Low Levels of IgM Recognizing 4-Hydroxy-2-Nonenal-Modified Apolipoprotein A-I Peptide and Its Association with the Severity of Coronary Artery Disease in Taiwanese Patients.

Autoantibodies against apolipoprotein A-I (ApoA-I) are associated with cardiovascular disease risks. We aimed to examine the 4-hydroxy-2-nonenal (HNE) modification of ApoA-I in coronary artery disease (CAD) and evaluate the potential risk of autoantibodies against their unmodified and HNE-modified peptides. We assessed plasma levels of ApoA-I, HNE-protein adducts, and autoantibodies against unmodified and HNE-peptide adducts, and significant correlations and odds ratios (ORs) were examined. Two novel CAD-specific HNE-peptide adducts, ApoA-I251-262 and ApoA-I70-83, were identified. Notably, immunoglobulin G (IgG) anti-ApoA-I251-262 HNE, IgM anti-ApoA-I70-83 HNE, IgG anti-ApoA-I251-262, IgG anti-ApoA-I70-83, and HNE-protein adducts were significantly correlated with triglycerides, creatinine, or high-density lipoprotein in CAD with various degrees of stenosis (<30% or >70%). The HNE-protein adduct (OR = 2.208-fold, p = 0.020) and IgM anti-ApoA-I251-262 HNE (2.046-fold, p = 0.035) showed an increased risk of progression from >30% stenosis in CAD. HNE-protein adducts and IgM anti-ApoA-I251-262 HNE may increase the severity of CAD at high and low levels, respectively.

Contributors to Hospitalized Infective Endocarditis Outcomes Among Patients With Substance Use.

Background: Patients with substance use (SU) diagnosed with infective endocarditis (IE) have high rates of discharge against medical advice (DAMA) and 30-day readmission. Objective: Evaluate contributors associated with DAMA and 30-day readmission among patients with SU and IE. Methods: This retrospective chart review included patients >18 years, admitted to one hospital in the Northeastern, United States for SU and IE from January 2018 to December 2020. Patient demographic and clinical characteristics and their association with DAMA and 30-day readmission were summarized using descriptive statistics and Logistic Regression. Results: Of the 144 patients, 60.4% used more than one substance, 38.2% experienced DAMA, and 61.1% were readmitted within 30 days. Age (odds ratio [OR], 0.96; 95% confidence interval [CI], 0.92-0.98), Length of stay (LOS) (OR, 0.95; 95% CI, 0.93-0.98), Medicaid (OR, 2.98; 95% CI, 1.45-6.16), Medicare (OR, 0.29; 95% CI, 0.10-0.81), opioid usage (OR, 2.29; 95% CI, 1.01-5.16), and stimulant usage (OR, 2.89; 95% CI, 1.43-5.84) were all significantly associated with DAMA but not with 30-day readmission. Conclusions: Additional investigations of factors associated with DAMA and 30-day readmission are needed to help improve practices and reduce negative outcomes. Implications for Nursing: Multiple factors can affect patient adherence to treatment in this high-risk population. Nursing directly impacts the identification and addressing of unique SU IE patient needs to optimize treatment goals.

PVP/CS/Phyllanthus emblica Nanofiber Membranes for Dry Facial Masks: Manufacturing Process and Evaluations.

In the wake of increasing demands on skin health, we propose simple, natural, and safe dry facial masks that restrict melanin synthesis. Phyllanthus emblica (P. emblica) is made into powders via a low-temperature extraction and freeze-drying process to serve as a natural agent. Next, it is added to mixtures containing Polyvinylpyrrolidone (PVP) and Chitosan (CS), after which the blends are electrospun into PVP/CS/P. emblica nanofiber membrane dry facial masks using the electrospinning technique. The dry facial masks are evaluated using the calibration analysis method, extraction rate test, scanning electron microscopy (SEM), release rate test, tyrosinase inhibition assay, biocompatibility test, and anti-inflammatory capacity test. Test results indicate that when the electrospinning mixture contains 29.0% P. emblica, the nanofibers have a diameter of ≤214.27 ± 74.51 nm and a water contact angle of 77.25 ± 2.21. P. emblica is completely released in twenty minutes, and the tyrosinase inhibition rate reaches 99.53 ± 0.45% and the cell activity ≥82.60 ± 1.30%. Moreover, the anti-inflammatory capacity test results suggest that dry facial masks confine inflammatory factors. PVP/CS/P. emblica nanofiber dry facial masks demonstrate excellent tyrosinase inhibition and are hydrophilic, biocompatible, and inflammation-free. The dry facial masks are a suitable material that is worthwhile exploring and applying to the cosmetic field.

A Study on Highly Effective Electromagnetic Wave Shield Textile Shell Fabrics Made of Point Polyester/Metallic Core-Spun Yarns.

