Deep learning-based methods for drug target binding affinity (DTA) prediction are improving the efficien cy of drug screening, but some limitations persist in current methodologies. Notably, prevailing models predominantly rely on static structural data while neglecting the conformational dynamics of drug target complexes, which compromises their capacity to discern subtle conformation dependent affinity variations. To address this issue, we first constructed MD-PDBbind, an enhanced sampled molecular dynamics simulation (MD) dataset. Building upon this foundation, the MDDTA model incorporating the novel FAFormer architecture was proposed to achieve (3) equivariance and invariance, allowing the model to better learn the geo metric information of the drug target complexes. Further more, we formulated a dynamic-aware loss function to enhance the adaptability of model to diverse conformations. The MDDTA demonstrates excellent scoring and ranking performance on the CASF-2016 dataset, with a case study providing intuitive validation of the effectiveness of incor porating dynamic information. Lastly, a drug screening process was developed using the MDDTA to screen 70 SARS CoV-2 candidate compounds, five of which have been validated in the literature. These results highlight the potential of MDDTA for practical drug screening.

This study aimed to investigate the potential of Venetoclax combined with ML385 to overcome drug resistance in leukemia cells and the related mechanisms. Analysis of Nrf2 expression and its prognostic significance in AML was performed utilizing the GEO and GEPIA2 databases. Bone marrow specimens were collected from newly diagnosed AML patients to evaluate Nrf2 expression levels and assess their correlation with established risk stratification and clinical prognosis. Two doxorubicin-resistant leukemia cell lines were established. Subsequently, stable Nrf2-knockdown cell lines were generated via lentiviral transduction. Cellular proliferation and apoptosis were analyzed. Levels of reactive oxygen species (ROS) and glutathione (GSH), alongside the expression of oxidative stress-related and apoptosis-related genes and proteins, were quantified. Furthermore, the effects of Venetoclax combined with ML385 on proliferation, apoptosis, ROS levels, and GSH levels were subsequently investigated in these doxorubicin-resistant cell lines. Mechanistically, the impact of the drug combination on oxidative stress and the PI3K/AKT signaling pathway was explored. Nrf2 was up-regulated in AML and predicted poor prognosis. In doxorubicin-resistant AML cells, oxidative-stress genes were elevated. Silencing Nrf2 inhibited proliferation, induced apoptosis, lowered GSH, raised ROS, increased pro-apoptotic BAX and Caspase-3, and decreased anti-apoptotic Bcl-2. Combining the venetoclax with ML385 significantly suppressed proliferation and induced apoptosis in drug-resistant leukemia cells. Mechanistically, this dual-targeting regimen concurrently attenuated both the Nrf2-mediated antioxidant defense and the pro-survival PI3K/AKT signaling axis, which collectively underpin its enhanced anti-leukemic efficacy. This study demonstrates venetoclax combined with ML385 overcomes chemotherapy resistance in acute myeloid leukemia by modulating Nrf2/ARE-mediated oxidative stress.These findings reveal a novel mechanism and a promising therapeutic strategy.

Purpose Acute myeloid leukemia (AML) is a hematological malignancy with a high recurrence rate, particularly in intermediate and high-risk AML patients. Therefore, maintenance therapy is particularly important. Azacitidine (AZA) monotherapy maintenance can significantly improve the prognosis of AML patients. The second-generation tyrosine kinase inhibitors (TKIs) combined with demethylating agents have exhibited a significant synergistic effect in promoting apoptosis and reducing methylation. Therefore, we reported the efficacy and safety of AZA combined with low-dose Dasatinib in the maintenance treatment of AML. Methods In this single-center, prospective, randomized phase II trial, newly diagnosed AML patients aged 18 to 76 years with intermediate-high risk were assigned (2:1) to receive either AZA (75 mg/m²/day, d1-d5) or AZA (75 mg/m²/day, d1-d5) plus Dasatinib (20 mg orally, d1-d28) with negative MRD status after induction and consolidation therapy (NCT05042531). Results The median overall survival (mOS) was 26 months (95% confidence interval, 18.9–33.1 months) in the AZA group, whereas the mOS was not reached in the AZA + Dasatinib group (p = 0.038). DFS did not differ significantly between the groups (p = 0.25). Hematological adverse events (AEs) occurred in 65% (13/20) of the AZA group versus 90% (9/10) of the AZA + Dasatinib group (p = 0.210). No patient discontinued the treatment due to adverse reactions. AZA in combination with low-dose Conclusions Dasatinib as a maintenance treatment exhibits promising efficacy and is well-tolerated in intermediate and high-risk AML patients. This combination may be a novel treatment option for AML patients.

Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy characterized by a high relapse rate and a low survival rate. Although chemotherapy and allogeneic hematopoietic stem cell transplantation (allo-HSCT) have improved the prognosis for AML patients, the overall survival rate remains suboptimal. MLN4924 is a neddylation inhibitor and is considered a promising treatment approach for AML. However, the exact molecular mechanism remains elusive and requires further investigation. This study aims to investigate the molecular mechanisms of MLN4924 and novel molecular pathways in AML. RNA sequencing (RNA-seq) reveals that the transcription factor (TF) EGR1 serves as a core regulator of MLN4924 and is upregulated by MLN4924 in AML. Mechanistic studies demonstrate that MLN4924 induces apoptosis by generating reactive oxygen species (ROS) and facilitates the nuclear translocation of EGR1. This translocated EGR1 interacts with the promoter region of BTG2, promoting its transcription and inhibiting the progression of AML. Notably, the ROS generated by MLN4924 influences the expression of both EGR1 and BTG2 and establishes a positive feedback loop between EGR1 and ROS. In vivo, we confirm that MLN4924 reduces the leukemic burden in AML cell-derived xenograft models by increasing the expression of both EGR1 and BTG2. In conclusion, these findings suggest that MLN4924 exerts an anti-tumor effect on AML by inducing apoptosis through the ROS-EGR1-BTG2 signaling axis. Our research provides a novel theoretical basis for the clinical potential of MLN4924 in improving the treatment of AML patients, offers novel strategies for AML treatment, and thereby advances the implementation of precision medicine.

Protein-RNA interactions play pivotal roles in biological processes. Despite the development of numerous computational models for protein-RNA binding site prediction, they still face critical challenges, including insufficient integration of global and local features, class imbalance undermining precision-recall, and poorly calibrated predictions. To address these issues, we first constructed a larger and more comprehensive data set (Train-1086 and Test-107). Specifically, we developed DGSite, a novel deep learning framework that captures long-range dependencies via the simplified Deformable Attention Transformer and extracts multiscale local contextual features using Graph Attention Networks. To mitigate class imbalance and reduce model uncertainty, we introduced Adaptive Bias Loss (ABL), based on optimal transport theory. On this foundation, we proposed a hybrid loss function, ABL+FL, that adaptively combines the complementary strengths of ABL and Focal Loss (FL) to achieve a superior balance between precision, recall, and calibration. Extensive experiments demonstrated that DGSite achieves high performance on both Test-107 and established classic data sets. The ABL+FL loss not only balanced precision and recall but also significantly reduced model uncertainty, yielding well-calibrated and more trustworthy predictions. Moreover, case-study visualizations confirmed the model's ability to minimize false positives and provide interpretable insights. Collectively, DGSite serves as a robust, high-performance, and well-calibrated computational tool for pinpointing protein-RNA binding sites.

