Immunophenotypic clustering in paediatric acute myeloid leukaemia.

Acute myeloid leukaemia (AML) is a highly heterogeneous disease, exhibiting diverse subtypes according to the characteristics of tumour cells. The immunophenotype is one of the aspects acquired routinely through flow cytometry in the diagnosis of AML. Here, we characterized the antigen expression in paediatric AML cases across both morphological and molecular genetic subgroups. We discovered a subgroup of patients with unfavourable prognosis that can be immunologically characterized, irrespective of morphological FAB results or genetic aberrations. Cox regression analysis unveiled key antigens influencing the prognosis of AML patients. In terms of underlying genotypes, we observed that the antigenic profiles and outcomes of one specific group, primarily composed of CBFA2T3::GLIS2 and FUS::ERG, were analogous to the reported RAM phenotype. Overall, our data highlight the significance of immunophenotype to tailor treatment for paediatric AML.

High-dose methotrexate pharmacokinetics and its impact on prognosis of paediatric acute lymphoblastic leukaemia patients: A population pharmacokinetic study.

This study delivers a comprehensive evaluation of the efficacy and pharmacokinetics of high-dose methotrexate (HDMTX) in a large cohort of Chinese paediatric acute lymphoblastic leukaemia patients. A total of 533 patients were included in the prognostic analysis. An association was observed between lower steady-state MTX concentrations (<56 µmol/L) and poorer outcomes in intermediate-/high-risk (IR/HR) patients. Subgroup analysis further revealed that this relationship between concentrations and prognosis was even more pronounced in patients with MLL rearrangements. In contrast, such an association did not emerge within the low-risk patient group. Additionally, utilizing population pharmacokinetic modelling (6051 concentrations from 815 patients), we identified the significant impact of physiological maturation, estimated glomerular filtration rate, sex and concurrent dasatinib administration on MTX pharmacokinetics. Simulation-based recommendations include a reduced dosage regimen for those with renal insufficiency and a specific 200 mg/kg dosage for infants under 1 year. The findings underscore the critical role of HDMTX in treating IR/HR populations and call for a reassessment of its application in lower-risk groups. An individualized pharmacokinetic dosage regimen could achieve the most optimal results, ensuring the largest proportion of steady-state concentrations within the optimal range.

Glass-Blowing-Inspired Upcycling of Thermosetting Polymer to Neuron-Like Hierarchical Carbon for Microwave Absorption and Conversion.

Upgrading thermosetting polymer waste and harvesting unwanted electromagnetic energy are of great significance in solving environmental pollution and energy shortage problems. Herein, inspired by the glass-blowing art, a spontaneous, controllable, and scalable strategy is proposed to prepare hollow carbon materials by inner blowing and outside blocking. Specifically, hierarchically neuron-like hollow carbon materials (HCMSs) with various sizes are fabricated from melamine-formaldehyde sponge (MS) waste. Benefiting from the synergistic of the hollow "cell body" and the connected "protrusions" networks, HCMSs reveal superior electromagnetic absorption performance with a strong reflection loss of -54.9 dB, electromagnetic-heat conversion ability with a high conversion efficiency of 34.4%, and efficient energy storage performance in supercapacitor. Furthermore, a multifunctional device integrating electromagnetic-heat-electrical energy conversion is designed, and its feasibility is proved by experiments and theoretical calculations. The integrated device reveals an output voltage of 34.5 mV and a maximum output power of 0.89 µW with electromagnetic radiation for 60 s. This work provides a novel solution to recycle polymer waste, electromagnetic energy, and unwanted thermal energy.

The role of marital status in gallbladder cancer: a real-world competing risk analysis.

BACKGROUND: The association between marital status and gallbladder cancer (GBC) remains uncertain. This study aimed to verify the relationship between marital status and GBC and construct a prognostic nomogram to predict the impact of marital status on GBC patients. METHOD: GBC patients were divided into married and unmarried groups using data from the Surveillance, Epidemiology, and End Results (SEER) database. We employed competing risk analyses, propensity score matching (PSM), and Kaplan-Meier survival analyses. The relationship between marital status and GBC was then verified, and the predicted nomogram was constructed. RESULTS: A total of 3913 GBC patients were obtained from the SEER database, and an additional 76 GBC patients from Hangzhou Traditional Chinese Medicine Hospital were selected as the external validation group. The competing risk analysis revealed a significant disparity in the 5-year cumulative incidence of cancer-specific death (CSD) between the two cohorts (59.1% vs. 65.2%, p = 0.003). Furthermore, the multivariate competing hazards regression analysis identified a significant association (HR, 1.17; 95% CI, 1.04-1.31; p = 0.007) between marital status and CSD. To assess the 1-, 3-, and 5-year risks of CSD, a comprehensive competing event nomogram was constructed using factors derived from the multivariate analysis. The area under the receiver operating characteristic curve (AUC) values for the 1-, 3-, and 5-year training cohorts were 0.806, 0.785, and 0.776, respectively. In the internal validation cohort, these values were 0.798, 0.790, and 0.790, while the external validation cohort exhibited AUC values of 0.748, 0.835, and 0.883 for the corresponding time intervals. Furthermore, calibration curves demonstrated a commendable level of concordance between the observed and predicted probabilities of CSD. CONCLUSION: Marriage was a protective factor for GBC patients after taking competing risk into consideration. The proposed nomogram demonstrated exceptional predictive power.

