Discovery of Novel Non-nucleoside DOT1LR231Q Inhibitors with Improved Pharmacokinetic Properties and Anti-lung Cancer Efficacy.

Given the considerable potential of DOT1LR231Q inhibitors in lung cancer therapy and the problematic pharmacokinetics of nucleoside inhibitors, our group launched a development program of non-nucleoside DOT1LR231Q inhibitors to improve the pharmacokinetic properties. Herein, two series of non-nucleoside compounds bearing piperidine or 3-(aminomethyl)pyrrolidin-3-ol as "ribose mimics" were designed and evaluated through antiproliferation assay and western blot analysis. The optimal TB22 inhibited the proliferation of H460R231Q cells with an IC50 value of 2.85 µM, about 13-fold more potent than SGC0946. Notably, TB22 demonstrated significant in vivo efficacy (TGI = 60.57%) in H460R231Q cell-derived xenograft models and improved pharmacokinetic properties (t1/2 = 6.06 ± 2.94 h and CL = 55.18 ± 8.56 mL/kg/min). Moreover, a mechanism study validated that TB22 suppressed malignant phenotypes of lung cancer cells harboring R231Q mutation via the MAPK/ERK signaling pathway. This work provides a promising molecule for lung cancer therapy in favor of clinical patients.

Discovery of first-in-class DOT1L inhibitors against the R231Q gain-of-function mutation in the catalytic domain with therapeutic potential of lung cancer.

Recent research certified that DOT1L and its mutations represented by R231Q were potential targets for the treatment of lung cancer. Herein, a series of adenosine-containing derivatives were identified with DOT1LR231Q inhibition through antiproliferation assay and Western blot analysis in the H460R231Q cell. The most promising compound 37 significantly reduced DOT1LR231Q mediated H3K79 methylation and effectively inhibited the proliferation, self-renewal, migration, and invasion of lung cancer cell lines at low micromolar concentrations. The cell permeability and cellular target engagement of 37 were verified by both CETSA and DARTS assays. In the H460R231Q OE cell-derived xenograft (CDX) model, 37 displayed pronounced tumor growth inhibition after intraperitoneal administration at 20 mg/kg dose for 3 weeks (TGI = 54.38%), without obvious toxicities. A pharmacokinetic study revealed that 37 possessed tolerable properties (t 1/2 = 1.93 ± 0.91 h, F = 97.2%) after intraperitoneal administration in rats. Mechanism study confirmed that 37 suppressed malignant phenotypes of lung cancer carrying R231Q gain-of-function mutation via the MAPK/ERK signaling pathway. Moreover, analysis of the binding modes between molecules and DOT1LWT/R231Q proteins put forward the "Induced-fit" allosteric model in favor to the discovery of potent DOT1L candidates.

Phase Behavior Modulation of a Unary DNA Origami System through Allosteric Stimuli.

A unary system is the most conceptually concise design for conducting self-assembly. However, in most DNA-guided self-assembly schemes, a unary system has rarely been adopted because of the inherent challenge of strictly decoupling the monomer synthesis process from the assembly process, which may directly lead to the inaccurate control over assembly. Herein, we provide a multi-stimulus-triggered assembly strategy based on the DNA origami structure, which allows the unary system to realize controllable crystallization and phase transition by exerting allosteric stimuli. We intentionally introduced a specific DNA stimulus to convert the self-aggregation of functionalized groups into the connection of nearby monomers, thus producing multidimensional high-quality crystals. Furthermore, this unary system can undergo a phase transition from simple cubic to face-centered cubic with the introduction of more cation stimuli. We believe that this dynamic stimulation strategy can offer a novel solution for fabricating materials with on-demand modulation.

Causal role of frontocentral beta oscillation in comprehending linguistic communicative functions.

