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.

Unraveling the Role of Metal Vacancy Sites and Doped Nitrogen in Enhancing Pseudocapacitance Performance of Defective MXene.

Nitrogen-doped titanium carbides (MXene) films exhibit extraordinary volumetric capacitance when high-concentration sulfuric acid electrolyte is utilized owing to the enhancement of pseudocapacitance. However, the energy storage mechanism of nitrogen-doped MXene is unclear due to the complex electrode structure and electrolyte ions' behavior. Here, based on pristine MXene (Ti3C2O2), three different MXene structures are constructed by introducing metal vacancy sites and doped nitrogen atoms, namely, defective MXene (Ti2.9C2O2), nitrogen-doped MXene (Ti3C2O1.9N0.1), and nitrogen-doped MXene with metal vacancy sites (Ti2.9C2O1.9N0.1). Then, the density functional theory (DFT)-based calculations coupled with the effective screening medium reference interaction site method (ESM-RISM) are applied to reveal the electrochemical behavior at the electrode/electrolyte interfacial area. Through analyzing the electronic structure, electrical double-layer capacitance (EDLC), and equilibrium potential of the pseudocapacitance reaction, the specific effect of structural changes on their performance can be clarified: metal vacancy sites can reduce the potential difference of gap layer (Outer Helmholtz plane) at charged state and increase the electronic capacity of Ti, which can be used to explain the high pseudocapacitance, low charge transfer resistance and high-rate capacity properties of nitrogen-doped MXene observed in experiments.

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.

Altered Effective Connectivity of the Pain Matrix in Herpes Zoster and Postherpetic Neuralgia Patients: Granger Causality Analysis of Resting-State fMRI.

BACKGROUND: Shingles can cause long-term pain and negative emotions, along with changes in brain function. In this study, Granger Causality Analysis (GCA) was used to compare herpes zoster (HZ) and postherpetic neuralgia (PHN) differences in effective connections within the "pain matrix" between patients and healthy controls to further understand patterns of interaction between brain regions and explore the relationship between changes in effective connections and clinical features. METHODS: Resting-state functional magnetic resonance imaging (fMRI) scans were performed on 55 HZ; 55 PHN; and 50 age-, sex- matched healthy controls (HCs). The brain regions associated with the pain matrix are used as the seeds of effective connectivity. GCA was used to analyze effective connections in brain regions that differed significantly between groups. Then the correlation between GCA values and clinical indicators was studied. RESULTS: Compared with HC, GCA values between the thalamus and the amygdala, between the thalamus and the precentral gyrus, from the thalamus to the postcentral gyrus, and from the parahippocampal gyrus to the amygdala, anterior cingulate gyrus were significantly reduced in HZ patients. Compared with HC, GCA values between the insular and the postcentral gyrus, from the insular to the inferior parietal lobe, and from the postcentral gyrus to the amygdala were significantly reduced in PHN patients. Compared with HZ, GCA values between the inferior parietal lobe and the parahippocampal gyrus, between the inferior parietal lobe and the anterior cingulate gyrus, and from the anterior cingulate gyrus to the amygdala were significantly increased in PHN patients. The visual analogue scale (VAS) score of PHN patients was positively correlated with the GCA value from the central posterior lobe to the insula. CONCLUSIONS: PHN and HZ patients showed a broad reduction in effective connections, mainly reflected in abnormal pain pathway regulation, pain perception, negative emotion and memory production, providing new perspectives to understand the neuroimaging mechanisms of shingles.

Identification of cuproptosis-related lncRNAs to predict prognosis and immune infiltration characteristics in alimentary tract malignancies.

BACKGROUND: Alimentary tract malignancies (ATM) caused nearly one-third of all tumor-related death. Cuproptosis is a newly identified cell death pattern. The role of cuproptosis-associated lncRNAs in ATM is unknown. METHOD: Data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to identify prognostic lncRNAs by Cox regression and LASSO. Then a predictive nomogram was constructed based on seven prognostic lncRNAs. In addition, the prognostic potential of the seven-lncRNA signature was verified via survival analysis, the receiver operating characteristic (ROC) curve, calibration curve, and clinicopathologic characteristics correlation analysis. Furthermore, we explored the associations between the signature risk score and immune landscape, and somatic gene mutation. RESULTS: We identified 1211 cuproptosis-related lncRNAs and seven survival-related lncRNAs. Patients were categorized into high-risk and low-risk groups with significantly different prognoses. ROC and calibration curve confirmed the good prediction capability of the risk model and nomogram. Somatic mutations between the two groups were compared. We also found that patients in the two groups responded differently to immune checkpoint inhibitors and immunotherapy. CONCLUSION: The proposed novel seven lncRNAs nomogram could predict prognosis and guide treatment of ATM. Further research was required to validate the nomogram.

