Supplementary decompression and extended surgical time contribute to hidden blood loss In percutaneous endoscopic lumbar discectomy.

Background: It is widely believed that the Percutaneous endoscopic lumbar discectomy (PELD) is associated with minimal blood loss. However, significant perioperative hidden blood loss (HBL) is frequently unaccounted for. This study aimed to investigate HBL and peri-operative factors contributing to HBL in a series of individuals undergoing PELD. Method: ology: A total of 156 consecutive patients with a mean age of 43.6 years (ranging from 18 to 80 years) who underwent PELD at our department from May 2019 to November 2020, were included in the study. Factors including gender, age, body mass index, symptom duration, operation approach/technique, operation duration, the presence of associated chronic diseases, and improvements in the Visual Analog Scale (VAS) score, Japanese Orthopaedic Association (JOA) score and the Oswestry Disability Index (ODI) were analyzed, and Gross's formula was applied to calculate blood loss, which was used to determine HBL. Results: The average total blood loss (TBL) was 221.0 ± 126.2 mL, while the average HBL was 181.7 ± 119.0 mL (82.2 % of TBL). There was no statistically significant difference in HBL between the transverse surgical approach and the interlayer approach. Additionally, no significant differences were observed in improvements in VAS, JOA, and ODI scores between the two surgical approaches. However, the multivariate linear regression analysis revealed that longer surgical time and foraminal decompression were factors contributing to the increase in HBL, which subsequently led to the occurrence of post-operative anemia. Conclusion: HBL is significant in PELD cases with long surgical time and lumbar foraminal decompression.

Exploring relationships among landfill leachate parameters through multivariate analysis for monitoring purposes.

Elucidating the properties of landfill leachate and the relationships among leachate parameters is crucial for efforts to determine appropriate landfill leachate monitoring activity and management strategies. This study investigated the physical, chemical and optical parameters of leachate in an old Japanese landfill over a 13-month period. The parameters were explored based on their relationships with the maximum fluorescence (Fmax) of three components (microbial humic-like C1, terrestrial humic-like C2 and protein-like C3) deconvoluted from excitation-emission matrix fluorescence spectroscopy coupled with parallel factor analysis. Dissolved organic carbon (DOC), chemical oxygen demand (COD), Cl- and SO42- concentrations and pH ranged from 2.6 to 38.2 mg C L-1, 9 to 324 mg L-1, 14 to 972 mg L-1, 26 to 1554 mg L-1 and 6.9 to 11.6, respectively. Linear regression analysis suggested that the Fmax values of C2 and C3 represented DOC, whereas the Fmax value of C2 alone could serve as a COD indicator. Hierarchical cluster analysis and principal component analysis were employed to successfully categorise leachate samples based on their locations. Higher dissolved organic matter levels were observed in leachate within the old disposal area, whereas elevated levels of inorganic components such as SO42- and Cl- were found in leachate collected from the extended disposal area and at a treatment facility. Statistical analysis provides crucial tools for assessing and managing various areas of a landfill, supporting targeted and effective waste management strategies.

Addressing the Gap: Racial Disparities and Public Health Strategies in the Epidemiology of Gastrointestinal Stromal Tumors.

