Correlation Analysis Research Articles

Evaluation of Rain Shelter Cultivation Mode Effects on Microecological Environment of Mountain Cultivated Ginseng Rhizosphere

Rainfall, particularly in continental climates with a monsoonal tendency, impacts the microbial niches during the growth of mountain cultivated ginseng. With shifts in the microbial community, diseases in ginseng cultivated and protected under rain shelter conditions may ultimately be altered. Such cultivation may influence microflora dynamics through variations in meteorological parameters; however, this is not yet clear. The present study found that rain shelter cultivation affected the distribution of fungal communities within mountain cultivated ginseng. This led to an improved community structure in the ginseng rhizosphere, characterized by the proliferation of antagonistic fungi and a reduction in pathogenic fungi. A correlation analysis of meteorological factors found that soil temperature and humidity were the primary meteorological factors affecting mountain cultivated ginseng. It is evident that rain shelter cultivation regulated the microecological environment of the mountain cultivated ginseng’s rhizosphere and resulted in positive outcomes. A disease investigation supported this finding. The incidence of ginseng root diseases, such as rust and root rot, was reduced by 5–6%. The incidence of ginseng leaf diseases, including gray mold and black spot, was reduced by 5–10%. This research provides evidence to address the dynamics of microbial ecology under rain shelter cultivation and its benefits for sustainable mountain cultivated ginseng management.

Exploring Kinematic Variations in Clear Hip Circle to Handstand: A Case Study of Performance Styles on Uneven Bars

(1) Background: This case study analyzed the successful performances of female gymnasts in the finals of the 39th and 40th World Cup in Maribor (SLO). The aim was to identify variations in their execution of the Clear Hip Circle to Handstand (CHCH) on uneven bars based on kinematic parameters. (2) Methods: This study involved elite female gymnasts from the 39th (n = 5, age: 17 ± 6 months) and 40th (n = 8, age: 17.5 ± 6 months) World Cups, totaling 13 gymnasts. Kinematic analysis was performed on 15 successful routines using the Ariel Performance Analysis System (Ariel Dynamics Inc., San Diego, CA). The analysis focused on 16 anthropometric reference points and 8 body segments, including the body mass center of gravity (CG). The main reference points analyzed were the hip joint, the shoulder joint, and the CG along the xy-axes. Trajectory, velocity, angle, and angular velocity of the hips and shoulders were calculated. Pearson correlation analysis was employed to assess the relationships between the kinematic variables. (3) Results: High intercorrelations between the reference points along the xy-axes (0.81–0.99) and optimal movement velocity were found. Dispersed results were observed for kinematic parameters of angle (0.10–0.16) and angular velocity of the hip joints (0.60–1.00), with similar dispersions for shoulder joints (0.51–1.00). Three distinct techniques were identified: (1) stretched body with minimal hip joint flexion throughout; (2) extended body with a short, quick hip joint extension during shoulder movement; and (3) hyperextension in the hip joint. (4) Conclusions: The kinematic analysis revealed three different performance styles of the CHCH among finalists. These variations in technique do not affect the success of the performance. This research contributes to a better understanding of the technique but does not prefer one style over another.

Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on 18F-FDG PET/CT

ObjectiveTo investigate the value of 18F-FDG PET/CT-based intratumoral and peritumoral radiomics in predicting the efficacy of neoadjuvant chemotherapy (NAC) for breast cancer.Methods190 patients who met the inclusion and exclusion criteria from 2017 to 2022 were studied. Features were extracted from the PET/CT intratumoral and peritumoral regions, feature selection was performed through the correlation analysis, t-tests, and least absolute shrinkage and selection operator regression (LASSO). Four classifiers, support vector machine (SVM), k-nearest neighbor (KNN), logistic regression (LR), and naive bayes (NB) were used to build the prediction models. The receiver operating characteristic (ROC) curves were plotted to measure the predictive performance of the models. Concurrent stratified analysis was conducted to establish subtype-specific features for each molecular subtype.ResultsCompared to intratumoral features alone, intratumoral + peritumoral features achieved higher AUC values in each classifier. The SVM model constructed with intratumoral + peritumoral features achieved the highest AUC values in both the train and test set (train set: 0.95 and test set: 0.83). Subtype-specific features improve performance in predicting the efficacy of NAC (luminal group: 0.90; HER2 + group: 0.86; triple negative group: 0.92).ConclusionIntratumoral and peritumoral radiomics models based on 18F-FDG PET/CT can reliably forecast the efficacy of NAC, thereby assisting clinical decision-making.

