Stepwise Multiple Linear Regression Research Articles

Machine learning-based QSAR modeling, molecular docking, dynamics simulation studies for cytotoxicity prediction in MDA-MB231 triple-negative breast cancer cell line

Triple-negative breast cancer (TNBC) is the most aggressive cancer type that tests negative for progesterone, estrogen, and HER2 protein receptors. Therefore, TNBC is unlikely to respond either to drugs that target HER2 receptors or to hormonal therapy drugs. In the present study, 2D-QSAR model was developed to predict the inhibitory concentration (IC50) of terpene derivatives against human breast cancer metastatic cell line MDA-MB231, using V-Life MDS v4.5, module. The model was developed using the forward stepwise multiple linear regression method, with a regression coefficient (r2) of 0.86, and a cross-validated r2 (q2) of 0.8448. Molecular descriptors namely electronegativity (Epsilon-3), carbon atoms separated through five bond distances (T_C_C_5), Sum of Electrotopological state indices of –CH2 group (SssCH2count), Dipole moment of coordinate-z (Zcomp Dipole), and Distance between highest positive and negative electrostatic potential on van-der Waals surface area (Most +ve & -ve Potential Distance) were found to be the most potent contributing chemical descriptors for cytotoxicity against TNBC MDA-MB231 cell line. Additionally, binding affinities and interaction patterns revealed that the proposed compounds exhibit good binding affinities and substantial stability with c-Met-and β-tubulin receptors, as assessed by docking studies. Molecular dynamics simulations (100 ns) and binding free energy calculations were also performed using the MMGBSA method. The pharmacokinetic and eADME/T analysis of predicted compounds were assessed through Discovery Studio software. These findings may be of immense importance in the optimization and development of dual inhibitory potent anti-cancer inhibitors against the MDA-MB231 TNBC cell line. Moreover, this novel QSAR based prediction model/method is implemented in R-package and software tool developed for virtual screening purposes and available online for download through the public repository GitHub.

Actual versus perceived noise levels among critical care nurses and their related adverse effects: A cross-sectional study.

Critical care nurses should help in reducing noise to improve the well-being of patients and health care providers. To measure actual noise levels in intensive care units, identify nurses' perceived irritation levels of noise sources and examine the impact of noise on nurses' work performance and well-being. This cross-sectional study was conducted from January to April 2023 at a teaching hospital's six intensive care units. It involved three phases: mapping locations for noise measurement, actual noise measurements in decibels and a cross-sectional survey to identify nurses' perceptions and the adverse effects of noise. Actual noise was measured between patients' beds, nursing stations and beside 16 noise sources for 7 days 24 h a day. For nurse perceptions, the mean of perceived irritation levels by a Likert scale for each noise source was calculated to present perceived noise levels. Ranking of noise sources according to the actual measured and perceived irritation by nurses was done based on mean values. Curve estimation regression test was used to predict the relationship between actual and perceived noise and stepwise multiple linear regression identified factors associated with noise adverse effects. The mean noise level in the intensive care units was 65.55 dB. Nurses perceived mechanical ventilator alarms as the most irritating noise. However, the mean noise measurements showed that conversations among colleagues were the primary source of noise. There was no significant predictive relationship between the actual and perceived noise. Nurses reported feeling distressed, irritable, fatigued and less productive due to noise. There was a discrepancy between actual and perceived noise levels by nurses. Perceived noise levels had more impact on nurses than actual noise. By incorporating both objective measurements and subjective perceptions into efforts aimed at reducing noise, health care providers can create quieter intensive care units.