Background Gastrointestinal stromal tumors (GISTs) represent the most common mesenchymal neoplasms of the gastrointestinal tract, arising from the interstitial cells of Cajal. These tumors bridge the nervous system and muscular layers of the gastrointestinal tract, playing a crucial role in the digestive process. The incidence of GISTs demonstrates notable variations across different racial and ethnic groups, underscoring the need for in-depth analysis to understand the interplay of genetic, environmental, and socioeconomic factors behind these disparities. Linear regression analysis is a pivotal statistical tool in such epidemiological studies, offering insights into the temporal dynamics of disease incidence and the impact of public health interventions. Methodology This investigation employed a detailed dataset from 2009 to 2020, documenting GIST incidences across Asian, African American, Hispanic, and White populations. A meticulous preprocessing routine prepared the dataset for analysis, which involved data cleaning, normalization of racial terminologies, and aggregation by year and race. Linear regression models and Pearson correlation coefficients were applied to analyze trends and correlations in GIST incidences across the different racial groups, emphasizing an understanding of temporal patterns and racial disparities in disease incidence. Results The study analyzed GIST cases among four racial groups, revealing a male predominance (53.19%) and an even distribution of cases across racial categories: Whites (27.66%), Hispanics (25.53%), African Americans (24.47%), and Asians (22.34%). Hypertension was the most common comorbidity (32.98%), followed by heart failure (28.72%). The linear regression analysis for Asians showed a decreasing trend in GIST incidences with a slope of -0.576, an R-squared value of 0.717, and a non-significant p-value of 0.153. A significant increasing trend was observed for Whites, with a slope of 0.581, an R-squared value of 0.971, and a p-value of 0.002. African Americans exhibited a moderate positive slope of 0.277 with an R-squared value of 0.470 and a p-value of 0.201, indicating a non-significant increase. Hispanics showed negligible change over time with a slope of -0.095, an R-squared value of 0.009, and a p-value of 0.879, suggesting no significant trend. Conclusions This study examines GIST incidences across racial groups, revealing significant disparities. Whites show an increasing trend (p = 0.002), while Asians display a decreasing trend (p = 0.153), with stable rates in African Americans and Hispanics. Such disparities suggest a complex interplay of genetics, environment, and socioeconomic factors, highlighting the need for targeted research and interventions that address these differences and the systemic inequalities influencing GIST outcomes.

Consumer awareness and knowledge regarding use of non-steroidal anti-inflammatory drugs (NSAIDs) in a metropolitan area.

Background: Non-steroidal anti-inflammatory drugs (NSAIDs) have well-known adverse effects, and numerous studies have shown inappropriate behaviors regarding their use. The primary aim of this study was to analyze the knowledge, attitudes, and behaviors regarding the use of NSAIDs simultaneously in one of the largest and most populated areas of Italy, Naples. Methods: From 2021 December 14th to 2022 January 4th, a cross-sectional survey study was conducted among community centers, working places, and universities using a snowball sampling method. For inclusion in the study, the participants were required to be at least 18 years old and residents in the metropolitan area of Naples. Three multiple linear regression analysis (MLRA) models were developed by including variables that could potentially be associated with the following outcomes of interest: knowledge (Model I), attitudes (Model II), and behavior (Model III) regarding the use of NSAIDs. Results: Data were acquired from 1,012 questionnaires administered to subjects evenly divided by gender with an average age of 36.8 years and revealed that only 7.9% of the participants self-admittedly did not take NSAIDs, while approximately half the participants (50%) admitted to occasionally using them. The results showed a statistically significant correlation between attitudes regarding the appropriate use of NSAIDs and less knowledge. The regression analyses indicated that behaviors regarding the appropriate use of NSAIDs were statistically significant in younger respondents, non-smokers, and those without children. These interesting results showed that behaviors regarding the appropriate use of NSAIDs were significantly higher among respondents with less knowledge and more positive attitudes. Conclusion: According to the collected data and statistical analysis results, it is possible to identify factors that can greatly affect inappropriate behaviors regarding the use of NSAIDs and establish targeted prevention programs.

Evaluating the association between lifestyle factors and heel bone mineral density in different inflammatory states.

Rationale: It is unclear whether lifestyle factors affect bone mineral density (BMD) during different inflammatory states. Objective: This study investigated the effects of coffee consumption, vitamin D (VD) intake, smoking, and alcohol consumption on heel BMD in adults with different inflammatory states. Methods: The phenotypic data from 249,825 participants were analyzed using the UK Biobank cohort. The inflammatory status was evaluated using C-reactive protein (CRP) levels and the systemic immune-inflammation index. Linear regression analysis was used to examine the association between coffee consumption, VD, smoking, alcohol consumption, and heel BMD in adults with different inflammatory states. Linear regression models were used to analyze the interaction between inflammation and the four lifestyle factors with respect to their influence on heel BMD in adults. Results: Our findings revealed that VD was positively associated with adult heel BMD (ß = 2.41 × 10-2, SE = 5.14 × 10-3, P = 2.72 × 10-6), while alcohol consumption and smoking were negatively associated with adult heel BMD. Coffee was negatively associated with adult heel BMD in low inflammatory states (ß = -1.27 × 10-2, SE = 4.79 × 10-3, P = 8.00 × 10-3), while there was no association between coffee and adult heel BMD in high inflammatory states. Overall, it was found that these four lifestyle factors interacted negatively with inflammatory states. Conclusion: Our study suggests that VD is positively associated with adult heel BMD and that alcohol consumption and smoking are negatively associated with adult heel BMD. Coffee may reverse the adverse effects of inflammation on BMD when the patient is in a highly inflammatory state, thus acting as a protective agent against heel BMD in adults.

