Comparing the performance of dengue virus IgG and IgG-capture enzyme-linked immunosorbent assays in seroprevalence study.

BACKGROUND: Dengue virus (DENV) is the leading cause of arboviral diseases in humans worldwide. Currently Dengvaxia, the first dengue vaccine licensed in 20 countries, was recommended for DENV seropositive individuals aged 9-45 years. Studying dengue seroprevalence can improve our understanding of the epidemiology and transmission dynamics of DENV, and facilitate future intervention strategies and assessment of vaccine efficacy. Several DENV envelope protein-based serological tests including IgG and IgG-capture enzyme-linked immunosorbent assays (ELISAs) have been employed in seroprevalence studies. Previously DENV IgG-capture ELISA was reported to distinguish primary and secondary DENV infections during early convalescence, however, its performance over time and in seroprevalence study remains understudied. METHODS: In this study, we used well-documented neutralization test- or reverse-transcription-polymerase-chain reaction-confirmed serum/plasma samples including DENV-naïve, primary and secondary DENV, primary West Nile virus, primary Zika virus, and Zika with previous DENV infection panels to compare the performance of three ELISAs. RESULTS: The sensitivity of the InBios IgG ELISA was higher than that of InBios IgG-capture and SD IgG-capture ELISAs. The sensitivity of IgG-capture ELISAs was higher for secondary than primary DENV infection panel. Within the secondary DENV infection panel, the sensitivity of InBios IgG-capture ELISA decreased from 77.8% at < 6 months to 41.7% at 1-1.5 years, 28.6% at 2-15 years and 0% at > 20 years (p < 0.001, Cochran-Armitage test for trend), whereas that of IgG ELISA remains 100%. A similar trend was observed for SD IgG-capture ELISA. CONCLUSIONS: Our findings demonstrate higher sensitivity of DENV IgG ELISA than IgG-capture ELISA in seroprevalence study and interpretation of DENV IgG-capture ELISA should take sampling time and primary or secondary DENV infection into consideration.

Validation of the Pockit Dengue Virus Reagent Set for Rapid Detection of Dengue Virus in Human Serum on a Field-Deployable PCR System.

Dengue virus (DENV) infection, a mosquito-borne disease, is a major public health problem in tropical countries. Point-of-care DENV detection with good sensitivity and specificity enables timely early diagnosis of DENV infection, facilitating effective disease management and control, particularly in regions of low resources. The Pockit dengue virus reagent set (GeneReach Biotech), a reverse transcription insulated isothermal PCR (RT-iiPCR), is available to detect all four serotypes of DENV on the field-deployable Pockit system, which is ready for on-site applications. In this study, analytical and clinical performances of the assay were evaluated. The index assay did not react with 14 non-DENV human viruses, indicating good specificity. Compared to the U.S. CDC DENV-1-4 real-time quantitative RT-PCR (qRT-PCR) assay, testing with serial dilutions of virus-spiked human sera demonstrated that the index assay had detection endpoints that were separately comparable with the 4 serotypes. Excellent reproducibility was observed among repeat tests done by six operators at three sites. In clinical performance, 195 clinical sera collected around Kaohsiung city in 2012 and 21 DENV-4-spiked sera were tested with the RT-iiPCR and qRT-PCR assays in parallel. The 121 (11 DENV-1, 78 DENV-2, 11 DENV-3, and 21 DENV-4) qRT-PCR-positive and 95 qRT-PCR-negative samples were all positive and negative by the RT-iiPCR reagent results, respectively, demonstrating high (100%) interrater agreement (95% confidence interval [CI95%], ∼98.81% to 100%; κ = 1). With analytical and clinical performance equivalent to those of the reference qRT-PCR assay, the index PCR assay on the field-deployable system can serve as a highly sensitive and specific on-site tool for DENV detection.

Glucocorticoid-Induced Leucine Zipper Promotes Neutrophil and T-Cell Polarization with Protective Effects in Acute Kidney Injury.