Evaluation of the quality grade of Congou black tea by the fusion of GC-E-Nose, E-tongue, and E-eye

In the present study, the comprehensive quality of Congou black tea (CBT) including aroma, taste, and liquid color was investigated by a combination of gas chromatography electronic nose (GC-E-Nose), electronic tongue (E-tongue), and electronic eye (E-eye). An excellent discrimination of different quality grades of CBT was accomplished through the fusion of GC-E-Nose, E-tongue, and E-eye combined with orthogonal partial least squares discriminant analysis, with parameters of R2Y = 0.803 and Q2 = 0.740. Moreover, the quantitative evaluation of CBT quality was successfully achieved by partial least squares regression analysis, with the absolute error within 1.39 point, and the relative error within 1.62%. Additionally, 12 key variables were screened out by stepwise multiple linear regression analysis, which significantly contributed to the comprehensive quality score of CBT. Our results suggest that the fusion of multiple intelligent sensory technologies offers great potential and practicability in the quality evaluation of black tea.

The Injury Risk Prediction of Firefighters with Biomechanical Parameters during Single- and Double-Leg Jumps

The incidence of knee injuries during firefighter training is high, but there is a lack of research on predictive factors and risk assessment for such injuries. Biomechanical assessments can provide a better understanding of how the body’s load changes during exercise, which may alter the risk of injury. Ten firefighters were recruited for our study. Each participant completed the FMS test and the single- and double-leg jump tasks. Motion information was collected and musculoskeletal models of the participants were constructed using OpenSim 4.4 to obtain the joint angle and joint moment. The peak GRF and CoM-CoP angle were also calculated. The findings showed a significantly larger PKFM (p = 0.0195), VAFM (p = 0.0039), and peak AP GRF (p = 0.0039) during the single-leg jump. The opposite performance was observed for KFA (p = 0.0098) and MPA (p = 0.0273). A stepwise multiple linear regression analysis was used to explore the relationship between these parameters and both the FMS score and the times of injuries. The risk of injury is higher in the single-leg jump compared to the double-leg jump. The biomechanical parameters of these two jumps can be used to assess sports injuries and to provide methods and references for injury risk monitoring during firefighter occupational training.

Water quality evaluation based on water quality index and multiple linear regression: A research on Hanyuan Lake in southern Sichuan Province, China.

This study aims to understand the changes in the water quality of Hanyuan Lake and to show these changes over time. In this study, monthly sampling was conducted at three sampling sites in Hanyuan Lake, and water samples were measured for water quality indicators in the laboratory according to the methods specified in the Environmental Quality Standards for Surface Water (GB3838-2002). Based on the monitoring data from January to December 2019, the WQI comprehensive evaluation method was used to conduct multiple linear stepwise regression analysis, extract key indicators, and establish the WQImin model. The results show that according to the WQI comprehensive evaluation method, the WQI values of Hanyuan Lake are all above 90, and the grade is excellent. The overall water quality of Hanyuan Lake is excellent, and most of the water quality indexes reach the Class I standard in the Environmental Quality Standards for Surface Water (GB3838-2002). WQImin1 (R2 = 0.86, p < 0.001, PE = 4.28) as the best WQImin model. In this study, a model with fewer parameters was established by multiple linear regression method, which is conducive to better monitoring of water quality at monitoring stations while saving costs. PRACTITIONER POINTS: According to the WQI comprehensive evaluation method, the WQI values of Hanyuan Lake are all above 90, the rating is excellent. From January 2019 to September 2020, the monthly change trend of each section is roughly the same, showing a trend of first decreasing, then rising, then decreasing, and finally rising and flattening. The WQImin model was developed to completely describe the change in the water body.

Association between urinary metals and prostate-specific antigen in aging population with depression: a cross-sectional study