Opioid analgesics are commonly prescribed to mitigate pathological pain. In addition to its analgesic effect, this pharmaceutical treatment program is well-known for its ability to induce adverse effects, including opioid-induced hyperalgesia (OIH) and analgesic tolerance. Thus, novel effective therapeutic strategies are urgently needed to improve opioid analgesia while mitigating side effects to ensure patient safety. Currently, efforts to increase the benefit/risk profiles of opioid analgesics, particularly combination pharmacotherapy, are highly promising and have made great progress. When combined, opioid analgesics and certain types of nonopioids have been found to reduce the required analgesic dose and decrease dose-limiting side effects compared with monotherapy. However, little is known about the mechanisms that underlie synergistic analgesia. The desensitization and internalization of the mu-opioid receptor (μOR), which is controlled by carboxyl-terminal phosphorylation, limits the efficacy of opioid drugs and underlies the initiation of analgesic tolerance and OIH. Here, we survey the synergistic effects of opioid and nonopioid combinations in pain treatment; these combinations improve opioid analgesia and reduce side effects by modulating μOR phosphorylation and dephosphorylation. Furthermore, we discuss how these nonopioid receptors and their agents are involved in the regulation of protein kinase-mediated μOR phosphorylation and protein phosphatase-mediated μOR dephosphorylation.

Chronic pain is a debilitating disease and remains challenging to treat. Morphine serves as the most commonly used drug for the treatment of pathological pain. However, detrimental side effects (e.g., hyperalgesia and tolerance) manifest during chronic administration, thus counteracting morphine analgesia. Investigators have sought methods to widen the therapeutic window of morphine in the management of chronic pain. Programmed cell death protein 1 (PD-1) is a recently validated analgesic target and is coexpressed with the mu opioid receptor (μOR) in dorsal root ganglion (DRG) sensory neurons. Here, we present evidence that PD-1 regulates the expression of μOR mRNA and influences μOR-mediated analgesia. Notably, the concomitant administration of PD-1 agonist H-20 greatly reduces the dosage of morphine needed for analgesia, thereby significantly decreasing opioid-related side effects. This new combination therapy may provide a solution for managing chronic pain in patients who require morphine.

Purpose:The aim of this study was to elucidate the molecular mechanism by which MLN4924 affects the progression of acute myeloid leukemia (AML) by regulating TRIM58 DNA methylation. Patients and Methods:Gene expression was analyzed by RT-qPCR and Western blot, while methylation changes were assessed via Methylation-sensitive restriction enzyme-quantitative PCR. Differentially expressed lncRNAs were identified through RNA sequencing. Subcellular localization was determined via nuclear-cytoplasmic fractionation-PCR. Protein-DNA/RNA interactions were analyzed by chromatin immunoprecipitation and RNA immunoprecipitation, respectively. In vivo experiments were conducted using a xenograft model, with tumor protein expression evaluated by immunohistochemistry. Results:TRIM58 downregulation in AML correlated with promoter hypermethylation, reversible by MLN4924 treatment. Functional studies demonstrated TRIM58 mediated MLN4924-induced apoptosis through AKT pathway inhibition. While MLN4924 upregulated the tumor-suppressive lncRNA LINC01128, its overexpression recapitulated TRIM58-mediated anti-leukemic effects, including expansion arrest, apoptosis induction, and BAX/BCL-2 axis modulation. Mechanistically, nuclear-localized LINC011128 functionally interacted with DNMT1 to mediate TRIM58 promoter demethylation, establishing an epigenetic regulatory axis. Rescue experiments revealed TRIM58 knockdown attenuated MLN4924's suppression of AKT phosphorylation and associated pro-apoptotic effects. Conclusion:In this study, we show that MLN4924 can upregulate LINC01128, which binds to and segregates DNMT1, thereby inhibiting methylation modification of the TRIM58 and ultimately suppressing AML.