Yoke-Type Elasto-Magnetic Sensor-Based Tension Force Monitoring Method for Enhancement of Field Applicability.

Tension members are key members that maintain stability and improve the strength of structures such as cable-stayed bridges, PSC structures, and slopes. Their application has recently been expanded to new fields such as mooring lines in subsea structures and aerospace fields. However, the tensile strength of the tension members can be abnormal owing to various risk factors that may lead to the collapse of the entire structure. Therefore, continuous tension monitoring is necessary to ensure structural safety. In this study, an improved elasto-magnetic (E/M) sensor was used to monitor tension force using a nondestructive method. General E/M sensors have limitations that make it difficult to apply them to operating tension members owing to their solenoid structure, which requires field winding. To overcome this problem, the magnetization part of the E/M sensor was improved to a yoke-type sensor, which was used in this study. For the development of the sensors, the numerical design and magnetization performance verification of the sensor were performed through eddy current solution-type simulations using ANSYS Maxwell. Using the manufactured yoke-type E/M sensor, the induced voltage signals according to the tension force of the specimen increasing from 0 to 10 tons at 1-ton intervals were repeatedly measured using DAQ with wireless communication. The measured signals were indexed using peak-to-peak value of induced voltages and used to analyze the signal change patterns as the tension increased. Finally, the analyzed results were compared with those of a solenoid-type E/M sensor to confirm the same pattern. Therefore, it was confirmed that the tension force of a tension member can be estimated using the proposed yoke-type E/M sensor. This is expected to become an effective tension monitoring technology through performance optimization and usability verification studies for each target tension member in the future.

Dietary patterns and the risk of diabetes in Korean adults: A cross-sectional and prospective cohort study.

OBJECTIVE: The aim of this study was to identify dietary patterns associated with diabetes in Korean adults and to investigate their association with diabetes risk in both a cross-sectional and prospective study. METHODS: Predefined food groups collected by the Korea National Health and Nutrition Examination Survey (KNHANES 2015-2018, n = 19 721) were entered in a reduced rank regression (RRR) model, followed by stepwise linear regression analyses to identify the most predictive dietary patterns. We evaluated the construct validity of dietary patterns in two independent samples from KNHANES 2019 to 2021 (n = 14 223) and the Health Examinees (HEXA) cohort study (n = 30 013). Associations between dietary patterns and diabetes risk were examined using multivariable regression and multivariable-adjusted Cox proportional hazard models, respectively. RESULTS: A dietary pattern was identified with high positive loadings for refined white rice, kimchi and salted vegetables, wheat flour and bread, and seasonings, and high negative loadings for whole grains, legumes with tofu and soymilk, poultry, eggs, and plant oils. The higher pattern scores were significantly associated with diabetes risk in KNHANES 2015 to 2018 (male: odds ratio [OR]: 1.59; 95% confidence interval [CI]: 1.35, 1.88; female: OR: 1.37; 95% CI: 1.18, 1.52), KNHANES 2019 to 2021 (male: OR: 1.47; 95% CI: 1.01, 1.69; female: OR: 1.37; 95% CI: 1.18, 1.54), and HEXA study (male: hazard ratio [HR]: 1.10; 95% CI: 1.01, 1.34; female: HR: 1.24; 95% CI: 1.02, 1.52). CONCLUSIONS: Dietary patterns derived by RRR followed by stepwise linear regression analyses were associated with increased risks of diabetes among Korean adults.

Exploring factors influencing delayed first antibiotic treatment for suspected early-onset sepsis in preterm newborns: a study before quality improvement initiative.