In this study, stainless steel (SS) filaments are wrapped in Ge fibers to form core-spun yarns. The yarns along with 500 D polyester (PET) fibers undergo weaving, thereby forming functional woven fabrics. The experiment is composed of two parts:yarns and fabrics. The yarns are twisted with TPI of 8, 9, 10, 11, and 12, and then tested for tensile strength and tensile elongation. The yarns possess mechanical properties that are dependent on the TPI-the higher the TPI, the better the mechanical properties. The maximal mechanical properties occur when the core-spun yarns are made of 12 TPI where the maximal tensile strength is 5.26 N and the lowest elongation is 43.2%. As for the functional woven fabrics, they are made of Ge/SS core-spun yarns as the weft yarns and 500 D PET yarns as the warp yarns. The tensile strength, tensile elongation, negative ion release, electromagnetic interference shielding effectiveness (EMI SE), and air permeability tests are conducted, determining the optimal woven fabrics. The 12 TPI core-spun yarns provide the woven fabrics with the maximal tensile strength of 153.6 N and the optimal elongation at break of 10.08%. In addition, the woven fabrics made with 8 or 9 TPI core-spun yarns exhibit an optimal EMI SE of 41 dB, an optimal air permeability of 212 cm3/cm2/s, and an optimal release amount of negative ion of 550-600 ions/cc. The proposed woven fabrics have a broad range of applications, such as functional garments and bedding.

A Study on Preparation and Property Evaluations of Composites Consisting of TPU/Triclosan Membranes and Tencel®/LMPET Nonwoven Fabrics.

This study investigated eco-friendly antibacterial medical protective clothing via the nonwoven process and characteristic evaluations. Firstly, Tencel® fibers and low melting point polyester (LMPET) fibers (re-sliced and granulated from recycled PET bottles) were mixed at different ratios and then needle punched at diverse needle rolling depths. The influences of manufacturing parameters on the Tencel®/LMPET nonwoven fabrics were examined in terms of mechanical properties, water vapor transmission rate, and stiffness. Next, Tencel®/LMPET nonwoven fabrics were combined with thermoplastic polyurethane (TPU)/Triclosan antibacterial membranes that contained different contents of triclosan using melt processing technology. The resulting Tencel®/LMPET/TPU/Triclosan composites were characterized via different measurements; an optimal bursting strength of 86.86 N, an optimal horizontal tensile strength of 41.90 N, and an optimal stiffness along the MD and CD of 8.60 cm were recorded. Furthermore, the Tencel®/LMPET/TPU/Triclosan composites exhibited a distinct inhibition zone in the antibacterial measurement, and the hydrostatic pressure met the requirements of the EN 14126:2003 and GB 19082-200 disposable medical protective gear test standards.

A Coronary Artery Disease Monitoring Model Built from Clinical Data and Alpha-1-Antichymotrypsin.

Coronary artery disease (CAD) is one of the most common subtypes of cardiovascular disease. The progression of CAD initiates from the plaque of atherosclerosis and coronary artery stenosis, and eventually turns into acute myocardial infarction (AMI) or stable CAD. Alpha-1-antichymotrypsin (AACT) has been highly associated with cardiac events. In this study, we proposed incorporating clinical data on AACT levels to establish a model for estimating the severity of CAD. Thirty-six healthy controls (HCs) and 162 CAD patients with stenosis rates of <30%, 30−70%, and >70% were included in this study. Plasma concentration of AACT was determined by enzyme-linked immunosorbent assay (ELISA). The receiver operating characteristic (ROC) curve analysis and associations were conducted. Further, five machine learning models, including decision tree, random forest, support vector machine, XGBoost, and lightGBM were implemented. The lightGBM model obtained a sensitivity of 81.4%, a specificity of 67.3%, and an area under the curve (AUC) of 0.822 for identifying CAD patients with a stenosis rate of <30% versus >30%. In this study, we provided a demonstration of a monitoring model with clinical data and AACT.

A Study on Carbon Fiber Composites with Low-Melting-Point Polyester Nonwoven Fabric Reinforcement: A Highly Effective Electromagnetic Wave Shield Textile Material.

In this study, a low-melting-point polyester nonwoven fabric (L), a nylon spacer fabric (N), and a carbon fiber woven fabric (C) are laminated in different orders and then needle-bonded at a depth of 15.0 cm to form NLC, NLN, CLC, and CLN composites with a sandwich construction. Regardless of the lamination order, four composite types exhibit high tensile strengths and tearing strengths. Based on the ASTM D4935-18 test standard, the electromagnetic wave shielding measurement is conducted in a frequency range of 1~3 GHz. The two groups-NLC and CLN-demonstrate different electromagnetic wave shields, which are -45~-65 dB for the former, and -60 dB for the latter. According to FTTS-FA-003, in the specified requirements of the test method for electromagnetic shielding textiles, the proposed composites achieve level III, which is the highest standard, and are thus qualified for use in the aviation, construction, and commerce fields.

Using Anti-Malondialdehyde Modified Peptide Autoantibodies to Import Machine Learning for Predicting Coronary Artery Stenosis in Taiwanese Patients with Coronary Artery Disease.