This study investigated whether the neddylation inhibitor MLN4924 induces aberrant DNA methylation patterns in acute myeloid leukemia and contributes to the reactivation of tumor suppressor genes. DNA methylation profiles of Kasumi-1 and KU812 acute myeloid leukemia cell lines before and after MLN4924 treatment were generated using the 850K Methylation BeadChip. RNA sequencing was used to obtain transcriptomic profiles of Kasumi-1 cells. Target genes were identified through a combined analysis of methylation and transcriptome data. Methylation-specific PCR and quantitative PCR validated the changes in methylation and expression. Prognostic analysis of target genes was performed using databases, and Pearson correlation was used to examine the relationship between methylation and expression levels. In Kasumi-1 and KU812 cells, 301 and 469 differentially methylated sites, respectively, were identified. A total of 4310 differential expression genes were detected in Kasumi-1. Combined analysis revealed that TRIM58 exhibited significant demethylation and upregulation after MLN4924 treatment, as confirmed by quantitative and methylation-specific PCR. Furthermore, database analysis revealed that both down-expression and promoter hypermethylation of TRIM58 were correlated with poor prognosis in acute myeloid leukemia. A negative correlation was observed between TRIM58 methylation and expression levels. This study suggests that MLN4924 alters DNA methylation patterns in acute myeloid leukemia and reactivates TRIM58, a potential tumor suppressor gene, through demethylation.

The purpose of this study was to identify whether the gut microbiota and metabolites of newly diagnosed acute myeloid leukemia (AML) patients displayed specific characteristic alterations and whether these changes could be used as potential biomarkers for predicting the disease. Notably, the gut microbiota and metabolites of AML patients exhibited significant structural and quantitative alterations at the time of their initial diagnosis. Beneficial bacteria, including Faecalibacterium, Collinsella, Lacticaseibacillus, and Roseburia, as well as butyric acid and acetic acid, were found to be considerably reduced in newly diagnosed AML patients. In contrast, Enterococcus and Lactobacillus, especially Enterococcus, were significantly enriched. Further investigation indicated that Enterococcus could serve as a potential intestinal marker, showing a strong negative correlation with the levels of acetic and butyric acid. Importantly, assays aimed at identifying AML demonstrated that Enterococcus, butyric acid, and acetatic acid exhibited excellent predictive effectiveness. Colonizing Enterococcus from patients were isolated for pathogen investigation, which revealed that these bacteria possess several strong virulence factors and multiple drug-resistance gene characteristics. Therefore, we speculate that the increase of Enterococcus may contribute to the development and progression of AML.

The black-box nature of deep learning has increasingly drawn attention to the reliability and uncertainty of predictive models. Currently, several uncertainty quantification (UQ) methods have been proposed and successfully applied in the fields of molecules and proteins, effectively improving model prediction quality and interpretability. Protein-RNA binding represents a fundamental aspect of protein research. Accurate prediction of binding sites and ensuring the reliability of such predictions are crucial for various scientific endeavors. However, many of the existing computational methods have a single feature extraction and lack of UQ. To address these, we propose MGCA (multiscale graph convolutional networks, convolutional neural networks and attention) to better capture local and global information and achieve competitive results in predicting protein-RNA binding sites. Moreover, we launch a UQ study based on MGCA and five prevalent models to verify the robustness of the results. Specifically, we introduce the Expected Calibration Error (ECE) to assess the uncertainty of the models. Additionally, a novel split-bins screening method is proposed based on the ECE, aiming to investigate the practical impact of reducing uncertainty on the models. Finally, temperature scaling (TS) is used to calibrate model uncertainty without changing performance. Results show that the split-bins screening method reduces false positives (FP), and TS significantly decreases the model ECE. The split-bins screening method combined with TS can further reduce FP and improve precision. Our findings demonstrate that TS effectively reduces uncertainty in protein-RNA binding site prediction, and minimizing model uncertainty enhances prediction quality. The data and code can be available at https://github.com/trustcm/UQ-TS-Split-bins-RBP.