The glucocorticoid-induced leucine zipper (GILZ) mediates anti-inflammatory effects of glucocorticoids. Acute kidney injury (AKI) mobilizes immune/inflammatory mechanisms, causing tissue injury, but the impact of GILZ in AKI is not known. Neutrophils play context-specific proinflammatory [type 1 neutrophil (N1)] and anti-inflammatory [type 2 neutrophil (N2)] functional roles. Also, regulatory T lymphocytes (Tregs) and regulatory T-17 (Treg17) cells exert counterinflammatory effects, including the suppression of effector T lymphocytes [e.g., T-helper (Th) 17 cells]. Thus, utilizing cell preparations of mice kidneys subjected to AKI or sham operation, we determined the effects of GILZ on T cells and neutrophil subtypes in the context of its renoprotective effect; these studies used the transactivator of transcription (TAT)-GILZ or the TAT peptide. AKI increased N1 and Th-17 cells but reduced N2, Tregs, and Treg17 cells in association with increased interleukin (IL)-17+ but reduced IL-10+ cells accompanied with the disruption of mitochondrial membrane potential (ψ m) and increased apoptosis/necrosis compared with sham kidneys. TAT-GILZ, compared with TAT, treatment reduced N1 and Th-17 cells but increased N2 and Tregs, without affecting Treg17 cells, in association with a reduction in IL-17+ cells but an increase in IL-10+ cells; TAT-GILZ caused less disruption of ψ m and reduced cell death in AKI. Importantly, TAT-GILZ increased perfusion of the ischemic-reperfused kidney but reduced tissue edema compared with TAT. Utilizing splenic T cells and bone marrow-derived neutrophils, we further showed marked reduction in the proliferation of Th cells in response to TAT-GILZ compared with response to TAT. Collectively, the results indicate that GILZ exerts renoprotection accompanied by the upregulation of the regulatory/suppressive arm of immunity in AKI, likely via regulating cross talk between T cells and neutrophils.

Major Challenges and Potential Microenvironment-Targeted Therapies in Glioblastoma.

Glioblastoma (GBM) is considered one of the most malignant, genetically heterogeneous, and therapy-resistant solid tumor. Therapeutic options are limited in GBM and involve surgical resection followed by chemotherapy and/or radiotherapy. Adjuvant therapies, including antiangiogenic treatments (AATs) targeting the VEGF-VEGFR pathway, have witnessed enhanced infiltration of bone marrow-derived myeloid cells, causing therapy resistance and tumor relapse in clinics and in preclinical models of GBM. This review article is focused on gathering previous clinical and preclinical reports featuring major challenges and lessons in GBM. Potential combination therapies targeting the tumor microenvironment (TME) to overcome the myeloid cell-mediated resistance problem in GBM are discussed. Future directions are focused on the use of TME-directed therapies in combination with standard therapy in clinical trials, and the exploration of novel therapies and GBM models for preclinical studies. We believe this review will guide the future of GBM research and therapy.

Assessment of chemical exchange in tryptophan-albumin solution through (19)F multicomponent transverse relaxation dispersion analysis.

A number of NMR methods possess the capability of probing chemical exchange dynamics in solution. However, certain drawbacks limit the applications of these NMR approaches, particularly, to a complex system. Here, we propose a procedure that integrates the regularized nonnegative least squares (NNLS) analysis of multiexponential T2 relaxation into Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion experiments to probe chemical exchange in a multicompartmental system. The proposed procedure was validated through analysis of (19)F T2 relaxation data of 6-fluoro-DL-tryptophan in a two-compartment solution with and without bovine serum albumin. Given the regularized NNLS analysis of a T2 relaxation curve acquired, for example, at the CPMG frequency υ CPMG  = 125, the nature of two distinct peaks in the associated T2 distribution spectrum indicated 6-fluoro-DL-tryptophan either retaining the free state, with geometric mean */multiplicative standard deviation (MSD) = 1851.2 ms */1.51, or undergoing free/albumin-bound interconversion, with geometric mean */MSD = 236.8 ms */1.54, in the two-compartment system. Quantities of the individual tryptophan species were accurately reflected by the associated T2 peak areas, with an interconversion state-to-free state ratio of 0.45 ± 0.11. Furthermore, the CPMG relaxation dispersion analysis estimated the exchange rate between the free and albumin-bound states in this fluorinated tryptophan analog and the corresponding dissociation constant of the fluorinated tryptophan-albumin complex in the chemical-exchanging, two-compartment system.

Sensitivity and specificity of univariate MRI analysis of experimentally degraded cartilage under clinical imaging conditions.

