Quantification Of Measurements Research Articles

Prediction of MRI relaxometry in the presence of hepatic steatosis by Monte Carlo simulations.

To develop Monte Carlo simulations to predict the relationship of with liver fat content at 1.5T and 3.0T. For various fat fractions (FFs) from 1% to 25%, four types of virtual liver models were developed by incorporating the size and spatial distribution of fat droplets. Magnetic fields were then generated under different fat susceptibilities at 1.5T and 3.0T, and proton movement was simulated for phase accrual and MRI signal synthesis. The synthesized signal was fit to single-peak and multi-peak fat signal models for and proton density fat fraction (PDFF) predictions. In addition, the relationships between and PDFF predictions were compared with in vivo calibrations and Bland-Altman analysis was performed to quantitatively evaluate the effects of these components (type of virtual liver model, fat susceptibility, and fat signal model) on predictions. A virtual liver model with realistic morphology of fat droplets was demonstrated, and and PDFF values were predicted by Monte Carlo simulations at 1.5T and 3.0T. predictions were linearly correlated with PDFF, while the slope was unaffected by the type of virtual liver model and increased as fat susceptibility increased. Compared with in vivo calibrations, the multi-peak fat signal model showed superior performance to the single-peak fat signal model, which yielded an underestimation of liver fat. The -PDFF relationships by simulations with fat susceptibility of 0.6ppm and the multi-peak fat signal model were ( , ) at 1.5T and ( , ) at 3.0T. Monte Carlo simulations provide a new means for -PDFF prediction, which is primarily determined by fat susceptibility, fat signal model, and magnetic field strength. Accurate -PDFF calibration has the potential to correct the effect of fat on quantification, and may be helpful for accurate measurements in liver iron overload. In this study, a Monte Carlo simulation of hepatic steatosis was developed to predict the relationship between and PDFF. Furthermore, the effects of fat droplet morphology, fat susceptibility, fat signal model, and magnetic field strength were evaluated for the -PDFF calibration. Our results suggest that Monte Carlo simulations provide a new means for -PDFF prediction and this means can be easily generated for various regimes, such as simulations with higher fields and different echo times, as well as correction of magnetic susceptibility measurements for liver iron quantification.

Investigation of the potential of in-line particle concentration measurements in gas particle separation processes by using low-cost particulate matter sensors

In addition to the costly laboratory-based particle measurement devices, low-cost particulate matter sensors for ambient air quality measurements can also be employed for the detection of PM in gas cleaning devices. The ability to spatially resolve the actual level of particle number concentration with high temporal resolution within a gas-particle separation process is of significant value for process monitoring and control. The quantitative reliability of the measurement data from low-cost particulate matter sensors remains uncertain when the particle concentrations in the apparatus exceed the upper measurement limit of the sensors, whether temporarily or permanently. This study examines the potential of low-cost particulate matter sensors for in-line particle concentration measurements in gas-particle separation processes. The measurement performance of the low-cost particulate matter sensors is initially examined under idealised conditions in a dust chamber. This is done in order to quantify the deviations of the low-cost particulate matter sensors in comparison to a state-of-the-art precision laboratory high-cost sensor. Subsequently, both sensor types are installed at a wet separator test facility, following the quantification of their respective measurement performances. The low-cost particulate matter sensors are capable of measuring particle number concentration above their specified limit (up to ≈6.1×104cm−3), depending on the measurement conditions. By applying a 3rd polynomial correction function, obtained from the initial quantification measurement, the low-cost particulate matter sensors are able to reproduce the particle number concentration measured by the high-cost sensor. Furthermore, the low-cost particulate matter sensors are capable of reproducing short-term fluctuations in the particle number concentration.

Quantification measurement of hemoglobin with large dynamic range and low detection limit via an optical fiber optofluidic laser with enzyme-catalyzed reaction

Quantitative measurement of hemoglobin (Hb) levels is an essential part of routine medical examinations, disease diagnosis and health status monitoring. In this study, we introduced optical fiber optofluidic laser (FOFL) technology combined with catalytic oxidation reaction to design a laser sensor for sensitive Hb detection. For the H2O2-rhodamine B (RhB) oxidation system, radially emitting FOFL was achieved with a thin-walled hollow optical fiber (HOF) as an optical microcavity and amplified the concentration change of RhB during oxidation by H2O2. Hb was employed as peroxide-mimicking enzyme to catalyze the oxidation system, which sped up the reaction, resulting in an earlier laser extinction time. With the laser extinction time as sensing signal, the Hb sensor achieved a dynamic range of five orders of magnitude and a limit of detection (LOD) of 46.0 pM at an assay time of 40 min. The developed method provides ideas for the exploitation of FOFL biosensing based on catalytic oxidation reactions.