The effect of the menstrual cycle phases on back squat performance, jumping ability and psychological state in women according to their level of performance -a randomized three-arm crossover study

ObjectiveThe influence of the menstrual cycle on practical power performance such as barbell back squats and jumping performance in women has not yet been fully investigated. In addition, the performance level of athletes has not been considered in previous studies. This study aimed to investigate the influence of different cycle phases on acute back squat performance, jumping ability and psychological state concerning the performance level.Methods24 female strength athletes (age: 25.2 ± 3.3 years; height: 169.5 ± 3.4 cm; body weight: 67.7 ± 7.3 kg) were recruited for the study. Level of performance was classified according to Santos et al. (intermittent (n = 13), advanced (n = 6), highly advanced (n = 5)). Participants were tested for 1RM barbell back squat and jumping performance (countermovement and squat jump) as well as two questionnaires assessing their psychological states in the menses (M), late follicular phase (FP) and mid-luteal phase (LP) in three MC. Saliva estradiol and progesterone concentrations with a menstrual cycle diary were used to confirm a normal MC. A principal components analysis for power performance, well-being, relaxation and alertness was carried out and a linear mixed model was used for statistical evaluation.ResultsNo significant differences were found between the MC phases in performance scores (p > 0.05), readiness (p > 0.05) and alertness (p > 0.05). However, a high correlation between MC phases, performance level and back squat performance was detected. Correlation analyses indicate that a higher performance level results in a higher variation depending on the MC of the squat performance. For well-being, a significantly lower score was detected in M than in FP and LP.ConclusionIn general the performance score of the lower body is not influenced by the MC. If strength performance and jumping ability are considered separately, there are indications that strength capability is influenced at a higher performance level. In addition, individual variance was also observed, so this should also be considered. However, further studies are needed to confirm this assumption due to the small sample sizes of the individual performance levels.Trial registrationGerman registry for clinical studies (DRKS00034816, Date: 08/01/2024).

Assessing the state of cognitive performance of employees and determining the range of thermal comfort of different genders in Ilam hospitals

Introduction: Thermal comfort is essential for a productive work environment and affects the well-being and performance of employees, so maintaining optimal levels of satisfaction, productivity, and efficiency, especially in indoor spaces, is essential. Therefore, the present study's aim is to evaluate the state of cognitive performance. Employees and determination of the thermal comfort range of different genders of employees in the hospitals of Ilam city were done. Methods and Materials: This research was conducted by survey and field method to identify the state of thermal comfort and cognitive performance of people in the real conditions of therapeutic spaces. For this purpose, the responses of 400 employees of five hospitals in Ilam City were recorded by simple sampling from the beginning of August to November 1402. The reliability status of the questionnaires was confirmed using Cronbach's alpha, and the thermal comfort status of the people was determined through the regression model. Linearity and correlation analysis between measured variables were analyzed through SPSS27 software. Results: The analysis of the linear regression model showed that the range of thermal comfort between men and women differs by 1.79 degrees Celsius, and this difference is a tendency for warmer temperatures in men and a tendency for colder temperatures in women, the average scores obtained at Zagros Hospital In the visual-spatial/executive component (7.00), attention (4.34), memory (3.08) has the best performance, Imam Khomeini Hospital (RA) has the best performance in the verbal component (2.95), Hazrat Qaim Hospital (A) In the abstraction component (2.02), it has the best performance and awareness of time and place in all hospitals equal to 6.00. Conclusion: The level of coverage and activity rate among women significantly affects the feeling of thermal comfort, cognitive performance, and productivity of employees at work. The results of this research show the need to revise the current standards of workplace clothing, attendance time, and employee activity rate. Moreover, changes in cognitive performance among hospital staff highlight the need to consider targeted cognitive enhancement strategies to increase staff efficiency.

