On analysis of topological indices and heat of formation for benzyl sulfamoyl network via curve fitting model.

The study explores the intricate relationship between topological indices and the heat of formation in the benzyl sulfamoyl network. Topological indices of benzyl sulfamoyl networks are studied and also emphasize their properties statistically. The benzyl sulfamoyl has unique properties due to its crystalline structure and it is used in the form of artificial substance. We analyze the distributions and correlations of the benzyl sulfamoyl network with others by using statistical methods and also build a computational analysis for topological indices. The findings show a strong association between the variables, indicating that topological indices may be used to accurately predict thermodynamic characteristics and improve the effectiveness of molecular modelling and simulation procedures.

In vitro fermentation potential of gut endogenous protein losses of growing pigs.

Fermentation of dietary and endogenous protein in the hindgut is generally considered detrimental to the health of pigs. We investigated the in vitro fermentation potential of porcine endogenous protein in ileal digesta and colonic mucus, using a N-free buffer with an excess of fermentable carbohydrates. Urea, whey protein isolate (WPI, positive control), WPI hydrolysate (WPIH), and combinations of the latter two were used to validate the assay. A new biphasic model, including a linear end simulation, fitted to the gas production data over a 48-h period identified the time point when substrate fermentation ended. A higher degree of hydrolysis of WPI resulted in a higher maximum gas production rate (Rmax, P < 0.01). Differences in Rmax and the time required to reach Rmax were observed among ileal digesta samples, with Rmax increasing with the insoluble protein content, and the highest Rmax occurring with colonic mucus samples (P < 0.05). The endogenous proteins entering the large intestine of pigs can ferment more rapidly compared to highly soluble and digestible protein sources, with Rmax positively correlated with decreasing solubility of endogenous nitrogenous components.

Protein fermentation in the hindgut of pigs can impact their health, affecting factors like growth rates and feed efficiency. Besides dietary protein, up to 50% of the protein entering the large intestine of growing pigs may be of endogenous origin. Therefore, we explored the fermentation potential of endogenous proteins compared to a well-known protein source, whey protein isolate (WPI). In developing and validating an in vitro gas production technique, we employed urea, WPI, WPI hydrolysate, and various combinations as substrates. The study introduces a new biphasic model for in vitro gas production, offering a detailed analysis of the fermentation process over a 48-h period. Our results revealed that porcine endogenous proteins can undergo rapid fermentation because the maximum gas production rate was higher compared to WPI. This insight is crucial for understanding the dynamics of protein fermentation in pigs. Additionally, we explored the solubility and molecular size of proteins, providing a comprehensive understanding of their fermentation characteristics. We found that endogenous proteins were less soluble compared to WPI but contained more smaller peptides. Unraveling the complexities of protein fermentation in pigs contributes to improvement of feed formulation for optimal gut health.

Biophysical essentials - A full stack open-source software framework for conserved and advanced analysis of patch-clamp recordings.

BACKGROUND AND OBJECTIVES: Patch-Clamp recordings allow for in depth electrophysiological characterization of single cells, their general biophysical properties as well as characteristics of voltage- and ligand-gated ionic currents. Different acquisition modes, such as whole-cell patch-clamp recordings in the current or voltage clamp configuration, capacitance measurements or single channel recordings from cultured cells as well as acute brain slices are routinely performed for these purposes. Nevertheless, multipurpose transparent and adaptable software tools to perform reproducible state-of-the-art analysis of multiple experiment types and to manage larger sets of experimental data are currently unavailable. METHODS: Biophysical Essentials (BPE) was developed as an open-source full stack python software for transparent and reproducible analysis of electrophysiological recordings. For validation, BPE results were compared with manually analyzed single-cell patch-clamp data acquired from a human in vitro nociceptor-model and mouse dorsal root ganglia neurons. RESULTS: While initially designed to improve time consuming and repetitive analysis steps, BPE was further optimized as a technical software solution for entire workflow processing including data acquisition, data preprocessing, normalization and visualization and of single recordings up to stacked calculations and statistics of multiple experiments. BPE can operate with different file formats from different amplifier systems and producers. An in-process database logs all analysis steps reproducible review and serves as a central storage point for recordings. Statistical testing as well as advanced analysis functions like Boltzmann-fitting and dimensional reduction methods further support the researchers' needs in projects involving electrophysiology techniques. CONCLUSIONS: BPE extends beyond available patch-clamp specific, open source - and commercial analysis tools in particular because of reproducible and sharable analysis workflows. BPE enables full analysis from raw data acquisition to publication ready result visualizations - all within one single program. Thereby, BPE significantly enhances transparency in the analytical process of patch-clamp data analysis. BPEs function scope is completely accessible through an easy-to-use graphical user interface eliminating the need for programing language proficiency as required by many community patch-clamp analysis frameworks and algorithms.