BACKGROUND: To evaluate the sensitivity and specificity of classification of pathomimetically degraded bovine nasal cartilage at 3 Tesla and 37°C using univariate MRI measurements of both pure parameter values and intensities of parameter-weighted images. METHODS: Pre- and posttrypsin degradation values of T1 , T2 , T2 *, magnetization transfer ratio (MTR), and apparent diffusion coefficient (ADC), and corresponding weighted images, were analyzed. Classification based on the Euclidean distance was performed and the quality of classification was assessed through sensitivity, specificity and accuracy (ACC). RESULTS: The classifiers with the highest accuracy values were ADC (ACC = 0.82 ± 0.06), MTR (ACC = 0.78 ± 0.06), T1 (ACC = 0.99 ± 0.01), T2 derived from a three-dimensional (3D) spin-echo sequence (ACC = 0.74 ± 0.05), and T2 derived from a 2D spin-echo sequence (ACC = 0.77 ± 0.06), along with two of the diffusion-weighted signal intensities (b = 333 s/mm(2) : ACC = 0.80 ± 0.05; b = 666 s/mm(2) : ACC = 0.85 ± 0.04). In particular, T1 values differed substantially between the groups, resulting in atypically high classification accuracy. The second-best classifier, diffusion weighting with b = 666 s/mm(2) , as well as all other parameters evaluated, exhibited substantial overlap between pre- and postdegradation groups, resulting in decreased accuracies. CONCLUSION: Classification according to T1 values showed excellent test characteristics (ACC = 0.99), with several other parameters also showing reasonable performance (ACC > 0.70). Of these, diffusion weighting is particularly promising as a potentially practical clinical modality. As in previous work, we again find that highly statistically significant group mean differences do not necessarily translate into accurate clinical classification rules.

Prediction of cartilage compressive modulus using multiexponential analysis of T(2) relaxation data and support vector regression.

Evaluation of mechanical characteristics of cartilage by magnetic resonance imaging would provide a noninvasive measure of tissue quality both for tissue engineering and when monitoring clinical response to therapeutic interventions for cartilage degradation. We use results from multiexponential transverse relaxation analysis to predict equilibrium and dynamic stiffness of control and degraded bovine nasal cartilage, a biochemical model for articular cartilage. Sulfated glycosaminoglycan concentration/wet weight (ww) and equilibrium and dynamic stiffness decreased with degradation from 103.6 ± 37.0 µg/mg ww, 1.71 ± 1.10 MPa and 15.3 ± 6.7 MPa in controls to 8.25 ± 2.4 µg/mg ww, 0.015 ± 0.006 MPa and 0.89 ± 0.25MPa, respectively, in severely degraded explants. Magnetic resonance measurements were performed on cartilage explants at 4 °C in a 9.4 T wide-bore NMR spectrometer using a Carr-Purcell-Meiboom-Gill sequence. Multiexponential T2 analysis revealed four water compartments with T2 values of approximately 0.14, 3, 40 and 150 ms, with corresponding weight fractions of approximately 3, 2, 4 and 91%. Correlations between weight fractions and stiffness based on conventional univariate and multiple linear regressions exhibited a maximum r(2) of 0.65, while those based on support vector regression (SVR) had a maximum r(2) value of 0.90. These results indicate that (i) compartment weight fractions derived from multiexponential analysis reflect cartilage stiffness and (ii) SVR-based multivariate regression exhibits greatly improved accuracy in predicting mechanical properties as compared with conventional regression.

XRCC1 haploinsufficiency in mice has little effect on aging, but adversely modifies exposure-dependent susceptibility.

Oxidative DNA damage plays a role in disease development and the aging process. A prominent participant in orchestrating the repair of oxidative DNA damage, particularly single-strand breaks, is the scaffold protein XRCC1. A series of chronological and biological aging parameters in XRCC1 heterozygous (HZ) mice were examined. HZ and wild-type (WT) C57BL/6 mice exhibit a similar median lifespan of ~26 months and a nearly identical maximal life expectancy of ~37 months. However, a number of HZ animals (7 of 92) showed a propensity for abdominal organ rupture, which may stem from developmental abnormalities given the prominent role of XRCC1 in endoderm and mesoderm formation. For other end-points evaluated-weight, fat composition, blood chemistries, condition of major organs, tissues and relevant cell types, behavior, brain volume and function, and chromosome and telomere integrity-HZ mice exhibited by-and-large a normal phenotype. Treatment of animals with the alkylating agent azoxymethane resulted in both liver toxicity and an increased incidence of precancerous lesions in the colon of HZ mice. Our study indicates that XRCC1 haploinsufficiency in mammals has little effect on chronological longevity and many key biological markers of aging in the absence of environmental challenges, but may adversely affect normal animal development or increase disease susceptibility to a relevant genotoxic exposure.