ObjectiveThis study aims to investigate the impact of depression and urinary metals on Prostate-Specific Antigen (PSA).MethodsAnalysis was conducted on 1901 samples collected from the National Health and Nutrition Examination Survey (NHANES) database between 2001 and 2010. Analytical methods included stepwise multiple linear regression (MLR) analysis of the overall population’s urinary metals and PSA relationship, analysis of urinary metals and PSA relationship in older adults and BMI subgroups, analysis of urinary metals and PSA relationship in the depressed population, and restricted cubic spline (RCS) analysis. A significance level of p &amp;lt; 0.05 was considered statistically significant.ResultsIn the stepwise multiple linear regression, beryllium (Be) showed a dose–response association with PSA (third quartile: β = 0.05, 95%CI (0.02, 0.09); fourth quartile: β = 0.07, 95%CI (0.02, 0.12), p trend = 0.048). Subgroup analysis indicated that in individuals aged &amp;gt;60, Be at Q4 level [β = 0.09, 95%CI (0.05, 0.21)] exhibited a dose–response correlation with PSA. In the population with 25 ≤ BMI &amp;lt; 30, Be might more significantly elevate PSA, with Q4 level having a pronounced impact on PSA levels [β = 0.03, 95%CI (0.02, 1.27)]. In the depressed population, urinary cadmium (Cd) levels showed a significant positive dose–response relationship, with Q4 level of Cd having the maximum impact on PSA [β = 0.3, 95%CI (0.09, 0.49)].ConclusionIndividuals exposed to beryllium (Be), especially the older adults and overweight, should monitor their PSA levels. In depressed patients, cadmium (Cd) levels may further elevate PSA levels, necessitating increased monitoring of PSA levels among males.

Serum 25-Hydroxyvitamin D Level Is Positively Associated with Vascular Reactivity Index in Patients with Type 2 Diabetes Mellitus.

Circulating 25-hydroxyvitamin D (25(OH)D) significantly influences endothelial function. This study assessed the correlation between serum 25(OH)D and endothelial function using the vascular reactivity index (VRI) in patients with type 2 diabetes mellitus (T2DM). Fasting blood samples from 102 T2DM participants and VRI were assessed. Patients were divided into three categories based on VRI: low (VRI < 1.0), intermediate (1.0 ≤ VRI < 2.0), and good (VRI ≥ 2.0). Among these patients, 30 (29.4%) had poor, 39 (38.2%) had intermediate, and 33 (32.4%) exhibited good vascular reactivity. Higher serum fasting glucose (p = 0.019), glycated hemoglobin (p = 0.009), and urinary albumin-to-creatinine ratio (p = 0.006) were associated, while lower prevalence of hypertension (p = 0.029), lower systolic blood pressure (p = 0.027), lower diastolic blood pressure (p < 0.001), and lower circulation 25(OH)D levels (p < 0.001) were associated with poor vascular reactivity. Significant independent associations between diastolic blood pressure (p = 0.002) and serum 25(OH)D level (p < 0.001) and VRI were seen in T2DM patients according to multivariable forward stepwise linear regression analysis. Serum 25(OH)D positively correlated with VRI values, and lower levels of serum 25(OH)D were linked to endothelial dysfunction in T2DM patients.

A decision tree-based study of pulmonary tuberculosis diagnosis-related groups.

Globally, pulmonary tuberculosis is a significant public health and social problem. We investigated the factors influencing the hospitalization cost of patients with pulmonary tuberculosis and grouped cases based on a decision tree model to provide a reference for enhancing the management of diagnosis-related groups (DRGs) of this disease. The data on the first page of the medical records of patients with the primary diagnosis of pulmonary tuberculosis were extracted from the designated tuberculosis hospital. The influencing factors of hospitalization cost were determined using the Wilcoxon rank sum test and multiple linear stepwise regression analysis, and the included cases were grouped using the chi-squared automated interaction test decision tree model, with these influential factors used as classification nodes. In addition, the included cases were grouped according to the ZJ-DRG grouping scheme piloted in Zhejiang Province, and the differences between the two grouping methods were compared. The length of hospital stay, respiratory failure, sex, and age were the determining factors of the hospitalization cost of patients with pulmonary tuberculosis, and these factors were incorporated into the decision tree model to form eight case combinations. The reduction in variance (RIV) using this grouping method was 60.60%, the heterogeneity between groups was high, the coefficients of variance ranged from 0.29 to 0.47, and the intra-group difference was small. The patients were also divided into four groups based on the ZJ-DRG grouping scheme piloted in Zhejiang Province. The RIV using this grouping method was 55.24, the differences between groups were acceptable, the coefficients of variance were 1.00, 0.61, 0.77, and 0.87, respectively, and the intra-group difference was significant. When the pulmonary tuberculosis cases were grouped according to the duration of hospital stay, respiratory failure, and age, the results were rather reasonable, providing a reference for DRG management and cost control of this disease.