Linguistic communication is often considered as an action serving the function of conveying the speaker's goal to the addressee. Although neuroimaging studies have suggested a role of the motor system in comprehending communicative functions, the underlying mechanism is yet to be specified. Here, by two EEG experiments and a tACS experiment, we demonstrate that the frontocentral beta oscillation, which represents action states, plays a crucial part in linguistic communication understanding. Participants read scripts involving two interlocutors and rated the interlocutors' attitudes. Each script included a critical sentence said by the speaker expressing a context-dependent function of either promise, request, or reply to the addressee's query. These functions were behaviorally discriminated, with higher addressee's will rating for the promise than for the reply and higher speaker's will rating for the request than for the reply. EEG multivariate analyses showed that different communicative functions were represented by different patterns of the frontocentral beta activity but not by patterns of alpha activity. Further tACS results showed that, relative to alpha tACS and sham stimulation, beta tACS improved the predictability of communicative functions of request or reply, as measured by the speaker's will rating. These results convergently suggest a causal role of the frontocentral beta activities in comprehending linguistic communications.

Specified functions of the first two fixations in face recognition: Sampling the general-to-specific facial information.

Visual perception is enacted and constrained by the constantly moving eyes. Although it is well known that the first two fixations are crucial for face recognition, the function of each fixation remains unspecified. Here we demonstrate a central-to-divergent pattern of the two fixations and specify their functions: Fix I clustered along the nose bridge to cover the broad facial information; Fix II diverged to eyes, nostrils, and lips to get the local information. Fix II correlated more than Fix I with the differentiating information between faces and contributed more to recognition responses. While face categories can be significantly discriminated by Fix II's but not Fix I's patterns alone, the combined patterns of the two yield better discrimination. Our results suggest a functional division and collaboration of the two fixations in sampling the general-to-specific facial information and add to understanding visual perception as an active process undertaken by structural motor programs.

NEMF-mediated CAT-tailing defines distinct branches of translocation-associated quality control.

Ribosome stalling during co-translational translocation at the endoplasmic reticulum (ER) causes translocon clogging and impairs ER protein biogenesis. Mammalian cells resolve translocon clogging vial a poorly characterized translocation-associated quality control (TAQC) process. Here, we combine genome-wide CRISPR screen with live cell imaging to dissect the molecular linchpin of TAQC. We show that substrates translated from mRNAs bearing a ribosome stalling poly(A) sequence are degraded by lysosomes and the proteasome, while substrates encoded by non-stop mRNAs are degraded by an unconventional ER-associated degradation (ERAD) mechanism involving ER-to-Golgi trafficking and KDEL-dependent substrate retrieval. The triaging diversity appears to result from the heterogeneity of NEMF-mediated CATylation, because a systematic characterization of representative CAT-tail mimetics establishes an AT-rich tail as a "degron" for ERAD, whereas an AG-rich tail can direct a secretory protein to the lysosome. Our study reveals an unexpected protein sorting function for CAT-tailing that safeguards ER protein biogenesis.

Comparative efficacy of non-pharmacological interventions for anxiety in adult intensive care unit patients: A systematic review and network meta-analysis.

BACKGROUND: The primary goal of the intensive care unit is to the anxiety of conscious patients is often ignored in the care unit. AIM: The purpose of this study was to assess the efficacy of various non-pharmacological therapies for anxiety disorders in adult patients in the intensive care unit, in order to enhance humanistic care in the intensive care unit and to promote the patients' physical and mental recovery together. STUDY DESIGN: We conducted a systematic and comprehensive search of the literature in five databases (including the Cochrane Library, PubMed, EBSCO, Web of Science, and Embase) covering nearly a decade for randomized controlled trials of non-pharmacological therapies to reduce anxiety in adult intensive care unit patients. Two researchers independently assessed the quality of the literature, collected and condensed the data, and used STATA software to perform a network meta-analysis. The ranking probabilities for each intervention were calculated using the Surface under the Cumulative Ranking (SUCRA) method. The study protocol was registered with PROSPERO. RESULTS: This study ultimately included 26 randomized controlled trials involving 2791 adult ICU patients. Non-pharmacological interventions for anxiety in adult ICU patients included music therapy, aromatherapy, ICU diary, virtual reality, massage therapy, monitoring room diary, and health education. when compared to the control group (usual care), aromatherapy + music therapy [MD = -2.65, 95% CI (-4.76, -0.54)] (P = 0.0137) and music therapy [MD = -1.77, 95% CI (-3.40, -0.13)] (P = 0.0338) were superior in reducing anxiety in adult ICU patients. The results of the network meta-analysis showed that aromatherapy combined with music therapy significantly alleviated anxiety in adult ICU patients (SUCRA: 99.8%). CONCLUSIONS: Music therapy combined with aromatherapy has demonstrated superior effectiveness compared to other non-pharmacological interventions for reducing anxiety in awake adults in the ICU. However, the underlying mechanisms of this combined therapy require further exploration. RELEVANCE TO CLINICAL PRACTICE: Future research on the use of music therapy combined with aromatherapy in the care unit may help reduce anxiety in patients while fostering their physical and mental healing; however, individual variances and unique clinical circumstances must be considered.

