Myeloid leukemia-derived galectin-1 downregulates CAR expression to hinder cytotoxicity of CAR T cells.

BACKGROUND: Chimeric antigen receptor (CAR) T cells have shown significant activity in B-lineage malignancies. However, their efficacy in myeloid leukemia has not been successful due to unclear molecular mechanisms. METHODS: We conducted in vitro and in vivo experiments to investigate whether myeloid leukemia cells directly induce CAR down-regulation. Furthermore, we designed a CD33 CARKR in which all lysines in the cytoplasmic domain of CAR were mutated to arginine and verified through in vitro experiments that it could reduce the down-regulation of surface CARs and enhance the killing ability. Transcriptome sequencing was performed on various AML and ALL cell lines and primary samples, and the galectin-1-specific inhibitory peptide (anginex) successfully rescued the killing defect and T-cell activation in in vitro assays. RESULTS: CAR down-regulation induced by myeloid leukemia cells under conditions of low effector-to-tumor ratio, which in turn impairs the cytotoxicity of CAR T cells. In contrast, lysosomal degradation or actin polymerization inhibitors can effectively alleviate CAR down-regulation and restore CAR T cell-mediated anti-tumor functions. In addition, this study identified galectin-1 as a critical factor used by myeloid leukemia cells to induce CAR down-regulation, resulting in impaired T-cell activation. CONCLUSION: The discovery of the role of galectin-1 in cell surface CAR down-regulation provides important insights for developing strategies to restore anti-tumor functions.

HIF-1α is an important regulator of IL-8 expression in human bone marrow stromal cells under hypoxic microenvironment.

The secretion of IL-8 has been found increasing for different reasons in human bone marrow stromal cells (BMSCs), resulting in poor prognosis in patients with hematologic neoplasms. Hypoxia, a typical feature of numerous hematologic neoplasms microenvironment, often produces hypoxia inducible factor-1α (HIF-1α) which stabilizes and promotes tumor progression. Besides, hypoxic conditions also induce IL-8 production in BMSCs. However, very little is known about the mechanism of increased IL-8 expression in BMSCs caused by hypoxia. In the present study, HIF-1α and IL-8 were found highly expressed in BMSC lines under hypoxic conditions. In addition, the expression and secretion of IL-8 were significantly inhibited by the knockdown of HIF-1α under hypoxic conditions. Furthermore, HIF-1α was found to transcriptionally regulate IL-8 by binding to the region of IL-8 promoter at - 147 to - 140. Collectively, these results demonstrate that IL-8's increase is partly due to the hypoxic microenvironment in hematologic neoplasms, and activation of HIF-1α in BMSCs contributes to the induction and transcriptional regulation of IL-8 expression.

Secreted insulin-like growth factor binding protein 5 functions as a tumor suppressor and chemosensitizer through inhibiting insulin-like growth factor 1 receptor/protein kinase B pathway in acute myeloid leukemia.

BACKGROUND: In addition to being secreted into the intercellular spaces by exocytosis, insulin-like growth factor binding protein 5 (IGFBP5) may also remain in the cytosol or be transported to the nucleus. Depending on the different cellular context and subcellular distribution, IGFBP5 can act as a tumor suppressor or promoter through insulin-like growth factor -dependent or -independent mechanisms. Yet, little is known about the impacts of IGFBP5 on acute myeloid leukemia (AML) and its underlying mechanism. METHODS: Here we investigated the roles of IGFBP5 in human AML by using recombinant human IGFBP5 (rhIGFBP5) protein and U937 and THP1 cell lines which stably and ectopically expressed IGFBP5 or mutant IGFBP5 (mtIGFBP5) with the lack of secretory signal peptide. Cell counting kit-8 and flow cytometry assay were conducted to assess the cell viability, cell apoptosis and cell cycle distribution. Cytotoxicity assay was used to detect the chemosensitivity. Leukemia xenograft model and hematoxylin-eosin staining were performed to evaluate AML progression and extramedullary infiltration in vivo. RESULTS: In silico analysis demonstrated a positive association between IGFBP5 expression and overall survival of the AML patients. Both IGFBP5 overexpression and extrinsic rhIGFBP5 suppressed the growth of THP1 and U937 cells by inducing cell apoptosis and arresting G1/S transition and promoted the chemosensitivity of U937 and THP1 cells to daunorubicin and cytarabine. However, overexpression of mtIGFBP5 failed to demonstrate these properties. An in vivo xenograft mouse model of U937 cells also indicated that overexpression of IGFBP5 rather than mtIGFBP5 alleviated AML progression and extramedullary infiltration. Mechanistically, these biological consequences depended on the inactivation of insulin-like growth factor 1 receptor -mediated phosphatidylinositol-3-kinase/protein kinase B pathway. CONCLUSIONS: Our findings revealed secreted rather than intracellular IGFBP5 as a tumor-suppressor and chemosensitizer in AML. Upregulation of serum IGFBP5 by overexpression or addition of extrinsic rhIGFBP5 may serve as a suitable therapeutic approach for AML.