A Novel Nomogram for Identifying Candidates for Adjuvant Chemotherapy in Patients With Stage IB Non-small Cell Lung Cancer.

BACKGROUND: This study aimed to develop a novel predictive nomogram to identify specific stage IB non-small cell lung cancer (NSCLC) populations who could benefit from adjuvant chemotherapy (ACT). METHOD: Stage IB NSCLC patients were included in the Surveillance, Epidemiology, and End Results (SEER) database and divided into the ACT and non-ACT groups. Then the methods of Kaplan-Meier analysis, propensity score matching (PSM), Least absolute shrink and selection operator (LASSO) regression, and multivariate logistic regression analyses were implemented. Finally, the predictive nomogram was constructed and validated. RESULTS: 9055 stage IB NSCLC patients were enrolled from the SEER database while 47 patients from Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University were identified as the external validation cohort. Of these patients, 1334 cases underwent ACT while the other 7721 patients didn't receive ACT. After PSM, the patients in the ACT group presented longer median overall survival (100 vs 82 months, P < .001). Among the ACT group, 482 (49.6%) patients achieving more prolonged overall survival than 82 months were regarded as the beneficiary population. Then the LASSO regression and multivariate logistic regression analyses were implemented. Finally, 8 predictors were selected for model construction, including age, gender, marital status, laterality, pathology, tumor size, regional nodes examined, and tumor size. The predictive nomogram demonstrated good discrimination in the training cohort (AUC = .781), internal validation cohort (AUC = .772), and external validation cohort (AUC = .851). And calibration curves indicated ideal consistency between the predicted and observed probabilities. Decision curve analysis presented a clinically useful model. CONCLUSION: The practical nomogram could guide treatment decision-making and select optimal ACT candidates among stage IB NSCLC patients.

A novel nomogram and risk stratification system predicting the cancer-specific survival of patients with gastric neuroendocrine carcinoma: a study based on SEER database and external validation.

BACKGROUND: Gastric neuroendocrine carcinoma (GNEC) is a rare histology of gastric cancer. The retrospective study was designed to construct and validate a nomogram for predicting the cancer-specific survival (CSS) of postoperative GNEC patients. METHODS: Data for 28 patients from the Hangzhou TCM Hospital were identified as the external validation cohort. A total of 1493 patients were included in the SEER database and randomly assigned to the training group (1045 patients) and internal validation group (448 patients). The nomogram was constructed using the findings of univariate and multivariate Cox regression studies. The model was evaluated by consistency index (C-index), calibration plots, and clinical net benefit. Finally, the effect between the nomogram and AJCC staging system was compared by net reclassification index (NRI) and integrated discrimination improvement (IDI). RESULTS: Age, gender, grade, T stage, N stage, metastasis, primary site, tumor size, RNE, and chemotherapy were incorporated in the nomogram. The C-indexes were 0.792 and 0.782 in the training and internal verification sets. The 1-, 3-, and 5-year CSS predicted by the nomogram and actual measurements had good agreement in calibration plots. The 1-, 3-, and 5-year NRI were 0.21, 0.29, and 0.37, respectively. The 1-, 3-, and 5-year IDI values were 0.10, 0.12, and 0.13 (P < 0.001), respectively. In 1-, 3-, and 5-year CSS prediction using DCA curves, the nomogram outperformed the AJCC staging system. The nomogram performed well in both the internal and external validation cohorts. CONCLUSION: We developed and validated a nomogram to predict 1-, 3-, and 5-year CSS for GNEC patients after surgical resection. This well-performing model could help doctors enhance the treatment plan.

A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma.

