-12 (p40), IL-15, IL-17E/IL-25, IL-27, IFNγ, TNFα, chemokines CXCL9/MIG and CXCL-10/IP-10 and growth factors FGF-2 and M-CSF were found at all stages of liver fibrosis. Elevated concentrations of cytokines IL-1α, IL-1β, IL-2, IL-6, IL-9, IL-10, IL-17F, IFNα, TNFβ, chemokines CCL2/MCP-1, CCL11/Eotaxin, CCL22/MDC and growth factors G-CSF, TGF-α, Flt-3L were found in severe liver fibrosis/cirrhosis. Correlation analysis revealed a relationship of high significance between the severity of liver fibrosis and the content of cytokines IL-6, IFNγ, TNFα, IL-7, chemokines CCL2/MCP-1, CCL11/Eotaxin, CXCL9/MIG, CXCL10/IP-10, CXCL1/GROα, growth factors TGF-α, PDGF-AA, PDGF-AB/BB. Thus, a certain profile of cytokines characteristic for CHC was revealed, cytokines, chemokines and growth factors significant for liver fibrosis in CHC were found.

The state of rheological properties of blood in pregnant smokers with chronic nonspecific bronchial inflammation

Aim. To evaluate the effect of smoking on the blood rheology of pregnant smokers with chronic nonspecific bronchial inflammation. Materials and methods. The prospective study included 107 pregnant smoking patients and 136 non-smoking pregnant women who were observed in a polyclinic. The control group consisted of 42 non-smoking women without chronic diseases. The patients were examined according to the clinical guidelines for the treatment of chronic obstructive pulmonary disease. The speed and volume indicators of the function of external respiration, indicators of blood rheology were studied. The reliability of the results was assessed using the methods of parametric and nonparametric statistics. Before applying all statistical research methods, it was checked whether the sample obeys the Gaussian (normal) distribution law. A single-factor analysis of variance was used to determine whether there was a statistically significant difference between the averages of three or more independent groups. Results. Having refuted the null hypothesis about the absence of the effect of smoking on hemoglobin, using the Student's t-test method for dependent samples, it was established. Conclusion. The longer the period of tobacco use lasted, the more likely it was to develop changes in the viscosity qualities of blood, which undoubtedly affected the condition of patients and the fetus.

A Child-Centred Design Evaluation of a Learning Game to Improve Children’s Legal Capability

Children lack awareness and understanding of their rights and the law. There is a need to address this gap and empower children to become advocates for their rights when they encounter law-related issues. A promising approach to achieving this is through the use of games. In particular, games focused on learning have evolved into novel tools that can raise awareness as well as help children acquire essential skills. In this paper, we present a child-centred design approach to evaluating the initial version of a learning game designed to help children across a wide age range (3-15 years) and with diverse characteristics, improve their legal knowledge, skills, and confidence. This study supports the integral role and value of child participation in testing the usability of a law-based learning game and shaping its design. A mixed methods approach, grounded in user-centred principles, was employed to assess the first prototype (P1) of the game. 45 children from various schools and early years settings in South Yorkshire and the Midlands, UK were involved. This included children from: 1) advisory groups, 2) case study groups, and 3) game development groups, with an age range of 4 to 16 years old. School staff were also invited to give their feedback. Quantitative and qualitative data were gathered through questionnaires, and field note observations, and analyses were conducted through both thematic analysis and non-parametric statistical methods. We found the game was received positively overall, but further development was needed to make it accessible and engaging, especially for the youngest participants. Importantly, participants of diverse ages and characteristics shared valuable insights into enhancements to make the game more intuitive, interactive, and enjoyable, and these findings informed the development of the beta version of the game.

Combined proteomics and metabolomics analysis reveal the effect of a training course on the immune function of Chinese elite short-track speed skaters.