Deletion of Mettl3 in mesenchymal stem cells promotes acute myeloid leukemia resistance to chemotherapy.

Acute myeloid leukemia (AML) cell survival and chemoresistance are influenced by the existence of bone marrow mesenchymal stem cells (BMMSCs); however, the pathways by which BMMSCs contribute to these processes remain unclear. We earlier revealed that methyltransferase-like 3 (METTL3) expression is significantly reduced in AML BMMSCs and that METTL3 mediates BMMSC adipogenesis to promote chemoresistance in human AML cell lines in vitro. In this investigation, we evaluated the METTL3 function in vivo. Mice exhibiting a conditional removal of Mettl3 in BMMSCs were developed by mating Prrx1-CreERT2;Mettl3fl/+ mice with Mettl3fl/fl mice using the CRISPR-Cas9 system. The Mettl3 deletion increased bone marrow adiposity, enhanced disease progression in the transplantation-induced MLL-AF9 AML mouse model, and chemoresistance to cytarabine. The removal of Mettl3 in BMMSCs resulted in a significant increase in BMMSC adipogenesis. This effect was attributed to the downregulation of AKT1 expression, an AKT serine/threonine kinase 1, in an m6A-dependent manner. The development of chemoresistance in AML is linked to the promoted adipogenesis of BMMSCs. We conclude that METTL3 expression in BMMSCs has a critical function in limiting AML progression and chemoresistance, providing a basis for the progression of therapeutic approaches for AML.

Cystatin C and eGFRCKD-EPI-CysC: novel biomarkers for renal impairment diagnosis and two-year progression-free survival in multiple myeloma.

To evaluate cystatin C (CysC) and estimation of glomerular filtration rate (GFR) calculated using the formula, CKD-EPI-CysC (eGFRCKD-EPI-CysC) for renal impairment diagnosis and predicting the prognosis of patients with multiple myeloma (MM). One hundred-fourteen patients with MM and 38 healthy individuals were recruited for the study. Data on clinical characteristics and renal function-related biochemical indicators were collected and analyzed. Patients with MM had increased levels of CysC (1.25 (0.97-2.31) vs. 0.84 (0.80-0.92), respectively, p < 0.001) and decreased levels of eGFRCKD-EPI-CysC (53.0 (24.4-81.1) vs. 97.2 (87.0-104.5), respectively, p < 0.001), compared with healthy individuals. There were significantly more patients with elevated CysC levels than with elevated sCr levels (64.9% vs. 41.2%, respectively, p < 0.001). The CKD-EPI-CysC formula detected more patients with eGFR < 60 ml/(min × 1.73 m2) than the CKD-EPI-sCr formula (52.63% vs. 37.72%, respectively, p < 0.001). Correlation analysis found that only CysC, eGFRCKD-EPI-CysC, and eGFRCKD-EPI-sCr-CysC strongly correlated with ß2-microglobulin in group ISS-I. Logistic regression analysis was used to screen CysC (OR = 1.495, 95% CI = 1.097-2.038, p = 0.011) and eGFRCKD-EPI-CysC (OR = 0.980, 95% CI = 0.967-0.993, p = 0.003) as independent prognostic indicators for 2-year-progression-free survival (PFS) of patients with MM. Receiver operating characteristic curve analysis found that CysC values >1.70 mg/L had 67.6% sensitivity and 65.2% specificity and eGFRCKD-EPI-CysC values <38.62 ml/(min × 1.73 m2) had 65.2% sensitivity and 67.6% specificity for 2-year PFS of patients with MM. In summary, CysC and eGFRCKD-EPI-CysC were more sensitive than sCr and eGFRCKD-EPI-sCr for predicting renal impairment in patients newly diagnosed with MM. Increased CysC and decreased eGFRCKD-EPI-CysC levels were effective predictors of 2-year PFS of patients with MM.