Multilevel network for large deformation image registration based on feature consistency and flow normalization.

BACKGROUND: Deformable image registration is an essential technique of medical image analysis, which plays important roles in several clinical applications. Existing deep learning-based registration methods have already achieved promising performance for the registrations with small deformations, while it is still challenging to deal with the large deformation registration due to the limits of the image intensity-similarity-based objective function. PURPOSE: To achieve the image registration with large-scale deformations, we proposed a multilevel network architecture FCNet to gradually refine the registration results based on semantic feature consistency constraint and flow normalization (FN) strategy. METHODS: At each level of FCNet, the architecture is mainly composed to a FeaExtractor, a FN module, and a spatial transformation module. FeaExtractor consists of three parallel streams which are used to extract the individual features of fixed and moving images, as well as their joint features, respectively. Using these features, the initial deformation field is estimated, which passes through a FN module to refine the deformation field based on the difference map of deformation filed between two adjacent levels. This allows the FCNet to progressively improve the registration performance. Finally, a spatial transformation module is used to get the warped image based on the deformation field. Moreover, in addition to the image intensity-similarity-based objective function, a semantic-feature consistency constraint is also introduced, which can further promote the alignments by imposing the similarity between the fixed and warped image features. To validate the effectiveness of the proposed method, we compared our method with the state-of-the-art methods on three different datasets. In EMPIRE10 dataset, 20, 3, and 7 fixed and moving 3D computer tomography (CT) image pairs were used for training, validation, and testing respectively; in IXI dataset, atlas to individual image registration task was performed, with 3D MR images of 408, 58, and 115 individuals were used for training, validation, and testing respectively; in the in-house dataset, patient to atlas registration task was implemented, with the 3D MR images of 94, 3, and 15 individuals being training, validation, and testing sets, respectively. RESULTS: The qualitative and quantitative comparison results demonstrated that the proposed method is beneficial for handling large deformation image registration problems, with the DSC and ASSD improved by at least 1.0% and 25.9% on EMPIRE10 dataset. The ablation experiments also verified the effectiveness of the proposed feature combination strategy, feature consistency constraint, and FN module. CONCLUSIONS: Our proposed FCNet enables multiscale registration from coarse to fine, surpassing existing SOTA registration methods and effectively handling long-range spatial relationships.

Leveraging cell death patterns to predict metastasis in prostate adenocarcinoma and targeting PTGDS for tumor suppression.