The aim of this study was to combine proteomics and metabolomics to evaluate the immune system of short-track speed skaters (STSS) before and after a training course. Our research focused on changes in urinary proteins and metabolites that have the potential to serve as indicators for training load. Urine samples were collected from 21 elite STSS (13 male and 8 female) of the China National Team before and immediately after one training course. First-beat sports sensor was used to monitor the training load. Proteomic detection was performed using a Thermo UltiMate 3000 ultra high performence chromatographynano liquid chromatograph and an Orbitrap Exploris 480 mass spectrometer. MSstats (R package) was used for the statistical evaluation of significant differences in proteins from the samples. Two filtration criteria (fold change [FC] > 2 and p < 0.05) were used to identify the differential expressed proteins. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis for differential proteins was performed to identify the pathways involved. Nontargeted metabolomic detection was performed using ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS_) with an ACQUITY 2D UPLC plus Q Exactive (QE) hybrid Quadrupole-Orbitrap mass spectrometer. Differential metabolites were identified using non-parametric statistical methods (Wilcox's rank test). Two filtration criteria (FC > 1.2 and p < 0.05) were used to identify differential metabolites. Combined analysis of proteomic and metabolomics were performed on the "Wu Kong" platform. Correlation analysis was performed using Spearman's rank correlation coefficient. (1) The most upregulated proteins were immune-related proteins, including complement proteins (C9, C4-B, and C9) and immunoglobulins (IgA, IgM, and IgG). The most downregulated proteins were osteopontin (OPN) and CD44 in urine. The correlation analysis showed that the content of OPN and CD44 (the receptor for OPN) in urine were significantly negatively correlated with the upregulated immune-related proteins. The content of OPN and CD44 is sex-dependent and negatively correlated with the training load. (2) The most upregulated metabolites included lactate, cortisol, inosine, glutamine, argininosuccinate (the precursor for arginine synthesis), 3-methyl-2-oxobutyrate (the catabolite of valine), 3-methyl-2-oxovalerate (the catabolite of isoleucine), and 4-methyl-2-oxopentanoate (the catabolite of leucine), which is sex-dependent and negatively correlated with OPN and CD44. (3) The joint analysis revealed five main related pathways, including the immune and innate immune systems. The enriched immune-related proteins included complements, immunoglobulins, and protein catabolism-related proteins. The enriched immune-related metabolites included cAMP, N-acetylgalactosamine, and glutamate. (4) There is a significant negative correlation between the content of OPN and CD44 in urine and the training load. One training course can lead to the activation of the immune system and a sex-dependent decrease in the content of OPN and CD44. Training load has a significant and negative correlation with the content of OPN and CD44, suggesting that OPN and CD44 could be potential indicators for training load.

단기 마음챙김기반 집단상담이 마음챙김과 스트레스에 미치는 영향

This study aimed to examine the effects of short-term mindfulness-based group counseling on mindfulness and stress. To achieve this, a short-term mindfulness-based group counseling program was conducted for the general public, and its effects on mindfulness and stress were investigated. Participants were recruited from the Busan area, and a total of 17 individuals participated in the experiment. Among them, 8 were assigned to the experimental group, while 9 were assigned to the control group. The participants in the experimental group underwent short-term mindfulness-based group counseling for five weeks, with one session per week, each lasting two hours. For data collection, a pre-test was conducted before the group counseling for both the experimental and control groups, followed by a post-test after the counseling, and a follow-up test five weeks after the completion of the group counseling. To measure changes in mindfulness, Park Seong-hyun's mindfulness scale was used, and to measure changes in stress, the psychosocial stress scale was employed. The collected data were analyzed using the generalized estimating equations, a non-parametric statistical method. The results showed that while the changes in mindfulness due to the short-term mindfulness-based group counseling were not significant, there was a significant improvement in stress levels. Finally, implications of the findings were presented.