Identifying Hub Genes for Glaucoma Based on Bulk RNA Sequencing Data and Multi-machine Learning Models.

AIMS: The aims of this study were to determine hub genes in glaucoma through multiple machine learning algorithms. BACKGROUND: Glaucoma has afflicted many patients for many years, with excessive pressure in the eye continuously damaging the nervous system and leading to severe blindness. An effective molecular diagnostic method is currently lacking. OBJECTIVE: The present study attempted to reveal the molecular mechanism and gene regulatory network of hub genes in glaucoma, followed by an attempt to reveal the drug-gene-disease network regulated by hub genes. METHODS: A microarray sequencing dataset (GSE9944) was obtained through the Gene Expression Omnibus database. The differentially expressed genes in Glaucoma were identified. Based on these genes, we constructed three machine learning models for feature training, Random Forest model (RF), Least absolute shrinkage and selection operator regression model (LASSO), and Support Vector Machines model (SVM). Meanwhile, Weighted Gene Co-Expression Network Analysis (WGCNA) was performed for GSE9944 expression profiles to identify Glaucoma-related genes. The overlapping genes in the four groups were considered as hub genes of Glaucoma. Based on these genes, we also constructed a molecular diagnostic model of Glaucoma. In this study, we also performed molecular docking analysis to explore the gene-drug network targeting hub genes. In addition, we evaluated the immune cell infiltration landscape in Glaucoma samples and normal samples by applying CIBERSORT method. RESULTS: 8 hub genes were determined: ATP6V0D1, PLEC, SLC25A1, HRSP12, PKN1, RHOD, TMEM158 and GSN. The diagnostic model showed excellent diagnostic performance (area under the curve=1). GSN might positively regulate T cell CD4 naïve as well as negatively regulate T cell regulation (Tregs). In addition, we constructed gene-drug networks in an attempt to explore novel therapeutic agents for Glaucoma. CONCLUSION: Our results systematically determined 8 hub genes and established a molecular diagnostic model that allowed the diagnosis of Glaucoma. Our study provided a basis for future systematic studies of Glaucoma pathogenesis.

Who are optimal candidates for primary tumor resection in patients with metastatic gastric adenocarcinoma? A population-based study.

BACKGROUND: The research aimed to construct a novel predictive nomogram to identify specific metastatic gastric adenocarcinoma (mGAC) populations who could benefit from primary tumor resection (PTR). METHOD: Patients with mGAC were included in the SEER database and divided into PTR and non-PTR groups. The Kaplan-Meier analysis, propensity score matching (PSM), least absolute shrink and selection operator (LASSO) regression, multivariable logistic regression, and multivariate Cox regression methods were then used. Finally, the prediction nomograms were built and tested. RESULTS: 3185 patients with mGAC were enrolled. Among the patients, 679 cases underwent PTR while the other 2506 patients didn't receive PTR. After PSM, the patients in the PTR group presented longer median overall survival (15.0 vs. 7.0 months, p < 0.001). Among the PTR group, 307 (72.9%) patients obtained longer overall survival than seven months (beneficial group). Then the LASSO logistic regression was performed, and gender, grade, T stage, N stage, pathology, and chemotherapy were included to construct the nomogram. In both the training and validation cohorts, the nomogram exhibited good discrimination (AUC: 0.761 and 0.753, respectively). Furthermore, the other nomogram was constructed to predict 3-, 6-, and 12-month cancer-specific survival based on the variables from the multivariate Cox analysis. The 3-, 6-, and 12-month AUC values were 0.794, 0.739, and 0.698 in the training cohort, and 0.805, 0.759, and 0.695 in the validation cohorts. The calibration curves demonstrated relatively good consistency between the predicted and observed probabilities of survival in two nomograms. The models' clinical utility was revealed through decision curve analysis. CONCLUSION: The benefit nomogram could guide surgeons in decision-making and selecting optimal candidates for PTR among mGAC patients. And the prognostic nomogram presented great prediction ability for these patients.

Human emissions of size-resolved fluorescent bioaerosols in control situations.

Human bioaerosols contribute significantly to indoor air quality. This study used a Wideband Integrated Bioaerosol Sensor (WIBS-4A) instrument for real-time measurement of particle size distribution and count to differentiate fluorescent bioaerosols from non-fluorescent aerosols. Through an experiment involving 12 subjects (six men and six women) wearing standard cotton clothing in a 2 m × 2 m × 2 m environmental chamber, we established a quantitative method to obtain the bioaerosol emission rate of a single subject, aiming to explore the effects of masks and sex on bioaerosol emissions from different individuals. The mean emission rates of fluorescent bioaerosols in the particle size ranges of 0.5-2.5 µm and 2.5-10 µm were 3.192±2.11×104 counts/(person·h) and 13.98±9.34×104 counts/(person·h), respectively. A comparison between those wearing and not wearing masks revealed no significant differences in the emissions of fluorescent bioaerosols. This suggests respiratory sources may not significantly impact the emissions of fluorescent bioaerosols from individuals under seated breathing conditions. Significant disparities in the fluorescent bioaerosol emission rates of different biological sexes were observed through independent sample analysis. Males exhibited 41 % and 15 % higher emission rates than females for particle size ranges of 0.5-2.5 µm and 2.5-10 µm, respectively, possibly because of different metabolic rates. A significant correlation between metabolic rates and fluorescent bioaerosols (sig = 0.044 < 0.05) was observed in all the subjects. These findings underscore the individual variations that affect bioaerosol emission rates. The data provided by this study will facilitate further analysis of the on-site measured data and source analysis.