BACKGROUND: The purpose of this research was to construct a novel predictive nomogram to identify specific stage IB gastric adenocarcinoma (GAC) populations who could benefit from postoperative adjuvant chemotherapy (ACT). METHOD: Between 2004 and 2015, 1889 stage IB GAC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) program database. Then Kaplan-Meier survival analysis, univariate and multivariable Cox analyses, and univariate and multivariable logistic analyses were implemented. Finally, the predictive nomograms were constructed. The methods of area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to validate the clinical effectiveness of the models. RESULTS: Of these patients, 708 cases underwent ACT, while the other 1181 patients didn't receive ACT. After PSM, the patients in the ACT group presented a longer median overall survival (133 vs. 85 months, p = 0.0087). Among the ACT group, 194 (36.0%) patients achieving more prolonged overall survival than 85 months were regarded as the beneficiary population. Then the logistic regression analyses were performed, and age, gender, marital status, primary site, tumor size, and regional nodes examined were included as predicting factors to construct the nomogram. The AUC value was 0.725 in the training cohort and 0.739 in the validation cohort, which demonstrated good discrimination. And calibration curves indicated ideal consistency between the predicted and observed probabilities. Decision curve analysis presented a clinically useful model. Furthermore, the prognostic nomogram predicting 1-, 3-, and 5-year cancer-specific survival presented good predictive ability. CONCLUSION: The benefit nomogram could guide clinicians in decision-making and selecting optimal candidates for ACT among stage IB GAC patients. And the prognostic nomogram presented great prediction ability for these patients.

De-escalating chemotherapy for stage I-II gastric neuroendocrine carcinoma? A real-world competing risk analysis.

BACKGROUND: The role of adjuvant chemotherapy in gastric neuroendocrine neoplasms (GNEC) has not been well clarified yet. The study was designed to investigate the potential effect of adjuvant chemotherapy in stage I-II GNEC patients and construct a predictive nomogram. METHOD: Stage I-II GNEC patients were included in the Surveillance, Epidemiology, and End Results (SEER) database and divided into chemotherapy and no-chemotherapy groups. We used Kaplan-Meier survival analyses, propensity score matching (PSM), and competing risk analyses. The predictive nomogram was then built and validated. RESULTS: Four hundred four patients with stage I-II GNEC were enrolled from the SEER database while 28 patients from Hangzhou TCM Hospital were identified as the external validation cohort. After PSM, similar 5-year cancer-specific survival was observed in two groups. The outcomes of competing risk analysis indicated a similar 5-year cumulative incidence of cancer-specific death (CSD) between the two cohorts (35.4% vs. 31.4%, p = 0.731). And there was no significant relation between chemotherapy and CSD in the multivariate competing risks regression analysis (HR, 0.79; 95% CI, 0.48-1.31; p = 0.36). Furthermore, based on the variables from the multivariate analysis, a competing event nomogram was created to assess the 1-, 3-, and 5-year risks of CSD. The 1-, 3-, and 5-year area under the receiver operating characteristic curve (AUC) values were 0.770, 0.759, and 0.671 in the training cohort, 0.809, 0.782, and 0.735 in the internal validation cohort, 0.786, 0.856, and 0.770 in the external validation cohort. Furthermore, calibration curves revealed that the expected and actual probabilities of CSD were relatively consistent. CONCLUSION: Stage I-II GNEC patients could not benefit from adjuvant chemotherapy after surgery. De-escalation of chemotherapy should be considered for stage I-II GNEC patients. The proposed nomogram exhibited excellent prediction ability.

Direction-of-Arrival Estimation Method Based on Neural Network with Temporal Structure for Underwater Acoustic Vector Sensor Array.

Acoustic vector sensor (AVS) is a kind of sensor widely used in underwater detection. Traditional methods use the covariance matrix of the received signal to estimate the direction-of-arrival (DOA), which not only loses the timing structure of the signal but also has the problem of weak anti-noise ability. Therefore, this paper proposes two DOA estimation methods for underwater AVS arrays, one based on a long short-term memory network and attention mechanism (LSTM-ATT), and the other based on Transformer. These two methods can capture the contextual information of sequence signals and extract features with important semantic information. The simulation results show that the two proposed methods perform much better than the multiple signal classification (MUSIC) method, especially in the case of low signal-to-noise ratio (SNR), the DOA estimation accuracy has been greatly improved. The accuracy of the DOA estimation method based on Transformer is comparable to that of the DOA estimation method based on LSTM-ATT, but the computational efficiency is obviously better than that of the DOA estimation method based on LSTM-ATT. Therefore, the DOA estimation method based on Transformer proposed in this paper can provide a reference for fast and effective DOA estimation under low SNR.

