Search Results (242)

Limited data on treosulfan pharmacokinetics in adults, particularly regarding autologous stem cell transplantation (ASCT) in acute myeloid leukemia (AML), is available to date. Furthermore, correlations between treosulfan exposure, toxicity, and clinical outcome remain understudied. In this single-center retrospective study, we analyzed data from 55 AML patients who underwent HDCT with treosulfan (14 g/m²) and melphalan (140 mg/m² or 200 mg/m²) (TreoMel) between August 2019 and November 2023 at the University Hospital of Bern. We assessed treosulfan pharmacokinetics and correlations with several physiological parameters with potential impact on its interpatient variability. We further analyzed how treosulfan exposure correlates with toxicity and clinical outcomes. Women above 55 years showed higher area under the curve (AUC) levels (median: 946 mg*h/L, range: 776–1370 mg*h/L), as compared to women under 55 (median: 758 mg*h/L, range: 459–1214 mg*h/L, p = 0.0487). Additionally, women above 55 showed higher peak levels (median: 387 mg/L, range: 308–468 mg/L), as compared to men of the same age range (median: 326 mg/L, range: 264–395 mg/L, p = 0.0159). Treosulfan levels varied significantly with body temperature, liver enzymes, hemoglobin/hematocrit., and treosulfan exposure correlated with diarrhea severity in women over 55 (p = 0.0076). Our study revealed age- and gender-related variability in treosulfan pharmacokinetics, with higher plasma levels observed in female patients above 55. Moreover, our data suggest that treosulfan plasma levels may vary with several physiological parameters and that higher treosulfan exposure may impact toxicity. Our study underlines the need for further research on treosulfan pharmacokinetics, especially in older patients undergoing HDCT in the ASCT setting. Full article

Gastric cancer (GC) is a leading cause of death, and this pathology often receives a diagnosis in an advanced stage. The development of a less invasive and cost-effective test for detection is essential for decreasing the mortality rate and increasing the life expectancy of GC patients. We evaluated the potential targeting of CD54/ICAM1, a marker of gastric cancer stem cells, with miRNAs to detect GC in blood samples. The analyses included 79 blood samples, 38 from GC patients and 41 from healthy donors, who attended INCan, México City. The total RNA was obtained from the blood plasma, and RT-PCR and qPCR were performed to obtain the relative expression of each miRNA. Hsa-miR-335-5p was detected in the plasma of GC patients and healthy donors at the same levels. The ROC curve analyses indicated that this miRNA was not a candidate for the molecular diagnosis of GC. We did not observe a correlation between the expression of hsa-miR-335-5p and clinical variables; however, the Kaplan–Meier analyses indicated that, in patients who survived more than 12 months, a lower expression of hsa-miR-335-5p was correlated with a better prognosis. It would be convenient to evaluate a larger panel of miRNAs, including miRNAs expressed in a limited number of cell types or with a low number targets, to obtain more specific candidates for developing a robust test for the diagnosis/prognosis of GC. Full article

(1) Background: The impact of inflammation on voriconazole exposure in oncohematological pediatric patients represents a debated issue. We aimed to investigate the impact of serum C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) levels on voriconazole exposure in oncohematological pediatric patients requiring allogeneic hematopoietic stem cell transplantation (HCT). (2) Methods: Pediatric patients undergoing allogeneic HCT and receiving therapeutic drug monitoring (TDM)-guided voriconazole as primary antifungal prophylaxis between January 2021 and December 2023 were included. The ratio between concentration and dose (C/D) of voriconazole was used as a surrogate marker of total clearance. A receiving operating characteristic curve analysis was performed by using CRP, PCT, or IL-6 values as the test variable and voriconazole C/D ratio > 0.188 or >0.375 (corresponding to a trough concentration value [C_min] of 3 mg/L normalized to the maintenance dose of 16 mg/kg/day in patients of age < 12 years and of 8 mg/kg/day in those ≥12 years, respectively) as the state variable. Area under the curve (AUC) and 95% confidence interval (CI) were calculated. (3) Results: Overall, 39 patients were included. The median (IQR) voriconazole C_min was 1.7 (0.7–3.0) mg/L. A CRP value > 8.49 mg/dL (AUC = 0.72; 95%CI 0.68–0.76; p < 0.0001), a PCT value > 2.6 ng/mL (AUC = 0.71; 95%CI 0.63–0.77; p < 0.0001), and an IL-6 value > 27.9 pg/mL (AUC = 0.80; 95%CI 0.71–0.88; p < 0.0001) were significantly associated with voriconazole overexposure. Consistent results were found in patients aged <12 and ≥12 years. (4) Conclusions: A single specific threshold of inflammatory biomarkers may be linked to a significantly higher risk of voriconazole exposure in oncohematological pediatric patients after HCT, irrespective of age. Adopting a TDM-guided strategy could be useful for minimizing the risk of voriconazole overexposure. Full article