Exploring exhaled breath volatile organic compounds in occupational asthma: a pilot cross-sectional study

Occupational asthma (OA) is divided into allergic asthma (AA) and irritant-induced asthma (IIA). IIA can be divided further into three different phenotypic subtypes. Volatile organic compounds (VOCs) in exhaled breath can reflect metabolic changes in the body, and a wide range of them have been associated with various diseases in the last two decades. This is the first known study to explore breath VOCs in subjects with OA, aimed to identify potential biomarkers to distinguish OA from healthy controls, as well as between different OA subgroups. In a cross-sectional investigation, exhaled breath from 40 patients with OA and 45 respiratory healthy healthcare workers were collected with ReCIVA® Breath Sampler. Samples were analyzed through an untargeted approach using thermal desorption-gas chromatography mass spectrometry (TD-GC-MS), and VOCs were identified according to tier classification. The data underwent analysis using both non-parametric and parametric statistical methods. 536 VOCs were identified. Significance (p<0.05) was observed in several emitted VOCs. Among these, compounds such as 1-hexadecanol, 2,3-butanediol, xylene, phenol, acetone, 3-methylhexane, methylcyclohexane, and isoprene have biological implications or are associated with exposures linked to OA. These VOCs may reflect metabolic changes in the body and the microbiome, as well as external exposures due to occupation.&#xD;In particular, 1-hexadecanol, 2,3-butanediol, xylene and phenol are associated with reduced nicotinamide adenine dinucleotide (NADH) and production of reactive oxygen species (ROS), mechanisms that can be linked to asthmatic diseases and therefore suggests its potential as biomarkers. This study demonstrates that VOCs detected in exhaled breath could serve as indicators of occupational exposure and enhance diagnostic accuracy for asthma.&#xD.

Integrating Sustainability and Circular Economy into Consumer-Brand Dynamics: A Saudi Arabia Perspective

This study examines the evolving consumer-brand dynamics within Saudi Arabia, particularly focusing on the integration of sustainability into consumer preferences and brand loyalty. Utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) and non-parametric statistical methods, this research is anchored in Consumer Culture Theory (CCT) and Self-Congruence Theory, exploring how brand personality and consumer self-congruence influence sustainable consumption behaviors and the adoption of circular economy practices among Saudi consumers. The findings reveal a significant correlation between brand loyalty and sustainable purchase decisions, underscoring the pivotal role of brand identity in fostering eco-conscious consumer choices. Additionally, the research highlights a nuanced landscape of brand loyalty, where attributes, such as social responsibility, though currently less influential, present opportunities for brands to align more closely with consumer values and national sustainability goals. The study also identifies demographic factors, such as age and income level, as significant influencers of sustainable purchasing decisions. This study provides insights into the generational shift towards environmental awareness and the implications for businesses and policymaking within the context of Saudi Arabia’s Vision 2030.

Assessment of water quality and identification of priority areas for intervention in Guanabara Bay basin, Rio de Janeiro, Brazil, using nonparametric and multivariate statistical methods.

The Guanabara Bay hydrographic region (GBHR) has served as a central hub for human settlement and resource utilization throughout Brazil's history. However, the region's high population density and intense industrial activity have come at a cost, leading to a significant decline in water quality. This work aimed to identify homogeneous regions in GBHR according to water quality parameters in dry and rainy periods. The following water quality monitoring variables were monitored at 49 gauge stations: total phosphorus (TP), nitrate (NO3-), dissolved oxygen (DO), hydrogenionic potential (pH), turbidity (Turb), thermotolerant coliforms (TCol), total dissolved solids (TDS), biochemical oxygen demand (BOD), water temperature (Tw), and air temperature (Ta). The statistical analysis consisted of determining principal components, cluster analysis, seasonal differences, and Spearman's correlation. The water quality parameter correlations were not expressively influenced by seasonality, but there are differences in the concentrations of these parameters in the dry and rainy periods. In the dry period, urban pressure on water quality is mainly due to fecal coliforms. The resulting clusters delimited areas under urban, agricultural, and forestry influence. Clusters located in areas with high demographic density showed high concentrations of TCol and TP, while clusters influenced by forestry and agriculture had better water quality. In the rainy season, clusters with urban influence showed problems with TCol and TP, in addition to some characteristics in each group, such as high TDS, NO3-, and BOD. Forested areas showed high DO, and clusters under agricultural influence had higher concentrations of TCol, BOD, and NO3- concerning forested regions. The troubling state of sanitation in GBHR occurs in metropolitan regions due to lack of a formal sanitation system.