Corrigendum: Identification and analysis of SARS-CoV-2 alpha variants in the largest Taiwan COVID-19 outbreak in 2021.

[This corrects the article DOI: 10.3389/fmed.2022.869818.].

The identification and phylogenetic analysis of SARS-CoV-2 delta variants in Taiwan.

In Taiwan, coronavirus disease 2019 (COVID-19) involving the delta variant occurred after that involving the alpha variant in 2021. In this study, we aimed to analyze the Delta variant. A total of 318 patients in Taiwan infected with delta variants were identified. The case fatality rate (CFR) of patients infected with delta variants was 0.94% in Taiwan compared with that of those infected with alpha variants (5.95%). The possible reasons for the low CFR might be hybrid immunity due to infection and rapid promotion of the COVID-19 vaccination program during the alpha variant outbreak. We identified three 21J delta variants. Two long gene deletions were detected in these severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) isolates: ORF7aΔ91 in KMUH-8 and SpikeΔ30 in KMUH-9. Protein structure prediction indicates that ORF7aΔ91 results in malfunction of NS7a as an interferon antagonist and that SpikeΔ30 results in a truncated spike protein (N679-A688del), resulting in a lower infection rate compared with the delta variant without these deletions. The impact of these two deletions on SARS-CoV-2-associated pathogenesis deserves further investigation. Delta variants still exist in many regions in the omicron era, and the backbone of the delta variant genome possibly spread worldwide in the form of delta-omicron hybrids (deltacron; e.g., XBC.1 and XAY.2), which casts a potential threat to public health. Our study further highlighted the importance of more understanding of the delta variants.

Epidemiology and analysis of SARS-CoV-2 Omicron subvariants BA.1 and 2 in Taiwan.

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first detected in October 2021, possessed many mutations compared to previous variants. We aimed to identify and analyze SARS-CoV-2 Omicron subvariants among coronavirus disease 2019 (COVID-19) patients between January 2022 and September 2022 in Taiwan. The results revealed that BA.2.3.7, featuring K97E and G1251V in the spike protein compared with BA.2, emerged in March 2022 and persistently dominated between April 2022 and August 2022, resulting in the largest COVID-19 outbreak since 2020. The accumulation of amino acid (AA) variations, mainly AA substitution, in the spike protein was accompanied by increasing severity in Omicron-related COVID-19 between April 2022 and January 2023. Older patients were more likely to have severe COVID-19, and comorbidity was a risk factor for COVID-19-related mortality. The accumulated case fatality rate (CFR) dropped drastically after Omicron variants, mainly BA.2.3.7, entered Taiwan after April 2022, and the CFR was 0.16% in Taiwan, which was lower than that worldwide (0.31%) between April 2021 and January 2023. The relatively low CFR in Omicron-related COVID-19 patients can be attributed to adjustments to public health policies, promotion of vaccination programs, effective antiviral drugs, and the lower severity of the Omicron variant.

Dengue virus serotype did not contribute to clinical severity or mortality in Taiwan's largest dengue outbreak in 2015.