Prognostic signatures and potential pathogenesis of eRNAs-related genes in colon adenocarcinoma.

Enhancer RNAs (eRNAs) are a subclass of long noncoding RNAs (lncRNAs) that have a wide effect in human tumors. However, the systematic analysis of potential functions of eRNAs-related genes (eRGs) in colon cancer (CC) remains unexplored. In this study, a total of 8231 eRGs including 6236 protein-coding genes and 1995 lncRNAs were identified in CC based on the multiple resources. These eRGs showed higher expression level and stability compared to other genes. What's more, the functions of these eRGs were closely related to cancer. Then a prognostic prediction model with 12 eRGs signatures were obtained for colon adenocarcinoma (COAD) patients. ROC curves showed the AUCs were 0.81, 0.77, and 0.78 for 1-, 3-, and 5-year survival prediction, respectively. And the prognostic model also manifested good performance in the validation datasets. Besides, the expression levels of two prognostic signatures, TMEM220 and LRRN2, were verified to be significantly lower in CC tissues than in adjacent noncancerous tissues (p < .05). Finally, the distinct molecular features were characterized between the high- and low-risk group through multiomics analysis including DNA mutation and methylation. Our results show eRGs signatures based prognostic model has high accuracy and may provide innovative biomarkers in COAD.

The formation of stipule requires the coordinated actions of the legume orthologs of Arabidopsis BLADE-ON-PETIOLE and LEAFY.

Stipule morphology is a classical botanical key character used in plant identification. Stipules are considerably diverse in size, function and architecture, such as leaf-like stipules, spines or tendrils. However, the molecular mechanism that regulates stipule identity remains largely unknown. We isolated mutants with abnormal stipules. The mutated gene encodes the NODULE ROOT1 (MtNOOT1), which is the ortholog of BLADE-ON-PETIOLE (BOP) in Medicago truncatula. We also obtained mutants of MtNOOT2, the homolog of MtNOOT1, but they do not show obvious defects in stipules. The mtnoot1 mtnoot2 double mutant shows a higher proportion of transformation from stipules to leaflet-like stipules than the single mutants, suggesting that they redundantly determine stipule identity. Further investigations show that MtNOOTs control stipule initiation together with SINGLE LEAFLET1 (SGL1), which functions in development of lateral leaflets. Increasing SGL1 activity in mtnoot1 mtnoot2 is sufficient for the transformation of stipules to leaves. Moreover, MtNOOTs inhibit SGL1 expression during stipule development, which is probably conserved in legume species. Our study proposes a genetic regulatory model for stipule development, specifically with regard to the MtNOOTs-SGL1 module, which functions in two phases of stipule development, first in the control of stipule initiation and second in stipule patterning.

LATE MERISTEM IDENTITY1 regulates leaf margin development via the auxin transporter gene SMOOTH LEAF MARGIN1.

Plant leaves have evolved into diverse shapes and LATE MERISTEM IDENTITY1 (LMI1) and its putative paralogous genes encode homeodomain leucine zipper transcription factors that are proposed evolutionary hotspots for the regulation of leaf development in plants. However, the LMI1-mediated regulatory mechanism underlying leaf shape formation is largely unknown. MtLMI1a and MtLMI1b are putative orthologs of LMI1 in the model legume barrelclover (Medicago truncatula). Here, we investigated the role of MtLMI1a and MtLMI1b in leaf margin morphogenesis by characterizing loss-of-function mutants. MtLMI1a and MtLMI1b are expressed along leaf margin in a near-complementary pattern, and they redundantly promote development of leaf margin serrations, as revealed by the relatively smooth leaf margin in their double mutants. Moreover, MtLMI1s directly activate expression of SMOOTH LEAF MARGIN1 (SLM1), which encodes an auxin efflux carrier, thereby regulating auxin distribution along the leaf margin. Further analysis indicates that MtLMI1s genetically interact with NO APICAL MERISTEM (MtNAM) and the ARGONAUTE7 (MtAGO7)-mediated trans-acting short interfering RNA3 (TAS3 ta-siRNA) pathway to develop the final leaf margin shape. The participation of MtLMI1s in auxin-dependent leaf margin formation is interesting in the context of functional conservation. Furthermore, the diverse expression patterns of LMI1s and their putative paralogs within key domains are important drivers for functional specialization, despite their functional equivalency among species.