Comparison of in vitro membrane permeabilities of diverse environmental chemicals with in silico predictions

The parallel artificial membrane permeability assay (PAMPA) is widely used for estimating biomembrane permeabilities of experimental drugs in pharmaceutical research. However, there are few reports of studies using PAMPA to measure membrane permeabilities of chemicals of environmental concern (CECs) outside the pharmaceutical domain, many of which differ substantially from drugs in their physicochemical properties. We applied PAMPA methods simulating gastrointestinal (PAMPA-GIT) and blood-brain barrier (PAMPA-BBB) membranes under consistent conditions to 51 CECs, including some pharmaceuticals. A backward stepwise multivariate linear regression was implemented to explore the correlation between the differences of measured permeabilities from PAMPA-GIT and PAMPA-BBB and Abraham solute descriptors. In addition, a previously reported in silico model was evaluated by comparing predicted and measured permeability results. PAMPA-GIT and PAMPA-BBB experimental permeability results agreed relatively well. The backward stepwise multivariate linear regression identified excess molar refraction and polarizability to be significant at the 0.10 level in predicting the differences between PAMPA-GIT and PAMPA-BBB. The in silico model performed well – with predicted permeability of most compounds within two-fold of experimentally measured values. We found that CECs pose experimental challenges to the PAMPA method in terms of having lower solubility and lower stability compared to most drugs.

Presence of Self-Reported Sleep Alterations After Stroke and Their Relationship With Disability: A Longitudinal Study.

Sleep disorders have a prevalence of 30% to 70% in post-stroke individuals. The presence of sleep disorders and poor sleep quality after stroke can affect important functions and lead to worse outcomes. However, most studies are restricted to the acute post-stroke stage only. To investigate the frequency of self-reported sleep alterations in a sample of chronic stroke individuals and to identify which self-reported sleep alterations were associated with disability. Prospective exploratory study. Self-reported sleep alterations were measured by the Pittsburgh Sleep Quality Index, Insomnia Severity Index, Epworth Sleepiness Scale, and STOP-Bang Questionnaire. The dependent variable was measured 3 years after the first contact by the Modified Rankin Scale (mRS). Step-wise multiple linear regression analysis was employed to identify which sleep alterations were associated with disability. Sixty-five individuals with stroke participated. About 67.7% of participants had poor sleep quality, 52.4% reported insomnia symptoms, 33.9% reported excessive daytime sleepiness, and 80.0% were classified as intermediate or high risk for obstructive sleep apnea. Only risk for obstructive sleep apnea was significantly associated with disability and explained 5% of the variance in the mRS scores. Self-reported sleep alterations had a considerable frequency in a sample of chronic stroke individuals. The risk of obstructive sleep apnea was associated with disability in the chronic stage of stroke. Sleep alterations must be considered and evaluated in the rehabilitation process even after a long period since the stroke onset.

Quantitative ultrasound techniques and biochemical markers to assess liver steatosis and fibrosis in newly diagnosed acromegaly.

The liver is known to be protected from steatosis under the influence of high GH/IGF-1. Cytokeratin 18 (CK18) and insulin-like growth factor binding protein 7 (IGFBP7) increase in liver steatosis and fibrosis. The aim of this study was to use quantitative ultrasound techniques and biochemical markers to assess liver steatosis and liver fibrosis in newly diagnosed acromegaly. This single-center, cross-sectional study included 23 patients with newly diagnosed acromegaly and 46 age, sex, body mass index (BMI) and waist circumference (WC)-matched controls. Liver steatosis was assessed using tissue attenuation imaging (TAI), and stiffness, indicative of fibrosis, was assessed by shear wave elastography (SWE). Serum IGFBP7 and CK18 were studied by ELISA. The acromegaly group had significantly lower liver steatosis (p = 0.006) and higher liver stiffness (p = 0.004), serum IGFBP7 (p = 0.048) and CK18 (p = 0.005) levels than the control group. The presence of fibrosis (p = 0.012) was significantly higher in the acromegaly group than in the control group. Moreover, CK18 was positively correlated with liver stiffness, WC, HOMA-IR, HbA1c, and triglyceride. In the acromegaly group, liver steatosis was negatively correlated with GH level. Stepwise multiple linear regression analysis revealed that BMI (p = 0.008) and CK18 (p = 0.015) were independent risk factors for increased liver stiffness. This study showed that there was an increased presence of liver fibrosis independent of liver steatosis in newly diagnosed acromegaly. Serum CK18 appears to be a potential marker of increased liver fibrosis in acromegaly.