Metastasis is the major cause of treatment failure in patients with prostate adenocarcinoma (PRAD). Diverse programmed cell death (PCD) patterns play an important role in tumor metastasis and hold promise as predictive indicators for PRAD metastasis. Using the LASSO Cox regression method, we developed PCD score (PCDS) based on differentially expressed genes (DEGs) associated with PCD. Clinical correlation, external validation, functional enrichment analysis, mutation landscape analysis, tumor immune environment analysis, and immunotherapy analysis were conducted. The role of Prostaglandin D2 Synthase (PTGDS) in PRAD was examined through in vitro experiments, single-cell, and Mendelian randomization (MR) analysis. PCDS is elevated in patients with higher Gleason scores, higher T stage, biochemical recurrence (BCR), and higher prostate-specific antigen (PSA) levels. Individuals with higher PCDS are prone to metastasis, metastasis after BCR, BCR, and castration resistance. Moreover, PRAD patients with low PCDS responded positively to immunotherapy. Random forest analysis and Mendelian randomization analysis identified PTGDS as the top gene associated with PRAD metastasis and in vitro experiments revealed that PTGDS was considerably downregulated in PRAD cells against normal prostate cells. Furthermore, the overexpression of PTGDS was found to suppress the migration, invasion, proliferationof DU145 and LNCaP cells. To sum up, PCDS may be a useful biomarker for forecasting the possibility of metastasis, recurrence, castration resistance, and the efficacy of immunotherapy in PRAD patients. Additionally, PTGDS was identified as a viable therapeutic target for the management of PRAD.

Correlation between the gut microbiota characteristics of hosts with severe acute pancreatitis and secondary intra-abdominal infection.

Objective: The objective of the study is to investigate the changes in the composition of intestinal microecology in severe acute pancreatitis (SAP) patients with or without intra-abdominal infection and also to analyze the expression of antibiotic resistance genes to provide evidence for early warning of infectious diseases and the rational use of antibiotics. Methods: Twenty patients with SAP were enrolled in the study. According to whether the enrolled patients had a secondary intra-abdominal infection, they were divided into two groups, each consisting of 10 patients. Stool specimens were collected when the patients were admitted to the emergency intensive care unit (EICU), and nucleic acid extraction was performed. Next-generation gene sequencing was used to compare the differences in intestinal microflora diversity and drug resistance gene expression between the two groups. Results: The gut microbiota of patients in the infection group exhibited distribution on multiple clustered branches with some intra-group heterogeneity, and their flora diversity was compromised. The infected group showed an enrichment of various opportunistic bacteria in the gut microbiota, along with a high number of metabolic functions, stress functions to external signals, and genes associated with pathogenesis. Drug resistance genes were expressed in the gut microbiota of both groups, but their abundance was significantly lower in the non-infected group. Conclusion: The intestinal microbiota of patients in the infection group exhibited distribution on multiple clustered branches with some intra-group heterogeneity, and their flora diversity was compromised. Additionally, drug resistance genes were expressed in the gut microbiota of both groups, although their abundance was significantly lower in the non-infected group.

IVIM parameters mapping with artificial neural network based on mean deviation prior.

BACKGROUND: The diffusion and perfusion parameters derived from intravoxel incoherent motion (IVIM) imaging provide promising biomarkers for noninvasively quantifying and managing various diseases. Nevertheless, due to the distribution gap between simulated and real datasets, the out-of-distribution (OOD) problem occurred in supervised learning-based methods degrades their performance and hinders their real applications. PURPOSE: To address the OOD problem in supervised methods and to further improve the accuracy and stability of IVIM parameter estimation, this work proposes a novel learning framework called IterANN, based on mean deviation prior (MDP) between training and estimated IVIM parameters on the test set. METHODS: Specifically, MDP indicates that the mean of the estimated IVIM parameters always locates between the mean of IVIM parameters in the test and train sets. In IterANN, we adopt a very simple artificial neural network (ANN) architecture of two hidden layers with 12 neurons per hidden layer, an input layer containing the signals acquired at multiple b-values and an output layer composed of three IVIM parameters ( D $D$ , F $F$ and D S t a r $DStar$ ). Inspired by MDP, the distribution of IVIM parameters in the training set (simulated data) is iteratively updated so that their mean gradually approaches the predicted values of the real data. This aims to achieve a strong correlation between the simulated data and the real data. To validate the effectiveness of IterANN, we compare it with several methods on both simulation and real acquisition datasets, including 21 healthy and 3 tumor subjects, in terms of residual errors of IVIM parameters or DW signals, the coefficients of variation (CV) of IVIM parameters, and the parameter contrast-to-noise ratio (PCNR) between normal and tumor tissues. RESULTS: On two simulation datasets, the proposed IterANN achieves the lowest residual error in IVIM parameters, especially in the case of low signal-to-noise ratio (SNR = 10), the residual error of D $D$ , F $F$ and D S t a r $DStar$ is decreased by 15.82 % / 14.92 % , 81.19 % / 74.04 % , 50.77 % / 1.549 % $15.82\%/14.92\%, 81.19\%/74.04\%, 50.77\%/1.549\%$ (Gaussian distribution /realistic distribution) respectively comparing to the suboptimal method. On real dataset, the IterANN achieves the highest PCNR when comparing the normal and tumor regions. Additionally, the proposed IterANN demonstrated better stability, with its CV being significantly lower than that of other methods in the vast majority of cases ( p < 0.01 $p<0.01$ , paired-sample Student's t-test). CONCLUSIONS: The superior performance of IterANN demonstrates that updating the distribution of the train set based on MDP can effectively solve the OOD problem, which allows us not only to improve the accuracy and stability of the estimated IVIM parameters, but also to increase the potential of IVIM in disease diagnosis.