Aquilaria sinensis leaf tea affects the immune system and increases sleep in zebrafish.

The importance of adequate sleep for good health cannot be overstated. Excessive light exposure at night disrupts sleep, therefore, it is important to find more healthy drinks that can promote sleep under sleep-disturbed conditions. The present study investigated the use of A. sinensis (Lour.) Spreng leaf tea, a natural product, to reduce the adverse effects of nighttime light on sleep. Here, Aquilaria sinensis leaf tea at 1.0 and 1.5 g/L significantly increased sleep time in zebrafish larvae (5-7 dpf) with light-induced sleep disturbance. Transcriptome sequencing and qRT-PCR analysis revealed a decrease in the immune-related genes, such as nfkbiab, tnfrsf1a, nfkbiaa, il1b, traf3, and cd40 in the 1.5 g/L Aquilaria sinensis leaf tea treatment group. In addition, a gene associated with sleep, bhlhe41, showed a significant decrease. Moreover, Aquilaria sinensis leaf tea suppressed the increase in neutrophils of Tg(mpo:GFP) zebrafish under sleep-disturbed conditions, indicating its ability to improve the immune response. Widely targeted metabolic profiling of the Aquilaria sinensis tea using ultra-performance liquid chromatography coupled with electrospray tandem mass spectrometry (UPLC-ESI-MS/MS) revealed flavonoids as the predominant component. Network pharmacological and molecular docking analyses suggested that the flavonoids quercetin and eupatilin in Aquilaria sinensis leaf tea improved the sleep of zebrafish by interacting with il1b and cd40 genes under light exposure at night. Therefore, the results of the study provide evidence supporting the notion that Aquilaria sinensis leaf tea has a positive impact on sleep patterns in zebrafish subjected to disrupted sleep due to nighttime light exposure. This suggests that the utilization of Aquilaria sinensis leaf tea as a potential therapeutic intervention for sleep disturbances induced by light may yield advantageous outcomes.

Feasibility evaluation of hsa_circ_0005480 as an auxiliary diagnostic and prognostic indicator for gastric cancer.

Aim: To explore the potential role of hsa_circ_0005480 as a marker for gastric cancer (GC). Methods: GSE83521, GSE93541 and GSE131414 were combined to screen the most potential circRNAs in GC. The expression of hsa_circ_0005480 was verified in clinical plasma samples and its diagnostic performance was evaluated by receiver operating characteristic (ROC) curve. Results: Hsa_circ_0005480 was upregulated in newly diagnosed GC patients, and performed well in distinguishing GC patients from healthy donors. Combination of hsa_circ_0005480 with traditional laboratory metrics showed increased sensitivity and accuracy than standalone application. In addition, hsa_circ_0005480 expression was low in GC patients treated with chemoradiotherapy or surgery, and decreased dynamically about 1 week postoperatively. Conclusion: Hsa_circ_0005480 may prove to be a marker for auxiliary diagnosis and prognostic evaluation of GC.

Interleukin-6 Facilitates Acute Myeloid Leukemia Chemoresistance via Mitofusin 1-Mediated Mitochondrial Fusion.