BACKGROUND: Early-onset sepsis (EOS) is a serious illness that affects preterm newborns, and delayed antibiotic initiation may increase the risk of adverse outcomes. PURPOSE: The objective of this study was to examine the present time of antibiotic administration in preterm infants with suspected EOS and the factors that contribute to delayed antibiotic initiation. METHODS: In this retrospective study in China, a total of 82 early preterm infants with suspected EOS between December 2021 and March 2023 were included. The study utilized a linear regression analytical approach to identify independent factors that contribute to delayed antibiotic administration. RESULTS: The mean gestational age and birth weight of the study population were 29.1 ± 1.4 weeks and 1265.7 ± 176.8 g, respectively. The median time of initial antibiotic administration was 3.8 (3.1-5.0) hours. Linear regression revealed that severe respiratory distress syndrome (RDS) (ß = 0.07, P = 0.013), penicillin skin test (PST) timing (ß = 0.06, P < 0.001) and medical order timing (ß = 0.04, P = 0.017) were significantly associated with the initial timing of antibiotic administration. CONCLUSIONS: There is an evident delay in antibiotic administration in preterm infants with suspected EOS in our unit. Severe RDS, PST postponement and delayed medical orders were found to be associated with the delayed use of antibiotics, which will be helpful for quality improvement efforts in the neonatal intensive care unit (NICU).

Statistical Analysis of Morphological Characteristics of Inconel 718 Formed by High Deposition Rate and High Laser Power Laser Cladding.

Laser cladding is one of the emerging additive manufacturing technologies and has been adopted in various industrial fields. In this study, the morphological characteristics of a single clad of Inconel 718 manufactured by coaxial laser cladding with high laser power from 4200 W to 5400 W, powder feeding rate from 25 g/min to 50 g/min, and cladding speed from 20 mm/s to 50 mm/s are studied. The cross-section of the melt pool is analyzed and classified by type into three types: shallow dilution, flat dilution, and fluctuating dilution. Nine parameters are designed to describe the morphological characteristics of the clad, and the corresponding linear regression models are developed to establish a quantitative relationship between the combined process parameters and morphological characteristics. The results indicate that the total area of the cross-section A, the clad area above the substrate Ac, the area of the molten substrate Am, the total height of the cross-section H, the height of the clad above the substrate hc, the penetration depth hm, the clad width W, the dilution ratio D, and the wetting angle θ are determined by complex coupling of energy input and mass accumulation, and they are proportional to PF0.4/V, P0.5F/V, P/F0.2/V0.4, P2F0.6/V, PF0.7/V, P2/F/V0.3, P/V0.8, P/FV0.2, and PF7/V0.8, respectively. The large linear regression coefficients and the analysis residuals indicate the high reliability of the statistical linear regression models. This work aims to provide a comprehensive understanding of the influence of the main processing parameters on the morphological characteristics of the clad, which is of great value in providing a reference and laying a basis for the practical application of laser cladding technology at a high deposition rate.

Hidden blood loss and its influencing factors after cement augmentation for vertebral metastasis.

Introduction: Few studies have focused on the risk factors for hidden blood loss (HBL) during cement augmentation surgery for pathologic vertebral compression fraction (PVCFs). Method: From January 2014 to December 2020, the clinical data of 169 PVCF patients (283 levels) who underwent cement augmentation were retrospectively analysed. HBL was calculated according to the linear Gross formula using the patient's average Hct during the perioperative course and PBV. Multivariate linear regression analysis was performed to evaluate the independent factors associated with HBL. Results: The mean HBL was 448.2 ± 267.2 ml, corresponding to 10.8% ± 6.2% of the patient blood volume (PBV). There were significant differences between pre- and postoperative haematocrit (Hct) (P < 0.001) and Hb (P < 0.001), and 132 patients developed anaemia postoperatively, while 79 patients had anaemia preoperatively (P < 0.001). Multivariate linear regression revealed that bone lesion quality (p = 0.028), number of PVCFs (p = 0.002), amount of bone cement (p = 0.027), bone cement leakage (p = 0.001), and percentage of vertebral height loss (VHL) (p = 0.011) were independent risk factors for HBL. Conclusion: In conclusion, patients with lytic vertebral destruction, larger amounts of bone cement, greater amounts of bone cement leakage, more PVCF(s), and greater percentages of VHL may be more prone to HBL.