Genome-Wide Bioinformatics Analysis of SWEET Gene Family and Expression Verification of Candidate PaSWEET Genes in Potentilla anserina.

Sugars act as the main energy sources in many fruit and vegetable crops. The biosynthesis and transportation of sugars are crucial and especially contribute to growth and development. SWEET is an important gene family that plays a vital role in plants' growth, development, and adaptation to various types of stresses (biotic and abiotic). Although SWEET genes have been identified in numerous plant species, there is no information on SWEETs in Potentilla anserina. In the present study, we performed a comprehensive genome-wide bioinformatics analysis and identified a total of 23 candidate PaSWEETs genes in the Potentilla anserina genome, which were randomly distributed on ten different chromosomes. The phylogenetic analysis, chromosomal location, gene structure, specific cis-elements, protein interaction network, and physiological characteristics of these genes were systematically examined. The identified results of the phylogenetic relationship with Arabidopsis thaliana revealed that these PaSWEET genes were divided into four clades (I, II, III, and IV). Moreover, tissue-specific gene expression through quantitative real-time polymerase chain reaction (qRT-PCR) validation exposed that the identified PaSWEETs were differentially expressed in various tissues (roots, stems, leaves, and flowers). Mainly, the relative fold gene expression in swollen and unswollen tubers effectively revealed that PaSWEETs (7, 9, and 12) were highly expressed (300-, 120-, and 100-fold) in swollen tubers. To further elucidate the function of PaSWEETs (7, 9, and 12), their subcellular location was confirmed by inserting them into tobacco leaves, and it was noted that these genes were present on the cell membrane. On the basis of the overall results, it is suggested that PaSWEETs (7, 9, and 12) are the candidate genes involved in swollen tuber formation in P. anserina. In crux, we speculated that our study provides a valuable theoretical base for further in-depth function analysis of the PaSWEET gene family and their role in tuber development and further enhancing the molecular breeding of Potentilla anserina.

Bone marrow stromal cells dictate lanosterol biosynthesis and ferroptosis of multiple myeloma.

Ferroptosis has been demonstrated a promising way to counteract chemoresistance of multiple myeloma (MM), however, roles and mechanism of bone marrow stromal cells (BMSCs) in regulating ferroptosis of MM cells remain elusive. Here, we uncovered that MM cells were more susceptible to ferroptotic induction under the interaction of BMSCs using in vitro and in vivo models. Mechanistically, BMSCs elevated the iron level in MM cells, thereby activating the steroid biosynthesis pathway, especially the production of lanosterol, a major source of reactive oxygen species (ROS) in MM cells. We discovered that direct coupling of CD40 ligand and CD40 receptor constituted the key signaling pathway governing lanosterol biosynthesis, and disruption of CD40/CD40L interaction using an anti-CD40 neutralizing antibody or conditional depletion of Cd40l in BMSCs successfully eliminated the iron level and lanosterol production of MM cells localized in the Vk*MYC Vk12653 or NSG mouse models. Our study deciphers the mechanism of BMSCs dictating ferroptosis of MM cells and highlights the therapeutic potential of non-apoptosis strategies for managing refractory or relapsed MM patients.

circRNAs as prognostic markers in pediatric acute myeloid leukemia.

Circular RNAs (circRNAs) arise from precursor mRNA processing through back-splicing and have been increasingly recognized for their functions in various cancers including acute myeloid leukemia (AML). However, the prognostic implications of circRNA in AML remain unclear. We conducted a comprehensive genome-wide analysis of circRNAs using RNA-seq data in pediatric AML. We revealed a group of circRNAs associated with inferior outcomes, exerting effects on cancer-related pathways. Several of these circRNAs were transcribed directly from genes with established functions in AML, such as circRUNX1, circWHSC1, and circFLT3. Further investigations indicated the increased number of circRNAs and linear RNAs splicing were significantly correlated with inferior clinical outcomes, highlighting the pivotal role of splicing dysregulation. Subsequent analysis identified a group of upregulated RNA binding proteins in AMLs associated with high number of circRNAs, with TROVE2 being a prominent candidate, suggesting their involvement in circRNA associated prognosis. Through the integration of drug sensitivity data, we pinpointed 25 drugs that could target high-risk AMLs characterized by aberrant circRNA transcription. These findings underscore prognostic significance of circRNAs in pediatric AML and offer an alternative perspective for treating high-risk cases in this malignancy.