Objectives: While ferroptosis induction emerges as a therapeutic strategy for solid tumors, its role in acute myeloid leukemia (AML) remains unexplored. This study aimed to investigate the role of MLN4924 in modulating ferroptosis and its molecular targets in AML.Methods: Transcriptome sequencing and bioinformatics analyses were performed to identify MLN4924 potential targets in ferroptosis. First, ferroptosis-related phenotypic assays were conducted, including assays of reactive oxygen species (ROS), glutathione (GSH), malondialdehyde (MDA), and Fe2+ levels. Second, cell viability assays were carried out with the combination of MLN4924 and ferroptosis inducers (Erastin, Sorafenib). Third, rescue experiments were used the ferroptosis inhibitor Ferrostatin-1 after MLN4924 treatment. In vivo efficacy was evaluated in NOD/SCID mice bearing AML xenografts treated with MLN4924, followed by tumor tissue analysis of GSH and Fe2+ levels, immunohistochemistry (IHC), and Western blotting for SLC7A11/GPX4 axis components.Results: Transcriptome sequencing and bioinformatics analyses identified SLC7A11 and GPX4 as key MLN4924 target genes, both of which are glutathione-related proteins. MLN4924 significantly suppressed SLC7A11 and GPX4 expression, decreased GSH activity, and increased ROS, Fe2+, and MDA levels. Ferroptosis inducers (Erastin, Sorafenib) further enhanced the antileukemic activity of MLN4924, and ferroptosis inhibitor Ferrostatin-1 partially reversed this toxicity. In vivo, MLN4924 reduced tumor burden, accompanied by SLC7A11/GPX4 downregulation and Fe2+ accumulation in xenografts.Conclusion: This study provides the first evidence that MLN4924 triggers ferroptosis in AML by inhibiting the SLC7A11/GPX4 axis. These findings establish MLN4924 as a ferroptosis sensitizer through synergistic effects with ferroptosis inducers, supporting its therapeutic potential in AML.

IntroductionNucleophosmin 1 (NPM1), FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD), and de novo methyl transferase 3 A (DNMT3A) triple-mutated acute myeloid leukemia (AML) represents a distinct entity with poor outcomes.MethodsWe explored the gene mutation spectrum and clinical characteristics of 165 AML patients retrospectively, particularly comparing patients with NPM1/FLT3-ITD/DNMT3A triple-mutations and those without.ResultsOur results demonstrated significantly elevated white blood cell counts (P < 0.001), bone marrow blast percentages (P = 0.037), and platelet counts (P = 0.007) in the triple-mutated cohort (6.7%) compared to the non-triple-mutated patients. Furthermore, all triple-mutated cases were classified as the M4/M5 subtype of the French-American-British classification (P = 0.017). Although no significant difference in complete remission rates was observed between the groups after initial treatment, the median overall survival for triple-mutated AML patients was only 4 months. Using the Gene Expression Omnibus (GEO) database and bioinformatics, we compared AMLNPM1mutFLT3-ITDmutDNMT3Amut and AMLNPM1mutFLT3-ITDmutDNMT3Awt. A total of 246 AML patients from the GEO dataset were included to evaluate the expression profiles of differentially expressed genes. The guanine nucleotide-binding protein subunit γ 4 (GNG4) was differentially expressed between AMLNPM1mutFLT3-ITDmutDNMT3Amut and AMLNPM1mutFLT3-ITDmutDNMT3Awt, which had the most adjacent nodes among hub genes. The prognostic value of GNG4 was further validated in AML patient samples through qRT-PCR.ConclusionClinical validation indicated a substantial downregulation of GNG4 in AMLNPM1mutFLT3-ITDmutDNMT3Amut compared to AMLNPM1mutFLT3-ITDmutDNMT3Awt patients. Thus, GNG4 may play a role in the low survival rate of AMLNPM1mutFLT3-ITDmutDNMT3Amut patients, offering novel insights into the prognosis, therapeutic targets, and prognostic evaluation of AML.