Predictive modeling of methylmercury in rice (Oryza sativa L.) and species-sensitivity-distribution-based derivation of the threshold of soil mercury in karst mountain areas.

The bioavailable mercury (Hg) in the soil is highly active and can affect the formulation of methyl-Hg (MeHg) in soil and its accumulation in rice. Herein, we predicted the concentration of MeHg in rice using bioavailable Hg extracted from soils; additionally, we determined the threshold value of soil Hg in karst mountain areas based on species sensitivity distribution. The bioavailable Hg was extracted using calcium chloride, hydrochloric acid (HCl), diethylenetriaminepentaacetic acid mixture, ammonium acetate, and thioglycolic acid. Results showed that HCl is the best extractant, and the prediction model demonstrated good predictability of the MeHg concentration in rice based on the HCl-extractable Hg, pH, and soil organic matter (SOM) data. Compared with the actual MeHg concentration in rice, approximately 99% of the predicted values (n = 103) were within the 95% prediction range, indicating the good performance of the rice MeHg prediction model based on soil pH, SOM, and bioavailable Hg in karst mountain areas. Based on this MeHg prediction model, the safety threshold of soil Hg was calculated to be 0.0936 mg/kg, which is much lower than the soil pollution risk screening value of agricultural land (0.5 mg/kg), suggesting that a stricter standard should be applied regarding soil Hg in karst mountain areas. This study presents the threshold of soil Hg pollution for rice safety in karst mountain areas, and future studies should target this threshold range.

Computational Fluid Dynamics Analysis and Empirical Evaluation of Carboxymethylcellulose/Alginate 3D Bioprinting Inks for Screw-Based Microextrusion.

Three-dimensional microextrusion bioprinting technology uses pneumatics, pistons, or screws to transfer and extrude bioinks containing biomaterials and cells to print biological tissues and organs. Computational fluid dynamics (CFD) analysis can simulate the flow characteristics of bioinks in a control volume, and the effect on cell viability can be predicted by calculating the physical quantities. In this study, we developed an analysis system to predict the effect of a screw-based dispenser system (SDS) on cell viability in bioinks through rheological and CFD analyses. Furthermore, carboxymethylcellulose/alginate-based bioinks were used for the empirical evaluation of high-viscous bioinks. The viscosity of bioinks was determined by rheological measurement, and the viscosity coefficient for the CFD analysis was derived from a correlation equation by non-linear regression analysis. The mass flow rate derived from the analysis was successfully validated by comparison with that from the empirical evaluation. Finally, the cell viability was confirmed after bioprinting with bioinks containing C2C12 cells, suggesting that the developed SDS may be suitable for application in the field of bioengineering. Consequently, the developed bioink analysis system is applicable to a wide range of systems and materials, contributing to time and cost savings in the bioengineering industry.

Factors affecting medical students' satisfaction with online learning: a regression analysis of a survey.

BACKGROUND: Medical education requires the implementation of different teaching methods and strategies for future doctors to achieve broad learning objectives. This wide range of methods and strategies includes the use of Information Technologies. For a long time, there was a call for a change in medical education for blending new teaching approaches to lessen medical students' class time. The COVID-19 pandemic then sped up the transition to the new way of medical education and classroom lectures were quickly moved to a virtual environment. We expect that these changes will continue, and online learning will be one of the main teaching strategies in medical education. Therefore, educational experiences during the COVID-19 pandemic will improve our understanding of online learning and will help to develop blended medical school curricula in the future. For this reason, we aimed to determine students' overall satisfaction with their online learning experience and to define the main factors affecting students' satisfaction with their online learning program at Cerrahpasa Medical Faculty. METHODS: A cross-sectional survey study was conducted to determine medical students' overall satisfaction with online learning methods and to identify factors associated with positive and negative satisfaction levels. A questionnaire, consisting of 24 questions to collect demographic characteristics, factors associated with online education experience and overall satisfaction levels was developed and distributed to 1600 medical students. Multivariable linear regression analysis was used to determine the factors associated with positive and negative satisfaction levels. RESULTS: Regression analysis showed that being familiar with online teaching techniques (ß = 0.19, 95% CI [0.07, 0.30], faculty members' higher online teaching skill levels (ß = 0.42, 95% CI [0.32, 0.51], interactive online teaching approaches (ß = 0.54, 95% CI [0.41, 0.67], having a personal workspace (ß = 0.43, 95% CI [0.19, 0.67], and a self-reported longer attention span (ß = 0.75, 95% CI [0.57, 0.92] were associated with higher overall satisfaction with online learning. The occurrence of technical problems (ß = -0.19, 95% CI [-0.26, -0.12] was associated with lower overall satisfaction. CONCLUSIONS: Higher online teaching skills of faculty members, use of interactive approaches, students' familiarity with online teaching techniques, provision of a personal workspace, and self-reported longer attention spans positively contributed to higher levels of student satisfaction with online learning. Considering the increasing significance of online educational methods, our study identified key components that affect students' level of satisfaction. This information might contribute to the development of online educational programs in the future.