Is Seeing Believing? A Practitioner's Perspective on High-Dimensional Statistical Inference in Cancer Genomics Studies.

Variable selection methods have been extensively developed for and applied to cancer genomics data to identify important omics features associated with complex disease traits, including cancer outcomes. However, the reliability and reproducibility of the findings are in question if valid inferential procedures are not available to quantify the uncertainty of the findings. In this article, we provide a gentle but systematic review of high-dimensional frequentist and Bayesian inferential tools under sparse models which can yield uncertainty quantification measures, including confidence (or Bayesian credible) intervals, p values and false discovery rates (FDR). Connections in high-dimensional inferences between the two realms have been fully exploited under the "unpenalized loss function + penalty term" formulation for regularization methods and the "likelihood function × shrinkage prior" framework for regularized Bayesian analysis. In particular, we advocate for robust Bayesian variable selection in cancer genomics studies due to its ability to accommodate disease heterogeneity in the form of heavy-tailed errors and structured sparsity while providing valid statistical inference. The numerical results show that robust Bayesian analysis incorporating exact sparsity has yielded not only superior estimation and identification results but also valid Bayesian credible intervals under nominal coverage probabilities compared with alternative methods, especially in the presence of heavy-tailed model errors and outliers.

Bedside right ventricle quantification using three-dimensional echocardiography in children with congenital heart disease: A comparative study with cardiac magnetic resonance imaging

BackgroundAccurate quantification of right ventricular (RV) volumes and function is crucial for the management of congenital heart diseases. AimsWe aimed to assess the feasibility and accuracy of bedside analysis using new RV quantification software from three-dimensional transthoracic echocardiography in children with or without congenital heart disease, and to compare measurements with cardiac magnetic resonance imaging. MethodsWe included paediatric patients with congenital heart disease (106 patients) responsible for RV volume overload and a control group (30 patients). All patients underwent three-dimensional transthoracic echocardiography using a Vivid E95 ultrasound system. RV end-diastolic and end-systolic volumes and RV ejection fraction were obtained using RV quantification software. Measurements were compared between RV quantification and cardiac magnetic resonance imaging in 27 patients. ResultsBedside RV quantification analysis was feasible in 133 patients (97.8%). Manual contour adjustment was necessary in 126 patients (93%). The mean time of analysis was 62±42s. RV end-diastolic and end-systolic volumes were larger in the congenital heart disease group than the control group: median 85.0 (interquartile range 29.5) mL/m2 vs 55.0 (interquartile range 20.5) mL/m2 for RV end-diastolic volume and 42.5 (interquartile range 15.3) mL/m2 vs 29.0 (interquartile range 11.8) mL/m2 for RV end-systolic volume, respectively. Good agreement for RV end-diastolic and end-systolic volumes and RV ejection fraction was found between RV quantification and magnetic resonance imaging measurements. RV quantification software underestimated RV end-diastolic volume/body surface area by 3mL/m2 and RV ejection fraction by 2.1%, and overestimated RV end-systolic volume/body surface area by 0.2mL/m2. ConclusionsWe found good feasibility and accuracy of bedside RV quantification analysis from three-dimensional transthoracic echocardiography in children with or without congenital heart disease. RV quantification could be a reliable and non-invasive method for RV assessment in daily practice, facilitating appropriate management and follow-up care.

Determination of Some Element’s Migrants in Aqueous Simulant from Plastic Food Contact Products by Inductively Coupled Plasma Mass Spectrometer