Dopamine (DA) plays a critical role in various neurological disorders, including Parkinson's disease and schizophrenia, making its accurate and ultra-sensitive detection crucial for early diagnosis and treatment. In this study, a novel electrochemical sensor for DA detection was developed using monolayer Ti3C2Tx Mxene material treated with oxygen plasma. The oxygen plasma treatment significantly enhanced the surface activity and electronic transport capabilities of Ti3C2Tx, resulting in an ultra-low detection limit of 0.005 nM for DA. Electrochemical tests demonstrated the sensor's excellent sensitivity, stability, and performance. To further elucidate the underlying mechanisms of enhanced electrochemical performance, density functional theory (DFT) calculations were employed to investigate the impact of oxygen plasma treatment on the electronic structure of Ti3C2Tx. The DFT results revealed that the oxygen plasma treatment notably increased the number of active sites by introducing more oxygen-terminated functional groups on the surface of Ti3C2Tx. These oxygenated functional groups acted as catalysts, lowering the activation energy required for DA electrochemical reactions. Additionally, the oxygen plasma treatment effectively reduced the lattice constant of Ti3C2Tx, improving its internal electronic transport properties and thus enhancing its conductivity. The theoretical studies are in strong agreement with the experimental results, providing a clear understanding of the interaction between DA molecules and the oxygen-functionalized Ti3C2Tx surface. This research highlights the potential of oxygen plasma-treated Ti3C2Tx as a high-performance electrochemical sensing material and offers new perspectives for the development of sensitive biosensors.

Abstract BACKGROUND Our previous research indicated a significant reduction in the beneficial metabolite butyrate acid, derived from gut microbiota, in the intestines and blood of patients with primary Acute Myelocytic Leukemia (AML). To investigate the key molecules through which butyrate acid influences AML progression, this study aimed to elucidate the anti-tumor mechanisms by which butyrate inhibits AML cell viability, promotes apoptosis, and blocks the cell cycle in vitro, while also assessing its efficacy in delaying AML progression in vivo.METHODS The effect of butyrate acid on the proliferation activity of AML cells was measured using the Cell Counting Kit-8 assay. Flow cytometry was used to detect the effect of butyrate acid on apoptosis and cell cycle of AML cells. Differentially expressed genes (DEGs) were screened by cellular transcriptomics and analyzed for functional enrichment. The mRNA of DEGs was verified by qRT-PCR, and the protein levels were detected by Western blot (WB). Patient-derived xenograft (PDX) AML models were constructed by luciferase labeling AML cells. The changes of gut microbiota were detected by 16S rRNA in mouse feces, and the SCFAs content were detected by targeted GC-MS in mouse feces and serum. Blood routine tests, peripheral blood and bone marrow blast cell tests, and in vivo fluorescence tests in mice were conducted to verify the tumor cell burden. HE was used to observe the pathological changes of organs, and immunohistochemistry (IHC) was used to detect the expression levels of key molecules.RESULTS Butyrate acid inhibited AML cell proliferative viability, promoted apoptosis, and blocked the G1 phase of the AML cell cycle. Butyrate acid significantly up-regulated the mRNA and protein expression of cyclin-dependent kinase inhibitor 1A (CDKN1A), and inhibited the phosphorylation levels of PI3K and AKT, but did not alter the expression of apoptosis-related proteins BAX and BCL-2. 16S-rRNA sequencing and SCFAs measurements showed that butyrate acid restored the abundance of some beneficial intestinal microbiota and directly replenished butyrate concentration in mice. The butyrate acid intervention prolonged the survival time of the mice, slowed down the spleen enlargement and colon shortening of AML mice, and reduced the AML cell load of AML mice; the Ki67 positivity rate of AML mice was significantly higher than that of the butyrate-intervened AML group. IHC and WB confirmed that butyric acid significantly up-regulated the expression of CDKN1A in the spleen.CONCLUSION Dysbiosis of gut microbiota accelerates AML disease progression, and AML disease alters the structure of intestinal flora. Butyrate plays an anti-AML tumor role as a key intermediate metabolite regulating CDKN1A expression, inhibiting the PI3K-AKT pathway while blocking the cell cycle and promoting apoptosis. Exogenous butyrate is a feasible new therapeutic strategy for AML and has good clinical prospects.

