MMSMAPlus: a multi-view multi-scale multi-attention embedding model for protein function prediction.

Protein is the most important component in organisms and plays an indispensable role in life activities. In recent years, a large number of intelligent methods have been proposed to predict protein function. These methods obtain different types of protein information, including sequence, structure and interaction network. Among them, protein sequences have gained significant attention where methods are investigated to extract the information from different views of features. However, how to fully exploit the views for effective protein sequence analysis remains a challenge. In this regard, we propose a multi-view, multi-scale and multi-attention deep neural model (MMSMA) for protein function prediction. First, MMSMA extracts multi-view features from protein sequences, including one-hot encoding features, evolutionary information features, deep semantic features and overlapping property features based on physiochemistry. Second, a specific multi-scale multi-attention deep network model (MSMA) is built for each view to realize the deep feature learning and preliminary classification. In MSMA, both multi-scale local patterns and long-range dependence from protein sequences can be captured. Third, a multi-view adaptive decision mechanism is developed to make a comprehensive decision based on the classification results of all the views. To further improve the prediction performance, an extended version of MMSMA, MMSMAPlus, is proposed to integrate homology-based protein prediction under the framework of multi-view deep neural model. Experimental results show that the MMSMAPlus has promising performance and is significantly superior to the state-of-the-art methods. The source code can be found at https://github.com/wzy-2020/MMSMAPlus.

The genetic landscape of histologically transformed marginal zone lymphomas.

BACKGROUND: Marginal zone lymphomas (MZLs) comprise a diverse group of indolent lymphoproliferative disorders; however, some patients develop histologic transformation (HT) with rapid progression to aggressive lymphoma. METHODS: Forty-three MZLs with HT (HT-MZLs), 535 MZLs, and 174 de novo diffuse large B-cell lymphomas (DLBCLs) without rearrangements of MYC, BCL2, and BCL6 were collected. Among these, 22 HT-MZLs, 39 MZLs, and 174 DLBCLs were subjected to 148-gene targeted exome sequencing. The clinicopathologic features of patients who had HT-MZL and their genetic alterations were compared with those of patients who had MZLs and DLBCLs. RESULTS: All 43 HT-MZLs corresponded to DLBCLs. No HT-MZLs harbored BCL2 and MYC and/or BCL6 rearrangements. Bone marrow involvement and higher levels of lactate dehydrogenase were significantly more common in HT-MZLs than in MZLs. Furthermore, upregulated BCL6, MUM1, C-MYC, and Ki-67 expression was observed more frequently in HT-MZLs than in MZLs. TBL1XR1 was the most frequently altered gene (63.6%) in HT-MZLs, followed by CCND3 (31.8%), CARD11, ID3, and TP53 (22.7%). A trend toward worse progression-free survival in patients with TBL1XR1 mutations was observed. Compared with MZLs and non-germinal center B-cell (GCB) type DLBCLs, significantly higher frequencies of TBL1XR1 and ID3 mutations were identified in HT-MZLs. PIM1 mutations frequently occurred in DLBCLs and were significantly associated with TBL1XR1 mutations but were mutated less in HT-MZLs that had TBL1XR1 mutations. CONCLUSIONS: The current findings reveal the clinicopathologic and genetic features of HT-MZLs, suggesting that these tumors might constitute a group distinct from MZL and de novo non-GCB type DLBCL. TBL1XR1 mutations may be considered a predictor of HT in MZL.

Quantitative Characterization of Protein N-Linked Core-Fucosylation by an Efficient Glycan Truncation Strategy.