Regenerative endodontics (REP) is a new clinical modality aiming to regenerate damaged soft and hard dental tissues, allowing for root completion in young adults’ teeth. Effective disinfection is crucial for REP success, but commonly used antimicrobials often harm the niche dental pulp stem cells (DPSCs). To our knowledge, this is the first study to explore the biocompatibility and antimicrobial potential of pectin as a potential natural intracanal medicament for REPs. Low methoxyl commercial citrus pectin (LM) (pectin CU701, Herbstreith&Fox.de) was used in all experiments. The pectin’s antibacterial activity against single species biofilms (E. faecalis and F. nucleatum) was assessed using growth curves. The pectin’s antimicrobial effect against mature dual-species biofilm was also evaluated using confocal laser scanning microscopy (CLSM) after 30 min and 7 days of treatment. The DPSC biocompatibility with 2% and 4% w/v of the pectin coatings was evaluated using live/dead staining, LDH, and WST-1 assays. Pectin showed a concentration-dependent inhibitory effect against single-species biofilms (E. faecalis and F. nucleatum) but failed to disrupt dual-species biofilm. Pectin at 2% w/v concentration proved to be biocompatible with the HDPSCs. However, 4% w/v pectin reduced both the viability and proliferation of the DPSCs. Low concentration (2% w/v) pectin was biocompatible with the DPSCs and showed an antimicrobial effect against single-species biofilms. This suggests the potential for using pectin as an injectable hydrogel for clinical applications in regenerative endodontics. Full article

Objective: The objective of this study was to evaluate the therapeutic efficacy of ursodeoxycholic acid (UDCA) and mesenchymal stem cells (MSCs) in patients with severe COVID-19. Methods: We included severe COVID-19 patients hospitalized at Shulan (Hangzhou) Hospital between December 2022 and June 2023. We used a logistic regression model to compare the use of UDCA and MSCs in the two distinct groups of improved and poor outcomes. It is noteworthy that the deterioration group encompassed instances of both death and abandonment of treatment. The receiver operating characteristic (ROC) curve was plotted to assess the performance of the model. The aim was to assess the therapeutic effect of UDCA and MSCs on the outcome of severe COVID-19 patients. Results: A total of 167 patients with severe COVID-19 were included in this study. The analysis revealed that out of 42 patients (25.1%), 17 patients (10.2%) had taken UDCA, and 17 patients (10.2%) had used MSCs. Following a multivariable logistic regression, the results indicated a negative association between UDCA treatment (OR = 0.38 (0.16–0.91), p = 0.029), MSCs treatment (OR = 0.21 (0.07–0.65), p = 0.007), and the risk of severe COVID-19 mortality. Additionally, age showed a positive association with the risk of mortality (OR = 1.03 (1.01–1.07), p = 0.025). Conclusions: UDCA and MSCs have shown potential in improving the prognosis of severe COVID-19 patients and could be considered as additional treatments for COVID-19 in the future. Full article

The educational expectations of students for themselves have been commonly corroborated to directly predict their higher academic performance. Nevertheless, some recent research has reported that the academic performance of students may also contribute to their better development of educational expectations. Moreover, more advanced but limited research has argued that both the educational expectations and academic performance of students are developmental and changeable over time rather than fixed and stable. Due to the importance of students’ science learning performance during the years of secondary school in relation to their later STEM development in adulthood, the current study is intended to investigate how the developmental and growth trajectories of students’ educational expectations and science learning performance reciprocally affect each other directly and inversely in secondary school and then later contribute to their successful completion of a STEM degree in adulthood. Based on the six-wave panel data containing a nationally representative sample of adolescent students from the Longitudinal Study of American Youth (LSAY), the current study was conducted by parallel-process latent growth curve modeling (PP-LGCM) and found that both the developmental and growth trajectories of students’ educational expectations and science learning performance were mutually predictive of each other across the years of secondary school, which then contributed to their later higher likelihood of successful completion of a STEM degree in adulthood. In addition, the conditional direct PP-LGCM model, which is to model the effects of students’ educational expectations on their science learning performance, and the conditional inverse PP-LGCM model, which is to model the effects of students’ science learning performance on their educational expectations, showed significant within- and cross-domain effects differently. The implications of the study findings related to educational reforms and policy designs are discussed. Full article

