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Background: Acute myeloid leukemia (AML) and hyperleukocytosis have an unfavorable prognosis, but the impact of hyperleukocytosis on the prognosis of pediatric AML remains uncertain. We investigated the clinical characteristics and prognosis of pediatric AML with hyperleukocytosis, defined as WBC ≥ 50 × 109/L. Methods: A total of 132 patients with newly diagnosed childhood AML with hyperleukocytosis were consecutively enrolled at our center from September 2009 to August 2021 to investigate prognostic factors and clinical outcomes. Results: Hyperleukocytosis occurred in 27.4% of AML patients. Pediatric patients with hyperleukocytosis had similar CR and OS rates to those without hyperleukocytosis, but had a lower EFS rate. In our study, rates of CR1, mortality, relapsed/refractory disease, and HSCT were comparable between AML patients with WBC counts of 50–100 × 109/L and ≥ 100 × 109/L. AML patients with a WBC count of 50–100 × 109/L had a similar 5-year OS rate to patients with a WBC count ≥ 100 × 109/L (74.6% vs. 75.4%, P = 0.921). Among all patients with hyperleukocytosis, the FAB M5 subtype was associated with significantly inferior survival, and the prognosis of CBF-AML was good. Conclusions: Pediatric AML patients with hyperleukocytosis have the similar prognosis regardless of whether their WBC count is 50–100 × 109/L or ≥ 100 × 109/L. [ABSTRACT FROM AUTHOR]

Aliphatic polycarbonates (APCs) have become an essential packaging material because of their renewability, biodegradability, and biocompatibility. In this study, a series of high molecular weights APCs have been successfully synthesized using dimethyl carbonate (DMC) and different lengths of aliphatic diols with even carbon (n-CH2 = 4–12) via melt polymerization. Thermal properties, isothermal crystallization behavior, crystal structure, and scale of microstructure of APCs indicated that the flexibility and crystallization of molecular chains gradually increased with the increasing number of methylene groups of repeating units. However, due to the rigidity of ester group was higher than methylene group, and crystallization could increase the rigidity of chain segments, yielding strength and Young's modulus of APCs decreased first and then gradually increased with the increasing number of methylene groups in the repeating units. Furthermore, the scale of microstructure indicated that Brill transition increased the distance between intermolecular chains. Therefore, although the trans-gauche coexistence chain conformation simultaneously decreased the rigidity and crystallization of chain segments, barrier property of poly(octamethylene carbonate) with Brill transition was similar to long-chain APCs because of the lengthened diffusion path. The analytical mechanism of structure-performance relationship from the viewpoint of molecular interactions and chain structure will provide an entirely new thought for developing new barrier materials. [ABSTRACT FROM AUTHOR]

Despite advances in parameters back-analysis of surrounding rocks, training and testing data have to be developed for individual projects because they require different support systems and are executed under different geological conditions, resulting in a tedious back-analysis process and low efficiency. In this study, the effects of support structure on surrounding rock were simulated using the support pressure, and a general parameters back-analysis database was created to rapidly determine the parameters of tunnels with different surrounding rock conditions, of varying depths, and requiring different support systems. To achieve this, the excavations of 1000 groups of tunnels with random depths and rock parameters were calculated using such methods as numerical simulation and machine learning, and a general back-analysis database were created. In the database, in situ stress and deformation were used as the input data, and the rock parameters were regarded as the output data. Subsequently, training and testing were executed using the GA-BP neural network to generate a trained parameters back-analysis model, with its reliability being verified using 13 engineering cases. Additionally, parameters back-analysis and tunnel excavation simulations were applied to the Xinjiang Water Diversion Project and the Xiaoqian Tunnel; the errors were negligible compared with the measured displacement. The results demonstrated that the simulation of the effects of support systems on surrounding rock using the support pressure was rational, and the dimensionless deformation can eliminate the effects of differences in tunnel shape and diameter. The database can be used to determine the surrounding rock parameters of tunnels in different projects. [ABSTRACT FROM AUTHOR]