Studies on Path Coefficient Analysis and Correlation to Evaluate the Relationships between Yield and Its Components in Fenugreek (Trigonella foenum-graecum L.)

The present investigation was carried out for correlation and path coefficient analysis in Fenugreek (Trigonella foenum-graecum L.) The correlation of different traits with seed yield was examined both at phenotypic and genotypic levels and the study showed that genotypic correlation coefficient values were higher than the phenotypic values. This indicated that how much of phenotypic correlation coefficient are influenced by environment. The seed yield per plant was positive and significant with biological yield per plant, test weight and number of branches per plant at genotypic and phenotypic levels. The maximum direct positive effect on seed yield per plant was observed in biological yield per plant, harvest index, days to 50 per cent flowering, number of seed per pod, number of branches per plant and number of pods per plant. In the present investigation, genotypes viz., AFG-4 and RMT-303 were superior for seed yield per plant along with other traits like biological yield, test weight and number of pods per plant. These diverse genotypes can be used in future breeding programme of fenugreek.

Altered serum metabolome is associated with disease activity and immune responses in rheumatoid arthritis.

Rheumatoid arthritis (RA) is widespread globally, with the emergence of metabolites derived from both the host and microbes playing a pivotal role in its pathogenesis. This study aims to elucidate the relationships between serum metabolites and the immunological and clinical features of RA. Serum samples were collected from 35 RA patients and 37 healthy controls (HC). Metabolite profiling was performed using gas chromatography-mass spectrometry (GC/MS). Principal component analysis revealed a significant distinction between the RA and HC cohorts. Employing univariate statistical analysis, we identified 36 differential metabolites. Among these, 9 metabolites, including galactose and glucose, were found to be enriched, while the remaining metabolites, such as citric acid, fumaric acid, and inosine, were depleted in RA. These diverse metabolites encompassed various metabolic processes, including the biosynthesis of fatty acids, amino acids, and glucose. The enrichment of glucose and galactose in RA exhibited a substantial correlation with elevated IgG levels, as determined through correlation analysis. Conversely, the depletion of citric acid was correlated with elevated levels of C3 and CRP. Methionine, which also declined in RA patients, displayed a negative correlation with ESR. Furthermore, galactose and glucose exhibited significant positive correlations with naïve B cells, while the decreased eicosanoic acid level in RA was significantly associated with an increase in natural killer cells. Our findings suggest that the altered serum metabolite profile in RA is closely linked to disease severity and the dysregulated immune responses observed in RA patients. Key Points • Identified nine metabolites with upregulated expression and twenty-seven metabolites with downregulated expression. • Established a correlation between alterations in serum metabolite levels and inflammatory markers in RA patients. • Discovered a significant association between changes in serum metabolites and immune cell profiles in RA patients.

Decoding core genes and intercellular communication in osteosarcoma: bioinformatic investigation and immune cell profiling for diagnostic and therapeutic insights

The study focusing on developing an artificial neural network (ANN) model in accordance with genetic characteristics of osteosarcoma (OS) to accurately speculate OS cases. In the present study, we identified 467 DEGs through differentially acting gene investigation and that 345 exist suppressed and 122 exist stimulated. The resultant of GO enrichment analysis displayed the functions mainly included T cell activation, secretory granule lumen, antioxidant property etc. The pathways identified in the differentially acting genes (DAGs) were greatly interacted with Phagosome, Staphylococcus aureus infection, Human T − cell leukemia virus 1 infection, etc. Next, we found out top ten hub DEGs (HDEGs) by PPI network analysis. In addition, through the validation of ANN itself and Test set samples, it was proved that the prediction performance of our constructed ANN model is accurate and reliable. Finally, the penetration of immune cells and its interaction with target CDEGs were examined, and variations in penetration of 22 types of immune cells amongst different classes were found, additionally correlation amongst immune cells and between immune cells and target CDEGs. Furthermore, we analyzed the expression of the top two CDEGs (YES1 and MFNG) in OS tissues and normal tissues, also the interrelationship among the activity of YES1 and MFNG in OS tissues and clinicopathological properties of OS cases. Furthermore, the correlation analysis between the top two CDEGs and immune infiltrating cells was performed in OS tissues. Our research results revealed that CDEGs-based ANN model is effective at predicting OS patients, which facilitates early diagnosis and treatment of OS.