Intratumoral heterogeneity (ITH) complicates the diagnosis and treatment of glioma, partly due to the diverse metabolic profiles driven by underlying genomic alterations. While multiparametric imaging enhances the characterization of ITH by capturing both spatial and functional variations, it falls short in directly assessing the metabolic activities that underpin these phenotypic differences. This gap stems from the challenge of integrating easily accessible, colocated pathology and detailed genomic data with metabolic insights. This study presents a multifaceted approach combining stereotactic biopsy with standard clinical open-craniotomy for sample collection, voxel-wise analysis of MR images, regression-based GAM, and whole-exome sequencing. This work aims to demonstrate the potential of machine learning algorithms to predict variations in cellular and molecular tumor characteristics. This retrospective study enrolled ten treatment-naïve patients with radiologically confirmed glioma. Each patient underwent a multiparametric MR scan (T1_W, T1_W-CE, T2_W, T2_W-FLAIR, DWI) prior to surgery. During standard craniotomy, at least 1 stereotactic biopsy was collected from each patient, with screenshots of the sample locations saved for spatial registration to pre-surgical MR data. Whole-exome sequencing was performed on flash-frozen tumor samples, prioritizing the signatures of five glioma-related genes: IDH1, TP53, EGFR, PIK3CA, and NF1. Regression was implemented with a GAM using a univariate shape function for each predictor. Standard receiver operating characteristic (ROC) analyses were used to evaluate detection, with AUC (area under curve) calculated for each gene target and MR contrast combination. Mean AUC for five gene targets and 31 MR contrast combinations was 0.75 ± 0.11; individual AUCs were as high as 0.96 for both IDH1 and TP53 with T2_W-FLAIR and ADC, and 0.99 for EGFR with T2_W and ADC. These results suggest the possibility of predicting exome-wide mutation events from noninvasive, in vivo imaging by combining stereotactic localization of glioma samples and a semi-parametric deep learning method. The genomic alterations identified, particularly in IDH1, TP53, EGFR, PIK3CA, and NF1, are known to play pivotal roles in metabolic pathways driving glioma heterogeneity. Our methodology, therefore, indirectly sheds light on the metabolic landscape of glioma through the lens of these critical genomic markers, suggesting a complex interplay between tumor genomics and metabolism. This approach holds potential for refining targeted therapy by better addressing the genomic heterogeneity of glioma tumors. Full article

A novel Bayesian spatial distributional regression model is presented to predict forest structural diversity in terms of the distributions of the stem diameter at breast height (DBH) in the protection forests in Ebensee, Austria. The distributional regression approach overcomes the limitations and uncertainties of traditional regression modeling, in which the conditional mean of the response is regressed against explanatory variables. The distributional regression addresses the complete conditional response distribution, instead. In total 36,338 sample trees were measured via a handheld mobile personal laser scanning system (PLS) on 273 sample plots each having a 20 m radius. Recent airborne laser scanning (ALS) data were used to derive regression covariates from the normalized digital vegetation height model (DVHM) and the digital terrain model (DTM). Candidate models were constructed that differed in their linear predictors of the two gamma distribution parameters. In the distributional regression approach, covariates can enter the model in a flexible form, such as via nonlinear smooth curves, cyclic smooths, or spatial effects. Supported by Bayesian diagnostics DIC and WAIC, nonlinear smoothing splines outperformed linear parametric slope coefficients, and the best implementation of spatial structured effects was achieved by a Gaussian process smooth. Model fitting and posterior parameter inference was achieved by using full Bayesian methodology and MCMC sampling algorithms implemented in the R-package BAMLSS. With BAMLSS, spatial interval predictions of the DBH distribution at any new geo-locations were enabled via straightforward access to the posterior predictive distributions of the model terms and by offering simple plug-in solutions for new covariate values. A cross-validation analysis validated the robustness of the proposed method’s parameter estimation and out-of-sample prediction. Spatial predictions of stem count proportions per DBH classes revealed that regeneration of smaller trees was lacking in certain areas of the protection forest landscape. Therefore, the intensity of final felling needs to be increased to reduce shading from the dense, overmature shelter trees and to promote sunlight for the young regeneration trees. Full article

In this paper, we study the nonlinear optical bistability (OB) in a symmetrical multilayer structure. This multilayer structure is constructed by embedding a nonlinear three-dimensional Dirac semimetal (3D DSM) into a Fabry–Perot cavity composed of one-dimensional photonic crystals. The OB phenomenon stems from the third order nonlinear conductivity of 3D DSM. The local field of resonance mode could enhance the nonlinearity and reduce the thresholds of OB. This structure achieves the tunability of OB due to the fact that the transmittance could be modulated by the Fermi energy. It is found that the OB threshold and threshold width could be remarkably reduced by increasing the Fermi energy of the 3D DSM. Besides, we also found that the OB curve depends heavily on the angle of incidence of the incident light, the structural parameters of the Fabry–Perot cavity, and the position of the 3D DSM inside the cavity. After parameter optimization, we obtained OB with a threshold of 106 V/m. We believe this simple multilayer structure could provide a reference idea for realizing low-threshold and tunable all-optical switching devices. Full article

