Immunotherapy-relevance of a candidate prognostic score for Acute Myeloid Leukemia.

Background: Acute Myeloid Leukemia (AML) exhibits a wide array of phenotypic manifestations, progression patterns, and heterogeneous responses to immunotherapies, suggesting involvement of complex immunobiological mechanisms. This investigation aimed to develop an integrated prognostic model for AML by incorporating cancer driver genes, along with clinical and phenotypic characteristics of the disease, and to assess its implications for immunotherapy responsiveness. Methods: Critical oncogenic driver genes linked to survival were identified by screening primary effector and corresponding gene pairs using data from The Cancer Genome Atlas (TCGA), through univariate Cox proportional hazard regression analysis. This was independently verified using dataset GSE37642. Primary effector genes were further refined using LASSO regression. Transcriptomic profiling was quantified using multivariate Cox regression, and the derived prognostic score was subsequently validated. Finally, a multivariate Cox regression model was developed, incorporating the transcriptomic score along with clinical parameters such as age, gender, and French-American-British (FAB) classification subtype. The 'Accurate Prediction Model of AML Overall Survival Score' (APMAO) was developed and subsequently validated. Investigations were conducted into functional pathway enrichment, alterations in the gene mutational landscape, and the extent of immune cell infiltration associated with varying APMAO scores. To further investigate the potential of APMAO scores as a predictive biomarker for responsiveness to cancer immunotherapy, we conducted a series of analyses. These included examining the expression profiles of genes related to immune checkpoints, the interferon-gamma signaling pathway, and m6A regulation. Additionally, we explored the relationship between these gene expression patterns and the Tumor Immune Dysfunction and Exclusion (TIDE) dysfunction scores. Results: Through the screening of 95 cancer genes associated with survival and 313 interacting gene pairs, seven genes (ACSL6, MAP3K1, CHIC2, HIP1, PTPN6, TFEB, and DAXX) were identified, leading to the derivation of a transcriptional score. Age and the transcriptional score were significant predictors in Cox regression analysis and were integral to the development of the final APMAO model, which exhibited an AUC greater than 0.75 and was successfully validated. Notable differences were observed in the distribution of the transcriptional score, age, cytogenetic risk categories, and French-American-British (FAB) classification between high and low APMAO groups. Samples with high APMAO scores demonstrated significantly higher mutation rates and pathway enrichments in NFKB, TNF, JAK-STAT, and NOTCH signaling. Additionally, variations in immune cell infiltration and immune checkpoint expression, activation of the interferon-γ pathway, and expression of m6A regulators were noted, including a negative correlation between CD160, m6A expression, and APMAO scores. Conclusion: The combined APMAO score integrating transcriptional and clinical parameters demonstrated robust prognostic performance in predicting AML survival outcomes. It was linked to unique phenotypic characteristics, distinctive immune and mutational profiles, and patterns of expression for markers related to immunotherapy sensitivity. These observations suggest the potential for facilitating precision immunotherapy and advocate for its exploration in upcoming clinical trials.

Reduction and Hydroxylation Metabolites of Mequindox in Holothurian Analysis by Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry.

This research proposed and validated an LC-MSMS method for five reduction and hydroxylation metabolites of Mequindox (MEQ) as well as the precursor in holothurian samples. Specially, three hydroxylation metabolites (2-isoethanol-mequindox, M3, 2-isoethanol-1-desoxymequindox, M4 and 2-isoethanol-4-desoxymequindox, M5) are novel for analysis. Target compounds were extracted with methanol and ethyl acetate in turn without any complicated acidolysis, alkaline hydrolysis or enzymolysis steps. Samples were further purified with C18 solid-phase extraction cartridges for LC-MSMS analysis. Mean recoveries in spiked samples ranged from 81 to 107% with intra-day relative standard deviation (RSD) and inter-day RSD <11.2 and 9.9%, respectively. Limit of detection was determined based on signal-to-noise ratio ≥3 ranged from 0.16 to 2.11 µg kg-1 for each target. The validated protocol was successfully applied for commercial holothurian samples with a positive rate at 13.3%. And concentrations of hydroxylation metabolites were higher than reduction metabolites and precursor MEQ in positive samples.

Online calibration technology for a one-dimensional laser Doppler velocimeter based on a strapdown inertial navigation system.