Dysregulation of protein core-fucosylation plays a pivotal role in the onset, progression, and immunosuppression of cancer. However, analyzing core-fucosylation, especially the accurate determination of the core-fucosylation (CF) site occupancy ratio, remains challenging. To address these problems, we developed a truncation strategy that efficiently converts intact glycopeptides with hundreds of different glycans into two truncated forms, i.e., a monosaccharide HexNAc and a disaccharide HexNAc+core-fucose. Further combination with data-independent analysis to form an integrated platform allowed the measurement of site-specific core-fucosylation abundances and the determination of the CF occupancy ratio with high reproducibility. Notably, three times CF sites were identified using this strategy compared to conventional methods based on intact glycopeptides. Application of this platform to characterize protein core-fucosylation in two breast cancer cell lines, i.e., MDA-MB-231 and MCF7, yields a total of 1615 unique glycosites and about 900 CF sites from one single LC-MS/MS analysis. Differential analysis unraveled the distinct glycosylation pattern for over 201 cell surface drug targets between breast cancer subtypes and provides insights into developing new therapeutic strategies to aid precision medicine. Given the robust performance of this platform, it would have broad application in discovering novel biomarkers based on the CF glycosylation pattern, investigating cancer mechanisms, as well as detecting new intervention targets.

Free heme induces neuroinflammation and cognitive impairment by microglial activation via the TLR4/MyD88/NF-κB signaling pathway.

BACKGROUND: Red blood cells (RBCs) transfusion is related to perioperative neurocognitive disorders. The toxic effect of free heme has been identified in many pathologies. However, the underlying mechanisms of RBCs transfusion or free heme in cognitive impairment have not been clearly explored. Therefore, this research was conducted to determine the mechanism of free heme-induced neuroinflammation and cognitive impairment. METHODS: Rats were received intraperitoneal injection of hemin alone or combined with intracerebroventricular injection of Hemopexin (HPX), and MWM test was conducted to measure cognitive function. The amount of heme-HPX complexes was evaluated by flow cytometry for CD91 + cells. The microglial inflammatory response in rat brain was observed by immunofluorescence staining of Iba-1, and the inflammatory factors of TNF-α, IL-1ß and IL-6 in rat brain and BV2 cells were detected by ELISA analysis. Furthermore, neuronal apoptosis in HT22 cells alone and in HT22 + BV2 coculture system was detected by flow cytometry and immunofluorescence staining. Finally, western blot was conducted to detect TLR4/MyD88/NF-κB proteins in rat brain and BV2 cells treated with hemin or combined with pathway inhibitors. Additionally, the M1 surface marker CD86 was observed in BV2 cells to further confirm neuroinflammation. RESULTS: Intraperitoneal injection of hemin induced cognitive impairment, increase of CD91 + cells, up-regulation of TNF-α and IL-1ß, down-regulation of IL-6, activation of microglia, and activation of the TLR4/MyD88/NF-κB signaling pathway in rat brain. Significantly, intracerebroventricular injection of HPX reduced the above effects. Hemin induced boost of TNF-α, IL-1ß and IL-6 in BV2 cells, as well as apoptosis in HT22 cells. Notably, when HT22 cells were cocultured with BV2 cells, apoptosis was significantly increased. Hemin also induced activation of the TLR4/MyD88/NF-κB signaling pathway and increased the M1 surface marker CD86 in BV2 cells, and inhibiting this pathway reduced the inflammatory responses. CONCLUSIONS: Free heme induces cognitive impairment, and the underlying mechanism may involve neuronal apoptosis and microglial inflammation via the TLR4/MyD88/NF-κB signaling pathway. HPX may have potential therapeutic effects. Video Abstract.

Multimodal Model to Predict Tissue-to-Blood Partition Coefficients of Chemicals in Mammals and Fish.

Tissue-to-blood partition coefficients (Ptb) are key parameters for assessing toxicokinetics of xenobiotics in organisms, yet their experimental data were lacking. Experimental methods for measuring Ptb values are inefficient, underscoring the urgent need for prediction models. However, most existing models failed to fully exploit Ptb data from diverse sources, and their applicability domain (AD) was limited. The current study developed a multimodal model capable of processing and integrating textual (categorical features) and numerical information (molecular descriptors/fingerprints) to simultaneously predict Ptb values across various species, tissues, blood matrices, and measurement methods. Artificial neural network algorithms with embedding layers were used for the multimodal modeling. The corresponding unimodal models were developed for comparison. Results showed that the multimodal model outperformed unimodal models. To enhance the reliability of the model, a method considering categorical features, weighted molecular similarity density, and weighted inconsistency in molecular activities of structure-activity landscapes was used to characterize the AD. The model constrained by the AD exhibited better prediction accuracy for the validation set, with the determination coefficient, root mean-square error, and mean absolute error being 0.843, 0.276, and 0.213 log units, respectively. The multimodal model coupled with the AD characterization can serve as an efficient tool for internal exposure assessment of chemicals.