Experimental investigation of performance, emissions, combustion characteristics, cyclic variations, and exergy efficiency of CI engine fueled with Karanja-camphor oil blends and diesel-camphor oil blends.

This article compares the influence of blending the low-viscous oxygenated camphor oil with hydrocarbon diesel fuel and high-viscous oxygenated Karanja oil. The experiment is conducted in a four-stroke one-cylinder naturally aspirated Kirloskar compression ignition (CI) engine coupled with an eddy current dynamometer. The three types of fuel blends are prepared by blending the camphor oil with Karanja oil on the volume ratio of 30:70 (C30K70), 50:50 (C50K50), and 70:30 (C70K30), and the other three types of fuels are prepared by blending the camphor oil with diesel on the volume ratio of 30:70 (C30D70), 50:50 (C50D50), and 70:30 (C70D30). The experimental efficiency results show higher thermal efficiency of 31.86% and 30.84% for C70D30 and C70K30 at rated operating conditions. The brake-specific energy consumptions of C70D30 and C70K30 were found to be 11.29 and 11.67 MJ/kWh, respectively, at rated operating conditions. The lowest CO, CO2, HC, and smoke emissions are found for C70D30 at rated operating conditions, which are 96.58%, 6.15%, 34.20%, and 7.59% lower than diesel. However, the NO emissions were found to be 27.62% higher for C70D30 than diesel at full load. The rate of pressure rise, net heat release rate, and cyclic variations were found to increase with increase in proportion of the camphor oil. The P-v diagram also confirms the lower heat addition period for the C70D30 and C70K30 with an increase in brake thermal efficiency. The actual compression ratio and the actual cutoff ratio are found to have a reasonable correlation with the thermal efficiency of the engine. The exergy efficiency of C30K70 is found higher which is 2.11% higher than diesel fuel at rated power. Second-order polynomial equations were obtained for the engine characteristics using the curve fitting method, and the characteristic equations confirmed the confidence level of 95%.

Evaluating models that predict epoxy conversion using rheological properties.

Simultaneous rheology and conversion measurements of neat and composite epoxy resins reveal that conventional models neither accurately nor fully describe the relationship between rheology and conversion. We find that models predicting thermoset conversion based on mixing rules of rheological properties are quantitatively inaccurate and do not account for chemical gelation. Models based on percolation theory and the divergence of the viscosity at the gel point are more accurate but only valid before the gel point. Here, we propose the use of the generalized effective medium (GEM) model, which incorporates the divergence of rheological properties on both sides of the critical gel point. We show that the GEM model works well for both neat resins and filled systems, and the resulting parameters estimate the gel point and scaling behavior on either side of the sol-gel transition.

DSFworld: A flexible and precise tool to analyze differential scanning fluorimetry data.