Occurrence, source apportionment, and ecological risk of legacy and emerging per- and poly-fluoroalkyl substances (PFASs) in the Dahei river basin of a typical arid region in China.

Per- and poly-fluoroalkyl substances (PFASs) are artificial chemicals with broad commercial and industrial applications. Many studies about PFASs have been conducted in densely industrial and populated regions. However, fewer studies have focused on the PFASs' status in a typical arid region. Here, we investigated 30 legacy and emerging PFASs in surface water from the mainstream and tributaries of the Dahei River. Our results revealed that total PFASs concentrations (∑30PFASs) in water ranged from 3.13 to 289.1 ng/L (mean: 25.40 ng/L). Perfluorooctanoic acid (PFOA) had the highest mean concentration of 2.44 ng/L with a 100% detection frequency (DF), followed by perfluorohexanoic acid (PFHxA) (mean concentration: 1.34 ng/L, DF: 59.26%). Also, perfluorohexane sulfonate (DF: 44.44%), perfluorobutane sulfonate (DF: 88.89%), and perfluorooctane sulfonate (PFOS) (DF: 92.59%) had mean concentrations of 12.94, 2.00, and 1.05 ng/L, respectively. Source apportionment through ratio analysis and principal component analysis-multiple linear regression analysis showed that treated or untreated sewage, aqueous film-forming foam, degradation of precursors, and fluoropolymer production were the primary sources. The PFOS alternatives were more prevalent than those of PFOA. Conductivity, total phosphorus, and chlorophyll a positively correlated with Σ30PFASs and total perfluoroalkane sulfonates concentrations. Furthermore, ecological risk assessment showed that more attention should be paid to perfluorooctadecanoic acid, perfluorohexadecanoic acid, perfluorooctane sulfonate, perfluorohexane sulfonate, and (6:2 and 6:2/8:2) polyfluoroalkyl phosphate mono- and di-esters. The mass load of PFASs to the Yellow River was 1.28 kg/year due to the low annual runoff in the Dahei River in the arid region. This study provides baseline data for PFASs in the Dahei River that can aid in the development of effective management strategies for controlling PFASs pollution in typical arid regions in China.

Association of nuclear cataract prevalence with UV radiation and heat load in lens of older people -five city study.

Epidemiological studies have reported that the frequency of nuclear cataracts (NUCs) is high among the elderly and in tropical countries. Ultraviolet (UV) irradiation and lens temperature are considered as key physical contributors, although their precise quantification is difficult. The aim of this study is to investigate the association of NUC prevalence with UV irradiation and heat load. First, we assessed the lens temperature using thermodynamic modeling considering the thermophysiological response. We then conducted a multivariate linear regression analysis for the epidemiological analysis of NUC prevalence across five cities. A strong correlation was observed between NUC prevalence and the combined effects of UV irradiation and cumulative equivalent minutes at 43 °C (CEM43°C) derived from the computed lens temperature (adjusted R2 = 0.933, p < 0.0001). Heat load significantly contributed to the prevalence at 52%, surpassing the contributions of UV irradiation (31%) and the decline in DNA repair capacity in the lens (17%). These results suggested that both UV radiation and heat load are associated with NUC, with heat load contributing more. Our findings provided important implications for future interventions, particularly in the context of global warming.

Prediction of Electrical Resistance with Conductive Sewing Patterns by Combining Artificial Neural Networks and Multiple Linear Regressions.