AbstractVarious chemicals present at different stages in the food supply chain can lead to the leaching of heavy metals. These metals can accumulate in the human body through the consumption of contaminated food. Consequently, it is necessary to validate an analytical technique for the quantification chemical that could contaminate food. This study presents a rapid, straightforward, and efficient analytical method for the direct quantification of some potentially toxic elements in aqueous simulants from plastic food contact products using an inductively coupled mass spectrometer (ICP-MS). The method’s validation encompassed the study of the estimated detection limits, practical quantification limits, linearity, accuracy, and measurement uncertainty of aluminium (Al), antimony (Sb), arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), iron (Fe), lead (Pb), manganese (Mn), nickel (Ni), and zinc (Zn) under optimized ICP-MS conditions. The estimated detection limits ranged from 7.5 × 10−4 to 0.074 mg/kg, while practical quantification limits spanned from 0.02 to 0.8 mg/kg. The average recoveries ± standard deviations at different spiking levels were varied between 85.7 ± 1.51 and 115.6 ± 0.88% with coefficients of variation between 0.42 and 5.85%. The method trueness was verified by using references materials (test material in aqueous acetic acid) purchased from Food Chemistry Proficiency Testing and Analysis (FAPAS) yielding satisfactory results within acceptable recovery and Z-score values. The method precision, in terms of relative standard deviation (RSD), was being below 4.22%. The method uncertainty expressed as expanded uncertainty of all validated elements was found to be ≤ 21.9%. Validated method was employed to determine specific elements in aqueous simulants of thirty commercial plastic food packaging samples, representing three distinct types of plastic polymers. The results showed that the mean concentrations, in mg/kg, were as follows: 2.04 (Al), 0.02 (As), 0.02 (Cd), 0.02 (Co), 0.06 (Cr), 0.41 (Cu), 1.55 (Fe), 0.09 (Mn), 0.15 (Ni), 0.07 (Pb), 0.05 (Sb), and 0.81 (Zn). Furthermore, 30% of analyzed samples exceeding the maximum permissible limits of Al for plastic materials and articles intended to come into contact with food.

Insights into gemcitabine resistance in pancreatic cancer: association with metabolic reprogramming and TP53 pathogenicity in patient derived xenografts

BackgroundWith poor prognosis and high mortality, pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. Standard of care therapies for PDAC have included gemcitabine for the past three decades, although resistance often develops within weeks of chemotherapy initiation through an array of possible mechanisms.MethodsWe reanalyzed publicly available RNA-seq gene expression profiles of 28 PDAC patient-derived xenograft (PDX) models before and after a 21-day gemcitabine treatment using our validated analysis pipeline to identify molecular markers of intrinsic and acquired resistance.ResultsUsing normalized RNA-seq quantification measurements, we first identified oxidative phosphorylation and interferon alpha pathways as the two most enriched cancer hallmark gene sets in the baseline gene expression profile associated with intrinsic gemcitabine resistance and sensitivity, respectively. Furthermore, we discovered strong correlations between drug-induced expression changes in glycolysis and oxidative phosphorylation genes and response to gemcitabine, which suggests that these pathways may be associated with acquired gemcitabine resistance mechanisms. Thus, we developed prediction models using baseline gene expression profiles in those pathways and validated them in another dataset of 12 PDAC models from Novartis. We also developed prediction models based on drug-induced expression changes in genes from the Molecular Signatures Database (MSigDB)’s curated 50 cancer hallmark gene sets. Finally, pathogenic TP53 mutations correlated with treatment resistance.ConclusionOur results demonstrate that concurrent upregulation of both glycolysis and oxidative phosphorylation pathways occurs in vivo in PDAC PDXs following gemcitabine treatment and that pathogenic TP53 status had association with gemcitabine resistance in these models. Our findings may elucidate the molecular basis for gemcitabine resistance and provide insights for effective drug combination in PDAC chemotherapy.

Fluorescence microfluidic system for real-time monitoring of PS and PVC sub-micron microplastics under flowing conditions

Plastics, recognized for their convenience, disposability, and recyclability, have emerged as a significant ecological challenge, particularly with the prevalence of microplastics (MPs, 1 μm – 5 mm) and sub-micron MPs (100 – 1000 nm) in natural environments. While extensive research has focused on their occurrence and environmental impacts, quantification methods developed for MPs exhibit limitations when applied to sub-micron MPs due to their smaller size. This study addresses these limitations by introducing a novel monitoring system that integrates fluorescence labeling with a microfluidic device and particle tracking software, enabling automated quantification and size measurement of both spherical and fragmented MPs of size in the sub-micrometer range. Results showed that the developed system enabled fast quantification and size measurement of 500- and 1000-nm polystyrene (PS) sub-micron MP beads and fragmented PS and polyvinyl chloride (PVC) sub-micron MPs. Additionally, fluorescence labeling enabled the real-time discrimination of PS and PVC sub-micron MPs. Lastly, the microfluidic system allowed the monitoring of sub-micron MPs within a small quantity of water samples. This automated system has a high potential for swift and real-time monitoring of sub-micron MPs in the environment. By enhancing our ability to detect and quantify sub-micron MPs, this study contributes to a more comprehensive understanding of their presence and distribution in environmental systems.