Is lobectomy superior to sub-lobectomy in non-small cell lung cancer with pleural invasion? A population-based competing risk analysis.

BACKGROUND: Pleural invasion (PL) has been regarded as an unfavorable prognostic factor for non-small cell lung cancer (NSCLC). But there was no agreement on the optimal surgical extent in NSCLC patients with PL. We aimed to compare the survival outcomes of lobectomy and sub-lobectomy in these patients. METHOD: 2717 patients were included in the Surveillance, Epidemiology, and End Results (SEER) database and divided into the lobectomy and sub-lobectomy groups. The propensity score matching (PSM) and competing risk analysis were implemented. Then the predictive nomogram was constructed and validated. RESULTS: 2230 Patients received lobectomy while the other 487 patients underwent sub-lobectomy. After 1:1 PSM, the cumulative incidence of cancer-specific death (CSD) was lower in the lobectomy group compared with the sub-lobectomy group (1-year: 12% vs. 15%; 3-year: 30% vs. 37%, 5-year: 34% vs. 45%, P = 0.04). According to the subgroup analysis, the patients who underwent lobectomy suffered lower CSD in the N0-1 stage, adenocarcinoma, and PL-2 cohort (p < 0.05). And there was a significant relationship between the sub-lobectomy group and CSD in the multivariate competing risks regression analysis (HR, 1.26; 95%CI, 1.02-1.56; P = 0.034). Furthermore, a competing event nomogram was constructed to assess the 1-, 3-, and 5-year chances of CSD based on the variables from the multivariate analysis. The 1-, 3-, 5-year area under the receiver operating characteristic curve (AUC) values were 0.720, 0.706, and 0.708 in the training cohort, and 0.738, 0.696, 0.680 in the validation cohorts, respectively. And calibration curves demonstrated ideal consistency between the predicted and observed probabilities of CSD. CONCLUSION: Lobectomy should be considered the preferred surgery compared to sub-lobectomy for NSCLC patients with PL. The proposed nomograms presented great prediction ability for these patients.

The role of chemotherapy in patients with stage IB gastric adenocarcinoma: a real-world competing risk analysis.

BACKGROUND: This study aimed to investigate the potential effect of adjuvant chemotherapy in patients diagnosed with stage IB gastric adenocarcinoma (GAC). METHOD: A total of 1727 patients were included in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 and divided into the chemotherapy and no-chemotherapy groups. Then, the methods of Kaplan-Meier analysis, propensity score matching (PSM), and competing risk analysis were implemented. RESULTS: After PSM, no significant difference was found in the chemotherapy and no-chemotherapy groups in overall survival (OS) (p=0.4) and cancer-specific survival (CSS) (p=0.12) in survival curves. The competing risk analysis presented that the 5-year cumulative incidence of cancer-specific death (CSD) was significantly lower in patients receiving chemotherapy (11.5% vs. 20.8%, p=0.007), while no significant discrepancy was observed in other causes of death (OCD) in both groups (10.6% vs. 10.9%, p=0.474). Multivariable competing risks regression models presented a significant correlation between chemotherapy and CSD (HR, 0.51; 95%CI, 0.31-0.82; p=0.007). CONCLUSION: The stage IB GAC patients can benefit from adjuvant chemotherapy based on this competing risk analysis.

Different roles of E proteins in t(8;21) leukemia: E2-2 compromises the function of AETFC and negatively regulates leukemogenesis.