BACKGROUND: Dengue virus serotype 2 (DENV-2) was the major serotype in the 2015 dengue outbreak in Taiwan, while DENV-1 and DENV-3 were dominant between 2005 and 2014. We aimed to investigate whether DENV-2 contributed to disease severity and mortality in the outbreak in Kaohsiung city, Taiwan. METHODS: We collected serum samples from dengue patients to detect the presence of DENV and determine the serotypes by using quantitative reverse transcription-polymerase chain reaction. Our cohorts comprised 105 DENV-1-infected cases and 1,550 DENV-2-infected cases. Demographic data, DENV serotype, and comorbidities were covariates for univariate and multivariate analyses to explore the association with severity and mortality. RESULTS: The results suggested that DENV-1 persisted and circulated, while DENV-2 was dominant during the dengue outbreak that occurred between September and December 2015. However, DENV-2 did not directly contribute to either severity or mortality. Aged patients and patients with diabetes mellitus (DM) or moderate to severe chronic kidney disease (CKD) had a higher risk of developing severe dengue. The mortality of dengue patients was related to a higher Charlson comorbidity index score and severe dengue. Among DENV-2-infected patients and older patients, preexisting anti-dengue IgG, DM, and moderate to severe CKD were associated with severe dengue. Moreover, female sex and severe dengue were associated with a significantly higher risk of death. CONCLUSIONS: Our findings highlight the importance of timely serological testing in elderly patients to identify potential secondary infections and focus on the meticulous management of elderly patients with DM or moderate to severe CKD to reduce dengue-related death.

Multivariate analysis of cartilage degradation using the support vector machine algorithm.

An important limitation in MRI studies of early osteoarthritis is that measured MRI parameters exhibit substantial overlap between different degrees of cartilage degradation. We investigated whether multivariate support vector machine analysis would permit improved tissue characterization. Bovine nasal cartilage samples were subjected to pathomimetic degradation and their T(1), T(2), magnetization transfer rate (k(m) ), and apparent diffusion coefficient (ADC) were measured. Support vector machine analysis performed using certain parameter combinations exhibited particularly favorable classification properties. The areas under the receiver operating characteristic (ROC) curve for detection of extensive and mild degradation were 1.00 and 0.94, respectively, using the set (T(1), k(m), ADC), compared with 0.97 and 0.60 using T(1), the best univariate classifier. Furthermore, a degradation probability for each sample, derived from the support vector machine formalism using the parameter set (T(1), k(m), ADC), demonstrated much stronger correlations (r(2) = 0.79-0.88) with direct measurements of tissue biochemical components than did even the best-performing individual MRI parameter, T(1) (r(2) = 0.53-0.64). These results, combined with our previous investigation of Gaussian cluster-based tissue discrimination, indicate that the combinations (T(1), k(m)) and (T(1), k(m), ADC) may emerge as particularly useful for characterization of early cartilage degradation.

Improved MR-based characterization of engineered cartilage using multiexponential T2 relaxation and multivariate analysis.

Noninvasive monitoring of tissue quality would be of substantial use in the development of cartilage tissue engineering strategies. Conventional MR parameters provide noninvasive measures of biophysical tissue properties and are sensitive to changes in matrix development, but do not clearly distinguish between groups with different levels of matrix development. Furthermore, MR outcomes are nonspecific, with particular changes in matrix components resulting in changes in multiple MR parameters. To address these limitations, we present two new approaches for the evaluation of tissue engineered constructs using MR, and apply them to immature and mature engineered cartilage after 1 and 5 weeks of development, respectively. First, we applied multiexponential T(2) analysis for the quantification of matrix macromolecule-associated water compartments. Second, we applied multivariate support vector machine analysis using multiple MR parameters to improve detection of degree of matrix development. Monoexponential T(2) values decreased with maturation, but without further specificity. Much more specific information was provided by multiexponential analysis. The T(2) distribution in both immature and mature constructs was qualitatively comparable to that of native cartilage. The analysis showed that proteoglycan-bound water increased significantly during maturation, from a fraction of 0.05 ± 0.01 to 0.07 ± 0.01. Classification of samples based on individual MR parameters, T(1), T(2), k(m) or apparent diffusion coefficient, showed that the best classifiers were T(1) and k(m), with classification accuracies of 85% and 84%, respectively. Support vector machine analysis improved the accuracy to 98% using the combination (k(m), apparent diffusion coefficient). These approaches were validated using biochemical and Fourier transform infrared imaging spectroscopic analyses, which showed increased proteoglycan and collagen with maturation. In summary, multiexponential T(2) and multivariate support vector machine analyses provide improved sensitivity to changes in matrix development and specificity to matrix composition in tissue engineered cartilage. These approaches show substantial potential for the evaluation of engineered cartilage tissue and for extension to other tissue engineering constructs.

Manganese-enhanced magnetic resonance imaging method detects age-related impairments in axonal transport in mice and attenuation of the impairments by a microtubule-stabilizing compound.