[Clinical and genetic analysis of a child with Focal segmental glomerulosclerosis due to a novel variant of PLCE1 gene].

OBJECTIVE: To explore the genetic basis and clinical phenotype of a Chinese pedigree affected with Focal segmental glomerulosclerosis (FSGS). METHODS: A male patient who was admitted to the First Affiliated Hospital of Zhengzhou University on July 26, 2018 was selected as the study subject. Clinical data of the patient was collected. Next generation sequencing and Sanger sequencing were carried out to detect the variant sites. Bioinformatic software was used to simulate the effect of candidate variant on the protein functions. RESULTS: Ultrasound exam of the patient showed enhanced echo for the renal parenchyma. Kidney biopsy had confirmed the pathological diagnosis of FSGS (non-specific). Electronic microscopy displayed segmental sclerosis of the glomeruli, mild hyperplasia of mesangial cells and matrix. The proband was found to harbor two novel variants of the PLCE1 gene, namely c.3199delA (p.N1067Mfs*15) and c.4441_4443delATC (p.1481_1481del), which were respectively inherited from his mother and father. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), both variants were rated as pathogenic (PVS1+PM2_Supporting+PP3; PM2_Supporting+PM3+PP3). Bioinformatic simulation suggested that both variants could significantly affect the tertiary structure of the PLCE1 protein. CONCLUSION: The c.4441_4443delATC and c.3199delA variants of the PLCE1 gene probably underlay the pathogenesis of the FSGS in this pedigree.

Deep learning method with integrated invertible wavelet scattering for improving the quality ofin vivocardiac DTI.

Objective.Respiratory motion, cardiac motion and inherently low signal-to-noise ratio (SNR) are major limitations ofin vivocardiac diffusion tensor imaging (DTI). We propose a novel enhancement method that uses unsupervised learning based invertible wavelet scattering (IWS) to improve the quality ofin vivocardiac DTI.Approach.Our method starts by extracting nearly transformation-invariant features from multiple cardiac diffusion-weighted (DW) image acquisitions using multi-scale wavelet scattering (WS). Then, the relationship between the WS coefficients and DW images is learned through a multi-scale encoder and a decoder network. Using the trained encoder, the deep features of WS coefficients of multiple DW image acquisitions are further extracted and then fused using an average rule. Finally, using the fused WS features and trained decoder, the enhanced DW images are derived.Main result.We evaluate the performance of the proposed method by comparing it with several methods on threein vivocardiac DTI datasets in terms of SNR, contrast to noise ratio (CNR), fractional anisotropy (FA), mean diffusivity (MD) and helix angle (HA). Comparing against the best comparison method, SNR/CNR of diastolic, gastric peristalsis influenced, and end-systolic DW images were improved by 1%/16%, 5%/6%, and 56%/30%, respectively. The approach also yielded consistent FA and MD values and more coherent helical fiber structures than the comparison methods used in this work.Significance.The ablation results verify that using the transformation-invariant and noise-robust wavelet scattering features enables us to effectively explore the useful information from the limited data, providing a potential mean to alleviate the dependence of the fusion results on the number of repeated acquisitions, which is beneficial for dealing with the issues of noise and residual motion simultaneously and therefore improving the quality ofinvivocardiac DTI. Code can be found inhttps://github.com/strawberry1996/WS-MCNN.