Diversity of Major Yield Traits and Nutritional Components Among Greenhouse Grown Chickpea (Cicer arietinum L.) Breeding Lines, Landraces, and Cultivars of Different Origins

This study analyzed the diversity of major yield traits and nutritional components across 122 chickpea breeding lines, cultivars, and landraces of different origins. All parameters showed significant variations, with a variance ranging from 4.61% in days to maturity (DM) to 43.04% in oleic acid. Six accessions, including CP021, CP022, CP026, CP037, CP066, and CP109, outperformed in yield traits and nutritional value. Origin significantly affected all phenotypic traits except total fatty acid contents, with Indian and Ukrainian accessions demonstrating contrasting performances. Most traits, except for the number of seeds per pod (SPP), palmitic acid, and total fatty acid contents, differed significantly among breeding lines, cultivars, and landraces. Breeding lines were the earliest to flower and to mature with average days to flowering (DF) of 50.23 days and DM of 101.50 days. They also had the highest average SPP, number of pods per plant (PPP), total seeds per plant (TSPP), total protein, crude fiber, dietary fiber, linoleic acid, and linolenic acid contents making them preferable for high yield and nutrition. Hierarchical cluster analysis classified the chickpea accessions into seven clusters, showing significant variations in yield traits and nutritional components. Principal component and Pearson’s correlation analyses indicated positive correlations between DM and DF, and between SPP, PPP, and TSPP. Nutritional components also displayed varying associations, with a notable negative correlation between oleic and linoleic acids, the two essential fatty acids. Overall, this study showed the diversity of key phenotypic traits in chickpea breeding lines, cultivars, and landraces of different origins. The significant effects of genotype and origin differences on these traits could be used as a basis for future metabolomics and genomics research.

Effect of Psychological Resilience on Posttraumatic Growth Among Midwives: The Mediating Roles of Perceived Stress and Positive Coping Strategies.

To explore the relationship between midwives' psychological resilience and posttraumatic growth, and the mediating role of perceived stress and positive coping strategies. A multicentre cross-sectional survey was used. Data were conducted among 339 midwives from 24 Grade III A hospitals in Sichuan Province from April to July 2023, using the Chinese version of the Connor Davidson Resilience Scale, Chinese version Perceived Stress Scale, Simplified Coping Style Questionnaire, Chinese-Posttraumatic Growth Inventory and General Demographic Data Questionnaire. A descriptive statistical approach, Pearson's correlation analysis and the Mplus 8.3 were used to analyse the available data. There was a significant correlation between psychological resilience, perceived stress, positive coping strategies and PTG. Psychological resilience could have a direct positive impact on PTG of midwives, but it could also indirectly affect PTG of midwives through three pathways: the mediating effect of perceived stress, the mediating effect of positive coping strategies and the chain mediating effect of perceived stress and positive coping strategies. Results suggest that nursing managers should help to improve the psychological resilience of midwives and to reduce individual stress perception, enhance coping abilities and achieve positive growth. Prior to data collection, we obtained approval from the nursing department of each hospital. Midwives who met the inclusion and exclusion criteria gave informed consent and invited to participate in this study. This study was guided by STROBE. During the data collection phase, 349 midwives took the time to carefully answer the questionnaire items related to this study.