ASSESSMENT OF THE RELATIONSHIP BETWEEN THE CONCENTRATION OF PSGL-1, NO-SYNTHASES AND NITRIC OXIDE METABOLITES IN THE BLOOD SERUM OF PATIENTS WITH ACUTE ARTERIAL THROMBOSIS

Introduction. PSGL-1 is a complex protein, that provides contacts between blood cells and endothelial cells by connecting with cell-adhesion mole-cules selectins, and it is a universal participant in the processes of leukocyte adhesion, inflammation and immune response. The study of the possible regulation of its functioning is an urgent topic, since the process of its interactions with selectins can be a point of therapeutic application. Aim of the study. Evaluation of the relationship between the concentration of universal ligand selectins PSGL-1, inducible (iNOS) and endothelial (eNOS) NO synthases and final metabolites of nitric oxide (II) in the blood serum of patients with acute arterial thrombosis. Material and methods. The concentrations of PSGL-1, iNOS and eNOS in blood serum were determined, using enzyme immunoassay on an enzyme immunoassay analyzer Stat Fax 2100. The total concentration of the final stable metabolites of nitric oxide(II) (nitrates and nitrites) was determined by the spectrophotometric method modified by V.A. Metelskaya, by coloring in the reaction of diazotization with nitrite of sulfonamide present in the com-position of the Griss reagent. The results were processed, using nonparametric statistics methods of Microsoft Office Excel 2016 and IBM SPSS Statistics 26 (StatSoftInc., USA). Results. The study revealed a statistically significant increase in the level of endothelial nitric oxide synthase and the final stable metabolites of nitric oxide in the blood of patients with acute arterial thrombosis, compared with the control group. A direct correlation of moderate severity was also found between the level of eNOS and the concentration of nitrates and nitrites. A low positive correlation was found between the concentration of PSGL-1 and the level of eNOS, and a low negative correlation was found between PSGL-1 and iNOS. Conclusions. According to the results of the study, it can be concluded that nitric oxide, which generated by endothelial NO synthase in patients with arterial thrombosis, may have a regulatory effect on the expression or functioning of the universal glycoprotein ligand of selectins – PSGL-1, which re-quires more in-depth study.

Rainfall Trend Analysis in Mysuru and Bengaluru Districts of Karnataka, India

Climate change is one of the most pressing challenges facing humanity today, with temperature, precipitation, and runoff being key indicators closely linked to its impact. Understanding the spatial variability and temporal trends of rainfall is crucial for effective water resource management and agriculture. This study focuses on analyzing rainfall data from the Mysuru and Bengaluru districts, located in the Southern and Eastern dry zones of Karnataka, respectively. These regions play a pivotal role in the state's agricultural development and overall economic growth. We utilized daily precipitation records from two meteorological stations, spanning the period from 1983 to 2018, to analyze rainfall trends on monthly, seasonal, and annual scales. To assess these trends, we applied both parametric and non-parametric statistical methods, including the simple regression method, Mann-Kendall test, and Sen’s slope estimator. The Mann-Kendall test was used to detect significant trends in the precipitation time series, while Sen’s slope estimator quantified the magnitude of these trends. Bengaluru had higher average annual rainfall (928.81 mm) compared to Mysuru (681.65 mm), with excess rainfall in 2005 and a positive Pre-Monsoon trend (+3.543 mm/year), while Mysuru experienced maximum rainfall deficit in 2016 and a negative Monsoon trend (-3.238 mm/year). Neither district showed a significant trend in annual rainfall. The findings of this trend analysis are essential for informed water resource planning and management in the region.

A Dunnett-Type Test and Its Sample Size Calculation for Comparing K ROC Curves with a Control.