Orthodontic Elastics: A Multivariable Analysis of YouTubeTM Videos.

Whether YouTube videos contain precise and adequate information on certain orthodontic procedures remains unclear. This study aimed to investigate the content and quality of YouTube videos on orthodontic elastics and identify the predictors of high-level content YouTube videos. Two hundred YouTube videos were screened for eligibility, and after applying the inclusion criteria, 133 videos were excluded. Student's t-test was used to compare the characteristics, quality parameters, and total content of the low-level and high-level content videos. Chi-square or Fisher's exact tests were implemented to identify the source and content element differences across low-level and high-level content videos. Pearson's correlation coefficients were used to determine the relationship between the total content score, video information and quality index (VIQI), and YouTube characteristics. Stepwise linear multiple regressions with forward selection were used to test the association of the YouTube characteristics and VIQI with the total content score. Among 67 included videos, only 19.4% of videos were classified as high-level content videos. High-level content videos had significantly higher mean number of likes (MD = 4041.7; SD = 4680.7; P-value=0.0068), VIQI score (MD = 4.17; SD = 4.87; P-value=0.0073), and total content score (MD = 4.04; SD = 1.23; P-value=<0.0001). The adjusted linear regression model demonstrated a significant association between the total content score and VIQI, where 1 unit increase in the VIQI was significantly associated with a 0.16 increase in the total content score (B = 0.16; standard error [SE]=0.04; P = 0.0003). Further, a significant association was observed between the total content score and video duration, where 1 minute increase in the video duration was significantly associated with a 0.15 increase in the total content score (B = 0.15; SE = 0.05; P = 0.008). This study demonstrated that YouTube content quality concerning orthodontic elastics is poor. Thus, future implementation of online visual content provided by certified orthodontists will ensure accurate and thorough information delivery.

Lipidomic and Fatty Acid Biomarkers in Whole Blood Can Predict the Dietary Intake of Eicosapentaenoic and Docosahexaenoic Acids in a Danish Population

BackgroundThe intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have been associated with health benefits. Blood levels of these fatty acids, measured by gas chromatography (GC), are associated with their dietary intake, but the relationships with lipidomic measurements are not well defined. ObjectivesThis study aimed to determine the lipidomic biomarkers in whole blood that predict intakes of EPA + DHA and examine the relationship between lipidomic and GC-based n–3 polyunsaturated fatty acid (n–3 PUFA) biomarkers. MethodsLipidomic and fatty acid analyses were completed on 120 whole blood samples collected from Danish participants. Dietary intakes were completed using a web-based 7-d food diary. Stepwise multiple linear regression was used to identify the fatty acid and lipidomic variables that predict intakes of EPA + DHA and to determine lipidomic species that predict commonly used fatty acid biomarkers. ResultsStepwise regression selected lipidomic variables with an R2 = 0.52 for predicting EPA + DHA intake compared to R2 = 0.40 for the selected fatty acid GC-based variables. More predictive models were generated when the lipidomic variables were selected for females only (R2 = 0.62, n = 68) and males only (R2 = 0.72, n = 52). Phosphatidylethanolamine plasmalogen species containing EPA or DHA tended to be the most predictive lipidomic variables. Stepwise regression also indicated that selected lipidomic variables can predict commonly used fatty acid GC-based n–3 PUFA biomarkers as the R2 values ranged from 0.84 to 0.91. ConclusionsBoth fatty acid and lipidomic data can be used to predict EPA + DHA intakes, and fatty acid GC-based biomarkers can be emulated by lipidomic species. Lipidomic-based biomarkers appear to be influenced by sex differences, probably in n–3 PUFA and lipoprotein metabolism. These results improve our ability to understand the relationship between novel lipidomic data and GC fatty acid data and will increase our ability to apply lipidomic methods to fatty acid and lipid nutritional research.