Acute myeloid leukemia (AML), an aggressive hematopoietic malignancy, exhibits poor prognosis and a high recurrence rate largely because of primary and secondary drug resistance. Elevated serum IL6 levels have been observed in patients with AML and are associated with chemoresistance. Chemoresistant AML cells are highly dependent on oxidative phosphorylation (OXPHOS), and mitochondrial network remodeling is essential for mitochondrial function. However, IL6-mediated regulation of mitochondrial remodeling and its effectiveness as a therapeutic target remain unclear. We aimed to determine the mechanisms through which IL6 facilitates the development of chemoresistance in AML cells. IL6 upregulated mitofusin 1 (MFN1)-mediated mitochondrial fusion, promoted OXPHOS, and induced chemoresistance in AML cells. MFN1 knockdown impaired the effects of IL6 on mitochondrial function and chemoresistance in AML cells. In an MLL::AF9 fusion gene-induced AML mouse model, IL6 reduced chemosensitivity to cytarabine (Ara-C), a commonly used antileukemia drug, accompanied by increased MFN1 expression, mitochondrial fusion, and OXPHOS status. In contrast, anti-IL6 antibodies downregulated MFN1 expression, suppressed mitochondrial fusion and OXPHOS, enhanced the curative effects of Ara-C, and prolonged overall survival. In conclusion, IL6 upregulated MFN1-mediated mitochondrial fusion in AML, which facilitated mitochondrial respiration, in turn, inducing chemoresistance. Thus, targeting IL6 may have therapeutic implications in overcoming IL6-mediated chemoresistance in AML. IMPLICATIONS: IL6 treatment induces MFN1-mediated mitochondrial fusion, promotes OXPHOS, and confers chemoresistance in AML cells. Targeting IL6 regulation in mitochondria is a promising therapeutic strategy to enhance the chemosensitivity of AML.

A Siamese Network With Node Convolution for Individualized Predictions Based on Connectivity Maps Extracted From Resting-State fMRI Data.

Deep learning has demonstrated great potential for objective diagnosis of neuropsychiatric disorders based on neuroimaging data, which includes the promising resting-state functional magnetic resonance imaging (RS-fMRI). However, the insufficient sample size has long been a bottleneck for deep model training for the purpose. In this study, we proposed a Siamese network with node convolution (SNNC) for individualized predictions based on RS-fMRI data. With the involvement of Siamese network, which uses sample pair (rather than a single sample) as input, the problem of insufficient sample size can largely be alleviated. To adapt to connectivity maps extracted from RS-fMRI data, we applied node convolution to each of the two branches of the Siamese network. For regression purposes, we replaced the contrastive loss in classic Siamese network with the mean square error loss and thus enabled Siamese network to quantitatively predict label differences. The label of a test sample can be predicted based on any of the training samples, by adding the label of the training sample to the predicted label difference between them. The final prediction for a test sample in this study was made by averaging the predictions based on each of the training samples. The performance of the proposed SNNC was evaluated with age and IQ predictions based on a public dataset (Cam-CAN). The results indicated that SNNC can make effective predictions even with a sample size of as small as 40, and SNNC achieved state-of-the-art accuracy among a variety of deep models and standard machine learning approaches.

Model-based reinforcement learning with non-Gaussian environment dynamics and its application to portfolio optimization.

The rapid development of quantitative portfolio optimization in financial engineering has produced promising results in AI-based algorithmic trading strategies. However, the complexity of financial markets poses challenges for comprehensive simulation due to various factors, such as abrupt transitions, unpredictable hidden causal factors, and heavy tail properties. This paper aims to address these challenges by employing heavy-tailed preserving normalizing flows to simulate the high-dimensional joint probability of the complex trading environment under a model-based reinforcement learning framework. Through experiments with various stocks from three financial markets (Dow, NASDAQ, and S&P), we demonstrate that Dow outperforms the other two based on multiple evaluation metrics in our testing system. Notably, our proposed method mitigates the impact of unpredictable financial market crises during the COVID-19 pandemic, resulting in a lower maximum drawdown. Additionally, we explore the explanation of our reinforcement learning algorithm, employing the pattern causality method to study interactive relationships among stocks, analyzing dynamics of training for loss functions to ensure convergence, visualizing high-dimensional state transition data with t-SNE to uncover effective patterns for portfolio optimization, and utilizing eigenvalue analysis to study convergence properties of the environment's model.