In this study a manganese-enhanced magnetic resonance imaging (MEMRI) method was developed for mice for measuring axonal transport (AXT) rates in real time in olfactory receptor neurons, which project from the olfactory epithelium to the olfactory neuronal layer of the olfactory bulb. Using this MEMRI method, two major experiments were conducted: 1) an evaluation of the effects of age on AXT rates and 2) an evaluation of the brain-penetrant, microtubule-stabilizing agent, Epothilone D for effect on AXT rates in aged mice. In these studies, we improved upon previous MEMRI approaches to develop a method where real-time measurements (32 time points) of AXT rates in mice can be determined over a single (approximately 100 min) scanning session. In the age comparisons, AXT rates were significantly higher in young (mean age ∼4.0 months old) versus aged (mean age ∼24.5 months old) mice. Moreover, in aged mice, eight weeks of treatment with Epothilone D, (0.3 and 1.0 mg/kg) was associated with statistically significant increases in AXT rates compared to vehicle-treated subjects. These experiments conducted in a living mammalian model (i.e., wild type, C57BL/6 mice), using a new modified MEMRI method, thus provide further evidence that the process of aging leads to decreases in AXT rates in the brain and they further support the argument that microtubule-based therapeutic strategies designed to improve AXT rates have potential for age-related neurological disorders.

Identification and Analysis of SARS-CoV-2 Alpha Variants in the Largest Taiwan COVID-19 Outbreak in 2021.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is believed to have originated in Wuhan City, Hubei Province, China, in December 2019. Infection with this highly dangerous human-infecting coronavirus via inhalation of respiratory droplets from SARS-CoV-2 carriers results in coronavirus disease 2019 (COVID-19), which features clinical symptoms such as fever, dry cough, shortness of breath, and life-threatening pneumonia. Several COVID-19 waves arose in Taiwan from January 2020 to March 2021, with the largest outbreak ever having a high case fatality rate (CFR) (5.95%) between May and June 2021. In this study, we identified five 20I (alpha, V1)/B.1.1.7/GR SARS-CoV-2 (KMUH-3 to 7) lineage viruses from COVID-19 patients in this largest COVID-19 outbreak. Sequence placement analysis using the existing SARS-CoV-2 phylogenetic tree revealed that KMUH-3 originated from Japan and that KMUH-4 to KMUH-7 possibly originated via local transmission. Spike mutations M1237I and D614G were identified in KMUH-4 to KMUH-7 as well as in 43 other alpha/B.1.1.7 sequences of 48 alpha/B.1.1.7 sequences deposited in GISAID derived from clinical samples collected in Taiwan between 20 April and July. However, M1237I mutation was not observed in the other 12 alpha/B.1.1.7 sequences collected between 26 December 2020, and 12 April 2021. We conclude that the largest COVID-19 outbreak in Taiwan between May and June 2021 was initially caused by the alpha/B.1.1.7 variant harboring spike D614G + M1237I mutations, which was introduced to Taiwan by China Airlines cargo crew members. To our knowledge, this is the first documented COVID-19 outbreak caused by alpha/B.1.1.7 variant harboring spike M1237I mutation thus far. The largest COVID-19 outbreak in Taiwan resulted in 13,795 cases and 820 deaths, with a high CFR, at 5.95%, accounting for 80.90% of all cases and 96.47% of all deaths during the first 2 years. The high CFR caused by SARS-CoV-2 alpha variants in Taiwan can be attributable to comorbidities and low herd immunity. We also suggest that timely SARS-CoV-2 isolation and/or sequencing are of importance in real-time epidemiological investigations and in epidemic prevention. The impact of D614G + M1237I mutations in the spike gene on the SARS-CoV-2 virus spreading as well as on high CFR remains to be elucidated.

Evaluation of a new NS1 rapid diagnostic test using a single acute-phase serum panel collected during the largest dengue outbreak in Taiwan history in 2015.