Background Although some acute myeloid leukemia (AML) patients achieve minimal residual disease (MRD) negativity following induction and consolidation therapy, many struggle with long-term remission, particularly those in intermediate and high-risk groups. High-risk AML patients who initially respond to treatment but are not eligible for allogeneic stem cell transplantation (ASCT) will eventually relapse with poor outcomes. Consequently, maintenance therapy is crucial. Research has demonstrated that tyrosine kinase inhibitors (TKIs) not only inhibit the abnormal activation of the tyrosine kinase pathway but also reduce DNA methylation. The combination of second-generation TKIs with demethylating agents exhibits a significant synergistic effect in promoting apoptosis and reducing methylation levels. However, real-world reports on the use of azacitidine (AZA) and Dasatinib for maintenance in intermediate and high-risk AML patients are limited. We therefore conducted a study to evaluate the efficacy and safety of combining AZA with Dasatinib in the maintenance therapy of intermediate and high-risk AML patients. Methods In this single-center, prospective, randomized phase II trial, newly diagnosed AML patients aged 11 to 76 years with intermediate-high risk (ELN 2022 AML risk stratification) were assigned (2:1) to receive either AZA or AZA plus Dasatinib with negative MRD status after induction and consolidation therapy (NCT05042531). The AZA + Dasatinib group received AZA (75 mg/m²/day) via subcutaneous injection on days 1-5 and Dasatinib (20 mg orally) from days 1-28. The AZA group received only AZA on the same schedule. Maintenance therapy may be interrupted or delayed for grade 3/4 toxicity, with the AZA dose adjustable to 50 mg/m²/day or 37.5 mg/m²/day, while Dasatinib remains at 20 mg. The primary endpoint was overall survival (OS), with secondary endpoints being disease-free survival (DFS) and adverse events (AEs). Results From April 2020 to April 2024, 33 patients were randomly allocated into either AZA (n=22) or AZA plus Dasatinib (n=11). The intention-to-treat population included 30 patients (20 in the AZA group and 10 in the AZA plus Dasatinib group. The median age was 42 years (range, 21-60.5) in the AZA group and 49 years (range, 44.3-53) in the AZA + Dasatinib group, with 50% males in both groups. Morphological characteristics in the AZA group were M2 (50%), M4 (15%), and M5 (35%), while in the AZA + Dasatinib group, they were M2 (60%), M4 (20%), and M5 (20%). Both groups received a median of 12 cycles of AZA. Baseline characteristics were generally balanced between the groups. With a median follow-up of 24.5 months (range, 13.3 to 40 months). The median overall survival (mOS) was 26 months (95% confidence interval 18.9-33.1 months) in the AZA group, while the mOS was not reached in the AZA + Dasatinib group, which had a statistically significant difference (log-rank test, p = 0.038). The two-year OS value of the AZA + Dasatinib group is better than the AZA group (90% versus 79.5%). DFS did not differ between the groups (p=0.65). In terms of AEs, hematological AEs occurred in 65% (13/20) of the AZA group versus 90% (9/10) of the AZA + Dasatinib group (p=0.210), with grade ≥4 events at 20% in both groups. Non-hematological events were 20% (4/20) in the AZA group versus 40% (4/10) in the AZA + Dasatinib group (p=0.384), with no serious non-hematological events reported. Conclusions AZA in combination with low-dose Dasatinib as a maintenance treatment exhibits promising efficacy and is well-tolerated compared with AZA monotherapy in intermediate and high-risk AML patients. This combination may be a novel treatment option for AML patients.