Background/Objectives: Contrast-induced acute kidney injury (AKI) is associated with early mortality and adverse events. However, in the setting of transcatheter aortic valve implantation (TAVI), previous literature has failed to establish a correlation between the absolute volume of contrast media administered and mortality. We aimed to investigate the impact of contrast volume administered normalised to estimated glomerular filtration rate (CV/eGFR) on the development of AKI and on 30-day all-cause mortality in TAVI patients. Methods: We retrospectively analysed a cohort of 1150 patients who underwent TAVI at our unit between 2015 and 2018. Results: Follow-up was complete for 1064 patients. There were 23 deaths within the follow-up period and 76 cases of AKI, 9 of which required new renal replacement therapy (RRT). Receiver-operating characteristic (ROC) curve analysis showed fair discrimination for 30-day all-cause mortality at a CV/eGFR ratio of 3.6 (area under the ROC curve (AUC) 0.671). Of patients in whom CV data were available, 86.0% (n = 757) had a CV/eGFR < 3.6 and 14.0% (n = 123) had a CV/eGFR ≥ 3.6. In multivariate logistic regression analysis, CV/eGFR ≥ 3.6 was the strongest predictor of 30-day all-cause mortality (odds ratio 5.06, 95% confidence interval [1.61–15.7], p = 0.004). Other independent predictors were procedural urgency (3.28 [1.04–10.3], p = 0.038) and being under general anaesthesia (4.81 [1.10–17.3], p = 0.023). CV/eGFR ≥ 3.6 was also independently associated with significantly increased odds of AKI (2.28 [1.20–4.17], p = 0.009) alongside significant non-left main stem coronary artery disease (2.56 [1.45–4.66], p = 0.001), and diabetes (1.82 [1.03–3.19], p = 0.037). In supplementary ROC curve analysis, a similar CV/eGFR cut point of 3.6 was found to be an excellent predictor for new RRT (AUC 0.833). Conclusions: In conclusion, a CV/eGFR ≥ 3.6 post-TAVI was found to be a strong predictor of 30-day mortality and AKI. The maximum contrast volume that can be safely administered in each patient without significantly increasing the risk of mortality and AKI can be calculated using this ratio. Full article

The use of mobile laser scanning for mapping forests has scarcely been studied in difficult forest conditions. In this paper, we compare the accuracy of retrieving tree attributes, particularly diameter at breast height (DBH), stem curve, stem volume, and tree height, using six different laser scanning systems in a managed natural boreal forest. These compared systems operated both under the forest canopy on handheld and unmanned aerial vehicle (UAV) platforms and above the canopy from a helicopter. The complexity of the studied forest sites ranged from easy to difficult, and thus, this is the first study to compare the performance of several laser scanning systems for the direct measurement of stem curve in difficult forest conditions. To automatically detect tree stems and to calculate their attributes, we utilized our previously developed algorithm integrated with a novel bias compensation method to reduce the overestimation of stem diameter arising from finite laser beam divergence. The bias compensation method reduced the absolute value of the diameter bias by 55–99%. The most accurate laser scanning systems were equipped with a Velodyne VLP-16 sensor, which has a relatively low beam divergence, on a handheld or UAV platform. In easy plots, these systems found a root-mean-square error (RMSE) of below 10% for DBH and stem curve estimates and approximately 10% for stem volume. With the handheld system in difficult plots, the DBH and stem curve estimates had an RMSE under 10%, and the stem volume RMSE was below 20%. Even though bias compensation reduced the difference in bias and RMSE between laser scanners with high and low beam divergence, the RMSE remained higher for systems with a high beam divergence. The airborne laser scanner operating above the forest canopy provided tree attribute estimates close to the accuracy of the under-canopy laser scanners, but with a significantly lower completeness rate for stem detection, especially in difficult forest conditions. Full article