This study aims to estimate the impact of sewing thread patterns on changes in the resistance of conductive yarns coated with silver paste. Firstly, the structure of the conductive yarns was examined, and various variations in the length and angle of individual sewing stitches were observed and analyzed through experiments. The results revealed that as the length of an individual stitch decreased, the width of the conductive yarn increased. Additionally, variations in the stitch angle resulted in different resistance values in the conductive yarn. These findings provide essential information for optimizing sewing patterns and designing components. Secondly, the comparison between models using multiple linear regression analysis and sewing neural networks was included to show optimized resistance prediction. The multiple linear regression analysis indicated that the stitch length and angle were significant variables affecting the resistance of the conductive thread. The artificial neural network model results can be valuable for optimizing sewing patterns and controlling resistance in various applications that utilize conductive thread. In addition, understanding the resistance variation in conductive thread according to sewing patterns and using optimized models to enhance component performance provides opportunities for innovation and progress. This research is necessary for the textile industry and materials engineering fields and holds high potential for practical applications in industrial settings.

The evaluation of potentially toxic elements using artificial neural networks and fuzzy linear regression analysis methods in cappadocian volcanic ash soils of Turkey.

The aim of this study is to determine the relationships between some potentially toxic elements (PTE) (Cu, Mn, Ni, Zn) in human stomach and intestinal tissues and toxic element contents in soil, vegetables and fruits. This study was conducted in the eastern of Erciyes Strato volcano, an area of 2400 km2 in Turkey. Tissue samples taken from the stomach and intestines of people living in the study area, soils, vegetables, and fruits were used as material. In the study, tissue samples of 26 people's stomach and intestines, 576 soil samples from 192 points and 3 different depths (0-30 cm, 30-60 cm, and 60-90 cm) and vegetable and fruit samples from 137 sampling points were taken. Cu, Mn, Ni, and Zn contents of human tissue samples, soil samples, vegetable and fruit samples were determined. Artificial Neural Networks method (ANN) and Fuzzy Linear Regression Analysis (FLRA) methods were used to determine the relationships between PTE contents in human tissue samples and soils, vegetables, and fruits. Root Mean squared error (RMSE) and coefficient of determination (R2) indices were used as the test criteria for goodness of fit. When compared with ANN method, it was determined that PTE values in stomach and intestinal tissue estimated by FLRA method had the lowest error and high R2 values. It was found that the most effective variable in estimating the average PTE value in stomach and intestinal tissue is PTE values in soil. It was determined that the FLRA regression analysis method has a better predictive power than the ANN method. Using FLRA and ANN regression methods, it was determined that there is a statistically high relationship between PTE contents in soils and stomach and intestinal tissues. It is recommended to make the study findings more meaningful with effective and reliable service planning by using different regression analysis methods in ecological and clinical studies.

Mass Spectrometry-Based Evaluation of the Bland-Altman Approach: Review, Discussion, and Proposal.