Differential scanning fluorimetry (DSF) is a method to determine the apparent melting temperature (Tma) of a purified protein. In DSF, the raw unfolding curves from which Tma is calculated vary widely in shape and complexity. However, the tools available for calculating Tma are only compatible with the simplest of DSF curves, hindering many otherwise straightforward applications of the technology. To overcome this limitation, we designed new mathematical models for Tma calculation that accommodate common forms of variation in DSF curves, including the number of transitions, the presence of high initial signal, and temperature-dependent signal decay. When tested these models against DSFbase, an open-source database of 6235 raw, real-life DSF curves, these models outperformed the existing standard approaches of sigmoid fitting and maximum of the first derivative. To make these models accessible, we created an open-source software and website, DSFworld (https://gestwickilab.shinyapps.io/dsfworld/). In addition to these improved fitting capabilities, DSFworld also includes features that overcome the practical limitations of many analysis workflows, including automatic reformatting of raw data exported from common qPCR instruments, labeling of data based on experimental variables, and flexible interactive plotting. We hope that DSFworld will enable more streamlined and accurate calculation of Tma values for DSF experiments.

Towards non-invasive tissue hydration measurements with optical coherence tomography.

The attenuation coefficient ( µ OCT ) measured by optical coherence tomography (OCT) has been used to determine tissue hydration. Previous dual-wavelength OCT systems could not attain the needed precision, which we attribute to the absence of wavelength-dependent scattering of tissue in the underlying model. Assuming that scattering can be described using two parameters, we propose a triple/quadrupole-OCT system to achieve clinically relevant precision in water volume fraction. In this study, we conduct a quantitative analysis to determine the necessary precision of µ OCT measurements and compare it with numerical simulation. Our findings emphasize that achieving a clinically relevant assessment of a 2% water fraction requires determining the attenuation coefficient with a remarkable precision of 0.01 m m - 1 . This precision threshold is influenced by the chosen wavelength for attenuation measurement and can be enhanced through the inclusion of a fourth wavelength range.

Global Trends of Medical Misadventures Using International Classification of Diseases, Tenth Revision Cluster Y62-Y69 Comparing Pre-, Intra-, and Post-COVID-19 Pandemic Phases: Protocol for a Retrospective Analysis Using the TriNetX Platform.

BACKGROUND: The COVID-19 pandemic has sharpened the focus on health care safety and quality, underscoring the importance of using standardized metrics such as the International Classification of Diseases, Tenth Revision (ICD-10). In this regard, the ICD-10 cluster Y62-Y69 serves as a proxy assessment of safety and quality in health care systems, allowing researchers to evaluate medical misadventures. Thus far, extensive research and reports support the need for more attention to safety and quality in health care. The study aims to leverage the pandemic's unique challenges to explore health care safety and quality trends during prepandemic, intrapandemic, and postpandemic phases, using the ICD-10 cluster Y62-Y69 as a key tool for their evaluation. OBJECTIVE: This research aims to perform a comprehensive retrospective analysis of incidence rates associated with ICD-10 cluster Y62-Y69, capturing both linear and nonlinear trends across prepandemic, intrapandemic, and postpandemic phases over an 8-year span. Therefore, it seeks to understand how these trends inform health care safety and quality improvements, policy, and future research. METHODS: This study uses the extensive data available through the TriNetX platform, using an observational, retrospective design and applying curve-fitting analyses and quadratic models to comprehend the relationships between incidence rates over an 8-year span (from 2015 to 2023). These techniques will enable the identification of nuanced trends in the data, facilitating a deeper understanding of the impacts of the COVID-19 pandemic on medical misadventures. The anticipated results aim to outline complex patterns in health care safety and quality during the COVID-19 pandemic, using global real-world data for robust and generalizable conclusions. This study will explore significant shifts in health care practices and outcomes, with a special focus on geographical variations and key clinical conditions in cardiovascular and oncological care, ensuring a comprehensive analysis of the pandemic's impact across different regions and medical fields. RESULTS: This study is currently in the data collection phase, with funding secured in November 2023 through the Ricerca Corrente scheme of the Italian Ministry of Health. Data collection via the TriNetX platform is anticipated to be completed in May 2024, covering an 8-year period from January 2015 to December 2023. This dataset spans pre-pandemic, intra-pandemic, and early post-pandemic phases, enabling a comprehensive analysis of trends in medical misadventures using the ICD-10 cluster Y62-Y69. The final analytics are anticipated to be completed by June 2024. The study's findings aim to provide actionable insights for enhancing healthcare safety and quality, reflecting on the pandemic's transformative impact on global healthcare systems. CONCLUSIONS: This study is anticipated to contribute significantly to health care safety and quality literature. It will provide actionable insights for health care professionals, policy makers, and researchers. It will highlight critical areas for intervention and funding to enhance health care safety and quality globally by examining the incidence rates of medical misadventures before, during, and after the pandemic. In addition, the use of global real-world data enhances the study's strength by providing a practical view of health care safety and quality, paving the way for initiatives that are informed by data and tailored to specific contexts worldwide. This approach ensures the findings are applicable and actionable across different health care settings, contributing significantly to the global understanding and improvement of health care safety and quality. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/54838.