Machine learning (ML) algorithms have been applied to predicting coronary artery disease (CAD). Our purpose was to utilize autoantibody isotypes against four different unmodified and malondialdehyde (MDA)-modified peptides among Taiwanese with CAD and healthy controls (HCs) for CAD prediction. In this study, levels of MDA, MDA-modified protein (MDA-protein) adducts, and autoantibody isotypes against unmodified peptides and MDA-modified peptides were measured with enzyme-linked immunosorbent assay (ELISA). To improve the performance of ML, we used decision tree (DT), random forest (RF), and support vector machine (SVM) coupled with five-fold cross validation and parameters optimization. Levels of plasma MDA and MDA-protein adducts were higher in CAD patients than in HCs. IgM anti-IGKC76-99 MDA and IgM anti-A1AT284-298 MDA decreased the most in patients with CAD compared to HCs. In the experimental results of CAD prediction, the decision tree classifier achieved an area under the curve (AUC) of 0.81; the random forest classifier achieved an AUC of 0.94; the support vector machine achieved an AUC of 0.65 for differentiating between CAD patients with stenosis rates of 70% and HCs. In this study, we demonstrated that autoantibody isotypes imported into machine learning algorithms can lead to accurate models for clinical use.

Lipoprotein Subfractions and Glucose Homeostasis in Prediabetes and Diabetes in Taiwan.

AIMS: Prediabetes and diabetes are associated with increased insulin resistance and decreased insulin production, dyslipidemia, and increased cardiovascular disease (CVD) risk. Our goals were to assess lipoprotein subfractions using novel assays in such subjects. METHODS: Fasting normal, prediabetic, and diabetic Taiwanese men and women (n=2,049) had their serum glucose, glycosylated hemoglobin, insulin, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), HDL3-C, apolipoprotein E-HDL-C, direct low-density lipoprotein cholesterol (LDL-C), small dense LDL-C (sdLDL-C), LDL-TG, and remnant lipoprotein cholesterol (RLP-C) levels measured using novel assays. HDL2-C, LDL-C, and large-buoyant LDL-C (lbLDL-C) were calculated. RESULTS: Prediabetic male and female subjects had significantly higher levels of TG, RLP-C, sdLDL-C, the sdLDL-C/LDL-C ratio, and LDL-TG than normal subjects, and statin treatment abolished this effect in men, but not in women. Diabetic male and female subjects had significantly higher TG and sdLDL-C/LDL-C ratios, and significantly lower levels of HDL-C, HDL2-C, HDL3-C, and apoE HDL-C than normal subjects, as did prediabetic women. Median direct LDL-C levels were ＞100 mg/dL in all groups, even in those receiving statin therapy. Calculated LDL-C significantly underestimated direct LDL-C by ＞10% in diabetic subjects. CONCLUSIONS: Our data indicate that prediabetic subjects were more likely to have significantly elevated RLP-C, sdLDL-C, and LDL-TG, while diabetic subjects were more likely to have significantly decreased HDL-C, HDL2-C, HDL3-C, and apoE HDL-C than normal subjects, and calculated LDL-C significantly underestimated their direct LDL-C. In our view, direct LDL-C and sdLDL-C should be measured and optimized in both diabetic and prediabetic subjects to reduce CVD risk.

A comparison of glycated albumin and glycosylated hemoglobin for the screening of diabetes mellitus in Taiwan.

OBJECTIVE: Glycated albumin (GA) values reflect an average plasma glucose level over approximately 2-4 weeks, and the assay is stable and can be run on serum or plasma. The aim of this study was to determine the universality and the clinical utility of GA in screening for diabetes mellitus. METHODS: Subjects consisted of 2192 male and female residents in Yi-lan County, Northern Taiwan (mean age 60.1 years), of whom 54.2% (n = 1188) had previously been diagnosed and treated for diabetes. Fasting blood samples were obtained to measure HbA1c, plasma glucose, serum GA, insulin, and measures of kidney and liver function. The reference values for these parameters were determined. Data from patients with diabetes and non-diabetic controls were also compared. RESULTS: Mean GA values were 13.8% in controls and 18.1% in diabetic subjects (31.2% higher, p < 0.0001), while mean HbA1c values were 5.6% in controls and 7.2% in diabetic subjects (29.2% higher, p < 0.0001). The 95th percentile values for GA and HbA1c in controls were 16.1% and 6.2%, respectively. Our suggested GA and HbA1c cut-points for prediabetes at the 75th percentile of the normal population would be 14.6% and 5.8%, respectively. For both parameters, values greater than these cut-points provided a reasonable degree of specificity and sensitivity for risk of having diabetes, while a GA value of 16.5% corresponds to an HbA1c level of 6.5%, diagnostic of diabetes. CONCLUSION: These data indicate that GA values can be used as a surrogate parameter for HbA1c in screening for prediabetes and diabetes mellitus.