Reliable quantification in biological systems of endogenous low- and high-molecular substances, drugs and their metabolites, is of particular importance in diagnosis and therapy, and in basic and clinical research. The analytical characteristics of analytical approaches have many differences, including in core features such as accuracy, precision, specificity, and limits of detection (LOD) and quantitation (LOQ). Several different mathematic approaches were developed and used for the comparison of two analytical methods applied to the same chemical compound in the same biological sample. Generally, comparisons of results obtained by two analytical methods yields different quantitative results. Yet, which mathematical approach gives the most reliable results? Which mathematical approach is best suited to demonstrate agreement between the methods, or the superiority of an analytical method A over analytical method B? The simplest and most frequently used method of comparison is the linear regression analysis of data observed by method A (y) and the data observed by method B (x): y = α + ßx. In 1986, Bland and Altman indicated that linear regression analysis, notably the use of the correlation coefficient, is inappropriate for method-comparison. Instead, Bland and Altman have suggested an alternative approach, which is generally known as the Bland-Altman approach. Originally, this method of comparison was applied in medicine, for instance, to measure blood pressure by two devices. The Bland-Altman approach was rapidly adapted in analytical chemistry and in clinical chemistry. To date, the approach suggested by Bland-Altman approach is one of the most widely used mathematical approaches for method-comparison. With about 37,000 citations, the original paper published in the journal The Lancet in 1986 is among the most frequently cited scientific papers in this area to date. Nevertheless, the Bland-Altman approach has not been really set on a quantitative basis. No criteria have been proposed thus far, in which the Bland-Altman approach can form the basis on which analytical agreement or the better analytical method can be demonstrated. In this article, the Bland-Altman approach is re-valuated from a quantitative bioanalytical perspective, and an attempt is made to propose acceptance criteria. For this purpose, different analytical methods were compared with Gold Standard analytical methods based on mass spectrometry (MS) and tandem mass spectrometry (MS/MS), i.e., GC-MS, GC-MS/MS, LC-MS and LC-MS/MS. Other chromatographic and non-chromatographic methods were also considered. The results for several different endogenous substances, including nitrate, anandamide, homoarginine, creatinine and malondialdehyde in human plasma, serum and urine are discussed. In addition to the Bland-Altman approach, linear regression analysis and the Oldham-Eksborg method-comparison approaches were used and compared. Special emphasis was given to the relation of difference and mean in the Bland-Altman approach. Currently available guidelines for method validation were also considered. Acceptance criteria for method agreement were proposed, including the slope and correlation coefficient in linear regression, and the coefficient of variation for the percentage difference in the Bland-Altman and Oldham-Eksborg approaches.

Association between the Temporomandibular Joint Morphology and Chewing Pattern.

This study aimed to investigate whether the morphology of the temporomandibular joint (TMJ) is associated with chewing patterns while considering skeletal morphology, sex, age, and symptoms of temporomandibular disorder (TMD). A cross-sectional observational study of 102 TMJs of 80 patients (age 16-40 years) was performed using pretreatment records of cone-beam computed tomography imaging of the TMJ, mandibular kinesiographic records of gum chewing, lateral and posteroanterior cephalometric radiographs, patient history, and pretreatment questionnaires. To select appropriate TMJ measurements, linear regression analyses were performed using TMJ measurements as dependent variables and chewing patterns as the independent variable with adjustment for other covariates, including Nasion-B plane (SNB) angle, Frankfort-mandibular plane angle (FMA), amount of lateral mandibular shift, sex, age, and symptoms of TMD. In multiple linear regression models adjusted for other covariates, the length of the horizontal short axis of the condyle and radius of the condyle at 135° from the medial pole were significantly (p < 0.05) associated with the chewing patterns in the frontal plane on the working side. "Non-bilateral grinding" displayed a more rounded shape of the mandibular condyle. Conversely, "bilateral grinding" exhibited a flatter shape in the anteroposterior aspect. These findings suggest that the mandibular condyle morphology might be related to skeletal and masticatory function, including chewing patterns.

A retrospective study of air quality associated with teratogenic pathogen screening in women of reproductive age in southern China.

Adverse pregnancy outcomes are associated with a poor ambient atmospheric environment. Infections by teratogenic pathogens such as cytomegalovirus (CMV) and herpes simplex virus (HSV) are the main cause of the worse pregnant outcomes. However, environmental factors governing these infections are uncertain and epidemiological studies are limited. An epidemiological study on relationships between air pollutants and antibodies against teratogenic pathogens will be explored. In total, 5475 women of childbearing age were enrolled in the study between January 2018 and December 2019 in a hospital in Shantou, China. Antibodies against pathogens were measured by electrochemical luminescence. Everyday air quality data, concerning particulate matter (PM), sulfur dioxide (SO2), nitrogen dioxide (NO2), and other parameters, were acquired from a government web site, and the relationships between them were evaluated with nonparametric and multivariate linear regression analyses. Not only titers of herpes simplex virus HSV(I+II) IgGs in spring, but also titers of cytomegalovirus IgG (CMV IgG) and HSV I IgG in autumn, both had positive associations with concentrations of SO2. When PM2.5 or PM10 exposure is elevated, HSV(I+II) IgGs, TOX IgM should be paid more attention in spring or summer. Air pollution may be crucial for teratogenic pathogen infections. This study highlights air pollution could increase the risk of teratogenic pathogen infection, implying stronger measures should be taken to protect air environment and screenings of associated antibody should be strengthened in different season.