Stigmas of dysembryogenesis of undifferentiated connective tissue dysplasia in bronchial asthma

Connective tissue dysplasia is a disturbance of its development during embryogenesis and the postnatal period due to genetically altered fibrillogenesis of the extracellular matrix. Undifferentiated connective tissue dysplasia (UCTD) includes a set of phenotypic characteristics that do not fit into any already known dysplastic syndrome or phenotype. It is this pathology of connective tissue that is widespread and is constantly encountered in the practice of doctors of various profiles, serving as the basis for the formation of various chronic diseases. As for bronchial asthma (BA), it is quite natural that studies have appeared to identify the characteristics of the course of BA with connective tissue dysplasia, primarily in children. It has been shown that asthma in children associated with connective tissue dysplasia has a number of clinical features: an earlier onset of the disease, a higher incidence of concomitant diseases, and a more severe course. The features of the course of bronchial asthma associated with connective tissue dysplasia in adults have been practically not studied. Our very first results from a study of adult patients with BA showed that in patients with a mild course of the disease, up to 3 stigmas of disembryogenesis were recorded, in patients with a moderate course - from 2 to 4, and in patients with a severe course - from 1 to 8 stigmas. Correlation analysis (the data was obtained on a small material, therefore we do not consider it statistically significant) provides a distinct basis for continuing the study. Thus, negative correlations have been identified between the presence of stigmas (myopia, dolichostenomelia, joint hypermobility, wide atrophic scars, varicose veins) and such an important characteristic of the disease as its controllability.

Association of Nursing Home Residents' Demographic and Clinical Attributes and Nursing Home Characteristics With Self-Reported Ratings of Nursing Home Satisfaction.

The current study explored the association of nursing home (NH) residents' demographic and clinical attributes and NH characteristics with resident-reported satisfaction with NH communities. Pearson correlations and multiple linear regression were used to test the association of demographic and clinical attributes of residents and NH characteristics with resident-reported NH satisfaction with 197 NH residents from 28 NHs. Correlational analysis and regressions indicated an association among residents' demographic and clinical characteristics, NH characteristics, and self-reported NH satisfaction. Higher age, higher education, and race (minority status) were associated with greater resident-reported NH satisfaction. Greater NH staffing and for-profit ownership status were associated with less NH satisfaction. Greater resident depressive symptoms and dressing assistance were associated with lower resident-reported NH satisfaction. Administrators and staff should look beyond NH characteristics and consider their residents' diverse personal characteristics to create an environment that promotes satisfaction and well-being. [Journal of Gerontological Nursing, 50(11), 6-12.].

Research on the Influencing Factors of House Prices based on Multiple Linear Regression Model

Abstract. House prices have risen rapidly, and finding the factors affecting house prices is significant for regulating house prices. Existing literature discusses the factors affecting house prices, but does not analyze the key factors affecting house prices and get a good fit with a multiple linear regression model. Therefore, this paper is of practical significance for the selection and fitting of key variables that explain the rise in house prices. In Spearman's correlation analysis, strong correlation and covariance diagnostics were found for gross product. After linear fitting, it is found that gross product, commercial real estate sales area will have an impact on house prices. The results of this paper on the impact of GDP and commercial real estate sales area on housing prices are conducive to the relevant agencies to take measures to adjust housing prices. At the same time, for people who have the need to buy a house, understanding the main influencing factors is conducive to consumers' initial judgment on the trend of house prices, and then make a decision.

Split tensile strength of fiber-reinforced coral aggregate concrete: Deep learning model and experimental validation

Machine learning methods are increasingly becoming an important research field for solving the complex mechanical behavior of concrete materials. A reliable deep learning model was developed based on a dataset consisting of 319 experimental data points to predict the split tensile strength of fiber-reinforced coral aggregate concrete (FRCAC). The feature selection was carried out using correlation analysis, and the neural network structure was optimized by adjusting hyperparameters based on the 10-fold cross-validation (CV). Subsequently, six statistical indicators were employed to evaluate the accuracy and generalization ability of the model. The deep neural network (DNN) model demonstrates excellent performance, with R2, MAE, and MAPE of 0.98, 0.181 MPa, and 0.037 for the training dataset and 0.95, 0.286 MPa, and 0.074 for the test dataset, respectively. Additionally, 24 sets of concrete proportions are designed using the trained DNN model, and the results indicate that the absolute error and relative error between predicted and experimental values are less than 0.4 MPa and 6.8 %, respectively. The feature analysis based on SHapley Additive exPlanations (SHAP) reveals that volume fraction, curing age, water-binder ratio, and the tensile strength of fiber have the highest contribution in estimating the split tensile strength of FRCAC. This research can provide a reference for optimizing the design of FRCAC.