Exploring the Potential of Crotalaria juncea L. for Phytoremediation: Insights from Gas Exchange, Pigment Quantification, and Growth Measurements under Copper Stress

Soil contamination by trace elements is a worldwide concern that can result from several sources, such as mining, smelting, car traffic exhaust, agriculture plant protection products such as fungicides, and fertilizers. Among the metals involved, copper can cause alterations in the photosynthetic, respiratory, and enzymatic processes of plants, leading to reduced growth of roots and shoots. An alternative to dealing with metals present in the soil is phytoremediation, which consists of using plants to extract or stabilize these elements. The leguminous Crotalaria juncea is widely used as a green manure and may be advantageous due to its capacity for biological nitrogen fixation and biomass accumulation. This research aimed to evaluate the growth and physiological behaviour of C. juncea in copper-contaminated soil and its potential use as a phytoremediation plant. For the fresh and dry mass of shoots and roots, compared with 30 mg.dm−3 of Cu, there was a decrease in values with the increase in concentrations up to a dose of 480 mg.dm−3. The roots were less sensitive to increased Cu concentrations than the shoots. The tolerance index decreased as copper concentrations in the soil increased. From 60 mg.dm−3, its vegetative growth decreased, but C. Juncea was able to tolerate and accumulate copper in the root system, presenting high potential as a phytostabilizing species.

Label-free detection of glutathione and glutathione disulfide in biological fluid by using an alpha-hederin nanopore

Glutathione (GSH) is indispensable for maintaining redox homeostasis in biological fluids and serves as a key component in cellular defense mechanisms. Accurate assessment of GSH relative to its oxidized counterpart, glutathione disulfide (GSSG), is critical for the early diagnosis and understanding of conditions related to oxidative stress. Despite existing methods for their quantification, the label-free and simultaneous measurement of GSH and GSSG in biological fluid presents significant challenges. Herein, we report the use of an alpha-hederin (Ah) nanopore for the direct measurement of the GSH:GSSG ratio in simulated biological fluid, containing fetal bovine serum (FBS). This system hinges on detecting characteristic relative ion blockades (ΔI/Io) as GSH and GSSG molecules pass through the Ah nanopore under an applied electric field. The distinct current blockage signals derived from the translocation of GSH and GSSG enabled us to determine the molar ratio of GSH and its oxidized form. Notably, the interactions between the hydroxyl groups of the sugar moiety lining the nanopore's inner surface and the sulfhydryl group of GSH significantly influence the translocation dynamics, resulting in a longer translocation time for GSH compared to GSSG. The Ah nanopore technology proposed in this study offers a promising approach for real-time, single molecule-level monitoring of glutathione redox status in biological fluids, eliminating the need for labeling or extensive sample preparation.

Altered Elastin Turnover, Immune Response, and Age-Related Retinal Thinning in a Transgenic Mouse Model With RPE-Specific HTRA1 Overexpression.

A single-nucleotide polymorphism in HTRA1 has been linked to age-related macular degeneration (AMD). Here we investigated the potential links between age-related retinal changes, elastin turnover, elastin autoantibody production, and complement C3 deposition in a mouse model with RPE-specific human HTRA1 overexpression. HTRA1 transgenic mice and age-matched CD1 wild-type mice were analyzed at 6 weeks and 4, 6, and 12 to 14months of age using in vivo retinal imaging by optical coherence tomography (OCT) and fundus photography, as well as molecular readouts, focusing on elastin and elastin-derived peptide quantification, antielastin autoantibody, and total Ig antibody measurements and immunohistochemistry to examine elastin, IgG, and C3 protein levels in retinal sections. OCT imaging indicated thinning of inner nuclear layer as an early phenotype in HTRA1 mice, followed by age and age/genotype-related thinning of the photoreceptor layer, RPE, and total retina. HTRA1 mice exhibited reduced elastin protein levels in the RPE/choroid and increased elastin breakdown products in the retina and serum. A corresponding age-dependent increase of serum antielastin IgG and IgM autoantibodies and total Ig antibody levels was observed. In the RPE/choroid, these changes were associated with an age-related increase of IgG and C3 deposition. Our results confirm that RPE-specific overexpression of human HTRA1 induces certain AMD-like phenotypes in mice. This includes altered elastin turnover, immune response, and complement deposition in the RPE/choroid in addition to age-related outer retinal and photoreceptor layer thinning. The identification of elastin-derived peptides and corresponding antielastin autoantibodies, together with increased C3 deposition in the RPE/choroid, provides a rationale for an overactive complement system in AMD irrespective of the underlying genetic risk.