Effectiveness of perioperative low-dose esketamine infusion for postoperative pain management in pediatric urological surgery: a prospective clinical trial.

BACKGROUND: Postoperative pain is common in pediatric urological surgery. The study assess the impact of perioperative intravenous infusion of low-dose esketamine on postoperative pain in pediatric urological surgery. METHODS: Pediatric patients (n = 80) undergoing urological surgery were randomized into four groups. Patients in the control group were administered an analgesic pump containing only hydromorphone at a dose of 0.1 mg/kg (Hydromorphone Group 1, H1) or 0.15 mg/kg (Hydromorphone Group 2, H2). Patients in the experimental group were injected intravenously with 0.3 mg/kg of esketamine (Esketamine group 1, ES1) or equal volume of saline (Esketamine Group 2, ES2) during anesthesia induction. Esketamine 1.0 mg/kg and hydromorphone 0.1 mg/kg were added to the analgesic pump. Face, Leg, Activity, Crying, and Comfort (FLACC) scale or the Numerical Rating Scale (NRS) and adverse effects were recorded at 2, 6, 24, and 48 h postoperatively. Additionally, total and effective PCA button presses were recorded. RESULTS: In comparison to the H1 group, the pain scores were notably reduced at all postoperative time points in both the ES1 and H2 groups. The ES2 group exhibited lower pain scores only at 24 and 48 h postoperatively. When compared to the H2 group, there were no significant differences in pain scores at various postoperative time points in the ES2 group. However, the ES1 group demonstrated significantly lower pain scores at 6, 24 and 48 h postoperatively, and these scores were also significantly lower than those observed in the ES2 group. The total and effective number of PCA button presses in the ES1, ES2 and H2 group were lower than that in the H1 group (P < 0.001). The incidence of adverse effects within 48 h after surgery was 15% in ES1, 22% in ES2, 58% in H1, and 42% in H2, respectively (P = 0.021). CONCLUSIONS: The use of low-dose esketamine infusion in analgesia pump can effectively alleviates postoperative pain in pediatric urological patients, leading to a significant reduction in the number of analgesic pump button press. The combined approach of perioperative anesthesia induction and analgesia pump administration is recommended for optimal pain management in these patients. TRIAL REGISTRATION: Chinese Clinical Trial Registry- ChiCTR2300073879 (24/07/2023).

Association of spinal-pelvic parameters with recurrence of lumbar disc herniation after endoscopic surgery: a retrospective case-control study.

PURPOSE: This study aimed to investigate the relationship between spinal-pelvic parameters and recurrence of lumbar disc herniation (rLDH) after percutaneous endoscopic lumbar discectomy (PELD) through a retrospective case-control study. METHODS: Patients who underwent PELD for single-segment LDH at our hospital were included in this study. The relationship between sagittal balance parameters of the spine and recurrence was analysed through correlation analysis, and ROC curves were plotted. The baseline characteristics, sagittal balance parameters of the spine and radiological parameters of the case and control groups were compared, and the relationship between sagittal balance parameters of the spine and recurrence of rLDH after PELD was determined through univariate and multivariate logistic regression analysis. RESULTS: Correlation analysis showed that PI and ∆PI-LL were negatively correlated with grouping (r = -0.090 and -0.120, respectively, P = 0.001 and 0.038). ROC curve analysis showed that the area under the curve (ROC-AUC) for predicting rLDH based on PI was 0.65 (CI95% = 0.598, 0.720), with a cut-off of 50.26°. The ROC-AUC for predicting rLDH based on ∆PI-LL was 0.56 (CI95% = 0.503, 0.634), with a cut-off of 28.21°. Multivariate logistic regression analysis showed that smoking status (OR = 2.667, P = 0.008), PI ≤ 50.26 (OR = 2.161, P = 0.009), ∆PI-LL ≤ 28.21 (OR = 3.185, P = 0.001) and presence of Modic changes (OR = 4.218, P = 0.001) were independent risk factors, while high DH (OR = 0.788, P = 0.001) was a protective factor. CONCLUSION: PI < 50.26 and ∆PI-LL < 28.21 were risk factors for recurrence of lumbar disc herniation after spinal endoscopic surgery and had some predictive value for post-operative recurrence.