Relationship between glycated hemoglobin levels and three-month outcomes in acute ischemic stroke patients with or without diabetes: a prospective Korean cohort study.

OBJECTIVE: In patients experiencing acute ischemic stroke, there is ongoing debate surrounding the connection between chronic hyperglycemic status and their initial clinical outcomes. Our objective was to examine the connection between glycated hemoglobin (HbA1c) levels and adverse clinical outcomes at both 3-months adverse clinical outcomes in individuals with acute ischemic stroke (AIS) with and without diabetes. METHODS: The present prospective cohort study involved 896 AIS patients without diabetes and 628 with diabetes treated at a South Korean hospital from January 2010 to December 2016. The target independent variable is HbA1c. The outcome variable is a modified Rankin scale score ≥ 3. A binary logistic regression model was applied to assess the connection between HbA1c levels and 3-month poor clinical outcomes in AIS patients with and without diabetes. Additionally, a generalized additive model and smoothed curve fitting were utilized to explore potential nonlinear associations between HbA1c levels and 3-month adverse clinical outcomes in AIS patients with and without diabetes. RESULTS: The binary logistic regression model could not identify any statistically significant connection between HbA1c and 3-month adverse clinical outcomes in AIS patients, both those with and without diabetes, after correcting for various factors. However, a nonlinear relationship emerged between HbA1c and 3-month adverse clinical outcomes in AIS patients with diabetes. The inflection point for HbA1c was determined to be 6.1%. For HbA1c values ≤ 6.1%, an inverse association was observed between HbA1c and 3-month adverse clinical outcomes in diabetic AIS patients, and each 1% increase in HbA1c in AIS patients with DM was associated with an 87% reduction in 3-month adverse clinical outcomes (OR = 0.13, 95% CI: 0.02-0.81). Conversely, when HbA1c exceeded 6.1%, a positive association between HbA1c and 3-month adverse clinical outcomes became apparent in diabetic AIS patients, and each 1% increase in HbA1c in AIS patients with DM was associated with a 23% increase in 3-month adverse clinical outcomes (OR = 1.23, 95%CI: 1.03-1.47). However, it's important to note that no significant linear or nonlinear relationships were observed between HbA1c levels and 3-month adverse clinical outcomes in AIS patients without diabetes. CONCLUSION: Our findings suggest a nonlinear connection and threshold effect between HbA1c and 3-month adverse clinical outcomes in AIS patients with diabetes. AIS patients with diabetes had a lower risk of 3-month adverse clinical outcomes when their HbA1c control was close to 6.1%. Our findings may aid treatment decision-making and potentially guide interventions to optimize glycemic control in AIS patients.

Association of serum vitamin D with anxiety in US adults: a cross-sectional study.