A review of measurement for quantification of carbon dioxide removal by enhanced weathering in soil

All pathways which limit global temperature rise to <2°C above pre-industrial temperatures now require carbon dioxide removal (CDR) in addition to rapid greenhouse gas emissions reductions. Novel and durable CDR strategies need to rapidly scale over the next few decades in order to reach Paris Agreement Targets. Terrestrial enhanced weathering (EW) involves the acceleration of natural weathering processes via the deployment of crushed rock feedstocks, typically Ca- and Mg-rich silicates, in soils. While models predict this has the potential to remove multiple gigatonnes of CO2 annually, as an open-system pathway, the measurement (monitoring), reporting, and verification (MRV) of carbon removal and storage is challenging. Here we provide a review of the current literature showing the state-of-play of different methods for monitoring EW. We focus on geochemical characterization of weathering processes at the weathering site itself, acknowledging that the final storage of carbon is largely in the oceans, with potential losses occurring during transfer. There are two main approaches for measuring EW, one focused on solid phase measurements, including exchangeable phases, and the other on the aqueous phase. Additionally, gas phase measurements have been employed to understand CO2 fluxes, but can be dominated by short-term organic carbon cycling. The approaches we review are grounded in established literature from the natural environment, but implementing these approaches for EW CDR quantification has strengths and limitations. The complexity inherent in open-system CDR pathways is navigable through surplus measurement strategies and well-designed experiments, which we highlight are critical in the early stage of the EW CDR industry.

Ocean surface radiation measurement best practices

Ocean surface radiation measurement best practices have been developed as a first step to support the interoperability of radiation measurements across multiple ocean platforms and between land and ocean networks. This document describes the consensus by a working group of radiation measurement experts from land, ocean, and aircraft communities. The scope was limited to broadband shortwave (solar) and longwave (terrestrial infrared) surface irradiance measurements for quantification of the surface radiation budget. Best practices for spectral measurements for biological purposes like photosynthetically active radiation and ocean color are only mentioned briefly to motivate future interactions between the physical surface flux and biological radiation measurement communities. Topics discussed in these best practices include instrument selection, handling of sensors and installation, data quality monitoring, data processing, and calibration. It is recognized that platform and resource limitations may prohibit incorporating all best practices into all measurements and that spatial coverage is also an important motivator for expanding current networks. Thus, one of the key recommendations is to perform interoperability experiments that can help quantify the uncertainty of different practices and lay the groundwork for a multi-tiered global network with a mix of high-accuracy reference stations and lower-cost platforms and practices that can fill in spatial gaps.

Three-year outcomes of a randomized clinical trial of perioperative vaginal estrogen as adjunct to native tissue vaginal apical prolapse repair