Time Kinetics and prognosis roles of calcitonin after surgery for medullary thyroid carcinoma.

BACKGROUND: Medullary thyroid carcinoma (MTC) is a malignant tumor with low incidence. Currently, most studies have focused on the prognostic risk factors of MTC, whatever, time kinetic and risk factors related to calcitonin normalization (CN) and biochemical persistence/recurrence (BP) are yet to be elucidated. METHODS: A retrospective study was conducted for 190 MTC patients. Risk factors related to calcitonin normalization (CN) and biochemical persistence/recurrence (BP) were analyzed. The predictors of calcitonin normalization time (CNT) and biochemical persistent/recurrent time (BPT) were identified. Further, the prognostic roles of CNT and BPT were also demonstrated. RESULTS: The 5- and 10-year DFS were 86.7% and 70.2%, respectively. The 5- and 10-year OS were 97.6% and 78.8%, respectively. CN was achieved in 120 (63.2%) patients, whereas BP was presented in 76 (40.0%) patients at the last follow up. After curative surgery, 39 (32.5%) and 106 (88.3%) patients achieved CN within 1 week and 1 month. All patients who failed to achieve CN turned to BP over time and 32/70 of them developed structural recurrence. The median time of CNT and BPT was 1 month (1 day to 84 months) and 6 month (3 day to 63months), respectively. LNR > 0.23 and male gender were independent predictors for CN and BP. LNR > 0.23 (Hazard ratio (HR), 0.24; 95% CI,0.13-0.46; P < 0.01) and male gender (HR, 0.65; 95% CI, 0.42-0.99; P = 0.045) were independent predictors for longer CNT. LNR > 0.23 (HR,5.10; 95% CI,2.15-12.11; P < 0.01) was still the strongest independent predictor followed by preoperative serum Ctn > 1400ng/L (HR,2.34; 95% CI,1.29-4.25; P = 0.005) for shorter BPT. In survival analysis, primary tumor size > 2 cm (HR, 5.81; 95% CI,2.20-15.38; P < 0.01), CNT > 1 month (HR, 5.69; 95% CI, 1.17-27.61; P = 0.031) and multifocality (HR, 3.10; 95% CI, 1.45-6.65; P = 0.004) were independent predictor of DFS. CONCLUSION: Early changes of Ctn after curative surgery can predict the long-term risks of biochemical and structural recurrence, which provide a useful real-time prognostic information. LNR significantly affect the time kinetic of biochemical prognosis. Tumor burden and CNT play a crucial role in MTC survival, the intensity of follow-up must be tailored accordingly.

Gigantic vortical differential scattering as a monochromatic probe for multiscale chiral structures.