The AML1-ETO fusion protein, generated by the t(8;21) chromosomal translocation, is causally involved in nearly 20% of acute myeloid leukemia (AML) cases. In leukemic cells, AML1-ETO resides in and functions through a stable protein complex, AML1-ETO-containing transcription factor complex (AETFC), that contains multiple transcription (co)factors. Among these AETFC components, HEB and E2A, two members of the ubiquitously expressed E proteins, directly interact with AML1-ETO, confer new DNA-binding capacity to AETFC, and are essential for leukemogenesis. However, the third E protein, E2-2, is specifically silenced in AML1-ETO-expressing leukemic cells, suggesting E2-2 as a negative factor of leukemogenesis. Indeed, ectopic expression of E2-2 selectively inhibits the growth of AML1-ETO-expressing leukemic cells, and this inhibition requires the bHLH DNA-binding domain. RNA-seq and ChIP-seq analyses reveal that, despite some overlap, the three E proteins differentially regulate many target genes. In particular, studies show that E2-2 both redistributes AETFC to, and activates, some genes associated with dendritic cell differentiation and represses MYC target genes. In AML patients, the expression of E2-2 is relatively lower in the t(8;21) subtype, and an E2-2 target gene, THPO, is identified as a potential predictor of relapse. In a mouse model of human t(8;21) leukemia, E2-2 suppression accelerates leukemogenesis. Taken together, these results reveal that, in contrast to HEB and E2A, which facilitate AML1-ETO-mediated leukemogenesis, E2-2 compromises the function of AETFC and negatively regulates leukemogenesis. The three E proteins thus define a heterogeneity of AETFC, which improves our understanding of the precise mechanism of leukemogenesis and assists development of diagnostic/therapeutic strategies.

Effects of perfluoroalkyl substances on soil respiration and enzymatic activity: differences in carbon chain-length dependence.

Perfluoroalkyl substances (PFASs) are anthropogenic compounds that exhibit ecotoxicity when discharged into the environment, causing increasing concern. An indoor experiment was conducted to investigate the effects of perfluoroalkyl carboxylic acids (PFCAs) and PFSAs on soil respiration, sucrase activity, and urease activity at 0, 7, 14, and 28 d for perfluorooctanoic acid (PFOA), perfluorohexanoic acid (PFHxA), and perfluorobutyric acid (PFBA), and at 14 and 28 d for perfluorooctane sulfonic acid (PFOS), perfluorohexanoic sulfonic acid (PFHxS), and perfluorobutyric sulfonic acid (PFBS). PFCAs significantly inhibited soil respiration, with a significant negative correlation between respiration and PFBA (P < 0.05) at 28 d. Sucrase activities were initially inhibited by PFCAs, and then recovered. Urease activities were inhibited by PFOA at 14 d and by PFHxA at 14 and 28 d, but not by PFBA. PFOS and PFBS briefly enhanced soil respiration. PFOS inhibited sucrase activity. PFSAs significantly decreased urease activity in a concentration- and time-dependent manner. The chain-length dependence of the ecotoxicity of PFASs varied depending on concentration and time. Toxicity demonstrated a trend of initial decrease followed by increase with carbon chain length. Our results first revealed that the chain-length dependences of PFASs were also related to concentrations and exposure time.

Quantum Energy Current Induced Coherence in a Spin Chain under Non-Markovian Environments.

We investigate the time-dependent behaviour of the energy current between a quantum spin chain and its surrounding non-Markovian and finite temperature baths, together with its relationship to the coherence dynamics of the system. To be specific, both the system and the baths are assumed to be initially in thermal equilibrium at temperature Ts and Tb, respectively. This model plays a fundamental role in study of quantum system evolution towards thermal equilibrium in an open system. The non-Markovian quantum state diffusion (NMQSD) equation approach is used to calculate the dynamics of the spin chain. The effects of non-Markovianity, temperature difference and system-bath interaction strength on the energy current and the corresponding coherence in cold and warm baths are analyzed, respectively. We show that the strong non-Markovianity, weak system-bath interaction and low temperature difference will help to maintain the system coherence and correspond to a weaker energy current. Interestingly, the warm baths destroy the coherence while the cold baths help to build coherence. Furthermore, the effects of the Dzyaloshinskii-Moriya (DM) interaction and the external magnetic field on the energy current and coherence are analyzed. Both energy current and coherence will change due to the increase of the system energy induced by the DM interaction and magnetic field. Significantly, the minimal coherence corresponds to the critical magnetic field which causes the first order phase transition.