As the muscular and connective tissue components of the vagina are estrogen responsive, clinicians may recommend vaginal estrogen to optimize tissues preoperatively and as a possible means to reduce prolapse recurrence, but long-term effects of perioperative intravaginal estrogen on surgical prolapse management are uncertain. This study aimed to compare the efficacy of perioperative vaginal estrogen vs placebo cream in reducing composite surgical treatment failure 36 months after native tissue transvaginal prolapse repair. This was an extended follow-up of a randomized superiority trial conducted at 3 tertiary US sites. Postmenopausal patients with bothersome anterior or apical vaginal prolapse were randomized 1:1 to 1-g conjugated estrogen cream (0.625 mg/g) or placebo, inserted vaginally twice weekly for ≥5 weeks preoperatively and continued twice weekly for 12 months postoperatively. All participants underwent vaginal hysterectomy (if the uterus was present) and standardized uterosacral or sacrospinous ligament suspension at the surgeon's discretion. The primary report's outcome was time to failure by 12 months postoperatively, defined by a composite outcome of objective prolapse of the anterior or posterior walls beyond the hymen or the vaginal apex descending below one-third the total vaginal length, subjective bulge symptoms, and/or retreatment. After 12 months, participants could choose to use-or not use-vaginal estrogen for atrophy symptom bother. The secondary outcomes included Pelvic Organ Prolapse Quantification points, subjective prolapse symptom severity using the Patient Global Impression of Severity and the Patient Global Impression of Improvement, and prolapse-specific subscales of the 20-Item Pelvic Floor Distress Inventory and the Pelvic Floor Impact Questionnaire-Short Form 7. Data were analyzed as intent to treat and "per protocol" (ie, ≥50% of expected cream use per medication diary). Of 206 postmenopausal patients, 199 were randomized, and 186 underwent surgery. Moreover, 164 postmenopausal patients (88.2%) provided 36-month data. The mean age was 65.0 years (standard deviation, 6.7). The characteristics were similar at baseline between the groups. Composite surgical failure rates were not significantly different between the estrogen group and the placebo group through 36 months, with model-estimated failure rates of 32.6% (95% confidence interval, 21.6%-42.0%) and 26.8% (95% confidence interval, 15.8%-36.3%), respectively (adjusted hazard ratio, 1.55; 95% confidence interval, 0.90-2.66; P=.11). The results were similar for the per-protocol analysis. Objective failures were more common than subjective failures, combined objective and subjective failures, or retreatment. Using the Patient Global Impression of Improvement, 75 of 80 estrogen participants (94%) and 72 of 76 placebo participants (95%) providing 36-month data reported that they were much or very much better 36 months after surgery (P>.99). These data included reports from 51 of 55 "surgical failures." Pelvic Organ Prolapse Quantification measurements, Patient Global Impression of Severity scores, and prolapse subscale scores of the 20-Item Pelvic Floor Distress Inventory and Pelvic Floor Impact Questionnaire-Short Form 7 all significantly improved for both the estrogen and placebo groups from baseline to 36 months postoperatively without differences between the groups. Of the 160 participants providing data on vaginal estrogen usage at 36 months postoperatively, 40 of 82 participants (49%) originally assigned to the estrogen group were using prescribed vaginal estrogen, and 47 of 78 participants (60%) assigned to the placebo group were using vaginal estrogen (P=.15). Adjunctive perioperative vaginal estrogen applied ≥5 weeks preoperatively and 12 months postoperatively did not improve surgical success rates 36 months after uterosacral or sacrospinous ligament suspension prolapse repair. Patient perception of improvement remained very high at 36 months.

Construction and characterization of a modA gene mutant strain of Klebsiella pneumoniae

To construct a mutant strain of Klebsiella pneumoniae NTUH- K2044 with modA gene deletion and its complementary strain and explore the role of modA gene in modulating anaerobic nitrate respiratory growth and phenotypes of K. pneumoniae. The modA deletion mutant K. pneumoniae strain was constructed by homologous recombination using the suicide vector pKO3-Km. To obtain the complementary strain C-modA, the whole sequence fragment containing the promoter, open reading frame and terminator regions of modA was cloned into pGEM-T-easy and electrically transformed into the modA deletion mutant. The NTUH-K2044 wild-type strain, modA gene deletion mutant and complementary strain were compared by measuring in vitro anaerobic nitrate respiration growth, competitiveness index, biofilm quantification, mucoviscosity assay and morphological measurement using Image J. The modA deletion mutant strain ΔmodA and the complementary strain C-modA were successfully constructed. The modA gene knockout strain showed inhibited anaerobic nitrate respiratory growth compared with the wild- type and C-modA strains with significantly weakened competitiveness, reduced capacity of biofilm synthesis during anaerobiosis, and lowered mucoviscosity under anaerobic conditions. The ΔmodA strain showed a spherical morphology in anaerobic conditions as compared with the normal short rod-like morphology of K. pneumoniae, with also distinctly shorter length than the wild-type and C-modA strains. The molybdate transport system encoding gene modA is associated with the pathogenic capacity of K. pneumoniae by modulating its anaerobic nitrate respiration, competitiveness, biofilm formation, hypermucoviscous phenotype and morphology.

A Comparative Study on the Performance of Covariance Functions in Gaussian Process Regression model: Application to Global Wheat Price

Gaussian Process Regression (GPR) is a nonparametric machine learning model that provides uncertainty quantification in making predictions. GPR utilizes several covariance functions (CFs) in the process of developing models to ensure high accuracy. There are five common CFs in GPR, which are the Radial Basis Function (RBF), Rational Quadratic (RQ), Periodic (Per), Matérn 3/2 (Mat 3/2), and Matérn 5/2 (Mat 5/2), where each covariance function (CF) has different characteristics and behaviors. This paper is to investigate the comparative performances of each CF when applied to the Global Wheat Prices dataset. Error metric measurement like Mean Square Error (MSE) and Root Mean Square Error (RMSE), while Coefficient of Variation (CV) for uncertainty quantification measurement is computed for each CF, and comparisons was made among the CFs to conclude the best CF for this application. The lowest values among them will be the best CF for the data. It should be noted that the CV for each model should be less than 5%, and the CF with the smallest value of CV is considered reliable. The five CFs were fit to the Global Wheat Prices dataset, and it was found that the Mat 3/2 produced the best performances with the lowest values of MSE, RMSE, and CV. Mat 3/2 is the most efficient CF for making predictions since it gives the lowest value of error metric measurement and the lowest value of CV under 5% among the other CFs, making it more reliable for modeling. Overall, the outcome shows that Mat 3/2 is the best CF to be used in developing a GPR model to predict Global Wheat Prices dataset.