Objective: There have been proposals that vitamin D may be associated with a reduction in the incidence of anxiety disorders. However, the findings thus far have been inconsistent, warranting further investigation. The purpose of this paper is to explore the link between serum vitamin D and anxiety. Methods: Data are from the National Health and Nutrition Examination Survey (NHANES) in the United States from 2007 to 2012. Study included a total of 12,232 participants, and through the multivariate logistic regression to study the relationship between serum vitamin D and anxiety, smooth curve fitting is used to study the nonlinear relationship between serum vitamin D levels and anxiety. Results: Serum vitamin D levels demonstrated a negative correlation with anxiety (p < 0.001). Vitamin D exhibited a significant impact on anxiety (Q4:OR = 0.774, 95% CI: 0.663-0.903, p < 0.01), and this effect remained significant even after adjusting for confounding variables (Q4:OR = 0.781, 95% CI: 0.669-0.912, p < 0.01). Smoothed curve fitting revealed a negative association between serum vitamin D levels and the risk of anxiety, and these findings persisted after accounting for confounding variables. Conclusion: Serum vitamin D levels were inversely associated with anxiety risk in US adults. In the future, more accurate prospective studies are needed to confirm this result.

Link between triglyceride-glucose-body mass index and future stroke risk in middle-aged and elderly chinese: a nationwide prospective cohort study.

OBJECTIVE: Current literature is deficient in robust evidence delineating the correlation between the triglyceride glucose-body mass index (TyG-BMI) and the incidence of stroke. Consequently, this investigation seeks to elucidate the potential link between TyG-BMI and stroke risk in a cohort of middle-aged and senior Chinese individuals. METHODS: This study employs longitudinal data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, and 2018, encompassing 8,698 participants. The CHARLS cohort was assembled using a multistage probability sampling technique. Participants underwent comprehensive evaluations through standardized questionnaires administered via face-to-face interviews. Our analytic strategy involved the application of Cox proportional hazards regression models to investigate the association between TyG-BMI and the risk of stroke. To discern potential non-linear relationships, we incorporated Cox proportional hazards regression with smooth curve fitting. Additionally, we executed a battery of sensitivity and subgroup analyses to validate the robustness of our findings. RESULTS: Our study utilized a multivariate Cox proportional hazards regression model and found a significant correlation between the TyG-BMI and the risk of stroke. Specifically, a 10-unit increase in TyG-BMI corresponded to a 4.9% heightened risk of stroke (HR = 1.049, 95% CI 1.029-1.069). The analysis also uncovered a non-linear pattern in this relationship, pinpointed by an inflection point at a TyG-BMI value of 174.63. To the left of this inflection point-meaning at lower TyG-BMI values-a 10-unit hike in TyG-BMI was linked to a more substantial 14.4% rise in stroke risk (HR 1.144; 95% CI 1.044-1.253). Conversely, to the right of the inflection point-at higher TyG-BMI values-each 10-unit increment was associated with a smaller, 3.8% increase in the risk of stroke (HR 1.038; 95% CI 1.016-1.061). CONCLUSIONS: In the middle-aged and elderly Chinese population, elevated TyG-BMI was significantly and positively associated with stroke risk. In addition, there was also a specific non-linear association between TyG-BMI and stroke (inflection point 174.63). Further reduction of TyG-BMI below 174.63 through lifestyle changes and dietary control can significantly reduce the risk of stroke.

The Changes in Relative Blood Volume during Dialysis Are Characterized by Ultrafiltration Rate and Predialysis Blood Test Values.

INTRODUCTION: Continuous monitoring of relative blood volume (percentage BV) in hemodialysis (HD) is critical for determining dry weight and preventing intradialytic hypotension. However, the cause of the BV variation remains unknown. This research aimed to examine factors that influence the percentage BV. METHODS: We devised a formula based on coefficients ("a," "τ," and "b") to predict changes in percentage BV. "a" denotes a significant decrease in percentage BV in the early stages of HD. "τ" represents the transition from early to late phase of HD. "b" denotes the slope of the decrease in percentage BV in the late phase of HD. We measured the percentage BV in 18 patients with end-stage renal disease. The coefficients were estimated by fitting experimental data from patients using a least squares optimization algorithm. A correlation analysis of these parameters and patient predialysis data was performed. RESULTS: Ultrafiltration rate (UFR) was found to be negatively correlated with "b" (r = -0.851, p < 0.01). However, UFR was not significantly related to "a." Predialysis serum total protein level was negatively correlated with "a" (r = -0.531, p = 0.042). Predialysis serum albumin and predialysis sodium were not significantly correlated with "a" and "τ." Plasma osmolarity did not have a significant relationship with "a" and "τ." DISCUSSION/CONCLUSION: UFR influenced the decrease in percentage BV in the late phase but did not influence the decrease of percentage BV in the early phase. "a" was associated with predialysis serum total protein level but not with plasma osmolality or predialysis sodium. This implies that colloid oncotic pressure is important for plasma refilling immediately after dialysis begins. During the change of percentage BV, the decrease in the early phase of dialysis was not related to UFR, but related to other parameters, especially predialysis total protein level. A decrease in the late phase of dialysis is related to UFR.