Influence of Individual Characteristics on Critical Environmental Limits in Middle-aged and Older Adults (PSU HEAT Project)

Critical environmental limits represent the temperature/humidity combinations at which heat balance can no longer be maintained for a given metabolic rate. Individual characteristics (e.g., sex, body weight and size, and aerobic fitness) are known to alter environmental heat exchange as well as thermoregulatory effector responses and therefore may modify critical environmental limits. PURPOSE: To determine which individual characteristics, if any, may be associated with higher or lower critical environmental limits [combinations of ambient dry-bulb temperature (Tdb) and relative humidity (rh)] in middle-aged and older adults. Methods: Forty-eight male (n=16) and female (n=32) participants (63±11 yrs; range: 40-92 yrs) were exposed to progressive heat stress at a low metabolic rate designed to reflect activities of daily living. Experiments were conducted in both hot-dry (HD; up to 53°C; ≤25% rh) and warm-humid (WH; ~35°C; ≥50% rh) environments. After determining critical limits for each age group and condition, forward stepwise multiple linear regression analyses were conducted with net metabolic rate (Mnet) and age entered into the model first, followed by sex, body mass, Vȯ2max, body surface area, and LDL cholesterol. Results: After accounting for Mnet and age, both sex and body mass further significantly improved the regression model in the HD environment (R2adj = 0.41, p &lt; 0.001) whereas only sex (R2adj = 0.51, P &lt; 0.001) added significantly to the WH model. Sex explained 11% of the variance in critical environmental limits in HD conditions and 14% of the variance in WH conditions. In both WH and HD environments, females exhibited lower critical combinations of Tdb and rh than their male counterparts. Additionally, body mass was negatively related to critical environmental limits in the HD environments and accounted for 8% of the variance after metabolic rate and age were accounted for. CONCLUSION: These data indicate a modest influence of individual characteristics, specifically sex and body mass, on critical environmental limits in both WH and HD environments in adults between the ages of 40 and 92. SIGNIFICANCE/NOVELTY: These results contrast previously published data in young adults showing no significant contribution of individual characteristics to the upper limits of heat balance at low metabolic rates reflecting activities of daily living. This reflects the heterogeneity of thermal-balance thresholds associated with aging relative to those seen in young adults. NIH R01 AG067471 (WLK) and NIA Grant T32 AG049676 (RMC). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Association of anhedonia with brain-derived neurotrophic factor and interleukin-10 in major depressive disorder

BackgroundAnhedonia, a core symptom of major depressive disorder (MDD), manifests in two forms: anticipatory and consummatory, reflecting a diminished capacity to anticipate or enjoy pleasurable activities. Prior studies suggest that brain-derived neurotrophic factor (BDNF) and interleukin-10 (IL-10) may play key roles in the emergence of anhedonia in MDD. The specific relationships between these biomarkers and the two forms of anhedonia remain unclear. This study investigated the potential links between BDNF, IL-10, and both forms of anhedonia in MDD patients. MethodsThis study included 43 participants diagnosed with MDD and 58 healthy controls. It involved detailed assessments of depression and anxiety levels, anticipatory and consummatory pleasure, cognitive functions, and a broad spectrum of plasma biomarkers, such as C-reactive protein, various interleukins, and BDNF. Using partial correlation, variables related to pleasant experiences were identified. Stepwise multiple linear regression analysis was applied to pinpoint the independent predictors of anhedonia in the MDD group. ResultsDemographically, both groups were comparable in terms of age, sex, body mass index, educational year, and marital status. Individuals with MDD displayed markedly reduced levels of anticipatory and consummatory pleasure, higher anxiety, and depression scores compared to healthy controls. Additionally, cognitive performance was notably poorer in the MDD group. These patients also had lower plasma diamine oxidase levels. Analysis linked anhedonia to impaired delayed memory. Regression results identified IL-10 and BDNF as independent predictors of anticipatory and consummatory anhedonia, respectively. ConclusionThese findings demonstrate that anticipatory and consummatory anhedonia are influenced by independent factors, thereby providing critical insights into the distinct neuroimmunological mechanisms that underlie various forms of anhedonia.Clinicl Trial Registration Number: NCT03790085