IntroductionNucleophosmin 1 (NPM1), FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD), and de novo methyl transferase 3 A (DNMT3A) triple-mutated acute myeloid leukemia (AML) represents a distinct entity with poor outcomes.MethodsWe explored the gene mutation spectrum and clinical characteristics of 165 AML patients retrospectively, particularly comparing patients with NPM1/FLT3-ITD/DNMT3A triple-mutations and those without.ResultsOur results demonstrated significantly elevated white blood cell counts (P < 0.001), bone marrow blast percentages (P = 0.037), and platelet counts (P = 0.007) in the triple-mutated cohort (6.7%) compared to the non-triple-mutated patients. Furthermore, all triple-mutated cases were classified as the M4/M5 subtype of the French-American-British classification (P = 0.017). Although no significant difference in complete remission rates was observed between the groups after initial treatment, the median overall survival for triple-mutated AML patients was only 4 months. Using the Gene Expression Omnibus (GEO) database and bioinformatics, we compared AMLNPM1mutFLT3-ITDmutDNMT3Amut and AMLNPM1mutFLT3-ITDmutDNMT3Awt. A total of 246 AML patients from the GEO dataset were included to evaluate the expression profiles of differentially expressed genes. The guanine nucleotide-binding protein subunit γ 4 (GNG4) was differentially expressed between AMLNPM1mutFLT3-ITDmutDNMT3Amut and AMLNPM1mutFLT3-ITDmutDNMT3Awt, which had the most adjacent nodes among hub genes. The prognostic value of GNG4 was further validated in AML patient samples through qRT-PCR.ConclusionClinical validation indicated a substantial downregulation of GNG4 in AMLNPM1mutFLT3-ITDmutDNMT3Amut compared to AMLNPM1mutFLT3-ITDmutDNMT3Awt patients. Thus, GNG4 may play a role in the low survival rate of AMLNPM1mutFLT3-ITDmutDNMT3Amut patients, offering novel insights into the prognosis, therapeutic targets, and prognostic evaluation of AML.

Chronic pain is a prevalent and persistent ailment that affects individuals worldwide. Conventional medications employed in the treatment of chronic pain typically demonstrate limited analgesic effectiveness and frequently give rise to debilitating side effects, such as tolerance and addiction, thereby diminishing patient compliance with medication. Consequently, there is an urgent need for the development of efficacious novel analgesics and innovative methodologies to address chronic pain. Recently, a growing body of evidence has suggested that multireceptor ligands targeting opioid receptors (ORs) are favorable for improving analgesic efficacy, decreasing the risk of adverse effects, and occasionally yielding additional advantages. In this study, the intrathecal injection of a recently developed peptide (VYWEMEDKN) at nanomolar concentrations decreased pain sensitivity in naïve mice and effectively reduced pain-related behaviors in nociceptive pain model mice with minimal opioid-related side effects. Importantly, the compound exerted significant rapid-acting antidepressant effects in both the forced swim test and tail suspension test. It is possible that the rapid antihyperalgesic and antidepressant effects of the peptide are mediated through the OR pathway. Overall, this peptide could both effectively provide pain relief and alleviate depression with fewer side effects, suggesting that it is a potential agent for chronic pain and depression comorbidities from the perspective of pharmaceutical development.

Phosphorylation is indispensable in comprehending biological processes, while biological experimental methods for identifying phosphorylation sites are tedious and arduous. With the rapid growth of biotechnology, deep learning methods have made significant progress in site prediction tasks. Nevertheless, most existing predictors only consider protein sequence information, that limits the capture of protein spatial information. Building upon the latest advancement in protein structure prediction by AlphaFold2, a novel integrated deep learning architecture PhosAF is developed to predict phosphorylation sites in human proteins by integrating CMA-Net and MFC-Net, which considers sequence and structure information predicted by AlphaFold2. Here, CMA-Net module is composed of multiple convolutional neural network layers and multi-head attention is appended to obtaining the local and long-term dependencies of sequence features. Meanwhile, the MFC-Net module composed of deep neural network layers is used to capture the complex representations of evolutionary and structure features. Furthermore, different features are combined to predict the final phosphorylation sites. In addition, we put forward a new strategy to construct reliable negative samples via protein secondary structures. Experimental results on independent test data and case study indicate that our model PhosAF surpasses the current most advanced methods in phosphorylation site prediction.