Identification of an m6A Natural Inhibitor, Lobeline, That Reverses Lenvatinib Resistance in Hepatocellular Tumors.

Hepatocellular carcinoma (HCC) is an aggressive cancer that has an effect on human health. As a first-line drug for HCC, despite its excellent efficacy, lenvatinib (Len) is prone to developing drug resistance in HCC patients. The N6-methyladenosine (m6A) modification is not only related to the development of HCC but also shows great potential in overcoming HCC resistance. Using Dot Blot, our group first screened a small molecule m6A regulator, lobeline (Lob), from a library of 390 compounds (mostly natural products). In vitro experiments demonstrated that Lob could significantly enhance the sensitivity to Len of Len-resistant HCC (HCC/Len) and inhibit migration of resistant cells. In Len-resistant cell-derived and patient-derived xenograft models, Lob could reverse the resistant phenotype, with reductions in tumor volume of 68% and 60%, respectively. Furthermore, MeRIP-m6A sequencing results indicated that the underlying molecular mechanism of Lob reversal of HCC drug resistance was related to UBE3B. Taken together, this study highlighted that Lob, a plant derived natural product, could reverse the resistance of HCC to Len by regulating the m6A levels. It is hoped that this will provide a pharmacological research basis for the clinical treatment of HCC patients.

Forming Single-Cell-Derived Colon Cancer Organoid Arrays on a Microfluidic Chip for High Throughput Tumor Heterogeneity Analysis.

Single-cell-derived tumor organoids (STOs) possess a distinct genetic background, making them valuable tools for demonstrating tumor heterogeneity. In order to fulfill the high throughput demands of STO assays, we have developed a microfluidic chip containing 30 000 microwells, which is dedicated to a single cell culture approach for selective expansion and differential induction of cancer stem cells. The microwells are coated with a hydrophilic copolymer to eliminate cell adhesion, and the cell culture is supported by poly(ethylene glycol) (PEG) to establish a nonadhesive culture environment. By utilizing an input cell density of 7 × 103·mL-1, it is possible to construct a 4000 single cell culture system through stochastic cell occupation. We demonstrate that the addition of 15% PEG10000 in the cell culture medium effectively prevents cell loss while facilitating tumor stem cell expansion. As were demonstrated by HCT116, HT29, and SW480 colon cancer cells, the microfluidic approach achieved a STO formation rate of ∼20%, resulting in over 800 STOs generated from a single culture. Comprehensive analysis through histomorphology, immunohistochemistry, drug response evaluation, assessment of cell invasion, and biomarker detection reveals the heterogeneity among individual STOs. Specifically, the smaller STOs exhibited higher invasion and drug resistance capabilities compared with the larger ones. The developed microfluidic approach effectively facilitates STO formation and offers promising prospects for investigating tumor heterogeneity, as well as conducting personalized therapy-focused drug screening.

Diverse associations between pancreatic intra-, inter-lobular fat and the development of type 2 diabetes in overweight or obese patients.