Spin angular momentum of light is vital to investigate enantiomers characterized by circular dichroism (CD), widely adopted in biology, chemistry, and material science. However, to discriminate chiral materials with multiscale features, CD spectroscopy normally requires wavelength-swept laser sources as well as wavelength-specific optical accessories. Here, we experimentally demonstrate an orbital-angular-momentum-assisted approach to yield chiroptical signals with monochromatic light. The gigantic vortical differential scattering (VDS) of ∼120% is achieved on intrinsically chiral microstructures fabricated by femtosecond laser. The VDS measurements can robustly generate chiroptical properties on microstructures with varying geometric features (e.g., diameters and helical pitches) and detect chiral molecules with high sensitivity. This VDS scheme lays a paradigm-shift pavement toward efficiently chiroptical discrimination of multiscale chiral structures with photonic orbital angular momentum. It simplifies and complements the conventional CD spectroscopy, opening possibilities for measuring weak optical chirality, especially on mesoscale chiral architectures and macromolecules.

The Spatiotemporal Dynamics of Insect Predator-Prey System Incorporating Refuge Effect.

The insect predator-prey system mediates several feedback mechanisms which regulate species abundance and spatial distribution. However, the spatiotemporal dynamics of such discrete systems with the refuge effect remain elusive. In this study, we analyzed a discrete Holling type II model incorporating the refuge effect using theoretical calculations and numerical simulations, and selected moths with high and low growth rates as two exemplifications. The result indicates that only the flip bifurcation opens the routes to chaos, and the system undergoes four spatiotemporally behavioral patterns (from the frozen random pattern to the defect chaotic diffusion pattern, then the competition intermittency pattern, and finally to the fully developed turbulence pattern). Furthermore, as the refuge effect increases, moths with relatively slower growth rates tend to maintain stability at relatively low densities, whereas moths with relatively faster growth rates can induce chaos and unpredictability on the population. According to the theoretical guidance of this study, the refuge effect can be adjusted to control pest populations effectively, which provides a new theoretical perspective and is a feasible tool for protecting crops.

A Smart DNA Hydrogel Enables Synergistic Immunotherapy and Photodynamic Therapy of Melanoma.

Immunotherapy faces insufficient immune activation and limited immune effectiveness. Herein, we report a smart DNA hydrogel that enables the release of multivalent functional units at the tumor site to enhance the efficacy of immunotherapy. The smart DNA hydrogel was assembled from two types of ultra-long DNA chains synthesized via rolling circle amplification. One DNA chain contained immune adjuvant CpG oligonucleotides and polyaptamers for loading natural killer cell-derived exosomes; the other chain contained multivalent G-quadruplex for loading photodynamic agents. DNA chains formed DNA hydrogel through base-pairing. HhaI restriction endonuclease sites were designed between functional units. Upon stimuli in the tumor sites, the hydrogel was effectively cleaved by the released HhaI and disassembled into functional units. Natural killer cell-derived exosomes played an anti-tumor role, and the CpG oligonucleotide activated antigen-presenting cells to enhance the immunotherapy. Besides the tumor-killing effect of photodynamic therapy, the generated cellular debris acted as an immune antigen to further enhance the immunotherapeutic effect. In a mouse melanoma orthotopic model, the smart DNA hydrogel as a localized therapeutic agent, achieved a remarkable tumor suppression rate of 91.2 %. The smart DNA hydrogel exhibited enhanced efficacy of synergistic immunotherapy and photodynamic therapy, expanding the application of DNA materials in biomedicine.

Development of an Integrated Platform for the Simultaneous Enrichment and Characterization of N- and O-Linked Intact Glycopeptides.

Both N-linked glycosylation and O-linked glycosylation play essential roles in the onset and progression of various diseases including cancer, and N-/O-linked site-specific glycans have been proven to be promising biomarkers for the discrimination of cancer. However, the micro-heterogeneity and low abundance nature of N-/O-linked glycosylation, as well as the time-consuming and tedious procedures for the enrichment of O-linked intact glycopeptides, pose great challenges for their efficient and accurate characterization. In this study, we developed an integrated platform for the simultaneous enrichment and characterization of N- and O-linked intact glycopeptides from the same serum sample. By fine-tuning the experimental conditions, we demonstrated that this platform allowed the selective separation of N- and O-linked intact glycopeptides into two fractions, with 85.1% O-linked intact glycopeptides presented in the first fraction and 93.4% N-linked intact glycopeptides presented in the second fraction. Determined with high reproducibility, this platform was further applied to the differential analysis of serum samples of gastric cancer and health control, which revealed 17 and 181 significantly changed O-linked and N-linked intact glycopeptides. Interestingly, five glycoproteins containing both significant regulation of N- and O-glycosylation were observed, hinting potential co-regulation of different types of glycosylation during tumor progress. In summary, this integrated platform opened a potentially useful avenue for the global analysis of protein glycosylation and can serve as a useful tool for the characterization of N-/O-linked intact glycopeptides at the proteomics scale.