Tanshinone IIA Alleviates Traumatic Brain Injury by Reducing Ischemia‒Reperfusion via the miR-124-5p/FoxO1 Axis.

Cerebral ischemia-reperfusion injury is a common complication of ischemic stroke that affects the prognosis of patients with ischemic stroke. The lipid-soluble diterpene Tanshinone IIA, which was isolated from Salvia miltiorrhiza, has been indicated to reduce cerebral ischemic injury. In this study, we investigated the molecular mechanism of Tanshinone IIA in alleviating reperfusion-induced brain injury. Middle cerebral artery occlusion animal models were established, and neurological scores, tetrazolium chloride staining, brain volume quantification, wet and dry brain water content measurement, Nissl staining, enzyme-linked immunosorbent assay, flow cytometry, western blotting, and reverse transcription-quantitative polymerase chain reaction were performed. The viability of cells was measured by 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide assays, while cell damage was measured by lactate dehydrogenase release in the in vitro oxygen glucose deprivation model. In addition, enzyme-linked immunosorbent assay, flow cytometry, western blotting, and reverse transcription-quantitative polymerase chain reaction were used to evaluate the therapeutic effect of Tanshinone IIA on ischemia/reperfusion (I/R) induced brain injury, as well as its effects on the inflammatory response and neuronal apoptosis, in vivo and in vitro. Furthermore, this study validated the targeting relationship between miR-124-5p and FoxO1 using a dual luciferase assay. Finally, we examined the role of Tanshinone IIA in brain injury from a molecular perspective by inhibiting miR-124-5p or increasing FoxO1 levels. After treatment with Tanshinone IIA in middle cerebral artery occlusion-reperfusion (MCAO/R) rats, the volume of cerebral infarction was reduced, the water content of the brain was decreased, the nerve function of the rats was significantly improved, and the cell damage was significantly reduced. In addition, Tanshinone IIA effectively inhibited the I/R-induced inflammatory response and neuronal apoptosis, that is, it inhibited the expression of inflammatory cytokines IL-1β, IL-6, TNF-α, decreased the expression of apoptotic protein Bax and Cleaved-caspase-3, and promoted the expression of antiapoptotic protein Bcl-2. In vitro oxygen-glucose deprivation/reoxygenation (OGD/R) cell model, Tanshinone IIA also inhibited the expression of inflammatory factors in neuronal cells and inhibited the occurrence of neuronal apoptosis. In addition, Tanshinone IIA promoted the expression of miR-124-5p. Transfection of miR-124-5p mimic has the same therapeutic effect as Tanshinone IIA and positive therapeutic effect on OGD cells, while transfection of miR-124-5p inhibitor has the opposite effect. The targeting of miR-124-5p negatively regulates FoxO1 expression. Inhibition of miR-124-5p or overexpression of FoxO1 can weaken the inhibitory effect of Tanshinone IIA on brain injury induced by I/R, while inhibition of miR-124-5p and overexpression of FoxO1 can further weaken the effect of Tanshinone IIA. Tanshinone IIA alleviates ischemic-reperfusion brain injury by inhibiting neuroinflammation through the miR-124-5p/FoxO1 axis. This finding provides a theoretical basis for mechanistic research on cerebral ischemia-reperfusion injury.

Adherence to newer second-line oral antidiabetic drugs among people with type 2 diabetes-A systematic review.