The creation of DMC-based biodegradable materials with excellent properties is a potential and sustainable option now that the industrial production of dimethyl carbonate (DMC) synthesis from carbon dioxide is commercially feasible. Herein, a series of kilogram-scale DMC-based biodegradable poly(butylene carbonate) (PBC) with distinct molecular weight gradients (number average molecular weight (Mn) varied from 23 to 67 kg/mol) were synthesized successfully through a facile melt polycondensation reaction using a 5 L stainless steel reactor. The microstructure of the polymers was confirmed by FTIR and 1H NMR. It was thoroughly discussed how molecular weight affected the physical performance of PBC, including thermal properties, rheological behaviors, mechanical characteristics, and degradation behaviors. The findings indicated that the molecular weight had significant influence on the physical characteristics of PBC. Especially, PBC with Mn greater than 46 kg/mol showed excellent mechanical strength and elongation at break with the values of 37.3 MPa and 559.1%, respectively. All the PBCs exhibited appreciable biodegradability under enzymatic degradation. In addition, as a novel and environmentally acceptable nucleating agent, magnesium mandelate (Mg(MdA)2) was introduced into PBC via melt blending. The non-isothermal behaviors and isothermal crystallization kinetics of the PBC/Mg(MdA)2 were specially forced. It was discovered that Mg(MdA)2 greatly accelerated both the non-isothermal and isothermal crystallization of PBC and exhibited a prominent nucleation activity on the crystallization of PBC. Moreover, the WAXD patterns of all the blend samples displayed the same distinctive peaks as neat PBC, proving that the structure of the PBC crystals had no modification with the addition of Mg(MdA)2. Accordingly, the current work proposed enlarged step-by-step synthesis of PBC material and physical modification which highlighted the technical feasibility of PBC industrial production and expansion of processing molding applications. [ABSTRACT FROM AUTHOR]

To reduce subjectivity and uncertainty when maintaining suitable earth pressure in earth pressure shields that can prevent heave or collapse, many prediction models using machine learning algorithms were proposed, but little research into the effects of other parameters on earth pressure has been undertaken, and soil conditioning parameters are always ignored. To establish a model with thorough parameters and probe into influences of other parameters, multiple machine learning algorithms were attempted. Given the accuracy, diversity and functions, random forest (RF), LightGBM and Attention-back-propagation neural network (Attention-BPNN) were further analyzed. Then, two RF models were compared in this research, one with soil conditioning parameters and the other without. Meanwhile, a case study was utilized to verify the reliability of the model. Finally, the feature importance of three models was compared and the variation rules of the most four important features were discussed by controlling variates. The results showed that soil conditioning parameters delivered a significant reduction in the prediction error. The case study demonstrated that the proposed model can satisfy engineering requirements. More earth pressure should give priority to increasing propulsion pressure, advance rate, and reducing foam air flow, rotational speed of screw conveyor, and vice versa. [ABSTRACT FROM AUTHOR]

Multiparameter flow cytometry (MFC)-based minimal residual disease has been a poor predictor of prognosis in children with acute myeloid leukemia (AML). This study aimed to evaluate the incremental value of serial monitoring by droplet digital PCR (ddPCR) in forecasting the outcome of AML. Twenty-four children with AML were enrolled and the relapse-free survival (RFS) rate was estimated using the Kaplan-Meier method. Survival estimates were compared using the log-rank test. Survival analysis showed that the RFS rate in the ddPCR ≥ 0.1% group was significantly lower than that in the < 0.1% group (35.7% ± 19.8% vs. 83.6% ± 10.8%, P = 0.003). Moreover, serial monitoring by ddPCR showed that some mutations remained positive in some patients even though other co-mutations were eliminated, and those patients were more prone to relapse, with a significantly poorer RFS compared to patients negative for mutation (22.0% ± 19.2% vs 83.3% ± 11.3%, P = 0.001). Consequently, ddPCR may assist in prognostic forecasting for pediatric AML. [ABSTRACT FROM AUTHOR]