Construction and application of the multidimensional quantitative model for game evaluation

Abstract. This article is a modeling study on the self-rating of board games. This article has reviewed and understood board games and various indicators of board games and stated the background of the topic and the questions raised. It has determined the dimensions of game characteristics that need to be evaluated. Through keyword retrieval, the text is transformed into the required numerical information, and through public calculation, the required data is obtained to fit the geek ratings and average player ratings of the 25 games in the target. Next, analyze the specific issues of each data through descriptive statistics. Then, through correlation analysis, which indicators are related were obtained, and a series of conclusions were drawn. Next, a second linear regression analysis will be conducted on the Geek rating and average rating, and a series of conclusions will be drawn. Summarize the conclusion, consider the advantages of the model, and reflect on the shortcomings of the model. Use sensitivity analysis to check if the conclusion is complete. This article randomly selected a game and analyzed it through a model. And draw relevant conclusions. Finally, the analysis and summary improved the modeling.

The Relationship Between Coping and Stress Levels in Students from The Class of 2020 at The Faculty of Medicine, Palangka Raya University, During Their Thesis Preparation

Introduction: Academic stress is prevalent among final-year students, with thesis preparation being a significant source of this stress. Coping are essential as they effectively represent the body’s conscious adaptive responses to reduce stress through self-adaptation. This research determines the relationship between coping and stress levels in students from the class of 2020 at the Faculty of Medicine, Palangka Raya University, during their thesis preparation. Methods: The study employs a quantitative analytical observational design with a cross-sectional approach. Simple random sampling was utilized for participant selection. The research instruments comprised coping questionnaires and the Perceived Stress Scale (PSS-10). Data were analyzed using Charles Spearman’s correlation analysis with a confidence interval of 95%. Results: Out of all 96 respondents, 49 individuals (51%) had good coping skills, and 80 individuals (83.3%) experienced moderate stress levels. Notably, among the 49 participants exhibiting good coping, a majority (42 individuals or 85.71%) experienced moderate stress levels. The Charles Spearman test findings revealed a significant value of 0,013 (p < 0.05) with a weak correlation and the opposite direction (r = -0.252). Conclusion: There is a significant relationship between coping and stress levels in students from the class of 2020 at the Faculty of Medicine, Palangka Raya University, during their thesis preparation.

Pre-service teachers’ pedagogical knowledge and attitudes towards slow learner students

The pedagogical knowledge and acceptance of pre-service teachers towards slow learner students contribute to the implementation of inclusive education in regular schools. This study investigates the level of knowledge and acceptance pre-service teachers have in applying effective teaching strategies for students with slower learning needs. The participants of this study were 187 students at a private university in. This research is ex-post facto research. The research instrument used was a pedagogical knowledge test and attitude questionnaire. The data obtained were analyzed using correlation analysis, and t-test, to determine the relationship between pedagogical knowledge and attitudes towards slow learner students. The finding reveals that there was a positive relationship between pedagogical knowledge and attitudes towards slow learners, but the correlation between the two is not strong, in the medium category. Pre-service teachers gain pedagogical knowledge from inclusive education courses. Pre-service teachers also form a positive attitude towards slow learner students because of their experience interacting with slow learner students. A strong correlation between the variables in this study suggests that pre-service teachers' pedagogical knowledge has a limited impact on their attitudes toward slow learners. This highlights the need for improved training in effective teaching strategies for slow learners.

Time-dependent electroretinogram, metabolomics and lipidomics screened metabolic markers for monitoring the process of diabetic retinopathy from scratch.