MCP-1/CCR2 axis is involved in the regulation of γδT cells in lupus nephritis.

γδT cells are important innate immune cells that are involved in the occurrence and development of autoimmune diseases such as systemic lupus erythematosus (SLE). Lupus nephritis (LN) is a serious complication of SLE, characterized by the accumulation of immune cells (including γδT cells) in the target organs to participate in the disease process. Therefore, clarifying how γδT cells chemotactically migrate to target organs may be a key to developing therapeutic methods against LN. Enzyme-linked immunosorbent assay (ELISA) was used to detect serum levels of chemokines in LN patients and healthy controls. Real-time polymerase chain reaction (RT-PCR) and flow cytometry were used to measure the expression of chemokine receptors on the surface of γδT cells. The chemotactic migration ability of γδT cells was detected by Transwell assay. Signalling pathway activation of γδT cells was detected by Automated Capillary Electrophoresis Immunoassay and flow cytometry. The serum levels of chemokines, including monocyte chemoattractant protein-1 (MCP-1) in LN patients, were significantly increased. CCR2, the receptor of MCP-1, was also highly expressed on the surface of peripheral γδT cells in LN patients. In addition, the exogenous addition of MCP-1 can enhance chemotactic migration of γδT cells in LN patients. MCP-1 could activate STAT3 signalling in LN patients' peripheral γδT cells. γδT cells might participate in the pathogenesis of LN through MCP-1/CCR2 axis. This finding provides new opportunities for developing treatment methods against LN by targeting MCP-1/CCR2 axis.

Machine Learning Model for Screening Thyroid Stimulating Hormone Receptor Agonists Based on Updated Datasets and Improved Applicability Domain Metrics.

Machine learning (ML) models for screening endocrine-disrupting chemicals (EDCs), such as thyroid stimulating hormone receptor (TSHR) agonists, are essential for sound management of chemicals. Previous models for screening TSHR agonists were built on imbalanced datasets and lacked applicability domain (AD) characterization essential for regulatory application. Herein, an updated TSHR agonist dataset was built, for which the ratio of active to inactive compounds greatly increased to 1:2.6, and chemical spaces of structure-activity landscapes (SALs) were enhanced. Resulting models based on 7 molecular representations and 4 ML algorithms were proven to outperform previous ones. Weighted similarity density (ρs) and weighted inconsistency of activities (IA) were proposed to characterize the SALs, and a state-of-the-art AD characterization methodology ADSAL{ρs, IA} was established. An optimal classifier developed with PubChem fingerprints and the random forest algorithm, coupled with ADSAL{ρs ≥ 0.15, IA ≤ 0.65}, exhibited good performance on the validation set with the area under the receiver operating characteristic curve being 0.984 and balanced accuracy being 0.941 and identified 90 TSHR agonist classes that could not be found previously. The classifier together with the ADSAL{ρs, IA} may serve as efficient tools for screening EDCs, and the AD characterization methodology may be applied to other ML models.

Applicability Domains Based on Molecular Graph Contrastive Learning Enable Graph Attention Network Models to Accurately Predict 15 Environmental End Points.