Water–rock interaction is a common phenomenon in rock mass engineering. Water–rock interaction alters the mineralogical and microstructural properties of a rock mass and leads to engineering problems such as leakage, deformation, and failure of a rock mass. To investigate the local leakage in the limestone reservoir, limestone specimens were taken from the underground chamber. In this study, two test conditions were designed: with and without regular replacement of the reservoir water condition. The results indicated that the porosity increased sharply in the early stages of the soaking. But, the rate of increment dropped after 120 d (regular replacement of reservoir water condition) and 90 d (unchanged reservoir water condition), respectively. The pore in the rock was 4.50 mm deep, while the reservoir water was replaced regularly, which is 1.54 times that of the unchanged reservoir water condition (i.e., 2.50 mm), in 360 soaking days. Relatively, the renewal of reservoir water enhanced the chemical reaction. The water–rock interaction altered the mineralogical composition, spatial structure of the crystal, and pore structure of the rock. The change in the longitudinal wave velocity Vm measures the state of pore development. The porosity evolution model for limestone rock was established by considering the impact of dissolution on the spatial structure of the crystal skeleton. The model accurately predicted the variation trend of porosity in the limestone rock under water–rock interaction. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging is a non-destructive, nonpolluting, and fast technology, which can capture up to several hundred images of different wavelengths and offer relevant spectral signatures. Hyperspectral imaging technology has achieved breakthroughs in the acquisition of agricultural information and the detection of external or internal quality attributes of the agricultural product. Deep learning techniques have boosted the performance of hyperspectral image analysis. Compared with traditional machine learning, deep learning architectures exploit both spatial and spectral information of hyperspectral image analysis. To scrutinize thoroughly the current efforts, provide insights, and identify potential research directions on deep learning for hyperspectral image analysis in agriculture, this paper presents a systematic and comprehensive review. Firstly, its applications in agriculture are summarized, include ripeness and component prediction, different classification themes, and plant disease detection. Then, the recent achievements are reviewed in hyperspectral image analysis from the aspects of the deep learning models and the feature networks. Finally, the existing challenges of hyperspectral image analysis based on deep learning are summarized and the prospects of future works are put forward. [ABSTRACT FROM AUTHOR]

Variation in normal blood cells during chemotherapy has not been recognised as a risk factor guiding chemotherapy in childhood acute lymphoblastic leukaemia (ALL). This study aims to explore whether variations in normal haematopoiesis determine prognosis as well as to improve risk-stratified treatment in childhood ALL. A retrospective study of 279 cases of ALL treated with the CCCG-ALL-2015 regimen in the Division of Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, from May 2015 to January 2017 was performed to analyse the prognostic impact of blood cell levels on day 19 of induction therapy by Kaplan-Meier method. Patients with childhood ALL with absolute neutrophil count (ANC) ≤ 90 cells/μl, absolute monocyte count (AMC) ≤ 10 cells/μl or absolute lymphocyte count (ALC) ≤ 1000 cells/μl on day 19 of induction therapy had a lower event-free survival (EFS) rate than those with higher values (all P < 0.05). Multivariate analysis confirmed that ANC ≤ 90 cells/μl and ALC ≤ 1000 cells/μl were independent adverse prognostic factors (HR = 1.981 and 2.162, respectively, both P < 0.05). Among patients with minimal residual disease (MRD) < 1% on day 19 of induction therapy, those with ANC ≤ 90 cells/μl had lower EFS than those with ANC > 90 cells/μl (70.8 ± 6.1% vs 86.4 ± 3.1%, P = 0.001). In the subgroup with the BCR/ABL1 fusion gene, patients with ANC ≤ 90 cells/μl on day 19 of induction therapy also had lower EFS than those with ANC > 90 cells/μl (34.4 ± 25.2% vs 25.0 ± 21.7%, P = 0.041). ANC and ALC during induction therapy are independent prognostic factors for childhood ALL. ANC contributes to guiding the prognosis of patients with low-level MRD or the BCR/ABL1 fusion gene. [ABSTRACT FROM AUTHOR]