Diabetic retinopathy (DR) is a severe complication of diabetes mellitus (DM), and it is challenging to diagnose DR at an early stage by conventional methods. The aim of the present work is to propose an innovative approach to monitor the process of DR from scratch. The plasma metabolites changed with DM were obtained by time-dependent metabolomics and lipidomics; the change of retinal function was measured by b-wave amplitude and total Ops-wave amplitude in electroretinography (ERG). Multivariate statistical analysis, logistic regression and correlation analysis were employed to identify metabolic markers from metabolites for the monitoring of DR and investigate the relationship between metabolic markers and retinal function. The metabolic markers LPE18:0, LPC15:0, SM d14:2/26:0, SM d12:0/28:2 and MG 21:0 associated with DR can be utilized as metabolic markers to monitor the process of DR; The decrease in myo-inositol and LPC22:5 and increase in xylonic acid and TAG10:0/16:0/18:1 indicated retinal dysfunction. The levels of metabolic markers can be used as an indicator of the onset of DR or as a means of monitoring changes in retinal function.

Sex-Specific Associations Between Leucocyte Measures and Obstructive Sleep Apnea in Han Chinese.

White blood cell (WBC) and its subset counts are standard, inexpensive, direct markers of inflammation. Obstructive sleep apnea (OSA) is implicated in changes in inflammation markers, and sex differences are evident in both OSA and inflammation. It is unknown whether sex modulates the relationship between OSA severity and leukocyte measures. 1222 patients (914 males, 308 females) underwent overnight laboratorial polysomnography and measurement of WBC and its subset (lymphocyte, neutrophil, monocyte) counts. Patients were divided into primary snoring and mild, moderate, and severe OSA groups, and differences in leukocyte parameters were analyzed separately by sex in multivariable analyses. In multiple regression models, higher apnea-hypopnea index (AHI) was independently associated with neutrophil counts only in men, and with higher total WBC, lymphocyte and monocyte counts both in women and men. Further ordinal logistic regression analysis revealed a significant association between AHI and total WBC (OR 1.87, 95% CI 1.09-3.23) and neutrophil (OR 1.77, 95% CI 1.02-3.07) counts in men only. Correlation analysis also revealed more robust relationships between leukocyte measures and cardiometabolic risk markers in men than in women. This study provides novel data suggesting a significant association between neutrophil count and OSA severity only in men but not women. Similarly, the relationship between leukocyte parameters and cardiometabolic risk markers were more pronounced in men than women. Our findings suggest a sex-specific impact of OSA on leukocyte measures and on their relationship with indices of cardiometabolic risk.

Analysis of the Correlation of Topic Feature Changes Based on the LDA Model

Abstract. As is well known, with the continuous development of artificial intelligence technology and the increasing accessibility of data, various social platforms are committed to using intelligent recommendation algorithms to cater to user preferences. Some platforms even exaggerate facts and push sensational, valueless information to users, leading to the "Screaming Effect" and the "Echo Chamber Effect." The prolonged existence of these effects may result in "Information Cocoon," which is detrimental to the healthy development of individuals and society. To address this issue, different topics can have varying trajectories as online comments ferment, potentially reaching a neutral consensus or resulting in polarization. As a mainstream social platform in China, Weibo users serve as nodes for the dissemination of public opinion information, and the characteristics of information release, reception, forwarding, and commenting all influence the effectiveness of communication. First, we selected the topics "COVID-19" and "IG Electronic Sports Club" as our research subjects, identifying a range of topic popularity through Baidu Index, followed by data collection. Second, we used perplexity and coherence to determine the optimal number of topics for LDA, analyzing the changes in topic feature characteristics over different time periods. Through correlation analysis, we reached the following conclusions: Higher Weibo levels correlate with better information dissemination effectiveness; the quantity of information published on Weibo negatively impacts the forwarding and commenting behaviors; and as events progress, the enthusiasm for information dissemination on Weibo declines, with daily dissemination gradually decreasing.