Red Blood Cell Distribution Width as a Potential Valuable Survival Predictor in Hepatitis B Virus-related Hepatocellular Carcinoma.

Objectives: Red blood cell distribution width (RDW) is a widely used clinical parameter recently deployed in predicting various cancers. This study aimed to evaluate the prognostic value of RDW in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Methods: We conducted a retrospective study of 745 patients with HBV-related HCC, 253 patients with chronic hepatitis B (CHB), and 256 healthy individuals to compare their hematological parameters and analyze their RDW levels. Potential risk factors for long-term all-cause mortality in patients with HBV-related HCC were predicted using Multivariate Cox regression. A nomogram was generated, and its performance was evaluated. Results: The RDW of patients with HBV-related HCC was significantly higher than that of those with CHB and healthy controls. In the former, splenomegaly, liver cirrhosis, larger tumor diameter, multiple tumor number, portal vein tumor thrombus, and lymphatic or distant metastasis were significantly increased, and the later the Child-Pugh grade and Barcelona clinic liver cancer stage, the higher the RDW. Furthermore, multivariate Cox regression analysis identified RDW as an independent risk factor for predicting long-term all-cause mortality in patients with HBV-related HCC. Finally, we successfully generated a nomogram incorporating RDW and validated its predictive ability. Conclusions: RDW is a potentially valuable hematological marker for predicting the survival and prognosis of patients with HBV-related HCC. The nomogram incorporating RDW can be used as an effective tool to plan the individualized treatment of such patients.

Downregulation of ITGA5 inhibits lymphangiogenesis and cell migration and invasion in male laryngeal squamous cell carcinoma.

ITGA5, a fibronectin receptor was highly expressed in laryngeal squamous cell carcinoma (LSCC) samples and was related to poor survival. However, the potential mechanism remains unclear. To elucidate the regulatory role of ITGA5 in LSCC progression, we investigated the effect of ITGA5 expression on lymphangiogenesis, migration, and invasion of LSCC cells in vitro and in vivo using immunohistochemistry, siRNA transfection, qRT-PCR, western blotting, enzyme-linked immunosorbent assay, flow cytometry, transwell co-culture, tube formation, cell migration, and invasion assays, and a subcutaneous graft tumor model. The expression of ITGA5 was higher in the LSCC tissues and linked to lymph node metastasis and T staging. Moreover, ITGA5 expression was significantly positively correlated with VEGF-C expression, and the lymphatic vessel density of patients with high ITGA5 expression was noticeably higher than that of patients with low ITGA5 expression. Additionally, it was found in vitro that downregulation of ITGA5 expression not only inhibited the expression and secretion of VEGF-C, but also suppressed the tube-forming ability of human lymphatic endothelial cells (HLECs) and the migration and invasion ability of LSCC cells, while exogenous VEGF-C supplementation reversed these phenomena. Furthermore, a tumor xenograft assay showed that si-ITGA5 restrained the growth and metastasis of TU212-derived tumors in vivo. Our findings suggested that ITGA5 induces lymphangiogenesis and LSCC cell migration and invasion by enhancing VEGF-C expression and secretion.

The impact of the COVID-19 pandemic on nosocomial infections: a retrospective analysis in a tertiary maternal and child healthcare hospital.