Diagnostic biomarkers are key components of diagnostics. In this paper, we consider diagnostic biomarkers taking continuous values that are associated with a dichotomous disease status, called malignant or benign. The performance of such a biomarker is evaluated by the area under the curve (AUC) of its receiver operating characteristic curve. We assume that, together with the disease status, one control and multiple experimental biomarkers are collected from each subject to test if any of the experimental biomarkers have a larger AUC than the control. In this case, each experimental biomarker will be compared with the control so that a multiple testing issue is involved in the comparisons. In this paper, we propose a simple non-parametric statistical testing procedure to compare K(≥2) experimental biomarkers with a control, adjusting for the multiplicity and its sample size calculation method. Our sample size formula requires the specification of the AUC values (or the standardized effect size of each biomarker between the benign and malignant groups) together with the correlation coefficients between the biomarkers, the prevalence of the malignant group in the study population, the type I error rate, and the power. Through simulations, we show that the statistical test controls the overall type I error rate accurately and the proposed sample size closely maintains the specified statistical power.

Machine Learning Prediction of Autism Spectrum Disorder From a Minimal Set of Medical and Background Information

Early identification of the likelihood of autism spectrum disorder (ASD) using minimal information is crucial for early diagnosis and intervention, which can affect developmental outcomes. To develop and validate a machine learning (ML) model for predicting ASD using a minimal set of features from background and medical information and to evaluate the predictors and the utility of the ML model. For this diagnostic study, a retrospective analysis of the Simons Foundation Powering Autism Research for Knowledge (SPARK) database, version 8 (released June 6, 2022), was conducted, including data from 30 660 participants after adjustments for missing values and class imbalances (15 330 with ASD and 15 330 without ASD). The SPARK database contains participants recruited from 31 university-affiliated research clinicals and online in 26 states in the US. All individuals with a professional ASD diagnosis and their families were eligible to participate. The model performance was validated on independent datasets from SPARK, version 10 (released July 21, 2023), and the Simons Simplex Collection (SSC), consisting of 14 790 participants, followed by phenotypic associations. Twenty-eight basic medical screening and background history items present before 24 months of age. Generalizable ML prediction models were developed for detecting ASD using 4 algorithms (logistic regression, decision tree, random forest, and eXtreme Gradient Boosting [XGBoost]). Performance metrics included accuracy, area under the receiver operating characteristics curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and F1 score, offering a comprehensive assessment of the predictive accuracy of the model. Explainable AI methods were applied to determine the effect of individual features in predicting ASD as secondary outcomes, enhancing the interpretability of the best-performing model. The secondary outcome analyses were further complemented by examining differences in various phenotypic measures using nonparametric statistical methods, providing insights into the ability of the model to differentiate between different presentations of ASD. The study included 19 477 (63.5%) male and 11 183 (36.5%) female participants (mean [SD] age, 106 [62] months). The mean (SD) age was 113 (68) months for the ASD group and 100 (55) months for the non-ASD group. The XGBoost (termed AutMedAI) model demonstrated strong performance with an AUROC score of 0.895, sensitivity of 0.805, specificity of 0.829, and PPV of 0.897. Developmental milestones and eating behavior were the most important predictors. Validation on independent cohorts showed an AUROC of 0.790, indicating good generalizability. In this diagnostic study of ML prediction of ASD, robust model performance was observed to identify autistic individuals with more symptoms and lower cognitive levels. The robustness and ML model generalizability results are promising for further validation and use in clinical and population settings.

Anatomical requirements for dacryocystorhinostomy ostium patency.

To identify anatomical factors affecting the outcome of dcryocystorhinostomy (DCR). The study included the results of dacryocystography in 73 patients after DCR: 37 cases of failed DCR and 36 cases of successful DCR. Biometric characteristics of the formed ostium were evaluated: the horizontal size of the bony "window" and the soft tissue part of the ostium, the vertical size of the bony "window" and soft tissue ostium, the height of the fragment of the remaining bone above and below the line of the common canaliculus, and the height of the "pocket" formed below the lower edge of the ostium. Statistical analysis was performed using parametric and non-parametric statistical methods. Differences were considered significant at p ≤ 0.05. Intergroup differences were identified in the values of the maximum horizontal size of the bony "window" (p = 0.015), the maximum horizontal size of the soft tissue "window" (p < 0.001), the maximum vertical size of the soft tissue "window" (p < 0.001), and the height of the fragment of the remaining bone below the level of the common canaliculus to the edge of the formed ostium (p = 0.004). The stage of forming the bony "window" influences the success of DCR. Not only the position of the "window" is important, but also the geometric properties of the formed ostium.