The adherence to oral antidiabetic drugs (OADs) among people with type 2 diabetes (T2D) is suboptimal. However, new OADs have been marketed within the last 10 years. As these new drugs differ in mechanism of action, treatment complexity, and side effects, they may influence adherence. Thus, the aim of this study was to assess the adherence to newer second-line OADs, defined as drugs marketed in 2012-2022, among people with T2D. A systematic review was performed in CINAHL, Cochrane Trials, Embase, PubMed, PsycINFO, and Scopus. Articles were included if they were original research of adherence to newer second-line OADs and reported objective adherence quantification. The quality of the articles was assessed using JBI's critical appraisal tools. The overall findings were reported according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and summarized in a narrative synthesis. All seven included articles were European retrospective cohort studies investigating alogliptin, canagliflozin, dapagliflozin, empagliflozin, and unspecified types of SGLT2i. Treatment discontinuation and medication possession ratio (MPR) were the most frequently reported adherence quantification measures. Within the first 12 months of treatment, 29%-44% of subjects on SGLT2i discontinued the treatment. In terms of MPR, 61.7%-94.9% of subjects on either alogliptin, canagliflozin, dapagliflozin, empagliflozin or an unspecified SGLT2i were adherent. The two investigated adherence quantification measures, treatment discontinuation and MPR, suggest that adherence to the newer second-line OADs may be better than that of older OADs. However, a study directly comparing older and newer OADs should be done to verify this.

Validation of a human saliva model for the determination of leachable monomers and other chemicals from dental materials

This study aimed to prove the validity of a mixture of chemicals, including salts, small organic molecules, mucin, and α-amylase, as saliva surrogate (“artificial saliva”) for assessing leakage of methacrylate monomers and other constituents from dental materials. To achieve this, we developed and validated a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the quantification of 2-hydroxyethyl methacrylate (HEMA), triethylene glycol dimethacrylate (TEGDMA), diurethane dimethacrylate (UDMA), bisphenol A glycerolate dimethacrylate (BisGMA), diphenyl(2,4,6-trimethylbenzoyl)phosphine oxide (TPO), bisphenol A (BPA), and five homologues of ethoxylated bisphenol A dimethacrylate (BisEMA EO2–6) in unstimulated and artificial saliva, and compared their concentrations in the two saliva media following either spiking with a mixture of the compounds or incubation of test specimens of printed biomaterials. Test specimens were immersed in unstimulated/artificial saliva, incubated at 37 °C for 24 h, and saliva aliquots were extracted with methanol and subsequently analyzed by LC-MS/MS. The method was validated with regard to matrix effects, linearity, selectivity, lower limits of quantification (LLOQ), precision, bias and combined measurement uncertainty (u′). The performance characteristics of the method were comparable for unstimulated and artificial saliva samples. The combined u’ for individual chemicals at a concentration of 10 × LLOQ were within the range of 5.3–14 % for unstimulated saliva and 6.9–16 % for artificial saliva, except for the BisEMA homologues. Combined u’ for the latter were 27–74 % in unstimulated saliva, and 27–79 % in artificial saliva. There was no detectable release of BPA from the test specimens, and the TPO concentrations were mainly below the LLOQ. TEGDMA and UDMA were detected in the highest quantities, and at comparable concentrations in the unstimulated and artificial saliva. For all BisEMA homologues, the release was higher in unstimulated saliva than in artificial saliva. The study showed that the artificial saliva model can be a suitable replacement for native saliva, but might underestimate leakage of more lipophilic methacrylates.

Multiomics Evaluation of Human iPSCs and iPSC-Derived Neurons.

Human induced pluripotent stem cells (iPSCs) can be differentiated into neurons, providing living human neurons to model brain diseases. However, it is unclear how different types of molecules work together to regulate stem cell and neuron biology in healthy and disease states. In this study, we conducted integrated proteomics, lipidomics, and metabolomics analyses with confident identification, accurate quantification, and reproducible measurements to compare the molecular profiles of human iPSCs and iPSC-derived neurons. Proteins, lipids, and metabolites related to mitosis, DNA replication, pluripotency, glycosphingolipids, and energy metabolism were highly enriched in iPSCs, whereas synaptic proteins, neurotransmitters, polyunsaturated fatty acids, cardiolipins, and axon guidance pathways were highly enriched in neurons. Mutations in the GRN gene lead to the deficiency of the progranulin (PGRN) protein, which has been associated with various neurodegenerative diseases. Using this multiomics platform, we evaluated the impact of PGRN deficiency on iPSCs and neurons at the whole-cell level. Proteomics, lipidomics, and metabolomics analyses implicated PGRN's roles in neuroinflammation, purine metabolism, and neurite outgrowth, revealing commonly altered pathways related to neuron projection, synaptic dysfunction, and brain metabolism. Multiomics data sets also pointed toward the same hypothesis that neurons seem to be more susceptible to PGRN loss compared to iPSCs, consistent with the neurological symptoms and cognitive impairment from patients carrying inherited GRN mutations.