Factors influencing C-reactive protein status on admission in neonates after birth.

OBJECTIVE: To explore the factors influencing C-reactive protein (CRP) status in neonates on admission after birth. METHODS: 820 newborns born and hospitalized at Xiangya Hospital of Central South University from Jan. 2020 to Dec. 2020 were retrospectively analyzed. Maternal medical history and medication use during pregnancy, neonatal demographic information and status at birth were collected through the electronic medical record system. Statistical software was used to analyze the possible relationship between perinatal factors and CRP on admission after birth. RESULTS: A total of 820 neonates were analyzed, including 463 males and 357 females with a mean gestational age (GA) of 36.07 ± 3.30 weeks. (1) Multifactor Logistic regression analysis: larger GA (OR: 1.13, 95%CI: 1.00-1.28, P = 0.042), premature rupture of membranes (PROM) ≥ 18 h (OR: 2.39, 95%CI: 1.35-4.23, P = 0.003) and maternal autoimmune diseases (OR: 5.30, 95%CI: 2.15-13.07, P < 0.001) were independent risk factors for CRP ≥ 8 mg/L. Cesarean delivery (OR 0.40, 95%CI: 0.26-0.60, P < 0.001) was independent protective factor for CRP ≥ 8 mg/L. (2) Threshold effect analysis: A non-linear relationship was found between GA and CRP. When GA is less than 33.9 weeks, the risk of CRP ≥ 8 mg/L was reduced by 28% with one week increased (P < 0.001), and when GA is more than 33.9 weeks, the risk of CRP ≥ 8 mg/L was increased by 61% with one week increased (P < 0.001). CONCLUSIONS: GA, PROM, maternal autoimmune diseases and cesarean delivery were all independent influences neonatal CRP ≥ 8 mg/L on admission, and there was a nonlinear relationship between GA and neonatal CRP ≥ 8 mg/L on admission.

Blood urea nitrogen has a nonlinear association with 3-month outcomes with acute ischemic stroke: A second analysis based on a prospective cohort study.

BACKGROUND: Evidence regarding the relationship between blood urea nitrogen (BUN) and 3-month outcomes in acute ischemic stroke (AIS) patients is still scarce. Therefore, the present study was preformed to explore the link between the BUN and 3-month poor outcomes in patients with AIS. METHODS: A retrospective study of 1866 participants with AIS enrolled from January 2010 to December 2016 at a hospital in South Korea. Binary logistic regression, smooth curve fitting, and a set of sensitivity analyses were used to analyze the association between BUN and 3-month poor outcomes. RESULTS: After adjusting covariates, the results of the binary logistic regression model suggested that the relationship between the BUN and the risk of 3-month poor outcomes for AIS patients was not statistically significant. However, there was a special nonlinear relationship between them, and the inflection point of the BUN was 13 mg/dl. On the left side of the inflection point, every unit increase in the BUN reduces the risk of 3-month poor outcomes by 14.1 % (OR = 0.859, 95%CI: 0.780-0.945, p = 0.0019). On the right side of the inflection point, the relationship is not statistically significant. CONCLUSION: There is a nonlinear relationship with saturation effect between BUN level and 3-month poor outcomes in AIS patients. Maintaining the BUN at around 13 mg/dl can reduce the risk of 3-month poor outcome in AIS patients.