Level of some matrix metalloproteinases in blood serum in relation to their genetic polymorphism depending on age

The article presents data on the state of the proteolysis system and genes for the regulation of matrix metalloproteinases in 180 conditionally healthy women and men of young, middle, elderly and senile ages. A single sampling of the material (buccal epithelium) was performed in patients. PCR examination of the buccal epithelium for the analysis of polymorphisms of the genes MMP-1 rs1799750 and MMP-3 rs 3025058 was carried out on the instrument base of the DNA amplifier Bio-Rad CFX96. Serum levels of MMP-1, MMP-3 were studied by the sandwich variant of solid-phase enzyme immunoassay. Statistical processing of the obtained results was carried out using the IBM SPSS Statistics 26 program using nonparametric statistics methods. The results of the study. The values of MMP-1 and MMP-3 in the group of conditionally healthy women at a young age were lower than the values of middle age, whereas in old age their serum levels varied in different directions: MMP-1 decreased, and MMP-3 increased. When analyzing polymorphisms of the MMP-1 rs1799750 gene, the homozygous genotype -/- with low expression of the MMP-1 gene prevailed in young and middle-aged women, and in women over 75 years of age, the carriage of the G/G homozygote with active gene expression was recorded. When evaluating the expression of the MMP-3 rs 3025058 gene, it was found that young women significantly more often had 5A/5A polymorphism with high gene activity, but with a lower level of MMP- 3. In middle and old age, 65% have a heterozygous 5A/6A allele with reduced gene expression activity. In conditionally healthy men, the level of MMP-1 in blood serum increased in the middle-aged and senile groups, the values of MMP-3 in the group under 45 years of age were low compared with the elderly group (p = 0.041). MMP-1 rs1799750 in men under 75 years of age was identified in the -/G variant in the majority. Homozygous polymorphism of the MMP-3 rs 3025058 5A/5A gene with high activity of MMP-3 prevailed in groups of men under 60 years of age with serum levels of MMP-3 100.2 ng/mL and 92.5 ng/mL, respectively.

Hip Circumferential Labral Reconstruction Provides Similar Distractive Stability to Labral Repair After Cam Over-Resection in a Biomechanical Model

To evaluate the change in hip distractive stability after a cam over-resection, labral tear, repair, labrectomy, or circumferential 6- or 10-mm labral reconstruction in a biomechanical model. Ten fresh-frozen matched-pair human cadaveric hips were analyzed using a materials testing system to measure the force and distance required to disrupt the suction seal of the hip (1) with an intact capsule and labrum; (2) after a capsulectomy and labral repair; (3) after a capsulectomy, 5-mm cam over-resection and labral repair; (4) after a capsulectomy, 5-mm cam over-resection and labral tear; (5) after a capsulectomy, 5-mm cam over-resection and labrectomy; and (6) after a capsulectomy, 5-mm cam over-resection and a 6- or 10-mm circumferential labral reconstruction with iliotibial band (5 hips each). Each specimen was retested at 0° flexion, 45° flexion, and 45° flexion and at 15° internal rotation and analyzed using nonparametric statistical methods. The Friedman test of differences was significant among structural conditions and hip positions (P= .001). In all positions, the resistive force that opposed the disruption of the suction seal in an intact hip was significantly greater compared with all other conditions. The resistive force for the capsulectomy, 5-mm cam over-resection and labrectomy condition was significantly less compared with almost all other conditions and hip positions. A qualitative suction seal was achieved in 20% of hip specimens with a 6-mm labral reconstruction, whereas a seal was in achieved 60% of specimens with a 10-mm labral reconstruction. After a cam over-resection, a circumferential labral reconstruction improves the distractive stability of a labral deficient hip, comparable to a labral repair or tear in a biomechanical model. Circumferential labral reconstruction may be a viable treatment option for patients with ongoing symptoms after hip arthroscopy with evidence of a cam over-resection and a deficient labrum.