Effects of Facilitating Condition, Social Influence and Self-Efficacy on Science Teachers’ Integration of Digital Technology in South Africa: A Regression-Based Approach

The ongoing failure to raise academic achievement in certain science subjects across rural areas of South Africa necessitates the consideration of technology-enhanced instructional approaches, as such strategies can augment learners’ understanding. Therefore, this study aimed to investigate the integration of digital technologies in teaching sciences in a rural district of South Africa. The study was guided by the unified theory of acceptance and use of technology as the theoretical framework. A cross-sectional survey was used to collect quantitative data. The research instrument was a questionnaire related to science teachers’ integration of digital technology. The sample size was 158 participants, who were selected using convenience sampling. Data were analysed using descriptive statistics and stepwise multiple linear regression. The study found that science teachers’ integration of digital technology was moderate. Stepwise multiple linear regression revealed that facilitating condition (? = 0.446, t = 6.088, p &lt; .05) was the most important predictor of teachers’ integration of digital technology, followed by self-efficacy (? = 0.295, t = 4.857, p &lt; .05) and social influence (? = 0.160, t = 2.213, p &lt; .05). The study offers insights to policymakers and educators on improving the integration of digital technology in science education. Suggestions for accelerating the integration of digital technology in economically disadvantaged rural communities are presented. The implications of the study are that improving facilitating conditions, self-efficacy, and social influence can enhance science teachers’ integration of digital technology. Future research is required to determine changes over time in the teachers’ integration of digital technology through longitudinal studies.

Differential influence of quadriceps rate of torque development on single- and double-leg landing mechanics in anterior cruciate ligament reconstructed and control females.

The capacity to explosively contract quadriceps within the critical timeframe associated with anterior cruciate ligament (ACL) injury, quantified by the rate of torque development, is potentially essential for safe landing mechanics. This study aimed to investigate the influence of explosive quadricepsstrength on ACL-related sagittal-plane landing mechanics in females with and without ACL reconstruction (ACLR). Quadricepsexplosive strength and landing mechanics were assessed in 19 ACLR and 19 control females during isometric contractions and double-and single-leg jump landings. A stepwise multiple linear regression model determined the variance in each of the landing biomechanics variables for the ACLR limb and nondominant limb of controls that could be explained by the group, rate of torque developmentand/or their interaction. If peak kinetic variables could be predicted by the rate of torque development or interaction, additional analyses were conducted, accounting for knee flexion as a covariate in the regression model. During single-leg landings, ACLR females exhibited greater knee flexion at initial contact than controls (p = 0.04). Greater quadricepsrate of torque development predicted higher peak posterior ground reaction force and anterior tibial shear force in both groups (p = 0.04). However, after controlling for knee flexion angle at those peak forces, quadriceps rate of torque development was not predictive. In double-leg landings, greater explosive quadriceps strength was associated with quicker attainment of peak knee extension moment and posterior ground reaction force in the ACLR limb (p = 0.03). Regardless of ACL injury status, females with greater explosive quadriceps strength adopted safer single-leg landings through increased knee flexion, potentially mitigating ACL loading despite encountering higher peak forces. During double-leg landings, a greater explosive quadriceps strength of the ACLR limb is associated with faster achievement of peak force upon landing. Incorporating explosive quadriceps strengthening into post-ACLR rehabilitation and injury prevention programmes may enhance landing mechanics for reducing primary and subsequent ACL injury risks. Level II.