Pancreatic fat is associated with obesity and type 2 diabetes mellitus (T2DM); however, the relationship between different types of pancreatic fat and diabetes status remains unclear. Therefore, we aimed to determine the potential of different types of pancreatic fat accumulation as a risk factor for T2DM in overweight or obese patients. In total, 104 overweight or obese patients were recruited from January 2020 to December 2022. The patients were divided into three groups: normal glucose tolerance (NGT), impaired fasting glucose or glucose tolerance (IFG/IGT), and T2DM. mDixon magnetic resonance imaging (MRI) was used to detect pancreatic fat in all three groups of patients. The pancreatic head fat (PHF), body fat (PBF), and tail fat (PTF) in the IFG/IGT group were 21, 20, and 31% more than those in the NGT group, respectively. PHF, PBF, and PTF were positively associated with glucose metabolic dysfunction markers in the NGT group, and inter-lobular fat volume (IFV) was positively associated with these markers in the IFG/IGT group. The areas under the receiver operating characteristic curves for PHF, PBF, and PTF (used to evaluate their diagnostic potential for glucose metabolic dysfunction) were 0.73, 0.73, and 0.78, respectively, while those for total pancreatic volume (TPV), pancreatic parenchymal volume, IFV, and IFV/TPV were 0.67, 0.67, 0.66, and 0.66, respectively. These results indicate that intra-lobular pancreatic fat, including PHF, PTF, and PBF, may be a potential independent risk factor for the development of T2DM. Additionally, IFV exacerbates glucose metabolic dysfunction. Intra-lobular pancreatic fat indices were better than IFV for the diagnosis of glucose metabolic dysfunction.

Molecular Cloning and Functional Identification of a Pericarp- and Testa-Abundant Gene's (AhN8DT-2) Promoter from Arachis hypogaea.

Cultivated peanut (Arachis hypogaea L.) is a key oil- and protein-providing legume crop of the world. It is full of nutrients, and its nutrient profile is comparable to that of other nuts. Peanut is a unique plant as it showcases a pegging phenomenon, producing flowers above ground, and after fertilization, the developing peg enters the soil and produces seeds underground. This geocarpic nature of peanut exposes its seeds to soil pathogens. Peanut seeds are protected by an inedible pericarp and testa. The pericarp- and testa-specific promoters can be effectively used to improve the seed defense. We identified a pericarp- and testa-abundant expression gene (AhN8DT-2) from available transcriptome expression data, whose tissue-specific expression was further confirmed by the qRT-PCR. The 1827bp promoter sequence was used to construct the expression vector using the pMDC164 vector for further analysis. Quantitative expression of the GUS gene in transgenic Arabidopsis plants showed its high expression in the pericarp. GUS staining showed a deep blue color in the pericarp and testa. Cryostat sectioning of stained Arabidopsis seeds showed that expression is only limited to seed coat (testa), and staining was not present in cotyledons and embryos. GUS staining was not detected in any other tissues, including seedlings, leaves, stems, and roots, except for some staining in flowers. Under different phytohormones, this promoter did not show an increase in expression level. These results indicated that the AhN8DT-2 promoter drives GUS gene expression in a pericarp- and testa-specific manner. The identified promoter can be utilized to drive disease resistance genes, specifically in the pericarp and testa, enhancing peanut seed defense against soil-borne pathogens. This approach has broader implications for improving the resilience of peanut crops and other legumes, contributing to sustainable agricultural practices and food security.

Carboxymethyl chitosan stabilized AuNPs/ACP nanohybrids in enamel white spot lesions.

Acidic bacterial biofilms-associated enamel white spot lesions (WSLs) are one of the hallmarks of early caries, causing demineralization and decomposition of dental hard tissues. Therefore, to effectively prevent and treat WSLs, it is important to inhibit the activity of cariogenic bacteria while promoting the remineralization of demineralized enamel. Amorphous calcium phosphate (ACP) favors hard tissue remineralization due to its biological activity and ability to release large amounts of Ca2+ and PO4 3-. However, ACP-based biomineralization technology is not effective due to its lack of antimicrobial properties. Here, carboxymethyl chitosan (CMCS) was employed as a reducing agent and stabilizer, and dual-functional nanohybrids CMCS/AuNPs/ACP with biofilm resistance and mineralization properties were successfully synthesized. The addition of AuNPs enhances the antimicrobial activity and participates in regulating the formation of hydroxyapatite (HAp). The nanohybrids exhibited significant destructive effects against cariogenic bacteria and their biofilms and showed bactericidal activity under bacteria-induced acidic conditions. More importantly, this nanohybrids showed superior results in promoting the remineralization of demineralized enamel, compared to fluoride and CMCS/ACP in vitro. The CMCS/AuNPs/ACP nanohybrids not only reverse the cariogenic microenvironment at the microbial level, but also promote self-repairing of enamel WSLs regarding the microstructure. The present work offers a theoretical and experimental basis for using the CMCS/AuNPs/ACP nanohybrids as a potential dual-functional agent for the clinical treatment of enamel WSLs.