In the integrated navigation system, which consists of a laser Doppler velocimeter (LDV) and strapdown inertial navigation system, it is necessary to calibrate the LDV. We propose an online calibration method for a LDV based on the strapdown inertial navigation system. This system uses highly accurate output information in the early stage of the inertial navigation system to carry out coarse calibration for the velocimeter and then employs a Kalman filter to correct the results of coarse calibration to achieve high precision calibration for the velocimeter. Experimental results show that the relative distance error of dead reckoning is less than 0.02%, indicating that the proposed online calibration method can achieve high-precision calibration for the velocimeter.

Position observation-based calibration method for an LDV/SINS integrated navigation system.

With the advantages of high velocity measurement accuracy and fast dynamic response, the laser Doppler velocimeter (LDV) is expected to replace the odometer to be combined with a strapdown inertial navigation system (SINS) to form a higher precision integrated navigation system. However, LDV scale factor error and misalignment angles between LDV and inertial measurement unit will affect the accuracy of navigation. Considering that not all global navigation satellite system (GNSS) receivers can directly provide velocity information and current mainstream calibration methods are sensitive to the measurement noise and outliers of velocity and position information, a robust calibration method aided by GNSS is proposed in this paper, which is based on position observation. Different from current popular calibration methods, the attitude information of the GNSS/SINS integrated navigation system obtained by an adaptive Kalman filter is used to construct the observation vector together with LDV velocity outputs and GNSS position outputs in this method. The LDV scale factor error and the misalignment angle are determined by the ratio of two observation vector modulus and the Davenport's q-method method, respectively. The accuracy and robustness of the calibration method are verified by one vehicle test with normal GNSS signals and one vehicle test with GNSS signals with outliers. And the horizontal position error of dead reckoning of the calibrated LDV/SINS integrated system are less than 0.0314% and 0.1033% of the mileage, respectively.

One-dimensional reference-beam LDV for accurate altitude estimation in a land vehicle.

In order to provide accurate altitude information autonomously for land navigation, a self-developed one-dimensional reference-beam laser Doppler velocimeter (1D LDV) with light weight, small volume, and low cost is integrated with a strapdown inertial navigation system (SINS). The velocity sensed by the 1D LDV and the altitude output by the SINS are fused by the dead reckoning algorithm. Dynamic vehicle tests are carried out in an urban area with the altitude difference of 28 m and a mountainous area with the altitude difference of 1363 m. The horizontal positioning error and the altitude error are 10.8 m and 0.5 m in the urban area and 45.9 m and 3.6 m in the mountainous area. The experimental results illustrate that the developed SINS/1D LDV integrated navigation system is viable to provide highly accurate altitude as well as horizontal parameters in practical application.

Calibration of a three-dimensional laser Doppler velocimeter in a land integrated navigation system.

In the land navigation field, a laser Doppler velocimeter (LDV), which is able to measure the speed of a carrier, can be combined with a strapdown inertial navigation system (SINS) to form an integrated navigation system. To realize the integrated navigation positioning of a free motion carrier on the ground accurately, this paper introduces a split-reuse three-dimensional (3D) LDV. For the error parameters during application, a Kalman filtering calibration method with the assistance of a differential global positioning system (DGPS) is put forward in this paper. Two groups of integrated navigation experiments are designed to validate the effectiveness of this method and the universality of the obtained parameters. The experimental results show that the calibration method proposed in this paper is effective and the 3D LDV after compensation can greatly improve the positioning accuracy of the integrated navigation. The maximum horizontal position errors of the two experiments calculated by the dead reckoning of the 3D LDV and the gyroscopes are 4.2 m and 2.9 m, and the maximum altitude errors are 0.8 m and 0.9 m, respectively.

Two-dimensional laser Doppler velocimeter and its integrated navigation with a strapdown inertial navigation system.

In the field of land navigation, a laser Doppler velocimeter (LDV) can be used to provide the velocity of a vehicle for an integrated navigation system with a strapdown inertial navigation system. In order to suppress the influence of vehicle jolts on a one-dimensional (1D) LDV, this paper designs a split-reuse two-dimensional (2D) LDV. The velocimeter is made up of two 1D velocimeter probes that are mirror-mounted. By the different effects of the vertical vibration on the two probes, the velocimeter can calculate the forward velocity and the vertical velocity of a vehicle. The results of the vehicle-integrated navigation experiments show that the 2D LDV not only can actually suppress the influence of vehicle jolts and greatly improve the navigation positioning accuracy, but also can give high-precision altitude information. The maximum horizontal position errors of the two experiments are 2.6 m and 3.2 m in 1.9 h, and the maximum altitude errors are 0.24 m and 0.22 m, respectively.