Dengue virus (DENV) infection results mostly from the bites of virus-carrying Aedes mosquitoes, which results in dengue fever (DF) with or without warning signs, severe dengue, or asymptomatic infections in humans. For point-of care identification of DENV-infected patients, a rapid diagnostic test (RDT) for DENV nonstructural protein 1 (NS1) has been developed to achieve early diagnosis and timely clinical management. We evaluated the performance of a new commercially available dengue NS1 RDT AsiaGen Dengue NS1 Antigen Rapid Diagnosis Test using real-time qRT-PCR as a reference method and compared the results with SD BIOLINE Dengue NS1 Ag using a single acute-phase serum panel collected during the largest dengue outbreak in the history of Taiwan in 2015. The results suggested that the sensitivity and specificity of AsiaGen Dengue NS1 Antigen RDT (96.9% and 100%) were similar to those of SD BIOLINE Dengue NS1 RDT (100% and 100%) for detection in the acute phase of DENV-2 infection. The results suggested that the sensitivity of both RDTs was similar (95.4% ~ 100%) for the sera collected at less than or equal to three days postsymptom onset (PSO). Our results suggested that the two DENV NS1 RDTs used in this study were promising for the timely diagnosis of DENV infection during dengue outbreaks, at least for DENV-2 in areas where authorized medical laboratories are not available or medical resources are limited. However, the performance of AsiaGen DENV NS1 RDTs in the detection of primary/secondary infections and infection by serotypes of DENV other than DENV-2 requires further investigation.

Mapping proteoglycan-bound water in cartilage: Improved specificity of matrix assessment using multiexponential transverse relaxation analysis.

Association of MR parameters with cartilage matrix components remains an area of ongoing investigation. Multiexponential analysis of nonlocalized transverse relaxation data has previously been used to quantify water compartments associated with matrix macromolecules in cartilage. We extend this to mapping the proteoglycan (PG)-bound water fraction in cartilage, using mature and young bovine nasal cartilage model systems, toward the goal of matrix component-specific imaging. PG-bound water fraction from mature and young bovine nasal cartilage was 0.31 ± 0.04 and 0.22 ± 0.06, respectively, in agreement with biochemically derived PG content and PG-to-water weight ratios. Fourier transform infrared imaging spectroscopic-derived PG maps normalized by water content (IR-PG(ww) ) showed spatial correspondence with PG-bound water fraction maps. Extensive simulation analysis demonstrated that the accuracy and precision of our determination of PG-bound water fraction was within 2%, which is well-within the observed tissue differences. Our results demonstrate the feasibility of performing imaging-based multiexponential analysis of transverse relaxation data to map PG in cartilage.

Improved specificity of cartilage matrix evaluation using multiexponential transverse relaxation analysis applied to pathomimetically degraded cartilage.

The noninvasive early detection of specific matrix alterations in degenerative cartilage disease would be of substantial use in basic science studies and clinically, but remains an elusive goal. Recently developed MRI methods exhibit some specificity, but require contrast agents or nonstandard pulse sequences and hardware. We present a multiexponential approach which does not require contrast agents or specialized hardware, and uses a standard multiple-echo spin-echo sequence. Experiments were performed on tissue models of degenerative cartilage using enzymes with distinct actions. MR results were validated using histologic, biochemical and infrared spectroscopic analyses. The sulfated glycosaminoglycan per dry weight (dw) in bovine nasal cartilage was 0.72 ± 0.06 mg/mg dw and was reduced through chondroitinase AC and collagenase digestion to 0.56 ± 0.12 and 0.58 ± 0.13 mg/mg dw, respectively. Multiexponential analysis of data obtained at 9.4 T permitted the identification of tissue compartments assigned to the proteoglycan component of the matrix and to bulk water. Enzymatic treatment resulted in a significant reduction in the ratio of proteoglycan-bound to free water from 0.13 ± 0.02 in control cartilage to 0.03 ± 0.02 and 0.05 ± 0.06 under chondroitinase AC and collagenase treatment, respectively. As expected, monoexponential T(2) increased with both degradation protocols, but without further specificity to the nature of the degradation. An important eventual extension of this approach may be to map articular cartilage degeneration in the clinical setting. As an initial step towards this, localized multiexponential T(2) analysis was performed on control and trypsin treated excised bovine patella. The results obtained on this articular cartilage sample were readily interpretable in terms of proteoglycan-associated and relatively free water compartments. In potential clinical applications, signal-to-noise ratio constraints will define the threshold for the detection of macromolecular compartment changes at a given spatial scale. The multiexponential approach has potential application to the early detection of cartilage degradation with the use of appropriate pulse parameters under high signal-to-noise ratio conditions.