Background: The aim of the present study was to provide ocular biometry percentile values for Indian children between the ages of 6 and 12 and to validate the usefulness of centiles in predicting myopia development. Methods: The study was part of a longitudinal study—the Sankara Nethralaya Tamil Nadu Essilor Myopia Study (STEM), where objective refraction and ocular biometry were measured for children studying in grades 1, 4, and 6 at baseline (2019–2020). These data were used to generate ocular biometry percentile curves (both for axial length (AL) and AL/corneal curvature (AL/CR) ratios). The usefulness of percentile values in predicting myopia development was estimated from follow-up data (2022). Results: The total number of children in the three grades at baseline was 4514 (age range 6 to 12). Boys represented 54% (n = 2442) of the overall sample. The prevalence of myopia at baseline was 11.7% (95% CI from 10.8 to 12.7%) in these three grades. Both the AL and AL/CR ratio centiles showed a linear trend with an increase in AL and AL/CR with increasing grades (p < 0.001) for all percentiles (2, 5, 10, 25, 50, 75, 90, 95, 98, and 99) when stratified by sex. In the follow-up data (n = 377), the 75th and 50th percentiles of the AL/CR ratio had an area under the curve (AUC) of 0.79 and 0.72 to predict myopia onset for grade 4 and 6 children at baseline. Combining baseline AL with the centile shift in follow-up as a predictor increased the AUC to 0.83. Conclusions: The present study has provided centile values specific for Indian children between the ages of 6 and 12 to monitor and intervene where children are at a higher risk of myopia development. Full article

The expansion of forested areas through afforestation and reforestation is widely recognized as a highly effective natural solution for mitigating climate change. Accurately assessing the potential carbon uptake capacity of newly afforested areas requires modelling tools to estimate biomass stocks, including site index curves and biomass models. Given the unique conditions in terms of tree size, uniform spacing, and tree allometries observed in young afforestations compared to natural stands, specific tools are necessary. In Spain, over 800,000 ha has been afforested with native forest species since 1992, but specific modelling tools for these plantations are lacking. Using data from 370 stem analyses collected across an extensive network of plots in young afforestations, we developed dynamic height growth and site index models for the main native species (five pines and five oaks) commonly used in afforestation in Spain. We compared various nonlinear models, such as ADA (algebraic difference approach) and GADA (generalized algebraic difference approach) expansions. The developed site index models were then used to predict the total biomass stored in the afforestation. Our results underscore the necessity for specific site index models tailored to afforestations, as well as the potential of the established site index in predicting biomass and carbon fixation capacity in these young forests. Full article

BRAF mutation identification is important for the diagnosis and treatment of several tumor types, both solid and hematologic. Rapid identification of BRAF mutations is required to determine eligibility for targeted BRAF inhibitor therapy. The Idylla BRAF mutation assay is a rapid, multiplex allele-specific PCR test designed to detect the most common oncogenic BRAF V600 mutations in formalin-fixed paraffin-embedded (FFPE) tissue samples. Here, we describe the validation of the Idylla BRAF mutation assay in our laboratory. During routine clinical practice, we noticed cases in which BRAF V600 mutations were identified with unusual amplification curves, with three cases displaying a delayed amplification within a double amplification pattern and two false-positive calls. We therefore initiated a quality improvement effort to systematically and retrospectively evaluate next-generation sequencing (NGS)-tested cases with BRAF mutations identified within five amino acids of BRAF codon V600 and did not identify additional false-positive cases. We hypothesize that late amplification in a double amplification pattern may represent non-specific amplification, whereas cases displaying single delayed amplification curves may stem from the presence of either non-V600 variants, very low-level V600 variants, cytosine deamination artifacts, and/or non-specific amplification by an allele-specific PCR primer. Regardless, we recommend that Idylla BRAF cases with non-classical amplification curves undergo reflex NGS testing. These findings are likely relevant for other Idylla assays interrogating hotspot mutations in genes such as EGFR, IDH1/2, KRAS, and NRAS. Full article

The unique zigzag-patterned tea plant is a rare germplasm resource. However, the molecular mechanism behind the formation of zigzag stems remains unclear. To address this, a BC1 genetic population of tea plants with zigzag stems was studied using histological observation and bulked segregant RNA-seq. The analysis revealed 1494 differentially expressed genes (DEGs) between the upright and zigzag stem groups. These DEGs may regulate the transduction and biosynthesis of plant hormones, and the effects on the phenylpropane biosynthesis pathways may cause the accumulation of lignin. Tissue sections further supported this finding, showing differences in cell wall thickness between upright and curved stems, potentially due to lignin accumulation. Additionally, 262 single-nucleotide polymorphisms (SNPs) across 38 genes were identified as key SNPs, and 5 genes related to zigzag stems were identified through homologous gene function annotation. Mutations in these genes may impact auxin distribution and content, resulting in the asymmetric development of vascular bundles in curved stems. In summary, we identified the key genes associated with the tortuous phenotype by using BSR-seq on a BC1 population to minimize genetic background noise. Full article