In silico models for predicting physicochemical properties and environmental fate parameters are necessary for the sound management of chemicals. This study employed graph attention network (GAT) algorithms to construct such models on 15 end points. The results showed that the GAT models outperformed the previous state-of-the-art models, and their performance was not influenced by the presence or absence of compounds with certain structures. Molecular similarity density (ρs) was found to be a key metrics characterizing data set modelability, in addition to the proportion of compounds at activity cliffs. By introducing molecular graph (MG) contrastive learning, MG-based ρs and molecular inconsistency in activities (IA) were calculated and employed for characterizing the structure-activity landscape (SAL)-based applicability domain ADSAL{ρs, IA}. The GAT models coupled with ADSAL{ρs, IA} significantly improved the prediction coefficient of determination (R2) on all the end points by an average of 14.4% and enabled all the end points to have R2 > 0.9, which could hardly be achieved previously. The models were employed to screen persistent, mobile, and/or bioaccumulative chemicals from inventories consisting of about 106 chemicals. Given the current state-of-the-art model performance and coverage of the various environmental end points, the constructed models with ADSAL{ρs, IA} may serve as benchmarks for future efforts to improve modeling efficacy.

Identification and Analysis of the Expression of the PIP5K Gene Family in Tomatoes.

To explore the function of phosphatidylinositol 4-phosphate 5-kinase (PIP5K) in tomatoes, members of the tomato PIP5K family were identified and characterized using bioinformatic methods, and their expression patterns were also analyzed under salt stress and in different tissues. Twenty-one PIP5K members-namely, SlPIP5K1-SlPIP5K21-were identified from ten chromosomes, and these were divided into three groups according to a phylogenetic analysis. Further bioinformatic analysis showed four pairs of collinear relationships and fragment replication events among the SlPIP5K family members. To understand the possible roles of the SlPIP5Ks, a cis-acting element analysis was conducted, which indicated that tomato PIP5Ks could be associated with plant growth, hormones, and stress responses. We further validated the results of the in silico analysis by integrating RNA-seq and qRT-PCR techniques for salt- and hormone-treated tomato plants. Our results showed that SlPIP5K genes exhibited tissue- and treatment-specific patterns, and some of the SlPIP5Ks exhibited significantly altered expressions after our treatments, suggesting that they might be involved in these stresses. We selected one of the SlPIP5Ks that responded to our treatments, SlPIP5K2, to further understand its subcellular localization. Our results showed that SlPIP5K2 was located on the membrane. This study lays a foundation for the analysis of the biological functions of the tomato SlPIP5K genes and can also provide a theoretical basis for the selection and breeding of new tomato varieties and germplasm innovation, especially under salt stress.

The neuroprotective mechanism of sevoflurane in rats with traumatic brain injury via FGF2.

BACKGROUND: Traumatic brain injury (TBI) is a kind of acquired brain injury, which is caused by external mechanical forces. Moreover, the neuroprotective role of sevoflurane (Sevo) has been identified in TBI. Therefore, this research was conducted to figure out the mechanism of Sevo in TBI via FGF2. METHODS: The key factors of neuroprotective effects of Sevo in TBI rats were predicted by bioinformatics analysis. A TBI model was induced on rats that then inhaled Sevo for 1 h and grouped via lentivirus injection. Modified Neurological Severity Score was adopted to evaluate neuronal damage in rats, followed by motor function and brain water content measurement. FGF2, EZH2, and HES1 expression in brain tissues was evaluated by immunofluorescence staining, and expression of related genes and autophagy factors by RT-qPCR and Western blot analysis. Methylation-specific PCR was performed to assess HES1 promoter methylation level, and ChIP assay to detect the enrichment of EZH2 in the HES1 promoter. Neuronal damage was assessed by cell immunofluorescence staining, and neuronal apoptosis by Nissl staining, TUNEL staining, and flow cytometry. RESULTS: Sevo diminished brain edema, improved neurological scores, and decreased neuronal apoptosis and autophagy in TBI rats. Sevo preconditioning could upregulate FGF2 that elevated EZH2 expression, and EZH2 bound to the HES1 promoter to downregulate HES1 in TBI rats. Also, FGF2 or EZH2 overexpression or HES silencing decreased brain edema, neurological deficits, and neuronal autophagy and apoptosis in Sevo-treated TBI rats. CONCLUSIONS: Our results provided a novel insight to the neuroprotective mechanism of Sevo in TBI rats by downregulating HES1 via FGF2/EZH2 axis activation.