Analysis of the Correlation Between Visceral Fat Area and Insulin Resistance in Patients with Type 2 Diabetes and Abdominal Obesity

Objective: To analyze the correlation between visceral fat area and insulin resistance index (HOMA-IR) in patients with type 2 diabetes mellitus (T2DM) and abdominal obesity and to provide a reference for screening and related research of such patients. Methods: Two hundred patients with T2DM admitted to Guandu People’s Hospital of Kunming were included. The study was carried out from October 2022 to December 2023. The patients were divided into three groups according to different abdominal visceral fat areas (VFA): Group A (n = 65) was less than 75cm2, Group B (n = 75) was 75–100 cm2, and Group C (n = 60) was greater than 100 cm2. The subjects in the three groups were all tested for glycated hemoglobin (HbA1c), fasting insulin (FINS), and fasting blood glucose (FPG). Height and weight were measured to calculate body mass index (BMI). The HOMA-IR and TYG (fasting triglyceride and glycemic index) were also calculated. Changes in the BMI, VFA, HOMA-IR, and TYG levels were observed in the three groups. Results: The VFA, BMI, HbA1c, FPG, FINS, HOMA-IR, and TYG of the patients all increased, with a more significant increase in the BMI, FINS, HOMA-IR, and TYG levels (P &lt; 0.01). Multiple linear stepwise regression analyses used visceral fat area (VFA) as the dependent variable. The results showed that VFA was closely related to BMI, FINS, HOMA-IR, and TYG. Conclusion: Early reduction of VFA to reduce insulin resistance may be a better treatment and effective method for T2DM, providing powerful measures and new strategies for effective blood sugar control and early prevention in the treatment of metabolic diseases.

Electrical Properties for Non-destructive Determination of Free Fatty Acid and Moisture Content in Oil Palm Fruit

FFA content is one of the essential qualities of oil palm fruit. FFA content exceeding 5% is considered unsuitable for human consumption. Commonly, FFA content is determined by chemical methods in the laboratory, but it is destructive, time-consuming, and costly. Several non-destructive methods have been investigated, but a maturity prediction approach has been primarily used with no direct relation to FFA content. Thus, there is a pressing need for a non-destructive framework to assess the FFA levels in the oil palm fruit directly. An attempt has been explored using a non-destructive palm fruit quality assessment that relied on electrical properties (impedance, admittance, resistance, and capacitance) in the frequency range from 50 Hz to 5 MHz was investigated to predict FFA and moisture content directly. Two statistical analyses were employed: stepwise multiple linear regressions (MLR) and artificial neural networks (ANN) to calibrate and validate electrical properties with FFA and moisture content. The best-performing models ANN showcased significant results: r= 0.96, R2=0.92, SEC at 0.86%, SEP at 0.97%, CV at 19.45%, consistency at 88.54, and RPD at 3.43 for FFA prediction, and r= 0.99, R2=0.98, SEC at 3.09 %, SEP at 3.46 %, CV at 5.44 %, consistency at 89.08 and RPD at 7.02 for predicting moisture content. In modeling oil palm quality determination, applying the ANN method significantly improved model performances, demonstrating its efficacy in predicting non-destructively both FFA levels based on admittance and moisture content based on impedance.

Dynamics Power Quality Cost Assessment Based on a Gradient Descent Method

The escalating demand for power load is increasingly prone to triggering power quality (PQ) issues, leading to severe economic losses. Aiming at reducing the economic losses, this paper focuses on the coordinated relationship between PQ and economic costs. Firstly, a multilayer multiple linear stepwise regression method is employed to screen PQ indicators, identifying harmonic and voltage deviation as the primary influencing factors of PQ. Secondly, a gradient descent optimization algorithm based on the Least Absolute Shrinkage and Selection Operator (LASSO) is proposed, enabling rapid computation of the minimum PQ cost. Finally, through validations of two case studies, the results confirm that the proposed method can rapidly calculate the minimum PQ cost based on real-time load demands, enabling the dynamic adjustment of PQ cost to meet the evolving needs of power system development.