KDM1A, a potent and selective target, for the treatment of DNMT3A-deficient non-small cell lung cancer.

BACKGROUND: DNMT3A is a crucial epigenetic regulation enzyme. However, due to its heterogeneous nature and frequent mutation in various cancers, the role of DNMT3A remains controversial. Here, we determine the role of DNMT3A in non-small cell lung cancer (NSCLC) to identify potential treatment strategies. METHODS: To investigate the role of loss-of-function mutations of DNMT3A in NSCLC, CRISPR/Cas9 was used to induce DNMT3A-inactivating mutations. Epigenetic inhibitor library was screened to find the synthetic lethal partner of DNMT3A. Both pharmacological inhibitors and gene manipulation were used to evaluate the synthetic lethal efficacy of DNMT3A/KDM1A in vitro and in vivo. Lastly, MS-PCR, ChIP-qPCR, dual luciferase reporter gene assay and clinical sample analysis were applied to elucidate the regulation mechanism of synthetic lethal interaction. RESULTS: We identified DNMT3A is a tumour suppressor gene in NSCLC and KDM1A as a synthetic lethal partner of DNMT3A deletion. Both chemical KDM1A inhibitors and gene manipulation can selectively reduce the viability of DNMT3A-KO cells through inducing cell apoptosis in vitro and in vivo. We clarified that the synthetic lethality is not only limited to the death mode, but also involved into tumour metastasis. Mechanistically, DNMT3A deficiency induces KDM1A upregulation through reducing the methylation status of the KDM1A promoter and analysis of clinical samples indicated that DNMT3A expression was negatively correlated with KDM1A level. CONCLUSION: Our results provide new insight into the role of DNMT3A in NSCLC and elucidate the mechanism of synthetic lethal interaction between KDM1A and DNMT3A, which might represent a promising approach for treating patients with DNMT3A-deficient tumours.

A novel quantitative double antigen sandwich ELISA for detecting total antibodies against Candida albicans enolase 1.

PURPOSE: This study aimed to develop a double antigen sandwich ELISA (DAgS-ELISA) method for more efficient, accurate, and quantitative detection of total antibodies against Candida albicans enolase1 (CaEno1) for diagnosing invasive candidiasis (IC). METHODS: DAgS-ELISA was developed using recombinant CaEno1 and a monoclonal antibody as the standard. Performance evaluation included limit of detection, accuracy, and repeatability. Dynamic changes in antibody levels against CaEno1 in serum from systemic candidiasis mice were analyzed using DAgS-ELISA. Patient serum samples from IC, Candida colonization, bacterial infections, and healthy controls were analyzed with DAgS-ELISA and indirect ELISA. RESULTS: DAgS-ELISA outperformed indirect ELISA in terms of linear range and test background. In systemic candidiasis mice, a distinctive 'double-peak' pattern in dynamic antibody levels was observed. Additionally, there was a high level of consistency in the positive rates of CaEno1 antibodies detected by both DAgS-ELISA and indirect ELISA. While the positivity rates differed among patient groups, no significant variations in antibody levels were detected among the various positive patient groups. CONCLUSIONS: DAgS-ELISA offers a reliable novel approach for IC diagnosis, enabling rapid, accurate, and quantitative detection of CaEno1 antibodies. Further validation and optimization are needed for its clinical application and effectiveness.