Objective: The constant changes in the control strategies of the Corona Virus Disease 2019 (COVID-19) pandemic have greatly affected the prevention and control of nosocomial infections (NIs). This study assessed the impact of these control strategies on the surveillance of NIs in a regional maternity hospital during the COVID-19 pandemic. Methods: This retrospective study compared the observation indicators of nosocomial infections and their changing trends in the hospital before and during the COVID-19 pandemic. Results: In total, 2,56,092 patients were admitted to the hospital during the study. During the COVID-19 pandemic, the main drug-resistant bacteria in hospitals were Escherichia coli, Streptococcus agalactiae, Staphylococcus aureus, Klebsiella pneumoniae, and Enterococcus faecalis. The detection rate of S. agalactiae increased annually, while that of E. faecalis remained the same. The detection rate of multidrug-resistant bacteria decreased during the pandemic (16.86 vs. 11.42%), especially that of CRKP (carbapenem-resistant Klebsiella pneumoniae 13.14 vs. 4.39, P < 0.001). The incidence of nosocomial infections in the pediatric surgery department decreased significantly (OR: 2.031, 95% CI: 1.405-2.934, P < 0.001). Regarding the source of infection, a significant reduction was observed in respiratory infections, followed by gastrointestinal infections. In the routine monitoring of the ICU, the incidence of central line-associated bloodstream infection (CLABSI) decreased significantly (9.4/1,000 catheter days vs. 2.2/1,000 catheter days, P < 0.001). Conclusion: The incidence of nosocomial infections was lower than that before the COVID-19 pandemic. The prevention and control measures for the COVID-19 pandemic have reduced the number of nosocomial infections, especially respiratory, gastrointestinal, and catheter-related infections.

Domain Adaptation via Low Rank and Class Discriminative Representation for Autism Spectrum Disorder identification: A Multi-site fMRI Study.

To construct a more effective model with good generalization performance for inter-site autism spectrum disorder (ASD) diagnosis, domain adaptation based ASD diagnostic models are proposed to alleviate the inter-site heterogeneity. However, most existing methods only reduce the marginal distribution difference without considering class discriminative information, and are difficult to achieve satisfactory results. In this paper, we propose a low rank and class discriminative representation (LRCDR) based multi-source unsupervised domain adaptation method to reduce the marginal and conditional distribution differences synchronously for improving ASD identification. Specifically, LRCDR adopts low rank representation to alleviate the marginal distribution difference between domains by aligning the global structure of the projected multi-site data. To reduce the conditional distribution difference of data from all sites, LRCDR learns the class discriminative representation of data from multiple source domains and the target domain to enhance the intra-class compactness and inter-class separability of the projected data. For inter-site prediction on all ABIDE data (1102 subjects from 17 sites), LRCDR obtains the mean accuracy of 73.1%, superior to the results of the compared state-of-the-art domain adaptation methods and multi-site ASD identification methods. In addition, we locate some meaningful biomarkers: Most of the top important biomarkers are inter-network resting-state functional connectivities (RSFCs). The proposed LRCDR method can effectively improve the identification of ASD, which has great potential as a clinical diagnostic tool.

Survival outcomes and the prognostic significance of clinicopathological features in patients with endometrial clear cell carcinoma: a 35-year single-center retrospective study.

BACKGROUND: To evaluate the oncological outcomes and the impact of clinicopathological factors on endometrial clear cell carcinoma (ECCC) outcomes. METHODS: Medical records of patients with primary ECCC treated at our center between 1985 and December 2020 were reviewed. Overall survival (OS) and progression-free survival (PFS) were the endpoints. The Kaplan-Meier method and Cox regression analysis were used. RESULTS: In total, 156 patients were included, of whom 59% and 41% had early- and advanced-stage ECCC, respectively. The median age of onset was 61 years, and 80.8% of the patients were postmenopausal. Ninety-two (59%) and 64 (41%) patients had pure ECCC and mixed endometrial carcinoma with clear cell carcinoma (CCC) components, respectively. Mixed pathological components, elevated cancer antigen 125 levels, positive lymphovascular space invasion, deep myometrial invasion, and malignant peritoneal washing cytology (PWC) were more frequently observed in the advanced stage. Thirty-nine patients (25%) experienced relapse and 32 patients (20.5%) died. The 5-year PFS and OS rates for the entire cohort were 72.6% and 79%, respectively. Multivariate analysis showed that advanced-stage disease and positive PWC significantly decreased PFS, while advanced-stage disease and older age (> 61 years) significantly decreased OS. CONCLUSIONS: ECCC is a rare and aggressive type II endometrial carcinoma that is common in older women and patients with advanced-stage disease. Positive PWC was associated with decreased PFS, although its presence did not influence the stage. Positive PWC, and advanced stage and older age were independent negative prognostic factors.