FLT3 inhibition upregulates HDAC8 via FOXO to inactivate p53 and promote maintenance of FLT3-ITD+ acute myeloid leukemia.

Internal tandem duplication (ITD) mutations within the FMS-like receptor tyrosine kinase-3 (FLT3) can be found in up to 25% to 30% of acute myeloid leukemia (AML) patients and confer a poor prognosis. Although FLT3 tyrosine kinase inhibitors (TKIs) have shown clinical responses, they cannot eliminate primitive FLT3-ITD+ AML cells, which are potential sources of relapse. Therefore, elucidating the mechanisms underlying FLT3-ITD+ AML maintenance and drug resistance is essential to develop novel effective treatment strategies. Here, we demonstrate that FLT3 inhibition induces histone deacetylase 8 (HDAC8) upregulation through FOXO1- and FOXO3-mediated transactivation in FLT3-ITD+ AML cells. Upregulated HDAC8 deacetylates and inactivates p53, leading to leukemia maintenance and drug resistance upon TKI treatment. Genetic or pharmacological inhibition of HDAC8 reactivates p53, abrogates leukemia maintenance, and significantly enhances TKI-mediated elimination of FLT3-ITD+ AML cells. Importantly, in FLT3-ITD+ AML patient-derived xenograft models, the combination of FLT3 TKI (AC220) and an HDAC8 inhibitor (22d) significantly inhibits leukemia progression and effectively reduces primitive FLT3-ITD+ AML cells. Moreover, we extend these findings to an AML subtype harboring another tyrosine kinase-activating mutation. In conclusion, our study demonstrates that HDAC8 upregulation is an important mechanism to resist TKIs and promote leukemia maintenance and suggests that combining HDAC8 inhibition with TKI treatment could be a promising strategy to treat FLT3-ITD+ AML and other tyrosine kinase mutation-harboring leukemias.

Yellow pumped Pr3+-doped ZBLAN fiber laser at 1015 nm.

To date, lasing in the visible to near-infrared wavelengths has been studied for praseodymium-doped fluoride fibers with the upper energy level of 3P0. In this Letter, a fiber laser operating at 1015 nm has been realized for the first time, to the best of our knowledge, which confirms a new mechanism where 1D2 can be the upper energy level. A maximum output power of 241 mW, with a slope efficiency of 30%, was achieved by using a 150-cm-long active fiber pumped at a maximum pump power of 823 mW. Furthermore, the broad emission spectra of Pr3+-doped fibers in the near-infrared band have been exploited as new, to the best of our knowledge, spectral sources.

Graph Attention Network Model with Defined Applicability Domains for Screening PBT Chemicals.

In silico models for screening environmentally persistent, bio-accumulative, and toxic (PBT) substances are necessary for sound management of chemicals. Due to the complex structure-activity landscapes (SALs) on the PBT attributes, previous models for screening PBT chemicals lack either applicability domain (AD) characterizations or interpretability, restricting their applications. Herein, graph attention networks (GATs), a novel neural network architecture, were introduced to construct models for screening PBT chemicals. Results show that the GAT model not only outperformed those in previous studies but also exhibited interpretability since it optimizes attention weight parameters (PAW) that indicate contributions of each atom to the PBT attributes. An AD characterization termed ADFP-AC, which considers both molecular fingerprint (FP) similarities and compounds at activity cliffs (ACs) of SALs, was proposed to describe the ADs, which further assured the performance of the GAT model. Eight previously unidentified classes of compounds were identified as PBT chemicals from the Inventory of Existing Chemical Substances in China. The GAT model together with the ADFP-AC characterization may serve as efficient tools for screening PBT chemicals, and the modeling methodology can be applied to other physicochemical, environmental, behavioral, and toxicological parameters of chemicals that are necessary for their risk assessment and management.