Association between platelet­to­lymphocyte ratio and serum prostate specific antigen.

There is evidence that the systemic inflammatory response may have an impact on prostate-specific antigen (PSA) levels. However, the relationship between the platelet-to-lymphocyte ratio (PLR) and PSA remains unclear. As a result, the relationship between PLR and PSA using the National Health and Nutrition Examination Survey (NHANES) database was examined. After the screening, 6,638 participants out of 52,186 in the NHANES survey conducted between 2001 to 2010 were suitable for the present study. The PLR was the independent variable in the present study, and PSA was the dependent variable. The selected subjects in the present study had an average age of 58.563±11.848 years. After controlling for covariates, the results showed that with every increase in PLR, the PSA concentration increased by 0.004 ng/ml (0.001, 0.007). This difference was statistically significant. Furthermore, a smoothing curve based on a fully adjusted model was created to investigate the possibility of a linear relationship between PLR and PSA concentration in men from USA. In men from USA, an independent and positive correlation between PLR and PSA was identified, which could potentially result in overdiagnosis of asymptomatic prostate cancer in populations with higher PLR levels.

Repeatability and reproducibility comparisons of liver IVIM imaging with free-breathing or respiratory-triggered sequences.

For liver intravoxel incoherent motion (IVIM) data acquisition, respiratory-triggering (RT) MRI is commonly used, and there are strong motivations to shorten the scan duration. For the same scan duration, more b values or higher numbers of excitations can be allowed for free-breathing (FB) imaging than for RT. We studied whether FB can be used to replace RT when careful IVIM image acquisition and image processing are conducted. MRI data of 22 healthy participants were acquired using a 3.0 T scanner. Diffusion imaging was based on a single-shot spin-echo-type echo-planar sequence and 16 b values of 0, 2, 4, 7, 10, 15, 20, 30, 46, 60, 72, 100, 150, 200, 400, and 600 s/mm2 . Each subject attended two scan sessions with an interval of 10-20 days. For each scan session, a subject was scanned twice, first with RT and then with FB. The mean image acquisition time was 5.4 min for FB and 10.8 min for RT. IVIM parameters were calculated with bi-exponential model segmented fitting with a threshold b value of 60 s/mm2 , and fitting started from b = 2 s/mm2 . There was no statistically significant difference between IVIM parameters measured with FB imaging or RT imaging. Perfusion fraction ICC (intraclass correlation coefficient) for FB imaging and RT imaging in the same scan session was 0.824. For perfusion fraction, wSD (within-subject standard deviation), BA (Bland-Altman) difference, BA 95% limit, and ICC were 0.022, 0.0001, -0.0635~0.0637, and 0.687 for FB and 0.031, 0.0122, -0.0723~0.0967, and 0.611 for RT. For Dslow (×10-3  s/mm2 ), wSD, BA difference, BA 95% limit, and ICC were 0.057, 0.0268, -0.1258~0.1793, and 0.471 for FB and 0.073, -0.0078, -0.2170-0.2014, and <0.4 for RT. The Dfast coefficient of variation was 0.20 for FB imaging and 0.28 for RT imaging. All reproducibility indicators slightly favored FB imaging.

Determination of the radii of coated and uncoated silicon AFM sharp tips using a height calibration standard grating and a nonlinear regression function.

AFM sharp tips are used to characterize nanostructures and quantify the mechanical properties of the materials in several areas of research. The analytical results can show unpredicted errors if we do not know the exact values of the AFM tip radius. There are many techniques of in situ measurements for determining the actual AFM tip radius, but they are limited to uncoated tips. This paper presents an alternative and simple method to determine the radii of coated tips and an uncoated tip. Pt-coated, Cr/Au-coated, and uncoated Si tips were used to scan a calibration standard grating in AFM contact mode with sub-nanonewton load to obtain the curved scan profile of the edge corner of the grating structure. The data points of the curved profile of each tip were fitted with a nonlinear regression function to estimate the curvature radius of the tip. The results show that the estimated radius of the coated tips is in the range of nominal values provided by the tip manufacturer, while the estimated radius of the uncoated Si tip is bigger than the nominal radius because of tip blunting during the scan. However, this method yields an accurate estimate of the tip radius with a low root mean squared error of the curve fitting results.