Lkb1 loss in regulatory T cells leads to dysregulation of hematopoietic stem cell expansion and differentiation in bone marrow.

The tumor suppressor Lkb1 is known to regulate the expression of forkhead box P3 (Foxp3), thereby maintaining the levels of Foxp3+ regulatory T cells (Treg) that play a crucial role in self-tolerance. However, the effect of Lkb1 in Treg on hematopoietic stem cells (HSCs) in the bone marrow (BM) remains obscure. Here, we demonstrated that conditional deletion of Lkb1 in Treg causes loss of Treg in the BM, which leads to failure of HSC homeostasis and the abnormal expansion. Moreover, the loss of BM Treg results in dysregulation of other developing progenitors/stem cell populations, leading to the defective differentiation of T cells and B cells. In addition, HSC from the BM with Treg loss exhibited poor engraftment efficiency, indicating that loss of Treg leads to irreversible impairment of HSC. Collectively, these results demonstrated the essential role of Lkb1 in Treg for maintaining HSC homeostasis and differentiation in mice. These findings provide insight into the mechanisms of HSC regulation and guidance for a strategy to improve the outcomes and reduce complications of HSC transplantation.

m6A RNA methylation regulators predict prognosis and indicate characteristics of tumour microenvironment infiltration in acute myeloid leukaemia.

Patients with acute myeloid leukaemia (AML) have poor prognoses and low overall survival (OS) rates owing to its heterogeneity and the complexity of its tumour microenvironment (TME). N6-methyladenosine (m6A) modification plays a key role in the initiation and progression of haematopoietic malignancies. However, the underlying function of m6A regulators in AML remains elusive. This study thoroughly analysed the m6A modification features of 177 AML patients based on 22 m6A regulators. Utilizing unsupervised clustering, we determined three distinct m6A modification patterns related to different biological functions, TME cell-infiltrating characteristics and clinical outcomes. Additionally, a risk score was constructed based on six m6A regulators-associated prognostic signatures and was validated as an independent and valuable prognostic factor for AML. Patients with a low-risk score exhibited better survival than those with a high-risk score. Many m6A regulators were aberrantly expressed in AML, among which METTL14, YTHDC2, ZC3H13 and RBM15 were observed to be associated with the OS of AML. In addition, these four m6A regulators were found to be noticeably related to the immune checkpoint inhibitor (ICI) treatments. Finally, we verified the expression levels of these four m6A regulators in AML and healthy samples and three groups of AML patients with different risk categories. Collectively, our study indicates that the m6A modification pattern is involved in TME immune-infiltrating characteristics and prognosis in AML. A better understanding of the m6A modification pattern will help enhance our knowledge of the molecular mechanisms of AML and develop potential prognosis prediction indicators and more effective immunotherapeutic strategies.

Preservation of sexual and reproductive function in the treatment of extragonadal yolk sac tumors in the female genital tract.

Objective: This study aimed to summarize the clinical features, treatment modalities, therapeutic effects, menstruation and fertility outcomes, and prognosis of extragonadal yolk sac tumors (YSTs) of the female genital tract. Methods: We reviewed 32 cases of extragonadal YSTs in the genital tract treated between 1983 and 2021. The medical records, including clinical characteristics, histopathology, treatments, chemo-reduced adverse events, and outcomes on long-term follow-up, were collected. Results: Among the 32 cases, 30 were vaginal YSTs and two were uterine YSTs (endometrial and cervical). Thirty patients (30/32, 93.8%) were <4 years. Abnormal vaginal bleeding (n = 31) and elevated serum alpha-fetoprotein level (n = 32) were the most common presentations. Vaginohysteroscopy and/or pediatric rhinoscopy were used for diagnosis in 17 pediatric patients and evaluation of chemotherapeutic efficacy in 21 pediatric patients. All the patients received combination chemotherapy. Bleomycin/etoposide/cisplatin (BEP) was chosen with prior consideration in 28 cases; 21 patients were treated with BEP alone. Yellow or grayish-yellow tissue with irregular shape was found in 66.7% of the cases during repeat examinations. Five patients underwent surgeries during repeat examinations and follow-ups, and no evidence of malignancy was noted in them. Thirty-one patients achieved complete remission. During a median follow-up of 63 months (2.4-240.3 months), two patients experienced recurrence, three died, and 29 remained disease-free. One patient recovered menstruation and five had undergone menarche. Conclusion: BEP chemotherapy can serve as a preferred treatment modality for vaginal and uterine YSTs. Vaginohysteroscopy and pediatric rhinoscopy can be used for diagnosis and evaluation of chemotherapeutic efficacy in pediatric patients. YSTs possibly appear as yellow or grayish-yellow after chemotherapy.

The Aetiology of Tourette Syndrome and Chronic Tic Disorder in Children and Adolescents: A Comprehensive Systematic Review of Case-Control Studies.

(1) Introduction: Tourette syndrome (TS) and chronic tic disorder (CTD) are common neurodevelopmental/-psychiatric disorders. The aetiological factors that contribute to the pathogenesis of TS/CTD are still poorly understood. The possible risk factors for TS/CTD are considered to be a combination of genetic, immunological, psychological and environmental factors. A comprehensive systematic review was conducted to assess the association between aetiological factors and TS/CTD. (2) Methods: Electronic databases, including PubMed, Embase, Web of Science, Wanfang data, and CNKI, were searched to identify the etiological factors of children and adolescents (≤18 years) with TS/CTD based on a case-control study. Quality assessments were performed according to the Newcastle-Ottawa scale (NOS). (3) Results: According to sample sizes and NOS values, recent evidence may support that genetic factors (BTBD9 and AADAC), immunological factors (streptococcus and mycoplasma pneumoniae infections), environmental factors (conflict, history of perinatal diseases, and family history of neurological and psychiatric diseases and recurrent respiratory infections) and psychological factors (major life events) are associated with the pathogenesis of TS/CTD. (4) Conclusions: Some risk factors in different categories may be the etiological factors of TS/CTD, but there is a lack of studies on the interaction among the factors, which may require more attention in the future.

Deep Spatio-Temporal Attention-Based Recurrent Network From Dynamic Adaptive Functional Connectivity for MCI Identification.

Most existing methods of constructing dynamic functional connectivity (dFC) network obtain the connectivity strength via the sliding window correlation (SWC) method, which estimates the connectivity strength at each time segment, rather than at each time point, and thus is difficult to produce accurate dFC network due to the influence of the window type and window width. Furthermore, the deep learning methods may not capture the discriminative spatio-temporal information that is closely related to disease, thus impacting the performance of mild cognitive impairment (MCI) identification. In this paper, a novel spatio-temporal attention-based bidirectional gated recurrent unit (STA-BiGRU) network is proposed to extract inherent spatio-temporal information from a dynamic adaptive functional connectivity (dAFC) network for MCI diagnosis. Specifically, we adopt a group lasso-based Kalman filter algorithm to obtain the dAFC network with more accurate connectivity strength at each time step. Then a spatial attention module with self-attention and a temporal attention module with multiple temporal attention vectors are incorporated into the BiGRU network to extract more discriminative disease-related spatio-temporal information. Finally, the spatio-temporal regularizations are employed to better guide the attention learning of STA-BiGRU network to enhance the robustness of the deep network. Experimental results show that the proposed framework achieves mean accuracies of 90.2%, 90.0%, and 81.5%, respectively, for three MCI classification tasks. This study provides a more effective deep spatio-temporal attention-based recurrent network and obtains good performance and interpretability of deep learning for psychiatry diagnosis research.