Comparison of Three Prediction Models for Predicting Chronic Obstructive Pulmonary Disease in China.

Purpose: To predict the future number of patients with chronic obstructive pulmonary disease (COPD) in China and compare the three prediction models. Methods: A generalized additive model (GAM), autoregressive integrated moving average (ARIMA) model, and curve-fitting method were used to fit and predict the number of patients with COPD in China. Data on the number of patients with COPD in China from 1990 to 2019 were obtained from the Global Burden of Disease (GBD) database. The coefficient of determination (R2), mean absolute error (MAE), mean absolute percentage error (MAPE), root mean squared error (RMSE), relative error of prediction, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) were used to evaluate and compare the fitting effect, prediction effect, and reliability of the three models. Results: The GAM, ARIMA, and curve-fitting methods could predict future trends in COPD in China. The performance of the GAM is the best among the three models, whereas the curve fitting method is the worst, and the ARIMA (0,1,2) model is in between. The prediction results of the three models showed that the number of patients with COPD in China is expected to increase from 2020 to 2025. Conclusion: GAM and AIRMA models are recommended for predicting the future prevalence of COPD in China. The number of patients with COPD in China is expected to increase in the next few years. The prevention and control of COPD in China still needs to be strengthened. Using appropriate models to predict future trends in COPD will provide support for health policymakers.

Auxiliary Diagnostic Signal for Deep-Level Detection.

We propose and demonstrate that temperature-dependent curve-fitting error values of the Schottky diode I-V curve in the forward regime can be an auxiliary diagnostic signal as the temperature-scan Capacitance DLTS (CDLTS) signals and helps to work time-efficiently with high accuracy when using the Laplace Transform (LT)-DLTS or Isothermal Capacitance transient spectroscopy (ICTS) method. Using Be-doped GaAs showing overlapping DLTS signals, we verify that the LT-DLTS or ICTS analysis within a specific temperature range around the characteristic temperature Tpeak coincides well with the results of the CDLTS and Fourier Transform DLTS performed within the whole temperature range. In particular, we found that the LT-DLTS signals appeared intensively around Tpeak, and we confirmed it with the ICTS result. The occurrence of the curve fitting error signal is attributed to the relatively increased misfit error by the increased thermal emission from the deep-level trap in the case near the Tpeak, because the applied transport model excludes defect characteristics.

TitrationAnalysis: a tool for high throughput binding kinetics data analysis for multiple label-free platforms.

Label-free techniques including Surface Plasmon Resonance (SPR) and Biolayer Interferometry (BLI) are biophysical tools widely used to collect binding kinetics data of bimolecular interactions. To efficiently analyze SPR and BLI binding kinetics data, we have built a new high throughput analysis tool named the TitrationAnalysis. It can be used as a package in the Mathematica scripting environment and ultilize the non-linear curve-fitting module of Mathematica for its core function. This tool can fit the binding time course data and estimate association and dissociation rate constants ( k a and k d respectively) for determining apparent dissociation constant ( K D) values. The high throughput fitting process is automatic, requires minimal knowledge on Mathematica scripting and can be applied to data from multiple label-free platforms. We demonstrate that the TitrationAnalysis is optimal to analyze antibody-antigen binding data acquired on Biacore T200 (SPR), Carterra LSA (SPR imaging) and ForteBio Octet Red384 (BLI) platforms. The k a, k d and K D values derived using TitrationAnalysis very closely matched the results from the commercial analysis software provided specifically for these instruments. Additionally, the TitrationAnalysis tool generates user-directed customizable results output that can be readily used in downstream Data Quality Control associated with Good Clinical Laboratory Practice operations. With the versatility in source of data input source and options of analysis result output, the TitrationAnalysis high throughput analysis tool offers investigators a powerful alternative in biomolecular interaction characterization.